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Sample records for multiple independent components

  1. Characterizing functional connectivity during rest in multiple sclerosis patients versus healthy volunteers using independent component analysis

    Energy Technology Data Exchange (ETDEWEB)

    Palacio Garcia, L.; Andrzejak, R.; Prchkovska, V.; Rodrigues, P.

    2016-07-01

    It is commonly thought that our brain is not active when it does not receive any external input. However, during rest, there are still certain distant regions of the brain that are functionally correlated between them: the so-called resting-state networks. This functional connectivity of the brain is disrupted in many neurological diseases. In particular, it has been shown that one of the most studied resting-state networks (the default-mode network) is affected in multiple sclerosis, which is the most common disabling neurological condition affecting the central nervous system of young adults. In this work, I focus on the study of the differences in the resting-state networks between multiple sclerosis patients and healthy volunteers. In order to study the effects of multiple sclerosis on the functional connectivity of the brain, a numerical method known as independent component analysis (ICA) is applied. This technique divides the resting-state fMRI data into independent components. Nonetheless, noise, which could be due to head motion or physiological artifacts, may corrupt the data by indicating a false activation. Therefore, I create a web user interface that allows the user to manually classify all the independent components for a given subject. Eventually, the components classified as noise should be removed from the functional data in order to prevent them from taking part in any further analysis. (Author)

  2. The Research of Multiple Attenuation Based on Feedback Iteration and Independent Component Analysis

    Science.gov (United States)

    Xu, X.; Tong, S.; Wang, L.

    2017-12-01

    How to solve the problem of multiple suppression is a difficult problem in seismic data processing. The traditional technology for multiple attenuation is based on the principle of the minimum output energy of the seismic signal, this criterion is based on the second order statistics, and it can't achieve the multiple attenuation when the primaries and multiples are non-orthogonal. In order to solve the above problems, we combine the feedback iteration method based on the wave equation and the improved independent component analysis (ICA) based on high order statistics to suppress the multiple waves. We first use iterative feedback method to predict the free surface multiples of each order. Then, in order to predict multiples from real multiple in amplitude and phase, we design an expanded pseudo multi-channel matching filtering method to get a more accurate matching multiple result. Finally, we present the improved fast ICA algorithm which is based on the maximum non-Gauss criterion of output signal to the matching multiples and get better separation results of the primaries and the multiples. The advantage of our method is that we don't need any priori information to the prediction of the multiples, and can have a better separation result. The method has been applied to several synthetic data generated by finite-difference model technique and the Sigsbee2B model multiple data, the primaries and multiples are non-orthogonal in these models. The experiments show that after three to four iterations, we can get the perfect multiple results. Using our matching method and Fast ICA adaptive multiple subtraction, we can not only effectively preserve the effective wave energy in seismic records, but also can effectively suppress the free surface multiples, especially the multiples related to the middle and deep areas.

  3. Multiple brain networks underpinning word learning from fluent speech revealed by independent component analysis.

    Science.gov (United States)

    López-Barroso, Diana; Ripollés, Pablo; Marco-Pallarés, Josep; Mohammadi, Bahram; Münte, Thomas F; Bachoud-Lévi, Anne-Catherine; Rodriguez-Fornells, Antoni; de Diego-Balaguer, Ruth

    2015-04-15

    Although neuroimaging studies using standard subtraction-based analysis from functional magnetic resonance imaging (fMRI) have suggested that frontal and temporal regions are involved in word learning from fluent speech, the possible contribution of different brain networks during this type of learning is still largely unknown. Indeed, univariate fMRI analyses cannot identify the full extent of distributed networks that are engaged by a complex task such as word learning. Here we used Independent Component Analysis (ICA) to characterize the different brain networks subserving word learning from an artificial language speech stream. Results were replicated in a second cohort of participants with a different linguistic background. Four spatially independent networks were associated with the task in both cohorts: (i) a dorsal Auditory-Premotor network; (ii) a dorsal Sensory-Motor network; (iii) a dorsal Fronto-Parietal network; and (iv) a ventral Fronto-Temporal network. The level of engagement of these networks varied through the learning period with only the dorsal Auditory-Premotor network being engaged across all blocks. In addition, the connectivity strength of this network in the second block of the learning phase correlated with the individual variability in word learning performance. These findings suggest that: (i) word learning relies on segregated connectivity patterns involving dorsal and ventral networks; and (ii) specifically, the dorsal auditory-premotor network connectivity strength is directly correlated with word learning performance. Copyright © 2015 Elsevier Inc. All rights reserved.

  4. Bayesian Independent Component Analysis

    DEFF Research Database (Denmark)

    Winther, Ole; Petersen, Kaare Brandt

    2007-01-01

    In this paper we present an empirical Bayesian framework for independent component analysis. The framework provides estimates of the sources, the mixing matrix and the noise parameters, and is flexible with respect to choice of source prior and the number of sources and sensors. Inside the engine...

  5. Independent component analysis: recent advances

    OpenAIRE

    Hyv?rinen, Aapo

    2013-01-01

    Independent component analysis is a probabilistic method for learning a linear transform of a random vector. The goal is to find components that are maximally independent and non-Gaussian (non-normal). Its fundamental difference to classical multi-variate statistical methods is in the assumption of non-Gaussianity, which enables the identification of original, underlying components, in contrast to classical methods. The basic theory of independent component analysis was mainly developed in th...

  6. Only low frequency event-related EEG activity is compromised in multiple sclerosis: insights from an independent component clustering analysis.

    Directory of Open Access Journals (Sweden)

    Hanni Kiiski

    Full Text Available Cognitive impairment (CI, often examined with neuropsychological tests such as the Paced Auditory Serial Addition Test (PASAT, affects approximately 65% of multiple sclerosis (MS patients. The P3b event-related potential (ERP, evoked when an infrequent target stimulus is presented, indexes cognitive function and is typically compared across subjects' scalp electroencephalography (EEG data. However, the clustering of independent components (ICs is superior to scalp-based EEG methods because it can accommodate the spatiotemporal overlap inherent in scalp EEG data. Event-related spectral perturbations (ERSPs; event-related mean power spectral changes and inter-trial coherence (ITCs; event-related consistency of spectral phase reveal a more comprehensive overview of EEG activity. Ninety-five subjects (56 MS patients, 39 controls completed visual and auditory two-stimulus P3b event-related potential tasks and the PASAT. MS patients were also divided into CI and non-CI groups (n = 18 in each based on PASAT scores. Data were recorded from 128-scalp EEG channels and 4 IC clusters in the visual, and 5 IC clusters in the auditory, modality were identified. In general, MS patients had significantly reduced ERSP theta power versus controls, and a similar pattern was observed for CI vs. non-CI MS patients. The ITC measures were also significantly different in the theta band for some clusters. The finding that MS patients had reduced P3b task-related theta power in both modalities is a reflection of compromised connectivity, likely due to demyelination, that may have disrupted early processes essential to P3b generation, such as orientating and signal detection. However, for posterior sources, MS patients had a greater decrease in alpha power, normally associated with enhanced cognitive function, which may reflect a compensatory mechanism in response to the compromised early cognitive processing.

  7. Blind Detection of Independent Dynamic Components

    DEFF Research Database (Denmark)

    Hansen, Lars Kai; Larsen, Jan; Kolenda, Thomas

    2001-01-01

    In certain applications of independent component analysis (ICA) it is of interest to test hypotheses concerning the number of components or simply to test whether a given number of components is significant relative to a "white noise" null hypothesis. We estimate probabilities of such competing h...

  8. Independent component analysis for understanding multimedia content

    DEFF Research Database (Denmark)

    Kolenda, Thomas; Hansen, Lars Kai; Larsen, Jan

    2002-01-01

    Independent component analysis of combined text and image data from Web pages has potential for search and retrieval applications by providing more meaningful and context dependent content. It is demonstrated that ICA of combined text and image features has a synergistic effect, i.e., the retrieval...

  9. Independent Component Analysis in Multimedia Modeling

    DEFF Research Database (Denmark)

    Larsen, Jan

    2003-01-01

    largely refers to text, images/video, audio and combinations of such data. We review a number of applications within single and combined media with the hope that this might provide inspiration for further research in this area. Finally, we provide a detailed presentation of our own recent work on modeling......Modeling of multimedia and multimodal data becomes increasingly important with the digitalization of the world. The objective of this paper is to demonstrate the potential of independent component analysis and blind sources separation methods for modeling and understanding of multimedia data, which...

  10. Emotional responses as independent components in EEG

    DEFF Research Database (Denmark)

    Jensen, Camilla Birgitte Falk; Petersen, Michael Kai; Larsen, Jakob Eg

    2014-01-01

    susceptible to noise if captured in a mobile context. Hypothesizing that retrieval of emotional responses in mobile usage scenarios could be enhanced through spatial filtering, we compare a standard EEG electrode based analysis against an approach based on independent component analysis (ICA). By clustering...... or unpleasant images; early posterior negativity (EPN) and late positive potential (LPP). Recent studies suggest that several time course components may be modulated by emotional content in images or text. However these neural signatures are characterized by small voltage changes that would be highly...... by emotional content. We propose that similar approaches to spatial filtering might allow us to retrieve more robust signals in real life mobile usage scenarios, and potentially facilitate design of cognitive interfaces that adapt the selection of media to our emotional responses....

  11. Quantifying identifiability in independent component analysis

    DEFF Research Database (Denmark)

    Sokol, Alexander; Maathuis, Marloes H.; Falkeborg, Benjamin

    2014-01-01

    We are interested in consistent estimation of the mixing matrix in the ICA model, when the error distribution is close to (but different from) Gaussian. In particular, we consider $n$ independent samples from the ICA model $X = A\\epsilon$, where we assume that the coordinates of $\\epsilon......$ are independent and identically distributed according to a contaminated Gaussian distribution, and the amount of contamination is allowed to depend on $n$. We then investigate how the ability to consistently estimate the mixing matrix depends on the amount of contamination. Our results suggest...

  12. Partitioning diversity into independent alpha and beta components.

    Science.gov (United States)

    Jost, Lou

    2007-10-01

    Existing general definitions of beta diversity often produce a beta with a hidden dependence on alpha. Such a beta cannot be used to compare regions that differ in alpha diversity. To avoid misinterpretation, existing definitions of alpha and beta must be replaced by a definition that partitions diversity into independent alpha and beta components. Such a unique definition is derived here. When these new alpha and beta components are transformed into their numbers equivalents (effective numbers of elements), Whittaker's multiplicative law (alpha x beta = gamma) is necessarily true for all indices. The new beta gives the effective number of distinct communities. The most popular similarity and overlap measures of ecology (Jaccard, Sorensen, Horn, and Morisita-Horn indices) are monotonic transformations of the new beta diversity. Shannon measures follow deductively from this formalism and do not need to be borrowed from information theory; they are shown to be the only standard diversity measures which can be decomposed into meaningful independent alpha and beta components when community weights are unequal.

  13. Tomato sorting using independent component analysis on spectral images

    NARCIS (Netherlands)

    Polder, G.; Heijden, van der G.W.A.M.; Young, I.T.

    2003-01-01

    Independent Component Analysis is one of the most widely used methods for blind source separation. In this paper we use this technique to estimate the most important compounds which play a role in the ripening of tomatoes. Spectral images of tomatoes were analyzed. Two main independent components

  14. How Many Separable Sources? Model Selection In Independent Components Analysis

    Science.gov (United States)

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

    2015-01-01

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

  15. Independent component analysis for automatic note extraction from musical trills

    Science.gov (United States)

    Brown, Judith C.; Smaragdis, Paris

    2004-05-01

    The method of principal component analysis, which is based on second-order statistics (or linear independence), has long been used for redundancy reduction of audio data. The more recent technique of independent component analysis, enforcing much stricter statistical criteria based on higher-order statistical independence, is introduced and shown to be far superior in separating independent musical sources. This theory has been applied to piano trills and a database of trill rates was assembled from experiments with a computer-driven piano, recordings of a professional pianist, and commercially available compact disks. The method of independent component analysis has thus been shown to be an outstanding, effective means of automatically extracting interesting musical information from a sea of redundant data.

  16. Signal-dependent independent component analysis by tunable mother wavelets

    International Nuclear Information System (INIS)

    Seo, Kyung Ho

    2006-02-01

    The objective of this study is to improve the standard independent component analysis when applied to real-world signals. Independent component analysis starts from the assumption that signals from different physical sources are statistically independent. But real-world signals such as EEG, ECG, MEG, and fMRI signals are not statistically independent perfectly. By definition, standard independent component analysis algorithms are not able to estimate statistically dependent sources, that is, when the assumption of independence does not hold. Therefore before independent component analysis, some preprocessing stage is needed. This paper started from simple intuition that wavelet transformed source signals by 'well-tuned' mother wavelet will be simplified sufficiently, and then the source separation will show better results. By the correlation coefficient method, the tuning process between source signal and tunable mother wavelet was executed. Gamma component of raw EEG signal was set to target signal, and wavelet transform was executed by tuned mother wavelet and standard mother wavelets. Simulation results by these wavelets was shown

  17. How Many Separable Sources? Model Selection In Independent Components Analysis

    DEFF Research Database (Denmark)

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

    2015-01-01

    among potential model categories with differing numbers of Gaussian components. Based on simulation studies, the assumptions and approximations underlying the Akaike Information Criterion do not hold in this setting, even with a very large number of observations. Cross-validation is a suitable, though....../Principal Components Analysis (mixed ICA/PCA) model described here accommodates one or more Gaussian components in the independent components analysis model and uses principal components analysis to characterize contributions from this inseparable Gaussian subspace. Information theory can then be used to select from...... might otherwise be questionable. Failure of the Akaike Information Criterion in model selection also has relevance in traditional independent components analysis where all sources are assumed non-Gaussian....

  18. Independent component analysis in non-hypothesis driven metabolomics

    DEFF Research Database (Denmark)

    Li, Xiang; Hansen, Jakob; Zhao, Xinjie

    2012-01-01

    In a non-hypothesis driven metabolomics approach plasma samples collected at six different time points (before, during and after an exercise bout) were analyzed by gas chromatography-time of flight mass spectrometry (GC-TOF MS). Since independent component analysis (ICA) does not need a priori...... information on the investigated process and moreover can separate statistically independent source signals with non-Gaussian distribution, we aimed to elucidate the analytical power of ICA for the metabolic pattern analysis and the identification of key metabolites in this exercise study. A novel approach...... based on descriptive statistics was established to optimize ICA model. In the GC-TOF MS data set the number of principal components after whitening and the number of independent components of ICA were optimized and systematically selected by descriptive statistics. The elucidated dominating independent...

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

    Science.gov (United States)

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

    2017-09-11

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

  20. Independent component analysis of edge information for face recognition

    CERN Document Server

    Karande, Kailash Jagannath

    2013-01-01

    The book presents research work on face recognition using edge information as features for face recognition with ICA algorithms. The independent components are extracted from edge information. These independent components are used with classifiers to match the facial images for recognition purpose. In their study, authors have explored Canny and LOG edge detectors as standard edge detection methods. Oriented Laplacian of Gaussian (OLOG) method is explored to extract the edge information with different orientations of Laplacian pyramid. Multiscale wavelet model for edge detection is also propos

  1. Independent component analysis based filtering for penumbral imaging

    International Nuclear Information System (INIS)

    Chen Yenwei; Han Xianhua; Nozaki, Shinya

    2004-01-01

    We propose a filtering based on independent component analysis (ICA) for Poisson noise reduction. In the proposed filtering, the image is first transformed to ICA domain and then the noise components are removed by a soft thresholding (shrinkage). The proposed filter, which is used as a preprocessing of the reconstruction, has been successfully applied to penumbral imaging. Both simulation results and experimental results show that the reconstructed image is dramatically improved in comparison to that without the noise-removing filters

  2. Multi-spectrometer calibration transfer based on independent component analysis.

    Science.gov (United States)

    Liu, Yan; Xu, Hao; Xia, Zhenzhen; Gong, Zhiyong

    2018-02-26

    Calibration transfer is indispensable for practical applications of near infrared (NIR) spectroscopy due to the need for precise and consistent measurements across different spectrometers. In this work, a method for multi-spectrometer calibration transfer is described based on independent component analysis (ICA). A spectral matrix is first obtained by aligning the spectra measured on different spectrometers. Then, by using independent component analysis, the aligned spectral matrix is decomposed into the mixing matrix and the independent components of different spectrometers. These differing measurements between spectrometers can then be standardized by correcting the coefficients within the independent components. Two NIR datasets of corn and edible oil samples measured with three and four spectrometers, respectively, were used to test the reliability of this method. The results of both datasets reveal that spectra measurements across different spectrometers can be transferred simultaneously and that the partial least squares (PLS) models built with the measurements on one spectrometer can predict that the spectra can be transferred correctly on another.

  3. Condition monitoring with Mean field independent components analysis

    DEFF Research Database (Denmark)

    Pontoppidan, Niels Henrik; Sigurdsson, Sigurdur; Larsen, Jan

    2005-01-01

    We discuss condition monitoring based on mean field independent components analysis of acoustic emission energy signals. Within this framework it is possible to formulate a generative model that explains the sources, their mixing and also the noise statistics of the observed signals. By using...... a novelty approach we may detect unseen faulty signals as indeed faulty with high precision, even though the model learns only from normal signals. This is done by evaluating the likelihood that the model generated the signals and adapting a simple threshold for decision. Acoustic emission energy signals...... from a large diesel engine is used to demonstrate this approach. The results show that mean field independent components analysis gives a better detection of fault compared to principal components analysis, while at the same time selecting a more compact model...

  4. Multiple independent identification decisions: a method of calibrating eyewitness identifications.

    Science.gov (United States)

    Pryke, Sean; Lindsay, R C L; Dysart, Jennifer E; Dupuis, Paul

    2004-02-01

    Two experiments (N = 147 and N = 90) explored the use of multiple independent lineups to identify a target seen live. In Experiment 1, simultaneous face, body, and sequential voice lineups were used. In Experiment 2, sequential face, body, voice, and clothing lineups were used. Both studies demonstrated that multiple identifications (by the same witness) from independent lineups of different features are highly diagnostic of suspect guilt (G. L. Wells & R. C. L. Lindsay, 1980). The number of suspect and foil selections from multiple independent lineups provides a powerful method of calibrating the accuracy of eyewitness identification. Implications for use of current methods are discussed. ((c) 2004 APA, all rights reserved)

  5. Constrained independent component analysis approach to nonobtrusive pulse rate measurements

    Science.gov (United States)

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

    2012-07-01

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

  6. Adaptive tools in virtual environments: Independent component analysis for multimedia

    DEFF Research Database (Denmark)

    Kolenda, Thomas

    2002-01-01

    The thesis investigates the role of independent component analysis in the setting of virtual environments, with the purpose of finding properties that reflect human context. A general framework for performing unsupervised classification with ICA is presented in extension to the latent semantic in...... were compared to investigate computational differences and separation results. The ICA properties were finally implemented in a chat room analysis tool and briefly investigated for visualization of search engines results....

  7. Extraction of Independent Structural Images for Principal Component Thermography

    Directory of Open Access Journals (Sweden)

    Dmitry Gavrilov

    2018-03-01

    Full Text Available Thermography is a powerful tool for non-destructive testing of a wide range of materials. Thermography has a number of approaches differing in both experiment setup and the way the collected data are processed. Among such approaches is the Principal Component Thermography (PCT method, which is based on the statistical processing of raw thermal images collected by thermal camera. The processed images (principal components or empirical orthogonal functions form an orthonormal basis, and often look like a superposition of all possible structural features found in the object under inspection—i.e., surface heating non-uniformity, internal defects and material structure. At the same time, from practical point of view it is desirable to have images representing independent structural features. The work presented in this paper proposes an approach for separation of independent image patterns (archetypes from a set of principal component images. The approach is demonstrated in the application of inspection of composite materials as well as the non-invasive analysis of works of art.

  8. Fast and accurate methods of independent component analysis: A survey

    Czech Academy of Sciences Publication Activity Database

    Tichavský, Petr; Koldovský, Zbyněk

    2011-01-01

    Roč. 47, č. 3 (2011), s. 426-438 ISSN 0023-5954 R&D Projects: GA MŠk 1M0572; GA ČR GA102/09/1278 Institutional research plan: CEZ:AV0Z10750506 Keywords : Blind source separation * artifact removal * electroencephalogram * audio signal processing Subject RIV: BB - Applied Statistics, Operational Research Impact factor: 0.454, year: 2011 http://library.utia.cas.cz/separaty/2011/SI/tichavsky-fast and accurate methods of independent component analysis a survey.pdf

  9. Systems of independent Markov components and their transient behavior

    International Nuclear Information System (INIS)

    Keilson, J.

    1975-01-01

    The transient behavior of redundant systems of independent, repairable, memoryless (two state) components is studied. Four failure times for such systems are considered, each an exit time from the set of working states for initial system conditions of interest: the failure time from the perfect state, the post-recovery exit time, the ergodic exit time, and the quasi-stationary exit time. The structure of these failure time distributions and their interrelation are discussed and asymptotic estimates and bounds for their expectations are presented. When such systems have high reliability, the failure time distributions are approximately exponential and asymptotically equivalent

  10. Fetal ECG extraction using independent component analysis by Jade approach

    Science.gov (United States)

    Giraldo-Guzmán, Jader; Contreras-Ortiz, Sonia H.; Lasprilla, Gloria Isabel Bautista; Kotas, Marian

    2017-11-01

    Fetal ECG monitoring is a useful method to assess the fetus health and detect abnormal conditions. In this paper we propose an approach to extract fetal ECG from abdomen and chest signals using independent component analysis based on the joint approximate diagonalization of eigenmatrices approach. The JADE approach avoids redundancy, what reduces matrix dimension and computational costs. Signals were filtered with a high pass filter to eliminate low frequency noise. Several levels of decomposition were tested until the fetal ECG was recognized in one of the separated sources output. The proposed method shows fast and good performance.

  11. Advances in independent component analysis and learning machines

    CERN Document Server

    Bingham, Ella; Laaksonen, Jorma; Lampinen, Jouko

    2015-01-01

    In honour of Professor Erkki Oja, one of the pioneers of Independent Component Analysis (ICA), this book reviews key advances in the theory and application of ICA, as well as its influence on signal processing, pattern recognition, machine learning, and data mining. Examples of topics which have developed from the advances of ICA, which are covered in the book are: A unifying probabilistic model for PCA and ICA Optimization methods for matrix decompositions Insights into the FastICA algorithmUnsupervised deep learning Machine vision and image retrieval A review of developments in the t

  12. Representation for dialect recognition using topographic independent component analysis

    Science.gov (United States)

    Wei, Qu

    2004-10-01

    In dialect speech recognition, the feature of tone in one dialect is subject to changes in pitch frequency as well as the length of tone. It is beneficial for the recognition if a representation can be derived to account for the frequency and length changes of tone in an effective and meaningful way. In this paper, we propose a method for learning such a representation from a set of unlabeled speech sentences containing the features of the dialect changed from various pitch frequencies and time length. Topographic independent component analysis (TICA) is applied for the unsupervised learning to produce an emergent result that is a topographic matrix made up of basis components. The dialect speech is topographic in the following sense: the basis components as the units of the speech are ordered in the feature matrix such that components of one dialect are grouped in one axis and changes in time windows are accounted for in the other axis. This provides a meaningful set of basis vectors that may be used to construct dialect subspaces for dialect speech recognition.

  13. Independent component analysis classification of laser induced breakdown spectroscopy spectra

    International Nuclear Information System (INIS)

    Forni, Olivier; Maurice, Sylvestre; Gasnault, Olivier; Wiens, Roger C.; Cousin, Agnès; Clegg, Samuel M.; Sirven, Jean-Baptiste; Lasue, Jérémie

    2013-01-01

    The ChemCam instrument on board Mars Science Laboratory (MSL) rover uses the laser-induced breakdown spectroscopy (LIBS) technique to remotely analyze Martian rocks. It retrieves spectra up to a distance of seven meters to quantify and to quantitatively analyze the sampled rocks. Like any field application, on-site measurements by LIBS are altered by diverse matrix effects which induce signal variations that are specific to the nature of the sample. Qualitative aspects remain to be studied, particularly LIBS sample identification to determine which samples are of interest for further analysis by ChemCam and other rover instruments. This can be performed with the help of different chemometric methods that model the spectra variance in order to identify a the rock from its spectrum. In this paper we test independent components analysis (ICA) rock classification by remote LIBS. We show that using measures of distance in ICA space, namely the Manhattan and the Mahalanobis distance, we can efficiently classify spectra of an unknown rock. The Mahalanobis distance gives overall better performances and is easier to manage than the Manhattan distance for which the determination of the cut-off distance is not easy. However these two techniques are complementary and their analytical performances will improve with time during MSL operations as the quantity of available Martian spectra will grow. The analysis accuracy and performances will benefit from a combination of the two approaches. - Highlights: • We use a novel independent component analysis method to classify LIBS spectra. • We demonstrate the usefulness of ICA. • We report the performances of the ICA classification. • We compare it to other classical classification schemes

  14. Gene Module Identification from Microarray Data Using Nonnegative Independent Component Analysis

    Directory of Open Access Journals (Sweden)

    Ting Gong

    2007-01-01

    Full Text Available Genes mostly interact with each other to form transcriptional modules for performing single or multiple functions. It is important to unravel such transcriptional modules and to determine how disturbances in them may lead to disease. Here, we propose a non-negative independent component analysis (nICA approach for transcriptional module discovery. nICA method utilizes the non-negativity constraint to enforce the independence of biological processes within the participated genes. In such, nICA decomposes the observed gene expression into positive independent components, which fi ts better to the reality of corresponding putative biological processes. In conjunction with nICA modeling, visual statistical data analyzer (VISDA is applied to group genes into modules in latent variable space. We demonstrate the usefulness of the approach through the identification of composite modules from yeast data and the discovery of pathway modules in muscle regeneration.

  15. Variational Bayesian Learning for Wavelet Independent Component Analysis

    Science.gov (United States)

    Roussos, E.; Roberts, S.; Daubechies, I.

    2005-11-01

    In an exploratory approach to data analysis, it is often useful to consider the observations as generated from a set of latent generators or "sources" via a generally unknown mapping. For the noisy overcomplete case, where we have more sources than observations, the problem becomes extremely ill-posed. Solutions to such inverse problems can, in many cases, be achieved by incorporating prior knowledge about the problem, captured in the form of constraints. This setting is a natural candidate for the application of the Bayesian methodology, allowing us to incorporate "soft" constraints in a natural manner. The work described in this paper is mainly driven by problems in functional magnetic resonance imaging of the brain, for the neuro-scientific goal of extracting relevant "maps" from the data. This can be stated as a `blind' source separation problem. Recent experiments in the field of neuroscience show that these maps are sparse, in some appropriate sense. The separation problem can be solved by independent component analysis (ICA), viewed as a technique for seeking sparse components, assuming appropriate distributions for the sources. We derive a hybrid wavelet-ICA model, transforming the signals into a domain where the modeling assumption of sparsity of the coefficients with respect to a dictionary is natural. We follow a graphical modeling formalism, viewing ICA as a probabilistic generative model. We use hierarchical source and mixing models and apply Bayesian inference to the problem. This allows us to perform model selection in order to infer the complexity of the representation, as well as automatic denoising. Since exact inference and learning in such a model is intractable, we follow a variational Bayesian mean-field approach in the conjugate-exponential family of distributions, for efficient unsupervised learning in multi-dimensional settings. The performance of the proposed algorithm is demonstrated on some representative experiments.

  16. Independent component processes underlying emotions during natural music listening.

    Science.gov (United States)

    Rogenmoser, Lars; Zollinger, Nina; Elmer, Stefan; Jäncke, Lutz

    2016-09-01

    The aim of this study was to investigate the brain processes underlying emotions during natural music listening. To address this, we recorded high-density electroencephalography (EEG) from 22 subjects while presenting a set of individually matched whole musical excerpts varying in valence and arousal. Independent component analysis was applied to decompose the EEG data into functionally distinct brain processes. A k-means cluster analysis calculated on the basis of a combination of spatial (scalp topography and dipole location mapped onto the Montreal Neurological Institute brain template) and functional (spectra) characteristics revealed 10 clusters referring to brain areas typically involved in music and emotion processing, namely in the proximity of thalamic-limbic and orbitofrontal regions as well as at frontal, fronto-parietal, parietal, parieto-occipital, temporo-occipital and occipital areas. This analysis revealed that arousal was associated with a suppression of power in the alpha frequency range. On the other hand, valence was associated with an increase in theta frequency power in response to excerpts inducing happiness compared to sadness. These findings are partly compatible with the model proposed by Heller, arguing that the frontal lobe is involved in modulating valenced experiences (the left frontal hemisphere for positive emotions) whereas the right parieto-temporal region contributes to the emotional arousal. © The Author (2016). Published by Oxford University Press. For Permissions, please email: journals.permissions@oup.com.

  17. A novel approach to analyzing fMRI and SNP data via parallel independent component analysis

    Science.gov (United States)

    Liu, Jingyu; Pearlson, Godfrey; Calhoun, Vince; Windemuth, Andreas

    2007-03-01

    There is current interest in understanding genetic influences on brain function in both the healthy and the disordered brain. Parallel independent component analysis, a new method for analyzing multimodal data, is proposed in this paper and applied to functional magnetic resonance imaging (fMRI) and a single nucleotide polymorphism (SNP) array. The method aims to identify the independent components of each modality and the relationship between the two modalities. We analyzed 92 participants, including 29 schizophrenia (SZ) patients, 13 unaffected SZ relatives, and 50 healthy controls. We found a correlation of 0.79 between one fMRI component and one SNP component. The fMRI component consists of activations in cingulate gyrus, multiple frontal gyri, and superior temporal gyrus. The related SNP component is contributed to significantly by 9 SNPs located in sets of genes, including those coding for apolipoprotein A-I, and C-III, malate dehydrogenase 1 and the gamma-aminobutyric acid alpha-2 receptor. A significant difference in the presences of this SNP component is found between the SZ group (SZ patients and their relatives) and the control group. In summary, we constructed a framework to identify the interactions between brain functional and genetic information; our findings provide new insight into understanding genetic influences on brain function in a common mental disorder.

  18. Multiple Independent Gate FETs: How Many Gates Do We Need?

    OpenAIRE

    Amarù, Luca; Hills, Gage; Gaillardon, Pierre-Emmanuel; Mitra, Subhasish; De Micheli, Giovanni

    2015-01-01

    Multiple Independent Gate Field Effect Transistors (MIGFETs) are expected to push FET technology further into the semiconductor roadmap. In a MIGFET, supplementary gates either provide (i) enhanced conduction properties or (ii) more intelligent switching functions. In general, each additional gate also introduces a side implementation cost. To enable more efficient digital systems, MIGFETs must leverage their expressive power to realize complex logic circuits with few physical resources. Rese...

  19. Multiple Independent File Parallel I/O with HDF5

    Energy Technology Data Exchange (ETDEWEB)

    Miller, M. C.

    2016-07-13

    The HDF5 library has supported the I/O requirements of HPC codes at Lawrence Livermore National Labs (LLNL) since the late 90’s. In particular, HDF5 used in the Multiple Independent File (MIF) parallel I/O paradigm has supported LLNL code’s scalable I/O requirements and has recently been gainfully used at scales as large as O(106) parallel tasks.

  20. Blind Separation of Event-Related Brain Responses into Independent Components

    National Research Council Canada - National Science Library

    Makeig, Scott

    1996-01-01

    .... We report here a method for the blind separation of event-related brain responses into spatially stationary and temporally independent subcomponents using an Independent Component Analysis algorithm...

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

    Science.gov (United States)

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

    2010-12-01

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

  2. Learning Algorithms for Audio and Video Processing: Independent Component Analysis and Support Vector Machine Based Approaches

    National Research Council Canada - National Science Library

    Qi, Yuan

    2000-01-01

    In this thesis, we propose two new machine learning schemes, a subband-based Independent Component Analysis scheme and a hybrid Independent Component Analysis/Support Vector Machine scheme, and apply...

  3. Multiple age components in individual molybdenite grains

    Science.gov (United States)

    Aleinikoff, John N.; Creaser, Robert A.; Lowers, Heather; Magee, Charles W.; Grauch, Richard I.

    2012-01-01

    Re–Os geochronology of fractions composed of unsized, coarse, and fine molybdenite from a pod of unusual monazite–xenotime gneiss within a granulite facies paragneiss, Hudson Highlands, NY, yielded dates of 950.5 ± 2.5, 953.8 ± 2.6, and 941.2 ± 2.6 Ma, respectively. These dates are not recorded by co-existing zircon, monazite, or xenotime. SEM–BSE imagery of thin sections and separated grains reveals that most molybdenite grains are composed of core and rim plates that are approximately perpendicular. Rim material invaded cores, forming irregular contacts, probably reflecting dissolution/reprecipitation. EPMA and LA-ICP-MS analyses show that cores and rims have different trace element concentrations (for example, cores are relatively enriched in W). On the basis of inclusions of zircon with metamorphic overgrowths, we conclude that molybdenite cores and rims formed after high-grade regional metamorphism. The discovery of cores and rims in individual molybdenite grains is analogous to multi-component U-Pb geochronometers such as zircon, monazite, and titanite; thus, molybdenite should be carefully examined before dating to ensure that the requirement of age homogeneity is fulfilled.

  4. Measuring multiple residual-stress components using the contour method and multiple cuts

    Energy Technology Data Exchange (ETDEWEB)

    Prime, Michael B [Los Alamos National Laboratory; Swenson, Hunter [Los Alamos National Laboratory; Pagliaro, Pierluigi [U. PALERMO; Zuccarello, Bernardo [U. PALERMO

    2009-01-01

    The conventional contour method determines one component of stress over the cross section of a part. The part is cut into two, the contour of the exposed surface is measured, and Bueckner's superposition principle is analytically applied to calculate stresses. In this paper, the contour method is extended to the measurement of multiple stress components by making multiple cuts with subsequent applications of superposition. The theory and limitations are described. The theory is experimentally tested on a 316L stainless steel disk with residual stresses induced by plastically indenting the central portion of the disk. The stress results are validated against independent measurements using neutron diffraction. The theory has implications beyond just multiple cuts. The contour method measurements and calculations for the first cut reveal how the residual stresses have changed throughout the part. Subsequent measurements of partially relaxed stresses by other techniques, such as laboratory x-rays, hole drilling, or neutron or synchrotron diffraction, can be superimposed back to the original state of the body.

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

    Science.gov (United States)

    Zhang, Sheng; Li, Chiang-Shan R

    2017-11-01

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

  6. Determination of the optimal number of components in independent components analysis.

    Science.gov (United States)

    Kassouf, Amine; Jouan-Rimbaud Bouveresse, Delphine; Rutledge, Douglas N

    2018-03-01

    Independent components analysis (ICA) may be considered as one of the most established blind source separation techniques for the treatment of complex data sets in analytical chemistry. Like other similar methods, the determination of the optimal number of latent variables, in this case, independent components (ICs), is a crucial step before any modeling. Therefore, validation methods are required in order to decide about the optimal number of ICs to be used in the computation of the final model. In this paper, three new validation methods are formally presented. The first one, called Random_ICA, is a generalization of the ICA_by_blocks method. Its specificity resides in the random way of splitting the initial data matrix into two blocks, and then repeating this procedure several times, giving a broader perspective for the selection of the optimal number of ICs. The second method, called KMO_ICA_Residuals is based on the computation of the Kaiser-Meyer-Olkin (KMO) index of the transposed residual matrices obtained after progressive extraction of ICs. The third method, called ICA_corr_y, helps to select the optimal number of ICs by computing the correlations between calculated proportions and known physico-chemical information about samples, generally concentrations, or between a source signal known to be present in the mixture and the signals extracted by ICA. These three methods were tested using varied simulated and experimental data sets and compared, when necessary, to ICA_by_blocks. Results were relevant and in line with expected ones, proving the reliability of the three proposed methods. Copyright © 2017 Elsevier B.V. All rights reserved.

  7. PRKCA and multiple sclerosis: association in two independent populations.

    Directory of Open Access Journals (Sweden)

    Janna Saarela

    2006-03-01

    Full Text Available Multiple sclerosis (MS is a chronic disease of the central nervous system responsible for a large portion of neurological disabilities in young adults. Similar to what occurs in numerous complex diseases, both unknown environmental factors and genetic predisposition are required to generate MS. We ascertained a set of 63 Finnish MS families, originating from a high-risk region of the country, to identify a susceptibility gene within the previously established 3.4-Mb region on 17q24. Initial single nucleotide polymorphism (SNP-based association implicated PRKCA (protein kinase C alpha gene, and this association was replicated in an independent set of 148 Finnish MS families (p = 0.0004; remaining significant after correction for multiple testing. Further, a dense set of 211 SNPs evenly covering the PRKCA gene and the flanking regions was selected from the dbSNP database and analyzed in two large, independent MS cohorts: in 211 Finnish and 554 Canadian MS families. A multipoint SNP analysis indicated linkage to PRKCA and its telomeric flanking region in both populations, and SNP haplotype and genotype combination analyses revealed an allelic variant of PRKCA, which covers the region between introns 3 and 8, to be over-represented in Finnish MS cases (odds ratio = 1.34, 95% confidence interval 1.07-1.68. A second allelic variant, covering the same region of the PRKCA gene, showed somewhat stronger evidence for association in the Canadian families (odds ratio = 1.64, 95% confidence interval 1.39-1.94. Initial functional relevance for disease predisposition was suggested by the expression analysis: The transcript levels of PRKCA showed correlation with the copy number of the Finnish and Canadian "risk" haplotypes in CD4-negative mononuclear cells of five Finnish multiplex families and in lymphoblast cell lines of 11 Centre d'Etude du Polymorphisme Humain (CEPH individuals of European origin.

  8. Independent Component Analysis and Time-Frequency Masking for Speech Recognition in Multitalker Conditions

    Directory of Open Access Journals (Sweden)

    Reinhold Orglmeister

    2010-01-01

    Full Text Available When a number of speakers are simultaneously active, for example in meetings or noisy public places, the sources of interest need to be separated from interfering speakers and from each other in order to be robustly recognized. Independent component analysis (ICA has proven a valuable tool for this purpose. However, ICA outputs can still contain strong residual components of the interfering speakers whenever noise or reverberation is high. In such cases, nonlinear postprocessing can be applied to the ICA outputs, for the purpose of reducing remaining interferences. In order to improve robustness to the artefacts and loss of information caused by this process, recognition can be greatly enhanced by considering the processed speech feature vector as a random variable with time-varying uncertainty, rather than as deterministic. The aim of this paper is to show the potential to improve recognition of multiple overlapping speech signals through nonlinear postprocessing together with uncertainty-based decoding techniques.

  9. Integrated Production-Distribution Scheduling Problem with Multiple Independent Manufacturers

    Directory of Open Access Journals (Sweden)

    Jianhong Hao

    2015-01-01

    Full Text Available We consider the nonstandard parts supply chain with a public service platform for machinery integration in China. The platform assigns orders placed by a machinery enterprise to multiple independent manufacturers who produce nonstandard parts and makes production schedule and batch delivery schedule for each manufacturer in a coordinate manner. Each manufacturer has only one plant with parallel machines and is located at a location far away from other manufacturers. Orders are first processed at the plants and then directly shipped from the plants to the enterprise in order to be finished before a given deadline. We study the above integrated production-distribution scheduling problem with multiple manufacturers to maximize a weight sum of the profit of each manufacturer under the constraints that all orders are finished before the deadline and the profit of each manufacturer is not negative. According to the optimal condition analysis, we formulate the problem as a mixed integer programming model and use CPLEX to solve it.

  10. Blind Separation of Acoustic Signals Combining SIMO-Model-Based Independent Component Analysis and Binary Masking

    Directory of Open Access Journals (Sweden)

    Hiekata Takashi

    2006-01-01

    Full Text Available A new two-stage blind source separation (BSS method for convolutive mixtures of speech is proposed, in which a single-input multiple-output (SIMO-model-based independent component analysis (ICA and a new SIMO-model-based binary masking are combined. SIMO-model-based ICA enables us to separate the mixed signals, not into monaural source signals but into SIMO-model-based signals from independent sources in their original form at the microphones. Thus, the separated signals of SIMO-model-based ICA can maintain the spatial qualities of each sound source. Owing to this attractive property, our novel SIMO-model-based binary masking can be applied to efficiently remove the residual interference components after SIMO-model-based ICA. The experimental results reveal that the separation performance can be considerably improved by the proposed method compared with that achieved by conventional BSS methods. In addition, the real-time implementation of the proposed BSS is illustrated.

  11. Estimation of compound distribution in spectral images of tomatoes using independent component analysis

    NARCIS (Netherlands)

    Polder, G.; Heijden, van der G.W.A.M.

    2003-01-01

    Independent Component Analysis (ICA) is one of the most widely used methods for blind source separation. In this paper we use this technique to estimate the important compounds which play a role in the ripening of tomatoes. Spectral images of tomatoes were analyzed. Two main independent components

  12. Observation of diffusion phenomena of liquid phase with multiple components

    International Nuclear Information System (INIS)

    Eguchi, Wataru

    1979-01-01

    The diffusion phenomena of liquid phase with multiple components was directly observed, and the factors contributing to complex material transfer were investigated, comparing to the former experimental results. The most excellent method of observing the diffusion behavior of liquid phase used heretofore is to trace the time history of concentration distribution for each component in unsteady diffusion process. The method of directly observing the concentration distribution is usually classified into the analysis of diffused samples, the checking of radioactive isotope tracers, and the measurement of light refraction and transmission. The most suitable method among these is to trace this time history by utilizing the spectrophotometer of position scanning type. An improved spectrophotometer was manufactured for trial. The outline of the measuring system and the detail of the optical system of this new type spectrophotometer are explained. The resolving power for position measurement is described with the numerical calculation. As for the observation examples of the diffusion phenomena of liquid phase with multiple components, the diffusion of multiple electrolytes in aqueous solution, the observation of the material transfer phenomena accompanied by heterogeneous and single phase chemical reaction, and the observation of concentration distribution in the liquid diaphragm in a reaction absorption system are described. For each experimental item, the test apparatus, the sample material, the test process, the test results and the evaluation are explained in detail, and the diffusion phenomena of liquid phase with multiple components were pretty well elucidated. (Nakai, Y.)

  13. How multiple causes combine: independence constraints on causal inference.

    Science.gov (United States)

    Liljeholm, Mimi

    2015-01-01

    According to the causal power view, two core constraints-that causes occur independently (i.e., no confounding) and influence their effects independently-serve as boundary conditions for causal induction. This study investigated how violations of these constraints modulate uncertainty about the existence and strength of a causal relationship. Participants were presented with pairs of candidate causes that were either confounded or not, and that either interacted or exerted their influences independently. Consistent with the causal power view, uncertainty about the existence and strength of causal relationships was greater when causes were confounded or interacted than when unconfounded and acting independently. An elemental Bayesian causal model captured differences in uncertainty due to confounding but not those due to an interaction. Implications of distinct sources of uncertainty for the selection of contingency information and causal generalization are discussed.

  14. Selection of independent components based on cortical mapping of electromagnetic activity

    Science.gov (United States)

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

    2012-10-01

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

  15. Adaptive Kalman filtering for diagnosis of multiple component degradations

    International Nuclear Information System (INIS)

    Aumeier, S. E.; Alpay, B.; Lee, J. C.

    2005-01-01

    We have developed an adaptive Kalman filtering algorithm for the diagnosis of faults or degradations of multiple components in nuclear power plants. We propose to detect the presence and magnitude of the fault(s) through noisy system observations when the measurements indicate significant deviations from predictions. Our diagnostic algorithm uses the measurement residuals, i.e., the difference between the measurements and predictions, to generate a noise input to the uncertain component state in an adaptive Kalman filtering algorithm so that various postulated component transitions or degradations may be statistically represented. The diagnostic algorithm has been tested with a balance of plant (BOP) model of a boiling water reactor (BWR). We have presented a set of algorithms for the detection and diagnosis of component faults of arbitrary magnitude and type within a multi-component system. By analyzing a number of transients including the one example illustrated in the paper, we find that these algorithms are not only capable of determining the correct component fault and magnitude for single components but also they can be used to determine binary faults satisfactorily. Additional study is under way to evaluate the performance of the proposed algorithm including the sensitivity of the diagnostic time to adaptive noise matrix introduced (see equations 7 and 8 illustrated in the paper)

  16. Independent component analysis applied to long bunch beams in the Los Alamos Proton Storage Ring

    Science.gov (United States)

    Kolski, Jeffrey S.; Macek, Robert J.; McCrady, Rodney C.; Pang, Xiaoying

    2012-11-01

    Independent component analysis (ICA) is a powerful blind source separation (BSS) method. Compared to the typical BSS method, principal component analysis, ICA is more robust to noise, coupling, and nonlinearity. The conventional ICA application to turn-by-turn position data from multiple beam position monitors (BPMs) yields information about cross-BPM correlations. With this scheme, multi-BPM ICA has been used to measure the transverse betatron phase and amplitude functions, dispersion function, linear coupling, sextupole strength, and nonlinear beam dynamics. We apply ICA in a new way to slices along the bunch revealing correlations of particle motion within the beam bunch. We digitize beam signals of the long bunch at the Los Alamos Proton Storage Ring with a single device (BPM or fast current monitor) for an entire injection-extraction cycle. ICA of the digitized beam signals results in source signals, which we identify to describe varying betatron motion along the bunch, locations of transverse resonances along the bunch, measurement noise, characteristic frequencies of the digitizing oscilloscopes, and longitudinal beam structure.

  17. Independent component analysis applied to long bunch beams in the Los Alamos Proton Storage Ring

    Directory of Open Access Journals (Sweden)

    Jeffrey S. Kolski

    2012-11-01

    Full Text Available Independent component analysis (ICA is a powerful blind source separation (BSS method. Compared to the typical BSS method, principal component analysis, ICA is more robust to noise, coupling, and nonlinearity. The conventional ICA application to turn-by-turn position data from multiple beam position monitors (BPMs yields information about cross-BPM correlations. With this scheme, multi-BPM ICA has been used to measure the transverse betatron phase and amplitude functions, dispersion function, linear coupling, sextupole strength, and nonlinear beam dynamics. We apply ICA in a new way to slices along the bunch revealing correlations of particle motion within the beam bunch. We digitize beam signals of the long bunch at the Los Alamos Proton Storage Ring with a single device (BPM or fast current monitor for an entire injection-extraction cycle. ICA of the digitized beam signals results in source signals, which we identify to describe varying betatron motion along the bunch, locations of transverse resonances along the bunch, measurement noise, characteristic frequencies of the digitizing oscilloscopes, and longitudinal beam structure.

  18. Separating complex compound patient motion tracking data using independent component analysis

    Science.gov (United States)

    Lindsay, C.; Johnson, K.; King, M. A.

    2014-03-01

    In SPECT imaging, motion from respiration and body motion can reduce image quality by introducing motion-related artifacts. A minimally-invasive way to track patient motion is to attach external markers to the patient's body and record their location throughout the imaging study. If a patient exhibits multiple movements simultaneously, such as respiration and body-movement, each marker location data will contain a mixture of these motions. Decomposing this complex compound motion into separate simplified motions can have the benefit of applying a more robust motion correction to the specific type of motion. Most motion tracking and correction techniques target a single type of motion and either ignore compound motion or treat it as noise. Few methods account for compound motion exist, but they fail to disambiguate super-position in the compound motion (i.e. inspiration in addition to body movement in the positive anterior/posterior direction). We propose a new method for decomposing the complex compound patient motion using an unsupervised learning technique called Independent Component Analysis (ICA). Our method can automatically detect and separate different motions while preserving nuanced features of the motion without the drawbacks of previous methods. Our main contributions are the development of a method for addressing multiple compound motions, the novel use of ICA in detecting and separating mixed independent motions, and generating motion transform with 12 DOFs to account for twisting and shearing. We show that our method works with clinical datasets and can be employed to improve motion correction in single photon emission computed tomography (SPECT) images.

  19. Application of independent component analysis to H-1 MR spectroscopic imaging exams of brain tumours

    NARCIS (Netherlands)

    Szabo de Edelenyi, F.; Simonetti, A.W.; Postma, G.; Huo, R.; Buydens, L.M.C.

    2005-01-01

    The low spatial resolution of clinical H-1 MRSI leads to partial volume effects. To overcome this problem, we applied independent component analysis (ICA) on a set of H-1 MRSI exams of brain turnours. With this method, tissue types that yield statistically independent spectra can be separated. Up to

  20. Independent component analysis of dynamic contrast-enhanced computed tomography images

    Energy Technology Data Exchange (ETDEWEB)

    Koh, T S [School of Electrical and Electronic Engineering, Nanyang Technological University, 50 Nanyang Ave, Singapore 639798 (Singapore); Yang, X [School of Electrical and Electronic Engineering, Nanyang Technological University, 50 Nanyang Ave, Singapore 639798 (Singapore); Bisdas, S [Department of Diagnostic and Interventional Radiology, Johann Wolfgang Goethe University Hospital, Theodor-Stern-Kai 7, D-60590 Frankfurt (Germany); Lim, C C T [Department of Neuroradiology, National Neuroscience Institute, 11 Jalan Tan Tock Seng, Singapore 308433 (Singapore)

    2006-10-07

    Independent component analysis (ICA) was applied on dynamic contrast-enhanced computed tomography images of cerebral tumours to extract spatial component maps of the underlying vascular structures, which correspond to different haemodynamic phases as depicted by the passage of the contrast medium. The locations of arteries, veins and tumours can be separately identified on these spatial component maps. As the contrast enhancement behaviour of the cerebral tumour differs from the normal tissues, ICA yields a tumour component map that reveals the location and extent of the tumour. Tumour outlines can be generated using the tumour component maps, with relatively simple segmentation methods. (note)

  1. Compressive Online Robust Principal Component Analysis with Multiple Prior Information

    DEFF Research Database (Denmark)

    Van Luong, Huynh; Deligiannis, Nikos; Seiler, Jürgen

    -rank components. Unlike conventional batch RPCA, which processes all the data directly, our method considers a small set of measurements taken per data vector (frame). Moreover, our method incorporates multiple prior information signals, namely previous reconstructed frames, to improve these paration...... and thereafter, update the prior information for the next frame. Using experiments on synthetic data, we evaluate the separation performance of the proposed algorithm. In addition, we apply the proposed algorithm to online video foreground and background separation from compressive measurements. The results show...

  2. Multiple isoforms of the human pentraxin serum amyloid P component

    DEFF Research Database (Denmark)

    Sørensen, Inge Juul; Andersen, Ove; Nielsen, EH

    1995-01-01

    Human serum amyloid P component (SAP) isolated from 20 healthy individuals was analyzed by anion exchange chromatography and isoelectric focusing (IEF) in order to investigate the existence of multiple forms of SAP and interindividual structural differences. Anion exchange chromatography showed one...... major and several minor subpopulations of SAP. IEF of all SAP isolates showed a previously unreported degree of heterogeneity with six isoelectric forms (pKi range 5.5-6.1) and with minor interindividual differences in respect of isoelectric points. Total enzymatic deglycosylation of SAP reduced...... the number of bands in IEF to two indicating the existence of two types of polypeptide chains....

  3. Mediator independently orchestrates multiple steps of preinitiation complex assembly in vivo.

    Science.gov (United States)

    Eyboulet, Fanny; Wydau-Dematteis, Sandra; Eychenne, Thomas; Alibert, Olivier; Neil, Helen; Boschiero, Claire; Nevers, Marie-Claire; Volland, Hervé; Cornu, David; Redeker, Virginie; Werner, Michel; Soutourina, Julie

    2015-10-30

    Mediator is a large multiprotein complex conserved in all eukaryotes, which has a crucial coregulator function in transcription by RNA polymerase II (Pol II). However, the molecular mechanisms of its action in vivo remain to be understood. Med17 is an essential and central component of the Mediator head module. In this work, we utilised our large collection of conditional temperature-sensitive med17 mutants to investigate Mediator's role in coordinating preinitiation complex (PIC) formation in vivo at the genome level after a transfer to a non-permissive temperature for 45 minutes. The effect of a yeast mutation proposed to be equivalent to the human Med17-L371P responsible for infantile cerebral atrophy was also analyzed. The ChIP-seq results demonstrate that med17 mutations differentially affected the global presence of several PIC components including Mediator, TBP, TFIIH modules and Pol II. Our data show that Mediator stabilizes TFIIK kinase and TFIIH core modules independently, suggesting that the recruitment or the stability of TFIIH modules is regulated independently on yeast genome. We demonstrate that Mediator selectively contributes to TBP recruitment or stabilization to chromatin. This study provides an extensive genome-wide view of Mediator's role in PIC formation, suggesting that Mediator coordinates multiple steps of a PIC assembly pathway. © The Author(s) 2015. Published by Oxford University Press on behalf of Nucleic Acids Research.

  4. Color Independent Components Based SIFT Descriptors for Object/Scene Classification

    Science.gov (United States)

    Ai, Dan-Ni; Han, Xian-Hua; Ruan, Xiang; Chen, Yen-Wei

    In this paper, we present a novel color independent components based SIFT descriptor (termed CIC-SIFT) for object/scene classification. We first learn an efficient color transformation matrix based on independent component analysis (ICA), which is adaptive to each category in a database. The ICA-based color transformation can enhance contrast between the objects and the background in an image. Then we compute CIC-SIFT descriptors over all three transformed color independent components. Since the ICA-based color transformation can boost the objects and suppress the background, the proposed CIC-SIFT can extract more effective and discriminative local features for object/scene classification. The comparison is performed among seven SIFT descriptors, and the experimental classification results show that our proposed CIC-SIFT is superior to other conventional SIFT descriptors.

  5. Residual dipolar couplings: are multiple independent alignments always possible?

    International Nuclear Information System (INIS)

    Higman, Victoria A.; Boyd, Jonathan; Smith, Lorna J.; Redfield, Christina

    2011-01-01

    RDCs for the 14 kDa protein hen egg-white lysozyme (HEWL) have been measured in eight different alignment media. The elongated shape and strongly positively charged surface of HEWL appear to limit the protein to four main alignment orientations. Furthermore, low levels of alignment and the protein’s interaction with some alignment media increases the experimental error. Together with heterogeneity across the alignment media arising from constraints on temperature, pH and ionic strength for some alignment media, these data are suitable for structure refinement, but not the extraction of dynamic parameters. For an analysis of protein dynamics the data must be obtained with very low errors in at least three or five independent alignment media (depending on the method used) and so far, such data have only been reported for three small 6–8 kDa proteins with identical folds: ubiquitin, GB1 and GB3. Our results suggest that HEWL is likely to be representative of many other medium to large sized proteins commonly studied by solution NMR. Comparisons with over 60 high-resolution crystal structures of HEWL reveal that the highest resolution structures are not necessarily always the best models for the protein structure in solution.

  6. Monitoring multiple components in vinegar fermentation using Raman spectroscopy.

    Science.gov (United States)

    Uysal, Reyhan Selin; Soykut, Esra Acar; Boyaci, Ismail Hakki; Topcu, Ali

    2013-12-15

    In this study, the utility of Raman spectroscopy (RS) with chemometric methods for quantification of multiple components in the fermentation process was investigated. Vinegar, the product of a two stage fermentation, was used as a model and glucose and fructose consumption, ethanol production and consumption and acetic acid production were followed using RS and the partial least squares (PLS) method. Calibration of the PLS method was performed using model solutions. The prediction capability of the method was then investigated with both model and real samples. HPLC was used as a reference method. The results from comparing RS-PLS and HPLC with each other showed good correlations were obtained between predicted and actual sample values for glucose (R(2)=0.973), fructose (R(2)=0.988), ethanol (R(2)=0.996) and acetic acid (R(2)=0.983). In conclusion, a combination of RS with chemometric methods can be applied to monitor multiple components of the fermentation process from start to finish with a single measurement in a short time. Copyright © 2013 Elsevier Ltd. All rights reserved.

  7. Insights from random vibration analyses using multiple earthquake components

    International Nuclear Information System (INIS)

    DebChaudhury, A.; Gasparini, D.A.

    1981-01-01

    The behavior of multi-degree-of-freedom systems subjected to multiple earthquake components is studied by the use of random vibration dynamic analyses. A linear system which has been decoupled into modes and has both translational and rotational degrees of freedom is analyzed. The seismic excitation is modelled as a correlated or uncorrelated, vector-valued, non-stationary random process having a Kanai-Tajimi type of frequency content. Non-stationarity is achieved by using a piece wise linear strength function. Therefore, almost any type of evolution and decay of an earthquake may be modelled. Also, in general, the components of the excitation have different frequency contents and strength functions; i.e. intensities and durations and the correlations between components can vary with time. A state-space, modal, random vibration approach is used. Exact analytical expressions for both the state transition matrix and the evolutionary modal covariance matrix are utilized to compute time histories of modal RMS responses. Desired responses are then computed by modal superposition. Specifically, relative displacement, relative velocity and absolute acceleration responses are studied. An important advantage of such analyses is that RMS responses vary smoothly in time therefore large time intervals may be used to generate response time histories. The modal superposition is exact; that is, all cross correlation terms between modal responses are included. (orig./RW)

  8. Extraction of a Weak Co-Channel Interfering Communication Signal Using Complex Independent Component Analysis

    Science.gov (United States)

    2013-06-01

    zarzoso/ biblio /tnn10.pdf"> % "Robust independent component analysis by iterative maximization</a> % <a href = "http://www.i3s.unice.fr/~zarzoso... biblio /tnn10.pdf"> % of the kurtosis contrast with algebraic optimal step size"</a>, % IEEE Transactions on Neural Networks, vol. 21, no. 2, % pp

  9. A method for independent component graph analysis of resting-state fMRI

    DEFF Research Database (Denmark)

    de Paula, Demetrius Ribeiro; Ziegler, Erik; Abeyasinghe, Pubuditha M.

    2017-01-01

    Introduction Independent component analysis (ICA) has been extensively used for reducing task-free BOLD fMRI recordings into spatial maps and their associated time-courses. The spatially identified independent components can be considered as intrinsic connectivity networks (ICNs) of non-contiguou......Introduction Independent component analysis (ICA) has been extensively used for reducing task-free BOLD fMRI recordings into spatial maps and their associated time-courses. The spatially identified independent components can be considered as intrinsic connectivity networks (ICNs) of non......-contiguous regions. To date, the spatial patterns of the networks have been analyzed with techniques developed for volumetric data. Objective Here, we detail a graph building technique that allows these ICNs to be analyzed with graph theory. Methods First, ICA was performed at the single-subject level in 15 healthy...... parcellated regions. Third, between-node functional connectivity was established by building edge weights for each networks. Group-level graph analysis was finally performed for each network and compared to the classical network. Results Network graph comparison between the classically constructed network...

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

    Science.gov (United States)

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

    2010-04-21

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

  11. A first application of independent component analysis to extracting structure from stock returns.

    Science.gov (United States)

    Back, A D; Weigend, A S

    1997-08-01

    This paper explores the application of a signal processing technique known as independent component analysis (ICA) or blind source separation to multivariate financial time series such as a portfolio of stocks. The key idea of ICA is to linearly map the observed multivariate time series into a new space of statistically independent components (ICs). We apply ICA to three years of daily returns of the 28 largest Japanese stocks and compare the results with those obtained using principal component analysis. The results indicate that the estimated ICs fall into two categories, (i) infrequent large shocks (responsible for the major changes in the stock prices), and (ii) frequent smaller fluctuations (contributing little to the overall level of the stocks). We show that the overall stock price can be reconstructed surprisingly well by using a small number of thresholded weighted ICs. In contrast, when using shocks derived from principal components instead of independent components, the reconstructed price is less similar to the original one. ICA is shown to be a potentially powerful method of analyzing and understanding driving mechanisms in financial time series. The application to portfolio optimization is described in Chin and Weigend (1998).

  12. Layout design of user interface components with multiple objectives

    Directory of Open Access Journals (Sweden)

    Peer S.K.

    2004-01-01

    Full Text Available A multi-goal layout problem may be formulated as a Quadratic Assignment model, considering multiple goals (or factors, both qualitative and quantitative in the objective function. The facilities layout problem, in general, varies from the location and layout of facilities in manufacturing plant to the location and layout of textual and graphical user interface components in the human–computer interface. In this paper, we propose two alternate mathematical approaches to the single-objective layout model. The first one presents a multi-goal user interface component layout problem, considering the distance-weighted sum of congruent objectives of closeness relationships and the interactions. The second one considers the distance-weighted sum of congruent objectives of normalized weighted closeness relationships and normalized weighted interactions. The results of first approach are compared with that of an existing single objective model for example task under consideration. Then, the results of first approach and second approach of the proposed model are compared for the example task under consideration.

  13. Equivalent water height extracted from GRACE gravity field model with robust independent component analysis

    Science.gov (United States)

    Guo, Jinyun; Mu, Dapeng; Liu, Xin; Yan, Haoming; Dai, Honglei

    2014-08-01

    The Level-2 monthly GRACE gravity field models issued by Center for Space Research (CSR), GeoForschungs Zentrum (GFZ), and Jet Propulsion Laboratory (JPL) are treated as observations used to extract the equivalent water height (EWH) with the robust independent component analysis (RICA). The smoothing radii of 300, 400, and 500 km are tested, respectively, in the Gaussian smoothing kernel function to reduce the observation Gaussianity. Three independent components are obtained by RICA in the spatial domain; the first component matches the geophysical signal, and the other two match the north-south strip and the other noises. The first mode is used to estimate EWHs of CSR, JPL, and GFZ, and compared with the classical empirical decorrelation method (EDM). The EWH STDs for 12 months in 2010 extracted by RICA and EDM show the obvious fluctuation. The results indicate that the sharp EWH changes in some areas have an important global effect, like in Amazon, Mekong, and Zambezi basins.

  14. All-phase MR angiography using independent component analysis of dynamic contrast enhanced MRI time series. φ-MRA

    International Nuclear Information System (INIS)

    Suzuki, Kiyotaka; Matsuzawa, Hitoshi; Watanabe, Masaki; Nakada, Tsutomu; Nakayama, Naoki; Kwee, I.L.

    2003-01-01

    Dynamic contrast enhanced magnetic resonance imaging (dynamic MRI) represents a MRI version of non-diffusible tracer methods, the main clinical use of which is the physiological construction of what is conventionally referred to as perfusion images. The raw data utilized for constructing MRI perfusion images are time series of pixel signal alterations associated with the passage of a gadolinium containing contrast agent. Such time series are highly compatible with independent component analysis (ICA), a novel statistical signal processing technique capable of effectively separating a single mixture of multiple signals into their original independent source signals (blind separation). Accordingly, we applied ICA to dynamic MRI time series. The technique was found to be powerful, allowing for hitherto unobtainable assessment of regional cerebral hemodynamics in vivo. (author)

  15. Analysis of independent components of cognitive event related potentials in a group of ADHD adults.

    Science.gov (United States)

    Markovska-Simoska, Silvana; Pop-Jordanova, Nada; Pop-Jordanov, Jordan

    In the last decade, many studies have tried to define the neural correlates of attention deficit hyperactivity disorder (ADHD). The main aim of this study is the comparison of the ERPs independent components in the four QEEG subtypes in a group of ADHD adults as a basis for defining the corresponding endophenotypes among ADHD population. Sixty-seven adults diagnosed as ADHD according to the DSM-IV criteria and 50 age-matched control subjects participated in the study. The brain activity of the subjects was recorded by 19 channel quantitative electroencephalography (QEEG) system in two neuropsychological tasks (visual and emotional continuous performance tests). The ICA method was applied for separation of the independent ERPs components. The components were associated with distinct psychological operations, such as engagement operations (P3bP component), comparison (vcomTL and vcom TR), motor inhibition (P3supF) and monitoring (P4monCC) operations. The ERPs results point out that there is disturbance in executive functioning in investigated ADHD group obtained by the significantly lower amplitude and longer latency for the engagement (P3bP), motor inhibition (P3supF) and monitoring (P4monCC) components. Particularly, the QEEG subtype IV was with the most significant ERPs differences comparing to the other subtypes. In particular, the most prominent difference in the ERPs independent components for the QEEG subtype IV in comparison to other three subtypes, rise many questions and becomes the subject for future research. This study aims to advance and facilitate the use of neurophysiological procedures (QEEG and ERPs) in clinical practice as objective measures of ADHD for better assessment, subtyping and treatment of ADHD.

  16. Denoising of chaotic signal using independent component analysis and empirical mode decomposition with circulate translating

    International Nuclear Information System (INIS)

    Wang Wen-Bo; Zhang Xiao-Dong; Chang Yuchan; Wang Xiang-Li; Wang Zhao; Chen Xi; Zheng Lei

    2016-01-01

    In this paper, a new method to reduce noises within chaotic signals based on ICA (independent component analysis) and EMD (empirical mode decomposition) is proposed. The basic idea is decomposing chaotic signals and constructing multidimensional input vectors, firstly, on the base of EMD and its translation invariance. Secondly, it makes the independent component analysis on the input vectors, which means that a self adapting denoising is carried out for the intrinsic mode functions (IMFs) of chaotic signals. Finally, all IMFs compose the new denoised chaotic signal. Experiments on the Lorenz chaotic signal composed of different Gaussian noises and the monthly observed chaotic sequence on sunspots were put into practice. The results proved that the method proposed in this paper is effective in denoising of chaotic signals. Moreover, it can correct the center point in the phase space effectively, which makes it approach the real track of the chaotic attractor. (paper)

  17. Multiple-input multiple-output visible light communication system based on disorder dispersion components

    Science.gov (United States)

    Yang, Tao; Zhang, Qi; Hao, Yue; Zhou, Xin-hui; Yi, Ming-dong; Wei, Wei; Huang, Wei; Li, Xing-ao

    2017-10-01

    A multiple-input multiple-output visible light communication (VLC) system based on disorder dispersion components is presented. Instead of monochromatic sources and large size photodetectors used in the traditional VLC systems, broadband sources with different spectra act as the transmitters and a compact imaging chip sensor accompanied by a disorder dispersion component and a calculating component serve as the receivers in the proposed system. This system has the merits of small size, more channels, simple structure, easy integration, and low cost. Simultaneously, the broadband sources are suitable to act as illumination sources for their white color. A regularized procedure is designed to solve a matrix equation for decoding the signals at the receivers. A proof-of-concept experiment using on-off keying modulation has been done to prove the feasibility of the design. The experimental results show that the signals decoded by the receivers fit well with those generated from the transmitters, but the bit error ratio is increased with the number of the signal channels. The experimental results can be further improved using a high-speed charge-coupled device, decreasing noises, and increasing the distance between the transmitters and the receivers.

  18. Applying independent component analysis to clinical fMRI at 7 T

    OpenAIRE

    Simon Daniel Robinson; Veronika eSchöpf; Pedro eCardoso; Alexander eGeissler; Alexander eGeissler; Florian Ph.S Fischmeister; Florian Ph.S Fischmeister; Moritz eWurnig; Moritz eWurnig; Siegfried eTrattnig; Roland eBeisteiner; Roland eBeisteiner

    2013-01-01

    Increased BOLD sensitivity at 7 T offers the possibility to increase the reliability of fMRI, but ultra-high field is also associated with an increase in artifacts related to head motion, Nyquist ghosting and parallel imaging reconstruction errors. In this study, the ability of Independent Component Analysis (ICA) to separate activation from these artifacts was assessed in a 7 T study of neurological patients performing chin and hand motor tasks. ICA was able to isolate primary motor activati...

  19. Independent component analysis: A new possibility for analysing series of electron energy loss spectra

    International Nuclear Information System (INIS)

    Bonnet, Nogl; Nuzillard, Danielle

    2005-01-01

    A complementary approach is proposed for analysing series of electron energy-loss spectra that can be recorded with the spectrum-line technique, across an interface for instance. This approach, called blind source separation (BSS) or independent component analysis (ICA), complements two existing methods: the spatial difference approach and multivariate statistical analysis. The principle of the technique is presented and illustrations are given through one simulated example and one real example

  20. Independent component analysis based digital signal processing in coherent optical fiber communication systems

    Science.gov (United States)

    Li, Xiang; Luo, Ming; Qiu, Ying; Alphones, Arokiaswami; Zhong, Wen-De; Yu, Changyuan; Yang, Qi

    2018-02-01

    In this paper, channel equalization techniques for coherent optical fiber transmission systems based on independent component analysis (ICA) are reviewed. The principle of ICA for blind source separation is introduced. The ICA based channel equalization after both single-mode fiber and few-mode fiber transmission for single-carrier and orthogonal frequency division multiplexing (OFDM) modulation formats are investigated, respectively. The performance comparisons with conventional channel equalization techniques are discussed.

  1. Crude oil price analysis and forecasting based on variational mode decomposition and independent component analysis

    Science.gov (United States)

    E, Jianwei; Bao, Yanling; Ye, Jimin

    2017-10-01

    As one of the most vital energy resources in the world, crude oil plays a significant role in international economic market. The fluctuation of crude oil price has attracted academic and commercial attention. There exist many methods in forecasting the trend of crude oil price. However, traditional models failed in predicting accurately. Based on this, a hybrid method will be proposed in this paper, which combines variational mode decomposition (VMD), independent component analysis (ICA) and autoregressive integrated moving average (ARIMA), called VMD-ICA-ARIMA. The purpose of this study is to analyze the influence factors of crude oil price and predict the future crude oil price. Major steps can be concluded as follows: Firstly, applying the VMD model on the original signal (crude oil price), the modes function can be decomposed adaptively. Secondly, independent components are separated by the ICA, and how the independent components affect the crude oil price is analyzed. Finally, forecasting the price of crude oil price by the ARIMA model, the forecasting trend demonstrates that crude oil price declines periodically. Comparing with benchmark ARIMA and EEMD-ICA-ARIMA, VMD-ICA-ARIMA can forecast the crude oil price more accurately.

  2. The Removal of EOG Artifacts From EEG Signals Using Independent Component Analysis and Multivariate Empirical Mode Decomposition.

    Science.gov (United States)

    Wang, Gang; Teng, Chaolin; Li, Kuo; Zhang, Zhonglin; Yan, Xiangguo

    2016-09-01

    The recorded electroencephalography (EEG) signals are usually contaminated by electrooculography (EOG) artifacts. In this paper, by using independent component analysis (ICA) and multivariate empirical mode decomposition (MEMD), the ICA-based MEMD method was proposed to remove EOG artifacts (EOAs) from multichannel EEG signals. First, the EEG signals were decomposed by the MEMD into multiple multivariate intrinsic mode functions (MIMFs). The EOG-related components were then extracted by reconstructing the MIMFs corresponding to EOAs. After performing the ICA of EOG-related signals, the EOG-linked independent components were distinguished and rejected. Finally, the clean EEG signals were reconstructed by implementing the inverse transform of ICA and MEMD. The results of simulated and real data suggested that the proposed method could successfully eliminate EOAs from EEG signals and preserve useful EEG information with little loss. By comparing with other existing techniques, the proposed method achieved much improvement in terms of the increase of signal-to-noise and the decrease of mean square error after removing EOAs.

  3. Entropy-based automated classification of independent components separated from fMCG

    International Nuclear Information System (INIS)

    Comani, S; Srinivasan, V; Alleva, G; Romani, G L

    2007-01-01

    Fetal magnetocardiography (fMCG) is a noninvasive technique suitable for the prenatal diagnosis of the fetal heart function. Reliable fetal cardiac signals can be reconstructed from multi-channel fMCG recordings by means of independent component analysis (ICA). However, the identification of the separated components is usually accomplished by visual inspection. This paper discusses a novel automated system based on entropy estimators, namely approximate entropy (ApEn) and sample entropy (SampEn), for the classification of independent components (ICs). The system was validated on 40 fMCG datasets of normal fetuses with the gestational age ranging from 22 to 37 weeks. Both ApEn and SampEn were able to measure the stability and predictability of the physiological signals separated with ICA, and the entropy values of the three categories were significantly different at p <0.01. The system performances were compared with those of a method based on the analysis of the time and frequency content of the components. The outcomes of this study showed a superior performance of the entropy-based system, in particular for early gestation, with an overall ICs detection rate of 98.75% and 97.92% for ApEn and SampEn respectively, as against a value of 94.50% obtained with the time-frequency-based system. (note)

  4. Detection of Connective Tissue Disorders from 3D Aortic MR Images Using Independent Component Analysis

    DEFF Research Database (Denmark)

    Hansen, Michael Sass; Zhao, Fei; Zhang, Honghai

    2006-01-01

    A computer-aided diagnosis (CAD) method is reported that allows the objective identification of subjects with connective tissue disorders from 3D aortic MR images using segmentation and independent component analysis (ICA). The first step to extend the model to 4D (3D + time) has also been taken....... ICA is an effective tool for connective tissue disease detection in the presence of sparse data using prior knowledge to order the components, and the components can be inspected visually. 3D+time MR image data sets acquired from 31 normal and connective tissue disorder subjects at end-diastole (R......-wave peak) and at 45\\$\\backslash\\$% of the R-R interval were used to evaluate the performance of our method. The automated 3D segmentation result produced accurate aortic surfaces covering the aorta. The CAD method distinguished between normal and connective tissue disorder subjects with a classification...

  5. GPR Detection of Buried Symmetrically Shaped Mine-like Objects using Selective Independent Component Analysis

    DEFF Research Database (Denmark)

    Karlsen, Brian; Sørensen, Helge Bjarup Dissing; Larsen, Jan

    2003-01-01

    from small-scale anti-personal (AP) mines to large-scale anti-tank (AT) mines were designed. Large-scale SF-GPR measurements on this series of mine-like objects buried in soil were performed. The SF-GPR data was acquired using a wideband monostatic bow-tie antenna operating in the frequency range 750......This paper addresses the detection of mine-like objects in stepped-frequency ground penetrating radar (SF-GPR) data as a function of object size, object content, and burial depth. The detection approach is based on a Selective Independent Component Analysis (SICA). SICA provides an automatic...... ranking of components, which enables the suppression of clutter, hence extraction of components carrying mine information. The goal of the investigation is to evaluate various time and frequency domain ICA approaches based on SICA. Performance comparison is based on a series of mine-like objects ranging...

  6. REPEATABILITY OF SPITZER/IRAC EXOPLANETARY ECLIPSES WITH INDEPENDENT COMPONENT ANALYSIS

    Energy Technology Data Exchange (ETDEWEB)

    Morello, G.; Waldmann, I. P.; Tinetti, G., E-mail: giuseppe.morello.11@ucl.ac.uk [Department of Physics and Astronomy, University College London, Gower Street, WC1E6BT (United Kingdom)

    2016-04-01

    The research of effective and reliable detrending methods for Spitzer data is of paramount importance for the characterization of exoplanetary atmospheres. To date, the totality of exoplanetary observations in the mid- and far-infrared, at wavelengths >3 μm, have been taken with Spitzer. In some cases, in past years, repeated observations and multiple reanalyses of the same data sets led to discrepant results, raising questions about the accuracy and reproducibility of such measurements. Morello et al. (2014, 2015) proposed a blind-source separation method based on the Independent Component Analysis of pixel time series (pixel-ICA) to analyze InfraRed Array Camera (IRAC) data, obtaining coherent results when applied to repeated transit observations previously debated in the literature. Here we introduce a variant to the pixel-ICA through the use of wavelet transform, wavelet pixel-ICA, which extends its applicability to low-signal-to-noise-ratio cases. We describe the method and discuss the results obtained over 12 eclipses of the exoplanet XO3b observed during the “Warm Spitzer” era in the 4.5 μm band. The final results are reported, in part, also in Ingalls et al. (2016), together with results obtained with other detrending methods, and over 10 synthetic eclipses that were analyzed for the “IRAC Data Challenge 2015.” Our results are consistent within 1σ with the ones reported in Wong et al. (2014) and with most of the results reported in Ingalls et al. (2016), which appeared on arXiv while this paper was under review. Based on many statistical tests discussed in Ingalls et al. (2016), the wavelet pixel-ICA method performs as well as or better than other state-of-art methods recently developed by other teams to analyze Spitzer/IRAC data, and, in particular, it appears to be the most repeatable and the most reliable, while reaching the photon noise limit, at least for the particular data set analyzed. Another strength of the ICA approach is its highest

  7. REPEATABILITY OF SPITZER/IRAC EXOPLANETARY ECLIPSES WITH INDEPENDENT COMPONENT ANALYSIS

    International Nuclear Information System (INIS)

    Morello, G.; Waldmann, I. P.; Tinetti, G.

    2016-01-01

    The research of effective and reliable detrending methods for Spitzer data is of paramount importance for the characterization of exoplanetary atmospheres. To date, the totality of exoplanetary observations in the mid- and far-infrared, at wavelengths >3 μm, have been taken with Spitzer. In some cases, in past years, repeated observations and multiple reanalyses of the same data sets led to discrepant results, raising questions about the accuracy and reproducibility of such measurements. Morello et al. (2014, 2015) proposed a blind-source separation method based on the Independent Component Analysis of pixel time series (pixel-ICA) to analyze InfraRed Array Camera (IRAC) data, obtaining coherent results when applied to repeated transit observations previously debated in the literature. Here we introduce a variant to the pixel-ICA through the use of wavelet transform, wavelet pixel-ICA, which extends its applicability to low-signal-to-noise-ratio cases. We describe the method and discuss the results obtained over 12 eclipses of the exoplanet XO3b observed during the “Warm Spitzer” era in the 4.5 μm band. The final results are reported, in part, also in Ingalls et al. (2016), together with results obtained with other detrending methods, and over 10 synthetic eclipses that were analyzed for the “IRAC Data Challenge 2015.” Our results are consistent within 1σ with the ones reported in Wong et al. (2014) and with most of the results reported in Ingalls et al. (2016), which appeared on arXiv while this paper was under review. Based on many statistical tests discussed in Ingalls et al. (2016), the wavelet pixel-ICA method performs as well as or better than other state-of-art methods recently developed by other teams to analyze Spitzer/IRAC data, and, in particular, it appears to be the most repeatable and the most reliable, while reaching the photon noise limit, at least for the particular data set analyzed. Another strength of the ICA approach is its highest

  8. Neuroinflammatory component of gray matter pathology in multiple sclerosis.

    Science.gov (United States)

    Herranz, Elena; Giannì, Costanza; Louapre, Céline; Treaba, Constantina A; Govindarajan, Sindhuja T; Ouellette, Russell; Loggia, Marco L; Sloane, Jacob A; Madigan, Nancy; Izquierdo-Garcia, David; Ward, Noreen; Mangeat, Gabriel; Granberg, Tobias; Klawiter, Eric C; Catana, Ciprian; Hooker, Jacob M; Taylor, Norman; Ionete, Carolina; Kinkel, Revere P; Mainero, Caterina

    2016-11-01

    In multiple sclerosis (MS), using simultaneous magnetic resonance-positron emission tomography (MR-PET) imaging with 11 C-PBR28, we quantified expression of the 18kDa translocator protein (TSPO), a marker of activated microglia/macrophages, in cortex, cortical lesions, deep gray matter (GM), white matter (WM) lesions, and normal-appearing WM (NAWM) to investigate the in vivo pathological and clinical relevance of neuroinflammation. Fifteen secondary-progressive MS (SPMS) patients, 12 relapsing-remitting MS (RRMS) patients, and 14 matched healthy controls underwent 11 C-PBR28 MR-PET. MS subjects underwent 7T T2*-weighted imaging for cortical lesion segmentation, and neurological and cognitive evaluation. 11 C-PBR28 binding was measured using normalized 60- to 90-minute standardized uptake values and volume of distribution ratios. Relative to controls, MS subjects exhibited abnormally high 11 C-PBR28 binding across the brain, the greatest increases being in cortex and cortical lesions, thalamus, hippocampus, and NAWM. MS WM lesions showed relatively modest TSPO increases. With the exception of cortical lesions, where TSPO expression was similar, 11 C-PBR28 uptake across the brain was greater in SPMS than in RRMS. In MS, increased 11 C-PBR28 binding in cortex, deep GM, and NAWM correlated with neurological disability and impaired cognitive performance; cortical thinning correlated with increased thalamic TSPO levels. In MS, neuroinflammation is present in the cortex, cortical lesions, deep GM, and NAWM, is closely linked to poor clinical outcome, and is at least partly linked to neurodegeneration. Distinct inflammatory-mediated factors may underlie accumulation of cortical and WM lesions. Quantification of TSPO levels in MS could prove to be a sensitive tool for evaluating in vivo the inflammatory component of GM pathology, particularly in cortical lesions. Ann Neurol 2016;80:776-790. © 2016 American Neurological Association.

  9. Time-independent and time-dependent contributions to the unavailability of standby safety system components

    International Nuclear Information System (INIS)

    Lofgren, E.V.; Uryasev, S.; Samanta, P.

    1997-01-01

    The unavailability of standby safety system components due to failures in nuclear power plants is considered to involve a time-independent and a time-dependent part. The former relates to the component's unavailability from demand stresses due to usage, and the latter represents the component's unavailability due to standby-time stresses related to the environment. In this paper, data from the nuclear plant reliability data system (NPRDS) were used to partition the component's unavailability into the contributions from standby-time stress (i.e., due to environmental factors) and demand stress (i.e., due to usage). Analyses are presented of motor-operated valves (MOVs), motor-driven pumps (MDPs), and turbine-driven pumps (TDPs). MOVs fail predominantly (approx. 78 %) from environmental factors (standby-time stress failures). MDPs fail slightly more frequently from demand stresses (approx. 63 %) than standby-time stresses, while TDPs fail predominantly from standby-time stresses (approx. 78 %). Such partitions of component unavailability have many uses in risk-informed and performance-based regulation relating to modifications to Technical Specification, in-service testing, precise determination of dominant accident sequences, and implementation of maintenance rules

  10. Independent component analysis reveals new and biologically significant structures in micro array data

    Directory of Open Access Journals (Sweden)

    Veerla Srinivas

    2006-06-01

    Full Text Available Abstract Background An alternative to standard approaches to uncover biologically meaningful structures in micro array data is to treat the data as a blind source separation (BSS problem. BSS attempts to separate a mixture of signals into their different sources and refers to the problem of recovering signals from several observed linear mixtures. In the context of micro array data, "sources" may correspond to specific cellular responses or to co-regulated genes. Results We applied independent component analysis (ICA to three different microarray data sets; two tumor data sets and one time series experiment. To obtain reliable components we used iterated ICA to estimate component centrotypes. We found that many of the low ranking components indeed may show a strong biological coherence and hence be of biological significance. Generally ICA achieved a higher resolution when compared with results based on correlated expression and a larger number of gene clusters with significantly enriched for gene ontology (GO categories. In addition, components characteristic for molecular subtypes and for tumors with specific chromosomal translocations were identified. ICA also identified more than one gene clusters significant for the same GO categories and hence disclosed a higher level of biological heterogeneity, even within coherent groups of genes. Conclusion Although the ICA approach primarily detects hidden variables, these surfaced as highly correlated genes in time series data and in one instance in the tumor data. This further strengthens the biological relevance of latent variables detected by ICA.

  11. Functional Components of Cognitive Impairment in Multiple Sclerosis: A Cross-Sectional Investigation

    Directory of Open Access Journals (Sweden)

    Jordi A. Matias-Guiu

    2017-11-01

    Full Text Available BackgroundCognitive impairment is frequent and disabling in multiple sclerosis (MS. Changes in information processing speed constitute the most important cognitive deficit in MS. However, given the clinical and topographical variability of the disease, cognitive impairment may vary greatly and appear in other forms in addition to slower information processing speed. Our aim was to determine the frequency of cognitive impairment, the principal cognitive domains, and components involved in MS and to identify factors associated with presence of cognitive impairment in these patients in a large series of patients.MethodsCross-sectional study of 311 patients with MS [236 with relapsing-remitting MS (RRMS, 52 with secondary progressive MS (SPMS, and 23 with primary progressive MS (PPMS]. Patients’ cognitive function was assessed with a comprehensive neuropsychological assessment protocol. Patients displaying deficits in 2 or more cognitive domains were considered to have cognitive impairment associated with MS. We conducted a principal component analysis to detect different cognitive patterns by identifying clusters of tests highly correlated to one another.ResultsCognitive impairment was detected in 41.5% of the sample, and it was more frequent in patients with SPMS and PPMS (P = 0.002. Expanded Disability Status Scale scores and education were independent predictors of cognitive impairment. Principal component analysis identified seven clusters: attention and basic executive function (including information processing speed, planning and high-level executive function, verbal memory and language, executive and visuospatial performance time, fatigue-depression, visuospatial function, and basic attention and verbal/visual working memory. Mean scoring of components 2 (high-order executive functioning and 3 (verbal memory-language was higher in patients with RRMS than in those with PPMS (component 2 and SPMS (component 3.ConclusionMS is linked to

  12. Applying independent component analysis to clinical fMRI at 7 T

    Directory of Open Access Journals (Sweden)

    Simon Daniel Robinson

    2013-09-01

    Full Text Available Increased BOLD sensitivity at 7 T offers the possibility to increase the reliability of fMRI, but ultra-high field is also associated with an increase in artifacts related to head motion, Nyquist ghosting and parallel imaging reconstruction errors. In this study, the ability of Independent Component Analysis (ICA to separate activation from these artifacts was assessed in a 7 T study of neurological patients performing chin and hand motor tasks. ICA was able to isolate primary motor activation with negligible contamination by motion effects. The results of General Linear Model (GLM analysis of these data were, in contrast, heavily contaminated by motion. Secondary motor areas, basal ganglia and thalamus involvement were apparent in ICA results, but there was low capability to isolate activation in the same brain regions in the GLM analysis, indicating that ICA was more sensitive as well as more specific. A method was developed to simplify the assessment of the large number of independent components. Task-related activation components could be automatically identified via intuitive and effective features. These findings demonstrate that ICA is a practical and sensitive analysis approach in high field fMRI studies, particularly where motion is evoked. Promising applications of ICA in clinical fMRI include presurgical planning and the study of pathologies affecting subcortical brain areas.

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

    Science.gov (United States)

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

    2009-02-01

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

  14. Automatic denoising of functional MRI data: combining independent component analysis and hierarchical fusion of classifiers.

    Science.gov (United States)

    Salimi-Khorshidi, Gholamreza; Douaud, Gwenaëlle; Beckmann, Christian F; Glasser, Matthew F; Griffanti, Ludovica; Smith, Stephen M

    2014-04-15

    Many sources of fluctuation contribute to the fMRI signal, and this makes identifying the effects that are truly related to the underlying neuronal activity difficult. Independent component analysis (ICA) - one of the most widely used techniques for the exploratory analysis of fMRI data - has shown to be a powerful technique in identifying various sources of neuronally-related and artefactual fluctuation in fMRI data (both with the application of external stimuli and with the subject "at rest"). ICA decomposes fMRI data into patterns of activity (a set of spatial maps and their corresponding time series) that are statistically independent and add linearly to explain voxel-wise time series. Given the set of ICA components, if the components representing "signal" (brain activity) can be distinguished form the "noise" components (effects of motion, non-neuronal physiology, scanner artefacts and other nuisance sources), the latter can then be removed from the data, providing an effective cleanup of structured noise. Manual classification of components is labour intensive and requires expertise; hence, a fully automatic noise detection algorithm that can reliably detect various types of noise sources (in both task and resting fMRI) is desirable. In this paper, we introduce FIX ("FMRIB's ICA-based X-noiseifier"), which provides an automatic solution for denoising fMRI data via accurate classification of ICA components. For each ICA component FIX generates a large number of distinct spatial and temporal features, each describing a different aspect of the data (e.g., what proportion of temporal fluctuations are at high frequencies). The set of features is then fed into a multi-level classifier (built around several different classifiers). Once trained through the hand-classification of a sufficient number of training datasets, the classifier can then automatically classify new datasets. The noise components can then be subtracted from (or regressed out of) the original

  15. Blind Extraction of Chaotic Signals by Using the Fast Independent Component Analysis Algorithm

    International Nuclear Information System (INIS)

    Hong-Bin, Chen; Jiu-Chao, Feng; Yong, Fang

    2008-01-01

    We report the results of using the fast independent component analysis (FastICA) algorithm to realize blind extraction of chaotic signals. Two cases are taken into consideration: namely, the mixture is noiseless or contaminated by noise. Pre-whitening is employed to reduce the effect of noise before using the FastICA algorithm. The correlation coefficient criterion is adopted to evaluate the performance, and the success rate is defined as a new criterion to indicate the performance with respect to noise or different mixing matrices. Simulation results show that the FastICA algorithm can extract the chaotic signals effectively. The impact of noise, the length of a signal frame, the number of sources and the number of observed mixtures on the performance is investigated in detail. It is also shown that regarding a noise as an independent source is not always correct

  16. Dual-energy x-ray image decomposition by independent component analysis

    Science.gov (United States)

    Jiang, Yifeng; Jiang, Dazong; Zhang, Feng; Zhang, Dengfu; Lin, Gang

    2001-09-01

    The spatial distributions of bone and soft tissue in human body are separated by independent component analysis (ICA) of dual-energy x-ray images. It is because of the dual energy imaging modelí-s conformity to the ICA model that we can apply this method: (1) the absorption in body is mainly caused by photoelectric absorption and Compton scattering; (2) they take place simultaneously but are mutually independent; and (3) for monochromatic x-ray sources the total attenuation is achieved by linear combination of these two absorption. Compared with the conventional method, the proposed one needs no priori information about the accurate x-ray energy magnitude for imaging, while the results of the separation agree well with the conventional one.

  17. A Novel Method for Surface Defect Detection of Photovoltaic Module Based on Independent Component Analysis

    Directory of Open Access Journals (Sweden)

    Xuewu Zhang

    2013-01-01

    Full Text Available This paper proposed a new method for surface defect detection of photovoltaic module based on independent component analysis (ICA reconstruction algorithm. Firstly, a faultless image is used as the training image. The demixing matrix and corresponding ICs are obtained by applying the ICA in the training image. Then we reorder the ICs according to the range values and reform the de-mixing matrix. Then the reformed de-mixing matrix is used to reconstruct the defect image. The resulting image can remove the background structures and enhance the local anomalies. Experimental results have shown that the proposed method can effectively detect the presence of defects in periodically patterned surfaces.

  18. Complex Signal Kurtosis and Independent Component Analysis for Wideband Radio Frequency Interference Detection

    Science.gov (United States)

    Schoenwald, Adam; Mohammed, Priscilla; Bradley, Damon; Piepmeier, Jeffrey; Wong, Englin; Gholian, Armen

    2016-01-01

    Radio-frequency interference (RFI) has negatively implicated scientific measurements across a wide variation passive remote sensing satellites. This has been observed in the L-band radiometers SMOS, Aquarius and more recently, SMAP [1, 2]. RFI has also been observed at higher frequencies such as K band [3]. Improvements in technology have allowed wider bandwidth digital back ends for passive microwave radiometry. A complex signal kurtosis radio frequency interference detector was developed to help identify corrupted measurements [4]. This work explores the use of ICA (Independent Component Analysis) as a blind source separation technique to pre-process radiometric signals for use with the previously developed real and complex signal kurtosis detectors.

  19. Applying independent component analysis to clinical FMRI at 7 t

    OpenAIRE

    Robinson, Simon Daniel; Schöpf, Veronika; Cardoso, Pedro; Geissler, Alexander; Fischmeister, Florian P S; Wurnig, Moritz; Trattnig, Siegfried; Beisteiner, Roland

    2013-01-01

    Increased BOLD sensitivity at 7 T offers the possibility to increase the reliability of fMRI, but ultra-high field is also associated with an increase in artifacts related to head motion, Nyquist ghosting, and parallel imaging reconstruction errors. In this study, the ability of independent component analysis (ICA) to separate activation from these artifacts was assessed in a 7 T study of neurological patients performing chin and hand motor tasks. ICA was able to isolate primary motor activat...

  20. Estimation of Frame Independent and Enhancement Components for Speech Communication over Packet Networks

    DEFF Research Database (Denmark)

    Giacobello, Daniele; Murthi, Manohar N.; Christensen, Mads Græsbøll

    2010-01-01

    In this paper, we describe a new approach to cope with packet loss in speech coders. The idea is to split the information present in each speech packet into two components, one to independently decode the given speech frame and one to enhance it by exploiting interframe dependencies. The scheme...... is based on sparse linear prediction and a redefinition of the analysis-by-synthesis process. We present Mean Opinion Scores for the presented coder with different degrees of packet loss and show that it performs similarly to frame dependent coders for low packet loss probability and similarly to frame...

  1. A K-means multivariate approach for clustering independent components from magnetoencephalographic data.

    Science.gov (United States)

    Spadone, Sara; de Pasquale, Francesco; Mantini, Dante; Della Penna, Stefania

    2012-09-01

    Independent component analysis (ICA) is typically applied on functional magnetic resonance imaging, electroencephalographic and magnetoencephalographic (MEG) data due to its data-driven nature. In these applications, ICA needs to be extended from single to multi-session and multi-subject studies for interpreting and assigning a statistical significance at the group level. Here a novel strategy for analyzing MEG independent components (ICs) is presented, Multivariate Algorithm for Grouping MEG Independent Components K-means based (MAGMICK). The proposed approach is able to capture spatio-temporal dynamics of brain activity in MEG studies by running ICA at subject level and then clustering the ICs across sessions and subjects. Distinctive features of MAGMICK are: i) the implementation of an efficient set of "MEG fingerprints" designed to summarize properties of MEG ICs as they are built on spatial, temporal and spectral parameters; ii) the implementation of a modified version of the standard K-means procedure to improve its data-driven character. This algorithm groups the obtained ICs automatically estimating the number of clusters through an adaptive weighting of the parameters and a constraint on the ICs independence, i.e. components coming from the same session (at subject level) or subject (at group level) cannot be grouped together. The performances of MAGMICK are illustrated by analyzing two sets of MEG data obtained during a finger tapping task and median nerve stimulation. The results demonstrate that the method can extract consistent patterns of spatial topography and spectral properties across sessions and subjects that are in good agreement with the literature. In addition, these results are compared to those from a modified version of affinity propagation clustering method. The comparison, evaluated in terms of different clustering validity indices, shows that our methodology often outperforms the clustering algorithm. Eventually, these results are

  2. Music video shot segmentation using independent component analysis and keyframe extraction based on image complexity

    Science.gov (United States)

    Li, Wei; Chen, Ting; Zhang, Wenjun; Shi, Yunyu; Li, Jun

    2012-04-01

    In recent years, Music video data is increasing at an astonishing speed. Shot segmentation and keyframe extraction constitute a fundamental unit in organizing, indexing, retrieving video content. In this paper a unified framework is proposed to detect the shot boundaries and extract the keyframe of a shot. Music video is first segmented to shots by illumination-invariant chromaticity histogram in independent component (IC) analysis feature space .Then we presents a new metric, image complexity, to extract keyframe in a shot which is computed by ICs. Experimental results show the framework is effective and has a good performance.

  3. Identifying constituents in commercial gasoline using Fourier transform-infrared spectroscopy and independent component analysis.

    Science.gov (United States)

    Pasadakis, Nikos; Kardamakis, Andreas A

    2006-09-25

    A new method is proposed that enables the identification of five refinery fractions present in commercial gasoline mixtures using infrared spectroscopic analysis. The data analysis and interpretation was carried out based on independent component analysis (ICA) and spectral similarity techniques. The FT-IR spectra of the gasoline constituents were determined using the ICA method, exclusively based on the spectra of their mixtures as a blind separation procedure, i.e. assuming unknown the spectra of the constituents. The identity of the constituents was subsequently determined using similarity measures commonly employed in spectra library searches against the spectra of the constituent components. The high correlation scores that were obtained in the identification of the constituents indicates that the developed method can be employed as a rapid and effective tool in quality control, fingerprinting or forensic applications, where gasoline constituents are suspected.

  4. Classification of fMRI independent components using IC-fingerprints and support vector machine classifiers.

    Science.gov (United States)

    De Martino, Federico; Gentile, Francesco; Esposito, Fabrizio; Balsi, Marco; Di Salle, Francesco; Goebel, Rainer; Formisano, Elia

    2007-01-01

    We present a general method for the classification of independent components (ICs) extracted from functional MRI (fMRI) data sets. The method consists of two steps. In the first step, each fMRI-IC is associated with an IC-fingerprint, i.e., a representation of the component in a multidimensional space of parameters. These parameters are post hoc estimates of global properties of the ICs and are largely independent of a specific experimental design and stimulus timing. In the second step a machine learning algorithm automatically separates the IC-fingerprints into six general classes after preliminary training performed on a small subset of expert-labeled components. We illustrate this approach in a multisubject fMRI study employing visual structure-from-motion stimuli encoding faces and control random shapes. We show that: (1) IC-fingerprints are a valuable tool for the inspection, characterization and selection of fMRI-ICs and (2) automatic classifications of fMRI-ICs in new subjects present a high correspondence with those obtained by expert visual inspection of the components. Importantly, our classification procedure highlights several neurophysiologically interesting processes. The most intriguing of which is reflected, with high intra- and inter-subject reproducibility, in one IC exhibiting a transiently task-related activation in the 'face' region of the primary sensorimotor cortex. This suggests that in addition to or as part of the mirror system, somatotopic regions of the sensorimotor cortex are involved in disambiguating the perception of a moving body part. Finally, we show that the same classification algorithm can be successfully applied, without re-training, to fMRI collected using acquisition parameters, stimulation modality and timing considerably different from those used for training.

  5. Diagnosis of Connective Tissue Disorders based on Independent Component Analysis of Aortic Shape and Motion from 4D MR Images

    DEFF Research Database (Denmark)

    Hansen, Michael Sass; Zhao, Fei; Zhang, Honghai

    2006-01-01

    Independent component analysis (ICA) is employed for com\\$\\backslash\\$-puter-aided diagnosis (CAD) allowing objective identification of subjects with connective tissue disorder from 4D aortic MR images. Stationary independent components assist in the disease detection, which is the first...

  6. Objective selection of EEG late potentials through residual dependence estimation of independent components

    International Nuclear Information System (INIS)

    Milanesi, M; James, C J; Martini, N; Menicucci, D; Gemignani, A; Ghelarducci, B; Landini, L

    2009-01-01

    This paper presents a novel method to objectively select electroencephalographic (EEG) cortical sources estimated by independent component analysis (ICA) in event-related potential (ERP) studies. A proximity measure based on mutual information is employed to estimate residual dependences of the components that are then hierarchically clustered based on these residual dependences. Next, the properties of each group of components are evaluated at each level of the hierarchical tree by two indices that aim to assess both cluster tightness and physiological reliability through a template matching process. These two indices are combined in three different approaches to bring to light the hierarchical structure of the cluster organizations. Our method is tested on a set of experiments with the purpose of enhancing late positive ERPs elicited by emotional picture stimuli. Results suggest that the best way to look for physiologically plausible late positive potential (LPP) sources is to explore in depth the tightness of those clusters that, taken together, best resemble the template. According to our results, after brain sources clustering, LPPs are always identified more accurately than from ensemble-averaged raw data. Since the late components of an ERP involve the same associative areas, regardless of the modality of stimulation or specific tasks administered, the proposed method can be simply adapted to other ERP studies, and extended from psychophysiological studies to pathological or sport training evaluation support

  7. The effect of image position on the Independent Components of natural binocular images.

    Science.gov (United States)

    Hunter, David W; Hibbard, Paul B

    2018-01-11

    Human visual performance degrades substantially as the angular distance from the fovea increases. This decrease in performance is found for both binocular and monocular vision. Although analysis of the statistics of natural images has provided significant insights into human visual processing, little research has focused on the statistical content of binocular images at eccentric angles. We applied Independent Component Analysis to rectangular image patches cut from locations within binocular images corresponding to different degrees of eccentricity. The distribution of components learned from the varying locations was examined to determine how these distributions varied across eccentricity. We found a general trend towards a broader spread of horizontal and vertical position disparity tunings in eccentric regions compared to the fovea, with the horizontal spread more pronounced than the vertical spread. Eccentric locations above the centroid show a strong bias towards far-tuned components, eccentric locations below the centroid show a strong bias towards near-tuned components. These distributions exhibit substantial similarities with physiological measurements in V1, however in common with previous research we also observe important differences, in particular distributions of binocular phase disparity which do not match physiology.

  8. Prefrontal cortex and somatosensory cortex in tactile crossmodal association: an independent component analysis of ERP recordings.

    Directory of Open Access Journals (Sweden)

    Yixuan Ku

    2007-08-01

    Full Text Available Our previous studies on scalp-recorded event-related potentials (ERPs showed that somatosensory N140 evoked by a tactile vibration in working memory tasks was enhanced when human subjects expected a coming visual stimulus that had been paired with the tactile stimulus. The results suggested that such enhancement represented the cortical activities involved in tactile-visual crossmodal association. In the present study, we further hypothesized that the enhancement represented the neural activities in somatosensory and frontal cortices in the crossmodal association. By applying independent component analysis (ICA to the ERP data, we found independent components (ICs located in the medial prefrontal cortex (around the anterior cingulate cortex, ACC and the primary somatosensory cortex (SI. The activity represented by the IC in SI cortex showed enhancement in expectation of the visual stimulus. Such differential activity thus suggested the participation of SI cortex in the task-related crossmodal association. Further, the coherence analysis and the Granger causality spectral analysis of the ICs showed that SI cortex appeared to cooperate with ACC in attention and perception of the tactile stimulus in crossmodal association. The results of our study support with new evidence an important idea in cortical neurophysiology: higher cognitive operations develop from the modality-specific sensory cortices (in the present study, SI cortex that are involved in sensation and perception of various stimuli.

  9. Denoising of chaotic signal using independent component analysis and empirical mode decomposition with circulate translating

    Science.gov (United States)

    Wen-Bo, Wang; Xiao-Dong, Zhang; Yuchan, Chang; Xiang-Li, Wang; Zhao, Wang; Xi, Chen; Lei, Zheng

    2016-01-01

    In this paper, a new method to reduce noises within chaotic signals based on ICA (independent component analysis) and EMD (empirical mode decomposition) is proposed. The basic idea is decomposing chaotic signals and constructing multidimensional input vectors, firstly, on the base of EMD and its translation invariance. Secondly, it makes the independent component analysis on the input vectors, which means that a self adapting denoising is carried out for the intrinsic mode functions (IMFs) of chaotic signals. Finally, all IMFs compose the new denoised chaotic signal. Experiments on the Lorenz chaotic signal composed of different Gaussian noises and the monthly observed chaotic sequence on sunspots were put into practice. The results proved that the method proposed in this paper is effective in denoising of chaotic signals. Moreover, it can correct the center point in the phase space effectively, which makes it approach the real track of the chaotic attractor. Project supported by the National Science and Technology, China (Grant No. 2012BAJ15B04), the National Natural Science Foundation of China (Grant Nos. 41071270 and 61473213), the Natural Science Foundation of Hubei Province, China (Grant No. 2015CFB424), the State Key Laboratory Foundation of Satellite Ocean Environment Dynamics, China (Grant No. SOED1405), the Hubei Provincial Key Laboratory Foundation of Metallurgical Industry Process System Science, China (Grant No. Z201303), and the Hubei Key Laboratory Foundation of Transportation Internet of Things, Wuhan University of Technology, China (Grant No.2015III015-B02).

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

    Science.gov (United States)

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

    2015-02-20

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

  11. Generalised model-independent characterisation of strong gravitational lenses. II. Transformation matrix between multiple images

    Science.gov (United States)

    Wagner, J.; Tessore, N.

    2018-05-01

    We determine the transformation matrix that maps multiple images with identifiable resolved features onto one another and that is based on a Taylor-expanded lensing potential in the vicinity of a point on the critical curve within our model-independent lens characterisation approach. From the transformation matrix, the same information about the properties of the critical curve at fold and cusp points can be derived as we previously found when using the quadrupole moment of the individual images as observables. In addition, we read off the relative parities between the images, so that the parity of all images is determined when one is known. We compare all retrievable ratios of potential derivatives to the actual values and to those obtained by using the quadrupole moment as observable for two- and three-image configurations generated by a galaxy-cluster scale singular isothermal ellipse. We conclude that using the quadrupole moments as observables, the properties of the critical curve are retrieved to a higher accuracy at the cusp points and to a lower accuracy at the fold points; the ratios of second-order potential derivatives are retrieved to comparable accuracy. We also show that the approach using ratios of convergences and reduced shear components is equivalent to ours in the vicinity of the critical curve, but yields more accurate results and is more robust because it does not require a special coordinate system as the approach using potential derivatives does. The transformation matrix is determined by mapping manually assigned reference points in the multiple images onto one another. If the assignment of the reference points is subject to measurement uncertainties under the influence of noise, we find that the confidence intervals of the lens parameters can be as large as the values themselves when the uncertainties are larger than one pixel. In addition, observed multiple images with resolved features are more extended than unresolved ones, so that

  12. Independent component analysis of gait-related movement artifact recorded using EEG electrodes during treadmill walking.

    Directory of Open Access Journals (Sweden)

    Kristine Lynne Snyder

    2015-12-01

    Full Text Available There has been a recent surge in the use of electroencephalography (EEG as a tool for mobile brain imaging due to its portability and fine time resolution. When EEG is combined with independent component analysis (ICA and source localization techniques, it can model electrocortical activity as arising from temporally independent signals located in spatially distinct cortical areas. However, for mobile tasks, it is not clear how movement artifacts influence ICA and source localization. We devised a novel method to collect pure movement artifact data (devoid of any electrophysiological signals with a 256-channel EEG system. We first blocked true electrocortical activity using a silicone swim cap. Over the silicone layer, we placed a simulated scalp with electrical properties similar to real human scalp. We collected EEG movement artifact signals from ten healthy, young subjects wearing this setup as they walked on a treadmill at speeds from 0.4-1.6 m/s. We performed ICA and dipole fitting on the EEG movement artifact data to quantify how accurately these methods would identify the artifact signals as non-neural. ICA and dipole fitting accurately localized 99% of the independent components in non-neural locations or lacked dipolar characteristics. The remaining 1% of sources had locations within the brain volume and low residual variances, but had topographical maps, power spectra, time courses, and event related spectral perturbations typical of non-neural sources. Caution should be exercised when interpreting ICA for data that includes semi-periodic artifacts including artifact arising from human walking. Alternative methods are needed for the identification and separation of movement artifact in mobile EEG signals, especially methods that can be performed in real time. Separating true brain signals from motion artifact could clear the way for EEG brain computer interfaces for assistance during mobile activities, such as walking.

  13. An assessment of independent component analysis for detection of military targets from hyperspectral images

    Science.gov (United States)

    Tiwari, K. C.; Arora, M. K.; Singh, D.

    2011-10-01

    Hyperspectral data acquired over hundreds of narrow contiguous wavelength bands are extremely suitable for target detection due to their high spectral resolution. Though spectral response of every material is expected to be unique, but in practice, it exhibits variations, which is known as spectral variability. Most target detection algorithms depend on spectral modelling using a priori available target spectra In practice, target spectra is, however, seldom available a priori. Independent component analysis (ICA) is a new evolving technique that aims at finding out components which are statistically independent or as independent as possible. The technique therefore has the potential of being used for target detection applications. A assessment of target detection from hyperspectral images using ICA and other algorithms based on spectral modelling may be of immense interest, since ICA does not require a priori target information. The aim of this paper is, thus, to assess the potential of ICA based algorithm vis a vis other prevailing algorithms for military target detection. Four spectral matching algorithms namely Orthogonal Subspace Projection (OSP), Constrained Energy Minimisation (CEM), Spectral Angle Mapper (SAM) and Spectral Correlation Mapper (SCM), and four anomaly detection algorithms namely OSP anomaly detector (OSPAD), Reed-Xiaoli anomaly detector (RXD), Uniform Target Detector (UTD) and a combination of Reed-Xiaoli anomaly detector and Uniform Target Detector (RXD-UTD) were considered. The experiments were conducted using a set of synthetic and AVIRIS hyperspectral images containing aircrafts as military targets. A comparison of true positive and false positive rates of target detections obtained from ICA and other algorithms plotted on a receiver operating curves (ROC) space indicates the superior performance of the ICA over other algorithms.

  14. Datafish Multiphase Data Mining Technique to Match Multiple Mutually Inclusive Independent Variables in Large PACS Databases.

    Science.gov (United States)

    Kelley, Brendan P; Klochko, Chad; Halabi, Safwan; Siegal, Daniel

    2016-06-01

    Retrospective data mining has tremendous potential in research but is time and labor intensive. Current data mining software contains many advanced search features but is limited in its ability to identify patients who meet multiple complex independent search criteria. Simple keyword and Boolean search techniques are ineffective when more complex searches are required, or when a search for multiple mutually inclusive variables becomes important. This is particularly true when trying to identify patients with a set of specific radiologic findings or proximity in time across multiple different imaging modalities. Another challenge that arises in retrospective data mining is that much variation still exists in how image findings are described in radiology reports. We present an algorithmic approach to solve this problem and describe a specific use case scenario in which we applied our technique to a real-world data set in order to identify patients who matched several independent variables in our institution's picture archiving and communication systems (PACS) database.

  15. Comparing brain graphs in which nodes are regions of interest or independent components: A simulation study.

    Science.gov (United States)

    Yu, Qingbao; Du, Yuhui; Chen, Jiayu; He, Hao; Sui, Jing; Pearlson, Godfrey; Calhoun, Vince D

    2017-11-01

    A key challenge in building a brain graph using fMRI data is how to define the nodes. Spatial brain components estimated by independent components analysis (ICA) and regions of interest (ROIs) determined by brain atlas are two popular methods to define nodes in brain graphs. It is difficult to evaluate which method is better in real fMRI data. Here we perform a simulation study and evaluate the accuracies of a few graph metrics in graphs with nodes of ICA components, ROIs, or modified ROIs in four simulation scenarios. Graph measures with ICA nodes are more accurate than graphs with ROI nodes in all cases. Graph measures with modified ROI nodes are modulated by artifacts. The correlations of graph metrics across subjects between graphs with ICA nodes and ground truth are higher than the correlations between graphs with ROI nodes and ground truth in scenarios with large overlapped spatial sources. Moreover, moving the location of ROIs would largely decrease the correlations in all scenarios. Evaluating graphs with different nodes is promising in simulated data rather than real data because different scenarios can be simulated and measures of different graphs can be compared with a known ground truth. Since ROIs defined using brain atlas may not correspond well to real functional boundaries, overall findings of this work suggest that it is more appropriate to define nodes using data-driven ICA than ROI approaches in real fMRI data. Copyright © 2017 Elsevier B.V. All rights reserved.

  16. A multi-level maintenance policy for a multi-component and multifailure mode system with two independent failure modes

    International Nuclear Information System (INIS)

    Zhu, Wenjin; Fouladirad, Mitra; Bérenguer, Christophe

    2016-01-01

    This paper studies the maintenance modelling of a multi-component system with two independent failure modes with imperfect prediction signal in the context of a system of systems. Each individual system consists of multiple series components and the failure modes of all the components are divided into two classes due to their consequences: hard failure and soft failure, where the former causes system failure while the later results in inferior performance (production reduction) of system. Besides, the system is monitored and can be alerted by imperfect prediction signal before hard failure. Based on an illustration example of offshore wind farm, in this paper three maintenance strategies are considered: periodic routine, reactive and opportunistic maintenance. The periodic routine maintenance is scheduled at fixed period for each individual system in the perspective of system of systems. Between two successive routine maintenances, the reactive maintenance is instructed by the imperfect prediction signal according to two criterion proposed in this study for the system components. Due to the high setup cost and practical restraints of implementing maintenance activities, both routine and reactive maintenance can create the opportunities of maintenance for the other components of an individual system. The life cycle of the system and the cost of the proposed maintenance policies are analytically derived. Restrained by the complexity from both the system failure modelling and maintenance strategies, the performances and application scope of the proposed maintenance model are evaluated by numerical simulations. - Highlights: • We study the life behavior of a complex system with two failure modes. • We consider the imperfect prediction signal of potential failure by monitoring. • We propose an integrated maintenance policy with three levels based on wind turbine. • We derive the mathematical cost formulations for the proposed maintenance policy.

  17. Classification in hyperspectral images by independent component analysis, segmented cross-validation and uncertainty estimates

    Directory of Open Access Journals (Sweden)

    Beatriz Galindo-Prieto

    2018-02-01

    Full Text Available Independent component analysis combined with various strategies for cross-validation, uncertainty estimates by jack-knifing and critical Hotelling’s T2 limits estimation, proposed in this paper, is used for classification purposes in hyperspectral images. To the best of our knowledge, the combined approach of methods used in this paper has not been previously applied to hyperspectral imaging analysis for interpretation and classification in the literature. The data analysis performed here aims to distinguish between four different types of plastics, some of them containing brominated flame retardants, from their near infrared hyperspectral images. The results showed that the method approach used here can be successfully used for unsupervised classification. A comparison of validation approaches, especially leave-one-out cross-validation and regions of interest scheme validation is also evaluated.

  18. RFI Detection and Mitigation using Independent Component Analysis as a Pre-Processor

    Science.gov (United States)

    Schoenwald, Adam J.; Gholian, Armen; Bradley, Damon C.; Wong, Mark; Mohammed, Priscilla N.; Piepmeier, Jeffrey R.

    2016-01-01

    Radio-frequency interference (RFI) has negatively impacted scientific measurements of passive remote sensing satellites. This has been observed in the L-band radiometers Soil Moisture and Ocean Salinity (SMOS), Aquarius and more recently, Soil Moisture Active Passive (SMAP). RFI has also been observed at higher frequencies such as K band. Improvements in technology have allowed wider bandwidth digital back ends for passive microwave radiometry. A complex signal kurtosis radio frequency interference detector was developed to help identify corrupted measurements. This work explores the use of Independent Component Analysis (ICA) as a blind source separation (BSS) technique to pre-process radiometric signals for use with the previously developed real and complex signal kurtosis detectors.

  19. A Parcellation Based Nonparametric Algorithm for Independent Component Analysis with Application to fMRI Data

    Directory of Open Access Journals (Sweden)

    Shanshan eLi

    2016-01-01

    Full Text Available Independent Component analysis (ICA is a widely used technique for separating signals that have been mixed together. In this manuscript, we propose a novel ICA algorithm using density estimation and maximum likelihood, where the densities of the signals are estimated via p-spline based histogram smoothing and the mixing matrix is simultaneously estimated using an optimization algorithm. The algorithm is exceedingly simple, easy to implement and blind to the underlying distributions of the source signals. To relax the identically distributed assumption in the density function, a modified algorithm is proposed to allow for different density functions on different regions. The performance of the proposed algorithm is evaluated in different simulation settings. For illustration, the algorithm is applied to a research investigation with a large collection of resting state fMRI datasets. The results show that the algorithm successfully recovers the established brain networks.

  20. Toward the detection of gravitational waves under non-Gaussian noises II. Independent component analysis.

    Science.gov (United States)

    Morisaki, Soichiro; Yokoyama, Jun'ichi; Eda, Kazunari; Itoh, Yousuke

    2016-01-01

    We introduce a new analysis method to deal with stationary non-Gaussian noises in gravitational wave detectors in terms of the independent component analysis. First, we consider the simplest case where the detector outputs are linear combinations of the inputs, consisting of signals and various noises, and show that this method may be helpful to increase the signal-to-noise ratio. Next, we take into account the time delay between the inputs and the outputs. Finally, we extend our method to nonlinearly correlated noises and show that our method can identify the coupling coefficients and remove non-Gaussian noises. Although we focus on gravitational wave data analysis, our methods are applicable to the detection of any signals under non-Gaussian noises.

  1. Cross coherence independent component analysis in resting and action states EEG discrimination

    International Nuclear Information System (INIS)

    Almurshedi, A; Ismail, A K

    2014-01-01

    Cross Coherence time frequency transform and independent component analysis (ICA) method were used to analyse the electroencephalogram (EEG) signals in resting and action states during open and close eyes conditions. From the topographical scalp distributions of delta, theta, alpha, and beta power spectrum can clearly discriminate between the signal when the eyes were open or closed, but it was difficult to distinguish between resting and action states when the eyes were closed. In open eyes condition, the frontal area (Fp1, Fp2) was activated (higher power) in delta and theta bands whilst occipital (O1, O2) and partial (P3, P4, Pz) area of brain was activated alpha band in closed eyes condition. The cross coherence method of time frequency analysis is capable of discrimination between rest and action brain signals in closed eyes condition

  2. Stabilizing bidirectional associative memory with Principles in Independent Component Analysis and Null Space (PICANS)

    Science.gov (United States)

    LaRue, James P.; Luzanov, Yuriy

    2013-05-01

    A new extension to the way in which the Bidirectional Associative Memory (BAM) algorithms are implemented is presented here. We will show that by utilizing the singular value decomposition (SVD) and integrating principles of independent component analysis (ICA) into the nullspace (NS) we have created a novel approach to mitigating spurious attractors. We demonstrate this with two applications. The first application utilizes a one-layer association while the second application is modeled after the several hierarchal associations of ventral pathways. The first application will detail the way in which we manage the associations in terms of matrices. The second application will take what we have learned from the first example and apply it to a cascade of a convolutional neural network (CNN) and perceptron this being our signal processing model of the ventral pathways, i.e., visual systems.

  3. A Novel Algorithm for Efficient Downlink Packet Scheduling for Multiple-Component-Carrier Cellular Systems

    Directory of Open Access Journals (Sweden)

    Yao-Liang Chung

    2016-11-01

    Full Text Available The simultaneous aggregation of multiple component carriers (CCs for use by a base station constitutes one of the more promising strategies for providing substantially enhanced bandwidths for packet transmissions in 4th and 5th generation cellular systems. To the best of our knowledge, however, few previous studies have undertaken a thorough investigation of various performance aspects of the use of a simple yet effective packet scheduling algorithm in which multiple CCs are aggregated for transmission in such systems. Consequently, the present study presents an efficient packet scheduling algorithm designed on the basis of the proportional fair criterion for use in multiple-CC systems for downlink transmission. The proposed algorithm includes a focus on providing simultaneous transmission support for both real-time (RT and non-RT traffic. This algorithm can, when applied with sufficiently efficient designs, provide adequate utilization of spectrum resources for the purposes of transmissions, while also improving energy efficiency to some extent. According to simulation results, the performance of the proposed algorithm in terms of system throughput, mean delay, and fairness constitute substantial improvements over those of an algorithm in which the CCs are used independently instead of being aggregated.

  4. Resource-sharing in multiple-component working memory

    OpenAIRE

    Doherty, Jason M.; Logie, Robert H.

    2016-01-01

    Working memory research often focuses on measuring the capacity of the system and how it relates to other cognitive abilities. However, research into the structure of working memory is less concerned with an overall capacity measure but rather with the intricacies of underlying components and their contribution to different tasks. A number of models of working memory structure have been proposed, each with different assumptions and predictions, but none of which adequately accounts for the fu...

  5. Sea level reconstructions from altimetry and tide gauges using independent component analysis

    Science.gov (United States)

    Brunnabend, Sandra-Esther; Kusche, Jürgen; Forootan, Ehsan

    2017-04-01

    Many reconstructions of global and regional sea level rise derived from tide gauges and satellite altimetry used the method of empirical orthogonal functions (EOF) to reduce noise, improving the spatial resolution of the reconstructed outputs and investigate the different signals in climate time series. However, the second order EOF method has some limitations, e.g. in the separation of individual physical signals into different modes of sea level variations and in the capability to physically interpret the different modes as they are assumed to be orthogonal. Therefore, we investigate the use of the more advanced statistical signal decomposition technique called independent component analysis (ICA) to reconstruct global and regional sea level change from satellite altimetry and tide gauge records. Our results indicate that the used method has almost no influence on the reconstruction of global mean sea level change (1.6 mm/yr from 1960-2010 and 2.9 mm/yr from 1993-2013). Only different numbers of modes are needed for the reconstruction. Using the ICA method is advantageous for separating independent climate variability signals from regional sea level variations as the mixing problem of the EOF method is strongly reduced. As an example, the modes most dominated by the El Niño-Southern Oscillation (ENSO) signal are compared. Regional sea level changes near Tianjin, China, Los Angeles, USA, and Majuro, Marshall Islands are reconstructed and the contributions from ENSO are identified.

  6. Separation of GRACE geoid time-variations using Independent Component Analysis

    Science.gov (United States)

    Frappart, F.; Ramillien, G.; Maisongrande, P.; Bonnet, M.

    2009-12-01

    Independent Component Analysis (ICA) is a blind separation method based on the simple assumptions of the independence of the sources and the non-Gaussianity of the observations. An approach based on this numerical method is used here to extract hydrological signals over land and oceans from the polluting striping noise due to orbit repetitiveness and present in the GRACE global mass anomalies. We took advantage of the availability of monthly Level-2 solutions from three official providers (i.e., CSR, JPL and GFZ) that can be considered as different observations of the same phenomenon. The efficiency of the methodology is first demonstrated on a synthetic case. Applied to one month of GRACE solutions, it allows to clearly separate the total water storage change from the meridional-oriented spurious gravity signals on the continents but not on the oceans. This technique gives results equivalent as the destriping method for continental water storage for the hydrological patterns with less smoothing. This methodology is then used to filter the complete series of the 2002-2009 GRACE solutions.

  7. Independent component analysis separates spikes of different origin in the EEG.

    Science.gov (United States)

    Urrestarazu, Elena; Iriarte, Jorge; Artieda, Julio; Alegre, Manuel; Valencia, Miguel; Viteri, César

    2006-02-01

    Independent component analysis (ICA) is a novel system that finds independent sources in recorded signals. Its usefulness in separating epileptiform activity of different origin has not been determined. The goal of this study was to demonstrate that ICA is useful for separating different spikes using samples of EEG of patients with focal epilepsy. Digital EEG samples from four patients with focal epilepsy were included. The patients had temporal (n = 2), centrotemporal (n = 1) or frontal spikes (n = 1). Twenty-six samples with two (or more) spikes from two different patients were created. The selection of the two spikes for each mixed EEG was performed randomly, trying to have all the different combinations and rejecting the mixture of two spikes from the same patient. Two different examiners studied the EEGs using ICA with JADE paradigm in Matlab platform, trying to separate and to identify the spikes. They agreed in the correct separation of the spikes in 24 of the 26 samples, classifying the spikes as frontal, temporal or centrotemporal, left or right sided. The demonstration of the possibility of detecting different artificially mixed spikes confirms that ICA may be useful in separating spikes or other elements in real EEGs.

  8. A simple iterative independent component analysis algorithm for vibration source signal identification of complex structures

    Directory of Open Access Journals (Sweden)

    Dong-Sup Lee

    2015-01-01

    Full Text Available Independent Component Analysis (ICA, one of the blind source separation methods, can be applied for extracting unknown source signals only from received signals. This is accomplished by finding statistical independence of signal mixtures and has been successfully applied to myriad fields such as medical science, image processing, and numerous others. Nevertheless, there are inherent problems that have been reported when using this technique: insta- bility and invalid ordering of separated signals, particularly when using a conventional ICA technique in vibratory source signal identification of complex structures. In this study, a simple iterative algorithm of the conventional ICA has been proposed to mitigate these problems. The proposed method to extract more stable source signals having valid order includes an iterative and reordering process of extracted mixing matrix to reconstruct finally converged source signals, referring to the magnitudes of correlation coefficients between the intermediately separated signals and the signals measured on or nearby sources. In order to review the problems of the conventional ICA technique and to vali- date the proposed method, numerical analyses have been carried out for a virtual response model and a 30 m class submarine model. Moreover, in order to investigate applicability of the proposed method to real problem of complex structure, an experiment has been carried out for a scaled submarine mockup. The results show that the proposed method could resolve the inherent problems of a conventional ICA technique.

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

    Science.gov (United States)

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

    2018-02-01

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

  10. Determination of arterial input function in dynamic susceptibility contrast MRI using group independent component analysis technique

    International Nuclear Information System (INIS)

    Chen, S.; Liu, H.-L.; Yang Yihong; Hsu, Y.-Y.; Chuang, K.-S.

    2006-01-01

    Quantification of cerebral blood flow (CBF) with dynamic susceptibility contrast (DSC) magnetic resonance imaging (MRI) requires the determination of the arterial input function (AIF). The segmentation of surrounding tissue by manual selection is error-prone due to the partial volume artifacts. Independent component analysis (ICA) has the advantage in automatically decomposing the signals into interpretable components. Recently group ICA technique has been applied to fMRI study and showed reduced variance caused by motion artifact and noise. In this work, we investigated the feasibility and efficacy of the use of group ICA technique to extract the AIF. Both simulated and in vivo data were analyzed in this study. The simulation data of eight phantoms were generated using randomized lesion locations and time activity curves. The clinical data were obtained from spin-echo EPI MR scans performed in seven normal subjects. Group ICA technique was applied to analyze data through concatenating across seven subjects. The AIFs were calculated from the weighted average of the signals in the region selected by ICA. Preliminary results of this study showed that group ICA technique could not extract accurate AIF information from regions around the vessel. The mismatched location of vessels within the group reduced the benefits of group study

  11. Time course based artifact identification for independent components of resting state fMRI

    Directory of Open Access Journals (Sweden)

    Christian eRummel

    2013-05-01

    Full Text Available In functional magnetic resonance imaging (fMRI coherent oscillations of the blood oxygen level dependent (BOLD signal can be detected. These arise when brain regions respond to external stimuli or are activated by tasks. The same networks have been characterized during wakeful rest when functional connectivity of the human brain is organized in generic resting state networks (RSN. Alterations of RSN emerge as neurobiological markers of pathological conditions such as altered mental state. In single-subject fMRI data the coherent components can be identified by blind source separation of the pre-processed BOLD data using spatial independent component analysis (ICA and related approaches. The resulting maps may represent physiological RSNs or may be due to various artifacts. In this methodological study, we propose a conceptually simple and fully automatic time course based filtering procedure to detect obvious artifacts in the ICA output for resting state fMRI. The filter is trained on six and tested on 29 healthy subjects, yielding mean filter accuracy, sensitivity and specificity of 0.80, 0.82 and 0.75 in out-of-sample tests. To estimate the impact of clearly artifactual single-subject components on group resting state studies we analyze unfiltered and filtered output with a second level ICA procedure. Although the automated filter does not reach performance values of visual analysis by human raters, we propose that resting state compatible analysis of ICA time courses could be very useful to complement the existing map or task/event oriented artifact classification algorithms.

  12. Temporal dynamics of sensorimotor integration in speech perception and production: Independent component analysis of EEG data

    Directory of Open Access Journals (Sweden)

    David eJenson

    2014-07-01

    Full Text Available Activity in premotor and sensorimotor cortices is found in speech production and some perception tasks. Yet, how sensorimotor integration supports these functions is unclear due to a lack of data examining the timing of activity from these regions. Beta (~20Hz and alpha (~10Hz spectral power within the EEG µ rhythm are considered indices of motor and somatosensory activity, respectively. In the current study, perception conditions required discrimination (same/different of syllables pairs (/ba/ and /da/ in quiet and noisy conditions. Production conditions required covert and overt syllable productions and overt word production. Independent component analysis was performed on EEG data obtained during these conditions to 1 identify clusters of µ components common to all conditions and 2 examine real-time event-related spectral perturbations (ERSP within alpha and beta bands. 17 and 15 out of 20 participants produced left and right µ-components, respectively, localized to precentral gyri. Discrimination conditions were characterized by significant (pFDR<.05 early alpha event-related synchronization (ERS prior to and during stimulus presentation and later alpha event-related desynchronization (ERD following stimulus offset. Beta ERD began early and gained strength across time. Differences were found between quiet and noisy discrimination conditions. Both overt syllable and word productions yielded similar alpha/beta ERD that began prior to production and was strongest during muscle activity. Findings during covert production were weaker than during overt production. One explanation for these findings is that µ-beta ERD indexes early predictive coding (e.g., internal modeling and/or overt and covert attentional / motor processes. µ-alpha ERS may index inhibitory input to the premotor cortex from sensory regions prior to and during discrimination, while µ-alpha ERD may index re-afferent sensory feedback during speech rehearsal and production.

  13. Characterization of Ground Displacement Sources from Variational Bayesian Independent Component Analysis of Space Geodetic Time Series

    Science.gov (United States)

    Gualandi, Adriano; Serpelloni, Enrico; Elina Belardinelli, Maria; Bonafede, Maurizio; Pezzo, Giuseppe; Tolomei, Cristiano

    2015-04-01

    A critical point in the analysis of ground displacement time series, as those measured by modern space geodetic techniques (primarly continuous GPS/GNSS and InSAR) is the development of data driven methods that allow to discern and characterize the different sources that generate the observed displacements. A widely used multivariate statistical technique is the Principal Component Analysis (PCA), which allows to reduce the dimensionality of the data space maintaining most of the variance of the dataset explained. It reproduces the original data using a limited number of Principal Components, but it also shows some deficiencies, since PCA does not perform well in finding the solution to the so-called Blind Source Separation (BSS) problem. The recovering and separation of the different sources that generate the observed ground deformation is a fundamental task in order to provide a physical meaning to the possible different sources. PCA fails in the BSS problem since it looks for a new Euclidean space where the projected data are uncorrelated. Usually, the uncorrelation condition is not strong enough and it has been proven that the BSS problem can be tackled imposing on the components to be independent. The Independent Component Analysis (ICA) is, in fact, another popular technique adopted to approach this problem, and it can be used in all those fields where PCA is also applied. An ICA approach enables us to explain the displacement time series imposing a fewer number of constraints on the model, and to reveal anomalies in the data such as transient deformation signals. However, the independence condition is not easy to impose, and it is often necessary to introduce some approximations. To work around this problem, we use a variational bayesian ICA (vbICA) method, which models the probability density function (pdf) of each source signal using a mix of Gaussian distributions. This technique allows for more flexibility in the description of the pdf of the sources

  14. 21 CFR 888.3030 - Single/multiple component metallic bone fixation appliances and accessories.

    Science.gov (United States)

    2010-04-01

    ... appliances and accessories. 888.3030 Section 888.3030 Food and Drugs FOOD AND DRUG ADMINISTRATION, DEPARTMENT....3030 Single/multiple component metallic bone fixation appliances and accessories. (a) Identification. Single/multiple component metallic bone fixation appliances and accessories are devices intended to be...

  15. Quantitative profiling of polar metabolites in herbal medicine injections for multivariate statistical evaluation based on independence principal component analysis.

    Directory of Open Access Journals (Sweden)

    Miaomiao Jiang

    Full Text Available Botanical primary metabolites extensively exist in herbal medicine injections (HMIs, but often were ignored to control. With the limitation of bias towards hydrophilic substances, the primary metabolites with strong polarity, such as saccharides, amino acids and organic acids, are usually difficult to detect by the routinely applied reversed-phase chromatographic fingerprint technology. In this study, a proton nuclear magnetic resonance (1H NMR profiling method was developed for efficient identification and quantification of small polar molecules, mostly primary metabolites in HMIs. A commonly used medicine, Danhong injection (DHI, was employed as a model. With the developed method, 23 primary metabolites together with 7 polyphenolic acids were simultaneously identified, of which 13 metabolites with fully separated proton signals were quantified and employed for further multivariate quality control assay. The quantitative 1H NMR method was validated with good linearity, precision, repeatability, stability and accuracy. Based on independence principal component analysis (IPCA, the contents of 13 metabolites were characterized and dimensionally reduced into the first two independence principal components (IPCs. IPC1 and IPC2 were then used to calculate the upper control limits (with 99% confidence ellipsoids of χ2 and Hotelling T2 control charts. Through the constructed upper control limits, the proposed method was successfully applied to 36 batches of DHI to examine the out-of control sample with the perturbed levels of succinate, malonate, glucose, fructose, salvianic acid and protocatechuic aldehyde. The integrated strategy has provided a reliable approach to identify and quantify multiple polar metabolites of DHI in one fingerprinting spectrum, and it has also assisted in the establishment of IPCA models for the multivariate statistical evaluation of HMIs.

  16. IMPROVING FUNCTIONAL INDEPENDENCE OF PATIENTS WITH MULTIPLE SCLEROSIS BY PHYSICAL THERAPY AND OCCUPATIONAL THERAPY

    Directory of Open Access Journals (Sweden)

    Ana-Maria Ticărat

    2011-06-01

    Full Text Available Introduction. Patients with multiple sclerosis can have a normal life despite of their real or possible disability and of the progressive nature of it. Scope. Patients who follow physical therapy and occupational therapy will have an increased quality of life and a greater functional independence.Methods. The randomized study was made on 7 patients with multiple sclerosis, from Oradea Day Centre, 3 times/week, ages between 35 – 55 years, functional level between mild and sever. Assessment and rehabilitation methods: inspection, BARTHEL Index. Frenkel method, brething exercises, weights exercises, gait exercises, writind exercises and games were used in the rehabilitation process. Group therapies: sociotherapy, arttherapy, music therapy. Results analysis consisted of the comparison of baseline and final means.Results. By analizing baseline and final means for Barthel Index for each functon separately, it was shown a mild improvement of functional independence for almost assessed functions, with at least 1-1,5 points.Conclusions. Persons with multiple sclerosis who follow physical therapy and occupational therapy presents a better functional independence after the treatment.

  17. Signal extraction and wave field separation in tunnel seismic prediction by independent component analysis

    Science.gov (United States)

    Yue, Y.; Jiang, T.; Zhou, Q.

    2017-12-01

    In order to ensure the rationality and the safety of tunnel excavation, the advanced geological prediction has been become an indispensable step in tunneling. However, the extraction of signal and the separation of P and S waves directly influence the accuracy of geological prediction. Generally, the raw data collected in TSP system is low quality because of the numerous disturb factors in tunnel projects, such as the power interference and machine vibration interference. It's difficult for traditional method (band-pass filtering) to remove interference effectively as well as bring little loss to signal. The power interference, machine vibration interference and the signal are original variables and x, y, z component as observation signals, each component of the representation is a linear combination of the original variables, which satisfy applicable conditions of independent component analysis (ICA). We perform finite-difference simulations of elastic wave propagation to synthetic a tunnel seismic reflection record. The method of ICA was adopted to process the three-component data, and the results show that extract the estimates of signal and the signals are highly correlated (the coefficient correlation is up to more than 0.93). In addition, the estimates of interference that separated from ICA and the interference signals are also highly correlated, and the coefficient correlation is up to more than 0.99. Thus, simulation results showed that the ICA is an ideal method for extracting high quality data from mixed signals. For the separation of P and S waves, the conventional separation techniques are based on physical characteristics of wave propagation, which require knowledge of the near-surface P and S waves velocities and density. Whereas the ICA approach is entirely based on statistical differences between P and S waves, and the statistical technique does not require a priori information. The concrete results of the wave field separation will be presented in

  18. Independent component analysis using prior information for signal detection in a functional imaging system of the retina

    NARCIS (Netherlands)

    Barriga, E. Simon; Pattichis, Marios; Ts’o, Dan; Abramoff, Michael; Kardon, Randy; Kwon, Young; Soliz, Peter

    2011-01-01

    Independent component analysis (ICA) is a statistical technique that estimates a set of sources mixed by an unknown mixing matrix using only a set of observations. For this purpose, the only assumption is that the sources are statistically independent. In many applications, some information about

  19. Automatic flow analysis of digital subtraction angiography using independent component analysis in patients with carotid stenosis.

    Directory of Open Access Journals (Sweden)

    Han-Jui Lee

    Full Text Available Current time-density curve analysis of digital subtraction angiography (DSA provides intravascular flow information but requires manual vasculature selection. We developed an angiographic marker that represents cerebral perfusion by using automatic independent component analysis.We retrospectively analyzed the data of 44 patients with unilateral carotid stenosis higher than 70% according to North American Symptomatic Carotid Endarterectomy Trial criteria. For all patients, magnetic resonance perfusion (MRP was performed one day before DSA. Fixed contrast injection protocols and DSA acquisition parameters were used before stenting. The cerebral circulation time (CCT was defined as the difference in the time to peak between the parietal vein and cavernous internal carotid artery in a lateral angiogram. Both anterior-posterior and lateral DSA views were processed using independent component analysis, and the capillary angiogram was extracted automatically. The full width at half maximum of the time-density curve in the capillary phase in the anterior-posterior and lateral DSA views was defined as the angiographic mean transient time (aMTT; i.e., aMTTAP and aMTTLat. The correlations between the degree of stenosis, CCT, aMTTAP and aMTTLat, and MRP parameters were evaluated.The degree of stenosis showed no correlation with CCT, aMTTAP, aMTTLat, or any MRP parameter. CCT showed a strong correlation with aMTTAP (r = 0.67 and aMTTLat (r = 0.72. Among the MRP parameters, CCT showed only a moderate correlation with MTT (r = 0.67 and Tmax (r = 0.40. aMTTAP showed a moderate correlation with Tmax (r = 0.42 and a strong correlation with MTT (r = 0.77. aMTTLat also showed similar correlations with Tmax (r = 0.59 and MTT (r = 0.73.Apart from vascular anatomy, aMTT estimates brain parenchyma hemodynamics from DSA and is concordant with MRP. This process is completely automatic and provides immediate measurement of quantitative peritherapeutic brain parenchyma

  20. Electrically evoked compound action potentials artefact rejection by independent component analysis: procedure automation.

    Science.gov (United States)

    Akhoun, Idrick; McKay, Colette; El-Deredy, Wael

    2015-01-15

    Independent-components-analysis (ICA) successfully separated electrically-evoked compound action potentials (ECAPs) from the stimulation artefact and noise (ECAP-ICA, Akhoun et al., 2013). This paper shows how to automate the ECAP-ICA artefact cancellation process. Raw-ECAPs without artefact rejection were consecutively recorded for each stimulation condition from at least 8 intra-cochlear electrodes. Firstly, amplifier-saturated recordings were discarded, and the data from different stimulus conditions (different current-levels) were concatenated temporally. The key aspect of the automation procedure was the sequential deductive source categorisation after ICA was applied with a restriction to 4 sources. The stereotypical aspect of the 4 sources enables their automatic classification as two artefact components, a noise and the sought ECAP based on theoretical and empirical considerations. The automatic procedure was tested using 8 cochlear implant (CI) users and one to four stimulus electrodes. The artefact and noise sources were successively identified and discarded, leaving the ECAP as the remaining source. The automated ECAP-ICA procedure successfully extracted the correct ECAPs compared to standard clinical forward masking paradigm in 22 out of 26 cases. ECAP-ICA does not require extracting the ECAP from a combination of distinct buffers as it is the case with regular methods. It is an alternative that does not have the possible bias of traditional artefact rejections such as alternate-polarity or forward-masking paradigms. The ECAP-ICA procedure bears clinical relevance, for example as the artefact rejection sub-module of automated ECAP-threshold detection techniques, which are common features of CI clinical fitting software. Copyright © 2014. Published by Elsevier B.V.

  1. Applying Different Independent Component Analysis Algorithms and Support Vector Regression for IT Chain Store Sales Forecasting

    Science.gov (United States)

    Dai, Wensheng

    2014-01-01

    Sales forecasting is one of the most important issues in managing information technology (IT) chain store sales since an IT chain store has many branches. Integrating feature extraction method and prediction tool, such as support vector regression (SVR), is a useful method for constructing an effective sales forecasting scheme. Independent component analysis (ICA) is a novel feature extraction technique and has been widely applied to deal with various forecasting problems. But, up to now, only the basic ICA method (i.e., temporal ICA model) was applied to sale forecasting problem. In this paper, we utilize three different ICA methods including spatial ICA (sICA), temporal ICA (tICA), and spatiotemporal ICA (stICA) to extract features from the sales data and compare their performance in sales forecasting of IT chain store. Experimental results from a real sales data show that the sales forecasting scheme by integrating stICA and SVR outperforms the comparison models in terms of forecasting error. The stICA is a promising tool for extracting effective features from branch sales data and the extracted features can improve the prediction performance of SVR for sales forecasting. PMID:25165740

  2. Gas Bubbles Investigation in Contaminated Water Using Optical Tomography Based on Independent Component Analysis Method

    Directory of Open Access Journals (Sweden)

    Mohd Taufiq Mohd Khairi

    2016-01-01

    Full Text Available This paper presents the results of concentration profiles for gas bubble flow in a vertical pipeline containing contaminated water using an optical tomography system. The concentration profiles for the bubble flow quantities are investigated under five different flows conditions, a single bubble, double bubbles, 25% of air opening, 50% of air opening, and 100% of air opening flow rates where a valve is used to control the gas flow in the vertical pipeline. The system is aided by the independent component analysis (ICA algorithm to reconstruct the concentration profiles of the liquid-gas flow. The behaviour of the gas bubbles was investigated in contaminated water in which the water sample was prepared by adding 25 mL of colour ingredients to 3 liters of pure water. The result shows that the application of ICA has enabled the system to detect the presence of gas bubbles in contaminated water. This information provides vital information on the flow inside the pipe and hence could be very significant in increasing the efficiency of the process industries.

  3. Applying different independent component analysis algorithms and support vector regression for IT chain store sales forecasting.

    Science.gov (United States)

    Dai, Wensheng; Wu, Jui-Yu; Lu, Chi-Jie

    2014-01-01

    Sales forecasting is one of the most important issues in managing information technology (IT) chain store sales since an IT chain store has many branches. Integrating feature extraction method and prediction tool, such as support vector regression (SVR), is a useful method for constructing an effective sales forecasting scheme. Independent component analysis (ICA) is a novel feature extraction technique and has been widely applied to deal with various forecasting problems. But, up to now, only the basic ICA method (i.e., temporal ICA model) was applied to sale forecasting problem. In this paper, we utilize three different ICA methods including spatial ICA (sICA), temporal ICA (tICA), and spatiotemporal ICA (stICA) to extract features from the sales data and compare their performance in sales forecasting of IT chain store. Experimental results from a real sales data show that the sales forecasting scheme by integrating stICA and SVR outperforms the comparison models in terms of forecasting error. The stICA is a promising tool for extracting effective features from branch sales data and the extracted features can improve the prediction performance of SVR for sales forecasting.

  4. Attribution of emotions to body postures: an independent component analysis study of functional connectivity in autism.

    Science.gov (United States)

    Libero, Lauren E; Stevens, Carl E; Kana, Rajesh K

    2014-10-01

    The ability to interpret others' body language is a vital skill that helps us infer their thoughts and emotions. However, individuals with autism spectrum disorder (ASD) have been found to have difficulty in understanding the meaning of people's body language, perhaps leading to an overarching deficit in processing emotions. The current fMRI study investigates the functional connectivity underlying emotion and action judgment in the context of processing body language in high-functioning adolescents and young adults with autism, using an independent components analysis (ICA) of the fMRI time series. While there were no reliable group differences in brain activity, the ICA revealed significant involvement of occipital and parietal regions in processing body actions; and inferior frontal gyrus, superior medial prefrontal cortex, and occipital cortex in body expressions of emotions. In a between-group analysis, participants with autism, relative to typical controls, demonstrated significantly reduced temporal coherence in left ventral premotor cortex and right superior parietal lobule while processing emotions. Participants with ASD, on the other hand, showed increased temporal coherence in left fusiform gyrus while inferring emotions from body postures. Finally, a positive predictive relationship was found between empathizing ability and the brain areas underlying emotion processing in ASD participants. These results underscore the differential role of frontal and parietal brain regions in processing emotional body language in autism. Copyright © 2014 Wiley Periodicals, Inc.

  5. Quantifying biological samples using Linear Poisson Independent Component Analysis for MALDI-ToF mass spectra

    Science.gov (United States)

    Deepaisarn, S; Tar, P D; Thacker, N A; Seepujak, A; McMahon, A W

    2018-01-01

    Abstract Motivation Matrix-assisted laser desorption/ionisation time-of-flight mass spectrometry (MALDI) facilitates the analysis of large organic molecules. However, the complexity of biological samples and MALDI data acquisition leads to high levels of variation, making reliable quantification of samples difficult. We present a new analysis approach that we believe is well-suited to the properties of MALDI mass spectra, based upon an Independent Component Analysis derived for Poisson sampled data. Simple analyses have been limited to studying small numbers of mass peaks, via peak ratios, which is known to be inefficient. Conventional PCA and ICA methods have also been applied, which extract correlations between any number of peaks, but we argue makes inappropriate assumptions regarding data noise, i.e. uniform and Gaussian. Results We provide evidence that the Gaussian assumption is incorrect, motivating the need for our Poisson approach. The method is demonstrated by making proportion measurements from lipid-rich binary mixtures of lamb brain and liver, and also goat and cow milk. These allow our measurements and error predictions to be compared to ground truth. Availability and implementation Software is available via the open source image analysis system TINA Vision, www.tina-vision.net. Contact paul.tar@manchester.ac.uk Supplementary information Supplementary data are available at Bioinformatics online. PMID:29091994

  6. Attenuation of artifacts in EEG signals measured inside an MRI scanner using constrained independent component analysis

    International Nuclear Information System (INIS)

    Rasheed, Tahir; Lee, Young-Koo; Lee, Soo Yeol; Kim, Tae-Seong

    2009-01-01

    Integration of electroencephalography (EEG) and functional magnetic imaging (fMRI) resonance will allow analysis of the brain activities at superior temporal and spatial resolution. However simultaneous acquisition of EEG and fMRI is hindered by the enhancement of artifacts in EEG, the most prominent of which are ballistocardiogram (BCG) and electro-oculogram (EOG) artifacts. The situation gets even worse if the evoked potentials are measured inside MRI for their minute responses in comparison to the spontaneous brain responses. In this study, we propose a new method of attenuating these artifacts from the spontaneous and evoked EEG data acquired inside an MRI scanner using constrained independent component analysis with a priori information about the artifacts as constraints. With the proposed techniques of reference function generation for the BCG and EOG artifacts as constraints, our new approach performs significantly better than the averaged artifact subtraction (AAS) method. The proposed method could be an alternative to the conventional ICA method for artifact attenuation, with some advantages. As a performance measure we have achieved much improved normalized power spectrum ratios (INPS) for continuous EEG and correlation coefficient (cc) values with outside MRI visual evoked potentials for visual evoked EEG, as compared to those obtained with the AAS method. The results show that our new approach is more effective than the conventional methods, almost fully automatic, and no extra ECG signal measurements are involved

  7. Stealthy false data injection attacks using matrix recovery and independent component analysis in smart grid

    Science.gov (United States)

    JiWei, Tian; BuHong, Wang; FuTe, Shang; Shuaiqi, Liu

    2017-05-01

    Exact state estimation is vital important to maintain common operations of smart grids. Existing researches demonstrate that state estimation output could be compromised by malicious attacks. However, to construct the attack vectors, a usual presumption in most works is that the attacker has perfect information regarding the topology and so on even such information is difficult to acquire in practice. Recent research shows that Independent Component Analysis (ICA) can be used for inferring topology information which can be used to originate undetectable attacks and even to alter the price of electricity for the profits of attackers. However, we found that the above ICA-based blind attack tactics is merely feasible in the environment with Gaussian noises. If there are outliers (device malfunction and communication errors), the Bad Data Detector will easily detect the attack. Hence, we propose a robust ICA based blind attack strategy that one can use matrix recovery to circumvent the outlier problem and construct stealthy attack vectors. The proposed attack strategies are tested with IEEE representative 14-bus system. Simulations verify the feasibility of the proposed method.

  8. Bridge Diagnosis by Using Nonlinear Independent Component Analysis and Displacement Analysis

    Science.gov (United States)

    Zheng, Juanqing; Yeh, Yichun; Ogai, Harutoshi

    A daily diagnosis system for bridge monitoring and maintenance is developed based on wireless sensors, signal processing, structure analysis, and displacement analysis. The vibration acceleration data of a bridge are firstly collected through the wireless sensor network by exerting. Nonlinear independent component analysis (ICA) and spectral analysis are used to extract the vibration frequencies of the bridge. After that, through a band pass filter and Simpson's rule the vibration displacement is calculated and the vibration model is obtained to diagnose the bridge. Since linear ICA algorithms work efficiently only in linear mixing environments, a nonlinear ICA model, which is more complicated, is more practical for bridge diagnosis systems. In this paper, we firstly use the post nonlinear method to change the signal data, after that perform linear separation by FastICA, and calculate the vibration displacement of the bridge. The processed data can be used to understand phenomena like corrosion and crack, and evaluate the health condition of the bridge. We apply this system to Nakajima Bridge in Yahata, Kitakyushu, Japan.

  9. Latent physiological factors of complex human diseases revealed by independent component analysis of clinarrays

    Directory of Open Access Journals (Sweden)

    Chen David P

    2010-10-01

    Full Text Available Abstract Background Diagnosis and treatment of patients in the clinical setting is often driven by known symptomatic factors that distinguish one particular condition from another. Treatment based on noticeable symptoms, however, is limited to the types of clinical biomarkers collected, and is prone to overlooking dysfunctions in physiological factors not easily evident to medical practitioners. We used a vector-based representation of patient clinical biomarkers, or clinarrays, to search for latent physiological factors that underlie human diseases directly from clinical laboratory data. Knowledge of these factors could be used to improve assessment of disease severity and help to refine strategies for diagnosis and monitoring disease progression. Results Applying Independent Component Analysis on clinarrays built from patient laboratory measurements revealed both known and novel concomitant physiological factors for asthma, types 1 and 2 diabetes, cystic fibrosis, and Duchenne muscular dystrophy. Serum sodium was found to be the most significant factor for both type 1 and type 2 diabetes, and was also significant in asthma. TSH3, a measure of thyroid function, and blood urea nitrogen, indicative of kidney function, were factors unique to type 1 diabetes respective to type 2 diabetes. Platelet count was significant across all the diseases analyzed. Conclusions The results demonstrate that large-scale analyses of clinical biomarkers using unsupervised methods can offer novel insights into the pathophysiological basis of human disease, and suggest novel clinical utility of established laboratory measurements.

  10. Revealing spatio-spectral electroencephalographic dynamics of musical mode and tempo perception by independent component analysis.

    Science.gov (United States)

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

    2014-02-28

    Music conveys emotion by manipulating musical structures, particularly musical mode- and tempo-impact. The neural correlates of musical mode and tempo perception revealed by electroencephalography (EEG) have not been adequately addressed in the literature. This study used independent component analysis (ICA) to systematically assess spatio-spectral EEG dynamics associated with the changes of musical mode and tempo. Empirical results showed that music with major mode augmented delta-band activity over the right sensorimotor cortex, suppressed theta activity over the superior parietal cortex, and moderately suppressed beta activity over the medial frontal cortex, compared to minor-mode music, whereas fast-tempo music engaged significant alpha suppression over the right sensorimotor cortex. The resultant EEG brain sources were comparable with previous studies obtained by other neuroimaging modalities, such as functional magnetic resonance imaging (fMRI) and positron emission tomography (PET). In conjunction with advanced dry and mobile EEG technology, the EEG results might facilitate the translation from laboratory-oriented research to real-life applications for music therapy, training and entertainment in naturalistic environments.

  11. Applying Different Independent Component Analysis Algorithms and Support Vector Regression for IT Chain Store Sales Forecasting

    Directory of Open Access Journals (Sweden)

    Wensheng Dai

    2014-01-01

    Full Text Available Sales forecasting is one of the most important issues in managing information technology (IT chain store sales since an IT chain store has many branches. Integrating feature extraction method and prediction tool, such as support vector regression (SVR, is a useful method for constructing an effective sales forecasting scheme. Independent component analysis (ICA is a novel feature extraction technique and has been widely applied to deal with various forecasting problems. But, up to now, only the basic ICA method (i.e., temporal ICA model was applied to sale forecasting problem. In this paper, we utilize three different ICA methods including spatial ICA (sICA, temporal ICA (tICA, and spatiotemporal ICA (stICA to extract features from the sales data and compare their performance in sales forecasting of IT chain store. Experimental results from a real sales data show that the sales forecasting scheme by integrating stICA and SVR outperforms the comparison models in terms of forecasting error. The stICA is a promising tool for extracting effective features from branch sales data and the extracted features can improve the prediction performance of SVR for sales forecasting.

  12. Differential recruitment of theory of mind brain network across three tasks: An independent component analysis.

    Science.gov (United States)

    Thye, Melissa D; Ammons, Carla J; Murdaugh, Donna L; Kana, Rajesh K

    2018-07-16

    Social neuroscience research has focused on an identified network of brain regions primarily associated with processing Theory of Mind (ToM). However, ToM is a broad cognitive process, which encompasses several sub-processes, such as mental state detection and intentional attribution, and the connectivity of brain regions underlying the broader ToM network in response to paradigms assessing these sub-processes requires further characterization. Standard fMRI analyses which focus only on brain activity cannot capture information about ToM processing at a network level. An alternative method, independent component analysis (ICA), is a data-driven technique used to isolate intrinsic connectivity networks, and this approach provides insight into network-level regional recruitment. In this fMRI study, three complementary, but distinct ToM tasks assessing mental state detection (e.g. RMIE: Reading the Mind in the Eyes; RMIV: Reading the Mind in the Voice) and intentional attribution (Causality task) were each analyzed using ICA in order to separately characterize the recruitment and functional connectivity of core nodes in the ToM network in response to the sub-processes of ToM. Based on visual comparison of the derived networks for each task, the spatiotemporal network patterns were similar between the RMIE and RMIV tasks, which elicited mentalizing about the mental states of others, and these networks differed from the network derived for the Causality task, which elicited mentalizing about goal-directed actions. The medial prefrontal cortex, precuneus, and right inferior frontal gyrus were seen in the components with the highest correlation with the task condition for each of the tasks highlighting the role of these regions in general ToM processing. Using a data-driven approach, the current study captured the differences in task-related brain response to ToM in three distinct ToM paradigms. The findings of this study further elucidate the neural mechanisms associated

  13. Unsupervised neural spike sorting for high-density microelectrode arrays with convolutive independent component analysis.

    Science.gov (United States)

    Leibig, Christian; Wachtler, Thomas; Zeck, Günther

    2016-09-15

    Unsupervised identification of action potentials in multi-channel extracellular recordings, in particular from high-density microelectrode arrays with thousands of sensors, is an unresolved problem. While independent component analysis (ICA) achieves rapid unsupervised sorting, it ignores the convolutive structure of extracellular data, thus limiting the unmixing to a subset of neurons. Here we present a spike sorting algorithm based on convolutive ICA (cICA) to retrieve a larger number of accurately sorted neurons than with instantaneous ICA while accounting for signal overlaps. Spike sorting was applied to datasets with varying signal-to-noise ratios (SNR: 3-12) and 27% spike overlaps, sampled at either 11.5 or 23kHz on 4365 electrodes. We demonstrate how the instantaneity assumption in ICA-based algorithms has to be relaxed in order to improve the spike sorting performance for high-density microelectrode array recordings. Reformulating the convolutive mixture as an instantaneous mixture by modeling several delayed samples jointly is necessary to increase signal-to-noise ratio. Our results emphasize that different cICA algorithms are not equivalent. Spike sorting performance was assessed with ground-truth data generated from experimentally derived templates. The presented spike sorter was able to extract ≈90% of the true spike trains with an error rate below 2%. It was superior to two alternative (c)ICA methods (≈80% accurately sorted neurons) and comparable to a supervised sorting. Our new algorithm represents a fast solution to overcome the current bottleneck in spike sorting of large datasets generated by simultaneous recording with thousands of electrodes. Copyright © 2016 Elsevier B.V. All rights reserved.

  14. Rapid discrimination of plastic packaging materials using MIR spectroscopy coupled with independent components analysis (ICA).

    Science.gov (United States)

    Kassouf, Amine; Maalouly, Jacqueline; Rutledge, Douglas N; Chebib, Hanna; Ducruet, Violette

    2014-11-01

    Plastic packaging wastes increased considerably in recent decades, raising a major and serious public concern on political, economical and environmental levels. Dealing with this kind of problems is generally done by landfilling and energy recovery. However, these two methods are becoming more and more expensive, hazardous to the public health and the environment. Therefore, recycling is gaining worldwide consideration as a solution to decrease the growing volume of plastic packaging wastes and simultaneously reduce the consumption of oil required to produce virgin resin. Nevertheless, a major shortage is encountered in recycling which is related to the sorting of plastic wastes. In this paper, a feasibility study was performed in order to test the potential of an innovative approach combining mid infrared (MIR) spectroscopy with independent components analysis (ICA), as a simple and fast approach which could achieve high separation rates. This approach (MIR-ICA) gave 100% discrimination rates in the separation of all studied plastics: polyethylene terephthalate (PET), polyethylene (PE), polypropylene (PP), polystyrene (PS) and polylactide (PLA). In addition, some more specific discriminations were obtained separating plastic materials belonging to the same polymer family e.g. high density polyethylene (HDPE) from low density polyethylene (LDPE). High discrimination rates were obtained despite the heterogeneity among samples especially differences in colors, thicknesses and surface textures. The reproducibility of the proposed approach was also tested using two spectrometers with considerable differences in their sensitivities. Discrimination rates were not affected proving that the developed approach could be extrapolated to different spectrometers. MIR combined with ICA is a promising tool for plastic waste separation that can help improve performance in this field; however further technological improvements and developments are required before it can be applied

  15. Task-evoked brain functional magnetic susceptibility mapping by independent component analysis (χICA).

    Science.gov (United States)

    Chen, Zikuan; Calhoun, Vince D

    2016-03-01

    Conventionally, independent component analysis (ICA) is performed on an fMRI magnitude dataset to analyze brain functional mapping (AICA). By solving the inverse problem of fMRI, we can reconstruct the brain magnetic susceptibility (χ) functional states. Upon the reconstructed χ dataspace, we propose an ICA-based brain functional χ mapping method (χICA) to extract task-evoked brain functional map. A complex division algorithm is applied to a timeseries of fMRI phase images to extract temporal phase changes (relative to an OFF-state snapshot). A computed inverse MRI (CIMRI) model is used to reconstruct a 4D brain χ response dataset. χICA is implemented by applying a spatial InfoMax ICA algorithm to the reconstructed 4D χ dataspace. With finger-tapping experiments on a 7T system, the χICA-extracted χ-depicted functional map is similar to the SPM-inferred functional χ map by a spatial correlation of 0.67 ± 0.05. In comparison, the AICA-extracted magnitude-depicted map is correlated with the SPM magnitude map by 0.81 ± 0.05. The understanding of the inferiority of χICA to AICA for task-evoked functional map is an ongoing research topic. For task-evoked brain functional mapping, we compare the data-driven ICA method with the task-correlated SPM method. In particular, we compare χICA with AICA for extracting task-correlated timecourses and functional maps. χICA can extract a χ-depicted task-evoked brain functional map from a reconstructed χ dataspace without the knowledge about brain hemodynamic responses. The χICA-extracted brain functional χ map reveals a bidirectional BOLD response pattern that is unavailable (or different) from AICA. Copyright © 2016 Elsevier B.V. All rights reserved.

  16. Resting State EEG in Children With Learning Disabilities: An Independent Component Analysis Approach.

    Science.gov (United States)

    Jäncke, Lutz; Alahmadi, Nsreen

    2016-01-01

    In this study, the neurophysiological underpinnings of learning disabilities (LD) in children are examined using resting state EEG. We were particularly interested in the neurophysiological differences between children with learning disabilities not otherwise specified (LD-NOS), learning disabilities with verbal disabilities (LD-Verbal), and healthy control (HC) children. We applied 2 different approaches to examine the differences between the different groups. First, we calculated theta/beta and theta/alpha ratios in order to quantify the relationship between slow and fast EEG oscillations. Second, we used a recently developed method for analyzing spectral EEG, namely the group independent component analysis (gICA) model. Using these measures, we identified substantial differences between LD and HC children and between LD-NOS and LD-Verbal children in terms of their spectral EEG profiles. We obtained the following findings: (a) theta/beta and theta/alpha ratios were substantially larger in LD than in HC children, with no difference between LD-NOS and LD-Verbal children; (b) there was substantial slowing of EEG oscillations, especially for gICs located in frontal scalp positions, with LD-NOS children demonstrating the strongest slowing; (c) the estimated intracortical sources of these gICs were mostly located in brain areas involved in the control of executive functions, attention, planning, and language; and (d) the LD-Verbal children demonstrated substantial differences in EEG oscillations compared with LD-NOS children, and these differences were localized in language-related brain areas. The general pattern of atypical neurophysiological activation found in LD children suggests that they suffer from neurophysiological dysfunction in brain areas involved with the control of attention, executive functions, planning, and language functions. LD-Verbal children also demonstrate atypical activation, especially in language-related brain areas. These atypical

  17. Phylogeographic and population genetic analyses reveal multiple species of Boa and independent origins of insular dwarfism.

    Science.gov (United States)

    Card, Daren C; Schield, Drew R; Adams, Richard H; Corbin, Andrew B; Perry, Blair W; Andrew, Audra L; Pasquesi, Giulia I M; Smith, Eric N; Jezkova, Tereza; Boback, Scott M; Booth, Warren; Castoe, Todd A

    2016-09-01

    Boa is a Neotropical genus of snakes historically recognized as monotypic despite its expansive distribution. The distinct morphological traits and color patterns exhibited by these snakes, together with the wide diversity of ecosystems they inhabit, collectively suggest that the genus may represent multiple species. Morphological variation within Boa also includes instances of dwarfism observed in multiple offshore island populations. Despite this substantial diversity, the systematics of the genus Boa has received little attention until very recently. In this study we examined the genetic structure and phylogenetic relationships of Boa populations using mitochondrial sequences and genome-wide SNP data obtained from RADseq. We analyzed these data at multiple geographic scales using a combination of phylogenetic inference (including coalescent-based species delimitation) and population genetic analyses. We identified extensive population structure across the range of the genus Boa and multiple lines of evidence for three widely-distributed clades roughly corresponding with the three primary land masses of the Western Hemisphere. We also find both mitochondrial and nuclear support for independent origins and parallel evolution of dwarfism on offshore island clusters in Belize and Cayos Cochinos Menor, Honduras. Copyright © 2016 Elsevier Inc. All rights reserved.

  18. Evidence for Multiple Mediator Complexes in Yeast Independently Recruited by Activated Heat Shock Factor.

    Science.gov (United States)

    Anandhakumar, Jayamani; Moustafa, Yara W; Chowdhary, Surabhi; Kainth, Amoldeep S; Gross, David S

    2016-07-15

    Mediator is an evolutionarily conserved coactivator complex essential for RNA polymerase II transcription. Although it has been generally assumed that in Saccharomyces cerevisiae, Mediator is a stable trimodular complex, its structural state in vivo remains unclear. Using the "anchor away" (AA) technique to conditionally deplete select subunits within Mediator and its reversibly associated Cdk8 kinase module (CKM), we provide evidence that Mediator's tail module is highly dynamic and that a subcomplex consisting of Med2, Med3, and Med15 can be independently recruited to the regulatory regions of heat shock factor 1 (Hsf1)-activated genes. Fluorescence microscopy of a scaffold subunit (Med14)-anchored strain confirmed parallel cytoplasmic sequestration of core subunits located outside the tail triad. In addition, and contrary to current models, we provide evidence that Hsf1 can recruit the CKM independently of core Mediator and that core Mediator has a role in regulating postinitiation events. Collectively, our results suggest that yeast Mediator is not monolithic but potentially has a dynamic complexity heretofore unappreciated. Multiple species, including CKM-Mediator, the 21-subunit core complex, the Med2-Med3-Med15 tail triad, and the four-subunit CKM, can be independently recruited by activated Hsf1 to its target genes in AA strains. Copyright © 2016, American Society for Microbiology. All Rights Reserved.

  19. Extracting intrinsic functional networks with feature-based group independent component analysis.

    Science.gov (United States)

    Calhoun, Vince D; Allen, Elena

    2013-04-01

    There is increasing use of functional imaging data to understand the macro-connectome of the human brain. Of particular interest is the structure and function of intrinsic networks (regions exhibiting temporally coherent activity both at rest and while a task is being performed), which account for a significant portion of the variance in functional MRI data. While networks are typically estimated based on the temporal similarity between regions (based on temporal correlation, clustering methods, or independent component analysis [ICA]), some recent work has suggested that these intrinsic networks can be extracted from the inter-subject covariation among highly distilled features, such as amplitude maps reflecting regions modulated by a task or even coordinates extracted from large meta analytic studies. In this paper our goal was to explicitly compare the networks obtained from a first-level ICA (ICA on the spatio-temporal functional magnetic resonance imaging (fMRI) data) to those from a second-level ICA (i.e., ICA on computed features rather than on the first-level fMRI data). Convergent results from simulations, task-fMRI data, and rest-fMRI data show that the second-level analysis is slightly noisier than the first-level analysis but yields strikingly similar patterns of intrinsic networks (spatial correlations as high as 0.85 for task data and 0.65 for rest data, well above the empirical null) and also preserves the relationship of these networks with other variables such as age (for example, default mode network regions tended to show decreased low frequency power for first-level analyses and decreased loading parameters for second-level analyses). In addition, the best-estimated second-level results are those which are the most strongly reflected in the input feature. In summary, the use of feature-based ICA appears to be a valid tool for extracting intrinsic networks. We believe it will become a useful and important approach in the study of the macro

  20. Rapid discrimination of plastic packaging materials using MIR spectroscopy coupled with independent components analysis (ICA)

    Energy Technology Data Exchange (ETDEWEB)

    Kassouf, Amine, E-mail: amine.kassouf@agroparistech.fr [ER004 “Lebanese Food Packaging”, Faculty of Sciences II, Lebanese University, 90656 Jdeideth El Matn, Fanar (Lebanon); INRA, UMR1145 Ingénierie Procédés Aliments, 1 Avenue des Olympiades, 91300 Massy (France); AgroParisTech, UMR1145 Ingénierie Procédés Aliments, 16 rue Claude Bernard, 75005 Paris (France); Maalouly, Jacqueline, E-mail: j_maalouly@hotmail.com [ER004 “Lebanese Food Packaging”, Faculty of Sciences II, Lebanese University, 90656 Jdeideth El Matn, Fanar (Lebanon); Rutledge, Douglas N., E-mail: douglas.rutledge@agroparistech.fr [INRA, UMR1145 Ingénierie Procédés Aliments, 1 Avenue des Olympiades, 91300 Massy (France); AgroParisTech, UMR1145 Ingénierie Procédés Aliments, 16 rue Claude Bernard, 75005 Paris (France); Chebib, Hanna, E-mail: hchebib@hotmail.com [ER004 “Lebanese Food Packaging”, Faculty of Sciences II, Lebanese University, 90656 Jdeideth El Matn, Fanar (Lebanon); Ducruet, Violette, E-mail: violette.ducruet@agroparistech.fr [INRA, UMR1145 Ingénierie Procédés Aliments, 1 Avenue des Olympiades, 91300 Massy (France); AgroParisTech, UMR1145 Ingénierie Procédés Aliments, 16 rue Claude Bernard, 75005 Paris (France)

    2014-11-15

    Highlights: • An innovative technique, MIR-ICA, was applied to plastic packaging separation. • This study was carried out on PE, PP, PS, PET and PLA plastic packaging materials. • ICA was applied to discriminate plastics and 100% separation rates were obtained. • Analyses performed on two spectrometers proved the reproducibility of the method. • MIR-ICA is a simple and fast technique allowing plastic identification/classification. - Abstract: Plastic packaging wastes increased considerably in recent decades, raising a major and serious public concern on political, economical and environmental levels. Dealing with this kind of problems is generally done by landfilling and energy recovery. However, these two methods are becoming more and more expensive, hazardous to the public health and the environment. Therefore, recycling is gaining worldwide consideration as a solution to decrease the growing volume of plastic packaging wastes and simultaneously reduce the consumption of oil required to produce virgin resin. Nevertheless, a major shortage is encountered in recycling which is related to the sorting of plastic wastes. In this paper, a feasibility study was performed in order to test the potential of an innovative approach combining mid infrared (MIR) spectroscopy with independent components analysis (ICA), as a simple and fast approach which could achieve high separation rates. This approach (MIR-ICA) gave 100% discrimination rates in the separation of all studied plastics: polyethylene terephthalate (PET), polyethylene (PE), polypropylene (PP), polystyrene (PS) and polylactide (PLA). In addition, some more specific discriminations were obtained separating plastic materials belonging to the same polymer family e.g. high density polyethylene (HDPE) from low density polyethylene (LDPE). High discrimination rates were obtained despite the heterogeneity among samples especially differences in colors, thicknesses and surface textures. The reproducibility of

  1. Rapid discrimination of plastic packaging materials using MIR spectroscopy coupled with independent components analysis (ICA)

    International Nuclear Information System (INIS)

    Kassouf, Amine; Maalouly, Jacqueline; Rutledge, Douglas N.; Chebib, Hanna; Ducruet, Violette

    2014-01-01

    Highlights: • An innovative technique, MIR-ICA, was applied to plastic packaging separation. • This study was carried out on PE, PP, PS, PET and PLA plastic packaging materials. • ICA was applied to discriminate plastics and 100% separation rates were obtained. • Analyses performed on two spectrometers proved the reproducibility of the method. • MIR-ICA is a simple and fast technique allowing plastic identification/classification. - Abstract: Plastic packaging wastes increased considerably in recent decades, raising a major and serious public concern on political, economical and environmental levels. Dealing with this kind of problems is generally done by landfilling and energy recovery. However, these two methods are becoming more and more expensive, hazardous to the public health and the environment. Therefore, recycling is gaining worldwide consideration as a solution to decrease the growing volume of plastic packaging wastes and simultaneously reduce the consumption of oil required to produce virgin resin. Nevertheless, a major shortage is encountered in recycling which is related to the sorting of plastic wastes. In this paper, a feasibility study was performed in order to test the potential of an innovative approach combining mid infrared (MIR) spectroscopy with independent components analysis (ICA), as a simple and fast approach which could achieve high separation rates. This approach (MIR-ICA) gave 100% discrimination rates in the separation of all studied plastics: polyethylene terephthalate (PET), polyethylene (PE), polypropylene (PP), polystyrene (PS) and polylactide (PLA). In addition, some more specific discriminations were obtained separating plastic materials belonging to the same polymer family e.g. high density polyethylene (HDPE) from low density polyethylene (LDPE). High discrimination rates were obtained despite the heterogeneity among samples especially differences in colors, thicknesses and surface textures. The reproducibility of

  2. On an efficient modification of singular value decomposition using independent component analysis for improved MRS denoising and quantification

    International Nuclear Information System (INIS)

    Stamatopoulos, V G; Karras, D A; Mertzios, B G

    2009-01-01

    An efficient modification of singular value decomposition (SVD) is proposed in this paper aiming at denoising and more importantly at quantifying more accurately the statistically independent spectra of metabolite sources in magnetic resonance spectroscopy (MRS). Although SVD is known in MRS applications and several efficient algorithms exist for estimating SVD summation terms in which the raw MRS data are analyzed, however, it would be more beneficial for such an analysis if techniques with the ability to estimate statistically independent spectra could be employed. SVD is known to separate signal and noise subspaces but it assumes orthogonal properties for the components comprising signal subspace, which is not always the case, and might impose heavy constraints for the MRS case. A much more relaxing constraint would be to assume statistically independent components. Therefore, a modification of the main methodology incorporating techniques for calculating the assumed statistically independent spectra is proposed by applying SVD on the MRS spectrogram through application of the short time Fourier transform (STFT). This approach is based on combining SVD on STFT spectrogram followed by an iterative application of independent component analysis (ICA). Moreover, it is shown that the proposed methodology combined with a regression analysis would lead to improved quantification of the MRS signals. An experimental study based on synthetic MRS signals has been conducted to evaluate the herein proposed methodologies. The results obtained have been discussed and it is shown to be quite promising

  3. A comparative and combined study of EMIS and GPR detectors by the use of Independent Component Analysis

    DEFF Research Database (Denmark)

    Morgenstjerne, Axel; Karlsen, Brian; Larsen, Jan

    2005-01-01

    Independent Component Analysis (ICA) is applied to classify unexploded ordnance (UXO) on laboratory UXO test-field data, acquired by stand-off detection. The data are acquired by an Electromagnetic Induction Spectroscopy (EMIS) metal detector and a ground penetrating radar (GPR) detector. The metal...

  4. Recent progresses of neural network unsupervised learning: I. Independent component analyses generalizing PCA

    Science.gov (United States)

    Szu, Harold H.

    1999-03-01

    The early vision principle of redundancy reduction of 108 sensor excitations is understandable from computer vision viewpoint toward sparse edge maps. It is only recently derived using a truly unsupervised learning paradigm of artificial neural networks (ANN). In fact, the biological vision, Hubel- Wiesel edge maps, is reproduced seeking the underlying independent components analyses (ICA) among 102 image samples by maximizing the ANN output entropy (partial)H(V)/(partial)[W] equals (partial)[W]/(partial)t. When a pair of newborn eyes or ears meet the bustling and hustling world without supervision, they seek ICA by comparing 2 sensory measurements (x1(t), x2(t))T equalsV X(t). Assuming a linear and instantaneous mixture model of the external world X(t) equals [A] S(t), where both the mixing matrix ([A] equalsV [a1, a2] of ICA vectors and the source percentages (s1(t), s2(t))T equalsV S(t) are unknown, we seek the independent sources approximately equals [I] where the approximated sign indicates that higher order statistics (HOS) may not be trivial. Without a teacher, the ANN weight matrix [W] equalsV [w1, w2] adjusts the outputs V(t) equals tanh([W]X(t)) approximately equals [W]X(t) until no desired outputs except the (Gaussian) 'garbage' (neither YES '1' nor NO '-1' but at linear may-be range 'origin 0') defined by Gaussian covariance G equals [I] equals [W][A] the internal knowledge representation [W], as the inverse of the external world matrix [A]-1. To unify IC, PCA, ANN & HOS theories since 1991 (advanced by Jutten & Herault, Comon, Oja, Bell-Sejnowski, Amari-Cichocki, Cardoso), the LYAPONOV function L(v1,...,vn, w1,...wn,) equals E(v1,...,vn) - H(w1,...wn) is constructed as the HELMHOTZ free energy to prove both convergences of supervised energy E and unsupervised entropy H learning. Consequently, rather using the faithful but dumb computer: 'GARBAGE-IN, GARBAGE-OUT,' the smarter neurocomputer will be equipped with an unsupervised learning that extracts

  5. The SPAtial EFficiency metric (SPAEF): multiple-component evaluation of spatial patterns for optimization of hydrological models

    Science.gov (United States)

    Koch, Julian; Cüneyd Demirel, Mehmet; Stisen, Simon

    2018-05-01

    The process of model evaluation is not only an integral part of model development and calibration but also of paramount importance when communicating modelling results to the scientific community and stakeholders. The modelling community has a large and well-tested toolbox of metrics to evaluate temporal model performance. In contrast, spatial performance evaluation does not correspond to the grand availability of spatial observations readily available and to the sophisticate model codes simulating the spatial variability of complex hydrological processes. This study makes a contribution towards advancing spatial-pattern-oriented model calibration by rigorously testing a multiple-component performance metric. The promoted SPAtial EFficiency (SPAEF) metric reflects three equally weighted components: correlation, coefficient of variation and histogram overlap. This multiple-component approach is found to be advantageous in order to achieve the complex task of comparing spatial patterns. SPAEF, its three components individually and two alternative spatial performance metrics, i.e. connectivity analysis and fractions skill score, are applied in a spatial-pattern-oriented model calibration of a catchment model in Denmark. Results suggest the importance of multiple-component metrics because stand-alone metrics tend to fail to provide holistic pattern information. The three SPAEF components are found to be independent, which allows them to complement each other in a meaningful way. In order to optimally exploit spatial observations made available by remote sensing platforms, this study suggests applying bias insensitive metrics which further allow for a comparison of variables which are related but may differ in unit. This study applies SPAEF in the hydrological context using the mesoscale Hydrologic Model (mHM; version 5.8), but we see great potential across disciplines related to spatially distributed earth system modelling.

  6. Combining multiple regression and principal component analysis for accurate predictions for column ozone in Peninsular Malaysia

    Science.gov (United States)

    Rajab, Jasim M.; MatJafri, M. Z.; Lim, H. S.

    2013-06-01

    This study encompasses columnar ozone modelling in the peninsular Malaysia. Data of eight atmospheric parameters [air surface temperature (AST), carbon monoxide (CO), methane (CH4), water vapour (H2Ovapour), skin surface temperature (SSKT), atmosphere temperature (AT), relative humidity (RH), and mean surface pressure (MSP)] data set, retrieved from NASA's Atmospheric Infrared Sounder (AIRS), for the entire period (2003-2008) was employed to develop models to predict the value of columnar ozone (O3) in study area. The combined method, which is based on using both multiple regressions combined with principal component analysis (PCA) modelling, was used to predict columnar ozone. This combined approach was utilized to improve the prediction accuracy of columnar ozone. Separate analysis was carried out for north east monsoon (NEM) and south west monsoon (SWM) seasons. The O3 was negatively correlated with CH4, H2Ovapour, RH, and MSP, whereas it was positively correlated with CO, AST, SSKT, and AT during both the NEM and SWM season periods. Multiple regression analysis was used to fit the columnar ozone data using the atmospheric parameter's variables as predictors. A variable selection method based on high loading of varimax rotated principal components was used to acquire subsets of the predictor variables to be comprised in the linear regression model of the atmospheric parameter's variables. It was found that the increase in columnar O3 value is associated with an increase in the values of AST, SSKT, AT, and CO and with a drop in the levels of CH4, H2Ovapour, RH, and MSP. The result of fitting the best models for the columnar O3 value using eight of the independent variables gave about the same values of the R (≈0.93) and R2 (≈0.86) for both the NEM and SWM seasons. The common variables that appeared in both regression equations were SSKT, CH4 and RH, and the principal precursor of the columnar O3 value in both the NEM and SWM seasons was SSKT.

  7. Application and Evaluation of Independent Component Analysis Methods to Generalized Seizure Disorder Activities Exhibited in the Brain.

    Science.gov (United States)

    George, S Thomas; Balakrishnan, R; Johnson, J Stanly; Jayakumar, J

    2017-07-01

    EEG records the spontaneous electrical activity of the brain using multiple electrodes placed on the scalp, and it provides a wealth of information related to the functions of brain. Nevertheless, the signals from the electrodes cannot be directly applied to a diagnostic tool like brain mapping as they undergo a "mixing" process because of the volume conduction effect in the scalp. A pervasive problem in neuroscience is determining which regions of the brain are active, given voltage measurements at the scalp. Because of which, there has been a surge of interest among the biosignal processing community to investigate the process of mixing and unmixing to identify the underlying active sources. According to the assumptions of independent component analysis (ICA) algorithms, the resultant mixture obtained from the scalp can be closely approximated by a linear combination of the "actual" EEG signals emanating from the underlying sources of electrical activity in the brain. As a consequence, using these well-known ICA techniques in preprocessing of the EEG signals prior to clinical applications could result in development of diagnostic tool like quantitative EEG which in turn can assist the neurologists to gain noninvasive access to patient-specific cortical activity, which helps in treating neuropathologies like seizure disorders. The popular and proven ICA schemes mentioned in various literature and applications were selected (which includes Infomax, JADE, and SOBI) and applied on generalized seizure disorder samples using EEGLAB toolbox in MATLAB environment to see their usefulness in source separations; and they were validated by the expert neurologist for clinical relevance in terms of pathologies on brain functionalities. The performance of Infomax method was found to be superior when compared with other ICA schemes applied on EEG and it has been established based on the validations carried by expert neurologist for generalized seizure and its clinical

  8. Resting State Functional Connectivity in Mild Traumatic Brain Injury at the Acute Stage: Independent Component and Seed-Based Analyses

    Science.gov (United States)

    Iraji, Armin; Benson, Randall R.; Welch, Robert D.; O'Neil, Brian J.; Woodard, John L.; Imran Ayaz, Syed; Kulek, Andrew; Mika, Valerie; Medado, Patrick; Soltanian-Zadeh, Hamid; Liu, Tianming; Haacke, E. Mark

    2015-01-01

    Abstract Mild traumatic brain injury (mTBI) accounts for more than 1 million emergency visits each year. Most of the injured stay in the emergency department for a few hours and are discharged home without a specific follow-up plan because of their negative clinical structural imaging. Advanced magnetic resonance imaging (MRI), particularly functional MRI (fMRI), has been reported as being sensitive to functional disturbances after brain injury. In this study, a cohort of 12 patients with mTBI were prospectively recruited from the emergency department of our local Level-1 trauma center for an advanced MRI scan at the acute stage. Sixteen age- and sex-matched controls were also recruited for comparison. Both group-based and individual-based independent component analysis of resting-state fMRI (rsfMRI) demonstrated reduced functional connectivity in both posterior cingulate cortex (PCC) and precuneus regions in comparison with controls, which is part of the default mode network (DMN). Further seed-based analysis confirmed reduced functional connectivity in these two regions and also demonstrated increased connectivity between these regions and other regions of the brain in mTBI. Seed-based analysis using the thalamus, hippocampus, and amygdala regions further demonstrated increased functional connectivity between these regions and other regions of the brain, particularly in the frontal lobe, in mTBI. Our data demonstrate alterations of multiple brain networks at the resting state, particularly increased functional connectivity in the frontal lobe, in response to brain concussion at the acute stage. Resting-state functional connectivity of the DMN could serve as a potential biomarker for improved detection of mTBI in the acute setting. PMID:25285363

  9. A New Generalized Two-Stage Direct Power Conversion Topology to Independently Supply Multiple AC Loads from Multiple Power Grids with Adjustable Power Loading

    DEFF Research Database (Denmark)

    Klumpner, Christian; Blaabjerg, Frede

    2004-01-01

    ) and continuously adjust these power fractions will become a desired feature. This paper presents a generalized Direct Power Converter topology, which is able to connect to multiple AC supplies proving complete decoupling and no circulating power between the input ports and to independently control multiple AC...

  10. Independent component analysis of normal and abnormal rhythm in twin pregnancies

    International Nuclear Information System (INIS)

    Mensah-Brown, Nana Aba; Lutter, William J; Wakai, Ronald T; Comani, Silvia; Strasburger, Janette F

    2011-01-01

    We investigated the utility of ICA for evaluation of fetal rhythm in five uncomplicated twin pregnancies and in five twin pregnancies complicated by fetal arrhythmia. Using objective and subjective criteria, we sought to determine how the signal-to-noise ratio, signal fidelity and interference rejection are affected when synthesizing the fetal signal using all the signal-containing ICA components (rank-p ICA) versus using the single dominant component (rank-1 ICA). The signal of each fetus was most commonly distributed over 1 or 2 ICA components, as previously observed in studies of singleton pregnancies; however, in 8 of 26 (31%) cases the signal of each fetus was distributed over 3, 4 or even 5 ICA components. Rank-1 ICA provided the highest SNR and interference rejection, but at the cost of reduced signal fidelity. Our results corroborate that in twin pregnancies, including twin pregnancies complicated by fetal arrhythmia, rank-1 ICA is very effective in isolating the QRS complexes of each fetus; however, it has some limitations when used for fetal rhythm evaluation due to signal distortion. Occasionally, rank-1 ICA completely separates the P-wave and the T-wave from the QRS complex, thus requiring the mixing of several ICA components to achieve acceptable signal fidelity

  11. Biclustered Independent Component Analysis for Complex Biomarker and Subtype Identification from Structural Magnetic Resonance Images in Schizophrenia

    Directory of Open Access Journals (Sweden)

    Cota Navin Gupta

    2017-09-01

    Full Text Available Clinical and cognitive symptoms domain-based subtyping in schizophrenia (Sz has been critiqued due to the lack of neurobiological correlates and heterogeneity in symptom scores. We, therefore, present a novel data-driven framework using biclustered independent component analysis to detect subtypes from the reliable and stable gray matter concentration (GMC of patients with Sz. The developed methodology consists of the following steps: source-based morphometry (SBM decomposition, selection and sorting of two component loadings, subtype component reconstruction using group information-guided ICA (GIG-ICA. This framework was applied to the top two group discriminative components namely the insula/superior temporal gyrus/inferior frontal gyrus (I-STG-IFG component and the superior frontal gyrus/middle frontal gyrus/medial frontal gyrus (SFG-MiFG-MFG component from our previous SBM study, which showed diagnostic group difference and had the highest effect sizes. The aggregated multisite dataset consisted of 382 patients with Sz regressed of age, gender, and site voxelwise. We observed two subtypes (i.e., two different subsets of subjects each heavily weighted on these two components, respectively. These subsets of subjects were characterized by significant differences in positive and negative syndrome scale (PANSS positive clinical symptoms (p = 0.005. We also observed an overlapping subtype weighing heavily on both of these components. The PANSS general clinical symptom of this subtype was trend level correlated with the loading coefficients of the SFG-MiFG-MFG component (r = 0.25; p = 0.07. The reconstructed subtype-specific component using GIG-ICA showed variations in voxel regions, when compared to the group component. We observed deviations from mean GMC along with conjunction of features from two components characterizing each deciphered subtype. These inherent variations in GMC among patients with Sz could possibly indicate the

  12. COMPARING INDEPENDENT COMPONENT ANALYSIS WITH PRINCIPLE COMPONENT ANALYSIS IN DETECTING ALTERATIONS OF PORPHYRY COPPER DEPOSIT (CASE STUDY: ARDESTAN AREA, CENTRAL IRAN

    Directory of Open Access Journals (Sweden)

    S. Mahmoudishadi

    2017-09-01

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

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

    Science.gov (United States)

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

    2017-09-01

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

  14. Color, Scale, and Rotation Independent Multiple License Plates Detection in Videos and Still Images

    Directory of Open Access Journals (Sweden)

    Narasimha Reddy Soora

    2016-01-01

    Full Text Available Most of the existing license plate (LP detection systems have shown significant development in the processing of the images, with restrictions related to environmental conditions and plate variations. With increased mobility and internationalization, there is a need to develop a universal LP detection system, which can handle multiple LPs of many countries and any vehicle, in an open environment and all weather conditions, having different plate variations. This paper presents a novel LP detection method using different clustering techniques based on geometrical properties of the LP characters and proposed a new character extraction method, for noisy/missed character components of the LP due to the presence of noise between LP characters and LP border. The proposed method detects multiple LPs from an input image or video, having different plate variations, under different environmental and weather conditions because of the geometrical properties of the set of characters in the LP. The proposed method is tested using standard media-lab and Application Oriented License Plate (AOLP benchmark LP recognition databases and achieved the success rates of 97.3% and 93.7%, respectively. Results clearly indicate that the proposed approach is comparable to the previously published papers, which evaluated their performance on publicly available benchmark LP databases.

  15. Gauge origin independent calculations of molecular magnetisabilities in relativistic four-component theory

    DEFF Research Database (Denmark)

    Iliaš, M.; Jensen, Hans Jørgen Aagaard; Bast, R.

    2013-01-01

    of the four-component relativistic linear response method at the self-consistent field single reference level. Benefits of employing the London atomic orbitals in relativistic calculations are illustrated with Hartree-Fock wave functions on the XF3 (X = N, P, As, Sb, Bi) series of molecules. Significantly...

  16. A Layered Searchable Encryption Scheme with Functional Components Independent of Encryption Methods

    Science.gov (United States)

    Luo, Guangchun; Qin, Ke

    2014-01-01

    Searchable encryption technique enables the users to securely store and search their documents over the remote semitrusted server, which is especially suitable for protecting sensitive data in the cloud. However, various settings (based on symmetric or asymmetric encryption) and functionalities (ranked keyword query, range query, phrase query, etc.) are often realized by different methods with different searchable structures that are generally not compatible with each other, which limits the scope of application and hinders the functional extensions. We prove that asymmetric searchable structure could be converted to symmetric structure, and functions could be modeled separately apart from the core searchable structure. Based on this observation, we propose a layered searchable encryption (LSE) scheme, which provides compatibility, flexibility, and security for various settings and functionalities. In this scheme, the outputs of the core searchable component based on either symmetric or asymmetric setting are converted to some uniform mappings, which are then transmitted to loosely coupled functional components to further filter the results. In such a way, all functional components could directly support both symmetric and asymmetric settings. Based on LSE, we propose two representative and novel constructions for ranked keyword query (previously only available in symmetric scheme) and range query (previously only available in asymmetric scheme). PMID:24719565

  17. A short study to assess the potential of independent component analysis for motion artifact separation in wearable pulse oximeter signals.

    Science.gov (United States)

    Yao, Jianchu; Warren, Steve

    2005-01-01

    Motion artifact reduction and separation become critical when medical sensors are used in wearable monitoring scenarios. Previous research has demonstrated that independent component analysis (ICA) can be applied to pulse oximeter signals to separate photoplethysmographic (PPG) data from motion artifacts, ambient light, and other interference in low-motion environments. However, ICA assumes that all source signal component pairs are mutually independent. It is important to assess the statistical independence of the source components in PPG data, especially if ICA is to be applied in ambulatory monitoring environments, where motion artifacts can have a substantial effect on the quality of data received from light-based sensors. This paper addresses the statistical relationship between motion artifacts and PPG data by calculating the correlation coefficients between arterial volume variations and motion over a range of stationary to high-motion conditions. Analyses indicate that motion significantly affects arterial flow, so care must be taken when applying ICA to light-based sensor data acquired from wearable platforms.

  18. Proton pump inhibitors induce a caspase-independent antitumor effect against human multiple myeloma.

    Science.gov (United States)

    Canitano, Andrea; Iessi, Elisabetta; Spugnini, Enrico Pierluigi; Federici, Cristina; Fais, Stefano

    2016-07-01

    Multiple Myeloma (MM) is the second most common hematological malignancy and is responsive to a limited number of drugs. Unfortunately, to date, despite the introduction of novel drugs, no relevant increase in survival rates has been obtained. Proton pump inhibitors (PPIs) have been shown to have significant antitumor action as single agents as well as in combination with chemotherapy. This study investigates the potential anti-tumor effectiveness of two PPIs, Lansoprazole and Omeprazole, against human MM cells. We found that Lansoprazole exerts straightforward efficacy against myeloma cells, even at suboptimal concentrations (50 µM), while Omeprazole has limited cytotoxic action. The Lansoprazole anti-MM effect was mostly mediated by a caspase-independent apoptotic-like cytotoxicity, with only a secondary anti-proliferative action. This study provides clear evidence supporting the use of Lansoprazole in the strive against MM with an efficacy proven much higher than current therapeutical approaches and without reported side effects. It is however conceivable that, consistent with the results obtained in other human tumors, Lansoprazole may well be combined with existing anti-myeloma therapies with the aim to improve the low level of efficacy of the current strategies. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

  19. Consensus of multiple autonomous underwater vehicles with double independent Markovian switching topologies and timevarying delays

    International Nuclear Information System (INIS)

    Yan Zhe-Ping; Liu Yi-Bo; Zhou Jia-Jia; Zhang Wei; Wang Lu

    2017-01-01

    A new method in which the consensus algorithm is used to solve the coordinate control problems of leaderless multiple autonomous underwater vehicles (multi-AUVs) with double independent Markovian switching communication topologies and time-varying delays among the underwater sensors is investigated. This is accomplished by first dividing the communication topology into two different switching parts, i.e., velocity and position, to reduce the data capacity per data package sent between the multi-AUVs in the ocean. Then, the state feedback linearization is used to simplify and rewrite the complex nonlinear and coupled mathematical model of the AUVs into a double-integrator dynamic model. Consequently, coordinate control of the multi-AUVs is regarded as an approximating consensus problem with various time-varying delays and velocity and position topologies. Considering these factors, sufficient conditions of consensus control are proposed and analyzed and the stability of the multi-AUVs is proven by Lyapunov–Krasovskii theorem. Finally, simulation results that validate the theoretical results are presented. (paper)

  20. Two Independent Mushroom Body Output Circuits Retrieve the Six Discrete Components of Drosophila Aversive Memory

    Directory of Open Access Journals (Sweden)

    Emna Bouzaiane

    2015-05-01

    Full Text Available Understanding how the various memory components are encoded and how they interact to guide behavior requires knowledge of the underlying neural circuits. Currently, aversive olfactory memory in Drosophila is behaviorally subdivided into four discrete phases. Among these, short- and long-term memories rely, respectively, on the γ and α/β Kenyon cells (KCs, two distinct subsets of the ∼2,000 neurons in the mushroom body (MB. Whereas V2 efferent neurons retrieve memory from α/β KCs, the neurons that retrieve short-term memory are unknown. We identified a specific pair of MB efferent neurons, named M6, that retrieve memory from γ KCs. Moreover, our network analysis revealed that six discrete memory phases actually exist, three of which have been conflated in the past. At each time point, two distinct memory components separately recruit either V2 or M6 output pathways. Memory retrieval thus features a dramatic convergence from KCs to MB efferent neurons.

  1. Developing a complex independent component analysis technique to extract non-stationary patterns from geophysical time-series

    Science.gov (United States)

    Forootan, Ehsan; Kusche, Jürgen

    2016-04-01

    Geodetic/geophysical observations, such as the time series of global terrestrial water storage change or sea level and temperature change, represent samples of physical processes and therefore contain information about complex physical interactionswith many inherent time scales. Extracting relevant information from these samples, for example quantifying the seasonality of a physical process or its variability due to large-scale ocean-atmosphere interactions, is not possible by rendering simple time series approaches. In the last decades, decomposition techniques have found increasing interest for extracting patterns from geophysical observations. Traditionally, principal component analysis (PCA) and more recently independent component analysis (ICA) are common techniques to extract statistical orthogonal (uncorrelated) and independent modes that represent the maximum variance of observations, respectively. PCA and ICA can be classified as stationary signal decomposition techniques since they are based on decomposing the auto-covariance matrix or diagonalizing higher (than two)-order statistical tensors from centered time series. However, the stationary assumption is obviously not justifiable for many geophysical and climate variables even after removing cyclic components e.g., the seasonal cycles. In this paper, we present a new decomposition method, the complex independent component analysis (CICA, Forootan, PhD-2014), which can be applied to extract to non-stationary (changing in space and time) patterns from geophysical time series. Here, CICA is derived as an extension of real-valued ICA (Forootan and Kusche, JoG-2012), where we (i) define a new complex data set using a Hilbert transformation. The complex time series contain the observed values in their real part, and the temporal rate of variability in their imaginary part. (ii) An ICA algorithm based on diagonalization of fourth-order cumulants is then applied to decompose the new complex data set in (i

  2. Spatiotemporal Patterns of Precipitation-Modulated Landslide Deformation From Independent Component Analysis of InSAR Time Series

    Science.gov (United States)

    Cohen-Waeber, J.; Bürgmann, R.; Chaussard, E.; Giannico, C.; Ferretti, A.

    2018-02-01

    Long-term landslide deformation is disruptive and costly in urbanized environments. We rely on TerraSAR-X satellite images (2009-2014) and an improved data processing algorithm (SqueeSAR™) to produce an exceptionally dense Interferometric Synthetic Aperture Radar ground deformation time series for the San Francisco East Bay Hills. Independent and principal component analyses of the time series reveal four distinct spatial and temporal surface deformation patterns in the area around Blakemont landslide, which we relate to different geomechanical processes. Two components of time-dependent landslide deformation isolate continuous motion and motion driven by precipitation-modulated pore pressure changes controlled by annual seasonal cycles and multiyear drought conditions. Two components capturing more widespread seasonal deformation separate precipitation-modulated soil swelling from annual cycles that may be related to groundwater level changes and thermal expansion of buildings. High-resolution characterization of landslide response to precipitation is a first step toward improved hazard forecasting.

  3. Light-effect transistor (LET with multiple independent gating controls for optical logic gates and optical amplification

    Directory of Open Access Journals (Sweden)

    Jason eMarmon

    2016-03-01

    Full Text Available Modern electronics are developing electronic-optical integrated circuits, while their electronic backbone, e.g. field-effect transistors (FETs, remains the same. However, further FET down scaling is facing physical and technical challenges. A light-effect transistor (LET offers electronic-optical hybridization at the component level, which can continue Moore’s law to quantum region without requiring a FET’s fabrication complexity, e.g. physical gate and doping, by employing optical gating and photoconductivity. Multiple independent gates are therefore readily realized to achieve unique functionalities without increasing chip space. Here we report LET device characteristics and novel digital and analog applications, such as optical logic gates and optical amplification. Prototype CdSe-nanowire-based LETs show output and transfer characteristics resembling advanced FETs, e.g. on/off ratios up to ~1.0x106 with a source-drain voltage of ~1.43 V, gate-power of ~260 nW, and subthreshold swing of ~0.3 nW/decade (excluding losses. Our work offers new electronic-optical integration strategies and electronic and optical computing approaches.

  4. Light-effect transistor (LET) with multiple independent gating controls for optical logic gates and optical amplification

    Science.gov (United States)

    Marmon, Jason; Rai, Satish; Wang, Kai; Zhou, Weilie; Zhang, Yong

    The pathway for CMOS technology beyond the 5-nm technology node remains unclear for both physical and technological reasons. A new transistor paradigm is required. A LET (Marmon et. al., Front. Phys. 2016, 4, No. 8) offers electronic-optical hybridization at the component level, and is capable of continuing Moore's law to the quantum scale. A LET overcomes a FET's fabrication complexity, e.g., physical gate and doping, by employing optical gating and photoconductivity, while multiple independent, optical gates readily realize unique functionalities. We report LET device characteristics and novel digital and analog applications, such as optical logic gates and optical amplification. Prototype CdSe-nanowire-based LETs, incorporating an M-S-M structure, show output and transfer characteristics resembling advanced FETs, e.g., on/off ratios up to 106 with a source-drain voltage of 1.43V, gate-power of 260nW, and a subthreshold swing of 0.3nW/decade (excluding losses). A LET has potential for high-switching (THz) speeds and extremely low-switching energies (aJ) in the ballistic transport region. Our work offers new electronic-optical integration strategies for high speed and low energy computing approaches, which could potentially be extended to other materials and devices.

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

    Science.gov (United States)

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

    2017-06-01

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

  6. System-wide versus component-specific trust using multiple aids.

    Science.gov (United States)

    Keller, David; Rice, Stephen

    2010-01-01

    Previous research in operator trust toward automated aids has focused primarily on single aids. The current study focuses on how operator trust is affected by the presence of multiple aids. Two competing theories of multiple-trust are presented. A component-specific trust theory predicts that operators will differentially place their trust in automated aids that vary in reliability. A system-wide trust theory predicts that operators will treat multiple imperfect aids as one "system" and merge their trust across aids despite differences in the aids' reliability. A simulated flight task was used to test these theories, whereby operators performed a pursuit tracking task while concurrently monitoring multiple system gauges that were augmented with perfect or imperfect automated aids. The data revealed that a system-wide trust theory best predicted the data; operators merged their trust across both aids, behaving toward a perfectly reliable aid in the same manner as they did towards unreliable aids.

  7. The relationship between multiple joint flexibility and functional performance in independent and physically active elderly women

    Directory of Open Access Journals (Sweden)

    Maria Joana de Carvalho

    2007-09-01

    Full Text Available Multi-joint flexibility assessment seems to be more appropriate for analyzing the association between fl exibility and functional fitness, but there is a lack of studies to confi rm this possibility in elderly people. The present study investigated the relationship between a multiple joint fl exibility assessment and the functional performance of 30 independent and physically active elderly women (age=68±1yr. Flexibility was assessed using the Chair Sit-and-Reach Test (CSRT. Functional performance was tested by a combination of three tasks: a Step Length (SL; b Time to Put on Sneakers (TPS; c Climbing Stairs (CS. The association between fl exibility and functional performance was tested by both simple and multiple correlation techniques. Pearson’s correlation was signifi cant for TPS (r = -.37; p ABSTRACT

  8. [Construction of multiple drug release system based on components of traditional Chinese medicine].

    Science.gov (United States)

    Liu, Dan; Jia, Xiaobin; Yu, Danhong; Zhang, Zhenhai; Sun, E

    2012-08-01

    With the development of the modernization drive of traditional Chinese medicine (TCM) preparations, new-type TCM dosage forms research have become a hot spot in the field. Because of complexity of TCM components as well as uncertainty of material base, there is still not a scientific system for modern TCM dosage forms so far. Modern TCM preparations inevitably take the nature of the multi-component and the general function characteristics of multi-link and multi-target into account. The author suggests building a multiple drug release system for TCM using diverse preparation techniques and drug release methods at levels on the basis the nature and function characteristics of TCM components. This essay expounds elaborates the ideas to build the multiple traditional Chinese medicine release system, theoretical basis, preparation techniques and assessment system, current problems and solutions, in order to build a multiple TCM release system with a view of enhancing the bioavailability of TCM components and provide a new form for TCM preparations.

  9. Iron deposition is independent of cellular inflammation in a cerebral model of multiple sclerosis

    Directory of Open Access Journals (Sweden)

    Lee Phil

    2011-06-01

    Full Text Available Abstract Background Perivenular inflammation is a common early pathological feature in multiple sclerosis (MS. A recent hypothesis stated that CNS inflammation is induced by perivenular iron deposits that occur in response to altered blood flow in MS subjects. In order to evaluate this hypothesis, an animal model was developed, called cerebral experimental autoimmune encephalomyelitis (cEAE, which presents with CNS perivascular iron deposits. This model was used to investigate the relationship of iron deposition to inflammation. Methods In order to generate cEAE, mice were given an encephalitogen injection followed by a stereotactic intracerebral injection of TNF-α and IFN-γ. Control animals received encephalitogen followed by an intracerebral injection of saline, or no encephalitogen plus an intracerebral injection of saline or cytokines. Laser Doppler was used to measure cerebral blood flow. MRI and iron histochemistry were used to localize iron deposits. Additional histological procedures were used to localize inflammatory cell infiltrates, microgliosis and astrogliosis. Results Doppler analysis revealed that cEAE mice had a reduction in cerebral blood flow compared to controls. MRI revealed T2 hypointense areas in cEAE animals that spatially correlated with iron deposition around vessels and at some sites of inflammation as detected by iron histochemistry. Vessels with associated iron deposits were distributed across both hemispheres. Mice with cEAE had more iron-labeled vessels compared to controls, but these vessels were not commonly associated with inflammatory cell infiltrates. Some iron-laden vessels had associated microgliosis that was above the background microglial response, and iron deposits were observed within reactive microglia. Vessels with associated astrogliosis were more commonly observed without colocalization of iron deposits. Conclusion The findings indicate that iron deposition around vessels can occur independently of

  10. A Method of Calculating Functional Independence Measure at Discharge from Functional Independence Measure Effectiveness Predicted by Multiple Regression Analysis Has a High Degree of Predictive Accuracy.

    Science.gov (United States)

    Tokunaga, Makoto; Watanabe, Susumu; Sonoda, Shigeru

    2017-09-01

    Multiple linear regression analysis is often used to predict the outcome of stroke rehabilitation. However, the predictive accuracy may not be satisfactory. The objective of this study was to elucidate the predictive accuracy of a method of calculating motor Functional Independence Measure (mFIM) at discharge from mFIM effectiveness predicted by multiple regression analysis. The subjects were 505 patients with stroke who were hospitalized in a convalescent rehabilitation hospital. The formula "mFIM at discharge = mFIM effectiveness × (91 points - mFIM at admission) + mFIM at admission" was used. By including the predicted mFIM effectiveness obtained through multiple regression analysis in this formula, we obtained the predicted mFIM at discharge (A). We also used multiple regression analysis to directly predict mFIM at discharge (B). The correlation between the predicted and the measured values of mFIM at discharge was compared between A and B. The correlation coefficients were .916 for A and .878 for B. Calculating mFIM at discharge from mFIM effectiveness predicted by multiple regression analysis had a higher degree of predictive accuracy of mFIM at discharge than that directly predicted. Copyright © 2017 National Stroke Association. Published by Elsevier Inc. All rights reserved.

  11. Comparing soil moisture anomalies from multiple independent sources over different regions across the globe

    Science.gov (United States)

    Cammalleri, Carmelo; Vogt, Jürgen V.; Bisselink, Bernard; de Roo, Ad

    2017-12-01

    Agricultural drought events can affect large regions across the world, implying the need for a suitable global tool for an accurate monitoring of this phenomenon. Soil moisture anomalies are considered a good metric to capture the occurrence of agricultural drought events, and they have become an important component of several operational drought monitoring systems. In the framework of the JRC Global Drought Observatory (GDO, eu/gdo/" target="_blank">http://edo.jrc.ec.europa.eu/gdo/), the suitability of three datasets as possible representations of root zone soil moisture anomalies has been evaluated: (1) the soil moisture from the Lisflood distributed hydrological model (namely LIS), (2) the remotely sensed Land Surface Temperature data from the MODIS satellite (namely LST), and (3) the ESA Climate Change Initiative combined passive/active microwave skin soil moisture dataset (namely CCI). Due to the independency of these three datasets, the triple collocation (TC) technique has been applied, aiming at quantifying the likely error associated with each dataset in comparison to the unknown true status of the system. TC analysis was performed on five macro-regions (namely North America, Europe, India, southern Africa and Australia) detected as suitable for the experiment, providing insight into the mutual relationship between these datasets as well as an assessment of the accuracy of each method. Even if no definitive statement on the spatial distribution of errors can be provided, a clear outcome of the TC analysis is the good performance of the remote sensing datasets, especially CCI, over dry regions such as Australia and southern Africa, whereas the outputs of LIS seem to be more reliable over areas that are well monitored through meteorological ground station networks, such as North America and Europe. In a global drought monitoring system, the results of the error analysis are used to design a weighted-average ensemble system that exploits the advantages of

  12. Comparing soil moisture anomalies from multiple independent sources over different regions across the globe

    Directory of Open Access Journals (Sweden)

    C. Cammalleri

    2017-12-01

    Full Text Available Agricultural drought events can affect large regions across the world, implying the need for a suitable global tool for an accurate monitoring of this phenomenon. Soil moisture anomalies are considered a good metric to capture the occurrence of agricultural drought events, and they have become an important component of several operational drought monitoring systems. In the framework of the JRC Global Drought Observatory (GDO, http://edo.jrc.ec.europa.eu/gdo/, the suitability of three datasets as possible representations of root zone soil moisture anomalies has been evaluated: (1 the soil moisture from the Lisflood distributed hydrological model (namely LIS, (2 the remotely sensed Land Surface Temperature data from the MODIS satellite (namely LST, and (3 the ESA Climate Change Initiative combined passive/active microwave skin soil moisture dataset (namely CCI. Due to the independency of these three datasets, the triple collocation (TC technique has been applied, aiming at quantifying the likely error associated with each dataset in comparison to the unknown true status of the system. TC analysis was performed on five macro-regions (namely North America, Europe, India, southern Africa and Australia detected as suitable for the experiment, providing insight into the mutual relationship between these datasets as well as an assessment of the accuracy of each method. Even if no definitive statement on the spatial distribution of errors can be provided, a clear outcome of the TC analysis is the good performance of the remote sensing datasets, especially CCI, over dry regions such as Australia and southern Africa, whereas the outputs of LIS seem to be more reliable over areas that are well monitored through meteorological ground station networks, such as North America and Europe. In a global drought monitoring system, the results of the error analysis are used to design a weighted-average ensemble system that exploits the advantages of each dataset.

  13. Independent principal component analysis for simulation of soil water content and bulk density in a Canadian Watershed

    Directory of Open Access Journals (Sweden)

    Alaba Boluwade

    2016-09-01

    Full Text Available Accurate characterization of soil properties such as soil water content (SWC and bulk density (BD is vital for hydrologic processes and thus, it is importance to estimate θ (water content and ρ (soil bulk density among other soil surface parameters involved in water retention and infiltration, runoff generation and water erosion, etc. The spatial estimation of these soil properties are important in guiding agricultural management decisions. These soil properties vary both in space and time and are correlated. Therefore, it is important to find an efficient and robust technique to simulate spatially correlated variables. Methods such as principal component analysis (PCA and independent component analysis (ICA can be used for the joint simulations of spatially correlated variables, but they are not without their flaws. This study applied a variant of PCA called independent principal component analysis (IPCA that combines the strengths of both PCA and ICA for spatial simulation of SWC and BD using the soil data set from an 11 km2 Castor watershed in southern Quebec, Canada. Diagnostic checks using the histograms and cumulative distribution function (cdf both raw and back transformed simulations show good agreement. Therefore, the results from this study has potential in characterization of water content variability and bulk density variation for precision agriculture.

  14. TITANIUM ISOTOPE SOURCE RELATIONS AND THE EXTENT OF MIXING IN THE PROTO-SOLAR NEBULA EXAMINED BY INDEPENDENT COMPONENT ANALYSIS

    Energy Technology Data Exchange (ETDEWEB)

    Steele, Robert C. J.; Boehnke, Patrick [Department of Earth, Planetary, and Space Sciences, University of California, Los Angeles, CA 90095 (United States)

    2015-04-01

    The Ti isotope variations observed in hibonites represent some of the largest isotope anomalies observed in the solar system. Titanium isotope compositions have previously been reported for a wide variety of different early solar system materials, including calcium, aluminum rich inclusions (CAIs) and CM hibonite grains, some of the earliest materials to form in the solar system, and bulk meteorites which formed later. These data have the potential to allow mixing of material to be traced between many different regions of the early solar system. We have used independent component analysis to examine the mixing end-members required to produce the compositions observed in the different data sets. The independent component analysis yields results identical to a linear regression for the bulk meteorites. The components identified for hibonite suggest that most of the grains are consistent with binary mixing from one of three highly anomalous nucleosynthetic sources. Comparison of these end-members show that the sources which dominate the variation of compositions in the meteorite parent body forming regions was not present in the region in which the hibonites formed. This suggests that the source which dominates variation in Ti isotope anomalies between the bulk meteorites was not present when the hibonite grains were forming. One explanation is that the bulk meteorite source may not be a primary nucleosynthetic source but was created by mixing two or more of the hibonite sources. Alternatively, the hibonite sources may have been diluted during subsequent nebula processing and are not a dominant solar system signatures.

  15. Multiple functions of a multi-component mating pheromone in sea lamprey Petromyzon marinus

    Science.gov (United States)

    Johnson, N.S.; Yun, S.-S.; Buchinger, T.J.; Li, W.

    2012-01-01

    The role of the C24 sulphate in the mating pheromone component, 7α,12α,24-trihydroxy-5α-cholan-3-one 24-sulphate (3kPZS), to specifically induce upstream movement in ovulated female sea lampreys Petromyzon marinus was investigated. 7α,12α-dihydroxy-5α-cholan-3-one 24-oic acid (3kACA), a structurally similar bile acid released by spermiated males, but lacking the C24 sulphate ester, was tested in bioassays at concentrations between 10−11 and 10−14 molar (M). 3kACA did not induce upstream movement in females or additional reproductive behaviours. In contrast, spermiated male washings induced upstream movement, prolonged retention on a nest and induced an array of nesting behaviours. Differential extraction and elution by solid-phase extraction resins showed that components other than 3kPZS + 3kACA are necessary to retain females on nests and induce nest cleaning behaviours. All pheromone components, including components in addition to 3kPZS + 3kACA that retain females and induce nest cleaning behaviours were released from the anterior region of the males, as had been reported for 3kPZS. It is concluded that the sea lamprey male mating pheromone has multiple functions and is composed of multiple components.

  16. Temporal and Spatial Independent Component Analysis for fMRI Data Sets Embedded in the AnalyzeFMRI R Package

    Directory of Open Access Journals (Sweden)

    Pierre Lafaye de Micheaux

    2011-10-01

    Full Text Available For statistical analysis of functional magnetic resonance imaging (fMRI data sets, we propose a data-driven approach based on independent component analysis (ICA implemented in a new version of the AnalyzeFMRI R package. For fMRI data sets, spatial dimension being much greater than temporal dimension, spatial ICA is the computationally tractable approach generally proposed. However, for some neuroscientific applications, temporal independence of source signals can be assumed and temporal ICA becomes then an attractive exploratory technique. In this work, we use a classical linear algebra result ensuring the tractability of temporal ICA. We report several experiments on synthetic data and real MRI data sets that demonstrate the potential interest of our R package.

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

    Science.gov (United States)

    Liu, Jiangang; Tian, Jie

    2007-03-01

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

  18. Genetic algorithm using independent component analysis in x-ray reflectivity curve fitting of periodic layer structures

    International Nuclear Information System (INIS)

    Tiilikainen, J; Bosund, V; Tilli, J-M; Sormunen, J; Mattila, M; Hakkarainen, T; Lipsanen, H

    2007-01-01

    A novel genetic algorithm (GA) utilizing independent component analysis (ICA) was developed for x-ray reflectivity (XRR) curve fitting. EFICA was used to reduce mutual information, or interparameter dependences, during the combinatorial phase. The performance of the new algorithm was studied by fitting trial XRR curves to target curves which were computed using realistic multilayer models. The median convergence properties of conventional GA, GA using principal component analysis and the novel GA were compared. GA using ICA was found to outperform the other methods with problems having 41 parameters or more to be fitted without additional XRR curve calculations. The computational complexity of the conventional methods was linear but the novel method had a quadratic computational complexity due to the applied ICA method which sets a practical limit for the dimensionality of the problem to be solved. However, the novel algorithm had the best capability to extend the fitting analysis based on Parratt's formalism to multiperiodic layer structures

  19. Integration of independent component analysis with near-infrared spectroscopy for analysis of bioactive components in the medicinal plant Gentiana scabra Bunge

    Directory of Open Access Journals (Sweden)

    Yung-Kun Chuang

    2014-09-01

    Full Text Available Independent component (IC analysis was applied to near-infrared spectroscopy for analysis of gentiopicroside and swertiamarin; the two bioactive components of Gentiana scabra Bunge. ICs that are highly correlated with the two bioactive components were selected for the analysis of tissue cultures, shoots and roots, which were found to distribute in three different positions within the domain [two-dimensional (2D and 3D] constructed by the ICs. This setup could be used for quantitative determination of respective contents of gentiopicroside and swertiamarin within the plants. For gentiopicroside, the spectral calibration model based on the second derivative spectra produced the best effect in the wavelength ranges of 600–700 nm, 1600–1700 nm, and 2000–2300 nm (correlation coefficient of calibration = 0.847, standard error of calibration = 0.865%, and standard error of validation = 0.909%. For swertiamarin, a spectral calibration model based on the first derivative spectra produced the best effect in the wavelength ranges of 600–800 nm and 2200–2300 nm (correlation coefficient of calibration = 0.948, standard error of calibration = 0.168%, and standard error of validation = 0.216%. Both models showed a satisfactory predictability. This study successfully established qualitative and quantitative correlations for gentiopicroside and swertiamarin with near-infrared spectra, enabling rapid and accurate inspection on the bioactive components of G. scabra Bunge at different growth stages.

  20. Long-term intensive gymnastic training induced changes in intra- and inter-network functional connectivity: an independent component analysis.

    Science.gov (United States)

    Huang, Huiyuan; Wang, Junjing; Seger, Carol; Lu, Min; Deng, Feng; Wu, Xiaoyan; He, Yuan; Niu, Chen; Wang, Jun; Huang, Ruiwang

    2018-01-01

    Long-term intensive gymnastic training can induce brain structural and functional reorganization. Previous studies have identified structural and functional network differences between world class gymnasts (WCGs) and non-athletes at the whole-brain level. However, it is still unclear how interactions within and between functional networks are affected by long-term intensive gymnastic training. We examined both intra- and inter-network functional connectivity of gymnasts relative to non-athletes using resting-state fMRI (R-fMRI). R-fMRI data were acquired from 13 WCGs and 14 non-athlete controls. Group-independent component analysis (ICA) was adopted to decompose the R-fMRI data into spatial independent components and associated time courses. An automatic component identification method was used to identify components of interest associated with resting-state networks (RSNs). We identified nine RSNs, the basal ganglia network (BG), sensorimotor network (SMN), cerebellum (CB), anterior and posterior default mode networks (aDMN/pDMN), left and right fronto-parietal networks (lFPN/rFPN), primary visual network (PVN), and extrastriate visual network (EVN). Statistical analyses revealed that the intra-network functional connectivity was significantly decreased within the BG, aDMN, lFPN, and rFPN, but increased within the EVN in the WCGs compared to the controls. In addition, the WCGs showed uniformly decreased inter-network functional connectivity between SMN and BG, CB, and PVN, BG and PVN, and pDMN and rFPN compared to the controls. We interpret this generally weaker intra- and inter-network functional connectivity in WCGs during the resting state as a result of greater efficiency in the WCGs' brain associated with long-term motor skill training.

  1. Fine-scale mapping of 8q24 locus identifies multiple independent risk variants for breast cancer

    DEFF Research Database (Denmark)

    Shi, Jiajun; Zhang, Yanfeng; Zheng, Wei

    2016-01-01

    public resources implied that SNPs rs7815245 in Signal 3, and rs1121948 in Signal 5 (in linkage disequilibrium with rs11780156, r(2)  = 0.77), were putatively functional variants for two of the five independent association signals. The results highlighted multiple 8q24 variants associated with breast...

  2. AS3MT-mediated tolerance to arsenic evolved by multiple independent horizontal gene transfers from bacteria to eukaryotes

    DEFF Research Database (Denmark)

    Palmgren, Michael; Engström, Karin; Hallström, Björn M.

    2017-01-01

    the evolutionary origin of AS3MT and assessed the ability of different genotypes to produce methylated arsenic metabolites. Phylogenetic analysis suggests that multiple, independent horizontal gene transfers between different bacteria, and from bacteria to eukaryotes, increased tolerance to environmental arsenic...

  3. MRI Study on the Functional and Spatial Consistency of Resting State-Related Independent Components of the Brain Network

    Energy Technology Data Exchange (ETDEWEB)

    Jeong, Bum Seok [Korea Advanced Institute of Science and Technology, Daejeon (Korea, Republic of); Choi, Jee Wook [Daejeon St. Mary' s Hospital, The Catholic University of Korea College of Medicine, Daejeon (Korea, Republic of); Kim, Ji Woong [College of Medical Science, Konyang University, Daejeon(Korea, Republic of)

    2012-06-15

    Resting-state networks (RSNs), including the default mode network (DMN), have been considered as markers of brain status such as consciousness, developmental change, and treatment effects. The consistency of functional connectivity among RSNs has not been fully explored, especially among resting-state-related independent components (RSICs). This resting-state fMRI study addressed the consistency of functional connectivity among RSICs as well as their spatial consistency between 'at day 1' and 'after 4 weeks' in 13 healthy volunteers. We found that most RSICs, especially the DMN, are reproducible across time, whereas some RSICs were variable in either their spatial characteristics or their functional connectivity. Relatively low spatial consistency was found in the basal ganglia, a parietal region of left frontoparietal network, and the supplementary motor area. The functional connectivity between two independent components, the bilateral angular/supramarginal gyri/intraparietal lobule and bilateral middle temporal/occipital gyri, was decreased across time regardless of the correlation analysis method employed, (Pearson's or partial correlation). RSICs showing variable consistency are different between spatial characteristics and functional connectivity. To understand the brain as a dynamic network, we recommend further investigation of both changes in the activation of specific regions and the modulation of functional connectivity in the brain network.

  4. MRI Study on the Functional and Spatial Consistency of Resting State-Related Independent Components of the Brain Network

    International Nuclear Information System (INIS)

    Jeong, Bum Seok; Choi, Jee Wook; Kim, Ji Woong

    2012-01-01

    Resting-state networks (RSNs), including the default mode network (DMN), have been considered as markers of brain status such as consciousness, developmental change, and treatment effects. The consistency of functional connectivity among RSNs has not been fully explored, especially among resting-state-related independent components (RSICs). This resting-state fMRI study addressed the consistency of functional connectivity among RSICs as well as their spatial consistency between 'at day 1' and 'after 4 weeks' in 13 healthy volunteers. We found that most RSICs, especially the DMN, are reproducible across time, whereas some RSICs were variable in either their spatial characteristics or their functional connectivity. Relatively low spatial consistency was found in the basal ganglia, a parietal region of left frontoparietal network, and the supplementary motor area. The functional connectivity between two independent components, the bilateral angular/supramarginal gyri/intraparietal lobule and bilateral middle temporal/occipital gyri, was decreased across time regardless of the correlation analysis method employed, (Pearson's or partial correlation). RSICs showing variable consistency are different between spatial characteristics and functional connectivity. To understand the brain as a dynamic network, we recommend further investigation of both changes in the activation of specific regions and the modulation of functional connectivity in the brain network.

  5. Time-correlated single-photon counting study of multiple photoluminescence lifetime components of silicon nanoclusters

    Energy Technology Data Exchange (ETDEWEB)

    Diamare, D., E-mail: d.diamare@ee.ucl.ac.uk [Department of Electronic and Electrical Engineering, University College London, Torrington Place, London, WC1E 7JE (United Kingdom); Wojdak, M. [Department of Electronic and Electrical Engineering, University College London, Torrington Place, London, WC1E 7JE (United Kingdom); Lettieri, S. [Institute for Superconductors and Innovative Materials, National Council of Research (CNR-SPIN), Via Cintia 80126, Naples (Italy); Department of Physical Sciences, University of Naples “Federico II”, Via Cintia 80126, Naples (Italy); Kenyon, A.J. [Department of Electronic and Electrical Engineering, University College London, Torrington Place, London, WC1E 7JE (United Kingdom)

    2013-04-15

    We report time-resolved photoluminescence measurements of thin films of silica containing silicon nanoclusters (Si NCs), produced by PECVD and annealed at temperatures between 700 °C and 1150 °C. While the near infrared emission of Si NCs has long been studied, visible light emission has only recently attracted interest due to its very short decay times and its recently-reported redshift with decreasing NCs size. We analyse the PL decay dynamics in the range 450–700 nm with picosecond time resolution using Time Correlated Single Photon Counting. In the resultant multi-exponential decays two dominant components can clearly be distinguished: a very short component, in the range of hundreds of picoseconds, and a nanosecond component. In this wavelength range we do not detect the microsecond component generally associated with excitonic recombination. We associate the nanosecond component to defect relaxation: it decreases in intensity in the sample annealed at higher temperature, suggesting that the contribution from defects decreases with increasing temperature. The origin of the very fast PL component (ps time region) is also discussed. We show that it is consistent with the Auger recombination times of multiple excitons. Further work needs to be done in order to assess the contribution of the Auger-controlled recombinations to the defect-assisted mechanism of photoluminescence. -- Highlights: ► We report time-resolved PL measurements of Si-Ncs embedded in SiO{sub 2} matrix. ► Net decrease of PL with increasing the annealing temperature has been observed. ► Lifetime distribution analysis revealed a multiexponential decay with ns and ps components. ► Ps components are consistent with the lifetime range of the Auger recombination times. ► No evidence for a fast direct transition at the Brillouin zone centre.

  6. Detection and Characterization of Ground Displacement Sources from Variational Bayesian Independent Component Analysis of GPS Time Series

    Science.gov (United States)

    Gualandi, A.; Serpelloni, E.; Belardinelli, M. E.

    2014-12-01

    A critical point in the analysis of ground displacements time series is the development of data driven methods that allow to discern and characterize the different sources that generate the observed displacements. A widely used multivariate statistical technique is the Principal Component Analysis (PCA), which allows to reduce the dimensionality of the data space maintaining most of the variance of the dataset explained. It reproduces the original data using a limited number of Principal Components, but it also shows some deficiencies. Indeed, PCA does not perform well in finding the solution to the so-called Blind Source Separation (BSS) problem, i.e. in recovering and separating the original sources that generated the observed data. This is mainly due to the assumptions on which PCA relies: it looks for a new Euclidean space where the projected data are uncorrelated. Usually, the uncorrelation condition is not strong enough and it has been proven that the BSS problem can be tackled imposing on the components to be independent. The Independent Component Analysis (ICA) is, in fact, another popular technique adopted to approach this problem, and it can be used in all those fields where PCA is also applied. An ICA approach enables us to explain the time series imposing a fewer number of constraints on the model, and to reveal anomalies in the data such as transient signals. However, the independence condition is not easy to impose, and it is often necessary to introduce some approximations. To work around this problem, we use a variational bayesian ICA (vbICA) method, which models the probability density function (pdf) of each source signal using a mix of Gaussian distributions. This technique allows for more flexibility in the description of the pdf of the sources, giving a more reliable estimate of them. Here we present the application of the vbICA technique to GPS position time series. First, we use vbICA on synthetic data that simulate a seismic cycle

  7. On the interpretation of the independent components underlying the abdominal phonogram: a study of their physiological relevance

    International Nuclear Information System (INIS)

    Jiménez-González, A; James, C J

    2012-01-01

    Recorded by positioning a sensitive acoustic sensor over the maternal womb, the abdominal phonogram is a signal that contains valuable information for foetal surveillance (e.g. heart rate), which is hidden by maternal and environmental sources. To recover such information, previous work used single-channel independent component analysis (SCICA) to separate the abdominal phonogram into statistically independent components (ICs) that, once acquired, must be objectively associated with the real sources underlying the abdominal phonogram—either physiological or environmental. This is a typical challenge for blind source separation methodologies and requires further research on the signals of interest to find a suitable solution. Here, we have conducted a joint study on 75 sets of ICs by means of statistical, spectral, complexity and time-structure analysis methods. As a result, valuable and consistent characteristics of the components separated from the abdominal phonogram by SCICA have been revealed: (1) the ICs are spectrally disjoint and sorted according to their frequency content, (2) only the ICs with lower frequency content present strong regular patterns and (3) such regular patterns are driven by well-known physiological processes given by the maternal breathing rate, the maternal heart rate and the foetal heart rate. This information was so promising that it has been used in current work for automatic classification of ICs and recovery of the traces of the physiological sources underlying the abdominal phonogram. Future work will look for the extraction of information useful for surveillance (e.g. heart rate), not only about foetal well-being, but also about maternal condition. (paper)

  8. Shifted Independent Component Analysis

    DEFF Research Database (Denmark)

    Mørup, Morten; Madsen, Kristoffer Hougaard; Hansen, Lars Kai

    2007-01-01

    Delayed mixing is a problem of theoretical interest and practical importance, e.g., in speech processing, bio-medical signal analysis and financial data modelling. Most previous analyses have been based on models with integer shifts, i.e., shifts by a number of samples, and have often been carried...

  9. Performance comparison of independent component analysis algorithms for fetal cardiac signal reconstruction: a study on synthetic fMCG data

    International Nuclear Information System (INIS)

    Mantini, D; II, K E Hild; Alleva, G; Comani, S

    2006-01-01

    Independent component analysis (ICA) algorithms have been successfully used for signal extraction tasks in the field of biomedical signal processing. We studied the performances of six algorithms (FastICA, CubICA, JADE, Infomax, TDSEP and MRMI-SIG) for fetal magnetocardiography (fMCG). Synthetic datasets were used to check the quality of the separated components against the original traces. Real fMCG recordings were simulated with linear combinations of typical fMCG source signals: maternal and fetal cardiac activity, ambient noise, maternal respiration, sensor spikes and thermal noise. Clusters of different dimensions (19, 36 and 55 sensors) were prepared to represent different MCG systems. Two types of signal-to-interference ratios (SIR) were measured. The first involves averaging over all estimated components and the second is based solely on the fetal trace. The computation time to reach a minimum of 20 dB SIR was measured for all six algorithms. No significant dependency on gestational age or cluster dimension was observed. Infomax performed poorly when a sub-Gaussian source was included; TDSEP and MRMI-SIG were sensitive to additive noise, whereas FastICA, CubICA and JADE showed the best performances. Of all six methods considered, FastICA had the best overall performance in terms of both separation quality and computation times

  10. Independent component analysis-based algorithm for automatic identification of Raman spectra applied to artistic pigments and pigment mixtures.

    Science.gov (United States)

    González-Vidal, Juan José; Pérez-Pueyo, Rosanna; Soneira, María José; Ruiz-Moreno, Sergio

    2015-03-01

    A new method has been developed to automatically identify Raman spectra, whether they correspond to single- or multicomponent spectra. The method requires no user input or judgment. There are thus no parameters to be tweaked. Furthermore, it provides a reliability factor on the resulting identification, with the aim of becoming a useful support tool for the analyst in the decision-making process. The method relies on the multivariate techniques of principal component analysis (PCA) and independent component analysis (ICA), and on some metrics. It has been developed for the application of automated spectral analysis, where the analyzed spectrum is provided by a spectrometer that has no previous knowledge of the analyzed sample, meaning that the number of components in the sample is unknown. We describe the details of this method and demonstrate its efficiency by identifying both simulated spectra and real spectra. The method has been applied to artistic pigment identification. The reliable and consistent results that were obtained make the methodology a helpful tool suitable for the identification of pigments in artwork or in paint in general.

  11. A Suboptimal Power-Saving Transmission Scheme in Multiple Component Carrier Networks

    Science.gov (United States)

    Chung, Yao-Liang; Tsai, Zsehong

    Power consumption due to transmissions in base stations (BSs) has been a major contributor to communication-related CO2 emissions. A power optimization model is developed in this study with respect to radio resource allocation and activation in a multiple Component Carrier (CC) environment. We formulate and solve the power-minimization problem of the BS transceivers for multiple-CC networks with carrier aggregation, while maintaining the overall system and respective users' utilities above minimum levels. The optimized power consumption based on this model can be viewed as a lower bound of that of other algorithms employed in practice. A suboptimal scheme with low computation complexity is proposed. Numerical results show that the power consumption of our scheme is much better than that of the conventional one in which all CCs are always active, if both schemes maintain the same required utilities.

  12. Multiple component codes based generalized LDPC codes for high-speed optical transport.

    Science.gov (United States)

    Djordjevic, Ivan B; Wang, Ting

    2014-07-14

    A class of generalized low-density parity-check (GLDPC) codes suitable for optical communications is proposed, which consists of multiple local codes. It is shown that Hamming, BCH, and Reed-Muller codes can be used as local codes, and that the maximum a posteriori probability (MAP) decoding of these local codes by Ashikhmin-Lytsin algorithm is feasible in terms of complexity and performance. We demonstrate that record coding gains can be obtained from properly designed GLDPC codes, derived from multiple component codes. We then show that several recently proposed classes of LDPC codes such as convolutional and spatially-coupled codes can be described using the concept of GLDPC coding, which indicates that the GLDPC coding can be used as a unified platform for advanced FEC enabling ultra-high speed optical transport. The proposed class of GLDPC codes is also suitable for code-rate adaption, to adjust the error correction strength depending on the optical channel conditions.

  13. Development of quantification methods for the myocardial blood flow using ensemble independent component analysis for dynamic H215O PET

    International Nuclear Information System (INIS)

    Lee, Byeong Il; Lee, Jae Sung; Lee, Dong Soo; Kang, Won Jun; Lee, Jong Jin; Kim, Soo Jin; Chung, June Key; Lee, Myung Chul; Choi, Seung Jin

    2004-01-01

    Factor analysis and independent component analysis (lCA) has been used for handling dynamic image sequences. Theoretical advantages of a newly suggested ICA method, ensemble ICA, leaded us to consider applying this method to the analysis of dynamic myocardial H 2 15 O PET data. In this study, we quantified patients, blood flow using the ensemble ICA method. Twenty subjects underwent H 2 15 O PET scans using ECAT EXACT 47 scanner and myocardial perfusion SPECT using Vertex scanner. After transmission scanning, dynamic emission scans were initiated simultaneously with the injection of 555∼740 MBq H 2 15 O. Hidden independent components can be extracted from the observed mixed data (PET image) by means of ICA algorithms. Ensemble learning is a variational Bayesian method that provides an analytical approximation to the parameter posterior using a tractable distribution. Variational approximation forms a lower bound on the ensemble likelihood and the maximization of the lower bound is achieved through minimizing the Kullback-Leibler divergence between the true posterior and the variational posterior. In this study, posterior pdf was approximated by a rectified Gaussian distribution to incorporate non-negativity constraint, which is suitable to dynamic images in nuclear medicine. Blood flow was measured in 9 regions - apex, four areas in mid wall, and four areas in base wall. Myocardial perfusion SPECT score and angiography results were compared with the regional blood flow. Major cardiac components were separated successfully by the ensemble ICA method and blood flow could be estimated in 15 among 20 patients. Mean myocardial blood flow was 1.2±0.40 ml/min/g in rest, 1.85±1.12 ml/min/g in stress state. Blood flow values obtained by an operator in two different occasion were highly correlated (r=0.99). In myocardium component image, the image contrast between left ventricle and myocardium was 1:2.7 in average. Perfusion reserve was significantly different between

  14. Magnetic Actuator with Multiple Vibration Components Arranged at Eccentric Positions for Use in Complex Piping

    Directory of Open Access Journals (Sweden)

    Hiroyuki Yaguchi

    2016-06-01

    Full Text Available This paper proposes a magnetic actuator using multiple vibration components to perform locomotion in a complex pipe with a 25 mm inner diameter. Due to the desire to increase the turning moment in a T-junction pipe, two vibration components were attached off-center to an acrylic plate with an eccentricity of 2 mm. The experimental results show that the magnetic actuator was able to move at 40.6 mm/s while pulling a load mass of 20 g in a pipe with an inner diameter of 25 mm. In addition, this magnetic actuator was able to move stably in U-junction and T-junction pipes. If a micro-camera is implemented in the future, the inspection of small complex pipes can be enabled. The possibility of inspection in pipes with a 25 mm inner diameter was shown by equipping the pipe with a micro-camera.

  15. Humans' Relationship to Flowers as an Example of the Multiple Components of Embodied Aesthetics.

    Science.gov (United States)

    Huss, Ephrat; Bar Yosef, Kfir; Zaccai, Michele

    2018-03-01

    This paper phenomenologically and qualitatively explores the relationship between humans and flowers as a relationship that throws light on the synergetic dynamics of embodied aesthetics. Its methods include qualitative description and thematic analyses of preferred flower types, as well as concept maps of the general term 'flower' by 120 students in Israel. The results revealed the interactive perceptual-compositional elements, as well as embodied, relational, and socially embedded elements of the aesthetic pleasure associated with flowers. Implications of this case study are generalized to understand the multiple and interactive components of embodied aesthetic experiences as a deep source of pleasure through interactive stimulation by and connection to the natural world.

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

    Science.gov (United States)

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

    2009-11-01

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

  17. Improved separability of dipole sources by tripolar versus conventional disk electrodes: a modeling study using independent component analysis.

    Science.gov (United States)

    Cao, H; Besio, W; Jones, S; Medvedev, A

    2009-01-01

    Tripolar electrodes have been shown to have less mutual information and higher spatial resolution than disc electrodes. In this work, a four-layer anisotropic concentric spherical head computer model was programmed, then four configurations of time-varying dipole signals were used to generate the scalp surface signals that would be obtained with tripolar and disc electrodes, and four important EEG artifacts were tested: eye blinking, cheek movements, jaw movements, and talking. Finally, a fast fixed-point algorithm was used for signal independent component analysis (ICA). The results show that signals from tripolar electrodes generated better ICA separation results than from disc electrodes for EEG signals with these four types of artifacts.

  18. Application of independent component analysis to ac dipole based optics measurement and correction at the Relativistic Heavy Ion Collider

    Directory of Open Access Journals (Sweden)

    X. Shen

    2013-11-01

    Full Text Available Correction of beta-beat is of great importance for performance improvement of high energy accelerators, like the Relativistic Hadron Ion Collider (RHIC. At RHIC, using the independent component analysis method, linear optical functions are extracted from the turn by turn beam position data of the ac dipole driven betatron oscillation. Despite the constraint of a limited number of available quadrupole correctors at RHIC, a global beta-beat correction scheme using a beta-beat response matrix method was developed and experimentally demonstrated. In both rings, a factor of 2 or better reduction of beta-beat was achieved within available beam time. At the same time, a new scheme of using horizontal closed orbit bump at sextupoles to correct beta-beat in the arcs was demonstrated in the Yellow ring of RHIC at beam energy of 255 GeV, and a peak beta-beat of approximately 7% was achieved.

  19. A hybrid sales forecasting scheme by combining independent component analysis with K-means clustering and support vector regression.

    Science.gov (United States)

    Lu, Chi-Jie; Chang, Chi-Chang

    2014-01-01

    Sales forecasting plays an important role in operating a business since it can be used to determine the required inventory level to meet consumer demand and avoid the problem of under/overstocking. Improving the accuracy of sales forecasting has become an important issue of operating a business. This study proposes a hybrid sales forecasting scheme by combining independent component analysis (ICA) with K-means clustering and support vector regression (SVR). The proposed scheme first uses the ICA to extract hidden information from the observed sales data. The extracted features are then applied to K-means algorithm for clustering the sales data into several disjoined clusters. Finally, the SVR forecasting models are applied to each group to generate final forecasting results. Experimental results from information technology (IT) product agent sales data reveal that the proposed sales forecasting scheme outperforms the three comparison models and hence provides an efficient alternative for sales forecasting.

  20. Independent component analysis for cochlear implant artifacts attenuation from electrically evoked auditory steady-state response measurements

    Science.gov (United States)

    Deprez, Hanne; Gransier, Robin; Hofmann, Michael; van Wieringen, Astrid; Wouters, Jan; Moonen, Marc

    2018-02-01

    Objective. Electrically evoked auditory steady-state responses (EASSRs) are potentially useful for objective cochlear implant (CI) fitting and follow-up of the auditory maturation in infants and children with a CI. EASSRs are recorded in the electro-encephalogram (EEG) in response to electrical stimulation with continuous pulse trains, and are distorted by significant CI artifacts related to this electrical stimulation. The aim of this study is to evaluate a CI artifacts attenuation method based on independent component analysis (ICA) for three EASSR datasets. Approach. ICA has often been used to remove CI artifacts from the EEG to record transient auditory responses, such as cortical evoked auditory potentials. Independent components (ICs) corresponding to CI artifacts are then often manually identified. In this study, an ICA based CI artifacts attenuation method was developed and evaluated for EASSR measurements with varying CI artifacts and EASSR characteristics. Artifactual ICs were automatically identified based on their spectrum. Main results. For 40 Hz amplitude modulation (AM) stimulation at comfort level, in high SNR recordings, ICA succeeded in removing CI artifacts from all recording channels, without distorting the EASSR. For lower SNR recordings, with 40 Hz AM stimulation at lower levels, or 90 Hz AM stimulation, ICA either distorted the EASSR or could not remove all CI artifacts in most subjects, except for two of the seven subjects tested with low level 40 Hz AM stimulation. Noise levels were reduced after ICA was applied, and up to 29 ICs were rejected, suggesting poor ICA separation quality. Significance. We hypothesize that ICA is capable of separating CI artifacts and EASSR in case the contralateral hemisphere is EASSR dominated. For small EASSRs or large CI artifact amplitudes, ICA separation quality is insufficient to ensure complete CI artifacts attenuation without EASSR distortion.

  1. "Capitalizing on Sport": Sport, Physical Education and Multiple Capitals in Scottish Independent Schools

    Science.gov (United States)

    Horne, John; Lingard, Bob; Weiner, Gaby; Forbes, Joan

    2011-01-01

    This paper draws on a research study into the existence and use of different forms of capital--including social, cultural and physical capital--in three independent schools in Scotland. We were interested in understanding how these forms of capital work to produce and reproduce "advantage" and "privilege". Analysis is framed by…

  2. Pseudo-random Trees: Multiple Independent Sequence Generators for Parallel and Branching Computations

    Science.gov (United States)

    Halton, John H.

    1989-09-01

    A class of families of linear congruential pseudo-random sequences is defined, for which it is possible to branch at any event without changing the sequence of random numbers used in the original random walk and for which the sequences in different branches show properties analogous to mutual statistical independence. This is a hitherto unavailable, and computationally desirable, tool.

  3. Bayesian evaluation of constrained hypotheses on variances of multiple independent groups

    NARCIS (Netherlands)

    Böing-Messing, F.; van Assen, M.A.L.M.; Hofman, A.D.; Hoijtink, H.; Mulder, J.

    2017-01-01

    Research has shown that independent groups often differ not only in their means, but also in their variances. Comparing and testing variances is therefore of crucial importance to understand the effect of a grouping variable on an outcome variable. Researchers may have specific expectations

  4. Independent component analysis for the extraction of reliable protein signal profiles from MALDI-TOF mass spectra.

    Science.gov (United States)

    Mantini, Dante; Petrucci, Francesca; Del Boccio, Piero; Pieragostino, Damiana; Di Nicola, Marta; Lugaresi, Alessandra; Federici, Giorgio; Sacchetta, Paolo; Di Ilio, Carmine; Urbani, Andrea

    2008-01-01

    Independent component analysis (ICA) is a signal processing technique that can be utilized to recover independent signals from a set of their linear mixtures. We propose ICA for the analysis of signals obtained from large proteomics investigations such as clinical multi-subject studies based on MALDI-TOF MS profiling. The method is validated on simulated and experimental data for demonstrating its capability of correctly extracting protein profiles from MALDI-TOF mass spectra. The comparison on peak detection with an open-source and two commercial methods shows its superior reliability in reducing the false discovery rate of protein peak masses. Moreover, the integration of ICA and statistical tests for detecting the differences in peak intensities between experimental groups allows to identify protein peaks that could be indicators of a diseased state. This data-driven approach demonstrates to be a promising tool for biomarker-discovery studies based on MALDI-TOF MS technology. The MATLAB implementation of the method described in the article and both simulated and experimental data are freely available at http://www.unich.it/proteomica/bioinf/.

  5. Performance comparison of six independent components analysis algorithms for fetal signal extraction from real fMCG data

    International Nuclear Information System (INIS)

    Hild, Kenneth E; Alleva, Giovanna; Nagarajan, Srikantan; Comani, Silvia

    2007-01-01

    In this study we compare the performance of six independent components analysis (ICA) algorithms on 16 real fetal magnetocardiographic (fMCG) datasets for the application of extracting the fetal cardiac signal. We also compare the extraction results for real data with the results previously obtained for synthetic data. The six ICA algorithms are FastICA, CubICA, JADE, Infomax, MRMI-SIG and TDSEP. The results obtained using real fMCG data indicate that the FastICA method consistently outperforms the others in regard to separation quality and that the performance of an ICA method that uses temporal information suffers in the presence of noise. These two results confirm the previous results obtained using synthetic fMCG data. There were also two notable differences between the studies based on real and synthetic data. The differences are that all six ICA algorithms are independent of gestational age and sensor dimensionality for synthetic data, but depend on gestational age and sensor dimensionality for real data. It is possible to explain these differences by assuming that the number of point sources needed to completely explain the data is larger than the dimensionality used in the ICA extraction

  6. Smart transactive energy framework in grid-connected multiple home microgrids under independent and coalition operations

    DEFF Research Database (Denmark)

    Marzband, Mousa; Azarinejadian, Fatemeh; Savaghebi, Mehdi

    2018-01-01

    This paper presents a smart Transactive energy (TE) framework in which home microgrids (H-MGs) can collaborate with each other in a multiple H-MG system by forming coalitions for gaining competitiveness in the market. Profit allocation due to coalition between H-MGs is an important issue...... for ensuring the optimal use of installed resources in the whole multiple H-MG system. In addition, considering demand fluctuations, energy production based on renewable resources in the multiple H-MG can be accomplished by demand-side management strategies that try to establish mechanisms to allow...... for a flatter demand curve. In this regard, demand shifting potential can be tapped through shifting certain amounts of energy demand from some time periods to others with lower expected demand, typically to match price values and to ensure that existing generation will be economically sufficient. It is also...

  7. Speckle noise reduction technique for Lidar echo signal based on self-adaptive pulse-matching independent component analysis

    Science.gov (United States)

    Xu, Fan; Wang, Jiaxing; Zhu, Daiyin; Tu, Qi

    2018-04-01

    Speckle noise has always been a particularly tricky problem in improving the ranging capability and accuracy of Lidar system especially in harsh environment. Currently, effective speckle de-noising techniques are extremely scarce and should be further developed. In this study, a speckle noise reduction technique has been proposed based on independent component analysis (ICA). Since normally few changes happen in the shape of laser pulse itself, the authors employed the laser source as a reference pulse and executed the ICA decomposition to find the optimal matching position. In order to achieve the self-adaptability of algorithm, local Mean Square Error (MSE) has been defined as an appropriate criterion for investigating the iteration results. The obtained experimental results demonstrated that the self-adaptive pulse-matching ICA (PM-ICA) method could effectively decrease the speckle noise and recover the useful Lidar echo signal component with high quality. Especially, the proposed method achieves 4 dB more improvement of signal-to-noise ratio (SNR) than a traditional homomorphic wavelet method.

  8. EEGLAB: an open source toolbox for analysis of single-trial EEG dynamics including independent component analysis.

    Science.gov (United States)

    Delorme, Arnaud; Makeig, Scott

    2004-03-15

    We have developed a toolbox and graphic user interface, EEGLAB, running under the crossplatform MATLAB environment (The Mathworks, Inc.) for processing collections of single-trial and/or averaged EEG data of any number of channels. Available functions include EEG data, channel and event information importing, data visualization (scrolling, scalp map and dipole model plotting, plus multi-trial ERP-image plots), preprocessing (including artifact rejection, filtering, epoch selection, and averaging), independent component analysis (ICA) and time/frequency decompositions including channel and component cross-coherence supported by bootstrap statistical methods based on data resampling. EEGLAB functions are organized into three layers. Top-layer functions allow users to interact with the data through the graphic interface without needing to use MATLAB syntax. Menu options allow users to tune the behavior of EEGLAB to available memory. Middle-layer functions allow users to customize data processing using command history and interactive 'pop' functions. Experienced MATLAB users can use EEGLAB data structures and stand-alone signal processing functions to write custom and/or batch analysis scripts. Extensive function help and tutorial information are included. A 'plug-in' facility allows easy incorporation of new EEG modules into the main menu. EEGLAB is freely available (http://www.sccn.ucsd.edu/eeglab/) under the GNU public license for noncommercial use and open source development, together with sample data, user tutorial and extensive documentation.

  9. Extraction of fast neuronal changes from multichannel functional near-infrared spectroscopy signals using independent component analysis

    Science.gov (United States)

    Morren, Geert; Wolf, Martin; Lemmerling, Philippe; Wolf, Ursula; Choi, Jee H.; Gratton, Enrico; De Lathauwer, Lieven; Van Huffel, Sabine

    2002-06-01

    Fast changes in the range of milliseconds in the optical properties of cerebral tissue, which are associated with brain activity, can be detected using non-invasive near-infrared spectroscopy (NIRS). These changes in light scattering are due to an alteration in the refractive index at neuronal membranes. The aim of this study was to develop highly sensitive data analysis algorithms to detect this fast signal, which is small compared to other physiological signals. A frequency-domain tissue oximeter, whose laser diodes were modulated at 110MHz was used. The amplitude, mean intensity and phase of the modulated optical signal was measured at 96Hz sample rate. The probe consisting of 4 crossed source detector pairs was placed above the motor cortex, contralateral to the hand performing a tapping exercise consisting of alternating rest- and tapping periods of 20s each. The tapping frequency, which was set to 3.55Hz or 2.5 times the heart rate of the subject to avoid the influence of harmonics on the signal, could not be observed in any of the individual signals measured by the detectors. An adaptive filter was used to remove the arterial pulsatility from the optical signals. Independent Component Analysis allowed to separate signal components in which the tapping frequency was clearly visible.

  10. Smart transactive energy framework in grid-connected multiple home microgrids under independent and coalition operations

    DEFF Research Database (Denmark)

    Marzband, Mousa; Azarinejadian, Fatemeh; Savaghebi, Mehdi

    2018-01-01

    This paper presents a smart Transactive energy (TE) framework in which home microgrids (H-MGs) can collaborate with each other in a multiple H-MG system by forming coalitions for gaining competitiveness in the market. Profit allocation due to coalition between H-MGs is an important issue...

  11. Key issues in decomposing fMRI during naturalistic and continuous music experience with independent component analysis.

    Science.gov (United States)

    Cong, Fengyu; Puoliväli, Tuomas; Alluri, Vinoo; Sipola, Tuomo; Burunat, Iballa; Toiviainen, Petri; Nandi, Asoke K; Brattico, Elvira; Ristaniemi, Tapani

    2014-02-15

    Independent component analysis (ICA) has been often used to decompose fMRI data mostly for the resting-state, block and event-related designs due to its outstanding advantage. For fMRI data during free-listening experiences, only a few exploratory studies applied ICA. For processing the fMRI data elicited by 512-s modern tango, a FFT based band-pass filter was used to further pre-process the fMRI data to remove sources of no interest and noise. Then, a fast model order selection method was applied to estimate the number of sources. Next, both individual ICA and group ICA were performed. Subsequently, ICA components whose temporal courses were significantly correlated with musical features were selected. Finally, for individual ICA, common components across majority of participants were found by diffusion map and spectral clustering. The extracted spatial maps (by the new ICA approach) common across most participants evidenced slightly right-lateralized activity within and surrounding the auditory cortices. Meanwhile, they were found associated with the musical features. Compared with the conventional ICA approach, more participants were found to have the common spatial maps extracted by the new ICA approach. Conventional model order selection methods underestimated the true number of sources in the conventionally pre-processed fMRI data for the individual ICA. Pre-processing the fMRI data by using a reasonable band-pass digital filter can greatly benefit the following model order selection and ICA with fMRI data by naturalistic paradigms. Diffusion map and spectral clustering are straightforward tools to find common ICA spatial maps. Copyright © 2013 Elsevier B.V. All rights reserved.

  12. Combining Multiple Features for Text-Independent Writer Identification and Verification

    OpenAIRE

    Bulacu , Marius; Schomaker , Lambert

    2006-01-01

    http://www.suvisoft.com; In recent years, we proposed a number of new and very effective features for automatic writer identification and verification. They are probability distribution functions (PDFs) extracted from the handwriting images and characterize writer individuality independently of the textual content of the written samples. In this paper, we perform an extensive analysis of feature combinations. In our fusion scheme, the final unique distance between two handwritten samples is c...

  13. Recurrent Rearrangements of Human Amylase Genes Create Multiple Independent CNV Series.

    Science.gov (United States)

    Shwan, Nzar A A; Louzada, Sandra; Yang, Fengtang; Armour, John A L

    2017-05-01

    The human amylase gene cluster includes the human salivary (AMY1) and pancreatic amylase genes (AMY2A and AMY2B), and is a highly variable and dynamic region of the genome. Copy number variation (CNV) of AMY1 has been implicated in human dietary adaptation, and in population association with obesity, but neither of these findings has been independently replicated. Despite these functional implications, the structural genomic basis of CNV has only been defined in detail very recently. In this work, we use high-resolution analysis of copy number, and analysis of segregation in trios, to define new, independent allelic series of amylase CNVs in sub-Saharan Africans, including a series of higher-order expansions of a unit consisting of one copy each of AMY1, AMY2A, and AMY2B. We use fiber-FISH (fluorescence in situ hybridization) to define unexpected complexity in the accompanying rearrangements. These findings demonstrate recurrent involvement of the amylase gene region in genomic instability, involving at least five independent rearrangements of the pancreatic amylase genes (AMY2A and AMY2B). Structural features shared by fundamentally distinct lineages strongly suggest that the common ancestral state for the human amylase cluster contained more than one, and probably three, copies of AMY1. © 2017 WILEY PERIODICALS, INC.

  14. Origins of mass-dependent and mass-independent Ca isotope variations in meteoritic components and meteorites

    Science.gov (United States)

    Bermingham, K. R.; Gussone, N.; Mezger, K.; Krause, J.

    2018-04-01

    The Ca isotope composition of meteorites and their components may vary due to mass-dependent and/or -independent isotope effects. In order to evaluate the origin of these effects, five amoeboid olivine aggregates (AOAs), three calcium aluminum inclusions (CAIs), five chondrules (C), a dark inclusion from Allende (CV3), two dark fragments from North West Africa 753 (NWA 753; R3.9), and a whole rock sample of Orgueil (CI1) were analyzed. This is the first coupled mass-dependent and -independent Ca isotope dataset to include AOAs, a dark inclusion, and dark fragments. Where sample masses permit, Ca isotope data are reported with corresponding petrographic analyses and rare earth element (REE) relative abundance patterns. The CAIs and AOAs are enriched in light Ca isotopes (δ44/40Ca -5.32 to +0.72, where δ44/40Ca is reported relative to SRM 915a). Samples CAI 5 and AOA 1 have anomalous Group II REE patterns. These REE and δ44/40Ca data suggest that the CAI 5 and AOA 1 compositions were set via kinetic isotope fractionation during condensation and evaporation. The remaining samples show mass-dependent Ca isotope variations which cluster between δ44/40Ca +0.53 and +1.59, some of which are coupled with unfractionated REE abundance patterns. These meteoritic components likely formed through the coaccretion of the evaporative residue and condensate following Group II CAI formation or their chemical and isotopic signatures were decoupled (e.g., via nebular or parent-body alteration). The whole rock sample of Orgueil has a δ44/40Ca +0.67 ± 0.18 which is in agreement with most published data. Parent-body alteration, terrestrial alteration, and variable sampling of Ca-rich meteoritic components can have an effect on δ44/40Ca compositions in whole rock meteorites. Samples AOA 1, CAI 5, C 2, and C 4 display mass-independent 48/44Ca anomalies (ε48/44Ca +6 to +12) which are resolved from the standard composition. Other samples measured for these effects (AOA 5, CAI 1, CAI 2

  15. Mediator independently orchestrates multiple steps of preinitiation complex assembly in vivo

    OpenAIRE

    Eyboulet, Fanny; Wydau-Dematteis, Sandra; Eychenne, Thomas; Alibert, Olivier; Neil, Helen; Boschiero, Claire; Nevers, Marie-Claire; Volland, Herv?; Cornu, David; Redeker, Virginie; Werner, Michel; Soutourina, Julie

    2015-01-01

    Mediator is a large multiprotein complex conserved in all eukaryotes, which has a crucial coregulator function in transcription by RNA polymerase II (Pol II). However, the molecular mechanisms of its action in vivo remain to be understood. Med17 is an essential and central component of the Mediator head module. In this work, we utilised our large collection of conditional temperature-sensitive med17 mutants to investigate Mediator's role in coordinating preinitiation complex (PIC) formation i...

  16. The Multiple-component Binary Hyad, vA 351 - a Progress Report

    Science.gov (United States)

    Benedict, George Fritz; Franz, Otto G.; Wasserman, Lawrence H.

    2017-06-01

    We extend results first announced by Franz et al. (1998) in the abstract, http://adsabs.harvard.edu/abs/1998AAS...19310207F ,that identified vA 351 = H346 in the Hyades as a multiple star system containing a white dwarf. With HST/FGS fringe tracking and scanning, spanning four years, we establish a parallax, relative orbit, and mass fraction for the A-B components, with a period, P~5.47y. With ground-based radial velocities from the McDonald Observatory Struve 2.1m telescope and Sandiford Spectrograph, spanning 14 years, we find that component B consists of BC, two M dwarf stars orbiting with a very short period (P(BC)~0.75 days), having a mass ratio C/B~0.94. We confirm that the total mass of the system can only be reconciled with the distance and component photometry by including a fainter, higher mass component, proposed to be a ~0.8Msun white dwarf. Thus, the quadruple system consists of three M dwarfs (A,B,C) and one white dwarf (D). The M dwarf masses and absolute magnitudes are consistent with the Benedict et al. (2016, http://adsabs.harvard.edu/abs/2016AJ....152..141B) lower Main Sequence Mass-Luminosity Relation. The radial velocity signal has so far yielded a signature only for the short-period BC orbital motion. Velocities from H-α and He I emission lines confirm the BC period from absorption lines, with similar (He I) and higher (H-α) velocity amplitudes.

  17. VizieR Online Data Catalog: CCDM (Components of Double and Multiple stars) (Dommanget+ 1994)

    Science.gov (United States)

    Dommanget, J.; Nys, O.

    1996-11-01

    The introduction to this catalogue has been the subject of a publication in the "Communications de l'Observatoire Royal de Belgique" (Serie A, number 115). Detailed are: its origins, its aims, its realization, the search of identifiers, the compilation of astrometric data and the related problems as well as the fundamental ties between the CCDM and the HIPPARCOS INPUT CATALOGUE (HIC). It also contains a complete bibliography of the referred papers. The contents of the general catalogue (63,463 systems) is also described as well as the conditions of its availability to the astronomical community and the projects underway for the next edition. For all these items, the user is invited to refer to this publication because hereafter only the format and the contents of the catalogue follow. To identify the systems and their components, we adopted the clever numbering process of the authors of the INDEX consisting in combining the right ascension and declination, respectively limited to 0.1 minute of time and to 1 minute of arc. In order to distinguish the CCDM numbers from the INDEX numbers - in addition to their different equinox: 2000 for the CCDM and 1900 for the INDEX - we adopted the signs + and - instead of the letters N and S for separating the coordinates. Consequently, in the INDEX and in the CCDM, one entry is devoted to a same system but the contrary to the INDEX, where a sub-entry is assigned to each group of two components, whatever the multiplicity of the system may be, the CCDM allows one sub-entry and thus one record per component. The present edition contains only the 34,031 systems (table below, part I) for which an accurate position has been found for at least one component. The catalogue extends thus much over the sample of the somewhat 14,000 systems finally retained for the HIPPARCOS INPUT CATALOGUE and assembled in its Annex 1. (1 data file).

  18. Cold in-place recycling characterization framework for single or multiple component binder systems

    Science.gov (United States)

    Cox, Benjamin C.

    Cold in-place recycling (CIR) is a pavement rehabilitation technique which has gained momentum in recent years. This momentum is due partly to its economic and sustainability characteristics, which has led to CIR market expansion. When pavement network deterioration is considered alongside increasing material costs, it is not beyond reason to expect demands on CIR to continue to increase. Historically, single component binder (SCB) systems, those with one stabilization binder (or two if the secondary binder dosage is 1% or less), have dominated the CIR market and could be considered the general state of practice. Common stabilization binders are either bituminous or cementitious. Two example SCB systems would be: 1) 3% portland cement, or 2) 3% asphalt emulsion with 1% hydrated lime. While traditional SCB systems have demonstrated positive economic and sustainability impacts, this dissertation focuses on multiple component binder (MCB) systems (bituminous and cementitious combined) which exhibit the potential to provide better overall economics and performance. Use of MCBs has the potential to alleviate SCB issues to some extent (e.g. cracking with cementitious SCBs, rutting with bituminous SCBs). Furthermore, to fairly represent both binders in an MCB system a universal design method which can accommodate multiple binder types is needed. The main objectives of this dissertation are to develop a universal CIR design framework and, using this framework, characterize multiple SCB and MCB systems. Approximately 1500 CIR specimens were tested herein along with approximately 300 asphalt concrete specimens which serve as a reference data set for CIR characterization. A case study of a high-traffic Mississippi CIR project which included cement SCB and emulsion SCB sections is also presented to support laboratory efforts. Individual components needed to comprise a universal design framework, such as curing protocols, were developed. SCB and MCB characterization indicated

  19. Robust spinal cord resting-state fMRI using independent component analysis-based nuisance regression noise reduction.

    Science.gov (United States)

    Hu, Yong; Jin, Richu; Li, Guangsheng; Luk, Keith Dk; Wu, Ed X

    2018-04-16

    Physiological noise reduction plays a critical role in spinal cord (SC) resting-state fMRI (rsfMRI). To reduce physiological noise and increase the robustness of SC rsfMRI by using an independent component analysis (ICA)-based nuisance regression (ICANR) method. Retrospective. Ten healthy subjects (female/male = 4/6, age = 27 ± 3 years, range 24-34 years). 3T/gradient-echo echo planar imaging (EPI). We used three alternative methods (no regression [Nil], conventional region of interest [ROI]-based noise reduction method without ICA [ROI-based], and correction of structured noise using spatial independent component analysis [CORSICA]) to compare with the performance of ICANR. Reduction of the influence of physiological noise on the SC and the reproducibility of rsfMRI analysis after noise reduction were examined. The correlation coefficient (CC) was calculated to assess the influence of physiological noise. Reproducibility was calculated by intraclass correlation (ICC). Results from different methods were compared by one-way analysis of variance (ANOVA) with post-hoc analysis. No significant difference in cerebrospinal fluid (CSF) pulsation influence or tissue motion influence were found (P = 0.223 in CSF, P = 0.2461 in tissue motion) in the ROI-based (CSF: 0.122 ± 0.020; tissue motion: 0.112 ± 0.015), and Nil (CSF: 0.134 ± 0.026; tissue motion: 0.124 ± 0.019). CORSICA showed a significantly stronger influence of CSF pulsation and tissue motion (CSF: 0.166 ± 0.045, P = 0.048; tissue motion: 0.160 ± 0.032, P = 0.048) than Nil. ICANR showed a significantly weaker influence of CSF pulsation and tissue motion (CSF: 0.076 ± 0.007, P = 0.0003; tissue motion: 0.081 ± 0.014, P = 0.0182) than Nil. The ICC values in the Nil, ROI-based, CORSICA, and ICANR were 0.669, 0.645, 0.561, and 0.766, respectively. ICANR more effectively reduced physiological noise from both tissue motion and CSF pulsation than three alternative methods. ICANR increases the robustness of SC rsf

  20. Utilization of independent component analysis for accurate pathological ripple detection in intracranial EEG recordings recorded extra- and intra-operatively.

    Science.gov (United States)

    Shimamoto, Shoichi; Waldman, Zachary J; Orosz, Iren; Song, Inkyung; Bragin, Anatol; Fried, Itzhak; Engel, Jerome; Staba, Richard; Sharan, Ashwini; Wu, Chengyuan; Sperling, Michael R; Weiss, Shennan A

    2018-01-01

    To develop and validate a detector that identifies ripple (80-200 Hz) events in intracranial EEG (iEEG) recordings in a referential montage and utilizes independent component analysis (ICA) to eliminate or reduce high-frequency artifact contamination. Also, investigate the correspondence of detected ripples and the seizure onset zone (SOZ). iEEG recordings from 16 patients were first band-pass filtered (80-600 Hz) and Infomax ICA was next applied to derive the first independent component (IC1). IC1 was subsequently pruned, and an artifact index was derived to reduce the identification of high-frequency events introduced by the reference electrode signal. A Hilbert detector identified ripple events in the processed iEEG recordings using amplitude and duration criteria. The identified ripple events were further classified and characterized as true or false ripple on spikes, or ripples on oscillations by utilizing a topographical analysis to their time-frequency plot, and confirmed by visual inspection. The signal to noise ratio was improved by pruning IC1. The precision of the detector for ripple events was 91.27 ± 4.3%, and the sensitivity of the detector was 79.4 ± 3.0% (N = 16 patients, 5842 ripple events). The sensitivity and precision of the detector was equivalent in iEEG recordings obtained during sleep or intra-operatively. Across all the patients, true ripple on spike rates and also the rates of false ripple on spikes, that were generated due to filter ringing, classified the seizure onset zone (SOZ) with an area under the receiver operating curve (AUROC) of >76%. The magnitude and spectral content of true ripple on spikes generated in the SOZ was distinct as compared with the ripples generated in the NSOZ (p ripple rates and properties defined using this approach may accurately delineate the seizure onset zone. Strategies to improve the spatial resolution of intracranial EEG and reduce artifact can help improve the clinical utility of

  1. Non-local coexistence of multiple spiral waves with independent frequencies

    International Nuclear Information System (INIS)

    Zhan Meng; Luo Jinming

    2009-01-01

    The interactions of several spiral waves with different independent rotation frequencies are studied in a model of two-dimensional complex Ginzburg-Laudau equation. We find a general coexistence phenomenon, non-local non-phase-locking-invasion coexistence, that is, the non-slowest spiral wave can survive and not be killed by the fastest spiral wave as it is insulated from the fastest one with the sacrifice of the slowest one, which stays in the spatial position between the fastest spiral and the non-slowest one. Both the parameter non-monotonicity and the non-phase-locking invasion between the fastest and the slowest spiral waves play key roles in this phenomenon. Importantly, the results could give a general idea for extensively observed coexistence of spiral waves in various inhomogeneous circumstances.

  2. Accounting for multiple climate components when estimating climate change exposure and velocity

    Science.gov (United States)

    Nadeau, Christopher P.; Fuller, Angela K.

    2015-01-01

    The effect of anthropogenic climate change on organisms will likely be related to climate change exposure and velocity at local and regional scales. However, common methods to estimate climate change exposure and velocity ignore important components of climate that are known to affect the ecology and evolution of organisms.We develop a novel index of climate change (climate overlap) that simultaneously estimates changes in the means, variation and correlation between multiple weather variables. Specifically, we estimate the overlap between multivariate normal probability distributions representing historical and current or projected future climates. We provide methods for estimating the statistical significance of climate overlap values and methods to estimate velocity using climate overlap.We show that climates have changed significantly across 80% of the continental United States in the last 32 years and that much of this change is due to changes in the variation and correlation between weather variables (two statistics that are rarely incorporated into climate change studies). We also show that projected future temperatures are predicted to be locally novel (using climate overlap compared to 1·4 km yr−1 when estimated using traditional methods.Our results suggest that accounting for changes in the means, variation and correlation between multiple weather variables can dramatically affect estimates of climate change exposure and velocity. These climate components are known to affect the ecology and evolution of organisms, but are ignored by most measures of climate change. We conclude with a set of future directions and recommend future work to determine which measures of climate change exposure and velocity are most related to biological responses to climate change.

  3. Geophysical Factor Resolving of Rainfall Mechanism for Super Typhoons by Using Multiple Spatiotemporal Components Analysis

    Science.gov (United States)

    Huang, Chien-Lin; Hsu, Nien-Sheng

    2016-04-01

    This study develops a novel methodology to resolve the geophysical cause of typhoon-induced rainfall considering diverse dynamic co-evolution at multiple spatiotemporal components. The multi-order hidden patterns of complex hydrological process in chaos are detected to understand the fundamental laws of rainfall mechanism. The discovered spatiotemporal features are utilized to develop a state-of-the-art descriptive statistical model for mechanism validation, modeling and further prediction during typhoons. The time series of hourly typhoon precipitation from different types of moving track, atmospheric field and landforms are respectively precede the signal analytical process to qualify each type of rainfall cause and to quantify the corresponding affected degree based on the measured geophysical atmospheric-hydrological variables. This study applies the developed methodology in Taiwan Island which is constituted by complex diverse landform formation. The identified driving-causes include: (1) cloud height to ground surface; (2) co-movement effect induced by typhoon wind field with monsoon; (3) stem capacity; (4) interaction between typhoon rain band and terrain; (5) structural intensity variance of typhoon; and (6) integrated cloudy density of rain band. Results show that: (1) for the central maximum wind speed exceeding 51 m/sec, Causes (1) and (3) are the primary ones to generate rainfall; (2) for the typhoon moving toward the direction of 155° to 175°, Cause (2) is the primary one; (3) for the direction of 90° to 155°, Cause (4) is the primary one; (4) for the typhoon passing through mountain chain which above 3500 m, Cause (5) is the primary one; and (5) for the moving speed lower than 18 km/hr, Cause (6) is the primary one. Besides, the multiple geophysical component-based precipitation modeling can achieve 81% of average accuracy and 0.732 of average correlation coefficient (CC) within average 46 hours of duration, that improve their predictability.

  4. Secondary components, integral multiplicity factor and coupling coefficients of cosmic rays in the Earth atmosphere and other planets

    International Nuclear Information System (INIS)

    Dorman, L.I.; Yanke, V.G.

    1979-01-01

    Integral multiples of cosmic rays in Earth and other planets atmospheres have been determined. Kinetic equations describing the evolution of hadronic cascade in atmosphere using modern accelerating data have been solved with that end in view. Bond coefficients for nucleonic, muonic and electronic components of secondary cosmic radiation have been built using integral multiples. Normalized bond coefficients for three components obtained for maximum solar activity are presented. Integral muon and nucleon generation and bond coefficients have also been given for Mars

  5. Group Independent Component Analysis (gICA) and Current Source Density (CSD) in the study of EEG in ADHD adults.

    Science.gov (United States)

    Ponomarev, Valery A; Mueller, Andreas; Candrian, Gian; Grin-Yatsenko, Vera A; Kropotov, Juri D

    2014-01-01

    To investigate the performance of the spectral analysis of resting EEG, Current Source Density (CSD) and group independent components (gIC) in diagnosing ADHD adults. Power spectra of resting EEG, CSD and gIC (19 channels, linked ears reference, eyes open/closed) from 96 ADHD and 376 healthy adults were compared between eyes open and eyes closed conditions, and between groups of subjects. Pattern of differences in gIC and CSD spectral power between conditions was approximately similar, whereas it was more widely spatially distributed for EEG. Size effect (Cohen's d) of differences in gIC and CSD spectral power between groups of subjects was considerably greater than in the case of EEG. Significant reduction of gIC and CSD spectral power depending on conditions was found in ADHD patients. Reducing power in a wide frequency range in the fronto-central areas is a common phenomenon regardless of whether the eyes were open or closed. Spectral power of local EEG activity isolated by gICA or CSD in the fronto-central areas may be a suitable marker for discrimination of ADHD and healthy adults. Spectral analysis of gIC and CSD provides better sensitivity to discriminate ADHD and healthy adults. Copyright © 2013 International Federation of Clinical Neurophysiology. Published by Elsevier Ireland Ltd. All rights reserved.

  6. Separating spectral mixtures in hyperspectral image data using independent component analysis: validation with oral cancer tissue sections

    Science.gov (United States)

    Duann, Jeng-Ren; Jan, Chia-Ing; Ou-Yang, Mang; Lin, Chia-Yi; Mo, Jen-Feng; Lin, Yung-Jiun; Tsai, Ming-Hsui; Chiou, Jin-Chern

    2013-12-01

    Recently, hyperspectral imaging (HSI) systems, which can provide 100 or more wavelengths of emission autofluorescence measures, have been used to delineate more complete spectral patterns associated with certain molecules relevant to cancerization. Such a spectral fingerprint may reliably correspond to a certain type of molecule and thus can be treated as a biomarker for the presence of that molecule. However, the outcomes of HSI systems can be a complex mixture of characteristic spectra of a variety of molecules as well as optical interferences due to reflection, scattering, and refraction. As a result, the mixed nature of raw HSI data might obscure the extraction of consistent spectral fingerprints. Here we present the extraction of the characteristic spectra associated with keratinized tissues from the HSI data of tissue sections from 30 oral cancer patients (31 tissue samples in total), excited at two different wavelength ranges (330 to 385 and 470 to 490 nm), using independent and principal component analysis (ICA and PCA) methods. The results showed that for both excitation wavelength ranges, ICA was able to resolve much more reliable spectral fingerprints associated with the keratinized tissues for all the oral cancer tissue sections with significantly higher mean correlation coefficients as compared to PCA (p<0.001).

  7. A Combined Methodology to Eliminate Artifacts in Multichannel Electrogastrogram Based on Independent Component Analysis and Ensemble Empirical Mode Decomposition.

    Science.gov (United States)

    Sengottuvel, S; Khan, Pathan Fayaz; Mariyappa, N; Patel, Rajesh; Saipriya, S; Gireesan, K

    2018-06-01

    Cutaneous measurements of electrogastrogram (EGG) signals are heavily contaminated by artifacts due to cardiac activity, breathing, motion artifacts, and electrode drifts whose effective elimination remains an open problem. A common methodology is proposed by combining independent component analysis (ICA) and ensemble empirical mode decomposition (EEMD) to denoise gastric slow-wave signals in multichannel EGG data. Sixteen electrodes are fixed over the upper abdomen to measure the EGG signals under three gastric conditions, namely, preprandial, postprandial immediately, and postprandial 2 h after food for three healthy subjects and a subject with a gastric disorder. Instantaneous frequencies of intrinsic mode functions that are obtained by applying the EEMD technique are analyzed to individually identify and remove each of the artifacts. A critical investigation on the proposed ICA-EEMD method reveals its ability to provide a higher attenuation of artifacts and lower distortion than those obtained by the ICA-EMD method and conventional techniques, like bandpass and adaptive filtering. Characteristic changes in the slow-wave frequencies across the three gastric conditions could be determined from the denoised signals for all the cases. The results therefore encourage the use of the EEMD-based technique for denoising gastric signals to be used in clinical practice.

  8. Independent component analysis-based artefact reduction: application to the electrocardiogram for improved magnetic resonance imaging triggering

    International Nuclear Information System (INIS)

    Oster, Julien; Pietquin, Olivier; Felblinger, Jacques; Abächerli, Roger; Kraemer, Michel

    2009-01-01

    Electrocardiogram (ECG) is required during magnetic resonance (MR) examination for monitoring patients under anaesthesia or with heart diseases and for synchronizing image acquisition with heart activity (triggering). Accurate and fast QRS detection is therefore desirable, but this task is complicated by artefacts related to the complex MR environment (high magnetic field, radio-frequency pulses and fast switching magnetic gradients). Specific signal processing has been proposed, whether using specific MR QRS detectors or ECG denoising methods. Most state-of-the-art techniques use a connection to the MR system for achieving their task, which is a major drawback since access to the MR system is often restricted. This paper introduces a new method for on-line ECG signal enhancement, called ICARE, which takes advantage of using multi-lead ECG and does not require any connection to the MR system. It is based on independent component analysis (ICA) and applied in real time. This algorithm yields accurate QRS detection for efficient triggering

  9. Brain network of semantic integration in sentence reading: insights from independent component analysis and graph theoretical analysis.

    Science.gov (United States)

    Ye, Zheng; Doñamayor, Nuria; Münte, Thomas F

    2014-02-01

    A set of cortical and sub-cortical brain structures has been linked with sentence-level semantic processes. However, it remains unclear how these brain regions are organized to support the semantic integration of a word into sentential context. To look into this issue, we conducted a functional magnetic resonance imaging (fMRI) study that required participants to silently read sentences with semantically congruent or incongruent endings and analyzed the network properties of the brain with two approaches, independent component analysis (ICA) and graph theoretical analysis (GTA). The GTA suggested that the whole-brain network is topologically stable across conditions. The ICA revealed a network comprising the supplementary motor area (SMA), left inferior frontal gyrus, left middle temporal gyrus, left caudate nucleus, and left angular gyrus, which was modulated by the incongruity of sentence ending. Furthermore, the GTA specified that the connections between the left SMA and left caudate nucleus as well as that between the left caudate nucleus and right thalamus were stronger in response to incongruent vs. congruent endings. Copyright © 2012 Wiley Periodicals, Inc.

  10. A Novel Power-Saving Transmission Scheme for Multiple-Component-Carrier Cellular Systems

    Directory of Open Access Journals (Sweden)

    Yao-Liang Chung

    2016-04-01

    Full Text Available As mobile data traffic levels have increased exponentially, resulting in rising energy costs in recent years, the demand for and development of green communication technologies has resulted in various energy-saving designs for cellular systems. At the same time, recent technological advances have allowed multiple component carriers (CCs to be simultaneously utilized in a base station (BS, a development that has made the energy consumption of BSs a matter of increasing concern. To help address this concern, herein we propose a novel scheme aimed at efficiently minimizing the power consumption of BS transceivers during transmission, while still ensuring good service quality and fairness for users. Specifically, the scheme utilizes the dynamic activation/deactivation of CCs during data transmission to increase power usage efficiency. To test its effectiveness, the proposed scheme was applied to a model consisting of a BS with orthogonal frequency division multiple access-based CCs in a downlink transmission environment. The results indicated that, given periods of relatively light traffic loads, the total power consumption of the proposed scheme is significantly lower than that of schemes in which all the CCs of a BS are constantly activated, suggesting the scheme’s potential for reducing both energy costs and carbon dioxide emissions.

  11. A Comparison of Mangrove Canopy Height Using Multiple Independent Measurements from Land, Air, and Space

    Science.gov (United States)

    Lagomasino, David; Fatoyinbo, Temilola; Lee, SeungKuk; Feliciano, Emanuelle; Trettin, Carl; Simard, Marc

    2016-01-01

    Canopy height is one of the strongest predictors of biomass and carbon in forested ecosystems. Additionally, mangrove ecosystems represent one of the most concentrated carbon reservoirs that are rapidly degrading as a result of deforestation, development, and hydrologic manipulation. Therefore, the accuracy of Canopy Height Models (CHM) over mangrove forest can provide crucial information for monitoring and verification protocols. We compared four CHMs derived from independent remotely sensed imagery and identified potential errors and bias between measurement types. CHMs were derived from three spaceborne datasets; Very-High Resolution (VHR) stereophotogrammetry, TerraSAR-X add-on for Digital Elevation Measurement (DEM), and Shuttle Radar Topography Mission (TanDEM-X), and lidar data which was acquired from an airborne platform. Each dataset exhibited different error characteristics that were related to spatial resolution, sensitivities of the sensors, and reference frames. Canopies over 10 meters were accurately predicted by all CHMs while the distributions of canopy height were best predicted by the VHR CHM. Depending on the guidelines and strategies needed for monitoring and verification activities, coarse resolution CHMs could be used to track canopy height at regional and global scales with finer resolution imagery used to validate and monitor critical areas undergoing rapid changes.

  12. Tempo and mode of performance evolution across multiple independent origins of adhesive toe pads in lizards.

    Science.gov (United States)

    Hagey, Travis J; Uyeda, Josef C; Crandell, Kristen E; Cheney, Jorn A; Autumn, Kellar; Harmon, Luke J

    2017-10-01

    Understanding macroevolutionary dynamics of trait evolution is an important endeavor in evolutionary biology. Ecological opportunity can liberate a trait as it diversifies through trait space, while genetic and selective constraints can limit diversification. While many studies have examined the dynamics of morphological traits, diverse morphological traits may yield the same or similar performance and as performance is often more proximately the target of selection, examining only morphology may give an incomplete understanding of evolutionary dynamics. Here, we ask whether convergent evolution of pad-bearing lizards has followed similar evolutionary dynamics, or whether independent origins are accompanied by unique constraints and selective pressures over macroevolutionary time. We hypothesized that geckos and anoles each have unique evolutionary tempos and modes. Using performance data from 59 species, we modified Brownian motion (BM) and Ornstein-Uhlenbeck (OU) models to account for repeated origins estimated using Bayesian ancestral state reconstructions. We discovered that adhesive performance in geckos evolved in a fashion consistent with Brownian motion with a trend, whereas anoles evolved in bounded performance space consistent with more constrained evolution (an Ornstein-Uhlenbeck model). Our results suggest that convergent phenotypes can have quite distinctive evolutionary patterns, likely as a result of idiosyncratic constraints or ecological opportunities. © 2017 The Author(s). Evolution © 2017 The Society for the Study of Evolution.

  13. A 2.9 ps equivalent resolution interpolating time counter based on multiple independent coding lines

    International Nuclear Information System (INIS)

    Szplet, R; Jachna, Z; Kwiatkowski, P; Rozyc, K

    2013-01-01

    We present the design, operation and test results of a time counter that has an equivalent resolution of 2.9 ps, a measurement uncertainty at the level of 6 ps, and a measurement range of 10 s. The time counter has been implemented in a general-purpose reprogrammable device Spartan-6 (Xilinx). To obtain both high precision and wide measurement range the counting of periods of a reference clock is combined with a two-stage interpolation within a single period of the clock signal. The interpolation involves a four-phase clock in the first interpolation stage (FIS) and an equivalent coding line (ECL) in the second interpolation stage (SIS). The ECL is created as a compound of independent discrete time coding lines (TCL). The number of TCLs used to create the virtual ECL has an effect on its resolution. We tested ECLs made from up to 16 TCLs, but the idea may be extended to a larger number of lines. In the presented time counter the coarse resolution of the counting method equal to 2 ns (period of the 500 MHz reference clock) is firstly improved fourfold in the FIS and next even more than 400 times in the SIS. The proposed solution allows us to overcome the technological limitation in achievable resolution and improve the precision of conversion of integrated interpolators based on tapped delay lines. (paper)

  14. Multiple independent regulatory pathways control UBI4 expression after heat shock in Saccharomyces cerevisiae.

    Science.gov (United States)

    Simon, J R; Treger, J M; McEntee, K

    1999-02-01

    Transcription of the polyubiquitin gene UBI4 of Saccharomyces cerevisiae is strongly induced by a variety of environmental stresses, such as heat shock, nutrient depletion and exposure to DNA-damaging agents. This transcriptional response of UBI4 is likely to be the primary mechanism for increasing the pool of ubiquitin for degradation of stress-damaged proteins. Deletion and promoter fusion studies of the 5' regulatory sequences indicated that two different elements, heat shock elements (HSEs) and stress response element (STREs), contributed independently to heat shock regulation of the UBI4 gene. In the absence of HSEs, STRE sequences localized to the intervals -264 to -238 and -215 to -183 were needed for stress control of transcription after heat shock. Site-directed mutagenesis of the STRE (AG4) at -252 to -248 abolished heat shock induction of UBI4 transcription. Northern analysis demonstrated that cells containing either a temperature-sensitive HSF or non-functional Msn2p/Msn4p transcription factors induced high levels of UBI4 transcripts after heat shock. In cells deficient in both heat stress pathways, heat-induced UBI4 transcript levels were considerably lower but not abolished, suggesting a role for another factor(s) in stress control of its expression.

  15. Multiple independent origins of mitochondrial control region duplications in the order Psittaciformes

    Science.gov (United States)

    Schirtzinger, Erin E.; Tavares, Erika S.; Gonzales, Lauren A.; Eberhard, Jessica R.; Miyaki, Cristina Y.; Sanchez, Juan J.; Hernandez, Alexis; Müeller, Heinrich; Graves, Gary R.; Fleischer, Robert C.; Wright, Timothy F.

    2012-01-01

    Mitochondrial genomes are generally thought to be under selection for compactness, due to their small size, consistent gene content, and a lack of introns or intergenic spacers. As more animal mitochondrial genomes are fully sequenced, rearrangements and partial duplications are being identified with increasing frequency, particularly in birds (Class Aves). In this study, we investigate the evolutionary history of mitochondrial control region states within the avian order Psittaciformes (parrots and cockatoos). To this aim, we reconstructed a comprehensive multi-locus phylogeny of parrots, used PCR of three diagnostic fragments to classify the mitochondrial control region state as single or duplicated, and mapped these states onto the phylogeny. We further sequenced 44 selected species to validate these inferences of control region state. Ancestral state reconstruction using a range of weighting schemes identified six independent origins of mitochondrial control region duplications within Psittaciformes. Analysis of sequence data showed that varying levels of mitochondrial gene and tRNA homology and degradation were present within a given clade exhibiting duplications. Levels of divergence between control regions within an individual varied from 0–10.9% with the differences occurring mainly between 51 and 225 nucleotides 3′ of the goose hairpin in domain I. Further investigations into the fates of duplicated mitochondrial genes, the potential costs and benefits of having a second control region, and the complex relationship between evolutionary rates, selection, and time since duplication are needed to fully explain these patterns in the mitochondrial genome. PMID:22543055

  16. Multiple independent structural dynamic events in the evolution of snake mitochondrial genomes.

    Science.gov (United States)

    Qian, Lifu; Wang, Hui; Yan, Jie; Pan, Tao; Jiang, Shanqun; Rao, Dingqi; Zhang, Baowei

    2018-05-10

    Mitochondrial DNA sequences have long been used in phylogenetic studies. However, little attention has been paid to the changes in gene arrangement patterns in the snake's mitogenome. Here, we analyzed the complete mitogenome sequences and structures of 65 snake species from 14 families and examined their structural patterns, organization and evolution. Our purpose was to further investigate the evolutionary implications and possible rearrangement mechanisms of the mitogenome within snakes. In total, eleven types of mitochondrial gene arrangement patterns were detected (Type I, II, III, III-A, III-B, III-B1, III-C, III-D, III-E, III-F, III-G), with mitochondrial genome rearrangements being a major trend in snakes, especially in Alethinophidia. In snake mitogenomes, the rearrangements mainly involved three processes, gene loss, translocation and duplication. Within Scolecophidia, the O L was lost several times in Typhlopidae and Leptotyphlopidae, but persisted as a plesiomorphy in the Alethinophidia. Duplication of the control region and translocation of the tRNA Leu gene are two visible features in Alethinophidian mitochondrial genomes. Independently and stochastically, the duplication of pseudo-Pro (P*) emerged in seven different lineages of unequal size in three families, indicating that the presence of P* was a polytopic event in the mitogenome. The WANCY tRNA gene cluster and the control regions and their adjacent segments were hotspots for mitogenome rearrangement. Maintenance of duplicate control regions may be the source for snake mitogenome structural diversity.

  17. Multiple independent colonization of the Canary Islands by the winged grasshopper genus Sphingonotus Fieber, 1852.

    Science.gov (United States)

    Husemann, Martin; Deppermann, Jana; Hochkirch, Axel

    2014-12-01

    Volcanic archipelagos represent ideal systems to study processes of colonization, differentiation and speciation. The Canary Islands are one of the best studied archipelagos, being composed of seven main islands with a well-known geological history. Most taxa have colonized these islands stepwise from the African or Iberian mainland from east to west, following their geological origin as well as the predominating wind direction and ocean currents. Furthermore, within-island radiations have been reported for several taxa. The grasshopper genus Sphingonotus is species-rich and occurs with nine fully winged species on the Canary Islands, seven of which are endemic to single or few islands. We inferred a phylogeny of these species and their North African and Iberian relatives based upon sequences of three mitochondrial genes and one nuclear gene of 136 specimens. Surprisingly, our results suggest that almost all Sphingonotus species colonized the archipelago independently from the mainland and nearly no inter-island colonization occurred. Despite their strong flight capabilities, only one pair of endemic species are closely related (S. sublaevis from Gran Canary and S. pachecoi from Lanzarote). Moreover, no within-island speciation events were detected. We hypothesize that passive wind dispersal from the African mainland was the main driver of the colonization process and that most Sphingonotus species are not able to cover inter-island distances by active flight. This, together with strong intrageneric niche overlap might explain the lack of within-island speciation in this taxon. Copyright © 2014 Elsevier Inc. All rights reserved.

  18. Multiple independent variants at the TERT locus are associated with telomere length and risks of breast and ovarian cancer

    OpenAIRE

    Bojesen, Stig E; Pooley, Karen A; Johnatty, Sharon E; Beesley, Jonathan; Michailidou, Kyriaki; Tyrer, Jonathan P; Edwards, Stacey L; Pickett, Hilda A; Shen, Howard C; Smart, Chanel E; Hillman, Kristine M; Mai, Phuong L; Lawrenson, Kate; Stutz, Michael D; Lu, Yi

    2013-01-01

    TERT-locus single nucleotide polymorphisms (SNPs) and leucocyte telomere measures are reportedly associated with risks of multiple cancers. Using the iCOGs chip, we analysed ~480 TERT-locus SNPs in breast (n=103,991), ovarian (n=39,774) and BRCA1 mutation carrier (11,705) cancer cases and controls. 53,724 participants have leucocyte telomere measures. Most associations cluster into three independent peaks. Peak 1 SNP rs2736108 minor allele associates with longer telomeres (P=5.8×10−7), reduce...

  19. Quantitative evaluation of deep and shallow tissue layers' contribution to fNIRS signal using multi-distance optodes and independent component analysis.

    Science.gov (United States)

    Funane, Tsukasa; Atsumori, Hirokazu; Katura, Takusige; Obata, Akiko N; Sato, Hiroki; Tanikawa, Yukari; Okada, Eiji; Kiguchi, Masashi

    2014-01-15

    To quantify the effect of absorption changes in the deep tissue (cerebral) and shallow tissue (scalp, skin) layers on functional near-infrared spectroscopy (fNIRS) signals, a method using multi-distance (MD) optodes and independent component analysis (ICA), referred to as the MD-ICA method, is proposed. In previous studies, when the signal from the shallow tissue layer (shallow signal) needs to be eliminated, it was often assumed that the shallow signal had no correlation with the signal from the deep tissue layer (deep signal). In this study, no relationship between the waveforms of deep and shallow signals is assumed, and instead, it is assumed that both signals are linear combinations of multiple signal sources, which allows the inclusion of a "shared component" (such as systemic signals) that is contained in both layers. The method also assumes that the partial optical path length of the shallow layer does not change, whereas that of the deep layer linearly increases along with the increase of the source-detector (S-D) distance. Deep- and shallow-layer contribution ratios of each independent component (IC) are calculated using the dependence of the weight of each IC on the S-D distance. Reconstruction of deep- and shallow-layer signals are performed by the sum of ICs weighted by the deep and shallow contribution ratio. Experimental validation of the principle of this technique was conducted using a dynamic phantom with two absorbing layers. Results showed that our method is effective for evaluating deep-layer contributions even if there are high correlations between deep and shallow signals. Next, we applied the method to fNIRS signals obtained on a human head with 5-, 15-, and 30-mm S-D distances during a verbal fluency task, a verbal working memory task (prefrontal area), a finger tapping task (motor area), and a tetrametric visual checker-board task (occipital area) and then estimated the deep-layer contribution ratio. To evaluate the signal separation

  20. Progressive Disintegration of Brain Networking from Normal Aging to Alzheimer Disease: Analysis of Independent Components of 18F-FDG PET Data.

    Science.gov (United States)

    Pagani, Marco; Giuliani, Alessandro; Öberg, Johanna; De Carli, Fabrizio; Morbelli, Silvia; Girtler, Nicola; Arnaldi, Dario; Accardo, Jennifer; Bauckneht, Matteo; Bongioanni, Francesca; Chincarini, Andrea; Sambuceti, Gianmario; Jonsson, Cathrine; Nobili, Flavio

    2017-07-01

    Brain connectivity has been assessed in several neurodegenerative disorders investigating the mutual correlations between predetermined regions or nodes. Selective breakdown of brain networks during progression from normal aging to Alzheimer disease dementia (AD) has also been observed. Methods: We implemented independent-component analysis of 18 F-FDG PET data in 5 groups of subjects with cognitive states ranging from normal aging to AD-including mild cognitive impairment (MCI) not converting or converting to AD-to disclose the spatial distribution of the independent components in each cognitive state and their accuracy in discriminating the groups. Results: We could identify spatially distinct independent components in each group, with generation of local circuits increasing proportionally to the severity of the disease. AD-specific independent components first appeared in the late-MCI stage and could discriminate converting MCI and AD from nonconverting MCI with an accuracy of 83.5%. Progressive disintegration of the intrinsic networks from normal aging to MCI to AD was inversely proportional to the conversion time. Conclusion: Independent-component analysis of 18 F-FDG PET data showed a gradual disruption of functional brain connectivity with progression of cognitive decline in AD. This information might be useful as a prognostic aid for individual patients and as a surrogate biomarker in intervention trials. © 2017 by the Society of Nuclear Medicine and Molecular Imaging.

  1. Multiple independent insertions of 5S rRNA genes in the spliced-leader gene family of trypanosome species.

    Science.gov (United States)

    Beauparlant, Marc A; Drouin, Guy

    2014-02-01

    Analyses of the 5S rRNA genes found in the spliced-leader (SL) gene repeat units of numerous trypanosome species suggest that such linkages were not inherited from a common ancestor, but were the result of independent 5S rRNA gene insertions. In trypanosomes, 5S rRNA genes are found either in the tandemly repeated units coding for SL genes or in independent tandemly repeated units. Given that trypanosome species where 5S rRNA genes are within the tandemly repeated units coding for SL genes are phylogenetically related, one might hypothesize that this arrangement is the result of an ancestral insertion of 5S rRNA genes into the tandemly repeated SL gene family of trypanosomes. Here, we use the types of 5S rRNA genes found associated with SL genes, the flanking regions of the inserted 5S rRNA genes and the position of these insertions to show that most of the 5S rRNA genes found within SL gene repeat units of trypanosome species were not acquired from a common ancestor but are the results of independent insertions. These multiple 5S rRNA genes insertion events in trypanosomes are likely the result of frequent founder events in different hosts and/or geographical locations in species having short generation times.

  2. Independent and inverse association of healthcare utilisation with physical activity in older adults with multiple chronic conditions.

    Science.gov (United States)

    Liu-Ambrose, T Y L; Ashe, M C; Marra, C

    2010-11-01

    In this study, whether physical activity is independently associated with direct healthcare costs in community-dwelling older adults with multiple chronic conditions was examined. Cross-sectional analysis. Research laboratory. 299 community-dwelling men and women volunteers aged 65 years and older with chronic conditions. None. Primary dependent variable was direct healthcare costs incurred in the previous 3 months. Participants completed the Health Resource Utilisation (HRU) questionnaire. To estimate HRU, direct costs in the previous 3 months were calculated using the three-party payer perspective of the British Columbia Ministry of Health, deemed representative of the Canadian healthcare system costs. For medications, the Retail Pharmacy Dispensed prescription cost tables were used. Primary independent variables were (1) self-report current level of physical activity as assessed by the Physical Activity Scale for Individuals with Physical Disabilities (PASIPD) and (2) general balance and mobility as assessed by the National Institute on Aging Balance Scale. The mean number of chronic conditions per participant was six. Current level of physical activity was independently and inversely associated with HRU. Age, sex, number of chronic conditions, global cognitive function, body mass index, and general balance and mobility together accounted for 24.3% of the total variance. Adding the PASIPD score resulted in an R2 change of 3.3% and significantly improved the model. The total variance accounted by the final model was 27.6%. Physical activity promotion may reduce healthcare costs in older adults with chronic conditions.

  3. Divergent Immunomodulation Capacity of Individual Myelin Peptides—Components of Liposomal Therapeutic against Multiple Sclerosis

    Directory of Open Access Journals (Sweden)

    Vilena V. Ivanova

    2017-10-01

    Full Text Available Multiple sclerosis (MS is an autoimmune disease characterized by demyelination and consequent neuron injury. Although the pathogenesis of MS is largely unknown, a breach in immune self-tolerance to myelin followed by development of autoreactive encephalitogenic T cells is suggested to play the central role. The myelin basic protein (MBP is believed to be one of the main targets for autoreactive lymphocytes. Recently, immunodominant MBP peptides encapsulated into the mannosylated liposomes, referred as Xemys, were shown to suppress development of experimental autoimmune encephalomyelitis, a rodent model of MS, and furthermore passed the initial stage of clinical trials. Here, we investigated the role of individual polypeptide components [MBP peptides 46–62 (GH17, 124–139 (GK16, and 147–170 (QR24] of this liposomal peptide therapeutic in cytokine release and activation of immune cells from MS patients and healthy donors. The overall effects were assessed using peripheral blood mononuclear cells (PBMCs, whereas alterations in antigen-presenting capacities were studied utilizing plasmacytoid dendritic cells (pDCs. Among three MBP-immunodominant peptides, QR24 and GK16 activated leukocytes, while GH17 was characterized by an immunosuppressive effect. Peptides QR24 and GK16 upregulated CD4 over CD8 T cells and induced proliferation of CD25+ cells, whereas GH17 decreased the CD4/CD8 T cell ratio and had limited effects on CD25+ T cells. Accordingly, components of liposomal peptide therapeutic differed in upregulation of cytokines upon addition to PBMCs and pDCs. Peptide QR24 was evidently more effective in upregulation of pro-inflammatory cytokines, whereas GH17 significantly increased production of IL-10 through treated cells. Altogether, these data suggest a complexity of action of the liposomal peptide therapeutic that does not seem to involve simple helper T cells (Th-shift but rather the rebalancing of the immune system.

  4. Classification of Hypertrophy of Labia Minora: Consideration of a Multiple Component Approach.

    Science.gov (United States)

    González, Pablo I

    2015-11-01

    Labia minora hypertrophy of unknown and under-reported incidence in the general population is considered a variant of normal anatomy. Its origin is multi-factorial including genetic, hormonal, and infectious factors, and voluntary elongation of the labiae minorae in some cultures. Consults with patients bothered by this condition have been increasing with patients complaining of poor aesthetics and symptoms such as difficulty with vaginal secretions, vulvovaginitis, chronic irritation, and superficial dyspareunia, all of which can have a negative effect on these patients' sexuality and self esteem. Surgical management of labial hypertrophy is an option for women with these physical complaints or aesthetic issues. Labia minora hypertrophy can consist of multiple components, including the clitoral hood, lateral prepuce, frenulum, and the body of the labia minora. To date, there is not a consensus in the literature with respect to the classification and definition of varying grades of hypertrophy, aside from measurement of the length in centimeters. In order to offer patients the most appropriate surgical technique, an objective and understandable classification that can be used as part of the preoperative evaluation is necessary. Such a classification should have the aim of offering patients the best cosmetic and functional results with the fewest complications.

  5. Raman hyperspectral imaging in conjunction with independent component analysis as a forensic tool for explosive analysis: The case of an ATM explosion.

    Science.gov (United States)

    Almeida, Mariana Ramos; Logrado, Lucio Paulo Lima; Zacca, Jorge Jardim; Correa, Deleon Nascimento; Poppi, Ronei Jesus

    2017-11-01

    In this work, Raman hyperspectral imaging, in conjunction with independent component analysis, was employed as an analytical methodology to detect an ammonium nitrate fuel oil (ANFO) explosive in banknotes after an ATM explosion experiment. The proposed methodology allows for the identification of the ANFO explosive without sample preparation or destroying the sample, at quantities as small as 70μgcm -2 . The explosive was identified following ICA data decomposition by the characteristic nitrate band at 1044cm -1 . The use of Raman hyperspectral imaging and independent component analysis shows great potential for identifying forensic samples by providing chemical and spatial information. Copyright © 2017 Elsevier B.V. All rights reserved.

  6. Multi-Temporal Independent Component Analysis and Landsat 8 for Delineating Maximum Extent of the 2013 Colorado Front Range Flood

    Directory of Open Access Journals (Sweden)

    Stephen M. Chignell

    2015-07-01

    Full Text Available Maximum flood extent—a key data need for disaster response and mitigation—is rarely quantified due to storm-related cloud cover and the low temporal resolution of optical sensors. While change detection approaches can circumvent these issues through the identification of inundated land and soil from post-flood imagery, their accuracy can suffer in the narrow and complex channels of increasingly developed and heterogeneous floodplains. This study explored the utility of the Operational Land Imager (OLI and Independent Component Analysis (ICA for addressing these challenges in the unprecedented 2013 Flood along the Colorado Front Range, USA. Pre- and post-flood images were composited and transformed with an ICA to identify change classes. Flooded pixels were extracted using image segmentation, and the resulting flood layer was refined with cloud and irrigated agricultural masks derived from the ICA. Visual assessment against aerial orthophotography showed close agreement with high water marks and scoured riverbanks, and a pixel-to-pixel validation with WorldView-2 imagery captured near peak flow yielded an overall accuracy of 87% and Kappa of 0.73. Additional tests showed a twofold increase in flood class accuracy over the commonly used modified normalized water index. The approach was able to simultaneously distinguish flood-related water and soil moisture from pre-existing water bodies and other spectrally similar classes within the narrow and braided channels of the study site. This was accomplished without the use of post-processing smoothing operations, enabling the important preservation of nuanced inundation patterns. Although flooding beneath moderate and sparse riparian vegetation canopy was captured, dense vegetation cover and paved regions of the floodplain were main sources of omission error, and commission errors occurred primarily in pixels of mixed land use and along the flood edge. Nevertheless, the unsupervised nature of ICA

  7. Response of secondary production and its components to multiple stressors in nematode field populations.

    NARCIS (Netherlands)

    Doroszuk, A.; Brake, te E.; Crespo-Gonzalez, D.; Kammenga, J.E.

    2007-01-01

    Realistic measures of the impact of individual or multiple stressors are important for ecological risk assessment. Although multiple anthropogenic stressors are common in human-dominated environments, knowledge of their influence on functional population parameters such as secondary production (P)

  8. Independent clonal origin of multiple uterine leiomyomas that was determined by X chromosome inactivation and microsatellite analysis

    DEFF Research Database (Denmark)

    Canevari, Renata A; Pontes, Anaglória; Rosa, Fabíola E

    2005-01-01

    OBJECTIVE: In an attempt to clarify the clonality and genetic relationships that are involved in the tumorigenesis of uterine leiomyomas, we used a total of 43 multiple leiomyomas from 14 patients and analyzed the allelic status with 15 microsatellite markers and X chromosome inactivation analysis...... of the 9 of 12 informative patients; different inactivation patterns were observed in 3 cases. CONCLUSION: Our data support the concept that uterine leiomyomas are derived from a single cell but are generated independently in the uterus. Loss of heterozygosity findings at 7p22-15 are consistent...... with previous data that suggested the relevance of chromosomal aberrations at 7p that were involved in individual uterine leiomyomas....

  9. Two adults with multiple disabilities use a computer-aided telephone system to make phone calls independently.

    Science.gov (United States)

    Lancioni, Giulio E; O'Reilly, Mark F; Singh, Nirbhay N; Sigafoos, Jeff; Oliva, Doretta; Alberti, Gloria; Lang, Russell

    2011-01-01

    This study extended the assessment of a newly developed computer-aided telephone system with two participants (adults) who presented with blindness or severe visual impairment and motor or motor and intellectual disabilities. For each participant, the study was carried out according to an ABAB design, in which the A represented baseline phases and the B represented intervention phases, during which the special telephone system was available. The system involved among others a net-book computer provided with specific software, a global system for mobile communication modem, and a microswitch. Both participants learned to use the system very rapidly and managed to make phone calls independently to a variety of partners such as family members, friends and staff personnel. The results were discussed in terms of the technology under investigation (its advantages, drawbacks, and need of improvement) and the social-communication impact it can make for persons with multiple disabilities. Copyright © 2011 Elsevier Ltd. All rights reserved.

  10. Multiple amino acid sequence alignment nitrogenase component 1: insights into phylogenetics and structure-function relationships.

    Directory of Open Access Journals (Sweden)

    James B Howard

    Full Text Available Amino acid residues critical for a protein's structure-function are retained by natural selection and these residues are identified by the level of variance in co-aligned homologous protein sequences. The relevant residues in the nitrogen fixation Component 1 α- and β-subunits were identified by the alignment of 95 protein sequences. Proteins were included from species encompassing multiple microbial phyla and diverse ecological niches as well as the nitrogen fixation genotypes, anf, nif, and vnf, which encode proteins associated with cofactors differing at one metal site. After adjusting for differences in sequence length, insertions, and deletions, the remaining >85% of the sequence co-aligned the subunits from the three genotypes. Six Groups, designated Anf, Vnf , and Nif I-IV, were assigned based upon genetic origin, sequence adjustments, and conserved residues. Both subunits subdivided into the same groups. Invariant and single variant residues were identified and were defined as "core" for nitrogenase function. Three species in Group Nif-III, Candidatus Desulforudis audaxviator, Desulfotomaculum kuznetsovii, and Thermodesulfatator indicus, were found to have a seleno-cysteine that replaces one cysteinyl ligand of the 8Fe:7S, P-cluster. Subsets of invariant residues, limited to individual groups, were identified; these unique residues help identify the gene of origin (anf, nif, or vnf yet should not be considered diagnostic of the metal content of associated cofactors. Fourteen of the 19 residues that compose the cofactor pocket are invariant or single variant; the other five residues are highly variable but do not correlate with the putative metal content of the cofactor. The variable residues are clustered on one side of the cofactor, away from other functional centers in the three dimensional structure. Many of the invariant and single variant residues were not previously recognized as potentially critical and their identification

  11. Fine-scale mapping of 8q24 locus identifies multiple independent risk variants for breast cancer.

    Science.gov (United States)

    Shi, Jiajun; Zhang, Yanfeng; Zheng, Wei; Michailidou, Kyriaki; Ghoussaini, Maya; Bolla, Manjeet K; Wang, Qin; Dennis, Joe; Lush, Michael; Milne, Roger L; Shu, Xiao-Ou; Beesley, Jonathan; Kar, Siddhartha; Andrulis, Irene L; Anton-Culver, Hoda; Arndt, Volker; Beckmann, Matthias W; Zhao, Zhiguo; Guo, Xingyi; Benitez, Javier; Beeghly-Fadiel, Alicia; Blot, William; Bogdanova, Natalia V; Bojesen, Stig E; Brauch, Hiltrud; Brenner, Hermann; Brinton, Louise; Broeks, Annegien; Brüning, Thomas; Burwinkel, Barbara; Cai, Hui; Canisius, Sander; Chang-Claude, Jenny; Choi, Ji-Yeob; Couch, Fergus J; Cox, Angela; Cross, Simon S; Czene, Kamila; Darabi, Hatef; Devilee, Peter; Droit, Arnaud; Dork, Thilo; Fasching, Peter A; Fletcher, Olivia; Flyger, Henrik; Fostira, Florentia; Gaborieau, Valerie; García-Closas, Montserrat; Giles, Graham G; Guenel, Pascal; Haiman, Christopher A; Hamann, Ute; Hartman, Mikael; Miao, Hui; Hollestelle, Antoinette; Hopper, John L; Hsiung, Chia-Ni; Ito, Hidemi; Jakubowska, Anna; Johnson, Nichola; Torres, Diana; Kabisch, Maria; Kang, Daehee; Khan, Sofia; Knight, Julia A; Kosma, Veli-Matti; Lambrechts, Diether; Li, Jingmei; Lindblom, Annika; Lophatananon, Artitaya; Lubinski, Jan; Mannermaa, Arto; Manoukian, Siranoush; Le Marchand, Loic; Margolin, Sara; Marme, Frederik; Matsuo, Keitaro; McLean, Catriona; Meindl, Alfons; Muir, Kenneth; Neuhausen, Susan L; Nevanlinna, Heli; Nord, Silje; Børresen-Dale, Anne-Lise; Olson, Janet E; Orr, Nick; van den Ouweland, Ans M W; Peterlongo, Paolo; Putti, Thomas Choudary; Rudolph, Anja; Sangrajrang, Suleeporn; Sawyer, Elinor J; Schmidt, Marjanka K; Schmutzler, Rita K; Shen, Chen-Yang; Hou, Ming-Feng; Shrubsole, Matha J; Southey, Melissa C; Swerdlow, Anthony; Teo, Soo Hwang; Thienpont, Bernard; Toland, Amanda E; Tollenaar, Robert A E M; Tomlinson, Ian; Truong, Therese; Tseng, Chiu-Chen; Wen, Wanqing; Winqvist, Robert; Wu, Anna H; Yip, Cheng Har; Zamora, Pilar M; Zheng, Ying; Floris, Giuseppe; Cheng, Ching-Yu; Hooning, Maartje J; Martens, John W M; Seynaeve, Caroline; Kristensen, Vessela N; Hall, Per; Pharoah, Paul D P; Simard, Jacques; Chenevix-Trench, Georgia; Dunning, Alison M; Antoniou, Antonis C; Easton, Douglas F; Cai, Qiuyin; Long, Jirong

    2016-09-15

    Previous genome-wide association studies among women of European ancestry identified two independent breast cancer susceptibility loci represented by single nucleotide polymorphisms (SNPs) rs13281615 and rs11780156 at 8q24. A fine-mapping study across 2.06 Mb (chr8:127,561,724-129,624,067, hg19) in 55,540 breast cancer cases and 51,168 controls within the Breast Cancer Association Consortium was conducted. Three additional independent association signals in women of European ancestry, represented by rs35961416 (OR = 0.95, 95% CI = 0.93-0.97, conditional p = 5.8 × 10(-6) ), rs7815245 (OR = 0.94, 95% CI = 0.91-0.96, conditional p = 1.1 × 10(-6) ) and rs2033101 (OR = 1.05, 95% CI = 1.02-1.07, conditional p = 1.1 × 10(-4) ) were found. Integrative analysis using functional genomic data from the Roadmap Epigenomics, the Encyclopedia of DNA Elements project, the Cancer Genome Atlas and other public resources implied that SNPs rs7815245 in Signal 3, and rs1121948 in Signal 5 (in linkage disequilibrium with rs11780156, r(2)  = 0.77), were putatively functional variants for two of the five independent association signals. The results highlighted multiple 8q24 variants associated with breast cancer susceptibility in women of European ancestry. © 2016 UICC.

  12. A service component-based accounting and charging architecture to support interim mechanisms across multiple domains

    NARCIS (Netherlands)

    Le, M. van; Beijnum, B.J.F. van; Huitema, G.B.

    2004-01-01

    Today, telematics services are often compositions of different chargeable service components offered by different service providers. To enhance component-based accounting and charging, the service composition information is used to match with the corresponding charging structure of a service

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

    Science.gov (United States)

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

    2000-06-01

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

  14. Different cellular effects of four anti-inflammatory eye drops on human corneal epithelial cells: independent in active components

    OpenAIRE

    Qu, Mingli; Wang, Yao; Yang, Lingling; Zhou, Qingjun

    2011-01-01

    Purpose To evaluate and compare the cellular effects of four commercially available anti-inflammatory eye drops and their active components on human corneal epithelial cells (HCECs) in vitro. Methods The cellular effects of four eye drops (Bromfenac Sodium Hydrate Eye Drops, Pranoprofen Eye Drops, Diclofenac Sodium Eye Drops, and Tobramycin & Dex Eye Drops) and their corresponding active components were evaluated in an HCEC line with five in vitro assays. Cell proliferation and migration were...

  15. 15 CFR 921.33 - Boundary changes, amendments to the management plan, and addition of multiple-site components.

    Science.gov (United States)

    2010-01-01

    ... management plan, and addition of multiple-site components. (a) Changes in the boundary of a Reserve and major changes to the final management plan, including state laws or regulations promulgated specifically for the... management plan change. Changes in the boundary of a Reserve involving the acquisition of properties not...

  16. A Service Component-based Accounting and Charging Architecture to Support Interim Mechanisms across Multiple Domains

    NARCIS (Netherlands)

    Le, V.M.; van Beijnum, Bernhard J.F.; Huitema, G.B.

    Today, telematics services are o Aen compositions of different chargeable service components offered by different service providers. To enhance component-based accounting and charging, the service composition information is used to match with the corresponding charging structure of a service

  17. Testing the Presence of Multiple Photometric Components in Nearby Early-type Galaxies Using SDSS

    Energy Technology Data Exchange (ETDEWEB)

    Oh, Semyeong; Greene, Jenny E. [Department of Astrophysical Sciences, Princeton University, Princeton, NJ 08544 (United States); Lackner, Claire N., E-mail: semyeong@astro.princeton.edu [Kavli Institute for the Physics and Mathematics of the Universe (WPI), Todai Institutes for Advanced Study, the University of Tokyo, Kashiwa (Japan)

    2017-02-10

    We investigate two-dimensional image decomposition of nearby, morphologically selected early-type galaxies (ETGs). We are motivated by recent observational evidence of significant size growth of quiescent galaxies and theoretical development advocating a two-phase formation scenario for ETGs. We find that a significant fraction of nearby ETGs show changes in isophotal shape that require multi-component models. The characteristic sizes of the inner and outer component are ∼3 and ∼15 kpc. The inner component lies on the mass–size relation of ETGs at z ∼ 0.25–0.75, while the outer component tends to be more elliptical and hints at a stochastic buildup process. We find real physical differences between single- and double-component ETGs, with double-component galaxies being younger and more metal-rich. The fraction of double-component ETGs increases with increasing σ and decreases in denser environments. We hypothesize that double-component systems were able to accrete gas and small galaxies until later times, boosting their central densities, building up their outer parts, and lowering their typical central ages. In contrast, the oldest galaxies, perhaps due to residing in richer environments, have no remaining hints of their last accretion episode.

  18. A comparison on parameter-estimation methods in multiple regression analysis with existence of multicollinearity among independent variables

    Directory of Open Access Journals (Sweden)

    Hukharnsusatrue, A.

    2005-11-01

    Full Text Available The objective of this research is to compare multiple regression coefficients estimating methods with existence of multicollinearity among independent variables. The estimation methods are Ordinary Least Squares method (OLS, Restricted Least Squares method (RLS, Restricted Ridge Regression method (RRR and Restricted Liu method (RL when restrictions are true and restrictions are not true. The study used the Monte Carlo Simulation method. The experiment was repeated 1,000 times under each situation. The analyzed results of the data are demonstrated as follows. CASE 1: The restrictions are true. In all cases, RRR and RL methods have a smaller Average Mean Square Error (AMSE than OLS and RLS method, respectively. RRR method provides the smallest AMSE when the level of correlations is high and also provides the smallest AMSE for all level of correlations and all sample sizes when standard deviation is equal to 5. However, RL method provides the smallest AMSE when the level of correlations is low and middle, except in the case of standard deviation equal to 3, small sample sizes, RRR method provides the smallest AMSE.The AMSE varies with, most to least, respectively, level of correlations, standard deviation and number of independent variables but inversely with to sample size.CASE 2: The restrictions are not true.In all cases, RRR method provides the smallest AMSE, except in the case of standard deviation equal to 1 and error of restrictions equal to 5%, OLS method provides the smallest AMSE when the level of correlations is low or median and there is a large sample size, but the small sample sizes, RL method provides the smallest AMSE. In addition, when error of restrictions is increased, OLS method provides the smallest AMSE for all level, of correlations and all sample sizes, except when the level of correlations is high and sample sizes small. Moreover, the case OLS method provides the smallest AMSE, the most RLS method has a smaller AMSE than

  19. Calcium-dependent and -independent binding of the pentraxin serum amyloid P component to glycosaminoglycans and amyloid proteins

    DEFF Research Database (Denmark)

    Danielsen, B; Sørensen, I J; Nybo, Mads

    1997-01-01

    precursor protein beta2M was observed. This binding was also enhanced at slightly acid pH, most pronounced at pH 5.0. The results of this study indicate that SAP can exhibit both Ca2(+)-dependent and -independent binding to ligands involved in amyloid fibril formation and that the binding is enhanced under...... and beta2M) by ELISA. An increase in the dose-dependent binding of SAP to heparan sulfate, AA-protein and beta2M was observed as the pH decreased from 8.0 to 5.0. Furthermore, a lower, but significant Ca2(+)-independent binding of SAP to heparan sulfate, dermatan sulfate, AA protein and the amyloid...

  20. Mass-flux subgrid-scale parameterization in analogy with multi-component flows: a formulation towards scale independence

    Directory of Open Access Journals (Sweden)

    J.-I. Yano

    2012-11-01

    Full Text Available A generalized mass-flux formulation is presented, which no longer takes a limit of vanishing fractional areas for subgrid-scale components. The presented formulation is applicable to a~situation in which the scale separation is still satisfied, but fractional areas occupied by individual subgrid-scale components are no longer small. A self-consistent formulation is presented by generalizing the mass-flux formulation under the segmentally-constant approximation (SCA to the grid–scale variabilities. The present formulation is expected to alleviate problems arising from increasing resolutions of operational forecast models without invoking more extensive overhaul of parameterizations.

    The present formulation leads to an analogy of the large-scale atmospheric flow with multi-component flows. This analogy allows a generality of including any subgrid-scale variability into the mass-flux parameterization under SCA. Those include stratiform clouds as well as cold pools in the boundary layer.

    An important finding under the present formulation is that the subgrid-scale quantities are advected by the large-scale velocities characteristic of given subgrid-scale components (large-scale subcomponent flows, rather than by the total large-scale flows as simply defined by grid-box average. In this manner, each subgrid-scale component behaves as if like a component of multi-component flows. This formulation, as a result, ensures the lateral interaction of subgrid-scale variability crossing the grid boxes, which are missing in the current parameterizations based on vertical one-dimensional models, and leading to a reduction of the grid-size dependencies in its performance. It is shown that the large-scale subcomponent flows are driven by large-scale subcomponent pressure gradients. The formulation, as a result, furthermore includes a self-contained description of subgrid-scale momentum transport.

    The main purpose of the present paper

  1. Different cellular effects of four anti-inflammatory eye drops on human corneal epithelial cells: independent in active components.

    Science.gov (United States)

    Qu, Mingli; Wang, Yao; Yang, Lingling; Zhou, Qingjun

    2011-01-01

    To evaluate and compare the cellular effects of four commercially available anti-inflammatory eye drops and their active components on human corneal epithelial cells (HCECs) in vitro. The cellular effects of four eye drops (Bromfenac Sodium Hydrate Eye Drops, Pranoprofen Eye Drops, Diclofenac Sodium Eye Drops, and Tobramycin & Dex Eye Drops) and their corresponding active components were evaluated in an HCEC line with five in vitro assays. Cell proliferation and migration were measured using 3-(4,5)-dimethylthiahiazo (-z-y1)-3 5-di-phenytetrazoliumromide (MTT) assay and transwell migration assay. Cell damage was determined with the lactate dehydrogenase (LDH) assay. Cell viability and median lethal time (LT₅₀) were measured by 7-amino-actinomycin D (7-AAD) staining and flow cytometry analysis. Cellular effects after exposure of HCECs to the four anti-inflammatory eye drops were concentration dependent. The differences of cellular toxicity on cell proliferation became significant at lower concentrations (Eye Drops showed significant increasing effects on cell damage and viability when compared with the other three solutions. Tobramycin & Dex Eye Drops inhibited the migration of HCECs significantly. Tobramycin & Dex Eye Drops showed the quickest effect on cell viability: the LT₅₀ was 3.28, 9.23, 10.38, and 23.80 min for Tobramycin & Dex Eye Drops, Diclofenac Sodium Eye Drops, Pranoprofen Eye Drops, and Bromfenac Sodium Hydrate Eye Drops, respectively. However, the comparisons of cellular toxicity revealed significant differences between the eye drops and their active components under the same concentration. The corneal epithelial toxicity differences among the active components of the four eye drops became significant as higher concentration (>0.020%). The four anti-inflammatory eye drops showed different cellular effects on HCECs, and the toxicity was not related with their active components, which provides new reference for the clinical application and drug

  2. Multiple independent variants at the TERT locus are associated with telomere length and risks of breast and ovarian cancer.

    Science.gov (United States)

    Bojesen, Stig E; Pooley, Karen A; Johnatty, Sharon E; Beesley, Jonathan; Michailidou, Kyriaki; Tyrer, Jonathan P; Edwards, Stacey L; Pickett, Hilda A; Shen, Howard C; Smart, Chanel E; Hillman, Kristine M; Mai, Phuong L; Lawrenson, Kate; Stutz, Michael D; Lu, Yi; Karevan, Rod; Woods, Nicholas; Johnston, Rebecca L; French, Juliet D; Chen, Xiaoqing; Weischer, Maren; Nielsen, Sune F; Maranian, Melanie J; Ghoussaini, Maya; Ahmed, Shahana; Baynes, Caroline; Bolla, Manjeet K; Wang, Qin; Dennis, Joe; McGuffog, Lesley; Barrowdale, Daniel; Lee, Andrew; Healey, Sue; Lush, Michael; Tessier, Daniel C; Vincent, Daniel; Bacot, Françis; Vergote, Ignace; Lambrechts, Sandrina; Despierre, Evelyn; Risch, Harvey A; González-Neira, Anna; Rossing, Mary Anne; Pita, Guillermo; Doherty, Jennifer A; Alvarez, Nuria; Larson, Melissa C; Fridley, Brooke L; Schoof, Nils; Chang-Claude, Jenny; Cicek, Mine S; Peto, Julian; Kalli, Kimberly R; Broeks, Annegien; Armasu, Sebastian M; Schmidt, Marjanka K; Braaf, Linde M; Winterhoff, Boris; Nevanlinna, Heli; Konecny, Gottfried E; Lambrechts, Diether; Rogmann, Lisa; Guénel, Pascal; Teoman, Attila; Milne, Roger L; Garcia, Joaquin J; Cox, Angela; Shridhar, Vijayalakshmi; Burwinkel, Barbara; Marme, Frederik; Hein, Rebecca; Sawyer, Elinor J; Haiman, Christopher A; Wang-Gohrke, Shan; Andrulis, Irene L; Moysich, Kirsten B; Hopper, John L; Odunsi, Kunle; Lindblom, Annika; Giles, Graham G; Brenner, Hermann; Simard, Jacques; Lurie, Galina; Fasching, Peter A; Carney, Michael E; Radice, Paolo; Wilkens, Lynne R; Swerdlow, Anthony; Goodman, Marc T; Brauch, Hiltrud; Garcia-Closas, Montserrat; Hillemanns, Peter; Winqvist, Robert; Dürst, Matthias; Devilee, Peter; Runnebaum, Ingo; Jakubowska, Anna; Lubinski, Jan; Mannermaa, Arto; Butzow, Ralf; Bogdanova, Natalia V; Dörk, Thilo; Pelttari, Liisa M; Zheng, Wei; Leminen, Arto; Anton-Culver, Hoda; Bunker, Clareann H; Kristensen, Vessela; Ness, Roberta B; Muir, Kenneth; Edwards, Robert; Meindl, Alfons; Heitz, Florian; Matsuo, Keitaro; du Bois, Andreas; Wu, Anna H; Harter, Philipp; Teo, Soo-Hwang; Schwaab, Ira; Shu, Xiao-Ou; Blot, William; Hosono, Satoyo; Kang, Daehee; Nakanishi, Toru; Hartman, Mikael; Yatabe, Yasushi; Hamann, Ute; Karlan, Beth Y; Sangrajrang, Suleeporn; Kjaer, Susanne Krüger; Gaborieau, Valerie; Jensen, Allan; Eccles, Diana; Høgdall, Estrid; Shen, Chen-Yang; Brown, Judith; Woo, Yin Ling; Shah, Mitul; Azmi, Mat Adenan Noor; Luben, Robert; Omar, Siti Zawiah; Czene, Kamila; Vierkant, Robert A; Nordestgaard, Børge G; Flyger, Henrik; Vachon, Celine; Olson, Janet E; Wang, Xianshu; Levine, Douglas A; Rudolph, Anja; Weber, Rachel Palmieri; Flesch-Janys, Dieter; Iversen, Edwin; Nickels, Stefan; Schildkraut, Joellen M; Silva, Isabel Dos Santos; Cramer, Daniel W; Gibson, Lorna; Terry, Kathryn L; Fletcher, Olivia; Vitonis, Allison F; van der Schoot, C Ellen; Poole, Elizabeth M; Hogervorst, Frans B L; Tworoger, Shelley S; Liu, Jianjun; Bandera, Elisa V; Li, Jingmei; Olson, Sara H; Humphreys, Keith; Orlow, Irene; Blomqvist, Carl; Rodriguez-Rodriguez, Lorna; Aittomäki, Kristiina; Salvesen, Helga B; Muranen, Taru A; Wik, Elisabeth; Brouwers, Barbara; Krakstad, Camilla; Wauters, Els; Halle, Mari K; Wildiers, Hans; Kiemeney, Lambertus A; Mulot, Claire; Aben, Katja K; Laurent-Puig, Pierre; Altena, Anne Mvan; Truong, Thérèse; Massuger, Leon F A G; Benitez, Javier; Pejovic, Tanja; Perez, Jose Ignacio Arias; Hoatlin, Maureen; Zamora, M Pilar; Cook, Linda S; Balasubramanian, Sabapathy P; Kelemen, Linda E; Schneeweiss, Andreas; Le, Nhu D; Sohn, Christof; Brooks-Wilson, Angela; Tomlinson, Ian; Kerin, Michael J; Miller, Nicola; Cybulski, Cezary; Henderson, Brian E; Menkiszak, Janusz; Schumacher, Fredrick; Wentzensen, Nicolas; Le Marchand, Loic; Yang, Hannah P; Mulligan, Anna Marie; Glendon, Gord; Engelholm, Svend Aage; Knight, Julia A; Høgdall, Claus K; Apicella, Carmel; Gore, Martin; Tsimiklis, Helen; Song, Honglin; Southey, Melissa C; Jager, Agnes; den Ouweland, Ans M Wvan; Brown, Robert; Martens, John W M; Flanagan, James M; Kriege, Mieke; Paul, James; Margolin, Sara; Siddiqui, Nadeem; Severi, Gianluca; Whittemore, Alice S; Baglietto, Laura; McGuire, Valerie; Stegmaier, Christa; Sieh, Weiva; Müller, Heiko; Arndt, Volker; Labrèche, France; Gao, Yu-Tang; Goldberg, Mark S; Yang, Gong; Dumont, Martine; McLaughlin, John R; Hartmann, Arndt; Ekici, Arif B; Beckmann, Matthias W; Phelan, Catherine M; Lux, Michael P; Permuth-Wey, Jenny; Peissel, Bernard; Sellers, Thomas A; Ficarazzi, Filomena; Barile, Monica; Ziogas, Argyrios; Ashworth, Alan; Gentry-Maharaj, Aleksandra; Jones, Michael; Ramus, Susan J; Orr, Nick; Menon, Usha; Pearce, Celeste L; Brüning, Thomas; Pike, Malcolm C; Ko, Yon-Dschun; Lissowska, Jolanta; Figueroa, Jonine; Kupryjanczyk, Jolanta; Chanock, Stephen J; Dansonka-Mieszkowska, Agnieszka; Jukkola-Vuorinen, Arja; Rzepecka, Iwona K; Pylkäs, Katri; Bidzinski, Mariusz; Kauppila, Saila; Hollestelle, Antoinette; Seynaeve, Caroline; Tollenaar, Rob A E M; Durda, Katarzyna; Jaworska, Katarzyna; Hartikainen, Jaana M; Kosma, Veli-Matti; Kataja, Vesa; Antonenkova, Natalia N; Long, Jirong; Shrubsole, Martha; Deming-Halverson, Sandra; Lophatananon, Artitaya; Siriwanarangsan, Pornthep; Stewart-Brown, Sarah; Ditsch, Nina; Lichtner, Peter; Schmutzler, Rita K; Ito, Hidemi; Iwata, Hiroji; Tajima, Kazuo; Tseng, Chiu-Chen; Stram, Daniel O; van den Berg, David; Yip, Cheng Har; Ikram, M Kamran; Teh, Yew-Ching; Cai, Hui; Lu, Wei; Signorello, Lisa B; Cai, Qiuyin; Noh, Dong-Young; Yoo, Keun-Young; Miao, Hui; Iau, Philip Tsau-Choong; Teo, Yik Ying; McKay, James; Shapiro, Charles; Ademuyiwa, Foluso; Fountzilas, George; Hsiung, Chia-Ni; Yu, Jyh-Cherng; Hou, Ming-Feng; Healey, Catherine S; Luccarini, Craig; Peock, Susan; Stoppa-Lyonnet, Dominique; Peterlongo, Paolo; Rebbeck, Timothy R; Piedmonte, Marion; Singer, Christian F; Friedman, Eitan; Thomassen, Mads; Offit, Kenneth; Hansen, Thomas V O; Neuhausen, Susan L; Szabo, Csilla I; Blanco, Ignacio; Garber, Judy; Narod, Steven A; Weitzel, Jeffrey N; Montagna, Marco; Olah, Edith; Godwin, Andrew K; Yannoukakos, Drakoulis; Goldgar, David E; Caldes, Trinidad; Imyanitov, Evgeny N; Tihomirova, Laima; Arun, Banu K; Campbell, Ian; Mensenkamp, Arjen R; van Asperen, Christi J; van Roozendaal, Kees E P; Meijers-Heijboer, Hanne; Collée, J Margriet; Oosterwijk, Jan C; Hooning, Maartje J; Rookus, Matti A; van der Luijt, Rob B; Os, Theo A Mvan; Evans, D Gareth; Frost, Debra; Fineberg, Elena; Barwell, Julian; Walker, Lisa; Kennedy, M John; Platte, Radka; Davidson, Rosemarie; Ellis, Steve D; Cole, Trevor; Bressac-de Paillerets, Brigitte; Buecher, Bruno; Damiola, Francesca; Faivre, Laurence; Frenay, Marc; Sinilnikova, Olga M; Caron, Olivier; Giraud, Sophie; Mazoyer, Sylvie; Bonadona, Valérie; Caux-Moncoutier, Virginie; Toloczko-Grabarek, Aleksandra; Gronwald, Jacek; Byrski, Tomasz; Spurdle, Amanda B; Bonanni, Bernardo; Zaffaroni, Daniela; Giannini, Giuseppe; Bernard, Loris; Dolcetti, Riccardo; Manoukian, Siranoush; Arnold, Norbert; Engel, Christoph; Deissler, Helmut; Rhiem, Kerstin; Niederacher, Dieter; Plendl, Hansjoerg; Sutter, Christian; Wappenschmidt, Barbara; Borg, Ake; Melin, Beatrice; Rantala, Johanna; Soller, Maria; Nathanson, Katherine L; Domchek, Susan M; Rodriguez, Gustavo C; Salani, Ritu; Kaulich, Daphne Gschwantler; Tea, Muy-Kheng; Paluch, Shani Shimon; Laitman, Yael; Skytte, Anne-Bine; Kruse, Torben A; Jensen, Uffe Birk; Robson, Mark; Gerdes, Anne-Marie; Ejlertsen, Bent; Foretova, Lenka; Savage, Sharon A; Lester, Jenny; Soucy, Penny; Kuchenbaecker, Karoline B; Olswold, Curtis; Cunningham, Julie M; Slager, Susan; Pankratz, Vernon S; Dicks, Ed; Lakhani, Sunil R; Couch, Fergus J; Hall, Per; Monteiro, Alvaro N A; Gayther, Simon A; Pharoah, Paul D P; Reddel, Roger R; Goode, Ellen L; Greene, Mark H; Easton, Douglas F; Berchuck, Andrew; Antoniou, Antonis C; Chenevix-Trench, Georgia; Dunning, Alison M

    2013-04-01

    TERT-locus SNPs and leukocyte telomere measures are reportedly associated with risks of multiple cancers. Using the Illumina custom genotyping array iCOGs, we analyzed ∼480 SNPs at the TERT locus in breast (n = 103,991), ovarian (n = 39,774) and BRCA1 mutation carrier (n = 11,705) cancer cases and controls. Leukocyte telomere measurements were also available for 53,724 participants. Most associations cluster into three independent peaks. The minor allele at the peak 1 SNP rs2736108 associates with longer telomeres (P = 5.8 × 10(-7)), lower risks for estrogen receptor (ER)-negative (P = 1.0 × 10(-8)) and BRCA1 mutation carrier (P = 1.1 × 10(-5)) breast cancers and altered promoter assay signal. The minor allele at the peak 2 SNP rs7705526 associates with longer telomeres (P = 2.3 × 10(-14)), higher risk of low-malignant-potential ovarian cancer (P = 1.3 × 10(-15)) and greater promoter activity. The minor alleles at the peak 3 SNPs rs10069690 and rs2242652 increase ER-negative (P = 1.2 × 10(-12)) and BRCA1 mutation carrier (P = 1.6 × 10(-14)) breast and invasive ovarian (P = 1.3 × 10(-11)) cancer risks but not via altered telomere length. The cancer risk alleles of rs2242652 and rs10069690, respectively, increase silencing and generate a truncated TERT splice variant.

  3. Multiple independent variants at the TERT locus are associated with telomere length and risks of breast and ovarian cancer

    Science.gov (United States)

    Bojesen, Stig E; Pooley, Karen A; Johnatty, Sharon E; Beesley, Jonathan; Michailidou, Kyriaki; Tyrer, Jonathan P; Edwards, Stacey L; Pickett, Hilda A; Shen, Howard C; Smart, Chanel E; Hillman, Kristine M; Mai, Phuong L; Lawrenson, Kate; Stutz, Michael D; Lu, Yi; Karevan, Rod; Woods, Nicholas; Johnston, Rebecca L; French, Juliet D; Chen, Xiaoqing; Weischer, Maren; Nielsen, Sune F; Maranian, Melanie J; Ghoussaini, Maya; Ahmed, Shahana; Baynes, Caroline; Bolla, Manjeet K; Wang, Qin; Dennis, Joe; McGuffog, Lesley; Barrowdale, Daniel; Lee, Andrew; Healey, Sue; Lush, Michael; Tessier, Daniel C; Vincent, Daniel; Bacot, Françis; Vergote, Ignace; Lambrechts, Sandrina; Despierre, Evelyn; Risch, Harvey A; González-Neira, Anna; Rossing, Mary Anne; Pita, Guillermo; Doherty, Jennifer A; Álvarez, Nuria; Larson, Melissa C; Fridley, Brooke L; Schoof, Nils; Chang-Claude, Jenny; Cicek, Mine S; Peto, Julian; Kalli, Kimberly R; Broeks, Annegien; Armasu, Sebastian M; Schmidt, Marjanka K; Braaf, Linde M; Winterhoff, Boris; Nevanlinna, Heli; Konecny, Gottfried E; Lambrechts, Diether; Rogmann, Lisa; Guénel, Pascal; Teoman, Attila; Milne, Roger L; Garcia, Joaquin J; Cox, Angela; Shridhar, Vijayalakshmi; Burwinkel, Barbara; Marme, Frederik; Hein, Rebecca; Sawyer, Elinor J; Haiman, Christopher A; Wang-Gohrke, Shan; Andrulis, Irene L; Moysich, Kirsten B; Hopper, John L; Odunsi, Kunle; Lindblom, Annika; Giles, Graham G; Brenner, Hermann; Simard, Jacques; Lurie, Galina; Fasching, Peter A; Carney, Michael E; Radice, Paolo; Wilkens, Lynne R; Swerdlow, Anthony; Goodman, Marc T; Brauch, Hiltrud; García-Closas, Montserrat; Hillemanns, Peter; Winqvist, Robert; Dürst, Matthias; Devilee, Peter; Runnebaum, Ingo; Jakubowska, Anna; Lubinski, Jan; Mannermaa, Arto; Butzow, Ralf; Bogdanova, Natalia V; Dörk, Thilo; Pelttari, Liisa M; Zheng, Wei; Leminen, Arto; Anton-Culver, Hoda; Bunker, Clareann H; Kristensen, Vessela; Ness, Roberta B; Muir, Kenneth; Edwards, Robert; Meindl, Alfons; Heitz, Florian; Matsuo, Keitaro; du Bois, Andreas; Wu, Anna H; Harter, Philipp; Teo, Soo-Hwang; Schwaab, Ira; Shu, Xiao-Ou; Blot, William; Hosono, Satoyo; Kang, Daehee; Nakanishi, Toru; Hartman, Mikael; Yatabe, Yasushi; Hamann, Ute; Karlan, Beth Y; Sangrajrang, Suleeporn; Kjaer, Susanne Krüger; Gaborieau, Valerie; Jensen, Allan; Eccles, Diana; Høgdall, Estrid; Shen, Chen-Yang; Brown, Judith; Woo, Yin Ling; Shah, Mitul; Azmi, Mat Adenan Noor; Luben, Robert; Omar, Siti Zawiah; Czene, Kamila; Vierkant, Robert A; Nordestgaard, Børge G; Flyger, Henrik; Vachon, Celine; Olson, Janet E; Wang, Xianshu; Levine, Douglas A; Rudolph, Anja; Weber, Rachel Palmieri; Flesch-Janys, Dieter; Iversen, Edwin; Nickels, Stefan; Schildkraut, Joellen M; Silva, Isabel Dos Santos; Cramer, Daniel W; Gibson, Lorna; Terry, Kathryn L; Fletcher, Olivia; Vitonis, Allison F; van der Schoot, C Ellen; Poole, Elizabeth M; Hogervorst, Frans B L; Tworoger, Shelley S; Liu, Jianjun; Bandera, Elisa V; Li, Jingmei; Olson, Sara H; Humphreys, Keith; Orlow, Irene; Blomqvist, Carl; Rodriguez-Rodriguez, Lorna; Aittomäki, Kristiina; Salvesen, Helga B; Muranen, Taru A; Wik, Elisabeth; Brouwers, Barbara; Krakstad, Camilla; Wauters, Els; Halle, Mari K; Wildiers, Hans; Kiemeney, Lambertus A; Mulot, Claire; Aben, Katja K; Laurent-Puig, Pierre; van Altena, Anne M; Truong, Thérèse; Massuger, Leon F A G; Benitez, Javier; Pejovic, Tanja; Perez, Jose Ignacio Arias; Hoatlin, Maureen; Zamora, M Pilar; Cook, Linda S; Balasubramanian, Sabapathy P; Kelemen, Linda E; Schneeweiss, Andreas; Le, Nhu D; Sohn, Christof; Brooks-Wilson, Angela; Tomlinson, Ian; Kerin, Michael J; Miller, Nicola; Cybulski, Cezary; Henderson, Brian E; Menkiszak, Janusz; Schumacher, Fredrick; Wentzensen, Nicolas; Marchand, Loic Le; Yang, Hannah P; Mulligan, Anna Marie; Glendon, Gord; Engelholm, Svend Aage; Knight, Julia A; Høgdall, Claus K; Apicella, Carmel; Gore, Martin; Tsimiklis, Helen; Song, Honglin; Southey, Melissa C; Jager, Agnes; van den Ouweland, Ans M W; Brown, Robert; Martens, John W M; Flanagan, James M; Kriege, Mieke; Paul, James; Margolin, Sara; Siddiqui, Nadeem; Severi, Gianluca; Whittemore, Alice S; Baglietto, Laura; McGuire, Valerie; Stegmaier, Christa; Sieh, Weiva; Müller, Heiko; Arndt, Volker; Labrèche, France; Gao, Yu-Tang; Goldberg, Mark S; Yang, Gong; Dumont, Martine; McLaughlin, John R; Hartmann, Arndt; Ekici, Arif B; Beckmann, Matthias W; Phelan, Catherine M; Lux, Michael P; Permuth-Wey, Jenny; Peissel, Bernard; Sellers, Thomas A; Ficarazzi, Filomena; Barile, Monica; Ziogas, Argyrios; Ashworth, Alan; Gentry-Maharaj, Aleksandra; Jones, Michael; Ramus, Susan J; Orr, Nick; Menon, Usha; Pearce, Celeste L; Brüning, Thomas; Pike, Malcolm C; Ko, Yon-Dschun; Lissowska, Jolanta; Figueroa, Jonine; Kupryjanczyk, Jolanta; Chanock, Stephen J; Dansonka-Mieszkowska, Agnieszka; Jukkola-Vuorinen, Arja; Rzepecka, Iwona K; Pylkäs, Katri; Bidzinski, Mariusz; Kauppila, Saila; Hollestelle, Antoinette; Seynaeve, Caroline; Tollenaar, Rob A E M; Durda, Katarzyna; Jaworska, Katarzyna; Hartikainen, Jaana M; Kosma, Veli-Matti; Kataja, Vesa; Antonenkova, Natalia N; Long, Jirong; Shrubsole, Martha; Deming-Halverson, Sandra; Lophatananon, Artitaya; Siriwanarangsan, Pornthep; Stewart-Brown, Sarah; Ditsch, Nina; Lichtner, Peter; Schmutzler, Rita K; Ito, Hidemi; Iwata, Hiroji; Tajima, Kazuo; Tseng, Chiu-Chen; Stram, Daniel O; van den Berg, David; Yip, Cheng Har; Ikram, M Kamran; Teh, Yew-Ching; Cai, Hui; Lu, Wei; Signorello, Lisa B; Cai, Qiuyin; Noh, Dong-Young; Yoo, Keun-Young; Miao, Hui; Iau, Philip Tsau-Choong; Teo, Yik Ying; McKay, James; Shapiro, Charles; Ademuyiwa, Foluso; Fountzilas, George; Hsiung, Chia-Ni; Yu, Jyh-Cherng; Hou, Ming-Feng; Healey, Catherine S; Luccarini, Craig; Peock, Susan; Stoppa-Lyonnet, Dominique; Peterlongo, Paolo; Rebbeck, Timothy R; Piedmonte, Marion; Singer, Christian F; Friedman, Eitan; Thomassen, Mads; Offit, Kenneth; Hansen, Thomas V O; Neuhausen, Susan L; Szabo, Csilla I; Blanco, Ignacio; Garber, Judy; Narod, Steven A; Weitzel, Jeffrey N; Montagna, Marco; Olah, Edith; Godwin, Andrew K; Yannoukakos, Drakoulis; Goldgar, David E; Caldes, Trinidad; Imyanitov, Evgeny N; Tihomirova, Laima; Arun, Banu K; Campbell, Ian; Mensenkamp, Arjen R; van Asperen, Christi J; van Roozendaal, Kees E P; Meijers-Heijboer, Hanne; Collée, J Margriet; Oosterwijk, Jan C; Hooning, Maartje J; Rookus, Matti A; van der Luijt, Rob B; van Os, Theo A M; Evans, D Gareth; Frost, Debra; Fineberg, Elena; Barwell, Julian; Walker, Lisa; Kennedy, M John; Platte, Radka; Davidson, Rosemarie; Ellis, Steve D; Cole, Trevor; Paillerets, Brigitte Bressac-de; Buecher, Bruno; Damiola, Francesca; Faivre, Laurence; Frenay, Marc; Sinilnikova, Olga M; Caron, Olivier; Giraud, Sophie; Mazoyer, Sylvie; Bonadona, Valérie; Caux-Moncoutier, Virginie; Toloczko-Grabarek, Aleksandra; Gronwald, Jacek; Byrski, Tomasz; Spurdle, Amanda B; Bonanni, Bernardo; Zaffaroni, Daniela; Giannini, Giuseppe; Bernard, Loris; Dolcetti, Riccardo; Manoukian, Siranoush; Arnold, Norbert; Engel, Christoph; Deissler, Helmut; Rhiem, Kerstin; Niederacher, Dieter; Plendl, Hansjoerg; Sutter, Christian; Wappenschmidt, Barbara; Borg, Åke; Melin, Beatrice; Rantala, Johanna; Soller, Maria; Nathanson, Katherine L; Domchek, Susan M; Rodriguez, Gustavo C; Salani, Ritu; Kaulich, Daphne Gschwantler; Tea, Muy-Kheng; Paluch, Shani Shimon; Laitman, Yael; Skytte, Anne-Bine; Kruse, Torben A; Jensen, Uffe Birk; Robson, Mark; Gerdes, Anne-Marie; Ejlertsen, Bent; Foretova, Lenka; Savage, Sharon A; Lester, Jenny; Soucy, Penny; Kuchenbaecker, Karoline B; Olswold, Curtis; Cunningham, Julie M; Slager, Susan; Pankratz, Vernon S; Dicks, Ed; Lakhani, Sunil R; Couch, Fergus J; Hall, Per; Monteiro, Alvaro N A; Gayther, Simon A; Pharoah, Paul D P; Reddel, Roger R; Goode, Ellen L; Greene, Mark H; Easton, Douglas F; Berchuck, Andrew; Antoniou, Antonis C; Chenevix-Trench, Georgia; Dunning, Alison M

    2013-01-01

    TERT-locus single nucleotide polymorphisms (SNPs) and leucocyte telomere measures are reportedly associated with risks of multiple cancers. Using the iCOGs chip, we analysed ~480 TERT-locus SNPs in breast (n=103,991), ovarian (n=39,774) and BRCA1 mutation carrier (11,705) cancer cases and controls. 53,724 participants have leucocyte telomere measures. Most associations cluster into three independent peaks. Peak 1 SNP rs2736108 minor allele associates with longer telomeres (P=5.8×10−7), reduced estrogen receptor negative (ER-negative) (P=1.0×10−8) and BRCA1 mutation carrier (P=1.1×10−5) breast cancer risks, and altered promoter-assay signal. Peak 2 SNP rs7705526 minor allele associates with longer telomeres (P=2.3×10−14), increased low malignant potential ovarian cancer risk (P=1.3×10−15) and increased promoter activity. Peak 3 SNPs rs10069690 and rs2242652 minor alleles increase ER-negative (P=1.2×10−12) and BRCA1 mutation carrier (P=1.6×10−14) breast and invasive ovarian (P=1.3×10−11) cancer risks, but not via altered telomere length. The cancer-risk alleles of rs2242652 and rs10069690 respectively increase silencing and generate a truncated TERT splice-variant. PMID:23535731

  4. Cycloheximide Can Induce Bax/Bak Dependent Myeloid Cell Death Independently of Multiple BH3-Only Proteins.

    Directory of Open Access Journals (Sweden)

    Katharine J Goodall

    Full Text Available Apoptosis mediated by Bax or Bak is usually thought to be triggered by BH3-only members of the Bcl-2 protein family. BH3-only proteins can directly bind to and activate Bax or Bak, or indirectly activate them by binding to anti-apoptotic Bcl-2 family members, thereby relieving their inhibition of Bax and Bak. Here we describe a third way of activation of Bax/Bak dependent apoptosis that does not require triggering by multiple BH3-only proteins. In factor dependent myeloid (FDM cell lines, cycloheximide induced apoptosis by a Bax/Bak dependent mechanism, because Bax-/-Bak-/- lines were profoundly resistant, whereas FDM lines lacking one or more genes for BH3-only proteins remained highly sensitive. Addition of cycloheximide led to the rapid loss of Mcl-1 but did not affect the expression of other Bcl-2 family proteins. In support of these findings, similar results were observed by treating FDM cells with the CDK inhibitor, roscovitine. Roscovitine reduced Mcl-1 abundance and caused Bax/Bak dependent cell death, yet FDM lines lacking one or more genes for BH3-only proteins remained highly sensitive. Therefore Bax/Bak dependent apoptosis can be regulated by the abundance of anti-apoptotic Bcl-2 family members such as Mcl-1, independently of several known BH3-only proteins.

  5. A novel GMO biosensor for rapid ultrasensitive and simultaneous detection of multiple DNA components in GMO products.

    Science.gov (United States)

    Huang, Lin; Zheng, Lei; Chen, Yinji; Xue, Feng; Cheng, Lin; Adeloju, Samuel B; Chen, Wei

    2015-04-15

    Since the introduction of genetically modified organisms (GMOs), there has been on-going and continuous concern and debates on the commercialization of products derived from GMOs. There is an urgent need for development of highly efficient analytical methods for rapid and high throughput screening of GMOs components, as required for appropriate labeling of GMO-derived foods, as well as for on-site inspection and import/export quarantine. In this study, we describe, for the first time, a multi-labeling based electrochemical biosensor for simultaneous detection of multiple DNA components of GMO products on the same sensing interface. Two-round signal amplification was applied by using both an exonuclease enzyme catalytic reaction and gold nanoparticle-based bio-barcode related strategies, respectively. Simultaneous multiple detections of different DNA components of GMOs were successfully achieved with satisfied sensitivity using this electrochemical biosensor. Furthermore, the robustness and effectiveness of the proposed approach was successfully demonstrated by application to various GMO products, including locally obtained and confirmed commercial GMO seeds and transgenetic plants. The proposed electrochemical biosensor demonstrated unique merits that promise to gain more interest in its use for rapid and on-site simultaneous multiple screening of different components of GMO products. Copyright © 2014 Elsevier B.V. All rights reserved.

  6. Sunlight-Driven Forging of Amide/Ester Bonds from Three Independent Components: An Approach to Carbamates.

    Science.gov (United States)

    Zhao, Yating; Huang, Binbin; Yang, Chao; Chen, Qingqing; Xia, Wujiong

    2016-11-04

    A photoredox catalytic route to carbamates enabled by visible irradiation (or simply sunlight) has been developed. This process leads to a novel approach to the construction of heterocyclic rings wherein the amide or ester motifs of carbamates were assembled from three isolated components. Large-scale experiments were realized by employing continuous flow techniques, and reuse of photocatalyst demonstrated the green and sustainable aspects of this method.

  7. Grouping and the pitch of a mistuned fundamental component: Effects of applying simultaneous multiple mistunings to the other harmonics.

    Science.gov (United States)

    Roberts, Brian; Holmes, Stephen D

    2006-12-01

    Mistuning a harmonic produces an exaggerated change in its pitch. This occurs because the component becomes inconsistent with the regular pattern that causes the other harmonics (constituting the spectral frame) to integrate perceptually. These pitch shifts were measured when the fundamental (F0) component of a complex tone (nominal F0 frequency = 200 Hz) was mistuned by +8% and -8%. The pitch-shift gradient was defined as the difference between these values and its magnitude was used as a measure of frame integration. An independent and random perturbation (spectral jitter) was applied simultaneously to most or all of the frame components. The gradient magnitude declined gradually as the degree of jitter increased from 0% to +/-40% of F0. The component adjacent to the mistuned target made the largest contribution to the gradient, but more distant components also contributed. The stimuli were passed through an auditory model, and the exponential height of the F0-period peak in the averaged summary autocorrelation function correlated well with the gradient magnitude. The fit improved when the weighting on more distant channels was attenuated by a factor of three per octave. The results are consistent with a grouping mechanism that computes a weighted average of periodicity strength across several components.

  8. Genetic components to caste allocation in a multiple-queen ant species

    NARCIS (Netherlands)

    Libbrecht, Romain; Schwander, Tanja; Keller, Laurent

    2011-01-01

    Reproductive division of labor and the coexistence of distinct castes are hallmarks of insect societies. In social insect species with multiple queens per colony, the fitness of nestmate queens directly depends on the process of caste allocation (i.e., the relative investment in queen, sterile

  9. Synergistic and independent actions of multiple terminal nucleotidyl transferases in the 3' tailing of small RNAs in Arabidopsis.

    Directory of Open Access Journals (Sweden)

    Xiaoyan Wang

    2015-04-01

    Full Text Available All types of small RNAs in plants, piwi-interacting RNAs (piRNAs in animals and a subset of siRNAs in Drosophila and C. elegans are subject to HEN1 mediated 3' terminal 2'-O-methylation. This modification plays a pivotal role in protecting small RNAs from 3' uridylation, trimming and degradation. In Arabidopsis, HESO1 is a major enzyme that uridylates small RNAs to trigger their degradation. However, U-tail is still present in null hen1 heso1 mutants, suggesting the existence of (an enzymatic activities redundant with HESO1. Here, we report that UTP: RNA uridylyltransferase (URT1 is a functional paralog of HESO1. URT1 interacts with AGO1 and plays a predominant role in miRNA uridylation when HESO1 is absent. Uridylation of miRNA is globally abolished in a hen1 heso1 urt1 triple mutant, accompanied by an extensive increase of 3'-to-5' trimming. In contrast, disruption of URT1 appears not to affect the heterochromatic siRNA uridylation. This indicates the involvement of additional nucleotidyl transferases in the siRNA pathway. Analysis of miRNA tailings in the hen1 heso1 urt1 triple mutant also reveals the existence of previously unknown enzymatic activities that can add non-uridine nucleotides. Importantly, we show HESO1 may also act redundantly with URT1 in miRNA uridylation when HEN1 is fully competent. Taken together, our data not only reveal a synergistic action of HESO1 and URT1 in the 3' uridylation of miRNAs, but also independent activities of multiple terminal nucleotidyl transferases in the 3' tailing of small RNAs and an antagonistic relationship between uridylation and trimming. Our results may provide further insight into the mechanisms of small RNA 3' end modification and stability control.

  10. Evaluation of multiple bio-pathological factors in colorectal adenocarcinomas: independent prognostic role of p53 and bcl-2.

    Science.gov (United States)

    Buglioni, S; D'Agnano, I; Cosimelli, M; Vasselli, S; D'Angelo, C; Tedesco, M; Zupi, G; Mottolese, M

    1999-12-22

    About 40% of patients with colorectal carcinoma will develop local or distant tumour recurrences. Integrated analyses of bio-pathological markers, predictive of tumour aggressiveness, may offer a more rational approach to planning adjuvant therapy. To this end, we analysed the correlation between p53 accumulation, Bcl-2 expression, DNA ploidy, cell proliferation and conventional clinico-pathological parameters by testing the prognostic significance of these variables in a series of 171 colorectal carcinoma patients with long-term follow-up. The relationships among the various bio-pathological parameters, analysed by multiple correspondence analysis, showed 2 different clinico-biological profiles. The first, characterised by p53 negativity, Bcl-2 positivity, diploidy, low percentage of cells in S-phase (%S-phase), a low Ki-67 score, is associated with Dukes' A-B stage, well differentiated tumours and lack of relapse. The second, defined by p53 positivity, Bcl-2 negativity, aneuploidy, high %S-phase and elevated Ki-67 score, correlates with Dukes' C-D stage, poorly differentiated tumours and presence of relapse. When these parameters were examined according to Kaplan-Meier's method, significantly shorter disease-free (DFS) and overall survival (OS) were also observed in patients bearing p53 positive and Bcl-2 negative tumours, in Dukes' B stage. In multivariate analysis, p53 accumulation and Bcl-2 expression emerged as independent predictors of a worse and better clinical outcome, respectively. Our results indicate that, in colorectal adenocarcinomas, a biological profile, based on the combined evaluation of p53 and Bcl-2, may be useful for identifying high risk patients to be enrolled in an adjuvant setting, mainly in an early stage of the disease. Int. J. Cancer (Pred. Oncol.) 84:545-552, 1999. Copyright 1999 Wiley-Liss, Inc.

  11. Working Memory Components and Problem-Solving Accuracy: Are There Multiple Pathways?

    Science.gov (United States)

    Swanson, H. Lee; Fung, Wenson

    2016-01-01

    This study determined the working memory (WM) components (executive, phonological short-term memory [STM], and visual-spatial sketchpad) that best predicted mathematical word problem-solving accuracy in elementary schoolchildren (N = 392). The battery of tests administered to assess mediators between WM and problem-solving included measures of…

  12. Background, design and conceptual model of the cluster randomized multiple-component workplace study

    DEFF Research Database (Denmark)

    Christensen, Jeanette Reffstrup; Bredahl, Thomas Viskum Gjelstrup; Hadrévi, Jenny

    2016-01-01

    health care workers. This was done through a multi-component intervention including 1) intelligent physical exercise training (IPET), dietary advice and weight loss (DAW) and cognitive behavioural training (CBT). DISCUSSION: The FRIDOM program has the potential to provide evidence-based knowledge...

  13. Multiple Two-Component Systems of Streptococcus mutans Regulate Agmatine Deiminase Gene Expression and Stress Tolerance▿

    OpenAIRE

    Liu, Yaling; Burne, Robert A.

    2009-01-01

    Induction of the agmatine deiminase system (AgDS) of Streptococcus mutans requires agmatine and is optimal at low pH. We show here that the VicRK, ComDE, and CiaRH two-component systems influence AgDS gene expression in response to acidic and thermal stresses.

  14. Mapping multiple components of malaria risk for improved targeting of elimination interventions.

    Science.gov (United States)

    Cohen, Justin M; Le Menach, Arnaud; Pothin, Emilie; Eisele, Thomas P; Gething, Peter W; Eckhoff, Philip A; Moonen, Bruno; Schapira, Allan; Smith, David L

    2017-11-13

    There is a long history of considering the constituent components of malaria risk and the malaria transmission cycle via the use of mathematical models, yet strategic planning in endemic countries tends not to take full advantage of available disease intelligence to tailor interventions. National malaria programmes typically make operational decisions about where to implement vector control and surveillance activities based upon simple categorizations of annual parasite incidence. With technological advances, an enormous opportunity exists to better target specific malaria interventions to the places where they will have greatest impact by mapping and evaluating metrics related to a variety of risk components, each of which describes a different facet of the transmission cycle. Here, these components and their implications for operational decision-making are reviewed. For each component, related mappable malaria metrics are also described which may be measured and evaluated by malaria programmes seeking to better understand the determinants of malaria risk. Implementing tailored programmes based on knowledge of the heterogeneous distribution of the drivers of malaria transmission rather than only consideration of traditional metrics such as case incidence has the potential to result in substantial improvements in decision-making. As programmes improve their ability to prioritize their available tools to the places where evidence suggests they will be most effective, elimination aspirations may become increasingly feasible.

  15. Components of a Fanconi-like pathway control Pso2-independent DNA interstrand crosslink repair in yeast.

    Directory of Open Access Journals (Sweden)

    Thomas A Ward

    Full Text Available Fanconi anemia (FA is a devastating genetic disease, associated with genomic instability and defects in DNA interstrand cross-link (ICL repair. The FA repair pathway is not thought to be conserved in budding yeast, and although the yeast Mph1 helicase is a putative homolog of human FANCM, yeast cells disrupted for MPH1 are not sensitive to ICLs. Here, we reveal a key role for Mph1 in ICL repair when the Pso2 exonuclease is inactivated. We find that the yeast FANCM ortholog Mph1 physically and functionally interacts with Mgm101, a protein previously implicated in mitochondrial DNA repair, and the MutSα mismatch repair factor (Msh2-Msh6. Co-disruption of MPH1, MGM101, MSH6, or MSH2 with PSO2 produces a lesion-specific increase in ICL sensitivity, the elevation of ICL-induced chromosomal rearrangements, and persistence of ICL-associated DNA double-strand breaks. We find that Mph1-Mgm101-MutSα directs the ICL-induced recruitment of Exo1 to chromatin, and we propose that Exo1 is an alternative 5'-3' exonuclease utilised for ICL repair in the absence of Pso2. Moreover, ICL-induced Rad51 chromatin loading is delayed when both Pso2 and components of the Mph1-Mgm101-MutSα and Exo1 pathway are inactivated, demonstrating that the homologous recombination stages of ICL repair are inhibited. Finally, the FANCJ- and FANCP-related factors Chl1 and Slx4, respectively, are also components of the genetic pathway controlled by Mph1-Mgm101-MutSα. Together this suggests that a prototypical FA-related ICL repair pathway operates in budding yeast, which acts redundantly with the pathway controlled by Pso2, and is required for the targeting of Exo1 to chromatin to execute ICL repair.

  16. Nonparametric predictive inference for reliability of a k-out-of-m:G system with multiple component types

    International Nuclear Information System (INIS)

    Aboalkhair, Ahmad M.; Coolen, Frank P.A.; MacPhee, Iain M.

    2014-01-01

    Nonparametric predictive inference for system reliability has recently been presented, with specific focus on k-out-of-m:G systems. The reliability of systems is quantified by lower and upper probabilities of system functioning, given binary test results on components, taking uncertainty about component functioning and indeterminacy due to limited test information explicitly into account. Thus far, systems considered were series configurations of subsystems, with each subsystem i a k i -out-of-m i :G system which consisted of only one type of components. Key results are briefly summarized in this paper, and as an important generalization new results are presented for a single k-out-of-m:G system consisting of components of multiple types. The important aspects of redundancy and diversity for such systems are discussed. - Highlights: • New results on nonparametric predictive inference for system reliability. • Prediction of system reliability based on test data for components. • New insights on system redundancy optimization and diversity. • Components that appear inferior in tests may be included to enhance redundancy

  17. Simultaneous and rapid determination of multiple component concentrations in a Kraft liquor process stream

    Science.gov (United States)

    Li, Jian [Marietta, GA; Chai, Xin Sheng [Atlanta, GA; Zhu, Junyoung [Marietta, GA

    2008-06-24

    The present invention is a rapid method of determining the concentration of the major components in a chemical stream. The present invention is also a simple, low cost, device of determining the in-situ concentration of the major components in a chemical stream. In particular, the present invention provides a useful method for simultaneously determining the concentrations of sodium hydroxide, sodium sulfide and sodium carbonate in aqueous kraft pulping liquors through use of an attenuated total reflectance (ATR) tunnel flow cell or optical probe capable of producing a ultraviolet absorbency spectrum over a wavelength of 190 to 300 nm. In addition, the present invention eliminates the need for manual sampling and dilution previously required to generate analyzable samples. The inventive method can be used in Kraft pulping operations to control white liquor causticizing efficiency, sulfate reduction efficiency in green liquor, oxidation efficiency for oxidized white liquor and the active and effective alkali charge to kraft pulping operations.

  18. Broadly tunable mid-infrared VECSEL for multiple components hydrocarbon gas sensing

    Science.gov (United States)

    Rey, J. M.; Fill, M.; Felder, F.; Sigrist, M. W.

    2014-12-01

    A new sensing platform to simultaneously identify and quantify volatile C1 to C4 alkanes in multi-component gas mixtures is presented. This setup is based on an optically pumped, broadly tunable mid-infrared vertical-external-cavity surface-emitting laser (VECSEL) developed for gas detection. The lead-chalcogenide VECSEL is the key component of the presented optical sensor. The potential of the proposed sensing setup is illustrated by experimental absorption spectra obtained from various mixtures of volatile hydrocarbons and water vapor. The sensor has a sub-ppm limit of detection for each targeted alkane in a hydrocarbon gas mixture even in the presence of a high water vapor content.

  19. Effects of multiple inhibitory components on anaerobic treatment processes in municipal solid waste incineration leachate.

    Science.gov (United States)

    Lei, Yuqing; Dang, Yan; Lan, Zhangheng; Sun, Dezhi

    2016-06-01

    This study served to investigate the comparative and combined effects of calcium, ammonia nitrogen, and aquatic humic substances (AHS) on specific methanogenic activity (SMA) in municipal solid waste leachate at mesophilic conditions. Using orthogonal experiments, anaerobic granular sludge was cultured with different concentrations combinations of the three added components for 13 days. The combination of 6000 mg/L calcium, 400 mg/L ammonia nitrogen, and 4000 mg/L AHS was the most inhibitory combination on the SMA of granular sludge, with a calculated 4.49 mL (standard temperature and atmospheric pressure) (STP) CH4/(gVSS·d) of SMA. The SMA with the addition of the inhibitory components was much lower than the control group's (1000 mg/L calcium, 200 mg/L ammonia nitrogen and 2000 mg/L AHS) with a calculated 12.97 mL (STP) CH4/(gVSS·d) of SMA. Calcium was the major inhibitor among the three components followed by AHS. High concentrations of calcium significantly inhibited the utilization of propionate and butyrate in the substrate and further affected the methanogenic process.

  20. Predicting timing of foot strike during running, independent of striking technique, using principal component analysis of joint angles.

    Science.gov (United States)

    Osis, Sean T; Hettinga, Blayne A; Leitch, Jessica; Ferber, Reed

    2014-08-22

    As 3-dimensional (3D) motion-capture for clinical gait analysis continues to evolve, new methods must be developed to improve the detection of gait cycle events based on kinematic data. Recently, the application of principal component analysis (PCA) to gait data has shown promise in detecting important biomechanical features. Therefore, the purpose of this study was to define a new foot strike detection method for a continuum of striking techniques, by applying PCA to joint angle waveforms. In accordance with Newtonian mechanics, it was hypothesized that transient features in the sagittal-plane accelerations of the lower extremity would be linked with the impulsive application of force to the foot at foot strike. Kinematic and kinetic data from treadmill running were selected for 154 subjects, from a database of gait biomechanics. Ankle, knee and hip sagittal plane angular acceleration kinematic curves were chained together to form a row input to a PCA matrix. A linear polynomial was calculated based on PCA scores, and a 10-fold cross-validation was performed to evaluate prediction accuracy against gold-standard foot strike as determined by a 10 N rise in the vertical ground reaction force. Results show 89-94% of all predicted foot strikes were within 4 frames (20 ms) of the gold standard with the largest error being 28 ms. It is concluded that this new foot strike detection is an improvement on existing methods and can be applied regardless of whether the runner exhibits a rearfoot, midfoot, or forefoot strike pattern. Copyright © 2014 Elsevier Ltd. All rights reserved.

  1. Distributed cerebellar plasticity implements generalized multiple-scale memory components in real-robot sensorimotor tasks

    Directory of Open Access Journals (Sweden)

    Claudia eCasellato

    2015-02-01

    Full Text Available The cerebellum plays a crucial role in motor learning and it acts as a predictive controller. Modeling it and embedding it into sensorimotor tasks allows us to create functional links between plasticity mechanisms, neural circuits and behavioral learning. Moreover, if applied to real-time control of a neurorobot, the cerebellar model has to deal with a real noisy and changing environment, thus showing its robustness and effectiveness in learning. A biologically inspired cerebellar model with distributed plasticity, both at cortical and nuclear sites, has been used. Two cerebellum-mediated paradigms have been designed: an associative Pavlovian task and a vestibulo-ocular reflex, with multiple sessions of acquisition and extinction and with different stimuli and perturbation patterns. The cerebellar controller succeeded to generate conditioned responses and finely tuned eye movement compensation, thus reproducing human-like behaviors. Through a productive plasticity transfer from cortical to nuclear sites, the distributed cerebellar controller showed in both tasks the capability to optimize learning on multiple time-scales, to store motor memory and to effectively adapt to dynamic ranges of stimuli.

  2. Independent component analysis applied to pulse oximetry in the estimation of the arterial oxygen saturation (SpO2) - a comparative study

    DEFF Research Database (Denmark)

    Jensen, Thomas; Duun, Sune Bro; Larsen, Jan

    2009-01-01

    We examine various independent component analysis (ICA) digital signal processing algorithms for estimating the arterial oxygen saturation (SpO2) as measured by a reflective pulse oximeter. The ICA algorithms examined are FastICA, Maximum Likelihood ICA (ICAML), Molgedey and Schuster ICA (ICAMS......), and Mean Field ICA (ICAMF). The signal processing includes pre-processing bandpass filtering to eliminate noise, and post-processing by calculating the SpO2. The algorithms are compared to the commercial state-of-the-art algorithm Discrete Saturation Transform (DST) by Masimo Corporation...

  3. Effect of halloysite nanotubes on the structure and function of important multiple blood components

    International Nuclear Information System (INIS)

    Wu, Keke; Feng, Ru; Jiao, Yanpeng; Zhou, Changren

    2017-01-01

    Many researchers have investigated the application of halloysite nanotubes (HNTs) in biomedicine, because of their special nanoscale hollow tubular structure. Although the cytocompatibility of HNTs has been studied, their blood compatibility has not been systematically investigated. In this work, the effect of HNTs on the structure and function of different blood components has been studied, including the morphology and hemolysis of red blood cells (RBCs). Based on scanning electron microscopy (SEM) observations, optical density test and flow cytometry analysis, we found that HNTs can affect the morphology and membrane integrity of RBCs in phosphate buffered saline (PBS) in a content-dependent way. In particular, based on UV–vis absorption spectra, fluorescence spectra and circular dichroism (CD) spectra, HNTs can alter the secondary structure and conformation of human fibrinogen and γ-globulins. In addition, the detection of biomarker molecules C3a and C5a in plasma suggests that HNTs can trigger complement activation. In the blood clotting assay, HNTs were found to significantly prolong the activated partial thromboplastin time (APTT), shorten the prothrombin time (PT) of platelet-poor plasma (PPP), and change the thromboelastography (TEG) parameters of whole blood coagulation. Furthermore, confocal laser scanning microscopy and flow cytometry analysis were used to test intracellular uptake by macrophages, and the cellular uptake of HNTs in the RAW 264.7 was found to be content-dependent, but not time-dependent. These findings provide insight for the potential use of HNTs as biofriendly nanocontainers for biomaterials in vivo. - Highlights: • Comprehensive study of blood compatibility halloysite nanotubes (HNTs) is processed. • We examine and analyze the effect of HNTs on conformation changes of three plasma proteins. • We prove HNTs can affect blood components at high content but little at low content. • We prove HNTs could be used as biomaterials

  4. Effect of halloysite nanotubes on the structure and function of important multiple blood components

    Energy Technology Data Exchange (ETDEWEB)

    Wu, Keke; Feng, Ru; Jiao, Yanpeng, E-mail: tjiaoyp@jnu.edu.cn; Zhou, Changren

    2017-06-01

    Many researchers have investigated the application of halloysite nanotubes (HNTs) in biomedicine, because of their special nanoscale hollow tubular structure. Although the cytocompatibility of HNTs has been studied, their blood compatibility has not been systematically investigated. In this work, the effect of HNTs on the structure and function of different blood components has been studied, including the morphology and hemolysis of red blood cells (RBCs). Based on scanning electron microscopy (SEM) observations, optical density test and flow cytometry analysis, we found that HNTs can affect the morphology and membrane integrity of RBCs in phosphate buffered saline (PBS) in a content-dependent way. In particular, based on UV–vis absorption spectra, fluorescence spectra and circular dichroism (CD) spectra, HNTs can alter the secondary structure and conformation of human fibrinogen and γ-globulins. In addition, the detection of biomarker molecules C3a and C5a in plasma suggests that HNTs can trigger complement activation. In the blood clotting assay, HNTs were found to significantly prolong the activated partial thromboplastin time (APTT), shorten the prothrombin time (PT) of platelet-poor plasma (PPP), and change the thromboelastography (TEG) parameters of whole blood coagulation. Furthermore, confocal laser scanning microscopy and flow cytometry analysis were used to test intracellular uptake by macrophages, and the cellular uptake of HNTs in the RAW 264.7 was found to be content-dependent, but not time-dependent. These findings provide insight for the potential use of HNTs as biofriendly nanocontainers for biomaterials in vivo. - Highlights: • Comprehensive study of blood compatibility halloysite nanotubes (HNTs) is processed. • We examine and analyze the effect of HNTs on conformation changes of three plasma proteins. • We prove HNTs can affect blood components at high content but little at low content. • We prove HNTs could be used as biomaterials

  5. Relativistic dissipative hydrodynamic equations at the second order for multi-component systems with multiple conserved currents

    International Nuclear Information System (INIS)

    Monnai, Akihiko; Hirano, Tetsufumi

    2010-01-01

    We derive the second order hydrodynamic equations for the relativistic system of multi-components with multiple conserved currents by generalizing the Israel-Stewart theory and Grad's moment method. We find that, in addition to the conventional moment equations, extra moment equations associated with conserved currents should be introduced to consistently match the number of equations with that of unknowns and to satisfy the Onsager reciprocal relations. Consistent expansion of the entropy current leads to constitutive equations which involve the terms not appearing in the original Israel-Stewart theory even in the single component limit. We also find several terms which exhibit thermal diffusion such as Soret and Dufour effects. We finally compare our results with those of other existing formalisms.

  6. Robot training of upper limb in multiple sclerosis: comparing protocols with or without manipulative task components.

    Science.gov (United States)

    Carpinella, Ilaria; Cattaneo, Davide; Bertoni, Rita; Ferrarin, Maurizio

    2012-05-01

    In this pilot study, we compared two protocols for robot-based rehabilitation of upper limb in multiple sclerosis (MS): a protocol involving reaching tasks (RT) requiring arm transport only and a protocol requiring both objects' reaching and manipulation (RMT). Twenty-two MS subjects were assigned to RT or RMT group. Both protocols consisted of eight sessions. During RT training, subjects moved the handle of a planar robotic manipulandum toward circular targets displayed on a screen. RMT protocol required patients to reach and manipulate real objects, by moving the robotic arm equipped with a handle which left the hand free for distal tasks. In both trainings, the robot generated resistive and perturbing forces. Subjects were evaluated with clinical and instrumental tests. The results confirmed that MS patients maintained the ability to adapt to the robot-generated forces and that the rate of motor learning increased across sessions. Robot-therapy significantly reduced arm tremor and improved arm kinematics and functional ability. Compared to RT, RMT protocol induced a significantly larger improvement in movements involving grasp (improvement in Grasp ARAT sub-score: RMT 77.4%, RT 29.5%, p=0.035) but not precision grip. Future studies are needed to evaluate if longer trainings and the use of robotic handles would significantly improve also fine manipulation.

  7. A principal component meta-analysis on multiple anthropometric traits identifies novel loci for body shape

    Science.gov (United States)

    Ried, Janina S.; Jeff M., Janina; Chu, Audrey Y.; Bragg-Gresham, Jennifer L.; van Dongen, Jenny; Huffman, Jennifer E.; Ahluwalia, Tarunveer S.; Cadby, Gemma; Eklund, Niina; Eriksson, Joel; Esko, Tõnu; Feitosa, Mary F.; Goel, Anuj; Gorski, Mathias; Hayward, Caroline; Heard-Costa, Nancy L.; Jackson, Anne U.; Jokinen, Eero; Kanoni, Stavroula; Kristiansson, Kati; Kutalik, Zoltán; Lahti, Jari; Luan, Jian'an; Mägi, Reedik; Mahajan, Anubha; Mangino, Massimo; Medina-Gomez, Carolina; Monda, Keri L.; Nolte, Ilja M.; Pérusse, Louis; Prokopenko, Inga; Qi, Lu; Rose, Lynda M.; Salvi, Erika; Smith, Megan T.; Snieder, Harold; Stančáková, Alena; Ju Sung, Yun; Tachmazidou, Ioanna; Teumer, Alexander; Thorleifsson, Gudmar; van der Harst, Pim; Walker, Ryan W.; Wang, Sophie R.; Wild, Sarah H.; Willems, Sara M.; Wong, Andrew; Zhang, Weihua; Albrecht, Eva; Couto Alves, Alexessander; Bakker, Stephan J. L.; Barlassina, Cristina; Bartz, Traci M.; Beilby, John; Bellis, Claire; Bergman, Richard N.; Bergmann, Sven; Blangero, John; Blüher, Matthias; Boerwinkle, Eric; Bonnycastle, Lori L.; Bornstein, Stefan R.; Bruinenberg, Marcel; Campbell, Harry; Chen, Yii-Der Ida; Chiang, Charleston W. K.; Chines, Peter S.; Collins, Francis S; Cucca, Fracensco; Cupples, L Adrienne; D'Avila, Francesca; de Geus, Eco J .C.; Dedoussis, George; Dimitriou, Maria; Döring, Angela; Eriksson, Johan G.; Farmaki, Aliki-Eleni; Farrall, Martin; Ferreira, Teresa; Fischer, Krista; Forouhi, Nita G.; Friedrich, Nele; Gjesing, Anette Prior; Glorioso, Nicola; Graff, Mariaelisa; Grallert, Harald; Grarup, Niels; Gräßler, Jürgen; Grewal, Jagvir; Hamsten, Anders; Harder, Marie Neergaard; Hartman, Catharina A.; Hassinen, Maija; Hastie, Nicholas; Hattersley, Andrew Tym; Havulinna, Aki S.; Heliövaara, Markku; Hillege, Hans; Hofman, Albert; Holmen, Oddgeir; Homuth, Georg; Hottenga, Jouke-Jan; Hui, Jennie; Husemoen, Lise Lotte; Hysi, Pirro G.; Isaacs, Aaron; Ittermann, Till; Jalilzadeh, Shapour; James, Alan L.; Jørgensen, Torben; Jousilahti, Pekka; Jula, Antti; Marie Justesen, Johanne; Justice, Anne E.; Kähönen, Mika; Karaleftheri, Maria; Tee Khaw, Kay; Keinanen-Kiukaanniemi, Sirkka M.; Kinnunen, Leena; Knekt, Paul B.; Koistinen, Heikki A.; Kolcic, Ivana; Kooner, Ishminder K.; Koskinen, Seppo; Kovacs, Peter; Kyriakou, Theodosios; Laitinen, Tomi; Langenberg, Claudia; Lewin, Alexandra M.; Lichtner, Peter; Lindgren, Cecilia M.; Lindström, Jaana; Linneberg, Allan; Lorbeer, Roberto; Lorentzon, Mattias; Luben, Robert; Lyssenko, Valeriya; Männistö, Satu; Manunta, Paolo; Leach, Irene Mateo; McArdle, Wendy L.; Mcknight, Barbara; Mohlke, Karen L.; Mihailov, Evelin; Milani, Lili; Mills, Rebecca; Montasser, May E.; Morris, Andrew P.; Müller, Gabriele; Musk, Arthur W.; Narisu, Narisu; Ong, Ken K.; Oostra, Ben A.; Osmond, Clive; Palotie, Aarno; Pankow, James S.; Paternoster, Lavinia; Penninx, Brenda W.; Pichler, Irene; Pilia, Maria G.; Polašek, Ozren; Pramstaller, Peter P.; Raitakari, Olli T; Rankinen, Tuomo; Rao, D. C.; Rayner, Nigel W.; Ribel-Madsen, Rasmus; Rice, Treva K.; Richards, Marcus; Ridker, Paul M.; Rivadeneira, Fernando; Ryan, Kathy A.; Sanna, Serena; Sarzynski, Mark A.; Scholtens, Salome; Scott, Robert A.; Sebert, Sylvain; Southam, Lorraine; Sparsø, Thomas Hempel; Steinthorsdottir, Valgerdur; Stirrups, Kathleen; Stolk, Ronald P.; Strauch, Konstantin; Stringham, Heather M.; Swertz, Morris A.; Swift, Amy J.; Tönjes, Anke; Tsafantakis, Emmanouil; van der Most, Peter J.; Van Vliet-Ostaptchouk, Jana V.; Vandenput, Liesbeth; Vartiainen, Erkki; Venturini, Cristina; Verweij, Niek; Viikari, Jorma S.; Vitart, Veronique; Vohl, Marie-Claude; Vonk, Judith M.; Waeber, Gérard; Widén, Elisabeth; Willemsen, Gonneke; Wilsgaard, Tom; Winkler, Thomas W.; Wright, Alan F.; Yerges-Armstrong, Laura M.; Hua Zhao, Jing; Carola Zillikens, M.; Boomsma, Dorret I.; Bouchard, Claude; Chambers, John C.; Chasman, Daniel I.; Cusi, Daniele; Gansevoort, Ron T.; Gieger, Christian; Hansen, Torben; Hicks, Andrew A.; Hu, Frank; Hveem, Kristian; Jarvelin, Marjo-Riitta; Kajantie, Eero; Kooner, Jaspal S.; Kuh, Diana; Kuusisto, Johanna; Laakso, Markku; Lakka, Timo A.; Lehtimäki, Terho; Metspalu, Andres; Njølstad, Inger; Ohlsson, Claes; Oldehinkel, Albertine J.; Palmer, Lyle J.; Pedersen, Oluf; Perola, Markus; Peters, Annette; Psaty, Bruce M.; Puolijoki, Hannu; Rauramaa, Rainer; Rudan, Igor; Salomaa, Veikko; Schwarz, Peter E. H.; Shudiner, Alan R.; Smit, Jan H.; Sørensen, Thorkild I. A.; Spector, Timothy D.; Stefansson, Kari; Stumvoll, Michael; Tremblay, Angelo; Tuomilehto, Jaakko; Uitterlinden, André G.; Uusitupa, Matti; Völker, Uwe; Vollenweider, Peter; Wareham, Nicholas J.; Watkins, Hugh; Wilson, James F.; Zeggini, Eleftheria; Abecasis, Goncalo R.; Boehnke, Michael; Borecki, Ingrid B.; Deloukas, Panos; van Duijn, Cornelia M.; Fox, Caroline; Groop, Leif C.; Heid, Iris M.; Hunter, David J.; Kaplan, Robert C.; McCarthy, Mark I.; North, Kari E.; O'Connell, Jeffrey R.; Schlessinger, David; Thorsteinsdottir, Unnur; Strachan, David P.; Frayling, Timothy; Hirschhorn, Joel N.; Müller-Nurasyid, Martina; Loos, Ruth J. F.

    2016-01-01

    Large consortia have revealed hundreds of genetic loci associated with anthropometric traits, one trait at a time. We examined whether genetic variants affect body shape as a composite phenotype that is represented by a combination of anthropometric traits. We developed an approach that calculates averaged PCs (AvPCs) representing body shape derived from six anthropometric traits (body mass index, height, weight, waist and hip circumference, waist-to-hip ratio). The first four AvPCs explain >99% of the variability, are heritable, and associate with cardiometabolic outcomes. We performed genome-wide association analyses for each body shape composite phenotype across 65 studies and meta-analysed summary statistics. We identify six novel loci: LEMD2 and CD47 for AvPC1, RPS6KA5/C14orf159 and GANAB for AvPC3, and ARL15 and ANP32 for AvPC4. Our findings highlight the value of using multiple traits to define complex phenotypes for discovery, which are not captured by single-trait analyses, and may shed light onto new pathways. PMID:27876822

  8. Cumulative organic anion transporter-mediated drug-drug interaction potential of multiple components in salvia miltiorrhiza (danshen) preparations.

    Science.gov (United States)

    Wang, Li; Venitz, Jürgen; Sweet, Douglas H

    2014-12-01

    To evaluate organic anion transporter-mediated drug-drug interaction (DDI) potential for individual active components of Danshen (Salvia miltiorrhiza) vs. combinations using in vitro and in silico approaches. Inhibition profiles for single Danshen components and combinations were generated in stably-expressing human (h)OAT1 and hOAT3 cells. Plasma concentration-time profiles for compounds were estimated from in vivo human data using an i.v. two-compartment model (with first-order elimination). The cumulative DDI index was proposed as an indicator of DDI potential for combination products. This index was used to evaluate the DDI potential for Danshen injectables from 16 different manufacturers and 14 different lots from a single manufacturer. The cumulative DDI index predicted in vivo inhibition potentials, 82% (hOAT1) and 74% (hOAT3), comparable with those observed in vitro, 72 ± 7% (hOAT1) and 81 ± 10% (hOAT3), for Danshen component combinations. Using simulated unbound Cmax values, a wide range in cumulative DDI index between manufacturers, and between lots, was predicted. Many products exhibited a cumulative DDI index > 1 (50% inhibition). Danshen injectables will likely exhibit strong potential to inhibit hOAT1 and hOAT3 function in vivo. The proposed cumulative DDI index might improve prediction of DDI potential of herbal medicines or pharmaceutical preparations containing multiple components.

  9. Stimulus-Related Independent Component and Voxel-Wise Analysis of Human Brain Activity during Free Viewing of a Feature Film

    Science.gov (United States)

    Lahnakoski, Juha M.; Salmi, Juha; Jääskeläinen, Iiro P.; Lampinen, Jouko; Glerean, Enrico; Tikka, Pia; Sams, Mikko

    2012-01-01

    Understanding how the brain processes stimuli in a rich natural environment is a fundamental goal of neuroscience. Here, we showed a feature film to 10 healthy volunteers during functional magnetic resonance imaging (fMRI) of hemodynamic brain activity. We then annotated auditory and visual features of the motion picture to inform analysis of the hemodynamic data. The annotations were fitted to both voxel-wise data and brain network time courses extracted by independent component analysis (ICA). Auditory annotations correlated with two independent components (IC) disclosing two functional networks, one responding to variety of auditory stimulation and another responding preferentially to speech but parts of the network also responding to non-verbal communication. Visual feature annotations correlated with four ICs delineating visual areas according to their sensitivity to different visual stimulus features. In comparison, a separate voxel-wise general linear model based analysis disclosed brain areas preferentially responding to sound energy, speech, music, visual contrast edges, body motion and hand motion which largely overlapped the results revealed by ICA. Differences between the results of IC- and voxel-based analyses demonstrate that thorough analysis of voxel time courses is important for understanding the activity of specific sub-areas of the functional networks, while ICA is a valuable tool for revealing novel information about functional connectivity which need not be explained by the predefined model. Our results encourage the use of naturalistic stimuli and tasks in cognitive neuroimaging to study how the brain processes stimuli in rich natural environments. PMID:22496909

  10. Stimulus-related independent component and voxel-wise analysis of human brain activity during free viewing of a feature film.

    Science.gov (United States)

    Lahnakoski, Juha M; Salmi, Juha; Jääskeläinen, Iiro P; Lampinen, Jouko; Glerean, Enrico; Tikka, Pia; Sams, Mikko

    2012-01-01

    Understanding how the brain processes stimuli in a rich natural environment is a fundamental goal of neuroscience. Here, we showed a feature film to 10 healthy volunteers during functional magnetic resonance imaging (fMRI) of hemodynamic brain activity. We then annotated auditory and visual features of the motion picture to inform analysis of the hemodynamic data. The annotations were fitted to both voxel-wise data and brain network time courses extracted by independent component analysis (ICA). Auditory annotations correlated with two independent components (IC) disclosing two functional networks, one responding to variety of auditory stimulation and another responding preferentially to speech but parts of the network also responding to non-verbal communication. Visual feature annotations correlated with four ICs delineating visual areas according to their sensitivity to different visual stimulus features. In comparison, a separate voxel-wise general linear model based analysis disclosed brain areas preferentially responding to sound energy, speech, music, visual contrast edges, body motion and hand motion which largely overlapped the results revealed by ICA. Differences between the results of IC- and voxel-based analyses demonstrate that thorough analysis of voxel time courses is important for understanding the activity of specific sub-areas of the functional networks, while ICA is a valuable tool for revealing novel information about functional connectivity which need not be explained by the predefined model. Our results encourage the use of naturalistic stimuli and tasks in cognitive neuroimaging to study how the brain processes stimuli in rich natural environments.

  11. Stimulus-related independent component and voxel-wise analysis of human brain activity during free viewing of a feature film.

    Directory of Open Access Journals (Sweden)

    Juha M Lahnakoski

    Full Text Available Understanding how the brain processes stimuli in a rich natural environment is a fundamental goal of neuroscience. Here, we showed a feature film to 10 healthy volunteers during functional magnetic resonance imaging (fMRI of hemodynamic brain activity. We then annotated auditory and visual features of the motion picture to inform analysis of the hemodynamic data. The annotations were fitted to both voxel-wise data and brain network time courses extracted by independent component analysis (ICA. Auditory annotations correlated with two independent components (IC disclosing two functional networks, one responding to variety of auditory stimulation and another responding preferentially to speech but parts of the network also responding to non-verbal communication. Visual feature annotations correlated with four ICs delineating visual areas according to their sensitivity to different visual stimulus features. In comparison, a separate voxel-wise general linear model based analysis disclosed brain areas preferentially responding to sound energy, speech, music, visual contrast edges, body motion and hand motion which largely overlapped the results revealed by ICA. Differences between the results of IC- and voxel-based analyses demonstrate that thorough analysis of voxel time courses is important for understanding the activity of specific sub-areas of the functional networks, while ICA is a valuable tool for revealing novel information about functional connectivity which need not be explained by the predefined model. Our results encourage the use of naturalistic stimuli and tasks in cognitive neuroimaging to study how the brain processes stimuli in rich natural environments.

  12. Independent and joint associations of TV viewing time and snack food consumption with the metabolic syndrome and its components; a cross-sectional study in Australian adults

    Science.gov (United States)

    2013-01-01

    Background Television (TV) viewing time is positively associated with the metabolic syndrome (MetS) in adults. However, the mechanisms through which TV viewing time is associated with MetS risk remain unclear. There is evidence that the consumption of energy-dense, nutrient poor snack foods increases during TV viewing time among adults, suggesting that these behaviors may jointly contribute towards MetS risk. While the association between TV viewing time and the MetS has previously been shown to be independent of adult’s overall dietary intake, the specific influence of snack food consumption on the relationship is yet to be investigated. The purpose of this study was to examine the independent and joint associations of daily TV viewing time and snack food consumption with the MetS and its components in a sample of Australian adults. Methods Population-based, cross-sectional study of 3,110 women and 2,572 men (>35 years) without diabetes or cardiovascular disease. Participants were recruited between May 1999 and Dec 2000 in the six states and the Northern Territory of Australia. Participants were categorised according to self-reported TV viewing time (low: 0-2 hr/d; high: >2 hr/d) and/or consumption of snack foods (low: 0-3 serves/d; high: >3 serves/d). Multivariate odds ratios [95% CI] for the MetS and its components were estimated using gender-specific, forced entry logistic regression. Results OR [95% CI] for the MetS was 3.59 [2.25, 5.74] (p≤0.001) in women and 1.45 [1.02, 3.45] (p = 0.04) in men who jointly reported high TV viewing time and high snack food consumption. Obesity, insulin resistance and hypertension (women only) were also jointly associated with high TV viewing time and high snack food consumption. Further adjustment for diet quality and central adiposity maintained the associations in women. High snack food consumption was also shown to be independently associated with MetS risk [OR: 1.94 (95% CI: 1.45, 2.60), p snack food

  13. Independent and joint associations of TV viewing time and snack food consumption with the metabolic syndrome and its components; a cross-sectional study in Australian adults.

    Science.gov (United States)

    Thorp, Alicia A; McNaughton, Sarah A; Owen, Neville; Dunstan, David W

    2013-08-09

    Television (TV) viewing time is positively associated with the metabolic syndrome (MetS) in adults. However, the mechanisms through which TV viewing time is associated with MetS risk remain unclear. There is evidence that the consumption of energy-dense, nutrient poor snack foods increases during TV viewing time among adults, suggesting that these behaviors may jointly contribute towards MetS risk. While the association between TV viewing time and the MetS has previously been shown to be independent of adult's overall dietary intake, the specific influence of snack food consumption on the relationship is yet to be investigated. The purpose of this study was to examine the independent and joint associations of daily TV viewing time and snack food consumption with the MetS and its components in a sample of Australian adults. Population-based, cross-sectional study of 3,110 women and 2,572 men (>35 years) without diabetes or cardiovascular disease. Participants were recruited between May 1999 and Dec 2000 in the six states and the Northern Territory of Australia. Participants were categorised according to self-reported TV viewing time (low: 0-2 hr/d; high: >2 hr/d) and/or consumption of snack foods (low: 0-3 serves/d; high: >3 serves/d). Multivariate odds ratios [95% CI] for the MetS and its components were estimated using gender-specific, forced entry logistic regression. OR [95% CI] for the MetS was 3.59 [2.25, 5.74] (p≤0.001) in women and 1.45 [1.02, 3.45] (p = 0.04) in men who jointly reported high TV viewing time and high snack food consumption. Obesity, insulin resistance and hypertension (women only) were also jointly associated with high TV viewing time and high snack food consumption. Further adjustment for diet quality and central adiposity maintained the associations in women. High snack food consumption was also shown to be independently associated with MetS risk [OR: 1.94 (95% CI: 1.45, 2.60), p snack food consumption are independently and

  14. Unique effects of energy versus estrogen deficiency on multiple components of bone strength in exercising women.

    Science.gov (United States)

    Southmayd, E A; Mallinson, R J; Williams, N I; Mallinson, D J; De Souza, M J

    2017-04-01

    Many female athletes are energy and/or estrogen deficient, but the independent effects on bone health have not been isolated. Energy deficiency was detrimental at the tibia while estrogen deficiency was detrimental at the radius. Nutrition must be considered alongside menstrual recovery when addressing compromised bone health in female athletes. The purpose of this study was to describe volumetric bone mineral density (vBMD), bone geometry, and estimated bone strength in exercising women (n = 60) grouped according to energy status (energy replete (EnR: n = 30) vs. energy deficient (EnD: n = 30)) and estrogen status (estrogen replete (E 2 R: n = 33) vs. estrogen deficient (E 2 D: n = 27)), resulting in four distinct groups: EnR + E 2 R (n = 17), EnR + E 2 D (n = 13), EnD + E 2 R (n = 16), EnD + E 2 D (n = 14). Energy status was determined using the ratio of measured to predicted resting energy expenditure (mREE/pREE). Estrogen status was based on self-reported menstrual status confirmed by daily evaluation of urinary estrone-1-glucoronide (E1G), pregnanediol glucuronide (PdG), and luteinizing hormone (LH). Eumenorrheic women were considered E 2 R, amenorrheic women were E 2 D, and oligomenorrheic women were categorized based on history of menses in the past year. Bone was assessed using peripheral quantitative computed tomography (pQCT). EnD women exhibited lower total vBMD, trabecular vBMD, cortical area, and BSI at the distal tibia and lower total vBMD, smaller cortical area and cortical thickness, and larger endosteal circumference at the proximal tibia compared to EnR women (p < 0.042). E 2 D women had lower total and cortical vBMD, larger total and trabecular area, and lower BSI at the distal radius and lower cortical vBMD at the proximal radius compared to E 2 R women (p < 0.023). Energy and estrogen interacted to affect total and trabecular area at the distal tibia (p < 0.021). Efforts to correct energy deficiency, which in turn may

  15. Effect of halloysite nanotubes on the structure and function of important multiple blood components.

    Science.gov (United States)

    Wu, Keke; Feng, Ru; Jiao, Yanpeng; Zhou, Changren

    2017-06-01

    Many researchers have investigated the application of halloysite nanotubes (HNTs) in biomedicine, because of their special nanoscale hollow tubular structure. Although the cytocompatibility of HNTs has been studied, their blood compatibility has not been systematically investigated. In this work, the effect of HNTs on the structure and function of different blood components has been studied, including the morphology and hemolysis of red blood cells (RBCs). Based on scanning electron microscopy (SEM) observations, optical density test and flow cytometry analysis, we found that HNTs can affect the morphology and membrane integrity of RBCs in phosphate buffered saline (PBS) in a content-dependent way. In particular, based on UV-vis absorption spectra, fluorescence spectra and circular dichroism (CD) spectra, HNTs can alter the secondary structure and conformation of human fibrinogen and γ-globulins. In addition, the detection of biomarker molecules C3a and C5a in plasma suggests that HNTs can trigger complement activation. In the blood clotting assay, HNTs were found to significantly prolong the activated partial thromboplastin time (APTT), shorten the prothrombin time (PT) of platelet-poor plasma (PPP), and change the thromboelastography (TEG) parameters of whole blood coagulation. Furthermore, confocal laser scanning microscopy and flow cytometry analysis were used to test intracellular uptake by macrophages, and the cellular uptake of HNTs in the RAW 264.7 was found to be content-dependent, but not time-dependent. These findings provide insight for the potential use of HNTs as biofriendly nanocontainers for biomaterials in vivo. Copyright © 2017 Elsevier B.V. All rights reserved.

  16. Multiple component patient safety intervention in English hospitals: controlled evaluation of second phase.

    Science.gov (United States)

    Benning, Amirta; Dixon-Woods, Mary; Nwulu, Ugochi; Ghaleb, Maisoon; Dawson, Jeremy; Barber, Nick; Franklin, Bryony Dean; Girling, Alan; Hemming, Karla; Carmalt, Martin; Rudge, Gavin; Naicker, Thirumalai; Kotecha, Amit; Derrington, M Clare; Lilford, Richard

    2011-02-03

    To independently evaluate the impact of the second phase of the Health Foundation's Safer Patients Initiative (SPI2) on a range of patient safety measures. Design A controlled before and after design. Five substudies: survey of staff attitudes; review of case notes from high risk (respiratory) patients in medical wards; review of case notes from surgical patients; indirect evaluation of hand hygiene by measuring hospital use of handwashing materials; measurement of outcomes (adverse events, mortality among high risk patients admitted to medical wards, patients' satisfaction, mortality in intensive care, rates of hospital acquired infection). Setting NHS hospitals in England. Nine hospitals participating in SPI2 and nine matched control hospitals. The SPI2 intervention was similar to the SPI1, with somewhat modified goals, a slightly longer intervention period, and a smaller budget per hospital. One of the scores (organisational climate) showed a significant (P = 0.009) difference in rate of change over time, which favoured the control hospitals, though the difference was only 0.07 points on a five point scale. Results of the explicit case note reviews of high risk medical patients showed that certain practices improved over time in both control and SPI2 hospitals (and none deteriorated), but there were no significant differences between control and SPI2 hospitals. Monitoring of vital signs improved across control and SPI2 sites. This temporal effect was significant for monitoring the respiratory rate at both the six hour (adjusted odds ratio 2.1, 99% confidence interval 1.0 to 4.3; P = 0.010) and 12 hour (2.4, 1.1 to 5.0; P = 0.002) periods after admission. There was no significant effect of SPI for any of the measures of vital signs. Use of a recommended system for scoring the severity of pneumonia improved from 1.9% (1/52) to 21.4% (12/56) of control and from 2.0% (1/50) to 41.7% (25/60) of SPI2 patients. This temporal change was significant (7.3, 1.4 to 37.7; P

  17. Multiple component patient safety intervention in English hospitals: controlled evaluation of second phase

    Science.gov (United States)

    Benning, Amirta; Dixon-Woods, Mary; Nwulu, Ugochi; Ghaleb, Maisoon; Dawson, Jeremy; Barber, Nick; Franklin, Bryony Dean; Girling, Alan; Hemming, Karla; Carmalt, Martin; Rudge, Gavin; Naicker, Thirumalai; Kotecha, Amit; Derrington, M Clare

    2011-01-01

    Objective To independently evaluate the impact of the second phase of the Health Foundation’s Safer Patients Initiative (SPI2) on a range of patient safety measures. Design A controlled before and after design. Five substudies: survey of staff attitudes; review of case notes from high risk (respiratory) patients in medical wards; review of case notes from surgical patients; indirect evaluation of hand hygiene by measuring hospital use of handwashing materials; measurement of outcomes (adverse events, mortality among high risk patients admitted to medical wards, patients’ satisfaction, mortality in intensive care, rates of hospital acquired infection). Setting NHS hospitals in England. Participants Nine hospitals participating in SPI2 and nine matched control hospitals. Intervention The SPI2 intervention was similar to the SPI1, with somewhat modified goals, a slightly longer intervention period, and a smaller budget per hospital. Results One of the scores (organisational climate) showed a significant (P=0.009) difference in rate of change over time, which favoured the control hospitals, though the difference was only 0.07 points on a five point scale. Results of the explicit case note reviews of high risk medical patients showed that certain practices improved over time in both control and SPI2 hospitals (and none deteriorated), but there were no significant differences between control and SPI2 hospitals. Monitoring of vital signs improved across control and SPI2 sites. This temporal effect was significant for monitoring the respiratory rate at both the six hour (adjusted odds ratio 2.1, 99% confidence interval 1.0 to 4.3; P=0.010) and 12 hour (2.4, 1.1 to 5.0; P=0.002) periods after admission. There was no significant effect of SPI for any of the measures of vital signs. Use of a recommended system for scoring the severity of pneumonia improved from 1.9% (1/52) to 21.4% (12/56) of control and from 2.0% (1/50) to 41.7% (25/60) of SPI2 patients. This temporal

  18. Multiple Scattering Principal Component-based Radiative Transfer Model (PCRTM) from Far IR to UV-Vis

    Science.gov (United States)

    Liu, X.; Wu, W.; Yang, Q.

    2017-12-01

    Modern satellite hyperspectral satellite remote sensors such as AIRS, CrIS, IASI, CLARREO all require accurate and fast radiative transfer models that can deal with multiple scattering of clouds and aerosols to explore the information contents. However, performing full radiative transfer calculations using multiple stream methods such as discrete ordinate (DISORT), doubling and adding (AD), successive order of scattering order of scattering (SOS) are very time consuming. We have developed a principal component-based radiative transfer model (PCRTM) to reduce the computational burden by orders of magnitudes while maintain high accuracy. By exploring spectral correlations, the PCRTM reduce the number of radiative transfer calculations in frequency domain. It further uses a hybrid stream method to decrease the number of calls to the computational expensive multiple scattering calculations with high stream numbers. Other fast parameterizations have been used in the infrared spectral region reduce the computational time to milliseconds for an AIRS forward simulation (2378 spectral channels). The PCRTM has been development to cover spectral range from far IR to UV-Vis. The PCRTM model have been be used for satellite data inversions, proxy data generation, inter-satellite calibrations, spectral fingerprinting, and climate OSSE. We will show examples of applying the PCRTM to single field of view cloudy retrievals of atmospheric temperature, moisture, traces gases, clouds, and surface parameters. We will also show how the PCRTM are used for the NASA CLARREO project.

  19. Fine-scale mapping of 8q24 locus identifies multiple independent risk variants for breast cancer

    NARCIS (Netherlands)

    J. Shi (Jiajun); Zhang, Y. (Yanfeng); W. Zheng (Wei); K. Michailidou (Kyriaki); M. Ghoussaini (Maya); M.K. Bolla (Manjeet K.); Wang, Q. (Qin); J. Dennis (Joe); Lush, M. (Michael); R.L. Milne (Roger); X.-O. Shu (Xiao-Ou); J. Beesley (Jonathan); S. Kar (Siddhartha); I.L. Andrulis (Irene); H. Anton-Culver (Hoda); Arndt, V. (Volker); M.W. Beckmann (Matthias); Z. Zhao (Zhiguo); Guo, X. (Xingyi); J. Benítez (Javier); A. Beeghly-Fadiel (Alicia); W.J. Blot (William); N.V. Bogdanova (Natalia); S.E. Bojesen (Stig); H. Brauch (Hiltrud); H. Brenner (Hermann); L.A. Brinton (Louise); A. Broeks (Annegien); T. Brüning (Thomas); B. Burwinkel (Barbara); H. Cai (Hui); S. Canisius (Sander); J. Chang-Claude (Jenny); Choi, J.-Y. (Ji-Yeob); F.J. Couch (Fergus); A. Cox (Angela); S.S. Cross (Simon); K. Czene (Kamila); H. Darabi (Hatef); P. Devilee (Peter); A. Droit (Arnaud); T. Dörk (Thilo); P.A. Fasching (Peter); O. Fletcher (Olivia); H. Flyger (Henrik); F. Fostira (Florentia); Gaborieau, V. (Valerie); M. García-Closas (Montserrat); G.G. Giles (Graham); Grip, M. (Mervi); P. Guénel (Pascal); C.A. Haiman (Christopher A.); U. Hamann (Ute); J.M. Hartman (Joost); X. Miao; A. Hollestelle (Antoinette); J.L. Hopper (John); Hsiung, C.-N. (Chia-Ni); H. Ito (Hidemi); A. Jakubowska (Anna); Johnson, N. (Nichola); D. Torres (Diana); M. Kabisch (Maria); D. Kang (Daehee); S. Khan (Sofia); J.A. Knight (Julia); V-M. Kosma (Veli-Matti); Lambrechts, D. (Diether); J. Li (Jingmei); A. Lindblom (Annika); A. Lophatananon (Artitaya); J. Lubinski (Jan); A. Mannermaa (Arto); S. Manoukian (Siranoush); L. Le Marchand (Loic); S. Margolin (Sara); Marme, F. (Frederik); K. Matsuo (Keitaro); C.A. McLean (Catriona Ann); A. Meindl (Alfons); K.R. Muir (K.); S.L. Neuhausen (Susan); H. Nevanlinna (Heli); S. Nord (Silje); A.-L. Borresen-Dale (Anne-Lise); J.E. Olson (Janet); N. Orr (Nick); A.M.W. van den Ouweland (Ans); P. Peterlongo (Paolo); T.C. Putti (Thomas Choudary); Rudolph, A. (Anja); Sangrajrang, S. (Suleeporn); E.J. Sawyer (Elinor); M.K. Schmidt (Marjanka); R.K. Schmutzler (Rita); C.-Y. Shen (Chen-Yang); M.-F. Hou (Ming-Feng); M. Shrubsole (Martha); M.C. Southey (Melissa); A.J. Swerdlow (Anthony ); Hwang Teo, S. (Soo); B. Thienpont (Bernard); A.E. Toland (Amanda); R.A.E.M. Tollenaar (Rob); I.P. Tomlinson (Ian); T. Truong (Thérèse); C.-C. Tseng (Chiu-Chen); W. Wen (Wanqing); R. Winqvist (Robert); A.H. Wu (Anna); C. Har Yip (Cheng); P.M. Zamora (Pilar M.); Zheng, Y. (Ying); O.A.M. Floris; Cheng, C.-Y. (Ching-Yu); M.J. Hooning (Maartje); J.W.M. Martens (John); C.M. Seynaeve (Caroline); V. Kristensen (Vessela); P. Hall (Per); P.D.P. Pharoah (Paul); J. Simard (Jacques); G. Chenevix-Trench (Georgia); A.M. Dunning (Alison); A.C. Antoniou (Antonis C.); D.F. Easton (Douglas F.); Q. Cai (Qiuyin); J. Long (Jirong)

    2016-01-01

    textabstractPrevious genome-wide association studies among women of European ancestry identified two independent breast cancer susceptibility loci represented by single nucleotide polymorphisms (SNPs) rs13281615 and rs11780156 at 8q24. A fine-mapping study across 2.06 Mb

  20. [Multiple analysis of the difference in intestinal absorption between the main components and the extract of Glycyrrhiza uralensis].

    Science.gov (United States)

    Wu, Qing-Qing; Chen, Yan; Xin, Ran; Wang, Jin-Yan; Zhou, Lei; Yuan, Ling; Jia, Xiao-Bin

    2012-05-01

    The aim of this study is to investigate the rat intestinal absorption behavior of two main active components, liquiritin, glycyrrhizin and the extract of Glycyrrhiza uralensis. The rat intestinal perfusion model was employed. Concentrations of the compounds of the interest in the intestinal perfusate, bile and plasma samples were determined by HPLC and UPLC. At the same time, the intestinal enzymes incubation test and the partition coefficient determination, the absorption of liquiritin and glycyrrhizin alone and the extract were multiple analyzed. The results showed that the P(eff) (effective permeability) of liquiritin or glycyrrhizin alone or the extract was less than 0.3, which suggested their poor absorption in the intestine. The P(eff) of the two main active components or the extract was not significantly different in duodenum, jejunum, colon and ileum segment. The P(eff) of the glycyrrhizin in the extract had no significant difference in the four intestinal segments compared with the glycyrrhizin alone. The absorption of the liquiritin displayed significant difference (P components might not increase the amount of liquiritin and glycyrrhizin in the bile and plasma within the duration of the test.

  1. Suppression of the µ rhythm during speech and non-speech discrimination revealed by independent component analysis: implications for sensorimotor integration in speech processing.

    Science.gov (United States)

    Bowers, Andrew; Saltuklaroglu, Tim; Harkrider, Ashley; Cuellar, Megan

    2013-01-01

    Constructivist theories propose that articulatory hypotheses about incoming phonetic targets may function to enhance perception by limiting the possibilities for sensory analysis. To provide evidence for this proposal, it is necessary to map ongoing, high-temporal resolution changes in sensorimotor activity (i.e., the sensorimotor μ rhythm) to accurate speech and non-speech discrimination performance (i.e., correct trials.). Sixteen participants (15 female and 1 male) were asked to passively listen to or actively identify speech and tone-sweeps in a two-force choice discrimination task while the electroencephalograph (EEG) was recorded from 32 channels. The stimuli were presented at signal-to-noise ratios (SNRs) in which discrimination accuracy was high (i.e., 80-100%) and low SNRs producing discrimination performance at chance. EEG data were decomposed using independent component analysis and clustered across participants using principle component methods in EEGLAB. ICA revealed left and right sensorimotor µ components for 14/16 and 13/16 participants respectively that were identified on the basis of scalp topography, spectral peaks, and localization to the precentral and postcentral gyri. Time-frequency analysis of left and right lateralized µ component clusters revealed significant (pFDRspeech discrimination trials relative to chance trials following stimulus offset. Findings are consistent with constructivist, internal model theories proposing that early forward motor models generate predictions about likely phonemic units that are then synthesized with incoming sensory cues during active as opposed to passive processing. Future directions and possible translational value for clinical populations in which sensorimotor integration may play a functional role are discussed.

  2. Multiple independent variants at the TERT locus are associated with telomere length and risks of breast and ovarian cancer

    NARCIS (Netherlands)

    Bojesen, Stig E.; Pooley, Karen A.; Johnatty, Sharon E.; Beesley, Jonathan; Michailidou, Kyriaki; Tyrer, Jonathan P.; Edwards, Stacey L.; Pickett, Hilda A.; Shen, Howard C.; Smart, Chanel E.; Hillman, Kristine M.; Mai, Phuong L.; Lawrenson, Kate; Stutz, Michael D.; Lu, Yi; Karevan, Rod; Woods, Nicholas; Johnston, Rebecca L.; French, Juliet D.; Chen, Xiaoqing; Weischer, Maren; Nielsen, Sune F.; Maranian, Melanie J.; Ghoussaini, Maya; Ahmed, Shahana; Baynes, Caroline; Bolla, Manjeet K.; Wang, Qin; Dennis, Joe; McGuffog, Lesley; Barrowdale, Daniel; Lee, Andrew; Healey, Sue; Lush, Michael; Tessier, Daniel C.; Vincent, Daniel; Bacot, Françis; Vergote, Ignace; Lambrechts, Sandrina; Despierre, Evelyn; Risch, Harvey A.; González-Neira, Anna; Rossing, Mary Anne; Pita, Guillermo; Doherty, Jennifer A.; Alvarez, Nuria; Larson, Melissa C.; Fridley, Brooke L.; Schoof, Nils; Chang-Claude, Jenny; Cicek, Mine S.; Peto, Julian; Kalli, Kimberly R.; Broeks, Annegien; Armasu, Sebastian M.; Schmidt, Marjanka K.; Braaf, Linde M.; Winterhoff, Boris; Nevanlinna, Heli; Konecny, Gottfried E.; Lambrechts, Diether; Rogmann, Lisa; Guénel, Pascal; Teoman, Attila; Milne, Roger L.; Garcia, Joaquin J.; Cox, Angela; Shridhar, Vijayalakshmi; Burwinkel, Barbara; Marme, Frederik; Hein, Rebecca; Sawyer, Elinor J.; Haiman, Christopher A.; Wang-Gohrke, Shan; Andrulis, Irene L.; Moysich, Kirsten B.; Hopper, John L.; Odunsi, Kunle; Lindblom, Annika; Giles, Graham G.; Brenner, Hermann; Simard, Jacques; Lurie, Galina; Fasching, Peter A.; Carney, Michael E.; Radice, Paolo; Wilkens, Lynne R.; Swerdlow, Anthony; Goodman, Marc T.; Brauch, Hiltrud; Garcia-Closas, Montserrat; Hillemanns, Peter; Winqvist, Robert; Dürst, Matthias; Devilee, Peter; Runnebaum, Ingo; Jakubowska, Anna; Lubinski, Jan; Mannermaa, Arto; Butzow, Ralf; Bogdanova, Natalia V.; Dörk, Thilo; Pelttari, Liisa M.; Zheng, Wei; Leminen, Arto; Anton-Culver, Hoda; Bunker, Clareann H.; Kristensen, Vessela; Ness, Roberta B.; Muir, Kenneth; Edwards, Robert; Meindl, Alfons; Heitz, Florian; Matsuo, Keitaro; du Bois, Andreas; Wu, Anna H.; Harter, Philipp; teo, Soo-Hwang; Schwaab, Ira; Shu, Xiao-Ou; Blot, William; Hosono, Satoyo; Kang, Daehee; Nakanishi, Toru; Hartman, Mikael; Yatabe, Yasushi; Hamann, Ute; Karlan, Beth Y.; Sangrajrang, Suleeporn; Kjaer, Susanne Krüger; Gaborieau, Valerie; Jensen, Allan; Eccles, Diana; Høgdall, Estrid; Shen, Chen-Yang; Brown, Judith; Woo, Yin Ling; Shah, Mitul; Azmi, Mat Adenan Noor; Luben, Robert; Omar, Siti Zawiah; Czene, Kamila; Vierkant, Robert A.; Nordestgaard, Børge G.; Flyger, Henrik; Vachon, Celine; Olson, Janet E.; Wang, Xianshu; Levine, Douglas A.; Rudolph, Anja; Weber, Rachel Palmieri; Flesch-Janys, Dieter; Iversen, Edwin; Nickels, Stefan; Schildkraut, Joellen M.; Silva, Isabel Dos Santos; Cramer, Daniel W.; Gibson, Lorna; Terry, Kathryn L.; Fletcher, Olivia; Vitonis, Allison F.; van der Schoot, C. Ellen; Poole, Elizabeth M.; Hogervorst, Frans B. L.; Tworoger, Shelley S.; Liu, Jianjun; Bandera, Elisa V.; Li, Jingmei; Olson, Sara H.; Humphreys, Keith; Orlow, Irene; Blomqvist, Carl; Rodriguez-Rodriguez, Lorna; Aittomäki, Kristiina; Salvesen, Helga B.; Muranen, Taru A.; Wik, Elisabeth; Brouwers, Barbara; Krakstad, Camilla; Wauters, Els; Halle, Mari K.; Wildiers, Hans; Kiemeney, Lambertus A.; Mulot, Claire; Aben, Katja K.; Laurent-Puig, Pierre; Altena, Anne Mvan; Truong, Thérèse; Massuger, Leon F. A. G.; Benitez, Javier; Pejovic, Tanja; Perez, Jose Ignacio Arias; Hoatlin, Maureen; Zamora, M. Pilar; Cook, Linda S.; Balasubramanian, Sabapathy P.; Kelemen, Linda E.; Schneeweiss, Andreas; Le, Nhu D.; Sohn, Christof; Brooks-Wilson, Angela; Tomlinson, Ian; Kerin, Michael J.; Miller, Nicola; Cybulski, Cezary; Henderson, Brian E.; Menkiszak, Janusz; Schumacher, Fredrick; Wentzensen, Nicolas; Le Marchand, Loic; Yang, Hannah P.; Mulligan, Anna Marie; Glendon, Gord; Engelholm, Svend Aage; Knight, Julia A.; Høgdall, Claus K.; Apicella, Carmel; Gore, Martin; Tsimiklis, Helen; Song, Honglin; Southey, Melissa C.; Jager, Agnes; den Ouweland, Ans M. Wvan; Brown, Robert; Martens, John W. M.; Flanagan, James M.; Kriege, Mieke; Paul, James; Margolin, Sara; Siddiqui, Nadeem; Severi, Gianluca; Whittemore, Alice S.; Baglietto, Laura; McGuire, Valerie; Stegmaier, Christa; Sieh, Weiva; Müller, Heiko; Arndt, Volker; Labrèche, France; Gao, Yu-Tang; Goldberg, Mark S.; Yang, Gong; Dumont, Martine; McLaughlin, John R.; Hartmann, Arndt; Ekici, Arif B.; Beckmann, Matthias W.; Phelan, Catherine M.; Lux, Michael P.; Permuth-Wey, Jenny; Peissel, Bernard; Sellers, Thomas A.; Ficarazzi, Filomena; Barile, Monica; Ziogas, Argyrios; Ashworth, Alan; Gentry-Maharaj, Aleksandra; Jones, Michael; Ramus, Susan J.; Orr, Nick; Menon, Usha; Pearce, Celeste L.; Brüning, Thomas; Pike, Malcolm C.; Ko, Yon-Dschun; Lissowska, Jolanta; Figueroa, Jonine; Kupryjanczyk, Jolanta; Chanock, Stephen J.; Dansonka-Mieszkowska, Agnieszka; Jukkola-Vuorinen, Arja; Rzepecka, Iwona K.; Pylkäs, Katri; Bidzinski, Mariusz; Kauppila, Saila; Hollestelle, Antoinette; Seynaeve, Caroline; Tollenaar, Rob A. E. M.; Durda, Katarzyna; Jaworska, Katarzyna; Hartikainen, Jaana M.; Kosma, Veli-Matti; Kataja, Vesa; Antonenkova, Natalia N.; Long, Jirong; Shrubsole, Martha; Deming-Halverson, Sandra; Lophatananon, Artitaya; Siriwanarangsan, Pornthep; Stewart-Brown, Sarah; Ditsch, Nina; Lichtner, Peter; Schmutzler, Rita K.; Ito, Hidemi; Iwata, Hiroji; Tajima, Kazuo; Tseng, Chiu-Chen; Stram, Daniel O.; van den Berg, David; Yip, Cheng Har; Ikram, M. Kamran; teh, Yew-Ching; Cai, Hui; Lu, Wei; Signorello, Lisa B.; Cai, Qiuyin; Noh, Dong-Young; Yoo, Keun-Young; Miao, Hui; Iau, Philip Tsau-Choong; teo, Yik Ying; McKay, James; Shapiro, Charles; Ademuyiwa, Foluso; Fountzilas, George; Hsiung, Chia-Ni; Yu, Jyh-Cherng; Hou, Ming-Feng; Healey, Catherine S.; Luccarini, Craig; Peock, Susan; Stoppa-Lyonnet, Dominique; Peterlongo, Paolo; Rebbeck, Timothy R.; Piedmonte, Marion; Singer, Christian F.; Friedman, Eitan; Thomassen, Mads; Offit, Kenneth; Hansen, Thomas V. O.; Neuhausen, Susan L.; Szabo, Csilla I.; Blanco, Ignacio; Garber, Judy; Narod, Steven A.; Weitzel, Jeffrey N.; Montagna, Marco; Olah, Edith; Godwin, Andrew K.; Yannoukakos, Drakoulis; Goldgar, David E.; Caldes, Trinidad; Imyanitov, Evgeny N.; Tihomirova, Laima; Arun, Banu K.; Campbell, Ian; Mensenkamp, Arjen R.; van Asperen, Christi J.; van Roozendaal, Kees E. P.; Meijers-Heijboer, Hanne; Collée, J. Margriet; Oosterwijk, Jan C.; Hooning, Maartje J.; Rookus, Matti A.; van der Luijt, Rob B.; Os, Theo A. Mvan; Evans, D. Gareth; Frost, Debra; Fineberg, Elena; Barwell, Julian; Walker, Lisa; Kennedy, M. John; Platte, Radka; Davidson, Rosemarie; Ellis, Steve D.; Cole, Trevor; Bressac-de Paillerets, Brigitte; Buecher, Bruno; Damiola, Francesca; Faivre, Laurence; Frenay, Marc; Sinilnikova, Olga M.; Caron, Olivier; Giraud, Sophie; Mazoyer, Sylvie; Bonadona, Valérie; Caux-Moncoutier, Virginie; Toloczko-Grabarek, Aleksandra; Gronwald, Jacek; Byrski, Tomasz; Spurdle, Amanda B.; Bonanni, Bernardo; Zaffaroni, Daniela; Giannini, Giuseppe; Bernard, Loris; Dolcetti, Riccardo; Manoukian, Siranoush; Arnold, Norbert; Engel, Christoph; Deissler, Helmut; Rhiem, Kerstin; Niederacher, Dieter; Plendl, Hansjoerg; Sutter, Christian; Wappenschmidt, Barbara; Borg, Ake; Melin, Beatrice; Rantala, Johanna; Soller, Maria; Nathanson, Katherine L.; Domchek, Susan M.; Rodriguez, Gustavo C.; Salani, Ritu; Kaulich, Daphne Gschwantler; tea, Muy-Kheng; Paluch, Shani Shimon; Laitman, Yael; Skytte, Anne-Bine; Kruse, Torben A.; Jensen, Uffe Birk; Robson, Mark; Gerdes, Anne-Marie; Ejlertsen, Bent; Foretova, Lenka; Savage, Sharon A.; Lester, Jenny; Soucy, Penny; Kuchenbaecker, Karoline B.; Olswold, Curtis; Cunningham, Julie M.; Slager, Susan; Pankratz, Vernon S.; Dicks, Ed; Lakhani, Sunil R.; Couch, Fergus J.; Hall, Per; Monteiro, Alvaro N. A.; Gayther, Simon A.; Pharoah, Paul D. P.; Reddel, Roger R.; Goode, Ellen L.; Greene, Mark H.; Easton, Douglas F.; Berchuck, Andrew; Antoniou, Antonis C.; Chenevix-Trench, Georgia; Dunning, Alison M.

    2013-01-01

    TERT-locus SNPs and leukocyte telomere measures are reportedly associated with risks of multiple cancers. Using the Illumina custom genotyping array iCOGs, we analyzed ∼480 SNPs at the TERT locus in breast (n = 103,991), ovarian (n = 39,774) and BRCA1 mutation carrier (n = 11,705) cancer cases and

  3. Multiple independent variants at the TERT locus are associated with telomere length and risks of breast and ovarian cancer

    DEFF Research Database (Denmark)

    Bojesen, Stig Egil; Pooley, Karen A; Johnatty, Sharon E

    2013-01-01

    TERT-locus SNPs and leukocyte telomere measures are reportedly associated with risks of multiple cancers. Using the Illumina custom genotyping array iCOGs, we analyzed ∼480 SNPs at the TERT locus in breast (n = 103,991), ovarian (n = 39,774) and BRCA1 mutation carrier (n = 11,705) cancer cases...

  4. Independent component and pathway-based analysis of miRNA-regulated gene expression in a model of type 1 diabetes

    Directory of Open Access Journals (Sweden)

    Hagedorn Peter H

    2011-02-01

    Full Text Available Abstract Background Several approaches have been developed for miRNA target prediction, including methods that incorporate expression profiling. However the methods are still in need of improvements due to a high false discovery rate. So far, none of the methods have used independent component analysis (ICA. Here, we developed a novel target prediction method based on ICA that incorporates both seed matching and expression profiling of miRNA and mRNA expressions. The method was applied on a cellular model of type 1 diabetes. Results Microrray profiling identified eight miRNAs (miR-124/128/192/194/204/375/672/708 with differential expression. Applying ICA on the mRNA profiling data revealed five significant independent components (ICs correlating to the experimental conditions. The five ICs also captured the miRNA expressions by explaining >97% of their variance. By using ICA, seven of the eight miRNAs showed significant enrichment of sequence predicted targets, compared to only four miRNAs when using simple negative correlation. The ICs were enriched for miRNA targets that function in diabetes-relevant pathways e.g. type 1 and type 2 diabetes and maturity onset diabetes of the young (MODY. Conclusions In this study, ICA was applied as an attempt to separate the various factors that influence the mRNA expression in order to identify miRNA targets. The results suggest that ICA is better at identifying miRNA targets than negative correlation. Additionally, combining ICA and pathway analysis constitutes a means for prioritizing between the predicted miRNA targets. Applying the method on a model of type 1 diabetes resulted in identification of eight miRNAs that appear to affect pathways of relevance to disease mechanisms in diabetes.

  5. Using 'component multiplication' in MONK to reduce pessimism in the dose rate assessment for water-filled (ullaged) transport packages

    International Nuclear Information System (INIS)

    Dean, M.H.

    2002-01-01

    The external dose rates from spent fuel packages consist of gamma ray and neutron components. The source of gamma rays is from fission products and actinides in the spent fuel and from activation products in structural components of the fuel element. Neutrons originate from spontaneous fission in actinides (for example from curium isotopes) within the spent fuel and from (alpha, n) reactions in oxide fuel. However, a significant number of neutrons are produced due to further fission within the fuel. This is known as neutron enhancement or multiplication (M). To treat the effects of enhancement, the neutron source may be scaled within the dose rate calculation. In a wet package, it has been customary to determine k effective (k eff ) for a completely water-filled package or a package with a defined water level (for the horizontal transport condition). The irradiation of the fuel is normally taken into account in calculating k eff for this purpose. The neutron enhancement is then obtained by calculating M=1/(1-k eff ), which is then applied as a source scaling factor throughout each fuel assembly. In a wet package, there is normally an ullage volume above the water level, the package only being partially flooded. The ullage volume is designed to accommodate pressure build-up within the package. Typically the top row of fuel assemblies may be partially covered and partially uncovered by water. When the above value of M is used for fuel within the dry part of the package, dose rates above the package tend to be overestimated and can limit the carrying capability of the package. (Also, a single value of M will tend to over-predict dose rate contributions from all assemblies around the periphery). Use of component multiplication (a new feature available in the MONK computer code) enables two separate values of 'k eff ' to be determined for the wet and dry parts of the package. These typically differ by a factor of three, leading to differences in the enhancement, M. Use

  6. Decoding the encoding of functional brain networks: An fMRI classification comparison of non-negative matrix factorization (NMF), independent component analysis (ICA), and sparse coding algorithms.

    Science.gov (United States)

    Xie, Jianwen; Douglas, Pamela K; Wu, Ying Nian; Brody, Arthur L; Anderson, Ariana E

    2017-04-15

    Brain networks in fMRI are typically identified using spatial independent component analysis (ICA), yet other mathematical constraints provide alternate biologically-plausible frameworks for generating brain networks. Non-negative matrix factorization (NMF) would suppress negative BOLD signal by enforcing positivity. Spatial sparse coding algorithms (L1 Regularized Learning and K-SVD) would impose local specialization and a discouragement of multitasking, where the total observed activity in a single voxel originates from a restricted number of possible brain networks. The assumptions of independence, positivity, and sparsity to encode task-related brain networks are compared; the resulting brain networks within scan for different constraints are used as basis functions to encode observed functional activity. These encodings are then decoded using machine learning, by using the time series weights to predict within scan whether a subject is viewing a video, listening to an audio cue, or at rest, in 304 fMRI scans from 51 subjects. The sparse coding algorithm of L1 Regularized Learning outperformed 4 variations of ICA (pcoding algorithms. Holding constant the effect of the extraction algorithm, encodings using sparser spatial networks (containing more zero-valued voxels) had higher classification accuracy (pcoding algorithms suggests that algorithms which enforce sparsity, discourage multitasking, and promote local specialization may capture better the underlying source processes than those which allow inexhaustible local processes such as ICA. Negative BOLD signal may capture task-related activations. Copyright © 2017 Elsevier B.V. All rights reserved.

  7. Androgen receptor-dependent and -independent mechanisms driving prostate cancer progression: Opportunities for therapeutic targeting from multiple angles

    Science.gov (United States)

    Hoang, David T; Iczkowski, Kenneth A; Kilari, Deepak; See, William; Nevalainen, Marja T

    2017-01-01

    Despite aggressive treatment for localized cancer, prostate cancer (PC) remains a leading cause of cancer-related death for American men due to a subset of patients progressing to lethal and incurable metastatic castrate-resistant prostate cancer (CRPC). Organ-confined PC is treated by surgery or radiation with or without androgen deprivation therapy (ADT), while options for locally advanced and disseminated PC include radiation combined with ADT, or systemic treatments including chemotherapy. Progression to CRPC results from failure of ADT, which targets the androgen receptor (AR) signaling axis and inhibits AR-driven proliferation and survival pathways. The exact mechanisms underlying the transition from androgen-dependent PC to CRPC remain incompletely understood. Reactivation of AR has been shown to occur in CRPC despite depletion of circulating androgens by ADT. At the same time, the presence of AR-negative cell populations in CRPC has also been identified. While AR signaling has been proposed as the primary driver of CRPC, AR-independent signaling pathways may represent additional mechanisms underlying CRPC progression. Identification of new therapeutic strategies to target both AR-positive and AR-negative PC cell populations and, thereby, AR-driven as well as non-AR-driven PC cell growth and survival mechanisms would provide a two-pronged approach to eliminate CRPC cells with potential for synthetic lethality. In this review, we provide an overview of AR-dependent and AR-independent molecular mechanisms which drive CRPC, with special emphasis on the role of the Jak2-Stat5a/b signaling pathway in promoting castrate-resistant growth of PC through both AR-dependent and AR-independent mechanisms. PMID:27741508

  8. Using synthetic data to evaluate multiple regression and principal component analyses for statistical modeling of daily building energy consumption

    Energy Technology Data Exchange (ETDEWEB)

    Reddy, T.A. (Energy Systems Lab., Texas A and M Univ., College Station, TX (United States)); Claridge, D.E. (Energy Systems Lab., Texas A and M Univ., College Station, TX (United States))

    1994-01-01

    Multiple regression modeling of monitored building energy use data is often faulted as a reliable means of predicting energy use on the grounds that multicollinearity between the regressor variables can lead both to improper interpretation of the relative importance of the various physical regressor parameters and to a model with unstable regressor coefficients. Principal component analysis (PCA) has the potential to overcome such drawbacks. While a few case studies have already attempted to apply this technique to building energy data, the objectives of this study were to make a broader evaluation of PCA and multiple regression analysis (MRA) and to establish guidelines under which one approach is preferable to the other. Four geographic locations in the US with different climatic conditions were selected and synthetic data sequence representative of daily energy use in large institutional buildings were generated in each location using a linear model with outdoor temperature, outdoor specific humidity and solar radiation as the three regression variables. MRA and PCA approaches were then applied to these data sets and their relative performances were compared. Conditions under which PCA seems to perform better than MRA were identified and preliminary recommendations on the use of either modeling approach formulated. (orig.)

  9. Performance optimization of Sparse Matrix-Vector Multiplication for multi-component PDE-based applications using GPUs

    KAUST Repository

    Abdelfattah, Ahmad

    2016-05-23

    Simulations of many multi-component PDE-based applications, such as petroleum reservoirs or reacting flows, are dominated by the solution, on each time step and within each Newton step, of large sparse linear systems. The standard solver is a preconditioned Krylov method. Along with application of the preconditioner, memory-bound Sparse Matrix-Vector Multiplication (SpMV) is the most time-consuming operation in such solvers. Multi-species models produce Jacobians with a dense block structure, where the block size can be as large as a few dozen. Failing to exploit this dense block structure vastly underutilizes hardware capable of delivering high performance on dense BLAS operations. This paper presents a GPU-accelerated SpMV kernel for block-sparse matrices. Dense matrix-vector multiplications within the sparse-block structure leverage optimization techniques from the KBLAS library, a high performance library for dense BLAS kernels. The design ideas of KBLAS can be applied to block-sparse matrices. Furthermore, a technique is proposed to balance the workload among thread blocks when there are large variations in the lengths of nonzero rows. Multi-GPU performance is highlighted. The proposed SpMV kernel outperforms existing state-of-the-art implementations using matrices with real structures from different applications. Copyright © 2016 John Wiley & Sons, Ltd. Copyright © 2016 John Wiley & Sons, Ltd.

  10. Performance optimization of Sparse Matrix-Vector Multiplication for multi-component PDE-based applications using GPUs

    KAUST Repository

    Abdelfattah, Ahmad; Ltaief, Hatem; Keyes, David E.; Dongarra, Jack

    2016-01-01

    Simulations of many multi-component PDE-based applications, such as petroleum reservoirs or reacting flows, are dominated by the solution, on each time step and within each Newton step, of large sparse linear systems. The standard solver is a preconditioned Krylov method. Along with application of the preconditioner, memory-bound Sparse Matrix-Vector Multiplication (SpMV) is the most time-consuming operation in such solvers. Multi-species models produce Jacobians with a dense block structure, where the block size can be as large as a few dozen. Failing to exploit this dense block structure vastly underutilizes hardware capable of delivering high performance on dense BLAS operations. This paper presents a GPU-accelerated SpMV kernel for block-sparse matrices. Dense matrix-vector multiplications within the sparse-block structure leverage optimization techniques from the KBLAS library, a high performance library for dense BLAS kernels. The design ideas of KBLAS can be applied to block-sparse matrices. Furthermore, a technique is proposed to balance the workload among thread blocks when there are large variations in the lengths of nonzero rows. Multi-GPU performance is highlighted. The proposed SpMV kernel outperforms existing state-of-the-art implementations using matrices with real structures from different applications. Copyright © 2016 John Wiley & Sons, Ltd. Copyright © 2016 John Wiley & Sons, Ltd.

  11. An Introductory Review of Parallel Independent Component Analysis (p-ICA and a Guide to Applying p-ICA to Genetic Data and Imaging Phenotypes to Identify Disease-Associated Biological Pathways and Systems in Common Complex Disorders

    Directory of Open Access Journals (Sweden)

    Godfrey D Pearlson

    2015-09-01

    Full Text Available Complex inherited phenotypes, including those for many common medical and psychiatric diseases, are most likely underpinned by multiple genes contributing to interlocking molecular biological processes, along with environmental factors (Owen et al., 2010. Despite this, genotyping strategies for complex, inherited, disease-related phenotypes mostly employ univariate analyses, e.g. genome wide association (GWA. Such procedures most often identify isolated risk-related SNPs or loci, not the underlying biological pathways necessary to help guide the development of novel treatment approaches. This article focuses on the multivariate analysis strategy of parallel (i.e. simultaneous combination of SNP and neuroimage information independent component analysis (p-ICA, which typically yields large clusters of functionally related SNPs statistically correlated with phenotype components, whose overall molecular biologic relevance is inferred subsequently using annotation software suites. Because this is a novel approach, whose details are relatively new to the field we summarize its underlying principles and address conceptual questions regarding interpretation of resulting data and provide practical illustrations of the method.

  12. THE COMPOSITION OF THE INTERIOR OF COMET 73P/SCHWASSMANN-WACHMANN 3: RESULTS FROM NARROWBAND PHOTOMETRY OF MULTIPLE COMPONENTS

    International Nuclear Information System (INIS)

    Schleicher, David G.; Bair, Allison N.

    2011-01-01

    We present analyses of and results for multiple components of Comet 73P/Schwassmann-Wachmann 3 at two apparitions. A total of eight nights of narrowband photometry were obtained during the comet's 2006 apparition from February 25 to September 24 at Lowell Observatory. The comet's very close passage of Earth and sporadic outbursts allowed us to successfully measure the primary body, 'C', as well as components 'B', 'G', and 'R'. We additionally include four nights of narrowband photometry from 1995, obtained at Perth Observatory between October 19 and November 21, one to two months after the initial fragmentation event and outburst. We determined production rates for OH, NH, CN, C 3 , and C 2 , along with a proxy for the dust production, A(θ)fρ, and our 2006 measurements show considerable variation in behavior among the components, and for the gas species as compared to the dust grains. The two components having the best temporal coverage, C and B, both exhibit evidence for strong seasonal effects with larger production rates prior to perihelion than after. Because C showed little or no evidence of outbursts, its derived active area (based on water production rates) appears to be dominated by ice vaporizing from the nucleus; the fractional active area of the total nucleus surface varied from 56% (2006 February) to 125% (May) and back down to 11% (September) following perihelion. Except for when Component B was in outburst, C always had higher production rates than B, implying a significantly larger effective active area on its nucleus' surface. Unlike the gas species, dust production showed large and varying trends with both aperture size and with time, implying a significant change in the properties of the dust grains during the 2006 apparition. Due to the fragmentation event in 1995, the majority of active surfaces on the various components observed in 2006 are freshly exposed from the interior of Schwassmann-Wachmann 3's nucleus, thus permitting us to directly

  13. The Impact of Multiple Concussions on Emotional Distress, Post-Concussive Symptoms, and Neurocognitive Functioning in Active Duty United States Marines Independent of Combat Exposure or Emotional Distress

    Science.gov (United States)

    Lathan, Corinna E.; Bleiberg, Joseph; Tsao, Jack W.

    2014-01-01

    Abstract Controversy exists as to whether the lingering effects of concussion on emotional, physical, and cognitive symptoms is because of the effects of brain trauma or purely to emotional factors such as post-traumatic stress disorder or depression. This study examines the independent effects of concussion on persistent symptoms. The Defense Automated Neurobehavioral Assessment, a clinical decision support tool, was used to assess neurobehavioral functioning in 646 United States Marines, all of whom were fit for duty. Marines were assessed for concussion history, post-concussive symptoms, emotional distress, neurocognitive functioning, and deployment history. Results showed that a recent concussion or ever having experienced a concussion was associated with an increase in emotional distress, but not with persistent post-concussive symptoms (PPCS) or neurocognitive functioning. Having had multiple lifetime concussions, however, was associated with greater emotional distress, PPCS, and reduced neurocognitive functioning that needs attention and rapid discrimination, but not for memory-based tasks. These results are independent of deployment history, combat exposure, and symptoms of post-traumatic stress disorder and depression. Results supported earlier findings that a previous concussion is not generally associated with post-concussive symptoms independent of covariates. In contrast with other studies that failed to find a unique contribution for concussion to PPCS, however, evidence of recent and multiple concussion was seen across a range of emotional distress, post-concussive symptoms, and neurocognitive functioning in this study population. Results are discussed in terms of implications for assessing concussion on return from combat. PMID:25003552

  14. Stratifying empiric risk of schizophrenia among first degree relatives using multiple predictors in two independent Indian samples.

    Science.gov (United States)

    Bhatia, Triptish; Gettig, Elizabeth A; Gottesman, Irving I; Berliner, Jonathan; Mishra, N N; Nimgaonkar, Vishwajit L; Deshpande, Smita N

    2016-12-01

    Schizophrenia (SZ) has an estimated heritability of 64-88%, with the higher values based on twin studies. Conventionally, family history of psychosis is the best individual-level predictor of risk, but reliable risk estimates are unavailable for Indian populations. Genetic, environmental, and epigenetic factors are equally important and should be considered when predicting risk in 'at risk' individuals. To estimate risk based on an Indian schizophrenia participant's family history combined with selected demographic factors. To incorporate variables in addition to family history, and to stratify risk, we constructed a regression equation that included demographic variables in addition to family history. The equation was tested in two independent Indian samples: (i) an initial sample of SZ participants (N=128) with one sibling or offspring; (ii) a second, independent sample consisting of multiply affected families (N=138 families, with two or more sibs/offspring affected with SZ). The overall estimated risk was 4.31±0.27 (mean±standard deviation). There were 19 (14.8%) individuals in the high risk group, 75 (58.6%) in the moderate risk and 34 (26.6%) in the above average risk (in Sample A). In the validation sample, risks were distributed as: high (45%), moderate (38%) and above average (17%). Consistent risk estimates were obtained from both samples using the regression equation. Familial risk can be combined with demographic factors to estimate risk for SZ in India. If replicated, the proposed stratification of risk may be easier and more realistic for family members. Copyright © 2016. Published by Elsevier B.V.

  15. Applying Least Absolute Shrinkage Selection Operator and Akaike Information Criterion Analysis to Find the Best Multiple Linear Regression Models between Climate Indices and Components of Cow's Milk.

    Science.gov (United States)

    Marami Milani, Mohammad Reza; Hense, Andreas; Rahmani, Elham; Ploeger, Angelika

    2016-07-23

    This study focuses on multiple linear regression models relating six climate indices (temperature humidity THI, environmental stress ESI, equivalent temperature index ETI, heat load HLI, modified HLI (HLI new ), and respiratory rate predictor RRP) with three main components of cow's milk (yield, fat, and protein) for cows in Iran. The least absolute shrinkage selection operator (LASSO) and the Akaike information criterion (AIC) techniques are applied to select the best model for milk predictands with the smallest number of climate predictors. Uncertainty estimation is employed by applying bootstrapping through resampling. Cross validation is used to avoid over-fitting. Climatic parameters are calculated from the NASA-MERRA global atmospheric reanalysis. Milk data for the months from April to September, 2002 to 2010 are used. The best linear regression models are found in spring between milk yield as the predictand and THI, ESI, ETI, HLI, and RRP as predictors with p -value < 0.001 and R ² (0.50, 0.49) respectively. In summer, milk yield with independent variables of THI, ETI, and ESI show the highest relation ( p -value < 0.001) with R ² (0.69). For fat and protein the results are only marginal. This method is suggested for the impact studies of climate variability/change on agriculture and food science fields when short-time series or data with large uncertainty are available.

  16. Lateral transfer of tetrahymanol-synthesizing genes has allowed multiple diverse eukaryote lineages to independently adapt to environments without oxygen

    Directory of Open Access Journals (Sweden)

    Takishita Kiyotaka

    2012-02-01

    Full Text Available Abstract Sterols are key components of eukaryotic cellular membranes that are synthesized by multi-enzyme pathways that require molecular oxygen. Because prokaryotes fundamentally lack sterols, it is unclear how the vast diversity of bacterivorous eukaryotes that inhabit hypoxic environments obtain, or synthesize, sterols. Here we show that tetrahymanol, a triterpenoid that does not require molecular oxygen for its biosynthesis, likely functions as a surrogate of sterol in eukaryotes inhabiting oxygen-poor environments. Genes encoding the tetrahymanol synthesizing enzyme squalene-tetrahymanol cyclase were found from several phylogenetically diverged eukaryotes that live in oxygen-poor environments and appear to have been laterally transferred among such eukaryotes. Reviewers This article was reviewed by Eric Bapteste and Eugene Koonin.

  17. Inclusive and exclusive cross sections for multiple ionization by fast, highly charged ions in the independent-electron approximation

    International Nuclear Information System (INIS)

    Ben-Itzhak, I.; Gray, T.J.; Legg, J.C.; McGuire, J.H.

    1988-01-01

    Cross sections for the ionization of n of N electrons with equal single-electron ionization probability P are considered. When both N and the projectile charge q are large, the cross sections for single and double ionization are both found to be approximately linear in q at 1 MeVamu. The ratio of double-to-single-ionization cross sections is independent of q. Moreover, first-order perturbation theory for the single-electron ionization probability P, which varies as q 2 , is found to be applicable due to the damping of contributions with large P caused by factors of (1-P)/sup N/ - /sup n/. For large P there are differences between the inclusive probability P and the probability NP commonly used for a target with N electrons. Both of these probabilities differ significantly from the exclusive probability NP(1-P)/sup N/ -1 for the ionization of only one electron. For large N and large q, the exclusive ionization probabilities for removing exactly n of the N electrons tend to be concentrated in somewhat separate ranges of impact parameters b, defining impact-parameter ''windows.'' The windows which we obtain using the quantum-mechanical semiclassical-Coulomb-approximation (SCA) probabilities are similar to those using classical Monte Carlo calculations. Model calculations, based on analytic fits to the SCA probabilities, are used to obtain approximate analytic expressions for single- and double-ionization cross sections and for the impact-parameter windows

  18. Drosophila Pumilio protein contains multiple autonomous repression domains that regulate mRNAs independently of Nanos and brain tumor.

    Science.gov (United States)

    Weidmann, Chase A; Goldstrohm, Aaron C

    2012-01-01

    Drosophila melanogaster Pumilio is an RNA-binding protein that potently represses specific mRNAs. In developing embryos, Pumilio regulates a key morphogen, Hunchback, in collaboration with the cofactor Nanos. To investigate repression by Pumilio and Nanos, we created cell-based assays and found that Pumilio inhibits translation and enhances mRNA decay independent of Nanos. Nanos robustly stimulates repression through interactions with the Pumilio RNA-binding domain. We programmed Pumilio to recognize a new binding site, which garners repression of new target mRNAs. We show that cofactors Brain Tumor and eIF4E Homologous Protein are not obligatory for Pumilio and Nanos activity. The conserved RNA-binding domain of Pumilio was thought to be sufficient for its function. Instead, we demonstrate that three unique domains in the N terminus of Pumilio possess the major repressive activity and can function autonomously. The N termini of insect and vertebrate Pumilio and Fem-3 binding factors (PUFs) are related, and we show that corresponding regions of human PUM1 and PUM2 have repressive activity. Other PUF proteins lack these repression domains. Our findings suggest that PUF proteins have evolved new regulatory functions through protein sequences appended to their conserved PUF repeat RNA-binding domains.

  19. Involvement of the anterior cingulate cortex in time-based prospective memory task monitoring: An EEG analysis of brain sources using Independent Component and Measure Projection Analysis.

    Directory of Open Access Journals (Sweden)

    Gabriela Cruz

    Full Text Available Time-based prospective memory (PM, remembering to do something at a particular moment in the future, is considered to depend upon self-initiated strategic monitoring, involving a retrieval mode (sustained maintenance of the intention plus target checking (intermittent time checks. The present experiment was designed to explore what brain regions and brain activity are associated with these components of strategic monitoring in time-based PM tasks.24 participants were asked to reset a clock every four minutes, while performing a foreground ongoing word categorisation task. EEG activity was recorded and data were decomposed into source-resolved activity using Independent Component Analysis. Common brain regions across participants, associated with retrieval mode and target checking, were found using Measure Projection Analysis.Participants decreased their performance on the ongoing task when concurrently performed with the time-based PM task, reflecting an active retrieval mode that relied on withdrawal of limited resources from the ongoing task. Brain activity, with its source in or near the anterior cingulate cortex (ACC, showed changes associated with an active retrieval mode including greater negative ERP deflections, decreased theta synchronization, and increased alpha suppression for events locked to the ongoing task while maintaining a time-based intention. Activity in the ACC was also associated with time-checks and found consistently across participants; however, we did not find an association with time perception processing per se.The involvement of the ACC in both aspects of time-based PM monitoring may be related to different functions that have been attributed to it: strategic control of attention during the retrieval mode (distributing attentional resources between the ongoing task and the time-based task and anticipatory/decision making processing associated with clock-checks.

  20. Bowen emission from Aquila X-1: evidence for multiple components and constraint on the accretion disc vertical structure

    Science.gov (United States)

    Jiménez-Ibarra, F.; Muñoz-Darias, T.; Wang, L.; Casares, J.; Mata Sánchez, D.; Steeghs, D.; Armas Padilla, M.; Charles, P. A.

    2018-03-01

    We present a detailed spectroscopic study of the optical counterpart of the neutron star X-ray transient Aquila X-1 during its 2011, 2013 and 2016 outbursts. We use 65 intermediate resolution GTC-10.4 m spectra with the aim of detecting irradiation-induced Bowen blend emission from the donor star. While Gaussian fitting does not yield conclusive results, our full phase coverage allows us to exploit Doppler mapping techniques to independently constrain the donor star radial velocity. By using the component N III 4640.64/4641.84 Å, we measure Kem = 102 ± 6 km s-1. This highly significant detection (≳13σ) is fully compatible with the true companion star radial velocity obtained from near-infrared spectroscopy during quiescence. Combining these two velocities we determine, for the first time, the accretion disc opening angle and its associated error from direct spectroscopic measurements and detailed modelling, obtaining α = 15.5 ^{+ 2.5}_{-5} deg. This value is consistent with theoretical work if significant X-ray irradiation is taken into account and is important in the light of recent observations of GX339-4, where discrepant results were obtained between the donor's intrinsic radial velocity and the Bowen-inferred value. We also discuss the limitations of the Bowen technique when complete phase coverage is not available.

  1. Energy independent scaling of the ridge and final state description of high multiplicity p +p collisions at √{s }=7 and 13 TeV

    Science.gov (United States)

    Sarkar, Debojit

    2018-02-01

    An energy independent scaling of the near-side ridge yield at a given multiplicity has been observed by the ATLAS and the CMS collaborations in p +p collisions at √{s }=7 and 13 TeV. Such a striking feature of the data can be successfully explained by approaches based on initial state momentum space correlation generated due to gluon saturation. In this paper, we try to examine if such a scaling is also an inherent feature of the approaches that employ strong final state interaction in p +p collisions. We find that hydrodynamical modeling of p +p collisions using EPOS 3 shows a violation of such scaling. The current study can, therefore, provide important new insights on the origin of long-range azimuthal correlations in high multiplicity p +p collisions at the LHC energies.

  2. Ancient and novel small RNA pathways compensate for the loss of piRNAs in multiple independent nematode lineages.

    Directory of Open Access Journals (Sweden)

    Peter Sarkies

    2015-02-01

    Full Text Available Small RNA pathways act at the front line of defence against transposable elements across the Eukaryota. In animals, Piwi interacting small RNAs (piRNAs are a crucial arm of this defence. However, the evolutionary relationships among piRNAs and other small RNA pathways targeting transposable elements are poorly resolved. To address this question we sequenced small RNAs from multiple, diverse nematode species, producing the first phylum-wide analysis of how small RNA pathways evolve. Surprisingly, despite their prominence in Caenorhabditis elegans and closely related nematodes, piRNAs are absent in all other nematode lineages. We found that there are at least two evolutionarily distinct mechanisms that compensate for the absence of piRNAs, both involving RNA-dependent RNA polymerases (RdRPs. Whilst one pathway is unique to nematodes, the second involves Dicer-dependent RNA-directed DNA methylation, hitherto unknown in animals, and bears striking similarity to transposon-control mechanisms in fungi and plants. Our results highlight the rapid, context-dependent evolution of small RNA pathways and suggest piRNAs in animals may have replaced an ancient eukaryotic RNA-dependent RNA polymerase pathway to control transposable elements.

  3. Recent independent emergence of multiple multidrug-resistant Serratia marcescens clones within the United Kingdom and Ireland.

    Science.gov (United States)

    Moradigaravand, Danesh; Boinett, Christine J; Martin, Veronique; Peacock, Sharon J; Parkhill, Julian

    2016-08-01

    Serratia marcescens, a member of the Enterobacteriaceae family, is a Gram-negative bacterium responsible for a wide range of nosocomial infections. The emergence of multidrug-resistant strains is an increasing danger to public health. To design effective means to control the dissemination of S. marcescens, an in-depth analysis of the population structure and variation is required. Utilizing whole-genome sequencing, we characterized the population structure and variation, as well as the antimicrobial resistance determinants, of a systematic collection of antimicrobial-resistant S. marcescens associated with bloodstream infections in hospitals across the United Kingdom and Ireland between 2001 and 2011. Our results show that S. marcescens is a diverse species with a high level of genomic variation. However, the collection was largely composed of a limited number of clones that emerged from this diverse background within the past few decades. We identified potential recent transmissions of these clones, within and between hospitals, and showed that they have acquired antimicrobial resistance determinants for different beta-lactams, ciprofloxacin, and tetracyclines on multiple occasions. The expansion of these multidrug-resistant clones suggests that the treatment of S. marcescens infections will become increasingly difficult in the future. © 2016 Moradigaravand et al.; Published by Cold Spring Harbor Laboratory Press.

  4. Interpretation of Ocular Melanin Drug Binding Assays. Alternatives to the Model of Multiple Classes of Independent Sites.

    Science.gov (United States)

    Manzanares, José A; Rimpelä, Anna-Kaisa; Urtti, Arto

    2016-04-04

    Melanin has a high binding affinity for a wide range of drugs. The determination of the melanin binding capacity and its binding affinity are important, e.g., in the determination of the ocular drug distribution, the prediction of drug effects in the eye, and the trans-scleral drug delivery. The binding parameters estimated from a given data set vary significantly when using different isotherms or different nonlinear fitting methods. In this work, the commonly used bi-Langmuir isotherm, which assumes two classes of independent sites, is confronted with the Sips isotherm. Direct, log-log, and Scatchard plots are used, and the interpretation of the binding curves in the latter is critically analyzed. In addition to the goodness of fit, the emphasis is placed on the physical meaning of the binding parameters. The bi-Langmuir model imposes a bimodal distribution of binding energies for the sites on the melanin granules, but the actual distribution is most likely continuous and unimodal, as assumed by the Sips isotherm. Hence, the latter describes more accurately the distribution of binding energies and also the experimental results of melanin binding to drugs and metal ions. Simulations are used to show that the existence of two classes of sites cannot be confirmed on the sole basis of the shape of the binding curve in the Scatchard plot, and that serious doubts may appear on the meaning of the binding parameters of the bi-Langmuir model. Experimental results of melanin binding to chloroquine and metoprolol are used to illustrate the importance of the choice of the binding isotherm and of the method used to evaluate the binding parameters.

  5. Multiple independent genetic factors at NOS1AP modulate the QT interval in a multi-ethnic population.

    Directory of Open Access Journals (Sweden)

    Dan E Arking

    Full Text Available Extremes of electrocardiographic QT interval are associated with increased risk for sudden cardiac death (SCD; thus, identification and characterization of genetic variants that modulate QT interval may elucidate the underlying etiology of SCD. Previous studies have revealed an association between a common genetic variant in NOS1AP and QT interval in populations of European ancestry, but this finding has not been extended to other ethnic populations. We sought to characterize the effects of NOS1AP genetic variants on QT interval in the multi-ethnic population-based Dallas Heart Study (DHS, n = 3,072. The SNP most strongly associated with QT interval in previous samples of European ancestry, rs16847548, was the most strongly associated in White (P = 0.005 and Black (P = 3.6 x 10(-5 participants, with the same direction of effect in Hispanics (P = 0.17, and further showed a significant SNP x sex-interaction (P = 0.03. A second SNP, rs16856785, uncorrelated with rs16847548, was also associated with QT interval in Blacks (P = 0.01, with qualitatively similar results in Whites and Hispanics. In a previously genotyped cohort of 14,107 White individuals drawn from the combined Atherosclerotic Risk in Communities (ARIC and Cardiovascular Health Study (CHS cohorts, we validated both the second locus at rs16856785 (P = 7.63 x 10(-8, as well as the sex-interaction with rs16847548 (P = 8.68 x 10(-6. These data extend the association of genetic variants in NOS1AP with QT interval to a Black population, with similar trends, though not statistically significant at P<0.05, in Hispanics. In addition, we identify a strong sex-interaction and the presence of a second independent site within NOS1AP associated with the QT interval. These results highlight the consistent and complex role of NOS1AP genetic variants in modulating QT interval.

  6. Age-related alterations of brain network underlying the retrieval of emotional autobiographical memories: an fMRI study using independent component analysis.

    Science.gov (United States)

    Ge, Ruiyang; Fu, Yan; Wang, Dahua; Yao, Li; Long, Zhiying

    2014-01-01

    Normal aging has been shown to modulate the neural underpinnings of autobiographical memory and emotion processing. Moreover, previous researches have suggested that aging produces a "positivity effect" in autobiographical memory. Although a few imaging studies have investigated the neural mechanism of the positivity effect, the neural substrates underlying the positivity effect in emotional autobiographical memory is unclear. To understand the age-related neural changes in emotional autobiographical memory that underlie the positivity effect, the present functional magnetic resonance imaging (fMRI) study used the independent component analysis (ICA) method to compare brain networks in younger and older adults as they retrieved positive and negative autobiographical events. Compared to their younger counterparts, older adults reported relatively higher positive feelings when retrieving emotional autobiographical events. Imaging data indicated an age-related reversal within the ventromedial prefrontal/anterior cingulate cortex (VMPFC/ACC) and the left amygdala of the brain networks that were engaged in the retrieval of autobiographical events with different valence. The retrieval of negative events compared to positive events induced stronger activity in the VMPFC/ACC and weaker activity in the amygdala for the older adults, whereas the younger adults showed a reversed pattern. Moreover, activity in the VMPFC/ACC within the task-related networks showed a negative correlation with the emotional valence intensity. These results may suggest that the positivity effect in older adults' autobiographical memories is potentially due to age-related changes in controlled emotional processing implemented by the VMPFC/ACC-amygdala circuit.

  7. Independent components analysis coupled with 3D-front-face fluorescence spectroscopy to study the interaction between plastic food packaging and olive oil.

    Science.gov (United States)

    Kassouf, Amine; El Rakwe, Maria; Chebib, Hanna; Ducruet, Violette; Rutledge, Douglas N; Maalouly, Jacqueline

    2014-08-11

    Olive oil is one of the most valued sources of fats in the Mediterranean diet. Its storage was generally done using glass or metallic packaging materials. Nowadays, plastic packaging has gained worldwide spread for the storage of olive oil. However, plastics are not inert and interaction phenomena may occur between packaging materials and olive oil. In this study, extra virgin olive oil samples were submitted to accelerated interaction conditions, in contact with polypropylene (PP) and polylactide (PLA) plastic packaging materials. 3D-front-face fluorescence spectroscopy, being a simple, fast and non destructive analytical technique, was used to study this interaction. Independent components analysis (ICA) was used to analyze raw 3D-front-face fluorescence spectra of olive oil. ICA was able to highlight a probable effect of a migration of substances with antioxidant activity. The signals extracted by ICA corresponded to natural olive oil fluorophores (tocopherols and polyphenols) as well as newly formed ones which were tentatively identified as fluorescent oxidation products. Based on the extracted fluorescent signals, olive oil in contact with plastics had slower aging rates in comparison with reference oils. Peroxide and free acidity values validated the results obtained by ICA, related to olive oil oxidation rates. Sorbed olive oil in plastic was also quantified given that this sorption could induce a swelling of the polymer thus promoting migration. Copyright © 2014 Elsevier B.V. All rights reserved.

  8. Functional connectivity analysis of the neural bases of emotion regulation: A comparison of independent component method with density-based k-means clustering method.

    Science.gov (United States)

    Zou, Ling; Guo, Qian; Xu, Yi; Yang, Biao; Jiao, Zhuqing; Xiang, Jianbo

    2016-04-29

    Functional magnetic resonance imaging (fMRI) is an important tool in neuroscience for assessing connectivity and interactions between distant areas of the brain. To find and characterize the coherent patterns of brain activity as a means of identifying brain systems for the cognitive reappraisal of the emotion task, both density-based k-means clustering and independent component analysis (ICA) methods can be applied to characterize the interactions between brain regions involved in cognitive reappraisal of emotion. Our results reveal that compared with the ICA method, the density-based k-means clustering method provides a higher sensitivity of polymerization. In addition, it is more sensitive to those relatively weak functional connection regions. Thus, the study concludes that in the process of receiving emotional stimuli, the relatively obvious activation areas are mainly distributed in the frontal lobe, cingulum and near the hypothalamus. Furthermore, density-based k-means clustering method creates a more reliable method for follow-up studies of brain functional connectivity.

  9. Investigation of True High Frequency Electrical Substrates of fMRI-Based Resting State Networks Using Parallel Independent Component Analysis of Simultaneous EEG/fMRI Data.

    Science.gov (United States)

    Kyathanahally, Sreenath P; Wang, Yun; Calhoun, Vince D; Deshpande, Gopikrishna

    2017-01-01

    Previous work using simultaneously acquired electroencephalography (EEG) and functional magnetic resonance imaging (fMRI) data has shown that the slow temporal dynamics of resting state brain networks (RSNs), e.g., default mode network (DMN), visual network (VN), obtained from fMRI are correlated with smoothed and down sampled versions of various EEG features such as microstates and band-limited power envelopes. Therefore, even though the down sampled and smoothed envelope of EEG gamma band power is correlated with fMRI fluctuations in the RSNs, it does not mean that the electrical substrates of the RSNs fluctuate with periods state fMRI fluctuations in the RSNs, researchers have speculated that truly high frequency electrical substrates may exist for the RSNs, which would make resting fluctuations obtained from fMRI more meaningful to typically occurring fast neuronal processes in the sub-100 ms time scale. In this study, we test this critical hypothesis using an integrated framework involving simultaneous EEG/fMRI acquisition, fast fMRI sampling ( TR = 200 ms) using multiband EPI (MB EPI), and EEG/fMRI fusion using parallel independent component analysis (pICA) which does not require the down sampling of EEG to fMRI temporal resolution . Our results demonstrate that with faster sampling, high frequency electrical substrates (fluctuating with periods <100 ms time scale) of the RSNs can be observed. This provides a sounder neurophysiological basis for the RSNs.

  10. Dysfunctional default mode network and executive control network in people with Internet gaming disorder: Independent component analysis under a probability discounting task.

    Science.gov (United States)

    Wang, L; Wu, L; Lin, X; Zhang, Y; Zhou, H; Du, X; Dong, G

    2016-04-01

    The present study identified the neural mechanism of risky decision-making in Internet gaming disorder (IGD) under a probability discounting task. Independent component analysis was used on the functional magnetic resonance imaging data from 19 IGD subjects (22.2 ± 3.08 years) and 21 healthy controls (HC, 22.8 ± 3.5 years). For the behavioral results, IGD subjects prefer the risky to the fixed options and showed shorter reaction time compared to HC. For the imaging results, the IGD subjects showed higher task-related activity in default mode network (DMN) and less engagement in the executive control network (ECN) than HC when making the risky decisions. Also, we found the activities of DMN correlate negatively with the reaction time and the ECN correlate positively with the probability discounting rates. The results suggest that people with IGD show altered modulation in DMN and deficit in executive control function, which might be the reason for why the IGD subjects continue to play online games despite the potential negative consequences. Copyright © 2016 Elsevier Masson SAS. All rights reserved.

  11. A proteomic analysis of LRRK2 binding partners reveals interactions with multiple signaling components of the WNT/PCP pathway.

    Science.gov (United States)

    Salašová, Alena; Yokota, Chika; Potěšil, David; Zdráhal, Zbyněk; Bryja, Vítězslav; Arenas, Ernest

    2017-07-11

    /PCP signaling pathway through its interaction to multiple WNT/PCP components. We suggest that LRRK2 regulates the balance between WNT/β-catenin and WNT/PCP signaling, depending on the binding partners. Since this balance is crucial for homeostasis of midbrain dopaminergic neurons, we hypothesize that its alteration may contribute to the pathophysiology of Parkinson's disease.

  12. The integration of multiple independent data reveals an unusual response to Pleistocene climatic changes in the hard tick Ixodes ricinus.

    Science.gov (United States)

    Porretta, Daniele; Mastrantonio, Valentina; Mona, Stefano; Epis, Sara; Montagna, Matteo; Sassera, Davide; Bandi, Claudio; Urbanelli, Sandra

    2013-03-01

    In the last few years, improved analytical tools and the integration of genetic data with multiple sources of information have shown that temperate species exhibited more complex responses to ice ages than previously thought. In this study, we investigated how Pleistocene climatic changes affected the current distribution and genetic diversity of European populations of the tick Ixodes ricinus, an ectoparasite with high ecological plasticity. We first used mitochondrial and nuclear genetic markers to investigate the phylogeographic structure of the species and its Pleistocene history using coalescent-based methods; then we used species distribution modelling to infer the climatic niche of the species at last glacial maximum; finally, we reviewed the literature on the I. ricinus hosts to identify the locations of their glacial refugia. Our results support the scenario that during the last glacial phase, I. ricinus never experienced a prolonged allopatric divergence in separate glacial refugia, but persisted with interconnected populations across Southern and Central Europe. The generalist behaviour in host choice of I. ricinus would have played a major role in maintaining connections between its populations. Although most of the hosts persisted in separate refugia, from the point of view of I. ricinus, they represented a continuity of 'bridges' among populations. Our study highlights the importance of species-specific ecology in affecting responses to Pleistocene glacial-interglacial cycles. Together with other cases in Europe and elsewhere, it contributes to setting new hypotheses on how species with wide ecological plasticity coped with Pleistocene climatic changes. © 2013 Blackwell Publishing Ltd.

  13. Crude Oil Price Forecasting Based on Hybridizing Wavelet Multiple Linear Regression Model, Particle Swarm Optimization Techniques, and Principal Component Analysis

    Science.gov (United States)

    Shabri, Ani; Samsudin, Ruhaidah

    2014-01-01

    Crude oil prices do play significant role in the global economy and are a key input into option pricing formulas, portfolio allocation, and risk measurement. In this paper, a hybrid model integrating wavelet and multiple linear regressions (MLR) is proposed for crude oil price forecasting. In this model, Mallat wavelet transform is first selected to decompose an original time series into several subseries with different scale. Then, the principal component analysis (PCA) is used in processing subseries data in MLR for crude oil price forecasting. The particle swarm optimization (PSO) is used to adopt the optimal parameters of the MLR model. To assess the effectiveness of this model, daily crude oil market, West Texas Intermediate (WTI), has been used as the case study. Time series prediction capability performance of the WMLR model is compared with the MLR, ARIMA, and GARCH models using various statistics measures. The experimental results show that the proposed model outperforms the individual models in forecasting of the crude oil prices series. PMID:24895666

  14. Crude Oil Price Forecasting Based on Hybridizing Wavelet Multiple Linear Regression Model, Particle Swarm Optimization Techniques, and Principal Component Analysis

    Directory of Open Access Journals (Sweden)

    Ani Shabri

    2014-01-01

    Full Text Available Crude oil prices do play significant role in the global economy and are a key input into option pricing formulas, portfolio allocation, and risk measurement. In this paper, a hybrid model integrating wavelet and multiple linear regressions (MLR is proposed for crude oil price forecasting. In this model, Mallat wavelet transform is first selected to decompose an original time series into several subseries with different scale. Then, the principal component analysis (PCA is used in processing subseries data in MLR for crude oil price forecasting. The particle swarm optimization (PSO is used to adopt the optimal parameters of the MLR model. To assess the effectiveness of this model, daily crude oil market, West Texas Intermediate (WTI, has been used as the case study. Time series prediction capability performance of the WMLR model is compared with the MLR, ARIMA, and GARCH models using various statistics measures. The experimental results show that the proposed model outperforms the individual models in forecasting of the crude oil prices series.

  15. Crude oil price forecasting based on hybridizing wavelet multiple linear regression model, particle swarm optimization techniques, and principal component analysis.

    Science.gov (United States)

    Shabri, Ani; Samsudin, Ruhaidah

    2014-01-01

    Crude oil prices do play significant role in the global economy and are a key input into option pricing formulas, portfolio allocation, and risk measurement. In this paper, a hybrid model integrating wavelet and multiple linear regressions (MLR) is proposed for crude oil price forecasting. In this model, Mallat wavelet transform is first selected to decompose an original time series into several subseries with different scale. Then, the principal component analysis (PCA) is used in processing subseries data in MLR for crude oil price forecasting. The particle swarm optimization (PSO) is used to adopt the optimal parameters of the MLR model. To assess the effectiveness of this model, daily crude oil market, West Texas Intermediate (WTI), has been used as the case study. Time series prediction capability performance of the WMLR model is compared with the MLR, ARIMA, and GARCH models using various statistics measures. The experimental results show that the proposed model outperforms the individual models in forecasting of the crude oil prices series.

  16. Age-related alterations of brain network underlying the retrieval of emotional autobiographical memories: An fMRI study using independent component analysis

    Directory of Open Access Journals (Sweden)

    Ruiyang eGe

    2014-08-01

    Full Text Available Normal aging has been shown to modulate the neural underpinnings of autobiographical memory and emotion processing. Moreover, previous researches have suggested that aging produces a positivity effect in autobiographical memory. Although a few imaging studies have investigated the neural mechanism of the positivity effect, the neural substrates underlying the positivity effect in emotional autobiographical memory is unclear. To understand the age-related neural changes in emotional autobiographical memory that underlie the positivity effect, the present functional magnetic resonance imaging (fMRI study used the independent component analysis (ICA method to compare brain networks in younger and older adults as they retrieved positive and negative autobiographical events. Compared to their younger counterparts, older adults reported relatively higher positive feelings when retrieving emotional autobiographical events. Imaging data indicated an age-related reversal within the ventromedial prefrontal/anterior cingulate cortex (VMPFC/ACC and the left amygdala of the brain networks that were engaged in the retrieval of autobiographical events with different valence. The retrieval of negative events compared to positive events induced stronger activity in the VMPFC/ACC and weaker activity in the amygdala for the older adults, whereas the younger adults showed a reversed pattern. Moreover, activity in the VMPFC/ACC within the task-related networks showed a negative correlation with the emotional valence intensity. These results may suggest that the positivity effect in older adults’ autobiographical memories is potentially due to age-related changes in controlled emotional processing implemented by the VMPFC/ACC-amygdala circuit.

  17. COMPLETE SEPARATION OF THE VERTICAL AND HORIZONTAL INDEPENDENT COMPONENTS OF THE FLIGHT IN POLICOPTER UAV NAU PKF "AURORA" AND MATHEMATICAL MODEL OF THIS FLIGHT

    Directory of Open Access Journals (Sweden)

    Volodymyr Kharchenko

    2017-07-01

    Full Text Available Purpose: This article presents a mathematical model and the experimental results of automatic flights of the policopter UAV NAU PKF "Aurora" of oktacopter scheme with additional elektroimpeler engines of horizontal thrust. Methods: UAV NAU PKF "Aurora" is developed for experimental flights in manual, semi-automatic and unmanned modes. The uniqueness and scientific novelty of data of flight testes is in a complete separation and isolation of vertical and horizontal components of the flight, which enables a fundamentally new way of moving of vehicle in the aerial space. This approach gives a ability to obtain all advantages and to eliminate disadvantages of helicopter and airplane in fundamentally new aircraft by structure and by function – namely in the policopter flyer with additional independent engines of the lateral thrust. Results: Obtained a new experimental data that allowed to better understand the nature of the physical forces, providing the flight of the policopter. Discussion: Revised a physical basis of the airscrew (propeller, namely on the example of flight of the policopter proved that most of the thrust of the propeller provided by the mechanical impulse (kinetic energy Ек=mv2/2 by the impulse, that a airscrew receives at his collisions with air molecules,but not by the gradient of air pressure below and above the airscrew. Is put forward a hypothesis of gravitational nature of the flight and introduced the notion of "functional antigravity", that a force completely identical in function and opposite on the direction of the force of gravity (gravity force. Deduced a mathematical formula of "functionally antigravitational" transport, namely:G·M·m/R2 = mI·v2/2 – for the flights of the aircraft with a mass m over universal astronomical body with a mass M, and m·g = mI·v2/2 – for the flights of the aircraft with mass m over a planet Earth.

  18. Performance comparison of machine learning algorithms and number of independent components used in fMRI decoding of belief vs. disbelief.

    Science.gov (United States)

    Douglas, P K; Harris, Sam; Yuille, Alan; Cohen, Mark S

    2011-05-15

    Machine learning (ML) has become a popular tool for mining functional neuroimaging data, and there are now hopes of performing such analyses efficiently in real-time. Towards this goal, we compared accuracy of six different ML algorithms applied to neuroimaging data of persons engaged in a bivariate task, asserting their belief or disbelief of a variety of propositional statements. We performed unsupervised dimension reduction and automated feature extraction using independent component (IC) analysis and extracted IC time courses. Optimization of classification hyperparameters across each classifier occurred prior to assessment. Maximum accuracy was achieved at 92% for Random Forest, followed by 91% for AdaBoost, 89% for Naïve Bayes, 87% for a J48 decision tree, 86% for K*, and 84% for support vector machine. For real-time decoding applications, finding a parsimonious subset of diagnostic ICs might be useful. We used a forward search technique to sequentially add ranked ICs to the feature subspace. For the current data set, we determined that approximately six ICs represented a meaningful basis set for classification. We then projected these six IC spatial maps forward onto a later scanning session within subject. We then applied the optimized ML algorithms to these new data instances, and found that classification accuracy results were reproducible. Additionally, we compared our classification method to our previously published general linear model results on this same data set. The highest ranked IC spatial maps show similarity to brain regions associated with contrasts for belief > disbelief, and disbelief < belief. Copyright © 2010 Elsevier Inc. All rights reserved.

  19. A comparison between the pathophysiology of multiple sclerosis and normal pressure hydrocephalus: is pulse wave encephalopathy a component of MS?

    Science.gov (United States)

    Bateman, Grant A; Lechner-Scott, Jeannette; Lea, Rodney A

    2016-09-22

    It has been suggested there is a chronic neurodegenerative disorder, underlying the pathophysiology of multiple sclerosis (MS), which is distinct from the more obvious immune-mediated attack on the white matter. Limited data exists indicating there is an alteration in pulse wave propagation within the craniospinal cavity in MS, similar to the findings in normal pressure hydrocephalus (NPH). It is hypothesized MS may harbor pulse wave encephalopathy. The purpose of this study is to compare blood flow and pulse wave measurements in MS patients with a cohort of NPH patients and control subjects, to test this hypothesis. Twenty patients with MS underwent magnetic resonance (MR) flow quantification techniques. Mean blood flow and stroke volume were measured in the arterial inflow and venous out flow from the sagittal (SSS) and straight sinus (ST). The arteriovenous delay (AVD) was defined. The results were compared with both age-matched controls and NPH patients. In MS there was a 35 % reduction in arteriovenous delay and a 5 % reduction in the percentage of the arterial inflow returning via the sagittal sinus compared to age matched controls. There was an alteration in pulse wave propagation, with a 26 % increase in arterial stroke volume but 30 % reduction in SSS and ST stroke volume. The AVD and blood flow changes were in the same direction to those of NPH patients. There are blood flow and pulsation propagation changes in MS patients which are similar to those of NPH patients. The findings would be consistent with an underlying pulse wave encephalopathy component in MS.

  20. 'Compromise position' image alignment to accommodate independent motion of multiple clinical target volumes during radiotherapy: A high risk prostate cancer example

    International Nuclear Information System (INIS)

    Rosewall, Tara; Alasti, Hamideh; Bayley, Andrew; Yan, Jing

    2017-01-01

    Inclusion of multiple independently moving clinical target volumes (CTVs) in the irradiated volume causes an image guidance conundrum. The purpose of this research was to use high risk prostate cancer as a clinical example to evaluate a 'compromise' image alignment strategy. The daily pre-treatment orthogonal EPI for 14 consecutive patients were included in this analysis. Image matching was performed by aligning to the prostate only, the bony pelvis only and using the 'compromise' strategy. Residual CTV surrogate displacements were quantified for each of the alignment strategies. Analysis of the 388 daily fractions indicated surrogate displacements were well-correlated in all directions (r 2 = 0.95 (LR), 0.67 (AP) and 0.59 (SI). Differences between the surrogates displacements (95% range) were −0.4 to 1.8 mm (LR), −1.2 to 5.2 mm (SI) and −1.2 to 5.2 mm (AP). The distribution of the residual displacements was significantly smaller using the 'compromise' strategy, compared to the other strategies (p 0.005). The 'compromise' strategy ensured the CTV was encompassed by the PTV in all fractions, compared to 47 PTV violations when aligned to prostate only. This study demonstrated the feasibility of a compromise position image guidance strategy to accommodate simultaneous displacements of two independently moving CTVs. Application of this strategy was facilitated by correlation between the CTV displacements and resulted in no geometric excursions of the CTVs beyond standard sized PTVs. This simple image guidance strategy may also be applicable to other disease sites that concurrently irradiate multiple CTVs, such as head and neck, lung and cervix cancer.

  1. Combining multiple hypothesis testing and affinity propagation clustering leads to accurate, robust and sample size independent classification on gene expression data

    Directory of Open Access Journals (Sweden)

    Sakellariou Argiris

    2012-10-01

    Full Text Available Abstract Background A feature selection method in microarray gene expression data should be independent of platform, disease and dataset size. Our hypothesis is that among the statistically significant ranked genes in a gene list, there should be clusters of genes that share similar biological functions related to the investigated disease. Thus, instead of keeping N top ranked genes, it would be more appropriate to define and keep a number of gene cluster exemplars. Results We propose a hybrid FS method (mAP-KL, which combines multiple hypothesis testing and affinity propagation (AP-clustering algorithm along with the Krzanowski & Lai cluster quality index, to select a small yet informative subset of genes. We applied mAP-KL on real microarray data, as well as on simulated data, and compared its performance against 13 other feature selection approaches. Across a variety of diseases and number of samples, mAP-KL presents competitive classification results, particularly in neuromuscular diseases, where its overall AUC score was 0.91. Furthermore, mAP-KL generates concise yet biologically relevant and informative N-gene expression signatures, which can serve as a valuable tool for diagnostic and prognostic purposes, as well as a source of potential disease biomarkers in a broad range of diseases. Conclusions mAP-KL is a data-driven and classifier-independent hybrid feature selection method, which applies to any disease classification problem based on microarray data, regardless of the available samples. Combining multiple hypothesis testing and AP leads to subsets of genes, which classify unknown samples from both, small and large patient cohorts with high accuracy.

  2. Development of a flattening filter free multiple source model for use as an independent, Monte Carlo, dose calculation, quality assurance tool for clinical trials.

    Science.gov (United States)

    Faught, Austin M; Davidson, Scott E; Popple, Richard; Kry, Stephen F; Etzel, Carol; Ibbott, Geoffrey S; Followill, David S

    2017-09-01

    The Imaging and Radiation Oncology Core-Houston (IROC-H) Quality Assurance Center (formerly the Radiological Physics Center) has reported varying levels of compliance from their anthropomorphic phantom auditing program. IROC-H studies have suggested that one source of disagreement between institution submitted calculated doses and measurement is the accuracy of the institution's treatment planning system dose calculations and heterogeneity corrections used. In order to audit this step of the radiation therapy treatment process, an independent dose calculation tool is needed. Monte Carlo multiple source models for Varian flattening filter free (FFF) 6 MV and FFF 10 MV therapeutic x-ray beams were commissioned based on central axis depth dose data from a 10 × 10 cm 2 field size and dose profiles for a 40 × 40 cm 2 field size. The models were validated against open-field measurements in a water tank for field sizes ranging from 3 × 3 cm 2 to 40 × 40 cm 2 . The models were then benchmarked against IROC-H's anthropomorphic head and neck phantom and lung phantom measurements. Validation results, assessed with a ±2%/2 mm gamma criterion, showed average agreement of 99.9% and 99.0% for central axis depth dose data for FFF 6 MV and FFF 10 MV models, respectively. Dose profile agreement using the same evaluation technique averaged 97.8% and 97.9% for the respective models. Phantom benchmarking comparisons were evaluated with a ±3%/2 mm gamma criterion, and agreement averaged 90.1% and 90.8% for the respective models. Multiple source models for Varian FFF 6 MV and FFF 10 MV beams have been developed, validated, and benchmarked for inclusion in an independent dose calculation quality assurance tool for use in clinical trial audits. © 2017 American Association of Physicists in Medicine.

  3. 'Compromise position' image alignment to accommodate independent motion of multiple clinical target volumes during radiotherapy: A high risk prostate cancer example.

    Science.gov (United States)

    Rosewall, Tara; Yan, Jing; Alasti, Hamideh; Cerase, Carla; Bayley, Andrew

    2017-04-01

    Inclusion of multiple independently moving clinical target volumes (CTVs) in the irradiated volume causes an image guidance conundrum. The purpose of this research was to use high risk prostate cancer as a clinical example to evaluate a 'compromise' image alignment strategy. The daily pre-treatment orthogonal EPI for 14 consecutive patients were included in this analysis. Image matching was performed by aligning to the prostate only, the bony pelvis only and using the 'compromise' strategy. Residual CTV surrogate displacements were quantified for each of the alignment strategies. Analysis of the 388 daily fractions indicated surrogate displacements were well-correlated in all directions (r 2  = 0.95 (LR), 0.67 (AP) and 0.59 (SI). Differences between the surrogates displacements (95% range) were -0.4 to 1.8 mm (LR), -1.2 to 5.2 mm (SI) and -1.2 to 5.2 mm (AP). The distribution of the residual displacements was significantly smaller using the 'compromise' strategy, compared to the other strategies (p 0.005). The 'compromise' strategy ensured the CTV was encompassed by the PTV in all fractions, compared to 47 PTV violations when aligned to prostate only. This study demonstrated the feasibility of a compromise position image guidance strategy to accommodate simultaneous displacements of two independently moving CTVs. Application of this strategy was facilitated by correlation between the CTV displacements and resulted in no geometric excursions of the CTVs beyond standard sized PTVs. This simple image guidance strategy may also be applicable to other disease sites that concurrently irradiate multiple CTVs, such as head and neck, lung and cervix cancer. © 2016 The Royal Australian and New Zealand College of Radiologists.

  4. Simultaneous quantification of multiple components in rat plasma by UPLC-MS/MS and pharmacokinetic study after oral administration of Huangqi decoction.

    Science.gov (United States)

    Zeng, Jia-Kai; Li, Yuan-Yuan; Wang, Tian-Ming; Zhong, Jie; Wu, Jia-Sheng; Liu, Ping; Zhang, Hua; Ma, Yue-Ming

    2018-05-01

    A rapid, sensitive and accurate UPLC-MS/MS method was developed for the simultaneous quantification of components of Huangqi decoction (HQD), such as calycosin-7-O-β-d-glucoside, calycosin-glucuronide, liquiritin, formononetin-glucuronide, isoliquiritin, liquiritigenin, ononin, calycosin, isoliquiritigenin, formononetin, glycyrrhizic acid, astragaloside IV, cycloastragenol, and glycyrrhetinic acid, in rat plasma. After plasma samples were extracted by protein precipitation, chromatographic separation was performed with a C 18 column, using a gradient of methanol and 0.05% acetic acid containing 4mm ammonium acetate as the mobile phase. Multiple reaction monitoring scanning was performed to quantify the analytes, and the electrospray ion source polarity was switched between positive and negative modes in a single run of 10 min. Method validation showed that specificity, linearity, accuracy, precision, extraction recovery, matrix effect and stability for 14 components met the requirements for their quantitation in biological samples. The established method was successfully applied to the pharmacokinetic study of multiple components in rats after intragastric administration of HQD. The results clarified the pharmacokinetic characteristics of multiple components found in HQD. This research provides useful information for understanding the relation between the chemical components of HQD and their therapeutic effects. Copyright © 2017 John Wiley & Sons, Ltd.

  5. SuperTRI: A new approach based on branch support analyses of multiple independent data sets for assessing reliability of phylogenetic inferences.

    Science.gov (United States)

    Ropiquet, Anne; Li, Blaise; Hassanin, Alexandre

    2009-09-01

    Supermatrix and supertree are two methods for constructing a phylogenetic tree by using multiple data sets. However, these methods are not a panacea, as conflicting signals between data sets can lead to misinterpret the evolutionary history of taxa. In particular, the supermatrix approach is expected to be misleading if the species-tree signal is not dominant after the combination of the data sets. Moreover, most current supertree methods suffer from two limitations: (i) they ignore or misinterpret secondary (non-dominant) phylogenetic signals of the different data sets; and (ii) the logical basis of node robustness measures is unclear. To overcome these limitations, we propose a new approach, called SuperTRI, which is based on the branch support analyses of the independent data sets, and where the reliability of the nodes is assessed using three measures: the supertree Bootstrap percentage and two other values calculated from the separate analyses: the mean branch support (mean Bootstrap percentage or mean posterior probability) and the reproducibility index. The SuperTRI approach is tested on a data matrix including seven genes for 82 taxa of the family Bovidae (Mammalia, Ruminantia), and the results are compared to those found with the supermatrix approach. The phylogenetic analyses of the supermatrix and independent data sets were done using four methods of tree reconstruction: Bayesian inference, maximum likelihood, and unweighted and weighted maximum parsimony. The results indicate, firstly, that the SuperTRI approach shows less sensitivity to the four phylogenetic methods, secondly, that it is more accurate to interpret the relationships among taxa, and thirdly, that interesting conclusions on introgression and radiation can be drawn from the comparisons between SuperTRI and supermatrix analyses.

  6. MO-C-17A-06: Online Adaptive Re-Planning to Account for Independent Motions Between Multiple Targets During Radiotherapy of Lung Cancer

    International Nuclear Information System (INIS)

    Liu, F; Tai, A; Ahunbay, E; Gore, E; Johnstone, C; Li, X

    2014-01-01

    Purpose: To quantify interfractional independent motions between multiple targets in radiotherapy (RT) of lung cancer, and to study the dosimetric benefits of an online adaptive replanning method to account for these variations. Methods: Ninety five diagnostic-quality daily CTs acquired for 9 lung cancer patients treated with IGRT using an in-room CT (CTVision, Siemens) were analyzed. On each daily CT set, contours of the targets (GTV, CTV, or involved nodes) and organs at risk were generated by populating the planning contours using an auto-segmentation tool (ABAS, Elekta) with manual editing. For each patient, an IMRT plan was generated based on the planning CT with a prescription dose of 60 Gy in 2Gy fractions. Three plans were generated and compared for each daily CT set: an IGRT (repositioning) plan by copying the original plan with the required shifts, an online adaptive plan by rapidly modifying the aperture shapes and segment weights of the original plan to conform to the daily anatomy, and a new fully re-optimized plan based on the daily CT using a planning system (Panther, Prowess). Results: The daily deviations of the distance between centers of masses of the targets from the plans varied daily from -10 to 8 mm with an average −0.9±4.1 mm (one standard deviation). The average CTV V100 are 99.0±0.7%, 97.9±2.8%, 99.0±0.6%, and 99.1±0.6%, and the lung V20 Gy 928±332 cc, 944±315 cc, 917±300 cc, and 891±295 cc for the original, repositioning, adaptive, and re-optimized plans, respectively. Wilcoxon signed-rank tests show that the adaptive plans are statistically significantly better than the repositioning plans and comparable with the reoptimized plans. Conclusion: There exist unpredictable, interfractional, relative volume changes and independent motions between multiple targets during lung cancer RT which cannot be accounted for by the current IGRT repositioning but can be corrected by the online adaptive replanning method

  7. MO-C-17A-06: Online Adaptive Re-Planning to Account for Independent Motions Between Multiple Targets During Radiotherapy of Lung Cancer

    Energy Technology Data Exchange (ETDEWEB)

    Liu, F; Tai, A; Ahunbay, E; Gore, E; Johnstone, C; Li, X [Medical College of Wisconsin, Milwaukee, WI (United States)

    2014-06-15

    Purpose: To quantify interfractional independent motions between multiple targets in radiotherapy (RT) of lung cancer, and to study the dosimetric benefits of an online adaptive replanning method to account for these variations. Methods: Ninety five diagnostic-quality daily CTs acquired for 9 lung cancer patients treated with IGRT using an in-room CT (CTVision, Siemens) were analyzed. On each daily CT set, contours of the targets (GTV, CTV, or involved nodes) and organs at risk were generated by populating the planning contours using an auto-segmentation tool (ABAS, Elekta) with manual editing. For each patient, an IMRT plan was generated based on the planning CT with a prescription dose of 60 Gy in 2Gy fractions. Three plans were generated and compared for each daily CT set: an IGRT (repositioning) plan by copying the original plan with the required shifts, an online adaptive plan by rapidly modifying the aperture shapes and segment weights of the original plan to conform to the daily anatomy, and a new fully re-optimized plan based on the daily CT using a planning system (Panther, Prowess). Results: The daily deviations of the distance between centers of masses of the targets from the plans varied daily from -10 to 8 mm with an average −0.9±4.1 mm (one standard deviation). The average CTV V100 are 99.0±0.7%, 97.9±2.8%, 99.0±0.6%, and 99.1±0.6%, and the lung V20 Gy 928±332 cc, 944±315 cc, 917±300 cc, and 891±295 cc for the original, repositioning, adaptive, and re-optimized plans, respectively. Wilcoxon signed-rank tests show that the adaptive plans are statistically significantly better than the repositioning plans and comparable with the reoptimized plans. Conclusion: There exist unpredictable, interfractional, relative volume changes and independent motions between multiple targets during lung cancer RT which cannot be accounted for by the current IGRT repositioning but can be corrected by the online adaptive replanning method.

  8. Existence of multiple receptors in single neurons: responses of single bullfrog olfactory neurons to many cAMP-dependent and independent odorants.

    Science.gov (United States)

    Kashiwayanagi, M; Shimano, K; Kurihara, K

    1996-11-04

    The responses of single bullfrog olfactory neurons to various odorants were measured with the whole-cell patch clamp which offers direct information on cellular events and with the ciliary recording technique to obtain stable quantitative data from many neurons. A large portion of single olfactory neurons (about 64% and 79% in the whole-cell recording and in the ciliary recording, respectively) responded to many odorants with quite diverse molecular structures, including both odorants previously indicated to be cAMP-dependent (increasing) and independent odorants. One odorant elicited a response in many cells; e.g. hedione and citralva elicited the response in 100% and 92% of total neurons examined with the ciliary recording technique. To confirm that a single neuron carries different receptors or transduction pathways, the cross-adaptation technique was applied to single neurons. Application of hedione to a single neuron after desensitization of the current in response to lyral or citralva induced an inward current with a similar magnitude to that applied alone. It was suggested that most single olfactory neurons carry multiple receptors and at least dual transduction pathways.

  9. Multiple independent loci at chromosome 15q25.1 affect smoking quantity: a meta-analysis and comparison with lung cancer and COPD.

    Directory of Open Access Journals (Sweden)

    Nancy L Saccone

    2010-08-01

    Full Text Available Recently, genetic association findings for nicotine dependence, smoking behavior, and smoking-related diseases converged to implicate the chromosome 15q25.1 region, which includes the CHRNA5-CHRNA3-CHRNB4 cholinergic nicotinic receptor subunit genes. In particular, association with the nonsynonymous CHRNA5 SNP rs16969968 and correlates has been replicated in several independent studies. Extensive genotyping of this region has suggested additional statistically distinct signals for nicotine dependence, tagged by rs578776 and rs588765. One goal of the Consortium for the Genetic Analysis of Smoking Phenotypes (CGASP is to elucidate the associations among these markers and dichotomous smoking quantity (heavy versus light smoking, lung cancer, and chronic obstructive pulmonary disease (COPD. We performed a meta-analysis across 34 datasets of European-ancestry subjects, including 38,617 smokers who were assessed for cigarettes-per-day, 7,700 lung cancer cases and 5,914 lung-cancer-free controls (all smokers, and 2,614 COPD cases and 3,568 COPD-free controls (all smokers. We demonstrate statistically independent associations of rs16969968 and rs588765 with smoking (mutually adjusted p-values<10(-35 and <10(-8 respectively. Because the risk alleles at these loci are negatively correlated, their association with smoking is stronger in the joint model than when each SNP is analyzed alone. Rs578776 also demonstrates association with smoking after adjustment for rs16969968 (p<10(-6. In models adjusting for cigarettes-per-day, we confirm the association between rs16969968 and lung cancer (p<10(-20 and observe a nominally significant association with COPD (p = 0.01; the other loci are not significantly associated with either lung cancer or COPD after adjusting for rs16969968. This study provides strong evidence that multiple statistically distinct loci in this region affect smoking behavior. This study is also the first report of association between rs588765

  10. The nebular spectra of the transitional Type Ia Supernovae 2007on and 2011iv: broad, multiple components indicate aspherical explosion cores

    Science.gov (United States)

    Mazzali, P. A.; Ashall, C.; Pian, E.; Stritzinger, M. D.; Gall, C.; Phillips, M. M.; Höflich, P.; Hsiao, E.

    2018-05-01

    The nebular-epoch spectrum of the rapidly declining, `transitional' Type Ia supernova (SN) 2007on showed double emission peaks, which have been interpreted as indicating that the SN was the result of the direct collision of two white dwarfs. The spectrum can be reproduced using two distinct emission components, one redshifted and one blueshifted. These components are similar in mass but have slightly different degrees of ionization. They recede from one another at a line-of-sight speed larger than the sum of the combined expansion velocities of their emitting cores, thereby acting as two independent nebulae. While this configuration appears to be consistent with the scenario of two white dwarfs colliding, it may also indicate an off-centre delayed detonation explosion of a near-Chandrasekhar-mass white dwarf. In either case, broad emission line widths and a rapidly evolving light curve can be expected for the bolometric luminosity of the SN. This is the case for both SNe 2007on and 2011iv, also a transitional SN Ia that exploded in the same elliptical galaxy, NGC 1404. Although SN 2011iv does not show double-peaked emission line profiles, the width of its emission lines is such that a two-component model yields somewhat better results than a single-component model. Most of the mass ejected is in one component, however, which suggests that SN 2011iv was the result of the off-centre ignition of a Chandrasekhar-mass white dwarf.

  11. Common and Low Frequency Variants in MERTK Are Independently Associated with Multiple Sclerosis Susceptibility with Discordant Association Dependent upon HLA-DRB1*15:01 Status.

    Directory of Open Access Journals (Sweden)

    Michele D Binder

    2016-03-01

    Full Text Available Multiple Sclerosis (MS is a chronic inflammatory demyelinating disease of the central nervous system. The risk of developing MS is strongly influenced by genetic predisposition, and over 100 loci have been established as associated with susceptibility. However, the biologically relevant variants underlying disease risk have not been defined for the vast majority of these loci, limiting the power of these genetic studies to define new avenues of research for the development of MS therapeutics. It is therefore crucial that candidate MS susceptibility loci are carefully investigated to identify the biological mechanism linking genetic polymorphism at a given gene to the increased chance of developing MS. MERTK has been established as an MS susceptibility gene and is part of a family of receptor tyrosine kinases known to be involved in the pathogenesis of demyelinating disease. In this study we have refined the association of MERTK with MS risk to independent signals from both common and low frequency variants. One of the associated variants was also found to be linked with increased expression of MERTK in monocytes and higher expression of MERTK was associated with either increased or decreased risk of developing MS, dependent upon HLA-DRB1*15:01 status. This discordant association potentially extended beyond MS susceptibility to alterations in disease course in established MS. This study provides clear evidence that distinct polymorphisms within MERTK are associated with MS susceptibility, one of which has the potential to alter MERTK transcription, which in turn can alter both susceptibility and disease course in MS patients.

  12. Distinguishing active from passive components of ankle plantar flexor stiffness in stroke, spinal cord injury and multiple sclerosis

    DEFF Research Database (Denmark)

    Lorentzen, Jakob; Grey, Michael James; Crone, Clarissa

    2010-01-01

    to distinguish the contribution of active reflex mechanisms from passive muscle properties to ankle joint stiffness in 31 healthy, 10 stroke, 30 multiple sclerosis and 16 spinal cord injured participants. The results were compared to routine clinical evaluation of spasticity. METHODS: A computer...... (Ashworth score1) showed normal reflex torque without normalization. With normalization this was only the case in 11 participants. Increased reflex mediated stiffness was detected in only 64% participants during clinical examination. CONCLUSION: The findings confirm that the clinical diagnosis of spasticity...

  13. The Multivariate Regression Statistics Strategy to Investigate Content-Effect Correlation of Multiple Components in Traditional Chinese Medicine Based on a Partial Least Squares Method.

    Science.gov (United States)

    Peng, Ying; Li, Su-Ning; Pei, Xuexue; Hao, Kun

    2018-03-01

    Amultivariate regression statisticstrategy was developed to clarify multi-components content-effect correlation ofpanaxginseng saponins extract and predict the pharmacological effect by components content. In example 1, firstly, we compared pharmacological effects between panax ginseng saponins extract and individual saponin combinations. Secondly, we examined the anti-platelet aggregation effect in seven different saponin combinations of ginsenoside Rb1, Rg1, Rh, Rd, Ra3 and notoginsenoside R1. Finally, the correlation between anti-platelet aggregation and the content of multiple components was analyzed by a partial least squares algorithm. In example 2, firstly, 18 common peaks were identified in ten different batches of panax ginseng saponins extracts from different origins. Then, we investigated the anti-myocardial ischemia reperfusion injury effects of the ten different panax ginseng saponins extracts. Finally, the correlation between the fingerprints and the cardioprotective effects was analyzed by a partial least squares algorithm. Both in example 1 and 2, the relationship between the components content and pharmacological effect was modeled well by the partial least squares regression equations. Importantly, the predicted effect curve was close to the observed data of dot marked on the partial least squares regression model. This study has given evidences that themulti-component content is a promising information for predicting the pharmacological effects of traditional Chinese medicine.

  14. The Multivariate Regression Statistics Strategy to Investigate Content-Effect Correlation of Multiple Components in Traditional Chinese Medicine Based on a Partial Least Squares Method

    Directory of Open Access Journals (Sweden)

    Ying Peng

    2018-03-01

    Full Text Available Amultivariate regression statisticstrategy was developed to clarify multi-components content-effect correlation ofpanaxginseng saponins extract and predict the pharmacological effect by components content. In example 1, firstly, we compared pharmacological effects between panax ginseng saponins extract and individual saponin combinations. Secondly, we examined the anti-platelet aggregation effect in seven different saponin combinations of ginsenoside Rb1, Rg1, Rh, Rd, Ra3 and notoginsenoside R1. Finally, the correlation between anti-platelet aggregation and the content of multiple components was analyzed by a partial least squares algorithm. In example 2, firstly, 18 common peaks were identified in ten different batches of panax ginseng saponins extracts from different origins. Then, we investigated the anti-myocardial ischemia reperfusion injury effects of the ten different panax ginseng saponins extracts. Finally, the correlation between the fingerprints and the cardioprotective effects was analyzed by a partial least squares algorithm. Both in example 1 and 2, the relationship between the components content and pharmacological effect was modeled well by the partial least squares regression equations. Importantly, the predicted effect curve was close to the observed data of dot marked on the partial least squares regression model. This study has given evidences that themulti-component content is a promising information for predicting the pharmacological effects of traditional Chinese medicine.

  15. Study of laser-induced damage on the exit surface of silica components in the nanosecond regime in a multiple wavelengths configuration

    International Nuclear Information System (INIS)

    Chambonneau, Maxime

    2014-01-01

    In this thesis, laser-induced damage phenomenon on the surface of fused silica components is investigated in the nanosecond regime. This phenomenon consists in an irreversible modification of the material. In the nanosecond regime, laser damage is tightly correlated to the presence of non-detectable precursor defects which are a consequence of the synthesis and the polishing of the components. In this thesis, we investigate laser damage in a multiple wavelengths configuration. In order to better understand this phenomenon in these conditions of irradiation, three studies are conducted. The first one focuses on damage initiation. The results obtained in the single wavelength configurations highlight a coupling in the multiple wavelengths one. A comparison between the experiments and a model developed during this thesis enables us to improve the knowledge of the fundamental processes involved during this damage phase. Then, we show that post mortem characterizations of damage morphology coupled to an accurate metrology allow us to understand both the nature and also the chronology of the physical mechanisms involved during damage formation. The proposed theoretical scenario is confirmed through various experiments. Finally, we study damage growth in both the single and the multiple wavelengths cases. Once again, this last configuration highlights a coupling between the wavelengths. We show the necessity to account for the spatial characteristics of the laser beams during a growth session. (author) [fr

  16. Modified fixation with pinning and external fixation components for feline femur multiple-lined fracture: A case report

    International Nuclear Information System (INIS)

    Okamoto, Y.; Minami, S.; Matuhashi, A.

    1992-01-01

    A 3-year-old female Japanese domestic cat, weighing 3kg, was referred to us because of right hind leg lameness occuring for 3 days' duration. Radiography of the affected leg revealed severe femoral diaphysial comminuted fracture. The affected leg was treated using wire with an intramedullary Stainman pin being placed completely through the femur. After suturing the wound, both ends of the intramedullary pin exposed both proximally and distally were fixed with external fixation components (two double clamps, two single clamps, two short rods and one long rod) to prevent the pin from rotation. There was a slight gait problem due to the external apparatus and no post-operative infection. The function of the right hind leg gradually recovered. The intramedullary pin and external fixative apparatus were removed on the 52nd day after surgery. This modified fixation appears to offer versatility in the treatment of various fractures in smaller dogs and cats

  17. A principal-component and least-squares method for allocating polycyclic aromatic hydrocarbons in sediment to multiple sources

    International Nuclear Information System (INIS)

    Burns, W.A.; Mankiewicz, P.J.; Bence, A.E.; Page, D.S.; Parker, K.R.

    1997-01-01

    A method was developed to allocate polycyclic aromatic hydrocarbons (PAHs) in sediment samples to the PAH sources from which they came. The method uses principal-component analysis to identify possible sources and a least-squares model to find the source mix that gives the best fit of 36 PAH analytes in each sample. The method identified 18 possible PAH sources in a large set of field data collected in Prince William Sound, Alaska, USA, after the 1989 Exxon Valdez oil spill, including diesel oil, diesel soot, spilled crude oil in various weathering states, natural background, creosote, and combustion products from human activities and forest fires. Spill oil was generally found to be a small increment of the natural background in subtidal sediments, whereas combustion products were often the predominant sources for subtidal PAHs near sites of past or present human activity. The method appears to be applicable to other situations, including other spills

  18. Empirical validation of the triple-code model of numerical processing for complex math operations using functional MRI and group Independent Component Analysis of the mental addition and subtraction of fractions.

    Science.gov (United States)

    Schmithorst, Vincent J; Brown, Rhonda Douglas

    2004-07-01

    The suitability of a previously hypothesized triple-code model of numerical processing, involving analog magnitude, auditory verbal, and visual Arabic codes of representation, was investigated for the complex mathematical task of the mental addition and subtraction of fractions. Functional magnetic resonance imaging (fMRI) data from 15 normal adult subjects were processed using exploratory group Independent Component Analysis (ICA). Separate task-related components were found with activation in bilateral inferior parietal, left perisylvian, and ventral occipitotemporal areas. These results support the hypothesized triple-code model corresponding to the activated regions found in the individual components and indicate that the triple-code model may be a suitable framework for analyzing the neuropsychological bases of the performance of complex mathematical tasks. Copyright 2004 Elsevier Inc.

  19. Innovative high-performance liquid chromatography method development for the screening of 19 antimalarial drugs based on a generic approach, using design of experiments, independent component analysis and design space.

    Science.gov (United States)

    Debrus, B; Lebrun, P; Kindenge, J Mbinze; Lecomte, F; Ceccato, A; Caliaro, G; Mbay, J Mavar Tayey; Boulanger, B; Marini, R D; Rozet, E; Hubert, Ph

    2011-08-05

    An innovative methodology based on design of experiments (DoE), independent component analysis (ICA) and design space (DS) was developed in previous works and was tested out with a mixture of 19 antimalarial drugs. This global LC method development methodology (i.e. DoE-ICA-DS) was used to optimize the separation of 19 antimalarial drugs to obtain a screening method. DoE-ICA-DS methodology is fully compliant with the current trend of quality by design. DoE was used to define the set of experiments to model the retention times at the beginning, the apex and the end of each peak. Furthermore, ICA was used to numerically separate coeluting peaks and estimate their unbiased retention times. Gradient time, temperature and pH were selected as the factors of a full factorial design. These retention times were modelled by stepwise multiple linear regressions. A recently introduced critical quality attribute, namely the separation criterion (S), was also used to assess the quality of separations rather than using the resolution. Furthermore, the resulting mathematical models were also studied from a chromatographic point of view to understand and investigate the chromatographic behaviour of each compound. Good adequacies were found between the mathematical models and the expected chromatographic behaviours predicted by chromatographic theory. Finally, focusing at quality risk management, the DS was computed as the multidimensional subspace where the probability for the separation criterion to lie in acceptance limits was higher than a defined quality level. The DS was computed propagating the prediction error from the modelled responses to the quality criterion using Monte Carlo simulations. DoE-ICA-DS allowed encountering optimal operating conditions to obtain a robust screening method for the 19 considered antimalarial drugs in the framework of the fight against counterfeit medicines. Moreover and only on the basis of the same data set, a dedicated method for the

  20. The prediction of parental self-efficacy and hyper-anxiety symptoms based on the components of mindfulness in women with multiple sclerosis

    Directory of Open Access Journals (Sweden)

    Mohammad Mohammadi Pour

    2017-08-01

    Full Text Available Introduction: The present study aimed to predict parental self-efficacy and hyper-anxiety symptoms based on the components of mindfulness in women with multiple sclerosis (MS. Materials and Methods: The statistical population of this descriptive-correlational study included all women with MS in Mashhad during March-Jun 2016 who referred for treatment to clinics, neurologists and psychological centers. The statistical sample consisted of 105 women with MS who were selected using convenient sampling method. In order to collect data, Parental Self-Efficacy Questionnaire, Beck Anxiety Inventory (BIA and Mindfulness Questionnaire were used. Data were analyzed using multivariate regression method. Results: The results revealed that the components of mindfulness, judgment and non-reactivity can reduce anxiety significantly in women with MS. In addition, action with awareness, judgment and non-reactivity can increase parental self-efficacy (P

  1. Quantification of Multiple Components of Complex Aluminum-Based Adjuvant Mixtures by Using Fourier Transform Infrared Spectroscopy and Partial Least Squares Modeling.

    Science.gov (United States)

    Dowling, Quinton M; Kramer, Ryan M

    2017-01-01

    Fourier transform infrared (FTIR) spectroscopy is widely used in the pharmaceutical industry for process monitoring, compositional quantification, and characterization of critical quality attributes in complex mixtures. Advantages over other spectroscopic measurements include ease of sample preparation, quantification of multiple components from a single measurement, and the ability to quantify optically opaque samples. This method describes the use of a multivariate model for quantifying a TLR4 agonist (GLA) adsorbed onto aluminum oxyhydroxide (Alhydrogel ® ) using FTIR spectroscopy that may be adapted to quantify other complex aluminum based adjuvant mixtures.

  2. Loss of heterozygosity on chromosome 11q13 in two families with acromegaly/gigantism is independent of mutations of the multiple endocrine neoplasia type I gene.

    Science.gov (United States)

    Gadelha, M R; Prezant, T R; Une, K N; Glick, R P; Moskal, S F; Vaisman, M; Melmed, S; Kineman, R D; Frohman, L A

    1999-01-01

    Familial acromegaly/gigantism occurring in the absence of multiple endocrine neoplasia type I (MEN-1) or the Carney complex has been reported in 18 families since the biochemical diagnosis of GH excess became available, and the genetic defect is unknown. In the present study we examined 2 unrelated families with isolated acromegaly/gigantism. In family A, 3 of 4 siblings were affected, with ages at diagnosis of 19, 21, and 23 yr. In family B, 5 of 13 siblings exhibited the phenotype and were diagnosed at 13, 15, 17, 17, and 24 yr of age. All 8 affected patients had elevated basal GH levels associated with high insulin-like growth factor I levels and/or nonsuppressible serum GH levels during an oral glucose tolerance test. GHRH levels were normal in affected members of family A. An invasive macroadenoma was found in 6 subjects, and a microadenoma was found in 1 subject from family B. The sequence of the GHRH receptor complementary DNA in 1 tumor from family A was normal. There was no history of consanguinity in either family, and the past medical history and laboratory results excluded MEN-1 and the Carney complex in all affected and unaffected screened subjects. Five of 8 subjects have undergone pituitary surgery to date, and paraffin-embedded pituitary blocks were available for analysis. Loss of heterozygosity on chromosome 11q13 was studied by comparing microsatellite polymorphisms of leukocyte and tumor DNA using PYGM (centromeric) and D11S527 (telomeric), markers closely linked to the MEN-1 tumor suppressor gene. All tumors exhibited a loss of heterozygosity at both markers. Sequencing of the MEN-1 gene revealed no germline mutations in either family, nor was a somatic mutation found in tumor DNA from one subject in family A. The integrity of the MEN-1 gene in this subject was further supported by demonstration of the presence of MEN-1 messenger ribonucleic acid, as assessed by RT-PCR. These data indicate that loss of heterozygosity in these affected family

  3. Factorial structure of the 'ToM Storybooks': A test evaluating multiple components of Theory of Mind.

    Science.gov (United States)

    Bulgarelli, Daniela; Testa, Silvia; Molina, Paola

    2015-06-01

    This study examined the factorial structure of the Theory of Mind (ToM) Storybooks, a comprehensive 93-item instrument tapping the five components in Wellman's model of ToM (emotion recognition, understanding of desire and beliefs, ability to distinguish between physical and mental entities, and awareness of the link between perception and knowledge). A sample of 681 three- to eight-year-old Italian children was divided into three age groups to assess whether factorial structure varied across different age ranges. Partial credit model analysis was applied to the data, leading to the empirical identification of 23 composite variables aggregating the ToM Storybooks items. Confirmatory factor analysis was then conducted on the composite variables, providing support for the theoretical model. There were partial differences in the specific composite variables making up the dimensions for each of the three age groups. A single test evaluating distinct dimensions of ToM is a valuable resource for clinical practice which may be used to define differential profiles for specific populations. © 2014 The British Psychological Society.

  4. Purified Cannabidiol, the main non-psychotropic component of Cannabis sativa, alone, counteracts neuronal apoptosis in experimental multiple sclerosis.

    Science.gov (United States)

    Giacoppo, S; Soundara Rajan, T; Galuppo, M; Pollastro, F; Grassi, G; Bramanti, P; Mazzon, E

    2015-12-01

    Multiple Sclerosis (MS) is a global concern disease leading to a progressive, chronic and demyelinating condition, affecting the central nervous system (CNS). The pathology has an inflammatory/autoimmune origin; nevertheless, neuronal cell death mechanisms are not to be underestimated. The present study was designed to test the effects of intraperitoneal administration of cannabidiol (CBD), the main non-psychotropic cannabinoid of Cannabis sativa (CS), in an experimental model of MS. The aim is to evaluate the capability of CBD administration to thwart the cascade of mediators involved in MS-induced apoptosis. Experimental Autoimmune Encephalomyelitis (EAE) was induced by immunization with myelin oligodendroglial glycoprotein (MOG)35-55 peptide in mice. After immunization, mice were observed daily for signs of EAE and weight loss. Disease signs were evaluated using a standardized scoring system. Immunohistochemical and Western blot assessments of key apoptotic markers reveal that CBD treatment is able to avoid Fas pathway activation, phospho-ERK p42/44 and cleaved caspase-3 triggering as well as alterations in mitochondrial permeability due to Bax/Bcl-2 unbalance. Moreover, CBD interferes with p53-p21 axis activation. As results, the absence of tissue apobody formation in spinal cord tissues of EAE-mice treated with CBD was established. Most of therapeutic properties of CS are currently ascribed to the psychotropic effects of phenylterpenoid delta-9 tetrahydrocannabinol. We have demonstrated that, alone, purified CBD possesses an anti-apoptotic power against the neurodegenerative processes underlying MS development. This represents an interesting new profile of CBD that could lead to its introduction in the clinical management of MS.

  5. Human alpha2-macroglobulin is composed of multiple domains, as predicted by homology with complement component C3.

    Science.gov (United States)

    Doan, Ninh; Gettins, Peter G W

    2007-10-01

    Human alpha2M (alpha2-macroglobulin) and the complement components C3 and C4 are thiol ester-containing proteins that evolved from the same ancestral gene. The recent structure determination of human C3 has allowed a detailed prediction of the location of domains within human alpha2M to be made. We describe here the expression and characterization of three alpha(2)M domains predicted to be involved in the stabilization of the thiol ester in native alpha2M and in its activation upon bait region proteolysis. The three newly expressed domains are MG2 (macroglobulin domain 2), TED (thiol ester-containing domain) and CUB (complement protein subcomponents C1r/C1s, urchin embryonic growth factor and bone morphogenetic protein 1) domain. Together with the previously characterized RBD (receptor-binding domain), they represent approx. 42% of the alpha2M polypeptide. Their expression as folded domains strongly supports the predicted domain organization of alpha2M. An X-ray crystal structure of MG2 shows it to have a fibronectin type-3 fold analogous to MG1-MG8 of C3. TED is, as predicted, an alpha-helical domain. CUB is a spliced domain composed of two stretches of polypeptide that flank TED in the primary structure. In intact C3 TED interacts with RBD, where it is in direct contact with the thiol ester, and with MG2 and CUB on opposite, flanking sides. In contrast, these alpha2M domains, as isolated species, show negligible interaction with one another, suggesting that the native conformation of alpha2M, and the consequent thiol ester-stabilizing domain-domain interactions, result from additional restraints imposed by the physical linkage of these domains or by additional domains in the protein.

  6. Human α2-macroglobulin is composed of multiple domains, as predicted by homology with complement component C3

    Science.gov (United States)

    Doan, Ninh; Gettins, Peter G. W.

    2007-01-01

    Human α2M (α2-macroglobulin) and the complement components C3 and C4 are thiol ester-containing proteins that evolved from the same ancestral gene. The recent structure determination of human C3 has allowed a detailed prediction of the location of domains within human α2M to be made. We describe here the expression and characterization of three α2M domains predicted to be involved in the stabilization of the thiol ester in native α2M and in its activation upon bait region proteolysis. The three newly expressed domains are MG2 (macroglobulin domain 2), TED (thiol ester-containing domain) and CUB (complement protein subcomponents C1r/C1s, urchin embryonic growth factor and bone morphogenetic protein 1) domain. Together with the previously characterized RBD (receptor-binding domain), they represent approx. 42% of the α2M polypeptide. Their expression as folded domains strongly supports the predicted domain organization of α2M. An X-ray crystal structure of MG2 shows it to have a fibronectin type-3 fold analogous to MG1–MG8 of C3. TED is, as predicted, an α-helical domain. CUB is a spliced domain composed of two stretches of polypeptide that flank TED in the primary structure. In intact C3 TED interacts with RBD, where it is in direct contact with the thiol ester, and with MG2 and CUB on opposite, flanking sides. In contrast, these α2M domains, as isolated species, show negligible interaction with one another, suggesting that the native conformation of α2M, and the consequent thiol ester-stabilizing domain–domain interactions, result from additional restraints imposed by the physical linkage of these domains or by additional domains in the protein. PMID:17608619

  7. Characterization of the multiple components of Acanthopanax Senticosus stem by ultra high performance liquid chromatography with quadrupole time-of-flight tandem mass spectrometry.

    Science.gov (United States)

    Sun, Hui; Liu, Jianhua; Zhang, Aihua; Zhang, Ying; Meng, Xiangcai; Han, Ying; Zhang, Yingzhi; Wang, Xijun

    2016-02-01

    Acanthopanax Senticosus Harms. has been used widely in traditional Chinese medicine for the treatment of chronic bronchitis, neurasthenia, hypertension and ischemic heart disease. However, the in vivo constituents of the stem of Acanthopanax Senticosus remain unknown. In this paper, ultra high performance liquid chromatography with electrospray ionization quadrupole time-of-flight mass spectrometry and the MarkerLynx(TM) software combined with multiple data processing approach were used to study the constituents in vitro and in vivo. The aqueous extract from the Acanthopanax Senticosus stem and the compositions in rat serum after intragastric administration were completely analyzed. Consequently, 115 compounds in the aqueous extract from Acanthopanax Senticosus stem and 41 compounds absorbed into blood were characterized. Of the 115 compounds in vitro, 54 were reported for first time, including sinapyl alcohol, sinapyl alcohol diglucoside, and 1-O-sinapoyl-β-D-glucose. In the 41 compounds in vivo, 7 were prototype components and 34 were metabolites which were from 21 components of aqueous extract from Acanthopanax Senticosus stem, and the metabolic pathways of the metabolites were elucidated for first time. The results narrowed the range of screening the active components and provided a basis for the study of action mechanism and pharmacology. © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

  8. Improving anxiety regulation in patients with breast cancer at the beginning of the survivorship period: a randomized clinical trial comparing the benefits of single-component and multiple-component group interventions.

    Science.gov (United States)

    Merckaert, Isabelle; Lewis, Florence; Delevallez, France; Herman, Sophie; Caillier, Marie; Delvaux, Nicole; Libert, Yves; Liénard, Aurore; Nogaret, Jean-Marie; Ogez, David; Scalliet, Pierre; Slachmuylder, Jean-Louis; Van Houtte, Paul; Razavi, Darius

    2017-08-01

    To compare in a multicenter randomized controlled trial the benefits in terms of anxiety regulation of a 15-session single-component group intervention (SGI) based on support with those of a 15-session multiple-component structured manualized group intervention (MGI) combining support with cognitive-behavioral and hypnosis components. Patients with nonmetastatic breast cancer were randomly assigned at the beginning of the survivorship period to the SGI (n = 83) or MGI (n = 87). Anxiety regulation was assessed, before and after group interventions, through an anxiety regulation task designed to assess their ability to regulate anxiety psychologically (anxiety levels) and physiologically (heart rates). Questionnaires were used to assess psychological distress, everyday anxiety regulation, and fear of recurrence. Group allocation was computer generated and concealed till baseline completion. Compared with patients in the SGI group (n = 77), patients attending the MGI group (n = 82) showed significantly reduced anxiety after a self-relaxation exercise (P = .006) and after exposure to anxiety triggers (P = .013) and reduced heart rates at different time points throughout the task (P = .001 to P = .047). The MGI participants also reported better everyday anxiety regulation (P = .005), greater use of fear of recurrence-related coping strategies (P = .022), and greater reduction in fear of recurrence-related psychological distress (P = .017) compared with the SGI group. This study shows that an MGI combining support with cognitive-behavioral techniques and hypnosis is more effective than an SGI based only on support in improving anxiety regulation in patients with breast cancer. Copyright © 2016 John Wiley & Sons, Ltd.

  9. Are Independent Probes Truly Independent?

    Science.gov (United States)

    Camp, Gino; Pecher, Diane; Schmidt, Henk G.; Zeelenberg, Rene

    2009-01-01

    The independent cue technique has been developed to test traditional interference theories against inhibition theories of forgetting. In the present study, the authors tested the critical criterion for the independence of independent cues: Studied cues not presented during test (and unrelated to test cues) should not contribute to the retrieval…

  10. Reliability of Multiple Component Systems

    Science.gov (United States)

    1975-07-15

    George Washington University Bethesda, Maryland .20014 Dr. Larry Cornwell Western Illinois University Macomb, Illinois 61455 Dr. Lester A...Jersey 07801 Robert M. Eissner USA Materiel Sys Anal Agency Aberdeen Proving Ground, Md. 21005 Bernard Engebos USA Electronics Command White...Philadelphia, Pennsylvania 19137 587 J Attendee»-- 19lh Design of Experiments Conference (continued) Captain Bernard J. Lawless Hqs

  11. Opening A New Independent Pharmacy 101

    Directory of Open Access Journals (Sweden)

    Azam Elabed

    2016-02-01

    Full Text Available Opening an independent pharmacy is a process that involves multiple components. The rationale of this project is to discuss different issues that must be investigated prior to opening a new independency pharmacy. This includes the location, structure of the corporation, start-up cost, picking a wholesaler, fulfilling state board requirements and Philadelphia requirements, having a valid license, making professional relationships, and knowing basic marketing research. Methods used include using the knowledge and expertise from an independent pharmacy owner, visiting pharmacies, and interviewing neighbors for basic marketing research. Many aspects of opening an independent pharmacy differ significantly from a retail pharmacy, as there are various issues within the pharmacy and outside the pharmacy that must be extensively researched prior to opening in order to be successful.   Type: Student Project

  12. Enriching an intraspecific genetic map and identifying QTL for fiber quality and yield component traits across multiple environments in Upland cotton (Gossypium hirsutum L.).

    Science.gov (United States)

    Liu, Xueying; Teng, Zhonghua; Wang, Jinxia; Wu, Tiantian; Zhang, Zhiqin; Deng, Xianping; Fang, Xiaomei; Tan, Zhaoyun; Ali, Iftikhar; Liu, Dexin; Zhang, Jian; Liu, Dajun; Liu, Fang; Zhang, Zhengsheng

    2017-12-01

    Cotton is a significant commercial crop that plays an indispensable role in many domains. Constructing high-density genetic maps and identifying stable quantitative trait locus (QTL) controlling agronomic traits are necessary prerequisites for marker-assisted selection (MAS). A total of 14,899 SSR primer pairs designed from the genome sequence of G. raimondii were screened for polymorphic markers between mapping parents CCRI 35 and Yumian 1, and 712 SSR markers showing polymorphism were used to genotype 180 lines from a (CCRI 35 × Yumian 1) recombinant inbred line (RIL) population. Genetic linkage analysis was conducted on 726 loci obtained from the 712 polymorphic SSR markers, along with 1379 SSR loci obtained in our previous study, and a high-density genetic map with 2051 loci was constructed, which spanned 3508.29 cM with an average distance of 1.71 cM between adjacent markers. Marker orders on the linkage map are highly consistent with the corresponding physical orders on a G. hirsutum genome sequence. Based on fiber quality and yield component trait data collected from six environments, 113 QTLs were identified through two analytical methods. Among these 113 QTLs, 50 were considered stable (detected in multiple environments or for which phenotypic variance explained by additive effect was greater than environment effect), and 18 of these 50 were identified with stability by both methods. These 18 QTLs, including eleven for fiber quality and seven for yield component traits, could be priorities for MAS.

  13. Analysis of the genetic phylogeny of multifocal prostate cancer identifies multiple independent clonal expansions in neoplastic and morphologically normal prostate tissue.

    Science.gov (United States)

    Cooper, Colin S; Eeles, Rosalind; Wedge, David C; Van Loo, Peter; Gundem, Gunes; Alexandrov, Ludmil B; Kremeyer, Barbara; Butler, Adam; Lynch, Andrew G; Camacho, Niedzica; Massie, Charlie E; Kay, Jonathan; Luxton, Hayley J; Edwards, Sandra; Kote-Jarai, ZSofia; Dennis, Nening; Merson, Sue; Leongamornlert, Daniel; Zamora, Jorge; Corbishley, Cathy; Thomas, Sarah; Nik-Zainal, Serena; O'Meara, Sarah; Matthews, Lucy; Clark, Jeremy; Hurst, Rachel; Mithen, Richard; Bristow, Robert G; Boutros, Paul C; Fraser, Michael; Cooke, Susanna; Raine, Keiran; Jones, David; Menzies, Andrew; Stebbings, Lucy; Hinton, Jon; Teague, Jon; McLaren, Stuart; Mudie, Laura; Hardy, Claire; Anderson, Elizabeth; Joseph, Olivia; Goody, Victoria; Robinson, Ben; Maddison, Mark; Gamble, Stephen; Greenman, Christopher; Berney, Dan; Hazell, Steven; Livni, Naomi; Fisher, Cyril; Ogden, Christopher; Kumar, Pardeep; Thompson, Alan; Woodhouse, Christopher; Nicol, David; Mayer, Erik; Dudderidge, Tim; Shah, Nimish C; Gnanapragasam, Vincent; Voet, Thierry; Campbell, Peter; Futreal, Andrew; Easton, Douglas; Warren, Anne Y; Foster, Christopher S; Stratton, Michael R; Whitaker, Hayley C; McDermott, Ultan; Brewer, Daniel S; Neal, David E

    2015-04-01

    Genome-wide DNA sequencing was used to decrypt the phylogeny of multiple samples from distinct areas of cancer and morphologically normal tissue taken from the prostates of three men. Mutations were present at high levels in morphologically normal tissue distant from the cancer, reflecting clonal expansions, and the underlying mutational processes at work in morphologically normal tissue were also at work in cancer. Our observations demonstrate the existence of ongoing abnormal mutational processes, consistent with field effects, underlying carcinogenesis. This mechanism gives rise to extensive branching evolution and cancer clone mixing, as exemplified by the coexistence of multiple cancer lineages harboring distinct ERG fusions within a single cancer nodule. Subsets of mutations were shared either by morphologically normal and malignant tissues or between different ERG lineages, indicating earlier or separate clonal cell expansions. Our observations inform on the origin of multifocal disease and have implications for prostate cancer therapy in individual cases.

  14. An imprinted non-coding genomic cluster at 14q32 defines clinically relevant molecular subtypes in osteosarcoma across multiple independent datasets

    OpenAIRE

    Hill, Katherine E.; Kelly, Andrew D.; Kuijjer, Marieke L.; Barry, William; Rattani, Ahmed; Garbutt, Cassandra C.; Kissick, Haydn; Janeway, Katherine; Perez-Atayde, Antonio; Goldsmith, Jeffrey; Gebhardt, Mark C.; Arredouani, Mohamed S.; Cote, Greg; Hornicek, Francis; Choy, Edwin

    2017-01-01

    Background: A microRNA (miRNA) collection on the imprinted 14q32 MEG3 region has been associated with outcome in osteosarcoma. We assessed the clinical utility of this miRNA set and their association with methylation status. Methods: We integrated coding and non-coding RNA data from three independent annotated clinical osteosarcoma cohorts (n = 65, n = 27, and n = 25) and miRNA and methylation data from one in vitro (19 cell lines) and one clinical (NCI Therapeutically Applicable Research to ...

  15. Load-Independent Harmonic Mitigation in SCR-Fed Three-Phase Multiple Adjustable Speed Drive Systems with Deliberately Dispatched Firing Angles

    DEFF Research Database (Denmark)

    Yang, Yongheng; Davari, Pooya; Blaabjerg, Frede

    2018-01-01

    Adjustable speed drives (ASD) are widely used in industry for energy savings, where low-cost diode rectifiers are still employed as the front-ends, also for simplicity in control and reliability in operation. However, significant harmonics appear at the grid, which should be tackled according...... a harmonic mitigation strategy for multiple ASD systems, where silicon-controlled rectifiers (SCR) with boost converters in the dc-link have been adopted to increase the harmonic-current controllability. More specific, the SCR firing angles are deliberately dispatched among the drive units, which results...

  16. Clinical application of RapidArc volumetric modulated arc therapy as a component in whole brain radiation therapy for poor prognostic, four or more multiple brain metastases

    Energy Technology Data Exchange (ETDEWEB)

    Lee, Seung Heon; Lee, Kyu Chan; Choi, Jin Ho; Kim, Hye Young; Lee, Seok Ho; Sung, Ki Hoon; Kim, Yun Mi [Gachon University Gil Hospital, Incheon (Korea, Republic of)

    2012-06-15

    To determine feasibility of RapidArc in sequential or simultaneous integrated tumor boost in whole brain radiation therapy (WBRT) for poor prognostic patients with four or more brain metastases. Nine patients with multiple ({>=}4) brain metastases were analyzed. Three patients were classified as class II in recursive partitioning analysis and 6 were class III. The class III patients presented with hemiparesis, cognitive deficit, or apraxia. The ratio of tumor to whole brain volume was 0.8-7.9%. Six patients received 2-dimensional bilateral WBRT, (30 Gy/10- 12 fractions), followed by sequential RapidArc tumor boost (15-30 Gy/4-10 fractions). Three patients received RapidArc WBRT with simultaneous integrated boost to tumors (48-50 Gy) in 10-20 fractions. The median biologically effective dose to metastatic tumors was 68.1 Gy10 and 67.2 Gy10 and the median brain volume irradiated more than 100 Gy3 were 1.9% (24 cm3) and 0.8% (13 cm3) for each group. With less than 3 minutes of treatment time, RapidArc was easily applied to the patients with poor performance status. The follow-up period was 0.3-16.5 months. Tumor responses among the 6 patients who underwent follow-up magnetic resonance imaging were partial and stable in 3 and 3, respectively. Overall survival at 6 and 12 months were 66.7% and 41.7%, respectively. The local progression-free survival at 6 and 12 months were 100% and 62.5%, respectively. RapidArc as a component in whole brain radiation therapy for poor prognostic, multiple brain metastases is an effective and safe modality with easy application.

  17. MultiComponent Exercise and theRApeutic lifeStyle (CERgAS) intervention to improve physical performance and maintain independent living among urban poor older people--a cluster randomised controlled trial.

    Science.gov (United States)

    Loh, Debbie Ann; Hairi, Noran Naqiah; Choo, Wan Yuen; Mohd Hairi, Farizah; Peramalah, Devi; Kandiben, Shathanapriya; Lee, Pek Ling; Gani, Norlissa; Madzlan, Mohamed Faris; Abd Hamid, Mohd Alif Idham; Akram, Zohaib; Chu, Ai Sean; Bulgiba, Awang; Cumming, Robert G

    2015-02-11

    The ability of older people to function independently is crucial as physical disability and functional limitation have profound impacts on health. Interventions that either delay the onset of frailty or attenuate its severity potentially have cascading benefits for older people, their families and society. This study aims to develop and evaluate the effectiveness of a multiComponent Exercise and theRApeutic lifeStyle (CERgAS) intervention program targeted at improving physical performance and maintaining independent living as compared to general health education among older people in an urban poor setting in Malaysia. This cluster randomised controlled trial will be a 6-week community-based intervention programme for older people aged 60 years and above from urban poor settings. A minimum of 164 eligible participants will be recruited from 8 clusters (low-cost public subsidised flats) and randomised to the intervention and control arm. This study will be underpinned by the Health Belief Model with an emphasis towards self-efficacy. The intervention will comprise multicomponent group exercise sessions, nutrition education, oral care education and on-going support and counselling. These will be complemented with a kit containing practical tips on exercise, nutrition and oral care after each session. Data will be collected over four time points; at baseline, immediately post-intervention, 3-months and 6-months follow-up. Findings from this trial will potentially provide valuable evidence to improve physical function and maintain independence among older people from low-resource settings. This will inform health policies and identify locally acceptable strategies to promote healthy aging, prevent and delay functional decline among older Malaysian adults. ISRCTN22749696.

  18. The main component of an alarm pheromone of kissing bugs plays multiple roles in the cognitive modulation of the escape response

    Directory of Open Access Journals (Sweden)

    Sebastián eMinoli

    2013-07-01

    Full Text Available Innate responses in animals can be modulated by experience. Disturbed adults of the triatomine bug Triatoma infestans release an alarm pheromone (AP that elicits an escape response in conspecific larvae. The main component of this AP, the isobutyric acid (IsoAc, alone has already shown to generate an escape response in this species. However, not much is known about the modulation of this behavior by non-associative and associative cognitive processes. We present here evidences of the cognitive capacities of T. infestans larvae in an escape context under different conditioning paradigms, including IsoAc in different roles. We show that: 1 the duration of a pre-exposure to IsoAc plays a main role in determining the type of non-associative learning expressed: short time pre-exposures elicit a sensitization while a longer pre-exposure time triggers a switch from repellence to attractiveness; 2 a simple pre-exposure event is enough to modulate the escape response of larvae to the AP and to its main component: IsoAc; 3 IsoAc and the AP are perceived as different chemical entities; 4 an association between IsoAc and an aversive stimulus can be created under a classical conditioning paradigm; 5 an association between IsoAc and a self-action can be generated under an operant conditioning. These results evince that IsoAc can attain multiple and different cognitive roles in the modulation of the escape response of triatomines and show how cognitive processes can modulate a key behavior for surviving, as it is the escaping response in presence of a potential danger in insects.

  19. Quantitative Raman spectral changes of the differentiation of mesenchymal stem cells into islet-like cells by biochemical component analysis and multiple peak fitting

    Science.gov (United States)

    Su, Xin; Fang, Shaoyin; Zhang, Daosen; Zhang, Qinnan; He, Yingtian; Lu, Xiaoxu; Liu, Shengde; Zhong, Liyun

    2015-12-01

    Mesenchymal stem cells (MSCs) differentiate into islet-like cells, providing a possible solution for type I diabetes treatment. To search for the precise molecular mechanism of the directional differentiation of MSC-derived islet-like cells, biomolecular composition, and structural conformation information during MSC differentiation, is required. Because islet-like cells lack specific surface markers, the commonly employed immunostaining technique is not suitable for their identification, physical separation, and enrichment. Combining Raman spectroscopic data, a fitting accuracy-improved biochemical component analysis, and multiple peaks fitting approach, we identified the quantitative biochemical and intensity change of Raman peaks that show the differentiation of MSCs into islet-like cells. Along with increases in protein and glycogen content, and decreases in deoxyribonucleic acid and ribonucleic acid content, in islet-like cells relative to MSCs, it was found that a characteristic peak of insulin (665 cm-1) has twice the intensity in islet-like cells relative to MSCs, indicating differentiation of MSCs into islet-like cells was successful. Importantly, these Raman signatures provide useful information on the structural and pathological states during MSC differentiation and help to develop noninvasive and label-free Raman sorting methods for stem cells and their lineages.

  20. Recombination dynamics of excitons with low non-radiative component in semi-polar (10-11)-oriented GaN/AlGaN multiple quantum wells

    International Nuclear Information System (INIS)

    Rosales, D.; Gil, B.; Bretagnon, T.; Guizal, B.; Izyumskaya, N.; Monavarian, M.; Zhang, F.; Okur, S.; Avrutin, V.; Özgür, Ü.; Morkoç, H.

    2014-01-01

    Optical properties of GaN/Al 0.2 Ga 0.8 N multiple quantum wells grown with semi-polar (10-11) orientation on patterned 7°-off Si (001) substrates have been investigated. Studies performed at 8 K reveal the in-plane anisotropic behavior of the QW photoluminescence (PL) intensity for this semi-polar orientation. The time resolved PL measurements were carried out in the temperature range from 8 to 295 K to deduce the effective recombination decay times, with respective radiative and non-radiative contributions. The non-radiative component remains relatively weak with increasing temperature, indicative of high crystalline quality. The radiative decay time is a consequence of contribution from both localized and free excitons. We report an effective density of interfacial defects of 2.3 × 10 12 cm −2 and a radiative recombination time of τ loc  = 355 ps for the localized excitons. This latter value is significantly larger than those reported for the non-polar structures, which we attribute to the presence of a weak residual electric field in the semi-polar QW layers

  1. Recombination dynamics of excitons with low non-radiative component in semi-polar (10-11)-oriented GaN/AlGaN multiple quantum wells

    Science.gov (United States)

    Rosales, D.; Gil, B.; Bretagnon, T.; Guizal, B.; Izyumskaya, N.; Monavarian, M.; Zhang, F.; Okur, S.; Avrutin, V.; Özgür, Ü.; Morkoç, H.

    2014-09-01

    Optical properties of GaN/Al0.2Ga0.8N multiple quantum wells grown with semi-polar (10-11) orientation on patterned 7°-off Si (001) substrates have been investigated. Studies performed at 8 K reveal the in-plane anisotropic behavior of the QW photoluminescence (PL) intensity for this semi-polar orientation. The time resolved PL measurements were carried out in the temperature range from 8 to 295 K to deduce the effective recombination decay times, with respective radiative and non-radiative contributions. The non-radiative component remains relatively weak with increasing temperature, indicative of high crystalline quality. The radiative decay time is a consequence of contribution from both localized and free excitons. We report an effective density of interfacial defects of 2.3 × 1012 cm-2 and a radiative recombination time of τloc = 355 ps for the localized excitons. This latter value is significantly larger than those reported for the non-polar structures, which we attribute to the presence of a weak residual electric field in the semi-polar QW layers.

  2. Recombination dynamics of excitons with low non-radiative component in semi-polar (10-11)-oriented GaN/AlGaN multiple quantum wells

    Energy Technology Data Exchange (ETDEWEB)

    Rosales, D.; Gil, B.; Bretagnon, T.; Guizal, B. [CNRS, Laboratoire Charles Coulomb, UMR 5221, F-34095 Montpellier (France); Université Montpellier 2, Laboratoire Charles Coulomb, UMR 5221, F-34095 Montpellier (France); Izyumskaya, N.; Monavarian, M.; Zhang, F.; Okur, S.; Avrutin, V.; Özgür, Ü.; Morkoç, H. [Department of Electrical and Computer Engineering, Virginia Commonwealth University, Richmond, Virginia 23238 (United States)

    2014-09-07

    Optical properties of GaN/Al{sub 0.2}Ga{sub 0.8}N multiple quantum wells grown with semi-polar (10-11) orientation on patterned 7°-off Si (001) substrates have been investigated. Studies performed at 8 K reveal the in-plane anisotropic behavior of the QW photoluminescence (PL) intensity for this semi-polar orientation. The time resolved PL measurements were carried out in the temperature range from 8 to 295 K to deduce the effective recombination decay times, with respective radiative and non-radiative contributions. The non-radiative component remains relatively weak with increasing temperature, indicative of high crystalline quality. The radiative decay time is a consequence of contribution from both localized and free excitons. We report an effective density of interfacial defects of 2.3 × 10{sup 12} cm{sup −2} and a radiative recombination time of τ{sub loc} = 355 ps for the localized excitons. This latter value is significantly larger than those reported for the non-polar structures, which we attribute to the presence of a weak residual electric field in the semi-polar QW layers.

  3. Effects of prior short multiple-sprint exercises with different intersprint recoveries on the slow component of oxygen uptake during high-intensity exercise.

    Science.gov (United States)

    Lanzi, Stefano; Borrani, Fabio; Wolf, Martin; Gojanovic, Boris; Malatesta, Davide

    2012-12-01

    This study compares the effects of two short multiple-sprint exercise (MSE) (6 × 6 s) sessions with two different recovery durations (30 s or 180 s) on the slow component of oxygen uptake ([Formula: see text]O(2)) during subsequent high-intensity exercise. Ten male subjects performed a 6-min cycling test at 50% of the difference between the gas exchange threshold and [Formula: see text]O(2peak) (Δ50). Then, the subjects performed two MSEs of 6 × 6 s separated by two intersprint recoveries of 30 s (MSE(30)) and 180 s (MSE(180)), followed 10 min later by the Δ50 (Δ50(30) and Δ50(180), respectively). Electromyography (EMG) activities of the vastus medialis and lateralis were measured throughout each exercise bout. During MSE(30), muscle activity (root mean square) increased significantly (p ≤ 0.04), with a significant leftward-shifted median frequency of the power density spectrum (MDF; p ≤ 0.01), whereas MDF was significantly rightward-shifted during MSE(180) (p = 0.02). The mean [Formula: see text]O(2) value was significantly higher in MSE(30) than in MSE(180) (p motor units recruitment profile (i.e., change in the type of muscle fibers recruited) and (or) an improved muscle O(2) delivery during subsequent exercise.

  4. Immunochip analyses identify a novel risk locus for primary biliary cirrhosis at 13q14, multiple independent associations at four established risk loci and epistasis between 1p31 and 7q32 risk variants

    Science.gov (United States)

    Juran, Brian D.; Hirschfield, Gideon M.; Invernizzi, Pietro; Atkinson, Elizabeth J.; Li, Yafang; Xie, Gang; Kosoy, Roman; Ransom, Michael; Sun, Ye; Bianchi, Ilaria; Schlicht, Erik M.; Lleo, Ana; Coltescu, Catalina; Bernuzzi, Francesca; Podda, Mauro; Lammert, Craig; Shigeta, Russell; Chan, Landon L.; Balschun, Tobias; Marconi, Maurizio; Cusi, Daniele; Heathcote, E. Jenny; Mason, Andrew L.; Myers, Robert P.; Milkiewicz, Piotr; Odin, Joseph A.; Luketic, Velimir A.; Bacon, Bruce R.; Bodenheimer, Henry C.; Liakina, Valentina; Vincent, Catherine; Levy, Cynthia; Franke, Andre; Gregersen, Peter K.; Bossa, Fabrizio; Gershwin, M. Eric; deAndrade, Mariza; Amos, Christopher I.; Lazaridis, Konstantinos N.; Seldin, Michael F.; Siminovitch, Katherine A.

    2012-01-01

    To further characterize the genetic basis of primary biliary cirrhosis (PBC), we genotyped 2426 PBC patients and 5731 unaffected controls from three independent cohorts using a single nucleotide polymorphism (SNP) array (Immunochip) enriched for autoimmune disease risk loci. Meta-analysis of the genotype data sets identified a novel disease-associated locus near the TNFSF11 gene at 13q14, provided evidence for association at six additional immune-related loci not previously implicated in PBC and confirmed associations at 19 of 22 established risk loci. Results of conditional analyses also provided evidence for multiple independent association signals at four risk loci, with haplotype analyses suggesting independent SNP effects at the 2q32 and 16p13 loci, but complex haplotype driven effects at the 3q25 and 6p21 loci. By imputing classical HLA alleles from this data set, four class II alleles independently contributing to the association signal from this region were identified. Imputation of genotypes at the non-HLA loci also provided additional associations, but none with stronger effects than the genotyped variants. An epistatic interaction between the IL12RB2 risk locus at 1p31and the IRF5 risk locus at 7q32 was also identified and suggests a complementary effect of these loci in predisposing to disease. These data expand the repertoire of genes with potential roles in PBC pathogenesis that need to be explored by follow-up biological studies. PMID:22936693

  5. Combined chemical (fluoranthene) and drought effects on Lumbricus rubellus demonstrate the applicability of the independent action model for multiple stressor assessment.

    Science.gov (United States)

    Long, Sara M; Reichenberg, Fredrik; Lister, Lindsay J; Hankard, Peter K; Townsend, Joanna; Mayer, Philipp; Wright, Julian; Holmstrup, Martin; Svendsen, Claus; Spurgeon, David J

    2009-03-01

    The combined effect of a chemical (fluoranthene) and a nonchemical stress (reduced soil moisture content) to the widely distributed earthworm Lumbricus rubellus were investigated in a laboratory study. Neither fluoranthene (up to 500 microg/g) nor low soil moisture (15% below optimal) had a significant effect on the survival of the exposed worms, but a significant effect on reproduction (cocoon production rate) was found for both stressors (p IA) model that is widely used in pharmacology and chemical mixture risk assessment. Fitting of the IA model provided a good description of the combined stressor data (accounting for 53.7% of total variation) and was the most parsimonious model describing joint effect (i.e., the description of the data was not improved by addition of further parameters accounting for synergism or antagonism). Thus, the independent action of the two responses was further supported by measurement of internal fluoranthene exposure. The chemical activity of fluoranthene in worm tissue was correlated only with soil fluoranthene concentration and not with soil moisture content. Taken together these results suggest that the IA model can help interpret the joint effects of chemical and nonchemical stressors. Such analyses should, however, be done with caution since the literature data set suggests that there may be cases where interactions between stressors result in joint effects that differ significantly from IA predictions.

  6. Fine-mapping and cross-validation of QTLs linked to fatty acid composition in multiple independent interspecific crosses of oil palm.

    Science.gov (United States)

    Ting, Ngoot-Chin; Yaakub, Zulkifli; Kamaruddin, Katialisa; Mayes, Sean; Massawe, Festo; Sambanthamurthi, Ravigadevi; Jansen, Johannes; Low, Leslie Eng Ti; Ithnin, Maizura; Kushairi, Ahmad; Arulandoo, Xaviar; Rosli, Rozana; Chan, Kuang-Lim; Amiruddin, Nadzirah; Sritharan, Kandha; Lim, Chin Ching; Nookiah, Rajanaidu; Amiruddin, Mohd Din; Singh, Rajinder

    2016-04-14

    The commercial oil palm (Elaeis guineensis Jacq.) produces a mesocarp oil (commonly called 'palm oil') with approximately equal proportions of saturated and unsaturated fatty acids (FAs). An increase in unsaturated FAs content or iodine value (IV) as a measure of the degree of unsaturation would help to open up new markets for the oil. One way to manipulate the fatty acid composition (FAC) in palm oil is through introgression of favourable alleles from the American oil palm, E. oleifera, which has a more unsaturated oil. In this study, a segregating E. oleifera x E. guineensis (OxG) hybrid population for FAC is used to identify quantitative trait loci (QTLs) linked to IV and various FAs. QTL analysis revealed 10 major and two putative QTLs for IV and six FAs, C14:0, C16:0, C16:1, C18:0, C18:1 and C18:2 distributed across six linkage groups (LGs), OT1, T2, T3, OT4, OT6 and T9. The major QTLs for IV and C16:0 on LGOT1 explained 60.0 - 69.0 % of the phenotypic trait variation and were validated in two independent BC2 populations. The genomic interval contains several key structural genes in the FA and oil biosynthesis pathways such as PATE/FATB, HIBCH, BASS2, LACS4 and DGAT1 and also a relevant transcription factor (TF), WRI1. The literature suggests that some of these genes can exhibit pleiotropic effects in the regulatory networks of these traits. Using the whole genome sequence data, markers tightly linked to the candidate genes were also developed. Clustering trait values according to the allelic forms of these candidate markers revealed significant differences in the IV and FAs of the palms in the mapping and validation crosses. The candidate gene approach described and exploited here is useful to identify the potential causal genes linked to FAC and can be adopted for marker-assisted selection (MAS) in oil palm.

  7. Simultaneous Determination of Multiple Components in Guanjiekang in Rat Plasma via the UPLC–MS/MS Method and Its Application in Pharmacokinetic Study

    Directory of Open Access Journals (Sweden)

    Jian Wu

    2016-12-01

    Full Text Available Guanjiekang (GJK that is formed by five medicinal herbs including Astragali Radix, Aconiti Lateralis Radix Praeparaia, Glycyrrhizae Radix et Rhizoma, Corydalis Rhizoma and Paeoniae Radix Alba was used for the treatment of rheumatoid arthritis (RA. However, the pharmacokinetic (PK profile of active components in GJK remains unclear. This study aims to evaluate the pharmacokinetic behavior of seven representative active constituents in GJK (i.e., benzoylhypaconine, benzoylmesaconine, paeoniflorin, tetrahydropalmatine, calycosin-7-glucoside, formononetin and isoliquiritigenin after oral administration of GJK in rats. A rapid, sensitive and reliable ultra-performance liquid chromatography-tandem mass spectrometer (UPLC–MS/MS method has been successfully developed for the simultaneous determination of these seven constituents in rat plasma. Chromatographic separation was achieved on a C18 column with a gradient elution program that consists of acetonitrile and water (containing 0.1% formic acid at a flow rate of 0.35 mL/min. Detection was performed under the multiple reaction monitoring (MRM in the positive electrospray ionization (ESI mode. The calibration curves exhibited good linearity (R2 > 0.99 over a wide concentration range for all constituents. The accuracies ranged from 92.9% to 107.8%, and the intra-day and inter-day precisions at three different levels were below 15%. Our PK results showed that these seven compounds were quickly absorbed after the administration of the GJK product, and Tmax ranged from 30 min to 189 min. The in vivo concentrations of paeoniflorin and isoliquiritigenin were significantly higher than the reported in vitro effective doses, indicating that they could partly contribute to the therapeutic effect of GJK. Therefore, we conclude that pharmacokinetic studies of representative bioactive chemicals after administration of complex herbal products are not only necessary but also feasible. Moreover, these seven

  8. Multiple crises and independences: Spain and its Monarchy Crisis e independencias: España y su monarquía

    Directory of Open Access Journals (Sweden)

    José María PORTILLO VALDÉS

    2009-05-01

    Full Text Available This article focuses on how the concept and practice of representation evolved during the crisis of the Spanish monarchy from 1808 onwards. It first proposes a conception of the crisis of the monarchy as a multiple process in which it evolved from a dynastic crisis to a constitutional one. Simultaneously to this evolution America appeared to be a decisive element for the solution of the crisis since it was declared an «essential» part of the Spanish monarchy by the Junta Central in 1809, ending the distinction between the metropolitan and colonial parts. This declaration was well accepted by a good part of the criollo elite whereas it was culturally impossible for the Spanish liberals to manage it in constitutional terms. This article analyses the consequences of this disruption between declarative and practical aspects of the first Spanish constitutional experience.Este artículo se centra en el estudio de la concepción y la práctica de la representación en el contexto de la crisis de la monarquía española desde 1808. Propone una interpretación compleja de la crisis señalando una evolución desde su dimensión dinástica hasta la constitucional. En la evolución de esa crisis, América resultó ser una pieza decisiva para su solución, desde que la Junta Central declarara en 1809 que conformaba una parte «esencial» de la monarquía, poniendo fin a la idea de una distinción entre parte metropolitana y colonial. Esta declaración fue asumida por buena parte de las elites criollas a la vez que los liberales españoles mostraron serias dificultades culturales para darle consecuencia constitucional. Este artículo analiza las consecuencias de esta bifurcación entre declaraciones y prácticas constitucionales.

  9. Independent preferences

    DEFF Research Database (Denmark)

    Vind, Karl

    1991-01-01

    A simple mathematical result characterizing a subset of a product set is proved and used to obtain additive representations of preferences. The additivity consequences of independence assumptions are obtained for preferences which are not total or transitive. This means that most of the economic ...... theory based on additive preferences - expected utility, discounted utility - has been generalized to preferences which are not total or transitive. Other economic applications of the theorem are given...

  10. Independent Directors

    DEFF Research Database (Denmark)

    Ringe, Wolf-Georg

    2013-01-01

    This paper re-evaluates the corporate governance concept of ‘board independence’ against the disappointing experiences during the 2007-08 financial crisis. Independent or outside directors had long been seen as an essential tool to improve the monitoring role of the board. Yet the crisis revealed...... that they did not prevent firms' excessive risk taking; further, these directors sometimes showed serious deficits in understanding the business they were supposed to control, and remained passive in addressing structural problems. A closer look reveals that under the surface of seemingly unanimous consensus...

  11. Independent production and Poisson distribution

    International Nuclear Information System (INIS)

    Golokhvastov, A.I.

    1994-01-01

    The well-known statement of factorization of inclusive cross-sections in case of independent production of particles (or clusters, jets etc.) and the conclusion of Poisson distribution over their multiplicity arising from it do not follow from the probability theory in any way. Using accurately the theorem of the product of independent probabilities, quite different equations are obtained and no consequences relative to multiplicity distributions are obtained. 11 refs

  12. Software component quality evaluation

    Science.gov (United States)

    Clough, A. J.

    1991-01-01

    The paper describes a software inspection process that can be used to evaluate the quality of software components. Quality criteria, process application, independent testing of the process and proposed associated tool support are covered. Early results indicate that this technique is well suited for assessing software component quality in a standardized fashion. With automated machine assistance to facilitate both the evaluation and selection of software components, such a technique should promote effective reuse of software components.

  13. Principal component regression for crop yield estimation

    CERN Document Server

    Suryanarayana, T M V

    2016-01-01

    This book highlights the estimation of crop yield in Central Gujarat, especially with regard to the development of Multiple Regression Models and Principal Component Regression (PCR) models using climatological parameters as independent variables and crop yield as a dependent variable. It subsequently compares the multiple linear regression (MLR) and PCR results, and discusses the significance of PCR for crop yield estimation. In this context, the book also covers Principal Component Analysis (PCA), a statistical procedure used to reduce a number of correlated variables into a smaller number of uncorrelated variables called principal components (PC). This book will be helpful to the students and researchers, starting their works on climate and agriculture, mainly focussing on estimation models. The flow of chapters takes the readers in a smooth path, in understanding climate and weather and impact of climate change, and gradually proceeds towards downscaling techniques and then finally towards development of ...

  14. Is Cognitive Activity of Speech Based On Statistical Independence?

    DEFF Research Database (Denmark)

    Feng, Ling; Hansen, Lars Kai

    2008-01-01

    This paper explores the generality of COgnitive Component Analysis (COCA), which is defined as the process of unsupervised grouping of data such that the ensuing group structure is well-aligned with that resulting from human cognitive activity. The hypothesis of {COCA} is ecological......: the essentially independent features in a context defined ensemble can be efficiently coded using a sparse independent component representation. Our devised protocol aims at comparing the performance of supervised learning (invoking cognitive activity) and unsupervised learning (statistical regularities) based...... on similar representations, and the only difference lies in the human inferred labels. Inspired by the previous research on COCA, we introduce a new pair of models, which directly employ the independent hypothesis. Statistical regularities are revealed at multiple time scales on phoneme, gender, age...

  15. Applying Independent Component Analysis on Sentinel-2 Imagery to Characterize Geomorphological Responses to an Extreme Flood Event near the Non-Vegetated Río Colorado Terminus, Salar de Uyuni, Bolivia

    Directory of Open Access Journals (Sweden)

    Jiaguang Li

    2018-05-01

    Full Text Available In some internally-draining dryland basins, ephemeral river systems terminate at the margins of playas. Extreme floods can exert significant geomorphological impacts on the lower reaches of these river systems and the playas, including causing changes to flood extent, channel-floodplain morphology, and sediment dispersal. However, the characterization of these impacts using remote sensing approaches has been challenging owing to variable vegetation and cloud cover, as well as the commonly limited spatial and temporal resolution of data. Here, we use Sentinel-2 Multispectral Instrument (MSI data to investigate the flood extent, flood patterns and channel-floodplain morphodynamics resulting from an extreme flood near the non-vegetated terminus of the Río Colorado, located at the margins of the world’s largest playa (Salar de Uyuni, Bolivia. Daily maximum precipitation frequency analysis based on a 42-year record of daily precipitation data (1976 through 2017 indicates that an approximately 40-year precipitation event (40.7 mm occurred on 6 January 2017, and this was associated with an extreme flood. Sentinel-2 data acquired after this extreme flood were used to separate water bodies and land, first by using modified normalized difference water index (MNDWI, and then by subsequently applying independent component analysis (ICA on the land section of the combined pre- and post-flood images to extract flooding areas. The area around the Río Colorado terminus system was classified into three categories: water bodies, wet land, and dry land. The results are in agreement with visual assessment, with an overall accuracy of 96% and Kappa of 0.9 for water-land classification and an overall accuracy of 83% and Kappa of 0.65 for dry land-wet land classification. The flood extent mapping revealed preferential overbank flow paths on the floodplain, which were closely related to geomorphological changes. Changes included the formation and enlargement of

  16. Design and Implementation of a Unified Command and Control Architecture for Multiple Cooperative Unmanned Vehicles Utilizing Commercial Off the Shelf Components

    Science.gov (United States)

    2015-12-24

    used as the backbone link to the ground station , allowing for a single high power transceiver on the backbone UAV to extend the range of the team. This...Patterson Air Force Base , Ohio DISTRIBUTION STATEMENT A APPROVED FOR PUBLIC RELEASE; DISTRIBUTION UNLIMITED. The views expressed in this document are...nation, and different cooperative missions. COTS components consisting primarily of open source hardware and software were integrated and tested based on

  17. MULTIPLE OBJECTS

    Directory of Open Access Journals (Sweden)

    A. A. Bosov

    2015-04-01

    Full Text Available Purpose. The development of complicated techniques of production and management processes, information systems, computer science, applied objects of systems theory and others requires improvement of mathematical methods, new approaches for researches of application systems. And the variety and diversity of subject systems makes necessary the development of a model that generalizes the classical sets and their development – sets of sets. Multiple objects unlike sets are constructed by multiple structures and represented by the structure and content. The aim of the work is the analysis of multiple structures, generating multiple objects, the further development of operations on these objects in application systems. Methodology. To achieve the objectives of the researches, the structure of multiple objects represents as constructive trio, consisting of media, signatures and axiomatic. Multiple object is determined by the structure and content, as well as represented by hybrid superposition, composed of sets, multi-sets, ordered sets (lists and heterogeneous sets (sequences, corteges. Findings. In this paper we study the properties and characteristics of the components of hybrid multiple objects of complex systems, proposed assessments of their complexity, shown the rules of internal and external operations on objects of implementation. We introduce the relation of arbitrary order over multiple objects, we define the description of functions and display on objects of multiple structures. Originality.In this paper we consider the development of multiple structures, generating multiple objects.Practical value. The transition from the abstract to the subject of multiple structures requires the transformation of the system and multiple objects. Transformation involves three successive stages: specification (binding to the domain, interpretation (multiple sites and particularization (goals. The proposed describe systems approach based on hybrid sets

  18. Towards Cognitive Component Analysis

    DEFF Research Database (Denmark)

    Hansen, Lars Kai; Ahrendt, Peter; Larsen, Jan

    2005-01-01

    Cognitive component analysis (COCA) is here defined as the process of unsupervised grouping of data such that the ensuing group structure is well-aligned with that resulting from human cognitive activity. We have earlier demonstrated that independent components analysis is relevant for representing...

  19. Multiple roles of mobile active center loops in the E1 component of the Escherichia coli pyruvate dehydrogenase complex - Linkage of protein dynamics to catalysis

    Science.gov (United States)

    Jordan, Frank; Arjunan, Palaniappa; Kale, Sachin; Nemeria, Natalia S.; Furey, William

    2009-01-01

    The region encompassing residues 401–413 on the E1 component of the pyruvate dehydrogenase multienzyme complex from Escherichia coli comprises a loop (the inner loop) which was not seen in the X-ray structure in the presence of thiamin diphosphate, the required cofactor for the enzyme. This loop is seen in the presence of a stable analogue of the pre-decarboxylation intermediate, the covalent adduct between the substrate analogue methyl acetylphosphonate and thiamin diphosphate, C2α-phosphonolactylthiamin diphosphate. It has been shown that the residue H407 and several other residues on this loop are required to reduce the mobility of the loop so electron density corresponding to it can be seen once the pre-decarboxylation intermediate is formed. Concomitantly, the loop encompassing residues 541–557 (the outer loop) appears to work in tandem with the inner loop and there is a hydrogen bond between the two loops ensuring their correlated motion. The inner loop was shown to: a) sequester the active center from carboligase side reactions; b) assist the interaction between the E1 and the E2 components, thereby affecting the overall reaction rate of the entire multienzyme complex; c) control substrate access to the active center. Using viscosity effects on kinetics it was shown that formation of the pre-decarboxylation intermediate is specifically affected by loop movement. A cysteine-less variant was created for the E1 component, onto which cysteines were substituted at selected loop positions. Introducing an electron spin resonance spin label and an 19F NMR label onto these engineered cysteines, the loop mobility was examined: a) both methods suggested that in the absence of ligand, the loop exists in two conformations; b) line-shape analysis of the NMR signal at different temperatures, enabled estimation of the rate constant for loop movement, and this rate constant was found to be of the same order of magnitude as the turnover number for the enzyme under the

  20. Multiple-layer laser deposition of steel components using gas- and water-atomised powders: the differences and the mechanisms leading to them

    International Nuclear Information System (INIS)

    Pinkerton, Andrew J.; Li Lin

    2005-01-01

    Functionally-graded or composite components have been recognised as having immense potential for many industries. The flexibility of direct metal deposition (DMD) has the potential to expand this to microstructurally graded components, but accurate control of the process is a problem. In this work, the effects of using different powder morphologies as a control mechanism for microstructure and other material properties are investigated experimentally. For the first time, comparison of the characteristics of two different gas-atomised (GA) and water-atomised (WA) materials is undertaken in order to evaluate the significance of the different DMD characteristics originating from the difference in atomisation method. 316L and H13 materials and a 1.2 kW CO 2 DMD system are used. Three primary factors for the differences are identified: increased vaporisation of the powder, a hotter melt pool and less powerful outward Marangoni flow when using water-atomised powder. The reasons for these, the influence they have on process characteristics and final material properties, and the circumstances under which they occur are discussed

  1. Systematic genetic array analysis links the Saccharomyces cerevisiae SAGA/SLIK and NuA4 component Tra1 to multiple cellular processes

    Directory of Open Access Journals (Sweden)

    Andrews Brenda

    2008-07-01

    Full Text Available Abstract Background Tra1 is an essential 437-kDa component of the Saccharomyces cerevisiae SAGA/SLIK and NuA4 histone acetyltransferase complexes. It is a member of a group of key signaling molecules that share a carboxyl-terminal domain related to phosphatidylinositol-3-kinase but unlike many family members, it lacks kinase activity. To identify genetic interactions for TRA1 and provide insight into its function we have performed a systematic genetic array analysis (SGA on tra1SRR3413, an allele that is defective in transcriptional regulation. Results The SGA analysis revealed 114 synthetic slow growth/lethal (SSL interactions for tra1SRR3413. The interacting genes are involved in a range of cellular processes including gene expression, mitochondrial function, and membrane sorting/protein trafficking. In addition many of the genes have roles in the cellular response to stress. A hierarchal cluster analysis revealed that the pattern of SSL interactions for tra1SRR3413 most closely resembles deletions of a group of regulatory GTPases required for membrane sorting/protein trafficking. Consistent with a role for Tra1 in cellular stress, the tra1SRR3413 strain was sensitive to rapamycin. In addition, calcofluor white sensitivity of the strain was enhanced by the protein kinase inhibitor staurosporine, a phenotype shared with the Ada components of the SAGA/SLIK complex. Through analysis of a GFP-Tra1 fusion we show that Tra1 is principally localized to the nucleus. Conclusion We have demonstrated a genetic association of Tra1 with nuclear, mitochondrial and membrane processes. The identity of the SSL genes also connects Tra1 with cellular stress, a result confirmed by the sensitivity of the tra1SRR3413 strain to a variety of stress conditions. Based upon the nuclear localization of GFP-Tra1 and the finding that deletion of the Ada components of the SAGA complex result in similar phenotypes as tra1SRR3413, we suggest that the effects of tra1SRR3413

  2. Background, design and conceptual model of the cluster randomized multiple-component workplace study: FRamed Intervention to Decrease Occupational Muscle pain - "FRIDOM"

    Directory of Open Access Journals (Sweden)

    Jeanette Reffstrup Christensen

    2016-10-01

    Full Text Available Abstract Background Several RCT studies have aimed to reduce either musculoskeletal disorders, sickness presenteeism, sickness absenteeism or a combination of these among females with high physical work demands. These studies have provided evidence that workplace health promotion (WHP interventions are effective, but long-term effects are still uncertain. These studies either lack to succeed in maintaining intervention effects or lack to document if effects are maintained past a one-year period. This paper describes the background, design and conceptual model of the FRIDOM (FRamed Intervention to Decrease Occupational Muscle pain WHP program among health care workers. A job group characterized by having high physical work demands, musculoskeletal disorders, high sickness presenteeism - and absenteeism. Methods FRIDOM aimed to reduce neck and shoulder pain. Secondary aims were to decrease sickness presenteeism, sickness absenteeism and lifestyle-diseases such as other musculoskeletal disorders as well as metabolic-, and cardiovascular disorders – and to maintain participation to regular physical exercise training, after a one year intervention period. The entire concept was tailored to a population of female health care workers. This was done through a multi-component intervention including 1 intelligent physical exercise training (IPET, dietary advice and weight loss (DAW and cognitive behavioural training (CBT. Discussion The FRIDOM program has the potential to provide evidence-based knowledge of the pain reducing effect of a multi component WHP among a female group of employees with a high prevalence of musculoskeletal disorders and in a long term perspective evaluate the effects on sickness presenteeism and absenteeism as well as risk of life-style diseases. Trial registration NCT02843269 , 06.27.2016 - retrospectively registered.

  3. Background, design and conceptual model of the cluster randomized multiple-component workplace study: FRamed Intervention to Decrease Occupational Muscle pain - "FRIDOM".

    Science.gov (United States)

    Christensen, Jeanette Reffstrup; Bredahl, Thomas Viskum Gjelstrup; Hadrévi, Jenny; Sjøgaard, Gisela; Søgaard, Karen

    2016-10-24

    Several RCT studies have aimed to reduce either musculoskeletal disorders, sickness presenteeism, sickness absenteeism or a combination of these among females with high physical work demands. These studies have provided evidence that workplace health promotion (WHP) interventions are effective, but long-term effects are still uncertain. These studies either lack to succeed in maintaining intervention effects or lack to document if effects are maintained past a one-year period. This paper describes the background, design and conceptual model of the FRIDOM (FRamed Intervention to Decrease Occupational Muscle pain) WHP program among health care workers. A job group characterized by having high physical work demands, musculoskeletal disorders, high sickness presenteeism - and absenteeism. FRIDOM aimed to reduce neck and shoulder pain. Secondary aims were to decrease sickness presenteeism, sickness absenteeism and lifestyle-diseases such as other musculoskeletal disorders as well as metabolic-, and cardiovascular disorders - and to maintain participation to regular physical exercise training, after a one year intervention period. The entire concept was tailored to a population of female health care workers. This was done through a multi-component intervention including 1) intelligent physical exercise training (IPET), dietary advice and weight loss (DAW) and cognitive behavioural training (CBT). The FRIDOM program has the potential to provide evidence-based knowledge of the pain reducing effect of a multi component WHP among a female group of employees with a high prevalence of musculoskeletal disorders and in a long term perspective evaluate the effects on sickness presenteeism and absenteeism as well as risk of life-style diseases. NCT02843269 , 06.27.2016 - retrospectively registered.

  4. A new method to quantify and compare the multiple components of fitness--a study case with kelp niche partition by divergent microstage adaptations to temperature.

    Directory of Open Access Journals (Sweden)

    Vasco M N C S Vieira

    Full Text Available Management of crops, commercialized or protected species, plagues or life-cycle evolution are subjects requiring comparisons among different demographic strategies. The simpler methods fail in relating changes in vital rates with changes in population viability whereas more complex methods lack accuracy by neglecting interactions among vital rates.The difference between the fitness (evaluated by the population growth rate λ of two alternative demographies is decomposed into the contributions of the differences between the pair-wised vital rates and their interactions. This is achieved through a full Taylor expansion (i.e. remainder = 0 of the demographic model. The significance of each term is determined by permutation tests under the null hypothesis that all demographies come from the same pool.An example is given with periodic demographic matrices of the microscopic haploid phase of two kelp cryptic species observed to partition their niche occupation along the Chilean coast. The method provided clear and synthetic results showing conditional differentiation of reproduction is an important driver for their differences in fitness along the latitudinal temperature gradient. But it also demonstrated that interactions among vital rates cannot be neglected as they compose a significant part of the differences between demographies.This method allows researchers to access the effects of multiple effective changes in a life-cycle from only two experiments. Evolutionists can determine with confidence the effective causes for changes in fitness whereas population managers can determine best strategies from simpler experimental designs.

  5. Simultaneous determination of components released from dental composite resins in human saliva by liquid chromatography/multiple-stage ion trap mass spectrometry.

    Science.gov (United States)

    Hsu, Wei-Yi; Wang, Ven-Shing; Lai, Chien-Chen; Tsai, Fuu-Jen

    2012-02-01

    Dental composite resins are widely used for fixing teeth; however, the monomers used in dental composite resins have been found to be cytotoxic and genotoxic, namely triethylene glycol dimethacrylate (TEGDMA), urethane dimethacrylate (UDMA), and bisphenol A glycol dimethacrylate (Bis-GMA). In this study, we incubated dental composite resins with human saliva for demonstrating the released monomers and biodegradation products. A simple saliva sample dilution method without purification or derivatization was used for quantification. We found that liquid chromatography coupled with multiple-stage ion trap mass spectrometry (LC-MS(n) ) operated in selected reaction monitoring (SRM) mode was able to separate the three monomers within 10 min. The calibration curves were linear (R² >0.996) over a wide range for each monomer in saliva: TEGDMA, 5-500 ppb; UDMA, 5-100 ppb, and Bis-GMA, 5-700 ppb. Furthermore, several biodegradation products were discovered with data-dependent MS/MS scan techniques. Although TEGMA degradation products have previously been reported, we identified two previously unknown UDMA degradation products. The LC-MS/MS method developed in this study was able to successfully quantify monomers and their principal biodegradation products from dental composite resins in human saliva. Copyright © 2012 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

  6. ABF2, an ABRE-binding bZIP factor, is an essential component of glucose signaling and its overexpression affects multiple stress tolerance.

    Science.gov (United States)

    Kim, Sunmi; Kang, Jung-Youn; Cho, Dong-Im; Park, Ji Hye; Kim, Soo Young

    2004-10-01

    Phytohormone abscisic acid (ABA) regulates stress-responsive gene expression during vegetative growth, which is mediated largely by cis-elements sharing the ACGTGGC consensus. Although many transcription factors are known to bind the elements in vitro, only a few have been demonstrated to have in vivo functions and their specific roles in ABA/stress responses are mostly unknown. Here, we report that ABF2, an ABF subfamily member of bZIP proteins interacting with the ABA-responsive elements, is involved in ABA/stress responses. Its overexpression altered ABA sensitivity, dehydration tolerance, and the expression levels of ABA/stress-regulated genes. Furthermore, ABF2 overexpression promoted glucose-induced inhibition of seedling development, whereas its mutation impaired glucose response. The reduced sugar sensitivity was not observed with mutants of two other ABF family members, ABF3 and ABF4. Instead, these mutants displayed defects in ABA, salt, and dehydration responses, which were not observed with the abf2 mutant. Our data indicate distinct roles of ABF family members: whereas ABF3 and ABF4 play essential roles in ABA/stress responses, ABF2 is required for normal glucose response. We also show that ABF2 overexpression affects multiple stress tolerance.

  7. Comprehensive two-dimensional HPLC to study the interaction of multiple components in Rheum palmatum L. with HSA by coupling a silica-bonded HSA column to a silica monolithic ODS column.

    Science.gov (United States)

    Hu, Lianghai; Li, Xin; Feng, Shun; Kong, Liang; Su, Xingye; Chen, Xueguo; Qin, Feng; Ye, Mingliang; Zou, Hanfa

    2006-04-01

    A mode of comprehensive 2-D LC was developed by coupling a silica-bonded HSA column to a silica monolithic ODS column. This system combined the affinity property of the HSA column and the high-speed separation ability of the monolithic ODS column. The affinity chromatography with HSA-immobilized stationary phase was applied to study the interaction of multiple components in traditional Chinese medicines (TCMs) with HSA according to their affinity to protein in the first dimension. Then the unresolved components retained on the HSA column were further separated on the silica monolithic ODS column in the second dimension. By hyphenating the 2-D separation system to diode array detector and MS detectors, the UV and molecular weight information of the separated compounds can also be obtained. The developed separation system was applied to analysis of the extract of Rheum palmatum L., a number of low-abundant components can be separated on a single peak from the HSA column after normalization of peak heights. Six compounds were preliminarily identified according to their UV and MS spectra. It showed that this system was very useful for biological fingerprinting analysis of the components in TCMs and natural products.

  8. Estimation of error components in a multi-error linear regression model, with an application to track fitting

    International Nuclear Information System (INIS)

    Fruehwirth, R.

    1993-01-01

    We present an estimation procedure of the error components in a linear regression model with multiple independent stochastic error contributions. After solving the general problem we apply the results to the estimation of the actual trajectory in track fitting with multiple scattering. (orig.)

  9. Distribution of maternal age and birth order groups in cases with unclassified multiple congenital abnormalities according to the number of component abnormalities: a national population-based case-control study.

    Science.gov (United States)

    Csermely, Gyula; Czeizel, Andrew E; Veszprémi, Béla

    2015-02-01

    Multiple congenital abnormalities are caused by chromosomal aberrations, mutant major genes and teratogens. A minor proportion of these patients are identified as syndromes but the major part belonging to the group of unclassified multiple CAs (UMCAs). The main objective of this study was to evaluate the maternal age and birth order in pregnant women who had offspring affected with UMCA. The strong association between numerical chromosomal aberrations, e.g., Down syndrome and advanced maternal age is well-known and tested here. The Hungarian Case-Control Surveillance of Congenital Abnormalities, 1980 to 1996, yielded a large population-based national data set with 22,843 malformed newborns or fetuses ("informative cases") included 1349 UMCA cases with their 2407 matched controls. Case-control comparison of maternal age and birth order was made for cases with UMCA, stratified by component numbers and their controls. In addition, 834 cases with Down syndrome were compared to 1432 matched controls. The well-known advanced maternal age with the higher risk for Down syndrome was confirmed. The findings of the study suggest that the young age of mothers associates with the higher risk of UMCA, in addition birth order 4 or more associates with the higher risk for UMCA with 2 and 3 component CAs. This study was the first to analyze the possible maternal and birth order effect for cases with UMCA, and the young age and higher birth order associated with a higher risk for UMCA. © 2014 Wiley Periodicals, Inc.

  10. Multiple origins of the phenol reaction negative phenotype in foxtail millet, Setaria italica (L.) P. Beauv., were caused by independent loss-of-function mutations of the polyphenol oxidase (Si7PPO) gene during domestication.

    Science.gov (United States)

    Inoue, Takahiko; Yuo, Takahisa; Ohta, Takeshi; Hitomi, Eriko; Ichitani, Katsuyuki; Kawase, Makoto; Taketa, Shin; Fukunaga, Kenji

    2015-08-01

    frequencies of ca. 25-67 % and those with negative Phr were broadly found in Europe and Asia. The stop codon type was found in 285 accessions and was broadly distributed in Europe and Asia, whereas the TE-1 insertion type was found in 99 accessions from Europe and Asia but was not found in India. The 6-bp duplication type was found in only 8 accessions from Nansei Islands (Okinawa Prefecture) of Japan. We also analyzed Phr in the wild ancestor and concluded that the negative Phr type was likely to have originated after domestication of foxtail millet. It was also implied that negative Phr of foxtail millet arose by multiple independent loss of function of PPO gene through dispersal because of some advantages under some environmental conditions and human selection as in rice and barley.

  11. Independent EEG sources are dipolar.

    Directory of Open Access Journals (Sweden)

    Arnaud Delorme

    Full Text Available Independent component analysis (ICA and blind source separation (BSS methods are increasingly used to separate individual brain and non-brain source signals mixed by volume conduction in electroencephalographic (EEG and other electrophysiological recordings. We compared results of decomposing thirteen 71-channel human scalp EEG datasets by 22 ICA and BSS algorithms, assessing the pairwise mutual information (PMI in scalp channel pairs, the remaining PMI in component pairs, the overall mutual information reduction (MIR effected by each decomposition, and decomposition 'dipolarity' defined as the number of component scalp maps matching the projection of a single equivalent dipole with less than a given residual variance. The least well-performing algorithm was principal component analysis (PCA; best performing were AMICA and other likelihood/mutual information based ICA methods. Though these and other commonly-used decomposition methods returned many similar components, across 18 ICA/BSS algorithms mean dipolarity varied linearly with both MIR and with PMI remaining between the resulting component time courses, a result compatible with an interpretation of many maximally independent EEG components as being volume-conducted projections of partially-synchronous local cortical field activity within single compact cortical domains. To encourage further method comparisons, the data and software used to prepare the results have been made available (http://sccn.ucsd.edu/wiki/BSSComparison.

  12. Other components

    International Nuclear Information System (INIS)

    Anon.

    1993-01-01

    This chapter includes descriptions of electronic and mechanical components which do not merit a chapter to themselves. Other hardware requires mention because of particularly high tolerance or intolerance of exposure to radiation. A more systematic analysis of radiation responses of structures which are definable by material was given in section 3.8. The components discussed here are field effect transistors, transducers, temperature sensors, magnetic components, superconductors, mechanical sensors, and miscellaneous electronic components

  13. [Multiple meningiomas].

    Science.gov (United States)

    Terrier, L-M; François, P

    2016-06-01

    Multiple meningiomas (MMs) or meningiomatosis are defined by the presence of at least 2 lesions that appear simultaneously or not, at different intracranial locations, without the association of neurofibromatosis. They present 1-9 % of meningiomas with a female predominance. The occurrence of multiple meningiomas is not clear. There are 2 main hypotheses for their development, one that supports the independent evolution of these tumors and the other, completely opposite, that suggests the propagation of tumor cells of a unique clone transformation, through cerebrospinal fluid. NF2 gene mutation is an important intrinsic risk factor in the etiology of multiple meningiomas and some exogenous risk factors have been suspected but only ionizing radiation exposure has been proven. These tumors can grow anywhere in the skull but they are more frequently observed in supratentorial locations. Their histologic types are similar to unique meningiomas of psammomatous, fibroblastic, meningothelial or transitional type and in most cases are benign tumors. The prognosis of these tumors is eventually good and does not differ from the unique tumors except for the cases of radiation-induced multiple meningiomas, in the context of NF2 or when diagnosed in children where the outcome is less favorable. Each meningioma lesion should be dealt with individually and their multiple character should not justify their resection at all costs. Copyright © 2016 Elsevier Masson SAS. All rights reserved.

  14. The Independent Payment Advisory Board.

    Science.gov (United States)

    Manchikanti, Laxmaiah; Falco, Frank J E; Singh, Vijay; Benyamin, Ramsin M; Hirsch, Joshua A

    2011-01-01

    The Independent Payment Advisory Board (IPAB) is a vastly powerful component of the president's health care reform law, with authority to issue recommendations to reduce the growth in Medicare spending, providing recommendations to be considered by Congress and implemented by the administration on a fast track basis. Ever since its inception, IPAB has been one of the most controversial issues of the Patient Protection and Affordable Care Act (ACA), even though the powers of IPAB are restricted and multiple sectors of health care have been protected in the law. IPAB works by recommending policies to Congress to help Medicare provide better care at a lower cost, which would include ideas on coordinating care, getting rid of waste in the system, providing incentives for best practices, and prioritizing primary care. Congress then has the power to accept or reject these recommendations. However, Congress faces extreme limitations, either to enact policies that achieve equivalent savings, or let the Secretary of Health and Human Services (HHS) follow IPAB's recommendations. IPAB has strong supporters and opponents, leading to arguments in favor of or against to the extreme of introducing legislation to repeal IPAB. The origins of IPAB are found in the ideology of the National Institute for Health and Clinical Excellence (NICE) and the impetus of exploring health care costs, even though IPAB's authority seems to be limited to Medicare only. The structure and operation of IPAB differs from Medicare and has been called the Medicare Payment Advisory Commission (MedPAC) on steroids. The board membership consists of 15 full-time members appointed by the president and confirmed by the Senate with options for recess appointments. The IPAB statute sets target growth rates for Medicare spending. The applicable percent for maximum savings appears to be 0.5% for year 2015, 1% for 2016, 1.25% for 2017, and 1.5% for 2018 and later. The IPAB Medicare proposal process involves

  15. Electronic components

    CERN Document Server

    Colwell, Morris A

    1976-01-01

    Electronic Components provides a basic grounding in the practical aspects of using and selecting electronics components. The book describes the basic requirements needed to start practical work on electronic equipment, resistors and potentiometers, capacitance, and inductors and transformers. The text discusses semiconductor devices such as diodes, thyristors and triacs, transistors and heat sinks, logic and linear integrated circuits (I.C.s) and electromechanical devices. Common abbreviations applied to components are provided. Constructors and electronics engineers will find the book useful

  16. Cognitive Component Analysis

    DEFF Research Database (Denmark)

    Feng, Ling

    2008-01-01

    This dissertation concerns the investigation of the consistency of statistical regularities in a signaling ecology and human cognition, while inferring appropriate actions for a speech-based perceptual task. It is based on unsupervised Independent Component Analysis providing a rich spectrum...... of audio contexts along with pattern recognition methods to map components to known contexts. It also involves looking for the right representations for auditory inputs, i.e. the data analytic processing pipelines invoked by human brains. The main ideas refer to Cognitive Component Analysis, defined...... as the process of unsupervised grouping of generic data such that the ensuing group structure is well-aligned with that resulting from human cognitive activity. Its hypothesis runs ecologically: features which are essentially independent in a context defined ensemble, can be efficiently coded as sparse...

  17. Independence and Product Systems

    OpenAIRE

    Skeide, Michael

    2003-01-01

    Starting from elementary considerations about independence and Markov processes in classical probability we arrive at the new concept of conditional monotone independence (or operator-valued monotone independence). With the help of product systems of Hilbert modules we show that monotone conditional independence arises naturally in dilation theory.

  18. Component reliability criticality or importance metrics for systems with degrading components

    NARCIS (Netherlands)

    Peng, H.; Coit, D.W.; Feng, Q.

    2012-01-01

    This paper proposes two new importance measures: one new importance measure for systems with -independent degrading components, and another one for systems with -correlated degrading components. Importance measures in previous research are inadequate for systems with degrading components because

  19. Are Independent Fiscal Institutions Really Independent?

    Directory of Open Access Journals (Sweden)

    Slawomir Franek

    2015-08-01

    Full Text Available In the last decade the number of independent fiscal institutions (known also as fiscal councils has tripled. They play an important oversight role over fiscal policy-making in democratic societies, especially as they seek to restore public finance stability in the wake of the recent financial crisis. Although common functions of such institutions include a role in analysis of fiscal policy, forecasting, monitoring compliance with fiscal rules or costing of spending proposals, their roles, resources and structures vary considerably across countries. The aim of the article is to determine the degree of independence of such institutions based on the analysis of the independence index of independent fiscal institutions. The analysis of this index values may be useful to determine the relations between the degree of independence of fiscal councils and fiscal performance of particular countries. The data used to calculate the index values will be derived from European Commission and IMF, which collect sets of information about characteristics of activity of fiscal councils.

  20. Information Flow Integrity for Systems of Independently-Developed Components

    Science.gov (United States)

    2015-06-22

    We also examined three programs (Apache, MySQL , and PHP) in detail to evaluate the efficacy of using the provided package test suites to generate...method are just as effective as hooks that were manually placed over the course of years while greatly reducing the burden on programmers. ”Leveraging...to validate optimizations of real-world, mature applications: the Apache software suite, the Mozilla Suite, and the MySQL database. ”Validating Library

  1. Prediction of the GC-MS Retention Indices for a Diverse Set of Terpenes as Constituent Components of Camu-camu (Myrciaria dubia (HBK Mc Vaugh Volatile Oil, Using Particle Swarm Optimization-Multiple Linear Regression (PSO-MLR

    Directory of Open Access Journals (Sweden)

    Majid Mohammadhosseini

    2014-05-01

    Full Text Available A reliable quantitative structure retention relationship (QSRR study has been evaluated to predict the retention indices (RIs of a broad spectrum of compounds, namely 118 non-linear, cyclic and heterocyclic terpenoids (both saturated and unsaturated, on an HP-5MS fused silica column. A principal component analysis showed that seven compounds lay outside of the main cluster. After elimination of the outliers, the data set was divided into training and test sets involving 80 and 28 compounds. The method was tested by application of the particle swarm optimization (PSO method to find the most effective molecular descriptors, followed by multiple linear regressions (MLR. The PSO-MLR model was further confirmed through “leave one out cross validation” (LOO-CV and “leave group out cross validation” (LGO-CV, as well as external validations. The promising statistical figures of merit associated with the proposed model (R2train=0.936, Q2LOO=0.928, Q2LGO=0.921, F=376.4 confirm its high ability to predict RIs with negligible relative errors of predictions (REP train=4.8%, REP test=6.0%.

  2. Central Bank independence

    Directory of Open Access Journals (Sweden)

    Vasile DEDU

    2012-08-01

    Full Text Available In this paper we present the key aspects regarding central bank’s independence. Most economists consider that the factor which positively influences the efficiency of monetary policy measures is the high independence of the central bank. We determined that the National Bank of Romania (NBR has a high degree of independence. NBR has both goal and instrument independence. We also consider that the hike of NBR’s independence played an important role in the significant disinflation process, as headline inflation dropped inside the targeted band of 3% ± 1 percentage point recently.

  3. Organizing Independent Student Work

    Directory of Open Access Journals (Sweden)

    Zhadyra T. Zhumasheva

    2015-03-01

    Full Text Available This article addresses issues in organizing independent student work. The author defines the term “independence”, discusses the concepts of independent learner work and independent learner work under the guidance of an instructor, proposes a classification of assignments to be done independently, and provides methodological recommendations as to the organization of independent student work. The article discusses the need for turning the student from a passive consumer of knowledge into an active creator of it, capable of formulating a problem, analyzing the ways of solving it, coming up with an optimum outcome, and proving its correctness. The preparation of highly qualified human resources is the primary condition for boosting Kazakhstan’s competitiveness. Independent student work is a means of fostering the professional competence of future specialists. The primary form of self-education is independent work.

  4. Controleum - an independently extensible control system

    DEFF Research Database (Denmark)

    Jensen, Martin Lykke Rytter

    2014-01-01

    challenging kind of system to design for independent extension. This thesis presents two new software technologies that improve the extensibility of control systems: First, the concept of dynamic links is introduced and Decouplink – an implementation of dynamic links for Java - is presented. Dynamic links...... is introduced, and an implementation is presented. The extensible controller is a component framework designed to automatically resolve conflicts among mutually unaware components in a control system. The solution is based on the idea that independent components implement different kinds of control concerns...

  5. Principal components

    NARCIS (Netherlands)

    Hallin, M.; Hörmann, S.; Piegorsch, W.; El Shaarawi, A.

    2012-01-01

    Principal Components are probably the best known and most widely used of all multivariate analysis techniques. The essential idea consists in performing a linear transformation of the observed k-dimensional variables in such a way that the new variables are vectors of k mutually orthogonal

  6. Simultaneous quantitative determination of multiple bioactive markers in Ocimum sanctum obtained from different locations and its marketed herbal formulations using UPLC-ESI-MS/MS combined with principal component analysis.

    Science.gov (United States)

    Pandey, Renu; Chandra, Preeti; Srivastava, Mukesh; Mishra, D K; Kumar, Brijesh

    2015-01-01

    Ocimum sanctum L., with phenolic acids, flavonoids, propenyl phenols and terpenoids as active pharmacological constituents, is a popular medicinal herb and is present as an ingredient in many herbal formulations. Therefore, development of a reliable analytical method for simultaneous determination of the pharmacologically active constituents of O. sanctum is of high importance. To develop and validate a new, rapid, sensitive and selective UPLC-ESI/MS/MS method for simultaneous determination of 23 bioactive markers including phenolic acids, flavonoids, propenyl phenol and terpenoid in the leaf extract and marketed herbal formulations of O. sanctum. An UPLC-ESI/MS/MS method using negative electrospray ionisation (ESI) in multiple-reaction-monitoring (MRM) mode was used for simultaneous determination. Chromatographic separation was achieved on an Acquity UPLC BEH C18 -column using a gradient elution with 0.1% formic acid in water and 0.1% formic acid in acetonitrile. Principal component analysis (PCA) was applied to correlate and discriminate eight geographical collections of O. sanctum based on quantitative data of the analytes. The developed method was validated as per International Conference on Harmonization guidelines and found to be accurate, with overall recovery in the range 95.09-104.84% (RSD ≤ 1.85%), precise (RSD ≤ 1.98%) and linear (r(2)  ≥ 0.9971) over the concentration range of 0.5-1000 ng/mL. Ursolic acid was found to be the most abundant marker in all the samples investigated, except for the marketed tablet. The method established is simple, rapid and sensitive, hence it can be reliably utilised for the quality control of O. sanctum and derived herbal formulations. Copyright © 2015 John Wiley & Sons, Ltd.

  7. Imputation and subset-based association analysis across different cancer types identifies multiple independent risk loci in the TERT-CLPTM1L region on chromosome 5p15.33

    Science.gov (United States)

    Wang, Zhaoming; Zhu, Bin; Zhang, Mingfeng; Parikh, Hemang; Jia, Jinping; Chung, Charles C.; Sampson, Joshua N.; Hoskins, Jason W.; Hutchinson, Amy; Burdette, Laurie; Ibrahim, Abdisamad; Hautman, Christopher; Raj, Preethi S.; Abnet, Christian C.; Adjei, Andrew A.; Ahlbom, Anders; Albanes, Demetrius; Allen, Naomi E.; Ambrosone, Christine B.; Aldrich, Melinda; Amiano, Pilar; Amos, Christopher; Andersson, Ulrika; Andriole, Gerald; Andrulis, Irene L.; Arici, Cecilia; Arslan, Alan A.; Austin, Melissa A.; Baris, Dalsu; Barkauskas, Donald A.; Bassig, Bryan A.; Beane Freeman, Laura E.; Berg, Christine D.; Berndt, Sonja I.; Bertazzi, Pier Alberto; Biritwum, Richard B.; Black, Amanda; Blot, William; Boeing, Heiner; Boffetta, Paolo; Bolton, Kelly; Boutron-Ruault, Marie-Christine; Bracci, Paige M.; Brennan, Paul; Brinton, Louise A.; Brotzman, Michelle; Bueno-de-Mesquita, H. Bas; Buring, Julie E.; Butler, Mary Ann; Cai, Qiuyin; Cancel-Tassin, Geraldine; Canzian, Federico; Cao, Guangwen; Caporaso, Neil E.; Carrato, Alfredo; Carreon, Tania; Carta, Angela; Chang, Gee-Chen; Chang, I-Shou; Chang-Claude, Jenny; Che, Xu; Chen, Chien-Jen; Chen, Chih-Yi; Chen, Chung-Hsing; Chen, Constance; Chen, Kuan-Yu; Chen, Yuh-Min; Chokkalingam, Anand P.; Chu, Lisa W.; Clavel-Chapelon, Francoise; Colditz, Graham A.; Colt, Joanne S.; Conti, David; Cook, Michael B.; Cortessis, Victoria K.; Crawford, E. David; Cussenot, Olivier; Davis, Faith G.; De Vivo, Immaculata; Deng, Xiang; Ding, Ti; Dinney, Colin P.; Di Stefano, Anna Luisa; Diver, W. Ryan; Duell, Eric J.; Elena, Joanne W.; Fan, Jin-Hu; Feigelson, Heather Spencer; Feychting, Maria; Figueroa, Jonine D.; Flanagan, Adrienne M.; Fraumeni, Joseph F.; Freedman, Neal D.; Fridley, Brooke L.; Fuchs, Charles S.; Gago-Dominguez, Manuela; Gallinger, Steven; Gao, Yu-Tang; Gapstur, Susan M.; Garcia-Closas, Montserrat; Garcia-Closas, Reina; Gastier-Foster, Julie M.; Gaziano, J. Michael; Gerhard, Daniela S.; Giffen, Carol A.; Giles, Graham G.; Gillanders, Elizabeth M.; Giovannucci, Edward L.; Goggins, Michael; Gokgoz, Nalan; Goldstein, Alisa M.; Gonzalez, Carlos; Gorlick, Richard; Greene, Mark H.; Gross, Myron; Grossman, H. Barton; Grubb, Robert; Gu, Jian; Guan, Peng; Haiman, Christopher A.; Hallmans, Goran; Hankinson, Susan E.; Harris, Curtis C.; Hartge, Patricia; Hattinger, Claudia; Hayes, Richard B.; He, Qincheng; Helman, Lee; Henderson, Brian E.; Henriksson, Roger; Hoffman-Bolton, Judith; Hohensee, Chancellor; Holly, Elizabeth A.; Hong, Yun-Chul; Hoover, Robert N.; Hosgood, H. Dean; Hsiao, Chin-Fu; Hsing, Ann W.; Hsiung, Chao Agnes; Hu, Nan; Hu, Wei; Hu, Zhibin; Huang, Ming-Shyan; Hunter, David J.; Inskip, Peter D.; Ito, Hidemi; Jacobs, Eric J.; Jacobs, Kevin B.; Jenab, Mazda; Ji, Bu-Tian; Johansen, Christoffer; Johansson, Mattias; Johnson, Alison; Kaaks, Rudolf; Kamat, Ashish M.; Kamineni, Aruna; Karagas, Margaret; Khanna, Chand; Khaw, Kay-Tee; Kim, Christopher; Kim, In-Sam; Kim, Jin Hee; Kim, Yeul Hong; Kim, Young-Chul; Kim, Young Tae; Kang, Chang Hyun; Jung, Yoo Jin; Kitahara, Cari M.; Klein, Alison P.; Klein, Robert; Kogevinas, Manolis; Koh, Woon-Puay; Kohno, Takashi; Kolonel, Laurence N.; Kooperberg, Charles; Kratz, Christian P.; Krogh, Vittorio; Kunitoh, Hideo; Kurtz, Robert C.; Kurucu, Nilgun; Lan, Qing; Lathrop, Mark; Lau, Ching C.; Lecanda, Fernando; Lee, Kyoung-Mu; Lee, Maxwell P.; Le Marchand, Loic; Lerner, Seth P.; Li, Donghui; Liao, Linda M.; Lim, Wei-Yen; Lin, Dongxin; Lin, Jie; Lindstrom, Sara; Linet, Martha S.; Lissowska, Jolanta; Liu, Jianjun; Ljungberg, Börje; Lloreta, Josep; Lu, Daru; Ma, Jing; Malats, Nuria; Mannisto, Satu; Marina, Neyssa; Mastrangelo, Giuseppe; Matsuo, Keitaro; McGlynn, Katherine A.; McKean-Cowdin, Roberta; McNeill, Lorna H.; McWilliams, Robert R.; Melin, Beatrice S.; Meltzer, Paul S.; Mensah, James E.; Miao, Xiaoping; Michaud, Dominique S.; Mondul, Alison M.; Moore, Lee E.; Muir, Kenneth; Niwa, Shelley; Olson, Sara H.; Orr, Nick; Panico, Salvatore; Park, Jae Yong; Patel, Alpa V.; Patino-Garcia, Ana; Pavanello, Sofia; Peeters, Petra H. M.; Peplonska, Beata; Peters, Ulrike; Petersen, Gloria M.; Picci, Piero; Pike, Malcolm C.; Porru, Stefano; Prescott, Jennifer; Pu, Xia; Purdue, Mark P.; Qiao, You-Lin; Rajaraman, Preetha; Riboli, Elio; Risch, Harvey A.; Rodabough, Rebecca J.; Rothman, Nathaniel; Ruder, Avima M.; Ryu, Jeong-Seon; Sanson, Marc; Schned, Alan; Schumacher, Fredrick R.; Schwartz, Ann G.; Schwartz, Kendra L.; Schwenn, Molly; Scotlandi, Katia; Seow, Adeline; Serra, Consol; Serra, Massimo; Sesso, Howard D.; Severi, Gianluca; Shen, Hongbing; Shen, Min; Shete, Sanjay; Shiraishi, Kouya; Shu, Xiao-Ou; Siddiq, Afshan; Sierrasesumaga, Luis; Sierri, Sabina; Loon Sihoe, Alan Dart; Silverman, Debra T.; Simon, Matthias; Southey, Melissa C.; Spector, Logan; Spitz, Margaret; Stampfer, Meir; Stattin, Par; Stern, Mariana C.; Stevens, Victoria L.; Stolzenberg-Solomon, Rachael Z.; Stram, Daniel O.; Strom, Sara S.; Su, Wu-Chou; Sund, Malin; Sung, Sook Whan; Swerdlow, Anthony; Tan, Wen; Tanaka, Hideo; Tang, Wei; Tang, Ze-Zhang; Tardon, Adonina; Tay, Evelyn; Taylor, Philip R.; Tettey, Yao; Thomas, David M.; Tirabosco, Roberto; Tjonneland, Anne; Tobias, Geoffrey S.; Toro, Jorge R.; Travis, Ruth C.; Trichopoulos, Dimitrios; Troisi, Rebecca; Truelove, Ann; Tsai, Ying-Huang; Tucker, Margaret A.; Tumino, Rosario; Van Den Berg, David; Van Den Eeden, Stephen K.; Vermeulen, Roel; Vineis, Paolo; Visvanathan, Kala; Vogel, Ulla; Wang, Chaoyu; Wang, Chengfeng; Wang, Junwen; Wang, Sophia S.; Weiderpass, Elisabete; Weinstein, Stephanie J.; Wentzensen, Nicolas; Wheeler, William; White, Emily; Wiencke, John K.; Wolk, Alicja; Wolpin, Brian M.; Wong, Maria Pik; Wrensch, Margaret; Wu, Chen; Wu, Tangchun; Wu, Xifeng; Wu, Yi-Long; Wunder, Jay S.; Xiang, Yong-Bing; Xu, Jun; Yang, Hannah P.; Yang, Pan-Chyr; Yatabe, Yasushi; Ye, Yuanqing; Yeboah, Edward D.; Yin, Zhihua; Ying, Chen; Yu, Chong-Jen; Yu, Kai; Yuan, Jian-Min; Zanetti, Krista A.; Zeleniuch-Jacquotte, Anne; Zheng, Wei; Zhou, Baosen; Mirabello, Lisa; Savage, Sharon A.; Kraft, Peter; Chanock, Stephen J.; Yeager, Meredith; Landi, Maria Terese; Shi, Jianxin; Chatterjee, Nilanjan; Amundadottir, Laufey T.

    2014-01-01

    Genome-wide association studies (GWAS) have mapped risk alleles for at least 10 distinct cancers to a small region of 63 000 bp on chromosome 5p15.33. This region harbors the TERT and CLPTM1L genes; the former encodes the catalytic subunit of telomerase reverse transcriptase and the latter may play a role in apoptosis. To investigate further the genetic architecture of common susceptibility alleles in this region, we conducted an agnostic subset-based meta-analysis (association analysis based on subsets) across six distinct cancers in 34 248 cases and 45 036 controls. Based on sequential conditional analysis, we identified as many as six independent risk loci marked by common single-nucleotide polymorphisms: five in the TERT gene (Region 1: rs7726159, P = 2.10 × 10−39; Region 3: rs2853677, P = 3.30 × 10−36 and PConditional = 2.36 × 10−8; Region 4: rs2736098, P = 3.87 × 10−12 and PConditional = 5.19 × 10−6, Region 5: rs13172201, P = 0.041 and PConditional = 2.04 × 10−6; and Region 6: rs10069690, P = 7.49 × 10−15 and PConditional = 5.35 × 10−7) and one in the neighboring CLPTM1L gene (Region 2: rs451360; P = 1.90 × 10−18 and PConditional = 7.06 × 10−16). Between three and five cancers mapped to each independent locus with both risk-enhancing and protective effects. Allele-specific effects on DNA methylation were seen for a subset of risk loci, indicating that methylation and subsequent effects on gene expression may contribute to the biology of risk variants on 5p15.33. Our results provide strong support for extensive pleiotropy across this region of 5p15.33, to an extent not previously observed in other cancer susceptibility loci. PMID:25027329

  8. Multiple inflation

    International Nuclear Information System (INIS)

    Murphy, P.J.

    1987-01-01

    The Theory of Inflation, namely, that at some point the entropy content of the universe was greatly increased, has much promise. It may solve the puzzles of homogeneity and the creation of structure. However, no particle physics model has yet been found that can successfully drive inflation. The difficulty in satisfying the constraint that the isotropy of the microwave background places on the effective potential of prospective models is immense. In this work we have codified the requirements of such models in a most general form. We have carefully calculated the amounts of inflation the various problems of the Standard Model need for their solution. We have derived a completely model independent upper bond on the inflationary Hubble parameter. We have developed a general notation with which to probe the possibilities of Multiple Inflation. We have shown that only in very unlikely circumstances will any evidence of an earlier inflation, survive the de Sitter period of its successor. In particular, it is demonstrated that it is most unlikely that two bouts of inflation will yield high amplitudes of density perturbations on small scales and low amplitudes on large. We conclude that, while multiple inflation will be of great theoretical interest, it is unlikely to have any observational impact

  9. Accounting for Independent Schools.

    Science.gov (United States)

    Sonenstein, Burton

    The diversity of independent schools in size, function, and mode of operation has resulted in a considerable variety of accounting principles and practices. This lack of uniformity has tended to make understanding, evaluation, and comparison of independent schools' financial statements a difficult and sometimes impossible task. This manual has…

  10. Optical CDMA components requirements

    Science.gov (United States)

    Chan, James K.

    1998-08-01

    Optical CDMA is a complementary multiple access technology to WDMA. Optical CDMA potentially provides a large number of virtual optical channels for IXC, LEC and CLEC or supports a large number of high-speed users in LAN. In a network, it provides asynchronous, multi-rate, multi-user communication with network scalability, re-configurability (bandwidth on demand), and network security (provided by inherent CDMA coding). However, optical CDMA technology is less mature in comparison to WDMA. The components requirements are also different from WDMA. We have demonstrated a video transport/switching system over a distance of 40 Km using discrete optical components in our laboratory. We are currently pursuing PIC implementation. In this paper, we will describe the optical CDMA concept/features, the demonstration system, and the requirements of some critical optical components such as broadband optical source, broadband optical amplifier, spectral spreading/de- spreading, and fixed/programmable mask.

  11. Probabilistic conditional independence structures

    CERN Document Server

    Studeny, Milan

    2005-01-01

    Probabilistic Conditional Independence Structures provides the mathematical description of probabilistic conditional independence structures; the author uses non-graphical methods of their description, and takes an algebraic approach.The monograph presents the methods of structural imsets and supermodular functions, and deals with independence implication and equivalence of structural imsets.Motivation, mathematical foundations and areas of application are included, and a rough overview of graphical methods is also given.In particular, the author has been careful to use suitable terminology, and presents the work so that it will be understood by both statisticians, and by researchers in artificial intelligence.The necessary elementary mathematical notions are recalled in an appendix.

  12. The Independence Pipeline project : ANR's supply link - Independence Pipeline, Transco's market link

    International Nuclear Information System (INIS)

    Persells, T.

    1998-01-01

    An overview of the Independence Pipeline project was presented. The project offers access from Chicago to the U.S. Midwest market, as well as to Ontario via MichCon, Consumers Power, Great Lakes and Panhandle. The project has three components: ANR's Supply Link, the Independence Pipeline and Transco's MarketLink. The three components are budgeted at $ 1.332 billion dollars and projected for completion between Nov 1999 and Nov 2000. Each component (services, access advantages, market links, rates, storage services, etc ) are described separately. figs

  13. A systematic approach for component-based software development

    NARCIS (Netherlands)

    Guareis de farias, Cléver; van Sinderen, Marten J.; Ferreira Pires, Luis

    2000-01-01

    Component-based software development enables the construction of software artefacts by assembling prefabricated, configurable and independently evolving building blocks, called software components. This paper presents an approach for the development of component-based software artefacts. This

  14. Independent technical review, handbook

    International Nuclear Information System (INIS)

    1994-02-01

    Purpose Provide an independent engineering review of the major projects being funded by the Department of Energy, Office of Environmental Restoration and Waste Management. The independent engineering review will address questions of whether the engineering practice is sufficiently developed to a point where a major project can be executed without significant technical problems. The independent review will focus on questions related to: (1) Adequacy of development of the technical base of understanding; (2) Status of development and availability of technology among the various alternatives; (3) Status and availability of the industrial infrastructure to support project design, equipment fabrication, facility construction, and process and program/project operation; (4) Adequacy of the design effort to provide a sound foundation to support execution of project; (5) Ability of the organization to fully integrate the system, and direct, manage, and control the execution of a complex major project

  15. Independent technical review, handbook

    Energy Technology Data Exchange (ETDEWEB)

    1994-02-01

    Purpose Provide an independent engineering review of the major projects being funded by the Department of Energy, Office of Environmental Restoration and Waste Management. The independent engineering review will address questions of whether the engineering practice is sufficiently developed to a point where a major project can be executed without significant technical problems. The independent review will focus on questions related to: (1) Adequacy of development of the technical base of understanding; (2) Status of development and availability of technology among the various alternatives; (3) Status and availability of the industrial infrastructure to support project design, equipment fabrication, facility construction, and process and program/project operation; (4) Adequacy of the design effort to provide a sound foundation to support execution of project; (5) Ability of the organization to fully integrate the system, and direct, manage, and control the execution of a complex major project.

  16. Independent Events in Elementary Probability Theory

    Science.gov (United States)

    Csenki, Attila

    2011-01-01

    In Probability and Statistics taught to mathematicians as a first introduction or to a non-mathematical audience, joint independence of events is introduced by requiring that the multiplication rule is satisfied. The following statement is usually tacitly assumed to hold (and, at best, intuitively motivated): If the n events E[subscript 1],…

  17. Signaling added response-independent reinforcement to assess Pavlovian processes in resistance to change and relapse.

    Science.gov (United States)

    Podlesnik, Christopher A; Fleet, James D

    2014-09-01

    Behavioral momentum theory asserts Pavlovian stimulus-reinforcer relations govern the persistence of operant behavior. Specifically, resistance to conditions of disruption (e.g., extinction, satiation) reflects the relation between discriminative stimuli and the prevailing reinforcement conditions. The present study assessed whether Pavlovian stimulus-reinforcer relations govern resistance to disruption in pigeons by arranging both response-dependent and -independent food reinforcers in two components of a multiple schedule. In one component, discrete-stimulus changes preceded response-independent reinforcers, paralleling methods that reduce Pavlovian conditioned responding to contextual stimuli. Compared to the control component with no added stimuli preceding response-independent reinforcement, response rates increased as discrete-stimulus duration increased (0, 5, 10, and 15 s) across conditions. Although resistance to extinction decreased as stimulus duration increased in the component with the added discrete stimulus, further tests revealed no effect of discrete stimuli, including other disrupters (presession food, intercomponent food, modified extinction) and reinstatement designed to control for generalization decrement. These findings call into question a straightforward conception that the stimulus-reinforcer relations governing resistance to disruption reflect the same processes as Pavlovian conditioning, as asserted by behavioral momentum theory. © Society for the Experimental Analysis of Behavior.

  18. The multiplicity dependence of inclusive pt spectra from p-p collisions at sqrt s = 200 GeV

    International Nuclear Information System (INIS)

    Adams, J.; Aggarwal, M.M.; Ahammed, Z.; Amonett, J.; Anderson, B.D.; Anderson, M.; Arkhipkin, D.; Averichev, G.S.; Bai, Y.; Balewski, J.; Barannikova, O.; Barnby, L.S.; Baudot, J.; Bekele, S.; Belaga, V.V.; Bellingeri-Laurikainen, A.; Bellwied, R.; Benedosso, F.; Bhardwaj, S.; Bhasin, A.; Bhati, A.K.; Bichsel, H.; Bielcik, J.; Bielcikova, J.; Bland, L.C.; Blyth, S.-L.; Bonner, B.E.; Botje, M.; Bouchet, J.; Brandin, A.V.; Bravar, A.; Bystersky, M.; Cadman, R.V.; Cai, X.Z.; Caines, H.; Calderonde la Barca Sanchez, M.; Castillo, J.; Catu, O.; Cebra, D.; Chajecki, Z.; Chaloupka, P.; Chattopadhyay, S.; Chen, H.F.; Chen, J.H.; Cheng, J.; Cherney, M.; Chikanian, A.; Christie, W.; Coffin, J.P.; Cormier, T.M.; Cosentino, M.R.; Cramer, J.G.; Crawford, H.J.; Das, D.; Das, S.; Daugherity, M.; de Moura, M.M.; Dedovich, T.G.; DePhillips, M.; Derevschikov, A.A.; Didenko, L.; Dietel, T.; Djawotho, P.; Dogra, S.M.; Dong, W.J.; Dong, X.; Draper, J.E.; Du, F.; Dunin, V.B.; Dunlop, J.C.; Dutta Mazumdar, M.R.; Eckardt, V.; Edwards, W.R.; Efimov, L.G.; Emelianov, V.; Engelage, J.; Eppley, G.; Erazmus, B.; Estienne, M.; Fachini, P.; Fatemi, R.; Fedorisin, J.; Filimonov, K.; Filip, P.; Finch, E.; Fine, V.; Fisyak, Y.; Fu, J.; Gagliardi, C.A.; Gaillard, L.; Ganti, M.S.; Ghazikhanian, V.; Ghosh, P.; Gonzalez, J.S.; Gorbunov, Y.G.; Gos, H.; Grebenyuk, O.; Grosnick, D.; Guertin, S.M.; Guimaraes, K.S.F.F.; Guo, Y.; Gupta, N.; Gutierrez, T.D.; Haag, B.; Hallman, T.J.; Hamed, A.; Harris, J.W.; He, W.; Heinz, M.; Henry, T.W.; Hepplemann, S.; Hippolyte, B.; Hirsch, A.; Hjort, E.; Hoffman, A.M.; Hoffmann, G.W.; Horner, M.J.; Huang, H.Z.; Huang, S.L.; Hughes, E.W.; Humanic, T.J.; Igo, G.; Jacobs, P.; Jacobs, W.W.; Jakl, P.; Jia, F.; Jiang, H.; Jones, P.G.; Judd, E.G.; Kabana, S.; Kang, K.; Kapitan, J.; Kaplan, M.; Keane, D.; Kechechyan, A.; Khodyrev, V.Yu.; Kim, B.C.; Kiryluk, J.; Kisiel, A.; Kislov, E.M.; Klein, S.R.; Kocoloski, A.; Koetke, D.D.; Kollegger, T.

    2006-01-01

    We report measurements of transverse momentum pt spectra for ten event multiplicity classes of p-p collisions at sqrt s = 200$ GeV. By analyzing the multiplicity dependence we find that the spectrum shape can be decomposed into a part with amplitude proportional to multiplicity and described by a Levy distribution on transverse mass mt, and a part with amplitude proportional to multiplicity squared and described by a gaussian distribution on transverse rapidity yt. The functional forms of the two parts are nearly independent of event multiplicity. The two parts can be identified with the soft and hard components of a two-component model of p-p collisions. This analysis then provides the first isolation of the hard component of the pt spectrum as a distribution of simple form on yt

  19. Initial Ada components evaluation

    Science.gov (United States)

    Moebes, Travis

    1989-01-01

    The SAIC has the responsibility for independent test and validation of the SSE. They have been using a mathematical functions library package implemented in Ada to test the SSE IV and V process. The library package consists of elementary mathematical functions and is both machine and accuracy independent. The SSE Ada components evaluation includes code complexity metrics based on Halstead's software science metrics and McCabe's measure of cyclomatic complexity. Halstead's metrics are based on the number of operators and operands on a logical unit of code and are compiled from the number of distinct operators, distinct operands, and total number of occurrences of operators and operands. These metrics give an indication of the physical size of a program in terms of operators and operands and are used diagnostically to point to potential problems. McCabe's Cyclomatic Complexity Metrics (CCM) are compiled from flow charts transformed to equivalent directed graphs. The CCM is a measure of the total number of linearly independent paths through the code's control structure. These metrics were computed for the Ada mathematical functions library using Software Automated Verification and Validation (SAVVAS), the SSE IV and V tool. A table with selected results was shown, indicating that most of these routines are of good quality. Thresholds for the Halstead measures indicate poor quality if the length metric exceeds 260 or difficulty is greater than 190. The McCabe CCM indicated a high quality of software products.

  20. Model-Independent Diffs

    DEFF Research Database (Denmark)

    Könemann, Patrick

    just contain a list of strings, one for each line, whereas the structure of models is defined by their meta models. There are tools available which are able to compute the diff between two models, e.g. RSA or EMF Compare. However, their diff is not model-independent, i.e. it refers to the models...

  1. All Those Independent Variables.

    Science.gov (United States)

    Meacham, Merle L.

    This paper presents a case study of a sixth grade remedial math class which illustrates the thesis that only the "experimental attitude," not the "experimental method," is appropriate in the classroom. The thesis is based on the fact that too many independent variables exist in a classroom situation to allow precise measurement. The case study…

  2. Independent safety organization

    International Nuclear Information System (INIS)

    Kato, W.Y.; Weinstock, E.V.; Carew, J.F.; Cerbone, R.J.; Guppy, J.G.; Hall, R.E.; Taylor, J.H.

    1985-01-01

    Brookhaven National Laboratory has conducted a study on the need and feasibility of an independent organization to investigate significant safety events for the Office for Analysis and Evaluation of Operational Data, USNRC. The study consists of three parts: the need for an