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...

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)

Color Independent Components Based SIFT Descriptors for Object/Scene Classification

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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.

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...

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

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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.

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

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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.

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

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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.

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.

Separating complex compound patient motion tracking data using independent component analysis

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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.

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

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...

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...

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.

Selection of independent components based on cortical mapping of electromagnetic activity

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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.

Extraction of Independent Structural Images for Principal Component Thermography

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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.

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

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)

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.

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....

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)

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).

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

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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.

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.

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

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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

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...

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.

Constrained independent component analysis approach to nonobtrusive pulse rate measurements

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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.

Representation for dialect recognition using topographic independent component analysis

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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.

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)

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

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.

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.

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.)

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

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.

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.

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.

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.

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...

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.

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....

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.

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

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

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.

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

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...

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.

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.

[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.

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.

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.

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.

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.

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.

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...

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...

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.

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.

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)

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...

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...

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.

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

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

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...

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.

Opening A New Independent Pharmacy 101

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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

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

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

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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.

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...

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.

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.

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)

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

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

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.

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

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.

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.

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.

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.

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.

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.

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.

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...

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.

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

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

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.

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.

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

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.

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

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.

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.

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.

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

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

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 ...

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...

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...

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...

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.

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)

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...

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.

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.

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...

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

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

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.)

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.

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.

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

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.

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.

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.

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.

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

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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.

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

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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.

Independent component processes underlying emotions during natural music listening.

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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.

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

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...

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

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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

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....

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.

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

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

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

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).

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.

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.

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.

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.

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.

Contrast and autoshaping in multiple schedules varying reinforcer rate and duration.

Science.gov (United States)

Hamilton, B E; Silberberg, A

1978-07-01

Thirteen master pigeons were exposed to multiple schedules in which reinforcement frequency (Experiment I) or duration (Experiment II) was varied. In Phases 1 and 3 of Experiment I, the values of the first and second components' random-interval schedules were 33 and 99 seconds, respectively. In Phase 2, these values were 99 seconds for both components. In Experiment II, a random-interval 33-second schedule was associated with each component. During Phases 1 and 3, the first and second components had hopper durations of 7.5 and 2.5 seconds respectively. During Phase 2, both components' hopper durations were 2.5 seconds. In each experiment, positive contrast obtained for about half the master subjects. The rest showed a rate increase in both components (positive induction). Each master subject's key colors and reinforcers were synchronously presented on a response-independent basis to a yoked control. Richer component key-pecking occurred during each experiment's Phases 1 and 3 among half these subjects. However, none responded during the contrast condition (unchanged component of each experiment's Phase 2). From this it is inferred that autoshaping did not contribute to the contrast and induction findings among master birds. Little evidence of local contrast (highest rate at beginning of richer component) was found in any subject. These data show that (a) contrast can occur independently from autoshaping, (b) contrast assays during equal-valued components may produce induction, (c) local contrast in multiple schedules often does not occur, and (d) differential hopper durations can produce autoshaping and contrast.

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)

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

Signaling added response-independent reinforcement to assess Pavlovian processes in resistance to change and relapse.

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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.

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.

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

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

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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.

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.

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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.

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

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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.

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

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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.

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

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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

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

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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.

Principal component analysis reveals gender-specific predictors of cardiometabolic risk in 6th graders

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Peterson Mark D

2012-11-01

Full Text Available Abstract Background The purpose of this study was to determine the sex-specific pattern of pediatric cardiometabolic risk with principal component analysis, using several biological, behavioral and parental variables in a large cohort (n = 2866 of 6th grade students. Methods Cardiometabolic risk components included waist circumference, fasting glucose, blood pressure, plasma triglycerides levels and HDL-cholesterol. Principal components analysis was used to determine the pattern of risk clustering and to derive a continuous aggregate score (MetScore. Stratified risk components and MetScore were analyzed for association with age, body mass index (BMI, cardiorespiratory fitness (CRF, physical activity (PA, and parental factors. Results In both boys and girls, BMI and CRF were associated with multiple risk components, and overall MetScore. Maternal smoking was associated with multiple risk components in girls and boys, as well as MetScore in boys, even after controlling for children’s BMI. Paternal family history of early cardiovascular disease (CVD and parental age were associated with increased blood pressure and MetScore for girls. Children’s PA levels, maternal history of early CVD, and paternal BMI were also indicative for various risk components, but not MetScore. Conclusions Several biological and behavioral factors were independently associated with children’s cardiometabolic disease risk, and thus represent a unique gender-specific risk profile. These data serve to bolster the independent contribution of CRF, PA, and family-oriented healthy lifestyles for improving children’s health.

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

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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.

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

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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

How multiple causes combine: independence constraints on causal inference.

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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.

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

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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

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

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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.

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

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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.

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

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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.

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

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

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.

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.

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

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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.

Simultaneous quantification of multiple components in rat plasma by UPLC-MS/MS and pharmacokinetic study after oral administration of Huangqi decoction.

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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.

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/.

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

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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.

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

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.

Competing failure analysis in phased-mission systems with multiple functional dependence groups

International Nuclear Information System (INIS)

Wang, Chaonan; Xing, Liudong; Peng, Rui; Pan, Zhusheng

2017-01-01

A phased-mission system (PMS) involves multiple, consecutive, non-overlapping phases of operation. The system structure function and component failure behavior in a PMS can change from phase to phase, posing big challenges to the system reliability analysis. Further complicating the problem is the functional dependence (FDEP) behavior where the failure of certain component(s) causes other component(s) to become unusable or inaccessible or isolated. Previous studies have shown that FDEP can cause competitions between failure propagation and failure isolation in the time domain. While such competing failure effects have been well addressed in single-phase systems, only little work has focused on PMSs with a restrictive assumption that a single FDEP group exists in one phase of the mission. Many practical systems (e.g., computer systems and networks), however may involve multiple FDEP groups during the mission. Moreover, different FDEP groups can be dependent due to sharing some common components; they may appear in a single phase or multiple phases. This paper makes new contributions by modeling and analyzing reliability of PMSs subject to multiple FDEP groups through a Markov chain-based methodology. Propagated failures with both global and selective effects are considered. Four case studies are presented to demonstrate application of the proposed method. - Highlights: • Reliability of phased-mission systems subject to competing failure propagation and isolation effects is modeled. • Multiple independent or dependent functional dependence groups are considered. • Propagated failures with global effects and selective effects are studied. • Four case studies demonstrate generality and application of the proposed Markov-based method.

Antimicrobial combinations: Bliss independence and Loewe additivity derived from mechanistic multi-hit models

Science.gov (United States)

Yu, Guozhi; Hozé, Nathanaël; Rolff, Jens

2016-01-01

Antimicrobial peptides (AMPs) and antibiotics reduce the net growth rate of bacterial populations they target. It is relevant to understand if effects of multiple antimicrobials are synergistic or antagonistic, in particular for AMP responses, because naturally occurring responses involve multiple AMPs. There are several competing proposals describing how multiple types of antimicrobials add up when applied in combination, such as Loewe additivity or Bliss independence. These additivity terms are defined ad hoc from abstract principles explaining the supposed interaction between the antimicrobials. Here, we link these ad hoc combination terms to a mathematical model that represents the dynamics of antimicrobial molecules hitting targets on bacterial cells. In this multi-hit model, bacteria are killed when a certain number of targets are hit by antimicrobials. Using this bottom-up approach reveals that Bliss independence should be the model of choice if no interaction between antimicrobial molecules is expected. Loewe additivity, on the other hand, describes scenarios in which antimicrobials affect the same components of the cell, i.e. are not acting independently. While our approach idealizes the dynamics of antimicrobials, it provides a conceptual underpinning of the additivity terms. The choice of the additivity term is essential to determine synergy or antagonism of antimicrobials. This article is part of the themed issue ‘Evolutionary ecology of arthropod antimicrobial peptides’. PMID:27160596

Antimicrobial combinations: Bliss independence and Loewe additivity derived from mechanistic multi-hit models.

Science.gov (United States)

Baeder, Desiree Y; Yu, Guozhi; Hozé, Nathanaël; Rolff, Jens; Regoes, Roland R

2016-05-26

Antimicrobial peptides (AMPs) and antibiotics reduce the net growth rate of bacterial populations they target. It is relevant to understand if effects of multiple antimicrobials are synergistic or antagonistic, in particular for AMP responses, because naturally occurring responses involve multiple AMPs. There are several competing proposals describing how multiple types of antimicrobials add up when applied in combination, such as Loewe additivity or Bliss independence. These additivity terms are defined ad hoc from abstract principles explaining the supposed interaction between the antimicrobials. Here, we link these ad hoc combination terms to a mathematical model that represents the dynamics of antimicrobial molecules hitting targets on bacterial cells. In this multi-hit model, bacteria are killed when a certain number of targets are hit by antimicrobials. Using this bottom-up approach reveals that Bliss independence should be the model of choice if no interaction between antimicrobial molecules is expected. Loewe additivity, on the other hand, describes scenarios in which antimicrobials affect the same components of the cell, i.e. are not acting independently. While our approach idealizes the dynamics of antimicrobials, it provides a conceptual underpinning of the additivity terms. The choice of the additivity term is essential to determine synergy or antagonism of antimicrobials.This article is part of the themed issue 'Evolutionary ecology of arthropod antimicrobial peptides'. © 2016 The Author(s).

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.

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

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.

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.

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.

Task-related component analysis for functional neuroimaging and application to near-infrared spectroscopy data.

Science.gov (United States)

Tanaka, Hirokazu; Katura, Takusige; Sato, Hiroki

2013-01-01

Reproducibility of experimental results lies at the heart of scientific disciplines. Here we propose a signal processing method that extracts task-related components by maximizing the reproducibility during task periods from neuroimaging data. Unlike hypothesis-driven methods such as general linear models, no specific time courses are presumed, and unlike data-driven approaches such as independent component analysis, no arbitrary interpretation of components is needed. Task-related components are constructed by a linear, weighted sum of multiple time courses, and its weights are optimized so as to maximize inter-block correlations (CorrMax) or covariances (CovMax). Our analysis method is referred to as task-related component analysis (TRCA). The covariance maximization is formulated as a Rayleigh-Ritz eigenvalue problem, and corresponding eigenvectors give candidates of task-related components. In addition, a systematic statistical test based on eigenvalues is proposed, so task-related and -unrelated components are classified objectively and automatically. The proposed test of statistical significance is found to be independent of the degree of autocorrelation in data if the task duration is sufficiently longer than the temporal scale of autocorrelation, so TRCA can be applied to data with autocorrelation without any modification. We demonstrate that simple extensions of TRCA can provide most distinctive signals for two tasks and can integrate multiple modalities of information to remove task-unrelated artifacts. TRCA was successfully applied to synthetic data as well as near-infrared spectroscopy (NIRS) data of finger tapping. There were two statistically significant task-related components; one was a hemodynamic response, and another was a piece-wise linear time course. In summary, we conclude that TRCA has a wide range of applications in multi-channel biophysical and behavioral measurements. Copyright © 2012 Elsevier Inc. All rights reserved.

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...

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.

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

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...

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.

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.

Classification of Single and Multiple Disturbances in Electric Signals

Directory of Open Access Journals (Sweden)

Ribeiro Moisés Vidal

2007-01-01

Full Text Available This paper discusses and presents a different perspective for classifying single and multiple disturbances in electric signals, such as voltage and current ones. Basically, the principle of divide to conquer is applied to decompose the electric signals into what we call primitive signals or components from which primitive patterns can be independently recognized. A technique based on such concept is introduced to demonstrate the effectiveness of such idea. This technique decomposes the electric signals into three main primitive components. In each primitive component, few high-order-statistics- (HOS- based features are extracted. Then, Bayes' theory-based techniques are applied to verify the ocurrence or not of single or multiple disturbances in the electric signals. The performance analysis carried out on a large number of data indicates that the proposed technique outperforms the performance attained by the technique introduced by He and Starzyk. Additionally, the numerical results verify that the proposed technique is capable of offering interesting results when it is applied to classify several sets of disturbances if one cycle of the main frequency is considered, at least.

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.

Endocytic crosstalk: cavins, caveolins, and caveolae regulate clathrin-independent endocytosis.

Directory of Open Access Journals (Sweden)

Natasha Chaudhary

2014-04-01

Full Text Available Several studies have suggested crosstalk between different clathrin-independent endocytic pathways. However, the molecular mechanisms and functional relevance of these interactions are unclear. Caveolins and cavins are crucial components of caveolae, specialized microdomains that also constitute an endocytic route. Here we show that specific caveolar proteins are independently acting negative regulators of clathrin-independent endocytosis. Cavin-1 and Cavin-3, but not Cavin-2 or Cavin-4, are potent inhibitors of the clathrin-independent carriers/GPI-AP enriched early endosomal compartment (CLIC/GEEC endocytic pathway, in a process independent of caveola formation. Caveolin-1 (CAV1 and CAV3 also inhibit the CLIC/GEEC pathway upon over-expression. Expression of caveolar protein leads to reduction in formation of early CLIC/GEEC carriers, as detected by quantitative electron microscopy analysis. Furthermore, the CLIC/GEEC pathway is upregulated in cells lacking CAV1/Cavin-1 or with reduced expression of Cavin-1 and Cavin-3. Inhibition by caveolins can be mimicked by the isolated caveolin scaffolding domain and is associated with perturbed diffusion of lipid microdomain components, as revealed by fluorescence recovery after photobleaching (FRAP studies. In the absence of cavins (and caveolae CAV1 is itself endocytosed preferentially through the CLIC/GEEC pathway, but the pathway loses polarization and sorting attributes with consequences for membrane dynamics and endocytic polarization in migrating cells and adult muscle tissue. We also found that noncaveolar Cavin-1 can act as a modulator for the activity of the key regulator of the CLIC/GEEC pathway, Cdc42. This work provides new insights into the regulation of noncaveolar clathrin-independent endocytosis by specific caveolar proteins, illustrating multiple levels of crosstalk between these pathways. We show for the first time a role for specific cavins in regulating the CLIC/GEEC pathway, provide

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.

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.

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.

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

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

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.

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.

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.

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.

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.

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.

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

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...

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...

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.

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.

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.

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

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.

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

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

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.

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.

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.

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

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

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

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

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.

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.

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....

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...

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.

Techniques to extract physical modes in model-independent analysis of rings

International Nuclear Information System (INIS)

Wang, C.-X.

2004-01-01

A basic goal of Model-Independent Analysis is to extract the physical modes underlying the beam histories collected at a large number of beam position monitors so that beam dynamics and machine properties can be deduced independent of specific machine models. Here we discuss techniques to achieve this goal, especially the Principal Component Analysis and the Independent Component Analysis.

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.

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

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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.

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.

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.

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...

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

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)

Reliability for systems of degrading components with distinct component shock sets

International Nuclear Information System (INIS)

Song, Sanling; Coit, David W.; Feng, Qianmei

2014-01-01

This paper studies reliability for multi-component systems subject to dependent competing risks of degradation wear and random shocks, with distinct shock sets. In practice, many systems are exposed to distinct and different types of shocks that can be categorized according to their sizes, function, affected components, etc. Previous research primarily focuses on simple systems with independent failure processes, systems with independent component time-to-failure, or components that share the same shock set or type of shocks. In our new model, we classify random shocks into different sets based on their sizes or function. Shocks with specific sizes or function can selectively affect one or more components in the system but not necessarily all components. Additionally the shocks from the different shock sets can arrive at different rates and have different relative magnitudes. Preventive maintenance (PM) optimization is conducted for the system with different component shock sets. Decision variables for two different maintenance scheduling problems, the PM replacement time interval, and the PM inspection time interval, are determined by minimizing a defined system cost rate. Sensitivity analysis is performed to provide insight into the behavior of the proposed maintenance policies. These models can be applied directly or customized for many complex systems that experience dependent competing failure processes with different component shock sets. A MEMS (Micro-electro mechanical systems) oscillator is a typical system subject to dependent and competing failure processes, and it is used as a numerical example to illustrate our new reliability and maintenance models

Genetic variants and multiple myeloma risk

DEFF Research Database (Denmark)

Martino, Alessandro; Campa, Daniele; Jurczyszyn, Artur

2014-01-01

BACKGROUND: Genetic background plays a role in multiple myeloma susceptibility. Several single-nucleotide polymorphisms (SNP) associated with genetic susceptibility to multiple myeloma were identified in the last years, but only a few of them were validated in independent studies. METHODS...... with multiple myeloma risk (P value range, 0.055-0.981), possibly with the exception of the SNP rs2227667 (SERPINE1) in women. CONCLUSIONS: We can exclude that the selected polymorphisms are major multiple myeloma risk factors. IMPACT: Independent validation studies are crucial to identify true genetic risk...

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.

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.

A composite measure to explore visual disability in primary progressive multiple sclerosis.

Science.gov (United States)

Poretto, Valentina; Petracca, Maria; Saiote, Catarina; Mormina, Enricomaria; Howard, Jonathan; Miller, Aaron; Lublin, Fred D; Inglese, Matilde

2017-01-01

Optical coherence tomography (OCT) and magnetic resonance imaging (MRI) can provide complementary information on visual system damage in multiple sclerosis (MS). The objective of this paper is to determine whether a composite OCT/MRI score, reflecting cumulative damage along the entire visual pathway, can predict visual deficits in primary progressive multiple sclerosis (PPMS). Twenty-five PPMS patients and 20 age-matched controls underwent neuro-ophthalmologic evaluation, spectral-domain OCT, and 3T brain MRI. Differences between groups were assessed by univariate general linear model and principal component analysis (PCA) grouped instrumental variables into main components. Linear regression analysis was used to assess the relationship between low-contrast visual acuity (LCVA), OCT/MRI-derived metrics and PCA-derived composite scores. PCA identified four main components explaining 80.69% of data variance. Considering each variable independently, LCVA 1.25% was significantly predicted by ganglion cell-inner plexiform layer (GCIPL) thickness, thalamic volume and optic radiation (OR) lesion volume (adjusted R 2 0.328, p  = 0.00004; adjusted R 2 0.187, p  = 0.002 and adjusted R 2 0.180, p  = 0.002). The PCA composite score of global visual pathway damage independently predicted both LCVA 1.25% (adjusted R 2 value 0.361, p  = 0.00001) and LCVA 2.50% (adjusted R 2 value 0.323, p  = 0.00003). A multiparametric score represents a more comprehensive and effective tool to explain visual disability than a single instrumental metric in PPMS.

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

Detection of independent functional networks during music listening using electroencephalogram and sLORETA-ICA.

Science.gov (United States)

Jäncke, Lutz; Alahmadi, Nsreen

2016-04-13

The measurement of brain activation during music listening is a topic that is attracting increased attention from many researchers. Because of their high spatial accuracy, functional MRI measurements are often used for measuring brain activation in the context of music listening. However, this technique faces the issues of contaminating scanner noise and an uncomfortable experimental environment. Electroencephalogram (EEG), however, is a neural registration technique that allows the measurement of neurophysiological activation in silent and more comfortable experimental environments. Thus, it is optimal for recording brain activations during pleasant music stimulation. Using a new mathematical approach to calculate intracortical independent components (sLORETA-IC) on the basis of scalp-recorded EEG, we identified specific intracortical independent components during listening of a musical piece and scales, which differ substantially from intracortical independent components calculated from the resting state EEG. Most intracortical independent components are located bilaterally in perisylvian brain areas known to be involved in auditory processing and specifically in music perception. Some intracortical independent components differ between the music and scale listening conditions. The most prominent difference is found in the anterior part of the perisylvian brain region, with stronger activations seen in the left-sided anterior perisylvian regions during music listening, most likely indicating semantic processing during music listening. A further finding is that the intracortical independent components obtained for the music and scale listening are most prominent in higher frequency bands (e.g. beta-2 and beta-3), whereas the resting state intracortical independent components are active in lower frequency bands (alpha-1 and theta). This new technique for calculating intracortical independent components is able to differentiate independent neural networks associated

Sandia_HighTemperatureComponentEvaluation_2015

Energy Technology Data Exchange (ETDEWEB)

Cashion, Avery T. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)

2015-03-01

The objective of this project is to perform independent evaluation of high temperature components to determine their suitability for use in high temperature geothermal tools. Development of high temperature components has been increasing rapidly due to demand from the high temperature oil and gas exploration and aerospace industries. Many of these new components are at the late prototype or first production stage of development and could benefit from third party evaluation of functionality and lifetime at elevated temperatures. In addition to independent testing of new components, this project recognizes that there is a paucity of commercial-off-the-shelf COTS components rated for geothermal temperatures. As such, high-temperature circuit designers often must dedicate considerable time and resources to determine if a component exists that they may be able to knead performance out of to meet their requirements. This project aids tool developers by characterization of select COTS component performances beyond published temperature specifications. The process for selecting components includes public announcements of project intent (e.g., FedBizOps), direct discussions with candidate manufacturers,and coordination with other DOE funded programs.

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.

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.

Characterizing speed-independence of high-level designs

DEFF Research Database (Denmark)

Kishinevsky, Michael; Staunstrup, Jørgen

1994-01-01

This paper characterizes the speed-independence of high-level designs. The characterization is a condition on the design description ensuring that the behavior of the design is independent of the speeds of its components. The behavior of a circuit is modeled as a transition system, that allows data...... types, and internal as well as external non-determinism. This makes it possible to verify the speed-independence of a design without providing an explicit realization of the environment. The verification can be done mechanically. A number of experimental designs have been verified including a speed-independent...

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.

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).

A high-pressure thermal gradient block for investigating microbial activity in multiple deep-sea samples

DEFF Research Database (Denmark)

Kallmeyer, J.; Ferdelman, TG; Jansen, KH

2003-01-01

Details about the construction and use of a high-pressure thermal gradient block for the simultaneous incubation of multiple samples are presented. Most parts used are moderately priced off-the-shelf components that easily obtainable. In order to keep the pressure independent of thermal expansion....... Sulfate reduction rates increase with increasing pressure and show maximum values at pressures higher than in situ. (C) 2003 Elsevier Science B.V. All rights reserved....

Local multiplicative Schwarz algorithms for convection-diffusion equations

Science.gov (United States)

Cai, Xiao-Chuan; Sarkis, Marcus

1995-01-01

We develop a new class of overlapping Schwarz type algorithms for solving scalar convection-diffusion equations discretized by finite element or finite difference methods. The preconditioners consist of two components, namely, the usual two-level additive Schwarz preconditioner and the sum of some quadratic terms constructed by using products of ordered neighboring subdomain preconditioners. The ordering of the subdomain preconditioners is determined by considering the direction of the flow. We prove that the algorithms are optimal in the sense that the convergence rates are independent of the mesh size, as well as the number of subdomains. We show by numerical examples that the new algorithms are less sensitive to the direction of the flow than either the classical multiplicative Schwarz algorithms, and converge faster than the additive Schwarz algorithms. Thus, the new algorithms are more suitable for fluid flow applications than the classical additive or multiplicative Schwarz algorithms.

History-independent cyclic response of nanotwinned metals

Science.gov (United States)

Pan, Qingsong; Zhou, Haofei; Lu, Qiuhong; Gao, Huajian; Lu, Lei

2017-11-01

Nearly 90 per cent of service failures of metallic components and structures are caused by fatigue at cyclic stress amplitudes much lower than the tensile strength of the materials involved. Metals typically suffer from large amounts of cumulative, irreversible damage to microstructure during cyclic deformation, leading to cyclic responses that are unstable (hardening or softening) and history-dependent. Existing rules for fatigue life prediction, such as the linear cumulative damage rule, cannot account for the effect of loading history, and engineering components are often loaded by complex cyclic stresses with variable amplitudes, mean values and frequencies, such as aircraft wings in turbulent air. It is therefore usually extremely challenging to predict cyclic behaviour and fatigue life under a realistic load spectrum. Here, through both atomistic simulations and variable-strain-amplitude cyclic loading experiments at stress amplitudes lower than the tensile strength of the metal, we report a history-independent and stable cyclic response in bulk copper samples that contain highly oriented nanoscale twins. We demonstrate that this unusual cyclic behaviour is governed by a type of correlated ‘necklace’ dislocation consisting of multiple short component dislocations in adjacent twins, connected like the links of a necklace. Such dislocations are formed in the highly oriented nanotwinned structure under cyclic loading and help to maintain the stability of twin boundaries and the reversible damage, provided that the nanotwins are tilted within about 15 degrees of the loading axis. This cyclic deformation mechanism is distinct from the conventional strain localizing mechanisms associated with irreversible microstructural damage in single-crystal, coarse-grained, ultrafine-grained and nanograined metals.

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.

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.

Relationship between theory of mind and functional independence is mediated by executive function.

Science.gov (United States)

Ahmed, Fayeza S; Miller, L Stephen

2013-06-01

Theory of mind (ToM) is the ability to comprehend another person's perspective. Although there is much literature of ToM in children, there is a limited and somewhat inconclusive amount of studies examining ToM in a geriatric population. This study examined ToM's relationship to functional independence. Two tests of ToM, tests of executive function, and a measure of functional ability were administered to cognitively intact older adults. Results showed that 1 test of ToM (Strange Stories test) significantly accounted for variance in functional ability, whereas the other did not (Faux Pas test). In addition, Strange Stories test performance was partially driven by a verbal abstraction-based executive function: proverb interpretation. A multiple mediation model was employed to examine whether executive functions explained the relationship between the Strange Stories test and functional ability. Results showed that both the combined and individual indirect effects of the executive function measures mediated the relationship. We argue that, although components of ToM are associated with functional independence, ToM does not appear to account for additional variance in functional independence beyond executive function measures. PsycINFO Database Record (c) 2013 APA, all rights reserved.

A quasi-independence model to estimate failure rates

International Nuclear Information System (INIS)

Colombo, A.G.

1988-01-01

The use of a quasi-independence model to estimate failure rates is investigated. Gate valves of nuclear plants are considered, and two qualitative covariates are taken into account: plant location and reactor system. Independence between the two covariates and an exponential failure model are assumed. The failure rate of the components of a given system and plant is assumed to be a constant, but it may vary from one system to another and from one plant to another. This leads to the analysis of a contingency table. A particular feature of the model is the different operating time of the components in the various cells which can also be equal to zero. The concept of independence of the covariates is then replaced by that of quasi-independence. The latter definition, however, is used in a broader sense than usual. Suitable statistical tests are discussed and a numerical example illustrates the use of the method. (author)

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

Sensitization to minor cat allergen components is associated with type-2 biomarkers in young asthmatics.

Science.gov (United States)

Tsolakis, N; Malinovschi, A; Nordvall, L; Mattsson, L; Lidholm, J; Pedroletti, C; Janson, C; Borres, M P; Alving, K

2018-03-25

Cat allergy is a major trigger of asthma world-wide. Molecular patterns of cat sensitization vary between individuals, but their relationship to inflammation in asthmatics has not been extensively studied. To investigate the prevalence and levels of IgE antibodies against different cat allergen components and their relationship to type-2 inflammation and total IgE among young asthmatic subjects sensitized to furry animals. Patients with asthma (age 10-35 years; n = 266) and IgE sensitization to cat, dog or horse extract (ImmunoCAP), were analysed for IgE to the cat allergen components Fel d 1 (secretoglobin), Fel d 2 (serum albumin), Fel d 4 and Fel d 7 (lipocalins). Independent associations between IgE-antibody concentrations, and fraction of exhaled nitric oxide (FeNO), blood eosinophil (B-Eos) count, and total IgE were analysed by multiple linear regression after adjustment for possible confounders. The level of IgE against Fel d 2 was independently related to FeNO (P = .012) and total IgE (P < .001), and IgE against Fel d 4 associated with Β-Eos count (P = .009) and total IgE (P < .001). IgE antibodies against Fel d 1 or cat extract did not independently relate to these inflammatory markers (P = .23-.51). Levels of IgE to lipocalin (Fel d 4) and serum albumin (Fel d 2), but not to secretoglobin (Fel d 1) or cat extract, were independently associated with type-2 biomarkers and total IgE in young asthmatics. We suggest that measurement of IgE to minor cat allergen components may be useful when investigating asthma morbidity in cat allergic subjects. © 2018 John Wiley & Sons Ltd.

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

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

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...

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

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.

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.

What Klein’s semantic gradient does and does not really show: decomposing Stroop interference into task and informational conflict components

Directory of Open Access Journals (Sweden)

Yulia eLevin

2016-02-01

Full Text Available The present study suggests that the idea that Stroop interference originates from multiple components may gain theoretically from integrating two independent frameworks. The first framework is represented by the well-known notion of semantic gradient of interference and the second one is the distinction between two types of conflict – the task and the informational conflict – giving rise to the interference (Goldfarb & Henik, 2007; McLeod & MacDonald, 2000. The proposed integration led to the conclusion that two (i.e., orthographic and lexical components of the four theoretically distinct components represent task conflict, and the other two (i.e., indirect and direct informational conflict components represent informational conflict. The four components were independently estimated in a series of experiments. The results confirmed the contribution of task conflict (estimated by a robust orthographic component and of informational conflict (estimated by a strong direct informational conflict component to Stroop interference. However, the performed critical review of the relevant literature (see General Discussion, as well as the results of the experiments reported, showed that the other two components expressing each type of conflict (i.e., the lexical component of task conflict and the indirect informational conflict were small, and unstable. The present analysis refines our knowledge of the origins of Stroop interference by providing evidence that each type of conflict has its major and minor contributions. The implications for cognitive control of an automatic reading process are also discussed.

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.

Reliability prediction of engineering systems with competing failure modes due to component degradation

International Nuclear Information System (INIS)

Son, Young Kap

2011-01-01

Reliability of an engineering system depends on two reliability metrics: the mechanical reliability, considering component failures, that a functional system topology is maintained and the performance reliability of adequate system performance in each functional configuration. Component degradation explains not only the component aging processes leading to failure in function, but also system performance change over time. Multiple competing failure modes for systems with degrading components in terms of system functionality and system performance are considered in this paper with the assumption that system functionality is not independent of system performance. To reduce errors in system reliability prediction, this paper tries to extend system performance reliability prediction methods in open literature through combining system mechanical reliability from component reliabilities and system performance reliability. The extended reliability prediction method provides a useful way to compare designs as well as to determine effective maintenance policy for efficient reliability growth. Application of the method to an electro-mechanical system, as an illustrative example, is explained in detail, and the prediction results are discussed. Both mechanical reliability and performance reliability are compared to total system reliability in terms of reliability prediction errors

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

Identification of chemical components of combustion emissions that affect pro-atherosclerotic vascular responses in mice.

Science.gov (United States)

Seilkop, Steven K; Campen, Matthew J; Lund, Amie K; McDonald, Jacob D; Mauderly, Joe L

2012-04-01

Combustion emissions cause pro-atherosclerotic responses in apolipoprotein E-deficient (ApoE/⁻) mice, but the causal components of these complex mixtures are unresolved. In studies previously reported, ApoE⁻/⁻ mice were exposed by inhalation 6 h/day for 50 consecutive days to multiple dilutions of diesel or gasoline exhaust, wood smoke, or simulated "downwind" coal emissions. In this study, the analysis of the combined four-study database using the Multiple Additive Regression Trees (MART) data mining approach to determine putative causal exposure components regardless of combustion source is reported. Over 700 physical-chemical components were grouped into 45 predictor variables. Response variables measured in aorta included endothelin-1, vascular endothelin growth factor, three matrix metalloproteinases (3, 7, 9), metalloproteinase inhibitor 2, heme-oxygenase-1, and thiobarbituric acid reactive substances. Two or three predictors typically explained most of the variation in response among the experimental groups. Overall, sulfur dioxide, ammonia, nitrogen oxides, and carbon monoxide were most highly predictive of responses, although their rankings differed among the responses. Consistent with the earlier finding that filtration of particles had little effect on responses, particulate components ranked third to seventh in predictive importance for the eight response variables. MART proved useful for identifying putative causal components, although the small number of pollution mixtures (4) can provide only suggestive evidence of causality. The potential independent causal contributions of these gases to the vascular responses, as well as possible interactions among them and other components of complex pollutant mixtures, warrant further evaluation.

[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.

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

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.

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.

Gray Matter Is Targeted in First-Attack Multiple Sclerosis

Energy Technology Data Exchange (ETDEWEB)

Schutzer, Steven E.; Angel, Thomas E.; Liu, Tao; Schepmoes, Athena A.; Xie, Fang; Bergquist, Jonas P.; Vecsei, Lazlo' ; Zadori, Denes; Camp, David G.; Holland, Bart K.; Smith, Richard D.; Coyle, Patricia K.

2013-09-10

The cause of multiple sclerosis (MS), its driving pathogenesis at the earliest stages, and what factors allow the first clinical attack to manifest remain unknown. Some imaging studies suggest gray rather than white matter may be involved early, and some postulate this may be predictive of developing MS. Other imaging studies are in conflict. To determine if there was objective molecular evidence of gray matter involvement in early MS we used high-resolution mass spectrometry to identify proteins in the cerebrospinal fluid (CSF) of first-attack MS patients (two independent groups) compared to established relapsing remitting (RR) MS and controls. We found that the CSF proteins in first-attack patients were differentially enriched for gray matter components (axon, neuron, synapse). Myelin components did not distinguish these groups. The results support that gray matter dysfunction is involved early in MS, and also may be integral for the initial clinical presentation.

Systems with randomly failing repairable components

DEFF Research Database (Denmark)

Der Kiureghian, Armen; Ditlevsen, Ove Dalager; Song, Junho

2005-01-01

Closed-form expressions are derived for the steady-state availability, mean rate of failure, mean duration of downtime and reliability of a general system with randomly and independently failing repairable components. Component failures are assumed to be homogeneous Poisson events in time and rep...

On Utmost Multiplicity of Hierarchical Stellar Systems

Directory of Open Access Journals (Sweden)

Gebrehiwot Y. M.

2016-12-01

Full Text Available According to theoretical considerations, multiplicity of hierarchical stellar systems can reach, depending on masses and orbital parameters, several hundred, while observational data confirm the existence of at most septuple (seven-component systems. In this study, we cross-match the stellar systems of very high multiplicity (six and more components in modern catalogues of visual double and multiple stars to find among them the candidates to hierarchical systems. After cross-matching the catalogues of closer binaries (eclipsing, spectroscopic, etc., some of their components were found to be binary/multiple themselves, what increases the system's degree of multiplicity. Optical pairs, known from literature or filtered by the authors, were flagged and excluded from the statistics. We compiled a list of hierarchical systems with potentially very high multiplicity that contains ten objects. Their multiplicity does not exceed 12, and we discuss a number of ways to explain the lack of extremely high multiplicity systems.

Sexting Coercion as a Component of Intimate Partner Polyvictimization.

Science.gov (United States)

Ross, Jody M; Drouin, Michelle; Coupe, Amanda

2016-07-01

We examined the role of sexting coercion as a component of the intimate partner abuse (IPA) construct among young adults to determine whether sexting coercion would emerge alongside other forms of partner aggression as a cumulative risk factor for psychological, sexual, and attachment problems. In a sample of 885 undergraduates (301 men and 584 women), 40% had experienced some type of coercion. Although there was some overlap between sexual coercion and sexting coercion (21% of participants had experienced both), some individuals had experienced only sexting coercion (8%) and some only sexual coercion (11%). Women were more likely than men to be coerced into sexting. Both sexting coercion and sexual coercion were significantly and independently related to negative mental health symptoms, sexual problems, and attachment dysfunction, and, notably, sexting coercion was found to be a cumulative risk factor for nearly all of these negative effects. These data support the idea that digital sexual victimization is a new component of IPA polyvictimization, potentially increasing the negative effects experienced by victims of multiple forms of partner aggression.

Association of objectively measured physical activity with body components in European adolescents.

Science.gov (United States)

Jiménez-Pavón, David; Fernández-Vázquez, Amaya; Alexy, Ute; Pedrero, Raquel; Cuenca-García, Magdalena; Polito, Angela; Vanhelst, Jérémy; Manios, Yannis; Kafatos, Anthony; Molnar, Dénes; Sjöström, Michael; Moreno, Luis A

2013-07-18

Physical activity (PA) is suggested to contribute to fat loss not only through increasing energy expenditure "per se" but also increasing muscle mass; therefore, it would be interesting to better understand the specific associations of PA with the different body's components such as fat mass and muscle mass. The aim of the present study was to examine the association between objectively measured PA and indices of fat mass and muscle components independently of each other giving, at the same time, gender-specific information in a wide cohort of European adolescents. A cross-sectional study in a school setting was conducted in 2200 (1016 males) adolescents (14.7 ± 1.2 years). Weight, height, skinfold thickness, bioimpedance and PA (accelerometry) were measured. Indices of fat mass (body mass index, % fat mass, sum of skinfolds) and muscular component (assessed as fat-free mass) were calculated. Multiple regression analyses were performed adjusting for several confounders including fat-free mass and fat mass when possible. Vigorous PA was positively associated with height (pgenders, except for average PA in relation with body mass index in females. Regarding muscular components, vigorous PA showed positive associations with fat-free mass and muscle mass (all pgenders. Average PA was positively associated with fat-free mass (both p<0.05) in males and females. The present study suggests that PA, especially vigorous PA, is negatively associated with indices of fat mass and positively associated with markers of muscle mass, after adjusting for several confounders (including indices of fat mass and muscle mass when possible). Future studies should focus not only on the classical relationship between PA and fat mass, but also on PA and muscular components, analyzing the independent role of both with the different PA intensities.

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.

A proposed centralised distribution model for the South African automotive component industry

Directory of Open Access Journals (Sweden)

Micheline J. Naude

2009-12-01

Full Text Available Purpose: This article explores the possibility of developing a distribution model, similar to the model developed and implemented by the South African pharmaceutical industry, which could be implemented by automotive component manufacturers for supply to independent retailers. Problem Investigated: The South African automotive components distribution chain is extensive with a number of players of varying sizes, from the larger spares distribution groups to a number of independent retailers. Distributing to the smaller independent retailers is costly for the automotive component manufacturers. Methodology: This study is based on a preliminary study of an explorative nature. Interviews were conducted with a senior staff member from a leading automotive component manufacturer in KwaZulu Natal and nine participants at a senior management level at five of their main customers (aftermarket retailers. Findings: The findings from the empirical study suggest that the aftermarket component industry is mature with the role players well established. The distribution chain to the independent retailer is expensive in terms of transaction and distribution costs for the automotive component manufacturer. A proposed centralised distribution model for supply to independent retailers has been developed which should reduce distribution costs for the automotive component manufacturer in terms of (1 the lowest possible freight rate; (2 timely and controlled delivery; and (3 reduced congestion at the customer's receiving dock. Originality: This research is original in that it explores the possibility of implementing a centralised distribution model for independent retailers in the automotive component industry. Furthermore, there is a dearth of published research on the South African automotive component industry particularly addressing distribution issues. Conclusion: The distribution model as suggested is a practical one and should deliver added value to automotive

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

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.

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.

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.

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.

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

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...

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.

'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.

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

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.

Baseline and changes in serum uric acid independently predict 11-year incidence of metabolic syndrome among community-dwelling women.

Science.gov (United States)

Kawamoto, R; Ninomiya, D; Kasai, Y; Senzaki, K; Kusunoki, T; Ohtsuka, N; Kumagi, T

2018-02-19

Metabolic syndrome (MetS) is associated with an increased risk of major cardiovascular events. In women, increased serum uric acid (SUA) levels are associated with MetS and its components. However, whether baseline and changes in SUA predict incidence of MetS and its components remains unclear. The subjects comprised 407 women aged 71 ± 8 years from a rural village. We have identified participants who underwent a similar examination 11 years ago, and examined the relationship between baseline and changes in SUA, and MetS based on the modified criteria of the National Cholesterol Education Program's Adult Treatment Panel (NCEP-ATP) III report. Of these subjects, 83 (20.4%) women at baseline and 190 (46.7%) women at follow-up had MetS. Multiple linear regression analysis was performed to evaluate the contribution of each confounding factor for MetS; both baseline and changes in SUA as well as history of cardiovascular disease, low-density lipoprotein cholesterol, and estimated glomerular filtration ratio (eGFR) were independently and significantly associated with the number of MetS components during an 11-year follow-up. The adjusted odds ratios (ORs) (95% confidence interval) for incident MetS across tertiles of baseline SUA and changes in SUA were 1.00, 1.47 (0.82-2.65), and 3.11 (1.66-5.83), and 1.00, 1.88 (1.03-3.40), and 2.49 (1.38-4.47), respectively. In addition, the combined effect between increased baseline and changes in SUA was also a significant and independent determinant for the accumulation of MetS components (F = 20.29, p baseline MetS. These results suggested that combined assessment of baseline and changes in SUA levels provides increased information for incident MetS, independent of other confounding factors in community-dwelling women.

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.

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.

Prosthetic component segmentation with blur compensation: a fast method for 3D fluoroscopy.

Science.gov (United States)

Tarroni, Giacomo; Tersi, Luca; Corsi, Cristiana; Stagni, Rita

2012-06-01

A new method for prosthetic component segmentation from fluoroscopic images is presented. The hybrid approach we propose combines diffusion filtering, region growing and level-set techniques without exploiting any a priori knowledge of the analyzed geometry. The method was evaluated on a synthetic dataset including 270 images of knee and hip prosthesis merged to real fluoroscopic data simulating different conditions of blurring and illumination gradient. The performance of the method was assessed by comparing estimated contours to references using different metrics. Results showed that the segmentation procedure is fast, accurate, independent on the operator as well as on the specific geometrical characteristics of the prosthetic component, and able to compensate for amount of blurring and illumination gradient. Importantly, the method allows a strong reduction of required user interaction time when compared to traditional segmentation techniques. Its effectiveness and robustness in different image conditions, together with simplicity and fast implementation, make this prosthetic component segmentation procedure promising and suitable for multiple clinical applications including assessment of in vivo joint kinematics in a variety of cases.

Model validation and calibration based on component functions of model output

International Nuclear Information System (INIS)

Wu, Danqing; Lu, Zhenzhou; Wang, Yanping; Cheng, Lei

2015-01-01

The target in this work is to validate the component functions of model output between physical observation and computational model with the area metric. Based on the theory of high dimensional model representations (HDMR) of independent input variables, conditional expectations are component functions of model output, and the conditional expectations reflect partial information of model output. Therefore, the model validation of conditional expectations tells the discrepancy between the partial information of the computational model output and that of the observations. Then a calibration of the conditional expectations is carried out to reduce the value of model validation metric. After that, a recalculation of the model validation metric of model output is taken with the calibrated model parameters, and the result shows that a reduction of the discrepancy in the conditional expectations can help decrease the difference in model output. At last, several examples are employed to demonstrate the rationality and necessity of the methodology in case of both single validation site and multiple validation sites. - Highlights: • A validation metric of conditional expectations of model output is proposed. • HDRM explains the relationship of conditional expectations and model output. • An improved approach of parameter calibration updates the computational models. • Validation and calibration process are applied at single site and multiple sites. • Validation and calibration process show a superiority than existing methods

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

INDICATORS AND DIAGNOSTICS OF INDEPENDENT WORK CULTURE FORMATION IN FUTURE MATHEMATICS TEACHERS

Directory of Open Access Journals (Sweden)

Олена Соя

2015-09-01

Full Text Available The article highlights the results of research of formation the culture of independent work of future mathematics teachers, indicating the effectiveness of selected theoretically grounded and practically implemented pedagogical conditions of its formation. Its semantic components that are interconnected and interdependent unity of cognitive, procedural, technological and motivational components were singled out on the basis of definition of independent work culture of future mathematics teachers. The system of indicators, which assessed the degree of mastering by students the culture of independent work by value-orientation, content-effective, reflective, constructive and operationally-activity criteria is reviewed.

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],…

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

Allocation and management issues in multiple-transaction open access transmission networks

Science.gov (United States)

Tao, Shu

This thesis focuses on some key issues related to allocation and management by the independent grid operator (IGO) of unbundled services in multiple-transaction open access transmission networks. The three unbundled services addressed in the thesis are transmission real power losses, reactive power support requirements from generation sources, and transmission congestion management. We develop the general framework that explicitly represents multiple transactions undertaken simultaneously in the transmission grid. This framework serves as the basis for formulating various problems treated in the thesis. We use this comprehensive framework to develop a physical-flow-based mechanism to allocate the total transmission losses to each transaction using the system. An important property of the allocation scheme is its capability to effectively deal with counter flows that result in the presence of specific transactions. Using the loss allocation results as the basis, we construct the equivalent loss compensation concept and apply it to develop flexible and effective procedures for compensating losses in multiple-transaction networks. We present a new physical-flow-based mechanism for allocating the reactive power support requirements provided by generators in multiple-transaction networks. The allocatable reactive support requirements are formulated as the sum of two specific components---the voltage magnitude variation component and the voltage angle variation component. The formulation utilizes the multiple-transaction framework and makes use of certain simplifying approximations. The formulation leads to a natural allocation as a function of the amount of each transaction. The physical interpretation of each allocation as a sensitivity of the reactive output of a generator is discussed. We propose a congestion management allocation scheme for multiple-transaction networks. The proposed scheme determines the allocation of congestion among the transactions on a physical

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.

Delay-independent stability of genetic regulatory networks.

Science.gov (United States)

Wu, Fang-Xiang

2011-11-01

Genetic regulatory networks can be described by nonlinear differential equations with time delays. In this paper, we study both locally and globally delay-independent stability of genetic regulatory networks, taking messenger ribonucleic acid alternative splicing into consideration. Based on nonnegative matrix theory, we first develop necessary and sufficient conditions for locally delay-independent stability of genetic regulatory networks with multiple time delays. Compared to the previous results, these conditions are easy to verify. Then we develop sufficient conditions for global delay-independent stability for genetic regulatory networks. Compared to the previous results, this sufficient condition is less conservative. To illustrate theorems developed in this paper, we analyze delay-independent stability of two genetic regulatory networks: a real-life repressilatory network with three genes and three proteins, and a synthetic gene regulatory network with five genes and seven proteins. The simulation results show that the theorems developed in this paper can effectively determine the delay-independent stability of genetic regulatory networks.

Component Commonality and Its Cost Implications - Increasing the Commonality of the Right Components

DEFF Research Database (Denmark)

Lyly-Yrjänäinen, Jouni; Suomala, Petri; Israelsen, Poul

Component commonality (Labro 2004, Zhou & Gruppström 2004) can be defined as the use of the same version of a component across multiple products. It is usually seen as a means to manage costs without sacrificing product variety. However, when managing costs with component commonality, the managers...... constructions was identified as the most important bottleneck for the delivery process causing many indirect costs, especially with respect to project-management-related activities. Interestingly, by eliminating the need for mechanical engineering, the context starts to approach assembly-to-order context, also...... should be able to identify rather rapidly which group of components would enable the most significant cost reductions. Unfortunately, the existing literature lacks profound discussion of how to identify the right components for increased component commonality. The objective of the paper is to discuss how...

Resting‐state connectivity of pre‐motor cortex reflects disability in multiple sclerosis

DEFF Research Database (Denmark)

Dogonowski, Anne-Marie; Siebner, Hartwig Roman; Soelberg Sørensen, P.

2013-01-01

Objective To characterize the relationship between motor resting-state connectivity of the dorsal pre-motor cortex (PMd) and clinical disability in patients with multiple sclerosis (MS). Materials and methods A total of 27 patients with relapsing–remitting MS (RR-MS) and 15 patients with secondary...... progressive MS (SP-MS) underwent functional resting-state magnetic resonance imaging. Clinical disability was assessed using the Expanded Disability Status Scale (EDSS). Independent component analysis was used to characterize motor resting-state connectivity. Multiple regression analysis was performed in SPM8...... between the individual expression of motor resting-state connectivity in PMd and EDSS scores including age as covariate. Separate post hoc analyses were performed for patients with RR-MS and SP-MS. Results The EDSS scores ranged from 0 to 7 with a median score of 4.3. Motor resting-state connectivity...

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.

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

Independent events in elementary probability theory

Science.gov (United States)

Csenki, Attila

2011-07-01

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): quote specific-use="indent"> If the n events E 1, E 2, … , E n are jointly independent then any two events A and B built in finitely many steps from two disjoint subsets of E 1, E 2, … , E n are also independent. The operations 'union', 'intersection' and 'complementation' are permitted only when forming the events A and B. quote>Here we examine this statement from the point of view of elementary probability theory. The approach described here is accessible also to users of probability theory and is believed to be novel.

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.

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

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.

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.

Energy independent optical potentials: construction and limitations

International Nuclear Information System (INIS)

Hussein, M.S.; Moniz, E.J.

1983-11-01

Properties of the energy-independent potential U sup(-) which is wave-function-equivalent to the usual optical potential U(E) are constructed and examined. A simple procedure is presented for constructing U sup(-) in the uniform medium, and physical examples are discussed. The general result for finite systems, a recursive expansion in powers of U(E), is used to investigate the multiple scattering expansion of U sup(-); the energy-independent potential is found to have serious short-comings for direct microscopic construction or phenomenological parametrization. The microscopic theory, as exemplified here by the multiple scattering approach, does not lead to a reliable approximation scheme. Phenomenological approaches to U sup(-) are unattractive because the physics does not guide the parametrization effectively: the structure of the nonlocality is not tied directly to the dynamics; Im U sup(-) changes sign; different elements of the physics, separate in U(E), are completely entangled in U sup(-). (Author) [pt

Vascular comorbidities in multiple sclerosis

DEFF Research Database (Denmark)

Thormann, Anja; Magyari, Melinda; Koch-Henriksen, Nils

2016-01-01

To investigate the occurrence of vascular comorbidities before and after the clinical onset of multiple sclerosis. In this combined case-control and cohort study, all Danish born citizens with onset of multiple sclerosis 1980-2005 were identified from the Danish Multiple Sclerosis Registry...... and randomly matched with controls regarding year of birth, gender, and municipality on January 1st in the year of multiple sclerosis (MS) onset (index date). Individual-level information on comorbidities was obtained from several independent nationwide registries and linked to the study population by unique...

Is Stacking Intervention Components Cost-Effective? An Analysis of the Incredible Years Program

Science.gov (United States)

Foster, E. Michael; Olchowski, Allison E.; Webster-Stratton, Carolyn H.

2007-01-01

The cost-effectiveness of delivering stacked multiple intervention components for children is compared to implementing single intervention by analyzing the Incredible Years Series program. The result suggests multiple intervention components are more cost-effective than single intervention components.

A high-pressure thermal gradient block for investigating microbial activity in multiple deep-sea samples

DEFF Research Database (Denmark)

Kallmeyer, J.; Ferdelman, TG; Jansen, KH

2003-01-01

Details about the construction and use of a high-pressure thermal gradient block for the simultaneous incubation of multiple samples are presented. Most parts used are moderately priced off-the-shelf components that easily obtainable. In order to keep the pressure independent of thermal expansion...... range of temperatures and pressures and can easily be modified to accommodate different experiments, either biological or chemical. As an application, we present measurements of bacterial sulfate reduction rates in hydrothermal sediments from Guyamas Basin over a wide range of temperatures and pressures...

The Independent and Shared Mechanisms of Intrinsic Brain Dynamics: Insights From Bistable Perception

Directory of Open Access Journals (Sweden)

Teng Cao

2018-04-01

Full Text Available In bistable perception, constant input leads to alternating perception. The dynamics of the changing perception reflects the intrinsic dynamic properties of the “unconscious inferential” process in the brain. Under the same condition, individuals differ in how fast they experience the perceptual alternation. In this study, testing many forms of bistable perception in a large number of observers, we investigated the key question of whether there is a general and common mechanism or multiple and independent mechanisms that control the dynamics of the inferential brain. Bistable phenomena tested include binocular rivalry, vase-face, Necker cube, moving plaid, motion induced blindness, biological motion, spinning dancer, rotating cylinder, Lissajous-figure, rolling wheel, and translating diamond. Switching dynamics for each bistable percept was measured in 100 observers. Results show that the switching rates of subsets of bistable percept are highly correlated. The clustering of dynamic properties of some bistable phenomena but not an overall general control of switching dynamics implies that the brain’s inferential processes are both shared and independent – faster in constructing 3D structure from motion does not mean faster in integrating components into an objects.

The M Word: Multicollinearity in Multiple Regression.

Science.gov (United States)

Morrow-Howell, Nancy

1994-01-01

Notes that existence of substantial correlation between two or more independent variables creates problems of multicollinearity in multiple regression. Discusses multicollinearity problem in social work research in which independent variables are usually intercorrelated. Clarifies problems created by multicollinearity, explains detection of…

The Multiple Tasks Test: development and normal strategies.

NARCIS (Netherlands)

Bloem, B.R.; Valkenburg, V.V.; Slabbekoorn, M.; Willemsen, M.D.

2001-01-01

Simultaneous challenge of posture and cognition ("dual tasks") may predict falls better than tests of isolated components of postural control. We describe a new balance test (the Multiple Tasks Test, MTT) which (1) is based upon simultaneous assessment of multiple (>2) postural components; (2)

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).

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

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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.

Factors predicting work outcome in Japanese patients with schizophrenia: role of multiple functioning levels.

Science.gov (United States)

Sumiyoshi, Chika; Harvey, Philip D; Takaki, Manabu; Okahisa, Yuko; Sato, Taku; Sora, Ichiro; Nuechterlein, Keith H; Subotnik, Kenneth L; Sumiyoshi, Tomiki

2015-09-01

Functional outcomes in individuals with schizophrenia suggest recovery of cognitive, everyday, and social functioning. Specifically improvement of work status is considered to be most important for their independent living and self-efficacy. The main purposes of the present study were 1) to identify which outcome factors predict occupational functioning, quantified as work hours, and 2) to provide cut-offs on the scales for those factors to attain better work status. Forty-five Japanese patients with schizophrenia and 111 healthy controls entered the study. Cognition, capacity for everyday activities, and social functioning were assessed by the Japanese versions of the MATRICS Cognitive Consensus Battery (MCCB), the UCSD Performance-based Skills Assessment-Brief (UPSA-B), and the Social Functioning Scale Individuals' version modified for the MATRICS-PASS (Modified SFS for PASS), respectively. Potential factors for work outcome were estimated by multiple linear regression analyses (predicting work hours directly) and a multiple logistic regression analyses (predicting dichotomized work status based on work hours). ROC curve analyses were performed to determine cut-off points for differentiating between the better- and poor work status. The results showed that a cognitive component, comprising visual/verbal learning and emotional management, and a social functioning component, comprising independent living and vocational functioning, were potential factors for predicting work hours/status. Cut-off points obtained in ROC analyses indicated that 60-70% achievements on the measures of those factors were expected to maintain the better work status. Our findings suggest that improvement on specific aspects of cognitive and social functioning are important for work outcome in patients with schizophrenia.

Independent center, independent electron approximation for dynamics of molecules and clusters

International Nuclear Information System (INIS)

McGuire, J.H.; Straton, J.C.; Wang, J.; Wang, Y.D.; Weaver, O.L.; Corchs, S.E.; Rivarola, R.D.

1996-01-01

A formalism is developed for evaluating probabilities and cross sections for multiple-electron transitions in scattering of molecules and clusters by charged collision partners. First, the molecule is divided into subclusters each made up of identical centers (atoms). Within each subcluster coherent scattering from identical centers may lead to observable phase terms and a geometrical structure factor. Then, using a mean field approximation to describe the interactions between centers we obtain A I ∼ summation k product ke iδ k I A Ik . Second, the independent electron approximation for each center may be obtained by neglecting the correlation between electrons in each center. The probability amplitude for each center is then a product of single electron transition probability amplitudes, a Ik i , i.e. A Ik ≅ product iaik i . Finally, the independent subcluster approximation is introduced by neglecting the interactions between different subclusters in the molecule or cluster. The total probability amplitude then reduces to a simple product of amplitudes for each subcluster, A≅ product IAI . Limitations of this simple approximation are discussed. copyright 1996 American Institute of Physics

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...

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

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

'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.

The potyviral suppressor of RNA silencing confers enhanced resistance to multiple pathogens

International Nuclear Information System (INIS)

Pruss, Gail J.; Lawrence, Christopher B.; Bass, Troy; Li Qingshun Q.; Bowman, Lewis H.; Vance, Vicki

2004-01-01

Helper component-protease (HC-Pro) is a plant viral suppressor of RNA silencing, and transgenic tobacco expressing HC-Pro has increased susceptibility to a broad range of viral pathogens. Here we report that these plants also exhibit enhanced resistance to unrelated heterologous pathogens. Tobacco mosaic virus (TMV) infection of HC-Pro-expressing plants carrying the N resistance gene results in fewer and smaller lesions compared to controls without HC-Pro. The resistance to TMV is compromised but not eliminated by expression of nahG, which prevents accumulation of salicylic acid (SA), an important defense signaling molecule. HC-Pro-expressing plants are also more resistant to tomato black ring nepovirus (TBRV) and to the oomycete Peronospora tabacina. Enhanced TBRV resistance is SA-independent, whereas the response to P. tabacina is associated with early induction of markers characteristic of SA-dependent defense. Thus, a plant viral suppressor of RNA silencing enhances resistance to multiple pathogens via both SA-dependent and SA-independent mechanisms

The potyviral suppressor of RNA silencing confers enhanced resistance to multiple pathogens.

Science.gov (United States)

Pruss, Gail J; Lawrence, Christopher B; Bass, Troy; Li, Qingshun Q; Bowman, Lewis H; Vance, Vicki

2004-03-01

Helper component-protease (HC-Pro) is a plant viral suppressor of RNA silencing, and transgenic tobacco expressing HC-Pro has increased susceptibility to a broad range of viral pathogens. Here we report that these plants also exhibit enhanced resistance to unrelated heterologous pathogens. Tobacco mosaic virus (TMV) infection of HC-Pro-expressing plants carrying the N resistance gene results in fewer and smaller lesions compared to controls without HC-Pro. The resistance to TMV is compromised but not eliminated by expression of nahG, which prevents accumulation of salicylic acid (SA), an important defense signaling molecule. HC-Pro-expressing plants are also more resistant to tomato black ring nepovirus (TBRV) and to the oomycete Peronospora tabacina. Enhanced TBRV resistance is SA-independent, whereas the response to P. tabacina is associated with early induction of markers characteristic of SA-dependent defense. Thus, a plant viral suppressor of RNA silencing enhances resistance to multiple pathogens via both SA-dependent and SA-independent mechanisms.

Stator for a rotating electrical machine having multiple control windings

Science.gov (United States)

Shah, Manoj R.; Lewandowski, Chad R.

2001-07-17

A rotating electric machine is provided which includes multiple independent control windings for compensating for rotor imbalances and for levitating/centering the rotor. The multiple independent control windings are placed at different axial locations along the rotor to oppose forces created by imbalances at different axial locations along the rotor. The multiple control windings can also be used to levitate/center the rotor with a relatively small magnetic field per unit area since the rotor and/or the main power winding provides the bias field.

The multi-faceted assessment of independence in patients with rheumatoid arthritis: preliminary validation from the ATTAIN study.

Science.gov (United States)

Hassett, Afton L; Li, Tracy; Buyske, Steven; Savage, Shantal V; Gignac, Monique A M

2008-05-01

To consider the feasibility of assessing multiple facets of independence in rheumatoid arthritis (RA) using a measure developed from existing items and examining its face validity, construct validity and responsiveness to change. The ATTAIN (Abatacept Trial in Treatment of Anti-tumor necrosis factor [TNF] Inadequate responders) database was used. Patients with RA were randomized 2:1, abatacept (n = 258) and placebo (n = 133). A multi-faceted scale to measure physical and psychosocial independence was constructed using items from the Health Assessment Questionnaire (HAQ) and Short Form 36 Health Survey (SF-36). Questions assessing activity limitations and need for outside caregiver help were also examined. Interviews with 20 RA patients assessed face validity. Item Response Theory analysis yielded two traits - 'Psychosocial Independence', derived from the number of days with activity limitations plus the Role Emotional, Social Functioning and Role Physical subscale items from the SF-36; and 'Physical Independence', derived from 15 HAQ items assessing need for help from another. The two traits showed no significant differential item functioning for age or gender and demonstrated good face validity. Changes over 169 days on Psychosocial Independence were greater (mean 0.46 units, 95% confidence interval [CI]: 0.17-0.75) for the abatacept group than for placebo (p = 0.002). Changes in Physical Independence were greater (mean 0.59 units, 95% CI: 0.35-0.82) for the abatacept group than for placebo (p anti-TNF therapy. However, we caution against an interpretation that these data suggest that abatacept improves independence because the component parts of this assessment came from instruments used in the ATTAIN trial where data had been previously analyzed.

Decreasing Multicollinearity: A Method for Models with Multiplicative Functions.

Science.gov (United States)

Smith, Kent W.; Sasaki, M. S.

1979-01-01

A method is proposed for overcoming the problem of multicollinearity in multiple regression equations where multiplicative independent terms are entered. The method is not a ridge regression solution. (JKS)

Principal component approach in variance component estimation for international sire evaluation

Directory of Open Access Journals (Sweden)

Jakobsen Jette

2011-05-01

Full Text Available Abstract Background The dairy cattle breeding industry is a highly globalized business, which needs internationally comparable and reliable breeding values of sires. The international Bull Evaluation Service, Interbull, was established in 1983 to respond to this need. Currently, Interbull performs multiple-trait across country evaluations (MACE for several traits and breeds in dairy cattle and provides international breeding values to its member countries. Estimating parameters for MACE is challenging since the structure of datasets and conventional use of multiple-trait models easily result in over-parameterized genetic covariance matrices. The number of parameters to be estimated can be reduced by taking into account only the leading principal components of the traits considered. For MACE, this is readily implemented in a random regression model. Methods This article compares two principal component approaches to estimate variance components for MACE using real datasets. The methods tested were a REML approach that directly estimates the genetic principal components (direct PC and the so-called bottom-up REML approach (bottom-up PC, in which traits are sequentially added to the analysis and the statistically significant genetic principal components are retained. Furthermore, this article evaluates the utility of the bottom-up PC approach to determine the appropriate rank of the (covariance matrix. Results Our study demonstrates the usefulness of both approaches and shows that they can be applied to large multi-country models considering all concerned countries simultaneously. These strategies can thus replace the current practice of estimating the covariance components required through a series of analyses involving selected subsets of traits. Our results support the importance of using the appropriate rank in the genetic (covariance matrix. Using too low a rank resulted in biased parameter estimates, whereas too high a rank did not result in

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.

Availability, reliability and downtime of systems with repairable components

DEFF Research Database (Denmark)

Kiureghian, Armen Der; Ditlevsen, Ove Dalager; Song, J.

2007-01-01

Closed-form expressions are derived for the steady-state availability, mean rate of failure, mean duration of downtime and lower bound reliability of a general system with randomly and independently failing repairable components. Component failures are assumed to be homogeneous Poisson events in ...

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.

Thermally activated, single component epoxy systems

KAUST Repository

Unruh, David A.; Pastine, Stefan J.; Moreton, Jessica C.; Frechet, Jean

2011-01-01

A single component epoxy system in which the resin and hardener components found in many two-component epoxies are combined onto the same molecule is described. The single molecule precursor to the epoxy resin contains both multiple epoxide moieties and a diamine held latent by thermally degradable carbamate linkages. These bis-carbamate "single molecule epoxies" have an essentially infinite shelf life and access a significant range in curing temperatures related to the structure of the carbamate linkages used. © 2011 American Chemical Society.

Thermally activated, single component epoxy systems

KAUST Repository

Unruh, David A.

2011-08-23

A single component epoxy system in which the resin and hardener components found in many two-component epoxies are combined onto the same molecule is described. The single molecule precursor to the epoxy resin contains both multiple epoxide moieties and a diamine held latent by thermally degradable carbamate linkages. These bis-carbamate "single molecule epoxies" have an essentially infinite shelf life and access a significant range in curing temperatures related to the structure of the carbamate linkages used. © 2011 American Chemical Society.

A review of multiple stressor studies that include ionising radiation

International Nuclear Information System (INIS)

Vanhoudt, Nathalie; Vandenhove, Hildegarde; Real, Almudena; Bradshaw, Clare; Stark, Karolina

2012-01-01

Studies were reviewed that investigated the combined effects of ionising radiation and other stressors on non-human biota. The aim was to determine the state of research in this area of science, and determine if a review of the literature might permit a gross generalization as to whether the combined effects of multi-stressors and radiation are fundamentally additive, synergistic or antagonistic. A multiple stressor database was established for different organism groups. Information was collected on species, stressors applied and effects evaluated. Studies were mostly laboratory based and investigated two-component mixtures. Interactions declared positive occurred in 58% of the studies, while 26% found negative interactions. Interactions were dependent on dose/concentration, on organism's life stage and exposure time and differed among endpoints. Except for one study, none of the studies predicted combined effects following Concentration Addition or Independent Action, and hence, no justified conclusions can be made about synergism or antagonism. - This review on multiple stressor studies involving radiation, highlights that most experimental designs used did not allow to deduce the nature of the interactive effects.

Making Judges Independent – Some Proposals Regarding the Judiciary

OpenAIRE

Lars P. Feld; Stefan Voigt

2004-01-01

It is argued that an independent judiciary is a necessary condition for both individual liberty and economic prosperity. After having surveyed the literature dealing with how to arrange for an independent judiciary, the authors derive some additional policy implications by drawing on two indicators of judicial independence (JI) recently introduced by them. De facto JI has a robust and highly significant impact on economic growth. Individual components of both de jure and de facto JI on econom...

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.

Evidence for modality-independent order coding in working memory.

Science.gov (United States)

Depoorter, Ann; Vandierendonck, André

2009-03-01

The aim of the present study was to investigate the representation of serial order in working memory, more specifically whether serial order is coded by means of a modality-dependent or a modality-independent order code. This was investigated by means of a series of four experiments based on a dual-task methodology in which one short-term memory task was embedded between the presentation and recall of another short-term memory task. Two aspects were varied in these memory tasks--namely, the modality of the stimulus materials (verbal or visuo-spatial) and the presence of an order component in the task (an order or an item memory task). The results of this study showed impaired primary-task recognition performance when both the primary and the embedded task included an order component, irrespective of the modality of the stimulus materials. If one or both of the tasks did not contain an order component, less interference was found. The results of this study support the existence of a modality-independent order code.

Scaling and mean normalized multiplicity in hadron-nucleus collisions

International Nuclear Information System (INIS)

Khan, M.Q.R.; Ahmad, M.S.; Hasan, R.

1987-01-01

Recently it has been reported that the dependence of the mean normalized multiplicity, R A , in hadron-nucleus collisions upon the effective number of projectile encounters, , is projectile independent. We report the failure of this kind of scaling using the world data at accelerator and cosmic ray energies. Infact, we have found that the dependence of R A upon the number of projectile encounters hA is projectile independent. This leads to a new kind of scaling. Further, the scaled multiplicity distributions are found independent on the nature and energy of the incident hadron in the energy range ≅ (17.2-300) GeV. (orig.)

Constraints on signaling network logic reveal functional subgraphs on Multiple Myeloma OMIC data.

Science.gov (United States)

Miannay, Bertrand; Minvielle, Stéphane; Magrangeas, Florence; Guziolowski, Carito

2018-03-21

The integration of gene expression profiles (GEPs) and large-scale biological networks derived from pathways databases is a subject which is being widely explored. Existing methods are based on network distance measures among significantly measured species. Only a small number of them include the directionality and underlying logic existing in biological networks. In this study we approach the GEP-networks integration problem by considering the network logic, however our approach does not require a prior species selection according to their gene expression level. We start by modeling the biological network representing its underlying logic using Logic Programming. This model points to reachable network discrete states that maximize a notion of harmony between the molecular species active or inactive possible states and the directionality of the pathways reactions according to their activator or inhibitor control role. Only then, we confront these network states with the GEP. From this confrontation independent graph components are derived, each of them related to a fixed and optimal assignment of active or inactive states. These components allow us to decompose a large-scale network into subgraphs and their molecular species state assignments have different degrees of similarity when compared to the same GEP. We apply our method to study the set of possible states derived from a subgraph from the NCI-PID Pathway Interaction Database. This graph links Multiple Myeloma (MM) genes to known receptors for this blood cancer. We discover that the NCI-PID MM graph had 15 independent components, and when confronted to 611 MM GEPs, we find 1 component as being more specific to represent the difference between cancer and healthy profiles.

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...

Universal transport characteristics of multiple topological superconducting wires with large charging energy

Energy Technology Data Exchange (ETDEWEB)

Kashuba, Oleksiy; Trauzettel, Bjoern [Institut fuer Theoretische Physik und Astrophysik, Universitaet Wuerzburg, 97074 Wuerzburg (Germany); Timm, Carsten [Institut fuer Theoretische Physik, TU Dresden, 01062 Dresden (Germany)

2016-07-01

The system with multiple Majorana states coupled to the normal lead can potentially support the interaction between Majorana fermions and electrons. Such system can be implemented by several floating topological superconducting wires with large charging energy asymmetrically coupled to two normal leads. The analysis of the renormalization flow shows that there is a single fixed point - the strong coupling limit of isotropic antiferromagnetic Kondo model. The topological Kondo-like interaction leads also to the selective renormalization of the tunneling coefficients, strongly enhancing one component and suppressing others. Thus, charging energy crucially changes the transport properties of the system leading to the universal single-channel conductance independently from the values of the initial leads-wires coupling.

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.

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

Graviton propagator from background-independent quantum gravity.

Science.gov (United States)

Rovelli, Carlo

2006-10-13

We study the graviton propagator in Euclidean loop quantum gravity. We use spin foam, boundary-amplitude, and group-field-theory techniques. We compute a component of the propagator to first order, under some approximations, obtaining the correct large-distance behavior. This indicates a way for deriving conventional spacetime quantities from a background-independent theory.

Influences on cocaine tolerance assessed under a multiple conjunctive schedule of reinforcement.

Science.gov (United States)

Yoon, Jin Ho; Branch, Marc N

2009-11-01

Under multiple schedules of reinforcement, previous research has generally observed tolerance to the rate-decreasing effects of cocaine that has been dependent on schedule-parameter size in the context of fixed-ratio (FR) schedules, but not under the context of fixed-interval (FI) schedules of reinforcement. The current experiment examined the effects of cocaine on key-pecking responses of White Carneau pigeons maintained under a three-component multiple conjunctive FI (10 s, 30 s, & 120 s) FR (5 responses) schedule of food presentation. Dose-effect curves representing the effects of presession cocaine on responding were assessed in the context of (1) acute administration of cocaine (2) chronic administration of cocaine and (3) daily administration of saline. Chronic administration of cocaine generally resulted in tolerance to the response-rate decreasing effects of cocaine, and that tolerance was generally independent of relative FI value, as measured by changes in ED50 values. Daily administration of saline decreased ED50 values to those observed when cocaine was administered acutely. The results show that adding a FR requirement to FI schedules is not sufficient to produce schedule-parameter-specific tolerance. Tolerance to cocaine was generally independent of FI-parameter under the present conjunctive schedules, indicating that a ratio requirement, per se, is not sufficient for tolerance to be dependent on FI parameter.

Factors predicting work outcome in Japanese patients with schizophrenia: role of multiple functioning levels

Directory of Open Access Journals (Sweden)

Chika Sumiyoshi

2015-09-01

Full Text Available Functional outcomes in individuals with schizophrenia suggest recovery of cognitive, everyday, and social functioning. Specifically improvement of work status is considered to be most important for their independent living and self-efficacy. The main purposes of the present study were 1 to identify which outcome factors predict occupational functioning, quantified as work hours, and 2 to provide cut-offs on the scales for those factors to attain better work status. Forty-five Japanese patients with schizophrenia and 111 healthy controls entered the study. Cognition, capacity for everyday activities, and social functioning were assessed by the Japanese versions of the MATRICS Cognitive Consensus Battery (MCCB, the UCSD Performance-based Skills Assessment-Brief (UPSA-B, and the Social Functioning Scale Individuals’ version modified for the MATRICS-PASS (Modified SFS for PASS, respectively. Potential factors for work outcome were estimated by multiple linear regression analyses (predicting work hours directly and a multiple logistic regression analyses (predicting dichotomized work status based on work hours. ROC curve analyses were performed to determine cut-off points for differentiating between the better- and poor work status. The results showed that a cognitive component, comprising visual/verbal learning and emotional management, and a social functioning component, comprising independent living and vocational functioning, were potential factors for predicting work hours/status. Cut-off points obtained in ROC analyses indicated that 60–70% achievements on the measures of those factors were expected to maintain the better work status. Our findings suggest that improvement on specific aspects of cognitive and social functioning are important for work outcome in patients with schizophrenia.

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

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.

Second-order multiple-scattering theory associated with backscattering enhancement for a millimeter wavelength weather radar with a finite beam width

Science.gov (United States)

Kobayashi, Satoru; Tanelli, Simone; Im, Eastwood

2005-01-01

Effects of multiple scattering on reflectivity are studied for millimeter wavelength weather radars. A time-independent vector theory, including up to second-order scattering, is derived for a single layer of hydrometeors of a uniform density and a uniform diameter. In this theory, spherical waves with a Gaussian antenna pattern are used to calculate ladder and cross terms in the analytical scattering theory. The former terms represent the conventional multiple scattering, while the latter terms cause backscattering enhancement in both the copolarized and cross-polarized components. As the optical thickness of the hydrometeor layer increases, the differences from the conventional plane wave theory become more significant, and essentially, the reflectivity of multiple scattering depends on the ratio of mean free path to radar footprint radius. These results must be taken into account when analyzing radar reflectivity for use in remote sensing.

Gigabit Ethernet signal transmission using asynchronous optical code division multiple access.

Science.gov (United States)

Ma, Philip Y; Fok, Mable P; Shastri, Bhavin J; Wu, Ben; Prucnal, Paul R

2015-12-15

We propose and experimentally demonstrate a novel architecture for interfacing and transmitting a Gigabit Ethernet (GbE) signal using asynchronous incoherent optical code division multiple access (OCDMA). This is the first such asynchronous incoherent OCDMA system carrying GbE data being demonstrated to be working among multi-users where each user is operating with an independent clock/data rate and is granted random access to the network. Three major components, the GbE interface, the OCDMA transmitter, and the OCDMA receiver are discussed in detail. The performance of the system is studied and characterized through measuring eye diagrams, bit-error rate and packet loss rate in real-time file transfer. Our Letter also addresses the near-far problem and realizes asynchronous transmission and detection of signal.

Contributory factors for the functional independence of oldest old

Directory of Open Access Journals (Sweden)

Dâmarys Kohlbeck de Melo Neu Ribeiro

2015-02-01

Full Text Available OBJECTIVE To investigate the socioeconomic and clinical factors that contribute to the functional independence of the oldest old of a community. METHOD Cross-sectional quantitative study whose sample consisted of 214 elderly people registered in Basic Health Units. Data were collected through structured interviews and application of the Functional Independence Measure. We used descriptive statistics, and for association of the variables we used the Student t-test, ANOVA and Tukey's test for multiple comparisons. RESULTS The significant variables that contributed to the functional independence were remaining economically active, practicing physical and leisure activities, having a social life, eating fruits, vegetables and meat. The orientation to conduct these practices reduces the demand for care and help needed in everyday activities. CONCLUSION Maintaining independence is primordial to delay disability and presents itself as an excellent field of work for nursing.

Phase Noise Effect on MIMO-OFDM Systems with Common and Independent Oscillators

Directory of Open Access Journals (Sweden)

Xiaoming Chen

2017-01-01

Full Text Available The effects of oscillator phase noises (PNs on multiple-input multiple-output (MIMO orthogonal frequency division multiplexing (OFDM systems are studied. It is shown that PNs of common oscillators at the transmitter and at the receiver have the same influence on the performance of (single-stream beamforming MIMO-OFDM systems, yet different influences on spatial multiplexing MIMO-OFDM systems with singular value decomposition (SVD based precoding/decoding. When each antenna is equipped with an independent oscillator, the PNs at the transmitter and at the receiver have different influences on beamforming MIMO-OFDM systems as well as spatial multiplexing MIMO-OFDM systems. Specifically, the PN effect on the transmitter (receiver can be alleviated by having more transmit (receive antennas for the case of independent oscillators. It is found that the independent oscillator case outperforms the common oscillator case in terms of error vector magnitude (EVM.

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.

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.

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

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.

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…

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.

Multiple sclerosis: current immunological aspects

Directory of Open Access Journals (Sweden)

Carlos Cuevas-García

2017-02-01

Full Text Available Multiple sclerosis is the most common inflammatory, chronic and degenerative condition of the central nervous system, and represents the first cause of disability in young adults. In Mexico, 11 to 20 out of every 100 000 people suffer from this disease. The causes of multiple sclerosis remain unknown, but several theories have been proposed on its origin: the interaction of environmental factors, viral infectious factors and genetic and immune susceptibility of each individual patient, which induce an autoimmune response and promote neuronal/axonal degeneration. In this review, the immune reaction main components and neurodegeneration present in multiple sclerosis are analyzed, as well as the inflammatory cascade associated with demyelination. Available treatments’ main purpose is to modulate aspects related to the adaptive immune response (B and T cells. The therapeutic challenge will be antigen-specific immune-tolerance induction, for example, with the use of tolerance protocols with peptides or DNA or nanoparticles vaccines. Future therapies should aim to control innate components (microglia, macrophages, astrocytes and to promote remyelination. To optimize the treatment, a combined therapeutic approach targeting the control of inflammatory and neurodegenerative components of the disease and monitoring of biomarkers will be necessary.

Memory attacks on device-independent quantum cryptography.

Science.gov (United States)

Barrett, Jonathan; Colbeck, Roger; Kent, Adrian

2013-01-04

Device-independent quantum cryptographic schemes aim to guarantee security to users based only on the output statistics of any components used, and without the need to verify their internal functionality. Since this would protect users against untrustworthy or incompetent manufacturers, sabotage, or device degradation, this idea has excited much interest, and many device-independent schemes have been proposed. Here we identify a critical weakness of device-independent protocols that rely on public communication between secure laboratories. Untrusted devices may record their inputs and outputs and reveal information about them via publicly discussed outputs during later runs. Reusing devices thus compromises the security of a protocol and risks leaking secret data. Possible defenses include securely destroying or isolating used devices. However, these are costly and often impractical. We propose other more practical partial defenses as well as a new protocol structure for device-independent quantum key distribution that aims to achieve composable security in the case of two parties using a small number of devices to repeatedly share keys with each other (and no other party).

Genetic variations in multiple myeloma I

DEFF Research Database (Denmark)

Vangsted, A.; Klausen, T.W.; Vogel, Ulla Birgitte

2012-01-01

Few risk factors have been established for the plasma cell disorder multiple myeloma, but some of these like African American ethnicity and a family history of B-cell lymphoproliferative diseases suggest a genetic component for the disease. Genetic variation represents the genetic basis of variab......Few risk factors have been established for the plasma cell disorder multiple myeloma, but some of these like African American ethnicity and a family history of B-cell lymphoproliferative diseases suggest a genetic component for the disease. Genetic variation represents the genetic basis...

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.

Cortical networks involved in visual awareness independent of visual attention.

Science.gov (United States)

Webb, Taylor W; Igelström, Kajsa M; Schurger, Aaron; Graziano, Michael S A

2016-11-29

It is now well established that visual attention, as measured with standard spatial attention tasks, and visual awareness, as measured by report, can be dissociated. It is possible to attend to a stimulus with no reported awareness of the stimulus. We used a behavioral paradigm in which people were aware of a stimulus in one condition and unaware of it in another condition, but the stimulus drew a similar amount of spatial attention in both conditions. The paradigm allowed us to test for brain regions active in association with awareness independent of level of attention. Participants performed the task in an MRI scanner. We looked for brain regions that were more active in the aware than the unaware trials. The largest cluster of activity was obtained in the temporoparietal junction (TPJ) bilaterally. Local independent component analysis (ICA) revealed that this activity contained three distinct, but overlapping, components: a bilateral, anterior component; a left dorsal component; and a right dorsal component. These components had brain-wide functional connectivity that partially overlapped the ventral attention network and the frontoparietal control network. In contrast, no significant activity in association with awareness was found in the banks of the intraparietal sulcus, a region connected to the dorsal attention network and traditionally associated with attention control. These results show the importance of separating awareness and attention when testing for cortical substrates. They are also consistent with a recent proposal that awareness is associated with ventral attention areas, especially in the TPJ.

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

Multiview Bayesian Correlated Component Analysis

DEFF Research Database (Denmark)

Kamronn, Simon Due; Poulsen, Andreas Trier; Hansen, Lars Kai

2015-01-01

are identical. Here we propose a hierarchical probabilistic model that can infer the level of universality in such multiview data, from completely unrelated representations, corresponding to canonical correlation analysis, to identical representations as in correlated component analysis. This new model, which...... we denote Bayesian correlated component analysis, evaluates favorably against three relevant algorithms in simulated data. A well-established benchmark EEG data set is used to further validate the new model and infer the variability of spatial representations across multiple subjects....

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

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

Science.gov (United States)

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

2016-05-04

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

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

Directory of Open Access Journals (Sweden)

Sofia Ximenes

2016-05-01

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

Multiplicity distributions for p-barp collisions

International Nuclear Information System (INIS)

Huang, D.W.; Yen, E.

1988-01-01

The multiplicity distribution for P-barP collisions at √s = 540 GeV is written as the sum of Poisson distributions at different impact parameter b. An energy independent relation between the variable z-bar and b is suggested. With this relation, the multiplicity distributions at √s = 200 and 900 GeV are described well. The distribution at √s = 1600 GeV is predicted

Component Structure of Individual Differences in True and False Recognition of Faces

Science.gov (United States)

Bartlett, James C.; Shastri, Kalyan K.; Abdi, Herve; Neville-Smith, Marsha

2009-01-01

Principal-component analyses of 4 face-recognition studies uncovered 2 independent components. The first component was strongly related to false-alarm errors with new faces as well as to facial "conjunctions" that recombine features of previously studied faces. The second component was strongly related to hits as well as to the conjunction/new…

Increased mean lung density: Another independent predictor of lung cancer?

Energy Technology Data Exchange (ETDEWEB)

Sverzellati, Nicola, E-mail: nicola.sverzellati@unipr.it [Department of Department of Surgical Sciences, Section of Diagnostic Imaging, University of Parma, Padiglione Barbieri, University Hospital of Parma, V. Gramsci 14, 43100 Parma (Italy); Randi, Giorgia, E-mail: giorgia.randi@marionegri.it [Department of Epidemiology, Mario Negri Institute, Via La Masa 19, 20156 Milan (Italy); Spagnolo, Paolo, E-mail: paolo.spagnolo@unimore.it [Respiratory Disease Unit, Center for Rare Lung Disease, Department of Oncology, Hematology and Respiratory Disease, University of Modena and Reggio Emilia, Via del Pozzo 71, 44124 Modena (Italy); Marchianò, Alfonso, E-mail: alfonso.marchiano@istitutotumori.mi.it [Department of Radiology, Fondazione IRCCS Istituto Nazionale dei Tumori, Via Venezian 1, 20133 Milan (Italy); Silva, Mario, E-mail: mac.mario@hotmail.it [Department of Department of Surgical Sciences, Section of Diagnostic Imaging, University of Parma, Padiglione Barbieri, University Hospital of Parma, V. Gramsci 14, 43100 Parma (Italy); Kuhnigk, Jan-Martin, E-mail: Jan-Martin.Kuhnigk@mevis.fraunhofer.de [Fraunhofer MEVIS, Universitaetsallee 29, 28359 Bremen (Germany); La Vecchia, Carlo, E-mail: carlo.lavecchia@marionegri.it [Department of Occupational Health, University of Milan, Via Venezian 1, 20133 Milan (Italy); Zompatori, Maurizio, E-mail: maurizio.zompatori@unibo.it [Department of Radiology, Cardio-Thoracic Section, S. Orsola-Malpighi Hospital, Via Albertoni 15, 40138 Bologna (Italy); Pastorino, Ugo, E-mail: ugo.pastorino@istitutotumori.mi.it [Department of Surgery, Section of Thoracic Surgery, Fondazione IRCCS Istituto Nazionale dei Tumori, Via Venezian 1, 20133 Milan (Italy)

2013-08-15

Objectives: To investigate the relationship between emphysema phenotype, mean lung density (MLD), lung function and lung cancer by using an automated multiple feature analysis tool on thin-section computed tomography (CT) data. Methods: Both emphysema phenotype and MLD evaluated by automated quantitative CT analysis were compared between outpatients and screening participants with lung cancer (n = 119) and controls (n = 989). Emphysema phenotype was defined by assessing features such as extent, distribution on core/peel of the lung and hole size. Adjusted multiple logistic regression models were used to evaluate independent associations of CT densitometric measurements and pulmonary function test (PFT) with lung cancer risk. Results: No emphysema feature was associated with lung cancer. Lung cancer risk increased with decreasing values of forced expiratory volume in 1 s (FEV{sub 1}) independently of MLD (OR 5.37, 95% CI: 2.63–10.97 for FEV{sub 1} < 60% vs. FEV{sub 1} ≥ 90%), and with increasing MLD independently of FEV{sub 1} (OR 3.00, 95% CI: 1.60–5.63 for MLD > −823 vs. MLD < −857 Hounsfield units). Conclusion: Emphysema per se was not associated with lung cancer whereas decreased FEV{sub 1} was confirmed as being a strong and independent risk factor. The cross-sectional association between increased MLD and lung cancer requires future validations.

Architecture independent environment for developing engineering software on MIMD computers

Science.gov (United States)

Valimohamed, Karim A.; Lopez, L. A.

1990-01-01

Engineers are constantly faced with solving problems of increasing complexity and detail. Multiple Instruction stream Multiple Data stream (MIMD) computers have been developed to overcome the performance limitations of serial computers. The hardware architectures of MIMD computers vary considerably and are much more sophisticated than serial computers. Developing large scale software for a variety of MIMD computers is difficult and expensive. There is a need to provide tools that facilitate programming these machines. First, the issues that must be considered to develop those tools are examined. The two main areas of concern were architecture independence and data management. Architecture independent software facilitates software portability and improves the longevity and utility of the software product. It provides some form of insurance for the investment of time and effort that goes into developing the software. The management of data is a crucial aspect of solving large engineering problems. It must be considered in light of the new hardware organizations that are available. Second, the functional design and implementation of a software environment that facilitates developing architecture independent software for large engineering applications are described. The topics of discussion include: a description of the model that supports the development of architecture independent software; identifying and exploiting concurrency within the application program; data coherence; engineering data base and memory management.

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.

Providing Device Independence to Mobile Services

OpenAIRE

Nylander, Stina; Bylund, Markus

2002-01-01

People want user interfaces to services that are functional and well suited to the device they choose for access. To provide this, services must be able to offer device specific user interfaces for the wide range of devices available today. We propose to combine the two dominant approaches to platform independence, "Write Once, Run Every-where™" and "different version for each device", to create multiple device specific user interfaces for mobile services. This gives possibilities to minimize...

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

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

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.

Phonemes as short time cognitive components

DEFF Research Database (Denmark)

Feng, Ling; Hansen, Lars Kai

2006-01-01

are the smallest contrastive unit in the sound system of a language. Generalizable components were found deriving from phonemes based on homomorphic filtering features with basic time scale (20 msec). We sparsified the features based on energy as a preprocessing means to eliminate the intrinsic noise. Independent...

"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…

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.)

Multiple fMRI system-level baseline connectivity is disrupted in patients with consciousness alterations.

Science.gov (United States)

Demertzi, Athena; Gómez, Francisco; Crone, Julia Sophia; Vanhaudenhuyse, Audrey; Tshibanda, Luaba; Noirhomme, Quentin; Thonnard, Marie; Charland-Verville, Vanessa; Kirsch, Murielle; Laureys, Steven; Soddu, Andrea

2014-03-01

In healthy conditions, group-level fMRI resting state analyses identify ten resting state networks (RSNs) of cognitive relevance. Here, we aim to assess the ten-network model in severely brain-injured patients suffering from disorders of consciousness and to identify those networks which will be most relevant to discriminate between patients and healthy subjects. 300 fMRI volumes were obtained in 27 healthy controls and 53 patients in minimally conscious state (MCS), vegetative state/unresponsive wakefulness syndrome (VS/UWS) and coma. Independent component analysis (ICA) reduced data dimensionality. The ten networks were identified by means of a multiple template-matching procedure and were tested on neuronality properties (neuronal vs non-neuronal) in a data-driven way. Univariate analyses detected between-group differences in networks' neuronal properties and estimated voxel-wise functional connectivity in the networks, which were significantly less identifiable in patients. A nearest-neighbor "clinical" classifier was used to determine the networks with high between-group discriminative accuracy. Healthy controls were characterized by more neuronal components compared to patients in VS/UWS and in coma. Compared to healthy controls, fewer patients in MCS and VS/UWS showed components of neuronal origin for the left executive control network, default mode network (DMN), auditory, and right executive control network. The "clinical" classifier indicated the DMN and auditory network with the highest accuracy (85.3%) in discriminating patients from healthy subjects. FMRI multiple-network resting state connectivity is disrupted in severely brain-injured patients suffering from disorders of consciousness. When performing ICA, multiple-network testing and control for neuronal properties of the identified RSNs can advance fMRI system-level characterization. Automatic data-driven patient classification is the first step towards future single-subject objective diagnostics

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.

Innovative approaches for addressing old challenges in component importance measures

International Nuclear Information System (INIS)

Rocco S, Claudio M.; Ramirez-Marquez, Jose Emmanuel

2012-01-01

Importance measures (IM) are component related indices that allow assessing how a component in a system affects one or more system level performance functions. While several IM have been presented in the literature, challenges still remain with respect to the following: (1) multiple ranking—multiple perspective, (2) multi-component importance and, (3) multi-function importance. To address these challenges, this paper proposes set of innovative solutions based on several available techniques: Hasse diagram, Copeland score and Multi-objective optimization. As such, the purpose of this research is twofold: first propose solutions and second foster new research to address these challenges. Each of the proposed solutions is exemplified with a working example.

Design Environment for Multifidelity and Multidisciplinary Components

Science.gov (United States)

Platt, Michael

2014-01-01

One of the greatest challenges when developing propulsion systems is predicting the interacting effects between the fluid loads, thermal loads, and structural deflection. The interactions between technical disciplines often are not fully analyzed, and the analysis in one discipline often uses a simplified representation of other disciplines as an input or boundary condition. For example, the fluid forces in an engine generate static and dynamic rotor deflection, but the forces themselves are dependent on the rotor position and its orbit. It is important to consider the interaction between the physical phenomena where the outcome of each analysis is heavily dependent on the inputs (e.g., changes in flow due to deflection, changes in deflection due to fluid forces). A rigid design process also lacks the flexibility to employ multiple levels of fidelity in the analysis of each of the components. This project developed and validated an innovative design environment that has the flexibility to simultaneously analyze multiple disciplines and multiple components with multiple levels of model fidelity. Using NASA's open-source multidisciplinary design analysis and optimization (OpenMDAO) framework, this multifaceted system will provide substantially superior capabilities to current design tools.

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.

Developmental Trampoline Activities for Individuals with Multiple Handicapping Conditions.

Science.gov (United States)

Thomas, Bill

1979-01-01

The use of trampoline activities with multiple handicapped students is discussed. Management considerations in safety are noted, and developmental trampoline skills are listed beginning with bouncing for stimulation. Progression to limited independence and finally independent jumping is described. The position statement of the American Alliance…

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

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...

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.

[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.

Correlations in multiple production on nuclei and Glauber model of multiple scattering

International Nuclear Information System (INIS)

Zoller, V.R.; Nikolaev, N.N.

1982-01-01

Critical analysis of possibility for describing correlation phenomena during multiple production on nuclei within the framework of the Glauber multiple seattering model generalized for particle production processes with Capella, Krziwinski and Shabelsky has been performed. It was mainly concluded that the suggested generalization of the Glauber model gives dependences on Ng(Np) (where Ng-the number of ''grey'' tracess, and Np-the number of protons flying out of nucleus) and, eventually, on #betta# (where #betta#-the number of intranuclear interactions) contradicting experience. Independent of choice of relation between #betta# and Ng(Np) in the model the rapidity corrletor Rsub(eta) is overstated in the central region and understated in the region of nucleus fragmentation. In mean multiplicities these two contradictions of experience are disguised with random compensation and agreement with experience in Nsub(S) (function of Ng) cannot be an argument in favour of the model. It is concluded that eiconal model doesn't permit to quantitatively describe correlation phenomena during the multiple production on nuclei

Multiple sclerosis and herpesvirus interaction

Directory of Open Access Journals (Sweden)

Guilherme Sciascia do Olival

2013-09-01

Full Text Available Multiple sclerosis is the most common autoimmune inflammatory demyelinating disease of the central nervous system, and its etiology is believed to have both genetic and environmental components. Several viruses have already been implicated as triggers and there are several studies that implicate members of the Herpesviridae family in the pathogenesis of MS. The most important characteristic of these viruses is that they have periods of latency and exacerbations within their biological sanctuary, the central nervous system. The Epstein-Barr, cytomegalovirus, human herpesvirus 6 and human herpesvirus 7 viruses are the members that are most studied as being possible triggers of multiple sclerosis. According to evidence in the literature, the herpesvirus family is strongly involved in the pathogenesis of this disease, but it is unlikely that they are the only component responsible for its development. There are probably multiple triggers and more studies are necessary to investigate and define these interactions.

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

Automated phase picker and source location algorithm for local distances using a single three component seismic station

International Nuclear Information System (INIS)

Saari, J.

1989-12-01

The paper describes procedures for automatic location of local events by using single-site, three-component (3c) seismogram records. Epicentral distance is determined from the time difference between P- and S-onsets. For onset time estimates a special phase picker algorithm is introduced. Onset detection is accomplished by comparing short-term average with long-term average after multiplication of north, east and vertical components of recording. For epicentral distances up to 100 km, errors seldom exceed 5 km. The slowness vector, essentially the azimuth, is estimated independently by using the Christoffersson et al. (1988) 'polarization' technique, although a priori knowledge of the P-onset time gives the best results. Differences between 'true' and observed azimuths are generally less than 12 deg C. Practical examples are given by demonstrating the viability of the procedures for automated 3c seismogram analysis. The results obtained compare favourably with those achieved by a miniarray of three stations. (orig.)

Influence of intravenous self-administered psychomotor stimulants on performance of rhesus monkeys in a multiple schedule paradigm.

Science.gov (United States)

Hoffmeister, F

1980-01-01

Rhesus monkeys were trained to complete three multiple schedules. The schedules consisted of three components: a fixed interval (component 1), a variable interval (component 2), and a fixed ratio (component 3). During components 1 and 2, pressing lever 1 was always reinforced by food delivery. During component 3, pressing lever 2 resulted in either food delivery or intravenous infusions of saline solution, solutions of cocaine, of d-amphetamine, of phenmetrazine, or fenetylline. In schedule I, animals were presented with all three components independent of key-pressing behavior during components 1 and 2. In schedule II the availability of component 2 was dependent on completion of component 1. Component 3 was made available only on completion of component 2. Noncompletion of components 1 or 2 resulted in time-out of 15 and 10 min, respectively. Schedule III was identical with schedule II, except that in schedule III the completion of components was indicated only by a change in the lever lights. The influence of self-administered drugs on behavior in all three components was evaluated. Self-administration of psychomotor stimulants impaired the performance of animals and delayed completion of components 1 and 2 of schedules I, II, and III. The effects on behavior were similar with low drug intake in schedule III, moderate intake in schedule II, and high drug intake in schedule I. These effects were strong with self-administration of phenmetrazine, moderate with self-administration of cocaine and d-amphetamine, and weak with self-administration of fenetylline.

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

The Updated Multiple Star Catalog

Science.gov (United States)

Tokovinin, Andrei

2018-03-01

The catalog of hierarchical stellar systems with three or more components is an update of the original 1997 version. For 2000 hierarchies, the new Multiple Star Catalog (MSC) provides distances, component masses and periods, and supplementary information (astrometry, photometry, identifiers, orbits, notes). The MSC content and format are explained, and its incompleteness and strong observational selection are stressed. Nevertheless, the MSC can be used for statistical studies and is a valuable source for planning observations of multiple stars. Rare classes of stellar hierarchies found in the MSC (with six or seven components, extremely eccentric orbits, planar and possibly resonant orbits, hosting planets) are briefly presented. High-order hierarchies have smaller velocity dispersion compared to triples and are often associated with moving groups. The paper concludes with an analysis of the ratio of periods and separations between inner and outer subsystems. In wide hierarchies, the ratio of semimajor axes, estimated statistically, is distributed between 3 and 300, with no evidence of dynamically unstable systems.

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)

On Phonemes As Cognitive Components of Speech

DEFF Research Database (Denmark)

Feng, Ling; Hansen, Lars Kai

2008-01-01

. The basic features are 25-dimensional short time (20ms) melfrequency weighted cepstral coefficients. Features are integrated by means of stacking to obtain features at longer time scales. Energy based sparsification is carried out to achieve sparse representations. Our hypothesis is ecological: we assume...... that features that essentially independent in a context defined ensemble can be efficiently coded using a sparse independent component representation. This means that supervised and unsupervised learning should result in similar representations. We indeed find that supervised and unsupervised learning seem...

Failure characteristic analysis of a component on standby state

International Nuclear Information System (INIS)

Shin, Sungmin; Kang, Hyungook

2013-01-01

Periodic operations for a specific type of component, however, can accelerate aging effects which increase component unavailability. For the other type of components, the aging effect caused by operation can be ignored. Therefore frequent operations can decrease component unavailability. Thus, to get optimum unavailability proper operation period and method should be studied considering the failure characteristics of each component. The information of component failure is given according to the main causes of failure depending on time flow. However, to get the optimal unavailability, proper interval of operation for inspection should be decided considering the time dependent and independent causes together. According to this study, gradually shorter operation interval for inspection is better to get the optimal component unavailability than that of specific period

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.

Inverse comorbidity in multiple sclerosis

DEFF Research Database (Denmark)

Thormann, Anja; Koch-Henriksen, Nils; Laursen, Bjarne

2016-01-01

onset of MS 1980-2005. We randomly matched each MS-case with five population controls. Comorbidity data were obtained from multiple, independent nationwide registries. Cases and controls were followed from January 1977 to the index date, and from the index date through December 2012. We controlled...

Retrospective assessment of interobserver agreement and accuracy in classifications and measurements in subsolid nodules with solid components less than 8mm: which window setting is better?

Energy Technology Data Exchange (ETDEWEB)

Yoo, Roh-Eul [Seoul National University College of Medicine, Department of Radiology, Seoul (Korea, Republic of); Seoul National University Medical Research Center, Institute of Radiation Medicine, Seoul (Korea, Republic of); Goo, Jin Mo; Park, Chang Min [Seoul National University College of Medicine, Department of Radiology, Seoul (Korea, Republic of); Seoul National University College of Medicine, Cancer Research Institute, Seoul (Korea, Republic of); Hwang, Eui Jin; Yoon, Soon Ho; Lee, Chang Hyun [Seoul National University College of Medicine, Department of Radiology, Seoul (Korea, Republic of); Ahn, Soyeon [Seoul National University Bundang Hospital, Medical Research Collaborating Center, Seongnam-si (Korea, Republic of)

2017-04-15

To compare interobserver agreements among multiple readers and accuracy for the assessment of solid components in subsolid nodules between the lung and mediastinal window settings. Seventy-seven surgically resected nodules with solid components smaller than 8 mm were included in this study. In both lung and mediastinal windows, five readers independently assessed the presence and size of solid component. Bootstrapping was used to compare the interobserver agreement between the two window settings. Imaging-pathology correlation was performed to evaluate the accuracy. There were no significant differences in the interobserver agreements between the two windows for both identification (lung windows, k = 0.51; mediastinal windows, k = 0.57) and measurements (lung windows, ICC = 0.70; mediastinal windows, ICC = 0.69) of solid components. The incidence of false negative results for the presence of invasive components and the median absolute difference between the solid component size and the invasive component size were significantly higher on mediastinal windows than on lung windows (P < 0.001 and P < 0.001, respectively). The lung window setting had a comparable reproducibility but a higher accuracy than the mediastinal window setting for nodule classifications and solid component measurements in subsolid nodules. (orig.)

Mean charged hadron multiplicities in high-energy collisions

Energy Technology Data Exchange (ETDEWEB)

Albini, E [Istituto di Matematica dell' Universita Cattolica di Brescia (Italy); Capiluppi, P; Giacomelli, G; Rossi, A M [Bologna Univ. (Italy). Istituto di Fisica

1976-03-01

A collection of mean charged hadron multiplicities per inelastic collision in various high-energy processes is presented. An extensive list of fits of as a function of energy is presented and discussed. As the energy increases the multiplicities for different collisions tend to a unique curve, independent of the type of colliding particles.

The future of the independent Egyptian music in the digital era

OpenAIRE

Maraghah, Mohammad

2013-01-01

Master's thesis in music management - University of Agder 2013 This thesis is investigating the impact of the digital era with its technological advanced components and revolutionized information platforms on shaping the future of the independent Egyptian music. The author investigated this impact through conducting fifteen semi structured qualitative interviews between the 15th of December 2012 to 25th of January 2013 with the relevant Independent Egyptian Music stakeholders who gave the ...

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

Hierarchical modeling of systems with similar components: A framework for adaptive monitoring and control

International Nuclear Information System (INIS)

Memarzadeh, Milad; Pozzi, Matteo; Kolter, J. Zico

2016-01-01

System management includes the selection of maintenance actions depending on the available observations: when a system is made up by components known to be similar, data collected on one is also relevant for the management of others. This is typically the case of wind farms, which are made up by similar turbines. Optimal management of wind farms is an important task due to high cost of turbines' operation and maintenance: in this context, we recently proposed a method for planning and learning at system-level, called PLUS, built upon the Partially Observable Markov Decision Process (POMDP) framework, which treats transition and emission probabilities as random variables, and is therefore suitable for including model uncertainty. PLUS models the components as independent or identical. In this paper, we extend that formulation, allowing for a weaker similarity among components. The proposed approach, called Multiple Uncertain POMDP (MU-POMDP), models the components as POMDPs, and assumes the corresponding parameters as dependent random variables. Through this framework, we can calibrate specific degradation and emission models for each component while, at the same time, process observations at system-level. We compare the performance of the proposed MU-POMDP with PLUS, and discuss its potential and computational complexity. - Highlights: • A computational framework is proposed for adaptive monitoring and control. • It adopts a scheme based on Markov Chain Monte Carlo for inference and learning. • Hierarchical Bayesian modeling is used to allow a system-level flow of information. • Results show potential of significant savings in management of wind farms.

Identification of Known and Novel Recurrent Viral Sequences in Data from Multiple Patients and Multiple Cancers

DEFF Research Database (Denmark)

Friis-Nielsen, Jens; Kjartansdóttir, Kristín Rós; Mollerup, Sarah

2016-01-01

have developed a species independent pipeline that utilises sequence clustering for the identification of nucleotide sequences that co-occur across multiple sequencing data instances. We applied the workflow to 686 sequencing libraries from 252 cancer samples of different cancer and tissue types, 32...

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.

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.

A Removal of Eye Movement and Blink Artifacts from EEG Data Using Morphological Component Analysis

Directory of Open Access Journals (Sweden)

Balbir Singh

2017-01-01

Full Text Available EEG signals contain a large amount of ocular artifacts with different time-frequency properties mixing together in EEGs of interest. The artifact removal has been substantially dealt with by existing decomposition methods known as PCA and ICA based on the orthogonality of signal vectors or statistical independence of signal components. We focused on the signal morphology and proposed a systematic decomposition method to identify the type of signal components on the basis of sparsity in the time-frequency domain based on Morphological Component Analysis (MCA, which provides a way of reconstruction that guarantees accuracy in reconstruction by using multiple bases in accordance with the concept of “dictionary.” MCA was applied to decompose the real EEG signal and clarified the best combination of dictionaries for this purpose. In our proposed semirealistic biological signal analysis with iEEGs recorded from the brain intracranially, those signals were successfully decomposed into original types by a linear expansion of waveforms, such as redundant transforms: UDWT, DCT, LDCT, DST, and DIRAC. Our result demonstrated that the most suitable combination for EEG data analysis was UDWT, DST, and DIRAC to represent the baseline envelope, multifrequency wave-forms, and spiking activities individually as representative types of EEG morphologies.

A Removal of Eye Movement and Blink Artifacts from EEG Data Using Morphological Component Analysis

Science.gov (United States)

Wagatsuma, Hiroaki

2017-01-01

EEG signals contain a large amount of ocular artifacts with different time-frequency properties mixing together in EEGs of interest. The artifact removal has been substantially dealt with by existing decomposition methods known as PCA and ICA based on the orthogonality of signal vectors or statistical independence of signal components. We focused on the signal morphology and proposed a systematic decomposition method to identify the type of signal components on the basis of sparsity in the time-frequency domain based on Morphological Component Analysis (MCA), which provides a way of reconstruction that guarantees accuracy in reconstruction by using multiple bases in accordance with the concept of “dictionary.” MCA was applied to decompose the real EEG signal and clarified the best combination of dictionaries for this purpose. In our proposed semirealistic biological signal analysis with iEEGs recorded from the brain intracranially, those signals were successfully decomposed into original types by a linear expansion of waveforms, such as redundant transforms: UDWT, DCT, LDCT, DST, and DIRAC. Our result demonstrated that the most suitable combination for EEG data analysis was UDWT, DST, and DIRAC to represent the baseline envelope, multifrequency wave-forms, and spiking activities individually as representative types of EEG morphologies. PMID:28194221

Independence of Terminal-Link Entry Rate and Immediacy in Concurrent Chains

Science.gov (United States)

Berg, Mark E.; Grace, Randolph C.

2004-01-01

In Phase 1, 4 pigeons were trained on a three-component multiple concurrent-chains procedure in which components differed only in terms of relative terminal-link entry rate. The terminal links were variable-interval schedules and were varied across four conditions to produce immediacy ratios of 4:1, 1:4, 2:1, and 1:2. Relative terminal-link entry…

Robust Tests for Additive Gene-Environment Interaction in Case-Control Studies Using Gene-Environment Independence

DEFF Research Database (Denmark)

Liu, Gang; Lee, Seunggeun; Lee, Alice W

2018-01-01

test with case-control data. Our simulation studies suggest that the EB approach uses the gene-environment independence assumption in a data-adaptive way and provides power gain compared to the standard logistic regression analysis and better control of Type I error when compared to the analysis......There have been recent proposals advocating the use of additive gene-environment interaction instead of the widely used multiplicative scale, as a more relevant public health measure. Using gene-environment independence enhances the power for testing multiplicative interaction in case......-control studies. However, under departure from this assumption, substantial bias in the estimates and inflated Type I error in the corresponding tests can occur. This paper extends the empirical Bayes (EB) approach previously developed for multiplicative interaction that trades off between bias and efficiency...

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...

Factor Structure of Indices of the Second Derivative of the Finger Photoplethysmogram with Metabolic Components and Other Cardiovascular Risk Indicators

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Tomoyuki Kawada

2013-02-01

Full Text Available BackgroundThe second derivative of the finger photoplethysmogram (SDPTG is an indicator of arterial stiffness. The present study was conducted to clarify the factor structure of indices of the SDPTG in combination with components of the metabolic syndrome (MetS, to elucidate the significance of the SDPTG among various cardiovascular risk factors.MethodsThe SDPTG was determined in the second forefinger of the left hand in 1,055 male workers (mean age, 44.2±6.4 years. Among 4 waves of SDPTG components, the ratios of the height of the "a" wave to that of the "b" and "d" waves were expressed as b/a and d/a, and used as SDPTG indices for the analysis.ResultsPrincipal axis factoring analysis was conducted using age, SDPTG indices, components of MetS, and the serum levels of C-reactive protein (CRP and uric acid. Three factors were extracted, and the SDPTG indices were categorized in combination with age as the third factor. Metabolic components and the SDPTG indices were independently categorized. These three factors explained 44.4% of the total variation. Multiple logistic regression analysis revealed age, d/a, serum uric acid, serum CRP, and regular exercise as independent determinants of the risk of MetS. The odds ratios (95% confidence intervals were 1.08 (1.04 to 1.11, 0.10 (0.01 to 0.73, 1.24 (1.06 to 1.44, 3.59 (2.37 to 5.42, and 0.48 (0.28 to 0.82, respectively.ConclusionThe SDPTG indices were categorized in combination with age, and they differed in characteristics from components of MetS or inflammatory markers. In addition, this cross-sectional study also revealed decrease of the d/a as a risk factor for the development of MetS.

EPICS: operating system independent device/driver support

International Nuclear Information System (INIS)

Kraimer, M.R.

2003-01-01

Originally EPICS input/output controllers (IOCs) were only supported on VME-based systems running the vxWorks operating system. Now IOCs are supported on many systems: vxWorks, RTEMS, Solaris, HPUX, Linux, WIN32, and Darwin. A challenge is to provide operating-system-independent device and driver support. This paper presents some techniques for providing such support. EPICS (Experimental Physics and Industrial Control System) is a set of software tools, libraries, and applications developed collaboratively and used worldwide to create distributed, real-time control systems for scientific instruments such as particle accelerators, telescopes, and other large scientific experiments. An important component of all EPICS-based control systems is a collection of input/output controllers (IOCs). An IOC has three primary components: (1) a real-time database; (2) channel access, which provides network access to the database; and (3) device/driver support for interfacing to equipment. This paper describes some projects related to providing device/driver support on non-vxWorks systems. In order to support IOCs on platforms other than vxWorks, operating-system-independent (OSI) application program interfaces (APIs) were defined for threads, semaphores, timers, etc. Providing support for a new platform consists of providing an operating-system-dependent implementation of the OSI APIs.

Multiple electron processes of He and Ne by proton impact

Science.gov (United States)

Terekhin, Pavel Nikolaevich; Montenegro, Pablo; Quinto, Michele; Monti, Juan; Fojon, Omar; Rivarola, Roberto

2016-05-01

A detailed investigation of multiple electron processes (single and multiple ionization, single capture, transfer-ionization) of He and Ne is presented for proton impact at intermediate and high collision energies. Exclusive absolute cross sections for these processes have been obtained by calculation of transition probabilities in the independent electron and independent event models as a function of impact parameter in the framework of the continuum distorted wave-eikonal initial state theory. A binomial analysis is employed to calculate exclusive probabilities. The comparison with available theoretical and experimental results shows that exclusive probabilities are needed for a reliable description of the experimental data. The developed approach can be used for obtaining the input database for modeling multiple electron processes of charged particles passing through the matter.

Multiplicity: An Explorative Interview Study on Personal Experiences of People with Multiple Selves.

Science.gov (United States)

Ribáry, Gergő; Lajtai, László; Demetrovics, Zsolt; Maraz, Aniko

2017-01-01

Background and aims: Personality psychology research relies on the notion that humans have a single self that is the result of the individual's thoughts, feelings, and behaviors that can be reliably described (i.e., through traits). People who identify themselves as "multiple" have a system of multiple or alternative, selves, that share the same physical body. This is the first study to explore the phenomenon of multiplicity by assessing the experiences of people who identify themselves as "multiple." Methods: First, an Internet forum search was performed using the terms "multiplicity" and "multiple system." Based on that search, people who identified themselves as multiple were contacted. Interviews were conducted by a consultant psychiatrist, which produced six case vignettes. Results: Multiplicity is discussed on Twitter, Tumblr, Google+ and several other personal websites, blogs, and forums maintained by multiples. According to the study's estimates, there are 200-300 individuals who participate in these forums and believe they are multiple. Based on the six interviews, it appears that multiples have several selves who are relatively independent of each other and constitute the personality's system. Each "resident person" or self, has their own unique behavioral pattern, which is triggered by different situations. However, multiples are a heterogeneous group in terms of their system organization, memory functions, and control over switching between selves. Conclusions: Multiplicity can be placed along a continuum between identity disturbance and dissociative identity disorder (DID), although most systems function relatively well in everyday life. Further research is needed to explore this phenomenon, especially in terms of the extent to which multiplicity can be regarded as a healthy way of coping.

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

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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…

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.

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.

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.

Anisotropic magnetoresistance components in (Ga,Mn)As.

Science.gov (United States)

Rushforth, A W; Výborný, K; King, C S; Edmonds, K W; Campion, R P; Foxon, C T; Wunderlich, J; Irvine, A C; Vasek, P; Novák, V; Olejník, K; Sinova, Jairo; Jungwirth, T; Gallagher, B L

2007-10-05

We explore the basic physical origins of the noncrystalline and crystalline components of the anisotropic magnetoresistance (AMR) in (Ga,Mn)As. The sign of the noncrystalline AMR is found to be determined by the form of spin-orbit coupling in the host band and by the relative strengths of the nonmagnetic and magnetic contributions to the Mn impurity potential. We develop experimental methods yielding directly the noncrystalline and crystalline AMR components which are then analyzed independently. We report the observation of an AMR dominated by a large uniaxial crystalline component and show that AMR can be modified by local strain relaxation. Generic implications of our findings for other dilute moment systems are discussed.

Principal components analysis in clinical studies.

Science.gov (United States)

Zhang, Zhongheng; Castelló, Adela

2017-09-01

In multivariate analysis, independent variables are usually correlated to each other which can introduce multicollinearity in the regression models. One approach to solve this problem is to apply principal components analysis (PCA) over these variables. This method uses orthogonal transformation to represent sets of potentially correlated variables with principal components (PC) that are linearly uncorrelated. PCs are ordered so that the first PC has the largest possible variance and only some components are selected to represent the correlated variables. As a result, the dimension of the variable space is reduced. This tutorial illustrates how to perform PCA in R environment, the example is a simulated dataset in which two PCs are responsible for the majority of the variance in the data. Furthermore, the visualization of PCA is highlighted.

VEGF-independent angiogenic pathways induced by PDGF-C

Science.gov (United States)

Kumar, Anil; Zhang, Fan; Lee, Chunsik; Li, Yang; Tang, Zhongshu; Arjunan, Pachiappan

2010-01-01

VEGF is believed to be a master regulator in both developmental and pathological angiogenesis. The role of PDGF-C in angiogenesis, however, is only at the beginning of being revealed. We and others have shown that PDGF-C is a critical player in pathological angiogenesis because of its pleiotropic effects on multiple cellular targets. The angiogenic pathways induced by PDGF-C are, to a large extent, VEGF-independent. These pathways may include, but not limited to, the direct effect of PDGF-C on vascular cells, the effect of PDGF-C on tissue stroma fibroblasts, and its effect on macrophages. Taken together, the pleiotropic, versatile and VEGF-independent angiogenic nature of PDGF-C has placed it among the most important target genes for antiangiogenic therapy. PMID:20871734

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.

Cooking for Independence: Middle School Students Gain Skills While Cooking

Science.gov (United States)

Mixon, Gloria

2011-01-01

Middle school students with intellectual disabilities often have difficulties achieving independence with instrumental activities of daily living (IADLs); therefore, these skills must be taught in school. IADLs are a complex component of skills that require a higher level of cognitive reasoning such as community mobility, shopping, meal…

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.

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.

On criteria for algebraic independence of collections of functions satisfying algebraic difference relations

Directory of Open Access Journals (Sweden)

Hiroshi Ogawara

2017-01-01

Full Text Available This paper gives conditions for algebraic independence of a collection of functions satisfying a certain kind of algebraic difference relations. As applications, we show algebraic independence of two collections of special functions: (1 Vignéras' multiple gamma functions and derivatives of the gamma function, (2 the logarithmic function, \\(q\\-exponential functions and \\(q\\-polylogarithm functions. In a similar way, we give a generalization of Ostrowski's theorem.

Observation of laser multiple filamentation process and multiple electron beams acceleration in a laser wakefield accelerator

International Nuclear Information System (INIS)

Li, Wentao; Liu, Jiansheng; Wang, Wentao; Chen, Qiang; Zhang, Hui; Tian, Ye; Zhang, Zhijun; Qi, Rong; Wang, Cheng; Leng, Yuxin; Li, Ruxin; Xu, Zhizhan

2013-01-01

The multiple filaments formation process in the laser wakefield accelerator (LWFA) was observed by imaging the transmitted laser beam after propagating in the plasma of different density. During propagation, the laser first self-focused into a single filament. After that, it began to defocus with energy spreading in the transverse direction. Two filaments then formed from it and began to propagate independently, moving away from each other. We have also demonstrated that the laser multiple filamentation would lead to the multiple electron beams acceleration in the LWFA via ionization-induced injection scheme. Besides, its influences on the accelerated electron beams were also analyzed both in the single-stage LWFA and cascaded LWFA

Hydrogen Production Cost Estimate Using Biomass Gasification: Independent Review

Energy Technology Data Exchange (ETDEWEB)

Ruth, M.

2011-10-01

This independent review is the conclusion arrived at from data collection, document reviews, interviews and deliberation from December 2010 through April 2011 and the technical potential of Hydrogen Production Cost Estimate Using Biomass Gasification. The Panel reviewed the current H2A case (Version 2.12, Case 01D) for hydrogen production via biomass gasification and identified four principal components of hydrogen levelized cost: CapEx; feedstock costs; project financing structure; efficiency/hydrogen yield. The panel reexamined the assumptions around these components and arrived at new estimates and approaches that better reflect the current technology and business environments.

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

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

Gait initiation time is associated with the risk of multiple falls-A population-based study.

Science.gov (United States)

Callisaya, Michele L; Blizzard, Leigh; Martin, Kara; Srikanth, Velandai K

2016-09-01

In a population-based study of older people to examine whether 1) overall gait initiation (GI) time or its components are associated with falls and 2) GI under dual-task is a stronger predictor of falls risk than under single-task. Participants aged 60-85 years were randomly selected from the electoral roll. GI was obtained with a force platform under both single and dual-task conditions. Falls were ascertained prospectively over a 12-month period. Log multinomial regression was used to examine the association between GI time (total and its components) and risk of single and multiple falls. Age, sex and physiological and cognitive falls risk factors were considered as confounders. The mean age of the sample (n=124) was 71.0 (SD 6.8) years and 58.9% (n=73) were male. Over 12 months 21.8% (n=27) of participants reported a single fall and 16.1% (n=20) reported multiple falls. Slower overall GI time under both single (RR all per 100ms 1.28, 95%CI 1.03, 1.58) and dual-task (RR 1.14, 95%CI 1.02, 1.27) was associated with increased risk of multiple, but not single falls (pfalls were also associated with slower time to first lateral movement under single-task (RR 1.90 95%CI 0.59, 1.51) and swing time under dual-task condition (RR 1.44 95%CI 1.08, 1.94). Slower GI time is associated with the risk of multiple falls independent of other risk factors, suggesting it could be used as part of a comprehensive falls assessment. Time to the first lateral movement under single-task may be the best measures of this risk. Copyright © 2016 Elsevier B.V. All rights reserved.

Effects of PECS Phase III Application Training on Independent Mands in Young Children with Autism

Science.gov (United States)

Love, Jessica June

2013-01-01

The purpose of this study was to examine the effects of PECS phase III application training on independent mands in young children with autism. Participants were five children with autism ranging from ages 2 to 4 years old. A multiple baseline across participants was used to evaluate acquisition of independent correct mands across baseline and…

Multiplicity: An Explorative Interview Study on Personal Experiences of People with Multiple Selves

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Gergő Ribáry

2017-06-01

Full Text Available Background and aims: Personality psychology research relies on the notion that humans have a single self that is the result of the individual's thoughts, feelings, and behaviors that can be reliably described (i.e., through traits. People who identify themselves as “multiple” have a system of multiple or alternative, selves, that share the same physical body. This is the first study to explore the phenomenon of multiplicity by assessing the experiences of people who identify themselves as “multiple.”Methods: First, an Internet forum search was performed using the terms “multiplicity” and “multiple system.” Based on that search, people who identified themselves as multiple were contacted. Interviews were conducted by a consultant psychiatrist, which produced six case vignettes.Results: Multiplicity is discussed on Twitter, Tumblr, Google+ and several other personal websites, blogs, and forums maintained by multiples. According to the study's estimates, there are 200–300 individuals who participate in these forums and believe they are multiple. Based on the six interviews, it appears that multiples have several selves who are relatively independent of each other and constitute the personality's system. Each “resident person” or self, has their own unique behavioral pattern, which is triggered by different situations. However, multiples are a heterogeneous group in terms of their system organization, memory functions, and control over switching between selves.Conclusions: Multiplicity can be placed along a continuum between identity disturbance and dissociative identity disorder (DID, although most systems function relatively well in everyday life. Further research is needed to explore this phenomenon, especially in terms of the extent to which multiplicity can be regarded as a healthy way of coping.

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

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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

Existence of multiple receptors in single neurons: responses of single bullfrog olfactory neurons to many cAMP-dependent and independent odorants.

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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.

Pipecolic Acid Orchestrates Plant Systemic Acquired Resistance and Defense Priming via Salicylic Acid-Dependent and -Independent Pathways.

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Bernsdorff, Friederike; Döring, Anne-Christin; Gruner, Katrin; Schuck, Stefan; Bräutigam, Andrea; Zeier, Jürgen

2016-01-01

We investigated the relationships of the two immune-regulatory plant metabolites, salicylic acid (SA) and pipecolic acid (Pip), in the establishment of plant systemic acquired resistance (SAR), SAR-associated defense priming, and basal immunity. Using SA-deficient sid2, Pip-deficient ald1, and sid2 ald1 plants deficient in both SA and Pip, we show that SA and Pip act both independently from each other and synergistically in Arabidopsis thaliana basal immunity to Pseudomonas syringae. Transcriptome analyses reveal that SAR establishment in Arabidopsis is characterized by a strong transcriptional response systemically induced in the foliage that prepares plants for future pathogen attack by preactivating multiple stages of defense signaling and that SA accumulation upon SAR activation leads to the downregulation of photosynthesis and attenuated jasmonate responses systemically within the plant. Whereas systemic Pip elevations are indispensable for SAR and necessary for virtually the whole transcriptional SAR response, a moderate but significant SA-independent component of SAR activation and SAR gene expression is revealed. During SAR, Pip orchestrates SA-dependent and SA-independent priming of pathogen responses in a FLAVIN-DEPENDENT-MONOOXYGENASE1 (FMO1)-dependent manner. We conclude that a Pip/FMO1 signaling module acts as an indispensable switch for the activation of SAR and associated defense priming events and that SA amplifies Pip-triggered responses to different degrees in the distal tissue of SAR-activated plants. © 2016 American Society of Plant Biologists. All rights reserved.

A gaze independent hybrid-BCI based on visual spatial attention

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Egan, John M.; Loughnane, Gerard M.; Fletcher, Helen; Meade, Emma; Lalor, Edmund C.

2017-08-01

Objective. Brain-computer interfaces (BCI) use measures of brain activity to convey a user’s intent without the need for muscle movement. Hybrid designs, which use multiple measures of brain activity, have been shown to increase the accuracy of BCIs, including those based on EEG signals reflecting covert attention. Our study examined whether incorporating a measure of the P3 response improved the performance of a previously reported attention-based BCI design that incorporates measures of steady-state visual evoked potentials (SSVEP) and alpha band modulations. Approach. Subjects viewed stimuli consisting of two bi-laterally located flashing white boxes on a black background. Streams of letters were presented sequentially within the boxes, in random order. Subjects were cued to attend to one of the boxes without moving their eyes, and they were tasked with counting the number of target-letters that appeared within. P3 components evoked by target appearance, SSVEPs evoked by the flashing boxes, and power in the alpha band are modulated by covert attention, and the modulations can be used to classify trials as left-attended or right-attended. Main Results. We showed that classification accuracy was improved by including a P3 feature along with the SSVEP and alpha features (the inclusion of a P3 feature lead to a 9% increase in accuracy compared to the use of SSVEP and Alpha features alone). We also showed that the design improves the robustness of BCI performance to individual subject differences. Significance. These results demonstrate that incorporating multiple neurophysiological indices of covert attention can improve performance in a gaze-independent BCI.

Mechanisms of component diffusion in mercury cadmium telluride

International Nuclear Information System (INIS)

Tang, M.S.; Stevenson, D.A.

1989-01-01

The component diffusion coefficients for the Hg/sub 0.8/Cd/sub 0.2/Te (MCT) system are measured using radioactive tracers. Multiple branches are observed in the tracer diffusion profiles which are related to fast and slow-diffusing components. Diffusion models for each component are proposed based on the defect chemistry of MCT, a calculation of the thermodynamic factor, and the relationship between component diffusion coefficients and the interdiffusion coefficients for pseudobinary systems. The model provides insight into the thermodynamic properties of the system, the mechanisms for diffusion, and the practical application of tracer diffusion data to interdiffusion and p-to-n conversion by Hg annealing

Independent Living Services and the Educational Motivation of Foster Youth

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Eriamiatoe, Osarumen Rachel

2011-01-01

The purpose of this qualitative study was to examine the components of independent living training and services to determine their effectiveness in preparing foster youth in Tennessee for adulthood, and whether the youth's perceived effectiveness of these services affected their educational motivation. Support factors (i.e., family, financial,…

Two component systems: physiological effect of a third component.

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Baldiri Salvado

Full Text Available Signal transduction systems mediate the response and adaptation of organisms to environmental changes. In prokaryotes, this signal transduction is often done through Two Component Systems (TCS. These TCS are phosphotransfer protein cascades, and in their prototypical form they are composed by a kinase that senses the environmental signals (SK and by a response regulator (RR that regulates the cellular response. This basic motif can be modified by the addition of a third protein that interacts either with the SK or the RR in a way that could change the dynamic response of the TCS module. In this work we aim at understanding the effect of such an additional protein (which we call "third component" on the functional properties of a prototypical TCS. To do so we build mathematical models of TCS with alternative designs for their interaction with that third component. These mathematical models are analyzed in order to identify the differences in dynamic behavior inherent to each design, with respect to functionally relevant properties such as sensitivity to changes in either the parameter values or the molecular concentrations, temporal responsiveness, possibility of multiple steady states, or stochastic fluctuations in the system. The differences are then correlated to the physiological requirements that impinge on the functioning of the TCS. This analysis sheds light on both, the dynamic behavior of synthetically designed TCS, and the conditions under which natural selection might favor each of the designs. We find that a third component that modulates SK activity increases the parameter space where a bistable response of the TCS module to signals is possible, if SK is monofunctional, but decreases it when the SK is bifunctional. The presence of a third component that modulates RR activity decreases the parameter space where a bistable response of the TCS module to signals is possible.

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...

The Relationship Between Problem Size and Fixation Patterns During Addition, Subtraction, Multiplication, and Division

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Evan T. Curtis

2016-08-01

Full Text Available Eye-tracking methods have only rarely been used to examine the online cognitive processing that occurs during mental arithmetic on simple arithmetic problems, that is, addition and multiplication problems with single-digit operands (e.g., operands 2 through 9; 2 + 3, 6 x 8 and the inverse subtraction and division problems (e.g., 5 – 3; 48 ÷ 6. Participants (N = 109 solved arithmetic problems from one of the four operations while their eye movements were recorded. We found three unique fixation patterns. During addition and multiplication, participants allocated half of their fixations to the operator and one-quarter to each operand, independent of problem size. The pattern was similar on small subtraction and division problems. However, on large subtraction problems, fixations were distributed approximately evenly across the three stimulus components. On large division problems, over half of the fixations occurred on the left operand, with the rest distributed between the operation sign and the right operand. We discuss the relations between these eye tracking patterns and other research on the differences in processing across arithmetic operations.