Terahertz emission from thermally-managed square intrinsic Josephson junction microstrip antennas

NASA Astrophysics Data System (ADS)

Klemm, Richard; Davis, Andrew; Wang, Qing

We show for thin square microstrip antennas that the transverse magnetic electromagnetic cavity modes are greatly restricted in number due to the point group symmetry of a square. For the ten lowest frequency emissions, we present plots of the orthonormal wave functions and of the angular distributions of the emission power obtained from the uniform Josephson current source and from the excitation of an electromagnetic cavity mode excited in the intrinsic Josephson junctions between the layers of a highly anisotropic layered superconductor.

Tool Wear Feature Extraction Based on Hilbert Marginal Spectrum

NASA Astrophysics Data System (ADS)

Guan, Shan; Song, Weijie; Pang, Hongyang

2017-09-01

In the metal cutting process, the signal contains a wealth of tool wear state information. A tool wear signal’s analysis and feature extraction method based on Hilbert marginal spectrum is proposed. Firstly, the tool wear signal was decomposed by empirical mode decomposition algorithm and the intrinsic mode functions including the main information were screened out by the correlation coefficient and the variance contribution rate. Secondly, Hilbert transform was performed on the main intrinsic mode functions. Hilbert time-frequency spectrum and Hilbert marginal spectrum were obtained by Hilbert transform. Finally, Amplitude domain indexes were extracted on the basis of the Hilbert marginal spectrum and they structured recognition feature vector of tool wear state. The research results show that the extracted features can effectively characterize the different wear state of the tool, which provides a basis for monitoring tool wear condition.

Detecting intrinsic dynamics of traffic flow with recurrence analysis and empirical mode decomposition

NASA Astrophysics Data System (ADS)

Xiong, Hui; Shang, Pengjian; Bian, Songhan

2017-05-01

In this paper, we apply the empirical mode decomposition (EMD) method to the recurrence plot (RP) and recurrence quantification analysis (RQA), to evaluate the frequency- and time-evolving dynamics of the traffic flow. Based on the cumulative intrinsic mode functions extracted by the EMD, the frequency-evolving RP regarding different oscillation of modes suggests that apparent dynamics of the data considered are mainly dominated by its components of medium- and low-frequencies while severely affected by fast oscillated noises contained in the signal. Noises are then eliminated to analyze the intrinsic dynamics and consequently, the denoised time-evolving RQA diversely characterizes the properties of the signal and marks crucial points more accurately where white bands in the RP occur, whereas a strongly qualitative agreement exists between all the non-denoised RQA measures. Generally, the EMD combining with the recurrence analysis sheds more reliable, abundant and inherent lights into the traffic flow, which is meaningful to the empirical analysis of complex systems.

Global Dynamics of Proteins: Bridging Between Structure and Function

PubMed Central

Bahar, Ivet; Lezon, Timothy R.; Yang, Lee-Wei; Eyal, Eran

2010-01-01

Biomolecular systems possess unique, structure-encoded dynamic properties that underlie their biological functions. Recent studies indicate that these dynamic properties are determined to a large extent by the topology of native contacts. In recent years, elastic network models used in conjunction with normal mode analyses have proven to be useful for elucidating the collective dynamics intrinsically accessible under native state conditions, including in particular the global modes of motions that are robustly defined by the overall architecture. With increasing availability of structural data for well-studied proteins in different forms (liganded, complexed, or free), there is increasing evidence in support of the correspondence between functional changes in structures observed in experiments and the global motions predicted by these coarse-grained analyses. These observed correlations suggest that computational methods may be advantageously employed for assessing functional changes in structure and allosteric mechanisms intrinsically favored by the native fold. PMID:20192781

Global dynamics of proteins: bridging between structure and function.

PubMed

Bahar, Ivet; Lezon, Timothy R; Yang, Lee-Wei; Eyal, Eran

2010-01-01

Biomolecular systems possess unique, structure-encoded dynamic properties that underlie their biological functions. Recent studies indicate that these dynamic properties are determined to a large extent by the topology of native contacts. In recent years, elastic network models used in conjunction with normal mode analyses have proven to be useful for elucidating the collective dynamics intrinsically accessible under native state conditions, including in particular the global modes of motions that are robustly defined by the overall architecture. With increasing availability of structural data for well-studied proteins in different forms (liganded, complexed, or free), there is increasing evidence in support of the correspondence between functional changes in structures observed in experiments and the global motions predicted by these coarse-grained analyses. These observed correlations suggest that computational methods may be advantageously employed for assessing functional changes in structure and allosteric mechanisms intrinsically favored by the native fold.

Image fusion method based on regional feature and improved bidimensional empirical mode decomposition

NASA Astrophysics Data System (ADS)

Qin, Xinqiang; Hu, Gang; Hu, Kai

2018-01-01

The decomposition of multiple source images using bidimensional empirical mode decomposition (BEMD) often produces mismatched bidimensional intrinsic mode functions, either by their number or their frequency, making image fusion difficult. A solution to this problem is proposed using a fixed number of iterations and a union operation in the sifting process. By combining the local regional features of the images, an image fusion method has been developed. First, the source images are decomposed using the proposed BEMD to produce the first intrinsic mode function (IMF) and residue component. Second, for the IMF component, a selection and weighted average strategy based on local area energy is used to obtain a high-frequency fusion component. Third, for the residue component, a selection and weighted average strategy based on local average gray difference is used to obtain a low-frequency fusion component. Finally, the fused image is obtained by applying the inverse BEMD transform. Experimental results show that the proposed algorithm provides superior performance over methods based on wavelet transform, line and column-based EMD, and complex empirical mode decomposition, both in terms of visual quality and objective evaluation criteria.

Graphene, a material for high temperature devices – intrinsic carrier density, carrier drift velocity, and lattice energy

PubMed Central

Yin, Yan; Cheng, Zengguang; Wang, Li; Jin, Kuijuan; Wang, Wenzhong

2014-01-01

Heat has always been a killing matter for traditional semiconductor machines. The underlining physical reason is that the intrinsic carrier density of a device made from a traditional semiconductor material increases very fast with a rising temperature. Once reaching a temperature, the density surpasses the chemical doping or gating effect, any p-n junction or transistor made from the semiconductor will fail to function. Here, we measure the intrinsic Fermi level (|EF| = 2.93 kBT) or intrinsic carrier density (nin = 3.87 × 106 cm−2K−2·T2), carrier drift velocity, and G mode phonon energy of graphene devices and their temperature dependencies up to 2400 K. Our results show intrinsic carrier density of graphene is an order of magnitude less sensitive to temperature than those of Si or Ge, and reveal the great potentials of graphene as a material for high temperature devices. We also observe a linear decline of saturation drift velocity with increasing temperature, and identify the temperature coefficients of the intrinsic G mode phonon energy. Above knowledge is vital in understanding the physical phenomena of graphene under high power or high temperature. PMID:25044003

Computing frequency by using generalized zero-crossing applied to intrinsic mode functions

NASA Technical Reports Server (NTRS)

Huang, Norden E. (Inventor)

2006-01-01

This invention presents a method for computing Instantaneous Frequency by applying Empirical Mode Decomposition to a signal and using Generalized Zero-Crossing (GZC) and Extrema Sifting. The GZC approach is the most direct, local, and also the most accurate in the mean. Furthermore, this approach will also give a statistical measure of the scattering of the frequency value. For most practical applications, this mean frequency localized down to quarter of a wave period is already a well-accepted result. As this method physically measures the period, or part of it, the values obtained can serve as the best local mean over the period to which it applies. Through Extrema Sifting, instead of the cubic spline fitting, this invention constructs the upper envelope and the lower envelope by connecting local maxima points and local minima points of the signal with straight lines, respectively, when extracting a collection of Intrinsic Mode Functions (IMFs) from a signal under consideration.

Towards automated human gait disease classification using phase space representation of intrinsic mode functions

NASA Astrophysics Data System (ADS)

Pratiher, Sawon; Patra, Sayantani; Pratiher, Souvik

2017-06-01

A novel analytical methodology for segregating healthy and neurological disorders from gait patterns is proposed by employing a set of oscillating components called intrinsic mode functions (IMF's). These IMF's are generated by the Empirical Mode Decomposition of the gait time series and the Hilbert transformed analytic signal representation forms the complex plane trace of the elliptical shaped analytic IMFs. The area measure and the relative change in the centroid position of the polygon formed by the Convex Hull of these analytic IMF's are taken as the discriminative features. Classification accuracy of 79.31% with Ensemble learning based Adaboost classifier validates the adequacy of the proposed methodology for a computer aided diagnostic (CAD) system for gait pattern identification. Also, the efficacy of several potential biomarkers like Bandwidth of Amplitude Modulation and Frequency Modulation IMF's and it's Mean Frequency from the Fourier-Bessel expansion from each of these analytic IMF's has been discussed for its potency in diagnosis of gait pattern identification and classification.

Intrinsic brain abnormalities in young healthy adults with childhood trauma: A resting-state functional magnetic resonance imaging study of regional homogeneity and functional connectivity.

PubMed

Lu, Shaojia; Gao, Weijia; Wei, Zhaoguo; Wang, Dandan; Hu, Shaohua; Huang, Manli; Xu, Yi; Li, Lingjiang

2017-06-01

Childhood trauma confers great risk for the development of multiple psychiatric disorders; however, the neural basis for this association is still unknown. The present resting-state functional magnetic resonance imaging study aimed to detect the effects of childhood trauma on brain function in a group of young healthy adults. In total, 24 healthy individuals with childhood trauma and 24 age- and sex-matched adults without childhood trauma were recruited. Each participant underwent resting-state functional magnetic resonance imaging scanning. Intra-regional brain activity was evaluated by regional homogeneity method and compared between groups. Areas with altered regional homogeneity were further selected as seeds in subsequent functional connectivity analysis. Statistical analyses were performed by setting current depression and anxiety as covariates. Adults with childhood trauma showed decreased regional homogeneity in bilateral superior temporal gyrus and insula, and the right inferior parietal lobule, as well as increased regional homogeneity in the right cerebellum and left middle temporal gyrus. Regional homogeneity values in the left middle temporal gyrus, right insula and right cerebellum were correlated with childhood trauma severity. In addition, individuals with childhood trauma also exhibited altered default mode network, cerebellum-default mode network and insula-default mode network connectivity when the left middle temporal gyrus, right cerebellum and right insula were selected as seed area, respectively. The present outcomes suggest that childhood trauma is associated with disturbed intrinsic brain function, especially the default mode network, in adults even without psychiatric diagnoses, which may mediate the relationship between childhood trauma and psychiatric disorders in later life.

Hearing voices in the resting brain: A review of intrinsic functional connectivity research on auditory verbal hallucinations

PubMed Central

Alderson-Day, Ben; McCarthy-Jones, Simon; Fernyhough, Charles

2018-01-01

Resting state networks (RSNs) are thought to reflect the intrinsic functional connectivity of brain regions. Alterations to RSNs have been proposed to underpin various kinds of psychopathology, including the occurrence of auditory verbal hallucinations (AVH). This review outlines the main hypotheses linking AVH and the resting state, and assesses the evidence for alterations to intrinsic connectivity provided by studies of resting fMRI in AVH. The influence of hallucinations during data acquisition, medication confounds, and movement are also considered. Despite a large variety of analytic methods and designs being deployed, it is possible to conclude that resting connectivity in the left temporal lobe in general and left superior temporal gyrus in particular are disrupted in AVH. There is also preliminary evidence of atypical connectivity in the default mode network and its interaction with other RSNs. Recommendations for future research include the adoption of a common analysis protocol to allow for more overlapping datasets and replication of intrinsic functional connectivity alterations. PMID:25956256

Greater preference consistency during the Willingness-to-Pay task is related to higher resting state connectivity between the ventromedial prefrontal cortex and the ventral striatum.

PubMed

Mackey, Scott; Olafsson, Valur; Aupperle, Robin L; Lu, Kun; Fonzo, Greg A; Parnass, Jason; Liu, Thomas; Paulus, Martin P

2016-09-01

The significance of why a similar set of brain regions are associated with the default mode network and value-related neural processes remains to be clarified. Here, we examined i) whether brain regions exhibiting willingness-to-pay (WTP) task-related activity are intrinsically connected when the brain is at rest, ii) whether these regions overlap spatially with the default mode network, and iii) whether individual differences in choice behavior during the WTP task are reflected in functional brain connectivity at rest. Blood-oxygen-level dependent (BOLD) signal was measured by functional magnetic resonance imaging while subjects performed the WTP task and at rest with eyes open. Brain regions that tracked the value of bids during the WTP task were used as seed regions in an analysis of functional connectivity in the resting state data. The seed in the ventromedial prefrontal cortex was functionally connected to core regions of the WTP task-related network. Brain regions within the WTP task-related network, namely the ventral precuneus, ventromedial prefrontal and posterior cingulate cortex overlapped spatially with publically available maps of the default mode network. Also, those individuals with higher functional connectivity during rest between the ventromedial prefrontal cortex and the ventral striatum showed greater preference consistency during the WTP task. Thus, WTP task-related regions are an intrinsic network of the brain that corresponds spatially with the default mode network, and individual differences in functional connectivity within the WTP network at rest may reveal a priori biases in choice behavior.

Greater preference consistency during the Willingness-to-Pay task is related to higher resting state connectivity between the ventromedial prefrontal cortex and the ventral striatum

PubMed Central

Mackey, Scott; Olafsson, Valur; Aupperle, Robin; Lu, Kun; Fonzo, Greg; Parnass, Jason; Liu, Thomas; Paulus, Martin P.

2015-01-01

The significance of why a similar set of brain regions are associated with the default mode network and value-related neural processes remains to be clarified. Here, we examined i) whether brain regions exhibiting willingness-to-pay (WTP) task-related activity are intrinsically connected when the brain is at rest, ii) whether these regions overlap spatially with the default mode network, and iii) whether individual differences in choice behavior during the WTP task are reflected in functional brain connectivity at rest. Blood-oxygen-level dependent (BOLD) signal was measured by functional magnetic resonance imaging while subjects performed the WTP task and at rest with eyes open. Brain regions that tracked the value of bids during the WTP task were used as seed regions in an analysis of functional connectivity in the resting state data. The seed in the ventromedial prefrontal cortex was functionally connected to core regions of the WTP task-related network. Brain regions within the WTP task-related network, namely the ventral precuneus, ventromedial prefrontal and posterior cingulate cortex overlapped spatially with publically available maps of the default mode network. Also, those individuals with higher functional connectivity during rest between the ventromedial prefrontal cortex and the ventral striatum showed greater preference consistency during the WTP task. Thus, WTP task-related regions are an intrinsic network of the brain that corresponds spatially with the default mode network, and individual differences in functional connectivity within the WTP network at rest may reveal a priori biases in choice behavior. PMID:26271206

Frequency regularities of acoustic modes and multi-colour mode identification in rapidly rotating stars

NASA Astrophysics Data System (ADS)

Reese, D. R.; Lignières, F.; Ballot, J.; Dupret, M.-A.; Barban, C.; van't Veer-Menneret, C.; MacGregor, K. B.

2017-05-01

Context. Mode identification has remained a major obstacle in the interpretation of pulsation spectra in rapidly rotating stars. This has motivated recent work on calculating realistic multi-colour mode visibilities in this type of star. Aims: We would like to test mode identification methods and seismic diagnostics in rapidly rotating stars, using oscillation spectra that are based on these new theoretical predictions. Methods: We investigate the auto-correlation function and Fourier transform of theoretically calculated frequency spectra, in which modes are selected according to their visibilities. Given that intrinsic mode amplitudes are determined by non-linear saturation and cannot currently be theoretically predicted, we experimented with various ad-hoc prescriptions for setting the mode amplitudes, including using random values. Furthermore, we analyse the ratios between mode amplitudes observed in different photometric bands to see up to what extent they can identify modes. Results: When non-random intrinsic mode amplitudes are used, our results show that it is possible to extract a mean value for the large frequency separation or half its value and, sometimes, twice the rotation rate, from the auto-correlation of the frequency spectra. Furthermore, the Fourier transforms are mostly sensitive to the large frequency separation or half its value. The combination of the two methods may therefore measure and distinguish the two types of separations. When the intrinsic mode amplitudes include random factors, which seems more representative of real stars, the results are far less favourable. It is only when the large separation or half its value coincides with twice the rotation rate, that it might be possible to detect the signature of a frequency regularity. We also find that amplitude ratios are a good way of grouping together modes with similar characteristics. By analysing the frequencies of these groups, it is possible to constrain mode identification, as well as determine the large frequency separation and the rotation rate.

A New Method for Nonlinear and Nonstationary Time Series Analysis and Its Application to the Earthquake and Building Response Records

NASA Technical Reports Server (NTRS)

Huang, Norden E.

1999-01-01

A new method for analyzing nonlinear and nonstationary data has been developed. The key part of the method is the Empirical Mode Decomposition method with which any complicated data set can be decomposed into a finite and often small number of Intrinsic Mode Functions (IMF). An IMF is defined as any function having the same numbers of zero-crossing and extrema, and also having symmetric envelopes defined by the local maxima and minima respectively. The IMF also admits well-behaved Hilbert transform. This decomposition method is adaptive, and, therefore, highly efficient. Since the decomposition is based on the local characteristic time scale of the data, it is applicable to nonlinear and nonstationary processes. With the Hilbert transform, the Intrinsic Mode Functions yield instantaneous frequencies as functions of time that give sharp identifications of imbedded structures. The final presentation of the results is an energy-frequency-time distribution, designated as the Hilbert Spectrum, Example of application of this method to earthquake and building response will be given. The results indicate those low frequency components, totally missed by the Fourier analysis, are clearly identified by the new method. Comparisons with Wavelet and window Fourier analysis show the new method offers much better temporal and frequency resolutions.

Computer implemented empirical mode decomposition method, apparatus, and article of manufacture for two-dimensional signals

NASA Technical Reports Server (NTRS)

Huang, Norden E. (Inventor)

2001-01-01

A computer implemented method of processing two-dimensional physical signals includes five basic components and the associated presentation techniques of the results. The first component decomposes the two-dimensional signal into one-dimensional profiles. The second component is a computer implemented Empirical Mode Decomposition that extracts a collection of Intrinsic Mode Functions (IMF's) from each profile based on local extrema and/or curvature extrema. The decomposition is based on the direct extraction of the energy associated with various intrinsic time scales in the profiles. In the third component, the IMF's of each profile are then subjected to a Hilbert Transform. The fourth component collates the Hilbert transformed IMF's of the profiles to form a two-dimensional Hilbert Spectrum. A fifth component manipulates the IMF's by, for example, filtering the two-dimensional signal by reconstructing the two-dimensional signal from selected IMF(s).

Ab initio calculations of ideal strength and lattice instability in W-Ta and W-Re alloys

NASA Astrophysics Data System (ADS)

Yang, Chaoming; Qi, Liang

2018-01-01

An important theoretical criterion to evaluate the ductility of metals with a body-centered cubic (bcc) lattice is the mechanical failure mode of their perfect crystals under tension along <;100 >; directions. When the tensile stress reaches the ideal tensile strength, the pure W crystal fails by a cleavage fracture along the {100 } plane so that it is intrinsically brittle. To discover the strategy to improve its ductility, we performed density functional theory and density functional perturbation theory calculations to study the ideal tensile strength and the lattice instability under <100 > tension for both W-Ta and W-Re alloys. Anisotropic linear elastic fracture mechanics (LEFM) theory and Rice's criterion were also applied to analyze the mechanical instability at the crack tip under <100 > tension based on the competition between cleavage propagation and dislocation emission. The results show that the intrinsic ductility can be achieved in both W-Ta and W-Re, however, by different mechanisms. Even though W-Ta alloys with low Ta concentrations are still intrinsically brittle, the intrinsic ductility of W-Ta alloys with high Ta concentrations is promoted by elastic shear instability before the cleavage failure. The intrinsic ductility of W-Re alloys is produced by unstable transverse phonon waves before the cleavage failure, and the corresponding phonon mode is related to the generation of 1/2 <111 > {2 ¯11 } dislocation in bcc crystals. The ideal tensile calculations, phonon analyses, and anisotropic LEFM examinations are mutually consistent in the evaluation of intrinsic ductility. These results bring us physical insights on the ductility-brittle mechanisms of W alloys under extreme stress conditions.

Applications of Hilbert Spectral Analysis for Speech and Sound Signals

NASA Technical Reports Server (NTRS)

Huang, Norden E.

2003-01-01

A new method for analyzing nonlinear and nonstationary data has been developed, and the natural applications are to speech and sound signals. The key part of the method is the Empirical Mode Decomposition method with which any complicated data set can be decomposed into a finite and often small number of Intrinsic Mode Functions (IMF). An IMF is defined as any function having the same numbers of zero-crossing and extrema, and also having symmetric envelopes defined by the local maxima and minima respectively. The IMF also admits well-behaved Hilbert transform. This decomposition method is adaptive, and, therefore, highly efficient. Since the decomposition is based on the local characteristic time scale of the data, it is applicable to nonlinear and nonstationary processes. With the Hilbert transform, the Intrinsic Mode Functions yield instantaneous frequencies as functions of time, which give sharp identifications of imbedded structures. This method invention can be used to process all acoustic signals. Specifically, it can process the speech signals for Speech synthesis, Speaker identification and verification, Speech recognition, and Sound signal enhancement and filtering. Additionally, as the acoustical signals from machinery are essentially the way the machines are talking to us. Therefore, the acoustical signals, from the machines, either from sound through air or vibration on the machines, can tell us the operating conditions of the machines. Thus, we can use the acoustic signal to diagnosis the problems of machines.

Multiscale Characterization of PM2.5 in Southern Taiwan based on Noise-assisted Multivariate Empirical Mode Decomposition and Time-dependent Intrinsic Correlation

NASA Astrophysics Data System (ADS)

Hsiao, Y. R.; Tsai, C.

2017-12-01

As the WHO Air Quality Guideline indicates, ambient air pollution exposes world populations under threat of fatal symptoms (e.g. heart disease, lung cancer, asthma etc.), raising concerns of air pollution sources and relative factors. This study presents a novel approach to investigating the multiscale variations of PM2.5 in southern Taiwan over the past decade, with four meteorological influencing factors (Temperature, relative humidity, precipitation and wind speed),based on Noise-assisted Multivariate Empirical Mode Decomposition(NAMEMD) algorithm, Hilbert Spectral Analysis(HSA) and Time-dependent Intrinsic Correlation(TDIC) method. NAMEMD algorithm is a fully data-driven approach designed for nonlinear and nonstationary multivariate signals, and is performed to decompose multivariate signals into a collection of channels of Intrinsic Mode Functions (IMFs). TDIC method is an EMD-based method using a set of sliding window sizes to quantify localized correlation coefficients for multiscale signals. With the alignment property and quasi-dyadic filter bank of NAMEMD algorithm, one is able to produce same number of IMFs for all variables and estimates the cross correlation in a more accurate way. The performance of spectral representation of NAMEMD-HSA method is compared with Complementary Empirical Mode Decomposition/ Hilbert Spectral Analysis (CEEMD-HSA) and Wavelet Analysis. The nature of NAMAMD-based TDICC analysis is then compared with CEEMD-based TDIC analysis and the traditional correlation analysis.

Multi-Fault Diagnosis of Rolling Bearings via Adaptive Projection Intrinsically Transformed Multivariate Empirical Mode Decomposition and High Order Singular Value Decomposition

PubMed Central

Lv, Yong; Song, Gangbing

2018-01-01

Rolling bearings are important components in rotary machinery systems. In the field of multi-fault diagnosis of rolling bearings, the vibration signal collected from single channels tends to miss some fault characteristic information. Using multiple sensors to collect signals at different locations on the machine to obtain multivariate signal can remedy this problem. The adverse effect of a power imbalance between the various channels is inevitable, and unfavorable for multivariate signal processing. As a useful, multivariate signal processing method, Adaptive-projection has intrinsically transformed multivariate empirical mode decomposition (APIT-MEMD), and exhibits better performance than MEMD by adopting adaptive projection strategy in order to alleviate power imbalances. The filter bank properties of APIT-MEMD are also adopted to enable more accurate and stable intrinsic mode functions (IMFs), and to ease mode mixing problems in multi-fault frequency extractions. By aligning IMF sets into a third order tensor, high order singular value decomposition (HOSVD) can be employed to estimate the fault number. The fault correlation factor (FCF) analysis is used to conduct correlation analysis, in order to determine effective IMFs; the characteristic frequencies of multi-faults can then be extracted. Numerical simulations and the application of multi-fault situation can demonstrate that the proposed method is promising in multi-fault diagnoses of multivariate rolling bearing signal. PMID:29659510

Multi-Fault Diagnosis of Rolling Bearings via Adaptive Projection Intrinsically Transformed Multivariate Empirical Mode Decomposition and High Order Singular Value Decomposition.

PubMed

Yuan, Rui; Lv, Yong; Song, Gangbing

2018-04-16

Rolling bearings are important components in rotary machinery systems. In the field of multi-fault diagnosis of rolling bearings, the vibration signal collected from single channels tends to miss some fault characteristic information. Using multiple sensors to collect signals at different locations on the machine to obtain multivariate signal can remedy this problem. The adverse effect of a power imbalance between the various channels is inevitable, and unfavorable for multivariate signal processing. As a useful, multivariate signal processing method, Adaptive-projection has intrinsically transformed multivariate empirical mode decomposition (APIT-MEMD), and exhibits better performance than MEMD by adopting adaptive projection strategy in order to alleviate power imbalances. The filter bank properties of APIT-MEMD are also adopted to enable more accurate and stable intrinsic mode functions (IMFs), and to ease mode mixing problems in multi-fault frequency extractions. By aligning IMF sets into a third order tensor, high order singular value decomposition (HOSVD) can be employed to estimate the fault number. The fault correlation factor (FCF) analysis is used to conduct correlation analysis, in order to determine effective IMFs; the characteristic frequencies of multi-faults can then be extracted. Numerical simulations and the application of multi-fault situation can demonstrate that the proposed method is promising in multi-fault diagnoses of multivariate rolling bearing signal.

Mental Task Classification Scheme Utilizing Correlation Coefficient Extracted from Interchannel Intrinsic Mode Function.

PubMed

Rahman, Md Mostafizur; Fattah, Shaikh Anowarul

2017-01-01

In view of recent increase of brain computer interface (BCI) based applications, the importance of efficient classification of various mental tasks has increased prodigiously nowadays. In order to obtain effective classification, efficient feature extraction scheme is necessary, for which, in the proposed method, the interchannel relationship among electroencephalogram (EEG) data is utilized. It is expected that the correlation obtained from different combination of channels will be different for different mental tasks, which can be exploited to extract distinctive feature. The empirical mode decomposition (EMD) technique is employed on a test EEG signal obtained from a channel, which provides a number of intrinsic mode functions (IMFs), and correlation coefficient is extracted from interchannel IMF data. Simultaneously, different statistical features are also obtained from each IMF. Finally, the feature matrix is formed utilizing interchannel correlation features and intrachannel statistical features of the selected IMFs of EEG signal. Different kernels of the support vector machine (SVM) classifier are used to carry out the classification task. An EEG dataset containing ten different combinations of five different mental tasks is utilized to demonstrate the classification performance and a very high level of accuracy is achieved by the proposed scheme compared to existing methods.

Broad-band, radio spectro-polarimetric study of 100 radiative-mode and jet-mode AGN

NASA Astrophysics Data System (ADS)

O'Sullivan, S. P.; Purcell, C. R.; Anderson, C. S.; Farnes, J. S.; Sun, X. H.; Gaensler, B. M.

2017-08-01

We present the results from a broad-band (1 to 3 GHz), spectro-polarimetry study of the integrated emission from 100 extragalactic radio sources with the Australia Telescope Compact Array, selected to be highly linearly polarized at 1.4 GHz. We use a general-purpose, polarization model-fitting procedure that describes the Faraday rotation measure (RM) and intrinsic polarization structure of up to three distinct polarized emission regions or `RM components' of a source. Overall, 37 per cent/52 per cent/11 per cent of sources are best fitted by one/two/three RM components. However, these fractions are dependent on the signal-to-noise ratio (S/N) in polarization (more RM components more likely at higher S/N). In general, our analysis shows that sources with high integrated degrees of polarization at 1.4 GHz have low Faraday depolarization, are typically dominated by a single RM component, have a steep spectral index and have a high intrinsic degree of polarization. After classifying our sample into radiative-mode and jet-mode AGN, we find no significant difference between the Faraday rotation or Faraday depolarization properties of jet-mode and radiative-mode AGN. However, there is a statistically significant difference in the intrinsic degree of polarization between the two types, with the jet-mode sources having more intrinsically ordered magnetic field structures than the radiative-mode sources. We also find a preferred perpendicular orientation of the intrinsic magnetic field structure of jet-mode AGN with respect to the jet direction, while no clear preference is found for the radiative-mode sources.

Altered Intrinsic Functional Brain Architecture in Children at Familial Risk of Major Depression.

PubMed

Chai, Xiaoqian J; Hirshfeld-Becker, Dina; Biederman, Joseph; Uchida, Mai; Doehrmann, Oliver; Leonard, Julia A; Salvatore, John; Kenworthy, Tara; Brown, Ariel; Kagan, Elana; de Los Angeles, Carlo; Gabrieli, John D E; Whitfield-Gabrieli, Susan

2016-12-01

Neuroimaging studies of patients with major depression have revealed abnormal intrinsic functional connectivity measured during the resting state in multiple distributed networks. However, it is unclear whether these findings reflect the state of major depression or reflect trait neurobiological underpinnings of risk for major depression. We compared resting-state functional connectivity, measured with functional magnetic resonance imaging, between unaffected children of parents who had documented histories of major depression (at-risk, n = 27; 8-14 years of age) and age-matched children of parents with no lifetime history of depression (control subjects, n = 16). At-risk children exhibited hyperconnectivity between the default mode network and subgenual anterior cingulate cortex/orbital frontal cortex, and the magnitude of connectivity positively correlated with individual symptom scores. At-risk children also exhibited 1) hypoconnectivity within the cognitive control network, which also lacked the typical anticorrelation with the default mode network; 2) hypoconnectivity between left dorsolateral prefrontal cortex and subgenual anterior cingulate cortex; and 3) hyperconnectivity between the right amygdala and right inferior frontal gyrus, a key region for top-down modulation of emotion. Classification between at-risk children and control subjects based on resting-state connectivity yielded high accuracy with high sensitivity and specificity that was superior to clinical rating scales. Children at familial risk for depression exhibited atypical functional connectivity in the default mode, cognitive control, and affective networks. Such task-independent functional brain measures of risk for depression in children could be used to promote early intervention to reduce the likelihood of developing depression. Copyright © 2016 Society of Biological Psychiatry. Published by Elsevier Inc. All rights reserved.

On nodes and modes in resting state fMRI

PubMed Central

Friston, Karl J.; Kahan, Joshua; Razi, Adeel; Stephan, Klaas Enno; Sporns, Olaf

2014-01-01

This paper examines intrinsic brain networks in light of recent developments in the characterisation of resting state fMRI timeseries — and simulations of neuronal fluctuations based upon the connectome. Its particular focus is on patterns or modes of distributed activity that underlie functional connectivity. We first demonstrate that the eigenmodes of functional connectivity – or covariance among regions or nodes – are the same as the eigenmodes of the underlying effective connectivity, provided we limit ourselves to symmetrical connections. This symmetry constraint is motivated by appealing to proximity graphs based upon multidimensional scaling. Crucially, the principal modes of functional connectivity correspond to the dynamically unstable modes of effective connectivity that decay slowly and show long term memory. Technically, these modes have small negative Lyapunov exponents that approach zero from below. Interestingly, the superposition of modes – whose exponents are sampled from a power law distribution – produces classical 1/f (scale free) spectra. We conjecture that the emergence of dynamical instability – that underlies intrinsic brain networks – is inevitable in any system that is separated from external states by a Markov blanket. This conjecture appeals to a free energy formulation of nonequilibrium steady-state dynamics. The common theme that emerges from these theoretical considerations is that endogenous fluctuations are dominated by a small number of dynamically unstable modes. We use this as the basis of a dynamic causal model (DCM) of resting state fluctuations — as measured in terms of their complex cross spectra. In this model, effective connectivity is parameterised in terms of eigenmodes and their Lyapunov exponents — that can also be interpreted as locations in a multidimensional scaling space. Model inversion provides not only estimates of edges or connectivity but also the topography and dimensionality of the underlying scaling space. Here, we focus on conceptual issues with simulated fMRI data and provide an illustrative application using an empirical multi-region timeseries. PMID:24862075

An adjoint-based sensitivity analysis of thermoacoustic network models

NASA Astrophysics Data System (ADS)

Sogaro, Francesca; Morgans, Aimee; Schmid, Peter

2017-11-01

Thermoacoustic instability is a phenomenon that occurs in numerous combustion systems, from rockets to land-based gas turbines. The acoustic oscillations of these systems are of significant importance as they can result in severe vibrations, thrust oscillations, thermal stresses and mechanical loads that lead to fatigue or even failure. In this work we use a low-order network model representation of a combustor system where linear acoustics are solved together with the appropriate boundary conditions, area change jump conditions, acoustic dampers and an appropriate flame transfer function. Special emphasis is directed towards the interaction between acoustically driven instabilities and flame-intrinsic modes. Adjoint methods are used to perform a sensitivity analysis of the spectral properties of the system to changes in the parameters involved. An exchange of modal identity between acoustic and intrinsic modes will be demonstrated and analyzed. The results provide insight into the interplay between various mode types and build a quantitative foundation for the design of combustors.

Adaptive variational mode decomposition method for signal processing based on mode characteristic

NASA Astrophysics Data System (ADS)

Lian, Jijian; Liu, Zhuo; Wang, Haijun; Dong, Xiaofeng

2018-07-01

Variational mode decomposition is a completely non-recursive decomposition model, where all the modes are extracted concurrently. However, the model requires a preset mode number, which limits the adaptability of the method since a large deviation in the number of mode set will cause the discard or mixing of the mode. Hence, a method called Adaptive Variational Mode Decomposition (AVMD) was proposed to automatically determine the mode number based on the characteristic of intrinsic mode function. The method was used to analyze the simulation signals and the measured signals in the hydropower plant. Comparisons have also been conducted to evaluate the performance by using VMD, EMD and EWT. It is indicated that the proposed method has strong adaptability and is robust to noise. It can determine the mode number appropriately without modulation even when the signal frequencies are relatively close.

Aberrant Intrinsic Activity and Connectivity in Cognitively Normal Parkinson's Disease.

PubMed

Harrington, Deborah L; Shen, Qian; Castillo, Gabriel N; Filoteo, J Vincent; Litvan, Irene; Takahashi, Colleen; French, Chelsea

2017-01-01

Disturbances in intrinsic activity during resting-state functional MRI (rsfMRI) are common in Parkinson's disease (PD), but have largely been studied in a priori defined subnetworks. The cognitive significance of abnormal intrinsic activity is also poorly understood, as are abnormalities that precede the onset of mild cognitive impairment. To address these limitations, we leveraged three different analytic approaches to identify disturbances in rsfMRI metrics in 31 cognitively normal PD patients (PD-CN) and 30 healthy adults. Subjects were screened for mild cognitive impairment using the Movement Disorders Society Task Force Level II criteria. Whole-brain data-driven analytic approaches first analyzed the amplitude of low-frequency intrinsic fluctuations (ALFF) and regional homogeneity (ReHo), a measure of local connectivity amongst functionally similar regions. We then examined if regional disturbances in these metrics altered functional connectivity with other brain regions. We also investigated if abnormal rsfMRI metrics in PD-CN were related to brain atrophy and executive, visual organization, and episodic memory functioning. The results revealed abnormally increased and decreased ALFF and ReHo in PD-CN patients within the default mode network (posterior cingulate, inferior parietal cortex, parahippocampus, entorhinal cortex), sensorimotor cortex (primary motor, pre/post-central gyrus), basal ganglia (putamen, caudate), and posterior cerebellar lobule VII, which mediates cognition. For default mode network regions, we also observed a compound profile of altered ALFF and ReHo. Most regional disturbances in ALFF and ReHo were associated with strengthened long-range interactions in PD-CN, notably with regions in different networks. Stronger long-range functional connectivity in PD-CN was also partly expanded to connections that were outside the networks of the control group. Abnormally increased activity and functional connectivity appeared to have a pathological, rather than compensatory influence on cognitive abilities tested in this study. Receiver operating curve analyses demonstrated excellent sensitivity (≥90%) of rsfMRI variables in distinguishing patients from controls, but poor accuracy for brain volume and cognitive variables. Altogether these results provide new insights into the topology, cognitive relevance, and sensitivity of aberrant intrinsic activity and connectivity that precedes clinically significant cognitive impairment. Longitudinal studies are needed to determine if these neurocognitive associations presage the development of future mild cognitive impairment or dementia.

Study on the Relationships between Intrinsic Functional Connectivity of the Default Mode Network and Transient Epileptic Activity.

PubMed

Lopes, Renaud; Moeller, Friederike; Besson, Pierre; Ogez, François; Szurhaj, William; Leclerc, Xavier; Siniatchkin, Michael; Chipaux, Mathilde; Derambure, Philippe; Tyvaert, Louise

2014-01-01

Simultaneous recording of electroencephalogram and functional MRI (EEG-fMRI) is a powerful tool for localizing epileptic networks via the detection of hemodynamic changes correlated with interictal epileptic discharges (IEDs). fMRI can be used to study the long-lasting effect of epileptic activity by assessing stationary functional connectivity during the resting-state period [especially, the connectivity of the default mode network (DMN)]. Temporal lobe epilepsy (TLE) and idiopathic generalized epilepsy (IGE) are associated with low responsiveness and disruption of DMN activity. A dynamic functional connectivity approach might enable us to determine the effect of IEDs on DMN connectivity and to better understand the correlation between DMN connectivity changes and altered consciousness. We studied dynamic changes in DMN intrinsic connectivity and their relation to IEDs. Six IGE patients (with generalized spike and slow-waves) and 6 TLE patients (with unilateral left temporal spikes) were included. Functional connectivity before, during, and after IEDs was estimated using a sliding window approach and compared with the baseline period. No dependence on window size was observed. The baseline DMN connectivity was decreased in the left hemisphere (ipsilateral to the epileptic focus) in TLEs and was less strong but remained bilateral in IGEs. We observed an overall increase in DMN intrinsic connectivity prior to the onset of IEDs in both IGEs and TLEs. After IEDs in TLEs, we found that DMN connectivity increased before it returned to baseline values. Most of the DMN regions with increased connectivity before and after IEDs were lateralized to the left hemisphere in TLE (i.e., ipsilateral to the epileptic focus). RESULTS suggest that DMN connectivity may facilitate IED generation and may be affected at the time of the IED. However, these results need to be confirmed in a larger independent cohort.

Similarity in Shape Dictates Signature Intrinsic Dynamics Despite No Functional Conservation in TIM Barrel Enzymes

PubMed Central

Tiwari, Sandhya P.; Reuter, Nathalie

2016-01-01

The conservation of the intrinsic dynamics of proteins emerges as we attempt to understand the relationship between sequence, structure and functional conservation. We characterise the conservation of such dynamics in a case where the structure is conserved but function differs greatly. The triosephosphate isomerase barrel fold (TBF), renowned for its 8 β-strand-α-helix repeats that close to form a barrel, is one of the most diverse and abundant folds found in known protein structures. Proteins with this fold have diverse enzymatic functions spanning five of six Enzyme Commission classes, and we have picked five different superfamily candidates for our analysis using elastic network models. We find that the overall shape is a large determinant in the similarity of the intrinsic dynamics, regardless of function. In particular, the β-barrel core is highly rigid, while the α-helices that flank the β-strands have greater relative mobility, allowing for the many possibilities for placement of catalytic residues. We find that these elements correlate with each other via the loops that link them, as opposed to being directly correlated. We are also able to analyse the types of motions encoded by the normal mode vectors of the α-helices. We suggest that the global conservation of the intrinsic dynamics in the TBF contributes greatly to its success as an enzymatic scaffold both through evolution and enzyme design. PMID:27015412

Improving EMG based classification of basic hand movements using EMD.

PubMed

Sapsanis, Christos; Georgoulas, George; Tzes, Anthony; Lymberopoulos, Dimitrios

2013-01-01

This paper presents a pattern recognition approach for the identification of basic hand movements using surface electromyographic (EMG) data. The EMG signal is decomposed using Empirical Mode Decomposition (EMD) into Intrinsic Mode Functions (IMFs) and subsequently a feature extraction stage takes place. Various combinations of feature subsets are tested using a simple linear classifier for the detection task. Our results suggest that the use of EMD can increase the discrimination ability of the conventional feature sets extracted from the raw EMG signal.

Acoustical Applications of the HHT Method

NASA Technical Reports Server (NTRS)

Huang, Norden E.

2003-01-01

A document discusses applications of a method based on the Huang-Hilbert transform (HHT). The method was described, without the HHT name, in Analyzing Time Series Using EMD and Hilbert Spectra (GSC-13817), NASA Tech Briefs, Vol. 24, No. 10 (October 2000), page 63. To recapitulate: The method is especially suitable for analyzing time-series data that represent nonstationary and nonlinear physical phenomena. The method involves the empirical mode decomposition (EMD), in which a complicated signal is decomposed into a finite number of functions, called intrinsic mode functions (IMFs), that admit well-behaved Hilbert transforms. The HHT consists of the combination of EMD and Hilbert spectral analysis.

Temporal Associations between Weather and Headache: Analysis by Empirical Mode Decomposition

PubMed Central

Yang, Albert C.; Fuh, Jong-Ling; Huang, Norden E.; Shia, Ben-Chang; Peng, Chung-Kang; Wang, Shuu-Jiun

2011-01-01

Background Patients frequently report that weather changes trigger headache or worsen existing headache symptoms. Recently, the method of empirical mode decomposition (EMD) has been used to delineate temporal relationships in certain diseases, and we applied this technique to identify intrinsic weather components associated with headache incidence data derived from a large-scale epidemiological survey of headache in the Greater Taipei area. Methodology/Principal Findings The study sample consisted of 52 randomly selected headache patients. The weather time-series parameters were detrended by the EMD method into a set of embedded oscillatory components, i.e. intrinsic mode functions (IMFs). Multiple linear regression models with forward stepwise methods were used to analyze the temporal associations between weather and headaches. We found no associations between the raw time series of weather variables and headache incidence. For decomposed intrinsic weather IMFs, temperature, sunshine duration, humidity, pressure, and maximal wind speed were associated with headache incidence during the cold period, whereas only maximal wind speed was associated during the warm period. In analyses examining all significant weather variables, IMFs derived from temperature and sunshine duration data accounted for up to 33.3% of the variance in headache incidence during the cold period. The association of headache incidence and weather IMFs in the cold period coincided with the cold fronts. Conclusions/Significance Using EMD analysis, we found a significant association between headache and intrinsic weather components, which was not detected by direct comparisons of raw weather data. Contributing weather parameters may vary in different geographic regions and different seasons. PMID:21297940

Neural Systems Approaches to Understanding Major Depressive Disorder: An Intrinsic Functional Organization Perspective

PubMed Central

Hamilton, J. Paul; Chen, Michael C.; Gotlib, Ian H.

2012-01-01

Recent research detailing the intrinsic functional organization of the brain provides a unique and useful framework to gain a better understanding of the neural bases of Major Depressive Disorder (MDD). In this review, we first present a brief history of neuroimaging research that has increased our understanding of the functional macro-architecture of the brain. From this macro-architectural perspective, we examine the extant body of functional neuroimaging research assessing MDD with a specific emphasis on the contributions of default-mode, executive, and salience networks in this debilitating disorder. Next, we describe recent investigations conducted in our laboratory in which we explicitly adopt a neural-systems perspective in examining the relations among these networks in MDD. Finally, we offer directions for future research that we believe will facilitate the development of more detailed and integrative models of neural dysfunction in depression. PMID:23477309

Beyond Functionality and Technocracy: Creating Human Involvement with Educational Technology

ERIC Educational Resources Information Center

Westera, Wim

2005-01-01

Innovation of education is highly topical. It is obviously boosted by a range of new technologies, which enable new modes of learning that, are independent of time and place through Web-based delivery and computer-mediated communication. However, innovators in education often encounter intrinsic conservatism or even deliberate obstructions. For…

The Hilbert-Huang Transform-Based Denoising Method for the TEM Response of a PRBS Source Signal

NASA Astrophysics Data System (ADS)

Hai, Li; Guo-qiang, Xue; Pan, Zhao; Hua-sen, Zhong; Khan, Muhammad Younis

2016-08-01

The denoising process is critical in processing transient electromagnetic (TEM) sounding data. For the full waveform pseudo-random binary sequences (PRBS) response, an inadequate noise estimation may result in an erroneous interpretation. We consider the Hilbert-Huang transform (HHT) and its application to suppress the noise in the PRBS response. The focus is on the thresholding scheme to suppress the noise and the analysis of the signal based on its Hilbert time-frequency representation. The method first decomposes the signal into the intrinsic mode function, and then, inspired by the thresholding scheme in wavelet analysis; an adaptive and interval thresholding is conducted to set to zero all the components in intrinsic mode function which are lower than a threshold related to the noise level. The algorithm is based on the characteristic of the PRBS response. The HHT-based denoising scheme is tested on the synthetic and field data with the different noise levels. The result shows that the proposed method has a good capability in denoising and detail preservation.

Eliminating the zero spectrum in Fourier transform profilometry using empirical mode decomposition.

PubMed

Li, Sikun; Su, Xianyu; Chen, Wenjing; Xiang, Liqun

2009-05-01

Empirical mode decomposition is introduced into Fourier transform profilometry to extract the zero spectrum included in the deformed fringe pattern without the need for capturing two fringe patterns with pi phase difference. The fringe pattern is subsequently demodulated using a standard Fourier transform profilometry algorithm. With this method, the deformed fringe pattern is adaptively decomposed into a finite number of intrinsic mode functions that vary from high frequency to low frequency by means of an algorithm referred to as a sifting process. Then the zero spectrum is separated from the high-frequency components effectively. Experiments validate the feasibility of this method.

Analysis and modeling of optical crosstalk in InP-based Geiger-mode avalanche photodiode FPAs

NASA Astrophysics Data System (ADS)

Chau, Quan; Jiang, Xudong; Itzler, Mark A.; Entwistle, Mark; Piccione, Brian; Owens, Mark; Slomkowski, Krystyna

2015-05-01

Optical crosstalk is a major factor limiting the performance of Geiger-mode avalanche photodiode (GmAPD) focal plane arrays (FPAs). This is especially true for arrays with increased pixel density and broader spectral operation. We have performed extensive experimental and theoretical investigations on the crosstalk effects in InP-based GmAPD FPAs for both 1.06-μm and 1.55-μm applications. Mechanisms responsible for intrinsic dark counts are Poisson processes, and their inter-arrival time distribution is an exponential function. In FPAs, intrinsic dark counts and cross talk events coexist, and the inter-arrival time distribution deviates from purely exponential behavior. From both experimental data and computer simulations, we show the dependence of this deviation on the crosstalk probability. The spatial characteristics of crosstalk are also demonstrated. From the temporal and spatial distribution of crosstalk, an efficient algorithm to identify and quantify crosstalk is introduced.

Calculation of intrinsic stresses in the diamond-like coatings produced by plasma ion deposition in modes of DC and pulse bias potentials

NASA Astrophysics Data System (ADS)

Kalinichenko, A. A.; Perepelkin, S. S.; Strel'nitskij, V. E.

2015-04-01

The formula derivation for calculation of intrinsic stress in diamond-like coatings deposited from the ion flux in modes of continuous and pulsed potentials in view of process of defects formation is given. The criterion of applicability of obtained formula allowing to determine critical parameters of the pulsed potential mode is suggested. Results of calculation of stresses in diamond-like coatings at deposition of low-energy ions C+ from filtered vacuum arc plasma are adduced. The influence of the bias potential, repetition frequency and pulse duration, on the value of intrinsic stress is discussed. Qualitative agreement of calculated stress and experimental data is stated. The important role of deposition temperature in control of intrinsic stress in deposited coating is noted.

Multifarious Roles of Intrinsic Disorder in Proteins Illustrate Its Broad Impact on Plant Biology

PubMed Central

Sun, Xiaolin; Rikkerink, Erik H.A.; Jones, William T.; Uversky, Vladimir N.

2013-01-01

Intrinsically disordered proteins (IDPs) are highly abundant in eukaryotic proteomes. Plant IDPs play critical roles in plant biology and often act as integrators of signals from multiple plant regulatory and environmental inputs. Binding promiscuity and plasticity allow IDPs to interact with multiple partners in protein interaction networks and provide important functional advantages in molecular recognition through transient protein–protein interactions. Short interaction-prone segments within IDPs, termed molecular recognition features, represent potential binding sites that can undergo disorder-to-order transition upon binding to their partners. In this review, we summarize the evidence for the importance of IDPs in plant biology and evaluate the functions associated with intrinsic disorder in five different types of plant protein families experimentally confirmed as IDPs. Functional studies of these proteins illustrate the broad impact of disorder on many areas of plant biology, including abiotic stress, transcriptional regulation, light perception, and development. Based on the roles of disorder in the protein–protein interactions, we propose various modes of action for plant IDPs that may provide insight for future experimental approaches aimed at understanding the molecular basis of protein function within important plant pathways. PMID:23362206

Intrinsic connectivity of neural networks in the awake rabbit.

PubMed

Schroeder, Matthew P; Weiss, Craig; Procissi, Daniel; Disterhoft, John F; Wang, Lei

2016-04-01

The way in which the brain is functionally connected into different networks has emerged as an important research topic in order to understand normal neural processing and signaling. Since some experimental manipulations are difficult or unethical to perform in humans, animal models are better suited to investigate this topic. Rabbits are a species that can undergo MRI scanning in an awake and conscious state with minimal preparation and habituation. In this study, we characterized the intrinsic functional networks of the resting New Zealand White rabbit brain using BOLD fMRI data. Group independent component analysis revealed seven networks similar to those previously found in humans, non-human primates and/or rodents including the hippocampus, default mode, cerebellum, thalamus, and visual, somatosensory, and parietal cortices. For the first time, the intrinsic functional networks of the resting rabbit brain have been elucidated demonstrating the rabbit's applicability as a translational animal model. Without the confounding effects of anesthetics or sedatives, future experiments may employ rabbits to understand changes in neural connectivity and brain functioning as a result of experimental manipulation (e.g., temporary or permanent network disruption, learning-related changes, and drug administration). Copyright © 2016 Elsevier Inc. All rights reserved.

Derivation of regularized Grad's moment system from kinetic equations: modes, ghosts and non-Markov fluxes

NASA Astrophysics Data System (ADS)

Karlin, Ilya

2018-04-01

Derivation of the dynamic correction to Grad's moment system from kinetic equations (regularized Grad's 13 moment system, or R13) is revisited. The R13 distribution function is found as a superposition of eight modes. Three primary modes, known from the previous derivation (Karlin et al. 1998 Phys. Rev. E 57, 1668-1672. (doi:10.1103/PhysRevE.57.1668)), are extended into the nonlinear parameter domain. Three essentially nonlinear modes are identified, and two ghost modes which do not contribute to the R13 fluxes are revealed. The eight-mode structure of the R13 distribution function implies partition of R13 fluxes into two types of contributions: dissipative fluxes (both linear and nonlinear) and nonlinear streamline convective fluxes. Physical interpretation of the latter non-dissipative and non-local in time effect is discussed. A non-perturbative R13-type solution is demonstrated for a simple Lorentz scattering kinetic model. The results of this study clarify the intrinsic structure of the R13 system. This article is part of the theme issue `Hilbert's sixth problem'.

Determination of intrinsic mode and linear mode coupling in solar microwave bursts

NASA Astrophysics Data System (ADS)

Huang, Guangli; Song, Qiwu; Li, Jianping

2013-05-01

An explicit equation of the propagational angle of microwave emission between the line-of-sight and the local magnetic field is newly derived based on the approximated formulae of nonthermal gyrosynchrotron emission (Dulk and Marsh in Astrophys. J. 259, 350, 1982). The existence of the solution of propagational angle is clearly shown under a series of typical parameters in solar microwave observations. It could be used to determine the intrinsic mode and linear mode coupling in solar microwave bursts by three steps. (1) The mode coupling may happen only when the angle approximately equals to 90 degrees, i.e., when the emission propagates through the quasi-transverse region (Cohen in Astrophys. J. 131, 664, 1960). (2) The inversion of polarization sense due to the weakly mode coupling takes place only when the transition frequency defined by Cohen (1960) is larger than the frequency of microwave emission, and an observable criterion of the weakly mode coupling in flaring loops was indicated by the same polarization sense in the two footpoints of a flaring loop (Melrose and Robinson in Proc. Astron. Soc. Aust. 11, 16, 1994). (3) Finally, the intrinsic mode of microwave emission is determined by the observed polarization and the calculated direction of local magnetic field according to the general plasma dispersion relation, together with the mode coupling process. However, a 180-degree ambiguity still exists in the direction of longitudinal magnetic field, to produce an uncertainty of the intrinsic mode. One example is selected to check the feasibility of the method in the 2001 September 25 event with a loop-like structure nearby the central meridian passage observed by Nobeyama Radio Heliograph and Polarimeters. The calculated angle in one footpoint (FP) varied around 90∘ in two time intervals of the maximum phase, which gives a direct evidence of the emission propagating through a quasi-transverse region where the linear mode coupling took place, while, the angle in another FP was always smaller than 90∘ where the mode coupling did not happen. Moreover, the right-circular sense at 17 GHz was always observed in both two FPs during the event, which supports that the transition frequency should be larger than 17 GHz in the first FP together with strong magnetic field of over 2000 Gauses in photosphere, where the weakly coupled case should happen. Moreover, there are two possibilities of the intrinsic mode in the two FPs due to the 180-degree ambiguity. (1) The emission of extraordinary (X) mode from the first FP turns to the ordinary (O) mode in the two time intervals of the maximum phase, while, the X-mode is always emitted from the second FP. (2) The inversion from O-mode to X-mode takes place in the first FP, while the O-mode keeps in the second FP. If the magnetic polarities in photosphere and corona are coincident in this event, the intrinsic mode belongs to the second case.

Visual attention in preterm born adults: specifically impaired attentional sub-mechanisms that link with altered intrinsic brain networks in a compensation-like mode.

PubMed

Finke, Kathrin; Neitzel, Julia; Bäuml, Josef G; Redel, Petra; Müller, Hermann J; Meng, Chun; Jaekel, Julia; Daamen, Marcel; Scheef, Lukas; Busch, Barbara; Baumann, Nicole; Boecker, Henning; Bartmann, Peter; Habekost, Thomas; Wolke, Dieter; Wohlschläger, Afra; Sorg, Christian

2015-02-15

Although pronounced and lasting deficits in selective attention have been observed for preterm born individuals it is unknown which specific attentional sub-mechanisms are affected and how they relate to brain networks. We used the computationally specified 'Theory of Visual Attention' together with whole- and partial-report paradigms to compare attentional sub-mechanisms of pre- (n=33) and full-term (n=32) born adults. Resting-state fMRI was used to evaluate both between-group differences and inter-individual variance in changed functional connectivity of intrinsic brain networks relevant for visual attention. In preterm born adults, we found specific impairments of visual short-term memory (vSTM) storage capacity while other sub-mechanisms such as processing speed or attentional weighting were unchanged. Furthermore, changed functional connectivity was found in unimodal visual and supramodal attention-related intrinsic networks. Among preterm born adults, the individual pattern of changed connectivity in occipital and parietal cortices was systematically associated with vSTM in such a way that the more distinct the connectivity differences, the better the preterm adults' storage capacity. These findings provide first evidence for selectively changed attentional sub-mechanisms in preterm born adults and their relation to altered intrinsic brain networks. In particular, data suggest that cortical changes in intrinsic functional connectivity may compensate adverse developmental consequences of prematurity on visual short-term storage capacity. Copyright © 2014 Elsevier Inc. All rights reserved.

Mind-Body Practice Changes Fractional Amplitude of Low Frequency Fluctuations in Intrinsic Control Networks

PubMed Central

Wei, Gao-Xia; Gong, Zhu-Qing; Yang, Zhi; Zuo, Xi-Nian

2017-01-01

Cognitive control impairment is a typical symptom largely reported in populations with neurological disorders. Previous studies have provided evidence about the changes in cognitive control induced by mind-body training. However, the neural correlates underlying the effect of extensive mind-body practice on cognitive control remain largely unknown. Using resting-state functional magnetic resonance imaging, we characterized dynamic fluctuations in large-scale intrinsic connectivity networks associated with mind-body practice, and examined their differences between healthy controls and Tai Chi Chuan (TCC) practitioners. Compared with a control group, the TCC group revealed significantly decreased fractional Amplitude of Low Frequency Fluctuations (fALFF) in the bilateral frontoparietal network, default mode network and dorsal prefrontal-angular gyri network. Furthermore, we detected a significant association between mind-body practice experience and fALFF in the default mode network, as well as an association between cognitive control performance and fALFF of the frontoparietal network. This provides the first evidence of large-scale functional connectivity in brain networks associated with mind-body practice, shedding light on the neural network changes that accompany intensive mind-body training. It also highlights the functionally plastic role of the frontoparietal network in the context of the “immune system” of mental health recently developed in relation to flexible hub theory. PMID:28736535

Mind-Body Practice Changes Fractional Amplitude of Low Frequency Fluctuations in Intrinsic Control Networks.

PubMed

Wei, Gao-Xia; Gong, Zhu-Qing; Yang, Zhi; Zuo, Xi-Nian

2017-01-01

Cognitive control impairment is a typical symptom largely reported in populations with neurological disorders. Previous studies have provided evidence about the changes in cognitive control induced by mind-body training. However, the neural correlates underlying the effect of extensive mind-body practice on cognitive control remain largely unknown. Using resting-state functional magnetic resonance imaging, we characterized dynamic fluctuations in large-scale intrinsic connectivity networks associated with mind-body practice, and examined their differences between healthy controls and Tai Chi Chuan (TCC) practitioners. Compared with a control group, the TCC group revealed significantly decreased fractional Amplitude of Low Frequency Fluctuations (fALFF) in the bilateral frontoparietal network, default mode network and dorsal prefrontal-angular gyri network. Furthermore, we detected a significant association between mind-body practice experience and fALFF in the default mode network, as well as an association between cognitive control performance and fALFF of the frontoparietal network. This provides the first evidence of large-scale functional connectivity in brain networks associated with mind-body practice, shedding light on the neural network changes that accompany intensive mind-body training. It also highlights the functionally plastic role of the frontoparietal network in the context of the "immune system" of mental health recently developed in relation to flexible hub theory.

Signal enhancement based on complex curvelet transform and complementary ensemble empirical mode decomposition

NASA Astrophysics Data System (ADS)

Dong, Lieqian; Wang, Deying; Zhang, Yimeng; Zhou, Datong

2017-09-01

Signal enhancement is a necessary step in seismic data processing. In this paper we utilize the complementary ensemble empirical mode decomposition (CEEMD) and complex curvelet transform (CCT) methods to separate signal from random noise further to improve the signal to noise (S/N) ratio. Firstly, the original data with noise is decomposed into a series of intrinsic mode function (IMF) profiles with the aid of CEEMD. Then the IMFs with noise are transformed into CCT domain. By choosing different thresholds which are based on the noise level difference of each IMF profile, the noise in original data can be suppressed. Finally, we illustrate the effectiveness of the approach by simulated and field datasets.

Cavity mode enhancement of terahertz emission from equilateral triangular microstrip antennas of the high-T c superconductor Bi2Sr2CaCu2O8 + δ.

PubMed

Cerkoney, Daniel P; Reid, Candy; Doty, Constance M; Gramajo, Ashley; Campbell, Tyler D; Morales, Manuel A; Delfanazari, Kaveh; Tsujimoto, Manabu; Kashiwagi, Takanari; Yamamoto, Takashi; Watanabe, Chiharu; Minami, Hidetoshi; Kadowaki, Kazuo; Klemm, Richard A

2017-01-11

We study the transverse magnetic (TM) electromagnetic cavity mode wave functions for an ideal equilateral triangular microstrip antenna (MSA) exhibiting C 3v point group symmetry. When the C 3v operations are imposed upon the antenna, the TM(m,n) modes with wave vectors [Formula: see text] are much less dense than commonly thought. The R 3 operations restrict the integral n and m to satisfy [Formula: see text], where [Formula: see text] and [Formula: see text] for the modes even and odd under reflections about the three mirror planes, respectively. We calculate the forms of representative wave functions and the angular dependence of the output power when these modes are excited by the uniform and non-uniform ac Josephson current sources in thin, ideally equilateral triangular MSAs employing the intrinsic Josephson junctions in the high transition temperature T c superconductor Bi 2 Sr 2 CaCu 2 [Formula: see text], and fit the emissions data from an earlier sample for which the C 3v symmetry was apparently broken.

Mutual 3:1 subharmonic synchronization in a micromachined silicon disk resonator

NASA Astrophysics Data System (ADS)

Taheri-Tehrani, Parsa; Guerrieri, Andrea; Defoort, Martial; Frangi, Attilio; Horsley, David A.

2017-10-01

We demonstrate synchronization between two intrinsically coupled oscillators that are created from two distinct vibration modes of a single micromachined disk resonator. The modes have a 3:1 subharmonic frequency relationship and cubic, non-dissipative electromechanical coupling between the modes enables their two frequencies to synchronize. Our experimental implementation allows the frequency of the lower frequency oscillator to be independently controlled from that of the higher frequency oscillator, enabling study of the synchronization dynamics. We find close quantitative agreement between the experimental behavior and an analytical coupled-oscillator model as a function of the energy in the two oscillators. We demonstrate that the synchronization range increases when the lower frequency oscillator is strongly driven and when the higher frequency oscillator is weakly driven. This result suggests that synchronization can be applied to the frequency-selective detection of weak signals and other mechanical signal processing functions.

Study on the Relationships between Intrinsic Functional Connectivity of the Default Mode Network and Transient Epileptic Activity

PubMed Central

Lopes, Renaud; Moeller, Friederike; Besson, Pierre; Ogez, François; Szurhaj, William; Leclerc, Xavier; Siniatchkin, Michael; Chipaux, Mathilde; Derambure, Philippe; Tyvaert, Louise

2014-01-01

Rationale: Simultaneous recording of electroencephalogram and functional MRI (EEG–fMRI) is a powerful tool for localizing epileptic networks via the detection of hemodynamic changes correlated with interictal epileptic discharges (IEDs). fMRI can be used to study the long-lasting effect of epileptic activity by assessing stationary functional connectivity during the resting-state period [especially, the connectivity of the default mode network (DMN)]. Temporal lobe epilepsy (TLE) and idiopathic generalized epilepsy (IGE) are associated with low responsiveness and disruption of DMN activity. A dynamic functional connectivity approach might enable us to determine the effect of IEDs on DMN connectivity and to better understand the correlation between DMN connectivity changes and altered consciousness. Method: We studied dynamic changes in DMN intrinsic connectivity and their relation to IEDs. Six IGE patients (with generalized spike and slow-waves) and 6 TLE patients (with unilateral left temporal spikes) were included. Functional connectivity before, during, and after IEDs was estimated using a sliding window approach and compared with the baseline period. Results: No dependence on window size was observed. The baseline DMN connectivity was decreased in the left hemisphere (ipsilateral to the epileptic focus) in TLEs and was less strong but remained bilateral in IGEs. We observed an overall increase in DMN intrinsic connectivity prior to the onset of IEDs in both IGEs and TLEs. After IEDs in TLEs, we found that DMN connectivity increased before it returned to baseline values. Most of the DMN regions with increased connectivity before and after IEDs were lateralized to the left hemisphere in TLE (i.e., ipsilateral to the epileptic focus). Conclusion: Results suggest that DMN connectivity may facilitate IED generation and may be affected at the time of the IED. However, these results need to be confirmed in a larger independent cohort. PMID:25346721

Intrinsic retrieval efficiency for quantum memories: A three-dimensional theory of light interaction with an atomic ensemble

NASA Astrophysics Data System (ADS)

Gujarati, Tanvi P.; Wu, Yukai; Duan, Luming

2018-03-01

Duan-Lukin-Cirac-Zoller quantum repeater protocol, which was proposed to realize long distance quantum communication, requires usage of quantum memories. Atomic ensembles interacting with optical beams based on off-resonant Raman scattering serve as convenient on-demand quantum memories. Here, a complete free space, three-dimensional theory of the associated read and write process for this quantum memory is worked out with the aim of understanding intrinsic retrieval efficiency. We develop a formalism to calculate the transverse mode structure for the signal and the idler photons and use the formalism to study the intrinsic retrieval efficiency under various configurations. The effects of atomic density fluctuations and atomic motion are incorporated by numerically simulating this system for a range of realistic experimental parameters. We obtain results that describe the variation in the intrinsic retrieval efficiency as a function of the memory storage time for skewed beam configuration at a finite temperature, which provides valuable information for optimization of the retrieval efficiency in experiments.

Brain State Differentiation and Behavioral Inflexibility in Autism†

PubMed Central

Uddin, Lucina Q.; Supekar, Kaustubh; Lynch, Charles J.; Cheng, Katherine M.; Odriozola, Paola; Barth, Maria E.; Phillips, Jennifer; Feinstein, Carl; Abrams, Daniel A.; Menon, Vinod

2015-01-01

Autism spectrum disorders (ASDs) are characterized by social impairments alongside cognitive and behavioral inflexibility. While social deficits in ASDs have extensively been characterized, the neurobiological basis of inflexibility and its relation to core clinical symptoms of the disorder are unknown. We acquired functional neuroimaging data from 2 cohorts, each consisting of 17 children with ASDs and 17 age- and IQ-matched typically developing (TD) children, during stimulus-evoked brain states involving performance of social attention and numerical problem solving tasks, as well as during intrinsic, resting brain states. Effective connectivity between key nodes of the salience network, default mode network, and central executive network was used to obtain indices of functional organization across evoked and intrinsic brain states. In both cohorts examined, a machine learning algorithm was able to discriminate intrinsic (resting) and evoked (task) functional brain network configurations more accurately in TD children than in children with ASD. Brain state discriminability was related to severity of restricted and repetitive behaviors, indicating that weak modulation of brain states may contribute to behavioral inflexibility in ASD. These findings provide novel evidence for a potential link between neurophysiological inflexibility and core symptoms of this complex neurodevelopmental disorder. PMID:25073720

Investigation of violin mode Q for wires of various materials

NASA Astrophysics Data System (ADS)

Dawid, Daryush J.; Kawamura, Seiji

1997-12-01

The Q factors of violin modes for wires of various materials have been measured in order to determine which would be most suitable for use in the suspension of test masses in the initial laser interferometer gravitational wave observatory (LIGO) interferometers. A "guitar" type apparatus was employed to measure violin mode Qs, and losses due to clamping and other practical sources were successfully suppressed below the level of intrinsic wire losses. Steel music wire was found to give the highest extrapolated Q factors under LIGO conditions among the wires we tested. This extrapolated Q sets a target for the LIGO suspension which can be attained if all the losses other than the intrinsic wire loss are successfully suppressed. The measured Qs for the steel, tungsten, and titanium wire, which were approximately frequency independent for the first two to three modes, were found to be roughly proportional to the square root of the tension in the wire. This is consistent with the theory of violin mode losses due to frequency-independent intrinsic wire losses.

Intrinsic phonon bands in high quality monolayer T' molybdenum ditelluride

NASA Astrophysics Data System (ADS)

Chen, Shao-Yu; Naylor, Carl; Goldstein, Thomas; Johnson, Charlie; Yan, Jun

Distorted octahedral (T') transition metal dichalcogenide (TMDC) is a type of layered semimetal that has attracted significant recent attention because of its fascination physical, chemical and nontrivial topological properties. Unlike its hexagonal counterpart, monolayer (1L) T'-TMDC is challenging to work with due to rapid sample degradation in air. In this talk, I will discuss well-protected 1L-T' - MoTe2 that exhibits sharp and robust intrinsic Raman bands, with intensities about one order of magnitude stronger than those from bulk T'-MoTe2. The high quality samples enable us to reveal for the first time the set of all nine even-parity zone-center optical phonons. Crystal angle and light polarization resolved measurements further indicate that all the intrinsic Raman modes belong to either z-mode (vibrating along the zigzag Mo atomic chain) or m-modes (vibrating in the mirror plane). Moreover, with the knowledge of vibrational symmetry, we can effectively distinguish the intrinsic modes from Te-metalloid-like modes with energy around 122 and 141 cm-1 which are associated to the sample degradation. Our studies offer a powerful non-destructive method for assessing sample quality, providing the fingerprint as well as key insights in understanding the fundamental properties of 1L T'-TMDCs.

Localized solutions of Lugiato-Lefever equations with focused pump.

PubMed

Cardoso, Wesley B; Salasnich, Luca; Malomed, Boris A

2017-12-04

Lugiato-Lefever (LL) equations in one and two dimensions (1D and 2D) accurately describe the dynamics of optical fields in pumped lossy cavities with the intrinsic Kerr nonlinearity. The external pump is usually assumed to be uniform, but it can be made tightly focused too-in particular, for building small pixels. We obtain solutions of the LL equations, with both the focusing and defocusing intrinsic nonlinearity, for 1D and 2D confined modes supported by the localized pump. In the 1D setting, we first develop a simple perturbation theory, based in the sech ansatz, in the case of weak pump and loss. Then, a family of exact analytical solutions for spatially confined modes is produced for the pump focused in the form of a delta-function, with a nonlinear loss (two-photon absorption) added to the LL model. Numerical findings demonstrate that these exact solutions are stable, both dynamically and structurally (the latter means that stable numerical solutions close to the exact ones are found when a specific condition, necessary for the existence of the analytical solution, does not hold). In 2D, vast families of stable confined modes are produced by means of a variational approximation and full numerical simulations.

Computer implemented empirical mode decomposition method, apparatus and article of manufacture

NASA Technical Reports Server (NTRS)

Huang, Norden E. (Inventor)

1999-01-01

A computer implemented physical signal analysis method is invented. This method includes two essential steps and the associated presentation techniques of the results. All the steps exist only in a computer: there are no analytic expressions resulting from the method. The first step is a computer implemented Empirical Mode Decomposition to extract a collection of Intrinsic Mode Functions (IMF) from nonlinear, nonstationary physical signals. The decomposition is based on the direct extraction of the energy associated with various intrinsic time scales in the physical signal. Expressed in the IMF's, they have well-behaved Hilbert Transforms from which instantaneous frequencies can be calculated. The second step is the Hilbert Transform. The final result is the Hilbert Spectrum. Thus, the invention can localize any event on the time as well as the frequency axis. The decomposition can also be viewed as an expansion of the data in terms of the IMF's. Then, these IMF's, based on and derived from the data, can serve as the basis of that expansion. The local energy and the instantaneous frequency derived from the IMF's through the Hilbert transform give a full energy-frequency-time distribution of the data which is designated as the Hilbert Spectrum.

Developmental process emerges from extended brain-body-behavior networks

PubMed Central

Byrge, Lisa; Sporns, Olaf; Smith, Linda B.

2014-01-01

Studies of brain connectivity have focused on two modes of networks: structural networks describing neuroanatomy and the intrinsic and evoked dependencies of functional networks at rest and during tasks. Each mode constrains and shapes the other across multiple time scales, and each also shows age-related changes. Here we argue that understanding how brains change across development requires understanding the interplay between behavior and brain networks: changing bodies and activities modify the statistics of inputs to the brain; these changing inputs mold brain networks; these networks, in turn, promote further change in behavior and input. PMID:24862251

Empirical mode decomposition for analyzing acoustical signals

NASA Technical Reports Server (NTRS)

Huang, Norden E. (Inventor)

2005-01-01

The present invention discloses a computer implemented signal analysis method through the Hilbert-Huang Transformation (HHT) for analyzing acoustical signals, which are assumed to be nonlinear and nonstationary. The Empirical Decomposition Method (EMD) and the Hilbert Spectral Analysis (HSA) are used to obtain the HHT. Essentially, the acoustical signal will be decomposed into the Intrinsic Mode Function Components (IMFs). Once the invention decomposes the acoustic signal into its constituting components, all operations such as analyzing, identifying, and removing unwanted signals can be performed on these components. Upon transforming the IMFs into Hilbert spectrum, the acoustical signal may be compared with other acoustical signals.

Functional ultrasound imaging of intrinsic connectivity in the living rat brain with high spatiotemporal resolution

PubMed Central

Osmanski, Bruno-Félix; Pezet, Sophie; Ricobaraza, Ana; Lenkei, Zsolt; Tanter, Mickael

2014-01-01

Long-range coherences in spontaneous brain activity reflect functional connectivity. Here we propose a novel, highly resolved connectivity mapping approach, using ultrafast functional ultrasound (fUS), which enables imaging of cerebral microvascular haemodynamics deep in the anaesthetized rodent brain, through a large thinned-skull cranial window, with pixel dimensions of 100 μm × 100 μm in-plane. The millisecond-range temporal resolution allows unambiguous cancellation of low-frequency cardio-respiratory noise. Both seed-based and singular value decomposition analysis of spatial coherences in the low-frequency (<0.1 Hz) spontaneous fUS signal fluctuations reproducibly report, at different coronal planes, overlapping high-contrast, intrinsic functional connectivity patterns. These patterns are similar to major functional networks described in humans by resting-state fMRI, such as the lateral task-dependent network putatively anticorrelated with the midline default-mode network. These results introduce fUS as a powerful novel neuroimaging method, which could be extended to portable systems for three-dimensional functional connectivity imaging in awake and freely moving rodents. PMID:25277668

Aging-related changes in the default mode network and its anti-correlated networks: a resting-state fMRI study.

PubMed

Wu, Jing-Tao; Wu, Hui-Zhen; Yan, Chao-Gan; Chen, Wen-Xin; Zhang, Hong-Ying; He, Yong; Yang, Hai-Shan

2011-10-17

Intrinsic brain activity in a resting state incorporates components of the task negative network called default mode network (DMN) and task-positive networks called attentional networks. In the present study, the reciprocal neuronal networks in the elder group were compared with the young group to investigate the differences of the intrinsic brain activity using a method of temporal correlation analysis based on seed regions of posterior cingulate cortex (PCC) and ventromedial prefrontal cortex (vmPFC). We found significant decreased positive correlations and negative correlations with the seeds of PCC and vmPFC in the old group. The decreased coactivations in the DMN network components and their negative networks in the old group may reflect age-related alterations in various brain functions such as attention, motor control and inhibition modulation in cognitive processing. These alterations in the resting state anti-correlative networks could provide neuronal substrates for the aging brain. Copyright © 2011 Elsevier Ireland Ltd. All rights reserved.

Capillary wave Hamiltonian for the Landau-Ginzburg-Wilson density functional

NASA Astrophysics Data System (ADS)

Chacón, Enrique; Tarazona, Pedro

2016-06-01

We study the link between the density functional (DF) formalism and the capillary wave theory (CWT) for liquid surfaces, focused on the Landau-Ginzburg-Wilson (LGW) model, or square gradient DF expansion, with a symmetric double parabola free energy, which has been extensively used in theoretical studies of this problem. We show the equivalence between the non-local DF results of Parry and coworkers and the direct evaluation of the mean square fluctuations of the intrinsic surface, as is done in the intrinsic sampling method for computer simulations. The definition of effective wave-vector dependent surface tensions is reviewed and we obtain new proposals for the LGW model. The surface weight proposed by Blokhuis and the surface mode analysis proposed by Stecki provide consistent and optimal effective definitions for the extended CWT Hamiltonian associated to the DF model. A non-local, or coarse-grained, definition of the intrinsic surface provides the missing element to get the mesoscopic surface Hamiltonian from the molecular DF description, as had been proposed a long time ago by Dietrich and coworkers.

Capillary wave Hamiltonian for the Landau-Ginzburg-Wilson density functional.

PubMed

Chacón, Enrique; Tarazona, Pedro

2016-06-22

We study the link between the density functional (DF) formalism and the capillary wave theory (CWT) for liquid surfaces, focused on the Landau-Ginzburg-Wilson (LGW) model, or square gradient DF expansion, with a symmetric double parabola free energy, which has been extensively used in theoretical studies of this problem. We show the equivalence between the non-local DF results of Parry and coworkers and the direct evaluation of the mean square fluctuations of the intrinsic surface, as is done in the intrinsic sampling method for computer simulations. The definition of effective wave-vector dependent surface tensions is reviewed and we obtain new proposals for the LGW model. The surface weight proposed by Blokhuis and the surface mode analysis proposed by Stecki provide consistent and optimal effective definitions for the extended CWT Hamiltonian associated to the DF model. A non-local, or coarse-grained, definition of the intrinsic surface provides the missing element to get the mesoscopic surface Hamiltonian from the molecular DF description, as had been proposed a long time ago by Dietrich and coworkers.

Comparison of intrinsic dynamics of cytochrome p450 proteins using normal mode analysis

PubMed Central

Dorner, Mariah E; McMunn, Ryan D; Bartholow, Thomas G; Calhoon, Brecken E; Conlon, Michelle R; Dulli, Jessica M; Fehling, Samuel C; Fisher, Cody R; Hodgson, Shane W; Keenan, Shawn W; Kruger, Alyssa N; Mabin, Justin W; Mazula, Daniel L; Monte, Christopher A; Olthafer, Augustus; Sexton, Ashley E; Soderholm, Beatrice R; Strom, Alexander M; Hati, Sanchita

2015-01-01

Cytochrome P450 enzymes are hemeproteins that catalyze the monooxygenation of a wide-range of structurally diverse substrates of endogenous and exogenous origin. These heme monooxygenases receive electrons from NADH/NADPH via electron transfer proteins. The cytochrome P450 enzymes, which constitute a diverse superfamily of more than 8,700 proteins, share a common tertiary fold but < 25% sequence identity. Based on their electron transfer protein partner, cytochrome P450 proteins are classified into six broad classes. Traditional methods of pro are based on the canonical paradigm that attributes proteins' function to their three-dimensional structure, which is determined by their primary structure that is the amino acid sequence. It is increasingly recognized that protein dynamics play an important role in molecular recognition and catalytic activity. As the mobility of a protein is an intrinsic property that is encrypted in its primary structure, we examined if different classes of cytochrome P450 enzymes display any unique patterns of intrinsic mobility. Normal mode analysis was performed to characterize the intrinsic dynamics of five classes of cytochrome P450 proteins. The present study revealed that cytochrome P450 enzymes share a strong dynamic similarity (root mean squared inner product > 55% and Bhattacharyya coefficient > 80%), despite the low sequence identity (< 25%) and sequence similarity (< 50%) across the cytochrome P450 superfamily. Noticeable differences in Cα atom fluctuations of structural elements responsible for substrate binding were noticed. These differences in residue fluctuations might be crucial for substrate selectivity in these enzymes. PMID:26130403

Altered Intrinsic Functional Brain Architecture in Children at Familial Risk of Major Depression

PubMed Central

Chai, Xiaoqian J.; Hirshfeld-Becker, Dina; Biederman, Joseph; Uchida, Mai; Doehrmann, Oliver; Leonard, Julia; Salvatore, John; Kenworthy, Tara; Brown, Ariel; Kagan, Elana; de los Angeles, Carlo; Gabrieli, John D.E.; Whitfield-Gabrieli, Susan

2015-01-01

Background Neuroimaging studies of patients with major depression have revealed abnormal intrinsic functional connectivity measured during the resting state in multiple, distributed networks. However, it is unclear whether these findings reflect the state of major depression or reflect trait neurobiological underpinnings of risk for major depression. Methods We compared resting-state functional connectivity, measured with functional magnetic resonance imaging (fMRI), between unaffected children of parents who had documented histories of major depression (at-risk, n = 27; 8–14 years of age) and age-matched children of parents with no lifetime history of depression (controls, n = 16). Results At-risk children exhibited hyperconnectivity between the default mode network (DMN) and subgenual anterior cingulate cortex (sgACC) / orbital frontal cortex (OFC), and the magnitude of connectivity positively correlated with individual symptom scores. At-risk children also exhibited (1) hypoconnectivity within the cognitive control network, which also lacked the typical anticorrelation with the DMN; (2) hypoconnectivity between left dorsolateral prefrontal cortex (DLPFC) and sgACC; and (3) hyperconnectivity between the right amygdala and right inferior frontal gyrus, a key region for top-down modulation of emotion. Classification between at-risk children and controls based on resting-state connectivity yielded high accuracy with high sensitivity and specificity that was superior to clinical rating scales. Conclusions Children at familial risk for depression exhibited atypical functional connectivity in the default-mode, cognitive-control, and affective networks. Such task-independent functional brain measures of risk for depression in children could be used to promote early intervention to reduce the likelihood of developing depression. PMID:26826874

Mode coupling in vortex beams

NASA Astrophysics Data System (ADS)

Eyyuboğlu, Halil T.

2018-05-01

We examine the mode coupling in vortex beams. Mode coupling also known as the crosstalk takes place due to turbulent characteristics of the atmospheric communication medium. This way, the transmitted intrinsic mode of the vortex beam leaks power to other extrinsic modes, thus preventing the correct detection of the transmitted symbol which is usually encoded into the mode index or the orbital angular momentum state of the vortex beam. Here we investigate the normalized power mode coupling ratios of several types of vortex beams, namely, Gaussian vortex beam, Bessel Gaussian beam, hypergeometric Gaussian beam and Laguerre Gaussian beam. It is found that smaller mode numbers lead to less mode coupling. The same is partially observed for increasing source sizes. Comparing the vortex beams amongst themselves, it is seen that hypergeometric Gaussian beam is the one retaining the most power in intrinsic mode during propagation, but only at lowest mode index of unity. At higher mode indices this advantage passes over to the Gaussian vortex beam.

Empirical mode decomposition-based facial pose estimation inside video sequences

NASA Astrophysics Data System (ADS)

Qing, Chunmei; Jiang, Jianmin; Yang, Zhijing

2010-03-01

We describe a new pose-estimation algorithm via integration of the strength in both empirical mode decomposition (EMD) and mutual information. While mutual information is exploited to measure the similarity between facial images to estimate poses, EMD is exploited to decompose input facial images into a number of intrinsic mode function (IMF) components, which redistribute the effect of noise, expression changes, and illumination variations as such that, when the input facial image is described by the selected IMF components, all the negative effects can be minimized. Extensive experiments were carried out in comparisons to existing representative techniques, and the results show that the proposed algorithm achieves better pose-estimation performances with robustness to noise corruption, illumination variation, and facial expressions.

Molecular friction dissipation and mode coupling in organic monolayers and polymer films.

PubMed

Knorr, Daniel B; Widjaja, Peggy; Acton, Orb; Overney, René M

2011-03-14

The impact of thermally active molecular rotational and translational relaxation modes on the friction dissipation process involving smooth nano-asperity contacts has been studied by atomic force microscopy, using the widely known Eyring analysis and a recently introduced method, dubbed intrinsic friction analysis. Two distinctly different model systems, i.e., monolayers of octadecyl-phosphonic acid (ODPA) and thin films of poly(tert-butyl acrylate) (PtBA) were investigated regarding shear-rate critical dissipation phenomena originating from diverging mode coupling behaviors between the external shear perturbation and the internal molecular modes of relaxation. Rapidly (ODPA) versus slowly (PtBA) relaxing systems, in comparison to the sliding rate, revealed monotonous logarithmic and nonmonotonous spectral shear rate dependences, respectively. Shear coupled, enthalpic activation energies of 46 kJ∕mol for ODPA and of 35 and ∼65 kJ∕mol for PtBA (below and above the glass transition) were found that could be attributed to intrinsic modes of relaxations. Also, entropic energies involved in the cooperative backbone mobility of PtBA could be quantified, dwarfing the activation energy by more than a factor of five. This study provides (i) a material specific understanding of the molecular scale dissipation process in shear compliant substances, (ii) analyses of material intrinsic shear-rate mode coupling, shear coordination and energetics, (iii) a verification of Eyring's model applied to tribological systems toward material intrinsic specificity, and (iv) a valuable extension of the Eyring analysis for complex macromolecular systems that are slowly relaxing, and thus, exhibit shear-rate mode coupling.

Method of assessing the state of a rolling bearing based on the relative compensation distance of multiple-domain features and locally linear embedding

NASA Astrophysics Data System (ADS)

Kang, Shouqiang; Ma, Danyang; Wang, Yujing; Lan, Chaofeng; Chen, Qingguo; Mikulovich, V. I.

2017-03-01

To effectively assess different fault locations and different degrees of performance degradation of a rolling bearing with a unified assessment index, a novel state assessment method based on the relative compensation distance of multiple-domain features and locally linear embedding is proposed. First, for a single-sample signal, time-domain and frequency-domain indexes can be calculated for the original vibration signal and each sensitive intrinsic mode function obtained by improved ensemble empirical mode decomposition, and the singular values of the sensitive intrinsic mode function matrix can be extracted by singular value decomposition to construct a high-dimensional hybrid-domain feature vector. Second, a feature matrix can be constructed by arranging each feature vector of multiple samples, the dimensions of each row vector of the feature matrix can be reduced by the locally linear embedding algorithm, and the compensation distance of each fault state of the rolling bearing can be calculated using the support vector machine. Finally, the relative distance between different fault locations and different degrees of performance degradation and the normal-state optimal classification surface can be compensated, and on the basis of the proposed relative compensation distance, the assessment model can be constructed and an assessment curve drawn. Experimental results show that the proposed method can effectively assess different fault locations and different degrees of performance degradation of the rolling bearing under certain conditions.

Characterization of Lateral Structure of the p-i-n Diode for Thin-Film Silicon Solar Cell.

PubMed

Kiaee, Zohreh; Joo, Seung Ki

2018-03-01

The lateral structure of the p-i-n diode was characterized for thin-film silicon solar cell application. The structure can benefit from a wide intrinsic layer, which can improve efficiency without increasing cell thickness. Compared with conventional thin-film p-i-n cells, the p-i-n diode lateral structure exploited direct light irradiation on the absorber layer, one-side contact, and bifacial irradiation. Considering the effect of different carrier lifetimes and recombinations, we calculated efficiency parameters by using a commercially available simulation program as a function of intrinsic layer width, as well as the distance between p/i or n/i junctions to contacts. We then obtained excellent parameter values of 706.52 mV open-circuit voltage, 24.16 mA/Cm2 short-circuit current, 82.66% fill factor, and 14.11% efficiency from a lateral cell (thickness = 3 μm; intrinsic layer width = 53 μm) in monofacial irradiation mode (i.e., only sunlight from the front side was considered). Simulation results of the cell without using rear-side reflector in bifacial irradiation mode showed 11.26% front and 9.72% rear efficiencies. Our findings confirmed that the laterally structured p-i-n cell can be a potentially powerful means for producing highly efficient, thin-film silicon solar cells.

Phase space interrogation of the empirical response modes for seismically excited structures

NASA Astrophysics Data System (ADS)

Paul, Bibhas; George, Riya C.; Mishra, Sudib K.

2017-07-01

Conventional Phase Space Interrogation (PSI) for structural damage assessment relies on exciting the structure with low dimensional chaotic waveform, thereby, significantly limiting their applicability to large structures. The PSI technique is presently extended for structure subjected to seismic excitations. The high dimensionality of the phase space for seismic response(s) are overcome by the Empirical Mode Decomposition (EMD), decomposing the responses to a number of intrinsic low dimensional oscillatory modes, referred as Intrinsic Mode Functions (IMFs). Along with their low dimensionality, a few IMFs, retain sufficient information of the system dynamics to reflect the damage induced changes. The mutually conflicting nature of low-dimensionality and the sufficiency of dynamic information are taken care by the optimal choice of the IMF(s), which is shown to be the third/fourth IMFs. The optimal IMF(s) are employed for the reconstruction of the Phase space attractor following Taken's embedding theorem. The widely referred Changes in Phase Space Topology (CPST) feature is then employed on these Phase portrait(s) to derive the damage sensitive feature, referred as the CPST of the IMFs (CPST-IMF). The legitimacy of the CPST-IMF is established as a damage sensitive feature by assessing its variation with a number of damage scenarios benchmarked in the IASC-ASCE building. The damage localization capability, remarkable tolerance to noise contamination and the robustness under different seismic excitations of the feature are demonstrated.

Salience and Default Mode Network Coupling Predicts Cognition in Aging and Parkinson's Disease.

PubMed

Putcha, Deepti; Ross, Robert S; Cronin-Golomb, Alice; Janes, Amy C; Stern, Chantal E

2016-02-01

Cognitive impairment is common in Parkinson's disease (PD). Three neurocognitive networks support efficient cognition: the salience network, the default mode network, and the central executive network. The salience network is thought to switch between activating and deactivating the default mode and central executive networks. Anti-correlated interactions between the salience and default mode networks in particular are necessary for efficient cognition. Our previous work demonstrated altered functional coupling between the neurocognitive networks in non-demented individuals with PD compared to age-matched control participants. Here, we aim to identify associations between cognition and functional coupling between these neurocognitive networks in the same group of participants. We investigated the extent to which intrinsic functional coupling among these neurocognitive networks is related to cognitive performance across three neuropsychological domains: executive functioning, psychomotor speed, and verbal memory. Twenty-four non-demented individuals with mild to moderate PD and 20 control participants were scanned at rest and evaluated on three neuropsychological domains. PD participants were impaired on tests from all three domains compared to control participants. Our imaging results demonstrated that successful cognition across healthy aging and Parkinson's disease participants was related to anti-correlated coupling between the salience and default mode networks. Individuals with poorer performance scores across groups demonstrated more positive salience network/default-mode network coupling. Successful cognition relies on healthy coupling between the salience and default mode networks, which may become dysfunctional in PD. These results can help inform non-pharmacological interventions (repetitive transcranial magnetic stimulation) targeting these specific networks before they become vulnerable in early stages of Parkinson's disease.

Quantification of the impact of a confounding variable on functional connectivity confirms anti-correlated networks in the resting-state.

PubMed

Carbonell, F; Bellec, P; Shmuel, A

2014-02-01

The effect of regressing out the global average signal (GAS) in resting state fMRI data has become a concern for interpreting functional connectivity analyses. It is not clear whether the reported anti-correlations between the Default Mode and the Dorsal Attention Networks are intrinsic to the brain, or are artificially created by regressing out the GAS. Here we introduce a concept, Impact of the Global Average on Functional Connectivity (IGAFC), for quantifying the sensitivity of seed-based correlation analyses to the regression of the GAS. This voxel-wise IGAFC index is defined as the product of two correlation coefficients: the correlation between the GAS and the fMRI time course of a voxel, times the correlation between the GAS and the seed time course. This definition enables the calculation of a threshold at which the impact of regressing-out the GAS would be large enough to introduce spurious negative correlations. It also yields a post-hoc impact correction procedure via thresholding, which eliminates spurious correlations introduced by regressing out the GAS. In addition, we introduce an Artificial Negative Correlation Index (ANCI), defined as the absolute difference between the IGAFC index and the impact threshold. The ANCI allows a graded confidence scale for ranking voxels according to their likelihood of showing artificial correlations. By applying this method, we observed regions in the Default Mode and Dorsal Attention Networks that were anti-correlated. These findings confirm that the previously reported negative correlations between the Dorsal Attention and Default Mode Networks are intrinsic to the brain and not the result of statistical manipulations. Our proposed quantification of the impact that a confound may have on functional connectivity can be generalized to global effect estimators other than the GAS. It can be readily applied to other confounds, such as systemic physiological or head movement interferences, in order to quantify their impact on functional connectivity in the resting state. © 2013.

Simulation of transverse modes with their intrinsic Landau damping for bunched beams in the presence of space charge

DOE PAGES

Macridin, Alexandru; Burov, Alexey; Stern, Eric; ...

2015-07-22

Transverse dipole modes in bunches with space charge are simulated using the synergia accelerator modeling package and analyzed with dynamic mode decomposition. The properties of the first three space charge modes, including their shape, damping rates, and tune shifts are described over the entire range of space charge strength. As a result, the intrinsic Landau damping predicted and estimated in 2009 by one of the authors is confirmed with a reasonable scaling factor of ≃2.4. For the KV distribution, very good agreement with PATRIC simulations performed by Kornilov and Boine-Frankenheim is obtained.

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

PubMed

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-connectome, particularly in the context of data fusion.

Beyond the Boost: Measuring the Intrinsic Dipole of the Cosmic Microwave Background Using the Spectral Distortions of the Monopole and Quadrupole.

PubMed

Yasini, Siavash; Pierpaoli, Elena

2017-12-01

We present a general framework for the accurate spectral modeling of the low multipoles of the cosmic microwave background (CMB) as observed in a boosted frame. In particular, we demonstrate how spectral measurements of the low multipoles can be used to separate the motion-induced dipole of the CMB from a possible intrinsic dipole component. In a moving frame, the leakage of an intrinsic dipole moment into the CMB monopole and quadrupole induces spectral distortions with distinct frequency functions that, respectively, peak at 337 and 276 GHz. The leakage into the quadrupole moment also induces a geometrical distortion to the spatial morphology of this mode. The combination of these effects can be used to lift the degeneracy between the motion-induced dipole and any intrinsic dipole that the CMB might possess. Assuming the current peculiar velocity measurements, the leakage of an intrinsic dipole with an amplitude of ΔT=30  μK into the monopole and quadrupole moments will be detectable by a PIXIE-like experiment at ∼40  nK (2.5σ) and ∼130  nK (11σ) level at their respective peak frequencies.

Trapped electron mode turbulence driven intrinsic rotation in Tokamak plasmas.

PubMed

Wang, W X; Hahm, T S; Ethier, S; Zakharov, L E; Diamond, P H

2011-02-25

Progress from global gyrokinetic simulations in understanding the origin of intrinsic rotation in toroidal plasmas is reported. The turbulence-driven intrinsic torque associated with nonlinear residual stress generation due to zonal flow shear induced asymmetry in the parallel wave number spectrum is shown to scale close to linearly with plasma gradients and the inverse of the plasma current, qualitatively reproducing experimental empirical scalings of intrinsic rotation. The origin of current scaling is found to be enhanced k(∥) symmetry breaking induced by the increased radial variation of the safety factor as the current decreases. The intrinsic torque is proportional to the pressure gradient because both turbulence intensity and zonal flow shear, which are two key ingredients for driving residual stress, increase with turbulence drive, which is R/L(T(e)) and R/L(n(e)) for the trapped electron mode. © 2011 American Physical Society

Terahertz emission from the intrinsic Josephson junctions of high-symmetry thermally-managed Bi2Sr2CaCu2O8+δ microstrip antennas

NASA Astrophysics Data System (ADS)

Klemm, Richard A.; Davis, Andrew E.; Wang, Qing X.; Yamamoto, Takashi; Cerkoney, Daniel P.; Reid, Candy; Koopman, Maximiliaan L.; Minami, Hidetoshi; Kashiwagi, Takanari; Rain, Joseph R.; Doty, Constance M.; Sedlack, Michael A.; Morales, Manuel A.; Watanabe, Chiharu; Tsujimoto, Manabu; Delfanazari, Kaveh; Kadowaki, Kazuo

2017-12-01

We show for high-symmetry disk, square, or equilateral triangular thin microstrip antennas of any composition respectively obeying C ∞v , C 4v , and C 3v point group symmetries, that the transverse magnetic electromagnetic cavity mode wave functions are restricted in form to those that are one-dimensional representations of those point groups. Plots of the common nodal points of the ten lowest-energy non-radiating two-dimensional representations of each of these three symmetries are presented. For comparison with symmetry-broken disk intrinsic Josephson junction microstrip antennas constructed from the highly anisotropic layered superconductor Bi2Sr2CaCu2O8+δ (BSCCO), we present plots of the ten lowest frequency orthonormal wave functions and of their emission power angular distributions. These results are compared with previous results for square and equilateral triangular thin microstrip antennas.

Cavity mode enhancement of terahertz emission from equilateral triangular microstrip antennas of the high-T c superconductor Bi2Sr2CaCu2O8 + δ

NASA Astrophysics Data System (ADS)

Cerkoney, Daniel P.; Reid, Candy; Doty, Constance M.; Gramajo, Ashley; Campbell, Tyler D.; Morales, Manuel A.; Delfanazari, Kaveh; Tsujimoto, Manabu; Kashiwagi, Takanari; Yamamoto, Takashi; Watanabe, Chiharu; Minami, Hidetoshi; Kadowaki, Kazuo; Klemm, Richard A.

2017-01-01

We study the transverse magnetic (TM) electromagnetic cavity mode wave functions for an ideal equilateral triangular microstrip antenna (MSA) exhibiting C 3v point group symmetry. When the C 3v operations are imposed upon the antenna, the TM(m,n) modes with wave vectors \\propto \\sqrt{{{m}2}+nm+{{n}2}} are much less dense than commonly thought. The R 3 operations restrict the integral n and m to satisfy |m-n| =3p , where p≥slant 0 and p≥slant 1 for the modes even and odd under reflections about the three mirror planes, respectively. We calculate the forms of representative wave functions and the angular dependence of the output power when these modes are excited by the uniform and non-uniform ac Josephson current sources in thin, ideally equilateral triangular MSAs employing the intrinsic Josephson junctions in the high transition temperature T c superconductor Bi2Sr2CaCu2 {{\\text{O}}8+δ} , and fit the emissions data from an earlier sample for which the C 3v symmetry was apparently broken.

Intrinsic Neuronal Properties Switch the Mode of Information Transmission in Networks

PubMed Central

Gjorgjieva, Julijana; Mease, Rebecca A.; Moody, William J.; Fairhall, Adrienne L.

2014-01-01

Diverse ion channels and their dynamics endow single neurons with complex biophysical properties. These properties determine the heterogeneity of cell types that make up the brain, as constituents of neural circuits tuned to perform highly specific computations. How do biophysical properties of single neurons impact network function? We study a set of biophysical properties that emerge in cortical neurons during the first week of development, eventually allowing these neurons to adaptively scale the gain of their response to the amplitude of the fluctuations they encounter. During the same time period, these same neurons participate in large-scale waves of spontaneously generated electrical activity. We investigate the potential role of experimentally observed changes in intrinsic neuronal properties in determining the ability of cortical networks to propagate waves of activity. We show that such changes can strongly affect the ability of multi-layered feedforward networks to represent and transmit information on multiple timescales. With properties modeled on those observed at early stages of development, neurons are relatively insensitive to rapid fluctuations and tend to fire synchronously in response to wave-like events of large amplitude. Following developmental changes in voltage-dependent conductances, these same neurons become efficient encoders of fast input fluctuations over few layers, but lose the ability to transmit slower, population-wide input variations across many layers. Depending on the neurons' intrinsic properties, noise plays different roles in modulating neuronal input-output curves, which can dramatically impact network transmission. The developmental change in intrinsic properties supports a transformation of a networks function from the propagation of network-wide information to one in which computations are scaled to local activity. This work underscores the significance of simple changes in conductance parameters in governing how neurons represent and propagate information, and suggests a role for background synaptic noise in switching the mode of information transmission. PMID:25474701

Interactive Structure (EUCLID) For Static And Dynamic Representation Of Human Body

NASA Astrophysics Data System (ADS)

Renaud, Ch.; Steck, R.

1983-07-01

A specific software (EUCLID) for static and dynamic representation of human models is described. The data processing system is connected with ERGODATA and used in interactive mode by intrinsic or specific functions. More or less complex representations in 3-D view of models of the human body are developed. Biostereometric and conventional anthropometric raw data from the data bank are processed for different applications in ergonomy.

[An EMD based time-frequency distribution and its application in EEG analysis].

PubMed

Li, Xiaobing; Chu, Meng; Qiu, Tianshuang; Bao, Haiping

2007-10-01

Hilbert-Huang transform (HHT) is a new time-frequency analytic method to analyze the nonlinear and the non-stationary signals. The key step of this method is the empirical mode decomposition (EMD), with which any complicated signal can be decomposed into a finite and small number of intrinsic mode functions (IMF). In this paper, a new EMD based method for suppressing the cross-term of Wigner-Ville distribution (WVD) is developed and is applied to analyze the epileptic EEG signals. The simulation data and analysis results show that the new method suppresses the cross-term of the WVD effectively with an excellent resolution.

Continuous-variable quantum computing in optical time-frequency modes using quantum memories.

PubMed

Humphreys, Peter C; Kolthammer, W Steven; Nunn, Joshua; Barbieri, Marco; Datta, Animesh; Walmsley, Ian A

2014-09-26

We develop a scheme for time-frequency encoded continuous-variable cluster-state quantum computing using quantum memories. In particular, we propose a method to produce, manipulate, and measure two-dimensional cluster states in a single spatial mode by exploiting the intrinsic time-frequency selectivity of Raman quantum memories. Time-frequency encoding enables the scheme to be extremely compact, requiring a number of memories that are a linear function of only the number of different frequencies in which the computational state is encoded, independent of its temporal duration. We therefore show that quantum memories can be a powerful component for scalable photonic quantum information processing architectures.

Altered intrinsic and extrinsic connectivity in schizophrenia.

PubMed

Zhou, Yuan; Zeidman, Peter; Wu, Shihao; Razi, Adeel; Chen, Cheng; Yang, Liuqing; Zou, Jilin; Wang, Gaohua; Wang, Huiling; Friston, Karl J

2018-01-01

Schizophrenia is a disorder characterized by functional dysconnectivity among distributed brain regions. However, it is unclear how causal influences among large-scale brain networks are disrupted in schizophrenia. In this study, we used dynamic causal modeling (DCM) to assess the hypothesis that there is aberrant directed (effective) connectivity within and between three key large-scale brain networks (the dorsal attention network, the salience network and the default mode network) in schizophrenia during a working memory task. Functional MRI data during an n-back task from 40 patients with schizophrenia and 62 healthy controls were analyzed. Using hierarchical modeling of between-subject effects in DCM with Parametric Empirical Bayes, we found that intrinsic (within-region) and extrinsic (between-region) effective connectivity involving prefrontal regions were abnormal in schizophrenia. Specifically, in patients (i) inhibitory self-connections in prefrontal regions of the dorsal attention network were decreased across task conditions; (ii) extrinsic connectivity between regions of the default mode network was increased; specifically, from posterior cingulate cortex to the medial prefrontal cortex; (iii) between-network extrinsic connections involving the prefrontal cortex were altered; (iv) connections within networks and between networks were correlated with the severity of clinical symptoms and impaired cognition beyond working memory. In short, this study revealed the predominance of reduced synaptic efficacy of prefrontal efferents and afferents in the pathophysiology of schizophrenia.

Ultrafast, Broad-Band, Passive Laser Shields Based on Novel Semiconductor/Conducting Polymer Interface Technology - SBIR 89.I (A89-083). Phase 1

DTIC Science & Technology

1990-02-14

of the present results to be in the tens of uJ/cm’. f) Comparatively high laser damage thresholds , due to the innate properties of the polymers used. g...number of interface systems switched in this mode as well. Intrinsic laser - induced polymer switching and nonlinear optical effects in these polymers...Effective Laser Shields Essential functional attributes of functional laser filters are ns or sub-ns risetimes, broad-band action (across the visible, near-IR

Comparison of two interpolation methods for empirical mode decomposition based evaluation of radiographic femur bone images.

PubMed

Udhayakumar, Ganesan; Sujatha, Chinnaswamy Manoharan; Ramakrishnan, Swaminathan

2013-01-01

Analysis of bone strength in radiographic images is an important component of estimation of bone quality in diseases such as osteoporosis. Conventional radiographic femur bone images are used to analyze its architecture using bi-dimensional empirical mode decomposition method. Surface interpolation of local maxima and minima points of an image is a crucial part of bi-dimensional empirical mode decomposition method and the choice of appropriate interpolation depends on specific structure of the problem. In this work, two interpolation methods of bi-dimensional empirical mode decomposition are analyzed to characterize the trabecular femur bone architecture of radiographic images. The trabecular bone regions of normal and osteoporotic femur bone images (N = 40) recorded under standard condition are used for this study. The compressive and tensile strength regions of the images are delineated using pre-processing procedures. The delineated images are decomposed into their corresponding intrinsic mode functions using interpolation methods such as Radial basis function multiquadratic and hierarchical b-spline techniques. Results show that bi-dimensional empirical mode decomposition analyses using both interpolations are able to represent architectural variations of femur bone radiographic images. As the strength of the bone depends on architectural variation in addition to bone mass, this study seems to be clinically useful.

Noise-assisted data processing with empirical mode decomposition in biomedical signals.

PubMed

Karagiannis, Alexandros; Constantinou, Philip

2011-01-01

In this paper, a methodology is described in order to investigate the performance of empirical mode decomposition (EMD) in biomedical signals, and especially in the case of electrocardiogram (ECG). Synthetic ECG signals corrupted with white Gaussian noise are employed and time series of various lengths are processed with EMD in order to extract the intrinsic mode functions (IMFs). A statistical significance test is implemented for the identification of IMFs with high-level noise components and their exclusion from denoising procedures. Simulation campaign results reveal that a decrease of processing time is accomplished with the introduction of preprocessing stage, prior to the application of EMD in biomedical time series. Furthermore, the variation in the number of IMFs according to the type of the preprocessing stage is studied as a function of SNR and time-series length. The application of the methodology in MIT-BIH ECG records is also presented in order to verify the findings in real ECG signals.

Adaptive DSPI phase denoising using mutual information and 2D variational mode decomposition

NASA Astrophysics Data System (ADS)

Xiao, Qiyang; Li, Jian; Wu, Sijin; Li, Weixian; Yang, Lianxiang; Dong, Mingli; Zeng, Zhoumo

2018-04-01

In digital speckle pattern interferometry (DSPI), noise interference leads to a low peak signal-to-noise ratio (PSNR) and measurement errors in the phase map. This paper proposes an adaptive DSPI phase denoising method based on two-dimensional variational mode decomposition (2D-VMD) and mutual information. Firstly, the DSPI phase map is subjected to 2D-VMD in order to obtain a series of band-limited intrinsic mode functions (BLIMFs). Then, on the basis of characteristics of the BLIMFs and in combination with mutual information, a self-adaptive denoising method is proposed to obtain noise-free components containing the primary phase information. The noise-free components are reconstructed to obtain the denoising DSPI phase map. Simulation and experimental results show that the proposed method can effectively reduce noise interference, giving a PSNR that is higher than that of two-dimensional empirical mode decomposition methods.

Acoustic emission signal processing technique to characterize reactor in-pile phenomena

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

Agarwal, Vivek, E-mail: vivek.agarwal@inl.gov; Tawfik, Magdy S., E-mail: magdy.tawfik@inl.gov; Smith, James A., E-mail: james.smith@inl.gov

2015-03-31

Existing and developing advanced sensor technologies and instrumentation will allow non-intrusive in-pile measurement of temperature, extension, and fission gases when coupled with advanced signal processing algorithms. The transmitted measured sensor signals from inside to the outside of containment structure are corrupted by noise and are attenuated, thereby reducing the signal strength and the signal-to-noise ratio. Identification and extraction of actual signal (representative of an in-pile phenomenon) is a challenging and complicated process. In the paper, empirical mode decomposition technique is utilized to reconstruct actual sensor signal by partially combining intrinsic mode functions. Reconstructed signal will correspond to phenomena and/or failuremore » modes occurring inside the reactor. In addition, it allows accurate non-intrusive monitoring and trending of in-pile phenomena.« less

Empirical mode decomposition apparatus, method and article of manufacture for analyzing biological signals and performing curve fitting

NASA Technical Reports Server (NTRS)

Huang, Norden E. (Inventor)

2004-01-01

A computer implemented physical signal analysis method includes four basic steps and the associated presentation techniques of the results. The first step is a computer implemented Empirical Mode Decomposition that extracts a collection of Intrinsic Mode Functions (IMF) from nonlinear, nonstationary physical signals. The decomposition is based on the direct extraction of the energy associated with various intrinsic time scales in the physical signal. Expressed in the IMF's, they have well-behaved Hilbert Transforms from which instantaneous frequencies can be calculated. The second step is the Hilbert Transform which produces a Hilbert Spectrum. Thus, the invention can localize any event on the time as well as the frequency axis. The decomposition can also be viewed as an expansion of the data in terms of the IMF's. Then, these IMF's, based on and derived from the data, can serve as the basis of that expansion. The local energy and the instantaneous frequency derived from the IMF's through the Hilbert transform give a full energy-frequency-time distribution of the data which is designated as the Hilbert Spectrum. The third step filters the physical signal by combining a subset of the IMFs. In the fourth step, a curve may be fitted to the filtered signal which may not have been possible with the original, unfiltered signal.

Instantaneous Respiratory Estimation from Thoracic Impedance by Empirical Mode Decomposition.

PubMed

Wang, Fu-Tai; Chan, Hsiao-Lung; Wang, Chun-Li; Jian, Hung-Ming; Lin, Sheng-Hsiung

2015-07-07

Impedance plethysmography provides a way to measure respiratory activity by sensing the change of thoracic impedance caused by inspiration and expiration. This measurement imposes little pressure on the body and uses the human body as the sensor, thereby reducing the need for adjustments as body position changes and making it suitable for long-term or ambulatory monitoring. The empirical mode decomposition (EMD) can decompose a signal into several intrinsic mode functions (IMFs) that disclose nonstationary components as well as stationary components and, similarly, capture respiratory episodes from thoracic impedance. However, upper-body movements usually produce motion artifacts that are not easily removed by digital filtering. Moreover, large motion artifacts disable the EMD to decompose respiratory components. In this paper, motion artifacts are detected and replaced by the data mirrored from the prior and the posterior before EMD processing. A novel intrinsic respiratory reconstruction index that considers both global and local properties of IMFs is proposed to define respiration-related IMFs for respiration reconstruction and instantaneous respiratory estimation. Based on the experiments performing a series of static and dynamic physical activates, our results showed the proposed method had higher cross correlations between respiratory frequencies estimated from thoracic impedance and those from oronasal airflow based on small window size compared to the Fourier transform-based method.

Instantaneous Respiratory Estimation from Thoracic Impedance by Empirical Mode Decomposition

PubMed Central

Wang, Fu-Tai; Chan, Hsiao-Lung; Wang, Chun-Li; Jian, Hung-Ming; Lin, Sheng-Hsiung

2015-01-01

Impedance plethysmography provides a way to measure respiratory activity by sensing the change of thoracic impedance caused by inspiration and expiration. This measurement imposes little pressure on the body and uses the human body as the sensor, thereby reducing the need for adjustments as body position changes and making it suitable for long-term or ambulatory monitoring. The empirical mode decomposition (EMD) can decompose a signal into several intrinsic mode functions (IMFs) that disclose nonstationary components as well as stationary components and, similarly, capture respiratory episodes from thoracic impedance. However, upper-body movements usually produce motion artifacts that are not easily removed by digital filtering. Moreover, large motion artifacts disable the EMD to decompose respiratory components. In this paper, motion artifacts are detected and replaced by the data mirrored from the prior and the posterior before EMD processing. A novel intrinsic respiratory reconstruction index that considers both global and local properties of IMFs is proposed to define respiration-related IMFs for respiration reconstruction and instantaneous respiratory estimation. Based on the experiments performing a series of static and dynamic physical activates, our results showed the proposed method had higher cross correlations between respiratory frequencies estimated from thoracic impedance and those from oronasal airflow based on small window size compared to the Fourier transform-based method. PMID:26198231

Empirical mode decomposition apparatus, method and article of manufacture for analyzing biological signals and performing curve fitting

NASA Technical Reports Server (NTRS)

Huang, Norden E. (Inventor)

2002-01-01

A computer implemented physical signal analysis method includes four basic steps and the associated presentation techniques of the results. The first step is a computer implemented Empirical Mode Decomposition that extracts a collection of Intrinsic Mode Functions (IMF) from nonlinear, nonstationary physical signals. The decomposition is based on the direct extraction of the energy associated with various intrinsic time scales in the physical signal. Expressed in the IMF's, they have well-behaved Hilbert Transforms from which instantaneous frequencies can be calculated. The second step is the Hilbert Transform which produces a Hilbert Spectrum. Thus, the invention can localize any event on the time as well as the frequency axis. The decomposition can also be viewed as an expansion of the data in terms of the IMF's. Then, these IMF's, based on and derived from the data, can serve as the basis of that expansion. The local energy and the instantaneous frequency derived from the IMF's through the Hilbert transform give a full energy-frequency-time distribution of the data which is designated as the Hilbert Spectrum. The third step filters the physical signal by combining a subset of the IMFs. In the fourth step, a curve may be fitted to the filtered signal which may not have been possible with the original, unfiltered signal.

Computer implemented empirical mode decomposition method apparatus, and article of manufacture utilizing curvature extrema

NASA Technical Reports Server (NTRS)

Shen, Zheng (Inventor); Huang, Norden Eh (Inventor)

2003-01-01

A computer implemented physical signal analysis method is includes two essential steps and the associated presentation techniques of the results. All the steps exist only in a computer: there are no analytic expressions resulting from the method. The first step is a computer implemented Empirical Mode Decomposition to extract a collection of Intrinsic Mode Functions (IMF) from nonlinear, nonstationary physical signals based on local extrema and curvature extrema. The decomposition is based on the direct extraction of the energy associated with various intrinsic time scales in the physical signal. Expressed in the IMF's, they have well-behaved Hilbert Transforms from which instantaneous frequencies can be calculated. The second step is the Hilbert Transform. The final result is the Hilbert Spectrum. Thus, the invention can localize any event on the time as well as the frequency axis. The decomposition can also be viewed as an expansion of the data in terms of the IMF's. Then, these IMF's, based on and derived from the data, can serve as the basis of that expansion. The local energy and the instantaneous frequency derived from the IMF's through the Hilbert transform give a full energy-frequency-time distribution of the data which is designated as the Hilbert Spectrum.

Wavelet-bounded empirical mode decomposition for measured time series analysis

NASA Astrophysics Data System (ADS)

Moore, Keegan J.; Kurt, Mehmet; Eriten, Melih; McFarland, D. Michael; Bergman, Lawrence A.; Vakakis, Alexander F.

2018-01-01

Empirical mode decomposition (EMD) is a powerful technique for separating the transient responses of nonlinear and nonstationary systems into finite sets of nearly orthogonal components, called intrinsic mode functions (IMFs), which represent the dynamics on different characteristic time scales. However, a deficiency of EMD is the mixing of two or more components in a single IMF, which can drastically affect the physical meaning of the empirical decomposition results. In this paper, we present a new approached based on EMD, designated as wavelet-bounded empirical mode decomposition (WBEMD), which is a closed-loop, optimization-based solution to the problem of mode mixing. The optimization routine relies on maximizing the isolation of an IMF around a characteristic frequency. This isolation is measured by fitting a bounding function around the IMF in the frequency domain and computing the area under this function. It follows that a large (small) area corresponds to a poorly (well) separated IMF. An optimization routine is developed based on this result with the objective of minimizing the bounding-function area and with the masking signal parameters serving as free parameters, such that a well-separated IMF is extracted. As examples of application of WBEMD we apply the proposed method, first to a stationary, two-component signal, and then to the numerically simulated response of a cantilever beam with an essentially nonlinear end attachment. We find that WBEMD vastly improves upon EMD and that the extracted sets of IMFs provide insight into the underlying physics of the response of each system.

BOLD signal and functional connectivity associated with loving kindness meditation

PubMed Central

Garrison, Kathleen A; Scheinost, Dustin; Constable, R Todd; Brewer, Judson A

2014-01-01

Loving kindness is a form of meditation involving directed well-wishing, typically supported by the silent repetition of phrases such as “may all beings be happy,” to foster a feeling of selfless love. Here we used functional magnetic resonance imaging to assess the neural substrate of loving kindness meditation in experienced meditators and novices. We first assessed group differences in blood oxygen level-dependent (BOLD) signal during loving kindness meditation. We next used a relatively novel approach, the intrinsic connectivity distribution of functional connectivity, to identify regions that differ in intrinsic connectivity between groups, and then used a data-driven approach to seed-based connectivity analysis to identify which connections differ between groups. Our findings suggest group differences in brain regions involved in self-related processing and mind wandering, emotional processing, inner speech, and memory. Meditators showed overall reduced BOLD signal and intrinsic connectivity during loving kindness as compared to novices, more specifically in the posterior cingulate cortex/precuneus (PCC/PCu), a finding that is consistent with our prior work and other recent neuroimaging studies of meditation. Furthermore, meditators showed greater functional connectivity during loving kindness between the PCC/PCu and the left inferior frontal gyrus, whereas novices showed greater functional connectivity during loving kindness between the PCC/PCu and other cortical midline regions of the default mode network, the bilateral posterior insula lobe, and the bilateral parahippocampus/hippocampus. These novel findings suggest that loving kindness meditation involves a present-centered, selfless focus for meditators as compared to novices. PMID:24944863

Intrinsic brain networks normalize with treatment in pediatric complex regional pain syndrome

PubMed Central

Becerra, Lino; Sava, Simona; Simons, Laura E.; Drosos, Athena M.; Sethna, Navil; Berde, Charles; Lebel, Alyssa A.; Borsook, David

2014-01-01

Pediatric complex regional pain syndrome (P-CRPS) offers a unique model of chronic neuropathic pain as it either resolves spontaneously or through therapeutic interventions in most patients. Here we evaluated brain changes in well-characterized children and adolescents with P-CRPS by measuring resting state networks before and following a brief (median = 3 weeks) but intensive physical and psychological treatment program, and compared them to matched healthy controls. Differences in intrinsic brain networks were observed in P-CRPS compared to controls before treatment (disease state) with the most prominent differences in the fronto-parietal, salience, default mode, central executive, and sensorimotor networks. Following treatment, behavioral measures demonstrated a reduction of symptoms and improvement of physical state (pain levels and motor functioning). Correlation of network connectivities with spontaneous pain measures pre- and post-treatment indicated concomitant reductions in connectivity in salience, central executive, default mode and sensorimotor networks (treatment effects). These results suggest a rapid alteration in global brain networks with treatment and provide a venue to assess brain changes in CRPS pre- and post-treatment, and to evaluate therapeutic effects. PMID:25379449

Graphene annealing: how clean can it be?

PubMed

Lin, Yung-Chang; Lu, Chun-Chieh; Yeh, Chao-Huei; Jin, Chuanhong; Suenaga, Kazu; Chiu, Po-Wen

2012-01-11

Surface contamination by polymer residues has long been a critical problem in probing graphene's intrinsic properties and in using graphene for unique applications in surface chemistry, biotechnology, and ultrahigh speed electronics. Poly(methyl methacrylate) (PMMA) is a macromolecule commonly used for graphene transfer and device processing, leaving a thin layer of residue to be empirically cleaned by annealing. Here we report on a systematic study of PMMA decomposition on graphene and of its impact on graphene's intrinsic properties using transmission electron microscopy (TEM) in combination with Raman spectroscopy. TEM images revealed that the physisorbed PMMA proceeds in two steps of weight loss in annealing and cannot be removed entirely at a graphene susceptible temperature before breaking. Raman analysis shows a remarkable blue-shift of the 2D mode after annealing, implying an anneal-induced band structure modulation in graphene with defects. Calculations using density functional theory show that local rehybridization of carbons from sp(2) to sp(3) on graphene defects may occur in the random scission of polymer chains and account for the blue-shift of the Raman 2D mode. © 2011 American Chemical Society

Chemical perturbation of an intrinsically disordered region of TFIID distinguishes two modes of transcription initiation

PubMed Central

Zhang, Zhengjian; Boskovic, Zarko; Hussain, Mahmud M; Hu, Wenxin; Inouye, Carla; Kim, Han-Je; Abole, A Katherine; Doud, Mary K; Lewis, Timothy A; Koehler, Angela N; Schreiber, Stuart L; Tjian, Robert

2015-01-01

Intrinsically disordered proteins/regions (IDPs/IDRs) are proteins or peptide segments that fail to form stable 3-dimensional structures in the absence of partner proteins. They are abundant in eukaryotic proteomes and are often associated with human diseases, but their biological functions have been elusive to study. In this study, we report the identification of a tin(IV) oxochloride-derived cluster that binds an evolutionarily conserved IDR within the metazoan TFIID transcription complex. Binding arrests an isomerization of promoter-bound TFIID that is required for the engagement of Pol II during the first (de novo) round of transcription initiation. However, the specific chemical probe does not affect reinitiation, which requires the re-entry of Pol II, thus, mechanistically distinguishing these two modes of transcription initiation. This work also suggests a new avenue for targeting the elusive IDRs by harnessing certain features of metal-based complexes for mechanistic studies, and for the development of novel pharmaceutical interventions. DOI: http://dx.doi.org/10.7554/eLife.07777.001 PMID:26314865

Analysis of the Nonlinear Trends and Non-Stationary Oscillations of Regional Precipitation in Xinjiang, Northwestern China, Using Ensemble Empirical Mode Decomposition

PubMed Central

Guo, Bin; Chen, Zhongsheng; Guo, Jinyun; Liu, Feng; Chen, Chuanfa; Liu, Kangli

2016-01-01

Changes in precipitation could have crucial influences on the regional water resources in arid regions such as Xinjiang. It is necessary to understand the intrinsic multi-scale variations of precipitation in different parts of Xinjiang in the context of climate change. In this study, based on precipitation data from 53 meteorological stations in Xinjiang during 1960–2012, we investigated the intrinsic multi-scale characteristics of precipitation variability using an adaptive method named ensemble empirical mode decomposition (EEMD). Obvious non-linear upward trends in precipitation were found in the north, south, east and the entire Xinjiang. Changes in precipitation in Xinjiang exhibited significant inter-annual scale (quasi-2 and quasi-6 years) and inter-decadal scale (quasi-12 and quasi-23 years). Moreover, the 2–3-year quasi-periodic fluctuation was dominant in regional precipitation and the inter-annual variation had a considerable effect on the regional-scale precipitation variation in Xinjiang. We also found that there were distinctive spatial differences in variation trends and turning points of precipitation in Xinjiang. The results of this study indicated that compared to traditional decomposition methods, the EEMD method, without using any a priori determined basis functions, could effectively extract the reliable multi-scale fluctuations and reveal the intrinsic oscillation properties of climate elements. PMID:27007388

Cerebrovascular pattern improved by ozone autohemotherapy: an entropy-based study on multiple sclerosis patients.

PubMed

Molinari, Filippo; Rimini, Daniele; Liboni, William; Acharya, U Rajendra; Franzini, Marianno; Pandolfi, Sergio; Ricevuti, Giovanni; Vaiano, Francesco; Valdenassi, Luigi; Simonetti, Vincenzo

2017-08-01

Ozone major autohemotherapy is effective in reducing the symptoms of multiple sclerosis (MS) patients, but its effects on brain are still not clear. In this work, we have monitored the changes in the cerebrovascular pattern of MS patients and normal subjects during major ozone autohemotherapy by using near-infrared spectroscopy (NIRS) as functional and vascular technique. NIRS signals are analyzed using a combination of time, time-frequency analysis and nonlinear analysis of intrinsic mode function signals obtained from empirical mode decomposition technique. Our results show that there is an improvement in the cerebrovascular pattern of all subjects indicated by increasing the entropy of the NIRS signals. Hence, we can conclude that the ozone therapy increases the brain metabolism and helps to recover from the lower activity levels which is predominant in MS patients.

EMD-WVD time-frequency distribution for analysis of multi-component signals

NASA Astrophysics Data System (ADS)

Chai, Yunzi; Zhang, Xudong

2016-10-01

Time-frequency distribution (TFD) is two-dimensional function that indicates the time-varying frequency content of one-dimensional signals. And The Wigner-Ville distribution (WVD) is an important and effective time-frequency analysis method. The WVD can efficiently show the characteristic of a mono-component signal. However, a major drawback is the extra cross-terms when multi-component signals are analyzed by WVD. In order to eliminating the cross-terms, we decompose signals into single frequency components - Intrinsic Mode Function (IMF) - by using the Empirical Mode decomposition (EMD) first, then use WVD to analyze each single IMF. In this paper, we define this new time-frequency distribution as EMD-WVD. And the experiment results show that the proposed time-frequency method can solve the cross-terms problem effectively and improve the accuracy of WVD time-frequency analysis.

Analysis of turbine-grid interaction of grid-connected wind turbine using HHT

NASA Astrophysics Data System (ADS)

Chen, A.; Wu, W.; Miao, J.; Xie, D.

2018-05-01

This paper processes the output power of the grid-connected wind turbine with the denoising and extracting method based on Hilbert Huang transform (HHT) to discuss the turbine-grid interaction. At first, the detailed Empirical Mode Decomposition (EMD) and the Hilbert Transform (HT) are introduced. Then, on the premise of decomposing the output power of the grid-connected wind turbine into a series of Intrinsic Mode Functions (IMFs), energy ratio and power volatility are calculated to detect the unessential components. Meanwhile, combined with vibration function of turbine-grid interaction, data fitting of instantaneous amplitude and phase of each IMF is implemented to extract characteristic parameters of different interactions. Finally, utilizing measured data of actual parallel-operated wind turbines in China, this work accurately obtains the characteristic parameters of turbine-grid interaction of grid-connected wind turbine.

Forced and intrinsic variability in the response to increased wind stress of an idealized Southern Ocean

NASA Astrophysics Data System (ADS)

Wilson, Chris; Hughes, Chris W.; Blundell, Jeffrey R.

2015-01-01

use ensemble runs of a three layer, quasi-geostrophic idealized Southern Ocean model to explore the roles of forced and intrinsic variability in response to a linear increase of wind stress imposed over a 30 year period. We find no increase of eastward circumpolar volume transport in response to the increased wind stress. A large part of the resulting time series can be explained by a response in which the eddy kinetic energy is linearly proportional to the wind stress with a possible time lag, but no statistically significant lag is found. However, this simple relationship is not the whole story: several intrinsic time scales also influence the response. We find an e-folding time scale for growth of small perturbations of 1-2 weeks. The energy budget for intrinsic variability at periods shorter than a year is dominated by exchange between kinetic and potential energy. At longer time scales, we find an intrinsic mode with period in the region of 15 years, which is dominated by changes in potential energy and frictional dissipation in a manner consistent with that seen by Hogg and Blundell (2006). A similar mode influences the response to changing wind stress. This influence, robust to perturbations, is different from the supposed linear relationship between wind stress and eddy kinetic energy, and persists for 5-10 years in this model, suggestive of a forced oscillatory mode with period of around 15 years. If present in the real ocean, such a mode would imply a degree of predictability of Southern Ocean dynamics on multiyear time scales.

Linked functional network abnormalities during intrinsic and extrinsic activity in schizophrenia as revealed by a data-fusion approach.

PubMed

Hashimoto, Ryu-Ichiro; Itahashi, Takashi; Okada, Rieko; Hasegawa, Sayaka; Tani, Masayuki; Kato, Nobumasa; Mimura, Masaru

2018-01-01

Abnormalities in functional brain networks in schizophrenia have been studied by examining intrinsic and extrinsic brain activity under various experimental paradigms. However, the identified patterns of abnormal functional connectivity (FC) vary depending on the adopted paradigms. Thus, it is unclear whether and how these patterns are inter-related. In order to assess relationships between abnormal patterns of FC during intrinsic activity and those during extrinsic activity, we adopted a data-fusion approach and applied partial least square (PLS) analyses to FC datasets from 25 patients with chronic schizophrenia and 25 age- and sex-matched normal controls. For the input to the PLS analyses, we generated a pair of FC maps during the resting state (REST) and the auditory deviance response (ADR) from each participant using the common seed region in the left middle temporal gyrus, which is a focus of activity associated with auditory verbal hallucinations (AVHs). PLS correlation (PLS-C) analysis revealed that patients with schizophrenia have significantly lower loadings of a component containing positive FCs in default-mode network regions during REST and a component containing positive FCs in the auditory and attention-related networks during ADR. Specifically, loadings of the REST component were significantly correlated with the severities of positive symptoms and AVH in patients with schizophrenia. The co-occurrence of such altered FC patterns during REST and ADR was replicated using PLS regression, wherein FC patterns during REST are modeled to predict patterns during ADR. These findings provide an integrative understanding of altered FCs during intrinsic and extrinsic activity underlying core schizophrenia symptoms.

Gap maps and intrinsic diffraction losses in one-dimensional photonic crystal slabs.

PubMed

Gerace, Dario; Andreani, Lucio Claudio

2004-05-01

A theoretical study of photonic bands for one-dimensional (1D) lattices embedded in planar waveguides with strong refractive index contrast is presented. The approach relies on expanding the electromagnetic field on the basis of guided modes of an effective waveguide, and on treating the coupling to radiative modes by perturbation theory. Photonic mode dispersion, gap maps, and intrinsic diffraction losses of quasi guided modes are calculated for the case of self-standing membranes as well as for silicon-on-insulator structures. Photonic band gaps in a waveguide are found to depend strongly on the core thickness and on polarization, so that the gaps for transverse electric and transverse magnetic modes most often do not overlap. Radiative losses of quasiguided modes above the light line depend in a nontrivial way on structure parameters, mode index, and wave vector. The results of this study may be useful for the design of integrated 1D photonic structures with low radiative losses.

Femtosecond buildup of phonon-plasmon coupling in photoexcited InP observed by ultrabroadband THz probing

NASA Astrophysics Data System (ADS)

Huber, Rupert; Kübler, Carl; Tübel, Stefan; Leitenstorfer, Alfred

2006-02-01

We study the ultrafast transition of a pure longitudinal optical phonon resonance to a coupled phonon-plasmon system. Following 10-fs photoexcitation of intrinsic indium phosphide, ultrabroadband THz opto-electronics monitors the buildup of coherent beats of the emerging hybrid modes directly in the time domain with sub-cycle resolution. Mutual repulsion and redistribution of the oscillator strength of the interacting phonons and plasmons are seen to emerge on a delayed femtosecond time scale. Both branches of the mixed modes are monitored for various excitation densities N. We observe a pronounced anticrossing of the coupled resonances as a function of N. The characteristic formation time for phonon-plasmon coupling exhibits density dependence. The time is approximately set by one oscillation cycle of the upper branch of the mixed modes.

Highly efficient optical power transfer to whispering-gallery modes by use of a symmetrical dual-coupling configuration.

PubMed

Cai, M; Vahala, K

2000-02-15

We report that greater than 99.8% optical power transfer to whispering-gallery modes was achieved in fused-silica microspheres by use of a dual-tapered-fiber coupling method. The intrinsic cavity loss and the taper-to-sphere coupling coefficient are inferred from the experimental data. It is shown that the low intrinsic cavity loss and the symmetrical dual-coupling structure are crucial for obtaining the high coupling efficiency.

Adaptive-projection intrinsically transformed multivariate empirical mode decomposition in cooperative brain-computer interface applications.

PubMed

Hemakom, Apit; Goverdovsky, Valentin; Looney, David; Mandic, Danilo P

2016-04-13

An extension to multivariate empirical mode decomposition (MEMD), termed adaptive-projection intrinsically transformed MEMD (APIT-MEMD), is proposed to cater for power imbalances and inter-channel correlations in real-world multichannel data. It is shown that the APIT-MEMD exhibits similar or better performance than MEMD for a large number of projection vectors, whereas it outperforms MEMD for the critical case of a small number of projection vectors within the sifting algorithm. We also employ the noise-assisted APIT-MEMD within our proposed intrinsic multiscale analysis framework and illustrate the advantages of such an approach in notoriously noise-dominated cooperative brain-computer interface (BCI) based on the steady-state visual evoked potentials and the P300 responses. Finally, we show that for a joint cognitive BCI task, the proposed intrinsic multiscale analysis framework improves system performance in terms of the information transfer rate. © 2016 The Author(s).

Default Mode Network Subsystems are Differentially Disrupted in Posttraumatic Stress Disorder

PubMed Central

Miller, Danielle R.; Hayes, Scott M.; Hayes, Jasmeet P.; Spielberg, Jeffrey M.; Lafleche, Ginette; Verfaellie, Mieke

2017-01-01

Background Posttraumatic stress disorder (PTSD) is a psychiatric disorder characterized by debilitating re-experiencing, avoidance, and hyperarousal symptoms following trauma exposure. Recent evidence suggests that individuals with PTSD show disrupted functional connectivity in the default mode network, an intrinsic network that consists of a midline core, a medial temporal lobe (MTL) subsystem, and a dorsomedial prefrontal cortex (dMPFC) subsystem. The present study examined whether functional connectivity in these subsystems is differentially disrupted in PTSD. Methods Sixty-nine returning war Veterans with PTSD and 44 trauma-exposed Veterans without PTSD underwent resting state functional MRI (rs-fMRI). To examine functional connectivity, seeds were placed in the core hubs of the default mode network, namely the posterior cingulate cortex (PCC) and anterior medial PFC (aMPFC), and in each subsystem. Results Compared to controls, individuals with PTSD had reduced functional connectivity between the PCC and the hippocampus, a region of the MTL subsystem. Groups did not differ in connectivity between the PCC and dMPFC subsystem or between the aMPFC and any region within either subsystem. In the PTSD group, connectivity between the PCC and hippocampus was negatively associated with avoidance/numbing symptoms. Examination of the MTL and dMPFC subsystems revealed reduced anticorrelation between the ventromedial PFC (vMPFC) seed of the MTL subsystem and the dorsal anterior cingulate cortex in the PTSD group. Conclusions Our results suggest that selective alterations in functional connectivity in the MTL subsystem of the default mode network in PTSD may be an important factor in PTSD pathology and symptomatology. PMID:28435932

Default Mode Network Subsystems are Differentially Disrupted in Posttraumatic Stress Disorder.

PubMed

Miller, Danielle R; Hayes, Scott M; Hayes, Jasmeet P; Spielberg, Jeffrey M; Lafleche, Ginette; Verfaellie, Mieke

2017-05-01

Posttraumatic stress disorder (PTSD) is a psychiatric disorder characterized by debilitating re-experiencing, avoidance, and hyperarousal symptoms following trauma exposure. Recent evidence suggests that individuals with PTSD show disrupted functional connectivity in the default mode network, an intrinsic network that consists of a midline core, a medial temporal lobe (MTL) subsystem, and a dorsomedial prefrontal cortex (dMPFC) subsystem. The present study examined whether functional connectivity in these subsystems is differentially disrupted in PTSD. Sixty-nine returning war Veterans with PTSD and 44 trauma-exposed Veterans without PTSD underwent resting state functional MRI (rs-fMRI). To examine functional connectivity, seeds were placed in the core hubs of the default mode network, namely the posterior cingulate cortex (PCC) and anterior medial PFC (aMPFC), and in each subsystem. Compared to controls, individuals with PTSD had reduced functional connectivity between the PCC and the hippocampus, a region of the MTL subsystem. Groups did not differ in connectivity between the PCC and dMPFC subsystem or between the aMPFC and any region within either subsystem. In the PTSD group, connectivity between the PCC and hippocampus was negatively associated with avoidance/numbing symptoms. Examination of the MTL and dMPFC subsystems revealed reduced anticorrelation between the ventromedial PFC (vMPFC) seed of the MTL subsystem and the dorsal anterior cingulate cortex in the PTSD group. Our results suggest that selective alterations in functional connectivity in the MTL subsystem of the default mode network in PTSD may be an important factor in PTSD pathology and symptomatology.

Functional connectivity in the developing brain: A longitudinal study from 4 to 9 months of age

PubMed Central

Damaraju, E.; Caprihan, A.; Lowe, J.R.; Allen, E.A.; Calhoun, V.D.; Phillips, J.P.

2013-01-01

We characterize the development of intrinsic connectivity networks (ICNs) from 4 to 9 months of age with resting state magnetic resonance imaging performed on sleeping infants without sedative medication. Data is analyzed with independent component analysis (ICA). Using both low (30 components) and high (100 components) ICA model order decompositions, we find that the functional network connectivity (FNC) map is largely similar at both 4 and 9 months. However at 9 months the connectivity strength decreases within local networks and increases between more distant networks. The connectivity within the default-mode network, which contains both local and more distant nodes, also increases in strength with age. The low frequency power spectrum increases with age only in the posterior cingulate cortex and posterior default mode network. These findings are consistent with a general developmental pattern of increasing longer distance functional connectivity over the first year of life and raise questions regarding the developmental importance of the posterior cingulate at this age. PMID:23994454

Functional connectivity in the developing brain: a longitudinal study from 4 to 9months of age.

PubMed

Damaraju, E; Caprihan, A; Lowe, J R; Allen, E A; Calhoun, V D; Phillips, J P

2014-01-01

We characterize the development of intrinsic connectivity networks (ICNs) from 4 to 9months of age with resting state magnetic resonance imaging performed on sleeping infants without sedative medication. Data is analyzed with independent component analysis (ICA). Using both low (30 components) and high (100 components) ICA model order decompositions, we find that the functional network connectivity (FNC) map is largely similar at both 4 and 9months. However at 9months the connectivity strength decreases within local networks and increases between more distant networks. The connectivity within the default-mode network, which contains both local and more distant nodes, also increases in strength with age. The low frequency power spectrum increases with age only in the posterior cingulate cortex and posterior default mode network. These findings are consistent with a general developmental pattern of increasing longer distance functional connectivity over the first year of life and raise questions regarding the developmental importance of the posterior cingulate at this age. © 2013.

Analyzing intrinsic plasmonic chirality by tracking the interplay of electric and magnetic dipole modes.

PubMed

Hu, Li; Huang, Yingzhou; Pan, Lujun; Fang, Yurui

2017-09-11

Plasmonic chirality represents significant potential for novel nanooptical devices due to its association with strong chiroptical responses. Previous reports on plasmonic chirality mechanism mainly focus on phase retardation and coupling. In this paper, we propose a model similar to the chiral molecules for explaining the intrinsic plasmonic chirality mechanism of varies 3D chiral structures quantitatively based on the interplay and mixing of electric and magnetic dipole modes (directly from electromagnetic field numerical simulations), which forms mixed electric and magnetic polarizability.

Experimental rig to estimate the coefficient of friction between tire and surface in airplane touchdown simulations.

PubMed

Li, Chengwei; Zhan, Liwei

2015-08-01

To estimate the coefficient of friction between tire and runway surface during airplane touchdowns, we designed an experimental rig to simulate such events and to record the impact and friction forces being executed. Because of noise in the measured signals, we developed a filtering method that is based on the ensemble empirical mode decomposition and the bandwidth of probability density function of each intrinsic mode function to extract friction and impact force signals. We can quantify the coefficient of friction by calculating the maximum values of the filtered force signals. Signal measurements are recorded for different drop heights and tire rotational speeds, and the corresponding coefficient of friction is calculated. The result shows that the values of the coefficient of friction change only slightly. The random noise and experimental artifact are the major reason of the change.

Phononic Crystal Tunable via Ferroelectric Phase Transition

NASA Astrophysics Data System (ADS)

Xu, Chaowei; Cai, Feiyan; Xie, Shuhong; Li, Fei; Sun, Rong; Fu, Xianzhu; Xiong, Rengen; Zhang, Yi; Zheng, Hairong; Li, Jiangyu

2015-09-01

Phononic crystals (PCs) consisting of periodic materials with different acoustic properties have potential applications in functional devices. To realize more smart functions, it is desirable to actively control the properties of PCs on demand, ideally within the same fabricated system. Here, we report a tunable PC made of Ba0.7Sr0.3Ti O3 (BST) ceramics, wherein a 20-K temperature change near room temperature results in a 20% frequency shift in the transmission spectra induced by a ferroelectric phase transition. The tunability phenomenon is attributed to the structure-induced resonant excitation of A0 and A1 Lamb modes that exist intrinsically in the uniform BST plate, while these Lamb modes are sensitive to the elastic properties of the plate and can be modulated by temperature in a BST plate around the Curie temperature. The study finds opportunities for creating tunable PCs and enables smart temperature-tuned devices such as the Lamb wave filter or sensor.

A combined cICA-EEMD analysis of EEG recordings from depressed or schizophrenic patients during olfactory stimulation

NASA Astrophysics Data System (ADS)

Götz, Th; Stadler, L.; Fraunhofer, G.; Tomé, A. M.; Hausner, H.; Lang, E. W.

2017-02-01

Objective. We propose a combination of a constrained independent component analysis (cICA) with an ensemble empirical mode decomposition (EEMD) to analyze electroencephalographic recordings from depressed or schizophrenic subjects during olfactory stimulation. Approach. EEMD serves to extract intrinsic modes (IMFs) underlying the recorded EEG time. The latter then serve as reference signals to extract the most similar underlying independent component within a constrained ICA. The extracted modes are further analyzed considering their power spectra. Main results. The analysis of the extracted modes reveals clear differences in the related power spectra between the disease characteristics of depressed and schizophrenic patients. Such differences appear in the high frequency γ-band in the intrinsic modes, but also in much more detail in the low frequency range in the α-, θ- and δ-bands. Significance. The proposed method provides various means to discriminate both disease pictures in a clinical environment.

Fluorescence Intrinsic Characterization of Excitation-Emission Matrix Using Multi-Dimensional Ensemble Empirical Mode Decomposition

PubMed Central

Chang, Chi-Ying; Chang, Chia-Chi; Hsiao, Tzu-Chien

2013-01-01

Excitation-emission matrix (EEM) fluorescence spectroscopy is a noninvasive method for tissue diagnosis and has become important in clinical use. However, the intrinsic characterization of EEM fluorescence remains unclear. Photobleaching and the complexity of the chemical compounds make it difficult to distinguish individual compounds due to overlapping features. Conventional studies use principal component analysis (PCA) for EEM fluorescence analysis, and the relationship between the EEM features extracted by PCA and diseases has been examined. The spectral features of different tissue constituents are not fully separable or clearly defined. Recently, a non-stationary method called multi-dimensional ensemble empirical mode decomposition (MEEMD) was introduced; this method can extract the intrinsic oscillations on multiple spatial scales without loss of information. The aim of this study was to propose a fluorescence spectroscopy system for EEM measurements and to describe a method for extracting the intrinsic characteristics of EEM by MEEMD. The results indicate that, although PCA provides the principal factor for the spectral features associated with chemical compounds, MEEMD can provide additional intrinsic features with more reliable mapping of the chemical compounds. MEEMD has the potential to extract intrinsic fluorescence features and improve the detection of biochemical changes. PMID:24240806

The interplay of intrinsic and extrinsic bounded noises in biomolecular networks.

PubMed

Caravagna, Giulio; Mauri, Giancarlo; d'Onofrio, Alberto

2013-01-01

After being considered as a nuisance to be filtered out, it became recently clear that biochemical noise plays a complex role, often fully functional, for a biomolecular network. The influence of intrinsic and extrinsic noises on biomolecular networks has intensively been investigated in last ten years, though contributions on the co-presence of both are sparse. Extrinsic noise is usually modeled as an unbounded white or colored gaussian stochastic process, even though realistic stochastic perturbations are clearly bounded. In this paper we consider Gillespie-like stochastic models of nonlinear networks, i.e. the intrinsic noise, where the model jump rates are affected by colored bounded extrinsic noises synthesized by a suitable biochemical state-dependent Langevin system. These systems are described by a master equation, and a simulation algorithm to analyze them is derived. This new modeling paradigm should enlarge the class of systems amenable at modeling. We investigated the influence of both amplitude and autocorrelation time of a extrinsic Sine-Wiener noise on: (i) the Michaelis-Menten approximation of noisy enzymatic reactions, which we show to be applicable also in co-presence of both intrinsic and extrinsic noise, (ii) a model of enzymatic futile cycle and (iii) a genetic toggle switch. In (ii) and (iii) we show that the presence of a bounded extrinsic noise induces qualitative modifications in the probability densities of the involved chemicals, where new modes emerge, thus suggesting the possible functional role of bounded noises.

Disrupted Intrinsic Networks Link Amyloid-β Pathology and Impaired Cognition in Prodromal Alzheimer's Disease.

PubMed

Koch, Kathrin; Myers, Nicholas E; Göttler, Jens; Pasquini, Lorenzo; Grimmer, Timo; Förster, Stefan; Manoliu, Andrei; Neitzel, Julia; Kurz, Alexander; Förstl, Hans; Riedl, Valentin; Wohlschläger, Afra M; Drzezga, Alexander; Sorg, Christian

2015-12-01

Amyloid-β pathology (Aβ) and impaired cognition characterize Alzheimer's disease (AD); however, neural mechanisms that link Aβ-pathology with impaired cognition are incompletely understood. Large-scale intrinsic connectivity networks (ICNs) are potential candidates for this link: Aβ-pathology affects specific networks in early AD, these networks show disrupted connectivity, and they process specific cognitive functions impaired in AD, like memory or attention. We hypothesized that, in AD, regional changes of ICNs, which persist across rest- and cognitive task-states, might link Aβ-pathology with impaired cognition via impaired intrinsic connectivity. Pittsburgh compound B (PiB)-positron emission tomography reflecting in vivo Aβ-pathology, resting-state fMRI, task-fMRI, and cognitive testing were used in patients with prodromal AD and healthy controls. In patients, default mode network's (DMN) functional connectivity (FC) was reduced in the medial parietal cortex during rest relative to healthy controls, relatively increased in the same region during an attention-demanding task, and associated with patients' cognitive impairment. Local PiB-uptake correlated negatively with DMN connectivity. Importantly, corresponding results were found for the right lateral parietal region of an attentional network. Finally, structural equation modeling confirmed a direct influence of DMN resting-state FC on the association between Aβ-pathology and cognitive impairment. Data provide evidence that disrupted intrinsic network connectivity links Aβ-pathology with cognitive impairment in early AD. © The Author 2014. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

Where is the breathing mode? High voltage Hall effect thruster studies with EMD method

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

Kurzyna, J.; Makowski, K.; Mazouffre, S.

2008-03-19

Discharge current and local plasma oscillations are studied in a high voltage Hall effect thruster PPS registered -X000. Characteristic time scales that appear in different operating conditions are resolved with the use of Hilbert-Huang spectra (HHS) which display time dependenc of instantaneous frequency and power. Sets of intrinsic mode functions (imfs) that are used for HHS calculation result due to application of empirical mode decomposition method (EMD) to nonstationary multicomponent signals. In the experiment the signals are captured in the electric circuit of the thruster as well locally, in the vicinity of the thruster exhaust region. Classical electric probes spacedmore » along the azimuth and/or thruster axis let us study correlations of signals which were captured in different locations. In this way azimuthal and axial propagation of disturbances is inspected. The discharge voltage is varied in the range of 200 divide 900 V while xenon mas flow rate of 5 divide 9 mg/s. LF, MF, and HF characteristic bands that are known from previous studies of PPS registered -100 thruster have been also detected here. However, expanding discharge current onto a set of intrinsic modes we can resolve MF mode more reliably than before. Moreover, for higher discharge voltages, this irregular mode turns into more regular waveform and tends to dominate in the discharge current masking almost completely the breathing mode (LF oscillations of the discharge current). In such a case triggering of HF oscillations is correlated with the phase of MF mode while in the case of PPS registered -100 thruster it was correlated with the appropriate phase of the breathing mode (LF band). Regular HF emission that can be unambiguously interpreted as azimuthal electrostatic wave now is observed only in the specific operating conditions of the thruster. However, even if irregular HF emission is observed the time delay of cross-correlated signals which are captured in different azimuthal locations corresponds to the velocity of azimuthal electron drift in the field of magnetic barrier.« less

A statistical study of atypical wave modes in the Earth's foreshock region

NASA Astrophysics Data System (ADS)

Hsieh, W.; Shue, J.; Lee, B.

2010-12-01

The Earth's foreshock, the region upstream the Earth’s bow shock, is filled with back-streaming particles and ultra-low frequency waves. Three different wave modes have been identified in the region, including 30-sec waves, 3-sec waves, and shocklets. Time History of Events and Macroscale Interactions during Substorms (THEMIS), a satellite mission that consists of five probes, provides multiple measuements of the Earth’s foreshock region. The method of Hilbert-Huang transform (HHT) includes the procedures of empirical mode decomposition and instantaneous frequency calculation. In this study, we use HHT to decompose intrinsic wave modes and perform a wave analysis of chaotic magnetic fields in the Earth's foreshock region. We find that some individual atypical wave modes other than 30-sec and 3-sec appear in the region. In this presentation, we will show the statistical characteristics, such as wave frequency, wave amplitude, and wave polarization of the atypical intrinsic wave modes, with respect to different locations in the foreshock region and to different solar wind conditions.

Palm vein recognition based on directional empirical mode decomposition

NASA Astrophysics Data System (ADS)

Lee, Jen-Chun; Chang, Chien-Ping; Chen, Wei-Kuei

2014-04-01

Directional empirical mode decomposition (DEMD) has recently been proposed to make empirical mode decomposition suitable for the processing of texture analysis. Using DEMD, samples are decomposed into a series of images, referred to as two-dimensional intrinsic mode functions (2-D IMFs), from finer to large scale. A DEMD-based 2 linear discriminant analysis (LDA) for palm vein recognition is proposed. The proposed method progresses through three steps: (i) a set of 2-D IMF features of various scale and orientation are extracted using DEMD, (ii) the 2LDA method is then applied to reduce the dimensionality of the feature space in both the row and column directions, and (iii) the nearest neighbor classifier is used for classification. We also propose two strategies for using the set of 2-D IMF features: ensemble DEMD vein representation (EDVR) and multichannel DEMD vein representation (MDVR). In experiments using palm vein databases, the proposed MDVR-based 2LDA method achieved recognition accuracy of 99.73%, thereby demonstrating its feasibility for palm vein recognition.

Multi-focus image fusion based on window empirical mode decomposition

NASA Astrophysics Data System (ADS)

Qin, Xinqiang; Zheng, Jiaoyue; Hu, Gang; Wang, Jiao

2017-09-01

In order to improve multi-focus image fusion quality, a novel fusion algorithm based on window empirical mode decomposition (WEMD) is proposed. This WEMD is an improved form of bidimensional empirical mode decomposition (BEMD), due to its decomposition process using the adding window principle, effectively resolving the signal concealment problem. We used WEMD for multi-focus image fusion, and formulated different fusion rules for bidimensional intrinsic mode function (BIMF) components and the residue component. For fusion of the BIMF components, the concept of the Sum-modified-Laplacian was used and a scheme based on the visual feature contrast adopted; when choosing the residue coefficients, a pixel value based on the local visibility was selected. We carried out four groups of multi-focus image fusion experiments and compared objective evaluation criteria with other three fusion methods. The experimental results show that the proposed fusion approach is effective and performs better at fusing multi-focus images than some traditional methods.

Photoelectrochemical information storage using an azobenzene derivative

NASA Astrophysics Data System (ADS)

Liu, Z. F.; Hashimoto, K.; Fujishima, A.

1990-10-01

HIGH-DENSITY information storage is becoming an increasingly important technological objective. The 'heat-mode' storage techniques (in which only the thermal energy of laser light is used in the recording process and hence information usually stored as a physical change of the storage media) that are used in current optical memories are limited by the diffraction properties of light1, and the alternative 'photon-mode' (in which information is stored as a photon-induced chemical change of the storage media) has attracted attention recently for high-density storage. The most promising candidates for realizing this mode seem to be photochro-ism and photochemical hole burning; but these have some intrinsic drawbacks1,2. Here we present a novel 'photon-mode' technique that uses the photoelectrochemical properties of a Langmuir-Blodgett film of an azobenzene derivative. The system can be interconverted photochemically or electrochemically between three chemical states, and this three-state system is shown to provide a potential storage process that allows for ultra-high storage density, multi-function memory and non-destructive information readout.

Failure strength of the bovine caudal disc under internal hydrostatic pressure.

PubMed

Schechtman, Helio; Robertson, Peter A; Broom, Neil D

2006-01-01

The structure of the disc is both complex and inhomogeneous, and it functions as a successful load-bearing organ by virtue of the integration of its various structural regions. These same features also render it impossible to assess the failure strength of the disc from isolated tissue samples, which at best can only yield material properties. This study investigated the intrinsic failure strength of the intact bovine caudal disc under a simple mode of internal hydrostatic pressure. Using a hydraulic actuator, coloured hydrogel was injected under monitored pressure into the nucleus through a hollow screw insert which passed longitudinally through one of the attached vertebrae. Failure did not involve vertebra/endplate structures. Rather, failure of the disc annulus was indicated by the simultaneous manifestation of a sudden loss of gel pressure, a flood of gel colouration appearing in the outer annulus and audible fibrous tearing. A mean hydrostatic failure pressure of 18+/-3 MPa was observed which was approximated as a thick-wall hoop stress of 45+/-7 MPa. The experiment provides a measurement of the intrinsic strength of the disc using a method of internal hydrostatic loading which avoids any disruption of the complex architecture of the annular wall. Although the disc in vivo is subjected to a much more complex pattern of loading than is achieved using simple hydrostatic pressurization, this latter mode provides a useful tool for investigating alterations in intrinsic disc strength associated with prior loading history or degeneration.

First-principles studies on infrared properties of semiconducting graphene monoxide

NASA Astrophysics Data System (ADS)

Pu, H. H.; Mattson, E. C.; Rhim, S. H.; Gajdardziksa-Josifovska, M.; Hirschmugl, C. J.; Weinert, M.; Chen, J. H.

2013-10-01

Graphene monoxide (GMO), a recently proposed 2D crystalline material in the graphene family, is attractive for next-generation nanoelectronics because of its predicted tunable band gap. As a guide to GMO experimental characterization, we calculate the vibrational properties and obtain three infrared active vibration modes (B1u, B2u, and B3u) and six Raman active modes (B1g, B2g, 2B3g, and 2Ag) for intrinsic GMO. The frequencies of the infrared active modes depend on both local structural deformations and interactions between adjacent GMO layers. These results are consistent with experimental observations and provide a means of estimating the number of layers in intrinsic GMO.

Sex and disease-related alterations of anterior insula functional connectivity in chronic abdominal pain.

PubMed

Hong, Jui-Yang; Kilpatrick, Lisa A; Labus, Jennifer S; Gupta, Arpana; Katibian, David; Ashe-McNalley, Cody; Stains, Jean; Heendeniya, Nuwanthi; Smith, Suzanne R; Tillisch, Kirsten; Naliboff, Bruce; Mayer, Emeran A

2014-10-22

Resting-state functional magnetic resonance imaging has been used to investigate intrinsic brain connectivity in healthy subjects and patients with chronic pain. Sex-related differences in the frequency power distribution within the human insula (INS), a brain region involved in the integration of interoceptive, affective, and cognitive influences, have been reported. Here we aimed to test sex and disease-related alterations in the intrinsic functional connectivity of the dorsal anterior INS. The anterior INS is engaged during goal-directed tasks and modulates the default mode and executive control networks. By comparing functional connectivity of the dorsal anterior INS in age-matched female and male healthy subjects and patients with irritable bowel syndrome (IBS), a common chronic abdominal pain condition, we show evidence for sex and disease-related alterations in the functional connectivity of this region: (1) male patients compared with female patients had increased positive connectivity of the dorsal anterior INS bilaterally with the medial prefrontal cortex (PFC) and dorsal posterior INS; (2) female patients compared with male patients had greater negative connectivity of the left dorsal anterior INS with the left precuneus; (3) disease-related differences in the connectivity between the bilateral dorsal anterior INS and the dorsal medial PFC were observed in female subjects; and (4) clinical characteristics were significantly correlated to the insular connectivity with the dorsal medial PFC in male IBS subjects and with the precuneus in female IBS subjects. These findings are consistent with the INS playing an important role in modulating the intrinsic functional connectivity of major networks in the resting brain and show that this role is influenced by sex and diagnosis. Copyright © 2014 the authors 0270-6474/14/3414252-08$15.00/0.

Markedly Divergent Tree Assemblage Responses to Tropical Forest Loss and Fragmentation across a Strong Seasonality Gradient.

PubMed

Orihuela, Rodrigo L L; Peres, Carlos A; Mendes, Gabriel; Jarenkow, João A; Tabarelli, Marcelo

2015-01-01

We examine the effects of forest fragmentation on the structure and composition of tree assemblages within three seasonal and aseasonal forest types of southern Brazil, including evergreen, Araucaria, and deciduous forests. We sampled three southernmost Atlantic Forest landscapes, including the largest continuous forest protected areas within each forest type. Tree assemblages in each forest type were sampled within 10 plots of 0.1 ha in both continuous forests and 10 adjacent forest fragments. All trees within each plot were assigned to trait categories describing their regeneration strategy, vertical stratification, seed-dispersal mode, seed size, and wood density. We detected differences among both forest types and landscape contexts in terms of overall tree species richness, and the density and species richness of different functional groups in terms of regeneration strategy, seed dispersal mode and woody density. Overall, evergreen forest fragments exhibited the largest deviations from continuous forest plots in assemblage structure. Evergreen, Araucaria and deciduous forests diverge in the functional composition of tree floras, particularly in relation to regeneration strategy and stress tolerance. By supporting a more diversified light-demanding and stress-tolerant flora with reduced richness and abundance of shade-tolerant, old-growth species, both deciduous and Araucaria forest tree assemblages are more intrinsically resilient to contemporary human-disturbances, including fragmentation-induced edge effects, in terms of species erosion and functional shifts. We suggest that these intrinsic differences in the direction and magnitude of responses to changes in landscape structure between forest types should guide a wide range of conservation strategies in restoring fragmented tropical forest landscapes worldwide.

Markedly Divergent Tree Assemblage Responses to Tropical Forest Loss and Fragmentation across a Strong Seasonality Gradient

PubMed Central

Orihuela, Rodrigo L. L.; Peres, Carlos A.; Mendes, Gabriel; Jarenkow, João A.; Tabarelli, Marcelo

2015-01-01

We examine the effects of forest fragmentation on the structure and composition of tree assemblages within three seasonal and aseasonal forest types of southern Brazil, including evergreen, Araucaria, and deciduous forests. We sampled three southernmost Atlantic Forest landscapes, including the largest continuous forest protected areas within each forest type. Tree assemblages in each forest type were sampled within 10 plots of 0.1 ha in both continuous forests and 10 adjacent forest fragments. All trees within each plot were assigned to trait categories describing their regeneration strategy, vertical stratification, seed-dispersal mode, seed size, and wood density. We detected differences among both forest types and landscape contexts in terms of overall tree species richness, and the density and species richness of different functional groups in terms of regeneration strategy, seed dispersal mode and woody density. Overall, evergreen forest fragments exhibited the largest deviations from continuous forest plots in assemblage structure. Evergreen, Araucaria and deciduous forests diverge in the functional composition of tree floras, particularly in relation to regeneration strategy and stress tolerance. By supporting a more diversified light-demanding and stress-tolerant flora with reduced richness and abundance of shade-tolerant, old-growth species, both deciduous and Araucaria forest tree assemblages are more intrinsically resilient to contemporary human-disturbances, including fragmentation-induced edge effects, in terms of species erosion and functional shifts. We suggest that these intrinsic differences in the direction and magnitude of responses to changes in landscape structure between forest types should guide a wide range of conservation strategies in restoring fragmented tropical forest landscapes worldwide. PMID:26309252

The development of the intrinsic functional connectivity of default network subsystems from age 3 to 5.

PubMed

Xiao, Yaqiong; Zhai, Hongchang; Friederici, Angela D; Jia, Fucang

2016-03-01

In recent years, research on human functional brain imaging using resting-state fMRI techniques has been increasingly prevalent. The term "default mode" was proposed to describe a baseline or default state of the brain during rest. Recent studies suggested that the default mode network (DMN) is comprised of two functionally distinct subsystems: a dorsal-medial prefrontal cortex (DMPFC) subsystem involved in self-oriented cognition (i.e., theory of mind) and a medial temporal lobe (MTL) subsystem engaged in memory and scene construction; both subsystems interact with the anterior medial prefrontal cortex (aMPFC) and posterior cingulate (PCC) as the core regions of DMN. The present study explored the development of DMN core regions and these two subsystems in both hemispheres from 3- to 5-year-old children. The analysis of the intrinsic activity showed strong developmental changes in both subsystems, and significant changes were specifically found in MTL subsystem, but not in DMPFC subsystem, implying distinct developmental trajectories for DMN subsystems. We found stronger interactions between the DMPFC and MTL subsystems in 5-year-olds, particularly in the left subsystems that support the development of environmental adaptation and relatively complex mental activities. These results also indicate that there is stronger right hemispheric lateralization at age 3, which then changes as bilateral development gradually increases through to age 5, suggesting in turn the hemispheric dominance in DMN subsystems changing with age. The present results provide primary evidence for the development of DMN subsystems in early life, which might be closely related to the development of social cognition in childhood.

Identifying the Role of Terahertz Vibrations in Metal-Organic Frameworks: From Gate-Opening Phenomenon to Shear-Driven Structural Destabilization

NASA Astrophysics Data System (ADS)

Ryder, Matthew R.; Civalleri, Bartolomeo; Bennett, Thomas D.; Henke, Sebastian; Rudić, Svemir; Cinque, Gianfelice; Fernandez-Alonso, Felix; Tan, Jin-Chong

2014-11-01

We present an unambiguous identification of low-frequency terahertz vibrations in the archetypal imidazole-based metal-organic framework (MOF) materials: ZIF-4, ZIF-7, and ZIF-8, all of which adopt a zeolite-like nanoporous structure. Using inelastic neutron scattering and synchrotron radiation far-infrared absorption spectroscopy, in conjunction with density functional theory (DFT), we have pinpointed all major sources of vibrational modes. Ab initio DFT calculations revealed the complex nature of the collective THz modes, which enable us to establish detailed correlations with experiments. We discover that low-energy conformational dynamics offers multiple pathways to elucidate novel physical phenomena observed in MOFs. New evidence demonstrates that THz modes are intrinsically linked, not only to anomalous elasticity underpinning gate-opening and pore-breathing mechanisms, but also to shear-induced phase transitions and the onset of structural instability.

Tourism forecasting using modified empirical mode decomposition and group method of data handling

NASA Astrophysics Data System (ADS)

Yahya, N. A.; Samsudin, R.; Shabri, A.

2017-09-01

In this study, a hybrid model using modified Empirical Mode Decomposition (EMD) and Group Method of Data Handling (GMDH) model is proposed for tourism forecasting. This approach reconstructs intrinsic mode functions (IMFs) produced by EMD using trial and error method. The new component and the remaining IMFs is then predicted respectively using GMDH model. Finally, the forecasted results for each component are aggregated to construct an ensemble forecast. The data used in this experiment are monthly time series data of tourist arrivals from China, Thailand and India to Malaysia from year 2000 to 2016. The performance of the model is evaluated using Root Mean Square Error (RMSE) and Mean Absolute Percentage Error (MAPE) where conventional GMDH model and EMD-GMDH model are used as benchmark models. Empirical results proved that the proposed model performed better forecasts than the benchmarked models.

An epileptic seizures detection algorithm based on the empirical mode decomposition of EEG.

PubMed

Orosco, Lorena; Laciar, Eric; Correa, Agustina Garces; Torres, Abel; Graffigna, Juan P

2009-01-01

Epilepsy is a neurological disorder that affects around 50 million people worldwide. The seizure detection is an important component in the diagnosis of epilepsy. In this study, the Empirical Mode Decomposition (EMD) method was proposed on the development of an automatic epileptic seizure detection algorithm. The algorithm first computes the Intrinsic Mode Functions (IMFs) of EEG records, then calculates the energy of each IMF and performs the detection based on an energy threshold and a minimum duration decision. The algorithm was tested in 9 invasive EEG records provided and validated by the Epilepsy Center of the University Hospital of Freiburg. In 90 segments analyzed (39 with epileptic seizures) the sensitivity and specificity obtained with the method were of 56.41% and 75.86% respectively. It could be concluded that EMD is a promissory method for epileptic seizure detection in EEG records.

Fringe-projection profilometry based on two-dimensional empirical mode decomposition.

PubMed

Zheng, Suzhen; Cao, Yiping

2013-11-01

In 3D shape measurement, because deformed fringes often contain low-frequency information degraded with random noise and background intensity information, a new fringe-projection profilometry is proposed based on 2D empirical mode decomposition (2D-EMD). The fringe pattern is first decomposed into numbers of intrinsic mode functions by 2D-EMD. Because the method has partial noise reduction, the background components can be removed to obtain the fundamental components needed to perform Hilbert transformation to retrieve the phase information. The 2D-EMD can effectively extract the modulation phase of a single direction fringe and an inclined fringe pattern because it is a full 2D analysis method and considers the relationship between adjacent lines of a fringe patterns. In addition, as the method does not add noise repeatedly, as does ensemble EMD, the data processing time is shortened. Computer simulations and experiments prove the feasibility of this method.

Tissue artifact removal from respiratory signals based on empirical mode decomposition.

PubMed

Liu, Shaopeng; Gao, Robert X; John, Dinesh; Staudenmayer, John; Freedson, Patty

2013-05-01

On-line measurement of respiration plays an important role in monitoring human physical activities. Such measurement commonly employs sensing belts secured around the rib cage and abdomen of the test object. Affected by the movement of body tissues, respiratory signals typically have a low signal-to-noise ratio. Removing tissue artifacts therefore is critical to ensuring effective respiration analysis. This paper presents a signal decomposition technique for tissue artifact removal from respiratory signals, based on the empirical mode decomposition (EMD). An algorithm based on the mutual information and power criteria was devised to automatically select appropriate intrinsic mode functions for tissue artifact removal and respiratory signal reconstruction. Performance of the EMD-algorithm was evaluated through simulations and real-life experiments (N = 105). Comparison with low-pass filtering that has been conventionally applied confirmed the effectiveness of the technique in tissue artifacts removal.

Analysis of Vibration and Noise of Construction Machinery Based on Ensemble Empirical Mode Decomposition and Spectral Correlation Analysis Method

NASA Astrophysics Data System (ADS)

Chen, Yuebiao; Zhou, Yiqi; Yu, Gang; Lu, Dan

In order to analyze the effect of engine vibration on cab noise of construction machinery in multi-frequency bands, a new method based on ensemble empirical mode decomposition (EEMD) and spectral correlation analysis is proposed. Firstly, the intrinsic mode functions (IMFs) of vibration and noise signals were obtained by EEMD method, and then the IMFs which have the same frequency bands were selected. Secondly, we calculated the spectral correlation coefficients between the selected IMFs, getting the main frequency bands in which engine vibration has significant impact on cab noise. Thirdly, the dominated frequencies were picked out and analyzed by spectral analysis method. The study result shows that the main frequency bands and dominated frequencies in which engine vibration have serious impact on cab noise can be identified effectively by the proposed method, which provides effective guidance to noise reduction of construction machinery.

Telephone-quality pathological speech classification using empirical mode decomposition.

PubMed

Kaleem, M F; Ghoraani, B; Guergachi, A; Krishnan, S

2011-01-01

This paper presents a computationally simple and effective methodology based on empirical mode decomposition (EMD) for classification of telephone quality normal and pathological speech signals. EMD is used to decompose continuous normal and pathological speech signals into intrinsic mode functions, which are analyzed to extract physically meaningful and unique temporal and spectral features. Using continuous speech samples from a database of 51 normal and 161 pathological speakers, which has been modified to simulate telephone quality speech under different levels of noise, a linear classifier is used with the feature vector thus obtained to obtain a high classification accuracy, thereby demonstrating the effectiveness of the methodology. The classification accuracy reported in this paper (89.7% for signal-to-noise ratio 30 dB) is a significant improvement over previously reported results for the same task, and demonstrates the utility of our methodology for cost-effective remote voice pathology assessment over telephone channels.

Three dimensional empirical mode decomposition analysis apparatus, method and article manufacture

NASA Technical Reports Server (NTRS)

Gloersen, Per (Inventor)

2004-01-01

An apparatus and method of analysis for three-dimensional (3D) physical phenomena. The physical phenomena may include any varying 3D phenomena such as time varying polar ice flows. A repesentation of the 3D phenomena is passed through a Hilbert transform to convert the data into complex form. A spatial variable is separated from the complex representation by producing a time based covariance matrix. The temporal parts of the principal components are produced by applying Singular Value Decomposition (SVD). Based on the rapidity with which the eigenvalues decay, the first 3-10 complex principal components (CPC) are selected for Empirical Mode Decomposition into intrinsic modes. The intrinsic modes produced are filtered in order to reconstruct the spatial part of the CPC. Finally, a filtered time series may be reconstructed from the first 3-10 filtered complex principal components.

Magnetic Fluctuation-Driven Intrinsic Flow in a Toroidal Plasma

NASA Astrophysics Data System (ADS)

Brower, D. L.; Ding, W. X.; Lin, L.; Almagri, A. F.; den Hartog, D. J.; Sarff, J. S.

2012-10-01

Magnetic fluctuations have been long observed in various magnetic confinement configurations. These perturbations may arise naturally from plasma instabilities such as tearing modes and energetic particle driven modes, but they can also be externally imposed by error fields or external magnetic coils. It is commonly observed that large MHD modes lead to plasma locking (no rotation) due to torque produced by eddy currents on the wall, and it is predicted that stochastic field induces flow damping where the radial electric field is reduced. Flow generation is of great importance to fusion plasma research, especially low-torque devices like ITER, as it can act to improve performance. Here we describe new measurements in the MST reversed field pinch (RFP) showing that the coherent interaction of magnetic and particle density fluctuations can produce a turbulent fluctuation-induced kinetic force, which acts to drive intrinsic plasma rotation. Key observations include; (1) the average kinetic force resulting from density fluctuations, ˜ 0.5 N/m^3, is comparable to the intrinsic flow acceleration, and (2) between sawtooth crashes, the spatial distribution of the kinetic force is directed to create a sheared parallel flow profile that is consistent with the measured flow profile in direction and amplitude, suggesting the kinetic force is responsible for intrinsic plasma rotation.

Does Aerobic Exercise Influence Intrinsic Brain Activity? An Aerobic Exercise Intervention among Healthy Old Adults

PubMed Central

Flodin, Pär; Jonasson, Lars S.; Riklund, Katrin; Nyberg, Lars; Boraxbekk, C. J.

2017-01-01

Previous studies have indicated that aerobic exercise could reduce age related decline in cognition and brain functioning. Here we investigated the effects of aerobic exercise on intrinsic brain activity. Sixty sedentary healthy males and females (64–78 years) were randomized into either an aerobic exercise group or an active control group. Both groups recieved supervised training, 3 days a week for 6 months. Multimodal brain imaging data was acquired before and after the intervention, including 10 min of resting state brain functional magnetic resonance imaging (rs-fMRI) and arterial spin labeling (ASL). Additionally, a comprehensive battery of cognitive tasks assessing, e.g., executive function and episodic memory was administered. Both the aerobic and the control group improved in aerobic capacity (VO2-peak) over 6 months, but a significant group by time interaction confirmed that the aerobic group improved more. Contrary to our hypothesis, we did not observe any significant group by time interactions with regard to any measure of intrinsic activity. To further probe putative relationships between fitness and brain activity, we performed post hoc analyses disregarding group belongings. At baseline, VO2-peak was negativly related to BOLD-signal fluctuations (BOLDSTD) in mid temporal areas. Over 6 months, improvements in aerobic capacity were associated with decreased connectivity between left hippocampus and contralateral precentral gyrus, and positively to connectivity between right mid-temporal areas and frontal and parietal regions. Independent component analysis identified a VO2-related increase in coupling between the default mode network and left orbitofrontal cortex, as well as a decreased connectivity between the sensorimotor network and thalamus. Extensive exploratory data analyses of global efficiency, connectome wide multivariate pattern analysis (connectome-MVPA), as well as ASL, did not reveal any relationships between aerobic fitness and intrinsic brain activity. Moreover, fitness-predicted changes in functional connectivity did not relate to changes in cognition, which is likely due to absent cross-sectional or longitudinal relationships between VO2-peak and cognition. We conclude that the aerobic exercise intervention had limited influence on patterns of intrinsic brain activity, although post hoc analyses indicated that individual changes in aerobic capacity preferentially influenced mid-temporal brain areas. PMID:28848424

Does Aerobic Exercise Influence Intrinsic Brain Activity? An Aerobic Exercise Intervention among Healthy Old Adults.

PubMed

Flodin, Pär; Jonasson, Lars S; Riklund, Katrin; Nyberg, Lars; Boraxbekk, C J

2017-01-01

Previous studies have indicated that aerobic exercise could reduce age related decline in cognition and brain functioning. Here we investigated the effects of aerobic exercise on intrinsic brain activity. Sixty sedentary healthy males and females (64-78 years) were randomized into either an aerobic exercise group or an active control group. Both groups recieved supervised training, 3 days a week for 6 months. Multimodal brain imaging data was acquired before and after the intervention, including 10 min of resting state brain functional magnetic resonance imaging (rs-fMRI) and arterial spin labeling (ASL). Additionally, a comprehensive battery of cognitive tasks assessing, e.g., executive function and episodic memory was administered. Both the aerobic and the control group improved in aerobic capacity (VO 2 -peak) over 6 months, but a significant group by time interaction confirmed that the aerobic group improved more. Contrary to our hypothesis, we did not observe any significant group by time interactions with regard to any measure of intrinsic activity. To further probe putative relationships between fitness and brain activity, we performed post hoc analyses disregarding group belongings. At baseline, VO 2 -peak was negativly related to BOLD-signal fluctuations (BOLD STD ) in mid temporal areas. Over 6 months, improvements in aerobic capacity were associated with decreased connectivity between left hippocampus and contralateral precentral gyrus, and positively to connectivity between right mid-temporal areas and frontal and parietal regions. Independent component analysis identified a VO 2 -related increase in coupling between the default mode network and left orbitofrontal cortex, as well as a decreased connectivity between the sensorimotor network and thalamus. Extensive exploratory data analyses of global efficiency, connectome wide multivariate pattern analysis (connectome-MVPA), as well as ASL, did not reveal any relationships between aerobic fitness and intrinsic brain activity. Moreover, fitness-predicted changes in functional connectivity did not relate to changes in cognition, which is likely due to absent cross-sectional or longitudinal relationships between VO 2 -peak and cognition. We conclude that the aerobic exercise intervention had limited influence on patterns of intrinsic brain activity, although post hoc analyses indicated that individual changes in aerobic capacity preferentially influenced mid-temporal brain areas.

Multimode excitation-induced phase shifts in intrinsic Fabry-Perot interferometric fiber sensor spectra.

PubMed

Ma, Cheng; Wang, Anbo

2010-09-01

We report the modal analysis of optical fiber single-mode-multimode-single-mode intrinsic Fabry-Perot interferometer sensors. The multimode nature of the Fabry-Perot cavity gives rise to an additional phase term in the spectrogram due to intermodal dispersion-induced wavefront distortion, which could significantly affect the cavity length demodulation accuracy. By using an exact model to analyze the modal behavior, this phase term is explained by employing a rotating vector approach. Comparison of the theoretical analysis with experimental results is presented.

Intrinsic Flow and Momentum Transport during Improved Confinement in MST

NASA Astrophysics Data System (ADS)

Craig, D.; Tan, E.; Schott, B.; Anderson, J. K.; Boguski, J.; Nornberg, M. D.; Xing, Z. A.

2017-10-01

Progress in absolute wavelength calibration of the Charge Exchange Recombination Spectroscopy (CHERS) system on MST has enabled new observations and analysis of intrinsic flow and momentum transport. Localized toroidal and poloidal flow measurements with systematic accuracy of +/- 3 km/s have been obtained during improved confinement Pulsed Parallel Current Drive (PPCD) plasmas at high plasma current (400-500 kA). The magnetic activity prior to and during the transition to improved confinement tends to increase the flow and sets the initial condition for the momentum profile evolution during improved confinement where intrinsic flow drive appears to weaken. Inboard flows change in time during PPCD, consistent with changes in the core-resonant m =1, n =6 tearing mode phase velocity. Outboard flows near the magnetic axis are time-independent, resulting in the development of a strongly sheared toroidal flow in the core and asymmetry in the poloidal flow profile. The deceleration of the n =6 mode during the period of improved confinement correlates well with the n =6 mode amplitude and is roughly consistent with the expected torque from eddy currents in the conducting shell. The level of Dα emission and secondary mode amplitudes (n =7-10) do not correlate with the mode deceleration suggesting that the momentum loss from charge exchange with neutrals and diffusion due to residual magnetic stochasticity are not significant in PPCD. This work has been supported by the U.S.D.O.E.

Electrophysiological signatures of atypical intrinsic brain connectivity networks in autism

NASA Astrophysics Data System (ADS)

Shou, Guofa; Mosconi, Matthew W.; Wang, Jun; Ethridge, Lauren E.; Sweeney, John A.; Ding, Lei

2017-08-01

Objective. Abnormal local and long-range brain connectivity have been widely reported in autism spectrum disorder (ASD), yet the nature of these abnormalities and their functional relevance at distinct cortical rhythms remains unknown. Investigations of intrinsic connectivity networks (ICNs) and their coherence across whole brain networks hold promise for determining whether patterns of functional connectivity abnormalities vary across frequencies and networks in ASD. In the present study, we aimed to probe atypical intrinsic brain connectivity networks in ASD from resting-state electroencephalography (EEG) data via characterizing the whole brain network. Approach. Connectivity within individual ICNs (measured by spectral power) and between ICNs (measured by coherence) were examined at four canonical frequency bands via a time-frequency independent component analysis on high-density EEG, which were recorded from 20 ASD and 20 typical developing (TD) subjects during an eyes-closed resting state. Main results. Among twelve identified electrophysiological ICNs, individuals with ASD showed hyper-connectivity in individual ICNs and hypo-connectivity between ICNs. Functional connectivity alterations in ASD were more severe in the frontal lobe and the default mode network (DMN) and at low frequency bands. These functional connectivity measures also showed abnormal age-related associations in ICNs related to frontal, temporal and motor regions in ASD. Significance. Our findings suggest that ASD is characterized by the opposite directions of abnormalities (i.e. hypo- and hyper-connectivity) in the hierarchical structure of the whole brain network, with more impairments in the frontal lobe and the DMN at low frequency bands, which are critical for top-down control of sensory systems, as well as for both cognition and social skills.

Origin of the monolayer Raman signature in hexagonal boron nitride: a first-principles analysis.

PubMed

Ontaneda, Jorge; Singh, Anjali; Waghmare, Umesh V; Grau-Crespo, Ricardo

2018-05-10

Monolayers of hexagonal boron nitride (h-BN) can in principle be identified by a Raman signature, consisting of an upshift in the frequency of the E 2g vibrational mode with respect to the bulk value, but the origin of this shift (intrinsic or support-induced) is still debated. Herein we use density functional theory calculations to investigate whether there is an intrinsic Raman shift in the h-BN monolayer in comparison with the bulk. There is universal agreement among all tested functionals in predicting the magnitude of the frequency shift upon a variation in the in-plane cell parameter. It is clear that a small in-plane contraction can explain the Raman peak upshift from bulk to monolayer. However, we show that the larger in-plane parameter in the bulk (compared to the monolayer) results from non-local correlation effects, which cannot be accounted for by local functionals or those with empirical dispersion corrections. Using a non-local-correlation functional, we then investigate the effect of finite temperatures on the Raman signature. We demonstrate that bulk h-BN thermally expands in the direction perpendicular to the layers, while the intralayer distances slightly contract, in agreement with observed experimental behavior. Interestingly, the difference in in-plane cell parameter between bulk and monolayer decreases with temperature, and becomes very small at room temperature. We conclude that the different thermal expansion of bulk and monolayer partially 'erases' the intrinsic Raman signature, accounting for its small magnitude in recent experiments on suspended samples.

Origin of the monolayer Raman signature in hexagonal boron nitride: a first-principles analysis

NASA Astrophysics Data System (ADS)

Ontaneda, Jorge; Singh, Anjali; Waghmare, Umesh V.; Grau-Crespo, Ricardo

2018-05-01

Monolayers of hexagonal boron nitride (h-BN) can in principle be identified by a Raman signature, consisting of an upshift in the frequency of the E2g vibrational mode with respect to the bulk value, but the origin of this shift (intrinsic or support-induced) is still debated. Herein we use density functional theory calculations to investigate whether there is an intrinsic Raman shift in the h-BN monolayer in comparison with the bulk. There is universal agreement among all tested functionals in predicting the magnitude of the frequency shift upon a variation in the in-plane cell parameter. It is clear that a small in-plane contraction can explain the Raman peak upshift from bulk to monolayer. However, we show that the larger in-plane parameter in the bulk (compared to the monolayer) results from non-local correlation effects, which cannot be accounted for by local functionals or those with empirical dispersion corrections. Using a non-local-correlation functional, we then investigate the effect of finite temperatures on the Raman signature. We demonstrate that bulk h-BN thermally expands in the direction perpendicular to the layers, while the intralayer distances slightly contract, in agreement with observed experimental behavior. Interestingly, the difference in in-plane cell parameter between bulk and monolayer decreases with temperature, and becomes very small at room temperature. We conclude that the different thermal expansion of bulk and monolayer partially ‘erases’ the intrinsic Raman signature, accounting for its small magnitude in recent experiments on suspended samples.

Experimental strain modal analysis for beam-like structure by using distributed fiber optics and its damage detection

NASA Astrophysics Data System (ADS)

Cheng, Liangliang; Busca, Giorgio; Cigada, Alfredo

2017-07-01

Modal analysis is commonly considered as an effective tool to obtain the intrinsic characteristics of structures including natural frequencies, modal damping ratios, and mode shapes, which are significant indicators for monitoring the health status of engineering structures. The complex mode indicator function (CMIF) can be regarded as an effective numerical tool to perform modal analysis. In this paper, experimental strain modal analysis based on the CMIF has been introduced. Moreover, a distributed fiber-optic sensor, as a dense measuring device, has been applied to acquire strain data along a beam surface. Thanks to the dense spatial resolution of the distributed fiber optics, more detailed mode shapes could be obtained. In order to test the effectiveness of the method, a mass lump—considered as a linear damage component—has been attached to the surface of the beam, and damage detection based on strain mode shape has been carried out. The results manifest that strain modal parameters can be estimated effectively by utilizing the CMIF based on the corresponding simulations and experiments. Furthermore, damage detection based on strain mode shapes benefits from the accuracy of strain mode shape recognition and the excellent performance of the distributed fiber optics.

Multi-scale pixel-based image fusion using multivariate empirical mode decomposition.

PubMed

Rehman, Naveed ur; Ehsan, Shoaib; Abdullah, Syed Muhammad Umer; Akhtar, Muhammad Jehanzaib; Mandic, Danilo P; McDonald-Maier, Klaus D

2015-05-08

A novel scheme to perform the fusion of multiple images using the multivariate empirical mode decomposition (MEMD) algorithm is proposed. Standard multi-scale fusion techniques make a priori assumptions regarding input data, whereas standard univariate empirical mode decomposition (EMD)-based fusion techniques suffer from inherent mode mixing and mode misalignment issues, characterized respectively by either a single intrinsic mode function (IMF) containing multiple scales or the same indexed IMFs corresponding to multiple input images carrying different frequency information. We show that MEMD overcomes these problems by being fully data adaptive and by aligning common frequency scales from multiple channels, thus enabling their comparison at a pixel level and subsequent fusion at multiple data scales. We then demonstrate the potential of the proposed scheme on a large dataset of real-world multi-exposure and multi-focus images and compare the results against those obtained from standard fusion algorithms, including the principal component analysis (PCA), discrete wavelet transform (DWT) and non-subsampled contourlet transform (NCT). A variety of image fusion quality measures are employed for the objective evaluation of the proposed method. We also report the results of a hypothesis testing approach on our large image dataset to identify statistically-significant performance differences.

Multi-Scale Pixel-Based Image Fusion Using Multivariate Empirical Mode Decomposition

PubMed Central

Rehman, Naveed ur; Ehsan, Shoaib; Abdullah, Syed Muhammad Umer; Akhtar, Muhammad Jehanzaib; Mandic, Danilo P.; McDonald-Maier, Klaus D.

2015-01-01

A novel scheme to perform the fusion of multiple images using the multivariate empirical mode decomposition (MEMD) algorithm is proposed. Standard multi-scale fusion techniques make a priori assumptions regarding input data, whereas standard univariate empirical mode decomposition (EMD)-based fusion techniques suffer from inherent mode mixing and mode misalignment issues, characterized respectively by either a single intrinsic mode function (IMF) containing multiple scales or the same indexed IMFs corresponding to multiple input images carrying different frequency information. We show that MEMD overcomes these problems by being fully data adaptive and by aligning common frequency scales from multiple channels, thus enabling their comparison at a pixel level and subsequent fusion at multiple data scales. We then demonstrate the potential of the proposed scheme on a large dataset of real-world multi-exposure and multi-focus images and compare the results against those obtained from standard fusion algorithms, including the principal component analysis (PCA), discrete wavelet transform (DWT) and non-subsampled contourlet transform (NCT). A variety of image fusion quality measures are employed for the objective evaluation of the proposed method. We also report the results of a hypothesis testing approach on our large image dataset to identify statistically-significant performance differences. PMID:26007714

Intrinsic phonon properties of double-walled carbon nanotubes

NASA Astrophysics Data System (ADS)

Tran, H. N.; Levshov, D. I.; Nguyen, V. C.; Paillet, M.; Arenal, R.; Than, X. T.; Zahab, A. A.; Yuzyuk, Y. I.; Phan, N. M.; Sauvajol, J.-L.; Michel, T.

2017-03-01

Double-walled carbon nanotubes (DWNT) are made of two concentric and weakly van der Waals coupled single-walled carbon nanotubes (SWNT). DWNTs are the simplest systems for studying the mechanical and electronic interactions between concentric carbon layers. In this paper we review recent results concerning the intrinsic features of phonons of DWNTs obtained from Raman experiments performed on index-identified DWNTs. The effect of the interlayer distance on the strength of the mechanical and electronic coupling between the layers, and thus on the frequencies of the Raman-active modes, namely the radial breathing-like modes (RBLMs) and G-modes, are evidenced and discussed. Invited talk at 8th International Workshop on Advanced Materials Science and Nanotechnology (IWAMSN2016), 8-12 November 2016, Ha Long City, Vietnam.

A data-driven method to enhance vibration signal decomposition for rolling bearing fault analysis

NASA Astrophysics Data System (ADS)

Grasso, M.; Chatterton, S.; Pennacchi, P.; Colosimo, B. M.

2016-12-01

Health condition analysis and diagnostics of rotating machinery requires the capability of properly characterizing the information content of sensor signals in order to detect and identify possible fault features. Time-frequency analysis plays a fundamental role, as it allows determining both the existence and the causes of a fault. The separation of components belonging to different time-frequency scales, either associated to healthy or faulty conditions, represents a challenge that motivates the development of effective methodologies for multi-scale signal decomposition. In this framework, the Empirical Mode Decomposition (EMD) is a flexible tool, thanks to its data-driven and adaptive nature. However, the EMD usually yields an over-decomposition of the original signals into a large number of intrinsic mode functions (IMFs). The selection of most relevant IMFs is a challenging task, and the reference literature lacks automated methods to achieve a synthetic decomposition into few physically meaningful modes by avoiding the generation of spurious or meaningless modes. The paper proposes a novel automated approach aimed at generating a decomposition into a minimal number of relevant modes, called Combined Mode Functions (CMFs), each consisting in a sum of adjacent IMFs that share similar properties. The final number of CMFs is selected in a fully data driven way, leading to an enhanced characterization of the signal content without any information loss. A novel criterion to assess the dissimilarity between adjacent CMFs is proposed, based on probability density functions of frequency spectra. The method is suitable to analyze vibration signals that may be periodically acquired within the operating life of rotating machineries. A rolling element bearing fault analysis based on experimental data is presented to demonstrate the performances of the method and the provided benefits.

Effects of functional group mass variance on vibrational properties and thermal transport in graphene

DOE PAGES

Lindsay, L.; Kuang, Y.

2017-03-13

Intrinsic thermal resistivity critically depends on features of phonon dispersions dictated by harmonic interatomic forces and masses. We present the effects of functional group mass variance on vibrational properties and thermal conductivity (κ ) of functionalized graphene from first principles calculations. We also use graphane, a buckled graphene backbone with covalently bonded Hydrogen atoms on both sides, as the base material and vary the mass of the Hydrogen atoms to simulate the effect of mass variance from other functional groups. We find non-monotonic behavior of κ with increasing mass of the functional group and an unusual cross-over from acoustic-dominated tomore » optic-dominated thermal transport behavior. We connect this cross-over to changes in the phonon dispersion with varying mass which suppress acoustic phonon velocities, but also give unusually high velocity optic modes. Further, we show that out-of-plane acoustic vibrations contribute significantly more to thermal transport than in-plane acoustic modes despite breaking of a reflection symmetry based scattering selection rule responsible for their large contributions in graphene. Our work demonstrates the potential for manipulation and engineering of thermal transport properties in two dimensional materials toward targeted applications.« less

To rise and to fall: functional connectivity in cognitively normal and cognitively impaired patients with Parkinson's disease.

PubMed

Gorges, Martin; Müller, Hans-Peter; Lulé, Dorothée; Pinkhardt, Elmar H; Ludolph, Albert C; Kassubek, Jan

2015-04-01

Cognitive decline is a burdensome extra-motor symptom associated with Parkinson's disease (PD). This study aimed at investigating intrinsic functional connectivity (iFC) of the brain in cognitively unimpaired (PD-CU) and impaired PD patients (PD-CI) compared with age-matched healthy controls. "Resting-state" functional magnetic resonance imaging was acquired in 53 subjects, that is, 14 PD-CU patients, 17 PD-CI patients, and 22 control subjects. Cognition and cognitive status for patient classification were assessed using detailed neuropsychological testing. In PD-CU patients versus controls, we demonstrated significantly increased iFC (hyperconnectivity) presenting as network expansions in cortical, limbic, and basal ganglia-thalamic areas. Significantly, decreased iFC in PD-CI patients compared with control subjects was observed, predominantly between major nodes of the default mode network. In conclusion, the increased iFC might be the initial manifestation of altered brain function preceding cognitive deficits. Hyperconnectivity could be an adaptive (compensatory) mechanism by recruiting additional resources to maintain normal cognitive performance. As PD-related pathology progresses, functional disruptions within the default mode networks seem to be considerably associated with cognitive decline. Copyright © 2015 Elsevier Inc. All rights reserved.

Effects of functional group mass variance on vibrational properties and thermal transport in graphene

NASA Astrophysics Data System (ADS)

Lindsay, L.; Kuang, Y.

2017-03-01

Intrinsic thermal resistivity critically depends on features of phonon dispersions dictated by harmonic interatomic forces and masses. Here we present the effects of functional group mass variance on vibrational properties and thermal conductivity (κ ) of functionalized graphene from first-principles calculations. We use graphane, a buckled graphene backbone with covalently bonded hydrogen atoms on both sides, as the base material and vary the mass of the hydrogen atoms to simulate the effect of mass variance from other functional groups. We find nonmonotonic behavior of κ with increasing mass of the functional group and an unusual crossover from acoustic-dominated to optic-dominated thermal transport behavior. We connect this crossover to changes in the phonon dispersion with varying mass which suppress acoustic phonon velocities, but also give unusually high velocity optic modes. Further, we show that out-of-plane acoustic vibrations contribute significantly more to thermal transport than in-plane acoustic modes despite breaking of a reflection-symmetry-based scattering selection rule responsible for their large contributions in graphene. This work demonstrates the potential for manipulation and engineering of thermal transport properties in two-dimensional materials toward targeted applications.

Effects of functional group mass variance on vibrational properties and thermal transport in graphene

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

Lindsay, L.; Kuang, Y.

Intrinsic thermal resistivity critically depends on features of phonon dispersions dictated by harmonic interatomic forces and masses. We present the effects of functional group mass variance on vibrational properties and thermal conductivity (κ ) of functionalized graphene from first principles calculations. We also use graphane, a buckled graphene backbone with covalently bonded Hydrogen atoms on both sides, as the base material and vary the mass of the Hydrogen atoms to simulate the effect of mass variance from other functional groups. We find non-monotonic behavior of κ with increasing mass of the functional group and an unusual cross-over from acoustic-dominated tomore » optic-dominated thermal transport behavior. We connect this cross-over to changes in the phonon dispersion with varying mass which suppress acoustic phonon velocities, but also give unusually high velocity optic modes. Further, we show that out-of-plane acoustic vibrations contribute significantly more to thermal transport than in-plane acoustic modes despite breaking of a reflection symmetry based scattering selection rule responsible for their large contributions in graphene. Our work demonstrates the potential for manipulation and engineering of thermal transport properties in two dimensional materials toward targeted applications.« less

Measurements of the toroidal torque balance of error field penetration locked modes

DOE PAGES

Shiraki, Daisuke; Paz-Soldan, Carlos; Hanson, Jeremy M.; ...

2015-01-05

Here, detailed measurements from the DIII-D tokamak of the toroidal dynamics of error field penetration locked modes under the influence of slowly evolving external fields, enable study of the toroidal torques on the mode, including interaction with the intrinsic error field. The error field in these low density Ohmic discharges is well known based on the mode penetration threshold, allowing resonant and non-resonant torque effects to be distinguished. These m/n = 2/1 locked modes are found to be well described by a toroidal torque balance between the resonant interaction with n = 1 error fields, and a viscous torque inmore » the electron diamagnetic drift direction which is observed to scale as the square of the perturbed field due to the island. Fitting to this empirical torque balance allows a time-resolved measurement of the intrinsic error field of the device, providing evidence for a time-dependent error field in DIII-D due to ramping of the Ohmic coil current.« less

Pipe leak diagnostic using high frequency piezoelectric pressure sensor and automatic selection of intrinsic mode function

NASA Astrophysics Data System (ADS)

Yusop, Hanafi M.; Ghazali, M. F.; Yusof, M. F. M.; Remli, M. A. Pi; Kamarulzaman, M. H.

2017-10-01

In a recent study, the analysis of pressure transient signals could be seen as an accurate and low-cost method for leak and feature detection in water distribution systems. Transient phenomena occurs due to sudden changes in the fluid’s propagation in pipelines system caused by rapid pressure and flow fluctuation due to events such as closing and opening valves rapidly or through pump failure. In this paper, the feasibility of the Hilbert-Huang transform (HHT) method/technique in analysing the pressure transient signals in presented and discussed. HHT is a way to decompose a signal into intrinsic mode functions (IMF). However, the advantage of HHT is its difficulty in selecting the suitable IMF for the next data postprocessing method which is Hilbert Transform (HT). This paper reveals that utilizing the application of an integrated kurtosis-based algorithm for a z-filter technique (I-Kaz) to kurtosis ratio (I-Kaz-Kurtosis) allows/contributes to/leads to automatic selection of the IMF that should be used. This technique is demonstrated on a 57.90-meter medium high-density polyethylene (MDPE) pipe installed with a single artificial leak. The analysis results using the I-Kaz-kurtosis ratio revealed/confirmed that the method can be used as an automatic selection of the IMF although the noise level ratio of the signal is low. Therefore, the I-Kaz-kurtosis ratio method is recommended as a means to implement an automatic selection technique of the IMF for HHT analysis.

Functional connectivity of default mode network components: correlation, anticorrelation, and causality

PubMed Central

Uddin, Lucina Q.; Clare Kelly, A. M.; Biswal, Bharat B.; Castellanos, F. Xavier; Milham, Michael P.

2013-01-01

The default mode network (DMN), based in ventromedial prefrontal cortex (vmPFC) and posterior cingulate cortex (PCC), exhibits higher metabolic activity at rest than during performance of externally-oriented cognitive tasks. Recent studies have suggested that competitive relationships between the DMN and various task-positive networks involved in task performance are intrinsically represented in the brain in the form of strong negative correlations (anticorrelations) between spontaneous fluctuations in these networks. Most neuroimaging studies characterize the DMN as a homogenous network, thus few have examined the differential contributions of DMN components to such competitive relationships. Here we examined functional differentiation within the default mode network, with an emphasis on understanding competitive relationships between this and other networks. We used a seed correlation approach on resting-state data to assess differences in functional connectivity between these two regions and their anticorrelated networks. While the positively correlated networks for the vmPFC and PCC seeds largely overlapped, the anticorrelated networks for each showed striking differences. Activity in vmPFC negatively predicted activity in parietal visual spatial and temporal attention networks, whereas activity in PCC negatively predicted activity in prefrontal-based motor control circuits. Granger causality analyses suggest that vmPFC and PCC exert greater influence on their anticorrelated networks than the other way around, suggesting that these two default mode nodes may directly modulate activity in task-positive networks. Thus, the two major nodes comprising the default mode network are differentiated with respect to the specific brain systems with which they interact, suggesting greater heterogeneity within this network than is commonly appreciated. PMID:18219617

Investigation of intrinsic toroidal rotation scaling in KSTAR

NASA Astrophysics Data System (ADS)

Yoo, J. W.; Lee, S. G.; Ko, S. H.; Seol, J.; Lee, H. H.; Kim, J. H.

2017-07-01

The behaviors of an intrinsic toroidal rotation without any external momentum sources are investigated in KSTAR. In these experiments, pure ohmic discharges with a wide range of plasma parameters are carefully selected and analyzed to speculate an unrevealed origin of toroidal rotation excluding any unnecessary heating sources, magnetic perturbations, and strong magneto-hydrodynamic activities. The measured core toroidal rotation in KSTAR is mostly in the counter-current direction and its magnitude strongly depends on the ion temperature divided by plasma current (Ti/IP). Especially the core toroidal rotation in the steady-state is well fitted by Ti/IP scaling with a slope of ˜-23, and the possible explanation of the scaling is compared with various candidates. As a result, the calculated offset rotation could not explain the measured core toroidal rotation since KSTAR has an extremely low intrinsic error field. For the stability conditions for ion and electron turbulences, it is hard to determine a dominant turbulence mode in this study. In addition, the intrinsic toroidal rotation level in ITER is estimated based on the KSTAR scaling since the intrinsic rotation plays an important role in stabilizing resistive wall modes for future reference.

Programming Cardiac Resynchronization Therapy for Electrical Synchrony: Reaching Beyond Left Bundle Branch Block and Left Ventricular Activation Delay.

PubMed

Varma, Niraj; O'Donnell, David; Bassiouny, Mohammed; Ritter, Philippe; Pappone, Carlo; Mangual, Jan; Cantillon, Daniel; Badie, Nima; Thibault, Bernard; Wisnoskey, Brian

2018-02-06

QRS narrowing following cardiac resynchronization therapy with biventricular (BiV) or left ventricular (LV) pacing is likely affected by patient-specific conduction characteristics (PR, qLV, LV-paced propagation interval), making a universal programming strategy likely ineffective. We tested these factors using a novel, device-based algorithm (SyncAV) that automatically adjusts paced atrioventricular delay (default or programmable offset) according to intrinsic atrioventricular conduction. Seventy-five patients undergoing cardiac resynchronization therapy (age 66±11 years; 65% male; 32% with ischemic cardiomyopathy; LV ejection fraction 28±8%; QRS duration 162±16 ms) with intact atrioventricular conduction (PR interval 194±34, range 128-300 ms), left bundle branch block, and optimized LV lead position were studied at implant. QRS duration (QRSd) reduction was compared for the following pacing configurations: nominal simultaneous BiV (Mode I: paced/sensed atrioventricular delay=140/110 ms), BiV+SyncAV with 50 ms offset (Mode II), BiV+SyncAV with offset that minimized QRSd (Mode III), or LV-only pacing+SyncAV with 50 ms offset (Mode IV). The intrinsic QRSd (162±16 ms) was reduced to 142±17 ms (-11.8%) by Mode I, 136±14 ms (-15.6%) by Mode IV, and 132±13 ms (-17.8%) by Mode II. Mode III yielded the shortest overall QRSd (123±12 ms, -23.9% [ P <0.001 versus all modes]) and was the only configuration without QRSd prolongation in any patient. QRS narrowing occurred regardless of QRSd, PR, or LV-paced intervals, or underlying ischemic disease. Post-implant electrical optimization in already well-selected patients with left bundle branch block and optimized LV lead position is facilitated by patient-tailored BiV pacing adjusted to intrinsic atrioventricular timing using an automatic device-based algorithm. © 2018 The Authors. Published on behalf of the American Heart Association, Inc., by Wiley.

Promoting Intrinsic and Extrinsic Motivation among Chemistry Students Using Computer-Assisted Instruction

ERIC Educational Resources Information Center

Gambari, Isiaka A.; Gbodi, Bimpe E.; Olakanmi, Eyitao U.; Abalaka, Eneojo N.

2016-01-01

The role of computer-assisted instruction in promoting intrinsic and extrinsic motivation among Nigerian secondary school chemistry students was investigated in this study. The study employed two modes of computer-assisted instruction (computer simulation instruction and computer tutorial instructional packages) and two levels of gender (male and…

NMR relaxation studies on the hydrate layer of intrinsically unstructured proteins.

PubMed

Bokor, Mónika; Csizmók, Veronika; Kovács, Dénes; Bánki, Péter; Friedrich, Peter; Tompa, Peter; Tompa, Kálmán

2005-03-01

Intrinsically unstructured/disordered proteins (IUPs) exist in a disordered and largely solvent-exposed, still functional, structural state under physiological conditions. As their function is often directly linked with structural disorder, understanding their structure-function relationship in detail is a great challenge to structural biology. In particular, their hydration and residual structure, both closely linked with their mechanism of action, require close attention. Here we demonstrate that the hydration of IUPs can be adequately approached by a technique so far unexplored with respect to IUPs, solid-state NMR relaxation measurements. This technique provides quantitative information on various features of hydrate water bound to these proteins. By freezing nonhydrate (bulk) water out, we have been able to measure free induction decays pertaining to protons of bound water from which the amount of hydrate water, its activation energy, and correlation times could be calculated. Thus, for three IUPs, the first inhibitory domain of calpastatin, microtubule-associated protein 2c, and plant dehydrin early responsive to dehydration 10, we demonstrate that they bind a significantly larger amount of water than globular proteins, whereas their suboptimal hydration and relaxation parameters are correlated with their differing modes of function. The theoretical treatment and experimental approach presented in this article may have general utility in characterizing proteins that belong to this novel structural class.

Intrinsic motivation, neurocognition and psychosocial functioning in schizophrenia: testing mediator and moderator effects.

PubMed

Nakagami, Eri; Xie, Bin; Hoe, Maanse; Brekke, John S

2008-10-01

This study examined the nature of the relationships among neurocognition, intrinsic motivation, and psychosocial functioning for persons with schizophrenia. Hypotheses concerning both mediator and moderator mechanisms were tested. 120 individuals diagnosed with schizophrenia were recruited as they entered outpatient psychosocial rehabilitation programs. Measures of psychosocial functioning and intrinsic motivation were administered at baseline. Measures of neurocognition were administered at baseline by testers blind to scores on other study variables. Data were analyzed using latent construct modeling to test for mediator and moderator effects. There were strong bivariate relationships between neurocognition, intrinsic motivation, and psychosocial functioning. The results demonstrated that intrinsic motivation strongly mediated the relationship between neurocognition and psychosocial functioning. This mediation was evidenced by: (i) the direct path from neurocognition to functional outcome no longer being statistically significant after the introduction of motivation into the model, (ii) the statistical significance of the indirect path from neurocognition through motivation to functional outcome. There was no support for the two moderation hypotheses: the level of neurocognition did not influence the relationship between intrinsic motivation and psychosocial functioning, nor did the level of intrinsic motivation influence the relationship between neurocognition and psychosocial functioning. Neurocognition influences psychosocial functioning through its relationship with intrinsic motivation. Intrinsic motivation is a critical mechanism for explaining the relationship between neurocognition and psychosocial functioning. Implications for the theoretical understanding and psychosocial treatment of intrinsic motivation in schizophrenia are discussed.

Lagrangian single-particle turbulent statistics through the Hilbert-Huang transform.

PubMed

Huang, Yongxiang; Biferale, Luca; Calzavarini, Enrico; Sun, Chao; Toschi, Federico

2013-04-01

The Hilbert-Huang transform is applied to analyze single-particle Lagrangian velocity data from numerical simulations of hydrodynamic turbulence. The velocity trajectory is described in terms of a set of intrinsic mode functions C(i)(t) and of their instantaneous frequency ω(i)(t). On the basis of this decomposition we define the ω-conditioned statistical moments of the C(i) modes, named q-order Hilbert spectra (HS). We show that such quantities have enhanced scaling properties as compared to traditional Fourier transform- or correlation-based (structure functions) statistical indicators, thus providing better insights into the turbulent energy transfer process. We present clear empirical evidence that the energylike quantity, i.e., the second-order HS, displays a linear scaling in time in the inertial range, as expected from a dimensional analysis. We also measure high-order moment scaling exponents in a direct way, without resorting to the extended self-similarity procedure. This leads to an estimate of the Lagrangian structure function exponents which are consistent with the multifractal prediction in the Lagrangian frame as proposed by Biferale et al. [Phys. Rev. Lett. 93, 064502 (2004)].

Temporal structure of neuronal population oscillations with empirical model decomposition

NASA Astrophysics Data System (ADS)

Li, Xiaoli

2006-08-01

Frequency analysis of neuronal oscillation is very important for understanding the neural information processing and mechanism of disorder in the brain. This Letter addresses a new method to analyze the neuronal population oscillations with empirical mode decomposition (EMD). Following EMD of neuronal oscillation, a series of intrinsic mode functions (IMFs) are obtained, then Hilbert transform of IMFs can be used to extract the instantaneous time frequency structure of neuronal oscillation. The method is applied to analyze the neuronal oscillation in the hippocampus of epileptic rats in vivo, the results show the neuronal oscillations have different descriptions during the pre-ictal, seizure onset and ictal periods of the epileptic EEG at the different frequency band. This new method is very helpful to provide a view for the temporal structure of neural oscillation.

Infrared multiple photon dissociation spectroscopy of group I and group II metal complexes with Boc-hydroxylamine.

PubMed

Dain, Ryan P; Gresham, Gary; Groenewold, Gary S; Steill, Jeffrey D; Oomens, Jos; Van Stipdonk, Michael J

2013-08-30

Hydroxamates are essential growth factors for some microbes, acting primarily as siderophores that solubilize iron for transport into a cell. Here we determined the intrinsic structure of 1:1 complexes between Boc-protected hydroxylamine and group I ([M(L)](+)) and group II ([M(L-H)](+)) cations, where M and L are the cation and ligand, respectively, which are convenient models for the functional unit of hydroxamate siderphores. The relevant complex ions were generated by electrospray ionization (ESI) and isolated and stored in a Fourier transform ion cyclotron resonance (FT-ICR) mass spectrometer. Infrared spectra of the isolated complexes were collected by monitoring (infrared) photodissociation yield as a function of photon energy. Experimental spectra were then compared to those predicted by density functional theory (DFT) calculations. The infrared multiple photon dissociation (IRMPD) spectra collected are in good agreement with those predicted to be lowest-energy by DFT. The spectra for the group I complexes contain six resolved absorptions that can be attributed to amide I and II type and hydroxylamine N-OH vibrations. Similar absorptions are observed for the group II cation complexes, with shifts of the amide I and amide II vibrations due to the change in structure with deprotonation of the hydroxylamine group. IRMPD spectroscopy unequivocally shows that the intrinsic binding mode for the group I cations involves the O atoms of the amide carbonyl and hydroxylamine groups of Boc-hydroxylamine. A similar binding mode is preferred for the group II cations, except that in this case the metal ion is coordinated by the O atom of the deprotonated hydroxylamine group. Copyright © 2013 John Wiley & Sons, Ltd.

Improving prediction accuracy of cooling load using EMD, PSR and RBFNN

NASA Astrophysics Data System (ADS)

Shen, Limin; Wen, Yuanmei; Li, Xiaohong

2017-08-01

To increase the accuracy for the prediction of cooling load demand, this work presents an EMD (empirical mode decomposition)-PSR (phase space reconstruction) based RBFNN (radial basis function neural networks) method. Firstly, analyzed the chaotic nature of the real cooling load demand, transformed the non-stationary cooling load historical data into several stationary intrinsic mode functions (IMFs) by using EMD. Secondly, compared the RBFNN prediction accuracies of each IMFs and proposed an IMF combining scheme that is combine the lower-frequency components (called IMF4-IMF6 combined) while keep the higher frequency component (IMF1, IMF2, IMF3) and the residual unchanged. Thirdly, reconstruct phase space for each combined components separately, process the highest frequency component (IMF1) by differential method and predict with RBFNN in the reconstructed phase spaces. Real cooling load data of a centralized ice storage cooling systems in Guangzhou are used for simulation. The results show that the proposed hybrid method outperforms the traditional methods.

Chemiresistive and Gravimetric Dual-Mode Gas Sensor toward Target Recognition and Differentiation.

PubMed

Chen, Yan; Zhang, Hao; Feng, Zhihong; Zhang, Hongxiang; Zhang, Rui; Yu, Yuanyuan; Tao, Jin; Zhao, Hongyuan; Guo, Wenlan; Pang, Wei; Duan, Xuexin; Liu, Jing; Zhang, Daihua

2016-08-24

We demonstrate a dual-mode gas sensor for simultaneous and independent acquisition of electrical and mechanical signals from the same gas adsorption event. The device integrates a graphene field-effect transistor (FET) with a piezoelectric resonator in a seamless manner by leveraging multiple structural and functional synergies. Dual signals resulting from independent physical processes, i.e., mass attachment and charge transfer can reflect intrinsic properties of gas molecules and potentially enable target recognition and quantification at the same time. Fabrication of the device is based on standard Integrated Circuit (IC) foundry processes and fully compatible with system-on-a-chip (SoC) integration to achieve extremely small form factors. In addition, the ability of simultaneous measurements of mass adsorption and charge transfer guides us to a more precise understanding of the interactions between graphene and various gas molecules. Besides its practical functions, the device serves as an effective tool to quantitatively investigate the physical processes and sensing mechanisms for a large library of sensing materials and target analytes.

The default-mode, ego-functions and free-energy: a neurobiological account of Freudian ideas

PubMed Central

Friston, K. J.

2010-01-01

This article explores the notion that Freudian constructs may have neurobiological substrates. Specifically, we propose that Freud’s descriptions of the primary and secondary processes are consistent with self-organized activity in hierarchical cortical systems and that his descriptions of the ego are consistent with the functions of the default-mode and its reciprocal exchanges with subordinate brain systems. This neurobiological account rests on a view of the brain as a hierarchical inference or Helmholtz machine. In this view, large-scale intrinsic networks occupy supraordinate levels of hierarchical brain systems that try to optimize their representation of the sensorium. This optimization has been formulated as minimizing a free-energy; a process that is formally similar to the treatment of energy in Freudian formulations. We substantiate this synthesis by showing that Freud’s descriptions of the primary process are consistent with the phenomenology and neurophysiology of rapid eye movement sleep, the early and acute psychotic state, the aura of temporal lobe epilepsy and hallucinogenic drug states. PMID:20194141

Intrinsic functional connectivity alterations in progressive supranuclear palsy: Differential effects in frontal cortex, motor, and midbrain networks.

PubMed

Rosskopf, Johannes; Gorges, Martin; Müller, Hans-Peter; Lulé, Dorothée; Uttner, Ingo; Ludolph, Albert C; Pinkhardt, Elmar; Juengling, Freimut D; Kassubek, Jan

2017-07-01

The topography of functional network changes in progressive supranuclear palsy can be mapped by intrinsic functional connectivity MRI. The objective of this study was to study functional connectivity and its clinical and behavioral correlates in dedicated networks comprising the cognition-related default mode and the motor and midbrain functional networks in patients with PSP. Whole-brain-based "resting-state" functional MRI and high-resolution T1-weighted magnetic resonance imaging data together with neuropsychological and video-oculographic data from 34 PSP patients (22 with Richardson subtype and 12 with parkinsonian subtype) and 35 matched healthy controls were subjected to network-based functional connectivity and voxel-based morphometry analysis. After correction for global patterns of brain atrophy, the group comparison between PSP patients and controls revealed significantly decreased functional connectivity (P < 0.05, corrected) in the prefrontal cortex, which was significantly correlated with cognitive performance (P = 0.006). Of note, midbrain network connectivity in PSP patients showed increased connectivity with the thalamus, on the one hand, whereas, on the other hand, lower functional connectivity within the midbrain was significantly correlated with vertical gaze impairment, as quantified by video-oculography (P = 0.004). PSP Richardson subtype showed significantly increased functional motor network connectivity with the medial prefrontal gyrus. PSP-associated neurodegeneration was attributed to both decreased and increased functional connectivity. Decreasing functional connectivity was associated with worse behavioral performance (ie, dementia severity and gaze palsy), whereas the pattern of increased functional connectivity may be a potential adaptive mechanism. © 2017 International Parkinson and Movement Disorder Society. © 2017 International Parkinson and Movement Disorder Society.

Mining Time-Resolved Functional Brain Graphs to an EEG-Based Chronnectomic Brain Aged Index (CBAI).

PubMed

Dimitriadis, Stavros I; Salis, Christos I

2017-01-01

The brain at rest consists of spatially and temporal distributed but functionally connected regions that called intrinsic connectivity networks (ICNs). Resting state electroencephalography (rs-EEG) is a way to characterize brain networks without confounds associated with task EEG such as task difficulty and performance. A novel framework of how to study dynamic functional connectivity under the notion of functional connectivity microstates (FCμstates) and symbolic dynamics is further discussed. Furthermore, we introduced a way to construct a single integrated dynamic functional connectivity graph (IDFCG) that preserves both the strength of the connections between every pair of sensors but also the type of dominant intrinsic coupling modes (DICM). The whole methodology is demonstrated in a significant and unexplored task for EEG which is the definition of an objective Chronnectomic Brain Aged index (CBAI) extracted from resting-state data ( N = 94 subjects) with both eyes-open and eyes-closed conditions. Novel features have been defined based on symbolic dynamics and the notion of DICM and FCμstates. The transition rate of FCμstates, the symbolic dynamics based on the evolution of FCμstates (the Markovian Entropy, the complexity index), the probability distribution of DICM, the novel Flexibility Index that captures the dynamic reconfiguration of DICM per pair of EEG sensors and the relative signal power constitute a valuable pool of features that can build the proposed CBAI. Here we applied a feature selection technique and Extreme Learning Machine (ELM) classifier to discriminate young adults from middle-aged and a Support Vector Regressor to build a linear model of the actual age based on EEG-based spatio-temporal features. The most significant type of features for both prediction of age and discrimination of young vs. adults age groups was the dynamic reconfiguration of dominant coupling modes derived from a subset of EEG sensor pairs. Specifically, our results revealed a very high prediction of age for eyes-open ( R 2 = 0.60; y = 0.79x + 8.03) and lower for eyes-closed ( R 2 = 0.48; y = 0.71x + 10.91) while we succeeded to correctly classify young vs. middle-age group with 97.8% accuracy in eyes-open and 87.2% for eyes-closed. Our results were reproduced also in a second dataset for further external validation of the whole analysis. The proposed methodology proved valuable for the characterization of the intrinsic properties of dynamic functional connectivity through the age untangling developmental differences using EEG resting-state recordings.

Doping-Induced Type-II to Type-I Transition and Interband Optical Gain in InAs/AlSb Quantum Wells

NASA Technical Reports Server (NTRS)

Kolokolov, K. I.; Ning, C. Z.

2003-01-01

We show that proper doping of the barrier regions can convert the well-known type-II InAs/AlSb QWs to type I, producing strong interband transitions comparable to regular type-I QWs. The interband gain for TM mode is as high as 4000 l/cm, thus providing an important alternative material system in the mid-infrared wavelength range. We also study the TE and TM gain as functions of doping level and intrinsic electron-hole density.

Noise reduction in Lidar signal using correlation-based EMD combined with soft thresholding and roughness penalty

NASA Astrophysics Data System (ADS)

Chang, Jianhua; Zhu, Lingyan; Li, Hongxu; Xu, Fan; Liu, Binggang; Yang, Zhenbo

2018-01-01

Empirical mode decomposition (EMD) is widely used to analyze the non-linear and non-stationary signals for noise reduction. In this study, a novel EMD-based denoising method, referred to as EMD with soft thresholding and roughness penalty (EMD-STRP), is proposed for the Lidar signal denoising. With the proposed method, the relevant and irrelevant intrinsic mode functions are first distinguished via a correlation coefficient. Then, the soft thresholding technique is applied to the irrelevant modes, and the roughness penalty technique is applied to the relevant modes to extract as much information as possible. The effectiveness of the proposed method was evaluated using three typical signals contaminated by white Gaussian noise. The denoising performance was then compared to the denoising capabilities of other techniques, such as correlation-based EMD partial reconstruction, correlation-based EMD hard thresholding, and wavelet transform. The use of EMD-STRP on the measured Lidar signal resulted in the noise being efficiently suppressed, with an improved signal to noise ratio of 22.25 dB and an extended detection range of 11 km.

News on the Scissors Mode

NASA Astrophysics Data System (ADS)

Pietralla, N.; Beller, J.; Beck, T.; Derya, V.; Löher, B.; Romig, C.; Savran, D.; Scheck, M.; Tornow, W.; Zweidinger, M.

2014-09-01

We report on our recent nuclear resonance fluorescence experiments on l52,l54,l56Gd. Decay branches of the scissors mode to intrinsic excitations are observed. They are interpreted as a new signature for a spherical-to-deformed nuclear shape phase transition.

Global gyrokinetic simulations of intrinsic rotation in ASDEX Upgrade Ohmic L-mode plasmas

NASA Astrophysics Data System (ADS)

Hornsby, W. A.; Angioni, C.; Lu, Z. X.; Fable, E.; Erofeev, I.; McDermott, R.; Medvedeva, A.; Lebschy, A.; Peeters, A. G.; The ASDEX Upgrade Team

2018-05-01

Non-linear, radially global, turbulence simulations of ASDEX Upgrade (AUG) plasmas are performed and the nonlinear generated intrinsic flow shows agreement with the intrinsic flow gradients measured in the core of Ohmic L-mode plasmas at nominal parameters. Simulations utilising the kinetic electron model show hollow intrinsic flow profiles as seen in a predominant number of experiments performed at similar plasma parameters. In addition, significantly larger flow gradients are seen than in a previous flux-tube analysis (Hornsby et al 2017 Nucl. Fusion 57 046008). Adiabatic electron model simulations can show a flow profile with opposing sign in the gradient with respect to a kinetic electron simulation, implying a reversal in the sign of the residual stress due to kinetic electrons. The shaping of the intrinsic flow is strongly determined by the density gradient profile. The sensitivity of the residual stress to variations in density profile curvature is calculated and seen to be significantly stronger than to neoclassical flows (Hornsby et al 2017 Nucl. Fusion 57 046008). This variation is strong enough on its own to explain the large variations in the intrinsic flow gradients seen in some AUG experiments. Analysis of the symmetry breaking properties of the turbulence shows that profile shearing is the dominant mechanism in producing a finite parallel wave-number, with turbulence gradient effects contributing a smaller portion of the parallel wave-vector.

Pleasure attainment or self-realization: the balance between two forms of well-beings are encoded in default mode network.

PubMed

Luo, Yangmei; Qi, Senqing; Chen, Xuhai; You, Xuqun; Huang, Xiting; Yang, Zhen

2017-10-01

What is a good life and how it can be achieved is one of the fundamental issues. When considering a good life, there is a division between hedonic (pleasure attainment) and eudaimonic well-being (meaning pursuing and self-realization). However, an integrated approach that can compare the brain functional and structural differences of these two forms of well-being is lacking. Here, we investigated how the individual tendency to eudaimonic well-being relative to hedonic well-being, measured using eudaimonic and hedonic balance (EHB) index, is reflected in the functional and structural features of a key network of well-being-the default mode network (DMN). We found that EHB was positively correlated with functional connectivity of bilateral ventral medial prefrontal cortex within anterior DMN and bilateral precuneus within posterior DMN. Brain morphometric analysis showed that EHB was also positively correlated with gray matter volume in left precuneus. These results demonstrated that the relative dominance of one form of well-being to the other is reflected in the morphometric characteristics and intrinsic functions of DMN. © The Author (2017). Published by Oxford University Press.

Fully integrated reflection-mode photoacoustic, two-photon, and second harmonic generation microscopy in vivo

NASA Astrophysics Data System (ADS)

Song, Wei; Xu, Qiang; Zhang, Yang; Zhan, Yang; Zheng, Wei; Song, Liang

2016-08-01

The ability to obtain comprehensive structural and functional information from intact biological tissue in vivo is highly desirable for many important biomedical applications, including cancer and brain studies. Here, we developed a fully integrated multimodal microscopy that can provide photoacoustic (optical absorption), two-photon (fluorescence), and second harmonic generation (SHG) information from tissue in vivo, with intrinsically co-registered images. Moreover, using a delicately designed optical-acoustic coupling configuration, a high-frequency miniature ultrasonic transducer was integrated into a water-immersion optical objective, thus allowing all three imaging modalities to provide a high lateral resolution of ~290 nm with reflection-mode imaging capability, which is essential for studying intricate anatomy, such as that of the brain. Taking advantage of the complementary and comprehensive contrasts of the system, we demonstrated high-resolution imaging of various tissues in living mice, including microvasculature (by photoacoustics), epidermis cells, cortical neurons (by two-photon fluorescence), and extracellular collagen fibers (by SHG). The intrinsic image co-registration of the three modalities conveniently provided improved visualization and understanding of the tissue microarchitecture. The reported results suggest that, by revealing complementary tissue microstructures in vivo, this multimodal microscopy can potentially facilitate a broad range of biomedical studies, such as imaging of the tumor microenvironment and neurovascular coupling.

The intrinsic B-mode polarisation of the Cosmic Microwave Background

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

Fidler, Christian; Pettinari, Guido W.; Crittenden, Robert

2014-07-01

We estimate the B-polarisation induced in the Cosmic Microwave Background by the non-linear evolution of density perturbations. Using the second-order Boltzmann code SONG, our analysis incorporates, for the first time, all physical effects at recombination. We also include novel contributions from the redshift part of the Boltzmann equation and from the bolometric definition of the temperature in the presence of polarisation. The remaining line-of-sight terms (lensing and time-delay) have previously been studied and must be calculated non-perturbatively. The intrinsic B-mode polarisation is present independent of the initial conditions and might contaminate the signal from primordial gravitational waves. We find thismore » contamination to be comparable to a primordial tensor-to-scalar ratio of r ≅ 10{sup −7} at the angular scale ℓ ≅ 100, where the primordial signal peaks, and r ≅ 5 × 10{sup −5} at ℓ ≅ 700, where the intrinsic signal peaks. Therefore, we conclude that the intrinsic B-polarisation from second-order effects is not likely to contaminate future searches of primordial gravitational waves.« less

Fault identification of rotor-bearing system based on ensemble empirical mode decomposition and self-zero space projection analysis

NASA Astrophysics Data System (ADS)

Jiang, Fan; Zhu, Zhencai; Li, Wei; Zhou, Gongbo; Chen, Guoan

2014-07-01

Accurately identifying faults in rotor-bearing systems by analyzing vibration signals, which are nonlinear and nonstationary, is challenging. To address this issue, a new approach based on ensemble empirical mode decomposition (EEMD) and self-zero space projection analysis is proposed in this paper. This method seeks to identify faults appearing in a rotor-bearing system using simple algebraic calculations and projection analyses. First, EEMD is applied to decompose the collected vibration signals into a set of intrinsic mode functions (IMFs) for features. Second, these extracted features under various mechanical health conditions are used to design a self-zero space matrix according to space projection analysis. Finally, the so-called projection indicators are calculated to identify the rotor-bearing system's faults with simple decision logic. Experiments are implemented to test the reliability and effectiveness of the proposed approach. The results show that this approach can accurately identify faults in rotor-bearing systems.

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

PubMed

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.

[A Feature Extraction Method for Brain Computer Interface Based on Multivariate Empirical Mode Decomposition].

PubMed

Wang, Jinjia; Liu, Yuan

2015-04-01

This paper presents a feature extraction method based on multivariate empirical mode decomposition (MEMD) combining with the power spectrum feature, and the method aims at the non-stationary electroencephalogram (EEG) or magnetoencephalogram (MEG) signal in brain-computer interface (BCI) system. Firstly, we utilized MEMD algorithm to decompose multichannel brain signals into a series of multiple intrinsic mode function (IMF), which was proximate stationary and with multi-scale. Then we extracted and reduced the power characteristic from each IMF to a lower dimensions using principal component analysis (PCA). Finally, we classified the motor imagery tasks by linear discriminant analysis classifier. The experimental verification showed that the correct recognition rates of the two-class and four-class tasks of the BCI competition III and competition IV reached 92.0% and 46.2%, respectively, which were superior to the winner of the BCI competition. The experimental proved that the proposed method was reasonably effective and stable and it would provide a new way for feature extraction.

An optimized time varying filtering based empirical mode decomposition method with grey wolf optimizer for machinery fault diagnosis

NASA Astrophysics Data System (ADS)

Zhang, Xin; Liu, Zhiwen; Miao, Qiang; Wang, Lei

2018-03-01

A time varying filtering based empirical mode decomposition (EMD) (TVF-EMD) method was proposed recently to solve the mode mixing problem of EMD method. Compared with the classical EMD, TVF-EMD was proven to improve the frequency separation performance and be robust to noise interference. However, the decomposition parameters (i.e., bandwidth threshold and B-spline order) significantly affect the decomposition results of this method. In original TVF-EMD method, the parameter values are assigned in advance, which makes it difficult to achieve satisfactory analysis results. To solve this problem, this paper develops an optimized TVF-EMD method based on grey wolf optimizer (GWO) algorithm for fault diagnosis of rotating machinery. Firstly, a measurement index termed weighted kurtosis index is constructed by using kurtosis index and correlation coefficient. Subsequently, the optimal TVF-EMD parameters that match with the input signal can be obtained by GWO algorithm using the maximum weighted kurtosis index as objective function. Finally, fault features can be extracted by analyzing the sensitive intrinsic mode function (IMF) owning the maximum weighted kurtosis index. Simulations and comparisons highlight the performance of TVF-EMD method for signal decomposition, and meanwhile verify the fact that bandwidth threshold and B-spline order are critical to the decomposition results. Two case studies on rotating machinery fault diagnosis demonstrate the effectiveness and advantages of the proposed method.

Influence of cerebrovascular disease on brain networks in prodromal and clinical Alzheimer's disease.

PubMed

Chong, Joanna Su Xian; Liu, Siwei; Loke, Yng Miin; Hilal, Saima; Ikram, Mohammad Kamran; Xu, Xin; Tan, Boon Yeow; Venketasubramanian, Narayanaswamy; Chen, Christopher Li-Hsian; Zhou, Juan

2017-11-01

Network-sensitive neuroimaging methods have been used to characterize large-scale brain network degeneration in Alzheimer's disease and its prodrome. However, few studies have investigated the combined effect of Alzheimer's disease and cerebrovascular disease on brain network degeneration. Our study sought to examine the intrinsic functional connectivity and structural covariance network changes in 235 prodromal and clinical Alzheimer's disease patients with and without cerebrovascular disease. We focused particularly on two higher-order cognitive networks-the default mode network and the executive control network. We found divergent functional connectivity and structural covariance patterns in Alzheimer's disease patients with and without cerebrovascular disease. Alzheimer's disease patients without cerebrovascular disease, but not Alzheimer's disease patients with cerebrovascular disease, showed reductions in posterior default mode network functional connectivity. By comparison, while both groups exhibited parietal reductions in executive control network functional connectivity, only Alzheimer's disease patients with cerebrovascular disease showed increases in frontal executive control network connectivity. Importantly, these distinct executive control network changes were recapitulated in prodromal Alzheimer's disease patients with and without cerebrovascular disease. Across Alzheimer's disease patients with and without cerebrovascular disease, higher default mode network functional connectivity z-scores correlated with greater hippocampal volumes while higher executive control network functional connectivity z-scores correlated with greater white matter changes. In parallel, only Alzheimer's disease patients without cerebrovascular disease showed increased default mode network structural covariance, while only Alzheimer's disease patients with cerebrovascular disease showed increased executive control network structural covariance compared to controls. Our findings demonstrate the differential neural network structural and functional changes in Alzheimer's disease with and without cerebrovascular disease, suggesting that the underlying pathology of Alzheimer's disease patients with cerebrovascular disease might differ from those without cerebrovascular disease and reflect a combination of more severe cerebrovascular disease and less severe Alzheimer's disease network degeneration phenotype. © The Author (2017). Published by Oxford University Press on behalf of the Guarantors of Brain.

Influence of cerebrovascular disease on brain networks in prodromal and clinical Alzheimer’s disease

PubMed Central

Chong, Joanna Su Xian; Liu, Siwei; Loke, Yng Miin; Hilal, Saima; Ikram, Mohammad Kamran; Xu, Xin; Tan, Boon Yeow; Venketasubramanian, Narayanaswamy; Chen, Christopher Li-Hsian

2017-01-01

Abstract Network-sensitive neuroimaging methods have been used to characterize large-scale brain network degeneration in Alzheimer’s disease and its prodrome. However, few studies have investigated the combined effect of Alzheimer’s disease and cerebrovascular disease on brain network degeneration. Our study sought to examine the intrinsic functional connectivity and structural covariance network changes in 235 prodromal and clinical Alzheimer’s disease patients with and without cerebrovascular disease. We focused particularly on two higher-order cognitive networks—the default mode network and the executive control network. We found divergent functional connectivity and structural covariance patterns in Alzheimer’s disease patients with and without cerebrovascular disease. Alzheimer’s disease patients without cerebrovascular disease, but not Alzheimer’s disease patients with cerebrovascular disease, showed reductions in posterior default mode network functional connectivity. By comparison, while both groups exhibited parietal reductions in executive control network functional connectivity, only Alzheimer’s disease patients with cerebrovascular disease showed increases in frontal executive control network connectivity. Importantly, these distinct executive control network changes were recapitulated in prodromal Alzheimer’s disease patients with and without cerebrovascular disease. Across Alzheimer’s disease patients with and without cerebrovascular disease, higher default mode network functional connectivity z-scores correlated with greater hippocampal volumes while higher executive control network functional connectivity z-scores correlated with greater white matter changes. In parallel, only Alzheimer’s disease patients without cerebrovascular disease showed increased default mode network structural covariance, while only Alzheimer’s disease patients with cerebrovascular disease showed increased executive control network structural covariance compared to controls. Our findings demonstrate the differential neural network structural and functional changes in Alzheimer’s disease with and without cerebrovascular disease, suggesting that the underlying pathology of Alzheimer’s disease patients with cerebrovascular disease might differ from those without cerebrovascular disease and reflect a combination of more severe cerebrovascular disease and less severe Alzheimer’s disease network degeneration phenotype. PMID:29053778

Capillary waves' dynamics at the nanoscale

NASA Astrophysics Data System (ADS)

Delgado-Buscalioni, Rafael; Chacón, Enrique; Tarazona, Pedro

2008-12-01

We study the dynamics of thermally excited capillary waves (CW) at molecular scales, using molecular dynamics simulations of simple liquid slabs. The analysis is based on the Fourier modes of the liquid surface, constructed via the intrinsic sampling method (Chacón and Tarazona 2003 Phys. Rev. Lett. 91 166103). We obtain the time autocorrelation of the Fourier modes to get the frequency and damping rate Γd(q) of each mode, with wavenumber q. Continuum hydrodynamics predicts \\Gamma (q) \\propto q\\gamma (q) and thus provides a dynamic measure of the q-dependent surface tension, γd(q). The dynamical estimation is much more robust than the structural prediction based on the amplitude of the Fourier mode, γs(q). Using the optimal estimation of the intrinsic surface, we obtain quantitative agreement between the structural and dynamic pictures. Quite surprisingly, the hydrodynamic prediction for CW remains valid up to wavelengths of about four molecular diameters. Surface tension hydrodynamics break down at shorter scales, whereby a transition to a molecular diffusion regime is observed.

Fabrication and electro-optic characteristics of polymer-stabilized V-mode FLCD and intrinsic H-V-mode FLCD: their application to AM LCDs

NASA Astrophysics Data System (ADS)

Kobayashi, Shunsuke; Furuta, Hirokazu; Murakami, Yuji; Xu, Jun; Mochizuki, Akihiro

2003-04-01

Defect free polymer-stabilized (PS-)V-mode FLCDs and intrinsic half (H-)V-mode FLCDs have been fabricated; they exhibit high contrast ratio over 700:1 and high reliability for a temperature cycling test by using specially developed polyimide alignment materials, RN-1411 series, from Nissan Chem. Ind., and also by adopting special alignment technique such as appropriate rubbing technique, photoalignment, and ion beam irradiation techniques and also particularly developed polymer-stabilization technique. These FLCDs are shown to be useful for implementing a field sequential type full color (FS-FC) LCDs due to their fast response with the response time of τ = 100μs ~ 500μs that is 10 to 100 times faster that those of LCDs using NLCs. We have developed several prototype models of FS-FC LCDs having VGA specifications that exhibit good performance for displaying fast moving video rate images with wide color gamut.

Income change alters default mode network connectivity for adolescents in poverty.

PubMed

Weissman, David G; Conger, Rand D; Robins, Richard W; Hastings, Paul D; Guyer, Amanda E

2018-04-01

Experiencing poverty during childhood and adolescence may affect brain function. However, income is dynamic, and studies have not addressed whether income change relates to brain function. In the present study, we investigated whether intrinsic functional connectivity of default mode network (DMN) regions was influenced by mean family income and family income change. Parents of 68 Mexican-origin adolescents (35 females) reported family income annually when adolescents were 10-16 years old. Intercept and slope of income at each of these ages were calculated for each participant. At age 16 years, adolescents completed a resting state functional neuroimaging scan. Adolescents from high and low income families did not differ in their functional connectivity, but for adolescents in families with lower incomes, their connectivity patterns depended on their income slope. Low-income adolescents whose income increased demonstrated greater connectivity between the posterior cingulate cortex (PCC) and the medial prefrontal cortex (mPFC), both DMN regions, and between the PCC and the right inferior frontal gyrus. Increases in income were associated with greater connectivity of the mPFC with the right inferior frontal gyrus and the left superior parietal lobule regardless of mean income. Increases in income, especially among adolescents in poverty, may alleviate stressors, influencing the development of brain networks. Copyright © 2018 The Authors. Published by Elsevier Ltd.. All rights reserved.

Dynamic New World: Refining Our View of Protein Structure, Function and Evolution

PubMed Central

Mannige, Ranjan V.

2014-01-01

Proteins are crucial to the functioning of all lifeforms. Traditional understanding posits that a single protein occupies a single structure (“fold”), which performs a single function. This view is radically challenged with the recognition that high structural dynamism—the capacity to be extra “floppy”—is more prevalent in functional proteins than previously assumed. As reviewed here, this dynamic take on proteins affects our understanding of protein “structure”, function, and evolution, and even gives us a glimpse into protein origination. Specifically, this review will discuss historical developments concerning protein structure, and important new relationships between dynamism and aspects of protein sequence, structure, binding modes, binding promiscuity, evolvability, and origination. Along the way, suggestions will be provided for how key parts of textbook definitions—that so far have excluded membership to intrinsically disordered proteins (IDPs)—could be modified to accommodate our more dynamic understanding of proteins. PMID:28250374

Fault Detection of Bearing Systems through EEMD and Optimization Algorithm

PubMed Central

Lee, Dong-Han; Ahn, Jong-Hyo; Koh, Bong-Hwan

2017-01-01

This study proposes a fault detection and diagnosis method for bearing systems using ensemble empirical mode decomposition (EEMD) based feature extraction, in conjunction with particle swarm optimization (PSO), principal component analysis (PCA), and Isomap. First, a mathematical model is assumed to generate vibration signals from damaged bearing components, such as the inner-race, outer-race, and rolling elements. The process of decomposing vibration signals into intrinsic mode functions (IMFs) and extracting statistical features is introduced to develop a damage-sensitive parameter vector. Finally, PCA and Isomap algorithm are used to classify and visualize this parameter vector, to separate damage characteristics from healthy bearing components. Moreover, the PSO-based optimization algorithm improves the classification performance by selecting proper weightings for the parameter vector, to maximize the visualization effect of separating and grouping of parameter vectors in three-dimensional space. PMID:29143772

Normal-Mode Analysis of Circular DNA at the Base-Pair Level. 2. Large-Scale Configurational Transformation of a Naturally Curved Molecule.

PubMed

Matsumoto, Atsushi; Tobias, Irwin; Olson, Wilma K

2005-01-01

Fine structural and energetic details embedded in the DNA base sequence, such as intrinsic curvature, are important to the packaging and processing of the genetic material. Here we investigate the internal dynamics of a 200 bp closed circular molecule with natural curvature using a newly developed normal-mode treatment of DNA in terms of neighboring base-pair "step" parameters. The intrinsic curvature of the DNA is described by a 10 bp repeating pattern of bending distortions at successive base-pair steps. We vary the degree of intrinsic curvature and the superhelical stress on the molecule and consider the normal-mode fluctuations of both the circle and the stable figure-8 configuration under conditions where the energies of the two states are similar. To extract the properties due solely to curvature, we ignore other important features of the double helix, such as the extensibility of the chain, the anisotropy of local bending, and the coupling of step parameters. We compare the computed normal modes of the curved DNA model with the corresponding dynamical features of a covalently closed duplex of the same chain length constructed from naturally straight DNA and with the theoretically predicted dynamical properties of a naturally circular, inextensible elastic rod, i.e., an O-ring. The cyclic molecules with intrinsic curvature are found to be more deformable under superhelical stress than rings formed from naturally straight DNA. As superhelical stress is accumulated in the DNA, the frequency, i.e., energy, of the dominant bending mode decreases in value, and if the imposed stress is sufficiently large, a global configurational rearrangement of the circle to the figure-8 form takes place. We combine energy minimization with normal-mode calculations of the two states to decipher the configurational pathway between the two states. We also describe and make use of a general analytical treatment of the thermal fluctuations of an elastic rod to characterize the motions of the minicircle as a whole from knowledge of the full set of normal modes. The remarkable agreement between computed and theoretically predicted values of the average deviation and dispersion of the writhe of the circular configuration adds to the reliability in the computational approach. Application of the new formalism to the computed modes of the figure-8 provides insights into macromolecular motions which are beyond the scope of current theoretical treatments.

Default-Mode-Like Network Activation in Awake Rodents

PubMed Central

Upadhyay, Jaymin; Baker, Scott J.; Chandran, Prasant; Miller, Loan; Lee, Younglim; Marek, Gerard J.; Sakoglu, Unal; Chin, Chih-Liang; Luo, Feng; Fox, Gerard B.; Day, Mark

2011-01-01

During wakefulness and in absence of performing tasks or sensory processing, the default-mode network (DMN), an intrinsic central nervous system (CNS) network, is in an active state. Non-human primate and human CNS imaging studies have identified the DMN in these two species. Clinical imaging studies have shown that the pattern of activity within the DMN is often modulated in various disease states (e.g., Alzheimer's, schizophrenia or chronic pain). However, whether the DMN exists in awake rodents has not been characterized. The current data provides evidence that awake rodents also possess ‘DMN-like’ functional connectivity, but only subsequent to habituation to what is initially a novel magnetic resonance imaging (MRI) environment as well as physical restraint. Specifically, the habituation process spanned across four separate scanning sessions (Day 2, 4, 6 and 8). At Day 8, significant (p<0.05) functional connectivity was observed amongst structures such as the anterior cingulate (seed region), retrosplenial, parietal, and hippocampal cortices. Prior to habituation (Day 2), functional connectivity was only detected (p<0.05) amongst CNS structures known to mediate anxiety (i.e., anterior cingulate (seed region), posterior hypothalamic area, amygdala and parabracial nucleus). In relating functional connectivity between cingulate-default-mode and cingulate-anxiety structures across Days 2-8, a significant inverse relationship (r = −0.65, p = 0.0004) was observed between these two functional interactions such that increased cingulate-DMN connectivity corresponded to decreased cingulate anxiety network connectivity. This investigation demonstrates that the cingulate is an important component of both the rodent DMN-like and anxiety networks. PMID:22125628

Exploring the Role of Intrinsic Nodal Activation on the Spread of Influence in Complex Networks

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

Visweswara Sathanur, Arun; Halappanavar, Mahantesh; Shi, Yi

In many complex networked systems such as online social networks, at any given time, activity originates at certain nodes and subsequently spreads on the network through influence. To model the spread of influence in such a scenario, we consider the problem of identification of influential entities in a complex network when nodal activation can happen through two different mechanisms. The first mode of activation is due mechanisms intrinsic to the node. The second mechanism is through the influence of connected neighbors. In this work, we present a simple probabilistic formulation that models such self-evolving systems where information diffusion occurs primarilymore » because of the intrinsic activity of users and the spread of activity occurs due to influence. We provide an algorithm to mine for the influential seeds in such a scenario by modifying the well-known influence maximization framework with the independent cascade diffusion model. We provide small motivating examples to provide an intuitive understanding of the effect of including the intrinsic activation mechanism. We sketch a proof of the submodularity of the influence function under the new formulation and demonstrate the same with larger graphs. We then show by means of additional experiments on a real-world twitter dataset how the formulation can be applied to real-world social media datasets. Finally we derive a computationally efficient centrality metric that takes into account, both the mechanisms of activation and provides for an accurate as well as computationally efficient alternative approach to the problem of identifying influencers under intrinsic activation.« less

Decreased intrinsic brain connectivity is associated with reduced clinical pain in fibromyalgia.

PubMed

Napadow, Vitaly; Kim, Jieun; Clauw, Daniel J; Harris, Richard E

2012-07-01

A major impediment to the development of novel treatment strategies for fibromyalgia (FM) is the lack of an objective marker that reflects spontaneously reported clinical pain in patients with FM. Studies of resting-state intrinsic brain connectivity in FM have demonstrated increased insular connectivity to the default mode network (DMN), a network whose activity is increased during nontask states. Moreover, increased insular connectivity to the DMN was associated with increased spontaneous pain levels. However, as these analyses were cross-sectional in nature, they provided no insight into dynamic changes in connectivity or their relationship to variations in self-reported clinical pain. The purpose of this study was to evaluate longitudinal changes in the intrinsic brain connectivity of FM patients treated with nonpharmacologic interventions known to modulate pain levels in this patient population, and to test the hypothesis that the reduction of DMN-insula connectivity following therapy would correlate with diminished pain. Seventeen FM patients underwent resting-state functional magnetic resonance imaging at baseline and following 4 weeks of a nonpharmacologic intervention to diminish pain. Intrinsic DMN connectivity was evaluated using probabilistic independent components analysis. Longitudinal changes in intrinsic DMN connectivity were evaluated by paired analysis, and correlations between longitudinal changes in clinical pain and changes in intrinsic DMN connectivity were investigated by multiple linear regression analysis. Changes in clinical pain were assessed with the short form of the McGill Pain Questionnaire (SF-MPQ). Clinical pain as assessed using the sensory scale of the SF-MPQ was reduced following therapy (P=0.02). Intrinsic DMN connectivity to the insula was reduced, and this reduction correlated with reductions in pain (corrected P<0.05). Our findings suggest that intrinsic brain connectivity can be used as a candidate objective marker that reflects changes in spontaneous chronic pain within individual FM patients. We propose that intrinsic connectivity measures could potentially be used in either research or clinical settings as a complementary, more objective outcome measure for use in FM. Copyright © 2012 by the American College of Rheumatology.

Experimentally observed evolution between dynamic patterns and intrinsic localized modes in a driven nonlinear electrical cyclic lattice

NASA Astrophysics Data System (ADS)

Shige, S.; Miyasaka, K.; Shi, W.; Soga, Y.; Sato, M.; Sievers, A. J.

2018-02-01

Locked intrinsic localized modes (ILMs) and large amplitude lattice spatial modes (LSMs) have been experimentally measured for a driven 1-D nonlinear cyclic electric transmission line, where the nonlinear element is a saturable capacitor. Depending on the number of cells and electrical lattice damping an LSM of fixed shape can be tuned across the modal spectrum. Interestingly, by tuning the driver frequency away from this spectrum the LSM can be continuously converted into ILMs and vice versa. The differences in pattern formation between simulations and experimental findings are due to a low concentration of impurities. Through this novel nonlinear excitation and switching channel in cyclic lattices either energy balanced or unbalanced LSMs and ILMs may occur. Because of the general nature of these dynamical results for nonintegrable lattices applications are to be expected. The ultimate stability of driven aero machinery containing nonlinear periodic structures may be one example.

Coupling between Catalytic Loop Motions and Enzyme Global Dynamics

PubMed Central

Kurkcuoglu, Zeynep; Bakan, Ahmet; Kocaman, Duygu; Bahar, Ivet; Doruker, Pemra

2012-01-01

Catalytic loop motions facilitate substrate recognition and binding in many enzymes. While these motions appear to be highly flexible, their functional significance suggests that structure-encoded preferences may play a role in selecting particular mechanisms of motions. We performed an extensive study on a set of enzymes to assess whether the collective/global dynamics, as predicted by elastic network models (ENMs), facilitates or even defines the local motions undergone by functional loops. Our dataset includes a total of 117 crystal structures for ten enzymes of different sizes and oligomerization states. Each enzyme contains a specific functional/catalytic loop (10–21 residues long) that closes over the active site during catalysis. Principal component analysis (PCA) of the available crystal structures (including apo and ligand-bound forms) for each enzyme revealed the dominant conformational changes taking place in these loops upon substrate binding. These experimentally observed loop reconfigurations are shown to be predominantly driven by energetically favored modes of motion intrinsically accessible to the enzyme in the absence of its substrate. The analysis suggests that robust global modes cooperatively defined by the overall enzyme architecture also entail local components that assist in suitable opening/closure of the catalytic loop over the active site. PMID:23028297

The relationship between default mode network connectivity and social functioning in individuals at familial high-risk for schizophrenia.

PubMed

Dodell-Feder, David; Delisi, Lynn E; Hooker, Christine I

2014-06-01

Unaffected first-degree relatives of individuals with schizophrenia (i.e., those at familial high-risk [FHR]), demonstrate social dysfunction qualitatively similar though less severe than that of their affected relatives. These social difficulties may be the consequence of genetically conferred disruption to aspects of the default mode network (DMN), such as the dMPFC subsystem, which overlaps with the network of brain regions recruited during social cognitive processes. In the present study, we investigate this possibility, testing DMN connectivity and its relationship to social functioning in FHR using resting-state fMRI. Twenty FHR individuals and 17 controls underwent fMRI during a resting-state scan. Hypothesis-driven functional connectivity analyses examined ROI-to-ROI correlations between the DMN's hubs, and regions of the dMPFC subsystem and MTL subsystem. Connectivity values were examined in relationship to a measure of social functioning and empathy/perspective-taking. Results demonstrate that FHR exhibit reduced connectivity specifically within the dMPFC subsystem of the DMN. Certain ROI-to-ROI correlations predicted aspects of social functioning and empathy/perspective-taking across all participants. Together, the data indicate that disruption to the dMPFC subsystem of the DMN may be associated with familial risk for schizophrenia, and that these intrinsic connections may carry measurable consequences for social functioning. Copyright © 2014 Elsevier B.V. All rights reserved.

The relationship between default mode network connectivity and social functioning in individuals at familial high-risk for schizophrenia

PubMed Central

Dodell-Feder, David; DeLisi, Lynn E.; Hooker, Christine I.

2014-01-01

Unaffected first-degree relatives of individuals with schizophrenia (i.e., those at familial high-risk [FHR]), demonstrate social dysfunction qualitatively similar though less severe than that of their affected relatives. These social difficulties may be the consequence of genetically conferred disruption to aspects of the default mode network (DMN), such as the dMPFC subsystem, which overlaps with the network of brain regions recruited during social cognitive processes. In the present study, we investigate this possibility, testing DMN connectivity and its relationship to social functioning in FHR using resting-state fMRI. Twenty FHR individuals and 17 controls underwent fMRI during a resting-state scan. Hypothesis-driven functional connectivity analyses examined ROI-to-ROI correlations between the DMN’s hubs, and regions of the dMPFC subsystem and MTL subsystem. Connectivity values were examined in relationship to a measure of social functioning and empathy/perspective-taking. Results demonstrate that FHR exhibit reduced connectivity specifically within the dMPFC subsystem of the DMN. Certain ROI-to-ROI correlations predicted aspects of social functioning and empathy/perspective-taking across all participants. Together, the data indicate that disruption to the dMPFC subsystem of the DMN may be associated with familial risk for schizophrenia, and that these intrinsic connections may carry measurable consequences for social functioning. PMID:24768131

Multimode Jahn-Teller effect in bulk systems: A case of the N V 0 center in diamond

DOE PAGES

Zhang, Jianhua; Wang, Cai -Zhuang; Zhu, Zizhong; ...

2018-04-15

Here, the multimode Jahn-Teller (JT) effect in a bulk system of a neutral nitrogen-vacancy (NV 0) center in diamond is investigated via first-principles density-functional-theory calculations and the intrinsic distortion path (IDP) method. The adiabatic potential energy surface of the electronic ground state of the NV 0 center is calculated based on the local spin-density approximation. Our calculations confirm the presence of the dynamic Jahn-Teller effect in the ground 2E state of the NV 0 center. Within the harmonic approximation, the IDP method provides the reactive path of JT distortion from unstable high-symmetry geometry to stable low-symmetry energy minimum geometry, andmore » it describes the active normal modes participating in the distortion. We find that there is more than one vibrational mode contributing to the distortion, and their contributions change along the IDP. Several vibrational modes with large contributions to JT distortion, especially those modes close to 44 meV, are clearly observed as the phonon sideband in photoluminescence spectra in a series of experiments, indicating that the dynamic Jahn-Teller effect plays an important role in the optical transition of the NV 0 center.« less

Multimode Jahn-Teller effect in bulk systems: A case of the N V0 center in diamond

NASA Astrophysics Data System (ADS)

Zhang, Jianhua; Wang, Cai-Zhuang; Zhu, Zizhong; Liu, Qing Huo; Ho, Kai-Ming

2018-04-01

The multimode Jahn-Teller (JT) effect in a bulk system of a neutral nitrogen-vacancy (N V0 ) center in diamond is investigated via first-principles density-functional-theory calculations and the intrinsic distortion path (IDP) method. The adiabatic potential energy surface of the electronic ground state of the N V0 center is calculated based on the local spin-density approximation. Our calculations confirm the presence of the dynamic Jahn-Teller effect in the ground 2E state of the N V0 center. Within the harmonic approximation, the IDP method provides the reactive path of JT distortion from unstable high-symmetry geometry to stable low-symmetry energy minimum geometry, and it describes the active normal modes participating in the distortion. We find that there is more than one vibrational mode contributing to the distortion, and their contributions change along the IDP. Several vibrational modes with large contributions to JT distortion, especially those modes close to 44 meV, are clearly observed as the phonon sideband in photoluminescence spectra in a series of experiments, indicating that the dynamic Jahn-Teller effect plays an important role in the optical transition of the N V0 center.

Multimode Jahn-Teller effect in bulk systems: A case of the N V 0 center in diamond

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

Zhang, Jianhua; Wang, Cai -Zhuang; Zhu, Zizhong

Here, the multimode Jahn-Teller (JT) effect in a bulk system of a neutral nitrogen-vacancy (NV 0) center in diamond is investigated via first-principles density-functional-theory calculations and the intrinsic distortion path (IDP) method. The adiabatic potential energy surface of the electronic ground state of the NV 0 center is calculated based on the local spin-density approximation. Our calculations confirm the presence of the dynamic Jahn-Teller effect in the ground 2E state of the NV 0 center. Within the harmonic approximation, the IDP method provides the reactive path of JT distortion from unstable high-symmetry geometry to stable low-symmetry energy minimum geometry, andmore » it describes the active normal modes participating in the distortion. We find that there is more than one vibrational mode contributing to the distortion, and their contributions change along the IDP. Several vibrational modes with large contributions to JT distortion, especially those modes close to 44 meV, are clearly observed as the phonon sideband in photoluminescence spectra in a series of experiments, indicating that the dynamic Jahn-Teller effect plays an important role in the optical transition of the NV 0 center.« less

A Compound Fault Diagnosis for Rolling Bearings Method Based on Blind Source Separation and Ensemble Empirical Mode Decomposition

PubMed Central

Wang, Huaqing; Li, Ruitong; Tang, Gang; Yuan, Hongfang; Zhao, Qingliang; Cao, Xi

2014-01-01

A Compound fault signal usually contains multiple characteristic signals and strong confusion noise, which makes it difficult to separate week fault signals from them through conventional ways, such as FFT-based envelope detection, wavelet transform or empirical mode decomposition individually. In order to improve the compound faults diagnose of rolling bearings via signals’ separation, the present paper proposes a new method to identify compound faults from measured mixed-signals, which is based on ensemble empirical mode decomposition (EEMD) method and independent component analysis (ICA) technique. With the approach, a vibration signal is firstly decomposed into intrinsic mode functions (IMF) by EEMD method to obtain multichannel signals. Then, according to a cross correlation criterion, the corresponding IMF is selected as the input matrix of ICA. Finally, the compound faults can be separated effectively by executing ICA method, which makes the fault features more easily extracted and more clearly identified. Experimental results validate the effectiveness of the proposed method in compound fault separating, which works not only for the outer race defect, but also for the rollers defect and the unbalance fault of the experimental system. PMID:25289644

Fault detection, isolation, and diagnosis of self-validating multifunctional sensors.

PubMed

Yang, Jing-Li; Chen, Yin-Sheng; Zhang, Li-Li; Sun, Zhen

2016-06-01

A novel fault detection, isolation, and diagnosis (FDID) strategy for self-validating multifunctional sensors is presented in this paper. The sparse non-negative matrix factorization-based method can effectively detect faults by using the squared prediction error (SPE) statistic, and the variables contribution plots based on SPE statistic can help to locate and isolate the faulty sensitive units. The complete ensemble empirical mode decomposition is employed to decompose the fault signals to a series of intrinsic mode functions (IMFs) and a residual. The sample entropy (SampEn)-weighted energy values of each IMFs and the residual are estimated to represent the characteristics of the fault signals. Multi-class support vector machine is introduced to identify the fault mode with the purpose of diagnosing status of the faulty sensitive units. The performance of the proposed strategy is compared with other fault detection strategies such as principal component analysis, independent component analysis, and fault diagnosis strategies such as empirical mode decomposition coupled with support vector machine. The proposed strategy is fully evaluated in a real self-validating multifunctional sensors experimental system, and the experimental results demonstrate that the proposed strategy provides an excellent solution to the FDID research topic of self-validating multifunctional sensors.

Application of Hilbert-Huang Transform for Improved Defect Detection in Terahertz NDE of Shuttle Tiles

NASA Technical Reports Server (NTRS)

Anastasi, Robert F.; Madaras, Eric I.

2005-01-01

Terahertz NDE is being examined as a method to inspect the adhesive bond-line of Space Shuttle tiles for defects. Terahertz signals are generated and detected, using optical excitation of biased semiconductors with femtosecond laser pulses. Shuttle tile samples were manufactured with defects that included repair regions unbond regions, and other conditions that occur in Shuttle structures. These samples were inspected with a commercial terahertz NDE system that scanned a tile and generated a data set of RF signals. The signals were post processed to generate C-scan type images that are typically seen in ultrasonic NDE. To improve defect visualization the Hilbert-Huang Transform, a transform that decomposes a signal into oscillating components called intrinsic mode functions, was applied to test signals identified as being in and out of the defect regions and then on a complete data set. As expected with this transform, the results showed that the decomposed low-order modes correspond to signal noise while the high-order modes correspond to low frequency oscillations in the signal and mid-order modes correspond to local signal oscillations. The local oscillations compare well with various reflection interfaces and the defect locations in the original signal.

Disrupted intrinsic and remote functional connectivity in heterotopia-related epilepsy.

PubMed

Liu, W; Hu, X; An, D; Gong, Q; Zhou, D

2018-01-01

Several neuroimaging studies have examined neural interactions in patients with periventricular nodular heterotopia (PNH). However, features of the underlying functional network remain poorly understood. In this study, we examined alterations in the local (regional) and remote (interregional) cerebral networks in this disorder. Twenty-eight subjects all having suffered from PNH with epilepsy, as well as 28 age- and sex- matched healthy controls, were enrolled in this study. Amplitude of low-frequency fluctuation (ALFF) and seed-based functional connectivity (FC) were calculated to detect regional neural function and functional network integration, respectively. Compared with healthy controls, patients with PNH-related epilepsy showed decreased ALFF in the ventromedial prefrontal cortex (vmPFC) and precuneus areas. ALFF values in both areas were negative correlated with epilepsy duration (P < .05, Bonferroni-corrected). Furthermore, patients with PNH-related epilepsy had increased remote interregional FC mainly in bilateral prefrontal and parietal cortices, supramarginal gyrus, dorsal cingulate gyrus, and right insula; lower FC was found in posterior brain regions including bilateral parahippocampal gyrus and inferior temporal gyrus. Focal spontaneous hypofunction, as assessed by ALFF, correlates with epilepsy duration in patients with PNH-related epilepsy. Abnormalities existed both within the default-mode network and then across the whole brain, demonstrating that intrinsic brain dysfunction may be related to specific network interactions. Our findings provide novel understanding of the connectivity-based pathophysiological mechanisms of PNH. © 2017 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

Functional connectivity within and between intrinsic brain networks correlates with trait mind wandering.

PubMed

Godwin, Christine A; Hunter, Michael A; Bezdek, Matthew A; Lieberman, Gregory; Elkin-Frankston, Seth; Romero, Victoria L; Witkiewitz, Katie; Clark, Vincent P; Schumacher, Eric H

2017-08-01

Individual differences across a variety of cognitive processes are functionally associated with individual differences in intrinsic networks such as the default mode network (DMN). The extent to which these networks correlate or anticorrelate has been associated with performance in a variety of circumstances. Despite the established role of the DMN in mind wandering processes, little research has investigated how large-scale brain networks at rest relate to mind wandering tendencies outside the laboratory. Here we examine the extent to which the DMN, along with the dorsal attention network (DAN) and frontoparietal control network (FPCN) correlate with the tendency to mind wander in daily life. Participants completed the Mind Wandering Questionnaire and a 5-min resting state fMRI scan. In addition, participants completed measures of executive function, fluid intelligence, and creativity. We observed significant positive correlations between trait mind wandering and 1) increased DMN connectivity at rest and 2) increased connectivity between the DMN and FPCN at rest. Lastly, we found significant positive correlations between trait mind wandering and fluid intelligence (Ravens) and creativity (Remote Associates Task). We interpret these findings within the context of current theories of mind wandering and executive function and discuss the possibility that certain instances of mind wandering may not be inherently harmful. Due to the controversial nature of global signal regression (GSReg) in functional connectivity analyses, we performed our analyses with and without GSReg and contrast the results from each set of analyses. Copyright © 2017 Elsevier Ltd. All rights reserved.

Sustained anxiety increases amygdala–dorsomedial prefrontal coupling: a mechanism for maintaining an anxious state in healthy adults

PubMed Central

Vytal, Katherine E.; Overstreet, Cassie; Charney, Danielle R.; Robinson, Oliver J.; Grillon, Christian

2014-01-01

Background Neuroimaging research has traditionally explored fear and anxiety in response to discrete threat cues (e.g., during fear conditioning). However, anxiety is a sustained aversive state that can persist in the absence of discrete threats. Little is known about mechanisms that maintain anxiety states over a prolonged period. Here, we used a robust translational paradigm (threat of shock) to induce sustained anxiety. Recent translational work has implicated an amygdala–prefrontal cortex (PFC) circuit in the maintenance of anxiety in rodents. To explore the functional homologues of this circuitry in humans, we used a novel paradigm to examine the impact of sustained anticipatory anxiety on amygdala–PFC intrinsic connectivity. Methods Task-independent fMRI data were collected in healthy participants during long-duration periods of shock anticipation and safety. We examined intrinsic functional connectivity. Results Our study involved 20 healthy participants. During sustained anxiety, amygdala activity was positively coupled with dorsomedial PFC (DMPFC) activity. High trait anxiety was associated with increased amygdala–DMPFC coupling. In addition, induced anxiety was associated with positive coupling between regions involved in defensive responding, and decreased coupling between regions involved in emotional control and the default mode network. Limitations Inferences regarding anxious pathology should be made with caution because this study was conducted in healthy participants. Conclusion Findings suggest that anticipatory anxiety increases intrinsic amygdala–DMPFC coupling and that the DMPFC may serve as a functional homologue for the rodent prefrontal regions by sustaining anxiety. Future research may use this defensive neural context to identify bio-markers of risk for anxious pathology and target these circuits for therapeutic intervention. PMID:24886788

Exploring the Associations Between Intrinsic Brain Connectivity and Creative Ability Using Functional Connectivity Strength and Connectome Analysis.

PubMed

Gao, Zhenni; Zhang, Delong; Liang, Aiying; Liang, Bishan; Wang, Zengjian; Cai, Yuxuan; Li, Junchao; Gao, Mengxia; Liu, Xiaojin; Chang, Song; Jiao, Bingqing; Huang, Ruiwang; Liu, Ming

2017-11-01

The present study aimed to explore the association between resting-state functional connectivity and creativity ability. Toward this end, the figural Torrance Tests of Creative Thinking (TTCT) scores were collected from 180 participants. Based on the figural TTCT measures, we collected resting-state functional magnetic resonance imaging data for participants with two different levels of creativity ability (a high-creativity group [HG, n = 22] and a low-creativity group [LG, n = 20]). For the aspect of group difference, this study combined voxel-wise functional connectivity strength (FCS) and seed-based functional connectivity to identify brain regions with group-change functional connectivity. Furthermore, the connectome properties of the identified regions and their associations with creativity were investigated using the permutation test, discriminative analysis, and brain-behavior correlation analysis. The results indicated that there were 4 regions with group differences in FCS, and these regions were linked to 30 other regions, demonstrating different functional connectivity between the groups. Together, these regions form a creativity-related network, and we observed higher network efficiency in the HG compared with the LG. The regions involved in the creativity network were widely distributed across the modality-specific/supramodality cerebral cortex, subcortex, and cerebellum. Notably, properties of regions in the supramodality networks (i.e., the default mode network and attention network) carried creativity-level discriminative information and were significantly correlated with the creativity performance. Together, these findings demonstrate a link between intrinsic brain connectivity and creative ability, which should provide new insights into the neural basis of creativity.

Generalised ballooning theory of two-dimensional tokamak modes

NASA Astrophysics Data System (ADS)

Abdoul, P. A.; Dickinson, D.; Roach, C. M.; Wilson, H. R.

2018-02-01

In this work, using solutions from a local gyrokinetic flux-tube code combined with higher order ballooning theory, a new analytical approach is developed to reconstruct the global linear mode structure with associated global mode frequency. In addition to the isolated mode (IM), which usually peaks on the outboard mid-plane, the higher order ballooning theory has also captured other types of less unstable global modes: (a) the weakly asymmetric ballooning theory (WABT) predicts a mixed mode (MM) that undergoes a small poloidal shift away from the outboard mid-plane, (b) a relatively more stable general mode (GM) balloons on the top (or bottom) of the tokamak plasma. In this paper, an analytic approach is developed to combine these disconnected analytical limits into a single generalised ballooning theory. This is used to investigate how an IM behaves under the effect of sheared toroidal flow. For small values of flow an IM initially converts into a MM where the results of WABT are recaptured, and eventually, as the flow increases, the mode asymptotically becomes a GM on the top (or bottom) of the plasma. This may be an ingredient in models for understanding why in some experimental scenarios, instead of large edge localised modes (ELMs), small ELMs are observed. Finally, our theory can have other important consequences, especially for calculations involving Reynolds stress driven intrinsic rotation through the radial asymmetry in the global mode structures. Understanding the intrinsic rotation is significant because external torque in a plasma the size of ITER is expected to be relatively low.

Inter-subject Functional Correlation Reveal a Hierarchical Organization of Extrinsic and Intrinsic Systems in the Brain.

PubMed

Ren, Yudan; Nguyen, Vinh Thai; Guo, Lei; Guo, Christine Cong

2017-09-07

The brain is constantly monitoring and integrating both cues from the external world and signals generated intrinsically. These extrinsically and intrinsically-driven neural processes are thought to engage anatomically distinct regions, which are thought to constitute the extrinsic and intrinsic systems of the brain. While the specialization of extrinsic and intrinsic system is evident in primary and secondary sensory cortices, a systematic mapping of the whole brain remains elusive. Here, we characterized the extrinsic and intrinsic functional activities in the brain during naturalistic movie-viewing. Using a novel inter-subject functional correlation (ISFC) analysis, we found that the strength of ISFC shifts along the hierarchical organization of the brain. Primary sensory cortices appear to have strong inter-subject functional correlation, consistent with their role in processing exogenous information, while heteromodal regions that attend to endogenous processes have low inter-subject functional correlation. Those brain systems with higher intrinsic tendency show greater inter-individual variability, likely reflecting the aspects of brain connectivity architecture unique to individuals. Our study presents a novel framework for dissecting extrinsically- and intrinsically-driven processes, as well as examining individual differences in brain function during naturalistic stimulation.

Multidimensional k-nearest neighbor model based on EEMD for financial time series forecasting

NASA Astrophysics Data System (ADS)

Zhang, Ningning; Lin, Aijing; Shang, Pengjian

2017-07-01

In this paper, we propose a new two-stage methodology that combines the ensemble empirical mode decomposition (EEMD) with multidimensional k-nearest neighbor model (MKNN) in order to forecast the closing price and high price of the stocks simultaneously. The modified algorithm of k-nearest neighbors (KNN) has an increasingly wide application in the prediction of all fields. Empirical mode decomposition (EMD) decomposes a nonlinear and non-stationary signal into a series of intrinsic mode functions (IMFs), however, it cannot reveal characteristic information of the signal with much accuracy as a result of mode mixing. So ensemble empirical mode decomposition (EEMD), an improved method of EMD, is presented to resolve the weaknesses of EMD by adding white noise to the original data. With EEMD, the components with true physical meaning can be extracted from the time series. Utilizing the advantage of EEMD and MKNN, the new proposed ensemble empirical mode decomposition combined with multidimensional k-nearest neighbor model (EEMD-MKNN) has high predictive precision for short-term forecasting. Moreover, we extend this methodology to the case of two-dimensions to forecast the closing price and high price of the four stocks (NAS, S&P500, DJI and STI stock indices) at the same time. The results indicate that the proposed EEMD-MKNN model has a higher forecast precision than EMD-KNN, KNN method and ARIMA.

Fault Detection of a Roller-Bearing System through the EMD of a Wavelet Denoised Signal

PubMed Central

Ahn, Jong-Hyo; Kwak, Dae-Ho; Koh, Bong-Hwan

2014-01-01

This paper investigates fault detection of a roller bearing system using a wavelet denoising scheme and proper orthogonal value (POV) of an intrinsic mode function (IMF) covariance matrix. The IMF of the bearing vibration signal is obtained through empirical mode decomposition (EMD). The signal screening process in the wavelet domain eliminates noise-corrupted portions that may lead to inaccurate prognosis of bearing conditions. We segmented the denoised bearing signal into several intervals, and decomposed each of them into IMFs. The first IMF of each segment is collected to become a covariance matrix for calculating the POV. We show that covariance matrices from healthy and damaged bearings exhibit different POV profiles, which can be a damage-sensitive feature. We also illustrate the conventional approach of feature extraction, of observing the kurtosis value of the measured signal, to compare the functionality of the proposed technique. The study demonstrates the feasibility of wavelet-based de-noising, and shows through laboratory experiments that tracking the proper orthogonal values of the covariance matrix of the IMF can be an effective and reliable measure for monitoring bearing fault. PMID:25196008

A singularity free approach to post glacial rebound calculations

NASA Technical Reports Server (NTRS)

Fang, Ming; Hager, Bradford H.

1994-01-01

Calculating the post glacial response of a viscoelastic Earth model using the exponential decay normal mode technique leads to intrinsic singularities if viscosity varies continuously as a function of radius. We develop a numerical implementation of the Complex Real Fourier transform (CRFT) method as an accurate and stable procedure to avoid these singularities. Using CRFT, we investigate the response of a set of Maxwell Earth models to surface loading. We find that the effect of expanding a layered viscosity structure into a continuously varying structure is to destroy the modes associated with the boundary between layers. Horizontal motion is more sensitive than vertical motion to the viscosity structure just below the lithosphere. Horizontal motion is less sensitive to the viscosity of the lower mantle than the vertical motion is. When the viscosity increases at 670 km depth by a factor of about 60, the response of the lower mantle is close to its elastic limit. Any further increase of the viscosity contrast at 670 km depth or further increase of viscosity as a continuous function of depth starting from 670 km depth is unlikely to be resolved.

Instability Paths in the Kirchhoff-Plateau Problem

NASA Astrophysics Data System (ADS)

Giusteri, Giulio G.; Franceschini, Paolo; Fried, Eliot

2016-08-01

The Kirchhoff-Plateau problem concerns the equilibrium shapes of a system in which a flexible filament in the form of a closed loop is spanned by a soap film, with the filament being modeled as a Kirchhoff rod and the action of the spanning surface being solely due to surface tension. Adopting a variational approach, we define an energy associated with shape deformations of the system and then derive general equilibrium and (linear) stability conditions by considering the first and second variations of the energy functional. We analyze in detail the transition to instability of flat circular configurations, which are ground states for the system in the absence of surface tension, when the latter is progressively increased. Such a theoretical study is particularly useful here, since the many different perturbations that can lead to instability make it challenging to perform an exhaustive experimental investigation. We generalize previous results, since we allow the filament to possess a curved intrinsic shape and also to display anisotropic flexural properties (as happens when the cross section of the filament is noncircular). This is accomplished by using a rod energy which is familiar from the modeling of DNA filaments. We find that the presence of intrinsic curvature is necessary to obtain a first buckling mode which is not purely tangent to the spanning surface. We also elucidate the role of twisting buckling modes, which become relevant in the presence of flexural anisotropy.

Deciphering the Dynamic Interaction Profile of an Intrinsically Disordered Protein by NMR Exchange Spectroscopy.

PubMed

Delaforge, Elise; Kragelj, Jaka; Tengo, Laura; Palencia, Andrés; Milles, Sigrid; Bouvignies, Guillaume; Salvi, Nicola; Blackledge, Martin; Jensen, Malene Ringkjøbing

2018-01-24

Intrinsically disordered proteins (IDPs) display a large number of interaction modes including folding-upon-binding, binding without major structural transitions, or binding through highly dynamic, so-called fuzzy, complexes. The vast majority of experimental information about IDP binding modes have been inferred from crystal structures of proteins in complex with short peptides of IDPs. However, crystal structures provide a mainly static view of the complexes and do not give information about the conformational dynamics experienced by the IDP in the bound state. Knowledge of the dynamics of IDP complexes is of fundamental importance to understand how IDPs engage in highly specific interactions without concomitantly high binding affinity. Here, we combine rotating-frame R 1ρ , Carr-Purcell-Meiboom Gill relaxation dispersion as well as chemical exchange saturation transfer to decipher the dynamic interaction profile of an IDP in complex with its partner. We apply the approach to the dynamic signaling complex formed between the mitogen-activated protein kinase (MAPK) p38α and the intrinsically disordered regulatory domain of the MAPK kinase MKK4. Our study demonstrates that MKK4 employs a subtle combination of interaction modes in order to bind to p38α, leading to a complex displaying significantly different dynamics across the bound regions.

Emotion Recognition from EEG Signals Using Multidimensional Information in EMD Domain.

PubMed

Zhuang, Ning; Zeng, Ying; Tong, Li; Zhang, Chi; Zhang, Hanming; Yan, Bin

2017-01-01

This paper introduces a method for feature extraction and emotion recognition based on empirical mode decomposition (EMD). By using EMD, EEG signals are decomposed into Intrinsic Mode Functions (IMFs) automatically. Multidimensional information of IMF is utilized as features, the first difference of time series, the first difference of phase, and the normalized energy. The performance of the proposed method is verified on a publicly available emotional database. The results show that the three features are effective for emotion recognition. The role of each IMF is inquired and we find that high frequency component IMF1 has significant effect on different emotional states detection. The informative electrodes based on EMD strategy are analyzed. In addition, the classification accuracy of the proposed method is compared with several classical techniques, including fractal dimension (FD), sample entropy, differential entropy, and discrete wavelet transform (DWT). Experiment results on DEAP datasets demonstrate that our method can improve emotion recognition performance.

Bayesian network analysis revealed the connectivity difference of the default mode network from the resting-state to task-state

PubMed Central

Wu, Xia; Yu, Xinyu; Yao, Li; Li, Rui

2014-01-01

Functional magnetic resonance imaging (fMRI) studies have converged to reveal the default mode network (DMN), a constellation of regions that display co-activation during resting-state but co-deactivation during attention-demanding tasks in the brain. Here, we employed a Bayesian network (BN) analysis method to construct a directed effective connectivity model of the DMN and compared the organizational architecture and interregional directed connections under both resting-state and task-state. The analysis results indicated that the DMN was consistently organized into two closely interacting subsystems in both resting-state and task-state. The directed connections between DMN regions, however, changed significantly from the resting-state to task-state condition. The results suggest that the DMN intrinsically maintains a relatively stable structure whether at rest or performing tasks but has different information processing mechanisms under varied states. PMID:25309414

Analyzing Tropical Waves Using the Parallel Ensemble Empirical Model Decomposition Method: Preliminary Results from Hurricane Sandy

NASA Technical Reports Server (NTRS)

Shen, Bo-Wen; Cheung, Samson; Li, Jui-Lin F.; Wu, Yu-ling

2013-01-01

In this study, we discuss the performance of the parallel ensemble empirical mode decomposition (EMD) in the analysis of tropical waves that are associated with tropical cyclone (TC) formation. To efficiently analyze high-resolution, global, multiple-dimensional data sets, we first implement multilevel parallelism into the ensemble EMD (EEMD) and obtain a parallel speedup of 720 using 200 eight-core processors. We then apply the parallel EEMD (PEEMD) to extract the intrinsic mode functions (IMFs) from preselected data sets that represent (1) idealized tropical waves and (2) large-scale environmental flows associated with Hurricane Sandy (2012). Results indicate that the PEEMD is efficient and effective in revealing the major wave characteristics of the data, such as wavelengths and periods, by sifting out the dominant (wave) components. This approach has a potential for hurricane climate study by examining the statistical relationship between tropical waves and TC formation.

Systemic klotho is associated with KLOTHO variation and predicts intrinsic cortical connectivity in healthy human aging.

PubMed

Yokoyama, Jennifer S; Marx, Gabe; Brown, Jesse A; Bonham, Luke W; Wang, Dan; Coppola, Giovanni; Seeley, William W; Rosen, Howard J; Miller, Bruce L; Kramer, Joel H; Dubal, Dena B

2017-04-01

Cognitive decline is a major biomedical challenge as the global population ages. Elevated levels of the longevity factor klotho suppress aging, enhance cognition, and promote synaptic plasticity and neural resilience against aging and Alzheimer's disease (AD)-related pathogenic proteins. Here, we examined the relationship between human genetic variants of KLOTHO and systemic klotho levels - and assessed neuroanatomic correlates of serum klotho in a cohort of healthy older adults. Serum klotho levels were increased with KL-VS heterozygosity, as anticipated. We report, for the first time, that serum klotho levels were paradoxically decreased with KL-VS homozygosity. Further, we found that higher serum klotho levels were associated with measures of greater intrinsic connectivity in key functional networks of the brain vulnerable to aging and AD such as the fronto-parietal and default mode networks. Our findings suggest that elevated klotho promotes a resilient brain, possibly through increased network connectivity of critical brain regions.

Intrinsic motivation as a mediator between metacognition deficits and impaired functioning in psychosis.

PubMed

Luther, Lauren; Firmin, Ruth L; Vohs, Jenifer L; Buck, Kelly D; Rand, Kevin L; Lysaker, Paul H

2016-09-01

Poor functioning has long been observed in individuals with psychosis. Recent studies have identified metacognition - one's ability to form complex ideas about oneself and others and to use that information to respond to psychological and social challenges-as being an important determinant of functioning. However, the exact process by which deficits in metacognition lead to impaired functioning remains unclear. This study first examined whether low intrinsic motivation, or the tendency to pursue novel experiences and to engage in self-improvement, mediates the relationship between deficits in metacognition and impaired functioning. We then examined whether intrinsic motivation significantly mediated the relationship when controlling for age, education, symptoms, executive functioning, and social cognition. Mediation models were examined in a cross-sectional data set. One hundred and seventy-five individuals with a psychotic disorder completed interview-based measures of metacognition, intrinsic motivation, symptoms, and functioning and performance-based measures of executive functioning and social cognition. Analyses revealed that intrinsic motivation mediated the relationship between metacognition deficits and impaired functioning (95% CI of indirect effect [0.12-0.43]), even after controlling for the aforesaid variables (95% CI of indirect effect [0.04-0.29]). Results suggest that intrinsic motivation may be a mechanism that underlies the link between deficits in metacognition and impaired functioning and indicate that metacognition and intrinsic motivation may be important treatment targets to improve functioning in individuals with psychosis. The findings of this study suggest that deficits in metacognition may indirectly lead to impaired functioning through their effect on intrinsic motivation in individuals with psychosis. Psychological treatments that target deficits in both metacognition and intrinsic motivation may help to alleviate impaired functioning in individuals with psychosis. The cross-sectional design of this study is a limitation, and additional longitudinal studies are needed to confirm the direction of the findings and rule out rival hypotheses. Generalization of the findings may be limited by the sample composition. It may be that different relationships exist between metacognition, intrinsic motivation, and functioning in those with early psychosis or among those in an acute phase or who decline treatment. © 2016 The British Psychological Society.

Electric-field-induced plasmon in AA-stacked bilayer graphene

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

Chuang, Y.C., E-mail: yingchih.chuang@gmail.com; Wu, J.Y., E-mail: yarst5@gmail.com; Lin, M.F., E-mail: mflin@mail.ncku.edu.tw

2013-12-15

The collective excitations in AA-stacked bilayer graphene for a perpendicular electric field are investigated analytically within the tight-binding model and the random-phase approximation. Such a field destroys the uniform probability distribution of the four sublattices. This drives a symmetry breaking between the intralayer and interlayer polarization intensities from the intrapair band excitations. A field-induced acoustic plasmon thus emerges in addition to the strongly field-tunable intrinsic acoustic and optical plasmons. At long wavelengths, the three modes show different dispersions and field dependence. The definite physical mechanism of the electrically inducible and tunable mode can be expected to also be present inmore » other AA-stacked few-layer graphenes. -- Highlights: •The analytical derivations are performed by the tight-binding model. •An electric field drives the non-uniformity of the charge distribution. •A symmetry breaking between the intralayer and interlayer polarizations is illustrated. •An extra plasmon emerges besides two intrinsic modes in AA-stacked bilayer graphene. •The mechanism of a field-induced mode is present in AA-stacked few-layer graphenes.« less

Temporal complexity in emission from Anderson localized lasers

NASA Astrophysics Data System (ADS)

Kumar, Randhir; Balasubrahmaniyam, M.; Alee, K. Shadak; Mujumdar, Sushil

2017-12-01

Anderson localization lasers exploit resonant cavities formed due to structural disorder. The inherent randomness in the structure of these cavities realizes a probability distribution in all cavity parameters such as quality factors, mode volumes, mode structures, and so on, implying resultant statistical fluctuations in the temporal behavior. Here we provide direct experimental measurements of temporal width distributions of Anderson localization lasing pulses in intrinsically and extrinsically disordered coupled-microresonator arrays. We first illustrate signature exponential decays in the spatial intensity distributions of the lasing modes that quantify their localized character, and then measure the temporal width distributions of the pulsed emission over several configurations. We observe a dependence of temporal widths on the disorder strength, wherein the widths show a single-peaked, left-skewed distribution in extrinsic disorder and a dual-peaked distribution in intrinsic disorder. We propose a model based on coupled rate equations for an emitter and an Anderson cavity with a random mode structure, which gives excellent quantitative and qualitative agreement with the experimental observations. The experimental and theoretical analyses bring to the fore the temporal complexity in Anderson-localization-based lasing systems.

Using ATM over SATCOM links

NASA Technical Reports Server (NTRS)

Comparetto, Gary M.

1995-01-01

The Asynchronous Transfer Mode (ATM) protocol is studied from the standpoint of determining what limitations, if any, exist in using it over satellite links. It is concluded that, while there is nothing intrinsic about ATM that would generally preclude its use over satellite links, there are, however, several intrinsic characteristics of satellite links, as well as some satellite system configuration-specific issues, that must be taken into account.

Rigid Residue Scan Simulations Systematically Reveal Residue Entropic Roles in Protein Allostery

PubMed Central

Liu, Jin

2016-01-01

Intra-protein information is transmitted over distances via allosteric processes. This ubiquitous protein process allows for protein function changes due to ligand binding events. Understanding protein allostery is essential to understanding protein functions. In this study, allostery in the second PDZ domain (PDZ2) in the human PTP1E protein is examined as model system to advance a recently developed rigid residue scan method combining with configurational entropy calculation and principal component analysis. The contributions from individual residues to whole-protein dynamics and allostery were systematically assessed via rigid body simulations of both unbound and ligand-bound states of the protein. The entropic contributions of individual residues to whole-protein dynamics were evaluated based on covariance-based correlation analysis of all simulations. The changes of overall protein entropy when individual residues being held rigid support that the rigidity/flexibility equilibrium in protein structure is governed by the La Châtelier’s principle of chemical equilibrium. Key residues of PDZ2 allostery were identified with good agreement with NMR studies of the same protein bound to the same peptide. On the other hand, the change of entropic contribution from each residue upon perturbation revealed intrinsic differences among all the residues. The quasi-harmonic and principal component analyses of simulations without rigid residue perturbation showed a coherent allosteric mode from unbound and bound states, respectively. The projection of simulations with rigid residue perturbation onto coherent allosteric modes demonstrated the intrinsic shifting of ensemble distributions supporting the population-shift theory of protein allostery. Overall, the study presented here provides a robust and systematic approach to estimate the contribution of individual residue internal motion to overall protein dynamics and allostery. PMID:27115535

The "quantized intrinsically localized modes" of a three-dimensional lattice

NASA Astrophysics Data System (ADS)

Kanbur, Derya

In this thesis, we have investigated the lowest-energy members of the quantized intrinsically localized modes of vibration (ILMs) of the monatomic beta Fermi-Pasta-Ulam Hamiltonian in three-dimensions. We analytically find the excitation of different center of mass momenta. Using the Ladder Approximation, we find that the ILMs occur preferentially for centre of mass momenta at which the van-Hove singularities in the two-phonon density of states coalesce. When the ILMs first form they split off from the top of the two-phonon continuum. The ILMs can be categorized as having a spin of either S=2 or S=0 and have other internal quantum numbers. Moreover, the S=0 ILMs form for lower values of the interaction than the S=2 ILMs. We also focus on the temperature dependence of the ILMs. At zero temperature, the ILMs can form in three-dimensions, but only if the interaction exceeds a minimum value. As the temperature is raised, the magnitude of the minimal interaction required to stabilize the ILM is reduced. This is in a qualitative agreement with the experiments of Manley it et al., which only found the ILMs of NaI at elevated temperatures. We have also examined the ILM many-body wave functions and find that the relative coordinate part of the wave functions has symmetries associated with internal quantum numbers. According to our numerical results, the localization length increases with decreasing values of the strength of interaction. The results are presented in D.Kanbur and P.S.Riseborough, Phil. Mag. Letts, 94, 424-432 (2014) and D.Kanbur and P.S.Riseborough, Phys.Rev.B, 90, 134301 (2014). This work was supported by the US Department of Energy, Office of Basic Energy Science, Materials Science and Engineering through the award DEFG02-84ER45872.

Intrinsic brain connectivity predicts impulse control disorders in patients with Parkinson's disease.

PubMed

Tessitore, Alessandro; De Micco, Rosa; Giordano, Alfonso; di Nardo, Federica; Caiazzo, Giuseppina; Siciliano, Mattia; De Stefano, Manuela; Russo, Antonio; Esposito, Fabrizio; Tedeschi, Gioacchino

2017-12-01

Impulse control disorders can be triggered by dopamine replacement therapies in patients with PD. Using resting-state functional MRI, we investigated the intrinsic brain network connectivity at baseline in a cohort of drug-naive PD patients who successively developed impulse control disorders over a 36-month follow-up period compared with patients who did not. Baseline 3-Tesla MRI images of 30 drug-naive PD patients and 20 matched healthy controls were analyzed. The impulse control disorders' presence and severity at follow-up were assessed by the Questionnaire for Impulsive-Compulsive Disorders in Parkinson's Disease Rating Scale. Single-subject and group-level independent component analysis was used to investigate functional connectivity differences within the major resting-state networks. We also compared internetwork connectivity between patients. Finally, a multivariate Cox regression model was used to investigate baseline predictors of impulse control disorder development. At baseline, decreased connectivity in the default-mode and right central executive networks and increased connectivity in the salience network were detected in PD patients with impulse control disorders at follow-up compared with those without. Increased default-mode/central executive internetwork connectivity was significantly associated with impulse control disorders development (P < 0.05). Our findings demonstrated that abnormal brain connectivity in the three large-scale networks characterizes drug-naive PD patients who will eventually develop impulse control disorders while on dopaminergic treatment. We hypothesize that these divergent cognitive and limbic network connectivity changes could represent a potential biomarker and an additional risk factor for the emergence of impulse control disorders. © 2017 International Parkinson and Movement Disorder Society. © 2017 International Parkinson and Movement Disorder Society.

Moderating effect of intrinsic religiosity on the relationship between depression and cognitive function among community-dwelling older adults.

PubMed

Foong, Hui Foh; Hamid, Tengku Aizan; Ibrahim, Rahimah; Haron, Sharifah Azizah

2018-04-01

Research has found that depression in later life is associated with cognitive impairment. Thus, the mechanism to reduce the effect of depression on cognitive function is warranted. In this paper, we intend to examine whether intrinsic religiosity mediates the association between depression and cognitive function. The study included 2322 nationally representative community-dwelling elderly in Malaysia, randomly selected through a multi-stage proportional cluster random sampling from Peninsular Malaysia. The elderly were surveyed on socio-demographic information, cognitive function, depression and intrinsic religiosity. A four-step moderated hierarchical regression analysis was employed to test the moderating effect. Statistical analyses were performed using SPSS (version 15.0). Bivariate analyses showed that both depression and intrinsic religiosity had significant relationships with cognitive function. In addition, four-step moderated hierarchical regression analysis revealed that the intrinsic religiosity moderated the association between depression and cognitive function, after controlling for selected socio-demographic characteristics. Intrinsic religiosity might reduce the negative effect of depression on cognitive function. Professionals who are working with depressed older adults should seek ways to improve their intrinsic religiosity as one of the strategies to prevent cognitive impairment.

The Role of Intrinsic Brain Functional Connectivity in Vulnerability and Resilience to Bipolar Disorder.

PubMed

Doucet, Gaelle E; Bassett, Danielle S; Yao, Nailin; Glahn, David C; Frangou, Sophia

2017-12-01

Bipolar disorder is a heritable disorder characterized by mood dysregulation associated with brain functional dysconnectivity. Previous research has focused on the detection of risk- and disease-associated dysconnectivity in individuals with bipolar disorder and their first-degree relatives. The present study seeks to identify adaptive brain connectivity features associated with resilience, defined here as avoidance of illness or delayed illness onset in unaffected siblings of patients with bipolar disorder. Graph theoretical methods were used to examine global and regional brain network topology in head-motion-corrected resting-state functional MRI data acquired from 78 patients with bipolar disorder, 64 unaffected siblings, and 41 healthy volunteers. Global network properties were preserved in patients and their siblings while both groups showed reductions in the cohesiveness of the sensorimotor network. In the patient group, these sensorimotor network abnormalities were coupled with reduced integration of core default mode network regions in the ventromedial cortex and hippocampus. Conversely, integration of the default mode network was increased in the sibling group compared with both the patient group and the healthy volunteer group. The authors found that trait-related vulnerability to bipolar disorder was associated with reduced resting-state cohesiveness of the sensorimotor network in patients with bipolar disorder. However, integration of the default mode network emerged as a key feature differentiating disease expression and resilience between the patients and their siblings. This is indicative of the presence of neural mechanisms that may promote resilience, or at least delay illness onset.

Investigation of Kelvin wave periods during Hai-Tang typhoon using Empirical Mode Decomposition

NASA Astrophysics Data System (ADS)

Kishore, P.; Jayalakshmi, J.; Lin, Pay-Liam; Velicogna, Isabella; Sutterley, Tyler C.; Ciracì, Enrico; Mohajerani, Yara; Kumar, S. Balaji

2017-11-01

Equatorial Kelvin waves (KWs) are fundamental components of the tropical climate system. In this study, we investigate Kelvin waves (KWs) during the Hai-Tang typhoon of 2005 using Empirical Mode Decomposition (EMD) of regional precipitation, zonal and meridional winds. For the analysis, we use daily precipitation datasets from the Global Precipitation Climatology Project (GPCP) and wind datasets from the European Centre for Medium-Range Weather Forecasts (ECMWF) Interim Re-analysis (ERA-Interim). As an additional measurement, we use in-situ precipitation datasets from rain-gauges over the Taiwan region. The maximum accumulated precipitation was approximately 2400 mm during the period July 17-21, 2005 over the southwestern region of Taiwan. The spectral analysis using the wind speed at 950 hPa found in the 2nd, 3rd, and 4th intrinsic mode functions (IMFs) reveals prevailing Kelvin wave periods of ∼3 days, ∼4-6 days, and ∼6-10 days, respectively. From our analysis of precipitation datasets, we found the Kelvin waves oscillated with periods between ∼8 and 20 days.

Investigation of KDP crystal surface based on an improved bidimensional empirical mode decomposition method

NASA Astrophysics Data System (ADS)

Lu, Lei; Yan, Jihong; Chen, Wanqun; An, Shi

2018-03-01

This paper proposed a novel spatial frequency analysis method for the investigation of potassium dihydrogen phosphate (KDP) crystal surface based on an improved bidimensional empirical mode decomposition (BEMD) method. Aiming to eliminate end effects of the BEMD method and improve the intrinsic mode functions (IMFs) for the efficient identification of texture features, a denoising process was embedded in the sifting iteration of BEMD method. With removing redundant information in decomposed sub-components of KDP crystal surface, middle spatial frequencies of the cutting and feeding processes were identified. Comparative study with the power spectral density method, two-dimensional wavelet transform (2D-WT), as well as the traditional BEMD method, demonstrated that the method developed in this paper can efficiently extract texture features and reveal gradient development of KDP crystal surface. Furthermore, the proposed method was a self-adaptive data driven technique without prior knowledge, which overcame shortcomings of the 2D-WT model such as the parameters selection. Additionally, the proposed method was a promising tool for the application of online monitoring and optimal control of precision machining process.

Altered functional and effective connectivity in anticorrelated intrinsic networks in children with benign childhood epilepsy with centrotemporal spikes.

PubMed

Luo, Cheng; Yang, Fei; Deng, Jiayan; Zhang, Yaodan; Hou, Changyue; Huang, Yue; Cao, Weifang; Wang, Jianjun; Xiao, Ruhui; Zeng, Nanlin; Wang, Xiaoming; Yao, Dezhong

2016-06-01

There are 2 intrinsic networks in the human brain: the task positive network (TPN) and task negative network (alternately termed the default mode network, DMN) in which inverse correlations have been observed during resting state and event-related functional magnetic resonance imaging (fMRI). The antagonism between the 2 networks might indicate a dynamic interaction in the brain that is associated with development.To evaluate the alterations in the relations of the 2 networks in children with benign childhood epilepsy with centrotemporal spikes (BECTS), resting state fMRI was performed in 17 patients with BECTS and 17 healthy controls. The functional and effective connectivities of 29 nodes in the TPN and DMN were analyzed. Positive functional connectivity (FC) within the networks and negative FC between the 2 networks were observed in both groups.The patients exhibited increased FC within both networks, particularly in the frontoparietal nodes such as the left superior frontal cortex, and enhanced antagonism between the 2 networks, suggesting abnormal functional integration of the nodes of the 2 networks in the patients. Granger causality analysis revealed a significant difference in the degree of outflow to inflow in the left superior frontal cortex and the left ventral occipital lobe.The alterations observed in the combined functional and effective connectivity analyses might indicate an association of an abnormal ability to integrate information between the DMN and TPN and the epileptic neuropathology of BECTS and provide preliminary evidence supporting the occurrence of abnormal development in children with BECTS.

Common and distinct changes of default mode and salience network in schizophrenia and major depression.

PubMed

Shao, Junming; Meng, Chun; Tahmasian, Masoud; Brandl, Felix; Yang, Qinli; Luo, Guangchun; Luo, Cheng; Yao, Dezhong; Gao, Lianli; Riedl, Valentin; Wohlschläger, Afra; Sorg, Christian

2018-02-19

Brain imaging reveals schizophrenia as a disorder of macroscopic brain networks. In particular, default mode and salience network (DMN, SN) show highly consistent alterations in both interacting brain activity and underlying brain structure. However, the same networks are also altered in major depression. This overlap in network alterations induces the question whether DMN and SN changes are different across both disorders, potentially indicating distinct underlying pathophysiological mechanisms. To address this question, we acquired T1-weighted, diffusion-weighted, and resting-state functional MRI in patients with schizophrenia, patients with major depression, and healthy controls. We measured regional gray matter volume, inter-regional structural and intrinsic functional connectivity of DMN and SN, and compared these measures across groups by generalized Wilcoxon rank tests, while controlling for symptoms and medication. When comparing patients with controls, we found in each patient group SN volume loss, impaired DMN structural connectivity, and aberrant DMN and SN functional connectivity. When comparing patient groups, SN gray matter volume loss and DMN structural connectivity reduction did not differ between groups, but in schizophrenic patients, functional hyperconnectivity between DMN and SN was less in comparison to depressed patients. Results provide evidence for distinct functional hyperconnectivity between DMN and SN in schizophrenia and major depression, while structural changes in DMN and SN were similar. Distinct hyperconnectivity suggests different pathophysiological mechanism underlying aberrant DMN-SN interactions in schizophrenia and depression.

Sex differences in normal age trajectories of functional brain networks.

PubMed

Scheinost, Dustin; Finn, Emily S; Tokoglu, Fuyuze; Shen, Xilin; Papademetris, Xenophon; Hampson, Michelle; Constable, R Todd

2015-04-01

Resting-state functional magnetic resonance image (rs-fMRI) is increasingly used to study functional brain networks. Nevertheless, variability in these networks due to factors such as sex and aging is not fully understood. This study explored sex differences in normal age trajectories of resting-state networks (RSNs) using a novel voxel-wise measure of functional connectivity, the intrinsic connectivity distribution (ICD). Males and females showed differential patterns of changing connectivity in large-scale RSNs during normal aging from early adulthood to late middle-age. In some networks, such as the default-mode network, males and females both showed decreases in connectivity with age, albeit at different rates. In other networks, such as the fronto-parietal network, males and females showed divergent connectivity trajectories with age. Main effects of sex and age were found in many of the same regions showing sex-related differences in aging. Finally, these sex differences in aging trajectories were robust to choice of preprocessing strategy, such as global signal regression. Our findings resolve some discrepancies in the literature, especially with respect to the trajectory of connectivity in the default mode, which can be explained by our observed interactions between sex and aging. Overall, results indicate that RSNs show different aging trajectories for males and females. Characterizing effects of sex and age on RSNs are critical first steps in understanding the functional organization of the human brain. © 2014 Wiley Periodicals, Inc.

Altered default mode, fronto-parietal and salience networks in adolescents with Internet addiction.

PubMed

Wang, Lubin; Shen, Hui; Lei, Yu; Zeng, Ling-Li; Cao, Fenglin; Su, Linyan; Yang, Zheng; Yao, Shuqiao; Hu, Dewen

2017-07-01

Internet addiction (IA) is a condition characterized by loss of control over Internet use, leading to a variety of negative psychosocial consequences. Recent neuroimaging studies have begun to identify IA-related changes in specific brain regions and connections. However, whether and how the interactions within and between the large-scale brain networks are disrupted in individuals with IA remain largely unexplored. Using group independent component analysis, we extracted five intrinsic connectivity networks (ICNs) from the resting-state fMRI data of 26 adolescents with IA and 43 controls, including the anterior and posterior default mode network (DMN), left and right fronto-parietal network (FPN), and salience network (SN). We then examined the possible group differences in the functional connectivity within each ICN and between the ICNs. We found that, compared with controls, IA subjects showed: (1) reduced inter-hemispheric functional connectivity of the right FPN, whereas increased intra-hemispheric functional connectivity of the left FPN; (2) reduced functional connectivity in the dorsal medial prefrontal cortex (mPFC) of the anterior DMN; (3) reduced functional connectivity between the SN and anterior DMN. Our findings suggest that IA is associated with imbalanced interactions among the DMN, FPN and SN, which may serve as system-level neural underpinnings for the uncontrollable Internet-using behaviors. Copyright © 2017 Elsevier Ltd. All rights reserved.

The Fourier decomposition method for nonlinear and non-stationary time series analysis.

PubMed

Singh, Pushpendra; Joshi, Shiv Dutt; Patney, Rakesh Kumar; Saha, Kaushik

2017-03-01

for many decades, there has been a general perception in the literature that Fourier methods are not suitable for the analysis of nonlinear and non-stationary data. In this paper, we propose a novel and adaptive Fourier decomposition method (FDM), based on the Fourier theory, and demonstrate its efficacy for the analysis of nonlinear and non-stationary time series. The proposed FDM decomposes any data into a small number of 'Fourier intrinsic band functions' (FIBFs). The FDM presents a generalized Fourier expansion with variable amplitudes and variable frequencies of a time series by the Fourier method itself. We propose an idea of zero-phase filter bank-based multivariate FDM (MFDM), for the analysis of multivariate nonlinear and non-stationary time series, using the FDM. We also present an algorithm to obtain cut-off frequencies for MFDM. The proposed MFDM generates a finite number of band-limited multivariate FIBFs (MFIBFs). The MFDM preserves some intrinsic physical properties of the multivariate data, such as scale alignment, trend and instantaneous frequency. The proposed methods provide a time-frequency-energy (TFE) distribution that reveals the intrinsic structure of a data. Numerical computations and simulations have been carried out and comparison is made with the empirical mode decomposition algorithms.

Youthful Brains in Older Adults: Preserved Neuroanatomy in the Default Mode and Salience Networks Contributes to Youthful Memory in Superaging.

PubMed

Sun, Felicia W; Stepanovic, Michael R; Andreano, Joseph; Barrett, Lisa Feldman; Touroutoglou, Alexandra; Dickerson, Bradford C

2016-09-14

Decline in cognitive skills, especially in memory, is often viewed as part of "normal" aging. Yet some individuals "age better" than others. Building on prior research showing that cortical thickness in one brain region, the anterior midcingulate cortex, is preserved in older adults with memory performance abilities equal to or better than those of people 20-30 years younger (i.e., "superagers"), we examined the structural integrity of two large-scale intrinsic brain networks in superaging: the default mode network, typically engaged during memory encoding and retrieval tasks, and the salience network, typically engaged during attention, motivation, and executive function tasks. We predicted that superagers would have preserved cortical thickness in critical nodes in these networks. We defined superagers (60-80 years old) based on their performance compared to young adults (18-32 years old) on the California Verbal Learning Test Long Delay Free Recall test. We found regions within the networks of interest where the cerebral cortex of superagers was thicker than that of typical older adults, and where superagers were anatomically indistinguishable from young adults; hippocampal volume was also preserved in superagers. Within the full group of older adults, thickness of a number of regions, including the anterior temporal cortex, rostral medial prefrontal cortex, and anterior midcingulate cortex, correlated with memory performance, as did the volume of the hippocampus. These results indicate older adults with youthful memory abilities have youthful brain regions in key paralimbic and limbic nodes of the default mode and salience networks that support attentional, executive, and mnemonic processes subserving memory function. Memory performance typically declines with age, as does cortical structural integrity, yet some older adults maintain youthful memory. We tested the hypothesis that superagers (older individuals with youthful memory performance) would exhibit preserved neuroanatomy in key brain networks subserving memory. We found that superagers not only perform similarly to young adults on memory testing, they also do not show the typical patterns of brain atrophy in certain regions. These regions are contained largely within two major intrinsic brain networks: the default mode network, implicated in memory encoding, storage, and retrieval, and the salience network, associated with attention and executive processes involved in encoding and retrieval. Preserved neuroanatomical integrity in these networks is associated with better memory performance among older adults. Copyright © 2016 Sun, Stepanovic et al.

Brain intrinsic network connectivity in individuals with frequent tanning behavior.

PubMed

Ketcherside, Ariel; Filbey, Francesca M; Aubert, Pamela M; Seibyl, John P; Price, Julianne L; Adinoff, Bryon

2018-05-01

Emergent studies suggest a bidirectional relationship between brain functioning and the skin. This neurocutaneous connection may be responsible for the reward response to tanning and, thus, may contribute to excessive tanning behavior. To date, however, this association has not yet been examined. To explore whether intrinsic brain functional connectivity within the default mode network (DMN) is related to indoor tanning behavior. Resting state functional connectivity (rsFC) was obtained in twenty adults (16 females) with a history of indoor tanning. Using a seed-based [(posterior cingulate cortex (PCC)] approach, the relationship between tanning severity and FC strength was assessed. Tanning severity was measured with symptom count from the Structured Clinical Interview for Tanning Abuse and Dependence (SITAD) and tanning intensity (lifetime indoor tanning episodes/years tanning). rsFC strength between the PCC and other DMN regions (left globus pallidus, left medial frontal gyrus, left superior frontal gyrus) is positively correlated with tanning symptom count. rsFC strength between the PCC and salience network regions (right anterior cingulate cortex, left inferior parietal lobe, left inferior temporal gyrus) is correlated with tanning intensity. Greater connectivity between tanning severity and DMN and salience network connectivity suggests that heightened self-awareness of salient stimuli may be a mechanism that underlies frequent tanning behavior. These findings add to the growing evidence of brain-skin connection and reflect dysregulation in the reward processing networks in those with frequent tanning.

Using Spatial Multiple Regression to Identify Intrinsic Connectivity Networks Involved in Working Memory Performance

PubMed Central

Gordon, Evan M.; Stollstorff, Melanie; Vaidya, Chandan J.

2012-01-01

Many researchers have noted that the functional architecture of the human brain is relatively invariant during task performance and the resting state. Indeed, intrinsic connectivity networks (ICNs) revealed by resting-state functional connectivity analyses are spatially similar to regions activated during cognitive tasks. This suggests that patterns of task-related activation in individual subjects may result from the engagement of one or more of these ICNs; however, this has not been tested. We used a novel analysis, spatial multiple regression, to test whether the patterns of activation during an N-back working memory task could be well described by a linear combination of ICNs delineated using Independent Components Analysis at rest. We found that across subjects, the cingulo-opercular Set Maintenance ICN, as well as right and left Frontoparietal Control ICNs, were reliably activated during working memory, while Default Mode and Visual ICNs were reliably deactivated. Further, involvement of Set Maintenance, Frontoparietal Control, and Dorsal Attention ICNs was sensitive to varying working memory load. Finally, the degree of left Frontoparietal Control network activation predicted response speed, while activation in both left Frontoparietal Control and Dorsal Attention networks predicted task accuracy. These results suggest that a close relationship between resting-state networks and task-evoked activation is functionally relevant for behavior, and that spatial multiple regression analysis is a suitable method for revealing that relationship. PMID:21761505

Intrinsic Connectivity Networks in post-traumatic stress disorder during sub- and supraliminal processing of threat-related stimuli.

PubMed

Rabellino, D; Tursich, M; Frewen, P A; Daniels, J K; Densmore, M; Théberge, J; Lanius, R A

2015-11-01

To investigate the functional connectivity of large-scale intrinsic connectivity networks (ICNs) in post-traumatic stress disorder (PTSD) during subliminal and supraliminal presentation of threat-related stimuli. Group independent component analysis was utilized to study functional connectivity within the ICNs most correlated with the Default-mode Network (DMN), Salience Network (SN), and Central Executive Network (CEN) in PTSD participants (n = 26) as compared to healthy controls (n = 20) during sub- and supraliminal processing of threat-related stimuli. Comparing patients with PTSD with healthy participants, prefrontal and anterior cingulate cortex involved in top-down regulation showed increased integration during subliminal threat processing within the CEN and SN and during supraliminal threat processing within the DMN. The right amygdala showed increased connectivity with the DMN during subliminal processing in PTSD as compared to controls. Brain regions associated with self-awareness and consciousness exhibited decreased connectivity during subliminal threat processing in PTSD as compared to controls: the claustrum within the SN and the precuneus within the DMN. Key nodes of the ICNs showed altered functional connectivity in PTSD as compared to controls, and differential results characterized sub- and supraliminal processing of threat-related stimuli. These findings enhance our understanding of ICNs underlying PTSD at different levels of conscious threat perception. © 2015 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

Overview of recent physics results from MAST

NASA Astrophysics Data System (ADS)

Kirk, A.; Adamek, J.; Akers, R. J.; Allan, S.; Appel, L.; Arese Lucini, F.; Barnes, M.; Barrett, T.; Ben Ayed, N.; Boeglin, W.; Bradley, J.; Browning, P. K.; Brunner, J.; Cahyna, P.; Cardnell, S.; Carr, M.; Casson, F.; Cecconello, M.; Challis, C.; Chapman, I. T.; Chapman, S.; Chorley, J.; Conroy, S.; Conway, N.; Cooper, W. A.; Cox, M.; Crocker, N.; Crowley, B.; Cunningham, G.; Danilov, A.; Darrow, D.; Dendy, R.; Dickinson, D.; Dorland, W.; Dudson, B.; Dunai, D.; Easy, L.; Elmore, S.; Evans, M.; Farley, T.; Fedorczak, N.; Field, A.; Fishpool, G.; Fitzgerald, I.; Fox, M.; Freethy, S.; Garzotti, L.; Ghim, Y. C.; Gi, K.; Gibson, K.; Gorelenkova, M.; Gracias, W.; Gurl, C.; Guttenfelder, W.; Ham, C.; Harrison, J.; Harting, D.; Havlickova, E.; Hawkes, N.; Hender, T.; Henderson, S.; Highcock, E.; Hillesheim, J.; Hnat, B.; Horacek, J.; Howard, J.; Howell, D.; Huang, B.; Imada, K.; Inomoto, M.; Imazawa, R.; Jones, O.; Kadowaki, K.; Kaye, S.; Keeling, D.; Klimek, I.; Kocan, M.; Kogan, L.; Komm, M.; Lai, W.; Leddy, J.; Leggate, H.; Hollocombe, J.; Lipschultz, B.; Lisgo, S.; Liu, Y. Q.; Lloyd, B.; Lomanowski, B.; Lukin, V.; Lupelli, I.; Maddison, G.; Madsen, J.; Mailloux, J.; Martin, R.; McArdle, G.; McClements, K.; McMillan, B.; Meakins, A.; Meyer, H.; Michael, C.; Militello, F.; Milnes, J.; Morris, A. W.; Motojima, G.; Muir, D.; Naylor, G.; Nielsen, A.; O'Brien, M.; O'Gorman, T.; O'Mullane, M.; Olsen, J.; Omotani, J.; Ono, Y.; Pamela, S.; Pangione, L.; Parra, F.; Patel, A.; Peebles, W.; Perez, R.; Pinches, S.; Piron, L.; Price, M.; Reinke, M.; Ricci, P.; Riva, F.; Roach, C.; Romanelli, M.; Ryan, D.; Saarelma, S.; Saveliev, A.; Scannell, R.; Schekochihin, A.; Sharapov, S.; Sharples, R.; Shevchenko, V.; Shinohara, K.; Silburn, S.; Simpson, J.; Stanier, A.; Storrs, J.; Summers, H.; Takase, Y.; Tamain, P.; Tanabe, H.; Tanaka, H.; Tani, K.; Taylor, D.; Thomas, D.; Thomas-Davies, N.; Thornton, A.; Turnyanskiy, M.; Valovic, M.; Vann, R.; Van Wyk, F.; Walkden, N.; Watanabe, T.; Wilson, H.; Wischmeier, M.; Yamada, T.; Young, J.; Zoletnik, S.; the MAST Team; the EUROfusion MST1 Team

2017-10-01

New results from MAST are presented that focus on validating models in order to extrapolate to future devices. Measurements during start-up experiments have shown how the bulk ion temperature rise scales with the square of the reconnecting field. During the current ramp-up, models are not able to correctly predict the current diffusion. Experiments have been performed looking at edge and core turbulence. At the edge, detailed studies have revealed how filament characteristics are responsible for determining the near and far scrape off layer density profiles. In the core the intrinsic rotation and electron scale turbulence have been measured. The role that the fast ion gradient has on redistributing fast ions through fishbone modes has led to a redesign of the neutral beam injector on MAST Upgrade. In H-mode the turbulence at the pedestal top has been shown to be consistent with being due to electron temperature gradient modes. A reconnection process appears to occur during edge localized modes (ELMs) and the number of filaments released determines the power profile at the divertor. Resonant magnetic perturbations can mitigate ELMs provided the edge peeling response is maximised and the core kink response minimised. The mitigation of intrinsic error fields with toroidal mode number n  >  1 has been shown to be important for plasma performance.

Statistical link between external climate forcings and modes of ocean variability

NASA Astrophysics Data System (ADS)

Malik, Abdul; Brönnimann, Stefan; Perona, Paolo

2017-07-01

In this study we investigate statistical link between external climate forcings and modes of ocean variability on inter-annual (3-year) to centennial (100-year) timescales using de-trended semi-partial-cross-correlation analysis technique. To investigate this link we employ observations (AD 1854-1999), climate proxies (AD 1600-1999), and coupled Atmosphere-Ocean-Chemistry Climate Model simulations with SOCOL-MPIOM (AD 1600-1999). We find robust statistical evidence that Atlantic multi-decadal oscillation (AMO) has intrinsic positive correlation with solar activity in all datasets employed. The strength of the relationship between AMO and solar activity is modulated by volcanic eruptions and complex interaction among modes of ocean variability. The observational dataset reveals that El Niño southern oscillation (ENSO) has statistically significant negative intrinsic correlation with solar activity on decadal to multi-decadal timescales (16-27-year) whereas there is no evidence of a link on a typical ENSO timescale (2-7-year). In the observational dataset, the volcanic eruptions do not have a link with AMO on a typical AMO timescale (55-80-year) however the long-term datasets (proxies and SOCOL-MPIOM output) show that volcanic eruptions have intrinsic negative correlation with AMO on inter-annual to multi-decadal timescales. The Pacific decadal oscillation has no link with solar activity, however, it has positive intrinsic correlation with volcanic eruptions on multi-decadal timescales (47-54-year) in reconstruction and decadal to multi-decadal timescales (16-32-year) in climate model simulations. We also find evidence of a link between volcanic eruptions and ENSO, however, the sign of relationship is not consistent between observations/proxies and climate model simulations.

Weibel instability for a streaming electron, counterstreaming e-e, and e-p plasmas with intrinsic temperature anisotropy

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

Ghorbanalilu, M.; Physics Department, Azarbaijan Shahid Madani University, Tabriz; Sadegzadeh, S.

2014-05-15

The existence of Weibel instability for a streaming electron, counterstreaming electron-electron (e-e), and electron-positron (e-p) plasmas with intrinsic temperature anisotropy is investigated. The temperature anisotropy is included in the directions perpendicular and parallel to the streaming direction. It is shown that the beam mean speed changes the instability mode, for a streaming electron beam, from the classic Weibel to the Weibel-like mode. The analytical and numerical solutions approved that Weibel-like modes are excited for both counterstreaming e-e and e-p plasmas. The growth rates of the instabilities in e-e and e-p plasmas are compared. The growth rate is larger for e-pmore » plasmas if the thermal anisotropy is small and the opposite is true for large thermal anisotropies. The analytical and numerical solutions are in good agreement only in the small parallel temperature and wave number limits, when the instability growth rate increases linearly with normalized wave number kc∕ω{sub p}.« less

Fabrication strategies, sensing modes and analytical applications of ratiometric electrochemical biosensors.

PubMed

Jin, Hui; Gui, Rijun; Yu, Jianbo; Lv, Wei; Wang, Zonghua

2017-05-15

Previously developed electrochemical biosensors with single-electric signal output are probably affected by intrinsic and extrinsic factors. In contrast, the ratiometric electrochemical biosensors (RECBSs) with dual-electric signal outputs have an intrinsic built-in correction to the effects from system or background electric signals, and therefore exhibit a significant potential to improve the accuracy and sensitivity in electrochemical sensing applications. In this review, we systematically summarize the fabrication strategies, sensing modes and analytical applications of RECBSs. First, the different fabrication strategies of RECBSs were introduced, referring to the analytes-induced single- and dual-dependent electrochemical signal strategies for RECBSs. Second, the different sensing modes of RECBSs were illustrated, such as differential pulse voltammetry, square wave voltammetry, cyclic voltammetry, alternating current voltammetry, electrochemiluminescence, and so forth. Third, the analytical applications of RECBSs were discussed based on the types of target analytes. Finally, the forthcoming development and future prospects in the research field of RECBSs were also highlighted. Copyright © 2017 Elsevier B.V. All rights reserved.

Functional Advantages of Conserved Intrinsic Disorder in RNA-Binding Proteins.

PubMed

Varadi, Mihaly; Zsolyomi, Fruzsina; Guharoy, Mainak; Tompa, Peter

2015-01-01

Proteins form large macromolecular assemblies with RNA that govern essential molecular processes. RNA-binding proteins have often been associated with conformational flexibility, yet the extent and functional implications of their intrinsic disorder have never been fully assessed. Here, through large-scale analysis of comprehensive protein sequence and structure datasets we demonstrate the prevalence of intrinsic structural disorder in RNA-binding proteins and domains. We addressed their functionality through a quantitative description of the evolutionary conservation of disordered segments involved in binding, and investigated the structural implications of flexibility in terms of conformational stability and interface formation. We conclude that the functional role of intrinsically disordered protein segments in RNA-binding is two-fold: first, these regions establish extended, conserved electrostatic interfaces with RNAs via induced fit. Second, conformational flexibility enables them to target different RNA partners, providing multi-functionality, while also ensuring specificity. These findings emphasize the functional importance of intrinsically disordered regions in RNA-binding proteins.

Correcting for Blood Arrival Time in Global Mean Regression Enhances Functional Connectivity Analysis of Resting State fMRI-BOLD Signals.

PubMed

Erdoğan, Sinem B; Tong, Yunjie; Hocke, Lia M; Lindsey, Kimberly P; deB Frederick, Blaise

2016-01-01

Resting state functional connectivity analysis is a widely used method for mapping intrinsic functional organization of the brain. Global signal regression (GSR) is commonly employed for removing systemic global variance from resting state BOLD-fMRI data; however, recent studies have demonstrated that GSR may introduce spurious negative correlations within and between functional networks, calling into question the meaning of anticorrelations reported between some networks. In the present study, we propose that global signal from resting state fMRI is composed primarily of systemic low frequency oscillations (sLFOs) that propagate with cerebral blood circulation throughout the brain. We introduce a novel systemic noise removal strategy for resting state fMRI data, "dynamic global signal regression" (dGSR), which applies a voxel-specific optimal time delay to the global signal prior to regression from voxel-wise time series. We test our hypothesis on two functional systems that are suggested to be intrinsically organized into anticorrelated networks: the default mode network (DMN) and task positive network (TPN). We evaluate the efficacy of dGSR and compare its performance with the conventional "static" global regression (sGSR) method in terms of (i) explaining systemic variance in the data and (ii) enhancing specificity and sensitivity of functional connectivity measures. dGSR increases the amount of BOLD signal variance being modeled and removed relative to sGSR while reducing spurious negative correlations introduced in reference regions by sGSR, and attenuating inflated positive connectivity measures. We conclude that incorporating time delay information for sLFOs into global noise removal strategies is of crucial importance for optimal noise removal from resting state functional connectivity maps.

A decision-making framework for the grouping and testing of nanomaterials (DF4nanoGrouping).

PubMed

Arts, Josje H E; Hadi, Mackenzie; Irfan, Muhammad-Adeel; Keene, Athena M; Kreiling, Reinhard; Lyon, Delina; Maier, Monika; Michel, Karin; Petry, Thomas; Sauer, Ursula G; Warheit, David; Wiench, Karin; Wohlleben, Wendel; Landsiedel, Robert

2015-03-15

The European Centre for Ecotoxicology and Toxicology of Chemicals (ECETOC) 'Nano Task Force' proposes a Decision-making framework for the grouping and testing of nanomaterials (DF4nanoGrouping) that consists of 3 tiers to assign nanomaterials to 4 main groups, to perform sub-grouping within the main groups and to determine and refine specific information needs. The DF4nanoGrouping covers all relevant aspects of a nanomaterial's life cycle and biological pathways, i.e. intrinsic material and system-dependent properties, biopersistence, uptake and biodistribution, cellular and apical toxic effects. Use (including manufacture), release and route of exposure are applied as 'qualifiers' within the DF4nanoGrouping to determine if, e.g. nanomaterials cannot be released from a product matrix, which may justify the waiving of testing. The four main groups encompass (1) soluble nanomaterials, (2) biopersistent high aspect ratio nanomaterials, (3) passive nanomaterials, and (4) active nanomaterials. The DF4nanoGrouping aims to group nanomaterials by their specific mode-of-action that results in an apical toxic effect. This is eventually directed by a nanomaterial's intrinsic properties. However, since the exact correlation of intrinsic material properties and apical toxic effect is not yet established, the DF4nanoGrouping uses the 'functionality' of nanomaterials for grouping rather than relying on intrinsic material properties alone. Such functionalities include system-dependent material properties (such as dissolution rate in biologically relevant media), bio-physical interactions, in vitro effects and release and exposure. The DF4nanoGrouping is a hazard and risk assessment tool that applies modern toxicology and contributes to the sustainable development of nanotechnological products. It ensures that no studies are performed that do not provide crucial data and therefore saves animals and resources. Copyright © 2015 The Authors. Published by Elsevier Inc. All rights reserved.

Feature Extraction and Classification of EHG between Pregnancy and Labour Group Using Hilbert-Huang Transform and Extreme Learning Machine.

PubMed

Chen, Lili; Hao, Yaru

2017-01-01

Preterm birth (PTB) is the leading cause of perinatal mortality and long-term morbidity, which results in significant health and economic problems. The early detection of PTB has great significance for its prevention. The electrohysterogram (EHG) related to uterine contraction is a noninvasive, real-time, and automatic novel technology which can be used to detect, diagnose, or predict PTB. This paper presents a method for feature extraction and classification of EHG between pregnancy and labour group, based on Hilbert-Huang transform (HHT) and extreme learning machine (ELM). For each sample, each channel was decomposed into a set of intrinsic mode functions (IMFs) using empirical mode decomposition (EMD). Then, the Hilbert transform was applied to IMF to obtain analytic function. The maximum amplitude of analytic function was extracted as feature. The identification model was constructed based on ELM. Experimental results reveal that the best classification performance of the proposed method can reach an accuracy of 88.00%, a sensitivity of 91.30%, and a specificity of 85.19%. The area under receiver operating characteristic (ROC) curve is 0.88. Finally, experimental results indicate that the method developed in this work could be effective in the classification of EHG between pregnancy and labour group.

Systematic error of the Gaia DR1 TGAS parallaxes from data for the red giant clump

NASA Astrophysics Data System (ADS)

Gontcharov, G. A.

2017-08-01

Based on the Gaia DR1 TGAS parallaxes and photometry from the Tycho-2, Gaia, 2MASS, andWISE catalogues, we have produced a sample of 100 000 clump red giants within 800 pc of the Sun. The systematic variations of the mode of their absolute magnitude as a function of the distance, magnitude, and other parameters have been analyzed. We show that these variations reach 0.7 mag and cannot be explained by variations in the interstellar extinction or intrinsic properties of stars and by selection. The only explanation seems to be a systematic error of the Gaia DR1 TGAS parallax dependent on the square of the observed distance in kpc: 0.18 R 2 mas. Allowance for this error reduces significantly the systematic dependences of the absolute magnitude mode on all parameters. This error reaches 0.1 mas within 800 pc of the Sun and allows an upper limit for the accuracy of the TGAS parallaxes to be estimated as 0.2 mas. A careful allowance for such errors is needed to use clump red giants as "standard candles." This eliminates all discrepancies between the theoretical and empirical estimates of the characteristics of these stars and allows us to obtain the first estimates of the modes of their absolute magnitudes from the Gaia parallaxes: mode( M H ) = -1.49 m ± 0.04 m , mode( M Ks ) = -1.63 m ± 0.03 m , mode( M W1) = -1.67 m ± 0.05 m mode( M W2) = -1.67 m ± 0.05 m , mode( M W3) = -1.66 m ± 0.02 m , mode( M W4) = -1.73 m ± 0.03 m , as well as the corresponding estimates of their de-reddened colors.

Partial differential equation transform — Variational formulation and Fourier analysis

PubMed Central

Wang, Yang; Wei, Guo-Wei; Yang, Siyang

2011-01-01

Nonlinear partial differential equation (PDE) models are established approaches for image/signal processing, data analysis and surface construction. Most previous geometric PDEs are utilized as low-pass filters which give rise to image trend information. In an earlier work, we introduced mode decomposition evolution equations (MoDEEs), which behave like high-pass filters and are able to systematically provide intrinsic mode functions (IMFs) of signals and images. Due to their tunable time-frequency localization and perfect reconstruction, the operation of MoDEEs is called a PDE transform. By appropriate selection of PDE transform parameters, we can tune IMFs into trends, edges, textures, noise etc., which can be further utilized in the secondary processing for various purposes. This work introduces the variational formulation, performs the Fourier analysis, and conducts biomedical and biological applications of the proposed PDE transform. The variational formulation offers an algorithm to incorporate two image functions and two sets of low-pass PDE operators in the total energy functional. Two low-pass PDE operators have different signs, leading to energy disparity, while a coupling term, acting as a relative fidelity of two image functions, is introduced to reduce the disparity of two energy components. We construct variational PDE transforms by using Euler-Lagrange equation and artificial time propagation. Fourier analysis of a simplified PDE transform is presented to shed light on the filter properties of high order PDE transforms. Such an analysis also offers insight on the parameter selection of the PDE transform. The proposed PDE transform algorithm is validated by numerous benchmark tests. In one selected challenging example, we illustrate the ability of PDE transform to separate two adjacent frequencies of sin(x) and sin(1.1x). Such an ability is due to PDE transform’s controllable frequency localization obtained by adjusting the order of PDEs. The frequency selection is achieved either by diffusion coefficients or by propagation time. Finally, we explore a large number of practical applications to further demonstrate the utility of proposed PDE transform. PMID:22207904

Gaussian intrinsic entanglement for states with partial minimum uncertainty

NASA Astrophysics Data System (ADS)

Mišta, Ladislav; Baksová, Klára

2018-01-01

We develop a recently proposed theory of a quantifier of bipartite Gaussian entanglement called Gaussian intrinsic entanglement (GIE) [L. Mišta, Jr. and R. Tatham, Phys. Rev. Lett. 117, 240505 (2016), 10.1103/PhysRevLett.117.240505]. Gaussian intrinsic entanglement provides a compromise between computable and physically meaningful entanglement quantifiers and so far it has been calculated for two-mode Gaussian states including all symmetric partial minimum-uncertainty states, weakly mixed asymmetric squeezed thermal states with partial minimum uncertainty, and weakly mixed symmetric squeezed thermal states. We improve the method of derivation of GIE and show that all previously derived formulas for GIE of weakly mixed states in fact hold for states with higher mixedness. In addition, we derive analytical formulas for GIE for several other classes of two-mode Gaussian states with partial minimum uncertainty. Finally, we show that, like for all previously known states, also for all currently considered states the GIE is equal to Gaussian Rényi-2 entanglement of formation. This finding strengthens a conjecture about the equivalence of GIE and Gaussian Rényi-2 entanglement of formation for all bipartite Gaussian states.

Tensor Minkowski Functionals: first application to the CMB

NASA Astrophysics Data System (ADS)

Ganesan, Vidhya; Chingangbam, Pravabati

2017-06-01

Tensor Minkowski Functionals (TMFs) are tensor generalizations of the usual Minkowski Functionals which are scalar quantities. We introduce them here for use in cosmological analysis, in particular to analyze the Cosmic Microwave Background (CMB) radiation. They encapsulate information about the shapes of structures and the orientation of distributions of structures. We focus on one of the TMFs, namely W21,1, which is the (1,1) rank tensor generalization of the genus. The ratio of the eigenvalues of the average of W21,1 over all structures, α, encodes the net orientation of the structures; and the average of the ratios of the eigenvalues of W21,1 for each structure, β, encodes the net intrinsic anisotropy of the structures. We have developed a code that computes W21,1, and from it α and β, for a set of structures on the 2-dimensional Euclidean plane. We use it to compute α and β as functions of chosen threshold levels for simulated Gaussian and isotropic CMB temperature and E mode fields. We obtain the value of α to be one for both temperature and E mode, which means that we recover the statistical isotropy of density fluctuations that we input in the simulations. We find that the standard ΛCDM model predicts a charateristic shape of β for temperature and E mode as a function of the threshold, and the average over thresholds is β~ 0.62 for temperature and β~ 0.63 for E mode. Accurate measurements of α and β can be used to test the standard model of cosmology and to search for deviations from it. For this purpose we compute α and β for temperature and E mode data of various data sets from PLANCK mission. We compare the values measured from observed data with those obtained from simulations to which instrument beam and noise characteristics of the 44GHz frequency channel have been added (which are provided as part of the PLANCK data release). We find very good agreement of β and α between all PLANCK temperature data sets with ΛCDM expectations. E mode data show good agreement for β but α for all data sets deviate from ΛCDM predictions higher than 3-σ. It is most likely that the deviations are probing the anisotropy of the noise field and beam characteristics of the detector rather than the true E mode signal since for 44GHz the signal-to-noise ratio is well below one. This will be further investigated after the full PLANCK data becomes publicly available.

Numerical simulations of fast-axis instability of vector solitons in mode-locked fiber lasers.

PubMed

Du, Yueqing; Shu, Xuewen; Cheng, Peiyun

2017-01-23

We demonstrate the fast-axis instability in mode-locked fiber lasers numerically for the first time. We find that the energy of the fast mode will be transferred to the slow mode when the strong pump strength makes the soliton period short. A nearly linearly polarized vector soliton along the slow-axis could be generated under certain cavity parameters. The final polarization of the vector soliton is related to the initial polarization of the seed pulse. Two regimes of energy exchanging between the slow mode and the fast mode are explored and the direction of the energy flow between two modes depends on the phase difference. The dip-type sidebands are found to be intrinsic characteristics of the mode-locked fiber lasers under high pulse energy.

Seizure classification in EEG signals utilizing Hilbert-Huang transform

PubMed Central

2011-01-01

Background Classification method capable of recognizing abnormal activities of the brain functionality are either brain imaging or brain signal analysis. The abnormal activity of interest in this study is characterized by a disturbance caused by changes in neuronal electrochemical activity that results in abnormal synchronous discharges. The method aims at helping physicians discriminate between healthy and seizure electroencephalographic (EEG) signals. Method Discrimination in this work is achieved by analyzing EEG signals obtained from freely accessible databases. MATLAB has been used to implement and test the proposed classification algorithm. The analysis in question presents a classification of normal and ictal activities using a feature relied on Hilbert-Huang Transform. Through this method, information related to the intrinsic functions contained in the EEG signal has been extracted to track the local amplitude and the frequency of the signal. Based on this local information, weighted frequencies are calculated and a comparison between ictal and seizure-free determinant intrinsic functions is then performed. Methods of comparison used are the t-test and the Euclidean clustering. Results The t-test results in a P-value < 0.02 and the clustering leads to accurate (94%) and specific (96%) results. The proposed method is also contrasted against the Multivariate Empirical Mode Decomposition that reaches 80% accuracy. Comparison results strengthen the contribution of this paper not only from the accuracy point of view but also with respect to its fast response and ease to use. Conclusion An original tool for EEG signal processing giving physicians the possibility to diagnose brain functionality abnormalities is presented in this paper. The proposed system bears the potential of providing several credible benefits such as fast diagnosis, high accuracy, good sensitivity and specificity, time saving and user friendly. Furthermore, the classification of mode mixing can be achieved using the extracted instantaneous information of every IMF, but it would be most likely a hard task if only the average value is used. Extra benefits of this proposed system include low cost, and ease of interface. All of that indicate the usefulness of the tool and its use as an efficient diagnostic tool. PMID:21609459

Seizure classification in EEG signals utilizing Hilbert-Huang transform.

PubMed

Oweis, Rami J; Abdulhay, Enas W

2011-05-24

Classification method capable of recognizing abnormal activities of the brain functionality are either brain imaging or brain signal analysis. The abnormal activity of interest in this study is characterized by a disturbance caused by changes in neuronal electrochemical activity that results in abnormal synchronous discharges. The method aims at helping physicians discriminate between healthy and seizure electroencephalographic (EEG) signals. Discrimination in this work is achieved by analyzing EEG signals obtained from freely accessible databases. MATLAB has been used to implement and test the proposed classification algorithm. The analysis in question presents a classification of normal and ictal activities using a feature relied on Hilbert-Huang Transform. Through this method, information related to the intrinsic functions contained in the EEG signal has been extracted to track the local amplitude and the frequency of the signal. Based on this local information, weighted frequencies are calculated and a comparison between ictal and seizure-free determinant intrinsic functions is then performed. Methods of comparison used are the t-test and the Euclidean clustering. The t-test results in a P-value < 0.02 and the clustering leads to accurate (94%) and specific (96%) results. The proposed method is also contrasted against the Multivariate Empirical Mode Decomposition that reaches 80% accuracy. Comparison results strengthen the contribution of this paper not only from the accuracy point of view but also with respect to its fast response and ease to use. An original tool for EEG signal processing giving physicians the possibility to diagnose brain functionality abnormalities is presented in this paper. The proposed system bears the potential of providing several credible benefits such as fast diagnosis, high accuracy, good sensitivity and specificity, time saving and user friendly. Furthermore, the classification of mode mixing can be achieved using the extracted instantaneous information of every IMF, but it would be most likely a hard task if only the average value is used. Extra benefits of this proposed system include low cost, and ease of interface. All of that indicate the usefulness of the tool and its use as an efficient diagnostic tool.

Dimensionless size scaling of intrinsic rotation in DIII-D

DOE PAGES

deGrassie, John S.; Solomon, Wayne M.; Rice, J. E.; ...

2016-08-01

A dimensionless empirical scaling for intrinsic toroidal rotation is given; M A ~β Nρ*, where M A is the toroidal velocity divided by the Alfvén velocity, β N the usual normalized β value, and ρ* is the ion gyroradius divided by the minor radius. This scaling describes well experimental data from DIII-D, and also some published data from C-Mod and JET. The velocity used in this scaling is in an outer location in minor radius, outside of the interior core and inside of the large gradient edge region in H-mode conditions. Furthermore, this scaling establishes the basic magnitude of themore » intrinsic toroidal rotation and its relation to the rich variety of rotation profiles that can be realized for intrinsic conditions is discussed.« less

Bypassing the energy-time uncertainty in time-resolved photoemission

NASA Astrophysics Data System (ADS)

Randi, Francesco; Fausti, Daniele; Eckstein, Martin

2017-03-01

The energy-time uncertainty is an intrinsic limit for time-resolved experiments imposing a tradeoff between the duration of the light pulses used in experiments and their frequency content. In standard time-resolved photoemission, this limitation maps directly onto a tradeoff between the time resolution of the experiment and the energy resolution that can be achieved on the electronic spectral function. Here we propose a protocol to disentangle the energy and time resolutions in photoemission. We demonstrate that dynamical information on all time scales can be retrieved from time-resolved photoemission experiments using suitably shaped light pulses of quantum or classical nature. As a paradigmatic example, we study the dynamical buildup of the Kondo peak, a narrow feature in the electronic response function arising from the screening of a magnetic impurity by the conduction electrons. After a quench, the electronic screening builds up on timescales shorter than the inverse width of the Kondo peak and we demonstrate that the proposed experimental scheme could be used to measure the intrinsic time scales of such electronic screening. The proposed approach provides an experimental framework to access the nonequilibrium response of collective electronic properties beyond the spectral uncertainty limit and will enable the direct measurement of phenomena such as excited Higgs modes and, possibly, the retarded interactions in superconducting systems.

Keyword extraction by entropy difference between the intrinsic and extrinsic mode

NASA Astrophysics Data System (ADS)

Yang, Zhen; Lei, Jianjun; Fan, Kefeng; Lai, Yingxu

2013-10-01

This paper proposes a new metric to evaluate and rank the relevance of words in a text. The method uses the Shannon’s entropy difference between the intrinsic and extrinsic mode, which refers to the fact that relevant words significantly reflect the author’s writing intention, i.e., their occurrences are modulated by the author’s purpose, while the irrelevant words are distributed randomly in the text. By using The Origin of Species by Charles Darwin as a representative text sample, the performance of our detector is demonstrated and compared to previous proposals. Since a reference text “corpus” is all of an author’s writings, books, papers, etc. his collected works is not needed. Our approach is especially suitable for single documents of which there is no a priori information available.

Intrinsic motivation as a predictor of work outcome after vocational rehabilitation in schizophrenia.

PubMed

Saperstein, Alice M; Fiszdon, Joanna M; Bell, Morris D

2011-09-01

Intrinsic motivation is a construct commonly used in explaining goal-directed behavior. In people with schizophrenia, intrinsic motivation is usually subsumed as a feature of negative symptoms or underlying neurocognitive dysfunction. A growing literature reflects an interest in defining and measuring motivational impairment in schizophrenia and in delineating the specific role of intrinsic motivation as both an independent predictor and a mediator of psychosocial functioning. This cross-sectional study examined intrinsic motivation as a predictor of vocational outcomes for 145 individuals with schizophrenia and schizoaffective disorder participating in a 6-month work rehabilitation trial. Correlation and mediation analyses examined baseline intrinsic motivation and negative symptoms in relation to work hours and work performance. Data support a significant relationship between intrinsic motivation and negative symptoms and significant correlations with outcome variables, such that lower negative symptoms and greater intrinsic motivation were associated with better work functioning. Moreover, in this sample, intrinsic motivation fully mediated the relationships between negative symptoms, work productivity, and work performance. These results have significant implications on the design of work rehabilitation interventions for people with schizophrenia and support a role for targeting intrinsic motivation directly to influence vocational functioning. Future directions for research and intervention are discussed.

Identifying the neural substrates of intrinsic motivation during task performance.

PubMed

Lee, Woogul; Reeve, Johnmarshall

2017-10-01

Intrinsic motivation is the inherent tendency to seek out novelty and challenge, to explore and investigate, and to stretch and extend one's capacities. When people imagine performing intrinsically motivating tasks, they show heightened anterior insular cortex (AIC) activity. To fully explain the neural system of intrinsic motivation, however, requires assessing neural activity while people actually perform intrinsically motivating tasks (i.e., while answering curiosity-inducing questions or solving competence-enabling anagrams). Using event-related functional magnetic resonance imaging, we found that the neural system of intrinsic motivation involves not only AIC activity, but also striatum activity and, further, AIC-striatum functional interactions. These findings suggest that subjective feelings of intrinsic satisfaction (associated with AIC activations), reward processing (associated with striatum activations), and their interactions underlie the actual experience of intrinsic motivation. These neural findings are consistent with the conceptualization of intrinsic motivation as the pursuit and satisfaction of subjective feelings (interest and enjoyment) as intrinsic rewards.

Creativity and the default network: A functional connectivity analysis of the creative brain at rest☆

PubMed Central

Beaty, Roger E.; Benedek, Mathias; Wilkins, Robin W.; Jauk, Emanuel; Fink, Andreas; Silvia, Paul J.; Hodges, Donald A.; Koschutnig, Karl; Neubauer, Aljoscha C.

2014-01-01

The present research used resting-state functional magnetic resonance imaging (fMRI) to examine whether the ability to generate creative ideas corresponds to differences in the intrinsic organization of functional networks in the brain. We examined the functional connectivity between regions commonly implicated in neuroimaging studies of divergent thinking, including the inferior prefrontal cortex and the core hubs of the default network. Participants were prescreened on a battery of divergent thinking tests and assigned to high- and low-creative groups based on task performance. Seed-based functional connectivity analysis revealed greater connectivity between the left inferior frontal gyrus (IFG) and the entire default mode network in the high-creative group. The right IFG also showed greater functional connectivity with bilateral inferior parietal cortex and the left dorsolateral prefrontal cortex in the high-creative group. The results suggest that the ability to generate creative ideas is characterized by increased functional connectivity between the inferior prefrontal cortex and the default network, pointing to a greater cooperation between brain regions associated with cognitive control and low-level imaginative processes. PMID:25245940

Shear-induced mechanical failure of β -G a2O3 from quantum mechanics simulations

NASA Astrophysics Data System (ADS)

An, Qi; Li, Guodong

2017-10-01

Monoclinic gallium oxide (β -G a2O3 ) has important applications in power devices and deep UV optoelectronic devices because of such novel properties as a wide band gap, high breakdown electric field, and a wide range of n -type doping conductivity. However, the intrinsic failure mechanisms of β -G a2O3 remain unknown, which limits the fabrication and packaging of β -G a2O3 -based electronic devices. Here we used density-functional theory at the Perdew-Burke-Ernzerhof level to examine the shear-induced failure mechanisms of β -G a2O3 along various plausible slip systems. We found that the (001 )/〈010 〉 slip system has the lowest ideal shear strength of 3.8 GPa among five plausible slip systems, suggesting that (001 )/〈010 〉 is the most plausible activated slip system. This slip leads to an intrinsic failure mechanism arising from breaking the longest Ga-O bond between octahedral Ga and fourfold-coordinated O. Then we identified the same failure mechanism of β -G a2O3 under biaxial shear deformation that mimics indentation stress conditions. Finally, the general stacking fault energy (SFE) surface is calculated for the (001) surface from which we concluded that there is no intrinsic stacking fault structure for β -G a2O3 . The deformation modes and SFE calculations are essential to understand the intrinsic mechanical processes of this semiconductor material, which provides insightful guidance for designing high-performance semiconductor devices.

Intrinsic brain connectivity in fibromyalgia is associated with chronic pain intensity.

PubMed

Napadow, Vitaly; LaCount, Lauren; Park, Kyungmo; As-Sanie, Sawsan; Clauw, Daniel J; Harris, Richard E

2010-08-01

Fibromyalgia (FM) is considered to be the prototypical central chronic pain syndrome and is associated with widespread pain that fluctuates spontaneously. Multiple studies have demonstrated altered brain activity in these patients. The objective of this study was to investigate the degree of connectivity between multiple brain networks in patients with FM, as well as how activity in these networks correlates with the level of spontaneous pain. Resting-state functional magnetic resonance imaging (FMRI) data from 18 patients with FM and 18 age-matched healthy control subjects were analyzed using dual-regression independent components analysis, which is a data-driven approach for the identification of independent brain networks. Intrinsic, or resting-state, connectivity was evaluated in multiple brain networks: the default mode network (DMN), the executive attention network (EAN), and the medial visual network (MVN), with the MVN serving as a negative control. Spontaneous pain levels were also analyzed for covariance with intrinsic connectivity. Patients with FM had greater connectivity within the DMN and right EAN (corrected P [P(corr)] < 0.05 versus controls), and greater connectivity between the DMN and the insular cortex, which is a brain region known to process evoked pain. Furthermore, greater intensity of spontaneous pain at the time of the FMRI scan correlated with greater intrinsic connectivity between the insula and both the DMN and right EAN (P(corr) < 0.05). These findings indicate that resting brain activity within multiple networks is associated with spontaneous clinical pain in patients with FM. These findings may also have broader implications for how subjective experiences such as pain arise from a complex interplay among multiple brain networks.

Intrinsic Brain Connectivity in Fibromyalgia is Associated with Chronic Pain Intensity

PubMed Central

Napadow, Vitaly; LaCount, Lauren; Park, Kyungmo; As-Sanie, Suzie; Clauw, Daniel J; Harris, Richard E

2010-01-01

OBJECTIVE Fibromyalgia (FM) is considered to be the prototypical central chronic pain syndrome and is associated with widespread pain that fluctuates spontaneously. Multiple studies have demonstrated altered brain activity in these patients. Our objective was to investigate the degree of connectivity between multiple brain networks in FM, as well as how activity in these networks correlates with spontaneous pain. METHODS Resting functional magnetic resonance imaging (fMRI) data in FM patients (n=18) and age-matched healthy controls (HC, n=18) were analyzed using dual regression independent component analysis (ICA) - a data driven approach used to identify independent brain networks. We evaluated intrinsic, or resting, connectivity in multiple brain networks: the default mode network (DMN), the executive attention network (EAN), and the medial visual network (MVN), with the MVN serving as a negative control. Spontaneous pain levels were also covaried with intrinsic connectivity. RESULTS We found that FM patients had greater connectivity within the DMN and right EAN (rEAN; p<0.05, corrected), and greater connectivity between the DMN and the insular cortex – a brain region known to process evoked pain. Furthermore, greater spontaneous pain at the time of the scan correlated with greater intrinsic connectivity between the insula and both the DMN and rEAN (p<0.05, corrected). CONCLUSION Our findings indicate that resting brain activity within multiple networks is associated with spontaneous clinical pain in FM. These findings may also have broader implications for how subjective experiences such as pain arise from a complex interplay amongst multiple brain networks. PMID:20506181

Construction and analysis of a modular model of caspase activation in apoptosis

PubMed Central

Harrington, Heather A; Ho, Kenneth L; Ghosh, Samik; Tung, KC

2008-01-01

Background A key physiological mechanism employed by multicellular organisms is apoptosis, or programmed cell death. Apoptosis is triggered by the activation of caspases in response to both extracellular (extrinsic) and intracellular (intrinsic) signals. The extrinsic and intrinsic pathways are characterized by the formation of the death-inducing signaling complex (DISC) and the apoptosome, respectively; both the DISC and the apoptosome are oligomers with complex formation dynamics. Additionally, the extrinsic and intrinsic pathways are coupled through the mitochondrial apoptosis-induced channel via the Bcl-2 family of proteins. Results A model of caspase activation is constructed and analyzed. The apoptosis signaling network is simplified through modularization methodologies and equilibrium abstractions for three functional modules. The mathematical model is composed of a system of ordinary differential equations which is numerically solved. Multiple linear regression analysis investigates the role of each module and reduced models are constructed to identify key contributions of the extrinsic and intrinsic pathways in triggering apoptosis for different cell lines. Conclusion Through linear regression techniques, we identified the feedbacks, dissociation of complexes, and negative regulators as the key components in apoptosis. The analysis and reduced models for our model formulation reveal that the chosen cell lines predominately exhibit strong extrinsic caspase, typical of type I cell, behavior. Furthermore, under the simplified model framework, the selected cells lines exhibit different modes by which caspase activation may occur. Finally the proposed modularized model of apoptosis may generalize behavior for additional cells and tissues, specifically identifying and predicting components responsible for the transition from type I to type II cell behavior. PMID:19077196

Prediction of Biological Motion Perception Performance from Intrinsic Brain Network Regional Efficiency

PubMed Central

Wang, Zengjian; Zhang, Delong; Liang, Bishan; Chang, Song; Pan, Jinghua; Huang, Ruiwang; Liu, Ming

2016-01-01

Biological motion perception (BMP) refers to the ability to perceive the moving form of a human figure from a limited amount of stimuli, such as from a few point lights located on the joints of a moving body. BMP is commonplace and important, but there is great inter-individual variability in this ability. This study used multiple regression model analysis to explore the association between BMP performance and intrinsic brain activity, in order to investigate the neural substrates underlying inter-individual variability of BMP performance. The resting-state functional magnetic resonance imaging (rs-fMRI) and BMP performance data were collected from 24 healthy participants, for whom intrinsic brain networks were constructed, and a graph-based network efficiency metric was measured. Then, a multiple linear regression model was used to explore the association between network regional efficiency and BMP performance. We found that the local and global network efficiency of many regions was significantly correlated with BMP performance. Further analysis showed that the local efficiency rather than global efficiency could be used to explain most of the BMP inter-individual variability, and the regions involved were predominately located in the Default Mode Network (DMN). Additionally, discrimination analysis showed that the local efficiency of certain regions such as the thalamus could be used to classify BMP performance across participants. Notably, the association pattern between network nodal efficiency and BMP was different from the association pattern of static directional/gender information perception. Overall, these findings show that intrinsic brain network efficiency may be considered a neural factor that explains BMP inter-individual variability. PMID:27853427

Dual-function photonic integrated circuit for frequency octo-tupling or single-side-band modulation.

PubMed

Hasan, Mehedi; Maldonado-Basilio, Ramón; Hall, Trevor J

2015-06-01

A dual-function photonic integrated circuit for microwave photonic applications is proposed. The circuit consists of four linear electro-optic phase modulators connected optically in parallel within a generalized Mach-Zehnder interferometer architecture. The photonic circuit is arranged to have two separate output ports. A first port provides frequency up-conversion of a microwave signal from the electrical to the optical domain; equivalently single-side-band modulation. A second port provides tunable millimeter wave carriers by frequency octo-tupling of an appropriate amplitude RF carrier. The circuit exploits the intrinsic relative phases between the ports of multi-mode interference couplers to provide substantially all the static optical phases needed. The operation of the proposed dual-function photonic integrated circuit is verified by computer simulations. The performance of the frequency octo-tupling and up-conversion functions is analyzed in terms of the electrical signal to harmonic distortion ratio and the optical single side band to unwanted harmonics ratio, respectively.

Quantifying Spasticity With Limited Swinging Cycles Using Pendulum Test Based on Phase Amplitude Coupling.

PubMed

Yeh, Chien Hung; Young, Hsu Wen Vincent; Wang, Cheng Yen; Wang, Yung Hung; Lee, Po Lei; Kang, Jiunn Horng; Lo, Men Tzung

2016-10-01

Parameters derived from the goniometer measures in the Pendulum test are insufficient in describing the function of abnormal muscle activity in the spasticity. To explore a quantitative evaluation of muscle activation-movement interaction, we propose a novel index based on phase amplitude coupling (PAC) analysis with the consideration of the relations between movement and surface electromyography (SEMG) activity among 22 hemiplegic stroke patients. To take off trend and noise, we use the empirical mode decomposition (EMD) to obtain intrinsic mode functions (IMFs) of the angular velocity due to its superior decomposing ability in nonlinear oscillations. Shannon entropy based on angular velocity (phase)-envelope of EMG (amplitude) distribution was calculated to demonstrate characteristics of the coupling between SEMG activity and joint movement. We also compare our results with those from traditional methods such as the normalized relaxation index derived from the Pendulum test and the mean root mean square (RMS) of the SEMG signals in the study. Our results show effective discrimination ability between spastic and nonaffected limbs using our method . This study indicates the feasibility of using the novel indices based on the PAC in evaluation the spasticity among the hemiplegic stroke patients with less than three swinging cycles.

Optical micro-bubble resonators as promising biosensors

NASA Astrophysics Data System (ADS)

Giannetti, A.; Barucci, A.; Berneschi, S.; Cosci, A.; Cosi, F.; Farnesi, D.; Nunzi Conti, G.; Pelli, S.; Soria, S.; Tombelli, S.; Trono, C.; Righini, G. C.; Baldini, F.

2015-05-01

Recently, optical micro-bubble resonators (OMBRs) have gained an increasing interest in many fields of photonics thanks to their particular properties. These hollow microstructures can be suitable for the realization of label - free optical biosensors by combining the whispering gallery mode (WGM) resonator properties with the intrinsic capability of integrated microfluidics. In fact, the WGMs are morphology-dependent modes: any change on the OMBR inner surface (due to chemical and/or biochemical binding) causes a shift of the resonance position and reduces the Q factor value of the cavity. By measuring this shift, it is possible to obtain information on the concentration of the analyte to be detected. A crucial step for the development of an OMBR-based biosensor is constituted by the functionalization of its inner surface. In this work we report on the development of a physical and chemical process able to guarantee a good homogeneity of the deposed bio-layer and, contemporary, to preserve a high quality factor Q of the cavity. The OMBR capability of working as bioassay was proved by different optical techniques, such as the real time measurement of the resonance broadening after each functionalization step and fluorescence microscopy.

Application of the Hilbert-Huang Transform to Financial Data

NASA Technical Reports Server (NTRS)

Huang, Norden

2005-01-01

A paper discusses the application of the Hilbert-Huang transform (HHT) method to time-series financial-market data. The method was described, variously without and with the HHT name, in several prior NASA Tech Briefs articles and supporting documents. To recapitulate: The method is especially suitable for analyzing time-series data that represent nonstationary and nonlinear phenomena including physical phenomena and, in the present case, financial-market processes. The method involves the empirical mode decomposition (EMD), in which a complicated signal is decomposed into a finite number of functions, called "intrinsic mode functions" (IMFs), that admit well-behaved Hilbert transforms. The HHT consists of the combination of EMD and Hilbert spectral analysis. The local energies and the instantaneous frequencies derived from the IMFs through Hilbert transforms can be used to construct an energy-frequency-time distribution, denoted a Hilbert spectrum. The instant paper begins with a discussion of prior approaches to quantification of market volatility, summarizes the HHT method, then describes the application of the method in performing time-frequency analysis of mortgage-market data from the years 1972 through 2000. Filtering by use of the EMD is shown to be useful for quantifying market volatility.

3D two-fluid simulations of turbulence in LAPD

NASA Astrophysics Data System (ADS)

Fisher, Dustin M.

The Large Plasma Device (LAPD) is modeled using a modified version of the 3D Global Braginskii Solver code (GBS) for a nominal Helium plasma. The unbiased low-flow regime is explored in simulations where there is an intrinsic E x B rotation of the plasma. In the simulations this rotation is caused primarily by sheath effects with the Reynolds stress and J x B torque due to a cross-field Pederson conductivity having little effect. Explicit biasing simulations are also explored for the first time where the intrinsic rotation of the plasma is modified through boundary conditions that mimic the biasable limiter used in LAPD. Comparisons to experimental measurements in the unbiased case show strong qualitative agreement with the data, particularly the radial dependence of the density fluctuations, cross-correlation lengths, radial flux dependence outside of the cathode edge, and camera imagery. Kelvin Helmholtz (KH) turbulence at relatively large scales is the dominant driver of cross-field transport in these simulations with smaller-scale drift waves and sheath modes playing a secondary role. Plasma holes and blobs arising from KH vortices are consistent with the scale sizes and overall appearance of those in LAPD camera images. The addition of ion-neutral collisions in the unbiased simulations at previously theorized values reduces the radial particle flux due to a modest stabilizing contribution of the collisions on the KH-modes driving the turbulent transport. In the biased runs the ion-neutral collisions have a much smaller effect due to the modification of the potential from sheath terms. In biasing the plasma to increase the intrinsic rotation, simulations show the emergence of a nonlinearly saturated coherent mode of order m = 6. In addition, the plasma inside of the cathode edge becomes quiescent due to the strong influence of the wall bias in setting up the equilibrium plasma potential. Biasing in the direction opposite to the intrinsic flow reduces the effective shear and leads to a stronger presence of drift modes that are seen to saturate when the KH drive has been suppressed. Both biasing cases show a moderate density confinement similarly seen in the experiment.

A brave new world of RNA-binding proteins.

PubMed

Hentze, Matthias W; Castello, Alfredo; Schwarzl, Thomas; Preiss, Thomas

2018-05-01

RNA-binding proteins (RBPs) are typically thought of as proteins that bind RNA through one or multiple globular RNA-binding domains (RBDs) and change the fate or function of the bound RNAs. Several hundred such RBPs have been discovered and investigated over the years. Recent proteome-wide studies have more than doubled the number of proteins implicated in RNA binding and uncovered hundreds of additional RBPs lacking conventional RBDs. In this Review, we discuss these new RBPs and the emerging understanding of their unexpected modes of RNA binding, which can be mediated by intrinsically disordered regions, protein-protein interaction interfaces and enzymatic cores, among others. We also discuss the RNA targets and molecular and cellular functions of the new RBPs, as well as the possibility that some RBPs may be regulated by RNA rather than regulate RNA.

Analyzing the Multiscale Processes in Tropical Cyclone Genesis Associated with African Easterly Waves using the PEEMD. Part I: Downscaling Processes

NASA Astrophysics Data System (ADS)

Wu, Y.; Shen, B. W.; Cheung, S.

2016-12-01

Recent advance in high-resolution global hurricane simulations and visualizations have collectively suggested the importance of both downscaling and upscaling processes in the formation and intensification of TCs. To reveal multiscale processes from massive volume of global data for multiple years, a scalable Parallel Ensemble Empirical Mode Decomposition (PEEMD) method has been developed for the analysis. In this study, the PEEMD is applied to analyzing 10-year (2004-2013) ERA-Interim global 0.750 resolution reanalysis data to explore the role of the downscaling processes in tropical cyclogenesis associated with African Easterly Waves (AEWs). Using the PEEMD, raw data are decomposed into oscillatory Intrinsic Function Modes (IMFs) that represent atmospheric systems of the various length scales and the trend mode that represents a non-oscillatory large scale environmental flow. Among oscillatory modes, results suggest that the third oscillatory mode (IMF3) is statistically correlated with the TC/AEW scale systems. Therefore, IMF3 and trend mode are analyzed in details. Our 10-year analysis shows that more than 50% of the AEW associated hurricanes reveal the association of storms' formation with the significant downscaling shear transfer from the larger-scale trend mode to the smaller scale IMF3. Future work will apply the PEEMD to the analysis of higher-resolution datasets to explore the role of the upscaling processes provided by the convection (or TC) in the development of the TC (or AEW). Figure caption: The tendency for horizontal wind shear for the total winds (black line), IMF3 (blue line), and trend mode (red line) and SLP (black dotted line) along the storm track of Helene (2006).

HLH-30/TFEB-mediated autophagy functions in a cell-autonomous manner for epithelium intrinsic cellular defense against bacterial pore-forming toxin in C. elegans.

PubMed

Chen, Huan-Da; Kao, Cheng-Yuan; Liu, Bang-Yu; Huang, Shin-Whei; Kuo, Cheng-Ju; Ruan, Jhen-Wei; Lin, Yen-Hung; Huang, Cheng-Rung; Chen, Yu-Hung; Wang, Horng-Dar; Aroian, Raffi V; Chen, Chang-Shi

2017-02-01

Autophagy is an evolutionarily conserved intracellular system that maintains cellular homeostasis by degrading and recycling damaged cellular components. The transcription factor HLH-30/TFEB-mediated autophagy has been reported to regulate tolerance to bacterial infection, but less is known about the bona fide bacterial effector that activates HLH-30 and autophagy. Here, we reveal that bacterial membrane pore-forming toxin (PFT) induces autophagy in an HLH-30-dependent manner in Caenorhabditis elegans. Moreover, autophagy controls the susceptibility of animals to PFT toxicity through xenophagic degradation of PFT and repair of membrane-pore cell-autonomously in the PFT-targeted intestinal cells in C. elegans. These results demonstrate that autophagic pathways and autophagy are induced partly at the transcriptional level through HLH-30 activation and are required to protect metazoan upon PFT intoxication. Together, our data show a new and powerful connection between HLH-30-mediated autophagy and epithelium intrinsic cellular defense against the single most common mode of bacterial attack in vivo.

Steepest Ascent Low/Non-Low-Frequency Ratio in Empirical Mode Decomposition to Separate Deterministic and Stochastic Velocities From a Single Lagrangian Drifter

NASA Astrophysics Data System (ADS)

Chu, Peter C.

2018-03-01

SOund Fixing And Ranging (RAFOS) floats deployed by the Naval Postgraduate School (NPS) in the California Current system from 1992 to 2001 at depth between 150 and 600 m (http://www.oc.nps.edu/npsRAFOS/) are used to study 2-D turbulent characteristics. Each drifter trajectory is adaptively decomposed using the empirical mode decomposition (EMD) into a series of intrinsic mode functions (IMFs) with corresponding specific scale for each IMF. A new steepest ascent low/non-low-frequency ratio is proposed in this paper to separate a Lagrangian trajectory into low-frequency (nondiffusive, i.e., deterministic) and high-frequency (diffusive, i.e., stochastic) components. The 2-D turbulent (or called eddy) diffusion coefficients are calculated on the base of the classical turbulent diffusion with mixing length theory from stochastic component of a single drifter. Statistical characteristics of the calculated 2-D turbulence length scale, strength, and diffusion coefficients from the NPS RAFOS data are presented with the mean values (over the whole drifters) of the 2-D diffusion coefficients comparable to the commonly used diffusivity tensor method.

Pseudo-fault signal assisted EMD for fault detection and isolation in rotating machines

NASA Astrophysics Data System (ADS)

Singh, Dheeraj Sharan; Zhao, Qing

2016-12-01

This paper presents a novel data driven technique for the detection and isolation of faults, which generate impacts in a rotating equipment. The technique is built upon the principles of empirical mode decomposition (EMD), envelope analysis and pseudo-fault signal for fault separation. Firstly, the most dominant intrinsic mode function (IMF) is identified using EMD of a raw signal, which contains all the necessary information about the faults. The envelope of this IMF is often modulated with multiple vibration sources and noise. A second level decomposition is performed by applying pseudo-fault signal (PFS) assisted EMD on the envelope. A pseudo-fault signal is constructed based on the known fault characteristic frequency of the particular machine. The objective of using external (pseudo-fault) signal is to isolate different fault frequencies, present in the envelope . The pseudo-fault signal serves dual purposes: (i) it solves the mode mixing problem inherent in EMD, (ii) it isolates and quantifies a particular fault frequency component. The proposed technique is suitable for real-time implementation, which has also been validated on simulated fault and experimental data corresponding to a bearing and a gear-box set-up, respectively.

A Cutting Pattern Recognition Method for Shearers Based on Improved Ensemble Empirical Mode Decomposition and a Probabilistic Neural Network

PubMed Central

Xu, Jing; Wang, Zhongbin; Tan, Chao; Si, Lei; Liu, Xinhua

2015-01-01

In order to guarantee the stable operation of shearers and promote construction of an automatic coal mining working face, an online cutting pattern recognition method with high accuracy and speed based on Improved Ensemble Empirical Mode Decomposition (IEEMD) and Probabilistic Neural Network (PNN) is proposed. An industrial microphone is installed on the shearer and the cutting sound is collected as the recognition criterion to overcome the disadvantages of giant size, contact measurement and low identification rate of traditional detectors. To avoid end-point effects and get rid of undesirable intrinsic mode function (IMF) components in the initial signal, IEEMD is conducted on the sound. The end-point continuation based on the practical storage data is performed first to overcome the end-point effect. Next the average correlation coefficient, which is calculated by the correlation of the first IMF with others, is introduced to select essential IMFs. Then the energy and standard deviation of the reminder IMFs are extracted as features and PNN is applied to classify the cutting patterns. Finally, a simulation example, with an accuracy of 92.67%, and an industrial application prove the efficiency and correctness of the proposed method. PMID:26528985

Defects diagnosis in laser brazing using near-infrared signals based on empirical mode decomposition

NASA Astrophysics Data System (ADS)

Cheng, Liyong; Mi, Gaoyang; Li, Shuo; Wang, Chunming; Hu, Xiyuan

2018-03-01

Real-time monitoring of laser welding plays a very important role in the modern automated production and online defects diagnosis is necessary to be implemented. In this study, the status of laser brazing was monitored in real time using an infrared photoelectric sensor. Four kinds of braze seams (including healthy weld, unfilled weld, hole weld and rough surface weld) along with corresponding near-infrared signals were obtained. Further, a new method called Empirical Mode Decomposition (EMD) was proposed to analyze the near-infrared signals. The results showed that the EMD method had a good performance in eliminating the noise on the near-infrared signals. And then, the correlation coefficient was developed for selecting the Intrinsic Mode Function (IMF) more sensitive to the weld defects. A more accurate signal was reconstructed with the selected IMF components. Simultaneously, the spectrum of selected IMF components was solved using fast Fourier transform, and the frequency characteristics were clearly revealed. The frequency energy of different frequency bands was computed to diagnose the defects. There was a significant difference in four types of weld defects. This approach has been proved to be an effective and efficient method for monitoring laser brazing defects.

Pathological speech signal analysis and classification using empirical mode decomposition.

PubMed

Kaleem, Muhammad; Ghoraani, Behnaz; Guergachi, Aziz; Krishnan, Sridhar

2013-07-01

Automated classification of normal and pathological speech signals can provide an objective and accurate mechanism for pathological speech diagnosis, and is an active area of research. A large part of this research is based on analysis of acoustic measures extracted from sustained vowels. However, sustained vowels do not reflect real-world attributes of voice as effectively as continuous speech, which can take into account important attributes of speech such as rapid voice onset and termination, changes in voice frequency and amplitude, and sudden discontinuities in speech. This paper presents a methodology based on empirical mode decomposition (EMD) for classification of continuous normal and pathological speech signals obtained from a well-known database. EMD is used to decompose randomly chosen portions of speech signals into intrinsic mode functions, which are then analyzed to extract meaningful temporal and spectral features, including true instantaneous features which can capture discriminative information in signals hidden at local time-scales. A total of six features are extracted, and a linear classifier is used with the feature vector to classify continuous speech portions obtained from a database consisting of 51 normal and 161 pathological speakers. A classification accuracy of 95.7 % is obtained, thus demonstrating the effectiveness of the methodology.

Characterising intra- and inter-intrinsic network synchrony in combat-related post-traumatic stress disorder.

PubMed

Dunkley, Benjamin T; Doesburg, Sam M; Jetly, Rakesh; Sedge, Paul A; Pang, Elizabeth W; Taylor, Margot J

2015-11-30

Soldiers with post-traumatic stress disorder (PTSD) exhibit elevated gamma-band synchrony in left fronto-temporal cortex, and connectivity measures in these regions correlate with comorbidities and PTSD severity, which suggests increased gamma synchrony is related to symptomology. However, little is known about the role of intrinsic, phase-synchronised networks in the disorder. Using magnetoencephalography (MEG), we characterised spectral connectivity in the default-mode, salience, visual, and attention networks during resting-state in a PTSD population and a trauma-exposed control group. Intrinsic network connectivity was examined in canonical frequency bands. We observed increased inter-network synchronisation in the PTSD group compared with controls in the gamma (30-80 Hz) and high-gamma range (80-150 Hz). Analyses of connectivity and symptomology revealed that PTSD severity was positively associated with beta synchrony in the ventral-attention-to-salience networks, and gamma synchrony within the salience network, but also negatively correlated with beta synchrony within the visual network. These novel results show that frequency-specific, network-level atypicalities may reflect trauma-related alterations of ongoing functional connectivity, and correlations of beta synchrony in attentional-to-salience and visual networks with PTSD severity suggest complicated network interactions mediate symptoms. These results contribute to accumulating evidence that PTSD is a complicated network-based disorder expressed as altered neural interactions. Crown Copyright © 2015. Published by Elsevier Ireland Ltd. All rights reserved.

Electrically tunable terahertz metamaterials with embedded large-area transparent thin-film transistor arrays

PubMed Central

Xu, Wei-Zong; Ren, Fang-Fang; Ye, Jiandong; Lu, Hai; Liang, Lanju; Huang, Xiaoming; Liu, Mingkai; Shadrivov, Ilya V.; Powell, David A.; Yu, Guang; Jin, Biaobing; Zhang, Rong; Zheng, Youdou; Tan, Hark Hoe; Jagadish, Chennupati

2016-01-01

Engineering metamaterials with tunable resonances are of great importance for improving the functionality and flexibility of terahertz (THz) systems. An ongoing challenge in THz science and technology is to create large-area active metamaterials as building blocks to enable efficient and precise control of THz signals. Here, an active metamaterial device based on enhancement-mode transparent amorphous oxide thin-film transistor arrays for THz modulation is demonstrated. Analytical modelling based on full-wave techniques and multipole theory exhibits excellent consistent with the experimental observations and reveals that the intrinsic resonance mode at 0.75 THz is dominated by an electric response. The resonant behavior can be effectively tuned by controlling the channel conductivity through an external bias. Such metal/oxide thin-film transistor based controllable metamaterials are energy saving, low cost, large area and ready for mass-production, which are expected to be widely used in future THz imaging, sensing, communications and other applications. PMID:27000419

EEMD-MUSIC-Based Analysis for Natural Frequencies Identification of Structures Using Artificial and Natural Excitations

PubMed Central

Amezquita-Sanchez, Juan P.; Romero-Troncoso, Rene J.; Osornio-Rios, Roque A.; Garcia-Perez, Arturo

2014-01-01

This paper presents a new EEMD-MUSIC- (ensemble empirical mode decomposition-multiple signal classification-) based methodology to identify modal frequencies in structures ranging from free and ambient vibration signals produced by artificial and natural excitations and also considering several factors as nonstationary effects, close modal frequencies, and noisy environments, which are common situations where several techniques reported in literature fail. The EEMD and MUSIC methods are used to decompose the vibration signal into a set of IMFs (intrinsic mode functions) and to identify the natural frequencies of a structure, respectively. The effectiveness of the proposed methodology has been validated and tested with synthetic signals and under real operating conditions. The experiments are focused on extracting the natural frequencies of a truss-type scaled structure and of a bridge used for both highway traffic and pedestrians. Results show the proposed methodology as a suitable solution for natural frequencies identification of structures from free and ambient vibration signals. PMID:24683346

EEMD-MUSIC-based analysis for natural frequencies identification of structures using artificial and natural excitations.

PubMed

Camarena-Martinez, David; Amezquita-Sanchez, Juan P; Valtierra-Rodriguez, Martin; Romero-Troncoso, Rene J; Osornio-Rios, Roque A; Garcia-Perez, Arturo

2014-01-01

This paper presents a new EEMD-MUSIC- (ensemble empirical mode decomposition-multiple signal classification-) based methodology to identify modal frequencies in structures ranging from free and ambient vibration signals produced by artificial and natural excitations and also considering several factors as nonstationary effects, close modal frequencies, and noisy environments, which are common situations where several techniques reported in literature fail. The EEMD and MUSIC methods are used to decompose the vibration signal into a set of IMFs (intrinsic mode functions) and to identify the natural frequencies of a structure, respectively. The effectiveness of the proposed methodology has been validated and tested with synthetic signals and under real operating conditions. The experiments are focused on extracting the natural frequencies of a truss-type scaled structure and of a bridge used for both highway traffic and pedestrians. Results show the proposed methodology as a suitable solution for natural frequencies identification of structures from free and ambient vibration signals.

A novel technique for phase synchrony measurement from the complex motor imaginary potential of combined body and limb action

NASA Astrophysics Data System (ADS)

Zhou, Zhong-xing; Wan, Bai-kun; Ming, Dong; Qi, Hong-zhi

2010-08-01

In this study, we proposed and evaluated the use of the empirical mode decomposition (EMD) technique combined with phase synchronization analysis to investigate the human brain synchrony of the supplementary motor area (SMA) and primary motor area (M1) during complex motor imagination of combined body and limb action. We separated the EEG data of the SMA and M1 into intrinsic mode functions (IMFs) using the EMD method and determined the characteristic IMFs by power spectral density (PSD) analysis. Thereafter, the instantaneous phases of the characteristic IMFs were obtained by the Hilbert transformation, and the single-trial phase-locking value (PLV) features for brain synchrony measurement between the SMA and M1 were investigated separately. The classification performance suggests that the proposed approach is effective for phase synchronization analysis and is promising for the application of a brain-computer interface in motor nerve reconstruction of the lower limbs.

Multiscale synchrony behaviors of paired financial time series by 3D multi-continuum percolation

NASA Astrophysics Data System (ADS)

Wang, M.; Wang, J.; Wang, B. T.

2018-02-01

Multiscale synchrony behaviors and nonlinear dynamics of paired financial time series are investigated, in an attempt to study the cross correlation relationships between two stock markets. A random stock price model is developed by a new system called three-dimensional (3D) multi-continuum percolation system, which is utilized to imitate the formation mechanism of price dynamics and explain the nonlinear behaviors found in financial time series. We assume that the price fluctuations are caused by the spread of investment information. The cluster of 3D multi-continuum percolation represents the cluster of investors who share the same investment attitude. In this paper, we focus on the paired return series, the paired volatility series, and the paired intrinsic mode functions which are decomposed by empirical mode decomposition. A new cross recurrence quantification analysis is put forward, combining with multiscale cross-sample entropy, to investigate the multiscale synchrony of these paired series from the proposed model. The corresponding research is also carried out for two China stock markets as comparison.

Multi-Sensor Data Fusion Identification for Shearer Cutting Conditions Based on Parallel Quasi-Newton Neural Networks and the Dempster-Shafer Theory.

PubMed

Si, Lei; Wang, Zhongbin; Liu, Xinhua; Tan, Chao; Xu, Jing; Zheng, Kehong

2015-11-13

In order to efficiently and accurately identify the cutting condition of a shearer, this paper proposed an intelligent multi-sensor data fusion identification method using the parallel quasi-Newton neural network (PQN-NN) and the Dempster-Shafer (DS) theory. The vibration acceleration signals and current signal of six cutting conditions were collected from a self-designed experimental system and some special state features were extracted from the intrinsic mode functions (IMFs) based on the ensemble empirical mode decomposition (EEMD). In the experiment, three classifiers were trained and tested by the selected features of the measured data, and the DS theory was used to combine the identification results of three single classifiers. Furthermore, some comparisons with other methods were carried out. The experimental results indicate that the proposed method performs with higher detection accuracy and credibility than the competing algorithms. Finally, an industrial application example in the fully mechanized coal mining face was demonstrated to specify the effect of the proposed system.

Phase correlation of foreign exchange time series

NASA Astrophysics Data System (ADS)

Wu, Ming-Chya

2007-03-01

Correlation of foreign exchange rates in currency markets is investigated based on the empirical data of USD/DEM and USD/JPY exchange rates for a period from February 1 1986 to December 31 1996. The return of exchange time series is first decomposed into a number of intrinsic mode functions (IMFs) by the empirical mode decomposition method. The instantaneous phases of the resultant IMFs calculated by the Hilbert transform are then used to characterize the behaviors of pricing transmissions, and the correlation is probed by measuring the phase differences between two IMFs in the same order. From the distribution of phase differences, our results show explicitly that the correlations are stronger in daily time scale than in longer time scales. The demonstration for the correlations in periods of 1986-1989 and 1990-1993 indicates two exchange rates in the former period were more correlated than in the latter period. The result is consistent with the observations from the cross-correlation calculation.

Shifted intrinsic connectivity of central executive and salience network in borderline personality disorder

PubMed Central

Doll, Anselm; Sorg, Christian; Manoliu, Andrei; Wöller, Andreas; Meng, Chun; Förstl, Hans; Zimmer, Claus; Wohlschläger, Afra M.; Riedl, Valentin

2013-01-01

Borderline personality disorder (BPD) is characterized by “stable instability” of emotions and behavior and their regulation. This emotional and behavioral instability corresponds with a neurocognitive triple network model of psychopathology, which suggests that aberrant emotional saliency and cognitive control is associated with aberrant interaction across three intrinsic connectivity networks [i.e., the salience network (SN), default mode network (DMN), and central executive network (CEN)]. The objective of the current study was to investigate whether and how such triple network intrinsic functional connectivity (iFC) is changed in patients with BPD. We acquired resting-state functional magnetic resonance imaging (rs-fMRI) data from 14 patients with BPD and 16 healthy controls. High-model order independent component analysis was used to extract spatiotemporal patterns of ongoing, coherent blood-oxygen-level-dependent signal fluctuations from rs-fMRI data. Main outcome measures were iFC within networks (intra-iFC) and between networks (i.e., network time course correlation inter-iFC). Aberrant intra-iFC was found in patients’ DMN, SN, and CEN, consistent with previous findings. While patients’ inter-iFC of the CEN was decreased, inter-iFC of the SN was increased. In particular, a balance index reflecting the relationship of CEN- and SN-inter-iFC across networks was strongly shifted from CEN to SN connectivity in patients. Results provide first preliminary evidence for aberrant triple network iFC in BPD. Our data suggest a shift of inter-network iFC from networks involved in cognitive control to those of emotion-related activity in BPD, potentially reflecting the persistent instability of emotion regulation in patients. PMID:24198777

Large-scale functional brain network changes in taxi drivers: evidence from resting-state fMRI.

PubMed

Wang, Lubin; Liu, Qiang; Shen, Hui; Li, Hong; Hu, Dewen

2015-03-01

Driving a car in the environment is a complex behavior that involves cognitive processing of visual information to generate the proper motor outputs and action controls. Previous neuroimaging studies have used virtual simulation to identify the brain areas that are associated with various driving-related tasks. Few studies, however, have focused on the specific patterns of functional organization in the driver's brain. The aim of this study was to assess differences in the resting-state networks (RSNs) of the brains of drivers and nondrivers. Forty healthy subjects (20 licensed taxi drivers, 20 nondrivers) underwent an 8-min resting-state functional MRI acquisition. Using independent component analysis, three sensory (primary and extrastriate visual, sensorimotor) RSNs and four cognitive (anterior and posterior default mode, left and right frontoparietal) RSNs were retrieved from the data. We then examined the group differences in the intrinsic brain activity of each RSN and in the functional network connectivity (FNC) between the RSNs. We found that the drivers had reduced intrinsic brain activity in the visual RSNs and reduced FNC between the sensory RSNs compared with the nondrivers. The major finding of this study, however, was that the FNC between the cognitive and sensory RSNs became more positively or less negatively correlated in the drivers relative to that in the nondrivers. Notably, the strength of the FNC between the left frontoparietal and primary visual RSNs was positively correlated with the number of taxi-driving years. Our findings may provide new insight into how the brain supports driving behavior. © 2014 Wiley Periodicals, Inc.

Structure and Function in Homodimeric Enzymes: Simulations of Cooperative and Independent Functional Motions.

PubMed

Wells, Stephen A; van der Kamp, Marc W; McGeagh, John D; Mulholland, Adrian J

2015-01-01

Large-scale conformational change is a common feature in the catalytic cycles of enzymes. Many enzymes function as homodimers with active sites that contain elements from both chains. Symmetric and anti-symmetric cooperative motions in homodimers can potentially lead to correlated active site opening and/or closure, likely to be important for ligand binding and release. Here, we examine such motions in two different domain-swapped homodimeric enzymes: the DcpS scavenger decapping enzyme and citrate synthase. We use and compare two types of all-atom simulations: conventional molecular dynamics simulations to identify physically meaningful conformational ensembles, and rapid geometric simulations of flexible motion, biased along normal mode directions, to identify relevant motions encoded in the protein structure. The results indicate that the opening/closure motions are intrinsic features of both unliganded enzymes. In DcpS, conformational change is dominated by an anti-symmetric cooperative motion, causing one active site to close as the other opens; however a symmetric motion is also significant. In CS, we identify that both symmetric (suggested by crystallography) and asymmetric motions are features of the protein structure, and as a result the behaviour in solution is largely non-cooperative. The agreement between two modelling approaches using very different levels of theory indicates that the behaviours are indeed intrinsic to the protein structures. Geometric simulations correctly identify and explore large amplitudes of motion, while molecular dynamics simulations indicate the ranges of motion that are energetically feasible. Together, the simulation approaches are able to reveal unexpected functionally relevant motions, and highlight differences between enzymes.

Structure and Function in Homodimeric Enzymes: Simulations of Cooperative and Independent Functional Motions

PubMed Central

McGeagh, John D.; Mulholland, Adrian J.

2015-01-01

Large-scale conformational change is a common feature in the catalytic cycles of enzymes. Many enzymes function as homodimers with active sites that contain elements from both chains. Symmetric and anti-symmetric cooperative motions in homodimers can potentially lead to correlated active site opening and/or closure, likely to be important for ligand binding and release. Here, we examine such motions in two different domain-swapped homodimeric enzymes: the DcpS scavenger decapping enzyme and citrate synthase. We use and compare two types of all-atom simulations: conventional molecular dynamics simulations to identify physically meaningful conformational ensembles, and rapid geometric simulations of flexible motion, biased along normal mode directions, to identify relevant motions encoded in the protein structure. The results indicate that the opening/closure motions are intrinsic features of both unliganded enzymes. In DcpS, conformational change is dominated by an anti-symmetric cooperative motion, causing one active site to close as the other opens; however a symmetric motion is also significant. In CS, we identify that both symmetric (suggested by crystallography) and asymmetric motions are features of the protein structure, and as a result the behaviour in solution is largely non-cooperative. The agreement between two modelling approaches using very different levels of theory indicates that the behaviours are indeed intrinsic to the protein structures. Geometric simulations correctly identify and explore large amplitudes of motion, while molecular dynamics simulations indicate the ranges of motion that are energetically feasible. Together, the simulation approaches are able to reveal unexpected functionally relevant motions, and highlight differences between enzymes. PMID:26241964

Intrinsic functional network architecture of human semantic processing: Modules and hubs.

PubMed

Xu, Yangwen; Lin, Qixiang; Han, Zaizhu; He, Yong; Bi, Yanchao

2016-05-15

Semantic processing entails the activation of widely distributed brain areas across the temporal, parietal, and frontal lobes. To understand the functional structure of this semantic system, we examined its intrinsic functional connectivity pattern using a database of 146 participants. Focusing on areas consistently activated during semantic processing generated from a meta-analysis of 120 neuroimaging studies (Binder et al., 2009), we found that these regions were organized into three stable modules corresponding to the default mode network (Module DMN), the left perisylvian network (Module PSN), and the left frontoparietal network (Module FPN). These three dissociable modules were integrated by multiple connector hubs-the left angular gyrus (AG) and the left superior/middle frontal gyrus linking all three modules, the left anterior temporal lobe linking Modules DMN and PSN, the left posterior portion of dorsal intraparietal sulcus (IPS) linking Modules DMN and FPN, and the left posterior middle temporal gyrus (MTG) linking Modules PSN and FPN. Provincial hubs, which converge local information within each system, were also identified: the bilateral posterior cingulate cortices/precuneus, the bilateral border area of the posterior AG and the superior lateral occipital gyrus for Module DMN; the left supramarginal gyrus, the middle part of the left MTG and the left orbital inferior frontal gyrus (IFG) for Module FPN; and the left triangular IFG and the left IPS for Module FPN. A neuro-functional model for semantic processing was derived based on these findings, incorporating the interactions of memory, language, and control. Copyright © 2016 Elsevier Inc. All rights reserved.

Binding Mechanisms of Intrinsically Disordered Proteins: Theory, Simulation, and Experiment

PubMed Central

Mollica, Luca; Bessa, Luiza M.; Hanoulle, Xavier; Jensen, Malene Ringkjøbing; Blackledge, Martin; Schneider, Robert

2016-01-01

In recent years, protein science has been revolutionized by the discovery of intrinsically disordered proteins (IDPs). In contrast to the classical paradigm that a given protein sequence corresponds to a defined structure and an associated function, we now know that proteins can be functional in the absence of a stable three-dimensional structure. In many cases, disordered proteins or protein regions become structured, at least locally, upon interacting with their physiological partners. Many, sometimes conflicting, hypotheses have been put forward regarding the interaction mechanisms of IDPs and the potential advantages of disorder for protein-protein interactions. Whether disorder may increase, as proposed, e.g., in the “fly-casting” hypothesis, or decrease binding rates, increase or decrease binding specificity, or what role pre-formed structure might play in interactions involving IDPs (conformational selection vs. induced fit), are subjects of intense debate. Experimentally, these questions remain difficult to address. Here, we review experimental studies of binding mechanisms of IDPs using NMR spectroscopy and transient kinetic techniques, as well as the underlying theoretical concepts and numerical methods that can be applied to describe these interactions at the atomic level. The available literature suggests that the kinetic and thermodynamic parameters characterizing interactions involving IDPs can vary widely and that there may be no single common mechanism that can explain the different binding modes observed experimentally. Rather, disordered proteins appear to make combined use of features such as pre-formed structure and flexibility, depending on the individual system and the functional context. PMID:27668217

The Touch and Zap method for in vivo whole-cell patch recording of intrinsic and visual responses of cortical neurons and glial cells.

PubMed

Schramm, Adrien E; Marinazzo, Daniele; Gener, Thomas; Graham, Lyle J

2014-01-01

Whole-cell patch recording is an essential tool for quantitatively establishing the biophysics of brain function, particularly in vivo. This method is of particular interest for studying the functional roles of cortical glial cells in the intact brain, which cannot be assessed with extracellular recordings. Nevertheless, a reasonable success rate remains a challenge because of stability, recording duration and electrical quality constraints, particularly for voltage clamp, dynamic clamp or conductance measurements. To address this, we describe "Touch and Zap", an alternative method for whole-cell patch clamp recordings, with the goal of being simpler, quicker and more gentle to brain tissue than previous approaches. Under current clamp mode with a continuous train of hyperpolarizing current pulses, seal formation is initiated immediately upon cell contact, thus the "Touch". By maintaining the current injection, whole-cell access is spontaneously achieved within seconds from the cell-attached configuration by a self-limited membrane electroporation, or "Zap", as seal resistance increases. We present examples of intrinsic and visual responses of neurons and putative glial cells obtained with the revised method from cat and rat cortices in vivo. Recording parameters and biophysical properties obtained with the Touch and Zap method compare favourably with those obtained with the traditional blind patch approach, demonstrating that the revised approach does not compromise the recorded cell. We find that the method is particularly well-suited for whole-cell patch recordings of cortical glial cells in vivo, targeting a wider population of this cell type than the standard method, with better access resistance. Overall, the gentler Touch and Zap method is promising for studying quantitative functional properties in the intact brain with minimal perturbation of the cell's intrinsic properties and local network. Because the Touch and Zap method is performed semi-automatically, this approach is more reproducible and less dependent on experimenter technique.

The Touch and Zap Method for In Vivo Whole-Cell Patch Recording of Intrinsic and Visual Responses of Cortical Neurons and Glial Cells

PubMed Central

Schramm, Adrien E.; Marinazzo, Daniele; Gener, Thomas; Graham, Lyle J.

2014-01-01

Whole-cell patch recording is an essential tool for quantitatively establishing the biophysics of brain function, particularly in vivo. This method is of particular interest for studying the functional roles of cortical glial cells in the intact brain, which cannot be assessed with extracellular recordings. Nevertheless, a reasonable success rate remains a challenge because of stability, recording duration and electrical quality constraints, particularly for voltage clamp, dynamic clamp or conductance measurements. To address this, we describe “Touch and Zap”, an alternative method for whole-cell patch clamp recordings, with the goal of being simpler, quicker and more gentle to brain tissue than previous approaches. Under current clamp mode with a continuous train of hyperpolarizing current pulses, seal formation is initiated immediately upon cell contact, thus the “Touch”. By maintaining the current injection, whole-cell access is spontaneously achieved within seconds from the cell-attached configuration by a self-limited membrane electroporation, or “Zap”, as seal resistance increases. We present examples of intrinsic and visual responses of neurons and putative glial cells obtained with the revised method from cat and rat cortices in vivo. Recording parameters and biophysical properties obtained with the Touch and Zap method compare favourably with those obtained with the traditional blind patch approach, demonstrating that the revised approach does not compromise the recorded cell. We find that the method is particularly well-suited for whole-cell patch recordings of cortical glial cells in vivo, targeting a wider population of this cell type than the standard method, with better access resistance. Overall, the gentler Touch and Zap method is promising for studying quantitative functional properties in the intact brain with minimal perturbation of the cell's intrinsic properties and local network. Because the Touch and Zap method is performed semi-automatically, this approach is more reproducible and less dependent on experimenter technique. PMID:24875855

Unlearning chronic pain: A randomized controlled trial to investigate changes in intrinsic brain connectivity following Cognitive Behavioral Therapy

PubMed Central

Shpaner, Marina; Kelly, Clare; Lieberman, Greg; Perelman, Hayley; Davis, Marcia; Keefe, Francis J.; Naylor, Magdalena R.

2014-01-01

Chronic pain is a complex physiological and psychological phenomenon. Implicit learning mechanisms contribute to the development of chronic pain and to persistent changes in the central nervous system. We hypothesized that these central abnormalities can be remedied with Cognitive Behavioral Therapy (CBT). Specifically, since regions of the anterior Default Mode Network (DMN) are centrally involved in emotional regulation via connections with limbic regions, such as the amygdala, remediation of maladaptive behavioral and cognitive patterns as a result of CBT for chronic pain would manifest itself as a change in the intrinsic functional connectivity (iFC) between these prefrontal and limbic regions. Resting-state functional neuroimaging was performed in patients with chronic pain before and after 11-week CBT (n = 19), as well as a matched (ages 19–59, both sexes) active control group of patients who received educational materials (n = 19). Participants were randomized prior to the intervention. To investigate the differential impact of treatment on intrinsic functional connectivity (iFC), we compared pre–post differences in iFC between groups. In addition, we performed exploratory whole brain analyses of changes in fractional amplitude of low frequency fluctuations (fALFF). The course of CBT led to significant improvements in clinical measures of pain and self-efficacy for coping with chronic pain. Significant group differences in pre–post changes in both iFC and fALFF were correlated with clinical outcomes. Compared to control patients, iFC between the anterior DMN and the amygdala/periaqueductal gray decreased following CBT, whereas iFC between the basal ganglia network and the right secondary somatosensory cortex increased following CBT. CBT patients also had increased post-therapy fALFF in the bilateral posterior cingulate and the cerebellum. By delineating neuroplasticity associated with CBT-related improvements, these results add to mounting evidence that CBT is a valuable treatment option for chronic pain. PMID:26958466

Intracavity vortex beam generation

NASA Astrophysics Data System (ADS)

Naidoo, Darryl; Aït-Ameur, Kamel; Forbes, Andrew

2011-10-01

In this paper we explore vortex beams and in particular the generation of single LG0l modes and superpositions thereof. Vortex beams carry orbital angular momentum (OAM) and this intrinsic property makes them prevalent in transferring this OAM to matter and to be used in quantum information processing. We explore an extra-cavity and intra-cavity approach in LG0l mode generation respectively. The outputs of a Porro-prism resonator are represented by "petals" and we show that through a full modal decomposition, the "petal" fields are a superposition of two LG0l modes.

Soft Phonon Modes Leading to Ultralow Thermal Conductivity and High Thermoelectric Performance in AgCuTe.

PubMed

Roychowdhury, Subhajit; Jana, Manoj K; Pan, Jaysree; Guin, Satya N; Sanyal, Dirtha; Waghmare, Umesh V; Biswas, Kanishka

2018-04-03

Crystalline solids with intrinsically low lattice thermal conductivity (κ L ) are crucial to realizing high-performance thermoelectric (TE) materials. Herein, we show an ultralow κ L of 0.35 Wm -1  K -1 in AgCuTe, which has a remarkable TE figure-of-merit, zT of 1.6 at 670 K when alloyed with 10 mol % Se. First-principles DFT calculation reveals several soft phonon modes in its room-temperature hexagonal phase, which are also evident from low-temperature heat-capacity measurement. These phonon modes, dominated by Ag vibrations, soften further with temperature giving a dynamic cation disorder and driving the superionic transition. Intrinsic factors cause an ultralow κ L in the room-temperature hexagonal phase, while the dynamic disorder of Ag/Cu cations leads to reduced phonon frequencies and mean free paths in the high-temperature rocksalt phase. Despite the cation disorder at elevated temperatures, the crystalline conduits of the rigid anion sublattice give a high power factor. © 2018 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.

Planar quadrature RF transceiver design using common-mode differential-mode (CMDM) transmission line method for 7T MR imaging.

PubMed

Li, Ye; Yu, Baiying; Pang, Yong; Vigneron, Daniel B; Zhang, Xiaoliang

2013-01-01

The use of quadrature RF magnetic fields has been demonstrated to be an efficient method to reduce transmit power and to increase the signal-to-noise (SNR) in magnetic resonance (MR) imaging. The goal of this project was to develop a new method using the common-mode and differential-mode (CMDM) technique for compact, planar, distributed-element quadrature transmit/receive resonators for MR signal excitation and detection and to investigate its performance for MR imaging, particularly, at ultrahigh magnetic fields. A prototype resonator based on CMDM method implemented by using microstrip transmission line was designed and fabricated for 7T imaging. Both the common mode (CM) and the differential mode (DM) of the resonator were tuned and matched at 298MHz independently. Numerical electromagnetic simulation was performed to verify the orthogonal B1 field direction of the two modes of the CMDM resonator. Both workbench tests and MR imaging experiments were carried out to evaluate the performance. The intrinsic decoupling between the two modes of the CMDM resonator was demonstrated by the bench test, showing a better than -36 dB transmission coefficient between the two modes at resonance frequency. The MR images acquired by using each mode and the images combined in quadrature showed that the CM and DM of the proposed resonator provided similar B1 coverage and achieved SNR improvement in the entire region of interest. The simulation and experimental results demonstrate that the proposed CMDM method with distributed-element transmission line technique is a feasible and efficient technique for planar quadrature RF coil design at ultrahigh fields, providing intrinsic decoupling between two quadrature channels and high frequency capability. Due to its simple and compact geometry and easy implementation of decoupling methods, the CMDM quadrature resonator can possibly be a good candidate for design blocks in multichannel RF coil arrays.

On the ρ ∗ scaling of intrinsic rotation in C-Mod plasmas with edge transport barriers

NASA Astrophysics Data System (ADS)

Rice, J. E.; Hughes, J. W.; Diamond, P. H.; Cao, N.; Chilenski, M. A.; Hubbard, A. E.; Irby, J. H.; Kosuga, Y.; Lin, Y.; Metcalf, I. W.; Reinke, M. L.; Tolman, E. A.; Victora, M. M.; Wolfe, S. M.; Wukitch, S. J.

2017-11-01

Changes in the core intrinsic toroidal rotation velocity following L- to H- and L- to I-mode transitions have been investigated in Alcator C-Mod tokamak plasmas. The magnitude of the co-current rotation increments is found to increase with the pedestal temperature gradient and q95 , and to decrease with toroidal magnetic field. These results are captured quantitatively by a model of fluctuation entropy balance which gives the Mach number Mi \\cong ρ _*/2 L_s/LT ∼ \

Functional Anthology of Intrinsic Disorder. I. Biological Processes and Functions of Proteins with Long Disordered Regions

PubMed Central

Xie, Hongbo; Vucetic, Slobodan; Iakoucheva, Lilia M.; Oldfield, Christopher J.; Dunker, A. Keith; Uversky, Vladimir N.; Obradovic, Zoran

2008-01-01

Identifying relationships between function, amino acid sequence and protein structure represents a major challenge. In this study we propose a bioinformatics approach that identifies functional keywords in the Swiss-Prot database that correlate with intrinsic disorder. A statistical evaluation is employed to rank the significance of these correlations. Protein sequence data redundancy and the relationship between protein length and protein structure were taken into consideration to ensure the quality of the statistical inferences. Over 200,000 proteins from Swiss-Prot database were analyzed using this approach. The predictions of intrinsic disorder were carried out using PONDR VL3E predictor of long disordered regions that achieves an accuracy of above 86%. Overall, out of the 710 Swiss-Prot functional keywords that were each associated with at least 20 proteins, 238 were found to be strongly positively correlated with predicted long intrinsically disordered regions, whereas 302 were strongly negatively correlated with such regions. The remaining 170 keywords were ambiguous without strong positive or negative correlation with the disorder predictions. These functions cover a large variety of biological activities and imply that disordered regions are characterized by a wide functional repertoire. Our results agree well with literature findings, as we were able to find at least one illustrative example of functional disorder or order shown experimentally for the vast majority of keywords showing the strongest positive or negative correlation with intrinsic disorder. This work opens a series of three papers, which enriches the current view of protein structure-function relationships, especially with regards to functionalities of intrinsically disordered proteins and provides researchers with a novel tool that could be used to improve the understanding of the relationships between protein structure and function. The first paper of the series describes our statistical approach, outlines the major findings and provides illustrative examples of biological processes and functions positively and negatively correlated with intrinsic disorder. PMID:17391014

Functional anthology of intrinsic disorder. 1. Biological processes and functions of proteins with long disordered regions.

PubMed

Xie, Hongbo; Vucetic, Slobodan; Iakoucheva, Lilia M; Oldfield, Christopher J; Dunker, A Keith; Uversky, Vladimir N; Obradovic, Zoran

2007-05-01

Identifying relationships between function, amino acid sequence, and protein structure represents a major challenge. In this study, we propose a bioinformatics approach that identifies functional keywords in the Swiss-Prot database that correlate with intrinsic disorder. A statistical evaluation is employed to rank the significance of these correlations. Protein sequence data redundancy and the relationship between protein length and protein structure were taken into consideration to ensure the quality of the statistical inferences. Over 200,000 proteins from the Swiss-Prot database were analyzed using this approach. The predictions of intrinsic disorder were carried out using PONDR VL3E predictor of long disordered regions that achieves an accuracy of above 86%. Overall, out of the 710 Swiss-Prot functional keywords that were each associated with at least 20 proteins, 238 were found to be strongly positively correlated with predicted long intrinsically disordered regions, whereas 302 were strongly negatively correlated with such regions. The remaining 170 keywords were ambiguous without strong positive or negative correlation with the disorder predictions. These functions cover a large variety of biological activities and imply that disordered regions are characterized by a wide functional repertoire. Our results agree well with literature findings, as we were able to find at least one illustrative example of functional disorder or order shown experimentally for the vast majority of keywords showing the strongest positive or negative correlation with intrinsic disorder. This work opens a series of three papers, which enriches the current view of protein structure-function relationships, especially with regards to functionalities of intrinsically disordered proteins, and provides researchers with a novel tool that could be used to improve the understanding of the relationships between protein structure and function. The first paper of the series describes our statistical approach, outlines the major findings, and provides illustrative examples of biological processes and functions positively and negatively correlated with intrinsic disorder.

Altered functional connectivity density in patients with herpes zoster and postherpetic neuralgia.

PubMed

Hong, Shunda; Gu, Lili; Zhou, Fuqing; Liu, Jiaqi; Huang, Muhua; Jiang, Jian; He, Laichang; Gong, Honghan; Zeng, Xianjun

2018-01-01

The aim of this study was to explore intrinsic functional connectivity patterns in patients with herpes zoster (HZ) and postherpetic neuralgia (PHN). Thirty-three right-handed HZ patients (13 males; mean age 57.15±9.30 years), 22 right-handed PHN patients (9 males; mean age 66.13±6.77 years), and 28 well-matched healthy controls (HC) (9 males; mean age 54.21±7.72 years) underwent resting-state functional magnetic resonance imaging for intrinsic functional connectivity analyses. Functional connectivity density (FCD) was calculated and compared among the PHN, HZ, and HC groups. In addition, the Pearson correlation coefficient was calculated to compare various clinical indices in the regions with abnormal FCD values. Compared with the HC, both HZ and PHN patients showed significantly decreased FCD in the precuneus, and patients with HZ displayed significantly increased FCD in the brainstem/limbic lobe/parahippocampalgyrus, whereas patients with PHN displayed significantly increased FCD in the hippocampus (correlation thresholds r =0.25, voxel level of P <0.01 and Gaussian random field theory at a cluster level of P <0.05). However, the FCD was not significantly different between the PHN and HZ patients. Furthermore, the decreased FCD in the precuneus was positively correlated with the visual analog scale score in the PHN group ( r =0.672; P =0.001). Decreased connectivity of the precuneus occurred in both HZ and PHN patients, indicating a disrupted default-mode network. Furthermore, in the HZ group (initial stage of the virus infection), hyperconnectivity was observed in systems involved in pain transmission and interpretation, but hyperconnectivity only occurred in the hippocampus in the PHN group (neuropathic pain stage).

Altered intrinsic organisation of brain networks implicated in attentional processes in adult attention-deficit/hyperactivity disorder: a resting-state study of attention, default mode and salience network connectivity.

PubMed

Sidlauskaite, Justina; Sonuga-Barke, Edmund; Roeyers, Herbert; Wiersema, Jan R

2016-06-01

Deficits in task-related attentional engagement in attention-deficit/hyperactivity disorder (ADHD) have been hypothesised to be due to altered interrelationships between attention, default mode and salience networks. We examined the intrinsic connectivity during rest within and between these networks. Six-minute resting-state scans were obtained. Using a network-based approach, connectivity within and between the dorsal and ventral attention, the default mode and the salience networks was compared between the ADHD and control group. The ADHD group displayed hyperconnectivity between the two attention networks and within the default mode and ventral attention network. The salience network was hypoconnected to the dorsal attention network. There were trends towards hyperconnectivity within the dorsal attention network and between the salience and ventral attention network in ADHD. Connectivity within and between other networks was unrelated to ADHD. Our findings highlight the altered connectivity within and between attention networks, and between them and the salience network in ADHD. One hypothesis to be tested in future studies is that individuals with ADHD are affected by an imbalance between ventral and dorsal attention systems with the former playing a dominant role during task engagement, making individuals with ADHD highly susceptible to distraction by salient task-irrelevant stimuli.

Changes in Intrinsic Motivation as a Function of Negative Feedback and Threats.

ERIC Educational Resources Information Center

Deci, Edward L.; Cascio, Wayne F.

Recent studies have demonstrated that external rewards can affect intrinsic motivation to perform an activity. Money tends to decrease intrinsic motivation, whereas positive verbal reinforcements tend to increase intrinsic motivation. This paper presents evidence that negative feedback and threats of punishment also decrease intrinsic motivation.…

Effect of q-profile structure on intrinsic torque reversals

NASA Astrophysics Data System (ADS)

Lu, Zhixin

2014-10-01

Intrinsic toroidal rotation plays an important role in mitigating macroinstability and regulating turbulent transport in ITER, where neutral beams are not sufficient to provide the requisite torque. Recent experiments on C-Mod with LHCD observed rotation reversal related to a change in the q profile. In this work, we focus on understanding the physics of intrinsic rotation reversals in LHCD plasmas, using nonlinear, global gyro-kinetic simulations and analysis of mode structure and spectrum symmetry breaking. The sensitive dependence of turbulent residual stress on magnetic shear is identified and characterized. The basic residual stress is non-vanishing when the k-parallel spectrum symmetry is broken, e.g., by E × B shear induced radial shift, non-uniformity in turbulence intensity, etc.. It is found that at low magnetic shear, the poloidal harmonics can shift strongly in the radial direction, as a feature of non-local effects, due to radial propagation and amplitude variation of the mode. This new symmetry breaking mechanism leads to a change in the sign of spectrum averaged parallel wave vector and thus the direction of intrinsic torque. Theoretical study shows that the competition between magnetic drift and ion kinetic effects determines the non-local effects and the structure of the asymmetry. Specifically, it is found that the direction of the intrinsic torque changes from counter- to co-current in the core, when magnetic shear decreases through a critical value. A critical shear ŝR = 0 . 2 ~ 0 . 5 for reversal of CTEM-induced intrinsic torque found by simulation is consistent with that from the LHCD C-Mod reversal experiments. In addition, simulations indicate ŝR = 1 ~ 2 for the reversal of ITG-induced torque, a prediction which can be tested by experiments. This work is supported by CER and CMTFO, UCSD and U.S. DOE-PPPL Contract DE-AC02-09CH11466.

Abnormal brain functional connectivity leads to impaired mood and cognition in hyperthyroidism: a resting-state functional MRI study

PubMed Central

Li, Ling; Zhi, Mengmeng; Hou, Zhenghua; Zhang, Yuqun; Yue, Yingying; Yuan, Yonggui

2017-01-01

Patients with hyperthyroidism frequently have neuropsychiatric complaints such as lack of concentration, poor memory, depression, anxiety, nervousness, and irritability, suggesting brain dysfunction. However, the underlying process of these symptoms remains unclear. Using resting-state functional magnetic resonance imaging (rs-fMRI), we depicted the altered graph theoretical metric degree centrality (DC) and seed-based resting-state functional connectivity (FC) in 33 hyperthyroid patients relative to 33 healthy controls. The peak points of significantly altered DC between the two groups were defined as the seed regions to calculate FC to the whole brain. Then, partial correlation analyses were performed between abnormal DC, FC and neuropsychological performances, as well as some clinical indexes. The decreased intrinsic functional connectivity in the posterior lobe of cerebellum (PLC) and medial frontal gyrus (MeFG), as well as the abnormal seed-based FC anchored in default mode network (DMN), attention network, visual network and cognitive network in this study, possibly constitutes the latent mechanism for emotional and cognitive changes in hyperthyroidism, including anxiety and impaired processing speed. PMID:28009983

Abnormal brain functional connectivity leads to impaired mood and cognition in hyperthyroidism: a resting-state functional MRI study.

PubMed

Li, Ling; Zhi, Mengmeng; Hou, Zhenghua; Zhang, Yuqun; Yue, Yingying; Yuan, Yonggui

2017-01-24

Patients with hyperthyroidism frequently have neuropsychiatric complaints such as lack of concentration, poor memory, depression, anxiety, nervousness, and irritability, suggesting brain dysfunction. However, the underlying process of these symptoms remains unclear. Using resting-state functional magnetic resonance imaging (rs-fMRI), we depicted the altered graph theoretical metric degree centrality (DC) and seed-based resting-state functional connectivity (FC) in 33 hyperthyroid patients relative to 33 healthy controls. The peak points of significantly altered DC between the two groups were defined as the seed regions to calculate FC to the whole brain. Then, partial correlation analyses were performed between abnormal DC, FC and neuropsychological performances, as well as some clinical indexes. The decreased intrinsic functional connectivity in the posterior lobe of cerebellum (PLC) and medial frontal gyrus (MeFG), as well as the abnormal seed-based FC anchored in default mode network (DMN), attention network, visual network and cognitive network in this study, possibly constitutes the latent mechanism for emotional and cognitive changes in hyperthyroidism, including anxiety and impaired processing speed.

Amygdala-cingulate intrinsic connectivity is associated with degree of social inhibition

PubMed Central

Blackford, Jennifer Urbano; Clauss, Jacqueline A.; Avery, Suzanne N.; Cowan, Ronald L.; Benningfield, Margaret M.; VanDerKlok, Ross M.

2014-01-01

The tendency to approach or avoid novel people is a fundamental human behavior and is a core dimension of social anxiety. Resting state fMRI was used to test for an association between social inhibition and intrinsic connectivity in 40 young adults ranging from low to high in social inhibition. Higher levels of social inhibition were associated with specific patterns of reduced amygdala-cingulate cortex connectivity. Connectivity was reduced between the superficial amygdala and the rostral cingulate cortex and between the centromedial amygdala and the dorsal anterior cingulate cortex. Social inhibition also modulated connectivity in several well-established intrinsic networks; higher social inhibition correlated with reduced connectivity with default mode and dorsal attention networks and enhanced connectivity in salience and executive control networks. These findings provide important preliminary evidence that social inhibition reflects differences in the underlying intrinsic connectivity of the brain in the absence of social stimuli or stressors. PMID:24534162

Deciphering death: a commentary on Gompertz (1825) ‘On the nature of the function expressive of the law of human mortality, and on a new mode of determining the value of life contingencies’

PubMed Central

Kirkwood, Thomas B. L.

2015-01-01

In 1825, the actuary Benjamin Gompertz read a paper, ‘On the nature of the function expressive of the law of human mortality, and on a new mode of determining the value of life contingencies’, to the Royal Society in which he showed that over much of the adult human lifespan, age-specific mortality rates increased in an exponential manner. Gompertz's work played an important role in shaping the emerging statistical science that underpins the pricing of life insurance and annuities. Latterly, as the subject of ageing itself became the focus of scientific study, the Gompertz model provided a powerful stimulus to examine the patterns of death across the life course not only in humans but also in a wide range of other organisms. The idea that the Gompertz model might constitute a fundamental ‘law of mortality’ has given way to the recognition that other patterns exist, not only across the species range but also in advanced old age. Nevertheless, Gompertz's way of representing the function expressive of the pattern of much of adult mortality retains considerable relevance for studying the factors that influence the intrinsic biology of ageing. This commentary was written to celebrate the 350th anniversary of the journal Philosophical Transactions of the Royal Society. PMID:25750242

Deciphering death: a commentary on Gompertz (1825) 'On the nature of the function expressive of the law of human mortality, and on a new mode of determining the value of life contingencies'.

PubMed

Kirkwood, Thomas B L

2015-04-19

In 1825, the actuary Benjamin Gompertz read a paper, 'On the nature of the function expressive of the law of human mortality, and on a new mode of determining the value of life contingencies', to the Royal Society in which he showed that over much of the adult human lifespan, age-specific mortality rates increased in an exponential manner. Gompertz's work played an important role in shaping the emerging statistical science that underpins the pricing of life insurance and annuities. Latterly, as the subject of ageing itself became the focus of scientific study, the Gompertz model provided a powerful stimulus to examine the patterns of death across the life course not only in humans but also in a wide range of other organisms. The idea that the Gompertz model might constitute a fundamental 'law of mortality' has given way to the recognition that other patterns exist, not only across the species range but also in advanced old age. Nevertheless, Gompertz's way of representing the function expressive of the pattern of much of adult mortality retains considerable relevance for studying the factors that influence the intrinsic biology of ageing. This commentary was written to celebrate the 350th anniversary of the journal Philosophical Transactions of the Royal Society.

Conformational Changes of Trialanine in Water Induced by Vibrational Relaxation of the Amide I Mode.

PubMed

Bastida, Adolfo; Zúñiga, José; Requena, Alberto; Miguel, Beatriz; Candela, María Emilia; Soler, Miguel Angel

2016-01-21

Most of the protein-based diseases are caused by anomalies in the functionality and stability of these molecules. Experimental and theoretical studies of the conformational dynamics of proteins are becoming in this respect essential to understand the origin of these anomalies. However, a description of the conformational dynamics of proteins based on mechano-energetic principles still remains elusive because of the intrinsic high flexibility of the peptide chains, the participation of weak noncovalent interactions, and the role of the ubiquitous water solvent. In this work, the conformational dynamics of trialanine dissolved in water (D2O) is investigated through Molecular Dynamics (MD) simulations combined with instantaneous normal modes (INMs) analysis both at equilibrium and after the vibrational excitation of the C-terminal amide I mode. The conformational equilibrium between α and pPII conformers is found to be altered by the intramolecular relaxation of the amide I mode as a consequence of the different relaxation pathways of each conformer which modify the amount of vibrational energy stored in the torsional motions of the tripeptide, so the α → pPII and pPII → α conversion rates are increased differently. The selectivity of the process comes from the shifts of the vibrational frequencies with the conformational changes that modify the resonance conditions driving the intramolecular energy flows.

How we may think: Imaging and writing technologies across the history of the neurosciences.

PubMed

Borck, Cornelius

2016-06-01

In the neurosciences, two alternative regimes of visualization can be differentiated: anatomical preparations for morphological images and physiological studies for functional representations. Adapting a distinction proposed by Peter Galison, this duality of visualization regimes is analyzed here as the contrast between an imaging and a writing approach: the imaging approach, focusing on mimetic representations, preserving material and spatial relations, and the writing approach as used in physiological studies, retaining functional relations. After a dominance of morphological images gathering iconic representations of brains and architectural brain theories, the advent of electroencephalography advanced writing approaches with their indexical signs. Addressing the brain allegedly at its mode of operation, electroencephalography was conceived as recording the brain's intrinsic language, extending the writing approach to include symbolic signs. The availability of functional neuroimaging signaled an opportunity to overcome the duality of imaging and writing, but revived initially a phrenological conflation of form and function, suppressing the writing approach in relation to imaging. More sophisticated visualization modes, however, converted this reductionism to the ontological productivity of social neuroscience and recuperated the theorizing from the writing approach. In light of the ongoing instrumental mediations between brains, data and theories, the question of how we may think, once proposed by Vannevar Bush as a prospect of enhanced human-machine interaction, has become the state of affairs in the entanglements of instruments and organic worlds. Copyright © 2016 Elsevier Ltd. All rights reserved.

Charge pattern matching as a ‘fuzzy’ mode of molecular recognition for the functional phase separations of intrinsically disordered proteins

NASA Astrophysics Data System (ADS)

Lin, Yi-Hsuan; Brady, Jacob P.; Forman-Kay, Julie D.; Chan, Hue Sun

2017-11-01

Biologically functional liquid-liquid phase separation of intrinsically disordered proteins (IDPs) is driven by interactions encoded by their amino acid sequences. Little is currently known about the molecular recognition mechanisms for distributing different IDP sequences into various cellular membraneless compartments. Pertinent physics was addressed recently by applying random-phase-approximation (RPA) polymer theory to electrostatics, which is a major energetic component governing IDP phase properties. RPA accounts for charge patterns and thus has advantages over Flory-Huggins (FH) and Overbeek-Voorn mean-field theories. To make progress toward deciphering the phase behaviors of multiple IDP sequences, the RPA formulation for one IDP species plus solvent is hereby extended to treat polyampholyte solutions containing two IDP species plus solvent. The new formulation generally allows for binary coexistence of two phases, each containing a different set of volume fractions ({φ }1,{φ }2) for the two different IDP sequences. The asymmetry between the two predicted coexisting phases with regard to their {φ }1/{φ }2 ratios for the two sequences increases with increasing mismatch between their charge patterns. This finding points to a multivalent, stochastic, ‘fuzzy’ mode of molecular recognition that helps populate various IDP sequences differentially into separate phase compartments. An intuitive illustration of this trend is provided by FH models, whereby a hypothetical case of ternary coexistence is also explored. Augmentations of the present RPA theory with a relative permittivity {ɛ }{{r}}(φ ) that depends on IDP volume fraction φ ={φ }1+{φ }2 lead to higher propensities to phase separate, in line with the case with one IDP species we studied previously. Notably, the cooperative, phase-separation-enhancing effects predicted by the prescriptions for {ɛ }{{r}}(φ ) we deem physically plausible are much more prominent than that entailed by common effective medium approximations based on Maxwell Garnett and Bruggeman mixing formulas. Ramifications of our findings on further theoretical development for IDP phase separation are discussed.

Unsteady locomotion: integrating muscle function with whole body dynamics and neuromuscular control

PubMed Central

Biewener, Andrew A.; Daley, Monica A.

2009-01-01

Summary By integrating studies of muscle function with analysis of whole body and limb dynamics, broader appreciation of neuromuscular function can be achieved. Ultimately, such studies need to address non-steady locomotor behaviors relevant to animals in their natural environments. When animals move slowly they likely rely on voluntary coordination of movement involving higher brain centers. However, when moving fast, their movements depend more strongly on responses controlled at more local levels. Our focus here is on control of fast-running locomotion. A key observation emerging from studies of steady level locomotion is that simple spring-mass dynamics, which help to economize energy expenditure, also apply to stabilization of unsteady running. Spring-mass dynamics apply to conditions that involve lateral impulsive perturbations, sudden changes in terrain height, and sudden changes in substrate stiffness or damping. Experimental investigation of unsteady locomotion is challenging, however, due to the variability inherent in such behaviors. Another emerging principle is that initial conditions associated with postural changes following a perturbation define different context-dependent stabilization responses. Distinct stabilization modes following a perturbation likely result from proximo-distal differences in limb muscle architecture, function and control strategy. Proximal muscles may be less sensitive to sudden perturbations and appear to operate, in such circumstances, under feed-forward control. In contrast, multiarticular distal muscles operate, via their tendons, to distribute energy among limb joints in a manner that also depends on the initial conditions of limb contact with the ground. Intrinsic properties of these distal muscle–tendon elements, in combination with limb and body dynamics, appear to provide rapid initial stabilizing mechanisms that are often consistent with spring-mass dynamics. These intrinsic mechanisms likely help to simplify the neural control task, in addition to compensating for delays inherent to subsequent force- and length-dependent neural feedback. Future work will benefit from integrative biomechanical approaches that employ a combination of modeling and experimental techniques to understand how the elegant interplay of intrinsic muscle properties, body dynamics and neural control allows animals to achieve stability and agility over a variety of conditions. PMID:17704070

A novel hybrid ensemble learning paradigm for tourism forecasting

NASA Astrophysics Data System (ADS)

Shabri, Ani

2015-02-01

In this paper, a hybrid forecasting model based on Empirical Mode Decomposition (EMD) and Group Method of Data Handling (GMDH) is proposed to forecast tourism demand. This methodology first decomposes the original visitor arrival series into several Intrinsic Model Function (IMFs) components and one residual component by EMD technique. Then, IMFs components and the residual components is forecasted respectively using GMDH model whose input variables are selected by using Partial Autocorrelation Function (PACF). The final forecasted result for tourism series is produced by aggregating all the forecasted results. For evaluating the performance of the proposed EMD-GMDH methodologies, the monthly data of tourist arrivals from Singapore to Malaysia are used as an illustrative example. Empirical results show that the proposed EMD-GMDH model outperforms the EMD-ARIMA as well as the GMDH and ARIMA (Autoregressive Integrated Moving Average) models without time series decomposition.

A study of the chiro-optical properties of Carvone

NASA Astrophysics Data System (ADS)

Lambert, Jason

2011-10-01

The intrinsic optical rotatory dispersion (IORD) and circular dichroism (CD) of the conformationally flexible carvone molecule has been investigated in 17 solvents and compared with results from calculations for the ``free'' (gas phase) molecule. The G3 method was used to determine the relative energies of the six conformers. The ORD of (R)-(-)-carvone at 589 nm was calculated using coupled cluster and density-functional methods, including temperature-dependent vibrational corrections. Vibrational corrections are significant and are primarily associated with normal modes involving the stereogenic carbon atom and the carbonyl group, whose n->&*circ; excitation plays a significant role in the chiroptical response of carvone. However, without the vibrational correction the calculated ORD is of opposite sign to that of the experiment for the CCSD and B3LYP methods. Calculations performed in solution using the PCM model were also opposite in sign to of the experiment when using the B3LYP density functional.

Intrinsic synchronization of an array of spin-torque oscillators driven by the spin-Hall effect

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

Siracusano, G., E-mail: giuliosiracusano@gmail.com; Puliafito, V.; Giordano, A.

2015-05-07

This paper micromagnetically studies the magnetization dynamics driven by the spin-Hall effect in a Platinum/Permalloy bi-layer. For a certain field and current range, the excitation of a uniform mode, characterized by a power with a spatial distribution in the whole ferromagnetic cross section, is observed. We suggest to use the ferromagnet of the bi-layer as basis for the realization of an array of spin-torque oscillators (STOs): the Permalloy ferromagnet will act as shared free layer, whereas the spacers and the polarizers are built on top of it. Following this strategy, the frequency of the uniform mode will be the samemore » for the whole device, creating an intrinsic synchronization. The synchronization of an array of parallely connected STOs will allow to increase the output power, as necessary for technological applications.« less

Vertical integration of high-Q silicon nitride microresonators into silicon-on-insulator platform.

PubMed

Li, Qing; Eftekhar, Ali A; Sodagar, Majid; Xia, Zhixuan; Atabaki, Amir H; Adibi, Ali

2013-07-29

We demonstrate a vertical integration of high-Q silicon nitride microresonators into the silicon-on-insulator platform for applications at the telecommunication wavelengths. Low-loss silicon nitride films with a thickness of 400 nm are successfully grown, enabling compact silicon nitride microresonators with ultra-high intrinsic Qs (~ 6 × 10(6) for 60 μm radius and ~ 2 × 10(7) for 240 μm radius). The coupling between the silicon nitride microresonator and the underneath silicon waveguide is based on evanescent coupling with silicon dioxide as buffer. Selective coupling to a desired radial mode of the silicon nitride microresonator is also achievable using a pulley coupling scheme. In this work, a 60-μm-radius silicon nitride microresonator has been successfully integrated into the silicon-on-insulator platform, showing a single-mode operation with an intrinsic Q of 2 × 10(6).

Intrinsic cavity QED and emergent quasinormal modes for a single photon

NASA Astrophysics Data System (ADS)

Dong, H.; Gong, Z. R.; Ian, H.; Zhou, Lan; Sun, C. P.

2009-06-01

We propose a special cavity design that is constructed by terminating a one-dimensional waveguide with a perfect mirror at one end and doping a two-level atom at the other. We show that this atom plays the intrinsic role of a semitransparent mirror for single-photon transports such that quasinormal modes emerge spontaneously in the cavity system. This atomic mirror has its reflection coefficient tunable through its level spacing and its coupling to the cavity field, for which the cavity system can be regarded as a two-end resonator with a continuously tunable leakage. The overall investigation predicts the existence of quasibound states in the waveguide continuum. Solid-state implementations based on a dc-superconducting quantum interference device circuit and a defected line resonator embedded in a photonic crystal are illustrated to show the experimental accessibility of the generic model.

Mode-coupling mechanisms in nanocontact spin-torque oscillators

DOE PAGES

Iacocca, Ezio; Dürrenfeld, Philipp; Heinonen, Olle; ...

2015-03-11

Spin torque oscillators (STOs) are devices that allow for the excitation of a variety of magneto-dynamical modes at the nanoscale. Depending on both external conditions and intrinsic magnetic properties, STOs can exhibit regimes of mode-hopping and even mode coexistence. Whereas mode hopping has been extensively studied in STOs patterned as nanopillars, coexistence has been only recently observed for localized modes in nanocontact STOs (NC-STOs) where the current is confined to flow through a NC fabricated on an extended pseudo spin valve. We investigate the physical origin of the mode coupling mechanisms favoring coexistence, by means of electrical characterization and amore » multi-mode STO theory. Two coupling mechanisms are identified: (i) magnon mediated scattering and (ii) inter-mode interactions. These mechanisms can be physically disentangled by fabricating devices where the NCs have an elliptical cross-section. Furthermore, the generation power and linewidth from such devices are found to be in good qualitative agreement with the theoretical predictions, as well as provide evidence of the dominant mode coupling mechanisms.« less

Continuous monitoring of high-rise buildings using seismic interferometry

NASA Astrophysics Data System (ADS)

Mordret, A.; Sun, H.; Prieto, G. A.; Toksoz, M. N.; Buyukozturk, O.

2016-12-01

The linear seismic response of a building is commonly extracted from ambient vibration measurements. Seismic deconvolution interferometry performed on ambient vibration measurements can also be used to estimate the dynamic characteristics of a building, such as the velocity of shear-waves travelling inside the building as well as a damping parameter depending on the intrinsic attenuation of the building and the soil-structure coupling. The continuous nature of the ambient vibrations allows us to measure these parameters repeatedly and to observe their temporal variations. We used 2 weeks of ambient vibration recorded by 36 accelerometers installed in the Green Building on the Massachusetts Institute of Technology campus (Cambridge, MA) to continuously monitor the shear-wave speed and the attenuation factor of the building. Due to the low strain of the ambient vibrations, the observed changes are totally reversible. The relative velocity changes between a reference deconvolution function and the current deconvolution functions are measured with two different methods: 1) the Moving Window Cross-Spectral technique and 2) the stretching technique. Both methods show similar results. We show that measuring the stretching coefficient for the deconvolution functions filtered around the fundamental mode frequency is equivalent to measuring the wandering of the fundamental frequency in the raw ambient vibration data. By comparing these results with local weather parameters, we show that the relative air humidity is the factor dominating the relative seismic velocity variations in the Green Building, as well as the wandering of the fundamental mode. The one-day periodic variations are affected by both the temperature and the humidity. The attenuation factor, measured as the exponential decay of the fundamental mode waveforms, shows a more complex behaviour with respect to the weather measurements.

Extrinsic and Intrinsic Brain Network Connectivity Maintains Cognition across the Lifespan Despite Accelerated Decay of Regional Brain Activation.

PubMed

Tsvetanov, Kamen A; Henson, Richard N A; Tyler, Lorraine K; Razi, Adeel; Geerligs, Linda; Ham, Timothy E; Rowe, James B

2016-03-16

The maintenance of wellbeing across the lifespan depends on the preservation of cognitive function. We propose that successful cognitive aging is determined by interactions both within and between large-scale functional brain networks. Such connectivity can be estimated from task-free functional magnetic resonance imaging (fMRI), also known as resting-state fMRI (rs-fMRI). However, common correlational methods are confounded by age-related changes in the neurovascular signaling. To estimate network interactions at the neuronal rather than vascular level, we used generative models that specified both the neural interactions and a flexible neurovascular forward model. The networks' parameters were optimized to explain the spectral dynamics of rs-fMRI data in 602 healthy human adults from population-based cohorts who were approximately uniformly distributed between 18 and 88 years (www.cam-can.com). We assessed directed connectivity within and between three key large-scale networks: the salience network, dorsal attention network, and default mode network. We found that age influences connectivity both within and between these networks, over and above the effects on neurovascular coupling. Canonical correlation analysis revealed that the relationship between network connectivity and cognitive function was age-dependent: cognitive performance relied on neural dynamics more strongly in older adults. These effects were driven partly by reduced stability of neural activity within all networks, as expressed by an accelerated decay of neural information. Our findings suggest that the balance of excitatory connectivity between networks, and the stability of intrinsic neural representations within networks, changes with age. The cognitive function of older adults becomes increasingly dependent on these factors. Maintaining cognitive function is critical to successful aging. To study the neural basis of cognitive function across the lifespan, we studied a large population-based cohort (n = 602, 18-88 years), separating neural connectivity from vascular components of fMRI signals. Cognitive ability was influenced by the strength of connection within and between functional brain networks, and this positive relationship increased with age. In older adults, there was more rapid decay of intrinsic neuronal activity in multiple regions of the brain networks, which related to cognitive performance. Our data demonstrate increased reliance on network flexibility to maintain cognitive function, in the presence of more rapid decay of neural activity. These insights will facilitate the development of new strategies to maintain cognitive ability. Copyright © 2016 Tsvetanov et al.

Extrinsic and Intrinsic Brain Network Connectivity Maintains Cognition across the Lifespan Despite Accelerated Decay of Regional Brain Activation

PubMed Central

Henson, Richard N.A.; Tyler, Lorraine K.; Razi, Adeel; Geerligs, Linda; Ham, Timothy E.; Rowe, James B.

2016-01-01

The maintenance of wellbeing across the lifespan depends on the preservation of cognitive function. We propose that successful cognitive aging is determined by interactions both within and between large-scale functional brain networks. Such connectivity can be estimated from task-free functional magnetic resonance imaging (fMRI), also known as resting-state fMRI (rs-fMRI). However, common correlational methods are confounded by age-related changes in the neurovascular signaling. To estimate network interactions at the neuronal rather than vascular level, we used generative models that specified both the neural interactions and a flexible neurovascular forward model. The networks' parameters were optimized to explain the spectral dynamics of rs-fMRI data in 602 healthy human adults from population-based cohorts who were approximately uniformly distributed between 18 and 88 years (www.cam-can.com). We assessed directed connectivity within and between three key large-scale networks: the salience network, dorsal attention network, and default mode network. We found that age influences connectivity both within and between these networks, over and above the effects on neurovascular coupling. Canonical correlation analysis revealed that the relationship between network connectivity and cognitive function was age-dependent: cognitive performance relied on neural dynamics more strongly in older adults. These effects were driven partly by reduced stability of neural activity within all networks, as expressed by an accelerated decay of neural information. Our findings suggest that the balance of excitatory connectivity between networks, and the stability of intrinsic neural representations within networks, changes with age. The cognitive function of older adults becomes increasingly dependent on these factors. SIGNIFICANCE STATEMENT Maintaining cognitive function is critical to successful aging. To study the neural basis of cognitive function across the lifespan, we studied a large population-based cohort (n = 602, 18–88 years), separating neural connectivity from vascular components of fMRI signals. Cognitive ability was influenced by the strength of connection within and between functional brain networks, and this positive relationship increased with age. In older adults, there was more rapid decay of intrinsic neuronal activity in multiple regions of the brain networks, which related to cognitive performance. Our data demonstrate increased reliance on network flexibility to maintain cognitive function, in the presence of more rapid decay of neural activity. These insights will facilitate the development of new strategies to maintain cognitive ability. PMID:26985024

Establishing the resting state default mode network derived from functional magnetic resonance imaging tasks as an endophenotype: A twins study.

PubMed

Korgaonkar, Mayuresh S; Ram, Kaushik; Williams, Leanne M; Gatt, Justine M; Grieve, Stuart M

2014-08-01

The resting state default mode network (DMN) has been shown to characterize a number of neurological and psychiatric disorders. Evidence suggests an underlying genetic basis for this network and hence could serve as potential endophenotype for these disorders. Heritability is a defining criterion for endophenotypes. The DMN is measured either using a resting-state functional magnetic resonance imaging (fMRI) scan or by extracting resting state activity from task-based fMRI. The current study is the first to evaluate heritability of this task-derived resting activity. 250 healthy adult twins (79 monozygotic and 46 dizygotic same sex twin pairs) completed five cognitive and emotion processing fMRI tasks. Resting state DMN functional connectivity was derived from these five fMRI tasks. We validated this approach by comparing connectivity estimates from task-derived resting activity for all five fMRI tasks, with those obtained using a dedicated task-free resting state scan in an independent cohort of 27 healthy individuals. Structural equation modeling using the classic twin design was used to estimate the genetic and environmental contributions to variance for the resting-state DMN functional connectivity. About 9-41% of the variance in functional connectivity between the DMN nodes was attributed to genetic contribution with the greatest heritability found for functional connectivity between the posterior cingulate and right inferior parietal nodes (P<0.001). Our data provide new evidence that functional connectivity measures from the intrinsic DMN derived from task-based fMRI datasets are under genetic control and have the potential to serve as endophenotypes for genetically predisposed psychiatric and neurological disorders. Copyright © 2014 Wiley Periodicals, Inc.

Intrinsic to extrinsic phonon lifetime transition in a GaAs-AlAs superlattice.

PubMed

Hofmann, F; Garg, J; Maznev, A A; Jandl, A; Bulsara, M; Fitzgerald, E A; Chen, G; Nelson, K A

2013-07-24

We have measured the lifetimes of two zone-center longitudinal acoustic phonon modes, at 320 and 640 GHz, in a 14 nm GaAs/2 nm AlAs superlattice structure. By comparing measurements at 296 and 79 K we separate the intrinsic contribution to phonon lifetime determined by phonon-phonon scattering from the extrinsic contribution due to defects and interface roughness. At 296 K, the 320 GHz phonon lifetime has approximately equal contributions from intrinsic and extrinsic scattering, whilst at 640 GHz it is dominated by extrinsic effects. These measurements are compared with intrinsic and extrinsic scattering rates in the superlattice obtained from first-principles lattice dynamics calculations. The calculated room-temperature intrinsic lifetime of longitudinal phonons at 320 GHz is in agreement with the experimentally measured value of 0.9 ns. The model correctly predicts the transition from predominantly intrinsic to predominantly extrinsic scattering; however the predicted transition occurs at higher frequencies. Our analysis indicates that the 'interfacial atomic disorder' model is not entirely adequate and that the observed frequency dependence of the extrinsic scattering rate is likely to be determined by a finite correlation length of interface roughness.

Gyrofluid Simulations of Intrinsic Rotation Generation in Reversed Shear Plasmas with Internal Transport Barriers

NASA Astrophysics Data System (ADS)

Jhang, Hogun; Kim, S. S.; Kwon, J. M.; Terzolo, L.; Kim, J. Y.; Diamond, P. H.

2010-11-01

It is accepted that the intrinsic rotation is generated via the residual stress, which is non-diffusive components of the turbulent Reynolds stress, without external momentum input. The physics leading to the onset of intrinsic rotation in L- and H- mode plasmas have been elucidated elsewhere. However, the physics responsible for the generation and transport of the intrinsic rotation and its relationship to the formation of internal transport barriers (ITBs) in reversed shear (RS) plasmas have not been explored in detail, which is the main subject in the present work. The revised version of the global gyrofluid code TRB is used for this study. It is found that the large intrinsic rotation (˜10-30% of the ion sound speed depending on ITB characteristics) is generated near the ITB region and propagates into the core. The intrinsic rotation increases linearly as the temperature gradient at ITB position increases, albeit not indefinitely. Key parameters related to the symmetry breaking, such as turbulent intensity and its gradient, the flux surface averaged parallel wavenumber are evaluated dynamically during the ITB formation. In particular, the role of reversed shear and the q-profile curvature is presented in relation to the symmetry breaking in RS plasmas.

Intrinsic Rotation and Momentum Transport in Reversed Shear Plasmas with Internal Transport Barriers

NASA Astrophysics Data System (ADS)

Jhang, Hogun; Kim, S. S.; Diamond, P. H.

2010-11-01

The intrinsic rotation in fusion plasmas is believed to be generated via the residual stress without external momentum input. The physical mechanism responsible for the generation and transport of intrinsic rotation in L- and H-mode tokamak plasmas has been studied extensively. However, it is noted that the physics of intrinsic rotation generation and its relationship to the formation of internal transport barriers (ITBs) in reversed shear (RS) tokamak plasmas have not been explored in detail, which is the main subject in the present work. A global gyrofluid code TRB is used for this study. It is found that the large intrinsic rotation (˜10-30% of the ion sound speed depending on ITB characteristics) is generated near the ITB region and propagates into the core. The intrinsic rotation increases linearly as the temperature gradient at ITB position increases, albeit not indefinitely. Key parameters related to the symmetry breaking, such as turbulent intensity and its gradient, the flux surface averaged parallel wavenumber are evaluated dynamically during the ITB formation. The role of reversed shear and the q-profile curvature is presented in relation to the symmetry breaking mechanism in RS plasmas.

Enhancing micro-seismic P-phase arrival picking: EMD-cosine function-based denoising with an application to the AIC picker

NASA Astrophysics Data System (ADS)

Shang, Xueyi; Li, Xibing; Morales-Esteban, A.; Dong, Longjun

2018-03-01

Micro-seismic P-phase arrival picking is an elementary step into seismic event location, source mechanism analysis, and seismic tomography. However, a micro-seismic signal is often mixed with high frequency noises and power frequency noises (50 Hz), which could considerably reduce P-phase picking accuracy. To solve this problem, an Empirical Mode Decomposition (EMD)-cosine function denoising-based Akaike Information Criterion (AIC) picker (ECD-AIC picker) is proposed for picking the P-phase arrival time. Unlike traditional low pass filters which are ineffective when seismic data and noise bandwidths overlap, the EMD adaptively separates the seismic data and the noise into different Intrinsic Mode Functions (IMFs). Furthermore, the EMD-cosine function-based denoising retains the P-phase arrival amplitude and phase spectrum more reliably than any traditional low pass filter. The ECD-AIC picker was tested on 1938 sets of micro-seismic waveforms randomly selected from the Institute of Mine Seismology (IMS) database of the Chinese Yongshaba mine. The results have shown that the EMD-cosine function denoising can effectively estimate high frequency and power frequency noises and can be easily adapted to perform on signals with different shapes and forms. Qualitative and quantitative comparisons show that the combined ECD-AIC picker provides better picking results than both the ED-AIC picker and the AIC picker, and the comparisons also show more reliable source localization results when the ECD-AIC picker is applied, thus showing the potential of this combined P-phase picking technique.

Functional Anthology of Intrinsic Disorder. III. Ligands, Postranslational Modifications and Diseases Associated with Intrinsically Disordered Proteins

PubMed Central

Xie, Hongbo; Vucetic, Slobodan; Iakoucheva, Lilia M.; Oldfield, Christopher J.; Dunker, A. Keith; Obradovic, Zoran; Uversky, Vladimir N.

2008-01-01

Currently, the understanding of the relationships between function, amino acid sequence and protein structure continues to represent one of the major challenges of the modern protein science. As much as 50% of eukaryotic proteins are likely to contain functionally important long disordered regions. Many proteins are wholly disordered but still possess numerous biologically important functions. However, the number of experimentally confirmed disordered proteins with known biological functions is substantially smaller than their actual number in nature. Therefore, there is a crucial need for novel bioinformatics approaches that allow projection of the current knowledge from a few experimentally verified examples to much larger groups of known and potential proteins. The elaboration of a bioinformatics tool for the analysis of functional diversity of intrinsically disordered proteins and application of this data mining tool to >200,000 proteins from Swiss-Prot database, each annotated with at least one of the 875 functional keywords was described in the first paper of this series (Xie H., Vucetic S., Iakoucheva L.M., Oldfield C.J., Dunker A.K., Obradovic Z., Uversky V.N. (2006) Functional anthology of intrinsic disorder. I. Biological processes and functions of proteins with long disordered regions. J. Proteome Res.). Using this tool, we have found that out of the 711 Swiss-Prot functional keywords associated with at least 20 proteins, 262 were strongly positively correlated with long intrinsically disordered regions, and 302 were strongly negatively correlated. Illustrative examples of functional disorder or order were found for the vast majority of keywords showing strongest positive or negative correlation with intrinsic disorder, respectively. Some 80 Swiss-Prot keywords associated with disorder- and order-driven biological processes and protein functions were described in the first paper (Xie H., Vucetic S., Iakoucheva L.M., Oldfield C.J., Dunker A.K., Obradovic Z., Uversky V.N. (2006) Functional anthology of intrinsic disorder. I. Biological processes and functions of proteins with long disordered regions. J. Proteome Res.). The second paper of the series was devoted to the presentation of 87 Swiss-Prot keywords attributed to the cellular components, domains, technical terms, developmental processes and coding sequence diversities possessing strong positive and negative correlation with long disordered regions (Vucetic S., Xie H., Iakoucheva L.M., Oldfield C.J., Dunker A.K., Obradovic Z., Uversky V.N. (2006) Functional anthology of intrinsic disorder. II. Cellular components, domains, technical terms, developmental processes and coding sequence diversities correlated with long disordered regions. J. Proteome Res.). Protein structure and functionality can be modulated by various posttranslational modifications or/and as a result of binding of specific ligands. Numerous human diseases are associated with protein misfolding/misassembly/ misfunctioning. This work concludes the series of papers dedicated to the functional anthology of intrinsic disorder and describes ~80 Swiss-Prot functional keywords that are related to ligands, posttranslational modifications and diseases possessing strong positive or negative correlation with the predicted long disordered regions in proteins. PMID:17391016

Mechanical Failure Mode of Metal Nanowires: Global Deformation versus Local Deformation

PubMed Central

Ho, Duc Tam; Im, Youngtae; Kwon, Soon-Yong; Earmme, Youn Young; Kim, Sung Youb

2015-01-01

It is believed that the failure mode of metal nanowires under tensile loading is the result of the nucleation and propagation of dislocations. Such failure modes can be slip, partial slip or twinning and therefore they are regarded as local deformation. Here we provide numerical and theoretical evidences to show that global deformation is another predominant failure mode of nanowires under tensile loading. At the global deformation mode, nanowires fail with a large contraction along a lateral direction and a large expansion along the other lateral direction. In addition, there is a competition between global and local deformations. Nanowires loaded at low temperature exhibit global failure mode first and then local deformation follows later. We show that the global deformation originates from the intrinsic instability of the nanowires and that temperature is a main parameter that decides the global or local deformation as the failure mode of nanowires. PMID:26087445

Alterations of Brain Functional Architecture Associated with Psychopathic Traits in Male Adolescents with Conduct Disorder.

PubMed

Pu, Weidan; Luo, Qiang; Jiang, Yali; Gao, Yidian; Ming, Qingsen; Yao, Shuqiao

2017-09-12

Psychopathic traits of conduct disorder (CD) have a core callous-unemotional (CU) component and an impulsive-antisocial component. Previous task-driven fMRI studies have suggested that psychopathic traits are associated with dysfunction of several brain areas involved in different cognitive functions (e.g., empathy, reward, and response inhibition etc.), but the relationship between psychopathic traits and intrinsic brain functional architecture has not yet been explored in CD. Using a holistic brain-wide functional connectivity analysis, this study delineated the alterations in brain functional networks in patients with conduct disorder. Compared with matched healthy controls, we found decreased anti-synchronization between the fronto-parietal network (FPN) and default mode network (DMN), and increased intra-network synchronization within the frontothalamic-basal ganglia, right frontoparietal, and temporal/limbic/visual networks in CD patients. Correlation analysis showed that the weakened FPN-DMN interaction was associated with CU traits, while the heightened intra-network functional connectivity was related to impulsivity traits in CD patients. Our findings suggest that decoupling of cognitive control (FPN) with social understanding of others (DMN) is associated with the CU traits, and hyper-functions of the reward and motor inhibition systems elevate impulsiveness in CD.

Creativity and the default network: A functional connectivity analysis of the creative brain at rest.

PubMed

Beaty, Roger E; Benedek, Mathias; Wilkins, Robin W; Jauk, Emanuel; Fink, Andreas; Silvia, Paul J; Hodges, Donald A; Koschutnig, Karl; Neubauer, Aljoscha C

2014-11-01

The present research used resting-state functional magnetic resonance imaging (fMRI) to examine whether the ability to generate creative ideas corresponds to differences in the intrinsic organization of functional networks in the brain. We examined the functional connectivity between regions commonly implicated in neuroimaging studies of divergent thinking, including the inferior prefrontal cortex and the core hubs of the default network. Participants were prescreened on a battery of divergent thinking tests and assigned to high- and low-creative groups based on task performance. Seed-based functional connectivity analysis revealed greater connectivity between the left inferior frontal gyrus (IFG) and the entire default mode network in the high-creative group. The right IFG also showed greater functional connectivity with bilateral inferior parietal cortex and the left dorsolateral prefrontal cortex in the high-creative group. The results suggest that the ability to generate creative ideas is characterized by increased functional connectivity between the inferior prefrontal cortex and the default network, pointing to a greater cooperation between brain regions associated with cognitive control and low-level imaginative processes. Copyright © 2014 The Authors. Published by Elsevier Ltd.. All rights reserved.

Novel scheme for rapid parallel parameter estimation of gravitational waves from compact binary coalescences

NASA Astrophysics Data System (ADS)

Pankow, C.; Brady, P.; Ochsner, E.; O'Shaughnessy, R.

2015-07-01

We introduce a highly parallelizable architecture for estimating parameters of compact binary coalescence using gravitational-wave data and waveform models. Using a spherical harmonic mode decomposition, the waveform is expressed as a sum over modes that depend on the intrinsic parameters (e.g., masses) with coefficients that depend on the observer dependent extrinsic parameters (e.g., distance, sky position). The data is then prefiltered against those modes, at fixed intrinsic parameters, enabling efficiently evaluation of the likelihood for generic source positions and orientations, independent of waveform length or generation time. We efficiently parallelize our intrinsic space calculation by integrating over all extrinsic parameters using a Monte Carlo integration strategy. Since the waveform generation and prefiltering happens only once, the cost of integration dominates the procedure. Also, we operate hierarchically, using information from existing gravitational-wave searches to identify the regions of parameter space to emphasize in our sampling. As proof of concept and verification of the result, we have implemented this algorithm using standard time-domain waveforms, processing each event in less than one hour on recent computing hardware. For most events we evaluate the marginalized likelihood (evidence) with statistical errors of ≲5 %, and even smaller in many cases. With a bounded runtime independent of the waveform model starting frequency, a nearly unchanged strategy could estimate neutron star (NS)-NS parameters in the 2018 advanced LIGO era. Our algorithm is usable with any noise curve and existing time-domain model at any mass, including some waveforms which are computationally costly to evolve.

Evolution of intrinsic disorder in eukaryotic proteins.

PubMed

Ahrens, Joseph B; Nunez-Castilla, Janelle; Siltberg-Liberles, Jessica

2017-09-01

Conformational flexibility conferred though regions of intrinsic structural disorder allows proteins to behave as dynamic molecules. While it is well-known that intrinsically disordered regions can undergo disorder-to-order transitions in real-time as part of their function, we also are beginning to learn more about the dynamics of disorder-to-order transitions along evolutionary time-scales. Intrinsically disordered regions endow proteins with functional promiscuity, which is further enhanced by the ability of some of these regions to undergo real-time disorder-to-order transitions. Disorder content affects gene retention after whole genome duplication, but it is not necessarily conserved. Altered patterns of disorder resulting from evolutionary disorder-to-order transitions indicate that disorder evolves to modify function through refining stability, regulation, and interactions. Here, we review the evolution of intrinsically disordered regions in eukaryotic proteins. We discuss the interplay between secondary structure and disorder on evolutionary time-scales, the importance of disorder for eukaryotic proteome expansion and functional divergence, and the evolutionary dynamics of disorder.

Research of Planetary Gear Fault Diagnosis Based on Permutation Entropy of CEEMDAN and ANFIS

PubMed Central

Kuai, Moshen; Cheng, Gang; Li, Yong

2018-01-01

For planetary gear has the characteristics of small volume, light weight and large transmission ratio, it is widely used in high speed and high power mechanical system. Poor working conditions result in frequent failures of planetary gear. A method is proposed for diagnosing faults in planetary gear based on permutation entropy of Complete Ensemble Empirical Mode Decomposition with Adaptive Noise (CEEMDAN) Adaptive Neuro-fuzzy Inference System (ANFIS) in this paper. The original signal is decomposed into 6 intrinsic mode functions (IMF) and residual components by CEEMDAN. Since the IMF contains the main characteristic information of planetary gear faults, time complexity of IMFs are reflected by permutation entropies to quantify the fault features. The permutation entropies of each IMF component are defined as the input of ANFIS, and its parameters and membership functions are adaptively adjusted according to training samples. Finally, the fuzzy inference rules are determined, and the optimal ANFIS is obtained. The overall recognition rate of the test sample used for ANFIS is 90%, and the recognition rate of gear with one missing tooth is relatively high. The recognition rates of different fault gears based on the method can also achieve better results. Therefore, the proposed method can be applied to planetary gear fault diagnosis effectively. PMID:29510569

Research of Planetary Gear Fault Diagnosis Based on Permutation Entropy of CEEMDAN and ANFIS.

PubMed

Kuai, Moshen; Cheng, Gang; Pang, Yusong; Li, Yong

2018-03-05

For planetary gear has the characteristics of small volume, light weight and large transmission ratio, it is widely used in high speed and high power mechanical system. Poor working conditions result in frequent failures of planetary gear. A method is proposed for diagnosing faults in planetary gear based on permutation entropy of Complete Ensemble Empirical Mode Decomposition with Adaptive Noise (CEEMDAN) Adaptive Neuro-fuzzy Inference System (ANFIS) in this paper. The original signal is decomposed into 6 intrinsic mode functions (IMF) and residual components by CEEMDAN. Since the IMF contains the main characteristic information of planetary gear faults, time complexity of IMFs are reflected by permutation entropies to quantify the fault features. The permutation entropies of each IMF component are defined as the input of ANFIS, and its parameters and membership functions are adaptively adjusted according to training samples. Finally, the fuzzy inference rules are determined, and the optimal ANFIS is obtained. The overall recognition rate of the test sample used for ANFIS is 90%, and the recognition rate of gear with one missing tooth is relatively high. The recognition rates of different fault gears based on the method can also achieve better results. Therefore, the proposed method can be applied to planetary gear fault diagnosis effectively.

Flexural phonon limited phonon drag thermopower in bilayer graphene

NASA Astrophysics Data System (ADS)

Ansari, Mohd Meenhaz; Ashraf, SSZ

2018-05-01

We investigate the phonon drag thermopower from flexural phonons as a function of electron temperature and carrier concentration in the Bloch-Gruneisen regime in non-strained bilayer graphene using Boltzmann transport equation approach. The flexural phonons are expected to be the major source of intrinsic scattering mechanism in unstrained bilayer graphene due to their large density. The flexural phonon modes dispersion relation is quadratic so these low energy flexural phonons abound at room temperature and as a result deform the bilayer graphene sheet in the out of plane direction and affects the transport properties. We also produce analytical result for phonon-drag thermopower from flexural phonons and find that phonon-drag thermopower depicts T2 dependence on temperature and n-1 on carrier concentration.

Tunable Mode Coupling in Nanocontact Spin-Torque Oscillators

DOE PAGES

Zhang, Steven S. -L.; Iacocca, Ezio; Heinonen, Olle

2017-07-27

Recent experiments on spin-torque oscillators have revealed interactions between multiple magneto-dynamic modes, including mode coexistence, mode hopping, and temperature-driven crossover between modes. The initial multimode theory indicates that a linear coupling between several dominant modes, arising from the interaction of the subdynamic system with a magnon bath, plays an essential role in the generation of various multimode behaviors, such as mode hopping and mode coexistence. In this work, we derive a set of rate equations to describe the dynamics of coupled magneto-dynamic modes in a nanocontact spin-torque oscillator. Here, expressions for both linear and nonlinear coupling terms are obtained, whichmore » allow us to analyze the dependence of the coupled dynamic behaviors of modes on external experimental conditions as well as intrinsic magnetic properties. For a minimal two-mode system, we further map the energy and phase difference of the two modes onto a two-dimensional phase space and demonstrate in the phase portraits how the manifolds of periodic orbits and fixed points vary with an external magnetic field as well as with the temperature.« less

Tunable Mode Coupling in Nanocontact Spin-Torque Oscillators

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

Zhang, Steven S. -L.; Iacocca, Ezio; Heinonen, Olle

Recent experiments on spin-torque oscillators have revealed interactions between multiple magneto-dynamic modes, including mode coexistence, mode hopping, and temperature-driven crossover between modes. The initial multimode theory indicates that a linear coupling between several dominant modes, arising from the interaction of the subdynamic system with a magnon bath, plays an essential role in the generation of various multimode behaviors, such as mode hopping and mode coexistence. In this work, we derive a set of rate equations to describe the dynamics of coupled magneto-dynamic modes in a nanocontact spin-torque oscillator. Here, expressions for both linear and nonlinear coupling terms are obtained, whichmore » allow us to analyze the dependence of the coupled dynamic behaviors of modes on external experimental conditions as well as intrinsic magnetic properties. For a minimal two-mode system, we further map the energy and phase difference of the two modes onto a two-dimensional phase space and demonstrate in the phase portraits how the manifolds of periodic orbits and fixed points vary with an external magnetic field as well as with the temperature.« less

Experimental evaluation and basis function optimization of the spatially variant image-space PSF on the Ingenuity PET/MR scanner

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

Kotasidis, Fotis A., E-mail: Fotis.Kotasidis@unige.ch; Zaidi, Habib; Geneva Neuroscience Centre, Geneva University, CH-1205 Geneva

2014-06-15

Purpose: The Ingenuity time-of-flight (TF) PET/MR is a recently developed hybrid scanner combining the molecular imaging capabilities of PET with the excellent soft tissue contrast of MRI. It is becoming common practice to characterize the system's point spread function (PSF) and understand its variation under spatial transformations to guide clinical studies and potentially use it within resolution recovery image reconstruction algorithms. Furthermore, due to the system's utilization of overlapping and spherical symmetric Kaiser-Bessel basis functions during image reconstruction, its image space PSF and reconstructed spatial resolution could be affected by the selection of the basis function parameters. Hence, a detailedmore » investigation into the multidimensional basis function parameter space is needed to evaluate the impact of these parameters on spatial resolution. Methods: Using an array of 12 × 7 printed point sources, along with a custom made phantom, and with the MR magnet on, the system's spatially variant image-based PSF was characterized in detail. Moreover, basis function parameters were systematically varied during reconstruction (list-mode TF OSEM) to evaluate their impact on the reconstructed resolution and the image space PSF. Following the spatial resolution optimization, phantom, and clinical studies were subsequently reconstructed using representative basis function parameters. Results: Based on the analysis and under standard basis function parameters, the axial and tangential components of the PSF were found to be almost invariant under spatial transformations (∼4 mm) while the radial component varied modestly from 4 to 6.7 mm. Using a systematic investigation into the basis function parameter space, the spatial resolution was found to degrade for basis functions with a large radius and small shape parameter. However, it was found that optimizing the spatial resolution in the reconstructed PET images, while having a good basis function superposition and keeping the image representation error to a minimum, is feasible, with the parameter combination range depending upon the scanner's intrinsic resolution characteristics. Conclusions: Using the printed point source array as a MR compatible methodology for experimentally measuring the scanner's PSF, the system's spatially variant resolution properties were successfully evaluated in image space. Overall the PET subsystem exhibits excellent resolution characteristics mainly due to the fact that the raw data are not under-sampled/rebinned, enabling the spatial resolution to be dictated by the scanner's intrinsic resolution and the image reconstruction parameters. Due to the impact of these parameters on the resolution properties of the reconstructed images, the image space PSF varies both under spatial transformations and due to basis function parameter selection. Nonetheless, for a range of basis function parameters, the image space PSF remains unaffected, with the range depending on the scanner's intrinsic resolution properties.« less

Nearest Neighbor Interactions Affect the Conformational Distribution in the Unfolded State of Peptides

NASA Astrophysics Data System (ADS)

Toal, Siobhan; Schweitzer-Stenner, Reinhard; Rybka, Karin; Schwalbe, Hardol

2013-03-01

In order to enable structural predictions of intrinsically disordered proteins (IDPs) the intrinsic conformational propensities of amino acids must be complimented by information on nearest-neighbor interactions. To explore the influence of nearest-neighbors on conformational distributions, we preformed a joint vibrational (Infrared, Vibrational Circular Dichroism (VCD), polarized Raman) and 2D-NMR study of selected GxyG host-guest peptides: GDyG, GSyG, GxLG, GxVG, where x/y ={A,K,LV}. D and S (L and V) were chosen at the x (y) position due to their observance to drastically change the distribution of alanine in xAy tripeptide sequences in truncated coil libraries. The conformationally sensitive amide' profiles of the respective spectra were analyzed in terms of a statistical ensemble described as a superposition of 2D-Gaussian functions in Ramachandran space representing sub-ensembles of pPII-, β-strand-, helical-, and turn-like conformations. Our analysis and simulation of the amide I' band profiles exploits excitonic coupling between the local amide I' vibrational modes in the tetra-peptides. The resulting distributions reveal that D and S, which themselves have high propensities for turn-structures, strongly affect the conformational distribution of their downstream neighbor. Taken together, our results indicate that Dx and Sx motifs might act as conformational randomizers in proteins, attenuating intrinsic propensities of neighboring residues. Overall, our results show that nearest neighbor interactions contribute significantly to the Gibbs energy landscape of disordered peptides and proteins.

Differentiable McCormick relaxations

DOE PAGES

Khan, Kamil A.; Watson, Harry A. J.; Barton, Paul I.

2016-05-27

McCormick's classical relaxation technique constructs closed-form convex and concave relaxations of compositions of simple intrinsic functions. These relaxations have several properties which make them useful for lower bounding problems in global optimization: they can be evaluated automatically, accurately, and computationally inexpensively, and they converge rapidly to the relaxed function as the underlying domain is reduced in size. They may also be adapted to yield relaxations of certain implicit functions and differential equation solutions. However, McCormick's relaxations may be nonsmooth, and this nonsmoothness can create theoretical and computational obstacles when relaxations are to be deployed. This article presents a continuously differentiablemore » variant of McCormick's original relaxations in the multivariate McCormick framework of Tsoukalas and Mitsos. Gradients of the new differentiable relaxations may be computed efficiently using the standard forward or reverse modes of automatic differentiation. Furthermore, extensions to differentiable relaxations of implicit functions and solutions of parametric ordinary differential equations are discussed. A C++ implementation based on the library MC++ is described and applied to a case study in nonsmooth nonconvex optimization.« less

Comparison of skin barrier function and sensory nerve electric current perception threshold between IgE-high extrinsic and IgE-normal intrinsic types of atopic dermatitis.

PubMed

Mori, T; Ishida, K; Mukumoto, S; Yamada, Y; Imokawa, G; Kabashima, K; Kobayashi, M; Bito, T; Nakamura, M; Ogasawara, K; Tokura, Y

2010-01-01

Background Two types of atopic dermatitis (AD) have been proposed, with different pathophysiological mechanisms underlying this seemingly heterogeneous disorder. The extrinsic type shows high IgE levels presumably as a consequence of skin barrier damage and feasible allergen permeation, whereas the intrinsic type exhibits normal IgE levels and is not mediated by allergen-specific IgE. Objectives To investigate the relationship between pruritus perception threshold and skin barrier function of patients with AD in a comparison between the extrinsic and intrinsic types. Methods Enrolled in this study were 32 patients with extrinsic AD, 17 with intrinsic AD and 24 healthy individuals. The barrier function of the stratum corneum was assessed by skin surface hydration and transepidermal water loss (TEWL), and pruritus perception was evaluated by the electric current perception threshold (CPT) of sensory nerves upon neuroselective transcutaneous electric stimulation. Results Skin surface hydration was significantly lower and TEWL was significantly higher in extrinsic AD than intrinsic AD or normal controls. Although there was no statistically significant difference in CPT among extrinsic AD, intrinsic AD and normal controls, CPT was significantly correlated with skin surface hydration and inversely with TEWL in intrinsic AD and normal controls, but not extrinsic AD. Finally, CPT was correlated with the visual analogue scale of itch in the nonlesional skin of patients with extrinsic but not intrinsic AD. Conclusions Patients with extrinsic AD have an impaired barrier, which increases the pre-existing pruritus but rather decreases sensitivity to external stimuli. In contrast, patients with intrinsic AD retain a normal barrier function and sensory reactivity to external pruritic stimuli.

Intrinsic motivation and metacognition as predictors of learning potential in patients with remitted schizophrenia.

PubMed

Tas, Cumhur; Brown, Elliot C; Esen-Danaci, Aysen; Lysaker, Paul H; Brüne, Martin

2012-08-01

Previous research has suggested that neurocognitive functioning predicts best the potential of patients with schizophrenia to acquire newly learned material, which, in turn may impact patients' social functioning. Recent studies have also shown that intrinsic motivation and metacognitive abilities play a decisive role in social functioning in schizophrenia. Accordingly, the present study sought to examine the relationship between intelligence, motivation, metacognition, and learning during a cognitive remediation experimental training. We hypothesized that metacognition and intrinsic motivation would have a strong relationship and independently predict learning potential. Thirty-two patients with schizophrenia who fulfilled the criteria of functional remission were recruited. In a pre-training-post experimental design, patients' learning potential was assessed using previously defined cognitive remediation training for WCST. Intrinsic motivation was examined using Intrinsic Motivation Inventory for schizophrenia; mastery, a domain of metacognition, was measured using the Metacognitive Assessment Scale. Metacognition significantly correlated with subdomains of intrinsic motivation. Patients with higher intrinsic motivation and preserved metacognition improved more in the learning paradigm compared to poorly motivated patients and patients with reduced metacognitive abilities. In particular, "mastery" was determined as an independent predictor of learning potential. Motivation and metacognition are important predictors of learning in schizophrenia. Psychological interventions in schizophrenia may therefore consider incorporating techniques to stimulate metacognitive and motivational abilities as well as developing individualized training programs. Copyright © 2012 Elsevier Ltd. All rights reserved.

Neural Correlates for Intrinsic Motivational Deficits of Schizophrenia; Implications for Therapeutics of Cognitive Impairment

PubMed Central

Takeda, Kazuyoshi; Sumiyoshi, Tomiki; Matsumoto, Madoka; Murayama, Kou; Ikezawa, Satoru; Matsumoto, Kenji; Nakagome, Kazuyuki

2018-01-01

The ultimate goal of the treatment of schizophrenia is recovery, a notion related to improvement of cognitive and social functioning. Cognitive remediation therapies (CRT), one of the most effective cognition enhancing methods, have been shown to moderately improve social functioning. For this purpose, intrinsic motivation, related to internal values such as interest and enjoyment, has been shown to play a key role. Although the impairment of intrinsic motivation is one of the characteristics of schizophrenia, its neural mechanisms remain unclear. This is related to the lack of feasible measures of intrinsic motivation, and its response to treatment. According to the self-determination theory (SDT), not only intrinsic motivation, but extrinsic motivation has been reported to enhance learning and memory in healthy subjects to some extent. This finding suggests the contribution of different types of motivation to potentiate the ability of the CRT to treat cognitive impairment of schizophrenia. In this paper, we provide a review of psychological characteristics, assessment methods, and neural correlates of intrinsic motivation in healthy subjects and patients with schizophrenia. Particularly, we focus on neuroimaging studies of intrinsic motivation, including our own. These considerations are relevant to enhancement of functional outcomes of schizophrenia. PMID:29922185

Neural Correlates for Intrinsic Motivational Deficits of Schizophrenia; Implications for Therapeutics of Cognitive Impairment.

PubMed

Takeda, Kazuyoshi; Sumiyoshi, Tomiki; Matsumoto, Madoka; Murayama, Kou; Ikezawa, Satoru; Matsumoto, Kenji; Nakagome, Kazuyuki

2018-01-01

The ultimate goal of the treatment of schizophrenia is recovery, a notion related to improvement of cognitive and social functioning. Cognitive remediation therapies (CRT), one of the most effective cognition enhancing methods, have been shown to moderately improve social functioning. For this purpose, intrinsic motivation, related to internal values such as interest and enjoyment, has been shown to play a key role. Although the impairment of intrinsic motivation is one of the characteristics of schizophrenia, its neural mechanisms remain unclear. This is related to the lack of feasible measures of intrinsic motivation, and its response to treatment. According to the self-determination theory (SDT), not only intrinsic motivation, but extrinsic motivation has been reported to enhance learning and memory in healthy subjects to some extent. This finding suggests the contribution of different types of motivation to potentiate the ability of the CRT to treat cognitive impairment of schizophrenia. In this paper, we provide a review of psychological characteristics, assessment methods, and neural correlates of intrinsic motivation in healthy subjects and patients with schizophrenia. Particularly, we focus on neuroimaging studies of intrinsic motivation, including our own. These considerations are relevant to enhancement of functional outcomes of schizophrenia.

Excessive coupling of the salience network with intrinsic neurocognitive brain networks during rectal distension in adolescents with irritable bowel syndrome: a preliminary report

PubMed Central

Liu, Xiaolin; Silverman, Alan; Kern, Mark; Ward, B. Douglas; Li, Shi-Jiang; Shaker, Reza; Sood, Manu R.

2015-01-01

Background The neural network mechanisms underlying visceral hypersensitivity in irritable bowel syndrome (IBS) are incompletely understood. It has been proposed that an intrinsic salience network plays an important role in chronic pain and IBS symptoms. Using neuroimaging, we examined brain responses to rectal distension in adolescent IBS patients, focusing on determining the alteration of salience network integrity in IBS and its functional implications in current theoretical frameworks. We hypothesized that (1) brain responses to visceral stimulation in adolescents are similar to those in adults, and (2) IBS is associated with an altered salience network interaction with other neurocognitive networks, particularly the default mode network (DMN) and executive control network (ECN), as predicted by the theoretical models. Methods IBS patients and controls received subliminal and liminal rectal distension during imaging. Stimulus-induced brain activations were determined. Salience network integrity was evaluated by functional connectivity of its seed regions activated by rectal distension in the insular and cingulate cortices. Key Results Compared with controls, IBS patients demonstrated greater activation to rectal distension in neural structures of the homeostatic afferent and emotional arousal networks, especially the anterior cingulate and insular cortices. Greater brain responses to liminal vs. subliminal distension were observed in both groups. Particularly, IBS is uniquely associated with an excessive coupling of the salience network with the DMN and ECN in their key frontal and parietal node areas. Conclusions & Inferences Our study provided consistent evidence supporting the theoretical predictions of altered salience network functioning as a neuropathological mechanism of IBS symptoms. PMID:26467966

Theoretical modeling of the infrared fluorescence from interstellar polycyclic aromatic hydrocarbons

NASA Technical Reports Server (NTRS)

Schutte, W. A.; Tielens, A. G. G. M.; Allamandola, L. J.

1993-01-01

We have modeled the family of interstellar IR emission bands at 3.3, 6.2, 7.7, 8.6, 11.3, and 12.7 microns by calculating the fluorescence from a size distribution of interstellar polycyclic aromatic hydrocarbons (PAHs) embedded in the radiation field of a hot star. It is found that the various emission bands are dominated by distinctly different PAHs, from molecules with much less than about 80 C atoms for the 3.3 micron feature, to molecules with 10 exp 2-10 exp 5 C atoms for the emission in the IRAS 12 and 25 micron bands. We quantitatively describe the influence on the emergent spectrum of various PAH properties such as the molecular structure, the amount of dehydrogenation, the intrinsic strength of the IR active modes, and the size distribution. Comparing our model results to the emission spectrum from the Orion Bar region, we conclude that interstellar PAHs are likely fully, or almost fully, hydrogenated. Moreover, it is found that the intrinsic strengths of the 6.2 and 7.7 micron C-C stretching modes, and the 8.6 micron C-H in-plane bending mode are 2-6 times larger than measured for neutral PAHs in the laboratory.

Completed Ensemble Empirical Mode Decomposition: a Robust Signal Processing Tool to Identify Sequence Strata

NASA Astrophysics Data System (ADS)

Purba, H.; Musu, J. T.; Diria, S. A.; Permono, W.; Sadjati, O.; Sopandi, I.; Ruzi, F.

2018-03-01

Well logging data provide many geological information and its trends resemble nonlinear or non-stationary signals. As long well log data recorded, there will be external factors can interfere or influence its signal resolution. A sensitive signal analysis is required to improve the accuracy of logging interpretation which it becomes an important thing to determine sequence stratigraphy. Complete Ensemble Empirical Mode Decomposition (CEEMD) is one of nonlinear and non-stationary signal analysis method which decomposes complex signal into a series of intrinsic mode function (IMF). Gamma Ray and Spontaneous Potential well log parameters decomposed into IMF-1 up to IMF-10 and each of its combination and correlation makes physical meaning identification. It identifies the stratigraphy and cycle sequence and provides an effective signal treatment method for sequence interface. This method was applied to BRK- 30 and BRK-13 well logging data. The result shows that the combination of IMF-5, IMF-6, and IMF-7 pattern represent short-term and middle-term while IMF-9 and IMF-10 represent the long-term sedimentation which describe distal front and delta front facies, and inter-distributary mouth bar facies, respectively. Thus, CEEMD clearly can determine the different sedimentary layer interface and better identification of the cycle of stratigraphic base level.

Experimental validation of a structural damage detection method based on marginal Hilbert spectrum

NASA Astrophysics Data System (ADS)

Banerji, Srishti; Roy, Timir B.; Sabamehr, Ardalan; Bagchi, Ashutosh

2017-04-01

Structural Health Monitoring (SHM) using dynamic characteristics of structures is crucial for early damage detection. Damage detection can be performed by capturing and assessing structural responses. Instrumented structures are monitored by analyzing the responses recorded by deployed sensors in the form of signals. Signal processing is an important tool for the processing of the collected data to diagnose anomalies in structural behavior. The vibration signature of the structure varies with damage. In order to attain effective damage detection, preservation of non-linear and non-stationary features of real structural responses is important. Decomposition of the signals into Intrinsic Mode Functions (IMF) by Empirical Mode Decomposition (EMD) and application of Hilbert-Huang Transform (HHT) addresses the time-varying instantaneous properties of the structural response. The energy distribution among different vibration modes of the intact and damaged structure depicted by Marginal Hilbert Spectrum (MHS) detects location and severity of the damage. The present work investigates damage detection analytically and experimentally by employing MHS. The testing of this methodology for different damage scenarios of a frame structure resulted in its accurate damage identification. The sensitivity of Hilbert Spectral Analysis (HSA) is assessed with varying frequencies and damage locations by means of calculating Damage Indices (DI) from the Hilbert spectrum curves of the undamaged and damaged structures.

Analysis of microvascular perfusion with multi-dimensional complete ensemble empirical mode decomposition with adaptive noise algorithm: Processing of laser speckle contrast images recorded in healthy subjects, at rest and during acetylcholine stimulation.

PubMed

Humeau-Heurtier, Anne; Marche, Pauline; Dubois, Severine; Mahe, Guillaume

2015-01-01

Laser speckle contrast imaging (LSCI) is a full-field imaging modality to monitor microvascular blood flow. It is able to give images with high temporal and spatial resolutions. However, when the skin is studied, the interpretation of the bidimensional data may be difficult. This is why an averaging of the perfusion values in regions of interest is often performed and the result is followed in time, reducing the data to monodimensional time series. In order to avoid such a procedure (that leads to a loss of the spatial resolution), we propose to extract patterns from LSCI data and to compare these patterns for two physiological states in healthy subjects: at rest and at the peak of acetylcholine-induced perfusion peak. For this purpose, the recent multi-dimensional complete ensemble empirical mode decomposition with adaptive noise (MCEEMDAN) algorithm is applied to LSCI data. The results show that the intrinsic mode functions and residue given by MCEEMDAN show different patterns for the two physiological states. The images, as bidimensional data, can therefore be processed to reveal microvascular perfusion patterns, hidden in the images themselves. This work is therefore a feasibility study before analyzing data in patients with microvascular dysfunctions.

An upgrade of the magnetic diagnostic system of the DIII-D tokamak for non-axisymmetric measurements

DOE PAGES

King, Joshua D.; Strait, Edward J.; Boivin, Rejean L.; ...

2014-08-07

Here, the DIII-D tokamak magnetic diagnostic system has been upgraded to significantly expand the measurement of the plasma response to intrinsic and applied non-axisymmetric “3D” fields. The placement and design of 101 additional sensors allow resolution of toroidal mode numbers 1 ≤ n ≤ 3, and poloidal wavelengths smaller than MARS-F, IPEC, and VMEC magnetohydrodynamic (MHD) model predictions. Small 3D perturbations, relative to the equilibrium field (10 –5 0 <10 –4), require sub-millimeter fabrication and installation tolerances. This high precision is achieved using electrical discharge machined components, and alignment techniques employing rotary laser levels and a coordinate measurement machine. Amore » 16-bit data acquisition system is used in conjunction with analog signal-processing to recover non-axisymmetric perturbations. Co-located radial and poloidal field measurements allow up to 14.2 cm spatial resolution of poloidal structures (plasma poloidal circumference is ~ 500 cm). The function of the new system is verified by comparing the rotating tearing mode structure, measured by 31 BP fluctuation sensors, with that measured by the upgraded B R saddle loop sensors after the mode locks to the vessel wall. The result is a nearly identical 2/1 helical eigenstructure in both cases.« less

Machinery Bearing Fault Diagnosis Using Variational Mode Decomposition and Support Vector Machine as a Classifier

NASA Astrophysics Data System (ADS)

Rama Krishna, K.; Ramachandran, K. I.

2018-02-01

Crack propagation is a major cause of failure in rotating machines. It adversely affects the productivity, safety, and the machining quality. Hence, detecting the crack’s severity accurately is imperative for the predictive maintenance of such machines. Fault diagnosis is an established concept in identifying the faults, for observing the non-linear behaviour of the vibration signals at various operating conditions. In this work, we find the classification efficiencies for both original and the reconstructed vibrational signals. The reconstructed signals are obtained using Variational Mode Decomposition (VMD), by splitting the original signal into three intrinsic mode functional components and framing them accordingly. Feature extraction, feature selection and feature classification are the three phases in obtaining the classification efficiencies. All the statistical features from the original signals and reconstructed signals are found out in feature extraction process individually. A few statistical parameters are selected in feature selection process and are classified using the SVM classifier. The obtained results show the best parameters and appropriate kernel in SVM classifier for detecting the faults in bearings. Hence, we conclude that better results were obtained by VMD and SVM process over normal process using SVM. This is owing to denoising and filtering the raw vibrational signals.

Local measurement of error field using naturally rotating tearing mode dynamics in EXTRAP T2R

NASA Astrophysics Data System (ADS)

Sweeney, R. M.; Frassinetti, L.; Brunsell, P.; Fridström, R.; Volpe, F. A.

2016-12-01

An error field (EF) detection technique using the amplitude modulation of a naturally rotating tearing mode (TM) is developed and validated in the EXTRAP T2R reversed field pinch. The technique was used to identify intrinsic EFs of m/n  =  1/-12, where m and n are the poloidal and toroidal mode numbers. The effect of the EF and of a resonant magnetic perturbation (RMP) on the TM, in particular on amplitude modulation, is modeled with a first-order solution of the modified Rutherford equation. In the experiment, the TM amplitude is measured as a function of the toroidal angle as the TM rotates rapidly in the presence of an unknown EF and a known, deliberately applied RMP. The RMP amplitude is fixed while the toroidal phase is varied from one discharge to the other, completing a full toroidal scan. Using three such scans with different RMP amplitudes, the EF amplitude and phase are inferred from the phases at which the TM amplitude maximizes. The estimated EF amplitude is consistent with other estimates (e.g. based on the best EF-cancelling RMP, resulting in the fastest TM rotation). A passive variant of this technique is also presented, where no RMPs are applied, and the EF phase is deduced.

Coiling of elastic rods on rigid substrates

PubMed Central

Jawed, Mohammad K.; Da, Fang; Joo, Jungseock; Grinspun, Eitan; Reis, Pedro M.

2014-01-01

We investigate the deployment of a thin elastic rod onto a rigid substrate and study the resulting coiling patterns. In our approach, we combine precision model experiments, scaling analyses, and computer simulations toward developing predictive understanding of the coiling process. Both cases of deposition onto static and moving substrates are considered. We construct phase diagrams for the possible coiling patterns and characterize them as a function of the geometric and material properties of the rod, as well as the height and relative speeds of deployment. The modes selected and their characteristic length scales are found to arise from a complex interplay between gravitational, bending, and twisting energies of the rod, coupled to the geometric nonlinearities intrinsic to the large deformations. We give particular emphasis to the first sinusoidal mode of instability, which we find to be consistent with a Hopf bifurcation, and analyze the meandering wavelength and amplitude. Throughout, we systematically vary natural curvature of the rod as a control parameter, which has a qualitative and quantitative effect on the pattern formation, above a critical value that we determine. The universality conferred by the prominent role of geometry in the deformation modes of the rod suggests using the gained understanding as design guidelines, in the original applications that motivated the study. PMID:25267649

High and low frequency unfolded partial least squares regression based on empirical mode decomposition for quantitative analysis of fuel oil samples.

PubMed

Bian, Xihui; Li, Shujuan; Lin, Ligang; Tan, Xiaoyao; Fan, Qingjie; Li, Ming

2016-06-21

Accurate prediction of the model is fundamental to the successful analysis of complex samples. To utilize abundant information embedded over frequency and time domains, a novel regression model is presented for quantitative analysis of hydrocarbon contents in the fuel oil samples. The proposed method named as high and low frequency unfolded PLSR (HLUPLSR), which integrates empirical mode decomposition (EMD) and unfolded strategy with partial least squares regression (PLSR). In the proposed method, the original signals are firstly decomposed into a finite number of intrinsic mode functions (IMFs) and a residue by EMD. Secondly, the former high frequency IMFs are summed as a high frequency matrix and the latter IMFs and residue are summed as a low frequency matrix. Finally, the two matrices are unfolded to an extended matrix in variable dimension, and then the PLSR model is built between the extended matrix and the target values. Coupled with Ultraviolet (UV) spectroscopy, HLUPLSR has been applied to determine hydrocarbon contents of light gas oil and diesel fuels samples. Comparing with single PLSR and other signal processing techniques, the proposed method shows superiority in prediction ability and better model interpretation. Therefore, HLUPLSR method provides a promising tool for quantitative analysis of complex samples. Copyright © 2016 Elsevier B.V. All rights reserved.

Robust multitask learning with three-dimensional empirical mode decomposition-based features for hyperspectral classification

NASA Astrophysics Data System (ADS)

He, Zhi; Liu, Lin

2016-11-01

Empirical mode decomposition (EMD) and its variants have recently been applied for hyperspectral image (HSI) classification due to their ability to extract useful features from the original HSI. However, it remains a challenging task to effectively exploit the spectral-spatial information by the traditional vector or image-based methods. In this paper, a three-dimensional (3D) extension of EMD (3D-EMD) is proposed to naturally treat the HSI as a cube and decompose the HSI into varying oscillations (i.e. 3D intrinsic mode functions (3D-IMFs)). To achieve fast 3D-EMD implementation, 3D Delaunay triangulation (3D-DT) is utilized to determine the distances of extrema, while separable filters are adopted to generate the envelopes. Taking the extracted 3D-IMFs as features of different tasks, robust multitask learning (RMTL) is further proposed for HSI classification. In RMTL, pairs of low-rank and sparse structures are formulated by trace-norm and l1,2 -norm to capture task relatedness and specificity, respectively. Moreover, the optimization problems of RMTL can be efficiently solved by the inexact augmented Lagrangian method (IALM). Compared with several state-of-the-art feature extraction and classification methods, the experimental results conducted on three benchmark data sets demonstrate the superiority of the proposed methods.

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

PubMed

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.

Intrinsic and Extrinsic School Motivation as a Function of Age: The Mediating Role of Autonomy Support

ERIC Educational Resources Information Center

Gillet, Nicolas; Vallerand, Robert J.; Lafreniere, Marc-Andre K.

2012-01-01

The main purpose of the present research was to investigate school intrinsic and extrinsic motivation, and amotivation as a function of age in a sample of 1,600 elementary and high school students aged 9-17 years. First, results revealed a systematic decrease in intrinsic motivation and self-determined extrinsic motivation from age 9 to 12 years,…

S. pombe Uba1-Ubc15 Structure Reveals a Novel Regulatory Mechanism of Ubiquitin E2 Activity.

PubMed

Lv, Zongyang; Rickman, Kimberly A; Yuan, Lingmin; Williams, Katelyn; Selvam, Shanmugam Panneer; Woosley, Alec N; Howe, Philip H; Ogretmen, Besim; Smogorzewska, Agata; Olsen, Shaun K

2017-02-16

Ubiquitin (Ub) E1 initiates the Ub conjugation cascade by activating and transferring Ub to tens of different E2s. How Ub E1 cooperates with E2s that differ substantially in their predicted E1-interacting residues is unknown. Here, we report the structure of S. pombe Uba1 in complex with Ubc15, a Ub E2 with intrinsically low E1-E2 Ub thioester transfer activity. The structure reveals a distinct Ubc15 binding mode that substantially alters the network of interactions at the E1-E2 interface compared to the only other available Ub E1-E2 structure. Structure-function analysis reveals that the intrinsically low activity of Ubc15 largely results from the presence of an acidic residue at its N-terminal region. Notably, Ub E2 N termini are serine/threonine rich in many other Ub E2s, leading us to hypothesize that phosphorylation of these sites may serve as a novel negative regulatory mechanism of Ub E2 activity, which we demonstrate biochemically and in cell-based assays. Copyright © 2017 Elsevier Inc. All rights reserved.

Investigation of mode partition noise in Fabry-Perot laser diode

NASA Astrophysics Data System (ADS)

Guo, Qingyi; Deng, Lanxin; Mu, Jianwei; Li, Xun; Huang, Wei-Ping

2014-09-01

Passive optical network (PON) is considered as the most appealing access network architecture in terms of cost-effectiveness, bandwidth management flexibility, scalability and durability. And to further reduce the cost per subscriber, a Fabry-Perot (FP) laser diode is preferred as the transmitter at the optical network units (ONUs) because of its lower cost compared to distributed feedback (DFB) laser diode. However, the mode partition noise (MPN) associated with the multi-longitudinal-mode FP laser diode becomes the limiting factor in the network. This paper studies the MPN characteristics of the FP laser diode using the time-domain simulation of noise-driven multi-mode laser rate equation. The probability density functions are calculated for each longitudinal mode. The paper focuses on the investigation of the k-factor, which is a simple yet important measure of the noise power, but is usually taken as a fitted or assumed value in the penalty calculations. In this paper, the sources of the k-factor are studied with simulation, including the intrinsic source of the laser Langevin noise, and the extrinsic source of the bit pattern. The photon waveforms are shown under four simulation conditions for regular or random bit pattern, and with or without Langevin noise. The k-factors contributed by those sources are studied with a variety of bias current and modulation current. Simulation results are illustrated in figures, and show that the contribution of Langevin noise to the k-factor is larger than that of the random bit pattern, and is more dominant at lower bias current or higher modulation current.

Identifying Decadal to Multi-decadal Variability in the Pacific by Empirical Mode Decomposition

NASA Astrophysics Data System (ADS)

Sommers, L. A.; Hamlington, B.; Cheon, S. H.

2016-12-01

Large scale climate variability in the Pacific Ocean like that associated with ENSO and the Pacific Decadal Oscillation (PDO) has been shown to have a significant impact on climate and sea level across a range of timescales. The changes related to these climate signals have worldwide impacts on fisheries, weather, and precipitation patterns among others. Understanding these inter-annual to multi-decadal oscillations is imperative to longer term climate forecasts and understanding how climate will behave, and its effect on changes in sea level. With a 110-year reconstruction of sea level, we examine decadal to multi-decadal variability seen in the sea level fluctuations in the Pacific Ocean. Using empirical mode decomposition (EMD), we break down regional sea level into a series of intrinsic mode functions (IMFs) and attempt attribution of these IMFs to specific climate modes of variability. In particular, and not unexpectedly, we identify IMFs associated with the PDO, finding correlations between the PDO Index and IMFs in the Pacific Ocean upwards of 0.6-0.8 over the 110-year reconstructed record. Perhaps more significantly, we also find evidence of a longer multi-decadal signal ( 50-60 years) in the higher order IMFs. This lower frequency variability has been suggested in previous literature as influencing GMSL, but here we find a regional pattern associated with this multi-decadal signal. By identifying and separating these periodic climate signals, we can gain a better understanding of how the sea level variability associated with these modes can impact sea level on short timescales and serve to exacerbate the effects of long-term sea level change.

Functional anthology of intrinsic disorder. 3. Ligands, post-translational modifications, and diseases associated with intrinsically disordered proteins.

PubMed

Xie, Hongbo; Vucetic, Slobodan; Iakoucheva, Lilia M; Oldfield, Christopher J; Dunker, A Keith; Obradovic, Zoran; Uversky, Vladimir N

2007-05-01

Currently, the understanding of the relationships between function, amino acid sequence, and protein structure continues to represent one of the major challenges of the modern protein science. As many as 50% of eukaryotic proteins are likely to contain functionally important long disordered regions. Many proteins are wholly disordered but still possess numerous biologically important functions. However, the number of experimentally confirmed disordered proteins with known biological functions is substantially smaller than their actual number in nature. Therefore, there is a crucial need for novel bionformatics approaches that allow projection of the current knowledge from a few experimentally verified examples to much larger groups of known and potential proteins. The elaboration of a bioinformatics tool for the analysis of functional diversity of intrinsically disordered proteins and application of this data mining tool to >200 000 proteins from the Swiss-Prot database, each annotated with at least one of the 875 functional keywords, was described in the first paper of this series (Xie, H.; Vucetic, S.; Iakoucheva, L. M.; Oldfield, C. J.; Dunker, A. K.; Obradovic, Z.; Uversky, V.N. Functional anthology of intrinsic disorder. 1. Biological processes and functions of proteins with long disordered regions. J. Proteome Res. 2007, 5, 1882-1898). Using this tool, we have found that out of the 710 Swiss-Prot functional keywords associated with at least 20 proteins, 262 were strongly positively correlated with long intrinsically disordered regions, and 302 were strongly negatively correlated. Illustrative examples of functional disorder or order were found for the vast majority of keywords showing strongest positive or negative correlation with intrinsic disorder, respectively. Some 80 Swiss-Prot keywords associated with disorder- and order-driven biological processes and protein functions were described in the first paper (see above). The second paper of the series was devoted to the presentation of 87 Swiss-Prot keywords attributed to the cellular components, domains, technical terms, developmental processes, and coding sequence diversities possessing strong positive and negative correlation with long disordered regions (Vucetic, S.; Xie, H.; Iakoucheva, L. M.; Oldfield, C. J.; Dunker, A. K.; Obradovic, Z.; Uversky, V. N. Functional anthology of intrinsic disorder. 2. Cellular components, domains, technical terms, developmental processes, and coding sequence diversities correlated with long disordered regions. J. Proteome Res. 2007, 5, 1899-1916). Protein structure and functionality can be modulated by various post-translational modifications or/and as a result of binding of specific ligands. Numerous human diseases are associated with protein misfolding/misassembly/misfunctioning. This work concludes the series of papers dedicated to the functional anthology of intrinsic disorder and describes approximately 80 Swiss-Prot functional keywords that are related to ligands, post-translational modifications, and diseases possessing strong positive or negative correlation with the predicted long disordered regions in proteins.

Intrinsic Coupled Ocean-Atmosphere Modes of the Asian Summer Monsoon: A Re-assessment of Monsoon-ENSO Relationships

NASA Technical Reports Server (NTRS)

Lau, K.-M.; Wu, H. T.

2000-01-01

Using global rainfall and sea surface temperature (SST) data for the past two decades (1979-1998), we have investigated the intrinsic modes of Asian summer monsoon (ASM) and ENSO co-variability. Three recurring ASM rainfall-SST coupled modes were identified. The first is a basin scale mode that features SST and rainfall variability over the entire tropics (including the ASM region), identifiable with those occurring during El Nino or La Nina. This mode is further characterized by a pronounced biennial variation in ASM rainfall and SST associated with fluctuations of the anomalous Walker circulation that occur during El Nino/La Nina transitions. The second mode comprises mixed regional and basin-scale rainfall and SST signals, with pronounced intraseasonal and interannual variabilities. This mode features a SST pattern associated with a developing La Nina, with a pronounced low level anticyclone in the subtropics of the western Pacific off the coast of East Asia. The third mode depicts an east-west rainfall and SST dipole across the southern equatorial Indian Ocean, most likely stemming from coupled ocean-atmosphere processes within the ASM region. This mode also possesses a decadal time scale and a linear trend, which are not associated with El Nino/La Nina variability. Possible causes of year-to-year rainfall variability over the ASM and sub-regions have been evaluated from a reconstruction of the observed rainfall from singular eigenvectors of the coupled modes. It is found that while basin-scale SST can account for portions of ASM rainfall variability during ENSO events (up to 60% in 1998), regional processes can accounts up to 20-25% of the rainfall variability in typical non-ENSO years. Stronger monsoon-ENSO relationship tends to occur in the boreal summer immediately preceding a pronounced La Nina, i.e., 1998, 1988 and 1983. Based on these results, we discuss the possible impacts of the ASM on ENSO variability via the west Pacific anticyclone and articulate a hypothesis that anomalous wind forcings derived from the anticyclone may be instrumental in inducing a strong biennial modulation to natural ENSO cycles.

System identification based on deconvolution and cross correlation: An application to a 20‐story instrumented building in Anchorage, Alaska

USGS Publications Warehouse

Wen, Weiping; Kalkan, Erol

2017-01-01

Deconvolution and cross‐correlation techniques are used for system identification of a 20‐story steel, moment‐resisting frame building in downtown Anchorage, Alaska. This regular‐plan midrise structure is instrumented with a 32‐channel accelerometer array at 10 levels. The impulse response functions (IRFs) and correlation functions (CFs) are computed based on waveforms recorded from ambient vibrations and five local and regional earthquakes. The earthquakes occurred from 2005 to 2014 with moment magnitudes between 4.7 and 6.2 over a range of azimuths at epicenter distances of 13.3–183 km. The building’s fundamental frequencies and mode shapes are determined using a complex mode indicator function based on singular value decomposition of multiple reference frequency‐response functions. The traveling waves, identified in IRFs with a virtual source at the roof, and CFs are used to estimate the intrinsic attenuation associated with the fundamental modes and shear‐wave velocity in the building. Although the cross correlation of the waveforms at various levels with the corresponding waveform at the first floor provides more complicated wave propagation than that from the deconvolution with virtual source at the roof, the shear‐wave velocities identified by both techniques are consistent—the largest difference in average values is within 8%. The median shear‐wave velocity from the IRFs of five earthquakes is 191  m/s for the east–west (E‐W), 205  m/s for the north–south (N‐S), and 176  m/s for the torsional responses. The building’s average intrinsic‐damping ratio is estimated to be 3.7% and 3.4% in the 0.2–1 Hz frequency band for the E‐W and N‐S directions, respectively. These results are intended to serve as reference for the undamaged condition of the building, which may be used for tracking changes in structural integrity during and after future earthquakes.

Revealing the functional neuroanatomy of intrinsic alertness using fMRI: methodological peculiarities.

PubMed

Clemens, Benjamin; Zvyagintsev, Mikhail; Sack, Alexander T; Sack, Alexander; Heinecke, Armin; Willmes, Klaus; Sturm, Walter

2011-01-01

Clinical observations and neuroimaging data revealed a right-hemisphere fronto-parietal-thalamic-brainstem network for intrinsic alertness, and additional left fronto-parietal activity during phasic alertness. The primary objective of this fMRI study was to map the functional neuroanatomy of intrinsic alertness as precisely as possible in healthy participants, using a novel assessment paradigm already employed in clinical settings. Both the paradigm and the experimental design were optimized to specifically assess intrinsic alertness, while at the same time controlling for sensory-motor processing. The present results suggest that the processing of intrinsic alertness is accompanied by increased activity within the brainstem, thalamus, anterior cingulate gyrus, right insula, and right parietal cortex. Additionally, we found increased activation in the left hemisphere around the middle frontal gyrus (BA 9), the insula, the supplementary motor area, and the cerebellum. Our results further suggest that rather minute aspects of the experimental design may induce aspects of phasic alertness, which in turn might lead to additional brain activation in left-frontal areas not normally involved in intrinsic alertness. Accordingly, left BA 9 activation may be related to co-activation of the phasic alertness network due to the switch between rest and task conditions functioning as an external warning cue triggering the phasic alertness network. Furthermore, activation of the intrinsic alertness network during fixation blocks due to enhanced expectancy shortly before the switch to the task block might, when subtracted from the task block, lead to diminished activation in the typical right hemisphere intrinsic alertness network. Thus, we cautiously suggest that--as a methodological artifact--left frontal activations might show up due to phasic alertness involvement and intrinsic alertness activations might be weakened due to contrasting with fixation blocks, when assessing the functional neuroanatomy of intrinsic alertness with a block design in fMRI studies.

Revealing the Functional Neuroanatomy of Intrinsic Alertness Using fMRI: Methodological Peculiarities

PubMed Central

Clemens, Benjamin; Zvyagintsev, Mikhail; Sack, Alexander; Heinecke, Armin; Willmes, Klaus; Sturm, Walter

2011-01-01

Clinical observations and neuroimaging data revealed a right-hemisphere fronto-parietal-thalamic-brainstem network for intrinsic alertness, and additional left fronto-parietal activity during phasic alertness. The primary objective of this fMRI study was to map the functional neuroanatomy of intrinsic alertness as precisely as possible in healthy participants, using a novel assessment paradigm already employed in clinical settings. Both the paradigm and the experimental design were optimized to specifically assess intrinsic alertness, while at the same time controlling for sensory-motor processing. The present results suggest that the processing of intrinsic alertness is accompanied by increased activity within the brainstem, thalamus, anterior cingulate gyrus, right insula, and right parietal cortex. Additionally, we found increased activation in the left hemisphere around the middle frontal gyrus (BA 9), the insula, the supplementary motor area, and the cerebellum. Our results further suggest that rather minute aspects of the experimental design may induce aspects of phasic alertness, which in turn might lead to additional brain activation in left-frontal areas not normally involved in intrinsic alertness. Accordingly, left BA 9 activation may be related to co-activation of the phasic alertness network due to the switch between rest and task conditions functioning as an external warning cue triggering the phasic alertness network. Furthermore, activation of the intrinsic alertness network during fixation blocks due to enhanced expectancy shortly before the switch to the task block might, when subtracted from the task block, lead to diminished activation in the typical right hemisphere intrinsic alertness network. Thus, we cautiously suggest that – as a methodological artifact – left frontal activations might show up due to phasic alertness involvement and intrinsic alertness activations might be weakened due to contrasting with fixation blocks, when assessing the functional neuroanatomy of intrinsic alertness with a block design in fMRI studies. PMID:21984928

Multimode nonlinear optical imaging of the dermis in ex vivo human skin based on the combination of multichannel mode and Lambda mode.

PubMed

Zhuo, Shuangmu; Chen, Jianxin; Luo, Tianshu; Zou, Dingsong

2006-08-21

A Multimode nonlinear optical imaging technique based on the combination of multichannel mode and Lambda mode is developed to investigate human dermis. Our findings show that this technique not only improves the image contrast of the structural proteins of extracellular matrix (ECM) but also provides an image-guided spectral analysis method to identify both cellular and ECM intrinsic components including collagen, elastin, NAD(P)H and flavin. By the combined use of multichannel mode and Lambda mode in tandem, the obtained in-depth two photon-excited fluorescence (TPEF) and second-harmonic generation (SHG) imaging and TPEF/SHG signals depth-dependence decay can offer a sensitive tool for obtaining quantitative tissue structural and biochemical information. These results suggest that the technique has the potential to provide more accurate information for determining tissue physiological and pathological states.

Multi-Sensor Data Fusion Identification for Shearer Cutting Conditions Based on Parallel Quasi-Newton Neural Networks and the Dempster-Shafer Theory

PubMed Central

Si, Lei; Wang, Zhongbin; Liu, Xinhua; Tan, Chao; Xu, Jing; Zheng, Kehong

2015-01-01

In order to efficiently and accurately identify the cutting condition of a shearer, this paper proposed an intelligent multi-sensor data fusion identification method using the parallel quasi-Newton neural network (PQN-NN) and the Dempster-Shafer (DS) theory. The vibration acceleration signals and current signal of six cutting conditions were collected from a self-designed experimental system and some special state features were extracted from the intrinsic mode functions (IMFs) based on the ensemble empirical mode decomposition (EEMD). In the experiment, three classifiers were trained and tested by the selected features of the measured data, and the DS theory was used to combine the identification results of three single classifiers. Furthermore, some comparisons with other methods were carried out. The experimental results indicate that the proposed method performs with higher detection accuracy and credibility than the competing algorithms. Finally, an industrial application example in the fully mechanized coal mining face was demonstrated to specify the effect of the proposed system. PMID:26580620

Fault Detection of Roller-Bearings Using Signal Processing and Optimization Algorithms

PubMed Central

Kwak, Dae-Ho; Lee, Dong-Han; Ahn, Jong-Hyo; Koh, Bong-Hwan

2014-01-01

This study presents a fault detection of roller bearings through signal processing and optimization techniques. After the occurrence of scratch-type defects on the inner race of bearings, variations of kurtosis values are investigated in terms of two different data processing techniques: minimum entropy deconvolution (MED), and the Teager-Kaiser Energy Operator (TKEO). MED and the TKEO are employed to qualitatively enhance the discrimination of defect-induced repeating peaks on bearing vibration data with measurement noise. Given the perspective of the execution sequence of MED and the TKEO, the study found that the kurtosis sensitivity towards a defect on bearings could be highly improved. Also, the vibration signal from both healthy and damaged bearings is decomposed into multiple intrinsic mode functions (IMFs), through empirical mode decomposition (EMD). The weight vectors of IMFs become design variables for a genetic algorithm (GA). The weights of each IMF can be optimized through the genetic algorithm, to enhance the sensitivity of kurtosis on damaged bearing signals. Experimental results show that the EMD-GA approach successfully improved the resolution of detectability between a roller bearing with defect, and an intact system. PMID:24368701

Appropriate IMFs associated with cepstrum and envelope analysis for ball-bearing fault diagnosis

NASA Astrophysics Data System (ADS)

Tsao, Wen-Chang; Pan, Min-Chun

2014-03-01

The traditional envelope analysis is an effective method for the fault detection of rolling bearings. However, all the resonant frequency bands must be examined during the bearing-fault detection process. To handle the above deficiency, this paper proposes using the empirical mode decomposition (EMD) to select a proper intrinsic mode function (IMF) for the subsequent detection tools; here both envelope analysis and cepstrum analysis are employed and compared. By virtue of the band-pass filtering nature of EMD, the resonant frequency bands of structure to be measured are captured in the IMFs. As impulses arising from rolling elements striking bearing faults modulate with structure resonance, proper IMFs potentially enable to characterize fault signatures. In the study, faulty ball bearings are used to justify the proposed method, and comparisons with the traditional envelope analysis are made. Post the use of IMFs highlighting faultybearing features, the performance of using envelope analysis and cepstrum analysis to single out bearing faults is objectively compared and addressed; it is noted that generally envelope analysis offers better performance.

Scissors modes: The first overtone

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

Hatada, Keisuke; INFN Laboratori Nazionali di Frascati, c.p. 13, I-00044 Frascati; Hayakawa, Kuniko

2011-07-15

Scissors modes were predicted in the framework of the two-rotor model. This model has an intrinsic harmonic spectrum, so that the level above the scissors mode, the first overtone, has excitation energy twice that of the scissors mode. Because the latter is of the order of 3 MeV in the rare-earth region, the energy of the overtone is below threshold for nucleon emission, and its width should remain small enough for the overtone to be observable. We find that B(E2){up_arrow}{sub overtone}=(1/64 {theta}{sub 0}{sup 2})B(E2){up_arrow}{sub scissors}, where {theta}{sub 0} is the zero-point oscillation amplitude, which in the rare-earth region is ofmore » order 10{sup -1}.« less

Atom detection and photon production in a scalable, open, optical microcavity.

PubMed

Trupke, M; Goldwin, J; Darquié, B; Dutier, G; Eriksson, S; Ashmore, J; Hinds, E A

2007-08-10

A microfabricated Fabry-Perot optical resonator has been used for atom detection and photon production with less than 1 atom on average in the cavity mode. Our cavity design combines the intrinsic scalability of microfabrication processes with direct coupling of the cavity field to single-mode optical waveguides or fibers. The presence of the atom is seen through changes in both the intensity and the noise characteristics of probe light reflected from the cavity input mirror. An excitation laser passing transversely through the cavity triggers photon emission into the cavity mode and hence into the single-mode fiber. These are first steps toward building an optical microcavity network on an atom chip for applications in quantum information processing.

Functional Anthology of Intrinsic Disorder. II. Cellular Components, Domains, Technical Terms, Developmental Processes and Coding Sequence Diversities Correlated with Long Disordered Regions

PubMed Central

Vucetic, Slobodan; Xie, Hongbo; Iakoucheva, Lilia M.; Oldfield, Christopher J.; Dunker, A. Keith; Obradovic, Zoran; Uversky, Vladimir N.

2008-01-01

Biologically active proteins without stable ordered structure (i.e., intrinsically disordered proteins) are attracting increased attention. Functional repertoires of ordered and disordered proteins are very different, and the ability to differentiate whether a given function is associated with intrinsic disorder or with a well-folded protein is crucial for modern protein science. However, there is a large gap between the number of proteins experimentally confirmed to be disordered and their actual number in nature. As a result, studies of functional properties of confirmed disordered proteins, while helpful in revealing the functional diversity of protein disorder, provide only a limited view. To overcome this problem, a bioinformatics approach for comprehensive study of functional roles of protein disorder was proposed in the first paper of this series (Xie H., Vucetic S., Iakoucheva L.M., Oldfield C.J., Dunker A.K., Obradovic Z., Uversky V.N. (2006) Functional anthology of intrinsic disorder. I. Biological processes and functions of proteins with long disordered regions. J. Proteome Res.). Applying this novel approach to Swiss-Prot sequences and functional keywords, we found over 238 and 302 keywords to be strongly positively or negatively correlated, respectively, with long intrinsically disordered regions. This paper describes ~90 Swiss-Prot keywords attributed to the cellular components, domains, technical terms, developmental processes and coding sequence diversities possessing strong positive and negative correlation with long disordered regions. PMID:17391015

Functional anthology of intrinsic disorder. 2. Cellular components, domains, technical terms, developmental processes, and coding sequence diversities correlated with long disordered regions.

PubMed

Vucetic, Slobodan; Xie, Hongbo; Iakoucheva, Lilia M; Oldfield, Christopher J; Dunker, A Keith; Obradovic, Zoran; Uversky, Vladimir N

2007-05-01

Biologically active proteins without stable ordered structure (i.e., intrinsically disordered proteins) are attracting increased attention. Functional repertoires of ordered and disordered proteins are very different, and the ability to differentiate whether a given function is associated with intrinsic disorder or with a well-folded protein is crucial for modern protein science. However, there is a large gap between the number of proteins experimentally confirmed to be disordered and their actual number in nature. As a result, studies of functional properties of confirmed disordered proteins, while helpful in revealing the functional diversity of protein disorder, provide only a limited view. To overcome this problem, a bioinformatics approach for comprehensive study of functional roles of protein disorder was proposed in the first paper of this series (Xie, H.; Vucetic, S.; Iakoucheva, L. M.; Oldfield, C. J.; Dunker, A. K.; Obradovic, Z.; Uversky, V. N. Functional anthology of intrinsic disorder. 1. Biological processes and functions of proteins with long disordered regions. J. Proteome Res. 2007, 5, 1882-1898). Applying this novel approach to Swiss-Prot sequences and functional keywords, we found over 238 and 302 keywords to be strongly positively or negatively correlated, respectively, with long intrinsically disordered regions. This paper describes approximately 90 Swiss-Prot keywords attributed to the cellular components, domains, technical terms, developmental processes, and coding sequence diversities possessing strong positive and negative correlation with long disordered regions.

Genome-Wide Prediction of Intrinsic Disorder; Sequence Alignment of Intrinsically Disordered Proteins

ERIC Educational Resources Information Center

Midic, Uros

2012-01-01

Intrinsic disorder (ID) is defined as a lack of stable tertiary and/or secondary structure under physiological conditions in vitro. Intrinsically disordered proteins (IDPs) are highly abundant in nature. IDPs possess a number of crucial biological functions, being involved in regulation, recognition, signaling and control, e.g. their functional…

Intrinsic Impact and Fatigue Property Degradation of Composite Materials in Sea Water

DTIC Science & Technology

2010-05-26

Erdogan and G. Sih. On the crack extension in plates under plane loading and transverse shear. Journal of Basic Engineering. 85, 1963. 519-527. L. B...using a thin tape . The adhesive was then applied to the other half and the specimen was bonded using a special fixture to guarantee dimensionality...a pure mode II crack is needed, rather than a kinked mode I crack. The angle of the crack kinking can be calculated theoretically ( Erdogan and Sih

Putative role of membranes in the HIV fusion inhibitor enfuvirtide mode of action at the molecular level.

PubMed Central

Veiga, Salomé; Henriques, Sónia; Santos, Nuno C; Castanho, Miguel

2004-01-01

Partition of the intrinsically fluorescent HIV fusion inhibitor enfuvirtide into lipidic membranes is relatively high (Delta G =6.6 kcal x mol(-1)) and modulated by cholesterol. A shallow position in the lipidic matrix makes it readily available for interaction with gp41. No conformational energetic barrier prevents enfuvirtide from being active in both aqueous solution and lipidic membranes. Lipidic membranes may play a key role in the enfuvirtide biochemical mode of action. PMID:14514352

Nonlinear optical magnetometry with accessible in situ optical squeezing

DOE PAGES

Otterstrom, N.; Pooser, R. C.; Lawrie, B. J.

2014-11-14

In this paper, we demonstrate compact and accessible squeezed-light magnetometry using four-wave mixing in a single hot rubidium vapor cell. The strong intrinsic coherence of the four-wave mixing process results in nonlinear magneto-optical rotation (NMOR) on each mode of a two-mode relative-intensity squeezed state. Finally, this framework enables 4.7 dB of quantum noise reduction while the opposing polarization rotation signals of the probe and conjugate fields add to increase the total signal to noise ratio.

Extraction of mobility and Degradation coefficients in double gate junctionless transistors

NASA Astrophysics Data System (ADS)

Bhuvaneshwari, Y. V.; Kranti, Abhinav

2017-12-01

In this work, we use the modified McLarty function to understand and extract accumulation (μ acc) and bulk (μ bulk) mobility in Double Gate (DG) Junctionless (JL) MOSFETs over a wide range of doping concentration (N d) and temperature range (250 K to 520 K). The approach enables the estimation of mobility and its attenuation factors (θ 1 and θ 2) by a single method. The extracted results indicate that μ acc can reach higher values than μ bulk due to the screening effect. Results also show that θ 2 extracted in the accumulation regime of JL transistors exhibit relatively low values in comparison to inversion and accumulation mode devices. It is shown that the attenuation factor (θ 1) in JL devices designed with higher N d (≥1019 cm-3) is mainly affected by series resistance (R sd) whereas, in inversion mode (IM) and Accumulation mode (AM) devices, θ 1 factor is governed by both the intrinsic mobility reduction factor (θ 10) and R sd. Additionally, the impact of variation in oxide thickness (T ox), gate length (L g), N d and temperature on θ 1 and θ 2 has been investigated for JL transistor. The weak dependence of μ bulk and μ acc on temperature shows the prevalence of coulomb scattering over phonon scattering for heavily doped JL transistors. The work provides insights into different modes of operation, extraction of mobility and attenuation factors which will be useful for the development of compact models for JL transistors.

A Reliability Model for Ni-BaTiO3-Based (BME) Ceramic Capacitors

NASA Technical Reports Server (NTRS)

Liu, Donhang

2014-01-01

The evaluation of multilayer ceramic capacitors (MLCCs) with base-metal electrodes (BMEs) for potential NASA space project applications requires an in-depth understanding of their reliability. The reliability of an MLCC is defined as the ability of the dielectric material to retain its insulating properties under stated environmental and operational conditions for a specified period of time t. In this presentation, a general mathematic expression of a reliability model for a BME MLCC is developed and discussed. The reliability model consists of three parts: (1) a statistical distribution that describes the individual variation of properties in a test group of samples (Weibull, log normal, normal, etc.), (2) an acceleration function that describes how a capacitors reliability responds to external stresses such as applied voltage and temperature (All units in the test group should follow the same acceleration function if they share the same failure mode, independent of individual units), and (3) the effect and contribution of the structural and constructional characteristics of a multilayer capacitor device, such as the number of dielectric layers N, dielectric thickness d, average grain size r, and capacitor chip size S. In general, a two-parameter Weibull statistical distribution model is used in the description of a BME capacitors reliability as a function of time. The acceleration function that relates a capacitors reliability to external stresses is dependent on the failure mode. Two failure modes have been identified in BME MLCCs: catastrophic and slow degradation. A catastrophic failure is characterized by a time-accelerating increase in leakage current that is mainly due to existing processing defects (voids, cracks, delamination, etc.), or the extrinsic defects. A slow degradation failure is characterized by a near-linear increase in leakage current against the stress time; this is caused by the electromigration of oxygen vacancies (intrinsic defects). The two identified failure modes follow different acceleration functions. Catastrophic failures follow the traditional power-law relationship to the applied voltage. Slow degradation failures fit well to an exponential law relationship to the applied electrical field. Finally, the impact of capacitor structure on the reliability of BME capacitors is discussed with respect to the number of dielectric layers in an MLCC unit, the number of BaTiO3 grains per dielectric layer, and the chip size of the capacitor device.

Computational modeling of intrinsic dissipation in nano-structure

NASA Astrophysics Data System (ADS)

Kunal, Kumar

In this work, using computational modeling, we study the different mechanisms of intrinsic dissipation in nano-electro mechanical systems (NEMS). We, first, use molecular dynamics (MD) simulation and gain an understanding of the underlying loss mechanisms. Using insights from the MD simulation, a multi-scale method to model intrinsic damping is developed. The high frequency vibration in NEMS have important applications. A few examples include the sensing of atomic mass, detection of biological molecules and observation of quantum effects in macroscopic objects. For all these potential applications, dissipation plays a limiting role. While a number of experimental and theoretical studies have been performed, the individual role of different mechanisms remains unclear. In this work, we attempt to isolate and understand the surface and size effect on some of the intrinsic mechanisms. We, first, consider the case of the Akhiezer damping. The Akhiezer dynamics is expected to play an important role in nano-resonators with frequencies in the GHz range. Using a judiciously devised MD set-up, we isolate Akhiezer dynamics. We show that the surfaces aid in reducing the dissipation rate through increasing the rate of thermalization of the phonons. We, next, study damping under the flexure mode of operation. A comparative analysis with the stretching mode shows that the flexure mode is less dissipative. A reduced order model is considered to understand this novel behavior. We, also, investigate the role of tension on the Q factor, a measure of the inverse of dissipation rate. From these studies, we conclude that Akhiezer dynamics plays a dominant role in nano-resonators. We, then, develop a quasi-harmonic based multi-scale method to model Akhiezer damping. A stress component, that characterizes the non-equilibrium phonon population, is derived. We obtain constitutive relation that governs the time evolution of the non-equilibrium stress. Different methods to parametrize the constitutive relation are discussed. Using the proposed formulation, we compute the dissipation rate for different cases. The results are compared with those obtained using MD. Next, we use the Boltzmann transport equation and investigate the Q factor due to the thermo-elastic dissipation (TED). The Q factor obtained shows deviations from the classical theory of TED. Correction to the classical formula, for the case of longitudinal modes, is provided. We, then, study damping is low dimensional structure. We first consider the case of two dimensional graphene sheet and under in-plane stretching. We show that the coupling between the in-plane and the out-of-plane motions plays an important role in the loss of mechanical energy. Further, a hysteresis behavior in the out-of-plane dynamics is observed. Next, we investigate the stretching motion of graphene nano-ribbon. A normal mode Langevin dynamics is devised to understand the results from the MD simulation.

Functions of intrinsic disorder in transmembrane proteins.

PubMed

Kjaergaard, Magnus; Kragelund, Birthe B

2017-09-01

Intrinsic disorder is common in integral membrane proteins, particularly in the intracellular domains. Despite this observation, these domains are not always recognized as being disordered. In this review, we will discuss the biological functions of intrinsically disordered regions of membrane proteins, and address why the flexibility afforded by disorder is mechanistically important. Intrinsically disordered regions are present in many common classes of membrane proteins including ion channels and transporters; G-protein coupled receptors (GPCRs), receptor tyrosine kinases and cytokine receptors. The functions of the disordered regions are many and varied. We will discuss selected examples including: (1) Organization of receptors, kinases, phosphatases and second messenger sources into signaling complexes. (2) Modulation of the membrane-embedded domain function by ball-and-chain like mechanisms. (3) Trafficking of membrane proteins. (4) Transient membrane associations. (5) Post-translational modifications most notably phosphorylation and (6) disorder-linked isoform dependent function. We finish the review by discussing the future challenges facing the membrane protein community regarding protein disorder.

Intrinsic superspin Hall current

NASA Astrophysics Data System (ADS)

Linder, Jacob; Amundsen, Morten; Risinggârd, Vetle

2017-09-01

We discover an intrinsic superspin Hall current: an injected charge supercurrent in a Josephson junction containing heavy normal metals and a ferromagnet generates a transverse spin supercurrent. There is no accompanying dissipation of energy, in contrast to the conventional spin Hall effect. The physical origin of the effect is an antisymmetric spin density induced among transverse modes ky near the interface of the superconductor arising due to the coexistence of p -wave and conventional s -wave superconducting correlations with a belonging phase mismatch. Our predictions can be tested in hybrid structures including thin heavy metal layers combined with strong ferromagnets and ordinary s -wave superconductors.

Probing Intrinsic Resting-State Networks in the Infant Rat Brain

PubMed Central

Bajic, Dusica; Craig, Michael M.; Borsook, David; Becerra, Lino

2016-01-01

Resting-state functional magnetic resonance imaging (rs-fMRI) measures spontaneous fluctuations in blood oxygenation level-dependent (BOLD) signal in the absence of external stimuli. It has become a powerful tool for mapping large-scale brain networks in humans and animal models. Several rs-fMRI studies have been conducted in anesthetized and awake adult rats, reporting consistent patterns of brain activity at the systems level. However, the evolution to adult patterns of resting-state activity has not yet been evaluated and quantified in the developing rat brain. In this study, we hypothesized that large-scale intrinsic networks would be easily detectable but not fully established as specific patterns of activity in lightly anesthetized 2-week-old rats (N = 11). Independent component analysis (ICA) identified 8 networks in 2-week-old-rats. These included Default mode, Sensory (Exteroceptive), Salience (Interoceptive), Basal Ganglia-Thalamic-Hippocampal, Basal Ganglia, Autonomic, Cerebellar, as well as Thalamic-Brainstem networks. Many of these networks consisted of more than one component, possibly indicative of immature, underdeveloped networks at this early time point. Except for the Autonomic network, infant rat networks showed reduced connectivity with subcortical structures in comparison to previously published adult networks. Reported slow fluctuations in the BOLD signal that correspond to functionally relevant resting-state networks in 2-week-old rats can serve as an important tool for future studies of brain development in the settings of different pharmacological applications or disease. PMID:27803653

Physics and Control of Locked Modes in the DIII-D Tokamak

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

Volpe, Francesco

This Final Technical Report summarizes an investigation, carried out under the auspices of the DOE Early Career Award, of the physics and control of non-rotating magnetic islands (“locked modes”) in tokamak plasmas. Locked modes are one of the main causes of disruptions in present tokamaks, and could be an even bigger concern in ITER, due to its relatively high beta (favoring the formation of Neoclassical Tearing Mode islands) and low rotation (favoring locking). For these reasons, this research had the goal of studying and learning how to control locked modes in the DIII-D National Fusion Facility under ITER-relevant conditions ofmore » high pressure and low rotation. Major results included: the first full suppression of locked modes and avoidance of the associated disruptions; the demonstration of error field detection from the interaction between locked modes, applied rotating fields and intrinsic errors; the analysis of a vast database of disruptive locked modes, which led to criteria for disruption prediction and avoidance.« less

Distinct turbulence sources and confinement features in the spherical tokamak plasma regime

DOE PAGES

Wang, W. X.; Ethier, S.; Ren, Y.; ...

2015-10-30

New turbulence contributions to plasma transport and confinement in the spherical tokamak (ST) regime are identified through nonlinear gyrokinetic simulations. The drift wave Kelvin-Helmholtz (KH) mode characterized by intrinsic mode asymmetry is shown to drive significant ion thermal transport in strongly rotating national spherical torus experiment (NSTX) L-modes. The long wavelength, quasi-coherent dissipative trapped electron mode (TEM) is destabilized in NSTX H-modes despite the presence of strong E x B shear, providing a robust turbulence source dominant over collisionless TEM. Dissipative trapped electron mode (DTEM)-driven transport in the NSTX parametric regime is shown to increase with electron collision frequency, offeringmore » one possible source for the confinement scaling observed in experiments. There exists a turbulence-free regime in the collision-induced collisionless trapped electron mode to DTEM transition for ST plasmas. In conclusion, this predicts a natural access to a minimum transport state in the low collisionality regime that future advanced STs may cover.« less

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

Collins, Liam; Belianinov, Alex; Proksch, Roger

We develop a full information capture approach for Magnetic Force Microscopy (MFM), referred to as generalized mode (G-Mode) MFM. G-Mode MFM acquires and stores the full data stream from the photodetector at sampling rates approaching the intrinsic photodiode limit. The data can be subsequently compressed, denoised, and analyzed, without information loss. Also, 3 G-Mode MFM is implemented and compared to traditional heterodyne based MFM on model systems including domain structures in ferromagnetic Yttrium Iron Garnet (YIG) and electronically and magnetically inhomogeneous high entropy alloy, CoFeMnNiSn. We investigate the use of information theory to mine the G-Mode MFM data and demonstratemore » its usefulness for extracting information which may be hidden in traditional MFM modes, including signatures of nonlinearities and mode coupling phenomena. Finally we demonstrate detection and separation of magnetic and electrostatic tip-sample interactions from a single G-Mode image, by analyzing the entire frequency response of the cantilever. G-Mode MFM is immediately implementable on any AFM platform and as such is expected to be a useful technique for probing spatiotemporal cantilever dynamics and mapping material properties as well as their mutual interactions.« less

Ovary and fimbrial stem cells: biology, niche and cancer origins.

PubMed

Ng, Annie; Barker, Nick

2015-10-01

The mammalian ovary is covered by a single-layered epithelium that undergoes rupture and remodelling following each ovulation. Although resident stem cells are presumed to be crucial for this cyclic regeneration, their identity and mode of action have been elusive. Surrogate stemness assays and in vivo fate-mapping studies using recently discovered stem cell markers have identified stem cell pools in the ovary and fimbria that ensure epithelial homeostasis. Recent findings provide insights into intrinsic mechanisms and local extrinsic cues that govern the function of ovarian and fimbrial stem cells. These discoveries have advanced our understanding of stem cell biology in the ovary and fimbria, and lay the foundations for evaluating the contribution of resident stem cells to the initiation and progression of human epithelial ovarian cancer.

Intrinsic electrical properties of mammalian neurons and CNS function: a historical perspective

PubMed Central

Llinás, Rodolfo R.

2014-01-01

This brief review summarizes work done in mammalian neuroscience concerning the intrinsic electrophysiological properties of four neuronal types; Cerebellar Purkinje cells, inferior olivary cells, thalamic cells, and some cortical interneurons. It is a personal perspective addressing an interesting time in neuroscience when the reflex view of brain function, as the paradigm to understand global neuroscience, began to be modified toward one in which sensory input modulates rather than dictates brain function. The perspective of the paper is not a comprehensive description of the intrinsic electrical properties of all nerve cells but rather addresses a set of cell types that provide indicative examples of mechanisms that modulate brain function. PMID:25408634

Functionality of intrinsic disorder in tumor necrosis factor-α and its receptors.

PubMed

Uversky, Vladimir N; El-Baky, Nawal Abd; El-Fakharany, Esmail M; Sabry, Amira; Mattar, Ehab H; Uversky, Alexey V; Redwan, Elrashdy M

2017-11-01

Tumor necrosis factor-α (TNF-α) is a pleiotropic inflammatory cytokine that exerts potent cytotoxic effects on solid tumor cells, while not affecting their normal counterparts. It is also known that TNF-α exerts many of its biological functions via interaction with specific receptors. To understand the potential roles of intrinsic disorder in the functioning of this important cytokine, we explored the peculiarities of intrinsic disorder distribution in human TNF-α and its homologs from various species, ranging from zebrafish to chimpanzee. We also studied the peculiarities of intrinsic disorder distribution in human TNF-α receptors, TNFR1 and TNFR2. Analysis revealed that cytoplasmic domains of TNF-α and its receptors are expected to be highly disordered. Furthermore, although the sequence identities of analyzed TNF-α homologs range from 99.57% (between human and chimpanzee proteins) to 22.33% (between frog and fish proteins), their intrinsic disorder profiles are characterized by a remarkable similarity. These observations indicate that the peculiarities of distribution of the intrinsic disorder propensity within the amino acid sequences are evolutionary conserved, and therefore could be of functional importance for this family of proteins. We also show that disordered and flexible regions of human TNF-α and its TNFR1 and TNFR2 receptors are crucial for some of their biological activities. © 2017 Federation of European Biochemical Societies.

CzeV293 and CzeV581-Two new high-amplitude double-mode delta Scuti stars

NASA Astrophysics Data System (ADS)

Skarka, M.; Cagaš, P.

2016-07-01

We report on the discovery of two high-amplitude double-mode delta Scuti stars in constellations of Hercules and Auriga. The stars were observed photometrically in five and two seasons, respectively. Frequency analysis revealed that both stars show complex pulsation behaviour with two independent modes and several combination peaks. Placing the stars into the Petersen diagram allowed us to identify the pulsation modes as the fundamental and the first overtone. Both stars follow the general trend for F/1O pulsators in the short-period part of the Petersen diagram and turned out to be classical members of HADS group of variables. Using empirical formulae we roughly estimate visual absolute magnitude, intrinsic (B - V) 0 colour index and temperature of the target stars.

Phase noise characterization of a QD-based diode laser frequency comb.

PubMed

Vedala, Govind; Al-Qadi, Mustafa; O'Sullivan, Maurice; Cartledge, John; Hui, Rongqing

2017-07-10

We measure, simultaneously, the phases of a large set of comb lines from a passively mode locked, InAs/InP, quantum dot laser frequency comb (QDLFC) by comparing the lines to a stable comb reference using multi-heterodyne coherent detection. Simultaneity permits the separation of differential and common mode phase noise and a straightforward determination of the wavelength corresponding to the minimum width of the comb line. We find that the common mode and differential phases are uncorrelated, and measure for the first time for a QDLFC that the intrinsic differential-mode phase (IDMP) between adjacent subcarriers is substantially the same for all subcarrier pairs. The latter observation supports an interpretation of 4.4ps as the standard deviation of IDMP on a 200µs time interval for this laser.

Resonant Raman spectra of grades of human brain glioma tumors reveal the content of tryptophan by the 1588 cm-1 mode

NASA Astrophysics Data System (ADS)

Zhou, Yan; Liu, Cheng-hui; Zhou, Lixin; Zhu, Ke; Liu, Yulong; Zhang, Lin; Boydston-White, Susie; Cheng, Gangge; Pu, Yang; Bidyut, Das; Alfano, Robert R.

2015-03-01

RR spectra of brain normal tissue, gliomas in low grade I and II, and malignant glioma tumors in grade III and IV were measured using a confocal micro Raman spectrometer. This report focus on the relative contents of tryptophan (W) in various grades of brain glioma tumors by the intrinsic molecular resonance Raman (RR) spectroscopy method using the 1588cm-1 of tryptophan mode by 532 nm excitation. The RR spectra of key fingerprints of tryptophan, with a main vibrational mode at 1588cm-1 (W8b), were observed. It was found that tryptophan contribution was accumulated in grade I to IV gliomas and the mode of 1588cm-1 in grade III and IV malignant gliomas were enhanced by resonance.

Variability in Cumulative Habitual Sleep Duration Predicts Waking Functional Connectivity.

PubMed

Khalsa, Sakh; Mayhew, Stephen D; Przezdzik, Izabela; Wilson, Rebecca; Hale, Joanne; Goldstone, Aimee; Bagary, Manny; Bagshaw, Andrew P

2016-01-01

We examined whether interindividual differences in habitual sleep patterns, quantified as the cumulative habitual total sleep time (cTST) over a 2-w period, were reflected in waking measurements of intranetwork and internetwork functional connectivity (FC) between major nodes of three intrinsically connected networks (ICNs): default mode network (DMN), salience network (SN), and central executive network (CEN). Resting state functional magnetic resonance imaging (fMRI) study using seed-based FC analysis combined with 14-d wrist actigraphy, sleep diaries, and subjective questionnaires (N = 33 healthy adults, mean age 34.3, standard deviation ± 11.6 y). Data were statistically analyzed using multiple linear regression. Fourteen consecutive days of wrist actigraphy in participant's home environment and fMRI scanning on day 14 at the Birmingham University Imaging Centre. Seed-based FC analysis on ICNs from resting-state fMRI data and multiple linear regression analysis performed for each ICN seed and target. cTST was used to predict FC (controlling for age). cTST was specific predictor of intranetwork FC when the mesial prefrontal cortex (MPFC) region of the DMN was used as a seed for FC, with a positive correlation between FC and cTST observed. No significant relationship between FC and cTST was seen for any pair of nodes not including the MPFC. Internetwork FC between the DMN (MPFC) and SN (right anterior insula) was also predicted by cTST, with a negative correlation observed between FC and cTST. This study improves understanding of the relationship between intranetwork and internetwork functional connectivity of intrinsically connected networks (ICNs) in relation to habitual sleep quality and duration. The cumulative amount of sleep that participants achieved over a 14-d period was significantly predictive of intranetwork and inter-network functional connectivity of ICNs, an observation that may underlie the link between sleep status and cognitive performance. © 2016 Associated Professional Sleep Societies, LLC.

Anomalous Ion Heating, Intrinsic and Induced Rotation in the Pegasus Toroidal Experiment

NASA Astrophysics Data System (ADS)

Burke, M. G.; Barr, J. L.; Bongard, M. W.; Fonck, R. J.; Hinson, E. T.; Perry, J. M.; Redd, A. J.; Thome, K. E.

2014-10-01

Pegasus plasmas are initiated through either standard, MHD stable, inductive current drive or non-solenoidal local helicity injection (LHI) current drive with strong reconnection activity, providing a rich environment to study ion dynamics. During LHI discharges, a large amount of anomalous impurity ion heating has been observed, with Ti ~ 800 eV but Te < 100 eV. The ion heating is hypothesized to be a result of large-scale magnetic reconnection activity, as the amount of heating scales with increasing fluctuation amplitude of the dominant, edge localized, n = 1 MHD mode. Chordal Ti spatial profiles indicate centrally peaked temperatures, suggesting a region of good confinement near the plasma core surrounded by a stochastic region. LHI plasmas are observed to rotate, perhaps due to an inward radial current generated by the stochastization of the plasma edge by the injected current streams. H-mode plasmas are initiated using a combination of high-field side fueling and Ohmic current drive. This regime shows a significant increase in rotation shear compared to L-mode plasmas. In addition, these plasmas have been observed to rotate in the counter-Ip direction without any external momentum sources. The intrinsic rotation direction is consistent with predictions from the saturated Ohmic confinement regime. Work supported by US DOE Grant DE-FG02-96ER54375.

Electroconvulsive therapy-induced brain functional connectivity predicts therapeutic efficacy in patients with schizophrenia: a multivariate pattern recognition study.

PubMed

Li, Peng; Jing, Ri-Xing; Zhao, Rong-Jiang; Ding, Zeng-Bo; Shi, Le; Sun, Hong-Qiang; Lin, Xiao; Fan, Teng-Teng; Dong, Wen-Tian; Fan, Yong; Lu, Lin

2017-05-11

Previous studies suggested that electroconvulsive therapy can influence regional metabolism and dopamine signaling, thereby alleviating symptoms of schizophrenia. It remains unclear what patients may benefit more from the treatment. The present study sought to identify biomarkers that predict the electroconvulsive therapy response in individual patients. Thirty-four schizophrenia patients and 34 controls were included in this study. Patients were scanned prior to treatment and after 6 weeks of treatment with antipsychotics only (n = 16) or a combination of antipsychotics and electroconvulsive therapy (n = 13). Subject-specific intrinsic connectivity networks were computed for each subject using a group information-guided independent component analysis technique. Classifiers were built to distinguish patients from controls and quantify brain states based on intrinsic connectivity networks. A general linear model was built on the classification scores of first scan (referred to as baseline classification scores) to predict treatment response. Classifiers built on the default mode network, the temporal lobe network, the language network, the corticostriatal network, the frontal-parietal network, and the cerebellum achieved a cross-validated classification accuracy of 83.82%, with specificity of 91.18% and sensitivity of 76.47%. After the electroconvulsive therapy, psychosis symptoms of the patients were relieved and classification scores of the patients were decreased. Moreover, the baseline classification scores were predictive for the treatment outcome. Schizophrenia patients exhibited functional deviations in multiple intrinsic connectivity networks which were able to distinguish patients from healthy controls at an individual level. Patients with lower classification scores prior to treatment had better treatment outcome, indicating that the baseline classification scores before treatment is a good predictor for treatment outcome. CONNECTIVITY NETWORKS REVEAL GOOD CANDIDATES FOR BRAIN STIMULATION: Connectivity patterns in the brain may help identify patients with schizophrenia most likely to benefit from electroconvulsive therapy. A team led by Lin Lu from Peking University, China, and Yong Fan from the University of Pennsylvania, USA, took functional magnetic resonance imaging (MRI) scans of 34 people with schizophrenia and 34 control individuals without mental illness. Those with schizophrenia were scanned before and after treatment; some received antipsychotics alone, others received medication plus electroconvulsive therapy. The researchers created organizational brain maps known as "intrinsic connectivity networks" for each individual, and showed that the neuroimaging pattern could discriminate between people with and without schizophrenia. For the schizophrenia patients, the connectivity networks taken prior to treatment also helped predict who would benefit from the brain-stimulation procedure. Such a biomarker could prove a useful diagnostic tool for clinicians.

Extracting Intrinsic Functional Networks with Feature-Based Group Independent Component Analysis

ERIC Educational Resources Information Center

Calhoun, Vince D.; Allen, Elena

2013-01-01

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…

Hyperparametric effects in a whispering-gallery mode rutile dielectric resonator at liquid helium temperatures

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

Nand, Nitin R.; Goryachev, Maxim; Floch, Jean-Michel le

2014-10-07

We report the first observation of low power drive level sensitivity, hyperparametric amplification, and single-mode hyperparametric oscillations in a dielectric rutile whispering-gallery mode resonator at 4.2 K. The latter gives rise to a comb of sidebands at 19.756 GHz. Whereas, most frequency combs in the literature have been observed in optical systems using an ensemble of equally spaced modes in microresonators or fibers, the present work represents generation of a frequency comb using only a single-mode. The experimental observations are explained by an additional 1/2 degree-of-freedom originating from an intrinsic material nonlinearity at optical frequencies, which affects the microwave propertiesmore » due to the extremely low loss of rutile. Using a model based on lumped circuits, we demonstrate that the resonance between the photonic and material 1/2 degree-of-freedom, is responsible for the hyperparametric energy transfer in the system.« less

Study of parametric instability in gravitational wave detectors with silicon test masses

NASA Astrophysics Data System (ADS)

Zhang, Jue; Zhao, Chunnong; Ju, Li; Blair, David

2017-03-01

Parametric instability is an intrinsic risk in high power laser interferometer gravitational wave detectors, in which the optical cavity modes interact with the acoustic modes of the mirrors, leading to exponential growth of the acoustic vibration. In this paper, we investigate the potential parametric instability for a proposed next generation gravitational wave detector, the LIGO Voyager blue design, with cooled silicon test masses of size 45 cm in diameter and 55 cm in thickness. It is shown that there would be about two unstable modes per test mass at an arm cavity power of 3 MW, with the highest parametric gain of  ∼76. While this is less than the predicted number of unstable modes for Advanced LIGO (∼40 modes with max gain of  ∼32 at the designed operating power of 830 kW), the importance of developing suitable instability suppression schemes is emphasized.

Brain Connectivity in Pathological and Pharmacological Coma

PubMed Central

Noirhomme, Quentin; Soddu, Andrea; Lehembre, Rémy; Vanhaudenhuyse, Audrey; Boveroux, Pierre; Boly, Mélanie; Laureys, Steven

2010-01-01

Recent studies in patients with disorders of consciousness (DOC) tend to support the view that awareness is not related to activity in a single brain region but to thalamo-cortical connectivity in the frontoparietal network. Functional neuroimaging studies have shown preserved albeit disconnected low-level cortical activation in response to external stimulation in patients in a “vegetative state” or unresponsive wakefulness syndrome. While activation of these “primary” sensory cortices does not necessarily reflect conscious awareness, activation in higher-order associative cortices in minimally conscious state patients seems to herald some residual perceptual awareness. PET studies have identified a metabolic dysfunction in a widespread frontoparietal “global neuronal workspace” in DOC patients including the midline default mode network (“intrinsic” system) and the lateral frontoparietal cortices or “extrinsic system.” Recent studies have investigated the relation of awareness to the functional connectivity within intrinsic and extrinsic networks, and with the thalami in both pathological and pharmacological coma. In brain damaged patients, connectivity in all default network areas was found to be non-linearly correlated with the degree of clinical consciousness impairment, ranging from healthy controls and locked-in syndrome to minimally conscious, vegetative, coma, and brain dead patients. Anesthesia-induced loss of consciousness was also shown to correlate with a global decrease in cortico-cortical and thalamo-cortical connectivity in both intrinsic and extrinsic networks, but not in auditory, or visual networks. In anesthesia, unconsciousness was also associated with a loss of cross-modal interactions between networks. These results suggest that conscious awareness critically depends on the functional integrity of thalamo-cortical and cortico-cortical frontoparietal connectivity within and between “intrinsic” and “extrinsic” brain networks. PMID:21191476

Resting state connectivity of the medial prefrontal cortex covaries with individual differences in high-frequency heart rate variability.

PubMed

Jennings, J Richard; Sheu, Lei K; Kuan, Dora C-H; Manuck, Stephen B; Gianaros, Peter J

2016-04-01

Resting high-frequency heart rate variability (HF-HRV) relates to cardiac vagal control and predicts individual differences in health and longevity, but its functional neural correlates are not well defined. The medial prefrontal cortex (mPFC) encompasses visceral control regions that are components of intrinsic networks of the brain, particularly the default mode network (DMN) and the salience network (SN). Might individual differences in resting HF-HRV covary with resting state neural activity in the DMN and SN, particularly within the mPFC? This question was addressed using fMRI data from an eyes-open, 5-min rest period during which echoplanar brain imaging yielded BOLD time series. Independent component analysis yielded functional connectivity estimates defining the DMN and SN. HF-HRV was measured in a rest period outside of the scanner. Midlife (52% female) adults were assessed in two studies (Study 1, N = 107; Study 2, N = 112). Neither overall DMN nor SN connectivity strength was related to HF-HRV. However, HF-HRV related to connectivity of one region within mPFC shared by the DMN and SN, namely, the perigenual anterior cingulate cortex, an area with connectivity to other regions involved in autonomic control. In sum, HF-HRV does not seem directly related to global resting state activity of intrinsic brain networks, but rather to more localized connectivity. A mPFC region was of particular interest as connectivity related to HF-HRV was shared by the DMN and SN. These findings may indicate a functional basis for the coordination of autonomic cardiac control with engagement and disengagement from the environment. © 2015 Society for Psychophysiological Research.

Conformational State Distributions and Catalytically Relevant Dynamics of a Hinge-Bending Enzyme Studied by Single-Molecule FRET and a Coarse-Grained Simulation

PubMed Central

Gabba, Matteo; Poblete, Simón; Rosenkranz, Tobias; Katranidis, Alexandros; Kempe, Daryan; Züchner, Tina; Winkler, Roland G.; Gompper, Gerhard; Fitter, Jörg

2014-01-01

Over the last few decades, a view has emerged showing that multidomain enzymes are biological machines evolved to harness stochastic kicks of solvent particles into highly directional functional motions. These intrinsic motions are structurally encoded, and Nature makes use of them to catalyze chemical reactions by means of ligand-induced conformational changes and states redistribution. Such mechanisms align reactive groups for efficient chemistry and stabilize conformers most proficient for catalysis. By combining single-molecule Förster resonance energy transfer measurements with normal mode analysis and coarse-grained mesoscopic simulations, we obtained results for a hinge-bending enzyme, namely phosphoglycerate kinase (PGK), which support and extend these ideas. From single-molecule Förster resonance energy transfer, we obtained insight into the distribution of conformational states and the dynamical properties of the domains. The simulations allowed for the characterization of interdomain motions of a compact state of PGK. The data show that PGK is intrinsically a highly dynamic system sampling a wealth of conformations on timescales ranging from nanoseconds to milliseconds and above. Functional motions encoded in the fold are performed by the PGK domains already in its ligand-free form, and substrate binding is not required to enable them. Compared to other multidomain proteins, these motions are rather fast and presumably not rate-limiting in the enzymatic reaction. Ligand binding slightly readjusts the orientation of the domains and feasibly locks the protein motions along a preferential direction. In addition, the functionally relevant compact state is stabilized by the substrates, and acts as a prestate to reach active conformations by means of Brownian motions. PMID:25418172

Evaluating aquatic invertebrate vulnerability to insecticides based on intrinsic sensitivity, biological traits, and toxic mode of action.

PubMed

Rico, Andreu; Van den Brink, Paul J

2015-08-01

In the present study, the authors evaluated the vulnerability of aquatic invertebrates to insecticides based on their intrinsic sensitivity and their population-level recovery potential. The relative sensitivity of invertebrates to 5 different classes of insecticides was calculated at the genus, family, and order levels using the acute toxicity data available in the US Environmental Protection Agency ECOTOX database. Biological trait information was linked to the calculated relative sensitivity to evaluate correlations between traits and sensitivity and to calculate a vulnerability index, which combines intrinsic sensitivity and traits describing the recovery potential of populations partially exposed to insecticides (e.g., voltinism, flying strength, occurrence in drift). The analysis shows that the relative sensitivity of arthropods depends on the insecticide mode of action. Traits such as degree of sclerotization, size, and respiration type showed good correlation to sensitivity and can be used to make predictions for invertebrate taxa without a priori sensitivity knowledge. The vulnerability analysis revealed that some of the Ephemeroptera, Plecoptera, and Trichoptera taxa were vulnerable to all insecticide classes and indicated that particular gastropod and bivalve species were potentially vulnerable. Microcrustaceans (e.g., daphnids, copepods) showed low potential vulnerability, particularly in lentic ecosystems. The methods described in the present study can be used for the selection of focal species to be included as part of ecological scenarios and higher tier risk assessments. © 2015 SETAC.

External control of semiconductor nanostructure lasers

NASA Astrophysics Data System (ADS)

Naderi, Nader A.

2011-12-01

Novel semiconductor nanostructure laser diodes such as quantum-dot and quantum-dash are key optoelectronic candidates for many applications such as data transmitters in ultra fast optical communications. This is mainly due to their unique carrier dynamics compared to conventional quantum-well lasers that enables their potential for high differential gain and modified linewidth enhancement factor. However, there are known intrinsic limitations associated with semiconductor laser dynamics that can hinder the performance including the mode stability, spectral linewidth, and direct modulation capabilities. One possible method to overcome these limitations is through the use of external control techniques. The electrical and/or optical external perturbations can be implemented to improve the parameters associated with the intrinsic laser's dynamics, such as threshold gain, damping rate, spectral linewidth, and mode selectivity. In this dissertation, studies on the impact of external control techniques through optical injection-locking, optical feedback and asymmetric current bias control on the overall performance of the nanostructure lasers were conducted in order to understand the associated intrinsic device limitations and to develop strategies for controlling the underlying dynamics to improve laser performance. In turn, the findings of this work can act as a guideline for making high performance nanostructure lasers for future ultra fast data transmitters in long-haul optical communication systems, and some can provide an insight into making a compact and low-cost terahertz optical source for future implementation in monolithic millimeter-wave integrated circuits.

Anisotropic lattice thermal expansion of PbFeBO 4: A study by X-ray and neutron diffraction, Raman spectroscopy and DFT calculations

DOE PAGES

Murshed, M. Mangir; Mendive, Cecilia B.; Curti, Mariano; ...

2014-11-01

We present the lattice thermal expansion of mullite-type PbFeBO 4 in this study. The thermal expansion coefficients of the metric parameters were obtained from composite data collected from temperature-dependent neutron and X-ray powder diffraction between 10 K and 700 K. The volume thermal expansion was modeled using extended Grüneisen first-order approximation to the zero-pressure equation of state. The additive frame of the model includes harmonic, quasi-harmonic and intrinsic anharmonic potentials to describe the change of the internal energy as a function of temperature. Moreover, the unit-cell volume at zero-pressure and 0 K was optimized during the DFT simulations. Harmonic frequenciesmore » of the optical Raman modes at the Γ-point of the Brillouin zone at 0 K were also calculated by DFT, which help to assign and crosscheck the experimental frequencies. The low-temperature Raman spectra showed significant anomaly in the antiferromagnetic regions, leading to softening or hardening of some phonons. Selected modes were analyzed using a modified Klemens model. The shift of the frequencies and the broadening of the line-widths helped to understand the anharmonic vibrational behaviors of the PbO4, FeO6 and BO3 polyhedra as a function of temperature.« less

Desynchronization and Plasticity of Striato-frontal Connectivity in Major Depressive Disorder.

PubMed

Leaver, Amber M; Espinoza, Randall; Joshi, Shantanu H; Vasavada, Megha; Njau, Stephanie; Woods, Roger P; Narr, Katherine L

2016-10-17

Major depressive disorder (MDD) is associated with dysfunctional corticolimbic networks, making functional connectivity studies integral for understanding the mechanisms underlying MDD pathophysiology and treatment. Resting-state functional connectivity (RSFC) studies analyze patterns of temporally coherent intrinsic brain activity in "resting-state networks" (RSNs). The default-mode network (DMN) has been of particular interest to depression research; however, a single RSN is unlikely to capture MDD pathophysiology in its entirety, and the DMN itself can be characterized by multiple RSNs. This, coupled with conflicting previous results, underscores the need for further research. Here, we measured RSFC in MDD by targeting RSNs overlapping with corticolimbic regions and further determined whether altered patterns of RSFC were restored with electroconvulsive therapy (ECT). MDD patients exhibited hyperconnectivity between ventral striatum (VS) and the ventral default-mode network (vDMN), while simultaneously demonstrating hypoconnectivity with the anterior DMN (aDMN). ECT influenced this pattern: VS-vDMN hyperconnectivity was significantly reduced while VS-aDMN hypoconnectivity only modestly improved. RSFC between the salience RSN and dorsomedial prefrontal cortex was also reduced in MDD, but was not affected by ECT. Taken together, our results support a model of ventral/dorsal imbalance in MDD and further suggest that the VS is a key structure contributing to this desynchronization. © The Author 2015. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

Cognitive and behavioral comorbidities in Rolandic epilepsy and their relation with default mode network's functional connectivity and organization.

PubMed

Ofer, Isabell; Jacobs, Julia; Jaiser, Nathalie; Akin, Burak; Hennig, Jürgen; Schulze-Bonhage, Andreas; LeVan, Pierre

2018-01-01

Rolandic epilepsy (RE) is characterized by typical interictal-electroencephalogram (EEG) patterns mainly localized in centrotemporal and parietooccipital areas. An aberrant intrinsic organization of the default mode network (DMN) due to repeated disturbances from spike-generating areas may be able to account for specific cognitive deficits and behavioral problems in RE. The aim of the present study was to investigate cognitive development (CD) and socioemotional development (SED) in patients with RE during active disease in relation to DMN connectivity and network topology. In 10 children with RE and active EEG, CD was assessed using the Wechsler Intelligence Scale for Children-IV (WISC-IV); SED was assessed using the Fünf-Faktoren-Fragebogen für Kinder (FFFK), a Big-Five inventory for the assessment of personality traits in children. Functional connectivity (FC) in the DMN was determined from a 15-minute resting state functional magnetic resonance imaging (fMRI), and network properties were calculated using standard graph-theoretical measures. More severe deficits of verbal abilities tended to be associated with an earlier age at epilepsy onset, but were not directly related to the number of seizures and disease duration. Nonetheless, at the network level, disease duration was associated with alterations of the efficiency and centrality of parietal network nodes and midline structures. Particularly, centrality of the left inferior parietal lobe (IPL) was found to be linked with CD. Reduced centrality of the left IPL and alterations supporting a rather segregated processing within DMN's subsystems was associated with a more favorable CD. A more complicated SED was associated with high seizure frequency and long disease duration, and revealed links with a less favorable CD. An impaired CD and - because of their interrelation - SED might be mediated by a common pathomechanism reflected in an aberrant organization, and thus, a potential functional deficit of the DMN. A functional segregation of (left) parietal network nodes from the DMN and a rather segregated processing mode within the DMN might have positive implications/protective value for CD in patients with RE. Copyright © 2017 Elsevier Inc. All rights reserved.

Relationship between cognitive function and prevalence of decrease in intrinsic academic motivation in adolescents

PubMed Central

2011-01-01

Background Decrease in intrinsic motivation is a common complaint among elementary and junior high school students, and is related to poor academic performance. Since grade-dependent development of cognitive functions also influences academic performance by these students, we examined whether cognitive functions are related to the prevalence of decrease in intrinsic academic motivation. Methods The study group consisted of 134 elementary school students from 4th to 6th grades and 133 junior high school students from 7th to 9th grades. Participants completed a questionnaire on intrinsic academic motivation. They also performed paper-and-pencil and computerized cognitive tests to measure abilities in motor processing, spatial construction, semantic fluency, immediate memory, short-term memory, delayed memory, spatial working memory, and selective, alternative, and divided attention. Results In multivariate logistic regression analyses adjusted for grade and gender, scores of none of the cognitive tests were correlated with the prevalence of decrease in intrinsic academic motivation in elementary school students. However, low digit span forward test score and score for comprehension of the story in the kana pick-out test were positively correlated with the prevalence of decrease in intrinsic academic motivation in junior high school students. Conclusions The present findings suggest that decrease in capacity for verbal memory is associated with the prevalence of decrease in intrinsic academic motivation among junior high school students. PMID:21235802

Relationship between cognitive function and prevalence of decrease in intrinsic academic motivation in adolescents.

PubMed

Mizuno, Kei; Tanaka, Masaaki; Fukuda, Sanae; Imai-Matsumura, Kyoko; Watanabe, Yasuyoshi

2011-01-14

Decrease in intrinsic motivation is a common complaint among elementary and junior high school students, and is related to poor academic performance. Since grade-dependent development of cognitive functions also influences academic performance by these students, we examined whether cognitive functions are related to the prevalence of decrease in intrinsic academic motivation. The study group consisted of 134 elementary school students from 4th to 6th grades and 133 junior high school students from 7th to 9th grades. Participants completed a questionnaire on intrinsic academic motivation. They also performed paper-and-pencil and computerized cognitive tests to measure abilities in motor processing, spatial construction, semantic fluency, immediate memory, short-term memory, delayed memory, spatial working memory, and selective, alternative, and divided attention. In multivariate logistic regression analyses adjusted for grade and gender, scores of none of the cognitive tests were correlated with the prevalence of decrease in intrinsic academic motivation in elementary school students. However, low digit span forward test score and score for comprehension of the story in the kana pick-out test were positively correlated with the prevalence of decrease in intrinsic academic motivation in junior high school students. The present findings suggest that decrease in capacity for verbal memory is associated with the prevalence of decrease in intrinsic academic motivation among junior high school students.

Instantaneous Frequency Analysis on Nonlinear EMIC Emissions: Arase Observation

NASA Astrophysics Data System (ADS)

Shoji, M.; Yoshizumi, M.; Omura, Y.; Kasaba, Y.; Ishisaka, K.; Matsuda, S.; Kasahara, Y.; Yagitani, S.; Matsuoka, A.; Teramoto, M.; Takashima, T.; Shinohara, I.

2017-12-01

In the inner magnetosphere, electromagnetic ion cyclotron (EMIC) waves cause nonlinear interactions with energetic protons. The waves drastically modify the proton distribution function, resulting in the particle loss in the radiation belt. Arase spacecraft, launched in late 2016, observed a nonlinear EMIC falling tone emission in the high magnetic latitude (MLAT) region of the inner magnetosphere. The wave growth with sub-packet structures of the falling tone emission is found by waveform data from PWE/EFD instrument. The evolution of the instantaneous frequency of the electric field of the EMIC falling tone emission is analyzed by Hilbert-Huang transform (HHT). We find several sub-packets with rising frequency in the falling tone wave. A self-consistent hybrid simulation suggested the complicate frequency evolution of the EMIC sub-packet emissions in the generation region. The intrinsic mode functions of Arase data derived from HHT are compared with the simulation data. The origin of the falling tone emission in the high MLAT region is also discussed.

The system N transporter SN2 doubles as a transmitter precursor furnisher and a potential regulator of NMDA receptors.

PubMed

Hamdani, El Hassan; Gudbrandsen, Marius; Bjørkmo, Mona; Chaudhry, Farrukh Abbas

2012-11-01

Activation of NMDA receptor requires two co-agonists, glutamate and glycine. Despite its intrinsic role in brain functions molecular mechanisms involved in glutamate replenishment and identification of the origin of glycine have eluded characterization. We have performed direct measurements of glycine flux by SN2 (Slc38a5; also known as SNAT5), executed extensive electrophysiological characterization as well as implemented ratiometric analyses to show that SN2 transport resembles SN1 in mechanism but differ in functional implications. We report that rat SN2 mediates electroneutral and bidirectional transport of glutamine and glycine at perisynaptic astroglial membranes. Sophisticated coupled and uncoupled movements of H(+) differentially associate with glutamine and glycine transport by SN2 and regulate pH(i) and the release mode of the transporter. Consequently, SN2 doubles as a transmitter precursor furnisher and a potential regulator of NMDA receptors. Copyright © 2012 Wiley Periodicals, Inc.

Error field detection in DIII-D by magnetic steering of locked modes

DOE PAGES

Shiraki, Daisuke; La Haye, Robert J.; Logan, Nikolas C.; ...

2014-02-20

Optimal correction coil currents for the n = 1 intrinsic error field of the DIII-D tokamak are inferred by applying a rotating external magnetic perturbation to steer the phase of a saturated locked mode with poloidal/toroidal mode number m/n = 2/1. The error field is detected non-disruptively in a single discharge, based on the toroidal torque balance of the resonant surface, which is assumed to be dominated by the balance of resonant electromagnetic torques. This is equivalent to the island being locked at all times to the resonant 2/1 component of the total of the applied and intrinsic error fields,more » such that the deviation of the locked mode phase from the applied field phase depends on the existing error field. The optimal set of correction coil currents is determined to be those currents which best cancels the torque from the error field, based on fitting of the torque balance model. The toroidal electromagnetic torques are calculated from experimental data using a simplified approach incorporating realistic DIII-D geometry, and including the effect of the plasma response on island torque balance based on the ideal plasma response to external fields. This method of error field detection is demonstrated in DIII-D discharges, and the results are compared with those based on the onset of low-density locked modes in ohmic plasmas. Furthermore, this magnetic steering technique presents an efficient approach to error field detection and is a promising method for ITER, particularly during initial operation when the lack of auxiliary heating systems makes established techniques based on rotation or plasma amplification unsuitable.« less

Terahertz electron cyclotron maser interactions with an axis-encircling electron beam

NASA Astrophysics Data System (ADS)

Li, G. D.; Kao, S. H.; Chang, P. C.; Chu, K. R.

2015-04-01

To generate terahertz radiation via the electron cyclotron maser instability, harmonic interactions are essential in order to reduce the required magnetic field to a practical value. Also, high-order mode operation is required to avoid excessive Ohmic losses. The weaker harmonic interaction and mode competition associated with an over-moded structure present challenging problems to overcome. The axis-encircling electron beam is a well-known recipe for both problems. It strengthens the harmonic interaction, as well as minimizing the competing modes. Here, we examine these advantages through a broad data base obtained for a low-power, step-tunable, gyrotron oscillator. Linear results indicate far more higher-harmonic modes can be excited with an axis-encircling electron beam than with an off-axis electron beam. However, multi-mode, time-dependent simulations reveal an intrinsic tendency for a higher-harmonic mode to switch over to a lower-harmonic mode at a high beam current or upon a rapid current rise. Methods are presented to identify the narrow windows in the parameter space for stable harmonic interactions.

Electro-optical resonance modulation of vertical-cavity surface-emitting lasers.

PubMed

Germann, Tim David; Hofmann, Werner; Nadtochiy, Alexey M; Schulze, Jan-Hindrik; Mutig, Alex; Strittmatter, André; Bimberg, Dieter

2012-02-27

Optical and electrical investigations of vertical-cavity surface-emitting lasers (VCSEL) with a monolithically integrated electro-optical modulator (EOM) allow for a detailed physical understanding of this complex compound cavity laser system. The EOM VCSEL light output is investigated to identify optimal working points. An electro-optic resonance feature triggered by the quantum confined Stark effect is used to modulate individual VCSEL modes by more than 20 dB with an extremely small EOM voltage change of less than 100 mV. Spectral mode analysis reveals modulation of higher order modes and very low wavelength chirp of < 0.5 nm. Dynamic experiments and simulation predict an intrinsic bandwidth of the EOM VCSEL exceeding 50 GHz.

[Lung protective ventilation. Ventilatory modes and ventilator parameters].

PubMed

Schädler, Dirk; Weiler, Norbert

2008-06-01

Mechanical ventilation has a considerable potential for injuring the lung tissue. Therefore, attention has to be paid to the proper choice of ventilatory mode and settings to secure lung-protective ventilation whenever possible. Such ventilator strategy should account for low tidal volume ventilation (6 ml/kg PBW), limited plateau pressure (30 to 35 cm H2O) and positive end-expiratory pressure (PEEP). It is unclear whether pressure controlled or volume controlled ventilation with square flow profile is beneficial. The adjustment of inspiration and expiration time should consider the actual breathing mechanics and anticipate the generation of intrinsic PEEP. Ventilatory modes with the possibility of supporting spontaneous breathing should be used as soon as possible.

Self-assisted complete hyperentangled Bell state analysis using quantum-dot spins in optical microcavities

NASA Astrophysics Data System (ADS)

Zeng, Zhi

2018-05-01

An efficient scheme for the discrimination of 16 hyperentangled Bell states of a two-photon system that is entangled in both polarization and spatial-mode degrees of freedom is presented in this paper. Using the interaction between the photons and quantum-dot spins in cavities, the spatial-mode Bell states can be distinguished completely and nondestructively in the first step. Subsequently, the preserved spatial-mode entanglement is utilized as an auxiliary to analyze the polarization Bell states. Compared with a previous scheme (Ren et al 2012 Opt. Express 20 24664-77), our scheme reduces the requirement for nonlinear interaction substantially by utilizing the intrinsic degrees of freedom in hyperentanglement.

G-mode magnetic force microscopy: Separating magnetic and electrostatic interactions using big data analytics

DOE PAGES

Collins, Liam; Belianinov, Alex; Proksch, Roger; ...

2016-05-09

We develop a full information capture approach for Magnetic Force Microscopy (MFM), referred to as generalized mode (G-Mode) MFM. G-Mode MFM acquires and stores the full data stream from the photodetector at sampling rates approaching the intrinsic photodiode limit. The data can be subsequently compressed, denoised, and analyzed, without information loss. Also, 3 G-Mode MFM is implemented and compared to traditional heterodyne based MFM on model systems including domain structures in ferromagnetic Yttrium Iron Garnet (YIG) and electronically and magnetically inhomogeneous high entropy alloy, CoFeMnNiSn. We investigate the use of information theory to mine the G-Mode MFM data and demonstratemore » its usefulness for extracting information which may be hidden in traditional MFM modes, including signatures of nonlinearities and mode coupling phenomena. Finally we demonstrate detection and separation of magnetic and electrostatic tip-sample interactions from a single G-Mode image, by analyzing the entire frequency response of the cantilever. G-Mode MFM is immediately implementable on any AFM platform and as such is expected to be a useful technique for probing spatiotemporal cantilever dynamics and mapping material properties as well as their mutual interactions.« less

Decoding Mode-mixing in Black-hole Merger Ringdown

NASA Technical Reports Server (NTRS)

Kelly, Bernard J.; Baker, John G.

2013-01-01

Optimal extraction of information from gravitational-wave observations of binary black-hole coalescences requires detailed knowledge of the waveforms. Current approaches for representing waveform information are based on spin-weighted spherical harmonic decomposition. Higher-order harmonic modes carrying a few percent of the total power output near merger can supply information critical to determining intrinsic and extrinsic parameters of the binary. One obstacle to constructing a full multi-mode template of merger waveforms is the apparently complicated behavior of some of these modes; instead of settling down to a simple quasinormal frequency with decaying amplitude, some |m| = modes show periodic bumps characteristic of mode-mixing. We analyze the strongest of these modes the anomalous (3, 2) harmonic mode measured in a set of binary black-hole merger waveform simulations, and show that to leading order, they are due to a mismatch between the spherical harmonic basis used for extraction in 3D numerical relativity simulations, and the spheroidal harmonics adapted to the perturbation theory of Kerr black holes. Other causes of mode-mixing arising from gauge ambiguities and physical properties of the quasinormal ringdown modes are also considered and found to be small for the waveforms studied here.

A Correspondence between Individual Differences in the Brain's Intrinsic Functional Architecture and the Content and Form of Self-Generated Thoughts

PubMed Central

Gorgolewski, Krzysztof J.; Lurie, Dan; Urchs, Sebastian; Kipping, Judy A.; Craddock, R. Cameron; Milham, Michael P.; Margulies, Daniel S.; Smallwood, Jonathan

2014-01-01

Although neural activity often reflects the processing of external inputs, intrinsic fluctuations in activity have been observed throughout the brain. These may relate to patterns of self-generated thought that can occur while not performing goal-driven tasks. To understand the relationship between self-generated mental activity and intrinsic neural fluctuations, we developed the New York Cognition Questionnaire (NYC-Q) to assess the content and form of an individual's experiences during the acquisition of resting-state fMRI data. The data were collected as a part of the Nathan Kline Rockland Enhanced sample. We decomposed NYC-Q scores using exploratory factor analysis and found that self-reported thoughts clustered into distinct dimensions of content (future related, past related, positive, negative, and social) and form (words, images, and specificity). We used these components to perform an individual difference analysis exploring how differences in the types of self-generated thoughts relate to whole brain measures of intrinsic brain activity (fractional amplitude of low frequency fluctuations, regional homogeneity, and degree centrality). We found patterns of self-generated thoughts related to changes that were distributed across a wide range of cortical areas. For example, individuals who reported greater imagery exhibited greater low frequency fluctuations in a region of perigenual cingulate cortex, a region that is known to participate in the so-called default-mode network. We also found certain forms of thought were associated with other areas, such as primary visual cortex, the insula, and the cerebellum. For example, individuals who reported greater future thought exhibited less homogeneous neural fluctuations in a region of lateral occipital cortex, a result that is consistent with the claim that particular types of self-generated thought depend on processes that are decoupled from sensory processes. These data provide evidence that self-generated thought is a heterogeneous category of experience and that studying its content can be helpful in understanding brain dynamics. PMID:24824880

Short-Circuit Fault Detection and Classification Using Empirical Wavelet Transform and Local Energy for Electric Transmission Line.

PubMed

Huang, Nantian; Qi, Jiajin; Li, Fuqing; Yang, Dongfeng; Cai, Guowei; Huang, Guilin; Zheng, Jian; Li, Zhenxin

2017-09-16

In order to improve the classification accuracy of recognizing short-circuit faults in electric transmission lines, a novel detection and diagnosis method based on empirical wavelet transform (EWT) and local energy (LE) is proposed. First, EWT is used to deal with the original short-circuit fault signals from photoelectric voltage transformers, before the amplitude modulated-frequency modulated (AM-FM) mode with a compactly supported Fourier spectrum is extracted. Subsequently, the fault occurrence time is detected according to the modulus maxima of intrinsic mode function (IMF₂) from three-phase voltage signals processed by EWT. After this process, the feature vectors are constructed by calculating the LE of the fundamental frequency based on the three-phase voltage signals of one period after the fault occurred. Finally, the classifier based on support vector machine (SVM) which was constructed with the LE feature vectors is used to classify 10 types of short-circuit fault signals. Compared with complementary ensemble empirical mode decomposition with adaptive noise (CEEMDAN) and improved CEEMDAN methods, the new method using EWT has a better ability to present the frequency in time. The difference in the characteristics of the energy distribution in the time domain between different types of short-circuit faults can be presented by the feature vectors of LE. Together, simulation and real signals experiment demonstrate the validity and effectiveness of the new approach.

Short-Circuit Fault Detection and Classification Using Empirical Wavelet Transform and Local Energy for Electric Transmission Line

PubMed Central

Huang, Nantian; Qi, Jiajin; Li, Fuqing; Yang, Dongfeng; Cai, Guowei; Huang, Guilin; Zheng, Jian; Li, Zhenxin

2017-01-01

In order to improve the classification accuracy of recognizing short-circuit faults in electric transmission lines, a novel detection and diagnosis method based on empirical wavelet transform (EWT) and local energy (LE) is proposed. First, EWT is used to deal with the original short-circuit fault signals from photoelectric voltage transformers, before the amplitude modulated-frequency modulated (AM-FM) mode with a compactly supported Fourier spectrum is extracted. Subsequently, the fault occurrence time is detected according to the modulus maxima of intrinsic mode function (IMF2) from three-phase voltage signals processed by EWT. After this process, the feature vectors are constructed by calculating the LE of the fundamental frequency based on the three-phase voltage signals of one period after the fault occurred. Finally, the classifier based on support vector machine (SVM) which was constructed with the LE feature vectors is used to classify 10 types of short-circuit fault signals. Compared with complementary ensemble empirical mode decomposition with adaptive noise (CEEMDAN) and improved CEEMDAN methods, the new method using EWT has a better ability to present the frequency in time. The difference in the characteristics of the energy distribution in the time domain between different types of short-circuit faults can be presented by the feature vectors of LE. Together, simulation and real signals experiment demonstrate the validity and effectiveness of the new approach. PMID:28926953

True randomness from an incoherent source

NASA Astrophysics Data System (ADS)

Qi, Bing

2017-11-01

Quantum random number generators (QRNGs) harness the intrinsic randomness in measurement processes: the measurement outputs are truly random, given the input state is a superposition of the eigenstates of the measurement operators. In the case of trusted devices, true randomness could be generated from a mixed state ρ so long as the system entangled with ρ is well protected. We propose a random number generation scheme based on measuring the quadrature fluctuations of a single mode thermal state using an optical homodyne detector. By mixing the output of a broadband amplified spontaneous emission (ASE) source with a single mode local oscillator (LO) at a beam splitter and performing differential photo-detection, we can selectively detect the quadrature fluctuation of a single mode output of the ASE source, thanks to the filtering function of the LO. Experimentally, a quadrature variance about three orders of magnitude larger than the vacuum noise has been observed, suggesting this scheme can tolerate much higher detector noise in comparison with QRNGs based on measuring the vacuum noise. The high quality of this entropy source is evidenced by the small correlation coefficients of the acquired data. A Toeplitz-hashing extractor is applied to generate unbiased random bits from the Gaussian distributed raw data, achieving an efficiency of 5.12 bits per sample. The output of the Toeplitz extractor successfully passes all the NIST statistical tests for random numbers.

New Growth Mode through Decorated Twin Boundaries

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

Bleikamp, Sebastian; Thoma, Arne; Polop, Celia

2006-03-24

Scanning tunneling microscopy and low energy electron diffraction were used to investigate the growth of partly twinned Ir thin films on Ir(111). A transition from the expected layer-by-layer to a defect dominated growth mode with a fixed lateral length scale and increasing roughness is observed. During growth, the majority of the film is stably transformed to twinned stacking. This transition is initiated by the energetic avoidance of the formation of intrinsic stacking faults compared to two independent twin faults. The atomistic details of the defect kinetics are outlined.

New growth mode through decorated twin boundaries.

PubMed

Bleikamp, Sebastian; Thoma, Arne; Polop, Celia; Pirug, Gerhard; Linke, Udo; Michely, Thomas

2006-03-24

Scanning tunneling microscopy and low energy electron diffraction were used to investigate the growth of partly twinned Ir thin films on Ir(111). A transition from the expected layer-by-layer to a defect dominated growth mode with a fixed lateral length scale and increasing roughness is observed. During growth, the majority of the film is stably transformed to twinned stacking. This transition is initiated by the energetic avoidance of the formation of intrinsic stacking faults compared to two independent twin faults. The atomistic details of the defect kinetics are outlined.

Visual imagery and functional connectivity in blindness: a single-case study

PubMed Central

Boucard, Christine C.; Rauschecker, Josef P.; Neufang, Susanne; Berthele, Achim; Doll, Anselm; Manoliu, Andrej; Riedl, Valentin; Sorg, Christian; Wohlschläger, Afra; Mühlau, Mark

2016-01-01

We present a case report on visual brain plasticity after total blindness acquired in adulthood. SH lost her sight when she was 27. Despite having been totally blind for 43 years, she reported to strongly rely on her vivid visual imagery. Three-Tesla magnetic resonance imaging (MRI) of SH and age-matched controls was performed. The MRI sequence included anatomical MRI, resting-state functional MRI, and task-related functional MRI where SH was instructed to imagine colours, faces, and motion. Compared to controls, voxel-based analysis revealed white matter loss along SH's visual pathway as well as grey matter atrophy in the calcarine sulci. Yet we demonstrated activation in visual areas, including V1, using functional MRI. Of the four identified visual resting-state networks, none showed alterations in spatial extent; hence, SH's preserved visual imagery seems to be mediated by intrinsic brain networks of normal extent. Time courses of two of these networks showed increased correlation with that of the inferior posterior default mode network, which may reflect adaptive changes supporting SH's strong internal visual representations. Overall, our findings demonstrate that conscious visual experience is possible even after years of absence of extrinsic input. PMID:25690326

Visual imagery and functional connectivity in blindness: a single-case study.

PubMed

Boucard, Christine C; Rauschecker, Josef P; Neufang, Susanne; Berthele, Achim; Doll, Anselm; Manoliu, Andrej; Riedl, Valentin; Sorg, Christian; Wohlschläger, Afra; Mühlau, Mark

2016-05-01

We present a case report on visual brain plasticity after total blindness acquired in adulthood. SH lost her sight when she was 27. Despite having been totally blind for 43 years, she reported to strongly rely on her vivid visual imagery. Three-Tesla magnetic resonance imaging (MRI) of SH and age-matched controls was performed. The MRI sequence included anatomical MRI, resting-state functional MRI, and task-related functional MRI where SH was instructed to imagine colours, faces, and motion. Compared to controls, voxel-based analysis revealed white matter loss along SH's visual pathway as well as grey matter atrophy in the calcarine sulci. Yet we demonstrated activation in visual areas, including V1, using functional MRI. Of the four identified visual resting-state networks, none showed alterations in spatial extent; hence, SH's preserved visual imagery seems to be mediated by intrinsic brain networks of normal extent. Time courses of two of these networks showed increased correlation with that of the inferior posterior default mode network, which may reflect adaptive changes supporting SH's strong internal visual representations. Overall, our findings demonstrate that conscious visual experience is possible even after years of absence of extrinsic input.

Anxiety Modulates Insula Recruitment in Resting-State Functional Magnetic Resonance Imaging in Youth and Adults

PubMed Central

Gotlib, Ian H.; Thompson, Paul M.; Thomason, Moriah E.

2011-01-01

Abstract Research on resting-state functional connectivity reveals intrinsically connected networks in the brain that are largely consistent across the general population. However, there are individual differences in these networks that have not been elucidated. Here, we measured the influence of naturally occurring mood on functional connectivity. In particular, we examined the association between self-reported levels of anxiety and connectivity in the default mode network (DMN). Healthy youth (n=43; ages 10–18) and adult participants (n=24, ages 19–59) completed a 6-min resting-state functional magnetic resonance imaging scan, then immediately completed questionnaires assessing their mood and thoughts during the scan. Regression analyses conducted separately for the youth and adult samples revealed brain regions in which increases in connectivity differentially corresponded to higher anxiety in each group. In one area, the left insular cortex, both groups showed similar increased connectivity to the DMN (youth: -30, 26, 14; adults: -33, 12, 14) with increased anxiety. State anxiety assessed during scanning was not correlated with trait anxiety, so our results likely reflect state levels of anxiety. To our knowledge, this is the first study to relate naturally occurring mood to resting state connectivity. PMID:22433052

A Four-Stage Hybrid Model for Hydrological Time Series Forecasting

PubMed Central

Di, Chongli; Yang, Xiaohua; Wang, Xiaochao

2014-01-01

Hydrological time series forecasting remains a difficult task due to its complicated nonlinear, non-stationary and multi-scale characteristics. To solve this difficulty and improve the prediction accuracy, a novel four-stage hybrid model is proposed for hydrological time series forecasting based on the principle of ‘denoising, decomposition and ensemble’. The proposed model has four stages, i.e., denoising, decomposition, components prediction and ensemble. In the denoising stage, the empirical mode decomposition (EMD) method is utilized to reduce the noises in the hydrological time series. Then, an improved method of EMD, the ensemble empirical mode decomposition (EEMD), is applied to decompose the denoised series into a number of intrinsic mode function (IMF) components and one residual component. Next, the radial basis function neural network (RBFNN) is adopted to predict the trend of all of the components obtained in the decomposition stage. In the final ensemble prediction stage, the forecasting results of all of the IMF and residual components obtained in the third stage are combined to generate the final prediction results, using a linear neural network (LNN) model. For illustration and verification, six hydrological cases with different characteristics are used to test the effectiveness of the proposed model. The proposed hybrid model performs better than conventional single models, the hybrid models without denoising or decomposition and the hybrid models based on other methods, such as the wavelet analysis (WA)-based hybrid models. In addition, the denoising and decomposition strategies decrease the complexity of the series and reduce the difficulties of the forecasting. With its effective denoising and accurate decomposition ability, high prediction precision and wide applicability, the new model is very promising for complex time series forecasting. This new forecast model is an extension of nonlinear prediction models. PMID:25111782

Empirical Mode Decomposition of Geophysical Well-log Data of Bombay Offshore Basin, Mumbai, India

NASA Astrophysics Data System (ADS)

Siddharth Gairola, Gaurav; Chandrasekhar, Enamundram

2016-04-01

Geophysical well-log data manifest the nonlinear behaviour of their respective physical properties of the heterogeneous subsurface layers as a function of depth. Therefore, nonlinear data analysis techniques must be implemented, to quantify the degree of heterogeneity in the subsurface lithologies. One such nonlinear data adaptive technique is empirical mode decomposition (EMD) technique, which facilitates to decompose the data into oscillatory signals of different wavelengths called intrinsic mode functions (IMF). In the present study EMD has been applied to gamma-ray log and neutron porosity log of two different wells: Well B and Well C located in the western offshore basin of India to perform heterogeneity analysis and compare the results with those obtained by multifractal studies of the same data sets. By establishing a relationship between the IMF number (m) and the mean wavelength associated with each IMF (Im), a heterogeneity index (ρ) associated with subsurface layers can be determined using the relation, Im=kρm, where 'k' is a constant. The ρ values bear an inverse relation with the heterogeneity of the subsurface: smaller ρ values designate higher heterogeneity and vice-versa. The ρ values estimated for different limestone payzones identified in the wells clearly show that Well C has higher degree of heterogeneity than Well B. This correlates well with the estimated Vshale values for the limestone reservoir zone showing higher shale content in Well C than Well B. The ρ values determined for different payzones of both wells will be used to quantify the degree of heterogeneity in different wells. The multifractal behaviour of each IMF of both the logs of both the wells will be compared with one another and discussed on the lines of their heterogeneity indices.

A four-stage hybrid model for hydrological time series forecasting.

PubMed

Di, Chongli; Yang, Xiaohua; Wang, Xiaochao

2014-01-01

Hydrological time series forecasting remains a difficult task due to its complicated nonlinear, non-stationary and multi-scale characteristics. To solve this difficulty and improve the prediction accuracy, a novel four-stage hybrid model is proposed for hydrological time series forecasting based on the principle of 'denoising, decomposition and ensemble'. The proposed model has four stages, i.e., denoising, decomposition, components prediction and ensemble. In the denoising stage, the empirical mode decomposition (EMD) method is utilized to reduce the noises in the hydrological time series. Then, an improved method of EMD, the ensemble empirical mode decomposition (EEMD), is applied to decompose the denoised series into a number of intrinsic mode function (IMF) components and one residual component. Next, the radial basis function neural network (RBFNN) is adopted to predict the trend of all of the components obtained in the decomposition stage. In the final ensemble prediction stage, the forecasting results of all of the IMF and residual components obtained in the third stage are combined to generate the final prediction results, using a linear neural network (LNN) model. For illustration and verification, six hydrological cases with different characteristics are used to test the effectiveness of the proposed model. The proposed hybrid model performs better than conventional single models, the hybrid models without denoising or decomposition and the hybrid models based on other methods, such as the wavelet analysis (WA)-based hybrid models. In addition, the denoising and decomposition strategies decrease the complexity of the series and reduce the difficulties of the forecasting. With its effective denoising and accurate decomposition ability, high prediction precision and wide applicability, the new model is very promising for complex time series forecasting. This new forecast model is an extension of nonlinear prediction models.

Attention reorganizes connectivity across networks in a frequency specific manner.

PubMed

Kwon, Soyoung; Watanabe, Masataka; Fischer, Elvira; Bartels, Andreas

2017-01-01

Attention allows our brain to focus its limited resources on a given task. It does so by selective modulation of neural activity and of functional connectivity (FC) across brain-wide networks. While there is extensive literature on activity changes, surprisingly few studies examined brain-wide FC modulations that can be cleanly attributed to attention compared to matched visual processing. In contrast to prior approaches, we used an ultra-long trial design that avoided transients from trial onsets, included slow fluctuations (<0.1Hz) that carry important information on FC, and allowed for frequency-segregated analyses. We found that FC derived from long blocks had a nearly two-fold higher gain compared to FC derived from traditional (short) block designs. Second, attention enhanced intrinsic (negative or positive) correlations across networks, such as between the default-mode network (DMN), the dorsal attention network (DAN), and the visual system (VIS). In contrast attention de-correlated the intrinsically correlated visual regions. Third, the de-correlation within VIS was driven primarily by high frequencies, whereas the increase in DAN-VIS predominantly by low frequencies. These results pinpoint two fundamentally distinct effects of attention on connectivity. Information flow increases between distinct large-scale networks, and de-correlation within sensory cortex indicates decreased redundancy. Copyright © 2016 Elsevier Inc. All rights reserved.

Intrinsic connectivity in the human brain does not reveal networks for ‘basic’ emotions

PubMed Central

Lindquist, Kristen A.; Dickerson, Bradford C.; Barrett, Lisa Feldman

2015-01-01

We tested two competing models for the brain basis of emotion, the basic emotion theory and the conceptual act theory of emotion, using resting-state functional connectivity magnetic resonance imaging (rs-fcMRI). The basic emotion view hypothesizes that anger, sadness, fear, disgust and happiness each arise from a brain network that is innate, anatomically constrained and homologous in other animals. The conceptual act theory of emotion hypothesizes that an instance of emotion is a brain state constructed from the interaction of domain-general, core systems within the brain such as the salience, default mode and frontoparietal control networks. Using peak coordinates derived from a meta-analysis of task-evoked emotion fMRI studies, we generated a set of whole-brain rs-fcMRI ‘discovery’ maps for each emotion category and examined the spatial overlap in their conjunctions. Instead of discovering a specific network for each emotion category, variance in the discovery maps was accounted for by the known domain-general network. Furthermore, the salience network is observed as part of every emotion category. These results indicate that specific networks for each emotion do not exist within the intrinsic architecture of the human brain and instead support the conceptual act theory of emotion. PMID:25680990

AICHA: An atlas of intrinsic connectivity of homotopic areas.

PubMed

Joliot, Marc; Jobard, Gaël; Naveau, Mikaël; Delcroix, Nicolas; Petit, Laurent; Zago, Laure; Crivello, Fabrice; Mellet, Emmanuel; Mazoyer, Bernard; Tzourio-Mazoyer, Nathalie

2015-10-30

Atlases of brain anatomical ROIs are widely used for functional MRI data analysis. Recently, it was proposed that an atlas of ROIs derived from a functional brain parcellation could be advantageous, in particular for understanding how different regions share information. However, functional atlases so far proposed do not account for a crucial aspect of cerebral organization, namely homotopy, i.e. that each region in one hemisphere has a homologue in the other hemisphere. We present AICHA (for Atlas of Intrinsic Connectivity of Homotopic Areas), a functional brain ROIs atlas based on resting-state fMRI data acquired in 281 individuals. AICHA ROIs cover the whole cerebrum, each having 1-homogeneity of its constituting voxels intrinsic activity, and 2-a unique homotopic contralateral counterpart with which it has maximal intrinsic connectivity. AICHA was built in 4 steps: (1) estimation of resting-state networks (RSNs) using individual resting-state fMRI independent components, (2) k-means clustering of voxel-wise group level profiles of connectivity, (3) homotopic regional grouping based on maximal inter-hemispheric functional correlation, and (4) ROI labeling. AICHA includes 192 homotopic region pairs (122 gyral, 50 sulcal, and 20 gray nuclei). As an application, we report inter-hemispheric (homotopic and heterotopic) and intra-hemispheric connectivity patterns at different sparsities. ROI functional homogeneity was higher for AICHA than for anatomical ROI atlases, but slightly lower than for another functional ROI atlas not accounting for homotopy. AICHA is ideally suited for intrinsic/effective connectivity analyses, as well as for investigating brain hemispheric specialization. Copyright © 2015 Elsevier B.V. All rights reserved.

Magnetic resonance-compatible model of isolated working heart from large animal for multimodal assessment of cardiac function, electrophysiology, and metabolism.

PubMed

Vaillant, Fanny; Magat, Julie; Bour, Pierre; Naulin, Jérôme; Benoist, David; Loyer, Virginie; Vieillot, Delphine; Labrousse, Louis; Ritter, Philippe; Bernus, Olivier; Dos Santos, Pierre; Quesson, Bruno

2016-05-15

To provide a model close to the human heart, and to study intrinsic cardiac function at the same time as electromechanical coupling, we developed a magnetic resonance (MR)-compatible setup of isolated working perfused pig hearts. Hearts from pigs (40 kg, n = 20) and sheep (n = 1) were blood perfused ex vivo in the working mode with and without loaded right ventricle (RV), for 80 min. Cardiac function was assessed by measuring left intraventricular pressure and left ventricular (LV) ejection fraction (LVEF), aortic and mitral valve dynamics, and native T1 mapping with MR imaging (1.5 Tesla). Potential myocardial alterations were assessed at the end of ex vivo perfusion from late-Gadolinium enhancement T1 mapping. The ex vivo cardiac function was stable across the 80 min of perfusion. Aortic flow and LV-dP/dtmin were significantly higher (P < 0.05) in hearts perfused with loaded RV, without differences for heart rate, maximal and minimal LV pressure, LV-dP/dtmax, LVEF, and kinetics of aortic and mitral valves. T1 mapping analysis showed a spatially homogeneous distribution over the LV. Simultaneous recording of hemodynamics, LVEF, and local cardiac electrophysiological signals were then successfully performed at baseline and during electrical pacing protocols without inducing alteration of MR images. Finally, (31)P nuclear MR spectroscopy (9.4 T) was also performed in two pig hearts, showing phosphocreatine-to-ATP ratio in accordance with data previously reported in vivo. We demonstrate the feasibility to perfuse isolated pig hearts in the working mode, inside an MR environment, allowing simultaneous assessment of cardiac structure, mechanics, and electrophysiology, illustrating examples of potential applications. Copyright © 2016 the American Physiological Society.

A novel hybrid model for air quality index forecasting based on two-phase decomposition technique and modified extreme learning machine.

PubMed

Wang, Deyun; Wei, Shuai; Luo, Hongyuan; Yue, Chenqiang; Grunder, Olivier

2017-02-15

The randomness, non-stationarity and irregularity of air quality index (AQI) series bring the difficulty of AQI forecasting. To enhance forecast accuracy, a novel hybrid forecasting model combining two-phase decomposition technique and extreme learning machine (ELM) optimized by differential evolution (DE) algorithm is developed for AQI forecasting in this paper. In phase I, the complementary ensemble empirical mode decomposition (CEEMD) is utilized to decompose the AQI series into a set of intrinsic mode functions (IMFs) with different frequencies; in phase II, in order to further handle the high frequency IMFs which will increase the forecast difficulty, variational mode decomposition (VMD) is employed to decompose the high frequency IMFs into a number of variational modes (VMs). Then, the ELM model optimized by DE algorithm is applied to forecast all the IMFs and VMs. Finally, the forecast value of each high frequency IMF is obtained through adding up the forecast results of all corresponding VMs, and the forecast series of AQI is obtained by aggregating the forecast results of all IMFs. To verify and validate the proposed model, two daily AQI series from July 1, 2014 to June 30, 2016 collected from Beijing and Shanghai located in China are taken as the test cases to conduct the empirical study. The experimental results show that the proposed hybrid model based on two-phase decomposition technique is remarkably superior to all other considered models for its higher forecast accuracy. Copyright © 2016 Elsevier B.V. All rights reserved.

Research on Ship-Radiated Noise Denoising Using Secondary Variational Mode Decomposition and Correlation Coefficient.

PubMed

Li, Yuxing; Li, Yaan; Chen, Xiao; Yu, Jing

2017-12-26

As the sound signal of ships obtained by sensors contains other many significant characteristics of ships and called ship-radiated noise (SN), research into a denoising algorithm and its application has obtained great significance. Using the advantage of variational mode decomposition (VMD) combined with the correlation coefficient for denoising, a hybrid secondary denoising algorithm is proposed using secondary VMD combined with a correlation coefficient (CC). First, different kinds of simulation signals are decomposed into several bandwidth-limited intrinsic mode functions (IMFs) using VMD, where the decomposition number by VMD is equal to the number by empirical mode decomposition (EMD); then, the CCs between the IMFs and the simulation signal are calculated respectively. The noise IMFs are identified by the CC threshold and the rest of the IMFs are reconstructed in order to realize the first denoising process. Finally, secondary denoising of the simulation signal can be accomplished by repeating the above steps of decomposition, screening and reconstruction. The final denoising result is determined according to the CC threshold. The denoising effect is compared under the different signal-to-noise ratio and the time of decomposition by VMD. Experimental results show the validity of the proposed denoising algorithm using secondary VMD (2VMD) combined with CC compared to EMD denoising, ensemble EMD (EEMD) denoising, VMD denoising and cubic VMD (3VMD) denoising, as well as two denoising algorithms presented recently. The proposed denoising algorithm is applied to feature extraction and classification for SN signals, which can effectively improve the recognition rate of different kinds of ships.

Impaired prefrontal activity to regulate the intrinsic motivation-action link in schizophrenia.

PubMed

Takeda, Kazuyoshi; Matsumoto, Madoka; Ogata, Yousuke; Maida, Keiko; Murakami, Hiroki; Murayama, Kou; Shimoji, Keigo; Hanakawa, Takashi; Matsumoto, Kenji; Nakagome, Kazuyuki

2017-01-01

A core feature of schizophrenia (SCZ) is impairment in intrinsic motivation. Although intrinsic motivation plays an important role in enhancing improvement of the social functioning, its neural mechanisms of impairment have yet to be clarified. We hypothesized that abnormal function of the frontostriatal loop consisting of the striatum and lateral prefrontal cortex (LPFC) may be related to impaired intrinsic motivation in SCZ. We tested this by comparing the brain activity measured by functional magnetic resonance imaging and behavioral parameters associated with movement, motivation, and cognitive control between 18 stable SCZ patients and 17 healthy control (HC) participants during a task that elicits intrinsic motivation. We also compared the functional connectivity during resting-state and the fractional anisotropy using diffusion tensor imaging analysis between the two groups. We adopted an enjoyable timing task to stop a stopwatch at an exact time, which in our previous study has demonstrated to elicit intrinsic motivation. Although the performance level in general was not different between groups, the SCZ group performed worse than the HC group in trials following "overshoot" errors (i.e., the response was too late). SCZ participants showed lower intrinsic motivation to the task than the HC group in an inventory report. The striatal activity during the prediction at the task cue period was consistently lower in SCZ participants than in HC. The LPFC activity at the task cue period positively correlated with intrinsic motivation and also with the rate of success following overshoot errors in the HC group, but not in the SCZ group. The LPFC activity at the task cue period was also positively correlated with the striatal activity in both groups. The striatal activity during the feedback period was not significantly different between groups. These results suggest that, unlike HC, the neural activity in the LPFC fails to mediate between prediction of hedonic events and cognitive control of action plans in SCZ, whereas the hedonic response is retained.

Gap discrete breathers in strained boron nitride

NASA Astrophysics Data System (ADS)

Barani, Elham; Korznikova, Elena A.; Chetverikov, Alexander P.; Zhou, Kun; Dmitriev, Sergey V.

2017-11-01

Linear and nonlinear dynamics of hexagonal boron nitride (h-BN) lattice is studied by means of molecular dynamics simulations with the use of the Tersoff interatomic potentials. It is found that sufficiently large homogeneous elastic strain along zigzag direction opens a wide gap in the phonon spectrum. Extended vibrational mode with boron and nitrogen sublattices vibrating in-plane as a whole in strained h-BN has frequency within the phonon gap. This fact suggests that a nonlinear spatially localized vibrational mode with frequencies in the phonon gap, called discrete breather (also often termed as intrinsic localized mode), can be excited. Properties of the gap discrete breathers in strained h-BN are contrasted with that for analogous vibrational mode found earlier in strained graphene. It is found that h-BN modeled with the Tersoff potentials does not support transverse discrete breathers.

Trading strategy based on dynamic mode decomposition: Tested in Chinese stock market

NASA Astrophysics Data System (ADS)

Cui, Ling-xiao; Long, Wen

2016-11-01

Dynamic mode decomposition (DMD) is an effective method to capture the intrinsic dynamical modes of complex system. In this work, we adopt DMD method to discover the evolutionary patterns in stock market and apply it to Chinese A-share stock market. We design two strategies based on DMD algorithm. The strategy which considers only timing problem can make reliable profits in a choppy market with no prominent trend while fails to beat the benchmark moving-average strategy in bull market. After considering the spatial information from spatial-temporal coherent structure of DMD modes, we improved the trading strategy remarkably. Then the DMD strategies profitability is quantitatively evaluated by performing SPA test to correct the data-snooping effect. The results further prove that DMD algorithm can model the market patterns well in sideways market.

Error Field Assessment from Driven Mode Rotation: Results from Extrap-T2R Reversed-Field-Pinch and Perspectives for ITER

NASA Astrophysics Data System (ADS)

Volpe, F. A.; Frassinetti, L.; Brunsell, P. R.; Drake, J. R.; Olofsson, K. E. J.

2012-10-01

A new ITER-relevant non-disruptive error field (EF) assessment technique not restricted to low density and thus low beta was demonstrated at the Extrap-T2R reversed field pinch. Resistive Wall Modes (RWMs) were generated and their rotation sustained by rotating magnetic perturbations. In particular, stable modes of toroidal mode number n=8 and 10 and unstable modes of n=1 were used in this experiment. Due to finite EFs, and in spite of the applied perturbations rotating uniformly and having constant amplitude, the RWMs were observed to rotate non-uniformly and be modulated in amplitude (in the case of unstable modes, the observed oscillation was superimposed to the mode growth). This behavior was used to infer the amplitude and toroidal phase of n=1, 8 and 10 EFs. The method was first tested against known, deliberately applied EFs, and then against actual intrinsic EFs. Applying equal and opposite corrections resulted in longer discharges and more uniform mode rotation, indicating good EF compensation. The results agree with a simple theoretical model. Extensions to tearing modes, to the non-uniform plasma response to rotating perturbations, and to tokamaks, including ITER, will be discussed.

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

Collins, Liam; Belianinov, Alex; Kalinin, Sergei V.

In this work, we develop a full information capture approach for Magnetic Force Microscopy (MFM), referred to as generalized mode (G-Mode) MFM. G-Mode MFM acquires and stores the full data stream from the photodetector, captured at sampling rates approaching the intrinsic photodiode limit. The data can be subsequently compressed, denoised, and analyzed, without information loss. Here, G-Mode MFM is implemented and compared to the traditional heterodyne-based MFM on model systems, including domain structures in ferromagnetic Yttrium Iron Garnet and the electronically and magnetically inhomogeneous high entropy alloy, CoFeMnNiSn. We investigate the use of information theory to mine the G-Mode MFMmore » data and demonstrate its usefulness for extracting information which may be hidden in traditional MFM modes, including signatures of nonlinearities and mode-coupling phenomena. Finally, we demonstrate detection and separation of magnetic and electrostatic tip-sample interactions from a single G-Mode image, by analyzing the entire frequency response of the cantilever. G-Mode MFM is immediately implementable on any atomic force microscopy platform and as such is expected to be a useful technique for probing spatiotemporal cantilever dynamics and mapping material properties, as well as their mutual interactions.« less

Dynamic functional connectivity of the default mode network tracks daydreaming.

PubMed

Kucyi, Aaron; Davis, Karen D

2014-10-15

Humans spend much of their time engaged in stimulus-independent thoughts, colloquially known as "daydreaming" or "mind-wandering." A fundamental question concerns how awake, spontaneous brain activity represents the ongoing cognition of daydreaming versus unconscious processes characterized as "intrinsic." Since daydreaming involves brief cognitive events that spontaneously fluctuate, we tested the hypothesis that the dynamics of brain network functional connectivity (FC) are linked with daydreaming. We determined the general tendency to daydream in healthy adults based on a daydreaming frequency scale (DDF). Subjects then underwent both resting state functional magnetic resonance imaging (rs-fMRI) and fMRI during sensory stimulation with intermittent thought probes to determine the occurrences of mind-wandering events. Brain regions within the default mode network (DMN), purported to be involved in daydreaming, were assessed for 1) static FC across the entire fMRI scans, and 2) dynamic FC based on FC variability (FCV) across 30s progressively sliding windows of 2s increments within each scan. We found that during both resting and sensory stimulation states, individual differences in DDF were negatively correlated with static FC between the posterior cingulate cortex and a ventral DMN subsystem involved in future-oriented thought. Dynamic FC analysis revealed that DDF was positively correlated with FCV within the same DMN subsystem in the resting state but not during stimulation. However, dynamic but not static FC, in this subsystem, was positively correlated with an individual's degree of self-reported mind-wandering during sensory stimulation. These findings identify temporal aspects of spontaneous DMN activity that reflect conscious and unconscious processes. Copyright © 2014 Elsevier Inc. All rights reserved.

Default mode network connectivity indicates episodic memory capacity in mesial temporal lobe epilepsy.

PubMed

McCormick, Cornelia; Quraan, Maher; Cohn, Melanie; Valiante, Taufik A; McAndrews, Mary Pat

2013-05-01

The clinical relevance of resting state functional connectivity in neurologic disorders, including mesial temporal lobe epilepsy (mTLE), remains unclear. This study investigated how connectivity in the default mode network changes with unilateral damage to one of its nodes, the hippocampus (HC), and how such connectivity can be exploited clinically to characterize memory deficits and indicate postsurgical memory change. Functional magnetic resonance imaging (fMRI) resting state scans and neuropsychological memory assessments (Warrington Recognition Tests for Words and Faces) were performed on 19 healthy controls, 20 patients with right mTLE, and 18 patients with left mTLE. In addition, postsurgical fMRI resting state and memory change (postsurgical memory performance-presurgical memory performance) data were available for half of these patients. Patients with mTLE showed reduced connectivity from the posterior cingulate cortex (PCC) to the epileptogenic HC and increased PCC connectivity to the contralateral HC. Stronger PCC connectivity to the epileptogenic HC was associated with better presurgical memory and with greater postsurgical memory decline. Stronger PCC connectivity to the contralateral HC was associated with less postsurgical memory decline. Following surgery, PCC connectivity to the remaining HC increased from presurgical values and showed enhanced correlation with postsurgical memory function. It is notable that this index was superior to others (hippocampal volume, preoperative memory scores) in explaining variance in memory change following surgery. Our results demonstrate the striking clinical significance of the brain's intrinsic connectivity in evaluating cognitive capacity and indicating the potential of postsurgical cognitive morbidity in patients with mTLE. Wiley Periodicals, Inc. © 2013 International League Against Epilepsy.

Edge-localized-modes in tokamaks

DOE PAGES

Leonard, Anthony W.

2014-09-11

Edge-localized-modes (ELMs) are a ubiquitous feature of H-mode in tokamaks. When gradients in the H-mode transport barrier grow to exceed the MHD stability limit the ELM instability grows explosively rapidly transporting energy and particles onto open field lines and material surfaces. Though ELMs provide additional particle and impurity transport through the H-mode transport barrier, enabling steady operation, the resulting heat flux transients to plasma facing surfaces project to large amplitude in future low collisionality burning plasma tokamaks. Measurements of the ELM heat flux deposition onto material surfaces in the divertor and main chamber indicate significant broadening compared to inter-ELM heatmore » flux, with a timescale for energy deposition that is consistent with sonic ion flow and numerical simulation. Comprehensive ELM simulation is highlighting the important physics processes of ELM transport including parallel transport due to magnetic reconnection and turbulence resulting from collapse of the H-mode transport barrier. As a result, encouraging prospects for ELM control and/or suppression in future tokamaks include intrinsic modes of ELM free operation, ELM triggering with frequent small pellet injection and the application of 3D magnetic fields.« less

Edge-localized-modes in tokamaksa)

NASA Astrophysics Data System (ADS)

Leonard, A. W.

2014-09-01

Edge-localized-modes (ELMs) are a ubiquitous feature of H-mode in tokamaks. When gradients in the H-mode transport barrier grow to exceed the MHD stability limit the ELM instability grows explosively, rapidly transporting energy and particles onto open field lines and material surfaces. Though ELMs provide additional particle and impurity transport through the H-mode transport barrier, enabling steady operation, the resulting heat flux transients to plasma facing surfaces project to large amplitude in future low collisionality burning plasma tokamaks. Measurements of the ELM heat flux deposition onto material surfaces in the divertor and main chamber indicate significant broadening compared to inter-ELM heat flux, with a timescale for energy deposition that is consistent with sonic ion flow and numerical simulation. Comprehensive ELM simulation is highlighting the important physics processes of ELM transport including parallel transport due to magnetic reconnection and turbulence resulting from collapse of the H-mode transport barrier. Encouraging prospects for ELM control and/or suppression in future tokamaks include intrinsic modes of ELM free operation, ELM triggering with frequent small pellet injection and the application of 3D magnetic fields.

Rayleigh scattering in few-mode optical fibers

PubMed Central

Wang, Zhen; Wu, Hao; Hu, Xiaolong; Zhao, Ningbo; Mo, Qi; Li, Guifang

2016-01-01

The extremely low loss of silica fibers has enabled the telecommunication revolution, but single-mode fiber-optic communication systems have been driven to their capacity limits. As a means to overcome this capacity crunch, space-division multiplexing (SDM) using few-mode fibers (FMF) has been proposed and demonstrated. In single-mode optical fibers, Rayleigh scattering serves as the dominant mechanism for optical loss. However, to date, the role of Rayleigh scattering in FMFs remains elusive. Here we establish and experimentally validate a general model for Rayleigh scattering in FMFs. Rayleigh backscattering not only sets the intrinsic loss limit for FMFs but also provides the theoretical foundation for few-mode optical time-domain reflectometry, which can be used to probe perturbation-induced mode-coupling dynamics in FMFs. We also show that forward inter-modal Rayleigh scattering ultimately sets a fundamental limit on inter-modal-crosstalk for FMFs. Therefore, this work not only has implications specifically for SDM systems but also broadly for few-mode fiber optics and its applications in amplifiers, lasers, and sensors in which inter-modal crosstalk imposes a fundamental performance limitation. PMID:27775003

Rayleigh scattering in few-mode optical fibers.

PubMed

Wang, Zhen; Wu, Hao; Hu, Xiaolong; Zhao, Ningbo; Mo, Qi; Li, Guifang

2016-10-24

The extremely low loss of silica fibers has enabled the telecommunication revolution, but single-mode fiber-optic communication systems have been driven to their capacity limits. As a means to overcome this capacity crunch, space-division multiplexing (SDM) using few-mode fibers (FMF) has been proposed and demonstrated. In single-mode optical fibers, Rayleigh scattering serves as the dominant mechanism for optical loss. However, to date, the role of Rayleigh scattering in FMFs remains elusive. Here we establish and experimentally validate a general model for Rayleigh scattering in FMFs. Rayleigh backscattering not only sets the intrinsic loss limit for FMFs but also provides the theoretical foundation for few-mode optical time-domain reflectometry, which can be used to probe perturbation-induced mode-coupling dynamics in FMFs. We also show that forward inter-modal Rayleigh scattering ultimately sets a fundamental limit on inter-modal-crosstalk for FMFs. Therefore, this work not only has implications specifically for SDM systems but also broadly for few-mode fiber optics and its applications in amplifiers, lasers, and sensors in which inter-modal crosstalk imposes a fundamental performance limitation.

Are intrinsic motivational factors of work associated with functional incapacity similarly regardless of the country?

PubMed

Väänänen, A; Pahkin, K; Huuhtanen, P; Kivimäki, M; Vahtera, J; Theorell, T; Kalimo, R

2005-10-01

Many psychosocial models of wellbeing at work emphasise the role of intrinsic motivational factors such as job autonomy, job complexity, and innovativeness. However, little is known about whether the employees of multinational enterprises differ from country to country with regard to intrinsic motivational factors, and whether these factors are associated with wellbeing similarly in the different countries. The purpose of this study was to examine the level of intrinsic motivational factors and their impact on functional incapacity in different countries in a multinational corporation. In 2000, data were collected from a globally operating corporation with a questionnaire survey. The participants were 13 795 employees (response rate 59%; 56% under age 45; 80% men; 61% blue collar employees), who worked in similar industrial occupations in five countries (Canada, China, Finland, France, and Sweden). The Chinese employees reported higher autonomy and lower complexity at work than the employees from the other countries. After adjustment for age, sex, socioeconomic status, and physical work environment, job autonomy, and job complexity at work were associated with functional incapacity in most countries, whereas in China the impact was significantly stronger. In Finland and in China employees with low innovativeness at work were more prone to functional incapacity than corresponding employees in other countries. The level of intrinsic motivational factors varied between the Chinese employees and those in other countries. In line with theoretical notions, the relation between intrinsic motivational factors of work and functional incapacity followed a similar pattern in the different countries. However, these country specific results show that a culture specific approach to employee wellbeing should also be applied.

A Novel Bearing Multi-Fault Diagnosis Approach Based on Weighted Permutation Entropy and an Improved SVM Ensemble Classifier.

PubMed

Zhou, Shenghan; Qian, Silin; Chang, Wenbing; Xiao, Yiyong; Cheng, Yang

2018-06-14

Timely and accurate state detection and fault diagnosis of rolling element bearings are very critical to ensuring the reliability of rotating machinery. This paper proposes a novel method of rolling bearing fault diagnosis based on a combination of ensemble empirical mode decomposition (EEMD), weighted permutation entropy (WPE) and an improved support vector machine (SVM) ensemble classifier. A hybrid voting (HV) strategy that combines SVM-based classifiers and cloud similarity measurement (CSM) was employed to improve the classification accuracy. First, the WPE value of the bearing vibration signal was calculated to detect the fault. Secondly, if a bearing fault occurred, the vibration signal was decomposed into a set of intrinsic mode functions (IMFs) by EEMD. The WPE values of the first several IMFs were calculated to form the fault feature vectors. Then, the SVM ensemble classifier was composed of binary SVM and the HV strategy to identify the bearing multi-fault types. Finally, the proposed model was fully evaluated by experiments and comparative studies. The results demonstrate that the proposed method can effectively detect bearing faults and maintain a high accuracy rate of fault recognition when a small number of training samples are available.

Information-Theoretical Quantifier of Brain Rhythm Based on Data-Driven Multiscale Representation

PubMed Central

2015-01-01

This paper presents a data-driven multiscale entropy measure to reveal the scale dependent information quantity of electroencephalogram (EEG) recordings. This work is motivated by the previous observations on the nonlinear and nonstationary nature of EEG over multiple time scales. Here, a new framework of entropy measures considering changing dynamics over multiple oscillatory scales is presented. First, to deal with nonstationarity over multiple scales, EEG recording is decomposed by applying the empirical mode decomposition (EMD) which is known to be effective for extracting the constituent narrowband components without a predetermined basis. Following calculation of Renyi entropy of the probability distributions of the intrinsic mode functions extracted by EMD leads to a data-driven multiscale Renyi entropy. To validate the performance of the proposed entropy measure, actual EEG recordings from rats (n = 9) experiencing 7 min cardiac arrest followed by resuscitation were analyzed. Simulation and experimental results demonstrate that the use of the multiscale Renyi entropy leads to better discriminative capability of the injury levels and improved correlations with the neurological deficit evaluation after 72 hours after cardiac arrest, thus suggesting an effective diagnostic and prognostic tool. PMID:26380297

Multispectral image fusion for illumination-invariant palmprint recognition

PubMed Central

Zhang, Xinman; Xu, Xuebin; Shang, Dongpeng

2017-01-01

Multispectral palmprint recognition has shown broad prospects for personal identification due to its high accuracy and great stability. In this paper, we develop a novel illumination-invariant multispectral palmprint recognition method. To combine the information from multiple spectral bands, an image-level fusion framework is completed based on a fast and adaptive bidimensional empirical mode decomposition (FABEMD) and a weighted Fisher criterion. The FABEMD technique decomposes the multispectral images into their bidimensional intrinsic mode functions (BIMFs), on which an illumination compensation operation is performed. The weighted Fisher criterion is to construct the fusion coefficients at the decomposition level, making the images be separated correctly in the fusion space. The image fusion framework has shown strong robustness against illumination variation. In addition, a tensor-based extreme learning machine (TELM) mechanism is presented for feature extraction and classification of two-dimensional (2D) images. In general, this method has fast learning speed and satisfying recognition accuracy. Comprehensive experiments conducted on the PolyU multispectral palmprint database illustrate that the proposed method can achieve favorable results. For the testing under ideal illumination, the recognition accuracy is as high as 99.93%, and the result is 99.50% when the lighting condition is unsatisfied. PMID:28558064

Multispectral image fusion for illumination-invariant palmprint recognition.

PubMed

Lu, Longbin; Zhang, Xinman; Xu, Xuebin; Shang, Dongpeng

2017-01-01

Multispectral palmprint recognition has shown broad prospects for personal identification due to its high accuracy and great stability. In this paper, we develop a novel illumination-invariant multispectral palmprint recognition method. To combine the information from multiple spectral bands, an image-level fusion framework is completed based on a fast and adaptive bidimensional empirical mode decomposition (FABEMD) and a weighted Fisher criterion. The FABEMD technique decomposes the multispectral images into their bidimensional intrinsic mode functions (BIMFs), on which an illumination compensation operation is performed. The weighted Fisher criterion is to construct the fusion coefficients at the decomposition level, making the images be separated correctly in the fusion space. The image fusion framework has shown strong robustness against illumination variation. In addition, a tensor-based extreme learning machine (TELM) mechanism is presented for feature extraction and classification of two-dimensional (2D) images. In general, this method has fast learning speed and satisfying recognition accuracy. Comprehensive experiments conducted on the PolyU multispectral palmprint database illustrate that the proposed method can achieve favorable results. For the testing under ideal illumination, the recognition accuracy is as high as 99.93%, and the result is 99.50% when the lighting condition is unsatisfied.

Faults Diagnostics of Railway Axle Bearings Based on IMF’s Confidence Index Algorithm for Ensemble EMD

PubMed Central

Yi, Cai; Lin, Jianhui; Zhang, Weihua; Ding, Jianming

2015-01-01

As train loads and travel speeds have increased over time, railway axle bearings have become critical elements which require more efficient non-destructive inspection and fault diagnostics methods. This paper presents a novel and adaptive procedure based on ensemble empirical mode decomposition (EEMD) and Hilbert marginal spectrum for multi-fault diagnostics of axle bearings. EEMD overcomes the limitations that often hypothesize about data and computational efforts that restrict the application of signal processing techniques. The outputs of this adaptive approach are the intrinsic mode functions that are treated with the Hilbert transform in order to obtain the Hilbert instantaneous frequency spectrum and marginal spectrum. Anyhow, not all the IMFs obtained by the decomposition should be considered into Hilbert marginal spectrum. The IMFs’ confidence index arithmetic proposed in this paper is fully autonomous, overcoming the major limit of selection by user with experience, and allows the development of on-line tools. The effectiveness of the improvement is proven by the successful diagnosis of an axle bearing with a single fault or multiple composite faults, e.g., outer ring fault, cage fault and pin roller fault. PMID:25970256

A novel hybrid decomposition-and-ensemble model based on CEEMD and GWO for short-term PM2.5 concentration forecasting

NASA Astrophysics Data System (ADS)

Niu, Mingfei; Wang, Yufang; Sun, Shaolong; Li, Yongwu

2016-06-01

To enhance prediction reliability and accuracy, a hybrid model based on the promising principle of "decomposition and ensemble" and a recently proposed meta-heuristic called grey wolf optimizer (GWO) is introduced for daily PM2.5 concentration forecasting. Compared with existing PM2.5 forecasting methods, this proposed model has improved the prediction accuracy and hit rates of directional prediction. The proposed model involves three main steps, i.e., decomposing the original PM2.5 series into several intrinsic mode functions (IMFs) via complementary ensemble empirical mode decomposition (CEEMD) for simplifying the complex data; individually predicting each IMF with support vector regression (SVR) optimized by GWO; integrating all predicted IMFs for the ensemble result as the final prediction by another SVR optimized by GWO. Seven benchmark models, including single artificial intelligence (AI) models, other decomposition-ensemble models with different decomposition methods and models with the same decomposition-ensemble method but optimized by different algorithms, are considered to verify the superiority of the proposed hybrid model. The empirical study indicates that the proposed hybrid decomposition-ensemble model is remarkably superior to all considered benchmark models for its higher prediction accuracy and hit rates of directional prediction.

Hilbert-Huang transform analysis of dynamic and earthquake motion recordings

USGS Publications Warehouse

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

2003-01-01

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

Improving forecasting accuracy of medium and long-term runoff using artificial neural network based on EEMD decomposition.

PubMed

Wang, Wen-chuan; Chau, Kwok-wing; Qiu, Lin; Chen, Yang-bo

2015-05-01

Hydrological time series forecasting is one of the most important applications in modern hydrology, especially for the effective reservoir management. In this research, an artificial neural network (ANN) model coupled with the ensemble empirical mode decomposition (EEMD) is presented for forecasting medium and long-term runoff time series. First, the original runoff time series is decomposed into a finite and often small number of intrinsic mode functions (IMFs) and a residual series using EEMD technique for attaining deeper insight into the data characteristics. Then all IMF components and residue are predicted, respectively, through appropriate ANN models. Finally, the forecasted results of the modeled IMFs and residual series are summed to formulate an ensemble forecast for the original annual runoff series. Two annual reservoir runoff time series from Biuliuhe and Mopanshan in China, are investigated using the developed model based on four performance evaluation measures (RMSE, MAPE, R and NSEC). The results obtained in this work indicate that EEMD can effectively enhance forecasting accuracy and the proposed EEMD-ANN model can attain significant improvement over ANN approach in medium and long-term runoff time series forecasting. Copyright © 2015 Elsevier Inc. All rights reserved.

Ab initio phonon thermal transport in monolayer InSe, GaSe, GaS, and alloys

NASA Astrophysics Data System (ADS)

Pandey, Tribhuwan; Parker, David S.; Lindsay, Lucas

2017-11-01

We compare vibrational properties and phonon thermal conductivities (κ) of monolayer InSe, GaSe, and GaS systems using density functional theory and Peierls-Boltzmann transport methods. In going from InSe to GaSe to GaS, system mass decreases giving both increasing acoustic phonon velocities and decreasing scattering of these heat-carrying modes with optic phonons, ultimately giving {κ }{InSe}< {κ }{GaSe}< {κ }{GaS}. This behavior is demonstrated by correlating the scattering phase space limited by fundamental conservation conditions with mode scattering rates and phonon dispersions for each material. We also show that, unlike flat monolayer systems such as graphene, in InSe, GaSe and GaS thermal transport is governed by in-plane vibrations. Alloying of InSe, GaSe, and GaS systems provides an effective method for modulating their κ through intrinsic vibrational modifications and phonon scattering from mass disorder giving reductions ˜2-3.5 times. This disorder also suppresses phonon mean free paths in the alloy systems compared to those in their crystalline counterparts. This work provides fundamental insights of lattice thermal transport from basic vibrational properties for an interesting set of two-dimensional materials.

Degradation trend estimation of slewing bearing based on LSSVM model

NASA Astrophysics Data System (ADS)

Lu, Chao; Chen, Jie; Hong, Rongjing; Feng, Yang; Li, Yuanyuan

2016-08-01

A novel prediction method is proposed based on least squares support vector machine (LSSVM) to estimate the slewing bearing's degradation trend with small sample data. This method chooses the vibration signal which contains rich state information as the object of the study. Principal component analysis (PCA) was applied to fuse multi-feature vectors which could reflect the health state of slewing bearing, such as root mean square, kurtosis, wavelet energy entropy, and intrinsic mode function (IMF) energy. The degradation indicator fused by PCA can reflect the degradation more comprehensively and effectively. Then the degradation trend of slewing bearing was predicted by using the LSSVM model optimized by particle swarm optimization (PSO). The proposed method was demonstrated to be more accurate and effective by the whole life experiment of slewing bearing. Therefore, it can be applied in engineering practice.

Nonlinear complexity behaviors of agent-based 3D Potts financial dynamics with random environments

NASA Astrophysics Data System (ADS)

Xing, Yani; Wang, Jun

2018-02-01

A new microscopic 3D Potts interaction financial price model is established in this work, to investigate the nonlinear complexity behaviors of stock markets. 3D Potts model, which extends the 2D Potts model to three-dimensional, is a cubic lattice model to explain the interaction behavior among the agents. In order to explore the complexity of real financial markets and the 3D Potts financial model, a new random coarse-grained Lempel-Ziv complexity is proposed to certain series, such as the price returns, the price volatilities, and the random time d-returns. Then the composite multiscale entropy (CMSE) method is applied to the intrinsic mode functions (IMFs) and the corresponding shuffled data to study the complexity behaviors. The empirical results indicate that the 3D financial model is feasible.

Intrinsic network connectivity and own body perception in gender dysphoria.

PubMed

Feusner, Jamie D; Lidström, Andreas; Moody, Teena D; Dhejne, Cecilia; Bookheimer, Susan Y; Savic, Ivanka

2017-08-01

Gender dysphoria (GD) is characterized by incongruence between one's identity and gender assigned at birth. The biological mechanisms of GD are unclear. We investigated brain network connectivity patterns involved in own body perception in the context of self in GD. Twenty-seven female-to-male (FtM) individuals with GD, 27 male controls, and 27 female controls underwent resting state fMRI. We compared functional connections within intrinsic connectivity networks involved in self-referential processes and own body perception -default mode network (DMN) and salience network - and visual networks, using independent components analyses. Behavioral correlates of network connectivity were also tested using self-perception ratings while viewing own body images morphed to their sex assigned at birth, and to the sex of their gender identity. FtM exhibited decreased connectivity of anterior and posterior cingulate and precuneus within the DMN compared with controls. In FtM, higher "self" ratings for bodies morphed towards the sex of their gender identity were associated with greater connectivity of the anterior cingulate within the DMN, during long viewing times. In controls, higher ratings for bodies morphed towards their gender assigned at birth were associated with right insula connectivity within the salience network, during short viewing times. Within visual networks FtM showed weaker connectivity in occipital and temporal regions. Results suggest disconnectivity within networks involved in own body perception in the context of self in GD. Moreover, perception of bodies in relation to self may be reflective rather than reflexive, as a function of mesial prefrontal processes. These may represent neurobiological correlates to the subjective disconnection between perception of body and self-identification.

Integrated ensemble noise-reconstructed empirical mode decomposition for mechanical fault detection

NASA Astrophysics Data System (ADS)

Yuan, Jing; Ji, Feng; Gao, Yuan; Zhu, Jun; Wei, Chenjun; Zhou, Yu

2018-05-01

A new branch of fault detection is utilizing the noise such as enhancing, adding or estimating the noise so as to improve the signal-to-noise ratio (SNR) and extract the fault signatures. Hereinto, ensemble noise-reconstructed empirical mode decomposition (ENEMD) is a novel noise utilization method to ameliorate the mode mixing and denoised the intrinsic mode functions (IMFs). Despite the possibility of superior performance in detecting weak and multiple faults, the method still suffers from the major problems of the user-defined parameter and the powerless capability for a high SNR case. Hence, integrated ensemble noise-reconstructed empirical mode decomposition is proposed to overcome the drawbacks, improved by two noise estimation techniques for different SNRs as well as the noise estimation strategy. Independent from the artificial setup, the noise estimation by the minimax thresholding is improved for a low SNR case, which especially shows an outstanding interpretation for signature enhancement. For approximating the weak noise precisely, the noise estimation by the local reconfiguration using singular value decomposition (SVD) is proposed for a high SNR case, which is particularly powerful for reducing the mode mixing. Thereinto, the sliding window for projecting the phase space is optimally designed by the correlation minimization. Meanwhile, the reasonable singular order for the local reconfiguration to estimate the noise is determined by the inflection point of the increment trend of normalized singular entropy. Furthermore, the noise estimation strategy, i.e. the selection approaches of the two estimation techniques along with the critical case, is developed and discussed for different SNRs by means of the possible noise-only IMF family. The method is validated by the repeatable simulations to demonstrate the synthetical performance and especially confirm the capability of noise estimation. Finally, the method is applied to detect the local wear fault from a dual-axis stabilized platform and the gear crack from an operating electric locomotive to verify its effectiveness and feasibility.

Intrinsic platelet reactivity before start with clopidogrel as predictor for on-clopidogrel platelet function and long-term clinical outcome.

PubMed

Hochholzer, Willibald; Valina, Christian M; Bömicke, Timo; Amann, Michael; Stratz, Christian; Nührenberg, Thomas; Trenk, Dietmar; Neumann, Franz-Josef

2015-07-01

High on-clopidogrel platelet reactivity is associated with worse clinical outcome. Previous data suggest that intrinsic platelet reactivity before initiation of clopidogrel contributes significantly to on-clopidogrel platelet reactivity. It is unknown whether intrinsic reactivity can sufficiently predict on-clopidogrel reactivity and therefore identify patients with insufficient response to clopidogrel before initiation of treatment and at risk for worse clinical outcome. This analysis included 765 consecutive patients undergoing elective coronary stent implantation. Platelet reactivity was assessed by light transmission aggregometry (5 µM ADP) before administration of clopidogrel 600mg and after intake of first maintenance dose of clopidogrel on day 1 following coronary stenting. Patients were followed for up to seven years. The combined primary endpoint was death of any cause or non-fatal myocardial infarction. Intrinsic and on-clopidogrel platelet reactivity were significant correlated (r=0.31; p < 0.001). Among all tested clinical and genetic factors including the cytochrome P450 2C19*2 polymorphism, intrinsic platelet reactivity was the strongest predictor for on-clopidogrel platelet reactivity. However, intrinsic platelet reactivity could only explain 8 % of variability of on-clopidogrel platelet function. Only on-treatment platelet reactivity was predictive for long-term clinical outcome (HR 1.47, 95 % CI 1.05-2.05; p = 0.02) whereas intrinsic platelet reactivity was not (HR 1.03, 95 % CI 0.74-1.43; p = 0.86). In conclusion, intrinsic platelet reactivity before initiation of clopidogrel is the strongest predictor of early on-clopidogrel platelet reactivity but can only explain a minor proportion of its variability and is not significantly associated with clinical outcome. Thus, baseline testing cannot substitute on-clopidogrel platelet function testing.

Intrinsic incompatibilities evolving as a by-product of divergent ecological selection: Considering them in empirical studies on divergence with gene flow.

PubMed

Kulmuni, J; Westram, A M

2017-06-01

The possibility of intrinsic barriers to gene flow is often neglected in empirical research on local adaptation and speciation with gene flow, for example when interpreting patterns observed in genome scans. However, we draw attention to the fact that, even with gene flow, divergent ecological selection may generate intrinsic barriers involving both ecologically selected and other interacting loci. Mechanistically, the link between the two types of barriers may be generated by genes that have multiple functions (i.e., pleiotropy), and/or by gene interaction networks. Because most genes function in complex networks, and their evolution is not independent of other genes, changes evolving in response to ecological selection can generate intrinsic barriers as a by-product. A crucial question is to what extent such by-product barriers contribute to divergence and speciation-that is whether they stably reduce gene flow. We discuss under which conditions by-product barriers may increase isolation. However, we also highlight that, depending on the conditions (e.g., the amount of gene flow and the strength of selection acting on the intrinsic vs. the ecological barrier component), the intrinsic incompatibility may actually destabilize barriers to gene flow. In practice, intrinsic barriers generated as a by-product of divergent ecological selection may generate peaks in genome scans that cannot easily be interpreted. We argue that empirical studies on divergence with gene flow should consider the possibility of both ecological and intrinsic barriers. Future progress will likely come from work combining population genomic studies, experiments quantifying fitness and molecular studies on protein function and interactions. © 2017 The Authors. Molecular Ecology Published by John Wiley & Sons Ltd.

Values: Jaundiced Perversions/Lucid Alternatives.

ERIC Educational Resources Information Center

Nissman, Albert

The American educational system must emphasize values education and the role of the teacher in instilling proper values. Within the context of this paper, values are the intrinsic regard people have for other people, ideas, attitudes, or modes of behavior. Values rest on a philosophical base and require the intellectual choice of the beholder.…

Effective field theory of emergent symmetry breaking in deformed atomic nuclei

DOE PAGES

Papenbrock, Thomas F.; Weidenmüller, H. A.

2015-09-03

Spontaneous symmetry breaking in non-relativistic quantum systems has previously been addressed in the framework of effective field theory. Low-lying excitations are constructed from Nambu–Goldstone modes using symmetry arguments only. In this study, we extend that approach to finite systems. The approach is very general. To be specific, however, we consider atomic nuclei with intrinsically deformed ground states. The emergent symmetry breaking in such systems requires the introduction of additional degrees of freedom on top of the Nambu–Goldstone modes. Symmetry arguments suffice to construct the low-lying states of the system. Lastly, in deformed nuclei these are vibrational modes each of whichmore » serves as band head of a rotational band.« less

Compact eccentric long period grating with improved sensitivity in low refractive index region.

PubMed

Shen, Fangcheng; Zhou, Kaiming; Gordon, Neil; Zhang, Lin; Shu, Xuewen

2017-07-10

We demonstrate a compact eccentric long period grating with enhanced sensitivity in low refractive index region. With a period designed at 15 µm for coupling light to high order cladding modes, the grating is more sensitive to surrounding refractive index in low refractive index region. The intrinsically low coupling coefficients for those high order cladding modes are significantly improved with the eccentric localized inscription induced by the femtosecond laser. The fabricated grating is compact with a length of 4.05 mm, and exhibits an average sensitivity of ~505 nm/RIU in low refractive index region (1.3328-1.3544). The proposed principle can also work in other refractive index region with a proper choice of the resonant cladding modes.

Nonlinear helicons bearing multi-scale structures

NASA Astrophysics Data System (ADS)

Abdelhamid, Hamdi M.; Yoshida, Zensho

2017-02-01

The helicon waves exhibit varying characters depending on plasma parameters, geometry, and wave numbers. Here, we elucidate an intrinsic multi-scale property embodied by the combination of the dispersive effect and nonlinearity. The extended magnetohydrodynamics model (exMHD) is capable of describing a wide range of parameter space. By using the underlying Hamiltonian structure of exMHD, we construct an exact nonlinear solution, which turns out to be a combination of two distinct modes, the helicon and Trivelpiece-Gould (TG) waves. In the regime of relatively low frequency or high density, however, the combination is made of the TG mode and an ion cyclotron wave (slow wave). The energy partition between these modes is determined by the helicities carried by the wave fields.

Investigating the Temporal Patterns within and between Intrinsic Connectivity Networks under Eyes-Open and Eyes-Closed Resting States: A Dynamical Functional Connectivity Study Based on Phase Synchronization

PubMed Central

Wang, Xun-Heng; Li, Lihua; Xu, Tao; Ding, Zhongxiang

2015-01-01

The brain active patterns were organized differently under resting states of eyes open (EO) and eyes closed (EC). The altered voxel-wise and regional-wise resting state active patterns under EO/EC were found by static analysis. More importantly, dynamical spontaneous functional connectivity has been observed in the resting brain. To the best of our knowledge, the dynamical mechanisms of intrinsic connectivity networks (ICNs) under EO/EC remain largely unexplored. The goals of this paper were twofold: 1) investigating the dynamical intra-ICN and inter-ICN temporal patterns during resting state; 2) analyzing the altered dynamical temporal patterns of ICNs under EO/EC. To this end, a cohort of healthy subjects with scan conditions of EO/EC were recruited from 1000 Functional Connectomes Project. Through Hilbert transform, time-varying phase synchronization (PS) was applied to evaluate the inter-ICN synchrony. Meanwhile, time-varying amplitude was analyzed as dynamical intra-ICN temporal patterns. The results found six micro-states of inter-ICN synchrony. The medial visual network (MVN) showed decreased intra-ICN amplitude during EC relative to EO. The sensory-motor network (SMN) and auditory network (AN) exhibited enhanced intra-ICN amplitude during EC relative to EO. Altered inter-ICN PS was found between certain ICNs. Particularly, the SMN and AN exhibited enhanced PS to other ICNs during EC relative to EO. In addition, the intra-ICN amplitude might influence the inter-ICN synchrony. Moreover, default mode network (DMN) might play an important role in information processing during EO/EC. Together, the dynamical temporal patterns within and between ICNs were altered during different scan conditions of EO/EC. Overall, the dynamical intra-ICN and inter-ICN temporal patterns could benefit resting state fMRI-related research, and could be potential biomarkers for human functional connectome. PMID:26469182

Nature of exciton transitions in hexagonal boron nitride

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

Li, J.; Cao, X. K.; Lin, J. Y.

2016-03-21

In contrast to other III-nitride semiconductors GaN and AlN, the intrinsic (or free) exciton transition in hexagonal boron nitride (h-BN) consists of rather complex fine spectral features (resolved into six sharp emission peaks) and the origin of which is still unclear. Here, the free exciton transition (FX) in h-BN bulk crystals synthesized by a solution method at atmospheric pressure has been probed by deep UV time-resolved photoluminescence (PL) spectroscopy. Based on the separations between the energy peak positions of the FX emission lines, the identical PL decay kinetics among different FX emission lines, and the known phonon modes in h-BN,more » we suggest that there is only one principal emission line corresponding to the direct intrinsic FX transition in h-BN, whereas all other fine features are a result of phonon-assisted transitions. The identified phonon modes are all associated with the center of the Brillouin zone. Our results offer a simple picture for the understanding of the fundamental exciton transitions in h-BN.« less

Functional ecology of aquatic phagotrophic protists - Concepts, limitations, and perspectives.

PubMed

Weisse, Thomas; Anderson, Ruth; Arndt, Hartmut; Calbet, Albert; Hansen, Per Juel; Montagnes, David J S

2016-08-01

Functional ecology is a subdiscipline that aims to enable a mechanistic understanding of patterns and processes from the organismic to the ecosystem level. This paper addresses some main aspects of the process-oriented current knowledge on phagotrophic, i.e. heterotrophic and mixotrophic, protists in aquatic food webs. This is not an exhaustive review; rather, we focus on conceptual issues, in particular on the numerical and functional response of these organisms. We discuss the evolution of concepts and define parameters to evaluate predator-prey dynamics ranging from Lotka-Volterra to the Independent Response Model. Since protists have extremely versatile feeding modes, we explore if there are systematic differences related to their taxonomic affiliation and life strategies. We differentiate between intrinsic factors (nutritional history, acclimatisation) and extrinsic factors (temperature, food, turbulence) affecting feeding, growth, and survival of protist populations. We briefly consider intraspecific variability of some key parameters and constraints inherent in laboratory microcosm experiments. We then upscale the significance of phagotrophic protists in food webs to the ocean level. Finally, we discuss limitations of the mechanistic understanding of protist functional ecology resulting from principal unpredictability of nonlinear dynamics. We conclude by defining open questions and identifying perspectives for future research on functional ecology of aquatic phagotrophic protists. Copyright © 2016 The Authors. Published by Elsevier GmbH.. All rights reserved.

Polymeric 3D Printed Functional Microcantilevers for Biosensing Applications.

PubMed

Stassi, Stefano; Fantino, Erika; Calmo, Roberta; Chiappone, Annalisa; Gillono, Matteo; Scaiola, Davide; Pirri, Candido Fabrizio; Ricciardi, Carlo; Chiadò, Alessandro; Roppolo, Ignazio

2017-06-07

In this study, we show for the first time the production of mass-sensitive polymeric biosensors by 3D printing technology with intrinsic functionalities. We also demonstrate the feasibility of mass-sensitive biosensors in the form of microcantilever in a one-step printing process, using acrylic acid as functional comonomer for introducing a controlled amount of functional groups that can covalently immobilize the biomolecules onto the polymer. The effectiveness of the application of 3D printed microcantilevers as biosensors is then demonstrated with their implementation in a standard immunoassay protocol. This study shows how 3D microfabrication techniques, material characterization, and biosensor development could be combined to obtain an engineered polymeric microcantilever with intrinsic functionalities. The possibility of tuning the composition of the starting photocurable resin with the addition of functional agents, and consequently controlling the functionalities of the 3D printed devices, paves the way to a new class of mass-sensing microelectromechanical system devices with intrinsic properties.

Disorder in milk proteins: caseins, intrinsically disordered colloids.

PubMed

Redwan, Elrashdy M; Xue, Bin; Almehdar, Hussein A; Uversky, Vladimir N

2015-01-01

This article opens a series of reviews on the abundance and roles of intrinsic disorder in milk proteins. The focus of this introductory article on caseins is symbolic, since caseins were among the first recognized functional unfolded proteins and since they are definitely the most disordered, the most abundant, and the most studied of all milk proteins. In eutherian milks, the casein family includes at least three and usually four major members (αs1-, αs2-, β-, and κ-caseins) that are unrelated in sequence. However, in some species, two different αS2-casein genes are active, and therefore the total number of caseins can be as high as five. These proteins have found a number of uses in food industry. The functional repertoire of caseins ranges from nutritional function to involvement in the improving and/or maintaining cardiovascular health, to crucial contribution to the milk capacity to transport calcium phosphate, to serve as molecular chaperones, and to protect the mother's mammary gland against amyloidoses and ectopic calcification. An intricate feature of caseins is their ability to assemble to colloidal protein particles, casein micelles, serving to sequester and transport amorphous calcium phosphate. These and many other functions of caseins are obviously dependent on their intrinsically disordered nature and are controlled by various posttranslational modifications. Since various aspects of casein structure and function are rather well studied and since several recent reviews emphasized the functional roles of caseins' intrinsic disorder, the major goal of this article is to show how intrinsic disorder is encoded in the amino acid sequences of these proteins.

Plasmon-induced carrier polarization in semiconductor nanocrystals.

PubMed

Yin, Penghui; Tan, Yi; Fang, Hanbing; Hegde, Manu; Radovanovic, Pavle V

2018-06-01

Spintronics 1 and valleytronics 2 are emerging quantum electronic technologies that rely on using electron spin and multiple extrema of the band structure (valleys), respectively, as additional degrees of freedom. There are also collective properties of electrons in semiconductor nanostructures that potentially could be exploited in multifunctional quantum devices. Specifically, plasmonic semiconductor nanocrystals 3-10 offer an opportunity for interface-free coupling between a plasmon and an exciton. However, plasmon-exciton coupling in single-phase semiconductor nanocrystals remains challenging because confined plasmon oscillations are generally not resonant with excitonic transitions. Here, we demonstrate a robust electron polarization in degenerately doped In 2 O 3 nanocrystals, enabled by non-resonant coupling of cyclotron magnetoplasmonic modes 11 with the exciton at the Fermi level. Using magnetic circular dichroism spectroscopy, we show that intrinsic plasmon-exciton coupling allows for the indirect excitation of the magnetoplasmonic modes, and subsequent Zeeman splitting of the excitonic states. Splitting of the band states and selective carrier polarization can be manipulated further by spin-orbit coupling. Our results effectively open up the field of plasmontronics, which involves the phenomena that arise from intrinsic plasmon-exciton and plasmon-spin interactions. Furthermore, the dynamic control of carrier polarization is readily achieved at room temperature, which allows us to harness the magnetoplasmonic mode as a new degree of freedom in practical photonic, optoelectronic and quantum-information processing devices.

Plasmon-induced carrier polarization in semiconductor nanocrystals

NASA Astrophysics Data System (ADS)

Yin, Penghui; Tan, Yi; Fang, Hanbing; Hegde, Manu; Radovanovic, Pavle V.

2018-06-01

Spintronics1 and valleytronics2 are emerging quantum electronic technologies that rely on using electron spin and multiple extrema of the band structure (valleys), respectively, as additional degrees of freedom. There are also collective properties of electrons in semiconductor nanostructures that potentially could be exploited in multifunctional quantum devices. Specifically, plasmonic semiconductor nanocrystals3-10 offer an opportunity for interface-free coupling between a plasmon and an exciton. However, plasmon-exciton coupling in single-phase semiconductor nanocrystals remains challenging because confined plasmon oscillations are generally not resonant with excitonic transitions. Here, we demonstrate a robust electron polarization in degenerately doped In2O3 nanocrystals, enabled by non-resonant coupling of cyclotron magnetoplasmonic modes11 with the exciton at the Fermi level. Using magnetic circular dichroism spectroscopy, we show that intrinsic plasmon-exciton coupling allows for the indirect excitation of the magnetoplasmonic modes, and subsequent Zeeman splitting of the excitonic states. Splitting of the band states and selective carrier polarization can be manipulated further by spin-orbit coupling. Our results effectively open up the field of plasmontronics, which involves the phenomena that arise from intrinsic plasmon-exciton and plasmon-spin interactions. Furthermore, the dynamic control of carrier polarization is readily achieved at room temperature, which allows us to harness the magnetoplasmonic mode as a new degree of freedom in practical photonic, optoelectronic and quantum-information processing devices.

Genetic and Diagnostic Biomarker Development in ASD Toddlers Using Resting State Functional MRI

DTIC Science & Technology

2017-11-01

and activation-based fMRI from the Courchesne lab report the presence of structural and functional abnormality in these structures by ages 1 to 2...young ages. With this invaluable resource, we will identify early developmental patterns of intrinsic functional network abnormalities in ASD infants...all infants and toddlers, analyses also investigate whether there may be subtypes of abnormal intrinsic connectivity patterns based on early clinical

Loss of Intrinsic Organization of Cerebellar Networks in Spinocerebellar Ataxia Type 1: Correlates with Disease Severity and Duration

PubMed Central

Peri, Eitan; Chen, E. Elinor; Ben-Jacob, Eshel; Gomez, Christopher M.

2011-01-01

The spinocerebellar ataxias (SCAs) are a genetically heterogeneous group of cerebellar degenerative disorders, characterized by progressive gait unsteadiness, hand incoordination, and dysarthria. The mutational mechanism in SCA1, a dominantly inherited form of SCA, consists of an expanded trinucleotide CAG repeat. In SCA1, there is loss of Purkinje cells, neuronal loss in dentate nucleus, olives, and pontine nuclei. In the present study, we sought to apply intrinsic functional connectivity analysis combined with diffusion tensor imaging to define the state of cerebellar connectivity in SCA1. Our results on the intrinsic functional connectivity in lateral cerebellum and thalamus showed progressive organizational changes in SCA1 noted as a progressive increase in the absolute value of the correlation coefficients. In the lateral cerebellum, the anatomical organization of functional clusters seen as parasagittal bands in controls is lost, changing to a patchy appearance in SCA1. Lastly, only fractional anisotropy in the superior peduncle and changes in functional organization in thalamus showed a linear dependence to duration and severity of disease. The present pilot work represents an initial effort describing connectivity biomarkers of disease progression in SCA1. The functional changes detected with intrinsic functional analysis and diffusion tensor imaging suggest that disease progression can be analyzed as a disconnection syndrome. PMID:20886327

Abnormalities of Intrinsic Functional Connectivity in Autism Spectrum Disorders

PubMed Central

Monk, Christopher S.; Peltier, Scott J.; Wiggins, Jillian Lee; Weng, Shih-Jen; Carrasco, Melisa; Risi, Susan; Lord, Catherine

2009-01-01

Autism spectrum disorders (ASD) impact social functioning and communication, and individuals with these disorders often have restrictive and repetitive behaviors. Accumulating data indicate that ASD is associated with alterations of neural circuitry. Functional MRI (FMRI) studies have focused on connectivity in the context of psychological tasks. However, even in the absence of a task, the brain exhibits a high degree of functional connectivity, known as intrinsic or resting connectivity. Notably, the default network, which includes the posterior cingulate cortex, retro-splenial, lateral parietal cortex/angular gyrus, medial prefrontal cortex, superior frontal gyrus, temporal lobe, and parahippocampal gyrus, is strongly active when there is no task. Altered intrinsic connectivity within the default network may underlie offline processing that may actuate ASD impairments. Using FMRI, we sought to evaluate intrinsic connectivity within the default network in ASD. Relative to controls, the ASD group showed weaker connectivity between the posterior cingulate cortex and superior frontal gyrus and stronger connectivity between the posterior cingulate cortex and both the right temporal lobe and right parahippocampal gyrus. Moreover, poorer social functioning in the ASD group was correlated with weaker connectivity between the posterior cingulate cortex and the superior frontal gyrus. In addition, more severe restricted and repetitive behaviors in ASD were correlated with stronger connectivity between the posterior cingulate cortex and right parahippocampal gyrus. These findings indicate that ASD subjects show altered intrinsic connectivity within the default network, and connectivity between these structures is associated with specific ASD symptoms. PMID:19409498

Electronegativity and intrinsic disorder of preeclampsia-related proteins.

PubMed

Polanco, Carlos; Castañón-González, Jorge Alberto; Uversky, Vladimir N; Buhse, Thomas; Samaniego Mendoza, José Lino; Calva, Juan J

2017-01-01

Preeclampsia, hemorrhage, and infection are the leading causes of maternal death in underdeveloped countries. Since several proteins associated with preeclampsia are known, we conducted a computational study which evaluated the commonness and potential functionality of intrinsic disorder of these proteins and also made an attempt to characterize their origin. The origin of the preeclampsia-related proteins was assessed with a supervised technique, a Polarity Index Method (PIM), which evaluates the electronegativity of proteins based solely on their sequence. The commonness of intrinsic disorder was evaluated using several disorder predictors from the PONDR family, the charge-hydropathy plot (CH-plot) and cumulative distribution function (CDF) analyses, and using the MobiDB web-based tool, whereas potential functionality of intrinsic disorder was studied with the D2P2 resource and ANCHOR predictor of disorder-based binding sites, and the STRING tool was used to build the interactivity networks of the preeclampsia-related proteins. Peculiarities of the PIM-derived polar profile of the group of preeclampsia-related proteins were then compared with profiles of a group of lipoproteins, antimicrobial peptides, angiogenesis-related proteins, and the intrinsically disordered proteins. Our results showed a high graphical correlation between preeclampsia proteins, lipoproteins, and the angiogenesis proteins. We also showed that many preeclampsia-related proteins contain numerous functional disordered regions. Therefore, these bioinformatics results led us to assume that the preeclampsia proteins are highly associated with the lipoproteins group, and that some preeclampsia-related proteins contain significant amounts of functional disorders.

Tai Chi Chuan optimizes the functional organization of the intrinsic human brain architecture in older adults

PubMed Central

Wei, Gao-Xia; Dong, Hao-Ming; Yang, Zhi; Luo, Jing; Zuo, Xi-Nian

2014-01-01

Whether Tai Chi Chuan (TCC) can influence the intrinsic functional architecture of the human brain remains unclear. To examine TCC-associated changes in functional connectomes, resting-state functional magnetic resonance images were acquired from 40 older individuals including 22 experienced TCC practitioners (experts) and 18 demographically matched TCC-naïve healthy controls, and their local functional homogeneities across the cortical mantle were compared. Compared to the controls, the TCC experts had significantly greater and more experience-dependent functional homogeneity in the right post-central gyrus (PosCG) and less functional homogeneity in the left anterior cingulate cortex (ACC) and the right dorsal lateral prefrontal cortex. Increased functional homogeneity in the PosCG was correlated with TCC experience. Intriguingly, decreases in functional homogeneity (improved functional specialization) in the left ACC and increases in functional homogeneity (improved functional integration) in the right PosCG both predicted performance gains on attention network behavior tests. These findings provide evidence for the functional plasticity of the brain’s intrinsic architecture toward optimizing locally functional organization, with great implications for understanding the effects of TCC on cognition, behavior and health in aging population. PMID:24860494

The Longitudinal Trajectory of Default Mode Network Connectivity in Healthy Older Adults Varies As a Function of Age and Is Associated with Changes in Episodic Memory and Processing Speed.

PubMed

Staffaroni, Adam M; Brown, Jesse A; Casaletto, Kaitlin B; Elahi, Fanny M; Deng, Jersey; Neuhaus, John; Cobigo, Yann; Mumford, Paige S; Walters, Samantha; Saloner, Rowan; Karydas, Anna; Coppola, Giovanni; Rosen, Howie J; Miller, Bruce L; Seeley, William W; Kramer, Joel H

2018-03-14

The default mode network (DMN) supports memory functioning and may be sensitive to preclinical Alzheimer's pathology. Little is known, however, about the longitudinal trajectory of this network's intrinsic functional connectivity (FC). In this study, we evaluated longitudinal FC in 111 cognitively normal older human adults (ages 49-87, 46 women/65 men), 92 of whom had at least three task-free fMRI scans ( n = 353 total scans). Whole-brain FC and three DMN subnetworks were assessed: (1) within-DMN, (2) between anterior and posterior DMN, and (3) between medial temporal lobe network and posterior DMN. Linear mixed-effects models demonstrated significant baseline age × time interactions, indicating a nonlinear trajectory. There was a trend toward increasing FC between ages 50-66 and significantly accelerating declines after age 74. A similar interaction was observed for whole-brain FC. APOE status did not predict baseline connectivity or change in connectivity. After adjusting for network volume, changes in within-DMN connectivity were specifically associated with changes in episodic memory and processing speed but not working memory or executive functions. The relationship with processing speed was attenuated after covarying for white matter hyperintensities (WMH) and whole-brain FC, whereas within-DMN connectivity remained associated with memory above and beyond WMH and whole-brain FC. Whole-brain and DMN FC exhibit a nonlinear trajectory, with more rapid declines in older age and possibly increases in connectivity early in the aging process. Within-DMN connectivity is a marker of episodic memory performance even among cognitively healthy older adults. SIGNIFICANCE STATEMENT Default mode network and whole-brain connectivity, measured using task-free fMRI, changed nonlinearly as a function of age, with some suggestion of early increases in connectivity. For the first time, longitudinal changes in DMN connectivity were shown to correlate with changes in episodic memory, whereas volume changes in relevant brain regions did not. This relationship was not accounted for by white matter hyperintensities or mean whole-brain connectivity. Functional connectivity may be an early biomarker of changes in aging but should be used with caution given its nonmonotonic nature, which could complicate interpretation. Future studies investigating longitudinal network changes should consider whole-brain changes in connectivity. Copyright © 2018 the authors 0270-6474/18/382810-09$15.00/0.