[Variable selection methods combined with local linear embedding theory used for optimization of near infrared spectral quantitative models].

PubMed

Hao, Yong; Sun, Xu-Dong; Yang, Qiang

2012-12-01

Variables selection strategy combined with local linear embedding (LLE) was introduced for the analysis of complex samples by using near infrared spectroscopy (NIRS). Three methods include Monte Carlo uninformation variable elimination (MCUVE), successive projections algorithm (SPA) and MCUVE connected with SPA were used for eliminating redundancy spectral variables. Partial least squares regression (PLSR) and LLE-PLSR were used for modeling complex samples. The results shown that MCUVE can both extract effective informative variables and improve the precision of models. Compared with PLSR models, LLE-PLSR models can achieve more accurate analysis results. MCUVE combined with LLE-PLSR is an effective modeling method for NIRS quantitative analysis.

Investigating the effects of nitrous oxide sedation on frontal-parietal interactions.

PubMed

Ryu, Ji-Ho; Kim, Pil-Jong; Kim, Hong-Gee; Koo, Yong-Seo; Shin, Teo Jeon

2017-06-09

Although functional connectivity has received considerable attention in the study of consciousness, few studies have investigated functional connectivity limited to the sedated state where consciousness is maintained but impaired. The aim of the present study was to investigate changes in functional connectivity of the parietal-frontal network resulting from nitrous oxide-induced sedation, and to determine the neural correlates of cognitive impairment during consciousness transition states. Electroencephalography was acquired from healthy adult patients who underwent nitrous oxide inhalation to induce cognitive impairment, and was analyzed using Granger causality (GC). Periods of awake, sedation and recovery for GC between frontal and parietal areas in the delta, theta, alpha, beta, gamma and total frequency bands were obtained. The Friedman test with post-hoc analysis was conducted for GC values of each period for comparison. As a sedated state was induced by nitrous oxide inhalation, power in the low frequency band showed increased activity in frontal regions that was reversed with discontinuation of nitrous oxide. Feedback and feedforward connections analyzed in spectral GC were changed differently in accordance with EEG frequency bands in the sedated state by nitrous oxide administration. Calculated spectral GC of the theta, alpha, and beta frequency regions in the parietal-to-frontal direction was significantly decreased in the sedated state while spectral GC in the reverse direction did not show significant change. Frontal-parietal functional connectivity is significantly affected by nitrous oxide inhalation. Significantly decreased parietal-to-frontal interaction may induce a sedated state. Copyright © 2017 Elsevier B.V. All rights reserved.

Dynamic analysis of beam-cable coupled systems using Chebyshev spectral element method

NASA Astrophysics Data System (ADS)

Huang, Yi-Xin; Tian, Hao; Zhao, Yang

2017-10-01

The dynamic characteristics of a beam-cable coupled system are investigated using an improved Chebyshev spectral element method in order to observe the effects of adding cables on the beam. The system is modeled as a double Timoshenko beam system interconnected by discrete springs. Utilizing Chebyshev series expansion and meshing the system according to the locations of its connections, numerical results of the natural frequencies and mode shapes are obtained using only a few elements, and the results are validated by comparing them with the results of a finite-element method. Then the effects of the cable parameters and layout of connections on the natural frequencies and mode shapes of a fixed-pinned beam are studied. The results show that the modes of a beam-cable coupled system can be classified into two types, beam mode and cable mode, according to the dominant deformation. To avoid undesirable vibrations of the cable, its parameters should be controlled in a reasonable range, or the layout of the connections should be optimized.

Spectral analysis and slow spreading dynamics on complex networks.

PubMed

Odor, Géza

2013-09-01

The susceptible-infected-susceptible (SIS) model is one of the simplest memoryless systems for describing information or epidemic spreading phenomena with competing creation and spontaneous annihilation reactions. The effect of quenched disorder on the dynamical behavior has recently been compared to quenched mean-field (QMF) approximations in scale-free networks. QMF can take into account topological heterogeneity and clustering effects of the activity in the steady state by spectral decomposition analysis of the adjacency matrix. Therefore, it can provide predictions on possible rare-region effects, thus on the occurrence of slow dynamics. I compare QMF results of SIS with simulations on various large dimensional graphs. In particular, I show that for Erdős-Rényi graphs this method predicts correctly the occurrence of rare-region effects. It also provides a good estimate for the epidemic threshold in case of percolating graphs. Griffiths Phases emerge if the graph is fragmented or if we apply a strong, exponentially suppressing weighting scheme on the edges. The latter model describes the connection time distributions in the face-to-face experiments. In case of a generalized Barabási-Albert type of network with aging connections, strong rare-region effects and numerical evidence for Griffiths Phase dynamics are shown. The dynamical simulation results agree well with the predictions of the spectral analysis applied for the weighted adjacency matrices.

SpectralNET – an application for spectral graph analysis and visualization

PubMed Central

Forman, Joshua J; Clemons, Paul A; Schreiber, Stuart L; Haggarty, Stephen J

2005-01-01

Background Graph theory provides a computational framework for modeling a variety of datasets including those emerging from genomics, proteomics, and chemical genetics. Networks of genes, proteins, small molecules, or other objects of study can be represented as graphs of nodes (vertices) and interactions (edges) that can carry different weights. SpectralNET is a flexible application for analyzing and visualizing these biological and chemical networks. Results Available both as a standalone .NET executable and as an ASP.NET web application, SpectralNET was designed specifically with the analysis of graph-theoretic metrics in mind, a computational task not easily accessible using currently available applications. Users can choose either to upload a network for analysis using a variety of input formats, or to have SpectralNET generate an idealized random network for comparison to a real-world dataset. Whichever graph-generation method is used, SpectralNET displays detailed information about each connected component of the graph, including graphs of degree distribution, clustering coefficient by degree, and average distance by degree. In addition, extensive information about the selected vertex is shown, including degree, clustering coefficient, various distance metrics, and the corresponding components of the adjacency, Laplacian, and normalized Laplacian eigenvectors. SpectralNET also displays several graph visualizations, including a linear dimensionality reduction for uploaded datasets (Principal Components Analysis) and a non-linear dimensionality reduction that provides an elegant view of global graph structure (Laplacian eigenvectors). Conclusion SpectralNET provides an easily accessible means of analyzing graph-theoretic metrics for data modeling and dimensionality reduction. SpectralNET is publicly available as both a .NET application and an ASP.NET web application from . Source code is available upon request. PMID:16236170

SpectralNET--an application for spectral graph analysis and visualization.

PubMed

Forman, Joshua J; Clemons, Paul A; Schreiber, Stuart L; Haggarty, Stephen J

2005-10-19

Graph theory provides a computational framework for modeling a variety of datasets including those emerging from genomics, proteomics, and chemical genetics. Networks of genes, proteins, small molecules, or other objects of study can be represented as graphs of nodes (vertices) and interactions (edges) that can carry different weights. SpectralNET is a flexible application for analyzing and visualizing these biological and chemical networks. Available both as a standalone .NET executable and as an ASP.NET web application, SpectralNET was designed specifically with the analysis of graph-theoretic metrics in mind, a computational task not easily accessible using currently available applications. Users can choose either to upload a network for analysis using a variety of input formats, or to have SpectralNET generate an idealized random network for comparison to a real-world dataset. Whichever graph-generation method is used, SpectralNET displays detailed information about each connected component of the graph, including graphs of degree distribution, clustering coefficient by degree, and average distance by degree. In addition, extensive information about the selected vertex is shown, including degree, clustering coefficient, various distance metrics, and the corresponding components of the adjacency, Laplacian, and normalized Laplacian eigenvectors. SpectralNET also displays several graph visualizations, including a linear dimensionality reduction for uploaded datasets (Principal Components Analysis) and a non-linear dimensionality reduction that provides an elegant view of global graph structure (Laplacian eigenvectors). SpectralNET provides an easily accessible means of analyzing graph-theoretic metrics for data modeling and dimensionality reduction. SpectralNET is publicly available as both a .NET application and an ASP.NET web application from http://chembank.broad.harvard.edu/resources/. Source code is available upon request.

A SPECTRAL GRAPH APPROACH TO DISCOVERING GENETIC ANCESTRY1

PubMed Central

Lee, Ann B.; Luca, Diana; Roeder, Kathryn

2010-01-01

Mapping human genetic variation is fundamentally interesting in fields such as anthropology and forensic inference. At the same time, patterns of genetic diversity confound efforts to determine the genetic basis of complex disease. Due to technological advances, it is now possible to measure hundreds of thousands of genetic variants per individual across the genome. Principal component analysis (PCA) is routinely used to summarize the genetic similarity between subjects. The eigenvectors are interpreted as dimensions of ancestry. We build on this idea using a spectral graph approach. In the process we draw on connections between multidimensional scaling and spectral kernel methods. Our approach, based on a spectral embedding derived from the normalized Laplacian of a graph, can produce more meaningful delineation of ancestry than by using PCA. The method is stable to outliers and can more easily incorporate different similarity measures of genetic data than PCA. We illustrate a new algorithm for genetic clustering and association analysis on a large, genetically heterogeneous sample. PMID:20689656

The outburst decay of the low magnetic field magnetar SWIFT J1822.3-1606: phase-resolved analysis and evidence for a variable cyclotron feature

NASA Astrophysics Data System (ADS)

Rodríguez Castillo, Guillermo A.; Israel, Gian Luca; Tiengo, Andrea; Salvetti, David; Turolla, Roberto; Zane, Silvia; Rea, Nanda; Esposito, Paolo; Mereghetti, Sandro; Perna, Rosalba; Stella, Luigi; Pons, José A.; Campana, Sergio; Götz, Diego; Motta, Sara

2016-03-01

We study the timing and spectral properties of the low-magnetic field, transient magnetar SWIFT J1822.3-1606 as it approached quiescence. We coherently phase-connect the observations over a time-span of ˜500 d since the discovery of SWIFT J1822.3-1606 following the Swift-Burst Alert Telescope (BAT) trigger on 2011 July 14, and carried out a detailed pulse phase spectroscopy along the outburst decay. We follow the spectral evolution of different pulse phase intervals and find a phase and energy-variable spectral feature, which we interpret as proton cyclotron resonant scattering of soft photon from currents circulating in a strong (≳1014 G) small-scale component of the magnetic field near the neutron star surface, superimposed to the much weaker (˜3 × 1013 G) magnetic field. We discuss also the implications of the pulse-resolved spectral analysis for the emission regions on the surface of the cooling magnetar.

MEG connectivity analysis in patients with Alzheimer's disease using cross mutual information and spectral coherence.

PubMed

Alonso, Joan Francesc; Poza, Jesús; Mañanas, Miguel Angel; Romero, Sergio; Fernández, Alberto; Hornero, Roberto

2011-01-01

Alzheimer's disease (AD) is an irreversible brain disorder which represents the most common form of dementia in western countries. An early and accurate diagnosis of AD would enable to develop new strategies for managing the disease; however, nowadays there is no single test that can accurately predict the development of AD. In this sense, only a few studies have focused on the magnetoencephalographic (MEG) AD connectivity patterns. This study compares brain connectivity in terms of linear and nonlinear couplings by means of spectral coherence and cross mutual information function (CMIF), respectively. The variables defined from these functions provide statistically significant differences (p < 0.05) between AD patients and control subjects, especially the variables obtained from CMIF. The results suggest that AD is characterized by both decreases and increases of functional couplings in different frequency bands as well as by an increase in regularity, that is, more evident statistical deterministic relationships in AD patients' MEG connectivity. The significant differences obtained indicate that AD could disturb brain interactions causing abnormal brain connectivity and operation. Furthermore, the combination of coherence and CMIF features to perform a diagnostic test based on logistic regression improved the tests based on individual variables for its robustness.

Semi-classical analysis and pseudo-spectra

NASA Astrophysics Data System (ADS)

Davies, E. B.

We prove an approximate spectral theorem for non-self-adjoint operators and investigate its applications to second-order differential operators in the semi-classical limit. This leads to the construction of a twisted FBI transform. We also investigate the connections between pseudo-spectra and boundary conditions in the semi-classical limit.

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

Massaro, F.; D’Abrusco, R.

Using data from the Wide-field Infrared Survey Explorer ( WISE ) all-sky survey, we discovered that the nonthermal infrared (IR) emission of blazars, the largest known population of extragalactic γ -ray sources, has peculiar spectral properties. In this work, we confirm and strengthen our previous analyses using the latest available releases of both the WISE and the Fermi source catalogs. We also show that there is a tight correlation between the mid-IR colors and the γ -ray spectral index of Fermi blazars. We name this correlation the infrared– γ -ray connection. We discuss how this connection links both the emittedmore » powers and the spectral shapes of particles accelerated in jets arising from blazars over 10 decades in energy. Based on this evidence, we argue that the infrared– γ -ray connection is stronger than the well-known radio– γ -ray connection.« less

Simultaneous fits in ISIS on the example of GRO J1008-57

NASA Astrophysics Data System (ADS)

Kühnel, Matthias; Müller, Sebastian; Kreykenbohm, Ingo; Schwarm, Fritz-Walter; Grossberger, Christoph; Dauser, Thomas; Pottschmidt, Katja; Ferrigno, Carlo; Rothschild, Richard E.; Klochkov, Dmitry; Staubert, Rüdiger; Wilms, Joern

2015-04-01

Parallel computing and steadily increasing computation speed have led to a new tool for analyzing multiple datasets and datatypes: fitting several datasets simultaneously. With this technique, physically connected parameters of individual data can be treated as a single parameter by implementing this connection into the fit directly. We discuss the terminology, implementation, and possible issues of simultaneous fits based on the X-ray data analysis tool Interactive Spectral Interpretation System (ISIS). While all data modeling tools in X-ray astronomy allow in principle fitting data from multiple data sets individually, the syntax used in these tools is not often well suited for this task. Applying simultaneous fits to the transient X-ray binary GRO J1008-57, we find that the spectral shape is only dependent on X-ray flux. We determine time independent parameters such as, e.g., the folding energy E_fold, with unprecedented precision.

The EEG Split Alpha Peak: Phenomenological Origins and Methodological Aspects of Detection and Evaluation.

PubMed

Olejarczyk, Elzbieta; Bogucki, Piotr; Sobieszek, Aleksander

2017-01-01

Electroencephalographic (EEG) patterns were analyzed in a group of ambulatory patients who ranged in age and sex using spectral analysis as well as Directed Transfer Function, a method used to evaluate functional brain connectivity. We tested the impact of window size and choice of reference electrode on the identification of two or more peaks with close frequencies in the spectral power distribution, so called "split alpha." Together with the connectivity analysis, examination of spatiotemporal maps showing the distribution of amplitudes of EEG patterns allowed for better explanation of the mechanisms underlying the generation of split alpha peaks. It was demonstrated that the split alpha spectrum can be generated by two or more independent and interconnected alpha wave generators located in different regions of the cerebral cortex, but not necessarily in the occipital cortex. We also demonstrated the importance of appropriate reference electrode choice during signal recording. In addition, results obtained using the original data were compared with results obtained using re-referenced data, using average reference electrode and reference electrode standardization techniques.

Altered effective connectivity within default mode network in major depression disorder

NASA Astrophysics Data System (ADS)

Li, Liang; Li, Baojuan; Bai, Yuanhan; Wang, Huaning; Zhang, Linchuan; Cui, Longbiao; Lu, Hongbing

2016-03-01

Understanding the neural basis of Major Depressive Disorder (MDD) is important for the diagnosis and treatment of this mental disorder. The default mode network (DMN) is considered to be highly involved in the MDD. To find directed interaction between DMN regions associated with the development of MDD, the effective connectivity within the DMN of the MDD patients and matched healthy controls was estimated by using a recently developed spectral dynamic causal modeling. Sixteen patients with MDD and sixteen matched healthy control subjects were included in this study. While the control group underwent the resting state fMRI scan just once, all patients underwent resting state fMRI scans before and after two months' treatment. The spectral dynamic causal modeling was used to estimate directed connections between four DMN nodes. Statistical analysis on connection strengths indicated that efferent connections from the medial frontal cortex (MFC) to posterior cingulate cortex (PCC) and to right parietal cortex (RPC) were significant higher in pretreatment MDD patients than those of the control group. After two-month treatment, the efferent connections from the MFC decreased significantly, while those from the left parietal cortex (LPC) to MFC, PCC and RPC showed a significant increase. These findings suggest that the MFC may play an important role for inhibitory conditioning of the DMN, which was disrupted in MDD patients. It also indicates that disrupted suppressive function of the MFC could be effectively restored after two-month treatment.

BLAZAR SPECTRAL PROPERTIES AT 74 MHz

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

Massaro, F.; Funk, S.; Giroletti, M.

2013-10-01

Blazars are the most extreme class of active galactic nuclei. Despite a previous investigation at 102 MHz for a small sample of BL Lac objects and our recent analysis of blazars detected in the Westerbork Northern Sky Survey, a systematic study of the blazar spectral properties at frequencies below 100 MHz has been never carried out. In this paper, we present the first analysis of the radio spectral behavior of blazars based on the recent Very Large Array Low-frequency Sky Survey (VLSS) at 74 MHz. We search for blazar counterparts in the VLSS catalog, confirming that they are detected atmore » 74 MHz. We then show that blazars present radio-flat spectra (i.e., radio spectral indices of ∼0.5) when evaluated, which also about an order of magnitude in frequency lower than previous analyses. Finally, we discuss the implications of our findings in the context of the blazars-radio galaxies connection since the low-frequency radio data provide a new diagnostic tool to verify the expectations of the unification scenario for radio-loud active galaxies.« less

Knowledge Discovery in Spectral Data by Means of Complex Networks

PubMed Central

Zanin, Massimiliano; Papo, David; Solís, José Luis González; Espinosa, Juan Carlos Martínez; Frausto-Reyes, Claudio; Anda, Pascual Palomares; Sevilla-Escoboza, Ricardo; Boccaletti, Stefano; Menasalvas, Ernestina; Sousa, Pedro

2013-01-01

In the last decade, complex networks have widely been applied to the study of many natural and man-made systems, and to the extraction of meaningful information from the interaction structures created by genes and proteins. Nevertheless, less attention has been devoted to metabonomics, due to the lack of a natural network representation of spectral data. Here we define a technique for reconstructing networks from spectral data sets, where nodes represent spectral bins, and pairs of them are connected when their intensities follow a pattern associated with a disease. The structural analysis of the resulting network can then be used to feed standard data-mining algorithms, for instance for the classification of new (unlabeled) subjects. Furthermore, we show how the structure of the network is resilient to the presence of external additive noise, and how it can be used to extract relevant knowledge about the development of the disease. PMID:24957895

Knowledge discovery in spectral data by means of complex networks.

PubMed

Zanin, Massimiliano; Papo, David; Solís, José Luis González; Espinosa, Juan Carlos Martínez; Frausto-Reyes, Claudio; Anda, Pascual Palomares; Sevilla-Escoboza, Ricardo; Jaimes-Reategui, Rider; Boccaletti, Stefano; Menasalvas, Ernestina; Sousa, Pedro

2013-03-11

In the last decade, complex networks have widely been applied to the study of many natural and man-made systems, and to the extraction of meaningful information from the interaction structures created by genes and proteins. Nevertheless, less attention has been devoted to metabonomics, due to the lack of a natural network representation of spectral data. Here we define a technique for reconstructing networks from spectral data sets, where nodes represent spectral bins, and pairs of them are connected when their intensities follow a pattern associated with a disease. The structural analysis of the resulting network can then be used to feed standard data-mining algorithms, for instance for the classification of new (unlabeled) subjects. Furthermore, we show how the structure of the network is resilient to the presence of external additive noise, and how it can be used to extract relevant knowledge about the development of the disease.

Simulation and analysis of Au-MgF2 structure in plasmonic sensor in near infrared spectral region

NASA Astrophysics Data System (ADS)

Sharma, Anuj K.

2018-05-01

Plasmonic sensor based on metal-dielectric combination of gold and MgF2 layers is studied in near infrared (NIR) spectral region. An emphasis is given on the effect of variable thickness of MgF2 layer in combination with operating wavelength and gold layer thickness on the sensor's performance in NIR. It is established that the variation in MgF2 thickness in connection with plasmon penetration depth leads to significant variation in sensor's performance. The analysis leads to a conclusion that taking smaller values of MgF2 layer thickness and operating at longer NIR wavelength leads to enhanced sensing performance. Also, fluoride glass can provide better sensing performance than chalcogenide glass and silicon substrate.

Correlating non-linear properties with spectral states of RXTE data: possible observational evidences for four different accretion modes around compact objects

NASA Astrophysics Data System (ADS)

Adegoke, Oluwashina; Dhang, Prasun; Mukhopadhyay, Banibrata; Ramadevi, M. C.; Bhattacharya, Debbijoy

2018-05-01

By analysing the time series of RXTE/PCA data, the non-linear variabilities of compact sources have been repeatedly established. Depending on the variation in temporal classes, compact sources exhibit different non-linear features. Sometimes they show low correlation/fractal dimension, but in other classes or intervals of time they exhibit stochastic nature. This could be because the accretion flow around a compact object is a non-linear general relativistic system involving magnetohydrodynamics. However, the more conventional way of addressing a compact source is the analysis of its spectral state. Therefore, the question arises: What is the connection of non-linearity to the underlying spectral properties of the flow when the non-linear properties are related to the associated transport mechanisms describing the geometry of the flow? This work is aimed at addressing this question. Based on the connection between observed spectral and non-linear (time series) properties of two X-ray binaries: GRS 1915+105 and Sco X-1, we attempt to diagnose the underlying accretion modes of the sources in terms of known accretion classes, namely, Keplerian disc, slim disc, advection dominated accretion flow and general advective accretion flow. We explore the possible transition of the sources from one accretion mode to others with time. We further argue that the accretion rate must play an important role in transition between these modes.

Spectral luminescence analysis of amniotic fluid

NASA Astrophysics Data System (ADS)

Slobozhanina, Ekaterina I.; Kozlova, Nataly M.; Kasko, Leonid P.; Mamontova, Marina V.; Chernitsky, Eugene A.

1997-12-01

It is shown that the amniotic fluid has intensive ultra-violet luminescence caused by proteins. Along with it amniotic fluid radiated in the field of 380 - 650 nm with maxima at 430 - 450 nm and 520 - 560 nm. The first peak of luminescence ((lambda) exc equals 350 nm; (lambda) em equals 430 - 440 nm) is caused (most probably) by the presence in amniotic fluid of some hormones, NADH2 and NADPH2. A more long-wave component ((lambda) exc equals 460 nm; (lambda) em equals 520 - 560 nm) is most likely connected with the presence in amniotic fluid pigments (bilirubin connected with protein and other). It is shown that intensity and maximum of ultra-violet luminescence spectra of amniotic fluid in normality and at pathology are identical. However both emission spectra and excitation spectra of long-wave ((lambda) greater than 450 nm) luminescence of amniotic fluid from pregnant women with such prenatal abnormal developments of a fetus as anencephaly and spina bifida are too long-wave region in comparison with the norm. Results of research testify that spectral luminescent analysis of amniotic fluid can be used for screening of malformations of the neural tube. It is very difficult for a practical obstetrician to reveal pregnant women with a high risk of congenital malformations of the fetus. Apart from ultrasonic examination, cytogenetic examination of amniotic fluid and defumination of concentrations of alpha-fetoprotein and acetylcholin-esterases in the amniotic fluid and blood plasma are the most widely used diagnostic approaches. However, biochemical and cytogenetic diagnostic methods are time-consuming. In the present work spectral luminescence properties of the amniotic fluid are investigated to determine spectral parameters that can be used to reveal pregnant women with a high risk of congenital malformations of their offsprings.

Hyperspectral imaging coupled with chemometric analysis for non-invasive differentiation of black pens

NASA Astrophysics Data System (ADS)

Chlebda, Damian K.; Majda, Alicja; Łojewski, Tomasz; Łojewska, Joanna

2016-11-01

Differentiation of the written text can be performed with a non-invasive and non-contact tool that connects conventional imaging methods with spectroscopy. Hyperspectral imaging (HSI) is a relatively new and rapid analytical technique that can be applied in forensic science disciplines. It allows an image of the sample to be acquired, with full spectral information within every pixel. For this paper, HSI and three statistical methods (hierarchical cluster analysis, principal component analysis, and spectral angle mapper) were used to distinguish between traces of modern black gel pen inks. Non-invasiveness and high efficiency are among the unquestionable advantages of ink differentiation using HSI. It is also less time-consuming than traditional methods such as chromatography. In this study, a set of 45 modern gel pen ink marks deposited on a paper sheet were registered. The spectral characteristics embodied in every pixel were extracted from an image and analysed using statistical methods, externally and directly on the hypercube. As a result, different black gel inks deposited on paper can be distinguished and classified into several groups, in a non-invasive manner.

Extending Stability Through Hierarchical Clusters in Echo State Networks

PubMed Central

Jarvis, Sarah; Rotter, Stefan; Egert, Ulrich

2009-01-01

Echo State Networks (ESN) are reservoir networks that satisfy well-established criteria for stability when constructed as feedforward networks. Recent evidence suggests that stability criteria are altered in the presence of reservoir substructures, such as clusters. Understanding how the reservoir architecture affects stability is thus important for the appropriate design of any ESN. To quantitatively determine the influence of the most relevant network parameters, we analyzed the impact of reservoir substructures on stability in hierarchically clustered ESNs, as they allow a smooth transition from highly structured to increasingly homogeneous reservoirs. Previous studies used the largest eigenvalue of the reservoir connectivity matrix (spectral radius) as a predictor for stable network dynamics. Here, we evaluate the impact of clusters, hierarchy and intercluster connectivity on the predictive power of the spectral radius for stability. Both hierarchy and low relative cluster sizes extend the range of spectral radius values, leading to stable networks, while increasing intercluster connectivity decreased maximal spectral radius. PMID:20725523

Upwelled spectral radiance distribution in relation to particulate matter in sea water

NASA Technical Reports Server (NTRS)

Clark, D. K.; Strong, A. E.; Baker, E. T.

1980-01-01

Spectral analysis of water color and concurrent measurements of the relative concentration of various particulate and dissolved constituents within a broad range of water types are necessary to quantify ocean color observations and successfully relate them to various biological and physical processes that can be monitored by remote sensing. Some of the results of a Nimbus-G prelaunch cruise in connection with the Coastal Zone Color Scanner (CZCS) experiment, which was carried out in the Gulf of Mexico in October 1977, are presented and discussed. Based upon a small but diverse sample of near-surface measurements, it appears possible to estimate total suspended particulate matter (SPM) to useful accuracies by forming ratios of the spectral radiances measured at wavelengths falling near the centers of certain CZCS bands, viz., 440 nm:550 nm and 440 nm:520 nm. Furthermore, the analysis suggests a very high degree of covariation between SPM and phytoplankton pigments except for certain well-defined special cases.

In situ SERS spectroelectrochemical analysis of antioxidants deposited on copper substrates: What is the effect of applied potential on sorption behavior?

NASA Astrophysics Data System (ADS)

Dendisova-Vyskovska, Marcela; Broncova, Gabriela; Clupek, Martin; Prokopec, Vadym; Matejka, Pavel

2012-12-01

The detection of p-coumaric acid and ferulic acid using a combined in situ electrochemical and surface-enhanced Raman scattering spectroscopic technique in specially made electrode cell is described. New in situ spectroelectrochemical cell was designed as the three-electrode arrangement connected via positioning device to fiber-optic probe of Raman spectrometer Dimension P2 (excitation wavelength 785 nm). In situ SERS spectra of p-coumaric acid and ferulic acid were recorded at varying applied negative potentials to copper substrates. The spectral intensities and shapes of bands as well as spatial orientation of molecules on the surface depend significantly on varying values of the applied electrode potential. The change of electrode potential influences analyte adsorption/desorption behavior on the surface of copper substrates, affecting the reversibility of the whole process and overall spectral enhancement level. Principal component analysis is used to distinguish several stages of spectral variations on potential changes.

Neurophysiological differences between patients clinically at high risk for schizophrenia and neurotypical controls--first steps in development of a biomarker.

PubMed

Duffy, Frank H; D'Angelo, Eugene; Rotenberg, Alexander; Gonzalez-Heydrich, Joseph

2015-11-02

Schizophrenia is a severe, disabling and prevalent mental disorder without cure and with a variable, incomplete pharmacotherapeutic response. Prior to onset in adolescence or young adulthood a prodromal period of abnormal symptoms lasting weeks to years has been identified and operationalized as clinically high risk (CHR) for schizophrenia. However, only a minority of subjects prospectively identified with CHR convert to schizophrenia, thereby limiting enthusiasm for early intervention(s). This study utilized objective resting electroencephalogram (EEG) quantification to determine whether CHR constitutes a cohesive entity and an evoked potential to assess CHR cortical auditory processing. This study constitutes an EEG-based quantitative neurophysiological comparison between two unmedicated subject groups: 35 neurotypical controls (CON) and 22 CHR patients. After artifact management, principal component analysis (PCA) identified EEG spectral and spectral coherence factors described by associated loading patterns. Discriminant function analysis (DFA) determined factors' discrimination success between subjects in the CON and CHR groups. Loading patterns on DFA-selected factors described CHR-specific spectral and coherence differences when compared to controls. The frequency modulated auditory evoked response (FMAER) explored functional CON-CHR differences within the superior temporal gyri. Variable reduction by PCA identified 40 coherence-based factors explaining 77.8% of the total variance and 40 spectral factors explaining 95.9% of the variance. DFA demonstrated significant CON-CHR group difference (P <0.00001) and successful jackknifed subject classification (CON, 85.7%; CHR, 86.4% correct). The population distribution plotted along the canonical discriminant variable was clearly bimodal. Coherence factors delineated loading patterns of altered connectivity primarily involving the bilateral posterior temporal electrodes. However, FMAER analysis showed no CON-CHR group differences. CHR subjects form a cohesive group, significantly separable from CON subjects by EEG-derived indices. Symptoms of CHR may relate to altered connectivity with the posterior temporal regions but not to primary auditory processing abnormalities within these regions.

Raman spectroscopy of normal oral buccal mucosa tissues: study on intact and incised biopsies

NASA Astrophysics Data System (ADS)

Deshmukh, Atul; Singh, S. P.; Chaturvedi, Pankaj; Krishna, C. Murali

2011-12-01

Oral squamous cell carcinoma is one of among the top 10 malignancies. Optical spectroscopy, including Raman, is being actively pursued as alternative/adjunct for cancer diagnosis. Earlier studies have demonstrated the feasibility of classifying normal, premalignant, and malignant oral ex vivo tissues. Spectral features showed predominance of lipids and proteins in normal and cancer conditions, respectively, which were attributed to membrane lipids and surface proteins. In view of recent developments in deep tissue Raman spectroscopy, we have recorded Raman spectra from superior and inferior surfaces of 10 normal oral tissues on intact, as well as incised, biopsies after separation of epithelium from connective tissue. Spectral variations and similarities among different groups were explored by unsupervised (principal component analysis) and supervised (linear discriminant analysis, factorial discriminant analysis) methodologies. Clusters of spectra from superior and inferior surfaces of intact tissues show a high overlap; whereas spectra from separated epithelium and connective tissue sections yielded clear clusters, though they also overlap on clusters of intact tissues. Spectra of all four groups of normal tissues gave exclusive clusters when tested against malignant spectra. Thus, this study demonstrates that spectra recorded from the superior surface of an intact tissue may have contributions from deeper layers but has no bearing from the classification of a malignant tissues point of view.

Large-scale DCMs for resting-state fMRI.

PubMed

Razi, Adeel; Seghier, Mohamed L; Zhou, Yuan; McColgan, Peter; Zeidman, Peter; Park, Hae-Jeong; Sporns, Olaf; Rees, Geraint; Friston, Karl J

2017-01-01

This paper considers the identification of large directed graphs for resting-state brain networks based on biophysical models of distributed neuronal activity, that is, effective connectivity . This identification can be contrasted with functional connectivity methods based on symmetric correlations that are ubiquitous in resting-state functional MRI (fMRI). We use spectral dynamic causal modeling (DCM) to invert large graphs comprising dozens of nodes or regions. The ensuing graphs are directed and weighted, hence providing a neurobiologically plausible characterization of connectivity in terms of excitatory and inhibitory coupling. Furthermore, we show that the use of to discover the most likely sparse graph (or model) from a parent (e.g., fully connected) graph eschews the arbitrary thresholding often applied to large symmetric (functional connectivity) graphs. Using empirical fMRI data, we show that spectral DCM furnishes connectivity estimates on large graphs that correlate strongly with the estimates provided by stochastic DCM. Furthermore, we increase the efficiency of model inversion using functional connectivity modes to place prior constraints on effective connectivity. In other words, we use a small number of modes to finesse the potentially redundant parameterization of large DCMs. We show that spectral DCM-with functional connectivity priors-is ideally suited for directed graph theoretic analyses of resting-state fMRI. We envision that directed graphs will prove useful in understanding the psychopathology and pathophysiology of neurodegenerative and neurodevelopmental disorders. We will demonstrate the utility of large directed graphs in clinical populations in subsequent reports, using the procedures described in this paper.

NuSTAR Observations of Water Megamaser AGN

NASA Technical Reports Server (NTRS)

Masini, A.; Comastri, A.; Balokvic, M.; Zaw, I.; Puccetti, S.; Ballantyne, D. R.; Bauer, F. E.; Boggs, S. E.; Brandt, W. N.; Zhang, William W.

2016-01-01

Aims. We study the connection between the masing disk and obscuring torus in Seyfert 2 galaxies. Methods. We present a uniform X-ray spectral analysis of the high energy properties of 14 nearby megamaser active galactic nuclei observed by NuSTAR. We use a simple analytical model to localize the maser disk and understand its connection with the torus by combining NuSTAR spectral parameters with the available physical quantities from VLBI mapping.Results. Most of the sources that we analyzed are heavily obscured, showing a column density in excess of approx.10(exp 23) cm(exp -2); in particular, 79% are Compton-thick [NH is greater than 1.5 x 10(exp 24) cm(exp -2)]. When using column densities measured by NuSTAR with the assumption that the torus is the extension of the maser disk, and further assuming a reasonable density profile, we can predict the torus dimensions. They are found to be consistent with mid-IR interferometry parsec-scale observations of Circinus and NGC 1068. In this picture, the maser disk is intimately connected to the inner part of the torus. It is probably made of a large number of molecular clouds that connect the torus and the outer part of the accretion disk, giving rise to a thin disk rotating in most cases in Keplerian or sub-Keplerian motion. This toy model explains the established close connection between water megamaser emission and nuclear obscuration as a geometric effect.

SCPS: a fast implementation of a spectral method for detecting protein families on a genome-wide scale.

PubMed

Nepusz, Tamás; Sasidharan, Rajkumar; Paccanaro, Alberto

2010-03-09

An important problem in genomics is the automatic inference of groups of homologous proteins from pairwise sequence similarities. Several approaches have been proposed for this task which are "local" in the sense that they assign a protein to a cluster based only on the distances between that protein and the other proteins in the set. It was shown recently that global methods such as spectral clustering have better performance on a wide variety of datasets. However, currently available implementations of spectral clustering methods mostly consist of a few loosely coupled Matlab scripts that assume a fair amount of familiarity with Matlab programming and hence they are inaccessible for large parts of the research community. SCPS (Spectral Clustering of Protein Sequences) is an efficient and user-friendly implementation of a spectral method for inferring protein families. The method uses only pairwise sequence similarities, and is therefore practical when only sequence information is available. SCPS was tested on difficult sets of proteins whose relationships were extracted from the SCOP database, and its results were extensively compared with those obtained using other popular protein clustering algorithms such as TribeMCL, hierarchical clustering and connected component analysis. We show that SCPS is able to identify many of the family/superfamily relationships correctly and that the quality of the obtained clusters as indicated by their F-scores is consistently better than all the other methods we compared it with. We also demonstrate the scalability of SCPS by clustering the entire SCOP database (14,183 sequences) and the complete genome of the yeast Saccharomyces cerevisiae (6,690 sequences). Besides the spectral method, SCPS also implements connected component analysis and hierarchical clustering, it integrates TribeMCL, it provides different cluster quality tools, it can extract human-readable protein descriptions using GI numbers from NCBI, it interfaces with external tools such as BLAST and Cytoscape, and it can produce publication-quality graphical representations of the clusters obtained, thus constituting a comprehensive and effective tool for practical research in computational biology. Source code and precompiled executables for Windows, Linux and Mac OS X are freely available at http://www.paccanarolab.org/software/scps.

Spectral Dynamics of Resting State fMRI Within the Ventral Tegmental Area and Dorsal Raphe Nuclei in Medication-Free Major Depressive Disorder in Young Adults.

PubMed

Wohlschläger, Afra; Karne, Harish; Jordan, Denis; Lowe, Mark J; Jones, Stephen E; Anand, Amit

2018-01-01

Background: Dorsal raphe nucleus (DRN) and ventral tegmental area (VTA) are major brainstem monamine nuclei consisting of serotonin and dopamine neurons respectively. Animal studies show that firing patterns in both nuclei are altered when animals exhibit depression like behaviors. Functional MRI studies in humans have shown reduced VTA activation and DRN connectivity in depression. This study for the first time aims at investigating the functional integrity of local neuronal firing concurrently in both the VTA and DRN in vivo in humans using spectral analysis of resting state low frequency fluctuation fMRI. Method: A total of 97 medication-free subjects-67 medication-free young patients (ages 18-30) with major depressive disorder and 30 closely matched healthy controls were included in the study to detect aberrant dynamics in DRN and VTA. For the investigation of altered localized dynamics we conducted power spectral analysis and above this spectral cross correlation between the two groups. Complementary to this, spectral dependence of permutation entropy, an information theoretical measure, was compared between groups. Results: Patients displayed significant spectral slowing in VTA vs. controls ( p = 0.035, corrected). In DRN, spectral slowing was less pronounced, but the amount of slowing significantly correlated with 17-item Hamilton Depression Rating scores of depression severity ( p = 0.038). Signal complexity as assessed via permutation entropy showed spectral alterations inline with the results on spectral slowing. Conclusion: Our results indicate that altered functional dynamics of VTA and DRN in depression can be detected from regional fMRI signal. On this basis, impact of antidepressant treatment and treatment response can be assessed using these markers in future studies.

Null boundary controllability of a one-dimensional heat equation with an internal point mass and variable coefficients

NASA Astrophysics Data System (ADS)

Ben Amara, Jamel; Bouzidi, Hedi

2018-01-01

In this paper, we consider a linear hybrid system which is composed by two non-homogeneous rods connected by a point mass with Dirichlet boundary conditions on the left end and a boundary control acts on the right end. We prove that this system is null controllable with Dirichlet or Neumann boundary controls. Our approach is mainly based on a detailed spectral analysis together with the moment method. In particular, we show that the associated spectral gap in both cases (Dirichlet or Neumann boundary controls) is positive without further conditions on the coefficients other than the regularities.

Connes distance function on fuzzy sphere and the connection between geometry and statistics

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

Devi, Yendrembam Chaoba, E-mail: chaoba@bose.res.in; Chakraborty, Biswajit, E-mail: biswajit@bose.res.in; Prajapat, Shivraj, E-mail: shraprajapat@gmail.com

An algorithm to compute Connes spectral distance, adaptable to the Hilbert-Schmidt operatorial formulation of non-commutative quantum mechanics, was developed earlier by introducing the appropriate spectral triple and used to compute infinitesimal distances in the Moyal plane, revealing a deep connection between geometry and statistics. In this paper, using the same algorithm, the Connes spectral distance has been calculated in the Hilbert-Schmidt operatorial formulation for the fuzzy sphere whose spatial coordinates satisfy the su(2) algebra. This has been computed for both the discrete and the Perelemov’s SU(2) coherent state. Here also, we get a connection between geometry and statistics which ismore » shown by computing the infinitesimal distance between mixed states on the quantum Hilbert space of a particular fuzzy sphere, indexed by n ∈ ℤ/2.« less

The effect of normalization of Partial Directed Coherence on the statistical assessment of connectivity patterns: a simulation study.

PubMed

Toppi, J; Petti, M; Vecchiato, G; Cincotti, F; Salinari, S; Mattia, D; Babiloni, F; Astolfi, L

2013-01-01

Partial Directed Coherence (PDC) is a spectral multivariate estimator for effective connectivity, relying on the concept of Granger causality. Even if its original definition derived directly from information theory, two modifies were introduced in order to provide better physiological interpretations of the estimated networks: i) normalization of the estimator according to rows, ii) squared transformation. In the present paper we investigated the effect of PDC normalization on the performances achieved by applying the statistical validation process on investigated connectivity patterns under different conditions of Signal to Noise ratio (SNR) and amount of data available for the analysis. Results of the statistical analysis revealed an effect of PDC normalization only on the percentages of type I and type II errors occurred by using Shuffling procedure for the assessment of connectivity patterns. No effects of the PDC formulation resulted on the performances achieved during the validation process executed instead by means of Asymptotic Statistic approach. Moreover, the percentages of both false positives and false negatives committed by Asymptotic Statistic are always lower than those achieved by Shuffling procedure for each type of normalization.

Low-frequency connectivity is associated with mild traumatic brain injury.

PubMed

Dunkley, B T; Da Costa, L; Bethune, A; Jetly, R; Pang, E W; Taylor, M J; Doesburg, S M

2015-01-01

Mild traumatic brain injury (mTBI) occurs from a closed-head impact. Often referred to as concussion, about 20% of cases complain of secondary psychological sequelae, such as disorders of attention and memory. Known as post-concussive symptoms (PCS), these problems can severely disrupt the patient's quality of life. Changes in local spectral power, particularly low-frequency amplitude increases and/or peak alpha slowing have been reported in mTBI, but large-scale connectivity metrics based on inter-regional amplitude correlations relevant for integration and segregation in functional brain networks, and their association with disorders in cognition and behaviour, remain relatively unexplored. Here, we used non-invasive neuroimaging with magnetoencephalography to examine functional connectivity in a resting-state protocol in a group with mTBI (n = 20), and a control group (n = 21). We observed a trend for atypical slow-wave power changes in subcortical, temporal and parietal regions in mTBI, as well as significant long-range increases in amplitude envelope correlations among deep-source, temporal, and frontal regions in the delta, theta, and alpha bands. Subsequently, we conducted an exploratory analysis of patterns of connectivity most associated with variability in secondary symptoms of mTBI, including inattention, anxiety, and depression. Differential patterns of altered resting state neurophysiological network connectivity were found across frequency bands. This indicated that multiple network and frequency specific alterations in large scale brain connectivity may contribute to overlapping cognitive sequelae in mTBI. In conclusion, we show that local spectral power content can be supplemented with measures of correlations in amplitude to define general networks that are atypical in mTBI, and suggest that certain cognitive difficulties are mediated by disturbances in a variety of alterations in network interactions which are differentially expressed across canonical neurophysiological frequency ranges.

EEG-MEG Integration Enhances the Characterization of Functional and Effective Connectivity in the Resting State Network

PubMed Central

Mideksa, Kidist Gebremariam; Anwar, Abdul Rauf; Stephani, Ulrich; Deuschl, Günther; Freitag, Christine M.; Siniatchkin, Michael

2015-01-01

At the sensor level many aspects, such as spectral power, functional and effective connectivity as well as relative-power-ratio ratio (RPR) and spatial resolution have been comprehensively investigated through both electroencephalography (EEG) and magnetoencephalography (MEG). Despite this, differences between both modalities have not yet been systematically studied by direct comparison. It remains an open question as to whether the integration of EEG and MEG data would improve the information obtained from the above mentioned parameters. Here, EEG (64-channel system) and MEG (275 sensor system) were recorded simultaneously in conditions with eyes open (EO) and eyes closed (EC) in 29 healthy adults. Spectral power, functional and effective connectivity, RPR, and spatial resolution were analyzed at five different frequency bands (delta, theta, alpha, beta and gamma). Networks of functional and effective connectivity were described using a spatial filter approach called the dynamic imaging of coherent sources (DICS) followed by the renormalized partial directed coherence (RPDC). Absolute mean power at the sensor level was significantly higher in EEG than in MEG data in both EO and EC conditions. At the source level, there was a trend towards a better performance of the combined EEG+MEG analysis compared with separate EEG or MEG analyses for the source mean power, functional correlation, effective connectivity for both EO and EC. The network of coherent sources and the spatial resolution were similar for both the EEG and MEG data if they were analyzed separately. Results indicate that the combined approach has several advantages over the separate analyses of both EEG and MEG. Moreover, by a direct comparison of EEG and MEG, EEG was characterized by significantly higher values in all measured parameters in both sensor and source level. All the above conclusions are specific to the resting state task and the specific analysis used in this study to have general conclusion multi-center studies would be helpful. PMID:26509448

Islanding detection technique using wavelet energy in grid-connected PV system

NASA Astrophysics Data System (ADS)

Kim, Il Song

2016-08-01

This paper proposes a new islanding detection method using wavelet energy in a grid-connected photovoltaic system. The method detects spectral changes in the higher-frequency components of the point of common coupling voltage and obtains wavelet coefficients by multilevel wavelet analysis. The autocorrelation of the wavelet coefficients can clearly identify islanding detection, even in the variations of the grid voltage harmonics during normal operating conditions. The advantage of the proposed method is that it can detect islanding condition the conventional under voltage/over voltage/under frequency/over frequency methods fail to detect. The theoretical method to obtain wavelet energies is evolved and verified by the experimental result.

SCoT: a Python toolbox for EEG source connectivity.

PubMed

Billinger, Martin; Brunner, Clemens; Müller-Putz, Gernot R

2014-01-01

Analysis of brain connectivity has become an important research tool in neuroscience. Connectivity can be estimated between cortical sources reconstructed from the electroencephalogram (EEG). Such analysis often relies on trial averaging to obtain reliable results. However, some applications such as brain-computer interfaces (BCIs) require single-trial estimation methods. In this paper, we present SCoT-a source connectivity toolbox for Python. This toolbox implements routines for blind source decomposition and connectivity estimation with the MVARICA approach. Additionally, a novel extension called CSPVARICA is available for labeled data. SCoT estimates connectivity from various spectral measures relying on vector autoregressive (VAR) models. Optionally, these VAR models can be regularized to facilitate ill posed applications such as single-trial fitting. We demonstrate basic usage of SCoT on motor imagery (MI) data. Furthermore, we show simulation results of utilizing SCoT for feature extraction in a BCI application. These results indicate that CSPVARICA and correct regularization can significantly improve MI classification. While SCoT was mainly designed for application in BCIs, it contains useful tools for other areas of neuroscience. SCoT is a software package that (1) brings combined source decomposition and connectivtiy estimation to the open Python platform, and (2) offers tools for single-trial connectivity estimation. The source code is released under the MIT license and is available online at github.com/SCoT-dev/SCoT.

SCoT: a Python toolbox for EEG source connectivity

PubMed Central

Billinger, Martin; Brunner, Clemens; Müller-Putz, Gernot R.

2014-01-01

Analysis of brain connectivity has become an important research tool in neuroscience. Connectivity can be estimated between cortical sources reconstructed from the electroencephalogram (EEG). Such analysis often relies on trial averaging to obtain reliable results. However, some applications such as brain-computer interfaces (BCIs) require single-trial estimation methods. In this paper, we present SCoT—a source connectivity toolbox for Python. This toolbox implements routines for blind source decomposition and connectivity estimation with the MVARICA approach. Additionally, a novel extension called CSPVARICA is available for labeled data. SCoT estimates connectivity from various spectral measures relying on vector autoregressive (VAR) models. Optionally, these VAR models can be regularized to facilitate ill posed applications such as single-trial fitting. We demonstrate basic usage of SCoT on motor imagery (MI) data. Furthermore, we show simulation results of utilizing SCoT for feature extraction in a BCI application. These results indicate that CSPVARICA and correct regularization can significantly improve MI classification. While SCoT was mainly designed for application in BCIs, it contains useful tools for other areas of neuroscience. SCoT is a software package that (1) brings combined source decomposition and connectivtiy estimation to the open Python platform, and (2) offers tools for single-trial connectivity estimation. The source code is released under the MIT license and is available online at github.com/SCoT-dev/SCoT. PMID:24653694

Multi-mode optical fibers for connecting space-based spectrometers

NASA Astrophysics Data System (ADS)

Roberts, W. T.; Lindenmisth, C. A.; Bender, S.; Miller, E. A.; Motts, E.; Ott, M.; LaRocca, F.; Thomes, J.

2017-11-01

Laser spectral analysis systems are increasingly being considered for in situ analysis of the atomic and molecular composition of selected rock and soil samples on other planets [1][2][3]. Both Laser Induced Breakdown Spectroscopy (LIBS) and Raman spectroscopy are used to identify the constituents of soil and rock samples in situ. LIBS instruments use a high peak-power laser to ablate a minute area of the surface of a sample. The resulting plasma is observed with an optical head, which collects the emitted light for analysis by one or more spectrometers. By identifying the ion emission lines observed in the plasma, the constituent elements and their abundance can be deduced. In Raman spectroscopy, laser photons incident on the sample surface are scattered and experience a Raman shift, exchanging small amounts of energy with the molecules scattering the light. By observing the spectrum of the scattered light, it is possible to determine the molecular composition of the sample. For both types of instruments, there are advantages to physically separating the light collecting optics from the spectroscopy optics. The light collection system will often have articulating or rotating elements to facilitate the interrogation of multiple samples with minimum expenditure of energy and motion. As such, the optical head is often placed on a boom or an appendage allowing it to be pointed in different directions or easily positioned in different locations. By contrast, the spectrometry portion of the instrument is often well-served by placing it in a more static location. The detectors often operate more consistently in a thermally-controlled environment. Placing them deep within the spacecraft structure also provides some shielding from ionizing radiation, extending the instrument's useful life. Finally, the spectrometry portion of the instrument often contains significant mass, such that keeping it off of the moving portion of the platform, allowing that portion to be significantly smaller, less massive and less robust. Large core multi-mode optical fibers are often used to accommodate the optical connection of the two separated portions of such instrumentation. In some cases, significant throughput efficiency improvement can be realized by judiciously orienting the strands of multi-fiber cable, close-bunching them to accommodate a tight focus of the optical system on the optical side of the connection, and splaying them out linearly along a spectrometer slit on the other end. For such instrumentation to work effectively in identifying elements and molecules, and especially to produce accurate quantitative results, the spectral throughput of the optical fiber connection must be consistent over varying temperatures, over the range of motion of the optical head (and it's implied optical cable stresses), and over angle-aperture invariant of the total system. While the first two of these conditions have been demonstrated[4], spectral observations of the latter present a cause for concern, and may have an impact on future design of fiber-connected LIBS and Raman spectroscopy instruments. In short, we have observed that the shape of the spectral efficiency curve of a large multi-mode core optical fiber changes as a function of input angle.

The CLAIR model: Extension of Brodmann areas based on brain oscillations and connectivity.

PubMed

Başar, Erol; Düzgün, Aysel

2016-05-01

Since the beginning of the last century, the localization of brain function has been represented by Brodmann areas, maps of the anatomic organization of the brain. They are used to broadly represent cortical structures with their given sensory-cognitive functions. In recent decades, the analysis of brain oscillations has become important in the correlation of brain functions. Moreover, spectral connectivity can provide further information on the dynamic connectivity between various structures. In addition, brain responses are dynamic in nature and structural localization is almost impossible, according to Luria (1966). Therefore, brain functions are very difficult to localize; hence, a combined analysis of oscillation and event-related coherences is required. In this study, a model termed as "CLAIR" is described to enrich and possibly replace the concept of the Brodmann areas. A CLAIR model with optimum function may take several years to develop, but this study sets out to lay its foundation. Copyright © 2016 The Authors. Published by Elsevier B.V. All rights reserved.

Human brain networks in physiological aging: a graph theoretical analysis of cortical connectivity from EEG data.

PubMed

Vecchio, Fabrizio; Miraglia, Francesca; Bramanti, Placido; Rossini, Paolo Maria

2014-01-01

Modern analysis of electroencephalographic (EEG) rhythms provides information on dynamic brain connectivity. To test the hypothesis that aging processes modulate the brain connectivity network, EEG recording was conducted on 113 healthy volunteers. They were divided into three groups in accordance with their ages: 36 Young (15-45 years), 46 Adult (50-70 years), and 31 Elderly (>70 years). To evaluate the stability of the investigated parameters, a subgroup of 10 subjects underwent a second EEG recording two weeks later. Graph theory functions were applied to the undirected and weighted networks obtained by the lagged linear coherence evaluated by eLORETA on cortical sources. EEG frequency bands of interest were: delta (2-4 Hz), theta (4-8 Hz), alpha1 (8-10.5 Hz), alpha2 (10.5-13 Hz), beta1 (13-20 Hz), beta2 (20-30 Hz), and gamma (30-40 Hz). The spectral connectivity analysis of cortical sources showed that the normalized Characteristic Path Length (λ) presented the pattern Young > Adult>Elderly in the higher alpha band. Elderly also showed a greater increase in delta and theta bands than Young. The correlation between age and λ showed that higher ages corresponded to higher λ in delta and theta and lower in the alpha2 band; this pattern reflects the age-related modulation of higher (alpha) and decreased (delta) connectivity. The Normalized Clustering coefficient (γ) and small-world network modeling (σ) showed non-significant age-modulation. Evidence from the present study suggests that graph theory can aid in the analysis of connectivity patterns estimated from EEG and can facilitate the study of the physiological and pathological brain aging features of functional connectivity networks.

The functional organization of human epileptic hippocampus

PubMed Central

Klimes, Petr; Duque, Juliano J.; Brinkmann, Ben; Van Gompel, Jamie; Stead, Matt; St. Louis, Erik K.; Halamek, Josef; Jurak, Pavel

2016-01-01

The function and connectivity of human brain is disrupted in epilepsy. We previously reported that the region of epileptic brain generating focal seizures, i.e., the seizure onset zone (SOZ), is functionally isolated from surrounding brain regions in focal neocortical epilepsy. The modulatory effect of behavioral state on the spatial and spectral scales over which the reduced functional connectivity occurs, however, is unclear. Here we use simultaneous sleep staging from scalp EEG with intracranial EEG recordings from medial temporal lobe to investigate how behavioral state modulates the spatial and spectral scales of local field potential synchrony in focal epileptic hippocampus. The local field spectral power and linear correlation between adjacent electrodes provide measures of neuronal population synchrony at different spatial scales, ∼1 and 10 mm, respectively. Our results show increased connectivity inside the SOZ and low connectivity between electrodes in SOZ and outside the SOZ. During slow-wave sleep, we observed decreased connectivity for ripple and fast ripple frequency bands within the SOZ at the 10 mm spatial scale, while the local synchrony remained high at the 1 mm spatial scale. Further study of these phenomena may prove useful for SOZ localization and help understand seizure generation, and the functional deficits seen in epileptic eloquent cortex. PMID:27030735

Spectral integration in primary auditory cortex attributable to temporally precise convergence of thalamocortical and intracortical input.

PubMed

Happel, Max F K; Jeschke, Marcus; Ohl, Frank W

2010-08-18

Primary sensory cortex integrates sensory information from afferent feedforward thalamocortical projection systems and convergent intracortical microcircuits. Both input systems have been demonstrated to provide different aspects of sensory information. Here we have used high-density recordings of laminar current source density (CSD) distributions in primary auditory cortex of Mongolian gerbils in combination with pharmacological silencing of cortical activity and analysis of the residual CSD, to dissociate the feedforward thalamocortical contribution and the intracortical contribution to spectral integration. We found a temporally highly precise integration of both types of inputs when the stimulation frequency was in close spectral neighborhood of the best frequency of the measurement site, in which the overlap between both inputs is maximal. Local intracortical connections provide both directly feedforward excitatory and modulatory input from adjacent cortical sites, which determine how concurrent afferent inputs are integrated. Through separate excitatory horizontal projections, terminating in cortical layers II/III, information about stimulus energy in greater spectral distance is provided even over long cortical distances. These projections effectively broaden spectral tuning width. Based on these data, we suggest a mechanism of spectral integration in primary auditory cortex that is based on temporally precise interactions of afferent thalamocortical inputs and different short- and long-range intracortical networks. The proposed conceptual framework allows integration of different and partly controversial anatomical and physiological models of spectral integration in the literature.

A Baseline for the Multivariate Comparison of Resting-State Networks

PubMed Central

Allen, Elena A.; Erhardt, Erik B.; Damaraju, Eswar; Gruner, William; Segall, Judith M.; Silva, Rogers F.; Havlicek, Martin; Rachakonda, Srinivas; Fries, Jill; Kalyanam, Ravi; Michael, Andrew M.; Caprihan, Arvind; Turner, Jessica A.; Eichele, Tom; Adelsheim, Steven; Bryan, Angela D.; Bustillo, Juan; Clark, Vincent P.; Feldstein Ewing, Sarah W.; Filbey, Francesca; Ford, Corey C.; Hutchison, Kent; Jung, Rex E.; Kiehl, Kent A.; Kodituwakku, Piyadasa; Komesu, Yuko M.; Mayer, Andrew R.; Pearlson, Godfrey D.; Phillips, John P.; Sadek, Joseph R.; Stevens, Michael; Teuscher, Ursina; Thoma, Robert J.; Calhoun, Vince D.

2011-01-01

As the size of functional and structural MRI datasets expands, it becomes increasingly important to establish a baseline from which diagnostic relevance may be determined, a processing strategy that efficiently prepares data for analysis, and a statistical approach that identifies important effects in a manner that is both robust and reproducible. In this paper, we introduce a multivariate analytic approach that optimizes sensitivity and reduces unnecessary testing. We demonstrate the utility of this mega-analytic approach by identifying the effects of age and gender on the resting-state networks (RSNs) of 603 healthy adolescents and adults (mean age: 23.4 years, range: 12–71 years). Data were collected on the same scanner, preprocessed using an automated analysis pipeline based in SPM, and studied using group independent component analysis. RSNs were identified and evaluated in terms of three primary outcome measures: time course spectral power, spatial map intensity, and functional network connectivity. Results revealed robust effects of age on all three outcome measures, largely indicating decreases in network coherence and connectivity with increasing age. Gender effects were of smaller magnitude but suggested stronger intra-network connectivity in females and more inter-network connectivity in males, particularly with regard to sensorimotor networks. These findings, along with the analysis approach and statistical framework described here, provide a useful baseline for future investigations of brain networks in health and disease. PMID:21442040

Anterior cingulate cortex-related connectivity in first-episode schizophrenia: a spectral dynamic causal modeling study with functional magnetic resonance imaging

PubMed Central

Cui, Long-Biao; Liu, Jian; Wang, Liu-Xian; Li, Chen; Xi, Yi-Bin; Guo, Fan; Wang, Hua-Ning; Zhang, Lin-Chuan; Liu, Wen-Ming; He, Hong; Tian, Ping; Yin, Hong; Lu, Hongbing

2015-01-01

Understanding the neural basis of schizophrenia (SZ) is important for shedding light on the neurobiological mechanisms underlying this mental disorder. Structural and functional alterations in the anterior cingulate cortex (ACC), dorsolateral prefrontal cortex (DLPFC), hippocampus, and medial prefrontal cortex (MPFC) have been implicated in the neurobiology of SZ. However, the effective connectivity among them in SZ remains unclear. The current study investigated how neuronal pathways involving these regions were affected in first-episode SZ using functional magnetic resonance imaging (fMRI). Forty-nine patients with a first-episode of psychosis and diagnosis of SZ—according to the Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition, Text Revision—were studied. Fifty healthy controls (HCs) were included for comparison. All subjects underwent resting state fMRI. We used spectral dynamic causal modeling (DCM) to estimate directed connections among the bilateral ACC, DLPFC, hippocampus, and MPFC. We characterized the differences using Bayesian parameter averaging (BPA) in addition to classical inference (t-test). In addition to common effective connectivity in these two groups, HCs displayed widespread significant connections predominantly involved in ACC not detected in SZ patients, but SZ showed few connections. Based on BPA results, SZ patients exhibited anterior cingulate cortico-prefrontal-hippocampal hyperconnectivity, as well as ACC-related and hippocampal-dorsolateral prefrontal-medial prefrontal hypoconnectivity. In summary, spectral DCM revealed the pattern of effective connectivity involving ACC in patients with first-episode SZ. This study provides a potential link between SZ and dysfunction of ACC, creating an ideal situation to associate mechanisms behind SZ with aberrant connectivity among these cognition and emotion-related regions. PMID:26578933

Experimental research of phase transitions in a melt of high-purity aluminum

NASA Astrophysics Data System (ADS)

Vorontsov, V. B.; Pershin, V. K.

2017-12-01

This scientific work is devoted to the studying of the genetic connection structures of solid and liquid phases. In this paper Fourier analysis of acoustic emission (AE) signals accompanying heating of high purity aluminum from the melting point up to 860 °C was performed. The experimental data allowed to follow the dynamics of disorder zones in the melt with increasing melt temperature up to their complete destruction. The presented results of spectral analysis of the signals were analyzed from the standpoint of the theory of cluster melting metals.

An exploratory data analysis of electroencephalograms using the functional boxplots approach

PubMed Central

Ngo, Duy; Sun, Ying; Genton, Marc G.; Wu, Jennifer; Srinivasan, Ramesh; Cramer, Steven C.; Ombao, Hernando

2015-01-01

Many model-based methods have been developed over the last several decades for analysis of electroencephalograms (EEGs) in order to understand electrical neural data. In this work, we propose to use the functional boxplot (FBP) to analyze log periodograms of EEG time series data in the spectral domain. The functional bloxplot approach produces a median curve—which is not equivalent to connecting medians obtained from frequency-specific boxplots. In addition, this approach identifies a functional median, summarizes variability, and detects potential outliers. By extending FBPs analysis from one-dimensional curves to surfaces, surface boxplots are also used to explore the variation of the spectral power for the alpha (8–12 Hz) and beta (16–32 Hz) frequency bands across the brain cortical surface. By using rank-based nonparametric tests, we also investigate the stationarity of EEG traces across an exam acquired during resting-state by comparing the spectrum during the early vs. late phases of a single resting-state EEG exam. PMID:26347598

Spectral kinetic energy transfer in turbulent premixed reacting flows.

PubMed

Towery, C A Z; Poludnenko, A Y; Urzay, J; O'Brien, J; Ihme, M; Hamlington, P E

2016-05-01

Spectral kinetic energy transfer by advective processes in turbulent premixed reacting flows is examined using data from a direct numerical simulation of a statistically planar turbulent premixed flame. Two-dimensional turbulence kinetic-energy spectra conditioned on the planar-averaged reactant mass fraction are computed through the flame brush and variations in the spectra are connected to terms in the spectral kinetic energy transport equation. Conditional kinetic energy spectra show that turbulent small-scale motions are suppressed in the burnt combustion products, while the energy content of the mean flow increases. An analysis of spectral kinetic energy transfer further indicates that, contrary to the net down-scale transfer of energy found in the unburnt reactants, advective processes transfer energy from small to large scales in the flame brush close to the products. Triadic interactions calculated through the flame brush show that this net up-scale transfer of energy occurs primarily at spatial scales near the laminar flame thermal width. The present results thus indicate that advective processes in premixed reacting flows contribute to energy backscatter near the scale of the flame.

High resolution measurements of the low state of Cyg X-1

NASA Technical Reports Server (NTRS)

Rothschild, R. E.; Boldt, E. A.; Holt, S. S.; Serlemitsos, P. J.

1976-01-01

Cyg X-1 was observed on two occasions separated by a year by the same X-ray rocket payload. High resolution temporal and spectral data reveal that Cyg X-1 was essentially unchanged in these two observations a year apart, with bursts of millisecond duration observed in the earlier flight and also, observed in the second. Analysis of these bursts has failed to reveal any internal temporal structure, either luminous or spectral. The shot noise character of temporal fluctuations on timescales approximately 1 second can be explained by the presence of exponential pulses with a fraction of a second time constant and a rate near 8 sec/1. The possible connection of these pulses with the bursts is examined.

Spectral analysis of /s/ sound with changing angulation of the maxillary central incisors.

PubMed

Runte, Christoph; Tawana, Djafar; Dirksen, Dieter; Runte, Bettina; Lamprecht-Dinnesen, Antoinette; Bollmann, Friedhelm; Seifert, Eberhard; Danesh, Gholamreza

2002-01-01

The aim of the study was to measure the influence of the maxillary central incisors free from adaptation phenomena using spectral analysis. The maxillary dentures of 18 subjects were duplicated. The central incisors were fixed in a pivoting appliance so that their position could be changed from labial to palatal direction. A mechanical push/pull cable enabled the incisor section to be handled extraorally. Connected to the control was a sound generator producing a sinus wave whose frequency was related to the central incisor angulation. This acoustic signal was recorded on one channel of a digital tape recorder. After calibration of the unit, the denture duplicate was inserted into the subject's mouth, and the signal of the /s/ sounds subsequently produced by the subject was recorded on the second channel during alteration of the inclination angle simultaneously with the generator signal. Spectral analysis was performed using a Kay Speech-Lab 4300B. Labial displacement in particular produced significant changes in spectral characteristics, with the lower boundary frequency of the /s/ sound being raised and the upper boundary frequency being reduced. Maxillary incisor position influences /s/ sound production. Displacement of the maxillary incisors must be considered a cause of immediate changes in /s/ sound distortion. Therefore, denture teeth should be placed in the original tooth position as accurately as possible. Our results also indicate that neuromuscular reactions are more important for initial speech sound distortions than are aerodynamic changes in the anterior speech sound-producing areas.

How Useful Is Electroencephalography in the Diagnosis of Autism Spectrum Disorders and the Delineation of Subtypes: A Systematic Review

PubMed Central

Gurau, Oana; Bosl, William J.; Newton, Charles R.

2017-01-01

Autism spectrum disorders (ASD) are thought to be associated with abnormal neural connectivity. Presently, neural connectivity is a theoretical construct that cannot be easily measured. Research in network science and time series analysis suggests that neural network structure, a marker of neural activity, can be measured with electroencephalography (EEG). EEG can be quantified by different methods of analysis to potentially detect brain abnormalities. The aim of this review is to examine evidence for the utility of three methods of EEG signal analysis in the ASD diagnosis and subtype delineation. We conducted a review of literature in which 40 studies were identified and classified according to the principal method of EEG analysis in three categories: functional connectivity analysis, spectral power analysis, and information dynamics. All studies identified significant differences between ASD patients and non-ASD subjects. However, due to high heterogeneity in the results, generalizations could not be inferred and none of the methods alone are currently useful as a new diagnostic tool. The lack of studies prevented the analysis of these methods as tools for ASD subtypes delineation. These results confirm EEG abnormalities in ASD, but as yet not sufficient to help in the diagnosis. Future research with larger samples and more robust study designs could allow for higher sensitivity and consistency in characterizing ASD, paving the way for developing new means of diagnosis. PMID:28747892

Visible to Near-infrared Spectral Reflectance, NGEE-Arctic Tram, Barrow, Alaska, 2015-2017

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

Meng, Ran; McMahon, Andrew; Rogers, Alistair

Canopy spectral reflectance collected from the NGEE-Arctic automated tram platform using a PP-Systems UniSpec-DC spectrometer. Downwelling radiance was measured using a 2 meter fiber optic cable connected to a cosine diffuser. Upwelling (i.e. reflected) radiance was measured using a 2 meter cable connected to a 12 degree field-of-view (FOV) lens. Canopy reflectance was calculated using the ratio of upwelling to downwelling radiance measured over a 99.99% reflectance Spectralon standard measured at the start of each measurement set.

Conductive connection induced speed-up of localized-surface-plasmon dynamics

NASA Astrophysics Data System (ADS)

Cun, Peng; Wang, Meng; Huang, Cuiying; Huang, Pei; He, Xinkui; Wei, Zhiyi; Zhang, Xinping

2018-01-01

Conductive connection of localized surface plasmons (LSPs) was achieved by depositing a layer of continuous gold film onto the top surface of a matrix of randomly distributed gold nanoparticles (AuNPs) that were originally isolated on a glass substrate. Ultrafast spectroscopic response of such plasmonic nanostructures was investigated by femtosecond pump-probe detection technique. The transient-absorption data showed large redshift and broadening of the resonance spectrum of the conductively connected AuNPs with respect to the isolated ones. Such effects led to modulation on the evolution dynamics of LSPs in a transient transition spectral band. Making use of the temporal and spectral dislocation between the edges of transition band, we achieved much increased speed of the plasmonic optical switching effect.

Source Space Estimation of Oscillatory Power and Brain Connectivity in Tinnitus

PubMed Central

Zobay, Oliver; Palmer, Alan R.; Hall, Deborah A.; Sereda, Magdalena; Adjamian, Peyman

2015-01-01

Tinnitus is the perception of an internally generated sound that is postulated to emerge as a result of structural and functional changes in the brain. However, the precise pathophysiology of tinnitus remains unknown. Llinas’ thalamocortical dysrhythmia model suggests that neural deafferentation due to hearing loss causes a dysregulation of coherent activity between thalamus and auditory cortex. This leads to a pathological coupling of theta and gamma oscillatory activity in the resting state, localised to the auditory cortex where normally alpha oscillations should occur. Numerous studies also suggest that tinnitus perception relies on the interplay between auditory and non-auditory brain areas. According to the Global Brain Model, a network of global fronto—parietal—cingulate areas is important in the generation and maintenance of the conscious perception of tinnitus. Thus, the distress experienced by many individuals with tinnitus is related to the top—down influence of this global network on auditory areas. In this magnetoencephalographic study, we compare resting-state oscillatory activity of tinnitus participants and normal-hearing controls to examine effects on spectral power as well as functional and effective connectivity. The analysis is based on beamformer source projection and an atlas-based region-of-interest approach. We find increased functional connectivity within the auditory cortices in the alpha band. A significant increase is also found for the effective connectivity from a global brain network to the auditory cortices in the alpha and beta bands. We do not find evidence of effects on spectral power. Overall, our results provide only limited support for the thalamocortical dysrhythmia and Global Brain models of tinnitus. PMID:25799178

Spectral dilation of L(B,H)-valued measures and its application to stationary dilation for Banach space valued processes

NASA Technical Reports Server (NTRS)

Miamee, A. G.

1988-01-01

Let B be a Banach space and H and K two Hilbert spaces. The spectral dilation of L(B,H)-valued measures is studied and it is shown that the recent results of Makagon and Salehi (1986) and Rosenberg (1982) on the dilation of L(K,H)-valued measures can be extended to hold for the general Banach space setting of L(B,H)-valued measures. These L(B,H)-valued measures are closely connected to the Banach space valued processes. This connection is recalled and as application of spectral dilation of L(B,H)-valued measures the well known stationary dilation results for scalar valued processes is extended to the case of Banach space valued processes.

Connection anonymity analysis in coded-WDM PONs

NASA Astrophysics Data System (ADS)

Sue, Chuan-Ching

2008-04-01

A coded wavelength division multiplexing passive optical network (WDM PON) is presented for fiber to the home (FTTH) systems to protect against eavesdropping. The proposed scheme applies spectral amplitude coding (SAC) with a unipolar maximal-length sequence (M-sequence) code matrix to generate a specific signature address (coding) and to retrieve its matching address codeword (decoding) by exploiting the cyclic properties inherent in array waveguide grating (AWG) routers. In addition to ensuring the confidentiality of user data, the proposed coded-WDM scheme is also a suitable candidate for the physical layer with connection anonymity. Under the assumption that the eavesdropper applies a photo-detection strategy, it is shown that the coded WDM PON outperforms the conventional TDM PON and WDM PON schemes in terms of a higher degree of connection anonymity. Additionally, the proposed scheme allows the system operator to partition the optical network units (ONUs) into appropriate groups so as to achieve a better degree of anonymity.

Observational aspects of outbursting black hole sources: Evolution of spectro-temporal features and X-ray variability

NASA Astrophysics Data System (ADS)

Sreehari, H.; Nandi, Anuj; Radhika, D.; Iyer, Nirmal; Mandal, Samir

2018-02-01

We report on our attempt to understand the outbursting profile of Galactic Black Hole sources, keeping in mind the evolution of temporal and spectral features during the outburst. We present results of evolution of quasi-periodic oscillations, spectral states and possible connection with jet ejections during the outburst phase. Further, we attempt to connect the observed X-ray variabilities (i.e., `class'/`structured' variabilities, similar to GRS 1915+105) with spectral states of black hole sources. Towards these studies, we consider three black hole sources that have undergone single (XTE J1859+226), a few (IGR J17091-3624) and many (GX 339-4) outbursts since the start of RXTE era. Finally, we model the broadband energy spectra (3-150 keV) of different spectral states using RXTE and NuSTAR observations. Results are discussed in the context of two-component advective flow model, while constraining the mass of the three black hole sources.

Epidemic threshold in directed networks.

PubMed

Li, Cong; Wang, Huijuan; Van Mieghem, Piet

2013-12-01

Epidemics have so far been mostly studied in undirected networks. However, many real-world networks, such as the online social network Twitter and the world wide web, on which information, emotion, or malware spreads, are directed networks, composed of both unidirectional links and bidirectional links. We define the directionality ξ as the percentage of unidirectional links. The epidemic threshold τ(c) for the susceptible-infected-susceptible (SIS) epidemic is lower bounded by 1/λ(1) in directed networks, where λ(1), also called the spectral radius, is the largest eigenvalue of the adjacency matrix. In this work, we propose two algorithms to generate directed networks with a given directionality ξ. The effect of ξ on the spectral radius λ(1), principal eigenvector x(1), spectral gap (λ(1)-|λ(2)|), and algebraic connectivity μ(N-1) is studied. Important findings are that the spectral radius λ(1) decreases with the directionality ξ, whereas the spectral gap and the algebraic connectivity increase with the directionality ξ. The extent of the decrease of the spectral radius depends on both the degree distribution and the degree-degree correlation ρ(D). Hence, in directed networks, the epidemic threshold is larger and a random walk converges to its steady state faster than that in undirected networks with the same degree distribution.

Epidemic threshold in directed networks

NASA Astrophysics Data System (ADS)

Li, Cong; Wang, Huijuan; Van Mieghem, Piet

2013-12-01

Epidemics have so far been mostly studied in undirected networks. However, many real-world networks, such as the online social network Twitter and the world wide web, on which information, emotion, or malware spreads, are directed networks, composed of both unidirectional links and bidirectional links. We define the directionality ξ as the percentage of unidirectional links. The epidemic threshold τc for the susceptible-infected-susceptible (SIS) epidemic is lower bounded by 1/λ1 in directed networks, where λ1, also called the spectral radius, is the largest eigenvalue of the adjacency matrix. In this work, we propose two algorithms to generate directed networks with a given directionality ξ. The effect of ξ on the spectral radius λ1, principal eigenvector x1, spectral gap (λ1-λ2), and algebraic connectivity μN-1 is studied. Important findings are that the spectral radius λ1 decreases with the directionality ξ, whereas the spectral gap and the algebraic connectivity increase with the directionality ξ. The extent of the decrease of the spectral radius depends on both the degree distribution and the degree-degree correlation ρD. Hence, in directed networks, the epidemic threshold is larger and a random walk converges to its steady state faster than that in undirected networks with the same degree distribution.

RMS Spectral Modelling - a powerful tool to probe the origin of variability in Active Galactic Nuclei

NASA Astrophysics Data System (ADS)

Mallick, Labani; Dewangan, Gulab chand; Misra, Ranjeev

2016-07-01

The broadband energy spectra of Active Galactic Nuclei (AGN) are very complex in nature with the contribution from many ingredients: accretion disk, corona, jets, broad-line region (BLR), narrow-line region (NLR) and Compton-thick absorbing cloud or TORUS. The complexity of the broadband AGN spectra gives rise to mean spectral model degeneracy, e.g, there are competing models for the broad feature near 5-7 keV in terms of blurred reflection and complex absorption. In order to overcome the energy spectral model degeneracy, the most reliable approach is to study the RMS variability spectrum which connects the energy spectrum with temporal variability. The origin of variability could be pivoting of the primary continuum, reflection and/or absorption. The study of RMS (Root Mean Square) spectra would help us to connect the energy spectra with the variability. In this work, we study the energy dependent variability of AGN by developing theoretical RMS spectral model in ISIS (Interactive Spectral Interpretation System) for different input energy spectra. In this talk, I would like to present results of RMS spectral modelling for few radio-loud and radio-quiet AGN observed by XMM-Newton, Suzaku, NuSTAR and ASTROSAT and will probe the dichotomy between these two classes of AGN.

Multichannel Dynamic Fourier-Transform IR Spectrometer

NASA Astrophysics Data System (ADS)

Balashov, A. A.; Vaguine, V. A.; Golyak, Il. S.; Morozov, A. N.; Khorokhorin, A. I.

2017-09-01

A design of a multichannel continuous scan Fourier-transform IR spectrometer for simultaneous recording and analysis of the spectral characteristics of several objects is proposed. For implementing the design, a multi-probe fiber is used, constructed from several optical fibers connected into a single optical connector and attached at the output of the interferometer. The Fourier-transform spectrometer is used as a signal modulator. Each fiber is individually mated with an investigated sample and a dedicated radiation detector. For the developed system, the radiation intensity of the spectrometer is calculated from the condition of the minimum spectral resolution and parameters of the optical fibers. Using the proposed design, emission spectra of a gas-discharge neon lamp have been recorded using a single fiber 1 mm in diameter with a numerical aperture NA = 0.22.

Broadband Study of GRB 091127: A Sub-energetic Burst at Higher Redshift?

NASA Astrophysics Data System (ADS)

Troja, E.; Sakamoto, T.; Guidorzi, C.; Norris, J. P.; Panaitescu, A.; Kobayashi, S.; Omodei, N.; Brown, J. C.; Burrows, D. N.; Evans, P. A.; Gehrels, N.; Marshall, F. E.; Mawson, N.; Melandri, A.; Mundell, C. G.; Oates, S. R.; Pal'shin, V.; Preece, R. D.; Racusin, J. L.; Steele, I. A.; Tanvir, N. R.; Vasileiou, V.; Wilson-Hodge, C.; Yamaoka, K.

2012-12-01

GRB 091127 is a bright gamma-ray burst (GRB) detected by Swift at a redshift z = 0.49 and associated with SN 2009nz. We present the broadband analysis of the GRB prompt and afterglow emission and study its high-energy properties in the context of the GRB/SN association. While the high luminosity of the prompt emission and standard afterglow behavior are typical of cosmological long GRBs, its low-energy release (E γ < 3 × 1049 erg), soft spectrum, and unusual spectral lag connect this GRB to the class of sub-energetic bursts. We discuss the suppression of high-energy emission in this burst, and investigate whether this behavior could be connected with the sub-energetic nature of the explosion.

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

Jassal, Anjali Rao; Vadawale, Santosh V.; Mithun, N. P. S.

Low-frequency quasi-periodic oscillations (QPOs) are commonly observed during the hard states of black hole binaries. Several studies have established various observational/empirical correlations between spectral parameters and QPO properties, indicating a close link between the two. However, the exact mechanism of generation of QPOs is not yet well understood. In this paper, we present our attempts to comprehend the connection between the spectral components and the low-frequency QPO (LFQPO) observed in GRS 1915+105 using the data from NuSTAR. Detailed spectral modeling as well as the presence of the LFQPO and its energy dependence during this observation have been reported by Millermore » et al. and Zhang et al., respectively. We investigate the compatibility of the spectral model and the energy dependence of the QPO by simulating light curves in various energy bands for small variation of the spectral parameters. The basic concept here is to establish the connection, if any, between the QPO and the variation of either a spectral component or a specific parameter, which in turn can shed some light on the origin of the QPO. We begin with the best-fit spectral model of Miller et al. and simulate the light curve by varying the spectral parameters at frequencies close to the observed QPO frequency in order to generate the simulated QPO. Furthermore we simulate similar light curves in various energy bands in order to reproduce the observed energy dependence of the rms amplitude of the QPO. We find that the observed trend of increasing rms amplitude with energy can be reproduced qualitatively if the spectral index is assumed to be varying with the phases of the QPO. Variation of any other spectral parameter does not reproduce the observed energy dependence.« less

A stable pattern of EEG spectral coherence distinguishes children with autism from neuro-typical controls - a large case control study.

PubMed

Duffy, Frank H; Als, Heidelise

2012-06-26

The autism rate has recently increased to 1 in 100 children. Genetic studies demonstrate poorly understood complexity. Environmental factors apparently also play a role. Magnetic resonance imaging (MRI) studies demonstrate increased brain sizes and altered connectivity. Electroencephalogram (EEG) coherence studies confirm connectivity changes. However, genetic-, MRI- and/or EEG-based diagnostic tests are not yet available. The varied study results likely reflect methodological and population differences, small samples and, for EEG, lack of attention to group-specific artifact. Of the 1,304 subjects who participated in this study, with ages ranging from 1 to 18 years old and assessed with comparable EEG studies, 463 children were diagnosed with autism spectrum disorder (ASD); 571 children were neuro-typical controls (C). After artifact management, principal components analysis (PCA) identified EEG spectral coherence factors with corresponding loading patterns. The 2- to 12-year-old subsample consisted of 430 ASD- and 554 C-group subjects (n = 984). Discriminant function analysis (DFA) determined the spectral coherence factors' discrimination success for the two groups. Loading patterns on the DFA-selected coherence factors described ASD-specific coherence differences when compared to controls. Total sample PCA of coherence data identified 40 factors which explained 50.8% of the total population variance. For the 2- to 12-year-olds, the 40 factors showed highly significant group differences (P < 0.0001). Ten randomly generated split half replications demonstrated high-average classification success (C, 88.5%; ASD, 86.0%). Still higher success was obtained in the more restricted age sub-samples using the jackknifing technique: 2- to 4-year-olds (C, 90.6%; ASD, 98.1%); 4- to 6-year-olds (C, 90.9%; ASD 99.1%); and 6- to 12-year-olds (C, 98.7%; ASD, 93.9%). Coherence loadings demonstrated reduced short-distance and reduced, as well as increased, long-distance coherences for the ASD-groups, when compared to the controls. Average spectral loading per factor was wide (10.1 Hz). Classification success suggests a stable coherence loading pattern that differentiates ASD- from C-group subjects. This might constitute an EEG coherence-based phenotype of childhood autism. The predominantly reduced short-distance coherences may indicate poor local network function. The increased long-distance coherences may represent compensatory processes or reduced neural pruning. The wide average spectral range of factor loadings may suggest over-damped neural networks.

On integrable boundaries in the 2 dimensional O(N) σ-models

NASA Astrophysics Data System (ADS)

Aniceto, Inês; Bajnok, Zoltán; Gombor, Tamás; Kim, Minkyoo; Palla, László

2017-09-01

We make an attempt to map the integrable boundary conditions for 2 dimensional non-linear O(N) σ-models. We do it at various levels: classically, by demanding the existence of infinitely many conserved local charges and also by constructing the double row transfer matrix from the Lax connection, which leads to the spectral curve formulation of the problem; at the quantum level, we describe the solutions of the boundary Yang-Baxter equation and derive the Bethe-Yang equations. We then show how to connect the thermodynamic limit of the boundary Bethe-Yang equations to the spectral curve.

Multivariate Classification of Major Depressive Disorder Using the Effective Connectivity and Functional Connectivity

PubMed Central

Geng, Xiangfei; Xu, Junhai; Liu, Baolin; Shi, Yonggang

2018-01-01

Major depressive disorder (MDD) is a mental disorder characterized by at least 2 weeks of low mood, which is present across most situations. Diagnosis of MDD using rest-state functional magnetic resonance imaging (fMRI) data faces many challenges due to the high dimensionality, small samples, noisy and individual variability. To our best knowledge, no studies aim at classification with effective connectivity and functional connectivity measures between MDD patients and healthy controls. In this study, we performed a data-driving classification analysis using the whole brain connectivity measures which included the functional connectivity from two brain templates and effective connectivity measures created by the default mode network (DMN), dorsal attention network (DAN), frontal-parietal network (FPN), and silence network (SN). Effective connectivity measures were extracted using spectral Dynamic Causal Modeling (spDCM) and transformed into a vectorial feature space. Linear Support Vector Machine (linear SVM), non-linear SVM, k-Nearest Neighbor (KNN), and Logistic Regression (LR) were used as the classifiers to identify the differences between MDD patients and healthy controls. Our results showed that the highest accuracy achieved 91.67% (p < 0.0001) when using 19 effective connections and 89.36% when using 6,650 functional connections. The functional connections with high discriminative power were mainly located within or across the whole brain resting-state networks while the discriminative effective connections located in several specific regions, such as posterior cingulate cortex (PCC), ventromedial prefrontal cortex (vmPFC), dorsal cingulate cortex (dACC), and inferior parietal lobes (IPL). To further compare the discriminative power of functional connections and effective connections, a classification analysis only using the functional connections from those four networks was conducted and the highest accuracy achieved 78.33% (p < 0.0001). Our study demonstrated that the effective connectivity measures might play a more important role than functional connectivity in exploring the alterations between patients and health controls and afford a better mechanistic interpretability. Moreover, our results showed a diagnostic potential of the effective connectivity for the diagnosis of MDD patients with high accuracies allowing for earlier prevention or intervention. PMID:29515348

D{sub {infinity}}-differential A{sub {infinity}}-algebras and spectral sequences

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

Lapin, S V

2002-02-28

In the present paper the construction of a D{sub {infinity}}-differential A{sub {infinity}}-(co)algebra is introduced and basic homotopy properties of this construction are studied. The connection between D{sub {infinity}}-differential A{sub {infinity}}-(co)algebras and spectral sequences is established, which enables us to construct the structure of an A{sub {infinity}} -coalgebra on the Milnor coalgebra directly from the differentials of the Adams spectral sequence.

Analysis of Non Local Image Denoising Methods

NASA Astrophysics Data System (ADS)

Pardo, Álvaro

Image denoising is probably one of the most studied problems in the image processing community. Recently a new paradigm on non local denoising was introduced. The Non Local Means method proposed by Buades, Morel and Coll attracted the attention of other researches who proposed improvements and modifications to their proposal. In this work we analyze those methods trying to understand their properties while connecting them to segmentation based on spectral graph properties. We also propose some improvements to automatically estimate the parameters used on these methods.

Quantum walks on the chimera graph and its variants

NASA Astrophysics Data System (ADS)

Sanders, Barry; Sun, Xiangxiang; Xu, Shu; Wu, Jizhou; Zhang, Wei-Wei; Arshed, Nigum

We study quantum walks on the chimera graph, which is an important graph for performing quantum annealing, and we explore the nature of quantum walks on variants of the chimera graph. Features of these quantum walks provide profound insights into the nature of the chimera graph, including effects of greater and lesser connectivity, strong differences between quantum and classical random walks, isotropic spreading and localization only in the quantum case, and random graphs. We analyze finite-size effects due to limited width and length of the graph, and we explore the effect of different boundary conditions such as periodic and reflecting. Effects are explained via spectral analysis and the properties of stationary states, and spectral analysis enables us to characterize asymptotic behavior of the quantum walker in the long-time limit. Supported by China 1000 Talent Plan, National Science Foundation of China, Hefei National Laboratory for Physical Sciences at Microscale Fellowship, and the Chinese Academy of Sciences President's International Fellowship Initiative.

Graph Frequency Analysis of Brain Signals

PubMed Central

Huang, Weiyu; Goldsberry, Leah; Wymbs, Nicholas F.; Grafton, Scott T.; Bassett, Danielle S.; Ribeiro, Alejandro

2016-01-01

This paper presents methods to analyze functional brain networks and signals from graph spectral perspectives. The notion of frequency and filters traditionally defined for signals supported on regular domains such as discrete time and image grids has been recently generalized to irregular graph domains, and defines brain graph frequencies associated with different levels of spatial smoothness across the brain regions. Brain network frequency also enables the decomposition of brain signals into pieces corresponding to smooth or rapid variations. We relate graph frequency with principal component analysis when the networks of interest denote functional connectivity. The methods are utilized to analyze brain networks and signals as subjects master a simple motor skill. We observe that brain signals corresponding to different graph frequencies exhibit different levels of adaptability throughout learning. Further, we notice a strong association between graph spectral properties of brain networks and the level of exposure to tasks performed, and recognize the most contributing and important frequency signatures at different levels of task familiarity. PMID:28439325

Dynamics of zebra finch and mockingbird vocalizations

NASA Astrophysics Data System (ADS)

Cimenser, Aylin

Along with humans, whales, and bats, three groups of birds which include songbirds (oscines) such as the Zebra Finch (Taeniopygia guttata) and Mockingbird (Mimus polyglottos) are the only creatures known to learn sounds by imitation. Numerous similarities between human and songbird vocalizations exist and, recently, it has been shown that Zebra Finch in particular possesses a gene, FoxP2, known to be involved in human language. This thesis investigates song development in Zebra Finches, as well as the temporal dynamics of song in Mockingbirds. Zebra Finches have long been the system of choice for studying vocal development, ontogeny, and complexity in birdsong. Physicists find them intriguing because the spectrally complex vocalizations of the Zebra Finch can exhibit sudden transitions to chaotic dynamics, period doubling & mode-locking phenomena. Mockingbirds, by contrast, provide an ideal system to examine the richness of an avian repertoire, since these musically versatile songbirds typically know upwards of 200 songs. To analyse birdsong data, we have developed a novel clustering algorithm that can be applied to the bird's syllables, tracing their dynamics back to the earliest stages of vocal development. To characterize birdsong we have used Fourier techniques, based upon multitaper spectral analysis, to optimally work around the constraints imposed by (Heisenberg's) time-frequency uncertainty principle. Furthermore, estimates that provide optimal compromise between frequency and temporal resolution have beautiful connections with solutions to the Helmholtz wave equation in prolate spheroidal coordinates. We have used this connection to provide firm foundation for certain heuristics used in the literature to compute associated spectral derivatives and supply a pedagogical account here in this thesis. They are of interest because spectral derivatives emphasize sudden changes in the dynamics of the underlying phenomenon, and often provide a nice way to visualize such dynamics. Our Zebra Finch data consist of continuous recordings of six tutored birds from the early, plastic stages of sound production to the development of fully crystallized mature song. Our analysis reveals that well before the Zebra Finch hears adult song, identifiably distinct clusters are observable for all birds in the same regions of feature space. (Abstract shortened by UMI.)

Re-analysis of previous laboratory phase curves: 2. Connections between opposition effect morphology and spectral features of stony meteorites

NASA Astrophysics Data System (ADS)

Déau, Estelle; Spilker, Linda J.; Flandes, Alberto

2016-07-01

We investigate connections between the opposition phase curves and the spectra from ultraviolet to near infrared wavelengths of stony meteorites. We use two datasets: the reflectance dataset of Capaccioni et al. ([1990] Icarus, 83, 325), which consists of optical phase curves (from 2° to 45°) of 17 stony meteorites (three carbonaceous chondrites, 11 ordinary chondrites, and three achondrites), and the spectral dataset from the RELAB database consisting of near-ultraviolet to near-infrared spectra of the same meteorites. We re-analyzed the first dataset and fit it with two morphological models to derive the amplitude A, the angular width HWHM of the surge and the slope S of the linear part. Our re-analysis confirms that stony meteorites have a non-monotonic behavior of the surge amplitude with albedo, which is also observed in planetary surfaces (Déau et al. [2013] Icarus, 226, 1465), laboratory samples (Nelson et al. [2004] Proc. Lunar Sci. Conf., 35, p. 1089) and asteroids (Belskaya and Shevchenko [2000] Icarus, 147, 94). We find a very strong correlation between the opposition effect morphological parameters and the slope of the spectra between 0.75 μm and 0.95 μm. In particular, we found that meteorites with a positive amplitude-albedo correlation have a positive spectral slope between 0.75 μm and 0.95 μm, while meteorites with a negative amplitude-albedo correlation have a negative spectral slope between 0.75 μm and 0.95 μm. We have ruled out the role of the meteorite samples' macro-properties (grain size, porosity and macroscopic roughness) in the correlations found because these properties were constant during the preparation of the samples. If this hypothesis is correct, this implies that other properties like the composition or the micro-properties (grain inclusions, grain shape or microscopic roughness) could have a preponderant role in the non-monotonic behavior of the surge morphology with albedo at small and moderate phase angles. Further accurate characterization of carbonaceous chondrites samples are necessary to draw conclusions about the role of the micro-properties.

Conditional Spectral Analysis of Replicated Multiple Time Series with Application to Nocturnal Physiology.

PubMed

Krafty, Robert T; Rosen, Ori; Stoffer, David S; Buysse, Daniel J; Hall, Martica H

2017-01-01

This article considers the problem of analyzing associations between power spectra of multiple time series and cross-sectional outcomes when data are observed from multiple subjects. The motivating application comes from sleep medicine, where researchers are able to non-invasively record physiological time series signals during sleep. The frequency patterns of these signals, which can be quantified through the power spectrum, contain interpretable information about biological processes. An important problem in sleep research is drawing connections between power spectra of time series signals and clinical characteristics; these connections are key to understanding biological pathways through which sleep affects, and can be treated to improve, health. Such analyses are challenging as they must overcome the complicated structure of a power spectrum from multiple time series as a complex positive-definite matrix-valued function. This article proposes a new approach to such analyses based on a tensor-product spline model of Cholesky components of outcome-dependent power spectra. The approach exibly models power spectra as nonparametric functions of frequency and outcome while preserving geometric constraints. Formulated in a fully Bayesian framework, a Whittle likelihood based Markov chain Monte Carlo (MCMC) algorithm is developed for automated model fitting and for conducting inference on associations between outcomes and spectral measures. The method is used to analyze data from a study of sleep in older adults and uncovers new insights into how stress and arousal are connected to the amount of time one spends in bed.

Coherent white light amplification

DOEpatents

Jovanovic, Igor; Barty, Christopher P.

2004-05-25

A system for coherent simultaneous amplification of a broad spectral range of light that includes an optical parametric amplifier and a source of a seed pulse is described. A first angular dispersive element is operatively connected to the source of a seed pulse. A first imaging telescope is operatively connected to the first angular dispersive element and operatively connected to the optical parametric amplifier. A source of a pump pulse is operatively connected to the optical parametric amplifier. A second imaging telescope is operatively connected to the optical parametric amplifier and a second angular dispersive element is operatively connected to the second imaging telescope.

Functional connectivity among multi-channel EEGs when working memory load reaches the capacity.

PubMed

Zhang, Dan; Zhao, Huipo; Bai, Wenwen; Tian, Xin

2016-01-15

Evidence from behavioral studies has suggested a capacity existed in working memory. As the concept of functional connectivity has been introduced into neuroscience research in the recent years, the aim of this study is to investigate the functional connectivity in the brain when working memory load reaches the capacity. 32-channel electroencephalographs (EEGs) were recorded for 16 healthy subjects, while they performed a visual working memory task with load 1-6. Individual working memory capacity was calculated according to behavioral results. Short-time Fourier transform was used to determine the principal frequency band (theta band) related to working memory. The functional connectivity among EEGs was measured by the directed transform function (DTF) via spectral Granger causal analysis. The capacity was 4 calculated from the behavioral results. The power was focused in the frontal midline region. The strongest connectivity strengths of EEG theta components from load 1 to 6 distributed in the frontal midline region. The curve of DTF values vs load numbers showed that DTF increased from load 1 to 4, peaked at load 4, then decreased after load 4. This study finds that the functional connectivity between EEGs, described quantitatively by DTF, became less strong when working memory load exceeded the capacity. Copyright © 2015 Elsevier B.V. All rights reserved.

Micro spectrometer for parallel light and method of use

NASA Technical Reports Server (NTRS)

Park, Yeonjoon (Inventor); Choi, Sang H. (Inventor); King, Glen C. (Inventor); Elliott, James R. (Inventor)

2011-01-01

A spectrometer system includes an optical assembly for collimating light, a micro-ring grating assembly having a plurality of coaxially-aligned ring gratings, an aperture device defining an aperture circumscribing a target focal point, and a photon detector. An electro-optical layer of the grating assembly may be electrically connected to an energy supply to change the refractive index of the electro-optical layer. Alternately, the gratings may be electrically connected to the energy supply and energized, e.g., with alternating voltages, to change the refractive index. A data recorder may record the predetermined spectral characteristic. A method of detecting a spectral characteristic of a predetermined wavelength of source light includes generating collimated light using an optical assembly, directing the collimated light onto the micro-ring grating assembly, and selectively energizing the micro-ring grating assembly to diffract the predetermined wavelength onto the target focal point, and detecting the spectral characteristic using a photon detector.

Optical design and optical properties of a VUV spectrographic imager for ICON mission

NASA Astrophysics Data System (ADS)

Loicq, Jerome; Kintziger, Christian; Mazzoli, Alexandra; Miller, Tim; Chou, Cathy; Frey, Harald U.; Immel, Thomas J.; Mende, Stephen B.

2016-07-01

In the frame of the ICON (Ionospheric Connection Explorer) mission of NASA led by UC Berkeley, CSL and SSL Berkeley have designed in cooperation a new Far UV spectro-imager. The instrument is based on a Czerny-Turner spectrograph coupled with two back imagers. The whole field of view covers [+/- 12° vertical, +/- 9° horizontal]. The instrument is surmounted by a rotating mirror to adjust the horizontal field of view pointing by +/- 30°. To meet the scientific imaging and spectral requirements the instrument has been optimized. The optimization philosophy and related analysis are presented in the present paper. PSF, distortion map and spectral properties are described. A tolerance study and alignment cases were performed to prove the instrument can be built and aligned. Finally straylight and out of band properties are discussed.

Broadband Study of GRB 091127: A Sub-Energetic Burst at Higher Redshift?

DOE PAGES

Troja, E.; Sakamoto, T.; Guidorzi, C.; ...

2012-11-21

GRB 091127 is a bright gamma-ray burst (GRB) detected by Swift at a redshift z = 0.49 and associated with SN 2009nz. In this paper, we present the broadband analysis of the GRB prompt and afterglow emission and study its high-energy properties in the context of the GRB/SN association. While the high luminosity of the prompt emission and standard afterglow behavior are typical of cosmological long GRBs, its low-energy release (E γ < 3 x 10 49 erg), soft spectrum, and unusual spectral lag connect this GRB to the class of sub-energetic bursts. Finally, we discuss the suppression of high-energymore » emission in this burst, and investigate whether this behavior could be connected with the sub-energetic nature of the explosion.« less

Wavelet-based clustering of resting state MRI data in the rat.

PubMed

Medda, Alessio; Hoffmann, Lukas; Magnuson, Matthew; Thompson, Garth; Pan, Wen-Ju; Keilholz, Shella

2016-01-01

While functional connectivity has typically been calculated over the entire length of the scan (5-10min), interest has been growing in dynamic analysis methods that can detect changes in connectivity on the order of cognitive processes (seconds). Previous work with sliding window correlation has shown that changes in functional connectivity can be observed on these time scales in the awake human and in anesthetized animals. This exciting advance creates a need for improved approaches to characterize dynamic functional networks in the brain. Previous studies were performed using sliding window analysis on regions of interest defined based on anatomy or obtained from traditional steady-state analysis methods. The parcellation of the brain may therefore be suboptimal, and the characteristics of the time-varying connectivity between regions are dependent upon the length of the sliding window chosen. This manuscript describes an algorithm based on wavelet decomposition that allows data-driven clustering of voxels into functional regions based on temporal and spectral properties. Previous work has shown that different networks have characteristic frequency fingerprints, and the use of wavelets ensures that both the frequency and the timing of the BOLD fluctuations are considered during the clustering process. The method was applied to resting state data acquired from anesthetized rats, and the resulting clusters agreed well with known anatomical areas. Clusters were highly reproducible across subjects. Wavelet cross-correlation values between clusters from a single scan were significantly higher than the values from randomly matched clusters that shared no temporal information, indicating that wavelet-based analysis is sensitive to the relationship between areas. Copyright © 2015 Elsevier Inc. All rights reserved.

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.

A Multiscale Vibrational Spectroscopic Approach for Identification and Biochemical Characterization of Pollen

PubMed Central

Bağcıoğlu, Murat; Zimmermann, Boris; Kohler, Achim

2015-01-01

Background Analysis of pollen grains reveals valuable information on biology, ecology, forensics, climate change, insect migration, food sources and aeroallergens. Vibrational (infrared and Raman) spectroscopies offer chemical characterization of pollen via identifiable spectral features without any sample pretreatment. We have compared the level of chemical information that can be obtained by different multiscale vibrational spectroscopic techniques. Methodology Pollen from 15 different species of Pinales (conifers) were measured by seven infrared and Raman methodologies. In order to obtain infrared spectra, both reflectance and transmission measurements were performed on ground and intact pollen grains (bulk measurements), in addition, infrared spectra were obtained by microspectroscopy of multigrain and single pollen grain measurements. For Raman microspectroscopy measurements, spectra were obtained from the same pollen grains by focusing two different substructures of pollen grain. The spectral data from the seven methodologies were integrated into one data model by the Consensus Principal Component Analysis, in order to obtain the relations between the molecular signatures traced by different techniques. Results The vibrational spectroscopy enabled biochemical characterization of pollen and detection of phylogenetic variation. The spectral differences were clearly connected to specific chemical constituents, such as lipids, carbohydrates, carotenoids and sporopollenins. The extensive differences between pollen of Cedrus and the rest of Pinaceae family were unambiguously connected with molecular composition of sporopollenins in pollen grain wall, while pollen of Picea has apparently higher concentration of carotenoids than the rest of the family. It is shown that vibrational methodologies have great potential for systematic collection of data on ecosystems and that the obtained phylogenetic variation can be well explained by the biochemical composition of pollen. Out of the seven tested methodologies, the best taxonomical differentiation of pollen was obtained by infrared measurements on bulk samples, as well as by Raman microspectroscopy measurements of the corpus region of the pollen grain. Raman microspectroscopy measurements indicate that measurement area, as well as the depth of focus, can have crucial influence on the obtained data. PMID:26376486

Human brain distinctiveness based on EEG spectral coherence connectivity.

PubMed

Rocca, D La; Campisi, P; Vegso, B; Cserti, P; Kozmann, G; Babiloni, F; Fallani, F De Vico

2014-09-01

The use of EEG biometrics, for the purpose of automatic people recognition, has received increasing attention in the recent years. Most of the current analyses rely on the extraction of features characterizing the activity of single brain regions, like power spectrum estimation, thus neglecting possible temporal dependencies between the generated EEG signals. However, important physiological information can be extracted from the way different brain regions are functionally coupled. In this study, we propose a novel approach that fuses spectral coherence-based connectivity between different brain regions as a possibly viable biometric feature. The proposed approach is tested on a large dataset of subjects (N = 108) during eyes-closed (EC) and eyes-open (EO) resting state conditions. The obtained recognition performance shows that using brain connectivity leads to higher distinctiveness with respect to power-spectrum measurements, in both the experimental conditions. Notably, a 100% recognition accuracy is obtained in EC and EO when integrating functional connectivity between regions in the frontal lobe, while a lower 97.5% is obtained in EC (96.26% in EO) when fusing power spectrum information from parieto-occipital (centro-parietal in EO) regions. Taken together, these results suggest that the functional connectivity patterns represent effective features for improving EEG-based biometric systems.

Potential of remotely-sensed data for mapping sediment connectivity pathways and their seasonal changes in dryland environments

NASA Astrophysics Data System (ADS)

Foerster, Saskia; Wilczok, Charlotte; Brosinsky, Arlena; Kroll, Anja; Segl, Karl; Francke, Till

2014-05-01

Many drylands are characterized by strong erosion in headwater catchments, where connectivity processes play an important role in the redistribution of water and sediments. Sediment connectivity relates to the physical transfer of sediment through a drainage basin (Bracken and Croke 2007). The identification of sediment source areas and the way they connect to the channel network are essential to environmental management (Reid et al. 2007), especially where high erosion and sediment delivery rates occur. Vegetation cover and its spatial and temporal pattern is one of the main factors affecting sediment connectivity. This is particularly true for patchy vegetation covers typical for dryland environments. While many connectivity studies are based on field-derived data, the potential of remotely-sensed data for sediment connectivity analyses has not yet been fully exploited. Recent advances in remote sensing allow for quantitative, spatially explicit, catchment-wide derivation of surface information to be used in connectivity analyses. These advances include a continuous increase in spatial image resolution to comprise processes at the plot to hillslope to catchment scale, an increase in the temporal resolution to cover seasonal and long-term changes and an increase in the spectral resolution enabling the discrimination of dry and green vegetation fractions from soil surfaces in heterogeneous dryland landscapes. The utilization of remotely-sensed data for connectivity studies raises questions on what type of information is required, how scale of sediment flux and image resolution match, how the connectivity information can be incorporated into water and sediment transport models and how this improves model predictions. The objective of this study is to demonstrate the potential of remotely-sensed data for mapping sediment connectivity pathways and their seasonal change at the example of a mesoscale dryland catchment in the Spanish Pyrenees. Here, sediment connectivity pathways have been mapped for two adjacent sub-catchments (approx. 70 km²) of the Isábena River in different seasons using a quantitative connectivity index based on fractional vegetation cover and topography data. Fractional cover of green and dry vegetation, bare soil and rock were derived by applying a Multiple Endmember Spectral Mixture Analysis approach applied to a hyperspectral image dataset. Sediment connectivity was mapped using the Index of Connectivity (Borselli et al. 2008), in which the effect of land cover on runoff and sediment fluxes is expressed by a spatially distributed weighing factor (in this study, the cover and management factor of the RUSLE). The resulting connectivity maps show that areas behave very differently with regard to connectivity, depending on the land cover but also on the spatial distribution of vegetation abundances and topographic barriers. Most parts of the catchment show higher connectivity values in summer than in spring. The studied sub-catchments show a slightly different connectivity behaviour reflecting the different land cover proportions and their spatial configuration. Future work includes the incorporation of sediment connectivity information into a hydrological model (WASA-SED, Mueller et al. 2010) to better reflect connectivity processes and testing the sensitivity of the model to different input data.

Selected issues connected with determination of requirements of spectral properties of camouflage patterns

NASA Astrophysics Data System (ADS)

Racek, František; Jobánek, Adam; Baláž, Teodor; Krejčí, Jaroslav

2017-10-01

Traditionally spectral reflectance of the material is measured and compared with permitted spectral reflectance boundaries. The boundaries are limited by upper and lower curve of spectral reflectance. The boundaries for unique color has to fulfil the operational requirements as a versatility of utilization through the all year seasons, day and weather condition on one hand and chromatic and spectral matching with background as well as the manufacturability on the other hand. The interval between the boundaries suffers with ambivalent feature. Camouflage pattern producer would be happy to see it much wider, but blending effect into its particular background could be better with narrower tolerance limits. From the point of view of long time user of camouflage pattern battledress, there seems to be another ambivalent feature. Width of the tolerance zone reflecting natural dispersion of spectral reflectance values allows the significant distortions of shape of the spectral curve inside the given boundaries.

Silicon Nitride Grating Coupler with Flexible Bandwidth Incorporating a Serially Concatenated Multimode Interference Filter

NASA Astrophysics Data System (ADS)

Kim, Woo-Ju; Lee, Hak-Soon; Lee, Sang-Shin

2012-04-01

A compact silicon nitride grating coupler with flexible bandwidth was demonstrated taking advantage of a basic grating integrated with a serially connected multistage multimode interference (MMI) filter. The spectral response could be tailored by varying the order of the MMI filter, without affecting the basic grating structure. The dependence of the spectral response of the proposed device on the order of the MMI stage was thoroughly investigated. As regards the fabricated grating coupler with a four-stage MMI filter, the observed spectral bandwidth was efficiently altered from 53 to 21 nm in the ˜1550 nm spectral band.

Direct Connection between the RII Chain and the Nonautonomous Discrete Modified KdV Lattice

NASA Astrophysics Data System (ADS)

Maeda, Kazuki; Tsujimoto, Satoshi

2013-11-01

The spectral transformation technique for symmetric RII polynomials is developed. Use of this technique reveals that the nonautonomous discrete modified KdV (nd-mKdV) lattice is directly connected with the RII chain. Hankel determinant solutions to the semi-infinite nd-mKdV lattice are also presented.

A stable pattern of EEG spectral coherence distinguishes children with autism from neuro-typical controls - a large case control study

PubMed Central

2012-01-01

Background The autism rate has recently increased to 1 in 100 children. Genetic studies demonstrate poorly understood complexity. Environmental factors apparently also play a role. Magnetic resonance imaging (MRI) studies demonstrate increased brain sizes and altered connectivity. Electroencephalogram (EEG) coherence studies confirm connectivity changes. However, genetic-, MRI- and/or EEG-based diagnostic tests are not yet available. The varied study results likely reflect methodological and population differences, small samples and, for EEG, lack of attention to group-specific artifact. Methods Of the 1,304 subjects who participated in this study, with ages ranging from 1 to 18 years old and assessed with comparable EEG studies, 463 children were diagnosed with autism spectrum disorder (ASD); 571 children were neuro-typical controls (C). After artifact management, principal components analysis (PCA) identified EEG spectral coherence factors with corresponding loading patterns. The 2- to 12-year-old subsample consisted of 430 ASD- and 554 C-group subjects (n = 984). Discriminant function analysis (DFA) determined the spectral coherence factors' discrimination success for the two groups. Loading patterns on the DFA-selected coherence factors described ASD-specific coherence differences when compared to controls. Results Total sample PCA of coherence data identified 40 factors which explained 50.8% of the total population variance. For the 2- to 12-year-olds, the 40 factors showed highly significant group differences (P < 0.0001). Ten randomly generated split half replications demonstrated high-average classification success (C, 88.5%; ASD, 86.0%). Still higher success was obtained in the more restricted age sub-samples using the jackknifing technique: 2- to 4-year-olds (C, 90.6%; ASD, 98.1%); 4- to 6-year-olds (C, 90.9%; ASD 99.1%); and 6- to 12-year-olds (C, 98.7%; ASD, 93.9%). Coherence loadings demonstrated reduced short-distance and reduced, as well as increased, long-distance coherences for the ASD-groups, when compared to the controls. Average spectral loading per factor was wide (10.1 Hz). Conclusions Classification success suggests a stable coherence loading pattern that differentiates ASD- from C-group subjects. This might constitute an EEG coherence-based phenotype of childhood autism. The predominantly reduced short-distance coherences may indicate poor local network function. The increased long-distance coherences may represent compensatory processes or reduced neural pruning. The wide average spectral range of factor loadings may suggest over-damped neural networks. PMID:22730909

Consistency with synchrotron emission in the bright GRB 160625B observed by Fermi

NASA Astrophysics Data System (ADS)

Ravasio, M. E.; Oganesyan, G.; Ghirlanda, G.; Nava, L.; Ghisellini, G.; Pescalli, A.; Celotti, A.

2018-05-01

We present time-resolved spectral analysis of prompt emission from GRB 160625B, one of the brightest bursts ever detected by Fermi in its nine years of operations. Standard empirical functions fail to provide an acceptable fit to the GBM spectral data, which instead require the addition of a low-energy break to the fitting function. We introduce a new fitting function, called 2SBPL, consisting of three smoothly connected power laws. Fitting this model to the data, the goodness of the fits significantly improves and the spectral parameters are well constrained. We also test a spectral model that combines non-thermal and thermal (black body) components, but find that the 2SBPL model is systematically favoured. The spectral evolution shows that the spectral break is located around Ebreak 100 keV, while the usual νFν peak energy feature Epeak evolves in the 0.5-6 MeV energy range. The slopes below and above Ebreak are consistent with the values -0.67 and -1.5, respectively, expected from synchrotron emission produced by a relativistic electron population with a low-energy cut-off. If Ebreak is interpreted as the synchrotron cooling frequency, the implied magnetic field in the emitting region is 10 Gauss, i.e. orders of magnitudes smaller than the value expected for a dissipation region located at 1013-14 cm from the central engine. The low ratio between Epeak and Ebreak implies that the radiative cooling is incomplete, contrary to what is expected in strongly magnetized and compact emitting regions.

Broadband Study of GRB 091127: A Sub-Energetic Burst at Higher Redshift?

NASA Technical Reports Server (NTRS)

Troja, E.; Sakamoto, T.; Guidorzi, C.; Norris, J. P.; Panaitescu, A.; Kobayashi, S.; Omodei, N.; Brown, J. C.; Burrows, D. N.; Evans, P. A.;

Calibrating AIS images using the surface as a reference

NASA Technical Reports Server (NTRS)

Smith, M. O.; Roberts, D. A.; Shipman, H. M.; Adams, J. B.; Willis, S. C.; Gillespie, A. R.

1987-01-01

A method of evaluating the initial assumptions and uncertainties of the physical connection between Airborne Imaging Spectrometer (AIS) image data and laboratory/field spectrometer data was tested. The Tuscon AIS-2 image connects to lab reference spectra by an alignment to the image spectral endmembers through a system gain and offset for each band. Images were calibrated to reflectance so as to transform the image into a measure that is independent of the solar radiant flux. This transformation also makes the image spectra directly comparable to data from lab and field spectrometers. A method was tested for calibrating AIS images using the surface as a reference. The surface heterogeneity is defined by lab/field spectral measurements. It was found that the Tuscon AIS-2 image is consistent with each of the initial hypotheses: (1) that the AIS-2 instrument calibration is nearly linear; (2) the spectral variance is caused by sub-pixel mixtures of spectrally distinct materials and shade, and (3) that sub-pixel mixtures can be treated as linear mixtures of pure endmembers. It was also found that the image can be characterized by relatively few endmembers using the AIS-2 spectra.

Wavelength-Filter Based Spectral Calibrated Wave number - Linearization in 1.3 mm Spectral Domain Optical Coherence.

PubMed

Wijeisnghe, Ruchire Eranga Henry; Cho, Nam Hyun; Park, Kibeom; Shin, Yongseung; Kim, Jeehyun

2013-12-01

In this study, we demonstrate the enhanced spectral calibration method for 1.3 μm spectral-domain optical coherence tomography (SD-OCT). The calibration method using wavelength-filter simplifies the SD-OCT system, and also the axial resolution and the entire speed of the OCT system can be dramatically improved as well. An externally connected wavelength-filter is utilized to obtain the information of the wavenumber and the pixel position. During the calibration process the wavelength-filter is placed after a broadband source by connecting through an optical circulator. The filtered spectrum with a narrow line width of 0.5 nm is detected by using a line-scan camera. The method does not require a filter or a software recalibration algorithm for imaging as it simply resamples the OCT signal from the detector array without employing rescaling or interpolation methods. One of the main drawbacks of SD-OCT is the broadened point spread functions (PSFs) with increasing imaging depth can be compensated by increasing the wavenumber-linearization order. The sensitivity of our system was measured at 99.8 dB at an imaging depth of 2.1 mm compared with the uncompensated case.

Identification of channel geometries applying seismic attributes and spectral decomposition techniques, Temsah Field, Offshore East Nile Delta, Egypt

NASA Astrophysics Data System (ADS)

Othman, Adel A. A.; Fathy, M.; Negm, Adel

2018-06-01

The Temsah field is located in eastern part of the Nile delta to seaward. The main reservoirs of the area are Middle Pliocene mainly consist from siliciclastic which associated with a close deep marine environment. The Distribution pattern of the reservoir facies is limited scale indicating fast lateral and vertical changes which are not easy to resolve by applying of conventional seismic attribute. The target of the present study is to create geophysical workflows to a better image of the channel sand distribution in the study area. We apply both Average Absolute Amplitude and Energy attribute which are indicated on the distribution of the sand bodies in the study area but filled to fully described the channel geometry. So another tool, which offers more detailed geometry description is needed. The spectral decomposition analysis method is an alternative technique focused on processing Discrete Fourier Transform which can provide better results. Spectral decomposition have been done over the upper channel shows that the frequency in the eastern part of the channel is the same frequency in places where the wells are drilled, which confirm the connection of both the eastern and western parts of the upper channel. Results suggest that application of the spectral decomposition method leads to reliable inferences. Hence, using the spectral decomposition method alone or along with other attributes has a positive impact on reserves growth and increased production where the reserve in the study area increases to 75bcf.

D{sub {infinity}}-differential E{sub {infinity}}-algebras and spectral sequences of fibrations

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

Lapin, Sergei V

2007-10-31

The notion of an E{sub {infinity}}-algebra with a filtration is introduced. The connections are established between E{sub {infinity}}-algebras with filtrations and the theory of D{sub {infinity}}-differential E{sub {infinity}}-algebras over fields. Based on the technique of D{sub {infinity}}-differential E{sub {infinity}}-algebras, the apparatus of spectral sequences is developed for E{sub {infinity}}-algebras with filtrations, and applications of this apparatus to the multiplicative cohomology spectral sequences of fibrations are given. Bibliography: 21 titles.

On the location of spectral edges in \\ {Z}-periodic media

NASA Astrophysics Data System (ADS)

Exner, Pavel; Kuchment, Peter; Winn, Brian

2010-11-01

Periodic second-order ordinary differential operators on \\ {R} are known to have the edges of their spectra to occur only at the spectra of periodic and anti-periodic boundary value problems. The multi-dimensional analog of this property is false, as was shown in a 2007 paper by some of the authors of this paper. However, one sometimes encounters the claims that in the case of a single periodicity (i.e., with respect to the lattice \\ {Z}), the 1D property still holds, and spectral edges occur at the periodic and anti-periodic spectra only. In this work, we show that even in the simplest case of quantum graphs this is not true. It is shown that this is true if the graph consists of a 1D chain of finite graphs connected by single edges, while if the connections are formed by at least two edges, the spectral edges can already occur away from the periodic and anti-periodic spectra. This paper is dedicated to the memory of P Duclos.

Connections between Narrow Line Seyfert 1 Galaxies and Stellar Black Hole Candidates

NASA Astrophysics Data System (ADS)

Negoro, H.

Connections between narrow line Seyfert 1 galaxies (NLS1s) and black hole candidates are described. It has been pointed out that X-ray properties of NLS1s are simlar to those of stellar black hole candidates (BHCs). It is, however, not clear that NLS1s are corresponding to what `state' in the BHCs. Recently, rapid spectral variations during X-ray flares in a few NLS1s have been discovered using ASCA data. The properties of the spectral variations are very similar to those seen in stellar black hole candidates in the hard state. Such temporal variability accompanying the spectral change has not been recognized in black hole candidates in other states. These and recent theoretical progress based on a time variability model of the BHCs in the hard state imply that the advection plays an important role in the accretion process not only in the BHCs in the hard state, but also in NLS1s.

Adaptation by normal listeners to upward spectral shifts of speech: implications for cochlear implants.

PubMed

Rosen, S; Faulkner, A; Wilkinson, L

1999-12-01

Multi-channel cochlear implants typically present spectral information to the wrong "place" in the auditory nerve array, because electrodes can only be inserted partway into the cochlea. Although such spectral shifts are known to cause large immediate decrements in performance in simulations, the extent to which listeners can adapt to such shifts has yet to be investigated. Here, the effects of a four-channel implant in normal listeners have been simulated, and performance tested with unshifted spectral information and with the equivalent of a 6.5-mm basalward shift on the basilar membrane (1.3-2.9 octaves, depending on frequency). As expected, the unshifted simulation led to relatively high levels of mean performance (e.g., 64% of words in sentences correctly identified) whereas the shifted simulation led to very poor results (e.g., 1% of words). However, after just nine 20-min sessions of connected discourse tracking with the shifted simulation, performance improved significantly for the identification of intervocalic consonants, medial vowels in monosyllables, and words in sentences (30% of words). Also, listeners were able to track connected discourse of shifted signals without lipreading at rates up to 40 words per minute. Although we do not know if complete adaptation to the shifted signals is possible, it is clear that short-term experiments seriously exaggerate the long-term consequences of such spectral shifts.

EEG Functional Connectivity Prior to Sleepwalking: Evidence of Interplay Between Sleep and Wakefulness

PubMed Central

Desjardins, Marie-Ève; Carrier, Julie; Lina, Jean-Marc; Fortin, Maxime; Gosselin, Nadia; Montplaisir, Jacques

2017-01-01

Abstract Study Objectives: Although sleepwalking (somnambulism) affects up to 4% of adults, its pathophysiology remains poorly understood. Sleepwalking can be preceded by fluctuations in slow-wave sleep EEG signals, but the significance of these pre-episode changes remains unknown and methods based on EEG functional connectivity have yet to be used to better comprehend the disorder. Methods: We investigated the sleep EEG of 27 adult sleepwalkers (mean age: 29 ± 7.6 years) who experienced a somnambulistic episode during slow-wave sleep. The 20-second segment of sleep EEG immediately preceding each patient’s episode was compared with the 20-second segment occurring 2 minutes prior to episode onset. Results: Results from spectral analyses revealed increased delta and theta spectral power in the 20 seconds preceding the episodes’ onset as compared to the 20 seconds occurring 2 minutes before the episodes. The imaginary part of the coherence immediately prior to episode onset revealed (1) decreased delta EEG functional connectivity in parietal and occipital regions, (2) increased alpha connectivity over a fronto-parietal network, and (3) increased beta connectivity involving symmetric inter-hemispheric networks implicating frontotemporal, parietal and occipital areas. Conclusions: Taken together, these modifications in EEG functional connectivity suggest that somnambulistic episodes are preceded by brain processes characterized by the co-existence of arousal and deep sleep. PMID:28204773

Fluvial reservoir characterization using topological descriptors based on spectral analysis of graphs

NASA Astrophysics Data System (ADS)

Viseur, Sophie; Chiaberge, Christophe; Rhomer, Jérémy; Audigane, Pascal

2015-04-01

Fluvial systems generate highly heterogeneous reservoir. These heterogeneities have major impact on fluid flow behaviors. However, the modelling of such reservoirs is mainly performed in under-constrained contexts as they include complex features, though only sparse and indirect data are available. Stochastic modeling is the common strategy to solve such problems. Multiple 3D models are generated from the available subsurface dataset. The generated models represent a sampling of plausible subsurface structure representations. From this model sampling, statistical analysis on targeted parameters (e.g.: reserve estimations, flow behaviors, etc.) and a posteriori uncertainties are performed to assess risks. However, on one hand, uncertainties may be huge, which requires many models to be generated for scanning the space of possibilities. On the other hand, some computations performed on the generated models are time consuming and cannot, in practice, be applied on all of them. This issue is particularly critical in: 1) geological modeling from outcrop data only, as these data types are generally sparse and mainly distributed in 2D at large scale but they may locally include high-resolution descriptions (e.g.: facies, strata local variability, etc.); 2) CO2 storage studies as many scales of investigations are required, from meter to regional ones, to estimate storage capacities and associated risks. Recent approaches propose to define distances between models to allow sophisticated multivariate statistics to be applied on the space of uncertainties so that only sub-samples, representative of initial set, are investigated for dynamic time-consuming studies. This work focuses on defining distances between models that characterize the topology of the reservoir rock network, i.e. its compactness or connectivity degree. The proposed strategy relies on the study of the reservoir rock skeleton. The skeleton of an object corresponds to its median feature. A skeleton is computed for each reservoir rock geobody and studied through a graph spectral analysis. To achieve this, the skeleton is converted into a graph structure. The spectral analysis applied on this graph structure allows a distance to be defined between pairs of graphs. Therefore, this distance is used as support for clustering analysis to gather models that share the same reservoir rock topology. To show the ability of the defined distances to discriminate different types of reservoir connectivity, a synthetic data set of fluvial models with different geological settings was generated and studied using the proposed approach. The results of the clustering analysis are shown and discussed.

Detection of Chorus Elements and other Wave Signatures Using Geometric Computational Techniques in the Van Allen radiation belts

NASA Astrophysics Data System (ADS)

Sengupta, A.; Kletzing, C.; Howk, R.; Kurth, W. S.

2017-12-01

An important goal of the Van Allen Probes mission is to understand wave particle interactions that can energize relativistic electron in the Earth's Van Allen radiation belts. The EMFISIS instrumentation suite provides measurements of wave electric and magnetic fields of wave features such as chorus that participate in these interactions. Geometric signal processing discovers structural relationships, e.g. connectivity across ridge-like features in chorus elements to reveal properties such as dominant angles of the element (frequency sweep rate) and integrated power along the a given chorus element. These techniques disambiguate these wave features against background hiss-like chorus. This enables autonomous discovery of chorus elements across the large volumes of EMFISIS data. At the scale of individual or overlapping chorus elements, topological pattern recognition techniques enable interpretation of chorus microstructure by discovering connectivity and other geometric features within the wave signature of a single chorus element or between overlapping chorus elements. Thus chorus wave features can be quantified and studied at multiple scales of spectral geometry using geometric signal processing techniques. We present recently developed computational techniques that exploit spectral geometry of chorus elements and whistlers to enable large-scale automated discovery, detection and statistical analysis of these events over EMFISIS data. Specifically, we present different case studies across a diverse portfolio of chorus elements and discuss the performance of our algorithms regarding precision of detection as well as interpretation of chorus microstructure. We also provide large-scale statistical analysis on the distribution of dominant sweep rates and other properties of the detected chorus elements.

THE LOW-FREQUENCY RADIO CATALOG OF FLAT-SPECTRUM SOURCES

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

Massaro, F.; Giroletti, M.; D'Abrusco, R.

A well known property of the γ-ray sources detected by Cos-B in the 1970s, by the Compton Gamma-Ray Observatory in the 1990s, and recently by the Fermi observations is the presence of radio counterparts, particularly for those associated with extragalactic objects. This observational evidence is the basis of the radio-γ-ray connection established for the class of active galactic nuclei known as blazars. In particular, the main spectral property of the radio counterparts associated with γ-ray blazars is that they show a flat spectrum in the GHz frequency range. Our recent analysis dedicated to search blazar-like candidates as potential counterparts formore » the unidentified γ-ray sources allowed us to extend the radio-γ-ray connection in the MHz regime. We also showed that blazars below 1 GHz maintain flat radio spectra. Thus, on the basis of these new results, we assembled a low-frequency radio catalog of flat-spectrum sources built by combining the radio observations of the Westerbork Northern Sky Survey and of the Westerbork in the southern hemisphere catalog with those of the NRAO Very Large Array Sky survey (NVSS). This could be used in the future to search for new, unknown blazar-like counterparts of γ-ray sources. First, we found NVSS counterparts of Westerbork Synthesis Radio Telescope radio sources, and then we selected flat-spectrum radio sources according to a new spectral criterion, specifically defined for radio observations performed below 1 GHz. We also described the main properties of the catalog listing 28,358 radio sources and their logN-logS distributions. Finally, a comparison with the Green Bank 6 cm radio source catalog was performed to investigate the spectral shape of the low-frequency flat-spectrum radio sources at higher frequencies.« less

Computerized recognition of persons by EEG spectral patterns.

PubMed

Stassen, H H

1980-07-01

Modified techniques of communication theory in connection with multivariate statistical procedures were applied to a sample of 82 patients for the purpose of defining EEG spectral patterns and for solving the relevant classification problems. Ten measurements per patient were made and it could be shown that a subject can be characterized and be recognized by his EEG spectral pattern with high reliability and a confidence probability of almost 90%. This result is valid not only for normal adults but also for schizophrenic patients, implying a close relationship between the EEG spectral pattern and the individual person. At the moment the nature of this relationship is not clear; in particular the supposed relationship to psychopathology could not be proved.

SPECTRAL GRAPH THEORY AND GRAPH ENERGY METRICS SHOW EVIDENCE FOR THE ALZHEIMER’S DISEASE DISCONNECTION SYNDROME IN APOE-4 RISK GENE CARRIERS

PubMed Central

Daianu, Madelaine; Mezher, Adam; Jahanshad, Neda; Hibar, Derrek P.; Nir, Talia M.; Jack, Clifford R.; Weiner, Michael W.; Bernstein, Matt A.; Thompson, Paul M.

2015-01-01

Our understanding of network breakdown in Alzheimer’s disease (AD) is likely to be enhanced through advanced mathematical descriptors. Here, we applied spectral graph theory to provide novel metrics of structural connectivity based on 3-Tesla diffusion weighted images in 42 AD patients and 50 healthy controls. We reconstructed connectivity networks using whole-brain tractography and examined, for the first time here, cortical disconnection based on the graph energy and spectrum. We further assessed supporting metrics - link density and nodal strength - to better interpret our results. Metrics were analyzed in relation to the well-known APOE-4 genetic risk factor for late-onset AD. The number of disconnected cortical regions increased with the number of copies of the APOE-4 risk gene in people with AD. Each additional copy of the APOE-4 risk gene may lead to more dysfunctional networks with weakened or abnormal connections, providing evidence for the previously hypothesized “disconnection syndrome”. PMID:26413205

SPECTRAL GRAPH THEORY AND GRAPH ENERGY METRICS SHOW EVIDENCE FOR THE ALZHEIMER'S DISEASE DISCONNECTION SYNDROME IN APOE-4 RISK GENE CARRIERS.

PubMed

Daianu, Madelaine; Mezher, Adam; Jahanshad, Neda; Hibar, Derrek P; Nir, Talia M; Jack, Clifford R; Weiner, Michael W; Bernstein, Matt A; Thompson, Paul M

2015-04-01

Our understanding of network breakdown in Alzheimer's disease (AD) is likely to be enhanced through advanced mathematical descriptors. Here, we applied spectral graph theory to provide novel metrics of structural connectivity based on 3-Tesla diffusion weighted images in 42 AD patients and 50 healthy controls. We reconstructed connectivity networks using whole-brain tractography and examined, for the first time here, cortical disconnection based on the graph energy and spectrum. We further assessed supporting metrics - link density and nodal strength - to better interpret our results. Metrics were analyzed in relation to the well-known APOE -4 genetic risk factor for late-onset AD. The number of disconnected cortical regions increased with the number of copies of the APOE -4 risk gene in people with AD. Each additional copy of the APOE -4 risk gene may lead to more dysfunctional networks with weakened or abnormal connections, providing evidence for the previously hypothesized "disconnection syndrome".

Phase-space networks of geometrically frustrated systems.

PubMed

Han, Yilong

2009-11-01

We illustrate a network approach to the phase-space study by using two geometrical frustration models: antiferromagnet on triangular lattice and square ice. Their highly degenerated ground states are mapped as discrete networks such that the quantitative network analysis can be applied to phase-space studies. The resulting phase spaces share some comon features and establish a class of complex networks with unique Gaussian spectral densities. Although phase-space networks are heterogeneously connected, the systems are still ergodic due to the random Poisson processes. This network approach can be generalized to phase spaces of some other complex systems.

Wave computation on the Poincaré dodecahedral space

NASA Astrophysics Data System (ADS)

Bachelot-Motet, Agnès

2013-12-01

We compute the waves propagating on a compact 3-manifold of constant positive curvature with a non-trivial topology: the Poincaré dodecahedral space that is a plausible model of multi-connected universe. We transform the Cauchy problem to a mixed problem posed on a fundamental domain determined by the quaternionic calculus. We adopt a variational approach using a space of finite elements that is invariant under the action of the binary icosahedral group. The computation of the transient waves is validated with their spectral analysis by computing a lot of eigenvalues of the Laplace-Beltrami operator.

Predicting protein instability in sustained protein delivery systems using spectral-phase interference.

PubMed

Seidel, Nina; Sitterberg, Johannes; Vornholt, Wolfgang; Bakowsky, Udo; Keusgen, Michael; Kissel, Thomas

2012-02-01

Biodegradable and non-biodegradable polymers represent promising materials for sustained protein delivery systems. However, structural protein instabilities due to interactions with the polymer surface are often observed. Aim of the present study was to analyze and predict these instabilities by determination of adsorption pattern and extent via biomolecular interaction analysis. A new optical method based on spectral-phase interference successfully demonstrated its suitability for this new application scope. It was characterized in terms of sensitivity, reproducibility and dynamic range using bovine serum albumin (BSA) as model compound. For protein-polymer interaction studies, materials with different wettabilities and zeta potential were selected and successfully applied on the sensor chip: Glass, poly(styrene), poly(lactic acid), poly(lactic-co-glycolic acid), and poly(ethylene carbonate). Concentration dependent adsorption curves revealed two principal adsorption patterns based on the connection between BSA spreading and supply rate. This connection was stronger influenced by polymer hydrophobicity than surface charge. Association, dissociation and binding rate constants in the range from 0.15 to 34.19 × 10(-6) M were obtained. Atomic force microscopy images of the films before and after adsorption confirmed the previous elaborated model. Poly(ethylene carbonate) emerged as highly promising biomaterial for protein delivery due to its favorable adsorption behavior based on low polymer-protein interactions. Copyright © 2011 Elsevier Ltd. All rights reserved.

Construction of multi-scale consistent brain networks: methods and applications.

PubMed

Ge, Bao; Tian, Yin; Hu, Xintao; Chen, Hanbo; Zhu, Dajiang; Zhang, Tuo; Han, Junwei; Guo, Lei; Liu, Tianming

2015-01-01

Mapping human brain networks provides a basis for studying brain function and dysfunction, and thus has gained significant interest in recent years. However, modeling human brain networks still faces several challenges including constructing networks at multiple spatial scales and finding common corresponding networks across individuals. As a consequence, many previous methods were designed for a single resolution or scale of brain network, though the brain networks are multi-scale in nature. To address this problem, this paper presents a novel approach to constructing multi-scale common structural brain networks from DTI data via an improved multi-scale spectral clustering applied on our recently developed and validated DICCCOLs (Dense Individualized and Common Connectivity-based Cortical Landmarks). Since the DICCCOL landmarks possess intrinsic structural correspondences across individuals and populations, we employed the multi-scale spectral clustering algorithm to group the DICCCOL landmarks and their connections into sub-networks, meanwhile preserving the intrinsically-established correspondences across multiple scales. Experimental results demonstrated that the proposed method can generate multi-scale consistent and common structural brain networks across subjects, and its reproducibility has been verified by multiple independent datasets. As an application, these multi-scale networks were used to guide the clustering of multi-scale fiber bundles and to compare the fiber integrity in schizophrenia and healthy controls. In general, our methods offer a novel and effective framework for brain network modeling and tract-based analysis of DTI data.

Spectral properties of four-time fermionic Green's functions

DOE PAGES

Shvaika, A. M.

2016-09-01

The spectral relations for the four-time fermionic Green's functions are derived in the most general case. The terms which correspond to the zero-frequency anomalies, known before only for the bosonic Green's functions, are separated and their connection with the second cumulants of the Boltzmann distribution function is elucidated. Furthermore, the high-frequency expansions of the four-time fermionic Green's functions are provided for different directions in the frequency space.

Spectral properties of four-time fermionic Green's functions

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

Shvaika, A. M.

The spectral relations for the four-time fermionic Green's functions are derived in the most general case. The terms which correspond to the zero-frequency anomalies, known before only for the bosonic Green's functions, are separated and their connection with the second cumulants of the Boltzmann distribution function is elucidated. Furthermore, the high-frequency expansions of the four-time fermionic Green's functions are provided for different directions in the frequency space.

Advanced astigmatism-corrected tandem Wadsworth mounting for small-scale spectral broadband imaging spectrometer.

PubMed

Lei, Yu; Lin, Guan-yu

2013-01-01

Tandem gratings of double-dispersion mount make it possible to design an imaging spectrometer for the weak light observation with high spatial resolution, high spectral resolution, and high optical transmission efficiency. The traditional tandem Wadsworth mounting is originally designed to match the coaxial telescope and large-scale imaging spectrometer. When it is used to connect the off-axis telescope such as off-axis parabolic mirror, it presents lower imaging quality than to connect the coaxial telescope. It may also introduce interference among the detector and the optical elements as it is applied to the short focal length and small-scale spectrometer in a close volume by satellite. An advanced tandem Wadsworth mounting has been investigated to deal with the situation. The Wadsworth astigmatism-corrected mounting condition for which is expressed as the distance between the second concave grating and the imaging plane is calculated. Then the optimum arrangement for the first plane grating and the second concave grating, which make the anterior Wadsworth condition fulfilling each wavelength, is analyzed by the geometric and first order differential calculation. These two arrangements comprise the advanced Wadsworth mounting condition. The spectral resolution has also been calculated by these conditions. An example designed by the optimum theory proves that the advanced tandem Wadsworth mounting performs excellently in spectral broadband.

A jackknife approach to quantifying single-trial correlation between covariance-based metrics undefined on a single-trial basis.

PubMed

Richter, Craig G; Thompson, William H; Bosman, Conrado A; Fries, Pascal

2015-07-01

The quantification of covariance between neuronal activities (functional connectivity) requires the observation of correlated changes and therefore multiple observations. The strength of such neuronal correlations may itself undergo moment-by-moment fluctuations, which might e.g. lead to fluctuations in single-trial metrics such as reaction time (RT), or may co-fluctuate with the correlation between activity in other brain areas. Yet, quantifying the relation between moment-by-moment co-fluctuations in neuronal correlations is precluded by the fact that neuronal correlations are not defined per single observation. The proposed solution quantifies this relation by first calculating neuronal correlations for all leave-one-out subsamples (i.e. the jackknife replications of all observations) and then correlating these values. Because the correlation is calculated between jackknife replications, we address this approach as jackknife correlation (JC). First, we demonstrate the equivalence of JC to conventional correlation for simulated paired data that are defined per observation and therefore allow the calculation of conventional correlation. While the JC recovers the conventional correlation precisely, alternative approaches, like sorting-and-binning, result in detrimental effects of the analysis parameters. We then explore the case of relating two spectral correlation metrics, like coherence, that require multiple observation epochs, where the only viable alternative analysis approaches are based on some form of epoch subdivision, which results in reduced spectral resolution and poor spectral estimators. We show that JC outperforms these approaches, particularly for short epoch lengths, without sacrificing any spectral resolution. Finally, we note that the JC can be applied to relate fluctuations in any smooth metric that is not defined on single observations. Copyright © 2015. Published by Elsevier Inc.

Detection of the Spermicide Nonoxynol-9 Via GC-MS

NASA Astrophysics Data System (ADS)

Musah, Rabi A.; Vuong, Angela L.; Henck, Colin; Shepard, Jason R. E.

2012-05-01

The spermicide nonoxynol-9 is actually a complex mixture of dozens of closely related amphiphilic compounds, and the chemical properties of this assortment significantly hamper its characterization by GC-MS. The inability to perform routine GC-MS testing on nonoxynol-9 has limited its evidentiary value in forensic casework, which relies heavily on this technique for analysis. A disturbing trend in sexual assault is the use of condoms by assailants, to avoid leaving behind DNA evidence that can connect a perpetrator to a victim. This observation necessitates the development of alternative methods for the analysis of trace evidence that can show causal links between a victim and a suspect. Detection of lubricants associated with sexual assault is one such way to establish this connection. The development of GC-MS methods that permit facile detection of both nonoxynol-9 alone and nonoxynol-9 extracted from other complex matrices that have potential as trace evidence in sexual assault is reported. A detection limit of 2.14 μg of nonoxynol-9 is demonstrated, and a detailed mass spectral profile that elaborates on what is known of its structure is provided.

Social network analysis of character interaction in the Stargate and Star Trek television series

NASA Astrophysics Data System (ADS)

Tan, Melody Shi Ai; Ujum, Ephrance Abu; Ratnavelu, Kuru

This paper undertakes a social network analysis of two science fiction television series, Stargate and Star Trek. Television series convey stories in the form of character interaction, which can be represented as “character networks”. We connect each pair of characters that exchanged spoken dialogue in any given scene demarcated in the television series transcripts. These networks are then used to characterize the overall structure and topology of each series. We find that the character networks of both series have similar structure and topology to that found in previous work on mythological and fictional networks. The character networks exhibit the small-world effects but found no significant support for power-law. Since the progression of an episode depends to a large extent on the interaction between each of its characters, the underlying network structure tells us something about the complexity of that episode’s storyline. We assessed the complexity using techniques from spectral graph theory. We found that the episode networks are structured either as (1) closed networks, (2) those containing bottlenecks that connect otherwise disconnected clusters or (3) a mixture of both.

EEG Functional Connectivity Prior to Sleepwalking: Evidence of Interplay Between Sleep and Wakefulness.

PubMed

Desjardins, Marie-Ève; Carrier, Julie; Lina, Jean-Marc; Fortin, Maxime; Gosselin, Nadia; Montplaisir, Jacques; Zadra, Antonio

2017-04-01

Although sleepwalking (somnambulism) affects up to 4% of adults, its pathophysiology remains poorly understood. Sleepwalking can be preceded by fluctuations in slow-wave sleep EEG signals, but the significance of these pre-episode changes remains unknown and methods based on EEG functional connectivity have yet to be used to better comprehend the disorder. We investigated the sleep EEG of 27 adult sleepwalkers (mean age: 29 ± 7.6 years) who experienced a somnambulistic episode during slow-wave sleep. The 20-second segment of sleep EEG immediately preceding each patient's episode was compared with the 20-second segment occurring 2 minutes prior to episode onset. Results from spectral analyses revealed increased delta and theta spectral power in the 20 seconds preceding the episodes' onset as compared to the 20 seconds occurring 2 minutes before the episodes. The imaginary part of the coherence immediately prior to episode onset revealed (1) decreased delta EEG functional connectivity in parietal and occipital regions, (2) increased alpha connectivity over a fronto-parietal network, and (3) increased beta connectivity involving symmetric inter-hemispheric networks implicating frontotemporal, parietal and occipital areas. Taken together, these modifications in EEG functional connectivity suggest that somnambulistic episodes are preceded by brain processes characterized by the co-existence of arousal and deep sleep. © Sleep Research Society 2017. Published by Oxford University Press on behalf of the Sleep Research Society. All rights reserved. For permissions, please e-mail journals.permissions@oup.com.

Soliton structure versus singularity analysis: Third-order completely intergrable nonlinear differential equations in 1 + 1-dimensions

NASA Astrophysics Data System (ADS)

Fuchssteiner, Benno; Carillo, Sandra

1989-01-01

Bäcklund transformations between all known completely integrable third-order differential equations in (1 + 1)-dimensions are established and the corresponding transformations formulas for their hereditary operators and Hamiltonian formulations are exhibited. Some of these Bäcklund transformations are not injective; therefore additional non-commutative symmetry groups are found for some equations. These non-commutative symmetry groups are classified as having a semisimple part isomorphic to the affine algebra A(1)1. New completely integrable third-order integro-differential equations, some depending explicitly on x, are given. These new equations give rise to nonin equation. Connections between the singularity equations (from the Painlevé analysis) and the nonlinear equations for interacting solitons are established. A common approach to singularity analysis and soliton structure is introduced. The Painlevé analysis is modified in such a sense that it carries over directly and without difficulty to the time evolution of singularity manifolds of equations like the sine-Gordon and nonlinear Schrödinger equation. A method to recover the Painlevé series from its constant level term is exhibit. The soliton-singularity transform is recognized to be connected to the Möbius group. This gives rise to a Darboux-like result for the spectral properties of the recursion operator. These connections are used in order to explain why poles of soliton equations move like trajectories of interacting solitons. Furthermore it is explicitly computed how solitons of singularity equations behave under the effect of this soliton-singularity transform. This then leads to the result that only for scaling degrees α = -1 and α = -2 the usual Painlevé analysis can be carried out. A new invariance principle, connected to kernels of differential operators is discovered. This new invariance, for example, connects the explicit solutions of the Liouville equation with the Miura transform. Simple methods are exhibited which allow to compute out of N-soliton solutions of the KdV (Bargman potentials) explicit solutions of equations like the Harry Dym equation. Certain solutions are plotted.

Hamiltonian indices and rational spectral densities

NASA Technical Reports Server (NTRS)

Byrnes, C. I.; Duncan, T. E.

1980-01-01

Several (global) topological properties of various spaces of linear systems, particularly symmetric, lossless, and Hamiltonian systems, and multivariable spectral densities of fixed McMillan degree are announced. The study is motivated by a result asserting that on a connected but not simply connected manifold, it is not possible to find a vector field having a sink as its only critical point. In the scalar case, this is illustrated by showing that only on the space of McMillan degree = /Cauchy index/ = n, scalar transfer functions can one define a globally convergent vector field. This result holds both in discrete-time and for the nonautonomous case. With these motivations in mind, theorems of Bochner and Fogarty are used in showing that spaces of transfer functions defined by symmetry conditions are, in fact, smooth algebraic manifolds.

Graph theoretical analysis of complex networks in the brain

PubMed Central

Stam, Cornelis J; Reijneveld, Jaap C

2007-01-01

Since the discovery of small-world and scale-free networks the study of complex systems from a network perspective has taken an enormous flight. In recent years many important properties of complex networks have been delineated. In particular, significant progress has been made in understanding the relationship between the structural properties of networks and the nature of dynamics taking place on these networks. For instance, the 'synchronizability' of complex networks of coupled oscillators can be determined by graph spectral analysis. These developments in the theory of complex networks have inspired new applications in the field of neuroscience. Graph analysis has been used in the study of models of neural networks, anatomical connectivity, and functional connectivity based upon fMRI, EEG and MEG. These studies suggest that the human brain can be modelled as a complex network, and may have a small-world structure both at the level of anatomical as well as functional connectivity. This small-world structure is hypothesized to reflect an optimal situation associated with rapid synchronization and information transfer, minimal wiring costs, as well as a balance between local processing and global integration. The topological structure of functional networks is probably restrained by genetic and anatomical factors, but can be modified during tasks. There is also increasing evidence that various types of brain disease such as Alzheimer's disease, schizophrenia, brain tumours and epilepsy may be associated with deviations of the functional network topology from the optimal small-world pattern. PMID:17908336

The transformation of organic carbon during river-groundwater exchange: An example from the Murray-Darling Basin

NASA Astrophysics Data System (ADS)

Keshavarzi, M.; Baker, A.; Andersen, M. S.; Kelly, B. F. J.

2016-12-01

Groundwater systems connected to rivers can act as carbon sinks and sources, but little is known about the distribution, transformation, and retention of organic carbon in rivers connected to aquifers as few studies are available. The characterisation of dissolved organic matter (DOM) using optical absorbance in connected water systems has potential to provide novel insights about the organic component of carbon fluxes. Here, the optical absorbance of the river and groundwater samples is investigated in a river reach that is hydraulically connected to an adjoining alluvial and karst aquifer system, within a semi-arid agricultural catchment in New South Wales, Australia. Water samples were collected from the river and groundwater within monitoring boreholes and intercepted by caves. These water samples were analysed for absorbance, dissolved organic carbon (DOC) and inorganic chemical constituents. Groundwater samples collected close to the river have DOM characteristics similar to the river water, indicating losing conditions. While, groundwater samples collected further away from the river have lower DOC and absorbance, higher SUVA, and a lower and more variable spectral slope, compared to the river. We infer that this change in DOM character reveals the presence of sedimentary OM, which provides a source of relatively high molecular weight DOM that is subsequently transformed. In a dry period, when there was low flow in the river, three downstream river-water samples exhibited low absorbance and spectral slope similar to the groundwater, while the contemporaneous upstream river-water samples had higher absorbance and spectral slope. This suggests gaining conditions and a contribution of groundwater organic carbon into the river. It is concluded that optical analyses can be used to study organic carbon fluxes to differentiate and quantify the source of organic matter, and identify losing and gaining streams.

On the equivalence of some spectral sequences for Serre fibrations

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

Onishchenko, Aleksandr Yu; Popelenskii, Fedor Yu

2011-04-30

Several different constructions of a spectral sequence for a Serre fibration {pi}:E{yields}B over a compact simply connected manifold B are considered in this paper. Namely, we consider the spectral sequence for the minimal model ({Lambda}Vx{Lambda}W,d) of the fibration, along with the spectral sequences arising from the Cech filtration in the complexes C*(U,A*{sub PL}({pi}{sup -1}(U))) and C*(U,S*({pi}{sup -1}(U))), where U=(U) is a covering of the base B. It is known that all these spectral sequences have the same terms E{sub 2}*{sup ,}*=H*(X)xH{sup *}(F) and converge to the cohomology of the total space E. A new natural isomorphism of these spectral sequencesmore » is constructed in every term E{sub r} with r{>=}2. It is also proved that in the case of a smooth locally trivial fibration these spectral sequences are isomorphic to the spectral sequences of the complex of smooth forms {Omega}*(E) and of the Cech-de Rham complex. It is therefore established that all these constructions give the same spectral sequence, starting from the E{sub 2} term. Bibliography: 9 titles.« less

On the equivalence of some spectral sequences for Serre fibrations

NASA Astrophysics Data System (ADS)

Onishchenko, Aleksandr Yu; Popelenskii, Fedor Yu

2011-04-01

Several different constructions of a spectral sequence for a Serre fibration \\pi\\colon E \\to B over a compact simply connected manifold B are considered in this paper. Namely, we consider the spectral sequence for the minimal model (\\Lambda V\\otimes \\Lambda W,d) of the fibration, along with the spectral sequences arising from the Čech filtration in the complexes \\check{C}^*(\\mathscr{U}, A_{PL}^*(\\pi^{-1}(U))) and \\check{C}^*(\\mathscr{U}, S^*(\\pi^{-1}(U))), where \\mathscr{U}=\\{U\\} is a covering of the base B. It is known that all these spectral sequences have the same terms E_2^{*,*}=H^*(X)\\otimes H^*(F) and converge to the cohomology of the total space E. A new natural isomorphism of these spectral sequences is constructed in every term E_r with r\\ge2. It is also proved that in the case of a smooth locally trivial fibration these spectral sequences are isomorphic to the spectral sequences of the complex of smooth forms \\Omega^*(E) and of the Čech-de Rham complex. It is therefore established that all these constructions give the same spectral sequence, starting from the E_2 term. Bibliography: 9 titles.

Agile Robust Autonomy: Inspired by Connecting Natural Flight and Biological Sensors

DTIC Science & Technology

2017-03-01

stabilization in insects while tethered. The stimulating is a rotating horizon line produced by UV and green LEDs (Figure 2). DISTRIBUTION A 12...recordings from the eyes. In the damselflies, we recorded from the compound eyes. The stimulation is a xenon light lamp producing light from the UV to near...addition to a green LED . One green light LED recording was taken after each spectral measurement. ............... 29 24. KHILS Projector Spectral

Spectral gain measurements of quantum confined emitters, and design and fabrication of intersubband quantum box laser structures

NASA Astrophysics Data System (ADS)

Tsvid, Gene

Semiconductor laser active regions are commonly characterized by photo- and electro-luminescence (PL, EL) and cavity length analysis. However quantitative spectral information is not readily extracted from PL and EL data and comparison of different active region materials can be difficult. More quantifiable spectral information is contained in the optical gain spectra. This work reports on spectral gain studies, using multi-segmented interband devices, of InGaAs quantum well and quantum dot active regions grown by metalorganic chemical vapor deposition (MOCVD). Using the fundamental connection between gain and spontaneous emission spectra, the spontaneous radiative current and spontaneous radiative efficiency is evaluated for these active regions. The spectral gain and spontaneous radiative efficiency measurements of 980 nm emitting InGaAs quantum well (QW) material provides a benchmark comparison to previous results obtained on highly-strained, 1200 nm emitting InGaAs QW material. These studies provide insight into carrier recombination and the role of the current injection efficiency in InGaAs QW lasers. The spectral gain of self-assembled MOCVD grown InGaAs quantum dots (QD) active regions are also investigated, allowing for comparison to InGaAs QW material. The second part of my talk will cover intersubband-transition QW and quantum-box (QB) lasers. Quantum cascade (QC) lasers have emerged as compact and technologically important light sources in the mid-infrared (IR) and far-IR wavelength ranges infringing on the near-IR and terahertz spectral regions respectively. However, the overall power conversion efficiency, so-called wallplug efficiency, of the best QC lasers, emitting around 5 microns, is ˜9% in CW operation and very unlikely to exceed 15%. In order to dramatically improve the wallplug efficiency of mid-IR lasers (i.e., to about 50%), intersubband QB (IQB) lasers have been proposed. The basic idea, the optimal design and the progress towards the fabrication of IQB lasers will be presented.

An-integrated seismic approach to de-risk hydrocarbon accumulation for Pliocene deep marine slope channels, offshore West Nile Delta, Egypt

NASA Astrophysics Data System (ADS)

Othman, Adel A. A.; Bakr, Ali; Maher, Ali

2017-12-01

The Nile Delta basin is a hydrocarbon rich province that has hydrocarbon accumulations generated from biogenic and thermogenic source rocks and trapped in a clastic channel reservoirs ranging in age from Pliocene to Early Cretaceous. Currently, the offshore Nile Delta is the most active exploration and development province in Egypt. The main challenge of the studied area is that we have only one well in a channel system exceeds fifteen km length, where seismic reservoir characterization is used to de-risk development scenarios for the field by discriminating between gas sand, water sand and shale. Extracting the gas-charged geobody from the seismic data is magnificent input for 3D reservoir static modelling. Seismic data, being non-stationary in nature, have varying frequency content in time. Spectral decomposition analysis unravels the seismic signal into its initial constituent frequencies. Frequency decomposition of a seismic signal aims to characterize the time-dependent frequency response of subsurface rocks and reservoirs for imaging and mapping of bed thickness, geologic discontinuities and channel connectivity. Inversion feasibility study using crossplot between P-wave impedance (Ip) and S-wave impedance (Is) which derived from well logs (P-wave velocity, S-wave velocity and density) is applied to investigate which inversion type would be sufficient enough to discriminate between gas sand, water sand and shale. Integration between spectral analysis, inversion results and Ip vs. Is crossplot cutoffs help to generate 3D lithofacies cubes, which used to extract gas sand and water sand geobodies, which is extremely wonderful for constructing facies depositional static model in area with unknown facies distribution and sand connectivity. Therefore de-risking hydrocarbon accumulation and GIIP estimation for the field became more confident for drilling new development wells.

XRD, vibrational spectra and quantum chemical studies of an anticancer drug: 6-Mercaptopurine.

PubMed

Kumar, S Suresh; Athimoolam, S; Sridhar, B

2015-07-05

The single crystal of the hydrated anticancer drug, 6-Mercaptopurine (6-MP), has been grown by slow evaporation technique under room temperature. The structure was determined by single crystal X-ray diffraction. The vibrational spectral analysis was carried out using Laser Raman and FT-IR spectroscopy in the range of 3300-100 and 4000-400 cm(-1). The single crystal X-ray studies shows that the crystal packing is dominated by N-H⋯O and O-H⋯N classical hydrogen bonds leading to a hydrogen bonded ensemble. This classical hydrogen bonds were further connected through O-H⋯S hydrogen bond to form two primary ring R4(4)(16) and R4(4)(12) motifs. These two primary ring motifs are interlinked with each other to build a ladder like structure. These ladders are connected through N-H⋯N hydrogen bond along c-axis of the unit cell through chain C(5) motifs. Further, the strength of the hydrogen bonds is studied through vibrational spectral measurements. The shifting of bands due to the intermolecular interactions was also analyzed in the solid crystalline state. Geometrical optimizations of the drug molecule were done by Density Functional Theory (DFT) using the B3LYP function and Hartree-Fock (HF) level with 6-311++G(d,p) basis set. The optimized molecular geometry and computed vibrational spectra are compared with experimental results which show significant agreement. The natural bond orbital (NBO) analysis was carried out to interpret hyperconjugative interaction and intramolecular charge transfer (ICT). The chemical hardness, electro-negativity and chemical potential of the molecule are carried out by HOMO-LUMO plot. In which, the frontier orbitals has lower band gap value indicating the possible pharmaceutical activity of the molecule. Copyright © 2015 Elsevier B.V. All rights reserved.

Orthostatic Intolerance and Postural Orthostatic Tachycardia Syndrome in Joint Hypermobility Syndrome/Ehlers-Danlos Syndrome, Hypermobility Type: Neurovegetative Dysregulation or Autonomic Failure?

PubMed

Celletti, Claudia; Camerota, Filippo; Castori, Marco; Censi, Federica; Gioffrè, Laura; Calcagnini, Giovanni; Strano, Stefano

2017-01-01

Background . Joint hypermobility syndrome/Ehlers-Danlos syndrome, hypermobility type (JHS/EDS-HT), is a hereditary connective tissue disorder mainly characterized by generalized joint hypermobility, skin texture abnormalities, and visceral and vascular dysfunctions, also comprising symptoms of autonomic dysfunction. This study aims to further evaluate cardiovascular autonomic involvement in JHS/EDS-HT by a battery of functional tests. Methods . The response to cardiovascular reflex tests comprising deep breathing, Valsalva maneuver, 30/15 ratio, handgrip test, and head-up tilt test was studied in 35 JHS/EDS-HT adults. Heart rate and blood pressure variability was also investigated by spectral analysis in comparison to age and sex healthy matched group. Results . Valsalva ratio was normal in all patients, but 37.2% of them were not able to finish the test. At tilt, 48.6% patients showed postural orthostatic tachycardia, 31.4% orthostatic intolerance, 20% normal results. Only one patient had orthostatic hypotension. Spectral analysis showed significant higher baroreflex sensitivity values at rest compared to controls. Conclusions. This study confirms the abnormal cardiovascular autonomic profile in adults with JHS/EDS-HT and found the higher baroreflex sensitivity as a potential disease marker and clue for future research.

Using RIXS to uncover elementary charge and spin excitations

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

Jia, Chunjing; Wohlfeld, Krzysztof; Wang, Yao

2016-05-13

Despite significant progress in resonant inelastic x-ray scattering (RIXS) experiments on cuprates at the Cu L-edge, a theoretical understanding of the cross section remains incomplete in terms of elementary excitations and the connection to both charge and spin structure factors. Here, we use state-of-the-art, unbiased numerical calculations to study the low-energy excitations probed by RIXS in the Hubbard model, relevant to the cuprates. The results highlight the importance of scattering geometry, in particular, both the incident and scattered x-ray photon polarization, and they demonstrate that on a qualitative level the RIXS spectral shape in the cross-polarized channel approximates that ofmore » the spin dynamical structure factor. Furthermore, in the parallel-polarized channel, the complexity of the RIXS process beyond a simple two-particle response complicates the analysis and demonstrates that approximations and expansions that attempt to relate RIXS to less complex correlation functions cannot reproduce the full diversity of RIXS spectral features.« less

Voxelwise Spectral Diffusional Connectivity and its Applications to Alzheimer’s Disease and Intelligence Prediction

PubMed Central

Li, Junning; Jin, Yan; Shi, Yonggang; Dinov, Ivo D.; Wang, Danny J.; Toga, Arthur W.; Thompson, Paul M.

2014-01-01

Human brain connectivity can be studied using graph theory. Many connectivity studies parcellate the brain into regions and count fibres extracted between them. The resulting network analyses require validation of the tractography, as well as region and parameter selection. Here we investigate whole brain connectivity from a different perspective. We propose a mathematical formulation based on studying the eigenvalues of the Laplacian matrix of the diffusion tensor field at the voxel level. This voxelwise matrix has over a million parameters, but we derive the Kirchhoff complexity and eigen-spectrum through elegant mathematical theorems, without heavy computation. We use these novel measures to accurately estimate the voxelwise connectivity in multiple biomedical applications such as Alzheimer’s disease and intelligence prediction. PMID:24505723

Adaptable radiation monitoring system and method

DOEpatents

Archer, Daniel E [Livermore, CA; Beauchamp, Brock R [San Ramon, CA; Mauger, G Joseph [Livermore, CA; Nelson, Karl E [Livermore, CA; Mercer, Michael B [Manteca, CA; Pletcher, David C [Sacramento, CA; Riot, Vincent J [Berkeley, CA; Schek, James L [Tracy, CA; Knapp, David A [Livermore, CA

2006-06-20

A portable radioactive-material detection system capable of detecting radioactive sources moving at high speeds. The system has at least one radiation detector capable of detecting gamma-radiation and coupled to an MCA capable of collecting spectral data in very small time bins of less than about 150 msec. A computer processor is connected to the MCA for determining from the spectral data if a triggering event has occurred. Spectral data is stored on a data storage device, and a power source supplies power to the detection system. Various configurations of the detection system may be adaptably arranged for various radiation detection scenarios. In a preferred embodiment, the computer processor operates as a server which receives spectral data from other networked detection systems, and communicates the collected data to a central data reporting system.

Establishing a direct connection between detrended fluctuation analysis and Fourier analysis

NASA Astrophysics Data System (ADS)

Kiyono, Ken

2015-10-01

To understand methodological features of the detrended fluctuation analysis (DFA) using a higher-order polynomial fitting, we establish the direct connection between DFA and Fourier analysis. Based on an exact calculation of the single-frequency response of the DFA, the following facts are shown analytically: (1) in the analysis of stochastic processes exhibiting a power-law scaling of the power spectral density (PSD), S (f ) ˜f-β , a higher-order detrending in the DFA has no adverse effect in the estimation of the DFA scaling exponent α , which satisfies the scaling relation α =(β +1 )/2 ; (2) the upper limit of the scaling exponents detectable by the DFA depends on the order of polynomial fit used in the DFA, and is bounded by m +1 , where m is the order of the polynomial fit; (3) the relation between the time scale in the DFA and the corresponding frequency in the PSD are distorted depending on both the order of the DFA and the frequency dependence of the PSD. We can improve the scale distortion by introducing the corrected time scale in the DFA corresponding to the inverse of the frequency scale in the PSD. In addition, our analytical approach makes it possible to characterize variants of the DFA using different types of detrending. As an application, properties of the detrending moving average algorithm are discussed.

Time Series Analysis of SOLSTICE Measurements

NASA Astrophysics Data System (ADS)

Wen, G.; Cahalan, R. F.

2003-12-01

Solar radiation is the major energy source for the Earth's biosphere and atmospheric and ocean circulations. Variations of solar irradiance have been a major concern of scientists both in solar physics and atmospheric sciences. A number of missions have been carried out to monitor changes in total solar irradiance (TSI) [see Fröhlich and Lean, 1998 for review] and spectral solar irradiance (SSI) [e.g., SOLSTICE on UARS and VIRGO on SOHO]. Observations over a long time period reveal the connection between variations in solar irradiance and surface magnetic fields of the Sun [Lean1997]. This connection provides a guide to scientists in modeling solar irradiances [e.g., Fontenla et al., 1999; Krivova et al., 2003]. Solar spectral observations have now been made over a relatively long time period, allowing statistical analysis. This paper focuses on predictability of solar spectral irradiance using observed SSI from SOLSTICE . Analysis of predictability is based on nonlinear dynamics using an artificial neural network in a reconstructed phase space [Abarbanel et al., 1993]. In the analysis, we first examine the average mutual information of the observed time series and a delayed time series. The time delay that gives local minimum of mutual information is chosen as the time-delay for phase space reconstruction [Fraser and Swinney, 1986]. The embedding dimension of the reconstructed phase space is determined using the false neighbors and false strands method [Kennel and Abarbanel, 2002]. Subsequently, we use a multi-layer feed-forward network with back propagation scheme [e.g., Haykin, 1994] to model the time series. The predictability of solar irradiance as a function of wavelength is considered. References Abarbanel, H. D. I., R. Brown, J. J. Sidorowich, and L. Sh. Tsimring, Rev. Mod. Phys. 65, 1331, 1993. Fraser, A. M. and H. L. Swinney, Phys. Rev. 33A, 1134, 1986. Fontenla, J., O. R. White, P. Fox, E. H. Avrett and R. L. Kurucz, The Astrophysical Journal, 518, 480-499, 1999. Fröhlich, C. and J. Lean, IAU Symposium 185: New Eyes to See Inside the Sun and Stars, edited by F. L. Deubner, 82-102, Kluwer Academic Publ., Dordrecht, The Netherland, 1998. Haykin, S., 696 pp, Macmillan, New York, 1994. Kennel, M. B. and H. D. I. Abarbanel, Phys. Rev. E 66, 026209, 2002. Krivova, N. A., S. K. Solanki, M. Fligge, and Y. C. Unruh, 399, L1-L4, 2003. Lean, J., Annu. Rev. Astron. Astrophys., 35, 33-67, 1997.

Post-Stroke Longitudinal Alterations of Inter-Hemispheric Correlation and Hemispheric Dominance in Mouse Pre-Motor Cortex

PubMed Central

Panarese, Alessandro; Alia, Claudia; Micera, Silvestro; Caleo, Matteo; Di Garbo, Angelo

2016-01-01

Purpose Limited restoration of function is known to occur spontaneously after an ischemic injury to the primary motor cortex. Evidence suggests that Pre-Motor Areas (PMAs) may “take over” control of the disrupted functions. However, little is known about functional reorganizations in PMAs. Forelimb movements in mice can be driven by two cortical regions, Caudal and Rostral Forelimb Areas (CFA and RFA), generally accepted as primary motor and pre-motor cortex, respectively. Here, we examined longitudinal changes in functional coupling between the two RFAs following unilateral photothrombotic stroke in CFA (mm from Bregma: +0.5 anterior, +1.25 lateral). Methods Local field potentials (LFPs) were recorded from the RFAs of both hemispheres in freely moving injured and naïve mice. Neural signals were acquired at 9, 16 and 23 days after surgery (sub-acute period in stroke animals) through one bipolar electrode per hemisphere placed in the center of RFA, with a ground screw over the occipital bone. LFPs were pre-processed through an efficient method of artifact removal and analysed through: spectral,cross-correlation, mutual information and Granger causality analysis. Results Spectral analysis demonstrated an early decrease (day 9) in the alpha band power in both the RFAs. In the late sub-acute period (days 16 and 23), inter-hemispheric functional coupling was reduced in ischemic animals, as shown by a decrease in the cross-correlation and mutual information measures. Within the gamma and delta bands, correlation measures were already reduced at day 9. Granger analysis, used as a measure of the symmetry of the inter-hemispheric causal connectivity, showed a less balanced activity in the two RFAs after stroke, with more frequent oscillations of hemispheric dominance. Conclusions These results indicate robust electrophysiological changes in PMAs after stroke. Specifically, we found alterations in transcallosal connectivity, with reduced inter-hemispheric functional coupling and a fluctuating dominance pattern. These reorganizations may underlie vicariation of lost functions following stroke. PMID:26752066

Post-Stroke Longitudinal Alterations of Inter-Hemispheric Correlation and Hemispheric Dominance in Mouse Pre-Motor Cortex.

PubMed

Vallone, Fabio; Lai, Stefano; Spalletti, Cristina; Panarese, Alessandro; Alia, Claudia; Micera, Silvestro; Caleo, Matteo; Di Garbo, Angelo

2016-01-01

Limited restoration of function is known to occur spontaneously after an ischemic injury to the primary motor cortex. Evidence suggests that Pre-Motor Areas (PMAs) may "take over" control of the disrupted functions. However, little is known about functional reorganizations in PMAs. Forelimb movements in mice can be driven by two cortical regions, Caudal and Rostral Forelimb Areas (CFA and RFA), generally accepted as primary motor and pre-motor cortex, respectively. Here, we examined longitudinal changes in functional coupling between the two RFAs following unilateral photothrombotic stroke in CFA (mm from Bregma: +0.5 anterior, +1.25 lateral). Local field potentials (LFPs) were recorded from the RFAs of both hemispheres in freely moving injured and naïve mice. Neural signals were acquired at 9, 16 and 23 days after surgery (sub-acute period in stroke animals) through one bipolar electrode per hemisphere placed in the center of RFA, with a ground screw over the occipital bone. LFPs were pre-processed through an efficient method of artifact removal and analysed through: spectral,cross-correlation, mutual information and Granger causality analysis. Spectral analysis demonstrated an early decrease (day 9) in the alpha band power in both the RFAs. In the late sub-acute period (days 16 and 23), inter-hemispheric functional coupling was reduced in ischemic animals, as shown by a decrease in the cross-correlation and mutual information measures. Within the gamma and delta bands, correlation measures were already reduced at day 9. Granger analysis, used as a measure of the symmetry of the inter-hemispheric causal connectivity, showed a less balanced activity in the two RFAs after stroke, with more frequent oscillations of hemispheric dominance. These results indicate robust electrophysiological changes in PMAs after stroke. Specifically, we found alterations in transcallosal connectivity, with reduced inter-hemispheric functional coupling and a fluctuating dominance pattern. These reorganizations may underlie vicariation of lost functions following stroke.

Complex symmetric matrices with strongly stable iterates

NASA Technical Reports Server (NTRS)

Tadmor, E.

1985-01-01

Complex-valued symmetric matrices are studied. A simple expression for the spectral norm of such matrices is obtained, by utilizing a unitarily congruent invariant form. A sharp criterion is provided for identifying those symmetric matrices whose spectral norm is not exceeding one: such strongly stable matrices are usually sought in connection with convergent difference approximations to partial differential equations. As an example, the derived criterion is applied to conclude the strong stability of a Lax-Wendroff scheme.

Multispectral Imaging in Cultural Heritage Conservation

NASA Astrophysics Data System (ADS)

Del Pozo, S.; Rodríguez-Gonzálvez, P.; Sánchez-Aparicio, L. J.; Muñoz-Nieto, A.; Hernández-López, D.; Felipe-García, B.; González-Aguilera, D.

2017-08-01

This paper sums up the main contribution derived from the thesis entitled "Multispectral imaging for the analysis of materials and pathologies in civil engineering, constructions and natural spaces" awarded by CIPA-ICOMOS for its connection with the preservation of Cultural Heritage. This thesis is framed within close-range remote sensing approaches by the fusion of sensors operating in the optical domain (visible to shortwave infrared spectrum). In the field of heritage preservation, multispectral imaging is a suitable technique due to its non-destructive nature and its versatility. It combines imaging and spectroscopy to analyse materials and land covers and enables the use of a variety of different geomatic sensors for this purpose. These sensors collect both spatial and spectral information for a given scenario and a specific spectral range, so that, their smaller storage units save the spectral properties of the radiation reflected by the surface of interest. The main goal of this research work is to characterise different construction materials as well as the main pathologies of Cultural Heritage elements by combining active and passive sensors recording data in different ranges. Conclusions about the suitability of each type of sensor and spectral range are drawn in relation to each particular case study and damage. It should be emphasised that results are not limited to images, since 3D intensity data from laser scanners can be integrated with 2D data from passive sensors obtaining high quality products due to the added value that metric brings to multispectral images.

Analysis of correlated mutations in HIV-1 protease using spectral clustering.

PubMed

Liu, Ying; Eyal, Eran; Bahar, Ivet

2008-05-15

The ability of human immunodeficiency virus-1 (HIV-1) protease to develop mutations that confer multi-drug resistance (MDR) has been a major obstacle in designing rational therapies against HIV. Resistance is usually imparted by a cooperative mechanism that can be elucidated by a covariance analysis of sequence data. Identification of such correlated substitutions of amino acids may be obscured by evolutionary noise. HIV-1 protease sequences from patients subjected to different specific treatments (set 1), and from untreated patients (set 2) were subjected to sequence covariance analysis by evaluating the mutual information (MI) between all residue pairs. Spectral clustering of the resulting covariance matrices disclosed two distinctive clusters of correlated residues: the first, observed in set 1 but absent in set 2, contained residues involved in MDR acquisition; and the second, included those residues differentiated in the various HIV-1 protease subtypes, shortly referred to as the phylogenetic cluster. The MDR cluster occupies sites close to the central symmetry axis of the enzyme, which overlap with the global hinge region identified from coarse-grained normal-mode analysis of the enzyme structure. The phylogenetic cluster, on the other hand, occupies solvent-exposed and highly mobile regions. This study demonstrates (i) the possibility of distinguishing between the correlated substitutions resulting from neutral mutations and those induced by MDR upon appropriate clustering analysis of sequence covariance data and (ii) a connection between global dynamics and functional substitution of amino acids.

Path connectivity based spectral defragmentation in flexible bandwidth networks.

PubMed

Wang, Ying; Zhang, Jie; Zhao, Yongli; Zhang, Jiawei; Zhao, Jie; Wang, Xinbo; Gu, Wanyi

2013-01-28

Optical networks with flexible bandwidth provisioning have become a very promising networking architecture. It enables efficient resource utilization and supports heterogeneous bandwidth demands. In this paper, two novel spectrum defragmentation approaches, i.e. Maximum Path Connectivity (MPC) algorithm and Path Connectivity Triggering (PCT) algorithm, are proposed based on the notion of Path Connectivity, which is defined to represent the maximum variation of node switching ability along the path in flexible bandwidth networks. A cost-performance-ratio based profitability model is given to denote the prons and cons of spectrum defragmentation. We compare these two proposed algorithms with non-defragmentation algorithm in terms of blocking probability. Then we analyze the differences of defragmentation profitability between MPC and PCT algorithms.

Spectroscopic classification of icy satellites of Saturn I: Identification of terrain units on Dione

NASA Astrophysics Data System (ADS)

Scipioni, F.; Tosi, F.; Stephan, K.; Filacchione, G.; Ciarniello, M.; Capaccioni, F.; Cerroni, P.

2013-11-01

Dione is one of the largest and densest icy satellites of Saturn. Its surface shows a marked asymmetry between its leading and trailing hemispheres, the leading side being brighter than the trailing side, which shows regions mantled by a dark veneer whose origin is likely exogenic. In order to identify different terrain units we applied the Spectral Angle Mapper (SAM) classification technique to Dione’s hyperspectral images acquired by the Visual and Infrared Mapping Spectrometer (VIMS) onboard the Cassini Orbiter in the infrared range (0.88-5.12 μm). On a relatively limited portion of the surface of Dione we first identified nine spectral endmembers, corresponding to as many terrain units, which mostly distinguish for water ice abundance and ice grain size. We then used these endmembers in SAM to achieve a comprehensive classification of the entire surface. The analysis of the infrared spectra returned by VIMS shows that different regions of Dione have variations in water ice bands depths, in average ice grain size, and in the concentration of contaminants, such as CO2 and hydrocarbons, which are clearly connected to morphological and geological structures. Generally, the spectral units that classify optically dark terrains are those showing suppressed water ice bands, a finer ice grain size and a higher concentration of carbon dioxide. Conversely, spectral units labeling brighter regions have deeper water ice absorption bands, higher albedo and a smaller concentration of contaminants. We also considered VIMS cubes of the small satellite Helene (one of the two Dione’s trojan moons) and we compared its infrared spectra to those of the spectral units found on Dione. We observe that the closest match between the spectra of the two satellites occurs for one of the youngest and freshest terrain units on Dione: the Creusa crater region.

The spatial structure of magnetospheric plasma disturbance estimated by using magnetic data obtained by SWARM satellites.

NASA Astrophysics Data System (ADS)

Yokoyama, Y.; Iyemori, T.; Aoyama, T.

2017-12-01

Field-aligned currents with various spatial scales flow into and out from high-latitude ionosphere. The magnetic fluctuations observed by LEO satellites along their orbits having period longer than a few seconds can be regarded as the manifestations of spatial structure of field aligned currents.This has been confirmed by using the initial orbital characteristics of 3 SWARM-satellites. From spectral analysis, we evaluated the spectral indices of these magnetic fluctuations and investigated their dependence on regions, such as magnetic latitude and MLT and so on. We found that the spectral indices take quite different values between the regions lower than the equatorward boundary of the auroral oval (around 63 degrees' in magnetic latitude) and the regions higher than that. On the other hands, we could not find the clear MLT dependence. In general, the FACs are believed to be generated in the magnetiospheric plasma sheet and boundary layer, and they flow along the field lines conserving their currents.The theory of FAC generation [e.g., Hasegawa and Sato ,1978] indicates that the FACs are strongly connected with magnetospheric plasma disturbances. Although the spectral indices above are these of spatial structures of the FACs over the ionosphere, by using the theoretical equation of FAC generation, we evaluate the spectral indices of magnetospheric plasma disturbance in FAC's generation regions. Furthermore, by projecting the area of fluctuations on the equatorial plane of magnetosphere (i.e. plasma sheet), we can estimate the spatial structure of magnetospheric plasma disturbance. In this presentation, we focus on the characteristics of disturbance in midnight region and discuss the relations to the substorm.

Auto- and cross-power spectral analysis of dual trap optical tweezer experiments using Bayesian inference.

PubMed

von Hansen, Yann; Mehlich, Alexander; Pelz, Benjamin; Rief, Matthias; Netz, Roland R

2012-09-01

The thermal fluctuations of micron-sized beads in dual trap optical tweezer experiments contain complete dynamic information about the viscoelastic properties of the embedding medium and-if present-macromolecular constructs connecting the two beads. To quantitatively interpret the spectral properties of the measured signals, a detailed understanding of the instrumental characteristics is required. To this end, we present a theoretical description of the signal processing in a typical dual trap optical tweezer experiment accounting for polarization crosstalk and instrumental noise and discuss the effect of finite statistics. To infer the unknown parameters from experimental data, a maximum likelihood method based on the statistical properties of the stochastic signals is derived. In a first step, the method can be used for calibration purposes: We propose a scheme involving three consecutive measurements (both traps empty, first one occupied and second empty, and vice versa), by which all instrumental and physical parameters of the setup are determined. We test our approach for a simple model system, namely a pair of unconnected, but hydrodynamically interacting spheres. The comparison to theoretical predictions based on instantaneous as well as retarded hydrodynamics emphasizes the importance of hydrodynamic retardation effects due to vorticity diffusion in the fluid. For more complex experimental scenarios, where macromolecular constructs are tethered between the two beads, the same maximum likelihood method in conjunction with dynamic deconvolution theory will in a second step allow one to determine the viscoelastic properties of the tethered element connecting the two beads.

Resting-state brain networks revealed by granger causal connectivity in frogs.

PubMed

Xue, Fei; Fang, Guangzhan; Yue, Xizi; Zhao, Ermi; Brauth, Steven E; Tang, Yezhong

2016-10-15

Resting-state networks (RSNs) refer to the spontaneous brain activity generated under resting conditions, which maintain the dynamic connectivity of functional brain networks for automatic perception or higher order cognitive functions. Here, Granger causal connectivity analysis (GCCA) was used to explore brain RSNs in the music frog (Babina daunchina) during different behavioral activity phases. The results reveal that a causal network in the frog brain can be identified during the resting state which reflects both brain lateralization and sexual dimorphism. Specifically (1) ascending causal connections from the left mesencephalon to both sides of the telencephalon are significantly higher than those from the right mesencephalon, while the right telencephalon gives rise to the strongest efferent projections among all brain regions; (2) causal connections from the left mesencephalon in females are significantly higher than those in males and (3) these connections are similar during both the high and low behavioral activity phases in this species although almost all electroencephalograph (EEG) spectral bands showed higher power in the high activity phase for all nodes. The functional features of this network match important characteristics of auditory perception in this species. Thus we propose that this causal network maintains auditory perception during the resting state for unexpected auditory inputs as resting-state networks do in other species. These results are also consistent with the idea that females are more sensitive to auditory stimuli than males during the reproductive season. In addition, these results imply that even when not behaviorally active, the frogs remain vigilant for detecting external stimuli. Copyright © 2016 IBRO. Published by Elsevier Ltd. All rights reserved.

Functional and effective brain connectivity for discrimination between Alzheimer's patients and healthy individuals: A study on resting state EEG rhythms.

PubMed

Blinowska, Katarzyna J; Rakowski, Franciszek; Kaminski, Maciej; De Vico Fallani, Fabrizio; Del Percio, Claudio; Lizio, Roberta; Babiloni, Claudio

2017-04-01

This exploratory study provided a proof of concept of a new procedure using multivariate electroencephalographic (EEG) topographic markers of cortical connectivity to discriminate normal elderly (Nold) and Alzheimer's disease (AD) individuals. The new procedure was tested on an existing database formed by resting state eyes-closed EEG data (19 exploring electrodes of 10-20 system referenced to linked-ear reference electrodes) recorded in 42 AD patients with dementia (age: 65.9years±8.5 standard deviation, SD) and 42 Nold non-consanguineous caregivers (age: 70.6years±8.5 SD). In this procedure, spectral EEG coherence estimated reciprocal functional connectivity while non-normalized directed transfer function (NDTF) estimated effective connectivity. Principal component analysis and computation of Mahalanobis distance integrated and combined these EEG topographic markers of cortical connectivity. The area under receiver operating curve (AUC) indexed the classification accuracy. A good classification of Nold and AD individuals was obtained by combining the EEG markers derived from NDTF and coherence (AUC=86%, sensitivity=0.85, specificity=0.70). These encouraging results motivate a cross-validation study of the new procedure in age- and education-matched Nold, stable and progressing mild cognitive impairment individuals, and de novo AD patients with dementia. If cross-validated, the new procedure will provide cheap, broadly available, repeatable over time, and entirely non-invasive EEG topographic markers reflecting abnormal cortical connectivity in AD patients diagnosed by direct or indirect measurement of cerebral amyloid β and hyperphosphorylated tau peptides. Copyright © 2016 International Federation of Clinical Neurophysiology. Published by Elsevier B.V. All rights reserved.

Moderating effects of music on resting state networks.

PubMed

Kay, Benjamin P; Meng, Xiangxiang; Difrancesco, Mark W; Holland, Scott K; Szaflarski, Jerzy P

2012-04-04

Resting state networks (RSNs) are spontaneous, synchronous, low-frequency oscillations observed in the brains of subjects who are awake but at rest. A particular RSN called the default mode network (DMN) has been shown to exhibit changes associated with neurological disorders such as temporal lobe epilepsy or Alzheimer's disease. Previous studies have also found that differing experimental conditions such as eyes-open versus eyes-closed can produce measurable changes in the DMN. These condition-associated changes have the potential of confounding the measurements of changes in RSNs related to or caused by disease state(s). In this study, we use fMRI measurements of resting-state connectivity paired with EEG measurements of alpha rhythm and employ independent component analysis, undirected graphs of partial spectral coherence, and spatiotemporal regression to investigate the effect of music-listening on RSNs and the DMN in particular. We observed similar patterns of DMN connectivity in subjects who were listening to music compared with those who were not, with a trend toward a more introspective pattern of resting-state connectivity during music-listening. We conclude that music-listening is a valid condition under which the DMN can be studied. Copyright © 2012 Elsevier B.V. All rights reserved.

Spectral mapping tools from the earth sciences applied to spectral microscopy data.

PubMed

Harris, A Thomas

2006-08-01

Spectral imaging, originating from the field of earth remote sensing, is a powerful tool that is being increasingly used in a wide variety of applications for material identification. Several workers have used techniques like linear spectral unmixing (LSU) to discriminate materials in images derived from spectral microscopy. However, many spectral analysis algorithms rely on assumptions that are often violated in microscopy applications. This study explores algorithms originally developed as improvements on early earth imaging techniques that can be easily translated for use with spectral microscopy. To best demonstrate the application of earth remote sensing spectral analysis tools to spectral microscopy data, earth imaging software was used to analyze data acquired with a Leica confocal microscope with mechanical spectral scanning. For this study, spectral training signatures (often referred to as endmembers) were selected with the ENVI (ITT Visual Information Solutions, Boulder, CO) "spectral hourglass" processing flow, a series of tools that use the spectrally over-determined nature of hyperspectral data to find the most spectrally pure (or spectrally unique) pixels within the data set. This set of endmember signatures was then used in the full range of mapping algorithms available in ENVI to determine locations, and in some cases subpixel abundances of endmembers. Mapping and abundance images showed a broad agreement between the spectral analysis algorithms, supported through visual assessment of output classification images and through statistical analysis of the distribution of pixels within each endmember class. The powerful spectral analysis algorithms available in COTS software, the result of decades of research in earth imaging, are easily translated to new sources of spectral data. Although the scale between earth imagery and spectral microscopy is radically different, the problem is the same: mapping material locations and abundances based on unique spectral signatures. (c) 2006 International Society for Analytical Cytology.

Spatial-spectral blood cell classification with microscopic hyperspectral imagery

NASA Astrophysics Data System (ADS)

Ran, Qiong; Chang, Lan; Li, Wei; Xu, Xiaofeng

2017-10-01

Microscopic hyperspectral images provide a new way for blood cell examination. The hyperspectral imagery can greatly facilitate the classification of different blood cells. In this paper, the microscopic hyperspectral images are acquired by connecting the microscope and the hyperspectral imager, and then tested for blood cell classification. For combined use of the spectral and spatial information provided by hyperspectral images, a spatial-spectral classification method is improved from the classical extreme learning machine (ELM) by integrating spatial context into the image classification task with Markov random field (MRF) model. Comparisons are done among ELM, ELM-MRF, support vector machines(SVM) and SVMMRF methods. Results show the spatial-spectral classification methods(ELM-MRF, SVM-MRF) perform better than pixel-based methods(ELM, SVM), and the proposed ELM-MRF has higher precision and show more accurate location of cells.

UV Spectroscopy of Lucy Mission Targets

NASA Astrophysics Data System (ADS)

Thomas, Cristina

2017-08-01

The Trojan asteroids are a significant population of primitive bodies trapped in Jupiter's stable L4 and L5 Lagrange regions. Their physical properties and existence in these particular orbits constrain the chemical and dynamical processes in our early Solar System. NASA's recently selected Lucy mission will perform the first reconnaissance of these asteroids and will answer many fundamental questions about the population. The compositions of the Trojans are not well understood. Spectroscopy and spectrophotometry in visible and near-infrared wavelengths show red slopes (spectra with reflectivity increasing towards the long wavelength end of the spectrum) and no diagnostic spectral absorption features. However, past spectral and photometric observations suggest there are unobserved features in ultraviolet wavelengths. We propose to obtain ultraviolet spectroscopy with WFC3 of four Trojan asteroids that are targets of the Lucy mission. Lucy will not have the capability to obtain ultraviolet spectra. The proposed observations can only be made using Hubble. We will determine if there are UV spectral features, as suggested by visible wavelength observations, and connect these features to candidate compositional components. These observations will enable connections between the compositions of Trojans and dynamical models of the early Solar System.

Generalized intermediate long-wave hierarchy in zero-curvature representation with noncommutative spectral parameter

NASA Astrophysics Data System (ADS)

Degasperis, A.; Lebedev, D.; Olshanetsky, M.; Pakuliak, S.; Perelomov, A.; Santini, P. M.

1992-11-01

The simplest generalization of the intermediate long-wave hierarchy (ILW) is considered to show how to extend the Zakharov-Shabat dressing method to nonlocal, i.e., integro-partial differential, equations. The purpose is to give a procedure of constructing the zero-curvature representation of this class of equations. This result obtains by combining the Drinfeld-Sokolov formalism together with the introduction of an operator-valued spectral parameter, namely, a spectral parameter that does not commute with the space variable x. This extension provides a connection between the ILWk hierarchy and the Saveliev-Vershik continuum graded Lie algebras. In the case of ILW2 the Fairlie-Zachos sinh-algebra was found.

Matrix Sturm-Liouville equation with a Bessel-type singularity on a finite interval

NASA Astrophysics Data System (ADS)

Bondarenko, Natalia

2017-03-01

The matrix Sturm-Liouville equation on a finite interval with a Bessel-type singularity in the end of the interval is studied. Special fundamental systems of solutions for this equation are constructed: analytic Bessel-type solutions with the prescribed behavior at the singular point and Birkhoff-type solutions with the known asymptotics for large values of the spectral parameter. The asymptotic formulas for Stokes multipliers, connecting these two fundamental systems of solutions, are derived. We also set boundary conditions and obtain asymptotic formulas for the spectral data (the eigenvalues and the weight matrices) of the boundary value problem. Our results will be useful in the theory of direct and inverse spectral problems.

Oxidation Resistance, Electrical and Thermal Conductivity, and Spectral Emittance of Fully Dense HfB2 and ZrB2 with SiC, TaSi2, and LaB6 Additives

DTIC Science & Technology

2012-01-26

Resistance , Electrical and Thermal Conductivity, and Spectral Emittance of Fully Dense HfB2 and ZrB2 "With SiC, TaSi2, and LaB6 Additives Sb. GRANT NUMBER... RESISTANCE , ELECTRICAL AND THERMAL CONDUCTIVITY, AND SPECTRAL EMITTANCE OF FULLY DENSE HfB2 AND ZrB2 WITH SiC, TaSi2, AND LaB6 ADDITIVES Air Force Office...thickened regions with dry 220 grit SiC sandpaper so that a low- resistance electrical connection could be achieved. A handheld multimeter was used to measure

A study of core Thomson scattering measurements in ITER using a multi-laser approach

NASA Astrophysics Data System (ADS)

Kurskiev, G. S.; Sdvizhenskii, P. A.; Bassan, M.; Andrew, P.; Bazhenov, A. N.; Bukreev, I. M.; Chernakov, P. V.; Kochergin, M. M.; Kukushkin, A. B.; Kukushkin, A. S.; Mukhin, E. E.; Razdobarin, A. G.; Samsonov, D. S.; Semenov, V. V.; Tolstyakov, S. Yu.; Kajita, S.; Masyukevich, S. V.

2015-05-01

The electron component is the main channel for anomalous power loss and the main indicator of transient processes in the tokamak plasma. The electron temperature and density profiles mainly determine the operational mode of the machine. This imposes demanding requirements on the precision and on the spatial and temporal resolution of the Thomson scattering (TS) measurements. Measurements of such high electron temperature with good accuracy in a large fusion device such as ITER using TS encounter a number of physical problems. The 40 keV TS spectrum has a significant blue shift. Due to the transmission functions of the fibres and to their darkening that can occur under a strong neutron irradiation, the operational wavelength range is bounded on the blue side. For example, high temperature measurements become impossible with the 1064 nm probing wavelength since the TS signal within the boundaries of the operational window weakly depends on Te. The second problem is connected with the TS calibration. The TS system for a large fusion machine like ITER will have a set of optical components inaccessible for maintenance, and their spectral characteristics may change with time. Since the present concept of the TS system for ITER relies on the classical approach to measuring the shape of the scattered spectra using wide spectral channels, the diagnostic will be very sensitive to the changes in the optical transmission. The third complication is connected with the deviation of the electron velocity distribution function from a Maxwellian that can happen under a strong ECRH/ECCD, and it may additionally hamper the measurements. This paper analyses the advantages of a ‘multi-laser approach’ implementation for the current design of the core TS system. Such an approach assumes simultaneous plasma probing with different wavelengths that allows the measurement accuracy to be improved significantly and to perform the spectral calibration of the TS system. Comparative analysis of the conservative and advanced approaches is given.

Retrieval of sea ice thickness during Arctic summer using melt pond color

NASA Astrophysics Data System (ADS)

Istomina, L.; Nicolaus, M.; Heygster, G.

2016-12-01

The thickness of sea ice is an important climatic variable. Together with the ice concentration, it defines the total sea ice volume, is linked within the climatic feedback mechanisms and affects the Arctic energy balance greatly. During Arctic summer, the sea ice cover changes rapidly, which includes the presence of melt ponds, as well as reduction of ice albedo and ice thickness. Currently available remote sensing retrievals of sea ice thickness utilize data from altimeter, microwave, thermal infrared sensors and their combinations. All of these methods are compromised in summer in the presence of melt. This only leaves in situ and airborne sea ice thickness data available in summer. At the same time, data of greater coverage is needed for assimilation in global circulation models and correct estimation of ice mass balance.This study presents a new approach to estimate sea ice thickness in summer in the presence of melt ponds. Analysis of field data obtained during the RV "Polarstern" cruise ARK27/3 (August - October 2012) has shown a clear connection of ice thickness under melt ponds to their measured spectral albedo and to melt pond color in the hue-saturation-luminance color space from field photographs. An empirical function is derived from the HSL values and applied to aerial imagery obtained during various airborne campaigns. Comparison to in situ ice thickness shows a good correspondence to the ice thickness value retrieved in the melt ponds. A similar retrieval is developed for satellite spectral bands using the connection of the measured pond spectral albedo to the ice thickness within the melt ponds. Correction of the retrieved ice thickness in ponds to derive total thickness of sea ice is discussed. Case studies and application to very high resolution optical data are presented, as well as a concept to transfer the method to satellite data of lower spatial resolution where melt ponds become subpixel features.

Connecting infrared spectra with plant traits to identify species

NASA Astrophysics Data System (ADS)

Buitrago, Maria F.; Skidmore, Andrew K.; Groen, Thomas A.; Hecker, Christoph A.

2018-05-01

Plant traits are used to define species, but also to evaluate the health status of forests, plantations and crops. Conventional methods of measuring plant traits (e.g. wet chemistry), although accurate, are inefficient and costly when applied over large areas or with intensive sampling. Spectroscopic methods, as used in the food industry and mineralogy, are nowadays applied to identify plant traits, however, most studies analysed visible to near infrared, while infrared spectra of longer wavelengths have been little used for identifying the spectral differences between plant species. This study measured the infrared spectra (1.4-16.0 μm) on individual, fresh leaves of 19 species (from herbaceous to woody species), as well as 14 leaf traits for each leaf. The results describe at which wavelengths in the infrared the leaves' spectra can differentiate most effectively between these plant species. A Quadratic Discrimination Analysis (QDA) shows that using five bands in the SWIR or the LWIR is enough to accurately differentiate these species (Kappa: 0.93, 0.94 respectively), while the MWIR has a lower classification accuracy (Kappa: 0.84). This study also shows that in the infrared spectra of fresh leaves, the identified species-specific features are correlated with leaf traits as well as changes in their values. Spectral features in the SWIR (1.66, 1.89 and 2.00 μm) are common to all species and match the main features of pure cellulose and lignin spectra. The depth of these features varies with changes of cellulose and leaf water content and can be used to differentiate species in this region. In the MWIR and LWIR, the absorption spectra of leaves are formed by key species-specific traits including lignin, cellulose, water, nitrogen and leaf thickness. The connection found in this study between leaf traits, features and spectral signatures are novel tools to assist when identifying plant species by spectroscopy and remote sensing.

Testing the Millennial-Scale Holocene Solar-Climate Connection in the Indo-Pacific Warm Pool

NASA Astrophysics Data System (ADS)

Khider, D.; Emile-Geay, J.; McKay, N.; Jackson, C. S.; Routson, C.

2016-12-01

The existence of 1000 and 2500-year periodicities found in reconstructions of total solar irradiance (TSI) and a number of Holocene climate records has led to the hypothesis of a causal relationship. However, attributing Holocene millennial-scale variability to solar forcing requires a mechanism by which small changes in total irradiance can influence a global climate response. One possible amplifier within the climate system is the ocean. If this is the case, then we need to know more about where and how this may be occurring. On the other hand, the similarity in spectral peaks could be merely coincidental, and this should be made apparent by a lack of coherence in how that power and phasing are distributed in time and space. The plausibility of the solar forcing hypothesis is assessed through a Bayesian model of the age uncertainties affecting marine sedimentary records that is propagated through spectral analysis of the climate and forcing signals at key frequencies. Preliminary work on Mg/Ca and alkenone records from the Indo-Pacific Warm Pool suggests that despite large uncertainties in the location of the spectral peaks within each individual record arising from age model uncertainty, sea surface variability on timescales of 1025±36 years and 2427±133 years (±standard error of the mean of the median periodicity in each record) are present in at least 95% and 70% of the ensemble spectra, respectively. However, we find a long phase delay between the peak in forcing and the maximum response in at least one of the records, challenging the solar forcing hypothesis and requiring further investigation between low- and high-latitude signals. Remarkably, all records suggest a periodicity near 1470±85 years, reminiscent of the cycles characteristic of Marine Isotope Stage 3; these cycles are absent from existing records of TSI, further questioning the millennial solar-climate connection.

Neural basis for brain responses to TV commercials: a high-resolution EEG study.

PubMed

Astolfi, Laura; De Vico Fallani, F; Cincotti, F; Mattia, D; Bianchi, L; Marciani, M G; Salinari, S; Colosimo, A; Tocci, A; Soranzo, R; Babiloni, F

2008-12-01

We investigated brain activity during the observation of TV commercials by tracking the cortical activity and the functional connectivity changes in normal subjects. The aim was to elucidate if the TV commercials that were remembered by the subjects several days after their first observation elicited particular brain activity and connectivity compared with those generated during the observation of TV commercials that were quickly forgotten. High-resolution electroencephalogram (EEG) recordings were performed in a group of healthy subjects and the cortical activity during the observation of TV commercials was evaluated in several regions of interest coincident with the Brodmann areas (BAs). The patterns of cortical connectivity were obtained in the four principal frequency bands, Theta (3-7 Hz), Alpha (8-12 Hz), Beta (13-30 Hz), Gamma (30-40 Hz) and the directed influences between any given pair of the estimated cortical signals were evaluated by use of a multivariate spectral technique known as partial directed coherence. The topology of the cortical networks has been identified with tools derived from graph theory. Results suggest that the cortical activity and connectivity elicited by the viewing of the TV commercials that were remembered by the experimental subjects are markedly different from the brain activity elicited during the observation of the TV commercials that were forgotten. In particular, during the observation of the TV commercials that were remembered, the amount of cortical spectral activity from the frontal areas (BA 8 and 9) and from the parietal areas (BA 5, 7, and 40) is higher compared with the activity elicited by the observation of TV commercials that were forgotten. In addition, network analysis suggests a clear role of the parietal areas as a target of the incoming flow of information from all the other parts of the cortex during the observation of TV commercials that have been remembered. The techniques presented here shed new light on all the cortical networks and their behavior during the memorization of TV commercials. Such techniques could also be relevant in neuroeconomics and neuromarketing for the investigation of the neural substrates subserving other decision-making and recognition tasks.

Synthesis, spectral, thermal and structural characterization of two complexes containing [N-(2-hydroxyethyl)-ethylenediamine] with carboxylate

NASA Astrophysics Data System (ADS)

Aycan, Tuǧba; Paşaoǧlu, Hümeyra

2018-02-01

Compounds based on the [Zn(hydet-en)2].(tpht).(H2O) (1) (tpht=dianion of terephthalic acid, hydet-en=N-(2-hydroxyethyl)ethylenediamine) has been synthesized which is characterized by single crystal X-ray determination, IR and thermal analysis. In 1, the Zinc(II) ion is six-coordinated that sandwiched by two hydet-en ligands which lies each hydeten ligand adopts a tripodal conformation and acts as tridentate ligand, carboxylate is uncoordinated. The coordination monomer is connected by C(13) chains and linear chains are connected by O-H...O H-bonds formed by DA:AD type 4 organization of aqua ligands and tpa2- ions resulting in R44(12 ) synthons to 3D structure. The FT-IR investigation of the complex were performed within the mid-IR region, mainly focusing on the characteristic vibrations of its free state and ligand behaviour in the case of complex formation. Thermal behaviours of 1 were followed using TG, DTA and DTG techniques.

Colorful Niches of Phytoplankton Shaped by the Spatial Connectivity in a Large River Ecosystem: A Riverscape Perspective

PubMed Central

Frenette, Jean-Jacques; Massicotte, Philippe; Lapierre, Jean-François

2012-01-01

Large rivers represent a significant component of inland waters and are considered sentinels and integrators of terrestrial and atmospheric processes. They represent hotspots for the transport and processing of organic and inorganic material from the surrounding landscape, which ultimately impacts the bio-optical properties and food webs of the rivers. In large rivers, hydraulic connectivity operates as a major forcing variable to structure the functioning of the riverscape, and–despite increasing interest in large-river studies–riverscape structural properties, such as the underwater spectral regime, and their impact on autotrophic ecological processes remain poorly studied. Here we used the St. Lawrence River to identify the mechanisms structuring the underwater spectral environment and their consequences on pico- and nanophytoplankton communities, which are good biological tracers of environmental changes. Our results, obtained from a 450 km sampling transect, demonstrate that tributaries exert a profound impact on the receiving river’s photosynthetic potential. This occurs mainly through injection of chromophoric dissolved organic matter (CDOM) and non-algal material (tripton). CDOM and tripton in the water column selectively absorbed wavelengths in a gradient from blue to red, and the resulting underwater light climate was in turn a strong driver of the phytoplankton community structure (prokaryote/eukaryote relative and absolute abundances) at scales of many kilometers from the tributary confluence. Our results conclusively demonstrate the proximal impact of watershed properties on underwater spectral composition in a highly dynamic river environment characterized by unique structuring properties such as high directional connectivity, numerous sources and forms of carbon, and a rapidly varying hydrodynamic regime. We surmise that the underwater spectral composition represents a key integrating and structural property of large, heterogeneous river ecosystems and a promising tool to study autotrophic functional properties. It confirms the usefulness of using the riverscape approach to study large-river ecosystems and initiate comparison along latitudinal gradients. PMID:22558259

Uppermost synchronized generators of spike-wave activity are localized in limbic cortical areas in late-onset absence status epilepticus.

PubMed

Piros, Palma; Puskas, Szilvia; Emri, Miklos; Opposits, Gabor; Spisak, Tamas; Fekete, Istvan; Clemens, Bela

2014-03-01

Absence status (AS) epilepticus with generalized spike-wave pattern is frequently found in severely ill patients in whom several disease states co-exist. The cortical generators of the ictal EEG pattern and EEG functional connectivity (EEGfC) of this condition are unknown. The present study investigated the localization of the uppermost synchronized generators of spike-wave activity in AS. Seven patients with late-onset AS were investigated by EEG spectral analysis, LORETA (Low Resolution Electromagnetic Tomography) source imaging, and LSC (LORETA Source Correlation) analysis, which estimates cortico-cortical EEGfC among 23 ROIs (regions of interest) in each hemisphere. All the patients showed generalized ictal EEG activity. Maximum Z-scored spectral power was found in the 1-6 Hz and 12-14 Hz frequency bands. LORETA showed that the uppermost synchronized generators of 1-6 Hz band activity were localized in frontal and temporal cortical areas that are parts of the limbic system. For the 12-14 Hz band, abnormally synchronized generators were found in the antero-medial frontal cortex. Unlike the rather stereotyped spectral and LORETA findings, the individual EEGfC patterns were very dissimilar. The findings are discussed in the context of nonconvulsive seizure types and the role of the underlying cortical areas in late-onset AS. The diversity of the EEGfC patterns remains an enigma. Localizing the cortical generators of the EEG patterns contributes to understanding the neurophysiology of the condition. Copyright © 2013 British Epilepsy Association. Published by Elsevier Ltd. All rights reserved.

Multi-wavelength Spectral Analysis of Ellerman Bombs Observed by FISS and IRIS

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

Hong, Jie; Ding, M. D.; Cao, Wenda, E-mail: dmd@nju.edu.cn

Ellerman bombs (EBs) are a kind of solar activity that is suggested to occur in the lower solar atmosphere. Recent observations using the Interface Region Imaging Spectrograph (IRIS) show connections between EBs and IRIS bombs (IBs), which imply that EBs might be heated to a much higher temperature (8 × 10{sup 4} K) than previous results. Here we perform a spectral analysis of EBs simultaneously observed by the Fast Imaging Solar Spectrograph and IRIS. The observational results show clear evidence of heating in the lower atmosphere, indicated by the wing enhancement in H α , Ca ii 8542 Å, andmore » Mg ii triplet lines and also by brightenings in images of the 1700 Å and 2832 Å ultraviolet continuum channels. Additionally, the intensity of the Mg ii triplet line is correlated with that of H α when an EB occurs, suggesting the possibility of using the triplet as an alternative way to identify EBs. However, we do not find any signal in IRIS hotter lines (C ii and Si iv). For further analysis, we employ a two-cloud model to fit the two chromospheric lines (H α and Ca ii 8542 Å) simultaneously, and obtain a temperature enhancement of 2300 K for a strong EB. This temperature is among the highest of previous modeling results, albeit still insufficient to produce IB signatures at ultraviolet wavelengths.« less

Programmable hyperspectral image mapper with on-array processing

NASA Technical Reports Server (NTRS)

Cutts, James A. (Inventor)

1995-01-01

A hyperspectral imager includes a focal plane having an array of spaced image recording pixels receiving light from a scene moving relative to the focal plane in a longitudinal direction, the recording pixels being transportable at a controllable rate in the focal plane in the longitudinal direction, an electronic shutter for adjusting an exposure time of the focal plane, whereby recording pixels in an active area of the focal plane are removed therefrom and stored upon expiration of the exposure time, an electronic spectral filter for selecting a spectral band of light received by the focal plane from the scene during each exposure time and an electronic controller connected to the focal plane, to the electronic shutter and to the electronic spectral filter for controlling (1) the controllable rate at which the recording is transported in the longitudinal direction, (2) the exposure time, and (3) the spectral band so as to record a selected portion of the scene through M spectral bands with a respective exposure time t(sub q) for each respective spectral band q.

A Fundamental Study on Spectrum Center Estimation of Solar Spectral Irradiation by the Statistical Pattern Recognition

NASA Astrophysics Data System (ADS)

Iijima, Aya; Suzuki, Kazumi; Wakao, Shinji; Kawasaki, Norihiro; Usami, Akira

With a background of environmental problems and energy issues, it is expected that PV systems will be introduced rapidly and connected with power grids on a large scale in the future. For this reason, the concern to which PV power generation will affect supply and demand adjustment in electric power in the future arises and the technique of correctly grasping the PV power generation becomes increasingly important. The PV power generation depends on solar irradiance, temperature of a module and solar spectral irradiance. Solar spectral irradiance is distribution of the strength of the light for every wavelength. As the spectrum sensitivity of solar cell depends on kind of solar cell, it becomes important for exact grasp of PV power generation. Especially the preparation of solar spectral irradiance is, however, not easy because the observational instrument of solar spectral irradiance is expensive. With this background, in this paper, we propose a new method based on statistical pattern recognition for estimating the spectrum center which is representative index of solar spectral irradiance. Some numerical examples obtained by the proposed method are also presented.

Hybrid least squares multivariate spectral analysis methods

DOEpatents

Haaland, David M.

2002-01-01

A set of hybrid least squares multivariate spectral analysis methods in which spectral shapes of components or effects not present in the original calibration step are added in a following estimation or calibration step to improve the accuracy of the estimation of the amount of the original components in the sampled mixture. The "hybrid" method herein means a combination of an initial classical least squares analysis calibration step with subsequent analysis by an inverse multivariate analysis method. A "spectral shape" herein means normally the spectral shape of a non-calibrated chemical component in the sample mixture but can also mean the spectral shapes of other sources of spectral variation, including temperature drift, shifts between spectrometers, spectrometer drift, etc. The "shape" can be continuous, discontinuous, or even discrete points illustrative of the particular effect.

Causality Analysis of Neural Connectivity: Critical Examination of Existing Methods and Advances of New Methods

PubMed Central

Hu, Sanqing; Dai, Guojun; Worrell, Gregory A.; Dai, Qionghai; Liang, Hualou

2012-01-01

Granger causality (GC) is one of the most popular measures to reveal causality influence of time series and has been widely applied in economics and neuroscience. Especially, its counterpart in frequency domain, spectral GC, as well as other Granger-like causality measures have recently been applied to study causal interactions between brain areas in different frequency ranges during cognitive and perceptual tasks. In this paper, we show that: 1) GC in time domain cannot correctly determine how strongly one time series influences the other when there is directional causality between two time series, and 2) spectral GC and other Granger-like causality measures have inherent shortcomings and/or limitations because of the use of the transfer function (or its inverse matrix) and partial information of the linear regression model. On the other hand, we propose two novel causality measures (in time and frequency domains) for the linear regression model, called new causality and new spectral causality, respectively, which are more reasonable and understandable than GC or Granger-like measures. Especially, from one simple example, we point out that, in time domain, both new causality and GC adopt the concept of proportion, but they are defined on two different equations where one equation (for GC) is only part of the other (for new causality), thus the new causality is a natural extension of GC and has a sound conceptual/theoretical basis, and GC is not the desired causal influence at all. By several examples, we confirm that new causality measures have distinct advantages over GC or Granger-like measures. Finally, we conduct event-related potential causality analysis for a subject with intracranial depth electrodes undergoing evaluation for epilepsy surgery, and show that, in the frequency domain, all measures reveal significant directional event-related causality, but the result from new spectral causality is consistent with event-related time–frequency power spectrum activity. The spectral GC as well as other Granger-like measures are shown to generate misleading results. The proposed new causality measures may have wide potential applications in economics and neuroscience. PMID:21511564

Data Field Modeling and Spectral-Spatial Feature Fusion for Hyperspectral Data Classification.

PubMed

Liu, Da; Li, Jianxun

2016-12-16

Classification is a significant subject in hyperspectral remote sensing image processing. This study proposes a spectral-spatial feature fusion algorithm for the classification of hyperspectral images (HSI). Unlike existing spectral-spatial classification methods, the influences and interactions of the surroundings on each measured pixel were taken into consideration in this paper. Data field theory was employed as the mathematical realization of the field theory concept in physics, and both the spectral and spatial domains of HSI were considered as data fields. Therefore, the inherent dependency of interacting pixels was modeled. Using data field modeling, spatial and spectral features were transformed into a unified radiation form and further fused into a new feature by using a linear model. In contrast to the current spectral-spatial classification methods, which usually simply stack spectral and spatial features together, the proposed method builds the inner connection between the spectral and spatial features, and explores the hidden information that contributed to classification. Therefore, new information is included for classification. The final classification result was obtained using a random forest (RF) classifier. The proposed method was tested with the University of Pavia and Indian Pines, two well-known standard hyperspectral datasets. The experimental results demonstrate that the proposed method has higher classification accuracies than those obtained by the traditional approaches.

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

Liu, Yu-Qian; Modjaz, Maryam; Bianco, Federica B., E-mail: YL1260@nyu.edu, E-mail: mmodjaz@nyu.edu

Super-luminous supernovae (SLSNe) are tremendously luminous explosions whose power sources and progenitors are highly debated. Broad-lined SNe Ic (SNe Ic-bl) are the only type of SNe that are connected with long-duration gamma-ray bursts (GRBs). Studying the spectral similarity and difference between the populations of hydrogen-poor SLSNe (SLSNe Ic) and of hydrogen-poor stripped-envelope core-collapse SNe, in particular SNe Ic and SNe Ic-bl, can provide crucial observations to test predictions of theories based on various power source models and progenitor models. In this paper, we collected all of the published optical spectra of 32 SLSNe Ic, 21 SNe Ic-bl, as well asmore » 17 SNe Ic, quantified their spectral features, constructed average spectra, and compared them in a systematic way using new tools we have developed. We find that SLSNe Ic and SNe Ic-bl, including those connected with GRBs, have comparable widths for their spectral features and average absorption velocities at all phases. Thus, our findings strengthen the connection between SLSNe Ic and GRBs. In particular, SLSNe Ic have average Fe ii λ 5169 absorption velocities of −15,000 ± 2600 km s{sup −1} at 10 days after peak, which are higher than those of SNe Ic by ∼7000 km s{sup −1} on average. SLSNe Ic also have significantly broader Fe ii λ 5169 lines than SNe Ic. Moreover, we find that such high absorption and width velocities of SLSNe Ic may be hard to explain with the interaction model, and none of the 13 SLSNe Ic with measured absorption velocities spanning over 10 days has a convincing flat velocity evolution, which is inconsistent with the magnetar model in one dimension. Lastly, we compare SN 2011kl, the first SN connected with an ultra-long GRB, with the mean spectrum of SLSNe Ic and of SNe Ic-bl.« less

Superpixel Based Factor Analysis and Target Transformation Method for Martian Minerals Detection

NASA Astrophysics Data System (ADS)

Wu, X.; Zhang, X.; Lin, H.

2018-04-01

The Factor analysis and target transformation (FATT) is an effective method to test for the presence of particular mineral on Martian surface. It has been used both in thermal infrared (Thermal Emission Spectrometer, TES) and near-infrared (Compact Reconnaissance Imaging Spectrometer for Mars, CRISM) hyperspectral data. FATT derived a set of orthogonal eigenvectors from a mixed system and typically selected first 10 eigenvectors to least square fit the library mineral spectra. However, minerals present only in a limited pixels will be ignored because its weak spectral features compared with full image signatures. Here, we proposed a superpixel based FATT method to detect the mineral distributions on Mars. The simple linear iterative clustering (SLIC) algorithm was used to partition the CRISM image into multiple connected image regions with spectral homogeneous to enhance the weak signatures by increasing their proportion in a mixed system. A least square fitting was used in target transformation and performed to each region iteratively. Finally, the distribution of the specific minerals in image was obtained, where fitting residual less than a threshold represent presence and otherwise absence. We validate our method by identifying carbonates in a well analysed CRISM image in Nili Fossae on Mars. Our experimental results indicate that the proposed method work well both in simulated and real data sets.

Basaltic material in the main belt: a tale of two (or more) parent bodies?

NASA Astrophysics Data System (ADS)

Ieva, S.; Dotto, E.; Lazzaro, D.; Fulvio, D.; Perna, D.; Epifani, E. Mazzotta; Medeiros, H.; Fulchignoni, M.

2018-06-01

The majority of basaltic objects in the main belt are dynamically connected to Vesta, the largest differentiated asteroid known. Others, due to their current orbital parameters, cannot be easily dynamically linked to Vesta. This is particularly true for all the basaltic asteroids located beyond 2.5 au, where lies the 3:1 mean motion resonance with Jupiter. In order to investigate the presence of other V-type asteroids in the middle and outer main belt (MOVs) we started an observational campaign to spectroscopically characterize in the visible range MOV candidates. We observed 18 basaltic candidates from TNG and ESO - NTT between 2015 and 2016. We derived spectral parameters using the same approach adopted in our recent statistical analysis and we compared our data with orbital parameters to look for possible clusters of MOVs in the main belt, symptomatic for a new basaltic family. Our analysis seemed to point out that MOVs show different spectral parameters respect to other basaltic bodies in the main belt, which could account for a diverse mineralogy than Vesta; moreover, some of them belong to the Eos family, suggesting the possibility of another basaltic progenitor. This could have strong repercussions on the temperature gradient present in the early Solar System, and on our current understanding of differentiation processes.

A catalogue of optical to X-ray spectral energy distributions of z ≈ 2 quasars observed with Swift - I. First results

NASA Astrophysics Data System (ADS)

Lawther, D.; Vestergaard, M.; Raimundo, S.; Grupe, D.

2017-06-01

We present the Swift optical to X-ray spectral energy distributions (SEDs) of 44 quasars at redshifts z ≈ 2 observed by Swift, part of a larger program to establish and characterize the optical through X-ray SEDs of moderate-redshift quasars. Here, we outline our analysis approach and present preliminary analysis and results for the first third of the full quasar sample. Not all quasars in the sample are detected in X-rays; all of the X-ray-detected objects so far are radio loud. As expected for radio-loud objects, they are X-ray bright relative to radio-quiet quasars of comparable optical luminosities, with an average αox =1.39 ± 0.03 (where αox is the power-law slope connecting the monochromatic flux at 2500 Å and at 2 keV), and display hard X-ray spectra. We find integrated 3000 Å-25 keV accretion luminosities of between 0.7 × 1046 erg s-1 and 5.2 × 1047 erg s-1. Based on single-epoch spectroscopic virial black hole mass estimates, we find that these quasars are accreting at substantial Eddington fractions, 0.1 ≲ L/LEdd ≲ 1.

Prefrontal cortex and mediodorsal thalamus reduced connectivity is associated with spatial working memory impairment in rats with inflammatory pain.

PubMed

Cardoso-Cruz, Helder; Sousa, Mafalda; Vieira, Joana B; Lima, Deolinda; Galhardo, Vasco

2013-11-01

The medial prefrontal cortex (mPFC) and the mediodorsal thalamus (MD) form interconnected neural circuits that are important for spatial cognition and memory, but it is not known whether the functional connectivity between these areas is affected by the onset of an animal model of inflammatory pain. To address this issue, we implanted 2 multichannel arrays of electrodes in the mPFC and MD of adult rats and recorded local field potential activity during a food-reinforced spatial working memory task. Recordings were performed for 3weeks, before and after the establishment of the pain model. Our results show that inflammatory pain caused an impairment of spatial working memory performance that is associated with changes in the activity of the mPFC-MD circuit; an analysis of partial directed coherence between the areas revealed a global decrease in the connectivity of the circuit. This decrease was observed over a wide frequency range in both the frontothalamic and thalamofrontal directions of the circuit, but was more evident from MD to mPFC. In addition, spectral analysis revealed significant oscillations of power across frequency bands, namely with a strong theta component that oscillated after the onset of the painful condition. Finally, our data revealed that chronic pain induces an increase in theta/gamma phase coherence and a higher level of mPFC-MD coherence, which is partially conserved across frequency bands. The present results demonstrate that functional disturbances in mPFC-MD connectivity are a relevant cause of deficits in pain-related working memory. Copyright © 2013 International Association for the Study of Pain. Published by Elsevier B.V. All rights reserved.

Resting State Dense Array Gamma Oscillatory Activity as a Response Marker for Cerebellar-Repetitive Transcranial Magnetic Stimulation (rTMS) in Schizophrenia.

PubMed

Tikka, Sai Krishna; Garg, Shobit; Sinha, Vinod Kumar; Nizamie, S Haque; Goyal, Nishant

2015-12-01

As cerebellum and its abnormalities have been implicated in the pathophysiology of schizophrenia, repetitive transcranial magnetic stimulation (rTMS) of this alternate site has been suggested as a novel target for treating patients with this disorder. As resting state gamma activity measures functional brain connectivity, it could be used as a specific treatment marker. To investigate the effect of cerebellar-rTMS on resting state gamma activity, while studying its efficacy in recent onset schizophrenia patients. This rater-blinded prospective study was completed by 11 schizophrenia patients. They received 10 sessions of high-frequency (theta patterned) rTMS to midline cerebellum over 2 weeks. Resting state EEG was recorded using high (192-channel) resolution EEG at baseline and post rTMS. Gamma spectral power was calculated using fast Fourier transformation, Hanning window averaged over 8 scalp segments corresponding 8 lobes. Clinical improvement rated on the Positive and Negative Syndrome Scale and depressive symptoms assessed using the Calgary Depression Scale for Schizophrenia were other outcome variables. Nonparametric statistics were used. Over the treatment course, significant reduction was seen on negative syndrome and depression scores. Gamma spectral power in left frontal and temporal segments reduced significantly. Spearman correlation analysis showed that percentage reduction in psychopathology scores had significant positive correlation with percentage reduction in gamma spectral power. Cerebellar-rTMS might be an effective adjunct to treat intricate and lingering negative and affective symptoms. Resting state gamma spectral power in frontal and temporal regions might be used as a biomarker for treatment response.

Vesta and the HED Meteorites: Comparison of Spectral Properties

NASA Technical Reports Server (NTRS)

Ammannito, E.; De Sanctis, M. C.; Fonte, S.; Magni, G.; Capaccioni, F.; Tosi, F.; Capria, M. T.; Blewett, D.; Combe, J. P.; Farina, M.;

Effect of erythrocyte aggregation on optical transmission of blood

NASA Astrophysics Data System (ADS)

Shvartsman, L. D.; Fine, I.

2007-02-01

We present here a bird-eye view of time-dependent optical transmission of blood in red-near infrared spectral range. This issue is of the key importance both for fundamental understanding and for various applications connected with non-invasive optical blood analysis. A number of experiments measuring kinetics of blood transmission in the case of natural heart pulsations and of artificial kinetics following over-systolic occlusion is reviewed. The comprehensive theoretical approach has to consider scattering-associated mechanism rather than the widely accepted absorption-associated one. Light scattering occurs on RBC aggregates. The size of aggregates and their shape change in time due to blood flow variations. It results in the corresponding changes of optical transmission.

Passive UHF RFID Tag for Multispectral Assessment

PubMed Central

Escobedo, Pablo; Carvajal, Miguel A.; Capitán-Vallvey, Luis F.; Fernández-Salmerón, José; Martínez-Olmos, Antonio; Palma, Alberto J.

2016-01-01

This work presents the design, fabrication, and characterization of a passive printed radiofrequency identification tag in the ultra-high-frequency band with multiple optical sensing capabilities. This tag includes five photodiodes to cover a wide spectral range from near-infrared to visible and ultraviolet spectral regions. The tag antenna and circuit connections have been screen-printed on a flexible polymeric substrate. An ultra-low-power microcontroller-based switch has been included to measure the five magnitudes issuing from the optical sensors, providing a spectral fingerprint of the incident electromagnetic radiation from ultraviolet to infrared, without requiring energy from a battery. The normalization procedure has been designed applying illuminants, and the entire system was tested by measuring cards from a colour chart and sensing fruit ripening. PMID:27428973

Passive UHF RFID Tag for Multispectral Assessment.

PubMed

Escobedo, Pablo; Carvajal, Miguel A; Capitán-Vallvey, Luis F; Fernández-Salmerón, José; Martínez-Olmos, Antonio; Palma, Alberto J

2016-07-14

This work presents the design, fabrication, and characterization of a passive printed radiofrequency identification tag in the ultra-high-frequency band with multiple optical sensing capabilities. This tag includes five photodiodes to cover a wide spectral range from near-infrared to visible and ultraviolet spectral regions. The tag antenna and circuit connections have been screen-printed on a flexible polymeric substrate. An ultra-low-power microcontroller-based switch has been included to measure the five magnitudes issuing from the optical sensors, providing a spectral fingerprint of the incident electromagnetic radiation from ultraviolet to infrared, without requiring energy from a battery. The normalization procedure has been designed applying illuminants, and the entire system was tested by measuring cards from a colour chart and sensing fruit ripening.

Connecting complexity with spectral entropy using the Laplace transformed solution to the fractional diffusion equation

NASA Astrophysics Data System (ADS)

Liang, Yingjie; Chen, Wen; Magin, Richard L.

2016-07-01

Analytical solutions to the fractional diffusion equation are often obtained by using Laplace and Fourier transforms, which conveniently encode the order of the time and the space derivatives (α and β) as non-integer powers of the conjugate transform variables (s, and k) for the spectral and the spatial frequencies, respectively. This study presents a new solution to the fractional diffusion equation obtained using the Laplace transform and expressed as a Fox's H-function. This result clearly illustrates the kinetics of the underlying stochastic process in terms of the Laplace spectral frequency and entropy. The spectral entropy is numerically calculated by using the direct integration method and the adaptive Gauss-Kronrod quadrature algorithm. Here, the properties of spectral entropy are investigated for the cases of sub-diffusion and super-diffusion. We find that the overall spectral entropy decreases with the increasing α and β, and that the normal or Gaussian case with α = 1 and β = 2, has the lowest spectral entropy (i.e., less information is needed to describe the state of a Gaussian process). In addition, as the neighborhood over which the entropy is calculated increases, the spectral entropy decreases, which implies a spatial averaging or coarse graining of the material properties. Consequently, the spectral entropy is shown to provide a new way to characterize the temporal correlation of anomalous diffusion. Future studies should be designed to examine changes of spectral entropy in physical, chemical and biological systems undergoing phase changes, chemical reactions and tissue regeneration.

Automated acoustic analysis of task dependency in adductor spasmodic dysphonia versus muscle tension dysphonia.

PubMed

Roy, Nelson; Mazin, Alqhazo; Awan, Shaheen N

2014-03-01

Distinguishing muscle tension dysphonia (MTD) from adductor spasmodic dysphonia (ADSD) can be difficult. Unlike MTD, ADSD is described as "task-dependent," implying that dysphonia severity varies depending upon the demands of the vocal task, with connected speech thought to be more symptomatic than sustained vowels. This study used an acoustic index of dysphonia severity (i.e., the Cepstral Spectral Index of Dysphonia [CSID]) to: 1) assess the value of "task dependency" to distinguish ADSD from MTD, and to 2) examine associations between the CSID and listener ratings. Case-Control Study. CSID estimates of dysphonia severity for connected speech and sustained vowels of patients with ADSD (n = 36) and MTD (n = 45) were compared. The diagnostic precision of task dependency (as evidenced by differences in CSID-estimated dysphonia severity between connected speech and sustained vowels) was examined. In ADSD, CSID-estimated severity for connected speech (M = 39. 2, SD = 22.0) was significantly worse than for sustained vowels (M = 29.3, SD = 21.9), [P = .020]. Whereas in MTD, no significant difference in CSID-estimated severity was observed between connected speech (M = 55.1, SD = 23.8) and sustained vowels (M = 50.0, SD = 27.4), [P = .177]. CSID evidence of task dependency correctly identified 66.7% of ADSD cases (sensitivity) and 64.4% of MTD cases (specificity). CSID and listener ratings were significantly correlated. Task dependency in ADSD, as revealed by differences in acoustically-derived estimates of dysphonia severity between connected speech and sustained vowel production, is a potentially valuable diagnostic marker. © 2013 The American Laryngological, Rhinological and Otological Society, Inc.

Changes of Functional and Directed Resting-State Connectivity Are Associated with Neuronal Oscillations, ApoE Genotype and Amyloid Deposition in Mild Cognitive Impairment

PubMed Central

Michels, Lars; Muthuraman, Muthuraman; Anwar, Abdul R.; Kollias, Spyros; Leh, Sandra E.; Riese, Florian; Unschuld, Paul G.; Siniatchkin, Michael; Gietl, Anton F.; Hock, Christoph

2017-01-01

The assessment of effects associated with cognitive impairment using electroencephalography (EEG) power mapping allows the visualization of frequency-band specific local changes in oscillatory activity. In contrast, measures of coherence and dynamic source synchronization allow for the study of functional and effective connectivity, respectively. Yet, these measures have rarely been assessed in parallel in the context of mild cognitive impairment (MCI) and furthermore it has not been examined if they are related to risk factors of Alzheimer’s disease (AD) such as amyloid deposition and apolipoprotein ε4 (ApoE) allele occurrence. Here, we investigated functional and directed connectivities with Renormalized Partial Directed Coherence (RPDC) in 17 healthy controls (HC) and 17 participants with MCI. Participants underwent ApoE-genotyping and Pittsburgh compound B positron emission tomography (PiB-PET) to assess amyloid deposition. We observed lower spectral source power in MCI in the alpha and beta bands. Coherence was stronger in HC than MCI across different neuronal sources in the delta, theta, alpha, beta and gamma bands. The directed coherence analysis indicated lower information flow between fronto-temporal (including the hippocampus) sources and unidirectional connectivity in MCI. In MCI, alpha and beta RPDC showed an inverse correlation to age and gender; global amyloid deposition was inversely correlated to alpha coherence, RPDC and beta and gamma coherence. Furthermore, the ApoE status was negatively correlated to alpha coherence and RPDC, beta RPDC and gamma coherence. A classification analysis of cognitive state revealed the highest accuracy using EEG power, coherence and RPDC as input. For this small but statistically robust (Bayesian power analyses) sample, our results suggest that resting EEG related functional and directed connectivities are sensitive to the cognitive state and are linked to ApoE and amyloid burden. PMID:29081745

Apparatus and system for multivariate spectral analysis

DOEpatents

Keenan, Michael R.; Kotula, Paul G.

2003-06-24

An apparatus and system for determining the properties of a sample from measured spectral data collected from the sample by performing a method of multivariate spectral analysis. The method can include: generating a two-dimensional matrix A containing measured spectral data; providing a weighted spectral data matrix D by performing a weighting operation on matrix A; factoring D into the product of two matrices, C and S.sup.T, by performing a constrained alternating least-squares analysis of D=CS.sup.T, where C is a concentration intensity matrix and S is a spectral shapes matrix; unweighting C and S by applying the inverse of the weighting used previously; and determining the properties of the sample by inspecting C and S. This method can be used by a spectrum analyzer to process X-ray spectral data generated by a spectral analysis system that can include a Scanning Electron Microscope (SEM) with an Energy Dispersive Detector and Pulse Height Analyzer.

Hybrid least squares multivariate spectral analysis methods

DOEpatents

Haaland, David M.

2004-03-23

A set of hybrid least squares multivariate spectral analysis methods in which spectral shapes of components or effects not present in the original calibration step are added in a following prediction or calibration step to improve the accuracy of the estimation of the amount of the original components in the sampled mixture. The hybrid method herein means a combination of an initial calibration step with subsequent analysis by an inverse multivariate analysis method. A spectral shape herein means normally the spectral shape of a non-calibrated chemical component in the sample mixture but can also mean the spectral shapes of other sources of spectral variation, including temperature drift, shifts between spectrometers, spectrometer drift, etc. The shape can be continuous, discontinuous, or even discrete points illustrative of the particular effect.

Analysis of spectrally resolved autofluorescence images by support vector machines

NASA Astrophysics Data System (ADS)

Mateasik, A.; Chorvat, D.; Chorvatova, A.

2013-02-01

Spectral analysis of the autofluorescence images of isolated cardiac cells was performed to evaluate and to classify the metabolic state of the cells in respect to the responses to metabolic modulators. The classification was done using machine learning approach based on support vector machine with the set of the automatically calculated features from recorded spectral profile of spectral autofluorescence images. This classification method was compared with the classical approach where the individual spectral components contributing to cell autofluorescence were estimated by spectral analysis, namely by blind source separation using non-negative matrix factorization. Comparison of both methods showed that machine learning can effectively classify the spectrally resolved autofluorescence images without the need of detailed knowledge about the sources of autofluorescence and their spectral properties.

New Results in {mathcal {N}}=2 N = 2 Theories from Non-perturbative String

NASA Astrophysics Data System (ADS)

Bonelli, Giulio; Grassi, Alba; Tanzini, Alessandro

2018-03-01

We describe the magnetic phase of SU(N) $\\mathcal{N}=2$ Super Yang-Mills theories in the self-dual Omega background in terms of a new class of multi-cut matrix models. These arise from a non-perturbative completion of topological strings in the dual four dimensional limit which engineers the gauge theory in the strongly coupled magnetic frame. The corresponding spectral determinants provide natural candidates for the tau functions of isomonodromy problems for flat spectral connections associated to the Seiberg-Witten geometry.

Energy repartition in the nonequilibrium steady state

NASA Astrophysics Data System (ADS)

Yan, Peng; Bauer, Gerrit E. W.; Zhang, Huaiwu

2017-01-01

The concept of temperature in nonequilibrium thermodynamics is an outstanding theoretical issue. We propose an energy repartition principle that leads to a spectral (mode-dependent) temperature in steady-state nonequilibrium systems. The general concepts are illustrated by analytic solutions of the classical Heisenberg spin chain connected to Langevin heat reservoirs with arbitrary temperature profiles. Gradients of external magnetic fields are shown to localize spin waves in a Wannier-Zeemann fashion, while magnon interactions renormalize the spectral temperature. Our generic results are applicable to other thermodynamic systems such as Newtonian liquids, elastic solids, and Josephson junctions.

The first 3-D LaIII-SrII heterometallic complex: Synthesis, structure and luminescent properties

NASA Astrophysics Data System (ADS)

Hong, Zhiwei; Ran, Jingwen; Li, Tao; Chen, Yanmei

2016-10-01

The first 3-D LaIII-SrII heterometallic complex, namely [La2Sr(pda)4(H2O)4]n·6nH2O (1, H2pda = pyridine-2,6-dicarboxylic acid), has been successfully synthesized under solvothermal conditions. Single crystal X-ray diffraction analysis reveals that complex 1 features a 3-D porous framework and displays a new topology. The crystal structure can be simplified to a 4,6-connected 3-D network with Schläfli symbol of {34·42·88·9}2{34·42}. The crystals also have been characterized by X-ray powder diffraction, elemental analysis, thermal analysis, and IR spectroscopy. The infrared spectral analysis indicates that complex 1 is a carboxylate coordinated compound, several water molecules exist in the compound. The thermal study shows that there are ten water molecules in the crystal structure. The luminescent property has also been investigated. It shows a blue-purple fluorescence emission.

Identification of phases, symmetries and defects through local crystallography

DOE PAGES

Belianinov, Alex; He, Qian; Kravchenko, Mikhail; ...

2015-07-20

Here we report that advances in electron and probe microscopies allow 10 pm or higher precision in measurements of atomic positions. This level of fidelity is sufficient to correlate the length (and hence energy) of bonds, as well as bond angles to functional properties of materials. Traditionally, this relied on mapping locally measured parameters to macroscopic variables, for example, average unit cell. This description effectively ignores the information contained in the microscopic degrees of freedom available in a high-resolution image. Here we introduce an approach for local analysis of material structure based on statistical analysis of individual atomic neighbourhoods. Clusteringmore » and multivariate algorithms such as principal component analysis explore the connectivity of lattice and bond structure, as well as identify minute structural distortions, thus allowing for chemical description and identification of phases. This analysis lays the framework for building image genomes and structure–property libraries, based on conjoining structural and spectral realms through local atomic behaviour.« less

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

Cameron, Maria K., E-mail: cameron@math.umd.edu

We develop computational tools for spectral analysis of stochastic networks representing energy landscapes of atomic and molecular clusters. Physical meaning and some properties of eigenvalues, left and right eigenvectors, and eigencurrents are discussed. We propose an approach to compute a collection of eigenpairs and corresponding eigencurrents describing the most important relaxation processes taking place in the system on its way to the equilibrium. It is suitable for large and complex stochastic networks where pairwise transition rates, given by the Arrhenius law, vary by orders of magnitude. The proposed methodology is applied to the network representing the Lennard-Jones-38 cluster created bymore » Wales's group. Its energy landscape has a double funnel structure with a deep and narrow face-centered cubic funnel and a shallower and wider icosahedral funnel. However, the complete spectrum of the generator matrix of the Lennard-Jones-38 network has no appreciable spectral gap separating the eigenvalue corresponding to the escape from the icosahedral funnel. We provide a detailed description of the escape process from the icosahedral funnel using the eigencurrent and demonstrate a superexponential growth of the corresponding eigenvalue. The proposed spectral approach is compared to the methodology of the Transition Path Theory. Finally, we discuss whether the Lennard-Jones-38 cluster is metastable from the points of view of a mathematician and a chemical physicist, and make a connection with experimental works.« less

Interhemispheric functional connectivity in anorexia and bulimia nervosa.

PubMed

Canna, Antonietta; Prinster, Anna; Monteleone, Alessio Maria; Cantone, Elena; Monteleone, Palmiero; Volpe, Umberto; Maj, Mario; Di Salle, Francesco; Esposito, Fabrizio

2017-05-01

The functional interplay between hemispheres is fundamental for behavioral, cognitive, and emotional control. Anorexia nervosa (AN) and bulimia nervosa (BN) have been largely studied with brain magnetic resonance imaging (MRI) in relation to the functional mechanisms of high-level processing, but not in terms of possible inter-hemispheric functional connectivity anomalies. Using resting-state functional MRI (fMRI), voxel-mirrored homotopic connectivity (VMHC) and regional inter-hemispheric spectral coherence (IHSC) were studied in 15 AN and 13 BN patients and 16 healthy controls (HC). Using T1-weighted and diffusion tensor imaging MRI scans, regional VMHC values were correlated with the left-right asymmetry of corresponding homotopic gray matter volumes and with the white matter callosal fractional anisotropy (FA). Compared to HC, AN patients exhibited reduced VMHC in cerebellum, insula, and precuneus, while BN patients showed reduced VMHC in dorso-lateral prefrontal and orbito-frontal cortices. The regional IHSC analysis highlighted that the inter-hemispheric functional connectivity was higher in the 'Slow-5' band in all regions except the insula. No group differences in left-right structural asymmetries and in VMHC vs. callosal FA correlations were significant in the comparisons between cohorts. These anomalies, not explained by structural changes, indicate that AN and BN, at least in their acute phase, are associated with a loss of inter-hemispheric connectivity in regions implicated in self-referential, cognitive control and reward processing. These findings may thus gather novel functional markers to explore aberrant features of these eating disorders. © 2016 Federation of European Neuroscience Societies and John Wiley & Sons Ltd.

Global field synchronization in gamma range of the sleep EEG tracks sleep depth: Artifact introduced by a rectangular analysis window.

PubMed

Rusterholz, Thomas; Achermann, Peter; Dürr, Roland; Koenig, Thomas; Tarokh, Leila

2017-06-01

Investigating functional connectivity between brain networks has become an area of interest in neuroscience. Several methods for investigating connectivity have recently been developed, however, these techniques need to be applied with care. We demonstrate that global field synchronization (GFS), a global measure of phase alignment in the EEG as a function of frequency, must be applied considering signal processing principles in order to yield valid results. Multichannel EEG (27 derivations) was analyzed for GFS based on the complex spectrum derived by the fast Fourier transform (FFT). We examined the effect of window functions on GFS, in particular of non-rectangular windows. Applying a rectangular window when calculating the FFT revealed high GFS values for high frequencies (>15Hz) that were highly correlated (r=0.9) with spectral power in the lower frequency range (0.75-4.5Hz) and tracked the depth of sleep. This turned out to be spurious synchronization. With a non-rectangular window (Tukey or Hanning window) these high frequency synchronization vanished. Both, GFS and power density spectra significantly differed for rectangular and non-rectangular windows. Previous papers using GFS typically did not specify the applied window and may have used a rectangular window function. However, the demonstrated impact of the window function raises the question of the validity of some previous findings at higher frequencies. We demonstrated that it is crucial to apply an appropriate window function for determining synchronization measures based on a spectral approach to avoid spurious synchronization in the beta/gamma range. Copyright © 2017 Elsevier B.V. All rights reserved.

Quantitative subpixel spectral detection of targets in multispectral images. [terrestrial and planetary surfaces

NASA Technical Reports Server (NTRS)

Sabol, Donald E., Jr.; Adams, John B.; Smith, Milton O.

1992-01-01

The conditions that affect the spectral detection of target materials at the subpixel scale are examined. Two levels of spectral mixture analysis for determining threshold detection limits of target materials in a spectral mixture are presented, the cases where the target is detected as: (1) a component of a spectral mixture (continuum threshold analysis) and (2) residuals (residual threshold analysis). The results of these two analyses are compared under various measurement conditions. The examples illustrate the general approach that can be used for evaluating the spectral detectability of terrestrial and planetary targets at the subpixel scale.

VizieR Online Data Catalog: V1357 Cyg spectroscopic monitoring in 2002-04 (Karitskaya+, 2008)

NASA Astrophysics Data System (ADS)

Karitskaya, E. A.; Bochkarev, N. G.; Bondar, A. V.; Galazutdinov, G. A.; Lee, B.-K.; Musaev, F. A.; Sapar, A. A.; Shimansky, V. V.

2008-11-01

The results of Cyg X-1 = HDE 226868/V1357 Cyg optical spectral monitoring in 2002-2004 are discussed. Spectral observations were carried out on Peak Terskol Observatory (Kabardino-Balkaria, Russia, resolution R=45000 and 13000) and Bohyunsan Optical Astronomy Observatory (BOAO, Korea, R=30000, 44000). Each spectrum covers the main part of optical spectral range. During 33 observational nights 75 echelle spectra were obtained in the times of the "soft" and "hard" states of Cyg X-1. The X-ray influence on spectral line profiles was studied. The RXTE/ASM data were used for this purpose. The X-ray flare resulted in strong variations of Halpha and HeII4686{AA} emission component profiles during night. This behaviour we connect with variations of ionization structure of matter in the system. Line profile variations with the orbital phase were observed. The spectral atlas for Cyg X-1 was constructed. The contented line identification was done. There were revealed 172 lines and blends which belong to 12 chemical elements: H, He, C, N, O, Ne, Mg, Al, Si, S, Fe, Zn. The HDE 226868 spectral classification as ON star was confirmed. (2 data files).

Semi-supervised spectral algorithms for community detection in complex networks based on equivalence of clustering methods

NASA Astrophysics Data System (ADS)

Ma, Xiaoke; Wang, Bingbo; Yu, Liang

2018-01-01

Community detection is fundamental for revealing the structure-functionality relationship in complex networks, which involves two issues-the quantitative function for community as well as algorithms to discover communities. Despite significant research on either of them, few attempt has been made to establish the connection between the two issues. To attack this problem, a generalized quantification function is proposed for community in weighted networks, which provides a framework that unifies several well-known measures. Then, we prove that the trace optimization of the proposed measure is equivalent with the objective functions of algorithms such as nonnegative matrix factorization, kernel K-means as well as spectral clustering. It serves as the theoretical foundation for designing algorithms for community detection. On the second issue, a semi-supervised spectral clustering algorithm is developed by exploring the equivalence relation via combining the nonnegative matrix factorization and spectral clustering. Different from the traditional semi-supervised algorithms, the partial supervision is integrated into the objective of the spectral algorithm. Finally, through extensive experiments on both artificial and real world networks, we demonstrate that the proposed method improves the accuracy of the traditional spectral algorithms in community detection.

Pharmacological modulation of pulvinar resting-state regional oscillations and network dynamics in major depression

PubMed Central

Tadayonnejad, Reza; Ajilore, Olusola; Mickey, Brian J.; Crane, Natania A.; Hsu, David T.; Kumar, Anand; Zubieta, Jon-Kar; Langenecker, Scott A.

2016-01-01

The pulvinar, the largest thalamus nucleus, has rich anatomical connections with several different cortical and subcortical regions suggesting its important involvement in high-level cognitive and emotional functions. Unfortunately, pulvinar dysfunction in psychiatric disorders particularly major depression disorder has not been thoroughly examined to date. In this study we explored the alterations in the baseline regional and network activities of the pulvinar in MDD by applying spectral analysis of resting-state oscillatory activity, functional connectivity and directed (effective) connectivity on resting-state fMRI data acquired from 20 healthy controls and 19 participants with MDD. Furthermore, we tested how pharmacological treatment with duloxetine can modulate the measured local and network variables in ten participants who completed treatment. Our results revealed a frequency-band dependent modulation of power spectrum characteristics of pulvinar regional oscillatory activity. At the network level, we found MDD is associated with aberrant causal interactions between pulvinar and several systems including default-mode and posterior insular networks. It was also shown that duloxetine treatment can correct or overcompensate the pathologic network behavior of the pulvinar. In conclusion, we suggest that pulvinar regional baseline oscillatory activity and its resting-state network dynamics are compromised in MDD and can be modulated therapeutically by pharmacological treatment. PMID:27148894

Frequency-response mismatch effects in Johnson noise thermometry

NASA Astrophysics Data System (ADS)

White, D. R.; Qu, J.-F.

2018-02-01

Johnson noise thermometry is of considerable interest at present due to the planned redefinition of the kelvin in 2019, and several determinations of the Boltzmann constant have recently been published in support of the redefinition. To determine the Boltzmann constant by noise thermometry, the thermal noise from a sensing resistor at the triple point of water is compared to a pseudo-random noise with a calculable power spectral density traceable to quantum electrical standards. In all the measurements to date, the two dominant sources of measurement uncertainty are strongly influenced by a single factor: the frequency-response mismatch between the sets of leads connecting the thermometer to the two noise sources. In the most recent determination at the National Institute of Metrology, China, substantial changes were made to the connecting leads to reduce the mismatch effects. The aims of this paper are, firstly, to describe and explain the rationale for the changes, and secondly, to better understand the effects of the least-squares fits and the bias-variance compromise in the analysis of measurements affected by the mismatch effects. While significant improvements can be made to the connecting leads to lessen the effects of the frequency-response mismatch, the efforts are unlikely to be rewarded by a significant increase in bandwidth or a significant reduction in uncertainty.

Metric learning with spectral graph convolutions on brain connectivity networks.

PubMed

Ktena, Sofia Ira; Parisot, Sarah; Ferrante, Enzo; Rajchl, Martin; Lee, Matthew; Glocker, Ben; Rueckert, Daniel

2018-04-01

Graph representations are often used to model structured data at an individual or population level and have numerous applications in pattern recognition problems. In the field of neuroscience, where such representations are commonly used to model structural or functional connectivity between a set of brain regions, graphs have proven to be of great importance. This is mainly due to the capability of revealing patterns related to brain development and disease, which were previously unknown. Evaluating similarity between these brain connectivity networks in a manner that accounts for the graph structure and is tailored for a particular application is, however, non-trivial. Most existing methods fail to accommodate the graph structure, discarding information that could be beneficial for further classification or regression analyses based on these similarities. We propose to learn a graph similarity metric using a siamese graph convolutional neural network (s-GCN) in a supervised setting. The proposed framework takes into consideration the graph structure for the evaluation of similarity between a pair of graphs, by employing spectral graph convolutions that allow the generalisation of traditional convolutions to irregular graphs and operates in the graph spectral domain. We apply the proposed model on two datasets: the challenging ABIDE database, which comprises functional MRI data of 403 patients with autism spectrum disorder (ASD) and 468 healthy controls aggregated from multiple acquisition sites, and a set of 2500 subjects from UK Biobank. We demonstrate the performance of the method for the tasks of classification between matching and non-matching graphs, as well as individual subject classification and manifold learning, showing that it leads to significantly improved results compared to traditional methods. Copyright © 2017 Elsevier Inc. All rights reserved.

Paleo-productivity changes revealed by spectral analysis performed on coccoliths assemblages

NASA Astrophysics Data System (ADS)

Palumbo, Eliana; Ornella Amore, Filomena; Perugia, Carmen

2010-05-01

Several climate changes occurred over geological time at different time-scales. Spectral analyses performed on paleo-climate data suggested that these cyclicities verify irregularly into time-space domain. Paleo-climate oscillations occur with high or low frequencies dues to the oscillation of the major orbital parameters (characterized by low frequencies and high period) and some minor high-frequencies events. During last years, analyses on frequencies domain have been performed also on coccoliths assemblages. Coccolithophores are a special phytoplankton group living today at all latitude regions within the photic zone (0-200 m of depth) (Winter & Siesser, 1994). They are sensitive indicators of environmental conditions because they directly depend on temperature, salinity and nutrients as well as the availability of sunlight (McIntyre and Bé, 1967; Giradeau et al., 1993; Winter & Siesser, 1994; Baumann & Freitag, 2004). Therefore coccolithophores quickly respond to fluctuations in climate as well as changes in surface-water conditions (Baumann & Freitag, 2004). Thus coccoliths can be clearly used as paleo-climate data because of their power of recordering and amplifying climatic change signals. In addition, primary productivity depends on the amount of insolation received by Earth surface. In this study Sun insolation has been calculated in terms of intensity and energy, in order to compare them with maximum productivity activity. Precession controls sun intensity insolation, while the energy is controlled by obliquity. Thus, the intensity depends on the duration of the insolation,while the energy is connected to the amount of insolation (Berger, 1978; Loutre et al., 2004; Huybers, 2006). In this study, spectral analyses have been performed on coccoliths data with the result of individuating high and low frequencies content in productivity signals. Auto-spectral and cross-spectral analyses have been performed through Matlab software using several available functions plus a new function created in order to evaluate cross-wavelet power spectra. Auto-spectral analysis aims to describe the distribution of variance contained in each single signal over frequency or wavelength, while cross-spectral analysis correlates two time series in the frequency domain (Trauth, 2009). We have performed spectral analyses using the complex Fourier transform and the Short time Fourier transform. Both the transforms lose any kind of time information in transforming the signal from time to frequency domain (Jenkins and Watt, 1968). These transforms don't allow us to individuate when an event occurred in the past. In order to overcome this limit we have also applied Wavelet analysis which represents frequency content of a signal over the time thus it allows us to visualize when an event occurred into time domain (Torrence and Compo, 1998; Prokoph and El Bilali, 2008; Grinsted et al., 2004). Moreover we have performed a simple cross and a cross-spectral analysis between different proxy groups to discover their possible correlations into time and frequency domains. References. Berger, A., 1978. J. Atmos. Sc., 35 (12): 2362-2367. Baumann, K.-H., and Freitag, T., 2004. Marine Micropaleontology 52: 195-215. Giraudeau, J., Monteiro, P.M.S., Nikodemus, K., 1993. Mar. Micropalaeontol. 22: 93- 110. Grinsted, A., Moore, J. C., and Jevrejeva, S., 2004. Nonlinear Processes in Geophysics 11: 561-566. Huybers, P., 2006. Science 313: 508-511. Jenkins, G. M., and Watt, D. G., 1968. Holden Day, pp. 410, Oakland. Loutre, M. F., Paillard, D., Vimeux, F., and Cortijo, E., 2004. Earth Planet. Sci. Lett., 221, 1-14. McIntyre, A., and Bè, A.H.W., 1967. Deep-Sea Res. 14, pp. 561-597. Prokoph, A., and El Bilali, H., 2008. Math Geosciences 40: 575-586. Torrence, C., and Compo, G. P., 1998. Bulletin of American Meteorological Society 79:61-78. Trauth, M.H., 2009. Springer 288 p. Winter, A., and Siesser, W., 1994. Cambridge University Press 242 p.

En face spectral domain optical coherence tomography analysis of lamellar macular holes.

PubMed

Clamp, Michael F; Wilkes, Geoff; Leis, Laura S; McDonald, H Richard; Johnson, Robert N; Jumper, J Michael; Fu, Arthur D; Cunningham, Emmett T; Stewart, Paul J; Haug, Sara J; Lujan, Brandon J

2014-07-01

To analyze the anatomical characteristics of lamellar macular holes using cross-sectional and en face spectral domain optical coherence tomography. Forty-two lamellar macular holes were retrospectively identified for analysis. The location, cross-sectional length, and area of lamellar holes were measured using B-scans and en face imaging. The presence of photoreceptor inner segment/outer segment disruption and the presence or absence of epiretinal membrane formation were recorded. Forty-two lamellar macular holes were identified. Intraretinal splitting occurred within the outer plexiform layer in 97.6% of eyes. The area of intraretinal splitting in lamellar holes did not correlate with visual acuity. Eyes with inner segment/outer segment disruption had significantly worse mean logMAR visual acuity (0.363 ± 0.169; Snellen = 20/46) than in eyes without inner segment/outer segment disruption (0.203 ± 0.124; Snellen = 20/32) (analysis of variance, P = 0.004). Epiretinal membrane was present in 34 of 42 eyes (81.0%). En face imaging allowed for consistent detection and quantification of intraretinal splitting within the outer plexiform layer in patients with lamellar macular holes, supporting the notion that an area of anatomical weakness exists within Henle's fiber layer, presumably at the synaptic connection of these fibers within the outer plexiform layer. However, the en face area of intraretinal splitting did not correlate with visual acuity, disruption of the inner segment/outer segment junction was associated with significantly worse visual acuity in patients with lamellar macular holes.

Temporal reflection as a spectral-broadening mechanism in dual-pumped dispersion-decreasing fibers and its connection to dispersive waves

NASA Astrophysics Data System (ADS)

Antikainen, Aku; Arteaga-Sierra, Francisco R.; Agrawal, Govind P.

2017-03-01

We show that temporal reflections off a moving refractive index barrier play a major role in the spectral broadening of a dual-wavelength input inside a highly nonlinear, dispersion-decreasing fiber. We also find that a recently developed linear theory of temporal reflections works well in predicting the reflected frequencies. Successive temporal reflections from multiple closely spaced solitons create a blueshifted spectral band, while continuous narrowing of solitons inside the dispersion-decreasing fiber enhances Raman-induced redshifts, leading to supercontinuum generation at relatively low pump powers. We also show how dispersive wave emission can be considered a special case of the more general process of temporal reflections. Hence our findings have implications on all systems able to support solitons.

Non-Fermi-liquid behavior in nonequilibrium transport through Co-doped Au chains connected to fourfold symmetric leads

NASA Astrophysics Data System (ADS)

Di Napoli, S.; Roura-Bas, P.; Weichselbaum, Andreas; Aligia, A. A.

2014-09-01

We calculate the differential conductance as a function of temperature and bias voltage, G (T,V), through Au monatomic chains with a substitutional Co atom as a magnetic impurity, connected to a fourfold symmetric lead. The system was recently proposed as a possible scenario for observation of the overscreened Kondo physics. Stretching the chain, the system could be tuned through a quantum critical point (QCP) with three different regimes: overscreened, underscreened, and non-Kondo phases. We present calculations of the impurity spectral function by using the numerical renormalization group for the three different regimes characterizing the QCP. Nontrivial behavior of the spectral function is reported near the QCP. Comparison with results using the noncrossing approximation (NCA) shows that the latter is reliable in the overscreened regime, when the anisotropy is larger than the Kondo temperature. For these parameters, which correspond to realistic previous estimates, G (T,V) calculated within NCA exhibits clear signatures of the non-Fermi-liquid behavior within the overscreened regime.

A novel baseline-correction method for standard addition based derivative spectra and its application to quantitative analysis of benzo(a)pyrene in vegetable oil samples.

PubMed

Li, Na; Li, Xiu-Ying; Zou, Zhe-Xiang; Lin, Li-Rong; Li, Yao-Qun

2011-07-07

In the present work, a baseline-correction method based on peak-to-derivative baseline measurement was proposed for the elimination of complex matrix interference that was mainly caused by unknown components and/or background in the analysis of derivative spectra. This novel method was applicable particularly when the matrix interfering components showed a broad spectral band, which was common in practical analysis. The derivative baseline was established by connecting two crossing points of the spectral curves obtained with a standard addition method (SAM). The applicability and reliability of the proposed method was demonstrated through both theoretical simulation and practical application. Firstly, Gaussian bands were used to simulate 'interfering' and 'analyte' bands to investigate the effect of different parameters of interfering band on the derivative baseline. This simulation analysis verified that the accuracy of the proposed method was remarkably better than other conventional methods such as peak-to-zero, tangent, and peak-to-peak measurements. Then the above proposed baseline-correction method was applied to the determination of benzo(a)pyrene (BaP) in vegetable oil samples by second-derivative synchronous fluorescence spectroscopy. The satisfactory results were obtained by using this new method to analyze a certified reference material (coconut oil, BCR(®)-458) with a relative error of -3.2% from the certified BaP concentration. Potentially, the proposed method can be applied to various types of derivative spectra in different fields such as UV-visible absorption spectroscopy, fluorescence spectroscopy and infrared spectroscopy.

Spectral power and functional connectivity changes during mindfulness meditation with eyes open: A magnetoencephalography (MEG) study in long-term meditators.

PubMed

Wong, W P; Camfield, D A; Woods, W; Sarris, J; Pipingas, A

2015-10-01

Whilst a number of previous studies have been conducted in order to investigate functional brain changes associated with eyes-closed meditation techniques, there is a relative scarcity in the literature with regards to changes occurring during eyes-open meditation. The current project used magnetoencephalography (MEG) to investigate differences in spectral power and functional connectivity between 11 long-term mindfulness meditators (LTMMs) with >5 years of experience and 12 meditation-naïve control participants both during baseline eyes-open rest and eyes-open open-monitoring (OM) mindfulness meditation. During resting with eyes-open, prior to meditating, greater mean alpha power was observed for LTMMs in comparison to controls. However, during the course of OM meditation, a significantly greater increase in theta power was observed over a broad fronto-centro-parietal region for control participants in comparison to LTMMs. In contrast, whole-head mean connectivity was found to be significantly greater for long-term meditators in comparison to controls in the theta band both during rest as well as during meditation. Additionally, mean connectivity was significantly lower for long-term meditators in the low gamma band during rest and significantly lower in both low and high gamma bands during meditation; and the variance of low-gamma connectivity scores for long-term meditators was significantly decreased compared to the control group. The current study provides important new information as to the trait functional changes in brain activity associated with long-term mindfulness meditation, as well as the state changes specifically associated with eyes-open open monitoring meditation techniques. Copyright © 2015 Elsevier B.V. All rights reserved.

Possibility of successive SRXFA use along with chemical-spectral methods for palladium analysis in geological samples

NASA Astrophysics Data System (ADS)

Kislov, E. V.; Kulikov, A. A.; Kulikova, A. B.

1989-10-01

Samples of basit-ultrabasit rocks and NiCu ores of the Ioko-Dovyren and Chaya massifs were analysed by SRXFA and a chemical-spectral method. SRXFA perfectly satisfies the quantitative noble-metals analysis of ore-free rocks. Combination of SRXFA and chemical-spectral analysis has good prospects. After analysis of a great number of samples by SRXFA it is necessary to select samples which would show minimal and maximal results for the chemical-spectral method.

Spectral Properties and Dynamics of Gold Nanorods Revealed by EMCCD Based Spectral-Phasor Method

PubMed Central

Chen, Hongtao; Digman, Michelle A.

2015-01-01

Gold nanorods (NRs) with tunable plasmon-resonant absorption in the near-infrared region have considerable advantages over organic fluorophores as imaging agents. However, the luminescence spectral properties of NRs have not been fully explored at the single particle level in bulk due to lack of proper analytic tools. Here we present a global spectral phasor analysis method which allows investigations of NRs' spectra at single particle level with their statistic behavior and spatial information during imaging. The wide phasor distribution obtained by the spectral phasor analysis indicates spectra of NRs are different from particle to particle. NRs with different spectra can be identified graphically in corresponding spatial images with high spectral resolution. Furthermore, spectral behaviors of NRs under different imaging conditions, e.g. different excitation powers and wavelengths, were carefully examined by our laser-scanning multiphoton microscope with spectral imaging capability. Our results prove that the spectral phasor method is an easy and efficient tool in hyper-spectral imaging analysis to unravel subtle changes of the emission spectrum. Moreover, we applied this method to study the spectral dynamics of NRs during direct optical trapping and by optothermal trapping. Interestingly, spectral shifts were observed in both trapping phenomena. PMID:25684346

Semi-blind Bayesian inference of CMB map and power spectrum

NASA Astrophysics Data System (ADS)

Vansyngel, Flavien; Wandelt, Benjamin D.; Cardoso, Jean-François; Benabed, Karim

2016-04-01

We present a new blind formulation of the cosmic microwave background (CMB) inference problem. The approach relies on a phenomenological model of the multifrequency microwave sky without the need for physical models of the individual components. For all-sky and high resolution data, it unifies parts of the analysis that had previously been treated separately such as component separation and power spectrum inference. We describe an efficient sampling scheme that fully explores the component separation uncertainties on the inferred CMB products such as maps and/or power spectra. External information about individual components can be incorporated as a prior giving a flexible way to progressively and continuously introduce physical component separation from a maximally blind approach. We connect our Bayesian formalism to existing approaches such as Commander, spectral mismatch independent component analysis (SMICA), and internal linear combination (ILC), and discuss possible future extensions.

Phase and amplitude analysis in time-frequency space--application to voluntary finger movement.

PubMed

Ginter, J; Blinowska, K J; Kamiński, M; Durka, P J

2001-09-30

Two methods operating in time-frequency space were applied to analysis of EEG activity accompanying voluntary finger movements. The first one, based on matching pursuit approach provided high-resolution distributions of power in time-frequency space. The phenomena of event related desynchronization (ERD) and synchronization (ERS) were investigated without the need of band-pass filtering. Time evolution of mu- and beta-components was observed in a detailed way. The second method was based on a multichannel autoregressive model (MVAR) adapted for investigation of short-time changes in EEG signal. The direction and spectral content of the EEG activity propagation was estimated by means of short-time directed transfer function (SDTF). The evidence of 'cross-talk' between different areas of motor and sensory cortex was found. The earlier known phenomena, connected with voluntary movements, were confirmed and a new evidence concerning focal ERD/surround ERS and beta activity post-movement synchronization was found.

X-Ray Evidence for the Accretion Disc-Outflow Connection in 3C 111

NASA Technical Reports Server (NTRS)

Tombesi, Frank; Sambruna, R. M.; Reeves, J. N.; Reynolds, C. S.; Braito, V.

2011-01-01

We present the spectral analysis of three Suzaku X-ray Imaging Spectrometer observations of 3C III requested to monitor the predicted variability of its ultrafast outflow on approximately 7 d time-scales. We detect an ionized iron emission line in the first observation and a blueshifted absorption line in the second, when the flux is approximately 30 per cent higher. The location of the material is constrained at less than 0.006 pc from the variability. Detailed modelling supports an identification with ionized reflection off the accretion disc at approximately 20-100rg from the black hole and a highly ionized and massive ultrafast outflow with velocity approximately 0.1c, respectively. The outflow is most probably accelerated by radiation pressure, but additional magnetic thrust cannot be excluded. The measured high outflow rate and mechanical energy support the claims that disc outflows may have a significant feedback role. This work provides the first direct evidence for an accretion disc-outflow connection in a radio-loud active galactic nucleus, possibly linked also to the jet activity.

New Insights on the Accretion Disk-Winds Connection in Radio-Loud AGNs from Suzaku

NASA Technical Reports Server (NTRS)

Tombesi, F.; Sambruna, R. M.; Reeves, J. N.; Braito, V.; Cappi, M.; Reynolds, S.; Mushotzky, R. F.

2011-01-01

From the spectral analysis of long Suzaku observations of five radio-loud AGNs we have been able to discover the presence of ultra-fast outflows with velocities ,,approx.0.1 c in three of them, namely 3C III, 3C 120 and 3C 390.3. They are consistent with being accretion disk winds/outflows. We also performed a follow-up on 3C III to monitor its outflow on approx.7 days time-scales and detected an anti-correlated variability of a possible relativistic emission line with respect to blue-shifted Fe K features, following a flux increase. This provides the first direct evidence for an accretion disc-wind connection in an AGN. The mass outflow rate of these outflows can be comparable to the accretion rate and their mechanical power can correspond to a significant fraction of the bolometric luminosity and is comparable to their typical jet power. Therefore, they can possibly play a significant role in the expected feedback from AGNs and can give us further clues on the relation between the accretion disk and the formation of winds/jets.

Photoproduct formation of endogeneous protoporphyrin and its photodynamic activity

NASA Astrophysics Data System (ADS)

Koenig, Karsten; Schneckenburger, Herbert; Rueck, Angelika C.; Auchter, S.

1991-11-01

Human skin shows a strong autofluorescence in the red spectral region caused on the porphyrin production of the Gram positive lipophile skin bacterium Propionibacterium acnes. Irradiation of these bacteria reduces the integral fluorescence intensity and induces the formation of fluorescent photoproducts. The fluorescence band at around 670 nm and the decay times of around 1 ns and 5 ns are typical for protoporphyrin products. The photoproduct formation is connected with an increased absorption in the red spectral region. However the photodynamic activity of these photoproducts determined by scattering measurements on human erythrocytes is lower than that of protoporphyrin IX. 1:

System optimization of a field-widened Michelson interferometric spectral filter for high spectral resolution lidar

NASA Astrophysics Data System (ADS)

Liu, Dong; Miller, Ian; Hostetler, Chris; Cook, Anthony; Hair, Johnathan

2011-06-01

High spectral resolution lidars (HSRLs) have recently shown great value in aerosol measurements form aircraft and are being called for in future space-based aerosol remote sensing applications. A quasi-monolithic field-widened, off-axis Michelson interferometer had been developed as the spectral discrimination filter for an HSRL currently under development at NASA Langley Research Center (LaRC). The Michelson filter consists of a cubic beam splitter, a solid arm and an air arm. The input light is injected at 1.5° off-axis to provide two output channels: standard Michelson output and the reflected complementary signal. Piezo packs connect the air arm mirror to the main part of the filter that allows it to be tuned within a small range. In this paper, analyses of the throughput wavephase, locking error, AR coating, and tilt angle of the interferometer are described. The transmission ratio for monochromatic light at the transmitted wavelength is used as a figure of merit for assessing each of these parameters.

Identification of segregated regions in the functional brain connectome of autistic patients by a combination of fuzzy spectral clustering and entropy analysis

PubMed Central

Sato, João Ricardo; Balardin, Joana; Vidal, Maciel Calebe; Fujita, André

2016-01-01

Background Several neuroimaging studies support the model of abnormal development of brain connectivity in patients with autism-spectrum disorders (ASD). In this study, we aimed to test the hypothesis of reduced functional network segregation in autistic patients compared with controls. Methods Functional MRI data from children acquired under a resting-state protocol (Autism Brain Imaging Data Exchange [ABIDE]) were submitted to both fuzzy spectral clustering (FSC) with entropy analysis and graph modularity analysis. Results We included data from 814 children in our analysis. We identified 5 regions of interest comprising the motor, temporal and occipito-temporal cortices with increased entropy (p < 0.05) in the clustering structure (i.e., more segregation in the controls). Moreover, we noticed a statistically reduced modularity (p < 0.001) in the autistic patients compared with the controls. Significantly reduced eigenvector centrality values (p < 0.05) in the patients were observed in the same regions that were identified in the FSC analysis. Limitations There is considerable heterogeneity in the fMRI acquisition protocols among the sites that contributed to the ABIDE data set (e.g., scanner type, pulse sequence, duration of scan and resting-state protocol). Moreover, the sites differed in many variables related to sample characterization (e.g., age, IQ and ASD diagnostic criteria). Therefore, we cannot rule out the possibility that additional differences in functional network organization would be found in a more homogeneous data sample of individuals with ASD. Conclusion Our results suggest that the organization of the whole-brain functional network in patients with ASD is different from that observed in controls, which implies a reduced modularity of the brain functional networks involved in sensorimotor, social, affective and cognitive processing. PMID:26505141

Periodized Daubechies wavelets

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

Restrepo, J.M.; Leaf, G.K.; Schlossnagle, G.

1996-03-01

The properties of periodized Daubechies wavelets on [0,1] are detailed and counterparts which form a basis for L{sup 2}(R). Numerical examples illustrate the analytical estimates for convergence and demonstrated by comparison with Fourier spectral methods the superiority of wavelet projection methods for approximations. The analytical solution to inner products of periodized wavelets and their derivatives, which are known as connection coefficients, is presented, and their use ius illustrated in the approximation of two commonly used differential operators. The periodization of the connection coefficients in Galerkin schemes is presented in detail.

Inferring hidden causal relations between pathway members using reduced Google matrix of directed biological networks

PubMed Central

2018-01-01

Signaling pathways represent parts of the global biological molecular network which connects them into a seamless whole through complex direct and indirect (hidden) crosstalk whose structure can change during development or in pathological conditions. We suggest a novel methodology, called Googlomics, for the structural analysis of directed biological networks using spectral analysis of their Google matrices, using parallels with quantum scattering theory, developed for nuclear and mesoscopic physics and quantum chaos. We introduce analytical “reduced Google matrix” method for the analysis of biological network structure. The method allows inferring hidden causal relations between the members of a signaling pathway or a functionally related group of genes. We investigate how the structure of hidden causal relations can be reprogrammed as a result of changes in the transcriptional network layer during cancerogenesis. The suggested Googlomics approach rigorously characterizes complex systemic changes in the wiring of large causal biological networks in a computationally efficient way. PMID:29370181

Oscillatory motor network activity during rest and movement: an fNIRS study

PubMed Central

Bajaj, Sahil; Drake, Daniel; Butler, Andrew J.; Dhamala, Mukesh

2014-01-01

Coherent network oscillations (<0.1 Hz) linking distributed brain regions are commonly observed in the brain during both rest and task conditions. What oscillatory network exists and how network oscillations change in connectivity strength, frequency and direction when going from rest to explicit task are topics of recent inquiry. Here, we study network oscillations within the sensorimotor regions of able-bodied individuals using hemodynamic activity as measured by functional near-infrared spectroscopy (fNIRS). Using spectral interdependency methods, we examined how the supplementary motor area (SMA), the left premotor cortex (LPMC) and the left primary motor cortex (LM1) are bound as a network during extended resting state (RS) and between-tasks resting state (btRS), and how the activity of the network changes as participants execute left, right, and bilateral hand (LH, RH, and BH) finger movements. We found: (i) power, coherence and Granger causality (GC) spectra had significant peaks within the frequency band (0.01–0.04 Hz) during RS whereas the peaks shifted to a bit higher frequency range (0.04–0.08 Hz) during btRS and finger movement tasks, (ii) there was significant bidirectional connectivity between all the nodes during RS and unidirectional connectivity from the LM1 to SMA and LM1 to LPMC during btRS, and (iii) the connections from SMA to LM1 and from LPMC to LM1 were significantly modulated in LH, RH, and BH finger movements relative to btRS. The unidirectional connectivity from SMA to LM1 just before the actual task changed to the bidirectional connectivity during LH and BH finger movement. The uni-directionality could be associated with movement suppression and the bi-directionality with preparation, sensorimotor update and controlled execution. These results underscore that fNIRS is an effective tool for monitoring spectral signatures of brain activity, which may serve as an important precursor before monitoring the recovery progress following brain injury. PMID:24550793

Spectral Entropy Based Neuronal Network Synchronization Analysis Based on Microelectrode Array Measurements

PubMed Central

Kapucu, Fikret E.; Välkki, Inkeri; Mikkonen, Jarno E.; Leone, Chiara; Lenk, Kerstin; Tanskanen, Jarno M. A.; Hyttinen, Jari A. K.

2016-01-01

Synchrony and asynchrony are essential aspects of the functioning of interconnected neuronal cells and networks. New information on neuronal synchronization can be expected to aid in understanding these systems. Synchronization provides insight in the functional connectivity and the spatial distribution of the information processing in the networks. Synchronization is generally studied with time domain analysis of neuronal events, or using direct frequency spectrum analysis, e.g., in specific frequency bands. However, these methods have their pitfalls. Thus, we have previously proposed a method to analyze temporal changes in the complexity of the frequency of signals originating from different network regions. The method is based on the correlation of time varying spectral entropies (SEs). SE assesses the regularity, or complexity, of a time series by quantifying the uniformity of the frequency spectrum distribution. It has been previously employed, e.g., in electroencephalogram analysis. Here, we revisit our correlated spectral entropy method (CorSE), providing evidence of its justification, usability, and benefits. Here, CorSE is assessed with simulations and in vitro microelectrode array (MEA) data. CorSE is first demonstrated with a specifically tailored toy simulation to illustrate how it can identify synchronized populations. To provide a form of validation, the method was tested with simulated data from integrate-and-fire model based computational neuronal networks. To demonstrate the analysis of real data, CorSE was applied on in vitro MEA data measured from rat cortical cell cultures, and the results were compared with three known event based synchronization measures. Finally, we show the usability by tracking the development of networks in dissociated mouse cortical cell cultures. The results show that temporal correlations in frequency spectrum distributions reflect the network relations of neuronal populations. In the simulated data, CorSE unraveled the synchronizations. With the real in vitro MEA data, CorSE produced biologically plausible results. Since CorSE analyses continuous data, it is not affected by possibly poor spike or other event detection quality. We conclude that CorSE can reveal neuronal network synchronization based on in vitro MEA field potential measurements. CorSE is expected to be equally applicable also in the analysis of corresponding in vivo and ex vivo data analysis. PMID:27803660

Spectral binning for energy production calculations and multijunction solar cell design

DOE PAGES

Garcia, Iván; McMahon, William E.; Habte, Aron; ...

2017-09-14

Currently, most solar cells are designed for and evaluated under standard spectra intended to represent typical spectral conditions. However, no single spectrum can capture the spectral variability needed for annual energy production (AEP) calculations, and this shortcoming becomes more significant for series-connected multijunction cells as the number of junctions increases. For this reason, AEP calculations are often performed on very detailed yearlong sets of data, but these pose 2 inherent challenges: (1) These data sets comprise thousands of data points, which appear as a scattered cloud of data when plotted against typical parameters and are hence cumbersome to classify andmore » compare, and (2) large sets of spectra bring with them a corresponding increase in computation or measurement time. Here, we show how a large spectral set can be reduced to just a few 'proxy' spectra, which still retain the spectral variability information needed for AEP design and evaluation. The basic 'spectral binning' methods should be extensible to a variety of multijunction device architectures. In this study, as a demonstration, the AEP of a 4-junction device is computed for both a full set of spectra and a reduced proxy set, and the results show excellent agreement for as few as 3 proxy spectra. This enables much faster (and thereby more detailed) calculations and indoor measurements and provides a manageable way to parameterize a spectral set, essentially creating a 'spectral fingerprint,' which should facilitate the understanding and comparison of different sites.« less

ACTIM: an EDA initiated study on spectral active imaging

NASA Astrophysics Data System (ADS)

Steinvall, O.; Renhorn, I.; Ahlberg, J.; Larsson, H.; Letalick, D.; Repasi, E.; Lutzmann, P.; Anstett, G.; Hamoir, D.; Hespel, L.; Boucher, Y.

2010-10-01

This paper will describe ongoing work from an EDA initiated study on Active Imaging with emphasis of using multi or broadband spectral lasers and receivers. Present laser based imaging and mapping systems are mostly based on a fixed frequency lasers. On the other hand great progress has recently occurred in passive multi- and hyperspectral imaging with applications ranging from environmental monitoring and geology to mapping, military surveillance, and reconnaissance. Data bases on spectral signatures allow the possibility to discriminate between different materials in the scene. Present multi- and hyperspectral sensors mainly operate in the visible and short wavelength region (0.4-2.5 μm) and rely on the solar radiation giving shortcoming due to shadows, clouds, illumination angles and lack of night operation. Active spectral imaging however will largely overcome these difficulties by a complete control of the illumination. Active illumination enables spectral night and low-light operation beside a robust way of obtaining polarization and high resolution 2D/3D information. Recent development of broadband lasers and advanced imaging 3D focal plane arrays has led to new opportunities for advanced spectral and polarization imaging with high range resolution. Fusing the knowledge of ladar and passive spectral imaging will result in new capabilities in the field of EO-sensing to be shown in the study. We will present an overview of technology, systems and applications for active spectral imaging and propose future activities in connection with some prioritized applications.

Spectral and Polarization Sensitivity of the Dipteran Visual System

PubMed Central

McCann, Gilbert D.; Arnett, David W.

1972-01-01

Spectral and polarization sensitivity measurements were made at several levels (retina, first and third optic ganglion, cervical connective, behavior) of the dipteran visual nervous system. At all levels, it was possible to reveal contributions from the retinular cell subsystem cells 1 to 6 or the retinular cell subsystem cells 7 and 8 or both. Only retinular cells 1 to 6 were directly studied, and all possessed the same spectral sensitivity characterized by two approximately equal sensitivity peaks at 350 and 480 nm. All units of both the sustaining and on-off variety in the first optic ganglion exhibited the same spectral sensitivity as that of retinular cells 1 to 6. It was possible to demonstrate for motion detection and optomotor responses two different spectral sensitivities depending upon the spatial wavelength of the stimulus. For long spatial wavelengths, the spectral sensitivity agreed with retinular cells 1 to 6; however, the spectral sensitivity at short spatial wavelengths was characterized by a single peak at 465 nm reflecting contributions from the (7, 8) subsystem. Although the two subsystems exhibited different spectral sensitivities, the difference was small and no indication of color discrimination mechanisms was observed. Although all retinular cells 1 to 6 exhibited a preferred polarization plane, sustaining and on-off units did not. Likewise, motion detection and optomotor responses were insensitive to the polarization plane for long spatial wavelength stimuli; however, sensitivity to select polarization planes was observed for short spatial wavelengths. PMID:5027759

Spectral binning for energy production calculations and multijunction solar cell design

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

Garcia, Iván; McMahon, William E.; Habte, Aron

Currently, most solar cells are designed for and evaluated under standard spectra intended to represent typical spectral conditions. However, no single spectrum can capture the spectral variability needed for annual energy production (AEP) calculations, and this shortcoming becomes more significant for series-connected multijunction cells as the number of junctions increases. For this reason, AEP calculations are often performed on very detailed yearlong sets of data, but these pose 2 inherent challenges: (1) These data sets comprise thousands of data points, which appear as a scattered cloud of data when plotted against typical parameters and are hence cumbersome to classify andmore » compare, and (2) large sets of spectra bring with them a corresponding increase in computation or measurement time. Here, we show how a large spectral set can be reduced to just a few 'proxy' spectra, which still retain the spectral variability information needed for AEP design and evaluation. The basic 'spectral binning' methods should be extensible to a variety of multijunction device architectures. In this study, as a demonstration, the AEP of a 4-junction device is computed for both a full set of spectra and a reduced proxy set, and the results show excellent agreement for as few as 3 proxy spectra. This enables much faster (and thereby more detailed) calculations and indoor measurements and provides a manageable way to parameterize a spectral set, essentially creating a 'spectral fingerprint,' which should facilitate the understanding and comparison of different sites.« less

Physical Characterization of Warm Spitzer-observed Near-Earth Objects

NASA Technical Reports Server (NTRS)

Thomas, Cristina A.; Emery, Joshua P.; Trilling, David E.; Delbo, Marco; Hora, Joseph L.; Mueller, Michael

2014-01-01

Near-infrared spectroscopy of Near-Earth Objects (NEOs) connects diagnostic spectral features to specific surface mineralogies. The combination of spectroscopy with albedos and diameters derived from thermal infrared observations can increase the scientific return beyond that of the individual datasets. For instance, some taxonomic classes can be separated into distinct compositional groupings with albedo and different mineralogies with similar albedos can be distinguished with spectroscopy. To that end, we have completed a spectroscopic observing campaign to complement the ExploreNEOs Warm Spitzer program that obtained albedos and diameters of nearly 600 NEOs (Trilling et al., 2010). The spectroscopy campaign included visible and near-infrared observations of ExploreNEOs targets from various observatories. Here we present the results of observations using the low-resolution prism mode (approx. 0.7-2.5 microns) of the SpeX instrument on the NASA Infrared Telescope Facility (IRTF). We also include near-infrared observations of Explore-NEOs targets from the MIT-UH-IRTF Joint Campaign for Spectral Reconnaissance. Our dataset includes near-infrared spectra of 187 ExploreNEOs targets (125 observations of 92 objects from our survey and 213 observations of 154 objects from the MIT survey). We identify a taxonomic class for each spectrum and use band parameter analysis to investigate the mineralogies for the S-, Q-, and V-complex objects. Our analysis suggests that for spectra that contain near-infrared data but lack the visible wavelength region, the Bus-DeMeo system misidentifies some S-types as Q-types. We find no correlation between spectral band parameters and ExploreNEOs albedos and diameters. We investigate the correlations of phase angle with band area ratio and near-infrared spectral slope. We find slightly negative Band Area Ratio (BAR) correlations with phase angle for Eros and Ivar, but a positive BAR correlation with phase angle for Ganymed.The results of our phase angle study are consistent with those of (Sanchez et al., 2012). We find evidence for spectral phase reddening for Eros, Ganymed, and Ivar. We identify the likely ordinary chondrite type analog for an appropriate subset of our sample. Our resulting proportions of H, L, and LL ordinary chondrites differ from those calculated for meteorite falls and in previous studies of ordinary chondrite-like NEOs.

Detecting Pilot's Engagement Using fNIRS Connectivity Features in an Automated vs. Manual Landing Scenario

PubMed Central

Verdière, Kevin J.; Roy, Raphaëlle N.; Dehais, Frédéric

2018-01-01

Monitoring pilot's mental states is a relevant approach to mitigate human error and enhance human machine interaction. A promising brain imaging technique to perform such a continuous measure of human mental state under ecological settings is Functional Near-InfraRed Spectroscopy (fNIRS). However, to our knowledge no study has yet assessed the potential of fNIRS connectivity metrics as long as passive Brain Computer Interfaces (BCI) are concerned. Therefore, we designed an experimental scenario in a realistic simulator in which 12 pilots had to perform landings under two contrasted levels of engagement (manual vs. automated). The collected data were used to benchmark the performance of classical oxygenation features (i.e., Average, Peak, Variance, Skewness, Kurtosis, Area Under the Curve, and Slope) and connectivity features (i.e., Covariance, Pearson's, and Spearman's Correlation, Spectral Coherence, and Wavelet Coherence) to discriminate these two landing conditions. Classification performance was obtained by using a shrinkage Linear Discriminant Analysis (sLDA) and a stratified cross validation using each feature alone or by combining them. Our findings disclosed that the connectivity features performed significantly better than the classical concentration metrics with a higher accuracy for the wavelet coherence (average: 65.3/59.9 %, min: 45.3/45.0, max: 80.5/74.7 computed for HbO/HbR signals respectively). A maximum classification performance was obtained by combining the area under the curve with the wavelet coherence (average: 66.9/61.6 %, min: 57.3/44.8, max: 80.0/81.3 computed for HbO/HbR signals respectively). In a general manner all connectivity measures allowed an efficient classification when computed over HbO signals. Those promising results provide methodological cues for further implementation of fNIRS-based passive BCIs. PMID:29422841

Spectral compression algorithms for the analysis of very large multivariate images

DOEpatents

Keenan, Michael R.

2007-10-16

A method for spectrally compressing data sets enables the efficient analysis of very large multivariate images. The spectral compression algorithm uses a factored representation of the data that can be obtained from Principal Components Analysis or other factorization technique. Furthermore, a block algorithm can be used for performing common operations more efficiently. An image analysis can be performed on the factored representation of the data, using only the most significant factors. The spectral compression algorithm can be combined with a spatial compression algorithm to provide further computational efficiencies.

Time and frequency constrained sonar signal design for optimal detection of elastic objects.

PubMed

Hamschin, Brandon; Loughlin, Patrick J

2013-04-01

In this paper, the task of model-based transmit signal design for optimizing detection is considered. Building on past work that designs the spectral magnitude for optimizing detection, two methods for synthesizing minimum duration signals with this spectral magnitude are developed. The methods are applied to the design of signals that are optimal for detecting elastic objects in the presence of additive noise and self-noise. Elastic objects are modeled as linear time-invariant systems with known impulse responses, while additive noise (e.g., ocean noise or receiver noise) and acoustic self-noise (e.g., reverberation or clutter) are modeled as stationary Gaussian random processes with known power spectral densities. The first approach finds the waveform that preserves the optimal spectral magnitude while achieving the minimum temporal duration. The second approach yields a finite-length time-domain sequence by maximizing temporal energy concentration, subject to the constraint that the spectral magnitude is close (in a least-squares sense) to the optimal spectral magnitude. The two approaches are then connected analytically, showing the former is a limiting case of the latter. Simulation examples that illustrate the theory are accompanied by discussions that address practical applicability and how one might satisfy the need for target and environmental models in the real-world.

Relationship between channel interaction and spectral-ripple discrimination in cochlear implant usersa

PubMed Central

Jones, Gary L.; Ho Won, Jong; Drennan, Ward R.; Rubinstein, Jay T.

2013-01-01

Cochlear implant (CI) users can achieve remarkable speech understanding, but there is great variability in outcomes that is only partially accounted for by age, residual hearing, and duration of deafness. Results might be improved with the use of psychophysical tests to predict which sound processing strategies offer the best potential outcomes. In particular, the spectral-ripple discrimination test offers a time-efficient, nonlinguistic measure that is correlated with perception of both speech and music by CI users. Features that make this “one-point” test time-efficient, and thus potentially clinically useful, are also connected to controversy within the CI field about what the test measures. The current work examined the relationship between thresholds in the one-point spectral-ripple test, in which stimuli are presented acoustically, and interaction indices measured under the controlled conditions afforded by direct stimulation with a research processor. Results of these studies include the following: (1) within individual subjects there were large variations in the interaction index along the electrode array, (2) interaction indices generally decreased with increasing electrode separation, and (3) spectral-ripple discrimination improved with decreasing mean interaction index at electrode separations of one, three, and five electrodes. These results indicate that spectral-ripple discrimination thresholds can provide a useful metric of the spectral resolution of CI users. PMID:23297914

Relationship between channel interaction and spectral-ripple discrimination in cochlear implant users.

PubMed

Jones, Gary L; Won, Jong Ho; Drennan, Ward R; Rubinstein, Jay T

2013-01-01

Cochlear implant (CI) users can achieve remarkable speech understanding, but there is great variability in outcomes that is only partially accounted for by age, residual hearing, and duration of deafness. Results might be improved with the use of psychophysical tests to predict which sound processing strategies offer the best potential outcomes. In particular, the spectral-ripple discrimination test offers a time-efficient, nonlinguistic measure that is correlated with perception of both speech and music by CI users. Features that make this "one-point" test time-efficient, and thus potentially clinically useful, are also connected to controversy within the CI field about what the test measures. The current work examined the relationship between thresholds in the one-point spectral-ripple test, in which stimuli are presented acoustically, and interaction indices measured under the controlled conditions afforded by direct stimulation with a research processor. Results of these studies include the following: (1) within individual subjects there were large variations in the interaction index along the electrode array, (2) interaction indices generally decreased with increasing electrode separation, and (3) spectral-ripple discrimination improved with decreasing mean interaction index at electrode separations of one, three, and five electrodes. These results indicate that spectral-ripple discrimination thresholds can provide a useful metric of the spectral resolution of CI users.

A Steady-State Kalman Predictor-Based Filtering Strategy for Non-Overlapping Sub-Band Spectral Estimation

PubMed Central

Li, Zenghui; Xu, Bin; Yang, Jian; Song, Jianshe

2015-01-01

This paper focuses on suppressing spectral overlap for sub-band spectral estimation, with which we can greatly decrease the computational complexity of existing spectral estimation algorithms, such as nonlinear least squares spectral analysis and non-quadratic regularized sparse representation. Firstly, our study shows that the nominal ability of the high-order analysis filter to suppress spectral overlap is greatly weakened when filtering a finite-length sequence, because many meaningless zeros are used as samples in convolution operations. Next, an extrapolation-based filtering strategy is proposed to produce a series of estimates as the substitutions of the zeros and to recover the suppression ability. Meanwhile, a steady-state Kalman predictor is applied to perform a linearly-optimal extrapolation. Finally, several typical methods for spectral analysis are applied to demonstrate the effectiveness of the proposed strategy. PMID:25609038

Method of multivariate spectral analysis

DOEpatents

Keenan, Michael R.; Kotula, Paul G.

2004-01-06

A method of determining the properties of a sample from measured spectral data collected from the sample by performing a multivariate spectral analysis. The method can include: generating a two-dimensional matrix A containing measured spectral data; providing a weighted spectral data matrix D by performing a weighting operation on matrix A; factoring D into the product of two matrices, C and S.sup.T, by performing a constrained alternating least-squares analysis of D=CS.sup.T, where C is a concentration intensity matrix and S is a spectral shapes matrix; unweighting C and S by applying the inverse of the weighting used previously; and determining the properties of the sample by inspecting C and S. This method can be used to analyze X-ray spectral data generated by operating a Scanning Electron Microscope (SEM) with an attached Energy Dispersive Spectrometer (EDS).

Evaluation of Infrared Target Discrimination Algorithms.

DTIC Science & Technology

1983-04-01

application of this work is embodied in a computer program called PALANTIR , which Ref. 2 also describes in some detail. From a given set of narrow band spectral...chan- nels PALANTIR chooses a prescribed number of channels, picking those that will provide the least error when used in connection with a minimum

Relating zeta functions of discrete and quantum graphs

NASA Astrophysics Data System (ADS)

Harrison, Jonathan; Weyand, Tracy

2018-02-01

We write the spectral zeta function of the Laplace operator on an equilateral metric graph in terms of the spectral zeta function of the normalized Laplace operator on the corresponding discrete graph. To do this, we apply a relation between the spectrum of the Laplacian on a discrete graph and that of the Laplacian on an equilateral metric graph. As a by-product, we determine how the multiplicity of eigenvalues of the quantum graph, that are also in the spectrum of the graph with Dirichlet conditions at the vertices, depends on the graph geometry. Finally we apply the result to calculate the vacuum energy and spectral determinant of a complete bipartite graph and compare our results with those for a star graph, a graph in which all vertices are connected to a central vertex by a single edge.

Landsat-faciliated vegetation classification of the Kenai National Wildlife Refuge and adjacent areas, Alaska

USGS Publications Warehouse

Talbot, S. S.; Shasby, M.B.; Bailey, T.N.

1985-01-01

A Landsat-based vegetation map was prepared for Kenai National Wildlife Refuge and adjacent lands, 2 million and 2.5 million acres respectively. The refuge lies within the middle boreal sub zone of south central Alaska. Seven major classes and sixteen subclasses were recognized: forest (closed needleleaf, needleleaf woodland, mixed); deciduous scrub (lowland and montane, subalpine); dwarf scrub (dwarf shrub tundra, lichen tundra, dwarf shrub and lichen tundra, dwarf shrub peatland, string bog/wetlands); herbaceous (graminoid meadows and marshes); scarcely vegetated areas ; water (clear, moderately turbid, highly turbid); and glaciers. The methodology employed a cluster-block technique. Sample areas were described based on a combination of helicopter-ground survey, aerial photo interpretation, and digital Landsat data. Major steps in the Landsat analysis involved: preprocessing (geometric connection), spectral class labeling of sample areas, derivation of statistical parameters for spectral classes, preliminary classification of the entree study area using a maximum-likelihood algorithm, and final classification through ancillary information such as digital elevation data. The vegetation map (scale 1:250,000) was a pioneering effort since there were no intermediate-sclae maps of the area. Representative of distinctive regional patterns, the map was suitable for use in comprehensive conservation planning and wildlife management.

Comparing Shock geometry from MHD simulation to that from the Q/A-scaling analysis

NASA Astrophysics Data System (ADS)

Li, G.; Zhao, L.; Jin, M.

2017-12-01

In large SEP events, ions can be accelerated at CME-driven shocks to very high energies. Spectra of heavy ions in many large SEP events show features such as roll-overs or spectral breaks. In some events when the spectra are plotted in energy/nucleon they can be shifted relatively to each other so that the spectra align. The amount of shift is charge-to-mass ratio (Q/A) dependent and varies from event to event. In the work of Li et al. (2009), the Q/A dependences of the scaling is related to shock geometry when the CME-driven shock is close to the Sun. For events where multiple in-situ spacecraft observations exist, one may expect that different spacecraft are connected to different portions of the CME-driven shock that have different shock geometries, therefore yielding different Q/A dependence. At the same time, shock geometry can be also obtained from MHD simulations. This means we can compare shock geometry from two completely different approaches: one from MHD simulation and the other from in-situ spectral fitting. In this work, we examine this comparison for selected events.

On the change in the spectral composition of solar ultraviolet emission preceding proton flares, and its connection with the preflare fluctuations in the horizontal component of the geomagnetic field

NASA Astrophysics Data System (ADS)

Sheiner, Olga; Snegirev, Sergei; Smirnova, Anna

The importance problem of Solar-terrestrial physics is regular forecasting of solar activity phenomena, which negatively influence the human’s health, operating safety, communication, radar sets and others. We previously reported the existence of long-period pulsations of H component of the geomagnetic field recorded at stations tested 2-3 days before the proton solar flares. There are the increasing of pulsation amplitude of the horizontal component of the magnetic field with periods of 30-60 minutes. The spectrum of the flux of ultraviolet solar radiation on the eve of proton flares was conducted to determine the presence of oscillations - precursors of flares, as one of the possible agents causing amplification of large periods pulsations of H component of the geomagnetic field. Used data on ultraviolet radiation of the sun with a wavelength of 115-127 nm are obtained from a geostationary satellite GOES 15, the method of wavelet analysis is used. It is found the congruence in the behavior of spectral components with periods of 30-60 minutes in the ground-based measurements and in UV emission for 3-1 days before the proton flare.

Connections Between Jet Formation and Multiwavelength Spectral Evolution in Black Hole Transients

NASA Technical Reports Server (NTRS)

Kakemci, Emrah; Chun, Yoon-Young; Dincer, Tolga; Buxton, Michelle; Tomsick, John A.; Corbel, Stephane; Kaaret, Philip

2011-01-01

Multiwavelength observations are the key to understand conditions of jet formation in Galactic black hole transient (GBHT) systems. By studying radio and optical-infrared evolution of such systems during outburst decays, the compact jet formation can be traced. Comparing this with X-ray spectral and timing evolution we can obtain physical and geometrical conditions for jet formation, and study the contribution of jets to X-ray emission. In this work, first X-ray evolution - jet relation for XTE J1752-223 will be discussed. This source had very good coverage in X-rays, optical, infrared and radio. A long exposure with INTEGRAL also allowed us to study gamma-ray behavior after the jet turns on. We will also show results from the analysis of data from GX 339-4 in the hard state with SUZAKU at low flux levels. The fits to iron line fluorescence emission show that the inner disk radius increases by a factor of greater than 27 with respect to radii in bright states. This result, along with other disk radius measurements in the hard state will be discussed within the context of conditions for launching and sustaining jets.

A semi-supervised classification algorithm using the TAD-derived background as training data

NASA Astrophysics Data System (ADS)

Fan, Lei; Ambeau, Brittany; Messinger, David W.

2013-05-01

In general, spectral image classification algorithms fall into one of two categories: supervised and unsupervised. In unsupervised approaches, the algorithm automatically identifies clusters in the data without a priori information about those clusters (except perhaps the expected number of them). Supervised approaches require an analyst to identify training data to learn the characteristics of the clusters such that they can then classify all other pixels into one of the pre-defined groups. The classification algorithm presented here is a semi-supervised approach based on the Topological Anomaly Detection (TAD) algorithm. The TAD algorithm defines background components based on a mutual k-Nearest Neighbor graph model of the data, along with a spectral connected components analysis. Here, the largest components produced by TAD are used as regions of interest (ROI's),or training data for a supervised classification scheme. By combining those ROI's with a Gaussian Maximum Likelihood (GML) or a Minimum Distance to the Mean (MDM) algorithm, we are able to achieve a semi supervised classification method. We test this classification algorithm against data collected by the HyMAP sensor over the Cooke City, MT area and University of Pavia scene.

Spectral and Temporal Laser Fluorescence Analysis Such as for Natural Aquatic Environments

NASA Technical Reports Server (NTRS)

Chekalyuk, Alexander (Inventor)

2015-01-01

An Advanced Laser Fluorometer (ALF) can combine spectrally and temporally resolved measurements of laser-stimulated emission (LSE) for characterization of dissolved and particulate matter, including fluorescence constituents, in liquids. Spectral deconvolution (SDC) analysis of LSE spectral measurements can accurately retrieve information about individual fluorescent bands, such as can be attributed to chlorophyll-a (Chl-a), phycobiliprotein (PBP) pigments, or chromophoric dissolved organic matter (CDOM), among others. Improved physiological assessments of photosynthesizing organisms can use SDC analysis and temporal LSE measurements to assess variable fluorescence corrected for SDC-retrieved background fluorescence. Fluorescence assessments of Chl-a concentration based on LSE spectral measurements can be improved using photo-physiological information from temporal measurements. Quantitative assessments of PBP pigments, CDOM, and other fluorescent constituents, as well as basic structural characterizations of photosynthesizing populations, can be performed using SDC analysis of LSE spectral measurements.

Development and analysis of spectroscopic learning tools and the light and spectroscopy concept inventory for introductory college astronomy

NASA Astrophysics Data System (ADS)

Bardar, Erin M.

Electromagnetic radiation is the fundamental carrier of astronomical information. Spectral features serve as the fingerprints of the universe, revealing many important properties of objects in the cosmos such as temperature, elemental compositions, and relative motion. Because of its importance to astronomical research, the nature of light and the electromagnetic spectrum is by far the most universally covered topic in astronomy education. Yet, to the surprise and disappointment of instructors, many students struggle to understand underlying fundamental concepts related to light and spectroscopic phenomena. This dissertation describes research into introductory college astronomy students' understanding of light and spectroscopy concepts, through the development and analysis of both instructional materials and an assessment instrument. The purpose of this research was two-fold: (1) to develop a novel suite of spectroscopic learning tools that enhance student understanding of light and spectroscopy and (2) to design and validate a Light and Spectroscopy Concept Inventory (LSCI) with the sensitivity to distinguish the relative effectiveness of various teaching interventions within the context of introductory college astronomy. Through a systematic investigation that included multiple rounds of clinical interviews, open-ended written surveys, and multiple-choice testing, introductory college astronomy students' commonly held misconceptions and reasoning difficulties were explored for concepts relating to: (1) The nature of the electromagnetic spectrum, including the interrelationships of wavelength, frequency, energy, and speed; (2) interpretation of Doppler shift; (3) properties of blackbody radiation; and (4) the connection between spectral features and underlying physical processes. These difficulties guided the development of instructional materials including six unique "homelab" exercises, a binocular spectrometer, a spectral analysis software tool, and the 26-question Light and Spectroscopy Concept Inventory (LSCI). In the fall of 2005, a multi-institution field-test of the LSCI was conducted with student examinees from 14 course sections at 11 colleges and universities employing various instructional techniques. Through statistical analysis, the inventory was proven to be a reliable (Cronbach's alpha = 0.77) and valid assessment instrument that was able to illustrate statistically significant learning gains (p < 0.05) for most course sections, with students utilizing our suite of instructional materials exhibiting among the highest performance gains (Effect Size = 1.31).

Controls on Thermal Discharge in Yellowstone NAtional Park, Wyoming

NASA Astrophysics Data System (ADS)

Mohrmann, Jacob Steven

2007-10-01

Significant fluctuations in discharge occur in hot springs in Yellowstone National Park on a seasonal to decadal scale (Ingebritsen et al., 2001) and an hourly scale (Vitale, 2002). The purpose of this study was to determine the interval of the fluctuations in discharge and to explain what causes those discharge patterns in three thermally influenced streams in Yellowstone National Park. By monitoring flow in these streams, whose primary source of input is thermal discharge, we were able to find several significant patterns of discharge fluctuations. Patterns were found by using two techniques of spectral analysis. The spectral analyses completed involved using the program "R" as well as Microsoft Excel, both of which use Fourier transforms. The Fourier transform is a linear operator that identifies frequencies in the original function. Stream flow data were collected using a FloDar open channel flow monitor. The flow meter collected data at15-minute intervals at White Creek and Rabbit Creek for a period of approximately two weeks each during the Fall. Flow data were also used from 15-minute data interval from a USGS gaging station at Tantalus Creek. Patterns of discharge fluctuation were found in each stream. By comparing spectral analysis results of flow data with spectral analysis of published tide data and barometric pressure data, connections were drawn between fluctuations in tidal and barometric-pressure patterns and flow patterns. Also, visual comparisons used to identify potential correspondence with earthquakes and precipitation events. At Tantalus Creek, patterns were affected only by barometric pressure changes. At White Creek, one pattern was attributed to barometric pressure fluctuations, and another pattern was found that could be associated with earth-tide forces. At Rabbit Creek, these patterns were absent. A pattern at 8.55 hours, which could not be attributed to barometric pressure or earth tide forces, was found at Rabbit and White Creeks. The 8.55 hour pattern in discharge found at both Rabbit and White Creeks may suggest a physical link between the sites, which are close (2.5 km). The time pattern could be a result of a shared hydrothermal aquifer, convectively heating and discharging at both streams. However, the common time pattern could also be the result of independent factors, which coincidentally caused a similar time pattern.

Classification of river water pollution using Hyperion data

NASA Astrophysics Data System (ADS)

Kar, Soumyashree; Rathore, V. S.; Champati ray, P. K.; Sharma, Richa; Swain, S. K.

2016-06-01

A novel attempt is made to use hyperspectral remote sensing to identify the spatial variability of metal pollutants present in river water. It was also attempted to classify the hyperspectral image - Earth Observation-1 (EO-1) Hyperion data of an 8 km stretch of the river Yamuna, near Allahabad city in India depending on its chemical composition. For validating image analysis results, a total of 10 water samples were collected and chemically analyzed using Inductively Coupled Plasma-Optical Emission Spectroscopy (ICP-OES). Two different spectral libraries from field and image data were generated for the 10 sample locations. Advanced per-pixel supervised classifications such as Spectral Angle Mapper (SAM), SAM target finder using BandMax and Support Vector Machine (SVM) were carried out along with the unsupervised clustering procedure - Iterative Self-Organizing Data Analysis Technique (ISODATA). The results were compared and assessed with respect to ground data. Analytical Spectral Devices (ASD), Inc. spectroradiometer, FieldSpec 4 was used to generate the spectra of the water samples which were compiled into a spectral library and used for Spectral Absorption Depth (SAD) analysis. The spectral depth pattern of image and field spectral libraries was found to be highly correlated (correlation coefficient, R2 = 0.99) which validated the image analysis results with respect to the ground data. Further, we carried out a multivariate regression analysis to assess the varying concentrations of metal ions present in water based on the spectral depth of the corresponding absorption feature. Spectral Absorption Depth (SAD) analysis along with metal analysis of field data revealed the order in which the metals affected the river pollution, which was in conformity with the findings of Central Pollution Control Board (CPCB). Therefore, it is concluded that hyperspectral imaging provides opportunity that can be used for satellite based remote monitoring of water quality from space.

Automatic classification of spectral units in the Aristarchus plateau

NASA Astrophysics Data System (ADS)

Erard, S.; Le Mouelic, S.; Langevin, Y.

1999-09-01

A reduction scheme has been recently proposed for the NIR images of Clementine (Le Mouelic et al, JGR 1999). This reduction has been used to build an integrated UVvis-NIR image cube of the Aristarchus region, from which compositional and maturity variations can be studied (Pinet et al, LPSC 1999). We will present an analysis of this image cube, providing a classification in spectral types and spectral units. The image cube is processed with Gmode analysis using three different data sets: Normalized spectra provide a classification based mainly on spectral slope variations (ie. maturity and volcanic glasses). This analysis discriminates between craters plus ejecta, mare basalts, and DMD. Olivine-rich areas and Aristarchus central peak are also recognized. Continuum-removed spectra provide a classification more related to compositional variations, which correctly identifies olivine and pyroxenes-rich areas (in Aristarchus, Krieger, Schiaparelli\\ldots). A third analysis uses spectral parameters related to maturity and Fe composition (reflectance, 1 mu m band depth, and spectral slope) rather than intensities. It provides the most spatially consistent picture, but fails in detecting Vallis Schroeteri and DMDs. A supplementary unit, younger and rich in pyroxene, is found on Aristarchus south rim. In conclusion, Gmode analysis can discriminate between different spectral types already identified with more classic methods (PCA, linear mixing\\ldots). No previous assumption is made on the data structure, such as endmembers number and nature, or linear relationship between input variables. The variability of the spectral types is intrinsically accounted for, so that the level of analysis is always restricted to meaningful limits. A complete classification should integrate several analyses based on different sets of parameters. Gmode is therefore a powerful light toll to perform first look analysis of spectral imaging data. This research has been partly founded by the French Programme National de Planetologie.

The Spectral Web of stationary plasma equilibria. II. Internal modes

NASA Astrophysics Data System (ADS)

Goedbloed, J. P.

2018-03-01

The new method of the Spectral Web to calculate the spectrum of waves and instabilities of plasma equilibria with sizeable flows, developed in the preceding Paper I [Goedbloed, Phys. Plasmas 25, 032109 (2018)], is applied to a collection of classical magnetohydrodynamic instabilities operating in cylindrical plasmas with shear flow or rotation. After a review of the basic concepts of the complementary energy giving the solution path and the conjugate path, which together constitute the Spectral Web, the cylindrical model is presented and the spectral equations are derived. The first example concerns the internal kink instabilities of a cylindrical force-free magnetic field of constant α subjected to a parabolic shear flow profile. The old stability diagram and the associated growth rate calculations for static equilibria are replaced by a new intricate stability diagram and associated complex growth rates for the stationary model. The power of the Spectral Web method is demonstrated by showing that the two associated paths in the complex ω-plane nearly automatically guide to the new class of global Alfvén instabilities of the force-free configuration that would have been very hard to predict by other methods. The second example concerns the Rayleigh-Taylor instability of a rotating theta-pinch. The old literature is revisited and shown to suffer from inconsistencies that are remedied. The most global n = 1 instability and a cluster sequence of more local but much more unstable n =2 ,3 ,…∞ modes are located on separate solution paths in the hydrodynamic (HD) version of the instability, whereas they merge in the MHD version. The Spectral Web offers visual demonstration of the central position the HD flow continuum and of the MHD Alfvén and slow magneto-sonic continua in the respective spectra by connecting the discrete modes in the complex plane by physically meaningful curves towards the continua. The third example concerns the magneto-rotational instability (MRI) thought to be operating in accretion disks about black holes. The sequence n =1 ,2 ,… of unstable MRIs is located on one continuous solution path, but also on infinitely many separate loops ("pancakes") of the conjugate path with just one MRI on each of them. For narrow accretion disks, those sequences are connected with the slow magneto-sonic continuum, which is far away though from the marginal stability transition. In this case, the Spectral Web method is the first to effectively incorporate the MRIs into the general MHD spectral theory of equilibria with background flows. Together, the three examples provide compelling evidence of the computational power of the Spectral Web Method.

[Estimation of Hunan forest carbon density based on spectral mixture analysis of MODIS data].

PubMed

Yan, En-ping; Lin, Hui; Wang, Guang-xing; Chen, Zhen-xiong

2015-11-01

With the fast development of remote sensing technology, combining forest inventory sample plot data and remotely sensed images has become a widely used method to map forest carbon density. However, the existence of mixed pixels often impedes the improvement of forest carbon density mapping, especially when low spatial resolution images such as MODIS are used. In this study, MODIS images and national forest inventory sample plot data were used to conduct the study of estimation for forest carbon density. Linear spectral mixture analysis with and without constraint, and nonlinear spectral mixture analysis were compared to derive the fractions of different land use and land cover (LULC) types. Then sequential Gaussian co-simulation algorithm with and without the fraction images from spectral mixture analyses were employed to estimate forest carbon density of Hunan Province. Results showed that 1) Linear spectral mixture analysis with constraint, leading to a mean RMSE of 0.002, more accurately estimated the fractions of LULC types than linear spectral and nonlinear spectral mixture analyses; 2) Integrating spectral mixture analysis model and sequential Gaussian co-simulation algorithm increased the estimation accuracy of forest carbon density to 81.5% from 74.1%, and decreased the RMSE to 5.18 from 7.26; and 3) The mean value of forest carbon density for the province was 30.06 t · hm(-2), ranging from 0.00 to 67.35 t · hm(-2). This implied that the spectral mixture analysis provided a great potential to increase the estimation accuracy of forest carbon density on regional and global level.

Spectral analysis for GNSS coordinate time series using chirp Fourier transform

NASA Astrophysics Data System (ADS)

Feng, Shengtao; Bo, Wanju; Ma, Qingzun; Wang, Zifan

2017-12-01

Spectral analysis for global navigation satellite system (GNSS) coordinate time series provides a principal tool to understand the intrinsic mechanism that affects tectonic movements. Spectral analysis methods such as the fast Fourier transform, Lomb-Scargle spectrum, evolutionary power spectrum, wavelet power spectrum, etc. are used to find periodic characteristics in time series. Among spectral analysis methods, the chirp Fourier transform (CFT) with less stringent requirements is tested with synthetic and actual GNSS coordinate time series, which proves the accuracy and efficiency of the method. With the length of series only limited to even numbers, CFT provides a convenient tool for windowed spectral analysis. The results of ideal synthetic data prove CFT accurate and efficient, while the results of actual data show that CFT is usable to derive periodic information from GNSS coordinate time series.

Determination of awareness in patients with severe brain injury using EEG power spectral analysis

PubMed Central

Goldfine, Andrew M.; Victor, Jonathan D.; Conte, Mary M.; Bardin, Jonathan C.; Schiff, Nicholas D.

2011-01-01

Objective To determine whether EEG spectral analysis could be used to demonstrate awareness in patients with severe brain injury. Methods We recorded EEG from healthy controls and three patients with severe brain injury, ranging from minimally conscious state (MCS) to locked-in-state (LIS), while they were asked to imagine motor and spatial navigation tasks. We assessed EEG spectral differences from 4 to 24 Hz with univariate comparisons (individual frequencies) and multivariate comparisons (patterns across the frequency range). Results In controls, EEG spectral power differed at multiple frequency bands and channels during performance of both tasks compared to a resting baseline. As patterns of signal change were inconsistent between controls, we defined a positive response in patient subjects as consistent spectral changes across task performances. One patient in MCS and one in LIS showed evidence of motor imagery task performance, though with patterns of spectral change different from the controls. Conclusion EEG power spectral analysis demonstrates evidence for performance of mental imagery tasks in healthy controls and patients with severe brain injury. Significance EEG power spectral analysis can be used as a flexible bedside tool to demonstrate awareness in brain-injured patients who are otherwise unable to communicate. PMID:21514214

Intrinsic Connectivity Provides the Baseline Framework for Variability in Motor Performance: A Multivariate Fusion Analysis of Low- and High-Frequency Resting-State Oscillations and Antisaccade Performance.

PubMed

Jamadar, Sharna D; Egan, Gary F; Calhoun, Vince D; Johnson, Beth; Fielding, Joanne

2016-07-01

Intrinsic brain activity provides the functional framework for the brain's full repertoire of behavioral responses; that is, a common mechanism underlies intrinsic and extrinsic neural activity, with extrinsic activity building upon the underlying baseline intrinsic activity. The generation of a motor movement in response to sensory stimulation is one of the most fundamental functions of the central nervous system. Since saccadic eye movements are among our most stereotyped motor responses, we hypothesized that individual variability in the ability to inhibit a prepotent saccade and make a voluntary antisaccade would be related to individual variability in intrinsic connectivity. Twenty-three individuals completed the antisaccade task and resting-state functional magnetic resonance imaging (fMRI). A multivariate analysis of covariance identified relationships between fMRI oscillations (0.01-0.2 Hz) of resting-state networks determined using high-dimensional independent component analysis and antisaccade performance (latency, error rate). Significant multivariate relationships between antisaccade latency and directional error rate were obtained in independent components across the entire brain. Some of the relationships were obtained in components that overlapped substantially with the task; however, many were obtained in components that showed little overlap with the task. The current results demonstrate that even in the absence of a task, spectral power in regions showing little overlap with task activity predicts an individual's performance on a saccade task.

An Improved Spectral Analysis Method for Fatigue Damage Assessment of Details in Liquid Cargo Tanks

NASA Astrophysics Data System (ADS)

Zhao, Peng-yuan; Huang, Xiao-ping

2018-03-01

Errors will be caused in calculating the fatigue damages of details in liquid cargo tanks by using the traditional spectral analysis method which is based on linear system, for the nonlinear relationship between the dynamic stress and the ship acceleration. An improved spectral analysis method for the assessment of the fatigue damage in detail of a liquid cargo tank is proposed in this paper. Based on assumptions that the wave process can be simulated by summing the sinusoidal waves in different frequencies and the stress process can be simulated by summing the stress processes induced by these sinusoidal waves, the stress power spectral density (PSD) is calculated by expanding the stress processes induced by the sinusoidal waves into Fourier series and adding the amplitudes of each harmonic component with the same frequency. This analysis method can take the nonlinear relationship into consideration and the fatigue damage is then calculated based on the PSD of stress. Take an independent tank in an LNG carrier for example, the accuracy of the improved spectral analysis method is proved much better than that of the traditional spectral analysis method by comparing the calculated damage results with the results calculated by the time domain method. The proposed spectral analysis method is more accurate in calculating the fatigue damages in detail of ship liquid cargo tanks.

Sub-Thz Vibrational Spectroscopy for Analysis of Ovarian Cancer Cells

NASA Astrophysics Data System (ADS)

Ferrance, Jerome P.; Sizov, Igor; Jazaeri, Amir; Moyer, Aaron; Gelmont, Boris; Globus, Tatiana

2016-06-01

Sub-THz vibrational spectroscopy utilizes wavelengths in the submillimeter-wave range ( 1.5-30 wn), beyond those traditionally used for chemical and biomolecular analysis. This low energy radiation excites low-frequency internal molecular motions (vibrations) involving hydrogen bonds and other weak connections within these molecules. The ability of sub-THz spectroscopy to identify and quantify biological molecules is based on detection of signature resonance absorbance at specific frequencies between 0.05 and 1 THz, for each molecule. The long wavelengths of this radiation, mean that it can even pass through entire cells, detecting the combinations of proteins and nucleic acids that exist within the cell. This research introduces a novel sub-THz resonance spectroscopy instrument with spectral resolution sufficient to identify individual resonance absorption peaks, for the analysis of ovarian cancer cells. In vitro cell cultures of SK-OV-3 and ES-2 cells, two human ovarian cancer subtypes, were characterized and compared with a normal non-transformed human fallopian tube epithelial cell line (FT131). A dramatic difference was observed between the THz absorption spectra of the cancer and normal cell sample materials with much higher absorption intensity and a very strong absorption peak at a frequency of 13 wn dominating the cancer sample spectra. Comparison of experimental spectra with molecular dynamic simulated spectroscopic signatures suggests that the high intensity spectral peak could originate from overexpressed mi-RNA molecules specific for ovarian cancer. Ovarian cancer cells are utilized as a proof of concept, but the sub-THz spectroscopy method is very general and could also be applied to other types of cancer.

Intelligent MEMS spectral sensor for NIR applications (Conference Presentation)

NASA Astrophysics Data System (ADS)

Kantojärvi, Uula; Antila, Jarkko E.; Mäkynen, Jussi; Suhonen, Janne

2017-05-01

Near Infrared (NIR) spectrometers have been widely used in many material inspection applications, but mainly in central laboratories. The role of miniaturization, robustness of spectrometer and portability are really crucial when field inspection tools should be developed. We present an advanced spectral sensor based on a tunable Microelectromechanical (MEMS) Fabry-Perot Interferometer which will meet these requirements. We describe the wireless device design, operation principle and easy-to-use algorithms to adapt the sensor to number of applications. Multiple devices can be operated simultaneously and seamlessly through cloud connectivity. We also present some practical NIR applications carried out with truly portable NIR device.

Non-axisymmetric local magnetostatic equilibrium

DOE PAGES

Candy, Jefferey M.; Belli, Emily A.

2015-03-24

In this study, we outline an approach to the problem of local equilibrium in non-axisymmetric configurations that adheres closely to Miller's original method for axisymmetric plasmas. Importantly, this method is novel in that it allows not only specification of 3D shape, but also explicit specification of the shear in the 3D shape. A spectrally-accurate method for solution of the resulting nonlinear partial differential equations is also developed. We verify the correctness of the spectral method, in the axisymmetric limit, through comparisons with an independent numerical solution. Some analytic results for the two-dimensional case are given, and the connection to Boozermore » coordinates is clarified.« less

No Disk Winds in Failed Black Hole Outbursts? New Observations of H1743-322

NASA Astrophysics Data System (ADS)

Neilsen, Joseph; Coriat, Mickael; Motta, Sara; Fender, Rob P.; Ponti, Gabriele; Corbel, Stephane

2016-04-01

The rich and complex physics of stellar-mass black holes in outburst is often referred to as the "disk-jet connection," a term that encapsulates the evolution of accretion disks over several orders of magnitude in Eddington ratio; through Compton scattering, reflection, and thermal emission; as they produce steady compact jets, relativistic plasma ejections, and (from high spectral resolution revelations of the last 15 years) massive, ionized disk winds. It is well established that steady jets are associated with radiatively inefficient X-ray states, and that winds tend to appear during states with more luminous disks, but the underlying physical processes that govern these connections (and their changes during state transitions) are not fully understood. I will present a unique perspective on the disk-wind-jet connection based on new Chandra HETGS, NuSTAR, and JVLA observations of the black hole H1743-322. Rather than following the usual outburst track, the 2015 outburst of H1743 fizzled: the disk never appeared in X-rays, and the source remained spectrally hard for the entire ~100 days. Remarkably, we find no evidence for any accretion disk wind in our data, even though H1743-322 has produced winds at comparable hard X-ray luminosities. I will discuss the implications of this "failed outburst" for our picture of winds from black holes and the astrophysics that governs them.

Target detection using the background model from the topological anomaly detection algorithm

NASA Astrophysics Data System (ADS)

Dorado Munoz, Leidy P.; Messinger, David W.; Ziemann, Amanda K.

2013-05-01

The Topological Anomaly Detection (TAD) algorithm has been used as an anomaly detector in hyperspectral and multispectral images. TAD is an algorithm based on graph theory that constructs a topological model of the background in a scene, and computes an anomalousness ranking for all of the pixels in the image with respect to the background in order to identify pixels with uncommon or strange spectral signatures. The pixels that are modeled as background are clustered into groups or connected components, which could be representative of spectral signatures of materials present in the background. Therefore, the idea of using the background components given by TAD in target detection is explored in this paper. In this way, these connected components are characterized in three different approaches, where the mean signature and endmembers for each component are calculated and used as background basis vectors in Orthogonal Subspace Projection (OSP) and Adaptive Subspace Detector (ASD). Likewise, the covariance matrix of those connected components is estimated and used in detectors: Constrained Energy Minimization (CEM) and Adaptive Coherence Estimator (ACE). The performance of these approaches and the different detectors is compared with a global approach, where the background characterization is derived directly from the image. Experiments and results using self-test data set provided as part of the RIT blind test target detection project are shown.

Crab Nebula Variations in Hard X-rays

NASA Technical Reports Server (NTRS)

Wilson-Hodge, Colleen A.

2012-01-01

The Crab Nebula was surprisingly variable from 2001-2010, with less variability before 2001 and since mid-2010. We presented evidence for spectral softening from RXTE, Swift/BAT, and Fermi GBM during the mid-2008-2010 flux decline. We see no clear connections between the hard X-ray variations and the GeV flares

Finite plateau in spectral gap of polychromatic constrained random networks

NASA Astrophysics Data System (ADS)

Avetisov, V.; Gorsky, A.; Nechaev, S.; Valba, O.

2017-12-01

We consider critical behavior in the ensemble of polychromatic Erdős-Rényi networks and regular random graphs, where network vertices are painted in different colors. The links can be randomly removed and added to the network subject to the condition of the vertex degree conservation. In these constrained graphs we run the Metropolis procedure, which favors the connected unicolor triads of nodes. Changing the chemical potential, μ , of such triads, for some wide region of μ , we find the formation of a finite plateau in the number of intercolor links, which exactly matches the finite plateau in the network algebraic connectivity (the value of the first nonvanishing eigenvalue of the Laplacian matrix, λ2). We claim that at the plateau the spontaneously broken Z2 symmetry is restored by the mechanism of modes collectivization in clusters of different colors. The phenomena of a finite plateau formation holds also for polychromatic networks with M ≥2 colors. The behavior of polychromatic networks is analyzed via the spectral properties of their adjacency and Laplacian matrices.

A Protocol for Using Förster Resonance Energy Transfer (FRET)-force Biosensors to Measure Mechanical Forces across the Nuclear LINC Complex.

PubMed

Arsenovic, Paul T; Bathula, Kranthidhar; Conway, Daniel E

2017-04-11

The LINC complex has been hypothesized to be the critical structure that mediates the transfer of mechanical forces from the cytoskeleton to the nucleus. Nesprin-2G is a key component of the LINC complex that connects the actin cytoskeleton to membrane proteins (SUN domain proteins) in the perinuclear space. These membrane proteins connect to lamins inside the nucleus. Recently, a Förster Resonance Energy Transfer (FRET)-force probe was cloned into mini-Nesprin-2G (Nesprin-TS (tension sensor)) and used to measure tension across Nesprin-2G in live NIH3T3 fibroblasts. This paper describes the process of using Nesprin-TS to measure LINC complex forces in NIH3T3 fibroblasts. To extract FRET information from Nesprin-TS, an outline of how to spectrally unmix raw spectral images into acceptor and donor fluorescent channels is also presented. Using open-source software (ImageJ), images are pre-processed and transformed into ratiometric images. Finally, FRET data of Nesprin-TS is presented, along with strategies for how to compare data across different experimental groups.

Statistical iterative material image reconstruction for spectral CT using a semi-empirical forward model

NASA Astrophysics Data System (ADS)

Mechlem, Korbinian; Ehn, Sebastian; Sellerer, Thorsten; Pfeiffer, Franz; Noël, Peter B.

2017-03-01

In spectral computed tomography (spectral CT), the additional information about the energy dependence of attenuation coefficients can be exploited to generate material selective images. These images have found applications in various areas such as artifact reduction, quantitative imaging or clinical diagnosis. However, significant noise amplification on material decomposed images remains a fundamental problem of spectral CT. Most spectral CT algorithms separate the process of material decomposition and image reconstruction. Separating these steps is suboptimal because the full statistical information contained in the spectral tomographic measurements cannot be exploited. Statistical iterative reconstruction (SIR) techniques provide an alternative, mathematically elegant approach to obtaining material selective images with improved tradeoffs between noise and resolution. Furthermore, image reconstruction and material decomposition can be performed jointly. This is accomplished by a forward model which directly connects the (expected) spectral projection measurements and the material selective images. To obtain this forward model, detailed knowledge of the different photon energy spectra and the detector response was assumed in previous work. However, accurately determining the spectrum is often difficult in practice. In this work, a new algorithm for statistical iterative material decomposition is presented. It uses a semi-empirical forward model which relies on simple calibration measurements. Furthermore, an efficient optimization algorithm based on separable surrogate functions is employed. This partially negates one of the major shortcomings of SIR, namely high computational cost and long reconstruction times. Numerical simulations and real experiments show strongly improved image quality and reduced statistical bias compared to projection-based material decomposition.

Multispectral analysis tools can increase utility of RGB color images in histology

NASA Astrophysics Data System (ADS)

Fereidouni, Farzad; Griffin, Croix; Todd, Austin; Levenson, Richard

2018-04-01

Multispectral imaging (MSI) is increasingly finding application in the study and characterization of biological specimens. However, the methods typically used come with challenges on both the acquisition and the analysis front. MSI can be slow and photon-inefficient, leading to long imaging times and possible phototoxicity and photobleaching. The resulting datasets can be large and complex, prompting the development of a number of mathematical approaches for segmentation and signal unmixing. We show that under certain circumstances, just three spectral channels provided by standard color cameras, coupled with multispectral analysis tools, including a more recent spectral phasor approach, can efficiently provide useful insights. These findings are supported with a mathematical model relating spectral bandwidth and spectral channel number to achievable spectral accuracy. The utility of 3-band RGB and MSI analysis tools are demonstrated on images acquired using brightfield and fluorescence techniques, as well as a novel microscopy approach employing UV-surface excitation. Supervised linear unmixing, automated non-negative matrix factorization and phasor analysis tools all provide useful results, with phasors generating particularly helpful spectral display plots for sample exploration.

Blast investigation by fast multispectral radiometric analysis

NASA Astrophysics Data System (ADS)

Devir, A. D.; Bushlin, Y.; Mendelewicz, I.; Lessin, A. B.; Engel, M.

2011-06-01

Knowledge regarding the processes involved in blasts and detonations is required in various applications, e.g. missile interception, blasts of high-explosive materials, final ballistics and IED identification. Blasts release large amount of energy in short time duration. Some part of this energy is released as intense radiation in the optical spectral bands. This paper proposes to measure the blast radiation by a fast multispectral radiometer. The measurement is made, simultaneously, in appropriately chosen spectral bands. These spectral bands provide extensive information on the physical and chemical processes that govern the blast through the time-dependence of the molecular and aerosol contributions to the detonation products. Multi-spectral blast measurements are performed in the visible, SWIR and MWIR spectral bands. Analysis of the cross-correlation between the measured multi-spectral signals gives the time dependence of the temperature, aerosol and gas composition of the blast. Farther analysis of the development of these quantities in time may indicate on the order of the detonation and amount and type of explosive materials. Examples of analysis of measured explosions are presented to demonstrate the power of the suggested fast multispectral radiometric analysis approach.

Measurements on the Magdalen Islands VAWT and future projects

NASA Astrophysics Data System (ADS)

Gallagher, N. C.; Rangi, R. S.

The rotor of a 224 kW vertical axis wind turbine (VAWT) is discussed. The rebuilt rotor of the 224 kW Magdalen Islands VAWT was installed in Sept. 1979 and is operating at its design speed (36.6 rpm). Agreement between measured and theoretical performance is generally good except that maximum power may exceed theoretical predictions. Measurements of drive train losses, torque and power ripple, and rotor stresses are discussed. Although peak-to-peak cyclic stress levels are low in relation to fatigue life limits, spectral analysis of stress data indicates that the 3-per-rev component is amplified by near-resonance with the first butterfly blade mode. This resonance was subsequently de-coupled by a damped connection between the blade struts and the central column.

[Age and gender characteristics of the content of macro- and trace elements in the organisms of the children from the European North].

PubMed

Soroko, S I; Maksimova, I A; Protasova, O V

2014-01-01

By means of the nuclear-emission spectral analysis with inductively connected argon plasma were studied the contents of 28 macro- and trace elements (Al, Ag, Li, Ba, Bi, Ca, Cd, Co, Cr, Cu, Fe, Ga, In, K, Mg, Mn, Na, Ni, Mo, P, Zn, Se, Tl, Pb, Sr, S, Si) in the hair of children and teenagers living in the European North of the Russian Federation (Arkhangelsk region). There were revealed both: decrease and increase of some elements' contents. Also were revealed the dynamics of mentioned elements contents in the hair of the same children in different years. Significant individual variability of the macro and trace elements' status of children-northerners and some gender dependence were revealed.

Development and creation of a remote-controlled underwater laser induced breakdown spectrometer for analysis of the chemical composition of sea water and bottom sediments

NASA Astrophysics Data System (ADS)

Golik, Sergey S.; Mayor, Alexsander Yu.; Proschenko, Dmitriy Yu.; Ilyin, Alexey A.; Nagorniy, Ivan G.; Biryukova, Yuliya S.; Babiy, Michael Yu.; Golik, Natalia N.; Gevorgyan, Tigran A.; Lisitsa, Vladimir V.; Borovskiy, Anton V.; Kulchin, Yuri N.

2017-10-01

The developed underwater laser induced breakdown spectrometer consists of two units: 1- remotely operated vehicle (ROV) with the next main characteristics: work deep - up to 150 meters, maximum speed of immersion 1 m/s, maximum cruise velocity - 2 m/s and 2 - spectrometer unit (SU) consist of a DPSS Nd: YAG laser excitation source (double pulse with 50 mJ energy for each pulse at wavelength 1064 nm, pulse width 12 ns and pulse repetition rate 1-15 Hz, DF251, SOL Instruments), a spectrum recording system (Maya HR4000 or 2000 Pro spectrometer, Ocean Optics) and microcomputer. These two units are connected by Ethernet network and registered spectral data are automatically processed in a MATLAB platform.

Diffusion spectral imaging modules correlate with EEG LORETA neuroimaging modules.

PubMed

Thatcher, Robert W; North, Duane M; Biver, Carl J

2012-05-01

The purpose of this study was to test the hypothesis that the highest temporal correlations between 3-dimensional EEG current source density corresponds to anatomical Modules of high synaptic connectivity. Eyes closed and eyes open EEG was recorded from 19 scalp locations with a linked ears reference from 71 subjects age 13-42 years. LORETA was computed from 1 to 30 Hz in 2,394 cortical gray matter voxels that were grouped into six anatomical Modules corresponding to the ROIs in the Hagmann et al.'s [2008] diffusion spectral imaging (DSI) study. All possible cross-correlations between voxels within a DSI Module were compared with the correlations between Modules. The Hagmann et al. [ 2008] Module correlation structure was replicated in the correlation structure of EEG three-dimensional current source density. EEG Temporal correlation between brain regions is related to synaptic density as measured by diffusion spectral imaging. Copyright © 2011 Wiley-Liss, Inc.

THE IMPACT OF ACCURATE EXTINCTION MEASUREMENTS FOR X-RAY SPECTRAL MODELS

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

Smith, Randall K.; Valencic, Lynne A.; Corrales, Lia, E-mail: lynne.a.valencic@nasa.gov

Interstellar extinction includes both absorption and scattering of photons from interstellar gas and dust grains, and it has the effect of altering a source's spectrum and its total observed intensity. However, while multiple absorption models exist, there are no useful scattering models in standard X-ray spectrum fitting tools, such as XSPEC. Nonetheless, X-ray halos, created by scattering from dust grains, are detected around even moderately absorbed sources, and the impact on an observed source spectrum can be significant, if modest, compared to direct absorption. By convolving the scattering cross section with dust models, we have created a spectral model asmore » a function of energy, type of dust, and extraction region that can be used with models of direct absorption. This will ensure that the extinction model is consistent and enable direct connections to be made between a source's X-ray spectral fits and its UV/optical extinction.« less

Improving urban land use and land cover classification from high-spatial-resolution hyperspectral imagery using contextual information

NASA Astrophysics Data System (ADS)

Yang, He; Ma, Ben; Du, Qian; Yang, Chenghai

2010-08-01

In this paper, we propose approaches to improve the pixel-based support vector machine (SVM) classification for urban land use and land cover (LULC) mapping from airborne hyperspectral imagery with high spatial resolution. Class spatial neighborhood relationship is used to correct the misclassified class pairs, such as roof and trail, road and roof. These classes may be difficult to be separated because they may have similar spectral signatures and their spatial features are not distinct enough to help their discrimination. In addition, misclassification incurred from within-class trivial spectral variation can be corrected by using pixel connectivity information in a local window so that spectrally homogeneous regions can be well preserved. Our experimental results demonstrate the efficiency of the proposed approaches in classification accuracy improvement. The overall performance is competitive to the object-based SVM classification.

Facilitated assignment of large protein NMR signals with covariance sequential spectra using spectral derivatives.

PubMed

Harden, Bradley J; Nichols, Scott R; Frueh, Dominique P

2014-09-24

Nuclear magnetic resonance (NMR) studies of larger proteins are hampered by difficulties in assigning NMR resonances. Human intervention is typically required to identify NMR signals in 3D spectra, and subsequent procedures depend on the accuracy of this so-called peak picking. We present a method that provides sequential connectivities through correlation maps constructed with covariance NMR, bypassing the need for preliminary peak picking. We introduce two novel techniques to minimize false correlations and merge the information from all original 3D spectra. First, we take spectral derivatives prior to performing covariance to emphasize coincident peak maxima. Second, we multiply covariance maps calculated with different 3D spectra to destroy erroneous sequential correlations. The maps are easy to use and can readily be generated from conventional triple-resonance experiments. Advantages of the method are demonstrated on a 37 kDa nonribosomal peptide synthetase domain subject to spectral overlap.

Spectral analysis using the CCD Chirp Z-transform

NASA Technical Reports Server (NTRS)

Eversole, W. L.; Mayer, D. J.; Bosshart, P. W.; Dewit, M.; Howes, C. R.; Buss, D. D.

1978-01-01

The charge coupled device (CCD) Chirp Z transformation (CZT) spectral analysis techniques were reviewed and results on state-of-the-art CCD CZT technology are presented. The CZT algorithm was examined and the advantages of CCD implementation are discussed. The sliding CZT which is useful in many spectral analysis applications is described, and the performance limitations of the CZT are studied.

Single season changes in resting state network power and the connectivity between regions distinguish head impact exposure level in high school and youth football players

NASA Astrophysics Data System (ADS)

Murugesan, Gowtham; Saghafi, Behrouz; Davenport, Elizabeth; Wagner, Ben; Urban, Jillian; Kelley, Mireille; Jones, Derek; Powers, Alex; Whitlow, Christopher; Stitzel, Joel; Maldjian, Joseph; Montillo, Albert

2018-02-01

The effect of repetitive sub-concussive head impact exposure in contact sports like American football on brain health is poorly understood, especially in the understudied populations of youth and high school players. These players, aged 9-18 years old may be particularly susceptible to impact exposure as their brains are undergoing rapid maturation. This study helps fill the void by quantifying the association between head impact exposure and functional connectivity, an important aspect of brain health measurable via resting-state fMRI (rs-fMRI). The contributions of this paper are three fold. First, the data from two separate studies (youth and high school) are combined to form a high-powered analysis with 60 players. These players experience head acceleration within overlapping impact exposure making their combination particularly appropriate. Second, multiple features are extracted from rs-fMRI and tested for their association with impact exposure. One type of feature is the power spectral density decomposition of intrinsic, spatially distributed networks extracted via independent components analysis (ICA). Another feature type is the functional connectivity between brain regions known often associated with mild traumatic brain injury (mTBI). Third, multiple supervised machine learning algorithms are evaluated for their stability and predictive accuracy in a low bias, nested cross-validation modeling framework. Each classifier predicts whether a player sustained low or high levels of head impact exposure. The nested cross validation reveals similarly high classification performance across the feature types, and the Support Vector, Extremely randomized trees, and Gradboost classifiers achieve F1-score up to 75%.

A new automated spectral feature extraction method and its application in spectral classification and defective spectra recovery

NASA Astrophysics Data System (ADS)

Wang, Ke; Guo, Ping; Luo, A.-Li

2017-03-01

Spectral feature extraction is a crucial procedure in automated spectral analysis. This procedure starts from the spectral data and produces informative and non-redundant features, facilitating the subsequent automated processing and analysis with machine-learning and data-mining techniques. In this paper, we present a new automated feature extraction method for astronomical spectra, with application in spectral classification and defective spectra recovery. The basic idea of our approach is to train a deep neural network to extract features of spectra with different levels of abstraction in different layers. The deep neural network is trained with a fast layer-wise learning algorithm in an analytical way without any iterative optimization procedure. We evaluate the performance of the proposed scheme on real-world spectral data. The results demonstrate that our method is superior regarding its comprehensive performance, and the computational cost is significantly lower than that for other methods. The proposed method can be regarded as a new valid alternative general-purpose feature extraction method for various tasks in spectral data analysis.

Granger causality analysis reveals distinct spatio-temporal connectivity patterns in motor and perceptual visuo-spatial working memory.

PubMed

Protopapa, Foteini; Siettos, Constantinos I; Evdokimidis, Ioannis; Smyrnis, Nikolaos

2014-01-01

We employed spectral Granger causality analysis on a full set of 56 electroencephalographic recordings acquired during the execution of either a 2D movement pointing or a perceptual (yes/no) change detection task with memory and non-memory conditions. On the basis of network characteristics across frequency bands, we provide evidence for the full dissociation of the corresponding cognitive processes. Movement-memory trial types exhibited higher degree nodes during the first 2 s of the delay period, mainly at central, left frontal and right-parietal areas. Change detection-memory trial types resulted in a three-peak temporal pattern of the total degree with higher degree nodes emerging mainly at central, right frontal, and occipital areas. Functional connectivity networks resulting from non-memory trial types were characterized by more sparse structures for both tasks. The movement-memory trial types encompassed an apparent coarse flow from frontal to parietal areas while the opposite flow from occipital, parietal to central and frontal areas was evident for the change detection-memory trial types. The differences among tasks and conditions were more profound in α (8-12 Hz) and β (12-30 Hz) and less in γ (30-45 Hz) band. Our results favor the hypothesis which considers spatial working memory as a by-product of specific mental processes that engages common brain areas under different network organizations.

Optimizing interconnections to maximize the spectral radius of interdependent networks

NASA Astrophysics Data System (ADS)

Chen, Huashan; Zhao, Xiuyan; Liu, Feng; Xu, Shouhuai; Lu, Wenlian

2017-03-01

The spectral radius (i.e., the largest eigenvalue) of the adjacency matrices of complex networks is an important quantity that governs the behavior of many dynamic processes on the networks, such as synchronization and epidemics. Studies in the literature focused on bounding this quantity. In this paper, we investigate how to maximize the spectral radius of interdependent networks by optimally linking k internetwork connections (or interconnections for short). We derive formulas for the estimation of the spectral radius of interdependent networks and employ these results to develop a suite of algorithms that are applicable to different parameter regimes. In particular, a simple algorithm is to link the k nodes with the largest k eigenvector centralities in one network to the node in the other network with a certain property related to both networks. We demonstrate the applicability of our algorithms via extensive simulations. We discuss the physical implications of the results, including how the optimal interconnections can more effectively decrease the threshold of epidemic spreading in the susceptible-infected-susceptible model and the threshold of synchronization of coupled Kuramoto oscillators.

Scattering of an electromagnetic light wave from a quasi-homogeneous medium with semisoft boundary

NASA Astrophysics Data System (ADS)

Zhou, Jianyang; Zhao, Daomu

2016-08-01

Based on the first-order Born approximation, the scattering of an electromagnetic plane wave from a relatively more realistic random medium, a quasi-homogeneous medium with semisoft boundary, has been investigated. The analytic expressions for the spectral density, the spectral degree of coherence and the spectral degree of polarization have been derived, and the effects of the characteristics of the medium and the polarization of the incident light wave on the far-zone scattered field are determined. The numerical simulations indicate that, with the increasing of the edge softness M of the medium, the spectral density presents a pattern with interference fringes, and the number, position and width of interference fringes can be modified by the parameter. It is also found that there is an obvious value saltation in the coherence profile. Besides, unlike the intensity and the coherence are significantly affected by the properties of the medium, the polarization of the scattered field is irrelevant to them due to the quasi-homogeneity and isotropy of the medium, and it is only connected with the polarization of the incident light.

Altered Resting State Effective Connectivity of Anterior Insula in Depression.

PubMed

Kandilarova, Sevdalina; Stoyanov, Drozdstoy; Kostianev, Stefan; Specht, Karsten

2018-01-01

Depression has been associated with changes in both functional and effective connectivity of large scale brain networks, including the default mode network, executive network, and salience network. However, studies of effective connectivity by means of spectral dynamic causal modeling (spDCM) are still rare and the interaction between the different resting state networks has not been investigated in detail. Thus, we aimed at exploring differences in effective connectivity among eight right hemisphere brain areas-anterior insula, inferior frontal gyrus, middle frontal gyrus (MFG), frontal eye field, anterior cingulate cortex, superior parietal lobe, amygdala, and hippocampus, between a group of healthy controls ( N  = 20) and medicated depressed patients ( N  = 20). We found that patients not only had significantly reduced strength of the connection from the anterior insula to the MFG (i.e., dorsolateral prefrontal cortex) but also a significant connection between the amygdala and the anterior insula. Moreover, depression severity correlated with connectivity of the hippocampal node. In conclusion, the results from this resting state spDCM study support and enrich previous data on the role of the right anterior insula in the pathophysiology of depression. Furthermore, our findings add to the growing evidence of an association between depression severity and disturbances of the hippocampal function in terms of impaired connectivity with other brain regions.

Altered Resting State Effective Connectivity of Anterior Insula in Depression

PubMed Central

Kandilarova, Sevdalina; Stoyanov, Drozdstoy; Kostianev, Stefan; Specht, Karsten

2018-01-01

Depression has been associated with changes in both functional and effective connectivity of large scale brain networks, including the default mode network, executive network, and salience network. However, studies of effective connectivity by means of spectral dynamic causal modeling (spDCM) are still rare and the interaction between the different resting state networks has not been investigated in detail. Thus, we aimed at exploring differences in effective connectivity among eight right hemisphere brain areas—anterior insula, inferior frontal gyrus, middle frontal gyrus (MFG), frontal eye field, anterior cingulate cortex, superior parietal lobe, amygdala, and hippocampus, between a group of healthy controls (N = 20) and medicated depressed patients (N = 20). We found that patients not only had significantly reduced strength of the connection from the anterior insula to the MFG (i.e., dorsolateral prefrontal cortex) but also a significant connection between the amygdala and the anterior insula. Moreover, depression severity correlated with connectivity of the hippocampal node. In conclusion, the results from this resting state spDCM study support and enrich previous data on the role of the right anterior insula in the pathophysiology of depression. Furthermore, our findings add to the growing evidence of an association between depression severity and disturbances of the hippocampal function in terms of impaired connectivity with other brain regions. PMID:29599728

A DCM study of spectral asymmetries in feedforward and feedback connections between visual areas V1 and V4 in the monkey.

PubMed

Bastos, A M; Litvak, V; Moran, R; Bosman, C A; Fries, P; Friston, K J

2015-03-01

This paper reports a dynamic causal modeling study of electrocorticographic (ECoG) data that addresses functional asymmetries between forward and backward connections in the visual cortical hierarchy. Specifically, we ask whether forward connections employ gamma-band frequencies, while backward connections preferentially use lower (beta-band) frequencies. We addressed this question by modeling empirical cross spectra using a neural mass model equipped with superficial and deep pyramidal cell populations-that model the source of forward and backward connections, respectively. This enabled us to reconstruct the transfer functions and associated spectra of specific subpopulations within cortical sources. We first established that Bayesian model comparison was able to discriminate between forward and backward connections, defined in terms of their cells of origin. We then confirmed that model selection was able to identify extrastriate (V4) sources as being hierarchically higher than early visual (V1) sources. Finally, an examination of the auto spectra and transfer functions associated with superficial and deep pyramidal cells confirmed that forward connections employed predominantly higher (gamma) frequencies, while backward connections were mediated by lower (alpha/beta) frequencies. We discuss these findings in relation to current views about alpha, beta, and gamma oscillations and predictive coding in the brain. Copyright © 2015. Published by Elsevier Inc.

Spectral analysis of variable-length coded digital signals

NASA Astrophysics Data System (ADS)

Cariolaro, G. L.; Pierobon, G. L.; Pupolin, S. G.

1982-05-01

A spectral analysis is conducted for a variable-length word sequence by an encoder driven by a stationary memoryless source. A finite-state sequential machine is considered as a model of the line encoder, and the spectral analysis of the encoded message is performed under the assumption that the sourceword sequence is composed of independent identically distributed words. Closed form expressions for both the continuous and discrete parts of the spectral density are derived in terms of the encoder law and sourceword statistics. The jump part exhibits jumps at multiple integers of per lambda(sub 0)T, where lambda(sub 0) is the greatest common divisor of the possible codeword lengths, and T is the symbol period. The derivation of the continuous part can be conveniently factorized, and the theory is applied to the spectral analysis of BnZS and HDBn codes.

Spectral classifying base on color of live corals and dead corals covered with algae

NASA Astrophysics Data System (ADS)

Nurdin, Nurjannah; Komatsu, Teruhisa; Barille, Laurent; Akbar, A. S. M.; Sawayama, Shuhei; Fitrah, Muh. Nur; Prasyad, Hermansyah

2016-05-01

Pigments in the host tissues of corals can make a significant contribution to their spectral signature and can affect their apparent color as perceived by a human observer. The aim of this study is classifying the spectral reflectance of corals base on different color. It is expected that they can be used as references in discriminating between live corals, dead coral covered with algae Spectral reflectance data was collected in three small islands, Spermonde Archipelago, Indonesia by using a hyperspectral radiometer underwater. First and second derivative analysis resolved the wavelength locations of dominant features contributing to reflectance in corals and support the distinct differences in spectra among colour existed. Spectral derivative analysis was used to determine the specific wavelength regions ideal for remote identification of substrate type. The analysis results shown that yellow, green, brown and violet live corals are spectrally separable from each other, but they are similar with dead coral covered with algae spectral.

Quantitative EEG reflects non-dopaminergic disease severity in Parkinson's disease.

PubMed

Geraedts, Victor J; Marinus, Johan; Gouw, Alida A; Mosch, Arne; Stam, Cornelis J; van Hilten, Jacobus J; Contarino, Maria Fiorella; Tannemaat, Martijn R

2018-05-29

In Parkinson's Disease (PD), measures of non-dopaminergic systems involvement may reflect disease severity and therefore contribute to patient-selection for Deep Brain Stimulation (DBS). There is currently no determinant for non-dopaminergic disease severity. In this exploratory study, we investigated whether quantitative EEG reflects non-dopaminergic disease severity in PD. Sixty-three consecutive PD patients screened for DBS were included (mean age 62.4 ± 7.2 years, 32% females). Relative spectral powers and the Phase-Lag-Index (PLI) reflecting functional connectivity were analysed on routine EEGs. Non-dopaminergic disease severity was quantified using the SENS-PD score and its subdomains; motor-severity was quantified using the MDS-UPDRS III. The SENS-PD composite score correlated with a spectral ratio ((δ + θ)/(α1 + α2 + β) powers) (global spectral ratio Pearson's r = 0.4, 95% Confidence Interval (95%CI) 0.1-0.6), and PLI in the α2 band (10-13 Hz) (r = -0.3, 95%CI -0.5 to -0.1). These correlations seem driven by the subdomains cognition and psychotic symptoms. MDS-UPDRS III was not significantly correlated with EEG parameters. EEG slowing and reduced functional connectivity in the α2 band were associated with non-dopaminergic disease severity in PD. The described EEG parameters may have complementary utility as determinants of non-dopaminergic involvement in PD. Copyright © 2018 International Federation of Clinical Neurophysiology. Published by Elsevier B.V. All rights reserved.

The Spectral Image Processing System (SIPS): Software for integrated analysis of AVIRIS data

NASA Technical Reports Server (NTRS)

Kruse, F. A.; Lefkoff, A. B.; Boardman, J. W.; Heidebrecht, K. B.; Shapiro, A. T.; Barloon, P. J.; Goetz, A. F. H.

1992-01-01

The Spectral Image Processing System (SIPS) is a software package developed by the Center for the Study of Earth from Space (CSES) at the University of Colorado, Boulder, in response to a perceived need to provide integrated tools for analysis of imaging spectrometer data both spectrally and spatially. SIPS was specifically designed to deal with data from the Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) and the High Resolution Imaging Spectrometer (HIRIS), but was tested with other datasets including the Geophysical and Environmental Research Imaging Spectrometer (GERIS), GEOSCAN images, and Landsat TM. SIPS was developed using the 'Interactive Data Language' (IDL). It takes advantage of high speed disk access and fast processors running under the UNIX operating system to provide rapid analysis of entire imaging spectrometer datasets. SIPS allows analysis of single or multiple imaging spectrometer data segments at full spatial and spectral resolution. It also allows visualization and interactive analysis of image cubes derived from quantitative analysis procedures such as absorption band characterization and spectral unmixing. SIPS consists of three modules: SIPS Utilities, SIPS_View, and SIPS Analysis. SIPS version 1.1 is described below.

An Analysis of Periodic Components in BL Lac Object S5 0716 +714 with MUSIC Method

NASA Astrophysics Data System (ADS)

Tang, J.

2012-01-01

Multiple signal classification (MUSIC) algorithms are introduced to the estimation of the period of variation of BL Lac objects.The principle of MUSIC spectral analysis method and theoretical analysis of the resolution of frequency spectrum using analog signals are included. From a lot of literatures, we have collected a lot of effective observation data of BL Lac object S5 0716 + 714 in V, R, I bands from 1994 to 2008. The light variation periods of S5 0716 +714 are obtained by means of the MUSIC spectral analysis method and periodogram spectral analysis method. There exist two major periods: (3.33±0.08) years and (1.24±0.01) years for all bands. The estimation of the period of variation of the algorithm based on the MUSIC spectral analysis method is compared with that of the algorithm based on the periodogram spectral analysis method. It is a super-resolution algorithm with small data length, and could be used to detect the period of variation of weak signals.

Spectral Knowledge (SK-UTALCA): Software for Exploratory Analysis of High-Resolution Spectral Reflectance Data on Plant Breeding

PubMed Central

Lobos, Gustavo A.; Poblete-Echeverría, Carlos

2017-01-01

This article describes public, free software that provides efficient exploratory analysis of high-resolution spectral reflectance data. Spectral reflectance data can suffer from problems such as poor signal to noise ratios in various wavebands or invalid measurements due to changes in incoming solar radiation or operator fatigue leading to poor orientation of sensors. Thus, exploratory data analysis is essential to identify appropriate data for further analyses. This software overcomes the problem that analysis tools such as Excel are cumbersome to use for the high number of wavelengths and samples typically acquired in these studies. The software, Spectral Knowledge (SK-UTALCA), was initially developed for plant breeding, but it is also suitable for other studies such as precision agriculture, crop protection, ecophysiology plant nutrition, and soil fertility. Various spectral reflectance indices (SRIs) are often used to relate crop characteristics to spectral data and the software is loaded with 255 SRIs which can be applied quickly to the data. This article describes the architecture and functions of SK-UTALCA and the features of the data that led to the development of each of its modules. PMID:28119705

Spectral Knowledge (SK-UTALCA): Software for Exploratory Analysis of High-Resolution Spectral Reflectance Data on Plant Breeding.

PubMed

Lobos, Gustavo A; Poblete-Echeverría, Carlos

2016-01-01

This article describes public, free software that provides efficient exploratory analysis of high-resolution spectral reflectance data. Spectral reflectance data can suffer from problems such as poor signal to noise ratios in various wavebands or invalid measurements due to changes in incoming solar radiation or operator fatigue leading to poor orientation of sensors. Thus, exploratory data analysis is essential to identify appropriate data for further analyses. This software overcomes the problem that analysis tools such as Excel are cumbersome to use for the high number of wavelengths and samples typically acquired in these studies. The software, Spectral Knowledge (SK-UTALCA), was initially developed for plant breeding, but it is also suitable for other studies such as precision agriculture, crop protection, ecophysiology plant nutrition, and soil fertility. Various spectral reflectance indices (SRIs) are often used to relate crop characteristics to spectral data and the software is loaded with 255 SRIs which can be applied quickly to the data. This article describes the architecture and functions of SK-UTALCA and the features of the data that led to the development of each of its modules.

Robust and transferable quantification of NMR spectral quality using IROC analysis

NASA Astrophysics Data System (ADS)

Zambrello, Matthew A.; Maciejewski, Mark W.; Schuyler, Adam D.; Weatherby, Gerard; Hoch, Jeffrey C.

2017-12-01

Non-Fourier methods are increasingly utilized in NMR spectroscopy because of their ability to handle nonuniformly-sampled data. However, non-Fourier methods present unique challenges due to their nonlinearity, which can produce nonrandom noise and render conventional metrics for spectral quality such as signal-to-noise ratio unreliable. The lack of robust and transferable metrics (i.e. applicable to methods exhibiting different nonlinearities) has hampered comparison of non-Fourier methods and nonuniform sampling schemes, preventing the identification of best practices. We describe a novel method, in situ receiver operating characteristic analysis (IROC), for characterizing spectral quality based on the Receiver Operating Characteristic curve. IROC utilizes synthetic signals added to empirical data as "ground truth", and provides several robust scalar-valued metrics for spectral quality. This approach avoids problems posed by nonlinear spectral estimates, and provides a versatile quantitative means of characterizing many aspects of spectral quality. We demonstrate applications to parameter optimization in Fourier and non-Fourier spectral estimation, critical comparison of different methods for spectrum analysis, and optimization of nonuniform sampling schemes. The approach will accelerate the discovery of optimal approaches to nonuniform sampling experiment design and non-Fourier spectrum analysis for multidimensional NMR.

Spatiochromatic Interactions between Individual Cone Photoreceptors in the Human Retina

PubMed Central

Sabesan, Ramkumar; Sincich, Lawrence C.

2017-01-01

A remarkable feature of human vision is that the retina and brain have evolved circuitry to extract useful spatial and spectral information from signals originating in a photoreceptor mosaic with trichromatic constituents that vary widely in their relative numbers and local spatial configurations. A critical early transformation applied to cone signals is horizontal-cell-mediated lateral inhibition, which imparts a spatially antagonistic surround to individual cone receptive fields, a signature inherited by downstream neurons and implicated in color signaling. In the peripheral retina, the functional connectivity of cone inputs to the circuitry that mediates lateral inhibition is not cone-type specific, but whether these wiring schemes are maintained closer to the fovea remains unsettled, in part because central retinal anatomy is not easily amenable to direct physiological assessment. Here, we demonstrate how the precise topography of the long (L)-, middle (M)-, and short (S)-wavelength-sensitive cones in the human parafovea (1.5° eccentricity) shapes perceptual sensitivity. We used adaptive optics microstimulation to measure psychophysical detection thresholds from individual cones with spectral types that had been classified independently by absorptance imaging. Measured against chromatic adapting backgrounds, the sensitivities of L and M cones were, on average, receptor-type specific, but individual cone thresholds varied systematically with the number of preferentially activated cones in the immediate neighborhood. The spatial and spectral patterns of these interactions suggest that interneurons mediating lateral inhibition in the central retina, likely horizontal cells, establish functional connections with L and M cones indiscriminately, implying that the cone-selective circuitry supporting red–green color vision emerges after the first retinal synapse. SIGNIFICANCE STATEMENT We present evidence for spatially antagonistic interactions between individual, spectrally typed cones in the central retina of human observers using adaptive optics. Using chromatic adapting fields to modulate the relative steady-state activity of long (L)- and middle (M)-wavelength-sensitive cones, we found that single-cone detection thresholds varied predictably with the spectral demographics of the surrounding cones. The spatial scale and spectral pattern of these photoreceptor interactions were consistent with lateral inhibition mediated by retinal horizontal cells that receive nonselective input from L and M cones. These results demonstrate a clear link between the neural architecture of the visual system inputs—cone photoreceptors—and visual perception and have implications for the neural locus of the cone-specific circuitry supporting color vision. PMID:28871030

SPAM- SPECTRAL ANALYSIS MANAGER (DEC VAX/VMS VERSION)

NASA Technical Reports Server (NTRS)

Solomon, J. E.

1994-01-01

The Spectral Analysis Manager (SPAM) was developed to allow easy qualitative analysis of multi-dimensional imaging spectrometer data. Imaging spectrometers provide sufficient spectral sampling to define unique spectral signatures on a per pixel basis. Thus direct material identification becomes possible for geologic studies. SPAM provides a variety of capabilities for carrying out interactive analysis of the massive and complex datasets associated with multispectral remote sensing observations. In addition to normal image processing functions, SPAM provides multiple levels of on-line help, a flexible command interpretation, graceful error recovery, and a program structure which can be implemented in a variety of environments. SPAM was designed to be visually oriented and user friendly with the liberal employment of graphics for rapid and efficient exploratory analysis of imaging spectrometry data. SPAM provides functions to enable arithmetic manipulations of the data, such as normalization, linear mixing, band ratio discrimination, and low-pass filtering. SPAM can be used to examine the spectra of an individual pixel or the average spectra over a number of pixels. SPAM also supports image segmentation, fast spectral signature matching, spectral library usage, mixture analysis, and feature extraction. High speed spectral signature matching is performed by using a binary spectral encoding algorithm to separate and identify mineral components present in the scene. The same binary encoding allows automatic spectral clustering. Spectral data may be entered from a digitizing tablet, stored in a user library, compared to the master library containing mineral standards, and then displayed as a timesequence spectral movie. The output plots, histograms, and stretched histograms produced by SPAM can be sent to a lineprinter, stored as separate RGB disk files, or sent to a Quick Color Recorder. SPAM is written in C for interactive execution and is available for two different machine environments. There is a DEC VAX/VMS version with a central memory requirement of approximately 242K of 8 bit bytes and a machine independent UNIX 4.2 version. The display device currently supported is the Raster Technologies display processor. Other 512 x 512 resolution color display devices, such as De Anza, may be added with minor code modifications. This program was developed in 1986.

SPAM- SPECTRAL ANALYSIS MANAGER (UNIX VERSION)

NASA Technical Reports Server (NTRS)

Solomon, J. E.

1994-01-01

The Spectral Analysis Manager (SPAM) was developed to allow easy qualitative analysis of multi-dimensional imaging spectrometer data. Imaging spectrometers provide sufficient spectral sampling to define unique spectral signatures on a per pixel basis. Thus direct material identification becomes possible for geologic studies. SPAM provides a variety of capabilities for carrying out interactive analysis of the massive and complex datasets associated with multispectral remote sensing observations. In addition to normal image processing functions, SPAM provides multiple levels of on-line help, a flexible command interpretation, graceful error recovery, and a program structure which can be implemented in a variety of environments. SPAM was designed to be visually oriented and user friendly with the liberal employment of graphics for rapid and efficient exploratory analysis of imaging spectrometry data. SPAM provides functions to enable arithmetic manipulations of the data, such as normalization, linear mixing, band ratio discrimination, and low-pass filtering. SPAM can be used to examine the spectra of an individual pixel or the average spectra over a number of pixels. SPAM also supports image segmentation, fast spectral signature matching, spectral library usage, mixture analysis, and feature extraction. High speed spectral signature matching is performed by using a binary spectral encoding algorithm to separate and identify mineral components present in the scene. The same binary encoding allows automatic spectral clustering. Spectral data may be entered from a digitizing tablet, stored in a user library, compared to the master library containing mineral standards, and then displayed as a timesequence spectral movie. The output plots, histograms, and stretched histograms produced by SPAM can be sent to a lineprinter, stored as separate RGB disk files, or sent to a Quick Color Recorder. SPAM is written in C for interactive execution and is available for two different machine environments. There is a DEC VAX/VMS version with a central memory requirement of approximately 242K of 8 bit bytes and a machine independent UNIX 4.2 version. The display device currently supported is the Raster Technologies display processor. Other 512 x 512 resolution color display devices, such as De Anza, may be added with minor code modifications. This program was developed in 1986.

Simulation of time-dispersion spectral device with sample spectra accumulation

NASA Astrophysics Data System (ADS)

Zhdanov, Arseny; Khansuvarov, Ruslan; Korol, Georgy

2014-09-01

This research is conducted in order to design a spectral device for light sources power spectrum analysis. The spectral device should process radiation from sources, direct contact with radiation of which is either impossible or undesirable. Such sources include jet blast of an aircraft, optical radiation in metallurgy and textile industry. In proposed spectral device optical radiation is guided out of unfavorable environment via a piece of optical fiber with high dispersion. It is necessary for analysis to make samples of analyzed radiation as short pulses. Dispersion properties of such optical fiber cause spectral decomposition of input optical pulses. The faster time of group delay vary the stronger the spectral decomposition effect. This effect allows using optical fiber with high dispersion as a major element of proposed spectral device. Duration of sample must be much shorter than group delay time difference of a dispersive system. In the given frequency range this characteristic has to be linear. The frequency range is 400 … 500 THz for typical optical fiber. Using photonic-crystal fiber (PCF) gives much wider spectral range for analysis. In this paper we propose simulation of single pulse transmission through dispersive system with linear dispersion characteristic and quadratic-detected output responses accumulation. During simulation we propose studying influence of optical fiber dispersion characteristic angle on spectral measurement results. We also consider pulse duration and group delay time difference impact on output pulse shape and duration. Results show the most suitable dispersion characteristic that allow choosing the structure of PCF - major element of time-dispersion spectral analysis method and required number of samples for reliable assessment of measured spectrum.

A statistical evaluation of spectral fingerprinting methods using analysis of variance and principal component analysis

USDA-ARS?s Scientific Manuscript database

Six methods were compared with respect to spectral fingerprinting of a well-characterized series of broccoli samples. Spectral fingerprints were acquired for finely-powdered solid samples using Fourier transform-infrared (IR) and Fourier transform-near infrared (NIR) spectrometry and for aqueous met...

What drives high flow events in the Swiss Alps? Recent developments in wavelet spectral analysis and their application to hydrology

NASA Astrophysics Data System (ADS)

Schaefli, B.; Maraun, D.; Holschneider, M.

2007-12-01

Extreme hydrological events are often triggered by exceptional co-variations of the relevant hydrometeorological processes and in particular by exceptional co-oscillations at various temporal scales. Wavelet and cross wavelet spectral analysis offers promising time-scale resolved analysis methods to detect and analyze such exceptional co-oscillations. This paper presents the state-of-the-art methods of wavelet spectral analysis, discusses related subtleties, potential pitfalls and recently developed solutions to overcome them and shows how wavelet spectral analysis, if combined to a rigorous significance test, can lead to reliable new insights into hydrometeorological processes for real-world applications. The presented methods are applied to detect potentially flood triggering situations in a high Alpine catchment for which a recent re-estimation of design floods encountered significant problems simulating the observed high flows. For this case study, wavelet spectral analysis of precipitation, temperature and discharge offers a powerful tool to help detecting potentially flood producing meteorological situations and to distinguish between different types of floods with respect to the prevailing critical hydrometeorological conditions. This opens very new perspectives for the analysis of model performances focusing on the occurrence and non-occurrence of different types of high flow events. Based on the obtained results, the paper summarizes important recommendations for future applications of wavelet spectral analysis in hydrology.

M Stars in the TW Hydra Association: A Chandra Large Program Survey

NASA Astrophysics Data System (ADS)

Punzi, Kristina; Kastner, Joel; Principe, David; Stelzer, Beate; Gorti, Uma; Pascucci, Illaria; Argiroffi, Costanza

2018-01-01

We have conducted a Cycle 18 Chandra Large Program survey of very cool members of the $\\sim$ 8 Myr-old TW Hydra Association (TWA) to extend our previous study of the potential connections between M star disks and X-rays (Kastner et al. 2016, AJ, 152, 3) to the extreme low-mass end of the stellar initial mass function. The spectral types of our targets extend down to the M/L borderline. Thus we can further investigate the potential connection between the intense X-ray emission from young, low-mass stars and the lifetimes of their circumstellar planet-forming discs, as well as better constrain the age at which coronal activity declines for stellar masses approaching the H-burning limit of $\\sim$ 0.08 M$_{\\odot}$. We present preliminary results from the Cycle 18 survey, including X-ray detection statistics and measurements of relative X-ray luminosities and coronal (X-ray) temperatures for those TWA stars detected by Chandra. This research is supported by SAO/CXC grant GO7-18002A and NASA Astrophysics Data Analysis program grants NNX12AH37G and NNX16AG13G to RIT.

Task-Related Modulations of BOLD Low-Frequency Fluctuations within the Default Mode Network

PubMed Central

Tommasin, Silvia; Mascali, Daniele; Gili, Tommaso; Assan, Ibrahim Eid; Moraschi, Marta; Fratini, Michela; Wise, Richard G.; Macaluso, Emiliano; Mangia, Silvia; Giove, Federico

2017-01-01

Spontaneous low-frequency Blood-Oxygenation Level-Dependent (BOLD) signals acquired during resting state are characterized by spatial patterns of synchronous fluctuations, ultimately leading to the identification of robust brain networks. The resting-state brain networks, including the Default Mode Network (DMN), are demonstrated to persist during sustained task execution, but the exact features of task-related changes of network properties are still not well characterized. In this work we sought to examine in a group of 20 healthy volunteers (age 33 ± 6 years, 8 F/12 M) the relationship between changes of spectral and spatiotemporal features of one prominent resting-state network, namely the DMN, during the continuous execution of a working memory n-back task. We found that task execution impacted on both functional connectivity and amplitude of BOLD fluctuations within large parts of the DMN, but these changes correlated between each other only in a small area of the posterior cingulate. We conclude that combined analysis of multiple parameters related to connectivity, and their changes during the transition from resting state to continuous task execution, can contribute to a better understanding of how brain networks rearrange themselves in response to a task. PMID:28845420

Characterizing the γ-ray long-term variability of PKS 2155-304 with H.E.S.S. and Fermi-LAT

NASA Astrophysics Data System (ADS)

H.E.S.S. Collaboration; Abdalla, H.; Abramowski, A.; Aharonian, F.; Ait Benkhali, F.; Akhperjanian, A. G.; Andersson, T.; Angüner, E. O.; Arrieta, M.; Aubert, P.; Backes, M.; Balzer, A.; Barnard, M.; Becherini, Y.; Becker Tjus, J.; Berge, D.; Bernhard, S.; Bernlöhr, K.; Blackwell, R.; Böttcher, M.; Boisson, C.; Bolmont, J.; Bordas, P.; Bregeon, J.; Brun, F.; Brun, P.; Bryan, M.; Bulik, T.; Capasso, M.; Carr, J.; Casanova, S.; Cerruti, M.; Chakraborty, N.; Chalme-Calvet, R.; Chaves, R. C. G.; Chen, A.; Chevalier, J.; Chrétien, M.; Colafrancesco, S.; Cologna, G.; Condon, B.; Conrad, J.; Cui, Y.; Davids, I. D.; Decock, J.; Degrange, B.; Deil, C.; Devin, J.; deWilt, P.; Dirson, L.; Djannati-Ataï, A.; Domainko, W.; Donath, A.; Drury, L. O.'C.; Dubus, G.; Dutson, K.; Dyks, J.; Edwards, T.; Egberts, K.; Eger, P.; Ernenwein, J.-P.; Eschbach, S.; Farnier, C.; Fegan, S.; Fernandes, M. V.; Fiasson, A.; Fontaine, G.; Förster, A.; Funk, S.; Füßling, M.; Gabici, S.; Gajdus, M.; Gallant, Y. A.; Garrigoux, T.; Giavitto, G.; Giebels, B.; Glicenstein, J. F.; Gottschall, D.; Goyal, A.; Grondin, M.-H.; Hadasch, D.; Hahn, J.; Haupt, M.; Hawkes, J.; Heinzelmann, G.; Henri, G.; Hermann, G.; Hervet, O.; Hinton, J. A.; Hofmann, W.; Hoischen, C.; Holler, M.; Horns, D.; Ivascenko, A.; Jacholkowska, A.; Jamrozy, M.; Janiak, M.; Jankowsky, D.; Jankowsky, F.; Jingo, M.; Jogler, T.; Jouvin, L.; Jung-Richardt, I.; Kastendieck, M. A.; Katarzyński, K.; Katz, U.; Kerszberg, D.; Khélifi, B.; Kieffer, M.; King, J.; Klepser, S.; Klochkov, D.; Kluźniak, W.; Kolitzus, D.; Komin, Nu.; Kosack, K.; Krakau, S.; Kraus, M.; Krayzel, F.; Krüger, P. P.; Laffon, H.; Lamanna, G.; Lau, J.; Lees, J.-P.; Lefaucheur, J.; Lefranc, V.; Lemière, A.; Lemoine-Goumard, M.; Lenain, J.-P.; Leser, E.; Lohse, T.; Lorentz, M.; Liu, R.; López-Coto, R.; Lypova, I.; Marandon, V.; Marcowith, A.; Mariaud, C.; Marx, R.; Maurin, G.; Maxted, N.; Mayer, M.; Meintjes, P. J.; Meyer, M.; Mitchell, A. M. W.; Moderski, R.; Mohamed, M.; Mohrmann, L.; Morå, K.; Moulin, E.; Murach, T.; de Naurois, M.; Niederwanger, F.; Niemiec, J.; Oakes, L.; O'Brien, P.; Odaka, H.; Öttl, S.; Ohm, S.; Ostrowski, M.; Oya, I.; Padovani, M.; Panter, M.; Parsons, R. D.; Pekeur, N. W.; Pelletier, G.; Perennes, C.; Petrucci, P.-O.; Peyaud, B.; Piel, Q.; Pita, S.; Poon, H.; Prokhorov, D.; Prokoph, H.; Pühlhofer, G.; Punch, M.; Quirrenbach, A.; Raab, S.; Reimer, A.; Reimer, O.; Renaud, M.; de los Reyes, R.; Rieger, F.; Romoli, C.; Rosier-Lees, S.; Rowell, G.; Rudak, B.; Rulten, C. B.; Sahakian, V.; Salek, D.; Sanchez, D. A.; Santangelo, A.; Sasaki, M.; Schlickeiser, R.; Schüssler, F.; Schulz, A.; Schwanke, U.; Schwemmer, S.; Settimo, M.; Seyffert, A. S.; Shafi, N.; Shilon, I.; Simoni, R.; Sol, H.; Spanier, F.; Spengler, G.; Spies, F.; Stawarz, Ł.; Steenkamp, R.; Stegmann, C.; Stinzing, F.; Stycz, K.; Sushch, I.; Tavernet, J.-P.; Tavernier, T.; Taylor, A. M.; Terrier, R.; Tibaldo, L.; Tiziani, D.; Tluczykont, M.; Trichard, C.; Tuffs, R.; Uchiyama, Y.; van der Walt, D. J.; van Eldik, C.; van Rensburg, C.; van Soelen, B.; Vasileiadis, G.; Veh, J.; Venter, C.; Viana, A.; Vincent, P.; Vink, J.; Voisin, F.; Völk, H. J.; Vuillaume, T.; Wadiasingh, Z.; Wagner, S. J.; Wagner, P.; Wagner, R. M.; White, R.; Wierzcholska, A.; Willmann, P.; Wörnlein, A.; Wouters, D.; Yang, R.; Zabalza, V.; Zaborov, D.; Zacharias, M.; Zdziarski, A. A.; Zech, A.; Zefi, F.; Ziegler, A.; Żywucka, N.

2017-02-01

Studying the temporal variability of BL Lac objects at the highest energies provides unique insights into the extreme physical processes occurring in relativistic jets and in the vicinity of super-massive black holes. To this end, the long-term variability of the BL Lac object PKS 2155-304 is analyzed in the high (HE, 100 MeV < E < 300 GeV) and very high energy (VHE, E > 200 GeV) γ-ray domain. Over the course of 9 yr of H.E.S.S. observations the VHE light curve in the quiescent state is consistent with a log-normal behavior. The VHE variability in this state is well described by flicker noise (power-spectral-density index ) on timescales larger than one day. An analysis of 5.5 yr of HE Fermi-LAT data gives consistent results (, on timescales larger than 10 days) compatible with the VHE findings. The HE and VHE power spectral densities show a scale invariance across the probed time ranges. A direct linear correlation between the VHE and HE fluxes could neither be excluded nor firmly established. These long-term-variability properties are discussed and compared to the red noise behavior (β 2) seen on shorter timescales during VHE-flaring states. The difference in power spectral noise behavior at VHE energies during quiescent and flaring states provides evidence that these states are influenced by different physical processes, while the compatibility of the HE and VHE long-term results is suggestive of a common physical link as it might be introduced by an underlying jet-disk connection.

Associations of Leaf Spectra with Genetic and Phylogenetic Variation in Oaks: Prospects for Remote Detection of Biodiversity

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

Cavender-Bares, Jeannine; Meireles, Jose; Couture, John

Species and phylogenetic lineages have evolved to differ in the way that they acquire and deploy resources, with consequences for their physiological, chemical and structural attributes, many of which can be detected using spectral reflectance form leaves. Recent technological advances for assessing optical properties of plants offer opportunities to detect functional traits of organisms and differentiate levels of biological organization across the tree of life. We connect leaf-level full range spectral data (400–2400 nm) of leaves to the hierarchical organization of plant diversity within the oak genus (Quercus) using field and greenhouse experiments in which environmental factors and plant agemore » are controlled. We show that spectral data significantly differentiate populations within a species and that spectral similarity is significantly associated with phylogenetic similarity among species. Furthermore, we show that hyperspectral information allows more accurate classification of taxa than spectrally-derived traits, which by definition are of lower dimensionality. Finally, model accuracy increases at higher levels in the hierarchical organization of plant diversity, such that we are able to better distinguish clades than species or populations. This pattern supports an evolutionary explanation for the degree of optical differentiation among plants and demonstrates potential for remote detection of genetic and phylogenetic diversity.« less

Modeling of a field-widened Michelson interferometric filter for application in a high spectral resolution lidar

NASA Astrophysics Data System (ADS)

Liu, Dong; Hostetler, Chris; Cook, Anthony; Miller, Ian; Hair, Johnathan

2011-11-01

High spectral resolution lidars (HSRLs) are increasingly being deployed on aircraft and called for on future space-based missions. The HSRL technique relies on spectral discrimination of the atmospheric backscatter signals to enable independent, unambiguous retrieval of aerosol extinction and backscatter. A compact, monolithic field-widened Michelson interferometer is being developed as the spectral discrimination filter for an HSRL system at NASA Langley Research Center. The interferometer consists of a cubic beam splitter, a solid glass arm, and an air arm. The spacer that connects the air arm mirror to the main part of the interferometer is designed to optimize thermal compensation such that the maximum interference can be tuned with great precision to the transmitted laser wavelength. In this paper, a comprehensive radiometric model for the field-widened Michelson interferometeric spectral filter is presented. The model incorporates the angular distribution and finite cross sectional area of the light source, reflectance of all surfaces, loss of absorption, and lack of parallelism between the air-arm and solid arm, etc. The model can be used to assess the performance of the interferometer and thus it is a useful tool to evaluate performance budgets and to set optical specifications for new designs of the same basic interferometer type.

Emergent spectral properties of river network topology: an optimal channel network approach.

PubMed

Abed-Elmdoust, Armaghan; Singh, Arvind; Yang, Zong-Liang

2017-09-13

Characterization of river drainage networks has been a subject of research for many years. However, most previous studies have been limited to quantities which are loosely connected to the topological properties of these networks. In this work, through a graph-theoretic formulation of drainage river networks, we investigate the eigenvalue spectra of their adjacency matrix. First, we introduce a graph theory model for river networks and explore the properties of the network through its adjacency matrix. Next, we show that the eigenvalue spectra of such complex networks follow distinct patterns and exhibit striking features including a spectral gap in which no eigenvalue exists as well as a finite number of zero eigenvalues. We show that such spectral features are closely related to the branching topology of the associated river networks. In this regard, we find an empirical relation for the spectral gap and nullity in terms of the energy dissipation exponent of the drainage networks. In addition, the eigenvalue distribution is found to follow a finite-width probability density function with certain skewness which is related to the drainage pattern. Our results are based on optimal channel network simulations and validated through examples obtained from physical experiments on landscape evolution. These results suggest the potential of the spectral graph techniques in characterizing and modeling river networks.

Associations of Leaf Spectra with Genetic and Phylogenetic Variation in Oaks: Prospects for Remote Detection of Biodiversity

DOE PAGES

Cavender-Bares, Jeannine; Meireles, Jose; Couture, John; ...

2016-03-09

Species and phylogenetic lineages have evolved to differ in the way that they acquire and deploy resources, with consequences for their physiological, chemical and structural attributes, many of which can be detected using spectral reflectance form leaves. Recent technological advances for assessing optical properties of plants offer opportunities to detect functional traits of organisms and differentiate levels of biological organization across the tree of life. We connect leaf-level full range spectral data (400–2400 nm) of leaves to the hierarchical organization of plant diversity within the oak genus (Quercus) using field and greenhouse experiments in which environmental factors and plant agemore » are controlled. We show that spectral data significantly differentiate populations within a species and that spectral similarity is significantly associated with phylogenetic similarity among species. Furthermore, we show that hyperspectral information allows more accurate classification of taxa than spectrally-derived traits, which by definition are of lower dimensionality. Finally, model accuracy increases at higher levels in the hierarchical organization of plant diversity, such that we are able to better distinguish clades than species or populations. This pattern supports an evolutionary explanation for the degree of optical differentiation among plants and demonstrates potential for remote detection of genetic and phylogenetic diversity.« less

Hyperspectral imaging simulation of object under sea-sky background

NASA Astrophysics Data System (ADS)

Wang, Biao; Lin, Jia-xuan; Gao, Wei; Yue, Hui

2016-10-01

Remote sensing image simulation plays an important role in spaceborne/airborne load demonstration and algorithm development. Hyperspectral imaging is valuable in marine monitoring, search and rescue. On the demand of spectral imaging of objects under the complex sea scene, physics based simulation method of spectral image of object under sea scene is proposed. On the development of an imaging simulation model considering object, background, atmosphere conditions, sensor, it is able to examine the influence of wind speed, atmosphere conditions and other environment factors change on spectral image quality under complex sea scene. Firstly, the sea scattering model is established based on the Philips sea spectral model, the rough surface scattering theory and the water volume scattering characteristics. The measured bi directional reflectance distribution function (BRDF) data of objects is fit to the statistical model. MODTRAN software is used to obtain solar illumination on the sea, sky brightness, the atmosphere transmittance from sea to sensor and atmosphere backscattered radiance, and Monte Carlo ray tracing method is used to calculate the sea surface object composite scattering and spectral image. Finally, the object spectrum is acquired by the space transformation, radiation degradation and adding the noise. The model connects the spectrum image with the environmental parameters, the object parameters, and the sensor parameters, which provide a tool for the load demonstration and algorithm development.

Digital techniques for ULF wave polarization analysis

NASA Technical Reports Server (NTRS)

Arthur, C. W.

1979-01-01

Digital power spectral and wave polarization analysis are powerful techniques for studying ULF waves in the earth's magnetosphere. Four different techniques for using the spectral matrix to perform such an analysis have been presented in the literature. Three of these techniques are similar in that they require transformation of the spectral matrix to the principal axis system prior to performing the polarization analysis. The differences in the three techniques lie in the manner in which determine this transformation. A comparative study of these three techniques using both simulated and real data has shown them to be approximately equal in quality of performance. The fourth technique does not require transformation of the spectral matrix. Rather, it uses the measured spectral matrix and state vectors for a desired wave type to design a polarization detector function in the frequency domain. The design of various detector functions and their application to both simulated and real data will be presented.

Global spectral graph wavelet signature for surface analysis of carpal bones

NASA Astrophysics Data System (ADS)

Masoumi, Majid; Rezaei, Mahsa; Ben Hamza, A.

2018-02-01

Quantitative shape comparison is a fundamental problem in computer vision, geometry processing and medical imaging. In this paper, we present a spectral graph wavelet approach for shape analysis of carpal bones of the human wrist. We employ spectral graph wavelets to represent the cortical surface of a carpal bone via the spectral geometric analysis of the Laplace-Beltrami operator in the discrete domain. We propose global spectral graph wavelet (GSGW) descriptor that is isometric invariant, efficient to compute, and combines the advantages of both low-pass and band-pass filters. We perform experiments on shapes of the carpal bones of ten women and ten men from a publicly-available database of wrist bones. Using one-way multivariate analysis of variance (MANOVA) and permutation testing, we show through extensive experiments that the proposed GSGW framework gives a much better performance compared to the global point signature embedding approach for comparing shapes of the carpal bones across populations.

Global spectral graph wavelet signature for surface analysis of carpal bones.

PubMed

Masoumi, Majid; Rezaei, Mahsa; Ben Hamza, A

2018-02-05

Quantitative shape comparison is a fundamental problem in computer vision, geometry processing and medical imaging. In this paper, we present a spectral graph wavelet approach for shape analysis of carpal bones of the human wrist. We employ spectral graph wavelets to represent the cortical surface of a carpal bone via the spectral geometric analysis of the Laplace-Beltrami operator in the discrete domain. We propose global spectral graph wavelet (GSGW) descriptor that is isometric invariant, efficient to compute, and combines the advantages of both low-pass and band-pass filters. We perform experiments on shapes of the carpal bones of ten women and ten men from a publicly-available database of wrist bones. Using one-way multivariate analysis of variance (MANOVA) and permutation testing, we show through extensive experiments that the proposed GSGW framework gives a much better performance compared to the global point signature embedding approach for comparing shapes of the carpal bones across populations.

GEOS-2 C-band radar system project. Spectral analysis as related to C-band radar data analysis

NASA Technical Reports Server (NTRS)

1972-01-01

Work performed on spectral analysis of data from the C-band radars tracking GEOS-2 and on the development of a data compaction method for the GEOS-2 C-band radar data is described. The purposes of the spectral analysis study were to determine the optimum data recording and sampling rates for C-band radar data and to determine the optimum method of filtering and smoothing the data. The optimum data recording and sampling rate is defined as the rate which includes an optimum compromise between serial correlation and the effects of frequency folding. The goal in development of a data compaction method was to reduce to a minimum the amount of data stored, while maintaining all of the statistical information content of the non-compacted data. A digital computer program for computing estimates of the power spectral density function of sampled data was used to perform the spectral analysis study.

From moonlight to movement and synchronized randomness: Fourier and wavelet analyses of animal location time series data

PubMed Central

Polansky, Leo; Wittemyer, George; Cross, Paul C.; Tambling, Craig J.; Getz, Wayne M.

2011-01-01

High-resolution animal location data are increasingly available, requiring analytical approaches and statistical tools that can accommodate the temporal structure and transient dynamics (non-stationarity) inherent in natural systems. Traditional analyses often assume uncorrelated or weakly correlated temporal structure in the velocity (net displacement) time series constructed using sequential location data. We propose that frequency and time–frequency domain methods, embodied by Fourier and wavelet transforms, can serve as useful probes in early investigations of animal movement data, stimulating new ecological insight and questions. We introduce a novel movement model with time-varying parameters to study these methods in an animal movement context. Simulation studies show that the spectral signature given by these methods provides a useful approach for statistically detecting and characterizing temporal dependency in animal movement data. In addition, our simulations provide a connection between the spectral signatures observed in empirical data with null hypotheses about expected animal activity. Our analyses also show that there is not a specific one-to-one relationship between the spectral signatures and behavior type and that departures from the anticipated signatures are also informative. Box plots of net displacement arranged by time of day and conditioned on common spectral properties can help interpret the spectral signatures of empirical data. The first case study is based on the movement trajectory of a lion (Panthera leo) that shows several characteristic daily activity sequences, including an active–rest cycle that is correlated with moonlight brightness. A second example based on six pairs of African buffalo (Syncerus caffer) illustrates the use of wavelet coherency to show that their movements synchronize when they are within ∼1 km of each other, even when individual movement was best described as an uncorrelated random walk, providing an important spatial baseline of movement synchrony and suggesting that local behavioral cues play a strong role in driving movement patterns. We conclude with a discussion about the role these methods may have in guiding appropriately flexible probabilistic models connecting movement with biotic and abiotic covariates. PMID:20503882

Water in the Early Solar System: Infrared Studies of Aqueously Altered and Minimally Processed Asteroids

NASA Astrophysics Data System (ADS)

McAdam, Margaret M.

This thesis investigates connections between low albedo asteroids and carbonaceous chondrite meteorites using spectroscopy. Meteorites and asteroids preserve information about the early solar system including accretion processes and parent body processes active on asteroids at these early times. One process of interest is aqueous alteration. This is the chemical reaction between coaccreted water and silicates producing hydrated minerals. Some carbonaceous chondrites have experienced extensive interactions with water through this process. Since these meteorites and their parent bodies formed close to the beginning of the Solar System, these asteroids and meteorites may provide clues to the distribution, abundance and timing of water in the Solar nebula at these times. Chapter 2 of this thesis investigates the relationships between extensively aqueously altered meteorites and their visible, near and mid-infrared spectral features in a coordinated spectral-mineralogical study. Aqueous alteration is a parent body process where initially accreted anhydrous minerals are converted into hydrated minerals in the presence of coaccreted water. Using samples of meteorites with known bulk properties, it is possible to directly connect changes in mineralogy caused by aqueous alteration with spectral features. Spectral features in the mid-infrared are found to change continuously with increasing amount of hydrated minerals or degree of alteration. Building on this result, the degrees of alteration of asteroids are estimated in a survey of new asteroid data obtained from SOFIA and IRTF as well as archived the Spitzer Space Telescope data. 75 observations of 73 asteroids are analyzed and presented in Chapter 4. Asteroids with hydrated minerals are found throughout the main belt indicating that significant ice must have been present in the disk at the time of carbonaceous asteroid accretion. Finally, some carbonaceous chondrite meteorites preserve amorphous iron-bearing materials that formed through disequilibrium condensation in the disk. These materials are readily destroyed in parent body processes so their presence indicates the meteorite/asteroid has undergone minimal parent body processes since the time of accretion. Presented in Chapter 3 is the spectral signature of meteorites that preserve significant amorphous iron-bearing materials and the identification of an asteroid, (93) Minerva, that also appears to preserve these materials.

Different techniques of multispectral data analysis for vegetation fraction retrieval

NASA Astrophysics Data System (ADS)

Kancheva, Rumiana; Georgiev, Georgi

2012-07-01

Vegetation monitoring is one of the most important applications of remote sensing technologies. In respect to farmlands, the assessment of crop condition constitutes the basis of growth, development, and yield processes monitoring. Plant condition is defined by a set of biometric variables, such as density, height, biomass amount, leaf area index, and etc. The canopy cover fraction is closely related to these variables, and is state-indicative of the growth process. At the same time it is a defining factor of the soil-vegetation system spectral signatures. That is why spectral mixtures decomposition is a primary objective in remotely sensed data processing and interpretation, specifically in agricultural applications. The actual usefulness of the applied methods depends on their prediction reliability. The goal of this paper is to present and compare different techniques for quantitative endmember extraction from soil-crop patterns reflectance. These techniques include: linear spectral unmixing, two-dimensional spectra analysis, spectral ratio analysis (vegetation indices), spectral derivative analysis (red edge position), colorimetric analysis (tristimulus values sum, chromaticity coordinates and dominant wavelength). The objective is to reveal their potential, accuracy and robustness for plant fraction estimation from multispectral data. Regression relationships have been established between crop canopy cover and various spectral estimators.

Thermal and Non-thermal emission in the Jets and Lobes of Cygnus A

NASA Astrophysics Data System (ADS)

De Vries, Martijn; Wise, Michael; Huppenkothen, Daniela; Nulsen, Paul; Snios, Bradford; Hardcastle, Martin

2017-08-01

We present a spatially-resolved, spectral analysis aimed at detecting and characterizing the non-thermal X-ray emission from the jets and lobes in the powerful radio galaxy Cygnus A based on a new, deep 1 Msec Chandra exposure. These jets and lobes are believed to be a primary means by which energy liberated by accretion onto the central supermassive black hole is transported into the outer galaxy and are integral to understanding the mechanisms that drive AGN feedback. Despite being well-studied over the years, we still do not understand how this energy is transported, the connection between the X-ray and radio structures, and the underlying emission mechanisms that produce them. The X-ray jets in Cygnus A show a clear misalignment with the radio and it has been proposed that they are either inverse Compton-emitting relics or a separate electron population emitting X-ray synchrotron emission. Previous X-ray studies of the jets and lobes have been unsuccessful in distinguishing between these possibilities largely due to the difficulty of separating any non-thermal components from thermal emission in the surrounding hot ICM at CCD spectral resolutions.In this presentation, we report on a new statistical analysis using MCMC sampling and Bayesian model selection to characterize the X-ray emission in the jets and lobes of Cygnus A. The model includes a mixture of thermal ICM emission and distinct non-thermal components from both the eastern and western jets and lobes. Our analysis clearly favors the presence of non-thermal emission and we find a distinct asymmetry with the western lobe roughly 20% fainter and with a much steeper photon index. Combining existing radio data with our X-ray fluxes and photon indices, we determine the energy densities and pressures for both synchrotron and inverse Compton (IC) emission models. For the IC model, we derive energy densities in the lobes consistent with the external pressure; however, both the eastern and western jets would be over-pressured by almost an order of magnitude arguing strongly for a synchrotron origin. We discuss these results in the context of the evolution of the jets and lobes and their connection to the ongoing feedback process in Cygnus A.

Subionospheric VLF/LF radio waves propagation characteristics before, during and after the Sofia, Bulgaria Mw=5.6 earthquake occurred on 22 May 2012

NASA Astrophysics Data System (ADS)

Moldovan, Iren Adelina; Emilian Toader, Victorin; Nenovski, Petko; Biagi, Pier Francesco; Maggipinto, Tommaso; Septimiu Moldovan, Adrian; Ionescu, Constantin

2013-04-01

In 2009, INFREP, a network of VLF (20-60 kHz) and LF (150-300 kHz) radio receivers, was put into operation in Europe having as principal goal, the study of disturbances produced by the earthquakes on the propagation properties of these signals. On May 22nd, 2012 an earthquake with Mw=567 occurred in Bulgaria, near Sofia, inside the "sensitive" area of the INFREP VLF/LF electromagnetic network. The data collected on different frequencies, during April-May 2012 were studied using different methods of analysis: daily correlation methods, spectral approaches and terminator time techniques, in order to find out possible connections between the seismic activity and the subionospheric propagation properties of radio waves. The studies were performed with the help of a specially designed LabVIEW application, which accesses the VLF/LF receiver through internet. This program opens the receiver's web-page and automatically retrieves the list of data files to synchronize the user-side data with the receiver's data. Missing zipped files are also automatically downloaded. The application performs primary, statistical correlation and spectral analysis, appends daily files into monthly and annual files and performs 3D colour-coded maps with graphic representations of VLF and LF signals' intensities versus the minute-of-the-day and the day-of-the-month, facilitating a near real-time observation of VLF and LF electromagnetic waves' propagation. Another feature of the software is the correlation of the daily recorded files for the studied frequencies by overlaying the 24 hours radio activity and taking into account the sunrise and sunset. Data are individually processed (spectral power, correlations, differentiation, filtered using bandpass, lowpass, highpass). JTFA spectrograms (Cone-Shaped Distribution CSD, Gabor, Wavelet, short-time Fourier transform STFT, Wigner-Ville Distribution WVD, Choi-Williams Distribution CWD) are used, too.

Fluorescent carbohydrate probes for cell lectins

NASA Astrophysics Data System (ADS)

Galanina, Oxana; Feofanov, Alexei; Tuzikov, Alexander B.; Rapoport, Evgenia; Crocker, Paul R.; Grichine, Alexei; Egret-Charlier, Marguerite; Vigny, Paul; Le Pendu, Jacques; Bovin, Nicolai V.

2001-09-01

Fluorescein labeled carbohydrate (Glyc) probes were synthesized as analytical tools for the study of cellular lectins, i.e. SiaLe x-PAA-flu, Sia 2-PAA-flu, GlcNAc 2-PAA-flu, LacNAc-PAA-flu and a number of similar ones, with PAA a soluble polyacrylamide carrier. The binding of SiaLe x-PAA-flu was assessed using CHO cells transfected with E-selectin, and the binding of Sia 2-PAA-flu was assessed by COS cells transfected with siglec-9. In flow cytometry assays, the fluorescein probes demonstrated a specific binding to the lectin-transfected cells that was inhibited by unlabeled carbohydrate ligands. The intense binding of SiaLe x-PAA- 3H to the E-selectin transfected cells and the lack of binding to both native and permeabilized control cells lead to the conclusion that the polyacrylamide carrier itself and the spacer arm connecting the carbohydrate moiety with PAA did not contribute anymore to the binding. Tumors were obtained from nude mice by injection of CHO E-selectin or mock transfected cells. The fluorescent SiaLe x-PAA-flu probe could bind to the tumor sections from E-selectin positive CHO cells, but not from the control ones. Thus, these probes can be used to reveal specifically the carbohydrate binding sites on cells in culture as well as cells in tissue sections. The use of the confocal spectral imaging technique with Glyc-PAA-flu probes offered the unique possibility to detect lectins in different cells, even when the level of lectin expression was rather low. The confocal mode of spectrum recording provided an analysis of the probe localization with 3D submicron resolution. The spectral analysis (as a constituent part of the confocal spectral imaging technique) enabled interfering signals of the probe and intrinsic cellular fluorescence to be accurately separated, the distribution of the probe to be revealed and its local concentration to be measured.

Evaluation criteria for spectral design of camouflage

NASA Astrophysics Data System (ADS)

Škerlind, Christina; Fagerström, Jan; Hallberg, Tomas; Kariis, Hans

2015-10-01

In development of visual (VIS) and infrared (IR) camouflage for signature management, the aim is the design of surface properties of an object to spectrally match or adapt to a background and thereby minimizing the contrast perceived by a threatening sensor. The so called 'ladder model" relates the requirements for task measure of effectiveness with surface structure properties through the steps signature effectiveness and object signature. It is intended to link materials properties via platform signature to military utility and vice versa. Spectral design of a surface intends to give it a desired wavelength dependent optical response to fit a specific application of interest. Six evaluation criteria were stated, with the aim to aid the process to put requirement on camouflage and for evaluation. The six criteria correspond to properties such as reflectance, gloss, emissivity, and degree of polarization as well as dynamic properties, and broadband or multispectral properties. These criteria have previously been exemplified on different kinds of materials and investigated separately. Anderson and Åkerlind further point out that the six criteria rarely were considered or described all together in one and same publication previously. The specific level of requirement of the different properties must be specified individually for each specific situation and environment to minimize the contrast between target and a background. The criteria or properties are not totally independent of one another. How they are correlated is part of the theme of this paper. However, prioritization has been made due to the limit of space. Therefore all of the interconnections between the six criteria will not be considered in the work of this report. The ladder step previous to digging into the different material composition possibilities and choice of suitable materials and structures (not covered here), includes the object signature and decision of what the spectral response should be, when intended for a specific environment. The chosen spectral response should give a low detection probability (DP). How detection probability connects to image analysis tools and implementation of the six criteria is part of this work.

Planck 2013 results. IX. HFI spectral response

NASA Astrophysics Data System (ADS)

Planck Collaboration; Ade, P. A. R.; Aghanim, N.; Armitage-Caplan, C.; Arnaud, M.; Ashdown, M.; Atrio-Barandela, F.; Aumont, J.; Baccigalupi, C.; Banday, A. J.; Barreiro, R. B.; Battaner, E.; Benabed, K.; Benoît, A.; Benoit-Lévy, A.; Bernard, J.-P.; Bersanelli, M.; Bielewicz, P.; Bobin, J.; Bock, J. J.; Bond, J. R.; Borrill, J.; Bouchet, F. R.; Boulanger, F.; Bridges, M.; Bucher, M.; Burigana, C.; Cardoso, J.-F.; Catalano, A.; Challinor, A.; Chamballu, A.; Chary, R.-R.; Chen, X.; Chiang, H. C.; Chiang, L.-Y.; Christensen, P. R.; Church, S.; Clements, D. L.; Colombi, S.; Colombo, L. P. L.; Combet, C.; Comis, B.; Couchot, F.; Coulais, A.; Crill, B. P.; Curto, A.; Cuttaia, F.; Danese, L.; Davies, R. D.; de Bernardis, P.; de Rosa, A.; de Zotti, G.; Delabrouille, J.; Delouis, J.-M.; Désert, F.-X.; Dickinson, C.; Diego, J. M.; Dole, H.; Donzelli, S.; Doré, O.; Douspis, M.; Dupac, X.; Efstathiou, G.; Enßlin, T. A.; Eriksen, H. K.; Falgarone, E.; Finelli, F.; Forni, O.; Frailis, M.; Franceschi, E.; Galeotta, S.; Ganga, K.; Giard, M.; Giraud-Héraud, Y.; González-Nuevo, J.; Górski, K. M.; Gratton, S.; Gregorio, A.; Gruppuso, A.; Hansen, F. K.; Hanson, D.; Harrison, D.; Henrot-Versillé, S.; Hernández-Monteagudo, C.; Herranz, D.; Hildebrandt, S. R.; Hivon, E.; Hobson, M.; Holmes, W. A.; Hornstrup, A.; Hovest, W.; Huffenberger, K. M.; Hurier, G.; Jaffe, A. H.; Jaffe, T. R.; Jones, W. C.; Juvela, M.; Keihänen, E.; Keskitalo, R.; Kisner, T. S.; Kneissl, R.; Knoche, J.; Knox, L.; Kunz, M.; Kurki-Suonio, H.; Lagache, G.; Lamarre, J.-M.; Lasenby, A.; Laureijs, R. J.; Lawrence, C. R.; Leahy, J. P.; Leonardi, R.; Leroy, C.; Lesgourgues, J.; Liguori, M.; Lilje, P. B.; Linden-Vørnle, M.; López-Caniego, M.; Lubin, P. M.; Macías-Pérez, J. F.; Maffei, B.; Mandolesi, N.; Maris, M.; Marshall, D. J.; Martin, P. G.; Martínez-González, E.; Masi, S.; Massardi, M.; Matarrese, S.; Matthai, F.; Mazzotta, P.; McGehee, P.; Melchiorri, A.; Mendes, L.; Mennella, A.; Migliaccio, M.; Mitra, S.; Miville-Deschênes, M.-A.; Moneti, A.; Montier, L.; Morgante, G.; Mortlock, D.; Munshi, D.; Murphy, J. A.; Naselsky, P.; Nati, F.; Natoli, P.; Netterfield, C. B.; Nørgaard-Nielsen, H. U.; North, C.; Noviello, F.; Novikov, D.; Novikov, I.; Osborne, S.; Oxborrow, C. A.; Paci, F.; Pagano, L.; Pajot, F.; Paoletti, D.; Pasian, F.; Patanchon, G.; Perdereau, O.; Perotto, L.; Perrotta, F.; Piacentini, F.; Piat, M.; Pierpaoli, E.; Pietrobon, D.; Plaszczynski, S.; Pointecouteau, E.; Polenta, G.; Ponthieu, N.; Popa, L.; Poutanen, T.; Pratt, G. W.; Prézeau, G.; Prunet, S.; Puget, J.-L.; Rachen, J. P.; Reinecke, M.; Remazeilles, M.; Renault, C.; Ricciardi, S.; Riller, T.; Ristorcelli, I.; Rocha, G.; Rosset, C.; Roudier, G.; Rusholme, B.; Santos, D.; Savini, G.; Scott, D.; Shellard, E. P. S.; Spencer, L. D.; Starck, J.-L.; Stolyarov, V.; Stompor, R.; Sudiwala, R.; Sureau, F.; Sutton, D.; Suur-Uski, A.-S.; Sygnet, J.-F.; Tauber, J. A.; Tavagnacco, D.; Terenzi, L.; Tomasi, M.; Tristram, M.; Tucci, M.; Umana, G.; Valenziano, L.; Valiviita, J.; Van Tent, B.; Vielva, P.; Villa, F.; Vittorio, N.; Wade, L. A.; Wandelt, B. D.; Yvon, D.; Zacchei, A.; Zonca, A.

2014-11-01

The Planck High Frequency Instrument (HFI) spectral response was determined through a series of ground based tests conducted with the HFI focal plane in a cryogenic environment prior to launch. The main goal of the spectral transmission tests was to measure the relative spectral response (includingthe level of out-of-band signal rejection) of all HFI detectors to a known source of electromagnetic radiation individually. This was determined by measuring the interferometric output of a continuously scanned Fourier transform spectrometer with all HFI detectors. As there is no on-board spectrometer within HFI, the ground-based spectral response experiments provide the definitive data set for the relative spectral calibration of the HFI. Knowledge of the relative variations in the spectral response between HFI detectors allows for a more thorough analysis of the HFI data. The spectral response of the HFI is used in Planck data analysis and component separation, this includes extraction of CO emission observed within Planck bands, dust emission, Sunyaev-Zeldovich sources, and intensity to polarization leakage. The HFI spectral response data have also been used to provide unit conversion and colour correction analysis tools. While previous papers describe the pre-flight experiments conducted on the Planck HFI, this paper focusses on the analysis of the pre-flight spectral response measurements and the derivation of data products, e.g. band-average spectra, unit conversion coefficients, and colour correction coefficients, all with related uncertainties. Verifications of the HFI spectral response data are provided through comparisons with photometric HFI flight data. This validation includes use of HFI zodiacal emission observations to demonstrate out-of-band spectral signal rejection better than 108. The accuracy of the HFI relative spectral response data is verified through comparison with complementary flight-data based unit conversion coefficients and colour correction coefficients. These coefficients include those based upon HFI observations of CO, dust, and Sunyaev-Zeldovich emission. General agreement is observed between the ground-based spectral characterization of HFI and corresponding in-flight observations, within the quoted uncertainty of each; explanations are provided for any discrepancies.

Quantum signature of chaos and thermalization in the kicked Dicke model

NASA Astrophysics Data System (ADS)

Ray, S.; Ghosh, A.; Sinha, S.

2016-09-01

We study the quantum dynamics of the kicked Dicke model (KDM) in terms of the Floquet operator, and we analyze the connection between chaos and thermalization in this context. The Hamiltonian map is constructed by suitably taking the classical limit of the Heisenberg equation of motion to study the corresponding phase-space dynamics, which shows a crossover from regular to chaotic motion by tuning the kicking strength. The fixed-point analysis and calculation of the Lyapunov exponent (LE) provide us with a complete picture of the onset of chaos in phase-space dynamics. We carry out a spectral analysis of the Floquet operator, which includes a calculation of the quasienergy spacing distribution and structural entropy to show the correspondence to the random matrix theory in the chaotic regime. Finally, we analyze the thermodynamics and statistical properties of the bosonic sector as well as the spin sector, and we discuss how such a periodically kicked system relaxes to a thermalized state in accordance with the laws of statistical mechanics.

Using Separable Nonnegative Matrix Factorization Techniques for the Analysis of Time-Resolved Raman Spectra

NASA Astrophysics Data System (ADS)

Luce, R.; Hildebrandt, P.; Kuhlmann, U.; Liesen, J.

2016-09-01

The key challenge of time-resolved Raman spectroscopy is the identification of the constituent species and the analysis of the kinetics of the underlying reaction network. In this work we present an integral approach that allows for determining both the component spectra and the rate constants simultaneously from a series of vibrational spectra. It is based on an algorithm for non-negative matrix factorization which is applied to the experimental data set following a few pre-processing steps. As a prerequisite for physically unambiguous solutions, each component spectrum must include one vibrational band that does not significantly interfere with vibrational bands of other species. The approach is applied to synthetic "experimental" spectra derived from model systems comprising a set of species with component spectra differing with respect to their degree of spectral interferences and signal-to-noise ratios. In each case, the species involved are connected via monomolecular reaction pathways. The potential and limitations of the approach for recovering the respective rate constants and component spectra are discussed.

Quantum signature of chaos and thermalization in the kicked Dicke model.

PubMed

Ray, S; Ghosh, A; Sinha, S

2016-09-01

We study the quantum dynamics of the kicked Dicke model (KDM) in terms of the Floquet operator, and we analyze the connection between chaos and thermalization in this context. The Hamiltonian map is constructed by suitably taking the classical limit of the Heisenberg equation of motion to study the corresponding phase-space dynamics, which shows a crossover from regular to chaotic motion by tuning the kicking strength. The fixed-point analysis and calculation of the Lyapunov exponent (LE) provide us with a complete picture of the onset of chaos in phase-space dynamics. We carry out a spectral analysis of the Floquet operator, which includes a calculation of the quasienergy spacing distribution and structural entropy to show the correspondence to the random matrix theory in the chaotic regime. Finally, we analyze the thermodynamics and statistical properties of the bosonic sector as well as the spin sector, and we discuss how such a periodically kicked system relaxes to a thermalized state in accordance with the laws of statistical mechanics.

Connectopic mapping with resting-state fMRI.

PubMed

Haak, Koen V; Marquand, Andre F; Beckmann, Christian F

2018-04-15

Brain regions are often topographically connected: nearby locations within one brain area connect with nearby locations in another area. Mapping these connection topographies, or 'connectopies' in short, is crucial for understanding how information is processed in the brain. Here, we propose principled, fully data-driven methods for mapping connectopies using functional magnetic resonance imaging (fMRI) data acquired at rest by combining spectral embedding of voxel-wise connectivity 'fingerprints' with a novel approach to spatial statistical inference. We apply the approach in human primary motor and visual cortex, and show that it can trace biologically plausible, overlapping connectopies in individual subjects that follow these regions' somatotopic and retinotopic maps. As a generic mechanism to perform inference over connectopies, the new spatial statistics approach enables rigorous statistical testing of hypotheses regarding the fine-grained spatial profile of functional connectivity and whether that profile is different between subjects or between experimental conditions. The combined framework offers a fundamental alternative to existing approaches to investigating functional connectivity in the brain, from voxel- or seed-pair wise characterizations of functional association, towards a full, multivariate characterization of spatial topography. Copyright © 2017 The Authors. Published by Elsevier Inc. All rights reserved.

Fluorescence detection and photodynamic activity of endogenous protoporphyrin in human skin

NASA Astrophysics Data System (ADS)

Koenig, Karsten; Rueck, Angelika C.; Schneckenburger, Herbert

1992-07-01

Human skin shows a strong autofluorescence in the red spectral region with main peaks around 600, 620, and 640 nm caused by the porphyrin production of the gram positive lipophile skin bacterium Propionibacterium acnes. Irradiation of these bacteria reduces the integral fluorescence intensity and induces the formation of photoproducts with fluorescence bands around 670 nm and decay times of about 1 and 5 ns. The photoproduct formation is connected with an increased absorption in the red spectral region. The endogenous fluorescent porphyrins act as photosensitizers. Photodestruction of Propionibacteria acnes by visible light appears therefore to be a promising therapy. The photodynamic activity of the photoproducts was lower than that of protoporphyrin IX.

Spectral analysis software improves confidence in plant and soil water stable isotope analyses performed by isotope ratio infrared spectroscopy (IRIS).

PubMed

West, A G; Goldsmith, G R; Matimati, I; Dawson, T E

2011-08-30

Previous studies have demonstrated the potential for large errors to occur when analyzing waters containing organic contaminants using isotope ratio infrared spectroscopy (IRIS). In an attempt to address this problem, IRIS manufacturers now provide post-processing spectral analysis software capable of identifying samples with the types of spectral interference that compromises their stable isotope analysis. Here we report two independent tests of this post-processing spectral analysis software on two IRIS systems, OA-ICOS (Los Gatos Research Inc.) and WS-CRDS (Picarro Inc.). Following a similar methodology to a previous study, we cryogenically extracted plant leaf water and soil water and measured the δ(2)H and δ(18)O values of identical samples by isotope ratio mass spectrometry (IRMS) and IRIS. As an additional test, we analyzed plant stem waters and tap waters by IRMS and IRIS in an independent laboratory. For all tests we assumed that the IRMS value represented the "true" value against which we could compare the stable isotope results from the IRIS methods. Samples showing significant deviations from the IRMS value (>2σ) were considered to be contaminated and representative of spectral interference in the IRIS measurement. Over the two studies, 83% of plant species were considered contaminated on OA-ICOS and 58% on WS-CRDS. Post-analysis, spectra were analyzed using the manufacturer's spectral analysis software, in order to see if the software correctly identified contaminated samples. In our tests the software performed well, identifying all the samples with major errors. However, some false negatives indicate that user evaluation and testing of the software are necessary. Repeat sampling of plants showed considerable variation in the discrepancies between IRIS and IRMS. As such, we recommend that spectral analysis of IRIS data must be incorporated into standard post-processing routines. Furthermore, we suggest that the results from spectral analysis be included when reporting stable isotope data from IRIS. Copyright © 2011 John Wiley & Sons, Ltd.

Highly sensitive index of sympathetic activity based on time-frequency spectral analysis of electrodermal activity.

PubMed

Posada-Quintero, Hugo F; Florian, John P; Orjuela-Cañón, Álvaro D; Chon, Ki H

2016-09-01

Time-domain indices of electrodermal activity (EDA) have been used as a marker of sympathetic tone. However, they often show high variation between subjects and low consistency, which has precluded their general use as a marker of sympathetic tone. To examine whether power spectral density analysis of EDA can provide more consistent results, we recently performed a variety of sympathetic tone-evoking experiments (43). We found significant increase in the spectral power in the frequency range of 0.045 to 0.25 Hz when sympathetic tone-evoking stimuli were induced. The sympathetic tone assessed by the power spectral density of EDA was found to have lower variation and more sensitivity for certain, but not all, stimuli compared with the time-domain analysis of EDA. We surmise that this lack of sensitivity in certain sympathetic tone-inducing conditions with time-invariant spectral analysis of EDA may lie in its inability to characterize time-varying dynamics of the sympathetic tone. To overcome the disadvantages of time-domain and time-invariant power spectral indices of EDA, we developed a highly sensitive index of sympathetic tone, based on time-frequency analysis of EDA signals. Its efficacy was tested using experiments designed to elicit sympathetic dynamics. Twelve subjects underwent four tests known to elicit sympathetic tone arousal: cold pressor, tilt table, stand test, and the Stroop task. We hypothesize that a more sensitive measure of sympathetic control can be developed using time-varying spectral analysis. Variable frequency complex demodulation, a recently developed technique for time-frequency analysis, was used to obtain spectral amplitudes associated with EDA. We found that the time-varying spectral frequency band 0.08-0.24 Hz was most responsive to stimulation. Spectral power for frequencies higher than 0.24 Hz were determined to be not related to the sympathetic dynamics because they comprised less than 5% of the total power. The mean value of time-varying spectral amplitudes in the frequency band 0.08-0.24 Hz were used as the index of sympathetic tone, termed TVSymp. TVSymp was found to be overall the most sensitive to the stimuli, as evidenced by a low coefficient of variation (0.54), and higher consistency (intra-class correlation, 0.96) and sensitivity (Youden's index > 0.75), area under the receiver operating characteristic (ROC) curve (>0.8, accuracy > 0.88) compared with time-domain and time-invariant spectral indices, including heart rate variability. Copyright © 2016 the American Physiological Society.

Spectral Analysis of Rich Network Topology in Social Networks

ERIC Educational Resources Information Center

Wu, Leting

2013-01-01

Social networks have received much attention these days. Researchers have developed different methods to study the structure and characteristics of the network topology. Our focus is on spectral analysis of the adjacency matrix of the underlying network. Recent work showed good properties in the adjacency spectral space but there are few…

New tools for the tracing of ancient starbursts: Analysing globular cluster systems using Lick indices

NASA Astrophysics Data System (ADS)

Lilly, T.; Fritze-v. Alvensleben, U.; de Grijs, R.

2005-05-01

We present mathematically advanced tools for the determination of age, metallicity, and mass of old Globular Clusters (CGs) using both broad-band colors and spectral indices, and we present their application to the Globular Cluster Systems (GCSs) of elliptical galaxies. Since one of the most intriguing questions of today's astronomy aims at the evolutionary connection between (young) violently interacting galaxies at high-redshift and the (old) elliptical galaxies we observe nearby, it is necessary to reveal the possibly violent star-formation history of these old galaxies. By means of evolutionary synthesis models, we can show that, using the integrated light of a galaxy's (composite) stellar content alone, it is impossible to date (and, actually, to identify) even very strong starbursts if these events took place more than two or three Gyr ago. However, since large and violent starbursts are associated with the formation of GCs, GCSs are very good tracers of the most violent starburst events in the history of their host galaxies. Using our well-established Göttingen SED (Spectral Energy Distribution) analysis tool, we can reveal the age, metallicity, mass (and possibly extinction) of GCs by comparing the observations with an extensive grid of SSP model colors. This is done in a statistically advanced and reasonable way, including their 1 σ uncertainties. However, since for all colors the evolution slows down considerably at ages older than about 8 Gyr, even with several passbands and a long wavelength base line, the results are severely uncertain for old clusters. Therefore, we incorporated empirical calibrations for Lick indices in our models and developed a Lick indices analysis tool that works in the same way as the SED analysis tool described above. We compare the theoretical possibilities and limitations of both methods as well as their results for the example of the cD galaxy NGC 1399, for which both multi-color observations and, for a subsample of clusters, spectral indices are available, and address implications for the nature and origin of the observed bimodal color distribution.

Development and Validation of a New Fallout Transport Method Using Variable Spectral Winds

NASA Astrophysics Data System (ADS)

Hopkins, Arthur Thomas

A new method has been developed to incorporate variable winds into fallout transport calculations. The method uses spectral coefficients derived by the National Meteorological Center. Wind vector components are computed with the coefficients along the trajectories of falling particles. Spectral winds are used in the two-step method to compute dose rate on the ground, downwind of a nuclear cloud. First, the hotline is located by computing trajectories of particles from an initial, stabilized cloud, through spectral winds, to the ground. The connection of particle landing points is the hotline. Second, dose rate on and around the hotline is computed by analytically smearing the falling cloud's activity along the ground. The feasibility of using specgtral winds for fallout particle transport was validated by computing Mount St. Helens ashfall locations and comparing calculations to fallout data. In addition, an ashfall equation was derived for computing volcanic ash mass/area on the ground. Ashfall data and the ashfall equation were used to back-calculate an aggregated particle size distribution for the Mount St. Helens eruption cloud. Further validation was performed by comparing computed and actual trajectories of a high explosive dust cloud (DIRECT COURSE). Using an error propagation formula, it was determined that uncertainties in spectral wind components produce less than four percent of the total dose rate variance. In summary, this research demonstrated the feasibility of using spectral coefficients for fallout transport calculations, developed a two-step smearing model to treat variable winds, and showed that uncertainties in spectral winds do not contribute significantly to the error in computed dose rate.

Physical characterization of Warm Spitzer-observed near-Earth objects

NASA Astrophysics Data System (ADS)

Thomas, Cristina A.; Emery, Joshua P.; Trilling, David E.; Delbó, Marco; Hora, Joseph L.; Mueller, Michael

2014-01-01

Near-infrared spectroscopy of Near-Earth Objects (NEOs) connects diagnostic spectral features to specific surface mineralogies. The combination of spectroscopy with albedos and diameters derived from thermal infrared observations can increase the scientific return beyond that of the individual datasets. For instance, some taxonomic classes can be separated into distinct compositional groupings with albedo and different mineralogies with similar albedos can be distinguished with spectroscopy. To that end, we have completed a spectroscopic observing campaign to complement the ExploreNEOs Warm Spitzer program that obtained albedos and diameters of nearly 600 NEOs (Trilling, D.E. et al. [2010]. Astron. J. 140, 770-784. http://dx.doi.org/10.1088/0004-6256/140/3/770). The spectroscopy campaign included visible and near-infrared observations of ExploreNEOs targets from various observatories. Here we present the results of observations using the low-resolution prism mode (˜0.7-2.5 μm) of the SpeX instrument on the NASA Infrared Telescope Facility (IRTF). We also include near-infrared observations of ExploreNEOs targets from the MIT-UH-IRTF Joint Campaign for Spectral Reconnaissance. Our dataset includes near-infrared spectra of 187 ExploreNEOs targets (125 observations of 92 objects from our survey and 213 observations of 154 objects from the MIT survey). We identify a taxonomic class for each spectrum and use band parameter analysis to investigate the mineralogies for the S-, Q-, and V-complex objects. Our analysis suggests that for spectra that contain near-infrared data but lack the visible wavelength region, the Bus-DeMeo system misidentifies some S-types as Q-types. We find no correlation between spectral band parameters and ExploreNEOs albedos and diameters. We investigate the correlations of phase angle with Band Area Ratio and near-infrared spectral slope. We find slightly negative Band Area Ratio (BAR) correlations with phase angle for Eros and Ivar, but a positive BAR correlation with phase angle for Ganymed. The results of our phase angle study are consistent with those of (Sanchez, J.A., Reddy, V., Nathues, A., Cloutis, E.A., Mann, P., Hiesinger, H. [2012]. Icarus 220, 36-50. http://dx.doi.org/10.1016/j.icarus.2012.04.008, arXiv:1205.0248). We find evidence for spectral phase reddening for Eros, Ganymed, and Ivar. We identify the likely ordinary chondrite type analog for an appropriate subset of our sample. Our resulting proportions of H, L, and LL ordinary chondrites differ from those calculated for meteorite falls and in previous studies of ordinary chondrite-like NEOs.

67P/CG morphological units and VIS-IR spectral classes: a Rosetta/VIRTIS-M perspective

NASA Astrophysics Data System (ADS)

Filacchione, Gianrico; Capaccioni, Fabrizio; Ciarniello, Mauro; Raponi, Andrea; De Sanctis, Maria Cristina; Tosi, Federico; Piccioni, Giuseppe; Cerroni, Priscilla; Capria, Maria Teresa; Palomba, Ernesto; Longobardo, Andrea; Migliorini, Alessandra; Erard, Stephane; Arnold, Gabriele; Bockelee-Morvan, Dominique; Leyrat, Cedric; Schmitt, Bernard; Quirico, Eric; Barucci, Antonella; McCord, Thomas B.; Stephan, Katrin; Kappel, David

2015-11-01

VIRTIS-M, the 0.25-5.1 µm imaging spectrometer on Rosetta (Coradini et al., 2007), has mapped the surface of 67P/CG nucleus since July 2014 from a wide range of distances. Spectral analysis of global scale data indicate that the nucleus presents different terrains uniformly covered by a very dark (Ciarniello et al., 2015) and dehydrated organic-rich material (Capaccioni et al., 2015). The morphological units identified so far (Thomas et al., 2015; El-Maarry et al., 2015) include dust-covered brittle materials regions (like Ash, Ma'at), exposed material regions (Seth), large-scale depressions (like Hatmehit, Aten, Nut), smooth terrains units (like Hapi, Anubis, Imhotep) and consolidated surfaces (like Hathor, Anuket, Aker, Apis, Khepry, Bastet, Maftet). For each of these regions average VIRTIS-M spectra were derived with the aim to explore possible connections between morphology and spectral properties. Photometric correction (Ciarniello et al., 2015), thermal emission removal in the 3.5-5 micron range and georeferencing have been applied to I/F data in order to derive spectral indicators, e.g. VIS-IR spectral slopes, their crossing wavelength (CW) and the 3.2 µm organic material band’s depth (BD), suitable to identify and map compositional variations. Our analysis shows that smooth terrains have the lower slopes in VIS (<1.7E-3 1/µm) and IR (0.4E-3 1/µm), CW=0.75 µm and BD=8-12%. Intermediate VIS slope=1.7-1.9E-3 1/µm, and higher BD=10-12.8%, are typical of consolidated surfaces, some dust covered regions and Seth where the maximum BD=13% has been observed. Large-scale depressions and Imhotep are redder with a VIS slope of 1.9-2.1E-3 1/µm, CW at 0.85-0.9 µm and BD=8-11%. The minimum VIS-IR slopes are observed above the Hapi, in agreement with the presence of water ice sublimation and recondensation processes observed by VIRTIS in this region (De Sanctis et al., 2015).Authors acknowledge ASI, CNES, DLR and NASA financial support.References:-Coradini et al., SSR, 28, 529-559, 2007-Ciarniello et al., A&A, in press-Capaccioni et al., Science, 347, aaa0628 1-4, 2015-Thomas et al., Science, 347, aaa0440 1-6, 2015-El-Marry et al., A&A, in press-De Sanctis et al., Nature, in press

A practical approach to spectral calibration of short wavelength infrared hyper-spectral imaging systems

NASA Astrophysics Data System (ADS)

Bürmen, Miran; Pernuš, Franjo; Likar, Boštjan

2010-02-01

Near-infrared spectroscopy is a promising, rapidly developing, reliable and noninvasive technique, used extensively in the biomedicine and in pharmaceutical industry. With the introduction of acousto-optic tunable filters (AOTF) and highly sensitive InGaAs focal plane sensor arrays, real-time high resolution hyper-spectral imaging has become feasible for a number of new biomedical in vivo applications. However, due to the specificity of the AOTF technology and lack of spectral calibration standardization, maintaining long-term stability and compatibility of the acquired hyper-spectral images across different systems is still a challenging problem. Efficiently solving both is essential as the majority of methods for analysis of hyper-spectral images relay on a priori knowledge extracted from large spectral databases, serving as the basis for reliable qualitative or quantitative analysis of various biological samples. In this study, we propose and evaluate fast and reliable spectral calibration of hyper-spectral imaging systems in the short wavelength infrared spectral region. The proposed spectral calibration method is based on light sources or materials, exhibiting distinct spectral features, which enable robust non-rigid registration of the acquired spectra. The calibration accounts for all of the components of a typical hyper-spectral imaging system such as AOTF, light source, lens and optical fibers. The obtained results indicated that practical, fast and reliable spectral calibration of hyper-spectral imaging systems is possible, thereby assuring long-term stability and inter-system compatibility of the acquired hyper-spectral images.

Multiple-region directed functional connectivity based on phase delays.

PubMed

Goelman, Gadi; Dan, Rotem

2017-03-01

Network analysis is increasingly advancing the field of neuroimaging. Neural networks are generally constructed from pairwise interactions with an assumption of linear relations between them. Here, a high-order statistical framework to calculate directed functional connectivity among multiple regions, using wavelet analysis and spectral coherence has been presented. The mathematical expression for 4 regions was derived and used to characterize a quartet of regions as a linear, combined (nonlinear), or disconnected network. Phase delays between regions were used to obtain network's temporal hierarchy and directionality. The validity of the mathematical derivation along with the effects of coupling strength and noise on its outcomes were studied by computer simulations of the Kuramoto model. The simulations demonstrated correct directionality for a large range of coupling strength and low sensitivity to Gaussian noise compared with pairwise coherences. The analysis was applied to resting-state fMRI data of 40 healthy young subjects to characterize the ventral visual system, motor system and default mode network (DMN). It was shown that the ventral visual system was predominantly composed of linear networks while the motor system and the DMN were composed of combined (nonlinear) networks. The ventral visual system exhibits its known temporal hierarchy, the motor system exhibits center ↔ out hierarchy and the DMN has dorsal ↔ ventral and anterior ↔ posterior organizations. The analysis can be applied in different disciplines such as seismology, or economy and in a variety of brain data including stimulus-driven fMRI, electrophysiology, EEG, and MEG, thus open new horizons in brain research. Hum Brain Mapp 38:1374-1386, 2017. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.

Neural oscillatory mechanisms during novel grammar learning underlying language analytical abilities.

PubMed

Kepinska, Olga; Pereda, Ernesto; Caspers, Johanneke; Schiller, Niels O

2017-12-01

The goal of the present study was to investigate the initial phases of novel grammar learning on a neural level, concentrating on mechanisms responsible for individual variability between learners. Two groups of participants, one with high and one with average language analytical abilities, performed an Artificial Grammar Learning (AGL) task consisting of learning and test phases. During the task, EEG signals from 32 cap-mounted electrodes were recorded and epochs corresponding to the learning phases were analysed. We investigated spectral power modulations over time, and functional connectivity patterns by means of a bivariate, frequency-specific index of phase synchronization termed Phase Locking Value (PLV). Behavioural data showed learning effects in both groups, with a steeper learning curve and higher ultimate attainment for the highly skilled learners. Moreover, we established that cortical connectivity patterns and profiles of spectral power modulations over time differentiated L2 learners with various levels of language analytical abilities. Over the course of the task, the learning process seemed to be driven by whole-brain functional connectivity between neuronal assemblies achieved by means of communication in the beta band frequency. On a shorter time-scale, increasing proficiency on the AGL task appeared to be supported by stronger local synchronisation within the right hemisphere regions. Finally, we observed that the highly skilled learners might have exerted less mental effort, or reduced attention for the task at hand once the learning was achieved, as evidenced by the higher alpha band power. Copyright © 2017 Elsevier Inc. All rights reserved.

Nondestructive detection of pork quality based on dual-band VIS/NIR spectroscopy

NASA Astrophysics Data System (ADS)

Wang, Wenxiu; Peng, Yankun; Li, Yongyu; Tang, Xiuying; Liu, Yuanyuan

2015-05-01

With the continuous development of living standards and the relative change of dietary structure, consumers' rising and persistent demand for better quality of meat is emphasized. Colour, pH value, and cooking loss are important quality attributes when evaluating meat. To realize nondestructive detection of multi-parameter of meat quality simultaneously is popular in production and processing of meat and meat products. The objectives of this research were to compare the effectiveness of two bands for rapid nondestructive and simultaneous detection of pork quality attributes. Reflectance spectra of 60 chilled pork samples were collected from a dual-band visible/near-infrared spectroscopy system which covered 350-1100 nm and 1000-2600 nm. Then colour, pH value and cooking loss were determined by standard methods as reference values. Standard normal variables transform (SNVT) was employed to eliminate the spectral noise. A spectrum connection method was put forward for effective integration of the dual-band spectrum to make full use of the whole efficient information. Partial least squares regression (PLSR) and Principal component analysis (PCA) were applied to establish prediction models using based on single-band spectrum and dual-band spectrum, respectively. The experimental results showed that the PLSR model based on dual-band spectral information was superior to the models based on single band spectral information with lower root means quare error (RMSE) and higher accuracy. The PLSR model based on dual-band (use the overlapping part of first band) yielded the best prediction result with correlation coefficient of validation (Rv) of 0.9469, 0.9495, 0.9180, 0.9054 and 0.8789 for L*, a*, b*, pH value and cooking loss, respectively. This mainly because dual-band spectrum can provide sufficient and comprehensive information which reflected the quality attributes. Data fusion from dual-band spectrum could significantly improve pork quality parameters prediction performance. The research also indicated that multi-band spectral information fusion has potential to comprehensively evaluate other quality and safety attributes of pork.

Propagating annotations of molecular networks using in silico fragmentation

PubMed Central

da Silva, Ricardo R.; Wang, Mingxun; Fox, Evan; Balunas, Marcy J.; Klassen, Jonathan L.; Dorrestein, Pieter C.

2018-01-01

The annotation of small molecules is one of the most challenging and important steps in untargeted mass spectrometry analysis, as most of our biological interpretations rely on structural annotations. Molecular networking has emerged as a structured way to organize and mine data from untargeted tandem mass spectrometry (MS/MS) experiments and has been widely applied to propagate annotations. However, propagation is done through manual inspection of MS/MS spectra connected in the spectral networks and is only possible when a reference library spectrum is available. One of the alternative approaches used to annotate an unknown fragmentation mass spectrum is through the use of in silico predictions. One of the challenges of in silico annotation is the uncertainty around the correct structure among the predicted candidate lists. Here we show how molecular networking can be used to improve the accuracy of in silico predictions through propagation of structural annotations, even when there is no match to a MS/MS spectrum in spectral libraries. This is accomplished through creating a network consensus of re-ranked structural candidates using the molecular network topology and structural similarity to improve in silico annotations. The Network Annotation Propagation (NAP) tool is accessible through the GNPS web-platform https://gnps.ucsd.edu/ProteoSAFe/static/gnps-theoretical.jsp. PMID:29668671

A simple dental caries detection system using full spectrum of laser-induced fluorescence

NASA Astrophysics Data System (ADS)

Rocha-Cabral, Renata Maciel; Mendes, Fausto Medeiros; Maldonado, Edison Puig; Zezell, Denise Maria

2015-06-01

Objectives: to develop an apparatus for the detection of early caries lesions in enamel using the full extent of the tooth fluorescence spectrum, through the integration of a laser diode, fiber optics, filters and one portable spectrometer connected to a computer, all commercially available; to evaluate the developed device in clinical and laboratory tests, and compare its performance with commercial equipment. Methods: clinical examinations were performed in patients with indication for exodontics of premolars. After examinations, the patients underwent surgery and the teeth were stored individually. The optical measurements were repeated approximately two months after extraction, on the same sites previously examined, then histological analysis was carried out. Results: the spectral detector has presented high specificity and moderate sensitivity when applied to differentiate between healthy and damaged tissues, with no significant differences from the performance of the commercial equipment. The developed device is able to detect initial damages in enamel, with depth of approximately 300 μm. Conclusions: we successfully demonstrated the development of a simple and portable system based in laser-induced fluorescence for caries detection, assembled from common commercial parts. As the spectral detector acquires a complete recording of the spectrum from each tissue, it is possible to use it for monitoring developments of caries lesions.

Measuring the ISM Content of Optically Luminous Type 2 Quasars

NASA Astrophysics Data System (ADS)

Marshall, Jameeka; Petric, Andreea; Flagey, Nicolas; Lacy, Mark; Omont, Alain

2018-01-01

There is a connection between black holes (BH) and the surrounding bulge stars. Measuring the cold interstellar medium (ISM) content of host galaxies is essential to understand the coevolution of galaxies and BHs. The ISM measurement is important because gas constitutes the raw material from which BHs grow and stars form. Quasars are extremely luminous active galaxies fueled by accreting supermassive black holes. Type 2 quasars have narrow spectral lines whereas type 1 quasars have broad spectral lines. Not only can the ISM measurements provide empirical data to help further clarify quasar models but it is also crucial in distinguishing the physical differences between type 1 and type 2 quasars. Observations of twenty type 2 quasars were made using IRAM, a single dish 30 meter radio telescope, to measure 12CO (1-0) and 12CO (2-1) emission. We used line widths to constrain the dynamical mass and gravitational potential of the host galaxy. Star formation rate (SFR) measured in the infrared (IR) and SFR derived from optical spectra were used to estimate star formation efficiency and gas depletion time scale (M H2/star formation rate). Preliminary analysis suggests that star formation efficiency in type 2 quasars is slightly higher than in type 1 quasars.

The Chemistry of Shocked High-energy Materials: Connecting Atomistic Simulations to Experiments

NASA Astrophysics Data System (ADS)

Islam, Md Mahbubul; Strachan, Alejandro

2017-06-01

A comprehensive atomistic-level understanding of the physics and chemistry of shocked high energy (HE) materials is crucial for designing safe and efficient explosives. Advances in the ultrafast spectroscopy and laser shocks enabled the study of shock-induced chemistry at extreme conditions occurring at picosecond timescales. Despite this progress experiments are not without limitations and do not enable a direct characterization of chemical reactions. At the same time, large-scale reactive molecular dynamics (MD) simulations are capable of providing description of the shocked-induced chemistry but the uncertainties resulting from the use of approximate descriptions of atomistic interactions remain poorly quantified. We use ReaxFF MD simulations to investigate the shock and temperature induced chemical decomposition mechanisms of polyvinyl nitrate, RDX, and nitromethane. The effect of various shock pressures on reaction initiation mechanisms is investigated for all three materials. We performed spectral analysis from atomistic velocities at different shock pressures to enable direct comparison with experiments. The simulations predict volume-increasing reactions at the shock-to-detonation transitions and the shock vs. particle velocity data are in good agreement with available experimental data. The ReaxFF MD simulations validated against experiments enabled prediction of reaction kinetics of shocked materials, and interpretation of experimental spectroscopy data via assignment of the spectral peaks to dictate various reaction pathways at extreme conditions.

Propagating annotations of molecular networks using in silico fragmentation.

PubMed

da Silva, Ricardo R; Wang, Mingxun; Nothias, Louis-Félix; van der Hooft, Justin J J; Caraballo-Rodríguez, Andrés Mauricio; Fox, Evan; Balunas, Marcy J; Klassen, Jonathan L; Lopes, Norberto Peporine; Dorrestein, Pieter C

2018-04-01

The annotation of small molecules is one of the most challenging and important steps in untargeted mass spectrometry analysis, as most of our biological interpretations rely on structural annotations. Molecular networking has emerged as a structured way to organize and mine data from untargeted tandem mass spectrometry (MS/MS) experiments and has been widely applied to propagate annotations. However, propagation is done through manual inspection of MS/MS spectra connected in the spectral networks and is only possible when a reference library spectrum is available. One of the alternative approaches used to annotate an unknown fragmentation mass spectrum is through the use of in silico predictions. One of the challenges of in silico annotation is the uncertainty around the correct structure among the predicted candidate lists. Here we show how molecular networking can be used to improve the accuracy of in silico predictions through propagation of structural annotations, even when there is no match to a MS/MS spectrum in spectral libraries. This is accomplished through creating a network consensus of re-ranked structural candidates using the molecular network topology and structural similarity to improve in silico annotations. The Network Annotation Propagation (NAP) tool is accessible through the GNPS web-platform https://gnps.ucsd.edu/ProteoSAFe/static/gnps-theoretical.jsp.

Confirming LBV Candidates Through Variability: A Photometric and Spectroscopic Monitoring Study

NASA Astrophysics Data System (ADS)

Stringfellow, Guy; Gvaramadze, Vasilii

2013-02-01

Luminous Blue Variable (LBV) stars represent an extremely rare class of luminous massive stars with high mass loss rates. The paucity ( 12) of confirmed Galactic LBV precludes determining a solid evolutionary connection between LBV and other intermediate (e.g. Ofpe/WN9, WNL) phases in the life of very massive stars. We've been conducting an optical/near-IR spectral survey of a large subset of central stars residing within newly discovered it Spitzer nebulae and have identified over two dozen new candidate LBVs (cLBVs) based on spectral similarity alone; confirming them as bona fide LBVs requires demonstrating 1-3 mag photometric and spectroscopic variability. This marks a significant advancement in the study of massive stars, far outweighing the return from many studies searching for LBVs and WRs the past several decades. Monitoring from semesters 2011B-2012A already has confirmed one new cLBV as a bona fide LBV. We propose to continue optical-IR photometric monitoring of these cLBVS with the 1.3m. Chiron, replacing the RC spectrograph on the 1.5m, now allows high-resolution optical spectroscopic monitoring of bright cLBVs, 11 of which are proposed herein. Spectra are important for understanding the physics driving photometric variability, properties of the wind, and allow analysis of line profiles.

Power Spectral Density Error Analysis of Spectral Subtraction Type of Speech Enhancement Methods

NASA Astrophysics Data System (ADS)

Händel, Peter

2006-12-01

A theoretical framework for analysis of speech enhancement algorithms is introduced for performance assessment of spectral subtraction type of methods. The quality of the enhanced speech is related to physical quantities of the speech and noise (such as stationarity time and spectral flatness), as well as to design variables of the noise suppressor. The derived theoretical results are compared with the outcome of subjective listening tests as well as successful design strategies, performed by independent research groups.

[Analysis of software for identifying spectral line of laser-induced breakdown spectroscopy based on LabVIEW].

PubMed

Hu, Zhi-yu; Zhang, Lei; Ma, Wei-guang; Yan, Xiao-juan; Li, Zhi-xin; Zhang, Yong-zhi; Wang, Le; Dong, Lei; Yin, Wang-bao; Jia, Suo-tang

2012-03-01

Self-designed identifying software for LIBS spectral line was introduced. Being integrated with LabVIEW, the soft ware can smooth spectral lines and pick peaks. The second difference and threshold methods were employed. Characteristic spectrum of several elements matches the NIST database, and realizes automatic spectral line identification and qualitative analysis of the basic composition of sample. This software can analyze spectrum handily and rapidly. It will be a useful tool for LIBS.

Cardiovascular response to acute stress in freely moving rats: time-frequency analysis.

PubMed

Loncar-Turukalo, Tatjana; Bajic, Dragana; Japundzic-Zigon, Nina

2008-01-01

Spectral analysis of cardiovascular series is an important tool for assessing the features of the autonomic control of the cardiovascular system. In this experiment Wistar rats ecquiped with intraarterial catheter for blood pressure (BP) recording were exposed to stress induced by blowing air. The problem of non stationary data was overcomed applying the Smoothed Pseudo Wigner Villle (SPWV) time-frequency distribution. Spectral analysis was done before stress, during stress, immediately after stress and later in recovery. The spectral indices were calculated for both systolic blood pressure (SBP) and pulse interval (PI) series. The time evolution of spectral indices showed perturbed sympathovagal balance.

Spectral BRDF-based determination of proper measurement geometries to characterize color shift of special effect coatings.

PubMed

Ferrero, Alejandro; Rabal, Ana; Campos, Joaquín; Martínez-Verdú, Francisco; Chorro, Elísabet; Perales, Esther; Pons, Alicia; Hernanz, María Luisa

2013-02-01

A reduced set of measurement geometries allows the spectral reflectance of special effect coatings to be predicted for any other geometry. A physical model based on flake-related parameters has been used to determine nonredundant measurement geometries for the complete description of the spectral bidirectional reflectance distribution function (BRDF). The analysis of experimental spectral BRDF was carried out by means of principal component analysis. From this analysis, a set of nine measurement geometries was proposed to characterize special effect coatings. It was shown that, for two different special effect coatings, these geometries provide a good prediction of their complete color shift.

Methods for spectral image analysis by exploiting spatial simplicity

DOEpatents

Keenan, Michael R.

2010-05-25

Several full-spectrum imaging techniques have been introduced in recent years that promise to provide rapid and comprehensive chemical characterization of complex samples. One of the remaining obstacles to adopting these techniques for routine use is the difficulty of reducing the vast quantities of raw spectral data to meaningful chemical information. Multivariate factor analysis techniques, such as Principal Component Analysis and Alternating Least Squares-based Multivariate Curve Resolution, have proven effective for extracting the essential chemical information from high dimensional spectral image data sets into a limited number of components that describe the spectral characteristics and spatial distributions of the chemical species comprising the sample. There are many cases, however, in which those constraints are not effective and where alternative approaches may provide new analytical insights. For many cases of practical importance, imaged samples are "simple" in the sense that they consist of relatively discrete chemical phases. That is, at any given location, only one or a few of the chemical species comprising the entire sample have non-zero concentrations. The methods of spectral image analysis of the present invention exploit this simplicity in the spatial domain to make the resulting factor models more realistic. Therefore, more physically accurate and interpretable spectral and abundance components can be extracted from spectral images that have spatially simple structure.

Methods for spectral image analysis by exploiting spatial simplicity

DOEpatents

Keenan, Michael R.

2010-11-23

Several full-spectrum imaging techniques have been introduced in recent years that promise to provide rapid and comprehensive chemical characterization of complex samples. One of the remaining obstacles to adopting these techniques for routine use is the difficulty of reducing the vast quantities of raw spectral data to meaningful chemical information. Multivariate factor analysis techniques, such as Principal Component Analysis and Alternating Least Squares-based Multivariate Curve Resolution, have proven effective for extracting the essential chemical information from high dimensional spectral image data sets into a limited number of components that describe the spectral characteristics and spatial distributions of the chemical species comprising the sample. There are many cases, however, in which those constraints are not effective and where alternative approaches may provide new analytical insights. For many cases of practical importance, imaged samples are "simple" in the sense that they consist of relatively discrete chemical phases. That is, at any given location, only one or a few of the chemical species comprising the entire sample have non-zero concentrations. The methods of spectral image analysis of the present invention exploit this simplicity in the spatial domain to make the resulting factor models more realistic. Therefore, more physically accurate and interpretable spectral and abundance components can be extracted from spectral images that have spatially simple structure.

Spectral Electroencephalogram Analysis for the Evaluation of Encephalopathy Grade in Children With Acute Liver Failure.

PubMed

Press, Craig A; Morgan, Lindsey; Mills, Michele; Stack, Cynthia V; Goldstein, Joshua L; Alonso, Estella M; Wainwright, Mark S

2017-01-01

Spectral electroencephalogram analysis is a method for automated analysis of electroencephalogram patterns, which can be performed at the bedside. We sought to determine the utility of spectral electroencephalogram for grading hepatic encephalopathy in children with acute liver failure. Retrospective cohort study. Tertiary care pediatric hospital. Patients between 0 and 18 years old who presented with acute liver failure and were admitted to the PICU. None. Electroencephalograms were analyzed by spectral analysis including total power, relative δ, relative θ, relative α, relative β, θ-to-Δ ratio, and α-to-Δ ratio. Normal values and ranges were first derived using normal electroencephalograms from 70 children of 0-18 years old. Age had a significant effect on each variable measured (p < 0.03). Electroencephalograms from 33 patients with acute liver failure were available for spectral analysis. The median age was 4.3 years, 14 of 33 were male, and the majority had an indeterminate etiology of acute liver failure. Neuroimaging was performed in 26 cases and was normal in 20 cases (77%). The majority (64%) survived, and 82% had a good outcome with a score of 1-3 on the Pediatric Glasgow Outcome Scale-Extended at the time of discharge. Hepatic encephalopathy grade correlated with the qualitative visual electroencephalogram scores assigned by blinded neurophysiologists (rs = 0.493; p < 0.006). Spectral electroencephalogram characteristics varied significantly with the qualitative electroencephalogram classification (p < 0.05). Spectral electroencephalogram variables including relative Δ, relative θ, relative α, θ-to-Δ ratio, and α-to-Δ ratio all significantly varied with the qualitative electroencephalogram (p < 0.025). Moderate to severe hepatic encephalopathy was correlated with a total power of less than or equal to 50% of normal for children 0-3 years old, and with a relative θ of less than or equal to 50% normal for children more than 3 years old (p > 0.05). Spectral electroencephalogram classification correlated with outcome (p < 0.05). Spectral electroencephalogram analysis can be used to evaluate even young patients for hepatic encephalopathy and correlates with outcome. Spectral electroencephalogram may allow improved quantitative and reproducible assessment of hepatic encephalopathy grade in children with acute liver failure.

Hyperspectral observation of anthropogenic and biogenic pollution in coastal zone

NASA Astrophysics Data System (ADS)

Lavrova, Olga; Loupian, Evgeny; Mityagina, Marina; Uvarov, Ivan

The work presents results of anthropogenic and biogenic pollution detection in coastal zones of the Black and Caspian Seas based on satellite hyperspetral data provided by the Hyperion and HICO instruments. Techniques developed on the basis of the analysis of spectral characteristics calculated in special points were employed to address the following problems: (a) assessment of the blooming intensity of cyanobacteria and their distribution in bays of western Crimea and discrimination between anthropogenic pollutant discharge events and algae bloom; (b) detection of anthropogenic pollution in Crimean lakes utilized as industrial liquid discharge reservoirs; (c) detection of oil pollution in areas of shelf oil production in the Caspian Sea. Information values of different spectral bands and their composites were estimated in connection with the retrieval of the main sea water components: phytoplankton, suspended matter and colored organic matter, and also various anthropogenic pollutants, including oil. Software tools for thematic hyperspectral data processing in application to the investigation of sea coastal zones and internal water bodies were developed on the basis of the See the Sea geoportal created by the Space Research Institute RAS. The geoportal is focused on the study of processes in the world ocean with the emphasis on the advantages of satellite systems of observation. The tools that were introduced into the portal allow joint analysis of quasi-simultaneous satellite data, in particular data from the Hyperion, HICO, OLI Landsat-8, ETM Landsat-7 and TM Landsat-5 instruments. Results of analysis attempts combining data from different sensors are discussed. Their strong and weak points are highlighted. The study was completed with partial financial support from The Russian Foundation for Basic Research grants # 14-05-00520-a and 13-07-12017.

HEAO-1 analysis of Low Energy Detectors (LED)

NASA Technical Reports Server (NTRS)

Nousek, John A.

1992-01-01

The activities at Penn State University are described. During the period Oct. 1990 to Dec. 1991 work on HEAO-1 analysis of the Low Energy Detectors (LED) concentrated on using the improved detector spectral simulation model and fitting diffuse x-ray background spectral data. Spectral fitting results, x-ray point sources, and diffuse x-ray sources are described.

Solar Spectral Irradiance and Climate

NASA Technical Reports Server (NTRS)

Pilewskie, P.; Woods, T.; Cahalan, R.

2012-01-01

Spectrally resolved solar irradiance is recognized as being increasingly important to improving our understanding of the manner in which the Sun influences climate. There is strong empirical evidence linking total solar irradiance to surface temperature trends - even though the Sun has likely made only a small contribution to the last half-century's global temperature anomaly - but the amplitudes cannot be explained by direct solar heating alone. The wavelength and height dependence of solar radiation deposition, for example, ozone absorption in the stratosphere, absorption in the ocean mixed layer, and water vapor absorption in the lower troposphere, contribute to the "top-down" and "bottom-up" mechanisms that have been proposed as possible amplifiers of the solar signal. New observations and models of solar spectral irradiance are needed to study these processes and to quantify their impacts on climate. Some of the most recent observations of solar spectral variability from the mid-ultraviolet to the near-infrared have revealed some unexpected behavior that was not anticipated prior to their measurement, based on an understanding from model reconstructions. The atmospheric response to the observed spectral variability, as quantified in climate model simulations, have revealed similarly surprising and in some cases, conflicting results. This talk will provide an overview on the state of our understanding of the spectrally resolved solar irradiance, its variability over many time scales, potential climate impacts, and finally, a discussion on what is required for improving our understanding of Sun-climate connections, including a look forward to future observations.

Vesta's UV Lightcurve: Hemispheric Variation in Brightness and Spectral Reversal

NASA Technical Reports Server (NTRS)

Hendrix, Amanda R.; Vilas, Faith; Festou, Michael

2003-01-01

Spectra of asteroid 4 Vesta obtained in October 1990 with the International Ultraviolet Explorer are reanalyzed and reinterpreted. A large portion of the eastern hemisphere (based on the prime meridian definition of Thomas et al., 1997a) is darker at UV Wavelengths than much of the western hemisphere. The UV lightcurve is in contrast with the visible lightcurve, which shows that the eastern hemisphere is brighter than the western. These IUE spectra of Vesta thus may be evidence for the "spectral reversal." first seen on the Moon by Apollo 17. where the visibly brighter lunar highlands are darker than the maria at far-UV wavelengths. This effect was linked to space weathering when it was noted (Wagner et al., 1987) that the spectral reversal appears in the laboratory spectra of lunar soils but not powdered lunar rocks. We investigate Vesta's UV lightcurve and spectral reversal, and its possible connection with space weathering. The addition to grain coatings of small amounts of submicroscopic iron (SMFe) through vapor deposition causes drastic spectral changes at UV-visible wavelengths (Hapke, 2001). while the longer wavelength spectrum remains largely unaffected. Other laboratory results (e.g., Hiroi and Pieters, 1998) indicate that the UV-visible wavelength range is affected by simulated weathering processes in a manner similar to what is seen on Vesta. It is likely that Vesta has experienced relatively minor amounts of space weathering, as indicated by the spectral reversal, along with the subtle visible-near infrared weathering effects (e.g., Binzel et al., 1997).

Single-hole spectral function and spin-charge separation in the t-J model

NASA Astrophysics Data System (ADS)

Mishchenko, A. S.; Prokof'ev, N. V.; Svistunov, B. V.

2001-07-01

Worm algorithm Monte Carlo simulations of the hole Green function with subsequent spectral analysis were performed for 0.1<=J/t<=0.4 on lattices with up to L×L=32×32 sites at a temperature as low as T=J/40, and present, apparently, the hole spectral function in the thermodynamic limit. Spectral analysis reveals a δ-function-sharp quasiparticle peak at the lower edge of the spectrum that is incompatible with the power-law singularity and thus rules out the possibility of spin-charge separation in this parameter range. Spectral continuum features two peaks separated by a gap ~4÷5 t.

Anisotropy of band gap absorption in TlGaSe2 semiconductor by ferroelectric phase transformation

NASA Astrophysics Data System (ADS)

Gulbinas, Karolis; Grivickas, Vytautas; Gavryushin, Vladimir

2014-12-01

The depth-resolved free-carrier absorption and the photo-acoustic response are used to examine the band-gap absorption in 2D-TlGaSe2 layered semiconductor after its transformation into the ferroelectric F-phase below 107 K. The absorption exhibits unusual behavior with a biaxial character in respect to the light polarization on the layer plane. A spectral analysis shows that the anisotropy is associated to the lowest Γ-direct optical transition. The Γ-absorption and the localized exciton at 2.11 eV are dipole-prohibited or partially allowed in two nearly perpendicular polarization directions. The shift of anisotropy axis in respect to crystallographic a- and b-directions demonstrates the non-equivalent zigzag rearrangement of the interlayer connecting Tl+ ions, which is responsible for occurrence of the F-phase.

Complexity and dynamics of topological and community structure in complex networks

NASA Astrophysics Data System (ADS)

Berec, Vesna

2017-07-01

Complexity is highly susceptible to variations in the network dynamics, reflected on its underlying architecture where topological organization of cohesive subsets into clusters, system's modular structure and resulting hierarchical patterns, are cross-linked with functional dynamics of the system. Here we study connection between hierarchical topological scales of the simplicial complexes and the organization of functional clusters - communities in complex networks. The analysis reveals the full dynamics of different combinatorial structures of q-th-dimensional simplicial complexes and their Laplacian spectra, presenting spectral properties of resulting symmetric and positive semidefinite matrices. The emergence of system's collective behavior from inhomogeneous statistical distribution is induced by hierarchically ordered topological structure, which is mapped to simplicial complex where local interactions between the nodes clustered into subcomplexes generate flow of information that characterizes complexity and dynamics of the full system.

Compact full-motion video hyperspectral cameras: development, image processing, and applications

NASA Astrophysics Data System (ADS)

Kanaev, A. V.

2015-10-01

Emergence of spectral pixel-level color filters has enabled development of hyper-spectral Full Motion Video (FMV) sensors operating in visible (EO) and infrared (IR) wavelengths. The new class of hyper-spectral cameras opens broad possibilities of its utilization for military and industry purposes. Indeed, such cameras are able to classify materials as well as detect and track spectral signatures continuously in real time while simultaneously providing an operator the benefit of enhanced-discrimination-color video. Supporting these extensive capabilities requires significant computational processing of the collected spectral data. In general, two processing streams are envisioned for mosaic array cameras. The first is spectral computation that provides essential spectral content analysis e.g. detection or classification. The second is presentation of the video to an operator that can offer the best display of the content depending on the performed task e.g. providing spatial resolution enhancement or color coding of the spectral analysis. These processing streams can be executed in parallel or they can utilize each other's results. The spectral analysis algorithms have been developed extensively, however demosaicking of more than three equally-sampled spectral bands has been explored scarcely. We present unique approach to demosaicking based on multi-band super-resolution and show the trade-off between spatial resolution and spectral content. Using imagery collected with developed 9-band SWIR camera we demonstrate several of its concepts of operation including detection and tracking. We also compare the demosaicking results to the results of multi-frame super-resolution as well as to the combined multi-frame and multiband processing.

Spectral identification of melon seeds variety based on k-nearest neighbor and Fisher discriminant analysis

NASA Astrophysics Data System (ADS)

Li, Cuiling; Jiang, Kai; Zhao, Xueguan; Fan, Pengfei; Wang, Xiu; Liu, Chuan

2017-10-01

Impurity of melon seeds variety will cause reductions of melon production and economic benefits of farmers, this research aimed to adopt spectral technology combined with chemometrics methods to identify melon seeds variety. Melon seeds whose varieties were "Yi Te Bai", "Yi Te Jin", "Jing Mi NO.7", "Jing Mi NO.11" and " Yi Li Sha Bai "were used as research samples. A simple spectral system was developed to collect reflective spectral data of melon seeds, including a light source unit, a spectral data acquisition unit and a data processing unit, the detection wavelength range of this system was 200-1100nm with spectral resolution of 0.14 7.7nm. The original reflective spectral data was pre-treated with de-trend (DT), multiple scattering correction (MSC), first derivative (FD), normalization (NOR) and Savitzky-Golay (SG) convolution smoothing methods. Principal Component Analysis (PCA) method was adopted to reduce the dimensions of reflective spectral data and extract principal components. K-nearest neighbour (KNN) and Fisher discriminant analysis (FDA) methods were used to develop discriminant models of melon seeds variety based on PCA. Spectral data pretreatments improved the discriminant effects of KNN and FDA, FDA generated better discriminant results than KNN, both KNN and FDA methods produced discriminant accuracies reaching to 90.0% for validation set. Research results showed that using spectral technology in combination with KNN and FDA modelling methods to identify melon seeds variety was feasible.

Examination of Spectral Transformations on Spectral Mixture Analysis

NASA Astrophysics Data System (ADS)

Deng, Y.; Wu, C.

2018-04-01

While many spectral transformation techniques have been applied on spectral mixture analysis (SMA), few study examined their necessity and applicability. This paper focused on exploring the difference between spectrally transformed schemes and untransformed scheme to find out which transformed scheme performed better in SMA. In particular, nine spectrally transformed schemes as well as untransformed scheme were examined in two study areas. Each transformed scheme was tested 100 times using different endmember classes' spectra under the endmember model of vegetation- high albedo impervious surface area-low albedo impervious surface area-soil (V-ISAh-ISAl-S). Performance of each scheme was assessed based on mean absolute error (MAE). Statistical analysis technique, Paired-Samples T test, was applied to test the significance of mean MAEs' difference between transformed and untransformed schemes. Results demonstrated that only NSMA could exceed the untransformed scheme in all study areas. Some transformed schemes showed unstable performance since they outperformed the untransformed scheme in one area but weakened the SMA result in another region.

Quantitative Doppler Analysis Using Conventional Color Flow Imaging Acquisitions.

PubMed

Karabiyik, Yucel; Ekroll, Ingvild Kinn; Eik-Nes, Sturla H; Lovstakken, Lasse

2018-05-01

Interleaved acquisitions used in conventional triplex mode result in a tradeoff between the frame rate and the quality of velocity estimates. On the other hand, workflow becomes inefficient when the user has to switch between different modes, and measurement variability is increased. This paper investigates the use of power spectral Capon estimator in quantitative Doppler analysis using data acquired with conventional color flow imaging (CFI) schemes. To preserve the number of samples used for velocity estimation, only spatial averaging was utilized, and clutter rejection was performed after spectral estimation. The resulting velocity spectra were evaluated in terms of spectral width using a recently proposed spectral envelope estimator. The spectral envelopes were also used for Doppler index calculations using in vivo and string phantom acquisitions. In vivo results demonstrated that the Capon estimator can provide spectral estimates with sufficient quality for quantitative analysis using packet-based CFI acquisitions. The calculated Doppler indices were similar to the values calculated using spectrograms estimated on a commercial ultrasound scanner.

Potential of FTIR spectroscopy for analysis of tears for diagnosis purposes.

PubMed

Travo, Adrian; Paya, Clément; Déléris, Gérard; Colin, Joseph; Mortemousque, Bruno; Forfar, Isabelle

2014-04-01

It has been widely reported that the tear film, which is crucially important as a protective barrier of the eye, undergoes biochemical changes as a result of a wide range of ocular pathology. This tends to suggest the possibility of early detection of ocular diseases on the basis of biochemical analysis of tears. However, studies of tears by conventional methods of biomolecular and biochemical analysis are often limited by methodological difficulties. Moreover, such analysis could not be applied in the clinic, where structural and morphological analyses by, mainly, slit-lamp biomicroscopy remains the recommended method. In this study, we assessed, for the first time, the potential of FTIR spectroscopy combined with advanced chemometric processing of spectral data for analysis of raw tears for diagnosis purposes. We first optimized sampling and spectral acquisition (tears collection method, tear sample volume, and preservation of the samples) for accurate spectral measurement. On the basis of the results, we focused our study on the possibility of discriminating tears from normal individuals from those of patients with different ocular pathologies, and showed that the most discriminating spectral range is that corresponding to variations of CH2 and CH3 of lipid aliphatic chains. We also report more subtle discrimination of tears from patients with keratoconus and those from patients with non-specific inflammatory ocular diseases, on the basis of variations in spectral ranges attributed notably to lipid and carbohydrate vibrations. Finally, we also succeeded in distinguishing tears from patients with early-stage and late-stage keratoconus on the basis of spectral features attributed to protein structure. Therefore, this study strongly suggests that FTIR spectral analysis of tears could be developed as a valuable and cost-saving tool for biochemical-based detection of ocular diseases, potentially before the appearance of the first morphological signs of diseases. Combined with supervised modelling methods and with use of a spectral data base acquired for representative patients, such a spectral approach could be a useful addition to current methods of clinical analysis for improvement of patient care.

Sleep Neurophysiological Dynamics Through the Lens of Multitaper Spectral Analysis

PubMed Central

Prerau, Michael J.; Brown, Ritchie E.; Bianchi, Matt T.; Ellenbogen, Jeffrey M.; Purdon, Patrick L.

2016-01-01

During sleep, cortical and subcortical structures within the brain engage in highly structured oscillatory dynamics that can be observed in the electroencephalogram (EEG). The ability to accurately describe changes in sleep state from these oscillations has thus been a major goal of sleep medicine. While numerous studies over the past 50 years have shown sleep to be a continuous, multifocal, dynamic process, long-standing clinical practice categorizes sleep EEG into discrete stages through visual inspection of 30-s epochs. By representing sleep as a coarsely discretized progression of stages, vital neurophysiological information on the dynamic interplay between sleep and arousal is lost. However, by using principled time-frequency spectral analysis methods, the rich dynamics of the sleep EEG are immediately visible—elegantly depicted and quantified at time scales ranging from a full night down to individual microevents. In this paper, we review the neurophysiology of sleep through this lens of dynamic spectral analysis. We begin by reviewing spectral estimation techniques traditionally used in sleep EEG analysis and introduce multitaper spectral analysis, a method that makes EEG spectral estimates clearer and more accurate than traditional approaches. Through the lens of the multitaper spectrogram, we review the oscillations and mechanisms underlying the traditional sleep stages. In doing so, we will demonstrate how multitaper spectral analysis makes the oscillatory structure of traditional sleep states instantaneously visible, closely paralleling the traditional hypnogram, but with a richness of information that suggests novel insights into the neural mechanisms of sleep, as well as novel clinical and research applications. PMID:27927806

Vibrations Detection in Industrial Pumps Based on Spectral Analysis to Increase Their Efficiency

NASA Astrophysics Data System (ADS)

Rachid, Belhadef; Hafaifa, Ahmed; Boumehraz, Mohamed

2016-03-01

Spectral analysis is the key tool for the study of vibration signals in rotating machinery. In this work, the vibration analysis applied for conditional preventive maintenance of such machines is proposed, as part of resolved problems related to vibration detection on the organs of these machines. The vibration signal of a centrifugal pump was treated to mount the benefits of the approach proposed. The obtained results present the signal estimation of a pump vibration using Fourier transform technique compared by the spectral analysis methods based on Prony approach.

Acoustic emission spectral analysis of fiber composite failure mechanisms

NASA Technical Reports Server (NTRS)

Egan, D. M.; Williams, J. H., Jr.

1978-01-01

The acoustic emission of graphite fiber polyimide composite failure mechanisms was investigated with emphasis on frequency spectrum analysis. Although visual examination of spectral densities could not distinguish among fracture sources, a paired-sample t statistical analysis of mean normalized spectral densities did provide quantitative discrimination among acoustic emissions from 10 deg, 90 deg, and plus or minus 45 deg, plus or minus 45 deg sub s specimens. Comparable discrimination was not obtained for 0 deg specimens.

Spectral and correlation analysis with applications to middle-atmosphere radars

NASA Technical Reports Server (NTRS)

Rastogi, Prabhat K.

1989-01-01

The correlation and spectral analysis methods for uniformly sampled stationary random signals, estimation of their spectral moments, and problems arising due to nonstationary are reviewed. Some of these methods are already in routine use in atmospheric radar experiments. Other methods based on the maximum entropy principle and time series models have been used in analyzing data, but are just beginning to receive attention in the analysis of radar signals. These methods are also briefly discussed.

Spectral signature verification using statistical analysis and text mining

NASA Astrophysics Data System (ADS)

DeCoster, Mallory E.; Firpi, Alexe H.; Jacobs, Samantha K.; Cone, Shelli R.; Tzeng, Nigel H.; Rodriguez, Benjamin M.

2016-05-01

In the spectral science community, numerous spectral signatures are stored in databases representative of many sample materials collected from a variety of spectrometers and spectroscopists. Due to the variety and variability of the spectra that comprise many spectral databases, it is necessary to establish a metric for validating the quality of spectral signatures. This has been an area of great discussion and debate in the spectral science community. This paper discusses a method that independently validates two different aspects of a spectral signature to arrive at a final qualitative assessment; the textual meta-data and numerical spectral data. Results associated with the spectral data stored in the Signature Database1 (SigDB) are proposed. The numerical data comprising a sample material's spectrum is validated based on statistical properties derived from an ideal population set. The quality of the test spectrum is ranked based on a spectral angle mapper (SAM) comparison to the mean spectrum derived from the population set. Additionally, the contextual data of a test spectrum is qualitatively analyzed using lexical analysis text mining. This technique analyzes to understand the syntax of the meta-data to provide local learning patterns and trends within the spectral data, indicative of the test spectrum's quality. Text mining applications have successfully been implemented for security2 (text encryption/decryption), biomedical3 , and marketing4 applications. The text mining lexical analysis algorithm is trained on the meta-data patterns of a subset of high and low quality spectra, in order to have a model to apply to the entire SigDB data set. The statistical and textual methods combine to assess the quality of a test spectrum existing in a database without the need of an expert user. This method has been compared to other validation methods accepted by the spectral science community, and has provided promising results when a baseline spectral signature is present for comparison. The spectral validation method proposed is described from a practical application and analytical perspective.

Statistical Analysis of Spectral Properties and Prosodic Parameters of Emotional Speech

NASA Astrophysics Data System (ADS)

Přibil, J.; Přibilová, A.

2009-01-01

The paper addresses reflection of microintonation and spectral properties in male and female acted emotional speech. Microintonation component of speech melody is analyzed regarding its spectral and statistical parameters. According to psychological research of emotional speech, different emotions are accompanied by different spectral noise. We control its amount by spectral flatness according to which the high frequency noise is mixed in voiced frames during cepstral speech synthesis. Our experiments are aimed at statistical analysis of cepstral coefficient values and ranges of spectral flatness in three emotions (joy, sadness, anger), and a neutral state for comparison. Calculated histograms of spectral flatness distribution are visually compared and modelled by Gamma probability distribution. Histograms of cepstral coefficient distribution are evaluated and compared using skewness and kurtosis. Achieved statistical results show good correlation comparing male and female voices for all emotional states portrayed by several Czech and Slovak professional actors.

Energy Finite Element Analysis Developments for Vibration Analysis of Composite Aircraft Structures

NASA Technical Reports Server (NTRS)

Vlahopoulos, Nickolas; Schiller, Noah H.

2011-01-01

The Energy Finite Element Analysis (EFEA) has been utilized successfully for modeling complex structural-acoustic systems with isotropic structural material properties. In this paper, a formulation for modeling structures made out of composite materials is presented. An approach based on spectral finite element analysis is utilized first for developing the equivalent material properties for the composite material. These equivalent properties are employed in the EFEA governing differential equations for representing the composite materials and deriving the element level matrices. The power transmission characteristics at connections between members made out of non-isotropic composite material are considered for deriving suitable power transmission coefficients at junctions of interconnected members. These coefficients are utilized for computing the joint matrix that is needed to assemble the global system of EFEA equations. The global system of EFEA equations is solved numerically and the vibration levels within the entire system can be computed. The new EFEA formulation for modeling composite laminate structures is validated through comparison to test data collected from a representative composite aircraft fuselage that is made out of a composite outer shell and composite frames and stiffeners. NASA Langley constructed the composite cylinder and conducted the test measurements utilized in this work.

Edge connectivity and the spectral gap of combinatorial and quantum graphs

NASA Astrophysics Data System (ADS)

Berkolaiko, Gregory; Kennedy, James B.; Kurasov, Pavel; Mugnolo, Delio

2017-09-01

We derive a number of upper and lower bounds for the first nontrivial eigenvalue of Laplacians on combinatorial and quantum graph in terms of the edge connectivity, i.e. the minimal number of edges which need to be removed to make the graph disconnected. On combinatorial graphs, one of the bounds corresponds to a well-known inequality of Fiedler, of which we give a new variational proof. On quantum graphs, the corresponding bound generalizes a recent result of Band and Lévy. All proofs are general enough to yield corresponding estimates for the p-Laplacian and allow us to identify the minimizers. Based on the Betti number of the graph, we also derive upper and lower bounds on all eigenvalues which are ‘asymptotically correct’, i.e. agree with the Weyl asymptotics for the eigenvalues of the quantum graph. In particular, the lower bounds improve the bounds of Friedlander on any given graph for all but finitely many eigenvalues, while the upper bounds improve recent results of Ariturk. Our estimates are also used to derive bounds on the eigenvalues of the normalized Laplacian matrix that improve known bounds of spectral graph theory.

Random Initialisation of the Spectral Variables: an Alternate Approach for Initiating Multivariate Curve Resolution Alternating Least Square (MCR-ALS) Analysis.

PubMed

Kumar, Keshav

2017-11-01

Multivariate curve resolution alternating least square (MCR-ALS) analysis is the most commonly used curve resolution technique. The MCR-ALS model is fitted using the alternate least square (ALS) algorithm that needs initialisation of either contribution profiles or spectral profiles of each of the factor. The contribution profiles can be initialised using the evolve factor analysis; however, in principle, this approach requires that data must belong to the sequential process. The initialisation of the spectral profiles are usually carried out using the pure variable approach such as SIMPLISMA algorithm, this approach demands that each factor must have the pure variables in the data sets. Despite these limitations, the existing approaches have been quite a successful for initiating the MCR-ALS analysis. However, the present work proposes an alternate approach for the initialisation of the spectral variables by generating the random variables in the limits spanned by the maxima and minima of each spectral variable of the data set. The proposed approach does not require that there must be pure variables for each component of the multicomponent system or the concentration direction must follow the sequential process. The proposed approach is successfully validated using the excitation-emission matrix fluorescence data sets acquired for certain fluorophores with significant spectral overlap. The calculated contribution and spectral profiles of these fluorophores are found to correlate well with the experimental results. In summary, the present work proposes an alternate way to initiate the MCR-ALS analysis.

Orientation dependence of temporal and spectral properties of high-order harmonics in solids [Orientation dependence of high-harmonic temporal and spectral properties in solids

DOE PAGES

Wu, Mengxi; You, Yongsing; Ghimire, Shambhu; ...

2017-12-18

We investigate the connection between crystal symmetry and temporal and spectral properties of high-order harmonics in solids. We calculate the orientation-dependent harmonic spectrum driven by an intense, linearly polarized infrared laser field, using a momentum-space description of the generation process in terms of strong-field-driven electron dynamics on the band structure. We show that the orientation dependence of both the spectral yield and the subcycle time profile of the harmonic radiation can be understood in terms of the coupling strengths and relative curvatures of the valence band and the low-lying conduction bands. In particular, we show that in some systems thismore » gives rise to a rapid shift of a quarter optical cycle in the timing of harmonics in the secondary plateau as the crystal is rotated relative to the laser polarization. Here, we address recent experimental results in MgO and show that the observed change in orientation dependence for the highest harmonics can be interpreted in the momentum space picture in terms of the contributions of several different conduction bands.« less

Orientation dependence of temporal and spectral properties of high-order harmonics in solids [Orientation dependence of high-harmonic temporal and spectral properties in solids

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

Wu, Mengxi; You, Yongsing; Ghimire, Shambhu

We investigate the connection between crystal symmetry and temporal and spectral properties of high-order harmonics in solids. We calculate the orientation-dependent harmonic spectrum driven by an intense, linearly polarized infrared laser field, using a momentum-space description of the generation process in terms of strong-field-driven electron dynamics on the band structure. We show that the orientation dependence of both the spectral yield and the subcycle time profile of the harmonic radiation can be understood in terms of the coupling strengths and relative curvatures of the valence band and the low-lying conduction bands. In particular, we show that in some systems thismore » gives rise to a rapid shift of a quarter optical cycle in the timing of harmonics in the secondary plateau as the crystal is rotated relative to the laser polarization. Here, we address recent experimental results in MgO and show that the observed change in orientation dependence for the highest harmonics can be interpreted in the momentum space picture in terms of the contributions of several different conduction bands.« less

Determining fast orientation changes of multi-spectral line cameras from the primary images

NASA Astrophysics Data System (ADS)

Wohlfeil, Jürgen

2012-01-01

Fast orientation changes of airborne and spaceborne line cameras cannot always be avoided. In such cases it is essential to measure them with high accuracy to ensure a good quality of the resulting imagery products. Several approaches exist to support the orientation measurement by using optical information received through the main objective/telescope. In this article an approach is proposed that allows the determination of non-systematic orientation changes between every captured line. It does not require any additional camera hardware or onboard processing capabilities but the payload images and a rough estimate of the camera's trajectory. The approach takes advantage of the typical geometry of multi-spectral line cameras with a set of linear sensor arrays for different spectral bands on the focal plane. First, homologous points are detected within the heavily distorted images of different spectral bands. With their help a connected network of geometrical correspondences can be built up. This network is used to calculate the orientation changes of the camera with the temporal and angular resolution of the camera. The approach was tested with an extensive set of aerial surveys covering a wide range of different conditions and achieved precise and reliable results.

High level white noise generator

DOEpatents

Borkowski, Casimer J.; Blalock, Theron V.

1979-01-01

A wide band, stable, random noise source with a high and well-defined output power spectral density is provided which may be used for accurate calibration of Johnson Noise Power Thermometers (JNPT) and other applications requiring a stable, wide band, well-defined noise power spectral density. The noise source is based on the fact that the open-circuit thermal noise voltage of a feedback resistor, connecting the output to the input of a special inverting amplifier, is available at the amplifier output from an equivalent low output impedance caused by the feedback mechanism. The noise power spectral density level at the noise source output is equivalent to the density of the open-circuit thermal noise or a 100 ohm resistor at a temperature of approximately 64,000 Kelvins. The noise source has an output power spectral density that is flat to within 0.1% (0.0043 db) in the frequency range of from 1 KHz to 100 KHz which brackets typical passbands of the signal-processing channels of JNPT's. Two embodiments, one of higher accuracy that is suitable for use as a standards instrument and another that is particularly adapted for ambient temperature operation, are illustrated in this application.

[NIR Assignment of Magnolol by 2D-COS Technology and Model Application Huoxiangzhengqi Oral Liduid].

PubMed

Pei, Yan-ling; Wu, Zhi-sheng; Shi, Xin-yuan; Pan, Xiao-ning; Peng, Yan-fang; Qiao, Yan-jiang

2015-08-01

Near infrared (NIR) spectroscopy assignment of Magnolol was performed using deuterated chloroform solvent and two-dimensional correlation spectroscopy (2D-COS) technology. According to the synchronous spectra of deuterated chloroform solvent and Magnolol, 1365~1455, 1600~1720, 2000~2181 and 2275~2465 nm were the characteristic absorption of Magnolol. Connected with the structure of Magnolol, 1440 nm was the stretching vibration of phenolic group O-H, 1679 nm was the stretching vibration of aryl and methyl which connected with aryl, 2117, 2304, 2339 and 2370 nm were the combination of the stretching vibration, bending vibration and deformation vibration for aryl C-H, 2445 nm were the bending vibration of methyl which linked with aryl group, these bands attribut to the characteristics of Magnolol. Huoxiangzhengqi Oral Liduid was adopted to study the Magnolol, the characteristic band by spectral assignment and the band by interval Partial Least Squares (iPLS) and Synergy interval Partial Least Squares (SiPLS) were used to establish Partial Least Squares (PLS) quantitative model, the coefficient of determination Rcal(2) and Rpre(2) were greater than 0.99, the Root Mean of Square Error of Calibration (RM-SEC), Root Mean of Square Error of Cross Validation (RMSECV) and Root Mean of Square Error of Prediction (RMSEP) were very small. It indicated that the characteristic band by spectral assignment has the same results with the Chemometrics in PLS model. It provided a reference for NIR spectral assignment of chemical compositions in Chinese Materia Medica, and the band filters of NIR were interpreted.

Waterbodies Extraction from LANDSAT8-OLI Imagery Using Awater Indexs-Guied Stochastic Fully-Connected Conditional Random Field Model and the Support Vector Machine

NASA Astrophysics Data System (ADS)

Wang, X.; Xu, L.

2018-04-01

One of the most important applications of remote sensing classification is water extraction. The water index (WI) based on Landsat images is one of the most common ways to distinguish water bodies from other land surface features. But conventional WI methods take into account spectral information only form a limited number of bands, and therefore the accuracy of those WI methods may be constrained in some areas which are covered with snow/ice, clouds, etc. An accurate and robust water extraction method is the key to the study at present. The support vector machine (SVM) using all bands spectral information can reduce for these classification error to some extent. Nevertheless, SVM which barely considers spatial information is relatively sensitive to noise in local regions. Conditional random field (CRF) which considers both spatial information and spectral information has proven to be able to compensate for these limitations. Hence, in this paper, we develop a systematic water extraction method by taking advantage of the complementarity between the SVM and a water index-guided stochastic fully-connected conditional random field (SVM-WIGSFCRF) to address the above issues. In addition, we comprehensively evaluate the reliability and accuracy of the proposed method using Landsat-8 operational land imager (OLI) images of one test site. We assess the method's performance by calculating the following accuracy metrics: Omission Errors (OE) and Commission Errors (CE); Kappa coefficient (KP) and Total Error (TE). Experimental results show that the new method can improve target detection accuracy under complex and changeable environments.

Fast Fourier Transform Spectral Analysis Program

NASA Technical Reports Server (NTRS)

Daniel, J. A., Jr.; Graves, M. L.; Hovey, N. M.

1969-01-01

Fast Fourier Transform Spectral Analysis Program is used in frequency spectrum analysis of postflight, space vehicle telemetered trajectory data. This computer program with a digital algorithm can calculate power spectrum rms amplitudes and cross spectrum of sampled parameters at even time increments.

Methods Development for Spectral Simplification of Room-Temperature Rotational Spectra

NASA Astrophysics Data System (ADS)

Kent, Erin B.; Shipman, Steven

2014-06-01

Room-temperature rotational spectra are dense and difficult to assign, and so we have been working to develop methods to accelerate this process. We have tested two different methods with our waveguide-based spectrometer, which operates from 8.7 to 26.5 GHz. The first method, based on previous work by Medvedev and De Lucia, was used to estimate lower state energies of transitions by performing relative intensity measurements at a range of temperatures between -20 and +50 °C. The second method employed hundreds of microwave-microwave double resonance measurements to determine level connectivity between rotational transitions. The relative intensity measurements were not particularly successful in this frequency range (the reasons for this will be discussed), but the information gleaned from the double-resonance measurements can be incorporated into other spectral search algorithms (such as autofit or genetic algorithm approaches) via scoring or penalty functions to help with the spectral assignment process. I.R. Medvedev, F.C. De Lucia, Astrophys. J. 656, 621-628 (2007).

Interactive Spectral Analysis and Computation (ISAAC)

NASA Technical Reports Server (NTRS)

Lytle, D. M.

1992-01-01

Isaac is a task in the NSO external package for IRAF. A descendant of a FORTRAN program written to analyze data from a Fourier transform spectrometer, the current implementation has been generalized sufficiently to make it useful for general spectral analysis and other one dimensional data analysis tasks. The user interface for Isaac is implemented as an interpreted mini-language containing a powerful, programmable vector calculator. Built-in commands provide much of the functionality needed to produce accurate line lists from input spectra. These built-in functions include automated spectral line finding, least squares fitting of Voigt profiles to spectral lines including equality constraints, various filters including an optimal filter construction tool, continuum fitting, and various I/O functions.

Program Package for the Analysis of High Resolution High Signal-To-Noise Stellar Spectra

NASA Astrophysics Data System (ADS)

Piskunov, N.; Ryabchikova, T.; Pakhomov, Yu.; Sitnova, T.; Alekseeva, S.; Mashonkina, L.; Nordlander, T.

2017-06-01

The program package SME (Spectroscopy Made Easy), designed to perform an analysis of stellar spectra using spectral fitting techniques, was updated due to adding new functions (isotopic and hyperfine splittins) in VALD and including grids of NLTE calculations for energy levels of few chemical elements. SME allows to derive automatically stellar atmospheric parameters: effective temperature, surface gravity, chemical abundances, radial and rotational velocities, turbulent velocities, taking into account all the effects defining spectral line formation. SME package uses the best grids of stellar atmospheres that allows us to perform spectral analysis with the similar accuracy in wide range of stellar parameters and metallicities - from dwarfs to giants of BAFGK spectral classes.

Signature extraction of ocean pollutants by eigenvector transformation of remote spectra

NASA Technical Reports Server (NTRS)

Grew, G. W.

1978-01-01

Spectral signatures of suspended matter in the ocean are being extracted through characteristic vector analysis of remote ocean color data collected with MOCS (Multichannel Ocean Color Sensor). Spectral signatures appear to be obtainable through analyses of 'linear' clusters that appear on scatter diagrams associated with eigenvectors. Signatures associated with acid waste, sewage sludge, oil, and algae are presented. The application of vector analysis to two acid waste dumps overflown two years apart is examined in some detail. The relationships between eigenvectors and spectral signatures for these examples are analyzed. These cases demonstrate the value of characteristic vector analysis in remotely identifying pollutants in the ocean and in determining the consistency of their spectral signatures.

Deeper H.E.S.S. observations of Vela Junior (RX J0852.0-4622): Morphology studies and resolved spectroscopy

NASA Astrophysics Data System (ADS)

H.E.S.S. Collaboration; Abdalla, H.; Abramowski, A.; Aharonian, F.; Ait Benkhali, F.; Akhperjanian, A. G.; Angüner, E. O.; Arakawa, M.; Arrieta, M.; Aubert, P.; Backes, M.; Balzer, A.; Barnard, M.; Becherini, Y.; Becker Tjus, J.; Berge, D.; Bernhard, S.; Bernlöhr, K.; Blackwell, R.; Böttcher, M.; Boisson, C.; Bolmont, J.; Bordas, P.; Bregeon, J.; Brun, F.; Brun, P.; Bryan, M.; Büchele, M.; Bulik, T.; Capasso, M.; Carr, J.; Casanova, S.; Cerruti, M.; Chakraborty, N.; Chalme-Calvet, R.; Chaves, R. C. G.; Chen, A.; Chevalier, J.; Chrétien, M.; Coffaro, M.; Colafrancesco, S.; Cologna, G.; Condon, B.; Conrad, J.; Cui, Y.; Davids, I. D.; Decock, J.; Degrange, B.; Deil, C.; Devin, J.; deWilt, P.; Dirson, L.; Djannati-Ataï, A.; Domainko, W.; Donath, A.; Drury, L. O.'C.; Dutson, K.; Dyks, J.; Edwards, T.; Egberts, K.; Eger, P.; Ernenwein, J.-P.; Eschbach, S.; Farnier, C.; Fegan, S.; Fernandes, M. V.; Fiasson, A.; Fontaine, G.; Förster, A.; Funk, S.; Füßling, M.; Gabici, S.; Gajdus, M.; Gallant, Y. A.; Garrigoux, T.; Giavitto, G.; Giebels, B.; Glicenstein, J. F.; Gottschall, D.; Goyal, A.; Grondin, M.-H.; Hahn, J.; Haupt, M.; Hawkes, J.; Heinzelmann, G.; Henri, G.; Hermann, G.; Hervet, O.; Hinton, J. A.; Hofmann, W.; Hoischen, C.; Holler, M.; Horns, D.; Ivascenko, A.; Iwasaki, H.; Jacholkowska, A.; Jamrozy, M.; Janiak, M.; Jankowsky, D.; Jankowsky, F.; Jingo, M.; Jogler, T.; Jouvin, L.; Jung-Richardt, I.; Kastendieck, M. A.; Katarzyński, K.; Katsuragawa, M.; Katz, U.; Kerszberg, D.; Khangulyan, D.; Khélifi, B.; Kieffer, M.; King, J.; Klepser, S.; Klochkov, D.; Kluźniak, W.; Kolitzus, D.; Komin, Nu.; Krakau, S.; Kraus, M.; Krüger, P. P.; Laffon, H.; Lamanna, G.; Lau, J.; Lees, J.-P.; Lefaucheur, J.; Lefranc, V.; Lemière, A.; Lemoine-Goumard, M.; Lenain, J.-P.; Leser, E.; Lohse, T.; Lorentz, M.; Liu, R.; López-Coto, R.; Lypova, I.; Marandon, V.; Marcowith, A.; Mariaud, C.; Marx, R.; Maurin, G.; Maxted, N.; Mayer, M.; Meintjes, P. J.; Meyer, M.; Mitchell, A. M. W.; Moderski, R.; Mohamed, M.; Mohrmann, L.; Morå, K.; Moulin, E.; Murach, T.; Nakashima, S.; de Naurois, M.; Niederwanger, F.; Niemiec, J.; Oakes, L.; O'Brien, P.; Odaka, H.; Öttl, S.; Ohm, S.; Ostrowski, M.; Oya, I.; Padovani, M.; Panter, M.; Parsons, R. D.; Paz Arribas, M.; Pekeur, N. W.; Pelletier, G.; Perennes, C.; Petrucci, P.-O.; Peyaud, B.; Piel, Q.; Pita, S.; Poon, H.; Prokhorov, D.; Prokoph, H.; Pühlhofer, G.; Punch, M.; Quirrenbach, A.; Raab, S.; Reimer, A.; Reimer, O.; Renaud, M.; de los Reyes, R.; Richter, S.; Rieger, F.; Romoli, C.; Rowell, G.; Rudak, B.; Rulten, C. B.; Sahakian, V.; Saito, S.; Salek, D.; Sanchez, D. A.; Santangelo, A.; Sasaki, M.; Schlickeiser, R.; Schüssler, F.; Schulz, A.; Schwanke, U.; Schwemmer, S.; Seglar-Arroyo, M.; Settimo, M.; Seyffert, A. S.; Shafi, N.; Shilon, I.; Simoni, R.; Sol, H.; Spanier, F.; Spengler, G.; Spies, F.; Stawarz, Ł.; Steenkamp, R.; Stegmann, C.; Stycz, K.; Sushch, I.; Takahashi, T.; Tavernet, J.-P.; Tavernier, T.; Taylor, A. M.; Terrier, R.; Tibaldo, L.; Tiziani, D.; Tluczykont, M.; Trichard, C.; Tsuji, N.; Tuffs, R.; Uchiyama, Y.; van der Walt, D. J.; van Eldik, C.; van Rensburg, C.; van Soelen, B.; Vasileiadis, G.; Veh, J.; Venter, C.; Viana, A.; Vincent, P.; Vink, J.; Voisin, F.; Völk, H. J.; Vuillaume, T.; Wadiasingh, Z.; Wagner, S. J.; Wagner, P.; Wagner, R. M.; White, R.; Wierzcholska, A.; Willmann, P.; Wörnlein, A.; Wouters, D.; Yang, R.; Zabalza, V.; Zaborov, D.; Zacharias, M.; Zanin, R.; Zdziarski, A. A.; Zech, A.; Zefi, F.; Ziegler, A.; Żywucka, N.

2018-04-01

Aims: We study γ-ray emission from the shell-type supernova remnant (SNR) RX J0852.0-4622 to better characterize its spectral properties and its distribution over the SNR. Methods: The analysis of an extended High Energy Spectroscopic System (H.E.S.S.) data set at very high energies (E > 100 GeV) permits detailed studies, as well as spatially resolved spectroscopy, of the morphology and spectrum of the whole RX J0852.0-4622 region. The H.E.S.S. data are combined with archival data from other wavebands and interpreted in the framework of leptonic and hadronic models. The joint Fermi-LAT-H.E.S.S. spectrum allows the direct determination of the spectral characteristics of the parent particle population in leptonic and hadronic scenarios using only GeV-TeV data. Results: An updated analysis of the H.E.S.S. data shows that the spectrum of the entire SNR connects smoothly to the high-energy spectrum measured by Fermi-LAT. The increased data set makes it possible to demonstrate that the H.E.S.S. spectrum deviates significantly from a power law and is well described by both a curved power law and a power law with an exponential cutoff at an energy of Ecut = (6.7 ± 1.2stat ± 1.2syst) TeV. The joint Fermi-LAT-H.E.S.S. spectrum allows the unambiguous identification of the spectral shape as a power law with an exponential cutoff. No significant evidence is found for a variation of the spectral parameters across the SNR, suggesting similar conditions of particle acceleration across the remnant. A simple modeling using one particle population to model the SNR emission demonstrates that both leptonic and hadronic emission scenarios remain plausible. It is also shown that at least a part of the shell emission is likely due to the presence of a pulsar wind nebula around PSR J0855-4644. A FITS image of the region of interest and two text files describing the H.E.S.S. spectrum of RX J0852.0-4622 are only available at the CDS via anonymous ftp to http://cdsarc.u-strasbg.fr (http://130.79.128.5) or via http://cdsarc.u-strasbg.fr/viz-bin/qcat?J/A+A/612/A7

Spectral Phasor approach for fingerprinting of photo-activatable fluorescent proteins Dronpa, Kaede and KikGR

PubMed Central

Cutrale, Francesco; Salih, Anya; Gratton, Enrico

2013-01-01

The phasor global analysis algorithm is common for fluorescence lifetime applications, but has only been recently proposed for spectral analysis. Here the phasor representation and fingerprinting is exploited in its second harmonic to determine the number and spectra of photo-activated states as well as their conversion dynamics. We follow the sequence of photo-activation of proteins over time by rapidly collecting multiple spectral images. The phasor representation of the cumulative images provides easy identification of the spectral signatures of each photo-activatable protein. PMID:24040513

UV spectroscopy including ISM line absorption: of the exciting star of Abell 35

NASA Astrophysics Data System (ADS)

Ziegler, M.; Rauch, T.; Werner, K.; Kruk, J. W.

Reliable spectral analysis that is based on high-resolution UV observations requires an adequate, simultaneous modeling of the interstellar line absorption and reddening. In the case of the central star of the planetary nebula Abell 35, BD-22 3467, we demonstrate our current standard spectral-analysis method that is based on the Tübingen NLTE Model-Atmosphere Package (TMAP). We present an on- going spectral analysis of FUSE and HST/STIS observations of BD-22 3467.

Laboratory spectroscopy of meteorite samples at UV-vis-NIR wavelengths: Analysis and discrimination by principal components analysis

NASA Astrophysics Data System (ADS)

Penttilä, Antti; Martikainen, Julia; Gritsevich, Maria; Muinonen, Karri

2018-02-01

Meteorite samples are measured with the University of Helsinki integrating-sphere UV-vis-NIR spectrometer. The resulting spectra of 30 meteorites are compared with selected spectra from the NASA Planetary Data System meteorite spectra database. The spectral measurements are transformed with the principal component analysis, and it is shown that different meteorite types can be distinguished from the transformed data. The motivation is to improve the link between asteroid spectral observations and meteorite spectral measurements.

Determining cantilever stiffness from thermal noise.

PubMed

Lübbe, Jannis; Temmen, Matthias; Rahe, Philipp; Kühnle, Angelika; Reichling, Michael

2013-01-01

We critically discuss the extraction of intrinsic cantilever properties, namely eigenfrequency f n , quality factor Q n and specifically the stiffness k n of the nth cantilever oscillation mode from thermal noise by an analysis of the power spectral density of displacement fluctuations of the cantilever in contact with a thermal bath. The practical applicability of this approach is demonstrated for several cantilevers with eigenfrequencies ranging from 50 kHz to 2 MHz. As such an analysis requires a sophisticated spectral analysis, we introduce a new method to determine k n from a spectral analysis of the demodulated oscillation signal of the excited cantilever that can be performed in the frequency range of 10 Hz to 1 kHz regardless of the eigenfrequency of the cantilever. We demonstrate that the latter method is in particular useful for noncontact atomic force microscopy (NC-AFM) where the required simple instrumentation for spectral analysis is available in most experimental systems.

Characterization of Disulfide-Linked Peptides Using Tandem Mass Spectrometry Coupled with Automated Data Analysis Software

NASA Astrophysics Data System (ADS)

Liang, Zhidan; McGuinness, Kenneth N.; Crespo, Alejandro; Zhong, Wendy

2018-05-01

Disulfide bond formation is critical for maintaining structure stability and function of many peptides and proteins. Mass spectrometry has become an important tool for the elucidation of molecular connectivity. However, the interpretation of the tandem mass spectral data of disulfide-linked peptides has been a major challenge due to the lack of appropriate tools. Developing proper data analysis software is essential to quickly characterize disulfide-linked peptides. A thorough and in-depth understanding of how disulfide-linked peptides fragment in mass spectrometer is a key in developing software to interpret the tandem mass spectra of these peptides. Two model peptides with inter- and intra-chain disulfide linkages were used to study fragmentation behavior in both collisional-activated dissociation (CAD) and electron-based dissociation (ExD) experiments. Fragments generated from CAD and ExD can be categorized into three major types, which result from different S-S and C-S bond cleavage patterns. DiSulFinder is a computer algorithm that was newly developed based on the fragmentation observed in these peptides. The software is vendor neutral and capable of quickly and accurately identifying a variety of fragments generated from disulfide-linked peptides. DiSulFinder identifies peptide backbone fragments with S-S and C-S bond cleavages and, more importantly, can also identify fragments with the S-S bond still intact to aid disulfide linkage determination. With the assistance of this software, more comprehensive disulfide connectivity characterization can be achieved. [Figure not available: see fulltext.

Characterization of Disulfide-Linked Peptides Using Tandem Mass Spectrometry Coupled with Automated Data Analysis Software

NASA Astrophysics Data System (ADS)

Liang, Zhidan; McGuinness, Kenneth N.; Crespo, Alejandro; Zhong, Wendy

2018-01-01

Disulfide bond formation is critical for maintaining structure stability and function of many peptides and proteins. Mass spectrometry has become an important tool for the elucidation of molecular connectivity. However, the interpretation of the tandem mass spectral data of disulfide-linked peptides has been a major challenge due to the lack of appropriate tools. Developing proper data analysis software is essential to quickly characterize disulfide-linked peptides. A thorough and in-depth understanding of how disulfide-linked peptides fragment in mass spectrometer is a key in developing software to interpret the tandem mass spectra of these peptides. Two model peptides with inter- and intra-chain disulfide linkages were used to study fragmentation behavior in both collisional-activated dissociation (CAD) and electron-based dissociation (ExD) experiments. Fragments generated from CAD and ExD can be categorized into three major types, which result from different S-S and C-S bond cleavage patterns. DiSulFinder is a computer algorithm that was newly developed based on the fragmentation observed in these peptides. The software is vendor neutral and capable of quickly and accurately identifying a variety of fragments generated from disulfide-linked peptides. DiSulFinder identifies peptide backbone fragments with S-S and C-S bond cleavages and, more importantly, can also identify fragments with the S-S bond still intact to aid disulfide linkage determination. With the assistance of this software, more comprehensive disulfide connectivity characterization can be achieved. [Figure not available: see fulltext.

Methodology for diagnosing of skin cancer on images of dermatologic spots by spectral analysis.

PubMed

Guerra-Rosas, Esperanza; Álvarez-Borrego, Josué

2015-10-01

In this paper a new methodology for the diagnosing of skin cancer on images of dermatologic spots using image processing is presented. Currently skin cancer is one of the most frequent diseases in humans. This methodology is based on Fourier spectral analysis by using filters such as the classic, inverse and k-law nonlinear. The sample images were obtained by a medical specialist and a new spectral technique is developed to obtain a quantitative measurement of the complex pattern found in cancerous skin spots. Finally a spectral index is calculated to obtain a range of spectral indices defined for skin cancer. Our results show a confidence level of 95.4%.

Methodology for diagnosing of skin cancer on images of dermatologic spots by spectral analysis

PubMed Central

Guerra-Rosas, Esperanza; Álvarez-Borrego, Josué

2015-01-01

In this paper a new methodology for the diagnosing of skin cancer on images of dermatologic spots using image processing is presented. Currently skin cancer is one of the most frequent diseases in humans. This methodology is based on Fourier spectral analysis by using filters such as the classic, inverse and k-law nonlinear. The sample images were obtained by a medical specialist and a new spectral technique is developed to obtain a quantitative measurement of the complex pattern found in cancerous skin spots. Finally a spectral index is calculated to obtain a range of spectral indices defined for skin cancer. Our results show a confidence level of 95.4%. PMID:26504638

Spatio-temporally resolved spectral measurements of laser-produced plasma and semiautomated spectral measurement-control and analysis software

NASA Astrophysics Data System (ADS)

Cao, S. Q.; Su, M. G.; Min, Q.; Sun, D. X.; O'Sullivan, G.; Dong, C. Z.

2018-02-01

A spatio-temporally resolved spectral measurement system of highly charged ions from laser-produced plasmas is presented. Corresponding semiautomated computer software for measurement control and spectral analysis has been written to achieve the best synchronicity possible among the instruments. This avoids the tedious comparative processes between experimental and theoretical results. To demonstrate the capabilities of this system, a series of spatio-temporally resolved experiments of laser-produced Al plasmas have been performed and applied to benchmark the software. The system is a useful tool for studying the spectral structures of highly charged ions and for evaluating the spatio-temporal evolution of laser-produced plasmas.

Modeling of a tilted pressure-tuned field-widened Michelson interferometer for application in high spectral resolution lidar

NASA Astrophysics Data System (ADS)

Liu, Dong; Hostetler, Chris; Miller, Ian; Cook, Anthony; Hair, Jonathan

2011-10-01

High spectral resolution lidars (HSRLs) designed for aerosol and cloud remote sensing are increasingly being deployed on aircraft and called for on future space-based missions. The HSRL technique relies on spectral discrimination of the atmospheric backscatter signals to enable independent, unambiguous retrieval of aerosol extinction and backscatter. A compact, monolithic field-widened Michelson interferometer is being developed as the spectral discrimination filter for an HSRL system at NASA Langley Research Center. The Michelson interferometer consists of a cubic beam splitter, a solid glass arm, and an air arm. The spacer that connects the air arm mirror to the main part of the interferometer is designed to optimize thermal compensation such that the frequency of maximum interference can be tuned with great precision to the transmitted laser wavelength. In this paper, a comprehensive radiometric model for the field-widened Michelson interferometeric spectral filter is presented. The model incorporates the angular distribution and finite cross sectional area of the light source, reflectance of all surfaces, loss of absorption, and lack of parallelism between the airarm and solid arm, etc. The model can be used to assess the performance of the interferometer and thus it is a useful tool to evaluate performance budgets and to set optical specifications for new designs of the same basic interferometer type.

Spectral reconstruction analysis for enhancing signal-to-noise in time-resolved spectroscopies

NASA Astrophysics Data System (ADS)

Wilhelm, Michael J.; Smith, Jonathan M.; Dai, Hai-Lung

2015-09-01

We demonstrate a new spectral analysis for the enhancement of the signal-to-noise ratio (SNR) in time-resolved spectroscopies. Unlike the simple linear average which produces a single representative spectrum with enhanced SNR, this Spectral Reconstruction analysis (SRa) improves the SNR (by a factor of ca. 0 . 6 √{ n } ) for all n experimentally recorded time-resolved spectra. SRa operates by eliminating noise in the temporal domain, thereby attenuating noise in the spectral domain, as follows: Temporal profiles at each measured frequency are fit to a generic mathematical function that best represents the temporal evolution; spectra at each time are then reconstructed with data points from the fitted profiles. The SRa method is validated with simulated control spectral data sets. Finally, we apply SRa to two distinct experimentally measured sets of time-resolved IR emission spectra: (1) UV photolysis of carbonyl cyanide and (2) UV photolysis of vinyl cyanide.

Radio observations of the Milky Way from the classroom

NASA Astrophysics Data System (ADS)

Chyży, Krzysztof T.

2014-12-01

We present the project to introduce the first European network of radio telescopes for education. It enables pupils to detect spectral line emission of neutral hydrogen in the Milky Way at a wavelength of 21 cm. Any classroom connected to Internet via any web-browser can remotely control one of the radio-telescopes, observe and analyse obtained spectra: derive the Milky-Way rotation curve and recognise spiral arms in hydrogen distribution. Doing exercises pupils, guided by their teachers, learn the basics of radio astronomy research, use scientific method to explore and interpret the attained spectral data. A range of attractive educational materials are prepared to help in disseminating the scientific knowledge in the classroom and demonstrate the modern information technology.

Investigation on efficiency declines due to spectral overlap between LDAs pump and laser medium in high power double face pumped slab laser

NASA Astrophysics Data System (ADS)

Lang, Ye; Chen, Yanzhong; Liao, Lifen; Guo, Guangyan; He, Jianguo; Fan, Zhongwei

2018-03-01

In high power diode lasers, the input cooling water temperature would affect both output power and output spectrum. In double face pumped slab laser, the spectrum of two laser diode arrays (LDAs) must be optimized for efficiency reason. The spectrum mismatch of two LDAs would result in energy storing decline. In this work, thermal induced efficiency decline due to spectral overlap between high power LDAs and laser medium was investigated. A numerical model was developed to describe the energy storing variation with changing LDAs cooling water temperature and configuration (series/parallel connected). A confirmatory experiment was conducted using a double face pumped slab module. The experiment results show good agreements with simulations.

A Silicon–Singlet Fission Tandem Solar Cell Exceeding 100% External Quantum Efficiency with High Spectral Stability

PubMed Central

2017-01-01

After 60 years of research, silicon solar cell efficiency saturated close to the theoretical limit, and radically new approaches are needed to further improve the efficiency. The use of tandem systems raises this theoretical power conversion efficiency limit from 34% to 45%. We present the advantageous spectral stability of using voltage-matched tandem solar cells with respect to their traditional series-connected counterparts and experimentally demonstrate how singlet fission can be used to produce simple voltage-matched tandems. Our singlet fission silicon–pentacene tandem solar cell shows efficient photocurrent addition. This allows the tandem system to benefit from carrier multiplication and to produce an external quantum efficiency exceeding 100% at the main absorption peak of pentacene. PMID:28261671

Frequency–specific network connectivity increases underlie accurate spatiotemporal memory retrieval

PubMed Central

Watrous, Andrew J.; Tandon, Nitin; Connor, Chris; Pieters, Thomas; Ekstrom, Arne D.

2013-01-01

The medial temporal lobes, prefrontal cortex, and parts of parietal cortex form the neural underpinnings of episodic memory, which includes remembering both where and when an event occurred. Yet how these three key regions interact during retrieval of spatial and temporal context remains largely untested. Here, we employed simultaneous electrocorticographical recordings across multiple lobular regions, employing phase synchronization as a measure of network functional connectivity, while patients retrieved spatial and temporal context associated with an episode. Successful memory retrieval was characterized by greater global connectivity compared to incorrect retrieval, with the MTL acting as a convergence hub for these interactions. Spatial vs. temporal context retrieval resulted in prominent differences in both the spectral and temporal patterns of network interactions. These results emphasize dynamic network interactions as central to episodic memory retrieval, providing novel insight into how multiple contexts underlying a single event can be recreated within the same network. PMID:23354333

Evolution of Large-Scale Magnetic Fields and State Transitions in Black Hole X-Ray Binaries

NASA Astrophysics Data System (ADS)

Wang, Ding-Xiong; Huang, Chang-Yin; Wang, Jiu-Zhou

2010-04-01

The state transitions of black hole (BH) X-ray binaries are discussed based on the evolution of large-scale magnetic fields, in which the combination of three energy mechanisms are involved: (1) the Blandford-Znajek (BZ) process related to the open field lines connecting a rotating BH with remote astrophysical loads, (2) the magnetic coupling (MC) process related to the closed field lines connecting the BH with its surrounding accretion disk, and (3) the Blandford-Payne (BP) process related to the open field lines connecting the disk with remote astrophysical loads. It turns out that each spectral state of the BH binaries corresponds to each configuration of magnetic field in BH magnetosphere, and the main characteristics of low/hard (LH) state, hard intermediate (HIM) state and steep power law (SPL) state are roughly fitted based on the evolution of large-scale magnetic fields associated with disk accretion.

Attempt at correlating Italian long lineaments from LANDSAT-1 satellite images with some geological phenomena. Possible use in geothermal energy research

NASA Technical Reports Server (NTRS)

Barbier, E.; Fanelli, M.

1975-01-01

By utilizing the images from the LANDSAT-1, in the spectral band 0.8-1.1 microns (near infrared), a photomosaic was obtained of Italian territory. From this mosaic the field of long lineaments was drawn, corresponding to fractures of the earth crust more than 100 km long. The relationship between lineaments, hot springs, volcanic areas, and earthquake epicenters is verified. There is a clear connection between long lineaments and hot springs: 78% of the springs are located on one or more lineaments, and the existence of hot lineaments was observed. A slightly weaker, but still significant, connection exists between the Pliocene-Quaternary volcanic areas and long lineaments. The relationship between earthquakes and long lineaments can only be verified in some cases. The lineaments which can be related to earthquakes have little or no connection with the other phenomena.

Antepartum Fetal Monitoring and Spectral Analysis of Preterm Birth Risk

NASA Astrophysics Data System (ADS)

Păsăricără, Alexandru; Nemescu, Dragoş; Arotăriţei, Dragoş; Rotariu, Cristian

2017-11-01

The monitoring and analysis of antepartum fetal and maternal recordings is a research area of notable interest due to the relatively high value of preterm birth. The interest stems from the improvement of devices used for monitoring. The current paper presents the spectral analysis of antepartum heart rate recordings conducted during a study in Romania at the Cuza Voda Obstetrics and Gynecology Clinical Hospital from Iasi between 2010 and 2014. The study focuses on normal and preterm birth risk subjects in order to determine differences between these two types or recordings in terms of spectral analysis.

Comparative Analysis of the Clinical Significance of Oscillatory Components in the Rhythmic Structure of Pulse Signal in the Diagnostics of Psychosomatic Disorders in School Age Children.

PubMed

Desova, A A; Dorofeyuk, A A; Anokhin, A M

2017-01-01

We performed a comparative analysis of the types of spectral density typical of various parameters of pulse signal. The experimental material was obtained during the examination of school age children with various psychosomatic disorders. We also performed a typological analysis of the spectral density functions corresponding to the time series of different parameters of a single oscillation of pulse signals; the results of their comparative analysis are presented. We determined the most significant spectral components for two disordersin children: arterial hypertension and mitral valve prolapse.

Atmospheric Properties Of T Dwarfs Inferred From Model Fits At Low Spectral Resolution

NASA Astrophysics Data System (ADS)

Giorla Godfrey, Paige A.; Rice, Emily L.; Filippazzo, Joseph C.; Douglas, Stephanie E.

2016-09-01

Brown dwarf spectral types (M, L, T, Y) correlate with spectral morphology, and generally appear to correspond with decreasing mass and effective temperature (Teff). Model fits to observed spectra suggest, however, that spectral subclasses do not share this monotonic temperature correlation, indicating that secondary parameters (gravity, metallicity, dust) significantly influence spectral morphology. We seekto disentangle the fundamental parameters that underlie the spectral type sequence of the coolest fully populated spectral class of brown dwarfs using atmosphere models. We investigate the relationship between spectral type and best fit model parameters for a sample of over 150 T dwarfs with low resolution (R 75-100) near-infrared ( 0.8-2.5 micron) SpeX Prism spectra. We use synthetic spectra from four model grids (Saumon & Marley 2008, Morley+ 2012, Saumon+ 2012, BT Settl 2013) and a Markov-Chain Monte Carlo (MCMC) analysis to determine robust best fit parameters and their uncertainties. We compare the consistency of each model grid by performing our analysis on the full spectrum and also on individual wavelength bands (Y,J,H,K). We find more consistent results between the J band and full spectrum fits and that our best fit spectral type-Teff results agree with the polynomial relationships of Stephens+2009 and Filippazzo+ 2015 using bolometric luminosities. Our analysis consists of the most extensive low resolution T dwarf model comparison to date, and lays the foundation for interpretation of cool brown dwarf and exoplanet spectra.

Building an EEG-fMRI Multi-Modal Brain Graph: A Concurrent EEG-fMRI Study

PubMed Central

Yu, Qingbao; Wu, Lei; Bridwell, David A.; Erhardt, Erik B.; Du, Yuhui; He, Hao; Chen, Jiayu; Liu, Peng; Sui, Jing; Pearlson, Godfrey; Calhoun, Vince D.

2016-01-01

The topological architecture of brain connectivity has been well-characterized by graph theory based analysis. However, previous studies have primarily built brain graphs based on a single modality of brain imaging data. Here we develop a framework to construct multi-modal brain graphs using concurrent EEG-fMRI data which are simultaneously collected during eyes open (EO) and eyes closed (EC) resting states. FMRI data are decomposed into independent components with associated time courses by group independent component analysis (ICA). EEG time series are segmented, and then spectral power time courses are computed and averaged within 5 frequency bands (delta; theta; alpha; beta; low gamma). EEG-fMRI brain graphs, with EEG electrodes and fMRI brain components serving as nodes, are built by computing correlations within and between fMRI ICA time courses and EEG spectral power time courses. Dynamic EEG-fMRI graphs are built using a sliding window method, versus static ones treating the entire time course as stationary. In global level, static graph measures and properties of dynamic graph measures are different across frequency bands and are mainly showing higher values in eyes closed than eyes open. Nodal level graph measures of a few brain components are also showing higher values during eyes closed in specific frequency bands. Overall, these findings incorporate fMRI spatial localization and EEG frequency information which could not be obtained by examining only one modality. This work provides a new approach to examine EEG-fMRI associations within a graph theoretic framework with potential application to many topics. PMID:27733821

Cyclone Activity in the Arctic From an Ensemble of Regional Climate Models (Arctic CORDEX)

NASA Astrophysics Data System (ADS)

Akperov, Mirseid; Rinke, Annette; Mokhov, Igor I.; Matthes, Heidrun; Semenov, Vladimir A.; Adakudlu, Muralidhar; Cassano, John; Christensen, Jens H.; Dembitskaya, Mariya A.; Dethloff, Klaus; Fettweis, Xavier; Glisan, Justin; Gutjahr, Oliver; Heinemann, Günther; Koenigk, Torben; Koldunov, Nikolay V.; Laprise, René; Mottram, Ruth; Nikiéma, Oumarou; Scinocca, John F.; Sein, Dmitry; Sobolowski, Stefan; Winger, Katja; Zhang, Wenxin

2018-03-01

The ability of state-of-the-art regional climate models to simulate cyclone activity in the Arctic is assessed based on an ensemble of 13 simulations from 11 models from the Arctic-CORDEX initiative. Some models employ large-scale spectral nudging techniques. Cyclone characteristics simulated by the ensemble are compared with the results forced by four reanalyses (ERA-Interim, National Centers for Environmental Prediction-Climate Forecast System Reanalysis, National Aeronautics and Space Administration-Modern-Era Retrospective analysis for Research and Applications Version 2, and Japan Meteorological Agency-Japanese 55-year reanalysis) in winter and summer for 1981-2010 period. In addition, we compare cyclone statistics between ERA-Interim and the Arctic System Reanalysis reanalyses for 2000-2010. Biases in cyclone frequency, intensity, and size over the Arctic are also quantified. Variations in cyclone frequency across the models are partly attributed to the differences in cyclone frequency over land. The variations across the models are largest for small and shallow cyclones for both seasons. A connection between biases in the zonal wind at 200 hPa and cyclone characteristics is found for both seasons. Most models underestimate zonal wind speed in both seasons, which likely leads to underestimation of cyclone mean depth and deep cyclone frequency in the Arctic. In general, the regional climate models are able to represent the spatial distribution of cyclone characteristics in the Arctic but models that employ large-scale spectral nudging show a better agreement with ERA-Interim reanalysis than the rest of the models. Trends also exhibit the benefits of nudging. Models with spectral nudging are able to reproduce the cyclone trends, whereas most of the nonnudged models fail to do so. However, the cyclone characteristics and trends are sensitive to the choice of nudged variables.

Comparative study of human blood Raman spectra and biochemical analysis of patients with cancer

NASA Astrophysics Data System (ADS)

Shamina, Lyudmila A.; Bratchenko, Ivan A.; Artemyev, Dmitry N.; Myakinin, Oleg O.; Moryatov, Alexander A.; Orlov, Andrey E.; Kozlov, Sergey V.; Zakharov, Valery P.

2018-04-01

In this study we measured spectral features of blood by Raman spectroscopy. Correlation of the obtained spectral data and biochemical studies results is investigated. Analysis of specific spectra allows for identification of informative spectral bands proportional to components whose content is associated with body fluids homeostasis changes at various pathological conditions. Regression analysis of the obtained spectral data allows for discriminating the lung cancer from other tumors with a posteriori probability of 88.3%. The potentiality of applying surface-enhanced Raman spectroscopy with utilized experimental setup for further studies of the body fluids component composition was estimated. The greatest signal amplification was achieved for the gold substrate with a surface roughness of 1 μm. In general, the developed approach of body fluids analysis provides the basis of a useful and minimally invasive method of pathologies screening.

Brain networks predict metabolism, diagnosis and prognosis at the bedside in disorders of consciousness.

PubMed

Chennu, Srivas; Annen, Jitka; Wannez, Sarah; Thibaut, Aurore; Chatelle, Camille; Cassol, Helena; Martens, Géraldine; Schnakers, Caroline; Gosseries, Olivia; Menon, David; Laureys, Steven

2017-08-01

Recent advances in functional neuroimaging have demonstrated novel potential for informing diagnosis and prognosis in the unresponsive wakeful syndrome and minimally conscious states. However, these technologies come with considerable expense and difficulty, limiting the possibility of wider clinical application in patients. Here, we show that high density electroencephalography, collected from 104 patients measured at rest, can provide valuable information about brain connectivity that correlates with behaviour and functional neuroimaging. Using graph theory, we visualize and quantify spectral connectivity estimated from electroencephalography as a dense brain network. Our findings demonstrate that key quantitative metrics of these networks correlate with the continuum of behavioural recovery in patients, ranging from those diagnosed as unresponsive, through those who have emerged from minimally conscious, to the fully conscious locked-in syndrome. In particular, a network metric indexing the presence of densely interconnected central hubs of connectivity discriminated behavioural consciousness with accuracy comparable to that achieved by expert assessment with positron emission tomography. We also show that this metric correlates strongly with brain metabolism. Further, with classification analysis, we predict the behavioural diagnosis, brain metabolism and 1-year clinical outcome of individual patients. Finally, we demonstrate that assessments of brain networks show robust connectivity in patients diagnosed as unresponsive by clinical consensus, but later rediagnosed as minimally conscious with the Coma Recovery Scale-Revised. Classification analysis of their brain network identified each of these misdiagnosed patients as minimally conscious, corroborating their behavioural diagnoses. If deployed at the bedside in the clinical context, such network measurements could complement systematic behavioural assessment and help reduce the high misdiagnosis rate reported in these patients. These metrics could also identify patients in whom further assessment is warranted using neuroimaging or conventional clinical evaluation. Finally, by providing objective characterization of states of consciousness, repeated assessments of network metrics could help track individual patients longitudinally, and also assess their neural responses to therapeutic and pharmacological interventions. © The Author (2017). Published by Oxford University Press on behalf of the Guarantors of Brain.

Characterization of Carbonates by Spectral Induced Polarization

NASA Astrophysics Data System (ADS)

Hupfer, Sarah; Halisch, Matthias; Weller, Andreas

2017-04-01

This study investigates the complex electrical conductivity of carbonate samples by Spectral Induced Polarization (SIP). The analysis is conducted in combination with petrophysical, mineralogical and geochemical measurements. SIP is a useful tool to obtain more detailed information about rock properties and receive a more qualitative pore space characterization. Rock parameters like permeability, pore-size and -surface area can be predicted. Up to this point, sandstones or sandy materials were investigated in detail by laboratory SIP-measurements. Several robust empirical relationships were found that connect IP-signals and petrophysical parameters (surface area, surface conductivity and cation exchange capacity). Different types of carbonates were analyzed with laboratory SIP-measurements. Rock properties like grain density, porosity, permeability and surface area were determined by petrophysical measurements. Geochemistry and mineralogy were used to differentiate the carbonate types. First results of the SIP-measurements showed polarization effects for all different types. Four different phase behavior were observed in the phase spectra. A constant phase angle, a constant slope, a combination of both and a maximum type could be identified. Each phase behavior can be assigned to the specific carbonate type used, but the constant phase occurs at two carbonate types. Further experiments were conducted to get more insight the phase behavior and get explanations. 1. Approach: An expected phase peak frequency for each sample was calculated to check if this frequency is within the measured spectrum of 2 mHz to 100 Hz. 2. Approach: Significantly reducing of the fluid conductivity to increase phase signal for a better interpretation. 3. Approach: The cation-exchange-capacity (CEC) was regarded as a factor as well. A dependence between imaginary part of conductivity and CEC was detected. 4. Approach: Imaging procedures (scanning electron microscope, x-ray computed tomography, microscopy) were used to create a qualitative image of the carbonate samples and to investigate the pore space, for example the ratio of connected to non-connected pore space. A comparison between SIP data and the petrophysical data of the sample set showed that the phase behavior of carbonates is highly complicated and challenging compared with sandstones. It seems that there is no correlation between polarization effects and any petrophysical parameter. Ongoing investigations and measurements will be conducted to get more insight to the polarization effects of carbonates.

Analysis of In-Situ Spectral Reflectance of Sago and Other Palms: Implications for Their Detection in Optical Satellite Images

NASA Astrophysics Data System (ADS)

Rendon Santillan, Jojene; Makinano-Santillan, Meriam

2018-04-01

We present a characterization, comparison and analysis of in-situ spectral reflectance of Sago and other palms (coconut, oil palm and nipa) to ascertain on which part of the electromagnetic spectrum these palms are distinguishable from each other. The analysis also aims to reveal information that will assist in selecting which band to use when mapping Sago palms using the images acquired by these sensors. The datasets used in the analysis consisted of averaged spectral reflectance curves of each palm species measured within the 345-1045 nm wavelength range using an Ocean Optics USB4000-VIS-NIR Miniature Fiber Optic Spectrometer. This in-situ reflectance data was also resampled to match the spectral response of the 4 bands of ALOS AVNIR-2, 3 bands of ASTER VNIR, 4 bands of Landsat 7 ETM+, 5 bands of Landsat 8, and 8 bands of Worldview-2 (WV2). Examination of the spectral reflectance curves showed that the near infra-red region, specifically at 770, 800 and 875 nm, provides the best wavelengths where Sago palms can be distinguished from other palms. The resampling of the in-situ reflectance spectra to match the spectral response of optical sensors made possible the analysis of the differences in reflectance values of Sago and other palms in different bands of the sensors. Overall, the knowledge learned from the analysis can be useful in the actual analysis of optical satellite images, specifically in determining which band to include or to exclude, or whether to use all bands of a sensor in discriminating and mapping Sago palms.

Caffeine reduces resting-state BOLD functional connectivity in the motor cortex.

PubMed

Rack-Gomer, Anna Leigh; Liau, Joy; Liu, Thomas T

2009-05-15

In resting-state functional magnetic resonance imaging (fMRI), correlations between spontaneous low-frequency fluctuations in the blood oxygenation level dependent (BOLD) signal are used to assess functional connectivity between different brain regions. Changes in resting-state BOLD connectivity measures are typically interpreted as changes in coherent neural activity across spatially distinct brain regions. However, this interpretation can be complicated by the complex dependence of the BOLD signal on both neural and vascular factors. For example, prior studies have shown that vasoactive agents that alter baseline cerebral blood flow, such as caffeine and carbon dioxide, can significantly alter the amplitude and dynamics of the task-related BOLD response. In this study, we examined the effect of caffeine (200 mg dose) on resting-state BOLD connectivity in the motor cortex across a sample of healthy young subjects (N=9). We found that caffeine significantly (p<0.05) reduced measures of resting-state BOLD connectivity in the motor cortex. Baseline cerebral blood flow and spectral energy in the low-frequency BOLD fluctuations were also significantly decreased by caffeine. These results suggest that caffeine usage should be carefully considered in the design and interpretation of resting-state BOLD fMRI studies.

Studies on spectral analysis of randomly sampled signals: Application to laser velocimetry data

NASA Technical Reports Server (NTRS)

Sree, David

1992-01-01

Spectral analysis is very useful in determining the frequency characteristics of many turbulent flows, for example, vortex flows, tail buffeting, and other pulsating flows. It is also used for obtaining turbulence spectra from which the time and length scales associated with the turbulence structure can be estimated. These estimates, in turn, can be helpful for validation of theoretical/numerical flow turbulence models. Laser velocimetry (LV) is being extensively used in the experimental investigation of different types of flows, because of its inherent advantages; nonintrusive probing, high frequency response, no calibration requirements, etc. Typically, the output of an individual realization laser velocimeter is a set of randomly sampled velocity data. Spectral analysis of such data requires special techniques to obtain reliable estimates of correlation and power spectral density functions that describe the flow characteristics. FORTRAN codes for obtaining the autocorrelation and power spectral density estimates using the correlation-based slotting technique were developed. Extensive studies have been conducted on simulated first-order spectrum and sine signals to improve the spectral estimates. A first-order spectrum was chosen because it represents the characteristics of a typical one-dimensional turbulence spectrum. Digital prefiltering techniques, to improve the spectral estimates from randomly sampled data were applied. Studies show that the spectral estimates can be increased up to about five times the mean sampling rate.

Temporal fractal analysis of the rs-BOLD signal identifies brain abnormalities in autism spectrum disorder.

PubMed

Dona, Olga; Hall, Geoffrey B; Noseworthy, Michael D

2017-01-01

Brain connectivity in autism spectrum disorders (ASD) has proven difficult to characterize due to the heterogeneous nature of the spectrum. Connectivity in the brain occurs in a complex, multilevel and multi-temporal manner, driving the fluctuations observed in local oxygen demand. These fluctuations can be characterized as fractals, as they auto-correlate at different time scales. In this study, we propose a model-free complexity analysis based on the fractal dimension of the rs-BOLD signal, acquired with magnetic resonance imaging. The fractal dimension can be interpreted as measure of signal complexity and connectivity. Previous studies have suggested that reduction in signal complexity can be associated with disease. Therefore, we hypothesized that a detectable difference in rs-BOLD signal complexity could be observed between ASD patients and Controls. Anatomical and functional data from fifty-five subjects with ASD (12.7 ± 2.4 y/o) and 55 age-matched (14.1 ± 3.1 y/o) healthy controls were accessed through the NITRC database and the ABIDE project. Subjects were scanned using a 3T GE Signa MRI and a 32-channel RF-coil. Axial FSPGR-3D images were used to prescribe rs-BOLD (TE/TR = 30/2000ms) where 300 time points were acquired. Motion correction was performed on the functional data and anatomical and functional images were aligned and spatially warped to the N27 standard brain atlas. Fractal analysis, performed on a grey matter mask, was done by estimating the Hurst exponent in the frequency domain using a power spectral density approach and refining the estimation in the time domain with de-trended fluctuation analysis and signal summation conversion methods. Voxel-wise fractal dimension (FD) was calculated for every subject in the control group and in the ASD group to create ROI-based Z-scores for the ASD patients. Voxel-wise validation of FD normality across controls was confirmed, and non-Gaussian voxels were eliminated from subsequent analysis. To maintain a 95% confidence level, only regions where Z-score values were at least 2 standard deviations away from the mean (i.e. where |Z| > 2.0) were included in the analysis. We found that the main regions, where signal complexity significantly decreased among ASD patients, were the amygdala (p = 0.001), the vermis (p = 0.02), the basal ganglia (p = 0.01) and the hippocampus (p = 0.02). No regions reported significant increase in signal complexity in this study. Our findings were correlated with ADIR and ADOS assessment tools, reporting the highest correlation with the ADOS metrics. Brain connectivity is best modeled as a complex system. Therefore, a measure of complexity as the fractal dimension of fluctuations in brain oxygen demand and utilization could provide important information about connectivity issues in ASD. Moreover, this technique can be used in the characterization of a single subject, with respect to controls, without the need for group analysis. Our novel approach provides an ideal avenue for personalized diagnostics, thus providing unique patient specific assessment that could help in individualizing treatments.

Fractional-order Fourier analysis for ultrashort pulse characterization.

PubMed

Brunel, Marc; Coetmellec, Sébastien; Lelek, Mickael; Louradour, Frédéric

2007-06-01

We report what we believe to be the first experimental demonstration of ultrashort pulse characterization using fractional-order Fourier analysis. The analysis is applied to the interpretation of spectral interferometry resolved in time (SPIRIT) traces [which are spectral phase interferometry for direct electric field reconstruction (SPIDER)-like interferograms]. First, the fractional-order Fourier transformation is shown to naturally allow the determination of the cubic spectral phase coefficient of pulses to be analyzed. A simultaneous determination of both cubic and quadratic spectral phase coefficients of the pulses using the fractional-order Fourier series expansion is further demonstrated. This latter technique consists of localizing relative maxima in a 2D cartography representing decomposition coefficients. It is further used to reconstruct or filter SPIRIT traces.

Preliminary Geologic/spectral Analysis of LANDSAT-4 Thematic Mapper Data, Wind River/bighorn Basin Area, Wyoming

NASA Technical Reports Server (NTRS)

Lang, H. R.; Conel, J. E.; Paylor, E. D.

1984-01-01

A LIDQA evaluation for geologic applications of a LANDSAT TM scene covering the Wind River/Bighorn Basin area, Wyoming, is examined. This involves a quantitative assessment of data quality including spatial and spectral characteristics. Analysis is concentrated on the 6 visible, near infrared, and short wavelength infrared bands. Preliminary analysis demonstrates that: (1) principal component images derived from the correlation matrix provide the most useful geologic information. To extract surface spectral reflectance, the TM radiance data must be calibrated. Scatterplots demonstrate that TM data can be calibrated and sensor response is essentially linear. Low instrumental offset and gain settings result in spectral data that do not utilize the full dynamic range of the TM system.

On the connection between the 3HE-enrichment and spectral index of solar energetic particles

NASA Technical Reports Server (NTRS)

Kocharov, L. G.; Dvoryanchikov, Y. V.

1985-01-01

A model is presented which explains the observed tendency of events with large 3He/4He ratios to have steeper spectra. In this model preferential injection of 3He, acceleration by Alfven waves and Coulomb deceleration of ions are considered simultaneously. The observed tendency may be obtained as a result of competition between injection and acceleration processes.

Fiber-Coupled Acousto-Optical-Filter Spectrometer

NASA Technical Reports Server (NTRS)

Levin, Kenneth H.; Li, Frank Yanan

1993-01-01

Fiber-coupled acousto-optical-filter spectrometer steps rapidly through commanded sequence of wavelengths. Sample cell located remotely from monochromator and associated electronic circuitry, connected to them with optical fibers. Optical-fiber coupling makes possible to monitor samples in remote, hazardous, or confined locations. Advantages include compactness, speed, and no moving parts. Potential applications include control of chemical processes, medical diagnoses, spectral imaging, and sampling of atmospheres.

A review of spectral methods

NASA Technical Reports Server (NTRS)

Lustman, L.

1984-01-01

An outline for spectral methods for partial differential equations is presented. The basic spectral algorithm is defined, collocation are emphasized and the main advantage of the method, the infinite order of accuracy in problems with smooth solutions are discussed. Examples of theoretical numerical analysis of spectral calculations are presented. An application of spectral methods to transonic flow is presented. The full potential transonic equation is among the best understood among nonlinear equations.

Comparative Analysis of Mass Spectral Similarity Measures on Peak Alignment for Comprehensive Two-Dimensional Gas Chromatography Mass Spectrometry

PubMed Central

2013-01-01

Peak alignment is a critical procedure in mass spectrometry-based biomarker discovery in metabolomics. One of peak alignment approaches to comprehensive two-dimensional gas chromatography mass spectrometry (GC×GC-MS) data is peak matching-based alignment. A key to the peak matching-based alignment is the calculation of mass spectral similarity scores. Various mass spectral similarity measures have been developed mainly for compound identification, but the effect of these spectral similarity measures on the performance of peak matching-based alignment still remains unknown. Therefore, we selected five mass spectral similarity measures, cosine correlation, Pearson's correlation, Spearman's correlation, partial correlation, and part correlation, and examined their effects on peak alignment using two sets of experimental GC×GC-MS data. The results show that the spectral similarity measure does not affect the alignment accuracy significantly in analysis of data from less complex samples, while the partial correlation performs much better than other spectral similarity measures when analyzing experimental data acquired from complex biological samples. PMID:24151524

Spectral analysis of time series of categorical variables in earth sciences

NASA Astrophysics Data System (ADS)

Pardo-Igúzquiza, Eulogio; Rodríguez-Tovar, Francisco J.; Dorador, Javier

2016-10-01

Time series of categorical variables often appear in Earth Science disciplines and there is considerable interest in studying their cyclic behavior. This is true, for example, when the type of facies, petrofabric features, ichnofabrics, fossil assemblages or mineral compositions are measured continuously over a core or throughout a stratigraphic succession. Here we deal with the problem of applying spectral analysis to such sequences. A full indicator approach is proposed to complement the spectral envelope often used in other disciplines. Additionally, a stand-alone computer program is provided for calculating the spectral envelope, in this case implementing the permutation test to assess the statistical significance of the spectral peaks. We studied simulated sequences as well as real data in order to illustrate the methodology.

Longitudinal Detection of Optic Nerve Head Changes by Spectral Domain Optical Coherence Tomography in Early Experimental Glaucoma

PubMed Central

He, Lin; Yang, Hongli; Gardiner, Stuart K.; Williams, Galen; Hardin, Christy; Strouthidis, Nicholas G.; Fortune, Brad; Burgoyne, Claude F.

2014-01-01

Purpose. We determined if the detection of spectral-domain optical coherence tomography (SDOCT) optic nerve head (ONH) change precedes the detection of confocal scanning laser tomography (CSLT) ONH surface, SDOCT retinal nerve fiber layer (RNFL), scanning laser perimetry (SLP), and multifocal electroretinography (mfERG) change in eight experimental glaucoma (EG) eyes. Methods. Both eyes from eight monkeys were tested at least three times at baseline, and then every 2 weeks following laser-induced chronic unilateral IOP elevation. Event and trend-based definitions of onset in the control and EG eyes for 11 SDOCT neural and connective tissue, CSLT surface, SDOCT RNFL, SLP, and mfERG parameters were explored. The frequency and timing of onset for each parameter were compared using a logrank test. Results. Maximum post-laser IOP was 18 to 42 mm Hg in the EG eyes and 12 to 20 mm Hg in the control eyes. For event- and trend-based analyses, onsets were achieved earliest and most frequently within the ONH neural and connective tissues using SDOCT, and at the ONH surface using CSLT. SDOCT ONH neural and connective tissue parameter change preceded or coincided with CSLT ONH surface change in most EG eyes. The SDOCT and SLP measures of RNFL thickness, and mfERG measures of visual function demonstrated similar onset rates, but occurred later than SDOCT ONH and CSLT surface change, and in fewer eyes. Conclusions. SDOCT ONH change detection commonly precedes or coincides with CSLT ONH surface change detection, and consistently precedes RNFLT, SLP, and mfERG change detection in monkey experimental glaucoma. PMID:24255047

Development of spectral analysis math models and software program and spectral analyzer, digital converter interface equipment design

NASA Technical Reports Server (NTRS)

Hayden, W. L.; Robinson, L. H.

1972-01-01

Spectral analyses of angle-modulated communication systems is studied by: (1) performing a literature survey of candidate power spectrum computational techniques, determining the computational requirements, and formulating a mathematical model satisfying these requirements; (2) implementing the model on UNIVAC 1230 digital computer as the Spectral Analysis Program (SAP); and (3) developing the hardware specifications for a data acquisition system which will acquire an input modulating signal for SAP. The SAP computational technique uses extended fast Fourier transform and represents a generalized approach for simple and complex modulating signals.

GABA content within medial prefrontal cortex predicts the variability of fronto-limbic effective connectivity

PubMed Central

Pizzi, Stefano Delli; Chiacchieretta, Piero; Mantini, Dante; Bubbico, Giovanna; Edden, Richard A.; Onofrj, Marco; Ferretti, Antonio

2017-01-01

The amygdala-medial prefrontal cortex (mPFC) circuit plays a key role in social behavior. The amygdala and mPFC are bidirectionally connected, functionally and anatomically, via the uncinate fasciculus. Recent evidence suggests that GABA-ergic neurotransmission within the mPFC could be central to the regulation of amygdala activity related to emotions and anxiety processing. However, the functional and neurochemical interactions within amygdala-mPFC circuits are unclear. In the current study, multimodal magnetic resonance imaging techniques were combined to investigate effective connectivity within the amygdala-mPFC network and its relationship with mPFC neurotransmission in 22 healthy subjects aged between 41 and 88 years. Effective connectivity in the amygdala-mPFC circuit was assessed on resting-state functional magnetic resonance imaging data using spectral dynamic causal modelling. State and trait anxiety were also assessed. The mPFC was shown to be the target of incoming outputs from the amygdalae and the source of exciting inputs to the limbic system. The amygdalae were reciprocally connected by excitatory projections. About half of the variance relating to the strength of top–down endogenous connection between right amygdala and mPFC was explained by mPFC GABA levels. State anxiety was correlated with the strength of the endogenous connections between right amygdala and mPFC. We suggest that mPFC GABA content predicts variability in the effective connectivity within the mPFC-amygdala circuit, providing new insights on emotional physiology and the underlying functional and neurochemical interactions. PMID:28386778

Spectral imaging toolbox: segmentation, hyperstack reconstruction, and batch processing of spectral images for the determination of cell and model membrane lipid order.

PubMed

Aron, Miles; Browning, Richard; Carugo, Dario; Sezgin, Erdinc; Bernardino de la Serna, Jorge; Eggeling, Christian; Stride, Eleanor

2017-05-12

Spectral imaging with polarity-sensitive fluorescent probes enables the quantification of cell and model membrane physical properties, including local hydration, fluidity, and lateral lipid packing, usually characterized by the generalized polarization (GP) parameter. With the development of commercial microscopes equipped with spectral detectors, spectral imaging has become a convenient and powerful technique for measuring GP and other membrane properties. The existing tools for spectral image processing, however, are insufficient for processing the large data sets afforded by this technological advancement, and are unsuitable for processing images acquired with rapidly internalized fluorescent probes. Here we present a MATLAB spectral imaging toolbox with the aim of overcoming these limitations. In addition to common operations, such as the calculation of distributions of GP values, generation of pseudo-colored GP maps, and spectral analysis, a key highlight of this tool is reliable membrane segmentation for probes that are rapidly internalized. Furthermore, handling for hyperstacks, 3D reconstruction and batch processing facilitates analysis of data sets generated by time series, z-stack, and area scan microscope operations. Finally, the object size distribution is determined, which can provide insight into the mechanisms underlying changes in membrane properties and is desirable for e.g. studies involving model membranes and surfactant coated particles. Analysis is demonstrated for cell membranes, cell-derived vesicles, model membranes, and microbubbles with environmentally-sensitive probes Laurdan, carboxyl-modified Laurdan (C-Laurdan), Di-4-ANEPPDHQ, and Di-4-AN(F)EPPTEA (FE), for quantification of the local lateral density of lipids or lipid packing. The Spectral Imaging Toolbox is a powerful tool for the segmentation and processing of large spectral imaging datasets with a reliable method for membrane segmentation and no ability in programming required. The Spectral Imaging Toolbox can be downloaded from https://uk.mathworks.com/matlabcentral/fileexchange/62617-spectral-imaging-toolbox .

Technical Training on High-Order Spectral Analysis and Thermal Anemometry Applications

NASA Technical Reports Server (NTRS)

Maslov, A. A.; Shiplyuk, A. N.; Sidirenko, A. A.; Bountin, D. A.

2003-01-01

The topics of thermal anemometry and high-order spectral analyses were the subject of the technical training. Specifically, the objective of the technical training was to study: (i) the recently introduced constant voltage anemometer (CVA) for high-speed boundary layer; and (ii) newly developed high-order spectral analysis techniques (HOSA). Both CVA and HOSA are relevant tools for studies of boundary layer transition and stability.

A theoretical-experimental methodology for assessing the sensitivity of biomedical spectral imaging platforms, assays, and analysis methods.

PubMed

Leavesley, Silas J; Sweat, Brenner; Abbott, Caitlyn; Favreau, Peter; Rich, Thomas C

2018-01-01

Spectral imaging technologies have been used for many years by the remote sensing community. More recently, these approaches have been applied to biomedical problems, where they have shown great promise. However, biomedical spectral imaging has been complicated by the high variance of biological data and the reduced ability to construct test scenarios with fixed ground truths. Hence, it has been difficult to objectively assess and compare biomedical spectral imaging assays and technologies. Here, we present a standardized methodology that allows assessment of the performance of biomedical spectral imaging equipment, assays, and analysis algorithms. This methodology incorporates real experimental data and a theoretical sensitivity analysis, preserving the variability present in biomedical image data. We demonstrate that this approach can be applied in several ways: to compare the effectiveness of spectral analysis algorithms, to compare the response of different imaging platforms, and to assess the level of target signature required to achieve a desired performance. Results indicate that it is possible to compare even very different hardware platforms using this methodology. Future applications could include a range of optimization tasks, such as maximizing detection sensitivity or acquisition speed, providing high utility for investigators ranging from design engineers to biomedical scientists. © 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

An experiment with spectral analysis of emotional speech affected by orthodontic appliances

NASA Astrophysics Data System (ADS)

Přibil, Jiří; Přibilová, Anna; Ďuračková, Daniela

2012-11-01

The contribution describes the effect of the fixed and removable orthodontic appliances on spectral properties of emotional speech. Spectral changes were analyzed and evaluated by spectrograms and mean Welch’s periodograms. This alternative approach to the standard listening test enables to obtain objective comparison based on statistical analysis by ANOVA and hypothesis tests. Obtained results of analysis performed on short sentences of a female speaker in four emotional states (joyous, sad, angry, and neutral) show that, first of all, the removable orthodontic appliance affects the spectrograms of produced speech.

Mass Defect from Nuclear Physics to Mass Spectral Analysis.

PubMed

Pourshahian, Soheil

2017-09-01

Mass defect is associated with the binding energy of the nucleus. It is a fundamental property of the nucleus and the principle behind nuclear energy. Mass defect has also entered into the mass spectrometry terminology with the availability of high resolution mass spectrometry and has found application in mass spectral analysis. In this application, isobaric masses are differentiated and identified by their mass defect. What is the relationship between nuclear mass defect and mass defect used in mass spectral analysis, and are they the same? Graphical Abstract ᅟ.

Task-related modulations of BOLD low-frequency fluctuations within the default mode network

NASA Astrophysics Data System (ADS)

Tommasin, Silvia; Mascali, Daniele; Gili, Tommaso; Eid Assan, Ibrahim; Moraschi, Marta; Fratini, Michela; Wise, Richard G.; Macaluso, Emiliano; Mangia, Silvia; Giove, Federico

2017-07-01

Spontaneous low-frequency Blood-Oxygenation Level-Dependent (BOLD) signals acquired during resting state are characterized by spatial patterns of synchronous fluctuations, ultimately leading to the identification of robust brain networks. The resting-state brain networks, including the Default Mode Network (DMN), are demonstrated to persist during sustained task execution, but the exact features of task-related changes of network properties are still not well characterized. In this work we sought to examine in a group of 20 healthy volunteers (age 33±6 years, 8F/12M) the relationship between changes of spectral and spatiotemporal features of one prominent resting-state network, namely the DMN, during the steady-state execution of a sustained working memory n-back task. We found that the steady state execution of such a task impacted on both functional connectivity and amplitude of BOLD fluctuations within large parts of the DMN, but these changes correlated between each other only in a small area of the posterior cingulate. We conclude that combined analysis of multiple parameters related to connectivity, and their changes during the transition from resting state to steady-state task execution, can contribute to a better understanding of how brain networks rearrange themselves in response of a task.

Simple index of functional connectivity at rest in Multiple Sclerosis fatigue.

PubMed

Buyukturkoglu, Korhan; Porcaro, Camillo; Cottone, Carlo; Cancelli, Andrea; Inglese, Matilde; Tecchio, Franca

2017-05-01

To investigate the EEG-derived functional connectivity at rest (FCR) patterns of fatigued Multiple Sclerosis (MS) patients in order to find good parameters for a future EEG-Neurofeedback intervention to reduce their fatigue symptoms. We evaluated FCR between hemispheric homologous areas, via spectral coherence between pairs of corresponding left and right bipolar derivations, in the Theta, Alpha and Beta bands. We estimated FCR in 18MS patients with different levels of fatigue and minimal clinical severity and in 11 age and gender matched healthy controls. We used correlation analysis to assess the relationship between the fatigue scores and the FCR values differing between fatigued MS patients and controls. Among FCR values differing between fatigued MS patients and controls, fatigue symptoms increased with higher Beta temporo-parietal FCR (p=0.00004). Also, positive correlations were found between the fatigue levels and the fronto-frontal FCR in Beta and Theta bands (p=0.0002 and p=0.001 respectively). We propose that a future EEG-Neurofeedback system against MS fatigue would train patients to decrease voluntarily the beta coherence between the homologous temporo-parietal areas. We extracted a feature for building an EEG-Neurofeedback system against fatigue in MS. Copyright © 2017 International Federation of Clinical Neurophysiology. Published by Elsevier B.V. All rights reserved.

Connection Between X-Ray Dips and Superluminal Ejections in the Radio Galaxy 3C 120

NASA Technical Reports Server (NTRS)

Aller, Margo F.

2005-01-01

This work represents a part of a long-term study of the X-ray flux variability of 3C 120 and its relation to flux and structural changes in the radio jet of this galaxy. The grant included fiinding for the rediiction and analysis of data obt,ained during the time pwiod of Rossi XTE cycle 8 (March 1, 2003-February 29, 2004). Prior RXTE observations, combined with single dish monitoring at centimeter wavelengths and 43 GHz mapping (monthly until February 1999 and bimonthly thereafter) of the inner jet with the VLBA, had identified the presence of X-ray dips in the light curves and X-ray spectral hardening 4 weeks prior to the ejection of new VLBI components in the radio jet. This suggested a picture in which the radio jet was fed by accretion events near the black hole. The specific goals of the cycle 8 observations were to better define the relation between the X-ray dips and the radio events using higher sampling, to include more events in the correlation and hence improve the statistics, to look for a possible optical X-ray connection, and to search for quasi periodicities on timescales of 1-3 days. In cycle 8 this project was awarded time for 4 pointings weekly with RXTE.

Acute Sleep Deprivation Induces a Local Brain Transfer Information Increase in the Frontal Cortex in a Widespread Decrease Context.

PubMed

Alonso, Joan F; Romero, Sergio; Mañanas, Miguel A; Alcalá, Marta; Antonijoan, Rosa M; Giménez, Sandra

2016-04-14

Sleep deprivation (SD) has adverse effects on mental and physical health, affecting the cognitive abilities and emotional states. Specifically, cognitive functions and alertness are known to decrease after SD. The aim of this work was to identify the directional information transfer after SD on scalp EEG signals using transfer entropy (TE). Using a robust methodology based on EEG recordings of 18 volunteers deprived from sleep for 36 h, TE and spectral analysis were performed to characterize EEG data acquired every 2 h. Correlation between connectivity measures and subjective somnolence was assessed. In general, TE showed medium- and long-range significant decreases originated at the occipital areas and directed towards different regions, which could be interpreted as the transfer of predictive information from parieto-occipital activity to the rest of the head. Simultaneously, short-range increases were obtained for the frontal areas, following a consistent and robust time course with significant maps after 20 h of sleep deprivation. Changes during sleep deprivation in brain network were measured effectively by TE, which showed increased local connectivity and diminished global integration. TE is an objective measure that could be used as a potential measure of sleep pressure and somnolence with the additional property of directed relationships.

Fusion of spectral models for dynamic modeling of sEMG and skeletal muscle force.

PubMed

Potluri, Chandrasekhar; Anugolu, Madhavi; Chiu, Steve; Urfer, Alex; Schoen, Marco P; Naidu, D Subbaram

2012-01-01

In this paper, we present a method of combining spectral models using a Kullback Information Criterion (KIC) data fusion algorithm. Surface Electromyographic (sEMG) signals and their corresponding skeletal muscle force signals are acquired from three sensors and pre-processed using a Half-Gaussian filter and a Chebyshev Type- II filter, respectively. Spectral models - Spectral Analysis (SPA), Empirical Transfer Function Estimate (ETFE), Spectral Analysis with Frequency Dependent Resolution (SPFRD) - are extracted from sEMG signals as input and skeletal muscle force as output signal. These signals are then employed in a System Identification (SI) routine to establish the dynamic models relating the input and output. After the individual models are extracted, the models are fused by a probability based KIC fusion algorithm. The results show that the SPFRD spectral models perform better than SPA and ETFE models in modeling the frequency content of the sEMG/skeletal muscle force data.

Novel full-spectral flow cytometry with multiple spectrally-adjacent fluorescent proteins and fluorochromes and visualization of in vivo cellular movement.

PubMed

Futamura, Koji; Sekino, Masashi; Hata, Akihiro; Ikebuchi, Ryoyo; Nakanishi, Yasutaka; Egawa, Gyohei; Kabashima, Kenji; Watanabe, Takeshi; Furuki, Motohiro; Tomura, Michio

2015-09-01

Flow cytometric analysis with multicolor fluoroprobes is an essential method for detecting biological signatures of cells. Here, we present a new full-spectral flow cytometer (spectral-FCM). Unlike conventional flow cytometer, this spectral-FCM acquires the emitted fluorescence for all probes across the full-spectrum from each cell with 32 channels sequential PMT unit after dispersion with prism, and extracts the signals of each fluoroprobe based on the spectral shape of each fluoroprobe using unique algorithm in high speed, high sensitive, accurate, automatic and real-time. The spectral-FCM detects the continuous changes in emission spectra from green to red of the photoconvertible protein, KikGR with high-spectral resolution and separates spectrally-adjacent fluoroprobes, such as FITC (Emission peak (Em) 519 nm) and EGFP (Em 507 nm). Moreover, the spectral-FCM can measure and subtract autofluorescence of each cell providing increased signal-to-noise ratios and improved resolution of dim samples, which leads to a transformative technology for investigation of single cell state and function. These advances make it possible to perform 11-color fluorescence analysis to visualize movement of multilinage immune cells by using KikGR-expressing mice. Thus, the novel spectral flow cytometry improves the combinational use of spectrally-adjacent various FPs and multicolor fluorochromes in metabolically active cell for the investigation of not only the immune system but also other research and clinical fields of use. © 2015 International Society for Advancement of Cytometry.

Use of Raman microscopy and band-target entropy minimization analysis to identify dyes in a commercial stamp. Implications for authentication and counterfeit detection.

PubMed

Widjaja, Effendi; Garland, Marc

2008-02-01

Raman microscopy was used in mapping mode to collect more than 1000 spectra in a 100 microm x 100 microm area from a commercial stamp. Band-target entropy minimization (BTEM) was then employed to unmix the mixture spectra in order to extract the pure component spectra of the samples. Three pure component spectral patterns with good signal-to-noise ratios were recovered, and their spatial distributions were determined. The three pure component spectral patterns were then identified as copper phthalocyanine blue, calcite-like material, and yellow organic dye material by comparison to known spectral libraries. The present investigation, consisting of (1) advanced curve resolution (blind-source separation) followed by (2) spectral data base matching, readily suggests extensions to authenticity and counterfeit studies of other types of commercial objects. The presence or absence of specific observable components form the basis for assessment. The present spectral analysis (BTEM) is applicable to highly overlapping spectral information. Since a priori information such as the number of components present and spectral libraries are not needed in BTEM, and since minor signals arising from trace components can be reconstructed, this analysis offers a robust approach to a wide variety of material problems involving authenticity and counterfeit issues.

Development of seismic fragility curves for low-rise masonry infilled reinforced concrete buildings by a coefficient-based method

NASA Astrophysics Data System (ADS)

Su, Ray Kai Leung; Lee, Chien-Liang

2013-06-01

This study presents a seismic fragility analysis and ultimate spectral displacement assessment of regular low-rise masonry infilled (MI) reinforced concrete (RC) buildings using a coefficient-based method. The coefficient-based method does not require a complicated finite element analysis; instead, it is a simplified procedure for assessing the spectral acceleration and displacement of buildings subjected to earthquakes. A regression analysis was first performed to obtain the best-fitting equations for the inter-story drift ratio (IDR) and period shift factor of low-rise MI RC buildings in response to the peak ground acceleration of earthquakes using published results obtained from shaking table tests. Both spectral acceleration- and spectral displacement-based fragility curves under various damage states (in terms of IDR) were then constructed using the coefficient-based method. Finally, the spectral displacements of low-rise MI RC buildings at the ultimate (or nearcollapse) state obtained from this paper and the literature were compared. The simulation results indicate that the fragility curves obtained from this study and other previous work correspond well. Furthermore, most of the spectral displacements of low-rise MI RC buildings at the ultimate state from the literature fall within the bounded spectral displacements predicted by the coefficient-based method.

Bridge-mediated hopping or superexchange electron-transfer processes in bis(triarylamine) systems

NASA Astrophysics Data System (ADS)

Lambert, Christoph; Nöll, Gilbert; Schelter, Jürgen

2002-09-01

Hopping and superexchange are generally considered to be alternative electron-transfer mechanisms in molecular systems. In this work we used mixed-valence radical cations as model systems for the investigation of electron-transfer pathways. We show that substituents attached to a conjugated bridge connecting two triarylamine redox centres have a marked influence on the near-infrared absorption spectra of the corresponding cations. Spectral analysis, followed by evaluation of the electron-transfer parameters using the Generalized Mulliken-Hush theory and simulation of the potential energy surfaces, indicate that hopping and superexchange are not alternatives, but are both present in the radical cation with a dimethoxybenzene bridge. We found that the type of electron-transfer mechanism depends on the bridge-reorganization energy as well as on the bridge-state energy. Because superexchange and hopping follow different distance laws, our findings have implications for the design of new molecular and polymeric electron-transfer materials.

On the use of microwave radar devices in chronobiology studies: an application with Periplaneta americana.

PubMed

Pasquali, Vittorio; Renzi, Paolo

2005-08-01

Modified motion detectors can be used to monitor locomotor activity and measure endogenous rhythms. Although these devices can help monitor insects in their home cages, the small size of the animals requires a very short wavelength detector. We modified a commercial microwave-based detection device, connected the detector's output to the digital input of a computer, and validated the device by recording circadian and ultradian rhythms. Periplaneta americana were housed in individual cages, and their activity was monitored at 18 degrees C and subsequently at 28 degrees C in constant darkness. Time series were analyzed by a discrete Fourier transform and a chi-square periodogram. Q10 values and the circadian free-running period confirmed the data reported in the literature, validating the apparatus. Moreover, the spectral analysis and periodogram revealed the presence of ultradian rhythmicity in the range of 1-8 h.

A new method for the measurement of tremor at rest.

PubMed

Comby, B; Chevalier, G; Bouchoucha, M

1992-01-01

This paper establishes a standard method for measuring human tremor. The electronic instrument described is an application of this method. It solves the need for an effective and simple tremor-measuring instrument fit for wide distribution. This instrument consists of a piezoelectric accelerometer connected to an electronic circuit and to an LCD display. The signal is also analysed by a computer after accelerometer analogic/digital conversion in order to test the method. The tremor of 1079 healthy subjects was studied. Spectral analysis showed frequency peaks between 5.85 and 8.80 Hz. Chronic cigarette-smoking and coffee drinking did not modify the tremor as compared with controls. Relaxation session decreased tremor significantly in healthy subjects (P less than 0.01). This new tremor-measuring method opens new horizons in the understanding of physiological and pathological tremor, stress, anxiety and in the means to avoid or compensate them.

Topological dimension tunes activity patterns in hierarchical modular networks

NASA Astrophysics Data System (ADS)

Safari, Ali; Moretti, Paolo; Muñoz, Miguel A.

2017-11-01

Connectivity patterns of relevance in neuroscience and systems biology can be encoded in hierarchical modular networks (HMNs). Recent studies highlight the role of hierarchical modular organization in shaping brain activity patterns, providing an excellent substrate to promote both segregation and integration of neural information. Here, we propose an extensive analysis of the critical spreading rate (or ‘epidemic’ threshold)—separating a phase with endemic persistent activity from one in which activity ceases—on diverse HMNs. By employing analytical and computational techniques we determine the nature of such a threshold and scrutinize how it depends on general structural features of the underlying HMN. We critically discuss the extent to which current graph-spectral methods can be applied to predict the onset of spreading in HMNs and, most importantly, we elucidate the role played by the network topological dimension as a relevant and unifying structural parameter, controlling the epidemic threshold.

A conjunct near-surface spectroscopy system for fix-angle and multi-angle continuous measurements of canopy reflectance and sun-induced chlorophyll fluorescence

NASA Astrophysics Data System (ADS)

Zhang, Qian; Fan, Yifeng; Zhang, Yongguang; Chou, Shuren; Ju, Weimin; Chen, Jing M.

2016-09-01

An automated spectroscopy system, which is divided into fix-angle and multi-angle subsystems, for collecting simultaneous, continuous and long-term measurements of canopy hyper-spectra in a crop ecosystem is developed. The fix-angle subsystem equips two spectrometers: one is HR2000+ (OceanOptics) covering the spectral range 200-1100 nm with 1.0 nm spectral resolution, and another one is QE65PRO (OceanOptics) providing 0.1 nm spectral resolution within the 730-780 nm spectral range. Both spectrometers connect a cosine-corrected fiber-optic fixed up-looking to collect the down-welling irradiance and a bare fiber-optic to measure the up-welling radiance from the vegetation. An inline fiber-optic shutter FOS-2x2-TTL (OceanOptics) is used to switch between input fibers to collect the signal from either the canopy or sky at one time. QE65PRO is used to permit estimation of vegetation Sun-Induced Fluorescence (SIF) in the O2-A band. The data collection scheme includes optimization of spectrometer integration time to maximize the signal to noise ratio and measurement of instrument dark currency. The multi-angle subsystem, which can help understanding bidirectional reflectance effects, alternatively use HR4000 (OceanOptics) providing 0.1 nm spectral resolution within the 680-800 nm spectral range to measure multi-angle SIF. This subsystem additionally includes a spectrometer Unispec-DC (PPSystems) featuring both up-welling and down-welling channels with 3 nm spectral resolution covering the 300-1100 nm spectral range. Two down-looking fiber-optics are mounted on a rotating device PTU-D46 (FLIR Systems), which can rotate horizontally and vertically at 10° angular step widths. Observations can be used to calculate canopy reflectance, vegetation indices and SIF for monitoring plant physiological processes.

The browning value changes and spectral analysis on the Maillard reaction product from glucose and methionine model system

NASA Astrophysics Data System (ADS)

Al-Baarri, A. N.; Legowo, A. M.; Widayat

2018-01-01

D-glucose has been understood to provide the various effect on the reactivity in Maillard reaction resulting in the changes in physical performance of food product. Therefore this research was done to analyse physical appearance of Maillard reaction product made of D-glucose and methionine as a model system. The changes in browning value and spectral analysis model system were determined. The glucose-methionine model system was produced through the heating treatment at 50°C and RH 70% for 24 hours. The data were collected for every three hour using spectrophotometer. As result, browning value was elevated with the increase of heating time and remarkably high if compare to the D-glucose only. Furthermore, the spectral analysis showed that methionine turned the pattern of peak appearance. As conclusion, methionine raised the browning value and changed the pattern of spectral analysis in Maillard reaction model system.

Principle component analysis and linear discriminant analysis of multi-spectral autofluorescence imaging data for differentiating basal cell carcinoma and healthy skin

NASA Astrophysics Data System (ADS)

Chernomyrdin, Nikita V.; Zaytsev, Kirill I.; Lesnichaya, Anastasiya D.; Kudrin, Konstantin G.; Cherkasova, Olga P.; Kurlov, Vladimir N.; Shikunova, Irina A.; Perchik, Alexei V.; Yurchenko, Stanislav O.; Reshetov, Igor V.

2016-09-01

In present paper, an ability to differentiate basal cell carcinoma (BCC) and healthy skin by combining multi-spectral autofluorescence imaging, principle component analysis (PCA), and linear discriminant analysis (LDA) has been demonstrated. For this purpose, the experimental setup, which includes excitation and detection branches, has been assembled. The excitation branch utilizes a mercury arc lamp equipped with a 365-nm narrow-linewidth excitation filter, a beam homogenizer, and a mechanical chopper. The detection branch employs a set of bandpass filters with the central wavelength of spectral transparency of λ = 400, 450, 500, and 550 nm, and a digital camera. The setup has been used to study three samples of freshly excised BCC. PCA and LDA have been implemented to analyze the data of multi-spectral fluorescence imaging. Observed results of this pilot study highlight the advantages of proposed imaging technique for skin cancer diagnosis.

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.

Objective determination of image end-members in spectral mixture analysis of AVIRIS data

NASA Technical Reports Server (NTRS)

Tompkins, Stefanie; Mustard, John F.; Pieters, Carle M.; Forsyth, Donald W.

1993-01-01

Spectral mixture analysis has been shown to be a powerful, multifaceted tool for analysis of multi- and hyper-spectral data. Applications of AVIRIS data have ranged from mapping soils and bedrock to ecosystem studies. During the first phase of the approach, a set of end-members are selected from an image cube (image end-members) that best account for its spectral variance within a constrained, linear least squares mixing model. These image end-members are usually selected using a priori knowledge and successive trial and error solutions to refine the total number and physical location of the end-members. However, in many situations a more objective method of determining these essential components is desired. We approach the problem of image end-member determination objectively by using the inherent variance of the data. Unlike purely statistical methods such as factor analysis, this approach derives solutions that conform to a physically realistic model.

Spectral mapping of brain functional connectivity from diffusion imaging.

PubMed

Becker, Cassiano O; Pequito, Sérgio; Pappas, George J; Miller, Michael B; Grafton, Scott T; Bassett, Danielle S; Preciado, Victor M

2018-01-23

Understanding the relationship between the dynamics of neural processes and the anatomical substrate of the brain is a central question in neuroscience. On the one hand, modern neuroimaging technologies, such as diffusion tensor imaging, can be used to construct structural graphs representing the architecture of white matter streamlines linking cortical and subcortical structures. On the other hand, temporal patterns of neural activity can be used to construct functional graphs representing temporal correlations between brain regions. Although some studies provide evidence that whole-brain functional connectivity is shaped by the underlying anatomy, the observed relationship between function and structure is weak, and the rules by which anatomy constrains brain dynamics remain elusive. In this article, we introduce a methodology to map the functional connectivity of a subject at rest from his or her structural graph. Using our methodology, we are able to systematically account for the role of structural walks in the formation of functional correlations. Furthermore, in our empirical evaluations, we observe that the eigenmodes of the mapped functional connectivity are associated with activity patterns associated with different cognitive systems.

Detecting Unknown Artificial Urban Surface Materials Based on Spectral Dissimilarity Analysis.

PubMed

Jilge, Marianne; Heiden, Uta; Habermeyer, Martin; Mende, André; Juergens, Carsten

2017-08-08

High resolution imaging spectroscopy data have been recognised as a valuable data resource for augmenting detailed material inventories that serve as input for various urban applications. Image-specific urban spectral libraries are successfully used in urban imaging spectroscopy studies. However, the regional- and sensor-specific transferability of such libraries is limited due to the wide range of different surface materials. With the developed methodology, incomplete urban spectral libraries can be utilised by assuming that unknown surface material spectra are dissimilar to the known spectra in a basic spectral library (BSL). The similarity measure SID-SCA (Spectral Information Divergence-Spectral Correlation Angle) is applied to detect image-specific unknown urban surfaces while avoiding spectral mixtures. These detected unknown materials are categorised into distinct and identifiable material classes based on their spectral and spatial metrics. Experimental results demonstrate a successful redetection of material classes that had been previously erased in order to simulate an incomplete BSL. Additionally, completely new materials e.g., solar panels were identified in the data. It is further shown that the level of incompleteness of the BSL and the defined dissimilarity threshold are decisive for the detection of unknown material classes and the degree of spectral intra-class variability. A detailed accuracy assessment of the pre-classification results, aiming to separate natural and artificial materials, demonstrates spectral confusions between spectrally similar materials utilizing SID-SCA. However, most spectral confusions occur between natural or artificial materials which are not affecting the overall aim. The dissimilarity analysis overcomes the limitations of working with incomplete urban spectral libraries and enables the generation of image-specific training databases.

Detecting Unknown Artificial Urban Surface Materials Based on Spectral Dissimilarity Analysis

PubMed Central

Jilge, Marianne; Heiden, Uta; Habermeyer, Martin; Mende, André; Juergens, Carsten

2017-01-01

High resolution imaging spectroscopy data have been recognised as a valuable data resource for augmenting detailed material inventories that serve as input for various urban applications. Image-specific urban spectral libraries are successfully used in urban imaging spectroscopy studies. However, the regional- and sensor-specific transferability of such libraries is limited due to the wide range of different surface materials. With the developed methodology, incomplete urban spectral libraries can be utilised by assuming that unknown surface material spectra are dissimilar to the known spectra in a basic spectral library (BSL). The similarity measure SID-SCA (Spectral Information Divergence-Spectral Correlation Angle) is applied to detect image-specific unknown urban surfaces while avoiding spectral mixtures. These detected unknown materials are categorised into distinct and identifiable material classes based on their spectral and spatial metrics. Experimental results demonstrate a successful redetection of material classes that had been previously erased in order to simulate an incomplete BSL. Additionally, completely new materials e.g., solar panels were identified in the data. It is further shown that the level of incompleteness of the BSL and the defined dissimilarity threshold are decisive for the detection of unknown material classes and the degree of spectral intra-class variability. A detailed accuracy assessment of the pre-classification results, aiming to separate natural and artificial materials, demonstrates spectral confusions between spectrally similar materials utilizing SID-SCA. However, most spectral confusions occur between natural or artificial materials which are not affecting the overall aim. The dissimilarity analysis overcomes the limitations of working with incomplete urban spectral libraries and enables the generation of image-specific training databases. PMID:28786947

An improved electronic determination of the Boltzmann constant by Johnson noise thermometry.

PubMed

Qu, Jifeng; Benz, Samuel P; Coakley, Kevin; Rogalla, Horst; Tew, Weston L; White, Rod; Zhou, Kunli; Zhou, Zhenyu

2017-08-01

Recent measurements using acoustic gas thermometry have determined the value of the Boltzmann constant, k , with a relative uncertainty less than 1 × 10 -6 . These results have been supported by a measurement with a relative uncertainty of 1.9 × 10 -6 made with dielectric-constant gas thermometry. Together, the measurements meet the requirements of the International Committee for Weights and Measures and enable them to proceed with the redefinition of the kelvin in 2018. In further support, we provide a new determination of k using a purely electronic approach, Johnson noise thermometry, in which the thermal noise power generated by a sensing resistor immersed in a triple-point-of-water cell is compared to the noise power of a quantum-accurate pseudo-random noise waveform of nominally equal noise power. The experimental setup differs from that of the 2015 determination in several respects: a 100 Ω resistor is used as the thermal noise source, identical thin coaxial cables made of solid beryllium-copper conductors and foam dielectrics are used to connect the thermal and quantum-accurate noise sources to the correlator so as to minimize the temperature and frequency sensitivity of the impedances in the connecting leads, and no trimming capacitors or inductors are inserted into the connecting leads. The combination of reduced uncertainty due to spectral mismatches in the connecting leads and reduced statistical uncertainty due to a longer integration period of 100 d results in an improved determination of k = 1.380 649 7(37) × 10 -23 J K -1 with a relative standard uncertainty of 2.7 × 10 -6 and a relative offset of 0.89 × 10 -6 from the CODATA 2014 recommended value. The most significant terms in the uncertainty budget, the statistical uncertainty and the spectral-mismatch uncertainty, are uncorrelated with the corresponding uncertainties in the 2015 measurements.

Investigating cardiorespiratory interaction by cross-spectral analysis of event series

NASA Astrophysics Data System (ADS)

Schäfer, Carsten; Rosenblum, Michael G.; Pikovsky, Arkady S.; Kurths, Jürgen

2000-02-01

The human cardiovascular and respiratory systems interact with each other and show effects of modulation and synchronization. Here we present a cross-spectral technique that specifically considers the event-like character of the heartbeat and avoids typical restrictions of other spectral methods. Using models as well as experimental data, we demonstrate how modulation and synchronization can be distinguished. Finally, we compare the method to traditional techniques and to the analysis of instantaneous phases.

Turbulent Fluid Motion 5: Fourier Analysis, the Spectral Form of the Continuum Equations, and Homogeneous Turbulence

NASA Technical Reports Server (NTRS)

Deissler, Robert G.

1996-01-01

Background material on Fourier analysis and on the spectral form of the continuum equations, both averaged and unaveraged, are given. The equations are applied to a number of cases of homogeneous turbulence with and without mean gradients. Spectral transfer of turbulent activity between scales of motion is studied in some detail. The effects of mean shear, heat transfer, normal strain, and buoyancy are included in the analyses.

Tests of Spectral Cloud Classification Using DMSP Fine Mode Satellite Data.

DTIC Science & Technology

1980-06-02

processing techniques of potential value. Fourier spectral analysis was identified as the most promising technique to upgrade automated processing of...these measurements on the Earth’s surface is 0. 3 n mi. 3. Pickett, R.M., and Blackman, E.S. (1976) Automated Processing of Satellite Imagery Data at Air...and Pickett. R. Al. (1977) Automated Processing of Satellite Imagery Data at the Air Force Global Weather Central: Demonstrations of Spectral Analysis

Hyperthyroidism is characterized by both increased sympathetic and decreased vagal modulation of heart rate: evidence from spectral analysis of heart rate variability.

PubMed

Chen, Jin-Long; Chiu, Hung-Wen; Tseng, Yin-Jiun; Chu, Woei-Chyn

2006-06-01

The clinical manifestations of hyperthyroidism resemble those of the hyperadrenergic state. This study was designed to evaluate the impact of hyperthyroidism on the autonomic nervous system (ANS) and to investigate the relationship between serum thyroid hormone concentrations and parameters of spectral heart rate variability (HRV) analysis in hyperthyroidism. Thirty-two hyperthyroid Graves' disease patients (mean age 31 years) and 32 sex-, age-, and body mass index (BMI)-matched normal control subjects were recruited to receive one-channel electrocardiogram (ECG) recording. The cardiac autonomic nervous function was evaluated by the spectral analysis of HRV, which indicates the autonomic modulation of the sinus node. The correlation coefficients between serum thyroid hormone concentrations and parameters of the spectral HRV analysis were also computed. The hyperthyroid patients revealed significant differences (P < 0.001) compared with the controls in the following HRV parameters: a decrease in total power (TP), very low frequency power (VLF), low frequency power (LF), high frequency power (HF), and HF in normalized units (HF%); and an increase in LF in normalized units (LF%) and in the ratio of LF to HF (LF/HF). After correction of hyperthyroidism in 28 patients, all of the above parameters were restored to levels comparable to those of the controls. In addition, serum thyroid hormone concentrations showed significant correlations with spectral HRV parameters. Hyperthyroidism is in a sympathovagal imbalanced state, characterized by both increased sympathetic and decreased vagal modulation of the heart rate. These autonomic dysfunctions can be detected simultaneously by spectral analysis of HRV, and the spectral HRV parameters could reflect the disease severity in hyperthyroid patients.

Principal components analysis of Jupiter VIMS spectra

USGS Publications Warehouse

Bellucci, G.; Formisano, V.; D'Aversa, E.; Brown, R.H.; Baines, K.H.; Bibring, J.-P.; Buratti, B.J.; Capaccioni, F.; Cerroni, P.; Clark, R.N.; Coradini, A.; Cruikshank, D.P.; Drossart, P.; Jaumann, R.; Langevin, Y.; Matson, D.L.; McCord, T.B.; Mennella, V.; Nelson, R.M.; Nicholson, P.D.; Sicardy, B.; Sotin, Christophe; Chamberlain, M.C.; Hansen, G.; Hibbits, K.; Showalter, M.; Filacchione, G.

2004-01-01

During Cassini - Jupiter flyby occurred in December 2000, Visual-Infrared mapping spectrometer (VIMS) instrument took several image cubes of Jupiter at different phase angles and distances. We have analysed the spectral images acquired by the VIMS visual channel by means of a principal component analysis technique (PCA). The original data set consists of 96 spectral images in the 0.35-1.05 ??m wavelength range. The product of the analysis are new PC bands, which contain all the spectral variance of the original data. These new components have been used to produce a map of Jupiter made of seven coherent spectral classes. The map confirms previously published work done on the Great Red Spot by using NIMS data. Some other new findings, presently under investigation, are presented. ?? 2004 Published by Elsevier Ltd on behalf of COSPAR.

Proton exchange membrane fuel cell diagnosis by spectral characterization of the electrochemical noise

NASA Astrophysics Data System (ADS)

Maizia, R.; Dib, A.; Thomas, A.; Martemianov, S.

2017-02-01

Electrochemical noise analysis (ENA) has been performed for the diagnosis of proton-exchange membrane fuel cell (PEMFC) under various operating conditions. Its interest is related with the possibility of a non-invasive on-line diagnosis of a commercial fuel cell. A methodology of spectral analysis has been developed and an evaluation of the stationarity of the signal has been proposed. It has been revealed that the spectral signature of fuel cell, is a linear slope with a fractional power dependence 1/fα where α = 2 for different relative humidities and current densities. Experimental results reveal that the electrochemical noise is sensitive to the water management, especially under dry conditions. At RHH2 = 20% and RHair = 20%, spectral analysis shows a three linear slopes signature on the spectrum at low frequency range (f < 100 Hz). This results indicates that power spectral density, calculated thanks to FFT, can be used for the detection of an incorrect fuel cell water balance.

Detection of hidden mineral deposits by airborne spectral analysis of forest canopies. [Spirit Lake, Washington; Catheart Mountain, Maine; Blacktail Mountain, Montana; and Cotter Basin, Montana

NASA Technical Reports Server (NTRS)

Collins, W.; Chang, S. H.; Kuo, J. T.

1984-01-01

Data from field surveys and biogeochemical tests conducted in Maine, Montana, and Washington strongly correlate with results obtained using high resolution airborne spectroradiometer which detects an anomalous spectral waveform that appears definitely associated with sulfide mineralization. The spectral region most affected by mineral stress is between 550 nm and 750 nm. Spectral variations observed in the field occur on the wings of the red chlorophyll band centered at about 690 nm. The metal-stress-induced variations on the absorption band wing are most successfully resolved in the high spectral resolution field data using a waveform analysis technique. The development of chlorophyll pigments was retarded in greenhouse plants doped with copper and zinc in the laboratory. The lowered chlorophyll production resulted in changes on the wings of the chlorophyll bands of reflectance spectra of the plants. The airborne spectroradiometer system and waveform analysis remains the most sensitive technique for biogeochemical surveys.

Cospectral budget of turbulence explains the bulk properties of smooth pipe flow.

PubMed

Katul, Gabriel G; Manes, Costantino

2014-12-01

Connections between the wall-normal turbulent velocity spectrum E(ww)(k) at wave number k and the mean velocity profile (MVP) are explored in pressure-driven flows confined within smooth walls at moderate to high bulk Reynolds numbers (Re). These connections are derived via a cospectral budget for the longitudinal (u') and wall-normal (w') velocity fluctuations, which include a production term due to mean shear interacting with E(ww)(k), viscous effects, and a decorrelation between u' and w' by pressure-strain effects [=π(k)]. The π(k) is modeled using a conventional Rotta-like return-to-isotropy closure but adjusted to include the effects of isotropization of the production term. The resulting cospectral budget yields a generalization of a previously proposed "spectral link" between the MVP and the spectrum of turbulence. The proposed cospectral budget is also shown to reproduce the measured MVP across the pipe with changing Re including the MVP shapes in the buffer and wake regions. Because of the links between E(ww)(k) and the MVP, the effects of intermittency corrections to inertial subrange scales and the so-called spectral bottleneck reported as k approaches viscous dissipation eddy sizes (η) on the MVP shapes are investigated and shown to be of minor importance. Inclusion of a local Reynolds number correction to a parameter associated with the spectral exponential cutoff as kη→1 appears to be more significant to the MVP shape in the buffer region. While the bulk shape of the MVP is reasonably reproduced in all regions of the pipe, the solution to the cospectral budget systematically underestimates the negative curvature of the MVP within the buffer layer.

Perceptual suppression revealed by adaptive multi-scale entropy analysis of local field potential in monkey visual cortex.

PubMed

Hu, Meng; Liang, Hualou

2013-04-01

Generalized flash suppression (GFS), in which a salient visual stimulus can be rendered invisible despite continuous retinal input, provides a rare opportunity to directly study the neural mechanism of visual perception. Previous work based on linear methods, such as spectral analysis, on local field potential (LFP) during GFS has shown that the LFP power at distinctive frequency bands are differentially modulated by perceptual suppression. Yet, the linear method alone may be insufficient for the full assessment of neural dynamic due to the fundamentally nonlinear nature of neural signals. In this study, we set forth to analyze the LFP data collected from multiple visual areas in V1, V2 and V4 of macaque monkeys while performing the GFS task using a nonlinear method - adaptive multi-scale entropy (AME) - to reveal the neural dynamic of perceptual suppression. In addition, we propose a new cross-entropy measure at multiple scales, namely adaptive multi-scale cross-entropy (AMCE), to assess the nonlinear functional connectivity between two cortical areas. We show that: (1) multi-scale entropy exhibits percept-related changes in all three areas, with higher entropy observed during perceptual suppression; (2) the magnitude of the perception-related entropy changes increases systematically over successive hierarchical stages (i.e. from lower areas V1 to V2, up to higher area V4); and (3) cross-entropy between any two cortical areas reveals higher degree of asynchrony or dissimilarity during perceptual suppression, indicating a decreased functional connectivity between cortical areas. These results, taken together, suggest that perceptual suppression is related to a reduced functional connectivity and increased uncertainty of neural responses, and the modulation of perceptual suppression is more effective at higher visual cortical areas. AME is demonstrated to be a useful technique in revealing the underlying dynamic of nonlinear/nonstationary neural signal.

International scientific collaboration in HIV and HPV: a network analysis.

PubMed

Vanni, Tazio; Mesa-Frias, Marco; Sanchez-Garcia, Ruben; Roesler, Rafael; Schwartsmann, Gilberto; Goldani, Marcelo Z; Foss, Anna M

2014-01-01

Research endeavours require the collaborative effort of an increasing number of individuals. International scientific collaborations are particularly important for HIV and HPV co-infection studies, since the burden of disease is rising in developing countries, but most experts and research funds are found in developed countries, where the prevalence of HIV is low. The objective of our study was to investigate patterns of international scientific collaboration in HIV and HPV research using social network analysis. Through a systematic review of the literature, we obtained epidemiological data, as well as data on countries and authors involved in co-infection studies. The collaboration network was analysed in respect to the following: centrality, density, modularity, connected components, distance, clustering and spectral clustering. We observed that for many low- and middle-income countries there were no epidemiological estimates of HPV infection of the cervix among HIV-infected individuals. Most studies found only involved researchers from the same country (64%). Studies derived from international collaborations including high-income countries and either low- or middle-income countries had on average three times larger sample sizes than those including only high-income countries or low-income countries. The high global clustering coefficient (0.9) coupled with a short average distance between researchers (4.34) suggests a "small-world phenomenon." Researchers from high-income countries seem to have higher degree centrality and tend to cluster together in densely connected communities. We found a large well-connected community, which encompasses 70% of researchers, and 49 other small isolated communities. Our findings suggest that in the field of HIV and HPV, there seems to be both room and incentives for researchers to engage in collaborations between countries of different income-level. Through international collaboration resources available to researchers in high-income countries can be efficiently used to enroll more participants in low- and middle-income countries.

Discrimination between landmine and mine-like targets using wavelets and spectral analysis

NASA Astrophysics Data System (ADS)

Mohana, Mahmoud A.; Abbas, Abbas M.; Gomaa, Mohamed L.; Ebrahim, Shereen M.

2013-06-01

Landmine is an explosive apparatus hidden in or on the ground, which blows up when a person or vehicle passes over it. Egypt is one of the countries suffering due to the unexploded ordnance (UXO). Around 2 million UXO are present in the Egyptian soil especially at Al-Alameen province, north of the western desert. Detection of buried landmines is a problem of military and humanitarian importance. Ground penetrating radar (GPR) is a powerful and non-destructive geophysical approach with a wide range of advantages in the field of landmine inspection. In the present paper, we apply different simulation models with Vivaldi antenna and mine-like targets by using the CST Microwave studio program. The field work is carried out by using a GPR device of model SIR 2000 from GSSI (Geophysical Survey Systems Incorporation) connected to 900 MHz antenna where the targets were buried in sand soil. Depending on the fact that the receiving powers (reflected, refracted and scattered) from the different materials are different, we study the spectral power densities for the received power from the different targets. The techniques used in this study are: direct fast Fourier transform, short time Fourier transform (spectrogram), wavelets transform and denoising techniques. Our results ought to be considered as finger prints for different scanned targets during this work. So we can discriminate between landmines and mine-like targets.

A (likely) X-ray jet from NGC6217 observed by XMM-Newton

NASA Astrophysics Data System (ADS)

Falocco, Serena; Larsson, Josefin; Nandi, Sumana

2017-12-01

NGC6217 is a nearby spiral galaxy with a starburst region near its centre. Evidence for a low-luminosity Active Galactic Nucleus (AGN) in its core has also been found in optical spectra. Intriguingly, X-ray observations by ROSAT revealed three knots aligned with the galaxy centre, resembling a jet structure. This paper presents a study of XMM-Newton observations made to assess the hypothesis of a jet emitted from the centre of NGC6217. The XMM data confirm the knots found with ROSAT and our spectral analysis shows that they have similar spectral properties with a hard photon index Γ ∼ 1.7. The core of NGC6217 is well fitted by a model with an AGN and a starburst component, where the AGN contributes at most 46 per cent of the total flux. The candidate jet has an apparent length ∼15 kpc and a luminosity of ∼5 × 1038 erg s- 1. It stands out by being hosted by a spiral galaxy, since jets are more widely associated with ellipticals. To explain the jet launching mechanism we consider the hypothesis of an advection dominated accretion flow with a low accretion rate. The candidate jet emitted from NGC6217 is intriguing since it represents a challenge to the current knowledge of the connection between AGN, jets and host galaxies.

Laterality of basic auditory perception.

PubMed

Sininger, Yvonne S; Bhatara, Anjali

2012-01-01

Laterality (left-right ear differences) of auditory processing was assessed using basic auditory skills: (1) gap detection, (2) frequency discrimination, and (3) intensity discrimination. Stimuli included tones (500, 1000, and 4000 Hz) and wide-band noise presented monaurally to each ear of typical adult listeners. The hypothesis tested was that processing of tonal stimuli would be enhanced by left ear (LE) stimulation and noise by right ear (RE) presentations. To investigate the limits of laterality by (1) spectral width, a narrow-band noise (NBN) of 450-Hz bandwidth was evaluated using intensity discrimination, and (2) stimulus duration, 200, 500, and 1000 ms duration tones were evaluated using frequency discrimination. A left ear advantage (LEA) was demonstrated with tonal stimuli in all experiments, but an expected REA for noise stimuli was not found. The NBN stimulus demonstrated no LEA and was characterised as a noise. No change in laterality was found with changes in stimulus durations. The LEA for tonal stimuli is felt to be due to more direct connections between the left ear and the right auditory cortex, which has been shown to be primary for spectral analysis and tonal processing. The lack of a REA for noise stimuli is unexplained. Sex differences in laterality for noise stimuli were noted but were not statistically significant. This study did establish a subtle but clear pattern of LEA for processing of tonal stimuli.

Laterality of Basic Auditory Perception

PubMed Central

Sininger, Yvonne S.; Bhatara, Anjali

2010-01-01

Laterality (left-right ear differences) of auditory processing was assessed using basic auditory skills: 1) gap detection 2) frequency discrimination and 3) intensity discrimination. Stimuli included tones (500, 1000 and 4000 Hz) and wide-band noise presented monaurally to each ear of typical adult listeners. The hypothesis tested was: processing of tonal stimuli would be enhanced by left ear (LE) stimulation and noise by right ear (RE) presentations. To investigate the limits of laterality by 1) spectral width, a narrow band noise (NBN) of 450 Hz bandwidth was evaluated using intensity discrimination and 2) stimulus duration, 200, 500 and 1000 ms duration tones were evaluated using frequency discrimination. Results A left ear advantage (LEA) was demonstrated with tonal stimuli in all experiments but an expected REA for noise stimuli was not found. The NBN stimulus demonstrated no LEA and was characterized as a noise. No change in laterality was found with changes in stimulus durations. The LEA for tonal stimuli is felt to be due to more direct connections between the left ear and the right auditory cortex which has been shown to be primary for spectral analysis and tonal processing. The lack of a REA for noise stimuli is unexplained. Sex differences in laterality for noise stimuli were noted but were not statistically significant. This study did establish a subtle but clear pattern of LEA for processing of tonal stimuli. PMID:22385138

A method for the estimation of the significance of cross-correlations in unevenly sampled red-noise time series

NASA Astrophysics Data System (ADS)

Max-Moerbeck, W.; Richards, J. L.; Hovatta, T.; Pavlidou, V.; Pearson, T. J.; Readhead, A. C. S.

2014-11-01

We present a practical implementation of a Monte Carlo method to estimate the significance of cross-correlations in unevenly sampled time series of data, whose statistical properties are modelled with a simple power-law power spectral density. This implementation builds on published methods; we introduce a number of improvements in the normalization of the cross-correlation function estimate and a bootstrap method for estimating the significance of the cross-correlations. A closely related matter is the estimation of a model for the light curves, which is critical for the significance estimates. We present a graphical and quantitative demonstration that uses simulations to show how common it is to get high cross-correlations for unrelated light curves with steep power spectral densities. This demonstration highlights the dangers of interpreting them as signs of a physical connection. We show that by using interpolation and the Hanning sampling window function we are able to reduce the effects of red-noise leakage and to recover steep simple power-law power spectral densities. We also introduce the use of a Neyman construction for the estimation of the errors in the power-law index of the power spectral density. This method provides a consistent way to estimate the significance of cross-correlations in unevenly sampled time series of data.

Software algorithm and hardware design for real-time implementation of new spectral estimator

PubMed Central

2014-01-01

Background Real-time spectral analyzers can be difficult to implement for PC computer-based systems because of the potential for high computational cost, and algorithm complexity. In this work a new spectral estimator (NSE) is developed for real-time analysis, and compared with the discrete Fourier transform (DFT). Method Clinical data in the form of 216 fractionated atrial electrogram sequences were used as inputs. The sample rate for acquisition was 977 Hz, or approximately 1 millisecond between digital samples. Real-time NSE power spectra were generated for 16,384 consecutive data points. The same data sequences were used for spectral calculation using a radix-2 implementation of the DFT. The NSE algorithm was also developed for implementation as a real-time spectral analyzer electronic circuit board. Results The average interval for a single real-time spectral calculation in software was 3.29 μs for NSE versus 504.5 μs for DFT. Thus for real-time spectral analysis, the NSE algorithm is approximately 150× faster than the DFT. Over a 1 millisecond sampling period, the NSE algorithm had the capability to spectrally analyze a maximum of 303 data channels, while the DFT algorithm could only analyze a single channel. Moreover, for the 8 second sequences, the NSE spectral resolution in the 3-12 Hz range was 0.037 Hz while the DFT spectral resolution was only 0.122 Hz. The NSE was also found to be implementable as a standalone spectral analyzer board using approximately 26 integrated circuits at a cost of approximately $500. The software files used for analysis are included as a supplement, please see the Additional files 1 and 2. Conclusions The NSE real-time algorithm has low computational cost and complexity, and is implementable in both software and hardware for 1 millisecond updates of multichannel spectra. The algorithm may be helpful to guide radiofrequency catheter ablation in real time. PMID:24886214

Mapping minerals, amorphous materials, environmental materials, vegetation, water, ice and snow, and other materials: The USGS tricorder algorithm

NASA Technical Reports Server (NTRS)

Clark, Roger N.; Swayze, Gregg A.

1995-01-01

One of the challenges of Imaging Spectroscopy is the identification, mapping and abundance determination of materials, whether mineral, vegetable, or liquid, given enough spectral range, spectral resolution, signal to noise, and spatial resolution. Many materials show diagnostic absorption features in the visual and near infrared region (0.4 to 2.5 micrometers) of the spectrum. This region is covered by the modern imaging spectrometers such as AVIRIS. The challenge is to identify the materials from absorption bands in their spectra, and determine what specific analyses must be done to derive particular parameters of interest, ranging from simply identifying its presence to deriving its abundance, or determining specific chemistry of the material. Recently, a new analysis algorithm was developed that uses a digital spectral library of known materials and a fast, modified-least-squares method of determining if a single spectral feature for a given material is present. Clark et al. made another advance in the mapping algorithm: simultaneously mapping multiple minerals using multiple spectral features. This was done by a modified-least-squares fit of spectral features, from data in a digital spectral library, to corresponding spectral features in the image data. This version has now been superseded by a more comprehensive spectral analysis system called Tricorder.

Using Separable Nonnegative Matrix Factorization Techniques for the Analysis of Time-Resolved Raman Spectra.

PubMed

Luce, Robert; Hildebrandt, Peter; Kuhlmann, Uwe; Liesen, Jörg

2016-09-01

The key challenge of time-resolved Raman spectroscopy is the identification of the constituent species and the analysis of the kinetics of the underlying reaction network. In this work we present an integral approach that allows for determining both the component spectra and the rate constants simultaneously from a series of vibrational spectra. It is based on an algorithm for nonnegative matrix factorization that is applied to the experimental data set following a few pre-processing steps. As a prerequisite for physically unambiguous solutions, each component spectrum must include one vibrational band that does not significantly interfere with the vibrational bands of other species. The approach is applied to synthetic "experimental" spectra derived from model systems comprising a set of species with component spectra differing with respect to their degree of spectral interferences and signal-to-noise ratios. In each case, the species involved are connected via monomolecular reaction pathways. The potential and limitations of the approach for recovering the respective rate constants and component spectra are discussed. © The Author(s) 2016.

ON THE HOST GALAXY OF GRB 150101B AND THE ASSOCIATED ACTIVE GALACTIC NUCLEUS

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

Xie, Chen; Fang, Taotao; Wang, Junfeng

We present a multi-wavelength analysis of the host galaxy of short-duration gamma-ray burst (GRB) 150101B. Follow-up optical and X-ray observations suggested that the host galaxy, 2MASX J12320498-1056010, likely harbors low-luminosity active galactic nuclei (AGNs). Our modeling of the spectral energy distribution has confirmed the nature of the AGN, making it the first reported GRB host that contains an AGN. We have also found the host galaxy is a massive elliptical galaxy with stellar population of ∼5.7 Gyr, one of the oldest among the short-duration GRB hosts. Our analysis suggests that the host galaxy can be classified as an X-ray bright,more » optically normal galaxy, and the central AGN is likely dominated by a radiatively inefficient accretion flow. Our work explores an interesting connection that may exist between GRB and AGN activities of the host galaxy, which can help in understanding the host environment of the GRB events and the roles of AGN feedback.« less

Spectral characteristics of Shuttle glow

NASA Technical Reports Server (NTRS)

Viereck, R. A.; Mende, S. B.; Murad, E.; Swenson, G. R.; Pike, C. P.; Culbertson, F. L.; Springer, R. C.

1992-01-01

The glowing cloud near the ram surfaces of the Space Shuttle was observed with a hand-held, intensified spectrograph operated by the astronauts from the aft-flight-deck of the Space Shuttle. The spectral measurements were made between 400 and 800 nm with a resolution of 3 nm. Analysis of the spectral response of the instrument and the transmission of the Shuttle window was performed on orbit using earth-airglow OH Meinel bands. This analysis resulted in a correction of the Shuttle glow intensity in the spectral region between 700 and 800 nm. The data presented in this report is in better agreement with laboratory measurements of the NO2 continuum.

Demodulation circuit for AC motor current spectral analysis

DOEpatents

Hendrix, Donald E.; Smith, Stephen F.

1990-12-18

A motor current analysis method for the remote, noninvasive inspection of electric motor-operated systems. Synchronous amplitude demodulation and phase demodulation circuits are used singly and in combination along with a frequency analyzer to produce improved spectral analysis of load-induced frequencies present in the electric current flowing in a motor-driven system.

Spectral analysis of the Crab Nebula and GRB 160530A with the Compton Spectrometer and Imager

NASA Astrophysics Data System (ADS)

Sleator, Clio; Boggs, Steven E.; Chiu, Jeng-Lun; Kierans, Carolyn; Lowell, Alexander; Tomsick, John; Zoglauer, Andreas; Amman, Mark; Chang, Hsiang-Kuang; Tseng, Chao-Hsiung; Yang, Chien-Ying; Lin, Chih H.; Jean, Pierre; von Ballmoos, Peter

2017-08-01

The Compton Spectrometer and Imager (COSI) is a balloon-borne soft gamma-ray (0.2-5 MeV) telescope designed to study astrophysical sources including gamma-ray bursts and compact objects. As a compact Compton telescope, COSI has inherent sensitivity to polarization. COSI utilizes 12 germanium detectors to provide excellent spectral resolution. On May 17, 2016, COSI was launched from Wanaka, New Zealand and completed a successful 46-day flight on NASA’s new Superpressure balloon. To perform spectral analysis with COSI, we have developed an accurate instrument model as required for the response matrix. With carefully chosen background regions, we are able to fit the background-subtracted spectra in XSPEC. We have developed a model of the atmosphere above COSI based on the NRLMSISE-00 Atmosphere Model to include in our spectral fits. The Crab and GRB 160530A are among the sources detected during the 2016 flight. We present spectral analysis of these two point sources. Our GRB 160530A results are consistent with those from other instruments, confirming COSI’s spectral abilities. Furthermore, we discuss prospects for measuring the Crab polarization with COSI.

Using foreground/background analysis to determine leaf and canopy chemistry

NASA Technical Reports Server (NTRS)

Pinzon, J. E.; Ustin, S. L.; Hart, Q. J.; Jacquemoud, S.; Smith, M. O.

1995-01-01

Spectral Mixture Analysis (SMA) has become a well established procedure for analyzing imaging spectrometry data, however, the technique is relatively insensitive to minor sources of spectral variation (e.g., discriminating stressed from unstressed vegetation and variations in canopy chemistry). Other statistical approaches have been tried e.g., stepwise multiple linear regression analysis to predict canopy chemistry. Grossman et al. reported that SMLR is sensitive to measurement error and that the prediction of minor chemical components are not independent of patterns observed in more dominant spectral components like water. Further, they observed that the relationships were strongly dependent on the mode of expressing reflectance (R, -log R) and whether chemistry was expressed on a weight (g/g) or are basis (g/sq m). Thus, alternative multivariate techniques need to be examined. Smith et al. reported a revised SMA that they termed Foreground/Background Analysis (FBA) that permits directing the analysis along any axis of variance by identifying vectors through the n-dimensional spectral volume orthonormal to each other. Here, we report an application of the FBA technique for the detection of canopy chemistry using a modified form of the analysis.

Spectral analysis comparisons of Fourier-theory-based methods and minimum variance (Capon) methods

NASA Astrophysics Data System (ADS)

Garbanzo-Salas, Marcial; Hocking, Wayne. K.

2015-09-01

In recent years, adaptive (data dependent) methods have been introduced into many areas where Fourier spectral analysis has traditionally been used. Although the data-dependent methods are often advanced as being superior to Fourier methods, they do require some finesse in choosing the order of the relevant filters. In performing comparisons, we have found some concerns about the mappings, particularly when related to cases involving many spectral lines or even continuous spectral signals. Using numerical simulations, several comparisons between Fourier transform procedures and minimum variance method (MVM) have been performed. For multiple frequency signals, the MVM resolves most of the frequency content only for filters that have more degrees of freedom than the number of distinct spectral lines in the signal. In the case of Gaussian spectral approximation, MVM will always underestimate the width, and can misappropriate the location of spectral line in some circumstances. Large filters can be used to improve results with multiple frequency signals, but are computationally inefficient. Significant biases can occur when using MVM to study spectral information or echo power from the atmosphere. Artifacts and artificial narrowing of turbulent layers is one such impact.

Imaging spectroscopy: Earth and planetary remote sensing with the USGS Tetracorder and expert systems

USGS Publications Warehouse

Clark, Roger N.; Swayze, Gregg A.; Livo, K. Eric; Kokaly, Raymond F.; Sutley, Steve J.; Dalton, J. Brad; McDougal, Robert R.; Gent, Carol A.

2003-01-01

Imaging spectroscopy is a tool that can be used to spectrally identify and spatially map materials based on their specific chemical bonds. Spectroscopic analysis requires significantly more sophistication than has been employed in conventional broadband remote sensing analysis. We describe a new system that is effective at material identification and mapping: a set of algorithms within an expert system decision‐making framework that we call Tetracorder. The expertise in the system has been derived from scientific knowledge of spectral identification. The expert system rules are implemented in a decision tree where multiple algorithms are applied to spectral analysis, additional expert rules and algorithms can be applied based on initial results, and more decisions are made until spectral analysis is complete. Because certain spectral features are indicative of specific chemical bonds in materials, the system can accurately identify and map those materials. In this paper we describe the framework of the decision making process used for spectral identification, describe specific spectral feature analysis algorithms, and give examples of what analyses and types of maps are possible with imaging spectroscopy data. We also present the expert system rules that describe which diagnostic spectral features are used in the decision making process for a set of spectra of minerals and other common materials. We demonstrate the applications of Tetracorder to identify and map surface minerals, to detect sources of acid rock drainage, and to map vegetation species, ice, melting snow, water, and water pollution, all with one set of expert system rules. Mineral mapping can aid in geologic mapping and fault detection and can provide a better understanding of weathering, mineralization, hydrothermal alteration, and other geologic processes. Environmental site assessment, such as mapping source areas of acid mine drainage, has resulted in the acceleration of site cleanup, saving millions of dollars and years in cleanup time. Imaging spectroscopy data and Tetracorder analysis can be used to study both terrestrial and planetary science problems. Imaging spectroscopy can be used to probe planetary systems, including their atmospheres, oceans, and land surfaces.

Spectral characterization of the LANDSAT thematic mapper sensors

NASA Technical Reports Server (NTRS)

Markham, B. L.; Barker, J. L.

1983-01-01

Data collected on the spectral characteristics of the LANDSAT-4 and LANDSAT-4 backup thematic mapper instruments, the protoflight (TM/PF) and flight (TM/F) models, respectively, are presented and analyzed. Tests were conducted on the instruments and their components to determine compliance with two sets of spectral specifications: band-by-band spectral coverage and channel-by-channel within-band spectral matching. Spectral coverage specifications were placed on: (1) band edges--points at 50% of peak response, (2) band edge slopes--steepness of rise and fall-off of response, (3) spectral flatness--evenness of response between edges, and (4) spurious system response--ratio of out-of-band response to in-band response. Compliance with the spectral coverage specifications was determined by analysis of spectral measurements on the individual components contributing to the overall spectral response: filters, detectors, and optical surfaces.

Spectral dependence of texture features integrated with hyperspectral data for area target classification improvement

NASA Astrophysics Data System (ADS)

Bangs, Corey F.; Kruse, Fred A.; Olsen, Chris R.

2013-05-01

Hyperspectral data were assessed to determine the effect of integrating spectral data and extracted texture feature data on classification accuracy. Four separate spectral ranges (hundreds of spectral bands total) were used from the Visible and Near Infrared (VNIR) and Shortwave Infrared (SWIR) portions of the electromagnetic spectrum. Haralick texture features (contrast, entropy, and correlation) were extracted from the average gray-level image for each of the four spectral ranges studied. A maximum likelihood classifier was trained using a set of ground truth regions of interest (ROIs) and applied separately to the spectral data, texture data, and a fused dataset containing both. Classification accuracy was measured by comparison of results to a separate verification set of test ROIs. Analysis indicates that the spectral range (source of the gray-level image) used to extract the texture feature data has a significant effect on the classification accuracy. This result applies to texture-only classifications as well as the classification of integrated spectral data and texture feature data sets. Overall classification improvement for the integrated data sets was near 1%. Individual improvement for integrated spectral and texture classification of the "Urban" class showed approximately 9% accuracy increase over spectral-only classification. Texture-only classification accuracy was highest for the "Dirt Path" class at approximately 92% for the spectral range from 947 to 1343nm. This research demonstrates the effectiveness of texture feature data for more accurate analysis of hyperspectral data and the importance of selecting the correct spectral range to be used for the gray-level image source to extract these features.

A solar radio dynamic spectrograph with flexible temporal-spectral resolution

NASA Astrophysics Data System (ADS)

Du, Qing-Fu; Chen, Lei; Zhao, Yue-Chang; Li, Xin; Zhou, Yan; Zhang, Jun-Rui; Yan, Fa-Bao; Feng, Shi-Wei; Li, Chuan-Yang; Chen, Yao

2017-09-01

Observation and research on solar radio emission have unique scientific values in solar and space physics and related space weather forecasting applications, since the observed spectral structures may carry important information about energetic electrons and underlying physical mechanisms. In this study, we present the design of a novel dynamic spectrograph that has been installed at the Chashan Solar Radio Observatory operated by the Laboratory for Radio Technologies, Institute of Space Sciences at Shandong University. The spectrograph is characterized by real-time storage of digitized radio intensity data in the time domain and its capability to perform off-line spectral analysis of the radio spectra. The analog signals received via antennas and amplified with a low-noise amplifier are converted into digital data at a speed reaching up to 32 k data points per millisecond. The digital data are then saved into a high-speed electronic disk for further off-line spectral analysis. Using different word lengths (1-32 k) and time cadences (5 ms-10 s) for off-line fast Fourier transform analysis, we can obtain the dynamic spectrum of a radio burst with different (user-defined) temporal (5 ms-10 s) and spectral (3 kHz˜320 kHz) resolutions. This enables great flexibility and convenience in data analysis of solar radio bursts, especially when some specific fine spectral structures are under study.

Quantitative Analysis of Spectral Interference of Spontaneous Raman Scattering in High-Pressure Fuel-Rich H2-Air Combustion

NASA Technical Reports Server (NTRS)

Kojima, Jun; Nguyen, Quang-Viet

2004-01-01

We present a theoretical study of the spectral interferences in the spontaneous Raman scattering spectra of major combustion products in 30-atm fuel-rich hydrogen-air flames. An effective methodology is introduced to choose an appropriate line-shape model for simulating Raman spectra in high-pressure combustion environments. The Voigt profile with the additive approximation assumption was found to provide a reasonable model of the spectral line shape for the present analysis. The rotational/vibrational Raman spectra of H2, N2, and H2O were calculated using an anharmonic-oscillator model using the latest collisional broadening coefficients. The calculated spectra were validated with data obtained in a 10-atm fuel-rich H2-air flame and showed excellent agreement. Our quantitative spectral analysis for equivalence ratios ranging from 1.5 to 5.0 revealed substantial amounts of spectral cross-talk between the rotational H2 lines and the N2 O-/Q-branch; and between the vibrational H2O(0,3) line and the vibrational H2O spectrum. We also address the temperature dependence of the spectral cross-talk and extend our analysis to include a cross-talk compensation technique that removes the nterference arising from the H2 Raman spectra onto the N2, or H2O spectra.

A Spiking Neurocomputational Model of High-Frequency Oscillatory Brain Responses to Words and Pseudowords

PubMed Central

Garagnani, Max; Lucchese, Guglielmo; Tomasello, Rosario; Wennekers, Thomas; Pulvermüller, Friedemann

2017-01-01

Experimental evidence indicates that neurophysiological responses to well-known meaningful sensory items and symbols (such as familiar objects, faces, or words) differ from those to matched but novel and senseless materials (unknown objects, scrambled faces, and pseudowords). Spectral responses in the high beta- and gamma-band have been observed to be generally stronger to familiar stimuli than to unfamiliar ones. These differences have been hypothesized to be caused by the activation of distributed neuronal circuits or cell assemblies, which act as long-term memory traces for learned familiar items only. Here, we simulated word learning using a biologically constrained neurocomputational model of the left-hemispheric cortical areas known to be relevant for language and conceptual processing. The 12-area spiking neural-network architecture implemented replicates physiological and connectivity features of primary, secondary, and higher-association cortices in the frontal, temporal, and occipital lobes of the human brain. We simulated elementary aspects of word learning in it, focussing specifically on semantic grounding in action and perception. As a result of spike-driven Hebbian synaptic plasticity mechanisms, distributed, stimulus-specific cell-assembly (CA) circuits spontaneously emerged in the network. After training, presentation of one of the learned “word” forms to the model correlate of primary auditory cortex induced periodic bursts of activity within the corresponding CA, leading to oscillatory phenomena in the entire network and spontaneous across-area neural synchronization. Crucially, Morlet wavelet analysis of the network's responses recorded during presentation of learned meaningful “word” and novel, senseless “pseudoword” patterns revealed stronger induced spectral power in the gamma-band for the former than the latter, closely mirroring differences found in neurophysiological data. Furthermore, coherence analysis of the simulated responses uncovered dissociated category specific patterns of synchronous oscillations in distant cortical areas, including indirectly connected primary sensorimotor areas. Bridging the gap between cellular-level mechanisms, neuronal-population behavior, and cognitive function, the present model constitutes the first spiking, neurobiologically, and anatomically realistic model able to explain high-frequency oscillatory phenomena indexing language processing on the basis of dynamics and competitive interactions of distributed cell-assembly circuits which emerge in the brain as a result of Hebbian learning and sensorimotor experience. PMID:28149276

Biologically-inspired data decorrelation for hyper-spectral imaging

NASA Astrophysics Data System (ADS)

Picon, Artzai; Ghita, Ovidiu; Rodriguez-Vaamonde, Sergio; Iriondo, Pedro Ma; Whelan, Paul F.

2011-12-01

Hyper-spectral data allows the construction of more robust statistical models to sample the material properties than the standard tri-chromatic color representation. However, because of the large dimensionality and complexity of the hyper-spectral data, the extraction of robust features (image descriptors) is not a trivial issue. Thus, to facilitate efficient feature extraction, decorrelation techniques are commonly applied to reduce the dimensionality of the hyper-spectral data with the aim of generating compact and highly discriminative image descriptors. Current methodologies for data decorrelation such as principal component analysis (PCA), linear discriminant analysis (LDA), wavelet decomposition (WD), or band selection methods require complex and subjective training procedures and in addition the compressed spectral information is not directly related to the physical (spectral) characteristics associated with the analyzed materials. The major objective of this article is to introduce and evaluate a new data decorrelation methodology using an approach that closely emulates the human vision. The proposed data decorrelation scheme has been employed to optimally minimize the amount of redundant information contained in the highly correlated hyper-spectral bands and has been comprehensively evaluated in the context of non-ferrous material classification

Stable homotopical algebra and [Gamma]-spaces

NASA Astrophysics Data System (ADS)

Schwede, Stefan

1999-03-01

In this paper we advertise the category of [Gamma]-spaces as a convenient framework for doing ‘algebra’ over ‘rings’ in stable homotopy theory. [Gamma]-spaces were introduced by Segal [Se] who showed that they give rise to a homotopy category equivalent to the usual homotopy category of connective (i.e. ([minus sign]1)-connected) spectra. Bousfield and Friedlander [BF] later provided model category structures for [Gamma]-spaces. The study of ‘rings, modules and algebras’ based on [Gamma]-spaces became possible when Lydakis [Ly] introduced a symmetric monoidal smash product with good homotopical properties. Here we develop model category structures for modules and algebras, set up (derived) smash products and associated spectral sequences and compare simplicial modules and algebras to their Eilenberg-MacLane spectra counterparts.

[Review of digital ground object spectral library].

PubMed

Zhou, Xiao-Hu; Zhou, Ding-Wu

2009-06-01

A higher spectral resolution is the main direction of developing remote sensing technology, and it is quite important to set up the digital ground object reflectance spectral database library, one of fundamental research fields in remote sensing application. Remote sensing application has been increasingly relying on ground object spectral characteristics, and quantitative analysis has been developed to a new stage. The present article summarized and systematically introduced the research status quo and development trend of digital ground object reflectance spectral libraries at home and in the world in recent years. Introducing the spectral libraries has been established, including desertification spectral database library, plants spectral database library, geological spectral database library, soil spectral database library, minerals spectral database library, cloud spectral database library, snow spectral database library, the atmosphere spectral database library, rocks spectral database library, water spectral database library, meteorites spectral database library, moon rock spectral database library, and man-made materials spectral database library, mixture spectral database library, volatile compounds spectral database library, and liquids spectral database library. In the process of establishing spectral database libraries, there have been some problems, such as the lack of uniform national spectral database standard and uniform standards for the ground object features as well as the comparability between different databases. In addition, data sharing mechanism can not be carried out, etc. This article also put forward some suggestions on those problems.

Multi range spectral feature fitting for hyperspectral imagery in extracting oilseed rape planting area

NASA Astrophysics Data System (ADS)

Pan, Zhuokun; Huang, Jingfeng; Wang, Fumin

2013-12-01

Spectral feature fitting (SFF) is a commonly used strategy for hyperspectral imagery analysis to discriminate ground targets. Compared to other image analysis techniques, SFF does not secure higher accuracy in extracting image information in all circumstances. Multi range spectral feature fitting (MRSFF) from ENVI software allows user to focus on those interesting spectral features to yield better performance. Thus spectral wavelength ranges and their corresponding weights must be determined. The purpose of this article is to demonstrate the performance of MRSFF in oilseed rape planting area extraction. A practical method for defining the weighted values, the variance coefficient weight method, was proposed to set up criterion. Oilseed rape field canopy spectra from the whole growth stage were collected prior to investigating its phenological varieties; oilseed rape endmember spectra were extracted from the Hyperion image as identifying samples to be used in analyzing the oilseed rape field. Wavelength range divisions were determined by the difference between field-measured spectra and image spectra, and image spectral variance coefficient weights for each wavelength range were calculated corresponding to field-measured spectra from the closest date. By using MRSFF, wavelength ranges were classified to characterize the target's spectral features without compromising spectral profile's entirety. The analysis was substantially successful in extracting oilseed rape planting areas (RMSE ≤ 0.06), and the RMSE histogram indicated a superior result compared to a conventional SFF. Accuracy assessment was based on the mapping result compared with spectral angle mapping (SAM) and the normalized difference vegetation index (NDVI). The MRSFF yielded a robust, convincible result and, therefore, may further the use of hyperspectral imagery in precision agriculture.

The stellar wind as a key to the understanding of the spectral activity of IN Com

NASA Astrophysics Data System (ADS)

Kozlova, O. V.; Alekseev, I. Yu.

2014-06-01

We present long-term spectral observations ( R = 20000) of IN Com in the region of the Hα, Hβ, and He I 5876 lines. One distinguishing characteristic of the stellar spectrum is the presence in the Hα line of an extended two-component emission with limits up to ±400 km/s. Emission parameters show the rotation modulation with the stellar rotation period and a significant variability on the long-term scale. Similar emissions are also observed in the Hβ and He I 5876 lines. Our results allow us to conclude that observational emission profiles are formed in an optically thin hot gas. This is a result of the presence of a circumstellar gas disk around IN Com. Its size does not exceed several stellar radii. The material for the disk is supported by the stellar wind from IN Com. The detected variability of Hα-emission parameters shows a clear connection with the photopolarimetric activity of the star. This fact allows us to associate the long-term spectral variability with cycles of stellar activity of IN Com.

Soil spectral measurements in the field: problems and solutions in light of the GEO-CARDEL project

NASA Astrophysics Data System (ADS)

Dor, E. Ben; Granot, Amihai

2017-09-01

The GEO-CRADEL project aims to establish several knowhow for GEO applications. One of them is food security in which soil spectroscopy plays a major role. To that end we had developed a new assembly for measuring surface reflectance in the field. This was done in order to fill the gap between laboratory and field soil spectral measurements. This device, named SoilPRO (SP) can be connected to any field spectrometer fiber's tip and used to measure representative and undisturbed surfaces of different soil types. The SoilPRO's performance was evaluated against laboratory measurements under optimal conditions and demonstrated high performance in the field. As the SP measurement is not dependent on main factors such as the sun's radiation, atmospheric variations, operator stability or measurement geometry, and it does not disturb the surface being measured, its measurement can be used with laboratory soil spectral data (SSL). To that end the SSL that is generated under the GEO-CARDEL project is now can be used for agro- application in the field.

Distortion in the thermal noise spectrum and quality factor of nanomechanical devices due to finite frequency resolution with applications to the atomic force microscope.

PubMed

Sader, John E; Sanelli, Julian; Hughes, Barry D; Monty, Jason P; Bieske, Evan J

2011-09-01

The thermal noise spectrum of nanomechanical devices is commonly used to characterize their mechanical properties and energy dissipation. This spectrum is measured from finite time series of Brownian motion of the device, which is windowed and Fourier transformed. Here, we present a theoretical and experimental investigation of the effect of such finite sampling on the measured device quality factor. We prove that if no spectral window is used, the thermal noise spectrum retains its original Lorentzian distribution but with a reduced quality factor, indicating an apparent enhancement in energy dissipation. A simple analytical formula is derived connecting the true and measured quality factors - this enables extraction of the true device quality factor from measured data. Common windows used to reduce spectral leakage are found to distort the (true) Lorentzian shape, potentially making fitting problematic. These findings are expected to be of particular importance for devices with high quality factors, where spectral resolution can be limited in practice. Comparison and validation using measurements on atomic force microscope cantilevers are presented. © 2011 American Institute of Physics

Long baseline planar superconducting gradiometer for biomagnetic imaging

NASA Astrophysics Data System (ADS)

Granata, C.; Vettoliere, A.; Nappi, C.; Lisitskiy, M.; Russo, M.

2009-07-01

A niobium based dc-superconducting quantum interference device (SQUID) planar gradiometer with a long baseline (50 mm) for biomagnetic applications has been developed. The pickup antenna consists of two integrated rectangular coils connected in series and magnetically coupled to a dc-SQUID in a double parallel washer configuration by two series multiturn input coils. Due to a high intrinsic responsivity, the sensors have shown at T =4.2 K a white magnetic flux noise spectral density as low as 3 μΦ0/Hz1/2. The spectral density of the magnetic field noise referred to one sensing coil, is 3.0 fT/Hz1/2 resulting in a gradient spectral noise of 0.6 fT/(cm Hz1/2). In order to verify the effectiveness of such sensors for biomagnetic applications, the magnetic response to a current dipole has been calculated and the results have been compared with those of an analogous axial gradiometer. The results show that there is no significant difference. Due to their high intrinsic balance and good performances, planar gradiometers may be the elective sensors for biomagnetic application in a soft shielded environment.

Spectral and geometrical variation of the bidirectional reflectance distribution function of diffuse reflectance standards.

PubMed

Ferrero, Alejandro; Rabal, Ana María; Campos, Joaquín; Pons, Alicia; Hernanz, María Luisa

2012-12-20

A study on the variation of the spectral bidirectional reflectance distribution function (BRDF) of four diffuse reflectance standards (matte ceramic, BaSO(4), Spectralon, and white Russian opal glass) is accomplished through this work. Spectral BRDF measurements were carried out and, using principal components analysis, its spectral and geometrical variation respect to a reference geometry was assessed from the experimental data. Several descriptors were defined in order to compare the spectral BRDF variation of the four materials.

Glycan characterization of the NIST RM monoclonal antibody using a total analytical solution: From sample preparation to data analysis.

PubMed

Hilliard, Mark; Alley, William R; McManus, Ciara A; Yu, Ying Qing; Hallinan, Sinead; Gebler, John; Rudd, Pauline M

Glycosylation is an important attribute of biopharmaceutical products to monitor from development through production. However, glycosylation analysis has traditionally been a time-consuming process with long sample preparation protocols and manual interpretation of the data. To address the challenges associated with glycan analysis, we developed a streamlined analytical solution that covers the entire process from sample preparation to data analysis. In this communication, we describe the complete analytical solution that begins with a simplified and fast N-linked glycan sample preparation protocol that can be completed in less than 1 hr. The sample preparation includes labelling with RapiFluor-MS tag to improve both fluorescence (FLR) and mass spectral (MS) sensitivities. Following HILIC-UPLC/FLR/MS analyses, the data are processed and a library search based on glucose units has been included to expedite the task of structural assignment. We then applied this total analytical solution to characterize the glycosylation of the NIST Reference Material mAb 8761. For this glycoprotein, we confidently identified 35 N-linked glycans and all three major classes, high mannose, complex, and hybrid, were present. The majority of the glycans were neutral and fucosylated; glycans featuring N-glycolylneuraminic acid and those with two galactoses connected via an α1,3-linkage were also identified.

Testing Proposed Neuronal Models of Effective Connectivity Within the Cortico-basal Ganglia-thalamo-cortical Loop During Loss of Consciousness.

PubMed

Crone, Julia Sophia; Lutkenhoff, Evan Scott; Bio, Branden Joseph; Laureys, Steven; Monti, Martin Max

2017-04-01

In recent years, a number of brain regions and connectivity patterns have been proposed to be crucial for loss and recovery of consciousness but have not been compared in detail. In a 3 T resting-state functional magnetic resonance imaging paradigm, we test the plausibility of these different neuronal models derived from theoretical and empirical knowledge. Specifically, we assess the fit of each model to the dynamic change in effective connectivity between specific cortical and subcortical regions at different consecutive levels of propofol-induced sedation by employing spectral dynamic causal modeling. Surprisingly, our findings indicate that proposed models of impaired consciousness do not fit the observed patterns of effective connectivity. Rather, the data show that loss of consciousness, at least in the context of propofol-induced sedation, is marked by a breakdown of corticopetal projections from the globus pallidus. Effective connectivity between the globus pallidus and the ventral posterior cingulate cortex, present during wakefulness, fades in the transition from lightly sedated to full loss of consciousness and returns gradually as consciousness recovers, thereby, demonstrating the dynamic shift in brain architecture of the posterior cingulate "hub" during changing states of consciousness. These findings highlight the functional role of a previously underappreciated direct pallido-cortical connectivity in supporting consciousness. © The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

Tracking slow modulations in synaptic gain using dynamic causal modelling: validation in epilepsy.

PubMed

Papadopoulou, Margarita; Leite, Marco; van Mierlo, Pieter; Vonck, Kristl; Lemieux, Louis; Friston, Karl; Marinazzo, Daniele

2015-02-15

In this work we propose a proof of principle that dynamic causal modelling can identify plausible mechanisms at the synaptic level underlying brain state changes over a timescale of seconds. As a benchmark example for validation we used intracranial electroencephalographic signals in a human subject. These data were used to infer the (effective connectivity) architecture of synaptic connections among neural populations assumed to generate seizure activity. Dynamic causal modelling allowed us to quantify empirical changes in spectral activity in terms of a trajectory in parameter space - identifying key synaptic parameters or connections that cause observed signals. Using recordings from three seizures in one patient, we considered a network of two sources (within and just outside the putative ictal zone). Bayesian model selection was used to identify the intrinsic (within-source) and extrinsic (between-source) connectivity. Having established the underlying architecture, we were able to track the evolution of key connectivity parameters (e.g., inhibitory connections to superficial pyramidal cells) and test specific hypotheses about the synaptic mechanisms involved in ictogenesis. Our key finding was that intrinsic synaptic changes were sufficient to explain seizure onset, where these changes showed dissociable time courses over several seconds. Crucially, these changes spoke to an increase in the sensitivity of principal cells to intrinsic inhibitory afferents and a transient loss of excitatory-inhibitory balance. Copyright © 2014. Published by Elsevier Inc.

Real-time spectral analysis of HRV signals: an interactive and user-friendly PC system.

PubMed

Basano, L; Canepa, F; Ottonello, P

1998-01-01

We present a real-time system, built around a PC and a low-cost data acquisition board, for the spectral analysis of the heart rate variability signal. The Windows-like operating environment on which it is based makes the computer program very user-friendly even for non-specialized personnel. The Power Spectral Density is computed through the use of a hybrid method, in which a classical FFT analysis follows an autoregressive finite-extension of data; the stationarity of the sequence is continuously checked. The use of this algorithm gives a high degree of robustness of the spectral estimation. Moreover, always in real time, the FFT of every data block is computed and displayed in order to corroborate the results as well as to allow the user to interactively choose a proper AR model order.

Feasibility study of a novel miniaturized spectral imaging system architecture in UAV surveillance

NASA Astrophysics Data System (ADS)

Liu, Shuyang; Zhou, Tao; Jia, Xiaodong; Cui, Hushan; Huang, Chengjun

2016-01-01

The spectral imaging technology is able to analysis the spectral and spatial geometric character of the target at the same time. To break through the limitation brought by the size, weight and cost of the traditional spectral imaging instrument, a miniaturized novel spectral imaging based on CMOS processing has been introduced in the market. This technology has enabled the possibility of applying spectral imaging in the UAV platform. In this paper, the relevant technology and the related possible applications have been presented to implement a quick, flexible and more detailed remote sensing system.

Spectrum Analyzers Incorporating Tunable WGM Resonators

NASA Technical Reports Server (NTRS)

Savchenkov, Anatoliy; Matsko, Andrey; Strekalov, Dmitry; Maleki, Lute

2009-01-01

A photonic instrument is proposed to boost the resolution for ultraviolet/ optical/infrared spectral analysis and spectral imaging allowing the detection of narrow (0.00007-to-0.07-picometer wavelength resolution range) optical spectral signatures of chemical elements in space and planetary atmospheres. The idea underlying the proposal is to exploit the advantageous spectral characteristics of whispering-gallery-mode (WGM) resonators to obtain spectral resolutions at least three orders of magnitude greater than those of optical spectrum analyzers now in use. Such high resolutions would enable measurement of spectral features that could not be resolved by prior instruments.

Spectral reflectance properties (0.4-2.5 μm) of secondary Fe-oxide, Fe-hydroxide, and Fe-sulphate-hydrate minerals associated with sulphide-bearing mine wastes

USGS Publications Warehouse

Crowley, J.K.; Williams, D.E.; Hammarstrom, J.M.; Piatak, N.; Chou, I.-Ming; Mars, J.C.

2003-01-01

Diffuse reflectance spectra of 15 mineral species commonly associated with sulphide-bearing mine wastes show diagnostic absorption bands related to electronic processes involving ferric and/or ferrous iron, and to vibrational processes involving water and hydroxyl. Many of these absorption bands are relatively broad and overlapping; however, spectral analysis methods, including continuum removal and derivative analysis, permit most of the minerals to be distinguished. Key spectral differences between the minerals are illustrated in a series of plots showing major absorption band centres and other spectral feature positions. Because secondary iron minerals are sensitive indicators of pH, Eh, relative humidity, and other environmental conditions, spectral mapping of mineral distributions promises to have important application to mine waste remediation studies.

Multispectral scanner system parameter study and analysis software system description, volume 2

NASA Technical Reports Server (NTRS)

Landgrebe, D. A. (Principal Investigator); Mobasseri, B. G.; Wiersma, D. J.; Wiswell, E. R.; Mcgillem, C. D.; Anuta, P. E.

1978-01-01

The author has identified the following significant results. The integration of the available methods provided the analyst with the unified scanner analysis package (USAP), the flexibility and versatility of which was superior to many previous integrated techniques. The USAP consisted of three main subsystems; (1) a spatial path, (2) a spectral path, and (3) a set of analytic classification accuracy estimators which evaluated the system performance. The spatial path consisted of satellite and/or aircraft data, data correlation analyzer, scanner IFOV, and random noise model. The output of the spatial path was fed into the analytic classification and accuracy predictor. The spectral path consisted of laboratory and/or field spectral data, EXOSYS data retrieval, optimum spectral function calculation, data transformation, and statistics calculation. The output of the spectral path was fended into the stratified posterior performance estimator.

Signal-to-noise contribution of principal component loads in reconstructed near-infrared Raman tissue spectra.

PubMed

Grimbergen, M C M; van Swol, C F P; Kendall, C; Verdaasdonk, R M; Stone, N; Bosch, J L H R

2010-01-01

The overall quality of Raman spectra in the near-infrared region, where biological samples are often studied, has benefited from various improvements to optical instrumentation over the past decade. However, obtaining ample spectral quality for analysis is still challenging due to device requirements and short integration times required for (in vivo) clinical applications of Raman spectroscopy. Multivariate analytical methods, such as principal component analysis (PCA) and linear discriminant analysis (LDA), are routinely applied to Raman spectral datasets to develop classification models. Data compression is necessary prior to discriminant analysis to prevent or decrease the degree of over-fitting. The logical threshold for the selection of principal components (PCs) to be used in discriminant analysis is likely to be at a point before the PCs begin to introduce equivalent signal and noise and, hence, include no additional value. Assessment of the signal-to-noise ratio (SNR) at a certain peak or over a specific spectral region will depend on the sample measured. Therefore, the mean SNR over the whole spectral region (SNR(msr)) is determined in the original spectrum as well as for spectra reconstructed from an increasing number of principal components. This paper introduces a method of assessing the influence of signal and noise from individual PC loads and indicates a method of selection of PCs for LDA. To evaluate this method, two data sets with different SNRs were used. The sets were obtained with the same Raman system and the same measurement parameters on bladder tissue collected during white light cystoscopy (set A) and fluorescence-guided cystoscopy (set B). This method shows that the mean SNR over the spectral range in the original Raman spectra of these two data sets is related to the signal and noise contribution of principal component loads. The difference in mean SNR over the spectral range can also be appreciated since fewer principal components can reliably be used in the low SNR data set (set B) compared to the high SNR data set (set A). Despite the fact that no definitive threshold could be found, this method may help to determine the cutoff for the number of principal components used in discriminant analysis. Future analysis of a selection of spectral databases using this technique will allow optimum thresholds to be selected for different applications and spectral data quality levels.

On Holo-Hilbert Spectral Analysis: A Full Informational Spectral Representation for Nonlinear and Non-Stationary Data

NASA Technical Reports Server (NTRS)

Huang, Norden E.; Hu, Kun; Yang, Albert C. C.; Chang, Hsing-Chih; Jia, Deng; Liang, Wei-Kuang; Yeh, Jia Rong; Kao, Chu-Lan; Juan, Chi-Huang; Peng, Chung Kang;

On Holo-Hilbert spectral analysis: a full informational spectral representation for nonlinear and non-stationary data

PubMed Central

Huang, Norden E.; Hu, Kun; Yang, Albert C. C.; Chang, Hsing-Chih; Jia, Deng; Liang, Wei-Kuang; Yeh, Jia Rong; Kao, Chu-Lan; Juan, Chi-Hung; Peng, Chung Kang; Meijer, Johanna H.; Wang, Yung-Hung; Long, Steven R.; Wu, Zhauhua

2016-01-01

The Holo-Hilbert spectral analysis (HHSA) method is introduced to cure the deficiencies of traditional spectral analysis and to give a full informational representation of nonlinear and non-stationary data. It uses a nested empirical mode decomposition and Hilbert–Huang transform (HHT) approach to identify intrinsic amplitude and frequency modulations often present in nonlinear systems. Comparisons are first made with traditional spectrum analysis, which usually achieved its results through convolutional integral transforms based on additive expansions of an a priori determined basis, mostly under linear and stationary assumptions. Thus, for non-stationary processes, the best one could do historically was to use the time–frequency representations, in which the amplitude (or energy density) variation is still represented in terms of time. For nonlinear processes, the data can have both amplitude and frequency modulations (intra-mode and inter-mode) generated by two different mechanisms: linear additive or nonlinear multiplicative processes. As all existing spectral analysis methods are based on additive expansions, either a priori or adaptive, none of them could possibly represent the multiplicative processes. While the earlier adaptive HHT spectral analysis approach could accommodate the intra-wave nonlinearity quite remarkably, it remained that any inter-wave nonlinear multiplicative mechanisms that include cross-scale coupling and phase-lock modulations were left untreated. To resolve the multiplicative processes issue, additional dimensions in the spectrum result are needed to account for the variations in both the amplitude and frequency modulations simultaneously. HHSA accommodates all the processes: additive and multiplicative, intra-mode and inter-mode, stationary and non-stationary, linear and nonlinear interactions. The Holo prefix in HHSA denotes a multiple dimensional representation with both additive and multiplicative capabilities. PMID:26953180

Ratiometric spectral imaging for fast tumor detection and chemotherapy monitoring in vivo

PubMed Central

Hwang, Jae Youn; Gross, Zeev; Gray, Harry B.; Medina-Kauwe, Lali K.; Farkas, Daniel L.

2011-01-01

We report a novel in vivo spectral imaging approach to cancer detection and chemotherapy assessment. We describe and characterize a ratiometric spectral imaging and analysis method and evaluate its performance for tumor detection and delineation by quantitatively monitoring the specific accumulation of targeted gallium corrole (HerGa) into HER2-positive (HER2 +) breast tumors. HerGa temporal accumulation in nude mice bearing HER2 + breast tumors was monitored comparatively by a. this new ratiometric imaging and analysis method; b. established (reflectance and fluorescence) spectral imaging; c. more commonly used fluorescence intensity imaging. We also tested the feasibility of HerGa imaging in vivo using the ratiometric spectral imaging method for tumor detection and delineation. Our results show that the new method not only provides better quantitative information than typical spectral imaging, but also better specificity than standard fluorescence intensity imaging, thus allowing enhanced in vivo outlining of tumors and dynamic, quantitative monitoring of targeted chemotherapy agent accumulation into them. PMID:21721808

Cloud cover analysis with Arctic Advanced Very High Resolution Radiometer data. II - Classification with spectral and textural measures

NASA Technical Reports Server (NTRS)

Key, J.

1990-01-01

The spectral and textural characteristics of polar clouds and surfaces for a 7-day summer series of AVHRR data in two Arctic locations are examined, and the results used in the development of a cloud classification procedure for polar satellite data. Since spatial coherence and texture sensitivity tests indicate that a joint spectral-textural analysis based on the same cell size is inappropriate, cloud detection with AVHRR data and surface identification with passive microwave data are first done on the pixel level as described by Key and Barry (1989). Next, cloud patterns within 250-sq-km regions are described, then the spectral and local textural characteristics of cloud patterns in the image are determined and each cloud pixel is classified by statistical methods. Results indicate that both spectral and textural features can be utilized in the classification of cloudy pixels, although spectral features are most useful for the discrimination between cloud classes.