Accurate mask-based spatially regularized correlation filter for visual tracking

NASA Astrophysics Data System (ADS)

Gu, Xiaodong; Xu, Xinping

2017-01-01

Recently, discriminative correlation filter (DCF)-based trackers have achieved extremely successful results in many competitions and benchmarks. These methods utilize a periodic assumption of the training samples to efficiently learn a classifier. However, this assumption will produce unwanted boundary effects, which severely degrade the tracking performance. Correlation filters with limited boundaries and spatially regularized DCFs were proposed to reduce boundary effects. However, their methods used the fixed mask or predesigned weights function, respectively, which was unsuitable for large appearance variation. We propose an accurate mask-based spatially regularized correlation filter for visual tracking. Our augmented objective can reduce the boundary effect even in large appearance variation. In our algorithm, the masking matrix is converted into the regularized function that acts on the correlation filter in frequency domain, which makes the algorithm fast convergence. Our online tracking algorithm performs favorably against state-of-the-art trackers on OTB-2015 Benchmark in terms of efficiency, accuracy, and robustness.

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

NASA Astrophysics Data System (ADS)

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

2018-05-01

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

Spatial Autocorrelation Approaches to Testing Residuals from Least Squares Regression

PubMed Central

Chen, Yanguang

2016-01-01

In geo-statistics, the Durbin-Watson test is frequently employed to detect the presence of residual serial correlation from least squares regression analyses. However, the Durbin-Watson statistic is only suitable for ordered time or spatial series. If the variables comprise cross-sectional data coming from spatial random sampling, the test will be ineffectual because the value of Durbin-Watson’s statistic depends on the sequence of data points. This paper develops two new statistics for testing serial correlation of residuals from least squares regression based on spatial samples. By analogy with the new form of Moran’s index, an autocorrelation coefficient is defined with a standardized residual vector and a normalized spatial weight matrix. Then by analogy with the Durbin-Watson statistic, two types of new serial correlation indices are constructed. As a case study, the two newly presented statistics are applied to a spatial sample of 29 China’s regions. These results show that the new spatial autocorrelation models can be used to test the serial correlation of residuals from regression analysis. In practice, the new statistics can make up for the deficiencies of the Durbin-Watson test. PMID:26800271

A Comparison of Weights Matrices on Computation of Dengue Spatial Autocorrelation

NASA Astrophysics Data System (ADS)

Suryowati, K.; Bekti, R. D.; Faradila, A.

2018-04-01

Spatial autocorrelation is one of spatial analysis to identify patterns of relationship or correlation between locations. This method is very important to get information on the dispersal patterns characteristic of a region and linkages between locations. In this study, it applied on the incidence of Dengue Hemorrhagic Fever (DHF) in 17 sub districts in Sleman, Daerah Istimewa Yogyakarta Province. The link among location indicated by a spatial weight matrix. It describe the structure of neighbouring and reflects the spatial influence. According to the spatial data, type of weighting matrix can be divided into two types: point type (distance) and the neighbourhood area (contiguity). Selection weighting function is one determinant of the results of the spatial analysis. This study use queen contiguity based on first order neighbour weights, queen contiguity based on second order neighbour weights, and inverse distance weights. Queen contiguity first order and inverse distance weights shows that there is the significance spatial autocorrelation in DHF, but not by queen contiguity second order. Queen contiguity first and second order compute 68 and 86 neighbour list

A physiologically motivated sparse, compact, and smooth (SCS) approach to EEG source localization.

PubMed

Cao, Cheng; Akalin Acar, Zeynep; Kreutz-Delgado, Kenneth; Makeig, Scott

2012-01-01

Here, we introduce a novel approach to the EEG inverse problem based on the assumption that principal cortical sources of multi-channel EEG recordings may be assumed to be spatially sparse, compact, and smooth (SCS). To enforce these characteristics of solutions to the EEG inverse problem, we propose a correlation-variance model which factors a cortical source space covariance matrix into the multiplication of a pre-given correlation coefficient matrix and the square root of the diagonal variance matrix learned from the data under a Bayesian learning framework. We tested the SCS method using simulated EEG data with various SNR and applied it to a real ECOG data set. We compare the results of SCS to those of an established SBL algorithm.

Multivariate analysis of scale-dependent associations between bats and landscape structure

USGS Publications Warehouse

Gorresen, P.M.; Willig, M.R.; Strauss, R.E.

2005-01-01

The assessment of biotic responses to habitat disturbance and fragmentation generally has been limited to analyses at a single spatial scale. Furthermore, methods to compare responses between scales have lacked the ability to discriminate among patterns related to the identity, strength, or direction of associations of biotic variables with landscape attributes. We present an examination of the relationship of population- and community-level characteristics of phyllostomid bats with habitat features that were measured at multiple spatial scales in Atlantic rain forest of eastern Paraguay. We used a matrix of partial correlations between each biotic response variable (i.e., species abundance, species richness, and evenness) and a suite of landscape characteristics to represent the multifaceted associations of bats with spatial structure. Correlation matrices can correspond based on either the strength (i.e., magnitude) or direction (i.e., sign) of association. Therefore, a simulation model independently evaluated correspondence in the magnitude and sign of correlations among scales, and results were combined via a meta-analysis to provide an overall test of significance. Our approach detected both species-specific differences in response to landscape structure and scale dependence in those responses. This matrix-simulation approach has broad applicability to ecological situations in which multiple intercorrelated factors contribute to patterns in space or time. ?? 2005 by the Ecological Society of America.

Functional inverted Wishart for Bayesian multivariate spatial modeling with application to regional climatology model data.

PubMed

Duan, L L; Szczesniak, R D; Wang, X

2017-11-01

Modern environmental and climatological studies produce multiple outcomes at high spatial resolutions. Multivariate spatial modeling is an established means to quantify cross-correlation among outcomes. However, existing models typically suffer from poor computational efficiency and lack the flexibility to simultaneously estimate auto- and cross-covariance structures. In this article, we undertake a novel construction of covariance by utilizing spectral convolution and by imposing an inverted Wishart prior on the cross-correlation structure. The cross-correlation structure with this functional inverted Wishart prior flexibly accommodates not only positive but also weak or negative associations among outcomes while preserving spatial resolution. Furthermore, the proposed model is computationally efficient and produces easily interpretable results, including the individual autocovariances and full cross-correlation matrices, as well as a partial cross-correlation matrix reflecting the outcome correlation after excluding the effects caused by spatial convolution. The model is examined using simulated data sets under different scenarios. It is also applied to the data from the North American Regional Climate Change Assessment Program, examining long-term associations between surface outcomes for air temperature, pressure, humidity, and radiation, on the land area of the North American West Coast. Results and predictive performance are compared with findings from approaches using convolution only or coregionalization.

Functional inverted Wishart for Bayesian multivariate spatial modeling with application to regional climatology model data

PubMed Central

Duan, L. L.; Szczesniak, R. D.; Wang, X.

2018-01-01

Modern environmental and climatological studies produce multiple outcomes at high spatial resolutions. Multivariate spatial modeling is an established means to quantify cross-correlation among outcomes. However, existing models typically suffer from poor computational efficiency and lack the flexibility to simultaneously estimate auto- and cross-covariance structures. In this article, we undertake a novel construction of covariance by utilizing spectral convolution and by imposing an inverted Wishart prior on the cross-correlation structure. The cross-correlation structure with this functional inverted Wishart prior flexibly accommodates not only positive but also weak or negative associations among outcomes while preserving spatial resolution. Furthermore, the proposed model is computationally efficient and produces easily interpretable results, including the individual autocovariances and full cross-correlation matrices, as well as a partial cross-correlation matrix reflecting the outcome correlation after excluding the effects caused by spatial convolution. The model is examined using simulated data sets under different scenarios. It is also applied to the data from the North American Regional Climate Change Assessment Program, examining long-term associations between surface outcomes for air temperature, pressure, humidity, and radiation, on the land area of the North American West Coast. Results and predictive performance are compared with findings from approaches using convolution only or coregionalization. PMID:29576735

The spatial-temporal characteristics of type I collagen-based extracellular matrix.

PubMed

Jones, Christopher Allen Rucksack; Liang, Long; Lin, Daniel; Jiao, Yang; Sun, Bo

2014-11-28

Type I collagen abounds in mammalian extracellular matrix (ECM) and is crucial to many biophysical processes. While previous studies have mostly focused on bulk averaged properties, here we provide a comprehensive and quantitative spatial-temporal characterization of the microstructure of type I collagen-based ECM as the gelation temperature varies. The structural characteristics including the density and nematic correlation functions are obtained by analyzing confocal images of collagen gels prepared at a wide range of gelation temperatures (from 16 °C to 36 °C). As temperature increases, the gel microstructure varies from a "bundled" network with strong orientational correlation between the fibers to an isotropic homogeneous network with no significant orientational correlation, as manifested by the decaying of length scales in the correlation functions. We develop a kinetic Monte-Carlo collagen growth model to better understand how ECM microstructure depends on various environmental or kinetic factors. We show that the nucleation rate, growth rate, and an effective hydrodynamic alignment of collagen fibers fully determines the spatiotemporal fluctuations of the density and orientational order of collagen gel microstructure. Also the temperature dependence of the growth rate and nucleation rate follow the prediction of classical nucleation theory.

Interactions between core and matrix thalamocortical projections in human sleep spindle synchronization

PubMed Central

Bonjean, Maxime; Baker, Tanya; Bazhenov, Maxim; Cash, Sydney; Halgren, Eric; Sejnowski, Terrence

2012-01-01

Sleep spindles, which are bursts of 11–15 Hz that occur during non-REM sleep, are highly synchronous across the scalp when measured with EEG, but have low spatial coherence and exhibit low correlation with EEG signals when simultaneously measured with MEG spindles in humans. We developed a computational model to explore the hypothesis that the spatial coherence of the EEG spindle is a consequence of diffuse matrix projections of the thalamus to layer 1 compared to the focal projections of the core pathway to layer 4 recorded by the MEG. Increasing the fanout of thalamocortical connectivity in the matrix pathway while keeping the core pathway fixed led to increased synchrony of the spindle activity in the superficial cortical layers in the model. In agreement with cortical recordings, the latency for spindles to spread from the core to the matrix was independent of the thalamocortical fanout but highly dependent on the probability of connections between cortical areas. PMID:22496571

Optoelectronic associative memory

NASA Technical Reports Server (NTRS)

Chao, Tien-Hsin (Inventor)

1993-01-01

An associative optical memory including an input spatial light modulator (SLM) in the form of an edge enhanced liquid crystal light valve (LCLV) and a pair of memory SLM's in the form of liquid crystal televisions (LCTV's) forms a matrix array of an input image which is cross correlated with a matrix array of stored images. The correlation product is detected and nonlinearly amplified to illuminate a replica of the stored image array to select the stored image correlating with the input image. The LCLV is edge enhanced by reducing the bias frequency and voltage and rotating its orientation. The edge enhancement and nonlinearity of the photodetection improves the orthogonality of the stored image. The illumination of the replicate stored image provides a clean stored image, uncontaminated by the image comparison process.

A Patch Density Recommendation based on Convergence Studies for Vehicle Panel Vibration Response resulting from Excitation by a Diffuse Acoustic Field

NASA Technical Reports Server (NTRS)

Smith, Andrew; LaVerde, Bruce; Jones, Douglas; Towner, Robert; Waldon, James; Hunt, Ron

2013-01-01

Producing fluid structural interaction estimates of panel vibration from an applied pressure field excitation are quite dependent on the spatial correlation of the pressure field. There is a danger of either over estimating a low frequency response or under predicting broad band panel response in the more modally dense bands if the pressure field spatial correlation is not accounted for adequately. It is a useful practice to simulate the spatial correlation of the applied pressure field over a 2d surface using a matrix of small patch area regions on a finite element model (FEM). Use of a fitted function for the spatial correlation between patch centers can result in an error if the choice of patch density is not fine enough to represent the more continuous spatial correlation function throughout the intended frequency range of interest. Several patch density assumptions to approximate the fitted spatial correlation function are first evaluated using both qualitative and quantitative illustrations. The actual response of a typical vehicle panel system FEM is then examined in a convergence study where the patch density assumptions are varied over the same model. The convergence study results illustrate the impacts possible from a poor choice of patch density on the analytical response estimate. The fitted correlation function used in this study represents a diffuse acoustic field (DAF) excitation of the panel to produce vibration response.

Analysis of network clustering behavior of the Chinese stock market

NASA Astrophysics Data System (ADS)

Chen, Huan; Mai, Yong; Li, Sai-Ping

2014-11-01

Random Matrix Theory (RMT) and the decomposition of correlation matrix method are employed to analyze spatial structure of stocks interactions and collective behavior in the Shanghai and Shenzhen stock markets in China. The result shows that there exists prominent sector structures, with subsectors including the Real Estate (RE), Commercial Banks (CB), Pharmaceuticals (PH), Distillers&Vintners (DV) and Steel (ST) industries. Furthermore, the RE and CB subsectors are mostly anti-correlated. We further study the temporal behavior of the dataset and find that while the sector structures are relatively stable from 2007 through 2013, the correlation between the real estate and commercial bank stocks shows large variations. By employing the ensemble empirical mode decomposition (EEMD) method, we show that this anti-correlation behavior is closely related to the monetary and austerity policies of the Chinese government during the period of study.

Effects of geometrical structure on spatial distribution of thermal energy in two-dimensional triangular lattices

NASA Astrophysics Data System (ADS)

Liu, Yong-Yang; Xu, Yu-Liang; Liu, Zhong-Qiang; Li, Jing; Wang, Chun-Yang; Kong, Xiang-Mu

2018-07-01

Employing the correlation matrix technique, the spatial distribution of thermal energy in two-dimensional triangular lattices in equilibrium, interacting with linear springs, is studied. It is found that the spatial distribution of thermal energy varies with the included angle of the springs. In addition, the average thermal energy of the longer springs is lower. Springs with different included angle and length will lead to an inhomogeneous spatial distribution of thermal energy. This suggests that the spatial distribution of thermal energy is affected by the geometrical structure of the system: the more asymmetric the geometrical structure of the system is, the more inhomogeneous is the spatial distribution of thermal energy.

Polarimetric optical imaging of scattering surfaces.

PubMed

Barter, J D; Lee, P H

1996-10-20

A polarimetric optical specular event detector (OSED) has been developed to provide spatially and temporally resolved polarimetric data of backscattering in the visible from water wave surfaces. The OSED acquires simultaneous, two-dimensionally resolved images of the remote target in two orthogonal planes of polarization. With the use of plane-polarized illumination the OSED presently can measure, in an ensemble of breaking waves, the equivalent four-element polarization matrix common to polarimetric radars. Upgrade to full Stokes parameter state of polarization measurements is straightforward with the use of present single-aperture, multi-imager CCD camera technology. The OSED is used in conjunction with a coherent pulse-chirped radar (PCR), which also measures the four-element polarization matrix, to provide direct time-correlated identification of backscattering mechanisms operative during wave-breaking events which heretofore have not been described theoretically. We describe the instrument and its implementation, and examples of spatially resolved polarimetric data are displayed as correlated with the PCR backscatter cross section and polarization ratio records.

Temporal and spatial correlation patterns of air pollutants in Chinese cities

PubMed Central

Dai, Yue-Hua

2017-01-01

As a huge threat to the public health, China’s air pollution has attracted extensive attention and continues to grow in tandem with the economy. Although the real-time air quality report can be utilized to update our knowledge on air quality, questions about how pollutants evolve across time and how pollutants are spatially correlated still remain a puzzle. In view of this point, we adopt the PMFG network method to analyze the six pollutants’ hourly data in 350 Chinese cities in an attempt to find out how these pollutants are correlated temporally and spatially. In terms of time dimension, the results indicate that, except for O3, the pollutants have a common feature of the strong intraday patterns of which the daily variations are composed of two contraction periods and two expansion periods. Besides, all the time series of the six pollutants possess strong long-term correlations, and this temporal memory effect helps to explain why smoggy days are always followed by one after another. In terms of space dimension, the correlation structure shows that O3 is characterized by the highest spatial connections. The PMFGs reveal the relationship between this spatial correlation and provincial administrative divisions by filtering the hierarchical structure in the correlation matrix and refining the cliques as the tinny spatial clusters. Finally, we check the stability of the correlation structure and conclude that, except for PM10 and O3, the other pollutants have an overall stable correlation, and all pollutants have a slight trend to become more divergent in space. These results not only enhance our understanding of the air pollutants’ evolutionary process, but also shed lights on the application of complex network methods into geographic issues. PMID:28832599

Spatial correlation in matter-wave interference as a measure of decoherence, dephasing, and entropy

NASA Astrophysics Data System (ADS)

Chen, Zilin; Beierle, Peter; Batelaan, Herman

2018-04-01

The loss of contrast in double-slit electron diffraction due to dephasing and decoherence processes is studied. It is shown that the spatial intensity correlation function of diffraction patterns can be used to distinguish between dephasing and decoherence. This establishes a measure of time reversibility that does not require the determination of coherence terms of the density matrix, while von Neumann entropy, another measure of time reversibility, does require coherence terms. This technique is exciting in view of the need to understand and control the detrimental experimental effect of contrast loss and for fundamental studies on the transition from the classical to the quantum regime.

Joint spatial-spectral hyperspectral image clustering using block-diagonal amplified affinity matrix

NASA Astrophysics Data System (ADS)

Fan, Lei; Messinger, David W.

2018-03-01

The large number of spectral channels in a hyperspectral image (HSI) produces a fine spectral resolution to differentiate between materials in a scene. However, difficult classes that have similar spectral signatures are often confused while merely exploiting information in the spectral domain. Therefore, in addition to spectral characteristics, the spatial relationships inherent in HSIs should also be considered for incorporation into classifiers. The growing availability of high spectral and spatial resolution of remote sensors provides rich information for image clustering. Besides the discriminating power in the rich spectrum, contextual information can be extracted from the spatial domain, such as the size and the shape of the structure to which one pixel belongs. In recent years, spectral clustering has gained popularity compared to other clustering methods due to the difficulty of accurate statistical modeling of data in high dimensional space. The joint spatial-spectral information could be effectively incorporated into the proximity graph for spectral clustering approach, which provides a better data representation by discovering the inherent lower dimensionality from the input space. We embedded both spectral and spatial information into our proposed local density adaptive affinity matrix, which is able to handle multiscale data by automatically selecting the scale of analysis for every pixel according to its neighborhood of the correlated pixels. Furthermore, we explored the "conductivity method," which aims at amplifying the block diagonal structure of the affinity matrix to further improve the performance of spectral clustering on HSI datasets.

Stability-driven nonnegative matrix factorization to interpret spatial gene expression and build local gene networks.

PubMed

Wu, Siqi; Joseph, Antony; Hammonds, Ann S; Celniker, Susan E; Yu, Bin; Frise, Erwin

2016-04-19

Spatial gene expression patterns enable the detection of local covariability and are extremely useful for identifying local gene interactions during normal development. The abundance of spatial expression data in recent years has led to the modeling and analysis of regulatory networks. The inherent complexity of such data makes it a challenge to extract biological information. We developed staNMF, a method that combines a scalable implementation of nonnegative matrix factorization (NMF) with a new stability-driven model selection criterion. When applied to a set ofDrosophilaearly embryonic spatial gene expression images, one of the largest datasets of its kind, staNMF identified 21 principal patterns (PP). Providing a compact yet biologically interpretable representation ofDrosophilaexpression patterns, PP are comparable to a fate map generated experimentally by laser ablation and show exceptional promise as a data-driven alternative to manual annotations. Our analysis mapped genes to cell-fate programs and assigned putative biological roles to uncharacterized genes. Finally, we used the PP to generate local transcription factor regulatory networks. Spatially local correlation networks were constructed for six PP that span along the embryonic anterior-posterior axis. Using a two-tail 5% cutoff on correlation, we reproduced 10 of the 11 links in the well-studied gap gene network. The performance of PP with theDrosophiladata suggests that staNMF provides informative decompositions and constitutes a useful computational lens through which to extract biological insight from complex and often noisy gene expression data.

EIT image reconstruction with four dimensional regularization.

PubMed

Dai, Tao; Soleimani, Manuchehr; Adler, Andy

2008-09-01

Electrical impedance tomography (EIT) reconstructs internal impedance images of the body from electrical measurements on body surface. The temporal resolution of EIT data can be very high, although the spatial resolution of the images is relatively low. Most EIT reconstruction algorithms calculate images from data frames independently, although data are actually highly correlated especially in high speed EIT systems. This paper proposes a 4-D EIT image reconstruction for functional EIT. The new approach is developed to directly use prior models of the temporal correlations among images and 3-D spatial correlations among image elements. A fast algorithm is also developed to reconstruct the regularized images. Image reconstruction is posed in terms of an augmented image and measurement vector which are concatenated from a specific number of previous and future frames. The reconstruction is then based on an augmented regularization matrix which reflects the a priori constraints on temporal and 3-D spatial correlations of image elements. A temporal factor reflecting the relative strength of the image correlation is objectively calculated from measurement data. Results show that image reconstruction models which account for inter-element correlations, in both space and time, show improved resolution and noise performance, in comparison to simpler image models.

Topological electronic liquids: Electronic physics of one dimension beyond the one spatial dimension

NASA Astrophysics Data System (ADS)

Wiegmann, P. B.

1999-06-01

There is a class of electronic liquids in dimensions greater than 1 that shows all essential properties of one-dimensional electronic physics. These are topological liquids-correlated electronic systems with a spectral flow. Compressible topological electronic liquids are superfluids. In this paper we present a study of a conventional model of a topological superfluid in two spatial dimensions. This model is thought to be relevant to a doped Mott insulator. We show how the spectral flow leads to the superfluid hydrodynamics and how the orthogonality catastrophe affects off-diagonal matrix elements. We also compute the major electronic correlation functions. Among them are the spectral function, the pair wave function, and various tunneling amplitudes. To compute correlation functions we develop a method of current algebra-an extension of the bosonization technique of one spatial dimension. In order to emphasize a similarity between electronic liquids in one dimension and topological liquids in dimensions greater than 1, we first review the Fröhlich-Peierls mechanism of ideal conductivity in one dimension and then extend the physics and the methods into two spatial dimensions.

A Study of Feature Extraction Using Divergence Analysis of Texture Features

NASA Technical Reports Server (NTRS)

Hallada, W. A.; Bly, B. G.; Boyd, R. K.; Cox, S.

1982-01-01

An empirical study of texture analysis for feature extraction and classification of high spatial resolution remotely sensed imagery (10 meters) is presented in terms of specific land cover types. The principal method examined is the use of spatial gray tone dependence (SGTD). The SGTD method reduces the gray levels within a moving window into a two-dimensional spatial gray tone dependence matrix which can be interpreted as a probability matrix of gray tone pairs. Haralick et al (1973) used a number of information theory measures to extract texture features from these matrices, including angular second moment (inertia), correlation, entropy, homogeneity, and energy. The derivation of the SGTD matrix is a function of: (1) the number of gray tones in an image; (2) the angle along which the frequency of SGTD is calculated; (3) the size of the moving window; and (4) the distance between gray tone pairs. The first three parameters were varied and tested on a 10 meter resolution panchromatic image of Maryville, Tennessee using the five SGTD measures. A transformed divergence measure was used to determine the statistical separability between four land cover categories forest, new residential, old residential, and industrial for each variation in texture parameters.

Gutzwiller Monte Carlo approach for a critical dissipative spin model

NASA Astrophysics Data System (ADS)

Casteels, Wim; Wilson, Ryan M.; Wouters, Michiel

2018-06-01

We use the Gutzwiller Monte Carlo approach to simulate the dissipative X Y Z model in the vicinity of a dissipative phase transition. This approach captures classical spatial correlations together with the full on-site quantum behavior while neglecting nonlocal quantum effects. By considering finite two-dimensional lattices of various sizes, we identify a ferromagnetic and two paramagnetic phases, in agreement with earlier studies. The greatly reduced numerical complexity of the Gutzwiller Monte Carlo approach facilitates efficient simulation of relatively large lattice sizes. The inclusion of the spatial correlations allows to capture parts of the phase diagram that are completely missed by the widely applied Gutzwiller decoupling of the density matrix.

Some issues on modeling atmospheric turbulence experienced by helicopter rotor blades

NASA Technical Reports Server (NTRS)

Costello, Mark; Gaonkar, G. H.; Prasad, J. V. R.; Schrage, D. P.

1992-01-01

The atmospheric turbulence velocities seen by nonrotating aircraft components and rotating blades can be substantially different. The differences are due to the spatial motion of the rotor blades, which move fore and aft through the gust waves. Body-fixed atmospheric turbulence refers to the actual atmospheric turbulence experienced by a point fixed on a nonrotating aircraft component such as the aircraft's center of gravity or the rotor hub, while blade-fixed atmospheric turbulence refers to the atmospheric turbulence experienced by an element of the rotating rotor blade. An example is presented, which, though overly simplified, shows important differences between blade- and body-fixed rotorcraft atmospheric turbulence models. All of the information necessary to develop the dynamic equations describing the atmospheric turbulence velocity field experienced by an aircraft is contained in the atmospheric turbulence velocity correlation matrix. It is for this reason that a generalized formulation of the correlation matrix describing atmospheric turbulence that a rotating blade encounters is developed. From this correlation matrix, earlier treated cases restricted to a rotor flying straight and level directly into the mean wind can be recovered as special cases.

Hierarchical spatial segregation of two Mediterranean vole species: the role of patch-network structure and matrix composition.

PubMed

Pita, Ricardo; Lambin, Xavier; Mira, António; Beja, Pedro

2016-09-01

According to ecological theory, the coexistence of competitors in patchy environments may be facilitated by hierarchical spatial segregation along axes of environmental variation, but empirical evidence is limited. Cabrera and water voles show a metapopulation-like structure in Mediterranean farmland, where they are known to segregate along space, habitat, and time axes within habitat patches. Here, we assess whether segregation also occurs among and within landscapes, and how this is influenced by patch-network and matrix composition. We surveyed 75 landscapes, each covering 78 ha, where we mapped all habitat patches potentially suitable for Cabrera and water voles, and the area effectively occupied by each species (extent of occupancy). The relatively large water vole tended to be the sole occupant of landscapes with high habitat amount but relatively low patch density (i.e., with a few large patches), and with a predominantly agricultural matrix, whereas landscapes with high patch density (i.e., many small patches) and low agricultural cover, tended to be occupied exclusively by the small Cabrera vole. The two species tended to co-occur in landscapes with intermediate patch-network and matrix characteristics, though their extents of occurrence were negatively correlated after controlling for environmental effects. In combination with our previous studies on the Cabrera-water vole system, these findings illustrated empirically the occurrence of hierarchical spatial segregation, ranging from within-patches to among-landscapes. Overall, our study suggests that recognizing the hierarchical nature of spatial segregation patterns and their major environmental drivers should enhance our understanding of species coexistence in patchy environments.

Stability-driven nonnegative matrix factorization to interpret spatial gene expression and build local gene networks

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

Wu, Siqi; Joseph, Antony; Hammonds, Ann S.

Spatial gene expression patterns enable the detection of local covariability and are extremely useful for identifying local gene interactions during normal development. The abundance of spatial expression data in recent years has led to the modeling and analysis of regulatory networks. The inherent complexity of such data makes it a challenge to extract biological information. We developed staNMF, a method that combines a scalable implementation of nonnegative matrix factorization (NMF) with a new stability-driven model selection criterion. When applied to a set of Drosophila early embryonic spatial gene expression images, one of the largest datasets of its kind, staNMF identifiedmore » 21 principal patterns (PP). Providing a compact yet biologically interpretable representation of Drosophila expression patterns, PP are comparable to a fate map generated experimentally by laser ablation and show exceptional promise as a data-driven alternative to manual annotations. Our analysis mapped genes to cell-fate programs and assigned putative biological roles to uncharacterized genes. Finally, we used the PP to generate local transcription factor regulatory networks. Spatially local correlation networks were constructed for six PP that span along the embryonic anterior-posterior axis. Using a two-tail 5% cutoff on correlation, we reproduced 10 of the 11 links in the well-studied gap gene network. In conclusion, the performance of PP with the Drosophila data suggests that staNMF provides informative decompositions and constitutes a useful computational lens through which to extract biological insight from complex and often noisy gene expression data.« less

Stability-driven nonnegative matrix factorization to interpret spatial gene expression and build local gene networks

DOE PAGES

Wu, Siqi; Joseph, Antony; Hammonds, Ann S.; ...

2016-04-06

Spatial gene expression patterns enable the detection of local covariability and are extremely useful for identifying local gene interactions during normal development. The abundance of spatial expression data in recent years has led to the modeling and analysis of regulatory networks. The inherent complexity of such data makes it a challenge to extract biological information. We developed staNMF, a method that combines a scalable implementation of nonnegative matrix factorization (NMF) with a new stability-driven model selection criterion. When applied to a set of Drosophila early embryonic spatial gene expression images, one of the largest datasets of its kind, staNMF identifiedmore » 21 principal patterns (PP). Providing a compact yet biologically interpretable representation of Drosophila expression patterns, PP are comparable to a fate map generated experimentally by laser ablation and show exceptional promise as a data-driven alternative to manual annotations. Our analysis mapped genes to cell-fate programs and assigned putative biological roles to uncharacterized genes. Finally, we used the PP to generate local transcription factor regulatory networks. Spatially local correlation networks were constructed for six PP that span along the embryonic anterior-posterior axis. Using a two-tail 5% cutoff on correlation, we reproduced 10 of the 11 links in the well-studied gap gene network. In conclusion, the performance of PP with the Drosophila data suggests that staNMF provides informative decompositions and constitutes a useful computational lens through which to extract biological insight from complex and often noisy gene expression data.« less

Stress as an order parameter for the glass transition

NASA Astrophysics Data System (ADS)

Visscher, P. B.; Logan, W. T.

1990-09-01

The stress tensor has been considered as a possible order parameter for the liquid-glass transition, and its autocorrelation matrix (elements of which are the integrands in the Green-Kubo formulas for bulk and shear viscosity) have been measured in simulations. However, only the k=0 spatial Fourier component has apparently been previously measured. We have measured four Fourier components of all matrix elements of the stress-stress correlation function, and we find that some of those with nonzero wave vector are significantly more persistent (slower decaying) than the k=0 component.

Exploiting the spatial locality of electron correlation within the parametric two-electron reduced-density-matrix method

NASA Astrophysics Data System (ADS)

DePrince, A. Eugene; Mazziotti, David A.

2010-01-01

The parametric variational two-electron reduced-density-matrix (2-RDM) method is applied to computing electronic correlation energies of medium-to-large molecular systems by exploiting the spatial locality of electron correlation within the framework of the cluster-in-molecule (CIM) approximation [S. Li et al., J. Comput. Chem. 23, 238 (2002); J. Chem. Phys. 125, 074109 (2006)]. The 2-RDMs of individual molecular fragments within a molecule are determined, and selected portions of these 2-RDMs are recombined to yield an accurate approximation to the correlation energy of the entire molecule. In addition to extending CIM to the parametric 2-RDM method, we (i) suggest a more systematic selection of atomic-orbital domains than that presented in previous CIM studies and (ii) generalize the CIM method for open-shell quantum systems. The resulting method is tested with a series of polyacetylene molecules, water clusters, and diazobenzene derivatives in minimal and nonminimal basis sets. Calculations show that the computational cost of the method scales linearly with system size. We also compute hydrogen-abstraction energies for a series of hydroxyurea derivatives. Abstraction of hydrogen from hydroxyurea is thought to be a key step in its treatment of sickle cell anemia; the design of hydroxyurea derivatives that oxidize more rapidly is one approach to devising more effective treatments.

Multidimensional Compressed Sensing MRI Using Tensor Decomposition-Based Sparsifying Transform

PubMed Central

Yu, Yeyang; Jin, Jin; Liu, Feng; Crozier, Stuart

2014-01-01

Compressed Sensing (CS) has been applied in dynamic Magnetic Resonance Imaging (MRI) to accelerate the data acquisition without noticeably degrading the spatial-temporal resolution. A suitable sparsity basis is one of the key components to successful CS applications. Conventionally, a multidimensional dataset in dynamic MRI is treated as a series of two-dimensional matrices, and then various matrix/vector transforms are used to explore the image sparsity. Traditional methods typically sparsify the spatial and temporal information independently. In this work, we propose a novel concept of tensor sparsity for the application of CS in dynamic MRI, and present the Higher-order Singular Value Decomposition (HOSVD) as a practical example. Applications presented in the three- and four-dimensional MRI data demonstrate that HOSVD simultaneously exploited the correlations within spatial and temporal dimensions. Validations based on cardiac datasets indicate that the proposed method achieved comparable reconstruction accuracy with the low-rank matrix recovery methods and, outperformed the conventional sparse recovery methods. PMID:24901331

Three-dimensional Model of Tissue and Heavy Ions Effects

NASA Technical Reports Server (NTRS)

Ponomarev, Artem L.; Sundaresan, Alamelu; Huff, Janice L.; Cucinotta, Francis A.

2007-01-01

A three-dimensional tissue model was incorporated into a new Monte Carlo algorithm that simulates passage of heavy ions in a tissue box . The tissue box was given as a realistic model of tissue based on confocal microscopy images. The action of heavy ions on the cellular matrix for 2- or 3-dimensional cases was simulated. Cells were modeled as a cell culture monolayer in one example, where the data were taken directly from microscopy (2-d cell matrix), and as a multi-layer obtained from confocal microscopy (3-d case). Image segmentation was used to identify cells with precise areas/volumes in an irradiated cell culture monolayer, and slices of tissue with many cell layers. The cells were then inserted into the model box of the simulated physical space pixel by pixel. In the case of modeled tissues (3-d), the tissue box had periodic boundary conditions imposed, which extrapolates the technique to macroscopic volumes of tissue. For the real tissue (3-d), specific spatial patterns for cell apoptosis and necrosis are expected. The cell patterns were modeled based on action cross sections for apoptosis and necrosis estimated from current experimental data. A spatial correlation function indicating a higher spatial concentration of damaged cells from heavy ions relative to the low-LET radiation cell damage pattern is presented. The spatial correlation effects among necrotic cells can help studying microlesions in organs, and probable effects of directionality of heavy ion radiation on epithelium and endothelium.

Quantum critical probing and simulation of colored quantum noise

NASA Astrophysics Data System (ADS)

Mascarenhas, Eduardo; de Vega, Inés

2017-12-01

We propose a protocol to simulate the evolution of a non-Markovian open quantum system by considering a collisional process with a many-body system, which plays the role of an environment. As a result of our protocol, the environment spatial correlations are mapped into the time correlations of a noise that drives the dynamics of the open system. Considering the weak coupling limit, the open system can also be considered as a probe of the environment properties. In this regard, when preparing the environment in its ground state, a measurement of the dynamics of the open system allows to determine the length of the environment spatial correlations and therefore its critical properties. To illustrate our proposal we simulate the full system dynamics with matrix-product-states and compare this to the reduced dynamics obtained with an approximated variational master equation.

Joint estimation of 2D-DOA and frequency based on space-time matrix and conformal array.

PubMed

Wan, Liang-Tian; Liu, Lu-Tao; Si, Wei-Jian; Tian, Zuo-Xi

2013-01-01

Each element in the conformal array has a different pattern, which leads to the performance deterioration of the conventional high resolution direction-of-arrival (DOA) algorithms. In this paper, a joint frequency and two-dimension DOA (2D-DOA) estimation algorithm for conformal array are proposed. The delay correlation function is used to suppress noise. Both spatial and time sampling are utilized to construct the spatial-time matrix. The frequency and 2D-DOA estimation are accomplished based on parallel factor (PARAFAC) analysis without spectral peak searching and parameter pairing. The proposed algorithm needs only four guiding elements with precise positions to estimate frequency and 2D-DOA. Other instrumental elements can be arranged flexibly on the surface of the carrier. Simulation results demonstrate the effectiveness of the proposed algorithm.

Improved Spatial Differencing Scheme for 2-D DOA Estimation of Coherent Signals with Uniform Rectangular Arrays.

PubMed

Shi, Junpeng; Hu, Guoping; Sun, Fenggang; Zong, Binfeng; Wang, Xin

2017-08-24

This paper proposes an improved spatial differencing (ISD) scheme for two-dimensional direction of arrival (2-D DOA) estimation of coherent signals with uniform rectangular arrays (URAs). We first divide the URA into a number of row rectangular subarrays. Then, by extracting all the data information of each subarray, we only perform difference-operation on the auto-correlations, while the cross-correlations are kept unchanged. Using the reconstructed submatrices, both the forward only ISD (FO-ISD) and forward backward ISD (FB-ISD) methods are developed under the proposed scheme. Compared with the existing spatial smoothing techniques, the proposed scheme can use more data information of the sample covariance matrix and also suppress the effect of additive noise more effectively. Simulation results show that both FO-ISD and FB-ISD can improve the estimation performance largely as compared to the others, in white or colored noise conditions.

Improved Spatial Differencing Scheme for 2-D DOA Estimation of Coherent Signals with Uniform Rectangular Arrays

PubMed Central

Hu, Guoping; Zong, Binfeng; Wang, Xin

2017-01-01

This paper proposes an improved spatial differencing (ISD) scheme for two-dimensional direction of arrival (2-D DOA) estimation of coherent signals with uniform rectangular arrays (URAs). We first divide the URA into a number of row rectangular subarrays. Then, by extracting all the data information of each subarray, we only perform difference-operation on the auto-correlations, while the cross-correlations are kept unchanged. Using the reconstructed submatrices, both the forward only ISD (FO-ISD) and forward backward ISD (FB-ISD) methods are developed under the proposed scheme. Compared with the existing spatial smoothing techniques, the proposed scheme can use more data information of the sample covariance matrix and also suppress the effect of additive noise more effectively. Simulation results show that both FO-ISD and FB-ISD can improve the estimation performance largely as compared to the others, in white or colored noise conditions. PMID:28837115

Variational Optimization of the Second-Order Density Matrix Corresponding to a Seniority-Zero Configuration Interaction Wave Function.

PubMed

Poelmans, Ward; Van Raemdonck, Mario; Verstichel, Brecht; De Baerdemacker, Stijn; Torre, Alicia; Lain, Luis; Massaccesi, Gustavo E; Alcoba, Diego R; Bultinck, Patrick; Van Neck, Dimitri

2015-09-08

We perform a direct variational determination of the second-order (two-particle) density matrix corresponding to a many-electron system, under a restricted set of the two-index N-representability P-, Q-, and G-conditions. In addition, we impose a set of necessary constraints that the two-particle density matrix must be derivable from a doubly occupied many-electron wave function, i.e., a singlet wave function for which the Slater determinant decomposition only contains determinants in which spatial orbitals are doubly occupied. We rederive the two-index N-representability conditions first found by Weinhold and Wilson and apply them to various benchmark systems (linear hydrogen chains, He, N2, and CN(-)). This work is motivated by the fact that a doubly occupied many-electron wave function captures in many cases the bulk of the static correlation. Compared to the general case, the structure of doubly occupied two-particle density matrices causes the associate semidefinite program to have a very favorable scaling as L(3), where L is the number of spatial orbitals. Since the doubly occupied Hilbert space depends on the choice of the orbitals, variational calculation steps of the two-particle density matrix are interspersed with orbital-optimization steps (based on Jacobi rotations in the space of the spatial orbitals). We also point to the importance of symmetry breaking of the orbitals when performing calculations in a doubly occupied framework.

Digital halftoning methods for selectively partitioning error into achromatic and chromatic channels

NASA Technical Reports Server (NTRS)

Mulligan, Jeffrey B.

1990-01-01

A method is described for reducing the visibility of artifacts arising in the display of quantized color images on CRT displays. The method is based on the differential spatial sensitivity of the human visual system to chromatic and achromatic modulations. Because the visual system has the highest spatial and temporal acuity for the luminance component of an image, a technique which will reduce luminance artifacts at the expense of introducing high-frequency chromatic errors is sought. A method based on controlling the correlations between the quantization errors in the individual phosphor images is explored. The luminance component is greatest when the phosphor errors are positively correlated, and is minimized when the phosphor errors are negatively correlated. The greatest effect of the correlation is obtained when the intensity quantization step sizes of the individual phosphors have equal luminances. For the ordered dither algorithm, a version of the method can be implemented by simply inverting the matrix of thresholds for one of the color components.

Resonant tunneling in GaAs/Al xGa 1-xAs superlattices with aperiodic potential profiles

NASA Astrophysics Data System (ADS)

Djelti, R.; Aziz, Z.; Bentata, S.; Besbes, A.

2011-12-01

Using the exact Airy function formalism and the transfer-matrix technique, we have numerically investigated in this paper the effect of intentional correlations in spatial disorder on transmission properties of one-dimensional superlattices. Such systems consist of two different structures randomly distributed along the growth direction, with the additional constraint that barriers (wells) of one kind always appear in triply. It is shown that the intentional correlations in disorder and superlattices structural parameters are responsible to obtain resonant tunneling in aperiodic structure.

Spatial and temporal variation of sources contributing to quasi-ultrafine particulate matter PM0.36 in Augsburg, Germany.

PubMed

Li, Fengxia; Schnelle-Kreis, Jürgen; Cyrys, Josef; Wolf, Kathrin; Karg, Erwin; Gu, Jianwei; Orasche, Jürgen; Abbaszade, Gülcin; Peters, Annette; Zimmermann, Ralf

2018-08-01

to study the sources contributing to quasi-ultrafine particle (UFP) organic carbon and the spatial temporal variability of the sources. 24h quasi-UFP (particulate matter <0.36μm in this study) was sampled at a reference site continuously and at one of 5 other sites (T1, T2, T3, T4 and B1) in parallel in Augsburg, Germany from April 11th, 2014 to February 22nd, 2015, attempting to conduct 2-week campaigns at each site in 3 different seasons. Positive matrix factorization (PMF) was applied to measured organic tracers for source apportionment analyses. Pearson correlation coefficient r and coefficient of divergence (COD) were calculated to investigate spatial temporal variation of source contributions. 5 sources were identified comprising biomass burning (BB), traffic emissions (Traffic), biogenic secondary organic aerosol (bioSOA), isoprene originated secondary organic aerosol (isoSOA) and biomass burning related secondary organic aerosol (bbSOA). In general, good temporal correlation and uniform distribution within the study area are found for bioSOA and bbSOA, probably resulting from regional formation/transport. Lower temporal correlation and spatial heterogeneity of isoSOA were found at the city background site with local influence from green space and less traffic impact. BB demonstrated very good temporal correlation, but higher contributions at sites influenced by local residential heating emissions were observed. Traffic showed the least seasonality and lower correlation over time among the sources. However, it demonstrated low spatial heterogeneity of absolute contribution, and only a few days of elevated contribution was found at T3 when wind came directly from the street nearby. temporal correlation and spatial variability of sources contributing to the organic fraction of quasi-UFP vary among sites and source types and show source-specific characteristics. Therefore, caution should be taken when using one monitor site measurement to assess human exposure in health effect studies of quasi-UFP. Copyright © 2018 Elsevier B.V. All rights reserved.

Moving Sound Source Localization Based on Sequential Subspace Estimation in Actual Room Environments

NASA Astrophysics Data System (ADS)

Tsuji, Daisuke; Suyama, Kenji

This paper presents a novel method for moving sound source localization and its performance evaluation in actual room environments. The method is based on the MUSIC (MUltiple SIgnal Classification) which is one of the most high resolution localization methods. When using the MUSIC, a computation of eigenvectors of correlation matrix is required for the estimation. It needs often a high computational costs. Especially, in the situation of moving source, it becomes a crucial drawback because the estimation must be conducted at every the observation time. Moreover, since the correlation matrix varies its characteristics due to the spatial-temporal non-stationarity, the matrix have to be estimated using only a few observed samples. It makes the estimation accuracy degraded. In this paper, the PAST (Projection Approximation Subspace Tracking) is applied for sequentially estimating the eigenvectors spanning the subspace. In the PAST, the eigen-decomposition is not required, and therefore it is possible to reduce the computational costs. Several experimental results in the actual room environments are shown to present the superior performance of the proposed method.

Interatomic interaction effects on second-order momentum correlations and Hong-Ou-Mandel interference of double-well-trapped ultracold fermionic atoms

NASA Astrophysics Data System (ADS)

Brandt, Benedikt B.; Yannouleas, Constantine; Landman, Uzi

2018-05-01

Identification and understanding of the evolution of interference patterns in two-particle momentum correlations as a function of the strength of interatomic interactions are important in explorations of the nature of quantum states of trapped particles. Together with the analysis of two-particle spatial correlations, they offer the prospect of uncovering fundamental symmetries and structure of correlated many-body states, as well as opening vistas into potential control and utilization of correlated quantum states as quantum-information resources. With the use of the second-order density matrix constructed via exact diagonalization of the microscopic Hamiltonian, and an analytic Hubbard-type model, we explore here the systematic evolution of characteristic interference patterns in the two-body momentum and spatial correlation maps of two entangled ultracold fermionic atoms in a double well, for the entire attractive- and repulsive-interaction range. We uncover quantum-statistics-governed bunching and antibunching, as well as interaction-dependent interference patterns, in the ground and excited states, and interpret our results in light of the Hong-Ou-Mandel interference physics, widely exploited in photon indistinguishability testing and quantum-information science.

A Gaussian random field model for similarity-based smoothing in Bayesian disease mapping.

PubMed

Baptista, Helena; Mendes, Jorge M; MacNab, Ying C; Xavier, Miguel; Caldas-de-Almeida, José

2016-08-01

Conditionally specified Gaussian Markov random field (GMRF) models with adjacency-based neighbourhood weight matrix, commonly known as neighbourhood-based GMRF models, have been the mainstream approach to spatial smoothing in Bayesian disease mapping. In the present paper, we propose a conditionally specified Gaussian random field (GRF) model with a similarity-based non-spatial weight matrix to facilitate non-spatial smoothing in Bayesian disease mapping. The model, named similarity-based GRF, is motivated for modelling disease mapping data in situations where the underlying small area relative risks and the associated determinant factors do not vary systematically in space, and the similarity is defined by "similarity" with respect to the associated disease determinant factors. The neighbourhood-based GMRF and the similarity-based GRF are compared and accessed via a simulation study and by two case studies, using new data on alcohol abuse in Portugal collected by the World Mental Health Survey Initiative and the well-known lip cancer data in Scotland. In the presence of disease data with no evidence of positive spatial correlation, the simulation study showed a consistent gain in efficiency from the similarity-based GRF, compared with the adjacency-based GMRF with the determinant risk factors as covariate. This new approach broadens the scope of the existing conditional autocorrelation models. © The Author(s) 2016.

Repeated decompositions reveal the stability of infomax decomposition of fMRI data

PubMed Central

Duann, Jeng-Ren; Jung, Tzyy-Ping; Sejnowski, Terrence J.; Makeig, Scott

2010-01-01

In this study, we decomposed 12 fMRI data sets from six subjects each 101 times using the infomax algorithm. The first decomposition was taken as a reference decomposition; the others were used to form a component matrix of 100 by 100 components. Equivalence relations between components in this matrix, defined as maximum spatial correlations to the components of the reference decomposition, were found by the Hungarian sorting method and used to form 100 equivalence classes for each data set. We then tested the reproducibility of the matched components in the equivalence classes using uncertainty measures based on component distributions, time courses, and ROC curves. Infomax ICA rarely failed to derive nearly the same components in different decompositions. Very few components per data set were poorly reproduced, even using vector angle uncertainty measures stricter than correlation and detection theory measures. PMID:17281453

Structuring Stokes correlation functions using vector-vortex beam

NASA Astrophysics Data System (ADS)

Kumar, Vijay; Anwar, Ali; Singh, R. P.

2018-01-01

Higher order statistical correlations of the optical vector speckle field, formed due to scattering of a vector-vortex beam, are explored. Here, we report on the experimental construction of the Stokes parameters covariance matrix, consisting of all possible spatial Stokes parameters correlation functions. We also propose and experimentally realize a new Stokes correlation functions called Stokes field auto correlation functions. It is observed that the Stokes correlation functions of the vector-vortex beam will be reflected in the respective Stokes correlation functions of the corresponding vector speckle field. The major advantage of proposing Stokes correlation functions is that the Stokes correlation function can be easily tuned by manipulating the polarization of vector-vortex beam used to generate vector speckle field and to get the phase information directly from the intensity measurements. Moreover, this approach leads to a complete experimental Stokes characterization of a broad range of random fields.

Neural Representation of Spatial Topology in the Rodent Hippocampus

PubMed Central

Chen, Zhe; Gomperts, Stephen N.; Yamamoto, Jun; Wilson, Matthew A.

2014-01-01

Pyramidal cells in the rodent hippocampus often exhibit clear spatial tuning in navigation. Although it has been long suggested that pyramidal cell activity may underlie a topological code rather than a topographic code, it remains unclear whether an abstract spatial topology can be encoded in the ensemble spiking activity of hippocampal place cells. Using a statistical approach developed previously, we investigate this question and related issues in greater details. We recorded ensembles of hippocampal neurons as rodents freely foraged in one and two-dimensional spatial environments, and we used a “decode-to-uncover” strategy to examine the temporally structured patterns embedded in the ensemble spiking activity in the absence of observed spatial correlates during periods of rodent navigation or awake immobility. Specifically, the spatial environment was represented by a finite discrete state space. Trajectories across spatial locations (“states”) were associated with consistent hippocampal ensemble spiking patterns, which were characterized by a state transition matrix. From this state transition matrix, we inferred a topology graph that defined the connectivity in the state space. In both one and two-dimensional environments, the extracted behavior patterns from the rodent hippocampal population codes were compared against randomly shuffled spike data. In contrast to a topographic code, our results support the efficiency of topological coding in the presence of sparse sample size and fuzzy space mapping. This computational approach allows us to quantify the variability of ensemble spiking activity, to examine hippocampal population codes during off-line states, and to quantify the topological complexity of the environment. PMID:24102128

Relative Contribution of Matrix Structure, Patch Resources and Management to the Local Densities of Two Large Blue Butterfly Species

PubMed Central

Skórka, Piotr; Nowicki, Piotr; Bonk, Maciej; Król, Wiesław; Szpiłyk, Damian; Woyciechowski, Michal

2016-01-01

The type of matrix, the landscape surrounding habitat patches, may determine the distribution and function of local populations. However, the matrix is often heterogeneous, and its various components may differentially contribute to metapopulation processes at different spatial scales, a phenomenon that has rarely been investigated. The aim of this study was to estimate the relative importance of matrix composition and spatial scale, habitat quality, and management intensity on the occurrence and density of local populations of two endangered large blue butterflies: Phengaris teleius and P. nausithous. Presence and abundance data were assessed over two years, 2011–12, in 100 local patches within two heterogeneous regions (near Kraków and Tarnów, southern Poland). The matrix composition was analyzed at eight spatial scales. We observed high occupancy rates in both species, regions and years. With the exception of area and isolation, almost all of the matrix components contributed to Phengaris sp. densities. The different matrix components acted at different spatial scales (grassland cover within 4 and 3 km, field cover within 0.4 and 0.3 km and water cover within 4 km radii for P. teleius and P. nausithous, respectively) and provided the highest independent contribution to the butterfly densities. Additionally, the effects of a 0.4 km radius of forest cover and a food plant cover on P. teleius, and a 1 km radius of settlement cover and management intensity on P. nausithous densities were observed. Contrary to former studies we conclude that the matrix heterogeneity and spatial scale rather than general matrix type are of relevance for densities of butterflies. Conservation strategies for these umbrella species should concentrate on maintaining habitat quality and managing matrix composition at the most appropriate spatial scales. PMID:28005942

Relative Contribution of Matrix Structure, Patch Resources and Management to the Local Densities of Two Large Blue Butterfly Species.

PubMed

Kajzer-Bonk, Joanna; Skórka, Piotr; Nowicki, Piotr; Bonk, Maciej; Król, Wiesław; Szpiłyk, Damian; Woyciechowski, Michal

2016-01-01

The type of matrix, the landscape surrounding habitat patches, may determine the distribution and function of local populations. However, the matrix is often heterogeneous, and its various components may differentially contribute to metapopulation processes at different spatial scales, a phenomenon that has rarely been investigated. The aim of this study was to estimate the relative importance of matrix composition and spatial scale, habitat quality, and management intensity on the occurrence and density of local populations of two endangered large blue butterflies: Phengaris teleius and P. nausithous. Presence and abundance data were assessed over two years, 2011-12, in 100 local patches within two heterogeneous regions (near Kraków and Tarnów, southern Poland). The matrix composition was analyzed at eight spatial scales. We observed high occupancy rates in both species, regions and years. With the exception of area and isolation, almost all of the matrix components contributed to Phengaris sp. densities. The different matrix components acted at different spatial scales (grassland cover within 4 and 3 km, field cover within 0.4 and 0.3 km and water cover within 4 km radii for P. teleius and P. nausithous, respectively) and provided the highest independent contribution to the butterfly densities. Additionally, the effects of a 0.4 km radius of forest cover and a food plant cover on P. teleius, and a 1 km radius of settlement cover and management intensity on P. nausithous densities were observed. Contrary to former studies we conclude that the matrix heterogeneity and spatial scale rather than general matrix type are of relevance for densities of butterflies. Conservation strategies for these umbrella species should concentrate on maintaining habitat quality and managing matrix composition at the most appropriate spatial scales.

Robust mosiacs of close-range high-resolution images

NASA Astrophysics Data System (ADS)

Song, Ran; Szymanski, John E.

2008-03-01

This paper presents a robust algorithm which relies only on the information contained within the captured images for the construction of massive composite mosaic images from close-range and high-resolution originals, such as those obtained when imaging architectural and heritage structures. We first apply Harris algorithm to extract a selection of corners and, then, employ both the intensity correlation and the spatial correlation between the corresponding corners for matching them. Then we estimate the eight-parameter projective transformation matrix by the genetic algorithm. Lastly, image fusion using a weighted blending function together with intensity compensation produces an effective seamless mosaic image.

Bath-induced correlations in an infinite-dimensional Hilbert space

NASA Astrophysics Data System (ADS)

Nizama, Marco; Cáceres, Manuel O.

2017-09-01

Quantum correlations between two free spinless dissipative distinguishable particles (interacting with a thermal bath) are studied analytically using the quantum master equation and tools of quantum information. Bath-induced coherence and correlations in an infinite-dimensional Hilbert space are shown. We show that for temperature T> 0 the time-evolution of the reduced density matrix cannot be written as the direct product of two independent particles. We have found a time-scale that characterizes the time when the bath-induced coherence is maximum before being wiped out by dissipation (purity, relative entropy, spatial dispersion, and mirror correlations are studied). The Wigner function associated to the Wannier lattice (where the dissipative quantum walks move) is studied as an indirect measure of the induced correlations among particles. We have supported the quantum character of the correlations by analyzing the geometric quantum discord.

The spatiotemporal characteristics of environmental hazards caused by offshore oil and gas operations in the Gulf of Mexico.

PubMed

Meng, Qingmin

2016-09-15

Marine ecosystems are home to a host of numerous species ranging from tiny planktonic organisms, fishes, and birds, to large mammals such as the whales, manatees, and seals. However, human activities such as offshore oil and gas operations increasingly threaten marine and coastal ecosystems, for which there has been little exploration into the spatial and temporal risks of offshore oil operations. Using the Gulf of Mexico, one of the world's hottest spots of offshore oil and gas mining, as the study area, we propose a spatiotemporal approach that integrates spatial statistics and geostatistics in a geographic information system environment to provide insight to environmental management and decision making for oil and gas operators, coastal communities, local governments, and the federal government. We use the records from 1995 to 2015 of twelve types of hazards caused by offshore oil and gas operations, and analyze them spatially over a five year period. The spatial clusters of these hazards are analyzed and mapped using Getis-Ord Gi and local Moran's I statistics. We then design a spatial correlation coefficient matrix for multivariate spatial correlation, which is the ratio of the cross variogram of two types of hazards to the product of the variograms of the two hazards, showing a primary understanding of the degrees of spatial correlation among the twelve types hazards. To the best of our knowledge, it is the first application of spatiotemporal analysis methods to environmental hazards caused by offshore oil and gas operations; the proposed methods can be applied to other regions for the management and monitoring of environmental hazards caused by offshore oil operations. Copyright © 2016 Elsevier B.V. All rights reserved.

Implementations of geographically weighted lasso in spatial data with multicollinearity (Case study: Poverty modeling of Java Island)

NASA Astrophysics Data System (ADS)

Setiyorini, Anis; Suprijadi, Jadi; Handoko, Budhi

2017-03-01

Geographically Weighted Regression (GWR) is a regression model that takes into account the spatial heterogeneity effect. In the application of the GWR, inference on regression coefficients is often of interest, as is estimation and prediction of the response variable. Empirical research and studies have demonstrated that local correlation between explanatory variables can lead to estimated regression coefficients in GWR that are strongly correlated, a condition named multicollinearity. It later results on a large standard error on estimated regression coefficients, and, hence, problematic for inference on relationships between variables. Geographically Weighted Lasso (GWL) is a method which capable to deal with spatial heterogeneity and local multicollinearity in spatial data sets. GWL is a further development of GWR method, which adds a LASSO (Least Absolute Shrinkage and Selection Operator) constraint in parameter estimation. In this study, GWL will be applied by using fixed exponential kernel weights matrix to establish a poverty modeling of Java Island, Indonesia. The results of applying the GWL to poverty datasets show that this method stabilizes regression coefficients in the presence of multicollinearity and produces lower prediction and estimation error of the response variable than GWR does.

Local Geostatistical Models and Big Data in Hydrological and Ecological Applications

NASA Astrophysics Data System (ADS)

Hristopulos, Dionissios

2015-04-01

The advent of the big data era creates new opportunities for environmental and ecological modelling but also presents significant challenges. The availability of remote sensing images and low-cost wireless sensor networks implies that spatiotemporal environmental data to cover larger spatial domains at higher spatial and temporal resolution for longer time windows. Handling such voluminous data presents several technical and scientific challenges. In particular, the geostatistical methods used to process spatiotemporal data need to overcome the dimensionality curse associated with the need to store and invert large covariance matrices. There are various mathematical approaches for addressing the dimensionality problem, including change of basis, dimensionality reduction, hierarchical schemes, and local approximations. We present a Stochastic Local Interaction (SLI) model that can be used to model local correlations in spatial data. SLI is a random field model suitable for data on discrete supports (i.e., regular lattices or irregular sampling grids). The degree of localization is determined by means of kernel functions and appropriate bandwidths. The strength of the correlations is determined by means of coefficients. In the "plain vanilla" version the parameter set involves scale and rigidity coefficients as well as a characteristic length. The latter determines in connection with the rigidity coefficient the correlation length of the random field. The SLI model is based on statistical field theory and extends previous research on Spartan spatial random fields [2,3] from continuum spaces to explicitly discrete supports. The SLI kernel functions employ adaptive bandwidths learned from the sampling spatial distribution [1]. The SLI precision matrix is expressed explicitly in terms of the model parameter and the kernel function. Hence, covariance matrix inversion is not necessary for parameter inference that is based on leave-one-out cross validation. This property helps to overcome a significant computational bottleneck of geostatistical models due to the poor scaling of the matrix inversion [4,5]. We present applications to real and simulated data sets, including the Walker lake data, and we investigate the SLI performance using various statistical cross validation measures. References [1] T. Hofmann, B. Schlkopf, A.J. Smola, Annals of Statistics, 36, 1171-1220 (2008). [2] D. T. Hristopulos, SIAM Journal on Scientific Computing, 24(6): 2125-2162 (2003). [3] D. T. Hristopulos and S. N. Elogne, IEEE Transactions on Signal Processing, 57(9): 3475-3487 (2009) [4] G. Jona Lasinio, G. Mastrantonio, and A. Pollice, Statistical Methods and Applications, 22(1):97-112 (2013) [5] Sun, Y., B. Li, and M. G. Genton (2012). Geostatistics for large datasets. In: Advances and Challenges in Space-time Modelling of Natural Events, Lecture Notes in Statistics, pp. 55-77. Springer, Berlin-Heidelberg.

Near-lossless multichannel EEG compression based on matrix and tensor decompositions.

PubMed

Dauwels, Justin; Srinivasan, K; Reddy, M Ramasubba; Cichocki, Andrzej

2013-05-01

A novel near-lossless compression algorithm for multichannel electroencephalogram (MC-EEG) is proposed based on matrix/tensor decomposition models. MC-EEG is represented in suitable multiway (multidimensional) forms to efficiently exploit temporal and spatial correlations simultaneously. Several matrix/tensor decomposition models are analyzed in view of efficient decorrelation of the multiway forms of MC-EEG. A compression algorithm is built based on the principle of “lossy plus residual coding,” consisting of a matrix/tensor decomposition-based coder in the lossy layer followed by arithmetic coding in the residual layer. This approach guarantees a specifiable maximum absolute error between original and reconstructed signals. The compression algorithm is applied to three different scalp EEG datasets and an intracranial EEG dataset, each with different sampling rate and resolution. The proposed algorithm achieves attractive compression ratios compared to compressing individual channels separately. For similar compression ratios, the proposed algorithm achieves nearly fivefold lower average error compared to a similar wavelet-based volumetric MC-EEG compression algorithm.

Gene expression based mouse brain parcellation using Markov random field regularized non-negative matrix factorization

NASA Astrophysics Data System (ADS)

Pathak, Sayan D.; Haynor, David R.; Thompson, Carol L.; Lein, Ed; Hawrylycz, Michael

2009-02-01

Understanding the geography of genetic expression in the mouse brain has opened previously unexplored avenues in neuroinformatics. The Allen Brain Atlas (www.brain-map.org) (ABA) provides genome-wide colorimetric in situ hybridization (ISH) gene expression images at high spatial resolution, all mapped to a common three-dimensional 200μm3 spatial framework defined by the Allen Reference Atlas (ARA) and is a unique data set for studying expression based structural and functional organization of the brain. The goal of this study was to facilitate an unbiased data-driven structural partitioning of the major structures in the mouse brain. We have developed an algorithm that uses nonnegative matrix factorization (NMF) to perform parts based analysis of ISH gene expression images. The standard NMF approach and its variants are limited in their ability to flexibly integrate prior knowledge, in the context of spatial data. In this paper, we introduce spatial connectivity as an additional regularization in NMF decomposition via the use of Markov Random Fields (mNMF). The mNMF algorithm alternates neighborhood updates with iterations of the standard NMF algorithm to exploit spatial correlations in the data. We present the algorithm and show the sub-divisions of hippocampus and somatosensory-cortex obtained via this approach. The results are compared with established neuroanatomic knowledge. We also highlight novel gene expression based sub divisions of the hippocampus identified by using the mNMF algorithm.

How reactive fluids alter fracture walls and affect shale-matrix accessibility

NASA Astrophysics Data System (ADS)

Fitts, J. P.; Deng, H.; Peters, C. A.

2014-12-01

Predictions of mass transfer across fracture boundaries and fluid flow in fracture networks provide fundamental inputs into risk and life cycle assessments of geologic energy technologies including oil and gas extraction, geothermal energy systems and geologic CO2 storage. However, major knowledge gaps exist due to the lack of experimental observations of how reactive fluids alter the pore structures and accessible surface area within fracture boundaries that control the mass transfer of organics, metals and salts, and influence fluid flow within the fracture. To investigate the fracture and rock matrix properties governing fracture boundary alteration, we developed a new flow-through cell that enables time-dependent 2D x-ray imaging of mineral dissolution and/or precipitation at a fracture surface. The parallel plate design provides an idealized fracture geometry to investigate the relationship between flow rate, reaction rate, and mineral spatial heterogeneity and variation. In the flow-cell, a carbonate-rich sample of Eagle Ford shale was reacted with acidified brine. The extent and rate of mineral dissolution were correlated with calcite abundance relative to less soluble silicate minerals. Three-dimensional x-ray tomography of the reacted fracture wall shows how calcite dissolution left behind a porous network of silicate minerals. And while this silicate network essentially preserved the location of the initial fracture wall, the pore network structures within the fracture boundary were dramatically altered, such that the accessible surface area of matrix components increased significantly. In a second set of experiments with a limestone specimen, however, the extent of dissolution and retreat of the fracture wall was not strictly correlated with the occurrence of calcite. Instead, the pattern and extent of dissolution suggested secondary causes such as calcite morphology, the presence of argillaceous minerals and other diagenetic features. Our experiments show that while calcite dissolution is the primary geochemical driver of fracture wall alterations, hydrodynamic properties and matrix accessibility within fracture boundaries evolve based on a complex relationship between mineral spatial heterogeneity and variation, fluid chemistry and flow rate.

Recursive flexible multibody system dynamics using spatial operators

NASA Technical Reports Server (NTRS)

Jain, A.; Rodriguez, G.

1992-01-01

This paper uses spatial operators to develop new spatially recursive dynamics algorithms for flexible multibody systems. The operator description of the dynamics is identical to that for rigid multibody systems. Assumed-mode models are used for the deformation of each individual body. The algorithms are based on two spatial operator factorizations of the system mass matrix. The first (Newton-Euler) factorization of the mass matrix leads to recursive algorithms for the inverse dynamics, mass matrix evaluation, and composite-body forward dynamics for the systems. The second (innovations) factorization of the mass matrix, leads to an operator expression for the mass matrix inverse and to a recursive articulated-body forward dynamics algorithm. The primary focus is on serial chains, but extensions to general topologies are also described. A comparison of computational costs shows that the articulated-body, forward dynamics algorithm is much more efficient than the composite-body algorithm for most flexible multibody systems.

Evaluating wilderness recreational opportunities: application of an impact matrix

USGS Publications Warehouse

Stohlgren, Thomas J.; Parsons, David J.

1992-01-01

An inventory of the severity and spatial distribution of wilderness campsite impacts in Sequoia and Kings Canyon National Parks identified a total of 273 distinct nodes of campsites or “management areas.” A campsite impact matrix was developed to evaluate management areas based on total impacts (correlated to the total area of campsite development) and the density, or concentration, of impacts relative to each area's potentially campable area. The matrix is used to quantify potential recreational opportunities for wilderness visitors in a spectrum from areas offering low impact-dispersed camping to those areas offering high impact-concentrated camping. Wilderness managers can use this type of information to evaluate use distribution patterns, identify areas to increase or decrease use, and to identify areas needing site-specific regulations (e.g., one-night camping limits) to preserve wilderness resources and guarantee outstanding opportunities for solitude.

Correlation of spatial climate/weather maps and the advantages of using the Mahalanobis metric in predictions

NASA Astrophysics Data System (ADS)

Stephenson, D. B.

1997-10-01

The skill in predicting spatially varying weather/climate maps depends on the definition of the measure of similarity between the maps. Under the justifiable approximation that the anomaly maps are distributed multinormally, it is shown analytically that the choice of weighting metric, used in defining the anomaly correlation between spatial maps, can change the resulting probability distribution of the correlation coefficient. The estimate of the numbers of degrees of freedom based on the variance of the correlation distribution can vary from unity up to the number of grid points depending on the choice of weighting metric. The (pseudo-) inverse of the sample covariance matrix acts as a special choice for the metric in that it gives a correlation distribution which has minimal kurtosis and maximum dimension. Minimal kurtosis suggests that the average predictive skill might be improved due to the rarer occurrence of troublesome outlier patterns far from the mean state. Maximum dimension has a disadvantage for analogue prediction schemes in that it gives the minimum number of analogue states. This metric also has an advantage in that it allows one to powerfully test the null hypothesis of multinormality by examining the second and third moments of the correlation coefficient which were introduced by Mardia as invariant measures of multivariate kurtosis and skewness. For these reasons, it is suggested that this metric could be usefully employed in the prediction of weather/climate and in fingerprinting anthropogenic climate change. The ideas are illustrated using the bivariate example of the observed monthly mean sea-level pressures at Darwin and Tahitifrom 1866 1995.

Spatial and temporal variability of fine particle composition and source types in five cities of Connecticut and Massachusetts

PubMed Central

Lee, Hyung Joo; Gent, Janneane F.; Leaderer, Brian P.; Koutrakis, Petros

2011-01-01

To protect public health from PM2.5 air pollution, it is critical to identify the source types of PM2.5 mass and chemical components associated with higher risks of adverse health outcomes. Source apportionment modeling using Positive Matrix Factorization (PMF), was used to identify PM2.5 source types and quantify the source contributions to PM2.5 in five cities of Connecticut and Massachusetts. Spatial and temporal variability of PM2.5 mass, components and source contributions were investigated. PMF analysis identified five source types: regional pollution as traced by sulfur, motor vehicle, road dust, oil combustion and sea salt. The sulfur-related regional pollution and traffic source type were major contributors to PM2.5. Due to sparse ground-level PM2.5 monitoring sites, current epidemiological studies are susceptible to exposure measurement errors. The higher correlations in concentrations and source contributions between different locations suggest less spatial variability, resulting in less exposure measurement errors. When concentrations and/or contributions were compared to regional averages, correlations were generally higher than between-site correlations. This suggests that for assigning exposures for health effects studies, using regional average concentrations or contributions from several PM2.5 monitors is more reliable than using data from the nearest central monitor. PMID:21429560

Measurement of correlations between low-frequency vibrational modes and particle rearrangements in quasi-two-dimensional colloidal glasses.

PubMed

Chen, Ke; Manning, M L; Yunker, Peter J; Ellenbroek, Wouter G; Zhang, Zexin; Liu, Andrea J; Yodh, A G

2011-09-02

We investigate correlations between low-frequency vibrational modes and rearrangements in two-dimensional colloidal glasses composed of thermosensitive microgel particles, which readily permit variation of the sample packing fraction. At each packing fraction, the particle displacement covariance matrix is measured and used to extract the vibrational spectrum of the "shadow" colloidal glass (i.e., the particle network with the same geometry and interactions as the sample colloid but absent damping). Rearrangements are induced by successive, small reductions in the packing fraction. The experimental results suggest that low-frequency quasilocalized phonon modes in colloidal glasses, i.e., modes that present low energy barriers for system rearrangements, are spatially correlated with rearrangements in this thermal system.

First and second order stereology of hyaline cartilage: Application on mice femoral cartilage.

PubMed

Noorafshan, Ali; Niazi, Behnam; Mohamadpour, Masoomeh; Hoseini, Leila; Hoseini, Najmeh; Owji, Ali Akbar; Rafati, Ali; Sadeghi, Yasaman; Karbalay-Doust, Saied

2016-11-01

Stereological techniques could be considered in research on cartilage to obtain quantitative data. The present study aimed to explain application of the first- and second-order stereological methods on articular cartilage of mice and the methods applied on the mice exposed to cadmium (Cd). The distal femoral articular cartilage of BALB/c mice (control and Cd-treated) was removed. Then, volume and surface area of the cartilage and number of chondrocytes were estimated using Cavalieri and optical dissector techniques on isotropic uniform random sections. Pair-correlation function [g(r)] and cross-correlation function were calculated to express the spatial arrangement of chondrocytes-chondrocytes and chondrocytes-matrix (chondrocyte clustering/dispersing), respectively. The mean±standard deviation of the cartilage volume, surface area, and thickness were 1.4±0.1mm 3 , 26.2±5.4mm 2 , and 52.8±6.7μm, respectively. Besides, the mean number of chondrocytes was 680±200 (×10 3 ). The cartilage volume, cartilage surface area, and number of chondrocytes were respectively reduced by 25%, 27%, and 27% in the Cd-treated mice in comparison to the control animals (p<0.03). Estimates of g(r) for the cells and matrix against the dipole distances, r, have been plotted. This plot showed that the chondrocytes and the matrix were neither dispersed nor clustered in the two study groups. Application of design-based stereological methods and also evaluation of spatial arrangement of the cartilage components carried potential advantages for investigating the cartilage in different joint conditions. Chondrocyte clustering/dispersing and cellularity can be evaluated in cartilage assessment in normal or abnormal situations. Copyright © 2016 Elsevier GmbH. All rights reserved.

Classification of fMRI resting-state maps using machine learning techniques: A comparative study

NASA Astrophysics Data System (ADS)

Gallos, Ioannis; Siettos, Constantinos

2017-11-01

We compare the efficiency of Principal Component Analysis (PCA) and nonlinear learning manifold algorithms (ISOMAP and Diffusion maps) for classifying brain maps between groups of schizophrenia patients and healthy from fMRI scans during a resting-state experiment. After a standard pre-processing pipeline, we applied spatial Independent component analysis (ICA) to reduce (a) noise and (b) spatial-temporal dimensionality of fMRI maps. On the cross-correlation matrix of the ICA components, we applied PCA, ISOMAP and Diffusion Maps to find an embedded low-dimensional space. Finally, support-vector-machines (SVM) and k-NN algorithms were used to evaluate the performance of the algorithms in classifying between the two groups.

Estimation of positive semidefinite correlation matrices by using convex quadratic semidefinite programming.

PubMed

Fushiki, Tadayoshi

2009-07-01

The correlation matrix is a fundamental statistic that is used in many fields. For example, GroupLens, a collaborative filtering system, uses the correlation between users for predictive purposes. Since the correlation is a natural similarity measure between users, the correlation matrix may be used in the Gram matrix in kernel methods. However, the estimated correlation matrix sometimes has a serious defect: although the correlation matrix is originally positive semidefinite, the estimated one may not be positive semidefinite when not all ratings are observed. To obtain a positive semidefinite correlation matrix, the nearest correlation matrix problem has recently been studied in the fields of numerical analysis and optimization. However, statistical properties are not explicitly used in such studies. To obtain a positive semidefinite correlation matrix, we assume the approximate model. By using the model, an estimate is obtained as the optimal point of an optimization problem formulated with information on the variances of the estimated correlation coefficients. The problem is solved by a convex quadratic semidefinite program. A penalized likelihood approach is also examined. The MovieLens data set is used to test our approach.

Efficient spectroscopic imaging by an optimized encoding of pre-targeted resonances

PubMed Central

Zhang, Zhiyong; Shemesh, Noam; Frydman, Lucio

2016-01-01

A “relaxation-enhanced” (RE) selective-excitation approach to acquire in vivo localized spectra with flat baselines and very good signal-to-noise ratios –particularly at high fields– has been recently proposed. As RE MRS targets a subset of a priori known resonances, new possibilities arise to acquire spectroscopic imaging data in a faster, more efficient manner. Hereby we present one such opportunity based on what we denominate Relaxation-Enhanced Chemical-shift-Encoded Spectroscopically-Separated (RECESS) imaging. RECESS delivers spectral/spatial correlations of various metabolites, by collecting a gradient echo train whose timing is defined by the chemical shifts of the various selectively excited resonances to be disentangled. Different sites thus impart distinct, coherent phase modulations on the images; condition number considerations allow one to disentangle these contributions of the various sites by a simple matrix inversion. The efficiency of the ensuing spectral/spatial correlation method is high enough to enable the examination of additional spatial axes via their phase encoding in CPMG-like spin-echo trains. The ensuing single-shot 1D spectral / 2D spatial RECESS method thus accelerates the acquisition of quality MRSI data by factors that, depending on the sensitivity, range between 2 and 50. This is illustrated with a number of phantom, of ex vivo and of in vivo acquisitions. PMID:26910285

Graphene Oxide as a Novel Evenly Continuous Phase Matrix for TOF-SIMS.

PubMed

Cai, Lesi; Sheng, Linfeng; Xia, Mengchan; Li, Zhanping; Zhang, Sichun; Zhang, Xinrong; Chen, Hongyuan

2017-03-01

Using matrix to enhance the molecular ion signals for biomolecule identification without loss of spatial resolution caused by matrix crystallization is a great challenge for the application of TOF-SIMS in real-world biological research. In this report, graphene oxide (GO) was used as a matrix for TOF-SIMS to improve the secondary ion yields of intact molecular ions ([M + H] + ). Identifying and distinguishing the molecular ions of lipids (m/z >700) therefore became straightforward. The spatial resolution of TOF-SIMS imaging could also be improved as GO can form a homogeneous layer of matrix instead of crystalline domain, which prevents high spatial resolution in TOF-SIMS imaging. Lipid mapping in presence of GO revealed the delicate morphology and distribution of single vesicles with a diameter of 800 nm. On GO matrix, the vesicles with similar shape but different chemical composition could be distinguished using molecular ions. This novel matrix holds potentials in such applications as the analysis and imaging of complex biological samples by TOF-SIMS. Graphical Abstract ᅟ.

Graphene Oxide as a Novel Evenly Continuous Phase Matrix for TOF-SIMS

NASA Astrophysics Data System (ADS)

Cai, Lesi; Sheng, Linfeng; Xia, Mengchan; Li, Zhanping; Zhang, Sichun; Zhang, Xinrong; Chen, Hongyuan

2017-03-01

Using matrix to enhance the molecular ion signals for biomolecule identification without loss of spatial resolution caused by matrix crystallization is a great challenge for the application of TOF-SIMS in real-world biological research. In this report, graphene oxide (GO) was used as a matrix for TOF-SIMS to improve the secondary ion yields of intact molecular ions ([M + H]+). Identifying and distinguishing the molecular ions of lipids ( m/z >700) therefore became straightforward. The spatial resolution of TOF-SIMS imaging could also be improved as GO can form a homogeneous layer of matrix instead of crystalline domain, which prevents high spatial resolution in TOF-SIMS imaging. Lipid mapping in presence of GO revealed the delicate morphology and distribution of single vesicles with a diameter of 800 nm. On GO matrix, the vesicles with similar shape but different chemical composition could be distinguished using molecular ions. This novel matrix holds potentials in such applications as the analysis and imaging of complex biological samples by TOF-SIMS.

Using phase information to enhance speckle noise reduction in the ultrasonic NDE of coarse grain materials

NASA Astrophysics Data System (ADS)

Lardner, Timothy; Li, Minghui; Gachagan, Anthony

2014-02-01

Materials with a coarse grain structure are becoming increasingly prevalent in industry due to their resilience to stress and corrosion. These materials are difficult to inspect with ultrasound because reflections from the grains lead to high noise levels which hinder the echoes of interest. Spatially Averaged Sub-Aperture Correlation Imaging (SASACI) is an advanced array beamforming technique that uses the cross-correlation between images from array sub-apertures to generate an image weighting matrix, in order to reduce noise levels. This paper presents a method inspired by SASACI to further improve imaging using phase information to refine focusing and reduce noise. A-scans from adjacent array elements are cross-correlated using both signal amplitude and phase to refine delay laws and minimize phase aberration. The phase-based and amplitude-based corrected images are used as inputs to a two-dimensional cross-correlation algorithm that will output a weighting matrix that can be applied to any conventional image. This approach was validated experimentally using a 5MHz array a coarse grained Inconel 625 step wedge, and compared to the Total Focusing Method (TFM). Initial results have seen SNR improvements of over 20dB compared to TFM, and a resolution that is much higher.

Finite element modeling predictions of region-specific cell-matrix mechanics in the meniscus.

PubMed

Upton, Maureen L; Guilak, Farshid; Laursen, Tod A; Setton, Lori A

2006-06-01

The knee meniscus exhibits significant spatial variations in biochemical composition and cell morphology that reflect distinct phenotypes of cells located in the radial inner and outer regions. Associated with these cell phenotypes is a spatially heterogeneous microstructure and mechanical environment with the innermost regions experiencing higher fluid pressures and lower tensile strains than the outer regions. It is presently unknown, however, how meniscus tissue mechanics correlate with the local micromechanical environment of cells. In this study, theoretical models were developed to study mechanics of inner and outer meniscus cells with varying geometries. The results for an applied biaxial strain predict significant regional differences in the cellular mechanical environment with evidence of tensile strains along the collagen fiber direction of approximately 0.07 for the rounded inner cells, as compared to levels of 0.02-0.04 for the elongated outer meniscus cells. The results demonstrate an important mechanical role of extracellular matrix anisotropy and cell morphology in regulating the region-specific micromechanics of meniscus cells, that may further play a role in modulating cellular responses to mechanical stimuli.

Least-Squares Approximation of an Improper Correlation Matrix by a Proper One.

ERIC Educational Resources Information Center

Knol, Dirk L.; ten Berge, Jos M. F.

1989-01-01

An algorithm, based on a solution for C. I. Mosier's oblique Procrustes rotation problem, is presented for the best least-squares fitting correlation matrix approximating a given missing value or improper correlation matrix. Results are of interest for missing value and tetrachoric correlation, indefinite matrix correlation, and constrained…

Posttranslational Amelogenin Processing and Changes in Matrix Assembly during Enamel Development

PubMed Central

Pandya, Mirali; Lin, Tiffani; Li, Leo; Allen, Michael J.; Jin, Tianquan; Luan, Xianghong; Diekwisch, Thomas G. H.

2017-01-01

The extracellular tooth enamel matrix is a unique, protein-rich environment that provides the structural basis for the growth of long and parallel oriented enamel crystals. Here we have conducted a series of in vivo and in vitro studies to characterize the changes in matrix shape and organization that take place during the transition from ameloblast intravesicular matrices to extracellular subunit compartments and pericrystalline sheath proteins, and correlated these changes with stages of amelogenin matrix protein posttranslational processing. Our transmission electron microscopic studies revealed a 2.5-fold difference in matrix subunit compartment dimensions between secretory vesicle and extracellular enamel protein matrix as well as conformational changes in matrix structure between vesicles, stippled materials, and pericrystalline matrix. Enamel crystal growth in organ culture demonstrated granular mineral deposits associated with the enamel matrix framework, dot-like mineral deposits along elongating initial enamel crystallites, and dramatic changes in enamel matrix configuration following the onset of enamel crystal formation. Atomic force micrographs provided evidence for the presence of both linear and hexagonal/ring-shaped full-length recombinant amelogenin protein assemblies on mica surfaces, while nickel-staining of the N-terminal amelogenin N92 His-tag revealed 20 nm diameter oval and globular amelogenin assemblies in N92 amelogenin matrices. Western blot analysis comparing loosely bound and mineral-associated protein fractions of developing porcine enamel organs, superficial and deep enamel layers demonstrated (i) a single, full-length amelogenin band in the enamel organ followed by 3 kDa cleavage upon entry into the enamel layer, (ii) a close association of 8–16 kDa C-terminal amelogenin cleavage products with the growing enamel apatite crystal surface, and (iii) a remaining pool of N-terminal amelogenin fragments loosely retained between the crystalline phases of the deep enamel layer. Together, our data establish a temporo-spatial correlation between amelogenin protein processing and the changes in enamel matrix configuration that take place during the transition from intracellular vesicle compartments to extracellular matrix assemblies and the formation of protein coats along elongating apatite crystal surfaces. In conclusion, our study suggests that enzymatic cleavage of the amelogenin enamel matrix protein plays a key role in the patterning of the organic matrix framework as it affects enamel apatite crystal growth and habit. PMID:29089900

Posttranslational Amelogenin Processing and Changes in Matrix Assembly during Enamel Development.

PubMed

Pandya, Mirali; Lin, Tiffani; Li, Leo; Allen, Michael J; Jin, Tianquan; Luan, Xianghong; Diekwisch, Thomas G H

2017-01-01

The extracellular tooth enamel matrix is a unique, protein-rich environment that provides the structural basis for the growth of long and parallel oriented enamel crystals. Here we have conducted a series of in vivo and in vitro studies to characterize the changes in matrix shape and organization that take place during the transition from ameloblast intravesicular matrices to extracellular subunit compartments and pericrystalline sheath proteins, and correlated these changes with stages of amelogenin matrix protein posttranslational processing. Our transmission electron microscopic studies revealed a 2.5-fold difference in matrix subunit compartment dimensions between secretory vesicle and extracellular enamel protein matrix as well as conformational changes in matrix structure between vesicles, stippled materials, and pericrystalline matrix. Enamel crystal growth in organ culture demonstrated granular mineral deposits associated with the enamel matrix framework, dot-like mineral deposits along elongating initial enamel crystallites, and dramatic changes in enamel matrix configuration following the onset of enamel crystal formation. Atomic force micrographs provided evidence for the presence of both linear and hexagonal/ring-shaped full-length recombinant amelogenin protein assemblies on mica surfaces, while nickel-staining of the N-terminal amelogenin N92 His-tag revealed 20 nm diameter oval and globular amelogenin assemblies in N92 amelogenin matrices. Western blot analysis comparing loosely bound and mineral-associated protein fractions of developing porcine enamel organs, superficial and deep enamel layers demonstrated (i) a single, full-length amelogenin band in the enamel organ followed by 3 kDa cleavage upon entry into the enamel layer, (ii) a close association of 8-16 kDa C-terminal amelogenin cleavage products with the growing enamel apatite crystal surface, and (iii) a remaining pool of N-terminal amelogenin fragments loosely retained between the crystalline phases of the deep enamel layer. Together, our data establish a temporo-spatial correlation between amelogenin protein processing and the changes in enamel matrix configuration that take place during the transition from intracellular vesicle compartments to extracellular matrix assemblies and the formation of protein coats along elongating apatite crystal surfaces. In conclusion, our study suggests that enzymatic cleavage of the amelogenin enamel matrix protein plays a key role in the patterning of the organic matrix framework as it affects enamel apatite crystal growth and habit.

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

PubMed

Han, Fang; Liu, Han

2017-02-01

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

Spatial and thematic assessment of object-based forest stand delineation using an OFA-matrix

NASA Astrophysics Data System (ADS)

Hernando, A.; Tiede, D.; Albrecht, F.; Lang, S.

2012-10-01

The delineation and classification of forest stands is a crucial aspect of forest management. Object-based image analysis (OBIA) can be used to produce detailed maps of forest stands from either orthophotos or very high resolution satellite imagery. However, measures are then required for evaluating and quantifying both the spatial and thematic accuracy of the OBIA output. In this paper we present an approach for delineating forest stands and a new Object Fate Analysis (OFA) matrix for accuracy assessment. A two-level object-based orthophoto analysis was first carried out to delineate stands on the Dehesa Boyal public land in central Spain (Avila Province). Two structural features were first created for use in class modelling, enabling good differentiation between stands: a relational tree cover cluster feature, and an arithmetic ratio shadow/tree feature. We then extended the OFA comparison approach with an OFA-matrix to enable concurrent validation of thematic and spatial accuracies. Its diagonal shows the proportion of spatial and thematic coincidence between a reference data and the corresponding classification. New parameters for Spatial Thematic Loyalty (STL), Spatial Thematic Loyalty Overall (STLOVERALL) and Maximal Interfering Object (MIO) are introduced to summarise the OFA-matrix accuracy assessment. A stands map generated by OBIA (classification data) was compared with a map of the same area produced from photo interpretation and field data (reference data). In our example the OFA-matrix results indicate good spatial and thematic accuracies (>65%) for all stand classes except for the shrub stands (31.8%), and a good STLOVERALL (69.8%). The OFA-matrix has therefore been shown to be a valid tool for OBIA accuracy assessment.

On Digital Simulation of Multicorrelated Random Processes and Its Applications. Ph.D. Thesis

NASA Technical Reports Server (NTRS)

Sinha, A. K.

1973-01-01

Two methods are described to simulate, on a digital computer, a set of correlated, stationary, and Gaussian time series with zero mean from the given matrix of power spectral densities and cross spectral densities. The first method is based upon trigonometric series with random amplitudes and deterministic phase angles. The random amplitudes are generated by using a standard random number generator subroutine. An example is given which corresponds to three components of wind velocities at two different spatial locations for a total of six correlated time series. In the second method, the whole process is carried out using the Fast Fourier Transform approach. This method gives more accurate results and works about twenty times faster for a set of six correlated time series.

A Chebyshev matrix method for spatial modes of the Orr-Sommerfeld equation

NASA Technical Reports Server (NTRS)

Danabasoglu, G.; Biringen, S.

1989-01-01

The Chebyshev matrix collocation method is applied to obtain the spatial modes of the Orr-Sommerfeld equation for Poiseuille flow and the Blausius boundary layer. The problem is linearized by the companion matrix technique for semi-infinite domain using a mapping transformation. The method can be easily adapted to problems with different boundary conditions requiring different transformations.

Polarization-correlation optical microscopy of anisotropic biological layers

NASA Astrophysics Data System (ADS)

Ushenko, A. G.; Dubolazov, A. V.; Ushenko, V. A.; Ushenko, Yu. A.; Sakhnovskiy, M. Y.; Balazyuk, V. N.; Khukhlina, O.; Viligorska, K.; Bykov, A.; Doronin, A.; Meglinski, I.

2016-09-01

The theoretical background of azimuthally stable method of Jones-matrix mapping of histological sections of biopsy of myocardium tissue on the basis of spatial frequency selection of the mechanisms of linear and circular birefringence is presented. The diagnostic application of a new correlation parameter - complex degree of mutual anisotropy - is analytically substantiated. The method of measuring coordinate distributions of complex degree of mutual anisotropy with further spatial filtration of their high- and low-frequency components is developed. The interconnections of such distributions with parameters of linear and circular birefringence of myocardium tissue histological sections are found. The comparative results of measuring the coordinate distributions of complex degree of mutual anisotropy formed by fibrillar networks of myosin fibrils of myocardium tissue of different necrotic states - dead due to coronary heart disease and acute coronary insufficiency are shown. The values and ranges of change of the statistical (moments of the 1st - 4th order) parameters of complex degree of mutual anisotropy coordinate distributions are studied. The objective criteria of differentiation of cause of death are determined.

Statistical analysis of latent generalized correlation matrix estimation in transelliptical distribution

PubMed Central

Han, Fang; Liu, Han

2016-01-01

Correlation matrix plays a key role in many multivariate methods (e.g., graphical model estimation and factor analysis). The current state-of-the-art in estimating large correlation matrices focuses on the use of Pearson’s sample correlation matrix. Although Pearson’s sample correlation matrix enjoys various good properties under Gaussian models, its not an effective estimator when facing heavy-tail distributions with possible outliers. As a robust alternative, Han and Liu (2013b) advocated the use of a transformed version of the Kendall’s tau sample correlation matrix in estimating high dimensional latent generalized correlation matrix under the transelliptical distribution family (or elliptical copula). The transelliptical family assumes that after unspecified marginal monotone transformations, the data follow an elliptical distribution. In this paper, we study the theoretical properties of the Kendall’s tau sample correlation matrix and its transformed version proposed in Han and Liu (2013b) for estimating the population Kendall’s tau correlation matrix and the latent Pearson’s correlation matrix under both spectral and restricted spectral norms. With regard to the spectral norm, we highlight the role of “effective rank” in quantifying the rate of convergence. With regard to the restricted spectral norm, we for the first time present a “sign subgaussian condition” which is sufficient to guarantee that the rank-based correlation matrix estimator attains the optimal rate of convergence. In both cases, we do not need any moment condition. PMID:28337068

Nonlocal polarization interferometer for entanglement detection

DOE PAGES

Williams, Brian P.; Humble, Travis S.; Grice, Warren P.

2014-10-30

We report a nonlocal interferometer capable of detecting entanglement and identifying Bell states statistically. This is possible due to the interferometer's unique correlation dependence on the antidiagonal elements of the density matrix, which have distinct bounds for separable states and unique values for the four Bell states. The interferometer consists of two spatially separated balanced Mach-Zehnder or Sagnac interferometers that share a polarization-entangled source. Correlations between these interferometers exhibit nonlocal interference, while single-photon interference is suppressed. This interferometer also allows for a unique version of the Clauser-Horne-Shimony-Holt Bell test where the local reality is the photon polarization. In conclusion, wemore » present the relevant theory and experimental results.« less

Problems with small area surveys: lensing covariance of supernova distance measurements.

PubMed

Cooray, Asantha; Huterer, Dragan; Holz, Daniel E

2006-01-20

While luminosity distances from type Ia supernovae (SNe) are a powerful probe of cosmology, the accuracy with which these distances can be measured is limited by cosmic magnification due to gravitational lensing by the intervening large-scale structure. Spatial clustering of foreground mass leads to correlated errors in SNe distances. By including the full covariance matrix of SNe, we show that future wide-field surveys will remain largely unaffected by lensing correlations. However, "pencil beam" surveys, and those with narrow (but possibly long) fields of view, can be strongly affected. For a survey with 30 arcmin mean separation between SNe, lensing covariance leads to a approximately 45% increase in the expected errors in dark energy parameters.

Identification of regional activation by factorization of high-density surface EMG signals: A comparison of Principal Component Analysis and Non-negative Matrix factorization.

PubMed

Gallina, Alessio; Garland, S Jayne; Wakeling, James M

2018-05-22

In this study, we investigated whether principal component analysis (PCA) and non-negative matrix factorization (NMF) perform similarly for the identification of regional activation within the human vastus medialis. EMG signals from 64 locations over the VM were collected from twelve participants while performing a low-force isometric knee extension. The envelope of the EMG signal of each channel was calculated by low-pass filtering (8 Hz) the monopolar EMG signal after rectification. The data matrix was factorized using PCA and NMF, and up to 5 factors were considered for each algorithm. Association between explained variance, spatial weights and temporal scores between the two algorithms were compared using Pearson correlation. For both PCA and NMF, a single factor explained approximately 70% of the variance of the signal, while two and three factors explained just over 85% or 90%. The variance explained by PCA and NMF was highly comparable (R > 0.99). Spatial weights and temporal scores extracted with non-negative reconstruction of PCA and NMF were highly associated (all p < 0.001, mean R > 0.97). Regional VM activation can be identified using high-density surface EMG and factorization algorithms. Regional activation explains up to 30% of the variance of the signal, as identified through both PCA and NMF. Copyright © 2018 Elsevier Ltd. All rights reserved.

Spatial and temporal variability of fine particle composition and source types in five cities of Connecticut and Massachusetts.

PubMed

Lee, Hyung Joo; Gent, Janneane F; Leaderer, Brian P; Koutrakis, Petros

2011-05-01

To protect public health from PM(2.5) air pollution, it is critical to identify the source types of PM(2.5) mass and chemical components associated with higher risks of adverse health outcomes. Source apportionment modeling using Positive Matrix Factorization (PMF), was used to identify PM(2.5) source types and quantify the source contributions to PM(2.5) in five cities of Connecticut and Massachusetts. Spatial and temporal variability of PM(2.5) mass, components and source contributions were investigated. PMF analysis identified five source types: regional pollution as traced by sulfur, motor vehicle, road dust, oil combustion and sea salt. The sulfur-related regional pollution and traffic source type were major contributors to PM(2.5). Due to sparse ground-level PM(2.5) monitoring sites, current epidemiological studies are susceptible to exposure measurement errors. The higher correlations in concentrations and source contributions between different locations suggest less spatial variability, resulting in less exposure measurement errors. When concentrations and/or contributions were compared to regional averages, correlations were generally higher than between-site correlations. This suggests that for assigning exposures for health effects studies, using regional average concentrations or contributions from several PM(2.5) monitors is more reliable than using data from the nearest central monitor. Copyright © 2011 Elsevier B.V. All rights reserved.

State-Space System Realization with Input- and Output-Data Correlation

NASA Technical Reports Server (NTRS)

Juang, Jer-Nan

1997-01-01

This paper introduces a general version of the information matrix consisting of the autocorrelation and cross-correlation matrices of the shifted input and output data. Based on the concept of data correlation, a new system realization algorithm is developed to create a model directly from input and output data. The algorithm starts by computing a special type of correlation matrix derived from the information matrix. The special correlation matrix provides information on the system-observability matrix and the state-vector correlation. A system model is then developed from the observability matrix in conjunction with other algebraic manipulations. This approach leads to several different algorithms for computing system matrices for use in representing the system model. The relationship of the new algorithms with other realization algorithms in the time and frequency domains is established with matrix factorization of the information matrix. Several examples are given to illustrate the validity and usefulness of these new algorithms.

Computationally Efficient 2D DOA Estimation with Uniform Rectangular Array in Low-Grazing Angle.

PubMed

Shi, Junpeng; Hu, Guoping; Zhang, Xiaofei; Sun, Fenggang; Xiao, Yu

2017-02-26

In this paper, we propose a computationally efficient spatial differencing matrix set (SDMS) method for two-dimensional direction of arrival (2D DOA) estimation with uniform rectangular arrays (URAs) in a low-grazing angle (LGA) condition. By rearranging the auto-correlation and cross-correlation matrices in turn among different subarrays, the SDMS method can estimate the two parameters independently with one-dimensional (1D) subspace-based estimation techniques, where we only perform difference for auto-correlation matrices and the cross-correlation matrices are kept completely. Then, the pair-matching of two parameters is achieved by extracting the diagonal elements of URA. Thus, the proposed method can decrease the computational complexity, suppress the effect of additive noise and also have little information loss. Simulation results show that, in LGA, compared to other methods, the proposed methods can achieve performance improvement in the white or colored noise conditions.

Computationally Efficient 2D DOA Estimation with Uniform Rectangular Array in Low-Grazing Angle

PubMed Central

Shi, Junpeng; Hu, Guoping; Zhang, Xiaofei; Sun, Fenggang; Xiao, Yu

2017-01-01

In this paper, we propose a computationally efficient spatial differencing matrix set (SDMS) method for two-dimensional direction of arrival (2D DOA) estimation with uniform rectangular arrays (URAs) in a low-grazing angle (LGA) condition. By rearranging the auto-correlation and cross-correlation matrices in turn among different subarrays, the SDMS method can estimate the two parameters independently with one-dimensional (1D) subspace-based estimation techniques, where we only perform difference for auto-correlation matrices and the cross-correlation matrices are kept completely. Then, the pair-matching of two parameters is achieved by extracting the diagonal elements of URA. Thus, the proposed method can decrease the computational complexity, suppress the effect of additive noise and also have little information loss. Simulation results show that, in LGA, compared to other methods, the proposed methods can achieve performance improvement in the white or colored noise conditions. PMID:28245634

Variance of the Quantum Dwell Time for a Nonrelativistic Particle

NASA Technical Reports Server (NTRS)

Hahne, Gerhard

2012-01-01

Munoz, Seidel, and Muga [Phys. Rev. A 79, 012108 (2009)], following an earlier proposal by Pollak and Miller [Phys. Rev. Lett. 53, 115 (1984)] in the context of a theory of a collinear chemical reaction, showed that suitable moments of a two-flux correlation function could be manipulated to yield expressions for the mean quantum dwell time and mean square quantum dwell time for a structureless particle scattering from a time-independent potential energy field between two parallel lines in a two-dimensional spacetime. The present work proposes a generalization to a charged, nonrelativistic particle scattering from a transient, spatially confined electromagnetic vector potential in four-dimensional spacetime. The geometry of the spacetime domain is that of the slab between a pair of parallel planes, in particular those defined by constant values of the third (z) spatial coordinate. The mean Nth power, N = 1, 2, 3, . . ., of the quantum dwell time in the slab is given by an expression involving an N-flux-correlation function. All these means are shown to be nonnegative. The N = 1 formula reduces to an S-matrix result published previously [G. E. Hahne, J. Phys. A 36, 7149 (2003)]; an explicit formula for N = 2, and of the variance of the dwell time in terms of the S-matrix, is worked out. A formula representing an incommensurability principle between variances of the output-minus-input flux of a pair of dynamical variables (such as the particle s time flux and others) is derived.

Flow environment and matrix structure interact to determine spatial competition in Pseudomonas aeruginosa biofilms.

PubMed

Nadell, Carey D; Ricaurte, Deirdre; Yan, Jing; Drescher, Knut; Bassler, Bonnie L

2017-01-13

Bacteria often live in biofilms, which are microbial communities surrounded by a secreted extracellular matrix. Here, we demonstrate that hydrodynamic flow and matrix organization interact to shape competitive dynamics in Pseudomonas aeruginosa biofilms. Irrespective of initial frequency, in competition with matrix mutants, wild-type cells always increase in relative abundance in planar microfluidic devices under simple flow regimes. By contrast, in microenvironments with complex, irregular flow profiles - which are common in natural environments - wild-type matrix-producing and isogenic non-producing strains can coexist. This result stems from local obstruction of flow by wild-type matrix producers, which generates regions of near-zero shear that allow matrix mutants to locally accumulate. Our findings connect the evolutionary stability of matrix production with the hydrodynamics and spatial structure of the surrounding environment, providing a potential explanation for the variation in biofilm matrix secretion observed among bacteria in natural environments.

General formalism for partial spatial coherence in reflection Mueller matrix polarimetry.

PubMed

Ossikovski, Razvigor; Hingerl, Kurt

2016-09-01

Starting from the first principles, we derive the expressions governing partially coherent Mueller matrix reflection polarimetry on spatially inhomogeneous samples. These are reported both in their general form and in the practically important specific form for two juxtaposed media.

CONSTRUCTING, PERTURBATION ANALYSIIS AND TESTING OF A MULTI-HABITAT PERIODIC MATRIX POPULATION MODEL

EPA Science Inventory

We present a matrix model that explicitly incorporates spatial habitat structure and seasonality and discuss preliminary results from a landscape level experimental test. Ecological risk to populations is often modeled without explicit treatment of spatially or temporally distri...

Spatio-temporal Reconstruction of Neural Sources Using Indirect Dominant Mode Rejection.

PubMed

Jafadideh, Alireza Talesh; Asl, Babak Mohammadzadeh

2018-04-27

Adaptive minimum variance based beamformers (MVB) have been successfully applied to magnetoencephalogram (MEG) and electroencephalogram (EEG) data to localize brain activities. However, the performance of these beamformers falls down in situations where correlated or interference sources exist. To overcome this problem, we propose indirect dominant mode rejection (iDMR) beamformer application in brain source localization. This method by modifying measurement covariance matrix makes MVB applicable in source localization in the presence of correlated and interference sources. Numerical results on both EEG and MEG data demonstrate that presented approach accurately reconstructs time courses of active sources and localizes those sources with high spatial resolution. In addition, the results of real AEF data show the good performance of iDMR in empirical situations. Hence, iDMR can be reliably used for brain source localization especially when there are correlated and interference sources.

An Efficient Local Correlation Matrix Decomposition Approach for the Localization Implementation of Ensemble-Based Assimilation Methods

NASA Astrophysics Data System (ADS)

Zhang, Hongqin; Tian, Xiangjun

2018-04-01

Ensemble-based data assimilation methods often use the so-called localization scheme to improve the representation of the ensemble background error covariance (Be). Extensive research has been undertaken to reduce the computational cost of these methods by using the localized ensemble samples to localize Be by means of a direct decomposition of the local correlation matrix C. However, the computational costs of the direct decomposition of the local correlation matrix C are still extremely high due to its high dimension. In this paper, we propose an efficient local correlation matrix decomposition approach based on the concept of alternating directions. This approach is intended to avoid direct decomposition of the correlation matrix. Instead, we first decompose the correlation matrix into 1-D correlation matrices in the three coordinate directions, then construct their empirical orthogonal function decomposition at low resolution. This procedure is followed by the 1-D spline interpolation process to transform the above decompositions to the high-resolution grid. Finally, an efficient correlation matrix decomposition is achieved by computing the very similar Kronecker product. We conducted a series of comparison experiments to illustrate the validity and accuracy of the proposed local correlation matrix decomposition approach. The effectiveness of the proposed correlation matrix decomposition approach and its efficient localization implementation of the nonlinear least-squares four-dimensional variational assimilation are further demonstrated by several groups of numerical experiments based on the Advanced Research Weather Research and Forecasting model.

Three-dimensional matrix fiber alignment modulates cell migration and MT1-MMP utility by spatially and temporally directing protrusions

NASA Astrophysics Data System (ADS)

Fraley, Stephanie I.; Wu, Pei-Hsun; He, Lijuan; Feng, Yunfeng; Krisnamurthy, Ranjini; Longmore, Gregory D.; Wirtz, Denis

2015-10-01

Multiple attributes of the three-dimensional (3D) extracellular matrix (ECM) have been independently implicated as regulators of cell motility, including pore size, crosslink density, structural organization, and stiffness. However, these parameters cannot be independently varied within a complex 3D ECM protein network. We present an integrated, quantitative study of these parameters across a broad range of complex matrix configurations using self-assembling 3D collagen and show how each parameter relates to the others and to cell motility. Increasing collagen density resulted in a decrease and then an increase in both pore size and fiber alignment, which both correlated significantly with cell motility but not bulk matrix stiffness within the range tested. However, using the crosslinking enzyme Transglutaminase II to alter microstructure independently of density revealed that motility is most significantly predicted by fiber alignment. Cellular protrusion rate, protrusion orientation, speed of migration, and invasion distance showed coupled biphasic responses to increasing collagen density not predicted by 2D models or by stiffness, but instead by fiber alignment. The requirement of matrix metalloproteinase (MMP) activity was also observed to depend on microstructure, and a threshold of MMP utility was identified. Our results suggest that fiber topography guides protrusions and thereby MMP activity and motility.

Osteopontin and the dento-osseous pathobiology of X-linked hypophosphatemia.

PubMed

Boukpessi, Tchilalo; Hoac, Betty; Coyac, Benjamin R; Leger, Thibaut; Garcia, Camille; Wicart, Philippe; Whyte, Michael P; Glorieux, Francis H; Linglart, Agnès; Chaussain, Catherine; McKee, Marc D

2017-02-01

Seven young patients with X-linked hypophosphatemia (XLH, having inactivating PHEX mutations) were discovered to accumulate osteopontin (OPN) at the sites of defective bone mineralization near osteocytes - the so-called hallmark periosteocytic (lacunar) "halos" of XLH. OPN was also localized in the pericanalicular matrix extending beyond the osteocyte lacunae, as well as in the hypomineralized matrix of tooth dentin. OPN, a potent inhibitor of mineralization normally degraded by PHEX, is a member of a family of acidic, phosphorylated, calcium-binding, extracellular matrix proteins known to regulate dental, skeletal, and pathologic mineralization. Associated with the increased amount of OPN (along with inhibitory OPN peptide fragments) in XLH bone matrix, we found an enlarged, hypomineralized, lacuno-canalicular network - a defective pattern of skeletal mineralization that decreases stiffness locally at: i) the cell-matrix interface in the pericellular environment of the mechanosensing osteocyte, and ii) the osteocyte's dendritic network of cell processes extending throughout the bone. Our findings of an excess of inhibitory OPN near osteocytes and their cell processes, and in dentin, spatially correlates with the defective mineralization observed at these sites in the skeleton and teeth of XLH patients. These changes likely contribute to the dento-osseous pathobiology of XLH, and participate in the aberrant bone adaptation and remodeling seen in XLH. Copyright © 2016 Elsevier Inc. All rights reserved.

High-resolution high-sensitivity and truly distributed optical frequency domain reflectometry for structural crack detection

NASA Astrophysics Data System (ADS)

Li, Wenhai; Bao, Xiaoyi; Chen, Liang

2014-05-01

Optical Frequency Domain Reflectometry (OFDR) with the use of polarization maintaining fiber (PMF) is capable of distinguishing strain and temperature, which is critical for successful field applications such as structural health monitoring (SHM) and smart material. Location-dependent measurement sensitivities along PMF are compensated by cross- and auto-correlations measurements of the spectra form a distributed parameter matrix. Simultaneous temperature and strain measurement accuracy of 1μstrain and 0.1°C is achieved with 2.5mm spatial resolution in over 180m range.

Sunspot Pattern Classification using PCA and Neural Networks (Poster)

NASA Technical Reports Server (NTRS)

Rajkumar, T.; Thompson, D. E.; Slater, G. L.

2005-01-01

The sunspot classification scheme presented in this paper is considered as a 2-D classification problem on archived datasets, and is not a real-time system. As a first step, it mirrors the Zuerich/McIntosh historical classification system and reproduces classification of sunspot patterns based on preprocessing and neural net training datasets. Ultimately, the project intends to move from more rudimentary schemes, to develop spatial-temporal-spectral classes derived by correlating spatial and temporal variations in various wavelengths to the brightness fluctuation spectrum of the sun in those wavelengths. Once the approach is generalized, then the focus will naturally move from a 2-D to an n-D classification, where "n" includes time and frequency. Here, the 2-D perspective refers both to the actual SOH0 Michelson Doppler Imager (MDI) images that are processed, but also refers to the fact that a 2-D matrix is created from each image during preprocessing. The 2-D matrix is the result of running Principal Component Analysis (PCA) over the selected dataset images, and the resulting matrices and their eigenvalues are the objects that are stored in a database, classified, and compared. These matrices are indexed according to the standard McIntosh classification scheme.

Physical, Spatial, and Molecular Aspects of Extracellular Matrix of In Vivo Niches and Artificial Scaffolds Relevant to Stem Cells Research

PubMed Central

Akhmanova, Maria; Osidak, Egor; Domogatsky, Sergey; Rodin, Sergey; Domogatskaya, Anna

2015-01-01

Extracellular matrix can influence stem cell choices, such as self-renewal, quiescence, migration, proliferation, phenotype maintenance, differentiation, or apoptosis. Three aspects of extracellular matrix were extensively studied during the last decade: physical properties, spatial presentation of adhesive epitopes, and molecular complexity. Over 15 different parameters have been shown to influence stem cell choices. Physical aspects include stiffness (or elasticity), viscoelasticity, pore size, porosity, amplitude and frequency of static and dynamic deformations applied to the matrix. Spatial aspects include scaffold dimensionality (2D or 3D) and thickness; cell polarity; area, shape, and microscale topography of cell adhesion surface; epitope concentration, epitope clustering characteristics (number of epitopes per cluster, spacing between epitopes within cluster, spacing between separate clusters, cluster patterns, and level of disorder in epitope arrangement), and nanotopography. Biochemical characteristics of natural extracellular matrix molecules regard diversity and structural complexity of matrix molecules, affinity and specificity of epitope interaction with cell receptors, role of non-affinity domains, complexity of supramolecular organization, and co-signaling by growth factors or matrix epitopes. Synergy between several matrix aspects enables stem cells to retain their function in vivo and may be a key to generation of long-term, robust, and effective in vitro stem cell culture systems. PMID:26351461

Dynamics of entanglement in expanding quantum fields

NASA Astrophysics Data System (ADS)

Berges, Jürgen; Floerchinger, Stefan; Venugopalan, Raju

2018-04-01

We develop a functional real-time approach to computing the entanglement between spatial regions for Gaussian states in quantum field theory. The entanglement entropy is characterized in terms of local correlation functions on space-like Cauchy hypersurfaces. The framework is applied to explore an expanding light cone geometry in the particular case of the Schwinger model for quantum electrodynamics in 1+1 space-time dimensions. We observe that the entanglement entropy becomes extensive in rapidity at early times and that the corresponding local reduced density matrix is a thermal density matrix for excitations around a coherent field with a time dependent temperature. Since the Schwinger model successfully describes many features of multiparticle production in e + e - collisions, our results provide an attractive explanation in this framework for the apparent thermal nature of multiparticle production even in the absence of significant final state scattering.

Partitioning Tungsten between Matrix Precursors and Chondrule Precursors through Relative Settling

NASA Astrophysics Data System (ADS)

Hubbard, Alexander

2016-08-01

Recent studies of chondrites have found a tungsten isotopic anomaly between chondrules and matrix. Given the refractory nature of tungsten, this implies that W was carried into the solar nebula by at least two distinct families of pre-solar grains. The observed chondrule/matrix split requires that the distinct families were kept separate during the dust coagulation process, and that the two families of grain interacted with the chondrule formation mechanism differently. We take the co-existence of different families of solids in the same general orbital region at the chondrule-precursor size as given, and explore the requirements for them to have interacted with the chondrule formation process at significantly different rates. We show that this sorting of families of solids into chondrule- and matrix-destined dust had to have been at least as powerful a sorting mechanism as the relative settling of aerodynamically distinct grains at least two scale heights above the midplane. The requirement that the chondrule formation mechanism was correlated in some fashion with a dust-grain sorting mechanism argues strongly for spatially localized chondrule formation mechanisms such as turbulent dissipation in non-thermally ionized disk surface layers, and argues against volume-filling mechanisms such as planetesimal bow shocks.

Pre-processing ambient noise cross-correlations with equalizing the covariance matrix eigenspectrum

NASA Astrophysics Data System (ADS)

Seydoux, Léonard; de Rosny, Julien; Shapiro, Nikolai M.

2017-09-01

Passive imaging techniques from ambient seismic noise requires a nearly isotropic distribution of the noise sources in order to ensure reliable traveltime measurements between seismic stations. However, real ambient seismic noise often partially fulfils this condition. It is generated in preferential areas (in deep ocean or near continental shores), and some highly coherent pulse-like signals may be present in the data such as those generated by earthquakes. Several pre-processing techniques have been developed in order to attenuate the directional and deterministic behaviour of this real ambient noise. Most of them are applied to individual seismograms before cross-correlation computation. The most widely used techniques are the spectral whitening and temporal smoothing of the individual seismic traces. We here propose an additional pre-processing to be used together with the classical ones, which is based on the spatial analysis of the seismic wavefield. We compute the cross-spectra between all available stations pairs in spectral domain, leading to the data covariance matrix. We apply a one-bit normalization to the covariance matrix eigenspectrum before extracting the cross-correlations in the time domain. The efficiency of the method is shown with several numerical tests. We apply the method to the data collected by the USArray, when the M8.8 Maule earthquake occurred on 2010 February 27. The method shows a clear improvement compared with the classical equalization to attenuate the highly energetic and coherent waves incoming from the earthquake, and allows to perform reliable traveltime measurement even in the presence of the earthquake.

Comparison of humus and till as prospecting material in areas of thick overburden and multiple ice-flow events: An example from northeastern New Brunswick

USGS Publications Warehouse

Broster, Bruce E.; Dickson, M.L.; Parkhill, M.A.

2009-01-01

Thirty-nine elements in humus and till matrix were compared at 109 sites overlying Ag-As-Cu-Mo-Pb-Zn mineralized occurrences in northeastern New Brunswick to assess humus for anomaly identification. Humus element concentrations were not consistently correlative with maximum or minimum concentrations found in the underlying till or bedrock. The humus demonstrated significantly higher mean elemental concentrations than the till for six specific elements: 9 times greater for Mn, 6 times greater for Cd, 5 times greater for Ag and Pb, 3 times greater for Hg, and double the concentration of Zn. Spatial dispersal patterns for these elements were much larger for humus content than that exhibited by the till matrix analysis, but did not delineate a point source. For elements in till, the highest concentrations were commonly found directly overlying the underlying mineralized bedrock source or within one km down-glacier of the source. The complexity of the humus geochemical patterns is attributed to the effects of post-glacial biogenic, down-slope hydrodynamic and solifluction modification of dispersed mineralization in the underlying till, and the greater capacity of humus to adsorb cations and form complexes with some elements, relative to the till matrix. Humus sampling in areas of glaciated terrain is considered to be mostly valuable for reconnaissance exploration as elements can be spatially dispersed over a much larger area than that found in the till or underlying bedrock. ?? 2009 Elsevier B.V. All rights reserved.

A New Methodology of Spatial Cross-Correlation Analysis

PubMed Central

Chen, Yanguang

2015-01-01

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

A new methodology of spatial cross-correlation analysis.

PubMed

Chen, Yanguang

2015-01-01

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

Estimation of regionalized compositions: A comparison of three methods

USGS Publications Warehouse

Pawlowsky, V.; Olea, R.A.; Davis, J.C.

1995-01-01

A regionalized composition is a random vector function whose components are positive and sum to a constant at every point of the sampling region. Consequently, the components of a regionalized composition are necessarily spatially correlated. This spatial dependence-induced by the constant sum constraint-is a spurious spatial correlation and may lead to misinterpretations of statistical analyses. Furthermore, the cross-covariance matrices of the regionalized composition are singular, as is the coefficient matrix of the cokriging system of equations. Three methods of performing estimation or prediction of a regionalized composition at unsampled points are discussed: (1) the direct approach of estimating each variable separately; (2) the basis method, which is applicable only when a random function is available that can he regarded as the size of the regionalized composition under study; (3) the logratio approach, using the additive-log-ratio transformation proposed by J. Aitchison, which allows statistical analysis of compositional data. We present a brief theoretical review of these three methods and compare them using compositional data from the Lyons West Oil Field in Kansas (USA). It is shown that, although there are no important numerical differences, the direct approach leads to invalid results, whereas the basis method and the additive-log-ratio approach are comparable. ?? 1995 International Association for Mathematical Geology.

A spatial operator algebra for manipulator modeling and control

NASA Technical Reports Server (NTRS)

Rodriguez, G.; Kreutz, K.; Milman, M.

1988-01-01

A powerful new spatial operator algebra for modeling, control, and trajectory design of manipulators is discussed along with its implementation in the Ada programming language. Applications of this algebra to robotics include an operator representation of the manipulator Jacobian matrix; the robot dynamical equations formulated in terms of the spatial algebra, showing the complete equivalence between the recursive Newton-Euler formulations to robot dynamics; the operator factorization and inversion of the manipulator mass matrix which immediately results in O(N) recursive forward dynamics algorithms; the joint accelerations of a manipulator due to a tip contact force; the recursive computation of the equivalent mass matrix as seen at the tip of a manipulator; and recursive forward dynamics of a closed chain system. Finally, additional applications and current research involving the use of the spatial operator algebra are discussed in general terms.

Age-dependence of power spectral density and fractal dimension of bone mineralized matrix in atomic force microscope topography images: potential correlates of bone tissue age and bone fragility in female femoral neck trabeculae

PubMed Central

Milovanovic, Petar; Djuric, Marija; Rakocevic, Zlatko

2012-01-01

There is an increasing interest in bone nano-structure, the ultimate goal being to reveal the basis of age-related bone fragility. In this study, power spectral density (PSD) data and fractal dimensions of the mineralized bone matrix were extracted from atomic force microscope topography images of the femoral neck trabeculae. The aim was to evaluate age-dependent differences in the mineralized matrix of human bone and to consider whether these advanced nano-descriptors might be linked to decreased bone remodeling observed by some authors and age-related decline in bone mechanical competence. The investigated bone specimens belonged to a group of young adult women (n = 5, age: 20–40 years) and a group of elderly women (n = 5, age: 70–95 years) without bone diseases. PSD graphs showed the roughness density distribution in relation to spatial frequency. In all cases, there was a fairly linear decrease in magnitude of the power spectra with increasing spatial frequencies. The PSD slope was steeper in elderly individuals (−2.374 vs. −2.066), suggesting the dominance of larger surface morphological features. Fractal dimension of the mineralized bone matrix showed a significant negative trend with advanced age, declining from 2.467 in young individuals to 2.313 in the elderly (r = 0.65, P = 0.04). Higher fractal dimension in young women reflects domination of smaller mineral grains, which is compatible with the more freshly remodeled structure. In contrast, the surface patterns in elderly individuals were indicative of older tissue age. Lower roughness and reduced structural complexity (decreased fractal dimension) of the interfibrillar bone matrix in the elderly suggest a decline in bone toughness, which explains why aged bone is more brittle and prone to fractures. PMID:22946475

Age-dependence of power spectral density and fractal dimension of bone mineralized matrix in atomic force microscope topography images: potential correlates of bone tissue age and bone fragility in female femoral neck trabeculae.

PubMed

Milovanovic, Petar; Djuric, Marija; Rakocevic, Zlatko

2012-11-01

There is an increasing interest in bone nano-structure, the ultimate goal being to reveal the basis of age-related bone fragility. In this study, power spectral density (PSD) data and fractal dimensions of the mineralized bone matrix were extracted from atomic force microscope topography images of the femoral neck trabeculae. The aim was to evaluate age-dependent differences in the mineralized matrix of human bone and to consider whether these advanced nano-descriptors might be linked to decreased bone remodeling observed by some authors and age-related decline in bone mechanical competence. The investigated bone specimens belonged to a group of young adult women (n = 5, age: 20-40 years) and a group of elderly women (n = 5, age: 70-95 years) without bone diseases. PSD graphs showed the roughness density distribution in relation to spatial frequency. In all cases, there was a fairly linear decrease in magnitude of the power spectra with increasing spatial frequencies. The PSD slope was steeper in elderly individuals (-2.374 vs. -2.066), suggesting the dominance of larger surface morphological features. Fractal dimension of the mineralized bone matrix showed a significant negative trend with advanced age, declining from 2.467 in young individuals to 2.313 in the elderly (r = 0.65, P = 0.04). Higher fractal dimension in young women reflects domination of smaller mineral grains, which is compatible with the more freshly remodeled structure. In contrast, the surface patterns in elderly individuals were indicative of older tissue age. Lower roughness and reduced structural complexity (decreased fractal dimension) of the interfibrillar bone matrix in the elderly suggest a decline in bone toughness, which explains why aged bone is more brittle and prone to fractures. © 2012 The Authors Journal of Anatomy © 2012 Anatomical Society.

Complex-valued time-series correlation increases sensitivity in FMRI analysis.

PubMed

Kociuba, Mary C; Rowe, Daniel B

2016-07-01

To develop a linear matrix representation of correlation between complex-valued (CV) time-series in the temporal Fourier frequency domain, and demonstrate its increased sensitivity over correlation between magnitude-only (MO) time-series in functional MRI (fMRI) analysis. The standard in fMRI is to discard the phase before the statistical analysis of the data, despite evidence of task related change in the phase time-series. With a real-valued isomorphism representation of Fourier reconstruction, correlation is computed in the temporal frequency domain with CV time-series data, rather than with the standard of MO data. A MATLAB simulation compares the Fisher-z transform of MO and CV correlations for varying degrees of task related magnitude and phase amplitude change in the time-series. The increased sensitivity of the complex-valued Fourier representation of correlation is also demonstrated with experimental human data. Since the correlation description in the temporal frequency domain is represented as a summation of second order temporal frequencies, the correlation is easily divided into experimentally relevant frequency bands for each voxel's temporal frequency spectrum. The MO and CV correlations for the experimental human data are analyzed for four voxels of interest (VOIs) to show the framework with high and low contrast-to-noise ratios in the motor cortex and the supplementary motor cortex. The simulation demonstrates the increased strength of CV correlations over MO correlations for low magnitude contrast-to-noise time-series. In the experimental human data, the MO correlation maps are noisier than the CV maps, and it is more difficult to distinguish the motor cortex in the MO correlation maps after spatial processing. Including both magnitude and phase in the spatial correlation computations more accurately defines the correlated left and right motor cortices. Sensitivity in correlation analysis is important to preserve the signal of interest in fMRI data sets with high noise variance, and avoid excessive processing induced correlation. Copyright © 2016 Elsevier Inc. All rights reserved.

Characteristics of global organic matrix in normal and pimpled chicken eggshells.

PubMed

Liu, Z; Song, L; Zhang, F; He, W; Linhardt, R J

2017-10-01

The organic matrix from normal and pimpled calcified chicken eggshells were dissociated into acid-insoluble, water-insoluble, and facultative-soluble (both acid- and water-soluble) components, to understand the influence of shell matrix on eggshell qualities. A linear correlation was shown among these 3 matrix components in normal eggshells but was not observed in pimpled eggshells. In pimpled eggshells, the percentage contents of all 4 groups of matrix (the total matrix, acid-insoluble matrix, water-insoluble matrix, and facultative-soluble matrix) were significantly higher than that in normal eggshells. The amounts of both total matrix and acid-insoluble matrix in individual pimpled calcified shells were high, even though their weight was much lower than a normal eggshell. In both normal and pimpled eggshells, the calcified eggshell weight and shell thickness significantly and positively correlated with the amounts of all 4 groups of matrix in an individual calcified shell. In normal eggshells, the calcified shell thickness and shell breaking strength showed no significant correlations with the percentage contents of all 4 groups of matrix. In normal eggshells, only the shell membrane weight significantly correlated with the constituent ratios of both acid-insoluble matrix and facultative-soluble matrix in the whole matrix. In pimpled eggshells, 3 variables (calcified shell weight, shell thickness, and breaking strength) were significantly correlated with the constituent proportions of both acid-insoluble matrix and facultative-matrix. This study suggests that mechanical properties of normal eggshells may not linearly depend on the organic matrix content in the calcified eggshells and that pimpled eggshells might result by the disequilibrium enrichment of some proteins with negative effects. © 2017 Poultry Science Association Inc.

A Familiar Pattern? Semantic Memory Contributes to the Enhancement of Visuo-Spatial Memories

ERIC Educational Resources Information Center

Riby, Leigh M.; Orme, Elizabeth

2013-01-01

In this study we quantify for the first time electrophysiological components associated with incorporating long-term semantic knowledge with visuo-spatial information using two variants of a traditional matrix patterns task. Results indicated that the matrix task with greater semantic content was associated with enhanced accuracy and RTs in a…

Nondestructive evaluation of a new hydrolytically degradable and photo-clickable PEG hydrogel for cartilage tissue engineering.

PubMed

Neumann, Alexander J; Quinn, Timothy; Bryant, Stephanie J

2016-07-15

Photopolymerizable and hydrolytically labile poly(ethylene glycol) (PEG) hydrogels formed from photo-clickable reactions were investigated as cell delivery platforms for cartilage tissue engineering (TE). PEG hydrogels were formed from thiol-norbornene PEG macromers whereby the crosslinks contained caprolactone segments with hydrolytically labile ester linkages. Juvenile bovine chondrocytes encapsulated in the hydrogels were cultured for up to four weeks and assessed biochemically and histologically, using standard destructive assays, and for mechanical and ultrasound properties, as nondestructive assays. Bulk degradation of acellular hydrogels was confirmed by a decrease in compressive modulus and an increase in mass swelling ratio over time. Chondrocytes deposited increasing amounts of sulfated glycosaminoglycans and collagens in the hydrogels with time. Spatially, collagen type II and aggrecan were present in the neotissue with formation of a territorial matrix beginning at day 21. Nondestructive measurements revealed an 8-fold increase in compressive modulus from days 7 to 28, which correlated with total collagen content. Ultrasound measurements revealed changes in the constructs over time, which differed from the mechanical properties, and appeared to correlate with ECM structure and organization shown by immunohistochemical analysis. Overall, non-destructive and destructive measurements show that this new hydrolytically degradable PEG hydrogel is promising for cartilage TE. Designing synthetic hydrogels whose degradation matches tissue growth is critical to maintaining mechanical integrity as the hydrogel degrades and new tissue forms, but is challenging due to the nature of the hydrogel crosslinks that inhibit diffusion of tissue matrix molecules. This study details a promising, new, photo-clickable and synthetic hydrogel whose degradation supports cartilaginous tissue matrix growth leading to the formation of a territorial matrix, concomitant with an increase in mechanical properties. Nondestructive assays based on mechanical and ultrasonic properties were also investigated using a novel instrument and found to correlate with matrix deposition and evolution. In sum, this study presents a new hydrogel platform combined with nondestructive assessments, which together have potential for in vitro cartilage tissue engineering. Copyright © 2016 Acta Materialia Inc. All rights reserved.

3D tensor-based blind multispectral image decomposition for tumor demarcation

NASA Astrophysics Data System (ADS)

Kopriva, Ivica; Peršin, Antun

2010-03-01

Blind decomposition of multi-spectral fluorescent image for tumor demarcation is formulated exploiting tensorial structure of the image. First contribution of the paper is identification of the matrix of spectral responses and 3D tensor of spatial distributions of the materials present in the image from Tucker3 or PARAFAC models of 3D image tensor. Second contribution of the paper is clustering based estimation of the number of the materials present in the image as well as matrix of their spectral profiles. 3D tensor of the spatial distributions of the materials is recovered through 3-mode multiplication of the multi-spectral image tensor and inverse of the matrix of spectral profiles. Tensor representation of the multi-spectral image preserves its local spatial structure that is lost, due to vectorization process, when matrix factorization-based decomposition methods (such as non-negative matrix factorization and independent component analysis) are used. Superior performance of the tensor-based image decomposition over matrix factorization-based decompositions is demonstrated on experimental red-green-blue (RGB) image with known ground truth as well as on RGB fluorescent images of the skin tumor (basal cell carcinoma).

Analytic tools for investigating the structure of network reliability measures with regard to observation correlations

NASA Astrophysics Data System (ADS)

Prószyński, W.; Kwaśniak, M.

2018-03-01

A global measure of observation correlations in a network is proposed, together with the auxiliary indices related to non-diagonal elements of the correlation matrix. Based on the above global measure, a specific representation of the correlation matrix is presented, being the result of rigorously proven theorem formulated within the present research. According to the theorem, each positive definite correlation matrix can be expressed by a scale factor and a so-called internal weight matrix. Such a representation made it possible to investigate the structure of the basic reliability measures with regard to observation correlations. Numerical examples carried out for two test networks illustrate the structure of those measures that proved to be dependent on global correlation index. Also, the levels of global correlation are proposed. It is shown that one can readily find an approximate value of the global correlation index, and hence the correlation level, for the expected values of auxiliary indices being the only knowledge about a correlation matrix of interest. The paper is an extended continuation of the previous study of authors that was confined to the elementary case termed uniform correlation. The extension covers arbitrary correlation matrices and a structure of correlation effect.

$n$ -Dimensional Discrete Cat Map Generation Using Laplace Expansions.

PubMed

Wu, Yue; Hua, Zhongyun; Zhou, Yicong

2016-11-01

Different from existing methods that use matrix multiplications and have high computation complexity, this paper proposes an efficient generation method of n -dimensional ( [Formula: see text]) Cat maps using Laplace expansions. New parameters are also introduced to control the spatial configurations of the [Formula: see text] Cat matrix. Thus, the proposed method provides an efficient way to mix dynamics of all dimensions at one time. To investigate its implementations and applications, we further introduce a fast implementation algorithm of the proposed method with time complexity O(n 4 ) and a pseudorandom number generator using the Cat map generated by the proposed method. The experimental results show that, compared with existing generation methods, the proposed method has a larger parameter space and simpler algorithm complexity, generates [Formula: see text] Cat matrices with a lower inner correlation, and thus yields more random and unpredictable outputs of [Formula: see text] Cat maps.

Universal sensitivity of speckle intensity correlations to wavefront change in light diffusers

PubMed Central

Kim, KyungDuk; Yu, Hyeonseung; Lee, KyeoReh; Park, YongKeun

2017-01-01

Here, we present a concept based on the realization that a complex medium can be used as a simple interferometer. Changes in the wavefront of an incident coherent beam can be retrieved by analyzing changes in speckle patterns when the beam passes through a light diffuser. We demonstrate that the spatial intensity correlations of the speckle patterns are independent of the light diffusers, and are solely determined by the phase changes of an incident beam. With numerical simulations using the random matrix theory, and an experimental pressure-driven wavefront-deforming setup using a microfluidic channel, we theoretically and experimentally confirm the universal sensitivity of speckle intensity correlations, which is attributed to the conservation of optical field correlation despite multiple light scattering. This work demonstrates that a light diffuser works as a simple interferometer, and presents opportunities to retrieve phase information of optical fields with a compact scattering layer in various applications in metrology, analytical chemistry, and biomedicine. PMID:28322268

A heteroskedastic error covariance matrix estimator using a first-order conditional autoregressive Markov simulation for deriving asympotical efficient estimates from ecological sampled Anopheles arabiensis aquatic habitat covariates

PubMed Central

Jacob, Benjamin G; Griffith, Daniel A; Muturi, Ephantus J; Caamano, Erick X; Githure, John I; Novak, Robert J

2009-01-01

Background Autoregressive regression coefficients for Anopheles arabiensis aquatic habitat models are usually assessed using global error techniques and are reported as error covariance matrices. A global statistic, however, will summarize error estimates from multiple habitat locations. This makes it difficult to identify where there are clusters of An. arabiensis aquatic habitats of acceptable prediction. It is therefore useful to conduct some form of spatial error analysis to detect clusters of An. arabiensis aquatic habitats based on uncertainty residuals from individual sampled habitats. In this research, a method of error estimation for spatial simulation models was demonstrated using autocorrelation indices and eigenfunction spatial filters to distinguish among the effects of parameter uncertainty on a stochastic simulation of ecological sampled Anopheles aquatic habitat covariates. A test for diagnostic checking error residuals in an An. arabiensis aquatic habitat model may enable intervention efforts targeting productive habitats clusters, based on larval/pupal productivity, by using the asymptotic distribution of parameter estimates from a residual autocovariance matrix. The models considered in this research extends a normal regression analysis previously considered in the literature. Methods Field and remote-sampled data were collected during July 2006 to December 2007 in Karima rice-village complex in Mwea, Kenya. SAS 9.1.4® was used to explore univariate statistics, correlations, distributions, and to generate global autocorrelation statistics from the ecological sampled datasets. A local autocorrelation index was also generated using spatial covariance parameters (i.e., Moran's Indices) in a SAS/GIS® database. The Moran's statistic was decomposed into orthogonal and uncorrelated synthetic map pattern components using a Poisson model with a gamma-distributed mean (i.e. negative binomial regression). The eigenfunction values from the spatial configuration matrices were then used to define expectations for prior distributions using a Markov chain Monte Carlo (MCMC) algorithm. A set of posterior means were defined in WinBUGS 1.4.3®. After the model had converged, samples from the conditional distributions were used to summarize the posterior distribution of the parameters. Thereafter, a spatial residual trend analyses was used to evaluate variance uncertainty propagation in the model using an autocovariance error matrix. Results By specifying coefficient estimates in a Bayesian framework, the covariate number of tillers was found to be a significant predictor, positively associated with An. arabiensis aquatic habitats. The spatial filter models accounted for approximately 19% redundant locational information in the ecological sampled An. arabiensis aquatic habitat data. In the residual error estimation model there was significant positive autocorrelation (i.e., clustering of habitats in geographic space) based on log-transformed larval/pupal data and the sampled covariate depth of habitat. Conclusion An autocorrelation error covariance matrix and a spatial filter analyses can prioritize mosquito control strategies by providing a computationally attractive and feasible description of variance uncertainty estimates for correctly identifying clusters of prolific An. arabiensis aquatic habitats based on larval/pupal productivity. PMID:19772590

Marine Stratocumulus Cloud Fields off the Coast of Southern California Observed Using LANDSAT Imagery. Part II: Textural Analysis.

NASA Astrophysics Data System (ADS)

Welch, R. M.; Sengupta, S. K.; Kuo, K. S.

1988-04-01

Statistical measures of the spatial distributions of gray levels (cloud reflectivities) are determined for LANDSAT Multispectral Scanner digital data. Textural properties for twelve stratocumulus cloud fields, seven cumulus fields, and two cirrus fields are examined using the Spatial Gray Level Co-Occurrence Matrix method. The co-occurrence statistics are computed for pixel separations ranging from 57 m to 29 km and at angles of 0°, 45°, 90° and 135°. Nine different textual measures are used to define the cloud field spatial relationships. However, the measures of contrast and correlation appear to be most useful in distinguishing cloud structure.Cloud field macrotexture describes general cloud field characteristics at distances greater than the size of typical cloud elements. It is determined from the spatial asymptotic values of the texture measures. The slope of the texture curves at small distances provides a measure of the microtexture of individual cloud cells. Cloud fields composed primarily of small cells have very steep slopes and reach their asymptotic values at short distances from the origin. As the cells composing the cloud field grow larger, the slope becomes more gradual and the asymptotic distance increases accordingly. Low asymptotic values of correlation show that stratocumulus cloud fields have no large scale organized structure.Besides the ability to distinguish cloud field structure, texture appears to be a potentially valuable tool in cloud classification. Stratocumulus clouds are characterized by low values of angular second moment and large values of entropy. Cirrus clouds appear to have extremely low values of contrast, low values of entropy, and very large values of correlation.Finally, we propose that sampled high spatial resolution satellite data be used in conjunction with coarser resolution operational satellite data to detect and identify cloud field structure and directionality and to locate regions of subresolution scale cloud contamination.

Market Correlation Structure Changes Around the Great Crash: A Random Matrix Theory Analysis of the Chinese Stock Market

NASA Astrophysics Data System (ADS)

Han, Rui-Qi; Xie, Wen-Jie; Xiong, Xiong; Zhang, Wei; Zhou, Wei-Xing

The correlation structure of a stock market contains important financial contents, which may change remarkably due to the occurrence of financial crisis. We perform a comparative analysis of the Chinese stock market around the occurrence of the 2008 crisis based on the random matrix analysis of high-frequency stock returns of 1228 Chinese stocks. Both raw correlation matrix and partial correlation matrix with respect to the market index in two time periods of one year are investigated. We find that the Chinese stocks have stronger average correlation and partial correlation in 2008 than in 2007 and the average partial correlation is significantly weaker than the average correlation in each period. Accordingly, the largest eigenvalue of the correlation matrix is remarkably greater than that of the partial correlation matrix in each period. Moreover, each largest eigenvalue and its eigenvector reflect an evident market effect, while other deviating eigenvalues do not. We find no evidence that deviating eigenvalues contain industrial sectorial information. Surprisingly, the eigenvectors of the second largest eigenvalues in 2007 and of the third largest eigenvalues in 2008 are able to distinguish the stocks from the two exchanges. We also find that the component magnitudes of the some largest eigenvectors are proportional to the stocks’ capitalizations.

Cluster structure in the correlation coefficient matrix can be characterized by abnormal eigenvalues

NASA Astrophysics Data System (ADS)

Nie, Chun-Xiao

2018-02-01

In a large number of previous studies, the researchers found that some of the eigenvalues of the financial correlation matrix were greater than the predicted values of the random matrix theory (RMT). Here, we call these eigenvalues as abnormal eigenvalues. In order to reveal the hidden meaning of these abnormal eigenvalues, we study the toy model with cluster structure and find that these eigenvalues are related to the cluster structure of the correlation coefficient matrix. In this paper, model-based experiments show that in most cases, the number of abnormal eigenvalues of the correlation matrix is equal to the number of clusters. In addition, empirical studies show that the sum of the abnormal eigenvalues is related to the clarity of the cluster structure and is negatively correlated with the correlation dimension.

Combination of synchrotron radiation-based Fourier transforms infrared microspectroscopy and confocal laser scanning microscopy to understand spatial heterogeneity in aquatic multispecies biofilms.

PubMed

Reuben, Sheela; Banas, Krzysztof; Banas, Agnieszka; Swarup, Sanjay

2014-11-01

Understanding the spatial heterogeneity within environmental biofilms can provide an insight into compartmentalization of different functions in biofilm communities. We used a non-destructive and label-free method by combining Synchrotron Radiation-based Fourier Transform Infrared Microspectroscopy (SR-FTIR) with Confocal Laser Scanning Microscopy (CLSM) to distinguish the spatial chemical changes within multispecies biofilms grown from natural storm waters in flow cells. Among the different surfaces tested for biofilm growth and optimal imaging, mylar membranes were most suited and it enabled successful spatial infrared imaging of natural biofilms for obtaining reliable and interpretable FTIR spectra. Time series analysis of biofilm growth showed that influx of water during biofilm growth, results in significant changes in biofilm formation. Early biofilms showed active nutrient acquisition and desiccation tolerance mechanisms corresponding with accumulation of secreted proteins. Statistical approach used for the evaluation of chemical spectra allowed for clustering and classification of various regions of the biofilm. Microheterogeneity was observed in the polymeric components of the biofilm matrix, including cellulose, glycocalyx and dextran-like molecules. Fructan and glycan-rich regions were distinguishable and glycocalyx was abundant in the strongly adhering peripheral regions of biofilms. Inner core showed coexistence of oxygen dimers and ferrihydrite that will likely support growth of Fe (II)-oxidising bacteria. The combined SR-FTIR microspectroscopy and CSLM approach for complex natural biofilms described here will be useful both in understanding heterogeneity of matrix components and in correlating functions of juxtaposed microbial species in complex natural biofilms with physicochemical microenvironment to which they are exposed. Copyright © 2014 Elsevier Ltd. All rights reserved.

Dynamic formation of microenvironments at the myotendinous junction correlates with muscle fiber morphogenesis in zebrafish

PubMed Central

Snow, Chelsi J.; Henry, Clarissa A.

2009-01-01

Muscle development involves the specification and morphogenesis of muscle fibers that attach to tendons. After attachment, muscles and tendons then function as an integrated unit to transduce force to the skeletal system and stabilize joints. The attachment site is the myotendinous junction, or MTJ, and is the primary site of force transmission. We find that attachment of fast-twitch myofibers to the MTJ correlates with the formation of novel microenvironments within the MTJ. The expression or activation of two proteins involved in anchoring the intracellular cytoskeleton to the extracellular matrix, Focal adhesion kinase (Fak) and β-dystroglycan is up-regulated. Conversely, the extracellular matrix protein Fibronectin (Fn) is down-regulated. This degradation of Fn as fast-twitch fibers attach to the MTJ results in Fn protein defining a novel microenvironment within the MTJ adjacent to slow-twitch, but not fast-twitch, muscle. Interestingly, however, Fak, laminin, Fn and β-dystroglycan concentrate at the MTJ in mutants that do not have slow-twitch fibers. Taken together, these data elucidate novel and dynamic microenvironments within the MTJ and indicate that MTJ morphogenesis is spatially and temporally complex. PMID:18783736

Interpretation of the Precision Matrix and Its Application in Estimating Sparse Brain Connectivity during Sleep Spindles from Human Electrocorticography Recordings

PubMed Central

Das, Anup; Sampson, Aaron L.; Lainscsek, Claudia; Muller, Lyle; Lin, Wutu; Doyle, John C.; Cash, Sydney S.; Halgren, Eric; Sejnowski, Terrence J.

2017-01-01

The correlation method from brain imaging has been used to estimate functional connectivity in the human brain. However, brain regions might show very high correlation even when the two regions are not directly connected due to the strong interaction of the two regions with common input from a third region. One previously proposed solution to this problem is to use a sparse regularized inverse covariance matrix or precision matrix (SRPM) assuming that the connectivity structure is sparse. This method yields partial correlations to measure strong direct interactions between pairs of regions while simultaneously removing the influence of the rest of the regions, thus identifying regions that are conditionally independent. To test our methods, we first demonstrated conditions under which the SRPM method could indeed find the true physical connection between a pair of nodes for a spring-mass example and an RC circuit example. The recovery of the connectivity structure using the SRPM method can be explained by energy models using the Boltzmann distribution. We then demonstrated the application of the SRPM method for estimating brain connectivity during stage 2 sleep spindles from human electrocorticography (ECoG) recordings using an 8 × 8 electrode array. The ECoG recordings that we analyzed were from a 32-year-old male patient with long-standing pharmaco-resistant left temporal lobe complex partial epilepsy. Sleep spindles were automatically detected using delay differential analysis and then analyzed with SRPM and the Louvain method for community detection. We found spatially localized brain networks within and between neighboring cortical areas during spindles, in contrast to the case when sleep spindles were not present. PMID:28095202

A method to detect layover and shadow based on distributed spaceborne single-baseline InSAR

NASA Astrophysics Data System (ADS)

Yun, Ren; Huanxin, Zou; Shilin, Zhou; Hao, Sun; Kefeng, Ji

2014-03-01

Layover and Shadow are inevitable phenomenena in InSAR, which seriously destroy the continuity of interferometric phase images and present difficulties in the follow-up phase unwrapping. Thus, it's significant to detect layover and shadow. This paper presents an approach to detect layover and shadow using the auto-correlation matrix and amplitude of the two images. The method can make full use of the spatial information of neighboring pixels and effectively detect layover and shadow regions in the case of low registration accuracy. Experiment result on the simulated data verifies effectiveness of the algorithm.

Continuous Sub-daily Rainfall Simulation for Regional Flood Risk Assessment - Modelling of Spatio-temporal Correlation Structure of Extreme Precipitation in the Austrian Alps

NASA Astrophysics Data System (ADS)

Salinas, J. L.; Nester, T.; Komma, J.; Bloeschl, G.

2017-12-01

Generation of realistic synthetic spatial rainfall is of pivotal importance for assessing regional hydroclimatic hazard as the input for long term rainfall-runoff simulations. The correct reproduction of observed rainfall characteristics, such as regional intensity-duration-frequency curves, and spatial and temporal correlations is necessary to adequately model the magnitude and frequency of the flood peaks, by reproducing antecedent soil moisture conditions before extreme rainfall events, and joint probability of flood waves at confluences. In this work, a modification of the model presented by Bardossy and Platte (1992), where precipitation is first modeled on a station basis as a multivariate autoregressive model (mAr) in a Normal space. The spatial and temporal correlation structures are imposed in the Normal space, allowing for a different temporal autocorrelation parameter for each station, and simultaneously ensuring the positive-definiteness of the correlation matrix of the mAr errors. The Normal rainfall is then transformed to a Gamma-distributed space, with parameters varying monthly according to a sinusoidal function, in order to adapt to the observed rainfall seasonality. One of the main differences with the original model is the simulation time-step, reduced from 24h to 6h. Due to a larger availability of daily rainfall data, as opposite to sub-daily (e.g. hourly), the parameters of the Gamma distributions are calibrated to reproduce simultaneously a series of daily rainfall characteristics (mean daily rainfall, standard deviations of daily rainfall, and 24h intensity-duration-frequency [IDF] curves), as well as other aggregated rainfall measures (mean annual rainfall, and monthly rainfall). The calibration of the spatial and temporal correlation parameters is performed in a way that the catchment-averaged IDF curves aggregated at different temporal scales fit the measured ones. The rainfall model is used to generate 10.000 years of synthetic precipitation, fed into a rainfall-runoff model to derive the flood frequency in the Tirolean Alps in Austria. Given the number of generated events, the simulation framework is able to generate a large variety of rainfall patterns, as well as reproduce the variograms of relevant extreme rainfall events in the region of interest.

Tumor image signatures and habitats: a processing pipeline of multimodality metabolic and physiological images.

PubMed

You, Daekeun; Kim, Michelle M; Aryal, Madhava P; Parmar, Hemant; Piert, Morand; Lawrence, Theodore S; Cao, Yue

2018-01-01

To create tumor "habitats" from the "signatures" discovered from multimodality metabolic and physiological images, we developed a framework of a processing pipeline. The processing pipeline consists of six major steps: (1) creating superpixels as a spatial unit in a tumor volume; (2) forming a data matrix [Formula: see text] containing all multimodality image parameters at superpixels; (3) forming and clustering a covariance or correlation matrix [Formula: see text] of the image parameters to discover major image "signatures;" (4) clustering the superpixels and organizing the parameter order of the [Formula: see text] matrix according to the one found in step 3; (5) creating "habitats" in the image space from the superpixels associated with the "signatures;" and (6) pooling and clustering a matrix consisting of correlation coefficients of each pair of image parameters from all patients to discover subgroup patterns of the tumors. The pipeline was applied to a dataset of multimodality images in glioblastoma (GBM) first, which consisted of 10 image parameters. Three major image "signatures" were identified. The three major "habitats" plus their overlaps were created. To test generalizability of the processing pipeline, a second image dataset from GBM, acquired on the scanners different from the first one, was processed. Also, to demonstrate the clinical association of image-defined "signatures" and "habitats," the patterns of recurrence of the patients were analyzed together with image parameters acquired prechemoradiation therapy. An association of the recurrence patterns with image-defined "signatures" and "habitats" was revealed. These image-defined "signatures" and "habitats" can be used to guide stereotactic tissue biopsy for genetic and mutation status analysis and to analyze for prediction of treatment outcomes, e.g., patterns of failure.

PARTITIONING TUNGSTEN BETWEEN MATRIX PRECURSORS AND CHONDRULE PRECURSORS THROUGH RELATIVE SETTLING

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

Hubbard, Alexander, E-mail: ahubbard@amnh.org

2016-08-01

Recent studies of chondrites have found a tungsten isotopic anomaly between chondrules and matrix. Given the refractory nature of tungsten, this implies that W was carried into the solar nebula by at least two distinct families of pre-solar grains. The observed chondrule/matrix split requires that the distinct families were kept separate during the dust coagulation process, and that the two families of grain interacted with the chondrule formation mechanism differently. We take the co-existence of different families of solids in the same general orbital region at the chondrule-precursor size as given, and explore the requirements for them to have interactedmore » with the chondrule formation process at significantly different rates. We show that this sorting of families of solids into chondrule- and matrix-destined dust had to have been at least as powerful a sorting mechanism as the relative settling of aerodynamically distinct grains at least two scale heights above the midplane. The requirement that the chondrule formation mechanism was correlated in some fashion with a dust-grain sorting mechanism argues strongly for spatially localized chondrule formation mechanisms such as turbulent dissipation in non-thermally ionized disk surface layers, and argues against volume-filling mechanisms such as planetesimal bow shocks.« less

Modeling and possible implementation of self-learning equivalence-convolutional neural structures for auto-encoding-decoding and clusterization of images

NASA Astrophysics Data System (ADS)

Krasilenko, Vladimir G.; Lazarev, Alexander A.; Nikitovich, Diana V.

2017-08-01

Self-learning equivalent-convolutional neural structures (SLECNS) for auto-coding-decoding and image clustering are discussed. The SLECNS architectures and their spatially invariant equivalent models (SI EMs) using the corresponding matrix-matrix procedures with basic operations of continuous logic and non-linear processing are proposed. These SI EMs have several advantages, such as the ability to recognize image fragments with better efficiency and strong cross correlation. The proposed clustering method of fragments with regard to their structural features is suitable not only for binary, but also color images and combines self-learning and the formation of weight clustered matrix-patterns. Its model is constructed and designed on the basis of recursively processing algorithms and to k-average method. The experimental results confirmed that larger images and 2D binary fragments with a large numbers of elements may be clustered. For the first time the possibility of generalization of these models for space invariant case is shown. The experiment for an image with dimension of 256x256 (a reference array) and fragments with dimensions of 7x7 and 21x21 for clustering is carried out. The experiments, using the software environment Mathcad, showed that the proposed method is universal, has a significant convergence, the small number of iterations is easily, displayed on the matrix structure, and confirmed its prospects. Thus, to understand the mechanisms of self-learning equivalence-convolutional clustering, accompanying her to the competitive processes in neurons, and the neural auto-encoding-decoding and recognition principles with the use of self-learning cluster patterns is very important which used the algorithm and the principles of non-linear processing of two-dimensional spatial functions of images comparison. These SIEMs can simply describe the signals processing during the all training and recognition stages and they are suitable for unipolar-coding multilevel signals. We show that the implementation of SLECNS based on known equivalentors or traditional correlators is possible if they are based on proposed equivalental two-dimensional functions of image similarity. The clustering efficiency in such models and their implementation depends on the discriminant properties of neural elements of hidden layers. Therefore, the main models and architecture parameters and characteristics depends on the applied types of non-linear processing and function used for image comparison or for adaptive-equivalental weighing of input patterns. Real model experiments in Mathcad are demonstrated, which confirm that non-linear processing on equivalent functions allows you to determine the neuron winners and adjust the weight matrix. Experimental results have shown that such models can be successfully used for auto- and hetero-associative recognition. They can also be used to explain some mechanisms known as "focus" and "competing gain-inhibition concept". The SLECNS architecture and hardware implementations of its basic nodes based on multi-channel convolvers and correlators with time integration are proposed. The parameters and performance of such architectures are estimated.

A generalization of random matrix theory and its application to statistical physics.

PubMed

Wang, Duan; Zhang, Xin; Horvatic, Davor; Podobnik, Boris; Eugene Stanley, H

2017-02-01

To study the statistical structure of crosscorrelations in empirical data, we generalize random matrix theory and propose a new method of cross-correlation analysis, known as autoregressive random matrix theory (ARRMT). ARRMT takes into account the influence of auto-correlations in the study of cross-correlations in multiple time series. We first analytically and numerically determine how auto-correlations affect the eigenvalue distribution of the correlation matrix. Then we introduce ARRMT with a detailed procedure of how to implement the method. Finally, we illustrate the method using two examples taken from inflation rates for air pressure data for 95 US cities.

Trypsin and MALDI matrix pre-coated targets simplify sample preparation for mapping proteomic distributions within biological tissues by imaging mass spectrometry

PubMed Central

Zubair, Faizan; Laibinis, Paul E.; Swisher, William G.; Yang, Junhai; Spraggins, Jeffrey M.; Norris, Jeremy L.; Caprioli, Richard M.

2017-01-01

Prefabricated surfaces containing α-cyano-4-hydroxycinnamic acid and trypsin have been developed to facilitate enzymatic digestion of endogenous tissue proteins prior to matrix-assisted laser desorption/ionization (MALDI) imaging mass spectrometry (IMS). Tissue sections are placed onto slides that were previously coated with α-cyano-4-hydroxycinnamic acid and trypsin. After incubation to promote enzymatic digestion, the tissue is analyzed by MALDI IMS to determine the spatial distribution of the tryptic fragments. The peptides detected in the MALDI IMS dataset were identified by Liquid chromatography-tandem mass spectrometry/mass spectrometry. Protein identification was further confirmed by correlating the localization of unique tryptic fragments originating from common parent proteins. Using this procedure, proteins with molecular weights as large as 300 kDa were identified and their distributions were imaged in sections of rat brain. In particular, large proteins such as myristoylated alanine-rich C-kinase substrate (29.8 kDa) and spectrin alpha chain, non-erythrocytic 1 (284 kDa) were detected that are not observed without trypsin. The pre-coated targets simplify workflow and increase sample throughput by decreasing the sample preparation time. Further, the approach allows imaging at higher spatial resolution compared with robotic spotters that apply one drop at a time. PMID:27676701

Remote sensing using MIMO systems

DOEpatents

Bikhazi, Nicolas; Young, William F; Nguyen, Hung D

2015-04-28

A technique for sensing a moving object within a physical environment using a MIMO communication link includes generating a channel matrix based upon channel state information of the MIMO communication link. The physical environment operates as a communication medium through which communication signals of the MIMO communication link propagate between a transmitter and a receiver. A spatial information variable is generated for the MIMO communication link based on the channel matrix. The spatial information variable includes spatial information about the moving object within the physical environment. A signature for the moving object is generated based on values of the spatial information variable accumulated over time. The moving object is identified based upon the signature.

Description and spatial inference of soil drainage using matrix soil colours in the Lower Hunter Valley, New South Wales, Australia

PubMed Central

McBratney, Alex B.; Minasny, Budiman

2018-01-01

Soil colour is often used as a general purpose indicator of internal soil drainage. In this study we developed a necessarily simple model of soil drainage which combines the tacit knowledge of the soil surveyor with observed matrix soil colour descriptions. From built up knowledge of the soils in our Lower Hunter Valley, New South Wales study area, the sequence of well-draining → imperfectly draining → poorly draining soils generally follows the colour sequence of red → brown → yellow → grey → black soil matrix colours. For each soil profile, soil drainage is estimated somewhere on a continuous index of between 5 (very well drained) and 1 (very poorly drained) based on the proximity or similarity to reference soil colours of the soil drainage colour sequence. The estimation of drainage index at each profile incorporates the whole-profile descriptions of soil colour where necessary, and is weighted such that observation of soil colour at depth and/or dominantly observed horizons are given more preference than observations near the soil surface. The soil drainage index, by definition disregards surficial soil horizons and consolidated and semi-consolidated parent materials. With the view to understanding the spatial distribution of soil drainage we digitally mapped the index across our study area. Spatial inference of the drainage index was made using Cubist regression tree model combined with residual kriging. Environmental covariates for deterministic inference were principally terrain variables derived from a digital elevation model. Pearson’s correlation coefficients indicated the variables most strongly correlated with soil drainage were topographic wetness index (−0.34), mid-slope position (−0.29), multi-resolution valley bottom flatness index (−0.29) and vertical distance to channel network (VDCN) (0.26). From the regression tree modelling, two linear models of soil drainage were derived. The partitioning of models was based upon threshold criteria of VDCN. Validation of the regression kriging model using a withheld dataset resulted in a root mean square error of 0.90 soil drainage index units. Concordance between observations and predictions was 0.49. Given the scale of mapping, and inherent subjectivity of soil colour description, these results are acceptable. Furthermore, the spatial distribution of soil drainage predicted in our study area is attuned with our mental model developed over successive field surveys. Our approach, while exclusively calibrated for the conditions observed in our study area, can be generalised once the unique soil colour and soil drainage relationship is expertly defined for an area or region in question. With such rules established, the quantitative components of the method would remain unchanged. PMID:29682425

Description and spatial inference of soil drainage using matrix soil colours in the Lower Hunter Valley, New South Wales, Australia.

PubMed

Malone, Brendan P; McBratney, Alex B; Minasny, Budiman

2018-01-01

Soil colour is often used as a general purpose indicator of internal soil drainage. In this study we developed a necessarily simple model of soil drainage which combines the tacit knowledge of the soil surveyor with observed matrix soil colour descriptions. From built up knowledge of the soils in our Lower Hunter Valley, New South Wales study area, the sequence of well-draining → imperfectly draining → poorly draining soils generally follows the colour sequence of red → brown → yellow → grey → black soil matrix colours. For each soil profile, soil drainage is estimated somewhere on a continuous index of between 5 (very well drained) and 1 (very poorly drained) based on the proximity or similarity to reference soil colours of the soil drainage colour sequence. The estimation of drainage index at each profile incorporates the whole-profile descriptions of soil colour where necessary, and is weighted such that observation of soil colour at depth and/or dominantly observed horizons are given more preference than observations near the soil surface. The soil drainage index, by definition disregards surficial soil horizons and consolidated and semi-consolidated parent materials. With the view to understanding the spatial distribution of soil drainage we digitally mapped the index across our study area. Spatial inference of the drainage index was made using Cubist regression tree model combined with residual kriging. Environmental covariates for deterministic inference were principally terrain variables derived from a digital elevation model. Pearson's correlation coefficients indicated the variables most strongly correlated with soil drainage were topographic wetness index (-0.34), mid-slope position (-0.29), multi-resolution valley bottom flatness index (-0.29) and vertical distance to channel network (VDCN) (0.26). From the regression tree modelling, two linear models of soil drainage were derived. The partitioning of models was based upon threshold criteria of VDCN. Validation of the regression kriging model using a withheld dataset resulted in a root mean square error of 0.90 soil drainage index units. Concordance between observations and predictions was 0.49. Given the scale of mapping, and inherent subjectivity of soil colour description, these results are acceptable. Furthermore, the spatial distribution of soil drainage predicted in our study area is attuned with our mental model developed over successive field surveys. Our approach, while exclusively calibrated for the conditions observed in our study area, can be generalised once the unique soil colour and soil drainage relationship is expertly defined for an area or region in question. With such rules established, the quantitative components of the method would remain unchanged.

Spatially resolved chemical analysis of cicada wings using laser-ablation electrospray ionization (LAESI) imaging mass spectrometry (IMS).

PubMed

Román, Jessica K; Walsh, Callee M; Oh, Junho; Dana, Catherine E; Hong, Sungmin; Jo, Kyoo D; Alleyne, Marianne; Miljkovic, Nenad; Cropek, Donald M

2018-03-01

Laser-ablation electrospray ionization (LAESI) imaging mass spectrometry (IMS) is an emerging bioanalytical tool for direct imaging and analysis of biological tissues. Performing ionization in an ambient environment, this technique requires little sample preparation and no additional matrix, and can be performed on natural, uneven surfaces. When combined with optical microscopy, the investigation of biological samples by LAESI allows for spatially resolved compositional analysis. We demonstrate here the applicability of LAESI-IMS for the chemical analysis of thin, desiccated biological samples, specifically Neotibicen pruinosus cicada wings. Positive-ion LAESI-IMS accurate ion-map data was acquired from several wing cells and superimposed onto optical images allowing for compositional comparisons across areas of the wing. Various putative chemical identifications were made indicating the presence of hydrocarbons, lipids/esters, amines/amides, and sulfonated/phosphorylated compounds. With the spatial resolution capability, surprising chemical distribution patterns were observed across the cicada wing, which may assist in correlating trends in surface properties with chemical distribution. Observed ions were either (1) equally dispersed across the wing, (2) more concentrated closer to the body of the insect (proximal end), or (3) more concentrated toward the tip of the wing (distal end). These findings demonstrate LAESI-IMS as a tool for the acquisition of spatially resolved chemical information from fragile, dried insect wings. This LAESI-IMS technique has important implications for the study of functional biomaterials, where understanding the correlation between chemical composition, physical structure, and biological function is critical. Graphical abstract Positive-ion laser-ablation electrospray ionization mass spectrometry coupled with optical imaging provides a powerful tool for the spatially resolved chemical analysis of cicada wings.

Spatial characterization of dissolved trace elements and heavy metals in the upper Han River (China) using multivariate statistical techniques.

PubMed

Li, Siyue; Zhang, Quanfa

2010-04-15

A data matrix (4032 observations), obtained during a 2-year monitoring period (2005-2006) from 42 sites in the upper Han River is subjected to various multivariate statistical techniques including cluster analysis, principal component analysis (PCA), factor analysis (FA), correlation analysis and analysis of variance to determine the spatial characterization of dissolved trace elements and heavy metals. Our results indicate that waters in the upper Han River are primarily polluted by Al, As, Cd, Pb, Sb and Se, and the potential pollutants include Ba, Cr, Hg, Mn and Ni. Spatial distribution of trace metals indicates the polluted sections mainly concentrate in the Danjiang, Danjiangkou Reservoir catchment and Hanzhong Plain, and the most contaminated river is in the Hanzhong Plain. Q-model clustering depends on geographical location of sampling sites and groups the 42 sampling sites into four clusters, i.e., Danjiang, Danjiangkou Reservoir region (lower catchment), upper catchment and one river in headwaters pertaining to water quality. The headwaters, Danjiang and lower catchment, and upper catchment correspond to very high polluted, moderate polluted and relatively low polluted regions, respectively. Additionally, PCA/FA and correlation analysis demonstrates that Al, Cd, Mn, Ni, Fe, Si and Sr are controlled by natural sources, whereas the other metals appear to be primarily controlled by anthropogenic origins though geogenic source contributing to them. 2009 Elsevier B.V. All rights reserved.

The spatial organisation of joint surface chondrocytes: review of its potential roles in tissue functioning, disease and early, preclinical diagnosis of osteoarthritis.

PubMed

Aicher, Wilhelm K; Rolauffs, Bernd

2014-04-01

Chondrocytes display within the articular cartilage depth-dependent variations of their many properties that are comparable to the depth-dependent changes of the properties of the surrounding extracellular matrix. However, not much is known about the spatial organisation of the chondrocytes throughout the tissue. Recent studies revealed that human chondrocytes display distinct spatial patterns of organisation within the articular surface, and each joint surface is dominated in a typical way by one of four basic spatial patterns. The resulting complex spatial organisations correlate with the specific diarthrodial joint type, suggesting an association of the chondrocyte organisation within the joint surface with the occurring biomechanical forces. In response to focal osteoarthritis (OA), the superficial chondrocytes experience a destruction of their spatial organisation within the OA lesion, but they also undergo a defined remodelling process distant from the OA lesion in the remaining, intact cartilage surface. One of the biological insights that can be derived from this spatial remodelling process is that the chondrocytes are able to respond in a generalised and coordinated fashion to distant focal OA. The spatial characteristics of this process are tremendously different from the cellular aggregations typical for OA lesions, suggesting differences in the underlying mechanisms. Here we summarise the available information on the spatial organisation of chondrocytes and its potential roles in cartilage functioning. The spatial organisation could be used to diagnose early OA onset before manifest OA results in tissue destruction and clinical symptoms. With further development, this concept may become clinically suitable for the diagnosis of preclinical OA.

Asymmetric correlation matrices: an analysis of financial data

NASA Astrophysics Data System (ADS)

Livan, G.; Rebecchi, L.

2012-06-01

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

3D Weight Matrices in Modeling Real Estate Prices

NASA Astrophysics Data System (ADS)

Mimis, A.

2016-10-01

Central role in spatial econometric models of real estate data has the definition of the weight matrix by which we capture the spatial dependence between the observations. The weight matrices presented in literature so far, treats space in a two dimensional manner leaving out the effect of the third dimension or in our case the difference in height where the property resides. To overcome this, we propose a new definition of the weight matrix including the third dimensional effect by using the Hadamard product. The results illustrated that the level effect can be absorbed into the new weight matrix.

The spatial QRS-T angle in the Frank vectorcardiogram: accuracy of estimates derived from the 12-lead electrocardiogram.

PubMed

Schreurs, Charlotte A; Algra, Annemijn M; Man, Sum-Che; Cannegieter, Suzanne C; van der Wall, Ernst E; Schalij, Martin J; Kors, Jan A; Swenne, Cees A

2010-01-01

The spatial QRS-T angle (SA), a predictor of sudden cardiac death, is a vectorcardiographic variable. Gold standard vertorcardiograms (VCGs) are recorded by using the Frank electrode positions. However, with the commonly available 12-lead ECG, VCGs must be synthesized by matrix multiplication (inverse Dower matrix/Kors matrix). Alternatively, Rautaharju proposed a method to calculate SA directly from the 12-lead ECG. Neither spatial angles computed by using the inverse Dower matrix (SA-D) nor by using the Kors matrix (SA-K) or by using Rautaharju's method (SA-R) have been validated with regard to the spatial angles as directly measured in the Frank VCG (SA-F). Our present study aimed to perform this essential validation. We analyzed SAs in 1220 simultaneously recorded 12-lead ECGs and VCGs, in all data, in SA-F-based tertiles, and after stratification according to pathology or sex. Linear regression of SA-K, SA-D, and SA-R on SA-F yielded offsets of 0.01 degree, 20.3 degrees, and 28.3 degrees and slopes of 0.96, 0.86, and 0.79, respectively. The bias of SA-K with respect to SA-F (mean +/- SD, -3.2 degrees +/- 13.9 degrees) was significantly (P < .001) smaller than the bias of both SA-D and SA-R with respect to SA-F (8.0 degrees +/- 18.6 degrees and 9.8 degrees +/- 24.6 degrees, respectively); tertile analysis showed a much more homogeneous behavior of the bias in SA-K than of both the bias in SA-D and in SA-R. In pathologic ECGs, there was no significant bias in SA-K; bias in men and women did not differ. SA-K resembled SA-F best. In general, when there is no specific reason either to synthesize VCGs with the inverse Dower matrix or to calculate the spatial QRS-T angle with Rautaharju's method, it seems prudent to use the Kors matrix. Copyright 2010 Elsevier Inc. All rights reserved.

Receptive-field subfields of V2 neurons in macaque monkeys are adult-like near birth.

PubMed

Zhang, Bin; Tao, Xiaofeng; Shen, Guofu; Smith, Earl L; Ohzawa, Izumi; Chino, Yuzo M

2013-02-06

Infant primates can discriminate texture-defined form despite their relatively low visual acuity. The neuronal mechanisms underlying this remarkable visual capacity of infants have not been studied in nonhuman primates. Since many V2 neurons in adult monkeys can extract the local features in complex stimuli that are required for form vision, we used two-dimensional dynamic noise stimuli and local spectral reverse correlation to measure whether the spatial map of receptive-field subfields in individual V2 neurons is sufficiently mature near birth to capture local features. As in adults, most V2 neurons in 4-week-old monkeys showed a relatively high degree of homogeneity in the spatial matrix of facilitatory subfields. However, ∼25% of V2 neurons had the subfield map where the neighboring facilitatory subfields substantially differed in their preferred orientations and spatial frequencies. Over 80% of V2 neurons in both infants and adults had "tuned" suppressive profiles in their subfield maps that could alter the tuning properties of facilitatory profiles. The differences in the preferred orientations between facilitatory and suppressive profiles were relatively large but extended over a broad range. Response immaturities in infants were mild; the overall strength of facilitatory subfield responses was lower than that in adults, and the optimal correlation delay ("latency") was longer in 4-week-old infants. These results suggest that as early as 4 weeks of age, the spatial receptive-field structure of V2 neurons is as complex as in adults and the ability of V2 neurons to compare local features of neighboring stimulus elements is nearly adult like.

Spatially resolved elemental distributions in articular cartilage

NASA Astrophysics Data System (ADS)

Reinert, T.; Reibetanz, U.; Vogt, J.; Butz, T.; Werner, A.; Gründer, W.

2001-07-01

In this study, the nuclear microprobe technique is employed to analyse the chemistry of joint cartilage in order to correlate internal structures of the collagen network with the elemental distribution. The samples were taken from pig's knee joint. 30 μm thick coronar cross-sections were prepared by means of cryosectioning and freeze-drying. We performed simultaneously particle induced X-ray emission (PIXE), Rutherford backscattering spectrometry (RBS) and elastic recoil detection analysis (ERDA). Thus we obtained spatially resolved distributions of the elements H, C, N, O, P, S, Cl, K and Ca. The main components of the organic matrix are H, C, N and O. It was shown that their relations vary with the cartilage structures. It could be shown that zones with aligned collagen fibrils contain less sulphur and potassium but more chlorine. The higher chlorine concentration is remarkable because newest biochemical studies found that hypochloric acid is involved in cartilage degradation. Furthermore, the calcium distribution is still of great interest. Its correlation to structural changes inside the cartilage is still being discussed. It could be disproved that zones of higher calcium concentration are related to the aligned structures of the collagen network.

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

PubMed

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

2010-07-01

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

Ultrasound Technologies for the Spatial Patterning of Cells and Extracellular Matrix Proteins and the Vascularization of Engineered Tissue

NASA Astrophysics Data System (ADS)

Garvin, Kelley A.

Technological advancements in the field of tissue engineering could save the lives of thousands of organ transplant patients who die each year while waiting for donor organs. Currently, two of the primary challenges preventing tissue engineers from developing functional replacement tissues and organs are the need to recreate complex cell and extracellular microenvironments and to vascularize the tissue to maintain cell viability and function. Ultrasound is a form of mechanical energy that can noninvasively and nondestructively interact with tissues at the cell and protein level. In this thesis, novel ultrasound-based technologies were developed for the spatial patterning of cells and extracellular matrix proteins and the vascularization of three-dimensional engineered tissue constructs. Acoustic radiation forces associated with ultrasound standing wave fields were utilized to noninvasively control the spatial organization of cells and cell-bound extracellular matrix proteins within collagen-based engineered tissue. Additionally, ultrasound induced thermal mechanisms were exploited to site-specifically pattern various extracellular matrix collagen microstructures within a single engineered tissue construct. Finally, ultrasound standing wave field technology was used to promote the rapid and extensive vascularization of three-dimensional tissue constructs. As such, the ultrasound technologies developed in these studies have the potential to provide the field of tissue engineering with novel strategies to spatially pattern cells and extracellular matrix components and to vascularize engineered tissue, and thus, could advance the fabrication of functional replacement tissues and organs in the field of tissue engineering.

Comparing Multipollutant Emissions-Based Mobile Source Indicators to Other Single Pollutant and Multipollutant Indicators in Different Urban Areas

PubMed Central

Oakes, Michelle M.; Baxter, Lisa K.; Duvall, Rachelle M.; Madden, Meagan; Xie, Mingjie; Hannigan, Michael P.; Peel, Jennifer L.; Pachon, Jorge E.; Balachandran, Siv; Russell, Armistead; Long, Thomas C.

2014-01-01

A variety of single pollutant and multipollutant metrics can be used to represent exposure to traffic pollutant mixtures and evaluate their health effects. Integrated mobile source indicators (IMSIs) that combine air quality concentration and emissions data have recently been developed and evaluated using data from Atlanta, Georgia. IMSIs were found to track trends in traffic-related pollutants and have similar or stronger associations with health outcomes. In the current work, we apply IMSIs for gasoline, diesel and total (gasoline + diesel) vehicles to two other cities (Denver, Colorado and Houston, Texas) with different emissions profiles as well as to a different dataset from Atlanta. We compare spatial and temporal variability of IMSIs to single-pollutant indicators (carbon monoxide (CO), nitrogen oxides (NOx) and elemental carbon (EC)) and multipollutant source apportionment factors produced by Positive Matrix Factorization (PMF). Across cities, PMF-derived and IMSI gasoline metrics were most strongly correlated with CO (r = 0.31–0.98), while multipollutant diesel metrics were most strongly correlated with EC (r = 0.80–0.98). NOx correlations with PMF factors varied across cities (r = 0.29–0.67), while correlations with IMSIs were relatively consistent (r = 0.61–0.94). In general, single-pollutant metrics were more correlated with IMSIs (r = 0.58–0.98) than with PMF-derived factors (r = 0.07–0.99). A spatial analysis indicated that IMSIs were more strongly correlated (r > 0.7) between two sites in each city than single pollutant and PMF factors. These findings provide confidence that IMSIs provide a transferable, simple approach to estimate mobile source air pollution in cities with differing topography and source profiles using readily available data. PMID:25405595

Quantification and micron-scale imaging of spatial distribution of trace beryllium in shrapnel fragments and metallurgic samples with correlative fluorescence detection method and secondary ion mass spectrometry (SIMS)

PubMed Central

Abraham, Jerrold L.; Chandra, Subhash; Agrawal, Anoop

2014-01-01

Recently, a report raised the possibility of shrapnel-induced chronic beryllium disease (CBD) from long-term exposure to the surface of retained aluminum shrapnel fragments in the body. Since the shrapnel fragments contained trace beryllium, methodological developments were needed for beryllium quantification and to study its spatial distribution in relation to other matrix elements, such as aluminum and iron, in metallurgic samples. In this work, we developed methodology for quantification of trace beryllium in samples of shrapnel fragments and other metallurgic sample-types with main matrix of aluminum (aluminum cans from soda, beer, carbonated water, and aluminum foil). Sample preparation procedures were developed for dissolving beryllium for its quantification with the fluorescence detection method for homogenized measurements. The spatial distribution of trace beryllium on the sample surface and in 3D was imaged with a dynamic secondary ion mass spectrometry (SIMS) instrument, CAMECA IMS 3f SIMS ion microscope. The beryllium content of shrapnel (~100 ppb) was the same as the trace quantities of beryllium found in aluminum cans. The beryllium content of aluminum foil (~25 ppb) was significantly lower than cans. SIMS imaging analysis revealed beryllium to be distributed in the form of low micron-sized particles and clusters distributed randomly in X-Y-and Z dimensions, and often in association with iron, in the main aluminum matrix of cans. These observations indicate a plausible formation of Be-Fe or Al-Be alloy in the matrix of cans. Further observations were made on fluids (carbonated water) for understanding if trace beryllium in cans leached out and contaminated the food product. A direct comparison of carbonated water in aluminum cans and plastic bottles revealed that beryllium was below the detection limits of the fluorescence detection method (~0.01 ppb). These observations indicate that beryllium present in aluminum matrix was either present in an immobile form or its mobilization into the food product was prevented by a polymer coating on the inside of cans, a practice used in food industry to prevent contamination of food products. The lack of such coating in retained shrapnel fragments renders their surface a possible source of contamination for long-term exposure of tissues and fluids and induction of disease, as characterized in a recent study. Methodological developments reported here can be extended to studies of beryllium in electronics devices and components. PMID:25146877

Quantification and micron-scale imaging of spatial distribution of trace beryllium in shrapnel fragments and metallurgic samples with correlative fluorescence detection method and secondary ion mass spectrometry (SIMS).

PubMed

Abraham, J L; Chandra, S; Agrawal, A

2014-11-01

Recently, a report raised the possibility of shrapnel-induced chronic beryllium disease from long-term exposure to the surface of retained aluminum shrapnel fragments in the body. Since the shrapnel fragments contained trace beryllium, methodological developments were needed for beryllium quantification and to study its spatial distribution in relation to other matrix elements, such as aluminum and iron, in metallurgic samples. In this work, we developed methodology for quantification of trace beryllium in samples of shrapnel fragments and other metallurgic sample-types with main matrix of aluminum (aluminum cans from soda, beer, carbonated water and aluminum foil). Sample preparation procedures were developed for dissolving beryllium for its quantification with the fluorescence detection method for homogenized measurements. The spatial distribution of trace beryllium on the sample surface and in 3D was imaged with a dynamic secondary ion mass spectrometry instrument, CAMECA IMS 3f secondary ion mass spectrometry ion microscope. The beryllium content of shrapnel (∼100 ppb) was the same as the trace quantities of beryllium found in aluminum cans. The beryllium content of aluminum foil (∼25 ppb) was significantly lower than cans. SIMS imaging analysis revealed beryllium to be distributed in the form of low micron-sized particles and clusters distributed randomly in X-Y- and Z dimensions, and often in association with iron, in the main aluminum matrix of cans. These observations indicate a plausible formation of Be-Fe or Al-Be alloy in the matrix of cans. Further observations were made on fluids (carbonated water) for understanding if trace beryllium in cans leached out and contaminated the food product. A direct comparison of carbonated water in aluminum cans and plastic bottles revealed that beryllium was below the detection limits of the fluorescence detection method (∼0.01 ppb). These observations indicate that beryllium present in aluminum matrix was either present in an immobile form or its mobilization into the food product was prevented by a polymer coating on the inside of cans, a practice used in food industry to prevent contamination of food products. The lack of such coating in retained shrapnel fragments renders their surface a possible source of contamination for long-term exposure of tissues and fluids and induction of disease, as characterized in a recent study. Methodological developments reported here can be extended to studies of beryllium in electronics devices and components. © 2014 The Authors Journal of Microscopy © 2014 Royal Microscopical Society.

Direct Measurement of the Density Matrix of a Quantum System

NASA Astrophysics Data System (ADS)

Thekkadath, G. S.; Giner, L.; Chalich, Y.; Horton, M. J.; Banker, J.; Lundeen, J. S.

2016-09-01

One drawback of conventional quantum state tomography is that it does not readily provide access to single density matrix elements since it requires a global reconstruction. Here, we experimentally demonstrate a scheme that can be used to directly measure individual density matrix elements of general quantum states. The scheme relies on measuring a sequence of three observables, each complementary to the last. The first two measurements are made weak to minimize the disturbance they cause to the state, while the final measurement is strong. We perform this joint measurement on polarized photons in pure and mixed states to directly measure their density matrix. The weak measurements are achieved using two walk-off crystals, each inducing a polarization-dependent spatial shift that couples the spatial and polarization degrees of freedom of the photons. This direct measurement method provides an operational meaning to the density matrix and promises to be especially useful for large dimensional states.

Direct Measurement of the Density Matrix of a Quantum System.

PubMed

Thekkadath, G S; Giner, L; Chalich, Y; Horton, M J; Banker, J; Lundeen, J S

2016-09-16

One drawback of conventional quantum state tomography is that it does not readily provide access to single density matrix elements since it requires a global reconstruction. Here, we experimentally demonstrate a scheme that can be used to directly measure individual density matrix elements of general quantum states. The scheme relies on measuring a sequence of three observables, each complementary to the last. The first two measurements are made weak to minimize the disturbance they cause to the state, while the final measurement is strong. We perform this joint measurement on polarized photons in pure and mixed states to directly measure their density matrix. The weak measurements are achieved using two walk-off crystals, each inducing a polarization-dependent spatial shift that couples the spatial and polarization degrees of freedom of the photons. This direct measurement method provides an operational meaning to the density matrix and promises to be especially useful for large dimensional states.

Methods and means of Fourier-Stokes polarimetry and the spatial frequency filtering of phase anisotropy manifestations

NASA Astrophysics Data System (ADS)

Novakovskaya, O. Yu.; Ushenko, A. G.; Dubolazov, A. V.; Ushenko, V. A.; Ushenko, Yu. A.; Sakhnovskiy, M. Yu.; Soltys, I. V.; Zhytaryuk, V. H.; Olar, O. V.; Sidor, M.; Gorsky, M. P.

2016-12-01

The theoretical background of azimuthally stable method of Jones-matrix mapping of histological sections of biopsy of myocardium tissue on the basis of spatial frequency selection of the mechanisms of linear and circular birefringence is presented. The diagnostic application of a new correlation parameter - complex degree of mutual anisotropy - is analytically substantiated. The method of measuring coordinate distributions of complex degree of mutual anisotropy with further spatial filtration of their high- and low-frequency components is developed. The interconnections of such distributions with parameters of linear and circular birefringence of myocardium tissue histological sections are found. The comparative results of measuring the coordinate distributions of complex degree of mutual anisotropy formed by fibrillar networks of myosin fibrils of myocardium tissue of different necrotic states - dead due to coronary heart disease and acute coronary insufficiency are shown. The values and ranges of change of the statistical (moments of the 1st - 4th order) parameters of complex degree of mutual anisotropy coordinate distributions are studied. The objective criteria of differentiation of cause of death are determined.

Multiple-Parameter Estimation Method Based on Spatio-Temporal 2-D Processing for Bistatic MIMO Radar

PubMed Central

Yang, Shouguo; Li, Yong; Zhang, Kunhui; Tang, Weiping

2015-01-01

A novel spatio-temporal 2-dimensional (2-D) processing method that can jointly estimate the transmitting-receiving azimuth and Doppler frequency for bistatic multiple-input multiple-output (MIMO) radar in the presence of spatial colored noise and an unknown number of targets is proposed. In the temporal domain, the cross-correlation of the matched filters’ outputs for different time-delay sampling is used to eliminate the spatial colored noise. In the spatial domain, the proposed method uses a diagonal loading method and subspace theory to estimate the direction of departure (DOD) and direction of arrival (DOA), and the Doppler frequency can then be accurately estimated through the estimation of the DOD and DOA. By skipping target number estimation and the eigenvalue decomposition (EVD) of the data covariance matrix estimation and only requiring a one-dimensional search, the proposed method achieves low computational complexity. Furthermore, the proposed method is suitable for bistatic MIMO radar with an arbitrary transmitted and received geometrical configuration. The correction and efficiency of the proposed method are verified by computer simulation results. PMID:26694385

Multiple-Parameter Estimation Method Based on Spatio-Temporal 2-D Processing for Bistatic MIMO Radar.

PubMed

Yang, Shouguo; Li, Yong; Zhang, Kunhui; Tang, Weiping

2015-12-14

A novel spatio-temporal 2-dimensional (2-D) processing method that can jointly estimate the transmitting-receiving azimuth and Doppler frequency for bistatic multiple-input multiple-output (MIMO) radar in the presence of spatial colored noise and an unknown number of targets is proposed. In the temporal domain, the cross-correlation of the matched filters' outputs for different time-delay sampling is used to eliminate the spatial colored noise. In the spatial domain, the proposed method uses a diagonal loading method and subspace theory to estimate the direction of departure (DOD) and direction of arrival (DOA), and the Doppler frequency can then be accurately estimated through the estimation of the DOD and DOA. By skipping target number estimation and the eigenvalue decomposition (EVD) of the data covariance matrix estimation and only requiring a one-dimensional search, the proposed method achieves low computational complexity. Furthermore, the proposed method is suitable for bistatic MIMO radar with an arbitrary transmitted and received geometrical configuration. The correction and efficiency of the proposed method are verified by computer simulation results.

Bias and uncertainty in regression-calibrated models of groundwater flow in heterogeneous media

USGS Publications Warehouse

Cooley, R.L.; Christensen, S.

2006-01-01

Groundwater models need to account for detailed but generally unknown spatial variability (heterogeneity) of the hydrogeologic model inputs. To address this problem we replace the large, m-dimensional stochastic vector ?? that reflects both small and large scales of heterogeneity in the inputs by a lumped or smoothed m-dimensional approximation ????*, where ?? is an interpolation matrix and ??* is a stochastic vector of parameters. Vector ??* has small enough dimension to allow its estimation with the available data. The consequence of the replacement is that model function f(????*) written in terms of the approximate inputs is in error with respect to the same model function written in terms of ??, ??,f(??), which is assumed to be nearly exact. The difference f(??) - f(????*), termed model error, is spatially correlated, generates prediction biases, and causes standard confidence and prediction intervals to be too small. Model error is accounted for in the weighted nonlinear regression methodology developed to estimate ??* and assess model uncertainties by incorporating the second-moment matrix of the model errors into the weight matrix. Techniques developed by statisticians to analyze classical nonlinear regression methods are extended to analyze the revised method. The analysis develops analytical expressions for bias terms reflecting the interaction of model nonlinearity and model error, for correction factors needed to adjust the sizes of confidence and prediction intervals for this interaction, and for correction factors needed to adjust the sizes of confidence and prediction intervals for possible use of a diagonal weight matrix in place of the correct one. If terms expressing the degree of intrinsic nonlinearity for f(??) and f(????*) are small, then most of the biases are small and the correction factors are reduced in magnitude. Biases, correction factors, and confidence and prediction intervals were obtained for a test problem for which model error is large to test robustness of the methodology. Numerical results conform with the theoretical analysis. ?? 2005 Elsevier Ltd. All rights reserved.

What affects the predictability of evolutionary constraints using a G-matrix? The relative effects of modular pleiotropy and mutational correlation.

PubMed

Chebib, Jobran; Guillaume, Frédéric

2017-10-01

Phenotypic traits do not always respond to selection independently from each other and often show correlated responses to selection. The structure of a genotype-phenotype map (GP map) determines trait covariation, which involves variation in the degree and strength of the pleiotropic effects of the underlying genes. It is still unclear, and debated, how much of that structure can be deduced from variational properties of quantitative traits that are inferred from their genetic (co) variance matrix (G-matrix). Here we aim to clarify how the extent of pleiotropy and the correlation among the pleiotropic effects of mutations differentially affect the structure of a G-matrix and our ability to detect genetic constraints from its eigen decomposition. We show that the eigenvectors of a G-matrix can be predictive of evolutionary constraints when they map to underlying pleiotropic modules with correlated mutational effects. Without mutational correlation, evolutionary constraints caused by the fitness costs associated with increased pleiotropy are harder to infer from evolutionary metrics based on a G-matrix's geometric properties because uncorrelated pleiotropic effects do not affect traits' genetic correlations. Correlational selection induces much weaker modular partitioning of traits' genetic correlations in absence then in presence of underlying modular pleiotropy. © 2017 The Author(s). Evolution © 2017 The Society for the Study of Evolution.

Substrate Screening Effects in ab initio Many-body Green's Function Calculations of Doped Graphene on SiC

NASA Astrophysics Data System (ADS)

Vigil-Fowler, Derek; Lischner, Johannes; Louie, Steven

2013-03-01

Understanding many-electron interaction effects and the influence of the substrate in graphene-on-substrate systems is of great theoretical and practical interest. Thus far, both model Hamiltonian and ab initio GW calculations for the quasiparticle properties of such systems have employed crude models for the effect of the substrate, often approximating the complicated substrate dielectric matrix by a single constant. We develop a method in which the spatially-dependent dielectric matrix of the substrate (e.g., SiC) is incorporated into that of doped graphene to obtain an accurate total dielectric matrix. We present ab initio GW + cumulant expansion calculations, showing that both the cumulant expansion (to include higher-order electron correlations) and a proper account of the substrate screening are needed to achieve agreement with features seen in ARPES. We discuss how this methodology could be used in other systems. This work was supported by NSF Grant No. DMR10-1006184 and U.S. DOE Contract No. DE-AC02-05CH11231. Computational resources have been provided by the NERSC and NICS. D.V-F. acknowledges funding from the DOD's NDSEG fellowship.

A computational model of in vitro angiogenesis based on extracellular matrix fibre orientation.

PubMed

Edgar, Lowell T; Sibole, Scott C; Underwood, Clayton J; Guilkey, James E; Weiss, Jeffrey A

2013-01-01

Recent interest in the process of vascularisation within the biomedical community has motivated numerous new research efforts focusing on the process of angiogenesis. Although the role of chemical factors during angiogenesis has been well documented, the role of mechanical factors, such as the interaction between angiogenic vessels and the extracellular matrix, remains poorly understood. In vitro methods for studying angiogenesis exist; however, measurements available using such techniques often suffer from limited spatial and temporal resolutions. For this reason, computational models have been extensively employed to investigate various aspects of angiogenesis. This paper outlines the formulation and validation of a simple and robust computational model developed to accurately simulate angiogenesis based on length, branching and orientation morphometrics collected from vascularised tissue constructs. Microvessels were represented as a series of connected line segments. The morphology of the vessels was determined by a linear combination of the collagen fibre orientation, the vessel density gradient and a random walk component. Excellent agreement was observed between computational and experimental morphometric data over time. Computational predictions of microvessel orientation within an anisotropic matrix correlated well with experimental data. The accuracy of this modelling approach makes it a valuable platform for investigating the role of mechanical interactions during angiogenesis.

Development of a scanning time of flight microscope and its application to the study of charge transport in phase separated structured organic semiconductors

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

Paul, Sanjoy; Ellman, Brett, E-mail: bellman@kent.edu; Singh, Gautam

We describe a tool for studying the two-dimensional spatial variation in electronic properties of organic semiconductors: the scanning time-of-flight microscope (STOFm). The STOFm simultaneously measures the transmittance of polarized light and time-of-flight current transients with a pixel size <30 μm, making it especially valuable for studies of the correlations of structure with charge generation and transport in liquid crystalline organic semiconductors (LC OSCs). Adapting a previously developed photopolymerization technique, we characterize the instrument using patterned samples of a LC OSC bounded by a non-semiconducting polymer matrix.

THE MEASUREMENT OF BONE QUALITY USING GRAY LEVEL CO-OCCURRENCE MATRIX TEXTURAL FEATURES.

PubMed

Shirvaikar, Mukul; Huang, Ning; Dong, Xuanliang Neil

2016-10-01

In this paper, statistical methods for the estimation of bone quality to predict the risk of fracture are reported. Bone mineral density and bone architecture properties are the main contributors of bone quality. Dual-energy X-ray Absorptiometry (DXA) is the traditional clinical measurement technique for bone mineral density, but does not include architectural information to enhance the prediction of bone fragility. Other modalities are not practical due to cost and access considerations. This study investigates statistical parameters based on the Gray Level Co-occurrence Matrix (GLCM) extracted from two-dimensional projection images and explores links with architectural properties and bone mechanics. Data analysis was conducted on Micro-CT images of 13 trabecular bones (with an in-plane spatial resolution of about 50μm). Ground truth data for bone volume fraction (BV/TV), bone strength and modulus were available based on complex 3D analysis and mechanical tests. Correlation between the statistical parameters and biomechanical test results was studied using regression analysis. The results showed Cluster-Shade was strongly correlated with the microarchitecture of the trabecular bone and related to mechanical properties. Once the principle thesis of utilizing second-order statistics is established, it can be extended to other modalities, providing cost and convenience advantages for patients and doctors.

THE MEASUREMENT OF BONE QUALITY USING GRAY LEVEL CO-OCCURRENCE MATRIX TEXTURAL FEATURES

PubMed Central

Shirvaikar, Mukul; Huang, Ning; Dong, Xuanliang Neil

2016-01-01

In this paper, statistical methods for the estimation of bone quality to predict the risk of fracture are reported. Bone mineral density and bone architecture properties are the main contributors of bone quality. Dual-energy X-ray Absorptiometry (DXA) is the traditional clinical measurement technique for bone mineral density, but does not include architectural information to enhance the prediction of bone fragility. Other modalities are not practical due to cost and access considerations. This study investigates statistical parameters based on the Gray Level Co-occurrence Matrix (GLCM) extracted from two-dimensional projection images and explores links with architectural properties and bone mechanics. Data analysis was conducted on Micro-CT images of 13 trabecular bones (with an in-plane spatial resolution of about 50μm). Ground truth data for bone volume fraction (BV/TV), bone strength and modulus were available based on complex 3D analysis and mechanical tests. Correlation between the statistical parameters and biomechanical test results was studied using regression analysis. The results showed Cluster-Shade was strongly correlated with the microarchitecture of the trabecular bone and related to mechanical properties. Once the principle thesis of utilizing second-order statistics is established, it can be extended to other modalities, providing cost and convenience advantages for patients and doctors. PMID:28042512

Predicting protein contact map using evolutionary and physical constraints by integer programming.

PubMed

Wang, Zhiyong; Xu, Jinbo

2013-07-01

Protein contact map describes the pairwise spatial and functional relationship of residues in a protein and contains key information for protein 3D structure prediction. Although studied extensively, it remains challenging to predict contact map using only sequence information. Most existing methods predict the contact map matrix element-by-element, ignoring correlation among contacts and physical feasibility of the whole-contact map. A couple of recent methods predict contact map by using mutual information, taking into consideration contact correlation and enforcing a sparsity restraint, but these methods demand for a very large number of sequence homologs for the protein under consideration and the resultant contact map may be still physically infeasible. This article presents a novel method PhyCMAP for contact map prediction, integrating both evolutionary and physical restraints by machine learning and integer linear programming. The evolutionary restraints are much more informative than mutual information, and the physical restraints specify more concrete relationship among contacts than the sparsity restraint. As such, our method greatly reduces the solution space of the contact map matrix and, thus, significantly improves prediction accuracy. Experimental results confirm that PhyCMAP outperforms currently popular methods no matter how many sequence homologs are available for the protein under consideration. http://raptorx.uchicago.edu.

Effect of Matrix Size on the Image Quality of Ultra-high-resolution CT of the Lung: Comparison of 512 × 512, 1024 × 1024, and 2048 × 2048.

PubMed

Hata, Akinori; Yanagawa, Masahiro; Honda, Osamu; Kikuchi, Noriko; Miyata, Tomo; Tsukagoshi, Shinsuke; Uranishi, Ayumi; Tomiyama, Noriyuki

2018-01-16

This study aimed to assess the effect of matrix size on the spatial resolution and image quality of ultra-high-resolution computed tomography (U-HRCT). Slit phantoms and 11 cadaveric lungs were scanned on U-HRCT. Slit phantom scans were reconstructed using a 20-mm field of view (FOV) with 1024 matrix size and a 320-mm FOV with 512, 1024, and 2048 matrix sizes. Cadaveric lung scans were reconstructed using 512, 1024, and 2048 matrix sizes. Three observers subjectively scored the images on a three-point scale (1 = worst, 3 = best), in terms of overall image quality, noise, streak artifact, vessel, bronchi, and image findings. The median score of the three observers was evaluated by Wilcoxon signed-rank test with Bonferroni correction. Noise was measured quantitatively and evaluated with the Tukey test. A P value of <.05 was considered significant. The maximum spatial resolution was 0.14 mm; among the 320-mm FOV images, the 2048 matrix had the highest resolution and was significantly better than the 1024 matrix in terms of overall quality, solid nodule, ground-glass opacity, emphysema, intralobular reticulation, honeycombing, and clarity of vessels (P < .05). Both the 2048 and 1024 matrices performed significantly better than the 512 matrix (P < .001), except for noise and streak artifact. The visual and quantitative noise decreased significantly in the order of 512, 1024, and 2048 (P < .001). In U-HRCT scans, a large matrix size maintained the spatial resolution and improved the image quality and assessment of lung diseases, despite an increase in image noise, when compared to a 512 matrix size. Copyright © 2018 The Association of University Radiologists. Published by Elsevier Inc. All rights reserved.

Simultaneous Denoising, Deconvolution, and Demixing of Calcium Imaging Data

PubMed Central

Pnevmatikakis, Eftychios A.; Soudry, Daniel; Gao, Yuanjun; Machado, Timothy A.; Merel, Josh; Pfau, David; Reardon, Thomas; Mu, Yu; Lacefield, Clay; Yang, Weijian; Ahrens, Misha; Bruno, Randy; Jessell, Thomas M.; Peterka, Darcy S.; Yuste, Rafael; Paninski, Liam

2016-01-01

SUMMARY We present a modular approach for analyzing calcium imaging recordings of large neuronal ensembles. Our goal is to simultaneously identify the locations of the neurons, demix spatially overlapping components, and denoise and deconvolve the spiking activity from the slow dynamics of the calcium indicator. Our approach relies on a constrained nonnegative matrix factorization that expresses the spatiotemporal fluorescence activity as the product of a spatial matrix that encodes the spatial footprint of each neuron in the optical field and a temporal matrix that characterizes the calcium concentration of each neuron over time. This framework is combined with a novel constrained deconvolution approach that extracts estimates of neural activity from fluorescence traces, to create a spatiotemporal processing algorithm that requires minimal parameter tuning. We demonstrate the general applicability of our method by applying it to in vitro and in vivo multineuronal imaging data, whole-brain light-sheet imaging data, and dendritic imaging data. PMID:26774160

Experimental investigation of the ordering pathway in a Ni-33 at.%Cr alloy

DOE PAGES

Gwalani, B.; Alam, T.; Miller, C.; ...

2016-06-17

The present study involves a detailed experimental investigation of the concurrent compositional clustering and long-range ordering tendencies in a Ni-33 at.%Cr alloy, carried out by coupling synchrotron-based X-ray diffraction (XRD), transmission electron microscopy (TEM), and atom probe tomography (APT). Synchrotron-based XRD results clearly exhibited progressively increasing lattice contraction in the matrix with increasing isothermal aging time, at 475 degrees C, eventually leading to the development of long-range ordering (LRO) of the Pt2Mo-type. Detailed TEM and APT investigations revealed that this LRO in the matrix is manifested in the form of nanometer-scale ordered domains, and the spatial distribution, size, morphology andmore » compositional evolution of these domains have been carefully investigated. Here, the APT results also revealed the early stages of compositional clustering prior to the onset of long-range ordering in this alloy and such compositional clustering can potentially be correlated to the lattice contraction and previously proposed short-range ordering tendencies.« less

Synchronization and desynchronization in a network of locally coupled Wilson-Cowan oscillators.

PubMed

Campbell, S; Wang, D

1996-01-01

A network of Wilson-Cowan (WC) oscillators is constructed, and its emergent properties of synchronization and desynchronization are investigated by both computer simulation and formal analysis. The network is a 2D matrix, where each oscillator is coupled only to its neighbors. We show analytically that a chain of locally coupled oscillators (the piecewise linear approximation to the WC oscillator) synchronizes, and we present a technique to rapidly entrain finite numbers of oscillators. The coupling strengths change on a fast time scale based on a Hebbian rule. A global separator is introduced which receives input from and sends feedback to each oscillator in the matrix. The global separator is used to desynchronize different oscillator groups. Unlike many other models, the properties of this network emerge from local connections that preserve spatial relationships among components and are critical for encoding Gestalt principles of feature grouping. The ability to synchronize and desynchronize oscillator groups within this network offers a promising approach for pattern segmentation and figure/ground segregation based on oscillatory correlation.

Stress distribution retrieval in granular materials: A multi-scale model and digital image correlation measurements

NASA Astrophysics Data System (ADS)

Bruno, Luigi; Decuzzi, Paolo; Gentile, Francesco

2016-01-01

The promise of nanotechnology lies in the possibility of engineering matter on the nanoscale and creating technological interfaces that, because of their small scales, may directly interact with biological objects, creating new strategies for the treatment of pathologies that are otherwise beyond the reach of conventional medicine. Nanotechnology is inherently a multiscale, multiphenomena challenge. Fundamental understanding and highly accurate predictive methods are critical to successful manufacturing of nanostructured materials, bio/mechanical devices and systems. In biomedical engineering, and in the mechanical analysis of biological tissues, classical continuum approaches are routinely utilized, even if these disregard the discrete nature of tissues, that are an interpenetrating network of a matrix (the extra cellular matrix, ECM) and a generally large but finite number of cells with a size falling in the micrometer range. Here, we introduce a nano-mechanical theory that accounts for the-non continuum nature of bio systems and other discrete systems. This discrete field theory, doublet mechanics (DM), is a technique to model the mechanical behavior of materials over multiple scales, ranging from some millimeters down to few nanometers. In the paper, we use this theory to predict the response of a granular material to an external applied load. Such a representation is extremely attractive in modeling biological tissues which may be considered as a spatial set of a large number of particulate (cells) dispersed in an extracellular matrix. Possibly more important of this, using digital image correlation (DIC) optical methods, we provide an experimental verification of the model.

ppcor: An R Package for a Fast Calculation to Semi-partial Correlation Coefficients.

PubMed

Kim, Seongho

2015-11-01

Lack of a general matrix formula hampers implementation of the semi-partial correlation, also known as part correlation, to the higher-order coefficient. This is because the higher-order semi-partial correlation calculation using a recursive formula requires an enormous number of recursive calculations to obtain the correlation coefficients. To resolve this difficulty, we derive a general matrix formula of the semi-partial correlation for fast computation. The semi-partial correlations are then implemented on an R package ppcor along with the partial correlation. Owing to the general matrix formulas, users can readily calculate the coefficients of both partial and semi-partial correlations without computational burden. The package ppcor further provides users with the level of the statistical significance with its test statistic.

Least-Squares Approximation of an Improper by a Proper Correlation Matrix Using a Semi-Infinite Convex Program. Research Report 87-7.

ERIC Educational Resources Information Center

Knol, Dirk L.; ten Berge, Jos M. F.

An algorithm is presented for the best least-squares fitting correlation matrix approximating a given missing value or improper correlation matrix. The proposed algorithm is based on a solution for C. I. Mosier's oblique Procrustes rotation problem offered by J. M. F. ten Berge and K. Nevels (1977). It is shown that the minimization problem…

Gaussian covariance graph models accounting for correlated marker effects in genome-wide prediction.

PubMed

Martínez, C A; Khare, K; Rahman, S; Elzo, M A

2017-10-01

Several statistical models used in genome-wide prediction assume uncorrelated marker allele substitution effects, but it is known that these effects may be correlated. In statistics, graphical models have been identified as a useful tool for covariance estimation in high-dimensional problems and it is an area that has recently experienced a great expansion. In Gaussian covariance graph models (GCovGM), the joint distribution of a set of random variables is assumed to be Gaussian and the pattern of zeros of the covariance matrix is encoded in terms of an undirected graph G. In this study, methods adapting the theory of GCovGM to genome-wide prediction were developed (Bayes GCov, Bayes GCov-KR and Bayes GCov-H). In simulated data sets, improvements in correlation between phenotypes and predicted breeding values and accuracies of predicted breeding values were found. Our models account for correlation of marker effects and permit to accommodate general structures as opposed to models proposed in previous studies, which consider spatial correlation only. In addition, they allow incorporation of biological information in the prediction process through its use when constructing graph G, and their extension to the multi-allelic loci case is straightforward. © 2017 Blackwell Verlag GmbH.

From Spatial Intelligence to Spatial Competences: The Results of Applied Geo-Research in Italian Schools

ERIC Educational Resources Information Center

Sarno, Emilia

2012-01-01

This contribution explains the connection between spatial intelligence and spatial competences and by indicating how the first is the cognitive matrix of abilities necessary to move in space as well as to represent it. Indeed, two are principal factors involved in the spatial intelligence: orientation and representation. Both are based on a close…

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

PubMed

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

2014-01-01

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

Characteristic Analysis on UAV-MIMO Channel Based on Normalized Correlation Matrix

PubMed Central

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

2014-01-01

Based on the three-dimensional GBSBCM (geometrically based double bounce cylinder model) channel model of MIMO for unmanned aerial vehicle (UAV), the simple form of UAV space-time-frequency channel correlation function which includes the LOS, SPE, and DIF components is presented. By the methods of channel matrix decomposition and coefficient normalization, the analytic formula of UAV-MIMO normalized correlation matrix is deduced. This formula can be used directly to analyze the condition number of UAV-MIMO channel matrix, the channel capacity, and other characteristic parameters. The simulation results show that this channel correlation matrix can be applied to describe the changes of UAV-MIMO channel characteristics under different parameter settings comprehensively. This analysis method provides a theoretical basis for improving the transmission performance of UAV-MIMO channel. The development of MIMO technology shows practical application value in the field of UAV communication. PMID:24977185

Modeling of non-uniform spatial arrangement of fibers in a ceramic matrix composite

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

Yang, S.; Tewari, A.; Gokhale, A.M.

In the unidirectional fiber reinforced composites, the spatial agreement of fibers is often non-uniform. These non-uniformities are linked to the processing conditions, and they affect the properties of the composite. In this contribution, a recently developed digital image analysis technique is used to quantify the non-uniform spatial arrangement of Nicalon fibers in a ceramic matrix composite (CMC). These quantitative data are utilized to develop a six parameter computer simulated microstructure model that is statistically equivalent to the non-uniform microstructure of the CMC. The simulated microstructure can be utilized as a RVE for the micro-mechanical modeling studies.

An efficient method for computation of the manipulator inertia matrix

NASA Technical Reports Server (NTRS)

Fijany, Amir; Bejczy, Antal K.

1989-01-01

An efficient method of computation of the manipulator inertia matrix is presented. Using spatial notations, the method leads to the definition of the composite rigid-body spatial inertia, which is a spatial representation of the notion of augmented body. The previously proposed methods, the physical interpretations leading to their derivation, and their redundancies are analyzed. The proposed method achieves a greater efficiency by eliminating the redundancy in the intrinsic equations as well as by a better choice of coordinate frame for their projection. In this case, removing the redundancy leads to greater efficiency of the computation in both serial and parallel senses.

Matrix-assisted laser-desorption/ionization mass spectrometric imaging of olanzapine in a single hair using esculetin as a matrix.

PubMed

Wang, Hang; Wang, Ying; Wang, Ge; Hong, Lizhi

2017-07-15

Matrix-assisted laser desorption/ionization-mass spectrometric imaging (MALDI-MSI) for the analysis of intact hair is a powerful tool for monitoring changes in drug consumption. The embedding of a low drug concentration in the hydrophobic hair matrix makes it difficult to extract and detect, and requires an improved method to increase detection sensitivity. In this study, an MSI method using MALDI-Fourier transform ion cyclotron resonance was developed for direct identification and imaging of olanzapine in hair samples using the positive ion mode. Following decontamination, scalp hair samples from an olanzapine user were scraped from the proximal to the distal end three times, and 5mm hair sections were fixed onto an Indium-Tin-Oxide (ITO)-coated microscopic glass slide. Esculetin (6,7-dihydroxy-2H-chromen-2-one) was used as a new hydrophobic matrix to increase the affinity, extraction and ionization efficiency of olanzapine in the hair samples. The spatial distribution of olanzapine was observed using five single hairs from the same drug user. This matrix improves the affinity of olanzapine in hair for molecular imaging with mass spectrometry. This method may provide a detection power for olanzapine to the nanogram level per 5mm hair. Time course changes in the MSI results were also compared with quantitative HPLC-MS/MS for each 5mm segment of single hair shafts selected from the MALDI target. MALDI imaging intensities in single hairs showed good semi-quantitative correlation with the results from conventional HPLC-MS/MS. MALDI-MSI is suitable for monitoring drug intake with a high time resolution. Copyright © 2017 Elsevier B.V. All rights reserved.

Spatial-Temporal Data Collection with Compressive Sensing in Mobile Sensor Networks

PubMed Central

Li, Jiayin; Guo, Wenzhong; Chen, Zhonghui; Xiong, Neal

2017-01-01

Compressive sensing (CS) provides an energy-efficient paradigm for data gathering in wireless sensor networks (WSNs). However, the existing work on spatial-temporal data gathering using compressive sensing only considers either multi-hop relaying based or multiple random walks based approaches. In this paper, we exploit the mobility pattern for spatial-temporal data collection and propose a novel mobile data gathering scheme by employing the Metropolis-Hastings algorithm with delayed acceptance, an improved random walk algorithm for a mobile collector to collect data from a sensing field. The proposed scheme exploits Kronecker compressive sensing (KCS) for spatial-temporal correlation of sensory data by allowing the mobile collector to gather temporal compressive measurements from a small subset of randomly selected nodes along a random routing path. More importantly, from the theoretical perspective we prove that the equivalent sensing matrix constructed from the proposed scheme for spatial-temporal compressible signal can satisfy the property of KCS models. The simulation results demonstrate that the proposed scheme can not only significantly reduce communication cost but also improve recovery accuracy for mobile data gathering compared to the other existing schemes. In particular, we also show that the proposed scheme is robust in unreliable wireless environment under various packet losses. All this indicates that the proposed scheme can be an efficient alternative for data gathering application in WSNs. PMID:29117152

Spatial-Temporal Data Collection with Compressive Sensing in Mobile Sensor Networks.

PubMed

Zheng, Haifeng; Li, Jiayin; Feng, Xinxin; Guo, Wenzhong; Chen, Zhonghui; Xiong, Neal

2017-11-08

Compressive sensing (CS) provides an energy-efficient paradigm for data gathering in wireless sensor networks (WSNs). However, the existing work on spatial-temporal data gathering using compressive sensing only considers either multi-hop relaying based or multiple random walks based approaches. In this paper, we exploit the mobility pattern for spatial-temporal data collection and propose a novel mobile data gathering scheme by employing the Metropolis-Hastings algorithm with delayed acceptance, an improved random walk algorithm for a mobile collector to collect data from a sensing field. The proposed scheme exploits Kronecker compressive sensing (KCS) for spatial-temporal correlation of sensory data by allowing the mobile collector to gather temporal compressive measurements from a small subset of randomly selected nodes along a random routing path. More importantly, from the theoretical perspective we prove that the equivalent sensing matrix constructed from the proposed scheme for spatial-temporal compressible signal can satisfy the property of KCS models. The simulation results demonstrate that the proposed scheme can not only significantly reduce communication cost but also improve recovery accuracy for mobile data gathering compared to the other existing schemes. In particular, we also show that the proposed scheme is robust in unreliable wireless environment under various packet losses. All this indicates that the proposed scheme can be an efficient alternative for data gathering application in WSNs .

Platelet geometry sensing spatially regulates α-granule secretion to enable matrix self-deposition

PubMed Central

Sakurai, Yumiko; Fitch-Tewfik, Jennifer L.; Qiu, Yongzhi; Ahn, Byungwook; Myers, David R.; Tran, Reginald; Fay, Meredith E.; Ding, Lingmei; Spearman, Paul W.; Michelson, Alan D.; Flaumenhaft, Robert

2015-01-01

Although the biology of platelet adhesion on subendothelial matrix after vascular injury is well characterized, how the matrix biophysical properties affect platelet physiology is unknown. Here we demonstrate that geometric orientation of the matrix itself regulates platelet α-granule secretion, a key component of platelet activation. Using protein microcontact printing, we show that platelets spread beyond the geometric constraints of fibrinogen or collagen micropatterns with <5-µm features. Interestingly, α-granule exocytosis and deposition of the α-granule contents such as fibrinogen and fibronectin were primarily observed in those areas of platelet extension beyond the matrix protein micropatterns. This enables platelets to “self-deposit” additional matrix, provide more cellular membrane to extend spreading, and reinforce platelet-platelet connections. Mechanistically, this phenomenon is mediated by actin polymerization, Rac1 activation, and αIIbβ3 integrin redistribution and activation, and is attenuated in gray platelet syndrome platelets, which lack α-granules, and Wiskott-Aldrich syndrome platelets, which have cytoskeletal defects. Overall, these studies demonstrate how platelets transduce geometric cues of the underlying matrix geometry into intracellular signals to extend spreading, which endows platelets spatial flexibility when spreading onto small sites of exposed subendothelium. PMID:25964667

Trust in Leadership DEOCS 4.1 Construct Validity Summary

DTIC Science & Technology

2017-08-01

Item Corrected Item- Total Correlation Cronbach’s Alpha if Item Deleted Four-point Scale Items I can depend on my immediate supervisor to meet...1974) were used to assess the fit between the data and the factor. The BTS hypothesizes that the correlation matrix is an identity matrix. The...to reject the null hypothesis that the correlation matrix is an identity, and to conclude that the factor analysis is an appropriate method to

Recurrence quantification analysis applied to spatiotemporal pattern analysis in high-density mapping of human atrial fibrillation.

PubMed

Zeemering, Stef; Bonizzi, Pietro; Maesen, Bart; Peeters, Ralf; Schotten, Ulrich

2015-01-01

Spatiotemporal complexity of atrial fibrillation (AF) patterns is often quantified by annotated intracardiac contact mapping. We introduce a new approach that applies recurrence plot (RP) construction followed by recurrence quantification analysis (RQA) to epicardial atrial electrograms, recorded with a high-density grid of electrodes. In 32 patients with no history of AF (aAF, n=11), paroxysmal AF (PAF, n=12) and persistent AF (persAF, n=9), RPs were constructed using a phase space electrogram embedding dimension equal to the estimated AF cycle length. Spatial information was incorporated by 1) averaging the recurrence over all electrodes, and 2) by applying principal component analysis (PCA) to the matrix of embedded electrograms and selecting the first principal component as a representation of spatial diversity. Standard RQA parameters were computed on the constructed RPs and correlated to the number of fibrillation waves per AF cycle (NW). Averaged RP RQA parameters showed no correlation with NW. Correlations improved when applying PCA, with maximum correlation achieved between RP threshold and NW (RR1%, r=0.68, p <; 0.001) and RP determinism (DET, r=-0.64, p <; 0.001). All studied RQA parameters based on the PCA RP were able to discriminate between persAF and aAF/PAF (DET persAF 0.40 ± 0.11 vs. 0.59 ± 0.14/0.62 ± 0.16, p <; 0.01). RP construction and RQA combined with PCA provide a quick and reliable tool to visualize dynamical behaviour and to assess the complexity of contact mapping patterns in AF.

Spatial vs. non-spatial eco-evolutionary dynamics in a tumor growth model.

PubMed

You, Li; Brown, Joel S; Thuijsman, Frank; Cunningham, Jessica J; Gatenby, Robert A; Zhang, Jingsong; Staňková, Kateřina

2017-12-21

Metastatic prostate cancer is initially treated with androgen deprivation therapy (ADT). However, resistance typically develops in about 1 year - a clinical condition termed metastatic castrate-resistant prostate cancer (mCRPC). We develop and investigate a spatial game (agent based continuous space) of mCRPC that considers three distinct cancer cell types: (1) those dependent on exogenous testosterone (T + ), (2) those with increased CYP17A expression that produce testosterone and provide it to the environment as a public good (T P ), and (3) those independent of testosterone (T - ). The interactions within and between cancer cell types can be represented by a 3 × 3 matrix. Based on the known biology of this cancer there are 22 potential matrices that give roughly three major outcomes depending upon the absence (good prognosis), near absence or high frequency (poor prognosis) of T -  cells at the evolutionarily stable strategy (ESS). When just two cell types coexist the spatial game faithfully reproduces the ESS of the corresponding matrix game. With three cell types divergences occur, in some cases just two strategies coexist in the spatial game even as a non-spatial matrix game supports all three. Discrepancies between the spatial game and non-spatial ESS happen because different cell types become more or less clumped in the spatial game - leading to non-random assortative interactions between cell types. Three key spatial scales influence the distribution and abundance of cell types in the spatial game: i. Increasing the radius at which cells interact with each other can lead to higher clumping of each type, ii. Increasing the radius at which cells experience limits to population growth can cause densely packed tumor clusters in space, iii. Increasing the dispersal radius of daughter cells promotes increased mixing of cell types. To our knowledge the effects of these spatial scales on eco-evolutionary dynamics have not been explored in cancer models. The fact that cancer interactions are spatially explicit and that our spatial game of mCRPC provides in general different outcomes than the non-spatial game might suggest that non-spatial models are insufficient for capturing key elements of tumorigenesis. Copyright © 2017 Elsevier Ltd. All rights reserved.

CPDES3: A preconditioned conjugate gradient solver for linear asymmetric matrix equations arising from coupled partial differential equations in three dimensions

NASA Astrophysics Data System (ADS)

Anderson, D. V.; Koniges, A. E.; Shumaker, D. E.

1988-11-01

Many physical problems require the solution of coupled partial differential equations on three-dimensional domains. When the time scales of interest dictate an implicit discretization of the equations a rather complicated global matrix system needs solution. The exact form of the matrix depends on the choice of spatial grids and on the finite element or finite difference approximations employed. CPDES3 allows each spatial operator to have 7, 15, 19, or 27 point stencils and allows for general couplings between all of the component PDE's and it automatically generates the matrix structures needed to perform the algorithm. The resulting sparse matrix equation is solved by either the preconditioned conjugate gradient (CG) method or by the preconditioned biconjugate gradient (BCG) algorithm. An arbitrary number of component equations are permitted only limited by available memory. In the sub-band representation used, we generate an algorithm that is written compactly in terms of indirect induces which is vectorizable on some of the newer scientific computers.

CPDES2: A preconditioned conjugate gradient solver for linear asymmetric matrix equations arising from coupled partial differential equations in two dimensions

NASA Astrophysics Data System (ADS)

Anderson, D. V.; Koniges, A. E.; Shumaker, D. E.

1988-11-01

Many physical problems require the solution of coupled partial differential equations on two-dimensional domains. When the time scales of interest dictate an implicit discretization of the equations a rather complicated global matrix system needs solution. The exact form of the matrix depends on the choice of spatial grids and on the finite element or finite difference approximations employed. CPDES2 allows each spatial operator to have 5 or 9 point stencils and allows for general couplings between all of the component PDE's and it automatically generates the matrix structures needed to perform the algorithm. The resulting sparse matrix equation is solved by either the preconditioned conjugate gradient (CG) method or by the preconditioned biconjugate gradient (BCG) algorithm. An arbitrary number of component equations are permitted only limited by available memory. In the sub-band representation used, we generate an algorithm that is written compactly in terms of indirect indices which is vectorizable on some of the newer scientific computers.

Estimating neighborhood variability with a binary comparison matrix.

USGS Publications Warehouse

Murphy, D.L.

1985-01-01

A technique which utilizes a binary comparison matrix has been developed to implement a neighborhood function for a raster format data base. The technique assigns an index value to the center pixel of 3- by 3-pixel neighborhoods. The binary comparison matrix provides additional information not found in two other neighborhood variability statistics; the function is sensitive to both the number of classes within the neighborhood and the frequency of pixel occurrence in each of the classes. Application of the function to a spatial data base from the Kenai National Wildlife Refuge, Alaska, demonstrates 1) the numerical distribution of the index values, and 2) the spatial patterns exhibited by the numerical values. -Author

Extension of latin hypercube samples with correlated variables.

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

Hora, Stephen Curtis; Helton, Jon Craig; Sallaberry, Cedric J. PhD.

2006-11-01

A procedure for extending the size of a Latin hypercube sample (LHS) with rank correlated variables is described and illustrated. The extension procedure starts with an LHS of size m and associated rank correlation matrix C and constructs a new LHS of size 2m that contains the elements of the original LHS and has a rank correlation matrix that is close to the original rank correlation matrix C. The procedure is intended for use in conjunction with uncertainty and sensitivity analysis of computationally demanding models in which it is important to make efficient use of a necessarily limited number ofmore » model evaluations.« less

[Evoked Potential Blind Extraction Based on Fractional Lower Order Spatial Time-Frequency Matrix].

PubMed

Long, Junbo; Wang, Haibin; Zha, Daifeng

2015-04-01

The impulsive electroencephalograph (EEG) noises in evoked potential (EP) signals is very strong, usually with a heavy tail and infinite variance characteristics like the acceleration noise impact, hypoxia and etc., as shown in other special tests. The noises can be described by a stable distribution model. In this paper, Wigner-Ville distribution (WVD) and pseudo Wigner-Ville distribution (PWVD) time-frequency distribution based on the fractional lower order moment are presented to be improved. We got fractional lower order WVD (FLO-WVD) and fractional lower order PWVD (FLO-PWVD) time-frequency distribution which could be suitable for a stable distribution process. We also proposed the fractional lower order spatial time-frequency distribution matrix (FLO-STFM) concept. Therefore, combining with time-frequency underdetermined blind source separation (TF-UBSS), we proposed a new fractional lower order spatial time-frequency underdetermined blind source separation (FLO-TF-UBSS) which can work in a stable distribution environment. We used the FLO-TF-UBSS algorithm to extract EPs. Simulations showed that the proposed method could effectively extract EPs in EEG noises, and the separated EPs and EEG signals based on FLO-TF-UBSS were almost the same as the original signal, but blind separation based on TF-UBSS had certain deviation. The correlation coefficient of the FLO-TF-UBSS algorithm was higher than the TF-UBSS algorithm when generalized signal-to-noise ratio (GSNR) changed from 10 dB to 30 dB and a varied from 1. 06 to 1. 94, and was approximately e- qual to 1. Hence, the proposed FLO-TF-UBSS method might be better than the TF-UBSS algorithm based on second order for extracting EP signal under an EEG noise environment.

Spatial coding-based approach for partitioning big spatial data in Hadoop

NASA Astrophysics Data System (ADS)

Yao, Xiaochuang; Mokbel, Mohamed F.; Alarabi, Louai; Eldawy, Ahmed; Yang, Jianyu; Yun, Wenju; Li, Lin; Ye, Sijing; Zhu, Dehai

2017-09-01

Spatial data partitioning (SDP) plays a powerful role in distributed storage and parallel computing for spatial data. However, due to skew distribution of spatial data and varying volume of spatial vector objects, it leads to a significant challenge to ensure both optimal performance of spatial operation and data balance in the cluster. To tackle this problem, we proposed a spatial coding-based approach for partitioning big spatial data in Hadoop. This approach, firstly, compressed the whole big spatial data based on spatial coding matrix to create a sensing information set (SIS), including spatial code, size, count and other information. SIS was then employed to build spatial partitioning matrix, which was used to spilt all spatial objects into different partitions in the cluster finally. Based on our approach, the neighbouring spatial objects can be partitioned into the same block. At the same time, it also can minimize the data skew in Hadoop distributed file system (HDFS). The presented approach with a case study in this paper is compared against random sampling based partitioning, with three measurement standards, namely, the spatial index quality, data skew in HDFS, and range query performance. The experimental results show that our method based on spatial coding technique can improve the query performance of big spatial data, as well as the data balance in HDFS. We implemented and deployed this approach in Hadoop, and it is also able to support efficiently any other distributed big spatial data systems.

Histomolecular interpretation of pleomorphic adenomas of the salivary gland by matrix-assisted laser desorption ionization imaging and spatial segmentation.

PubMed

Ernst, Günther; Guntinas-Lichius, Orlando; Hauberg-Lotte, Lena; Trede, Dennis; Becker, Michael; Alexandrov, Theodore; von Eggeling, Ferdinand

2015-07-01

Despite efforts in localization of key proteins using immunohistochemistry, the complex proteomic composition of pleomorphic adenomas has not yet been characterized. Matrix-assisted laser desorption/ionization imaging mass spectrometry (MALDI imaging) allows label-free and spatially resolved detection of hundreds of proteins directly from tissue sections and of histomorphological regions by finding colocalized molecular signals. Spatial segmentation of MALDI imaging data is an algorithmic method for finding regions of similar proteomic composition as functionally similar regions. We investigated 2 pleomorphic adenomas by applying spatial segmentation to the MALDI imaging data of tissue sections. The spatial segmentation subdivided the tissue in a good accordance with the tissue histology. Numerous molecular signals colocalized with histologically defined tissue regions were found. Our study highlights the cellular transdifferentiation within the pleomorphic adenoma. It could be shown that spatial segmentation of MALDI imaging data is a promising approach in the emerging field of digital histological analysis and characterization of tumors. © 2014 Wiley Periodicals, Inc.

Coherent Activity in Bilateral Parieto-Occipital Cortices during P300-BCI Operation.

PubMed

Takano, Kouji; Ora, Hiroki; Sekihara, Kensuke; Iwaki, Sunao; Kansaku, Kenji

2014-01-01

The visual P300 brain-computer interface (BCI), a popular system for electroencephalography (EEG)-based BCI, uses the P300 event-related potential to select an icon arranged in a flicker matrix. In earlier studies, we used green/blue (GB) luminance and chromatic changes in the P300-BCI system and reported that this luminance and chromatic flicker matrix was associated with better performance and greater subject comfort compared with the conventional white/gray (WG) luminance flicker matrix. To highlight areas involved in improved P300-BCI performance, we used simultaneous EEG-fMRI recordings and showed enhanced activities in bilateral and right lateralized parieto-occipital areas. Here, to capture coherent activities of the areas during P300-BCI, we collected whole-head 306-channel magnetoencephalography data. When comparing functional connectivity between the right and left parieto-occipital channels, significantly greater functional connectivity in the alpha band was observed under the GB flicker matrix condition than under the WG flicker matrix condition. Current sources were estimated with a narrow-band adaptive spatial filter, and mean imaginary coherence was computed in the alpha band. Significantly greater coherence was observed in the right posterior parietal cortex under the GB than under the WG condition. Re-analysis of previous EEG-based P300-BCI data showed significant correlations between the power of the coherence of the bilateral parieto-occipital cortices and their performance accuracy. These results suggest that coherent activity in the bilateral parieto-occipital cortices plays a significant role in effectively driving the P300-BCI.

Postconcussive Symptoms in OEF-OIF Veterans: Factor Structure and Impact of Posttraumatic Stress

DTIC Science & Technology

2009-06-03

correlations between NSI full items are presented in Appendix A. Visual inspection of the correlation matrix, the Kaiser - Meyer - Olkin coefficient of .92, and...Spearman rho correlations between NSI residuals are pre- sented in Appendix B. Again, visual inspection of the correla- tion matrix, the Kaiser - Meyer ... Olkin coefficient of .83, and Bartlett’s test of sphericity (x2 5 1,936.0, p , .01) suggested that the matrix could be factored. Principal-components

A new procedure of modal parameter estimation for high-speed digital image correlation

NASA Astrophysics Data System (ADS)

Huňady, Róbert; Hagara, Martin

2017-09-01

The paper deals with the use of 3D digital image correlation in determining modal parameters of mechanical systems. It is a non-contact optical method, which for the measurement of full-field spatial displacements and strains of bodies uses precise digital cameras with high image resolution. Most often this method is utilized for testing of components or determination of material properties of various specimens. In the case of using high-speed cameras for measurement, the correlation system is capable of capturing various dynamic behaviors, including vibration. This enables the potential use of the mentioned method in experimental modal analysis. For that purpose, the authors proposed a measuring chain for the correlation system Q-450 and developed a software application called DICMAN 3D, which allows the direct use of this system in the area of modal testing. The created application provides the post-processing of measured data and the estimation of modal parameters. It has its own graphical user interface, in which several algorithms for the determination of natural frequencies, mode shapes and damping of particular modes of vibration are implemented. The paper describes the basic principle of the new estimation procedure which is crucial in the light of post-processing. Since the FRF matrix resulting from the measurement is usually relatively large, the estimation of modal parameters directly from the FRF matrix may be time-consuming and may occupy a large part of computer memory. The procedure implemented in DICMAN 3D provides a significant reduction in memory requirements and computational time while achieving a high accuracy of modal parameters. Its computational efficiency is particularly evident when the FRF matrix consists of thousands of measurement DOFs. The functionality of the created software application is presented on a practical example in which the modal parameters of a composite plate excited by an impact hammer were determined. For the verification of the obtained results a verification experiment was conducted during which the vibration responses were measured using conventional acceleration sensors. In both cases MIMO analysis was realized.

A metrics for soil hydrological processes and their intrinsic dimensionality in heterogeneous systems

NASA Astrophysics Data System (ADS)

Lischeid, G.; Hohenbrink, T.; Schindler, U.

2012-04-01

Hydrology is based on the observation that catchments process input signals, e.g., precipitation, in a highly deterministic way. Thus, the Darcy or the Richards equation can be applied to model water fluxes in the saturated or vadose zone, respectively. Soils and aquifers usually exhibit substantial spatial heterogeneities at different scales that can, in principle, be represented by corresponding parameterisations of the models. In practice, however, data are hardly available at the required spatial resolution, and accounting for observed heterogeneities of soil and aquifer structure renders models very time and CPU consuming. We hypothesize that the intrinsic dimensionality of soil hydrological processes, which is induced by spatial heterogeneities, actually is very low and that soil hydrological processes in heterogeneous soils follow approximately the same trajectory. That means, the way how the soil transforms any hydrological input signals is the same for different soil textures and structures. Different soils differ only with respect to the extent of transformation of input signals. In a first step, we analysed the output of a soil hydrological model, based on the Richards equation, for homogeneous soils down to 5 m depth for different soil textures. A matrix of time series of soil matrix potential and soil water content at 10 cm depth intervals was set up. The intrinsic dimensionality of that matrix was assessed using the Correlation Dimension and a non-linear principal component approach. The latter provided a metrics for the extent of transformation ("damping") of the input signal. In a second step, model outputs for heterogeneous soils were analysed. In a last step, the same approaches were applied to 55 time series of observed soil water content from 15 sites and different depths. In all cases, the intrinsic dimensionality in fact was very close to unity, confirming our hypothesis. The metrics provided a very efficient tool to quantify the observed behaviour, depending on depth and soil heterogeneity: Different soils differed primarily with respect to the extent of damping per depth interval rather than to the kind of damping. We will show how that metrics can be used in a very efficient way for representing soil heterogeneities in simulation models.

Exploring multicollinearity using a random matrix theory approach.

PubMed

Feher, Kristen; Whelan, James; Müller, Samuel

2012-01-01

Clustering of gene expression data is often done with the latent aim of dimension reduction, by finding groups of genes that have a common response to potentially unknown stimuli. However, what is poorly understood to date is the behaviour of a low dimensional signal embedded in high dimensions. This paper introduces a multicollinear model which is based on random matrix theory results, and shows potential for the characterisation of a gene cluster's correlation matrix. This model projects a one dimensional signal into many dimensions and is based on the spiked covariance model, but rather characterises the behaviour of the corresponding correlation matrix. The eigenspectrum of the correlation matrix is empirically examined by simulation, under the addition of noise to the original signal. The simulation results are then used to propose a dimension estimation procedure of clusters from data. Moreover, the simulation results warn against considering pairwise correlations in isolation, as the model provides a mechanism whereby a pair of genes with `low' correlation may simply be due to the interaction of high dimension and noise. Instead, collective information about all the variables is given by the eigenspectrum.

Neutrinoless ββ decay mediated by the exchange of light and heavy neutrinos: the role of nuclear structure correlations

NASA Astrophysics Data System (ADS)

Menéndez, J.

2018-01-01

Neutrinoless β β decay nuclear matrix elements calculated with the shell model and energy-density functional theory typically disagree by more than a factor of two in the standard scenario of light-neutrino exchange. In contrast, for a decay mediated by sterile heavy neutrinos the deviations are reduced to about 50%, an uncertainty similar to the one due to short-range effects. We compare matrix elements in the light- and heavy-neutrino-exchange channels, exploring the radial, momentum transfer and angular momentum-parity matrix element distributions, and considering transitions that involve correlated and uncorrelated nuclear states. We argue that the shorter-range heavy-neutrino exchange is less sensitive to collective nuclear correlations, and that discrepancies in matrix elements are mostly due to the treatment of long-range correlations in many-body calculations. Our analysis supports previous studies suggesting that isoscalar pairing correlations, which affect mostly the longer-range part of the neutrinoless β β decay operator, are partially responsible for the differences between nuclear matrix elements in the standard light-neutrino-exchange mechanism.

Market power in electric power markets: Indications of competitiveness in spatial prices for wholesale electricity

NASA Astrophysics Data System (ADS)

Denton, Michael John

The issue of market delineation and power in the wholesale electric energy market is explored using three separate approaches: two of these are analyses of spatial pricing data to explore the functional size of the markets, and the third is a series of experimental tests of the effects of different cost structures and market mechanisms on oligopoly strength in those markets. An equilibrium model of spatial network competition is shown to yield linear relationships between spatial prices. A data set comprising two years of spatial weekly peak and off-peak prices and weather for 6 locations in the Western States Coordinating Council and the Southwest Power Pool is subjected to a pairwise cointegration analysis. The use of dummy variables to account the the flow directions is found to significantly improve model performance. The second analytical technique utilizes the extraction of principal components from a spatial price correlation matrix to identify the extent of natural markets. One year of daily price observations for eleven locations within the WSCC is compiled and eigenvectors are extracted and subjected to oblique rotation, each of which is then interpreted as representing a separate geographic market. The results show that two distinct natural markets, correlated at 84%, account for over 96% of the variation in the spatial prices in the WSSC. Together, the findings support the assertion that the wholesale electricity market in the Western U.S. is large and highly competitive. The experimental analysis utilizes a radial three node network in which suppliers located at the outer nodes sell to buyers located at the central node. The parameterization captures the salient characteristics of the existing bulk power markets, and includes cyclical demand, transmission losses, as well as fixed and avoidable fixed costs for all agents. Treatments varied the number of sellers, the avoidable fixed cost structures, and the trading mechanism. Results indicated that sealed bid markets greatly reduced the ability of sellers to exert market power. Overall the existence of higher avoidable fixed costs tended to ameliorate market power effects.

Eigenvalue density of cross-correlations in Sri Lankan financial market

NASA Astrophysics Data System (ADS)

Nilantha, K. G. D. R.; Ranasinghe; Malmini, P. K. C.

2007-05-01

We apply the universal properties with Gaussian orthogonal ensemble (GOE) of random matrices namely spectral properties, distribution of eigenvalues, eigenvalue spacing predicted by random matrix theory (RMT) to compare cross-correlation matrix estimators from emerging market data. The daily stock prices of the Sri Lankan All share price index and Milanka price index from August 2004 to March 2005 were analyzed. Most eigenvalues in the spectrum of the cross-correlation matrix of stock price changes agree with the universal predictions of RMT. We find that the cross-correlation matrix satisfies the universal properties of the GOE of real symmetric random matrices. The eigen distribution follows the RMT predictions in the bulk but there are some deviations at the large eigenvalues. The nearest-neighbor spacing and the next nearest-neighbor spacing of the eigenvalues were examined and found that they follow the universality of GOE. RMT with deterministic correlations found that each eigenvalue from deterministic correlations is observed at values, which are repelled from the bulk distribution.

Noise suppression for dual-energy CT via penalized weighted least-square optimization with similarity-based regularization

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

Harms, Joseph; Wang, Tonghe; Petrongolo, Michael

Purpose: Dual-energy CT (DECT) expands applications of CT imaging in its capability to decompose CT images into material images. However, decomposition via direct matrix inversion leads to large noise amplification and limits quantitative use of DECT. Their group has previously developed a noise suppression algorithm via penalized weighted least-square optimization with edge-preservation regularization (PWLS-EPR). In this paper, the authors improve method performance using the same framework of penalized weighted least-square optimization but with similarity-based regularization (PWLS-SBR), which substantially enhances the quality of decomposed images by retaining a more uniform noise power spectrum (NPS). Methods: The design of PWLS-SBR is basedmore » on the fact that averaging pixels of similar materials gives a low-noise image. For each pixel, the authors calculate the similarity to other pixels in its neighborhood by comparing CT values. Using an empirical Gaussian model, the authors assign high/low similarity value to one neighboring pixel if its CT value is close/far to the CT value of the pixel of interest. These similarity values are organized in matrix form, such that multiplication of the similarity matrix to the image vector reduces image noise. The similarity matrices are calculated on both high- and low-energy CT images and averaged. In PWLS-SBR, the authors include a regularization term to minimize the L-2 norm of the difference between the images without and with noise suppression via similarity matrix multiplication. By using all pixel information of the initial CT images rather than just those lying on or near edges, PWLS-SBR is superior to the previously developed PWLS-EPR, as supported by comparison studies on phantoms and a head-and-neck patient. Results: On the line-pair slice of the Catphan{sup ©}600 phantom, PWLS-SBR outperforms PWLS-EPR and retains spatial resolution of 8 lp/cm, comparable to the original CT images, even at 90% reduction in noise standard deviation (STD). Similar performance on spatial resolution is observed on an anthropomorphic head phantom. In addition, results of PWLS-SBR show substantially improved image quality due to preservation of image NPS. On the Catphan{sup ©}600 phantom, NPS using PWLS-SBR has a correlation of 93% with that via direct matrix inversion, while the correlation drops to −52% for PWLS-EPR. Electron density measurement studies indicate high accuracy of PWLS-SBR. On seven different materials, the measured electron densities calculated from the decomposed material images using PWLS-SBR have a root-mean-square error (RMSE) of 1.20%, while the results of PWLS-EPR have a RMSE of 2.21%. In the study on a head-and-neck patient, PWLS-SBR is shown to reduce noise STD by a factor of 3 on material images with image qualities comparable to CT images, whereas fine structures are lost in the PWLS-EPR result. Additionally, PWLS-SBR better preserves low contrast on the tissue image. Conclusions: The authors propose improvements to the regularization term of an optimization framework which performs iterative image-domain decomposition for DECT with noise suppression. The regularization term avoids calculation of image gradient and is based on pixel similarity. The proposed method not only achieves a high decomposition accuracy, but also improves over the previous algorithm on NPS as well as spatial resolution.« less

Noise suppression for dual-energy CT via penalized weighted least-square optimization with similarity-based regularization

PubMed Central

Harms, Joseph; Wang, Tonghe; Petrongolo, Michael; Niu, Tianye; Zhu, Lei

2016-01-01

Purpose: Dual-energy CT (DECT) expands applications of CT imaging in its capability to decompose CT images into material images. However, decomposition via direct matrix inversion leads to large noise amplification and limits quantitative use of DECT. Their group has previously developed a noise suppression algorithm via penalized weighted least-square optimization with edge-preservation regularization (PWLS-EPR). In this paper, the authors improve method performance using the same framework of penalized weighted least-square optimization but with similarity-based regularization (PWLS-SBR), which substantially enhances the quality of decomposed images by retaining a more uniform noise power spectrum (NPS). Methods: The design of PWLS-SBR is based on the fact that averaging pixels of similar materials gives a low-noise image. For each pixel, the authors calculate the similarity to other pixels in its neighborhood by comparing CT values. Using an empirical Gaussian model, the authors assign high/low similarity value to one neighboring pixel if its CT value is close/far to the CT value of the pixel of interest. These similarity values are organized in matrix form, such that multiplication of the similarity matrix to the image vector reduces image noise. The similarity matrices are calculated on both high- and low-energy CT images and averaged. In PWLS-SBR, the authors include a regularization term to minimize the L-2 norm of the difference between the images without and with noise suppression via similarity matrix multiplication. By using all pixel information of the initial CT images rather than just those lying on or near edges, PWLS-SBR is superior to the previously developed PWLS-EPR, as supported by comparison studies on phantoms and a head-and-neck patient. Results: On the line-pair slice of the Catphan©600 phantom, PWLS-SBR outperforms PWLS-EPR and retains spatial resolution of 8 lp/cm, comparable to the original CT images, even at 90% reduction in noise standard deviation (STD). Similar performance on spatial resolution is observed on an anthropomorphic head phantom. In addition, results of PWLS-SBR show substantially improved image quality due to preservation of image NPS. On the Catphan©600 phantom, NPS using PWLS-SBR has a correlation of 93% with that via direct matrix inversion, while the correlation drops to −52% for PWLS-EPR. Electron density measurement studies indicate high accuracy of PWLS-SBR. On seven different materials, the measured electron densities calculated from the decomposed material images using PWLS-SBR have a root-mean-square error (RMSE) of 1.20%, while the results of PWLS-EPR have a RMSE of 2.21%. In the study on a head-and-neck patient, PWLS-SBR is shown to reduce noise STD by a factor of 3 on material images with image qualities comparable to CT images, whereas fine structures are lost in the PWLS-EPR result. Additionally, PWLS-SBR better preserves low contrast on the tissue image. Conclusions: The authors propose improvements to the regularization term of an optimization framework which performs iterative image-domain decomposition for DECT with noise suppression. The regularization term avoids calculation of image gradient and is based on pixel similarity. The proposed method not only achieves a high decomposition accuracy, but also improves over the previous algorithm on NPS as well as spatial resolution. PMID:27147376

Spatial distribution of organic pollutants in industrial construction and demolition waste and their mutual interaction on an abandoned pesticide manufacturing plant.

PubMed

Huang, Sheng; Zhao, Xin; Sun, Yanqiu; Ma, Jianli; Gao, Xiaofeng; Xie, Tian; Xu, Dongsheng; Yu, Yi; Zhao, Youcai

2016-04-01

A comprehensive field investigation of organic pollutants was examined in industrial construction and demolition waste (ICDW) inside an abandoned pesticide manufacturing plant. Concentrations of eight types of pesticides, a metabolite and two intermediates were studied. The ICDW was under severe and long-term contamination by organophosphorus, intermediates and pyrethroid pesticide with mean concentrations of 23,429, 3538 and 179.4 mg kg(-1), respectively. FT-IR analysis suggested that physical absorption and chemical bonding were their mutual interaction forms. Patterns of total pesticide spatial distribution showed good correlations with manufacturing processes spreading all over the plant both in enclosed workshops and in residues randomly dumped outside, while bricks and coatings were the most vulnerable to pollutants. Ultimately the fate of the OPPs was diversified as the immersion of ICDW in water largely transferred the pollutants into aquatic systems while exposure outside did not largely lead to pesticide degradation. The adoption of centralized collections for the disposal of wastes could only eliminate part of the contaminated ICDW, probably due to lack of knowledge and criteria. Correlation matrix and cluster analysis indicated that regulated disposal and management of polluted ICDW was effective, thus presenting the requirement for its appropriate disposal.

Smoothing effect for spatially distributed renewable resources and its impact on power grid robustness.

PubMed

Nagata, Motoki; Hirata, Yoshito; Fujiwara, Naoya; Tanaka, Gouhei; Suzuki, Hideyuki; Aihara, Kazuyuki

2017-03-01

In this paper, we show that spatial correlation of renewable energy outputs greatly influences the robustness of the power grids against large fluctuations of the effective power. First, we evaluate the spatial correlation among renewable energy outputs. We find that the spatial correlation of renewable energy outputs depends on the locations, while the influence of the spatial correlation of renewable energy outputs on power grids is not well known. Thus, second, by employing the topology of the power grid in eastern Japan, we analyze the robustness of the power grid with spatial correlation of renewable energy outputs. The analysis is performed by using a realistic differential-algebraic equations model. The results show that the spatial correlation of the energy resources strongly degrades the robustness of the power grid. Our results suggest that we should consider the spatial correlation of the renewable energy outputs when estimating the stability of power grids.

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

PubMed

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

2018-02-15

Microarray technology can be used to study the expression of thousands of genes across a number of different experimental conditions, usually hundreds. The underlying principle is that genes sharing similar expression patterns, across different samples, can be part of the same co-expression system, or they may share the same biological functions. Groups of genes are usually identified based on cluster analysis. Clustering methods rely on the similarity matrix between genes. A common choice to measure similarity is to compute the sample correlation matrix. Dimensionality reduction is another popular data analysis task which is also based on covariance/correlation matrix estimates. Unfortunately, covariance/correlation matrix estimation suffers from the intrinsic noise present in high-dimensional data. Sources of noise are: sampling variations, presents of outlying sample units, and the fact that in most cases the number of units is much larger than the number of genes. In this paper, we propose a robust correlation matrix estimator that is regularized based on adaptive thresholding. The resulting method jointly tames the effects of the high-dimensionality, and data contamination. Computations are easy to implement and do not require hand tunings. Both simulated and real data are analyzed. A Monte Carlo experiment shows that the proposed method is capable of remarkable performances. Our correlation metric is more robust to outliers compared with the existing alternatives in two gene expression datasets. It is also shown how the regularization allows to automatically detect and filter spurious correlations. The same regularization is also extended to other less robust correlation measures. Finally, we apply the ARACNE algorithm on the SyNTreN gene expression data. Sensitivity and specificity of the reconstructed network is compared with the gold standard. We show that ARACNE performs better when it takes the proposed correlation matrix estimator as input. The R software is available at https://github.com/angy89/RobustSparseCorrelation. aserra@unisa.it or robtag@unisa.it. Supplementary data are available at Bioinformatics online. © The Author (2017). Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com

Complete spatiotemporal characterization and optical transfer matrix inversion of a 420 mode fiber.

PubMed

Carpenter, Joel; Eggleton, Benjamin J; Schröder, Jochen

2016-12-01

The ability to measure a scattering medium's optical transfer matrix, the mapping between any spatial input and output, has enabled applications such as imaging to be performed through media which would otherwise be opaque due to scattering. However, the scattering of light occurs not just in space, but also in time. We complete the characterization of scatter by extending optical transfer matrix methods into the time domain, allowing any spatiotemporal input state at one end to be mapped directly to its corresponding spatiotemporal output state. We have measured the optical transfer function of a multimode fiber in its entirety; it consists of 420 modes in/out at 32768 wavelengths, the most detailed complete characterization of multimode waveguide light propagation to date, to the best of our knowledge. We then demonstrate the ability to generate any spatial/polarization state at the output of the fiber at any wavelength, as well as predict the temporal response of any spatial/polarization input state.

Scale-Free Nonparametric Factor Analysis: A User-Friendly Introduction with Concrete Heuristic Examples.

ERIC Educational Resources Information Center

Mittag, Kathleen Cage

Most researchers using factor analysis extract factors from a matrix of Pearson product-moment correlation coefficients. A method is presented for extracting factors in a non-parametric way, by extracting factors from a matrix of Spearman rho (rank correlation) coefficients. It is possible to factor analyze a matrix of association such that…

Complex mode indication function and its applications to spatial domain parameter estimation

NASA Astrophysics Data System (ADS)

Shih, C. Y.; Tsuei, Y. G.; Allemang, R. J.; Brown, D. L.

1988-10-01

This paper introduces the concept of the Complex Mode Indication Function (CMIF) and its application in spatial domain parameter estimation. The concept of CMIF is developed by performing singular value decomposition (SVD) of the Frequency Response Function (FRF) matrix at each spectral line. The CMIF is defined as the eigenvalues, which are the square of the singular values, solved from the normal matrix formed from the FRF matrix, [ H( jω)] H[ H( jω)], at each spectral line. The CMIF appears to be a simple and efficient method for identifying the modes of the complex system. The CMIF identifies modes by showing the physical magnitude of each mode and the damped natural frequency for each root. Since multiple reference data is applied in CMIF, repeated roots can be detected. The CMIF also gives global modal parameters, such as damped natural frequencies, mode shapes and modal participation vectors. Since CMIF works in the spatial domain, uneven frequency spacing data such as data from spatial sine testing can be used. A second-stage procedure for accurate damped natural frequency and damping estimation as well as mode shape scaling is also discussed in this paper.

Evolution of In-Situ Generated Reinforcement Precipitates in Metal Matrix Composites

NASA Technical Reports Server (NTRS)

Sen, S.; Kar, S. K.; Catalina, A. V.; Stefanescu, D. M.; Dhindaw, B. K.

2004-01-01

Due to certain inherent advantages, in-situ production of Metal Matrix Composites (MMCs) have received considerable attention in the recent past. ln-situ techniques typically involve a chemical reaction that results in precipitation of a ceramic reinforcement phase. The size and spatial distribution of these precipitates ultimately determine the mechanical properties of these MMCs. In this paper we will investigate the validity of using classical growth laws and analytical expressions to describe the interaction between a precipitate and a solid-liquid interface (SLI) to predict the size and spatial evolution of the in-situ generated precipitates. Measurements made on size and distribution of Tic precipitates in a Ni&I matrix will be presented to test the validity of such an approach.

Decentralized state estimation for a large-scale spatially interconnected system.

PubMed

Liu, Huabo; Yu, Haisheng

2018-03-01

A decentralized state estimator is derived for the spatially interconnected systems composed of many subsystems with arbitrary connection relations. An optimization problem on the basis of linear matrix inequality (LMI) is constructed for the computations of improved subsystem parameter matrices. Several computationally effective approaches are derived which efficiently utilize the block-diagonal characteristic of system parameter matrices and the sparseness of subsystem connection matrix. Moreover, this decentralized state estimator is proved to converge to a stable system and obtain a bounded covariance matrix of estimation errors under certain conditions. Numerical simulations show that the obtained decentralized state estimator is attractive in the synthesis of a large-scale networked system. Copyright © 2018 ISA. Published by Elsevier Ltd. All rights reserved.

Systematic Correlation Matrix Evaluation (SCoMaE) - a bottom-up, science-led approach to identifying indicators

NASA Astrophysics Data System (ADS)

Mengis, Nadine; Keller, David P.; Oschlies, Andreas

2018-01-01

This study introduces the Systematic Correlation Matrix Evaluation (SCoMaE) method, a bottom-up approach which combines expert judgment and statistical information to systematically select transparent, nonredundant indicators for a comprehensive assessment of the state of the Earth system. The methods consists of two basic steps: (1) the calculation of a correlation matrix among variables relevant for a given research question and (2) the systematic evaluation of the matrix, to identify clusters of variables with similar behavior and respective mutually independent indicators. Optional further analysis steps include (3) the interpretation of the identified clusters, enabling a learning effect from the selection of indicators, (4) testing the robustness of identified clusters with respect to changes in forcing or boundary conditions, (5) enabling a comparative assessment of varying scenarios by constructing and evaluating a common correlation matrix, and (6) the inclusion of expert judgment, for example, to prescribe indicators, to allow for considerations other than statistical consistency. The example application of the SCoMaE method to Earth system model output forced by different CO2 emission scenarios reveals the necessity of reevaluating indicators identified in a historical scenario simulation for an accurate assessment of an intermediate-high, as well as a business-as-usual, climate change scenario simulation. This necessity arises from changes in prevailing correlations in the Earth system under varying climate forcing. For a comparative assessment of the three climate change scenarios, we construct and evaluate a common correlation matrix, in which we identify robust correlations between variables across the three considered scenarios.

Correlating PMC-MMC Bonded Joint 3D FEA with Test

NASA Technical Reports Server (NTRS)

Jacobson, Mindy; Rodini, Benjamin; Chen, Wayne C.; Flom, Yury A.; Posey, Alan J.

2005-01-01

A viewgraph presentation on the correlation of Polymer Matrix Composites (PMC) and Metal Matrix Composites (MMC) bonded joints using three dimensional finite element analyses with materials tests is shown.

Matrix-assisted laser desorption/ionization imaging mass spectrometry for direct measurement of clozapine in rat brain tissue.

PubMed

Hsieh, Yunsheng; Casale, Roger; Fukuda, Elaine; Chen, Jiwen; Knemeyer, Ian; Wingate, Julia; Morrison, Richard; Korfmacher, Walter

2006-01-01

Matrix-assisted laser desorption/ionization hyphenated with quadrupole time-of-flight (QTOF) mass spectrometry (MS) has been used to directly determine the distribution of pharmaceuticals in rat brain tissue slices which might unravel their disposition for new drug development. Clozapine, an antipsychotic drug, and norclozapine were used as model compounds to investigate fundamental parameters such as matrix and solvent effects and irradiance dependence on MALDI intensity but also to address the issues with direct tissue imaging MS technique such as (1) uniform coating by the matrix, (2) linearity of MALDI signals, and (3) redistribution of surface analytes. The tissue sections were coated with various matrices on MALDI plates by airspray deposition prior to MS detection. MALDI signals of analytes were detected by monitoring the dissociation of the individual protonated molecules to their predominant MS/MS product ions. The matrices were chosen for tissue applications based on their ability to form a homogeneous coating of dense crystals and to yield greater sensitivity. Images revealing the spatial localization in tissue sections using MALDI-QTOF following a direct infusion of (3)H-clozapine into rat brain were found to be in good correlation with those using a radioautographic approach. The density of clozapine and its major metabolites from whole brain homogenates was further confirmed using fast high-performance liquid chromatography/tandem mass spectrometry (HPLC-MS/MS) procedures. Copyright (c) 2006 John Wiley & Sons, Ltd.

Group identification in Indonesian stock market

NASA Astrophysics Data System (ADS)

Nurriyadi Suparno, Ervano; Jo, Sung Kyun; Lim, Kyuseong; Purqon, Acep; Kim, Soo Yong

2016-08-01

The characteristic of Indonesian stock market is interesting especially because it represents developing countries. We investigate the dynamics and structures by using Random Matrix Theory (RMT). Here, we analyze the cross-correlation of the fluctuations of the daily closing price of stocks from the Indonesian Stock Exchange (IDX) between January 1, 2007, and October 28, 2014. The eigenvalue distribution of the correlation matrix consists of noise which is filtered out using the random matrix as a control. The bulk of the eigenvalue distribution conforms to the random matrix, allowing the separation of random noise from original data which is the deviating eigenvalues. From the deviating eigenvalues and the corresponding eigenvectors, we identify the intrinsic normal modes of the system and interpret their meaning based on qualitative and quantitative approach. The results show that the largest eigenvector represents the market-wide effect which has a predominantly common influence toward all stocks. The other eigenvectors represent highly correlated groups within the system. Furthermore, identification of the largest components of the eigenvectors shows the sector or background of the correlated groups. Interestingly, the result shows that there are mainly two clusters within IDX, natural and non-natural resource companies. We then decompose the correlation matrix to investigate the contribution of the correlated groups to the total correlation, and we find that IDX is still driven mainly by the market-wide effect.

Scanning electron microscopy of bone.

PubMed

Boyde, Alan

2012-01-01

This chapter described methods for Scanning Electron Microscopical imaging of bone and bone cells. Backscattered electron (BSE) imaging is by far the most useful in the bone field, followed by secondary electrons (SE) and the energy dispersive X-ray (EDX) analytical modes. This chapter considers preparing and imaging samples of unembedded bone having 3D detail in a 3D surface, topography-free, polished or micromilled, resin-embedded block surfaces, and resin casts of space in bone matrix. The chapter considers methods for fixation, drying, looking at undersides of bone cells, and coating. Maceration with alkaline bacterial pronase, hypochlorite, hydrogen peroxide, and sodium or potassium hydroxide to remove cells and unmineralised matrix is described in detail. Attention is given especially to methods for 3D BSE SEM imaging of bone samples and recommendations for the types of resin embedding of bone for BSE imaging are given. Correlated confocal and SEM imaging of PMMA-embedded bone requires the use of glycerol to coverslip. Cathodoluminescence (CL) mode SEM imaging is an alternative for visualising fluorescent mineralising front labels such as calcein and tetracyclines. Making spatial casts from PMMA or other resin embedded samples is an important use of this material. Correlation with other imaging means, including microradiography and microtomography is important. Shipping wet bone samples between labs is best done in glycerol. Environmental SEM (ESEM, controlled vacuum mode) is valuable in eliminating -"charging" problems which are common with complex, cancellous bone samples.

Numerical implementation, verification and validation of two-phase flow four-equation drift flux model with Jacobian-free Newton–Krylov method

DOE PAGES

Zou, Ling; Zhao, Haihua; Zhang, Hongbin

2016-08-24

This study presents a numerical investigation on using the Jacobian-free Newton–Krylov (JFNK) method to solve the two-phase flow four-equation drift flux model with realistic constitutive correlations (‘closure models’). The drift flux model is based on Isshi and his collaborators’ work. Additional constitutive correlations for vertical channel flow, such as two-phase flow pressure drop, flow regime map, wall boiling and interfacial heat transfer models, were taken from the RELAP5-3D Code Manual and included to complete the model. The staggered grid finite volume method and fully implicit backward Euler method was used for the spatial discretization and time integration schemes, respectively. Themore » Jacobian-free Newton–Krylov method shows no difficulty in solving the two-phase flow drift flux model with a discrete flow regime map. In addition to the Jacobian-free approach, the preconditioning matrix is obtained by using the default finite differencing method provided in the PETSc package, and consequently the labor-intensive implementation of complex analytical Jacobian matrix is avoided. Extensive and successful numerical verification and validation have been performed to prove the correct implementation of the models and methods. Code-to-code comparison with RELAP5-3D has further demonstrated the successful implementation of the drift flux model.« less

Statistics of time delay and scattering correlation functions in chaotic systems. I. Random matrix theory

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

Novaes, Marcel

2015-06-15

We consider the statistics of time delay in a chaotic cavity having M open channels, in the absence of time-reversal invariance. In the random matrix theory approach, we compute the average value of polynomial functions of the time delay matrix Q = − iħS{sup †}dS/dE, where S is the scattering matrix. Our results do not assume M to be large. In a companion paper, we develop a semiclassical approximation to S-matrix correlation functions, from which the statistics of Q can also be derived. Together, these papers contribute to establishing the conjectured equivalence between the random matrix and the semiclassical approaches.

Comparative Controller Design for a Marine Gas Turbine Propulsion Plant

DTIC Science & Technology

1988-09-01

ADDRESS (City State, and ZIP Code) ,onterey, California 93943-5000 Monterey, California 93943-5000 Sa. NAME OF FUNDING/SPONSORING 8b OFFICE SYMBOL 9 ...155 7. A21 MATRIX COEFFICIENT CORRELATION DATA ----------- 156 8. A22 MATRIX COEFFICIENT CORRELATION DATA ----------- 157 9 . A23 MATRIX...Flowchart of VRD Algorithm ----------------------- 29 8. Steady State Convergence Map --------------------- 34 9 . Smoothed Dynamic Transition Map

Comparison of Spatial Correlation Parameters between Full and Model Scale Launch Vehicles

NASA Technical Reports Server (NTRS)

Kenny, Jeremy; Giacomoni, Clothilde

2016-01-01

The current vibro-acoustic analysis tools require specific spatial correlation parameters as input to define the liftoff acoustic environment experienced by the launch vehicle. Until recently these parameters have not been very well defined. A comprehensive set of spatial correlation data were obtained during a scale model acoustic test conducted in 2014. From these spatial correlation data, several parameters were calculated: the decay coefficient, the diffuse to propagating ratio, and the angle of incidence. Spatial correlation data were also collected on the EFT-1 flight of the Delta IV vehicle which launched on December 5th, 2014. A comparison of the spatial correlation parameters from full scale and model scale data will be presented.

POLYMAT-C: a comprehensive SPSS program for computing the polychoric correlation matrix.

PubMed

Lorenzo-Seva, Urbano; Ferrando, Pere J

2015-09-01

We provide a free noncommercial SPSS program that implements procedures for (a) obtaining the polychoric correlation matrix between a set of ordered categorical measures, so that it can be used as input for the SPSS factor analysis (FA) program; (b) testing the null hypothesis of zero population correlation for each element of the matrix by using appropriate simulation procedures; (c) obtaining valid and accurate confidence intervals via bootstrap resampling for those correlations found to be significant; and (d) performing, if necessary, a smoothing procedure that makes the matrix amenable to any FA estimation procedure. For the main purpose (a), the program uses a robust unified procedure that allows four different types of estimates to be obtained at the user's choice. Overall, we hope the program will be a very useful tool for the applied researcher, not only because it provides an appropriate input matrix for FA, but also because it allows the researcher to carefully check the appropriateness of the matrix for this purpose. The SPSS syntax, a short manual, and data files related to this article are available as Supplemental materials that are available for download with this article.

Characterization of CDOM of river waters in China using fluorescence excitation-emission matrix and regional integration techniques

NASA Astrophysics Data System (ADS)

Zhao, Ying; Song, Kaishan; Shang, Yingxin; Shao, Tiantian; Wen, Zhidan; Lv, Lili

2017-08-01

The spatial characteristics of fluorescent dissolved organic matter (FDOM) components in river waters in China were first examined by excitation-emission matrix spectra and fluorescence regional integration (FRI) with the data collected during September to November between 2013 and 2015. One tyrosine-like (R1), one tryptophan-like (R2), one fulvic-like (R3), one microbial protein-like (R4), and one humic-like (R5) components have been identified by FRI method. Principal component analysis (PCA) was conducted to assess variations in the five FDOM components (FRί (ί = 1, 2, 3, 4, and 5)) and the humification index for all 194 river water samples. The average fluorescence intensities of the five fluorescent components and the total fluorescence intensities FSUM differed under spatial variation among the seven major river basins (Songhua, Liao, Hai, Yellow and Huai, Yangtze, Pearl, and Inflow Rivers) in China. When all the river water samples were pooled together, the fulvic-like FR3 and the humic-like FR5 showed a strong positive linear relationship (R2 = 0.90, n = 194), indicating that the two allochthonous FDOM components R3 and R5 may originate from similar sources. There is a moderate strong positive correlation between the tryptophan-like FR2 and the microbial protein-like FR4 (R2 = 0.71, n = 194), suggesting that parts of two autochthonous FDOM components R2 and R4 are likely from some common sources. However, the total allochthonous substance FR(3+5) and the total autochthonous substances FR(1+2+4) exhibited a weak correlation (R2 = 0.40, n = 194). Significant positive linear relationships between FR3 (R2 = 0.69, n = 194), FR5 (R2 = 0.79, n = 194), and chromophoric DOM (CDOM) absorption coefficient a(254) were observed, which demonstrated that the CDOM absorption was dominated by the allochthonous FDOM components R3 and R5.

Flow Classification and Cave Discharge Characteristics in Unsaturated Karst Formation

NASA Astrophysics Data System (ADS)

Mariethoz, G.; Mahmud, K.; Baker, A.; Treble, P. C.

2015-12-01

In this study we utilize the spatial array of automated cave drip monitoring in two large chambers of the Golgotha Cave, SW Australia, developed in Quaternary aeolianite (dune limestone), with the aim of understanding infiltration water movement via the relationships between infiltration, stalactite morphology and groundwater recharge. Mahmud et al. (2015) used the Terrestrial LiDAR measurements to analyze stalactite morphology and to characterize possible flow locations in this cave. Here we identify the stalactites feeding the drip loggers and classify each as matrix (soda straw or icicle), fracture or combined-flow. These morphology-based classifications are compared with flow characteristics from the drip logger time series and the discharge from each stalactite is calculated. The total estimated discharge from each area is compared with infiltration estimates to better understand flow from the surface to the cave ceilings of the studied areas. The drip discharge data agrees with the morphology-based flow classification in terms of flow and geometrical characteristics of cave ceiling stalactites. No significant relationships were observed between the drip logger discharge, skewness and coefficient of variation with overburden thickness, due to the possibility of potential vadose-zone storage volume and increasing complexity of the karst architecture. However, these properties can be used to characterize different flow categories. A correlation matrix demonstrates that similar flow categories are positively correlated, implying significant influence of spatial distribution. The infiltration water comes from a larger surface area, suggesting that infiltration is being focused to the studied ceiling areas of each chamber. Most of the ceiling in the cave site is dry, suggesting the possibility of capillary effects with water moving around the cave rather than passing through it. Reference:Mahmud et al. (2015), Terrestrial Lidar Survey and Morphological Analysis to Identify Infiltration Properties in the Tamala Limestone, Western Australia, IEEE JSTARS, DOI: 10.1109/JSTARS.2015.2451088, in Press.

A Method of Q-Matrix Validation for the Linear Logistic Test Model

PubMed Central

Baghaei, Purya; Hohensinn, Christine

2017-01-01

The linear logistic test model (LLTM) is a well-recognized psychometric model for examining the components of difficulty in cognitive tests and validating construct theories. The plausibility of the construct model, summarized in a matrix of weights, known as the Q-matrix or weight matrix, is tested by (1) comparing the fit of LLTM with the fit of the Rasch model (RM) using the likelihood ratio (LR) test and (2) by examining the correlation between the Rasch model item parameters and LLTM reconstructed item parameters. The problem with the LR test is that it is almost always significant and, consequently, LLTM is rejected. The drawback of examining the correlation coefficient is that there is no cut-off value or lower bound for the magnitude of the correlation coefficient. In this article we suggest a simulation method to set a minimum benchmark for the correlation between item parameters from the Rasch model and those reconstructed by the LLTM. If the cognitive model is valid then the correlation coefficient between the RM-based item parameters and the LLTM-reconstructed item parameters derived from the theoretical weight matrix should be greater than those derived from the simulated matrices. PMID:28611721

Functional CAR models for large spatially correlated functional datasets.

PubMed

Zhang, Lin; Baladandayuthapani, Veerabhadran; Zhu, Hongxiao; Baggerly, Keith A; Majewski, Tadeusz; Czerniak, Bogdan A; Morris, Jeffrey S

2016-01-01

We develop a functional conditional autoregressive (CAR) model for spatially correlated data for which functions are collected on areal units of a lattice. Our model performs functional response regression while accounting for spatial correlations with potentially nonseparable and nonstationary covariance structure, in both the space and functional domains. We show theoretically that our construction leads to a CAR model at each functional location, with spatial covariance parameters varying and borrowing strength across the functional domain. Using basis transformation strategies, the nonseparable spatial-functional model is computationally scalable to enormous functional datasets, generalizable to different basis functions, and can be used on functions defined on higher dimensional domains such as images. Through simulation studies, we demonstrate that accounting for the spatial correlation in our modeling leads to improved functional regression performance. Applied to a high-throughput spatially correlated copy number dataset, the model identifies genetic markers not identified by comparable methods that ignore spatial correlations.

On evolutionary spatial heterogeneous games

NASA Astrophysics Data System (ADS)

Fort, H.

2008-03-01

How cooperation between self-interested individuals evolve is a crucial problem, both in biology and in social sciences, that is far from being well understood. Evolutionary game theory is a useful approach to this issue. The simplest model to take into account the spatial dimension in evolutionary games is in terms of cellular automata with just a one-parameter payoff matrix. Here, the effects of spatial heterogeneities of the environment and/or asymmetries in the interactions among the individuals are analysed through different extensions of this model. Instead of using the same universal payoff matrix, bimatrix games in which each cell at site ( i, j) has its own different ‘temptation to defect’ parameter T(i,j) are considered. First, the case in which these individual payoffs are constant in time is studied. Second, an evolving evolutionary spatial game such that T=T(i,j;t), i.e. besides depending on the position evolves (by natural selection), is used to explore the combination of spatial heterogeneity and natural selection of payoff matrices.

Statistical properties of cross-correlation in the Korean stock market

NASA Astrophysics Data System (ADS)

Oh, G.; Eom, C.; Wang, F.; Jung, W.-S.; Stanley, H. E.; Kim, S.

2011-01-01

We investigate the statistical properties of the cross-correlation matrix between individual stocks traded in the Korean stock market using the random matrix theory (RMT) and observe how these affect the portfolio weights in the Markowitz portfolio theory. We find that the distribution of the cross-correlation matrix is positively skewed and changes over time. We find that the eigenvalue distribution of original cross-correlation matrix deviates from the eigenvalues predicted by the RMT, and the largest eigenvalue is 52 times larger than the maximum value among the eigenvalues predicted by the RMT. The β_{473} coefficient, which reflect the largest eigenvalue property, is 0.8, while one of the eigenvalues in the RMT is approximately zero. Notably, we show that the entropy function E(σ) with the portfolio risk σ for the original and filtered cross-correlation matrices are consistent with a power-law function, E( σ) σ^{-γ}, with the exponent γ 2.92 and those for Asian currency crisis decreases significantly.

A bias correction for covariance estimators to improve inference with generalized estimating equations that use an unstructured correlation matrix.

PubMed

Westgate, Philip M

2013-07-20

Generalized estimating equations (GEEs) are routinely used for the marginal analysis of correlated data. The efficiency of GEE depends on how closely the working covariance structure resembles the true structure, and therefore accurate modeling of the working correlation of the data is important. A popular approach is the use of an unstructured working correlation matrix, as it is not as restrictive as simpler structures such as exchangeable and AR-1 and thus can theoretically improve efficiency. However, because of the potential for having to estimate a large number of correlation parameters, variances of regression parameter estimates can be larger than theoretically expected when utilizing the unstructured working correlation matrix. Therefore, standard error estimates can be negatively biased. To account for this additional finite-sample variability, we derive a bias correction that can be applied to typical estimators of the covariance matrix of parameter estimates. Via simulation and in application to a longitudinal study, we show that our proposed correction improves standard error estimation and statistical inference. Copyright © 2012 John Wiley & Sons, Ltd.

An attempt to determine the effect of increase of observation correlations on detectability and identifiability of a single gross error

NASA Astrophysics Data System (ADS)

Prószyński, Witold; Kwaśniak, Mieczysław

2016-12-01

The paper presents the results of investigating the effect of increase of observation correlations on detectability and identifiability of a single gross error, the outlier test sensitivity and also the response-based measures of internal reliability of networks. To reduce in a research a practically incomputable number of possible test options when considering all the non-diagonal elements of the correlation matrix as variables, its simplest representation was used being a matrix with all non-diagonal elements of equal values, termed uniform correlation. By raising the common correlation value incrementally, a sequence of matrix configurations could be obtained corresponding to the increasing level of observation correlations. For each of the measures characterizing the above mentioned features of network reliability the effect is presented in a diagram form as a function of the increasing level of observation correlations. The influence of observation correlations on sensitivity of the w-test for correlated observations (Förstner 1983, Teunissen 2006) is investigated in comparison with the original Baarda's w-test designated for uncorrelated observations, to determine the character of expected sensitivity degradation of the latter when used for correlated observations. The correlation effects obtained for different reliability measures exhibit mutual consistency in a satisfactory extent. As a by-product of the analyses, a simple formula valid for any arbitrary correlation matrix is proposed for transforming the Baarda's w-test statistics into the w-test statistics for correlated observations.

Joint transform correlators with spatially incoherent illumination

NASA Astrophysics Data System (ADS)

Bykovsky, Yuri A.; Karpiouk, Andrey B.; Markilov, Anatoly A.; Rodin, Vladislav G.; Starikov, Sergey N.

1997-03-01

Two variants of joint transform correlators with monochromatic spatially incoherent illumination are considered. The Fourier-holograms of the reference and recognized images are recorded simultaneously or apart in a time on the same spatial light modulator directly by monochromatic spatially incoherent light. To create the signal of mutual correlation of the images it is necessary to execute nonlinear transformation when the hologram is illuminated by coherent light. In the first scheme of the correlator this aim was achieved by using double pas of a restoring coherent wave through the hologram. In the second variant of the correlator the non-linearity of the characteristic of the spatial light modulator for hologram recording was used. Experimental schemes and results on processing teste images by both variants of joint transform correlators with monochromatic spatially incoherent illumination. The use of spatially incoherent light on the input of joint transform correlators permits to reduce the requirements to optical quality of elements, to reduce accuracy requirements on elements positioning and to expand a number of devices suitable to input images in correlators.

Matrix recrystallization for MALDI-MS imaging of maize lipids at high-spatial resolution

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

Duenas, Maria Emilia; Carlucci, Laura; Lee, Young Jin

Matrix recrystallization is optimized and applied to improve lipid ion signals in maize embryos and leaves. A systematic study was performed varying solvent and incubation time. During this study, unexpected side reactions were found when methanol was used as a recrystallization solvent, resulting in the formation of a methyl ester of phosphatidic acid. Furthermore, using an optimum recrystallization condition with isopropanol, there is no apparent delocalization demonstrated with a transmission electron microscopy (TEM) pattern and maize leaf images obtained at 10 μm spatial resolution.

Matrix recrystallization for MALDI-MS imaging of maize lipids at high-spatial resolution

DOE PAGES

Duenas, Maria Emilia; Carlucci, Laura; Lee, Young Jin

2016-06-27

Matrix recrystallization is optimized and applied to improve lipid ion signals in maize embryos and leaves. A systematic study was performed varying solvent and incubation time. During this study, unexpected side reactions were found when methanol was used as a recrystallization solvent, resulting in the formation of a methyl ester of phosphatidic acid. Furthermore, using an optimum recrystallization condition with isopropanol, there is no apparent delocalization demonstrated with a transmission electron microscopy (TEM) pattern and maize leaf images obtained at 10 μm spatial resolution.

Matrix Recrystallization for MALDI-MS Imaging of Maize Lipids at High-Spatial Resolution

NASA Astrophysics Data System (ADS)

Dueñas, Maria Emilia; Carlucci, Laura; Lee, Young Jin

2016-09-01

Matrix recrystallization is optimized and applied to improve lipid ion signals in maize embryos and leaves. A systematic study was performed varying solvent and incubation time. During this study, unexpected side reactions were found when methanol was used as a recrystallization solvent, resulting in the formation of a methyl ester of phosphatidic acid. Using an optimum recrystallization condition with isopropanol, there is no apparent delocalization demonstrated with a transmission electron microscopy (TEM) pattern and maize leaf images obtained at 10 μm spatial resolution.

Matrix Recrystallization for MALDI-MS Imaging of Maize Lipids at High-Spatial Resolution.

PubMed

Dueñas, Maria Emilia; Carlucci, Laura; Lee, Young Jin

2016-09-01

Matrix recrystallization is optimized and applied to improve lipid ion signals in maize embryos and leaves. A systematic study was performed varying solvent and incubation time. During this study, unexpected side reactions were found when methanol was used as a recrystallization solvent, resulting in the formation of a methyl ester of phosphatidic acid. Using an optimum recrystallization condition with isopropanol, there is no apparent delocalization demonstrated with a transmission electron microscopy (TEM) pattern and maize leaf images obtained at 10 μm spatial resolution. Graphical Abstract ᅟ.

Biogeochemistry and Spatial Distribution of the Microbial-Mineral Interface Using I2LD-FTMS

NASA Astrophysics Data System (ADS)

Scott, J. R.; Kauffman, M. E.; Kauffman, M. E.; Tremblay, P. L.

2001-12-01

Previous studies indicate that biogeochemistry can vary within individual mineral specimens in contact with microorganisms. These same studies have shown that microcosms containing a mixture of minerals simulating a heterogeneous geologic matrix do not yield the same results as the naturally occurring rock. Therefore, it is of utmost importance to develop analytical tools that can provide spatially correlative biogeochemical data of the microbial-mineral interface within naturally occurring geologic matrices. Imaging internal laser desorption Fourier transform mass spectrometry (I2LD-FTMS) can provide elemental and molecular information of the microbial-mineral interface at a spatial resolution limited only by the optical diffraction limit of the final focusing lens (down to 2 μ m). Additionally, the I2LD-FTMS used in this study has exceptional reproducibility, which can provide successive mapping sequences for depth-profiling studies. Basalt core samples, taken from the Snake River Plain Aquifer in southeastern Idaho, were mapped prior to, and after, exposure to a bacterial culture. The bacteria-basalt interface spectra were collected using the I2LD-FTMS at the INEEL. Mass spectra were recorded over a mass-to-charge range of 30-2500 Da with an average peak resolution of 15,000 using 10 μ m spots. Two-dimensional maps were constructed depicting the spatial distribution of the minerals within the basalt as well as the spatial distribution of the bacteria on the basalt surface. This represents the first reported application of I2LD-FTMS in the field of biogeochemistry.

Local sensitivity to stimulus orientation and spatial frequency within the receptive fields of neurons in visual area 2 of macaque monkeys

PubMed Central

Tao, X.; Zhang, B.; Smith, E. L.; Nishimoto, S.; Ohzawa, I.

2012-01-01

We used dynamic dense noise stimuli and local spectral reverse correlation methods to reveal the local sensitivities of neurons in visual area 2 (V2) of macaque monkeys to orientation and spatial frequency within their receptive fields. This minimized the potentially confounding assumptions that are inherent in stimulus selections. The majority of neurons exhibited a relatively high degree of homogeneity for the preferred orientations and spatial frequencies in the spatial matrix of facilitatory subfields. However, about 20% of all neurons showed maximum orientation differences between neighboring subfields that were greater than 25 deg. The neurons preferring horizontal or vertical orientations showed less inhomogeneity in space than the neurons preferring oblique orientations. Over 50% of all units also exhibited suppressive profiles, and those were more heterogeneous than facilitatory profiles. The preferred orientation and spatial frequency of suppressive profiles differed substantially from those of facilitatory profiles, and the neurons with suppressive subfields had greater orientation selectivity than those without suppressive subfields. The peak suppression occurred with longer delays than the peak facilitation. These results suggest that the receptive field profiles of the majority of V2 neurons reflect the orderly convergence of V1 inputs over space, but that a subset of V2 neurons exhibit more complex response profiles having both suppressive and facilitatory subfields. These V2 neurons with heterogeneous subfield profiles could play an important role in the initial processing of complex stimulus features. PMID:22114163

Correlation and volatility in an Indian stock market: A random matrix approach

NASA Astrophysics Data System (ADS)

Kulkarni, Varsha; Deo, Nivedita

2007-11-01

We examine the volatility of an Indian stock market in terms of correlation of stocks and quantify the volatility using the random matrix approach. First we discuss trends observed in the pattern of stock prices in the Bombay Stock Exchange for the three-year period 2000 2002. Random matrix analysis is then applied to study the relationship between the coupling of stocks and volatility. The study uses daily returns of 70 stocks for successive time windows of length 85 days for the year 2001. We compare the properties of matrix C of correlations between price fluctuations in time regimes characterized by different volatilities. Our analyses reveal that (i) the largest (deviating) eigenvalue of C correlates highly with the volatility of the index, (ii) there is a shift in the distribution of the components of the eigenvector corresponding to the largest eigenvalue across regimes of different volatilities, (iii) the inverse participation ratio for this eigenvector anti-correlates significantly with the market fluctuations and finally, (iv) this eigenvector of C can be used to set up a Correlation Index, CI whose temporal evolution is significantly correlated with the volatility of the overall market index.

ChromAlign: A two-step algorithmic procedure for time alignment of three-dimensional LC-MS chromatographic surfaces.

PubMed

Sadygov, Rovshan G; Maroto, Fernando Martin; Hühmer, Andreas F R

2006-12-15

We present an algorithmic approach to align three-dimensional chromatographic surfaces of LC-MS data of complex mixture samples. The approach consists of two steps. In the first step, we prealign chromatographic profiles: two-dimensional projections of chromatographic surfaces. This is accomplished by correlation analysis using fast Fourier transforms. In this step, a temporal offset that maximizes the overlap and dot product between two chromatographic profiles is determined. In the second step, the algorithm generates correlation matrix elements between full mass scans of the reference and sample chromatographic surfaces. The temporal offset from the first step indicates a range of the mass scans that are possibly correlated, then the correlation matrix is calculated only for these mass scans. The correlation matrix carries information on highly correlated scans, but it does not itself determine the scan or time alignment. Alignment is determined as a path in the correlation matrix that maximizes the sum of the correlation matrix elements. The computational complexity of the optimal path generation problem is reduced by the use of dynamic programming. The program produces time-aligned surfaces. The use of the temporal offset from the first step in the second step reduces the computation time for generating the correlation matrix and speeds up the process. The algorithm has been implemented in a program, ChromAlign, developed in C++ language for the .NET2 environment in WINDOWS XP. In this work, we demonstrate the applications of ChromAlign to alignment of LC-MS surfaces of several datasets: a mixture of known proteins, samples from digests of surface proteins of T-cells, and samples prepared from digests of cerebrospinal fluid. ChromAlign accurately aligns the LC-MS surfaces we studied. In these examples, we discuss various aspects of the alignment by ChromAlign, such as constant time axis shifts and warping of chromatographic surfaces.

Matrix diffusion coefficients in volcanic rocks at the Nevada test site: influence of matrix porosity, matrix permeability, and fracture coating minerals.

PubMed

Reimus, Paul W; Callahan, Timothy J; Ware, S Doug; Haga, Marc J; Counce, Dale A

2007-08-15

Diffusion cell experiments were conducted to measure nonsorbing solute matrix diffusion coefficients in forty-seven different volcanic rock matrix samples from eight different locations (with multiple depth intervals represented at several locations) at the Nevada Test Site. The solutes used in the experiments included bromide, iodide, pentafluorobenzoate (PFBA), and tritiated water ((3)HHO). The porosity and saturated permeability of most of the diffusion cell samples were measured to evaluate the correlation of these two variables with tracer matrix diffusion coefficients divided by the free-water diffusion coefficient (D(m)/D*). To investigate the influence of fracture coating minerals on matrix diffusion, ten of the diffusion cells represented paired samples from the same depth interval in which one sample contained a fracture surface with mineral coatings and the other sample consisted of only pure matrix. The log of (D(m)/D*) was found to be positively correlated with both the matrix porosity and the log of matrix permeability. A multiple linear regression analysis indicated that both parameters contributed significantly to the regression at the 95% confidence level. However, the log of the matrix diffusion coefficient was more highly-correlated with the log of matrix permeability than with matrix porosity, which suggests that matrix diffusion coefficients, like matrix permeabilities, have a greater dependence on the interconnectedness of matrix porosity than on the matrix porosity itself. The regression equation for the volcanic rocks was found to provide satisfactory predictions of log(D(m)/D*) for other types of rocks with similar ranges of matrix porosity and permeability as the volcanic rocks, but it did a poorer job predicting log(D(m)/D*) for rocks with lower porosities and/or permeabilities. The presence of mineral coatings on fracture walls did not appear to have a significant effect on matrix diffusion in the ten paired diffusion cell experiments.

Matrix diffusion coefficients in volcanic rocks at the Nevada test site: Influence of matrix porosity, matrix permeability, and fracture coating minerals

NASA Astrophysics Data System (ADS)

Reimus, Paul W.; Callahan, Timothy J.; Ware, S. Doug; Haga, Marc J.; Counce, Dale A.

2007-08-01

Diffusion cell experiments were conducted to measure nonsorbing solute matrix diffusion coefficients in forty-seven different volcanic rock matrix samples from eight different locations (with multiple depth intervals represented at several locations) at the Nevada Test Site. The solutes used in the experiments included bromide, iodide, pentafluorobenzoate (PFBA), and tritiated water ( 3HHO). The porosity and saturated permeability of most of the diffusion cell samples were measured to evaluate the correlation of these two variables with tracer matrix diffusion coefficients divided by the free-water diffusion coefficient ( Dm/ D*). To investigate the influence of fracture coating minerals on matrix diffusion, ten of the diffusion cells represented paired samples from the same depth interval in which one sample contained a fracture surface with mineral coatings and the other sample consisted of only pure matrix. The log of ( Dm/ D*) was found to be positively correlated with both the matrix porosity and the log of matrix permeability. A multiple linear regression analysis indicated that both parameters contributed significantly to the regression at the 95% confidence level. However, the log of the matrix diffusion coefficient was more highly-correlated with the log of matrix permeability than with matrix porosity, which suggests that matrix diffusion coefficients, like matrix permeabilities, have a greater dependence on the interconnectedness of matrix porosity than on the matrix porosity itself. The regression equation for the volcanic rocks was found to provide satisfactory predictions of log( Dm/ D*) for other types of rocks with similar ranges of matrix porosity and permeability as the volcanic rocks, but it did a poorer job predicting log( Dm/ D*) for rocks with lower porosities and/or permeabilities. The presence of mineral coatings on fracture walls did not appear to have a significant effect on matrix diffusion in the ten paired diffusion cell experiments.

Biomineralization of calcium carbonate in the cell wall of Lithothamnion crispatum (Hapalidiales, Rhodophyta): correlation between the organic matrix and the mineral phase.

PubMed

de Carvalho, Rodrigo Tomazetto; Salgado, Leonardo Tavares; Amado Filho, Gilberto Menezes; Leal, Rachel Nunes; Werckmann, Jacques; Rossi, André Linhares; Campos, Andrea Porto Carreiro; Karez, Cláudia Santiago; Farina, Marcos

2017-06-01

Over the past few decades, progress has been made toward understanding the mechanisms of coralline algae mineralization. However, the relationship between the mineral phase and the organic matrix in coralline algae has not yet been thoroughly examined. The aim of this study was to describe the cell wall ultrastructure of Lithothamnion crispatum, a cosmopolitan rhodolith-forming coralline algal species collected near Salvador (Brazil), and examine the relationship between the organic matrix and the nucleation and growth/shape modulation of calcium carbonate crystals. A nanostructured pattern was observed in L. crispatum along the cell walls. At the nanoscale, the crystals from L. crispatum consisted of several single crystallites assembled and associated with organic material. The crystallites in the bulk of the cell wall had a high level of spatial organization. However, the crystals displayed cleavages in the (104) faces after ultrathin sectioning with a microtome. This organism is an important model for biomineralization studies as the crystallographic data do not fit in any of the general biomineralization processes described for other organisms. Biomineralization in L. crispatum is dependent on both the soluble and the insoluble organic matrix, which are involved in the control of mineral formation and organizational patterns through an organic matrix-mediated process. This knowledge concerning the mineral composition and organizational patterns of crystals within the cell walls should be taken into account in future studies of changing ocean conditions as they represent important factors influencing the physico-chemical interactions between rhodoliths and the environment in coralline reefs. © 2017 Phycological Society of America.

Study on the regulation of focal adesions and cortical actin by matrix nanotopography in 3D environment

NASA Astrophysics Data System (ADS)

Han, Jingjing; Lin, Keng-Hui; Chew, Lock Yue

2017-11-01

Matrix nanotopography plays an important role in regulating cell behaviors by providing spatial as well as mechanical cues for cells to sense. It has been proposed that nanoscale topography is possible to modulate the tensions which direct the formation of cytoskeleton and the organization of the membrane receptor within the cell, which in turn regulate intracellular mechanical and biochemical signaling. With current studies on this topic being performed mainly in 2D platforms, the question on how nanotopography can influence cell bahaviors in 3D environments has yet to be addressed. In this paper, we explored this question by placing cells in 3D hollow spherical polydimethylsiloxane scaffolds. After culturing rat embryonic fibroblast cells in two kinds of scaffold, one with smooth surface and the other with numerous nano-spikes, we observed that cells in the smooth scaffold have more anchoring sites and more focal adhesions than in the etched scaffold. Moreover, we found the presence of correlation between cortical actin, the important component for supporting cell attachment, and local cell geometry.

A model relating Eulerian spatial and temporal velocity correlations

NASA Astrophysics Data System (ADS)

Cholemari, Murali R.; Arakeri, Jaywant H.

2006-03-01

In this paper we propose a model to relate Eulerian spatial and temporal velocity autocorrelations in homogeneous, isotropic and stationary turbulence. We model the decorrelation as the eddies of various scales becoming decorrelated. This enables us to connect the spatial and temporal separations required for a certain decorrelation through the ‘eddy scale’. Given either the spatial or the temporal velocity correlation, we obtain the ‘eddy scale’ and the rate at which the decorrelation proceeds. This leads to a spatial separation from the temporal correlation and a temporal separation from the spatial correlation, at any given value of the correlation relating the two correlations. We test the model using experimental data from a stationary axisymmetric turbulent flow with homogeneity along the axis.

Hyperspectral and multispectral data fusion based on linear-quadratic nonnegative matrix factorization

NASA Astrophysics Data System (ADS)

Benhalouche, Fatima Zohra; Karoui, Moussa Sofiane; Deville, Yannick; Ouamri, Abdelaziz

2017-04-01

This paper proposes three multisharpening approaches to enhance the spatial resolution of urban hyperspectral remote sensing images. These approaches, related to linear-quadratic spectral unmixing techniques, use a linear-quadratic nonnegative matrix factorization (NMF) multiplicative algorithm. These methods begin by unmixing the observable high-spectral/low-spatial resolution hyperspectral and high-spatial/low-spectral resolution multispectral images. The obtained high-spectral/high-spatial resolution features are then recombined, according to the linear-quadratic mixing model, to obtain an unobservable multisharpened high-spectral/high-spatial resolution hyperspectral image. In the first designed approach, hyperspectral and multispectral variables are independently optimized, once they have been coherently initialized. These variables are alternately updated in the second designed approach. In the third approach, the considered hyperspectral and multispectral variables are jointly updated. Experiments, using synthetic and real data, are conducted to assess the efficiency, in spatial and spectral domains, of the designed approaches and of linear NMF-based approaches from the literature. Experimental results show that the designed methods globally yield very satisfactory spectral and spatial fidelities for the multisharpened hyperspectral data. They also prove that these methods significantly outperform the used literature approaches.

The link between employee attitudes and employee effectiveness: Data matrix of meta-analytic estimates based on 1161 unique correlations.

PubMed

Mackay, Michael M

2016-09-01

This article offers a correlation matrix of meta-analytic estimates between various employee job attitudes (i.e., Employee engagement, job satisfaction, job involvement, and organizational commitment) and indicators of employee effectiveness (i.e., Focal performance, contextual performance, turnover intention, and absenteeism). The meta-analytic correlations in the matrix are based on over 1100 individual studies representing over 340,000 employees. Data was collected worldwide via employee self-report surveys. Structural path analyses based on the matrix, and the interpretation of the data, can be found in "Investigating the incremental validity of employee engagement in the prediction of employee effectiveness: a meta-analytic path analysis" (Mackay et al., 2016) [1].

Estimation of Covariance Matrix on Bi-Response Longitudinal Data Analysis with Penalized Spline Regression

NASA Astrophysics Data System (ADS)

Islamiyati, A.; Fatmawati; Chamidah, N.

2018-03-01

The correlation assumption of the longitudinal data with bi-response occurs on the measurement between the subjects of observation and the response. It causes the auto-correlation of error, and this can be overcome by using a covariance matrix. In this article, we estimate the covariance matrix based on the penalized spline regression model. Penalized spline involves knot points and smoothing parameters simultaneously in controlling the smoothness of the curve. Based on our simulation study, the estimated regression model of the weighted penalized spline with covariance matrix gives a smaller error value compared to the error of the model without covariance matrix.

Resource availability, matrix quality, microclimate, and spatial pattern as predictors of patch use by the Karner blue butterfly

USGS Publications Warehouse

Grundel, R.; Pavlovic, N.B.

2007-01-01

Determination of which aspects of habitat quality and habitat spatial arrangement best account for variation in a species’ distribution can guide management for organisms such as the Karner blue butterfly (Lycaeides melissa samuelis), a federally endangered subspecies inhabiting savannas of Midwest and Eastern United States. We examined the extent to which three sets of predictors, (1) larval host plant (Lupinus perennis, wild lupine) availability, (2) characteristics of the matrix surrounding host plant patches, and (3) factors affecting a patch’s thermal environment, accounted for variation in lupine patch use by Karner blues at Indiana Dunes National Lakeshore, Indiana and Fort McCoy, Wisconsin, USA. Each predictor set accounted for 7–13% of variation in patch occupancy by Karner blues at both sites and in larval feeding activity among patches at Indiana Dunes. Patch area, an indicator of host plant availability, was an exception, accounting for 30% of variation in patch occupancy at Indiana Dunes. Spatially structured patterns of patch use across the landscape accounted for 9–16% of variation in patch use and explained more variation in larval feeding activity than did spatial autocorrelation between neighboring patches. Because of this broader spatial trend across sites, a given management action may be more effective in promoting patch use in some portions of the landscape than in others. Spatial trend, resource availability, matrix quality, and microclimate, in general, accounted for similar amounts of variation in patch use and each should be incorporated into habitat management planning for the Karner blue butterfly.

Analysis of spatial correlation in predictive models of forest variables that use LiDAR auxiliary information

Treesearch

F. Mauro; Vicente J. Monleon; H. Temesgen; L.A. Ruiz

2017-01-01

Accounting for spatial correlation of LiDAR model errors can improve the precision of model-based estimators. To estimate spatial correlation, sample designs that provide close observations are needed, but their implementation might be prohibitively expensive. To quantify the gains obtained by accounting for the spatial correlation of model errors, we examined (

Direct Visualization of Neurotransmitters in Rat Brain Slices by Desorption Electrospray Ionization Mass Spectrometry Imaging (DESI - MS)

NASA Astrophysics Data System (ADS)

Fernandes, Anna Maria A. P.; Vendramini, Pedro H.; Galaverna, Renan; Schwab, Nicolas V.; Alberici, Luciane C.; Augusti, Rodinei; Castilho, Roger F.; Eberlin, Marcos N.

2016-12-01

Mass spectrometry imaging (MSI) of neurotransmitters has so far been mainly performed by matrix-assisted laser desorption/ionization (MALDI) where derivatization reagents, deuterated matrix and/or high resolution, or tandem MS have been applied to circumvent problems with interfering ion peaks from matrix and from isobaric species. We herein describe the application of desorption electrospray ionization mass spectrometry imaging (DESI)-MSI in rat brain coronal and sagittal slices for direct spatial monitoring of neurotransmitters and choline with no need of derivatization reagents and/or deuterated materials. The amino acids γ-aminobutyric (GABA), glutamate, aspartate, serine, as well as acetylcholine, dopamine, and choline were successfully imaged using a commercial DESI source coupled to a hybrid quadrupole-Orbitrap mass spectrometer. The spatial distribution of the analyzed compounds in different brain regions was determined. We conclude that the ambient matrix-free DESI-MSI is suitable for neurotransmitter imaging and could be applied in studies that involve evaluation of imbalances in neurotransmitters levels.

Escherichia coli Biofilms Have an Organized and Complex Extracellular Matrix Structure

PubMed Central

Hung, Chia; Zhou, Yizhou; Pinkner, Jerome S.; Dodson, Karen W.; Crowley, Jan R.; Heuser, John; Chapman, Matthew R.; Hadjifrangiskou, Maria; Henderson, Jeffrey P.; Hultgren, Scott J.

2013-01-01

ABSTRACT Bacterial biofilms are ubiquitous in nature, and their resilience is derived in part from a complex extracellular matrix that can be tailored to meet environmental demands. Although common developmental stages leading to biofilm formation have been described, how the extracellular components are organized to allow three-dimensional biofilm development is not well understood. Here we show that uropathogenic Escherichia coli (UPEC) strains produce a biofilm with a highly ordered and complex extracellular matrix (ECM). We used electron microscopy (EM) techniques to image floating biofilms (pellicles) formed by UPEC. EM revealed intricately constructed substructures within the ECM that encase individual, spatially segregated bacteria with a distinctive morphology. Mutational and biochemical analyses of these biofilms confirmed curli as a major matrix component and revealed important roles for cellulose, flagella, and type 1 pili in pellicle integrity and ECM infrastructure. Collectively, the findings of this study elucidated that UPEC pellicles have a highly organized ultrastructure that varies spatially across the multicellular community. PMID:24023384

Easy way to determine quantitative spatial resolution distribution for a general inverse problem

NASA Astrophysics Data System (ADS)

An, M.; Feng, M.

2013-12-01

The spatial resolution computation of a solution was nontrivial and more difficult than solving an inverse problem. Most geophysical studies, except for tomographic studies, almost uniformly neglect the calculation of a practical spatial resolution. In seismic tomography studies, a qualitative resolution length can be indicatively given via visual inspection of the restoration of a synthetic structure (e.g., checkerboard tests). An effective strategy for obtaining quantitative resolution length is to calculate Backus-Gilbert resolution kernels (also referred to as a resolution matrix) by matrix operation. However, not all resolution matrices can provide resolution length information, and the computation of resolution matrix is often a difficult problem for very large inverse problems. A new class of resolution matrices, called the statistical resolution matrices (An, 2012, GJI), can be directly determined via a simple one-parameter nonlinear inversion performed based on limited pairs of random synthetic models and their inverse solutions. The total procedure were restricted to forward/inversion processes used in the real inverse problem and were independent of the degree of inverse skill used in the solution inversion. Spatial resolution lengths can be directly given during the inversion. Tests on 1D/2D/3D model inversion demonstrated that this simple method can be at least valid for a general linear inverse problem.

Spatially varying dispersion to model breakthrough curves.

PubMed

Li, Guangquan

2011-01-01

Often the water flowing in a karst conduit is a combination of contaminated water entering at a sinkhole and cleaner water released from the limestone matrix. Transport processes in the conduit are controlled by advection, mixing (dilution and dispersion), and retention-release. In this article, a karst transport model considering advection, spatially varying dispersion, and dilution (from matrix seepage) is developed. Two approximate Green's functions are obtained using transformation of variables, respectively, for the initial-value problem and for the boundary-value problem. A numerical example illustrates that mixing associated with strong spatially varying conduit dispersion can cause strong skewness and long tailing in spring breakthrough curves. Comparison of the predicted breakthrough curve against that measured from a dye-tracing experiment between Ames Sink and Indian Spring, Northwest Florida, shows that the conduit dispersivity can be as large as 400 m. Such a large number is believed to imply strong solute interaction between the conduit and the matrix and/or multiple flow paths in a conduit network. It is concluded that Taylor dispersion is not dominant in transport in a karst conduit, and the complicated retention-release process between mobile- and immobile waters may be described by strong spatially varying conduit dispersion. Copyright © 2010 The Author(s). Journal compilation © 2010 National Ground Water Association.

The modelling of the flow-induced vibrations of periodic flat and axial-symmetric structures with a wave-based method

NASA Astrophysics Data System (ADS)

Errico, F.; Ichchou, M.; De Rosa, S.; Bareille, O.; Franco, F.

2018-06-01

The stochastic response of periodic flat and axial-symmetric structures, subjected to random and spatially-correlated loads, is here analysed through an approach based on the combination of a wave finite element and a transfer matrix method. Although giving a lower computational cost, the present approach keeps the same accuracy of classic finite element methods. When dealing with homogeneous structures, the accuracy is also extended to higher frequencies, without increasing the time of calculation. Depending on the complexity of the structure and the frequency range, the computational cost can be reduced more than two orders of magnitude. The presented methodology is validated both for simple and complex structural shapes, under deterministic and random loads.

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.

Molecular symmetry with quaternions.

PubMed

Fritzer, H P

2001-09-01

A new and relatively simple version of the quaternion calculus is offered which is especially suitable for applications in molecular symmetry and structure. After introducing the real quaternion algebra and its classical matrix representation in the group SO(4) the relations with vectors in 3-space and the connection with the rotation group SO(3) through automorphism properties of the algebra are discussed. The correlation of the unit quaternions with both the Cayley-Klein and the Euler parameters through the group SU(2) is presented. Besides rotations the extension of quaternions to other important symmetry operations, reflections and the spatial inversion, is given. Finally, the power of the quaternion calculus for molecular symmetry problems is revealed by treating some examples applied to icosahedral symmetry.

A covariance correction that accounts for correlation estimation to improve finite-sample inference with generalized estimating equations: A study on its applicability with structured correlation matrices

PubMed Central

Westgate, Philip M.

2016-01-01

When generalized estimating equations (GEE) incorporate an unstructured working correlation matrix, the variances of regression parameter estimates can inflate due to the estimation of the correlation parameters. In previous work, an approximation for this inflation that results in a corrected version of the sandwich formula for the covariance matrix of regression parameter estimates was derived. Use of this correction for correlation structure selection also reduces the over-selection of the unstructured working correlation matrix. In this manuscript, we conduct a simulation study to demonstrate that an increase in variances of regression parameter estimates can occur when GEE incorporates structured working correlation matrices as well. Correspondingly, we show the ability of the corrected version of the sandwich formula to improve the validity of inference and correlation structure selection. We also study the relative influences of two popular corrections to a different source of bias in the empirical sandwich covariance estimator. PMID:27818539

A covariance correction that accounts for correlation estimation to improve finite-sample inference with generalized estimating equations: A study on its applicability with structured correlation matrices.

PubMed

Westgate, Philip M

2016-01-01

When generalized estimating equations (GEE) incorporate an unstructured working correlation matrix, the variances of regression parameter estimates can inflate due to the estimation of the correlation parameters. In previous work, an approximation for this inflation that results in a corrected version of the sandwich formula for the covariance matrix of regression parameter estimates was derived. Use of this correction for correlation structure selection also reduces the over-selection of the unstructured working correlation matrix. In this manuscript, we conduct a simulation study to demonstrate that an increase in variances of regression parameter estimates can occur when GEE incorporates structured working correlation matrices as well. Correspondingly, we show the ability of the corrected version of the sandwich formula to improve the validity of inference and correlation structure selection. We also study the relative influences of two popular corrections to a different source of bias in the empirical sandwich covariance estimator.

Random matrix theory and portfolio optimization in Moroccan stock exchange

NASA Astrophysics Data System (ADS)

El Alaoui, Marwane

2015-09-01

In this work, we use random matrix theory to analyze eigenvalues and see if there is a presence of pertinent information by using Marčenko-Pastur distribution. Thus, we study cross-correlation among stocks of Casablanca Stock Exchange. Moreover, we clean correlation matrix from noisy elements to see if the gap between predicted risk and realized risk would be reduced. We also analyze eigenvectors components distributions and their degree of deviations by computing the inverse participation ratio. This analysis is a way to understand the correlation structure among stocks of Casablanca Stock Exchange portfolio.

Matrix Approach of Seismic Wave Imaging: Application to Erebus Volcano

NASA Astrophysics Data System (ADS)

Blondel, T.; Chaput, J.; Derode, A.; Campillo, M.; Aubry, A.

2017-12-01

This work aims at extending to seismic imaging a matrix approach of wave propagation in heterogeneous media, previously developed in acoustics and optics. More specifically, we will apply this approach to the imaging of the Erebus volcano in Antarctica. Volcanoes are actually among the most challenging media to explore seismically in light of highly localized and abrupt variations in density and wave velocity, extreme topography, extensive fractures, and the presence of magma. In this strongly scattering regime, conventional imaging methods suffer from the multiple scattering of waves. Our approach experimentally relies on the measurement of a reflection matrix associated with an array of geophones located at the surface of the volcano. Although these sensors are purely passive, a set of Green's functions can be measured between all pairs of geophones from ice-quake coda cross-correlations (1-10 Hz) and forms the reflection matrix. A set of matrix operations can then be applied for imaging purposes. First, the reflection matrix is projected, at each time of flight, in the ballistic focal plane by applying adaptive focusing at emission and reception. It yields a response matrix associated with an array of virtual geophones located at the ballistic depth. This basis allows us to get rid of most of the multiple scattering contribution by applying a confocal filter to seismic data. Iterative time reversal is then applied to detect and image the strongest scatterers. Mathematically, it consists in performing a singular value decomposition of the reflection matrix. The presence of a potential target is assessed from a statistical analysis of the singular values, while the corresponding eigenvectors yield the corresponding target images. When stacked, the results obtained at each depth give a three-dimensional image of the volcano. While conventional imaging methods lead to a speckle image with no connection to the actual medium's reflectivity, our method enables to highlight a chimney-shaped structure inside Erebus volcano with true positive rates ranging from 80% to 95%. Although computed independently, the results at each depth are spatially consistent, substantiating their physical reliability. The identified structure is therefore likely to describe accurately the internal structure of the Erebus volcano.

Prediction of the filtrate particle size distribution from the pore size distribution in membrane filtration: Numerical correlations from computer simulations

NASA Astrophysics Data System (ADS)

Marrufo-Hernández, Norma Alejandra; Hernández-Guerrero, Maribel; Nápoles-Duarte, José Manuel; Palomares-Báez, Juan Pedro; Chávez-Rojo, Marco Antonio

2018-03-01

We present a computational model that describes the diffusion of a hard spheres colloidal fluid through a membrane. The membrane matrix is modeled as a series of flat parallel planes with circular pores of different sizes and random spatial distribution. This model was employed to determine how the size distribution of the colloidal filtrate depends on the size distributions of both, the particles in the feed and the pores of the membrane, as well as to describe the filtration kinetics. A Brownian dynamics simulation study considering normal distributions was developed in order to determine empirical correlations between the parameters that characterize these distributions. The model can also be extended to other distributions such as log-normal. This study could, therefore, facilitate the selection of membranes for industrial or scientific filtration processes once the size distribution of the feed is known and the expected characteristics in the filtrate have been defined.

Compact hybrid optoelectrical unit for image processing and recognition

NASA Astrophysics Data System (ADS)

Cheng, Gang; Jin, Guofan; Wu, Minxian; Liu, Haisong; He, Qingsheng; Yuan, ShiFu

1998-07-01

In this paper a compact opto-electric unit (CHOEU) for digital image processing and recognition is proposed. The central part of CHOEU is an incoherent optical correlator, which is realized with a SHARP QA-1200 8.4 inch active matrix TFT liquid crystal display panel which is used as two real-time spatial light modulators for both the input image and reference template. CHOEU can do two main processing works. One is digital filtering; the other is object matching. Using CHOEU an edge-detection operator is realized to extract the edges from the input images. Then the reprocessed images are sent into the object recognition unit for identifying the important targets. A novel template- matching method is proposed for gray-tome image recognition. A positive and negative cycle-encoding method is introduced to realize the absolute difference measurement pixel- matching on a correlator structure simply. The system has god fault-tolerance ability for rotation distortion, Gaussian noise disturbance or information losing. The experiments are given at the end of this paper.

Correlations induced by depressing synapses in critically self-organized networks with quenched dynamics

NASA Astrophysics Data System (ADS)

Campos, João Guilherme Ferreira; Costa, Ariadne de Andrade; Copelli, Mauro; Kinouchi, Osame

2017-04-01

In a recent work, mean-field analysis and computer simulations were employed to analyze critical self-organization in networks of excitable cellular automata where randomly chosen synapses in the network were depressed after each spike (the so-called annealed dynamics). Calculations agree with simulations of the annealed version, showing that the nominal branching ratio σ converges to unity in the thermodynamic limit, as expected of a self-organized critical system. However, the question remains whether the same results apply to the biological case where only the synapses of firing neurons are depressed (the so-called quenched dynamics). We show that simulations of the quenched model yield significant deviations from σ =1 due to spatial correlations. However, the model is shown to be critical, as the largest eigenvalue of the synaptic matrix approaches unity in the thermodynamic limit, that is, λc=1 . We also study the finite size effects near the critical state as a function of the parameters of the synaptic dynamics.

Applying petrophysical models to radar travel time and electrical resistivity tomograms: Resolution-dependent limitations

USGS Publications Warehouse

Day-Lewis, F. D.; Singha, K.; Binley, A.M.

2005-01-01

Geophysical imaging has traditionally provided qualitative information about geologic structure; however, there is increasing interest in using petrophysical models to convert tomograms to quantitative estimates of hydrogeologic, mechanical, or geochemical parameters of interest (e.g., permeability, porosity, water content, and salinity). Unfortunately, petrophysical estimation based on tomograms is complicated by limited and variable image resolution, which depends on (1) measurement physics (e.g., electrical conduction or electromagnetic wave propagation), (2) parameterization and regularization, (3) measurement error, and (4) spatial variability. We present a framework to predict how core-scale relations between geophysical properties and hydrologic parameters are altered by the inversion, which produces smoothly varying pixel-scale estimates. We refer to this loss of information as "correlation loss." Our approach upscales the core-scale relation to the pixel scale using the model resolution matrix from the inversion, random field averaging, and spatial statistics of the geophysical property. Synthetic examples evaluate the utility of radar travel time tomography (RTT) and electrical-resistivity tomography (ERT) for estimating water content. This work provides (1) a framework to assess tomograms for geologic parameter estimation and (2) insights into the different patterns of correlation loss for ERT and RTT. Whereas ERT generally performs better near boreholes, RTT performs better in the interwell region. Application of petrophysical models to the tomograms in our examples would yield misleading estimates of water content. Although the examples presented illustrate the problem of correlation loss in the context of near-surface geophysical imaging, our results have clear implications for quantitative analysis of tomograms for diverse geoscience applications. Copyright 2005 by the American Geophysical Union.

Angiogenic Type I Collagen Extracellular Matrix Integrated with Recombinant Bacteriophages Displaying Vascular Endothelial Growth Factors.

PubMed

Yoon, Junghyo; Korkmaz Zirpel, Nuriye; Park, Hyun-Ji; Han, Sewoon; Hwang, Kyung Hoon; Shin, Jisoo; Cho, Seung-Woo; Nam, Chang-Hoon; Chung, Seok

2016-01-21

Here, a growth-factor-integrated natural extracellular matrix of type I collagen is presented that induces angiogenesis. The developed matrix adapts type I collagen nanofibers integrated with synthetic colloidal particles of recombinant bacteriophages that display vascular endothelial growth factor (VEGF). The integration is achieved during or after gelation of the type I collagen and the matrix enables spatial delivery of VEGF into a desired region. Endothelial cells that contact the VEGF are found to invade into the matrix to form tube-like structures both in vitro and in vivo, proving the angiogenic potential of the matrix. © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

0{nu}{beta}{beta}-decay nuclear matrix elements with self-consistent short-range correlations

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

Simkovic, Fedor; Bogoliubov Laboratory of Theoretical Physics, JINR, RU-141 980 Dubna, Moscow region; Department of Nuclear Physics, Comenius University, Mlynska dolina F1, SK-842 15 Bratislava

A self-consistent calculation of nuclear matrix elements of the neutrinoless double-beta decays (0{nu}{beta}{beta}) of {sup 76}Ge, {sup 82}Se, {sup 96}Zr, {sup 100}Mo, {sup 116}Cd, {sup 128}Te, {sup 130}Te, and {sup 136}Xe is presented in the framework of the renormalized quasiparticle random phase approximation (RQRPA) and the standard QRPA. The pairing and residual interactions as well as the two-nucleon short-range correlations are for the first time derived from the same modern realistic nucleon-nucleon potentials, namely, from the charge-dependent Bonn potential (CD-Bonn) and the Argonne V18 potential. In a comparison with the traditional approach of using the Miller-Spencer Jastrow correlations, matrix elementsmore » for the 0{nu}{beta}{beta} decay are obtained that are larger in magnitude. We analyze the differences among various two-nucleon correlations including those of the unitary correlation operator method (UCOM) and quantify the uncertainties in the calculated 0{nu}{beta}{beta}-decay matrix elements.« less

Polarization characterization of an LCTV with a Mueller matrix imaging polarimeter

NASA Astrophysics Data System (ADS)

Pezzaniti, J. Larry; Chipman, Russell A.; Gregory, Don A.

1993-10-01

The polarization properties of a TVT-6000 LCTV have been investigated. Mueller matrices of multiple ray paths through the TVT-6000 were measured for a single (typical) pixel, and through several pixels, using an imaging polarimeter. The TVT-6000 was characterized as a function of applied voltage and angle of incidence. From the Mueller matrices, the spatially dependent retardance, diattenuation, and depolarization are calculated and displayed as topographic maps. In another set of measurements, the LCTV is illuminated with a plane wave, and the spatial distribution of polarization in the Far Field Diffraction Pattern is measured in Mueller matrix form.

Direct-laser metal writing of surface acoustic wave transducers for integrated-optic spatial light modulators in lithium niobate

NASA Astrophysics Data System (ADS)

Datta, Bianca C.; Savidis, Nickolaos; Moebius, Michael; Jolly, Sundeep; Mazur, Eric; Bove, V. Michael

2017-02-01

Recently, the fabrication of high-resolution silver nanostructures using a femtosecond laser-based direct write process in a gelatin matrix was reported. The application of direct metal writing towards feature development has also been explored with direct metal fusion, in which metal is fused onto the surface of the substrate via a femtosecond laser process. In this paper, we present a comparative study of gelatin matrix and metal fusion approaches for directly laser-written fabrication of surface acoustic wave transducers on a lithium niobate substrate for application in integrated optic spatial light modulators.

Distribution of the Determinant of the Sample Correlation Matrix: Monte Carlo Type One Error Rates.

ERIC Educational Resources Information Center

Reddon, John R.; And Others

1985-01-01

Computer sampling from a multivariate normal spherical population was used to evaluate the type one error rates for a test of sphericity based on the distribution of the determinant of the sample correlation matrix. (Author/LMO)

Spatial versus sequential correlations for random access coding

NASA Astrophysics Data System (ADS)

Tavakoli, Armin; Marques, Breno; Pawłowski, Marcin; Bourennane, Mohamed

2016-03-01

Random access codes are important for a wide range of applications in quantum information. However, their implementation with quantum theory can be made in two very different ways: (i) by distributing data with strong spatial correlations violating a Bell inequality or (ii) using quantum communication channels to create stronger-than-classical sequential correlations between state preparation and measurement outcome. Here we study this duality of the quantum realization. We present a family of Bell inequalities tailored to the task at hand and study their quantum violations. Remarkably, we show that the use of spatial and sequential quantum correlations imposes different limitations on the performance of quantum random access codes: Sequential correlations can outperform spatial correlations. We discuss the physics behind the observed discrepancy between spatial and sequential quantum correlations.

Multi beam observations of cosmic radio noise using a VHF radar with beam forming by a Butler matrix

NASA Astrophysics Data System (ADS)

Renkwitz, T.; Singer, W.; Latteck, R.; Rapp, M.

2011-08-01

The Leibniz-Institute of Atmospheric Physics (IAP) in Kühlungsborn started to install a new MST radar on the North-Norwegian island Andøya (69.30° N, 16.04° E) in 2009. The new Middle Atmosphere Alomar Radar System (MAARSY) replaces the previous ALWIN radar which has been successfully operated for more than 10 years. The MAARSY radar provides increased temporal and spatial resolution combined with a flexible sequential point-to-point steering of the radar beam. To increase the spatiotemporal resolution of the observations a 16-port Butler matrix has been built and implemented to the radar. In conjunction with 64 Yagi antennas of the former ALWIN antenna array the Butler matrix simultaneously provides 16 individual beams. The beam forming capability of the Butler matrix arrangement has been verified observing the galactic cosmic radio noise of the supernova remnant Cassiopeia A. Furthermore, this multi beam configuration has been used in passive experiments to estimate the cosmic noise absorption at 53.5 MHz during events of enhanced solar and geomagnetic activity as indicators for enhanced ionization at altitudes below 90 km. These observations are well correlated with simultaneous observations of corresponding beams of the co-located imaging riometer AIRIS (69.14° N, 16.02° E) at 38.2 MHz. In addition, enhanced cosmic noise absorption goes along with enhanced electron densities at altitudes below about 90 km as observed with the co-located Saura MF radar using differential absorption and differential phase measurements.

Matrix-Dependent Regulation of AKT in Hepsin-Overexpressing PC3 Prostate Cancer Cells12

PubMed Central

Wittig-Blaich, Stephanie M; Kacprzyk, Lukasz A; Eismann, Thorsten; Bewerunge-Hudler, Melanie; Kruse, Petra; Winkler, Eva; Strauss, Wolfgang S L; Hibst, Raimund; Steiner, Rudolf; Schrader, Mark; Mertens, Daniel; Sültmann, Holger; Wittig, Rainer

2011-01-01

The serine-protease hepsin is one of the most prominently overexpressed genes in human prostate carcinoma. Forced expression of the enzyme in mice prostates is associated with matrix degradation, invasive growth, and prostate cancer progression. Conversely, hepsin overexpression in metastatic prostate cancer cell lines was reported to induce cell cycle arrest and reduction of invasive growth in vitro. We used a system for doxycycline (dox)-inducible target gene expression in metastasis-derived PC3 cells to analyze the effects of hepsin in a quantitative manner. Loss of viability and adhesion correlated with hepsin expression levels during anchorage-dependent but not anchorage-independent growth. Full expression of hepsin led to cell death and detachment and was specifically associated with reduced phosphorylation of AKT at Ser473, which was restored by growth on matrix derived from RWPE1 normal prostatic epithelial cells. In the chorioallantoic membrane xenograft model, hepsin overexpression in PC3 cells reduced the viability of tumors but did not suppress invasive growth. The data presented here provide evidence that elevated levels of hepsin interfere with cell adhesion and viability in the background of prostate cancer as well as other tissue types, the details of which depend on the microenvironment provided. Our findings suggest that overexpression of the enzyme in prostate carcinogenesis must be spatially and temporally restricted for the efficient development of tumors and metastases. PMID:21750652

Detection of LSB+/-1 steganography based on co-occurrence matrix and bit plane clipping

NASA Astrophysics Data System (ADS)

Abolghasemi, Mojtaba; Aghaeinia, Hassan; Faez, Karim; Mehrabi, Mohammad Ali

2010-01-01

Spatial LSB+/-1 steganography changes smooth characteristics between adjoining pixels of the raw image. We present a novel steganalysis method for LSB+/-1 steganography based on feature vectors derived from the co-occurrence matrix in the spatial domain. We investigate how LSB+/-1 steganography affects the bit planes of an image and show that it changes more least significant bit (LSB) planes of it. The co-occurrence matrix is derived from an image in which some of its most significant bit planes are clipped. By this preprocessing, in addition to reducing the dimensions of the feature vector, the effects of embedding were also preserved. We compute the co-occurrence matrix in different directions and with different dependency and use the elements of the resulting co-occurrence matrix as features. This method is sensitive to the data embedding process. We use a Fisher linear discrimination (FLD) classifier and test our algorithm on different databases and embedding rates. We compare our scheme with the current LSB+/-1 steganalysis methods. It is shown that the proposed scheme outperforms the state-of-the-art methods in detecting the LSB+/-1 steganographic method for grayscale images.

The BMS4 algebra at spatial infinity

NASA Astrophysics Data System (ADS)

Troessaert, Cédric

2018-04-01

We show how a global BMS4 algebra appears as part of the asymptotic symmetry algebra at spatial infinity. Using linearised theory, we then show that this global BMS4 algebra is the one introduced by Strominger as a symmetry of the S-matrix.

Spatially Correlated Gene Expression in Bacterial Groups: The Role of Lineage History, Spatial Gradients, and Cell-Cell Interactions.

PubMed

van Vliet, Simon; Dal Co, Alma; Winkler, Annina R; Spriewald, Stefanie; Stecher, Bärbel; Ackermann, Martin

2018-04-25

Gene expression levels in clonal bacterial groups have been found to be spatially correlated. These correlations can partly be explained by the shared lineage history of nearby cells, although they could also arise from local cell-cell interactions. Here, we present a quantitative framework that allows us to disentangle the contributions of lineage history, long-range spatial gradients, and local cell-cell interactions to spatial correlations in gene expression. We study pathways involved in toxin production, SOS stress response, and metabolism in Escherichia coli microcolonies and find for all pathways that shared lineage history is the main cause of spatial correlations in gene expression levels. However, long-range spatial gradients and local cell-cell interactions also contributed to spatial correlations in SOS response, amino acid biosynthesis, and overall metabolic activity. Together, our data show that the phenotype of a cell is influenced by its lineage history and population context, raising the question of whether bacteria can arrange their activities in space to perform functions they cannot achieve alone. Copyright © 2018 Elsevier Inc. All rights reserved.

Recursive mass matrix factorization and inversion: An operator approach to open- and closed-chain multibody dynamics

NASA Technical Reports Server (NTRS)

Rodriguez, G.; Kreutz, K.

1988-01-01

This report advances a linear operator approach for analyzing the dynamics of systems of joint-connected rigid bodies.It is established that the mass matrix M for such a system can be factored as M=(I+H phi L)D(I+H phi L) sup T. This yields an immediate inversion M sup -1=(I-H psi L) sup T D sup -1 (I-H psi L), where H and phi are given by known link geometric parameters, and L, psi and D are obtained recursively by a spatial discrete-step Kalman filter and by the corresponding Riccati equation associated with this filter. The factors (I+H phi L) and (I-H psi L) are lower triangular matrices which are inverses of each other, and D is a diagonal matrix. This factorization and inversion of the mass matrix leads to recursive algortihms for forward dynamics based on spatially recursive filtering and smoothing. The primary motivation for advancing the operator approach is to provide a better means to formulate, analyze and understand spatial recursions in multibody dynamics. This is achieved because the linear operator notation allows manipulation of the equations of motion using a very high-level analytical framework (a spatial operator algebra) that is easy to understand and use. Detailed lower-level recursive algorithms can readily be obtained for inspection from the expressions involving spatial operators. The report consists of two main sections. In Part 1, the problem of serial chain manipulators is analyzed and solved. Extensions to a closed-chain system formed by multiple manipulators moving a common task object are contained in Part 2. To retain ease of exposition in the report, only these two types of multibody systems are considered. However, the same methods can be easily applied to arbitrary multibody systems formed by a collection of joint-connected regid bodies.

Investigation on Constrained Matrix Factorization for Hyperspectral Image Analysis

DTIC Science & Technology

2005-07-25

analysis. Keywords: matrix factorization; nonnegative matrix factorization; linear mixture model ; unsupervised linear unmixing; hyperspectral imagery...spatial resolution permits different materials present in the area covered by a single pixel. The linear mixture model says that a pixel reflectance in...in r. In the linear mixture model , r is considered as the linear mixture of m1, m2, …, mP as nMαr += (1) where n is included to account for

Network analysis of a financial market based on genuine correlation and threshold method

NASA Astrophysics Data System (ADS)

Namaki, A.; Shirazi, A. H.; Raei, R.; Jafari, G. R.

2011-10-01

A financial market is an example of an adaptive complex network consisting of many interacting units. This network reflects market’s behavior. In this paper, we use Random Matrix Theory (RMT) notion for specifying the largest eigenvector of correlation matrix as the market mode of stock network. For a better risk management, we clean the correlation matrix by removing the market mode from data and then construct this matrix based on the residuals. We show that this technique has an important effect on correlation coefficient distribution by applying it for Dow Jones Industrial Average (DJIA). To study the topological structure of a network we apply the removing market mode technique and the threshold method to Tehran Stock Exchange (TSE) as an example. We show that this network follows a power-law model in certain intervals. We also show the behavior of clustering coefficients and component numbers of this network for different thresholds. These outputs are useful for both theoretical and practical purposes such as asset allocation and risk management.

Pragmatic estimation of a spatio-temporal air quality model with irregular monitoring data

NASA Astrophysics Data System (ADS)

Sampson, Paul D.; Szpiro, Adam A.; Sheppard, Lianne; Lindström, Johan; Kaufman, Joel D.

2011-11-01

Statistical analyses of health effects of air pollution have increasingly used GIS-based covariates for prediction of ambient air quality in "land use" regression models. More recently these spatial regression models have accounted for spatial correlation structure in combining monitoring data with land use covariates. We present a flexible spatio-temporal modeling framework and pragmatic, multi-step estimation procedure that accommodates essentially arbitrary patterns of missing data with respect to an ideally complete space by time matrix of observations on a network of monitoring sites. The methodology incorporates a model for smooth temporal trends with coefficients varying in space according to Partial Least Squares regressions on a large set of geographic covariates and nonstationary modeling of spatio-temporal residuals from these regressions. This work was developed to provide spatial point predictions of PM 2.5 concentrations for the Multi-Ethnic Study of Atherosclerosis and Air Pollution (MESA Air) using irregular monitoring data derived from the AQS regulatory monitoring network and supplemental short-time scale monitoring campaigns conducted to better predict intra-urban variation in air quality. We demonstrate the interpretation and accuracy of this methodology in modeling data from 2000 through 2006 in six U.S. metropolitan areas and establish a basis for likelihood-based estimation.

Subcellular-level resolution MALDI-MS imaging of maize leaf metabolites by MALDI-linear ion trap-Orbitrap mass spectrometer

DOE PAGES

Korte, Andrew R.; Yandeau-Nelson, Marna D.; Nikolau, Basil J.; ...

2015-01-25

A significant limiting factor in achieving high spatial resolution for matrix-assisted laser desorption ionization-mass spectrometry (MALDI-MS) imaging is the size of the laser spot at the sample surface. We present modifications to the beam-delivery optics of a commercial MALDI-linear ion trap-Orbitrap instrument, incorporating an external Nd:YAG laser, beam-shaping optics, and an aspheric focusing lens, to reduce the minimum laser spot size from ~50 μm for the commercial configuration down to ~9 μm for the modified configuration. This improved system was applied for MALDI-MS imaging of cross sections of juvenile maize leaves at 5-μm spatial resolution using an oversampling method. Theremore » are a variety of different metabolites including amino acids, glycerolipids, and defense-related compounds were imaged at a spatial resolution well below the size of a single cell. Such images provide unprecedented insights into the metabolism associated with the different tissue types of the maize leaf, which is known to asymmetrically distribute the reactions of C4 photosynthesis among the mesophyll and bundle sheath cell types. The metabolite ion images correlate with the optical images that reveal the structures of the different tissues, and previously known and newly revealed asymmetric metabolic features are observed.« less

Modal smoothing for analysis of room reflections measured with spherical microphone and loudspeaker arrays.

PubMed

Morgenstern, Hai; Rafaely, Boaz

2018-02-01

Spatial analysis of room acoustics is an ongoing research topic. Microphone arrays have been employed for spatial analyses with an important objective being the estimation of the direction-of-arrival (DOA) of direct sound and early room reflections using room impulse responses (RIRs). An optimal method for DOA estimation is the multiple signal classification algorithm. When RIRs are considered, this method typically fails due to the correlation of room reflections, which leads to rank deficiency of the cross-spectrum matrix. Preprocessing methods for rank restoration, which may involve averaging over frequency, for example, have been proposed exclusively for spherical arrays. However, these methods fail in the case of reflections with equal time delays, which may arise in practice and could be of interest. In this paper, a method is proposed for systems that combine a spherical microphone array and a spherical loudspeaker array, referred to as multiple-input multiple-output systems. This method, referred to as modal smoothing, exploits the additional spatial diversity for rank restoration and succeeds where previous methods fail, as demonstrated in a simulation study. Finally, combining modal smoothing with a preprocessing method is proposed in order to increase the number of DOAs that can be estimated using low-order spherical loudspeaker arrays.

Relationships between species feeding traits and environmental conditions in fish communities: a three-matrix approach.

PubMed

Brind'Amour, Anik; Boisclair, Daniel; Dray, Stéphane; Legendre, Pierre

2011-03-01

Understanding the relationships between species biological traits and the environment is crucial to predicting the effect of habitat perturbations on fish communities. It is also an essential step in the assessment of the functional diversity. Using two complementary three-matrix approaches (fourth-corner and RLQ analyses), we tested the hypothesis that feeding-oriented traits determine the spatial distributions of littoral fish species by assessing the relationship between fish spatial distributions, fish species traits, and habitat characteristics in two Laurentian Shield lakes. Significant associations between the feeding-oriented traits and the environmental characteristics suggested that fish communities in small lakes (displaying low species richness) can be spatially structured. Three groups of traits, mainly categorized by the species spatial and temporal feeding activity, were identified. The water column may be divided in two sections, each of them corresponding to a group of traits related to the vertical distribution of the prey coupled with the position of the mouth. Lake areas of low structural complexity were inhabited by functional assemblages dominated by surface feeders while structurally more complex areas were occupied by mid-water and benthic feeders. A third group referring to the time of feeding activity was observed. Our work could serve as a guideline study to evaluate species traits x environment associations at multiple spatial scales. Our results indicate that three-matrix statistical approaches are powerful tools that can be used to study such relationships. These recent statistical approaches open up new research directions such as the study of spatially based biological functions in lakes. They also provide new analytical tools for determining, for example, the potential size of freshwater protected areas.

A random matrix approach to credit risk.

PubMed

Münnix, Michael C; Schäfer, Rudi; Guhr, Thomas

2014-01-01

We estimate generic statistical properties of a structural credit risk model by considering an ensemble of correlation matrices. This ensemble is set up by Random Matrix Theory. We demonstrate analytically that the presence of correlations severely limits the effect of diversification in a credit portfolio if the correlations are not identically zero. The existence of correlations alters the tails of the loss distribution considerably, even if their average is zero. Under the assumption of randomly fluctuating correlations, a lower bound for the estimation of the loss distribution is provided.

A Random Matrix Approach to Credit Risk

PubMed Central

Guhr, Thomas

2014-01-01

We estimate generic statistical properties of a structural credit risk model by considering an ensemble of correlation matrices. This ensemble is set up by Random Matrix Theory. We demonstrate analytically that the presence of correlations severely limits the effect of diversification in a credit portfolio if the correlations are not identically zero. The existence of correlations alters the tails of the loss distribution considerably, even if their average is zero. Under the assumption of randomly fluctuating correlations, a lower bound for the estimation of the loss distribution is provided. PMID:24853864

LC-MS/MS signal suppression effects in the analysis of pesticides in complex environmental matrices.

PubMed

Choi, B K; Hercules, D M; Gusev, A I

2001-02-01

The application of LC separation and mobile phase additives in addressing LC-MS/MS matrix signal suppression effects for the analysis of pesticides in a complex environmental matrix was investigated. It was shown that signal suppression is most significant for analytes eluting early in the LC-MS analysis. Introduction of different buffers (e.g. ammonium formate, ammonium hydroxide, formic acid) into the LC mobile phase was effective in improving signal correlation between the matrix and standard samples. The signal improvement is dependent on buffer concentration as well as LC separation of the matrix components. The application of LC separation alone was not effective in addressing suppression effects when characterizing complex matrix samples. Overloading of the LC column by matrix components was found to significantly contribute to analyte-matrix co-elution and suppression of signal. This signal suppression effect can be efficiently compensated by 2D LC (LC-LC) separation techniques. The effectiveness of buffers and LC separation in improving signal correlation between standard and matrix samples is discussed.

What Do They Have in Common? Drivers of Streamflow Spatial Correlation and Prediction of Flow Regimes in Ungauged Locations

NASA Astrophysics Data System (ADS)

Betterle, A.; Radny, D.; Schirmer, M.; Botter, G.

2017-12-01

The spatial correlation of daily streamflows represents a statistical index encapsulating the similarity between hydrographs at two arbitrary catchment outlets. In this work, a process-based analytical framework is utilized to investigate the hydrological drivers of streamflow spatial correlation through an extensive application to 78 pairs of stream gauges belonging to 13 unregulated catchments in the eastern United States. The analysis provides insight on how the observed heterogeneity of the physical processes that control flow dynamics ultimately affect streamflow correlation and spatial patterns of flow regimes. Despite the variability of recession properties across the study catchments, the impact of heterogeneous drainage rates on the streamflow spatial correlation is overwhelmed by the spatial variability of frequency and intensity of effective rainfall events. Overall, model performances are satisfactory, with root mean square errors between modeled and observed streamflow spatial correlation below 10% in most cases. We also propose a method for estimating streamflow correlation in the absence of discharge data, which proves useful to predict streamflow regimes in ungauged areas. The method consists in setting a minimum threshold on the modeled flow correlation to individuate hydrologically similar sites. Catchment outlets that are most correlated (ρ>0.9) are found to be characterized by analogous streamflow distributions across a broad range of flow regimes.

Integrative Spatial Data Analytics for Public Health Studies of New York State

PubMed Central

Chen, Xin; Wang, Fusheng

2016-01-01

Increased accessibility of health data made available by the government provides unique opportunity for spatial analytics with much higher resolution to discover patterns of diseases, and their correlation with spatial impact indicators. This paper demonstrated our vision of integrative spatial analytics for public health by linking the New York Cancer Mapping Dataset with datasets containing potential spatial impact indicators. We performed spatial based discovery of disease patterns and variations across New York State, and identify potential correlations between diseases and demographic, socio-economic and environmental indicators. Our methods were validated by three correlation studies: the correlation between stomach cancer and Asian race, the correlation between breast cancer and high education population, and the correlation between lung cancer and air toxics. Our work will allow public health researchers, government officials or other practitioners to adequately identify, analyze, and monitor health problems at the community or neighborhood level for New York State. PMID:28269834

Downscaling RCP8.5 daily temperatures and precipitation in Ontario using localized ensemble optimal interpolation (EnOI) and bias correction

NASA Astrophysics Data System (ADS)

Deng, Ziwang; Liu, Jinliang; Qiu, Xin; Zhou, Xiaolan; Zhu, Huaiping

2017-10-01

A novel method for daily temperature and precipitation downscaling is proposed in this study which combines the Ensemble Optimal Interpolation (EnOI) and bias correction techniques. For downscaling temperature, the day to day seasonal cycle of high resolution temperature of the NCEP climate forecast system reanalysis (CFSR) is used as background state. An enlarged ensemble of daily temperature anomaly relative to this seasonal cycle and information from global climate models (GCMs) are used to construct a gain matrix for each calendar day. Consequently, the relationship between large and local-scale processes represented by the gain matrix will change accordingly. The gain matrix contains information of realistic spatial correlation of temperature between different CFSR grid points, between CFSR grid points and GCM grid points, and between different GCM grid points. Therefore, this downscaling method keeps spatial consistency and reflects the interaction between local geographic and atmospheric conditions. Maximum and minimum temperatures are downscaled using the same method. For precipitation, because of the non-Gaussianity issue, a logarithmic transformation is used to daily total precipitation prior to conducting downscaling. Cross validation and independent data validation are used to evaluate this algorithm. Finally, data from a 29-member ensemble of phase 5 of the Coupled Model Intercomparison Project (CMIP5) GCMs are downscaled to CFSR grid points in Ontario for the period from 1981 to 2100. The results show that this method is capable of generating high resolution details without changing large scale characteristics. It results in much lower absolute errors in local scale details at most grid points than simple spatial downscaling methods. Biases in the downscaled data inherited from GCMs are corrected with a linear method for temperatures and distribution mapping for precipitation. The downscaled ensemble projects significant warming with amplitudes of 3.9 and 6.5 °C for 2050s and 2080s relative to 1990s in Ontario, respectively; Cooling degree days and hot days will significantly increase over southern Ontario and heating degree days and cold days will significantly decrease in northern Ontario. Annual total precipitation will increase over Ontario and heavy precipitation events will increase as well. These results are consistent with conclusions in many other studies in the literature.

Nonmonotonic spatial structure of interneuronal correlations in prefrontal microcircuits

PubMed Central

Safavi, Shervin; Dwarakanath, Abhilash; Kapoor, Vishal; Werner, Joachim; Hatsopoulos, Nicholas G.; Logothetis, Nikos K.; Panagiotaropoulos, Theofanis I.

2018-01-01

Correlated fluctuations of single neuron discharges, on a mesoscopic scale, decrease as a function of lateral distance in early sensory cortices, reflecting a rapid spatial decay of lateral connection probability and excitation. However, spatial periodicities in horizontal connectivity and associational input as well as an enhanced probability of lateral excitatory connections in the association cortex could theoretically result in nonmonotonic correlation structures. Here, we show such a spatially nonmonotonic correlation structure, characterized by significantly positive long-range correlations, in the inferior convexity of the macaque prefrontal cortex. This functional connectivity kernel was more pronounced during wakefulness than anesthesia and could be largely attributed to the spatial pattern of correlated variability between functionally similar neurons during structured visual stimulation. These results suggest that the spatial decay of lateral functional connectivity is not a common organizational principle of neocortical microcircuits. A nonmonotonic correlation structure could reflect a critical topological feature of prefrontal microcircuits, facilitating their role in integrative processes. PMID:29588415

Separable decompositions of bipartite mixed states

NASA Astrophysics Data System (ADS)

Li, Jun-Li; Qiao, Cong-Feng

2018-04-01

We present a practical scheme for the decomposition of a bipartite mixed state into a sum of direct products of local density matrices, using the technique developed in Li and Qiao (Sci. Rep. 8:1442, 2018). In the scheme, the correlation matrix which characterizes the bipartite entanglement is first decomposed into two matrices composed of the Bloch vectors of local states. Then, we show that the symmetries of Bloch vectors are consistent with that of the correlation matrix, and the magnitudes of the local Bloch vectors are lower bounded by the correlation matrix. Concrete examples for the separable decompositions of bipartite mixed states are presented for illustration.

Thaw depth spatial and temporal variability at the Limnopolar Lake CALM-S site, Byers Peninsula, Livingston Island, Antarctica.

PubMed

de Pablo, M A; Ramos, M; Molina, A; Prieto, M

2018-02-15

A new Circumpolar Active Layer Monitoring (CALM) site was established in 2009 at the Limnopolar Lake watershed in Byers Peninsula, Livingston Island, Antarctica, to provide a node in the western Antarctic Peninsula, one of the regions that recorded the highest air temperature increase in the planet during the last decades. The first detailed analysis of the temporal and spatial evolution of the thaw depth at the Limnopolar Lake CALM-S site is presented here, after eight years of monitoring. The average values range between 48 and 29cm, decreasing at a ratio of 16cm/decade. The annual thaw depth observations in the 100×100 m CALM grid are variable (Variability Index of 34 to 51%), although both the Variance Coefficient and the Climate Matrix Analysis Residual point to the internal consistency of the data. Those differences could be explained then by the terrain complexity and node-specific variability due to the ground properties. The interannual variability was about 60% during 2009-2012, increasing to 124% due to the presence of snow in 2013, 2015 and 2016. The snow has been proposed here as one of the most important factors controlling the spatial variability of ground thaw depth, since its values correlate with the snow thickness but also with the ground surface temperature and unconfined compression resistance, as measured in 2010. The topography explains the thaw depth spatial distribution pattern, being related to snowmelt water and its accumulation in low-elevation areas (downslope-flow). Patterned grounds and other surface features correlate well with high thaw depth patterns as well. The edaphic factor (E=0.05842m 2 /°C·day; R 2 =0.63) is in agreement with other permafrost environments, since frozen index (F>0.67) and MAAT (<-2°C) denote a continuous permafrost existence in the area. All these characteristics provided the basis for further comparative analyses between others nearby CALM sites. Copyright © 2017 Elsevier B.V. All rights reserved.

Blind identification of full-field vibration modes from video measurements with phase-based video motion magnification

NASA Astrophysics Data System (ADS)

Yang, Yongchao; Dorn, Charles; Mancini, Tyler; Talken, Zachary; Kenyon, Garrett; Farrar, Charles; Mascareñas, David

2017-02-01

Experimental or operational modal analysis traditionally requires physically-attached wired or wireless sensors for vibration measurement of structures. This instrumentation can result in mass-loading on lightweight structures, and is costly and time-consuming to install and maintain on large civil structures, especially for long-term applications (e.g., structural health monitoring) that require significant maintenance for cabling (wired sensors) or periodic replacement of the energy supply (wireless sensors). Moreover, these sensors are typically placed at a limited number of discrete locations, providing low spatial sensing resolution that is hardly sufficient for modal-based damage localization, or model correlation and updating for larger-scale structures. Non-contact measurement methods such as scanning laser vibrometers provide high-resolution sensing capacity without the mass-loading effect; however, they make sequential measurements that require considerable acquisition time. As an alternative non-contact method, digital video cameras are relatively low-cost, agile, and provide high spatial resolution, simultaneous, measurements. Combined with vision based algorithms (e.g., image correlation, optical flow), video camera based measurements have been successfully used for vibration measurements and subsequent modal analysis, based on techniques such as the digital image correlation (DIC) and the point-tracking. However, they typically require speckle pattern or high-contrast markers to be placed on the surface of structures, which poses challenges when the measurement area is large or inaccessible. This work explores advanced computer vision and video processing algorithms to develop a novel video measurement and vision-based operational (output-only) modal analysis method that alleviate the need of structural surface preparation associated with existing vision-based methods and can be implemented in a relatively efficient and autonomous manner with little user supervision and calibration. First a multi-scale image processing method is applied on the frames of the video of a vibrating structure to extract the local pixel phases that encode local structural vibration, establishing a full-field spatiotemporal motion matrix. Then a high-spatial dimensional, yet low-modal-dimensional, over-complete model is used to represent the extracted full-field motion matrix using modal superposition, which is physically connected and manipulated by a family of unsupervised learning models and techniques, respectively. Thus, the proposed method is able to blindly extract modal frequencies, damping ratios, and full-field (as many points as the pixel number of the video frame) mode shapes from line of sight video measurements of the structure. The method is validated by laboratory experiments on a bench-scale building structure and a cantilever beam. Its ability for output (video measurements)-only identification and visualization of the weakly-excited mode is demonstrated and several issues with its implementation are discussed.

Dynamic mode decomposition for plasma diagnostics and validation.

PubMed

Taylor, Roy; Kutz, J Nathan; Morgan, Kyle; Nelson, Brian A

2018-05-01

We demonstrate the application of the Dynamic Mode Decomposition (DMD) for the diagnostic analysis of the nonlinear dynamics of a magnetized plasma in resistive magnetohydrodynamics. The DMD method is an ideal spatio-temporal matrix decomposition that correlates spatial features of computational or experimental data while simultaneously associating the spatial activity with periodic temporal behavior. DMD can produce low-rank, reduced order surrogate models that can be used to reconstruct the state of the system with high fidelity. This allows for a reduction in the computational cost and, at the same time, accurate approximations of the problem, even if the data are sparsely sampled. We demonstrate the use of the method on both numerical and experimental data, showing that it is a successful mathematical architecture for characterizing the helicity injected torus with steady inductive (HIT-SI) magnetohydrodynamics. Importantly, the DMD produces interpretable, dominant mode structures, including a stationary mode consistent with our understanding of a HIT-SI spheromak accompanied by a pair of injector-driven modes. In combination, the 3-mode DMD model produces excellent dynamic reconstructions across the domain of analyzed data.

Dynamic mode decomposition for plasma diagnostics and validation

NASA Astrophysics Data System (ADS)

Taylor, Roy; Kutz, J. Nathan; Morgan, Kyle; Nelson, Brian A.

2018-05-01

We demonstrate the application of the Dynamic Mode Decomposition (DMD) for the diagnostic analysis of the nonlinear dynamics of a magnetized plasma in resistive magnetohydrodynamics. The DMD method is an ideal spatio-temporal matrix decomposition that correlates spatial features of computational or experimental data while simultaneously associating the spatial activity with periodic temporal behavior. DMD can produce low-rank, reduced order surrogate models that can be used to reconstruct the state of the system with high fidelity. This allows for a reduction in the computational cost and, at the same time, accurate approximations of the problem, even if the data are sparsely sampled. We demonstrate the use of the method on both numerical and experimental data, showing that it is a successful mathematical architecture for characterizing the helicity injected torus with steady inductive (HIT-SI) magnetohydrodynamics. Importantly, the DMD produces interpretable, dominant mode structures, including a stationary mode consistent with our understanding of a HIT-SI spheromak accompanied by a pair of injector-driven modes. In combination, the 3-mode DMD model produces excellent dynamic reconstructions across the domain of analyzed data.

Augmented Reality for the Assessment of Children's Spatial Memory in Real Settings

PubMed Central

Juan, M.-Carmen; Mendez-Lopez, Magdalena; Perez-Hernandez, Elena; Albiol-Perez, Sergio

2014-01-01

Short-term memory can be defined as the capacity for holding a small amount of information in mind in an active state for a short period of time. Although some instruments have been developed to study spatial short-term memory in real environments, there are no instruments that are specifically designed to assess visuospatial short-term memory in an attractive way to children. In this paper, we present the ARSM (Augmented Reality Spatial Memory) task, the first Augmented Reality task that involves a user's movement to assess spatial short-term memory in healthy children. The experimental procedure of the ARSM task was designed to assess the children's skill to retain visuospatial information. They were individually asked to remember the real place where augmented reality objects were located. The children (N = 76) were divided into two groups: preschool (5–6 year olds) and primary school (7–8 year olds). We found a significant improvement in ARSM task performance in the older group. The correlations between scores for the ARSM task and traditional procedures were significant. These traditional procedures were the Dot Matrix subtest for the assessment of visuospatial short-term memory of the computerized AWMA-2 battery and a parent's questionnaire about a child's everyday spatial memory. Hence, we suggest that the ARSM task has high verisimilitude with spatial short-term memory skills in real life. In addition, we evaluated the ARSM task's usability and perceived satisfaction. The study revealed that the younger children were more satisfied with the ARSM task. This novel instrument could be useful in detecting visuospatial short-term difficulties that affect specific developmental navigational disorders and/or school academic achievement. PMID:25438146

Augmented reality for the assessment of children's spatial memory in real settings.

PubMed

Juan, M-Carmen; Mendez-Lopez, Magdalena; Perez-Hernandez, Elena; Albiol-Perez, Sergio

2014-01-01

Short-term memory can be defined as the capacity for holding a small amount of information in mind in an active state for a short period of time. Although some instruments have been developed to study spatial short-term memory in real environments, there are no instruments that are specifically designed to assess visuospatial short-term memory in an attractive way to children. In this paper, we present the ARSM (Augmented Reality Spatial Memory) task, the first Augmented Reality task that involves a user's movement to assess spatial short-term memory in healthy children. The experimental procedure of the ARSM task was designed to assess the children's skill to retain visuospatial information. They were individually asked to remember the real place where augmented reality objects were located. The children (N = 76) were divided into two groups: preschool (5-6 year olds) and primary school (7-8 year olds). We found a significant improvement in ARSM task performance in the older group. The correlations between scores for the ARSM task and traditional procedures were significant. These traditional procedures were the Dot Matrix subtest for the assessment of visuospatial short-term memory of the computerized AWMA-2 battery and a parent's questionnaire about a child's everyday spatial memory. Hence, we suggest that the ARSM task has high verisimilitude with spatial short-term memory skills in real life. In addition, we evaluated the ARSM task's usability and perceived satisfaction. The study revealed that the younger children were more satisfied with the ARSM task. This novel instrument could be useful in detecting visuospatial short-term difficulties that affect specific developmental navigational disorders and/or school academic achievement.

Testing Pattern Hypotheses for Correlation Matrices

ERIC Educational Resources Information Center

McDonald, Roderick P.

1975-01-01

The treatment of covariance matrices given by McDonald (1974) can be readily modified to cover hypotheses prescribing zeros and equalities in the correlation matrix rather than the covariance matrix, still with the convenience of the closed-form Least Squares solution and the classical Newton method. (Author/RC)

Structure-function correlations in glaucoma using matrix and standard automated perimetry versus time-domain and spectral-domain OCT devices.

PubMed

Pinto, Luciano Moreira; Costa, Elaine Fiod; Melo, Luiz Alberto S; Gross, Paula Blasco; Sato, Eduardo Toshio; Almeida, Andrea Pereira; Maia, Andre; Paranhos, Augusto

2014-04-10

We examined the structure-function relationship between two perimetric tests, the frequency doubling technology (FDT) matrix and standard automated perimetry (SAP), and two optical coherence tomography (OCT) devices (time-domain and spectral-domain). This cross-sectional study included 97 eyes from 29 healthy individuals, and 68 individuals with early, moderate, or advanced primary open-angle glaucoma. The correlations between overall and sectorial parameters of retinal nerve fiber layer thickness (RNFL) measured with Stratus and Spectralis OCT, and the visual field sensitivity obtained with FDT matrix and SAP were assessed. The relationship also was evaluated using a previously described linear model. The correlation coefficients for the threshold sensitivity measured with SAP and Stratus OCT ranged from 0.44 to 0.79, and those for Spectralis OCT ranged from 0.30 to 0.75. Regarding FDT matrix, the correlation ranged from 0.40 to 0.79 with Stratus OCT and from 0.39 to 0.79 with Spectralis OCT. Stronger correlations were found in the overall measurements and the arcuate sectors for both visual fields and OCT devices. A linear relationship was observed between FDT matrix sensitivity and the OCT devices. The previously described linear model fit the data from SAP and the OCT devices well, particularly in the inferotemporal sector. The FDT matrix and SAP visual sensitivities were related strongly to the RNFL thickness measured with the Stratus and Spectralis OCT devices, particularly in the overall and arcuate sectors. Copyright 2014 The Association for Research in Vision and Ophthalmology, Inc.

In situ analysis of the organic framework in the prismatic layer of mollusc shell.

PubMed

Tong, Hua; Hu, Jiming; Ma, Wentao; Zhong, Guirong; Yao, Songnian; Cao, Nianxing

2002-06-01

A novel in situ analytic approach was constructed by means of ion sputtering, decalcification and deprotein techniques combining with scanning electron microscopy (SEM) and transmission electron microscope (TEM) ultrastructural analysis. The method was employed to determine the spatial distribution of the organic framework outside and the inner crystal and organic/inorganic interface spatial geometrical relationship in the prismatic layer of cristaris plicate (leach). The results show that there is a substructure of organic matrix in the intracrystalline region. The prismatic layer forms according to strict hierarchical configuration of regular pattern. Each unit of organic template of prismatic layer can uniquely determine the column crystal growth direction, spatial orientation and size. Cavity templates are responsible for supporting. limiting size and shape and determining the crystal growth spatial orientation, while the intracrystal organic matrix is responsible for providing nucleation point and inducing the nucleation process of calcite. The stereo hierarchical fabrication of prismatic layer was elucidated for the first time.

Localization of ergot alkaloids in sclerotia of Claviceps purpurea by matrix-assisted laser desorption/ionization mass spectrometry imaging.

PubMed

Dopstadt, Julian; Vens-Cappell, Simeon; Neubauer, Lisa; Tudzynski, Paul; Cramer, Benedikt; Dreisewerd, Klaus; Humpf, Hans-Ulrich

2017-02-01

The fungus Claviceps purpurea produces highly toxic ergot alkaloids and accumulates these in the hardened bodies of fungal mycelium. These so-called sclerotia, or ergot bodies, replace the crop seed of infected plants, which can include numerous important food- and feedstuff such as rye and wheat. While several studies have explored details of the infection process and development of ergot bodies, little information is available on the spatial distribution of the mycotoxins in the sclerotia. Here we used matrix-assisted laser desorption/ionization mass spectrometry imaging (MALDI-MSI) at a lateral resolution of 35 μm to visualize the distribution of two representative alkaloids, ergocristine and ergometrine, produced by Ecc93 and Gal 310 variants of C. purpurea, respectively, after infection of rye. To improve cryosectioning of this fragile biological material tissue with complex texture, we developed a practical embedding protocol based on cellulose polymers. The MALDI-MS images recorded from the so produced intact tissues sections revealed that ergometrine exhibited a relatively homogeneous distribution throughout the ergot body, whereas ergocristine was found to be enriched in the proximal region. This finding can be correlated to the morphological development of sclerotia as ergot alkaloids are only produced in the sphacelial stage. The ability to localize toxins and other secondary metabolites in intact sections of crop-infecting fungi with high lateral resolution renders MALDI-MSI a powerful tool for investigating biosynthetic pathways and for obtaining a deeper understanding of the parasite-host interaction. Graphical abstract Workflow for identification and spatial localization of ergot alkaloids in infected rye grains.

Calibration of the ROSAT HRI Spectral Response

NASA Technical Reports Server (NTRS)

Prestwich, Andrea

1998-01-01

The ROSAT High Resolution Imager has a limited (2-band) spectral response. This spectral capability can give X-ray hardness ratios on spatial scales of 5 arcseconds. The spectral response of the center of the detector was calibrated before the launch of ROSAT, but the gain decreases-with time and also is a function of position on the detector. To complicate matters further, the satellite is "wobbled", possibly moving a source across several spatial gain states. These difficulties have prevented the spectral response of the ROSAT HRI from being used for scientific measurements. We have used Bright Earth data and in-flight calibration sources to map the spatial and temporal gain changes, and written software which will allow ROSAT users to generate a calibrated XSPEC response matrix and hence determine a calibrated hardness ratio. In this report, we describe the calibration procedure and show how to obtain a response matrix. In Section 2 we give an overview of the calibration procedure, in Section 3 we give a summary of HRI spatial and temporal gain variations. Section 4 describes the routines used to determine the gain distribution of a source. In Sections 5 and 6, we describe in detail how the Bright Earth database and calibration sources are used to derive a corrected response matrix for a given observation. Finally, Section 7 describes how to use the software.

Calibration of the ROSAT HRI Spectral Response

NASA Technical Reports Server (NTRS)

Prestwich, Andrea H.; Silverman, John; McDowell, Jonathan; Callanan, Paul; Snowden, Steve

2000-01-01

The ROSAT High Resolution Imager has a limited (2-band) spectral response. This spectral capability can give X-ray hardness ratios on spatial scales of 5 arcseconds. The spectral response of the center of the detector was calibrated before the launch of ROSAT, but the gain decreases with time and also is a function of position on the detector. To complicate matters further, the satellite is 'wobbled', possibly moving a source across several spatial gain states. These difficulties have prevented the spectral response of the ROSAT High Resolution Imager (HRI) from being used for scientific measurements. We have used Bright Earth data and in-flight calibration sources to map the spatial and temporal gain changes, and written software which will allow ROSAT users to generate a calibrated XSPEC (an x ray spectral fitting package) response matrix and hence determine a calibrated hardness ratio. In this report, we describe the calibration procedure and show how to obtain a response matrix. In Section 2 we give an overview of the calibration procedure, in Section 3 we give a summary of HRI spatial and temporal gain variations. Section 4 describes the routines used to determine the gain distribution of a source. In Sections 5 and 6, we describe in detail how, the Bright Earth database and calibration sources are used to derive a corrected response matrix for a given observation. Finally, Section 7 describes how to use the software.

Principal regression analysis and the index leverage effect

NASA Astrophysics Data System (ADS)

Reigneron, Pierre-Alain; Allez, Romain; Bouchaud, Jean-Philippe

2011-09-01

We revisit the index leverage effect, that can be decomposed into a volatility effect and a correlation effect. We investigate the latter using a matrix regression analysis, that we call ‘Principal Regression Analysis' (PRA) and for which we provide some analytical (using Random Matrix Theory) and numerical benchmarks. We find that downward index trends increase the average correlation between stocks (as measured by the most negative eigenvalue of the conditional correlation matrix), and makes the market mode more uniform. Upward trends, on the other hand, also increase the average correlation between stocks but rotates the corresponding market mode away from uniformity. There are two time scales associated to these effects, a short one on the order of a month (20 trading days), and a longer time scale on the order of a year. We also find indications of a leverage effect for sectorial correlations as well, which reveals itself in the second and third mode of the PRA.

Assessment of imputation methods using varying ecological information to fill the gaps in a tree functional trait database

NASA Astrophysics Data System (ADS)

Poyatos, Rafael; Sus, Oliver; Vilà-Cabrera, Albert; Vayreda, Jordi; Badiella, Llorenç; Mencuccini, Maurizio; Martínez-Vilalta, Jordi

2016-04-01

Plant functional traits are increasingly being used in ecosystem ecology thanks to the growing availability of large ecological databases. However, these databases usually contain a large fraction of missing data because measuring plant functional traits systematically is labour-intensive and because most databases are compilations of datasets with different sampling designs. As a result, within a given database, there is an inevitable variability in the number of traits available for each data entry and/or the species coverage in a given geographical area. The presence of missing data may severely bias trait-based analyses, such as the quantification of trait covariation or trait-environment relationships and may hamper efforts towards trait-based modelling of ecosystem biogeochemical cycles. Several data imputation (i.e. gap-filling) methods have been recently tested on compiled functional trait databases, but the performance of imputation methods applied to a functional trait database with a regular spatial sampling has not been thoroughly studied. Here, we assess the effects of data imputation on five tree functional traits (leaf biomass to sapwood area ratio, foliar nitrogen, maximum height, specific leaf area and wood density) in the Ecological and Forest Inventory of Catalonia, an extensive spatial database (covering 31900 km2). We tested the performance of species mean imputation, single imputation by the k-nearest neighbors algorithm (kNN) and a multiple imputation method, Multivariate Imputation with Chained Equations (MICE) at different levels of missing data (10%, 30%, 50%, and 80%). We also assessed the changes in imputation performance when additional predictors (species identity, climate, forest structure, spatial structure) were added in kNN and MICE imputations. We evaluated the imputed datasets using a battery of indexes describing departure from the complete dataset in trait distribution, in the mean prediction error, in the correlation matrix and in selected bivariate trait relationships. MICE yielded imputations which better preserved the variability and covariance structure of the data and provided an estimate of between-imputation uncertainty. We found that adding species identity as a predictor in MICE and kNN improved imputation for all traits, but adding climate did not lead to any appreciable improvement. However, forest structure and spatial structure did reduce imputation errors in maximum height and in leaf biomass to sapwood area ratios, respectively. Although species mean imputations showed the lowest error for 3 out the 5 studied traits, dataset-averaged errors were lowest for MICE imputations with all additional predictors, when missing data levels were 50% or lower. Species mean imputations always resulted in larger errors in the correlation matrix and appreciably altered the studied bivariate trait relationships. In conclusion, MICE imputations using species identity, climate, forest structure and spatial structure as predictors emerged as the most suitable method of the ones tested here, but it was also evident that imputation performance deteriorates at high levels of missing data (80%).

Matrix assisted laser desorption/ionization-mass spectrometry imaging (MALDI-MSI) for direct visualization of plant metabolites in situ

DOE PAGES

Sturtevant, Drew; Lee, Young -Jin; Chapman, Kent D.

2015-11-22

Direct visualization of plant tissues by matrix assisted laser desorption ionization-mass spectrometry imaging (MALDI-MSI) has revealed key insights into the localization of metabolites in situ. Recent efforts have determined the spatial distribution of primary and secondary metabolites in plant tissues and cells. Strategies have been applied in many areas of metabolism including isotope flux analyses, plant interactions, and transcriptional regulation of metabolite accumulation. Technological advances have pushed achievable spatial resolution to subcellular levels and increased instrument sensitivity by several orders of magnitude. Furthermore, it is anticipated that MALDI-MSI and other MSI approaches will bring a new level of understanding tomore » metabolomics as scientists will be encouraged to consider spatial heterogeneity of metabolites in descriptions of metabolic pathway regulation.« less

Matrix assisted laser desorption/ionization-mass spectrometry imaging (MALDI-MSI) for direct visualization of plant metabolites in situ

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

Sturtevant, Drew; Lee, Young -Jin; Chapman, Kent D.

Direct visualization of plant tissues by matrix assisted laser desorption ionization-mass spectrometry imaging (MALDI-MSI) has revealed key insights into the localization of metabolites in situ. Recent efforts have determined the spatial distribution of primary and secondary metabolites in plant tissues and cells. Strategies have been applied in many areas of metabolism including isotope flux analyses, plant interactions, and transcriptional regulation of metabolite accumulation. Technological advances have pushed achievable spatial resolution to subcellular levels and increased instrument sensitivity by several orders of magnitude. Furthermore, it is anticipated that MALDI-MSI and other MSI approaches will bring a new level of understanding tomore » metabolomics as scientists will be encouraged to consider spatial heterogeneity of metabolites in descriptions of metabolic pathway regulation.« less

Functional overestimation due to spatial smoothing of fMRI data.

PubMed

Liu, Peng; Calhoun, Vince; Chen, Zikuan

2017-11-01

Pearson correlation (simply correlation) is a basic technique for neuroimage function analysis. It has been observed that the spatial smoothing may cause functional overestimation, which however remains a lack of complete understanding. Herein, we present a theoretical explanation from the perspective of correlation scale invariance. For a task-evoked spatiotemporal functional dataset, we can extract the functional spatial map by calculating the temporal correlations (tcorr) of voxel timecourses against the task timecourse. From the relationship between image noise level (changed through spatial smoothing) and the tcorr map calculation, we show that the spatial smoothing causes a noise reduction, which in turn smooths the tcorr map and leads to a spatial expansion on neuroactivity blob estimation. Through numerical simulations and subject experiments, we show that the spatial smoothing of fMRI data may overestimate activation spots in the correlation functional map. Our results suggest a small spatial smoothing (with a smoothing kernel with a full width at half maximum (FWHM) of no more than two voxels) on fMRI data processing for correlation-based functional mapping COMPARISON WITH EXISTING METHODS: In extreme noiselessness, the correlation of scale-invariance property defines a meaningless binary tcorr map. In reality, a functional activity blob in a tcorr map is shaped due to the spoilage of image noise on correlative responses. We may reduce data noise level by smoothing processing, which poses a smoothing effect on correlation. This logic allows us to understand the noise dependence and the smoothing effect of correlation-based fMRI data analysis. Copyright © 2017 Elsevier B.V. All rights reserved.

Density matrix renormalization group with efficient dynamical electron correlation through range separation

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

Hedegård, Erik Donovan, E-mail: erik.hedegard@phys.chem.ethz.ch; Knecht, Stefan; Reiher, Markus, E-mail: markus.reiher@phys.chem.ethz.ch

2015-06-14

We present a new hybrid multiconfigurational method based on the concept of range-separation that combines the density matrix renormalization group approach with density functional theory. This new method is designed for the simultaneous description of dynamical and static electron-correlation effects in multiconfigurational electronic structure problems.

Determining the Number of Components from the Matrix of Partial Correlations

ERIC Educational Resources Information Center

Velicer, Wayne F.

1976-01-01

A method is presented for determining the number of components to retain in a principal components or image components analysis which utilizes a matrix of partial correlations. Advantages and uses of the method are discussed and a comparison of the proposed method with existing methods is presented. (JKS)

Asymptotic coincidence of the statistics for degenerate and non-degenerate correlated real Wishart ensembles

NASA Astrophysics Data System (ADS)

Wirtz, Tim; Kieburg, Mario; Guhr, Thomas

2017-06-01

The correlated Wishart model provides the standard benchmark when analyzing time series of any kind. Unfortunately, the real case, which is the most relevant one in applications, poses serious challenges for analytical calculations. Often these challenges are due to square root singularities which cannot be handled using common random matrix techniques. We present a new way to tackle this issue. Using supersymmetry, we carry out an anlaytical study which we support by numerical simulations. For large but finite matrix dimensions, we show that statistical properties of the fully correlated real Wishart model generically approach those of a correlated real Wishart model with doubled matrix dimensions and doubly degenerate empirical eigenvalues. This holds for the local and global spectral statistics. With Monte Carlo simulations we show that this is even approximately true for small matrix dimensions. We explicitly investigate the k-point correlation function as well as the distribution of the largest eigenvalue for which we find a surprisingly compact formula in the doubly degenerate case. Moreover we show that on the local scale the k-point correlation function exhibits the sine and the Airy kernel in the bulk and at the soft edges, respectively. We also address the positions and the fluctuations of the possible outliers in the data.

Anatomical relationships between serotonin 5-HT2A and dopamine D2 receptors in living human brain.

PubMed

Ishii, Tatsuya; Kimura, Yasuyuki; Ichise, Masanori; Takahata, Keisuke; Kitamura, Soichiro; Moriguchi, Sho; Kubota, Manabu; Zhang, Ming-Rong; Yamada, Makiko; Higuchi, Makoto; Okubo, Yoshinori; Suhara, Tetsuya

2017-01-01

Seven healthy volunteers underwent PET scans with [18F]altanserin and [11C]FLB 457 for 5-HT2A and D2 receptors, respectively. As a measure of receptor density, a binding potential (BP) was calculated from PET data for 76 cerebral cortical regions. A correlation matrix was calculated between the binding potentials of [18F]altanserin and [11C]FLB 457 for those regions. The regional relationships were investigated using a bicluster analysis of the correlation matrix with an iterative signature algorithm. We identified two clusters of regions. The first cluster identified a distinct profile of correlation coefficients between 5-HT2A and D2 receptors, with the former in regions related to sensorimotor integration (supplementary motor area, superior parietal gyrus, and paracentral lobule) and the latter in most cortical regions. The second cluster identified another distinct profile of correlation coefficients between 5-HT2A receptors in the bilateral hippocampi and D2 receptors in most cortical regions. The observation of two distinct clusters in the correlation matrix suggests regional interactions between 5-HT2A and D2 receptors in sensorimotor integration and hippocampal function. A bicluster analysis of the correlation matrix of these neuroreceptors may be beneficial in understanding molecular networks in the human brain.

Data mining graphene: Correlative analysis of structure and electronic degrees of freedom in graphenic monolayers with defects

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

Ziatdinov, Maxim A.; Fujii, Shintaro; Kiguchi, Manabu

The link between changes in the material crystal structure and its mechanical, electronic, magnetic, and optical functionalities known as the structure-property relationship is the cornerstone of the contemporary materials science research. The recent advances in scanning transmission electron and scanning probe microscopies (STEM and SPM) have opened an unprecedented path towards examining the materials structure property relationships on the single-impurity and atomic-configuration levels. Lacking, however, are the statistics-based approaches for cross-correlation of structure and property variables obtained in different information channels of the STEM and SPM experiments. Here we have designed an approach based on a combination of sliding windowmore » Fast Fourier Transform, Pearson correlation matrix, linear and kernel canonical correlation, to study a relationship between lattice distortions and electron scattering from the SPM data on graphene with defects. Our analysis revealed that the strength of coupling to strain is altered between different scattering channels which can explain coexistence of several quasiparticle interference patterns in the nanoscale regions of interest. In addition, the application of the kernel functions allowed us extracting a non-linear component of the relationship between the lattice strain and scattering intensity in graphene. Lastly, the outlined approach can be further utilized to analyzing correlations in various multi-modal imaging techniques where the information of interest is spatially distributed and has usually a complex multidimensional nature.« less

Equilibration and GGE in interacting-to-free quantum quenches in dimensions d\\gt 1

NASA Astrophysics Data System (ADS)

Sotiriadis, Spyros; Martelloni, Gabriele

2016-03-01

Ground states ofinteracting QFTs are non-Gaussian states, i.e. their connected n-point correlation functions do not vanish for n\\gt 2, in contrast to the free QFT case. We show that, when the ground state of an interacting QFT evolves under a free massive QFT for a long time (a scenario that can be realised by a quantum quench), the connected correlation functions decay and all local physical observables equilibrate to values that are given by a Gaussian density matrix that retains memory only of the two-point initial correlation function. The argument hinges upon the fundamental physical principle of cluster decomposition, which is valid for the ground state of a general QFT. An analogous result was already known to be valid in the case of d = 1 spatial dimensions, where it is a special case of the so-called generalised Gibbs ensemble (GGE) hypothesis, and we now generalise it to higher dimensions. Moreover, in the case of massless free evolution, despite the fact that the evolution may lead not to equilibration but instead to unbounded increase of correlations with time, the GGE gives correctly the leading-order asymptotic behaviour of correlation functions in the thermodynamic and large time limit. The demonstration is performed in the context of a bosonic relativistic QFT, but the arguments apply more generally.

Data mining graphene: Correlative analysis of structure and electronic degrees of freedom in graphenic monolayers with defects

DOE PAGES

Ziatdinov, Maxim A.; Fujii, Shintaro; Kiguchi, Manabu; ...

2016-11-09

The link between changes in the material crystal structure and its mechanical, electronic, magnetic, and optical functionalities known as the structure-property relationship is the cornerstone of the contemporary materials science research. The recent advances in scanning transmission electron and scanning probe microscopies (STEM and SPM) have opened an unprecedented path towards examining the materials structure property relationships on the single-impurity and atomic-configuration levels. Lacking, however, are the statistics-based approaches for cross-correlation of structure and property variables obtained in different information channels of the STEM and SPM experiments. Here we have designed an approach based on a combination of sliding windowmore » Fast Fourier Transform, Pearson correlation matrix, linear and kernel canonical correlation, to study a relationship between lattice distortions and electron scattering from the SPM data on graphene with defects. Our analysis revealed that the strength of coupling to strain is altered between different scattering channels which can explain coexistence of several quasiparticle interference patterns in the nanoscale regions of interest. In addition, the application of the kernel functions allowed us extracting a non-linear component of the relationship between the lattice strain and scattering intensity in graphene. Lastly, the outlined approach can be further utilized to analyzing correlations in various multi-modal imaging techniques where the information of interest is spatially distributed and has usually a complex multidimensional nature.« less

Nonparametric Bayesian models for a spatial covariance.

PubMed

Reich, Brian J; Fuentes, Montserrat

2012-01-01

A crucial step in the analysis of spatial data is to estimate the spatial correlation function that determines the relationship between a spatial process at two locations. The standard approach to selecting the appropriate correlation function is to use prior knowledge or exploratory analysis, such as a variogram analysis, to select the correct parametric correlation function. Rather that selecting a particular parametric correlation function, we treat the covariance function as an unknown function to be estimated from the data. We propose a flexible prior for the correlation function to provide robustness to the choice of correlation function. We specify the prior for the correlation function using spectral methods and the Dirichlet process prior, which is a common prior for an unknown distribution function. Our model does not require Gaussian data or spatial locations on a regular grid. The approach is demonstrated using a simulation study as well as an analysis of California air pollution data.

Structure of a financial cross-correlation matrix under attack

NASA Astrophysics Data System (ADS)

Lim, Gyuchang; Kim, SooYong; Kim, Junghwan; Kim, Pyungsoo; Kang, Yoonjong; Park, Sanghoon; Park, Inho; Park, Sang-Bum; Kim, Kyungsik

2009-09-01

We investigate the structure of a perturbed stock market in terms of correlation matrices. For the purpose of perturbing a stock market, two distinct methods are used, namely local and global perturbation. The former involves replacing a correlation coefficient of the cross-correlation matrix with one calculated from two Gaussian-distributed time series while the latter reconstructs the cross-correlation matrix just after replacing the original return series with Gaussian-distributed time series. Concerning the local case, it is a technical study only and there is no attempt to model reality. The term ‘global’ means the overall effect of the replacement on other untouched returns. Through statistical analyses such as random matrix theory (RMT), network theory, and the correlation coefficient distributions, we show that the global structure of a stock market is vulnerable to perturbation. However, apart from in the analysis of inverse participation ratios (IPRs), the vulnerability becomes dull under a small-scale perturbation. This means that these analysis tools are inappropriate for monitoring the whole stock market due to the low sensitivity of a stock market to a small-scale perturbation. In contrast, when going down to the structure of business sectors, we confirm that correlation-based business sectors are regrouped in terms of IPRs. This result gives a clue about monitoring the effect of hidden intentions, which are revealed via portfolios taken mostly by large investors.

Non-covalent interactions of a drug molecule encapsulated in a hybrid silica gel.

PubMed

Paul, Geo; Steuernagel, Stefan; Koller, Hubert

2007-12-28

The drug molecule Propranolol has been encapsulated by a sol-gel process in an organic-inorganic hybrid matrix by in-situ self-assembly; the 2D HETCOR solid state NMR spectroscopy provides direct proof of the intimate spatial relationship between the host matrix and guest drug molecules.

The derivative and tangent operators of a motion in Lorentzian space

NASA Astrophysics Data System (ADS)

Durmaz, Olgun; Aktaş, Buşra; Gündoğan, Hali˙t

In this paper, by using Lorentzian matrix multiplication, L-Tangent operator is obtained in Lorentzian space. The L-Tangent operators related with planar, spherical and spatial motion are computed via special matrix groups. L-Tangent operators are related to vectors. Some illustrative examples for applications of L-Tangent operators are also presented.

Density matrix embedding in an antisymmetrized geminal power bath

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

Tsuchimochi, Takashi; Welborn, Matthew; Van Voorhis, Troy, E-mail: tvan@mit.edu

2015-07-14

Density matrix embedding theory (DMET) has emerged as a powerful tool for performing wave function-in-wave function embedding for strongly correlated systems. In traditional DMET, an accurate calculation is performed on a small impurity embedded in a mean field bath. Here, we extend the original DMET equations to account for correlation in the bath via an antisymmetrized geminal power (AGP) wave function. The resulting formalism has a number of advantages. First, it allows one to properly treat the weak correlation limit of independent pairs, which DMET is unable to do with a mean-field bath. Second, it associates a size extensive correlationmore » energy with a given density matrix (for the models tested), which AGP by itself is incapable of providing. Third, it provides a reasonable description of charge redistribution in strongly correlated but non-periodic systems. Thus, AGP-DMET appears to be a good starting point for describing electron correlation in molecules, which are aperiodic and possess both strong and weak electron correlation.« less

Generation of organized germ layers from a single mouse embryonic stem cell.

PubMed

Poh, Yeh-Chuin; Chen, Junwei; Hong, Ying; Yi, Haiying; Zhang, Shuang; Chen, Junjian; Wu, Douglas C; Wang, Lili; Jia, Qiong; Singh, Rishi; Yao, Wenting; Tan, Youhua; Tajik, Arash; Tanaka, Tetsuya S; Wang, Ning

2014-05-30

Mammalian inner cell mass cells undergo lineage-specific differentiation into germ layers of endoderm, mesoderm and ectoderm during gastrulation. It has been a long-standing challenge in developmental biology to replicate these organized germ layer patterns in culture. Here we present a method of generating organized germ layers from a single mouse embryonic stem cell cultured in a soft fibrin matrix. Spatial organization of germ layers is regulated by cortical tension of the colony, matrix dimensionality and softness, and cell-cell adhesion. Remarkably, anchorage of the embryoid colony from the 3D matrix to collagen-1-coated 2D substrates of ~1 kPa results in self-organization of all three germ layers: ectoderm on the outside layer, mesoderm in the middle and endoderm at the centre of the colony, reminiscent of generalized gastrulating chordate embryos. These results suggest that mechanical forces via cell-matrix and cell-cell interactions are crucial in spatial organization of germ layers during mammalian gastrulation. This new in vitro method could be used to gain insights on the mechanisms responsible for the regulation of germ layer formation.

Geostatistical borehole image-based mapping of karst-carbonate aquifer pores

USGS Publications Warehouse

Michael Sukop,; Cunningham, Kevin J.

2016-01-01

Quantification of the character and spatial distribution of porosity in carbonate aquifers is important as input into computer models used in the calculation of intrinsic permeability and for next-generation, high-resolution groundwater flow simulations. Digital, optical, borehole-wall image data from three closely spaced boreholes in the karst-carbonate Biscayne aquifer in southeastern Florida are used in geostatistical experiments to assess the capabilities of various methods to create realistic two-dimensional models of vuggy megaporosity and matrix-porosity distribution in the limestone that composes the aquifer. When the borehole image data alone were used as the model training image, multiple-point geostatistics failed to detect the known spatial autocorrelation of vuggy megaporosity and matrix porosity among the three boreholes, which were only 10 m apart. Variogram analysis and subsequent Gaussian simulation produced results that showed a realistic conceptualization of horizontal continuity of strata dominated by vuggy megaporosity and matrix porosity among the three boreholes.

Expression Levels of Myostatin and Matrix Metalloproteinase 14 mRNAs in Uterine Leiomyoma are Correlated With Dysmenorrhea.

PubMed

Tsigkou, Anastasia; Reis, Fernando M; Ciarmela, Pasquapina; Lee, Meng H; Jiang, Bingjie; Tosti, Claudia; Shen, Fang-Rong; Shi, Zhendan; Chen, You-Guo; Petraglia, Felice

2015-12-01

Uterine leiomyoma is the most common benign neoplasm of female reproductive system, found in about 50% of women in reproductive age. The mechanisms of leiomyoma growth include cell proliferation, which is modulated by growth factors, and deposition of extracellular matrix (ECM). Activin A and myostatin are growth factors that play a role in proliferation of leiomyoma cells. Matrix metalloproteinases (MMPs) are known for their ability to remodel the ECM in different biological systems. The aim of this study was to evaluate the expression levels of activin βA-subunit, myostatin, and MMP14 messenger RNAs (mRNAs) in uterine leiomyomas and the possible correlation of these factors with clinical features of the disease. Matrix metalloproteinase 14 was highly expressed in uterine leiomyoma and correlated with myostatin and activin A mRNA expression. Moreover, MMP14 and myostatin mRNA expression correlated significantly and directly with the intensity of dysmenorrhea. Overall, the present findings showed that MMP14 mRNA is highly expressed in uterine leiomyoma, where it correlates with the molecular expression of growth factors and is further increased in cases of intense dysmenorrhea. © The Author(s) 2015.

In silico study on the effects of matrix structure in controlled drug release

NASA Astrophysics Data System (ADS)

Villalobos, Rafael; Cordero, Salomón; Maria Vidales, Ana; Domínguez, Armando

2006-07-01

Purpose: To study the effects of drug concentration and spatial distribution of the medicament, in porous solid dosage forms, on the kinetics and total yield of drug release. Methods: Cubic networks are used as models of drug release systems. They were constructed by means of the dual site-bond model framework, which allows a substrate to have adequate geometrical and topological distribution of its pore elements. Drug particles can move inside the networks by following a random walk model with excluded volume interactions between the particles. The drug release time evolution for different drug concentration and different initial drug spatial distribution has been monitored. Results: The numerical results show that in all the studied cases, drug release presents an anomalous behavior, and the consequences of the matrix structural properties, i.e., drug spatial distribution and drug concentration, on the drug release profile have been quantified. Conclusions: The Weibull function provides a simple connection between the model parameters and the microstructure of the drug release device. A critical modeling of drug release from matrix-type delivery systems is important in order to understand the transport mechanisms that are implicated, and to predict the effect of the device design parameters on the release rate.

Characterization of human kidney stones using micro-PIXE and RBS: a comparative study between two different populations.

PubMed

Pineda-Vargas, C A; Eisa, M E M; Rodgers, A L

2009-03-01

The micro-PIXE and RBS techniques are used to investigate the matrix as well as the trace elemental composition of calcium-rich human tissues on a microscopic scale. This paper deals with the spatial distribution of trace metals in hard human tissues such as kidney stone concretions, undertaken at the nuclear microprobe (NMP) facility. Relevant information about ion beam techniques used for material characterization will be discussed. Mapping correlation between different trace metals to extract information related to micro-regions composition will be illustrated with an application using proton energies of 1.5 and 3.0 MeV and applied to a comparative study for human kidney stone concretions nucleation region analysis from two different population groups (Sudan and South Africa).

Projected quasiparticle theory for molecular electronic structure

NASA Astrophysics Data System (ADS)

Scuseria, Gustavo E.; Jiménez-Hoyos, Carlos A.; Henderson, Thomas M.; Samanta, Kousik; Ellis, Jason K.

2011-09-01

We derive and implement symmetry-projected Hartree-Fock-Bogoliubov (HFB) equations and apply them to the molecular electronic structure problem. All symmetries (particle number, spin, spatial, and complex conjugation) are deliberately broken and restored in a self-consistent variation-after-projection approach. We show that the resulting method yields a comprehensive black-box treatment of static correlations with effective one-electron (mean-field) computational cost. The ensuing wave function is of multireference character and permeates the entire Hilbert space of the problem. The energy expression is different from regular HFB theory but remains a functional of an independent quasiparticle density matrix. All reduced density matrices are expressible as an integration of transition density matrices over a gauge grid. We present several proof-of-principle examples demonstrating the compelling power of projected quasiparticle theory for quantum chemistry.

Compression of Born ratio for fluorescence molecular tomography/x-ray computed tomography hybrid imaging: methodology and in vivo validation.

PubMed

Mohajerani, Pouyan; Ntziachristos, Vasilis

2013-07-01

The 360° rotation geometry of the hybrid fluorescence molecular tomography/x-ray computed tomography modality allows for acquisition of very large datasets, which pose numerical limitations on the reconstruction. We propose a compression method that takes advantage of the correlation of the Born-normalized signal among sources in spatially formed clusters to reduce the size of system model. The proposed method has been validated using an ex vivo study and an in vivo study of a nude mouse with a subcutaneous 4T1 tumor, with and without inclusion of a priori anatomical information. Compression rates of up to two orders of magnitude with minimum distortion of reconstruction have been demonstrated, resulting in large reduction in weight matrix size and reconstruction time.

A CLT on the SNR of Diagonally Loaded MVDR Filters

NASA Astrophysics Data System (ADS)

Rubio, Francisco; Mestre, Xavier; Hachem, Walid

2012-08-01

This paper studies the fluctuations of the signal-to-noise ratio (SNR) of minimum variance distorsionless response (MVDR) filters implementing diagonal loading in the estimation of the covariance matrix. Previous results in the signal processing literature are generalized and extended by considering both spatially as well as temporarily correlated samples. Specifically, a central limit theorem (CLT) is established for the fluctuations of the SNR of the diagonally loaded MVDR filter, under both supervised and unsupervised training settings in adaptive filtering applications. Our second-order analysis is based on the Nash-Poincar\\'e inequality and the integration by parts formula for Gaussian functionals, as well as classical tools from statistical asymptotic theory. Numerical evaluations validating the accuracy of the CLT confirm the asymptotic Gaussianity of the fluctuations of the SNR of the MVDR filter.

Spatial and Seasonal Dynamics of Water Environmental Capacity in Mountainous Rivers of the Southeastern Coast, China

PubMed Central

Jiang, Jingang; Jing, Changwei

2018-01-01

The south-east littoral is one of the most populous and developed regions in China suffering from serious water pollution problems, and the Xian-Jiang Basin in the mid of this region is among the most polluted watersheds. Critical information is needed but lacking for improved pollution control and water quality assessment, among which water environmental capacity (WEC) is the most important variable but is difficult to calculate. In this study, a one-dimensional water quality model combined with a matrix calculation algorithm was first developed and calibrated with in-situ observations in the Xian-Jiang basin. Then, the model was applied to analyze the spatial and temporal patterns of WEC of the entire basin. The results indicated that, in 2015, the total pollutant discharges into the river reached 6719.68 t/yr, 488.12 t/yr, and 128.57 t/yr for COD, NH3-N and TP, respectively. The spatial pattern suggested a strong correlation between these water contaminants and industrial enterprises, residential areas, and land-use types in the basin. Furthermore, it was noticed that there was a significant seasonal pattern in WEC that the dry season pollution is much greater than that in the plum season, while that in the typhoon season appears to be the weakest among all seasons. The WEC differed significantly among the 24 sub-basins during the dry season but varied to a smaller extent in other seasons, suggesting differential complex spatial-temporal dependency of the WEC. PMID:29315265

P04.19 Recommendations for computation of textural measures obtained from 3D brain tumor MRIs: A robustness analysis points out the need for standardization.

PubMed Central

Molina, D.; Pérez-Beteta, J.; Martínez-González, A.; Velásquez, C.; Martino, J.; Luque, B.; Revert, A.; Herruzo, I.; Arana, E.; Pérez-García, V. M.

2017-01-01

Abstract Introduction: Textural analysis refers to a variety of mathematical methods used to quantify the spatial variations in grey levels within images. In brain tumors, textural features have a great potential as imaging biomarkers having been shown to correlate with survival, tumor grade, tumor type, etc. However, these measures should be reproducible under dynamic range and matrix size changes for their clinical use. Our aim is to study this robustness in brain tumors with 3D magnetic resonance imaging, not previously reported in the literature. Materials and methods: 3D T1-weighted images of 20 patients with glioblastoma (64.80 ± 9.12 years-old) obtained from a 3T scanner were analyzed. Tumors were segmented using an in-house semi-automatic 3D procedure. A set of 16 3D textural features of the most common types (co-occurrence and run-length matrices) were selected, providing regional (run-length based measures) and local information (co-ocurrence matrices) on the tumor heterogeneity. Feature robustness was assessed by means of the coefficient of variation (CV) under both dynamic range (16, 32 and 64 gray levels) and/or matrix size (256x256 and 432x432) changes. Results: None of the textural features considered were robust under dynamic range changes. The textural co-occurrence matrix feature Entropy was the only textural feature robust (CV < 10%) under spatial resolution changes. Conclusions: In general, textural measures of three-dimensional brain tumor images are neither robust under dynamic range nor under matrix size changes. Thus, it becomes mandatory to fix standards for image rescaling after acquisition before the textural features are computed if they are to be used as imaging biomarkers. For T1-weighted images a dynamic range of 16 grey levels and a matrix size of 256x256 (and isotropic voxel) is found to provide reliable and comparable results and is feasible with current MRI scanners. The implications of this work go beyond the specific tumor type and MRI sequence studied here and pose the need for standardization in textural feature calculation of oncological images. FUNDING: James S. Mc. Donnell Foundation (USA) 21st Century Science Initiative in Mathematical and Complex Systems Approaches for Brain Cancer [Collaborative award 220020450 and planning grant 220020420], MINECO/FEDER [MTM2015-71200-R], JCCM [PEII-2014-031-P].

Commander and User Perceptions of the Army’s Intransit Visibility (ITV) Architecture

DTIC Science & Technology

2007-03-01

covariance matrix; (c) Bartlett’s test of Sphericity; and (d) Kaiser-Meyer- Olkin ( KMO ) measure of sampling adequacy. The inter-item correlation matrix...001), and all diagonal terms had a value of 1 while off-diagonal terms were 0. The KMO measure of sampling adequacy reflects the homogeneity...amongst the variables and serves as an index for comparing the magnitudes of correlation coefficients to partial correlation coefficients. KMO values at

Mapping of Mechanical Strains and Stresses around Quiescent Engineered Three-Dimensional Epithelial Tissues

PubMed Central

Gjorevski, Nikolce; Nelson, Celeste M.

2012-01-01

Understanding how physical signals guide biological processes requires qualitative and quantitative knowledge of the mechanical forces generated and sensed by cells in a physiologically realistic three-dimensional (3D) context. Here, we used computational modeling and engineered epithelial tissues of precise geometry to define the experimental parameters that are required to measure directly the mechanical stress profile of 3D tissues embedded within native type I collagen. We found that to calculate the stresses accurately in these settings, we had to account for mechanical heterogeneities within the matrix, which we visualized and quantified using confocal reflectance and atomic force microscopy. Using this technique, we were able to obtain traction forces at the epithelium-matrix interface, and to resolve and quantify patterns of mechanical stress throughout the surrounding matrix. We discovered that whereas single cells generate tension by contracting and pulling on the matrix, the contraction of multicellular tissues can also push against the matrix, causing emergent compression. Furthermore, tissue geometry defines the spatial distribution of mechanical stress across the epithelium, which communicates mechanically over distances spanning hundreds of micrometers. Spatially resolved mechanical maps can provide insight into the types and magnitudes of physical parameters that are sensed and interpreted by multicellular tissues during normal and pathological processes. PMID:22828342

Spatial operator factorization and inversion of the manipulator mass matrix

NASA Technical Reports Server (NTRS)

Rodriguez, Guillermo; Kreutz-Delgado, Kenneth

1992-01-01

This paper advances two linear operator factorizations of the manipulator mass matrix. Embedded in the factorizations are many of the techniques that are regarded as very efficient computational solutions to inverse and forward dynamics problems. The operator factorizations provide a high-level architectural understanding of the mass matrix and its inverse, which is not visible in the detailed algorithms. They also lead to a new approach to the development of computer programs or organize complexity in robot dynamics.

Wiener-matrix image restoration beyond the sampling passband

NASA Technical Reports Server (NTRS)

Rahman, Zia-Ur; Alter-Gartenberg, Rachel; Fales, Carl L.; Huck, Friedrich O.

1991-01-01

A finer-than-sampling-lattice resolution image can be obtained using multiresponse image gathering and Wiener-matrix restoration. The multiresponse image gathering weighs the within-passband and aliased signal components differently, allowing the Wiener-matrix restoration filter to unscramble these signal components and restore spatial frequencies beyond the sampling passband of the photodetector array. A multiresponse images can be reassembled into a single minimum mean square error image with a resolution that is sq rt A times finer than the photodetector-array sampling lattice.

Thermal form-factor approach to dynamical correlation functions of integrable lattice models

NASA Astrophysics Data System (ADS)

Göhmann, Frank; Karbach, Michael; Klümper, Andreas; Kozlowski, Karol K.; Suzuki, Junji

2017-11-01

We propose a method for calculating dynamical correlation functions at finite temperature in integrable lattice models of Yang-Baxter type. The method is based on an expansion of the correlation functions as a series over matrix elements of a time-dependent quantum transfer matrix rather than the Hamiltonian. In the infinite Trotter-number limit the matrix elements become time independent and turn into the thermal form factors studied previously in the context of static correlation functions. We make this explicit with the example of the XXZ model. We show how the form factors can be summed utilizing certain auxiliary functions solving finite sets of nonlinear integral equations. The case of the XX model is worked out in more detail leading to a novel form-factor series representation of the dynamical transverse two-point function.

Scale Free Reduced Rank Image Analysis.

ERIC Educational Resources Information Center

Horst, Paul

In the traditional Guttman-Harris type image analysis, a transformation is applied to the data matrix such that each column of the transformed data matrix is the best least squares estimate of the corresponding column of the data matrix from the remaining columns. The model is scale free. However, it assumes (1) that the correlation matrix is…

Random matrix theory and fund of funds portfolio optimisation

NASA Astrophysics Data System (ADS)

Conlon, T.; Ruskin, H. J.; Crane, M.

2007-08-01

The proprietary nature of Hedge Fund investing means that it is common practise for managers to release minimal information about their returns. The construction of a fund of hedge funds portfolio requires a correlation matrix which often has to be estimated using a relatively small sample of monthly returns data which induces noise. In this paper, random matrix theory (RMT) is applied to a cross-correlation matrix C, constructed using hedge fund returns data. The analysis reveals a number of eigenvalues that deviate from the spectrum suggested by RMT. The components of the deviating eigenvectors are found to correspond to distinct groups of strategies that are applied by hedge fund managers. The inverse participation ratio is used to quantify the number of components that participate in each eigenvector. Finally, the correlation matrix is cleaned by separating the noisy part from the non-noisy part of C. This technique is found to greatly reduce the difference between the predicted and realised risk of a portfolio, leading to an improved risk profile for a fund of hedge funds.

Linear scaling computation of the Fock matrix. VI. Data parallel computation of the exchange-correlation matrix

NASA Astrophysics Data System (ADS)

Gan, Chee Kwan; Challacombe, Matt

2003-05-01

Recently, early onset linear scaling computation of the exchange-correlation matrix has been achieved using hierarchical cubature [J. Chem. Phys. 113, 10037 (2000)]. Hierarchical cubature differs from other methods in that the integration grid is adaptive and purely Cartesian, which allows for a straightforward domain decomposition in parallel computations; the volume enclosing the entire grid may be simply divided into a number of nonoverlapping boxes. In our data parallel approach, each box requires only a fraction of the total density to perform the necessary numerical integrations due to the finite extent of Gaussian-orbital basis sets. This inherent data locality may be exploited to reduce communications between processors as well as to avoid memory and copy overheads associated with data replication. Although the hierarchical cubature grid is Cartesian, naive boxing leads to irregular work loads due to strong spatial variations of the grid and the electron density. In this paper we describe equal time partitioning, which employs time measurement of the smallest sub-volumes (corresponding to the primitive cubature rule) to load balance grid-work for the next self-consistent-field iteration. After start-up from a heuristic center of mass partitioning, equal time partitioning exploits smooth variation of the density and grid between iterations to achieve load balance. With the 3-21G basis set and a medium quality grid, equal time partitioning applied to taxol (62 heavy atoms) attained a speedup of 61 out of 64 processors, while for a 110 molecule water cluster at standard density it achieved a speedup of 113 out of 128. The efficiency of equal time partitioning applied to hierarchical cubature improves as the grid work per processor increases. With a fine grid and the 6-311G(df,p) basis set, calculations on the 26 atom molecule α-pinene achieved a parallel efficiency better than 99% with 64 processors. For more coarse grained calculations, superlinear speedups are found to result from reduced computational complexity associated with data parallelism.

Profiling of adrenocorticotropic hormone and arginine vasopressin in human pituitary gland and tumor thin tissue sections using droplet-based liquid-microjunction surface-sampling-HPLC–ESI-MS–MS

DOE PAGES

Kertesz, Vilmos; Calligaris, David; Feldman, Daniel R.; ...

2015-06-18

Described here are the results from the profiling of the proteins arginine vasopressin (AVP) and adrenocorticotropic hormone (ACTH) from normal human pituitary gland and pituitary adenoma tissue sections using a fully automated droplet-based liquid microjunction surface sampling-HPLC-ESI-MS/MS system for spatially resolved sampling, HPLC separation, and mass spectral detection. Excellent correlation was found between the protein distribution data obtained with this droplet-based liquid microjunction surface sampling-HPLC-ESI-MS/MS system and those data obtained with matrix assisted laser desorption ionization (MALDI) chemical imaging analyses of serial sections of the same tissue. The protein distributions correlated with the visible anatomic pattern of the pituitary gland.more » AVP was most abundant in the posterior pituitary gland region (neurohypophysis) and ATCH was dominant in the anterior pituitary gland region (adenohypophysis). The relative amounts of AVP and ACTH sampled from a series of ACTH secreting and non-secreting pituitary adenomas correlated with histopathological evaluation. ACTH was readily detected at significantly higher levels in regions of ACTH secreting adenomas and in normal anterior adenohypophysis compared to non-secreting adenoma and neurohypophysis. AVP was mostly detected in normal neurohypophysis as anticipated. This work demonstrates that a fully automated droplet-based liquid microjunction surface sampling system coupled to HPLC-ESI-MS/MS can be readily used for spatially resolved sampling, separation, detection, and semi-quantitation of physiologically-relevant peptide and protein hormones, such as AVP and ACTH, directly from human tissue. In addition, the relative simplicity, rapidity and specificity of the current methodology support the potential of this basic technology with further advancement for assisting surgical decision-making.« less

Holocene monsoon variability as resolved in small complex networks from palaeodata

NASA Astrophysics Data System (ADS)

Rehfeld, K.; Marwan, N.; Breitenbach, S.; Kurths, J.

2012-04-01

To understand the impacts of Holocene precipitation and/or temperature changes in the spatially extensive and complex region of Asia, it is promising to combine the information from palaeo archives, such as e.g. stalagmites, tree rings and marine sediment records from India and China. To this end, complex networks present a powerful and increasingly popular tool for the description and analysis of interactions within complex spatially extended systems in the geosciences and therefore appear to be predestined for this task. Such a network is typically constructed by thresholding a similarity matrix which in turn is based on a set of time series representing the (Earth) system dynamics at different locations. Looking into the pre-instrumental past, information about the system's processes and thus its state is available only through the reconstructed time series which -- most often -- are irregularly sampled in time and space. Interpolation techniques are often used for signal reconstruction, but they introduce additional errors, especially when records have large gaps. We have recently developed and extensively tested methods to quantify linear (Pearson correlation) and non-linear (mutual information) similarity in presence of heterogeneous and irregular sampling. To illustrate our approach we derive small networks from significantly correlated, linked, time series which are supposed to capture the underlying Asian Monsoon dynamics. We assess and discuss whether and where links and directionalities in these networks from irregularly sampled time series can be soundly detected. Finally, we investigate the role of the Northern Hemispheric temperature with respect to the correlation patterns and find that those derived from warm phases (e.g. Medieval Warm Period) are significantly different from patterns found in cold phases (e.g. Little Ice Age).

Profiling of adrenocorticotropic hormone and arginine vasopressin in human pituitary gland and tumor thin tissue sections using droplet-based liquid-microjunction surface-sampling-HPLC-ESI-MS-MS.

PubMed

Kertesz, Vilmos; Calligaris, David; Feldman, Daniel R; Changelian, Armen; Laws, Edward R; Santagata, Sandro; Agar, Nathalie Y R; Van Berkel, Gary J

2015-08-01

Described here are the results from the profiling of the proteins arginine vasopressin (AVP) and adrenocorticotropic hormone (ACTH) from normal human pituitary gland and pituitary adenoma tissue sections, using a fully automated droplet-based liquid-microjunction surface-sampling-HPLC-ESI-MS-MS system for spatially resolved sampling, HPLC separation, and mass spectrometric detection. Excellent correlation was found between the protein distribution data obtained with this method and data obtained with matrix-assisted laser desorption/ionization (MALDI) chemical imaging analyses of serial sections of the same tissue. The protein distributions correlated with the visible anatomic pattern of the pituitary gland. AVP was most abundant in the posterior pituitary gland region (neurohypophysis), and ATCH was dominant in the anterior pituitary gland region (adenohypophysis). The relative amounts of AVP and ACTH sampled from a series of ACTH-secreting and non-secreting pituitary adenomas correlated with histopathological evaluation. ACTH was readily detected at significantly higher levels in regions of ACTH-secreting adenomas and in normal anterior adenohypophysis compared with non-secreting adenoma and neurohypophysis. AVP was mostly detected in normal neurohypophysis, as expected. This work reveals that a fully automated droplet-based liquid-microjunction surface-sampling system coupled to HPLC-ESI-MS-MS can be readily used for spatially resolved sampling, separation, detection, and semi-quantitation of physiologically-relevant peptide and protein hormones, including AVP and ACTH, directly from human tissue. In addition, the relative simplicity, rapidity, and specificity of this method support the potential of this basic technology, with further advancement, for assisting surgical decision-making. Graphical Abstract Mass spectrometry based profiling of hormones in human pituitary gland and tumor thin tissue sections.

Profiling of adrenocorticotropic hormone and arginine vasopressin in human pituitary gland and tumor thin tissue sections using droplet-based liquid-microjunction surface-sampling-HPLC–ESI-MS–MS

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

Kertesz, Vilmos; Calligaris, David; Feldman, Daniel R.

Described here are the results from the profiling of the proteins arginine vasopressin (AVP) and adrenocorticotropic hormone (ACTH) from normal human pituitary gland and pituitary adenoma tissue sections using a fully automated droplet-based liquid microjunction surface sampling-HPLC-ESI-MS/MS system for spatially resolved sampling, HPLC separation, and mass spectral detection. Excellent correlation was found between the protein distribution data obtained with this droplet-based liquid microjunction surface sampling-HPLC-ESI-MS/MS system and those data obtained with matrix assisted laser desorption ionization (MALDI) chemical imaging analyses of serial sections of the same tissue. The protein distributions correlated with the visible anatomic pattern of the pituitary gland.more » AVP was most abundant in the posterior pituitary gland region (neurohypophysis) and ATCH was dominant in the anterior pituitary gland region (adenohypophysis). The relative amounts of AVP and ACTH sampled from a series of ACTH secreting and non-secreting pituitary adenomas correlated with histopathological evaluation. ACTH was readily detected at significantly higher levels in regions of ACTH secreting adenomas and in normal anterior adenohypophysis compared to non-secreting adenoma and neurohypophysis. AVP was mostly detected in normal neurohypophysis as anticipated. This work demonstrates that a fully automated droplet-based liquid microjunction surface sampling system coupled to HPLC-ESI-MS/MS can be readily used for spatially resolved sampling, separation, detection, and semi-quantitation of physiologically-relevant peptide and protein hormones, such as AVP and ACTH, directly from human tissue. In addition, the relative simplicity, rapidity and specificity of the current methodology support the potential of this basic technology with further advancement for assisting surgical decision-making.« less

MEG source imaging method using fast L1 minimum-norm and its applications to signals with brain noise and human resting-state source amplitude images.

PubMed

Huang, Ming-Xiong; Huang, Charles W; Robb, Ashley; Angeles, AnneMarie; Nichols, Sharon L; Baker, Dewleen G; Song, Tao; Harrington, Deborah L; Theilmann, Rebecca J; Srinivasan, Ramesh; Heister, David; Diwakar, Mithun; Canive, Jose M; Edgar, J Christopher; Chen, Yu-Han; Ji, Zhengwei; Shen, Max; El-Gabalawy, Fady; Levy, Michael; McLay, Robert; Webb-Murphy, Jennifer; Liu, Thomas T; Drake, Angela; Lee, Roland R

2014-01-01

The present study developed a fast MEG source imaging technique based on Fast Vector-based Spatio-Temporal Analysis using a L1-minimum-norm (Fast-VESTAL) and then used the method to obtain the source amplitude images of resting-state magnetoencephalography (MEG) signals for different frequency bands. The Fast-VESTAL technique consists of two steps. First, L1-minimum-norm MEG source images were obtained for the dominant spatial modes of sensor-waveform covariance matrix. Next, accurate source time-courses with millisecond temporal resolution were obtained using an inverse operator constructed from the spatial source images of Step 1. Using simulations, Fast-VESTAL's performance was assessed for its 1) ability to localize multiple correlated sources; 2) ability to faithfully recover source time-courses; 3) robustness to different SNR conditions including SNR with negative dB levels; 4) capability to handle correlated brain noise; and 5) statistical maps of MEG source images. An objective pre-whitening method was also developed and integrated with Fast-VESTAL to remove correlated brain noise. Fast-VESTAL's performance was then examined in the analysis of human median-nerve MEG responses. The results demonstrated that this method easily distinguished sources in the entire somatosensory network. Next, Fast-VESTAL was applied to obtain the first whole-head MEG source-amplitude images from resting-state signals in 41 healthy control subjects, for all standard frequency bands. Comparisons between resting-state MEG sources images and known neurophysiology were provided. Additionally, in simulations and cases with MEG human responses, the results obtained from using conventional beamformer technique were compared with those from Fast-VESTAL, which highlighted the beamformer's problems of signal leaking and distorted source time-courses. © 2013.

MEG Source Imaging Method using Fast L1 Minimum-norm and its Applications to Signals with Brain Noise and Human Resting-state Source Amplitude Images

PubMed Central

Huang, Ming-Xiong; Huang, Charles W.; Robb, Ashley; Angeles, AnneMarie; Nichols, Sharon L.; Baker, Dewleen G.; Song, Tao; Harrington, Deborah L.; Theilmann, Rebecca J.; Srinivasan, Ramesh; Heister, David; Diwakar, Mithun; Canive, Jose M.; Edgar, J. Christopher; Chen, Yu-Han; Ji, Zhengwei; Shen, Max; El-Gabalawy, Fady; Levy, Michael; McLay, Robert; Webb-Murphy, Jennifer; Liu, Thomas T.; Drake, Angela; Lee, Roland R.

2014-01-01

The present study developed a fast MEG source imaging technique based on Fast Vector-based Spatio-Temporal Analysis using a L1-minimum-norm (Fast-VESTAL) and then used the method to obtain the source amplitude images of resting-state magnetoencephalography (MEG) signals for different frequency bands. The Fast-VESTAL technique consists of two steps. First, L1-minimum-norm MEG source images were obtained for the dominant spatial modes of sensor-waveform covariance matrix. Next, accurate source time-courses with millisecond temporal resolution were obtained using an inverse operator constructed from the spatial source images of Step 1. Using simulations, Fast-VESTAL’s performance of was assessed for its 1) ability to localize multiple correlated sources; 2) ability to faithfully recover source time-courses; 3) robustness to different SNR conditions including SNR with negative dB levels; 4) capability to handle correlated brain noise; and 5) statistical maps of MEG source images. An objective pre-whitening method was also developed and integrated with Fast-VESTAL to remove correlated brain noise. Fast-VESTAL’s performance was then examined in the analysis of human mediannerve MEG responses. The results demonstrated that this method easily distinguished sources in the entire somatosensory network. Next, Fast-VESTAL was applied to obtain the first whole-head MEG source-amplitude images from resting-state signals in 41 healthy control subjects, for all standard frequency bands. Comparisons between resting-state MEG sources images and known neurophysiology were provided. Additionally, in simulations and cases with MEG human responses, the results obtained from using conventional beamformer technique were compared with those from Fast-VESTAL, which highlighted the beamformer’s problems of signal leaking and distorted source time-courses. PMID:24055704

Simulating Non-Fickian Transport across Péclet Regimes by doing Lévy Flights in the Rank Space of Velocity

NASA Astrophysics Data System (ADS)

Most, S.; Dentz, M.; Bolster, D.; Bijeljic, B.; Nowak, W.

2017-12-01

Transport in real porous media shows non-Fickian characteristics. In the Lagrangian perspective this leads to skewed distributions of particle arrival times. The skewness is triggered by particles' memory of velocity that persists over a characteristic length. Capturing process memory is essential to represent non-Fickianity thoroughly. Classical non-Fickian models (e.g., CTRW models) simulate the effects of memory but not the mechanisms leading to process memory. CTRWs have been applied successfully in many studies but nonetheless they have drawbacks. In classical CTRWs each particle makes a spatial transition for which each particle adapts a random transit time. Consecutive transit times are drawn independently from each other, and this is only valid for sufficiently large spatial transitions. If we want to apply a finer numerical resolution than that, we have to implement memory into the simulation. Recent CTRW methods use transitions matrices to simulate correlated transit times. However, deriving such transition matrices require transport data of a fine-scale transport simulation, and the obtained transition matrix is solely valid for this single Péclet regime. The CTRW method we propose overcomes all three drawbacks: 1) We simulate transport without restrictions in transition length. 2) We parameterize our CTRW without requiring a transport simulation. 3) Our parameterization scales across Péclet regimes. We do so by sampling the pore-scale velocity distribution to generate correlated transit times as a Lévy flight on the CDF-axis of velocities with reflection at 0 and 1. The Lévy flight is parametrized only by the correlation length. We explicitly model memory including the evolution and decay of non-Fickianity, so it extends from local via pre-asymptotic to asymptotic scales.

Correlating laser-induced breakdown spectroscopy with neutron activation analysis to determine the elemental concentration in the ionome of the Populus trichocarpa leaf

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

Martin, Madhavi Z.; Glasgow, David C.; Tschaplinski, Timothy J.

The black cottonwood poplar (Populus trichocarpa) leaf ionome (inorganic trace elements and mineral nutrients) is an important aspect for determining the physiological and developmental processes contributing to biomass production. A number of techniques are used to measure the ionome, yet characterizing the leaf spatial heterogeneity remains a challenge, especially in solid samples. Laser-induced breakdown spectroscopy (LIBS) has been used to determine the elemental composition of leaves and is able to raster across solid matrixes at 10 μm resolution. Here, we evaluate the use of LIBS for solid sample leaf elemental characterization in relation to neutron activation. In fact, neutron activationmore » analysis is a laboratory-based technique which is used by the National Institute of Standards and Technology (NIST) to certify trace elements in candidate reference materials including plant leaf matrices. Introduction to the techniques used in this research has been presented in this manuscript. Neutron activation analysis (NAA) data has been correlated to the LIBS spectra to achieve quantification of the elements or ions present within poplar leaves. The regression coefficients of calibration and validation using multivariate analysis (MVA) methodology for six out of seven elements have been determined and vary between 0.810 and 0.998. LIBS and NAA data has been presented for the elements such as, calcium, magnesium, manganese, aluminum, copper, and potassium. Chlorine was also detected but it did not show good correlation between the LIBS and NAA techniques. This research shows that LIBS can be used as a fast, high-spatial resolution technique to quantify elements as part of large-scale field phenotyping projects.« less

Correlating laser-induced breakdown spectroscopy with neutron activation analysis to determine the elemental concentration in the ionome of the Populus trichocarpa leaf

NASA Astrophysics Data System (ADS)

Martin, Madhavi Z.; Glasgow, David C.; Tschaplinski, Timothy J.; Tuskan, Gerald A.; Gunter, Lee E.; Engle, Nancy L.; Wymore, Ann M.; Weston, David J.

2017-12-01

The black cottonwood poplar (Populus trichocarpa) leaf ionome (inorganic trace elements and mineral nutrients) is an important aspect for determining the physiological and developmental processes contributing to biomass production. A number of techniques are used to measure the ionome, yet characterizing the leaf spatial heterogeneity remains a challenge, especially in solid samples. Laser-induced breakdown spectroscopy (LIBS) has been used to determine the elemental composition of leaves and is able to raster across solid matrixes at 10 μm resolution. Here, we evaluate the use of LIBS for solid sample leaf elemental characterization in relation to neutron activation. In fact, neutron activation analysis is a laboratory-based technique which is used by the National Institute of Standards and Technology (NIST) to certify trace elements in candidate reference materials including plant leaf matrices. Introduction to the techniques used in this research has been presented in this manuscript. Neutron activation analysis (NAA) data has been correlated to the LIBS spectra to achieve quantification of the elements or ions present within poplar leaves. The regression coefficients of calibration and validation using multivariate analysis (MVA) methodology for six out of seven elements have been determined and vary between 0.810 and 0.998. LIBS and NAA data has been presented for the elements such as, calcium, magnesium, manganese, aluminum, copper, and potassium. Chlorine was also detected but it did not show good correlation between the LIBS and NAA techniques. This research shows that LIBS can be used as a fast, high-spatial resolution technique to quantify elements as part of large-scale field phenotyping projects.

Correlating laser-induced breakdown spectroscopy with neutron activation analysis to determine the elemental concentration in the ionome of the Populus trichocarpa leaf

DOE PAGES

Martin, Madhavi Z.; Glasgow, David C.; Tschaplinski, Timothy J.; ...

2017-10-17

The black cottonwood poplar (Populus trichocarpa) leaf ionome (inorganic trace elements and mineral nutrients) is an important aspect for determining the physiological and developmental processes contributing to biomass production. A number of techniques are used to measure the ionome, yet characterizing the leaf spatial heterogeneity remains a challenge, especially in solid samples. Laser-induced breakdown spectroscopy (LIBS) has been used to determine the elemental composition of leaves and is able to raster across solid matrixes at 10 μm resolution. Here, we evaluate the use of LIBS for solid sample leaf elemental characterization in relation to neutron activation. In fact, neutron activationmore » analysis is a laboratory-based technique which is used by the National Institute of Standards and Technology (NIST) to certify trace elements in candidate reference materials including plant leaf matrices. Introduction to the techniques used in this research has been presented in this manuscript. Neutron activation analysis (NAA) data has been correlated to the LIBS spectra to achieve quantification of the elements or ions present within poplar leaves. The regression coefficients of calibration and validation using multivariate analysis (MVA) methodology for six out of seven elements have been determined and vary between 0.810 and 0.998. LIBS and NAA data has been presented for the elements such as, calcium, magnesium, manganese, aluminum, copper, and potassium. Chlorine was also detected but it did not show good correlation between the LIBS and NAA techniques. This research shows that LIBS can be used as a fast, high-spatial resolution technique to quantify elements as part of large-scale field phenotyping projects.« less

Development of a local size hierarchy causes regular spacing of trees in an even-aged Abies forest: analyses using spatial autocorrelation and the mark correlation function.

PubMed

Suzuki, Satoshi N; Kachi, Naoki; Suzuki, Jun-Ichirou

2008-09-01

During the development of an even-aged plant population, the spatial distribution of individuals often changes from a clumped pattern to a random or regular one. The development of local size hierarchies in an Abies forest was analysed for a period of 47 years following a large disturbance in 1959. In 1980 all trees in an 8 x 8 m plot were mapped and their height growth after the disturbance was estimated. Their mortality and growth were then recorded at 1- to 4-year intervals between 1980 and 2006. Spatial distribution patterns of trees were analysed by the pair correlation function. Spatial correlations between tree heights were analysed with a spatial autocorrelation function and the mark correlation function. The mark correlation function was able to detect a local size hierarchy that could not be detected by the spatial autocorrelation function alone. The small-scale spatial distribution pattern of trees changed from clumped to slightly regular during the 47 years. Mortality occurred in a density-dependent manner, which resulted in regular spacing between trees after 1980. The spatial autocorrelation and mark correlation functions revealed the existence of tree patches consisting of large trees at the initial stage. Development of a local size hierarchy was detected within the first decade after the disturbance, although the spatial autocorrelation was not negative. Local size hierarchies that developed persisted until 2006, and the spatial autocorrelation became negative at later stages (after about 40 years). This is the first study to detect local size hierarchies as a prelude to regular spacing using the mark correlation function. The results confirm that use of the mark correlation function together with the spatial autocorrelation function is an effective tool to analyse the development of a local size hierarchy of trees in a forest.

Assessment of the impact of modeling axial compression on PET image reconstruction.

PubMed

Belzunce, Martin A; Reader, Andrew J

2017-10-01

To comprehensively evaluate both the acceleration and image-quality impacts of axial compression and its degree of modeling in fully 3D PET image reconstruction. Despite being used since the very dawn of 3D PET reconstruction, there are still no extensive studies on the impact of axial compression and its degree of modeling during reconstruction on the end-point reconstructed image quality. In this work, an evaluation of the impact of axial compression on the image quality is performed by extensively simulating data with span values from 1 to 121. In addition, two methods for modeling the axial compression in the reconstruction were evaluated. The first method models the axial compression in the system matrix, while the second method uses an unmatched projector/backprojector, where the axial compression is modeled only in the forward projector. The different system matrices were analyzed by computing their singular values and the point response functions for small subregions of the FOV. The two methods were evaluated with simulated and real data for the Biograph mMR scanner. For the simulated data, the axial compression with span values lower than 7 did not show a decrease in the contrast of the reconstructed images. For span 11, the standard sinogram size of the mMR scanner, losses of contrast in the range of 5-10 percentage points were observed when measured for a hot lesion. For higher span values, the spatial resolution was degraded considerably. However, impressively, for all span values of 21 and lower, modeling the axial compression in the system matrix compensated for the spatial resolution degradation and obtained similar contrast values as the span 1 reconstructions. Such approaches have the same processing times as span 1 reconstructions, but they permit significant reduction in storage requirements for the fully 3D sinograms. For higher span values, the system has a large condition number and it is therefore difficult to recover accurately the higher frequencies. Modeling the axial compression also achieved a lower coefficient of variation but with an increase of intervoxel correlations. The unmatched projector/backprojector achieved similar contrast values to the matched version at considerably lower reconstruction times, but at the cost of noisier images. For a line source scan, the reconstructions with modeling of the axial compression achieved similar resolution to the span 1 reconstructions. Axial compression applied to PET sinograms was found to have a negligible impact for span values lower than 7. For span values up to 21, the spatial resolution degradation due to the axial compression can be almost completely compensated for by modeling this effect in the system matrix at the expense of considerably larger processing times and higher intervoxel correlations, while retaining the storage benefit of compressed data. For even higher span values, the resolution loss cannot be completely compensated possibly due to an effective null space in the system. The use of an unmatched projector/backprojector proved to be a practical solution to compensate for the spatial resolution degradation at a reasonable computational cost but can lead to noisier images. © 2017 The Authors. Medical Physics published by Wiley Periodicals, Inc. on behalf of American Association of Physicists in Medicine.

A photoreversible protein-patterning approach for guiding stem cell fate in three-dimensional gels

NASA Astrophysics Data System (ADS)

Deforest, Cole A.; Tirrell, David A.

2015-05-01

Although biochemically patterned hydrogels are capable of recapitulating many critical aspects of the heterogeneous cellular niche, exercising spatial and temporal control of the presentation and removal of biomolecular signalling cues in such systems has proved difficult. Here, we demonstrate a synthetic strategy that exploits two bioorthogonal photochemistries to achieve reversible immobilization of bioactive full-length proteins with good spatial and temporal control within synthetic, cell-laden biomimetic scaffolds. A photodeprotection-oxime-ligation sequence permits user-defined quantities of proteins to be anchored within distinct subvolumes of a three-dimensional matrix, and an ortho-nitrobenzyl ester photoscission reaction facilitates subsequent protein removal. By using this approach to pattern the presentation of the extracellular matrix protein vitronectin, we accomplished reversible differentiation of human mesenchymal stem cells to osteoblasts in a spatially defined manner. Our protein-patterning approach should provide further avenues to probe and direct changes in cell physiology in response to dynamic biochemical signalling.

Accounting for connectivity and spatial correlation in the optimal placement of wildlife habitat

Treesearch

John Hof; Curtis H. Flather

1996-01-01

This paper investigates optimization approaches to simultaneously modelling habitat fragmentation and spatial correlation between patch populations. The problem is formulated with habitat connectivity affecting population means and variances, with spatial correlations accounted for in covariance calculations. Population with a pre-specifled confidence level is then...

Ergodic channel capacity of spatial correlated multiple-input multiple-output free space optical links using multipulse pulse-position modulation

NASA Astrophysics Data System (ADS)

Wang, Huiqin; Wang, Xue; Cao, Minghua

2017-02-01

The spatial correlation extensively exists in the multiple-input multiple-output (MIMO) free space optical (FSO) communication systems due to the channel fading and the antenna space limitation. Wilkinson's method was utilized to investigate the impact of spatial correlation on the MIMO FSO communication system employing multipulse pulse-position modulation. Simulation results show that the existence of spatial correlation reduces the ergodic channel capacity, and the reception diversity is more competent to resist this kind of performance degradation.

Relationship between second-generation frequency doubling technology and standard automated perimetry in patients with glaucoma.

PubMed

Zarkovic, Andrea; Mora, Justin; McKelvie, James; Gamble, Greg

2007-12-01

The aim of the study was to establish the correlation between visual filed loss as shown by second-generation Frequency Doubling Technology (Humphrey Matrix) and Standard Automated Perimetry (Humphrey Field Analyser) in patients with glaucoma. Also, compared were the test duration and reliability. Forty right eyes from glaucoma patients from a private ophthalmology practice were included in this prospective study. All participants had tests within an 8-month period. Pattern deviation plots and mean deviation were compared to establish the correlation between the two perimetry tests. Overall correlation and correlation between hemifields, quadrants and individual test locations were assessed. Humphrey Field Analyser tests were slightly more reliable (37/40 vs. 34/40 for Matrix)) but overall of longer duration. There was good correlation (0.69) between mean deviations. Superior hemifields and superonasal quadrants had the highest correlation (0.88 [95% CI 0.79, 0.94]). Correlation between individual points was independent of distance from the macula. Generally, the Matrix and Humphrey Field Analyser perimetry correlate well; however, each machine utilizes a different method of analysing data and thus the direct comparison should be made with caution.

Dynamic Remodeling of Microbial Biofilms by Functionally Distinct Exopolysaccharides

PubMed Central

Chew, Su Chuen; Kundukad, Binu; Seviour, Thomas; van der Maarel, Johan R. C.; Yang, Liang; Rice, Scott A.; Doyle, Patrick

2014-01-01

ABSTRACT Biofilms are densely populated communities of microbial cells protected and held together by a matrix of extracellular polymeric substances. The structure and rheological properties of the matrix at the microscale influence the retention and transport of molecules and cells in the biofilm, thereby dictating population and community behavior. Despite its importance, quantitative descriptions of the matrix microstructure and microrheology are limited. Here, particle-tracking microrheology in combination with genetic approaches was used to spatially and temporally study the rheological contributions of the major exopolysaccharides Pel and Psl in Pseudomonas aeruginosa biofilms. Psl increased the elasticity and effective cross-linking within the matrix, which strengthened its scaffold and appeared to facilitate the formation of microcolonies. Conversely, Pel reduced effective cross-linking within the matrix. Without Psl, the matrix becomes more viscous, which facilitates biofilm spreading. The wild-type biofilm decreased in effective cross-linking over time, which would be advantageous for the spreading and colonization of new surfaces. This suggests that there are regulatory mechanisms to control production of the exopolysaccharides that serve to remodel the matrix of developing biofilms. The exopolysaccharides were also found to have profound effects on the spatial organization and integration of P. aeruginosa in a mixed-species biofilm model of P. aeruginosa-Staphylococcus aureus. Pel was required for close association of the two species in mixed-species microcolonies. In contrast, Psl was important for P. aeruginosa to form single-species biofilms on top of S. aureus biofilms. Our results demonstrate that Pel and Psl have distinct physical properties and functional roles during biofilm formation. PMID:25096883

Robustness of Thirty Meter Telescope primary mirror control

NASA Astrophysics Data System (ADS)

Macmynowski, Douglas G.; Thompson, Peter M.; Shelton, Chris; Roberts, Lewis C., Jr.

2010-07-01

The primary mirror control system for the Thirty Meter Telescope (TMT) maintains the alignment of the 492 segments in the presence of both quasi-static (gravity and thermal) and dynamic disturbances due to unsteady wind loads. The latter results in a desired control bandwidth of 1Hz at high spatial frequencies. The achievable bandwidth is limited by robustness to (i) uncertain telescope structural dynamics (control-structure interaction) and (ii) small perturbations in the ill-conditioned influence matrix that relates segment edge sensor response to actuator commands. Both of these effects are considered herein using models of TMT. The former is explored through multivariable sensitivity analysis on a reduced-order Zernike-basis representation of the structural dynamics. The interaction matrix ("A-matrix") uncertainty has been analyzed theoretically elsewhere, and is examined here for realistic amplitude perturbations due to segment and sensor installation errors, and gravity and thermal induced segment motion. The primary influence of A-matrix uncertainty is on the control of "focusmode"; this is the least observable mode, measurable only through the edge-sensor (gap-dependent) sensitivity to the dihedral angle between segments. Accurately estimating focus-mode will require updating the A-matrix as a function of the measured gap. A-matrix uncertainty also results in a higher gain-margin requirement for focus-mode, and hence the A-matrix and CSI robustness need to be understood simultaneously. Based on the robustness analysis, the desired 1 Hz bandwidth is achievable in the presence of uncertainty for all except the lowest spatial-frequency response patterns of the primary mirror.

Correlative characterization of primary particles formed in as-cast Al-Mg alloy containing a high level of Sc

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

Zhou, Shi'ang

Primary particles formed in as-cast Al-5Mg-0.6Sc alloy and their role in microstructure and mechanical properties of the alloy were investigated using optical microscopy (OM), scanning electron microscopy (SEM), electron back-scatter diffraction (EBSD) and tensile testing. It was found that primary particles due to a close orientation to matrix could serve as the potent heterogeneous nucleation sites for α-Al during solidification and thus impose a remarkable grain refinement effect. Eutectic structure consisted of layer by layer of ‘Al{sub 3}Sc + α-Al + Al{sub 3}Sc + ⋯’ and cellular-dendritic substructure were simultaneously observed at the particles inside, indicating that these particles couldmore » be identified as the eutectics rather than individual Al{sub 3}Sc phase. A calculating method, based on EBSD results, was introduced for the spatial distribution of these particles in matrix. The results showed that these eutectic particles randomly distributed in matrix. In addition, the formation of primary eutectic particles significant improved the strength of the Al-Mg alloy in as-cast condition, which is ascribed to the structural evolution from coarse dendrites to prefect fine equiaxed grains. On the other hand, these large-sized particles due to the tendency to act as the microcrack sources could cause a harmful effect in the ductility of Al-Mg-Sc alloy. - Highlights: •Primary particles exhibit an ‘Al{sub 3}Sc + α-Al + Al{sub 3}Sc + ⋯’ multilayer feature with a cellular-dendritic mode of growth. •EBSD analyses the mechanism of grain refinement and the distribution of primary particles in α-Al matrix. •A computational method was presented to calculate the habit planes of primary particles.« less

A Noise Removal Method for Uniform Circular Arrays in Complex Underwater Noise Environments with Low SNR

PubMed Central

Xia, Huijun; Yang, Kunde; Ma, Yuanliang; Wang, Yong; Liu, Yaxiong

2017-01-01

Generally, many beamforming methods are derived under the assumption of white noise. In practice, the actual underwater ambient noise is complex. As a result, the noise removal capacity of the beamforming method may be deteriorated considerably. Furthermore, in underwater environment with extremely low signal-to-noise ratio (SNR), the performances of the beamforming method may be deteriorated. To tackle these problems, a noise removal method for uniform circular array (UCA) is proposed to remove the received noise and improve the SNR in complex noise environments with low SNR. First, the symmetrical noise sources are defined and the spatial correlation of the symmetrical noise sources is calculated. Then, based on the preceding results, the noise covariance matrix is decomposed into symmetrical and asymmetrical components. Analysis indicates that the symmetrical component only affect the real part of the noise covariance matrix. Consequently, the delay-and-sum (DAS) beamforming is performed by using the imaginary part of the covariance matrix to remove the symmetrical component. However, the noise removal method causes two problems. First, the proposed method produces a false target. Second, the proposed method would seriously suppress the signal when it is located in some directions. To solve the first problem, two methods to reconstruct the signal covariance matrix are presented: based on the estimation of signal variance and based on the constrained optimization algorithm. To solve the second problem, we can design the array configuration and select the suitable working frequency. Theoretical analysis and experimental results are included to demonstrate that the proposed methods are particularly effective in complex noise environments with low SNR. The proposed method can be extended to any array. PMID:28598386

DBDA as a Novel Matrix for the Analyses of Small Molecules and Quantification of Fatty Acids by Negative Ion MALDI-TOF MS.

PubMed

Ling, Ling; Li, Ying; Wang, Sheng; Guo, Liming; Xiao, Chunsheng; Chen, Xuesi; Guo, Xinhua

2018-04-01

Matrix interference ions in low mass range has always been a concern when using matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS) to analyze small molecules (<500 Da). In this work, a novel matrix, N1,N4-dibenzylidenebenzene-1,4-diamine (DBDA) was synthesized for the analyses of small molecules by negative ion MALDI-TOF MS. Notably, only neat ions ([M-H] - ) of fatty acids without matrix interference appeared in the mass spectra and the limit of detection (LOD) reached 0.3 fmol. DBDA also has great performance towards other small molecules such as amino acids, peptides, and nucleotide. Furthermore, with this novel matrix, the free fatty acids in serum were quantitatively analyzed based on the correlation curves with correlation coefficient of 0.99. In addition, UV-Vis experiments and molecular orbital calculations were performed to explore mechanism about DBDA used as matrix in the negative ion mode. The present work shows that the DBDA matrix is a highly sensitive matrix with few interference ions for analysis of small molecules. Meanwhile, DBDA is able to precisely quantify the fatty acids in real biological samples. Graphical Abstract ᅟ.

Iterative image-domain decomposition for dual-energy CT

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

Niu, Tianye; Dong, Xue; Petrongolo, Michael

2014-04-15

Purpose: Dual energy CT (DECT) imaging plays an important role in advanced imaging applications due to its capability of material decomposition. Direct decomposition via matrix inversion suffers from significant degradation of image signal-to-noise ratios, which reduces clinical values of DECT. Existing denoising algorithms achieve suboptimal performance since they suppress image noise either before or after the decomposition and do not fully explore the noise statistical properties of the decomposition process. In this work, the authors propose an iterative image-domain decomposition method for noise suppression in DECT, using the full variance-covariance matrix of the decomposed images. Methods: The proposed algorithm ismore » formulated in the form of least-square estimation with smoothness regularization. Based on the design principles of a best linear unbiased estimator, the authors include the inverse of the estimated variance-covariance matrix of the decomposed images as the penalty weight in the least-square term. The regularization term enforces the image smoothness by calculating the square sum of neighboring pixel value differences. To retain the boundary sharpness of the decomposed images, the authors detect the edges in the CT images before decomposition. These edge pixels have small weights in the calculation of the regularization term. Distinct from the existing denoising algorithms applied on the images before or after decomposition, the method has an iterative process for noise suppression, with decomposition performed in each iteration. The authors implement the proposed algorithm using a standard conjugate gradient algorithm. The method performance is evaluated using an evaluation phantom (Catphan©600) and an anthropomorphic head phantom. The results are compared with those generated using direct matrix inversion with no noise suppression, a denoising method applied on the decomposed images, and an existing algorithm with similar formulation as the proposed method but with an edge-preserving regularization term. Results: On the Catphan phantom, the method maintains the same spatial resolution on the decomposed images as that of the CT images before decomposition (8 pairs/cm) while significantly reducing their noise standard deviation. Compared to that obtained by the direct matrix inversion, the noise standard deviation in the images decomposed by the proposed algorithm is reduced by over 98%. Without considering the noise correlation properties in the formulation, the denoising scheme degrades the spatial resolution to 6 pairs/cm for the same level of noise suppression. Compared to the edge-preserving algorithm, the method achieves better low-contrast detectability. A quantitative study is performed on the contrast-rod slice of Catphan phantom. The proposed method achieves lower electron density measurement error as compared to that by the direct matrix inversion, and significantly reduces the error variation by over 97%. On the head phantom, the method reduces the noise standard deviation of decomposed images by over 97% without blurring the sinus structures. Conclusions: The authors propose an iterative image-domain decomposition method for DECT. The method combines noise suppression and material decomposition into an iterative process and achieves both goals simultaneously. By exploring the full variance-covariance properties of the decomposed images and utilizing the edge predetection, the proposed algorithm shows superior performance on noise suppression with high image spatial resolution and low-contrast detectability.« less

The cluster-cluster correlation function. [of galaxies

NASA Technical Reports Server (NTRS)

Postman, M.; Geller, M. J.; Huchra, J. P.

1986-01-01

The clustering properties of the Abell and Zwicky cluster catalogs are studied using the two-point angular and spatial correlation functions. The catalogs are divided into eight subsamples to determine the dependence of the correlation function on distance, richness, and the method of cluster identification. It is found that the Corona Borealis supercluster contributes significant power to the spatial correlation function to the Abell cluster sample with distance class of four or less. The distance-limited catalog of 152 Abell clusters, which is not greatly affected by a single system, has a spatial correlation function consistent with the power law Xi(r) = 300r exp -1.8. In both the distance class four or less and distance-limited samples the signal in the spatial correlation function is a power law detectable out to 60/h Mpc. The amplitude of Xi(r) for clusters of richness class two is about three times that for richness class one clusters. The two-point spatial correlation function is sensitive to the use of estimated redshifts.

A test of the hypothesis that correlational selection generates genetic correlations.

PubMed

Roff, Derek A; Fairbairn, Daphne J

2012-09-01

Theory predicts that correlational selection on two traits will cause the major axis of the bivariate G matrix to orient itself in the same direction as the correlational selection gradient. Two testable predictions follow from this: for a given pair of traits, (1) the sign of correlational selection gradient should be the same as that of the genetic correlation, and (2) the correlational selection gradient should be positively correlated with the value of the genetic correlation. We test this hypothesis with a meta-analysis utilizing empirical estimates of correlational selection gradients and measures of the correlation between the two focal traits. Our results are consistent with both predictions and hence support the underlying hypothesis that correlational selection generates a genetic correlation between the two traits and hence orients the bivariate G matrix. © 2012 The Author(s). Evolution© 2012 The Society for the Study of Evolution.

Modelling soil properties in a crop field located in Croatia

NASA Astrophysics Data System (ADS)

Bogunovic, Igor; Pereira, Paulo; Millan, Mesic; Percin, Aleksandra; Zgorelec, Zeljka

2016-04-01

Development of tillage activities had negative effects on soil quality as destruction of soil horizons, compacting and aggregates destruction, increasing soil erosion and loss of organic matter. For a better management in order to mitigate the effects of intensive soil management in land degradation it is fundamental to map the spatial distribution of soil properties (Brevik et al., 2016). The understanding the distribution of the variables in space is very important for a sustainable management, in order to identify areas that need a potential intervention and decrease the economic losses (Galiati et al., 2016). The objective of this work is study the spatial distribution of some topsoil properties as clay, fine silt, coarse silt, fine sand, coarse sand, penetration resistance, moisture and organic matter in a crop field located in Croatia. A grid with 275x25 (625 m2) was designed and a total of 48 samples were collected. Previous to data modelling, data normality was checked using the Shapiro wilk-test. As in previous cases (Pereira et al., 2015), data did not followed the normal distribution, even after a logarithmic (Log), square-root, and box cox transformation. Thus, for modeling proposes, we used the log transformed data, since was the closest to the normality. In order to identify groups among the variables we applied a principal component analysis (PCA), based on the correlation matrix. On average clay content was 15.47% (±3.23), fine silt 24.24% (±4.08), coarse silt 35.34% (±3.12), fine sand 20.93% (±4.68), coarse sand 4.02% (±1.69), penetration resistance 0.66 MPa (±0.28), organic matter 1.51% (±0.25) and soil moisture 32.04% (±3.27). The results showed that the PCA identified three factors explained at least one of the variables. The first factor had high positive loadings in soil clay, fine silt and organic matter and a high negative loading in fine sand. The second factor had high positive loadings in coarse sand and moisture and a high negative loading in coarse silt. Finally, the factor 3 had a positive loading in penetration resistance. The loadings of these three factors were mapped using ordinary kriging method. The analysis of incremental spatial correlation identified that the highest spatial correlation in the factor 1 was identified at 41.87 m, in factor 2 at 75.61 m and factor 3 at 143.9 m. In the case of factor 2, the maximum peak of spatial autocorrelation was significant at a p<0.05. This showed that the variable has a random distribution, as confirmed with the Moran's I spatial correlation analysis. In relation to the other factors the maximum peaks were significantly clustered at a p<0.001. These results suggested that the each factor has a different spatial pattern and the studied soil properties explained by each factor had a different spatial distribution. References Breivik, E., Baumgarten, A., Calzolari, C., Miller, B., Pereira, P., Kabala, C., Jordán, A. Soil mapping, classification, and modelling: history and future directions. Geoderma, 264, Part B, 256-274. Galiati, A., Gristina, L., Crescimanno, Barone, E., Novara, A. (2016) Towards more efficient incentives for agri-environment measures in degraded and eroded vineyards. Land Degradation and Development, DOI: 10.1002/ldr.2389 Pereira, P., Cerdà, A., Úbeda, X., Mataix-Solera, J. Arcenegui, V., Zavala, L. (2015) Modelling the impacts of wildfire on ash thickness in a short-term period, Land Degradation and Development, 26, 180-192.

Metacommunity composition of web-spiders in a fragmented neotropical forest: relative importance of environmental and spatial effects.

PubMed

Baldissera, Ronei; Rodrigues, Everton N L; Hartz, Sandra M

2012-01-01

The distribution of beta diversity is shaped by factors linked to environmental and spatial control. The relative importance of both processes in structuring spider metacommunities has not yet been investigated in the Atlantic Forest. The variance explained by purely environmental, spatially structured environmental, and purely spatial components was compared for a metacommunity of web spiders. The study was carried out in 16 patches of Atlantic Forest in southern Brazil. Field work was done in one landscape mosaic representing a slight gradient of urbanization. Environmental variables encompassed plot- and patch-level measurements and a climatic matrix, while principal coordinates of neighbor matrices (PCNMs) acted as spatial variables. A forward selection procedure was carried out to select environmental and spatial variables influencing web-spider beta diversity. Variation partitioning was used to estimate the contribution of pure environmental and pure spatial effects and their shared influence on beta-diversity patterns, and to estimate the relative importance of selected environmental variables. Three environmental variables (bush density, land use in the surroundings of patches, and shape of patches) and two spatial variables were selected by forward selection procedures. Variation partitioning revealed that 15% of the variation of beta diversity was explained by a combination of environmental and PCNM variables. Most of this variation (12%) corresponded to pure environmental and spatially environmental structure. The data indicated that (1) spatial legacy was not important in explaining the web-spider beta diversity; (2) environmental predictors explained a significant portion of the variation in web-spider composition; (3) one-third of environmental variation was due to a spatial structure that jointly explains variation in species distributions. We were able to detect important factors related to matrix management influencing the web-spider beta-diversity patterns, which are probably linked to historical deforestation events.

Multi-population Genomic Relationships for Estimating Current Genetic Variances Within and Genetic Correlations Between Populations.

PubMed

Wientjes, Yvonne C J; Bijma, Piter; Vandenplas, Jérémie; Calus, Mario P L

2017-10-01

Different methods are available to calculate multi-population genomic relationship matrices. Since those matrices differ in base population, it is anticipated that the method used to calculate genomic relationships affects the estimate of genetic variances, covariances, and correlations. The aim of this article is to define the multi-population genomic relationship matrix to estimate current genetic variances within and genetic correlations between populations. The genomic relationship matrix containing two populations consists of four blocks, one block for population 1, one block for population 2, and two blocks for relationships between the populations. It is known, based on literature, that by using current allele frequencies to calculate genomic relationships within a population, current genetic variances are estimated. In this article, we theoretically derived the properties of the genomic relationship matrix to estimate genetic correlations between populations and validated it using simulations. When the scaling factor of across-population genomic relationships is equal to the product of the square roots of the scaling factors for within-population genomic relationships, the genetic correlation is estimated unbiasedly even though estimated genetic variances do not necessarily refer to the current population. When this property is not met, the correlation based on estimated variances should be multiplied by a correction factor based on the scaling factors. In this study, we present a genomic relationship matrix which directly estimates current genetic variances as well as genetic correlations between populations. Copyright © 2017 by the Genetics Society of America.

Evaluation of CDOM sources and their links with water quality in the lakes of Northeast China using fluorescence spectroscopy

NASA Astrophysics Data System (ADS)

Zhao, Ying; Song, Kaishan; Wen, Zhidan; Fang, Chong; Shang, Yingxin; Lv, Lili

2017-07-01

The spatial distributions of the fluorescence intensities Fmax for chromophoric dissolved organic matter (CDOM) components, the fluorescence indices (FI370 and FI310) and their correlations with water quality of 19 lakes in the Songhua River Basin (SHRB) across semiarid regions of Northeast China were examined with the data collected in September 2012 and 2015. The 19 lakes were divided into two groups according to EC (threshold value = 800 μS cm-1): fresh water (N = 13) and brackish water lakes (N = 6). The fluorescent characteristics of CDOM in the 19 lakes were investigated using excitation-emission matrix fluorescence spectroscopy (EEM) coupled with parallel factor (PARAFAC) and multivariate analysis. Two humic-like components (C1 and C3), one tryptophan-like component (C2), and one tyrosine-like component (C4) were identified by PARAFAC. The component C4 was not included in subsequent analyses due to the strong scatter in some colloidal water samples from brackish water lakes. The correlations between Fmax for the three EEM-PARAFAC extracted CDOM components C1-C3, the fluorescence indices (FI370 and FI310) and the water quality parameters (i.e., TN, TP, Chl-a, pH, EC, turbidity (Turb) and dissolved organic carbon (DOC)) were determined by redundancy analysis (RDA). The results of RDA analysis showed that spatial variation in land cover, pollution sources, and salinity/EC gradients in water quality affected Fmax for the fluorescent components C1-C3 and the fluorescence indices (FI370 and FI310). Further examination indicated that the CDOM fluorescent components and the fluorescence indices (FI370 and FI310) did not significantly differ (t-test, p > 0.05) in fresh water (N = 13) and brackish water lakes (N = 6). There was a difference in the distribution of the average Fmax for the CDOM fluorescent components between C1 to C3 from agricultural sources and urban wastewater sources in hypereutrophic brackish water lakes. The Fmax for humic-like components C1 and C3 spatially varied with land cover among the 19 lakes. Our results indicated that the spatial distributions of Fmax for CDOM fluorescent components and their correlations with water quality can be evaluated by EEM-PARAFAC and multivariate analysis among the 19 lakes across semiarid regions of Northeast China, which has potential implication for lakes with similar genesis.

Spatial-Operator Algebra For Flexible-Link Manipulators

NASA Technical Reports Server (NTRS)

Jain, Abhinandan; Rodriguez, Guillermo

1994-01-01

Method of computing dynamics of multiple-flexible-link robotic manipulators based on spatial-operator algebra, which originally applied to rigid-link manipulators. Aspects of spatial-operator-algebra approach described in several previous articles in NASA Tech Briefs-most recently "Robot Control Based on Spatial-Operator Algebra" (NPO-17918). In extension of spatial-operator algebra to manipulators with flexible links, each link represented by finite-element model: mass of flexible link apportioned among smaller, lumped-mass rigid bodies, coupling of motions expressed in terms of vibrational modes. This leads to operator expression for modal-mass matrix of link.

Pixelated filters for spatial imaging

NASA Astrophysics Data System (ADS)

Mathieu, Karine; Lequime, Michel; Lumeau, Julien; Abel-Tiberini, Laetitia; Savin De Larclause, Isabelle; Berthon, Jacques

2015-10-01

Small satellites are often used by spatial agencies to meet scientific spatial mission requirements. Their payloads are composed of various instruments collecting an increasing amount of data, as well as respecting the growing constraints relative to volume and mass; So small-sized integrated camera have taken a favored place among these instruments. To ensure scene specific color information sensing, pixelated filters seem to be more attractive than filter wheels. The work presented here, in collaboration with Institut Fresnel, deals with the manufacturing of this kind of component, based on thin film technologies and photolithography processes. CCD detectors with a pixel pitch about 30 μm were considered. In the configuration where the matrix filters are positioned the closest to the detector, the matrix filters are composed of 2x2 macro pixels (e.g. 4 filters). These 4 filters have a bandwidth about 40 nm and are respectively centered at 550, 700, 770 and 840 nm with a specific rejection rate defined on the visible spectral range [500 - 900 nm]. After an intense design step, 4 thin-film structures have been elaborated with a maximum thickness of 5 μm. A run of tests has allowed us to choose the optimal micro-structuration parameters. The 100x100 matrix filters prototypes have been successfully manufactured with lift-off and ion assisted deposition processes. High spatial and spectral characterization, with a dedicated metrology bench, showed that initial specifications and simulations were globally met. These excellent performances knock down the technological barriers for high-end integrated specific multi spectral imaging.

MOnthly TEmperature DAtabase of Spain 1951-2010: MOTEDAS (2): The Correlation Decay Distance (CDD) and the spatial variability of maximum and minimum monthly temperature in Spain during (1981-2010).

NASA Astrophysics Data System (ADS)

Cortesi, Nicola; Peña-Angulo, Dhais; Simolo, Claudia; Stepanek, Peter; Brunetti, Michele; Gonzalez-Hidalgo, José Carlos

2014-05-01

One of the key point in the develop of the MOTEDAS dataset (see Poster 1 MOTEDAS) in the framework of the HIDROCAES Project (Impactos Hidrológicos del Calentamiento Global en España, Spanish Ministery of Research CGL2011-27574-C02-01) is the reference series for which no generalized metadata exist. In this poster we present an analysis of spatial variability of monthly minimum and maximum temperatures in the conterminous land of Spain (Iberian Peninsula, IP), by using the Correlation Decay Distance function (CDD), with the aim of evaluating, at sub-regional level, the optimal threshold distance between neighbouring stations for producing the set of reference series used in the quality control (see MOTEDAS Poster 1) and the reconstruction (see MOREDAS Poster 3). The CDD analysis for Tmax and Tmin was performed calculating a correlation matrix at monthly scale between 1981-2010 among monthly mean values of maximum (Tmax) and minimum (Tmin) temperature series (with at least 90% of data), free of anomalous data and homogenized (see MOTEDAS Poster 1), obtained from AEMEt archives (National Spanish Meteorological Agency). Monthly anomalies (difference between data and mean 1981-2010) were used to prevent the dominant effect of annual cycle in the CDD annual estimation. For each station, and time scale, the common variance r2 (using the square of Pearson's correlation coefficient) was calculated between all neighbouring temperature series and the relation between r2 and distance was modelled according to the following equation (1): Log (r2ij) = b*°dij (1) being Log(rij2) the common variance between target (i) and neighbouring series (j), dij the distance between them and b the slope of the ordinary least-squares linear regression model applied taking into account only the surrounding stations within a starting radius of 50 km and with a minimum of 5 stations required. Finally, monthly, seasonal and annual CDD values were interpolated using the Ordinary Kriging with a spherical variogram over conterminous land of Spain, and converted on a regular 10 km2 grid (resolution similar to the mean distance between stations) to map the results. In the conterminous land of Spain the distance at which couples of stations have a common variance in temperature (both maximum Tmax, and minimum Tmin) above the selected threshold (50%, r Pearson ~0.70) on average does not exceed 400 km, with relevant spatial and temporal differences. The spatial distribution of the CDD shows a clear coastland-to-inland gradient at annual, seasonal and monthly scale, with highest spatial variability along the coastland areas and lower variability inland. The highest spatial variability coincide particularly with coastland areas surrounded by mountain chains and suggests that the orography is one of the most driving factor causing higher interstation variability. Moreover, there are some differences between the behaviour of Tmax and Tmin, being Tmin spatially more homogeneous than Tmax, but its lower CDD values indicate that night-time temperature is more variable than diurnal one. The results suggest that in general local factors affects the spatial variability of monthly Tmin more than Tmax and then higher network density would be necessary to capture the higher spatial variability highlighted for Tmin respect to Tmax. The results suggest that in general local factors affects the spatial variability of Tmin more than Tmax and then higher network density would be necessary to capture the higher spatial variability highlighted for minimum temperature respect to maximum temperature. A conservative distance for reference series could be evaluated in 200 km, that we propose for continental land of Spain and use in the development of MOTEDAS.

Simulation of speckle patterns with pre-defined correlation distributions.

PubMed

Song, Lipei; Zhou, Zhen; Wang, Xueyan; Zhao, Xing; Elson, Daniel S

2016-03-01

We put forward a method to easily generate a single or a sequence of fully developed speckle patterns with pre-defined correlation distribution by utilizing the principle of coherent imaging. The few-to-one mapping between the input correlation matrix and the correlation distribution between simulated speckle patterns is realized and there is a simple square relationship between the values of these two correlation coefficient sets. This method is demonstrated both theoretically and experimentally. The square relationship enables easy conversion from any desired correlation distribution. Since the input correlation distribution can be defined by a digital matrix or a gray-scale image acquired experimentally, this method provides a convenient way to simulate real speckle-related experiments and to evaluate data processing techniques.

Simulation of speckle patterns with pre-defined correlation distributions

PubMed Central

Song, Lipei; Zhou, Zhen; Wang, Xueyan; Zhao, Xing; Elson, Daniel S.

2016-01-01

We put forward a method to easily generate a single or a sequence of fully developed speckle patterns with pre-defined correlation distribution by utilizing the principle of coherent imaging. The few-to-one mapping between the input correlation matrix and the correlation distribution between simulated speckle patterns is realized and there is a simple square relationship between the values of these two correlation coefficient sets. This method is demonstrated both theoretically and experimentally. The square relationship enables easy conversion from any desired correlation distribution. Since the input correlation distribution can be defined by a digital matrix or a gray-scale image acquired experimentally, this method provides a convenient way to simulate real speckle-related experiments and to evaluate data processing techniques. PMID:27231589

Classification Features of US Images Liver Extracted with Co-occurrence Matrix Using the Nearest Neighbor Algorithm

NASA Astrophysics Data System (ADS)

Moldovanu, Simona; Bibicu, Dorin; Moraru, Luminita; Nicolae, Mariana Carmen

2011-12-01

Co-occurrence matrix has been applied successfully for echographic images characterization because it contains information about spatial distribution of grey-scale levels in an image. The paper deals with the analysis of pixels in selected regions of interest of an US image of the liver. The useful information obtained refers to texture features such as entropy, contrast, dissimilarity and correlation extract with co-occurrence matrix. The analyzed US images were grouped in two distinct sets: healthy liver and steatosis (or fatty) liver. These two sets of echographic images of the liver build a database that includes only histological confirmed cases: 10 images of healthy liver and 10 images of steatosis liver. The healthy subjects help to compute four textural indices and as well as control dataset. We chose to study these diseases because the steatosis is the abnormal retention of lipids in cells. The texture features are statistical measures and they can be used to characterize irregularity of tissues. The goal is to extract the information using the Nearest Neighbor classification algorithm. The K-NN algorithm is a powerful tool to classify features textures by means of grouping in a training set using healthy liver, on the one hand, and in a holdout set using the features textures of steatosis liver, on the other hand. The results could be used to quantify the texture information and will allow a clear detection between health and steatosis liver.

Noise-immune complex correlation for vasculature imaging based on standard and Jones-matrix optical coherence tomography

NASA Astrophysics Data System (ADS)

Makita, Shuichi; Kurokawa, Kazuhiro; Hong, Young-Joo; Li, En; Miura, Masahiro; Yasuno, Yoshiaki

2016-03-01

A new optical coherence angiography (OCA) method, called correlation mapping OCA (cmOCA), is presented by using the SNR-corrected complex correlation. An SNR-correction theory for the complex correlation calculation is presented. The method also integrates a motion-artifact-removal method for the sample motion induced decorrelation artifact. The theory is further extended to compute more reliable correlation by using multi- channel OCT systems, such as Jones-matrix OCT. The high contrast vasculature imaging of in vivo human posterior eye has been obtained. Composite imaging of cmOCA and degree of polarization uniformity indicates abnormalities of vasculature and pigmented tissues simultaneously.

On the influence of surface patterning on tissue self-assembly and mechanics.

PubMed

Coppola, Valerio; Ventre, Maurizio; Natale, Carlo F; Rescigno, Francesca; Netti, Paolo A

2018-04-28

Extracellular matrix assembly and composition influence the biological and mechanical functions of tissues. Developing strategies to control the spatial arrangement of cells and matrix is of central importance for tissue engineering-related approaches relying on self-assembling and scaffoldless processes. Literature reports demonstrated that signals patterned on material surfaces are able to control cell positioning and matrix orientation. However, the mechanisms underlying the interactions between material signals and the structure of the de novo synthesized matrix are far from being thoroughly understood. In this work, we investigated the ordering effect provided by nanoscale topographic patterns on the assembly of tissue sheets grown in vitro. We stimulated MC3T3-E1 preosteoblasts to produce and assemble a collagen-rich matrix on substrates displaying patterns with long- or short-range order. Then, we investigated microstructural features and mechanical properties of the tissue in uniaxial tension. Our results demonstrate that patterned material surfaces are able to control the initial organization of cells in close contact to the surface; then cell-generated contractile forces profoundly remodel tissue structure towards mechanically stable spatial patterns. Such a remodelling effect acts both locally, as it affects cell and nuclear shape and globally, by affecting the gross mechanical response of the tissue. Such an aspect of dynamic interplay between cells and the surrounding matrix must be taken into account when designing material platform for the in vitro generation of tissue with specific microstructural assemblies. Copyright © 2018 John Wiley & Sons, Ltd.

Cortical dipole imaging using truncated total least squares considering transfer matrix error.

PubMed

Hori, Junichi; Takeuchi, Kosuke

2013-01-01

Cortical dipole imaging has been proposed as a method to visualize electroencephalogram in high spatial resolution. We investigated the inverse technique of cortical dipole imaging using a truncated total least squares (TTLS). The TTLS is a regularization technique to reduce the influence from both the measurement noise and the transfer matrix error caused by the head model distortion. The estimation of the regularization parameter was also investigated based on L-curve. The computer simulation suggested that the estimation accuracy was improved by the TTLS compared with Tikhonov regularization. The proposed method was applied to human experimental data of visual evoked potentials. We confirmed the TTLS provided the high spatial resolution of cortical dipole imaging.

Imaging bolometer

DOEpatents

Wurden, G.A.

1999-01-19

Radiation-hard, steady-state imaging bolometer is disclosed. A bolometer employing infrared (IR) imaging of a segmented-matrix absorber of plasma radiation in a cooled-pinhole camera geometry is described. The bolometer design parameters are determined by modeling the temperature of the foils from which the absorbing matrix is fabricated by using a two-dimensional time-dependent solution of the heat conduction equation. The resulting design will give a steady-state bolometry capability, with approximately 100 Hz time resolution, while simultaneously providing hundreds of channels of spatial information. No wiring harnesses will be required, as the temperature-rise data will be measured via an IR camera. The resulting spatial data may be used to tomographically investigate the profile of plasmas. 2 figs.

Imaging bolometer

DOEpatents

Wurden, Glen A.

1999-01-01

Radiation-hard, steady-state imaging bolometer. A bolometer employing infrared (IR) imaging of a segmented-matrix absorber of plasma radiation in a cooled-pinhole camera geometry is described. The bolometer design parameters are determined by modeling the temperature of the foils from which the absorbing matrix is fabricated by using a two-dimensional time-dependent solution of the heat conduction equation. The resulting design will give a steady-state bolometry capability, with approximately 100 Hz time resolution, while simultaneously providing hundreds of channels of spatial information. No wiring harnesses will be required, as the temperature-rise data will be measured via an IR camera. The resulting spatial data may be used to tomographically investigate the profile of plasmas.

[Temporal and spatial characteristics of ecological risk in Shunyi, Beijing, China based on landscape structure.

PubMed

Qing, Feng Ting; Peng, Yu

2016-05-01

Based on the remote sensing data in 1997, 2001, 2005, 2009 and 2013, this article classified the landscape types of Shunyi, and the ecological risk index was built based on landscape disturbance index and landscape fragility. The spatial auto-correlation and geostatistical analysis by GS + and ArcGIS was used to study temporal and spatial changes of ecological risk. The results showed that eco-risk degree in the study region had positive spatial correlation which decreased with the increasing grain size. Within a certain grain range (<12 km), the spatial auto-correlation had an obvious dependence on scale. The random variation of spatial heterogeneity was less than spatial auto-correlation variation from 1997 to 2013, which meant the auto-correlation had a dominant role in spatial heterogeneity. The ecological risk of Shunyi was mainly at moderate level during the study period. The area of the district with higher and lower ecological risk increased, while that of mode-rate ecological risk decreased. The area with low ecological risk was mainly located in the airport region and forest of southeast Shunyi, while that with high ecological risk was mainly concentrated in the water landscape, such as the banks of Chaobai River.

EVALUATING EFFECTS OF LOW QUALITY HABITATS ON REGIONAL GROWTH IN PEOMYCUS LEUCOPUS: INSIGHTS FROM FIELD-PARAMETERIZED SPATIAL MATRIX MODELS.

EPA Science Inventory

Due to complex population dynamics and source-sink metapopulation processes, animal fitness sometimes varies across landscapes in ways that cannot be deduced from simple density patterns. In this study, we examine spatial patterns in fitness using a combination of intensive fiel...

Staring 2-D hadamard transform spectral imager

DOEpatents

Gentry, Stephen M [Albuquerque, NM; Wehlburg, Christine M [Albuquerque, NM; Wehlburg, Joseph C [Albuquerque, NM; Smith, Mark W [Albuquerque, NM; Smith, Jody L [Albuquerque, NM

2006-02-07

A staring imaging system inputs a 2D spatial image containing multi-frequency spectral information. This image is encoded in one dimension of the image with a cyclic Hadamarid S-matrix. The resulting image is detecting with a spatial 2D detector; and a computer applies a Hadamard transform to recover the encoded image.

Using temporal detrending to observe the spatial correlation of traffic.

PubMed

Ermagun, Alireza; Chatterjee, Snigdhansu; Levinson, David

2017-01-01

This empirical study sheds light on the spatial correlation of traffic links under different traffic regimes. We mimic the behavior of real traffic by pinpointing the spatial correlation between 140 freeway traffic links in a major sub-network of the Minneapolis-St. Paul freeway system with a grid-like network topology. This topology enables us to juxtapose the positive and negative correlation between links, which has been overlooked in short-term traffic forecasting models. To accurately and reliably measure the correlation between traffic links, we develop an algorithm that eliminates temporal trends in three dimensions: (1) hourly dimension, (2) weekly dimension, and (3) system dimension for each link. The spatial correlation of traffic links exhibits a stronger negative correlation in rush hours, when congestion affects route choice. Although this correlation occurs mostly in parallel links, it is also observed upstream, where travelers receive information and are able to switch to substitute paths. Irrespective of the time-of-day and day-of-week, a strong positive correlation is witnessed between upstream and downstream links. This correlation is stronger in uncongested regimes, as traffic flow passes through consecutive links more quickly and there is no congestion effect to shift or stall traffic. The extracted spatial correlation structure can augment the accuracy of short-term traffic forecasting models.

Using temporal detrending to observe the spatial correlation of traffic

PubMed Central

2017-01-01

This empirical study sheds light on the spatial correlation of traffic links under different traffic regimes. We mimic the behavior of real traffic by pinpointing the spatial correlation between 140 freeway traffic links in a major sub-network of the Minneapolis—St. Paul freeway system with a grid-like network topology. This topology enables us to juxtapose the positive and negative correlation between links, which has been overlooked in short-term traffic forecasting models. To accurately and reliably measure the correlation between traffic links, we develop an algorithm that eliminates temporal trends in three dimensions: (1) hourly dimension, (2) weekly dimension, and (3) system dimension for each link. The spatial correlation of traffic links exhibits a stronger negative correlation in rush hours, when congestion affects route choice. Although this correlation occurs mostly in parallel links, it is also observed upstream, where travelers receive information and are able to switch to substitute paths. Irrespective of the time-of-day and day-of-week, a strong positive correlation is witnessed between upstream and downstream links. This correlation is stronger in uncongested regimes, as traffic flow passes through consecutive links more quickly and there is no congestion effect to shift or stall traffic. The extracted spatial correlation structure can augment the accuracy of short-term traffic forecasting models. PMID:28472093

Multireference quantum chemistry through a joint density matrix renormalization group and canonical transformation theory.

PubMed

Yanai, Takeshi; Kurashige, Yuki; Neuscamman, Eric; Chan, Garnet Kin-Lic

2010-01-14

We describe the joint application of the density matrix renormalization group and canonical transformation theory to multireference quantum chemistry. The density matrix renormalization group provides the ability to describe static correlation in large active spaces, while the canonical transformation theory provides a high-order description of the dynamic correlation effects. We demonstrate the joint theory in two benchmark systems designed to test the dynamic and static correlation capabilities of the methods, namely, (i) total correlation energies in long polyenes and (ii) the isomerization curve of the [Cu(2)O(2)](2+) core. The largest complete active spaces and atomic orbital basis sets treated by the joint DMRG-CT theory in these systems correspond to a (24e,24o) active space and 268 atomic orbitals in the polyenes and a (28e,32o) active space and 278 atomic orbitals in [Cu(2)O(2)](2+).

Model correlation and damage location for large space truss structures: Secant method development and evaluation

NASA Technical Reports Server (NTRS)

Smith, Suzanne Weaver; Beattie, Christopher A.

1991-01-01

On-orbit testing of a large space structure will be required to complete the certification of any mathematical model for the structure dynamic response. The process of establishing a mathematical model that matches measured structure response is referred to as model correlation. Most model correlation approaches have an identification technique to determine structural characteristics from the measurements of the structure response. This problem is approached with one particular class of identification techniques - matrix adjustment methods - which use measured data to produce an optimal update of the structure property matrix, often the stiffness matrix. New methods were developed for identification to handle problems of the size and complexity expected for large space structures. Further development and refinement of these secant-method identification algorithms were undertaken. Also, evaluation of these techniques is an approach for model correlation and damage location was initiated.

[Spatial scale effect of land use landscape pattern in Yongdeng County, Gansu Province, China.

PubMed

Liu, Yuan Yuan; Liu, Xue Lu

2016-04-22

Based on "patch-corridor-matrix" pattern, spatial scale effect of landscape pattern was studied in Yongdeng County of Lanzhou City, Gansu Province, China. The results showed that the grassland was the matrix of landscape structure in the studied area, road and river played the corridor role, and the other landscape elements (cultivated land, forest land, garden land, residential land, industrial and mineral land, public management and service land, and the other land) acted as patches. The patch level index and the landscape level index all showed obvious dependence on spatial extent. The scale effect of patch index of different landscape elements existed differently in different extent intervals, so did the scale effect of the landscape level index. Within the extent of 1-20 km, the scale effect showed the most obvious difference between the element types and the index types, while it became smaller in 21-90 km, and disappeared beyond 90 km. 90 km×90 km might be the effective extent to study the dependence of spatial extent of landscape structure.

Cross-section fluctuations in chaotic scattering systems.

PubMed

Ericson, Torleif E O; Dietz, Barbara; Richter, Achim

2016-10-01

Exact analytical expressions for the cross-section correlation functions of chaotic scattering systems have hitherto been derived only under special conditions. The objective of the present article is to provide expressions that are applicable beyond these restrictions. The derivation is based on a statistical model of Breit-Wigner type for chaotic scattering amplitudes which has been shown to describe the exact analytical results for the scattering (S)-matrix correlation functions accurately. Our results are given in the energy and in the time representations and apply in the whole range from isolated to overlapping resonances. The S-matrix contributions to the cross-section correlations are obtained in terms of explicit irreducible and reducible correlation functions. Consequently, the model can be used for a detailed exploration of the key features of the cross-section correlations and the underlying physical mechanisms. In the region of isolated resonances, the cross-section correlations contain a dominant contribution from the self-correlation term. For narrow states the self-correlations originate predominantly from widely spaced states with exceptionally large partial width. In the asymptotic region of well-overlapping resonances, the cross-section autocorrelation functions are given in terms of the S-matrix autocorrelation functions. For inelastic correlations, in particular, the Ericson fluctuations rapidly dominate in that region. Agreement with known analytical and experimental results is excellent.

Aggregation of carbon dioxide sequestration storage assessment units

USGS Publications Warehouse

Blondes, Madalyn S.; Schuenemeyer, John H.; Olea, Ricardo A.; Drew, Lawrence J.

2013-01-01

The U.S. Geological Survey is currently conducting a national assessment of carbon dioxide (CO2) storage resources, mandated by the Energy Independence and Security Act of 2007. Pre-emission capture and storage of CO2 in subsurface saline formations is one potential method to reduce greenhouse gas emissions and the negative impact of global climate change. Like many large-scale resource assessments, the area under investigation is split into smaller, more manageable storage assessment units (SAUs), which must be aggregated with correctly propagated uncertainty to the basin, regional, and national scales. The aggregation methodology requires two types of data: marginal probability distributions of storage resource for each SAU, and a correlation matrix obtained by expert elicitation describing interdependencies between pairs of SAUs. Dependencies arise because geologic analogs, assessment methods, and assessors often overlap. The correlation matrix is used to induce rank correlation, using a Cholesky decomposition, among the empirical marginal distributions representing individually assessed SAUs. This manuscript presents a probabilistic aggregation method tailored to the correlations and dependencies inherent to a CO2 storage assessment. Aggregation results must be presented at the basin, regional, and national scales. A single stage approach, in which one large correlation matrix is defined and subsets are used for different scales, is compared to a multiple stage approach, in which new correlation matrices are created to aggregate intermediate results. Although the single-stage approach requires determination of significantly more correlation coefficients, it captures geologic dependencies among similar units in different basins and it is less sensitive to fluctuations in low correlation coefficients than the multiple stage approach. Thus, subsets of one single-stage correlation matrix are used to aggregate to basin, regional, and national scales.

An examination of relationship between neurological soft signs and neurocognition.

PubMed

Solanki, Ram Kumar; Swami, Mukesh Kumar; Singh, Paramjeet

2012-03-01

Neurological soft signs (NSS) and cognitive function had been examined in schizophrenia, but their relationship has remained elusive for several years. We examined the relationship between NSS and cognitive functions in the present study. A cross sectional study was carried out. Subjects were drawn from first degree relatives of schizophrenia patients, admitted as inpatient or attending as an outpatient. Controls were recruited by word of mouth from hospital staff and visitors of hospitalized patients. Those subjects who satisfied the screening process were subjected to Cambridge Neurological Inventory for soft sign assessment and digit span test, paired associate learning test (PALT) and visuo-spatial working memory matrix (VSWMM) for cognitive function assessment. Correlation analysis and structural equation modeling (SEM) was used for analysis. Significant negative correlation of primitive reflexes with PALT; of motor coordination with VSWMM, working memory (WM) and cognitive index; of total NSS with WM and cognitive index among first degree relatives. SEM showed that motor soft signs have important negative influence over WM. The current findings indicate that NSS have significant negative effect on cognitive functioning. Copyright © 2011 Elsevier B.V. All rights reserved.

A highly distributed Bragg stack with unique geometry provides effective camouflage for Loliginid squid eyes

PubMed Central

Holt, Amanda L.; Sweeney, Alison M.; Johnsen, Sönke; Morse, Daniel E.

2011-01-01

Cephalopods possess a sophisticated array of mechanisms to achieve camouflage in dynamic underwater environments. While active mechanisms such as chromatophore patterning and body posturing are well known, passive mechanisms such as manipulating light with highly evolved reflectors may also play an important role. To explore the contribution of passive mechanisms to cephalopod camouflage, we investigated the optical and biochemical properties of the silver layer covering the eye of the California fishery squid, Loligo opalescens. We discovered a novel nested-spindle geometry whose correlated structure effectively emulates a randomly distributed Bragg reflector (DBR), with a range of spatial frequencies resulting in broadband visible reflectance, making it a nearly ideal passive camouflage material for the depth at which these animals live. We used the transfer-matrix method of optical modelling to investigate specular reflection from the spindle structures, demonstrating that a DBR with widely distributed thickness variations of high refractive index elements is sufficient to yield broadband reflectance over visible wavelengths, and that unlike DBRs with one or a few spatial frequencies, this broadband reflectance occurs from a wide range of viewing angles. The spindle shape of the cells may facilitate self-assembly of a random DBR to achieve smooth spatial distributions in refractive indices. This design lends itself to technological imitation to achieve a DBR with wide range of smoothly varying layer thicknesses in a facile, inexpensive manner. PMID:21325315

Habitat fragmentation effects on the orchid bee communities in remnant forests of southeastern Brazil.

PubMed

Knoll, Fátima do Rosário Naschenveng; Penatti, N C

2012-10-01

The effect of habitat fragmentation on the structure of orchid bee communities was analyzed by the investigation of the existence of a spatial structure in the richness and abundance of Euglossini species and by determining the relationship between these data and environmental factors. The surveys were carried out in four different forest fragments and one university campus. Richness, abundance, and diversity of species were analyzed in relation to abiotic (size of the area, extent of the perimeter, perimeter/area ratio, and shape index) and biotic characteristics (vegetation index of the fragment and of the matrix of each of the locations studied). We observed a highly significant positive correlation between the diversity index and the vegetation index of the fragment, landscape and shape index. Our analysis demonstrated that the observed variation could be explained mainly by the vegetation index and the size of the fragment. Variations in relative abundance showed a tendency toward an aggregated spatial distribution between the fragments studied, as well as between the sampling stations within the same habitat, demonstrating the existence of a spatial structure on a small scale in the populations of Euglossini. This distribution will determine the composition of species that coexist in the area after fragmentation. These data help in understanding the differences and similarities in the structure of communities of Euglossini resulting from forest fragmentation.

Dispersion curve estimation via a spatial covariance method with ultrasonic wavefield imaging.

PubMed

Chong, See Yenn; Todd, Michael D

2018-05-01

Numerous Lamb wave dispersion curve estimation methods have been developed to support damage detection and localization strategies in non-destructive evaluation/structural health monitoring (NDE/SHM) applications. In this paper, the covariance matrix is used to extract features from an ultrasonic wavefield imaging (UWI) scan in order to estimate the phase and group velocities of S0 and A0 modes. A laser ultrasonic interrogation method based on a Q-switched laser scanning system was used to interrogate full-field ultrasonic signals in a 2-mm aluminum plate at five different frequencies. These full-field ultrasonic signals were processed in three-dimensional space-time domain. Then, the time-dependent covariance matrices of the UWI were obtained based on the vector variables in Cartesian and polar coordinate spaces for all time samples. A spatial covariance map was constructed to show spatial correlations within the full wavefield. It was observed that the variances may be used as a feature for S0 and A0 mode properties. The phase velocity and the group velocity were found using a variance map and an enveloped variance map, respectively, at five different frequencies. This facilitated the estimation of Lamb wave dispersion curves. The estimated dispersion curves of the S0 and A0 modes showed good agreement with the theoretical dispersion curves. Copyright © 2018 Elsevier B.V. All rights reserved.

Spatial correlation in precipitation trends in the Brazilian Amazon

NASA Astrophysics Data System (ADS)

Buarque, Diogo Costa; Clarke, Robin T.; Mendes, Carlos Andre Bulhoes

2010-06-01

A geostatistical analysis of variables derived from Amazon daily precipitation records (trends in annual precipitation totals, trends in annual maximum precipitation accumulated over 1-5 days, trend in length of dry spell, trend in number of wet days per year) gave results that are consistent with those previously reported. Averaged over the Brazilian Amazon region as a whole, trends in annual maximum precipitations were slightly negative, the trend in the length of dry spell was slightly positive, and the trend in the number of wet days in the year was slightly negative. For trends in annual maximum precipitation accumulated over 1-5 days, spatial correlation between trends was found to extend up to a distance equivalent to at least half a degree of latitude or longitude, with some evidence of anisotropic correlation. Time trends in annual precipitation were found to be spatially correlated up to at least ten degrees of separation, in both W-E and S-N directions. Anisotropic spatial correlation was strongly evident in time trends in length of dry spell with much stronger evidence of spatial correlation in the W-E direction, extending up to at least five degrees of separation, than in the S-N. Because the time trends analyzed are shown to be spatially correlated, it is argued that methods at present widely used to test the statistical significance of climate trends over time lead to erroneous conclusions if spatial correlation is ignored, because records from different sites are assumed to be statistically independent.

Effect of landscape matrix type on nesting ecology of the Northern Cardinal

Treesearch

R.A. Sargent; J.C. Kilgo; B.R. Chapman; K.V. Miller

2015-01-01

Spatial distribution of forests relative to other habitats in a landscape may influence nest success of songbirds. For example, nest predation in mature forests increases as the percentage of clear-cut land in the surrounding matrix increases (Yahner and Scott 1988). Blake and Karr (1987) noted that birds breeding in forest fragments may incorporate adjacent habitats,...

Unifying research on the fragmentation of terrestrial and aquatic habitats: patches, connectivity and the matrix in riverscapes

USGS Publications Warehouse

Eros, Tibor; Grant, Evan H. Campbell

2015-01-01

Fragmentation of habitats is a critical issue in the conservation and management of stream networks across spatial scales. Although the effects of individual barriers (e.g. dams) are well documented, we argue that a more comprehensive patch–matrix landscape model will improve our understanding of fragmentation effects and improve management in riverscapes.

Magnetic resonance microscopy for assessment of morphological changes in hydrating hydroxypropylmethyl cellulose matrix tablets in situ.

PubMed

Kulinowski, Piotr; Młynarczyk, Anna; Dorożyński, Przemysław; Jasiński, Krzysztof; Gruwel, Marco L H; Tomanek, Bogusław; Węglarz, Władysław P

2012-12-01

To resolve contradictions found in morphology of hydrating hydroxypropylmethyl cellulose (HPMC) matrix as studied using Magnetic Resonance Imaging (MRI) techniques. Until now, two approaches were used in the literature: either two or three regions that differ in physicochemical properties were identified. Multiparametric, spatially and temporally resolved T(2) MR relaxometry in situ was applied to study the hydration progress in HPMC matrix tablets using a 11.7 T MRI system. Two spin-echo based pulse sequences-one of them designed to specifically study short T(2) signals-were used. Two components in the T(2) decay envelope were estimated and spatial distributions of their parameters, i.e. amplitudes and T(2) values, were obtained. Based on the data, five different regions and their temporal evolution were identified: dry glassy, hydrated solid like, two interface layers and gel layer. The regions were found to be separated by four evolving fronts identified as penetration, full hydration, total gelification and apparent erosion. The MRI results showed morphological details of the hydrating HPMC matrices matching compound theoretical models. The proposed method will allow for adequate evaluation of controlled release polymeric matrix systems loaded with drug substances of different solubility.

The cost of space independence in P300-BCI spellers.

PubMed

Chennu, Srivas; Alsufyani, Abdulmajeed; Filetti, Marco; Owen, Adrian M; Bowman, Howard

2013-07-29

Though non-invasive EEG-based Brain Computer Interfaces (BCI) have been researched extensively over the last two decades, most designs require control of spatial attention and/or gaze on the part of the user. In healthy adults, we compared the offline performance of a space-independent P300-based BCI for spelling words using Rapid Serial Visual Presentation (RSVP), to the well-known space-dependent Matrix P300 speller. EEG classifiability with the RSVP speller was as good as with the Matrix speller. While the Matrix speller's performance was significantly reliant on early, gaze-dependent Visual Evoked Potentials (VEPs), the RSVP speller depended only on the space-independent P300b. However, there was a cost to true spatial independence: the RSVP speller was less efficient in terms of spelling speed. The advantage of space independence in the RSVP speller was concomitant with a marked reduction in spelling efficiency. Nevertheless, with key improvements to the RSVP design, truly space-independent BCIs could approach efficiencies on par with the Matrix speller. With sufficiently high letter spelling rates fused with predictive language modelling, they would be viable for potential applications with patients unable to direct overt visual gaze or covert attentional focus.

Computationally Efficient Adaptive Beamformer for Ultrasound Imaging Based on QR Decomposition.

PubMed

Park, Jongin; Wi, Seok-Min; Lee, Jin S

2016-02-01

Adaptive beamforming methods for ultrasound imaging have been studied to improve image resolution and contrast. The most common approach is the minimum variance (MV) beamformer which minimizes the power of the beamformed output while maintaining the response from the direction of interest constant. The method achieves higher resolution and better contrast than the delay-and-sum (DAS) beamformer, but it suffers from high computational cost. This cost is mainly due to the computation of the spatial covariance matrix and its inverse, which requires O(L(3)) computations, where L denotes the subarray size. In this study, we propose a computationally efficient MV beamformer based on QR decomposition. The idea behind our approach is to transform the spatial covariance matrix to be a scalar matrix σI and we subsequently obtain the apodization weights and the beamformed output without computing the matrix inverse. To do that, QR decomposition algorithm is used and also can be executed at low cost, and therefore, the computational complexity is reduced to O(L(2)). In addition, our approach is mathematically equivalent to the conventional MV beamformer, thereby showing the equivalent performances. The simulation and experimental results support the validity of our approach.

Protein addressing on patterned microchip by coupling chitosan electrodeposition and 'electro-click' chemistry.

PubMed

Shi, Xiao-Wen; Qiu, Ling; Nie, Zhen; Xiao, Ling; Payne, Gregory F; Du, Yumin

2013-12-01

Many applications in proteomics and lab-on-chip analysis require methods that guide proteins to assemble at surfaces with high spatial and temporal control. Electrical inputs are particularly convenient to control, and there has been considerable effort to discover simple and generic mechanisms that allow electrical inputs to trigger protein assembly on-demand. Here, we report the electroaddressing of a protein to a patterned surface by coupling two generic electroaddressing mechanisms. First, we electrodeposit the stimuli-responsive film-forming aminopolysaccharide chitosan to form a hydrogel matrix at the electrode surface. After deposition, the matrix is chemically functionalized with alkyne groups. Second, we ''electro-click' an azide-tagged protein to the functionalized matrix using electrical signals to trigger conjugation by Huisgen 1,3-dipolar cycloadditions. Specifically, a cathodic potential is applied to the matrix-coated electrode to reduce Cu(II) to Cu(I) which is required for the click reaction. Using fluorescently-labeled bovine serum albumin as our model, we demonstrate that protein conjugation can be controlled spatially and temporally. We anticipate that the coupling of polysaccharide electrodeposition and electro-click chemistry will provide a simple and generic approach to electroaddress proteins within compatible hydrogel matrices.

Network trending; leadership, followership and neutrality among companies: A random matrix approach

NASA Astrophysics Data System (ADS)

Mobarhan, N. S. Safavi; Saeedi, A.; Roodposhti, F. Rahnamay; Jafari, G. R.

2016-11-01

In this article, we analyze the cross-correlation between returns of different stocks to answer the following important questions. The first one is: If there exists collective behavior in a financial market, how could we detect it? And the second question is: Is there a particular company among the companies of a market as the leader of the collective behavior? Or is there no specified leadership governing the system similar to some complex systems? We use the method of random matrix theory to answer the mentioned questions. Cross-correlation matrix of index returns of four different markets is analyzed. The participation ratio quantity related to each matrices' eigenvectors and the eigenvalue spectrum is calculated. We introduce shuffled-matrix created of cross correlation matrix in such a way that the elements of the later one are displaced randomly. Comparing the participation ratio quantities obtained from a correlation matrix of a market and its related shuffled-one, on the bulk distribution region of the eigenvalues, we detect a meaningful deviation between the mentioned quantities indicating the collective behavior of the companies forming the market. By calculating the relative deviation of participation ratios, we obtain a measure to compare the markets according to their collective behavior. Answering the second question, we show there are three groups of companies: The first group having higher impact on the market trend called leaders, the second group is followers and the third one is the companies who have not a considerable role in the trend. The results can be utilized in portfolio construction.

Role of quantum coherence in shaping the line shape of an exciton interacting with a spatially and temporally correlated bath

PubMed Central

Dutta, Rajesh; Bagchi, Kaushik

2017-01-01

Kubo’s fluctuation theory of line shape forms the backbone of our understanding of optical and vibrational line shapes, through such concepts as static heterogeneity and motional narrowing. However, the theory does not properly address the effects of quantum coherences on optical line shape, especially in extended systems where a large number of eigenstates are present. In this work, we study the line shape of an exciton in a one-dimensional lattice consisting of regularly placed and equally separated optical two level systems. We consider both linear array and cyclic ring systems of different sizes. Detailed analytical calculations of line shape have been carried out by using Kubo’s stochastic Liouville equation (SLE). We make use of the observation that in the site representation, the Hamiltonian of our system with constant off-diagonal coupling J is a tridiagonal Toeplitz matrix (TDTM) whose eigenvalues and eigenfunctions are known analytically. This identification is particularly useful for long chains where the eigenvalues of TDTM help understanding crossover between static and fast modulation limits. We summarize the new results as follows. (i) In the slow modulation limit when the bath correlation time is large, the effects of spatial correlation are not negligible. Here the line shape is broadened and the number of peaks increases beyond the ones obtained from TDTM (constant off-diagonal coupling element J and no fluctuation). (ii) However, in the fast modulation limit when the bath correlation time is small, the spatial correlation is less important. In this limit, the line shape shows motional narrowing with peaks at the values predicted by TDTM (constant J and no fluctuation). (iii) Importantly, we find that the line shape can capture that quantum coherence affects in the two limits differently. (iv) In addition to linear chains of two level systems, we also consider a cyclic tetramer. The cyclic polymers can be designed for experimental verification. (v) We also build a connection between line shape and population transfer dynamics. In the fast modulation limit, both the line shape and the population relaxation, for both correlated and uncorrelated bath, show similar behavior. However, in slow modulation limit, they show profoundly different behavior. (vi) This study explains the unique role of the rate of fluctuation (inverse of the bath correlation time) in the sustenance and propagation of coherence. We also examine the effects of off-diagonal fluctuation in spectral line shape. Finally, we use Tanimura-Kubo formalism to derive a set of coupled equations to include temperature effects (partly neglected in the SLE employed here) and effects of vibrational mode in energy transfer dynamics. PMID:28527457

Altering textural properties of fermented milk by using surface-engineered Lactococcus lactis.

PubMed

Tarazanova, Mariya; Huppertz, Thom; Kok, Jan; Bachmann, Herwig

2018-05-09

Lactic acid bacteria are widely used for the fermentation of dairy products. While bacterial acidification rates, proteolytic activity and the production of exopolysaccharides are known to influence textural properties of fermented milk products, little is known about the role of the microbial surface on microbe-matrix interactions in dairy products. To investigate how alterations of the bacterial cell surface affect fermented milk properties, 25 isogenic Lactococcus lactis strains that differed with respect to surface charge, hydrophobicity, cell chaining, cell-clumping, attachment to milk proteins, pili expression and EPS production were used to produce fermented milk. We show that overexpression of pili increases surface hydrophobicity of various strains from 3-19% to 94-99%. A profound effect of different cell surface properties was an altered spatial distribution of the cells in the fermented product. Aggregated cells tightly fill the cavities of the protein matrix, while chaining cells seem to be localized randomly. A positive correlation was found between pili overexpression and viscosity and gel hardness of fermented milk. Gel hardness also positively correlated with clumping of cells in the fermented milk. Viscosity of fermented milk was also higher when it was produced with cells with a chaining phenotype or with cells that overexpress exopolysaccharides. Our results show that alteration of cell surface morphology affects textural parameters of fermented milk and cell localization in the product. This is indicative of a cell surface-dependent potential of bacterial cells as structure elements in fermented foods. © 2018 The Authors. Microbial Biotechnology published by John Wiley & Sons Ltd and Society for Applied Microbiology.

Isolation and characterization of chicken bile matrix metalloproteinase

USDA-ARS?s Scientific Manuscript database

Avian bile is rich in matrix metalloproteinases (MMP), the enzymes that cleave extracellular matrix (ECM) proteins such as collagens and proteoglycans. Changes in bile MMP expression have been correlated with hepatic and gall bladder pathologies but the significance of their expression in normal, he...

A Electro-Optical Image Algebra Processing System for Automatic Target Recognition

NASA Astrophysics Data System (ADS)

Coffield, Patrick Cyrus

The proposed electro-optical image algebra processing system is designed specifically for image processing and other related computations. The design is a hybridization of an optical correlator and a massively paralleled, single instruction multiple data processor. The architecture of the design consists of three tightly coupled components: a spatial configuration processor (the optical analog portion), a weighting processor (digital), and an accumulation processor (digital). The systolic flow of data and image processing operations are directed by a control buffer and pipelined to each of the three processing components. The image processing operations are defined in terms of basic operations of an image algebra developed by the University of Florida. The algebra is capable of describing all common image-to-image transformations. The merit of this architectural design is how it implements the natural decomposition of algebraic functions into spatially distributed, point use operations. The effect of this particular decomposition allows convolution type operations to be computed strictly as a function of the number of elements in the template (mask, filter, etc.) instead of the number of picture elements in the image. Thus, a substantial increase in throughput is realized. The implementation of the proposed design may be accomplished in many ways. While a hybrid electro-optical implementation is of primary interest, the benefits and design issues of an all digital implementation are also discussed. The potential utility of this architectural design lies in its ability to control a large variety of the arithmetic and logic operations of the image algebra's generalized matrix product. The generalized matrix product is the most powerful fundamental operation in the algebra, thus allowing a wide range of applications. No other known device or design has made this claim of processing speed and general implementation of a heterogeneous image algebra.

Decay of correlations between cross-polarized electromagnetic waves in a two-dimensional random medium.

PubMed

Gorodnichev, E E

2018-04-01

The problem of multiple scattering of polarized light in a two-dimensional medium composed of fiberlike inhomogeneities is studied. The attenuation lengths for the density matrix elements are calculated. For a highly absorbing medium it is found that, as the sample thickness increases, the intensity of waves polarized along the fibers decays faster than the other density matrix elements. With further increase in the sample thickness, the off-diagonal elements which are responsible for correlations between the cross-polarized waves disappear. In the asymptotic limit of very thick samples the scattered light proves to be polarized perpendicular to the fibers. The difference in the attenuation lengths between the density matrix elements results in a nonmonotonic depth dependence of the degree of polarization. In the opposite case of a weakly absorbing medium, the off-diagonal element of the density matrix and, correspondingly, the correlations between the cross-polarized fields are shown to decay faster than the intensity of waves polarized along and perpendicular to the fibers.

Matrix elements of N-particle explicitly correlated Gaussian basis functions with complex exponential parameters

NASA Astrophysics Data System (ADS)

Bubin, Sergiy; Adamowicz, Ludwik

2006-06-01

In this work we present analytical expressions for Hamiltonian matrix elements with spherically symmetric, explicitly correlated Gaussian basis functions with complex exponential parameters for an arbitrary number of particles. The expressions are derived using the formalism of matrix differential calculus. In addition, we present expressions for the energy gradient that includes derivatives of the Hamiltonian integrals with respect to the exponential parameters. The gradient is used in the variational optimization of the parameters. All the expressions are presented in the matrix form suitable for both numerical implementation and theoretical analysis. The energy and gradient formulas have been programed and used to calculate ground and excited states of the He atom using an approach that does not involve the Born-Oppenheimer approximation.

Matrix elements of N-particle explicitly correlated Gaussian basis functions with complex exponential parameters.

PubMed

Bubin, Sergiy; Adamowicz, Ludwik

2006-06-14

In this work we present analytical expressions for Hamiltonian matrix elements with spherically symmetric, explicitly correlated Gaussian basis functions with complex exponential parameters for an arbitrary number of particles. The expressions are derived using the formalism of matrix differential calculus. In addition, we present expressions for the energy gradient that includes derivatives of the Hamiltonian integrals with respect to the exponential parameters. The gradient is used in the variational optimization of the parameters. All the expressions are presented in the matrix form suitable for both numerical implementation and theoretical analysis. The energy and gradient formulas have been programmed and used to calculate ground and excited states of the He atom using an approach that does not involve the Born-Oppenheimer approximation.

System of multifunctional Jones matrix tomography of phase anisotropy in diagnostics of endometriosis

NASA Astrophysics Data System (ADS)

Ushenko, V. O.; Koval, G. D.; Ushenko, Yu. O.; Pidkamin, L. Y.; Sidor, M. I.; Vanchuliak, O.; Motrich, A. V.; Gorsky, M. P.; Meglinskiy, I.

2017-09-01

The paper presents the results of Jones-matrix mapping of uterine wall histological sections with second-degree and third-degree endometriosis. The technique of experimental measurement of coordinate distributions of the modulus and phase values of Jones matrix elements is suggested. Within the statistical and cross-correlation approaches the modulus and phase maps of Jones matrix images of optically thin biological layers of polycrystalline films of plasma and cerebrospinal fluid are analyzed. A set of objective parameters (statistical and generalized correlation moments), which are the most sensitive to changes in the phase of anisotropy, associated with the features of polycrystalline structure of uterine wall histological sections with second-degree and third-degree endometriosis are determined.

Modeling the formation of cell-matrix adhesions on a single 3D matrix fiber.

PubMed

Escribano, J; Sánchez, M T; García-Aznar, J M

2015-11-07

Cell-matrix adhesions are crucial in different biological processes like tissue morphogenesis, cell motility, and extracellular matrix remodeling. These interactions that link cell cytoskeleton and matrix fibers are built through protein clutches, generally known as adhesion complexes. The adhesion formation process has been deeply studied in two-dimensional (2D) cases; however, the knowledge is limited for three-dimensional (3D) cases. In this work, we simulate different local extracellular matrix properties in order to unravel the fundamental mechanisms that regulate the formation of cell-matrix adhesions in 3D. We aim to study the mechanical interaction of these biological structures through a three dimensional discrete approach, reproducing the transmission pattern force between the cytoskeleton and a single extracellular matrix fiber. This numerical model provides a discrete analysis of the proteins involved including spatial distribution, interaction between them, and study of the different phenomena, such as protein clutches unbinding or protein unfolding. Copyright © 2015 Elsevier Ltd. All rights reserved.

Human aqueous humor levels of transforming growth factor-β2: Association with matrix metalloproteinases/tissue inhibitors of matrix metalloproteinases

PubMed Central

Jia, Yan; Yue, Yu; Hu, Dan-Ning; Chen, Ji-Li; Zhou, Ji-Bo

2017-01-01

The present study aims to investigate the association of transforming growth factor-β2 (TGF-β2) and matrix metalloproteinases (MMPs), MMP-2 and MMP-3, and tissue inhibitors of matrix metalloproteinases (TIMPs), TIMP-1, TIMP-2 and TIMP-3 in the aqueous humor of patients with high myopia or cataracts. The levels of TGF-β2 and MMPs/TIMPs were measured with the Luminex xMAP Technology using commercially available Milliplex xMAP kits. The association between TGF-β2 and MMPs/TIMPs levels was analyzed using the Spearmans correlation test. The levels of TGF-β2 were identified to be positively correlated with the levels of TIMP-1 and TIMP-3 (TIMP-1: r=0.334; P=0.007; TIMP-3: r=0.309; P=0.012). The levels of MMP-2, MMP-3 and TIMP-2 did not significantly correlate with TGF-β2 levels (P>0.05). A positive correlation was identified between TGF-β2 and TIMPs in the aqueous humor of human eyes with elongated axial length. It appears that TGF-β2 stimulates the expression of TIMPs as a compensatory reaction to the development of high myopia. PMID:29188062

Brueckner G -matrix approach for neutron-proton pairing correlations in the deformed BCS approach

NASA Astrophysics Data System (ADS)

Ha, Eunja; Cheoun, Myung-Ki; Šimkovic, F.

2015-10-01

Ground states of even-even Ge isotopes with mass number A =64 -76 have been studied in the deformed Bardeen-Cooper-Schrieffer (BCS) theory by taking neutron-proton (n p ) pairing correlations as well as neutron-neutron (n n ) and proton-proton (p p ) pairing correlations. The n p pairing has two different modes J =0 ,T =1 (isotriplet) and J =1 ,T =0 (isosinglet). In this work, the Brueckner G matrix, based on the CD-Bonn potential, has been exploited to reduce the ambiguity regarding nucleon-nucleon interactions inside nuclei compared to the results by a simple schematic phenomenological force. We found that the G matrix plays important roles to obtain reasonable descriptions of even-even nuclei compared to the schematic force. The n p pairing strength has been shown to have a clear correlation with quadrupole deformation parameter β2 for the isotopes, and affects the smearing of the Fermi surfaces of not only N =Z nuclei but also N ≠Z nuclei. In particular, the coexistence of the like particle (n n and p p ) and the n p pairing modes was found to become more salient by the G -matrix approach than by the schematic force approach.

Distribution Analysis of Anthocyanins, Sugars, and Organic Acids in Strawberry Fruits Using Matrix-Assisted Laser Desorption/Ionization-Imaging Mass Spectrometry.

PubMed

Enomoto, Hirofumi; Sato, Kei; Miyamoto, Koji; Ohtsuka, Akira; Yamane, Hisakazu

2018-05-16

Anthocyanins, sugars, and organic acids contribute to the appearance, health benefits, and taste of strawberries. However, their spatial distribution in the ripe fruit has been fully unrevealed. Therefore, we performed matrix-assisted laser desorption/ionization, MALDI-IMS, analysis to investigate their spatial distribution in ripe strawberries. The detection sensitivity was improved by using the TM-Sprayer for matrix application. In the receptacle, pelargonidins were distributed in the skin, cortical, and pith tissues, whereas cyanidins and delphinidins were slightly localized in the skin. In the achene, mainly cyanidins were localized in the outside of the skin. Citric acid was mainly distributed in the upper and bottom side of cortical tissue. Although hexose was distributed almost equally throughout the fruits, sucrose was mainly distributed in the upper side of cortical and pith tissues. These results suggest that using the TM-Sprayer in MALDI-IMS was useful for microscopic distribution analysis of anthocyanins, sugars, and organic acids in strawberries.

Geostatistical Borehole Image-Based Mapping of Karst-Carbonate Aquifer Pores.

PubMed

Sukop, Michael C; Cunningham, Kevin J

2016-03-01

Quantification of the character and spatial distribution of porosity in carbonate aquifers is important as input into computer models used in the calculation of intrinsic permeability and for next-generation, high-resolution groundwater flow simulations. Digital, optical, borehole-wall image data from three closely spaced boreholes in the karst-carbonate Biscayne aquifer in southeastern Florida are used in geostatistical experiments to assess the capabilities of various methods to create realistic two-dimensional models of vuggy megaporosity and matrix-porosity distribution in the limestone that composes the aquifer. When the borehole image data alone were used as the model training image, multiple-point geostatistics failed to detect the known spatial autocorrelation of vuggy megaporosity and matrix porosity among the three boreholes, which were only 10 m apart. Variogram analysis and subsequent Gaussian simulation produced results that showed a realistic conceptualization of horizontal continuity of strata dominated by vuggy megaporosity and matrix porosity among the three boreholes. © 2015, National Ground Water Association.

Three dimensional time reversal optical tomography

NASA Astrophysics Data System (ADS)

Wu, Binlin; Cai, W.; Alrubaiee, M.; Xu, M.; Gayen, S. K.

2011-03-01

Time reversal optical tomography (TROT) approach is used to detect and locate absorptive targets embedded in a highly scattering turbid medium to assess its potential in breast cancer detection. TROT experimental arrangement uses multi-source probing and multi-detector signal acquisition and Multiple-Signal-Classification (MUSIC) algorithm for target location retrieval. Light transport from multiple sources through the intervening medium with embedded targets to the detectors is represented by a response matrix constructed using experimental data. A TR matrix is formed by multiplying the response matrix by its transpose. The eigenvectors with leading non-zero eigenvalues of the TR matrix correspond to embedded objects. The approach was used to: (a) obtain the location and spatial resolution of an absorptive target as a function of its axial position between the source and detector planes; and (b) study variation in spatial resolution of two targets at the same axial position but different lateral positions. The target(s) were glass sphere(s) of diameter ~9 mm filled with ink (absorber) embedded in a 60 mm-thick slab of Intralipid-20% suspension in water with an absorption coefficient μa ~ 0.003 mm-1 and a transport mean free path lt ~ 1 mm at 790 nm, which emulate the average values of those parameters for human breast tissue. The spatial resolution and accuracy of target location depended on axial position, and target contrast relative to the background. Both the targets could be resolved and located even when they were only 4-mm apart. The TROT approach is fast, accurate, and has the potential to be useful in breast cancer detection and localization.

Investigation of damage mechanisms in a cross-ply metal-matrix composite under thermomechanical loading. Master's thesis

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

Schubbe, J.J.

1990-12-01

Metal matrix composites (MMCs) are rapidly becoming strong candidates for high temperature and high stiffness structural applications such as the Advanced Tactical Fighter (ATF). This study systematically investigated the failure modes and associated damage in a cross-ply, (0/90)2s SCS6/Ti-15-3 metal matrix composite under in-phase and out-of-phase thermomechanic fatigue. Initiation and progression of fatigue damage were recorded and correlated to changes in Young's Modulus of the composite material. Experimental results show an internal stabilization of reaction zone size but degradation and separation from constituent materials under extended cyclic thermal loading. Critical to damage were transverse cracks initiating in the 90 degreesmore » plies, growing and coalescing from fiber/matrix interfaces internal to the specimen, progressing outward through the 0 degree plies before failure. Maximum mechanical strain at failure was determined to be approximately 0.0075 mm/mm. A correlation was made relating maximum matrix stress to failure life, resulting in a fatigue threshold limit of 280 MPa. An attempt was made to correlate the degradation in Young's Modulus (Damage=1-E/Eo) with the applied life cycles from different TMF tests.« less

Performance on a virtual reality angled laparoscope task correlates with spatial ability of trainees.

PubMed

Rosenthal, Rachel; Hamel, Christian; Oertli, Daniel; Demartines, Nicolas; Gantert, Walter A

2010-08-01

The aim of the present study was to investigate whether trainees' performance on a virtual reality angled laparoscope navigation task correlates with scores obtained on a validated conventional test of spatial ability. 56 participants of a surgery workshop performed an angled laparoscope navigation task on the Xitact LS 500 virtual reality Simulator. Performance parameters were correlated with the score of a validated paper-and-pencil test of spatial ability. Performance at the conventional spatial ability test significantly correlated with performance at the virtual reality task for overall task score (p < 0.001), task completion time (p < 0.001) and economy of movement (p = 0.035), not for endoscope travel speed (p = 0.947). In conclusion, trainees' performance in a standardized virtual reality camera navigation task correlates with their innate spatial ability. This VR session holds potential to serve as an assessment tool for trainees.

A multi-pixel InSAR time series analysis method: Simultaneous estimation of atmospheric noise, orbital errors and deformation

NASA Astrophysics Data System (ADS)

Jolivet, R.; Simons, M.

2016-12-01

InSAR time series analysis allows reconstruction of ground deformation with meter-scale spatial resolution and high temporal sampling. For instance, the ESA Sentinel-1 Constellation is capable of providing 6-day temporal sampling, thereby opening a new window on the spatio-temporal behavior of tectonic processes. However, due to computational limitations, most time series methods rely on a pixel-by-pixel approach. This limitation is a concern because (1) accounting for orbital errors requires referencing all interferograms to a common set of pixels before reconstruction of the time series and (2) spatially correlated atmospheric noise due to tropospheric turbulence is ignored. Decomposing interferograms into statistically independent wavelets will mitigate issues of correlated noise, but prior estimation of orbital uncertainties will still be required. Here, we explore a method that considers all pixels simultaneously when solving for the spatio-temporal evolution of interferometric phase Our method is based on a massively parallel implementation of a conjugate direction solver. We consider an interferogram as the sum of the phase difference between 2 SAR acquisitions and the corresponding orbital errors. In addition, we fit the temporal evolution with a physically parameterized function while accounting for spatially correlated noise in the data covariance. We assume noise is isotropic for any given InSAR pair with a covariance described by an exponential function that decays with increasing separation distance between pixels. We regularize our solution in space using a similar exponential function as model covariance. Given the problem size, we avoid matrix multiplications of the full covariances by computing convolutions in the Fourier domain. We first solve the unregularized least squares problem using the LSQR algorithm to approach the final solution, then run our conjugate direction solver to account for data and model covariances. We present synthetic tests showing the efficiency of our method. We then reconstruct a 20-year continuous time series covering Northern Chile. Without input from any additional GNSS data, we recover the secular deformation rate, seasonal oscillations and the deformation fields from the 2005 Mw 7.8 Tarapaca and 2007 Mw 7.7 Tocopilla earthquakes.

DBDA as a Novel Matrix for the Analyses of Small Molecules and Quantification of Fatty Acids by Negative Ion MALDI-TOF MS

NASA Astrophysics Data System (ADS)

Ling, Ling; Li, Ying; Wang, Sheng; Guo, Liming; Xiao, Chunsheng; Chen, Xuesi; Guo, Xinhua

2018-01-01

Matrix interference ions in low mass range has always been a concern when using matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS) to analyze small molecules (<500 Da). In this work, a novel matrix, N1,N4-dibenzylidenebenzene-1,4-diamine (DBDA) was synthesized for the analyses of small molecules by negative ion MALDI-TOF MS. Notably, only neat ions ([M-H]-) of fatty acids without matrix interference appeared in the mass spectra and the limit of detection (LOD) reached 0.3 fmol. DBDA also has great performance towards other small molecules such as amino acids, peptides, and nucleotide. Furthermore, with this novel matrix, the free fatty acids in serum were quantitatively analyzed based on the correlation curves with correlation coefficient of 0.99. In addition, UV-Vis experiments and molecular orbital calculations were performed to explore mechanism about DBDA used as matrix in the negative ion mode. The present work shows that the DBDA matrix is a highly sensitive matrix with few interference ions for analysis of small molecules. Meanwhile, DBDA is able to precisely quantify the fatty acids in real biological samples. [Figure not available: see fulltext.

Spatial orientation of the vestibular system

NASA Technical Reports Server (NTRS)

Raphan, T.; Dai, M.; Cohen, B.

1992-01-01

1. A simplified three-dimensional state space model of visual vestibular interaction was formulated. Matrix and dynamical system operators representing coupling from the semicircular canals and the visual system to the velocity storage integrator were incorporated into the model. 2. It was postulated that the system matrix for a tilted position was a composition of two linear transformations of the system matrix for the upright position. One transformation modifies the eigenvalues of the system matrix while another rotates the pitch and roll eigenvectors with the head, while maintaining the yaw axis eigenvector approximately spatially invariant. Using this representation, the response characteristics of the pitch, roll, and yaw eye velocity were obtained in terms of the eigenvalues and associated eigenvectors. 3. Using OKAN data obtained from monkeys and comparing to the model predictions, the eigenvalues and eigenvectors of the system matrix were identified as a function of tilt to the side or of tilt to the prone positions, using a modification of the Marquardt algorithm. The yaw eigenvector for right-side-down tilt and for downward pitch cross-coupling was approximately 30 degrees from the spatial vertical. For the prone position, the eigenvector was computed to be approximately 20 degrees relative to the spatial vertical. For both side-down and prone positions, oblique OKN induced along eigenvector directions generated OKAN which decayed to zero along a straight line with approximately a single time constant. This was verified by a spectral analysis of the residual sequence about the straight line fit to the decaying data. The residual sequence was associated with a narrow autocorrelation function and a wide power spectrum. 4. Parameters found using the Marquardt algorithm were incorporated into the model. Diagonal matrices in a head coordinate frame were introduced to represent the direct pathway and the coupling of the visual system to the integrator. Model simulations predicted the behavior of yaw and pitch OKN and OKAN when the animal was upright, as well as the cross-coupling in the tilted position. The trajectories in velocity space were also accurately simulated. 5. There were similarities between the monkey eigenvectors and human perception of the spatial vertical. For side-down tilts and downward eye velocity cross-coupling, there was only an Aubert (A) effect. For upward eye velocity cross-coupling there were both Muller (E) and Aubert (A) effects. The mean of the eigenvectors for upward and downward eye velocities overlay human 1 x g perceptual data.(ABSTRACT TRUNCATED AT 400 WORDS).

Teacher spatial skills are linked to differences in geometry instruction.

PubMed

Otumfuor, Beryl Ann; Carr, Martha

2017-12-01

Spatial skills have been linked to better performance in mathematics. The purpose of this study was to examine the relationship between teacher spatial skills and their instruction, including teacher content and pedagogical knowledge, use of pictorial representations, and use of gestures during geometry instruction. Fifty-six middle school teachers participated in the study. The teachers were administered spatial measures of mental rotations and spatial visualization. Next, a single geometry class was videotaped. Correlational analyses revealed that spatial skills significantly correlate with teacher's use of representational gestures and content and pedagogical knowledge during instruction of geometry. Spatial skills did not independently correlate with the use of pointing gestures or the use of pictorial representations. However, an interaction term between spatial skills and content and pedagogical knowledge did correlate significantly with the use of pictorial representations. Teacher experience as measured by the number of years of teaching and highest degree did not appear to affect the relationships among the variables with the exception of the relationship between spatial skills and teacher content and pedagogical knowledge. Teachers with better spatial skills are also likely to use representational gestures and to show better content and pedagogical knowledge during instruction. Spatial skills predict pictorial representation use only as a function of content and pedagogical knowledge. © 2017 The British Psychological Society.

The G matrix under fluctuating correlational mutation and selection.

PubMed

Revell, Liam J

2007-08-01

Theoretical quantitative genetics provides a framework for reconstructing past selection and predicting future patterns of phenotypic differentiation. However, the usefulness of the equations of quantitative genetics for evolutionary inference relies on the evolutionary stability of the additive genetic variance-covariance matrix (G matrix). A fruitful new approach for exploring the evolutionary dynamics of G involves the use of individual-based computer simulations. Previous studies have focused on the evolution of the eigenstructure of G. An alternative approach employed in this paper uses the multivariate response-to-selection equation to evaluate the stability of G. In this approach, I measure similarity by the correlation between response-to-selection vectors due to random selection gradients. I analyze the dynamics of G under several conditions of correlational mutation and selection. As found in a previous study, the eigenstructure of G is stabilized by correlational mutation and selection. However, over broad conditions, instability of G did not result in a decreased consistency of the response to selection. I also analyze the stability of G when the correlation coefficients of correlational mutation and selection and the effective population size change through time. To my knowledge, no prior study has used computer simulations to investigate the stability of G when correlational mutation and selection fluctuate. Under these conditions, the eigenstructure of G is unstable under some simulation conditions. Different results are obtained if G matrix stability is assessed by eigenanalysis or by the response to random selection gradients. In this case, the response to selection is most consistent when certain aspects of the eigenstructure of G are least stable and vice versa.

Combined infrared and ultraviolet-visible spectroscopy matrix-isolated carbon vapor

NASA Technical Reports Server (NTRS)

Kurtz, Joe; Huffman, Donald R.

1990-01-01

Infrared and UV-visible absorption spectra have been measured on the same sample of matrix-isolated carbon vapor in order to establish correlations between absorption intensities of vibrational and electronic transitions as a function of sample annealing. A high degree of correlation has been found between the IR feature at 1998/cm recently assigned to C8 and a UV absorption feature at about 3100 A. Thus, for the first time, direct evidence is given for the assignment of one of the unknown UV-visible features of the long-studied matrix-isolated carbon vapor spectrum.

[Spatial point patterns of Antarctic krill fishery in the northern Antarctic Peninsula].

PubMed

Yang, Xiao Ming; Li, Yi Xin; Zhu, Guo Ping

2016-12-01

As a key species in the Antarctic ecosystem, the spatial distribution of Antarctic krill (thereafter krill) often tends to present aggregation characteristics, which therefore reflects the spatial patterns of krill fishing operation. Based on the fishing data collected from Chinese krill fishing vessels, of which vessel A was professional krill fishing vessel and Vessel B was a fishing vessel which shifted between Chilean jack mackerel (Trachurus murphyi) fishing ground and krill fishing ground. In order to explore the characteristics of spatial distribution pattern and their ecological effects of two obvious different fishing fleets under a high and low nominal catch per unit effort (CPUE), from the viewpoint of spatial point pattern, the present study analyzed the spatial distribution characteristics of krill fishery in the northern Antarctic Peninsula from three aspects: (1) the two vessels' point pattern characteristics of higher CPUEs and lower CPUEs at different scales; (2) correlation of the bivariate point patterns between these points of higher CPUE and lower CPUE; and (3) correlation patterns of CPUE. Under the analysis derived from the Ripley's L function and mark correlation function, the results showed that the point patterns of the higher/lo-wer catch available were similar, both showing an aggregation distribution in this study windows at all scale levels. The aggregation intensity of krill fishing was nearly maximum at 15 km spatial scale, and kept stably higher values at the scale of 15-50 km. The aggregation intensity of krill fishery point patterns could be described in order as higher CPUE of vessel A > lower CPUE of vessel B >higher CPUE of vessel B > higher CPUE of vessel B. The relationship of the higher and lo-wer CPUEs of vessel A showed positive correlation at the spatial scale of 0-75 km, and presented stochastic relationship after 75 km scale, whereas vessel B showed positive correlation at all spatial scales. The point events of higher and lower CPUEs were synchronized, showing significant correlations at most of spatial scales because of the dynamics nature and complex of krill aggregation patterns. The distribution of vessel A's CPUEs was positively correlated at scales of 0-44 km, but negatively correlated at the scales of 44-80 km. The distribution of vessel B's CPUEs was negatively correlated at the scales of 50-70 km, but no significant correlations were found at other scales. The CPUE mark point patterns showed a negative correlation, which indicated that intraspecific competition for space and prey was significant. There were significant differences in spatial point pattern distribution between vessel A with higher fishing capacity and vessel B with lower fishing capacity. The results showed that the professional krill fishing vessel is suitable to conduct the analysis of spatial point pattern and scientific fishery survey.

The Spatial and Temporal Variability of Meltwater Flow Paths: Insights From a Grid of Over 100 Snow Lysimeters

NASA Astrophysics Data System (ADS)

Webb, R. W.; Williams, M. W.; Erickson, T. A.

2018-02-01

Snowmelt is an important part of the hydrologic cycle and ecosystem dynamics for headwater systems. However, the physical process of water flow through snow is a poorly understood aspect of snow hydrology as meltwater flow paths tend to be highly complex. Meltwater flow paths diverge and converge as percolating meltwater reaches stratigraphic layer interfaces creating high spatial variability. Additionally, a snowpack is temporally heterogeneous due to rapid localized metamorphism that occurs during melt. This study uses a snowmelt lysimeter array at tree line in the Niwot Ridge study area of northern Colorado. The array is designed to address the issue of spatial and temporal variability of basal discharge at 105 locations over an area of 1,300 m2. Observed coefficients of variation ranged from 0 to almost 10 indicating more variability than previously observed, though this variability decreased throughout each melt season. Snowmelt basal discharge also significantly increases as snow depth decreases displaying a cluster pattern that peaks during weeks 3-5 of the snowmelt season. These results are explained by the flow of meltwater along snow layer interfaces. As the snowpack becomes less stratified through the melt season, the pattern transforms from preferential flow paths to uniform matrix flow. Correlation ranges of the observed basal discharge correspond to a mean representative elementary area of 100 m2, or a characteristic length of 10 m. Snowmelt models representing processes at scales less than this will need to explicitly incorporate the spatial variability of snowmelt discharge and meltwater flow paths through snow between model pixels.

18F-FDG PET radiomics approaches: comparing and clustering features in cervical cancer.

PubMed

Tsujikawa, Tetsuya; Rahman, Tasmiah; Yamamoto, Makoto; Yamada, Shizuka; Tsuyoshi, Hideaki; Kiyono, Yasushi; Kimura, Hirohiko; Yoshida, Yoshio; Okazawa, Hidehiko

2017-11-01

The aims of our study were to find the textural features on 18 F-FDG PET/CT which reflect the different histological architectures between cervical cancer subtypes and to make a visual assessment of the association between 18 F-FDG PET textural features in cervical cancer. Eighty-three cervical cancer patients [62 squamous cell carcinomas (SCCs) and 21 non-SCCs (NSCCs)] who had undergone pretreatment 18 F-FDG PET/CT were enrolled. A texture analysis was performed on PET/CT images, from which 18 PET radiomics features were extracted including first-order features such as standardized uptake value (SUV), metabolic tumor volume (MTV) and total lesion glycolysis (TLG), second- and high-order textural features using SUV histogram, normalized gray-level co-occurrence matrix (NGLCM), and neighborhood gray-tone difference matrix, respectively. These features were compared between SCC and NSCC using a Bonferroni adjusted P value threshold of 0.0028 (0.05/18). To assess the association between PET features, a heat map analysis with hierarchical clustering, one of the radiomics approaches, was performed. Among 18 PET features, correlation, a second-order textural feature derived from NGLCM, was a stable parameter and it was the only feature which showed a robust trend toward significant difference between SCC and NSCC. Cervical SCC showed a higher correlation (0.70 ± 0.07) than NSCC (0.64 ± 0.07, P = 0.0030). The other PET features did not show any significant differences between SCC and NSCC. A higher correlation in SCC might reflect higher structural integrity and stronger spatial/linear relationship of cancer cells compared with NSCC. A heat map with a PET feature dendrogram clearly showed 5 distinct clusters, where correlation belonged to a cluster including MTV and TLG. However, the association between correlation and MTV/TLG was not strong. Correlation was a relatively independent PET feature in cervical cancer. 18 F-FDG PET textural features might reflect the differences in histological architecture between cervical cancer subtypes. PET radiomics approaches reveal the association between PET features and will be useful for finding a single feature or a combination of features leading to precise diagnoses, potential prognostic models, and effective therapeutic strategies.

Identification of Pyridinoline Trivalent Collagen Cross-Links by Raman Microspectroscopy.

PubMed

Gamsjaeger, Sonja; Robins, Simon P; Tatakis, Dimitris N; Klaushofer, Klaus; Paschalis, Eleftherios P

2017-06-01

Intermolecular cross-linking of bone collagen is intimately related to the way collagen molecules are arranged in a fibril, imparts certain mechanical properties to the fibril, and may be involved in the initiation of mineralization. Raman microspectroscopy allows the analysis of minimally processed bone blocks and provides simultaneous information on both the mineral and organic matrix (mainly type I collagen) components, with a spatial resolution of ~1 μm. The aim of the present study was to validate Raman spectroscopic parameters describing one of the major mineralizing type I trivalent cross-links, namely pyridinoline (PYD). To achieve this, a series of collagen cross-linked peptides with known PYD content (as determined by HPLC analysis), human bone, porcine skin, predentin and dentin animal model tissues were analyzed by Raman microspectroscopy. The results of the present study confirm that it is feasible to monitor PYD trivalent collagen cross-links by Raman spectroscopic analysis in mineralized tissues, exclusively through a Raman band ~1660 wavenumbers. This allows determination of the relative PYD content in undecalcified bone tissues with a spatial resolution of ~1 μm, thus enabling correlations with histologic and histomorphometric parameters.

Assessment of groundwater potential of the crystalline basement of Wadi-Fira (Eastern Chad) using a multi-criteria correlation analysis and Remote Sensing data

NASA Astrophysics Data System (ADS)

Brahim Mahamat, Hamza; Coz Mathieu, Le; Abderamane, Hamit; Razack, Moumtaz

2017-04-01

Access to water in the Wadi-Fira aquifer system is a crucial problem in Eastern Chad because of (i) the complexity of the hydrogeological context (fractured basement), (ii) large extent of the study area (50,000 km2); And (iii) hard-to-access field data (only 34 water points were available to determine physicochemical and hydrodynamic parameters) often associated with high uncertainty. This groundwater resource is paramount in this arid environment, to meet the water needs of an increasingly growing population (refugees from Darfur) with a predominant pastoral activity. In order to optimally exploit the available data, correlative analyzes are carried out by integrating the spatial dimension of the data with GIS tools. A three-step strategy is thus implemented, based on: (i) point field data with physicochemical and hydrodynamic parameters; (ii) maps interpolated from point data, to increase the number of ''comparable'' parameters for each site; and (iii) interpolated maps coupled to maps from Remote Sensing results describing the area's structural geomorphology (slopes, hydrographic network, faults). The first results show marked correlations between physico-chemical and hydrodynamical parameters. According to the correlation matrix, the static level correlates significantly with the dominant cations (Ca2+ ; R = 0.52) and anions (HCO3- ; R = 0.53). Correlations are lower between electrical conductivity and transmissivity, and electrical conductivity and measured static level. A negative correlation is observed between Fluorine and transmissivity (r = -0.65), and the altered horizon (r = -0.5). The most significant discharges are obtained in fissured horizons. The correlative analysis allowsto differentiate mapped sectors according to the productivity and chemical quality regarding groundwater resource. Keywords: Hydrodynamics, Hydrochemistry, Remote Sensing, SRTM, Basement aquifer, Alteration, Lineaments, Wadi-Fira, Tchad.

Failure criterion for materials with spatially correlated mechanical properties

NASA Astrophysics Data System (ADS)

Faillettaz, J.; Or, D.

2015-03-01

The role of spatially correlated mechanical elements in the failure behavior of heterogeneous materials represented by fiber bundle models (FBMs) was evaluated systematically for different load redistribution rules. Increasing the range of spatial correlation for FBMs with local load sharing is marked by a transition from ductilelike failure characteristics into brittlelike failure. The study identified a global failure criterion based on macroscopic properties (external load and cumulative damage) that is independent of spatial correlation or load redistribution rules. This general metric could be applied to assess the mechanical stability of complex and heterogeneous systems and thus provide an important component for early warning of a class of geophysical ruptures.

The extracellular matrix in myocardial injury, repair, and remodeling

PubMed Central

2017-01-01

The cardiac extracellular matrix (ECM) not only provides mechanical support, but also transduces essential molecular signals in health and disease. Following myocardial infarction, dynamic ECM changes drive inflammation and repair. Early generation of bioactive matrix fragments activates proinflammatory signaling. The formation of a highly plastic provisional matrix facilitates leukocyte infiltration and activates infarct myofibroblasts. Deposition of matricellular proteins modulates growth factor signaling and contributes to the spatial and temporal regulation of the reparative response. Mechanical stress due to pressure and volume overload and metabolic dysfunction also induce profound changes in ECM composition that contribute to the pathogenesis of heart failure. This manuscript reviews the role of the ECM in cardiac repair and remodeling and discusses matrix-based therapies that may attenuate remodeling while promoting repair and regeneration. PMID:28459429

Coexistence of species with different dispersal across landscapes: a critical role of spatial correlation in disturbance.

PubMed

Liao, Jinbao; Ying, Zhixia; Woolnough, Daelyn A; Miller, Adam D; Li, Zhenqing; Nijs, Ivan

2016-05-11

Disturbance is key to maintaining species diversity in plant communities. Although the effects of disturbance frequency and extent on species diversity have been studied, we do not yet have a mechanistic understanding of how these aspects of disturbance interact with spatial structure of disturbance to influence species diversity. Here we derive a novel pair approximation model to explore competitive outcomes in a two-species system subject to spatially correlated disturbance. Generally, spatial correlation in disturbance favoured long-range dispersers, while distance-limited dispersers were greatly suppressed. Interestingly, high levels of spatial aggregation of disturbance promoted long-term species coexistence that is not possible in the absence of disturbance, but only when the local disperser was intrinsically competitively superior. However, spatial correlation in disturbance led to different competitive outcomes, depending on the disturbed area. Concerning ecological conservation and management, we theoretically demonstrate that introducing a spatially correlated disturbance to the system or altering an existing disturbance regime can be a useful strategy either to control species invasion or to promote species coexistence. Disturbance pattern analysis may therefore provide new insights into biodiversity conservation. © 2016 The Author(s).

High-Spatial and High-Mass Resolution Imaging of Surface Metabolites of Arabidopsis thaliana by Laser Desorption-Ionization Mass Spectrometry Using Colloidal Silver

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

Jun, Ji Hyun; Song, Zhihong; Liu, Zhenjiu

High-spatial resolution and high-mass resolution techniques are developed and adopted for the mass spectrometric imaging of epicuticular lipids on the surface of Arabidopsis thaliana. Single cell level spatial resolution of {approx}12 {micro}m was achieved by reducing the laser beam size by using an optical fiber with 25 {micro}m core diameter in a vacuum matrix-assisted laser desorption ionization-linear ion trap (vMALDI-LTQ) mass spectrometer and improved matrix application using an oscillating capillary nebulizer. Fine chemical images of a whole flower were visualized in this high spatial resolution showing substructure of an anther and single pollen grains at the stigma and anthers. Themore » LTQ-Orbitrap with a MALDI ion source was adopted to achieve MS imaging in high mass resolution. Specifically, isobaric silver ion adducts of C29 alkane (m/z 515.3741) and C28 aldehyde (m/z 515.3377), indistinguishable in low-resolution LTQ, can now be clearly distinguished and their chemical images could be separately constructed. In the application to roots, the high spatial resolution allowed molecular MS imaging of secondary roots and the high mass resolution allowed direct identification of lipid metabolites on root surfaces.« less

Effects of Spatial Variability of Soil Properties on the Triggering of Rainfall-Induced Shallow Landslides

NASA Astrophysics Data System (ADS)

Fan, Linfeng; Lehmann, Peter; Or, Dani

2015-04-01

Naturally-occurring spatial variations in soil properties (e.g., soil depth, moisture, and texture) affect key hydrological processes and potentially the mechanical response of soil to hydromechanical loading (relative to the commonly-assumed uniform soil mantle). We quantified the effects of soil spatial variability on the triggering of rainfall-induced shallow landslides at the hillslope- and catchment-scales, using a physically-based landslide triggering model that considers interacting soil columns with mechanical strength thresholds (represented by the Fiber Bundle Model). The spatial variations in soil properties are represented as Gaussian random distributions and the level of variation is characterized by the coefficient of variation and correlation lengths of soil properties (i.e., soil depth, soil texture and initial water content in this study). The impacts of these spatial variations on landslide triggering characteristics were measured by comparing the times to triggering and landslide volumes for heterogeneous soil properties and homogeneous cases. Results at hillslope scale indicate that for spatial variations of an individual property (without cross correlation), the increasing of coefficient of variation introduces weak spots where mechanical damage is accelerated and leads to earlier onset of landslide triggering and smaller volumes. Increasing spatial correlation length of soil texture and initial water content also induces early landslide triggering and small released volumes due to the transition of failure mode from brittle to ductile failure. In contrast, increasing spatial correlation length of soil depth "reduces" local steepness and postpones landslide triggering. Cross-correlated soil properties generally promote landslide initiation, but depending on the internal structure of spatial distribution of each soil property, landslide triggering may be reduced. The effects of cross-correlation between initial water content and soil texture were investigated in detail at the catchment scale by incorporating correlations of both variables with topography. Results indicate that the internal structure of the spatial distribution of each soil property together with their interplays determine the overall performance of the coupled spatial variability. This study emphasizes the importance of both the randomness and spatial structure of soil properties on landslide triggering and characteristics.

Pair correlation functions for identifying spatial correlation in discrete domains

NASA Astrophysics Data System (ADS)

Gavagnin, Enrico; Owen, Jennifer P.; Yates, Christian A.

2018-06-01

Identifying and quantifying spatial correlation are important aspects of studying the collective behavior of multiagent systems. Pair correlation functions (PCFs) are powerful statistical tools that can provide qualitative and quantitative information about correlation between pairs of agents. Despite the numerous PCFs defined for off-lattice domains, only a few recent studies have considered a PCF for discrete domains. Our work extends the study of spatial correlation in discrete domains by defining a new set of PCFs using two natural and intuitive definitions of distance for a square lattice: the taxicab and uniform metric. We show how these PCFs improve upon previous attempts and compare between the quantitative data acquired. We also extend our definitions of the PCF to other types of regular tessellation that have not been studied before, including hexagonal, triangular, and cuboidal. Finally, we provide a comprehensive PCF for any tessellation and metric, allowing investigation of spatial correlation in irregular lattices for which recognizing correlation is less intuitive.

Raman and Fourier Transform Infrared (FT-IR) Mineral to Matrix Ratios Correlate with Physical Chemical Properties of Model Compounds and Native Bone Tissue.

PubMed

Taylor, Erik A; Lloyd, Ashley A; Salazar-Lara, Carolina; Donnelly, Eve

2017-10-01

Raman and Fourier transform infrared (FT-IR) spectroscopic imaging techniques can be used to characterize bone composition. In this study, our objective was to validate the Raman mineral:matrix ratios (ν 1 PO 4 :amide III, ν 1 PO 4 :amide I, ν 1 PO 4 :Proline + hydroxyproline, ν 1 PO 4 :Phenylalanine, ν 1 PO 4 :δ CH 2 peak area ratios) by correlating them to ash fraction and the IR mineral:matrix ratio (ν 3 PO 4 :amide I peak area ratio) in chemical standards and native bone tissue. Chemical standards consisting of varying ratios of synthetic hydroxyapatite (HA) and collagen, as well as bone tissue from humans, sheep, and mice, were characterized with confocal Raman spectroscopy and FT-IR spectroscopy and gravimetric analysis. Raman and IR mineral:matrix ratio values from chemical standards increased reciprocally with ash fraction (Raman ν 1 PO 4 /Amide III: P < 0.01, R 2  = 0.966; Raman ν 1 PO 4 /Amide I: P < 0.01, R 2  = 0.919; Raman ν 1 PO 4 /Proline + Hydroxyproline: P < 0.01, R 2  = 0.976; Raman ν 1 PO 4 /Phenylalanine: P < 0.01, R 2  = 0.911; Raman ν 1 PO 4 /δ CH 2 : P < 0.01, R 2  = 0.894; IR P < 0.01, R 2  = 0.91). Fourier transform infrared mineral:matrix ratio values from native bone tissue were also similar to theoretical mineral:matrix ratio values for a given ash fraction. Raman and IR mineral:matrix ratio values were strongly correlated ( P < 0.01, R 2  = 0.82). These results were confirmed by calculating the mineral:matrix ratio for theoretical IR spectra, developed by applying the Beer-Lambert law to calculate the relative extinction coefficients of HA and collagen over the same range of wavenumbers (800-1800 cm -1 ). The results confirm that the Raman mineral:matrix bone composition parameter correlates strongly to ash fraction and to its IR counterpart. Finally, the mineral:matrix ratio values of the native bone tissue are similar to those of both chemical standards and theoretical values, confirming the biological relevance of the chemical standards and the characterization techniques.

Spatial structure of correlations around a quantum impurity at the edge of a two-dimensional topological insulator

NASA Astrophysics Data System (ADS)

Allerdt, Andrew; Feiguin, A. E.; Martins, G. B.

2017-07-01

We calculate exact zero-temperature real-space properties of a substitutional magnetic impurity coupled to the edge of a zigzag silicenelike nanoribbon. Using a Lanczos transformation [A. Allerdt et al., Phys. Rev. B 91, 085101 (2015), 10.1103/PhysRevB.91.085101] and the density-matrix renormalization-group method, we obtain a realistic description of stanene and germanene that includes the bulk and the edges as boundary one-dimensional helical metallic states. Our results for substitutional impurities indicate that the development of a Kondo state and the structure of the spin correlations between the impurity and the electron spins in the metallic edge state depend considerably on the location of the impurity. More specifically, our real-space resolution allows us to conclude that there is a sharp distinction between the impurity being located at a crest or a trough site at the zigzag edge. We also observe, as expected, that the spin correlations are anisotropic due to an emerging Dzyaloshinskii-Moriya interaction with the conduction electrons and that the edges scatter from the impurity and "snake" or circle around it. Our estimates for the Kondo temperature indicate that there is a very weak enhancement due to the presence of spin-orbit coupling.

Variations of DOM quality in inflows of a drinking water reservoir: linking of van Krevelen diagrams with EEMF spectra by rank correlation.

PubMed

Herzsprung, Peter; von Tümpling, Wolf; Hertkorn, Norbert; Harir, Mourad; Büttner, Olaf; Bravidor, Jenny; Friese, Kurt; Schmitt-Kopplin, Philippe

2012-05-15

Elevated concentrations of dissolved organic matter (DOM) such as humic substances in raw water pose significant challenges during the processing of the commercial drinking water supplies. This is a relevant issue in Saxony, Central East Germany, and many other regions worldwide, where drinking water is produced from raw waters with noticeable presence of chromophoric DOM (CDOM), which is assumed to originate from forested watersheds in spring regions of the catchment area. For improved comprehension of DOM molecular composition, the seasonal and spatial variations of humic-like fluorescence and elemental formulas in the catchment area of the Muldenberg reservoir were recorded by excitation emission matrix fluorescence (EEMF) and ultrahigh-resolution mass spectrometry (FT-ICR-MS). The Spearman rank correlation was applied to link the EEMF intensities with exact molecular formulas and their corresponding relative mass peak abundances. Thereby, humic-like fluorescence could be allocated to the pool of oxygen-rich and relatively unsaturated components with stoichiometries similar to those of tannic acids, which are suspected to have a comparatively high disinfection byproduct formation potential associated with the chlorination of raw water. Analogous relationships were established for UV absorption at 254 nm (UV(254)) and dissolved organic carbon (DOC) and compared to the EEMF correlation.

Collaboration space division in collaborative product development based on a genetic algorithm

NASA Astrophysics Data System (ADS)

Qian, Xueming; Ma, Yanqiao; Feng, Huan

2018-02-01

The advance in the global environment, rapidly changing markets, and information technology has created a new stage for design. In such an environment, one strategy for success is the Collaborative Product Development (CPD). Organizing people effectively is the goal of Collaborative Product Development, and it solves the problem with certain foreseeability. The development group activities are influenced not only by the methods and decisions available, but also by correlation among personnel. Grouping the personnel according to their correlation intensity is defined as collaboration space division (CSD). Upon establishment of a correlation matrix (CM) of personnel and an analysis of the collaboration space, the genetic algorithm (GA) and minimum description length (MDL) principle may be used as tools in optimizing collaboration space. The MDL principle is used in setting up an object function, and the GA is used as a methodology. The algorithm encodes spatial information as a chromosome in binary. After repetitious crossover, mutation, selection and multiplication, a robust chromosome is found, which can be decoded into an optimal collaboration space. This new method can calculate the members in sub-spaces and individual groupings within the staff. Furthermore, the intersection of sub-spaces and public persons belonging to all sub-spaces can be determined simultaneously.

Comparison of Matrix Frequency-Doubling Technology (FDT) Perimetry with the SWEDISH Interactive Thresholding Algorithm (SITA) Standard Automated Perimetry (SAP) in Mild Glaucoma.

PubMed

Doozandeh, Azadeh; Irandoost, Farnoosh; Mirzajani, Ali; Yazdani, Shahin; Pakravan, Mohammad; Esfandiari, Hamed

2017-01-01

This study aimed to compare second-generation frequency-doubling technology (FDT) perimetry with standard automated perimetry (SAP) in mild glaucoma. Forty-seven eyes of 47 participants who had mild visual field defect by SAP were included in this study. All participants were examined using SITA 24-2 (SITA-SAP) and matrix 24-2 (Matrix-FDT). The correlations of global indices and the number of defects on pattern deviation (PD) plots were determined. Agreement between two sets regarding the stage of visual field damage was assessed. Pearson's correlation, intra-cluster comparison, paired t-test, and 95% limit of agreement were calculated. Although there was no significant difference between global indices, the agreement between the two devices regarding the global indices was weak (the limit of agreement for mean deviation was -6.08 to 6.08 and that for pattern standard deviation was -4.42 to 3.42). The agreement between SITA-SAP and Matrix-FDT regarding the Glaucoma Hemifield Test (GHT) and the number of defective points in each quadrant and staging of the visual field damage was also weak. Because the correlation between SITA-SAP and Matrix-FDT regarding global indices, GHT, number of defective points, and stage of the visual field damage in mild glaucoma is weak, Matrix-FDT cannot be used interchangeably with SITA-SAP in the early stages of glaucoma.

Efficient Computation Of Manipulator Inertia Matrix

NASA Technical Reports Server (NTRS)

Fijany, Amir; Bejczy, Antal K.

1991-01-01

Improved method for computation of manipulator inertia matrix developed, based on concept of spatial inertia of composite rigid body. Required for implementation of advanced dynamic-control schemes as well as dynamic simulation of manipulator motion. Motivated by increasing demand for fast algorithms to provide real-time control and simulation capability and, particularly, need for faster-than-real-time simulation capability, required in many anticipated space teleoperation applications.

The nuclear matrix prepared by amine modification

PubMed Central

Wan, Katherine M.; Nickerson, Jeffrey A.; Krockmalnic, Gabriela; Penman, Sheldon

1999-01-01

The nucleus is spatially ordered by attachments to a nonchromatin nuclear structure, the nuclear matrix. The nuclear matrix and chromatin are intimately connected and integrated structures, and so a major technical challenge in nuclear matrix research has been to remove chromatin while retaining a native nuclear matrix. Most methods for removing chromatin require first a nuclease digestion and then a salt extraction to remove cut chromatin. We have hypothesized that cut chromatin is held in place by charge interactions involving nucleosomal amino groups. We have tested this hypothesis by chemically modifying amino groups after nuclease digestion. By using this protocol, chromatin could be effectively removed at physiological ionic strength. We compared the ultrastructure and composition of this nuclear matrix preparation with the traditional high-salt nuclear matrix and with the third nuclear matrix preparation that we have developed from which chromatin is removed after extensive crosslinking. All three matrix preparations reveal internal nuclear matrix structures that are built on a network of branched filaments of about 10 nm diameter. That such different chromatin-removal protocols reveal similar principles of nuclear matrix construction increases our confidence that we are observing important architectural elements of the native structure in the living cell. PMID:9927671

Robust alignment of chromatograms by statistically analyzing the shifts matrix generated by moving window fast Fourier transform cross-correlation.

PubMed

Zhang, Mingjing; Wen, Ming; Zhang, Zhi-Min; Lu, Hongmei; Liang, Yizeng; Zhan, Dejian

2015-03-01

Retention time shift is one of the most challenging problems during the preprocessing of massive chromatographic datasets. Here, an improved version of the moving window fast Fourier transform cross-correlation algorithm is presented to perform nonlinear and robust alignment of chromatograms by analyzing the shifts matrix generated by moving window procedure. The shifts matrix in retention time can be estimated by fast Fourier transform cross-correlation with a moving window procedure. The refined shift of each scan point can be obtained by calculating the mode of corresponding column of the shifts matrix. This version is simple, but more effective and robust than the previously published moving window fast Fourier transform cross-correlation method. It can handle nonlinear retention time shift robustly if proper window size has been selected. The window size is the only one parameter needed to adjust and optimize. The properties of the proposed method are investigated by comparison with the previous moving window fast Fourier transform cross-correlation and recursive alignment by fast Fourier transform using chromatographic datasets. The pattern recognition results of a gas chromatography mass spectrometry dataset of metabolic syndrome can be improved significantly after preprocessing by this method. Furthermore, the proposed method is available as an open source package at https://github.com/zmzhang/MWFFT2. © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

From nano- to macro-scale: nanotechnology approaches for spatially controlled delivery of bioactive factors for bone and cartilage engineering.

PubMed

Santo, Vítor E; Gomes, Manuela E; Mano, João F; Reis, Rui L

2012-07-01

The field of biomaterials has advanced towards the molecular and nanoscale design of bioactive systems for tissue engineering, regenerative medicine and drug delivery. Spatial cues are displayed in the 3D extracellular matrix and can include signaling gradients, such as those observed during chemotaxis. Architectures range from the nanometer to the centimeter length scales as exemplified by extracellular matrix fibers, cells and macroscopic shapes. The main focus of this review is the application of a biomimetic approach by the combination of architectural cues, obtained through the application of micro- and nanofabrication techniques, with the ability to sequester and release growth factors and other bioactive agents in a spatiotemporal controlled manner for bone and cartilage engineering.

Dynamics of fractional condensation of a substance on a probe for spectral analysis

NASA Astrophysics Data System (ADS)

Zakharov, Yu. A.; Kokorina, O. B.; Lysogorskiĭ, Yu. V.; Sevastianov, A. A.

2008-11-01

The fractional separation of trace metals on a cold tungsten probe from salt matrix vapor, which interferes with the spectral analysis, is studied. The spatial structure of the vapor flows of sodium chloride, potassium sulfate, and indium atoms is visualized at characteristic wavelengths as they interact with the probe. The vapor flow rate and the probe orientation were varied. It is found that the smoke of the matrix does not prevent the deposition of the metal on the probe because of spatial separation of these fractions and that the detrimental effect of thermal gas expansion and other factors is eliminated. The sensitivity of the atomic absorption analysis of indium impurities in these salts is increased by an order of magnitude.

Robust adaptive multichannel SAR processing based on covariance matrix reconstruction

NASA Astrophysics Data System (ADS)

Tan, Zhen-ya; He, Feng

2018-04-01

With the combination of digital beamforming (DBF) processing, multichannel synthetic aperture radar(SAR) systems in azimuth promise well in high-resolution and wide-swath imaging, whereas conventional processing methods don't take the nonuniformity of scattering coefficient into consideration. This paper brings up a robust adaptive Multichannel SAR processing method which utilizes the Capon spatial spectrum estimator to obtain the spatial spectrum distribution over all ambiguous directions first, and then the interference-plus-noise covariance Matrix is reconstructed based on definition to acquire the Multichannel SAR processing filter. The performance of processing under nonuniform scattering coefficient is promoted by this novel method and it is robust again array errors. The experiments with real measured data demonstrate the effectiveness and robustness of the proposed method.

Vertices cannot be hidden from quantum spatial search for almost all random graphs

NASA Astrophysics Data System (ADS)

Glos, Adam; Krawiec, Aleksandra; Kukulski, Ryszard; Puchała, Zbigniew

2018-04-01

In this paper, we show that all nodes can be found optimally for almost all random Erdős-Rényi G(n,p) graphs using continuous-time quantum spatial search procedure. This works for both adjacency and Laplacian matrices, though under different conditions. The first one requires p=ω (log ^8(n)/n), while the second requires p≥ (1+ɛ )log (n)/n, where ɛ >0. The proof was made by analyzing the convergence of eigenvectors corresponding to outlying eigenvalues in the \\Vert \\cdot \\Vert _∞ norm. At the same time for p<(1-ɛ )log (n)/n, the property does not hold for any matrix, due to the connectivity issues. Hence, our derivation concerning Laplacian matrix is tight.

Expanding (3+1)-dimensional universe from a lorentzian matrix model for superstring theory in (9+1) dimensions.

PubMed

Kim, Sang-Woo; Nishimura, Jun; Tsuchiya, Asato

2012-01-06

We reconsider the matrix model formulation of type IIB superstring theory in (9+1)-dimensional space-time. Unlike the previous works in which the Wick rotation was used to make the model well defined, we regularize the Lorentzian model by introducing infrared cutoffs in both the spatial and temporal directions. Monte Carlo studies reveal that the two cutoffs can be removed in the large-N limit and that the theory thus obtained has no parameters other than one scale parameter. Moreover, we find that three out of nine spatial directions start to expand at some "critical time," after which the space has SO(3) symmetry instead of SO(9).

Matrix elements of explicitly correlated Gaussian basis functions with arbitrary angular momentum

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

Joyce, Tennesse; Varga, Kálmán

2016-05-14

A new algorithm for calculating the Hamiltonian matrix elements with all-electron explicitly correlated Gaussian functions for quantum-mechanical calculations of atoms with arbitrary angular momentum is presented. The calculations are checked on several excited states of three and four electron systems. The presented formalism can be used as unified framework for high accuracy calculations of properties of small atoms and molecules.

Magnetic resonance microscopy for assessment of morphological changes in hydrating hydroxypropylmethylcellulose matrix tablets in situ-is it possible to detect phenomena related to drug dissolution within the hydrated matrices?

PubMed

Kulinowski, Piotr; Młynarczyk, Anna; Jasiński, Krzysztof; Talik, Przemysław; Gruwel, Marco L H; Tomanek, Bogusław; Węglarz, Władysław P; Dorożyński, Przemysław

2014-09-01

So far, the hydrated part of the HPMC matrix has commonly been denoted as a "gel" or "pseudogel" layer. No MRI-based results have been published regarding observation of internal phenomena related to drug dissolution inside swelling polymeric matrices during hydration. The purpose of the study was to detect such phenomena. Multiparametric, spatially and temporally resolved T2 MR relaxometry, in situ, was applied to study formation of the hydration progress in HPMC matrix tablets loaded with L-dopa and ketoprofen using a 11.7 T MRI system. Two spin-echo based pulse sequences were used, one of them specifically designed to study short T2 signals. Two components in the T2 decay envelope were estimated and spatial distributions of their parameters, i.e. amplitudes and T2 values, were obtained. Based on the data, different region formation patterns (i.e. multilayer structure) were registered depending on drug presence and solubility. Inside the matrix with incorporated sparingly soluble drug a specific layer formation due to drug dissolution was detected, whereas a matrix with very slightly soluble drug does not form distinct external "gel-like" layer. We have introduced a new paradigm in the characterization of hydrating matrices using (1)H MRI methods. It reflects molecular mobility and concentration of water inside the hydrated matrix. For the first time, drug dissolution related phenomena, i.e. particular front and region formation, were observed by MRI methods.

Species extinction thresholds in the face of spatially correlated periodic disturbance.

PubMed

Liao, Jinbao; Ying, Zhixia; Hiebeler, David E; Wang, Yeqiao; Takada, Takenori; Nijs, Ivan

2015-10-20

The spatial correlation of disturbance is gaining attention in landscape ecology, but knowledge is still lacking on how species traits determine extinction thresholds under spatially correlated disturbance regimes. Here we develop a pair approximation model to explore species extinction risk in a lattice-structured landscape subject to aggregated periodic disturbance. Increasing disturbance extent and frequency accelerated population extinction irrespective of whether dispersal was local or global. Spatial correlation of disturbance likewise increased species extinction risk, but only for local dispersers. This indicates that models based on randomly simulated disturbances (e.g., mean-field or non-spatial models) may underestimate real extinction rates. Compared to local dispersal, species with global dispersal tolerated more severe disturbance, suggesting that the spatial correlation of disturbance favors long-range dispersal from an evolutionary perspective. Following disturbance, intraspecific competition greatly enhanced the extinction risk of distance-limited dispersers, while it surprisingly did not influence the extinction thresholds of global dispersers, apart from decreasing population density to some degree. As species respond differently to disturbance regimes with different spatiotemporal properties, different regimes may accommodate different species.

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

Niu, T; Dong, X; Petrongolo, M

Purpose: Dual energy CT (DECT) imaging plays an important role in advanced imaging applications due to its material decomposition capability. Direct decomposition via matrix inversion suffers from significant degradation of image signal-to-noise ratios, which reduces clinical value. Existing de-noising algorithms achieve suboptimal performance since they suppress image noise either before or after the decomposition and do not fully explore the noise statistical properties of the decomposition process. We propose an iterative image-domain decomposition method for noise suppression in DECT, using the full variance-covariance matrix of the decomposed images. Methods: The proposed algorithm is formulated in the form of least-square estimationmore » with smoothness regularization. It includes the inverse of the estimated variance-covariance matrix of the decomposed images as the penalty weight in the least-square term. Performance is evaluated using an evaluation phantom (Catphan 600) and an anthropomorphic head phantom. Results are compared to those generated using direct matrix inversion with no noise suppression, a de-noising method applied on the decomposed images, and an existing algorithm with similar formulation but with an edge-preserving regularization term. Results: On the Catphan phantom, our method retains the same spatial resolution as the CT images before decomposition while reducing the noise standard deviation of decomposed images by over 98%. The other methods either degrade spatial resolution or achieve less low-contrast detectability. Also, our method yields lower electron density measurement error than direct matrix inversion and reduces error variation by over 97%. On the head phantom, it reduces the noise standard deviation of decomposed images by over 97% without blurring the sinus structures. Conclusion: We propose an iterative image-domain decomposition method for DECT. The method combines noise suppression and material decomposition into an iterative process and achieves both goals simultaneously. The proposed algorithm shows superior performance on noise suppression with high image spatial resolution and low-contrast detectability. This work is supported by a Varian MRA grant.« less

Effective correlator for RadioAstron project

NASA Astrophysics Data System (ADS)

Sergeev, Sergey

This paper presents the implementation of programme FX-correlator for Very Long Baseline Interferometry, adapted for the project "RadioAstron". Software correlator implemented for heterogeneous computing systems using graphics accelerators. It is shown that for the task interferometry implementation of the graphics hardware has a high efficiency. The host processor of heterogeneous computing system, performs the function of forming the data flow for graphics accelerators, the number of which corresponds to the number of frequency channels. So, for the Radioastron project, such channels is seven. Each accelerator is perform correlation matrix for all bases for a single frequency channel. Initial data is converted to the floating-point format, is correction for the corresponding delay function and computes the entire correlation matrix simultaneously. Calculation of the correlation matrix is performed using the sliding Fourier transform. Thus, thanks to the compliance of a solved problem for architecture graphics accelerators, managed to get a performance for one processor platform Kepler, which corresponds to the performance of this task, the computing cluster platforms Intel on four nodes. This task successfully scaled not only on a large number of graphics accelerators, but also on a large number of nodes with multiple accelerators.

Exchange-correlation approximations for reduced-density-matrix-functional theory at finite temperature: Capturing magnetic phase transitions in the homogeneous electron gas

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

Baldsiefen, Tim; Cangi, Attila; Eich, F. G.

Here, we derive an intrinsically temperature-dependent approximation to the correlation grand potential for many-electron systems in thermodynamical equilibrium in the context of finite-temperature reduced-density-matrix-functional theory (FT-RDMFT). We demonstrate its accuracy by calculating the magnetic phase diagram of the homogeneous electron gas. We compare it to known limits from highly accurate quantum Monte Carlo calculations as well as to phase diagrams obtained within existing exchange-correlation approximations from density functional theory and zero-temperature RDMFT.

Exchange-correlation approximations for reduced-density-matrix-functional theory at finite temperature: Capturing magnetic phase transitions in the homogeneous electron gas

DOE PAGES

Baldsiefen, Tim; Cangi, Attila; Eich, F. G.; ...

2017-12-18

Here, we derive an intrinsically temperature-dependent approximation to the correlation grand potential for many-electron systems in thermodynamical equilibrium in the context of finite-temperature reduced-density-matrix-functional theory (FT-RDMFT). We demonstrate its accuracy by calculating the magnetic phase diagram of the homogeneous electron gas. We compare it to known limits from highly accurate quantum Monte Carlo calculations as well as to phase diagrams obtained within existing exchange-correlation approximations from density functional theory and zero-temperature RDMFT.

Spatial operator approach to flexible multibody system dynamics and control

NASA Technical Reports Server (NTRS)

Rodriguez, G.

1991-01-01

The inverse and forward dynamics problems for flexible multibody systems were solved using the techniques of spatially recursive Kalman filtering and smoothing. These algorithms are easily developed using a set of identities associated with mass matrix factorization and inversion. These identities are easily derived using the spatial operator algebra developed by the author. Current work is aimed at computational experiments with the described algorithms and at modelling for control design of limber manipulator systems. It is also aimed at handling and manipulation of flexible objects.

Generalized sub-Schawlow-Townes laser linewidths via material dispersion

NASA Astrophysics Data System (ADS)

Pillay, Jason Cornelius; Natsume, Yuki; Stone, A. Douglas; Chong, Y. D.

2014-03-01

A recent S-matrix-based theory of the quantum-limited linewidth, which is applicable to general lasers, including spatially nonuniform laser cavities operating above threshold, is analyzed in various limits. For broadband gain, a simple interpretation of the Petermann and bad-cavity factors is presented in terms of geometric relations between the zeros and poles of the S matrix. When there is substantial dispersion, on the frequency scale of the cavity lifetime, the theory yields a generalization of the bad-cavity factor, which was previously derived for spatially uniform one-dimensional lasers. This effect can lead to sub-Schawlow-Townes linewidths in lasers with very narrow gain widths. We derive a formula for the linewidth in terms of the lasing mode functions, which has accuracy comparable to the previous formula involving the residue of the lasing pole. These results for the quantum-limited linewidth are valid even in the regime of strong line pulling and spatial hole burning, where the linewidth cannot be factorized into independent Petermann and bad-cavity factors.

AP-MALDI Mass Spectrometry Imaging of Gangliosides Using 2,6-Dihydroxyacetophenone

NASA Astrophysics Data System (ADS)

Jackson, Shelley N.; Muller, Ludovic; Roux, Aurelie; Oktem, Berk; Moskovets, Eugene; Doroshenko, Vladimir M.; Woods, Amina S.

2018-03-01

Matrix-assisted laser/desorption ionization (MALDI) mass spectrometry imaging (MSI) is widely used as a unique tool to record the distribution of a large range of biomolecules in tissues. 2,6-Dihydroxyacetophenone (DHA) matrix has been shown to provide efficient ionization of lipids, especially gangliosides. The major drawback for DHA as it applies to MS imaging is that it sublimes under vacuum (low pressure) at the extended time necessary to complete both high spatial and mass resolution MSI studies of whole organs. To overcome the problem of sublimation, we used an atmospheric pressure (AP)-MALDI source to obtain high spatial resolution images of lipids in the brain using a high mass resolution mass spectrometer. Additionally, the advantages of atmospheric pressure and DHA for imaging gangliosides are highlighted. The imaging of [M-H]- and [M-H2O-H]- mass peaks for GD1 gangliosides showed different distribution, most likely reflecting the different spatial distribution of GD1a and GD1b species in the brain. [Figure not available: see fulltext.

A familiar pattern? Semantic memory contributes to the enhancement of visuo-spatial memories.

PubMed

Riby, Leigh M; Orme, Elizabeth

2013-03-01

In this study we quantify for the first time electrophysiological components associated with incorporating long-term semantic knowledge with visuo-spatial information using two variants of a traditional matrix patterns task. Results indicated that the matrix task with greater semantic content was associated with enhanced accuracy and RTs in a change-detection paradigm; this was also associated with increased P300 and N400 components as well as a sustained negative slow wave (NSW). In contrast, processing of the low semantic stimuli was associated with an increased N200 and a reduction in the P300. These findings suggest that semantic content can aid in reducing early visual processing of information and subsequent memory load by unitizing complex patterns into familiar forms. The N400/NSW may be associated with the requirements for maintaining visuo-spatial information about semantic forms such as orientation and relative location. Evidence for individual differences in semantic elaboration strategies used by participants is also discussed. Copyright © 2012 Elsevier Inc. All rights reserved.

Evaluation of entropy and JM-distance criterions as features selection methods using spectral and spatial features derived from LANDSAT images

NASA Technical Reports Server (NTRS)

Parada, N. D. J. (Principal Investigator); Dutra, L. V.; Mascarenhas, N. D. A.; Mitsuo, Fernando Augusta, II

1984-01-01

A study area near Ribeirao Preto in Sao Paulo state was selected, with predominance in sugar cane. Eight features were extracted from the 4 original bands of LANDSAT image, using low-pass and high-pass filtering to obtain spatial features. There were 5 training sites in order to acquire the necessary parameters. Two groups of four channels were selected from 12 channels using JM-distance and entropy criterions. The number of selected channels was defined by physical restrictions of the image analyzer and computacional costs. The evaluation was performed by extracting the confusion matrix for training and tests areas, with a maximum likelihood classifier, and by defining performance indexes based on those matrixes for each group of channels. Results show that in spatial features and supervised classification, the entropy criterion is better in the sense that allows a more accurate and generalized definition of class signature. On the other hand, JM-distance criterion strongly reduces the misclassification within training areas.

Spectral-Spatial Shared Linear Regression for Hyperspectral Image Classification.

PubMed

Haoliang Yuan; Yuan Yan Tang

2017-04-01

Classification of the pixels in hyperspectral image (HSI) is an important task and has been popularly applied in many practical applications. Its major challenge is the high-dimensional small-sized problem. To deal with this problem, lots of subspace learning (SL) methods are developed to reduce the dimension of the pixels while preserving the important discriminant information. Motivated by ridge linear regression (RLR) framework for SL, we propose a spectral-spatial shared linear regression method (SSSLR) for extracting the feature representation. Comparing with RLR, our proposed SSSLR has the following two advantages. First, we utilize a convex set to explore the spatial structure for computing the linear projection matrix. Second, we utilize a shared structure learning model, which is formed by original data space and a hidden feature space, to learn a more discriminant linear projection matrix for classification. To optimize our proposed method, an efficient iterative algorithm is proposed. Experimental results on two popular HSI data sets, i.e., Indian Pines and Salinas demonstrate that our proposed methods outperform many SL methods.

Correlation, Cost Risk, and Geometry

NASA Technical Reports Server (NTRS)

Dean, Edwin B.

1992-01-01

The geometric viewpoint identifies the choice of a correlation matrix for the simulation of cost risk with the pairwise choice of data vectors corresponding to the parameters used to obtain cost risk. The correlation coefficient is the cosine of the angle between the data vectors after translation to an origin at the mean and normalization for magnitude. Thus correlation is equivalent to expressing the data in terms of a non orthogonal basis. To understand the many resulting phenomena requires the use of the tensor concept of raising the index to transform the measured and observed covariant components into contravariant components before vector addition can be applied. The geometric viewpoint also demonstrates that correlation and covariance are geometric properties, as opposed to purely statistical properties, of the variates. Thus, variates from different distributions may be correlated, as desired, after selection from independent distributions. By determining the principal components of the correlation matrix, variates with the desired mean, magnitude, and correlation can be generated through linear transforms which include the eigenvalues and the eigenvectors of the correlation matrix. The conversion of the data to a non orthogonal basis uses a compound linear transformation which distorts or stretches the data space. Hence, the correlated data does not have the same properties as the uncorrelated data used to generate it. This phenomena is responsible for seemingly strange observations such as the fact that the marginal distributions of the correlated data can be quite different from the distributions used to generate the data. The joint effect of statistical distributions and correlation remains a fertile area for further research. In terms of application to cost estimating, the geometric approach demonstrates that the estimator must have data and must understand that data in order to properly choose the correlation matrix appropriate for a given estimate. There is a general feeling by employers and managers that the field of cost requires little technical or mathematical background. Contrary to that opinion, this paper demonstrates that a background in mathematics equivalent to that needed for typical engineering and scientific disciplines at the masters or doctorate level is appropriate within the field of cost risk.

Spatial compression algorithm for the analysis of very large multivariate images

DOEpatents

Keenan, Michael R [Albuquerque, NM

2008-07-15

A method for spatially compressing data sets enables the efficient analysis of very large multivariate images. The spatial compression algorithms use a wavelet transformation to map an image into a compressed image containing a smaller number of pixels that retain the original image's information content. Image analysis can then be performed on a compressed data matrix consisting of a reduced number of significant wavelet coefficients. Furthermore, a block algorithm can be used for performing common operations more efficiently. The spatial compression algorithms can be combined with spectral compression algorithms to provide further computational efficiencies.

Quantification of spatial and seasonal variations in the proportional contribution of nitrate sources using a multi-isotope approach and Bayesian isotope mixing model.

PubMed

Meghdadi, Aminreza; Javar, Narmin

2018-04-01

Spatial and seasonal variations in nitrate contamination are a globally concern. While numerous studies have used δ 15 N-NO 3 and δ 18 O-NO 3 to elucidate the dominant sources of nitrate in groundwater, this approach has significant limitations due to the overlap of nitrate isotopic ranges and the occurrence of nitrate isotopic fractionation. This study quantitatively assessed the spatial and seasonal variations in the proportional contributions of nitrate sources from different land uses in the Tarom watershed in North-West Iran. To achieve this aim, orthogonal projection of the hydrochemical and isotopic dataset of the principal component analysis (PCA) as well as correlation coefficient matrix (Corr-PCA) were evaluated to reduce the dimensionality of the inter-correlated dataset. Next, a nitrate isotopic biplot accompanied with a Bayesian isotope mixing model (SIAR) were applied to specify the spatial and seasonal trends in the proportional contribution of three dominant sources of nitrate (fertilizers, animal manure and residential waste) in the watershed. Finally, in order to provide a sensitive framework for nitrate source appointment and overcome the associated limitations of dual nitrate isotope application, the integration of boron isotope (δ 11 B) and strontium isotopic ratio ( 87 Sr/ 86 Sr) was introduced. The results revealed that the mean contribution of residential sewage increased (17%-27.5%), while the mean contribution of fertilizers decreased (28.3%-19%), from late spring to early autumn. Also, fertilizer was the highest contributor (42.1% ± 3.2) during late spring, especially in regions with more than 75% agricultural land. Meanwhile, the mean contribution of sewage was highest in early autumn (32.1% ± 2.8) in the areas with more than 20% residential land. These results were confirmed by coupled application of δ 11 B and 87 Sr/ 86 Sr. This study provides a useful insight for environmental managers to verify groundwater pollution contributors and to better apply remedial solutions. Copyright © 2017 Elsevier Ltd. All rights reserved.

Combined X-ray CT and mass spectrometry for biomedical imaging applications

NASA Astrophysics Data System (ADS)

Schioppa, E., Jr.; Ellis, S.; Bruinen, A. L.; Visser, J.; Heeren, R. M. A.; Uher, J.; Koffeman, E.

2014-04-01

Imaging technologies play a key role in many branches of science, especially in biology and medicine. They provide an invaluable insight into both internal structure and processes within a broad range of samples. There are many techniques that allow one to obtain images of an object. Different techniques are based on the analysis of a particular sample property by means of a dedicated imaging system, and as such, each imaging modality provides the researcher with different information. The use of multimodal imaging (imaging with several different techniques) can provide additional and complementary information that is not possible when employing a single imaging technique alone. In this study, we present for the first time a multi-modal imaging technique where X-ray computerized tomography (CT) is combined with mass spectrometry imaging (MSI). While X-ray CT provides 3-dimensional information regarding the internal structure of the sample based on X-ray absorption coefficients, MSI of thin sections acquired from the same sample allows the spatial distribution of many elements/molecules, each distinguished by its unique mass-to-charge ratio (m/z), to be determined within a single measurement and with a spatial resolution as low as 1 μm or even less. The aim of the work is to demonstrate how molecular information from MSI can be spatially correlated with 3D structural information acquired from X-ray CT. In these experiments, frozen samples are imaged in an X-ray CT setup using Medipix based detectors equipped with a CO2 cooled sample holder. Single projections are pre-processed before tomographic reconstruction using a signal-to-thickness calibration. In the second step, the object is sliced into thin sections (circa 20 μm) that are then imaged using both matrix-assisted laser desorption/ionization mass spectrometry (MALDI-MS) and secondary ion (SIMS) mass spectrometry, where the spatial distribution of specific molecules within the sample is determined. The combination of two vastly different imaging approaches provides complementary information (i.e., anatomical and molecular distributions) that allows the correlation of distinct structural features with specific molecules distributions leading to unique insights in disease development.

Analyses and assessments of span wise gust gradient data from NASA B-57B aircraft

NASA Technical Reports Server (NTRS)

Frost, Walter; Chang, Ho-Pen; Ringnes, Erik A.

1987-01-01

Analysis of turbulence measured across the airfoil of a Cambera B-57 aircraft is reported. The aircraft is instrumented with probes for measuring wind at both wing tips and at the nose. Statistical properties of the turbulence are reported. These consist of the standard deviations of turbulence measured by each individual probe, standard deviations and probability distribution of differences in turbulence measured between probes and auto- and two-point spatial correlations and spectra. Procedures associated with calculations of two-point spatial correlations and spectra utilizing data were addressed. Methods and correction procedures for assuring the accuracy of aircraft measured winds are also described. Results are found, in general, to agree with correlations existing in the literature. The velocity spatial differences fit a Gaussian/Bessel type probability distribution. The turbulence agrees with the von Karman turbulence correlation and with two-point spatial correlations developed from the von Karman correlation.

Modeling space-time correlations of velocity fluctuations in wind farms

NASA Astrophysics Data System (ADS)

Lukassen, Laura J.; Stevens, Richard J. A. M.; Meneveau, Charles; Wilczek, Michael

2018-07-01

An analytical model for the streamwise velocity space-time correlations in turbulent flows is derived and applied to the special case of velocity fluctuations in large wind farms. The model is based on the Kraichnan-Tennekes random sweeping hypothesis, capturing the decorrelation in time while including a mean wind velocity in the streamwise direction. In the resulting model, the streamwise velocity space-time correlation is expressed as a convolution of the pure space correlation with an analytical temporal decorrelation kernel. Hence, the spatio-temporal structure of velocity fluctuations in wind farms can be derived from the spatial correlations only. We then explore the applicability of the model to predict spatio-temporal correlations in turbulent flows in wind farms. Comparisons of the model with data from a large eddy simulation of flow in a large, spatially periodic wind farm are performed, where needed model parameters such as spatial and temporal integral scales and spatial correlations are determined from the large eddy simulation. Good agreement is obtained between the model and large eddy simulation data showing that spatial data may be used to model the full temporal structure of fluctuations in wind farms.

Matrix isolation studies of hydrogen bonding - An historical perspective

NASA Astrophysics Data System (ADS)

Barnes, Austin J.

2018-07-01

An historical introduction sets matrix isolation in perspective with other spectroscopic techniques for studying hydrogen-bonded complexes. This is followed by detailed accounts of various aspects of hydrogen-bonded complexes that have been studied using matrix isolation spectroscopy: Matrix effects: stabilisation of complexes. Strongly hydrogen-bonded molecular complexes: the vibrational correlation diagram. Anomalous spectra: the Ratajczak-Yaremko model. Metastable complexes. Csbnd H hydrogen bonding and blue shifting hydrogen bonds.

Structure-performance relationships of phenyl cinnamic acid derivatives as MALDI-MS matrices for sulfatide detection.

PubMed

Tambe, Suparna; Blott, Henning; Fülöp, Annabelle; Spang, Nils; Flottmann, Dirk; Bräse, Stefan; Hopf, Carsten; Junker, Hans-Dieter

2017-02-01

A key aspect for the further development of matrix-assisted laser desorption ionization (MALDI)-mass spectrometry (MS) is a better understanding of the working principles of MALDI matrices. To address this issue, a chemical compound library of 59 structurally related cinnamic acid derivatives was synthesized. Potential MALDI matrices were evaluated with sulfatides, a class of anionic lipids which are abundant in complex brain lipid mixtures. For each matrix relative mean S/N ratios of sulfatides were determined against 9-aminoacridine as a reference matrix using negative ion mass spectrometry with 355 and 337 nm laser systems. The comparison of matrix features with their corresponding relative mean S/N ratios for sulfatide detection identified correlations between matrix substitution patterns, their chemical functionality, and their MALDI-MS performance. Crystal structures of six selected matrices provided structural insight in hydrogen bond interactions in the solid state. Principal component analysis allowed the additional identification of correlation trends between structural and physical matrix properties like number of exchangeable protons at the head group, MW, logP, UV-Vis, and sulfatide detection sensitivity. Graphical abstract Design, synthesis and mass spectrometric evaluation of MALDI-MS matrix compound libraries allows the identification of matrix structure - MALDI-MS performance relationships using multivariate statistics as a tool.

Combining Correlation Matrices: Simulation Analysis of Improved Fixed-Effects Methods

ERIC Educational Resources Information Center

Hafdahl, Adam R.

2007-01-01

The originally proposed multivariate meta-analysis approach for correlation matrices--analyze Pearson correlations, with each study's observed correlations replacing their population counterparts in its conditional-covariance matrix--performs poorly. Two refinements are considered: Analyze Fisher Z-transformed correlations, and substitute better…

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

NASA Astrophysics Data System (ADS)

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

2013-09-01

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

Analysis of field-scale spatial correlations and variations of soil nutrients using geostatistics.

PubMed

Liu, Ruimin; Xu, Fei; Yu, Wenwen; Shi, Jianhan; Zhang, Peipei; Shen, Zhenyao

2016-02-01

Spatial correlations and soil nutrient variations are important for soil nutrient management. They help to reduce the negative impacts of agricultural nonpoint source pollution. Based on the sampled available nitrogen (AN), available phosphorus (AP), and available potassium (AK), soil nutrient data from 2010, the spatial correlation, was analyzed, and the probabilities of the nutrient's abundance or deficiency were discussed. This paper presents a statistical approach to spatial analysis, the spatial correlation analysis (SCA), which was originally developed for describing heterogeneity in the presence of correlated variation and based on ordinary kriging (OK) results. Indicator kriging (IK) was used to assess the susceptibility of excess of soil nutrients based on crop needs. The kriged results showed there was a distinct spatial variability in the concentration of all three soil nutrients. High concentrations of these three soil nutrients were found near Anzhou. As the distance from the center of town increased, the concentration of the soil nutrients gradually decreased. Spatially, the relationship between AN and AP was negative, and the relationship between AP and AK was not clear. The IK results showed that there were few areas with a risk of AN and AP overabundance. However, almost the entire study region was at risk of AK overabundance. Based on the soil nutrient distribution results, it is clear that the spatial variability of the soil nutrients differed throughout the study region. This spatial soil nutrient variability might be caused by different fertilizer types and different fertilizing practices.

Empirical data and the variance-covariance matrix for the 1969 Smithsonian Standard Earth (2)

NASA Technical Reports Server (NTRS)

Gaposchkin, E. M.

1972-01-01

The empirical data used in the 1969 Smithsonian Standard Earth (2) are presented. The variance-covariance matrix, or the normal equations, used for correlation analysis, are considered. The format and contents of the matrix, available on magnetic tape, are described and a sample printout is given.

Low-temperature matrix effects on orientational motion of Methyl radical trapped in gas solids: Angular tunneling vs. libration

NASA Astrophysics Data System (ADS)

Dmitriev, Yurij A.; Zelenetckii, Ilia A.; Benetis, Nikolas P.

2018-05-01

EPR investigation of the lineshape of matrix -isolated methyl radical, CH3, spectra recorded in solid N2O and CO2 was carried out. Reversible temperature-dependent line width anisotropy was observed in both matrices. This effect is a fingerprint of the extra-slow radical rotation about the in-plane C2 axes. The rotation was found to be anisotropic and closely correlated to the orientational dynamics of the matrix molecules. It was suggested that a recently discovered "hoping precession" effect of matrix molecules in solid CO2 is a common feature of matrices of the linear molecules CO, N2O, and CO2. A new low-temperature matrix effect, referred to as "libration trap", was proposed which accounts for the changing CH3 reorientational motion about the radical C3-axis from rotation to libration. Temperature dependence of the intensity of the EPR satellites produced by these nonrotating-but librating methyls was presented. This allowed for a rough estimation of the rotation hindering potential due to correlation mismatch between the radical and the nearest matrix molecules' librations.

Entanglement convertibility by sweeping through the quantum phases of the alternating bonds XXZ chain

PubMed Central

Tzeng, Yu-Chin; Dai, Li; Chung, Ming-Chiang; Amico, Luigi; Kwek, Leong-Chuan

2016-01-01

We study the entanglement structure and the topological edge states of the ground state of the spin-1/2 XXZ model with bond alternation. We employ parity-density matrix renormalization group with periodic boundary conditions. The finite-size scaling of Rényi entropies S2 and S∞ are used to construct the phase diagram of the system. The phase diagram displays three possible phases: Haldane type (an example of symmetry protected topological ordered phases), Classical Dimer and Néel phases, the latter bounded by two continuous quantum phase transitions. The entanglement and non-locality in the ground state are studied and quantified by the entanglement convertibility. We found that, at small spatial scales, the ground state is not convertible within the topological Haldane dimer phase. The phenomenology we observe can be described in terms of correlations between edge states. We found that the entanglement spectrum also exhibits a distinctive response in the topological phase: the effective rank of the reduced density matrix displays a specifically large “susceptibility” in the topological phase. These findings support the idea that although the topological order in the ground state cannot be detected by local inspection, the ground state response at local scale can tell the topological phases apart from the non-topological phases. PMID:27216970

The evolutionary stability of cross-sex, cross-trait genetic covariances.

PubMed

Gosden, Thomas P; Chenoweth, Stephen F

2014-06-01

Although knowledge of the selective agents behind the evolution of sexual dimorphism has advanced considerably in recent years, we still lack a clear understanding of the evolutionary durability of cross-sex genetic covariances that often constrain its evolution. We tested the relative stability of cross-sex genetic covariances for a suite of homologous contact pheromones of the fruit fly Drosophila serrata, along a latitudinal gradient where these traits have diverged in mean. Using a Bayesian framework, which allowed us to account for uncertainty in all parameter estimates, we compared divergence in the total amount and orientation of genetic variance across populations, finding divergence in orientation but not total variance. We then statistically compared orientation divergence of within-sex (G) to cross-sex (B) covariance matrices. In line with a previous theoretical prediction, we find that the cross-sex covariance matrix, B, is more variable than either within-sex G matrix. Decomposition of B matrices into their symmetrical and nonsymmetrical components revealed that instability is linked to the degree of asymmetry. We also find that the degree of asymmetry correlates with latitude suggesting a role for spatially varying natural selection in shaping genetic constraints on the evolution of sexual dimorphism. © 2014 The Author(s). Evolution © 2014 The Society for the Study of Evolution.

In Situ Molecular Imaging of the Biofilm and Its Matrix.

PubMed

Ding, Yuanzhao; Zhou, Yufan; Yao, Juan; Szymanski, Craig; Fredrickson, James; Shi, Liang; Cao, Bin; Zhu, Zihua; Yu, Xiao-Ying

2016-11-15

Molecular mapping of live biofilms at submicrometer resolution presents a grand challenge. Here, we present the first chemical mapping results of biofilm extracellular polymeric substance (EPS) in biofilms using correlative imaging between super resolution fluorescence microscopy and liquid time-of-flight secondary ion mass spectrometry (TOF-SIMS). Shewanella oneidensis is used as a model organism. Heavy metal chromate (Cr 2 O 7 2- ) anions consisting of chromium Cr(VI) was used as a model environmental stressor to treat the biofilms. Of particular interest, biologically relevant water clusters have been first observed in the biofilms. Characteristic fragments of biofilm matrix components such as proteins, polysaccharides, and lipids can be spatially imaged. Furthermore, characteristic fatty acids (e.g., palmitic acid), quinolone signal, and riboflavin fragments were found to respond after the biofilm is treated with Cr(VI), leading to biofilm dispersal. Significant changes in water clusters and quorum sensing signals indicative of intercellular communication in the aqueous environment were observed, suggesting that they might result in fatty acid synthesis and inhibition of riboflavin production. The Cr(VI) reduction seems to follow the Mtr pathway leading to Cr(III) formation. Our approach potentially opens a new avenue for mechanistic insight of microbial community processes and communications using in situ imaging mass spectrometry and super resolution optical microscopy.

Adaptive bearing estimation and tracking of multiple targets in a realistic passive sonar scenario

NASA Astrophysics Data System (ADS)

Rajagopal, R.; Challa, Subhash; Faruqi, Farhan A.; Rao, P. R.

1997-06-01

In a realistic passive sonar environment, the received signal consists of multipath arrivals from closely separated moving targets. The signals are contaminated by spatially correlated noise. The differential MUSIC has been proposed to estimate the DOAs in such a scenario. This method estimates the 'noise subspace' in order to estimate the DOAs. However, the 'noise subspace' estimate has to be updated as and when new data become available. In order to save the computational costs, a new adaptive noise subspace estimation algorithm is proposed in this paper. The salient features of the proposed algorithm are: (1) Noise subspace estimation is done by QR decomposition of the difference matrix which is formed from the data covariance matrix. Thus, as compared to standard eigen-decomposition based methods which require O(N3) computations, the proposed method requires only O(N2) computations. (2) Noise subspace is updated by updating the QR decomposition. (3) The proposed algorithm works in a realistic sonar environment. In the second part of the paper, the estimated bearing values are used to track multiple targets. In order to achieve this, the nonlinear system/linear measurement extended Kalman filtering proposed is applied. Computer simulation results are also presented to support the theory.

Entanglement convertibility by sweeping through the quantum phases of the alternating bonds XXZ chain.

PubMed

Tzeng, Yu-Chin; Dai, Li; Chung, Ming-Chiang; Amico, Luigi; Kwek, Leong-Chuan

2016-05-24

We study the entanglement structure and the topological edge states of the ground state of the spin-1/2 XXZ model with bond alternation. We employ parity-density matrix renormalization group with periodic boundary conditions. The finite-size scaling of Rényi entropies S2 and S∞ are used to construct the phase diagram of the system. The phase diagram displays three possible phases: Haldane type (an example of symmetry protected topological ordered phases), Classical Dimer and Néel phases, the latter bounded by two continuous quantum phase transitions. The entanglement and non-locality in the ground state are studied and quantified by the entanglement convertibility. We found that, at small spatial scales, the ground state is not convertible within the topological Haldane dimer phase. The phenomenology we observe can be described in terms of correlations between edge states. We found that the entanglement spectrum also exhibits a distinctive response in the topological phase: the effective rank of the reduced density matrix displays a specifically large "susceptibility" in the topological phase. These findings support the idea that although the topological order in the ground state cannot be detected by local inspection, the ground state response at local scale can tell the topological phases apart from the non-topological phases.

Quantitative second-harmonic generation imaging to detect osteogenesis imperfecta in human skin samples

NASA Astrophysics Data System (ADS)

Adur, J.; Ferreira, A. E.; D'Souza-Li, L.; Pelegati, V. B.; de Thomaz, A. A.; Almeida, D. B.; Baratti, M. O.; Carvalho, H. F.; Cesar, C. L.

2012-03-01

Osteogenesis Imperfecta (OI) is a genetic disorder that leads to bone fractures due to mutations in the Col1A1 or Col1A2 genes that affect the primary structure of the collagen I chain with the ultimate outcome in collagen I fibrils that are either reduced in quantity or abnormally organized in the whole body. A quick test screening of the patients would largely reduce the sample number to be studied by the time consuming molecular genetics techniques. For this reason an assessment of the human skin collagen structure by Second Harmonic Generation (SHG) can be used as a screening technique to speed up the correlation of genetics/phenotype/OI types understanding. In the present work we have used quantitative second harmonic generation (SHG) imaging microscopy to investigate the collagen matrix organization of the OI human skin samples comparing with normal control patients. By comparing fibril collagen distribution and spatial organization, we calculated the anisotropy and texture patterns of this structural protein. The analysis of the anisotropy was performed by means of the two-dimensional Discrete Fourier Transform and image pattern analysis with Gray-Level Co-occurrence Matrix (GLCM). From these results, we show that statistically different results are obtained for the normal and disease states of OI.

S-matrix analysis of the baryon electric charge correlation

NASA Astrophysics Data System (ADS)

Lo, Pok Man; Friman, Bengt; Redlich, Krzysztof; Sasaki, Chihiro

2018-03-01

We compute the correlation of the net baryon number with the electric charge (χBQ) for an interacting hadron gas using the S-matrix formulation of statistical mechanics. The observable χBQ is particularly sensitive to the details of the pion-nucleon interaction, which are consistently incorporated in the current scheme via the empirical scattering phase shifts. Comparing to the recent lattice QCD studies in the (2 + 1)-flavor system, we find that the natural implementation of interactions and the proper treatment of resonances in the S-matrix approach lead to an improved description of the lattice data over that obtained in the hadron resonance gas model.

A class of parallel algorithms for computation of the manipulator inertia matrix

NASA Technical Reports Server (NTRS)

Fijany, Amir; Bejczy, Antal K.

1989-01-01

Parallel and parallel/pipeline algorithms for computation of the manipulator inertia matrix are presented. An algorithm based on composite rigid-body spatial inertia method, which provides better features for parallelization, is used for the computation of the inertia matrix. Two parallel algorithms are developed which achieve the time lower bound in computation. Also described is the mapping of these algorithms with topological variation on a two-dimensional processor array, with nearest-neighbor connection, and with cardinality variation on a linear processor array. An efficient parallel/pipeline algorithm for the linear array was also developed, but at significantly higher efficiency.

Efficient Storage Scheme of Covariance Matrix during Inverse Modeling

NASA Astrophysics Data System (ADS)

Mao, D.; Yeh, T. J.

2013-12-01

During stochastic inverse modeling, the covariance matrix of geostatistical based methods carries the information about the geologic structure. Its update during iterations reflects the decrease of uncertainty with the incorporation of observed data. For large scale problem, its storage and update cost too much memory and computational resources. In this study, we propose a new efficient storage scheme for storage and update. Compressed Sparse Column (CSC) format is utilized to storage the covariance matrix, and users can assign how many data they prefer to store based on correlation scales since the data beyond several correlation scales are usually not very informative for inverse modeling. After every iteration, only the diagonal terms of the covariance matrix are updated. The off diagonal terms are calculated and updated based on shortened correlation scales with a pre-assigned exponential model. The correlation scales are shortened by a coefficient, i.e. 0.95, every iteration to show the decrease of uncertainty. There is no universal coefficient for all the problems and users are encouraged to try several times. This new scheme is tested with 1D examples first. The estimated results and uncertainty are compared with the traditional full storage method. In the end, a large scale numerical model is utilized to validate this new scheme.

Tensor models, Kronecker coefficients and permutation centralizer algebras

NASA Astrophysics Data System (ADS)

Geloun, Joseph Ben; Ramgoolam, Sanjaye

2017-11-01

We show that the counting of observables and correlators for a 3-index tensor model are organized by the structure of a family of permutation centralizer algebras. These algebras are shown to be semi-simple and their Wedderburn-Artin decompositions into matrix blocks are given in terms of Clebsch-Gordan coefficients of symmetric groups. The matrix basis for the algebras also gives an orthogonal basis for the tensor observables which diagonalizes the Gaussian two-point functions. The centres of the algebras are associated with correlators which are expressible in terms of Kronecker coefficients (Clebsch-Gordan multiplicities of symmetric groups). The color-exchange symmetry present in the Gaussian model, as well as a large class of interacting models, is used to refine the description of the permutation centralizer algebras. This discussion is extended to a general number of colors d: it is used to prove the integrality of an infinite family of number sequences related to color-symmetrizations of colored graphs, and expressible in terms of symmetric group representation theory data. Generalizing a connection between matrix models and Belyi maps, correlators in Gaussian tensor models are interpreted in terms of covers of singular 2-complexes. There is an intriguing difference, between matrix and higher rank tensor models, in the computational complexity of superficially comparable correlators of observables parametrized by Young diagrams.

Four-Photon Imaging with Thermal Light

NASA Astrophysics Data System (ADS)

Wen, Feng; Xue, Xinxin; Zhang, Xun; Yuan, Chenzhi; Sun, Jia; Song, Jianping; Zhang, Yanpeng

2014-10-01

In a near-field four-photon correlation measurement, ghost imaging with classical incoherent light is investigated. By applying the Klyshko advanced-wave picture, we consider the properties of four-photon spatial correlation and find that the fourth-order spatial correlation function can be decomposed into multiple lower-order correlation functions. On the basis of the spatial correlation properties, a proof-of-principle four-photon ghost imaging is proposed, and the effect of each part in a fourth-order correlation function on imaging is also analyzed. In addition, the similarities and differences among ghost imaging by fourth-, second-, and third-order correlations are also discussed. It is shown that the contrast and visibility of fourth-order correlated imaging are improved significantly, while the resolution is unchanged. Such studies can be very useful in better understanding multi photon interference and multi-channel correlation imaging.

Correlative imaging reveals physiochemical heterogeneity of microcalcifications in human breast carcinomas.

PubMed

Kunitake, Jennie A M R; Choi, Siyoung; Nguyen, Kayla X; Lee, Meredith M; He, Frank; Sudilovsky, Daniel; Morris, Patrick G; Jochelson, Maxine S; Hudis, Clifford A; Muller, David A; Fratzl, Peter; Fischbach, Claudia; Masic, Admir; Estroff, Lara A

2018-04-01

Microcalcifications (MCs) are routinely used to detect breast cancer in mammography. Little is known, however, about their materials properties and associated organic matrix, or their correlation to breast cancer prognosis. We combine histopathology, Raman microscopy, and electron microscopy to image MCs within snap-frozen human breast tissue and generate micron-scale resolution correlative maps of crystalline phase, trace metals, particle morphology, and organic matrix chemical signatures within high grade ductal carcinoma in situ (DCIS) and invasive cancer. We reveal the heterogeneity of mineral-matrix pairings, including punctate apatitic particles (<2 µm) with associated trace elements (e.g., F, Na, and unexpectedly Al) distributed within the necrotic cores of DCIS, and both apatite and spheroidal whitlockite particles in invasive cancer within a matrix containing spectroscopic signatures of collagen, non-collagen proteins, cholesterol, carotenoids, and DNA. Among the three DCIS samples, we identify key similarities in MC morphology and distribution, supporting a dystrophic mineralization pathway. This multimodal methodology lays the groundwork for establishing MC heterogeneity in the context of breast cancer biology, and could dramatically improve current prognostic models. Copyright © 2017 Elsevier Inc. All rights reserved.

On the Feynman-Hellmann theorem in quantum field theory and the calculation of matrix elements

DOE PAGES

Bouchard, Chris; Chang, Chia Cheng; Kurth, Thorsten; ...

2017-07-12

In this paper, the Feynman-Hellmann theorem can be derived from the long Euclidean-time limit of correlation functions determined with functional derivatives of the partition function. Using this insight, we fully develop an improved method for computing matrix elements of external currents utilizing only two-point correlation functions. Our method applies to matrix elements of any external bilinear current, including nonzero momentum transfer, flavor-changing, and two or more current insertion matrix elements. The ability to identify and control all the systematic uncertainties in the analysis of the correlation functions stems from the unique time dependence of the ground-state matrix elements and the fact that all excited states and contact terms are Euclidean-time dependent. We demonstrate the utility of our method with a calculation of the nucleon axial charge using gradient-flowed domain-wall valence quarks on themore » $$N_f=2+1+1$$ MILC highly improved staggered quark ensemble with lattice spacing and pion mass of approximately 0.15 fm and 310 MeV respectively. We show full control over excited-state systematics with the new method and obtain a value of $$g_A = 1.213(26)$$ with a quark-mass-dependent renormalization coefficient.« less

Development and experimental design of a novel controlled-release matrix tablet formulation for indapamide hemihydrate.

PubMed

Antovska, Packa; Ugarkovic, Sonja; Petruševski, Gjorgji; Stefanova, Bosilka; Manchevska, Blagica; Petkovska, Rumenka; Makreski, Petre

2017-11-01

Development, experimental design and in vitro in vivo correlation (IVIVC) of controlled-release matrix formulation. Development of novel oral controlled delivery system for indapamide hemihydrate, optimization of the formulation by experimental design and evaluation regarding IVIVC on a pilot scale batch as a confirmation of a well-established formulation. In vitro dissolution profiles of controlled-release tablets of indapamide hemihydrate from four different matrices had been evaluated in comparison to the originator's product Natrilix (Servier) as a direction for further development and optimization of a hydroxyethylcellulose-based matrix controlled-release formulation. A central composite factorial design had been applied for the optimization of a chosen controlled-release tablet formulation. The controlled-release tablets with appropriate physical and technological properties had been obtained with a matrix: binder concentration variations in the range: 20-40w/w% for the matrix and 1-3w/w% for the binder. The experimental design had defined the design space for the formulation and was prerequisite for extraction of a particular formulation that would be a subject for transfer on pilot scale and IVIV correlation. The release model of the optimized formulation has shown best fit to the zero order kinetics depicted with the Hixson-Crowell erosion-dependent mechanism of release. Level A correlation was obtained.

Method for estimating power outages and restoration during natural and man-made events

DOEpatents

Omitaomu, Olufemi A.; Fernandez, Steven J.

2016-01-05

A method of modeling electric supply and demand with a data processor in combination with a recordable medium, and for estimating spatial distribution of electric power outages and affected populations. A geographic area is divided into cells to form a matrix. Within the matrix, supply cells are identified as containing electric substations and demand cells are identified as including electricity customers. Demand cells of the matrix are associated with the supply cells as a function of the capacity of each of the supply cells and the proximity and/or electricity demand of each of the demand cells. The method includes estimating a power outage by applying disaster event prediction information to the matrix, and estimating power restoration using the supply and demand cell information of the matrix and standardized and historical restoration information.

A variance-decomposition approach to investigating multiscale habitat associations

USGS Publications Warehouse

Lawler, J.J.; Edwards, T.C.

2006-01-01

The recognition of the importance of spatial scale in ecology has led many researchers to take multiscale approaches to studying habitat associations. However, few of the studies that investigate habitat associations at multiple spatial scales have considered the potential effects of cross-scale correlations in measured habitat variables. When cross-scale correlations in such studies are strong, conclusions drawn about the relative strength of habitat associations at different spatial scales may be inaccurate. Here we adapt and demonstrate an analytical technique based on variance decomposition for quantifying the influence of cross-scale correlations on multiscale habitat associations. We used the technique to quantify the variation in nest-site locations of Red-naped Sapsuckers (Sphyrapicus nuchalis) and Northern Flickers (Colaptes auratus) associated with habitat descriptors at three spatial scales. We demonstrate how the method can be used to identify components of variation that are associated only with factors at a single spatial scale as well as shared components of variation that represent cross-scale correlations. Despite the fact that no explanatory variables in our models were highly correlated (r < 0.60), we found that shared components of variation reflecting cross-scale correlations accounted for roughly half of the deviance explained by the models. These results highlight the importance of both conducting habitat analyses at multiple spatial scales and of quantifying the effects of cross-scale correlations in such analyses. Given the limits of conventional analytical techniques, we recommend alternative methods, such as the variance-decomposition technique demonstrated here, for analyzing habitat associations at multiple spatial scales. ?? The Cooper Ornithological Society 2006.

Objective Assessment and Design Improvement of a Staring, Sparse Transducer Array by the Spatial Crosstalk Matrix for 3D Photoacoustic Tomography

PubMed Central

Kosik, Ivan; Raess, Avery

2015-01-01

Accurate reconstruction of 3D photoacoustic (PA) images requires detection of photoacoustic signals from many angles. Several groups have adopted staring ultrasound arrays, but assessment of array performance has been limited. We previously reported on a method to calibrate a 3D PA tomography (PAT) staring array system and analyze system performance using singular value decomposition (SVD). The developed SVD metric, however, was impractical for large system matrices, which are typical of 3D PAT problems. The present study consisted of two main objectives. The first objective aimed to introduce the crosstalk matrix concept to the field of PAT for system design. Figures-of-merit utilized in this study were root mean square error, peak signal-to-noise ratio, mean absolute error, and a three dimensional structural similarity index, which were derived between the normalized spatial crosstalk matrix and the identity matrix. The applicability of this approach for 3D PAT was validated by observing the response of the figures-of-merit in relation to well-understood PAT sampling characteristics (i.e. spatial and temporal sampling rate). The second objective aimed to utilize the figures-of-merit to characterize and improve the performance of a near-spherical staring array design. Transducer arrangement, array radius, and array angular coverage were the design parameters examined. We observed that the performance of a 129-element staring transducer array for 3D PAT could be improved by selection of optimal values of the design parameters. The results suggested that this formulation could be used to objectively characterize 3D PAT system performance and would enable the development of efficient strategies for system design optimization. PMID:25875177

The concentration parameter thermal microstresses as the thermophysical characteristics of two-phase materials

NASA Astrophysics Data System (ADS)

Kuanishev, V. T.; Sachkov, I. N.; Sorogin, I. G.; Sorogina, T. I.

2017-11-01

Thermal strength is one of the main thermophysical characteristics of structural materials. For homogeneous systems it is determined by the strength characteristics of the material. While for inhomogeneous systems, in particular, multiphase ones, it is necessary to consider the nature of the microstructure. Heat resistant real materials such as steels are known to be multi-phase systems. One of the mechanisms of their destruction is associated with the presence of propagating heat fluxes that generate thermal stresses. The aim of this paper is to evaluate the patterns of the formation of spatial distributions of thermal stresses in matrix systems of round inclusions characterized by different mutual disposition. The spatial distributions of thermal stresses in a two-phase material characterized by a matrix structure with round inclusions are investigated. For the numerical solution of the problem of stationary thermal conductivity the finite element method with discretization of the medium by triangular elements is used. It was found that at certain points in the medium the values of thermal stresses are ten times higher than the average for the material. It is shown that the spatial distribution and the local magnitude of the temperature gradient depend on the shape of the particles of the phase components and the values of their thermal conductivities. It is considered that the elastic moduli of inclusion and matrix differ little from each other.

Local pressure and matrix component effects on verteporfin distribution in pancreatic tumors (Conference Presentation)

NASA Astrophysics Data System (ADS)

Nieskoski, Michael D.; Marra, Kayla; Gunn, Jason R.; Doyley, Marvin; Samkoe, Kimberly S.; Pereira, Stephen P.; Trembly, B. Stuart; Pogue, Brian W.

2017-02-01

Pancreatic tumors are characterized by large interstitial hypertension from enhanced deposition of extracellular matrix components, resulting in widespread vascular collapse and reduced molecular uptake of systemically delivered therapies. Although the origins of hypoperfusion is debated amongst researchers, spatial distribution of collagen density and hyaluronic acid content have shown to be a key metric in understanding the lack of efficacy for both acute and chronic therapies in these tumors. In this study, the AsPC-1 tumor model was used both subcutaneously and orthotopically to study the measurable factors which are related to this. A conventional piezoelectric pressure catheter was used to measure total tissue pressure (TTP), defined as a combination of solid stress (SS) and interstitial fluid pressure (IFP), TTP = SS + IFP, in multiple locations within the tumor interstitium. Matrix components such as collagen and hyaluronic acid were scored using masson's trichrome stain and hyaluronic acid binding protein (HABP), respectively, and co-registered with values of TTP. The results show that these key measurements are related to the spatial distribution of verteporfin in the same tumors. Photodynamic treatment with verteporfin is known to ablate large regions of tumor tissue and also allow better permeability for chemotherapies. The study of spatial distribution of verteporfin in relation to stromal content and TTP will help us better control these types of combination therapies.

A temporal and spatial analysis of ground-water levels for effective monitoring in Huron County, Michigan

USGS Publications Warehouse

Holtschlag, David J.; Sweat, M.J.

1999-01-01

Quarterly water-level measurements were analyzed to assess the effectiveness of a monitoring network of 26 wells in Huron County, Michigan. Trends were identified as constant levels and autoregressive components were computed at all wells on the basis of data collected from 1993 to 1997, using structural time series analysis. Fixed seasonal components were identified at 22 wells and outliers were identified at 23 wells. The 95- percent confidence intervals were forecast for water-levels during the first and second quarters of 1998. Intervals in the first quarter were consistent with 92.3 percent of the measured values. In the second quarter, measured values were within the forecast intervals only 65.4 percent of the time. Unusually low precipitation during the second quarter is thought to have contributed to the reduced reliability of the second-quarter forecasts. Spatial interrelations among wells were investigated on the basis of the autoregressive components, which were filtered to create a set of innovation sequences that were temporally uncorrelated. The empirical covariance among the innovation sequences indicated both positive and negative spatial interrelations. The negative covariance components are considered to be physically implausible and to have resulted from random sampling error. Graphical modeling, a form of multivariate analysis, was used to model the covariance structure. Results indicate that only 29 of the 325 possible partial correlations among the water-level innovations were statistically significant. The model covariance matrix, corresponding to the model partial correlation structure, contained only positive elements. This model covariance was sequentially partitioned to compute a set of partial covariance matrices that were used to rank the effectiveness of the 26 monitoring wells from greatest to least. Results, for example, indicate that about 50 percent of the uncertainty of the water-level innovations currently monitored by the 26- well network could be described by the 6 most effective wells.

TU-H-206-01: An Automated Approach for Identifying Geometric Distortions in Gamma Cameras

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

Mann, S; Nelson, J; Samei, E

2016-06-15

Purpose: To develop a clinically-deployable, automated process for detecting artifacts in routine nuclear medicine (NM) quality assurance (QA) bar phantom images. Methods: An artifact detection algorithm was created to analyze bar phantom images as part of an ongoing QA program. A low noise, high resolution reference image was acquired from an x-ray of the bar phantom with a Philips Digital Diagnost system utilizing image stitching. NM bar images, acquired for 5 million counts over a 512×512 matrix, were registered to the template image by maximizing mutual information (MI). The MI index was used as an initial test for artifacts; lowmore » values indicate an overall presence of distortions regardless of their spatial location. Images with low MI scores were further analyzed for bar linearity, periodicity, alignment, and compression to locate differences with respect to the template. Findings from each test were spatially correlated and locations failing multiple tests were flagged as potential artifacts requiring additional visual analysis. The algorithm was initially deployed for GE Discovery 670 and Infinia Hawkeye gamma cameras. Results: The algorithm successfully identified clinically relevant artifacts from both systems previously unnoticed by technologists performing the QA. Average MI indices for artifact-free images are 0.55. Images with MI indices < 0.50 have shown 100% sensitivity and specificity for artifact detection when compared with a thorough visual analysis. Correlation of geometric tests confirms the ability to spatially locate the most likely image regions containing an artifact regardless of initial phantom orientation. Conclusion: The algorithm shows the potential to detect gamma camera artifacts that may be missed by routine technologist inspections. Detection and subsequent correction of artifacts ensures maximum image quality and may help to identify failing hardware before it impacts clinical workflow. Going forward, the algorithm is being deployed to monitor data from all gamma cameras within our health system.« less