Sample records for spatial correlation structure
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Nonmonotonic spatial structure of interneuronal correlations in prefrontal microcircuits
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
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Assessing the role of spatial correlations during collective cell spreading
Treloar, Katrina K.; Simpson, Matthew J.; Binder, Benjamin J.; McElwain, D. L. Sean; Baker, Ruth E.
2014-01-01
Spreading cell fronts are essential features of development, repair and disease processes. Many mathematical models used to describe the motion of cell fronts, such as Fisher's equation, invoke a mean–field assumption which implies that there is no spatial structure, such as cell clustering, present. Here, we examine the presence of spatial structure using a combination of in vitro circular barrier assays, discrete random walk simulations and pair correlation functions. In particular, we analyse discrete simulation data using pair correlation functions to show that spatial structure can form in a spreading population of cells either through sufficiently strong cell–to–cell adhesion or sufficiently rapid cell proliferation. We analyse images from a circular barrier assay describing the spreading of a population of MM127 melanoma cells using the same pair correlation functions. Our results indicate that the spreading melanoma cell populations remain very close to spatially uniform, suggesting that the strength of cell–to–cell adhesion and the rate of cell proliferation are both sufficiently small so as not to induce any spatial patterning in the spreading populations. PMID:25026987
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Yenilmez, Firdes; Düzgün, Sebnem; Aksoy, Aysegül
2015-01-01
In this study, kernel density estimation (KDE) was coupled with ordinary two-dimensional kriging (OK) to reduce the number of sampling locations in measurement and kriging of dissolved oxygen (DO) concentrations in Porsuk Dam Reservoir (PDR). Conservation of the spatial correlation structure in the DO distribution was a target. KDE was used as a tool to aid in identification of the sampling locations that would be removed from the sampling network in order to decrease the total number of samples. Accordingly, several networks were generated in which sampling locations were reduced from 65 to 10 in increments of 4 or 5 points at a time based on kernel density maps. DO variograms were constructed, and DO values in PDR were kriged. Performance of the networks in DO estimations were evaluated through various error metrics, standard error maps (SEM), and whether the spatial correlation structure was conserved or not. Results indicated that smaller number of sampling points resulted in loss of information in regard to spatial correlation structure in DO. The minimum representative sampling points for PDR was 35. Efficacy of the sampling location selection method was tested against the networks generated by experts. It was shown that the evaluation approach proposed in this study provided a better sampling network design in which the spatial correlation structure of DO was sustained for kriging.
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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.
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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
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Functional CAR models for large spatially correlated functional datasets.
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.
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Three dimensional simulation of spatial and temporal variability of stratospheric hydrogen chloride
NASA Technical Reports Server (NTRS)
Kaye, Jack A.; Rood, Richard B.; Jackman, Charles H.; Allen, Dale J.; Larson, Edmund M.
1989-01-01
Spatial and temporal variability of atmospheric HCl columns are calculated for January 1979 using a three-dimensional chemistry-transport model designed to provide the best possible representation of stratospheric transport. Large spatial and temporal variability of the HCl columns is shown to be correlated with lower stratospheric potential vorticity and thus to be of dynamical origin. Systematic longitudinal structure is correlated with planetary wave structure. These results can help place spatially and temporally isolated column and profile measurements in a regional and/or global perspective.
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Temporal and spatial correlation patterns of air pollutants in Chinese cities
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
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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.
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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.
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Revisiting crash spatial heterogeneity: A Bayesian spatially varying coefficients approach.
Xu, Pengpeng; Huang, Helai; Dong, Ni; Wong, S C
2017-01-01
This study was performed to investigate the spatially varying relationships between crash frequency and related risk factors. A Bayesian spatially varying coefficients model was elaborately introduced as a methodological alternative to simultaneously account for the unstructured and spatially structured heterogeneity of the regression coefficients in predicting crash frequencies. The proposed method was appealing in that the parameters were modeled via a conditional autoregressive prior distribution, which involved a single set of random effects and a spatial correlation parameter with extreme values corresponding to pure unstructured or pure spatially correlated random effects. A case study using a three-year crash dataset from the Hillsborough County, Florida, was conducted to illustrate the proposed model. Empirical analysis confirmed the presence of both unstructured and spatially correlated variations in the effects of contributory factors on severe crash occurrences. The findings also suggested that ignoring spatially structured heterogeneity may result in biased parameter estimates and incorrect inferences, while assuming the regression coefficients to be spatially clustered only is probably subject to the issue of over-smoothness. Copyright © 2016 Elsevier Ltd. All rights reserved.
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Rich structure in the correlation matrix spectra in non-equilibrium steady states
NASA Astrophysics Data System (ADS)
Biswas, Soham; Leyvraz, Francois; Monroy Castillero, Paulino; Seligman, Thomas H.
2017-01-01
It has been shown that, if a model displays long-range (power-law) spatial correlations, its equal-time correlation matrix will also have a power law tail in the distribution of its high-lying eigenvalues. The purpose of this paper is to show that the converse is generally incorrect: a power-law tail in the high-lying eigenvalues of the correlation matrix may exist even in the absence of equal-time power law correlations in the initial model. We may therefore view the study of the eigenvalue distribution of the correlation matrix as a more powerful tool than the study of spatial Correlations, one which may in fact uncover structure, that would otherwise not be apparent. Specifically, we show that in the Totally Asymmetric Simple Exclusion Process, whereas there are no clearly visible correlations in the steady state, the eigenvalues of its correlation matrix exhibit a rich structure which we describe in detail.
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Rich structure in the correlation matrix spectra in non-equilibrium steady states.
Biswas, Soham; Leyvraz, Francois; Monroy Castillero, Paulino; Seligman, Thomas H
2017-01-17
It has been shown that, if a model displays long-range (power-law) spatial correlations, its equal-time correlation matrix will also have a power law tail in the distribution of its high-lying eigenvalues. The purpose of this paper is to show that the converse is generally incorrect: a power-law tail in the high-lying eigenvalues of the correlation matrix may exist even in the absence of equal-time power law correlations in the initial model. We may therefore view the study of the eigenvalue distribution of the correlation matrix as a more powerful tool than the study of spatial Correlations, one which may in fact uncover structure, that would otherwise not be apparent. Specifically, we show that in the Totally Asymmetric Simple Exclusion Process, whereas there are no clearly visible correlations in the steady state, the eigenvalues of its correlation matrix exhibit a rich structure which we describe in detail.
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Welhan, J.A.; Reed, M.F.
1997-01-01
The regional spatial correlation structure of bulk horizontal hydraulic conductivity (Kb) estimated from published transmissivity data from 79 open boreholes in the fractured basalt aquifer of the eastern Snake River Plain was analyzed with geostatistical methods. The two-dimensional spatial correlation structure of In Kb shows a pronounced 4:1 range anisotropy, with a maximum correlation range in the north-northwest- south-southeast direction of about 6 km. The maximum variogram range of In Kb is similar to the mean length of flow groups exposed at the surface. The In Kb range anisotropy is similar to the mean width/length ratio of late Quaternary and Holocene basalt lava flows and the orientations of the major volcanic structural features on the eastern Snake River Plain. The similarity between In Kb correlation scales and basalt flow dimensions and between basalt flow orientations and correlation range anisotropy suggests that the spatial distribution of zones of high hydraulic conductivity may be controlled by the lateral dimensions, spatial distribution, and interconnection between highly permeable zones which are known to occur between lava flows within flow groups. If hydraulic conductivity and lithology are eventually shown to be cross correlative in this geologic setting, it may be possible to stochastically simulate hydraulic conductivity distributions, which are conditional on a knowledge of volcanic stratigraphy.
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Finer parcellation reveals detailed correlational structure of resting-state fMRI signals.
Dornas, João V; Braun, Jochen
2018-01-15
Even in resting state, the human brain generates functional signals (fMRI) with complex correlational structure. To simplify this structure, it is common to parcellate a standard brain into coarse chunks. Finer parcellations are considered less reproducible and informative, due to anatomical and functional variability of individual brains. Grouping signals with similar local correlation profiles, restricted to each anatomical region (Tzourio-Mazoyer et al., 2002), we divide a standard brain into 758 'functional clusters' averaging 1.7cm 3 gray matter volume ('MD758' parcellation). We compare 758 'spatial clusters' of similar size ('S758'). 'Functional clusters' are spatially contiguous and cluster quality (integration and segregation of temporal variance) is far superior to 'spatial clusters', comparable to multi-modal parcellations of half the resolution (Craddock et al., 2012; Glasser et al., 2016). Moreover, 'functional clusters' capture many long-range functional correlations, with O(10 5 ) reproducibly correlated cluster pairs in different anatomical regions. The pattern of functional correlations closely mirrors long-range anatomical connectivity established by fibre tracking. MD758 is comparable to coarser parcellations (Craddock et al., 2012; Glasser et al., 2016) in terms of cluster quality, correlational structure (54% relative mutual entropy vs 60% and 61%), and sparseness (35% significant pairwise correlations vs 36% and 44%). We describe and evaluate a simple path to finer functional parcellations of the human brain. Detailed correlational structure is surprisingly consistent between individuals, opening new possibilities for comparing functional correlations between cognitive conditions, states of health, or pharmacological interventions. Copyright © 2017 The Author(s). Published by Elsevier B.V. All rights reserved.
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Coherent manipulation of spin correlations in the Hubbard model
NASA Astrophysics Data System (ADS)
Wurz, N.; Chan, C. F.; Gall, M.; Drewes, J. H.; Cocchi, E.; Miller, L. A.; Pertot, D.; Brennecke, F.; Köhl, M.
2018-05-01
We coherently manipulate spin correlations in a two-component atomic Fermi gas loaded into an optical lattice using spatially and time-resolved Ramsey spectroscopy combined with high-resolution in situ imaging. This technique allows us not only to imprint spin patterns but also to probe the static magnetic structure factor at an arbitrary wave vector, in particular, the staggered structure factor. From a measurement along the diagonal of the first Brillouin zone of the optical lattice, we determine the magnetic correlation length and the individual spatial spin correlators. At half filling, the staggered magnetic structure factor serves as a sensitive thermometer, which we employ to study the equilibration in the spin and density sector during a slow quench of the lattice depth.
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ERIC Educational Resources Information Center
Friedlander, Myrna L.; Highlen, Pamela S.
1984-01-01
Examined the interpersonal structures of interviews by Ackerman, Bowen, Jackson, and Whitaker with the same family to identify common features across counselors. Multidimensional scaling provided a spatial representation of the hidden structure in the communication patterns of these interviews. Correlations indicated counselors' interactions were…
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Emergent spatial synaptic structure from diffusive plasticity.
Sweeney, Yann; Clopath, Claudia
2017-04-01
Some neurotransmitters can diffuse freely across cell membranes, influencing neighbouring neurons regardless of their synaptic coupling. This provides a means of neural communication, alternative to synaptic transmission, which can influence the way in which neural networks process information. Here, we ask whether diffusive neurotransmission can also influence the structure of synaptic connectivity in a network undergoing plasticity. We propose a form of Hebbian synaptic plasticity which is mediated by a diffusive neurotransmitter. Whenever a synapse is modified at an individual neuron through our proposed mechanism, similar but smaller modifications occur in synapses connecting to neighbouring neurons. The effects of this diffusive plasticity are explored in networks of rate-based neurons. This leads to the emergence of spatial structure in the synaptic connectivity of the network. We show that this spatial structure can coexist with other forms of structure in the synaptic connectivity, such as with groups of strongly interconnected neurons that form in response to correlated external drive. Finally, we explore diffusive plasticity in a simple feedforward network model of receptive field development. We show that, as widely observed across sensory cortex, the preferred stimulus identity of neurons in our network become spatially correlated due to diffusion. Our proposed mechanism of diffusive plasticity provides an efficient mechanism for generating these spatial correlations in stimulus preference which can flexibly interact with other forms of synaptic organisation. © 2016 Federation of European Neuroscience Societies and John Wiley & Sons Ltd.
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Selecting a Separable Parametric Spatiotemporal Covariance Structure for Longitudinal Imaging Data
George, Brandon; Aban, Inmaculada
2014-01-01
Longitudinal imaging studies allow great insight into how the structure and function of a subject’s internal anatomy changes over time. Unfortunately, the analysis of longitudinal imaging data is complicated by inherent spatial and temporal correlation: the temporal from the repeated measures, and the spatial from the outcomes of interest being observed at multiple points in a patients body. We propose the use of a linear model with a separable parametric spatiotemporal error structure for the analysis of repeated imaging data. The model makes use of spatial (exponential, spherical, and Matérn) and temporal (compound symmetric, autoregressive-1, Toeplitz, and unstructured) parametric correlation functions. A simulation study, inspired by a longitudinal cardiac imaging study on mitral regurgitation patients, compared different information criteria for selecting a particular separable parametric spatiotemporal correlation structure as well as the effects on Type I and II error rates for inference on fixed effects when the specified model is incorrect. Information criteria were found to be highly accurate at choosing between separable parametric spatiotemporal correlation structures. Misspecification of the covariance structure was found to have the ability to inflate the Type I error or have an overly conservative test size, which corresponded to decreased power. An example with clinical data is given illustrating how the covariance structure procedure can be done in practice, as well as how covariance structure choice can change inferences about fixed effects. PMID:25293361
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Huang, Yi; Yang, Lei
2013-01-01
This study attempts to discuss the relationship between land use spatial distribution structure and energy-related carbon emission intensity in Guangdong during 1996–2008. We quantized the spatial distribution structure of five land use types including agricultural land, industrial land, residential and commercial land, traffic land, and other land through applying spatial Lorenz curve and Gini coefficient. Then the corresponding energy-related carbon emissions in each type of land were calculated in the study period. Through building the reasonable regression models, we found that the concentration degree of industrial land is negatively correlated with carbon emission intensity in the long term, whereas the concentration degree is positively correlated with carbon emission intensity in agricultural land, residential and commercial land, traffic land, and other land. The results also indicate that land use spatial distribution structure affects carbon emission intensity more intensively than energy efficiency and production efficiency do. These conclusions provide valuable reference to develop comprehensive policies for energy conservation and carbon emission reduction in a new perspective. PMID:23476128
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Huang, Yi; Xia, Bin; Yang, Lei
2013-01-01
This study attempts to discuss the relationship between land use spatial distribution structure and energy-related carbon emission intensity in Guangdong during 1996-2008. We quantized the spatial distribution structure of five land use types including agricultural land, industrial land, residential and commercial land, traffic land, and other land through applying spatial Lorenz curve and Gini coefficient. Then the corresponding energy-related carbon emissions in each type of land were calculated in the study period. Through building the reasonable regression models, we found that the concentration degree of industrial land is negatively correlated with carbon emission intensity in the long term, whereas the concentration degree is positively correlated with carbon emission intensity in agricultural land, residential and commercial land, traffic land, and other land. The results also indicate that land use spatial distribution structure affects carbon emission intensity more intensively than energy efficiency and production efficiency do. These conclusions provide valuable reference to develop comprehensive policies for energy conservation and carbon emission reduction in a new perspective.
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Influence of thermal light correlations on photosynthetic structures
NASA Astrophysics Data System (ADS)
de Mendoza, Adriana; Manrique, Pedro; Caycedo-Soler, Felipe; Johnson, Neil F.; Rodríguez, Ferney J.; Quiroga, Luis
2014-03-01
The thermal light from the sun is characterized by both classical and quantum mechanical correlations. These correlations have left a fingerprint on the natural harvesting structures developed through five billion years of evolutionary pressure, specially in photosynthetic organisms. In this work, based upon previous extensive studies of spatio-temporal correlations of light fields, we hypothesize that structures involving photosensitive pigments like those present in purple bacteria vesicles emerge as an evolutionary response to the different properties of incident light. By using burstiness and memory as measures that quantify higher moments of the photon arrival statistics, we generate photon-time traces. They are used to simulate absorption on detectors spatially extended over regions comparable to these light fields coherence length. Finally, we provide some insights into the connection between these photo-statistical features with the photosynthetic membrane architecture and the lights' spatial correlation. Facultad de Ciencias Uniandes.
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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.
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NASA Astrophysics Data System (ADS)
Yamaguchi, Tadashi; Hachiya, Hiroyuki; Kamiyama, Naohisa; Moriyasu, Fuminori
2002-05-01
To realize a quantitative diagnosis of liver cirrhosis, we have been analyzing the characteristics of echo amplitude in B-mode images. Realizing the distinction between liver diseases such as liver cirrhosis and chronic hepatitis is required in the field of medical ultrasonics. In this study, we examine the spatial correlation, with the coefficient of correlation between the frames and the amplitude characteristics of each frame, using the volumetric data of RF echo signals from normal and diseased liver. It is found that there is a relationship between the tissue structure of liver and the spatial correlation of echo information.
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Can Retinal Ganglion Cell Dipoles Seed Iso-Orientation Domains in the Visual Cortex?
Schottdorf, Manuel; Eglen, Stephen J.; Wolf, Fred; Keil, Wolfgang
2014-01-01
It has been argued that the emergence of roughly periodic orientation preference maps (OPMs) in the primary visual cortex (V1) of carnivores and primates can be explained by a so-called statistical connectivity model. This model assumes that input to V1 neurons is dominated by feed-forward projections originating from a small set of retinal ganglion cells (RGCs). The typical spacing between adjacent cortical orientation columns preferring the same orientation then arises via Moiré-Interference between hexagonal ON/OFF RGC mosaics. While this Moiré-Interference critically depends on long-range hexagonal order within the RGC mosaics, a recent statistical analysis of RGC receptive field positions found no evidence for such long-range positional order. Hexagonal order may be only one of several ways to obtain spatially repetitive OPMs in the statistical connectivity model. Here, we investigate a more general requirement on the spatial structure of RGC mosaics that can seed the emergence of spatially repetitive cortical OPMs, namely that angular correlations between so-called RGC dipoles exhibit a spatial structure similar to that of OPM autocorrelation functions. Both in cat beta cell mosaics as well as primate parasol receptive field mosaics we find that RGC dipole angles are spatially uncorrelated. To help assess the level of these correlations, we introduce a novel point process that generates mosaics with realistic nearest neighbor statistics and a tunable degree of spatial correlations of dipole angles. Using this process, we show that given the size of available data sets, the presence of even weak angular correlations in the data is very unlikely. We conclude that the layout of ON/OFF ganglion cell mosaics lacks the spatial structure necessary to seed iso-orientation domains in the primary visual cortex. PMID:24475081
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Can retinal ganglion cell dipoles seed iso-orientation domains in the visual cortex?
Schottdorf, Manuel; Eglen, Stephen J; Wolf, Fred; Keil, Wolfgang
2014-01-01
It has been argued that the emergence of roughly periodic orientation preference maps (OPMs) in the primary visual cortex (V1) of carnivores and primates can be explained by a so-called statistical connectivity model. This model assumes that input to V1 neurons is dominated by feed-forward projections originating from a small set of retinal ganglion cells (RGCs). The typical spacing between adjacent cortical orientation columns preferring the same orientation then arises via Moiré-Interference between hexagonal ON/OFF RGC mosaics. While this Moiré-Interference critically depends on long-range hexagonal order within the RGC mosaics, a recent statistical analysis of RGC receptive field positions found no evidence for such long-range positional order. Hexagonal order may be only one of several ways to obtain spatially repetitive OPMs in the statistical connectivity model. Here, we investigate a more general requirement on the spatial structure of RGC mosaics that can seed the emergence of spatially repetitive cortical OPMs, namely that angular correlations between so-called RGC dipoles exhibit a spatial structure similar to that of OPM autocorrelation functions. Both in cat beta cell mosaics as well as primate parasol receptive field mosaics we find that RGC dipole angles are spatially uncorrelated. To help assess the level of these correlations, we introduce a novel point process that generates mosaics with realistic nearest neighbor statistics and a tunable degree of spatial correlations of dipole angles. Using this process, we show that given the size of available data sets, the presence of even weak angular correlations in the data is very unlikely. We conclude that the layout of ON/OFF ganglion cell mosaics lacks the spatial structure necessary to seed iso-orientation domains in the primary visual cortex.
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Lee, D K; Song, Y K; Park, B W; Cho, H P; Yeom, J S; Cho, G; Cho, H
2018-04-15
To evaluate the robustness of MR transverse relaxation times of trabecular bone from spin-echo and gradient-echo acquisitions at multiple spatial resolutions of 7 T. The effects of MRI resolutions to T 2 and T2* of trabecular bone were numerically evaluated by Monte Carlo simulations. T 2 , T2*, and trabecular structural indices from multislice multi-echo and UTE acquisitions were measured in defatted human distal femoral condyles on a 7 T scanner. Reference structural indices were extracted from high-resolution microcomputed tomography images. For bovine knee trabecular samples with intact bone marrow, T 2 and T2* were measured by degrading spatial resolutions on a 7 T system. In the defatted trabecular experiment, both T 2 and T2* values showed strong ( |r| > 0.80) correlations with trabecular spacing and number, at a high spatial resolution of 125 µm 3 . The correlations for MR image-segmentation-derived structural indices were significantly degraded ( |r| < 0.50) at spatial resolutions of 250 and 500 µm 3 . The correlations for T2* rapidly dropped ( |r| < 0.50) at a spatial resolution of 500 µm 3 , whereas those for T 2 remained consistently high ( |r| > 0.85). In the bovine trabecular experiments with intact marrow, low-resolution (approximately 1 mm 3 , 2 minutes) T 2 values did not shorten ( |r| > 0.95 with respect to approximately 0.4 mm 3 , 11 minutes) and maintained consistent correlations ( |r| > 0.70) with respect to trabecular spacing (turbo spin echo, 22.5 minutes). T 2 measurements of trabeculae at 7 T are robust with degrading spatial resolution and may be preferable in assessing trabecular spacing index with reduced scan time, when high-resolution 3D micro-MRI is difficult to obtain. © 2018 International Society for Magnetic Resonance in Medicine.
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Selecting a separable parametric spatiotemporal covariance structure for longitudinal imaging data.
George, Brandon; Aban, Inmaculada
2015-01-15
Longitudinal imaging studies allow great insight into how the structure and function of a subject's internal anatomy changes over time. Unfortunately, the analysis of longitudinal imaging data is complicated by inherent spatial and temporal correlation: the temporal from the repeated measures and the spatial from the outcomes of interest being observed at multiple points in a patient's body. We propose the use of a linear model with a separable parametric spatiotemporal error structure for the analysis of repeated imaging data. The model makes use of spatial (exponential, spherical, and Matérn) and temporal (compound symmetric, autoregressive-1, Toeplitz, and unstructured) parametric correlation functions. A simulation study, inspired by a longitudinal cardiac imaging study on mitral regurgitation patients, compared different information criteria for selecting a particular separable parametric spatiotemporal correlation structure as well as the effects on types I and II error rates for inference on fixed effects when the specified model is incorrect. Information criteria were found to be highly accurate at choosing between separable parametric spatiotemporal correlation structures. Misspecification of the covariance structure was found to have the ability to inflate the type I error or have an overly conservative test size, which corresponded to decreased power. An example with clinical data is given illustrating how the covariance structure procedure can be performed in practice, as well as how covariance structure choice can change inferences about fixed effects. Copyright © 2014 John Wiley & Sons, Ltd.
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NASA Astrophysics Data System (ADS)
Martina, M. L. V.; Vitolo, R.; Todini, E.; Stephenson, D. B.; Cook, I. M.
2009-04-01
The possibility that multiple catastrophic events occur within a given timespan and affect the same portfolio of insured properties may induce enhanced risk. For this reason, in the insurance industry it is of interest to characterise not only the point probability of catastrophic events, but also their spatial structure. As far as floods are concerned it is important to determine the probability of having multiple simultaneous events in different parts of the same basin: in this case, indeed, the loss in a portfolio can be significantly different. Understanding the spatial structure of the precipitation field is a necessary step for the proper modelling of the spatial dependence and correlation of river discharge. Several stochastic models are available in the scientific literature for the multi-site generation of precipitation. Although most models achieve good performance in modelling mean values, temporal variability and inter-site dependence of extremes are still delicate issues. In this work we aim at identifying the main spatial characteristics of the precipitation structure and then at analysing them in a real case. We consider data from a large network of raingauges in the Danube catchment. This catchment is a good example of a large-scale catchment where the spatial correlation of flood events can radically change the effect in term of flood damage.
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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.
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Courtin, C; Hervé, P-Y; Petit, L; Zago, L; Vigneau, M; Beaucousin, V; Jobard, G; Mazoyer, B; Mellet, E; Tzourio-Mazoyer, N
2010-09-01
"Highly iconic" structures in Sign Language enable a narrator to act, switch characters, describe objects, or report actions in four-dimensions. This group of linguistic structures has no real spoken-language equivalent. Topographical descriptions are also achieved in a sign-language specific manner via the use of signing-space and spatial-classifier signs. We used functional magnetic resonance imaging (fMRI) to compare the neural correlates of topographic discourse and highly iconic structures in French Sign Language (LSF) in six hearing native signers, children of deaf adults (CODAs), and six LSF-naïve monolinguals. LSF materials consisted of videos of a lecture excerpt signed without spatially organized discourse or highly iconic structures (Lect LSF), a tale signed using highly iconic structures (Tale LSF), and a topographical description using a diagrammatic format and spatial-classifier signs (Topo LSF). We also presented texts in spoken French (Lect French, Tale French, Topo French) to all participants. With both languages, the Topo texts activated several different regions that are involved in mental navigation and spatial working memory. No specific correlate of LSF spatial discourse was evidenced. The same regions were more activated during Tale LSF than Lect LSF in CODAs, but not in monolinguals, in line with the presence of signing-space structure in both conditions. Motion processing areas and parts of the fusiform gyrus and precuneus were more active during Tale LSF in CODAs; no such effect was observed with French or in LSF-naïve monolinguals. These effects may be associated with perspective-taking and acting during personal transfers. 2010 Elsevier Inc. All rights reserved.
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Spatial correlation of shear-wave velocity within San Francisco Bay Sediments
Thompson, E.M.; Baise, L.G.; Kayen, R.E.
2006-01-01
Sediment properties are spatially variable at all scales, and this variability at smaller scales influences high frequency ground motions. We show that surface shear-wave velocity is highly correlated within San Francisco Bay Area sediments using shear-wave velocity measurements from 210 seismic cone penetration tests. We use this correlation to estimate the surface sediment velocity structure using geostatistics. We find that the variance of the estimated shear-wave velocity is reduced using ordinary kriging, and that including this velocity structure in 2D ground motion simulations of a moderate sized earthquake improves the accuracy of the synthetics. Copyright ASCE 2006.
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Using temporal detrending to observe the spatial correlation of traffic.
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.
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Using temporal detrending to observe the spatial correlation of traffic
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
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Species extinction thresholds in the face of spatially correlated periodic disturbance.
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.
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Detto, Matteo; Muller-Landau, Helene C; Mascaro, Joseph; Asner, Gregory P
2013-01-01
An understanding of the spatial variability in tropical forest structure and biomass, and the mechanisms that underpin this variability, is critical for designing, interpreting, and upscaling field studies for regional carbon inventories. We investigated the spatial structure of tropical forest vegetation and its relationship to the hydrological network and associated topographic structure across spatial scales of 10-1000 m using high-resolution maps of LiDAR-derived mean canopy profile height (MCH) and elevation for 4930 ha of tropical forest in central Panama. MCH was strongly associated with the hydrological network: canopy height was highest in areas of positive convexity (valleys, depressions) close to channels draining 1 ha or more. Average MCH declined strongly with decreasing convexity (transition to ridges, hilltops) and increasing distance from the nearest channel. Spectral analysis, performed with wavelet decomposition, showed that the variance in MCH had fractal similarity at scales of ∼30-600 m, and was strongly associated with variation in elevation, with peak correlations at scales of ∼250 m. Whereas previous studies of topographic correlates of tropical forest structure conducted analyses at just one or a few spatial grains, our study found that correlations were strongly scale-dependent. Multi-scale analyses of correlations of MCH with slope, aspect, curvature, and Laplacian convexity found that MCH was most strongly related to convexity measured at scales of 20-300 m, a topographic variable that is a good proxy for position with respect to the hydrological network. Overall, our results support the idea that, even in these mesic forests, hydrological networks and associated topographical variation serve as templates upon which vegetation is organized over specific ranges of scales. These findings constitute an important step towards a mechanistic understanding of these patterns, and can guide upscaling and downscaling.
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Anthropogenic contamination is typically distributed heterogeneously through space. This spatial structure can have different effects on the cumulative doses of individuals exposed to contamination within the environment. These effects are accentuated when individuals pursue di...
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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).
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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.
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Exploring the spatial variability of soil properties in an Alfisol Catena
DOE Office of Scientific and Technical Information (OSTI.GOV)
Rosemary, F.; Vitharana, U. W. A.; Indraratne, S. P.
Detailed digital soil maps showing the spatial heterogeneity of soil properties consistent with the landscape are required for site-specific management of plant nutrients, land use planning and process-based environmental modeling. We characterized the short-scale spatial heterogeneity of soil properties in an Alfisol catena in a tropical landscape of Sri Lanka. The impact of different land-uses (paddy, vegetable and un-cultivated) was examined to assess the impact of anthropogenic activities on the variability of soil properties at the catenary level. Conditioned Latin hypercube sampling was used to collect 58 geo-referenced topsoil samples (0–30 cm) from the study area. Soil samples were analyzedmore » for pH, electrical conductivity (EC), organic carbon (OC), cation exchange capacity (CEC) and texture. The spatial correlation between soil properties was analyzed by computing crossvariograms and subsequent fitting of theoretical model. Spatial distribution maps were developed using ordinary kriging. The range of soil properties, pH: 4.3–7.9; EC: 0.01–0.18 dS m –1 ; OC: 0.1–1.37%; CEC: 0.44– 11.51 cmol (+) kg –1 ; clay: 1.5–25% and sand: 59.1–84.4% and their coefficient of variations indicated a large variability in the study area. Electrical conductivity and pH showed a strong spatial correlation which was reflected by the cross-variogram close to the hull of the perfect correlation. Moreover, cross-variograms calculated for EC and Clay, CEC and OC, CEC and clay and CEC and pH indicated weak positive spatial correlation between these properties. Relative nugget effect (RNE) calculated from variograms showed strongly structured spatial variability for pH, EC and sand content (RNE < 25%) while CEC, organic carbon and clay content showed moderately structured spatial variability (25% < RNE < 75%). Spatial dependencies for examined soil properties ranged from 48 to 984 m. The mixed effects model fitting followed by Tukey's post-hoc test showed significant effect of land use on the spatial variability of EC. Our study revealed a structured variability of topsoil properties in the selected tropical Alfisol catena. Except for EC, observed variability was not modified by the land uses. Investigated soil properties showed distinct spatial structures at different scales and magnitudes of strength. Our results will be useful for digital soil mapping, site specific management of soil properties, developing appropriate land use plans and quantifying anthropogenic impacts on the soil system.« less
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Colom, Roberto; Stein, Jason L.; Rajagopalan, Priya; Martínez, Kenia; Hermel, David; Wang, Yalin; Álvarez-Linera, Juan; Burgaleta, Miguel; Quiroga, MªÁngeles; Shih, Pei Chun; Thompson, Paul M.
2014-01-01
Here we apply a method for automated segmentation of the hippocampus in 3D high-resolution structural brain MRI scans. One hundred and four healthy young adults completed twenty one tasks measuring abstract, verbal, and spatial intelligence, along with working memory, executive control, attention, and processing speed. After permutation tests corrected for multiple comparisons across vertices (p < .05) significant relationships were found for spatial intelligence, spatial working memory, and spatial executive control. Interactions with sex revealed significant relationships with the general factor of intelligence (g), along with abstract and spatial intelligence. These correlations were mainly positive for males but negative for females, which might support the efficiency hypothesis in women. Verbal intelligence, attention, and processing speed were not related to hippocampal structural differences. PMID:25632167
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Bastardie, Francois
2014-01-01
Trawl survey data with high spatial and seasonal coverage were analysed using a variant of the Log Gaussian Cox Process (LGCP) statistical model to estimate unbiased relative fish densities. The model estimates correlations between observations according to time, space, and fish size and includes zero observations and over-dispersion. The model utilises the fact the correlation between numbers of fish caught increases when the distance in space and time between the fish decreases, and the correlation between size groups in a haul increases when the difference in size decreases. Here the model is extended in two ways. Instead of assuming a natural scale size correlation, the model is further developed to allow for a transformed length scale. Furthermore, in the present application, the spatial- and size-dependent correlation between species was included. For cod (Gadus morhua) and whiting (Merlangius merlangus), a common structured size correlation was fitted, and a separable structure between the time and space-size correlation was found for each species, whereas more complex structures were required to describe the correlation between species (and space-size). The within-species time correlation is strong, whereas the correlations between the species are weaker over time but strong within the year. PMID:24911631
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de Muinck, Eric J; Lundin, Knut E A; Trosvik, Pål
2017-01-01
The gastrointestinal (GI) microbiome is a densely populated ecosystem where dynamics are determined by interactions between microbial community members, as well as host factors. The spatial organization of this system is thought to be important in human health, yet this aspect of our resident microbiome is still poorly understood. In this study, we report significant spatial structure of the GI microbiota, and we identify general categories of spatial patterning in the distribution of microbial taxa along a healthy human GI tract. We further estimate the biotic interaction structure in the GI microbiota, both through time series and cooccurrence modeling of microbial community data derived from a large number of sequentially collected fecal samples. Comparison of these two approaches showed that species pairs involved in significant negative interactions had strong positive contemporaneous correlations and vice versa, while for species pairs without significant interactions, contemporaneous correlations were distributed around zero. We observed similar patterns when comparing these models to the spatial correlations between taxa identified in the adherent microbiota. This suggests that colocalization of microbial taxon pairs, and thus the spatial organization of the GI microbiota, is driven, at least in part, by direct or indirect biotic interactions. Thus, our study can provide a basis for an ecological interpretation of the biogeography of the human gut. IMPORTANCE The human gut microbiome is the subject of intense study due to its importance in health and disease. The majority of these studies have been based on the analysis of feces. However, little is known about how the microbial composition in fecal samples relates to the spatial distribution of microbial taxa along the gastrointestinal tract. By characterizing the microbial content both in intestinal tissue samples and in fecal samples obtained daily, we provide a conceptual framework for how the spatial structure relates to biotic interactions on the community level. We further describe general categories of spatial distribution patterns and identify taxa conforming to these categories. To our knowledge, this is the first study combining spatial and temporal analyses of the human gut microbiome. This type of analysis can be used for identifying candidate probiotics and designing strategies for clinical intervention.
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A class of covariate-dependent spatiotemporal covariance functions
Reich, Brian J; Eidsvik, Jo; Guindani, Michele; Nail, Amy J; Schmidt, Alexandra M.
2014-01-01
In geostatistics, it is common to model spatially distributed phenomena through an underlying stationary and isotropic spatial process. However, these assumptions are often untenable in practice because of the influence of local effects in the correlation structure. Therefore, it has been of prolonged interest in the literature to provide flexible and effective ways to model non-stationarity in the spatial effects. Arguably, due to the local nature of the problem, we might envision that the correlation structure would be highly dependent on local characteristics of the domain of study, namely the latitude, longitude and altitude of the observation sites, as well as other locally defined covariate information. In this work, we provide a flexible and computationally feasible way for allowing the correlation structure of the underlying processes to depend on local covariate information. We discuss the properties of the induced covariance functions and discuss methods to assess its dependence on local covariate information by means of a simulation study and the analysis of data observed at ozone-monitoring stations in the Southeast United States. PMID:24772199
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Bhaskar, Anand; Javanmard, Adel; Courtade, Thomas A; Tse, David
2017-03-15
Genetic variation in human populations is influenced by geographic ancestry due to spatial locality in historical mating and migration patterns. Spatial population structure in genetic datasets has been traditionally analyzed using either model-free algorithms, such as principal components analysis (PCA) and multidimensional scaling, or using explicit spatial probabilistic models of allele frequency evolution. We develop a general probabilistic model and an associated inference algorithm that unify the model-based and data-driven approaches to visualizing and inferring population structure. Our spatial inference algorithm can also be effectively applied to the problem of population stratification in genome-wide association studies (GWAS), where hidden population structure can create fictitious associations when population ancestry is correlated with both the genotype and the trait. Our algorithm Geographic Ancestry Positioning (GAP) relates local genetic distances between samples to their spatial distances, and can be used for visually discerning population structure as well as accurately inferring the spatial origin of individuals on a two-dimensional continuum. On both simulated and several real datasets from diverse human populations, GAP exhibits substantially lower error in reconstructing spatial ancestry coordinates compared to PCA. We also develop an association test that uses the ancestry coordinates inferred by GAP to accurately account for ancestry-induced correlations in GWAS. Based on simulations and analysis of a dataset of 10 metabolic traits measured in a Northern Finland cohort, which is known to exhibit significant population structure, we find that our method has superior power to current approaches. Our software is available at https://github.com/anand-bhaskar/gap . abhaskar@stanford.edu or ajavanma@usc.edu. Supplementary data are available at Bioinformatics online. © The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com
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Universal Spatial Correlation Functions for Describing and Reconstructing Soil Microstructure
Skvortsova, Elena B.; Mallants, Dirk
2015-01-01
Structural features of porous materials such as soil define the majority of its physical properties, including water infiltration and redistribution, multi-phase flow (e.g. simultaneous water/air flow, or gas exchange between biologically active soil root zone and atmosphere) and solute transport. To characterize soil microstructure, conventional soil science uses such metrics as pore size and pore-size distributions and thin section-derived morphological indicators. However, these descriptors provide only limited amount of information about the complex arrangement of soil structure and have limited capability to reconstruct structural features or predict physical properties. We introduce three different spatial correlation functions as a comprehensive tool to characterize soil microstructure: 1) two-point probability functions, 2) linear functions, and 3) two-point cluster functions. This novel approach was tested on thin-sections (2.21×2.21 cm2) representing eight soils with different pore space configurations. The two-point probability and linear correlation functions were subsequently used as a part of simulated annealing optimization procedures to reconstruct soil structure. Comparison of original and reconstructed images was based on morphological characteristics, cluster correlation functions, total number of pores and pore-size distribution. Results showed excellent agreement for soils with isolated pores, but relatively poor correspondence for soils exhibiting dual-porosity features (i.e. superposition of pores and micro-cracks). Insufficient information content in the correlation function sets used for reconstruction may have contributed to the observed discrepancies. Improved reconstructions may be obtained by adding cluster and other correlation functions into reconstruction sets. Correlation functions and the associated stochastic reconstruction algorithms introduced here are universally applicable in soil science, such as for soil classification, pore-scale modelling of soil properties, soil degradation monitoring, and description of spatial dynamics of soil microbial activity. PMID:26010779
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Universal spatial correlation functions for describing and reconstructing soil microstructure.
Karsanina, Marina V; Gerke, Kirill M; Skvortsova, Elena B; Mallants, Dirk
2015-01-01
Structural features of porous materials such as soil define the majority of its physical properties, including water infiltration and redistribution, multi-phase flow (e.g. simultaneous water/air flow, or gas exchange between biologically active soil root zone and atmosphere) and solute transport. To characterize soil microstructure, conventional soil science uses such metrics as pore size and pore-size distributions and thin section-derived morphological indicators. However, these descriptors provide only limited amount of information about the complex arrangement of soil structure and have limited capability to reconstruct structural features or predict physical properties. We introduce three different spatial correlation functions as a comprehensive tool to characterize soil microstructure: 1) two-point probability functions, 2) linear functions, and 3) two-point cluster functions. This novel approach was tested on thin-sections (2.21×2.21 cm2) representing eight soils with different pore space configurations. The two-point probability and linear correlation functions were subsequently used as a part of simulated annealing optimization procedures to reconstruct soil structure. Comparison of original and reconstructed images was based on morphological characteristics, cluster correlation functions, total number of pores and pore-size distribution. Results showed excellent agreement for soils with isolated pores, but relatively poor correspondence for soils exhibiting dual-porosity features (i.e. superposition of pores and micro-cracks). Insufficient information content in the correlation function sets used for reconstruction may have contributed to the observed discrepancies. Improved reconstructions may be obtained by adding cluster and other correlation functions into reconstruction sets. Correlation functions and the associated stochastic reconstruction algorithms introduced here are universally applicable in soil science, such as for soil classification, pore-scale modelling of soil properties, soil degradation monitoring, and description of spatial dynamics of soil microbial activity.
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Stochastic Geometric Models with Non-stationary Spatial Correlations in Lagrangian Fluid Flows
NASA Astrophysics Data System (ADS)
Gay-Balmaz, François; Holm, Darryl D.
2018-01-01
Inspired by spatiotemporal observations from satellites of the trajectories of objects drifting near the surface of the ocean in the National Oceanic and Atmospheric Administration's "Global Drifter Program", this paper develops data-driven stochastic models of geophysical fluid dynamics (GFD) with non-stationary spatial correlations representing the dynamical behaviour of oceanic currents. Three models are considered. Model 1 from Holm (Proc R Soc A 471:20140963, 2015) is reviewed, in which the spatial correlations are time independent. Two new models, called Model 2 and Model 3, introduce two different symmetry breaking mechanisms by which the spatial correlations may be advected by the flow. These models are derived using reduction by symmetry of stochastic variational principles, leading to stochastic Hamiltonian systems, whose momentum maps, conservation laws and Lie-Poisson bracket structures are used in developing the new stochastic Hamiltonian models of GFD.
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Stochastic Geometric Models with Non-stationary Spatial Correlations in Lagrangian Fluid Flows
NASA Astrophysics Data System (ADS)
Gay-Balmaz, François; Holm, Darryl D.
2018-06-01
Inspired by spatiotemporal observations from satellites of the trajectories of objects drifting near the surface of the ocean in the National Oceanic and Atmospheric Administration's "Global Drifter Program", this paper develops data-driven stochastic models of geophysical fluid dynamics (GFD) with non-stationary spatial correlations representing the dynamical behaviour of oceanic currents. Three models are considered. Model 1 from Holm (Proc R Soc A 471:20140963, 2015) is reviewed, in which the spatial correlations are time independent. Two new models, called Model 2 and Model 3, introduce two different symmetry breaking mechanisms by which the spatial correlations may be advected by the flow. These models are derived using reduction by symmetry of stochastic variational principles, leading to stochastic Hamiltonian systems, whose momentum maps, conservation laws and Lie-Poisson bracket structures are used in developing the new stochastic Hamiltonian models of GFD.
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Large-scale cortical correlation structure of spontaneous oscillatory activity
Hipp, Joerg F.; Hawellek, David J.; Corbetta, Maurizio; Siegel, Markus; Engel, Andreas K.
2013-01-01
Little is known about the brain-wide correlation of electrophysiological signals. Here we show that spontaneous oscillatory neuronal activity exhibits frequency-specific spatial correlation structure in the human brain. We developed an analysis approach that discounts spurious correlation of signal power caused by the limited spatial resolution of electrophysiological measures. We applied this approach to source estimates of spontaneous neuronal activity reconstructed from magnetoencephalography (MEG). Overall, correlation of power across cortical regions was strongest in the alpha to beta frequency range (8–32 Hz) and correlation patterns depended on the underlying oscillation frequency. Global hubs resided in the medial temporal lobe in the theta frequency range (4–6 Hz), in lateral parietal areas in the alpha to beta frequency range (8–23 Hz), and in sensorimotor areas for higher frequencies (32–45 Hz). Our data suggest that interactions in various large-scale cortical networks may be reflected in frequency specific power-envelope correlations. PMID:22561454
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NASA Astrophysics Data System (ADS)
Bugaychuk, Svitlana A.; Gnatovskyy, Vladimir O.; Sidorenko, Andrey V.; Pryadko, Igor I.; Negriyko, Anatoliy M.
2015-11-01
New approach for the correlation technique, which is based on multiple periodic structures to create a controllable angular spectrum, is proposed and investigated both theoretically and experimentally. The transformation of an initial laser beam occurs due to the actions of consecutive phase periodic structures, which may differ by their parameters. Then, after the Fourier transformation of a complex diffraction field, the output diffraction orders will be changed both by their intensities and by their spatial position. The controllable change of output angular spectrum is carried out by a simple control of the parameters of the periodic structures. We investigate several simple examples of such management.
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The Latent Structure of Spatial Skills and Mathematics: A Replication of the Two-Factor Model
ERIC Educational Resources Information Center
Mix, Kelly S.; Levine, Susan C.; Cheng, Yi-Lang; Young, Christopher J.; Hambrick, David Z.; Konstantopoulos, Spyros
2017-01-01
In a previous study, Mix et al. (2016) reported that spatial skill and mathematics were composed of 2 highly correlated, domain-specific factors, with a few cross-domain loadings. The overall structure was consistent across grade (kindergarten, 3rd grade, 6th grade), but the cross-domain loadings varied with age. The present study sought to…
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NASA Astrophysics Data System (ADS)
Ushakov, V. N.
1995-10-01
A video-frequency acousto-optical correlator with spatial integration, which widens the functional capabilities of correlation-type acousto-optical processors, is described. The correlator is based on a two-dimensional reference transparency and it can filter arbitrary video signals of spectral width limited by the pass band of an acousto-optical modulator. The calculated pulse characteristic is governed by the structure of the reference transparency. A procedure for the synthesis of this transparency is considered and experimental results are reported.
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Anti-correlation and subsector structure in financial systems
NASA Astrophysics Data System (ADS)
Jiang, X. F.; Zheng, B.
2012-02-01
With the random matrix theory, we study the spatial structure of the Chinese stock market, the American stock market and global market indices. After taking into account the signs of the components in the eigenvectors of the cross-correlation matrix, we detect the subsector structure of the financial systems. The positive and negative subsectors are anti-correlated with respect to each other in the corresponding eigenmode. The subsector structure is strong in the Chinese stock market, while somewhat weaker in the American stock market and global market indices. Characteristics of the subsector structures in different markets are revealed.
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Spatial correlation of auroral zone geomagnetic variations
NASA Astrophysics Data System (ADS)
Jackel, B. J.; Davalos, A.
2016-12-01
Magnetic field perturbations in the auroral zone are produced by a combination of distant ionospheric and local ground induced currents. Spatial and temporal structure of these currents is scientifically interesting and can also have a significant influence on critical infrastructure.Ground-based magnetometer networks are an essential tool for studying these phenomena, with the existing complement of instruments in Canada providing extended local time coverage. In this study we examine the spatial correlation between magnetic field observations over a range of scale lengths. Principal component and canonical correlation analysis are used to quantify relationships between multiple sites. Results could be used to optimize network configurations, validate computational models, and improve methods for empirical interpolation.
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NASA Astrophysics Data System (ADS)
Marra, Francesco; Morin, Efrat
2018-02-01
Small scale rainfall variability is a key factor driving runoff response in fast responding systems, such as mountainous, urban and arid catchments. In this paper, the spatial-temporal autocorrelation structure of convective rainfall is derived with extremely high resolutions (60 m, 1 min) using estimates from an X-Band weather radar recently installed in a semiarid-arid area. The 2-dimensional spatial autocorrelation of convective rainfall fields and the temporal autocorrelation of point-wise and distributed rainfall fields are examined. The autocorrelation structures are characterized by spatial anisotropy, correlation distances 1.5-2.8 km and rarely exceeding 5 km, and time-correlation distances 1.8-6.4 min and rarely exceeding 10 min. The observed spatial variability is expected to negatively affect estimates from rain gauges and microwave links rather than satellite and C-/S-Band radars; conversely, the temporal variability is expected to negatively affect remote sensing estimates rather than rain gauges. The presented results provide quantitative information for stochastic weather generators, cloud-resolving models, dryland hydrologic and agricultural models, and multi-sensor merging techniques.
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Long range stress correlations in the inherent structures of liquids at rest
DOE Office of Scientific and Technical Information (OSTI.GOV)
Chowdhury, Sadrul; Abraham, Sneha; Hudson, Toby
2016-03-28
Simulation studies of the atomic shear stress in the local potential energy minima (inherent structures) are reported for binary liquid mixtures in 2D and 3D. These inherent structure stresses are fundamental to slow stress relaxation and high viscosity in supercooled liquids. We find that the atomic shear stress in the inherent structures (IS’s) of both liquids at rest exhibits slowly decaying anisotropic correlations. We show that the stress correlations contribute significantly to the variance of the total shear stress of the IS configurations and consider the origins of the anisotropy and spatial extent of the stress correlations.
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CONSTRAINTS ON SPATIAL VARIATIONS IN THE FINE-STRUCTURE CONSTANT FROM PLANCK
DOE Office of Scientific and Technical Information (OSTI.GOV)
O'Bryan, Jon; Smidt, Joseph; De Bernardis, Francesco
2015-01-01
We use the cosmic microwave background (CMB) anisotropy data from Planck to constrain the spatial fluctuations of the fine-structure constant α at a redshift of 1100. We use a quadratic estimator to measure the four-point correlation function of the CMB temperature anisotropies and extract the angular power spectrum fine-structure constant spatial variations projected along the line of sight at the last scattering surface. At tens of degree angular scales and above, we constrain the fractional rms fluctuations of the fine-structure constant to be (δα/α){sub rms} < 3.4 × 10{sup –3} at the 68% confidence level. We find no evidence formore » a spatially varying α at a redshift of 10{sup 3}.« less
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Detto, Matteo; Muller-Landau, Helene C.; Mascaro, Joseph; Asner, Gregory P.
2013-01-01
An understanding of the spatial variability in tropical forest structure and biomass, and the mechanisms that underpin this variability, is critical for designing, interpreting, and upscaling field studies for regional carbon inventories. We investigated the spatial structure of tropical forest vegetation and its relationship to the hydrological network and associated topographic structure across spatial scales of 10–1000 m using high-resolution maps of LiDAR-derived mean canopy profile height (MCH) and elevation for 4930 ha of tropical forest in central Panama. MCH was strongly associated with the hydrological network: canopy height was highest in areas of positive convexity (valleys, depressions) close to channels draining 1 ha or more. Average MCH declined strongly with decreasing convexity (transition to ridges, hilltops) and increasing distance from the nearest channel. Spectral analysis, performed with wavelet decomposition, showed that the variance in MCH had fractal similarity at scales of ∼30–600 m, and was strongly associated with variation in elevation, with peak correlations at scales of ∼250 m. Whereas previous studies of topographic correlates of tropical forest structure conducted analyses at just one or a few spatial grains, our study found that correlations were strongly scale-dependent. Multi-scale analyses of correlations of MCH with slope, aspect, curvature, and Laplacian convexity found that MCH was most strongly related to convexity measured at scales of 20–300 m, a topographic variable that is a good proxy for position with respect to the hydrological network. Overall, our results support the idea that, even in these mesic forests, hydrological networks and associated topographical variation serve as templates upon which vegetation is organized over specific ranges of scales. These findings constitute an important step towards a mechanistic understanding of these patterns, and can guide upscaling and downscaling. PMID:24204610
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NASA Astrophysics Data System (ADS)
Maksimova, L. A.; Ryabukho, P. V.; Mysina, N. Yu.; Lyakin, D. V.; Ryabukho, V. P.
2018-04-01
We have investigated the capabilities of the method of digital speckle interferometry for determining subpixel displacements of a speckle structure formed by a displaceable or deformable object with a scattering surface. An analysis of spatial spectra of speckle structures makes it possible to perform measurements with a subpixel accuracy and to extend the lower boundary of the range of measurements of displacements of speckle structures to the range of subpixel values. The method is realized on the basis of digital recording of the images of undisplaced and displaced speckle structures, their spatial frequency analysis using numerically specified constant phase shifts, and correlation analysis of spatial spectra of speckle structures. Transformation into the frequency range makes it possible to obtain quantities to be measured with a subpixel accuracy from the shift of the interference-pattern minimum in the diffraction halo by introducing an additional phase shift into the complex spatial spectrum of the speckle structure or from the slope of the linear plot of the function of accumulated phase difference in the field of the complex spatial spectrum of the displaced speckle structure. The capabilities of the method have been investigated in natural experiment.
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Harmonic Brain Modes: A Unifying Framework for Linking Space and Time in Brain Dynamics.
Atasoy, Selen; Deco, Gustavo; Kringelbach, Morten L; Pearson, Joel
2018-06-01
A fundamental characteristic of spontaneous brain activity is coherent oscillations covering a wide range of frequencies. Interestingly, these temporal oscillations are highly correlated among spatially distributed cortical areas forming structured correlation patterns known as the resting state networks, although the brain is never truly at "rest." Here, we introduce the concept of harmonic brain modes-fundamental building blocks of complex spatiotemporal patterns of neural activity. We define these elementary harmonic brain modes as harmonic modes of structural connectivity; that is, connectome harmonics, yielding fully synchronous neural activity patterns with different frequency oscillations emerging on and constrained by the particular structure of the brain. Hence, this particular definition implicitly links the hitherto poorly understood dimensions of space and time in brain dynamics and its underlying anatomy. Further we show how harmonic brain modes can explain the relationship between neurophysiological, temporal, and network-level changes in the brain across different mental states ( wakefulness, sleep, anesthesia, psychedelic). Notably, when decoded as activation of connectome harmonics, spatial and temporal characteristics of neural activity naturally emerge from the interplay between excitation and inhibition and this critical relation fits the spatial, temporal, and neurophysiological changes associated with different mental states. Thus, the introduced framework of harmonic brain modes not only establishes a relation between the spatial structure of correlation patterns and temporal oscillations (linking space and time in brain dynamics), but also enables a new dimension of tools for understanding fundamental principles underlying brain dynamics in different states of consciousness.
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NASA Astrophysics Data System (ADS)
Mizyuk, Artem; Senderov, Maxim; Korotaev, Gennady
2016-04-01
Large number of numerical ocean models were implemented for the Black Sea basin during last two decades. They reproduce rather similar structure of synoptical variability of the circulation. Since 00-s numerical studies of the mesoscale structure are carried out using high performance computing (HPC). With the growing capacity of computing resources it is now possible to reconstruct the Black Sea currents with spatial resolution of several hundreds meters. However, how realistic these results can be? In the proposed study an attempt is made to understand which spatial scales are reproduced by ocean model in the Black Sea. Simulations are made using parallel version of NEMO (Nucleus for European Modelling of the Ocean). A two regional configurations with spatial resolutions 5 km and 2.5 km are described. Comparison of the SST from simulations with two spatial resolutions shows rather qualitative difference of the spatial structures. Results of high resolution simulation are compared also with satellite observations and observation-based products from Copernicus using spatial correlation and spectral analysis. Spatial scales of correlations functions for simulated and observed SST are rather close and differs much from satellite SST reanalysis. Evolution of spectral density for modelled SST and reanalysis showed agreed time periods of small scales intensification. Using of the spectral analysis for satellite measurements is complicated due to gaps. The research leading to this results has received funding from Russian Science Foundation (project № 15-17-20020)
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Exploring the Structure of Spatial Representations
Madl, Tamas; Franklin, Stan; Chen, Ke; Trappl, Robert; Montaldi, Daniela
2016-01-01
It has been suggested that the map-like representations that support human spatial memory are fragmented into sub-maps with local reference frames, rather than being unitary and global. However, the principles underlying the structure of these ‘cognitive maps’ are not well understood. We propose that the structure of the representations of navigation space arises from clustering within individual psychological spaces, i.e. from a process that groups together objects that are close in these spaces. Building on the ideas of representational geometry and similarity-based representations in cognitive science, we formulate methods for learning dissimilarity functions (metrics) characterizing participants’ psychological spaces. We show that these learned metrics, together with a probabilistic model of clustering based on the Bayesian cognition paradigm, allow prediction of participants’ cognitive map structures in advance. Apart from insights into spatial representation learning in human cognition, these methods could facilitate novel computational tools capable of using human-like spatial concepts. We also compare several features influencing spatial memory structure, including spatial distance, visual similarity and functional similarity, and report strong correlations between these dimensions and the grouping probability in participants’ spatial representations, providing further support for clustering in spatial memory. PMID:27347681
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Imaging subsurface hydrothermal structure using a dense geophone array in Yellowstone
NASA Astrophysics Data System (ADS)
Wu, S. M.; Lin, F. C.; Farrell, J.; Smith, R. B.
2016-12-01
The recent development of ambient noise cross-correlation and the availability of large N seismic arrays allow for the study of detailed shallow crustal structure. In this study, we apply multi-component noise cross-correlation to explore shallow hydrothermal structure near Old Faithful geyser in Yellowstone National Park using a temporary geophone array. The array was composed of 133 three-component 5-Hz geophones and was deployed for two weeks during November 2015. The average station spacing is 50 meters and the full aperture of the array is around 1 km with good azimuthal and spatial coverage. The Upper Geyser Basin, where Old Faithful is located, has the largest concentration of geysers in the world. This unique active hydrothermal environment and hence the extremely inhomogeneous noise source distribution makes the construction of empirical Green's functions difficult based on the traditional noise cross-correlation method. In this presentation, we show examples of the constructed cross-correlation functions and demonstrate their spatial and temporal relationships with known hydrothermal activity. We also demonstrate how useful seismic signals can be extracted from these cross-correlation functions and used for subsurface imaging. In particular, we will discuss the existence of a recharge cavity beneath Old Faithful revealed by the noise cross-correlations. In addition, we also investigated the temporal structure variation based on time-lapse noise cross-correlations and these preliminary results will also be discussed.
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Blob-hole correlation model for edge turbulence and comparisons with NSTX gas puff imaging data
NASA Astrophysics Data System (ADS)
Myra, J. R.; Zweben, S. J.; Russell, D. A.
2018-07-01
Gas puff imaging (GPI) observations made in NSTX (Zweben et al 2017 Phys. Plasmas 24 102509) have revealed two-point spatial correlations of edge and scrape-off layer (SOL) turbulence in the plane perpendicular to the magnetic field. A common feature is the occurrence of dipole-like patterns with significant regions of negative correlation. In this paper, we explore the possibility that these dipole patterns may be due to blob-hole pairs. Statistical methods are applied to determine the two-point spatial correlation that results from a model of blob-hole pair formation. It is shown that the model produces dipole correlation patterns that are qualitatively similar to the GPI data in several respects. Effects of the reference location (confined surfaces or SOL), a superimposed random background, hole velocity and lifetime, and background sheared flows are explored and discussed with respect to experimental observations. Additional analysis of the experimental GPI dataset is performed to further test this blob-hole correlation model. A time delay two-point spatial correlation study did not reveal inward propagation of the negative correlation structures that were postulated to correspond to holes in the data nor did it suggest that the negative correlation structures are due to neutral shadowing. However, tracking of the highest and lowest values (extrema) of the normalized GPI fluctuations shows strong evidence for mean inward propagation of minima and outward propagation of maxima, in qualitative agreement with theoretical expectations. Other properties of the experimentally observed extrema are discussed.
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Ban, Ehsan; Zhang, Sijia; Zarei, Vahhab; Barocas, Victor H; Winkelstein, Beth A; Picu, Catalin R
2017-07-01
The spinal facet capsular ligament (FCL) is primarily comprised of heterogeneous arrangements of collagen fibers. This complex fibrous structure and its evolution under loading play a critical role in determining the mechanical behavior of the FCL. A lack of analytical tools to characterize the spatial anisotropy and heterogeneity of the FCL's microstructure has limited the current understanding of its structure-function relationships. Here, the collagen organization was characterized using spatial correlation analysis of the FCL's optically obtained fiber orientation field. FCLs from the cervical and lumbar spinal regions were characterized in terms of their structure, as was the reorganization of collagen in stretched cervical FCLs. Higher degrees of intra- and intersample heterogeneity were found in cervical FCLs than in lumbar specimens. In the cervical FCLs, heterogeneity was manifested in the form of curvy patterns formed by collections of collagen fibers or fiber bundles. Tensile stretch, a common injury mechanism for the cervical FCL, significantly increased the spatial correlation length in the stretch direction, indicating an elongation of the observed structural features. Finally, an affine estimation for the change of correlation length under loading was performed which gave predictions very similar to the actual values. These findings provide structural insights for multiscale mechanical analyses of the FCLs from various spinal regions and also suggest methods for quantitative characterization of complex tissue patterns.
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Bianchini, Edmilson; Garcia, Cristina C; Pimenta, José A; Torezan, José M D
2010-09-01
Size structure and spatial arrangement of 13 abundant tree species were determined in a riparian forest fragment in Paraná State, South Brazil (23°16'S and 51°01'W). The studied species were Aspidosperma polyneuron Müll. Arg., Astronium graveolens Jacq. and Gallesia integrifolia (Spreng) Harms (emergent species); Alseis floribunda Schott, Ruprechtia laxiflora Meisn. and Bougainvillea spectabilis Willd. (shade-intolerant canopy species); Machaerium paraguariense Hassl, Myroxylum peruiferum L. and Chrysophyllum gonocarpum (Mart. & Eichler ex Miq.) Engl. (shade-tolerant canopy species); Sorocea bonplandii (Baill.) Bürger, Trichilia casaretti C. Dc, Trichilia catigua A. Juss. and Actinostemon concolor (Spreng.) Müll. Arg. (understory small trees species). Height and diameter structures and basal area of species were analyzed. Spatial patterns and slope correlation were analyzed by Moran's / spatial autocorrelation coefficient and partial Mantel test, respectively. The emergent and small understory species showed the highest and the lowest variations in height, diameter and basal area. Size distribution differed among emergent species and also among canopy shade-intolerant species. The spatial pattern ranged among species in all groups, except in understory small tree species. The slope was correlated with spatial pattern for A. polyneuron, A. graveolens, A. floribunda, R. laxiflora, M. peruiferum and T. casaretti. The results indicated that most species occurred in specific places, suggesting that niche differentiation can be an important factor in structuring the tree community.
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High Annular Resolution Stellar Interferometry.
1985-07-31
correlation is separable, C3 (Ax,At) = C1 (Ax) C2 (At), then the spatial structure and time evolution are uncorrelated and under these conditions one would...the following one. Reference 6 points out the bias obtained on the shape of the normalised spatial correlation function of dynamic speckle under the...MS student) 1982 H Daum (U1 assistant) 1981 C S ________ 20. 6. MUPID This appendix oontains oopies of the 20 publioations produced under this
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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.
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NASA Technical Reports Server (NTRS)
Smith, Andrew; LaVerde, Bruce; Jones, Douglas; Towner, Robert; Hunt, Ron
2013-01-01
Fluid structural interaction problems that estimate 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. Even when the analyst elects to use a fitted function for the spatial correlation an error may be introduced 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. Both qualitative and quantitative illustrations evaluating the adequacy of different patch density assumptions to approximate the fitted spatial correlation function are provided. The actual response of a typical vehicle panel system is then evaluated in a convergence study where the patch density assumptions are varied over the same finite element model. The convergence study results are presented illustrating the impact resulting from a poor choice of patch density. The fitted correlation function used in this study represents a Diffuse Acoustic Field (DAF) excitation of the panel to produce vibration response.
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Cooperation and age structure in spatial games
NASA Astrophysics Data System (ADS)
Wang, Zhen; Wang, Zhen; Zhu, Xiaodan; Arenzon, Jeferson J.
2012-01-01
We study the evolution of cooperation in evolutionary spatial games when the payoff correlates with the increasing age of players (the level of correlation is set through a single parameter, α). The demographic heterogeneous age distribution, directly affecting the outcome of the game, is thus shown to be responsible for enhancing the cooperative behavior in the population. In particular, moderate values of α allow cooperators not only to survive but to outcompete defectors, even when the temptation to defect is large and the ageless, standard α=0 model does not sustain cooperation. The interplay between age structure and noise is also considered, and we obtain the conditions for optimal levels of cooperation.
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Structure identification within a transitioning swept-wing boundary layer
NASA Astrophysics Data System (ADS)
Chapman, Keith Lance
1997-08-01
Extensive measurements are made in a transitioning swept-wing boundary layer using hot-film, hot-wire and cross-wire anemometry. The crossflow-dominated flow contains stationary vortices that breakdown near mid-chord. The most amplified vortex wavelength is forced by the use of artificial roughness elements near the leading edge. Two-component velocity and spanwise surface shear-stress correlation measurements are made at two constant chord locations, before and after transition. Streamwise surface shear stresses are also measured through the entire transition region. Correlation techniques are used to identify stationary structures in the laminar regime and coherent structures in the turbulent regime. Basic techniques include observation of the spatial correlations and the spatially distributed auto-spectra. The primary and secondary instability mechanisms are identified in the spectra in all measured fields. The primary mechanism is seen to grow, cause transition and produce large-scale turbulence. The secondary mechanism grows through the entire transition region and produces the small-scale turbulence. Advanced techniques use linear stochastic estimation (LSE) and proper orthogonal decomposition (POD) to identify the spatio-temporal evolutions of structures in the boundary layer. LSE is used to estimate the instantaneous velocity fields using temporal data from just two spatial locations and the spatial correlations. Reference locations are selected using maximum RMS values to provide the best available estimates. POD is used to objectively determine modes characteristic of the measured flow based on energy. The stationary vortices are identified in the first laminar modes of each velocity component and shear component. Experimental evidence suggests that neighboring vortices interact and produce large coherent structures with spanwise periodicity at double the stationary vortex wavelength. An objective transition region detection method is developed using streamwise spatial POD solutions which isolate the growth of the primary and secondary instability mechanisms in the first and second modes, respectively. Temporal evolutions of dominant POD modes in all measured fields are calculated. These scalar POD coefficients contain the integrated characteristics of the entire field, greatly reducing the amount of data to characterize the instantaneous field. These modes may then be used to train future flow control algorithms based on neural networks.
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Structure Identification Within a Transitioning Swept-Wing Boundary Layer
NASA Technical Reports Server (NTRS)
Chapman, Keith; Glauser, Mark
1996-01-01
Extensive measurements are made in a transitioning swept-wing boundary layer using hot-film, hot-wire and cross-wire anemometry. The crossflow-dominated flow contains stationary vortices that breakdown near mid-chord. The most amplified vortex wavelength is forced by the use of artificial roughness elements near the leading edge. Two-component velocity and spanwise surface shear-stress correlation measurements are made at two constant chord locations, before and after transition. Streamwise surface shear stresses are also measured through the entire transition region. Correlation techniques are used to identify stationary structures in the laminar regime and coherent structures in the turbulent regime. Basic techniques include observation of the spatial correlations and the spatially distributed auto-spectra. The primary and secondary instability mechanisms are identified in the spectra in all measured fields. The primary mechanism is seen to grow, cause transition and produce large-scale turbulence. The secondary mechanism grows through the entire transition region and produces the small-scale turbulence. Advanced techniques use Linear Stochastic Estimation (LSE) and Proper Orthogonal Decomposition (POD) to identify the spatio-temporal evolutions of structures in the boundary layer. LSE is used to estimate the instantaneous velocity fields using temporal data from just two spatial locations and the spatial correlations. Reference locations are selected using maximum RMS values to provide the best available estimates. POD is used to objectively determine modes characteristic of the measured flow based on energy. The stationary vortices are identified in the first laminar modes of each velocity component and shear component. Experimental evidence suggests that neighboring vortices interact and produce large coherent structures with spanwise periodicity at double the stationary vortex wavelength. An objective transition region detection method is developed using streamwise spatial POD solutions which isolate the growth of the primary and secondary instability mechanisms in the first and second modes, respectively. Temporal evolutions of dominant POD modes in all measured fields are calculated. These scalar POD coefficients contain the integrated characteristics of the entire field, greatly reducing the amount of data to characterize the instantaneous field. These modes may then be used to train future flow control algorithms based on neural networks.
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Space-time modeling of soil moisture
NASA Astrophysics Data System (ADS)
Chen, Zijuan; Mohanty, Binayak P.; Rodriguez-Iturbe, Ignacio
2017-11-01
A physically derived space-time mathematical representation of the soil moisture field is carried out via the soil moisture balance equation driven by stochastic rainfall forcing. The model incorporates spatial diffusion and in its original version, it is shown to be unable to reproduce the relative fast decay in the spatial correlation functions observed in empirical data. This decay resulting from variations in local topography as well as in local soil and vegetation conditions is well reproduced via a jitter process acting multiplicatively over the space-time soil moisture field. The jitter is a multiplicative noise acting on the soil moisture dynamics with the objective to deflate its correlation structure at small spatial scales which are not embedded in the probabilistic structure of the rainfall process that drives the dynamics. These scales of order of several meters to several hundred meters are of great importance in ecohydrologic dynamics. Properties of space-time correlation functions and spectral densities of the model with jitter are explored analytically, and the influence of the jitter parameters, reflecting variabilities of soil moisture at different spatial and temporal scales, is investigated. A case study fitting the derived model to a soil moisture dataset is presented in detail.
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Hyperspectral Image Denoising Using a Nonlocal Spectral Spatial Principal Component Analysis
NASA Astrophysics Data System (ADS)
Li, D.; Xu, L.; Peng, J.; Ma, J.
2018-04-01
Hyperspectral images (HSIs) denoising is a critical research area in image processing duo to its importance in improving the quality of HSIs, which has a negative impact on object detection and classification and so on. In this paper, we develop a noise reduction method based on principal component analysis (PCA) for hyperspectral imagery, which is dependent on the assumption that the noise can be removed by selecting the leading principal components. The main contribution of paper is to introduce the spectral spatial structure and nonlocal similarity of the HSIs into the PCA denoising model. PCA with spectral spatial structure can exploit spectral correlation and spatial correlation of HSI by using 3D blocks instead of 2D patches. Nonlocal similarity means the similarity between the referenced pixel and other pixels in nonlocal area, where Mahalanobis distance algorithm is used to estimate the spatial spectral similarity by calculating the distance in 3D blocks. The proposed method is tested on both simulated and real hyperspectral images, the results demonstrate that the proposed method is superior to several other popular methods in HSI denoising.
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Hierarchical drivers of reef-fish metacommunity structure.
MacNeil, M Aaron; Graham, Nicholas A J; Polunin, Nicholas V C; Kulbicki, Michel; Galzin, René; Harmelin-Vivien, Mireille; Rushton, Steven P
2009-01-01
Coral reefs are highly complex ecological systems, where multiple processes interact across scales in space and time to create assemblages of exceptionally high biodiversity. Despite the increasing frequency of hierarchically structured sampling programs used in coral-reef science, little progress has been made in quantifying the relative importance of processes operating across multiple scales. The vast majority of reef studies are conducted, or at least analyzed, at a single spatial scale, ignoring the implicitly hierarchical structure of the overall system in favor of small-scale experiments or large-scale observations. Here we demonstrate how alpha (mean local number of species), beta diversity (degree of species dissimilarity among local sites), and gamma diversity (overall species richness) vary with spatial scale, and using a hierarchical, information-theoretic approach, we evaluate the relative importance of site-, reef-, and atoll-level processes driving the fish metacommunity structure among 10 atolls in French Polynesia. Process-based models, representing well-established hypotheses about drivers of reef-fish community structure, were assembled into a candidate set of 12 hierarchical linear models. Variation in fish abundance, biomass, and species richness were unevenly distributed among transect, reef, and atoll levels, establishing the relative contribution of variation at these spatial scales to the structure of the metacommunity. Reef-fish biomass, species richness, and the abundance of most functional-groups corresponded primarily with transect-level habitat diversity and atoll-lagoon size, whereas detritivore and grazer abundances were largely correlated with potential covariates of larval dispersal. Our findings show that (1) within-transect and among-atoll factors primarily drive the relationship between alpha and gamma diversity in this reef-fish metacommunity; (2) habitat is the primary correlate with reef-fish metacommunity structure at multiple spatial scales; and (3) inter-atoll connectedness was poorly correlated with the nonrandom clustering of reef-fish species. These results demonstrate the importance of modeling hierarchical data and processes in understanding reef-fish metacommunity structure.
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Spatial variability of macrobenthic zonation on exposed sandy beaches
NASA Astrophysics Data System (ADS)
Veiga, Puri; Rubal, Marcos; Cacabelos, Eva; Maldonado, Cristina; Sousa-Pinto, Isabel
2014-07-01
We analysed the consistence of vertical patterns of distribution (i.e. zonation) for macrofauna at different spatial scales on four intermediate exposed beaches in the North of Portugal. We tested the hypothesis that biological zonation on exposed sandy beaches would vary at the studied spatial scales. For this aim, abundance, diversity and structure of macrobenthic assemblages were examined at the scales of transect and beach. Moreover, the main environmental factors that could potentially drive zonation patterns were investigated. Univariate and multivariate analyses revealed that the number of biological zones ranged from two to three depending on the beach and from indistinct zonation to three zones at the scale of transect. Therefore, results support our working hypothesis because zonation patterns were not consistent at the studied spatial scales. The median particle size, sorting coefficient and water content were significantly correlated with zonation patterns of macrobenthic assemblages. However, a high degree of correlation was not reached when the total structure of the assemblage was considered.
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Imaging of supersonic flow over a double elliptic surface
NASA Astrophysics Data System (ADS)
Zhang, Qing-Hu; Yi, Shi-He; He, Lin; Zhu, Yang-Zhu; Chen, Zhi
2013-11-01
The coherent structures of flow over a double elliptic surface are experimentally investigated in a supersonic low-noise wind tunnel at Mach number 3 using nano-tracer planar laser scattering (NPLS) and particle image velocimetry (PIV) techniques. High spatiotemporal resolution images and velocity fields of both laminar and turbulent inflows over the test model are captured. Based on the time-correlation images, the spatial and temporal evolutionary characteristics of the coherent structures are investigated. The flow structures in the NPLS images are in good agreement with the velocity fluctuation fields by PIV. From statistically significant ensembles, spatial correlation analysis of both cases is performed to quantify the mean size and the orientation of coherent structures. The results indicate that the mean structure is elliptical in shape and the structural angles in the separated region of laminar inflow are slightly smaller than that of turbulent inflow. Moreover, the structural angles of both cases increase with their distance away from the wall.
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On the role of spatial phase and phase correlation in vision, illusion, and cognition
Gladilin, Evgeny; Eils, Roland
2015-01-01
Numerous findings indicate that spatial phase bears an important cognitive information. Distortion of phase affects topology of edge structures and makes images unrecognizable. In turn, appropriately phase-structured patterns give rise to various illusions of virtual image content and apparent motion. Despite a large body of phenomenological evidence not much is known yet about the role of phase information in neural mechanisms of visual perception and cognition. Here, we are concerned with analysis of the role of spatial phase in computational and biological vision, emergence of visual illusions and pattern recognition. We hypothesize that fundamental importance of phase information for invariant retrieval of structural image features and motion detection promoted development of phase-based mechanisms of neural image processing in course of evolution of biological vision. Using an extension of Fourier phase correlation technique, we show that the core functions of visual system such as motion detection and pattern recognition can be facilitated by the same basic mechanism. Our analysis suggests that emergence of visual illusions can be attributed to presence of coherently phase-shifted repetitive patterns as well as the effects of acuity compensation by saccadic eye movements. We speculate that biological vision relies on perceptual mechanisms effectively similar to phase correlation, and predict neural features of visual pattern (dis)similarity that can be used for experimental validation of our hypothesis of “cognition by phase correlation.” PMID:25954190
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On the role of spatial phase and phase correlation in vision, illusion, and cognition.
Gladilin, Evgeny; Eils, Roland
2015-01-01
Numerous findings indicate that spatial phase bears an important cognitive information. Distortion of phase affects topology of edge structures and makes images unrecognizable. In turn, appropriately phase-structured patterns give rise to various illusions of virtual image content and apparent motion. Despite a large body of phenomenological evidence not much is known yet about the role of phase information in neural mechanisms of visual perception and cognition. Here, we are concerned with analysis of the role of spatial phase in computational and biological vision, emergence of visual illusions and pattern recognition. We hypothesize that fundamental importance of phase information for invariant retrieval of structural image features and motion detection promoted development of phase-based mechanisms of neural image processing in course of evolution of biological vision. Using an extension of Fourier phase correlation technique, we show that the core functions of visual system such as motion detection and pattern recognition can be facilitated by the same basic mechanism. Our analysis suggests that emergence of visual illusions can be attributed to presence of coherently phase-shifted repetitive patterns as well as the effects of acuity compensation by saccadic eye movements. We speculate that biological vision relies on perceptual mechanisms effectively similar to phase correlation, and predict neural features of visual pattern (dis)similarity that can be used for experimental validation of our hypothesis of "cognition by phase correlation."
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Restoring method for missing data of spatial structural stress monitoring based on correlation
NASA Astrophysics Data System (ADS)
Zhang, Zeyu; Luo, Yaozhi
2017-07-01
Long-term monitoring of spatial structures is of great importance for the full understanding of their performance and safety. The missing part of the monitoring data link will affect the data analysis and safety assessment of the structure. Based on the long-term monitoring data of the steel structure of the Hangzhou Olympic Center Stadium, the correlation between the stress change of the measuring points is studied, and an interpolation method of the missing stress data is proposed. Stress data of correlated measuring points are selected in the 3 months of the season when missing data is required for fitting correlation. Data of daytime and nighttime are fitted separately for interpolation. For a simple linear regression when single point's correlation coefficient is 0.9 or more, the average error of interpolation is about 5%. For multiple linear regression, the interpolation accuracy is not significantly increased after the number of correlated points is more than 6. Stress baseline value of construction step should be calculated before interpolating missing data in the construction stage, and the average error is within 10%. The interpolation error of continuous missing data is slightly larger than that of the discrete missing data. The data missing rate of this method should better not exceed 30%. Finally, a measuring point's missing monitoring data is restored to verify the validity of the method.
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NASA Astrophysics Data System (ADS)
Dong, Jingnuo; Ochsner, Tyson E.
2018-03-01
Soil moisture patterns are commonly thought to be dominated by land surface characteristics, such as soil texture, at small scales and by atmospheric processes, such as precipitation, at larger scales. However, a growing body of evidence challenges this conceptual model. We investigated the structural similarity and spatial correlations between mesoscale (˜1-100 km) soil moisture patterns and land surface and atmospheric factors along a 150 km transect using 4 km multisensor precipitation data and a cosmic-ray neutron rover, with a 400 m diameter footprint. The rover was used to measure soil moisture along the transect 18 times over 13 months. Spatial structures of soil moisture, soil texture (sand content), and antecedent precipitation index (API) were characterized using autocorrelation functions and fitted with exponential models. Relative importance of land surface characteristics and atmospheric processes were compared using correlation coefficients (r) between soil moisture and sand content or API. The correlation lengths of soil moisture, sand content, and API ranged from 12-32 km, 13-20 km, and 14-45 km, respectively. Soil moisture was more strongly correlated with sand content (r = -0.536 to -0.704) than with API for all but one date. Thus, land surface characteristics exhibit coherent spatial patterns at scales up to 20 km, and those patterns often exert a stronger influence than do precipitation patterns on mesoscale spatial patterns of soil moisture.
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Wong, Stephen; Hargreaves, Eric L; Baltuch, Gordon H; Jaggi, Jurg L; Danish, Shabbar F
2012-01-01
Microelectrode recording (MER) is necessary for precision localization of target structures such as the subthalamic nucleus during deep brain stimulation (DBS) surgery. Attempts to automate this process have produced quantitative temporal trends (feature activity vs. time) extracted from mobile MER data. Our goal was to evaluate computational methods of generating spatial profiles (feature activity vs. depth) from temporal trends that would decouple automated MER localization from the clinical procedure and enhance functional localization in DBS surgery. We evaluated two methods of interpolation (standard vs. kernel) that generated spatial profiles from temporal trends. We compared interpolated spatial profiles to true spatial profiles that were calculated with depth windows, using correlation coefficient analysis. Excellent approximation of true spatial profiles is achieved by interpolation. Kernel-interpolated spatial profiles produced superior correlation coefficient values at optimal kernel widths (r = 0.932-0.940) compared to standard interpolation (r = 0.891). The choice of kernel function and kernel width resulted in trade-offs in smoothing and resolution. Interpolation of feature activity to create spatial profiles from temporal trends is accurate and can standardize and facilitate MER functional localization of subcortical structures. The methods are computationally efficient, enhancing localization without imposing additional constraints on the MER clinical procedure during DBS surgery. Copyright © 2012 S. Karger AG, Basel.
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Performance analysis of structured gradient algorithm. [for adaptive beamforming linear arrays
NASA Technical Reports Server (NTRS)
Godara, Lal C.
1990-01-01
The structured gradient algorithm uses a structured estimate of the array correlation matrix (ACM) to estimate the gradient required for the constrained least-mean-square (LMS) algorithm. This structure reflects the structure of the exact array correlation matrix for an equispaced linear array and is obtained by spatial averaging of the elements of the noisy correlation matrix. In its standard form the LMS algorithm does not exploit the structure of the array correlation matrix. The gradient is estimated by multiplying the array output with the receiver outputs. An analysis of the two algorithms is presented to show that the covariance of the gradient estimated by the structured method is less sensitive to the look direction signal than that estimated by the standard method. The effect of the number of elements on the signal sensitivity of the two algorithms is studied.
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Correlation of morphological and molecular parameters for colon cancer
NASA Astrophysics Data System (ADS)
Yuan, Shuai; Roney, Celeste A.; Li, Qian; Jiang, James; Cable, Alex; Summers, Ronald M.; Chen, Yu
2010-02-01
Colorectal cancer (CRC) is the second leading cause of cancer death in the United States. There is great interest in studying the relationship among microstructures and molecular processes of colorectal cancer during its progression at early stages. In this study, we use our multi-modality optical system that could obtain co-registered optical coherence tomography (OCT) and fluorescence molecular imaging (FMI) images simultaneously to study CRC. The overexpressed carbohydrate α-L-fucose on the surfaces of polyps facilitates the bond of adenomatous polyps with UEA-1 and is used as biomarker. Tissue scattering coefficient derived from OCT axial scan is used as quantitative value of structural information. Both structural images from OCT and molecular images show spatial heterogeneity of tumors. Correlations between those values are analyzed and demonstrate that scattering coefficients are positively correlated with FMI signals in conjugated. In UEA-1 conjugated samples (8 polyps and 8 control regions), the correlation coefficient is ranged from 0.45 to 0.99. These findings indicate that the microstructure of polyps is changed gradually during cancer progression and the change is well correlated with certain molecular process. Our study demonstrated that multi-parametric imaging is able to simultaneously detect morphology and molecular information and it can enable spatially and temporally correlated studies of structure-function relationships during tumor progression.
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Yang, Linglu; Yan, Bo; Reinhard, Björn M.
2009-01-01
The optical spectra of individual Ag-Au alloy hollow particles were correlated with the particles’ structures obtained by transmission electron microscopy (TEM). The TEM provided direct experimental access to the dimension of the cavity, thickness of the metal shell, and the interparticle distance of hollow particle dimers with high spatial resolution. The analysis of correlated spectral and structural information enabled the quantification of the influence of the core-shell structure on the resonance energy, plasmon lifetime, and plasmon coupling efficiency. Electron beam exposure during TEM inspection was observed to affect plasmon wavelength and lifetime, making optical inspection prior to structural characterization mandatory. PMID:19768108
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Astrophysical data analysis with information field theory
NASA Astrophysics Data System (ADS)
Enßlin, Torsten
2014-12-01
Non-parametric imaging and data analysis in astrophysics and cosmology can be addressed by information field theory (IFT), a means of Bayesian, data based inference on spatially distributed signal fields. IFT is a statistical field theory, which permits the construction of optimal signal recovery algorithms. It exploits spatial correlations of the signal fields even for nonlinear and non-Gaussian signal inference problems. The alleviation of a perception threshold for recovering signals of unknown correlation structure by using IFT will be discussed in particular as well as a novel improvement on instrumental self-calibration schemes. IFT can be applied to many areas. Here, applications in in cosmology (cosmic microwave background, large-scale structure) and astrophysics (galactic magnetism, radio interferometry) are presented.
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LETTER TO THE EDITOR: Evidence for global mixing in real influenza epidemics
NASA Astrophysics Data System (ADS)
Bonabeau, Eric; Toubiana, Laurent; Flahault, Antoine
1998-05-01
The spatiotemporal behaviour of the spread of influenza in France has been studied, and algebraic spatial correlations (with exponent 0305-4470/31/19/001/img5) spanning the whole territory have been found to be present as soon as the number of reported cases begins to increase, about 15 - 25 weeks before the peak of the epidemic. This result is surprising, as one would expect long-range correlations, if any, only in the vicinity of the maximum incidence, whereas our observations suggest that there exists an underlying non-trivial spatial structure at the very beginning of the observed epidemic. The observed long-range correlations are in fact present in the spatial distribution of the population. Correlations in the number of cases normalized by local population density are characterized by 0305-4470/31/19/001/img6. This suggests that the spread of the epidemic is statistically uniform in space over a complex substrate that already contains the observed long-range correlations.
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NASA Astrophysics Data System (ADS)
Massoudieh, A.; Dentz, M.; Le Borgne, T.
2017-12-01
In heterogeneous media, the velocity distribution and the spatial correlation structure of velocity for solute particles determine the breakthrough curves and how they evolve as one moves away from the solute source. The ability to predict such evolution can help relating the spatio-statistical hydraulic properties of the media to the transport behavior and travel time distributions. While commonly used non-local transport models such as anomalous dispersion and classical continuous time random walk (CTRW) can reproduce breakthrough curve successfully by adjusting the model parameter values, they lack the ability to relate model parameters to the spatio-statistical properties of the media. This in turns limits the transferability of these models. In the research to be presented, we express concentration or flux of solutes as a distribution over their velocity. We then derive an integrodifferential equation that governs the evolution of the particle distribution over velocity at given times and locations for a particle ensemble, based on a presumed velocity correlation structure and an ergodic cross-sectional velocity distribution. This way, the spatial evolution of breakthrough curves away from the source is predicted based on cross-sectional velocity distribution and the connectivity, which is expressed by the velocity transition probability density. The transition probability is specified via a copula function that can help construct a joint distribution with a given correlation and given marginal velocities. Using this approach, we analyze the breakthrough curves depending on the velocity distribution and correlation properties. The model shows how the solute transport behavior evolves from ballistic transport at small spatial scales to Fickian dispersion at large length scales relative to the velocity correlation length.
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Andrus, J Malia; Porter, Matthew D; Rodríguez, Luis F; Kuehlhorn, Timothy; Cooke, Richard A C; Zhang, Yuanhui; Kent, Angela D; Zilles, Julie L
2014-02-01
Denitrifying biofilters can remove agricultural nitrates from subsurface drainage, reducing nitrate pollution that contributes to coastal hypoxic zones. The performance and reliability of natural and engineered systems dependent upon microbially mediated processes, such as the denitrifying biofilters, can be affected by the spatial structure of their microbial communities. Furthermore, our understanding of the relationship between microbial community composition and function is influenced by the spatial distribution of samples.In this study we characterized the spatial structure of bacterial communities in a denitrifying biofilter in central Illinois. Bacterial communities were assessed using automated ribosomal intergenic spacer analysis for bacteria and terminal restriction fragment length polymorphism of nosZ for denitrifying bacteria.Non-metric multidimensional scaling and analysis of similarity (ANOSIM) analyses indicated that bacteria showed statistically significant spatial structure by depth and transect,while denitrifying bacteria did not exhibit significant spatial structure. For determination of spatial patterns, we developed a package of automated functions for the R statistical environment that allows directional analysis of microbial community composition data using either ANOSIM or Mantel statistics.Applying this package to the biofilter data, the flow path correlation range for the bacterial community was 6.4 m at the shallower, periodically in undated depth and 10.7 m at the deeper, continually submerged depth. These spatial structures suggest a strong influence of hydrology on the microbial community composition in these denitrifying biofilters. Understanding such spatial structure can also guide optimal sample collection strategies for microbial community analyses.
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Revisiting Temporal Markov Chains for Continuum modeling of Transport in Porous Media
NASA Astrophysics Data System (ADS)
Delgoshaie, A. H.; Jenny, P.; Tchelepi, H.
2017-12-01
The transport of fluids in porous media is dominated by flow-field heterogeneity resulting from the underlying permeability field. Due to the high uncertainty in the permeability field, many realizations of the reference geological model are used to describe the statistics of the transport phenomena in a Monte Carlo (MC) framework. There has been strong interest in working with stochastic formulations of the transport that are different from the standard MC approach. Several stochastic models based on a velocity process for tracer particle trajectories have been proposed. Previous studies have shown that for high variances of the log-conductivity, the stochastic models need to account for correlations between consecutive velocity transitions to predict dispersion accurately. The correlated velocity models proposed in the literature can be divided into two general classes of temporal and spatial Markov models. Temporal Markov models have been applied successfully to tracer transport in both the longitudinal and transverse directions. These temporal models are Stochastic Differential Equations (SDEs) with very specific drift and diffusion terms tailored for a specific permeability correlation structure. The drift and diffusion functions devised for a certain setup would not necessarily be suitable for a different scenario, (e.g., a different permeability correlation structure). The spatial Markov models are simple discrete Markov chains that do not require case specific assumptions. However, transverse spreading of contaminant plumes has not been successfully modeled with the available correlated spatial models. Here, we propose a temporal discrete Markov chain to model both the longitudinal and transverse dispersion in a two-dimensional domain. We demonstrate that these temporal Markov models are valid for different correlation structures without modification. Similar to the temporal SDEs, the proposed model respects the limited asymptotic transverse spreading of the plume in two-dimensional problems.
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Multivariate analysis of scale-dependent associations between bats and landscape structure
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.
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Separate but correlated: The latent structure of space and mathematics across development.
Mix, Kelly S; Levine, Susan C; Cheng, Yi-Ling; Young, Chris; Hambrick, D Zachary; Ping, Raedy; Konstantopoulos, Spyros
2016-09-01
The relations among various spatial and mathematics skills were assessed in a cross-sectional study of 854 children from kindergarten, third, and sixth grades (i.e., 5 to 13 years of age). Children completed a battery of spatial mathematics tests and their scores were submitted to exploratory factor analyses both within and across domains. In the within domain analyses, all of the measures formed single factors at each age, suggesting consistent, unitary structures across this age range. Yet, as in previous work, the 2 domains were highly correlated, both in terms of overall composite score and pairwise comparisons of individual tasks. When both spatial and mathematics scores were submitted to the same factor analysis, the 2 domain specific factors again emerged, but there also were significant cross-domain factor loadings that varied with age. Multivariate regressions replicated the factor analysis and further revealed that mental rotation was the best predictor of mathematical performance in kindergarten, and visual-spatial working memory was the best predictor of mathematical performance in sixth grade. The mathematical tasks that predicted the most variance in spatial skill were place value (K, 3rd, 6th), word problems (3rd, 6th), calculation (K), fraction concepts (3rd), and algebra (6th). Thus, although spatial skill and mathematics each have strong internal structures, they also share significant overlap, and have particularly strong cross-domain relations for certain tasks. (PsycINFO Database Record (c) 2016 APA, all rights reserved).
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Hu, Rui Bin; Fang, Xi; Xiang, Wen Hua; Jiang, Fang; Lei, Pi Feng; Zhao, Li Juan; Zhu, Wen Juan; Deng, Xiang Wen
2016-03-01
In order to investigate spatial variations in soil phosphorus (P) concentration and the influencing factors, one permanent plot of 1 hm 2 was established and stand structure was surveyed in Choerospondias axillaries deciduous broadleaved forest in Dashanchong Forest Park in Changsha County, Hunan Province, China. Soil samples were collected with equidistant grid point sampling method and soil P concentration and its spatial variation were analyzed by using geo-statistics and geographical information system (GIS) techniques. The results showed that the variations of total P and available P concentrations in humus layer and in the soil profile at depth of 0-10, 10-20 and 20-30 cm were moderate and the available P showed higher variability in a specific soil layer compared with total P. Concentrations of total P and available P in soil decreased, while the variations increased with the increase in soil depth. The total P and available P showed high spatial autocorrelation, primarily resulted from the structural factors. The spatial heterogeneity of available P was stronger than that of total P, and the spatial autocorrelation ranges of total P and available P varied from 92.80 to 168.90 m and from 79.43 to 106.20 m in different soil layers, respectively. At the same soil depth, fractal dimensions of total P were higher than that of available P, with more complex spatial pattern, while available P showed stronger spatial correlation with stronger spatial structure. In humus layer and soil depths of 0-10, 10-20 and 20-30 cm, the spatial variation pattern of total P and available P concentrations showed an apparent belt-shaped and spot massive gradient change. The high value appeared at low elevation and valley position, and the low value appeared in the high elevation and ridge area. The total P and available P concentrations showed significantly negative correlation with elevation and litter, but the relationship with convexity, species, numbers and soil pH was not significant. The total P and available P exhibited significant positive correlations with soil organic carbon (SOC), total nitrogen concentration, indicating the leaching characteristics of soil P. Its spatial variability was affected by many interactive factors.
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Blob-hole correlation model for edge turbulence and comparisons with NSTX gas puff imaging data
DOE Office of Scientific and Technical Information (OSTI.GOV)
Myra, J. R.; Zweben, S. J.; Russell, D. A.
We report that gas puff imaging (GPI) observations made in NSTX [Zweben S J, et al., 2017 Phys. Plasmas 24 102509] have revealed two-point spatial correlations of edge and scrape-off layer turbulence in the plane perpendicular to the magnetic field. A common feature is the occurrence of dipole-like patterns with significant regions of negative correlation. In this paper, we explore the possibility that these dipole patterns may be due to blob-hole pairs. Statistical methods are applied to determine the two-point spatial correlation that results from a model of blob-hole pair formation. It is shown that the model produces dipole correlationmore » patterns that are qualitatively similar to the GPI data in several respects. Effects of the reference location (confined surfaces or scrape-off layer), a superimposed random background, hole velocity and lifetime, and background sheared flows are explored and discussed with respect to experimental observations. Additional analysis of the experimental GPI dataset is performed to further test this blob-hole correlation model. A time delay two-point spatial correlation study did not reveal inward propagation of the negative correlation structures that were postulated to correspond to holes in the data nor did it suggest that the negative correlation structures are due to neutral shadowing. However, tracking of the highest and lowest values (extrema) of the normalized GPI fluctuations shows strong evidence for mean inward propagation of minima and outward propagation of maxima, in qualitative agreement with theoretical expectations. Finally, other properties of the experimentally observed extrema are discussed.« less
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Blob-hole correlation model for edge turbulence and comparisons with NSTX gas puff imaging data
Myra, J. R.; Zweben, S. J.; Russell, D. A.
2018-05-15
We report that gas puff imaging (GPI) observations made in NSTX [Zweben S J, et al., 2017 Phys. Plasmas 24 102509] have revealed two-point spatial correlations of edge and scrape-off layer turbulence in the plane perpendicular to the magnetic field. A common feature is the occurrence of dipole-like patterns with significant regions of negative correlation. In this paper, we explore the possibility that these dipole patterns may be due to blob-hole pairs. Statistical methods are applied to determine the two-point spatial correlation that results from a model of blob-hole pair formation. It is shown that the model produces dipole correlationmore » patterns that are qualitatively similar to the GPI data in several respects. Effects of the reference location (confined surfaces or scrape-off layer), a superimposed random background, hole velocity and lifetime, and background sheared flows are explored and discussed with respect to experimental observations. Additional analysis of the experimental GPI dataset is performed to further test this blob-hole correlation model. A time delay two-point spatial correlation study did not reveal inward propagation of the negative correlation structures that were postulated to correspond to holes in the data nor did it suggest that the negative correlation structures are due to neutral shadowing. However, tracking of the highest and lowest values (extrema) of the normalized GPI fluctuations shows strong evidence for mean inward propagation of minima and outward propagation of maxima, in qualitative agreement with theoretical expectations. Finally, other properties of the experimentally observed extrema are discussed.« less
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NASA Astrophysics Data System (ADS)
Austermann, J. E.; Aretxaga, I.; Hughes, D. H.; Kang, Y.; Kim, S.; Lowenthal, J. D.; Perera, T. A.; Sanders, D. B.; Scott, K. S.; Scoville, N.; Wilson, G. W.; Yun, M. S.
2009-03-01
We report an overdensity of bright submillimetre galaxies (SMGs) in the 0.15 deg2 AzTEC/COSMOS survey and a spatial correlation between the SMGs and the optical-IR galaxy density at z <~ 1.1. This portion of the COSMOS field shows a ~3σ overdensity of robust SMG detections when compared to a background, or `blank-field', population model that is consistent with SMG surveys of fields with no extragalactic bias. The SMG overdensity is most significant in the number of very bright detections (14 sources with measured fluxes S1.1mm > 6 mJy), which is entirely incompatible with sample variance within our adopted blank-field number densities and infers an overdensity significance of >> 4σ. We find that the overdensity and spatial correlation to optical-IR galaxy density are most consistent with lensing of a background SMG population by foreground mass structures along the line of sight, rather than physical association of the SMGs with the z <~ 1.1 galaxies/clusters. The SMG positions are only weakly correlated with weak-lensing maps, suggesting that the dominant sources of correlation are individual galaxies and the more tenuous structures in the survey region, and not the massive and compact clusters. These results highlight the important roles cosmic variance and large-scale structure can play in the study of SMGs.
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A New Methodology of Spatial Cross-Correlation Analysis
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
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A new methodology of spatial cross-correlation analysis.
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.
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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.
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Genetic Structure of Bluefin Tuna in the Mediterranean Sea Correlates with Environmental Variables
Riccioni, Giulia; Stagioni, Marco; Landi, Monica; Ferrara, Giorgia; Barbujani, Guido; Tinti, Fausto
2013-01-01
Background Atlantic Bluefin Tuna (ABFT) shows complex demography and ecological variation in the Mediterranean Sea. Genetic surveys have detected significant, although weak, signals of population structuring; catch series analyses and tagging programs identified complex ABFT spatial dynamics and migration patterns. Here, we tested the hypothesis that the genetic structure of the ABFT in the Mediterranean is correlated with mean surface temperature and salinity. Methodology We used six samples collected from Western and Central Mediterranean integrated with a new sample collected from the recently identified easternmost reproductive area of Levantine Sea. To assess population structure in the Mediterranean we used a multidisciplinary framework combining classical population genetics, spatial and Bayesian clustering methods and a multivariate approach based on factor analysis. Conclusions FST analysis and Bayesian clustering methods detected several subpopulations in the Mediterranean, a result also supported by multivariate analyses. In addition, we identified significant correlations of genetic diversity with mean salinity and surface temperature values revealing that ABFT is genetically structured along two environmental gradients. These results suggest that a preference for some spawning habitat conditions could contribute to shape ABFT genetic structuring in the Mediterranean. However, further studies should be performed to assess to what extent ABFT spawning behaviour in the Mediterranean Sea can be affected by environmental variation. PMID:24260341
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NASA Astrophysics Data System (ADS)
Maksov, Artem; Ziatdinov, Maxim; Li, Li; Sefat, Athena; Maksymovych, Petro; Kalinin, Sergei
Crystalline matter on the nanoscale level often exhibits strongly inhomogeneous structural and electronic orders, which have a profound effect on macroscopic properties. This may be caused by subtle interplay between chemical disorder, strain, magnetic, and structural order parameters. We present a novel approach based on combination of high resolution scanning tunneling microscopy/spectroscopy (STM/S) and deep data style analysis for automatic separation, extraction, and correlation of structural and electronic behavior which might lead us to uncovering the underlying sources of inhomogeneity in in iron-based family of superconductors (FeSe, BaFe2As2) . We identify STS spectral features using physically robust Bayesian linear unmixing, and show their direct relevance to the fundamental physical properties of the system, including electronic states associated with individual defects and impurities. We collect structural data from individual unit cells on the crystalline lattice, and calculate both global and local indicators of spatial correlation with electronic features, demonstrating, for the first time, a direct quantifiable connection between observed structural order parameters extracted from the STM data and electronic order parameters identified within the STS data. This research was sponsored by the Division of Materials Sciences and Engineering, Office of Science, Basic Energy Sciences, US DOE.
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Li, Gang; He, Bin; Huang, Hongwei; Tang, Limin
2016-01-01
The spatial–temporal correlation is an important feature of sensor data in wireless sensor networks (WSNs). Most of the existing works based on the spatial–temporal correlation can be divided into two parts: redundancy reduction and anomaly detection. These two parts are pursued separately in existing works. In this work, the combination of temporal data-driven sleep scheduling (TDSS) and spatial data-driven anomaly detection is proposed, where TDSS can reduce data redundancy. The TDSS model is inspired by transmission control protocol (TCP) congestion control. Based on long and linear cluster structure in the tunnel monitoring system, cooperative TDSS and spatial data-driven anomaly detection are then proposed. To realize synchronous acquisition in the same ring for analyzing the situation of every ring, TDSS is implemented in a cooperative way in the cluster. To keep the precision of sensor data, spatial data-driven anomaly detection based on the spatial correlation and Kriging method is realized to generate an anomaly indicator. The experiment results show that cooperative TDSS can realize non-uniform sensing effectively to reduce the energy consumption. In addition, spatial data-driven anomaly detection is quite significant for maintaining and improving the precision of sensor data. PMID:27690035
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A composite likelihood approach for spatially correlated survival data
Paik, Jane; Ying, Zhiliang
2013-01-01
The aim of this paper is to provide a composite likelihood approach to handle spatially correlated survival data using pairwise joint distributions. With e-commerce data, a recent question of interest in marketing research has been to describe spatially clustered purchasing behavior and to assess whether geographic distance is the appropriate metric to describe purchasing dependence. We present a model for the dependence structure of time-to-event data subject to spatial dependence to characterize purchasing behavior from the motivating example from e-commerce data. We assume the Farlie-Gumbel-Morgenstern (FGM) distribution and then model the dependence parameter as a function of geographic and demographic pairwise distances. For estimation of the dependence parameters, we present pairwise composite likelihood equations. We prove that the resulting estimators exhibit key properties of consistency and asymptotic normality under certain regularity conditions in the increasing-domain framework of spatial asymptotic theory. PMID:24223450
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A composite likelihood approach for spatially correlated survival data.
Paik, Jane; Ying, Zhiliang
2013-01-01
The aim of this paper is to provide a composite likelihood approach to handle spatially correlated survival data using pairwise joint distributions. With e-commerce data, a recent question of interest in marketing research has been to describe spatially clustered purchasing behavior and to assess whether geographic distance is the appropriate metric to describe purchasing dependence. We present a model for the dependence structure of time-to-event data subject to spatial dependence to characterize purchasing behavior from the motivating example from e-commerce data. We assume the Farlie-Gumbel-Morgenstern (FGM) distribution and then model the dependence parameter as a function of geographic and demographic pairwise distances. For estimation of the dependence parameters, we present pairwise composite likelihood equations. We prove that the resulting estimators exhibit key properties of consistency and asymptotic normality under certain regularity conditions in the increasing-domain framework of spatial asymptotic theory.
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A spatially adaptive spectral re-ordering technique for lossless coding of hyper-spectral images
NASA Technical Reports Server (NTRS)
Memon, Nasir D.; Galatsanos, Nikolas
1995-01-01
In this paper, we propose a new approach, applicable to lossless compression of hyper-spectral images, that alleviates some limitations of linear prediction as applied to this problem. According to this approach, an adaptive re-ordering of the spectral components of each pixel is performed prior to prediction and encoding. This re-ordering adaptively exploits, on a pixel-by pixel basis, the presence of inter-band correlations for prediction. Furthermore, the proposed approach takes advantage of spatial correlations, and does not introduce any coding overhead to transmit the order of the spectral bands. This is accomplished by using the assumption that two spatially adjacent pixels are expected to have similar spectral relationships. We thus have a simple technique to exploit spectral and spatial correlations in hyper-spectral data sets, leading to compression performance improvements as compared to our previously reported techniques for lossless compression. We also look at some simple error modeling techniques for further exploiting any structure that remains in the prediction residuals prior to entropy coding.
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Spatial Correlations in Natural Scenes Modulate Response Reliability in Mouse Visual Cortex
Rikhye, Rajeev V.
2015-01-01
Intrinsic neuronal variability significantly limits information encoding in the primary visual cortex (V1). Certain stimuli can suppress this intertrial variability to increase the reliability of neuronal responses. In particular, responses to natural scenes, which have broadband spatiotemporal statistics, are more reliable than responses to stimuli such as gratings. However, very little is known about which stimulus statistics modulate reliable coding and how this occurs at the neural ensemble level. Here, we sought to elucidate the role that spatial correlations in natural scenes play in reliable coding. We developed a novel noise-masking method to systematically alter spatial correlations in natural movies, without altering their edge structure. Using high-speed two-photon calcium imaging in vivo, we found that responses in mouse V1 were much less reliable at both the single neuron and population level when spatial correlations were removed from the image. This change in reliability was due to a reorganization of between-neuron correlations. Strongly correlated neurons formed ensembles that reliably and accurately encoded visual stimuli, whereas reducing spatial correlations reduced the activation of these ensembles, leading to an unreliable code. Together with an ensemble-specific normalization model, these results suggest that the coordinated activation of specific subsets of neurons underlies the reliable coding of natural scenes. SIGNIFICANCE STATEMENT The natural environment is rich with information. To process this information with high fidelity, V1 neurons have to be robust to noise and, consequentially, must generate responses that are reliable from trial to trial. While several studies have hinted that both stimulus attributes and population coding may reduce noise, the details remain unclear. Specifically, what features of natural scenes are important and how do they modulate reliability? This study is the first to investigate the role of spatial correlations, which are a fundamental attribute of natural scenes, in shaping stimulus coding by V1 neurons. Our results provide new insights into how stimulus spatial correlations reorganize the correlated activation of specific ensembles of neurons to ensure accurate information processing in V1. PMID:26511254
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Zhang, Guojin; Senak, Laurence; Moore, David J
2011-05-01
Spatially resolved infrared (IR) and Raman images are acquired from human hair cross sections or intact hair fibers. The full informational content of these spectra are spatially correlated to hair chemistry, anatomy, and structural organization through univariate and multivariate data analysis. Specific IR and Raman images from untreated human hair describing the spatial dependence of lipid and protein distribution, protein secondary structure, lipid chain conformational order, and distribution of disulfide cross-links in hair protein are presented in this study. Factor analysis of the image plane acquired with IR microscopy in hair sections, permits delineation of specific micro-regions within the hair. These data indicate that both IR and Raman imaging of molecular structural changes in a specific region of hair will prove to be valuable tools in the understanding of hair structure, physiology, and the effect of various stresses upon its integrity.
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Kalkhan, M.A.; Stohlgren, T.J.
2000-01-01
Land managers need better techniques to assess exoticplant invasions. We used the cross-correlationstatistic, IYZ, to test for the presence ofspatial cross-correlation between pair-wisecombinations of soil characteristics, topographicvariables, plant species richness, and cover ofvascular plants in a 754 ha study site in RockyMountain National Park, Colorado, U.S.A. Using 25 largeplots (1000 m2) in five vegetation types, 8 of 12variables showed significant spatial cross-correlationwith at least one other variable, while 6 of 12variables showed significant spatial auto-correlation. Elevation and slope showed significant spatialcross-correlation with all variables except percentcover of native and exotic species. Percent cover ofnative species had significant spatialcross-correlations with soil variables, but not withexotic species. This was probably because of thepatchy distributions of vegetation types in the studyarea. At a finer resolution, using data from ten1 m2 subplots within each of the 1000 m2 plots, allvariables showed significant spatial auto- andcross-correlation. Large-plot sampling was moreaffected by topographic factors than speciesdistribution patterns, while with finer resolutionsampling, the opposite was true. However, thestatistically and biologically significant spatialcorrelation of native and exotic species could only bedetected with finer resolution sampling. We foundexotic plant species invading areas with high nativeplant richness and cover, and in fertile soils high innitrogen, silt, and clay. Spatial auto- andcross-correlation statistics, along with theintegration of remotely sensed data and geographicinformation systems, are powerful new tools forevaluating the patterns and distribution of native andexotic plant species in relation to landscape structure.
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Intermittency, nonlinear dynamics and dissipation in the solar wind and astrophysical plasmas
Matthaeus, W. H.; Wan, Minping; Servidio, S.; Greco, A.; Osman, K. T.; Oughton, S.; Dmitruk, P.
2015-01-01
An overview is given of important properties of spatial and temporal intermittency, including evidence of its appearance in fluids, magnetofluids and plasmas, and its implications for understanding of heliospheric plasmas. Spatial intermittency is generally associated with formation of sharp gradients and coherent structures. The basic physics of structure generation is ideal, but when dissipation is present it is usually concentrated in regions of strong gradients. This essential feature of spatial intermittency in fluids has been shown recently to carry over to the realm of kinetic plasma, where the dissipation function is not known from first principles. Spatial structures produced in intermittent plasma influence dissipation, heating, and transport and acceleration of charged particles. Temporal intermittency can give rise to very long time correlations or a delayed approach to steady-state conditions, and has been associated with inverse cascade or quasi-inverse cascade systems, with possible implications for heliospheric prediction. PMID:25848085
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Submarine slope failures due to pipe structure formation.
Elger, Judith; Berndt, Christian; Rüpke, Lars; Krastel, Sebastian; Gross, Felix; Geissler, Wolfram H
2018-02-19
There is a strong spatial correlation between submarine slope failures and the occurrence of gas hydrates. This has been attributed to the dynamic nature of gas hydrate systems and the potential reduction of slope stability due to bottom water warming or sea level drop. However, 30 years of research into this process found no solid supporting evidence. Here we present new reflection seismic data from the Arctic Ocean and numerical modelling results supporting a different link between hydrates and slope stability. Hydrates reduce sediment permeability and cause build-up of overpressure at the base of the gas hydrate stability zone. Resulting hydro-fracturing forms pipe structures as pathways for overpressured fluids to migrate upward. Where these pipe structures reach shallow permeable beds, this overpressure transfers laterally and destabilises the slope. This process reconciles the spatial correlation of submarine landslides and gas hydrate, and it is independent of environmental change and water depth.
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Statistics of natural scenes and cortical color processing.
Cecchi, Guillermo A; Rao, A Ravishankar; Xiao, Youping; Kaplan, Ehud
2010-09-01
We investigate the spatial correlations of orientation and color information in natural images. We find that the correlation of orientation information falls off rapidly with increasing distance, while color information is more highly correlated over longer distances. We show that orientation and color information are statistically independent in natural images and that the spatial correlation of jointly encoded orientation and color information decays faster than that of color alone. Our findings suggest that: (a) orientation and color information should be processed in separate channels and (b) the organization of cortical color and orientation selectivity at low spatial frequencies is a reflection of the cortical adaptation to the statistical structure of the visual world. These findings are in agreement with biological observations, as form and color are thought to be represented by different classes of neurons in the primary visual cortex, and the receptive fields of color-selective neurons are larger than those of orientation-selective neurons. The agreement between our findings and biological observations supports the ecological theory of perception.
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NASA Astrophysics Data System (ADS)
Chowdhry, Bhawani Shankar; White, Neil M.; Jeswani, Jai Kumar; Dayo, Khalil; Rathi, Manorma
2009-07-01
Disasters affecting infrastructure, such as the 2001 earthquakes in India, 2005 in Pakistan, 2008 in China and the 2004 tsunami in Asia, provide a common need for intelligent buildings and smart civil structures. Now, imagine massive reductions in time to get the infrastructure working again, realtime information on damage to buildings, massive reductions in cost and time to certify that structures are undamaged and can still be operated, reductions in the number of structures to be rebuilt (if they are known not to be damaged). Achieving these ideas would lead to huge, quantifiable, long-term savings to government and industry. Wireless sensor networks (WSNs) can be deployed in buildings to make any civil structure both smart and intelligent. WSNs have recently gained much attention in both public and research communities because they are expected to bring a new paradigm to the interaction between humans, environment, and machines. This paper presents the deployment of WSN nodes in the Top Quality Centralized Instrumentation Centre (TQCIC). We created an ad hoc networking application to collect real-time data sensed from the nodes that were randomly distributed throughout the building. If the sensors are relocated, then the application automatically reconfigures itself in the light of the new routing topology. WSNs are event-based systems that rely on the collective effort of several micro-sensor nodes, which are continuously observing a physical phenomenon. WSN applications require spatially dense sensor deployment in order to achieve satisfactory coverage. The degree of spatial correlation increases with the decreasing inter-node separation. Energy consumption is reduced dramatically by having only those sensor nodes with unique readings transmit their data. We report on an algorithm based on a spatial correlation technique that assures high QoS (in terms of SNR) of the network as well as proper utilization of energy, by suppressing redundant data transmission. The visualization and analysis of WSN data are presented in a Windows-based user interface.
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Temporal evolution of the spatial covariability of rainfall in South America
NASA Astrophysics Data System (ADS)
Ciemer, Catrin; Boers, Niklas; Barbosa, Henrique M. J.; Kurths, Jürgen; Rammig, Anja
2017-10-01
The climate of South America exhibits pronounced differences between rainy and dry seasons, associated with specific synoptic features such as the establishment of the South Atlantic convergence zone. Here, we analyze the spatiotemporal correlation structure and in particular teleconnections of daily rainfall associated with these features by means of evolving complex networks. A modification of Pearson's correlation coefficient is introduced to handle the intricate statistical properties of daily rainfall. On this basis, spatial correlation networks are constructed, and new appropriate network measures are introduced in order to analyze the temporal evolution of the networks' characteristics. We particularly focus on the identification of coherent areas of similar rainfall patterns and previously unknown teleconnection structures between remote areas. We show that the monsoon onset is characterized by an abrupt transition from erratic to organized regional connectivity that prevails during the monsoon season, while only the onset times themselves exhibit anomalous large-scale organization of teleconnections. Furthermore, we reveal that the two mega-droughts in the Amazon basin were already announced in the previous year by an anomalous behavior of the connectivity structure.
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Spatio-temporal correlations in the Manna model in one, three and five dimensions
NASA Astrophysics Data System (ADS)
Willis, Gary; Pruessner, Gunnar
2018-02-01
Although the paradigm of criticality is centered around spatial correlations and their anomalous scaling, not many studies of self-organized criticality (SOC) focus on spatial correlations. Often, integrated observables, such as avalanche size and duration, are used, not least as to avoid complications due to the unavoidable lack of translational invariance. The present work is a survey of spatio-temporal correlation functions in the Manna Model of SOC, measured numerically in detail in d = 1,3 and 5 dimensions and compared to theoretical results, in particular relating them to “integrated” observables such as avalanche size and duration scaling, that measure them indirectly. Contrary to the notion held by some of SOC models organizing into a critical state by re-arranging their spatial structure avalanche by avalanche, which may be expected to result in large, nontrivial, system-spanning spatial correlations in the quiescent state (between avalanches), correlations of inactive particles in the quiescent state have a small amplitude that does not and cannot increase with the system size, although they display (noisy) power law scaling over a range linear in the system size. Self-organization, however, does take place as the (one-point) density of inactive particles organizes into a particular profile that is asymptotically independent of the driving location, also demonstrated analytically in one dimension. Activity and its correlations, on the other hand, display nontrivial long-ranged spatio-temporal scaling with exponents that can be related to established results, in particular avalanche size and duration exponents. The correlation length and amplitude are set by the system size (confirmed analytically for some observables), as expected in systems displaying finite size scaling. In one dimension, we find some surprising inconsistencies of the dynamical exponent. A (spatially extended) mean field theory (MFT) is recovered, with some corrections, in five dimensions.
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Gothe, Emma; Sandin, Leonard; Allen, Craig R.; Angeler, David G.
2014-01-01
The distribution of functional traits within and across spatiotemporal scales has been used to quantify and infer the relative resilience across ecosystems. We use explicit spatial modeling to evaluate within- and cross-scale redundancy in headwater streams, an ecosystem type with a hierarchical and dendritic network structure. We assessed the cross-scale distribution of functional feeding groups of benthic invertebrates in Swedish headwater streams during two seasons. We evaluated functional metrics, i.e., Shannon diversity, richness, and evenness, and the degree of redundancy within and across modeled spatial scales for individual feeding groups. We also estimated the correlates of environmental versus spatial factors of both functional composition and the taxonomic composition of functional groups for each spatial scale identified. Measures of functional diversity and within-scale redundancy of functions were similar during both seasons, but both within- and cross-scale redundancy were low. This apparent low redundancy was partly attributable to a few dominant taxa explaining the spatial models. However, rare taxa with stochastic spatial distributions might provide additional information and should therefore be considered explicitly for complementing future resilience assessments. Otherwise, resilience may be underestimated. Finally, both environmental and spatial factors correlated with the scale-specific functional and taxonomic composition. This finding suggests that resilience in stream networks emerges as a function of not only local conditions but also regional factors such as habitat connectivity and invertebrate dispersal.
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Damage evolution analysis of coal samples under cyclic loading based on single-link cluster method
NASA Astrophysics Data System (ADS)
Zhang, Zhibo; Wang, Enyuan; Li, Nan; Li, Xuelong; Wang, Xiaoran; Li, Zhonghui
2018-05-01
In this paper, the acoustic emission (AE) response of coal samples under cyclic loading is measured. The results show that there is good positive relation between AE parameters and stress. The AE signal of coal samples under cyclic loading exhibits an obvious Kaiser Effect. The single-link cluster (SLC) method is applied to analyze the spatial evolution characteristics of AE events and the damage evolution process of coal samples. It is found that a subset scale of the SLC structure becomes smaller and smaller when the number of cyclic loading increases, and there is a negative linear relationship between the subset scale and the degree of damage. The spatial correlation length ξ of an SLC structure is calculated. The results show that ξ fluctuates around a certain value from the second cyclic loading process to the fifth cyclic loading process, but spatial correlation length ξ clearly increases in the sixth loading process. Based on the criterion of microcrack density, the coal sample failure process is the transformation from small-scale damage to large-scale damage, which is the reason for changes in the spatial correlation length. Through a systematic analysis, the SLC method is an effective method to research the damage evolution process of coal samples under cyclic loading, and will provide important reference values for studying coal bursts.
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Scales of snow depth variability in high elevation rangeland sagebrush
NASA Astrophysics Data System (ADS)
Tedesche, Molly E.; Fassnacht, Steven R.; Meiman, Paul J.
2017-09-01
In high elevation semi-arid rangelands, sagebrush and other shrubs can affect transport and deposition of wind-blown snow, enabling the formation of snowdrifts. Datasets from three field experiments were used to investigate the scales of spatial variability of snow depth around big mountain sagebrush ( Artemisia tridentata Nutt.) at a high elevation plateau rangeland in North Park, Colorado, during the winters of 2002, 2003, and 2008. Data were collected at multiple resolutions (0.05 to 25 m) and extents (2 to 1000 m). Finer scale data were collected specifically for this study to examine the correlation between snow depth, sagebrush microtopography, the ground surface, and the snow surface, as well as the temporal consistency of snow depth patterns. Variograms were used to identify the spatial structure and the Moran's I statistic was used to determine the spatial correlation. Results show some temporal consistency in snow depth at several scales. Plot scale snow depth variability is partly a function of the nature of individual shrubs, as there is some correlation between the spatial structure of snow depth and sagebrush, as well as between the ground and snow depth. The optimal sampling resolution appears to be 25-cm, but over a large area, this would require a multitude of samples, and thus a random stratified approach is recommended with a fine measurement resolution of 5-cm.
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Habyarimana, Faustin; Zewotir, Temesgen; Ramroop, Shaun
2018-03-01
The main objective of this study was to assess the risk factors and spatial correlates of domestic violence against women of reproductive age in Rwanda. A structured spatial approach was used to account for the nonlinear nature of some covariates and the spatial variability on domestic violence. The nonlinear effect was modeled through second-order random walk, and the structured spatial effect was modeled through Gaussian Markov Random Fields specified as an intrinsic conditional autoregressive model. The data from the Rwanda Demographic and Health Survey 2014/2015 were used as an application. The findings of this study revealed that the risk factors of domestic violence against women are the wealth quintile of the household, the size of the household, the husband or partner's age, the husband or partner's level of education, ownership of the house, polygamy, the alcohol consumption status of the husband or partner, the woman's perception of wife-beating attitude, and the use of contraceptive methods. The study also highlighted the significant spatial variation of domestic violence against women at district level.
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Modi, Mehrab N; Dhawale, Ashesh K; Bhalla, Upinder S
2014-01-01
Animals can learn causal relationships between pairs of stimuli separated in time and this ability depends on the hippocampus. Such learning is believed to emerge from alterations in network connectivity, but large-scale connectivity is difficult to measure directly, especially during learning. Here, we show that area CA1 cells converge to time-locked firing sequences that bridge the two stimuli paired during training, and this phenomenon is coupled to a reorganization of network correlations. Using two-photon calcium imaging of mouse hippocampal neurons we find that co-time-tuned neurons exhibit enhanced spontaneous activity correlations that increase just prior to learning. While time-tuned cells are not spatially organized, spontaneously correlated cells do fall into distinct spatial clusters that change as a result of learning. We propose that the spatial re-organization of correlation clusters reflects global network connectivity changes that are responsible for the emergence of the sequentially-timed activity of cell-groups underlying the learned behavior. DOI: http://dx.doi.org/10.7554/eLife.01982.001 PMID:24668171
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NASA Astrophysics Data System (ADS)
Huang, D.; Wang, G.
2014-12-01
Stochastic simulation of spatially distributed ground-motion time histories is important for performance-based earthquake design of geographically distributed systems. In this study, we develop a novel technique to stochastically simulate regionalized ground-motion time histories using wavelet packet analysis. First, a transient acceleration time history is characterized by wavelet-packet parameters proposed by Yamamoto and Baker (2013). The wavelet-packet parameters fully characterize ground-motion time histories in terms of energy content, time- frequency-domain characteristics and time-frequency nonstationarity. This study further investigates the spatial cross-correlations of wavelet-packet parameters based on geostatistical analysis of 1500 regionalized ground motion data from eight well-recorded earthquakes in California, Mexico, Japan and Taiwan. The linear model of coregionalization (LMC) is used to develop a permissible spatial cross-correlation model for each parameter group. The geostatistical analysis of ground-motion data from different regions reveals significant dependence of the LMC structure on regional site conditions, which can be characterized by the correlation range of Vs30 in each region. In general, the spatial correlation and cross-correlation of wavelet-packet parameters are stronger if the site condition is more homogeneous. Using the regional-specific spatial cross-correlation model and cokriging technique, wavelet packet parameters at unmeasured locations can be best estimated, and regionalized ground-motion time histories can be synthesized. Case studies and blind tests demonstrated that the simulated ground motions generally agree well with the actual recorded data, if the influence of regional-site conditions is considered. The developed method has great potential to be used in computational-based seismic analysis and loss estimation in a regional scale.
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NASA Astrophysics Data System (ADS)
Li, Shi-Yao; She, Zhen-Su; Chen, Jun
2017-11-01
A velocity-vorticity correlation structure (VVCS) analysis is applied to the direct numerical simulation (DNS) of compressible turbulent boundary layer (CTBL) at Mach numbers, Ma = 2.25 , 4.50 and 6.0 . It is shown that the VVCS analysis captures the geometry variation in the streamwise direction during the transition and in the wall-normal direction in the fully developed regime. Specifically, before transition, the VVCS captures the instability wave number, while in the transition region it displays a distinct scaling change of the dimensions. The fully developed turbulence regime is characterized by a nearly constant spatial extension of the VVCS. Particularly, after turbulence is well developed, a multi-layer structure in the wall normal direction is observed in the maximum correlation coefficient and in the length scales of the VVCS, as expected from a recent symmetry-based theory, the ensemble structure dynamics (SED). The most interesting outcome is an observed linear dependence of the length scale of the VVCS from y+ 50 to 200, which is a direct support to Townsend's attached-eddy theory. In conclusion, the VVCS analysis quantifies the geometrical characteristics of the coherent structures in turbulent compressible shear flows throughout the whole domain. Supported by NSFC (11172006, 11221062, 11452002) and by MOST (China) 973 project (2009CB724100).
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Gundogdu, Erhan; Ozkan, Huseyin; Alatan, A Aydin
2017-11-01
Correlation filters have been successfully used in visual tracking due to their modeling power and computational efficiency. However, the state-of-the-art correlation filter-based (CFB) tracking algorithms tend to quickly discard the previous poses of the target, since they consider only a single filter in their models. On the contrary, our approach is to register multiple CFB trackers for previous poses and exploit the registered knowledge when an appearance change occurs. To this end, we propose a novel tracking algorithm [of complexity O(D) ] based on a large ensemble of CFB trackers. The ensemble [of size O(2 D ) ] is organized over a binary tree (depth D ), and learns the target appearance subspaces such that each constituent tracker becomes an expert of a certain appearance. During tracking, the proposed algorithm combines only the appearance-aware relevant experts to produce boosted tracking decisions. Additionally, we propose a versatile spatial windowing technique to enhance the individual expert trackers. For this purpose, spatial windows are learned for target objects as well as the correlation filters and then the windowed regions are processed for more robust correlations. In our extensive experiments on benchmark datasets, we achieve a substantial performance increase by using the proposed tracking algorithm together with the spatial windowing.
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Building Complex Kondo Impurities by Manipulating Entangled Spin Chains.
Choi, Deung-Jang; Robles, Roberto; Yan, Shichao; Burgess, Jacob A J; Rolf-Pissarczyk, Steffen; Gauyacq, Jean-Pierre; Lorente, Nicolás; Ternes, Markus; Loth, Sebastian
2017-10-11
The creation of molecule-like structures in which magnetic atoms interact controllably is full of potential for the study of complex or strongly correlated systems. Here, we create spin chains in which a strongly correlated Kondo state emerges from magnetic coupling of transition-metal atoms. We build chains up to ten atoms in length by placing Fe and Mn atoms on a Cu 2 N surface with a scanning tunneling microscope. The atoms couple antiferromagnetically via superexchange interaction through the nitrogen atom network of the surface. The emergent Kondo resonance is spatially distributed along the chain. Its strength can be controlled by mixing atoms of different transition metal elements and manipulating their spatial distribution. We show that the Kondo screening of the full chain by the electrons of the nonmagnetic substrate depends on the interatomic entanglement of the spins in the chain, demonstrating the prerequisites to build and probe spatially extended strongly correlated nanostructures.
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Kumar, Dushyant; Hariharan, Hari; Faizy, Tobias D; Borchert, Patrick; Siemonsen, Susanne; Fiehler, Jens; Reddy, Ravinder; Sedlacik, Jan
2018-05-12
We present a computationally feasible and iterative multi-voxel spatially regularized algorithm for myelin water fraction (MWF) reconstruction. This method utilizes 3D spatial correlations present in anatomical/pathological tissues and underlying B1 + -inhomogeneity or flip angle inhomogeneity to enhance the noise robustness of the reconstruction while intrinsically accounting for stimulated echo contributions using T2-distribution data alone. Simulated data and in vivo data acquired using 3D non-selective multi-echo spin echo (3DNS-MESE) were used to compare the reconstruction quality of the proposed approach against those of the popular algorithm (the method by Prasloski et al.) and our previously proposed 2D multi-slice spatial regularization spatial regularization approach. We also investigated whether the inter-sequence correlations and agreements improved as a result of the proposed approach. MWF-quantifications from two sequences, 3DNS-MESE vs 3DNS-gradient and spin echo (3DNS-GRASE), were compared for both reconstruction approaches to assess correlations and agreements between inter-sequence MWF-value pairs. MWF values from whole-brain data of six volunteers and two multiple sclerosis patients are being reported as well. In comparison with competing approaches such as Prasloski's method or our previously proposed 2D multi-slice spatial regularization method, the proposed method showed better agreements with simulated truths using regression analyses and Bland-Altman analyses. For 3DNS-MESE data, MWF-maps reconstructed using the proposed algorithm provided better depictions of white matter structures in subcortical areas adjoining gray matter which agreed more closely with corresponding contrasts on T2-weighted images than MWF-maps reconstructed with the method by Prasloski et al. We also achieved a higher level of correlations and agreements between inter-sequence (3DNS-MESE vs 3DNS-GRASE) MWF-value pairs. The proposed algorithm provides more noise-robust fits to T2-decay data and improves MWF-quantifications in white matter structures especially in the sub-cortical white matter and major white matter tract regions. Copyright © 2018 Elsevier Inc. All rights reserved.
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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.
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Zhang, Rong; Leng, Yun-fa; Zhu, Meng-meng; Wang, Fang
2007-11-01
Based on geographic information system and geostatistics, the spatial structure of Therioaphis trifolii population of different periods in Yuanzhou district of Guyuan City, the southern Ningxia Province, was analyzed. The spatial distribution of Therioaphis trifolii population was also simulated by ordinary Kriging interpretation. The results showed that Therioaphis trifolii population of different periods was correlated spatially in the study area. The semivariograms of Therioaphis trifolii could be described by exponential model, indicating an aggregated spatial arrangement. The spatial variance varied from 34.13%-48.77%, and the range varied from 8.751-12.049 km. The degree and direction of aggregation showed that the trend was increased gradually from southwest to northeast. The dynamic change of Therioaphis trifolii population in different periods could be analyzed intuitively on the simulated maps of the spatial distribution from the two aspects of time and space, The occurrence position and degree of Therioaphis trifolii to a state of certain time could be determined easily.
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NASA Astrophysics Data System (ADS)
Darcel, C.; Davy, P.; Le Goc, R.; Maillot, J.; Selroos, J. O.
2017-12-01
We present progress on Discrete Fracture Network (DFN) flow modeling, including realistic advanced DFN spatial structures and local fracture transmissivity properties, through an application to the Forsmark site in Sweden. DFN models are a framework to combine fracture datasets from different sources and scales and to interpolate them in combining statistical distributions and stereological relations. The resulting DFN upscaling function - size density distribution - is a model component key to extrapolating fracture size densities between data gaps, from borehole core up to site scale. Another important feature of DFN models lays in the spatial correlations between fractures, with still unevaluated consequences on flow predictions. Indeed, although common Poisson (i.e. spatially random) models are widely used, they do not reflect these geological evidences for more complex structures. To model them, we define a DFN growth process from kinematic rules for nucleation, growth and stopping conditions. It mimics in a simplified way the geological fracturing processes and produces DFN characteristics -both upscaling function and spatial correlations- fully consistent with field observations. DFN structures are first compared for constant transmissivities. Flow simulations for the kinematic and equivalent Poisson DFN models show striking differences: with the kinematic DFN, connectivity and permeability are significantly smaller, down to a difference of one order of magnitude, and flow is much more channelized. Further flow analyses are performed with more realistic transmissivity distribution conditions (sealed parts, relations to fracture sizes, orientations and in-situ stress field). The relative importance of the overall DFN structure in the final flow predictions is discussed.
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Shakeshaft, Nicholas G.; Rimfeld, Kaili; Schofield, Kerry L.; Selzam, Saskia; Malanchini, Margherita; Rodic, Maja; Kovas, Yulia; Plomin, Robert
2016-01-01
Spatial abilities–defined broadly as the capacity to manipulate mental representations of objects and the relations between them–have been studied widely, but with little agreement reached concerning their nature or structure. Two major putative spatial abilities are “mental rotation” (rotating mental models) and “visualisation” (complex manipulations, such as identifying objects from incomplete information), but inconsistent findings have been presented regarding their relationship to one another. Similarly inconsistent findings have been reported for the relationship between two- and three-dimensional stimuli. Behavioural genetic methods offer a largely untapped means to investigate such relationships. 1,265 twin pairs from the Twins Early Development Study completed the novel “Bricks” test battery, designed to tap these abilities in isolation. The results suggest substantial genetic influence unique to spatial ability as a whole, but indicate that dissociations between the more specific constructs (rotation and visualisation, in 2D and 3D) disappear when tested under identical conditions: they are highly correlated phenotypically, perfectly correlated genetically (indicating that the same genetic influences underpin performance), and are related similarly to other abilities. This has important implications for the structure of spatial ability, suggesting that the proliferation of apparent sub-domains may sometimes reflect idiosyncratic tasks rather than meaningful dissociations. PMID:27476554
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Wang, Y.S.; Miller, D.R.; Anderson, D.E.; Cionco, R.M.; Lin, J.D.
1992-01-01
Turbulent flow within and above an almond orchard was measured with three-dimensional wind sensors and fine-wire thermocouple sensors arranged in a horizontal array. The data showed organized turbulent structures as indicated by coherent asymmetric ramp patterns in the time series traces across the sensor array. Space-time correlation analysis indicated that velocity and temperature fluctuations were significantly correlated over a transverse distance more than 4m. Integral length scales of velocity and temperature fluctuations were substantially greater in unstable conditions than those in stable conditions. The coherence spectral analysis indicated that Davenport's geometric similarity hypothesis was satisfied in the lower frequency region. From the geometric similarity hypothesis, the spatial extents of large ramp structures were also estimated with the coherence functions.
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The spectral signature of cloud spatial structure in shortwave irradiance
Song, Shi; Schmidt, K. Sebastian; Pilewskie, Peter; King, Michael D.; Heidinger, Andrew K.; Walther, Andi; Iwabuchi, Hironobu; Wind, Gala; Coddington, Odele M.
2017-01-01
In this paper, we used cloud imagery from a NASA field experiment in conjunction with three-dimensional radiative transfer calculations to show that cloud spatial structure manifests itself as a spectral signature in shortwave irradiance fields – specifically in transmittance and net horizontal photon transport in the visible and near-ultraviolet wavelength range. We found a robust correlation between the magnitude of net horizontal photon transport (H) and its spectral dependence (slope), which is scale-invariant and holds for the entire pixel population of a domain. This was surprising at first given the large degree of spatial inhomogeneity. We prove that the underlying physical mechanism for this phenomenon is molecular scattering in conjunction with cloud spatial structure. On this basis, we developed a simple parameterization through a single parameter ε, which quantifies the characteristic spectral signature of spatial inhomogeneities. In the case we studied, neglecting net horizontal photon transport leads to a local transmittance bias of ±12–19 %, even at the relatively coarse spatial resolution of 20 km. Since three-dimensional effects depend on the spatial context of a given pixel in a nontrivial way, the spectral dimension of this problem may emerge as the starting point for future bias corrections. PMID:28824698
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The spectral signature of cloud spatial structure in shortwave irradiance.
Song, Shi; Schmidt, K Sebastian; Pilewskie, Peter; King, Michael D; Heidinger, Andrew K; Walther, Andi; Iwabuchi, Hironobu; Wind, Gala; Coddington, Odele M
2016-11-08
In this paper, we used cloud imagery from a NASA field experiment in conjunction with three-dimensional radiative transfer calculations to show that cloud spatial structure manifests itself as a spectral signature in shortwave irradiance fields - specifically in transmittance and net horizontal photon transport in the visible and near-ultraviolet wavelength range. We found a robust correlation between the magnitude of net horizontal photon transport ( H ) and its spectral dependence (slope), which is scale-invariant and holds for the entire pixel population of a domain. This was surprising at first given the large degree of spatial inhomogeneity. We prove that the underlying physical mechanism for this phenomenon is molecular scattering in conjunction with cloud spatial structure. On this basis, we developed a simple parameterization through a single parameter ε , which quantifies the characteristic spectral signature of spatial inhomogeneities. In the case we studied, neglecting net horizontal photon transport leads to a local transmittance bias of ±12-19 %, even at the relatively coarse spatial resolution of 20 km. Since three-dimensional effects depend on the spatial context of a given pixel in a nontrivial way, the spectral dimension of this problem may emerge as the starting point for future bias corrections.
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Zagrebelsky, Marta; Lonnemann, Niklas; Fricke, Steffen; Kellner, Yves; Preuß, Eike; Michaelsen-Preusse, Kristin; Korte, Martin
2017-02-01
Behavioral learning has been shown to involve changes in the function and structure of synaptic connections of the central nervous system (CNS). On the other hand, the neuronal circuitry in the mature brain is characterized by a high degree of stability possibly providing a correlate for long-term storage of information. This observation indicates the requirement for a set of molecules inhibiting plasticity and promoting stability thereby providing temporal and spatial specificity to plastic processes. Indeed, signaling of Nogo-A via its receptors has been shown to play a crucial role in restricting activity-dependent functional and structural plasticity in the adult CNS. However, whether Nogo-A controls learning and memory formation and what are the cellular and molecular mechanisms underlying this function is still unclear. Here we show that Nogo-A signaling controls spatial learning and reference memory formation upon training in the Morris water maze and negatively modulates structural changes at spines in the mouse hippocampus. Learning processes and the correlated structural plasticity have been shown to involve changes in excitatory as well as in inhibitory neuronal connections. We show here that Nogo-A is highly expressed not only in excitatory, but also in inhibitory, Parvalbumin positive neurons in the adult hippocampus. By this means our current and previous data indicate that Nogo-A loss-of-function positively influences spatial learning by priming the neuronal structure to a higher plasticity level. Taken together our results link the role of Nogo-A in negatively regulating plastic processes to a physiological function in controlling learning and memory processes in the mature hippocampus and open the interesting possibility that it might mainly act by controlling the function of the hippocampal inhibitory circuitry. Copyright © 2016 Elsevier Inc. All rights reserved.
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Geography of Genetic Structure in Barley Wild Relative Hordeum vulgare subsp. spontaneum in Jordan.
Thormann, Imke; Reeves, Patrick; Reilley, Ann; Engels, Johannes M M; Lohwasser, Ulrike; Börner, Andreas; Pillen, Klaus; Richards, Christopher M
2016-01-01
Informed collecting, conservation, monitoring and utilization of genetic diversity requires knowledge of the distribution and structure of the variation occurring in a species. Hordeum vulgare subsp. spontaneum (K. Koch) Thell., a primary wild relative of barley, is an important source of genetic diversity for barley improvement and co-occurs with the domesticate within the center of origin. We studied the current distribution of genetic diversity and population structure in H. vulgare subsp. spontaneum in Jordan and investigated whether it is correlated with either spatial or climatic variation inferred from publically available climate layers commonly used in conservation and ecogeographical studies. The genetic structure of 32 populations collected in 2012 was analyzed with 37 SSRs. Three distinct genetic clusters were identified. Populations were characterized by admixture and high allelic richness, and genetic diversity was concentrated in the northern part of the study area. Genetic structure, spatial location and climate were not correlated. This may point out a limitation in using large scale climatic data layers to predict genetic diversity, especially as it is applied to regional genetic resources collections in H. vulgare subsp. spontaneum.
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Geography of Genetic Structure in Barley Wild Relative Hordeum vulgare subsp. spontaneum in Jordan
Reeves, Patrick; Reilley, Ann; Engels, Johannes M. M.; Lohwasser, Ulrike; Börner, Andreas; Pillen, Klaus; Richards, Christopher M.
2016-01-01
Informed collecting, conservation, monitoring and utilization of genetic diversity requires knowledge of the distribution and structure of the variation occurring in a species. Hordeum vulgare subsp. spontaneum (K. Koch) Thell., a primary wild relative of barley, is an important source of genetic diversity for barley improvement and co-occurs with the domesticate within the center of origin. We studied the current distribution of genetic diversity and population structure in H. vulgare subsp. spontaneum in Jordan and investigated whether it is correlated with either spatial or climatic variation inferred from publically available climate layers commonly used in conservation and ecogeographical studies. The genetic structure of 32 populations collected in 2012 was analyzed with 37 SSRs. Three distinct genetic clusters were identified. Populations were characterized by admixture and high allelic richness, and genetic diversity was concentrated in the northern part of the study area. Genetic structure, spatial location and climate were not correlated. This may point out a limitation in using large scale climatic data layers to predict genetic diversity, especially as it is applied to regional genetic resources collections in H. vulgare subsp. spontaneum. PMID:27513459
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Shui, Wei; DU, Yong; Chen, Yi Ping; Jian, Xiao Mei; Fan, Bing Xiong
2017-04-18
Anxi County, specializing in tea cultivation, was taken as a case in this research. Pearson correlation analysis, ordinary least squares model (OLS) and geographically weighted regression model (GWR) were used to select four primary influence factors of specialization in tea cultivation (i.e., the average elevation, net income per capita, proportion of agricultural population, and the distance from roads) by analyzing the specialization degree of each town of Anxi County. Meanwhile, the spatial patterns of specialization in tea cultivation of Anxi County were evaluated. The results indicated that specialization in tea cultivation of Anxi County showed an obvious spatial auto-correlation, and a spatial pattern with "low-middle-high" circle structure, which was similar to Von Thünen's circle structure model, appeared from the county town to its surrounding region. Meanwhile, GWR (0.624) had a better fitting degree than OLS (0.595), and GWR could reasonably expound the spatial data. Contrary to the agricultural location theory of Von Thünen's model, which indicated that distance from market was a determination factor, the specialization degree of tea cultivation in Anxi was mainly decided by natural conditions of mountain area, instead of the social factors. Specialization degree of tea cultivation was positively correlated with the average elevation, net income per capita and the proportion of agricultural population, while a negative correlation was found between the distance from roads and specialization degree of tea cultivation. Coefficients of regression between the specialization degree of tea cultivation and two factors (i.e., the average elevation and net income per capita) showed a spatial pattern of higher level in the north direction and lower level in the south direction. On the contrary, the regression coefficients for the proportion of agricultural population increased from south to north of Anxi County. Furthermore, regression coefficient for the distance from roads showed a spatial pattern of higher level in the northeast direction and lower level in the southwest direction of Anxi County.
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Environmental and Spatial Influences on Biogeography and Community Structure of Benthic Diatoms
NASA Astrophysics Data System (ADS)
Plante, C.; Hill-Spanik, K.; Lowry, J.
2016-02-01
Several theoretical and practical reasons suggest that benthic microalgae could be useful bioindicators. For instance, an ideal indicator species or community would be associated with a given habitat due to local physical conditions or biotic interactions (i.e., `environmental filtering'), not due to dispersal limitation. Due to their small size, immense abundances, and reliance on passive dispersal, the popular notion about micro-organisms is that `Everything is everywhere, but, the environment selects' (Baas-Becking 1934). Although much recent research concerning planktonic bacteria and dispersal limitation has been conducted, very little in this regard is known about microeukaryotes, especially benthic microbes. The purpose of our study was to identify and compare spatial and environmental influences on benthic diatom community structure and biogeography. In summer 2015, sediment was sampled at various spatial scales from four barrier island beaches in South Carolina, USA, and high-throughput (Ion Torrent) DNA sequencing was used to characterize diatom assemblages. ANOSIM and principal coordinates analysis revealed that communities were statistically distinct on the four islands. Community dissimilarity was compared to both spatial distance and environmental differences to determine potential influences of these variables on community structure. We found that geographic distance had the strongest correlation with community similarity, with and without one anomalous location, while differences in temperature (air, water, and sediment), nutrients, organic matter, and turbidity also had significant but weaker relationships with community structure. Surprisingly, air temperature, which changes on very short time scales, appeared to be the environmental factor most strongly related to diatom species composition, potentially implicating some unmeasured variable (e.g., cloud cover). However, we also found that temperature and geographic distance were strongly correlated. Future research will expand the spatial scope of this preliminary study and employ techniques (partial Mantel tests) to control for co-variation among variables.
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Separate but Correlated: The Latent Structure of Space and Mathematics across Development
ERIC Educational Resources Information Center
Mix, Kelly S.; Levine, Susan C.; Cheng, Yi-Ling; Young, Chris; Hambrick, D. Zachary; Ping, Raedy
2016-01-01
The relations among various spatial and mathematics skills were assessed in a cross-sectional study of 854 children from kindergarten, third, and sixth grades (i.e., 5 to 13 years of age). Children completed a battery of spatial mathematics tests and their scores were submitted to exploratory factor analyses both within and across domains. In the…
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D. J. Isaak; R. F. Thurow; B. E. Rieman; J. B. Dunham
2003-01-01
Metapopulation dynamics have emerged as a key consideration in conservation planning for salmonid fishes. Implicit to many models of spatially structured populations is a degree of synchrony, or correlation, among populations. We used a spatially and temporally extensive database of chinook salmon (Oncorhynchus tshawytscha) redd counts from a wilderness area in central...
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NASA Astrophysics Data System (ADS)
Gill, G.; Sakrani, T.; Cheng, W.; Zhou, J.
2017-09-01
Many studies have utilized the spatial correlations among traffic crash data to develop crash prediction models with the aim to investigate the influential factors or predict crash counts at different sites. The spatial correlation have been observed to account for heterogeneity in different forms of weight matrices which improves the estimation performance of models. But very rarely have the weight matrices been compared for the prediction accuracy for estimation of crash counts. This study was targeted at the comparison of two different approaches for modelling the spatial correlations among crash data at macro-level (County). Multivariate Full Bayesian crash prediction models were developed using Decay-50 (distance-based) and Queen-1 (adjacency-based) weight matrices for simultaneous estimation crash counts of four different modes: vehicle, motorcycle, bike, and pedestrian. The goodness-of-fit and different criteria for accuracy at prediction of crash count reveled the superiority of Decay-50 over Queen-1. Decay-50 was essentially different from Queen-1 with the selection of neighbors and more robust spatial weight structure which rendered the flexibility to accommodate the spatially correlated crash data. The consistently better performance of Decay-50 at prediction accuracy further bolstered its superiority. Although the data collection efforts to gather centroid distance among counties for Decay-50 may appear to be a downside, but the model has a significant edge to fit the crash data without losing the simplicity of computation of estimated crash count.
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Guo, Qiang; Xu, Pengpeng; Pei, Xin; Wong, S C; Yao, Danya
2017-02-01
Pedestrian safety is increasingly recognized as a major public health concern. Extensive safety studies have been conducted to examine the influence of multiple variables on the occurrence of pedestrian-vehicle crashes. However, the explicit relationship between pedestrian safety and road network characteristics remains unknown. This study particularly focused on the role of different road network patterns on the occurrence of crashes involving pedestrians. A global integration index via space syntax was introduced to quantify the topological structures of road networks. The Bayesian Poisson-lognormal (PLN) models with conditional autoregressive (CAR) prior were then developed via three different proximity structures: contiguity, geometry-centroid distance, and road network connectivity. The models were also compared with the PLN counterpart without spatial correlation effects. The analysis was based on a comprehensive crash dataset from 131 selected traffic analysis zones in Hong Kong. The results indicated that higher global integration was associated with more pedestrian-vehicle crashes; the irregular pattern network was proved to be safest in terms of pedestrian crash occurrences, whereas the grid pattern was the least safe; the CAR model with a neighborhood structure based on road network connectivity was found to outperform in model goodness-of-fit, implying the importance of accurately accounting for spatial correlation when modeling spatially aggregated crash data. Copyright © 2016 Elsevier Ltd. All rights reserved.
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Simmonds, Benjamin; Chacron, Maurice J
2015-01-01
Correlations between the activities of neighboring neurons are observed ubiquitously across systems and species and are dynamically regulated by several factors such as the stimulus' spatiotemporal extent as well as by the brain's internal state. Using the electrosensory system of gymnotiform weakly electric fish, we recorded the activities of pyramidal cell pairs within the electrosensory lateral line lobe (ELL) under spatially localized and diffuse stimulation. We found that both signal and noise correlations were markedly reduced (>40%) under the latter stimulation. Through a network model incorporating key anatomical features of the ELL, we reveal how activation of diffuse parallel fiber feedback from granule cells by spatially diffuse stimulation can explain both the reduction in signal as well as the reduction in noise correlations seen experimentally through independent mechanisms. First, we show that burst-timing dependent plasticity, which leads to a negative image of the stimulus and thereby reduces single neuron responses, decreases signal but not noise correlations. Second, we show trial-to-trial variability in the responses of single granule cells to sensory input reduces noise but not signal correlations. Thus, our model predicts that the same feedback pathway can simultaneously reduce both signal and noise correlations through independent mechanisms. To test this prediction experimentally, we pharmacologically inactivated parallel fiber feedback onto ELL pyramidal cells. In agreement with modeling predictions, we found that inactivation increased both signal and noise correlations but that there was no significant relationship between magnitude of the increase in signal correlations and the magnitude of the increase in noise correlations. The mechanisms reported in this study are expected to be generally applicable to the cerebellum as well as other cerebellum-like structures. We further discuss the implications of such decorrelation on the neural coding strategies used by the electrosensory and by other systems to process natural stimuli.
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Hetzroni, Orit E; Shalahevich, Kiril
2018-03-01
Analogical reasoning was investigated among children with autism spectrum disorders (ASD) without intellectual disabilities and typical development (TD). Children were asked to select one of two targets in two conditions: (1) with and without spatial structure similarity; (2) with and without a perceptual distractor. Results demonstrate that children with ASD were able to select targets based on structural similarity, but this ability decreased to chance level when presented with a perceptual distractor. Everyday executive functions were positively correlated with structural selections among children with ASD. Results suggest that although children with ASD were able to select based on systematicity principle, perceptual distractor decreased their selection so that their cognitive system produced less structure similarities, that negatively affects spatial analogical reasoning.
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Suppression of the "Quasiclassical" proximity gap in correlated-metal--superconductor structures.
Nikolić, Branislav K; Freericks, J K; Miller, P
2002-02-18
We study the energy and spatial dependence of the local density of states in a superconductor--correlated-metal--superconductor Josephson junction, where the correlated metal is a non-Fermi liquid (described by the Falicov-Kimball model). Many-body correlations are treated with dynamical mean-field theory, extended to inhomogeneous systems. While quasiclassical theories predict a minigap in the spectrum of a disordered Fermi liquid which is proximity-coupled within a mesoscopic junction, we find that increasing electron correlations destroy any minigap that might be opened in the absence of many-body correlations.
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Evolution of spatial and temporal correlations in the solar wind - Observations and interpretation
NASA Technical Reports Server (NTRS)
Klein, L. W.; Matthaeus, W. H.; Roberts, D. A.; Goldstein, M. L.
1992-01-01
Observations of solar wind magnetic field spectra from 1-22 AU indicate a distinctive structure in frequency which evolves with increasing heliocentric distance. At 1 AU extremely low frequency correlations are associated with temporal variations at the solar period and its first few harmonics. For periods of l2-96 hours, a l/f distribution is observed, which we interpret as an aggregate of uncorrelated coronal structures which have not dynamically interacted by 1 AU. At higher frequencies the familiar Kolmogorov-like power law is seen. Farther from the sun the frequency break point between the shallow l/f and the steeper Kolmogorov spectrum evolves systematically towards lower frequencies. We suggest that the Kolmogorov-like spectra emerge due to in situ turbulence that generates spatial correlations associated with the turbulent cascade and that the background l/f noise is a largely temporal phenomenon, not associated with in situ dynamical processes. In this paper we discuss these ideas from the standpoint of observations from several interplanetary spacecraft.
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Chirombo, James; Lowe, Rachel; Kazembe, Lawrence
2014-01-01
Background After years of implementing Roll Back Malaria (RBM) interventions, the changing landscape of malaria in terms of risk factors and spatial pattern has not been fully investigated. This paper uses the 2010 malaria indicator survey data to investigate if known malaria risk factors remain relevant after many years of interventions. Methods We adopted a structured additive logistic regression model that allowed for spatial correlation, to more realistically estimate malaria risk factors. Our model included child and household level covariates, as well as climatic and environmental factors. Continuous variables were modelled by assuming second order random walk priors, while spatial correlation was specified as a Markov random field prior, with fixed effects assigned diffuse priors. Inference was fully Bayesian resulting in an under five malaria risk map for Malawi. Results Malaria risk increased with increasing age of the child. With respect to socio-economic factors, the greater the household wealth, the lower the malaria prevalence. A general decline in malaria risk was observed as altitude increased. Minimum temperatures and average total rainfall in the three months preceding the survey did not show a strong association with disease risk. Conclusions The structured additive regression model offered a flexible extension to standard regression models by enabling simultaneous modelling of possible nonlinear effects of continuous covariates, spatial correlation and heterogeneity, while estimating usual fixed effects of categorical and continuous observed variables. Our results confirmed that malaria epidemiology is a complex interaction of biotic and abiotic factors, both at the individual, household and community level and that risk factors are still relevant many years after extensive implementation of RBM activities. PMID:24991915
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Chirombo, James; Lowe, Rachel; Kazembe, Lawrence
2014-01-01
After years of implementing Roll Back Malaria (RBM) interventions, the changing landscape of malaria in terms of risk factors and spatial pattern has not been fully investigated. This paper uses the 2010 malaria indicator survey data to investigate if known malaria risk factors remain relevant after many years of interventions. We adopted a structured additive logistic regression model that allowed for spatial correlation, to more realistically estimate malaria risk factors. Our model included child and household level covariates, as well as climatic and environmental factors. Continuous variables were modelled by assuming second order random walk priors, while spatial correlation was specified as a Markov random field prior, with fixed effects assigned diffuse priors. Inference was fully Bayesian resulting in an under five malaria risk map for Malawi. Malaria risk increased with increasing age of the child. With respect to socio-economic factors, the greater the household wealth, the lower the malaria prevalence. A general decline in malaria risk was observed as altitude increased. Minimum temperatures and average total rainfall in the three months preceding the survey did not show a strong association with disease risk. The structured additive regression model offered a flexible extension to standard regression models by enabling simultaneous modelling of possible nonlinear effects of continuous covariates, spatial correlation and heterogeneity, while estimating usual fixed effects of categorical and continuous observed variables. Our results confirmed that malaria epidemiology is a complex interaction of biotic and abiotic factors, both at the individual, household and community level and that risk factors are still relevant many years after extensive implementation of RBM activities.
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Spatially resolved speckle-correlometry of sol-gel transition
NASA Astrophysics Data System (ADS)
Isaeva, A. A.; Isaeva, E. A.; Pantyukov, A. V.; Zimnyakov, D. A.
2018-04-01
Sol-gel transition was studied using the speckle correlometry method with a localized light source and spatial filtering of backscattered radiation. Water solutions of technical or food gelatin with added TiO2 nanoparticles were used as studied objects. Structural transformation of "sol-gel" system was studied at various temperatures from 25°C to 50°C using analysis of the correlation and structure functions of speckle intensity fluctuations. The characteristic temperatures of "sol - gel" transition were evaluated for studied systems. Obtained results can be used for various applications in biomedicine and food industry.
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NASA Astrophysics Data System (ADS)
Ushenko, Yu. A.; Angelskii, P. O.; Dubolazov, A. V.; Karachevtsev, A. O.; Sidor, M. I.; Mintser, O. P.; Oleinichenko, B. P.; Bizer, L. I.
2013-10-01
We present a theoretical formalism of correlation phase analysis of laser images of human blood plasma with spatial-frequency selection of manifestations of mechanisms of linear and circular birefringence of albumin and globulin polycrystalline networks. Comparative results of the measurement of coordinate distributions of the correlation parameter—the modulus of the degree of local correlation of amplitudes—of laser images of blood plasma taken from patients of three groups—healthy patients (donors), rheumatoid-arthritis patients, and breast-cancer patients—are presented. We investigate values and ranges of change of statistical (the first to fourth statistical moments), correlation (excess of autocorrelation functions), and fractal (slopes of approximating curves and dispersion of extrema of logarithmic dependences of power spectra) parameters of coordinate distributions of the degree of local correlation of amplitudes. Objective criteria for diagnostics of occurrence and differentiation of inflammatory and oncological states are determined.
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Peucker, Amanda J.; Valautham, Sureen K.; Styan, Craig A.; Dann, Peter
2015-01-01
Factors responsible for spatial structuring of population genetic variation are varied, and in many instances there may be no obvious explanations for genetic structuring observed, or those invoked may reflect spurious correlations. A study of little penguins (Eudyptula minor) in southeast Australia documented low spatial structuring of genetic variation with the exception of colonies at the western limit of sampling, and this distinction was attributed to an intervening oceanographic feature (Bonney Upwelling), differences in breeding phenology, or sea level change. Here, we conducted sampling across the entire Australian range, employing additional markers (12 microsatellites and mitochondrial DNA, 697 individuals, 17 colonies). The zone of elevated genetic structuring previously observed actually represents the eastern half of a genetic cline, within which structuring exists over much shorter spatial scales than elsewhere. Colonies separated by as little as 27 km in the zone are genetically distinguishable, while outside the zone, homogeneity cannot be rejected at scales of up to 1400 km. Given a lack of additional physical or environmental barriers to gene flow, the zone of elevated genetic structuring may reflect secondary contact of lineages (with or without selection against interbreeding), or recent colonization and expansion from this region. This study highlights the importance of sampling scale to reveal the cause of genetic structuring. PMID:25833231
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NASA Astrophysics Data System (ADS)
Shafer, J. M.; Varljen, M. D.
1990-08-01
A fundamental requirement for geostatistical analyses of spatially correlated environmental data is the estimation of the sample semivariogram to characterize spatial correlation. Selecting an underlying theoretical semivariogram based on the sample semivariogram is an extremely important and difficult task that is subject to a great deal of uncertainty. Current standard practice does not involve consideration of the confidence associated with semivariogram estimates, largely because classical statistical theory does not provide the capability to construct confidence limits from single realizations of correlated data, and multiple realizations of environmental fields are not found in nature. The jackknife method is a nonparametric statistical technique for parameter estimation that may be used to estimate the semivariogram. When used in connection with standard confidence procedures, it allows for the calculation of closely approximate confidence limits on the semivariogram from single realizations of spatially correlated data. The accuracy and validity of this technique was verified using a Monte Carlo simulation approach which enabled confidence limits about the semivariogram estimate to be calculated from many synthetically generated realizations of a random field with a known correlation structure. The synthetically derived confidence limits were then compared to jackknife estimates from single realizations with favorable results. Finally, the methodology for applying the jackknife method to a real-world problem and an example of the utility of semivariogram confidence limits were demonstrated by constructing confidence limits on seasonal sample variograms of nitrate-nitrogen concentrations in shallow groundwater in an approximately 12-mi2 (˜30 km2) region in northern Illinois. In this application, the confidence limits on sample semivariograms from different time periods were used to evaluate the significance of temporal change in spatial correlation. This capability is quite important as it can indicate when a spatially optimized monitoring network would need to be reevaluated and thus lead to more robust monitoring strategies.
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Does hemipelvis structure and position influence acetabulum orientation?
Musielak, Bartosz; Jóźwiak, Marek; Rychlik, Michał; Chen, Brian Po-Jung; Idzior, Maciej; Grzegorzewski, Andrzej
2016-03-16
Although acetabulum orientation is well established anatomically and radiographically, its relation to the innominate bone has rarely been addressed. If explored, it could open the discussion on patomechanisms of such complex disorders as femoroacetabular impingement (FAI). We therefore evaluated the influence of pelvic bone position and structure on acetabular spatial orientation. We describe this relation and its clinical implications. This retrospective study was based on computed tomography scanning of three-dimensional models of 31 consecutive male pelvises (62 acetabulums). All measurements were based on CT spatial reconstruction with the use of highly specialized software (Rhinoceros). Relations between acetabular orientation (inclination, tilt, anteversion angles) and pelvic structure were evaluated. The following parameters were evaluated to assess the pelvic structure: iliac opening angle, iliac tilt angle, interspinous distance (ISD), intertuberous distance (ITD), height of the pelvis (HP), and the ISD/ITD/HP ratio. The linear and nonlinear dependence of the acetabular angles and hemipelvic measurements were examined with Pearson's product - moment correlation and Spearman's rank correlation coefficient. Correlations different from 0 with p < 0.05 were considered statistically significant. Comparison of the axis position with pelvis structure with orientation in the horizontal plane revealed a significant positive correlation between the acetabular anteversion angle and the iliac opening angle (p = 0.041 and 0.008, respectively). In the frontal plane, there was a positive correlation between the acetabular inclination angle and the iliac tilt angle (p = 0.025 and 0.014, respectively) and the acetabular inclination angle and the ISD/ITD/HP ratio (both p = 0.048). There is a significant correlation of the hemipelvic structure and acetabular orientation under anatomic conditions, especially in the frontal and horizontal planes. In the anteroposterior view, the more tilted-down innominate bone causes a more caudally oriented acetabulum axis, whereas in the horizontal view this relation is reversed. This study may serve as a basis for the discussion on the role of the pelvis in common disorders of the hip.
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Krause, Florian; Lindemann, Oliver; Toni, Ivan; Bekkering, Harold
2014-04-01
A dominant hypothesis on how the brain processes numerical size proposes a spatial representation of numbers as positions on a "mental number line." An alternative hypothesis considers numbers as elements of a generalized representation of sensorimotor-related magnitude, which is not obligatorily spatial. Here we show that individuals' relative use of spatial and nonspatial representations has a cerebral counterpart in the structural organization of the posterior parietal cortex. Interindividual variability in the linkage between numbers and spatial responses (faster left responses to small numbers and right responses to large numbers; spatial-numerical association of response codes effect) correlated with variations in gray matter volume around the right precuneus. Conversely, differences in the disposition to link numbers to force production (faster soft responses to small numbers and hard responses to large numbers) were related to gray matter volume in the left angular gyrus. This finding suggests that numerical cognition relies on multiple mental representations of analogue magnitude using different neural implementations that are linked to individual traits.
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NASA Technical Reports Server (NTRS)
Maestrello, Lucio
2002-01-01
Acoustic and turbulent boundary layer flow loadings over a flexible structure are used to study the spatial-temporal dynamics of the response of the structure. The stability of the spatial synchronization and desynchronization by an active external force is investigated with an array of coupled transducers on the structure. In the synchronous state, the structural phase is locked, which leads to the formation of spatial patterns while the amplitude peaks exhibit chaotic behaviors. Large amplitude, spatially symmetric loading is superimposed on broadband, but in the desynchronized state, the spectrum broadens and the phase space is lost. The resulting pattern bears a striking resemblance to phase turbulence. The transition is achieved by using a low power external actuator to trigger broadband behaviors from the knowledge of the external acoustic load inducing synchronization. The changes are made favorably and efficiently to alter the frequency distribution of power, not the total power level. Before synchronization effects are seen, the panel response to the turbulent boundary layer loading is discontinuously spatio-temporally correlated. The stability develops from different competing wavelengths; the spatial scale is significantly shorter than when forced with the superimposed external sound. When the external sound level decreases and the synchronized phases are lost, changes in the character of the spectra can be linked to the occurrence of spatial phase transition. These changes can develop broadband response. Synchronized responses of fuselage structure panels have been observed in subsonic and supersonic aircraft; results from two flights tests are discussed.
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A mini-review on econophysics: Comparative study of Chinese and western financial markets
NASA Astrophysics Data System (ADS)
Zheng, Bo; Jiang, Xiong-Fei; Ni, Peng-Yun
2014-07-01
We present a review of our recent research in econophysics, and focus on the comparative study of Chinese and western financial markets. By virtue of concepts and methods in statistical physics, we investigate the time correlations and spatial structure of financial markets based on empirical high-frequency data. We discover that the Chinese stock market shares common basic properties with the western stock markets, such as the fat-tail probability distribution of price returns, the long-range auto-correlation of volatilities, and the persistence probability of volatilities, while it exhibits very different higher-order time correlations of price returns and volatilities, spatial correlations of individual stock prices, and large-fluctuation dynamic behaviors. Furthermore, multi-agent-based models are developed to simulate the microscopic interaction and dynamic evolution of the stock markets.
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Brillouin Optical Correlation Domain Analysis in Composite Material Beams
Stern, Yonatan; London, Yosef; Preter, Eyal; Antman, Yair; Diamandi, Hilel Hagai; Silbiger, Maayan; Adler, Gadi; Shalev, Doron; Zadok, Avi
2017-01-01
Structural health monitoring is a critical requirement in many composites. Numerous monitoring strategies rely on measurements of temperature or strain (or both), however these are often restricted to point-sensing or to the coverage of small areas. Spatially-continuous data can be obtained with optical fiber sensors. In this work, we report high-resolution distributed Brillouin sensing over standard fibers that are embedded in composite structures. A phase-coded, Brillouin optical correlation domain analysis (B-OCDA) protocol was employed, with spatial resolution of 2 cm and sensitivity of 1 °K or 20 micro-strain. A portable measurement setup was designed and assembled on the premises of a composite structures manufacturer. The setup was successfully utilized in several structural health monitoring scenarios: (a) monitoring the production and curing of a composite beam over 60 h; (b) estimating the stiffness and Young’s modulus of a composite beam; and (c) distributed strain measurements across the surfaces of a model wing of an unmanned aerial vehicle. The measurements are supported by the predictions of structural analysis calculations. The results illustrate the potential added values of high-resolution, distributed Brillouin sensing in the structural health monitoring of composites. PMID:28974041
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Brillouin Optical Correlation Domain Analysis in Composite Material Beams.
Stern, Yonatan; London, Yosef; Preter, Eyal; Antman, Yair; Diamandi, Hilel Hagai; Silbiger, Maayan; Adler, Gadi; Levenberg, Eyal; Shalev, Doron; Zadok, Avi
2017-10-02
Structural health monitoring is a critical requirement in many composites. Numerous monitoring strategies rely on measurements of temperature or strain (or both), however these are often restricted to point-sensing or to the coverage of small areas. Spatially-continuous data can be obtained with optical fiber sensors. In this work, we report high-resolution distributed Brillouin sensing over standard fibers that are embedded in composite structures. A phase-coded, Brillouin optical correlation domain analysis (B-OCDA) protocol was employed, with spatial resolution of 2 cm and sensitivity of 1 °K or 20 micro-strain. A portable measurement setup was designed and assembled on the premises of a composite structures manufacturer. The setup was successfully utilized in several structural health monitoring scenarios: (a) monitoring the production and curing of a composite beam over 60 h; (b) estimating the stiffness and Young's modulus of a composite beam; and (c) distributed strain measurements across the surfaces of a model wing of an unmanned aerial vehicle. The measurements are supported by the predictions of structural analysis calculations. The results illustrate the potential added values of high-resolution, distributed Brillouin sensing in the structural health monitoring of composites.
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A Correlational Study of Seven Projective Spatial Structures with Regard to the Phases of the MOON^
NASA Astrophysics Data System (ADS)
Wellner, Karen Linette
1995-01-01
This study investigated the relationship between projective spatial structures and the ability to construct a scientific model. In addition, gender-related performance and the influence of prior astronomy experience on task success were evaluated. Sixty-one college science undergraduates were individually administered Piagetian tasks to assess for projective spatial structures and the ability to set up a phases of the moon model. The spatial tasks included: (a) Mountains task (coordination of perspectives); (b) Railroad task (size and intervals of objects with increasing distance); (c) Telephone Poles task (masking and ordering objects); and (d) Shadows task (spatial relationships between an object and its shadow, dependent upon the object's orientation). Cramer coefficient analyses indicated that significant relationships existed between Moon task and spatial task success. In particular, the Shadows task, requiring subjects to draw shadows of objects in different orientations, proved most difficult and was most strongly associated with with a subject's understanding of lunar phases. Chi-square tests for two independent samples were used to analyze gender performance differences on each of the Ave tasks. Males performed significantly better at a.05 significance level in regard to the Shadows task and the Moon task. Chi-square tests for two independent samples showed no significant difference in Moon task performance between subjects with astronomy or Earth science coursework, and those without such science classroom experience. Overall, only six subjects passed all seven projective spatial structure tasks. Piaget (1967) contends that concrete -operational spatial structures must be established before an individual is able to develop formal-operational patterns of thinking. The results of this study indicate that 90% of the interviewed science majors are still operating at the concrete-operational level. Several educational implications were drawn from this study: (1) The teaching of spatially dependent content to students without prerequisite spatial structures results in understanding no further beyond that which can be memorized; (2) assessment for projective spatial structures should precede science lessons dealing with time-space relationships, and (3) a student's level of spatial ability may directly impact upon interpretation of three-dimensional models.
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Large-scale changes in network interactions as a physiological signature of spatial neglect
Baldassarre, Antonello; Ramsey, Lenny; Hacker, Carl L.; Callejas, Alicia; Astafiev, Serguei V.; Metcalf, Nicholas V.; Zinn, Kristi; Rengachary, Jennifer; Snyder, Abraham Z.; Carter, Alex R.; Shulman, Gordon L.
2014-01-01
The relationship between spontaneous brain activity and behaviour following focal injury is not well understood. Here, we report a large-scale study of resting state functional connectivity MRI and spatial neglect following stroke in a large (n = 84) heterogeneous sample of first-ever stroke patients (within 1–2 weeks). Spatial neglect, which is typically more severe after right than left hemisphere injury, includes deficits of spatial attention and motor actions contralateral to the lesion, and low general attention due to impaired vigilance/arousal. Patients underwent structural and resting state functional MRI scans, and spatial neglect was measured using the Posner spatial cueing task, and Mesulam and Behavioural Inattention Test cancellation tests. A principal component analysis of the behavioural tests revealed a main factor accounting for 34% of variance that captured three correlated behavioural deficits: visual neglect of the contralesional visual field, visuomotor neglect of the contralesional field, and low overall performance. In an independent sample (21 healthy subjects), we defined 10 resting state networks consisting of 169 brain regions: visual-fovea and visual-periphery, sensory-motor, auditory, dorsal attention, ventral attention, language, fronto-parietal control, cingulo-opercular control, and default mode. We correlated the neglect factor score with the strength of resting state functional connectivity within and across the 10 resting state networks. All damaged brain voxels were removed from the functional connectivity:behaviour correlational analysis. We found that the correlated behavioural deficits summarized by the factor score were associated with correlated multi-network patterns of abnormal functional connectivity involving large swaths of cortex. Specifically, dorsal attention and sensory-motor networks showed: (i) reduced interhemispheric functional connectivity; (ii) reduced anti-correlation with fronto-parietal and default mode networks in the right hemisphere; and (iii) increased intrahemispheric connectivity with the basal ganglia. These patterns of functional connectivity:behaviour correlations were stronger in patients with right- as compared to left-hemisphere damage and were independent of lesion volume. Our findings identify large-scale changes in resting state network interactions that are a physiological signature of spatial neglect and may relate to its right hemisphere lateralization. PMID:25367028
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Petrella, L I; Cai, Y; Sereno, J V; Gonçalves, S I; Silva, A J; Castelo-Branco, M
2016-09-01
Neurofibromatosis type-1 (NF1) is a common neurogenetic disorder and an important cause of intellectual disability. Brain-behaviour associations can be examined in vivo using morphometric magnetic resonance imaging (MRI) and diffusion tensor imaging (DTI) to study brain structure. Here, we studied structural and behavioural phenotypes in heterozygous Nf1 mice (Nf1(+/-) ) using T2-weighted imaging MRI and DTI, with a focus on social recognition deficits. We found that Nf1(+/-) mice have larger volumes than wild-type (WT) mice in regions of interest involved in social cognition, the prefrontal cortex (PFC) and the caudate-putamen (CPu). Higher diffusivity was found across a distributed network of cortical and subcortical brain regions, within and beyond these regions. Significant differences were observed for the social recognition test. Most importantly, significant structure-function correlations were identified concerning social recognition performance and PFC volumes in Nf1(+/-) mice. Analyses of spatial learning corroborated the previously known deficits in the mutant mice, as corroborated by platform crossings, training quadrant time and average proximity measures. Moreover, linear discriminant analysis of spatial performance identified 2 separate sub-groups in Nf1(+/-) mice. A significant correlation between quadrant time and CPu volumes was found specifically for the sub-group of Nf1(+/-) mice with lower spatial learning performance, suggesting additional evidence for reorganization of this region. We found strong evidence that social and spatial cognition deficits can be associated with PFC/CPu structural changes and reorganization in NF1. © 2016 John Wiley & Sons Ltd and International Behavioural and Neural Genetics Society.
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Correlated Imaging – A Grand Challenge in Chemical Analysis
Masyuko, Rachel; Lanni, Eric; Sweedler, Jonathan V.; Bohn, Paul W.
2013-01-01
Correlated chemical imaging is an emerging strategy for acquisition of images by combining information from multiplexed measurement platforms to track, visualize, and interpret in situ changes in the structure, organization, and activities of interesting chemical systems, frequently spanning multiple decades in space and time. Acquiring and correlating information from complementary imaging experiments has the potential to expose complex chemical behavior in ways that are simply not available from single methods applied in isolation, thereby greatly amplifying the information gathering power of imaging experiments. However, in order to correlate image information across platforms, a number of issues must be addressed. First, signals are obtained from disparate experiments with fundamentally different figures of merit, including pixel size, spatial resolution, dynamic range, and acquisition rates. In addition, images are often acquired on different instruments in different locations, so the sample must be registered spatially so that the same area of the sample landscape is addressed. The signals acquired must be correlated in both spatial and temporal domains, and the resulting information has to be presented in a way that is readily understood. These requirements pose special challenges for image cross-correlation that go well beyond those posed in single technique imaging approaches. The special opportunities and challenges that attend correlated imaging are explored by specific reference to correlated mass spectrometric and Raman imaging, a topic of substantial and growing interest. PMID:23431559
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NASA Astrophysics Data System (ADS)
Manzo, Ciro; Braga, Federica; Zaggia, Luca; Brando, Vittorio Ernesto; Giardino, Claudia; Bresciani, Mariano; Bassani, Cristiana
2018-04-01
This paper describes a procedure to perform spatio-temporal analysis of river plume dispersion in prodelta areas by multi-temporal Landsat-8-derived products for identifying zones sensitive to water discharge and for providing geostatistical patterns of turbidity linked to different meteo-marine forcings. In particular, we characterized the temporal and spatial variability of turbidity and sea surface temperature (SST) in the Po River prodelta (Northern Adriatic Sea, Italy) during the period 2013-2016. To perform this analysis, a two-pronged processing methodology was implemented and the resulting outputs were analysed through a series of statistical tools. A pixel-based spatial correlation analysis was carried out by comparing temporal curves of turbidity and SST hypercubes with in situ time series of wind speed and water discharge, providing correlation coefficient maps. A geostatistical analysis was performed to determine the spatial dependency of the turbidity datasets per each satellite image, providing maps of correlation and variograms. The results show a linear correlation between water discharge and turbidity variations in the points more affected by the buoyant plumes and along the southern coast of Po River delta. Better inverse correlation was found between turbidity and SST during floods rather than other periods. The correlation maps of wind speed with turbidity show different spatial patterns depending on local or basin-scale wind effects. Variogram maps identify different spatial anisotropy structures of turbidity in response to ambient conditions (i.e. strong Bora or Scirocco winds, floods). Since the implemented processing methodology is based on open source software and free satellite data, it represents a promising tool for the monitoring of maritime ecosystems and to address water quality analyses and the investigations of sediment dynamics in estuarine and coastal waters.
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Carasatorre, Mariana; Ochoa-Alvarez, Adrian; Velázquez-Campos, Giovanna; Lozano-Flores, Carlos; Ramírez-Amaya, Víctor; Díaz-Cintra, Sofía Y
2015-01-01
Spatial water maze (WM) overtraining induces hippocampal mossy fiber (MF) expansion, and it has been suggested that spatial pattern separation depends on the MF pathway. We hypothesized that WM experience inducing MF expansion in rats would improve spatial pattern separation in the hippocampal network. We first tested this by using the the delayed non-matching to place task (DNMP), in animals that had been previously trained on the water maze (WM) and found that these animals, as well as animals treated as swim controls (SC), performed better than home cage control animals the DNMP task. The "catFISH" imaging method provided neurophysiological evidence that hippocampal pattern separation improved in animals treated as SC, and this improvement was even clearer in animals that experienced the WM training. Moreover, these behavioral treatments also enhance network reliability and improve partial pattern separation in CA1 and pattern completion in CA3. By measuring the area occupied by synaptophysin staining in both the stratum oriens and the stratun lucidum of the distal CA3, we found evidence of structural synaptic plasticity that likely includes MF expansion. Finally, the measures of hippocampal network coding obtained with catFISH correlate significantly with the increased density of synaptophysin staining, strongly suggesting that structural synaptic plasticity in the hippocampus induced by the WM and SC experience is related to the improvement of spatial information processing in the hippocampus.
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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.
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NASA Astrophysics Data System (ADS)
Wang, Hui; Wellmann, Florian; Verweij, Elizabeth; von Hebel, Christian; van der Kruk, Jan
2017-04-01
Lateral and vertical spatial heterogeneity of subsurface properties such as soil texture and structure influences the available water and resource supply for crop growth. High-resolution mapping of subsurface structures using non-invasive geo-referenced geophysical measurements, like electromagnetic induction (EMI), enables a characterization of 3D soil structures, which have shown correlations to remote sensing information of the crop states. The benefit of EMI is that it can return 3D subsurface information, however the spatial dimensions are limited due to the labor intensive measurement procedure. Although active and passive sensors mounted on air- or space-borne platforms return 2D images, they have much larger spatial dimensions. Combining both approaches provides us with a potential pathway to extend the detailed 3D geophysical information to a larger area by using remote sensing information. In this study, we aim at extracting and providing insights into the spatial and statistical correlation of the geophysical and remote sensing observations of the soil/vegetation continuum system. To this end, two key points need to be addressed: 1) how to detect and recognize the geometric patterns (i.e., spatial heterogeneity) from multiple data sets, and 2) how to quantitatively describe the statistical correlation between remote sensing information and geophysical measurements. In the current study, the spatial domain is restricted to shallow depths up to 3 meters, and the geostatistical database contains normalized difference vegetation index (NDVI) derived from RapidEye satellite images and apparent electrical conductivities (ECa) measured from multi-receiver EMI sensors for nine depths of exploration ranging from 0-2.7 m. The integrated data sets are mapped into both the physical space (i.e. the spatial domain) and feature space (i.e. a two-dimensional space framed by the NDVI and the ECa data). Hidden Markov Random Fields (HMRF) are employed to model the underlying heterogeneities in spatial domain and finite Gaussian mixture models are adopted to quantitatively describe the statistical patterns in terms of center vectors and covariance matrices in feature space. A recently developed parallel stochastic clustering algorithm is adopted to implement the HMRF models and the Markov chain Monte Carlo based Bayesian inference. Certain spatial patterns such as buried paleo-river channels covered by shallow sediments are investigated as typical examples. The results indicate that the geometric patterns of the subsurface heterogeneity can be represented and quantitatively characterized by HMRF. Furthermore, the statistical patterns of the NDVI and the EMI data from the soil/vegetation-continuum system can be inferred and analyzed in a quantitative manner.
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Structural correlates of subjective and objective memory performance in multiple sclerosis.
Pardini, Matteo; Bergamino, Maurizio; Bommarito, Giulia; Bonzano, Laura; Luigi Mancardi, Gian; Roccatagliata, Luca
2014-04-01
Subjective and objective memory deficits represent a frequent and ill-understood aspect of multiple sclerosis (MS), and a significant cause of disability and quality of life reduction. The aim of the study is to verify the role of hippocampal and temporal associative fibers' damage in MS-related memory complaints. To reach this aim, 25 patients with low disability relapsing-remitting MS and 19 healthy controls were included in the study. All subjects underwent 3D T1 structural imaging and Diffusion Tensor Imaging. Additionally, MS patients underwent neuropsychological evaluation of objective (Selective Reminding Test and Spatial Recall Test) and of subjective (Perceived Deficit Questionnaire, Retrospective and Prospective Memory Subscales) memory deficits. Normalized hippocampal volume (NHV) and mean Fractional Anisotropy (FA) for the uncinate fasciculus (UF) and for the ventral division of the cingulum bundle (VCB) were calculated for all subjects. We showed that, compared to controls, MS subjects presented with reduced right NHV and with reduced mean FA bilaterally in the UF and the VCB. In the MS group, verbal memory scores correlated with left NHV, spatial memory scores correlated with right NHV, while perceived retrospective and prospective memory deficits correlated with left VCB and left UF mean FA respectively. Our data confirm an early involvement of memory-related brain structures in MS patients. Our data suggest that verbal and nonverbal memory as well as perceived retrospective and prospective memory deficits are related to alterations of discrete anatomical structures in the low-disability phase of MS. Copyright © 2013 Wiley Periodicals, Inc.
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Spatial and temporal variations of evapotranspiration, groundwater and precipitation in Amazonia
NASA Astrophysics Data System (ADS)
Niu, J.; Riley, W. J.; Shen, C.; Melack, J. M.; Qiu, H.
2017-12-01
We used wavelet coherence analysis to investigate the effects of precipitation (P) and groundwater dynamics (total water storage anomaly, TWSA) on evapotranspiration (ET) at kilometer, sub-basin, and whole basin scales in the Amazon basin. The Amazon-scale averaged ET, P, and TWSA have about the same annual periodicity. The phase lag between ET and P (ΦET-P) is 1 to 3 months, and between ET and TWSA (ΦET-TWSA) is 3 to 7 months. The phase patterns have a south-north divide due to significant variation in climatic conditions. The correlation between ΦET-P and ΦET-TWSA is affected by the aridity index (the ratio between potential ET (PET) and P, PET / P), of each sub-basin, as determined using the Budyko framework at the sub-basin level. The spatial structure of ΦET-P is negatively correlated with the spatial structure of annual ET. At Amazon-scale during a drought year (e.g., 2010), both phases decreased, while in the subsequent years, ΦET-TWSA increased, indicating strong groundwater effects on ET immediately following dry years Amazon-wide.
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Species composition and morphologic variation of Porites in the Gulf of California
NASA Astrophysics Data System (ADS)
López-Pérez, R. A.
2013-09-01
Morphometric analysis of corallite calices confirmed that from the late Miocene to the Recent, four species of Porites have inhabited the Gulf of California: the extinct Porites carrizensis, the locally extirpated Porites lobata and the extant Porites sverdrupi and Porites panamensis. Furthermore, large-scale spatial and temporal phenotypic plasticity was observed in the dominant species P. panamensis. Canonical discriminant analysis and ANOVA demonstrated that the calice structures of P. panamensis experienced size reduction between the late Pleistocene and Recent. Similarly, PERMANOVA, regression and correlation analyses demonstrated that across the 800 km north to south in the gulf, P. panamensis populations displayed a similar reduction in calice structures. Based on correlation analysis with environmental data, these large spatial changes are likely related to changes in nutrient concentration and sea surface temperature. As such, the large-scale spatial and temporal phenotypic variation recorded in populations of P. panamensis in the Gulf of California is likely related to optimization of corallite performance (energy acquisition) within various environmental scenarios. These findings may have relevance to modern conservation efforts within this ecological dominant genus.
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Coupling fine-scale root and canopy structure using ground-based remote sensing
Hardiman, Brady S.; Gough, Christopher M.; Butnor, John R.; ...
2017-02-21
Ecosystem physical structure, defined by the quantity and spatial distribution of biomass, influences a range of ecosystem functions. Remote sensing tools permit the non-destructive characterization of canopy and root features, potentially providing opportunities to link above- and belowground structure at fine spatial resolution in functionally meaningful ways. To test this possibility, we employed ground-based portable canopy LiDAR (PCL) and ground penetrating radar (GPR) along co-located transects in forested sites spanning multiple stages of ecosystem development and, consequently, of structural complexity. We examined canopy and root structural data for coherence (i.e., correlation in the frequency of spatial variation) at multiple spatialmore » scales 10 m within each site using wavelet analysis. Forest sites varied substantially in vertical canopy and root structure, with leaf area index and root mass more becoming even vertically as forests aged. In all sites, above- and belowground structure, characterized as mean maximum canopy height and root mass, exhibited significant coherence at a scale of 3.5–4 m, and results suggest that the scale of coherence may increase with stand age. Our findings demonstrate that canopy and root structure are linked at characteristic spatial scales, which provides the basis to optimize scales of observation. Lastly, our study highlights the potential, and limitations, for fusing LiDAR and radar technologies to quantitatively couple above- and belowground ecosystem structure.« less
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Coupling fine-scale root and canopy structure using ground-based remote sensing
DOE Office of Scientific and Technical Information (OSTI.GOV)
Hardiman, Brady S.; Gough, Christopher M.; Butnor, John R.
Ecosystem physical structure, defined by the quantity and spatial distribution of biomass, influences a range of ecosystem functions. Remote sensing tools permit the non-destructive characterization of canopy and root features, potentially providing opportunities to link above- and belowground structure at fine spatial resolution in functionally meaningful ways. To test this possibility, we employed ground-based portable canopy LiDAR (PCL) and ground penetrating radar (GPR) along co-located transects in forested sites spanning multiple stages of ecosystem development and, consequently, of structural complexity. We examined canopy and root structural data for coherence (i.e., correlation in the frequency of spatial variation) at multiple spatialmore » scales 10 m within each site using wavelet analysis. Forest sites varied substantially in vertical canopy and root structure, with leaf area index and root mass more becoming even vertically as forests aged. In all sites, above- and belowground structure, characterized as mean maximum canopy height and root mass, exhibited significant coherence at a scale of 3.5–4 m, and results suggest that the scale of coherence may increase with stand age. Our findings demonstrate that canopy and root structure are linked at characteristic spatial scales, which provides the basis to optimize scales of observation. Lastly, our study highlights the potential, and limitations, for fusing LiDAR and radar technologies to quantitatively couple above- and belowground ecosystem structure.« less
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NASA Astrophysics Data System (ADS)
Porzycki, Jakub; WÄ s, Jarosław; Hedayatifar, Leila; Hassanibesheli, Forough; Kułakowski, Krzysztof
2017-08-01
The aim of the paper is an analysis of self-organization patterns observed in the unidirectional flow of pedestrians. On the basis of experimental data from Zhang et al. [J. Zhang et al., J. Stat. Mech. (2011) P06004, 10.1088/1742-5468/2011/06/P06004], we analyze the mutual positions and velocity correlations between pedestrians when walking along a corridor. The angular and spatial dependencies of the mutual positions reveal a spatial structure that remains stable during the crowd motion. This structure differs depending on the value of n , for the consecutive n th -nearest-neighbor position set. The preferred position for the first-nearest neighbor is on the side of the pedestrian, while for further neighbors, this preference shifts to the axis of movement. The velocity correlations vary with the angle formed by the pair of neighboring pedestrians and the direction of motion and with the time delay between pedestrians' movements. The delay dependence of the correlations shows characteristic oscillations, produced by the velocity oscillations when striding; however, a filtering of the main frequency of individual striding out reduces the oscillations only partially. We conclude that pedestrians select their path directions so as to evade the necessity of continuously adjusting their speed to their neighbors'. They try to keep a given distance, but follow the person in front of them, as well as accepting and observing pedestrians on their sides. Additionally, we show an empirical example that illustrates the shape of a pedestrian's personal space during movement.
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Wessén, Ella; Söderström, Mats; Stenberg, Maria; Bru, David; Hellman, Maria; Welsh, Allana; Thomsen, Frida; Klemedtson, Leif; Philippot, Laurent; Hallin, Sara
2011-01-01
Characterization of spatial patterns of functional microbial communities could facilitate the understanding of the relationships between the ecology of microbial communities, the biogeochemical processes they perform and the corresponding ecosystem functions. Because of the important role the ammonia-oxidizing bacteria (AOB) and archaea (AOA) have in nitrogen cycling and nitrate leaching, we explored the spatial distribution of their activity, abundance and community composition across a 44-ha large farm divided into an organic and an integrated farming system. The spatial patterns were mapped by geostatistical modeling and correlations to soil properties and ecosystem functioning in terms of nitrate leaching were determined. All measured community components for both AOB and AOA exhibited spatial patterns at the hectare scale. The patchy patterns of community structures did not reflect the farming systems, but the AOB community was weakly related to differences in soil pH and moisture, whereas the AOA community to differences in soil pH and clay content. Soil properties related differently to the size of the communities, with soil organic carbon and total nitrogen correlating positively to AOB abundance, while clay content and pH showed a negative correlation to AOA abundance. Contrasting spatial patterns were observed for the abundance distributions of the two groups indicating that the AOB and AOA may occupy different niches in agro-ecosystems. In addition, the two communities correlated differently to community and ecosystem functions. Our results suggest that the AOA, not the AOB, were contributing to nitrate leaching at the site by providing substrate for the nitrite oxidizers. PMID:21228891
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Konstantinou, Nikos; Constantinidou, Fofi; Kanai, Ryota
2017-02-01
Working memory is responsible for keeping information in mind when it is no longer in view, linking perception with higher cognitive functions. Despite such crucial role, short-term maintenance of visual information is severely limited. Research suggests that capacity limits in visual short-term memory (VSTM) are correlated with sustained activity in distinct brain areas. Here, we investigated whether variability in the structure of the brain is reflected in individual differences of behavioral capacity estimates for spatial and object VSTM. Behavioral capacity estimates were calculated separately for spatial and object information using a novel adaptive staircase procedure and were found to be unrelated, supporting domain-specific VSTM capacity limits. Voxel-based morphometry (VBM) analyses revealed dissociable neuroanatomical correlates of spatial versus object VSTM. Interindividual variability in spatial VSTM was reflected in the gray matter density of the inferior parietal lobule. In contrast, object VSTM was reflected in the gray matter density of the left insula. These dissociable findings highlight the importance of considering domain-specific estimates of VSTM capacity and point to the crucial brain regions that limit VSTM capacity for different types of visual information. Hum Brain Mapp 38:767-778, 2017. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.
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Structural covariance networks across healthy young adults and their consistency.
Guo, Xiaojuan; Wang, Yan; Guo, Taomei; Chen, Kewei; Zhang, Jiacai; Li, Ke; Jin, Zhen; Yao, Li
2015-08-01
To investigate structural covariance networks (SCNs) as measured by regional gray matter volumes with structural magnetic resonance imaging (MRI) from healthy young adults, and to examine their consistency and stability. Two independent cohorts were included in this study: Group 1 (82 healthy subjects aged 18-28 years) and Group 2 (109 healthy subjects aged 20-28 years). Structural MRI data were acquired at 3.0T and 1.5T using a magnetization prepared rapid-acquisition gradient echo sequence for these two groups, respectively. We applied independent component analysis (ICA) to construct SCNs and further applied the spatial overlap ratio and correlation coefficient to evaluate the spatial consistency of the SCNs between these two datasets. Seven and six independent components were identified for Group 1 and Group 2, respectively. Moreover, six SCNs including the posterior default mode network, the visual and auditory networks consistently existed across the two datasets. The overlap ratios and correlation coefficients of the visual network reached the maximums of 72% and 0.71. This study demonstrates the existence of consistent SCNs corresponding to general functional networks. These structural covariance findings may provide insight into the underlying organizational principles of brain anatomy. © 2014 Wiley Periodicals, Inc.
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Yang, Fang; Yang, Min; Hu, Yuehua; Zhang, Juying
2016-01-01
Background Hand, Foot, and Mouth Disease (HFMD) is a worldwide infectious disease. In China, many provinces have reported HFMD cases, especially the south and southwest provinces. Many studies have found a strong association between the incidence of HFMD and climatic factors such as temperature, rainfall, and relative humidity. However, few studies have analyzed cluster effects between various geographical units. Methods The nonlinear relationships and lag effects between weekly HFMD cases and climatic variables were estimated for the period of 2008–2013 using a polynomial distributed lag model. The extra-Poisson multilevel spatial polynomial model was used to model the exact relationship between weekly HFMD incidence and climatic variables after considering cluster effects, provincial correlated structure of HFMD incidence and overdispersion. The smoothing spline methods were used to detect threshold effects between climatic factors and HFMD incidence. Results The HFMD incidence spatial heterogeneity distributed among provinces, and the scale measurement of overdispersion was 548.077. After controlling for long-term trends, spatial heterogeneity and overdispersion, temperature was highly associated with HFMD incidence. Weekly average temperature and weekly temperature difference approximate inverse “V” shape and “V” shape relationships associated with HFMD incidence. The lag effects for weekly average temperature and weekly temperature difference were 3 weeks and 2 weeks. High spatial correlated HFMD incidence were detected in northern, central and southern province. Temperature can be used to explain most of variation of HFMD incidence in southern and northeastern provinces. After adjustment for temperature, eastern and Northern provinces still had high variation HFMD incidence. Conclusion We found a relatively strong association between weekly HFMD incidence and weekly average temperature. The association between the HFMD incidence and climatic variables spatial heterogeneity distributed across provinces. Future research should explore the risk factors that cause spatial correlated structure or high variation of HFMD incidence which can be explained by temperature. When analyzing association between HFMD incidence and climatic variables, spatial heterogeneity among provinces should be evaluated. Moreover, the extra-Poisson multilevel model was capable of modeling the association between overdispersion of HFMD incidence and climatic variables. PMID:26808311
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Liao, Jiaqiang; Yu, Shicheng; Yang, Fang; Yang, Min; Hu, Yuehua; Zhang, Juying
2016-01-01
Hand, Foot, and Mouth Disease (HFMD) is a worldwide infectious disease. In China, many provinces have reported HFMD cases, especially the south and southwest provinces. Many studies have found a strong association between the incidence of HFMD and climatic factors such as temperature, rainfall, and relative humidity. However, few studies have analyzed cluster effects between various geographical units. The nonlinear relationships and lag effects between weekly HFMD cases and climatic variables were estimated for the period of 2008-2013 using a polynomial distributed lag model. The extra-Poisson multilevel spatial polynomial model was used to model the exact relationship between weekly HFMD incidence and climatic variables after considering cluster effects, provincial correlated structure of HFMD incidence and overdispersion. The smoothing spline methods were used to detect threshold effects between climatic factors and HFMD incidence. The HFMD incidence spatial heterogeneity distributed among provinces, and the scale measurement of overdispersion was 548.077. After controlling for long-term trends, spatial heterogeneity and overdispersion, temperature was highly associated with HFMD incidence. Weekly average temperature and weekly temperature difference approximate inverse "V" shape and "V" shape relationships associated with HFMD incidence. The lag effects for weekly average temperature and weekly temperature difference were 3 weeks and 2 weeks. High spatial correlated HFMD incidence were detected in northern, central and southern province. Temperature can be used to explain most of variation of HFMD incidence in southern and northeastern provinces. After adjustment for temperature, eastern and Northern provinces still had high variation HFMD incidence. We found a relatively strong association between weekly HFMD incidence and weekly average temperature. The association between the HFMD incidence and climatic variables spatial heterogeneity distributed across provinces. Future research should explore the risk factors that cause spatial correlated structure or high variation of HFMD incidence which can be explained by temperature. When analyzing association between HFMD incidence and climatic variables, spatial heterogeneity among provinces should be evaluated. Moreover, the extra-Poisson multilevel model was capable of modeling the association between overdispersion of HFMD incidence and climatic variables.
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Latitude delineates patterns of biogeography in terrestrial Streptomyces.
Choudoir, Mallory J; Doroghazi, James R; Buckley, Daniel H
2016-12-01
The biogeography of Streptomyces was examined at regional spatial scales to identify factors that govern patterns of microbial diversity. Streptomyces are spore forming filamentous bacteria which are widespread in soil. Streptomyces strains were isolated from perennial grass habitats sampled across a spatial scale of more than 6000 km. Previous analysis of this geographically explicit culture collection provided evidence for a latitudinal diversity gradient in Streptomyces species. Here the hypothesis that this latitudinal diversity gradient is a result of evolutionary dynamics associated with historical demographic processes was evaluated. Historical demographic phenomena have genetic consequences that can be evaluated through analysis of population genetics. Population genetic approaches were applied to analyze population structure in six of the most numerically abundant and geographically widespread Streptomyces phylogroups from our culture collection. Streptomyces population structure varied at regional spatial scales, and allelic diversity correlated with geographic distance. In addition, allelic diversity and gene flow are partitioned by latitude. Finally, it was found that nucleotide diversity within phylogroups was negatively correlated with latitude. These results indicate that phylogroup diversification is constrained by dispersal limitation at regional spatial scales, and they are consistent with the hypothesis that historical demographic processes have influenced the contemporary biogeography of Streptomyces. © 2016 Society for Applied Microbiology and John Wiley & Sons Ltd.
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Spectral statistics of random geometric graphs
NASA Astrophysics Data System (ADS)
Dettmann, C. P.; Georgiou, O.; Knight, G.
2017-04-01
We use random matrix theory to study the spectrum of random geometric graphs, a fundamental model of spatial networks. Considering ensembles of random geometric graphs we look at short-range correlations in the level spacings of the spectrum via the nearest-neighbour and next-nearest-neighbour spacing distribution and long-range correlations via the spectral rigidity Δ3 statistic. These correlations in the level spacings give information about localisation of eigenvectors, level of community structure and the level of randomness within the networks. We find a parameter-dependent transition between Poisson and Gaussian orthogonal ensemble statistics. That is the spectral statistics of spatial random geometric graphs fits the universality of random matrix theory found in other models such as Erdős-Rényi, Barabási-Albert and Watts-Strogatz random graphs.
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Spatial correlation analysis of cascading failures: Congestions and Blackouts
Daqing, Li; Yinan, Jiang; Rui, Kang; Havlin, Shlomo
2014-01-01
Cascading failures have become major threats to network robustness due to their potential catastrophic consequences, where local perturbations can induce global propagation of failures. Unlike failures spreading via direct contacts due to structural interdependencies, overload failures usually propagate through collective interactions among system components. Despite the critical need in developing protection or mitigation strategies in networks such as power grids and transportation, the propagation behavior of cascading failures is essentially unknown. Here we find by analyzing our collected data that jams in city traffic and faults in power grid are spatially long-range correlated with correlations decaying slowly with distance. Moreover, we find in the daily traffic, that the correlation length increases dramatically and reaches maximum, when morning or evening rush hour is approaching. Our study can impact all efforts towards improving actively system resilience ranging from evaluation of design schemes, development of protection strategies to implementation of mitigation programs. PMID:24946927
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Influence of landscape structure on reef fish assemblages
Grober-Dunsmore, R.; Frazer, T.K.; Beets, J.P.; Lindberg, W.J.; Zwick, P.; Funicelli, N.A.
2008-01-01
Management of tropical marine environments calls for interdisciplinary studies and innovative methodologies that consider processes occurring over broad spatial scales. We investigated relationships between landscape structure and reef fish assemblage structure in the US Virgin Islands. Measures of landscape structure were transformed into a reduced set of composite indices using principal component analyses (PCA) to synthesize data on the spatial patterning of the landscape structure of the study reefs. However, composite indices (e.g., habitat diversity) were not particularly informative for predicting reef fish assemblage structure. Rather, relationships were interpreted more easily when functional groups of fishes were related to individual habitat features. In particular, multiple reef fish parameters were strongly associated with reef context. Fishes responded to benthic habitat structure at multiple spatial scales, with various groups of fishes each correlated to a unique suite of variables. Accordingly, future experiments should be designed to test functional relationships based on the ecology of the organisms of interest. Our study demonstrates that landscape-scale habitat features influence reef fish communities, illustrating promise in applying a landscape ecology approach to better understand factors that structure coral reef ecosystems. Furthermore, our findings may prove useful in design of spatially-based conservation approaches such as marine protected areas (MPAs), because landscape-scale metrics may serve as proxies for areas with high species diversity and abundance within the coral reef landscape. ?? 2007 Springer Science+Business Media B.V.
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Modes in light wave propagating in semiconductor laser
NASA Technical Reports Server (NTRS)
Manko, Margarita A.
1994-01-01
The study of semiconductor laser based on an analogy of the Schrodinger equation and an equation describing light wave propagation in nonhomogeneous medium is developed. The active region of semiconductor laser is considered as optical waveguide confining the electromagnetic field in the cross-section (x,y) and allowing waveguide propagation along the laser resonator (z). The mode structure is investigated taking into account the transversal and what is the important part of the suggested consideration longitudinal nonhomogeneity of the optical waveguide. It is shown that the Gaussian modes in the case correspond to spatial squeezing and correlation. Spatially squeezed two-mode structure of nonhomogeneous optical waveguide is given explicitly. Distribution of light among the laser discrete modes is presented. Properties of the spatially squeezed two-mode field are described. The analog of Franck-Condon principle for finding the maxima of the distribution function and the analog of Ramsauer effect for control of spatial distribution of laser emission are discussed.
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Vibration Response Models of a Stiffened Aluminum Plate Excited by a Shaker
NASA Technical Reports Server (NTRS)
Cabell, Randolph H.
2008-01-01
Numerical models of structural-acoustic interactions are of interest to aircraft designers and the space program. This paper describes a comparison between two energy finite element codes, a statistical energy analysis code, a structural finite element code, and the experimentally measured response of a stiffened aluminum plate excited by a shaker. Different methods for modeling the stiffeners and the power input from the shaker are discussed. The results show that the energy codes (energy finite element and statistical energy analysis) accurately predicted the measured mean square velocity of the plate. In addition, predictions from an energy finite element code had the best spatial correlation with measured velocities. However, predictions from a considerably simpler, single subsystem, statistical energy analysis model also correlated well with the spatial velocity distribution. The results highlight a need for further work to understand the relationship between modeling assumptions and the prediction results.
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Parallel structure among environmental gradients and three trophic levels in a subarctic estuary
Speckman, Suzann G.; Piatt, John F.; Minte-Vera, C. V.; Parrish, Julia K.
2005-01-01
We assessed spatial and temporal variability in the physical environment of a subarctic estuary, and examined concurrent patterns of chlorophyll α abundance (fluorescence), and zooplankton and forage fish community structure. Surveys were conducted in lower Cook Inlet, Alaska, during late July and early August from 1997 through 1999. Principle components analysis (PCA) revealed that spatial heterogeneity in the physical oceanographic environment of lower Cook Inlet could be modeled as three marine-estuarine gradients characterized by temperature, salinity, bottom depth, and turbidity. The gradients persisted from 1997 through 1999, and PCA explained 68% to 92% of the variance in physical oceanography for each gradient-year combination. Correlations between chlorophyll α abundance and distribution and the PCA axes were weak. Chlorophyll was reduced by turbidity, and low levels occurred in areas with high levels of suspended sediments. Detrended correspondence analysis (DCA) was used to order the sample sites based on species composition and to order the zooplankton and forage fish taxa based on similarities among sample sites for each gradient-year. Correlations between the structure of the physical environment (PCA axis 1) and zooplankton community structure (DCA axis 1) were strong (r = 0.43-0.86) in all years for the three marine-estuarine gradients, suggesting that zooplankton community composition was structured by the physical environment. The physical environment (PCA) and forage fish community structure (DCA) were weakly correlated in all years along Gradient 2, defined by halocline intensity and surface temperature and salinity, even though these physical variables were more important for defining zooplankton habitats. However, the physical environment (PCA) and forage fish community structure (DCA) were strongly correlated along the primary marine-estuarine gradient (#1) in 1997 (r = 0.87) and 1998 (r = 0.82). The correlation was poor (r = 0.32) in 1999, when fish community structure changed markedly in lower Cook Inlet. Capelin (Mallotus villosus), walleye pollock (Theragra chalcogramma), and arrowtooth flounder (Atheresthes stomias) were caught farther north than in previous years. Waters were significantly colder and more saline in 1999, a La Nina year, than in other years of the study. Interannual fluctuations in environmental conditions in lower Cook Inlet did not have substantial effects on zooplankton community structure, although abundance of individual taxa varied significantly. The abundance and distribution of chlorophyll α, zooplankton and forage fish were affected much more by spatial variability in physical oceanography than by interannual variability. Our examination of physical-biological linkages in lower Cook Inlet supports the concept of "bottom-up control," i.e., that variability in the physical environment structures higher trophic-level communities by influencing their distribution and abundance across space.
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Parallel structure among environmental gradients and three trophic levels in a subarctic estuary
NASA Astrophysics Data System (ADS)
Speckman, Suzann G.; Piatt, John F.; Minte-Vera, Carolina V.; Parrish, Julia K.
2005-07-01
We assessed spatial and temporal variability in the physical environment of a subarctic estuary, and examined concurrent patterns of chlorophyll α abundance (fluorescence), and zooplankton and forage fish community structure. Surveys were conducted in lower Cook Inlet, Alaska, during late July and early August from 1997 through 1999. Principle components analysis (PCA) revealed that spatial heterogeneity in the physical oceanographic environment of lower Cook Inlet could be modeled as three marine-estuarine gradients characterized by temperature, salinity, bottom depth, and turbidity. The gradients persisted from 1997 through 1999, and PCA explained 68% to 92% of the variance in physical oceanography for each gradient-year combination. Correlations between chlorophyll α abundance and distribution and the PCA axes were weak. Chlorophyll was reduced by turbidity, and low levels occurred in areas with high levels of suspended sediments. Detrended correspondence analysis (DCA) was used to order the sample sites based on species composition and to order the zooplankton and forage fish taxa based on similarities among sample sites for each gradient-year. Correlations between the structure of the physical environment (PCA axis 1) and zooplankton community structure (DCA axis 1) were strong ( r = 0.43-0.86) in all years for the three marine-estuarine gradients, suggesting that zooplankton community composition was structured by the physical environment. The physical environment (PCA) and forage fish community structure (DCA) were weakly correlated in all years along Gradient 2, defined by halocline intensity and surface temperature and salinity, even though these physical variables were more important for defining zooplankton habitats. However, the physical environment (PCA) and forage fish community structure (DCA) were strongly correlated along the primary marine-estuarine gradient (#1) in 1997 ( r = 0.87) and 1998 ( r = 0.82). The correlation was poor ( r = 0.32) in 1999, when fish community structure changed markedly in lower Cook Inlet. Capelin ( Mallotus villosus), walleye pollock ( Theragra chalcogramma), and arrowtooth flounder ( Atheresthes stomias) were caught farther north than in previous years. Waters were significantly colder and more saline in 1999, a La Niña year, than in other years of the study. Interannual fluctuations in environmental conditions in lower Cook Inlet did not have substantial effects on zooplankton community structure, although abundance of individual taxa varied significantly. The abundance and distribution of chlorophyll α, zooplankton and forage fish were affected much more by spatial variability in physical oceanography than by interannual variability. Our examination of physical-biological linkages in lower Cook Inlet supports the concept of “bottom-up control,” i.e., that variability in the physical environment structures higher trophic-level communities by influencing their distribution and abundance across space.
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Spatial Correlation of Solar-Wind Turbulence from Two-Point Measurements
NASA Technical Reports Server (NTRS)
Matthaeus, W. H.; Milano, L. J.; Dasso, S.; Weygand, J. M.; Smith, C. W.; Kivelson, M. G.
2005-01-01
Interplanetary turbulence, the best studied case of low frequency plasma turbulence, is the only directly quantified instance of astrophysical turbulence. Here, magnetic field correlation analysis, using for the first time only proper two-point, single time measurements, provides a key step in unraveling the space-time structure of interplanetary turbulence. Simultaneous magnetic field data from the Wind, ACE, and Cluster spacecraft are analyzed to determine the correlation (outer) scale, and the Taylor microscale near Earth's orbit.
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Kistemann, Thomas; Zimmer, Sonja; Vågsholm, Ivar; Andersson, Yvonne
2004-01-01
This article describes the spatial and temporal distribution of verotoxin-producing Escherichia coli among humans (EHEC) and cattle (VTEC) in Sweden, in order to evaluate relationships between the incidence of EHEC in humans, prevalence of VTEC O157 in livestock and agricultural structure by an ecological study. The spatial patterns of the distribution of human infections were described and compared with spatial patterns of occurrence in cattle, using a Geographic Information System (GIS). The findings implicate a concentration of human infection and cattle prevalence in the southwest of Sweden. The use of probability mapping confirmed unusual patterns of infection rates. The comparison of human and cattle infection indicated a spatial and statistical association. The correlation between variables of the agricultural structure and human EHEC incidence was high, indicating a significant statistical association of cattle and farm density with human infection. The explained variation of a multiple linear regression model was 0.56. PMID:15188718
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Chen, Shi; Ilany, Amiyaal; White, Brad J; Sanderson, Michael W; Lanzas, Cristina
2015-01-01
Animal social network is the key to understand many ecological and epidemiological processes. We used real-time location system (RTLS) to accurately track cattle position, analyze their proximity networks, and tested the hypothesis of temporal stationarity and spatial homogeneity in these networks during different daily time periods and in different areas of the pen. The network structure was analyzed using global network characteristics (network density), subgroup clustering (modularity), triadic property (transitivity), and dyadic interactions (correlation coefficient from a quadratic assignment procedure) at hourly level. We demonstrated substantial spatial-temporal heterogeneity in these networks and potential link between indirect animal-environment contact and direct animal-animal contact. But such heterogeneity diminished if data were collected at lower spatial (aggregated at entire pen level) or temporal (aggregated at daily level) resolution. The network structure (described by the characteristics such as density, modularity, transitivity, etc.) also changed substantially at different time and locations. There were certain time (feeding) and location (hay) that the proximity network structures were more consistent based on the dyadic interaction analysis. These results reveal new insights for animal network structure and spatial-temporal dynamics, provide more accurate descriptions of animal social networks, and allow more accurate modeling of multiple (both direct and indirect) disease transmission pathways.
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ERIC Educational Resources Information Center
Keeley, Robin J.; Wartman, Brianne C.; Hausler, Alexander N.; Holahan, Matthew R.
2010-01-01
Research has demonstrated that Long-Evans rats (LER) display superior mnemonic function over Wistar rats (WR). These differences are correlated with endogenous and input-dependent properties of the hippocampus. The present work sought to determine if juvenile pretraining might enhance hippocampal structural markers and if this would be associated…
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Spatiotemporal correlation structure of the Earth's surface temperature
NASA Astrophysics Data System (ADS)
Fredriksen, Hege-Beate; Rypdal, Kristoffer; Rypdal, Martin
2015-04-01
We investigate the spatiotemporal temperature variability for several gridded instrumental and climate model data sets. The temporal variability is analysed by estimating the power spectral density and studying the differences between local and global temperatures, land and sea, and among local temperature records at different locations. The spatiotemporal correlation structure is analysed through cross-spectra that allow us to compute frequency-dependent spatial autocorrelation functions (ACFs). Our results are then compared to theoretical spectra and frequency-dependent spatial ACFs derived from a fractional stochastic-diffusive energy balance model (FEBM). From the FEBM we expect both local and global temperatures to have a long-range persistent temporal behaviour, and the spectral exponent (β) is expected to increase by a factor of two when going from local to global scales. Our comparison of the average local spectrum and the global spectrum shows good agreement with this model, although the FEBM has so far only been studied for a pure land planet and a pure ocean planet, respectively, with no seasonal forcing. Hence it cannot capture the substantial variability among the local spectra, in particular between the spectra for land and sea, and for equatorial and non-equatorial temperatures. Both models and observation data show that land temperatures in general have a low persistence, while sea surface temperatures show a higher, and also more variable degree of persistence. Near the equator the spectra deviate from the power-law shape expected from the FEBM. Instead we observe large variability at time scales of a few years due to ENSO, and a flat spectrum at longer time scales, making the spectrum more reminiscent of that of a red noise process. From the frequency-dependent spatial ACFs we observe that the spatial correlation length increases with increasing time scale, which is also consistent with the FEBM. One consequence of this is that longer-lasting structures must also be wider in space. The spatial correlation length is also observed to be longer for land than for sea. The climate model simulations studied are mainly CMIP5 control runs of length 500-1000 yr. On time scales up to several centuries we do not observe that the difference between the local and global spectral exponents vanish. This also follows from the FEBM and shows that the dynamics is spatiotemporal (not just temporal) even on these time scales.
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Is a matrix exponential specification suitable for the modeling of spatial correlation structures?
Strauß, Magdalena E.; Mezzetti, Maura; Leorato, Samantha
2018-01-01
This paper investigates the adequacy of the matrix exponential spatial specifications (MESS) as an alternative to the widely used spatial autoregressive models (SAR). To provide as complete a picture as possible, we extend the analysis to all the main spatial models governed by matrix exponentials comparing them with their spatial autoregressive counterparts. We propose a new implementation of Bayesian parameter estimation for the MESS model with vague prior distributions, which is shown to be precise and computationally efficient. Our implementations also account for spatially lagged regressors. We further allow for location-specific heterogeneity, which we model by including spatial splines. We conclude by comparing the performances of the different model specifications in applications to a real data set and by running simulations. Both the applications and the simulations suggest that the spatial splines are a flexible and efficient way to account for spatial heterogeneities governed by unknown mechanisms. PMID:29492375
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Georgiades, Anna; Rijsdijk, Fruhling; Kane, Fergus; Rebollo-Mesa, Irene; Kalidindi, Sridevi; Schulze, Katja K; Stahl, Daniel; Walshe, Muriel; Sahakian, Barbara J; McDonald, Colm; Hall, Mei-Hua; Murray, Robin M; Kravariti, Eugenia
2016-06-01
Twin studies have lacked statistical power to apply advanced genetic modelling techniques to the search for cognitive endophenotypes for bipolar disorder. To quantify the shared genetic variability between bipolar disorder and cognitive measures. Structural equation modelling was performed on cognitive data collected from 331 twins/siblings of varying genetic relatedness, disease status and concordance for bipolar disorder. Using a parsimonious AE model, verbal episodic and spatial working memory showed statistically significant genetic correlations with bipolar disorder (rg = |0.23|-|0.27|), which lost statistical significance after covarying for affective symptoms. Using an ACE model, IQ and visual-spatial learning showed statistically significant genetic correlations with bipolar disorder (rg = |0.51|-|1.00|), which remained significant after covarying for affective symptoms. Verbal episodic and spatial working memory capture a modest fraction of the bipolar diathesis. IQ and visual-spatial learning may tap into genetic substrates of non-affective symptomatology in bipolar disorder. © The Royal College of Psychiatrists 2016.
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Jiménez, Juan J; Decaëns, Thibaud; Lavelle, Patrick; Rossi, Jean-Pierre
2014-12-05
Studying the drivers and determinants of species, population and community spatial patterns is central to ecology. The observed structure of community assemblages is the result of deterministic abiotic (environmental constraints) and biotic factors (positive and negative species interactions), as well as stochastic colonization events (historical contingency). We analyzed the role of multi-scale spatial component of soil environmental variability in structuring earthworm assemblages in a gallery forest from the Colombian "Llanos". We aimed to disentangle the spatial scales at which species assemblages are structured and determine whether these scales matched those expressed by soil environmental variables. We also tested the hypothesis of the "single tree effect" by exploring the spatial relationships between root-related variables and soil nutrient and physical variables in structuring earthworm assemblages. Multivariate ordination techniques and spatially explicit tools were used, namely cross-correlograms, Principal Coordinates of Neighbor Matrices (PCNM) and variation partitioning analyses. The relationship between the spatial organization of earthworm assemblages and soil environmental parameters revealed explicitly multi-scale responses. The soil environmental variables that explained nested population structures across the multi-spatial scale gradient differed for earthworms and assemblages at the very-fine- (<10 m) to medium-scale (10-20 m). The root traits were correlated with areas of high soil nutrient contents at a depth of 0-5 cm. Information on the scales of PCNM variables was obtained using variogram modeling. Based on the size of the plot, the PCNM variables were arbitrarily allocated to medium (>30 m), fine (10-20 m) and very fine scales (<10 m). Variation partitioning analysis revealed that the soil environmental variability explained from less than 1% to as much as 48% of the observed earthworm spatial variation. A large proportion of the spatial variation did not depend on the soil environmental variability for certain species. This finding could indicate the influence of contagious biotic interactions, stochastic factors, or unmeasured relevant soil environmental variables.
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Spatial Competition: Roughening of an Experimental Interface.
Allstadt, Andrew J; Newman, Jonathan A; Walter, Jonathan A; Korniss, G; Caraco, Thomas
2016-07-28
Limited dispersal distance generates spatial aggregation. Intraspecific interactions are then concentrated within clusters, and between-species interactions occur near cluster boundaries. Spread of a locally dispersing invader can become motion of an interface between the invading and resident species, and spatial competition will produce variation in the extent of invasive advance along the interface. Kinetic roughening theory offers a framework for quantifying the development of these fluctuations, which may structure the interface as a self-affine fractal, and so induce a series of temporal and spatial scaling relationships. For most clonal plants, advance should become spatially correlated along the interface, and width of the interface (where invader and resident compete directly) should increase as a power function of time. Once roughening equilibrates, interface width and the relative location of the most advanced invader should each scale with interface length. We tested these predictions by letting white clover (Trifolium repens) invade ryegrass (Lolium perenne). The spatial correlation of clover growth developed as anticipated by kinetic roughening theory, and both interface width and the most advanced invader's lead scaled with front length. However, the scaling exponents differed from those predicted by recent simulation studies, likely due to clover's growth morphology.
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Spatial Competition: Roughening of an Experimental Interface
Allstadt, Andrew J.; Newman, Jonathan A.; Walter, Jonathan A.; Korniss, G.; Caraco, Thomas
2016-01-01
Limited dispersal distance generates spatial aggregation. Intraspecific interactions are then concentrated within clusters, and between-species interactions occur near cluster boundaries. Spread of a locally dispersing invader can become motion of an interface between the invading and resident species, and spatial competition will produce variation in the extent of invasive advance along the interface. Kinetic roughening theory offers a framework for quantifying the development of these fluctuations, which may structure the interface as a self-affine fractal, and so induce a series of temporal and spatial scaling relationships. For most clonal plants, advance should become spatially correlated along the interface, and width of the interface (where invader and resident compete directly) should increase as a power function of time. Once roughening equilibrates, interface width and the relative location of the most advanced invader should each scale with interface length. We tested these predictions by letting white clover (Trifolium repens) invade ryegrass (Lolium perenne). The spatial correlation of clover growth developed as anticipated by kinetic roughening theory, and both interface width and the most advanced invader’s lead scaled with front length. However, the scaling exponents differed from those predicted by recent simulation studies, likely due to clover’s growth morphology. PMID:27465518
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The Purine Bias of Coding Sequences is Determined by Physicochemical Constraints on Proteins.
Ponce de Leon, Miguel; de Miranda, Antonio Basilio; Alvarez-Valin, Fernando; Carels, Nicolas
2014-01-01
For this report, we analyzed protein secondary structures in relation to the statistics of three nucleotide codon positions. The purpose of this investigation was to find which properties of the ribosome, tRNA or protein level, could explain the purine bias (Rrr) as it is observed in coding DNA. We found that the Rrr pattern is the consequence of a regularity (the codon structure) resulting from physicochemical constraints on proteins and thermodynamic constraints on ribosomal machinery. The physicochemical constraints on proteins mainly come from the hydropathy and molecular weight (MW) of secondary structures as well as the energy cost of amino acid synthesis. These constraints appear through a network of statistical correlations, such as (i) the cost of amino acid synthesis, which is in favor of a higher level of guanine in the first codon position, (ii) the constructive contribution of hydropathy alternation in proteins, (iii) the spatial organization of secondary structure in proteins according to solvent accessibility, (iv) the spatial organization of secondary structure according to amino acid hydropathy, (v) the statistical correlation of MW with protein secondary structures and their overall hydropathy, (vi) the statistical correlation of thymine in the second codon position with hydropathy and the energy cost of amino acid synthesis, and (vii) the statistical correlation of adenine in the second codon position with amino acid complexity and the MW of secondary protein structures. Amino acid physicochemical properties and functional constraints on proteins constitute a code that is translated into a purine bias within the coding DNA via tRNAs. In that sense, the Rrr pattern within coding DNA is the effect of information transfer on nucleotide composition from protein to DNA by selection according to the codon positions. Thus, coding DNA structure and ribosomal machinery co-evolved to minimize the energy cost of protein coding given the functional constraints on proteins.
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Fine-scale population dynamics in a marine fish species inferred from dynamic state-space models.
Rogers, Lauren A; Storvik, Geir O; Knutsen, Halvor; Olsen, Esben M; Stenseth, Nils C
2017-07-01
Identifying the spatial scale of population structuring is critical for the conservation of natural populations and for drawing accurate ecological inferences. However, population studies often use spatially aggregated data to draw inferences about population trends and drivers, potentially masking ecologically relevant population sub-structure and dynamics. The goals of this study were to investigate how population dynamics models with and without spatial structure affect inferences on population trends and the identification of intrinsic drivers of population dynamics (e.g. density dependence). Specifically, we developed dynamic, age-structured, state-space models to test different hypotheses regarding the spatial structure of a population complex of coastal Atlantic cod (Gadus morhua). Data were from a 93-year survey of juvenile (age 0 and 1) cod sampled along >200 km of the Norwegian Skagerrak coast. We compared two models: one which assumes all sampled cod belong to one larger population, and a second which assumes that each fjord contains a unique population with locally determined dynamics. Using the best supported model, we then reconstructed the historical spatial and temporal dynamics of Skagerrak coastal cod. Cross-validation showed that the spatially structured model with local dynamics had better predictive ability. Furthermore, posterior predictive checks showed that a model which assumes one homogeneous population failed to capture the spatial correlation pattern present in the survey data. The spatially structured model indicated that population trends differed markedly among fjords, as did estimates of population parameters including density-dependent survival. Recent biomass was estimated to be at a near-record low all along the coast, but the finer scale model indicated that the decline occurred at different times in different regions. Warm temperatures were associated with poor recruitment, but local changes in habitat and fishing pressure may have played a role in driving local dynamics. More generally, we demonstrated how state-space models can be used to test evidence for population spatial structure based on survey time-series data. Our study shows the importance of considering spatially structured dynamics, as the inferences from such an approach can lead to a different ecological understanding of the drivers of population declines, and fundamentally different management actions to restore populations. © 2017 The Authors. Journal of Animal Ecology published by John Wiley & Sons Ltd on behalf of British Ecological Society.
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NASA Astrophysics Data System (ADS)
Wu, Kai; Shu, Hong; Nie, Lei; Jiao, Zhenhang
2018-01-01
Spatially correlated errors are typically ignored in data assimilation, thus degenerating the observation error covariance R to a diagonal matrix. We argue that a nondiagonal R carries more observation information making assimilation results more accurate. A method, denoted TC_Cov, was proposed for soil moisture data assimilation to estimate spatially correlated observation error covariance based on triple collocation (TC). Assimilation experiments were carried out to test the performance of TC_Cov. AMSR-E soil moisture was assimilated with a diagonal R matrix computed using the TC and assimilated using a nondiagonal R matrix, as estimated by proposed TC_Cov. The ensemble Kalman filter was considered as the assimilation method. Our assimilation results were validated against climate change initiative data and ground-based soil moisture measurements using the Pearson correlation coefficient and unbiased root mean square difference metrics. These experiments confirmed that deterioration of diagonal R assimilation results occurred when model simulation is more accurate than observation data. Furthermore, nondiagonal R achieved higher correlation coefficient and lower ubRMSD values over diagonal R in experiments and demonstrated the effectiveness of TC_Cov to estimate richly structuralized R in data assimilation. In sum, compared with diagonal R, nondiagonal R may relieve the detrimental effects of assimilation when simulated model results outperform observation data.
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Spatial patterns and broad-scale weather cues of beech mast seeding in Europe.
Vacchiano, Giorgio; Hacket-Pain, Andrew; Turco, Marco; Motta, Renzo; Maringer, Janet; Conedera, Marco; Drobyshev, Igor; Ascoli, Davide
2017-07-01
Mast seeding is a crucial population process in many tree species, but its spatio-temporal patterns and drivers at the continental scale remain unknown . Using a large dataset (8000 masting observations across Europe for years 1950-2014) we analysed the spatial pattern of masting across the entire geographical range of European beech, how it is influenced by precipitation, temperature and drought, and the temporal and spatial stability of masting-weather correlations. Beech masting exhibited a general distance-dependent synchronicity and a pattern structured in three broad geographical groups consistent with continental climate regimes. Spearman's correlations and logistic regression revealed a general pattern of beech masting correlating negatively with temperature in the summer 2 yr before masting, and positively with summer temperature 1 yr before masting (i.e. 2T model). The temperature difference between the two previous summers (DeltaT model) was also a good predictor. Moving correlation analysis applied to the longest eight chronologies (74-114 yr) revealed stable correlations between temperature and masting, confirming consistency in weather cues across space and time. These results confirm widespread dependency of masting on temperature and lend robustness to the attempts to reconstruct and predict mast years using temperature data. © 2017 The Authors. New Phytologist © 2017 New Phytologist Trust.
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Probing GFP-actin diffusion in living cells using fluorescence correlation spectroscopy.
Engelke, Hanna; Heinrich, Doris; Rädler, Joachim O
2010-12-22
The cytoskeleton of eukaryotic cells is continuously remodeled by polymerization and depolymerization of actin. Consequently, the relative content of polymerized filamentous actin (F-actin) and monomeric globular actin (G-actin) is subject to temporal and spatial fluctuations. Since fluorescence correlation spectroscopy (FCS) can measure the diffusion of fluorescently labeled actin it seems likely that FCS allows us to determine the dynamics and hence indirectly the structural properties of the cytoskeleton components with high spatial resolution. To this end we investigate the FCS signal of GFP-actin in living Dictyostelium discoideum cells and explore the inherent spatial and temporal signatures of the actin cytoskeleton. Using the free green fluorescent protein (GFP) as a reference, we find that actin diffusion inside cells is dominated by G-actin and slower than diffusion in diluted cell extract. The FCS signal in the dense cortical F-actin network near the cell membrane is probed using the cytoskeleton protein LIM and is found to be slower than cytosolic G-actin diffusion. Furthermore, we show that polymerization of the cytoskeleton induced by Jasplakinolide leads to a substantial decrease of G-actin diffusion. Pronounced fluctuations in the distribution of the FCS correlation curves can be induced by latrunculin, which is known to induce actin waves. Our work suggests that the FCS signal of GFP-actin in combination with scanning or spatial correlation techniques yield valuable information about the local dynamics and concomitant cytoskeletal properties.
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Optical Measurement of In-plane Waves in Mechanical Metamaterials Through Digital Image Correlation
NASA Astrophysics Data System (ADS)
Schaeffer, Marshall; Trainiti, Giuseppe; Ruzzene, Massimo
2017-02-01
We report on a Digital Image Correlation-based technique for the detection of in-plane elastic waves propagating in structural lattices. The experimental characterization of wave motion in lattice structures is currently of great interest due its relevance to the design of novel mechanical metamaterials with unique/unusual properties such as strongly directional behaviour, negative refractive indexes and topologically protected wave motion. Assessment of these functionalities often requires the detection of highly spatially resolved in-plane wavefields, which for reticulated or porous structural assemblies is an open challenge. A Digital Image Correlation approach is implemented that tracks small displacements of the lattice nodes by centring image subsets about the lattice intersections. A high speed camera records the motion of the points by properly interleaving subse- quent frames thus artificially enhancing the available sampling rate. This, along with an imaging stitching procedure, enables the capturing of a field of view that is sufficiently large for subsequent processing. The transient response is recorded in the form of the full wavefields, which are processed to unveil features of wave motion in a hexagonal lattice. Time snapshots and frequency contours in the spatial Fourier domain are compared with numerical predictions to illustrate the accuracy of the recorded wavefields.
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Haney, Matthew M.; Mikesell, T. Dylan; van Wijk, Kasper; Nakahara, Hisashi
2012-01-01
Using ambient seismic noise for imaging subsurface structure dates back to the development of the spatial autocorrelation (SPAC) method in the 1950s. We present a theoretical analysis of the SPAC method for multicomponent recordings of surface waves to determine the complete 3 × 3 matrix of correlations between all pairs of three-component motions, called the correlation matrix. In the case of isotropic incidence, when either Rayleigh or Love waves arrive from all directions with equal power, the only non-zero off-diagonal terms in the matrix are the vertical–radial (ZR) and radial–vertical (RZ) correlations in the presence of Rayleigh waves. Such combinations were not considered in the development of the SPAC method. The method originally addressed the vertical–vertical (ZZ), RR and TT correlations, hence the name spatial autocorrelation. The theoretical expressions we derive for the ZR and RZ correlations offer additional ways to measure Rayleigh wave dispersion within the SPAC framework. Expanding on the results for isotropic incidence, we derive the complete correlation matrix in the case of generally anisotropic incidence. We show that the ZR and RZ correlations have advantageous properties in the presence of an out-of-plane directional wavefield compared to ZZ and RR correlations. We apply the results for mixed-component correlations to a data set from Akutan Volcano, Alaska and find consistent estimates of Rayleigh wave phase velocity from ZR compared to ZZ correlations. This work together with the recently discovered connections between the SPAC method and time-domain correlations of ambient noise provide further insights into the retrieval of surface wave Green’s functions from seismic noise.
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Large-scale changes in network interactions as a physiological signature of spatial neglect.
Baldassarre, Antonello; Ramsey, Lenny; Hacker, Carl L; Callejas, Alicia; Astafiev, Serguei V; Metcalf, Nicholas V; Zinn, Kristi; Rengachary, Jennifer; Snyder, Abraham Z; Carter, Alex R; Shulman, Gordon L; Corbetta, Maurizio
2014-12-01
The relationship between spontaneous brain activity and behaviour following focal injury is not well understood. Here, we report a large-scale study of resting state functional connectivity MRI and spatial neglect following stroke in a large (n=84) heterogeneous sample of first-ever stroke patients (within 1-2 weeks). Spatial neglect, which is typically more severe after right than left hemisphere injury, includes deficits of spatial attention and motor actions contralateral to the lesion, and low general attention due to impaired vigilance/arousal. Patients underwent structural and resting state functional MRI scans, and spatial neglect was measured using the Posner spatial cueing task, and Mesulam and Behavioural Inattention Test cancellation tests. A principal component analysis of the behavioural tests revealed a main factor accounting for 34% of variance that captured three correlated behavioural deficits: visual neglect of the contralesional visual field, visuomotor neglect of the contralesional field, and low overall performance. In an independent sample (21 healthy subjects), we defined 10 resting state networks consisting of 169 brain regions: visual-fovea and visual-periphery, sensory-motor, auditory, dorsal attention, ventral attention, language, fronto-parietal control, cingulo-opercular control, and default mode. We correlated the neglect factor score with the strength of resting state functional connectivity within and across the 10 resting state networks. All damaged brain voxels were removed from the functional connectivity:behaviour correlational analysis. We found that the correlated behavioural deficits summarized by the factor score were associated with correlated multi-network patterns of abnormal functional connectivity involving large swaths of cortex. Specifically, dorsal attention and sensory-motor networks showed: (i) reduced interhemispheric functional connectivity; (ii) reduced anti-correlation with fronto-parietal and default mode networks in the right hemisphere; and (iii) increased intrahemispheric connectivity with the basal ganglia. These patterns of functional connectivity:behaviour correlations were stronger in patients with right- as compared to left-hemisphere damage and were independent of lesion volume. Our findings identify large-scale changes in resting state network interactions that are a physiological signature of spatial neglect and may relate to its right hemisphere lateralization. © The Author (2014). Published by Oxford University Press on behalf of the Guarantors of Brain. All rights reserved. For Permissions, please email: journals.permissions@oup.com.
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DNA viewed as an out-of-equilibrium structure
NASA Astrophysics Data System (ADS)
Provata, A.; Nicolis, C.; Nicolis, G.
2014-05-01
The complexity of the primary structure of human DNA is explored using methods from nonequilibrium statistical mechanics, dynamical systems theory, and information theory. A collection of statistical analyses is performed on the DNA data and the results are compared with sequences derived from different stochastic processes. The use of χ2 tests shows that DNA can not be described as a low order Markov chain of order up to r =6. Although detailed balance seems to hold at the level of a binary alphabet, it fails when all four base pairs are considered, suggesting spatial asymmetry and irreversibility. Furthermore, the block entropy does not increase linearly with the block size, reflecting the long-range nature of the correlations in the human genomic sequences. To probe locally the spatial structure of the chain, we study the exit distances from a specific symbol, the distribution of recurrence distances, and the Hurst exponent, all of which show power law tails and long-range characteristics. These results suggest that human DNA can be viewed as a nonequilibrium structure maintained in its state through interactions with a constantly changing environment. Based solely on the exit distance distribution accounting for the nonequilibrium statistics and using the Monte Carlo rejection sampling method, we construct a model DNA sequence. This method allows us to keep both long- and short-range statistical characteristics of the native DNA data. The model sequence presents the same characteristic exponents as the natural DNA but fails to capture spatial correlations and point-to-point details.
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NASA Astrophysics Data System (ADS)
Anderson, C. S.; Gaensler, B. M.; Heald, G. H.; O’Sullivan, S. P.; Kaczmarek, J. F.; Feain, I. J.
2018-03-01
We present observations and analysis of the polarized radio emission from the nearby radio galaxy Fornax A over 1.28–3.1 GHz, using data from the Australia Telescope Compact Array. In this, the first of two associated papers, we use modern broadband polarimetric techniques to examine the nature and origin of conspicuous low-polarization (low-p) patches in the lobes. We resolve the (low-p) patches and find that their low fractional polarization is associated with complicated frequency-dependent interference in the polarized signal generated by Faraday effects along the line of sight (LOS). The low-p patches are spatially correlated with interfaces in the magnetic structure of the lobe, across which the LOS-projected magnetic field changes direction. Spatial correlations with the sky-projected magnetic field orientation and structure in total intensity are also identified and discussed. We argue that the (low-p) patches, along with associated reversals in the LOS magnetic field and other related phenomena, are best explained by the presence of { \\mathcal O }({10}9) {M}ȯ of magnetized thermal plasma in the lobes, structured in shells or filaments, and likely advected from the interstellar medium of NCG 1316 or its surrounding intracluster medium. Our study underscores the power and utility of spatially resolved, broadband, full-polarization radio observations to reveal new facets of flow behaviors and magneto-ionic structure in radio lobes and their interplay with the surrounding environment.
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DNA viewed as an out-of-equilibrium structure.
Provata, A; Nicolis, C; Nicolis, G
2014-05-01
The complexity of the primary structure of human DNA is explored using methods from nonequilibrium statistical mechanics, dynamical systems theory, and information theory. A collection of statistical analyses is performed on the DNA data and the results are compared with sequences derived from different stochastic processes. The use of χ^{2} tests shows that DNA can not be described as a low order Markov chain of order up to r=6. Although detailed balance seems to hold at the level of a binary alphabet, it fails when all four base pairs are considered, suggesting spatial asymmetry and irreversibility. Furthermore, the block entropy does not increase linearly with the block size, reflecting the long-range nature of the correlations in the human genomic sequences. To probe locally the spatial structure of the chain, we study the exit distances from a specific symbol, the distribution of recurrence distances, and the Hurst exponent, all of which show power law tails and long-range characteristics. These results suggest that human DNA can be viewed as a nonequilibrium structure maintained in its state through interactions with a constantly changing environment. Based solely on the exit distance distribution accounting for the nonequilibrium statistics and using the Monte Carlo rejection sampling method, we construct a model DNA sequence. This method allows us to keep both long- and short-range statistical characteristics of the native DNA data. The model sequence presents the same characteristic exponents as the natural DNA but fails to capture spatial correlations and point-to-point details.
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Application of biospeckles for assessment of structural and cellular changes in muscle tissue
NASA Astrophysics Data System (ADS)
Maksymenko, Oleksandr P.; Muravsky, Leonid I.; Berezyuk, Mykola I.
2015-09-01
A modified spatial-temporal speckle correlation technique for operational assessment of structural changes in muscle tissues after slaughtering is considered. Coefficient of biological activity as a quantitative indicator of structural changes of biochemical processes in biological tissues is proposed. The experimental results have shown that this coefficient properly evaluates the biological activity of pig and chicken muscle tissue samples. Studying the degradation processes in muscle tissue during long-time storage in a refrigerator by measuring the spatial-temporal dynamics of biospeckle patterns is carried out. The reduction of the bioactivity level of refrigerated muscle tissue samples connected with the initiation of muscle fiber cracks and ruptures, reduction of sarcomeres, nuclei deformation, nuclear chromatin diminishing, and destruction of mitochondria is analyzed.
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NASA Astrophysics Data System (ADS)
Bonef, Bastien; Grenier, Adeline; Gerard, Lionel; Jouneau, Pierre-Henri; André, Regis; Blavette, Didier; Bougerol, Catherine
2018-02-01
The correlative use of atom probe tomography (APT) and energy dispersive x-ray spectroscopy in scanning transmission electron microscopy (STEM) allows us to characterize the structure of ZnTe/CdSe superlattices at the nanometre scale. Both techniques reveal the segregation of zinc along [111] stacking faults in CdSe layers, which is interpreted as a manifestation of the Suzuki effect. Quantitative measurements reveal a zinc enrichment around 9 at. % correlated with a depletion of cadmium in the stacking faults. Raw concentration data were corrected so as to account for the limited spatial resolution of both STEM and APT techniques. A simple calculation reveals that the stacking faults are almost saturated in Zn atoms (˜66 at. % of Zn) at the expense of Cd that is depleted.
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NASA Astrophysics Data System (ADS)
Nampally, Subhadra; Padhy, Simanchal; Dimri, Vijay P.
2018-01-01
The nature of spatial distribution of heterogeneities in the source area of the 2015 Nepal earthquake is characterized based on the seismic b-value and fractal analysis of its aftershocks. The earthquake size distribution of aftershocks gives a b-value of 1.11 ± 0.08, possibly representing the highly heterogeneous and low stress state of the region. The aftershocks exhibit a fractal structure characterized by a spectrum of generalized dimensions, Dq varying from D2 = 1.66 to D22 = 0.11. The existence of a fractal structure suggests that the spatial distribution of aftershocks is not a random phenomenon, but it self-organizes into a critical state, exhibiting a scale-independent structure governed by a power-law scaling, where a small perturbation in stress is sufficient enough to trigger aftershocks. In order to obtain the bias in fractal dimensions resulting from finite data size, we compared the multifractal spectrum for the real data and random simulations. On comparison, we found that the lower limit of bias in D2 is 0.44. The similarity in their multifractal spectra suggests the lack of long-range correlation in the data, with an only weakly multifractal or a monofractal with a single correlation dimension D2 characterizing the data. The minimum number of events required for a multifractal process with an acceptable error is discussed. We also tested for a possible correlation between changes in D2 and energy released during the earthquakes. The values of D2 rise during the two largest earthquakes (M > 7.0) in the sequence. The b- and D2 values are related by D2 = 1.45 b that corresponds to the intermediate to large earthquakes. Our results provide useful constraints on the spatial distribution of b- and D2-values, which are useful for seismic hazard assessment in the aftershock area of a large earthquake.
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Loescher, Henry; Ayres, Edward; Duffy, Paul; Luo, Hongyan; Brunke, Max
2014-01-01
Soils are highly variable at many spatial scales, which makes designing studies to accurately estimate the mean value of soil properties across space challenging. The spatial correlation structure is critical to develop robust sampling strategies (e.g., sample size and sample spacing). Current guidelines for designing studies recommend conducting preliminary investigation(s) to characterize this structure, but are rarely followed and sampling designs are often defined by logistics rather than quantitative considerations. The spatial variability of soils was assessed across ∼1 ha at 60 sites. Sites were chosen to represent key US ecosystems as part of a scaling strategy deployed by the National Ecological Observatory Network. We measured soil temperature (Ts) and water content (SWC) because these properties mediate biological/biogeochemical processes below- and above-ground, and quantified spatial variability using semivariograms to estimate spatial correlation. We developed quantitative guidelines to inform sample size and sample spacing for future soil studies, e.g., 20 samples were sufficient to measure Ts to within 10% of the mean with 90% confidence at every temperate and sub-tropical site during the growing season, whereas an order of magnitude more samples were needed to meet this accuracy at some high-latitude sites. SWC was significantly more variable than Ts at most sites, resulting in at least 10× more SWC samples needed to meet the same accuracy requirement. Previous studies investigated the relationship between the mean and variability (i.e., sill) of SWC across space at individual sites across time and have often (but not always) observed the variance or standard deviation peaking at intermediate values of SWC and decreasing at low and high SWC. Finally, we quantified how far apart samples must be spaced to be statistically independent. Semivariance structures from 10 of the 12-dominant soil orders across the US were estimated, advancing our continental-scale understanding of soil behavior. PMID:24465377
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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.
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Soil respiration across a permafrost transition zone: spatial structure and environmental correlates
DOE Office of Scientific and Technical Information (OSTI.GOV)
Stegen, James C.; Anderson, Carolyn G.; Bond-Lamberty, Ben
Soil respiration is a key ecosystem function whereby shifts in respiration rates can shift systems from carbon sinks to sources. Soil respiration in permafrost-associated systems is particularly important given climate change driven permafrost thaw that leads to significant uncertainty in resulting ecosystem carbon dynamics. Here we characterize the spatial structure and environmental drivers of soil respiration across a permafrost transition zone. We find that soil respiration is characterized by a non-linear threshold that occurs at active-layer depths greater than 140 cm. We also find that within each season, tree basal area is a dominant driver of soil respiration regardless of spatial scale, but onlymore » in spatial domains with significant spatial variability in basal area. Our analyses further show that spatial variation (the coefficient of variation) and mean-variance power-law scaling of soil respiration in our boreal system are consistent with previous work in other ecosystems (e.g., tropical forests) and in population ecology, respectively. Comparing our results to those in other ecosystems suggests that temporally stable features such as tree-stand structure are often primary drivers of spatial variation in soil respiration. If so, this provides an opportunity to better estimate the magnitude and spatial variation in soil respiration through remote sensing. Finally, combining such an approach with broader knowledge of thresholding behavior – here related to active layer depth – would provide empirical constraints on models aimed at predicting ecosystem responses to ongoing permafrost thaw.« less
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Soil respiration across a permafrost transition zone: spatial structure and environmental correlates
Stegen, James C.; Anderson, Carolyn G.; Bond-Lamberty, Ben; ...
2017-09-28
Soil respiration is a key ecosystem function whereby shifts in respiration rates can shift systems from carbon sinks to sources. Soil respiration in permafrost-associated systems is particularly important given climate change driven permafrost thaw that leads to significant uncertainty in resulting ecosystem carbon dynamics. Here we characterize the spatial structure and environmental drivers of soil respiration across a permafrost transition zone. We find that soil respiration is characterized by a non-linear threshold that occurs at active-layer depths greater than 140 cm. We also find that within each season, tree basal area is a dominant driver of soil respiration regardless of spatial scale, but onlymore » in spatial domains with significant spatial variability in basal area. Our analyses further show that spatial variation (the coefficient of variation) and mean-variance power-law scaling of soil respiration in our boreal system are consistent with previous work in other ecosystems (e.g., tropical forests) and in population ecology, respectively. Comparing our results to those in other ecosystems suggests that temporally stable features such as tree-stand structure are often primary drivers of spatial variation in soil respiration. If so, this provides an opportunity to better estimate the magnitude and spatial variation in soil respiration through remote sensing. Finally, combining such an approach with broader knowledge of thresholding behavior – here related to active layer depth – would provide empirical constraints on models aimed at predicting ecosystem responses to ongoing permafrost thaw.« less
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Soil respiration across a permafrost transition zone: spatial structure and environmental correlates
NASA Astrophysics Data System (ADS)
Stegen, James C.; Anderson, Carolyn G.; Bond-Lamberty, Ben; Crump, Alex R.; Chen, Xingyuan; Hess, Nancy
2017-09-01
Soil respiration is a key ecosystem function whereby shifts in respiration rates can shift systems from carbon sinks to sources. Soil respiration in permafrost-associated systems is particularly important given climate change driven permafrost thaw that leads to significant uncertainty in resulting ecosystem carbon dynamics. Here we characterize the spatial structure and environmental drivers of soil respiration across a permafrost transition zone. We find that soil respiration is characterized by a non-linear threshold that occurs at active-layer depths greater than 140 cm. We also find that within each season, tree basal area is a dominant driver of soil respiration regardless of spatial scale, but only in spatial domains with significant spatial variability in basal area. Our analyses further show that spatial variation (the coefficient of variation) and mean-variance power-law scaling of soil respiration in our boreal system are consistent with previous work in other ecosystems (e.g., tropical forests) and in population ecology, respectively. Comparing our results to those in other ecosystems suggests that temporally stable features such as tree-stand structure are often primary drivers of spatial variation in soil respiration. If so, this provides an opportunity to better estimate the magnitude and spatial variation in soil respiration through remote sensing. Combining such an approach with broader knowledge of thresholding behavior - here related to active layer depth - would provide empirical constraints on models aimed at predicting ecosystem responses to ongoing permafrost thaw.
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Related Structure Characters and Stability of Structural Defects in a Metallic Glass
Niu, Xiaofeng; Feng, Shidong; Pan, Shaopeng
2018-01-01
Structural defects were investigated by a recently proposed structural parameter, quasi-nearest atom (QNA), in a modeled Zr50Cu50 metallic glass through molecular dynamics simulations. More QNAs around an atom usually means that more defects are located near the atom. Structural analysis reveals that the spatial distribution of the numbers of QNAs displays to be clearly heterogeneous. Furthermore, QNA is closely correlated with cluster connections, especially four-atom cluster connections. Atoms with larger coordination numbers usually have less QNAs. When two atoms have the same coordination number, the atom with larger five-fold symmetry has less QNAs. The number of QNAs around an atom changes rather frequently and the change of QNAs might be correlated with the fast relaxation metallic glasses. PMID:29565298
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Thompson, E.M.; Wald, D.J.
2012-01-01
Despite obvious limitations as a proxy for site amplification, the use of time-averaged shear-wave velocity over the top 30 m (VS30) remains widely practiced, most notably through its use as an explanatory variable in ground motion prediction equations (and thus hazard maps and ShakeMaps, among other applications). As such, we are developing an improved strategy for producing VS30 maps given the common observational constraints. Using the abundant VS30 measurements in Taiwan, we compare alternative mapping methods that combine topographic slope, surface geology, and spatial correlation structure. The different VS30 mapping algorithms are distinguished by the way that slope and geology are combined to define a spatial model of VS30. We consider the globally applicable slope-only model as a baseline to which we compare two methods of combining both slope and geology. For both hybrid approaches, we model spatial correlation structure of the residuals using the kriging-with-a-trend technique, which brings the map into closer agreement with the observations. Cross validation indicates that we can reduce the uncertainty of the VS30 map by up to 16% relative to the slope-only approach.
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Urban Thermodynamic Island in a Coastal City Analysed from an Optimized Surface Network
NASA Astrophysics Data System (ADS)
Pigeon, Grégoire; Lemonsu, Aude; Long, Nathalie; Barrié, Joël; Masson, Valéry; Durand, Pierre
2006-08-01
Within the framework of ESCOMPTE, a French experiment performed in June and July 2001 in the south-east of France to study the photo-oxidant pollution at the regional scale, the urban boundary layer (UBL) program focused on the study of the urban atmosphere over the coastal city of Marseille. A methodology developed to optimize a network of 20 stations measuring air temperature and moisture over the city is presented. It is based on the analysis of a numerical simulation, performed with the non-hydrostatic, mesoscale Meso-NH model, run with four nested-grids down to a horizontal resolution of 250 m over the city and including a specific parametrization for the urban surface energy balance. A three-day period was modelled and evaluated against data collected during the preparatory phase for the project in summer 2000. The simulated thermodynamic surface fields were analysed using an empirical orthogonal function (EOF) decomposition in order to determine the optimal network configuration designed to capture the dominant characteristics of the fields. It is the first attempt of application of this kind of methodology to the field of urban meteorology. The network, of 20 temperature and moisture sensors, was implemented during the UBL-ESCOMPTE experiment and continuously recorded data from 12 June to 14 July 2001. The measurements were analysed in order to assess the urban thermodynamic island spatio-temporal structure, also using EOF decomposition. During nighttime, the influence of urbanization on temperature is clear the field is characterized by concentric thermo-pleths around the old core of the city, which is the warmest area of the domain. The moisture field is more influenced by proximity to the sea and airflow patterns. During the day, the sea breeze often moves from west or south-west and consequently the spatial pattern for both parameters is characterized by a gradient perpendicular to the shoreline. Finally, in order to assess the methodology adopted, the spatial structures extracted from the simulation of the 2000 preparatory campaign and observations gathered in 2001 have been compared. They are highly correlated, which is a relevant validation of the methodology proposed. The relations between these spatial structures and geographical characteristics of the site have also been studied. High correlations between temperature spatial structure during nighttime and urban cover fraction or street aspect ratio are observed and simulated. For temperature during daytime or moisture during both daytime and nighttime these geographical factors are not correlated with thermodynamic fields spatial structures.
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NASA Technical Reports Server (NTRS)
Franklin, Rima B.; Mills, Aaron L.
2003-01-01
To better understand the distribution of soil microbial communities at multiple spatial scales, a survey was conducted to examine the spatial organization of community structure in a wheat field in eastern Virginia (USA). Nearly 200 soil samples were collected at a variety of separation distances ranging from 2.5 cm to 11 m. Whole-community DNA was extracted from each sample, and community structure was compared using amplified fragment length polymorphism (AFLP) DNA fingerprinting. Relative similarity was calculated between each pair of samples and compared using geostatistical variogram analysis to study autocorrelation as a function of separation distance. Spatial autocorrelation was found at scales ranging from 30 cm to more than 6 m, depending on the sampling extent considered. In some locations, up to four different correlation length scales were detected. The presence of nested scales of variability suggests that the environmental factors regulating the development of the communities in this soil may operate at different scales. Kriging was used to generate maps of the spatial organization of communities across the plot, and the results demonstrated that bacterial distributions can be highly structured, even within a habitat that appears relatively homogeneous at the plot and field scale. Different subsets of the microbial community were distributed differently across the plot, and this is thought to be due to the variable response of individual populations to spatial heterogeneity associated with soil properties. c2003 Federation of European Microbiological Societies. Published by Elsevier Science B.V. All rights reserved.
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Burles, Ford; Slone, Edward; Iaria, Giuseppe
2017-04-01
The retrosplenial complex is a region within the posterior cingulate cortex implicated in spatial navigation. Here, we investigated the functional specialization of this large and anatomically heterogeneous region using fMRI and resting-state functional connectivity combined with a spatial task with distinct phases of spatial 'updating' (i.e., integrating and maintaining object locations in memory during spatial displacement) and 'orienting' (i.e., recalling unseen locations from current position in space). Both spatial 'updating' and 'orienting' produced bilateral activity in the retrosplenial complex, among other areas. However, spatial 'updating' produced slightly greater activity in ventro-lateral portions, of the retrosplenial complex, whereas spatial 'orienting' produced greater activity in a more dorsal and medial portion of it (both regions localized along the parieto-occipital fissure). At rest, both ventro-lateral and dorso-medial subregions of the retrosplenial complex were functionally connected to the hippocampus and parahippocampus, regions both involved in spatial orientation and navigation. However, the ventro-lateral subregion of the retrosplenial complex displayed more positive functional connectivity with ventral occipital and temporal object recognition regions, whereas the dorso-medial subregion activity was more correlated to dorsal activity and frontal activity, as well as negatively correlated with more ventral parietal structures. These findings provide evidence for a dorso-medial to ventro-lateral functional specialization within the human retrosplenial complex that may shed more light on the complex neural mechanisms underlying spatial orientation and navigation in humans.
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NASA Astrophysics Data System (ADS)
Bicalho, E. S.; Teixeira, D. B.; Panosso, A. R.; Perillo, L. I.; Iamaguti, J. L.; Pereira, G. T.; La Scala, N., Jr.
2012-04-01
Soil CO2 emission (FCO2) is influenced by chemical, physical and biological factors that affect the production of CO2 in the soil and its transport to the atmosphere, varying in time and space depending on environmental conditions, including the management of agricultural area. The aim of this study was to investigate the structure of spatial variability of FCO2 and soil properties by using fractal dimension (DF), derived from isotropic variograms at different scales, and construction of fractograms. The experimental area consisted of a regular grid of 60 × 60 m on sugarcane area under green management, containing 141 points spaced at minimum distances ranging from 0.5 to 10 m. Soil CO2 emission, soil temperature and soil moisture were evaluated over a period of 7 days, and soil chemical and physical properties were determined by sampling at a depth of 0.0 to 0.1 m. FCO2 showed an overall average of 1.51 µmol m-2 s-1, correlated significantly (p < 0.05) with soil physical factors such as soil bulk density, air-filled pore space, macroporosity and microporosity. Significant DF values were obtained in the characterization of FCO2 in medium and large scales (from 20 m). Variations in DF with the scale, which is the fractogram, indicate that the structure of FCO2 variability is similar to that observed for the soil temperature and total pore volume, and reverse for the other soil properties, except for macroporosity, sand content, soil organic matter, carbon stock, C/N ratio and CEC, which fractograms were not significantly correlated to the FCO2 fractogram. Thus, the structure of spatial variability for most soil properties, characterized by fractogram, presents a significant relationship with the structure of spatial variability of FCO2, generally with similar or dissimilar behavior, indicating the possibility of using the fractogram as tool to better observe the behavior of the spatial dependence of the variables along the scale.
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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.
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NASA Astrophysics Data System (ADS)
Sadat Mohajerani, Matin; Müller, Marcus; Hartmann, Jana; Zhou, Hao; Wehmann, Hergo-H.; Veit, Peter; Bertram, Frank; Christen, Jürgen; Waag, Andreas
2016-05-01
Three-dimensional (3D) InGaN/GaN quantum-well (QW) core-shell light emitting diodes (LEDs) are a promising candidate for the future solid state lighting. In this contribution, we study direct correlations of structural and optical properties of the core-shell LEDs using highly spatially-resolved cathodoluminescence spectroscopy (CL) in combination with scanning electron microscopy (SEM) and scanning transmission electron microscopy (STEM). Temperature-dependent resonant photoluminescence (PL) spectroscopy has been performed to understand recombination mechanisms and to estimate the internal quantum efficiency (IQE).
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Simulation Studies of the Effect of Forest Spatial Structure on InSAR Signature
NASA Technical Reports Server (NTRS)
Sun, Guoqing; Liu, Dawei; Ranson, K. Jon; Koetz, Benjamin
2007-01-01
The height of scattering phase retrieved from InSAR data is considered being correlated with the tree height and the spatial structure of the forest stand. Though some researchers have used simple backscattering models to estimate tree height from the height of scattering center, the effect of forest spatial structure on InSAR data is not well understood yet. A three-dimensional coherent radar backscattering model for forest canopies based on realistic three-dimensional scene was used to investigate the effect in this paper. The realistic spatial structure of forest canopies was established either by field measurements (stem map) or through use of forest growth model. Field measurements or a forest growth model parameterized using local environmental parameters provides information of forest species composition and tree sizes in certain growth phases. A fractal tree model (L-system) was used to simulate individual 3- D tree structure of different ages or heights. Trees were positioned in a stand in certain patterns resulting in a 3-D medium of discrete scatterers. The radar coherent backscatter model took the 3-D forest scene as input and simulates the coherent radar backscattering signature. Interferometric SAR images of 3D scenes were simulated and heights of scattering phase centers were estimated from the simulated InSAR data. The effects of tree height, crown cover, crown depth, and the spatial distribution patterns of trees on the scattering phase center were analyzed. The results will be presented in the paper.
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Porous media flux sensitivity to pore-scale geostatistics: A bottom-up approach
NASA Astrophysics Data System (ADS)
Di Palma, P. R.; Guyennon, N.; Heße, F.; Romano, E.
2017-04-01
Macroscopic properties of flow through porous media can be directly computed by solving the Navier-Stokes equations at the scales related to the actual flow processes, while considering the porous structures in an explicit way. The aim of this paper is to investigate the effects of the pore-scale spatial distribution on seepage velocity through numerical simulations of 3D fluid flow performed by the lattice Boltzmann method. To this end, we generate multiple random Gaussian fields whose spatial correlation follows an assigned semi-variogram function. The Exponential and Gaussian semi-variograms are chosen as extreme-cases of correlation for short distances and statistical properties of the resulting porous media (indicator field) are described using the Matèrn covariance model, with characteristic lengths of spatial autocorrelation (pore size) varying from 2% to 13% of the linear domain. To consider the sensitivity of the modeling results to the geostatistical representativeness of the domain as well as to the adopted resolution, porous media have been generated repetitively with re-initialized random seeds and three different resolutions have been tested for each resulting realization. The main difference among results is observed between the two adopted semi-variograms, indicating that the roughness (short distances autocorrelation) is the property mainly affecting the flux. However, computed seepage velocities show additionally a wide variability (about three orders of magnitude) for each semi-variogram model in relation to the assigned correlation length, corresponding to pore sizes. The spatial resolution affects more the results for short correlation lengths (i.e., small pore sizes), resulting in an increasing underestimation of the seepage velocity with the decreasing correlation length. On the other hand, results show an increasing uncertainty as the correlation length approaches the domain size.
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Modal energy analysis for mechanical systems excited by spatially correlated loads
NASA Astrophysics Data System (ADS)
Zhang, Peng; Fei, Qingguo; Li, Yanbin; Wu, Shaoqing; Chen, Qiang
2018-10-01
MODal ENergy Analysis (MODENA) is an energy-based method, which is proposed to deal with vibroacoustic problems. The performance of MODENA on the energy analysis of a mechanical system under spatially correlated excitation is investigated. A plate/cavity coupling system excited by a pressure field is studied in a numerical example, in which four kinds of pressure fields are involved, which include the purely random pressure field, the perfectly correlated pressure field, the incident diffuse field, and the turbulent boundary layer pressure fluctuation. The total energies of subsystems differ to reference solution only in the case of purely random pressure field and only for the non-excited subsystem (the cavity). A deeper analysis on the scale of modal energy is further conducted via another numerical example, in which two structural modes excited by correlated forces are coupled with one acoustic mode. A dimensionless correlation strength factor is proposed to determine the correlation strength between modal forces. Results show that the error on modal energy increases with the increment of the correlation strength factor. A criterion is proposed to establish a link between the error and the correlation strength factor. According to the criterion, the error is negligible when the correlation strength is weak, in this situation the correlation strength factor is less than a critical value.
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Single-photon-level quantum image memory based on cold atomic ensembles
Ding, Dong-Sheng; Zhou, Zhi-Yuan; Shi, Bao-Sen; Guo, Guang-Can
2013-01-01
A quantum memory is a key component for quantum networks, which will enable the distribution of quantum information. Its successful development requires storage of single-photon light. Encoding photons with spatial shape through higher-dimensional states significantly increases their information-carrying capability and network capacity. However, constructing such quantum memories is challenging. Here we report the first experimental realization of a true single-photon-carrying orbital angular momentum stored via electromagnetically induced transparency in a cold atomic ensemble. Our experiments show that the non-classical pair correlation between trigger photon and retrieved photon is retained, and the spatial structure of input and retrieved photons exhibits strong similarity. More importantly, we demonstrate that single-photon coherence is preserved during storage. The ability to store spatial structure at the single-photon level opens the possibility for high-dimensional quantum memories. PMID:24084711
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Probing quantum correlation functions through energy-absorption interferometry
NASA Astrophysics Data System (ADS)
Withington, S.; Thomas, C. N.; Goldie, D. J.
2017-08-01
An interferometric technique is described for determining the spatial forms of the individual degrees of freedom through which a many-body system can absorb energy from its environment. The method separates out the spatial forms of the coherent excitations present at any single frequency; it is not necessary to sweep the frequency and then infer the spatial forms of possible excitations from resonant absorption features. The system under test is excited with two external sources, which create generalized forces, and the fringe in the total power dissipated is measured as the relative phase between the sources is varied. If the complex fringe visibility is measured for different pairs of source locations, the anti-Hermitian part of the complex-valued nonlocal correlation tensor can be determined, which can then be decomposed to give the natural dynamical modes of the system and their relative responsivities. If each source in the interferometer creates a different kind of force, the spatial forms of the individual excitations that are responsible for cross-correlated response can be found. The technique is related to holography, but measures the state of coherence to which the system is maximally sensitive. It can be applied across a wide range of wavelengths, in a variety of ways, to homogeneous media, thin films, patterned structures, and components such as sensors, detectors, and energy-harvesting absorbers.
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Neurobiological and Endocrine Correlates of Individual Differences in Spatial Learning Ability
Sandi, Carmen; Cordero, M. Isabel; Merino, José J.; Kruyt, Nyika D.; Regan, Ciaran M.; Murphy, Keith J.
2004-01-01
The polysialylated neural cell adhesion molecule (PSA-NCAM) has been implicated in activity-dependent synaptic remodeling and memory formation. Here, we questioned whether training-induced modulation of PSA-NCAM expression might be related to individual differences in spatial learning abilities. At 12 h posttraining, immunohistochemical analyses revealed a learning-induced up-regulation of PSA-NCAM in the hippocampal dentate gyrus that was related to the spatial learning abilities displayed by rats during training. Specifically, a positive correlation was found between latency to find the platform and subsequent activated PSA levels, indicating that greater induction of polysialylation was observed in rats with the slower acquisition curve. At posttraining times when no learning-associated activation of PSA was observed, no such correlation was found. Further experiments revealed that performance in the massed water maze training is related to a pattern of spatial learning and memory abilities, and to learning-related glucocorticoid responsiveness. Taken together, our findings suggest that the learning-related neural circuits of fast learners are better suited to solving the water maze task than those of slow learners, the latter relying more on structural reorganization to form memory, rather than the relatively economic mechanism of altering synaptic efficacy that is likely used by the former. PMID:15169853
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Neurobiological and endocrine correlates of individual differences in spatial learning ability.
Sandi, Carmen; Cordero, M Isabel; Merino, José J; Kruyt, Nyika D; Regan, Ciaran M; Murphy, Keith J
2004-01-01
The polysialylated neural cell adhesion molecule (PSA-NCAM) has been implicated in activity-dependent synaptic remodeling and memory formation. Here, we questioned whether training-induced modulation of PSA-NCAM expression might be related to individual differences in spatial learning abilities. At 12 h posttraining, immunohistochemical analyses revealed a learning-induced up-regulation of PSA-NCAM in the hippocampal dentate gyrus that was related to the spatial learning abilities displayed by rats during training. Specifically, a positive correlation was found between latency to find the platform and subsequent activated PSA levels, indicating that greater induction of polysialylation was observed in rats with the slower acquisition curve. At posttraining times when no learning-associated activation of PSA was observed, no such correlation was found. Further experiments revealed that performance in the massed water maze training is related to a pattern of spatial learning and memory abilities, and to learning-related glucocorticoid responsiveness. Taken together, our findings suggest that the learning-related neural circuits of fast learners are better suited to solving the water maze task than those of slow learners, the latter relying more on structural reorganization to form memory, rather than the relatively economic mechanism of altering synaptic efficacy that is likely used by the former.
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Spatial correlations in polydisperse, frictionless, two-dimensional packings
NASA Astrophysics Data System (ADS)
O'Donovan, C. B.; Möbius, M. E.
2011-08-01
We investigate next-nearest-neighbor correlations of the contact number in simulations of polydisperse, frictionless packings in two dimensions. We find that disks with few contacting neighbors are predominantly in contact with disks that have many neighbors and vice versa at all packing fractions. This counterintuitive result can be explained by drawing a direct analogy to the Aboav-Weaire law in cellular structures. We find an empirical one parameter relation similar to the Aboav-Weaire law that satisfies an exact sum rule constraint. Surprisingly, there are no correlations in the radii between neighboring particles, despite correlations between contact number and radius.
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Atomic Scale Medium Range Order and Relaxation Dynamics in Metallic Glass
NASA Astrophysics Data System (ADS)
Zhang, Pei
We studied the atomic scale structure of bulk metallic glass (BMG) with the combination of fluctuation electron microscopy (FEM) and hybrid reverse Monte Carlo (HRMC) simulation. Medium range order (MRO), which occupies the length scale between short range order (SRO) and long-range order, plays an important role on the properties of metallic glass, but the characterization of MRO in experiment is difficult because conventional techniques are not sensitive to the structure at MRO scale. Compared with the X-ray and neutron which can measure SRO by two-body correlation functions, FEM is an effective way to detect MRO structure through three and four-body correlation functions, providing information about the size, distribution, and internal structure of MRO combing HRMC modeling. Thickness estimation is necessary in FEM experiment and HRMC calculation, so in Chapter 3, we measured the elastic and inelastic mean free paths of metallic glass alloys based on focused ion beam prepared thin samples with measured thickness gradients. We developed a model based on the Wentzel atomic model to predict the elastic mean free path for other amorphous materials. In Chapter 4, we studied the correlation of MRO and glass forming ability ZrCuAl alloy. Results from Variable resolution fluctuation microscopy show that in Zr50Cu35Al15 the crystal-like clusters shrink but become more ordered, while icosahedral-like clusters grow. Compared with Zr50Cu45Al5, Zr50Cu35Al15 with poorer glass forming ability exhibits more stable crystal-like structure under annealing, indicating that destabilizing crystal-like structures is important to achieve better glass forming ability in this alloy. In Chapter 5, we studied the crystallization and MRO structural in deformed and quenched Ni60Nb40 metallic glass. The deformed Ni60Nb40 contains fewer icosahedral-like Voronoi clusters and more crystal-like and bcc-like Voronoi clusters. The crystal-like and bcc-like medium range order clusters may be the structural origin for its lower crystallization temperature compared with quenched alloy. Dynamics heterogeneity is proposed to be the microscopic origin of the dynamic nature of glass transition. Some experimental evidence and simulation have indicated that different regions of materials indeed relax at fast or slow rate. However, the spatial distribution of relaxation time visualized from the experiment as the direct evidence of heterogeneous dynamics is still challenging. We proposed to measure the structural dynamics of supercooled metallic glasses with electron correlation microscopy (ECM) technique at the nanometer scale. ECM was developed as a way to measure structural relaxation times of liquids with nanometer-scale spatial resolution using the coherent electron scattering equivalent of photon correlation spectroscopy. In chapter 6, we studied the experimental requirements of ECM to obtain reliable results. For example, the trajectory length must be at least 40 times the relaxation time to obtain a well-converged g2( t), and the time per frame must be less than 0.1 time the relaxation time to obtain sufficient sampling. ECM experiment was firstly realized in scanning transmission electron microscopy (STEM) mode and applied to measure the structural relaxation time of Pd based metallic glass. In order to overcome the drift problem and capture the spatial information, we developed ECM experiment in dark field (DF) mode. In Chapter 7, through DF-ECM, we visualized the spatially heterogeneous dynamics by in-situ heating Pt57.5Cu14.7Ni 5.3P22.5 nanowire into supercooled liquid state, and quantify the size of the heterogeneity by four-point correlation function. The thickness effect and temporal evolution of the heterogeneous domain were also discussed. Additionally, a fast near-surface dynamics was discovered, providing an effective mechanism for surface crystallization of liquids by homogeneous nucleation.
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The Urban Heat Island Impact in Consideration of Spatial Pattern of Urban Landscape and Structure
NASA Astrophysics Data System (ADS)
Kim, J.; Lee, D. K.; Jeong, W.; Sung, S.; Park, J.
2015-12-01
Preceding study has established a clear relationship between land surface temperature and area of land covers. However, only few studies have specifically examined the effects of spatial patterns of land covers and urban structure. To examine how much the local climate is affected by the spatial pattern in highly urbanized city, we investigated the correlation between land surface temperature and spatial patterns of land covers. In the analysis of correlation, we categorized urban structure to four different land uses: Apartment residential area, low rise residential area, industrial area and central business district. Through this study, we aims to examine the types of residential structure and land cover pattern for reducing urban heat island and sustainable development. Based on land surface temperature, we investigated the phenomenon of urban heat island through using the data of remote sensing. This study focused on Daegu in Korea. This city, one of the hottest city in Korea has basin form. We used high-resolution land cover data and land surface temperature by using Landsat8 satellite image to examine 100 randomly selected sample sites of 884.15km2 (1)In each land use, we quantified several landscape-levels and class-level landscape metrics for the sample study sites. (2)In addition, we measured the land surface temperature in 3 year hot summer seasons (July to September). Then, we investigated the pattern of land surface temperature for each land use through Ecognition package. (3)We deducted the Pearson correlation coefficients between land surface temperature and each landscape metrics. (4)We analyzed the variance among the four land uses. (5)Using linear regression, we determined land surface temperature model for each land use. (6)Through this analysis, we aims to examine the best pattern of land cover and artificial structure for reducing urban heat island effect in highly urbanized city. The results of linear regression showed that proportional land cover of grass, tree, water and impervious surfaces well explained the temperature in apartment residential areas. In contrast, the changes in the pattern of water, grass, tree and impervious surfaces were the best to determine the temperature in low rise residential area, central business district and industrial area.
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Spatial path models with multiple indicators and multiple causes: mental health in US counties.
Congdon, Peter
2011-06-01
This paper considers a structural model for the impact on area mental health outcomes (poor mental health, suicide) of spatially structured latent constructs: deprivation, social capital, social fragmentation and rurality. These constructs are measured by multiple observed effect indicators, with the constructs allowed to be correlated both between and within areas. However, in the scheme developed here, particular latent constructs may also be influenced by known variables, or, via path sequences, by other constructs, possibly nonlinearly. For example, area social capital may be measured by effect indicators (e.g. associational density, charitable activity), but influenced as causes by other constructs (e.g. area deprivation), and by observed features of the socio-ethnic structure of areas. A model incorporating these features is applied to suicide mortality and the prevalence of poor mental health in 3141 US counties, which are related to the latent spatial constructs and to observed variables (e.g. county ethnic mix). Copyright © 2011 Elsevier Ltd. All rights reserved.
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Correlative cryogenic tomography of cells using light and soft x-rays
Smith, Elizabeth A.; Cinquin, Bertrand P.; Do, Myan; McDermott, Gerry; Le Gros, Mark A.; Larabell, Carolyn A.
2013-01-01
Correlated imaging is the process of imaging a specimen with two complementary modalities, and then combining the two data sets to create a highly informative, composite view. A recent implementation of this concept has been the combination of soft x-ray tomography (SXT) with fluorescence cryogenic microscopy (FCM). SXT-FCM is used to visualize cells that are held in a near-native, cryo-preserved state. The resultant images are, therefore, highly representative of both the cellular architecture and molecular organization in vivo. SXT quantitatively visualizes the cell and sub-cellular structures; FCM images the spatial distribution of fluorescently labeled molecules. Here, we review the characteristics of SXT-FCM, and briefly discuss how this method compares with existing correlative imaging techniques. We also describe how the incorporation of a cryo-rotation stage into a cryogenic fluorescence microscope allows acquisition of fluorescence cryogenic tomography (FCT) data. FCT is optimally suited to correlation with SXT, since both techniques image the specimen in 3-D, potentially with similar, isotropic spatial resolution. PMID:24355261
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Vaessen, Maarten J; Saj, Arnaud; Lovblad, Karl-Olof; Gschwind, Markus; Vuilleumier, Patrik
2016-04-01
Spatial neglect is a neuropsychological syndrome in which patients fail to perceive and orient to stimuli located in the space contralateral to the lesioned hemisphere. It is characterized by a wide heterogeneity in clinical symptoms which can be grouped into distinct behavioral components correlating with different lesion sites. Moreover, damage to white-matter (WM) fiber tracts has been suggested to disconnect brain networks that mediate different functions associated with spatial cognition and attention. However, it remains unclear what WM pathways are associated with functionally dissociable neglect components. In this study we examined nine patients with a focal right hemisphere stroke using a series of neuropsychological tests and diffusion tensor imaging (DTI) in order to disentangle the role of specific WM pathways in neglect symptoms. First, following previous work, the behavioral test scores of patients were factorized into three independent components reflecting perceptual, exploratory, and object-centered deficits in spatial awareness. We then examined the structural neural substrates of these components by correlating indices of WM integrity (fractional anisotropy) with the severity of deficits along each profile. Several locations in the right parietal and frontal WM correlated with neuropsychological scores. Fiber tracts projecting from these locations indicated that posterior parts of the superior longitudinal fasciculus (SLF), as well as nearby callosal fibers connecting ipsilateral and contralateral parietal areas, were associated with perceptual spatial deficits, whereas more anterior parts of SLF and inferior fronto-occipital fasciculus (IFOF) were predominantly associated with object-centered deficits. In addition, connections between frontal areas and superior colliculus were found to be associated with the exploratory deficits. Our results provide novel support to the view that neglect may result from disconnection lesions in distributed brain networks, but also extend these notions by highlighting the role of dissociable circuits in different functional components of the neglect syndrome. However these preliminary findings require replication with larger samples of patients. Copyright © 2016 Elsevier Ltd. All rights reserved.
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NASA Technical Reports Server (NTRS)
Tuominen, H. V. (Principal Investigator); Kuosmanen, V.
1975-01-01
The author has identified the following significant results. On the central Baltic Shield, the concept of drainage patterns can be extended to smaller scales in which case many cultural features become involved to the spatial patterns influenced by bedrock structure. Features resulting from agriculture activity and timbering often exaggerate the influence of the bedrock on the image texture.
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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.
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Optical and tunneling microscopy and spectroscopy at the ultimate spatial limit
NASA Astrophysics Data System (ADS)
Chen, Chi
2009-12-01
The combination of optical detection system with a scanning tunneling microscope (STM) leads to the possibility of resolving radiative transition probability with the ultrahigh spatial resolution of STM in real space. This opens an innovative approach toward revealing the correlation between molecular structure, electronic characteristics, and optical properties. This thesis describes a series of experiments that manifests this correlation, including atomic silver chains and single porphine molecules. In atomic silver chains, the number and positions of the emission maxima in the photon images match the nodes in the dI/d V images of "particle-in-a-box" states. This surprising correlation between the emission maxima and nodes in the density of states is a manifestation of Fermi's golden rule in real space for radiative transitions, which provides an understanding of the mechanism of STM induced light emission. From single porphine molecules, orthogonal spatial contrast of two types of vibronic coupling is resolved by both photon spectroscopy and vibronic-mode-selected photon images. Intramolecular transitions from the two orthogonal LUMOs individually couple to different molecular normal modes. This is the first demonstration of the photon emission probability of a single molecule and its direct correlations with the molecular orbitals. This also provides the first real space experimental evidence to separate the tangled effects of molecular conformations and nano-environments on the inhomogeneity of molecular emission. DSB molecules are found to have two conformational isomers and one of them shows surface chirality. All these conformers and enantiomers can be switched to each other by electron injection. Different DSB conformers present distinct manipulation dynamics, which demonstrate how different conformations and their preferred adsorption geometries can have pronounced influence on the molecular mechanics on the surface. Overall, this thesis studies the very fundamental nature of single molecules and artificial nanostructures by integrating all kinds of important functions of STM: topography, spectroscopy, manipulation, and photon emission. Detailed correlations between the emission patterns and orbital structures are revealed by the ultimate spatial resolution of our "STM photon microscopy".
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Weininger, Arthur; Weininger, Susan
2015-01-01
The ability to identify the functional correlates of structural and sequence variation in proteins is a critical capability. We related structures of influenza A N10 and N11 proteins that have no established function to structures of proteins with known function by identifying spatially conserved atoms. We identified atoms with common distributed spatial occupancy in PDB structures of N10 protein, N11 protein, an influenza A neuraminidase, an influenza B neuraminidase, and a bacterial neuraminidase. By superposing these spatially conserved atoms, we aligned the structures and associated molecules. We report spatially and sequence invariant residues in the aligned structures. Spatially invariant residues in the N6 and influenza B neuraminidase active sites were found in previously unidentified spatially equivalent sites in the N10 and N11 proteins. We found the corresponding secondary and tertiary structures of the aligned proteins to be largely identical despite significant sequence divergence. We found structural precedent in known non-neuraminidase structures for residues exhibiting structural and sequence divergence in the aligned structures. In N10 protein, we identified staphylococcal enterotoxin I-like domains. In N11 protein, we identified hepatitis E E2S-like domains, SARS spike protein-like domains, and toxin components shared by alpha-bungarotoxin, staphylococcal enterotoxin I, anthrax lethal factor, clostridium botulinum neurotoxin, and clostridium tetanus toxin. The presence of active site components common to the N6, influenza B, and S. pneumoniae neuraminidases in the N10 and N11 proteins, combined with the absence of apparent neuraminidase function, suggests that the role of neuraminidases in H17N10 and H18N11 emerging influenza A viruses may have changed. The presentation of E2S-like, SARS spike protein-like, or toxin-like domains by the N10 and N11 proteins in these emerging viruses may indicate that H17N10 and H18N11 sialidase-facilitated cell entry has been supplemented or replaced by sialidase-independent receptor binding to an expanded cell population that may include neurons and T-cells. PMID:25706124
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Unveiling Spatial Epidemiology of HIV with Mobile Phone Data
NASA Astrophysics Data System (ADS)
Brdar, Sanja; Gavrić, Katarina; Ćulibrk, Dubravko; Crnojević, Vladimir
2016-01-01
An increasing amount of geo-referenced mobile phone data enables the identification of behavioral patterns, habits and movements of people. With this data, we can extract the knowledge potentially useful for many applications including the one tackled in this study - understanding spatial variation of epidemics. We explored the datasets collected by a cell phone service provider and linked them to spatial HIV prevalence rates estimated from publicly available surveys. For that purpose, 224 features were extracted from mobility and connectivity traces and related to the level of HIV epidemic in 50 Ivory Coast departments. By means of regression models, we evaluated predictive ability of extracted features. Several models predicted HIV prevalence that are highly correlated (>0.7) with actual values. Through contribution analysis we identified key elements that correlate with the rate of infections and could serve as a proxy for epidemic monitoring. Our findings indicate that night connectivity and activity, spatial area covered by users and overall migrations are strongly linked to HIV. By visualizing the communication and mobility flows, we strived to explain the spatial structure of epidemics. We discovered that strong ties and hubs in communication and mobility align with HIV hot spots.
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Unveiling Spatial Epidemiology of HIV with Mobile Phone Data
Brdar, Sanja; Gavrić, Katarina; Ćulibrk, Dubravko; Crnojević, Vladimir
2016-01-01
An increasing amount of geo-referenced mobile phone data enables the identification of behavioral patterns, habits and movements of people. With this data, we can extract the knowledge potentially useful for many applications including the one tackled in this study - understanding spatial variation of epidemics. We explored the datasets collected by a cell phone service provider and linked them to spatial HIV prevalence rates estimated from publicly available surveys. For that purpose, 224 features were extracted from mobility and connectivity traces and related to the level of HIV epidemic in 50 Ivory Coast departments. By means of regression models, we evaluated predictive ability of extracted features. Several models predicted HIV prevalence that are highly correlated (>0.7) with actual values. Through contribution analysis we identified key elements that correlate with the rate of infections and could serve as a proxy for epidemic monitoring. Our findings indicate that night connectivity and activity, spatial area covered by users and overall migrations are strongly linked to HIV. By visualizing the communication and mobility flows, we strived to explain the spatial structure of epidemics. We discovered that strong ties and hubs in communication and mobility align with HIV hot spots. PMID:26758042
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NASA Astrophysics Data System (ADS)
Hanke, John R.; Fischer, Mark P.; Pollyea, Ryan M.
2018-03-01
In this study, the directional semivariogram is deployed to investigate the spatial variability of map-scale fracture network attributes in the Paradox Basin, Utah. The relative variability ratio (R) is introduced as the ratio of integrated anisotropic semivariogram models, and R is shown to be an effective metric for quantifying the magnitude of spatial variability for any two azimuthal directions. R is applied to a GIS-based data set comprising roughly 1200 fractures, in an area which is bounded by a map-scale anticline and a km-scale normal fault. This analysis reveals that proximity to the fault strongly influences the magnitude of spatial variability for both fracture intensity and intersection density within 1-2 km. Additionally, there is significant anisotropy in the spatial variability, which is correlated with trends of the anticline and fault. The direction of minimum spatial correlation is normal to the fault at proximal distances, and gradually rotates and becomes subparallel to the fold axis over the same 1-2 km distance away from the fault. We interpret these changes to reflect varying scales of influence of the fault and the fold on fracture network development: the fault locally influences the magnitude and variability of fracture network attributes, whereas the fold sets the background level and structure of directional variability.
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The genetic and environmental aetiology of spatial, mathematics and general anxiety
Malanchini, Margherita; Rimfeld, Kaili; Shakeshaft, Nicholas G.; Rodic, Maja; Schofield, Kerry; Selzam, Saskia; Dale, Philip S.; Petrill, Stephen A.; Kovas, Yulia
2017-01-01
Individuals differ in their level of general anxiety as well as in their level of anxiety towards specific activities, such as mathematics and spatial tasks. Both specific anxieties correlate moderately with general anxiety, but the aetiology of their association remains unexplored. Moreover, the factor structure of spatial anxiety is to date unknown. The present study investigated the factor structure of spatial anxiety, its aetiology, and the origins of its association with general and mathematics anxiety in a sample of 1,464 19-21-year-old twin pairs from the UK representative Twins Early Development Study. Participants reported their general, mathematics and spatial anxiety as part of an online battery of tests. We found that spatial anxiety is a multifactorial construct, including two components: navigation anxiety and rotation/visualization anxiety. All anxiety measures were moderately heritable (30% to 41%), and non-shared environmental factors explained the remaining variance. Multivariate genetic analysis showed that, although some genetic and environmental factors contributed to all anxiety measures, a substantial portion of genetic and non-shared environmental influences were specific to each anxiety construct. This suggests that anxiety is a multifactorial construct phenotypically and aetiologically, highlighting the importance of studying anxiety within specific contexts. PMID:28220830
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The genetic and environmental aetiology of spatial, mathematics and general anxiety.
Malanchini, Margherita; Rimfeld, Kaili; Shakeshaft, Nicholas G; Rodic, Maja; Schofield, Kerry; Selzam, Saskia; Dale, Philip S; Petrill, Stephen A; Kovas, Yulia
2017-02-21
Individuals differ in their level of general anxiety as well as in their level of anxiety towards specific activities, such as mathematics and spatial tasks. Both specific anxieties correlate moderately with general anxiety, but the aetiology of their association remains unexplored. Moreover, the factor structure of spatial anxiety is to date unknown. The present study investigated the factor structure of spatial anxiety, its aetiology, and the origins of its association with general and mathematics anxiety in a sample of 1,464 19-21-year-old twin pairs from the UK representative Twins Early Development Study. Participants reported their general, mathematics and spatial anxiety as part of an online battery of tests. We found that spatial anxiety is a multifactorial construct, including two components: navigation anxiety and rotation/visualization anxiety. All anxiety measures were moderately heritable (30% to 41%), and non-shared environmental factors explained the remaining variance. Multivariate genetic analysis showed that, although some genetic and environmental factors contributed to all anxiety measures, a substantial portion of genetic and non-shared environmental influences were specific to each anxiety construct. This suggests that anxiety is a multifactorial construct phenotypically and aetiologically, highlighting the importance of studying anxiety within specific contexts.
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Correlated randomness: Some examples of exotic statistical physics
NASA Astrophysics Data System (ADS)
Stanley, H. Eugene
2005-05-01
One challenge of biology, medicine, and economics is that the systems treated by these sciences have no perfect metronome in time and no perfect spatial architecture -- crystalline or otherwise. Nonetheless, as if by magic, out of nothing but randomness one finds remarkably fine-tuned processes in time and remarkably fine-tuned structures in space. To understand this `miracle', one might consider placing aside the human tendency to see the universe as a machine. Instead, one might address the challenge of uncovering how, through randomness (albeit, as we shall see, strongly correlated randomness), one can arrive at many spatial and temporal patterns in biology, medicine, and economics. Inspired by principles developed by statistical physics over the past 50 years -- scale invariance and universality -- we review some recent applications of correlated randomness to fields that might startle Boltzmann if he were alive today.
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Static and dynamic properties of two-dimensional Coulomb clusters.
Ash, Biswarup; Chakrabarti, J; Ghosal, Amit
2017-10-01
We study the temperature dependence of static and dynamic responses of Coulomb interacting particles in two-dimensional confinements across the crossover from solid- to liquid-like behaviors. While static correlations that investigate the translational and bond orientational order in the confinements show the footprints of hexatic-like phase at low temperatures, dynamics of the particles slow down considerably in this phase, reminiscent of a supercooled liquid. Using density correlations, we probe long-lived heterogeneities arising from the interplay of the irregularity in the confinement and long-range Coulomb interactions. The relaxation at multiple time scales show stretched-exponential decay of spatial correlations in irregular traps. Temperature dependence of characteristic time scales, depicting the structural relaxation of the system, show striking similarities with those observed for the glassy systems, indicating that some of the key signatures of supercooled liquids emerge in confinements with lower spatial symmetries.
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Wang, Jun-Sheng; Olszewski, Emily; Devine, Erin E; Hoffman, Matthew R; Zhang, Yu; Shao, Jun; Jiang, Jack J
2016-08-01
To evaluate the spatiotemporal correlation of vocal fold vibration using eigenmode analysis before and after polyp removal and explore the potential clinical relevance of spatiotemporal analysis of correlation length and entropy as quantitative voice parameters. We hypothesized that increased order in the vibrating signal after surgical intervention would decrease the eigenmode-based entropy and increase correlation length. Prospective case series. Forty subjects (23 males, 17 females) with unilateral (n = 24) or bilateral (n = 16) polyps underwent polyp removal. High-speed videoendoscopy was performed preoperatively and 2 weeks postoperatively. Spatiotemporal analysis was performed to determine entropy, quantification of signal disorder, correlation length, size, and spatially ordered structure of vocal fold vibration in comparison to full spatial consistency. The signal analyzed consists of the vibratory pattern in space and time derived from the high-speed video glottal area contour. Entropy decreased (Z = -3.871, P < .001) and correlation length increased (t = -8.913, P < .001) following polyp excision. The intraclass correlation coefficients (ICC) for correlation length and entropy were 0.84 and 0.93. Correlation length and entropy are sensitive to mass lesions. These parameters could potentially be used to augment subjective visualization after polyp excision when evaluating procedural efficacy. © The Author(s) 2016.
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Soil variability in engineering applications
NASA Astrophysics Data System (ADS)
Vessia, Giovanna
2014-05-01
Natural geomaterials, as soils and rocks, show spatial variability and heterogeneity of physical and mechanical properties. They can be measured by in field and laboratory testing. The heterogeneity concerns different values of litho-technical parameters pertaining similar lithological units placed close to each other. On the contrary, the variability is inherent to the formation and evolution processes experienced by each geological units (homogeneous geomaterials on average) and captured as a spatial structure of fluctuation of physical property values about their mean trend, e.g. the unit weight, the hydraulic permeability, the friction angle, the cohesion, among others. The preceding spatial variations shall be managed by engineering models to accomplish reliable designing of structures and infrastructures. Materon (1962) introduced the Geostatistics as the most comprehensive tool to manage spatial correlation of parameter measures used in a wide range of earth science applications. In the field of the engineering geology, Vanmarcke (1977) developed the first pioneering attempts to describe and manage the inherent variability in geomaterials although Terzaghi (1943) already highlighted that spatial fluctuations of physical and mechanical parameters used in geotechnical designing cannot be neglected. A few years later, Mandelbrot (1983) and Turcotte (1986) interpreted the internal arrangement of geomaterial according to Fractal Theory. In the same years, Vanmarcke (1983) proposed the Random Field Theory providing mathematical tools to deal with inherent variability of each geological units or stratigraphic succession that can be resembled as one material. In this approach, measurement fluctuations of physical parameters are interpreted through the spatial variability structure consisting in the correlation function and the scale of fluctuation. Fenton and Griffiths (1992) combined random field simulation with the finite element method to produce the Random Finite Element Method (RFEM). This method has been used to investigate the random behavior of soils in the context of a variety of classical geotechnical problems. Afterward, some following studies collected the worldwide variability values of many technical parameters of soils (Phoon and Kulhawy 1999a) and their spatial correlation functions (Phoon and Kulhawy 1999b). In Italy, Cherubini et al. (2007) calculated the spatial variability structure of sandy and clayey soils from the standard cone penetration test readings. The large extent of the worldwide measured spatial variability of soils and rocks heavily affects the reliability of geotechnical designing as well as other uncertainties introduced by testing devices and engineering models. So far, several methods have been provided to deal with the preceding sources of uncertainties in engineering designing models (e.g. First Order Reliability Method, Second Order Reliability Method, Response Surface Method, High Dimensional Model Representation, etc.). Nowadays, the efforts in this field have been focusing on (1) measuring spatial variability of different rocks and soils and (2) developing numerical models that take into account the spatial variability as additional physical variable. References Cherubini C., Vessia G. and Pula W. 2007. Statistical soil characterization of Italian sites for reliability analyses. Proc. 2nd Int. Workshop. on Characterization and Engineering Properties of Natural Soils, 3-4: 2681-2706. Griffiths D.V. and Fenton G.A. 1993. Seepage beneath water retaining structures founded on spatially random soil, Géotechnique, 43(6): 577-587. Mandelbrot B.B. 1983. The Fractal Geometry of Nature. San Francisco: W H Freeman. Matheron G. 1962. Traité de Géostatistique appliquée. Tome 1, Editions Technip, Paris, 334 p. Phoon K.K. and Kulhawy F.H. 1999a. Characterization of geotechnical variability. Can Geotech J, 36(4): 612-624. Phoon K.K. and Kulhawy F.H. 1999b. Evaluation of geotechnical property variability. Can Geotech J, 36(4): 625-639. Terzaghi K. 1943. Theoretical Soil Mechanics. New York: John Wiley and Sons. Turcotte D.L. 1986. Fractals and fragmentation. J Geophys Res, 91: 1921-1926. Vanmarcke E.H. 1977. Probabilistic modeling of soil profiles. J Geotech Eng Div, ASCE, 103: 1227-1246. Vanmarcke E.H. 1983. Random fields: analysis and synthesis. MIT Press, Cambridge.
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Phase-detected Brillouin optical correlation-domain reflectometry
NASA Astrophysics Data System (ADS)
Mizuno, Yosuke; Hayashi, Neisei; Fukuda, Hideyuki; Nakamura, Kentaro
2018-05-01
Optical fiber sensing techniques based on Brillouin scattering have been extensively studied for structural health monitoring owing to their capability of distributed strain and temperature measurement. Although a higher signal-to-noise ratio (leading to high spatial resolution and high-speed measurement) is generally obtained for two-end-access systems, they reduce the degree of freedom in embedding the sensors into structures, and render the measurement no longer feasible when extremely high loss or breakage occurs at a point of the sensing fiber. To overcome these drawbacks, a one-end-access sensing technique called Brillouin optical correlation-domain reflectometry (BOCDR) has been developed. BOCDR has a high spatial resolution and cost efficiency, but its conventional configuration suffered from relatively low-speed operation. In this paper, we review the recently developed high-speed configurations of BOCDR, including phase-detected BOCDR, with which we demonstrate real-time distributed measurement by tracking a propagating mechanical wave. We also demonstrate breakage detection with a wide strain dynamic range.
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Phase-detected Brillouin optical correlation-domain reflectometry
NASA Astrophysics Data System (ADS)
Mizuno, Yosuke; Hayashi, Neisei; Fukuda, Hideyuki; Nakamura, Kentaro
2018-06-01
Optical fiber sensing techniques based on Brillouin scattering have been extensively studied for structural health monitoring owing to their capability of distributed strain and temperature measurement. Although a higher signal-to-noise ratio (leading to high spatial resolution and high-speed measurement) is generally obtained for two-end-access systems, they reduce the degree of freedom in embedding the sensors into structures, and render the measurement no longer feasible when extremely high loss or breakage occurs at a point of the sensing fiber. To overcome these drawbacks, a one-end-access sensing technique called Brillouin optical correlation-domain reflectometry (BOCDR) has been developed. BOCDR has a high spatial resolution and cost efficiency, but its conventional configuration suffered from relatively low-speed operation. In this paper, we review the recently developed high-speed configurations of BOCDR, including phase-detected BOCDR, with which we demonstrate real-time distributed measurement by tracking a propagating mechanical wave. We also demonstrate breakage detection with a wide strain dynamic range.
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Can tintinnids be used for discriminating water quality status in marine ecosystems?
Feng, Meiping; Zhang, Wuchang; Wang, Weiding; Zhang, Guangtao; Xiao, Tian; Xu, Henglong
2015-12-30
Ciliated protozoa have many advantages in bioassessment of water quality. The ability of tintinnids for assessing water quality status was studied during a 7-yearcycle in Jiaozhou Bay of the Yellow Sea, northern China. The samples were collected monthly at four sites with a spatial gradient of environmental pollution. Environmental variables, e.g., temperature, salinity, chlorophyll a (Chl a), dissolved inorganic nitrogen, soluble reactive phosphate (SRP), and soluble active silicate (SRSi), were measured synchronously for comparison with biotic parameters. Results showed that: (1) tintinnid community structures represented significant differences among the four sampling sites; (2) spatial patterns of the tintinnid communities were significantly correlated with environmental variables, especially SRSi and nutrients; and (3) the community structural parameters and the five dominant species were significantly correlated with SRSi and nutrients. We suggested that tintinnids may be used as a potential bioindicator for discriminating water quality status in marine ecosystems. Copyright © 2015 Elsevier Ltd. All rights reserved.
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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.
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Banaj, Nerisa; Piras, Federica; Piras, Fabrizio; Ciullo, Valentina; Iorio, Mariangela; Battaglia, Claudia; Pantoli, Donatella; Ducci, Giuseppe; Spalletta, Gianfranco
2018-06-01
The brain structural correlates of cognitive and psychopathological symptoms within the active phase in severely psychotic schizophrenic inpatients have been rarely investigated. Twenty-eight inpatients with a DSM-5 diagnosis of Schizophrenia (SZ), admitted for acute psychotic decompensation, were assessed through a comprehensive neuropsychological and psychopathological battery. All patients underwent a high-resolution T1-weighted magnetic resonance imaging investigation. Increased psychotic severity was related to reduced grey matter volumes in the medial portion of the right superior frontal cortex, the superior orbitofrontal cortex bilaterally and to white matter volume reduction in the medial portion of the left superior frontal area. Immediate verbal memory performance was related to left insula and inferior parietal cortex volume, while long-term visuo-spatial memory was related to grey matter volume of the right middle temporal cortex, and the right (lobule VII, CRUS1) and left (lobule VI) cerebellum. Moreover, psychotic severity correlated with cognitive inflexibility and negative symptom severity was related to visuo-spatial processing and reasoning disturbances. These findings indicate that a disruption of the cortical-subcortical-cerebellar circuit, and distorted memory function contribute to the development and maintenance of psychotic exacerbation.
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Nanotextured phase coexistence in the correlated insulator V2O3
NASA Astrophysics Data System (ADS)
McLeod, Alexander
The Mott insulator-metal transition remains among the most studied phenomena in correlated electron physics. However, the formation of spontaneous spatial patterns amidst coexisting insulating and metallic phases remains poorly explored on the meso- and nanoscales. Here we present real-space evolution of the insulator-metal transition in a thin film of V2O3, the ``canonical'' Mott insulator, imaged at high spatial resolution by cryogenic near-field infrared microscopy. We resolve spontaneously nanotextured coexistence of metal and correlated Mott insulator phases near the insulator-metal transition (T = 160-180 K) associated with percolation and an underlying structural phase transition. Augmented with macroscopic temperature-resolved X-ray diffraction measurements of the same film, a quantitative analysis of nano-infrared images acquired across the transition suggests decoupling of electronic and structural transformations. Persistent low-temperature metallicity is accompanied by unconventional dimensional scaling among metallic ``puddles,'' implicating relevance of a long-range Coulombic interaction through the film's first-order insulator-metal transition. The speaker and co-authors acknowledge support from DOE-DE-SC0012375, DOE-DE-SC0012592, and AFOSR Grant No. FA9550-12-1-0381. The speaker also acknowledges support from a US Dept. of Energy Office of Science Graduate Fellowship (DOE SCGF).
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Regional gray matter correlates of vocational interests
2012-01-01
Background Previous studies have identified brain areas related to cognitive abilities and personality, respectively. In this exploratory study, we extend the application of modern neuroimaging techniques to another area of individual differences, vocational interests, and relate the results to an earlier study of cognitive abilities salient for vocations. Findings First, we examined the psychometric relationships between vocational interests and abilities in a large sample. The primary relationships between those domains were between Investigative (scientific) interests and general intelligence and between Realistic (“blue-collar”) interests and spatial ability. Then, using MRI and voxel-based morphometry, we investigated the relationships between regional gray matter volume and vocational interests. Specific clusters of gray matter were found to be correlated with Investigative and Realistic interests. Overlap analyses indicated some common brain areas between the correlates of Investigative interests and general intelligence and between the correlates of Realistic interests and spatial ability. Conclusions Two of six vocational-interest scales show substantial relationships with regional gray matter volume. The overlap between the brain correlates of these scales and cognitive-ability factors suggest there are relationships between individual differences in brain structure and vocations. PMID:22591829
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Regional gray matter correlates of vocational interests.
Schroeder, David H; Haier, Richard J; Tang, Cheuk Ying
2012-05-16
Previous studies have identified brain areas related to cognitive abilities and personality, respectively. In this exploratory study, we extend the application of modern neuroimaging techniques to another area of individual differences, vocational interests, and relate the results to an earlier study of cognitive abilities salient for vocations. First, we examined the psychometric relationships between vocational interests and abilities in a large sample. The primary relationships between those domains were between Investigative (scientific) interests and general intelligence and between Realistic ("blue-collar") interests and spatial ability. Then, using MRI and voxel-based morphometry, we investigated the relationships between regional gray matter volume and vocational interests. Specific clusters of gray matter were found to be correlated with Investigative and Realistic interests. Overlap analyses indicated some common brain areas between the correlates of Investigative interests and general intelligence and between the correlates of Realistic interests and spatial ability. Two of six vocational-interest scales show substantial relationships with regional gray matter volume. The overlap between the brain correlates of these scales and cognitive-ability factors suggest there are relationships between individual differences in brain structure and vocations.
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Thompson, Stacey Lee; Bérubé, Yanik; Bruneau, Anne; Ritland, Kermit
2008-10-01
Asexual reproduction has the potential to promote population structuring through matings between clones as well as through limited dispersal of related progeny. Here we present an application of three-gene identity coefficients that tests whether clonal reproduction promotes inbreeding and spatial relatedness within populations. With this method, the first two genes are sampled to estimate pairwise relatedness or inbreeding, whereas the third gene is sampled from either a clone or a sexually derived individual. If three-gene coefficients are significantly greater for clones than nonclones, then clonality contributes excessively to genetic structure. First, we describe an estimator of three-gene identity and briefly evaluate its properties. We then use this estimator to test the effect of clonality on the genetic structure within populations of yellow-cedar (Callitropsis nootkatensis) using a molecular marker survey. Five microsatellite loci were genotyped for 485 trees sampled from nine populations. Our three-gene analyses show that clonal ramets promote inbreeding and spatial structure in most populations. Among-population correlations between clonal extent and genetic structure generally support these trends, yet with less statistical significance. Clones appear to contribute to genetic structure through the limited dispersal of offspring from replicated ramets of the same clonal genet, whereas this structure is likely maintained by mating among these relatives.
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DOE Office of Scientific and Technical Information (OSTI.GOV)
Mace, R.E.; Nance, H.S.; Laubach, S.E.
1995-06-01
Faults and joints are conduits for ground-water flow and targets for horizontal drilling in the petroleum industry. Spacing and size distribution are rarely predicted accurately by current structural models or documented adequately by conventional borehole or outcrop samples. Tunnel excavations present opportunities to measure fracture attributes in continuous subsurface exposures. These fracture measurements ran be used to improve structural models, guide interpretation of conventional borehole and outcrop data, and geostatistically quantify spatial and spacing characteristics for comparison to outcrop data or for generating distributions of fracture for numerical flow and transport modeling. Structure maps of over 9 mi of nearlymore » continuous tunnel excavations in Austin Chalk at the Superconducting Super Collider (SSC) site in Ellis County, Texas, provide a unique database of fault and joint populations for geostatistical analysis. Observationally, small faults (<10 ft. throw) occur in clusters or swarms that have as many as 24 faults, fault swarms are as much as 2,000 ft. wide and appear to be on average 1,000 ft. apart, and joints are in swarms spaced 500 to more than 2l,000 ft. apart. Semi-variograms show varying degrees of spatial correlation. These variograms have structured sills that correlate directly to highs and lows in fracture frequency observed in the tunnel. Semi-variograms generated with respect to fracture spacing and number also have structured sills, but tend to not show any near-field correlation. The distribution of fault spacing can be described with a negative exponential, which suggests a random distribution. However, there is clearly some structure and clustering in the spacing data as shown by running average and variograms, which implies that a number of different methods should be utilized to characterize fracture spacing.« less
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Modular and hierarchical structure of social contact networks
NASA Astrophysics Data System (ADS)
Ge, Yuanzheng; Song, Zhichao; Qiu, Xiaogang; Song, Hongbin; Wang, Yong
2013-10-01
Social contact networks exhibit overlapping qualities of communities, hierarchical structure and spatial-correlated nature. We propose a mixing pattern of modular and growing hierarchical structures to reconstruct social contact networks by using an individual’s geospatial distribution information in the real world. The hierarchical structure of social contact networks is defined based on the spatial distance between individuals, and edges among individuals are added in turn from the modular layer to the highest layer. It is a gradual process to construct the hierarchical structure: from the basic modular model up to the global network. The proposed model not only shows hierarchically increasing degree distribution and large clustering coefficients in communities, but also exhibits spatial clustering features of individual distributions. As an evaluation of the method, we reconstruct a hierarchical contact network based on the investigation data of a university. Transmission experiments of influenza H1N1 are carried out on the generated social contact networks, and results show that the constructed network is efficient to reproduce the dynamic process of an outbreak and evaluate interventions. The reproduced spread process exhibits that the spatial clustering of infection is accordant with the clustering of network topology. Moreover, the effect of individual topological character on the spread of influenza is analyzed, and the experiment results indicate that the spread is limited by individual daily contact patterns and local clustering topology rather than individual degree.
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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.
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Zhou, Zhiyi; Bernard, Melanie R; Bonds, A B
2008-04-02
Spatiotemporal relationships among contour segments can influence synchronization of neural responses in the primary visual cortex. We performed a systematic study to dissociate the impact of spatial and temporal factors in the signaling of contour integration via synchrony. In addition, we characterized the temporal evolution of this process to clarify potential underlying mechanisms. With a 10 x 10 microelectrode array, we recorded the simultaneous activity of multiple cells in the cat primary visual cortex while stimulating with drifting sine-wave gratings. We preserved temporal integrity and systematically degraded spatial integrity of the sine-wave gratings by adding spatial noise. Neural synchronization was analyzed in the time and frequency domains by conducting cross-correlation and coherence analyses. The general association between neural spike trains depends strongly on spatial integrity, with coherence in the gamma band (35-70 Hz) showing greater sensitivity to the change of spatial structure than other frequency bands. Analysis of the temporal dynamics of synchronization in both time and frequency domains suggests that spike timing synchronization is triggered nearly instantaneously by coherent structure in the stimuli, whereas frequency-specific oscillatory components develop more slowly, presumably through network interactions. Our results suggest that, whereas temporal integrity is required for the generation of synchrony, spatial integrity is critical in triggering subsequent gamma band synchronization.
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Evaluation of Deep Learning Representations of Spatial Storm Data
NASA Astrophysics Data System (ADS)
Gagne, D. J., II; Haupt, S. E.; Nychka, D. W.
2017-12-01
The spatial structure of a severe thunderstorm and its surrounding environment provide useful information about the potential for severe weather hazards, including tornadoes, hail, and high winds. Statistics computed over the area of a storm or from the pre-storm environment can provide descriptive information but fail to capture structural information. Because the storm environment is a complex, high-dimensional space, identifying methods to encode important spatial storm information in a low-dimensional form should aid analysis and prediction of storms by statistical and machine learning models. Principal component analysis (PCA), a more traditional approach, transforms high-dimensional data into a set of linearly uncorrelated, orthogonal components ordered by the amount of variance explained by each component. The burgeoning field of deep learning offers two potential approaches to this problem. Convolutional Neural Networks are a supervised learning method for transforming spatial data into a hierarchical set of feature maps that correspond with relevant combinations of spatial structures in the data. Generative Adversarial Networks (GANs) are an unsupervised deep learning model that uses two neural networks trained against each other to produce encoded representations of spatial data. These different spatial encoding methods were evaluated on the prediction of severe hail for a large set of storm patches extracted from the NCAR convection-allowing ensemble. Each storm patch contains information about storm structure and the near-storm environment. Logistic regression and random forest models were trained using the PCA and GAN encodings of the storm data and were compared against the predictions from a convolutional neural network. All methods showed skill over climatology at predicting the probability of severe hail. However, the verification scores among the methods were very similar and the predictions were highly correlated. Further evaluations are being performed to determine how the choice of input variables affects the results.
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Bray, Signe
2017-05-01
Healthy brain development involves changes in brain structure and function that are believed to support cognitive maturation. However, understanding how structural changes such as grey matter thinning relate to functional changes is challenging. To gain insight into structure-function relationships in development, the present study took a data driven approach to define age-related patterns of variation in gray matter volume (GMV), cerebral blood flow (CBF) and blood-oxygen level dependent (BOLD) signal variation (fractional amplitude of low-frequency fluctuations; fALFF) in 59 healthy children aged 7-18 years, and examined relationships between modalities. Principal components analysis (PCA) was applied to each modality in parallel, and participant scores for the top components were assessed for age associations. We found that decompositions of CBF, GMV and fALFF all included components for which scores were significantly associated with age. The dominant patterns in GMV and CBF showed significant (GMV) or trend level (CBF) associations with age and a strong spatial overlap, driven by increased signal intensity in default mode network (DMN) regions. GMV, CBF and fALFF additionally showed components accounting for 3-5% of variability with significant age associations. However, these patterns were relatively spatially independent, with small-to-moderate overlap between modalities. Independence of age effects was further demonstrated by correlating individual subject maps between modalities: CBF was significantly less correlated with GMV and fALFF in older children relative to younger. These spatially independent effects of age suggest that the parallel decline observed in global GMV and CBF may not reflect spatially synchronized processes. Hum Brain Mapp 38:2398-2407, 2017. © 2017 Wiley Periodicals, Inc. © 2017 Wiley Periodicals, Inc.
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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.
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NASA Astrophysics Data System (ADS)
Feng, Hua; Olsen, Michael G.; Hill, James C.; Fox, Rodney O.
2007-06-01
Simultaneous velocity and concentration fields in a confined liquid-phase rectangular jet with a Reynolds number based on the hydraulic diameter of 50,000 (or 10,000 based on the velocity difference between streams and the jet exit dimension) and a Schmidt number of 1,250 were obtained by means of a combined particle image velocimetry (PIV) and planar laser-induced fluorescence (PLIF) system. Data were collected at the jet exit and six further downstream locations. The velocity and concentration field data were analyzed for flow statistics such as turbulent fluxes, turbulent viscosity and diffusivity, and turbulent Schmidt number ( Sc T ). The streamwise turbulent flux was found to be larger than the transverse turbulent flux, and the mean concentration gradient was not aligned with the turbulent flux vector. The average Sc T was found to vary both in streamwise and in cross stream directions and had a mean value around 0.8, a value consistent with the literature. Spatial correlation fields of turbulent fluxes and concentration were then determined. The R u'ϕ' correlation was elliptical in shape with a major axis tilted downward with respect to the streamwise axis, whereas the R v'ϕ' correlation was an ellipse with a major axis aligned with the cross-stream direction. Negative regions of R u'ϕ' were observed in the outer streams, and these negatively correlated regions decayed with downstream distance and finally disappeared altogether. The R ϕ'ϕ' correlation field was found to be an ellipse with the major axis inclined at about 45° with respect to the streamwise direction. Linear stochastic estimation was used to interpret spatial correlation data and to determine conditional flow structures. It is believed that a vortex street formed near the splitter plate is responsible for the negatively correlated region observed in the R u'ϕ' spatial correlations of turbulent fluxes. A positive concentration fluctuation event was observed to correspond to a finger of nearly uniform concentration fluid reaching out into the outer stream, whereas a negative event corresponds to a pocket of nearly uniform fluid being entrained from the outer stream into the center jet region. Large-scale vortical structures were observed in the conditional velocity fields with an elliptical shape and a streamwise major axis. The growth of the structure size increased linearly initially but then grew more slowly as the flow transitioned toward channel flow.
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Significance tests for functional data with complex dependence structure.
Staicu, Ana-Maria; Lahiri, Soumen N; Carroll, Raymond J
2015-01-01
We propose an L 2 -norm based global testing procedure for the null hypothesis that multiple group mean functions are equal, for functional data with complex dependence structure. Specifically, we consider the setting of functional data with a multilevel structure of the form groups-clusters or subjects-units, where the unit-level profiles are spatially correlated within the cluster, and the cluster-level data are independent. Orthogonal series expansions are used to approximate the group mean functions and the test statistic is estimated using the basis coefficients. The asymptotic null distribution of the test statistic is developed, under mild regularity conditions. To our knowledge this is the first work that studies hypothesis testing, when data have such complex multilevel functional and spatial structure. Two small-sample alternatives, including a novel block bootstrap for functional data, are proposed, and their performance is examined in simulation studies. The paper concludes with an illustration of a motivating experiment.
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Earliest evidence for the structure of Homo sapiens populations in Africa
NASA Astrophysics Data System (ADS)
Scerri, Eleanor M. L.; Drake, Nick A.; Jennings, Richard; Groucutt, Huw S.
2014-10-01
Understanding the structure and variation of Homo sapiens populations in Africa is critical for interpreting multiproxy evidence of their subsequent dispersals into Eurasia. However, there is no consensus on early H. sapiens demographic structure, or its effects on intra-African dispersals. Here, we show how a patchwork of ecological corridors and bottlenecks triggered a successive budding of populations across the Sahara. Using a temporally and spatially explicit palaeoenvironmental model, we found that the Sahara was not uniformly ameliorated between ∼130 and 75 thousand years ago (ka), as has been stated. Model integration with multivariate analyses of corresponding stone tools then revealed several spatially defined technological clusters which correlated with distinct palaeobiomes. Similarities between technological clusters were such that they decreased with distance except where connected by palaeohydrological networks. These results indicate that populations at the Eurasian gateway were strongly structured, which has implications for refining the demographic parameters of dispersals out of Africa.
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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.
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NASA Technical Reports Server (NTRS)
Maynard, J. D.
1983-01-01
This project involves the development of the Nearfield Acoustic Holography (NAH) technique (in particular its extension from single frequency to wideband noise measurement) and its application in a detailed study of the noise radiation characteristics of several samples of aircraft sidewall panels. With the extensive amount of information provided by the NAH technique, the properties of the sound field radiated by the panels may be correlated with their structure, mounting, and excitation (single frequency or wideband, spatially correlated or uncorrelated, structure-borne). The work accomplished at the beginning of this grant period included: (1) Calibration of the 256 microphone array and test of its accuracy. (2) extension of the facility to permit measurements on wideband noise sources. The extensions incuded the addition of high-speed data acquisition hardware and an array processor, and the development of new software. (3) Installation of motion picture graphics for correlating panel motion with structure, mounting, radiation, etc. (4) Development of new holographic data processing techniques.
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Robinson, Stacie J.; Samuel, Michael D.; Lopez, Davin L.; Shelton, Paul
2012-01-01
One of the pervasive challenges in landscape genetics is detecting gene flow patterns within continuous populations of highly mobile wildlife. Understanding population genetic structure within a continuous population can give insights into social structure, movement across the landscape and contact between populations, which influence ecological interactions, reproductive dynamics or pathogen transmission. We investigated the genetic structure of a large population of deer spanning the area of Wisconsin and Illinois, USA, affected by chronic wasting disease. We combined multiscale investigation, landscape genetic techniques and spatial statistical modelling to address the complex questions of landscape factors influencing population structure. We sampled over 2000 deer and used spatial autocorrelation and a spatial principal components analysis to describe the population genetic structure. We evaluated landscape effects on this pattern using a spatial autoregressive model within a model selection framework to test alternative hypotheses about gene flow. We found high levels of genetic connectivity, with gradients of variation across the large continuous population of white-tailed deer. At the fine scale, spatial clustering of related animals was correlated with the amount and arrangement of forested habitat. At the broader scale, impediments to dispersal were important to shaping genetic connectivity within the population. We found significant barrier effects of individual state and interstate highways and rivers. Our results offer an important understanding of deer biology and movement that will help inform the management of this species in an area where overabundance and disease spread are primary concerns.
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Flexural waves induced by electro-impulse deicing forces
NASA Technical Reports Server (NTRS)
Gien, P. H.
1990-01-01
The generation, reflection and propagation of flexural waves created by electroimpulsive deicing forces are demonstrated both experimentally and analytically in a thin circular plate and a thin semicylindrical shell. Analytical prediction of these waves with finite element models shows good correlation with acceleration and displacement measurements at discrete points on the structures studied. However, sensitivity to spurious flexural waves resulting from the spatial discretization of the structures is shown to be significant. Consideration is also given to composite structures as an extension of these studies.
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2017-01-01
Abstract While a topographic map of auditory space exists in the vertebrate midbrain, it is absent in the forebrain. Yet, both brain regions are implicated in sound localization. The heterogeneous spatial tuning of adjacent sites in the forebrain compared to the midbrain reflects different underlying circuitries, which is expected to affect the correlation structure, i.e., signal (similarity of tuning) and noise (trial-by-trial variability) correlations. Recent studies have drawn attention to the impact of response correlations on the information readout from a neural population. We thus analyzed the correlation structure in midbrain and forebrain regions of the barn owl’s auditory system. Tetrodes were used to record in the midbrain and two forebrain regions, Field L and the downstream auditory arcopallium (AAr), in anesthetized owls. Nearby neurons in the midbrain showed high signal and noise correlations (RNCs), consistent with shared inputs. As previously reported, Field L was arranged in random clusters of similarly tuned neurons. Interestingly, AAr neurons displayed homogeneous monotonic azimuth tuning, while response variability of nearby neurons was significantly less correlated than the midbrain. Using a decoding approach, we demonstrate that low RNC in AAr restricts the potentially detrimental effect it can have on information, assuming a rate code proposed for mammalian sound localization. This study harnesses the power of correlation structure analysis to investigate the coding of auditory space. Our findings demonstrate distinct correlation structures in the auditory midbrain and forebrain, which would be beneficial for a rate-code framework for sound localization in the nontopographic forebrain representation of auditory space. PMID:28674698
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NASA Astrophysics Data System (ADS)
Nano, Tomi; Escartin, Terenz; Karim, Karim S.; Cunningham, Ian A.
2016-03-01
The ability to improve visualization of structural information in digital radiography without increasing radiation exposures requires improved image quality across all spatial frequencies, especially at high frequencies. The detective quantum efficiency (DQE) as a function of spatial frequency quantifies image quality given by an x-ray detector. We present a method of increasing DQE at high spatial frequencies by improving the modulation transfer function (MTF) and reducing noise aliasing. The Apodized Aperature Pixel (AAP) design uses a detector with micro-elements to synthesize desired pixels and provide higher DQE than conventional detector designs. A cascaded system analysis (CSA) that incorporates x-ray interactions is used for comparison of the theoretical MTF, noise power spectrum (NPS), and DQE. Signal and noise transfer through the converter material is shown to consist of correlated an uncorrelated terms. The AAP design was shown to improve the DQE of both material types that have predominantly correlated transfer (such as CsI) and predominantly uncorrelated transfer (such as Se). Improvement in the MTF by 50% and the DQE by 100% at the sampling cut-off frequency is obtained when uncorrelated transfer is prevalent through the converter material. Optimizing high-frequency DQE results in improved image contrast and visualization of small structures and fine-detail.
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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 (
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Structure-specific magnetic field inhomogeneities and its effect on the correlation time.
Ziener, Christian H; Bauer, Wolfgang R; Melkus, Gerd; Weber, Thomas; Herold, Volker; Jakob, Peter M
2006-12-01
We describe the relationship between the correlation time and microscopic spatial inhomogeneities in the static magnetic field. The theory takes into account diffusion of nuclear spins in the inhomogeneous field created by magnetized objects. A simple general expression for the correlation time is obtained. It is shown that the correlation time is dependent on a characteristic length, the diffusion coefficient of surrounding medium, the permeability of the surface and the volume fraction of the magnetized objects. For specific geometries (spheres and cylinders), exact analytical expressions for the correlation time are given. The theory can be applied to contrast agents (magnetically labeled cells), capillary network, BOLD effect and so forth.
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NASA Astrophysics Data System (ADS)
Valous, N. A.; Delgado, A.; Drakakis, K.; Sun, D.-W.
2014-02-01
The study of plant tissue parenchyma's intercellular air spaces contributes to the understanding of anatomy and physiology. This is challenging due to difficulty in making direct measurements of the pore space and the complex mosaic of parenchymatous tissue. The architectural complexity of pore space has shown that single geometrical measurements are not sufficient for characterization. The inhomogeneity of distribution depends not only on the percentage content of phase, but also on how the phase fills the space. The lacunarity morphometric, as multiscale measure, provides information about the distribution of gaps that correspond to degree of spatial organization in parenchyma. Additionally, modern theories have suggested strategies, where the focus has shifted from the study of averages and histograms to the study of patterns in data fluctuations. Detrended fluctuation analysis provides information on the correlation properties of the parenchyma at different spatial scales. The aim is to quantify (with the aid of the aforementioned metrics), the mesostructural changes—that occur from one cycle of freezing and thawing—in the void phase of pome fruit parenchymatous tissue, acquired with X-ray microcomputed tomography. Complex systems methods provide numerical indices and detailed insights regarding the freezing-induced modifications upon the arrangement of cells and voids. These structural changes have the potential to lead to physiological disorders. The work can further stimulate interest for the analysis of internal plant tissue structures coupled with other physico-chemical processes or phenomena.
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Levashov, V A; Stepanov, M G
2016-01-01
Considerations of local atomic-level stresses associated with each atom represent a particular approach to address structures of disordered materials at the atomic level. We studied structural correlations in a two-dimensional model liquid using molecular dynamics simulations in the following way. We diagonalized the atomic-level stress tensor of every atom and investigated correlations between the eigenvalues and orientations of the eigenvectors of different atoms as a function of distance between them. It is demonstrated that the suggested approach can be used to characterize structural correlations in disordered materials. In particular, we found that changes in the stress correlation functions on decrease of temperature are the most pronounced for the pairs of atoms with separation distance that corresponds to the first minimum in the pair density function. We also show that the angular dependencies of the stress correlation functions previously reported by Wu et al. [Phys. Rev. E 91, 032301 (2015)10.1103/PhysRevE.91.032301] do not represent the anisotropic Eshelby's stress fields, as it is suggested, but originate in the rotational properties of the stress tensors.
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X-ray microtomography analysis of soil structure deformation caused by centrifugation
NASA Astrophysics Data System (ADS)
Schlüter, Steffen; Leuther, Frederic; Vogler, Steffen; Vogel, Hans-Jörg
2016-04-01
Centrifugation provides a fast method to measure soil water retention curves over a wide moisture range. However, deformation of soil structure may occur at high angular velocities in the centrifuge. The objective of this study was to capture these changes in soil structure with X-ray microtomography and to measure local deformations via digital volume correlation. Two samples were investigated that differ in texture and rock content. A detailed analysis of the pore space reveals an interplay between shrinkage due to drying and soil compaction due to compression. Macroporosity increases at moderate angular velocity because of crack formation due to moisture release. At higher angular velocities, corresponding to capillary pressure of <-100kPa, macroporosity decreases again because of structure deformation due to compression. While volume changes due to swelling clay minerals are immanent to any drying process, the compaction of soil is a specific drawback of the centrifugation method. A new protocol for digital volume correlation was developed to analyze the spatial heterogeneity of deformation. In both samples the displacement of soil constituents is highest in the top part of the sample and exhibits high lateral variability explained by the spatial distribution of macropores in the sample. Centrifugation should therefore only be applied after the completion of all other hydraulic or thermal experiments, or any other analysis that depends on the integrity of soil structure.
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X-ray microtomography analysis of soil structure deformation caused by centrifugation
NASA Astrophysics Data System (ADS)
Schlüter, S.; Leuther, F.; Vogler, S.; Vogel, H.-J.
2016-01-01
Centrifugation provides a fast method to measure soil water retention curves over a wide moisture range. However, deformation of soil structure may occur at high angular velocities in the centrifuge. The objective of this study was to capture these changes in soil structure with X-ray microtomography and to measure local deformations via digital volume correlation. Two samples were investigated that differ in texture and rock content. A detailed analysis of the pore space reveals an interplay between shrinkage due to drying and soil compaction due to compression. Macroporosity increases at moderate angular velocity because of crack formation due to moisture release. At higher angular velocities, corresponding to capillary pressure of ψ < -100 kPa, macroporosity decreases again because of structure deformation due to compression. While volume changes due to swelling clay minerals are immanent in any drying process, the compaction of soil is a specific drawback of the centrifugation method. A new protocol for digital volume correlation was developed to analyze the spatial heterogeneity of deformation. In both samples the displacement of soil constituents is highest in the top part of the sample and exhibits high lateral variability explained by the spatial distribution of macropores in the sample. Centrifugation should therefore only be applied after the completion of all other hydraulic or thermal experiments, or any other analysis that depends on the integrity of soil structure.
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[Study on ecological suitability regionalization of Eucommia ulmoides in Guizhou].
Kang, Chuan-Zhi; Wang, Qing-Qing; Zhou, Tao; Jiang, Wei-Ke; Xiao, Cheng-Hong; Xie, Yu
2014-05-01
To study the ecological suitability regionalization of Eucommia ulmoides, for selecting artificial planting base and high-quality industrial raw material purchase area of the herb in Guizhou. Based on the investigation of 14 Eucommia ulmoides producing areas, pinoresinol diglucoside content and ecological factors were obtained. Using spatial analysis method to carry on ecological suitability regionalization. Meanwhile, combining pinoresinol diglucoside content, the correlation of major active components and environmental factors were analyzed by statistical analysis. The most suitability planting area of Eucommia ulmoides was the northwest of Guizhou. The distribution of Eucommia ulmoides was mainly affected by the type and pH value of soil, and monthly precipitation. The spatial structure of major active components in Eucommia ulmoides were randomly distributed in global space, but had only one aggregation point which had a high positive correlation in local space. The major active components of Eucommia ulmoides had no correlation with altitude, longitude or latitude. Using the spatial analysis method and statistical analysis method, based on environmental factor and pinoresinol diglucoside content, the ecological suitability regionalization of Eucommia ulmoides can provide reference for the selection of suitable planting area, artificial planting base and directing production layout.
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Spatio-temporal wildland arson crime functions
David T. Butry; Jeffrey P. Prestemon
2005-01-01
Wildland arson creates damages to structures and timber and affects the health and safety of people living in rural and wildland urban interface areas. We develop a model that incorporates temporal autocorrelations and spatial correlations in wildland arson ignitions in Florida. A Poisson autoregressive model of order p, or PAR(p)...
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An Investigation of Calculus Learning Using Factorial Modeling.
ERIC Educational Resources Information Center
Dick, Thomas P.; Balomenos, Richard H.
Structural covariance models that would explain the correlations observed among mathematics achievement and participation measures and related cognitive and affective variables were developed. A sample of college calculus students (N=268; 124 females and 144 males) was administered a battery of cognitive tests (including measures of spatial-visual…
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Advanced analysis of complex seismic waveforms to characterize the subsurface Earth structure
NASA Astrophysics Data System (ADS)
Jia, Tianxia
2011-12-01
This thesis includes three major parts, (1) Body wave analysis of mantle structure under the Calabria slab, (2) Spatial Average Coherency (SPAC) analysis of microtremor to characterize the subsurface structure in urban areas, and (3) Surface wave dispersion inversion for shear wave velocity structure. Although these three projects apply different techniques and investigate different parts of the Earth, their aims are the same, which is to better understand and characterize the subsurface Earth structure by analyzing complex seismic waveforms that are recorded on the Earth surface. My first project is body wave analysis of mantle structure under the Calabria slab. Its aim is to better understand the subduction structure of the Calabria slab by analyzing seismograms generated by natural earthquakes. The rollback and subduction of the Calabrian Arc beneath the southern Tyrrhenian Sea is a case study of slab morphology and slab-mantle interactions at short spatial scale. I analyzed the seismograms traversing the Calabrian slab and upper mantle wedge under the southern Tyrrhenian Sea through body wave dispersion, scattering and attenuation, which are recorded during the PASSCAL CAT/SCAN experiment. Compressional body waves exhibit dispersion correlating with slab paths, which is high-frequency components arrivals being delayed relative to low-frequency components. Body wave scattering and attenuation are also spatially correlated with slab paths. I used this correlation to estimate the positions of slab boundaries, and further suggested that the observed spatial variation in near-slab attenuation could be ascribed to mantle flow patterns around the slab. My second project is Spatial Average Coherency (SPAC) analysis of microtremors for subsurface structure characterization. Shear-wave velocity (Vs) information in soil and rock has been recognized as a critical parameter for site-specific ground motion prediction study, which is highly necessary for urban areas located in seismic active zones. SPAC analysis of microtremors provides an efficient way to estimate Vs structure. Compared with other Vs estimating methods, SPAC is noninvasive and does not require any active sources, and therefore, it is especially useful in big cities. I applied SPAC method in two urban areas. The first is the historic city, Charleston, South Carolina, where high levels of seismic hazard lead to great public concern. Accurate Vs information, therefore, is critical for seismic site classification and site response studies. The second SPAC study is in Manhattan, New York City, where depths of high velocity contrast and soil-to-bedrock are different along the island. The two experiments show that Vs structure could be estimated with good accuracy using SPAC method compared with borehole and other techniques. SPAC is proved to be an effective technique for Vs estimation in urban areas. One important issue in seismology is the inversion of subsurface structures from surface recordings of seismograms. My third project focuses on solving this complex geophysical inverse problems, specifically, surface wave phase velocity dispersion curve inversion for shear wave velocity. In addition to standard linear inversion, I developed advanced inversion techniques including joint inversion using borehole data as constrains, nonlinear inversion using Monte Carlo, and Simulated Annealing algorithms. One innovative way of solving the inverse problem is to make inference from the ensemble of all acceptable models. The statistical features of the ensemble provide a better way to characterize the Earth model.
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NASA Astrophysics Data System (ADS)
Sund, Nicole L.; Bolster, Diogo; Dawson, Clint
2015-11-01
In this study we extend the Spatial Markov model, which has been successfully used to upscale conservative transport across a diverse range of porous media flows, to test if it can accurately upscale reactive transport, defined by a spatially heterogeneous first order degradation rate. We test the model in a well known highly simplified geometry, commonly considered as an idealized pore or fracture structure, a periodic channel with wavy boundaries. The edges of the flow domain have a layer through which there is no flow, but in which diffusion of a solute still occurs. Reactions are confined to this region. We demonstrate that the Spatial Markov model, an upscaled random walk model that enforces correlation between successive jumps, can reproduce breakthrough curves measured from microscale simulations that explicitly resolve all pertinent processes. We also demonstrate that a similar random walk model that does not enforce successive correlations is unable to reproduce all features of the measured breakthrough curves.
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Uniform functional structure across spatial scales in an intertidal benthic assemblage.
Barnes, R S K; Hamylton, Sarah
2015-05-01
To investigate the causes of the remarkable similarity of emergent assemblage properties that has been demonstrated across disparate intertidal seagrass sites and assemblages, this study examined whether their emergent functional-group metrics are scale related by testing the null hypothesis that functional diversity and the suite of dominant functional groups in seagrass-associated macrofauna are robust structural features of such assemblages and do not vary spatially across nested scales within a 0.4 ha area. This was carried out via a lattice of 64 spatially referenced stations. Although densities of individual components were patchily dispersed across the locality, rank orders of importance of the 14 functional groups present, their overall functional diversity and evenness, and the proportions of the total individuals contained within each showed, in contrast, statistically significant spatial uniformity, even at areal scales <2 m(2). Analysis of the proportional importance of the functional groups in their geospatial context also revealed weaker than expected levels of spatial autocorrelation, and then only at the smaller scales and amongst the most dominant groups, and only a small number of negative correlations occurred between the proportional importances of the individual groups. In effect, such patterning was a surface veneer overlying remarkable stability of assemblage functional composition across all spatial scales. Although assemblage species composition is known to be homogeneous in some soft-sediment marine systems over equivalent scales, this combination of patchy individual components yet basically constant functional-group structure seems as yet unreported. Copyright © 2015 Elsevier Ltd. All rights reserved.
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Rasic, Gordana; Keyghobadi, Nusha
2012-01-01
The spatial scale at which samples are collected and analysed influences the inferences that can be drawn from landscape genetic studies. We examined genetic structure and its landscape correlates in the pitcher plant midge, Metriocnemus knabi, an inhabitant of the purple pitcher plant, Sarracenia purpurea, across several spatial scales that are naturally delimited by the midge's habitat (leaf, plant, cluster of plants, bog and system of bogs). We analysed 11 microsatellite loci in 710 M. knabi larvae from two systems of bogs in Algonquin Provincial Park (Canada) and tested the hypotheses that variables related to habitat structure are associated with genetic differentiation in this midge. Up to 54% of variation in individual-based genetic distances at several scales was explained by broadscale landscape variables of bog size, pitcher plant density within bogs and connectivity of pitcher plant clusters. Our results indicate that oviposition behaviour of females at fine scales, as inferred from the spatial locations of full-sib larvae, and spatially limited gene flow at broad scales represent the important processes underlying observed genetic patterns in M. knabi. Broadscale landscape features (bog size and plant density) appear to influence oviposition behaviour of midges, which in turn influences the patterns of genetic differentiation observed at both fine and broad scales. Thus, we inferred linkages among genetic patterns, landscape patterns and ecological processes across spatial scales in M. knabi. Our results reinforce the value of exploring such links simultaneously across multiple spatial scales and landscapes when investigating genetic diversity within a species. © 2011 Blackwell Publishing Ltd.
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Fiber fault location utilizing traffic signal in optical network.
Zhao, Tong; Wang, Anbang; Wang, Yuncai; Zhang, Mingjiang; Chang, Xiaoming; Xiong, Lijuan; Hao, Yi
2013-10-07
We propose and experimentally demonstrate a method for fault location in optical communication network. This method utilizes the traffic signal transmitted across the network as probe signal, and then locates the fault by correlation technique. Compared with conventional techniques, our method has a simple structure and low operation expenditure, because no additional device is used, such as light source, modulator and signal generator. The correlation detection in this method overcomes the tradeoff between spatial resolution and measurement range in pulse ranging technique. Moreover, signal extraction process can improve the location result considerably. Experimental results show that we achieve a spatial resolution of 8 cm and detection range of over 23 km with -8-dBm mean launched power in optical network based on synchronous digital hierarchy protocols.
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Marsden, Clare D; Woodroffe, Rosie; Mills, Michael G L; McNutt, J Weldon; Creel, Scott; Groom, Rosemary; Emmanuel, Masenga; Cleaveland, Sarah; Kat, Pieter; Rasmussen, Gregory S A; Ginsberg, Joshua; Lines, Robin; André, Jean-Marc; Begg, Colleen; Wayne, Robert K; Mable, Barbara K
2012-03-01
Deciphering patterns of genetic variation within a species is essential for understanding population structure, local adaptation and differences in diversity between populations. Whilst neutrally evolving genetic markers can be used to elucidate demographic processes and genetic structure, they are not subject to selection and therefore are not informative about patterns of adaptive variation. As such, assessments of pertinent adaptive loci, such as the immunity genes of the major histocompatibility complex (MHC), are increasingly being incorporated into genetic studies. In this study, we combined neutral (microsatellite, mtDNA) and adaptive (MHC class II DLA-DRB1 locus) markers to elucidate the factors influencing patterns of genetic variation in the African wild dog (Lycaon pictus); an endangered canid that has suffered extensive declines in distribution and abundance. Our genetic analyses found all extant wild dog populations to be relatively small (N(e) < 30). Furthermore, through coalescent modelling, we detected a genetic signature of a recent and substantial demographic decline, which correlates with human expansion, but contrasts with findings in some other African mammals. We found strong structuring of wild dog populations, indicating the negative influence of extensive habitat fragmentation and loss of gene flow between habitat patches. Across populations, we found that the spatial and temporal structure of microsatellite diversity and MHC diversity were correlated and strongly influenced by demographic stability and population size, indicating the effects of genetic drift in these small populations. Despite this correlation, we detected signatures of selection at the MHC, implying that selection has not been completely overwhelmed by genetic drift. © 2012 Blackwell Publishing Ltd.
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Chung, Mi Yoon; Nason, John D; Chung, Myong Gi
2007-07-01
Spatial genetic structure within plant populations is influenced by variation in demographic processes through space and time, including a population's successional status. To determine how demographic structure and fine-scale genetic structure (FSGS) change with stages in a population's successional history, we studied Hemerocallis thunbergii (Liliaceae), a nocturnal flowering and hawkmoth-pollinated herbaceous perennial with rapid population turnover dynamics. We examined nine populations assigned to three successive stages of population succession: expansion, maturation, and senescence. We developed stage-specific expectations for within-population demographic and genetic structure, and then for each population quantified the spatial aggregation of individuals and genotypes using spatial autocorrelation methods (nonaccumulative O-ring and kinship statistics, respectively), and at the landscape level measured inbreeding and genetic structure using Wright's F-statistics. Analyses using the O-ring statistic revealed significant aggregation of individuals at short spatial scales in expanding and senescing populations, in particular, which may reflect restricted seed dispersal around maternal individuals combined with relatively low local population densities at these stages. Significant FSGS was found for three of four expanding, no mature, and only one senescing population, a pattern generally consistent with expectations of successional processes. Although allozyme genetic diversity was high within populations (mean %P = 78.9 and H(E) = 0.281), landscape-level differentiation among sites was also high (F(ST) = 0.166) and all populations exhibited a significant deficit of heterozygotes relative to Hardy-Weinberg expectations (range F = 0.201-0.424, mean F(IS) = 0.321). Within populations, F was not correlated with the degree of FSGS, thus suggesting inbreeding due primarily to selfing as opposed to mating among close relatives in spatially structured populations. Our results demonstrate considerable variation in the spatial distribution of individuals and patterns and magnitude of FSGS in H. thunbergii populations across the landscape. This variation is generally consistent with succession-stage-specific differences in ecological processes operating within these populations.
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Spatial Linkage and Urban Expansion: AN Urban Agglomeration View
NASA Astrophysics Data System (ADS)
Jiao, L. M.; Tang, X.; Liu, X. P.
2017-09-01
Urban expansion displays different characteristics in each period. From the perspective of the urban agglomeration, studying the spatial and temporal characteristics of urban expansion plays an important role in understanding the complex relationship between urban expansion and network structure of urban agglomeration. We analyze urban expansion in the Yangtze River Delta Urban Agglomeration (YRD) through accessibility to and spatial interaction intensity from core cities as well as accessibility of road network. Results show that: (1) Correlation between urban expansion intensity and spatial indicators such as location and space syntax variables is remarkable and positive, while it decreases after rapid expansion. (2) Urban expansion velocity displays a positive correlation with spatial indicators mentioned above in the first (1980-1990) and second (1990-2000) period. However, it exhibits a negative relationship in the third period (2000-2010), i.e., cities located in the periphery of urban agglomeration developing more quickly. Consequently, the hypothesis of convergence of urban expansion in rapid expansion stage is put forward. (3) Results of Zipf's law and Gibrat's law show urban expansion in YRD displays a convergent trend in rapid expansion stage, small and medium-sized cities growing faster. This study shows that spatial linkage plays an important but evolving role in urban expansion within the urban agglomeration. In addition, it serves as a reference to the planning of Yangtze River Delta Urban Agglomeration and regulation of urban expansion of other urban agglomerations.
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NASA Astrophysics Data System (ADS)
Tang, Yunwei; Atkinson, Peter M.; Zhang, Jingxiong
2015-03-01
A cross-scale data integration method was developed and tested based on the theory of geostatistics and multiple-point geostatistics (MPG). The goal was to downscale remotely sensed images while retaining spatial structure by integrating images at different spatial resolutions. During the process of downscaling, a rich spatial correlation model in the form of a training image was incorporated to facilitate reproduction of similar local patterns in the simulated images. Area-to-point cokriging (ATPCK) was used as locally varying mean (LVM) (i.e., soft data) to deal with the change of support problem (COSP) for cross-scale integration, which MPG cannot achieve alone. Several pairs of spectral bands of remotely sensed images were tested for integration within different cross-scale case studies. The experiment shows that MPG can restore the spatial structure of the image at a fine spatial resolution given the training image and conditioning data. The super-resolution image can be predicted using the proposed method, which cannot be realised using most data integration methods. The results show that ATPCK-MPG approach can achieve greater accuracy than methods which do not account for the change of support issue.
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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.
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Santora, Jarrod A; Schroeder, Isaac D; Field, John C; Wells, Brian K; Sydeman, William J
Studies of predator–prey demographic responses and the physical drivers of such relationships are rare, yet essential for predicting future changes in the structure and dynamics of marine ecosystems. Here, we hypothesize that predator–prey relationships vary spatially in association with underlying physical ocean conditions, leading to observable changes in demographic rates, such as reproduction. To test this hypothesis, we quantified spatio-temporal variability in hydrographic conditions, krill, and forage fish to model predator (seabird) demographic responses over 18 years (1990–2007). We used principal component analysis and spatial correlation maps to assess coherence among ocean conditions, krill, and forage fish, and generalized additive models to quantify interannual variability in seabird breeding success relative to prey abundance. The first principal component of four hydrographic measurements yielded an index that partitioned “warm/weak upwelling” and “cool/strong upwelling” years. Partitioning of krill and forage fish time series among shelf and oceanic regions yielded spatially explicit indicators of prey availability. Krill abundance within the oceanic region was remarkably consistent between years, whereas krill over the shelf showed marked interannual fluctuations in relation to ocean conditions. Anchovy abundance varied on the shelf, and was greater in years of strong stratification, weak upwelling and warmer temperatures. Spatio-temporal variability of juvenile forage fish co-varied strongly with each other and with krill, but was weakly correlated with hydrographic conditions. Demographic responses between seabirds and prey availability revealed spatially variable associations indicative of the dynamic nature of “predator–habitat” relationships. Quantification of spatially explicit demographic responses, and their variability through time, demonstrate the possibility of delineating specific critical areas where the implementation of protective measures could maintain functions and productivity of central place foraging predators.
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Effects of calcium leaching on diffusion properties of hardened and altered cement pastes
NASA Astrophysics Data System (ADS)
Kurumisawa, Kiyofumi; Haga, Kazuko; Hayashi, Daisuke; Owada, Hitoshi
2017-06-01
It is very important to predict alterations in the concrete used for fabricating disposal containers for radioactive waste. Therefore, it is necessary to understand the alteration of cementitious materials caused by calcium leaching when they are in contact with ground water in the long term. To evaluate the long-term transport characteristics of cementitious materials, the microstructural behavior of these materials should be considered. However, many predictive models of transport characteristics focus on the pore structure, while only few such models consider both, the spatial distribution of calcium silicate hydrate (C-S-H), portlandite, and the pore spaces. This study focused on the spatial distribution of these cement phases. The auto-correlation function of each phase of cementitious materials was calculated from two-dimensional backscattered electron imaging, and the three-dimensional spatial image of the cementitious material was produced using these auto-correlation functions. An attempt was made to estimate the diffusion coefficient of chloride from the three-dimensional spatial image. The estimated diffusion coefficient of the altered sample from the three-dimensional spatial image was found to be comparable to the measured value. This demonstrated that it is possible to predict the diffusion coefficient of the altered cement paste by using the proposed model.
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A Spatial Poisson Hurdle Model for Exploring Geographic Variation in Emergency Department Visits
Neelon, Brian; Ghosh, Pulak; Loebs, Patrick F.
2012-01-01
Summary We develop a spatial Poisson hurdle model to explore geographic variation in emergency department (ED) visits while accounting for zero inflation. The model consists of two components: a Bernoulli component that models the probability of any ED use (i.e., at least one ED visit per year), and a truncated Poisson component that models the number of ED visits given use. Together, these components address both the abundance of zeros and the right-skewed nature of the nonzero counts. The model has a hierarchical structure that incorporates patient- and area-level covariates, as well as spatially correlated random effects for each areal unit. Because regions with high rates of ED use are likely to have high expected counts among users, we model the spatial random effects via a bivariate conditionally autoregressive (CAR) prior, which introduces dependence between the components and provides spatial smoothing and sharing of information across neighboring regions. Using a simulation study, we show that modeling the between-component correlation reduces bias in parameter estimates. We adopt a Bayesian estimation approach, and the model can be fit using standard Bayesian software. We apply the model to a study of patient and neighborhood factors influencing emergency department use in Durham County, North Carolina. PMID:23543242
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Gryglewski, Gregor; Seiger, René; James, Gregory Miles; Godbersen, Godber Mathis; Komorowski, Arkadiusz; Unterholzner, Jakob; Michenthaler, Paul; Hahn, Andreas; Wadsak, Wolfgang; Mitterhauser, Markus; Kasper, Siegfried; Lanzenberger, Rupert
2018-08-01
The quantification of big pools of diverse molecules provides important insights on brain function, but is often restricted to a limited number of observations, which impairs integration with other modalities. To resolve this issue, a method allowing for the prediction of mRNA expression in the entire brain based on microarray data provided in the Allen Human Brain Atlas was developed. Microarray data of 3702 samples from 6 brain donors was registered to MNI and cortical surface space using FreeSurfer. For each of 18,686 genes, spatial dependence of transcription was assessed using variogram modelling. Variogram models were employed in Gaussian process regression to calculate best linear unbiased predictions for gene expression at all locations represented in well-established imaging atlases for cortex, subcortical structures and cerebellum. For validation, predicted whole-brain transcription of the HTR1A gene was correlated with [carbonyl- 11 C]WAY-100635 positron emission tomography data collected from 30 healthy subjects. Prediction results showed minimal bias ranging within ±0.016 (cortical surface), ±0.12 (subcortical regions) and ±0.14 (cerebellum) in units of log2 expression intensity for all genes. Across genes, the correlation of predicted and observed mRNA expression in leave-one-out cross-validation correlated with the strength of spatial dependence (cortical surface: r = 0.91, subcortical regions: r = 0.85, cerebellum: r = 0.84). 816 out of 18,686 genes exhibited a high spatial dependence accounting for more than 50% of variance in the difference of gene expression on the cortical surface. In subcortical regions and cerebellum, different sets of genes were implicated by high spatially structured variability. For the serotonin 1A receptor, correlation between PET binding potentials and predicted comprehensive mRNA expression was markedly higher (Spearman ρ = 0.72 for cortical surface, ρ = 0.84 for subcortical regions) than correlation of PET and discrete samples only (ρ = 0.55 and ρ = 0.63, respectively). Prediction of mRNA expression in the entire human brain allows for intuitive visualization of gene transcription and seamless integration in multimodal analysis without bias arising from non-uniform distribution of available samples. Extension of this methodology promises to facilitate translation of omics research and enable investigation of human brain function at a systems level. Copyright © 2018 Elsevier Inc. All rights reserved.
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Spatially resolved heat release rate measurements in turbulent premixed flames
DOE Office of Scientific and Technical Information (OSTI.GOV)
Ayoola, B.O.; Kaminski, C.F.; Balachandran, R.
Heat release rate is a fundamental property of great importance for the theoretical and experimental elucidation of unsteady flame behaviors such as combustion noise, combustion instabilities, and pulsed combustion. Investigations of such thermoacoustic interactions require a reliable indicator of heat release rate capable of resolving spatial structures in turbulent flames. Traditionally, heat release rate has been estimated via OH or CH radical chemiluminescence; however, chemiluminescence suffers from being a line-of-sight technique with limited capability for resolving small-scale structures. In this paper, we report spatially resolved two-dimensional measurements of a quantity closely related to heat release rate. The diagnostic technique usesmore » simultaneous OH and CH{sub 2}O planar laser-induced fluorescence (PLIF), and the pixel-by-pixel product of the OH and CH{sub 2}O PLIF signals has previously been shown to correlate well with local heat release rates. Results from this diagnostic technique, which we refer to as heat release rate imaging (HR imaging), are compared with traditional OH chemiluminescence measurements in several flames. Studies were performed in lean premixed ethylene flames stabilized between opposed jets and with a bluff body. Correlations between bulk strain rates and local heat release rates were obtained and the effects of curvature on heat release rate were investigated. The results show that the heat release rate tends to increase with increasing negative curvature for the flames investigated for which Lewis numbers are greater than unity. This correlation becomes more pronounced as the flame gets closer to global extinction.« less
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Dissociable brain biomarkers of fluid intelligence.
Paul, Erick J; Larsen, Ryan J; Nikolaidis, Aki; Ward, Nathan; Hillman, Charles H; Cohen, Neal J; Kramer, Arthur F; Barbey, Aron K
2016-08-15
Cognitive neuroscience has long sought to understand the biological foundations of human intelligence. Decades of research have revealed that general intelligence is correlated with two brain-based biomarkers: the concentration of the brain biochemical N-acetyl aspartate (NAA) measured by proton magnetic resonance spectroscopy (MRS) and total brain volume measured using structural MR imaging (MRI). However, the relative contribution of these biomarkers in predicting performance on core facets of human intelligence remains to be well characterized. In the present study, we sought to elucidate the role of NAA and brain volume in predicting fluid intelligence (Gf). Three canonical tests of Gf (BOMAT, Number Series, and Letter Sets) and three working memory tasks (Reading, Rotation, and Symmetry span tasks) were administered to a large sample of healthy adults (n=211). We conducted exploratory factor analysis to investigate the factor structure underlying Gf independent from working memory and observed two Gf components (verbal/spatial and quantitative reasoning) and one working memory component. Our findings revealed a dissociation between two brain biomarkers of Gf (controlling for age and sex): NAA concentration correlated with verbal/spatial reasoning, whereas brain volume correlated with quantitative reasoning and working memory. A follow-up analysis revealed that this pattern of findings is observed for males and females when analyzed separately. Our results provide novel evidence that distinct brain biomarkers are associated with specific facets of human intelligence, demonstrating that NAA and brain volume are independent predictors of verbal/spatial and quantitative facets of Gf. Copyright © 2016 The Authors. Published by Elsevier Inc. All rights reserved.
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Effects of Forest Disturbances on Forest Structural Parameters Retrieval from Lidar Waveform Data
NASA Technical Reports Server (NTRS)
Ranson, K, Lon; Sun, G.
2011-01-01
The effect of forest disturbance on the lidar waveform and the forest biomass estimation was demonstrated by model simulation. The results show that the correlation between stand biomass and the lidar waveform indices changes when the stand spatial structure changes due to disturbances rather than the natural succession. This has to be considered in developing algorithms for regional or global mapping of biomass from lidar waveform data.
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NASA Astrophysics Data System (ADS)
Yang, Yang; Dou, Yanxing; Liu, Dong; An, Shaoshan
2017-07-01
Spatial pattern and heterogeneity of soil moisture is important for the hydrological process on the Loess Plateau. This study combined the classical and geospatial statistical techniques to examine the spatial pattern and heterogeneity of soil moisture along a transect scale (e.g. land use types and topographical attributes) on the Loess Plateau. The average values of soil moisture were on the order of farmland > orchard > grassland > abandoned land > shrubland > forestland. Vertical distribution characteristics of soil moisture (0-500 cm) were similar among land use types. Highly significant (p < 0.01) negative correlations were found between soil moisture and elevation (h) except for shrubland (p > 0.05), whereas no significant correlations were found between soil moisture and plan curvature (Kh), stream power index (SPI), compound topographic index (CTI) (p > 0.05), indicating that topographical attributes (mainly h) have a negative effect on the soil moisture spatial heterogeneity. Besides, soil moisture spatial heterogeneity decreased from forestland to grassland and farmland, accompanied by a decline from 15° to 1° alongside upper to lower slope position. This study highlights the importance of land use types and topographical attributes on the soil moisture spatial heterogeneity from a combined analysis of the structural equation model (SEM) and generalized additive models (GAMs), and the relative contribution of land use types to the soil moisture spatial heterogeneity was higher than that of topographical attributes, which provides insights for researches focusing on soil moisture varitions on the Loess Plateau.
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Fine-scale genetic structure and social organization in female white-tailed deer.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Comer, Christopher E.; Kilgo, John C.; D'Angelo, Gino J.
Abstract: Social behavior of white-tailed deer (Odocoileus virginianus) can have important management implications. The formation of matrilineal social groups among female deer has been documented and management strategies have been proposed based on this well-developed social structure. Using radiocollared (n = 17) and hunter or vehicle-killed (n = 21) does, we examined spatial and genetic structure in white-tailed deer on a 7,000-ha portion of the Savannah River Site in the upper Coastal Plain of South Carolina, USA. We used 14 microsatellite DNA loci to calculate pairwise relatedness among individual deer and to assign doe pairs to putative relationship categories. Linearmore » distance and genetic relatedness were weakly correlated (r = –0.08, P = 0.058). Relationship categories differed in mean spatial distance, but only 60% of first-degree-related doe pairs (full sibling or mother–offspring pairs) and 38% of second-degree-related doe pairs (half sibling, grandmother–granddaughter pairs) were members of the same social group based on spatial association. Heavy hunting pressure in this population has created a young age structure among does, where the average age is <2.5 years, and <4% of does are >4.5 years old. This—combined with potentially elevated dispersal among young does—could limit the formation of persistent, cohesive social groups. Our results question the universal applicability of recently proposed models of spatial and genetic structuring in white-tailed deer, particularly in areas with differing harvest histories.« less
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Cho, Hanna; Kim, Jin Su; Choi, Jae Yong; Ryu, Young Hoon; Lyoo, Chul Hyoung
2014-01-01
We developed a new computed tomography (CT)-based spatial normalization method and CT template to demonstrate its usefulness in spatial normalization of positron emission tomography (PET) images with [(18)F] fluorodeoxyglucose (FDG) PET studies in healthy controls. Seventy healthy controls underwent brain CT scan (120 KeV, 180 mAs, and 3 mm of thickness) and [(18)F] FDG PET scans using a PET/CT scanner. T1-weighted magnetic resonance (MR) images were acquired for all subjects. By averaging skull-stripped and spatially-normalized MR and CT images, we created skull-stripped MR and CT templates for spatial normalization. The skull-stripped MR and CT images were spatially normalized to each structural template. PET images were spatially normalized by applying spatial transformation parameters to normalize skull-stripped MR and CT images. A conventional perfusion PET template was used for PET-based spatial normalization. Regional standardized uptake values (SUV) measured by overlaying the template volume of interest (VOI) were compared to those measured with FreeSurfer-generated VOI (FSVOI). All three spatial normalization methods underestimated regional SUV values by 0.3-20% compared to those measured with FSVOI. The CT-based method showed slightly greater underestimation bias. Regional SUV values derived from all three spatial normalization methods were correlated significantly (p < 0.0001) with those measured with FSVOI. CT-based spatial normalization may be an alternative method for structure-based spatial normalization of [(18)F] FDG PET when MR imaging is unavailable. Therefore, it is useful for PET/CT studies with various radiotracers whose uptake is expected to be limited to specific brain regions or highly variable within study population.
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Correlative cryogenic tomography of cells using light and soft x-rays.
Smith, Elizabeth A; Cinquin, Bertrand P; Do, Myan; McDermott, Gerry; Le Gros, Mark A; Larabell, Carolyn A
2014-08-01
Correlated imaging is the process of imaging a specimen with two complementary modalities, and then combining the two data sets to create a highly informative, composite view. A recent implementation of this concept has been the combination of soft x-ray tomography (SXT) with fluorescence cryogenic microscopy (FCM). SXT-FCM is used to visualize cells that are held in a near-native, cryopreserved. The resultant images are, therefore, highly representative of both the cellular architecture and molecular organization in vivo. SXT quantitatively visualizes the cell and sub-cellular structures; FCM images the spatial distribution of fluorescently labeled molecules. Here, we review the characteristics of SXT-FCM, and briefly discuss how this method compares with existing correlative imaging techniques. We also describe how the incorporation of a cryo-rotation stage into a cryogenic fluorescence microscope allows acquisition of fluorescence cryogenic tomography (FCT) data. FCT is optimally suited for correlation with SXT, since both techniques image the specimen in 3-D, potentially with similar, isotropic spatial resolution. © 2013 Elsevier B.V. All rights reserved.
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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.
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Spatial confinement induces hairpins in nicked circular DNA
Japaridze, Aleksandre; Orlandini, Enzo; Smith, Kathleen Beth; Gmür, Lucas; Valle, Francesco; Micheletti, Cristian
2017-01-01
Abstract In living cells, DNA is highly confined in space with the help of condensing agents, DNA binding proteins and high levels of supercoiling. Due to challenges associated with experimentally studying DNA under confinement, little is known about the impact of spatial confinement on the local structure of the DNA. Here, we have used well characterized slits of different sizes to collect high resolution atomic force microscopy images of confined circular DNA with the aim of assessing the impact of the spatial confinement on global and local conformational properties of DNA. Our findings, supported by numerical simulations, indicate that confinement imposes a large mechanical stress on the DNA as evidenced by a pronounced anisotropy and tangent–tangent correlation function with respect to non-constrained DNA. For the strongest confinement we observed nanometer sized hairpins and interwound structures associated with the nicked sites in the DNA sequence. Based on these findings, we propose that spatial DNA confinement in vivo can promote the formation of localized defects at mechanically weak sites that could be co-opted for biological regulatory functions. PMID:28201616
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The spatial pattern of suicide in the US in relation to deprivation, fragmentation and rurality.
Congdon, Peter
2011-01-01
Analysis of geographical patterns of suicide and psychiatric morbidity has demonstrated the impact of latent ecological variables (such as deprivation, rurality). Such latent variables may be derived by conventional multivariate techniques from sets of observed indices (for example, by principal components), by composite variable methods or by methods which explicitly consider the spatial framework of areas and, in particular, the spatial clustering of latent risks and outcomes. This article considers a latent random variable approach to explaining geographical contrasts in suicide in the US; and it develops a spatial structural equation model incorporating deprivation, social fragmentation and rurality. The approach allows for such latent spatial constructs to be correlated both within and between areas. Potential effects of area ethnic mix are also included. The model is applied to male and female suicide deaths over 2002–06 in 3142 US counties.
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Song, Xiaoying; Huang, Qijun; Chang, Sheng; He, Jin; Wang, Hao
2016-12-01
To address the low compression efficiency of lossless compression and the low image quality of general near-lossless compression, a novel near-lossless compression algorithm based on adaptive spatial prediction is proposed for medical sequence images for possible diagnostic use in this paper. The proposed method employs adaptive block size-based spatial prediction to predict blocks directly in the spatial domain and Lossless Hadamard Transform before quantization to improve the quality of reconstructed images. The block-based prediction breaks the pixel neighborhood constraint and takes full advantage of the local spatial correlations found in medical images. The adaptive block size guarantees a more rational division of images and the improved use of the local structure. The results indicate that the proposed algorithm can efficiently compress medical images and produces a better peak signal-to-noise ratio (PSNR) under the same pre-defined distortion than other near-lossless methods.
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Numerical simulation of backward erosion piping in heterogeneous fields
NASA Astrophysics Data System (ADS)
Liang, Yue; Yeh, Tian-Chyi Jim; Wang, Yu-Li; Liu, Mingwei; Wang, Junjie; Hao, Yonghong
2017-04-01
Backward erosion piping (BEP) is one of the major causes of seepage failures in levees. Seepage fields dictate the BEP behaviors and are influenced by the heterogeneity of soil properties. To investigate the effects of the heterogeneity on the seepage failures, we develop a numerical algorithm and conduct simulations to study BEP progressions in geologic media with spatially stochastic parameters. Specifically, the void ratio e, the hydraulic conductivity k, and the ratio of the particle contents r of the media are represented as the stochastic variables. They are characterized by means and variances, the spatial correlation structures, and the cross correlation between variables. Results of the simulations reveal that the heterogeneity accelerates the development of preferential flow paths, which profoundly increase the likelihood of seepage failures. To account for unknown heterogeneity, we define the probability of the seepage instability (PI) to evaluate the failure potential of a given site. Using Monte-Carlo simulation (MCS), we demonstrate that the PI value is significantly influenced by the mean and the variance of ln k and its spatial correlation scales. But the other parameters, such as means and variances of e and r, and their cross correlation, have minor impacts. Based on PI analyses, we introduce a risk rating system to classify the field into different regions according to risk levels. This rating system is useful for seepage failures prevention and assists decision making when BEP occurs.
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NASA Astrophysics Data System (ADS)
Lu, Feng; Liu, Kang; Duan, Yingying; Cheng, Shifen; Du, Fei
2018-07-01
A better characterization of the traffic influence among urban roads is crucial for traffic control and traffic forecasting. The existence of spatial heterogeneity imposes great influence on modeling the extent and degree of road traffic correlation, which is usually neglected by the traditional distance based method. In this paper, we propose a traffic-enhanced community detection approach to spatially reveal the traffic correlation in city road networks. First, the road network is modeled as a traffic-enhanced dual graph with the closeness between two road segments determined not only by their topological connection, but also by the traffic correlation between them. Then a flow-based community detection algorithm called Infomap is utilized to identify the road segment clusters. Evaluated by Moran's I, Calinski-Harabaz Index and the traffic interpolation application, we find that compared to the distance based method and the community based method, our proposed traffic-enhanced community based method behaves better in capturing the extent of traffic relevance as both the topological structure of the road network and the traffic correlations among urban roads are considered. It can be used in more traffic-related applications, such as traffic forecasting, traffic control and guidance.
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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.
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Integrative Spatial Data Analytics for Public Health Studies of New York State
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
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Urban structure and dengue fever in Puntarenas, Costa Rica
Troyo, Adriana; Fuller, Douglas O.; Calderón-Arguedas, Olger; Solano, Mayra E.; Beier, John C.
2009-01-01
Dengue is currently the most important arboviral disease globally and is usually associated with built environments in tropical areas. Remotely sensed information can facilitate the study of urban mosquito-borne diseases by providing multiple temporal and spatial resolutions appropriate to investigate urban structure and ecological characteristics associated with infectious disease. In this study, coarse, medium and fine resolution satellite imagery (Moderate Resolution Imaging Spectrometer, Advanced Spaceborne Thermal Emission and Reflection Radiometer and QuickBird respectively) and ground-based data were analyzed for the Greater Puntarenas area, Costa Rica for the years 2002–04. The results showed that the mean normalized difference vegetation index (NDVI) was generally higher in the localities with lower incidence of dengue fever during 2002, although the correlation was statistically significant only in the dry season (r=−0.40; p=0.03). Dengue incidence was inversely correlated to built area and directly correlated with tree cover (r=0.75, p=0.01). Overall, the significant correlations between dengue incidence and urban structural variables (tree cover and building density) suggest that properties of urban structure may be associated with dengue incidence in tropical urban settings. PMID:20161131
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Simulation of self-assembly of polyzwitterions into vesicles
Mahalik, Jyoti P.; Muthukumar, Murugappan
2016-08-19
Using the Langevin dynamics method and a coarse-grained model, we have researched the formation of vesicles by hydrophobic polymers consisting of periodically placed zwitterion side groups in dilute salt-free aqueous solutions. The zwitterions, being permanent charge dipoles, provide long-range electrostatic correlations which are interfered by the conformational entropy of the polymer. Our simulations are geared towards gaining conceptual understanding in these correlated dipolar systems, where theoretical calculations are at present formidable. A competition between hydrophobic interactions and dipole-dipole interactions leads to a series of self-assembled structures. As the spacing d between the successive zwitterion side groups decreases, single chains undergomore » globule → disk → worm-like structures. We have calculated the Flory-Huggins χ parameter for these systems in terms of d and monitored the radius of gyration, hydrodynamic radius, spatial correlations among hydrophobic and dipole monomers, and dipole-dipole orientational correlation functions. During the subsequent stages of self-assembly, these structures lead to larger globules and vesicles as d is decreased up to a threshold value, below which no large scale morphology forms. Finally the vesicles form via a polynucleation mechanism whereby disk-like structures form first, followed by their subsequent merger.« less
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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
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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
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Kinyoki, Damaris K; Kandala, Ngianga-Bakwin; Manda, Samuel O; Krainski, Elias T; Fuglstad, Geir-Arne; Moloney, Grainne M; Berkley, James A; Noor, Abdisalan M
2016-01-01
Objective Wasting and stunting may occur together at the individual child level; however, their shared geographic distribution and correlates remain unexplored. Understanding shared and separate correlates may inform interventions. We aimed to assess the spatial codistribution of wasting, stunting and underweight and investigate their shared correlates among children aged 6–59 months in Somalia. Setting Cross-sectional nutritional assessments surveys were conducted using structured interviews among communities in Somalia biannually from 2007 to 2010. A two-stage cluster sampling methodology was used to select children aged 6–59 months from households across three livelihood zones (pastoral, agropastoral and riverine). Using these data and environmental covariates, we implemented a multivariate spatial technique to estimate the codistribution and divergence of the risks and correlates of wasting and stunting at the 1×1 km spatial resolution. Participants 73 778 children aged 6–59 months from 1066 survey clusters in Somalia. Results Observed pairwise child level empirical correlations were 0.30, 0.70 and 0.73 between weight-for-height and height-for-age; height-for-age and weight-for-age, and weight-for-height and weight-for-age, respectively. Access to foods with high protein content and vegetation cover, a proxy of rainfall or drought, were associated with lower risk of wasting and stunting. Age, gender, illness, access to carbohydrates and temperature were correlates of all three indicators. The spatial codistribution was highest between stunting and underweight with relative risk values ranging between 0.15 and 6.20, followed by wasting and underweight (range: 0.18–5.18) and lowest between wasting and stunting (range: 0.26–4.32). Conclusions The determinants of wasting and stunting are largely shared, but their correlation is relatively variable in space. Significant hotspots of different forms of malnutrition occurred in the South Central regions of the country. Although nutrition response in Somalia has traditionally focused on wasting rather than stunting, integrated programming and interventions can effectively target both conditions to alleviate common risk factors. PMID:26962034
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Kinyoki, Damaris K; Kandala, Ngianga-Bakwin; Manda, Samuel O; Krainski, Elias T; Fuglstad, Geir-Arne; Moloney, Grainne M; Berkley, James A; Noor, Abdisalan M
2016-03-09
Wasting and stunting may occur together at the individual child level; however, their shared geographic distribution and correlates remain unexplored. Understanding shared and separate correlates may inform interventions. We aimed to assess the spatial codistribution of wasting, stunting and underweight and investigate their shared correlates among children aged 6-59 months in Somalia. Cross-sectional nutritional assessments surveys were conducted using structured interviews among communities in Somalia biannually from 2007 to 2010. A two-stage cluster sampling methodology was used to select children aged 6-59 months from households across three livelihood zones (pastoral, agropastoral and riverine). Using these data and environmental covariates, we implemented a multivariate spatial technique to estimate the codistribution and divergence of the risks and correlates of wasting and stunting at the 1 × 1 km spatial resolution. 73,778 children aged 6-59 months from 1066 survey clusters in Somalia. Observed pairwise child level empirical correlations were 0.30, 0.70 and 0.73 between weight-for-height and height-for-age; height-for-age and weight-for-age, and weight-for-height and weight-for-age, respectively. Access to foods with high protein content and vegetation cover, a proxy of rainfall or drought, were associated with lower risk of wasting and stunting. Age, gender, illness, access to carbohydrates and temperature were correlates of all three indicators. The spatial codistribution was highest between stunting and underweight with relative risk values ranging between 0.15 and 6.20, followed by wasting and underweight (range: 0.18-5.18) and lowest between wasting and stunting (range: 0.26-4.32). The determinants of wasting and stunting are largely shared, but their correlation is relatively variable in space. Significant hotspots of different forms of malnutrition occurred in the South Central regions of the country. Although nutrition response in Somalia has traditionally focused on wasting rather than stunting, integrated programming and interventions can effectively target both conditions to alleviate common risk factors. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://www.bmj.com/company/products-services/rights-and-licensing/
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NASA Technical Reports Server (NTRS)
Franklin, Rima B.; Blum, Linda K.; McComb, Alison C.; Mills, Aaron L.
2002-01-01
Small-scale variations in bacterial abundance and community structure were examined in salt marsh sediments from Virginia's eastern shore. Samples were collected at 5 cm intervals (horizontally) along a 50 cm elevation gradient, over a 215 cm horizontal transect. For each sample, bacterial abundance was determined using acridine orange direct counts and community structure was analyzed using randomly amplified polymorphic DNA fingerprinting of whole-community DNA extracts. A geostatistical analysis was used to determine the degree of spatial autocorrelation among the samples, for each variable and each direction (horizontal and vertical). The proportion of variance in bacterial abundance that could be accounted for by the spatial model was quite high (vertical: 60%, horizontal: 73%); significant autocorrelation was found among samples separated by 25 cm in the vertical direction and up to 115 cm horizontally. In contrast, most of the variability in community structure was not accounted for by simply considering the spatial separation of samples (vertical: 11%, horizontal: 22%), and must reflect variability from other parameters (e.g., variation at other spatial scales, experimental error, or environmental heterogeneity). Microbial community patch size based upon overall similarity in community structure varied between 17 cm (vertical) and 35 cm (horizontal). Overall, variability due to horizontal position (distance from the creek bank) was much smaller than that due to vertical position (elevation) for both community properties assayed. This suggests that processes more correlated with elevation (e.g., drainage and redox potential) vary at a smaller scale (therefore producing smaller patch sizes) than processes controlled by distance from the creek bank. c2002 Federation of European Microbiological Societies. Published by Elsevier Science B.V. All rights reserved.
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Liquid structure of dibutyl sulfoxide
Lo Celso, Fabrizio; Aoun, Bachir; Triolo, Alessandro; ...
2016-05-16
We present experimental (x-ray diffraction) data on the structure of liquid dibutyl sulfoxide at 320 K and rationalize them by means of Molecular Dynamics simulations. Not unexpectedly, DBSO bearing a strong dipolar moiety and two medium length, apolar, butyl chains, this compound turns out to be characterised by a distinct degree of polar-vs-apolar structural differentiation at the nm spatial scale that is fingerprinted in a low Q peak in its x-ray diffraction pattern. Similarly to, but to a larger extent than its shorter chain family members (such as DMSO), DBSO is also characterised by an enhanced dipole-dipole correlation that ismore » responsible for the moderate Kirkwood correlation factor as well as for the self-association detected in this compound. In conclusion, we show however that the supposedly relevant hydrogen bonding correlations between oxygen and butyl chain hydrogens are of limited extent and only in the case of α-hydrogens appreciable indication of the existence of such an interaction is found, but it turns out to be a mere consequence of the strong dipole-dipole correlation.« less
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NASA Technical Reports Server (NTRS)
Cavelier, C.; Scanvic, J. Y.; Weecksteen, G.; Zizerman, A.
1973-01-01
A preliminary study of the MSS imagery of a sedimentary basin whose structure is regular is reported. Crops and natural vegetation are distributed all over the site located under temperate climate. Ground data available concern plant species geology and tectonic and are correlated with results from ERTS 1 imagery. This comparison shows a good correlation. The main geological units are detected or enhanced by way of agricultural land use and/or natural vegetation. Alluvial deposits are outlined by vegetation grass land and poplar trees. Some spatial relationship of geostructures, suspected until now, are identified or extended in associating results from different spectral bands.
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Crotty, Patrick; García-Bellido, Juan; Lesgourgues, Julien; Riazuelo, Alain
2003-10-24
We obtain very stringent bounds on the possible cold dark matter, baryon, and neutrino isocurvature contributions to the primordial fluctuations in the Universe, using recent cosmic microwave background and large scale structure data. Neglecting the possible effects of spatial curvature, tensor perturbations, and reionization, we perform a Bayesian likelihood analysis with nine free parameters, and find that the amplitude of the isocurvature component cannot be larger than about 31% for the cold dark matter mode, 91% for the baryon mode, 76% for the neutrino density mode, and 60% for the neutrino velocity mode, at 2sigma, for uncorrelated models. For correlated adiabatic and isocurvature components, the fraction could be slightly larger. However, the cross-correlation coefficient is strongly constrained, and maximally correlated/anticorrelated models are disfavored. This puts strong bounds on the curvaton model.
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Spatial correlation of probabilistic earthquake ground motion and loss
Wesson, R.L.; Perkins, D.M.
2001-01-01
Spatial correlation of annual earthquake ground motions and losses can be used to estimate the variance of annual losses to a portfolio of properties exposed to earthquakes A direct method is described for the calculations of the spatial correlation of earthquake ground motions and losses. Calculations for the direct method can be carried out using either numerical quadrature or a discrete, matrix-based approach. Numerical results for this method are compared with those calculated from a simple Monte Carlo simulation. Spatial correlation of ground motion and loss is induced by the systematic attenuation of ground motion with distance from the source, by common site conditions, and by the finite length of fault ruptures. Spatial correlation is also strongly dependent on the partitioning of the variability, given an event, into interevent and intraevent components. Intraevent variability reduces the spatial correlation of losses. Interevent variability increases spatial correlation of losses. The higher the spatial correlation, the larger the variance in losses to a port-folio, and the more likely extreme values become. This result underscores the importance of accurately determining the relative magnitudes of intraevent and interevent variability in ground-motion studies, because of the strong impact in estimating earthquake losses to a portfolio. The direct method offers an alternative to simulation for calculating the variance of losses to a portfolio, which may reduce the amount of calculation required.
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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
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Ramsey, Lenny; Rengachary, Jennifer; Zinn, Kristi; Siegel, Joshua S.; Metcalf, Nicholas V.; Strube, Michael J.; Snyder, Abraham Z.; Corbetta, Maurizio; Shulman, Gordon L.
2016-01-01
Strokes often cause multiple behavioural deficits that are correlated at the population level. Here, we show that motor and attention deficits are selectively associated with abnormal patterns of resting state functional connectivity in the dorsal attention and motor networks. We measured attention and motor deficits in 44 right hemisphere-damaged patients with a first-time stroke at 1–2 weeks post-onset. The motor battery included tests that evaluated deficits in both upper and lower extremities. The attention battery assessed both spatial and non-spatial attention deficits. Summary measures for motor and attention deficits were identified through principal component analyses on the raw behavioural scores. Functional connectivity in structurally normal cortex was estimated based on the temporal correlation of blood oxygenation level-dependent signals measured at rest with functional magnetic resonance imaging. Any correlation between motor and attention deficits and between functional connectivity in the dorsal attention network and motor networks that might spuriously affect the relationship between each deficit and functional connectivity was statistically removed. We report a double dissociation between abnormal functional connectivity patterns and attention and motor deficits, respectively. Attention deficits were significantly more correlated with abnormal interhemispheric functional connectivity within the dorsal attention network than motor networks, while motor deficits were significantly more correlated with abnormal interhemispheric functional connectivity patterns within the motor networks than dorsal attention network. These findings indicate that functional connectivity patterns in structurally normal cortex following a stroke link abnormal physiology in brain networks to the corresponding behavioural deficits. PMID:27225794
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Map LineUps: Effects of spatial structure on graphical inference.
Beecham, Roger; Dykes, Jason; Meulemans, Wouter; Slingsby, Aidan; Turkay, Cagatay; Wood, Jo
2017-01-01
Fundamental to the effective use of visualization as an analytic and descriptive tool is the assurance that presenting data visually provides the capability of making inferences from what we see. This paper explores two related approaches to quantifying the confidence we may have in making visual inferences from mapped geospatial data. We adapt Wickham et al.'s 'Visual Line-up' method as a direct analogy with Null Hypothesis Significance Testing (NHST) and propose a new approach for generating more credible spatial null hypotheses. Rather than using as a spatial null hypothesis the unrealistic assumption of complete spatial randomness, we propose spatially autocorrelated simulations as alternative nulls. We conduct a set of crowdsourced experiments (n=361) to determine the just noticeable difference (JND) between pairs of choropleth maps of geographic units controlling for spatial autocorrelation (Moran's I statistic) and geometric configuration (variance in spatial unit area). Results indicate that people's abilities to perceive differences in spatial autocorrelation vary with baseline autocorrelation structure and the geometric configuration of geographic units. These results allow us, for the first time, to construct a visual equivalent of statistical power for geospatial data. Our JND results add to those provided in recent years by Klippel et al. (2011), Harrison et al. (2014) and Kay & Heer (2015) for correlation visualization. Importantly, they provide an empirical basis for an improved construction of visual line-ups for maps and the development of theory to inform geospatial tests of graphical inference.
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Multi-scale integration and predictability in resting state brain activity
Kolchinsky, Artemy; van den Heuvel, Martijn P.; Griffa, Alessandra; Hagmann, Patric; Rocha, Luis M.; Sporns, Olaf; Goñi, Joaquín
2014-01-01
The human brain displays heterogeneous organization in both structure and function. Here we develop a method to characterize brain regions and networks in terms of information-theoretic measures. We look at how these measures scale when larger spatial regions as well as larger connectome sub-networks are considered. This framework is applied to human brain fMRI recordings of resting-state activity and DSI-inferred structural connectivity. We find that strong functional coupling across large spatial distances distinguishes functional hubs from unimodal low-level areas, and that this long-range functional coupling correlates with structural long-range efficiency on the connectome. We also find a set of connectome regions that are both internally integrated and coupled to the rest of the brain, and which resemble previously reported resting-state networks. Finally, we argue that information-theoretic measures are useful for characterizing the functional organization of the brain at multiple scales. PMID:25104933
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Hyperspectral optical imaging of two different species of lepidoptera
2011-01-01
In this article, we report a hyperspectral optical imaging application for measurement of the reflectance spectra of photonic structures that produce structural colors with high spatial resolution. The measurement of the spectral reflectance function is exemplified in the butterfly wings of two different species of Lepidoptera: the blue iridescence reflected by the nymphalid Morpho didius and the green iridescence of the papilionid Papilio palinurus. Color coordinates from reflectance spectra were calculated taking into account human spectral sensitivity. For each butterfly wing, the observed color is described by a characteristic color map in the chromaticity diagram and spreads over a limited volume in the color space. The results suggest that variability in the reflectance spectra is correlated with different random arrangements in the spatial distribution of the scales that cover the wing membranes. Hyperspectral optical imaging opens new ways for the non-invasive study and classification of different forms of irregularity in structural colors. PMID:21711872
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Lagrangian coherent structures separate dynamically distinct regions in fluid flows.
Kelley, Douglas H; Allshouse, Michael R; Ouellette, Nicholas T
2013-07-01
Using filter-space techniques, we study the scale-to-scale transport of energy in a quasi-two-dimensional, weakly turbulent fluid flow averaged along the trajectories of fluid elements. We find that although the spatial mean of this Lagrangian-averaged flux is nearly unchanged from its Eulerian counterpart, the spatial structure of the scale-to-scale energy flux changes significantly. In particular, its features appear to correlate with the positions of Lagrangian coherent structures (LCS's). We show that the LCS's tend to lie at zeros of the scale-to-scale flux, and therefore that the LCS's separate regions that have qualitatively different dynamics. Since LCS's are also known to be impenetrable barriers to advection and mixing, we therefore find that the fluid on either side of an LCS is both kinematically and dynamically distinct. Our results extend the utility of LCS's by making clear the role they play in the flow dynamics in addition to the kinematics.
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Functional overestimation due to spatial smoothing of fMRI data.
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.
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Zhang, Chuan; Chen, Hong-Song; Zhang, Wei; Nie, Yun-Peng; Ye, Ying-Ying; Wang, Ke-Lin
2014-06-01
Surface soil water-physical properties play a decisive role in the dynamics of deep soil water. Knowledge of their spatial variation is helpful in understanding the processes of rainfall infiltration and runoff generation, which will contribute to the reasonable utilization of soil water resources in mountainous areas. Based on a grid sampling scheme (10 m x 10 m) and geostatistical methods, this paper aimed to study the spatial variability of surface (0-10 cm) soil water content, soil bulk density and saturated hydraulic conductivity on a typical shrub slope (90 m x 120 m, projected length) in Karst area of northwest Guangxi, southwest China. The results showed that the surface soil water content, bulk density and saturated hydraulic conductivity had different spatial dependence and spatial structure. Sample variogram of the soil water content was fitted well by Gaussian models with the nugget effect, while soil bulk density and saturated hydraulic conductivity were fitted well by exponential models with the nugget effect. Variability of soil water content showed strong spatial dependence, while the soil bulk density and saturated hydraulic conductivity showed moderate spatial dependence. The spatial ranges of the soil water content and saturated hydraulic conductivity were small, while that of the soil bulk density was much bigger. In general, the soil water content increased with the increase of altitude while it was opposite for the soil bulk densi- ty. However, the soil saturated hydraulic conductivity had a random distribution of large amounts of small patches, showing high spatial heterogeneity. Soil water content negatively (P < 0.01) correlated with the bulk density and saturated hydraulic conductivity, while there was no significant correlation between the soil bulk density and saturated hydraulic conductivity.
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Nonlinear electric field structures in the inner magnetosphere
Malaspina, D. M.; Andersson, L.; Ergun, R. E.; ...
2014-08-28
Recent observations by the Van Allen Probes spacecraft have demonstrated that a variety of electric field structures and nonlinear waves frequently occur in the inner terrestrial magnetosphere, including phase space holes, kinetic field-line resonances, nonlinear whistler-mode waves, and several types of double layer. However, it is nuclear whether such structures and waves have a significant impact on the dynamics of the inner magnetosphere, including the radiation belts and ring current. To make progress toward quantifying their importance, this study statistically evaluates the correlation of such structures and waves with plasma boundaries. A strong correlation is found. These statistical results, combinedmore » with observations of electric field activity at propagating plasma boundaries, are consistent with the identification of these boundaries as the source of free energy responsible for generating the electric field structures and nonlinear waves of interest. Therefore, the ability of these structures and waves to influence plasma in the inner magnetosphere is governed by the spatial extent and dynamics of macroscopic plasma boundaries in that region.« less
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Crespo-García, Maité; Zeiller, Monika; Leupold, Claudia; Kreiselmeyer, Gernot; Rampp, Stefan; Hamer, Hajo M; Dalal, Sarang S
2016-11-15
Human hippocampal theta oscillations play a key role in accurate spatial coding. Associative encoding involves similar hippocampal networks but, paradoxically, is also characterized by theta power decreases. Here, we investigated how theta activity relates to associative encoding of place contexts resulting in accurate navigation. Using MEG, we found that slow-theta (2-5Hz) power negatively correlated with subsequent spatial accuracy for virtual contextual locations in posterior hippocampus and other cortical structures involved in spatial cognition. A rare opportunity to simultaneously record MEG and intracranial EEG in an epilepsy patient provided crucial insights: during power decreases, slow-theta in right anterior hippocampus and left inferior frontal gyrus phase-led the left temporal cortex and predicted spatial accuracy. Our findings indicate that decreased slow-theta activity reflects local and long-range neural mechanisms that encode accurate spatial contexts, and strengthens the view that local suppression of low-frequency activity is essential for more efficient processing of detailed information. Copyright © 2016 Elsevier Inc. All rights reserved.
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2015-08-02
Optics Gabriel Molina-Terriza, Macquarie University, Australia 17:35-18:00 Tunable Coherent Multicolored Vector Vortex Beam Generator using a q...17:35 Designing Meta-Atoms for Transformation Optics, Gabriel Molina-Terriza, Macquarie University The objective in the field of transformation...copy of the light field interacts with the object and a non spatially resolving detector and the other copy is recorded with a camera . Correlations
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NASA Astrophysics Data System (ADS)
Messaoudi, Akila; Laouami, Nasser; Mezouar, Nourredine
2017-07-01
During the May 21, 2003 M w 6.8 Boumerdes earthquake, in the "Cité des 102 Logements" built on a hilltop, in Corso, heavy damages were observed: near the crest, a four-story RC building collapsed while others experienced severe structural damage and far from the crest, slight damage was observed. In the present paper, we perform a 2D slope topography seismic analysis and investigate its effects on the response at the plateau as well as the correlation with the observed damage distribution. A site-specific seismic scenario is used involving seismological, geological, and geotechnical data. 2D finite element numerical seismic study of the idealized Corso site subjected to vertical SV wave propagation is carried out by the universal code FLUSH. The results highlighted the main factors that explain the causes of block collapse, located 8-26 m far from the crest. These are as follows: (i) a significant spatial variation of ground response along the plateau due to the topographic effect, (ii) this spatial variation presents high loss of coherence, (iii) the seismic ground responses (PGA and response spectra) reach their maxima, and (iv) the fundamental frequency of the collapsed blocks coincides with the frequency content of the topographic component. For distances far from the crest where slight damages were observed, the topographic contribution is found negligible. On the basis of these results, it is important to take into account the topographic effect and the induced spatial variability in the seismic design of structures sited near the crest of slope.
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Nonparametric Bayesian models for a spatial covariance.
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.
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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.
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McLeish, Tom C.B.; Cann, Martin J.; Rodgers, Thomas L.
2015-01-01
We examine the contrast between mechanisms for allosteric signaling that involve structural change, and those that do not, from the perspective of allosteric pathways. In particular we treat in detail the case of fluctuation-allostery by which amplitude modulation of the thermal fluctuations of the elastic normal modes conveys the allosteric signal, and address the question of what an allosteric pathway means in this case. We find that a perturbation theory of thermal elastic solids and nonperturbative approach (by super-coarse-graining elasticity into internal bending modes) have opposite signatures in their structure of correlated pathways. We illustrate the effect from analysis of previous results from GlxR of Corynebacterium glutamicum, an example of the CRP/FNR transcription family of allosteric homodimers. We find that the visibility of both correlated pathways and disconnected sites of correlated motion in this protein suggests that mechanisms of local elastic stretch and bend are recruited for the purpose of creating and controlling allosteric cooperativity. PMID:26338443
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Bent dark soliton dynamics in two spatial dimensions beyond the mean field approximation
NASA Astrophysics Data System (ADS)
Mistakidis, Simeon; Katsimiga, Garyfallia; Koutentakis, Georgios; Kevrekidis, Panagiotis; Schmelcher, Peter; Theory Group of Fundamental Processes in Quantum Physics Team
2017-04-01
The dynamics of a bented dark soliton embedded in two spatial dimensions beyond the mean-field approximation is explored. We examine the case of a single bented dark soliton comparing the mean-field approximation to a correlated approach that involves multiple orbitals. Fragmentation is generally present and significantly affects the dynamics, especially in the case of stronger interparticle interactions and in that of lower atom numbers. It is shown that the presence of fragmentation allows for the appearance of solitonic and vortex structures in the higher-orbital dynamics. In particular, a variety of excitations including dark solitons in multiple orbitals and vortex-antidark complexes is observed to arise spontaneously within the beyond mean-field dynamics. Deutsche Forschungsgemeinschaft (DFG) in the framework of the SFB 925 ``Light induced dynamics and control of correlated quantum systems''.
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NASA Technical Reports Server (NTRS)
Smith, Andrew M.; Davis, Robert Ben; LaVerde, Bruce T.; Jones, Douglas C.; Band, Jonathon L.
2012-01-01
Using the patch method to represent the continuous spatial correlation function of a phased pressure field over a structural surface is an approximation. The approximation approaches the continuous function as patches become smaller. Plotting comparisons of the approximation vs the continuous function may provide insight revealing: (1) For what patch size/density should the approximation be very good? (2) What the approximation looks like when it begins to break down? (3) What the approximation looks like when the patch size is grossly too large. Following these observations with a convergence study using one FEM may allow us to see the importance of patch density. We may develop insights that help us to predict sufficient patch density to provide adequate convergence for the intended purpose frequency range of interest
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O'Hanlon, Erik; Howley, Sarah; Prasad, Sarah; McGrath, Jane; Leemans, Alexander; McDonald, Colm; Garavan, Hugh; Murphy, Kieran C
2016-12-01
Impaired spatial working memory is a core cognitive deficit observed in people with 22q11 Deletion syndrome (22q11DS) and has been suggested as a candidate endophenotype for schizophrenia. However, to date, the neuroanatomical mechanisms describing its structural and functional underpinnings in 22q11DS remain unclear. We quantitatively investigate the cognitive processes and associated neuroanatomy of spatial working memory in people with 22q11DS compared to matched controls. We examine whether there are significant between-group differences in spatial working memory using task related fMRI, Voxel based morphometry and white matter fiber tractography. Multimodal magnetic resonance imaging employing functional, diffusion and volumetric techniques were used to quantitatively assess the cognitive and neuroanatomical features of spatial working memory processes in 22q11DS. Twenty-six participants with genetically confirmed 22q11DS aged between 9 and 52 years and 26 controls aged between 8 and 46 years, matched for age, gender, and handedness were recruited. People with 22q11DS have significant differences in spatial working memory functioning accompanied by a gray matter volume reduction in the right precuneus. Gray matter volume was significantly correlated with task performance scores in these areas. Tractography revealed extensive differences along fibers between task-related cortical activations with pronounced differences localized to interhemispheric commissural fibers within the parietal section of the corpus callosum. Abnormal spatial working memory in 22q11DS is associated with aberrant functional activity in conjunction with gray and white matter structural abnormalities. These anomalies in discrete brain regions may increase susceptibility to the development of psychiatric disorders such as schizophrenia. Hum Brain Mapp 37:4689-4705, 2016. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.
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NASA Astrophysics Data System (ADS)
Polcher, Jan; Barella-Ortiz, Anaïs; Piles, Maria; Gelati, Emiliano; de Rosnay, Patricia
2017-04-01
The SMOS satellite, operated by ESA, observes the surface in the L-band. On continental surface these observations are sensitive to moisture and in particular surface-soil moisture (SSM). In this presentation we will explore how the observations of this satellite can be exploited over the Iberian Peninsula by comparing its results with two land surface models : ORCHIDEE and HTESSEL. Measured and modelled brightness temperatures show a good agreement in their temporal evolution, but their spatial structures are not consistent. An empirical orthogonal function analysis of the brightness temperature's error identifies a dominant structure over the south-west of the Iberian Peninsula which evolves during the year and is maximum in autumn and winter. Hypotheses concerning forcing-induced biases and assumptions made in the radiative transfer model are analysed to explain this inconsistency, but no candidate is found to be responsible for the weak spatial correlations. The analysis of spatial inconsistencies between modelled and measured TBs is important, as these can affect the estimation of geophysical variables and TB assimilation in operational models, as well as result in misleading validation studies. When comparing the surface-soil moisture of the models with the product derived operationally by ESA from SMOS observations similar results are found. The spatial correlation over the IP between SMOS and ORCHIDEE SSM estimates is poor (ρ 0.3). A single value decomposition (SVD) analysis of rainfall and SSM shows that the co-varying patterns of these variables are in reasonable agreement between both products. Moreover the first three SVD soil moisture patterns explain over 80% of the SSM variance simulated by the model while the explained fraction is only 52% of the remotely sensed values. These results suggest that the rainfall-driven soil moisture variability may not account for the poor spatial correlation between SMOS and ORCHIDEE products. Other reasons have to be sought to explain the poor agreement in spatial patterns between satellite derived and modelled SSM. This presentation will hopefully contribute to the discussion of how SMOS and other observations can be used to prepare, carry-out and exploit a field campaign over the Iberian Peninsula which aims at improving our understanding of semi-arid land surface processes.
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Analysis of evoked deep brain connectivity.
Klimeš, Petr; Janeček, Jiři; Jurák, Pavel; Halámek, Josef; Chládek, Han; Brázdil, Milan
2013-01-01
Establishing dependencies and connectivity among different structures in the human brain is an extremely complex issue. Methods that are often used for connectivity analysis are based on correlation mechanisms. Correlation methods can analyze changes in signal shape or instantaneous power level. Although recent studies imply that observation of results from both groups of methods together can disclose some of the basic functions and behavior of the human brain during mental activity and decision-making, there is no technique covering changes in the shape of signals along with changes in their power levels. We present a method using a time evaluation of the correlation along with a comparison of power levels in every available contact pair from intracranial electrodes placed in deep brain structures. Observing shape changes in signals after stimulation together with their power levels provides us with new information about signal character between different structures in the brain during task-related events - visual stimulation with motor response. The results for a subject with 95 intracerebral contacts used in this paper demonstrate a clear methodology capable of spatially analyzing connectivity among deep brain structures.
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Extinction threshold for spatial forest dynamics with height structure.
Garcia-Domingo, Josep L; Saldaña, Joan
2011-05-07
We present a pair-approximation model for spatial forest dynamics defined on a regular lattice. The model assumes three possible states for a lattice site: empty (gap site), occupied by an immature tree, and occupied by a mature tree, and considers three nonlinearities in the dynamics associated to the processes of light interference, gap expansion, and recruitment. We obtain an expression of the basic reproduction number R(0) which, in contrast to the one obtained under the mean-field approach, uses information about the spatial arrangement of individuals close to extinction. Moreover, we analyze the corresponding survival-extinction transition of the forest and the spatial correlations among gaps, immature and mature trees close to this critical point. Predictions of the pair-approximation model are compared with those of a cellular automaton. Copyright © 2011 Elsevier Ltd. All rights reserved.
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The Michelin red guide of the brain: role of dopamine in goal-oriented navigation.
Retailleau, Aude; Boraud, Thomas
2014-01-01
Spatial learning has been recognized over the years to be under the control of the hippocampus and related temporal lobe structures. Hippocampal damage often causes severe impairments in the ability to learn and remember a location in space defined by distal visual cues. Such cognitive disabilities are found in Parkinsonian patients. We recently investigated the role of dopamine in navigation in the 6-Hydroxy-dopamine (6-OHDA) rat, a model of Parkinson's disease (PD) commonly used to investigate the pathophysiology of dopamine depletion (Retailleau et al., 2013). We demonstrated that dopamine (DA) is essential to spatial learning as its depletion results in spatial impairments. Our results showed that the behavioral effect of DA depletion is correlated with modification of the neural encoding of spatial features and decision making processes in hippocampus. However, the origin of these alterations in the neural processing of the spatial information needs to be clarified. It could result from a local effect: dopamine depletion disturbs directly the processing of relevant spatial information at hippocampal level. Alternatively, it could result from a more distributed network effect: dopamine depletion elsewhere in the brain (entorhinal cortex, striatum, etc.) modifies the way hippocampus processes spatial information. Recent experimental evidence in rodents, demonstrated indeed, that other brain areas are involved in the acquisition of spatial information. Amongst these, the cortex-basal ganglia (BG) loop is known to be involved in reinforcement learning and has been identified as an important contributor to spatial learning. In particular, it has been shown that altered activity of the BG striatal complex can impair the ability to perform spatial learning tasks. The present review provides a glimpse of the findings obtained over the past decade that support a dialog between these two structures during spatial learning under DA control.
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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.
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Geographic variation in patterns of nestedness among local stream fish assemblages in Virginia
Cook, R.R.; Angermeier, P.L.; Finn, D.S.; Poff, N.L.; Krueger, K.L.
2004-01-01
Nestedness of faunal assemblages is a multiscale phenomenon, potentially influenced by a variety of factors. Prior small-scale studies have found freshwater fish species assemblages to be nested along stream courses as a result of either selective colonization or extinction. However, within-stream gradients in temperature and other factors are correlated with the distributions of many fish species and may also contribute to nestedness. At a regional level, strongly nested patterns would require a consistent set of structuring mechanisms across streams, and correlation among species' tolerances of the environmental factors that influence distribution. Thus, nestedness should be negatively associated with the spatial extent of the region analyzed and positively associated with elevational gradients (a correlate of temperature and other environmental factors). We examined these relationships for the freshwater fishes of Virginia. Regions were defined within a spatial hierarchy and included whole river drainages, portions of drainages within physiographic provinces, and smaller subdrainages. In most cases, nestedness was significantly stronger in regions of smaller spatial extent and in regions characterized by greater topographic relief. Analysis of hydrologic variability and patterns of faunal turnover provided no evidence that interannual colonization/extinction dynamics contributed to elevational differences in nestedness. These results suggest that, at regional scales, nestedness is influenced by interactions between biotic and abiotic factors, and that the strongest nestedness is likely to occur where a small number of organizational processes predominate, i.e., over small spatial extents and regions exhibiting strong environmental gradients. ?? Springer-Verlag 2004.
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Nugent, Allison C; Luber, Bruce; Carver, Frederick W; Robinson, Stephen E; Coppola, Richard; Zarate, Carlos A
2017-02-01
Recently, independent components analysis (ICA) of resting state magnetoencephalography (MEG) recordings has revealed resting state networks (RSNs) that exhibit fluctuations of band-limited power envelopes. Most of the work in this area has concentrated on networks derived from the power envelope of beta bandpass-filtered data. Although research has demonstrated that most networks show maximal correlation in the beta band, little is known about how spatial patterns of correlations may differ across frequencies. This study analyzed MEG data from 18 healthy subjects to determine if the spatial patterns of RSNs differed between delta, theta, alpha, beta, gamma, and high gamma frequency bands. To validate our method, we focused on the sensorimotor network, which is well-characterized and robust in both MEG and functional magnetic resonance imaging (fMRI) resting state data. Synthetic aperture magnetometry (SAM) was used to project signals into anatomical source space separately in each band before a group temporal ICA was performed over all subjects and bands. This method preserved the inherent correlation structure of the data and reflected connectivity derived from single-band ICA, but also allowed identification of spatial spectral modes that are consistent across subjects. The implications of these results on our understanding of sensorimotor function are discussed, as are the potential applications of this technique. Hum Brain Mapp 38:779-791, 2017. © 2016 Wiley Periodicals, Inc. Published 2016. This article is a U.S. Government work and is in the public domain in the USA.
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Martínez, Kenia; Janssen, Joost; Pineda-Pardo, José Ángel; Carmona, Susanna; Román, Francisco Javier; Alemán-Gómez, Yasser; Garcia-Garcia, David; Escorial, Sergio; Quiroga, María Ángeles; Santarnecchi, Emiliano; Navas-Sánchez, Francisco Javier; Desco, Manuel; Arango, Celso; Colom, Roberto
2017-07-15
Global structural brain connectivity has been reported to be sex-dependent with women having increased interhemispheric connectivity (InterHc) and men having greater intrahemispheric connectivity (IntraHc). However, (a) smaller brains show greater InterHc, (b) larger brains show greater IntraHc, and (c) women have, on average, smaller brains than men. Therefore, sex differences in brain size may modulate sex differences in global brain connectivity. At the behavioural level, sex-dependent differences in connectivity are thought to contribute to men-women differences in spatial and verbal abilities. But this has never been tested at the individual level. The current study assessed whether individual differences in global structural connectome measures (InterHc, IntraHc and the ratio of InterHc relative to IntraHc) predict spatial and verbal ability while accounting for the effect of sex and brain size. The sample included forty men and forty women, who did neither differ in age nor in verbal and spatial latent components defined by a broad battery of tests and tasks. High-resolution T 1 -weighted and diffusion-weighted images were obtained for computing brain size and reconstructing the structural connectome. Results showed that men had higher IntraHc than women, while women had an increased ratio InterHc/IntraHc. However, these sex differences were modulated by brain size. Increased InterHc relative to IntraHc predicted higher spatial and verbal ability irrespective of sex and brain size. The positive correlations between the ratio InterHc/IntraHc and the spatial and verbal abilities were confirmed in 1000 random samples generated by bootstrapping. Therefore, sex differences in global structural connectome connectivity were modulated by brain size and did not underlie sex differences in verbal and spatial abilities. Rather, the level of dominance of InterHc over IntraHc may be associated with individual differences in verbal and spatial abilities in both men and women. Copyright © 2017 Elsevier Inc. All rights reserved.
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[Features of brain biopotentials' spatial organization in adolescents].
Kruchinina, O V; Gal'perina, E I; Shepoval'nikov, A N
2014-01-01
Adolescence is characterized by an intensive formation of inter-regional cortical fields interaction, in this period significantly reorganized the activities of deep brain structures and cortical-subcortical interaction are enhanced. Our objectives were to evaluate the nature of changes in the spatial organization of brain bioelectric potentials with age and characteristics of such an organization in adolescents. For this purpose, EEG studies have been conducted in 230 subjects of both sexes aged 4 to 35 years. We estimated interdependent changes of biopotentials correlations fluctuations in 20-lead EEG, using the integral index Vol. Analyzed age-related changes of EEG correlations in rest condition and during verbal activity (Russian and English texts audition). Verbal tasks were sued in subjects over 8 years. It was found that the spatial synchronization of the EEG both in background and verbal activity increases with age, but after 20 years the rate of change is significantly reduced. In adolescence (12-17 years old), sex differences appear between the degree of EEG coherence processes occurring in the left and right hemispheres in subjects performing verbal tasks. In males 12 to 14 years nonlinear changes in overall correlation (indicators VOL) was observed, whereas in females of this age systemic reorganization of the brain interrelations occurs more smoothly, ahead of 1.5-2 years.
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NASA Astrophysics Data System (ADS)
Wang, Rui-Wu; Dunn, Derek W.; Luo, Jun; He, Jun-Zhou; Shi, Lei
2015-10-01
Understanding the factors that enable mutualisms to evolve and to subsequently remain stable over time, is essential to fully understand patterns of global biodiversity and for evidence based conservation policy. Theoretically, spatial heterogeneity of mutualists, through increased likelihood of fidelity between cooperative partners in structured populations, and ‘self-restraint’ of symbionts, due to selection against high levels of virulence leading to short-term host overexploitation, will result in either a positive correlation between the reproductive success of both mutualists prior to the total exploitation of any host resource or no correlation after any host resource has been fully exploited. A quantitative review by meta-analysis on the results of 96 studies from 35 papers, showed no evidence of a significant fitness correlation between mutualists across a range of systems that captured much taxonomic diversity. However, when the data were split according to four categories of host: 1) cnidarian corals, 2) woody plants, 3) herbaceous plants, and 4) insects, a significantly positive effect in corals was revealed. The trends for the remaining three categories did not significantly differ to zero. Our results suggest that stability in mutualisms requires alternative processes, or mechanisms in addition to, spatial heterogeneity of hosts and/or ‘self-restraint’ of symbionts.
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A spatial epidemiological analysis of self-rated mental health in the slums of Dhaka
2011-01-01
Background The deprived physical environments present in slums are well-known to have adverse health effects on their residents. However, little is known about the health effects of the social environments in slums. Moreover, neighbourhood quantitative spatial analyses of the mental health status of slum residents are still rare. The aim of this paper is to study self-rated mental health data in several slums of Dhaka, Bangladesh, by accounting for neighbourhood social and physical associations using spatial statistics. We hypothesised that mental health would show a significant spatial pattern in different population groups, and that the spatial patterns would relate to spatially-correlated health-determining factors (HDF). Methods We applied a spatial epidemiological approach, including non-spatial ANOVA/ANCOVA, as well as global and local univariate and bivariate Moran's I statistics. The WHO-5 Well-being Index was used as a measure of self-rated mental health. Results We found that poor mental health (WHO-5 scores < 13) among the adult population (age ≥15) was prevalent in all slum settlements. We detected spatially autocorrelated WHO-5 scores (i.e., spatial clusters of poor and good mental health among different population groups). Further, we detected spatial associations between mental health and housing quality, sanitation, income generation, environmental health knowledge, education, age, gender, flood non-affectedness, and selected properties of the natural environment. Conclusions Spatial patterns of mental health were detected and could be partly explained by spatially correlated HDF. We thereby showed that the socio-physical neighbourhood was significantly associated with health status, i.e., mental health at one location was spatially dependent on the mental health and HDF prevalent at neighbouring locations. Furthermore, the spatial patterns point to severe health disparities both within and between the slums. In addition to examining health outcomes, the methodology used here is also applicable to residuals of regression models, such as helping to avoid violating the assumption of data independence that underlies many statistical approaches. We assume that similar spatial structures can be found in other studies focussing on neighbourhood effects on health, and therefore argue for a more widespread incorporation of spatial statistics in epidemiological studies. PMID:21599932
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Physical modeling of the formation and evolution of seismically active fault zones
Ponomarev, A.V.; Zavyalov, A.D.; Smirnov, V.B.; Lockner, D.A.
1997-01-01
Acoustic emission (AE) in rocks is studied as a model of natural seismicity. A special technique for rock loading has been used to help study the processes that control the development of AE during brittle deformation. This technique allows us to extend to hours fault growth which would normally occur very rapidly. In this way, the period of most intense interaction of acoustic events can be studied in detail. Characteristics of the acoustic regime (AR) include the Gutenberg-Richter b-value, spatial distribution of hypocenters with characteristic fractal (correlation) dimension d, Hurst exponent H, and crack concentration parameter Pc. The fractal structure of AR changes with the onset of the drop in differential stress during sample deformation. The change results from the active interaction of microcracks. This transition of the spatial distribution of AE hypocenters is accompanied by a corresponding change in the temporal correlation of events and in the distribution of event amplitudes as signified by a decrease of b-value. The characteristic structure that develops in the low-energy background AE is similar to the sequence of the strongest microfracture events. When the AR fractal structure develops, the variations of d and b are synchronous and d = 3b. This relation which occurs once the fractal structure is formed only holds for average values of d and b. Time variations of d and b are anticorrelated. The degree of temporal correlation of AR has time variations that are similar to d and b variations. The observed variations in laboratory AE experiments are compared with natural seismicity parameters. The close correspondence between laboratory-scale observations and naturally occurring seismicity suggests a possible new approach for understanding the evolution of complex seismicity patterns in nature. ?? 1997 Elsevier Science B.V. All rights reserved.
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NASA Astrophysics Data System (ADS)
Fischer, R.; Richardi, J.; Fries, P. H.; Krienke, H.
2002-11-01
Structural properties and energies of solvation are simulated for alkali and halide ions. The solvation structure is discussed in terms of various site-site distribution functions, of solvation numbers, and of orientational correlation functions of the solvent molecules around the ions. The solvent polarizability has notable effects which cannot be intuitively predicted. In particular, it is necessary to reproduce the experimental solvation numbers of small ions. The changes of solvation properties are investigated along the alkali and halide series. By comparing the solvation of ions in acetone to that in acetonitrile, it is shown that the spatial correlations among the solvent molecules around an ion result in a strong screening of the ion-solvent direct intermolecular potential and are essential to understand the changes in the solvation structures and energies between different solvents. The solvation properties derived from the simulations are compared to earlier predictions of the hypernetted chain (HNC) approximation of the molecular Ornstein-Zernike (MOZ) theory [J. Richardi, P. H. Fries, and H. Krienke, J. Chem. Phys. 108, 4079 (1998)]. The MOZ(HNC) formalism gives an overall qualitatively correct picture of the solvation and its various unexpected findings are corroborated. For the larger ions, its predictions become quantitative. The MOZ approach allows to calculate solvent-solvent and ion-solvent potentials of mean force, which shed light on the 3D labile molecular and ionic architectures in the solution. These potentials of mean force convey a unique information which is necessary to fully interpret the angle-averaged structural functions computed from the simulations. Finally, simulations of solutions at finite concentrations show that the solvent-solvent and ion-solvent spatial correlations at infinite dilution are marginally altered by the introduction of fair amounts of ions.
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Electric currents and coronal heating in NOAA active region 6952
NASA Technical Reports Server (NTRS)
Metcalf, T. R.; Canfield, R. C.; Hudson, H. S.; Mickey, D. L.; Wulser, J. -P.; Martens, P. C. H.; Tsuneta, S.
1994-01-01
We examine the spatial and temporal relationship between coronal structures observed with the soft X-ray telescope (SXT) on board the Yohkoh spacecraft and the vertical electric current density derived from photospheric vector magnetograms obtained using the Stokes Polarimeter at the Mees Solar Observatory. We focus on a single active region: AR 6952 which we observed on 7 days during 1991 December. For 11 independent maps of the vertical electric current density co-aligned with non-flaring X-ray images, we search for a morphological relationship between sites of high vertical current density in the photosphere and enhanced X-ray emission in the overlying corona. We find no compelling spatial or temporal correlation between the sites of vertical current and the bright X-ray structures in this active region.
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NASA Astrophysics Data System (ADS)
Newell, Reginald E.; Wu, Zhong-Xiang
1992-03-01
Fields of sea surface temperature anomalies from the Global Ocean Surface Temperature Atlas (GOSTA) and microwave sounding measurements (MSU) of temperature in the troposphere are examined separately and together for the 1979-1988 period. Global correlation patterns of both sets of fields are investigated at a range of leads and lags up to 6 months and exhibit a wide range of correlation structure. There are regions, such as the tropical eastern Pacific, where sea surface temperature anomalies persist for several months and are associated with local air temperature anomalies; in this particular example, about 0.7°C air temperature change is associated with a 1.0°C sea temperature change. By contrast, some ocean regions and many atmospheric regions, mostly in middle and high latitude, show only local spatial correlations that disappear completely in a month or two. The most persistent and extensive spatial correlation patterns are quite different for the sea and the air. In the sea the "butterfly" pattern of the Pacific is the most important and reverses sign between the eastern equatorial Pacific and the western Pacific and subtropics. In the warm phase the temperature anomalies associated with this pattern are similar to the correlation pattern. For the atmosphere the main correlation pattern is an equatorial belt with no sign changes in the tropics; this pattern is linked to the oceanic El Niño mode. In the warm phase the temperature anomalies show peak values on both sides of the equator in the eastern and central Pacific. Based mainly on the results from the spatial patterns, certain regions are selected for intercomparison of time series. In the tropical eastern Pacific the sea leads the air by about a month while in the Gulf Stream and Kuroshio regions the sequence is reversed.
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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.
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Perturbing laser field dependent high harmonic phase modulations
NASA Astrophysics Data System (ADS)
Li, Zhengyan; Kong, Fanqi; Brown, Graham; Hammond, TJ; Ko, Dong-Hyuk; Zhang, Chunmei; Corkum, P. B.
2018-06-01
A perturbing laser pulse modulates and controls the phase of the high harmonic radiation driven by an intense fundamental pulse. Thus, a structured wave front can impress a specific spatial phase onto the generated high harmonic wave front. This modulation procedure leads to all-optical spatial light modulators for VUV or XUV radiation created by high harmonic generation. Here, through theoretical analysis and experiment, we study the correlation between the high harmonic phase modulations and the perturbing laser field amplitude and phase, providing guidelines for practical high harmonic spatial light modulators. In addition, we show that the petahertz optical oscilloscope for measuring electric fields of a perturbing beam is most robust using low order harmonics, far from the cut-off.
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Direct Femtosecond Laser Surface Structuring with Optical Vortex Beams Generated by a q-plate
JJ Nivas, Jijil; He, Shutong; Rubano, Andrea; Vecchione, Antonio; Paparo, Domenico; Marrucci, Lorenzo; Bruzzese, Riccardo; Amoruso, Salvatore
2015-01-01
Creation of patterns and structures on surfaces at the micro- and nano-scale is a field of growing interest. Direct femtosecond laser surface structuring with a Gaussian-like beam intensity profile has already distinguished itself as a versatile method to fabricate surface structures on metals and semiconductors. Here we present an approach for direct femtosecond laser surface structuring based on optical vortex beams with different spatial distributions of the state of polarization, which are easily generated by means of a q-plate. The different states of an optical vortex beam carrying an orbital angular momentum ℓ = ±1 are used to demonstrate the fabrication of various regular surface patterns on silicon. The spatial features of the regular rippled and grooved surface structures are correlated with the state of polarization of the optical vortex beam. Moreover, scattered surface wave theory approach is used to rationalize the dependence of the surface structures on the local state of the laser beam characteristics (polarization and fluence). The present approach can be further extended to fabricate even more complex and unconventional surface structures by exploiting the possibilities offered by femtosecond optical vector fields. PMID:26658307
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Multi-temporal LiDAR and Landsat quantification of fire-induced changes to forest structure
McCarley, T. Ryan; Kolden, Crystal A.; Vaillant, Nicole M.; Hudak, Andrew T.; Smith, Alistair M.S.; Wing, Brian M.; Kellogg, Bryce; Kreitler, Jason R.
2017-01-01
Measuring post-fire effects at landscape scales is critical to an ecological understanding of wildfire effects. Predominantly this is accomplished with either multi-spectral remote sensing data or through ground-based field sampling plots. While these methods are important, field data is usually limited to opportunistic post-fire observations, and spectral data often lacks validation with specific variables of change. Additional uncertainty remains regarding how best to account for environmental variables influencing fire effects (e.g., weather) for which observational data cannot easily be acquired, and whether pre-fire agents of change such as bark beetle and timber harvest impact model accuracy. This study quantifies wildfire effects by correlating changes in forest structure derived from multi-temporal Light Detection and Ranging (LiDAR) acquisitions to multi-temporal spectral changes captured by the Landsat Thematic Mapper and Operational Land Imager for the 2012 Pole Creek Fire in central Oregon. Spatial regression modeling was assessed as a methodology to account for spatial autocorrelation, and model consistency was quantified across areas impacted by pre-fire mountain pine beetle and timber harvest. The strongest relationship (pseudo-r2 = 0.86, p < 0.0001) was observed between the ratio of shortwave infrared and near infrared reflectance (d74) and LiDAR-derived estimate of canopy cover change. Relationships between percentage of LiDAR returns in forest strata and spectral indices generally increased in strength with strata height. Structural measurements made closer to the ground were not well correlated. The spatial regression approach improved all relationships, demonstrating its utility, but model performance declined across pre-fire agents of change, suggesting that such studies should stratify by pre-fire forest condition. This study establishes that spectral indices such as d74 and dNBR are most sensitive to wildfire-caused structural changes such as reduction in canopy cover and perform best when that structure has not been reduced pre-fire.
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On the role of general system theory for functional neuroimaging.
Stephan, Klaas Enno
2004-12-01
One of the most important goals of neuroscience is to establish precise structure-function relationships in the brain. Since the 19th century, a major scientific endeavour has been to associate structurally distinct cortical regions with specific cognitive functions. This was traditionally accomplished by correlating microstructurally defined areas with lesion sites found in patients with specific neuropsychological symptoms. Modern neuroimaging techniques with high spatial resolution have promised an alternative approach, enabling non-invasive measurements of regionally specific changes of brain activity that are correlated with certain components of a cognitive process. Reviewing classic approaches towards brain structure-function relationships that are based on correlational approaches, this article argues that these approaches are not sufficient to provide an understanding of the operational principles of a dynamic system such as the brain but must be complemented by models based on general system theory. These models reflect the connectional structure of the system under investigation and emphasize context-dependent couplings between the system elements in terms of effective connectivity. The usefulness of system models whose parameters are fitted to measured functional imaging data for testing hypotheses about structure-function relationships in the brain and their potential for clinical applications is demonstrated by several empirical examples.
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Correlations among stand ages and forest strata in mixed-oak forests of southeastern Ohio
P. Charles Goebel; David M. Hix
1997-01-01
Many models of landscape ecosystem development, as well as of forest stand dynamics, are based upon spatial and temporal changes in the species composition and structure of various forest strata. However, few document the interrelationships among forest strata, or the response of different strata to alterations of natural disturbance regimes. To examine how...
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Basic data features and results from a spatially dense seismic array on the San Jacinto fault zone
NASA Astrophysics Data System (ADS)
Ben-Zion, Yehuda; Vernon, Frank L.; Ozakin, Yaman; Zigone, Dimitri; Ross, Zachary E.; Meng, Haoran; White, Malcolm; Reyes, Juan; Hollis, Dan; Barklage, Mitchell
2015-07-01
We discuss several outstanding aspects of seismograms recorded during >4 weeks by a spatially dense Nodal array, straddling the damage zone of the San Jacinto fault in southern California, and some example results. The waveforms contain numerous spikes and bursts of high-frequency waves (up to the recorded 200 Hz) produced in part by minute failure events in the shallow crust. The high spatial density of the array facilitates the detection of 120 small local earthquakes in a single day, most of which not detected by the surrounding ANZA and regional southern California networks. Beamforming results identify likely ongoing cultural noise sources dominant in the frequency range 1-10 Hz and likely ongoing earthquake sources dominant in the frequency range 20-40 Hz. Matched-field processing and back-projection of seismograms provide alternate event location. The median noise levels during the experiment at different stations, waves generated by Betsy gunshots, and wavefields from nearby earthquakes point consistently to several structural units across the fault. Seismic trapping structure and local sedimentary basin produce localized motion amplification and stronger attenuation than adjacent regions. Cross correlations of high-frequency noise recorded at closely spaced stations provide a structural image of the subsurface material across the fault zone. The high spatial density and broad frequency range of the data can be used for additional high resolution studies of structure and source properties in the shallow crust.
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NASA Astrophysics Data System (ADS)
Kapoor, Mudit
The first part of my dissertation considers the estimation of a panel data model with error components that are both spatially and time-wise correlated. The dissertation combines widely used model for spatial correlation (Cliff and Ord (1973, 1981)) with the classical error component panel data model. I introduce generalizations of the generalized moments (GM) procedure suggested in Kelejian and Prucha (1999) for estimating the spatial autoregressive parameter in case of a single cross section. I then use those estimators to define feasible generalized least squares (GLS) procedures for the regression parameters. I give formal large sample results concerning the consistency of the proposed GM procedures, as well as the consistency and asymptotic normality of the proposed feasible GLS procedures. The new estimators remain computationally feasible even in large samples. The second part of my dissertation employs a Cliff-Ord-type model to empirically estimate the nature and extent of price competition in the US wholesale gasoline industry. I use data on average weekly wholesale gasoline price for 289 terminals (distribution facilities) in the US. Data on demand factors, cost factors and market structure that affect price are also used. I consider two time periods, a high demand period (August 1999) and a low demand period (January 2000). I find a high level of competition in prices between neighboring terminals. In particular, price in one terminal is significantly and positively correlated to the price of its neighboring terminal. Moreover, I find this to be much higher during the low demand period, as compared to the high demand period. In contrast to previous work, I include for each terminal the characteristics of the marginal customer by controlling for demand factors in the neighboring location. I find these demand factors to be important during period of high demand and insignificant during the low demand period. Furthermore, I have also considered spatial correlation in unobserved factors that affect price. I find it to be high and significant only during the low demand period. Not correcting for it leads to incorrect inferences regarding exogenous explanatory variables.
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The Geographic Concentration of Enterprise in Developing Countries
Felkner, John S.; Townsend, Robert M.
2011-01-01
A nation’s economic geography can have an enormous impact on its development. In Thailand, we show that a high concentration of enterprise in an area predicts high subsequent growth in and around that area. We also find spatially contiguous convergence of enterprise with stagnant areas left behind. Exogenous physiographic conditions are correlated with enterprise location and growth. We fit a structural, micro-founded model of occupation transitions with fine-tuned geographic capabilities to village data and replicate these salient facts. Key elements of the model include costs, credit constraints on occupation choice, and spatially varying expansion of financial service providers. PMID:22844158
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Large trench-parallel gravity variations predict seismogenic behavior in subduction zones.
Song, Teh-Ru Alex; Simons, Mark
2003-08-01
We demonstrate that great earthquakes occur predominantly in regions with a strongly negative trench-parallel gravity anomaly (TPGA), whereas regions with strongly positive TPGA are relatively aseismic. These observations suggest that, over time scales up to at least 1 million years, spatial variations of seismogenic behavior within a given subduction zone are stationary and linked to the geological structure of the fore-arc. The correlations we observe are consistent with a model in which spatial variations in frictional properties on the plate interface control trench-parellel variations in fore-arc topography, gravity, and seismogenic behavior.
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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.
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NASA Astrophysics Data System (ADS)
Stowell, Marilyn Ruth
This research compared the effectiveness and performance of interactive visualizations of the GIS&T Body of Knowledge 1. The visualizations were created using Processing, and display the structure and content of the Body of Knowledge using various spatial layout methods: the Indented List, Tree Graph, treemap and Similarity Graph. The first three methods utilize the existing hierarchical structure of the BoK text, while the fourth method (Similarity Graph) serves as a jumping off point for exploring content-based visualizations of the BoK. The following questions have guided the framework of this research: (1) Which of the spatial layouts is most effective for completing tasks related to the GIS&T; BoK overall? How do they compare to each other in terms of performance? (2) Is one spatial layout significantly more or less effective than others for completing a particular cognitive task? (3) Is the user able to utilize the BoK as a basemap or reference system and make inferences based on BoK scorecard overlays? (4) Which design aspects of the interface assist in carrying out the survey objectives? Which design aspects of the application detract from fulfilling the objectives? To answer these questions, human subjects were recruited to participate in a survey, during which they were assigned a random spatial layout and were asked questions about the BoK based on their interaction with the visualization tool. 75 users were tested, 25 for each spatial layout. Statistical analysis revealed that there were no statistically significant differences between means for overall accuracy when comparing the three visualizations. In looking at individual questions, Tree Graph and Indented List yielded statistically significant higher scores for questions regarding the structure of the Body of Knowledge, as compared to the treemap. There was a significant strong positive correlation between the time taken to complete the survey and the final survey score. This correlation was particularly strong with treemap, possibly confirming the steeper learning curve with the more complex layout. Users were asked for feedback on the perceived "ease" of using the interface, and though few users said the interface was easy to use, there was a positive correlation between perceived "ease" and overall score. Qualitative feedback revealed that the external controls on the interface were not inviting to use, and the interface overall was not intuitive. Additional human subjects were recruited from the professional GIS community to participate in testing remotely. These results weren't significant due to small sample size, but helped to verify the feedback and results from the controlled testing.
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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.
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Morin, Dana J.; Fuller, Angela K.; Royle, J. Andrew; Sutherland, Chris
2017-01-01
Conservation and management of spatially structured populations is challenging because solutions must consider where individuals are located, but also differential individual space use as a result of landscape heterogeneity. A recent extension of spatial capture–recapture (SCR) models, the ecological distance model, uses spatial encounter histories of individuals (e.g., a record of where individuals are detected across space, often sequenced over multiple sampling occasions), to estimate the relationship between space use and characteristics of a landscape, allowing simultaneous estimation of both local densities of individuals across space and connectivity at the scale of individual movement. We developed two model-based estimators derived from the SCR ecological distance model to quantify connectivity over a continuous surface: (1) potential connectivity—a metric of the connectivity of areas based on resistance to individual movement; and (2) density-weighted connectivity (DWC)—potential connectivity weighted by estimated density. Estimates of potential connectivity and DWC can provide spatial representations of areas that are most important for the conservation of threatened species, or management of abundant populations (i.e., areas with high density and landscape connectivity), and thus generate predictions that have great potential to inform conservation and management actions. We used a simulation study with a stationary trap design across a range of landscape resistance scenarios to evaluate how well our model estimates resistance, potential connectivity, and DWC. Correlation between true and estimated potential connectivity was high, and there was positive correlation and high spatial accuracy between estimated DWC and true DWC. We applied our approach to data collected from a population of black bears in New York, and found that forested areas represented low levels of resistance for black bears. We demonstrate that formal inference about measures of landscape connectivity can be achieved from standard methods of studying animal populations which yield individual encounter history data such as camera trapping. Resulting biological parameters including resistance, potential connectivity, and DWC estimate the spatial distribution and connectivity of the population within a statistical framework, and we outline applications to many possible conservation and management problems.
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Accounting for connectivity and spatial correlation in the optimal placement of wildlife habitat
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...
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Hore, Victoria R A; Troy, John B; Eglen, Stephen J
2012-11-01
The receptive fields of on- and off-center parasol cell mosaics independently tile the retina to ensure efficient sampling of visual space. A recent theoretical model represented the on- and off-center mosaics by noisy hexagonal lattices of slightly different density. When the two lattices are overlaid, long-range Moiré interference patterns are generated. These Moiré interference patterns have been suggested to drive the formation of highly structured orientation maps in visual cortex. Here, we show that noisy hexagonal lattices do not capture the spatial statistics of parasol cell mosaics. An alternative model based upon local exclusion zones, termed as the pairwise interaction point process (PIPP) model, generates patterns that are statistically indistinguishable from parasol cell mosaics. A key difference between the PIPP model and the hexagonal lattice model is that the PIPP model does not generate Moiré interference patterns, and hence stimulated orientation maps do not show any hexagonal structure. Finally, we estimate the spatial extent of spatial correlations in parasol cell mosaics to be only 200-350 μm, far less than that required to generate Moiré interference. We conclude that parasol cell mosaics are too disordered to drive the formation of highly structured orientation maps in visual cortex.
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Spatial diversity of bacterioplankton communities in surface water of northern South China Sea.
Li, Jialin; Li, Nan; Li, Fuchao; Zou, Tao; Yu, Shuxian; Wang, Yinchu; Qin, Song; Wang, Guangyi
2014-01-01
The South China Sea is one of the largest marginal seas, with relatively frequent passage of eddies and featuring distinct spatial variation in the western tropical Pacific Ocean. Here, we report a phylogenetic study of bacterial community structures in surface seawater of the northern South China Sea (nSCS). Samples collected from 31 sites across large environmental gradients were used to construct clone libraries and yielded 2,443 sequences grouped into 170 OTUs. Phylogenetic analysis revealed 23 bacterial classes with major components α-, β- and γ-Proteobacteria, as well as Cyanobacteria. At class and genus taxon levels, community structure of coastal waters was distinctively different from that of deep-sea waters and displayed a higher diversity index. Redundancy analyses revealed that bacterial community structures displayed a significant correlation with the water depth of individual sampling sites. Members of α-Proteobacteria were the principal component contributing to the differences of the clone libraries. Furthermore, the bacterial communities exhibited heterogeneity within zones of upwelling and anticyclonic eddies. Our results suggested that surface bacterial communities in nSCS had two-level patterns of spatial distribution structured by ecological types (coastal VS. oceanic zones) and mesoscale physical processes, and also provided evidence for bacterial phylogenetic phyla shaped by ecological preferences.
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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.
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Kalkhan, M.A.; Stafford, E.J.; Woodly, P.J.; Stohlgren, T.J.
2007-01-01
Rocky Mountain National Park (RMNP), Colorado, USA, contains a diversity of plant species. However, many exotic plant species have become established, potentially impacting the structure and function of native plant communities. Our goal was to quantify patterns of exotic plant species in relation to native plant species, soil characteristics, and other abiotic factors that may indicate or predict their establishment and success. Our research approach for field data collection was based on a field plot design called the pixel nested plot. The pixel nested plot provides a link to multi-phase and multi-scale spatial modeling-mapping techniques that can be used to estimate total species richness and patterns of plant diversity at finer landscape scales. Within the eastern region of RMNP, in an area of approximately 35,000 ha, we established a total of 60 pixel nested plots in 9 vegetation types. We used canonical correspondence analysis (CCA) and multiple linear regressions to quantify relationships between soil characteristics and native and exotic plant species richness and cover. We also used linear correlation, spatial autocorrelation and cross correlation statistics to test for the spatial patterns of variables of interest. CCA showed that exotic species were significantly (P < 0.05) associated with photosynthetically active radiation (r = 0.55), soil nitrogen (r = 0.58) and bare ground (r = -0.66). Pearson's correlation statistic showed significant linear relationships between exotic species, organic carbon, soil nitrogen, and bare ground. While spatial autocorrelations indicated that our 60 pixel nested plots were spatially independent, the cross correlation statistics indicated that exotic plant species were spatially associated with bare ground, in general, exotic plant species were most abundant in areas of high native species richness. This indicates that resource managers should focus on the protection of relatively rare native rich sites with little canopy cover, and fertile soils. Using the pixel nested plot approach for data collection can facilitate the ecological monitoring of these vulnerable areas at the landscape scale in a time- and cost-effective manner. ?? 2006 Elsevier B.V. All rights reserved.
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NASA Astrophysics Data System (ADS)
Moslehi, Mahsa; de Barros, Felipe P. J.
2017-01-01
We investigate how the uncertainty stemming from disordered porous media that display long-range correlation in the hydraulic conductivity (K) field propagates to predictions of environmental performance metrics (EPMs). In this study, the EPMs are quantities that are of relevance to risk analysis and remediation, such as peak flux-averaged concentration, early and late arrival times among others. By using stochastic simulations, we quantify the uncertainty associated with the EPMs for a given disordered spatial structure of the K-field and identify the probability distribution function (PDF) model that best captures the statistics of the EPMs of interest. Results indicate that the probabilistic distribution of the EPMs considered in this study follows lognormal PDF. Finally, through the use of information theory, we reveal how the persistent/anti-persistent correlation structure of the K-field influences the EPMs and corresponding uncertainties.
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A low-dimensional approach to closed-loop control of a Mach 0.6 jet
NASA Astrophysics Data System (ADS)
Low, Kerwin R.; Berger, Zachary P.; Kostka, Stanislav; ElHadidi, Basman; Gogineni, Sivaram; Glauser, Mark N.
2013-04-01
Simultaneous time-resolved measurements of the near-field hydrodynamic pressure field, 2-component streamwise velocity field, and far-field acoustics are taken for an un-heated, axisymmetric Mach 0.6 jet in co-flow. Synthetic jet actuators placed around the periphery of the nozzle lip provide localized perturbations to the shear layer. The goal of this study was to develop an understanding of how the acoustic nature of the jet responds to unsteady shear layer excitation, and subsequently how this can be used to reduce the far-field noise. Review of the cross-correlations between the most energetic low-order spatial Fourier modes of the pressure and the far-field region reveals that mode 0 has a strong correlation and mode 1 has a weak correlation with the far-field. These modes are emulated with the synthetic jet array and used as drivers of the developing shear layer. In open loop forcing configurations, there is energy transfer among spatial scales, enhanced mixing, a reconfiguration of the low-dimensional spatial structure, and an increase in the overall sound pressure level (OASPL). In the closed loop configuration, changes to these quantities are more subtle but there is a reduction in the overall fluctuating sound pressure level OASPLf by 1.35 dB. It is argued that this reduction is correlated with the closed loop control feeding back the dynamical low-order information measured in the largest noise producing region.
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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.
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Do MAGSAT anomalies contain a record of past and present-day mantle convection under South America?
NASA Technical Reports Server (NTRS)
Hastings, D. A.
1985-01-01
Global anomaly maps from the National Aeronautics and Space Administration's Magnetic Field Satellite (MAGSAT) have been spatially filtered to reduce the prominence of long-wavelength east-west bands and to improve the discrimination of anomalies within structural provinces. Previous research suggested a correlation between total-field MAGSAT anomaly lows in equatorial regions with crustal bodies of relatively high average magnetic susceptibility (such as Archaean shields), and of anomaly highs with bodies of low susceptibility (such as deep parts of basins). These correlations reverse at higher latitudes.
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Time-resolved Sensing of Meso-scale Shock Compression with Multilayer Photonic Crystal Structures
NASA Astrophysics Data System (ADS)
Scripka, David; Lee, Gyuhyon; Summers, Christopher J.; Thadhani, Naresh
2017-06-01
Multilayer Photonic Crystal structures can provide spatially and temporally resolved data needed to validate theoretical and computational models relevant for understanding shock compression in heterogeneous materials. Two classes of 1-D photonic crystal multilayer structures were studied: optical microcavities (OMC) and distributed Bragg reflectors (DBR). These 0.5 to 5 micron thick structures were composed of SiO2, Al2O3, Ag, and PMMA layers fabricated primarily via e-beam evaporation. The multilayers have unique spectral signatures inherently linked to their time-resolved physical states. By observing shock-induced changes in these signatures, an optically-based pressure sensor was developed. Results to date indicate that both OMCs and DBRs exhibit nanosecond-resolved spectral shifts of several to 10s of nanometers under laser-driven shock compression loads of 0-10 GPa, with the magnitude of the shift strongly correlating to the shock load magnitude. Additionally, spatially and temporally resolved spectral shifts under heterogeneous laser-driven shock compression created by partial beam blocking have been successfully demonstrated. These results illustrate the potential for multilayer structures to serve as meso-scale sensors, capturing temporal and spatial pressure profile evolutions in shock-compressed heterogeneous materials, and revealing meso-scale pressure distributions across a shocked surface. Supported by DTRA Grant HDTRA1-12-1-005 and DoD, AFOSR, National Defense Science and Eng. Graduate Fellowship, 32 CFR 168a.
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Photon Entanglement Through Brain Tissue.
Shi, Lingyan; Galvez, Enrique J; Alfano, Robert R
2016-12-20
Photon entanglement, the cornerstone of quantum correlations, provides a level of coherence that is not present in classical correlations. Harnessing it by study of its passage through organic matter may offer new possibilities for medical diagnosis technique. In this work, we study the preservation of photon entanglement in polarization, created by spontaneous parametric down-conversion, after one entangled photon propagates through multiphoton-scattering brain tissue slices with different thickness. The Tangle-Entropy (TS) plots show the strong preservation of entanglement of photons propagating in brain tissue. By spatially filtering the ballistic scattering of an entangled photon, we find that its polarization entanglement is preserved and non-locally correlated with its twin in the TS plots. The degree of entanglement correlates better with structure and water content than with sample thickness.
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Photon Entanglement Through Brain Tissue
NASA Astrophysics Data System (ADS)
Shi, Lingyan; Galvez, Enrique J.; Alfano, Robert R.
2016-12-01
Photon entanglement, the cornerstone of quantum correlations, provides a level of coherence that is not present in classical correlations. Harnessing it by study of its passage through organic matter may offer new possibilities for medical diagnosis technique. In this work, we study the preservation of photon entanglement in polarization, created by spontaneous parametric down-conversion, after one entangled photon propagates through multiphoton-scattering brain tissue slices with different thickness. The Tangle-Entropy (TS) plots show the strong preservation of entanglement of photons propagating in brain tissue. By spatially filtering the ballistic scattering of an entangled photon, we find that its polarization entanglement is preserved and non-locally correlated with its twin in the TS plots. The degree of entanglement correlates better with structure and water content than with sample thickness.
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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.
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Multiple paternity and sporophytic inbreeding depression in a dioicous moss species.
Szövényi, P; Ricca, M; Shaw, A J
2009-11-01
Multiple paternity (polyandry) frequently occurs in flowering plants and animals and is assumed to have an important function in the evolution of reproductive traits. Polyandry in bryophytes may occur among multiple sporophytes of a female gametophyte; however, its occurrence and extent is unknown. In this study we investigate the occurrence and extent of multiple paternity, spatial genetic structure, and sporophytic inbreeding depression in natural populations of a dioicous bryophyte species, Sphagnum lescurii, using microsatellite markers. Multiple paternity is prevalent among sporophytes of a female gametophyte and male genotypes exhibit significant skew in paternity. Despite significant spatial genetic structure in the population, suggesting frequent inbreeding, the number of inbred and outbred sporophytes was balanced, resulting in an average fixation coefficient and population level selfing rate of zero. In line with the prediction of sporophytic inbreeding depression sporophyte size was significantly correlated with the level of heterozygosity. Furthermore, female gametophytes preferentially supported sporophytes with higher heterozygosity. These results indicate that polyandry provides the opportunity for postfertilization selection in bryophytes having short fertilization distances and spatially structured populations facilitating inbreeding. Preferential maternal support of the more heterozygous sporophytes suggests active inbreeding avoidance that may have significant implications for mating system evolution in bryophytes.
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Telles, Mariana Pires de Campos; Bastos, Rogério Pereira; Soares, Thannya Nascimento; Resende, Lucileide Vilela; Diniz-Filho, José Alexandre Felizola
2006-01-01
Studies about the organization of the genetic variability and population structure in natural populations are used either to understand microevolutionary processes or the effects of isolation by human-inducted landscape modifications. In this paper, we analyzed patterns of genetic population structure using 126 RAPD loci scored for 214 individuals of Physalaemus cuvieri, sampled from 18 local populations. Around 97% of these loci were polymorphic. The among-population variation component (Phi(ST)) obtained by AMOVA was equal to 0.101 and theta B obtained using a Bayesian approach for dominant markers was 0.103. Genetic divergence, analyzed by Mantel spatial correlogram, revealed only a short-distance significant correlation between genetic and geographic distances. This is expected if low levels of population differentiation, due to high abundance buffering the effect of stochastic processes, are combined with low spatially restricted gene flow. Although this may be consistent with the current knowledge of species' biology, the spatial distribution of local populations observed in this study also suggest that, at least in part, recent human occupation and habitat fragmentation may also explain part of the interpopulational component of the genetic variation.
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The spatial-temporal characteristics of type I collagen-based extracellular matrix.
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.
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Yang, Lin; Zhang, Feng; Meng, Fan -Qiang; ...
2018-05-12
A metastable ε-Al 60Sm 11 phase appears during the initial devitrification of as-quenched Al-10.2 at.% Sm glasses. The ε phase is nonstoichiometric in nature since Al occupation is observed on the 16 f Sm lattice sites. Scanning transmission electron microscopic images reveal profound spatial correlation of Sm content on these sites, which cannot be explained by the “average crystal” description from Rietveld analysis of diffraction data. Thermodynamically favorable configurations, established by Monte Carlo (MC) simulations based on a cluster-expansion model, also give qualitatively different correlation functions from experimental observations. On the other hand, molecular dynamics simulations of the growth ofmore » ε-Al 60Sm 11 in undercooled liquid show that when the diffusion range of Sm is limited to ~4 Å, the correlation function of the as-grown crystal structure agrees well with that of the scanning transmission electronic microscopy (STEM) images. Furthermore, our results show that kinetic effects, especially the limited diffusivity of Sm atoms plays the fundamental role in determining the nonstoichiometric site occupancies of the ε-Al 60Sm 11 phase during the crystallization process.« less
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DOE Office of Scientific and Technical Information (OSTI.GOV)
Yang, Lin; Zhang, Feng; Meng, Fan -Qiang
A metastable ε-Al 60Sm 11 phase appears during the initial devitrification of as-quenched Al-10.2 at.% Sm glasses. The ε phase is nonstoichiometric in nature since Al occupation is observed on the 16 f Sm lattice sites. Scanning transmission electron microscopic images reveal profound spatial correlation of Sm content on these sites, which cannot be explained by the “average crystal” description from Rietveld analysis of diffraction data. Thermodynamically favorable configurations, established by Monte Carlo (MC) simulations based on a cluster-expansion model, also give qualitatively different correlation functions from experimental observations. On the other hand, molecular dynamics simulations of the growth ofmore » ε-Al 60Sm 11 in undercooled liquid show that when the diffusion range of Sm is limited to ~4 Å, the correlation function of the as-grown crystal structure agrees well with that of the scanning transmission electronic microscopy (STEM) images. Furthermore, our results show that kinetic effects, especially the limited diffusivity of Sm atoms plays the fundamental role in determining the nonstoichiometric site occupancies of the ε-Al 60Sm 11 phase during the crystallization process.« less
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Surface and finite size effect on fluctuations dynamics in nanoparticles with long-range order
NASA Astrophysics Data System (ADS)
Morozovska, A. N.; Eliseev, E. A.
2010-02-01
The influence of surface and finite size on the dynamics of the order parameter fluctuations and critical phenomena in the three-dimensional (3D)-confined systems with long-range order was not considered theoretically. In this paper, we study the influence of surface and finite size on the dynamics of the order parameter fluctuations in the particles of arbitrary shape. We consider concrete examples of the spherical and cylindrical ferroic nanoparticles within Landau-Ginzburg-Devonshire phenomenological approach. Allowing for the strong surface energy contribution in micro and nanoparticles, the analytical expressions derived for the Ornstein-Zernike correlator of the long-range order parameter spatial-temporal fluctuations, dynamic generalized susceptibility, relaxation times, and correlation radii discrete spectra are different from those known for bulk systems. Obtained analytical expressions for the correlation function of the order parameter spatial-temporal fluctuations in micro and nanosized systems can be useful for the quantitative analysis of the dynamical structural factors determined from magnetic resonance diffraction and scattering spectra. Besides the practical importance of the correlation function for the analysis of the experimental data, derived expressions for the fluctuations strength determine the fundamental limits of phenomenological theories applicability for 3D-confined systems.
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Reinhold, Ann Marie; Bramblett, Robert G.; Zale, Alexander V.; Poole, Geoffrey C.; Roberts, David W.
2017-01-01
The alteration of rivers by anthropogenic bank stabilization to prevent the erosion of economically valuable lands and structures has become commonplace. However, such alteration has ambiguous consequences for fish assemblages, especially in large rivers. Because most large, temperate rivers have impoundments, it can be difficult to separate the influences of bank stabilization structures from those of main-stem impoundments, especially because both stabilization structures and impoundments can cause side-channel loss. Few large rivers are free flowing and retain extensive side channels, but the Yellowstone River (our study area) is one such river. We hypothesized that in this river (1) bank stabilization has changed fish assemblage structure by altering habitats, (2) side-channel availability has influenced fish assemblage structure by providing habitat heterogeneity, and (3) the influences of bank stabilization and side channels on fish assemblages were spatially scale dependent. We developed a spatially explicit framework to test these hypotheses. Fish assemblage structure varied with the extent of bank stabilization and the availability of side channels; however, not all assemblage subsets were influenced. Nevertheless, bank stabilization and side channels had different and sometimes opposite influences on the fish assemblage. The effects of side channels on fish were more consistent and widespread than those of bank stabilization; the catches of more fishes were positively correlated with side-channel availability than with the extent of bank stabilization. The influences of bank stabilization and side channels on the relative abundances of fish also varied, depending on species and river bend geomorphology. The variation in river morphology probably contributed to the assemblage differences between stabilized and reference river bends; stabilized alluvial pools were deeper than reference alluvial pools, but the depths of stabilized and reference bluff pools did not differ. The strengths of the relationships among fish assemblages, bank stabilization, and side channels were spatially scale dependent; optimum spatial scales ranged from less than 200 m to 3,200 m up- and downstream, suggesting that bank stabilization and side channels influenced fish assemblages across multiple spatial scales.
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NASA Astrophysics Data System (ADS)
Li, Dongfang; Pacifici, Domenico
The spectral degree of coherence describes the correlation of electromagnetic fields, which plays a key role in many applications, including free-space optical communications and speckle-free bioimaging. Recently, plasmonic interferometry, i.e. optical interferometry that employs surface plasmon polaritons (SPPs), has enabled enhanced light transmission and high-sensitivity biosensing, among other applications. It offers new ways to characterize and engineer electromagnetic fields using nano-structured thin metal films. Here, we employ plasmonic interferometry to demonstrate full control of spatial coherence at length scales comparable to the wavelength of the incident light. Specifically, by measuring the diffraction pattern of several double-slit plasmonic structures etched on a metal film, the amplitude and phase of the degree of spatial coherence is determined as a function of slit-slit separation distance and incident wavelength. When the SPP contribution is turned on (i.e., by changing the polarization of the incident light from TE to TM illumination mode), strong modulation of both amplitude and phase of the spatial coherence is observed. These findings may help design compact modulators of optical spatial coherence and other optical elements to shape the light intensity in the far-field.
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DOE Office of Scientific and Technical Information (OSTI.GOV)
Song, Y. L.; Zhang, M., E-mail: ylsong@bao.ac.cn
Many previous studies have shown that magnetic fields and sunspot structures present rapid and irreversible changes associated with solar flares. In this paper, we first use five X-class flares observed by Solar Dynamics Observatory /Helioseismic and Magnetic Imager to show that not only do magnetic fields and sunspot structures show rapid, irreversible changes, but also that these changes are closely related both spatially and temporally. The magnitudes of the correlation coefficients between the temporal variations of the horizontal magnetic field and sunspot intensity are all larger than 0.90, with a maximum value of 0.99 and an average value of 0.96.more » Then, using four active regions during quiescent periods, three observed and one simulated, we show that in sunspot penumbra regions there also exists a close correlation between sunspot intensity and horizontal magnetic field strength in addition to the well-known correlation between sunspot intensity and the normal magnetic field strength. By connecting these two observational phenomena, we show that the sunspot structure change and magnetic field change are two facets of the same phenomena of solar flares; one change might be induced by the change of the other due to a linear correlation between sunspot intensity and magnetic field strength out of a local force balance.« less
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Teijeiro, E J; Macías, R J; Morales, J M; Guerra, E; López, G; Alvarez, L M; Fernández, F; Maragoto, C; Seijo, F; Alvarez, E
The Neurosurgical Deep Recording System (NDRS) using a personal computer takes the place of complex electronic equipment for recording and processing deep cerebral electrical activity, as a guide in stereotaxic functional neurosurgery. It also permits increased possibilities of presenting information in direct graphic form with automatic management and sufficient flexibility to implement different analyses. This paper describes the possibilities of automatic simultaneous graphic representation in three almost orthogonal planes, available with the new 5.1 version of NDRS so as to facilitate the analysis of anatomophysiological correlation in the localization of deep structures of the brain during minimal access surgery. This new version can automatically show the spatial behaviour of signals registered throughout the path of the electrode inside the brain, superimposed simultaneously on sagittal, coronal and axial sections of an anatomical atlas of the brain, after adjusting the scale automatically according to the dimensions of the brain of each individual patient. This may also be shown in a tridimensional representation of the different planes themselves intercepting. The NDRS system has been successfully used in Spain and Cuba in over 300 functional neurosurgery operations. The new version further facilitates analysis of spatial anatomophysiological correlation for the localization of brain structures. This system has contributed to increase the precision and safety in selecting surgical targets in the control of Parkinson s disease and other disorders of movement.
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Yang, M. H.; Li, J. H.; Liu, B. X.
2016-01-01
Based on the newly constructed n-body potential of Ni-Ti-Mo system, Molecular Dynamics and Monte Carlo simulations predict an energetically favored glass formation region and an optimal composition sub-region with the highest glass-forming ability. In order to compare the producing techniques between liquid melt quenching (LMQ) and solid-state amorphization (SSA), inherent hierarchical structure and its effect on mechanical property were clarified via atomistic simulations. It is revealed that both producing techniques exhibit no pronounced differences in the local atomic structure and mechanical behavior, while the LMQ method makes a relatively more ordered structure and a higher intrinsic strength. Meanwhile, it is found that the dominant short-order clusters of Ni-Ti-Mo metallic glasses obtained by LMQ and SSA are similar. By analyzing the structural evolution upon uniaxial tensile deformation, it is concluded that the gradual collapse of the spatial structure network is intimately correlated to the mechanical response of metallic glasses and acts as a structural signature of the initiation and propagation of shear bands. PMID:27418115
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Spatial EPR entanglement in atomic vapor quantum memory
NASA Astrophysics Data System (ADS)
Parniak, Michal; Dabrowski, Michal; Wasilewski, Wojciech
Spatially-structured quantum states of light are staring to play a key role in modern quantum science with the rapid development of single-photon sensitive cameras. In particular, spatial degree of freedom holds a promise to enhance continous-variable quantum memories. Here we present the first demonstration of spatial entanglement between an atomic spin-wave and a photon measured with an I-sCMOS camera. The system is realized in a warm atomic vapor quantum memory based on rubidium atoms immersed in inert buffer gas. In the experiment we create and characterize a 12-dimensional entangled state exhibiting quantum correlations between a photon and an atomic ensemble in position and momentum bases. This state allows us to demonstrate the Einstein-Podolsky-Rosen paradox in its original version, with an unprecedented delay time of 6 μs between generation of entanglement and detection of the atomic state.
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Glassy behavior and dynamic tweed in defect-free multiferroics
NASA Astrophysics Data System (ADS)
Wang, Xiaofei; Salje, Ekhard K. H.; Sun, Jun; Ding, Xiangdong
2018-01-01
Multiferroics often show significant elastic fluctuations even when the transition is strongly stepwise. Molecular dynamics simulations of a generic toy model show the appearance of tweed nanostructures (cross hatched patterns) in the paraelastic phase just above the transition point. This tweed lowers the elastic modulus C12 when approaching the transition temperature. The spatial and temporal correlations of the tweed structure follow the Vogel-Fulcher relationship, and the Vogel-Fulcher temperature is slightly below the transition temperature Ttrans, preventing this glassy state to freeze completely. Spatial correlations of shear strain show that the size of tweed patches reaches about eight lattice spacings near Ttrans. Cross- and rod-shaped diffuse scattering, similar to that in relaxors, emerges around {hh0}* and {h00}* Bragg reflections. The viscosity of the sample increases dramatically at the transition point with a significant precursor increase in the tweed regime.
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DOE Office of Scientific and Technical Information (OSTI.GOV)
Ushenko, Yu A; Gorskii, M P; Dubolazov, A V
2012-08-31
Theory of polarisation-correlation analysis of laser images of histological sections of biopsy material from cervix tissue based on spatial frequency selection of linear and circular birefringence mechanisms is formulated. Comparative results of measuring the coordinate distributions of the complex degree of mutual anisotropy (CDMA), produced by fibrillar networks formed by myosin and collagen fibres of cervix tissue in different pathological conditions, namely, pre-cancer (dysplasia) and cancer (adenocarcinoma), are presented. The values and variation ranges of statistical (moments of the first - fourth order), correlation (excess-autocorrelation functions), and fractal (slopes of approximating curves and dispersion of extrema of logarithmic dependences ofmore » power spectra) parameters of the CDMA coordinate distributions are studied. Objective criteria for pathology diagnostics and differentiation of its severity degree are determined. (image processing)« less
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NASA Astrophysics Data System (ADS)
Ushenko, Yu A.; Gorskii, M. P.; Dubolazov, A. V.; Motrich, A. V.; Ushenko, V. A.; Sidor, M. I.
2012-08-01
Theory of polarisation-correlation analysis of laser images of histological sections of biopsy material from cervix tissue based on spatial frequency selection of linear and circular birefringence mechanisms is formulated. Comparative results of measuring the coordinate distributions of the complex degree of mutual anisotropy (CDMA), produced by fibrillar networks formed by myosin and collagen fibres of cervix tissue in different pathological conditions, namely, pre-cancer (dysplasia) and cancer (adenocarcinoma), are presented. The values and variation ranges of statistical (moments of the first — fourth order), correlation (excess-autocorrelation functions), and fractal (slopes of approximating curves and dispersion of extrema of logarithmic dependences of power spectra) parameters of the CDMA coordinate distributions are studied. Objective criteria for pathology diagnostics and differentiation of its severity degree are determined.
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Infrared Spectroscopy of Pa-beta and [Fe II] Emission in NGC 4151
NASA Technical Reports Server (NTRS)
Knop, R. A.; Armus, L.; Larkin, J. E.; Matthews, K.; Shupe, D. L.; Soifer, B. T.
1996-01-01
We present spatially resolved 1.24-1.30 micron spectroscopy with a resolution of 240 km/s of the Seyfert 1.5 galaxy NGC 4151. Broad Pa-beta, narrow Pa-beta, and narrow [Fe II] (lambda = 1.2567 micron) emission lines are identified in the spectrum. Additionally, a spatially unresolved narrow component probably due to [S ix] (lambda = 1.25235 micron) is observed on the nucleus. The narrow Pa-beta and [Fe II] lines are observed to be extended over a scale of 5 sec. The spatial variation of the velocity centers of the Pa-beta and [Fe II] lines show remarkable similarity, and additionally show similarities to the velocity structure previously observed in ground based spectroscopy of [O III] emission in NGC 4151. This leads to the conclusion that the [Fe II] emission arises in clouds in the Seyfert narrow line region that are physically correlated with those narrow line clouds responsible for the optical emission. The [Fe II] emission line, however, is significantly wider than the Pa-beta emission line along the full spatial extent of the observed emission. This result suggests that despite the correlation between the bulk kinematics of Pa-beta and [Fe II], there is an additional process, perhaps fast shocks from a wind in the Seyfert nucleus, contributing to the [Fe II] emission.
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Li, Dan; Wang, Xia; Dey, Dipak K
2016-09-01
Our present work proposes a new survival model in a Bayesian context to analyze right-censored survival data for populations with a surviving fraction, assuming that the log failure time follows a generalized extreme value distribution. Many applications require a more flexible modeling of covariate information than a simple linear or parametric form for all covariate effects. It is also necessary to include the spatial variation in the model, since it is sometimes unexplained by the covariates considered in the analysis. Therefore, the nonlinear covariate effects and the spatial effects are incorporated into the systematic component of our model. Gaussian processes (GPs) provide a natural framework for modeling potentially nonlinear relationship and have recently become extremely powerful in nonlinear regression. Our proposed model adopts a semiparametric Bayesian approach by imposing a GP prior on the nonlinear structure of continuous covariate. With the consideration of data availability and computational complexity, the conditionally autoregressive distribution is placed on the region-specific frailties to handle spatial correlation. The flexibility and gains of our proposed model are illustrated through analyses of simulated data examples as well as a dataset involving a colon cancer clinical trial from the state of Iowa. © 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.
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A STED-FLIM microscope applied to imaging the natural killer cell immune synapse
NASA Astrophysics Data System (ADS)
Lenz, M. O.; Brown, A. C. N.; Auksorius, E.; Davis, D. M.; Dunsby, C.; Neil, M. A. A.; French, P. M. W.
2011-03-01
We present a stimulated emission depletion (STED) fluorescence lifetime imaging (FLIM) microscope, excited by a microstructured optical fibre supercontinuum source that is pumped by a femtosecond Ti:Sapphire-laser, which is also used for depletion. Implemented using a piezo-scanning stage on a laser scanning confocal fluorescence microscope system with FLIM realised using time correlated single photon counting (TCSPC), this provides convenient switching between confocal and STED-FLIM with spatial resolution down to below 60 nm. We will present our design considerations to make a robust instrument for biological applications including a comparison between fixed phase plate and spatial light modulator (SLM) approaches to shape the STED beam and the correlation of STED and confocal FLIM microscopy. Following our previous application of FLIM-FRET to study intercellular signalling at the immunological synapse (IS), we are employing STED microscopy to characterize the spatial distribution of cellular molecules with subdiffraction resolution at the IS. In particular, we are imaging cytoskeletal structure at the Natural Killer cell activated immune synapse. We will also present our progress towards multilabel STED microscopy to determine how relative spatial molecular organization, previously undetectable by conventional microscopy techniques, is important for NK cell cytotoxic function. Keywords: STED, Stimulated Emission Depletion Microscopy, Natural Killer (NK) cell, Fluorescence lifetime imaging, FLIM, Super resolution microscopy.
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Observations of the Winter Thermal Structure of Lake Superior
NASA Astrophysics Data System (ADS)
Titze, Daniel James
Moored thermistor strings that span the water column have been deployed at up to seven locations throughout Lake Superior from 2005 through present, producing a unique year-round record of the thermal structure of a large lake. This extensive temperature record reveals significant interannual and spatial variability in Lake Superior's winter heat content, thermocline depth, and phenology. Of particular mention is a stark contrast in thermal structure between the cold, icy winter of 2009 and the much warmer winter of 2012, during which especially strong and weak negative stratification was observed, respectively. Significant interannual and spatial variability was also observed in Lake Superior ice cover, as shown through data extracted from Ice Mapping System satellite imagery (NOAA/NESDIS 2004). When water column heat content was estimated from temperature data and analyzed in concert with lake ice-cover data, it was found that ice cover can inhibit heat flux between the lake and the atmosphere, and that spatial variability in ice cover can translate into spatial variability in end-of-winter heat content. Such variability in end-of-winter heat content is found to be preserved through the spring warming season, and is strongly correlated with variability in the timing of the onset of summer stratification, with regions that have warmer end-of-winter water columns stratifying earlier than regions with colder end-of-winter water-columns.
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Community structure of aquatic insects in the Esparza River, Costa Rica.
Herrera-Vásquez, Jonathan
2009-01-01
This study focused on the structure of the aquatic insect community in spatial and temporal scales in the Esparza River. The river was sampled for one full year throughout 2007. During the dry season low flow months, five sampling points were selected in two different habitats (currents and pools), with five replicates per sample site. During the wet season with peak rain, only the data in the "current habitat" were sampled at each site. Specimens present in the different substrates were collected and preserved in situ. A nested ANOVA was then applied to the data to determine richness and density as the response variables. The variations in temporal and spatial scales were analyzed using width, depth and discharge of the river, and then analyzed using a nested ANOVA. Only a correlation of 51% similarity in richness was found, while in spatial scale, richness showed significant variation between sampling sites, but not between habitats. However, the temporal scale showed significant differences between habitats. Density showed differences between sites and habitats during the dry season in the spatial scale, while in the temporal scale significant variation was found between sampling sites. Width varied between habitats during the dry season, but not between sampling points. Depth showed differences between sampling sites and season. This work studies the importance of community structure of aquatic insects in rivers, and its relevance for the quality of water in rivers and streams.
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Sun, Jin; Kelbert, Anna; Egbert, G.D.
2015-01-01
Long-period global-scale electromagnetic induction studies of deep Earth conductivity are based almost exclusively on magnetovariational methods and require accurate models of external source spatial structure. We describe approaches to inverting for both the external sources and three-dimensional (3-D) conductivity variations and apply these methods to long-period (T≥1.2 days) geomagnetic observatory data. Our scheme involves three steps: (1) Observatory data from 60 years (only partly overlapping and with many large gaps) are reduced and merged into dominant spatial modes using a scheme based on frequency domain principal components. (2) Resulting modes are inverted for corresponding external source spatial structure, using a simplified conductivity model with radial variations overlain by a two-dimensional thin sheet. The source inversion is regularized using a physically based source covariance, generated through superposition of correlated tilted zonal (quasi-dipole) current loops, representing ionospheric source complexity smoothed by Earth rotation. Free parameters in the source covariance model are tuned by a leave-one-out cross-validation scheme. (3) The estimated data modes are inverted for 3-D Earth conductivity, assuming the source excitation estimated in step 2. Together, these developments constitute key components in a practical scheme for simultaneous inversion of the catalogue of historical and modern observatory data for external source spatial structure and 3-D Earth conductivity.
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Zhu, Yao-Jun; Bourgeois, C; Lin, Guang-Xuan; Wu, Xiao-Dong; Guo, Ju-Lan; Guo, Zhi-Hua
2012-08-01
Mangrove wetland is an important type of coastal wetlands, and also, an important sediment trap. Sediment is an essential medium for mangrove recruitment and development, which records the environmental history of mangrove wetlands and can be used for the analysis of material sources and the inference of the materials depositing process, being essential to the ecological restoration and conservation of mangrove. In this paper, surface sediment samples were collected along a hydrodynamic gradient in Gaoqiao, Zhanjiang Mangrove National Nature Reserve in 2011. The characteristics of the surface sediments were analyzed based on grain size analysis, and the prediction surfaces were generated by the geo-statistical methods with ArcGIS 9.2 software. A correlation analysis was also conducted on the sediment organic matter content and the mangrove community structure. In the study area, clay and silt dominated the sediment texture, and the mean content of sand, silt, and clay was (27.8 +/- 15.4)%, (40.3 +/- 15.4)%, and (32.1 +/- 11.4)%, respectively. The spatial gradient of the sediment characteristics was expressed in apparent interpolation raster. With increasing distance from the seawall, the sediment sand content increased, clay content decreased, and silt content was relatively stable at a certain level. There was a positive correlation between the contents of sediment organic matter and silt, and a negative correlation between the contents of sediment organic matter and sand. Much more sediment organic matter was located at the high tide area with weak tide energy. There existed apparent discrepancies in the characteristics of the surface sediments in different biotopes. The sediment characteristics had definite correlations with the community structure of mangroves, reflecting the complicated correlations between the hydrodynamic conditions and the mangroves.
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NASA Astrophysics Data System (ADS)
Golay, Jean; Kanevski, Mikhaïl
2013-04-01
The present research deals with the exploration and modeling of a complex dataset of 200 measurement points of sediment pollution by heavy metals in Lake Geneva. The fundamental idea was to use multivariate Artificial Neural Networks (ANN) along with geostatistical models and tools in order to improve the accuracy and the interpretability of data modeling. The results obtained with ANN were compared to those of traditional geostatistical algorithms like ordinary (co)kriging and (co)kriging with an external drift. Exploratory data analysis highlighted a great variety of relationships (i.e. linear, non-linear, independence) between the 11 variables of the dataset (i.e. Cadmium, Mercury, Zinc, Copper, Titanium, Chromium, Vanadium and Nickel as well as the spatial coordinates of the measurement points and their depth). Then, exploratory spatial data analysis (i.e. anisotropic variography, local spatial correlations and moving window statistics) was carried out. It was shown that the different phenomena to be modeled were characterized by high spatial anisotropies, complex spatial correlation structures and heteroscedasticity. A feature selection procedure based on General Regression Neural Networks (GRNN) was also applied to create subsets of variables enabling to improve the predictions during the modeling phase. The basic modeling was conducted using a Multilayer Perceptron (MLP) which is a workhorse of ANN. MLP models are robust and highly flexible tools which can incorporate in a nonlinear manner different kind of high-dimensional information. In the present research, the input layer was made of either two (spatial coordinates) or three neurons (when depth as auxiliary information could possibly capture an underlying trend) and the output layer was composed of one (univariate MLP) to eight neurons corresponding to the heavy metals of the dataset (multivariate MLP). MLP models with three input neurons can be referred to as Artificial Neural Networks with EXternal drift (ANNEX). Moreover, the exact number of output neurons and the selection of the corresponding variables were based on the subsets created during the exploratory phase. Concerning hidden layers, no restriction were made and multiple architectures were tested. For each MLP model, the quality of the modeling procedure was assessed by variograms: if the variogram of the residuals demonstrates pure nugget effect and if the level of the nugget exactly corresponds to the nugget value of the theoretical variogram of the corresponding variable, all the structured information has been correctly extracted without overfitting. Finally, it is worth mentioning that simple MLP models are not always able to remove all the spatial correlation structure from the data. In that case, Neural Network Residual Kriging (NNRK) can be carried out and risk assessment can be conducted with Neural Network Residual Simulations (NNRS). Finally, the results of the ANNEX models were compared to those of ordinary (co)kriging and (co)kriging with an external drift. It was shown that the ANNEX models performed better than traditional geostatistical algorithms when the relationship between the variable of interest and the auxiliary predictor was not linear. References Kanevski, M. and Maignan, M. (2004). Analysis and Modelling of Spatial Environmental Data. Lausanne: EPFL Press.
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DOE Office of Scientific and Technical Information (OSTI.GOV)
Tucker, Eric; Boreman, Glenn, E-mail: gboreman@uncc.edu; D'Archangel, Jeffrey
Near- and far-field measurements of phase-ramped loop and patch structures are presented and compared to simulations. The far-field deflection measurements show that the phase-ramped structures can deflect a beam away from specular reflection, consistent with simulations. Scattering scanning near-field optical microscopy of the elements comprising the phase ramped structures reveals part of the underlying near-field phase contribution that dictates the far-field deflection, which correlates with the far-field phase behavior that was expected. These measurements provide insight into the resonances, coupling, and spatial phase variation among phase-ramped frequency selective surface (FSS) elements, which are important for the performance of FSS reflectarrays.
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NASA Astrophysics Data System (ADS)
Ginsberg, Naomi
2015-03-01
The migration of Frenkel excitons, tightly-bound electron-hole pairs, in polymeric organic semiconducting films is critical to the efficiency of bulk heterojunction solar cells. While these materials exhibit a high degree of structural heterogeneity on the nanoscale, traditional measurements of exciton diffusion lengths are performed on bulk samples. Since both the characteristic length scales of structural heterogeneity and the reported bulk diffusion lengths are smaller than the optical diffraction limit, we adapt far-field super-resolution fluorescence imaging to uncover the correlations between the structural and energetic landscapes that the excitons explore.
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NASA Astrophysics Data System (ADS)
Yang, Yongchao; Dorn, Charles; Mancini, Tyler; Talken, Zachary; Nagarajaiah, Satish; Kenyon, Garrett; Farrar, Charles; Mascareñas, David
2017-03-01
Enhancing the spatial and temporal resolution of vibration measurements and modal analysis could significantly benefit dynamic modelling, analysis, and health monitoring of structures. For example, spatially high-density mode shapes are critical for accurate vibration-based damage localization. In experimental or operational modal analysis, higher (frequency) modes, which may be outside the frequency range of the measurement, contain local structural features that can improve damage localization as well as the construction and updating of the modal-based dynamic model of the structure. In general, the resolution of vibration measurements can be increased by enhanced hardware. Traditional vibration measurement sensors such as accelerometers have high-frequency sampling capacity; however, they are discrete point-wise sensors only providing sparse, low spatial sensing resolution measurements, while dense deployment to achieve high spatial resolution is expensive and results in the mass-loading effect and modification of structure's surface. Non-contact measurement methods such as scanning laser vibrometers provide high spatial and temporal resolution sensing capacity; however, they make measurements sequentially that requires 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 or template matching, optical flow, etc.), video camera based measurements have been successfully used for experimental and operational vibration measurement and subsequent modal analysis. However, the sampling frequency of most affordable digital cameras is limited to 30-60 Hz, while high-speed cameras for higher frequency vibration measurements are extremely costly. This work develops a computational algorithm capable of performing vibration measurement at a uniform sampling frequency lower than what is required by the Shannon-Nyquist sampling theorem for output-only modal analysis. In particular, the spatio-temporal uncoupling property of the modal expansion of structural vibration responses enables a direct modal decoupling of the temporally-aliased vibration measurements by existing output-only modal analysis methods, yielding (full-field) mode shapes estimation directly. Then the signal aliasing properties in modal analysis is exploited to estimate the modal frequencies and damping ratios. The proposed method is validated by laboratory experiments where output-only modal identification is conducted on temporally-aliased acceleration responses and particularly the temporally-aliased video measurements of bench-scale structures, including a three-story building structure and a cantilever beam.
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Empirical spatial econometric modelling of small scale neighbourhood
NASA Astrophysics Data System (ADS)
Gerkman, Linda
2012-07-01
The aim of the paper is to model small scale neighbourhood in a house price model by implementing the newest methodology in spatial econometrics. A common problem when modelling house prices is that in practice it is seldom possible to obtain all the desired variables. Especially variables capturing the small scale neighbourhood conditions are hard to find. If there are important explanatory variables missing from the model, the omitted variables are spatially autocorrelated and they are correlated with the explanatory variables included in the model, it can be shown that a spatial Durbin model is motivated. In the empirical application on new house price data from Helsinki in Finland, we find the motivation for a spatial Durbin model, we estimate the model and interpret the estimates for the summary measures of impacts. By the analysis we show that the model structure makes it possible to model and find small scale neighbourhood effects, when we know that they exist, but we are lacking proper variables to measure them.
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Simultaneous PIV and PLIF measurement of passive scalar mixing in a confined planar jet
NASA Astrophysics Data System (ADS)
Feng, Hua
2005-11-01
Simultaneous velocity and concentration fields in a confined liquid-phase planar jet with a Reynolds number based on hydraulic diameter of 50,000 were obtained using combined particle image velocimetry (PIV) and planar laser-induced fluorescence (PLIF). Data at six downstream locations were analyzed for flow statistics such as mean velocity, Reynolds stresses, turbulent kinetic energy, concentration mean and variance, turbulent fluxes, turbulent viscosity and diffusivity, and turbulent Schmidt number. Spatial correlation fields of turbulent fluxes and concentration were then determined. The Ru'φ' correlation was elliptical in shape with a major axis tilted downward with respect to the streamwise axis, whereas the Rv'φ' correlation was a horizontally oriented ellipse. The Rφ'φ' correlation field was found to be an ellipse with the major axis inclined at about 45-degrees with respect to the streamwise direction. Linear stochastic estimation was used to determine conditional flow structures. Large-scale structures were observed in the conditional velocity fields that are elliptical in shape with a streamwise major axis. The size of the structure initially increased linearly with respect to downstream distance, but then grew more slowly as the flow evolved towards channel flow.
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Amygdala reactivity in healthy adults is correlated with prefrontal cortical thickness.
Foland-Ross, Lara C; Altshuler, Lori L; Bookheimer, Susan Y; Lieberman, Matthew D; Townsend, Jennifer; Penfold, Conor; Moody, Teena; Ahlf, Kyle; Shen, Jim K; Madsen, Sarah K; Rasser, Paul E; Toga, Arthur W; Thompson, Paul M
2010-12-08
Recent evidence suggests that putting feelings into words activates the prefrontal cortex (PFC) and suppresses the response of the amygdala, potentially helping to alleviate emotional distress. To further elucidate the relationship between brain structure and function in these regions, structural and functional magnetic resonance imaging (MRI) data were collected from a sample of 20 healthy human subjects. Structural MRI data were processed using cortical pattern-matching algorithms to produce spatially normalized maps of cortical thickness. During functional scanning, subjects cognitively assessed an emotional target face by choosing one of two linguistic labels (label emotion condition) or matched geometric forms (control condition). Manually prescribed regions of interest for the left amygdala were used to extract percentage signal change in this region occurring during the contrast of label emotion versus match forms. A correlation analysis between left amygdala activation and cortical thickness was then performed along each point of the cortical surface, resulting in a color-coded r value at each cortical point. Correlation analyses revealed that gray matter thickness in left ventromedial PFC was inversely correlated with task-related activation in the amygdala. These data add support to a general role of the ventromedial PFC in regulating activity of the amygdala.
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Wang, Tuo; Park, Yong Bum; Hong, Mei
2015-01-01
The structural role of pectins in plant primary cell walls is not yet well understood because of the complex and disordered nature of the cell wall polymers. We recently introduced multidimensional solid-state nuclear magnetic resonance spectroscopy to characterize the spatial proximities of wall polysaccharides. The data showed extensive cross peaks between pectins and cellulose in the primary wall of Arabidopsis (Arabidopsis thaliana), indicating subnanometer contacts between the two polysaccharides. This result was unexpected because stable pectin-cellulose interactions are not predicted by in vitro binding assays and prevailing cell wall models. To investigate whether the spatial contacts that give rise to the cross peaks are artifacts of sample preparation, we now compare never-dried Arabidopsis primary walls with dehydrated and rehydrated samples. One-dimensional 13C spectra, two-dimensional 13C-13C correlation spectra, water-polysaccharide correlation spectra, and dynamics data all indicate that the structure, mobility, and intermolecular contacts of the polysaccharides are indistinguishable between never-dried and rehydrated walls. Moreover, a partially depectinated cell wall in which 40% of homogalacturonan is extracted retains cellulose-pectin cross peaks, indicating that the cellulose-pectin contacts are not due to molecular crowding. The cross peaks are observed both at −20°C and at ambient temperature, thus ruling out freezing as a cause of spatial contacts. These results indicate that rhamnogalacturonan I and a portion of homogalacturonan have significant interactions with cellulose microfibrils in the native primary wall. This pectin-cellulose association may be formed during wall biosynthesis and may involve pectin entrapment in or between cellulose microfibrils, which cannot be mimicked by in vitro binding assays. PMID:26036615
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Optical magnetic imaging of living cells
Le Sage, D.; Arai, K.; Glenn, D. R.; DeVience, S. J.; Pham, L. M.; Rahn-Lee, L.; Lukin, M. D.; Yacoby, A.; Komeili, A.; Walsworth, R. L.
2013-01-01
Magnetic imaging is a powerful tool for probing biological and physical systems. However, existing techniques either have poor spatial resolution compared to optical microscopy and are hence not generally applicable to imaging of sub-cellular structure (e.g., magnetic resonance imaging [MRI]1), or entail operating conditions that preclude application to living biological samples while providing sub-micron resolution (e.g., scanning superconducting quantum interference device [SQUID] microscopy2, electron holography3, and magnetic resonance force microscopy [MRFM]4). Here we demonstrate magnetic imaging of living cells (magnetotactic bacteria) under ambient laboratory conditions and with sub-cellular spatial resolution (400 nm), using an optically-detected magnetic field imaging array consisting of a nanoscale layer of nitrogen-vacancy (NV) colour centres implanted at the surface of a diamond chip. With the bacteria placed on the diamond surface, we optically probe the NV quantum spin states and rapidly reconstruct images of the vector components of the magnetic field created by chains of magnetic nanoparticles (magnetosomes) produced in the bacteria, and spatially correlate these magnetic field maps with optical images acquired in the same apparatus. Wide-field sCMOS acquisition allows parallel optical and magnetic imaging of multiple cells in a population with sub-micron resolution and >100 micron field-of-view. Scanning electron microscope (SEM) images of the bacteria confirm that the correlated optical and magnetic images can be used to locate and characterize the magnetosomes in each bacterium. The results provide a new capability for imaging bio-magnetic structures in living cells under ambient conditions with high spatial resolution, and will enable the mapping of a wide range of magnetic signals within cells and cellular networks5, 6. PMID:23619694
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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.
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2011-01-01
Background Population extinction risk in a fragmented landscape is related to the differential ability of the species to spread its genes across the landscape. The impact of landscape fragmentation on plant population dynamics will therefore vary across different spatial scales. We quantified successful seed-mediated dispersal of the dioecious shrub Juniperus communis in a fragmented landscape across northwestern Europe by using amplified fragment length polymorphism (AFLP) markers. Furthermore we investigated the genetic diversity and structure on two spatial scales: across northwestern Europe and across Flanders (northern Belgium). We also studied whether seed viability and populations size were correlated with genetic diversity. Results Unexpectedly, estimated seed-mediated dispersal rates were quite high and ranged between 3% and 14%. No population differentiation and no spatial genetic structure were detected on the local, Flemish scale. A significant low to moderate genetic differentiation between populations was detected at the regional, northwest European scale (PhiPT = 0.10). In general, geographically nearby populations were also genetically related. High levels of within-population genetic diversity were detected but no correlation was found between any genetic diversity parameter and population size or seed viability. Conclusions In northwestern Europe, landscape fragmentation has lead to a weak isolation-by-distance pattern but not to genetic impoverishment of common juniper. Substantial rates of successful migration by seed-mediated gene flow indicate a high dispersal ability which could enable Juniperus communis to naturally colonize suitable habitats. However, it is not clear whether the observed levels of migration will suffice to counterbalance the effects of genetic drift in small populations on the long run. PMID:21859457
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Vanden-Broeck, An; Gruwez, Robert; Cox, Karen; Adriaenssens, Sandy; Michalczyk, Inga M; Verheyen, Kris
2011-08-22
Population extinction risk in a fragmented landscape is related to the differential ability of the species to spread its genes across the landscape. The impact of landscape fragmentation on plant population dynamics will therefore vary across different spatial scales. We quantified successful seed-mediated dispersal of the dioecious shrub Juniperus communis in a fragmented landscape across northwestern Europe by using amplified fragment length polymorphism (AFLP) markers. Furthermore we investigated the genetic diversity and structure on two spatial scales: across northwestern Europe and across Flanders (northern Belgium). We also studied whether seed viability and populations size were correlated with genetic diversity. Unexpectedly, estimated seed-mediated dispersal rates were quite high and ranged between 3% and 14%. No population differentiation and no spatial genetic structure were detected on the local, Flemish scale. A significant low to moderate genetic differentiation between populations was detected at the regional, northwest European scale (PhiPT = 0.10). In general, geographically nearby populations were also genetically related. High levels of within-population genetic diversity were detected but no correlation was found between any genetic diversity parameter and population size or seed viability. In northwestern Europe, landscape fragmentation has lead to a weak isolation-by-distance pattern but not to genetic impoverishment of common juniper. Substantial rates of successful migration by seed-mediated gene flow indicate a high dispersal ability which could enable Juniperus communis to naturally colonize suitable habitats. However, it is not clear whether the observed levels of migration will suffice to counterbalance the effects of genetic drift in small populations on the long run.
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Spatio-temporal patterns of key exploited marine species in the Northwestern Mediterranean Sea.
Morfin, Marie; Fromentin, Jean-Marc; Jadaud, Angélique; Bez, Nicolas
2012-01-01
This study analyzes the temporal variability/stability of the spatial distributions of key exploited species in the Gulf of Lions (Northwestern Mediterranean Sea). To do so, we analyzed data from the MEDITS bottom-trawl scientific surveys from 1994 to 2010 at 66 fixed stations and selected 12 key exploited species. We proposed a geostatistical approach to handle zero-inflated and non-stationary distributions and to test for the temporal stability of the spatial structures. Empirical Orthogonal Functions and other descriptors were then applied to investigate the temporal persistence and the characteristics of the spatial patterns. The spatial structure of the distribution (i.e. the pattern of spatial autocorrelation) of the 12 key species studied remained highly stable over the time period sampled. The spatial distributions of all species obtained through kriging also appeared to be stable over time, while each species displayed a specific spatial distribution. Furthermore, adults were generally more densely concentrated than juveniles and occupied areas included in the distribution of juveniles. Despite the strong persistence of spatial distributions, we also observed that the area occupied by each species was correlated to its abundance: the more abundant the species, the larger the occupation area. Such a result tends to support MacCall's basin theory, according to which density-dependence responses would drive the expansion of those 12 key species in the Gulf of Lions. Further analyses showed that these species never saturated their habitats, suggesting that they are below their carrying capacity; an assumption in agreement with the overexploitation of several of these species. Finally, the stability of their spatial distributions over time and their potential ability to diffuse outside their main habitats give support to Marine Protected Areas as a potential pertinent management tool.
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Paciorek, Christopher J; Liu, Yang
2012-05-01
Research in scientific, public health, and policy disciplines relating to the environment increasingly makes use of high-dimensional remote sensing and the output of numerical models in conjunction with traditional observations. Given the public health and resultant public policy implications of the potential health effects of particulate matter (PM*) air pollution, specifically fine PM with an aerodynamic diameter < or = 2.5 pm (PM2.5), there has been substantial recent interest in the use of remote-sensing information, in particular aerosol optical depth (AOD) retrieved from satellites, to help characterize variability in ground-level PM2.5 concentrations in space and time. While the United States and some other developed countries have extensive PM monitoring networks, gaps in data across space and time necessarily occur; the hope is that remote sensing can help fill these gaps. In this report, we are particularly interested in using remote-sensing data to inform estimates of spatial patterns in ambient PM2.5 concentrations at monthly and longer time scales for use in epidemiologic analyses. However, we also analyzed daily data to better disentangle spatial and temporal relationships. For AOD to be helpful, it needs to add information beyond that available from the monitoring network. For analyses of chronic health effects, it needs to add information about the concentrations of long-term average PM2.5; therefore, filling the spatial gaps is key. Much recent evidence has shown that AOD is correlated with PM2.5 in the eastern United States, but the use of AOD in exposure analysis for epidemiologic work has been rare, in part because discrepancies necessarily exist between satellite-retrieved estimates of AOD, which is an atmospheric-column average, and ground-level PM2.5. In this report, we summarize the results of a number of empirical analyses and of the development of statistical models for the use of proxy information, in particular satellite AOD, in predicting PM2.5 concentrations in the eastern United States. We analyzed the spatiotemporal structure of the relationship between PM2.5 and AOD, first using simple correlations both before and after calibration based on meteorology, as well as large-scale spatial and temporal calibration to account for discrepancies between AOD and PM2.5. We then used both raw and calibrated AOD retrievals in statistical models to predict PM2.5 concentrations, accounting for AOD in two ways: primarily as a separate data source contributing a second likelihood to a Bayesian statistical model, as well as a data source on which we could directly regress. Previous consideration of satellite AOD has largely focused on the National Aeronautics and Space Administration (NASA) moderate resolution imaging spectroradiometer (MODIS) and multiangle imaging spectroradiometer (MISR) instruments. One contribution of our work is more extensive consideration of AOD derived from the Geostationary Operational Environmental Satellite East Aerosol/Smoke Product (GOES GASP) AOD and its relationship with PM2.5. In addition to empirically assessing the spatiotemporal relationship between GASP AOD and PM2.5, we considered new statistical techniques to screen anomalous GOES reflectance measurements and account for background surface reflectance. In our statistical work, we developed a new model structure that allowed for more flexible modeling of the proxy discrepancy than previous statistical efforts have had, with a computationally efficient implementation. We also suggested a diagnostic for assessing the scales of the spatial relationship between the proxy and the spatial process of interest (e.g., PM2.5). In brief, we had little success in improving predictions in our eastern-United States domain for use in epidemiologic applications. We found positive correlations of AOD with PM2.5 over time, but less correlation for long-term averages over space, unless we used calibration that adjusted for large-scale discrepancy between AOD and PM2.5 (see sections 3, 4, and 5). Statistical models that combined AOD, PM2.5 observations, and land-use and meteorologic variables were highly predictive of PM2.5 observations held out of the modeling, but AOD added little information beyond that provided by the other sources (see sections 5 and 6). When we used PM2.5 data estimates from the Community Multiscale Air Quality model (CMAQ) as the proxy instead of using AOD, we similarly found little improvement in predicting held-out observations of PM2.5, but when we regressed on CMAQ PM2.5 estimates, the predictions improved moderately in some cases. These results appeared to be caused in part by the fact that large-scale spatial patterns in PM2.5 could be predicted well by smoothing the monitor values, while small-scale spatial patterns in AOD appeared to weakly reflect the variation in PM2.5 inferred from the observations. Using a statistical model that allowed for potential proxy discrepancy at both large and small spatial scales was an important component of our modeling. In particular, when our models did not include a component to account for small-scale discrepancy, predictive performance decreased substantially. Even long-term averages of MISR AOD, considered the best, albeit most sparse, of the AOD products, were only weakly correlated with measured PM2.5 (see section 4). This might have been partly related to the fact that our analysis did not account for spatial variation in the vertical profile of the aerosol. Furthermore, we found evidence that some of the correlation between raw AOD and PM2.5 might have been a function of surface brightness related to land use, rather than having been driven by the detection of aerosol in the AOD retrieval algorithms (see sections 4 and 7). Difficulties in estimating the background surface reflectance in the retrieval algorithms likely explain this finding. With regard to GOES, we found moderate correlations of GASP AOD and PM2.5. The higher correlations of monthly and yearly averages after calibration reflected primarily the improved large-scale correlation, a necessary result of the calibration procedure (see section 3). While the results of this study's GOES reflectance screening and surface reflection correction appeared sensible, correlations of our proposed reflectance-based proxy with PM2.5 were no better than GASP AOD correlations with PM2.5 (see section 7). We had difficulty improving spatial prediction of monthly and yearly average PM2.5 using AOD in the eastern United States, which we attribute to the spatial discrepancy between AOD and measured PM2.5, particularly at smaller scales. This points to the importance of paying attention to the discrepancy structure of proxy information, both from remote-sensing and deterministic models. In particular, important statistical challenges arise in accounting for the discrepancy, given the difficulty in the face of sparse observations of distinguishing the discrepancy from the component of the proxy that is informative about the process of interest. Associations between adverse health outcomes and large-scale variation in PM2.5 (e.g., across regions) may be confounded by unmeasured spatial variation in factors such as diet. Therefore, one important goal was to use AOD to improve predictions of PM2.5 for use in epidemiologic analyses at small-to-moderate spatial scales (within urban areas and within regions). In addition, large-scale PM2.5 variation is well estimated from the monitoring data, at least in the United States. We found little evidence that current AOD products are helpful for improving prediction at small-to-moderate scales in the eastern United States and believe more evidence for the reliability of AOD as a proxy at such scales is needed before making use of AOD for PM2.5 prediction in epidemiologic contexts. While our results relied in part on relatively complicated statistical models, which may be sensitive to modeling assumptions, our exploratory correlation analyses (see sections 3 and 5) and relatively simple regression-style modeling of MISR AOD (see section 4) were consistent with the more complicated modeling results. When assessing the usefulness of AOD in the context of studying chronic health effects, we believe efforts need to focus on disentangling the temporal from the spatial correlations of AOD and PM2.5 and on understanding the spatial scale of correlation and of the discrepancy structure. While our results are discouraging, it is important to note that we attempted to make use of smaller-scale spatial variation in AOD to distinguish spatial variations of relatively small magnitude in long-term concentrations of ambient PM2.5. Our efforts pushed the limits of current technology in a spatial domain with relatively low PM2.5 levels and limited spatial variability. AOD may hold more promise in areas with higher aerosol levels, as the AOD signal would be stronger there relative to the background surface reflectance. Furthermore, for developing countries with high aerosol levels, it is difficult to build statistical models based on PM2.5 measurements and land-use covariates, so AOD may add more incremental information in those contexts. More generally, researchers in remote sensing are involved in ongoing efforts to improve AOD products and develop new approaches to using AOD, such as calibration with model-estimated vertical profiles and the use of speciation information in MISR AOD; these efforts warrant continued investigation of the usefulness of remotely sensed AOD for public health research.
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Keith S. Summerville; Michael R. Saunders; Jamie L. Lane
2013-01-01
The response of forest insect communities to disturbances such as timber harvest likely will depend on the underlying ecological assembly rules that affect community structure. Two competing hypotheses are niche assembly, which seeks to demonstrate significant species-environment correlations, and dispersal-assembly, which seeks to demonstrate spatial autocorrelation...
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Villate, L; Fievet, V; Hanse, B; Delemarre, F; Plantard, O; Esmenjaud, D; van Helden, M
2008-08-01
The nematode Xiphinema index is, economically, the major virus vector in viticulture, transmitting specifically the Grapevine fanleaf virus (GFLV), the most severe grapevine virus disease worldwide. Increased knowledge of the spatial distribution of this nematode, both horizontally and vertically, and of correlative GFLV plant infections, is essential to efficiently control the disease. In two infested blocks of the Bordeaux vineyard, vertical distribution data showed that the highest numbers of individuals occurred at 40 to 110 cm depth, corresponding to the two layers where the highest densities of fine roots were observed. Horizontal distribution based on a 10 x 15 m grid sampling procedure revealed a significant aggregative pattern but no significant neighborhood structure of nematode densities. At a finer scale ( approximately 2 x 2 m), nematode sampling performed in a third block confirmed a significant aggregative pattern, with patches of 6 to 8 m diameter, together with a significant neighborhood structure of nematode densities, thus identifying the relevant sampling scale to describe the nematode distribution. Nematode patches correlate significantly with those of GFLV-infected grapevine plants. Finally, nematode and virus spread were shown to extend preferentially parallel to vine rows, probably due to tillage during mechanical weeding.
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On factors structuring the flatfish assemblage in the southern North Sea
NASA Astrophysics Data System (ADS)
Piet, G. J.; Pfisterer, A. B.; Rijnsdorp, A. D.
1998-09-01
Ten species of flatfish were studied to see to what extent interspecific competition influences their diet or spatial distribution and whether the potential of these flatfish species to avoid interspecific competition through resource partitioning is constrained by specific morphological characteristics. For this, seven morphological characteristics were measured, diet composition was determined from gut content analyses and overlap in distribution was determined from the co-occurrence in trawl hauls. Canonical correspondence analysis revealed the morphological characteristics that were most strongly correlated with the diet composition. Based on these findings the mouth gape was considered to be the most important morphological constraint affecting the choice of food. Two resource dimensions were distinguished along which interspecific competition can act on the flatfish assemblage: the trophic dimension (diet composition) and the spatial dimension (distribution). Resource partitioning was observed along both dimensions separately and, more importantly, the degree of resource partitioning along the two dimensions was negatively correlated. Especially the latter was considered strong circumstantial evidence that interspecific competition is a major factor structuring the flatfish assemblage. Resource partitioning along the two resource dimensions increased with decreasing mouth gape, suggesting that interspecific competition mainly acts on the small-mouthed fish, i.e. juveniles.
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Modulation of Temporal Precision in Thalamic Population Responses to Natural Visual Stimuli
Desbordes, Gaëlle; Jin, Jianzhong; Alonso, Jose-Manuel; Stanley, Garrett B.
2010-01-01
Natural visual stimuli have highly structured spatial and temporal properties which influence the way visual information is encoded in the visual pathway. In response to natural scene stimuli, neurons in the lateral geniculate nucleus (LGN) are temporally precise – on a time scale of 10–25 ms – both within single cells and across cells within a population. This time scale, established by non stimulus-driven elements of neuronal firing, is significantly shorter than that of natural scenes, yet is critical for the neural representation of the spatial and temporal structure of the scene. Here, a generalized linear model (GLM) that combines stimulus-driven elements with spike-history dependence associated with intrinsic cellular dynamics is shown to predict the fine timing precision of LGN responses to natural scene stimuli, the corresponding correlation structure across nearby neurons in the population, and the continuous modulation of spike timing precision and latency across neurons. A single model captured the experimentally observed neural response, across different levels of contrasts and different classes of visual stimuli, through interactions between the stimulus correlation structure and the nonlinearity in spike generation and spike history dependence. Given the sensitivity of the thalamocortical synapse to closely timed spikes and the importance of fine timing precision for the faithful representation of natural scenes, the modulation of thalamic population timing over these time scales is likely important for cortical representations of the dynamic natural visual environment. PMID:21151356
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Schwegmann, Alexander; Lindemann, Jens P.; Egelhaaf, Martin
2014-01-01
Knowing the depth structure of the environment is crucial for moving animals in many behavioral contexts, such as collision avoidance, targeting objects, or spatial navigation. An important source of depth information is motion parallax. This powerful cue is generated on the eyes during translatory self-motion with the retinal images of nearby objects moving faster than those of distant ones. To investigate how the visual motion pathway represents motion-based depth information we analyzed its responses to image sequences recorded in natural cluttered environments with a wide range of depth structures. The analysis was done on the basis of an experimentally validated model of the visual motion pathway of insects, with its core elements being correlation-type elementary motion detectors (EMDs). It is the key result of our analysis that the absolute EMD responses, i.e., the motion energy profile, represent the contrast-weighted nearness of environmental structures during translatory self-motion at a roughly constant velocity. In other words, the output of the EMD array highlights contours of nearby objects. This conclusion is largely independent of the scale over which EMDs are spatially pooled and was corroborated by scrutinizing the motion energy profile after eliminating the depth structure from the natural image sequences. Hence, the well-established dependence of correlation-type EMDs on both velocity and textural properties of motion stimuli appears to be advantageous for representing behaviorally relevant information about the environment in a computationally parsimonious way. PMID:25136314
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NASA Astrophysics Data System (ADS)
Mazzucchi, Gabriel; Caballero-Benitez, Santiago F.; Mekhov, Igor B.
2016-08-01
Ultracold atomic systems offer a unique tool for understanding behavior of matter in the quantum degenerate regime, promising studies of a vast range of phenomena covering many disciplines from condensed matter to quantum information and particle physics. Coupling these systems to quantized light fields opens further possibilities of observing delicate effects typical of quantum optics in the context of strongly correlated systems. Measurement backaction is one of the most funda- mental manifestations of quantum mechanics and it is at the core of many famous quantum optics experiments. Here we show that quantum backaction of weak measurement can be used for tailoring long-range correlations of ultracold fermions, realizing quantum states with spatial modulations of the density and magnetization, thus overcoming usual requirement for a strong interatomic interactions. We propose detection schemes for implementing antiferromagnetic states and density waves. We demonstrate that such long-range correlations cannot be realized with local addressing, and they are a consequence of the competition between global but spatially structured backaction of weak quantum measurement and unitary dynamics of fermions.
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Hu, Po-Sheng; Wu, Cheng-En; Chen, Guan-Lin
2017-12-21
In this research, the Zn(C₅H₇O₂)₂·xH₂O-based growth of ZnO micro/nanostructures in a low temperature, vapor-trapped chemical vapor deposition system was attempted to optimize structural and optical properties for potential biomedical applications. By trapping in-flow gas molecules and Zinc vapor inside a chamber tube by partially obstructing a chamber outlet, a high pressure condition can be achieved, and this experimental setup has the advantages of ease of synthesis, being a low temperature process, and cost effectiveness. Empirically, the growth process proceeded under a chamber condition of an atmospheric pressure of 730 torr, a controlled volume flow rate of input gas, N₂/O₂, of 500/500 Standard Cubic Centimeters per Minute (SCCM), and a designated oven temperature of 500 °C. Specifically, the dependence of structural and optical properties of the structures on growth duration and spatially dependent temperature were investigated utilizing scanning electron microscopy, X-ray diffraction (XRD), photoluminescence (PL), and ultraviolet-visible transmission spectroscopy. The experimental results indicate that the grown thin film observed with hexagonal structures and higher structural uniformity enables more prominent structural and optical signatures. XRD spectra present the dominant peaks along crystal planes of (002) and (101) as the main direction of crystallization. In addition, while the structures excited with laser wavelength of 325 nm emit a signature radiation around 380 nm, an ultraviolet lamp with a wavelength of 254 nm revealed distinctive photoluminescence peaks at 363.96 nm and 403.52 nm, elucidating different degrees of structural correlation as functions of growth duration and the spatial gradient of temperature. Transmittance spectra of the structures illustrate typical variation in the wavelength range of 200 nm to 400 nm, and its structural correlation is less significant when compared with PL.
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Hu, Po-Sheng; Wu, Cheng-En; Chen, Guan-Lin
2017-01-01
In this research, the Zn(C5H7O2)2·xH2O-based growth of ZnO micro/nanostructures in a low temperature, vapor-trapped chemical vapor deposition system was attempted to optimize structural and optical properties for potential biomedical applications. By trapping in-flow gas molecules and Zinc vapor inside a chamber tube by partially obstructing a chamber outlet, a high pressure condition can be achieved, and this experimental setup has the advantages of ease of synthesis, being a low temperature process, and cost effectiveness. Empirically, the growth process proceeded under a chamber condition of an atmospheric pressure of 730 torr, a controlled volume flow rate of input gas, N2/O2, of 500/500 Standard Cubic Centimeters per Minute (SCCM), and a designated oven temperature of 500 °C. Specifically, the dependence of structural and optical properties of the structures on growth duration and spatially dependent temperature were investigated utilizing scanning electron microscopy, X-ray diffraction (XRD), photoluminescence (PL), and ultraviolet-visible transmission spectroscopy. The experimental results indicate that the grown thin film observed with hexagonal structures and higher structural uniformity enables more prominent structural and optical signatures. XRD spectra present the dominant peaks along crystal planes of (002) and (101) as the main direction of crystallization. In addition, while the structures excited with laser wavelength of 325 nm emit a signature radiation around 380 nm, an ultraviolet lamp with a wavelength of 254 nm revealed distinctive photoluminescence peaks at 363.96 nm and 403.52 nm, elucidating different degrees of structural correlation as functions of growth duration and the spatial gradient of temperature. Transmittance spectra of the structures illustrate typical variation in the wavelength range of 200 nm to 400 nm, and its structural correlation is less significant when compared with PL. PMID:29267196
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NASA Astrophysics Data System (ADS)
Astuti Thamrin, Sri; Taufik, Irfan
2018-03-01
Dengue haemorrhagic fever (DHF) is an infectious disease caused by dengue virus. The increasing number of people with DHF disease correlates with the neighbourhood, for example sub-districts, and the characteristics of the sub-districts are formed from individuals who are domiciled in the sub-districts. Data containing individuals and sub-districts is a hierarchical data structure, called multilevel analysis. Frequently encountered response variable of the data is the time until an event occurs. Multilevel and spatial models are being increasingly used to obtain substantive information on area-level inequalities in DHF survival. Using a case study approach, we report on the implications of using multilevel with spatial survival models to study geographical inequalities in all cause survival.
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Emergent Archetype Hydrological-Biogeochemical Response Patterns in Heterogeneous Catchments
NASA Astrophysics Data System (ADS)
Jawitz, J. W.; Gall, H. E.; Rao, P.
2013-12-01
What can spatiotemporally integrated patterns observed in stream hydrologic and biogeochemical signals generated in response to transient hydro-climatic and anthropogenic forcing tell us about the interactions between spatially heterogeneous soil-mediated hydrological and biogeochemical processes? We seek to understand how the spatial structure of solute sources coupled with hydrologic responses affect observed concentration-discharge (C-Q) patterns. These patterns are expressions of the spatiotemporal structure of solute loads exported from managed catchments, and their likely ecological consequences manifested in receiving water bodies (e.g., wetlands, rivers, lakes, and coastal waters). We investigated the following broad questions: (1) How does the correlation between flow-generating areas and biogeochemical source areas across a catchment evolve under stochastic hydro-climatic forcing? (2) What are the feasible hydrologic and biogeochemical responses that lead to the emergence of the observed archetype C-Q patterns? and; (3) What implications do these coupled dynamics have for catchment monitoring and implementation of management practices? We categorize the observed temporal signals into three archetypical C-Q patterns: dilution; accretion, and constant concentration. We introduce a parsimonious stochastic model of heterogeneous catchments, which act as hydrologic and biogeochemical filters, to examine the relationship between spatial heterogeneity and temporal history of solute export signals. The core concept of the modeling framework is considering the types and degree of spatial correlation between solute source zones and flow generating zones, and activation of different portions of the catchments during rainfall events. Our overarching hypothesis is that each of the archetype C-Q patterns can be generated by explicitly linking landscape-scale hydrologic responses and spatial distributions of solute source properties within a catchment. The model simulations reproduce the three major C-Q patterns observed in published data, offering valuable insight into coupled catchment processes. The findings have important implications for effective catchment management for water quality improvement, and stream monitoring strategies.
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Soil heterogeneity in Mojave Desert shrublands: Biotic and abiotic processes
NASA Astrophysics Data System (ADS)
Caldwell, Todd G.; Young, Michael H.; McDonald, Eric V.; Zhu, Jianting
2012-09-01
Geological and ecological processes play critical roles in the evolution of desert piedmonts. Feedback between fast cyclic biotic and slow cumulative pedogenic processes on arid alluvial fan systems results in a heterogeneous landscape of interspace and canopy microsites. Defining the spatial extent between these processes will allow a better connection to ecosystem service and climate change. We use a soil chronosequence in the Mojave Desert and high spatial resolution infiltrometer measurements along transects radiating from canopies of perennial shrubs to assess the extent of biotic and abiotic processes and the heterogeneity of soil properties in arid shrublands. Results showed higher saturated conductivity under vegetation regardless of surface age, but it was more conspicuous on older, developed soils. At proximal locations to the shrub, bulk density, soil structure grade, silt, and clay content significantly increased radially from the canopy, while sand and organic material decreased. Soil properties at distal locations 2-5 times the canopy radius had no significant spatial correlation. The extent of the biotic influence of the shrub was 1.34 ± 0.32 times the canopy radius. Hydraulic properties were weakly correlated in space, but 75% of the variance could be attributed to sand content, soil structure grade, mean-particle diameter, and soil organic material, none of which are exclusively biotic or abiotic. The fast cyclic biotic processes occurring under vegetation are clearly overprinted on slow cumulative abiotic processes, resulting in the deterministic variability observed at the plant scale.
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Pérez de Rosas, Alicia R; Segura, Elsa L; Fusco, Octavio; Guiñazú, Adolfo L Bareiro; García, Beatriz A
2013-03-01
Fine scale patterns of genetic structure and dispersal in Triatoma infestans populations from Argentina was analysed. A total of 314 insects from 22 domestic and peridomestic sites from the locality of San Martín (Capayán department, Catamarca province) were typed for 10 polymorphic microsatellite loci. The results confirm subdivision of T. infestans populations with restricted dispersal among sampling sites and suggest inbreeding and/or stratification within the different domestic and peridomestic structures. Spatial correlation analysis showed that the scale of structuring is approximately of 400 m, indicating that active dispersal would occur within this distance range. It was detected difference in scale of structuring among sexes, with females dispersing over greater distances than males. This study suggests that insecticide treatment and surveillance should be extended within a radius of 400 m around the infested area, which would help to reduce the probability of reinfestation by covering an area of active dispersal. The inferences made from fine-scale spatial genetic structure analyses of T. infestans populations has demonstrated to be important for community-wide control programs, providing a complementary approach to help improve vector control strategies.
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Single-shot imaging of trapped Fermi gas
NASA Astrophysics Data System (ADS)
Gajda, Mariusz; Mostowski, Jan; Sowiński, Tomasz; Załuska-Kotur, Magdalena
2016-07-01
Recently developed techniques allow for simultaneous measurements of the positions of all ultra-cold atoms in a trap with high resolution. Each such single-shot experiment detects one element of the quantum ensemble formed by the cloud of atoms. Repeated single-shot measurements can be used to determine all correlations between particle positions as opposed to standard measurements that determine particle density or two-particle correlations only. In this paper we discuss the possible outcomes of such single-shot measurements in the case of cloud of ultra-cold noninteracting Fermi atoms. We show that the Pauli exclusion principle alone leads to correlations between particle positions that originate from unexpected spatial structures formed by the atoms.
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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.
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Maillet, David; Rajah, M Natasha
2011-10-28
Age-related declines in memory for context have been linked to volume loss in the hippocampal head (HH) with age. However, it remains unclear how this volumetric decline correlates with age-related changes in whole-brain activity during context encoding, and subsequent context retrieval. In the current study we examine this. We collected functional magnetic resonance imaging data in young and older adults during the encoding of item, spatial context and temporal context. HH volume and subsequent retrieval performance was measured in all participants. In young adults only there was a positive three-way correlation between larger HH volumes, better memory retrieval, and increased activity in right hippocampus, right ventrolateral prefrontal cortex (VLPFC) and midline brain regions during episodic encoding. In contrast, older adults exhibited a positive three-way association between HH volume, generalized activity in bilateral hippocampus and dorsolateral PFC across all encoding tasks, and subsequent spatial context retrieval. Young adults also engaged this network, but only during the most difficult temporal context encoding task and activity in this network correlated with subsequent temporal context retrieval. We conclude that age-related volumetric reductions in HH disrupted the structure-function association between the hippocampus and activity in the first general encoding network recruited by young adults. Instead, older adults recruited those brain regions young adults only engaged for the most difficult temporal task, at lower difficulty levels. This altered pattern of association correlated with spatial context retrieval in older adults, but was not sufficient to maintain context memory abilities overall. Crown Copyright © 2011. Published by Elsevier B.V. All rights reserved.
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DOE R&D Accomplishments Database
Prigogine, I.
1989-10-01
As in the previous period, our work has been concerned with the study of the properties of nonequilibrium systems and especially with the mechanism of self-organization. As is well-known, the study of self-organization began with the investigation of hydrodynamical or chemical instabilities studied from the point of view of macroscopic physics. The main outcome is that nonequilibrium generates spatial correlations of macroscopic physics. The main outcome is that nonequilibrium generated spatial correlations of macroscopic range whose characteristics length is an intrinsic property and whose amplitude is determined by nonequilibrium constraints. A survey of the macroscopic approach to nonequilibrium states is given in the paper. "Nonequilibrium States and Long Range Correlations in Chemical Dynamics", by G. Nicolis at al. However, over the last few years important progress has been made in the simulation of nonequilibrium situations using mainly molecular dynamics. It appears now that processes corresponding to self-organization as well as the appearance of long-range correlations can be obtained in this way starting from a program involving Newtonian dynamics (generally the laws of interaction correspond to hard spheres or hard disks). Examples of such types of studies leading to Benard instabilities, to chemical clocks, or to spatial structure formation are given in this report. As a result, we may now view self-organization as a direct expression of tan appropriate microscopic dynamics. This is the reason why we have devoted much work to the study of large Poincare systems (LPS) involving continuous sets of resonances. These systems have been shown to lead, according to the constraints, either to equilibrium situations or to nonequilibrium states involving long range correlations. We discuss LPS in the frame of classical mechanics.
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Vaughan, Adam S; Kramer, Michael R; Cooper, Hannah L F; Rosenberg, Eli S; Sullivan, Patrick S
2017-02-01
Theory and research on HIV and among men who have sex with men (MSM) have long suggested the importance of non-residential locations in defining structural exposures. Despite this, most studies within these fields define place as a residential context, neglecting the potential influence of non-residential locations on HIV-related outcomes. The concept of activity spaces, defined as a set of locations to which an individual is routinely exposed, represents one theoretical basis for addressing this potential imbalance. Using a one-time online survey to collect demographic, behavioral, and spatial data from MSM, this paper describes activity spaces and examines correlates of this spatial variation. We used latent class analysis to identify categories of activity spaces using spatial data on home, routine, potential sexual risk, and HIV prevention locations. We then assessed individual and area-level covariates for their associations with these categories. Classes were distinguished by the degree of spatial variation in routine and prevention behaviors (which were the same within each class) and in sexual risk behaviors (i.e., sex locations and locations of meeting sex partners). Partner type (e.g. casual or main) represented a key correlate of the activity space. In this early examination of activity spaces in an online sample of MSM, patterns of spatial behavior represent further evidence of significant spatial variation in locations of routine, potential HIV sexual risk, and HIV prevention behaviors among MSM. Although prevention behaviors tend to have similar geographic variation as routine behaviors, locations where men engage in potentially high-risk behaviors may be more spatially focused for some MSM than for others. Copyright © 2016 Elsevier Ltd. All rights reserved.
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Correlation analysis of fracture arrangement in space
NASA Astrophysics Data System (ADS)
Marrett, Randall; Gale, Julia F. W.; Gómez, Leonel A.; Laubach, Stephen E.
2018-03-01
We present new techniques that overcome limitations of standard approaches to documenting spatial arrangement. The new techniques directly quantify spatial arrangement by normalizing to expected values for randomly arranged fractures. The techniques differ in terms of computational intensity, robustness of results, ability to detect anti-correlation, and use of fracture size data. Variation of spatial arrangement across a broad range of length scales facilitates distinguishing clustered and periodic arrangements-opposite forms of organization-from random arrangements. Moreover, self-organized arrangements can be distinguished from arrangements due to extrinsic organization. Traditional techniques for analysis of fracture spacing are hamstrung because they account neither for the sequence of fracture spacings nor for possible coordination between fracture size and position, attributes accounted for by our methods. All of the new techniques reveal fractal clustering in a test case of veins, or cement-filled opening-mode fractures, in Pennsylvanian Marble Falls Limestone. The observed arrangement is readily distinguishable from random and periodic arrangements. Comparison of results that account for fracture size with results that ignore fracture size demonstrates that spatial arrangement is dominated by the sequence of fracture spacings, rather than coordination of fracture size with position. Fracture size and position are not completely independent in this example, however, because large fractures are more clustered than small fractures. Both spatial and size organization of veins here probably emerged from fracture interaction during growth. The new approaches described here, along with freely available software to implement the techniques, can be applied with effect to a wide range of structures, or indeed many other phenomena such as drilling response, where spatial heterogeneity is an issue.
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Teacher spatial skills are linked to differences in geometry instruction.
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.
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Covariance analyses of satellite-derived mesoscale wind fields
NASA Technical Reports Server (NTRS)
Maddox, R. A.; Vonder Haar, T. H.
1979-01-01
Statistical structure functions have been computed independently for nine satellite-derived mesoscale wind fields that were obtained on two different days. Small cumulus clouds were tracked at 5 min intervals, but since these clouds occurred primarily in the warm sectors of midlatitude cyclones the results cannot be considered representative of the circulations within cyclones in general. The field structure varied considerably with time and was especially affected if mesoscale features were observed. The wind fields on the 2 days studied were highly anisotropic with large gradients in structure occurring approximately normal to the mean flow. Structure function calculations for the combined set of satellite winds were used to estimate random error present in the fields. It is concluded for these data that the random error in vector winds derived from cumulus cloud tracking using high-frequency satellite data is less than 1.75 m/s. Spatial correlation functions were also computed for the nine data sets. Normalized correlation functions were considerably different for u and v components and decreased rapidly as data point separation increased for both components. The correlation functions for transverse and longitudinal components decreased less rapidly as data point separation increased.
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Bedrosian, P.A.; Maercklin, N.; Weckmann, U.; Bartov, Y.; Ryberg, T.; Ritter, O.
2007-01-01
Magnetotelluric and seismic methods provide complementary information about the resistivity and velocity structure of the subsurface on similar scales and resolutions. No global relation, however, exists between these parameters, and correlations are often valid for only a limited target area. Independently derived inverse models from these methods can be combined using a classification approach to map geologic structure. The method employed is based solely on the statistical correlation of physical properties in a joint parameter space and is independent of theoretical or empirical relations linking electrical and seismic parameters. Regions of high correlation (classes) between resistivity and velocity can in turn be mapped back and re-examined in depth section. The spatial distribution of these classes, and the boundaries between them, provide structural information not evident in the individual models. This method is applied to a 10 km long profile crossing the Dead Sea Transform in Jordan. Several prominent classes are identified with specific lithologies in accordance with local geology. An abrupt change in lithology across the fault, together with vertical uplift of the basement suggest the fault is sub-vertical within the upper crust. ?? 2007 The Authors Journal compilation ?? 2007 RAS.
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Rapid divergence of mussel populations despite incomplete barriers to dispersal.
Maas, Diede L; Prost, Stefan; Bi, Ke; Smith, Lydia L; Armstrong, Ellie E; Aji, Ludi P; Toha, Abdul Hamid A; Gillespie, Rosemary G; Becking, Leontine E
2018-04-01
Striking genetic structure among marine populations at small spatial scales is becoming evident with extensive molecular studies. Such observations suggest isolation at small scales may play an important role in forming patterns of genetic diversity within species. Isolation-by-distance, isolation-by-environment and historical priority effects are umbrella terms for a suite of processes that underlie genetic structure, but their relative importance at different spatial and temporal scales remains elusive. Here, we use marine lakes in Indonesia to assess genetic structure and assess the relative roles of the processes in shaping genetic differentiation in populations of a bivalve mussel (Brachidontes sp.). Marine lakes are landlocked waterbodies of similar age (6,000-10,000 years), but with heterogeneous environments and varying degrees of connection to the sea. Using a population genomic approach (double-digest restriction-site-associated DNA sequencing), we show strong genetic structuring across populations (range F ST : 0.07-0.24) and find limited gene flow through admixture plots. At large spatial scales (>1,400 km), a clear isolation-by-distance pattern was detected. At smaller spatial scales (<200 km), this pattern is maintained, but accompanied by an association of genetic divergence with degree of connection. We hypothesize that (incomplete) dispersal barriers can cause initial isolation, allowing priority effects to give the numerical advantage necessary to initiate strong genetic structure. Priority effects may be strengthened by local adaptation, which the data may corroborate by showing a high correlation between mussel genotypes and temperature. Our study indicates an often-neglected role of (evolution-mediated) priority effects in shaping population divergence. © 2018 The Authors. Molecular Ecology published by John Wiley & Sons Ltd.
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Kandala, Sridhar; Nolan, Dan; Laumann, Timothy O.; Power, Jonathan D.; Adeyemo, Babatunde; Harms, Michael P.; Petersen, Steven E.; Barch, Deanna M.
2016-01-01
Abstract Like all resting-state functional connectivity data, the data from the Human Connectome Project (HCP) are adversely affected by structured noise artifacts arising from head motion and physiological processes. Functional connectivity estimates (Pearson's correlation coefficients) were inflated for high-motion time points and for high-motion participants. This inflation occurred across the brain, suggesting the presence of globally distributed artifacts. The degree of inflation was further increased for connections between nearby regions compared with distant regions, suggesting the presence of distance-dependent spatially specific artifacts. We evaluated several denoising methods: censoring high-motion time points, motion regression, the FMRIB independent component analysis-based X-noiseifier (FIX), and mean grayordinate time series regression (MGTR; as a proxy for global signal regression). The results suggest that FIX denoising reduced both types of artifacts, but left substantial global artifacts behind. MGTR significantly reduced global artifacts, but left substantial spatially specific artifacts behind. Censoring high-motion time points resulted in a small reduction of distance-dependent and global artifacts, eliminating neither type. All denoising strategies left differences between high- and low-motion participants, but only MGTR substantially reduced those differences. Ultimately, functional connectivity estimates from HCP data showed spatially specific and globally distributed artifacts, and the most effective approach to address both types of motion-correlated artifacts was a combination of FIX and MGTR. PMID:27571276
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Improving the Quality of Low-Cost GPS Receiver Data for Monitoring Using Spatial Correlations
NASA Astrophysics Data System (ADS)
Zhang, Li; Schwieger, Volker
2016-06-01
The investigations on low-cost single frequency GPS receivers at the Institute of Engineering Geodesy (IIGS) show that u-blox LEA-6T GPS receivers combined with Trimble Bullet III GPS antennas containing self-constructed L1-optimized choke rings can already obtain an accuracy in the range of millimeters which meets the requirements of geodetic precise monitoring applications (see [
27 ]). However, the quality (accuracy and reliability) of low-cost GPS receiver data, particularly in shadowing environment, should still be improved, since the multipath effects are the major error for the short baselines. For this purpose, several adjoined stations with low-cost GPS receivers and antennas were set up next to the metal wall on the roof of the IIGS building and measured statically for several days. The time series of three-dimensional coordinates of the GPS receivers were analyzed. Spatial correlations between the adjoined stations, possibly caused by multipath effect, will be taken into account. The coordinates of one station can be corrected using the spatial correlations of the adjoined stations, so that the quality of the GPS measurements is improved. The developed algorithms are based on the coordinates and the results will be delivered in near-real-time (in about 30 minutes), so that they are suitable for structural health monitoring applications. -
Sivley, R Michael; Sheehan, Jonathan H; Kropski, Jonathan A; Cogan, Joy; Blackwell, Timothy S; Phillips, John A; Bush, William S; Meiler, Jens; Capra, John A
2018-01-23
Next-generation sequencing of individuals with genetic diseases often detects candidate rare variants in numerous genes, but determining which are causal remains challenging. We hypothesized that the spatial distribution of missense variants in protein structures contains information about function and pathogenicity that can help prioritize variants of unknown significance (VUS) and elucidate the structural mechanisms leading to disease. To illustrate this approach in a clinical application, we analyzed 13 candidate missense variants in regulator of telomere elongation helicase 1 (RTEL1) identified in patients with Familial Interstitial Pneumonia (FIP). We curated pathogenic and neutral RTEL1 variants from the literature and public databases. We then used homology modeling to construct a 3D structural model of RTEL1 and mapped known variants into this structure. We next developed a pathogenicity prediction algorithm based on proximity to known disease causing and neutral variants and evaluated its performance with leave-one-out cross-validation. We further validated our predictions with segregation analyses, telomere lengths, and mutagenesis data from the homologous XPD protein. Our algorithm for classifying RTEL1 VUS based on spatial proximity to pathogenic and neutral variation accurately distinguished 7 known pathogenic from 29 neutral variants (ROC AUC = 0.85) in the N-terminal domains of RTEL1. Pathogenic proximity scores were also significantly correlated with effects on ATPase activity (Pearson r = -0.65, p = 0.0004) in XPD, a related helicase. Applying the algorithm to 13 VUS identified from sequencing of RTEL1 from patients predicted five out of six disease-segregating VUS to be pathogenic. We provide structural hypotheses regarding how these mutations may disrupt RTEL1 ATPase and helicase function. Spatial analysis of missense variation accurately classified candidate VUS in RTEL1 and suggests how such variants cause disease. Incorporating spatial proximity analyses into other pathogenicity prediction tools may improve accuracy for other genes and genetic diseases.
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The Influence of Mexican Hat Recurrent Connectivity on Noise Correlations and Stimulus Encoding
Meyer, Robert; Ladenbauer, Josef; Obermayer, Klaus
2017-01-01
Noise correlations are a common feature of neural responses and have been observed in many cortical areas across different species. These correlations can influence information processing by enhancing or diminishing the quality of the neural code, but the origin of these correlations is still a matter of controversy. In this computational study we explore the hypothesis that noise correlations are the result of local recurrent excitatory and inhibitory connections. We simulated two-dimensional networks of adaptive spiking neurons with local connection patterns following Gaussian kernels. Noise correlations decay with distance between neurons but are only observed if the range of excitatory connections is smaller than the range of inhibitory connections (“Mexican hat” connectivity) and if the connection strengths are sufficiently strong. These correlations arise from a moving blob-like structure of evoked activity, which is absent if inhibitory interactions have a smaller range (“inverse Mexican hat” connectivity). Spatially structured external inputs fixate these blobs to certain locations and thus effectively reduce noise correlations. We further investigated the influence of these network configurations on stimulus encoding. On the one hand, the observed correlations diminish information about a stimulus encoded by a network. On the other hand, correlated activity allows for more precise encoding of stimulus information if the decoder has only access to a limited amount of neurons. PMID:28539881
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[Spatial point patterns of Antarctic krill fishery in the northern Antarctic Peninsula].
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.
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Huang, Qi; Lv, Xin; He, Yushuang; Wei, Xing; Ma, Meigang; Liao, Yuhan; Qin, Chao; Wu, Yuan
2017-12-01
Patients with epilepsy (PWE) are more likely to suffer from migraine attack, and aberrant white matter (WM) organization may be the mechanism underlying this phenomenon. This study aimed to use diffusion tensor imaging (DTI) technique to quantify WM structural differences in PWE with interictal migraine. Diffusion tensor imaging data were acquired in 13 PWE with migraine and 12 PWE without migraine. Diffusion metrics were analyzed using tract-atlas-based spatial statistics analysis. Atlas-based and tract-based spatial statistical analyses were conducted for robustness analysis. Correlation was explored between altered DTI metrics and clinical parameters. The main results are as follows: (i) Axonal damage plays a key role in PWE with interictal migraine. (ii) Significant diffusing alterations included higher fractional anisotropy (FA) in the fornix, higher mean diffusivity (MD) in the middle cerebellar peduncle (CP), left superior CP, and right uncinate fasciculus, and higher axial diffusivity (AD) in the middle CP and right medial lemniscus. (iii) Diffusion tensor imaging metrics has the tendency of correlation with seizure/migraine type and duration. Results indicate that characteristic structural impairments exist in PWE with interictal migraine. Epilepsy may contribute to migraine by altering WMs in the brain stem. White matter tracts in the fornix and right uncinate fasciculus also mediate migraine after epilepsy. This finding may improve our understanding of the pathological mechanisms underlying migraine attack after epilepsy. Copyright © 2017 Elsevier Inc. All rights reserved.
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NASA Astrophysics Data System (ADS)
George, Michael G.; Wang, Jian; Banerjee, Rupak; Bazylak, Aimy
2016-03-01
The novel application of scanning transmission X-ray microscopy (STXM) to the microporous layer (MPL) of a polymer electrolyte membrane fuel cell is investigated. A spatially resolved chemical component distribution map is obtained for the MPL of a commercially available SGL 25 BC sample. This is achieved with near edge X-ray absorption fine structure spectroscopic analysis. Prior to analysis the sample is embedded in non-reactive epoxy and ultra-microtomed to a thickness of 100 nm. Polytetrafluoroethylene (PTFE), carbon particle agglomerates, and supporting epoxy resin distributions are identified and reconstructed for a scanning area of 6 μm × 6 μm. It is observed that the spatial distribution of PTFE is strongly correlated to the carbon particle agglomerations. Additionally, agglomerate structures of PTFE are identified, possibly indicating the presence of a unique mesostructure in the MPL. STXM analysis is presented as a useful technique for the investigation of chemical species distributions in the MPL.
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Pissard, Audrey; Arbizu, Carlos; Ghislain, Marc; Faux, Anne-Michèle; Paulet, Sébastien; Bertin, Pierre
2008-01-01
Oxalis tuberosa is an important crop cultivated in the highest Andean zones. A germplasm collection is maintained ex situ by CIP, which has developed a morphological markers system to classify the accessions into morphotypes, i.e. groups of morphologically identical accessions. However, their genetic uniformity is currently unknown. The ISSR technique was used in two experiments to determine the relationships between both morphological and molecular markers systems. The intra-morphotype genetic diversity, the spatial structures of the diversity and the congruence between both markers systems were determined. In the first experience, 44 accessions representing five morphotypes, clearly distinct from each other, were analyzed. At the molecular level, the accessions exactly clustered according to their morphotypes. However, a genetic variability was observed inside each morphotype. In the second experiment, 34 accessions gradually differing from each other on morphological base were analyzed. The morphological clustering showed no geographical structure. On the opposite, the molecular analysis showed that the genetic structure was slightly related to the collection site. The correlation between both markers systems was weak but significant. The lack of perfect congruence between morphological and molecular data suggests that the morphological system may be useful for the morphotypes management but is not appropriate to study the genetic structure of the oca. The spatial structure of the genetic diversity can be related to the evolution of the species and the discordance between the morphological and molecular structures may result from similar selection pressures at different places leading to similar forms with a different genetic background.
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Payn, R.A.; Gooseff, M.N.; McGlynn, B.L.; Bencala, K.E.; Wondzell, S.M.
2012-01-01
Relating watershed structure to streamflow generation is a primary focus of hydrology. However, comparisons of longitudinal variability in stream discharge with adjacent valley structure have been rare, resulting in poor understanding of the distribution of the hydrologic mechanisms that cause variability in streamflow generation along valleys. This study explores detailed surveys of stream base flow across a gauged, 23 km2 mountain watershed. Research objectives were (1) to relate spatial variability in base flow to fundamental elements of watershed structure, primarily topographic contributing area, and (2) to assess temporal changes in the spatial patterns of those relationships during a seasonal base flow recession. We analyzed spatiotemporal variability in base flow using (1) summer hydrographs at the study watershed outlet and 5 subwatershed outlets and (2) longitudinal series of discharge measurements every ~100 m along the streams of the 3 largest subwatersheds (1200 to 2600 m in valley length), repeated 2 to 3 times during base flow recession. Reaches within valley segments of 300 to 1200 m in length tended to demonstrate similar streamflow generation characteristics. Locations of transitions between these segments were consistent throughout the recession, and tended to be collocated with abrupt longitudinal transitions in valley slope or hillslope-riparian characteristics. Both within and among subwatersheds, correlation between the spatial distributions of streamflow and topographic contributing area decreased during the recession, suggesting a general decrease in the influence of topography on stream base flow contributions. As topographic controls on base flow evidently decreased, multiple aspects of subsurface structure were likely to have gained influence.
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Regional and local species richness in an insular environment: Serpentine plants in California
Harrison, S.; Safford, H.D.; Grace, J.B.; Viers, J.H.; Davies, K.F.
2006-01-01
We asked how the richness of the specialized (endemic) flora of serpentine rock outcrops in California varies at both the regional and local scales. Our study had two goals: first, to test whether endemic richness is affected by spatial habitat structure (e.g., regional serpentine area, local serpentine outcrop area, regional and local measures of outcrop isolation), and second, to conduct this test in the context of a broader assessment of environmental influences (e.g., climate, soils, vegetation, disturbance) and historical influences (e.g., geologic age, geographic province) on local and regional species richness. We measured endemic and total richness and environmental variables in 109 serpentine sites (1000-m2 paired plots) in 78 serpentine-containing regions of the state. We used structural equation modeling (SEM) to simultaneously relate regional richness to regionalscale predictors, and local richness to both local-scale and regional-scale predictors. Our model for serpentine endemics explained 66% of the variation in local endemic richness based on local environment (vegetation, soils, rock cover) and on regional endemic richness. It explained 73% of the variation in regional endemic richness based on regional environment (climate and productivity), historical factors (geologic age and geographic province), and spatial structure (regional total area of serpentine, the only significant spatial variable in our analysis). We did not find a strong influence of spatial structure on species richness. However, we were able to distinguish local vs. regional influences on species richness to a novel extent, despite the existence of correlations between local and regional conditions. ?? 2006 by the Ecological Society of America.
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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.
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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.
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Thermal behaviour of nanofluids confined in nanochannels
DOE Office of Scientific and Technical Information (OSTI.GOV)
Frank, Michael, E-mail: d.drikakis@cranfield.ac.uk; Drikakis, Dimitris, E-mail: d.drikakis@cranfield.ac.uk; Asproulis, Nikolaos, E-mail: d.drikakis@cranfield.ac.uk
2015-02-17
This work investigates the effect of spatial restriction on the thermal properties of nanofluids. Using Molecular Dynamics simulations, a Copper-Argon nanofluid is restricted within idealized walls. The thermal conductivity of the suspension is calculated using the Green-Kubo relations and is correlated with the volume fraction of the copper particles within the system as well as the channel width. The thermal conductivity is further broken down into its individual components in the three dimensions, revealing anisotropy between the directions parallel and normal to the channel walls. The observed thermodynamic patterns are justified by considering how the spatial restriction affects the liquidmore » structure around the nanoparticle.« less
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Yang, Xiao-Ying; Luo, Xing-Zhang; Zheng, Zheng; Fang, Shu-Bo
2012-09-01
Two high-density snap-shot samplings were conducted along the Yincungang canal, one important tributary of the Lake Tai, in April (low flow period) and June (high flow period) of 2010. Geostatistical analysis based on the river network distance was used to analyze the spatial and temporal patterns of the pollutant concentrations along the canal with an emphasis on chemical oxygen demand (COD) and total nitrogen (TN). Study results have indicated: (1) COD and TN concentrations display distinctly different spatial and temporal patterns between the low and high flow periods. COD concentration in June is lower than that in April, while TN concentration has the contrary trend. (2) COD load is relatively constant during the period between the two monitoring periods. The spatial correlation structure of COD is exponential for both April and June, and the change of COD concentration is mainly influenced by hydrological conditions. (3) Nitrogen load from agriculture increased significantly during the period between the two monitoring periods. Large amount of chaotic fertilizing by individual farmers has led to the loss of the spatial correlation among the observed TN concentrations. Hence, changes of TN concentration in June are under the dual influence of agricultural fertilizing and hydrological conditions. In the view of the complex hydrological conditions and serious water pollution in the Lake Taihu region, geostatistical analysis is potentially a useful tool for studying the characteristics of pollutant distribution and making predictions in the region.
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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.
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Material Structure of a Graded Refractive Index Lens in Decapod Squid
NASA Astrophysics Data System (ADS)
Cai, Jing; Heiney, Paul; Sweeney, Alison
2013-03-01
Underwater vision with a camera-type eye that is simultaneously acute and sensitive requires a spherical lens with a graded distribution of refractive index. Squids have this type of lens, and our previous work has shown that its optical properties are likely achieved with radially variable densities of a single protein with multiple isoforms. Here we measure the spatial organization of this novel protein material in concentric layers of the lens and use these data to suggest possible mechanisms of self-assembly of the proteins into a graded refractive index structure. First, we performed small angle x-ray scattering (SAXS) to study how the protein is spatially organized. Then, molecular dynamic simulation allowed us to correlate structure to the possible dynamics of the system in different regions of the lens. The combination of simulation and SAXS data in this system revealed the likely protein-protein interactions, resulting material structure and its relationship to the observed and variable optical properties of this graded index system. We believe insights into the material properties of the squid lens system will inform the invention of self-assembling graded index devices.
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Population coding in sparsely connected networks of noisy neurons.
Tripp, Bryan P; Orchard, Jeff
2012-01-01
This study examines the relationship between population coding and spatial connection statistics in networks of noisy neurons. Encoding of sensory information in the neocortex is thought to require coordinated neural populations, because individual cortical neurons respond to a wide range of stimuli, and exhibit highly variable spiking in response to repeated stimuli. Population coding is rooted in network structure, because cortical neurons receive information only from other neurons, and because the information they encode must be decoded by other neurons, if it is to affect behavior. However, population coding theory has often ignored network structure, or assumed discrete, fully connected populations (in contrast with the sparsely connected, continuous sheet of the cortex). In this study, we modeled a sheet of cortical neurons with sparse, primarily local connections, and found that a network with this structure could encode multiple internal state variables with high signal-to-noise ratio. However, we were unable to create high-fidelity networks by instantiating connections at random according to spatial connection probabilities. In our models, high-fidelity networks required additional structure, with higher cluster factors and correlations between the inputs to nearby neurons.
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Study of phase clustering method for analyzing large volumes of meteorological observation data
NASA Astrophysics Data System (ADS)
Volkov, Yu. V.; Krutikov, V. A.; Botygin, I. A.; Sherstnev, V. S.; Sherstneva, A. I.
2017-11-01
The article describes an iterative parallel phase grouping algorithm for temperature field classification. The algorithm is based on modified method of structure forming by using analytic signal. The developed method allows to solve tasks of climate classification as well as climatic zoning for any time or spatial scale. When used to surface temperature measurement series, the developed algorithm allows to find climatic structures with correlated changes of temperature field, to make conclusion on climate uniformity in a given area and to overview climate changes over time by analyzing offset in type groups. The information on climate type groups specific for selected geographical areas is expanded by genetic scheme of class distribution depending on change in mutual correlation level between ground temperature monthly average.
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Ceschin, Rafael; Lee, Vince K; Schmithorst, Vince; Panigrahy, Ashok
2015-01-01
Preterm born children with spastic diplegia type of cerebral palsy and white matter injury or periventricular leukomalacia (PVL), are known to have motor, visual and cognitive impairments. Most diffusion tensor imaging (DTI) studies performed in this group have demonstrated widespread abnormalities using averaged deterministic tractography and voxel-based DTI measurements. Little is known about structural network correlates of white matter topography and reorganization in preterm cerebral palsy, despite the availability of new therapies and the need for brain imaging biomarkers. Here, we combined novel post-processing methodology of probabilistic tractography data in this preterm cohort to improve spatial and regional delineation of longitudinal cortical association tract abnormalities using an along-tract approach, and compared these data to structural DTI cortical network topology analysis. DTI images were acquired on 16 preterm children with cerebral palsy (mean age 5.6 ± 4) and 75 healthy controls (mean age 5.7 ± 3.4). Despite mean tract analysis, Tract-Based Spatial Statistics (TBSS) and voxel-based morphometry (VBM) demonstrating diffusely reduced fractional anisotropy (FA) reduction in all white matter tracts, the along-tract analysis improved the detection of regional tract vulnerability. The along-tract map-structural network topology correlates revealed two associations: (1) reduced regional posterior-anterior gradient in FA of the longitudinal visual cortical association tracts (inferior fronto-occipital fasciculus, inferior longitudinal fasciculus, optic radiation, posterior thalamic radiation) correlated with reduced posterior-anterior gradient of intra-regional (nodal efficiency) metrics with relative sparing of frontal and temporal regions; and (2) reduced regional FA within frontal-thalamic-striatal white matter pathways (anterior limb/anterior thalamic radiation, superior longitudinal fasciculus and cortical spinal tract) correlated with alteration in eigenvector centrality, clustering coefficient (inter-regional) and participation co-efficient (inter-modular) alterations of frontal-striatal and fronto-limbic nodes suggesting re-organization of these pathways. Both along tract and structural topology network measurements correlated strongly with motor and visual clinical outcome scores. This study shows the value of combining along-tract analysis and structural network topology in depicting not only selective parietal occipital regional vulnerability but also reorganization of frontal-striatal and frontal-limbic pathways in preterm children with cerebral palsy. These finding also support the concept that widespread, but selective posterior-anterior neural network connectivity alterations in preterm children with cerebral palsy likely contribute to the pathogenesis of neurosensory and cognitive impairment in this group.
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Photon Entanglement Through Brain Tissue
Shi, Lingyan; Galvez, Enrique J.; Alfano, Robert R.
2016-01-01
Photon entanglement, the cornerstone of quantum correlations, provides a level of coherence that is not present in classical correlations. Harnessing it by study of its passage through organic matter may offer new possibilities for medical diagnosis technique. In this work, we study the preservation of photon entanglement in polarization, created by spontaneous parametric down-conversion, after one entangled photon propagates through multiphoton-scattering brain tissue slices with different thickness. The Tangle-Entropy (TS) plots show the strong preservation of entanglement of photons propagating in brain tissue. By spatially filtering the ballistic scattering of an entangled photon, we find that its polarization entanglement is preserved and non-locally correlated with its twin in the TS plots. The degree of entanglement correlates better with structure and water content than with sample thickness. PMID:27995952
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Origins of collectivity in small systems
NASA Astrophysics Data System (ADS)
Schenke, Björn
2017-11-01
We review recent developments in the theoretical description and understanding of multi-particle correlation measurements in collisions of small projectiles (p/d/3He) with heavy nuclei (Au, Pb) as well as proton+proton collisions. We focus on whether the physical processes responsible for the observed long range rapidity correlations and their azimuthal structure are the same in small systems as in heavy ion collisions. In the latter they are interpreted as generated by the initial spatial geometry being transformed into momentum correlations by strong final state interactions. However, explicit calculations show that also initial state momentum correlations are present and could contribute to observables in small systems. If strong final state interactions are present in small systems, recent developments show that results are sensitive to the shape of the proton and its fluctuations.
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Liu, Yang; Lv, Jianshu; Zhang, Bing; Bi, Jun
2013-04-15
Identifying the sources of spatial variability and deficiency risk of soil nutrients is a crucial issue for soil and agriculture management. A total of 1247 topsoil samples (0-20 cm) were collected at the nodes of a 2×2 km grid in Rizhao City and the contents of soil organic carbon (OC), total nitrogen (TN), and total phosphorus (TP) were determined. Factorial kriging analysis (FKA), stepwise multiple regression, and indicator kriging (IK) were appled to investigate the scale dependent correlations among soil nutrients, identify the sources of spatial variability at each spatial scale, and delineate the potential risk of soil nutrient deficiency. Linear model of co-regionalization (LMC) fitting indicated that the presence of multi-scale variation was comprised of nugget effect, an exponential structure with a range of 12 km (local scale), and a spherical structure with a range of 84 km (regional scale). The short-range variation of OC and TN was mainly dominated by land use types, and TP was controlled by terrain. At long-range scale, spatial variation of OC, TN, and TP was dominated by parent material. Indicator kriging maps depicted the probability of soil nutrient deficiency compared with the background values in eastern Shandong province. The high deficiency risk area of all nutrient integration was mainly located in eastern and northwestern parts. Copyright © 2013 Elsevier B.V. All rights reserved.
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Bourceret, Amélia; Leyval, Corinne; de Fouquet, Chantal; Cébron, Aurélie
2015-01-01
Rhizoremediation uses root development and exudation to favor microbial activity. Thus it can enhance polycyclic aromatic hydrocarbon (PAH) biodegradation in contaminated soils. Spatial heterogeneity of rhizosphere processes, mainly linked to the root development stage and to the plant species, could explain the contrasted rhizoremediation efficiency levels reported in the literature. Aim of the present study was to test if spatial variability in the whole plant rhizosphere, explored at the centimetre-scale, would influence the abundance of microorganisms (bacteria and fungi), and the abundance and activity of PAH-degrading bacteria, leading to spatial variability in PAH concentrations. Two contrasted rhizospheres were compared after 37 days of alfalfa or ryegrass growth in independent rhizotron devices. Almost all spiked PAHs were degraded, and the density of the PAH-degrading bacterial populations increased in both rhizospheres during the incubation period. Mapping of multiparametric data through geostatistical estimation (kriging) revealed that although root biomass was spatially structured, PAH distribution was not. However a greater variability of the PAH content was observed in the rhizosphere of alfalfa. Yet, in the ryegrass-planted rhizotron, the Gram-positive PAH-degraders followed a reverse depth gradient to root biomass, but were positively correlated to the soil pH and carbohydrate concentrations. The two rhizospheres structured the microbial community differently: a fungus-to-bacterium depth gradient similar to the root biomass gradient only formed in the alfalfa rhizotron. PMID:26599438
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Banerjee, Samiran; Kennedy, Nabla; Richardson, Alan E; Egger, Keith N; Siciliano, Steven D
2016-06-01
Archaea are ubiquitous and highly abundant in Arctic soils. Because of their oligotrophic nature, archaea play an important role in biogeochemical processes in nutrient-limited Arctic soils. With the existing knowledge of high archaeal abundance and functional potential in Arctic soils, this study employed terminal restriction fragment length polymorphism (t-RFLP) profiling and geostatistical analysis to explore spatial dependency and edaphic determinants of the overall archaeal (ARC) and ammonia-oxidizing archaeal (AOA) communities in a high Arctic polar oasis soil. ARC communities were spatially dependent at the 2-5 m scale (P < 0.05), whereas AOA communities were dependent at the ∼1 m scale (P < 0.0001). Soil moisture, pH, and total carbon content were key edaphic factors driving both the ARC and AOA community structure. However, AOA evenness had simultaneous correlations with dissolved organic nitrogen and mineral nitrogen, indicating a possible niche differentiation for AOA in which dry mineral and wet organic soil microsites support different AOA genotypes. Richness, evenness, and diversity indices of both ARC and AOA communities showed high spatial dependency along the landscape and resembled scaling of edaphic factors. The spatial link between archaeal community structure and soil resources found in this study has implications for predictive understanding of archaea-driven processes in polar oases.
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Understanding the brain through its spatial structure
NASA Astrophysics Data System (ADS)
Morrison, Will Zachary
The spatial location of cells in neural tissue can be easily extracted from many imaging modalities, but the information contained in spatial relationships between cells is seldom utilized. This is because of a lack of recognition of the importance of spatial relationships to some aspects of brain function, and the reflection in spatial statistics of other types of information. The mathematical tools necessary to describe spatial relationships are also unknown to many neuroscientists, and biologists in general. We analyze two cases, and show that spatial relationships can be used to understand the role of a particular type of cell, the astrocyte, in Alzheimer's disease, and that the geometry of axons in the brain's white matter sheds light on the process of establishing connectivity between areas of the brain. Astrocytes provide nutrients for neuronal metabolism, and regulate the chemical environment of the brain, activities that require manipulation of spatial distributions (of neurotransmitters, for example). We first show, through the use of a correlation function, that inter-astrocyte forces determine the size of independent regulatory domains in the cortex. By examining the spatial distribution of astrocytes in a mouse model of Alzheimer's Disease, we determine that astrocytes are not actively transported to fight the disease, as was previously thought. The paths axons take through the white matter determine which parts of the brain are connected, and how quickly signals are transmitted. The rules that determine these paths (i.e. shortest distance) are currently unknown. By measurement of axon orientation distributions using three-point correlation functions and the statistics of axon turning and branching, we reveal that axons are restricted to growth in three directions, like a taxicab traversing city blocks, albeit in three-dimensions. We show how geometric restrictions at the small scale are related to large-scale trajectories. Finally we discuss the implications of this finding for experimental and theoretical connectomics.
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Capturing spatial heterogeneity of soil organic carbon under changing climate
NASA Astrophysics Data System (ADS)
Mishra, U.; Fan, Z.; Jastrow, J. D.; Matamala, R.; Vitharana, U.
2015-12-01
The spatial heterogeneity of the land surface affects water, energy, and greenhouse gas exchanges with the atmosphere. Designing observation networks that capture land surface spatial heterogeneity is a critical scientific challenge. Here, we present a geospatial approach to capture the existing spatial heterogeneity of soil organic carbon (SOC) stocks across Alaska, USA. We used the standard deviation of 556 georeferenced SOC profiles previously compiled in Mishra and Riley (2015, Biogeosciences, 12:3993-4004) to calculate the number of observations that would be needed to reliably estimate Alaskan SOC stocks. This analysis indicated that 906 randomly distributed observation sites would be needed to quantify the mean value of SOC stocks across Alaska at a confidence interval of ± 5 kg m-2. We then used soil-forming factors (climate, topography, land cover types, surficial geology) to identify the locations of appropriately distributed observation sites by using the conditioned Latin hypercube sampling approach. Spatial correlation and variogram analyses demonstrated that the spatial structures of soil-forming factors were adequately represented by these 906 sites. Using the spatial correlation length of existing SOC observations, we identified 484 new observation sites would be needed to provide the best estimate of the present status of SOC stocks in Alaska. We then used average decadal projections (2020-2099) of precipitation, temperature, and length of growing season for three representative concentration pathway (RCP 4.5, 6.0, and 8.5) scenarios of the Intergovernmental Panel on Climate Change to investigate whether the location of identified observation sites will shift/change under future climate. Our results showed 12-41 additional observation sites (depending on emission scenarios) will be required to capture the impact of projected climatic conditions by 2100 on the spatial heterogeneity of Alaskan SOC stocks. Our results represent an ideal distribution of observation sites across Alaska that captures the land surface spatial heterogeneity and can be used in efforts to quantify SOC stocks, monitor greenhouse gas emissions, and benchmark Earth System Model results.
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NASA Astrophysics Data System (ADS)
Moore, J. K.
2016-02-01
The efficiency of the biological pump is influenced by complex interactions between chemical, biological, and physical processes. The efficiency of export out of surface waters and down through the water column to the deep ocean has been linked to a number of factors including biota community composition, production of mineral ballast components, physical aggregation and disaggregation processes, and ocean oxygen concentrations. I will examine spatial patterns in the export ratio and the efficiency of the biological pump at the global scale using the Community Earth System Model (CESM). There are strong spatial variations in the export efficiency as simulated by the CESM, which are strongly correlated with new nutrient inputs to the euphotic zone and their impacts on phytoplankton community structure. I will compare CESM simulations that include dynamic, variable export ratios driven by the phytoplankton community structure, with simulations that impose a near-constant export ratio to examine the effects of export efficiency on nutrient and surface chlorophyll distributions. The model predicted export ratios will also be compared with recent satellite-based estimates.
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Muñoz–Negrete, Francisco J.; Oblanca, Noelia; Rebolleda, Gema
2018-01-01
Purpose To study the structure-function relationship in glaucoma and healthy patients assessed with Spectralis OCT and Humphrey perimetry using new statistical approaches. Materials and Methods Eighty-five eyes were prospectively selected and divided into 2 groups: glaucoma (44) and healthy patients (41). Three different statistical approaches were carried out: (1) factor analysis of the threshold sensitivities (dB) (automated perimetry) and the macular thickness (μm) (Spectralis OCT), subsequently applying Pearson's correlation to the obtained regions, (2) nonparametric regression analysis relating the values in each pair of regions that showed significant correlation, and (3) nonparametric spatial regressions using three models designed for the purpose of this study. Results In the glaucoma group, a map that relates structural and functional damage was drawn. The strongest correlation with visual fields was observed in the peripheral nasal region of both superior and inferior hemigrids (r = 0.602 and r = 0.458, resp.). The estimated functions obtained with the nonparametric regressions provided the mean sensitivity that corresponds to each given macular thickness. These functions allowed for accurate characterization of the structure-function relationship. Conclusions Both maps and point-to-point functions obtained linking structure and function damage contribute to a better understanding of this relationship and may help in the future to improve glaucoma diagnosis. PMID:29850196
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NASA Astrophysics Data System (ADS)
Bettinardi, R. G.; Deco, G.; Karlaftis, V. M.; Van Hartevelt, T. J.; Fernandes, H. M.; Kourtzi, Z.; Kringelbach, M. L.; Zamora-López, G.
2017-04-01
Intrinsic brain activity is characterized by highly organized co-activations between different regions, forming clustered spatial patterns referred to as resting-state networks. The observed co-activation patterns are sustained by the intricate fabric of millions of interconnected neurons constituting the brain's wiring diagram. However, as for other real networks, the relationship between the connectional structure and the emergent collective dynamics still evades complete understanding. Here, we show that it is possible to estimate the expected pair-wise correlations that a network tends to generate thanks to the underlying path structure. We start from the assumption that in order for two nodes to exhibit correlated activity, they must be exposed to similar input patterns from the entire network. We then acknowledge that information rarely spreads only along a unique route but rather travels along all possible paths. In real networks, the strength of local perturbations tends to decay as they propagate away from the sources, leading to a progressive attenuation of the original information content and, thus, of their influence. Accordingly, we define a novel graph measure, topological similarity, which quantifies the propensity of two nodes to dynamically correlate as a function of the resemblance of the overall influences they are expected to receive due to the underlying structure of the network. Applied to the human brain, we find that the similarity of whole-network inputs, estimated from the topology of the anatomical connectome, plays an important role in sculpting the backbone pattern of time-average correlations observed at rest.
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Vasconcelos, Luciano de Gois; Jackowski, Andrea Parolin; Oliveira, Maira Okada de; Flor, Yoná Mayara Ribeiro; Bueno, Orlando Francisco Amodeo; Brucki, Sonia Maria Dozzi
2011-01-01
The role of structural brain changes and their correlations with neuropsychiatric symptoms and disability in Alzheimer's disease are still poorly understood. To establish whether structural changes in grey matter volume in patients with mild Alzheimer's disease are associated with neuropsychiatric symptoms and disability Nineteen Alzheimer's disease patients (9 females; total mean age =75.2 y old +4.7; total mean education level =8.5 y +4.9) underwent a magnetic resonance imaging (MRI) examination and voxel-based morphometry analysis. T1-weighted images were spatially normalized and segmented. Grey matter images were smoothed and analyzed using a multiple regression design. The results were corrected for multiple comparisons. The Neuropsychiatric Inventory was used to evaluate the neuropsychiatric symptoms, and the Functional Activities Questionnaire and Disability Assessment for Dementia were used for functional evaluation A significant negative correlation was found between the bilateral middle frontal gyri, left inferior temporal gyrus, right orbitofrontal gyrus, and Neuropsychiatric Inventory scores. A negative correlation was found between bilateral middle temporal gyri, left hippocampus, bilateral fusiform gyri, and the Functional Activities Questionnaire. There was a positive correlation between the right amygdala, bilateral fusiform gyri, right anterior insula, left inferior and middle temporal gyri, right superior temporal gyrus, and Disability Assessment for Dementia scores The results suggest that the neuropsychiatric symptoms observed in Alzheimer's disease patients could be mainly due to frontal structural abnormalities, whereas disability could be associated with reductions in temporal structures.
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A Spatial Correlation Model of Permeability on the Columbia River Plateau
NASA Astrophysics Data System (ADS)
Jayne, R., Jr.; Pollyea, R. M.
2017-12-01
This study presents a spatial correlation model of regional scale permeability variability within the Columbia River Basalt Group (CRBG). The data were compiled from the literature, and include 893 aquifer test results from 598 individual wells. In order to quantify the spatial variation of permeability within the CRBG, three experimental variograms (two horizontal and one vertical) are calculated and then fit with a linear combination of mathematical models. The horizontal variograms show there is a 4.5:1 anisotropy ratio for the permeability correlation structure with a long-range correlation of 35 km at N40°E. The km-scale range of these variograms suggests that there is regional control on permeability within the CRBG. One plausible control on the permeability distribution is that rapid crustal loading during CRBG emplacement ( 80% over 1M years) resulted in an isostatic response where the Columbia Plateau had previously undergone subsidence. To support this hypothesis, we calculate a 200 m moving average of all permeability values with depth. This calculation shows that permeability generally follows a systematic decay until 1,100 m depth, beyond which the 200 m moving average permeability increases 3 orders of magnitude. Since basalt fracture networks govern permeability on Columbia River Plateau, this observation is consistent with basal flexure causing tensile stress that counteract lithostatic loading, thus maintaining higher than expected permeability at depth within the Columbia River Basalt Group. These results may have important implications for regional CRBG groundwater management, as well as engineered reservoirs for carbon capture and sequestration and nuclear waste storage.
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Champagne, Emilie; Moore, Ben D; Côté, Steeve D; Tremblay, Jean-Pierre
2018-03-01
Associational effects, that is, the influence of neighboring plants on herbivory suffered by a plant, are an outcome of forage selection. Although forage selection is a hierarchical process, few studies have investigated associational effects at multiple spatial scales. Because the nutritional quality of plants can be spatially structured, it might differently influence associational effects across multiple scales. Our objective was to determine the radius of influence of neighbor density and nutritional quality on balsam fir ( Abies balsamea ) herbivory by white-tailed deer ( Odocoileus virginianus ) in winter. We quantified browsing rates on fir and the density and quality of neighboring trees in a series of 10-year-old cutovers on Anticosti Island (Canada). We used cross-correlations to investigate relationships between browsing rates and the density and nutritional quality of neighboring trees at distances up to 1,000 m. Balsam fir and white spruce ( Picea glauca ) fiber content and dry matter in vitro true digestibility were correlated with fir browsing rate at the finest extra-patch scale (across distance of up to 50 m) and between cutover areas (300-400 m). These correlations suggest associational effects, that is, low nutritional quality of neighbors reduces the likelihood of fir herbivory (associational defense). Our results may indicate associational effects mediated by intraspecific variation in plant quality and suggest that these effects could occur at scales from tens to hundreds of meters. Understanding associational effects could inform strategies for restoration or conservation; for example, planting of fir among existing natural regeneration could be concentrated in areas of low nutritional quality.
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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.
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Positron annihilation spectroscopy: Applications to Si, ZnO, and multilayer semiconductor structures
NASA Astrophysics Data System (ADS)
Schaffer, J. P.; Rohatgi, A.; Dewald, A. B.; Frost, R. L.; Pang, S. K.
1989-11-01
The potential of positron annihilation spectroscopy (PAS) for defect characterization at the atomic scale in semiconductors is demonstrated for Si, ZnO, and multilayer structures, such as an AlGaAs/GaAs solar cell. The types of defects discussed include: i) vacancy complexes, oxygen impurities and dopants, ii) the influence of cooling rates on spatial non-uniformities in defects, and iii) characterization of buried interfaces. In sev-eral instances, the results of the PAS investigations are correlated with data from other established semiconductor characterization techniques.
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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.
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Zhu, Yi; Cai, Zhonghou; Chen, Pice; ...
2016-02-26
Dynamical phase separation during a solid-solid phase transition poses a challenge for understanding the fundamental processes in correlated materials. Critical information underlying a phase transition, such as localized phase competition, is difficult to reveal by measurements that are spatially averaged over many phase seperated regions. The ability to simultanousely track the spatial and temporal evolution of such systems is essential to understanding mesoscopic processes during a phase transition. Using state-of- the-art time-resolved hard x-ray diffraction microscopy, we directly visualize the structural phase progression in a VO 2 film upon photoexcitation. Following a homogenous in-plane optical excitation, the phase transformation ismore » initiated at discrete sites and completed by the growth of one lattice structure into the other, instead of a simultaneous isotropic lattice symmetry change. The time-dependent x-ray diffraction spatial maps show that the in-plane phase progression in laser-superheated VO 2 is via a displacive lattice transformation as a result of relaxation from an excited monoclinic phase into a rutile phase. The speed of the phase front progression is quantitatively measured, which is faster than the process driven by in-plane thermal diffusion but slower than the sound speed in VO 2. Lastly, the direct visualization of localized structural changes in the time domain opens a new avenue to study mesoscopic processes in driven systems.« less
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NASA Astrophysics Data System (ADS)
Zhu, Yi; Cai, Zhonghou; Chen, Pice; Zhang, Qingteng; Highland, Matthew J.; Jung, Il Woong; Walko, Donald A.; Dufresne, Eric M.; Jeong, Jaewoo; Samant, Mahesh G.; Parkin, Stuart S. P.; Freeland, John W.; Evans, Paul G.; Wen, Haidan
2016-02-01
Dynamical phase separation during a solid-solid phase transition poses a challenge for understanding the fundamental processes in correlated materials. Critical information underlying a phase transition, such as localized phase competition, is difficult to reveal by measurements that are spatially averaged over many phase separated regions. The ability to simultaneously track the spatial and temporal evolution of such systems is essential to understanding mesoscopic processes during a phase transition. Using state-of-the-art time-resolved hard x-ray diffraction microscopy, we directly visualize the structural phase progression in a VO2 film upon photoexcitation. Following a homogenous in-plane optical excitation, the phase transformation is initiated at discrete sites and completed by the growth of one lattice structure into the other, instead of a simultaneous isotropic lattice symmetry change. The time-dependent x-ray diffraction spatial maps show that the in-plane phase progression in laser-superheated VO2 is via a displacive lattice transformation as a result of relaxation from an excited monoclinic phase into a rutile phase. The speed of the phase front progression is quantitatively measured, and is faster than the process driven by in-plane thermal diffusion but slower than the sound speed in VO2. The direct visualization of localized structural changes in the time domain opens a new avenue to study mesoscopic processes in driven systems.
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Zhu, Yi; Cai, Zhonghou; Chen, Pice; Zhang, Qingteng; Highland, Matthew J; Jung, Il Woong; Walko, Donald A; Dufresne, Eric M; Jeong, Jaewoo; Samant, Mahesh G; Parkin, Stuart S P; Freeland, John W; Evans, Paul G; Wen, Haidan
2016-02-26
Dynamical phase separation during a solid-solid phase transition poses a challenge for understanding the fundamental processes in correlated materials. Critical information underlying a phase transition, such as localized phase competition, is difficult to reveal by measurements that are spatially averaged over many phase separated regions. The ability to simultaneously track the spatial and temporal evolution of such systems is essential to understanding mesoscopic processes during a phase transition. Using state-of-the-art time-resolved hard x-ray diffraction microscopy, we directly visualize the structural phase progression in a VO2 film upon photoexcitation. Following a homogenous in-plane optical excitation, the phase transformation is initiated at discrete sites and completed by the growth of one lattice structure into the other, instead of a simultaneous isotropic lattice symmetry change. The time-dependent x-ray diffraction spatial maps show that the in-plane phase progression in laser-superheated VO2 is via a displacive lattice transformation as a result of relaxation from an excited monoclinic phase into a rutile phase. The speed of the phase front progression is quantitatively measured, and is faster than the process driven by in-plane thermal diffusion but slower than the sound speed in VO2. The direct visualization of localized structural changes in the time domain opens a new avenue to study mesoscopic processes in driven systems.
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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.
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NASA Astrophysics Data System (ADS)
Feng, J.; Bai, L.; Liu, S.; Su, X.; Hu, H.
2012-07-01
In this paper, the MODIS remote sensing data, featured with low-cost, high-timely and moderate/low spatial resolutions, in the North China Plain (NCP) as a study region were firstly used to carry out mixed-pixel spectral decomposition to extract an useful regionalized indicator parameter (RIP) (i.e., an available ratio, that is, fraction/percentage, of winter wheat planting area in each pixel as a regionalized indicator variable (RIV) of spatial sampling) from the initial selected indicators. Then, the RIV values were spatially analyzed, and the spatial structure characteristics (i.e., spatial correlation and variation) of the NCP were achieved, which were further processed to obtain the scalefitting, valid a priori knowledge or information of spatial sampling. Subsequently, founded upon an idea of rationally integrating probability-based and model-based sampling techniques and effectively utilizing the obtained a priori knowledge or information, the spatial sampling models and design schemes and their optimization and optimal selection were developed, as is a scientific basis of improving and optimizing the existing spatial sampling schemes of large-scale cropland remote sensing monitoring. Additionally, by the adaptive analysis and decision strategy the optimal local spatial prediction and gridded system of extrapolation results were able to excellently implement an adaptive report pattern of spatial sampling in accordance with report-covering units in order to satisfy the actual needs of sampling surveys.
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Double inflation - A possible resolution of the large-scale structure problem
NASA Technical Reports Server (NTRS)
Turner, Michael S.; Villumsen, Jens V.; Vittorio, Nicola; Silk, Joseph; Juszkiewicz, Roman
1987-01-01
A model is presented for the large-scale structure of the universe in which two successive inflationary phases resulted in large small-scale and small large-scale density fluctuations. This bimodal density fluctuation spectrum in an Omega = 1 universe dominated by hot dark matter leads to large-scale structure of the galaxy distribution that is consistent with recent observational results. In particular, large, nearly empty voids and significant large-scale peculiar velocity fields are produced over scales of about 100 Mpc, while the small-scale structure over less than about 10 Mpc resembles that in a low-density universe, as observed. Detailed analytical calculations and numerical simulations are given of the spatial and velocity correlations.
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Natural Models for Autonomous Control of Spatial Navigation, Sensing, and Guidance. Part 1
2012-02-13
ketocarotenoid pigment astaxanthin is deposited in the antennal scale of a stomatopod crustacean, Odontodactylus scyllarus. Positive correlation between...partial polarization and the presence of astaxanthin indicates that the antennal scale polarizes light with astaxanthin . Both the optical properties and...the fine structure of the polarizationally-active cuticle suggest that the dipole axes of the astaxanthin molecules are oriented nearly normal to the
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Analysis of Alaskan burn severity patterns using remotely sensed data
Duffy, P.A.; Epting, J.; Graham, J.M.; Rupp, T.S.; McGuire, A.D.
2007-01-01
Wildland fire is the dominant large-scale disturbance mechanism in the Alaskan boreal forest, and it strongly influences forest structure and function. In this research, patterns of burn severity in the Alaskan boreal forest are characterised using 24 fires. First, the relationship between burn severity and area burned is quantified using a linear regression. Second, the spatial correlation of burn severity as a function of topography is modelled using a variogram analysis. Finally, the relationship between vegetation type and spatial patterns of burn severity is quantified using linear models where variograms account for spatial correlation. These results show that: 1) average burn severity increases with the natural logarithm of the area of the wildfire, 2) burn severity is more variable in topographically complex landscapes than in flat landscapes, and 3) there is a significant relationship between burn severity and vegetation type in flat landscapes but not in topographically complex landscapes. These results strengthen the argument that differential flammability of vegetation exists in some boreal landscapes of Alaska. Additionally, these results suggest that through feedbacks between vegetation and burn severity, the distribution of forest vegetation through time is likely more stable in flat terrain than it is in areas with more complex topography. ?? IAWF 2007.
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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%).
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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.
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Liu, Jiankang; Zhang, Kebin
2018-05-09
Enclosure is an effective practice for restoring and rehabilitating the degraded grassland ecosystem caused by overgrazing. Shrub species, which are dominant in most desert grasslands in arid and semiarid regions, have some beneficial ecological functions for grassland restoration. However, how the population structure and spatial pattern of the Artemisia ordosica shrub changes in a grassland ecosystem under enclosed practice is not well understood. This study, conducted in the Mu Us desert in northwest China, was designed to measure the A. ordosica population according to the chronosequence of enclosure (enclosure periods ranged from 5 years, 10 years, 15 years, and 25 years), contrasting this with an adjacent continuously grazed grassland. The results showed that the enclosed grasslands had a higher number of individuals of different age classes (seedling, adult, aging, and dead group) and greater population coverage, but shrubs had significant lower ( p < 0.05) crown diameter and height in comparison with those in continuously grazed grassland. Further, enclosed grasslands had a significantly higher ( p < 0.05) Shannon-Wiener index (H) and Evenness index (E), but a significantly lower ( p < 0.05) Richness index (R) than continuously grazed grassland. The crown of A. ordosica showed a significant linear positive correlation with height in all plots across succession, indicating that it was feasible to analyze the age structure by crown. The crown-class distribution structure of the A. ordosica population approximated a Gaussian distribution model in all survey plots. Within the population, seedling and adult groups exhibited aggregated spatial distribution at small scales, while aging and dead A. ordosica groups showed random distribution at almost all scales in different plots. The seedling A. ordosica group showed a positive correlation with adults at small scales in all plots except in 10 years of enclosure. However, it showed independent correlation with aging and dead groups at almost all scales. In long-term enclosed plots, the mortality rate of the A. ordosica population increased, therefore assistance management practices, such as fertilization, mowing, interval grazing, and seasonal grazing, must be employed to maintain population stability after long-term enclosure. This study can improve understanding and clarify the effects of enclosures in the desert grasslands of northwest China.
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Scaling impacts on environmental controls and spatial heterogeneity of soil organic carbon stocks
NASA Astrophysics Data System (ADS)
Mishra, U.; Riley, W. J.
2015-01-01
The spatial heterogeneity of land surfaces affects energy, moisture, and greenhouse gas exchanges with the atmosphere. However, representing heterogeneity of terrestrial hydrological and biogeochemical processes in earth system models (ESMs) remains a critical scientific challenge. We report the impact of spatial scaling on environmental controls, spatial structure, and statistical properties of soil organic carbon (SOC) stocks across the US state of Alaska. We used soil profile observations and environmental factors such as topography, climate, land cover types, and surficial geology to predict the SOC stocks at a 50 m spatial scale. These spatially heterogeneous estimates provide a dataset with reasonable fidelity to the observations at a sufficiently high resolution to examine the environmental controls on the spatial structure of SOC stocks. We upscaled both the predicted SOC stocks and environmental variables from finer to coarser spatial scales (s = 100, 200, 500 m, 1, 2, 5, 10 km) and generated various statistical properties of SOC stock estimates. We found different environmental factors to be statistically significant predictors at different spatial scales. Only elevation, temperature, potential evapotranspiration, and scrub land cover types were significant predictors at all scales. The strengths of control (the median value of geographically weighted regression coefficients) of these four environmental variables on SOC stocks decreased with increasing scale and were accurately represented using mathematical functions (R2 = 0.83-0.97). The spatial structure of SOC stocks across Alaska changed with spatial scale. Although the variance (sill) and unstructured variability (nugget) of the calculated variograms of SOC stocks decreased exponentially with scale, the correlation length (range) remained relatively constant across scale. The variance of predicted SOC stocks decreased with spatial scale over the range of 50 to ~ 500 m, and remained constant beyond this scale. The fitted exponential function accounted for 98% of variability in the variance of SOC stocks. We found moderately-accurate linear relationships between mean and higher-order moments of predicted SOC stocks (R2 ~ 0.55-0.63). Current ESMs operate at coarse spatial scales (50-100 km), and are therefore unable to represent environmental controllers and spatial heterogeneity of high-latitude SOC stocks consistent with observations. We conclude that improved understanding of the scaling behavior of environmental controls and statistical properties of SOC stocks can improve ESM land model benchmarking and perhaps allow representation of spatial heterogeneity of biogeochemistry at scales finer than those currently resolved by ESMs.
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Scaling impacts on environmental controls and spatial heterogeneity of soil organic carbon stocks
NASA Astrophysics Data System (ADS)
Mishra, U.; Riley, W. J.
2015-07-01
The spatial heterogeneity of land surfaces affects energy, moisture, and greenhouse gas exchanges with the atmosphere. However, representing the heterogeneity of terrestrial hydrological and biogeochemical processes in Earth system models (ESMs) remains a critical scientific challenge. We report the impact of spatial scaling on environmental controls, spatial structure, and statistical properties of soil organic carbon (SOC) stocks across the US state of Alaska. We used soil profile observations and environmental factors such as topography, climate, land cover types, and surficial geology to predict the SOC stocks at a 50 m spatial scale. These spatially heterogeneous estimates provide a data set with reasonable fidelity to the observations at a sufficiently high resolution to examine the environmental controls on the spatial structure of SOC stocks. We upscaled both the predicted SOC stocks and environmental variables from finer to coarser spatial scales (s = 100, 200, and 500 m and 1, 2, 5, and 10 km) and generated various statistical properties of SOC stock estimates. We found different environmental factors to be statistically significant predictors at different spatial scales. Only elevation, temperature, potential evapotranspiration, and scrub land cover types were significant predictors at all scales. The strengths of control (the median value of geographically weighted regression coefficients) of these four environmental variables on SOC stocks decreased with increasing scale and were accurately represented using mathematical functions (R2 = 0.83-0.97). The spatial structure of SOC stocks across Alaska changed with spatial scale. Although the variance (sill) and unstructured variability (nugget) of the calculated variograms of SOC stocks decreased exponentially with scale, the correlation length (range) remained relatively constant across scale. The variance of predicted SOC stocks decreased with spatial scale over the range of 50 m to ~ 500 m, and remained constant beyond this scale. The fitted exponential function accounted for 98 % of variability in the variance of SOC stocks. We found moderately accurate linear relationships between mean and higher-order moments of predicted SOC stocks (R2 ∼ 0.55-0.63). Current ESMs operate at coarse spatial scales (50-100 km), and are therefore unable to represent environmental controllers and spatial heterogeneity of high-latitude SOC stocks consistent with observations. We conclude that improved understanding of the scaling behavior of environmental controls and statistical properties of SOC stocks could improve ESM land model benchmarking and perhaps allow representation of spatial heterogeneity of biogeochemistry at scales finer than those currently resolved by ESMs.
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Scaling impacts on environmental controls and spatial heterogeneity of soil organic carbon stocks
Mishra, U.; Riley, W. J.
2015-07-02
The spatial heterogeneity of land surfaces affects energy, moisture, and greenhouse gas exchanges with the atmosphere. However, representing the heterogeneity of terrestrial hydrological and biogeochemical processes in Earth system models (ESMs) remains a critical scientific challenge. We report the impact of spatial scaling on environmental controls, spatial structure, and statistical properties of soil organic carbon (SOC) stocks across the US state of Alaska. We used soil profile observations and environmental factors such as topography, climate, land cover types, and surficial geology to predict the SOC stocks at a 50 m spatial scale. These spatially heterogeneous estimates provide a data setmore » with reasonable fidelity to the observations at a sufficiently high resolution to examine the environmental controls on the spatial structure of SOC stocks. We upscaled both the predicted SOC stocks and environmental variables from finer to coarser spatial scales ( s = 100, 200, and 500 m and 1, 2, 5, and 10 km) and generated various statistical properties of SOC stock estimates. We found different environmental factors to be statistically significant predictors at different spatial scales. Only elevation, temperature, potential evapotranspiration, and scrub land cover types were significant predictors at all scales. The strengths of control (the median value of geographically weighted regression coefficients) of these four environmental variables on SOC stocks decreased with increasing scale and were accurately represented using mathematical functions ( R 2 = 0.83–0.97). The spatial structure of SOC stocks across Alaska changed with spatial scale. Although the variance (sill) and unstructured variability (nugget) of the calculated variograms of SOC stocks decreased exponentially with scale, the correlation length (range) remained relatively constant across scale. The variance of predicted SOC stocks decreased with spatial scale over the range of 50 m to ~ 500 m, and remained constant beyond this scale. The fitted exponential function accounted for 98 % of variability in the variance of SOC stocks. We found moderately accurate linear relationships between mean and higher-order moments of predicted SOC stocks ( R 2 ∼ 0.55–0.63). Current ESMs operate at coarse spatial scales (50–100 km), and are therefore unable to represent environmental controllers and spatial heterogeneity of high-latitude SOC stocks consistent with observations. We conclude that improved understanding of the scaling behavior of environmental controls and statistical properties of SOC stocks could improve ESM land model benchmarking and perhaps allow representation of spatial heterogeneity of biogeochemistry at scales finer than those currently resolved by ESMs.« less
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Scaling impacts on environmental controls and spatial heterogeneity of soil organic carbon stocks
Mishra, U.; Riley, W. J.
2015-01-01
The spatial heterogeneity of land surfaces affects energy, moisture, and greenhouse gas exchanges with the atmosphere. However, representing heterogeneity of terrestrial hydrological and biogeochemical processes in earth system models (ESMs) remains a critical scientific challenge. We report the impact of spatial scaling on environmental controls, spatial structure, and statistical properties of soil organic carbon (SOC) stocks across the US state of Alaska. We used soil profile observations and environmental factors such as topography, climate, land cover types, and surficial geology to predict the SOC stocks at a 50 m spatial scale. These spatially heterogeneous estimates provide a dataset with reasonablemore » fidelity to the observations at a sufficiently high resolution to examine the environmental controls on the spatial structure of SOC stocks. We upscaled both the predicted SOC stocks and environmental variables from finer to coarser spatial scales ( s = 100, 200, 500 m, 1, 2, 5, 10 km) and generated various statistical properties of SOC stock estimates. We found different environmental factors to be statistically significant predictors at different spatial scales. Only elevation, temperature, potential evapotranspiration, and scrub land cover types were significant predictors at all scales. The strengths of control (the median value of geographically weighted regression coefficients) of these four environmental variables on SOC stocks decreased with increasing scale and were accurately represented using mathematical functions ( R 2 = 0.83–0.97). The spatial structure of SOC stocks across Alaska changed with spatial scale. Although the variance (sill) and unstructured variability (nugget) of the calculated variograms of SOC stocks decreased exponentially with scale, the correlation length (range) remained relatively constant across scale. The variance of predicted SOC stocks decreased with spatial scale over the range of 50 to ~ 500 m, and remained constant beyond this scale. The fitted exponential function accounted for 98% of variability in the variance of SOC stocks. We found moderately-accurate linear relationships between mean and higher-order moments of predicted SOC stocks ( R 2 ~ 0.55–0.63). Current ESMs operate at coarse spatial scales (50–100 km), and are therefore unable to represent environmental controllers and spatial heterogeneity of high-latitude SOC stocks consistent with observations. We conclude that improved understanding of the scaling behavior of environmental controls and statistical properties of SOC stocks can improve ESM land model benchmarking and perhaps allow representation of spatial heterogeneity of biogeochemistry at scales finer than those currently resolved by ESMs.« less
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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.
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NASA Technical Reports Server (NTRS)
Smith, R. B.; Bruhn, R. L.
1984-01-01
Using 1500 km of industry-released seismic reflection data, surface geology, velocity models from refraction data, and earthquake data, the large extensional structures in the crust of the eastern Basin-Range and its transition into the Middle Rocky Mountains and Colorado Plateau have been studied. It is suggested that the close spatial correlation between normal faults and thrust fault segmentation along the Wasatch Front reflects major east-trending structural and lithological boundaries inherited from tectonic processes associated with the evolution of the cordilleran miogeocline, which began in the Precambrian.
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Neural correlates of abnormal sensory discrimination in laryngeal dystonia.
Termsarasab, Pichet; Ramdhani, Ritesh A; Battistella, Giovanni; Rubien-Thomas, Estee; Choy, Melissa; Farwell, Ian M; Velickovic, Miodrag; Blitzer, Andrew; Frucht, Steven J; Reilly, Richard B; Hutchinson, Michael; Ozelius, Laurie J; Simonyan, Kristina
2016-01-01
Aberrant sensory processing plays a fundamental role in the pathophysiology of dystonia; however, its underpinning neural mechanisms in relation to dystonia phenotype and genotype remain unclear. We examined temporal and spatial discrimination thresholds in patients with isolated laryngeal form of dystonia (LD), who exhibited different clinical phenotypes (adductor vs. abductor forms) and potentially different genotypes (sporadic vs. familial forms). We correlated our behavioral findings with the brain gray matter volume and functional activity during resting and symptomatic speech production. We found that temporal but not spatial discrimination was significantly altered across all forms of LD, with higher frequency of abnormalities seen in familial than sporadic patients. Common neural correlates of abnormal temporal discrimination across all forms were found with structural and functional changes in the middle frontal and primary somatosensory cortices. In addition, patients with familial LD had greater cerebellar involvement in processing of altered temporal discrimination, whereas sporadic LD patients had greater recruitment of the putamen and sensorimotor cortex. Based on the clinical phenotype, adductor form-specific correlations between abnormal discrimination and brain changes were found in the frontal cortex, whereas abductor form-specific correlations were observed in the cerebellum and putamen. Our behavioral and neuroimaging findings outline the relationship of abnormal sensory discrimination with the phenotype and genotype of isolated LD, suggesting the presence of potentially divergent pathophysiological pathways underlying different manifestations of this disorder.
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Reconstruction of explicit structural properties at the nanoscale via spectroscopic microscopy
NASA Astrophysics Data System (ADS)
Cherkezyan, Lusik; Zhang, Di; Subramanian, Hariharan; Taflove, Allen; Backman, Vadim
2016-02-01
The spectrum registered by a reflected-light bright-field spectroscopic microscope (SM) can quantify the microscopically indiscernible, deeply subdiffractional length scales within samples such as biological cells and tissues. Nevertheless, quantification of biological specimens via any optical measures most often reveals ambiguous information about the specific structural properties within the studied samples. Thus, optical quantification remains nonintuitive to users from the diverse fields of technique application. In this work, we demonstrate that the SM signal can be analyzed to reconstruct explicit physical measures of internal structure within label-free, weakly scattering samples: characteristic length scale and the amplitude of spatial refractive-index (RI) fluctuations. We present and validate the reconstruction algorithm via finite-difference time-domain solutions of Maxwell's equations on an example of exponential spatial correlation of RI. We apply the validated algorithm to experimentally measure structural properties within isolated cells from two genetic variants of HT29 colon cancer cell line as well as within a prostate tissue biopsy section. The presented methodology can lead to the development of novel biophotonics techniques that create two-dimensional maps of explicit structural properties within biomaterials: the characteristic size of macromolecular complexes and the variance of local mass density.
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NASA Astrophysics Data System (ADS)
McKeon, Beverley
2015-11-01
The importance of critical layers in determining aspects of the structure of wall turbulence is discussed. We have shown (Jacobi & McKeon, 2013) that the amplitude modulation coefficient investigated most recently by Hutchins & Marusic (2007) and co-authors, which describes the correlation between large scales above a (spatial) wavelength filter with the envelope of small scales below the filter, is dominated by very large scale motion (VLSM) at a single wavelength. The resolvent analysis of McKeon & Sharma (2010) gives a suitable model for the three-dimensional, three-component form of the VLSM and energetic structure at other wavelengths. This model is used to identify the three-dimensional spatial variation of instantaneous critical layers in the presence of a mean velocity profile and to relate this to earlier observations of coherent structure in unperturbed flows (both experimental and via the resolvent model, Sharma & McKeon, 2013); to the phase relationships between scales identified by Chung & McKeon (2010, 2014); and to the structure of wall turbulence that has been modified by the addition of single synthetic scales, e.g. Jacobi & McKeon (2011), Duvvuri & McKeon (2015). The support of AFOSR under grant number FA 9550-12-1-0469 is gratefully acknowledged.
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DOE Office of Scientific and Technical Information (OSTI.GOV)
Zhu, Yi; Cai, Zhonghou; Chen, Pice
Dynamical phase separation during a solid-solid phase transition poses a challenge for understanding the fundamental processes in correlated materials. Critical information underlying a phase transition, such as localized phase competition, is difficult to reveal by measurements that are spatially averaged over many phase seperated regions. The ability to simultanousely track the spatial and temporal evolution of such systems is essential to understanding mesoscopic processes during a phase transition. Using state-of- the-art time-resolved hard x-ray diffraction microscopy, we directly visualize the structural phase progression in a VO 2 film upon photoexcitation. Following a homogenous in-plane optical excitation, the phase transformation ismore » initiated at discrete sites and completed by the growth of one lattice structure into the other, instead of a simultaneous isotropic lattice symmetry change. The time-dependent x-ray diffraction spatial maps show that the in-plane phase progression in laser-superheated VO 2 is via a displacive lattice transformation as a result of relaxation from an excited monoclinic phase into a rutile phase. The speed of the phase front progression is quantitatively measured, which is faster than the process driven by in-plane thermal diffusion but slower than the sound speed in VO 2. Lastly, the direct visualization of localized structural changes in the time domain opens a new avenue to study mesoscopic processes in driven systems.« less
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Rau, D; Rodriguez, M; Rapposelli, E; Murgia, M L; Papa, R; Brown, A H D; Attene, G
2016-12-01
Nuclear and chloroplast markers and phenotypic characters were integrated to analyse the population genetic structure of wild cardoon, Cynara cardunculus var. sylvestris, the ancestor of cultivated globe artichoke, Cynara cardunculus var. scolymus on the island of Sardinia, Italy. The spatial scale ranged from a few metres to ∼200km. Wild cardoon appears to be genetically fragmented, with significant genetic divergence at various scales, indicating that gene flow is insufficient to counterbalance the effects of genetic drift or founder effects. Divergence between populations was higher for chloroplast (40%) than for nuclear markers (15%), suggesting that gene flow via seed was lower than via pollen. Two main genetic groups were detected; these correlated with differences in flowering time, capitula size, glossiness, and anthocyanin pigmentation. A complex population structure of wild cardoon emerged over small spatial scales, likely resulting from the interplay between gene dispersal, colonisation history and selective forces. Indeed, Sardinia appears to be a 'hybrid zone' of different gene pools. The island has unique diverse germplasm that has originated from hybridisation among different gene pools. The sampling of seeds from a few plants but from many sites is suggested as the best strategy to harvest the genetic diversity of wild cardoon. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.
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Kjellberg, Finn; Proffit, Magali
2016-02-01
The food webs consisting of plants, herbivorous insects and their insect parasitoids are a major component of terrestrial biodiversity. They play a central role in the functioning of all terrestrial ecosystems, and the number of species involved is mind-blowing (Nyman et al. 2015). Nevertheless, our understanding of the evolutionary and ecological determinants of their diversity is still in its infancy. In this issue of Molecular Ecology, Sutton et al. (2016) open a window into the comparative analysis of spatial genetic structuring in a set of comparable multitrophic models, involving highly species-specific interactions: figs and fig wasps. This is the first study to compare genetic structure using population genetics tools in a fig-pollinating wasp (Pleistodontes imperialis sp1) and its main parasitoid (Sycoscapter sp.A). The fig-pollinating wasp has a discontinuous spatial distribution that correlates with genetic differentiation, while the parasitoid bridges the discontinuity by parasitizing other pollinator species on the same host fig tree and presents basically no spatial genetic structure. The full implications of these results for our general understanding of plant-herbivorous insect-insect parasitoids diversification become apparent when envisioned within the framework of recent advances in fig and fig wasp biology. © 2016 John Wiley & Sons Ltd.
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Estimation of the vortex length scale and intensity from two-dimensional samples
NASA Technical Reports Server (NTRS)
Reuss, D. L.; Cheng, W. P.
1992-01-01
A method is proposed for estimating flow features that influence flame wrinkling in reciprocating internal combustion engines, where traditional statistical measures of turbulence are suspect. Candidate methods were tested in a computed channel flow where traditional turbulence measures are valid and performance can be rationally evaluated. Two concepts are tested. First, spatial filtering is applied to the two-dimensional velocity distribution and found to reveal structures corresponding to the vorticity field. Decreasing the spatial-frequency cutoff of the filter locally changes the character and size of the flow structures that are revealed by the filter. Second, vortex length scale and intensity is estimated by computing the ensemble-average velocity distribution conditionally sampled on the vorticity peaks. The resulting conditionally sampled 'average vortex' has a peak velocity less than half the rms velocity and a size approximately equal to the two-point-correlation integral-length scale.
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Meirer, Florian; Morris, Darius T.; Kalirai, Sam; ...
2015-01-02
Full-field transmission X-ray microscopy has been used to determine the 3D structure of a whole individual fluid catalytic cracking (FCC) particle at high spatial resolution and in a fast, noninvasive manner, maintaining the full integrity of the particle. Using X-ray absorption mosaic imaging to combine multiple fields of view, computed tomography was performed to visualize the macropore structure of the catalyst and its availability for mass transport. We mapped the relative spatial distributions of Ni and Fe using multiple-energy tomography at the respective X-ray absorption K-edges and correlated these distributions with porosity and permeability of an equilibrated catalyst (E-cat) particle.more » Both metals were found to accumulate in outer layers of the particle, effectively decreasing porosity by clogging of pores and eventually restricting access into the FCC particle.« less
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Optics. Spatially structured photons that travel in free space slower than the speed of light.
Giovannini, Daniel; Romero, Jacquiline; Potoček, Václav; Ferenczi, Gergely; Speirits, Fiona; Barnett, Stephen M; Faccio, Daniele; Padgett, Miles J
2015-02-20
That the speed of light in free space is constant is a cornerstone of modern physics. However, light beams have finite transverse size, which leads to a modification of their wave vectors resulting in a change to their phase and group velocities. We study the group velocity of single photons by measuring a change in their arrival time that results from changing the beam's transverse spatial structure. Using time-correlated photon pairs, we show a reduction in the group velocity of photons in both a Bessel beam and photons in a focused Gaussian beam. In both cases, the delay is several micrometers over a propagation distance of ~1 meter. Our work highlights that, even in free space, the invariance of the speed of light only applies to plane waves. Copyright © 2015, American Association for the Advancement of Science.