Spatial correlation between weed species densities and soil properties

DEFF Research Database (Denmark)

Walter, Mette; Christensen, Svend; Simmelsgaard, Svend Erik

2002-01-01

The spatial cross-correlation between weed species densities and six soil properties within fields was analysed using cross-semivariograms. The survey was carried out in three successive years in two fields. The most consistent relationship between weed species density (numbers m−2) and soil...... properties was negative cross-correlation between the density of Viola arvensis Murray and clay content. This correlation was found in both fields; however, the range of spatial dependence varied between fields. In one of the fields, the density of Lamium purpureum L. was positively cross......-correlated with the phosphorus content in the soil in all years. The density of Veronica spp. and Poa annua L. was negatively cross-correlated with pH in all three years. Other spatial cross-correlations that were found in this study were inconsistent over time or field site. The densities of some of the weed species were...

Spatial correlation length of normalized cone data in sand

DEFF Research Database (Denmark)

Firouzianbandpey, Sarah; Griffiths, D. V.; Ibsen, Lars Bo

2014-01-01

The main topic of this study is to assess the anisotropic spatial correlation lengths of a sand layer deposit based on cone penetration testing with pore pressure measurement (CPTu) data. Spatial correlation length can be an important factor in reliability analysis of geotechnical systems, yet it...

Spatial-Temporal Correlation Properties of the 3GPP Spatial Channel Model and the Kronecker MIMO Channel Model

Directory of Open Access Journals (Sweden)

Cheng-Xiang Wang

2007-02-01

Full Text Available The performance of multiple-input multiple-output (MIMO systems is greatly influenced by the spatial-temporal correlation properties of the underlying MIMO channels. This paper investigates the spatial-temporal correlation characteristics of the spatial channel model (SCM in the Third Generation Partnership Project (3GPP and the Kronecker-based stochastic model (KBSM at three levels, namely, the cluster level, link level, and system level. The KBSM has both the spatial separability and spatial-temporal separability at all the three levels. The spatial-temporal separability is observed for the SCM only at the system level, but not at the cluster and link levels. The SCM shows the spatial separability at the link and system levels, but not at the cluster level since its spatial correlation is related to the joint distribution of the angle of arrival (AoA and angle of departure (AoD. The KBSM with the Gaussian-shaped power azimuth spectrum (PAS is found to fit best the 3GPP SCM in terms of the spatial correlations. Despite its simplicity and analytical tractability, the KBSM is restricted to model only the average spatial-temporal behavior of MIMO channels. The SCM provides more insights of the variations of different MIMO channel realizations, but the implementation complexity is relatively high.

Spatial variability of correlated color temperature of lightning channels

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Nobuaki Shimoji

Full Text Available In this paper, we present the spatial variability of the correlated color temperature of lightning channel shown in a digital still image. In order to analyze the correlated color temperature, we calculated chromaticity coordinates of the lightning channels in the digital still image. From results, the spatial variation of the correlated color temperature of the lightning channel was confirmed. Moreover, the results suggest that the correlated color temperature and peak current of the lightning channels are related to each other. Keywords: Lightning, Color analysis, Correlated color temperature, Chromaticity coordinate, CIE 1931 xy-chromaticity diagram

Measurement-Based Spatial Correlation and Capacity of Indoor Distributed MIMO System

Directory of Open Access Journals (Sweden)

Yan Zhang

2013-01-01

Full Text Available Distributed MIMO (D-MIMO system is one of the candidates for future wireless access networks. In this study, the spatial correlation and capacity in indoor D-MIMO system are presented. All results are from the actual channel measurements in typical indoor scenarios, including office and corridor. Based on measured data, spatial correlation coefficients between distributed transmitting antennas are analyzed. Although the literature about D-MIMO system assumes the small scale fading between distributed antennas is independent, we find that spatial correlation may still exist in specific propagation scenario. This correlation can also degrade the performance of D-MIMO system. To mitigate the impact of spatial correlation, one efficient method is to use transmitting antenna selection technique.

Spatial Correlation of PAN UWB-MIMO Channel Including User Dynamics

DEFF Research Database (Denmark)

Wang, Yu; Kovacs, Istvan Zsolt; Pedersen, Gert Frølund

. It is found the channel shows spatial correlated wideband power, and spatial uncorrelated complex channel coefficients at different frequencies and delays with respect to a correlation coefficient threshold of 0.7. The Kronecker model is proved not suitable for the investigated scenarios. The MIMO UWB channel......In this paper we present and analyze spatial correlation properties of indoor 4x2 MIMO UWB channels in personal area network (PAN) scenarios. The presented results are based on measurement of radio links between an access point like device and a hand held or belt mounted device with dynamic user...

Measurement of spatial correlation functions using image processing techniques

International Nuclear Information System (INIS)

Berryman, J.G.

1985-01-01

A procedure for using digital image processing techniques to measure the spatial correlation functions of composite heterogeneous materials is presented. Methods for eliminating undesirable biases and warping in digitized photographs are discussed. Fourier transform methods and array processor techniques for calculating the spatial correlation functions are treated. By introducing a minimal set of lattice-commensurate triangles, a method of sorting and storing the values of three-point correlation functions in a compact one-dimensional array is developed. Examples are presented at each stage of the analysis using synthetic photographs of cross sections of a model random material (the penetrable sphere model) for which the analytical form of the spatial correlations functions is known. Although results depend somewhat on magnification and on relative volume fraction, it is found that photographs digitized with 512 x 512 pixels generally have sufficiently good statistics for most practical purposes. To illustrate the use of the correlation functions, bounds on conductivity for the penetrable sphere model are calculated with a general numerical scheme developed for treating the singular three-dimensional integrals which must be evaluated

Time-varying correlations in global real estate markets: A multivariate GARCH with spatial effects approach

Science.gov (United States)

Gu, Huaying; Liu, Zhixue; Weng, Yingliang

2017-04-01

The present study applies the multivariate generalized autoregressive conditional heteroscedasticity (MGARCH) with spatial effects approach for the analysis of the time-varying conditional correlations and contagion effects among global real estate markets. A distinguishing feature of the proposed model is that it can simultaneously capture the spatial interactions and the dynamic conditional correlations compared with the traditional MGARCH models. Results reveal that the estimated dynamic conditional correlations have exhibited significant increases during the global financial crisis from 2007 to 2009, thereby suggesting contagion effects among global real estate markets. The analysis further indicates that the returns of the regional real estate markets that are in close geographic and economic proximities exhibit strong co-movement. In addition, evidence of significantly positive leverage effects in global real estate markets is also determined. The findings have significant implications on global portfolio diversification opportunities and risk management practices.

Spatial correlation genetic algorithm for fractal image compression

International Nuclear Information System (INIS)

Wu, M.-S.; Teng, W.-C.; Jeng, J.-H.; Hsieh, J.-G.

2006-01-01

Fractal image compression explores the self-similarity property of a natural image and utilizes the partitioned iterated function system (PIFS) to encode it. This technique is of great interest both in theory and application. However, it is time-consuming in the encoding process and such drawback renders it impractical for real time applications. The time is mainly spent on the search for the best-match block in a large domain pool. In this paper, a spatial correlation genetic algorithm (SC-GA) is proposed to speed up the encoder. There are two stages for the SC-GA method. The first stage makes use of spatial correlations in images for both the domain pool and the range pool to exploit local optima. The second stage is operated on the whole image to explore more adequate similarities if the local optima are not satisfied. With the aid of spatial correlation in images, the encoding time is 1.5 times faster than that of traditional genetic algorithm method, while the quality of the retrieved image is almost the same. Moreover, about half of the matched blocks come from the correlated space, so fewer bits are required to represent the fractal transform and therefore the compression ratio is also improved

Spatial-Temporal Similarity Correlation between Public Transit Passengers Using Smart Card Data

Directory of Open Access Journals (Sweden)

Hamed Faroqi

2017-01-01

Full Text Available The increasing availability of public transit smart card data has enabled several studies to focus on identifying passengers with similar spatial and/or temporal trip characteristics. However, this paper goes one step further by investigating the relationship between passengers’ spatial and temporal characteristics. For the first time, this paper investigates the correlation of the spatial similarity with the temporal similarity between public transit passengers by developing spatial similarity and temporal similarity measures for the public transit network with a novel passenger-based perspective. The perspective considers the passengers as agents who can make multiple trips in the network. The spatial similarity measure takes into account direction as well as the distance between the trips of the passengers. The temporal similarity measure considers both the boarding and alighting time in a continuous linear space. The spatial-temporal similarity correlation between passengers is analysed using histograms, Pearson correlation coefficients, and hexagonal binning. Also, relations between the spatial and temporal similarity values with the trip time and length are examined. The proposed methodology is implemented for four-day smart card data including 80,000 passengers in Brisbane, Australia. The results show a nonlinear spatial-temporal similarity correlation among the passengers.

Spatial Decomposition of Translational Water–Water Correlation Entropy in Binding Pockets

Science.gov (United States)

2015-01-01

A number of computational tools available today compute the thermodynamic properties of water at surfaces and in binding pockets by using inhomogeneous solvation theory (IST) to analyze explicit-solvent simulations. Such methods enable qualitative spatial mappings of both energy and entropy around a solute of interest and can also be applied quantitatively. However, the entropy estimates of existing methods have, to date, been almost entirely limited to the first-order terms in the IST’s entropy expansion. These first-order terms account for localization and orientation of water molecules in the field of the solute but not for the modification of water–water correlations by the solute. Here, we present an extension of the Grid Inhomogeneous Solvation Theory (GIST) approach which accounts for water–water translational correlations. The method involves rewriting the two-point density of water in terms of a conditional density and utilizes the efficient nearest-neighbor entropy estimation approach. Spatial maps of this second order term, for water in and around the synthetic host cucurbit[7]uril and in the binding pocket of the enzyme Factor Xa, reveal mainly negative contributions, indicating solute-induced water–water correlations relative to bulk water; particularly strong signals are obtained for sites at the entrances of cavities or pockets. This second-order term thus enters with the same, negative, sign as the first order translational and orientational terms. Numerical and convergence properties of the methodology are examined. PMID:26636620

Continuous-wave spatial quantum correlations of light induced by multiple scattering

DEFF Research Database (Denmark)

Smolka, Stephan; Ott, Johan Raunkjær; Huck, Alexander

2012-01-01

and reflectance. Utilizing frequency-resolved quantum noise measurements, we observe that the strength of the spatial quantum correlation function can be controlled by changing the quantum state of an incident bright squeezed-light source. Our results are found to be in excellent agreement with the developed......We present theoretical and experimental results on spatial quantum correlations induced by multiple scattering of nonclassical light. A continuous-mode quantum theory is derived that enables determining the spatial quantum correlation function from the fluctuations of the total transmittance...... theory and form a basis for future research on, e. g., quantum interference of multiple quantum states in a multiple scattering medium....

Considering built environment and spatial correlation in modeling pedestrian injury severity.

Science.gov (United States)

Prato, Carlo G; Kaplan, Sigal; Patrier, Alexandre; Rasmussen, Thomas K

2018-01-02

This study looks at mitigating and aggravating factors that are associated with the injury severity of pedestrians when they have crashes with another road user and overcomes existing limitations in the literature by focusing attention on the built environment and considering spatial correlation across crashes. Reports for 6,539 pedestrian crashes occurred in Denmark between 2006 and 2015 were merged with geographic information system resources containing detailed information about the built environment and exposure at the crash locations. A linearized spatial logit model estimated the probability of pedestrians sustaining a severe or fatal injury conditional on the occurrence of a crash with another road user. This study confirms previous findings about older pedestrians and intoxicated pedestrians being the most vulnerable road users and crashes with heavy vehicles and in roads with higher speed limits being related to the most severe outcomes. This study provides novel perspectives by showing positive spatial correlations of crashes with the same severity outcomes and emphasizing the role of the built environment in the proximity of the crash. This study emphasizes the need for thinking about traffic calming measures, illumination solutions, road maintenance programs, and speed limit reductions. Moreover, this study emphasizes the role of the built environment, because shopping areas, residential areas, and walking traffic density are positively related to a reduction in pedestrian injury severity. Often, these areas have in common a larger pedestrian mass that is more likely to make other road users more aware and attentive, whereas the same does not seem to apply to areas with lower pedestrian density.

Applying spatial clustering analysis to a township-level social vulnerability assessment in Taiwan

Directory of Open Access Journals (Sweden)

Wen-Yen Lin

2016-09-01

Full Text Available The degree of social vulnerability may vary according to the conditions and backgrounds of different locations, yet spatial clustering phenomena may exist when nearby spatial units exhibit similar characteristics. This study applied spatial autocorrelation statistics to analyze the spatial association of vulnerability among townships in Taiwan. The vulnerability was first assessed on the basis of a social vulnerability index that was constructed using Fuzzy Delphi and analytic hierarchy process methods. Subsequently, the corresponding indicator variables were applied to calculate standardized vulnerability assessment scores by using government data. According to the results of the vulnerability assessment in which T scores were normalized, the distribution of social vulnerabilities varied among the townships. The scores were further analyzed using spatial autocorrelation statistics for spatial clustering of vulnerability distribution. The Local G statistic identified 42 significant spatial association pockets, whereas the Global G statistic indicated no spatial phenomenon of clustering. This phenomenon was verified and explained by applying Moran's I statistics to examine the homogeneity and heterogeneity of spatial associations. Although both statistics were originally designed to identify the existence of spatial clustering, they serve diverse purposes, and the results can be compared to obtain additional insights into the distribution patterns of social vulnerability.

Binary zone-plate array for a parallel joint transform correlator applied to face recognition.

Science.gov (United States)

Kodate, K; Hashimoto, A; Thapliya, R

1999-05-10

Taking advantage of small aberrations, high efficiency, and compactness, we developed a new, to our knowledge, design procedure for a binary zone-plate array (BZPA) and applied it to a parallel joint transform correlator for the recognition of the human face. Pairs of reference and unknown images of faces are displayed on a liquid-crystal spatial light modulator (SLM), Fourier transformed by the BZPA, intensity recorded on an optically addressable SLM, and inversely Fourier transformed to obtain correlation signals. Consideration of the bandwidth allows the relations among the channel number, the numerical aperture of the zone plates, and the pattern size to be determined. Experimentally a five-channel parallel correlator was implemented and tested successfully with a 100-person database. The design and the fabrication of a 20-channel BZPA for phonetic character recognition are also included.

Observation of spatial quantum correlations induced by multiple scattering of nonclassical light

DEFF Research Database (Denmark)

Smolka, Stephan; Huck, Alexander; Andersen, Ulrik Lund

2009-01-01

and negative spatial quantum correlations are observed when varying the quantum state incident to the multiple scattering medium, and the strength of the correlations is controlled by the number of photons. The experimental results are in excellent agreement with recent theoretical proposals by implementing......We present the experimental realization of spatial quantum correlations of photons that are induced by multiple scattering of squeezed light. The quantum correlation relates photons propagating along two different light paths through the random medium and is infinite in range. Both positive...... the full quantum model of multiple scattering....

Spatial and statistical methods for correlating the interaction between groundwater contamination and tap water exposure in karst regions

Science.gov (United States)

Padilla, I. Y.; Rivera, V. L.; Macchiavelli, R. E.; Torres Torres, N. I.

2016-12-01

Groundwater systems in karst regions are highly vulnerable to contamination and have an enormous capacity to store and rapidly convey pollutants to potential exposure zones over long periods of time. Contaminants in karst aquifers used for drinking water purposes can, therefore, enter distributions lines and the tap water point of use. This study applies spatial and statistical analytical methods to assess potential correlations between contaminants in a karst groundwater system in northern Puerto Rico and exposure in the tap water. It focuses on chlorinated volatile organic compounds (CVOC) and phthalates because of their ubiquitous presence in the environment and the potential public health impacts. The work integrates historical data collected from regulatory agencies and current field measurements involving groundwater and tap water sampling and analysis. Contaminant distributions and cluster analysis is performed with Geographic Information System technology. Correlations between detection frequencies and contaminants concentration in source groundwater and tap water point of use are assessed using Pearson's Chi Square and T-Test analysis. Although results indicate that correlations are contaminant-specific, detection frequencies are generally higher for total CVOC in groundwater than tap water samples, but greater for phthalates in tap water than groundwater samples. Spatial analysis shows widespread distribution of CVOC and phthalates in both groundwater and tap water, suggesting that contamination comes from multiple sources. Spatial correlation analysis indicates that association between tap water and groundwater contamination depends on the source and type of contaminants, spatial location, and time. Full description of the correlations may, however, need to take into consideration variable anthropogenic interventions.

Revealing Spatial Variation and Correlation of Urban Travels from Big Trajectory Data

Science.gov (United States)

Li, X.; Tu, W.; Shen, S.; Yue, Y.; Luo, N.; Li, Q.

2017-09-01

With the development of information and communication technology, spatial-temporal data that contain rich human mobility information are growing rapidly. However, the consistency of multi-mode human travel behind multi-source spatial-temporal data is not clear. To this aim, we utilized a week of taxies' and buses' GPS trajectory data and smart card data in Shenzhen, China to extract city-wide travel information of taxi, bus and metro and tested the correlation of multi-mode travel characteristics. Both the global correlation and local correlation of typical travel indicator were examined. The results show that: (1) Significant differences exist in of urban multi-mode travels. The correlation between bus travels and taxi travels, metro travel and taxi travels are globally low but locally high. (2) There are spatial differences of the correlation relationship between bus, metro and taxi travel. These findings help us understanding urban travels deeply therefore facilitate both the transport policy making and human-space interaction research.

REVEALING SPATIAL VARIATION AND CORRELATION OF URBAN TRAVELS FROM BIG TRAJECTORY DATA

Directory of Open Access Journals (Sweden)

X. Li

2017-09-01

Full Text Available With the development of information and communication technology, spatial-temporal data that contain rich human mobility information are growing rapidly. However, the consistency of multi-mode human travel behind multi-source spatial-temporal data is not clear. To this aim, we utilized a week of taxies’ and buses’ GPS trajectory data and smart card data in Shenzhen, China to extract city-wide travel information of taxi, bus and metro and tested the correlation of multi-mode travel characteristics. Both the global correlation and local correlation of typical travel indicator were examined. The results show that: (1 Significant differences exist in of urban multi-mode travels. The correlation between bus travels and taxi travels, metro travel and taxi travels are globally low but locally high. (2 There are spatial differences of the correlation relationship between bus, metro and taxi travel. These findings help us understanding urban travels deeply therefore facilitate both the transport policy making and human-space interaction research.

Spatial and temporal correlation in dynamic, multi-electron quantum systems

Energy Technology Data Exchange (ETDEWEB)

Godunov, A.L.; McGuire, J.H.; Shakov, Kh.Kh. [Department of Physics, Tulane University, New Orleans, LA (United States); Ivanov, P.B.; Shipakov, V.A. [Troitsk Institute for Innovation and Fusion Research, Troitsk (Russian Federation); Merabet, H.; Bruch, R.; Hanni, J. [Department of Physics, University of Nevada Reno, Reno, NV (United States)

2001-12-28

Cross sections for ionization with excitation and for double excitation in helium are evaluated in a full second Born calculation. These full second Born calculations are compared to calculations in the independent electron approximation, where spatial correlation between the electrons is removed. Comparison is also made to calculations in the independent time approximation, where time correlation between the electrons is removed. The two-electron transitions considered here are caused by interactions with incident protons and electrons with velocities ranging between 2 and 10 au. Good agreement is found between our full calculations and experiment, except for the lowest velocities, where higher Born terms are expected to be significant. Spatial electron correlation, arising from internal electron-electron interactions, and time correlation, arising from time ordering of the external interactions, can both give rise to observable effects. Our method may be used for photon impact. (author)

Accounting for connectivity and spatial correlation in the optimal placement of wildlife habitat

Science.gov (United States)

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...

SPATIAL CORRELATION BETWEEN PHYSICAL PROPERTIES OF SOIL AND WEEDS IN TWO MANAGEMENT SYSTEMS

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Valter Roberto Schaffrath

2015-02-01

Full Text Available The spatial correlation between soil properties and weeds is relevant in agronomic and environmental terms. The analysis of this correlation is crucial for the interpretation of its meaning, for influencing factors such as dispersal mechanisms, seed production and survival, and the range of influence of soil management techniques. This study aimed to evaluate the spatial correlation between the physical properties of soil and weeds in no-tillage (NT and conventional tillage (CT systems. The following physical properties of soil and weeds were analyzed: soil bulk density, macroporosity, microporosity, total porosity, aeration capacity of soil matrix, soil water content at field capacity, weed shoot biomass, weed density, Commelina benghalensis density, and Bidens pilosa density. Generally, the ranges of the spatial correlations were higher in NT than in CT. The cross-variograms showed that many variables have a structure of combined spatial variation and can therefore be mapped from one another by co-kriging. This combined variation also allows inferences about the physical and biological meanings of the study variables. Results also showed that soil management systems influence the spatial dependence structure significantly.

A Big Spatial Data Processing Framework Applying to National Geographic Conditions Monitoring

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F. Xiao

2018-04-01

Full Text Available In this paper, a novel framework for spatial data processing is proposed, which apply to National Geographic Conditions Monitoring project of China. It includes 4 layers: spatial data storage, spatial RDDs, spatial operations, and spatial query language. The spatial data storage layer uses HDFS to store large size of spatial vector/raster data in the distributed cluster. The spatial RDDs are the abstract logical dataset of spatial data types, and can be transferred to the spark cluster to conduct spark transformations and actions. The spatial operations layer is a series of processing on spatial RDDs, such as range query, k nearest neighbor and spatial join. The spatial query language is a user-friendly interface which provide people not familiar with Spark with a comfortable way to operation the spatial operation. Compared with other spatial frameworks, it is highlighted that comprehensive technologies are referred for big spatial data processing. Extensive experiments on real datasets show that the framework achieves better performance than traditional process methods.

A Big Spatial Data Processing Framework Applying to National Geographic Conditions Monitoring

Science.gov (United States)

Xiao, F.

2018-04-01

In this paper, a novel framework for spatial data processing is proposed, which apply to National Geographic Conditions Monitoring project of China. It includes 4 layers: spatial data storage, spatial RDDs, spatial operations, and spatial query language. The spatial data storage layer uses HDFS to store large size of spatial vector/raster data in the distributed cluster. The spatial RDDs are the abstract logical dataset of spatial data types, and can be transferred to the spark cluster to conduct spark transformations and actions. The spatial operations layer is a series of processing on spatial RDDs, such as range query, k nearest neighbor and spatial join. The spatial query language is a user-friendly interface which provide people not familiar with Spark with a comfortable way to operation the spatial operation. Compared with other spatial frameworks, it is highlighted that comprehensive technologies are referred for big spatial data processing. Extensive experiments on real datasets show that the framework achieves better performance than traditional process methods.

Spatially correlated disorder in striped precursor magnetic modulations

International Nuclear Information System (INIS)

Porta, Marcel; Castan, Teresa; LLoveras, Pol; Planes, Antoni; Saxena, Avadh

2007-01-01

We use a Ginzburg-Landau model that includes long-range dipolar interactions and spatially correlated quenched-in disorder coupled to the local magnetization to study the properties of the precursor magnetic modulations as a function of the characteristics of the disorder. We find that although the modulation pattern is very robust and does not depend on details of the pair correlation function G(r), the scaling behaviour of the characteristic length of the striped magnetic modulations depends on the behaviour of G(r) for small values of r

Stochastic Geometric Models with Non-stationary Spatial Correlations in Lagrangian Fluid Flows

Science.gov (United States)

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.

Stochastic Geometric Models with Non-stationary Spatial Correlations in Lagrangian Fluid Flows

Science.gov (United States)

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.

Spatially varying cross-correlation coefficients in the presence of nugget effects

KAUST Repository

Kleiber, William; Genton, Marc G.

2012-01-01

We derive sufficient conditions for the cross-correlation coefficient of a multivariate spatial process to vary with location when the spatial model is augmented with nugget effects. The derived class is valid for any choice of covariance functions, and yields substantial flexibility between multiple processes. The key is to identify the cross-correlation coefficient matrix with a contraction matrix, which can be either diagonal, implying a parsimonious formulation, or a fully general contraction matrix, yielding greater flexibility but added model complexity. We illustrate the approach with a bivariate minimum and maximum temperature dataset in Colorado, allowing the two variables to be positively correlated at low elevations and nearly independent at high elevations, while still yielding a positive definite covariance matrix. © 2012 Biometrika Trust.

Spatially varying cross-correlation coefficients in the presence of nugget effects

KAUST Repository

Kleiber, William

2012-11-29

We derive sufficient conditions for the cross-correlation coefficient of a multivariate spatial process to vary with location when the spatial model is augmented with nugget effects. The derived class is valid for any choice of covariance functions, and yields substantial flexibility between multiple processes. The key is to identify the cross-correlation coefficient matrix with a contraction matrix, which can be either diagonal, implying a parsimonious formulation, or a fully general contraction matrix, yielding greater flexibility but added model complexity. We illustrate the approach with a bivariate minimum and maximum temperature dataset in Colorado, allowing the two variables to be positively correlated at low elevations and nearly independent at high elevations, while still yielding a positive definite covariance matrix. © 2012 Biometrika Trust.

Horizontal Residual Mean Circulation: Evaluation of Spatial Correlations in Coarse Resolution Ocean Models

Science.gov (United States)

Li, Y.; McDougall, T. J.

2016-02-01

Coarse resolution ocean models lack knowledge of spatial correlations between variables on scales smaller than the grid scale. Some researchers have shown that these spatial correlations play a role in the poleward heat flux. In order to evaluate the poleward transport induced by the spatial correlations at a fixed horizontal position, an equation is obtained to calculate the approximate transport from velocity gradients. The equation involves two terms that can be added to the quasi-Stokes streamfunction (based on temporal correlations) to incorporate the contribution of spatial correlations. Moreover, these new terms do not need to be parameterized and is ready to be evaluated by using model data directly. In this study, data from a high resolution ocean model have been used to estimate the accuracy of this HRM approach for improving the horizontal property fluxes in coarse-resolution ocean models. A coarse grid is formed by sub-sampling and box-car averaging the fine grid scale. The transport calculated on the coarse grid is then compared to the transport on original high resolution grid scale accumulated over a corresponding number of grid boxes. The preliminary results have shown that the estimate on coarse resolution grids roughly match the corresponding transports on high resolution grids.

Estimating the spatial distribution of field-applied mushroom compost in the Brandywine-Christina River Basin using multispectral remote sensing

Science.gov (United States)

Moxey, Kelsey A.

The world's greatest concentration of mushroom farms is settled within the Brandywine-Christina River Basin in Chester County in southeastern Pennsylvania. This industry produces a nutrient-rich byproduct known as spent mushroom compost, which has been traditionally applied to local farm fields as an organic fertilizer and soil amendment. While mushroom compost has beneficial properties, the possible over-application to farm fields could potentially degrade stream water quality. The goal of this study was to estimate the spatial extent and intensity of field-applied mushroom compost. We applied a remote sensing approach using Landsat multispectral imagery. We utilized the soil line technique, using the red and near-infrared bands, to estimate differences in soil wetness as a result of increased soil organic matter content from mushroom compost. We validated soil wetness estimates by examining the spectral response of references sites. We performed a second independent validation analysis using expert knowledge from agricultural extension agents. Our results showed that the soil line based wetness index worked well. The spectral validation illustrated that compost changes the spectral response of soil because of changes in wetness. The independent expert validation analysis produced a strong significant correlation between our remotely-sensed wetness estimates and the empirical ratings of compost application intensities. Overall, the methodology produced realistic spatial distributions of field-applied compost application intensities across the study area. These spatial distributions will be used for follow-up studies to assess the effect of spent mushroom compost on stream water quality.

A composite likelihood approach for spatially correlated survival data

Science.gov (United States)

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

A composite likelihood approach for spatially correlated survival data.

Science.gov (United States)

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.

Investigation of spatial correlation in MR images of human cerebral white matter using geostatistical methods

International Nuclear Information System (INIS)

Keil, Fabian

2014-01-01

Investigating the structure of human cerebral white matter is gaining interest in the neurological as well as in the neuroscientific community. It has been demonstrated in many studies that white matter is a very dynamic structure, rather than a static construct which does not change for a lifetime. That means, structural changes within white matter can be observed even on short timescales, e.g. in the course of normal ageing, neurodegenerative diseases or even during learning processes. To investigate these changes, one method of choice is the texture analysis of images obtained from white matter. In this regard, MRI plays a distinguished role as it provides a completely non-invasive way of acquiring in vivo images of human white matter. This thesis adapted a statistical texture analysis method, known as variography, to quantify the spatial correlation of human cerebral white matter based on MR images. This method, originally introduced in geoscience, relies on the idea of spatial correlation in geological phenomena: in naturally grown structures near things are correlated stronger to each other than distant things. This work reveals that the geological principle of spatial correlation can be applied to MR images of human cerebral white matter and proves that variography is an adequate method to quantify alterations therein. Since the process of MRI data acquisition is completely different to the measuring process used to quantify geological phenomena, the variographic analysis had to be adapted carefully to MR methods in order to provide a correctly working methodology. Therefore, theoretical considerations were evaluated with numerical samples in a first, and validated with real measurements in a second step. It was shown that MR variography facilitates to reduce the information stored in the texture of a white matter image to a few highly significant parameters, thereby quantifying heterogeneity and spatial correlation distance with an accuracy better than 5

Correlated density matrix theory of spatially inhomogeneous Bose fluids

International Nuclear Information System (INIS)

Gernoth, K.A.; Clark, J.W.; Ristig, M.L.

1994-06-01

In this paper, the variational Hartree-Jastrow theory of the ground state of spatially inhomogeneous Bose systems is extended to finite temperatures. The theory presented here is a generalization also in the sense that it extends the correlated density matrix approach, formulated previously for uniform Bose fluids, to systems with nonuniform density profiles. The method provides a framework in which the effects of thermal excitations on the spatial structure of a Bose fluid, as represented by the density profile and the two-body distribution functions, may be discussed on the basis on an ab initio microscopic description of the system. Thermal excitations make their appearance through self-consistently determined one-body and two-body potentials which enter the nonlinear, coupled Euler-Lagrange equations for the one-body density and for the pair distribution function. Since back-flow correlations are neglected, the excitations are described by a Feynman eigenvalue equation, suitably generalized to nonzero temperatures. The only external quantities entering the correlated density matrix theory elaborated here are the bare two-body interaction potential and, in actual applications, the boundary conditions to be imposed on the one-body density. 30 refs

Utilisation of spatial and temporal correlations in positron emission tomography

International Nuclear Information System (INIS)

Sureau, F.

2008-06-01

In this thesis we propose, implement, and evaluate algorithms improving spatial resolution in reconstructed images and reducing data noise in positron emission tomography imaging. These algorithms have been developed for a high resolution tomograph (HRRT) and applied to brain imaging, but can be used for other tomographs or studies. We first developed an iterative reconstruction algorithm including a stationary and isotropic model of resolution in image space, experimentally measured. We evaluated the impact of such a model of resolution in Monte-Carlo simulations, physical phantom experiments and in two clinical studies by comparing our algorithm with a reference reconstruction algorithm. This study suggests that biases due to partial volume effects are reduced, in particular in the clinical studies. Better spatial and temporal correlations are also found at the voxel level. However, other methods should be developed to further reduce data noise. We then proposed a maximum a posteriori de-noising algorithm that can be used for dynamic data to de-noise temporally raw data (sino-grams) or reconstructed images. The a priori modeled the coefficients in a wavelet basis of all the signals without noise (in an image or sinogram). We compared this technique with a reference de-noising method on replicated simulations. This illustrates the potential benefits of our approach of sinogram de-noising. (author)

Spatially heterogeneous dynamics investigated via a time-dependent four-point density correlation function

DEFF Research Database (Denmark)

Lacevic, N.; Starr, F. W.; Schrøder, Thomas

2003-01-01

correlation function g4(r,t) and corresponding "structure factor" S4(q,t) which measure the spatial correlations between the local liquid density at two points in space, each at two different times, and so are sensitive to dynamical heterogeneity. We study g4(r,t) and S4(q,t) via molecular dynamics......Relaxation in supercooled liquids above their glass transition and below the onset temperature of "slow" dynamics involves the correlated motion of neighboring particles. This correlated motion results in the appearance of spatially heterogeneous dynamics or "dynamical heterogeneity." Traditional...... two-point time-dependent density correlation functions, while providing information about the transient "caging" of particles on cooling, are unable to provide sufficiently detailed information about correlated motion and dynamical heterogeneity. Here, we study a four-point, time-dependent density...

Spatial correlations, clustering and percolation-like transitions in homicide crimes

Science.gov (United States)

Alves, L. G. A.; Lenzi, E. K.; Mendes, R. S.; Ribeiro, H. V.

2015-07-01

The spatial dynamics of criminal activities has been recently studied through statistical physics methods; however, models and results have been focusing on local scales (city level) and much less is known about these patterns at larger scales, e.g. at a country level. Here we report on a characterization of the spatial dynamics of the homicide crimes along the Brazilian territory using data from all cities (˜5000) in a period of more than thirty years. Our results show that the spatial correlation function in the per capita homicides decays exponentially with the distance between cities and that the characteristic correlation length displays an acute increasing trend in the latest years. We also investigate the formation of spatial clusters of cities via a percolation-like analysis, where clustering of cities and a phase-transition-like behavior describing the size of the largest cluster as a function of a homicide threshold are observed. This transition-like behavior presents evolutive features characterized by an increasing in the homicide threshold (where the transitions occur) and by a decreasing in the transition magnitudes (length of the jumps in the cluster size). We believe that our work sheds new light on the spatial patterns of criminal activities at large scales, which may contribute for better political decisions and resources allocation as well as opens new possibilities for modeling criminal activities by setting up fundamental empirical patterns at large scales.

Comparison of different spatial transformations applied to EEG data: A case study of error processing

NARCIS (Netherlands)

Cohen, M.X.

2015-01-01

The purpose of this paper is to compare the effects of different spatial transformations applied to the same scalp-recorded EEG data. The spatial transformations applied are two referencing schemes (average and linked earlobes), the surface Laplacian, and beamforming (a distributed source

Two-particle spatial correlations in superfluid nuclei

International Nuclear Information System (INIS)

Pillet, N.; Berger, J.-F.; Sandulescu, N.; Schuck, P.

2010-01-01

We discuss the effect of pairing on two-neutron space correlations in deformed nuclei. The spatial correlations are described by the pairing tensor in coordinate space calculated in the HFB approach. Calculations are done using the D1S Gogny force. We show that the pairing tensor has a rather small extension in the relative coordinate, a feature observed earlier in spherical nuclei. It is pointed out that in deformed nuclei the coherence length corresponding to the pairing tensor has a pattern similar to what we have found previously in spherical nuclei; that is, it is maximal in the interior of the nucleus and then it decreases rather rapidly in the surface region, where it reaches a minimal value of about 2 fm. This minimal value of the coherence length in the surface is essentially determined by the finite size properties of single-particle states in the vicinity of the chemical potential and has little to do with enhanced pairing correlations in the nuclear surface. It is shown that in nuclei the coherence length is not a good indicator of the intensity of pairing correlations. This feature is contrasted with the situation in infinite matter.

A DATA FIELD METHOD FOR URBAN REMOTELY SENSED IMAGERY CLASSIFICATION CONSIDERING SPATIAL CORRELATION

Directory of Open Access Journals (Sweden)

Y. Zhang

2016-06-01

Full Text Available Spatial correlation between pixels is important information for remotely sensed imagery classification. Data field method and spatial autocorrelation statistics have been utilized to describe and model spatial information of local pixels. The original data field method can represent the spatial interactions of neighbourhood pixels effectively. However, its focus on measuring the grey level change between the central pixel and the neighbourhood pixels results in exaggerating the contribution of the central pixel to the whole local window. Besides, Geary’s C has also been proven to well characterise and qualify the spatial correlation between each pixel and its neighbourhood pixels. But the extracted object is badly delineated with the distracting salt-and-pepper effect of isolated misclassified pixels. To correct this defect, we introduce the data field method for filtering and noise limitation. Moreover, the original data field method is enhanced by considering each pixel in the window as the central pixel to compute statistical characteristics between it and its neighbourhood pixels. The last step employs a support vector machine (SVM for the classification of multi-features (e.g. the spectral feature and spatial correlation feature. In order to validate the effectiveness of the developed method, experiments are conducted on different remotely sensed images containing multiple complex object classes inside. The results show that the developed method outperforms the traditional method in terms of classification accuracies.

Correlated cryo-fluorescence and cryo-electron microscopy with high spatial precision and improved sensitivity

International Nuclear Information System (INIS)

Schorb, Martin; Briggs, John A.G.

2014-01-01

Performing fluorescence microscopy and electron microscopy on the same sample allows fluorescent signals to be used to identify and locate features of interest for subsequent imaging by electron microscopy. To carry out such correlative microscopy on vitrified samples appropriate for structural cryo-electron microscopy it is necessary to perform fluorescence microscopy at liquid-nitrogen temperatures. Here we describe an adaptation of a cryo-light microscopy stage to permit use of high-numerical aperture objectives. This allows high-sensitivity and high-resolution fluorescence microscopy of vitrified samples. We describe and apply a correlative cryo-fluorescence and cryo-electron microscopy workflow together with a fiducial bead-based image correlation procedure. This procedure allows us to locate fluorescent bacteriophages in cryo-electron microscopy images with an accuracy on the order of 50 nm, based on their fluorescent signal. It will allow the user to precisely and unambiguously identify and locate objects and events for subsequent high-resolution structural study, based on fluorescent signals. - Highlights: • Workflow for correlated cryo-fluorescence and cryo-electron microscopy. • Cryo-fluorescence microscopy setup incorporating a high numerical aperture objective. • Fluorescent signals located in cryo-electron micrographs with 50 nm spatial precision

Correlated cryo-fluorescence and cryo-electron microscopy with high spatial precision and improved sensitivity

Energy Technology Data Exchange (ETDEWEB)

Schorb, Martin [Structural and Computational Biology Unit, European Molecular Biology Laboratory, D-69117 Heidelberg (Germany); Briggs, John A.G., E-mail: john.briggs@embl.de [Structural and Computational Biology Unit, European Molecular Biology Laboratory, D-69117 Heidelberg (Germany); Cell Biology and Biophysics Unit, European Molecular Biology Laboratory, D-69117 Heidelberg (Germany)

2014-08-01

Performing fluorescence microscopy and electron microscopy on the same sample allows fluorescent signals to be used to identify and locate features of interest for subsequent imaging by electron microscopy. To carry out such correlative microscopy on vitrified samples appropriate for structural cryo-electron microscopy it is necessary to perform fluorescence microscopy at liquid-nitrogen temperatures. Here we describe an adaptation of a cryo-light microscopy stage to permit use of high-numerical aperture objectives. This allows high-sensitivity and high-resolution fluorescence microscopy of vitrified samples. We describe and apply a correlative cryo-fluorescence and cryo-electron microscopy workflow together with a fiducial bead-based image correlation procedure. This procedure allows us to locate fluorescent bacteriophages in cryo-electron microscopy images with an accuracy on the order of 50 nm, based on their fluorescent signal. It will allow the user to precisely and unambiguously identify and locate objects and events for subsequent high-resolution structural study, based on fluorescent signals. - Highlights: • Workflow for correlated cryo-fluorescence and cryo-electron microscopy. • Cryo-fluorescence microscopy setup incorporating a high numerical aperture objective. • Fluorescent signals located in cryo-electron micrographs with 50 nm spatial precision.

Characterizing the spatial variations and correlations of large rainstorms for landslide study

Directory of Open Access Journals (Sweden)

L. Gao

2017-09-01

Full Text Available Rainfall is the primary trigger of landslides in Hong Kong; hence, rainstorm spatial distribution is an important piece of information in landslide hazard analysis. The primary objective of this paper is to quantify spatial correlation characteristics of three landslide-triggering large storms in Hong Kong. The spatial maximum rolling rainfall is represented by a rotated ellipsoid trend surface and a random field of residuals. The maximum rolling 4, 12, 24, and 36 h rainfall amounts of these storms are assessed via surface trend fitting, and the spatial correlation of the detrended residuals is determined through studying the scales of fluctuation along eight directions. The principal directions of the surface trend are between 19 and 43°, and the major and minor axis lengths are 83–386 and 55–79 km, respectively. The scales of fluctuation of the residuals are found between 5 and 30 km. The spatial distribution parameters for the three large rainstorms are found to be similar to those for four ordinary rainfall events. The proposed rainfall spatial distribution model and parameters help define the impact area, rainfall intensity and local topographic effects for landslide hazard evaluation in the future.

Investigation of spatial correlation in MR images of human cerebral white matter using geostatistical methods

Energy Technology Data Exchange (ETDEWEB)

Keil, Fabian

2014-03-20

Investigating the structure of human cerebral white matter is gaining interest in the neurological as well as in the neuroscientific community. It has been demonstrated in many studies that white matter is a very dynamic structure, rather than a static construct which does not change for a lifetime. That means, structural changes within white matter can be observed even on short timescales, e.g. in the course of normal ageing, neurodegenerative diseases or even during learning processes. To investigate these changes, one method of choice is the texture analysis of images obtained from white matter. In this regard, MRI plays a distinguished role as it provides a completely non-invasive way of acquiring in vivo images of human white matter. This thesis adapted a statistical texture analysis method, known as variography, to quantify the spatial correlation of human cerebral white matter based on MR images. This method, originally introduced in geoscience, relies on the idea of spatial correlation in geological phenomena: in naturally grown structures near things are correlated stronger to each other than distant things. This work reveals that the geological principle of spatial correlation can be applied to MR images of human cerebral white matter and proves that variography is an adequate method to quantify alterations therein. Since the process of MRI data acquisition is completely different to the measuring process used to quantify geological phenomena, the variographic analysis had to be adapted carefully to MR methods in order to provide a correctly working methodology. Therefore, theoretical considerations were evaluated with numerical samples in a first, and validated with real measurements in a second step. It was shown that MR variography facilitates to reduce the information stored in the texture of a white matter image to a few highly significant parameters, thereby quantifying heterogeneity and spatial correlation distance with an accuracy better than 5

Probing heterogeneous dynamics from spatial density correlation in glass-forming liquids.

Science.gov (United States)

Li, Yan-Wei; Zhu, You-Liang; Sun, Zhao-Yan

2016-12-01

We numerically investigate the connection between spatial density correlation and dynamical heterogeneity in glass-forming liquids. We demonstrate that the cluster size defined by the spatial aggregation of densely packed particles (DPPs) can better capture the difference between the dynamics of the Lennard-Jones glass model and the Weeks-Chandler-Andersen truncation model than the commonly used pair correlation functions. More interestingly, we compare the mobility of DPPs and loosely packed particles, and we find that high local density correlates well with slow dynamics in systems with relatively hard repulsive interactions but links to mobile ones in the system with soft repulsive interactions at one relaxation time scale. Our results show clear evidence that the above model dependence behavior stems from the hopping motion of DPPs at the end of the caging stage due to the compressive nature of soft repulsive spheres, which activates the dynamics of DPPs in the α relaxation stage.

Improved Side Information Generation for Distributed Video Coding by Exploiting Spatial and Temporal Correlations

Directory of Open Access Journals (Sweden)

Ye Shuiming

2009-01-01

Full Text Available Distributed video coding (DVC is a video coding paradigm allowing low complexity encoding for emerging applications such as wireless video surveillance. Side information (SI generation is a key function in the DVC decoder, and plays a key-role in determining the performance of the codec. This paper proposes an improved SI generation for DVC, which exploits both spatial and temporal correlations in the sequences. Partially decoded Wyner-Ziv (WZ frames, based on initial SI by motion compensated temporal interpolation, are exploited to improve the performance of the whole SI generation. More specifically, an enhanced temporal frame interpolation is proposed, including motion vector refinement and smoothing, optimal compensation mode selection, and a new matching criterion for motion estimation. The improved SI technique is also applied to a new hybrid spatial and temporal error concealment scheme to conceal errors in WZ frames. Simulation results show that the proposed scheme can achieve up to 1.0 dB improvement in rate distortion performance in WZ frames for video with high motion, when compared to state-of-the-art DVC. In addition, both the objective and perceptual qualities of the corrupted sequences are significantly improved by the proposed hybrid error concealment scheme, outperforming both spatial and temporal concealments alone.

Multivariate Receptor Models for Spatially Correlated Multipollutant Data

KAUST Repository

Jun, Mikyoung

2013-08-01

The goal of multivariate receptor modeling is to estimate the profiles of major pollution sources and quantify their impacts based on ambient measurements of pollutants. Traditionally, multivariate receptor modeling has been applied to multiple air pollutant data measured at a single monitoring site or measurements of a single pollutant collected at multiple monitoring sites. Despite the growing availability of multipollutant data collected from multiple monitoring sites, there has not yet been any attempt to incorporate spatial dependence that may exist in such data into multivariate receptor modeling. We propose a spatial statistics extension of multivariate receptor models that enables us to incorporate spatial dependence into estimation of source composition profiles and contributions given the prespecified number of sources and the model identification conditions. The proposed method yields more precise estimates of source profiles by accounting for spatial dependence in the estimation. More importantly, it enables predictions of source contributions at unmonitored sites as well as when there are missing values at monitoring sites. The method is illustrated with simulated data and real multipollutant data collected from eight monitoring sites in Harris County, Texas. Supplementary materials for this article, including data and R code for implementing the methods, are available online on the journal web site. © 2013 Copyright Taylor and Francis Group, LLC.

Effect of spatially correlated noise on coherence resonance in a network of excitable cells

International Nuclear Information System (INIS)

Kwon, Okyu; Jo, Hang-Hyun; Moon, Hie-Tae

2005-01-01

We study the effect of spatially correlated noise on coherence resonance (CR) in a Watts-Strogatz small-world network of Fitz Hugh-Nagumo neurons, where the noise correlation decays exponentially with distance between neurons. It is found that CR is considerably improved just by a small fraction of long-range connections for an intermediate coupling strength. For other coupling strengths, an abrupt change in CR occurs following the drastic fracture of the clustered structures in the network. Our study shows that spatially correlated noise plays a significant role in the phenomenon of CR reinforcing the role of the clustered structure of the system

Quantum diffraction and interference of spatially correlated photon pairs and its Fourier-optical analysis

International Nuclear Information System (INIS)

Shimizu, Ryosuke; Edamatsu, Keiichi; Itoh, Tadashi

2006-01-01

We present one- and two-photon diffraction and interference experiments involving parametric down-converted photon pairs. By controlling the divergence of the pump beam in parametric down-conversion, the diffraction-interference pattern produced by an object changes from a quantum (perfectly correlated) case to a classical (uncorrelated) one. The observed diffraction and interference patterns are accurately reproduced by Fourier-optical analysis taking into account the quantum spatial correlation. We show that the relation between the spatial correlation and the object size plays a crucial role in the formation of both one- and two-photon diffraction-interference patterns

Applying Spatial Audio to Human Interfaces: 25 Years of NASA Experience

Science.gov (United States)

Begault, Durand R.; Wenzel, Elizabeth M.; Godfrey, Martine; Miller, Joel D.; Anderson, Mark R.

2010-01-01

From the perspective of human factors engineering, the inclusion of spatial audio within a human-machine interface is advantageous from several perspectives. Demonstrated benefits include the ability to monitor multiple streams of speech and non-speech warning tones using a cocktail party advantage, and for aurally-guided visual search. Other potential benefits include the spatial coordination and interaction of multimodal events, and evaluation of new communication technologies and alerting systems using virtual simulation. Many of these technologies were developed at NASA Ames Research Center, beginning in 1985. This paper reviews examples and describes the advantages of spatial sound in NASA-related technologies, including space operations, aeronautics, and search and rescue. The work has involved hardware and software development as well as basic and applied research.

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

Science.gov (United States)

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.

Extending Correlation Filter-Based Visual Tracking by Tree-Structured Ensemble and Spatial Windowing.

Science.gov (United States)

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.

Estimates of spatial correlation in volcanic tuff, Yucca Mountain, Nevada: Yucca Mountain Site Characterization Project

International Nuclear Information System (INIS)

Rautman, C.A.

1991-02-01

The spatial correlation structure of volcanic tuffs at and near the site of the proposed high-level nuclear waste repository at Yucca Mountain, Nevada, is estimated using samples obtained from surface outcrops and drill holes. Data are examined for four rock properties: porosity, air permeability, saturated hydraulic conductivity, and dry bulk density. Spatial continuity patterns are identified in both lateral and vertical (stratigraphic) dimensions. The data are examined for the Calico Hills tuff stratigraphic unit and also without regard for stratigraphy. Variogram models fitted to the sample data from the tuffs of Calico Hills indicate that porosity is correlated laterally over distances of up to 3000 feet. If air permeability and saturated conductivity values are viewed as semi-interchangeable for purposes of identifying spatial structure, the data suggest a maximum range of correlation of 300 to 500 feet without any obvious horizontal to vertical anisotropy. Continuity exists over vertical distances of roughly 200 feet. Similar variogram models fitted to sample data taken from vertical drill holes without regard for stratigraphy suggest that correlation exists over distances of 500 to 800 feet for each rock property examined. Spatial correlation of rock properties violates the sample-independence assumptions of classical statistics to a degree not usually acknowledged. In effect, the existence of spatial structure reduces the ''equivalent'' number of samples below the number of physical samples. This reduction in the effective sampling density has important implications for site characterization for the Yucca Mountain Project. 19 refs., 43 figs., 5 tabs

Universal Spatial Correlation Functions for Describing and Reconstructing Soil Microstructure

Science.gov (United States)

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

Spatial Correlation in the Ambient Core Noise Field of a Turbofan Engine

Science.gov (United States)

Miles, Jeffrey Hilton

2012-01-01

An acoustic transfer function relating combustion noise and turbine exit noise in the presence of enclosed ambient core noise is investigated using a dynamic system model and an acoustic system model for the particular turbofan engine studied and for a range of operating conditions. Measurements of cross-spectra magnitude and phase between the combustor and turbine exit and auto-spectra at the turbine exit and combustor are used to show the presence of indirect and direct combustion noise over the frequency range of 0 400 Hz. The procedure used evaluates the ratio of direct to indirect combustion noise. The procedure used also evaluates the post-combustion residence time in the combustor which is a factor in the formation of thermal NOx and soot in this region. These measurements are masked by the ambient core noise sound field in this frequency range which is observable since the transducers are situated within an acoustic wavelength of one another. An ambient core noise field model based on one and two dimensional spatial correlation functions is used to replicate the spatially correlated response of the pair of transducers. The spatial correlation function increases measured attenuation due to destructive interference and masks the true attenuation of the turbine.

The Effect of Spatial Interference Correlation and Jamming on Secrecy in Cellular Networks

KAUST Repository

Ali, Konpal S.

2017-06-02

Recent studies on secure wireless communication have shed light on a scenario where interference has a desirable impact on network performance. Particularly, assuming independent interference-power fluctuations at the eavesdropper and the receiver, opportunistic secure-information transfer can occur on the legitimate-link. However, interference is spatially correlated due to the common set of interfering sources, which may diminish the opportunistic-secure-spectrum-access (OSSA) probability. We study and quantify the effect of spatial interference correlation on OSSA in cellular-networks and investigate the potential of full-duplex jamming (FDJ) solutions. The results highlight the scenarios where FDJ improves OSSA performance.

The Effect of Spatial Interference Correlation and Jamming on Secrecy in Cellular Networks

KAUST Repository

Ali, Konpal S.; Elsawy, Hesham; Haenggi, Martin; Alouini, Mohamed-Slim

2017-01-01

Recent studies on secure wireless communication have shed light on a scenario where interference has a desirable impact on network performance. Particularly, assuming independent interference-power fluctuations at the eavesdropper and the receiver, opportunistic secure-information transfer can occur on the legitimate-link. However, interference is spatially correlated due to the common set of interfering sources, which may diminish the opportunistic-secure-spectrum-access (OSSA) probability. We study and quantify the effect of spatial interference correlation on OSSA in cellular-networks and investigate the potential of full-duplex jamming (FDJ) solutions. The results highlight the scenarios where FDJ improves OSSA performance.

Decomposition of Variance for Spatial Cox Processes.

Science.gov (United States)

Jalilian, Abdollah; Guan, Yongtao; Waagepetersen, Rasmus

2013-03-01

Spatial Cox point processes is a natural framework for quantifying the various sources of variation governing the spatial distribution of rain forest trees. We introduce a general criterion for variance decomposition for spatial Cox processes and apply it to specific Cox process models with additive or log linear random intensity functions. We moreover consider a new and flexible class of pair correlation function models given in terms of normal variance mixture covariance functions. The proposed methodology is applied to point pattern data sets of locations of tropical rain forest trees.

Monte Carlo power iteration: Entropy and spatial correlations

International Nuclear Information System (INIS)

Nowak, Michel; Miao, Jilang; Dumonteil, Eric; Forget, Benoit; Onillon, Anthony; Smith, Kord S.; Zoia, Andrea

2016-01-01

Highlights: • We show that the entropy function might be misleading in criticality simulations. • We interpret the spatial fluctuations of the fission chains in terms of the key parameters of the simulated system. • We show that the behavior of the entropy function is related to the theory of neutron clustering. - Abstract: The behavior of Monte Carlo criticality simulations is often assessed by examining the convergence of the so-called entropy function. In this work, we shall show that the entropy function may lead to a misleading interpretation, and that potential issues occur when spatial correlations induced by fission events are important. We will support our analysis by examining the higher-order moments of the entropy function and the center of mass of the neutron population. Within the framework of a simplified model based on branching processes, we will relate the behavior of the spatial fluctuations of the fission chains to the key parameters of the simulated system, namely, the number of particles per generation, the reactor size and the migration area. Numerical simulations of a fuel rod and of a whole core suggest that the obtained results are quite general and hold true also for real-world applications.

Tools for Multimode Quantum Information: Modulation, Detection, and Spatial Quantum Correlations

DEFF Research Database (Denmark)

Lassen, Mikael Østergaard; Delaubert, Vincent; Janousek, Jirí

2007-01-01

We present here all the tools required for continuous variable parallel quantum information protocols based on spatial multi-mode quantum correlations and entanglement. We describe techniques for encoding and detecting this quantum information with high efficiency in the individual modes. We use ...

Understanding structure of urban traffic network based on spatial-temporal correlation analysis

Science.gov (United States)

Yang, Yanfang; Jia, Limin; Qin, Yong; Han, Shixiu; Dong, Honghui

2017-08-01

Understanding the structural characteristics of urban traffic network comprehensively can provide references for improving road utilization rate and alleviating traffic congestion. This paper focuses on the spatial-temporal correlations between different pairs of traffic series and proposes a complex network-based method of constructing the urban traffic network. In the 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 spatial-temporal correlation. Further, a modified PageRank algorithm, named the geographical weight-based PageRank algorithm (GWPA), is proposed to analyze the spatial distribution of important segments in the road network. Finally, experiments are conducted by using three kinds of traffic series collected from the urban road network in Beijing. Experimental results show that the urban traffic networks constructed by three traffic variables all indicate both small-world and scale-free characteristics. Compared with the results of PageRank algorithm, GWPA is proved to be valid in evaluating the importance of segments and identifying the important segments with small degree.

Spatial Correlation Characterization of a Full Dimension Massive MIMO System

KAUST Repository

Nadeem, Qurrat-Ul-Ain

2017-02-07

Elevation beamforming and Full Dimension MIMO (FD-MIMO) are currently active areas of research and standardization in 3GPP LTE-Advanced. FD-MIMO utilizes an active antenna array system (AAS), that provides the ability of adaptive electronic beam control over the elevation dimension, resulting in a better system performance as compared to the conventional 2D MIMO systems. FD-MIMO is more advantageous when amalgamated with massive MIMO systems, in that it exploits the additional degrees of freedom offered by a large number of antennas in the elevation. To facilitate the evaluation of these systems, a large effort in 3D channel modeling is needed. This paper aims at providing a summary of the recent 3GPP activity around 3D channel modeling. The 3GPP proposed approach to model antenna radiation pattern is compared with the ITU approach. A closed-form expression is then worked out for the spatial correlation function (SCF) for channels constituted by individual antenna elements in the array by exploiting results on spherical harmonics and Legendre polynomials. The proposed expression can be used to obtain correlation coefficients for any arbitrary 3D propagation environment. Simulation results corroborate and study the derived spatial correlation expression. The results are directly applicable to the analysis of future 5G 3D massive MIMO systems.

Modelling the distribution of fish accounting for spatial correlation and overdispersion

DEFF Research Database (Denmark)

Lewy, Peter; Kristensen, Kasper

2009-01-01

correlation between observations. It is therefore possible to predict and interpolate unobserved densities at any location in the area. This is important for obtaining unbiased estimates of stock concentration and other measures depending on the distribution in the entire area. Results show that the spatial...

Effect of spatially correlated noise on stochastic synchronization in globally coupled FitzHugh-Nagumo neuron systems

Directory of Open Access Journals (Sweden)

Yange Shao

2014-01-01

Full Text Available The phenomenon of stochastic synchronization in globally coupled FitzHugh-Nagumo (FHN neuron system subjected to spatially correlated Gaussian noise is investigated based on dynamical mean-field approximation (DMA and direct simulation (DS. Results from DMA are in good quantitative or qualitative agreement with those from DS for weak noise intensity and larger system size. Whether the consisting single FHN neuron is staying at the resting state, subthreshold oscillatory regime, or the spiking state, our investigation shows that the synchronization ratio of the globally coupled system becomes higher as the noise correlation coefficient increases, and thus we conclude that spatial correlation has an active effect on stochastic synchronization, and the neurons can achieve complete synchronization in the sense of statistics when the noise correlation coefficient tends to one. Our investigation also discloses that the noise spatial correlation plays the same beneficial role as the global coupling strength in enhancing stochastic synchronization in the ensemble. The result might be useful in understanding the information coding mechanism in neural systems.

Managing the spatial properties and photon correlations in squeezed non-classical twisted light

Science.gov (United States)

Zakharov, R. V.; Tikhonova, O. V.

2018-05-01

Spatial photon correlations and mode content of the squeezed vacuum light generated in a system of two separated nonlinear crystals is investigated. The contribution of both the polar and azimuthal modes with non-zero orbital angular momentum is analyzed. The control and engineering of the spatial properties and degree of entanglement of the non-classical squeezed light by changing the distance between crystals and pump parameters is demonstrated. Methods for amplification of certain spatial modes and managing the output mode content and intensity profile of quantum twisted light are suggested.

Ergodic channel capacity of spatial correlated multiple-input multiple-output free space optical links using multipulse pulse-position modulation

Science.gov (United States)

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.

Spatial correlation of the ionsphere total electron content at the equatorial anomaly crest

International Nuclear Information System (INIS)

Huang, Y.

1984-01-01

The spatial correlation of the ionospheric total electron content (TEC) at the equatorial anomaly crest was studied by recording Faraday rotation angle of the ETS-II geostationary satellite at Lunping and Kaohsiung whose subionospheric points are located at 23.0 0 N, 121.0 0 N, and 20.9 0 N, 121.1 0 E, respectively, and are about 280 km apart. The results show that the spatial correlation of TEC at the equatorial crest region is smaller than that at other places. The day-to-day variabilities of TEC differences between two subionospheric points are quite large. The day-to-day variabilities of the fountain effect seem to play an important role

Generating Improved Experimental Designs with Spatially and Genetically Correlated Observations Using Mixed Models

Directory of Open Access Journals (Sweden)

Lazarus K. Mramba

2018-03-01

Full Text Available The aim of this study was to generate and evaluate the efficiency of improved field experiments while simultaneously accounting for spatial correlations and different levels of genetic relatedness using a mixed models framework for orthogonal and non-orthogonal designs. Optimality criteria and a search algorithm were implemented to generate randomized complete block (RCB, incomplete block (IB, augmented block (AB and unequally replicated (UR designs. Several conditions were evaluated including size of the experiment, levels of heritability, and optimality criteria. For RCB designs with half-sib or full-sib families, the optimization procedure yielded important improvements under the presence of mild to strong spatial correlation levels and relatively low heritability values. Also, for these designs, improvements in terms of overall design efficiency (ODE% reached values of up to 8.7%, but these gains varied depending on the evaluated conditions. In general, for all evaluated designs, higher ODE% values were achieved from genetically unrelated individuals compared to experiments with half-sib and full-sib families. As expected, accuracy of prediction of genetic values improved as levels of heritability and spatial correlations increased. This study has demonstrated that important improvements in design efficiency and prediction accuracies can be achieved by optimizing how the levels of a treatment are assigned to the experimental units.

Nearest neighbor imputation using spatial-temporal correlations in wireless sensor networks.

Science.gov (United States)

Li, YuanYuan; Parker, Lynne E

2014-01-01

Missing data is common in Wireless Sensor Networks (WSNs), especially with multi-hop communications. There are many reasons for this phenomenon, such as unstable wireless communications, synchronization issues, and unreliable sensors. Unfortunately, missing data creates a number of problems for WSNs. First, since most sensor nodes in the network are battery-powered, it is too expensive to have the nodes retransmit missing data across the network. Data re-transmission may also cause time delays when detecting abnormal changes in an environment. Furthermore, localized reasoning techniques on sensor nodes (such as machine learning algorithms to classify states of the environment) are generally not robust enough to handle missing data. Since sensor data collected by a WSN is generally correlated in time and space, we illustrate how replacing missing sensor values with spatially and temporally correlated sensor values can significantly improve the network's performance. However, our studies show that it is important to determine which nodes are spatially and temporally correlated with each other. Simple techniques based on Euclidean distance are not sufficient for complex environmental deployments. Thus, we have developed a novel Nearest Neighbor (NN) imputation method that estimates missing data in WSNs by learning spatial and temporal correlations between sensor nodes. To improve the search time, we utilize a k d-tree data structure, which is a non-parametric, data-driven binary search tree. Instead of using traditional mean and variance of each dimension for k d-tree construction, and Euclidean distance for k d-tree search, we use weighted variances and weighted Euclidean distances based on measured percentages of missing data. We have evaluated this approach through experiments on sensor data from a volcano dataset collected by a network of Crossbow motes, as well as experiments using sensor data from a highway traffic monitoring application. Our experimental

Spatial- and Time-Correlated Detection of Fission Fragments

Directory of Open Access Journals (Sweden)

Platkevic M.

2012-02-01

Full Text Available With the goal to measure angular correlations of fission fragments in rare fission decay (e.g. ternary and quaternary fission, a multi-detector coincidence system based on two and up to four position sensitive pixel detectors Timepix has been built. In addition to the high granularity, wide dynamic range and per pixel signal threshold, these devices are equipped with per pixel energy and time sensitivity providing more information (position, energy, time, enhances particle-type identification and selectivity of event-by-event detection. Operation of the device with the integrated USB 2.0 based readout interface FITPix and the control and data acquisition software tool Pixelman enables online visualization and flexible/adjustable operation for a different type of experiments. Spatially correlated fission fragments can be thus registered in coincidence. Similarly triggered measurements are performed using an integrated spectrometric module with analogue signal chain electronics. The current status of development together with demonstration of the technique with a 252Cf source is presented.

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

OpenAIRE

Stephenson, D. B.

2011-01-01

he skill in predicting spatially varying weather/climate maps depends on the definition of the measure of similarity between the maps. Under the justifiable approximation that the anomaly maps are distributed multinormally, it is shown analytically that the choice of weighting metric, used in defining the anomaly correlation between spatial maps, can change the resulting probability distribution of the correlation coefficient. The estimate of the numbers of degrees of freedom based on the var...

Augmented GNSS Differential Corrections Minimum Mean Square Error Estimation Sensitivity to Spatial Correlation Modeling Errors

Directory of Open Access Journals (Sweden)

Nazelie Kassabian

2014-06-01

Full Text Available Railway signaling is a safety system that has evolved over the last couple of centuries towards autonomous functionality. Recently, great effort is being devoted in this field, towards the use and exploitation of Global Navigation Satellite System (GNSS signals and GNSS augmentation systems in view of lower railway track equipments and maintenance costs, that is a priority to sustain the investments for modernizing the local and regional lines most of which lack automatic train protection systems and are still manually operated. The objective of this paper is to assess the sensitivity of the Linear Minimum Mean Square Error (LMMSE algorithm to modeling errors in the spatial correlation function that characterizes true pseudorange Differential Corrections (DCs. This study is inspired by the railway application; however, it applies to all transportation systems, including the road sector, that need to be complemented by an augmentation system in order to deliver accurate and reliable positioning with integrity specifications. A vector of noisy pseudorange DC measurements are simulated, assuming a Gauss-Markov model with a decay rate parameter inversely proportional to the correlation distance that exists between two points of a certain environment. The LMMSE algorithm is applied on this vector to estimate the true DC, and the estimation error is compared to the noise added during simulation. The results show that for large enough correlation distance to Reference Stations (RSs distance separation ratio values, the LMMSE brings considerable advantage in terms of estimation error accuracy and precision. Conversely, the LMMSE algorithm may deteriorate the quality of the DC measurements whenever the ratio falls below a certain threshold.

Spatial accuracy of a simplified disaggregation method for traffic emissions applied in seven mid-sized Chilean cities

Science.gov (United States)

Ossés de Eicker, Margarita; Zah, Rainer; Triviño, Rubén; Hurni, Hans

The spatial accuracy of top-down traffic emission inventory maps obtained with a simplified disaggregation method based on street density was assessed in seven mid-sized Chilean cities. Each top-down emission inventory map was compared against a reference, namely a more accurate bottom-up emission inventory map from the same study area. The comparison was carried out using a combination of numerical indicators and visual interpretation. Statistically significant differences were found between the seven cities with regard to the spatial accuracy of their top-down emission inventory maps. In compact cities with a simple street network and a single center, a good accuracy of the spatial distribution of emissions was achieved with correlation values>0.8 with respect to the bottom-up emission inventory of reference. In contrast, the simplified disaggregation method is not suitable for complex cities consisting of interconnected nuclei, resulting in correlation valuessituation to get an overview on the spatial distribution of the emissions generated by traffic activities.

Applying Spatially Distributed Rainfall to a Hydrological Model in a Tropical Watershed, Manoa Watershed, in Hawaii

Science.gov (United States)

Huang, Y. F.; Tsang, Y. P.

2017-12-01

Rainfall in Hawaii is characterized with high spatial and temporal variability. In the south side of Oahu, the Manoa watershed, with an area of 11 km2, has the annual maximum rainfall of 3900mm and the minimum rainfall of 1000 mm. Despite this high spatial heterogeneity, the rain gage network seems insufficiently capture this pattern. When simulating stream flow and predicting floods with hydrological models in Hawaii, the model performance is often unsatisfactory because of inadequate representation of rainfall data. Longman et al. (in prep.) have developed the spatially distributed daily rainfall across the Hawaiian Islands by applying ordinary kriging, yet these data have not been applied to hydrological models. In this study, we used the Soil and Water Assessment Tool (SWAT) model to assess the streamflow simulation by applying spatially-distributed rainfall in the Manoa watershed. We first used point daily-rainfall at Lyon Arboretum from National Center of Environmental Information (NCEI) as the uniform rainfall input. Secondly, we summarized sub-watershed mean rainfall from the daily spatial-statistical rainfall. Both rainfall data are available from 1999 to 2014. The SWAT was set up for five-year warm-up, nine-year calibration, and two-year validation. The model parameters were calibrated and validated with four U.S. Geological Survey stream gages. We compared the calibrated watershed parameters, characteristics, and assess the streamflow hydrographs from these two rainfall inputs. The differences and improvement of using spatially distributed rainfall input in SWAT were discussed. In addition to improving the model by the representation of rainfall, this study helped us having a better understanding of the watershed hydrological response in Hawaii.

Improving Geoscience Students' Spatial Thinking Skills: Applying Cognitive Science Research in the Classroom

Science.gov (United States)

Ormand, C. J.; Shipley, T. F.; Manduca, C. A.; Tikoff, B.

2011-12-01

Spatial thinking skills are critical to success in many subdisciplines of the geosciences (and beyond). There are many components of spatial thinking, such as mental rotation, penetrative visualization, disembedding, perspective taking, and navigation. Undergraduate students in introductory and upper-level geoscience courses bring a wide variety of spatial skill levels to the classroom, as measured by psychometric tests of many of these components of spatial thinking. Furthermore, it is not unusual for individual students to excel in some of these areas while struggling in others. Although pre- and post-test comparisons show that student skill levels typically improve over the course of an academic term, average gains are quite modest. This suggests that it may be valuable to develop interventions to help undergraduate students develop a range of spatial skills that can be used to solve geoscience problems. Cognitive science research suggests a number of strong strategies for building students' spatial skills. Practice is essential, and time on task is correlated to improvement. Progressive alignment may be used to scaffold students' successes on simpler problems, allowing them to see how more complex problems are related to those they can solve. Gesturing has proven effective in moving younger students from incorrect problem-solving strategies to correct strategies in other disciplines. These principles can be used to design instructional materials to improve undergraduate geoscience students' spatial skills; we will present some examples of such materials.

Overcoming artificial spatial correlations in simulations of superstructure domain growth with parallel Monte Carlo algorithms

International Nuclear Information System (INIS)

Schleier, W.; Besold, G.; Heinz, K.

1992-01-01

The authors study the applicability of parallelized/vectorized Monte Carlo (MC) algorithms to the simulation of domain growth in two-dimensional lattice gas models undergoing an ordering process after a rapid quench below an order-disorder transition temperature. As examples they consider models with 2 x 1 and c(2 x 2) equilibrium superstructures on the square and rectangular lattices, respectively. They also study the case of phase separation ('1 x 1' islands) on the square lattice. A generalized parallel checkerboard algorithm for Kawasaki dynamics is shown to give rise to artificial spatial correlations in all three models. However, only if superstructure domains evolve do these correlations modify the kinetics by influencing the nucleation process and result in a reduced growth exponent compared to the value from the conventional heat bath algorithm with random single-site updates. In order to overcome these artificial modifications, two MC algorithms with a reduced degree of parallelism ('hybrid' and 'mask' algorithms, respectively) are presented and applied. As the results indicate, these algorithms are suitable for the simulation of superstructure domain growth on parallel/vector computers. 60 refs., 10 figs., 1 tab

Quantum metrology subject to spatially correlated Markovian noise: restoring the Heisenberg limit

International Nuclear Information System (INIS)

Jeske, Jan; Cole, Jared H; Huelga, Susana F

2014-01-01

Environmental noise can hinder the metrological capabilities of entangled states. While the use of entanglement allows for Heisenberg-limited resolution, the largest permitted by quantum mechanics, deviations from strictly unitary dynamics quickly restore the standard scaling dictated by the central limit theorem. Product and maximally entangled states become asymptotically equivalent when the noisy evolution is both local and strictly Markovian. However, temporal correlations in the noise have been shown to lift this equivalence while fully (spatially) correlated noise allows for the identification of decoherence-free subspaces. Here we analyze precision limits in the presence of noise with finite correlation length and show that there exist robust entangled state preparations which display persistent Heisenberg scaling despite the environmental decoherence, even for small correlation length. Our results emphasize the relevance of noise correlations in the study of quantum advantage and could be relevant beyond metrological applications. (paper)

Quantifying spatial scaling patterns and their local and regional correlates in headwater streams: Implications for resilience

Science.gov (United States)

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.

The change in spatial distribution of upper trapezius muscle activity is correlated to contraction duration.

Science.gov (United States)

Farina, Dario; Leclerc, Frédéric; Arendt-Nielsen, Lars; Buttelli, Olivier; Madeleine, Pascal

2008-02-01

The aim of the study was to confirm the hypothesis that the longer a contraction is sustained, the larger are the changes in the spatial distribution of muscle activity. For this purpose, surface electromyographic (EMG) signals were recorded with a 13 x 5 grid of electrodes from the upper trapezius muscle of 11 healthy male subjects during static contractions with shoulders 90 degrees abducted until endurance. The entropy (degree of uniformity) and center of gravity of the EMG root mean square map were computed to assess spatial inhomogeneity in muscle activation and changes over time in EMG amplitude spatial distribution. At the endurance time, entropy decreased (mean+/-SD, percent change 2.0+/-1.6%; Pgrid) root mean square was positively correlated with the shift in the center of gravity (R(2)=0.51, P<0.05). Moreover, the shift in the center of gravity was negatively correlated to both initial and final (at the endurance) entropy (R(2)=0.54 and R(2)=0.56, respectively; P<0.01 in both cases), indicating that subjects with less uniform root mean square maps had larger shift of the center of gravity over time. The spatial changes in root mean square EMG were likely due to spatially-dependent changes in motor unit activation during the sustained contraction. It was concluded that the changes in spatial muscle activity distribution play a role in the ability to maintain a static contraction.

Laser correlation velocimetry performance in diesel applications: spatial selectivity and velocity sensitivity

Energy Technology Data Exchange (ETDEWEB)

Hespel, Camille [Universite d' Orleans, Laboratoire PRISME, Orleans (France); Blaisot, Jean-Bernard; Gazon, Matthieu; Godard, Gilles [CORIA, UMR 6614, CNRS, Universite et INSA de Rouen, Saint Etienne du Rouvray (France)

2012-07-15

The characterization of diesel jets in the near field of the nozzle exit still presents challenges for experimenters. Detailed velocity measurements are needed to characterize diesel injector performance and also to establish boundary conditions for CFD codes. The present article examines the efficiency of laser correlation velocimetry (LCV) applied to diesel spray characterization. A new optical configuration based on a long-distance microscope was tested, and special care was taken to examine the spatial selectivity of the technique. Results show that the depth of the measurement volume (along the laser beam) of LCV extends beyond the depth of field of the imaging setup. The LCV results were also found to be particularly sensitive to high-speed elements of a spray. Results from high-pressure diesel jets in a back-pressure environment indicate that this technique is particularly suited to the very near field of the nozzle exit, where the flow is the narrowest and where the velocity distribution is not too large. It is also shown that the performance of the LCV technique is controlled by the filtering and windowing parameters used in the processing of the raw signals. (orig.)

Laser correlation velocimetry performance in diesel applications: spatial selectivity and velocity sensitivity

Science.gov (United States)

Hespel, Camille; Blaisot, Jean-Bernard; Gazon, Matthieu; Godard, Gilles

2012-07-01

The characterization of diesel jets in the near field of the nozzle exit still presents challenges for experimenters. Detailed velocity measurements are needed to characterize diesel injector performance and also to establish boundary conditions for CFD codes. The present article examines the efficiency of laser correlation velocimetry (LCV) applied to diesel spray characterization. A new optical configuration based on a long-distance microscope was tested, and special care was taken to examine the spatial selectivity of the technique. Results show that the depth of the measurement volume (along the laser beam) of LCV extends beyond the depth of field of the imaging setup. The LCV results were also found to be particularly sensitive to high-speed elements of a spray. Results from high-pressure diesel jets in a back-pressure environment indicate that this technique is particularly suited to the very near field of the nozzle exit, where the flow is the narrowest and where the velocity distribution is not too large. It is also shown that the performance of the LCV technique is controlled by the filtering and windowing parameters used in the processing of the raw signals.

The correlated k-distribution technique as applied to the AVHRR channels

Science.gov (United States)

Kratz, David P.

1995-01-01

Correlated k-distributions have been created to account for the molecular absorption found in the spectral ranges of the five Advanced Very High Resolution Radiometer (AVHRR) satellite channels. The production of the k-distributions was based upon an exponential-sum fitting of transmissions (ESFT) technique which was applied to reference line-by-line absorptance calculations. To account for the overlap of spectral features from different molecular species, the present routines made use of the multiplication transmissivity property which allows for considerable flexibility, especially when altering relative mixing ratios of the various molecular species. To determine the accuracy of the correlated k-distribution technique as compared to the line-by-line procedure, atmospheric flux and heating rate calculations were run for a wide variety of atmospheric conditions. For the atmospheric conditions taken into consideration, the correlated k-distribution technique has yielded results within about 0.5% for both the cases where the satellite spectral response functions were applied and where they were not. The correlated k-distribution's principal advantages is that it can be incorporated directly into multiple scattering routines that consider scattering as well as absorption by clouds and aerosol particles.

Characterizing short-range vs. long-range spatial correlations in dislocation distributions

International Nuclear Information System (INIS)

Chevy, Juliette; Fressengeas, Claude; Lebyodkin, Mikhail; Taupin, Vincent; Bastie, Pierre; Duval, Paul

2010-01-01

Hard X-ray diffraction experiments have provided evidence of a strongly heterogeneous distribution of dislocation densities along the axis of cylindrical ice single crystals oriented for basal slip in torsion creep. The dislocation arrangements showed a complex scale-invariant character, which was analyzed by means of statistical and multifractal techniques. A trend to decreasing autocorrelation of the dislocation distribution was observed as deformation proceeds. At low strain levels, long-range spatial correlations control the distribution, but short-range correlations in relation with cross-slip progressively prevail when strain increases. This trend was reproduced by a model based on field dislocation dynamics, a theory accounting for both long-range elastic interactions and short-range interactions through transport of dislocation densities.

Characterizing short-range vs. long-range spatial correlations in dislocation distributions

Energy Technology Data Exchange (ETDEWEB)

Chevy, Juliette, E-mail: juliette.chevy@gmail.com [Laboratoire de Glaciologie et Geophysique de l' Environnement-CNRS, 54 rue Moliere, 38402 St. Martin d' Heres (France)] [Laboratoire Science et Ingenierie des Materiaux et Procedes, Grenoble INP-CNRS-UJF, BP 75, 38402 St. Martin d' Heres Cedex (France); Fressengeas, Claude; Lebyodkin, Mikhail; Taupin, Vincent [Laboratoire de Physique et Mecanique des Materiaux, Universite Paul Verlaine-Metz/CNRS, Ile du Saulcy, 57045 Metz Cedex (France); Bastie, Pierre [Laboratoire de Spectrometrie Physique, BP 87, 38402 St. Martin d' Heres Cedex (France)] [Institut Laue Langevin, BP 156, 38042 Grenoble Cedex 9 (France); Duval, Paul [Laboratoire de Glaciologie et Geophysique de l' Environnement-CNRS, 54 rue Moliere, 38402 St. Martin d' Heres (France)

2010-03-15

Hard X-ray diffraction experiments have provided evidence of a strongly heterogeneous distribution of dislocation densities along the axis of cylindrical ice single crystals oriented for basal slip in torsion creep. The dislocation arrangements showed a complex scale-invariant character, which was analyzed by means of statistical and multifractal techniques. A trend to decreasing autocorrelation of the dislocation distribution was observed as deformation proceeds. At low strain levels, long-range spatial correlations control the distribution, but short-range correlations in relation with cross-slip progressively prevail when strain increases. This trend was reproduced by a model based on field dislocation dynamics, a theory accounting for both long-range elastic interactions and short-range interactions through transport of dislocation densities.

Quantifying spatial scaling patterns and their local and regional correlates in headwater streams: implications for resilience

Directory of Open Access Journals (Sweden)

Emma Göthe

2014-09-01

Full Text Available 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.

The SPAtial EFficiency metric (SPAEF): multiple-component evaluation of spatial patterns for optimization of hydrological models

Science.gov (United States)

Koch, Julian; Cüneyd Demirel, Mehmet; Stisen, Simon

2018-05-01

The process of model evaluation is not only an integral part of model development and calibration but also of paramount importance when communicating modelling results to the scientific community and stakeholders. The modelling community has a large and well-tested toolbox of metrics to evaluate temporal model performance. In contrast, spatial performance evaluation does not correspond to the grand availability of spatial observations readily available and to the sophisticate model codes simulating the spatial variability of complex hydrological processes. This study makes a contribution towards advancing spatial-pattern-oriented model calibration by rigorously testing a multiple-component performance metric. The promoted SPAtial EFficiency (SPAEF) metric reflects three equally weighted components: correlation, coefficient of variation and histogram overlap. This multiple-component approach is found to be advantageous in order to achieve the complex task of comparing spatial patterns. SPAEF, its three components individually and two alternative spatial performance metrics, i.e. connectivity analysis and fractions skill score, are applied in a spatial-pattern-oriented model calibration of a catchment model in Denmark. Results suggest the importance of multiple-component metrics because stand-alone metrics tend to fail to provide holistic pattern information. The three SPAEF components are found to be independent, which allows them to complement each other in a meaningful way. In order to optimally exploit spatial observations made available by remote sensing platforms, this study suggests applying bias insensitive metrics which further allow for a comparison of variables which are related but may differ in unit. This study applies SPAEF in the hydrological context using the mesoscale Hydrologic Model (mHM; version 5.8), but we see great potential across disciplines related to spatially distributed earth system modelling.

The Effect of Velocity Correlation on the Spatial Evolution of Breakthrough Curves in Heterogeneous Media

Science.gov (United States)

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.

Frequency and spatial correlation functions in a fading communication channel through the ionosphere

International Nuclear Information System (INIS)

Liu, C.H.; Yeh, K.C.

1975-01-01

Equations for the two-frequency two-position mutual coherence functions are derived under the usual parabolic and Markov approximations. These equations are then solved numerically. It is shown that the mutual coherence functions occur naturally in the study of pulse distortion through a random communication channel and in the investigation of signal correlations. Contour plots of correlation functions show the possibility of having equal values at two frequency separations for a given spatial separation. This behavior is explainable in terms of overlapping Fresnel zones

Latent spatial models and sampling design for landscape genetics

Science.gov (United States)

Hanks, Ephraim M.; Hooten, Mevin B.; Knick, Steven T.; Oyler-McCance, Sara J.; Fike, Jennifer A.; Cross, Todd B.; Schwartz, Michael K.

2016-01-01

We propose a spatially-explicit approach for modeling genetic variation across space and illustrate how this approach can be used to optimize spatial prediction and sampling design for landscape genetic data. We propose a multinomial data model for categorical microsatellite allele data commonly used in landscape genetic studies, and introduce a latent spatial random effect to allow for spatial correlation between genetic observations. We illustrate how modern dimension reduction approaches to spatial statistics can allow for efficient computation in landscape genetic statistical models covering large spatial domains. We apply our approach to propose a retrospective spatial sampling design for greater sage-grouse (Centrocercus urophasianus) population genetics in the western United States.

Linear mixing model applied to coarse spatial resolution data from multispectral satellite sensors

Science.gov (United States)

Holben, Brent N.; Shimabukuro, Yosio E.

1993-01-01

A linear mixing model was applied to coarse spatial resolution data from the NOAA Advanced Very High Resolution Radiometer. The reflective component of the 3.55-3.95 micron channel was used with the two reflective channels 0.58-0.68 micron and 0.725-1.1 micron to run a constrained least squares model to generate fraction images for an area in the west central region of Brazil. The fraction images were compared with an unsupervised classification derived from Landsat TM data acquired on the same day. The relationship between the fraction images and normalized difference vegetation index images show the potential of the unmixing techniques when using coarse spatial resolution data for global studies.

Flow distributions and spatial correlations in human brain capillary networks

Science.gov (United States)

Lorthois, Sylvie; Peyrounette, Myriam; Larue, Anne; Le Borgne, Tanguy

2015-11-01

The vascular system of the human brain cortex is composed of a space filling mesh-like capillary network connected upstream and downstream to branched quasi-fractal arterioles and venules. The distribution of blood flow rates in these networks may affect the efficiency of oxygen transfer processes. Here, we investigate the distribution and correlation properties of blood flow velocities from numerical simulations in large 3D human intra-cortical vascular network (10000 segments) obtained from an anatomical database. In each segment, flow is solved from a 1D non-linear model taking account of the complex rheological properties of blood flow in microcirculation to deduce blood pressure, blood flow and red blood cell volume fraction distributions throughout the network. The network structural complexity is found to impart broad and spatially correlated Lagrangian velocity distributions, leading to power law transit time distributions. The origins of this behavior (existence of velocity correlations in capillary networks, influence of the coupling with the feeding arterioles and draining veins, topological disorder, complex blood rheology) are studied by comparison with results obtained in various model capillary networks of controlled disorder. ERC BrainMicroFlow GA615102, ERC ReactiveFronts GA648377.

A new maximum likelihood blood velocity estimator incorporating spatial and temporal correlation

DEFF Research Database (Denmark)

Schlaikjer, Malene; Jensen, Jørgen Arendt

2001-01-01

and space. This paper presents a new estimator (STC-MLE), which incorporates the correlation property. It is an expansion of the maximum likelihood estimator (MLE) developed by Ferrara et al. With the MLE a cross-correlation analysis between consecutive RF-lines on complex form is carried out for a range...... of possible velocities. In the new estimator an additional similarity investigation for each evaluated velocity and the available velocity estimates in a temporal (between frames) and spatial (within frames) neighborhood is performed. An a priori probability density term in the distribution...... of the observations gives a probability measure of the correlation between the velocities. Both the MLE and the STC-MLE have been evaluated on simulated and in-vivo RF-data obtained from the carotid artery. Using the MLE 4.1% of the estimates deviate significantly from the true velocities, when the performance...

Impact of Non-Idealities System on Spatial Correlation in a Multi-Probe Based MIMO OTA Setup

DEFF Research Database (Denmark)

Fan, Wei; Nielsen, Jesper Ødum; Carreño, Xavier

2013-01-01

MIMO OTA testing methodologies are being intensively investigated by CTIA and 3GPP, where a multi-probe anechoic chamber based solution is an important candidate for future standardized testing. In this paper, the probes located on an OTA ring are used to reproduce the channel spatial information....... This paper investigates the extent to which we can emulate the channel spatial characteristics inside the test zone where the device under test is located. The focus is on performance deterioration introduced by system non-idealities on spatial correlation emulation in practical MIMO OTA test systems....

Impact of spatially correlated pore-scale heterogeneity on drying porous media

Science.gov (United States)

Borgman, Oshri; Fantinel, Paolo; Lühder, Wieland; Goehring, Lucas; Holtzman, Ran

2017-07-01

We study the effect of spatially-correlated heterogeneity on isothermal drying of porous media. We combine a minimal pore-scale model with microfluidic experiments with the same pore geometry. Our simulated drying behavior compares favorably with experiments, considering the large sensitivity of the emergent behavior to the uncertainty associated with even small manufacturing errors. We show that increasing the correlation length in particle sizes promotes preferential drying of clusters of large pores, prolonging liquid connectivity and surface wetness and thus higher drying rates for longer periods. Our findings improve our quantitative understanding of how pore-scale heterogeneity impacts drying, which plays a role in a wide range of processes ranging from fuel cells to curing of paints and cements to global budgets of energy, water and solutes in soils.

Spatial correlation characterization of a uniform circular array in 3D MIMO systems

KAUST Repository

Nadeem, Qurrat-Ul-Ain; Kammoun, Abla; Debbah, Merouane; Alouini, Mohamed-Slim

2016-01-01

In this paper, we consider a uniform circular array (UCA) of directional antennas at the base station (BS) and the mobile station (MS) and derive an exact closed-form expression for the spatial correlation present in the 3D multiple-input multiple-output (MIMO) channel constituted by these arrays. The underlying method leverages the mathematical convenience of the spherical harmonic expansion (SHE) of plane waves and the trigonometric expansion of Legendre and associated Legendre polynomials. In contrast to the existing results, this generalized closed-form expression is independent of the form of the underlying angular distributions and antenna patterns. Moreover, the incorporation of the elevation dimension into the antenna pattern and channel model renders the proposed expression extremely useful for the performance evaluation of 3D MIMO systems in the future. Verification is achieved with the help of simulation results, which highlight the dependence of the spatial correlation on channel and array parameters. An interesting interplay between the mean angle of departure (AoD), angular spread and the positioning of antennas in the array is demonstrated. © 2016 IEEE.

Spatial correlation characterization of a uniform circular array in 3D MIMO systems

KAUST Repository

Nadeem, Qurrat-Ul-Ain

2016-08-11

In this paper, we consider a uniform circular array (UCA) of directional antennas at the base station (BS) and the mobile station (MS) and derive an exact closed-form expression for the spatial correlation present in the 3D multiple-input multiple-output (MIMO) channel constituted by these arrays. The underlying method leverages the mathematical convenience of the spherical harmonic expansion (SHE) of plane waves and the trigonometric expansion of Legendre and associated Legendre polynomials. In contrast to the existing results, this generalized closed-form expression is independent of the form of the underlying angular distributions and antenna patterns. Moreover, the incorporation of the elevation dimension into the antenna pattern and channel model renders the proposed expression extremely useful for the performance evaluation of 3D MIMO systems in the future. Verification is achieved with the help of simulation results, which highlight the dependence of the spatial correlation on channel and array parameters. An interesting interplay between the mean angle of departure (AoD), angular spread and the positioning of antennas in the array is demonstrated. © 2016 IEEE.

Spatial Vertical Directionality and Correlation of Low-Frequency Ambient Noise in Deep Ocean Direct-Arrival Zones

Directory of Open Access Journals (Sweden)

Qiulong Yang

2018-01-01

Full Text Available Wind-driven and distant shipping noise sources contribute to the total noise field in the deep ocean direct-arrival zones. Wind-driven and distant shipping noise sources may significantly and simultaneously affect the spatial characteristics of the total noise field to some extent. In this work, a ray approach and parabolic equation solution method were jointly utilized to model the low-frequency ambient noise field in a range-dependent deep ocean environment by considering their calculation accuracy and efficiency in near-field wind-driven and far-field distant shipping noise fields. The reanalysis databases of National Center of Environment Prediction (NCEP and Volunteer Observation System (VOS were used to model the ambient noise source intensity and distribution. Spatial vertical directionality and correlation were analyzed in three scenarios that correspond to three wind speed conditions. The noise field was dominated by distant shipping noise sources when the wind speed was less than 3 m/s, and then the spatial vertical directionality and vertical correlation of the total noise field were nearly consistent with those of distant shipping noise field. The total noise field was completely dominated by near field wind generated noise sources when the wind speed was greater than 12 m/s at 150 Hz, and then the spatial vertical correlation coefficient and directionality pattern of the total noise field was approximately consistent with that of the wind-driven noise field. The spatial characteristics of the total noise field for wind speeds between 3 m/s and 12 m/s were the weighted results of wind-driven and distant shipping noise fields. Furthermore, the spatial characteristics of low-frequency ambient noise field were compared with the classical Cron/Sherman deep water noise field coherence function. Simulation results with the described modeling method showed good agreement with the experimental measurement results based on the vertical line

Spatial Vertical Directionality and Correlation of Low-Frequency Ambient Noise in Deep Ocean Direct-Arrival Zones

Science.gov (United States)

Yang, Qiulong; Yang, Kunde; Cao, Ran; Duan, Shunli

2018-01-01

Wind-driven and distant shipping noise sources contribute to the total noise field in the deep ocean direct-arrival zones. Wind-driven and distant shipping noise sources may significantly and simultaneously affect the spatial characteristics of the total noise field to some extent. In this work, a ray approach and parabolic equation solution method were jointly utilized to model the low-frequency ambient noise field in a range-dependent deep ocean environment by considering their calculation accuracy and efficiency in near-field wind-driven and far-field distant shipping noise fields. The reanalysis databases of National Center of Environment Prediction (NCEP) and Volunteer Observation System (VOS) were used to model the ambient noise source intensity and distribution. Spatial vertical directionality and correlation were analyzed in three scenarios that correspond to three wind speed conditions. The noise field was dominated by distant shipping noise sources when the wind speed was less than 3 m/s, and then the spatial vertical directionality and vertical correlation of the total noise field were nearly consistent with those of distant shipping noise field. The total noise field was completely dominated by near field wind generated noise sources when the wind speed was greater than 12 m/s at 150 Hz, and then the spatial vertical correlation coefficient and directionality pattern of the total noise field was approximately consistent with that of the wind-driven noise field. The spatial characteristics of the total noise field for wind speeds between 3 m/s and 12 m/s were the weighted results of wind-driven and distant shipping noise fields. Furthermore, the spatial characteristics of low-frequency ambient noise field were compared with the classical Cron/Sherman deep water noise field coherence function. Simulation results with the described modeling method showed good agreement with the experimental measurement results based on the vertical line array deployed near

Spatial Organization and Molecular Correlation of Tumor-Infiltrating Lymphocytes Using Deep Learning on Pathology Images

Directory of Open Access Journals (Sweden)

Joel Saltz

2018-04-01

Full Text Available Summary: Beyond sample curation and basic pathologic characterization, the digitized H&E-stained images of TCGA samples remain underutilized. To highlight this resource, we present mappings of tumor-infiltrating lymphocytes (TILs based on H&E images from 13 TCGA tumor types. These TIL maps are derived through computational staining using a convolutional neural network trained to classify patches of images. Affinity propagation revealed local spatial structure in TIL patterns and correlation with overall survival. TIL map structural patterns were grouped using standard histopathological parameters. These patterns are enriched in particular T cell subpopulations derived from molecular measures. TIL densities and spatial structure were differentially enriched among tumor types, immune subtypes, and tumor molecular subtypes, implying that spatial infiltrate state could reflect particular tumor cell aberration states. Obtaining spatial lymphocytic patterns linked to the rich genomic characterization of TCGA samples demonstrates one use for the TCGA image archives with insights into the tumor-immune microenvironment. : Tumor-infiltrating lymphocytes (TILs were identified from standard pathology cancer images by a deep-learning-derived “computational stain” developed by Saltz et al. They processed 5,202 digital images from 13 cancer types. Resulting TIL maps were correlated with TCGA molecular data, relating TIL content to survival, tumor subtypes, and immune profiles. Keywords: digital pathology, immuno-oncology, machine learning, lymphocytes, tumor microenvironment, deep learning, tumor-infiltrating lymphocytes, artificial intelligence, bioinformatics, computer vision

Designs of Optoelectronic Trinary Signed-Digit Multiplication by use of Joint Spatial Encodings and Optical Correlation

Science.gov (United States)

Cherri, Abdallah K.

1999-02-01

Trinary signed-digit (TSD) symbolic-substitution-based (SS-based) optical adders, which were recently proposed, are used as the basic modules for designing highly parallel optical multiplications by use of cascaded optical correlators. The proposed multiplications perform carry-free generation of the multiplication partial products of two words in constant time. Also, three different multiplication designs are presented, and new joint spatial encodings for the TSD numbers are introduced. The proposed joint spatial encodings allow one to reduce the SS computation rules involved in optical multiplication. In addition, the proposed joint spatial encodings increase the space bandwidth product of the spatial light modulators of the optical system. This increase is achieved by reduction of the numbers of pixels in the joint spatial encodings for the input TSD operands as well as reduction of the number of pixels used in the proposed matched spatial filters for the optical multipliers.

Spatial dependence and correlation of rainfall in the Danube catchment and its role in flood risk assessment.

Science.gov (United States)

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.

An iterative detection method of MIMO over spatial correlated frequency selective channel: using list sphere decoding for simplification

Science.gov (United States)

Shi, Zhiping; Yan, Bing

2010-08-01

In multiple-input multiple-output(MIMO) wireless systems, combining good channel codes(e.g., Non-binary Repeat Accumulate codes) with adaptive turbo equalization is a good option to get better performance and lower complexity under Spatial Correlated Frequency Selective(SCFS) Channel. The key of this method is after joint antennas MMSE detection (JAD/MMSE) based on interruption cancelling using soft information, considering the detection result as an output of a Gaussian equivalent flat fading channel, and performing maximum likelihood detection(ML) to get more correct estimated result. But the using of ML brings great complexity increase, which is not allowed. In this paper, a low complexity method called list sphere decoding is introduced and applied to replace the ML in order to simplify the adaptive iterative turbo equalization system.

Spatially resolved D-T(2) correlation NMR of porous media.

Science.gov (United States)

Zhang, Yan; Blümich, Bernhard

2014-05-01

Within the past decade, 2D Laplace nuclear magnetic resonance (NMR) has been developed to analyze pore geometry and diffusion of fluids in porous media on the micrometer scale. Many objects like rocks and concrete are heterogeneous on the macroscopic scale, and an integral analysis of microscopic properties provides volume-averaged information. Magnetic resonance imaging (MRI) resolves this spatial average on the contrast scale set by the particular MRI technique. Desirable contrast parameters for studies of fluid transport in porous media derive from the pore-size distribution and the pore connectivity. These microscopic parameters are accessed by 1D and 2D Laplace NMR techniques. It is therefore desirable to combine MRI and 2D Laplace NMR to image functional information on fluid transport in porous media. Because 2D Laplace resolved MRI demands excessive measuring time, this study investigates the possibility to restrict the 2D Laplace analysis to the sum signals from low-resolution pixels, which correspond to pixels of similar amplitude in high-resolution images. In this exploratory study spatially resolved D-T2 correlation maps from glass beads and mortar are analyzed. Regions of similar contrast are first identified in high-resolution images to locate corresponding pixels in low-resolution images generated with D-T2 resolved MRI for subsequent pixel summation to improve the signal-to-noise ratio of contrast-specific D-T2 maps. This method is expected to contribute valuable information on correlated sample heterogeneity from the macroscopic and the microscopic scales in various types of porous materials including building materials and rock. Copyright © 2014 Elsevier Inc. All rights reserved.

Correlation characteristics of optical coherence tomography images of turbid media with statistically inhomogeneous optical parameters

International Nuclear Information System (INIS)

Dolin, Lev S.; Sergeeva, Ekaterina A.; Turchin, Ilya V.

2012-01-01

Noisy structure of optical coherence tomography (OCT) images of turbid medium contains information about spatial variations of its optical parameters. We propose analytical model of statistical characteristics of OCT signal fluctuations from turbid medium with spatially inhomogeneous coefficients of absorption and backscattering. Analytically predicted correlation characteristics of OCT signal from spatially inhomogeneous medium are in good agreement with the results of correlation analysis of OCT images of different biological tissues. The proposed model can be efficiently applied for quantitative evaluation of statistical properties of absorption and backscattering fluctuations basing on correlation characteristics of OCT images.

Spatial correlations of Diceroprocta apache and its host plants: Evidence for a negative impact from Tamarix invasion

Science.gov (United States)

Ellingson, A.R.; Andersen, D.C.

2002-01-01

1. The hypothesis that the habitat-scale spatial distribution of the Apache cicada Diceroprocta apache Davis is unaffected by the presence of the invasive exotic saltcedar Tamarix ramosissima was tested using data from 205 1-m2 quadrats placed within the flood-plain of the Bill Williams River, Arizona, U.S.A. Spatial dependencies within and between cicada density and habitat variables were estimated using Moran's I and its bivariate analogue to discern patterns and associations at spatial scales from 1 to 30 m.2. Apache cicadas were spatially aggregated in high-density clusters averaging 3 m in diameter. A positive association between cicada density, estimated by exuvial density, and the per cent canopy cover of a native tree, Goodding's willow Salix gooddingii, was detected in a non-spatial correlation analysis. No non-spatial association between cicada density and saltcedar canopy cover was detected.3. Tests for spatial cross-correlation using the bivariate IYZ indicated the presence of a broad-scale negative association between cicada density and saltcedar canopy cover. This result suggests that large continuous stands of saltcedar are associated with reduced cicada density. In contrast, positive associations detected at spatial scales larger than individual quadrats suggested a spill-over of high cicada density from areas featuring Goodding's willow canopy into surrounding saltcedar monoculture.4. Taken together and considered in light of the Apache cicada's polyphagous habits, the observed spatial patterns suggest that broad-scale factors such as canopy heterogeneity affect cicada habitat use more than host plant selection. This has implications for management of lower Colorado River riparian woodlands to promote cicada presence and density through maintenance or creation of stands of native trees as well as manipulation of the characteristically dense and homogeneous saltcedar canopies.

Discrete capacity limits and neuroanatomical correlates of visual short-term memory for objects and spatial locations.

Science.gov (United States)

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.

Diffuse correlation tomography reveals spatial and temporal difference in blood flow changes among murine femoral grafts

Science.gov (United States)

Han, Songfeng; Proctor, Ashley R.; Benoit, Danielle S. W.; Choe, Regine

2017-07-01

Diffuse correlation tomography was utilized to noninvasively monitor 3D blood flow changes in three types of healing mouse femoral grafts. Results reveal the spatial and temporal difference among the groups.

Characterization of the spatial structure of local functional connectivity using multi-distance average correlation measures.

Science.gov (United States)

Macia, Didac; Pujol, Jesus; Blanco-Hinojo, Laura; Martínez-Vilavella, Gerard; Martín-Santos, Rocío; Deus, Joan

2018-04-24

There is ample evidence from basic research in neuroscience of the importance of local cortico-cortical networks. Millimetric resolution is achievable with current functional MRI (fMRI) scanners and sequences, and consequently a number of "local" activity similarity measures have been defined to describe patterns of segregation and integration at this spatial scale. We have introduced the use of Iso-Distant local Average Correlation (IDAC), easily defined as the average fMRI temporal correlation of a given voxel with other voxels placed at increasingly separated iso-distant intervals, to characterize the curve of local fMRI signal similarities. IDAC curves can be statistically compared using parametric multivariate statistics. Furthermore, by using RGB color-coding to display jointly IDAC values belonging to three different distance lags, IDAC curves can also be displayed as multi-distance IDAC maps. We applied IDAC analysis to a sample of 41 subjects scanned under two different conditions, a resting state and an auditory-visual continuous stimulation. Multi-distance IDAC mapping was able to discriminate between gross anatomo-functional cortical areas and, moreover, was sensitive to modulation between the two brain conditions in areas known to activate and de-activate during audio-visual tasks. Unlike previous fMRI local similarity measures already in use, our approach draws special attention to the continuous smooth pattern of local functional connectivity.

Spatial preference heterogeneity in forest recreation

DEFF Research Database (Denmark)

Abildtrup, Jens; Garcia, Serge; Olsen, Søren Bøye

2013-01-01

In this study, we analyze the preferences for recreational use of forests in Lorraine (Northeastern France), applying stated preference data. Our approach allows us to estimate individual-specific preferences for recreational use of different forest types. These estimates are used in a second stage...... in the estimation of welfare economic values for parking and picnic facilities in the analyzed model. The results underline the importance of considering spatial heterogeneity of preferences carrying out economic valuation of spatial-delineated environmental goods and that the spatial variation in willingness...... of the analysis where we test whether preferences depend on access to recreation sites. We find that there is significant preference heterogeneity with respect to most forest attributes. The spatial analysis shows that preferences for forests with parking and picnic facilities are correlated with having access...

Many-body correlation effects in the spatially separated electron and hole layers in the coupled quantum wells

Energy Technology Data Exchange (ETDEWEB)

Babichenko, V.S. [RRC Kurchatov Institute, Kurchatov Sq., 1, 123182 Moscow (Russian Federation); Polishchuk, I.Ya., E-mail: iyppolishchuk@gmail.com [RRC Kurchatov Institute, Kurchatov Sq., 1, 123182 Moscow (Russian Federation); Moscow Institute of Physics and Technology, 141700, 9, Institutskii per., Dolgoprudny, Moscow Region (Russian Federation)

2014-11-15

The many-body correlation effects in the spatially separated electron and hole layers in the coupled quantum wells are investigated. A special case of the many-component electron–hole system is considered. It is shown that if the hole mass is much greater than the electron mass, the negative correlation energy is mainly determined by the holes. The ground state of the system is found to be the 2D electron–hole liquid with the energy smaller than the exciton phase. It is shown that the system decays into the spatially separated neutral electron–hole drops if the initially created charge density in the layers is smaller than the certain critical value n{sub eq}.

Spatial occupancy models applied to atlas data show Southern Ground Hornbills strongly depend on protected areas.

Science.gov (United States)

Broms, Kristin M; Johnson, Devin S; Altwegg, Res; Conquest, Loveday L

2014-03-01

Determining the range of a species and exploring species--habitat associations are central questions in ecology and can be answered by analyzing presence--absence data. Often, both the sampling of sites and the desired area of inference involve neighboring sites; thus, positive spatial autocorrelation between these sites is expected. Using survey data for the Southern Ground Hornbill (Bucorvus leadbeateri) from the Southern African Bird Atlas Project, we compared advantages and disadvantages of three increasingly complex models for species occupancy: an occupancy model that accounted for nondetection but assumed all sites were independent, and two spatial occupancy models that accounted for both nondetection and spatial autocorrelation. We modeled the spatial autocorrelation with an intrinsic conditional autoregressive (ICAR) model and with a restricted spatial regression (RSR) model. Both spatial models can readily be applied to any other gridded, presence--absence data set using a newly introduced R package. The RSR model provided the best inference and was able to capture small-scale variation that the other models did not. It showed that ground hornbills are strongly dependent on protected areas in the north of their South African range, but less so further south. The ICAR models did not capture any spatial autocorrelation in the data, and they took an order, of magnitude longer than the RSR models to run. Thus, the RSR occupancy model appears to be an attractive choice for modeling occurrences at large spatial domains, while accounting for imperfect detection and spatial autocorrelation.

The Threshold Hypothesis Applied to Spatial Skill and Mathematics

Science.gov (United States)

Freer, Daniel

2017-01-01

This cross-sectional study assessed the relation between spatial skills and mathematics in 854 participants across kindergarten, third grade, and sixth grade. Specifically, the study probed for a threshold for spatial skills when performing mathematics, above which spatial scores and mathematics scores would be significantly less related. This…

On the role of spatial phase and phase correlation in vision, illusion, and cognition.

Science.gov (United States)

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."

On the role of spatial phase and phase correlation in vision, illusion and cognition

Directory of Open Access Journals (Sweden)

Evgeny eGladilin

2015-04-01

Full Text Available 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 (dissimilarity that can be used for experimental validation of our hypothesis of 'cognition by phase correlation'.

Velocity correlations and spatial dependencies between neighbors in a unidirectional flow of pedestrians

Science.gov (United States)

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.

Spatial variations of storm runoff pollution and their correlation with land-use in a rapidly urbanizing catchment in China.

Science.gov (United States)

Qin, Hua-Peng; Khu, Soon-Thiam; Yu, Xiang-Ying

2010-09-15

The composition of land use for a rapidly urbanizing catchment is usually heterogeneous, and this may result in significant spatial variations of storm runoff pollution and increase the difficulties of water quality management. The Shiyan Reservoir catchment, a typical rapidly urbanizing area in China, is chosen as a study area, and temporary monitoring sites were set at the downstream of its 6 sub-catchments to synchronously measure rainfall, runoff and water quality during 4 storm events in 2007 and 2009. Due to relatively low frequency monitoring, the IHACRES and exponential pollutant wash-off simulation models are used to interpolate the measured data to compensate for data insufficiency. Three indicators, event pollutant loads per unit area (EPL), event mean concentration (EMC) and pollutant loads transported by the first 50% of runoff volume (FF50), were used to describe the runoff pollution for different pollutants in each sub-catchment during the storm events, and the correlations between runoff pollution spatial variations and land-use patterns were tested by Spearman's rank correlation analysis. The results indicated that similar spatial variation trends were found for different pollutants (EPL or EMC) in light storm events, which strongly correlate with the proportion of residential land use; however, they have different trends in heavy storm events, which correlate with not only the residential land use, but also agricultural and bare land use. And some pairs of pollutants (such as COD/BOD, NH(3)-N/TN) might have the similar source because they have strong or moderate positive spatial correlation. Moreover, the first flush intensity (FF50) varies with impervious land areas and different interception ratio of initial storm runoff volume should be adopted in different sub-catchments. Copyright 2010 Elsevier B.V. All rights reserved.

Hybrid optical CDMA-FSO communications network under spatially correlated gamma-gamma scintillation.

Science.gov (United States)

Jurado-Navas, Antonio; Raddo, Thiago R; Garrido-Balsells, José María; Borges, Ben-Hur V; Olmos, Juan José Vegas; Monroy, Idelfonso Tafur

2016-07-25

In this paper, we propose a new hybrid network solution based on asynchronous optical code-division multiple-access (OCDMA) and free-space optical (FSO) technologies for last-mile access networks, where fiber deployment is impractical. The architecture of the proposed hybrid OCDMA-FSO network is thoroughly described. The users access the network in a fully asynchronous manner by means of assigned fast frequency hopping (FFH)-based codes. In the FSO receiver, an equal gain-combining technique is employed along with intensity modulation and direct detection. New analytical formalisms for evaluating the average bit error rate (ABER) performance are also proposed. These formalisms, based on the spatially correlated gamma-gamma statistical model, are derived considering three distinct scenarios, namely, uncorrelated, totally correlated, and partially correlated channels. Numerical results show that users can successfully achieve error-free ABER levels for the three scenarios considered as long as forward error correction (FEC) algorithms are employed. Therefore, OCDMA-FSO networks can be a prospective alternative to deliver high-speed communication services to access networks with deficient fiber infrastructure.

Spatial correlations in intense ionospheric scintillations - comparison between numerical computation and observation

International Nuclear Information System (INIS)

Kumagai, H.

1987-01-01

The spatial correlations in intense ionospheric scintillations were analyzed by comparing numerical results with observational ones. The observational results were obtained by spaced-receiver scintillation measurements of VHF satellite radiowave. The numerical computation was made by using the fourth-order moment equation with fairly realistic ionospheric irregularity models, in which power-law irregularities with spectral index 4, both thin and thick slabs, and both isotropic and anisotropic irregularities, were considered. Evolution of the S(4) index and the transverse correlation function was computed. The numerical result that the transverse correlation distance decreases with the increase in S(4) was consistent with that obtained in the observation, suggesting that multiple scattering plays an important role in the intense scintillations observed. The anisotropy of irregularities proved to act as if the density fluctuation increased. This effect, as well as the effect of slab thickness, was evaluated by the total phase fluctuations that the radiowave experienced in the slab. On the basis of the comparison, the irregularity height and electron-density fluctuation which is necessary to produce a particular strength of scintillation were estimated. 30 references

World wide spatial capital.

Science.gov (United States)

Sen, Rijurekha; Quercia, Daniele

2018-01-01

In its most basic form, the spatial capital of a neighborhood entails that most aspects of daily life are located close at hand. Urban planning researchers have widely recognized its importance, not least because it can be transformed in other forms of capital such as economical capital (e.g., house prices, retail sales) and social capital (e.g., neighborhood cohesion). Researchers have already studied spatial capital from official city data. Their work led to important planning decisions, yet it also relied on data that is costly to create and update, and produced metrics that are difficult to compare across cities. By contrast, we propose to measure spatial capital in cheap and standardized ways around the world. Hence the name of our project "World Wide Spatial Capital". Our measures are cheap as they rely on the most basic information about a city that is currently available on the Web (i.e., which amenities are available and where). They are also standardized because they can be applied in any city in the five continents (as opposed to previous metrics that were mainly applied in USA and UK). We show that, upon these metrics, one could produce insights at the core of the urban planning discipline: which areas would benefit the most from urban interventions; how to inform planning depending on whether a city's activity is mono- or poly-centric; how different cities fare against each other; and how spatial capital correlates with other urban characteristics such as mobility patterns and road network structure.

World wide spatial capital.

Directory of Open Access Journals (Sweden)

Rijurekha Sen

Full Text Available In its most basic form, the spatial capital of a neighborhood entails that most aspects of daily life are located close at hand. Urban planning researchers have widely recognized its importance, not least because it can be transformed in other forms of capital such as economical capital (e.g., house prices, retail sales and social capital (e.g., neighborhood cohesion. Researchers have already studied spatial capital from official city data. Their work led to important planning decisions, yet it also relied on data that is costly to create and update, and produced metrics that are difficult to compare across cities. By contrast, we propose to measure spatial capital in cheap and standardized ways around the world. Hence the name of our project "World Wide Spatial Capital". Our measures are cheap as they rely on the most basic information about a city that is currently available on the Web (i.e., which amenities are available and where. They are also standardized because they can be applied in any city in the five continents (as opposed to previous metrics that were mainly applied in USA and UK. We show that, upon these metrics, one could produce insights at the core of the urban planning discipline: which areas would benefit the most from urban interventions; how to inform planning depending on whether a city's activity is mono- or poly-centric; how different cities fare against each other; and how spatial capital correlates with other urban characteristics such as mobility patterns and road network structure.

Spatial correlation of conductive filaments for multiple switching cycles in CBRAM

KAUST Repository

Pey, K. L.

2014-06-01

Conducting bridge random access memory (CBRAM) is one of the potential technologies being considered for replacement of Flash memory for non-volatile data storage. CBRAM devices operate on the principle of nucleation and rupture of metallic filaments. One key concern for commercializing this technology is the question of variability which could arise due to nucleation of multiple filaments across the device at spatially different locations. The spatial spread of the filament location may cause long tails at the low and high percentile regions for the switching parameter distribution as the new filament that nucleates may have a completely different shape and size. It is therefore essential to probe whether switching in CBRAM occurs every time at the same filament location or whether there are other new filaments that could nucleate during repeated cycling with some spatial correlation (if any) to the original filament. To investigate this issue, we make use of a metal-insulator-semiconductor (M-I-S) transistor test structure with Ni as the top electrode and HfOx/SiOx as the dielectric stack. In-situ stressing using a nano-tip on the M-I-S stack is performed and the filament is imaged in real-time using a high resolution transmission electron microscope (TEM). We also extract the location of the filament (LFIL) along the channel of the transistor after the nucleation stage using the weighted proportion of the source and drain currents. © 2014 IEEE.

Correlative Stochastic Optical Reconstruction Microscopy and Electron Microscopy

Science.gov (United States)

Kim, Doory; Deerinck, Thomas J.; Sigal, Yaron M.; Babcock, Hazen P.; Ellisman, Mark H.; Zhuang, Xiaowei

2015-01-01

Correlative fluorescence light microscopy and electron microscopy allows the imaging of spatial distributions of specific biomolecules in the context of cellular ultrastructure. Recent development of super-resolution fluorescence microscopy allows the location of molecules to be determined with nanometer-scale spatial resolution. However, correlative super-resolution fluorescence microscopy and electron microscopy (EM) still remains challenging because the optimal specimen preparation and imaging conditions for super-resolution fluorescence microscopy and EM are often not compatible. Here, we have developed several experiment protocols for correlative stochastic optical reconstruction microscopy (STORM) and EM methods, both for un-embedded samples by applying EM-specific sample preparations after STORM imaging and for embedded and sectioned samples by optimizing the fluorescence under EM fixation, staining and embedding conditions. We demonstrated these methods using a variety of cellular targets. PMID:25874453

Density dependence of the fine-differential disturbed gamma-gamma-spatial correlation in gaseous 111InI-sources

International Nuclear Information System (INIS)

Schuetter, K.

1985-01-01

An instrument for measuring a time-differential disturbed angular correlation was developed. Using this instrument the disturbance of the spatial correlation of the γ-quanta of the 171-245 keV γ-γ-cascade in 111 Cd was examined in dependence of the density of the gaseous 111 InI-systems and the time difference between the emission of the both γ-quanta. (BBOE)

Ensemble correlation PIV applied to bubble plumes rising in a bubble column.

NARCIS (Netherlands)

Delnoij, E.; Westerweel, J.; Deen, N.G.; Kuipers, J.A.M.; van Swaaij, Willibrordus Petrus Maria

1999-01-01

This paper discusses an ensemble correlation, double-exposure single-frame, particle image velocimetry (PIV) technique that can be applied to study dispersed gas¿liquid two-phase flows. The essentials of this technique will be reviewed and several important issues concerning the implementation of

Fractal analytical approach of urban form based on spatial correlation function

International Nuclear Information System (INIS)

Chen, Yanguang

2013-01-01

Highlights: ► Many fractal parameter relations of cities can be derived by scaling analysis. ► The area-radius scaling of cities suggests a spatial correlation function. ► Spectral analysis can be used to estimate fractal dimension values of urban form. ► The valid range of fractal dimension of urban form comes between 1.5 and 2. ► The traditional scale concept will be replaced by scaling concept in geography. -- Abstract: Urban form has been empirically demonstrated to be of scaling invariance and can be described with fractal geometry. However, the rational range of fractal dimension value and the relationships between various fractal indicators of cities are not yet revealed in theory. By mathematical deduction and transform (e.g., Fourier transform), I find that scaling analysis, spectral analysis, and spatial correlation analysis are all associated with fractal concepts and can be integrated into a new approach to fractal analysis of cities. This method can be termed ‘3S analyses’ of urban form. Using the 3S analysis, I derived a set of fractal parameter equations, by which different fractal parameters of cities can be linked up with one another. Each fractal parameter has its own reasonable extent of values. According to the fractal parameter equations, the intersection of the rational ranges of different fractal parameters suggests the proper scale of the fractal dimension of urban patterns, which varies from 1.5 to 2. The fractal dimension equations based on the 3S analysis and the numerical relationships between different fractal parameters are useful for geographers to understand urban evolution and potentially helpful for future city planning

Introduction to the transverse spatial correlations in spontaneous parametric down-conversion through the biphoton birth zone

International Nuclear Information System (INIS)

Schneeloch, James; Howell, John C

2016-01-01

As a tutorial to the spatial aspects of spontaneous parametric downconversion (SPDC), we present a detailed first-principles derivation of the transverse correlation width of photon pairs in degenerate collinear SPDC. This width defines the size of a biphoton birth zone, the region where the signal and idler photons are likely to be found when conditioning on the position of the destroyed pump photon. Along the way, we discuss the quantum-optical calculation of the amplitude for the SPDC process, as well as its simplified form for nearly collinear degenerate phase matching. Following this, we show how this biphoton amplitude can be approximated with a double-Gaussian wavefunction, and give a brief discussion of the measurement statistics (and subsequent convenience) of such double-Gaussian wavefunctions. Next, we use this approximation to get a simplified estimation of the transverse correlation width, and compare it to more accurate calculations as well as experimental results. We then conclude with a discussion of the concept of a biphoton birth zone, using it to develop intuition for the tradeoff between the first-order spatial coherence and bipohoton correlations in SPDC. (tutorial)

Spatial correlation in 3D MIMO channels using fourier coefficients of power spectrums

KAUST Repository

Nadeem, Qurrat-Ul-Ain

2015-03-01

In this paper, an exact closed-form expression for the Spatial Correlation Function (SCF) is derived for the standardized three-dimensional (3D) multiple-input multiple-output (MIMO) channel. This novel SCF is developed for a uniform linear array of antennas with non-isotropic antenna patterns. The proposed method resorts to the spherical harmonic expansion (SHE) of plane waves and the trigonometric expansion of Legendre and associated Legendre polynomials to obtain a closed-form expression for the SCF for arbitrary angular distributions and antenna patterns. The resulting expression depends on the underlying angular distributions and antenna patterns through the Fourier Series (FS) coefficients of power azimuth and elevation spectrums. The novelty of the proposed method lies in the SCF being valid for any 3D propagation environment. Numerical results validate the proposed analytical expression and study the impact of angular spreads on the correlation. The derived SCF will help evaluate the performance of correlated 3D MIMO channels in the future. © 2015 IEEE.

Quantum correlated cluster mean-field theory applied to the transverse Ising model.

Science.gov (United States)

Zimmer, F M; Schmidt, M; Maziero, Jonas

2016-06-01

Mean-field theory (MFT) is one of the main available tools for analytical calculations entailed in investigations regarding many-body systems. Recently, there has been a surge of interest in ameliorating this kind of method, mainly with the aim of incorporating geometric and correlation properties of these systems. The correlated cluster MFT (CCMFT) is an improvement that succeeded quite well in doing that for classical spin systems. Nevertheless, even the CCMFT presents some deficiencies when applied to quantum systems. In this article, we address this issue by proposing the quantum CCMFT (QCCMFT), which, in contrast to its former approach, uses general quantum states in its self-consistent mean-field equations. We apply the introduced QCCMFT to the transverse Ising model in honeycomb, square, and simple cubic lattices and obtain fairly good results both for the Curie temperature of thermal phase transition and for the critical field of quantum phase transition. Actually, our results match those obtained via exact solutions, series expansions or Monte Carlo simulations.

Spatial and temporal correlation between beach and wave processes: implications for bar-berm sediment transition

Science.gov (United States)

Joevivek, V.; Chandrasekar, N.; Saravanan, S.; Anandakumar, H.; Thanushkodi, K.; Suguna, N.; Jaya, J.

2018-06-01

Investigation of a beach and its wave conditions is highly requisite for understanding the physical processes in a coast. This study composes spatial and temporal correlation between beach and nearshore processes along the extensive sandy beach of Nagapattinam coast, southeast peninsular India. The data collection includes beach profile, wave data, and intertidal sediment samples for 2 years from January 2011 to January 2013. The field data revealed significant variability in beach and wave morphology during the northeast (NE) and southwest (SW) monsoon. However, the beach has been stabilized by the reworking of sediment distribution during the calm period. The changes in grain sorting and longshore sediment transport serve as a clear evidence of the sediment migration that persevered between foreshore and nearshore regions. The Empirical Orthogonal Function (EOF) analysis and Canonical Correlation Analysis (CCA) were utilized to investigate the spatial and temporal linkages between beach and nearshore criterions. The outcome of the multivariate analysis unveiled that the seasonal variations in the wave climate tends to influence the bar-berm sediment transition that is discerned in the coast.

Spatial and temporal correlation between beach and wave processes: implications for bar-berm sediment transition

Science.gov (United States)

Joevivek, V.; Chandrasekar, N.; Saravanan, S.; Anandakumar, H.; Thanushkodi, K.; Suguna, N.; Jaya, J.

2017-06-01

Investigation of a beach and its wave conditions is highly requisite for understanding the physical processes in a coast. This study composes spatial and temporal correlation between beach and nearshore processes along the extensive sandy beach of Nagapattinam coast, southeast peninsular India. The data collection includes beach profile, wave data, and intertidal sediment samples for 2 years from January 2011 to January 2013. The field data revealed significant variability in beach and wave morphology during the northeast (NE) and southwest (SW) monsoon. However, the beach has been stabilized by the reworking of sediment distribution during the calm period. The changes in grain sorting and longshore sediment transport serve as a clear evidence of the sediment migration that persevered between foreshore and nearshore regions. The Empirical Orthogonal Function (EOF) analysis and Canonical Correlation Analysis (CCA) were utilized to investigate the spatial and temporal linkages between beach and nearshore criterions. The outcome of the multivariate analysis unveiled that the seasonal variations in the wave climate tends to influence the bar-berm sediment transition that is discerned in the coast.

Denoising Algorithm for CFA Image Sensors Considering Inter-Channel Correlation.

Science.gov (United States)

Lee, Min Seok; Park, Sang Wook; Kang, Moon Gi

2017-05-28

In this paper, a spatio-spectral-temporal filter considering an inter-channel correlation is proposed for the denoising of a color filter array (CFA) sequence acquired by CCD/CMOS image sensors. Owing to the alternating under-sampled grid of the CFA pattern, the inter-channel correlation must be considered in the direct denoising process. The proposed filter is applied in the spatial, spectral, and temporal domain, considering the spatio-tempo-spectral correlation. First, nonlocal means (NLM) spatial filtering with patch-based difference (PBD) refinement is performed by considering both the intra-channel correlation and inter-channel correlation to overcome the spatial resolution degradation occurring with the alternating under-sampled pattern. Second, a motion-compensated temporal filter that employs inter-channel correlated motion estimation and compensation is proposed to remove the noise in the temporal domain. Then, a motion adaptive detection value controls the ratio of the spatial filter and the temporal filter. The denoised CFA sequence can thus be obtained without motion artifacts. Experimental results for both simulated and real CFA sequences are presented with visual and numerical comparisons to several state-of-the-art denoising methods combined with a demosaicing method. Experimental results confirmed that the proposed frameworks outperformed the other techniques in terms of the objective criteria and subjective visual perception in CFA sequences.

Learning to echolocate in sighted people: a correlational study on attention, working memory and spatial abilities.

Science.gov (United States)

Ekkel, M R; van Lier, R; Steenbergen, B

2017-03-01

Echolocation can be beneficial for the orientation and mobility of visually impaired people. Research has shown considerable individual differences for acquiring this skill. However, individual characteristics that affect the learning of echolocation are largely unknown. In the present study, we examined individual factors that are likely to affect learning to echolocate: sustained and divided attention, working memory, and spatial abilities. To that aim, sighted participants with normal hearing performed an echolocation task that was adapted from a previously reported size-discrimination task. In line with existing studies, we found large individual differences in echolocation ability. We also found indications that participants were able to improve their echolocation ability. Furthermore, we found a significant positive correlation between improvement in echolocation and sustained and divided attention, as measured in the PASAT. No significant correlations were found with our tests regarding working memory and spatial abilities. These findings may have implications for the development of guidelines for training echolocation that are tailored to the individual with a visual impairment.

Planar spatial correlations, anisotropy, and specific surface area of stationary random porous media

International Nuclear Information System (INIS)

Berryman, J.G.

1998-01-01

An earlier result of the author showed that an anisotropic spatial correlation function of a random porous medium could be used to compute the specific surface area when it is stationary as well as anisotropic by first performing a three-dimensional radial average and then taking the first derivative with respect to lag at the origin. This result generalized the earlier result for isotropic porous media of Debye et al. [J. Appl. Phys. 28, 679 (1957)]. The present article provides more detailed information about the use of spatial correlation functions for anisotropic porous media and in particular shows that, for stationary anisotropic media, the specific surface area can be related to the derivative of the two-dimensional radial average of the correlation function measured from cross sections taken through the anisotropic medium. The main concept is first illustrated using a simple pedagogical example for an anisotropic distribution of spherical voids. Then, a general derivation of formulas relating the derivative of the planar correlation functions to surface integrals is presented. When the surface normal is uniformly distributed (as is the case for any distribution of spherical voids), our formulas can be used to relate a specific surface area to easily measurable quantities from any single cross section. When the surface normal is not distributed uniformly (as would be the case for an oriented distribution of ellipsoidal voids), our results show how to obtain valid estimates of specific surface area by averaging measurements on three orthogonal cross sections. One important general observation for porous media is that the surface area from nearly flat cracks may be underestimated from measurements on orthogonal cross sections if any of the cross sections happen to lie in the plane of the cracks. This result is illustrated by taking the very small aspect ratio (penny-shaped crack) limit of an oblate spheroid, but holds for other types of flat surfaces as well

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

Science.gov (United States)

Stephenson, D. B.

1997-10-01

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

Triple collocation-based estimation of spatially correlated observation error covariance in remote sensing soil moisture data assimilation

Science.gov (United States)

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.

Effects of fading and spatial correlation on node selection for estimation in Wireless Sensor Networks

KAUST Repository

Al-Murad, Tamim M.

2010-06-01

In densely deployed sensor networks, correlation among measurements may be high. Spatial sampling through node selection is usually used to minimize this correlation and to save energy consumption. However because of the fading nature of the wireless channels, extra care should be taken when performing this sampling. In this paper, we develop expressions for the distortion which include the channel effects. The asymptotic behavior of the distortion as the number of sensors or total transmit power increase without bound is also investigated. Further, based on the channel and position information we propose and test several node selection schemes.

Z-1 perturbation theory applied to the correlation energy problem of atoms

International Nuclear Information System (INIS)

Robinson, B.H.

1975-01-01

Rayleigh--Schroedinger Perturbation Theory is applied to obtain directly exact and explicit analytic formulas for the electron correlation energies of N electron systems in terms of their pairwise interactions through second order in Z -1 , where Z is the nucleus of the atom. It is demonstrated that the second order correlation energy may be expressed as exactly the sum of pairwise correlation energies. In the case of no zeroth order degeneracy, the zeroth and first order terms vanish. The expression for the pairwise energies is an infinite sum, all terms of which are of the same sign. There is no numerical differencing. In the case of zeroth order degeneracy it is shown that the above statement concerning the second order energy still holds, but the expressions are a bit more complicated. It is shown that they ''almost'' reduce to a much simpler form. Also, the computation of the first order correlation energy is considered

Multilevel discretized random field models with 'spin' correlations for the simulation of environmental spatial data

Science.gov (United States)

Žukovič, Milan; Hristopulos, Dionissios T.

2009-02-01

A current problem of practical significance is how to analyze large, spatially distributed, environmental data sets. The problem is more challenging for variables that follow non-Gaussian distributions. We show by means of numerical simulations that the spatial correlations between variables can be captured by interactions between 'spins'. The spins represent multilevel discretizations of environmental variables with respect to a number of pre-defined thresholds. The spatial dependence between the 'spins' is imposed by means of short-range interactions. We present two approaches, inspired by the Ising and Potts models, that generate conditional simulations of spatially distributed variables from samples with missing data. Currently, the sampling and simulation points are assumed to be at the nodes of a regular grid. The conditional simulations of the 'spin system' are forced to respect locally the sample values and the system statistics globally. The second constraint is enforced by minimizing a cost function representing the deviation between normalized correlation energies of the simulated and the sample distributions. In the approach based on the Nc-state Potts model, each point is assigned to one of Nc classes. The interactions involve all the points simultaneously. In the Ising model approach, a sequential simulation scheme is used: the discretization at each simulation level is binomial (i.e., ± 1). Information propagates from lower to higher levels as the simulation proceeds. We compare the two approaches in terms of their ability to reproduce the target statistics (e.g., the histogram and the variogram of the sample distribution), to predict data at unsampled locations, as well as in terms of their computational complexity. The comparison is based on a non-Gaussian data set (derived from a digital elevation model of the Walker Lake area, Nevada, USA). We discuss the impact of relevant simulation parameters, such as the domain size, the number of

Spatial correlation structure of the ionosphere predicted by geomagnetic indices and application to global field modelling

Science.gov (United States)

Holschneider, M.; Ferrat, K.; Lesur, V.; Stolle, C.

2017-12-01

Ionospheric fields are modelled in terms of random structures taking into account a mean behaviour as well as random fluctuations which are described through two point correlation kernels. These kernels are estimated from long time series of numerical simulations from various models. These correlations are best expressed in SM system of coordinates. For the moment we limit ourselves to spatial correlations only in this coordinate system. We study the influence of various indices as possible predictor parameters for these correlations as well as seasonal effects. The various time series of ionospheric fields are stored in a HDF5 database which is accessible via a web interface. The obtained correlation structures serve as prior information to separate external and internal field components from observatory based measurements. We present a model that predicts the correlations as a function of time and some geomagnetic indices. First results of the inversion from observatory data are presented.

Can spatial autocorrelation method be applied to arbitrary array shape; Kukan jiko sokanho no nin`i array eno tekiyo kanosei

Energy Technology Data Exchange (ETDEWEB)

Yamamoto, H; Iwamoto, K; Saito, T; Tachibana, M [Iwate University, Iwate (Japan). Faculty of Engineering

1997-05-27

Methods to learn underground structures by utilizing the dispersion phenomenon of surface waves contained in microtremors include the frequency-wave number analysis method (the F-K method) and the spatial autocorrelation method (the SAC method). Despite the fact that the SAC method is capable of exploring structures at greater depths, the method is not utilized because of its stringent restriction in arrangement of seismometers during observation that they must be arranged evenly on the same circumference. In order to eliminate this restriction in the SAC method, a research group in the Hokuriku University has proposed an expanded spatial autocorrelation (ESAC) method. Using the concept of the ESAC method as its base, a method was realized to improve phase velocity estimation by making a simulation on an array shifted to the radius direction. As a result of the discussion, it was found that the proposed improvement method can be applied to places where waves come from a number of directions, such as urban areas. If the improvement method can be applied, the spatial autocorrelation function needs not be even in the circumferential direction. In other words, the SAC method can be applied to arbitrary arrays. 1 ref., 7 figs.

[Spatial distribution of COD and the correlations with other parameters in the northern region of Lake Taihu].

Science.gov (United States)

Zhang, Yun-lin; Yang, Long-yuan; Qin, Bo-qiang; Gao, Guang; Luo, Lian-cong; Zhu, Guang-wei; Liu, Ming-liang

2008-06-01

Spatial variation of chemical oxygen demand (COD) concentration was documented and significant correlations between COD concentration and chromophoric dissolved organic matter (CDOM) absorption, fluorescence, DOC concentration were found based on a cruise sampling in the northern region of Lake Taihu in summer including 42 samplings. The possible source of COD was also discussed using every two cruise samplings in summer and winter, respectively. The COD concentration ranged from 3.77 to 7.96 mg x L(-1) with a mean value of (5.90 +/- 1.54) mg x L(-1). The mean COD concentrations in Meiliang Bay and the central lake basin were (6.93 +/- 0.89) mg x L(-1) and (4.21 +/- 0.49) mg x L(-1) respectively. A significant spatial difference was found between Meiliang Bay and the central lake basin in COD concentration, CDOM absorption coefficient, fluorescence, DOC and phytoplankton pigment concentrations, decreasing from the river mouth to inner bay, outer bay and the central lake basin. Significant correlations between COD concentration and CDOM absorption, fluorescence, DOC concentration, suggested that COD concentration could be estimated and organic pollution could be assessed using CDOM absorption retrieved from remote sensing images. Significant and positive correlation was found between COD concentration and chlorophyll a concentration in summer. However, the correlation was weak or no correlation was found in winter. Furthermore, a significant higher COD concentration was found in summer than in winter (p summer, except for river terrestrial input.

Summary of the Nevada Applied Ecology Group and correlative programs

International Nuclear Information System (INIS)

Friesen, H.N.

1992-10-01

This summary document presents results in a broad context; it is not limited to findings of the Nevada Applied Ecology Group. This book is organized to present the findings of the Nevada Applied Ecology Group and correlative programs in accordance with the originally stated objectives of the Nevada Applied Ecology Group. This plan, in essence, traces plutonium from its injection into the environment to movement in the ecosystem to development of cleanup techniques. Information on other radionuclides was also obtained and will be presented briefly. Chapter 1 presents a brief description of the ecological setting of the Test Range Complex. The results of investigations for plutonium distribution are presented in Chapter 2 for the area surrounding the Test Range Complex and in Chapter 3 for on-site locations. Chapters 4 and 5 present the results of investigations concerned with concentrations and movement, respectively, of plutonium in the ecosystem of the Test Range Complex, and Chapter 6 summarizes the potential hazard from this plutonium. Development of techniques for cleanup and treatment is presented in Chapter 7, and the inventory of radionuclides other than plutonium is presented briefly in Chapter 8

Restoring method for missing data of spatial structural stress monitoring based on correlation

Science.gov (United States)

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.

Memory-induced sign reversals of the spatial cross-correlation for particles in viscoelastic shear flows

International Nuclear Information System (INIS)

Sauga, Ako; Laas, Katrin; Mankin, Romi

2015-01-01

Highlights: • Cross-correlation (CC) of coordinates of particles in viscoelastic shear flows is discussed. • Expressions for CC functions subjected to both internal and external noises are presented. • Impact of internal and external noises on CC functions are compared. • Memory-induced reentrant sign reversals of the spatial cross-moment are established. - Abstract: The behavior of shear-induced cross-correlation functions between particle fluctuations along orthogonal directions in the shear plane for harmonically trapped Brownian particles in a viscoelastic shear flow is studied. A generalized Langevin equation with a power-law-type memory kernel is used to model the complex structure of the viscoelastic media. Interaction with fluctuations of environmental parameters is modeled by a multiplicative white Gaussian noise, by an internal fractional Gaussian noise, and by an additive external white noise. It is shown that the presence of a memory has a profound effect on the behavior of the cross-correlation functions. Particularly, memory-induced reentrant sign reversals of the spatial cross-moment between orthogonal random displacements of a particle are established, i.e., an increase of the memory exponent can cause the sign reversal from positive to negative, but by a further increase of the memory exponent a reentrant transition from negative to positive values appears. Similarities and differences between the behavior of the models with additive internal and external noises are considered. It is shown that additive external and internal noises cause qualitatively different dependencies of the cross-correlation functions on the time lag. The occurrence of energetic instability due to the influence of multiplicative noise is also discussed.

The Correlation between Pre-Service Science Teachers' Astronomy Achievement, Attitudes towards Astronomy and Spatial Thinking Skills

Science.gov (United States)

Türk, Cumhur

2016-01-01

The purpose of this study was to examine the changes in pre-service Science teachers' astronomy achievement, attitudes towards astronomy and skills for spatial thinking in terms of their years of study. Another purpose of the study was to find out whether there was correlation between pre-service teachers' astronomy achievement, attitudes towards…

Spatial Distribution Characteristics of Healthcare Facilities in Nanjing: Network Point Pattern Analysis and Correlation Analysis

Directory of Open Access Journals (Sweden)

Jianhua Ni

2016-08-01

Full Text Available The spatial distribution of urban service facilities is largely constrained by the road network. In this study, network point pattern analysis and correlation analysis were used to analyze the relationship between road network and healthcare facility distribution. The weighted network kernel density estimation method proposed in this study identifies significant differences between the outside and inside areas of the Ming city wall. The results of network K-function analysis show that private hospitals are more evenly distributed than public hospitals, and pharmacy stores tend to cluster around hospitals along the road network. After computing the correlation analysis between different categorized hospitals and street centrality, we find that the distribution of these hospitals correlates highly with the street centralities, and that the correlations are higher with private and small hospitals than with public and large hospitals. The comprehensive analysis results could help examine the reasonability of existing urban healthcare facility distribution and optimize the location of new healthcare facilities.

Spatial Correlation of Pathology and Perfusion Changes within the Cortex and White Matter in Multiple Sclerosis.

Science.gov (United States)

Mulholland, A D; Vitorino, R; Hojjat, S-P; Ma, A Y; Zhang, L; Lee, L; Carroll, T J; Cantrell, C G; Figley, C R; Aviv, R I

2018-01-01

The spatial correlation between WM and cortical GM disease in multiple sclerosis is controversial and has not been previously assessed with perfusion MR imaging. We sought to determine the nature of association between lobar WM, cortical GM, volume and perfusion. Nineteen individuals with secondary-progressive multiple sclerosis, 19 with relapsing-remitting multiple sclerosis, and 19 age-matched healthy controls were recruited. Quantitative MR perfusion imaging was used to derive CBF, CBV, and MTT within cortical GM, WM, and T2-hyperintense lesions. A 2-step multivariate linear regression (corrected for age, disease duration, and Expanded Disability Status Scale) was used to assess correlations between perfusion and volume measures in global and lobar normal-appearing WM, cortical GM, and T2-hyperintense lesions. The Bonferroni adjustment was applied as appropriate. Global cortical GM and WM volume was significantly reduced for each group comparison, except cortical GM volume of those with relapsing-remitting multiple sclerosis versus controls. Global and lobar cortical GM CBF and CBV were reduced in secondary-progressive multiple sclerosis compared with other groups but not for relapsing-remitting multiple sclerosis versus controls. Global and lobar WM CBF and CBV were not significantly different across groups. The distribution of lobar cortical GM and WM volume reduction was disparate, except for the occipital lobes in patients with secondary-progressive multiple sclerosis versus those with relapsing-remitting multiple sclerosis. Moderate associations were identified between lobar cortical GM and lobar normal-appearing WM volume in controls and in the left temporal lobe in relapsing-remitting multiple sclerosis. No significant associations occurred between cortical GM and WM perfusion or volume. Strong correlations were observed between cortical-GM perfusion, normal appearing WM and lesional perfusion, with respect to each global and lobar region within HC, and

Correlation between electron-irradiation defects and applied stress in graphene: A molecular dynamics study

Energy Technology Data Exchange (ETDEWEB)

Kida, Shogo; Yamamoto, Masaya; Kawata, Hiroaki; Hirai, Yoshihiko; Yasuda, Masaaki, E-mail: yasuda@pe.osakafu-u.ac.jp [Department of Physics and Electronics, Osaka Prefecture University, Sakai, Osaka 599-8531 (Japan); Tada, Kazuhiro [Department of Electrical and Control Systems Engineering, National Institute of Technology, Toyama College, Toyama 939-8630 (Japan)

2015-09-15

Molecular dynamics (MD) simulations are performed to study the correlation between electron irradiation defects and applied stress in graphene. The electron irradiation effect is introduced by the binary collision model in the MD simulation. By applying a tensile stress to graphene, the number of adatom-vacancy (AV) and Stone–Wales (SW) defects increase under electron irradiation, while the number of single-vacancy defects is not noticeably affected by the applied stress. Both the activation and formation energies of an AV defect and the activation energy of an SW defect decrease when a tensile stress is applied to graphene. Applying tensile stress also relaxes the compression stress associated with SW defect formation. These effects induced by the applied stress cause the increase in AV and SW defect formation under electron irradiation.

Correlation measurements for fusion plasma diagnostics

International Nuclear Information System (INIS)

Pazsit, I.

1995-01-01

A list of a few methods for plasma diagnostics via fluctuations (noise) analysis of random (both temporally and spatially) system parameters is reviewed. Analogy is drawn with certain noise analysis methods, used in the diagnostics of fission reactors. These methods have been applied also to fusion measurements to some extent. However, the treatment of fusion plasma fluctuations is dominated by an approach that allows for temporal randomness, but assumes periodicity in space. This approach suits well a large class of phenomena such as magnetic fluctuations (MHD effects), but is much less suited to treat localised effects such as turbulence and density fluctuations. This paper discusses the potentials of the former approach, i.e. ordinary noise analysis methods of non-periodic variables in fusion plasma diagnostics. A new recommendation is to use the crossed beam correlation analysis of soft X-ray signals for determining the local short-range correlations in the plasma and to perform a systematic exploration of the plasma spatial correlation structure with that and other methods. 16 refs, 7 figs

Spatial correlations in compressible granular flows

OpenAIRE

Van Noije, T. P. C.; Ernst, M. H.; Brito López, Ricardo

1998-01-01

The clustering instability in freely evolving granular fluids manifests itself in the density-density correlation function and structure factor. These functions are calculated from fluctuating hydrodynamics. As time increases, the structure factor of density fluctuations develops a maximum, which shifts to smaller wave numbers (growing correlation length). Furthermore, the inclusion of longitudinal velocity fluctuations changes long-range correlations in the flow field qualitatively and exten...

Spatial but not temporal numerosity thresholds correlate with formal math skills in children.

Science.gov (United States)

Anobile, Giovanni; Arrighi, Roberto; Castaldi, Elisa; Grassi, Eleonora; Pedonese, Lara; Moscoso, Paula A M; Burr, David C

2018-03-01

Humans and other animals are able to make rough estimations of quantities using what has been termed the approximate number system (ANS). Much evidence suggests that sensitivity to numerosity correlates with symbolic math capacity, leading to the suggestion that the ANS may serve as a start-up tool to develop symbolic math. Many experiments have demonstrated that numerosity perception transcends the sensory modality of stimuli and their presentation format (sequential or simultaneous), but it remains an open question whether the relationship between numerosity and math generalizes over stimulus format and modality. Here we measured precision for estimating the numerosity of clouds of dots and sequences of flashes or clicks, as well as for paired comparisons of the numerosity of clouds of dots. Our results show that in children, formal math abilities correlate positively with sensitivity for estimation and paired-comparisons of the numerosity of visual arrays of dots. However, precision of numerosity estimation for sequences of flashes or sounds did not correlate with math, although sensitivities in all estimations tasks (for sequential or simultaneous stimuli) were strongly correlated with each other. In adults, we found no significant correlations between math scores and sensitivity to any of the psychophysical tasks. Taken together these results support the existence of a generalized number sense, and go on to demonstrate an intrinsic link between mathematics and perception of spatial, but not temporal numerosity. (PsycINFO Database Record (c) 2018 APA, all rights reserved).

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

Science.gov (United States)

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

2017-11-01

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

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

Science.gov (United States)

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

Detecting the Land-Cover Changes Induced by Large-Physical Disturbances Using Landscape Metrics, Spatial Sampling, Simulation and Spatial Analysis

Directory of Open Access Journals (Sweden)

Hone-Jay Chu

2009-08-01

Full Text Available The objectives of the study are to integrate the conditional Latin Hypercube Sampling (cLHS, sequential Gaussian simulation (SGS and spatial analysis in remotely sensed images, to monitor the effects of large chronological disturbances on spatial characteristics of landscape changes including spatial heterogeneity and variability. The multiple NDVI images demonstrate that spatial patterns of disturbed landscapes were successfully delineated by spatial analysis such as variogram, Moran’I and landscape metrics in the study area. The hybrid method delineates the spatial patterns and spatial variability of landscapes caused by these large disturbances. The cLHS approach is applied to select samples from Normalized Difference Vegetation Index (NDVI images from SPOT HRV images in the Chenyulan watershed of Taiwan, and then SGS with sufficient samples is used to generate maps of NDVI images. In final, the NDVI simulated maps are verified using indexes such as the correlation coefficient and mean absolute error (MAE. Therefore, the statistics and spatial structures of multiple NDVI images present a very robust behavior, which advocates the use of the index for the quantification of the landscape spatial patterns and land cover change. In addition, the results transferred by Open Geospatial techniques can be accessed from web-based and end-user applications of the watershed management.

Correlates of individual, and age-related, differences in short-term learning.

Science.gov (United States)

Zhang, Zhiyong; Davis, Hasker P; Salthouse, Timothy A; Tucker-Drob, Elliot M

2007-07-01

Latent growth models were applied to data on multitrial verbal and spatial learning tasks from two independent studies. Although significant individual differences in both initial level of performance and subsequent learning were found in both tasks, age differences were found only in mean initial level, and not in mean learning. In neither task was fluid or crystallized intelligence associated with learning. Although there were moderate correlations among the level parameters across the verbal and spatial tasks, the learning parameters were not significantly correlated with one another across task modalities. These results are inconsistent with the existence of a general (e.g., material-independent) learning ability.

Panel data models with spatial correlation: Estimation theory and an empirical investigation of the United States wholesale gasoline industry

Science.gov (United States)

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

Multilevel discretized random field models with 'spin' correlations for the simulation of environmental spatial data

International Nuclear Information System (INIS)

Žukovič, Milan; Hristopulos, Dionissios T

2009-01-01

A current problem of practical significance is how to analyze large, spatially distributed, environmental data sets. The problem is more challenging for variables that follow non-Gaussian distributions. We show by means of numerical simulations that the spatial correlations between variables can be captured by interactions between 'spins'. The spins represent multilevel discretizations of environmental variables with respect to a number of pre-defined thresholds. The spatial dependence between the 'spins' is imposed by means of short-range interactions. We present two approaches, inspired by the Ising and Potts models, that generate conditional simulations of spatially distributed variables from samples with missing data. Currently, the sampling and simulation points are assumed to be at the nodes of a regular grid. The conditional simulations of the 'spin system' are forced to respect locally the sample values and the system statistics globally. The second constraint is enforced by minimizing a cost function representing the deviation between normalized correlation energies of the simulated and the sample distributions. In the approach based on the N c -state Potts model, each point is assigned to one of N c classes. The interactions involve all the points simultaneously. In the Ising model approach, a sequential simulation scheme is used: the discretization at each simulation level is binomial (i.e., ± 1). Information propagates from lower to higher levels as the simulation proceeds. We compare the two approaches in terms of their ability to reproduce the target statistics (e.g., the histogram and the variogram of the sample distribution), to predict data at unsampled locations, as well as in terms of their computational complexity. The comparison is based on a non-Gaussian data set (derived from a digital elevation model of the Walker Lake area, Nevada, USA). We discuss the impact of relevant simulation parameters, such as the domain size, the number of

Spatially explicit models for inference about density in unmarked or partially marked populations

Science.gov (United States)

Chandler, Richard B.; Royle, J. Andrew

2013-01-01

Recently developed spatial capture–recapture (SCR) models represent a major advance over traditional capture–recapture (CR) models because they yield explicit estimates of animal density instead of population size within an unknown area. Furthermore, unlike nonspatial CR methods, SCR models account for heterogeneity in capture probability arising from the juxtaposition of animal activity centers and sample locations. Although the utility of SCR methods is gaining recognition, the requirement that all individuals can be uniquely identified excludes their use in many contexts. In this paper, we develop models for situations in which individual recognition is not possible, thereby allowing SCR concepts to be applied in studies of unmarked or partially marked populations. The data required for our model are spatially referenced counts made on one or more sample occasions at a collection of closely spaced sample units such that individuals can be encountered at multiple locations. Our approach includes a spatial point process for the animal activity centers and uses the spatial correlation in counts as information about the number and location of the activity centers. Camera-traps, hair snares, track plates, sound recordings, and even point counts can yield spatially correlated count data, and thus our model is widely applicable. A simulation study demonstrated that while the posterior mean exhibits frequentist bias on the order of 5–10% in small samples, the posterior mode is an accurate point estimator as long as adequate spatial correlation is present. Marking a subset of the population substantially increases posterior precision and is recommended whenever possible. We applied our model to avian point count data collected on an unmarked population of the northern parula (Parula americana) and obtained a density estimate (posterior mode) of 0.38 (95% CI: 0.19–1.64) birds/ha. Our paper challenges sampling and analytical conventions in ecology by demonstrating

Pilot study for supervised target detection applied to spatially registered multiparametric MRI in order to non-invasively score prostate cancer.

Science.gov (United States)

Mayer, Rulon; Simone, Charles B; Skinner, William; Turkbey, Baris; Choykey, Peter

2018-03-01

Gleason Score (GS) is a validated predictor of prostate cancer (PCa) disease progression and outcomes. GS from invasive needle biopsies suffers from significant inter-observer variability and possible sampling error, leading to underestimating disease severity ("underscoring") and can result in possible complications. A robust non-invasive image-based approach is, therefore, needed. Use spatially registered multi-parametric MRI (MP-MRI), signatures, and supervised target detection algorithms (STDA) to non-invasively GS PCa at the voxel level. This study retrospectively analyzed 26 MP-MRI from The Cancer Imaging Archive. The MP-MRI (T2, Diffusion Weighted, Dynamic Contrast Enhanced) were spatially registered to each other, combined into stacks, and stitched together to form hypercubes. Multi-parametric (or multi-spectral) signatures derived from a training set of registered MP-MRI were transformed using statistics-based Whitening-Dewhitening (WD). Transformed signatures were inserted into STDA (having conical decision surfaces) applied to registered MP-MRI determined the tumor GS. The MRI-derived GS was quantitatively compared to the pathologist's assessment of the histology of sectioned whole mount prostates from patients who underwent radical prostatectomy. In addition, a meta-analysis of 17 studies of needle biopsy determined GS with confusion matrices and was compared to the MRI-determined GS. STDA and histology determined GS are highly correlated (R = 0.86, p < 0.02). STDA more accurately determined GS and reduced GS underscoring of PCa relative to needle biopsy as summarized by meta-analysis (p < 0.05). This pilot study found registered MP-MRI, STDA, and WD transforms of signatures shows promise in non-invasively GS PCa and reducing underscoring with high spatial resolution. Copyright © 2018 Elsevier Ltd. All rights reserved.

Mineralogy of the clay fraction of alfisols in two slope curvatures: IV - spatial correlation with physical properties

Directory of Open Access Journals (Sweden)

Livia Arantes Camargo

2013-04-01

Full Text Available Although the influence of clay mineralogy on soil physical properties has been widely studied, spatial relationships between these features in Alfisols have rarely been examined. The purpose of this work was to relate the clay minerals and physical properties of an Alfisol of sandstone origin in two slope curvatures. The crystallographic properties such as mean crystallite size (MCS and width at half height (WHH of hematite, goethite, kaolinite and gibbsite; contents of hematite and goethite; aluminium substitution (AS and specific surface area (SSA of hematite and goethite; the goethite/(goethite+hematite and kaolinite/(kaolinite+gibbsite ratios; and the citrate/bicarbonate/dithionite extractable Fe (Fe d were correlated with the soil physical properties through Pearson correlation coefficients and cross-semivariograms. The correlations found between aluminium substitution in goethite and the soil physical properties suggest that the degree of crystallinity of this mineral influences soil properties used as soil quality indicators. Thus, goethite with a high aluminium substitution resulted in large aggregate sizes and a high porosity, and also in a low bulk density and soil penetration resistance. The presence of highly crystalline gibbsite resulted in a high density and micropore content, as well as in smaller aggregates. Interpretation of the cross-semivariogram and classification of landscape compartments in terms of the spatial dependence pattern for the relief-dependent physical and mineralogical properties of the soil proved an effective supplementary method for assessing Pearson correlations between the soil physical and mineralogical properties.

Considering built environment and spatial correlation in modelling pedestrian injury severity

DEFF Research Database (Denmark)

Prato, Carlo G.; Kaplan, Sigal; Patrier, Alexandre

traffic calming measures, illumination solutions, road maintenance programs and speed limit reductions. Moreover, this study emphasises the role of the built environment, as shopping areas, residential areas, and walking traffic density are positively related to a reduction in pedestrian injury severity......This study looks at mitigating and aggravating factors that are associated with the injury severity of pedestrians when they have crashes with another road user and overcomes existing limitations in the literature by posing attention on the built environment and considering spatial correlation...... of pedestrians to sustain a severe or fatal injury conditional on the occurrence of a crash with another road user. This study confirms previous findings about older pedestrians and intoxicated pedestrians being the most vulnerable road users, and crashes with heavy vehicles and in roads with higher speed limits...

Considering built environment and spatial correlation in modelling pedestrian injury severity

DEFF Research Database (Denmark)

Prato, Carlo G.; Kaplan, Sigal; Patrier, Alexandre

2018-01-01

traffic calming measures, illumination solutions, road maintenance programs and speed limit reductions. Moreover, this study emphasises the role of the built environment, as shopping areas, residential areas, and walking traffic density are positively related to a reduction in pedestrian injury severity......This study looks at mitigating and aggravating factors that are associated with the injury severity of pedestrians when they have crashes with another road user and overcomes existing limitations in the literature by posing attention on the built environment and considering spatial correlation...... of pedestrians to sustain a severe or fatal injury conditional on the occurrence of a crash with another road user. This study confirms previous findings about older pedestrians and intoxicated pedestrians being the most vulnerable road users, and crashes with heavy vehicles and in roads with higher speed limits...

Methane fugitive emissions quantification using the novel 'plume camera' (spatial correlation) method

Science.gov (United States)

Crosson, E.; Rella, C.

2012-12-01

Fugitive emissions of methane into the atmosphere are a major concern facing the natural gas production industry. Given that the global warming potential of methane is many times greater than that of carbon dioxide, the importance of quantifying methane emissions becomes clear. The rapidly increasing reliance on shale gas (or other unconventional sources) is only intensifying the interest in fugitive methane releases. Natural gas (which is predominantly methane) is an attractive energy source, as it emits 40% less carbon dioxide per Joule of energy generated than coal. However, if just a small percentage of the natural gas consumed is lost due to fugitive emissions during production, processing, or transport, this global warming benefit is lost (Howarth et al. 2012). It is therefore imperative, as production of natural gas increases, that the fugitive emissions of methane are quantified accurately. Traditional direct measurement techniques often involve physical access of the leak itself to quantify the emissions rate, and are generally require painstaking effort to first find the leak and then quantify the emissions rate. With over half a million natural gas producing wells in the U.S. (U.S. Energy Information Administration), not including the associated processing, storage, and transport facilities, and with each facility having hundreds or even thousands of fittings that can potentially leak, the need is clear to develop methodologies that can provide a rapid and accurate assessment of the total emissions rate on a per-well head basis. In this paper we present a novel method for emissions quantification which uses a 'plume camera' with three 'pixels' to quantify emissions using direct measurements of methane concentration in the downwind plume. By analyzing the spatial correlation between the pixels, the spatial extent of the instantaneous plume can be inferred. This information, when combined with the wind speed through the measurement plane, provides a direct

Fiber transport of spatially entangled photons

Science.gov (United States)

Löffler, W.; Eliel, E. R.; Woerdman, J. P.; Euser, T. G.; Scharrer, M.; Russell, P.

2012-03-01

High-dimensional entangled photons pairs are interesting for quantum information and cryptography: Compared to the well-known 2D polarization case, the stronger non-local quantum correlations could improve noise resistance or security, and the larger amount of information per photon increases the available bandwidth. One implementation is to use entanglement in the spatial degree of freedom of twin photons created by spontaneous parametric down-conversion, which is equivalent to orbital angular momentum entanglement, this has been proven to be an excellent model system. The use of optical fiber technology for distribution of such photons has only very recently been practically demonstrated and is of fundamental and applied interest. It poses a big challenge compared to the established time and frequency domain methods: For spatially entangled photons, fiber transport requires the use of multimode fibers, and mode coupling and intermodal dispersion therein must be minimized not to destroy the spatial quantum correlations. We demonstrate that these shortcomings of conventional multimode fibers can be overcome by using a hollow-core photonic crystal fiber, which follows the paradigm to mimic free-space transport as good as possible, and are able to confirm entanglement of the fiber-transported photons. Fiber transport of spatially entangled photons is largely unexplored yet, therefore we discuss the main complications, the interplay of intermodal dispersion and mode mixing, the influence of external stress and core deformations, and consider the pros and cons of various fiber types.

Brain correlates of the orientation of auditory spatial attention onto speaker location in a "cocktail-party" situation.

Science.gov (United States)

Lewald, Jörg; Hanenberg, Christina; Getzmann, Stephan

2016-10-01

Successful speech perception in complex auditory scenes with multiple competing speakers requires spatial segregation of auditory streams into perceptually distinct and coherent auditory objects and focusing of attention toward the speaker of interest. Here, we focused on the neural basis of this remarkable capacity of the human auditory system and investigated the spatiotemporal sequence of neural activity within the cortical network engaged in solving the "cocktail-party" problem. Twenty-eight subjects localized a target word in the presence of three competing sound sources. The analysis of the ERPs revealed an anterior contralateral subcomponent of the N2 (N2ac), computed as the difference waveform for targets to the left minus targets to the right. The N2ac peaked at about 500 ms after stimulus onset, and its amplitude was correlated with better localization performance. Cortical source localization for the contrast of left versus right targets at the time of the N2ac revealed a maximum in the region around left superior frontal sulcus and frontal eye field, both of which are known to be involved in processing of auditory spatial information. In addition, a posterior-contralateral late positive subcomponent (LPCpc) occurred at a latency of about 700 ms. Both these subcomponents are potential correlates of allocation of spatial attention to the target under cocktail-party conditions. © 2016 Society for Psychophysiological Research.

The Problem of English Spatial, Non-spatial and Idiomatic Adpositions in Iranian EFL Environment: A Prototypical Approach

Directory of Open Access Journals (Sweden)

Nassim Golaghaei

2010-11-01

Full Text Available Several studies of L2 learners’ interlanguage have addressed the complexity of the English adpositional system due to several reasons like L1 transfer, lack of knowledge in L2 and the strong collocational relations of prepositions with other elements of the English language. The major purpose of the present study is to evaluate the performance of Iranian students in dealing with three broad categories of spatial, non-spatial and idiomatic adpositions in English. To achieve the inclinations of the research project, 60 students majoring in TEFL at Roudehen University were selected. A paper-based TOEFL test of English Proficiency was administered to obtain some information about the participants’ general language proficiency. Three completion tasks with the division of spatial, non-spatial (nominal, adjectival and verbal and idiomatic adpositions were administered. The obtained results represented the fact that the Iranian participants were considerably inclined to transfer their L1 adpositional patterns to their L2 production. The correlational analyses indicated that whereas the scores related to adposition task in general, non-spatial as well as the idiomatic subtests were strongly correlated with the scores obtained from the TOEFL test, there was a moderate correlation between the spatial subtest and the TOEFL one. The independent sample t-test results between the freshmen and sophomores dealing with spatial, nominal and adjectival subtests were considered to be significant.  However, in reference to the verbal subtest, the difference between the two groups was not significant. The results obtained from the independent sample t-test indicated no significant differences between the freshmen and sophomores in their performance on idiomatic adpositions. Finally, the result of the correlation coefficients showed high correlation coefficients between the whole adposition test and the three subtests of spatial, non-spatial and idiomatic ones

TRENDS IN FLOODS AND LOW FLOWS IN THE UNITED STATES: IMPACT OF SPATIAL CORRELATION. (R824992,R826888)

Science.gov (United States)

Trends in flood and low flows in the US were evaluated using a regional average Kendall's S trend test at two spatial scales and over two timeframes. Field significance was assessed using a bootstrap methodology to account for the observed regional cross-correlation of streamflow...

Fast methods for spatially correlated multilevel functional data

KAUST Repository

Staicu, A.-M.

2010-01-19

We propose a new methodological framework for the analysis of hierarchical functional data when the functions at the lowest level of the hierarchy are correlated. For small data sets, our methodology leads to a computational algorithm that is orders of magnitude more efficient than its closest competitor (seconds versus hours). For large data sets, our algorithm remains fast and has no current competitors. Thus, in contrast to published methods, we can now conduct routine simulations, leave-one-out analyses, and nonparametric bootstrap sampling. Our methods are inspired by and applied to data obtained from a state-of-the-art colon carcinogenesis scientific experiment. However, our models are general and will be relevant to many new data sets where the object of inference are functions or images that remain dependent even after conditioning on the subject on which they are measured. Supplementary materials are available at Biostatistics online.

IMPROVING CORRELATION FUNCTION FITTING WITH RIDGE REGRESSION: APPLICATION TO CROSS-CORRELATION RECONSTRUCTION

International Nuclear Information System (INIS)

Matthews, Daniel J.; Newman, Jeffrey A.

2012-01-01

Cross-correlation techniques provide a promising avenue for calibrating photometric redshifts and determining redshift distributions using spectroscopy which is systematically incomplete (e.g., current deep spectroscopic surveys fail to obtain secure redshifts for 30%-50% or more of the galaxies targeted). In this paper, we improve on the redshift distribution reconstruction methods from our previous work by incorporating full covariance information into our correlation function fits. Correlation function measurements are strongly covariant between angular or spatial bins, and accounting for this in fitting can yield substantial reduction in errors. However, frequently the covariance matrices used in these calculations are determined from a relatively small set (dozens rather than hundreds) of subsamples or mock catalogs, resulting in noisy covariance matrices whose inversion is ill-conditioned and numerically unstable. We present here a method of conditioning the covariance matrix known as ridge regression which results in a more well behaved inversion than other techniques common in large-scale structure studies. We demonstrate that ridge regression significantly improves the determination of correlation function parameters. We then apply these improved techniques to the problem of reconstructing redshift distributions. By incorporating full covariance information, applying ridge regression, and changing the weighting of fields in obtaining average correlation functions, we obtain reductions in the mean redshift distribution reconstruction error of as much as ∼40% compared to previous methods. We provide a description of POWERFIT, an IDL code for performing power-law fits to correlation functions with ridge regression conditioning that we are making publicly available.

Remote Sensing Image Fusion Based on the Combination Grey Absolute Correlation Degree and IHS Transform

Directory of Open Access Journals (Sweden)

Hui LIN

2014-12-01

Full Text Available An improved fusion algorithm for multi-source remote sensing images with high spatial resolution and multi-spectral capacity is proposed based on traditional IHS fusion and grey correlation analysis. Firstly, grey absolute correlation degree is used to discriminate non-edge pixels and edge pixels in high-spatial resolution images, by which the weight of intensity component is identified in order to combine it with high-spatial resolution image. Therefore, image fusion is achieved using IHS inverse transform. The proposed method is applied to ETM+ multi-spectral images and panchromatic image, and Quickbird’s multi-spectral images and panchromatic image respectively. The experiments prove that the fusion method proposed in the paper can efficiently preserve spectral information of the original multi-spectral images while enhancing spatial resolution greatly. By comparison and analysis, the proposed fusion algorithm is better than traditional IHS fusion and fusion method based on grey correlation analysis and IHS transform.

The Neural Correlates of Spatial and Object Working Memory in Elderly and Parkinson's Disease Subjects

OpenAIRE

Caminiti, Silvia P.; Siri, Chiara; Guidi, Lucia; Antonini, Angelo; Perani, Daniela

2015-01-01

This fMRI study deals with the neural correlates of spatial and objects working memory (SWM and OWM) in elderly subjects (ESs) and idiopathic Parkinson’s disease (IPD). Normal aging and IPD can be associated with a WM decline. In IPD population, some studies reported similar SWM and OWM deficits; others reported a greater SWM than OWM impairment. In the present fMRI research, we investigated whether compensated IPD patients and elderly subjects with comparable performance during the execution...

Perception and psychological evaluation for visual and auditory environment based on the correlation mechanisms

Science.gov (United States)

Fujii, Kenji

2002-06-01

In this dissertation, the correlation mechanism in modeling the process in the visual perception is introduced. It has been well described that the correlation mechanism is effective for describing subjective attributes in auditory perception. The main result is that it is possible to apply the correlation mechanism to the process in temporal vision and spatial vision, as well as in audition. (1) The psychophysical experiment was performed on subjective flicker rates for complex waveforms. A remarkable result is that the phenomenon of missing fundamental is found in temporal vision as analogous to the auditory pitch perception. This implies the existence of correlation mechanism in visual system. (2) For spatial vision, the autocorrelation analysis provides useful measures for describing three primary perceptual properties of visual texture: contrast, coarseness, and regularity. Another experiment showed that the degree of regularity is a salient cue for texture preference judgment. (3) In addition, the autocorrelation function (ACF) and inter-aural cross-correlation function (IACF) were applied for analysis of the temporal and spatial properties of environmental noise. It was confirmed that the acoustical properties of aircraft noise and traffic noise are well described. These analyses provided useful parameters extracted from the ACF and IACF in assessing the subjective annoyance for noise. Thesis advisor: Yoichi Ando Copies of this thesis written in English can be obtained from Junko Atagi, 6813 Mosonou, Saijo-cho, Higashi-Hiroshima 739-0024, Japan. E-mail address: atagi\\@urban.ne.jp.

Laboratory demonstration of Stellar Intensity Interferometry using a software correlator

Science.gov (United States)

Matthews, Nolan; Kieda, David

2017-06-01

In this talk I will present measurements of the spatial coherence function of laboratory thermal (black-body) sources using Hanbury-Brown and Twiss interferometry with a digital off-line correlator. Correlations in the intensity fluctuations of a thermal source, such as a star, allow retrieval of the second order coherence function which can be used to perform high resolution imaging and source geometry characterization. We also demonstrate that intensity fluctuations between orthogonal polarization states are uncorrelated but can be used to reduce systematic noise. The work performed here can readily be applied to existing and future Imaging Air-Cherenkov telescopes to measure spatial properties of stellar sources. Some possible candidates for astronomy applications include close binary star systems, fast rotators, Cepheid variables, and potentially even exoplanet characterization.

A GIS-based spatial correlation analysis for ambient air pollution and AECOPD hospitalizations in Jinan, China.

Science.gov (United States)

Wang, Wenqiao; Ying, Yangyang; Wu, Quanyuan; Zhang, Haiping; Ma, Dedong; Xiao, Wei

2015-03-01

workplace associated with a 7% (95%CI: [3.3%, 10%]) increase of hospitalizations due to AECOPD. Ambient air pollution is correlated with AECOPD hospitalizations spatially. A 10 μg/m(3) increase of PM10 at workplace was associated with a 7% (95%CI: [3.3%, 10%]) increase of hospitalizations due to AECOPD in Jinan, 2009. As a spatial data processing tool, GIS has novel and great potential on air pollutants exposure assessment and spatial analysis in AECOPD research. Copyright © 2015 Elsevier Ltd. All rights reserved.

Applying Metrological Techniques to Satellite Fundamental Climate Data Records

Science.gov (United States)

Woolliams, Emma R.; Mittaz, Jonathan PD; Merchant, Christopher J.; Hunt, Samuel E.; Harris, Peter M.

2018-02-01

Quantifying long-term environmental variability, including climatic trends, requires decadal-scale time series of observations. The reliability of such trend analysis depends on the long-term stability of the data record, and understanding the sources of uncertainty in historic, current and future sensors. We give a brief overview on how metrological techniques can be applied to historical satellite data sets. In particular we discuss the implications of error correlation at different spatial and temporal scales and the forms of such correlation and consider how uncertainty is propagated with partial correlation. We give a form of the Law of Propagation of Uncertainties that considers the propagation of uncertainties associated with common errors to give the covariance associated with Earth observations in different spectral channels.

Photon propagation in heterogeneous optical media with spatial correlations: enhanced mean-free-paths and wider-than-exponential free-path distributions

International Nuclear Information System (INIS)

Davis, A.B.; Marshak, Alexander

2004-01-01

Beer's law of exponential decay in direct transmission is well-known but its break-down in spatially variable optical media has been discussed only sporadically in the literature. We document here this break-down in three-dimensional (3D) media with complete generality and explore its ramifications for photon propagation. We show that effective transmission laws and their associated free-path distributions (FPDs) are in fact never exactly exponential in variable media of any kind. Moreover, if spatial correlations in the extinction field extend at least to the scale of the mean-free-path (MFP), FPDs are necessarily wider-than-exponential in the sense that all higher-order moments of the relevant mean-field FPDs exceed those of the exponential FPD, even if it is tuned to yield the proper MFP. The MFP itself is always larger than the inverse of average extinction in a variable medium. In a vast and important class of spatially-correlated random media, the MFP is indeed the average of the inverse of extinction. We translate these theoretical findings into a practical method for deciding a priori when 3D effects become important. Finally, we discuss an obvious but limited analogy between our analysis of spatial variability and the well-known effects of strong spectral variability in gaseous media when observed or modeled at moderate resolution

A Generalized Spatial Correlation Model for 3D MIMO Channels based on the Fourier Coefficients of Power Spectrums

KAUST Repository

Nadeem, Qurrat-Ul-Ain

2015-05-07

Previous studies have confirmed the adverse impact of fading correlation on the mutual information (MI) of two-dimensional (2D) multiple-input multiple-output (MIMO) systems. More recently, the trend is to enhance the system performance by exploiting the channel’s degrees of freedom in the elevation, which necessitates the derivation and characterization of three-dimensional (3D) channels in the presence of spatial correlation. In this paper, an exact closed-form expression for the Spatial Correlation Function (SCF) is derived for 3D MIMO channels. This novel SCF is developed for a uniform linear array of antennas with nonisotropic antenna patterns. The proposed method resorts to the spherical harmonic expansion (SHE) of plane waves and the trigonometric expansion of Legendre and associated Legendre polynomials. The resulting expression depends on the underlying arbitrary angular distributions and antenna patterns through the Fourier Series (FS) coefficients of power azimuth and elevation spectrums. The novelty of the proposed method lies in the SCF being valid for any 3D propagation environment. The developed SCF determines the covariance matrices at the transmitter and the receiver that form the Kronecker channel model. In order to quantify the effects of correlation on the system performance, the information-theoretic deterministic equivalents of the MI for the Kronecker model are utilized in both mono-user and multi-user cases. Numerical results validate the proposed analytical expressions and elucidate the dependence of the system performance on azimuth and elevation angular spreads and antenna patterns. Some useful insights into the behaviour of MI as a function of downtilt angles are provided. The derived model will help evaluate the performance of correlated 3D MIMO channels in the future.

Correlation analysis of the urban heat island effect and the spatial and temporal distribution of atmospheric particulates using TM images in Beijing

International Nuclear Information System (INIS)

Xu, L.Y.; Xie, X.D.; Li, S.

2013-01-01

This study combines the methods of observation statistics and remote sensing retrieval, using remote sensing information including the urban heat island (UHI) intensity index, the normalized difference vegetation index (NDVI), the normalized difference water index (NDWI), and the difference vegetation index (DVI) to analyze the correlation between the urban heat island effect and the spatial and temporal concentration distributions of atmospheric particulates in Beijing. The analysis establishes (1) a direct correlation between UHI and DVI; (2) an indirect correlation among UHI, NDWI and DVI; and (3) an indirect correlation among UHI, NDVI, and DVI. The results proved the existence of three correlation types with regional and seasonal effects and revealed an interesting correlation between UHI and DVI, that is, if UHI is below 0.1, then DVI increases with the increase in UHI, and vice versa. Also, DVI changes more with UHI in the two middle zones of Beijing. -- Highlights: •We analyze the correlation from the spatial and temporal views. •We present correlation analyses among UHI, NDWI, NDVI, and DVI from three perspectives. •Three correlations are proven to exist with regional and seasonal effects. •If UHI is below 0.1, then DVI increases with the increase in UHI, and vice versa. •The DVI changes more with UHI in the two middle zones of Beijing. -- Generally, if UHI is below 0.1 in the weak heat island or green island range, then DVI increases with the increase in UHI, and vice versa

Spatially heterogeneous ages in glassy dynamics

International Nuclear Information System (INIS)

Castillo, Horacio E.; Chamon, Claudio Chamon; Cugliandolo, Leticia F.; Iguain, Jose Luis; Kennett, Malcolm P.

2003-09-01

We construct a framework for the study of fluctuations in the nonequilibrium relaxation of glassy systems with and without quenched disorder. We study two types of two-time local correlators with the aim of characterizing the heterogeneous evolution in these systems: in one case we average the local correlators over histories of the thermal noise, in the other case we simply coarse-grain the local correlators obtained for a given noise realization. We explain why the noise-averaged correlators describe the fingerprint of quenched disorder when it exists, while the coarse-grained correlators are linked to noise-induced mesoscopic fluctuations. We predict constraints on the distribution of the fluctuations of the coarse-grained quantities. In particular, we show that locally defined correlations and responses are connected by a generalized local out-of-equilibrium fluctuation-dissipation relation. We argue that large size heterogeneities in the age of the system survive in the long-time limit. A symmetry of the underlying theory, namely invariance under reparametrizations of the time coordinates, underlies these results. We establish a connection between the probabilities of spatial distributions of local coarse-grained quantities and the theory of dynamic random manifolds. We define, and discuss the behavior of, a two-time dependent correlation length from the spatial decay of the fluctuations in the two-time local functions. We characterize the fluctuations in the system in terms of their fractal properties. For concreteness, we present numerical tests performed on disordered spin models in finite and infinite dimensions. Finally, we explain how these ideas can be applied to the analysis of the dynamics of other glassy systems that can be either spin models without disorder or atomic and molecular glassy systems. (author)

Nonparametric Bayesian models for a spatial covariance.

Science.gov (United States)

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.

Physically-based modeling of topographic effects on spatial evapotranspiration and soil moisture patterns through radiation and wind

Directory of Open Access Journals (Sweden)

M. Liu

2012-02-01

Full Text Available In this paper, simulations with the Soil Water Atmosphere Plant (SWAP model are performed to quantify the spatial variability of both potential and actual evapotranspiration (ET, and soil moisture content (SMC caused by topography-induced spatial wind and radiation differences. To obtain the spatially distributed ET/SMC patterns, the field scale SWAP model is applied in a distributed way for both pointwise and catchment wide simulations. An adapted radiation model from r.sun and the physically-based meso-scale wind model METRAS PC are applied to obtain the spatial radiation and wind patterns respectively, which show significant spatial variation and correlation with aspect and elevation respectively. Such topographic dependences and spatial variations further propagate to ET/SMC. A strong spatial, seasonal-dependent, scale-relevant intra-catchment variability in daily/annual ET and less variability in SMC can be observed from the numerical experiments. The study concludes that topography has a significant effect on ET/SMC in the humid region where ET is a energy limited rather than water availability limited process. It affects the spatial runoff generation through spatial radiation and wind, therefore should be applied to inform hydrological model development. In addition, the methodology used in the study can serve as a general method for physically-based ET estimation for data sparse regions.

Spatial-Temporal Clustering of Tornadoes

Science.gov (United States)

Malamud, Bruce D.; Turcotte, Donald L.; Brooks, Harold E.

2017-04-01

The standard measure of the intensity of a tornado is the Enhanced Fujita scale, which is based qualitatively on the damage caused by a tornado. An alternative measure of tornado intensity is the tornado path length, L. Here we examine the spatial-temporal clustering of severe tornadoes, which we define as having path lengths L ≥ 10 km. Of particular concern are tornado outbreaks, when a large number of severe tornadoes occur in a day in a restricted region. We apply a spatial-temporal clustering analysis developed for earthquakes. We take all pairs of severe tornadoes in observed and modelled outbreaks, and for each pair plot the spatial lag (distance between touchdown points) against the temporal lag (time between touchdown points). We apply our spatial-temporal lag methodology to the intense tornado outbreaks in the central United States on 26 and 27 April 2011, which resulted in over 300 fatalities and produced 109 severe (L ≥ 10 km) tornadoes. The patterns of spatial-temporal lag correlations that we obtain for the 2 days are strikingly different. On 26 April 2011, there were 45 severe tornadoes and our clustering analysis is dominated by a complex sequence of linear features. We associate the linear patterns with the tornadoes generated in either a single cell thunderstorm or a closely spaced cluster of single cell thunderstorms moving at a near-constant velocity. Our study of a derecho tornado outbreak of six severe tornadoes on 4 April 2011 along with modelled outbreak scenarios confirms this association. On 27 April 2011, there were 64 severe tornadoes and our clustering analysis is predominantly random with virtually no embedded linear patterns. We associate this pattern with a large number of interacting supercell thunderstorms generating tornadoes randomly in space and time. In order to better understand these associations, we also applied our approach to the Great Plains tornado outbreak of 3 May 1999. Careful studies by others have associated

Wiener spectral effects of spatial correlation between the sites of characteristic x-ray emission and reabsorption in radiographic screen-film systems

Energy Technology Data Exchange (ETDEWEB)

Metz, C E; Vyborny, C J [Chicago Univ., IL (USA). Dept. of Radiology

1983-05-01

When characteristic x-rays are generated and reabsorbed in the phosphor of a radiographic screen-film system, the positions at which light is emitted from the initial and secondary interactions are correlated. A simple statistical model is developed to account for the effect of this correlation on the Wiener spectrum of quantum mottle. Unlike previous models, which ignore spatial correlation, the new model predicts that not only noise magnitude but also noise texture is changed as the incident x-ray energy exceeds the phosphor K-edge.

Spatially resolved vertical vorticity in solar supergranulation using helioseismology and local correlation tracking

Science.gov (United States)

Langfellner, J.; Gizon, L.; Birch, A. C.

2015-09-01

Flow vorticity is a fundamental property of turbulent convection in rotating systems. Solar supergranules exhibit a preferred sense of rotation, which depends on the hemisphere. This is due to the Coriolis force acting on the diverging horizontal flows. We aim to spatially resolve the vertical flow vorticity of the average supergranule at different latitudes, both for outflow and inflow regions. To measure the vertical vorticity, we use two independent techniques: time-distance helioseismology (TD) and local correlation tracking of granules in intensity images (LCT) using data from the Helioseismic and Magnetic Imager (HMI) on board the Solar Dynamics Observatory (SDO). Both maps are corrected for center-to-limb systematic errors. We find that 8 h TD and LCT maps of vertical vorticity are highly correlated at large spatial scales. Associated with the average supergranule outflow, we find tangential (vortical) flows that reach about 10 m s-1 in the clockwise direction at 40° latitude. In average inflow regions, the tangential flow reaches the same magnitude, but in the anticlockwise direction. These tangential velocities are much smaller than the radial (diverging) flow component (300 m s-1 for the average outflow and 200 m s-1 for the average inflow). The results for TD and LCT as measured from HMI are in excellent agreement for latitudes between -60° and 60°. From HMI LCT, we measure the vorticity peak of the average supergranule to have a full width at half maximum of about 13 Mm for outflows and 8 Mm for inflows. This is larger than the spatial resolution of the LCT measurements (about 3 Mm). On the other hand, the vorticity peak in outflows is about half the value measured at inflows (e.g., 4 × 10-6 s-1 clockwise compared to 8 × 10-6 s-1 anticlockwise at 40° latitude). Results from the Michelson Doppler Imager (MDI) on board the Solar and Heliospheric Observatory (SOHO) obtained in 2010 are biased compared to the HMI/SDO results for the same period

Integrating spatially explicit indices of abundance and habitat quality: an applied example for greater sage-grouse management.

Science.gov (United States)

Coates, Peter S; Casazza, Michael L; Ricca, Mark A; Brussee, Brianne E; Blomberg, Erik J; Gustafson, K Benjamin; Overton, Cory T; Davis, Dawn M; Niell, Lara E; Espinosa, Shawn P; Gardner, Scott C; Delehanty, David J

2016-02-01

intensity across multiple spatial scales. As applied to sage-grouse, the composite map identifies spatially explicit management categories within sagebrush steppe that are most critical to sustaining sage-grouse populations as well as those areas where changes in land use would likely have minimal impact. Importantly, collaborative efforts among stakeholders guide which intersections of habitat selection indices and abundance and space use classes are used to define management categories. Because sage-grouse are an umbrella species, our joint-index modelling approach can help target effective conservation for other sagebrush obligate species and can be readily applied to species in other ecosystems with similar life histories, such as central-placed breeding.

Integrating spatially explicit indices of abundance and habitat quality: an applied example for greater sage-grouse management

Science.gov (United States)

Coates, Peter S.; Casazza, Michael L.; Ricca, Mark A.; Brussee, Brianne E.; Blomberg, Erik J.; Gustafson, K. Benjamin; Overton, Cory T.; Davis, Dawn M.; Niell, Lara E.; Espinosa, Shawn P.; Gardner, Scott C.; Delehanty, David J.

2016-01-01

multiple spatial scales. As applied to sage-grouse, the composite map identifies spatially explicit management categories within sagebrush steppe that are most critical to sustaining sage-grouse populations as well as those areas where changes in land use would likely have minimal impact. Importantly, collaborative efforts among stakeholders guide which intersections of habitat selection indices and abundance and space use classes are used to define management categories. Because sage-grouse are an umbrella species, our joint-index modelling approach can help target effective conservation for other sagebrush obligate species, and can be readily applied to species in other ecosystems with similar life histories, such as central-placed breeding.

Visual Spatial Attention Training Improve Spatial Attention and Motor Control for Unilateral Neglect Patients.

Science.gov (United States)

Wang, Wei; Ji, Xiangtong; Ni, Jun; Ye, Qian; Zhang, Sicong; Chen, Wenli; Bian, Rong; Yu, Cui; Zhang, Wenting; Shen, Guangyu; Machado, Sergio; Yuan, Tifei; Shan, Chunlei

2015-01-01

To compare the effect of visual spatial training on the spatial attention to that on motor control and to correlate the improvement of spatial attention to motor control progress after visual spatial training in subjects with unilateral spatial neglect (USN). 9 cases with USN after right cerebral stroke were randomly divided into Conventional treatment group + visual spatial attention and Conventional treatment group. The Conventional treatment group + visual spatial attention received conventional rehabilitation therapy (physical and occupational therapy) and visual spatial attention training (optokinetic stimulation and right half-field eye patching). The Conventional treatment group was only treated with conventional rehabilitation training (physical and occupational therapy). All patients were assessed by behavioral inattention test (BIT), Fugl-Meyer Assessment of motor function (FMA), equilibrium coordination test (ECT) and non-equilibrium coordination test (NCT) before and after 4 weeks treatment. Total scores in both groups (without visual spatial attention/with visual spatial attention) improved significantly (BIT: P=0.021/P=0.000, d=1.667/d=2.116, power=0.69/power=0.98, 95%CI[-0.8839,45.88]/95%CI=[16.96,92.64]; FMA: P=0.002/P=0.000, d=2.521/d=2.700, power=0.93/power=0.98, 95%CI[5.707,30.79]/95%CI=[16.06,53.94]; ECT: P=0.002/ P=0.000, d=2.031/d=1.354, power=0.90/power=0.17, 95%CI[3.380,42.61]/95%CI=[-1.478,39.08]; NCT: P=0.013/P=0.000, d=1.124/d=1.822, power=0.41/power=0.56, 95%CI[-7.980,37.48]/95%CI=[4.798,43.60],) after treatment. Among the 2 groups, the group with visual spatial attention significantly improved in BIT (P=0.003, d=3.103, power=1, 95%CI[15.68,48.92]), FMA of upper extremity (P=0.006, d=2.771, power=1, 95%CI[5.061,20.14]) and NCT (P=0.010, d=2.214, power=0.81-0.90, 95%CI[3.018,15.88]). Correlative analysis shows that the change of BIT scores is positively correlated to the change of FMA total score (r=0.77, Pvisual spatial training could

A Comparison of Weights Matrices on Computation of Dengue Spatial Autocorrelation

Science.gov (United States)

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

Multivariate and spatial statistical analysis of Callovo-Oxfordian physical properties from lab and borehole logs data: towards a characterization of lateral and vertical spatial trends in the Meuse/Haute-Marne transposition zone

International Nuclear Information System (INIS)

Garcia, M.H.; Rabaute, A.; Yven, B.; Guillemot, D.

2010-01-01

Document available in extended abstract form only. The geological exploration of the Meuse/Haute-Marne area began in 1994. Several boreholes were drilled, and the Callovo-Oxfordian argillite, thought to become a potential storage formation, were cored and logged. 2D and 3D seismic surveys were completed, as well as geological field observations, and an underground research laboratory was created. A 250 km 2 -wide Transposition Zone was delimited, which was subject to further investigations in 2007 and 2008, including another series of coring and logging in four additional boreholes, and a tighter 2D seismic survey. The main objective of this study was to improve the knowledge of the spatial variability of geological and physical properties of the Callovo-Oxfordian formation. The paper focuses on the three following aspects of the study to present and discuss the methods that have been used and the results that have been obtained: - Use of well-log data to identify equivalent homogeneous log-units on the boreholes. - Relating log attributes to physical properties of argillites measured on cores in laboratory. - Study of lateral and vertical spatial trends of selected physical properties across the Transposition Zone (TZ). To identify equivalent homogeneous log-units, a combination of Principal Component Analysis (PCA) and Fuzzy Cluster Analysis (FCA) was used. PCA was classically performed to reduce the number of variables to retain principal components gathering most of the original dataset variance. PCA was also used to identify isolated groups of correlated variables that could be associated to different properties of the formation. Then, FCA was applied to identify homogeneous log-units on the eight boreholes across the TZ. Well-logs data being much more numerous and better distributed along boreholes than lab data measured on rock samples, relations and correlations were sought between the two types of data to identify log attributes that were likely to provide

Summary of the Nevada Applied Ecology Group and correlative programs. Version 1

Energy Technology Data Exchange (ETDEWEB)

Friesen, H.N. [Raytheon Services Nevada, Las Vegas, NV (United States)

1992-10-01

This summary document presents results in a broad context; it is not limited to findings of the Nevada Applied Ecology Group. This book is organized to present the findings of the Nevada Applied Ecology Group and correlative programs in accordance with the originally stated objectives of the Nevada Applied Ecology Group. This plan, in essence, traces plutonium from its injection into the environment to movement in the ecosystem to development of cleanup techniques. Information on other radionuclides was also obtained and will be presented briefly. Chapter 1 presents a brief description of the ecological setting of the Test Range Complex. The results of investigations for plutonium distribution are presented in Chapter 2 for the area surrounding the Test Range Complex and in Chapter 3 for on-site locations. Chapters 4 and 5 present the results of investigations concerned with concentrations and movement, respectively, of plutonium in the ecosystem of the Test Range Complex, and Chapter 6 summarizes the potential hazard from this plutonium. Development of techniques for cleanup and treatment is presented in Chapter 7, and the inventory of radionuclides other than plutonium is presented briefly in Chapter 8.

Complex Networks Dynamics Based on Events-Phase Synchronization and Intensity Correlation Applied to The Anomaly Patterns and Extremes in The Tropical African Climate System

Science.gov (United States)

Oluoch, K.; Marwan, N.; Trauth, M.; Loew, A.; Kurths, J.

2012-04-01

The African continent lie almost entirely within the tropics and as such its (tropical) climate systems are predominantly governed by the heterogeneous, spatial and temporal variability of the Hadley and Walker circulations. The variabilities in these meridional and zonal circulations lead to intensification or suppression of the intensities, durations and frequencies of the Inter-tropical Convergence Zone (ICTZ) migration, trade winds and subtropical high-pressure regions and the continental monsoons. The above features play a central role in determining the African rainfall spatial and temporal variability patterns. The current understanding of these climate features and their influence on the rainfall patterns is not sufficiently understood. Like many real-world systems, atmospheric-oceanic processes exhibit non-linear properties that can be better explored using non-linear (NL) methods of time-series analysis. Over the recent years, the complex network approach has evolved as a powerful new player in understanding spatio-temporal dynamics and evolution of complex systems. Together with NL techniques, it is continuing to find new applications in many areas of science and technology including climate research. We would like to use these two powerful methods to understand the spatial structure and dynamics of African rainfall anomaly patterns and extremes. The method of event synchronization (ES) developed by Quiroga et al., 2002 and first applied to climate networks by Malik et al., 2011 looks at correlations with a dynamic time lag and as such, it is a more intuitive way to correlate a complex and heterogeneous system like climate networks than a fixed time delay most commonly used. On the other hand, the short comings of ES is its lack of vigorous test statistics for the significance level of the correlations, and the fact that only the events' time indices are synchronized while all information about how the relative intensities propagate within network

Contamination and Spatial Variation of Heavy Metals in the Soil-Rice System in Nanxun County, Southeastern China

Science.gov (United States)

Zhao, Keli; Fu, Weijun; Ye, Zhengqian; Zhang, Chaosheng

2015-01-01

There is an increasing concern about heavy metal contamination in farmland in China and worldwide. In order to reveal the spatial features of heavy metals in the soil-rice system, soil and rice samples were collected from Nanxun, Southeastern China. Compared with the guideline values, elevated concentrations of heavy metals in soils were observed, while heavy metals in rice still remained at a safe level. Heavy metals in soils and rice had moderate to strong spatial dependence (nugget/sill ratios: 13.2% to 49.9%). The spatial distribution of copper (Cu), nickel (Ni), lead (Pb) and zinc (Zn) in soils illustrated that their high concentrations were located in the southeast part. The high concentrations of cadmium (Cd) in soils were observed in the northeast part. The accumulation of all the studied metals is related to the long-term application of agrochemicals and industrial activities. Heavy metals in rice showed different spatial distribution patterns. Cross-correlograms were produced to quantitatively determine the spatial correlation between soil properties and heavy metals composition in rice. The pH and soil organic matter had significant spatial correlations with the concentration of heavy metals in rice. Most of the selected variables had clear spatial correlation ranges for heavy metals in rice, which could be further applied to divide agricultural management zones. PMID:25635917

Contamination and Spatial Variation of Heavy Metals in the Soil-Rice System in Nanxun County, Southeastern China

Directory of Open Access Journals (Sweden)

Keli Zhao

2015-01-01

Full Text Available There is an increasing concern about heavy metal contamination in farmland in China and worldwide. In order to reveal the spatial features of heavy metals in the soil-rice system, soil and rice samples were collected from Nanxun, Southeastern China. Compared with the guideline values, elevated concentrations of heavy metals in soils were observed, while heavy metals in rice still remained at a safe level. Heavy metals in soils and rice had moderate to strong spatial dependence (nugget/sill ratios: 13.2% to 49.9%. The spatial distribution of copper (Cu, nickel (Ni, lead (Pb and zinc (Zn in soils illustrated that their high concentrations were located in the southeast part. The high concentrations of cadmium (Cd in soils were observed in the northeast part. The accumulation of all the studied metals is related to the long-term application of agrochemicals and industrial activities. Heavy metals in rice showed different spatial distribution patterns. Cross-correlograms were produced to quantitatively determine the spatial correlation between soil properties and heavy metals composition in rice. The pH and soil organic matter had significant spatial correlations with the concentration of heavy metals in rice. Most of the selected variables had clear spatial correlation ranges for heavy metals in rice, which could be further applied to divide agricultural management zones.

Contamination and spatial variation of heavy metals in the soil-rice system in Nanxun County, Southeastern China.

Science.gov (United States)

Zhao, Keli; Fu, Weijun; Ye, Zhengqian; Zhang, Chaosheng

2015-01-28

There is an increasing concern about heavy metal contamination in farmland in China and worldwide. In order to reveal the spatial features of heavy metals in the soil-rice system, soil and rice samples were collected from Nanxun, Southeastern China. Compared with the guideline values, elevated concentrations of heavy metals in soils were observed, while heavy metals in rice still remained at a safe level. Heavy metals in soils and rice had moderate to strong spatial dependence (nugget/sill ratios: 13.2% to 49.9%). The spatial distribution of copper (Cu), nickel (Ni), lead (Pb) and zinc (Zn) in soils illustrated that their high concentrations were located in the southeast part. The high concentrations of cadmium (Cd) in soils were observed in the northeast part. The accumulation of all the studied metals is related to the long-term application of agrochemicals and industrial activities. Heavy metals in rice showed different spatial distribution patterns. Cross-correlograms were produced to quantitatively determine the spatial correlation between soil properties and heavy metals composition in rice. The pH and soil organic matter had significant spatial correlations with the concentration of heavy metals in rice. Most of the selected variables had clear spatial correlation ranges for heavy metals in rice, which could be further applied to divide agricultural management zones.

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

Science.gov (United States)

Chen, Zilin; Beierle, Peter; Batelaan, Herman

2018-04-01

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

Estimating Function Approaches for Spatial Point Processes

Science.gov (United States)

Deng, Chong

Spatial point pattern data consist of locations of events that are often of interest in biological and ecological studies. Such data are commonly viewed as a realization from a stochastic process called spatial point process. To fit a parametric spatial point process model to such data, likelihood-based methods have been widely studied. However, while maximum likelihood estimation is often too computationally intensive for Cox and cluster processes, pairwise likelihood methods such as composite likelihood, Palm likelihood usually suffer from the loss of information due to the ignorance of correlation among pairs. For many types of correlated data other than spatial point processes, when likelihood-based approaches are not desirable, estimating functions have been widely used for model fitting. In this dissertation, we explore the estimating function approaches for fitting spatial point process models. These approaches, which are based on the asymptotic optimal estimating function theories, can be used to incorporate the correlation among data and yield more efficient estimators. We conducted a series of studies to demonstrate that these estmating function approaches are good alternatives to balance the trade-off between computation complexity and estimating efficiency. First, we propose a new estimating procedure that improves the efficiency of pairwise composite likelihood method in estimating clustering parameters. Our approach combines estimating functions derived from pairwise composite likeli-hood estimation and estimating functions that account for correlations among the pairwise contributions. Our method can be used to fit a variety of parametric spatial point process models and can yield more efficient estimators for the clustering parameters than pairwise composite likelihood estimation. We demonstrate its efficacy through a simulation study and an application to the longleaf pine data. Second, we further explore the quasi-likelihood approach on fitting

Propagating wave correlations in complex systems

International Nuclear Information System (INIS)

Creagh, Stephen C; Gradoni, Gabriele; Hartmann, Timo; Tanner, Gregor

2017-01-01

We describe a novel approach for computing wave correlation functions inside finite spatial domains driven by complex and statistical sources. By exploiting semiclassical approximations, we provide explicit algorithms to calculate the local mean of these correlation functions in terms of the underlying classical dynamics. By defining appropriate ensemble averages, we show that fluctuations about the mean can be characterised in terms of classical correlations. We give in particular an explicit expression relating fluctuations of diagonal contributions to those of the full wave correlation function. The methods have a wide range of applications both in quantum mechanics and for classical wave problems such as in vibro-acoustics and electromagnetism. We apply the methods here to simple quantum systems, so-called quantum maps, which model the behaviour of generic problems on Poincaré sections. Although low-dimensional, these models exhibit a chaotic classical limit and share common characteristics with wave propagation in complex structures. (paper)

Feasibility of real-time calculation of correlation integral derived statistics applied to EGG time series

NARCIS (Netherlands)

van den Broek, PLC; van Egmond, J; van Rijn, CM; Takens, F; Coenen, AML; Booij, LHDJ

2005-01-01

Background: This study assessed the feasibility of online calculation of the correlation integral (C(r)) aiming to apply C(r)derived statistics. For real-time application it is important to reduce calculation time. It is shown how our method works for EEG time series. Methods: To achieve online

Feasibility of real-time calculation of correlation integral derived statistics applied to EEG time series

NARCIS (Netherlands)

Broek, P.L.C. van den; Egmond, J. van; Rijn, C.M. van; Takens, F.; Coenen, A.M.L.; Booij, L.H.D.J.

2005-01-01

This study assessed the feasibility of online calculation of the correlation integral (C(r)) aiming to apply C(r)-derived statistics. For real-time application it is important to reduce calculation time. It is shown how our method works for EEG time series. Methods: To achieve online calculation of

OPTICAL correlation identification technology applied in underwater laser imaging target identification

Science.gov (United States)

Yao, Guang-tao; Zhang, Xiao-hui; Ge, Wei-long

2012-01-01

The underwater laser imaging detection is an effective method of detecting short distance target underwater as an important complement of sonar detection. With the development of underwater laser imaging technology and underwater vehicle technology, the underwater automatic target identification has gotten more and more attention, and is a research difficulty in the area of underwater optical imaging information processing. Today, underwater automatic target identification based on optical imaging is usually realized with the method of digital circuit software programming. The algorithm realization and control of this method is very flexible. However, the optical imaging information is 2D image even 3D image, the amount of imaging processing information is abundant, so the electronic hardware with pure digital algorithm will need long identification time and is hard to meet the demands of real-time identification. If adopt computer parallel processing, the identification speed can be improved, but it will increase complexity, size and power consumption. This paper attempts to apply optical correlation identification technology to realize underwater automatic target identification. The optics correlation identification technology utilizes the Fourier transform characteristic of Fourier lens which can accomplish Fourier transform of image information in the level of nanosecond, and optical space interconnection calculation has the features of parallel, high speed, large capacity and high resolution, combines the flexibility of calculation and control of digital circuit method to realize optoelectronic hybrid identification mode. We reduce theoretical formulation of correlation identification and analyze the principle of optical correlation identification, and write MATLAB simulation program. We adopt single frame image obtained in underwater range gating laser imaging to identify, and through identifying and locating the different positions of target, we can improve

Assessing and updating the reliability of concrete bridges subjected to spatial deterioration - principles and software implementation

DEFF Research Database (Denmark)

Schneider, Ronald; Fischer, Johannes; Bügler, Maximilian

2015-01-01

to implement the method presented here. The software prototype is applied to a typical highway bridge and the influence of inspection information on the system deterioration state and the structural reliability is quantified taking into account the spatial correlation of the corrosion process. This work...

High Incidence of Breast Cancer in Light-Polluted Areas with Spatial Effects in Korea.

Science.gov (United States)

Kim, Yun Jeong; Park, Man Sik; Lee, Eunil; Choi, Jae Wook

2016-01-01

We have reported a high prevalence of breast cancer in light-polluted areas in Korea. However, it is necessary to analyze the spatial effects of light polluted areas on breast cancer because light pollution levels are correlated with region proximity to central urbanized areas in studied cities. In this study, we applied a spatial regression method (an intrinsic conditional autoregressive [iCAR] model) to analyze the relationship between the incidence of breast cancer and artificial light at night (ALAN) levels in 25 regions including central city, urbanized, and rural areas. By Poisson regression analysis, there was a significant correlation between ALAN, alcohol consumption rates, and the incidence of breast cancer. We also found significant spatial effects between ALAN and the incidence of breast cancer, with an increase in the deviance information criterion (DIC) from 374.3 to 348.6 and an increase in R2 from 0.574 to 0.667. Therefore, spatial analysis (an iCAR model) is more appropriate for assessing ALAN effects on breast cancer. To our knowledge, this study is the first to show spatial effects of light pollution on breast cancer, despite the limitations of an ecological study. We suggest that a decrease in ALAN could reduce breast cancer more than expected because of spatial effects.

Statistical inference and visualization in scale-space for spatially dependent images

KAUST Repository

Vaughan, Amy

2012-03-01

SiZer (SIgnificant ZERo crossing of the derivatives) is a graphical scale-space visualization tool that allows for statistical inferences. In this paper we develop a spatial SiZer for finding significant features and conducting goodness-of-fit tests for spatially dependent images. The spatial SiZer utilizes a family of kernel estimates of the image and provides not only exploratory data analysis but also statistical inference with spatial correlation taken into account. It is also capable of comparing the observed image with a specific null model being tested by adjusting the statistical inference using an assumed covariance structure. Pixel locations having statistically significant differences between the image and a given null model are highlighted by arrows. The spatial SiZer is compared with the existing independent SiZer via the analysis of simulated data with and without signal on both planar and spherical domains. We apply the spatial SiZer method to the decadal temperature change over some regions of the Earth. © 2011 The Korean Statistical Society.

Generating spatial precipitation ensembles: impact of temporal correlation structure

Science.gov (United States)

Rakovec, O.; Hazenberg, P.; Torfs, P. J. J. F.; Weerts, A. H.; Uijlenhoet, R.

2012-09-01

Sound spatially distributed rainfall fields including a proper spatial and temporal error structure are of key interest for hydrologists to force hydrological models and to identify uncertainties in the simulated and forecasted catchment response. The current paper presents a temporally coherent error identification method based on time-dependent multivariate spatial conditional simulations, which are conditioned on preceding simulations. A sensitivity analysis and real-world experiment are carried out within the hilly region of the Belgian Ardennes. Precipitation fields are simulated for pixels of 10 km × 10 km resolution. Uncertainty analyses in the simulated fields focus on (1) the number of previous simulation hours on which the new simulation is conditioned, (2) the advection speed of the rainfall event, (3) the size of the catchment considered, and (4) the rain gauge density within the catchment. The results for a sensitivity analysis show for typical advection speeds >20 km h-1, no uncertainty is added in terms of across ensemble spread when conditioned on more than one or two previous hourly simulations. However, for the real-world experiment, additional uncertainty can still be added when conditioning on a larger number of previous simulations. This is because for actual precipitation fields, the dynamics exhibit a larger spatial and temporal variability. Moreover, by thinning the observation network with 50%, the added uncertainty increases only slightly and the cross-validation shows that the simulations at the unobserved locations are unbiased. Finally, the first-order autocorrelation coefficients show clear temporal coherence in the time series of the areal precipitation using the time-dependent multivariate conditional simulations, which was not the case using the time-independent univariate conditional simulations. The presented work can be easily implemented within a hydrological calibration and data assimilation framework and can be used as an

Using 3D spatial correlations to improve the noise robustness of multi component analysis of 3D multi echo quantitative T2 relaxometry data.

Science.gov (United States)

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

Outage probability analysis of wireless sensor networks in the presence of channel fading and spatial correlation

KAUST Repository

Al-Murad, Tamim M.

2011-07-01

Evaluating the reliability of wireless sensor networks is becoming more important as theses networks are being used in crucial applications. The outage probability defined as the probability that the error in the system exceeds a maximum acceptable threshold has recently been used as a measure of the reliability of such systems. In this work we find the outage probability of wireless sensor network in different scenarios of distributed sensing where sensors\\' readings are affected by spatial correlation and in the presence of channel fading. © 2011 IEEE.

Auxiliary variables for the mapping of the drainage network: spatial correlation between relieve units, lithotypes and springs in Benevente River basin-ES

Directory of Open Access Journals (Sweden)

Tony Vinicius Moreira Sampaio

2014-12-01

Full Text Available Process of the drainage network mapping present methodological limitations re- sulting in inaccurate maps, restricting their use in environmental studies. Such problems demand the realization of long field surveys to verify the error and the search for auxiliary variables to optimize this works and turn possible the analysis of map accuracy. This research aims at the measurement of the correlation be- tween springs, lithotypes and relieve units, characterized by Roughness Concentration Index (RCI in River Basin Benevente-ES, focusing on the operations of map algebra and the use of spatial statistical techniques. These procedures have identified classes of RCI and lithotypes that present the highest and the lowest correlation with the spatial distribution of springs, indicating its potential use as auxiliary variables to verify the map accuracy.

A study on the spatial characteristics and correlation of migrant workers' urban integration and well-being: A case study of Xi’an (China)

Science.gov (United States)

Wang, D. H.; Yang, X. J.; Hao, F. J.

2017-07-01

This paper used SPSS and ARCGIS to measure the urban integration degree and well-being index, spatial features, and their correlation. This results show: (1) The space differentiation of migrant workers’ urban integration degree in Xi’an distinct: The northern great site protection zone area is low, eastern military area is peak and the western electronic district and southwest high-tech zone are second peak areas. (2) Migrant workers’ well-being index has differentiation spatial distribution: eastern military area is significantly higher than other regions, northern economic zone shows low-lying shape, southern cultural and educational area is higher than northern economic development zone, and central business district is higher than the surrounding. (3) As the result of correlation analysis in SPSS 19.0, it is shown that there is certain positive correlation between urban integration degree and well-being index of migrant workers in main urban districts of Xi’an. Economic integration and social integration have positive prediction to well-being.

Spatially correlated two-dimensional arrays of semiconductor and metal quantum dots in GaAs-based heterostructures

International Nuclear Information System (INIS)

Nevedomskiy, V. N.; Bert, N. A.; Chaldyshev, V. V.; Preobrazhernskiy, V. V.; Putyato, M. A.; Semyagin, B. R.

2015-01-01

A single molecular-beam epitaxy process is used to produce GaAs-based heterostructures containing two-dimensional arrays of InAs semiconductor quantum dots and AsSb metal quantum dots. The twodimensional array of AsSb metal quantum dots is formed by low-temperature epitaxy which provides a large excess of arsenic in the epitaxial GaAs layer. During the growth of subsequent layers at a higher temperature, excess arsenic forms nanoinclusions, i.e., metal quantum dots in the GaAs matrix. The two-dimensional array of such metal quantum dots is created by the δ doping of a low-temperature GaAs layer with antimony which serves as a precursor for the heterogeneous nucleation of metal quantum dots and accumulates in them with the formation of AsSb metal alloy. The two-dimensional array of InAs semiconductor quantum dots is formed via the Stranski–Krastanov mechanism at the GaAs surface. Between the arrays of metal and semiconductor quantum dots, a 3-nm-thick AlAs barrier layer is grown. The total spacing between the arrays of metal and semiconductor quantum dots is 10 nm. Electron microscopy of the structure shows that the arrangement of metal quantum dots and semiconductor quantum dots in the two-dimensional arrays is spatially correlated. The spatial correlation is apparently caused by elastic strain and stress fields produced by both AsSb metal and InAs semiconductor quantum dots in the GaAs matrix

Geo-spatial Cognition on Human's Social Activity Space Based on Multi-scale Grids

Directory of Open Access Journals (Sweden)

ZHAI Weixin

2016-12-01

Full Text Available Widely applied location aware devices, including mobile phones and GPS receivers, have provided great convenience for collecting large volume individuals' geographical information. The researches on the human's society behavior space has attracts an increasingly number of researchers. In our research, based on location-based Flickr data From 2004 to May, 2014 in China, we choose five levels of spatial grids to form the multi-scale frame for investigate the correlation between the scale and the geo-spatial cognition on human's social activity space. The HT-index is selected as the fractal inspired by Alexander to estimate the maturity of the society activity on different scales. The results indicate that that the scale characteristics are related to the spatial cognition to a certain extent. It is favorable to use the spatial grid as a tool to control scales for geo-spatial cognition on human's social activity space.

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

Science.gov (United States)

Setiyorini, Anis; Suprijadi, Jadi; Handoko, Budhi

2017-03-01

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

An effective correlated mean-field theory applied in the spin-1/2 Ising ferromagnetic model

Energy Technology Data Exchange (ETDEWEB)

Roberto Viana, J.; Salmon, Octávio R. [Universidade Federal do Amazonas – UFAM, Manaus 69077-000, AM (Brazil); Ricardo de Sousa, J. [Universidade Federal do Amazonas – UFAM, Manaus 69077-000, AM (Brazil); National Institute of Science and Technology for Complex Systems, Universidade Federal do Amazonas, 3000, Japiim, 69077-000 Manaus, AM (Brazil); Neto, Minos A.; Padilha, Igor T. [Universidade Federal do Amazonas – UFAM, Manaus 69077-000, AM (Brazil)

2014-11-15

We developed a new treatment for mean-field theory applied in spins systems, denominated effective correlated mean-field (ECMF). We apply this theory to study the spin-1/2 Ising ferromagnetic model with nearest-neighbor interactions on a square lattice. We use clusters of finite sizes and study the criticality of the ferromagnetic system, where we obtain a convergence of critical temperature for the value k{sub B}T{sub c}/J≃2.27905±0.00141. Also the behavior of magnetic and thermodynamic properties, using the condition of minimum energy of the physical system is obtained. - Highlights: • We developed spin models to study real magnetic systems. • We study the thermodynamic and magnetic properties of the ferromagnetism. • We enhanced a mean-field theory applied in spins models.

Spatial Correlation Analysis between Particulate Matter 10 (PM10) Hazard and Respiratory Diseases in Chiang Mai Province, Thailand

Science.gov (United States)

Trang, N. Ha; Tripathi, N. K.

2014-11-01

Every year, during dry season, Chiang Mai and other northern provinces of Thailand face the problem of haze which is mainly generated by the burning of agricultural waste and forest fire, contained high percentage of particulate matter. Particulate matter 10 (PM10), being very small in size, can be inhaled easily to the deepest parts of the human lung and throat respiratory functions. Due to this, it increases the risk of respiratory diseases mainly in the case of continuous exposure to this seasonal smog. MODIS aerosol images (MOD04) have been used for four weeks in March 2007 for generating the hazard map by linking to in-situ values of PM10. Simple linear regression model between PM10 and AOD got fair correlation with R2 = 0.7 and was applied to transform PM10 pattern. The hazard maps showed the dominance of PM10 in northern part of Chiang Mai, especially in second week of March when PM10 level was three to four times higher than standard. The respiratory disease records and public health station of each village were collected from Provincial Public Health Department in Chiang Mai province. There are about 300 public health stations out of 2070 villages; hence thiessen polygon was created to determine the representative area of each public health station. Within each thiessen polygon, respiratory disease incident rate (RDIR) was calculated based on the number of patients and population. Global Moran's I was computed for RDIR to explore spatial pattern of diseases through four weeks of March. Moran's I index depicted a cluster pattern of respiratory diseases in 2nd week than other weeks. That made sense for a relationship between PM10 and respiratory diseases infections. In order to examine how PM10 affect the human respiratory system, geographically weighted regression model was used to observe local correlation coefficient between RDIR and PM10 across study area. The result captured a high correlation between respiratory diseases and high level of PM10 in

Hedonic approaches based on spatial econometrics and spatial statistics: application to evaluation of project benefits

Science.gov (United States)

Tsutsumi, Morito; Seya, Hajime

2009-12-01

This study discusses the theoretical foundation of the application of spatial hedonic approaches—the hedonic approach employing spatial econometrics or/and spatial statistics—to benefits evaluation. The study highlights the limitations of the spatial econometrics approach since it uses a spatial weight matrix that is not employed by the spatial statistics approach. Further, the study presents empirical analyses by applying the Spatial Autoregressive Error Model (SAEM), which is based on the spatial econometrics approach, and the Spatial Process Model (SPM), which is based on the spatial statistics approach. SPMs are conducted based on both isotropy and anisotropy and applied to different mesh sizes. The empirical analysis reveals that the estimated benefits are quite different, especially between isotropic and anisotropic SPM and between isotropic SPM and SAEM; the estimated benefits are similar for SAEM and anisotropic SPM. The study demonstrates that the mesh size does not affect the estimated amount of benefits. Finally, the study provides a confidence interval for the estimated benefits and raises an issue with regard to benefit evaluation.

Geometrical optics in correlated imaging systems

International Nuclear Information System (INIS)

Cao Dezhong; Xiong Jun; Wang Kaige

2005-01-01

We discuss the geometrical optics of correlated imaging for two kinds of spatial correlations corresponding, respectively, to a classical thermal light source and a quantum two-photon entangled source. Due to the different features in the second-order spatial correlation, the two sources obey different imaging equations. The quantum entangled source behaves as a mirror, whereas the classical thermal source looks like a phase-conjugate mirror in the correlated imaging

Spatial and spectral interpolation of ground-motion intensity measure observations

Science.gov (United States)

Worden, Charles; Thompson, Eric M.; Baker, Jack W.; Bradley, Brendon A.; Luco, Nicolas; Wilson, David

2018-01-01

Following a significant earthquake, ground‐motion observations are available for a limited set of locations and intensity measures (IMs). Typically, however, it is desirable to know the ground motions for additional IMs and at locations where observations are unavailable. Various interpolation methods are available, but because IMs or their logarithms are normally distributed, spatially correlated, and correlated with each other at a given location, it is possible to apply the conditional multivariate normal (MVN) distribution to the problem of estimating unobserved IMs. In this article, we review the MVN and its application to general estimation problems, and then apply the MVN to the specific problem of ground‐motion IM interpolation. In particular, we present (1) a formulation of the MVN for the simultaneous interpolation of IMs across space and IM type (most commonly, spectral response at different oscillator periods) and (2) the inclusion of uncertain observation data in the MVN formulation. These techniques, in combination with modern empirical ground‐motion models and correlation functions, provide a flexible framework for estimating a variety of IMs at arbitrary locations.

Adaptive Spatial Filter Based on Similarity Indices to Preserve the Neural Information on EEG Signals during On-Line Processing

Directory of Open Access Journals (Sweden)

Denis Delisle-Rodriguez

2017-11-01

Full Text Available This work presents a new on-line adaptive filter, which is based on a similarity analysis between standard electrode locations, in order to reduce artifacts and common interferences throughout electroencephalography (EEG signals, but preserving the useful information. Standard deviation and Concordance Correlation Coefficient (CCC between target electrodes and its correspondent neighbor electrodes are analyzed on sliding windows to select those neighbors that are highly correlated. Afterwards, a model based on CCC is applied to provide higher values of weight to those correlated electrodes with lower similarity to the target electrode. The approach was applied to brain computer-interfaces (BCIs based on Canonical Correlation Analysis (CCA to recognize 40 targets of steady-state visual evoked potential (SSVEP, providing an accuracy (ACC of 86.44 ± 2.81%. In addition, also using this approach, features of low frequency were selected in the pre-processing stage of another BCI to recognize gait planning. In this case, the recognition was significantly ( p < 0.01 improved for most of the subjects ( A C C ≥ 74.79 % , when compared with other BCIs based on Common Spatial Pattern, Filter Bank-Common Spatial Pattern, and Riemannian Geometry.

Generating spatial precipitation ensembles: impact of temporal correlation structure

Directory of Open Access Journals (Sweden)

O. Rakovec

2012-09-01

Full Text Available Sound spatially distributed rainfall fields including a proper spatial and temporal error structure are of key interest for hydrologists to force hydrological models and to identify uncertainties in the simulated and forecasted catchment response. The current paper presents a temporally coherent error identification method based on time-dependent multivariate spatial conditional simulations, which are conditioned on preceding simulations. A sensitivity analysis and real-world experiment are carried out within the hilly region of the Belgian Ardennes. Precipitation fields are simulated for pixels of 10 km × 10 km resolution. Uncertainty analyses in the simulated fields focus on (1 the number of previous simulation hours on which the new simulation is conditioned, (2 the advection speed of the rainfall event, (3 the size of the catchment considered, and (4 the rain gauge density within the catchment. The results for a sensitivity analysis show for typical advection speeds >20 km h⁻¹, no uncertainty is added in terms of across ensemble spread when conditioned on more than one or two previous hourly simulations. However, for the real-world experiment, additional uncertainty can still be added when conditioning on a larger number of previous simulations. This is because for actual precipitation fields, the dynamics exhibit a larger spatial and temporal variability. Moreover, by thinning the observation network with 50%, the added uncertainty increases only slightly and the cross-validation shows that the simulations at the unobserved locations are unbiased. Finally, the first-order autocorrelation coefficients show clear temporal coherence in the time series of the areal precipitation using the time-dependent multivariate conditional simulations, which was not the case using the time-independent univariate conditional simulations. The presented work can be easily implemented within a hydrological calibration and data assimilation

Two phase formation of massive elliptical galaxies: study through cross-correlation including spatial effect

Science.gov (United States)

Modak, Soumita; Chattopadhyay, Tanuka; Chattopadhyay, Asis Kumar

2017-11-01

Area of study is the formation mechanism of the present-day population of elliptical galaxies, in the context of hierarchical cosmological models accompanied by accretion and minor mergers. The present work investigates the formation and evolution of several components of the nearby massive early-type galaxies (ETGs) through cross-correlation function (CCF), using the spatial parameters right ascension (RA) and declination (DEC), and the intrinsic parameters mass (M_{*}) and size. According to the astrophysical terminology, here these variables, namely mass, size, RA and DEC are termed as parameters, whereas the unknown constants involved in the kernel function are called hyperparameters. Throughout this paper, the parameter size is used to represent the effective radius (Re). Following Huang et al. (2013a), each nearby ETG is divided into three parts on the basis of its Re value. We study the CCF between each of these three components of nearby massive ETGs and the ETGs in the high redshift range, 0.5conflict raised in a previous work (De et al. 2014) suggesting other possibilities for the formation of the outermost part. A probable cause of this improvement is the inclusion of the spatial effects in addition to the other parameters in the study.

MOnthly TEmperature DAtabase of Spain 1951-2010: MOTEDAS (2): The Correlation Decay Distance (CDD) and the spatial variability of maximum and minimum monthly temperature in Spain during (1981-2010).

Science.gov (United States)

Cortesi, Nicola; Peña-Angulo, Dhais; Simolo, Claudia; Stepanek, Peter; Brunetti, Michele; Gonzalez-Hidalgo, José Carlos

2014-05-01

One of the key point in the develop of the MOTEDAS dataset (see Poster 1 MOTEDAS) in the framework of the HIDROCAES Project (Impactos Hidrológicos del Calentamiento Global en España, Spanish Ministery of Research CGL2011-27574-C02-01) is the reference series for which no generalized metadata exist. In this poster we present an analysis of spatial variability of monthly minimum and maximum temperatures in the conterminous land of Spain (Iberian Peninsula, IP), by using the Correlation Decay Distance function (CDD), with the aim of evaluating, at sub-regional level, the optimal threshold distance between neighbouring stations for producing the set of reference series used in the quality control (see MOTEDAS Poster 1) and the reconstruction (see MOREDAS Poster 3). The CDD analysis for Tmax and Tmin was performed calculating a correlation matrix at monthly scale between 1981-2010 among monthly mean values of maximum (Tmax) and minimum (Tmin) temperature series (with at least 90% of data), free of anomalous data and homogenized (see MOTEDAS Poster 1), obtained from AEMEt archives (National Spanish Meteorological Agency). Monthly anomalies (difference between data and mean 1981-2010) were used to prevent the dominant effect of annual cycle in the CDD annual estimation. For each station, and time scale, the common variance r2 (using the square of Pearson's correlation coefficient) was calculated between all neighbouring temperature series and the relation between r2 and distance was modelled according to the following equation (1): Log (r2ij) = b*°dij (1) being Log(rij2) the common variance between target (i) and neighbouring series (j), dij the distance between them and b the slope of the ordinary least-squares linear regression model applied taking into account only the surrounding stations within a starting radius of 50 km and with a minimum of 5 stations required. Finally, monthly, seasonal and annual CDD values were interpolated using the Ordinary Kriging with a

On Information Metrics for Spatial Coding.

Science.gov (United States)

Souza, Bryan C; Pavão, Rodrigo; Belchior, Hindiael; Tort, Adriano B L

2018-04-01

The hippocampal formation is involved in navigation, and its neuronal activity exhibits a variety of spatial correlates (e.g., place cells, grid cells). The quantification of the information encoded by spikes has been standard procedure to identify which cells have spatial correlates. For place cells, most of the established metrics derive from Shannon's mutual information (Shannon, 1948), and convey information rate in bits/s or bits/spike (Skaggs et al., 1993, 1996). Despite their widespread use, the performance of these metrics in relation to the original mutual information metric has never been investigated. In this work, using simulated and real data, we find that the current information metrics correlate less with the accuracy of spatial decoding than the original mutual information metric. We also find that the top informative cells may differ among metrics, and show a surrogate-based normalization that yields comparable spatial information estimates. Since different information metrics may identify different neuronal populations, we discuss current and alternative definitions of spatially informative cells, which affect the metric choice. Copyright © 2018 IBRO. Published by Elsevier Ltd. All rights reserved.

Spatial analysis techniques applied to uranium prospecting in Chihuahua State, Mexico

Science.gov (United States)

Hinojosa de la Garza, Octavio R.; Montero Cabrera, María Elena; Sanín, Luz H.; Reyes Cortés, Manuel; Martínez Meyer, Enrique

2014-07-01

To estimate the distribution of uranium minerals in Chihuahua, the advanced statistical model "Maximun Entropy Method" (MaxEnt) was applied. A distinguishing feature of this method is that it can fit more complex models in case of small datasets (x and y data), as is the location of uranium ores in the State of Chihuahua. For georeferencing uranium ores, a database from the United States Geological Survey and workgroup of experts in Mexico was used. The main contribution of this paper is the proposal of maximum entropy techniques to obtain the mineral's potential distribution. For this model were used 24 environmental layers like topography, gravimetry, climate (worldclim), soil properties and others that were useful to project the uranium's distribution across the study area. For the validation of the places predicted by the model, comparisons were done with other research of the Mexican Service of Geological Survey, with direct exploration of specific areas and by talks with former exploration workers of the enterprise "Uranio de Mexico". Results. New uranium areas predicted by the model were validated, finding some relationship between the model predictions and geological faults. Conclusions. Modeling by spatial analysis provides additional information to the energy and mineral resources sectors.

Spatial Hotspot Analysis of Acute Myocardial Infarction Events in an Urban Population: A Correlation Study of Health Problems and Industrial Installation.

Science.gov (United States)

Namayande, Motahareh Sadat; Nejadkoorki, Farhad; Namayande, Seyedeh Mahdieh; Dehghan, Hamidreza

2016-01-01

The current study's objectives were to find any possible spatial patterns and hotspot of cardiovascular events and to perform a correlation study to find any possible relevance between cardiovascular disease (CVE) and location of industrial installation said above. We used the Acute Myocardial Infarction (AMI) hospital admission record in three main hospitals in Yazd, Yazd Province, Iran during 2013, because of CVDs and searched for possible correlation between industries as point-source pollutants and non-random distribution of AMI events. MI incidence rate in Yazd was obtained 531 per 100,000 person-year among men, 458 per 100,000 person-year among women and 783/100,000 person-yr totally. We applied a GIS Hotspot analysis to determine feasible clusters and two sets of clusters were observed. Mean age of 56 AMI events occurred in the cluster cells was calculated as 62.21±14.75 yr. Age and sex as main confounders of AMI were evaluated in the cluster areas in comparison to other areas. We observed no significant difference regarding sex (59% in cluster cells versus 55% in total for men) and age (62.21±14.7 in cluster cells versus 63.28±13.98 in total for men). We found proximity of AMI events cluster to industries installations, and a steel industry, specifically. There could be an association between road-related pollutants and the observed sets of cluster due to the proximity exist between rather crowded highways nearby the events cluster.

Particulate morphology mathematics applied to particle assemblies

CERN Document Server

Gotoh, Keishi

2012-01-01

Encompassing over fifty years of research, Professor Gotoh addresses the correlation function of spatial structures and the statistical geometry of random particle assemblies. In this book morphological study is formed into random particle assemblies to which various mathematics are applied such as correlation function, radial distribution function and statistical geometry. This leads to the general comparison between the thermodynamic state such as gases and liquids and the random particle assemblies. Although structures of molecular configurations change at every moment due to thermal vibration, liquids can be regarded as random packing of particles. Similarly, gaseous states correspond to particle dispersion. If physical and chemical properties are taken away from the subject, the remainder is the structure itself. Hence, the structural study is ubiquitous and of fundamental importance. This book will prove useful to chemical engineers working on powder technology as well as mathematicians interested in le...

Spatial correlations in compressible granular flows

NARCIS (Netherlands)

van Noije, T.P.C.; Ernst, M.H.; Brito, R.

The clustering instability in freely evolving granular fluids manifests itself in the density-density correlation function and structure factor. These functions are calculated from fluctuating hydrodynamics. As time increases, the structure factor of density fluctuations develops a maximum, which

A spatial epidemiological analysis of self-rated mental health in the slums of Dhaka

Directory of Open Access Journals (Sweden)

Müller Daniel

2011-05-01

Full Text Available Abstract 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 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.

Applied social geography

OpenAIRE

Hilpert, Markus

2002-01-01

Applied social geography : management of spatial planning in reflective discourse ; research perspectives towards a ‚Theory of Practice‘. - In: Geografija in njene aplikativne moˆznosti = Prospects of applied geography. - Ljubljana : Oddelek za Geografijo, Filozofska Fakulteta, 2002. S. 29-39. - (Dela / Oddelek za geografijo Filozofske fakultete v Ljubljani ; 18)

Bayesian spatial modelling and the significance of agricultural land use to scrub typhus infection in Taiwan.

Science.gov (United States)

Wardrop, Nicola A; Kuo, Chi-Chien; Wang, Hsi-Chieh; Clements, Archie C A; Lee, Pei-Fen; Atkinson, Peter M

2013-11-01

Scrub typhus is transmitted by the larval stage of trombiculid mites. Environmental factors, including land cover and land use, are known to influence breeding and survival of trombiculid mites and, thus, also the spatial heterogeneity of scrub typhus risk. Here, a spatially autoregressive modelling framework was applied to scrub typhus incidence data from Taiwan, covering the period 2003 to 2011, to provide increased understanding of the spatial pattern of scrub typhus risk and the environmental and socioeconomic factors contributing to this pattern. A clear spatial pattern in scrub typhus incidence was observed within Taiwan, and incidence was found to be significantly correlated with several land cover classes, temperature, elevation, normalized difference vegetation index, rainfall, population density, average income and the proportion of the population that work in agriculture. The final multivariate regression model included statistically significant correlations between scrub typhus incidence and average income (negatively correlated), the proportion of land that contained mosaics of cropland and vegetation (positively correlated) and elevation (positively correlated). These results highlight the importance of land cover on scrub typhus incidence: mosaics of cropland and vegetation represent a transitional land cover type which can provide favourable habitats for rodents and, therefore, trombiculid mites. In Taiwan, these transitional land cover areas tend to occur in less populated and mountainous areas, following the frontier establishment and subsequent partial abandonment of agricultural cultivation, due to demographic and socioeconomic changes. Future land use policy decision-making should ensure that potential public health outcomes, such as modified risk of scrub typhus, are considered.

Correlated ion stopping in plasmas

International Nuclear Information System (INIS)

Zwicknagel, G.; Deutsch, C.

1997-01-01

The basic features of correlated ion stopping in plasmas are demonstrated by employing two opposite extremes of cluster structures, a statistical model with a spatial ion distribution of Gaussian shape and the highly regular configuration of N-ion chains and cubic boxes. In the case of the ion chains the resonant character of correlated stopping due to the interference of the excited wake fields is discussed in detail. The general behavior of correlation effects is summarized and its dependence on the ratio of cluster size and interion spacing to the screening length in the plasma, as well as the ratio of the cluster velocity to the mean electron velocity in the target, is stressed out. The validity and applicability of the dielectric response formalism used for describing correlated stopping is critically reviewed. A scheme is presented to extend the linear formalism to weak nonlinear situations that occur, in particular, for small highly charged clusters at moderate or low velocities. For the Gaussian cluster a fit formula is given, which allows a fast and accurate calculation of the enhancement of stopping due to correlation effects and applies for all degrees of degeneracy of the electrons and arbitrary cluster velocities. copyright 1997 The American Physical Society

Directional semivariogram analysis to identify and rank controls on the spatial variability of fracture networks

Science.gov (United States)

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.

Is a matrix exponential specification suitable for the modeling of spatial correlation structures?

Science.gov (United States)

Strauß, Magdalena E; Mezzetti, Maura; Leorato, Samantha

2017-05-01

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.

Spatial correlations and probability density function of the phase difference in a developed speckle-field: numerical and natural experiments

International Nuclear Information System (INIS)

Mysina, N Yu; Maksimova, L A; Ryabukho, V P; Gorbatenko, B B

2015-01-01

Investigated are statistical properties of the phase difference of oscillations in speckle-fields at two points in the far-field diffraction region, with different shapes of the scatterer aperture. Statistical and spatial nonuniformity of the probability density function of the field phase difference is established. Numerical experiments show that, for the speckle-fields with an oscillating alternating-sign transverse correlation function, a significant nonuniformity of the probability density function of the phase difference in the correlation region of the field complex amplitude, with the most probable values 0 and p, is observed. A natural statistical interference experiment using Young diagrams has confirmed the results of numerical experiments. (laser applications and other topics in quantum electronics)

Robust Unit Commitment Considering the Temporal and Spatial Correlations of Wind Farms Using a Data-Adaptive Approach

DEFF Research Database (Denmark)

Zhang, Yipu; Ai, Xiaomeng; Wen, Jinyu

2018-01-01

. In this paper, a novel data-adaptive robust optimization method for the unit commitment is proposed for the power system with wind farms integrated. The extreme scenario extraction and the two stage robust optimization are combined in the proposed method. The data-adaptive set consisting of a few extreme...... scenarios is derived to reduce the conservativeness by considering the temporal and spatial correlations of multiple wind farms. Numerical results demonstrate that the proposed data-adaptive robust optimization algorithm is less conservative than the current two-stage optimization approaches while maintains...

Spatially varying small-strain stiffness in soils subjected to K0 loading

KAUST Repository

Kim, Hyun-Ki; Santamarina, Carlos

2017-01-01

Grain-scale characteristics and formation history determine spatial variability in granular masses. We investigate the effect of spatially varying stiffness on the load-deformation response under zero-lateral strain conditions using numerical simulations of correlated random fields, where the granular medium is represented by a non-linear stress-dependent meso-scale model. Results show that stiffness heterogeneity results in higher global compressibility as compared to the homogeneous medium with the same arithmetic mean stiffness. Furthermore, the non-homogeneous stress field that develops inside the granular mass is characterized by focused load transfer along columnar regions, higher stress anisotropy and lower horizontal-to-vertical stress ratio K0 than in a granular medium of homogenous stiffness. As the applied stress increases, the inherent stress-dependent response of the granular material leads to a more homogenous stress field. While greater variance in stiffness causes lower global stiffness, a longer correlation length results in greater variance in global mechanical response among multiple realizations.

Spatially varying small-strain stiffness in soils subjected to K0 loading

KAUST Repository

Kim, Hyun-Ki

2017-08-08

Grain-scale characteristics and formation history determine spatial variability in granular masses. We investigate the effect of spatially varying stiffness on the load-deformation response under zero-lateral strain conditions using numerical simulations of correlated random fields, where the granular medium is represented by a non-linear stress-dependent meso-scale model. Results show that stiffness heterogeneity results in higher global compressibility as compared to the homogeneous medium with the same arithmetic mean stiffness. Furthermore, the non-homogeneous stress field that develops inside the granular mass is characterized by focused load transfer along columnar regions, higher stress anisotropy and lower horizontal-to-vertical stress ratio K0 than in a granular medium of homogenous stiffness. As the applied stress increases, the inherent stress-dependent response of the granular material leads to a more homogenous stress field. While greater variance in stiffness causes lower global stiffness, a longer correlation length results in greater variance in global mechanical response among multiple realizations.

Modelling the Spatial Isotope Variability of Precipitation in Syria

Energy Technology Data Exchange (ETDEWEB)

Kattan, Z.; Kattaa, B. [Department of Geology, Atomic Energy Commission of Syria (AECS), Damascus (Syrian Arab Republic)

2013-07-15

Attempts were made to model the spatial variability of environmental isotope ({sup 18}O, {sup 2}H and {sup 3}H) compositions of precipitation in syria. Rainfall samples periodically collected on a monthly basis from 16 different stations were used for processing and demonstrating the spatial distributions of these isotopes, together with those of deuterium excess (d) values. Mathematically, the modelling process was based on applying simple polynomial models that take into consideration the effects of major geographic factors (Lon.E., Lat.N., and altitude). The modelling results of spatial distribution of stable isotopes ({sup 18}O and {sup 2}H) were generally good, as shown from the high correlation coefficients (R{sup 2} = 0.7-0.8), calculated between the observed and predicted values. In the case of deuterium excess and tritium distributions, the results were most likely approximates (R{sup 2} = 0.5-0.6). Improving the simulation of spatial isotope variability probably requires the incorporation of other local meteorological factors, such as relative air humidity, precipitation amount and vapour pressure, which are supposed to play an important role in such an arid country. (author)

Spatial correlations between browsing on balsam fir by white-tailed deer and the nutritional value of neighboring winter forage.

Science.gov (United States)

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.

Correlation Factors Describing Primary and Spatial Sensations of Sound Fields

Science.gov (United States)

ANDO, Y.

2002-11-01

The theory of subjective preference of the sound field in a concert hall is established based on the model of human auditory-brain system. The model consists of the autocorrelation function (ACF) mechanism and the interaural crosscorrelation function (IACF) mechanism for signals arriving at two ear entrances, and the specialization of human cerebral hemispheres. This theory can be developed to describe primary sensations such as pitch or missing fundamental, loudness, timbre and, in addition, duration sensation which is introduced here as a fourth. These four primary sensations may be formulated by the temporal factors extracted from the ACF associated with the left hemisphere and, spatial sensations such as localization in the horizontal plane, apparent source width and subjective diffuseness are described by the spatial factors extracted from the IACF associated with the right hemisphere. Any important subjective responses of sound fields may be described by both temporal and spatial factors.

Measurement of turbulent spatial structure and kinetic energy spectrum by exact temporal-to-spatial mapping

DEFF Research Database (Denmark)

Buchhave, Preben; Velte, Clara Marika

2017-01-01

distortions caused by Taylor’s hypothesis. The method is first confirmed to produce the correct statistics using computer simulations and later applied to measurements in some of the most difficult regions of a round turbulent jet—the non-equilibrium developing region and the outermost parts of the developed......We present a method for converting a time record of turbulent velocity measured at a point in a flow to a spatial velocity record consisting of consecutive convection elements. The spatial record allows computation of dynamic statistical moments such as turbulent kinetic wavenumber spectra...... and spatial structure functions in a way that completely bypasses the need for Taylor’s hypothesis. The spatial statistics agree with the classical counterparts, such as the total kinetic energy spectrum, at least for spatial extents up to the Taylor microscale. The requirements for applying the method...

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

Science.gov (United States)

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.

Intensity correlation imaging with sunlight-like source

Science.gov (United States)

Wang, Wentao; Tang, Zhiguo; Zheng, Huaibin; Chen, Hui; Yuan, Yuan; Liu, Jinbin; Liu, Yanyan; Xu, Zhuo

2018-05-01

We show a method of intensity correlation imaging of targets illuminated by a sunlight-like source both theoretically and experimentally. With a Faraday anomalous dispersion optical filter (FADOF), we have modulated the coherence time of a thermal source up to 0.167 ns. And we carried out measurements of temporal and spatial correlations, respectively, with an intensity interferometer setup. By skillfully using the even Fourier fitting on the very sparse sampling data, the images of targets are successfully reconstructed from the low signal-noise-ratio(SNR) interference pattern by applying an iterative phase retrieval algorithm. The resulting imaging quality is as well as the one obtained by the theoretical fitting. The realization of such a case will bring this technique closer to geostationary satellite imaging illuminated by sunlight.

Teacher spatial skills are linked to differences in geometry instruction.

Science.gov (United States)

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.

Evaluating the effect of sampling and spatial correlation on ground-water travel time uncertainty coupling geostatistical, stochastic, and first order, second moment methods

International Nuclear Information System (INIS)

Andrews, R.W.; LaVenue, A.M.; McNeish, J.A.

1989-01-01

Ground-water travel time predictions at potential high-level waste repositories are subject to a degree of uncertainty due to the scale of averaging incorporated in conceptual models of the ground-water flow regime as well as the lack of data on the spatial variability of the hydrogeologic parameters. The present study describes the effect of limited observations of a spatially correlated permeability field on the predicted ground-water travel time uncertainty. Varying permeability correlation lengths have been used to investigate the importance of this geostatistical property on the tails of the travel time distribution. This study uses both geostatistical and differential analysis techniques. Following the generation of a spatially correlated permeability field which is considered reality, semivariogram analyses are performed upon small random subsets of the generated field to determine the geostatistical properties of the field represented by the observations. Kriging is then employed to generate a kriged permeability field and the corresponding standard deviation of the estimated field conditioned by the limited observations. Using both the real and kriged fields, the ground-water flow regime is simulated and ground-water travel paths and travel times are determined for various starting points. These results are used to define the ground-water travel time uncertainty due to path variability. The variance of the ground-water travel time along particular paths due to the variance of the permeability field estimated using kriging is then calculated using the first order, second moment method. The uncertainties in predicted travel time due to path and parameter uncertainties are then combined into a single distribution

Selected results on strong and coulomb-induced correlations from the STAR experiment

International Nuclear Information System (INIS)

Sumbera, M.

2007-01-01

Using recent high-statistics STAR data from Au + Au and Cu + Cu collisions at full RHIC energy I discuss strong and Coulomb-induced final state interaction effects on identical (pi-pi) and non-identical (pi-XI) particle correlations. Analysis of pi-XI correlations reveals the strong and Coulomb-induced FSI effects, allowing for the first time to estimate spatial extension of pi and XI sources and the average shift between them. Source imaging techniques provide clean separation of details of the source function and are applied to the one-dimensional relative momentum correlation function of identical pions. For low momentum pions, and/or non-central collisions, a large departure from a single-Gaussian shape is observed. (author)

Spatial problem-solving strategies of middle school students: Wayfinding with geographic information systems

Science.gov (United States)

Wigglesworth, John C.

2000-06-01

Geographic Information Systems (GIS) is a powerful computer software package that emphasizes the use of maps and the management of spatially referenced environmental data archived in a systems data base. Professional applications of GIS have been in place since the 1980's, but only recently has GIS gained significant attention in the K--12 classroom. Students using GIS are able to manipulate and query data in order to solve all manners of spatial problems. Very few studies have examined how this technological innovation can support classroom learning. In particular, there has been little research on how experience in using the software correlates with a child's spatial cognition and his/her ability to understand spatial relationships. This study investigates the strategies used by middle school students to solve a wayfinding (route-finding) problem using the ArcView GIS software. The research design combined an individual background questionnaire, results from the Group Assessment of Logical Thinking (GALT) test, and analysis of reflective think-aloud sessions to define the characteristics of the strategies students' used to solve this particular class of spatial problem. Three uniquely different spatial problem solving strategies were identified. Visual/Concrete Wayfinders used a highly visual strategy; Logical/Abstract Wayfinders used GIS software tools to apply a more analytical and systematic approach; Transitional Wayfinders used an approach that showed evidence of one that was shifting from a visual strategy to one that was more analytical. The triangulation of data sources indicates that this progression of wayfinding strategy can be correlated both to Piagetian stages of logical thought and to experience with the use of maps. These findings suggest that GIS teachers must be aware that their students' performance will lie on a continuum that is based on cognitive development, spatial ability, and prior experience with maps. To be most effective, GIS teaching

On the performance of dual-hop systems with multiple antennas: Effects of spatial correlation, keyhole, and co-channel interference

KAUST Repository

Yang, Liang

2012-12-01

In this paper, taking into account realistic propagation conditions, namely, spatial correlation, keyhole channels, and unequal-power co-channel interference, we investigate the performance of a wireless relay network where all the nodes are equipped with multiple antennas. Considering channel state information assisted amplify-and-forward protocol, we present analytical expressions for the symbol error rate (SER) and outage probability. More specifically, we first derive the SER expressions of a relay system with orthogonal space-time block coding (OSTBC) over correlated/keyhole fading channels. We also analyze the outage probability of interference corrupted relay systems with maximal ratio combing (MRC) at the receiver as well as multiple-input multiple-output MRC (MIMO MRC). Numerical results are given to illustrate and verify the analytical results. © 2012 IEEE.

On the performance of dual-hop systems with multiple antennas: Effects of spatial correlation, keyhole, and co-channel interference

KAUST Repository

Yang, Liang; Alouini, Mohamed-Slim; Qaraqe, Khalid A.; Liu, Weiping

2012-01-01

In this paper, taking into account realistic propagation conditions, namely, spatial correlation, keyhole channels, and unequal-power co-channel interference, we investigate the performance of a wireless relay network where all the nodes are equipped with multiple antennas. Considering channel state information assisted amplify-and-forward protocol, we present analytical expressions for the symbol error rate (SER) and outage probability. More specifically, we first derive the SER expressions of a relay system with orthogonal space-time block coding (OSTBC) over correlated/keyhole fading channels. We also analyze the outage probability of interference corrupted relay systems with maximal ratio combing (MRC) at the receiver as well as multiple-input multiple-output MRC (MIMO MRC). Numerical results are given to illustrate and verify the analytical results. © 2012 IEEE.

Comparing Spatial Predictions

KAUST Repository

Hering, Amanda S.

2011-11-01

Under a general loss function, we develop a hypothesis test to determine whether a significant difference in the spatial predictions produced by two competing models exists on average across the entire spatial domain of interest. The null hypothesis is that of no difference, and a spatial loss differential is created based on the observed data, the two sets of predictions, and the loss function chosen by the researcher. The test assumes only isotropy and short-range spatial dependence of the loss differential but does allow it to be non-Gaussian, non-zero-mean, and spatially correlated. Constant and nonconstant spatial trends in the loss differential are treated in two separate cases. Monte Carlo simulations illustrate the size and power properties of this test, and an example based on daily average wind speeds in Oklahoma is used for illustration. Supplemental results are available online. © 2011 American Statistical Association and the American Society for Qualitys.

Correlates of individual, and age-related, differences in short-term learning☆

OpenAIRE

Zhang, Zhiyong; Davis, Hasker P.; Salthouse, Timothy A.; Tucker-Drob, Elliot M.

2007-01-01

Latent growth models were applied to data on multitrial verbal and spatial learning tasks from two independent studies. Although significant individual differences in both initial level of performance and subsequent learning were found in both tasks, age differences were found only in mean initial level, and not in mean learning. In neither task was fluid or crystallized intelligence associated with learning. Although there were moderate correlations among the level parameters across the verb...

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

Science.gov (United States)

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.

Socio-economic factors of bacillary dysentery based on spatial correlation analysis in Guangxi Province, China.

Directory of Open Access Journals (Sweden)

Chengjing Nie

Full Text Available BACKGROUND: In the past decade, bacillary dysentery was still a big public health problem in China, especially in Guangxi Province, where thousands of severe diarrhea cases occur every year. METHODS: Reported bacillary dysentery cases in Guangxi Province were obtained from local Centers for Diseases Prevention and Control. The 14 socio-economic indexes were selected as potential explanatory variables for the study. The spatial correlation analysis was used to explore the associations between the selected factors and bacillary dysentery incidence at county level, which was based on the software of ArcGIS10.2 and GeoDA 0.9.5i. RESULTS: The proportion of primary industry, the proportion of younger than 5-year-old children in total population, the number of hospitals per thousand persons and the rates of bacillary dysentery incidence show statistically significant positive correlation. But the proportion of secondary industry, per capital GDP, per capital government revenue, rural population proportion, popularization rate of tap water in rural area, access rate to the sanitation toilets in rural, number of beds in hospitals per thousand persons, medical and technical personnel per thousand persons and the rate of bacillary dysentery incidence show statistically significant negative correlation. The socio-economic factors can be divided into four aspects, including economic development, health development, medical development and human own condition. The four aspects were not isolated from each other, but interacted with each other.

Determination and correlation of spatial distribution of trace elements in normal and neoplastic breast tissues evaluated by μ-XRF

International Nuclear Information System (INIS)

Silva, M.P.; Oliveira, M.A.; Poletti, M.E.

2012-01-01

Full text: Some trace elements, naturally present in breast tissues, participate in a large number of biological processes, which include among others, activation or inhibition of enzymatic reactions and changes on cell membranes permeability, suggesting that these elements may influence carcinogenic processes. Thus, knowledge of the amounts of these elements and their spatial distribution in normal and neoplastic tissues may help in understanding the role of these elements in the carcinogenic process and tumor progression of breast cancers. Concentrations of trace elements like Ca, Fe, Cu and Zn, previously studied at LNLS using TXRF and conventional XRF, were elevated in neoplastic breast tissues compared to normal tissues. In this study we determined the spatial distribution of these elements in normal and neoplastic breast tissues using μ-XRF technique. We analyzed 22 samples of normal and neoplastic breast tissues (malignant and benign) obtained from paraffin blocks available for study at the Department of Pathology HC-FMRP/USP. From the blocks, a small fraction of material was removed and subjected to histological sections of 60 μm thick made with a microtome. The slices where placed in holder samples and covered with ultralen film. Tissue samples were irradiated with a white beam of synchrotron radiation. The samples were positioned at 45 degrees with respect to the incident beam on a table with 3 freedom degrees (x, y and z), allowing independent positioning of the sample in these directions. The white beam was collimated by a 20 μm microcapillary and samples were fully scanned. At each step, a spectrum was detected for 10 s. The fluorescence emitted by elements present in the sample was detected by a Si (Li) detector with 165 eV at 5.9 keV energy resolution, placed at 90 deg with respect to the incident beam. Results reveal that trace elements Ca-Zn and Fe-Cu could to be correlated in malignant breast tissues. Quantitative results, achieved by Spearman

Pore Network Modeling: Alternative Methods to Account for Trapping and Spatial Correlation

KAUST Repository

De La Garza Martinez, Pablo

2016-05-01

Pore network models have served as a predictive tool for soil and rock properties with a broad range of applications, particularly in oil recovery, geothermal energy from underground reservoirs, and pollutant transport in soils and aquifers [39]. They rely on the representation of the void space within porous materials as a network of interconnected pores with idealised geometries. Typically, a two-phase flow simulation of a drainage (or imbibition) process is employed, and by averaging the physical properties at the pore scale, macroscopic parameters such as capillary pressure and relative permeability can be estimated. One of the most demanding tasks in these models is to include the possibility of fluids to remain trapped inside the pore space. In this work I proposed a trapping rule which uses the information of neighboring pores instead of a search algorithm. This approximation reduces the simulation time significantly and does not perturb the accuracy of results. Additionally, I included spatial correlation to generate the pore sizes using a matrix decomposition method. Results show higher relative permeabilities and smaller values for irreducible saturation, which emphasizes the effects of ignoring the intrinsic correlation seen in pore sizes from actual porous media. Finally, I implemented the algorithm from Raoof et al. (2010) [38] to generate the topology of a Fontainebleau sandstone by solving an optimization problem using the steepest descent algorithm with a stochastic approximation for the gradient. A drainage simulation is performed on this representative network and relative permeability is compared with published results. The limitations of this algorithm are discussed and other methods are suggested to create a more faithful representation of the pore space.

Pore Network Modeling: Alternative Methods to Account for Trapping and Spatial Correlation

KAUST Repository

De La Garza Martinez, Pablo

2016-01-01

Pore network models have served as a predictive tool for soil and rock properties with a broad range of applications, particularly in oil recovery, geothermal energy from underground reservoirs, and pollutant transport in soils and aquifers [39]. They rely on the representation of the void space within porous materials as a network of interconnected pores with idealised geometries. Typically, a two-phase flow simulation of a drainage (or imbibition) process is employed, and by averaging the physical properties at the pore scale, macroscopic parameters such as capillary pressure and relative permeability can be estimated. One of the most demanding tasks in these models is to include the possibility of fluids to remain trapped inside the pore space. In this work I proposed a trapping rule which uses the information of neighboring pores instead of a search algorithm. This approximation reduces the simulation time significantly and does not perturb the accuracy of results. Additionally, I included spatial correlation to generate the pore sizes using a matrix decomposition method. Results show higher relative permeabilities and smaller values for irreducible saturation, which emphasizes the effects of ignoring the intrinsic correlation seen in pore sizes from actual porous media. Finally, I implemented the algorithm from Raoof et al. (2010) [38] to generate the topology of a Fontainebleau sandstone by solving an optimization problem using the steepest descent algorithm with a stochastic approximation for the gradient. A drainage simulation is performed on this representative network and relative permeability is compared with published results. The limitations of this algorithm are discussed and other methods are suggested to create a more faithful representation of the pore space.

Integrating Hands-On Undergraduate Research in an Applied Spatial Science Senior Level Capstone Course

Science.gov (United States)

Kulhavy, David L.; Unger, Daniel R.; Hung, I-Kuai; Douglass, David

2015-01-01

A senior within a spatial science Ecological Planning capstone course designed an undergraduate research project to increase his spatial science expertise and to assess the hands-on instruction methodology employed within the Bachelor of Science in Spatial Science program at Stephen F Austin State University. The height of 30 building features…

Evaluating spatial patterns in hydrological modelling

DEFF Research Database (Denmark)

Koch, Julian

the contiguous United Sates (10^6 km2). To this end, the thesis at hand applies a set of spatial performance metrics on various hydrological variables, namely land-surface-temperature (LST), evapotranspiration (ET) and soil moisture. The inspiration for the applied metrics is found in related fields...... is not fully exploited by current modelling frameworks due to the lack of suitable spatial performance metrics. Furthermore, the traditional model evaluation using discharge is found unsuitable to lay confidence on the predicted catchment inherent spatial variability of hydrological processes in a fully...

Trajectories of Brownian particles with space-correlated noise

Indian Academy of Sciences (India)

Spatial correlations of the noise are usually ruled out, and the paths traced by the random walkers are statistically independent. In this study, I consider instead noise which is white in time and has a Gaussian correlation in space, and by means of numerical simulation, I show how the spatial correlation determines the time ...

Spatial organization and correlation properties quantify structural changes on mesoscale of parenchymatous plant tissue

Energy Technology Data Exchange (ETDEWEB)

Valous, N. A.; Delgado, A.; Sun, D.-W., E-mail: dawen.sun@ucd.ie [School of Biosystems Engineering, University College Dublin, National University of Ireland, Belfield, Dublin 4, Dublin (Ireland); Drakakis, K. [Complex and Adaptive Systems Laboratory, University College Dublin, National University of Ireland, Belfield, Dublin 4, Dublin (Ireland)

2014-02-14

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.

Spatial organization and correlation properties quantify structural changes on mesoscale of parenchymatous plant tissue

International Nuclear Information System (INIS)

Valous, N. A.; Delgado, A.; Sun, D.-W.; Drakakis, K.

2014-01-01

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

Current data warehousing and OLAP technologies’ status applied to spatial databases

Directory of Open Access Journals (Sweden)

Diego Orlando Abril Fradel

2007-01-01

Full Text Available Organisations require their information on a timely, dynamic, friendly, centralised and easy-to-access basis for analysing it and taking correct decisions at the right time. Centralisation can be achieved with data warehouse technology. On-line analytical processing (OLAP is used for analysis. Technologies using graphics and maps in data presentation can be exploited for an overall view of a company and helping to take better decisions. Geo- graphic information systems (GIS are useful for spatially locating information and representing it using maps. Data warehouses are generally implemented with a multidimensional data model to make OLAP analysis easier. A fundamental point in this model is the definition of measurements and dimensions; geography lies within such dimensions. Many researchers have concluded that the geographic dimension is another attribute for describing data in current analysis systems but without having an in-depth study of its spatial feature and without locating them on a map, like GIS does. Seen this way, interoperability is necessary between GIS and OLAP (called spatial OLAP or SOLAP and several entities are currently researching this. This document summarises the current status of such research.

Environmental Correlation and Spatial Autocorrelation of Soil Properties in Keller Peninsula, Maritime Antarctica

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André Geraldo de Lima Moraes

2018-01-01

Full Text Available ABSTRACT: The pattern of variation in soil and landform properties in relation to environmental covariates are closely related to soil type distribution. The aim of this study was to apply digital soil mapping techniques to analysis of the pattern of soil property variation in relation to environmental covariates under periglacial conditions at Keller Peninsula, Maritime Antarctica. We considered the hypothesis that covariates normally used for environmental correlation elsewhere can be adequately employed in periglacial areas in Maritime Antarctica. For that purpose, 138 soil samples from 47 soil sites were collected for analysis of soil chemical and physical properties. We tested the correlation between soil properties (clay, potassium, sand, organic carbon, and pH and environmental covariates. The environmental covariates selected were correlated with soil properties according to the terrain attributes of the digital elevation model (DEM. The models evaluated were linear regression, ordinary kriging, and regression kriging. The best performance was obtained using normalized height as a covariate, with an R2 of 0.59 for sand. In contrast, the lowest R2 of 0.15 was obtained for organic carbon, also using the regression kriging method. Overall, results indicate that, despite the predominant periglacial conditions, the environmental covariates normally used for digital terrain mapping of soil properties worldwide can be successfully employed for understanding the main variations in soil properties and soil-forming factors in this region.

Pair correlation of particles in strongly nonideal systems

International Nuclear Information System (INIS)

Vaulina, O. S.

2012-01-01

A new semiempirical model is proposed for describing the spatial correlation between interacting particles in nonideal systems. The developed model describes the main features in the behavior of the pair correlation function for crystalline structures and can also be used for qualitative and quantitative description of the spatial correlation of particles in strongly nonideal liquid systems. The proposed model is compared with the results of simulation of the pair correlation function.

EFFECTS OF HETEROGENIETY ON SPATIAL PATTERN ANALYSIS OF WILD PISTACHIO TREES IN ZAGROS WOODLANDS, IRAN

Directory of Open Access Journals (Sweden)

Y. Erfanifard

2014-10-01

Full Text Available Vegetation heterogeneity biases second-order summary statistics, e.g., Ripley's K-function, applied for spatial pattern analysis in ecology. Second-order investigation based on Ripley's K-function and related statistics (i.e., L- and pair correlation function g is widely used in ecology to develop hypothesis on underlying processes by characterizing spatial patterns of vegetation. The aim of this study was to demonstrate effects of underlying heterogeneity of wild pistachio (Pistacia atlantica Desf. trees on the second-order summary statistics of point pattern analysis in a part of Zagros woodlands, Iran. The spatial distribution of 431 wild pistachio trees was accurately mapped in a 40 ha stand in the Wild Pistachio & Almond Research Site, Fars province, Iran. Three commonly used second-order summary statistics (i.e., K-, L-, and g-functions were applied to analyse their spatial pattern. The two-sample Kolmogorov-Smirnov goodness-of-fit test showed that the observed pattern significantly followed an inhomogeneous Poisson process null model in the study region. The results also showed that heterogeneous pattern of wild pistachio trees biased the homogeneous form of K-, L-, and g-functions, demonstrating a stronger aggregation of the trees at the scales of 0–50 m than actually existed and an aggregation at scales of 150–200 m, while regularly distributed. Consequently, we showed that heterogeneity of point patterns may bias the results of homogeneous second-order summary statistics and we also suggested applying inhomogeneous summary statistics with related null models for spatial pattern analysis of heterogeneous vegetations.

Effects of Heterogeniety on Spatial Pattern Analysis of Wild Pistachio Trees in Zagros Woodlands, Iran

Science.gov (United States)

Erfanifard, Y.; Rezayan, F.

2014-10-01

Vegetation heterogeneity biases second-order summary statistics, e.g., Ripley's K-function, applied for spatial pattern analysis in ecology. Second-order investigation based on Ripley's K-function and related statistics (i.e., L- and pair correlation function g) is widely used in ecology to develop hypothesis on underlying processes by characterizing spatial patterns of vegetation. The aim of this study was to demonstrate effects of underlying heterogeneity of wild pistachio (Pistacia atlantica Desf.) trees on the second-order summary statistics of point pattern analysis in a part of Zagros woodlands, Iran. The spatial distribution of 431 wild pistachio trees was accurately mapped in a 40 ha stand in the Wild Pistachio & Almond Research Site, Fars province, Iran. Three commonly used second-order summary statistics (i.e., K-, L-, and g-functions) were applied to analyse their spatial pattern. The two-sample Kolmogorov-Smirnov goodness-of-fit test showed that the observed pattern significantly followed an inhomogeneous Poisson process null model in the study region. The results also showed that heterogeneous pattern of wild pistachio trees biased the homogeneous form of K-, L-, and g-functions, demonstrating a stronger aggregation of the trees at the scales of 0-50 m than actually existed and an aggregation at scales of 150-200 m, while regularly distributed. Consequently, we showed that heterogeneity of point patterns may bias the results of homogeneous second-order summary statistics and we also suggested applying inhomogeneous summary statistics with related null models for spatial pattern analysis of heterogeneous vegetations.

Calculation of the spatial resolution in two-photon absorption spectroscopy applied to plasma diagnosis

Energy Technology Data Exchange (ETDEWEB)

Garcia-Lechuga, M. [Departamento de Física Teórica, Atómica y Óptica, Universidad de Valladolid, 47011-Valladolid (Spain); Laser Processing Group, Instituto de Óptica “Daza de Valdés,” CSIC, 28006-Madrid (Spain); Fuentes, L. M. [Departamento de Física Aplicada, Universidad de Valladolid, 47011-Valladolid (Spain); Grützmacher, K.; Pérez, C., E-mail: concha@opt.uva.es; Rosa, M. I. de la [Departamento de Física Teórica, Atómica y Óptica, Universidad de Valladolid, 47011-Valladolid (Spain)

2014-10-07

We report a detailed characterization of the spatial resolution provided by two-photon absorption spectroscopy suited for plasma diagnosis via the 1S-2S transition of atomic hydrogen for optogalvanic detection and laser induced fluorescence (LIF). A precise knowledge of the spatial resolution is crucial for a correct interpretation of measurements, if the plasma parameters to be analysed undergo strong spatial variations. The present study is based on a novel approach which provides a reliable and realistic determination of the spatial resolution. Measured irradiance distribution of laser beam waists in the overlap volume, provided by a high resolution UV camera, are employed to resolve coupled rate equations accounting for two-photon excitation, fluorescence decay and ionization. The resulting three-dimensional yield distributions reveal in detail the spatial resolution for optogalvanic and LIF detection and related saturation due to depletion. Two-photon absorption profiles broader than the Fourier transform-limited laser bandwidth are also incorporated in the calculations. The approach allows an accurate analysis of the spatial resolution present in recent and future measurements.

Calculation of the spatial resolution in two-photon absorption spectroscopy applied to plasma diagnosis

International Nuclear Information System (INIS)

Garcia-Lechuga, M.; Fuentes, L. M.; Grützmacher, K.; Pérez, C.; Rosa, M. I. de la

2014-01-01

We report a detailed characterization of the spatial resolution provided by two-photon absorption spectroscopy suited for plasma diagnosis via the 1S-2S transition of atomic hydrogen for optogalvanic detection and laser induced fluorescence (LIF). A precise knowledge of the spatial resolution is crucial for a correct interpretation of measurements, if the plasma parameters to be analysed undergo strong spatial variations. The present study is based on a novel approach which provides a reliable and realistic determination of the spatial resolution. Measured irradiance distribution of laser beam waists in the overlap volume, provided by a high resolution UV camera, are employed to resolve coupled rate equations accounting for two-photon excitation, fluorescence decay and ionization. The resulting three-dimensional yield distributions reveal in detail the spatial resolution for optogalvanic and LIF detection and related saturation due to depletion. Two-photon absorption profiles broader than the Fourier transform-limited laser bandwidth are also incorporated in the calculations. The approach allows an accurate analysis of the spatial resolution present in recent and future measurements.

Neural correlates of virtual route recognition in congenital blindness

DEFF Research Database (Denmark)

Kupers, Ron; Chebat, Daniel R; Madsen, Kristoffer H

2010-01-01

Despite the importance of vision for spatial navigation, blind subjects retain the ability to represent spatial information and to move independently in space to localize and reach targets. However, the neural correlates of navigation in subjects lacking vision remain elusive. We therefore used...... functional MRI (fMRI) to explore the cortical network underlying successful navigation in blind subjects. We first trained congenitally blind and blindfolded sighted control subjects to perform a virtual navigation task with the tongue display unit (TDU), a tactile-to-vision sensory substitution device...... that translates a visual image into electrotactile stimulation applied to the tongue. After training, participants repeated the navigation task during fMRI. Although both groups successfully learned to use the TDU in the virtual navigation task, the brain activation patterns showed substantial differences. Blind...

Self-avoiding walk on a square lattice with correlated vacancies

Science.gov (United States)

Cheraghalizadeh, J.; Najafi, M. N.; Mohammadzadeh, H.; Saber, A.

2018-04-01

The self-avoiding walk on the square site-diluted correlated percolation lattice is considered. The Ising model is employed to realize the spatial correlations of the metric space. As a well-accepted result, the (generalized) Flory's mean-field relation is tested to measure the effect of correlation. After exploring a perturbative Fokker-Planck-like equation, we apply an enriched Rosenbluth Monte Carlo method to study the problem. To be more precise, the winding angle analysis is also performed from which the diffusivity parameter of Schramm-Loewner evolution theory (κ ) is extracted. We find that at the critical Ising (host) system, the exponents are in agreement with Flory's approximation. For the off-critical Ising system, we find also a behavior for the fractal dimension of the walker trace in terms of the correlation length of the Ising system ξ (T ) , i.e., DFSAW(T ) -DFSAW(Tc) ˜1/√{ξ (T ) } .

Fractional Progress Toward Understanding the Fractional Diffusion Limit: The Electromagnetic Response of Spatially Correlated Geomaterials

Science.gov (United States)

Weiss, C. J.; Beskardes, G. D.; Everett, M. E.

2016-12-01

In this presentation we review the observational evidence for anomalous electromagnetic diffusion in near-surface geophysical exploration and how such evidence is consistent with a detailed, spatially-correlated geologic medium. To date, the inference of multi-scale geologic correlation is drawn from two independent methods of data analysis. The first of which is analogous to seismic move-out, where the arrival time of an electromagnetic pulse is plotted as a function of transmitter/receiver separation. The "anomalous" diffusion is evident by the fractional-order power law behavior of these arrival times, with an exponent value between unity (pure diffusion) and 2 (lossless wave propagation). The second line of evidence comes from spectral analysis of small-scale fluctuations in electromagnetic profile data which cannot be explained in terms of instrument, user or random error. Rather, the power-law behavior of the spectral content of these signals (i.e., power versus wavenumber) and their increments reveals them to lie in a class of signals with correlations over multiple length scales, a class of signals known formally as fractional Brownian motion. Numerical results over simulated geology with correlated electrical texture - representative of, for example, fractures, sedimentary bedding or metamorphic lineation - are consistent with the (albeit limited, but growing) observational data, suggesting a possible mechanism and modeling approach for a more realistic geology. Furthermore, we show how similar simulated results can arise from a modeling approach where geologic texture is economically captured by a modified diffusion equation containing exotic, but manageable, fractional derivatives. These derivatives arise physically from the generalized convolutional form for the electromagnetic constitutive laws and thus have merit beyond mere mathematical convenience. In short, we are zeroing in on the anomalous, fractional diffusion limit from two converging

Correlated Raman micro-spectroscopy and scanning electron microscopy analyses of flame retardants in environmental samples: a micro-analytical tool for probing chemical composition, origin and spatial distribution.

Science.gov (United States)

Ghosal, Sutapa; Wagner, Jeff

2013-07-07

We present correlated application of two micro-analytical techniques: scanning electron microscopy/energy dispersive X-ray spectroscopy (SEM/EDS) and Raman micro-spectroscopy (RMS) for the non-invasive characterization and molecular identification of flame retardants (FRs) in environmental dusts and consumer products. The SEM/EDS-RMS technique offers correlated, morphological, molecular, spatial distribution and semi-quantitative elemental concentration information at the individual particle level with micrometer spatial resolution and minimal sample preparation. The presented methodology uses SEM/EDS analyses for rapid detection of particles containing FR specific elements as potential indicators of FR presence in a sample followed by correlated RMS analyses of the same particles for characterization of the FR sub-regions and surrounding matrices. The spatially resolved characterization enabled by this approach provides insights into the distributional heterogeneity as well as potential transfer and exposure mechanisms for FRs in the environment that is typically not available through traditional FR analysis. We have used this methodology to reveal a heterogeneous distribution of highly concentrated deca-BDE particles in environmental dust, sometimes in association with identifiable consumer materials. The observed coexistence of deca-BDE with consumer material in dust is strongly indicative of its release into the environment via weathering/abrasion of consumer products. Ingestion of such enriched FR particles in dust represents a potential for instantaneous exposure to high FR concentrations. Therefore, correlated SEM/RMS analysis offers a novel investigative tool for addressing an area of important environmental concern.

Visualization and Analysis of Wireless Sensor Network Data for Smart Civil Structure Applications Based On Spatial Correlation Technique

Science.gov (United States)

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

Panel data models extended to spatial error autocorrelation or a spatially lagged dependent variable

NARCIS (Netherlands)

Elhorst, J. Paul

2001-01-01

This paper surveys panel data models extended to spatial error autocorrelation or a spatially lagged dependent variable. In particular, it focuses on the specification and estimation of four panel data models commonly used in applied research: the fixed effects model, the random effects model, the

Analysis and Assessment of the Spatial and Temporal Distribution of Burned Areas in the Amazon Forest

Directory of Open Access Journals (Sweden)

Francielle da Silva Cardozo

2014-08-01

Full Text Available The objective of this study was to analyze the spatial and temporal distribution of burned areas in Rondônia State, Brazil during the years 2000 to 2011 and evaluate the burned area maps. A Linear Spectral Mixture Model (LSMM was applied to MODIS surface reflectance images to originate the burned areas maps, which were validated with TM/Landsat 5 and ETM+/Landsat 7 images and field data acquired in August 2013. The validation presented a correlation ranging from 67% to 96% with an average value of 86%. The lower correlation values are related to the distinct spatial resolutions of the MODIS and TM/ETM+ sensors because small burn scars are not detected in MODIS images and higher spatial correlations are related to the presence of large fires, which are better identified in MODIS, increasing the accuracy of the mapping methodology. In addition, the 12-year burned area maps of Rondônia indicate that fires, as a general pattern, occur in areas that have already been converted to some land use, such as vegetal extraction, large animal livestock areas or diversified permanent crops. Furthermore, during the analyzed period, land use conversion associated with climatic events significantly influenced the occurrence of fire in Rondônia and amplified its impacts.

Behavioral correlates of the distributed coding of spatial context.

Science.gov (United States)

Anderson, Michael I; Killing, Sarah; Morris, Caitlin; O'Donoghue, Alan; Onyiagha, Dikennam; Stevenson, Rosemary; Verriotis, Madeleine; Jeffery, Kathryn J

2006-01-01

Hippocampal place cells respond heterogeneously to elemental changes of a compound spatial context, suggesting that they form a distributed code of context, whereby context information is shared across a population of neurons. The question arises as to what this distributed code might be useful for. The present study explored two possibilities: one, that it allows contexts with common elements to be disambiguated, and the other, that it allows a given context to be associated with more than one outcome. We used two naturalistic measures of context processing in rats, rearing and thigmotaxis (boundary-hugging), to explore how rats responded to contextual novelty and to relate this to the behavior of place cells. In experiment 1, rats showed dishabituation of rearing to a novel reconfiguration of familiar context elements, suggesting that they perceived the reconfiguration as novel, a behavior that parallels that of place cells in a similar situation. In experiment 2, rats were trained in a place preference task on an open-field arena. A change in the arena context triggered renewed thigmotaxis, and yet navigation continued unimpaired, indicating simultaneous representation of both the altered contextual and constant spatial cues. Place cells similarly exhibited a dual population of responses, consistent with the hypothesis that their activity underlies spatial behavior. Together, these experiments suggest that heterogeneous context encoding (or "partial remapping") by place cells may function to allow the flexible assignment of associations to contexts, a faculty that could be useful in episodic memory encoding. Copyright (c) 2006 Wiley-Liss, Inc.

Soil erosion evolution and spatial correlation analysis in a typical karst geomorphology using RUSLE with GIS

Science.gov (United States)

Zeng, Cheng; Wang, Shijie; Bai, Xiaoyong; Li, Yangbing; Tian, Yichao; Li, Yue; Wu, Luhua; Luo, Guangjie

2017-07-01

Although some scholars have studied soil erosion in karst landforms, analyses of the spatial and temporal evolution of soil erosion and correlation analyses with spatial elements have been insufficient. The lack of research has led to an inaccurate assessment of environmental effects, especially in the mountainous area of Wuling in China. Soil erosion and rocky desertification in this area influence the survival and sustainability of a population of 0.22 billion people. This paper analyzes the spatiotemporal evolution of soil erosion and explores its relationship with rocky desertification using GIS technology and the revised universal soil loss equation (RUSLE). Furthermore, this paper analyzes the relationship between soil erosion and major natural elements in southern China. The results are as follows: (1) from 2000 to 2013, the proportion of the area experiencing micro-erosion and mild erosion was at increasing risk in contrast to areas where moderate and high erosion are decreasing. The area changes in this time sequence reflect moderate to high levels of erosion tending to convert into micro-erosion and mild erosion. (2) The soil erosion area on the slope, at 15-35°, accounted for 60.59 % of the total erosion area, and the corresponding soil erosion accounted for 40.44 %. (3) The annual erosion rate in the karst region decreased much faster than in the non-karst region. Soil erosion in all of the rock outcrop areas indicates an improving trend, and dynamic changes in soil erosion significantly differ among the various lithological distribution belts. (4) The soil erosion rate decreased in the rocky desertification regions, to below moderate levels, but increased in the severe rocky desertification areas. The temporal and spatial variations in soil erosion gradually decreased in the study area. Differences in the spatial distribution between lithology and rocky desertification induced extensive soil loss. As rocky desertification became worse, the erosion

Soil erosion evolution and spatial correlation analysis in a typical karst geomorphology using RUSLE with GIS

Directory of Open Access Journals (Sweden)

C. Zeng

2017-07-01

Full Text Available Although some scholars have studied soil erosion in karst landforms, analyses of the spatial and temporal evolution of soil erosion and correlation analyses with spatial elements have been insufficient. The lack of research has led to an inaccurate assessment of environmental effects, especially in the mountainous area of Wuling in China. Soil erosion and rocky desertification in this area influence the survival and sustainability of a population of 0.22 billion people. This paper analyzes the spatiotemporal evolution of soil erosion and explores its relationship with rocky desertification using GIS technology and the revised universal soil loss equation (RUSLE. Furthermore, this paper analyzes the relationship between soil erosion and major natural elements in southern China. The results are as follows: (1 from 2000 to 2013, the proportion of the area experiencing micro-erosion and mild erosion was at increasing risk in contrast to areas where moderate and high erosion are decreasing. The area changes in this time sequence reflect moderate to high levels of erosion tending to convert into micro-erosion and mild erosion. (2 The soil erosion area on the slope, at 15–35°, accounted for 60.59 % of the total erosion area, and the corresponding soil erosion accounted for 40.44 %. (3 The annual erosion rate in the karst region decreased much faster than in the non-karst region. Soil erosion in all of the rock outcrop areas indicates an improving trend, and dynamic changes in soil erosion significantly differ among the various lithological distribution belts. (4 The soil erosion rate decreased in the rocky desertification regions, to below moderate levels, but increased in the severe rocky desertification areas. The temporal and spatial variations in soil erosion gradually decreased in the study area. Differences in the spatial distribution between lithology and rocky desertification induced extensive soil loss. As rocky desertification

The spatial analysis on hemorrhagic fever with renal syndrome in Jiangsu province, China based on geographic information system.

Directory of Open Access Journals (Sweden)

Changjun Bao

Full Text Available Hemorrhagic fever with renal syndrome (HFRS is endemic in mainland China, accounting for 90% of total reported cases worldwide, and Jiangsu is one of the most severely affected provinces. In this study, the authors conducted GIS-based spatial analyses in order to determine the spatial distribution of the HFRS cases, identify key areas and explore risk factors for public health planning and resource allocation.Interpolation maps by inverse distance weighting were produced to detect the spatial distribution of HFRS cases in Jiangsu from 2001 to 2011. Spatio-temporal clustering was applied to identify clusters at the county level. Spatial correlation analysis was conducted to detect influencing factors of HFRS in Jiangsu.HFRS cases in Jiangsu from 2001 to 2011 were mapped and the results suggested that cases in Jiangsu were not distributed randomly. Cases were mainly distributed in northeastern and southwestern Jiangsu, especially in Dafeng and Sihong counties. It was notable that prior to this study, Sihong county had rarely been reported as a high-risk area of HFRS. With the maximum spatial size of 50% of the total population and the maximum temporal size of 50% of the total population, spatio-temporal clustering showed that there was one most likely cluster (LLR = 624.52, P<0.0001, RR = 8.19 and one second-most likely cluster (LLR = 553.97, P<0.0001, RR = 8.25, and both of these clusters appeared from 2001 to 2004. Spatial correlation analysis showed that the incidence of HFRS in Jiangsu was influenced by distances to highways, railways, rivers and lakes.The application of GIS together with spatial interpolation, spatio-temporal clustering and spatial correlation analysis can effectively identify high-risk areas and factors influencing HFRS incidence to lay a foundation for researching its pathogenesis.

Application of Spatial Regression Models to Income Poverty Ratios in Middle Delta Contiguous Counties in Egypt

Directory of Open Access Journals (Sweden)

Sohair F Higazi

2013-02-01

Full Text Available Regression analysis depends on several assumptions that have to be satisfied. A major assumption that is never satisfied when variables are from contiguous observations is the independence of error terms. Spatial analysis treated the violation of that assumption by two derived models that put contiguity of observations into consideration. Data used are from Egypt's 2006 latest census, for 93 counties in middle delta seven adjacent Governorates. The dependent variable used is the percent of individuals classified as poor (those who make less than 1$ daily. Predictors are some demographic indicators. Explanatory Spatial Data Analysis (ESDA is performed to examine the existence of spatial clustering and spatial autocorrelation between neighboring counties. The ESDA revealed spatial clusters and spatial correlation between locations. Three statistical models are applied to the data, the Ordinary Least Square regression model (OLS, the Spatial Error Model (SEM and the Spatial Lag Model (SLM.The Likelihood Ratio test and some information criterions are used to compare SLM and SEM to OLS. The SEM model proved to be better than the SLM model. Recommendations are drawn regarding the two spatial models used.

Spatial attraction in migrants' settlement patterns in the city of Catania

Directory of Open Access Journals (Sweden)

Angelo Mazza

2016-07-01

Full Text Available Background: In broad terms, and apart from ethnic discriminatory rules enforced in some places and at some times, residential segregation may be ascribed both to economic inhomogeneities in the urban space (e.g., in the cost of rents, or in occupation opportunities and to spatial attraction among individuals sharing the same group identity and culture. Objective: Traditional indices of spatial segregation do not distinguish between these two sources of clustering. Furthermore, they typically rely on census tracts, a scale that does not allow for fine-grained analysis. Also, the use of alternative zoning often leads to conflicting results. The aim of this paper is to measure spatial attraction among groups of foreign migrants in Catania (Italy using individual household data. Methods: We apply a version of Ripley's K-function specially conceived for assessing spatial attraction while adjusting for the effects of spatial inhomogeneity. To avoid the risk of confounding the two sources of clustering, spatial inhomogeneity is estimated following a case-control approach. Results: Different parts of the city exhibit different suitabilities for migrants of different nationalities, with groups mainly involved in housekeeping and caregiving being more spread than the ones specialized in peddling and retailing. A significant spatial attraction has been found for Sri Lankan, Mauritians, Senegalese, and Chinese. Conversely, the settlement patterns of Tunisians and Moroccans comply with random allocation. These results seem consistent with the hypothesis of a relevant correlation between chain migration and spatial attraction.

Photon correlation holography.

Science.gov (United States)

Naik, Dinesh N; Singh, Rakesh Kumar; Ezawa, Takahiro; Miyamoto, Yoko; Takeda, Mitsuo

2011-01-17

Unconventional holography called photon correlation holography is proposed and experimentally demonstrated. Using photon correlation, i.e. intensity correlation or fourth order correlation of optical field, a 3-D image of the object recorded in a hologram is reconstructed stochastically with illumination through a random phase screen. Two different schemes for realizing photon correlation holography are examined by numerical simulations, and the experiment was performed for one of the reconstruction schemes suitable for the experimental proof of the principle. The technique of photon correlation holography provides a new insight into how the information is embedded in the spatial as well as temporal correlation of photons in the stochastic pseudo thermal light.

Spatial strategies for managing visitor impacts in National Parks

Science.gov (United States)

Leung, Y.-F.; Marion, J.L.

1999-01-01

Resource and social impacts caused by recreationists and tourists have become a management concern in national parks and equivalent protected areas. The need to contain visitor impacts within acceptable limits has prompted park and protected area managers to implement a wide variety of strategies and actions, many of which are spatial in nature. This paper classifies and illustrates the basic spatial strategies for managing visitor impacts in parks and protected areas. A typology of four spatial strategies was proposed based on the recreation and park management literature. Spatial segregation is a common strategy for shielding sensitive resources from visitor impacts or for separating potentially conflicting types of use. Two forms of spatial segregation are zoning and closure. A spatial containment strategy is intended to minimize the aggregate extent of visitor impacts by confining use to limited designated or established Iocations. In contrast, a spatial dispersal strategy seeks to spread visitor use, reducing the frequency of use to levels that avoid or minimize permanent resource impacts or visitor crowding and conflict. Finally, a spatial configuration strategy minimizes impacting visitor behavior though the judicious spatial arrangement of facilities. These four spatial strategics can be implemented separately or in combination at varying spatial scales within a single park. A survey of national park managers provides an empirical example of the diversity of implemented spatial strategies in managing visitor impacts. Spatial segregation is frequently applied in the form of camping restrictions or closures to protect sensitive natural or cultural resources and to separate incompatible visitor activities. Spatial containment is the most widely applied strategy for minimizing the areal extent of resource impacts. Spatial dispersal is commonly applied to reduce visitor crowding or conflicts in popular destination areas but is less frequently applied or

Applying Spatial-Temporal Model and Game Theory to Asymmetric Threat Prediction

National Research Council Canada - National Science Library

Wei, Mo; Chen, Genshe; Cruz, Jr., Jose B; Haynes, Leonard; Kruger, Martin

2007-01-01

.... In most Command and Control "C2" applications, the existing techniques, such as spatial-temporal point models for ECOA prediction or Discrete Choice Model "DCM", assume that insurgent attack features...

Compress compound images in H.264/MPGE-4 AVC by exploiting spatial correlation.

Science.gov (United States)

Lan, Cuiling; Shi, Guangming; Wu, Feng

2010-04-01

Compound images are a combination of text, graphics and natural image. They present strong anisotropic features, especially on the text and graphics parts. These anisotropic features often render conventional compression inefficient. Thus, this paper proposes a novel coding scheme from the H.264 intraframe coding. In the scheme, two new intramodes are developed to better exploit spatial correlation in compound images. The first is the residual scalar quantization (RSQ) mode, where intrapredicted residues are directly quantized and coded without transform. The second is the base colors and index map (BCIM) mode that can be viewed as an adaptive color quantization. In this mode, an image block is represented by several representative colors, referred to as base colors, and an index map to compress. Every block selects its coding mode from two new modes and the previous intramodes in H.264 by rate-distortion optimization (RDO). Experimental results show that the proposed scheme improves the coding efficiency even more than 10 dB at most bit rates for compound images and keeps a comparable efficient performance to H.264 for natural images.

Neural correlates of reward-based spatial learning in persons with cocaine dependence.

Science.gov (United States)

Tau, Gregory Z; Marsh, Rachel; Wang, Zhishun; Torres-Sanchez, Tania; Graniello, Barbara; Hao, Xuejun; Xu, Dongrong; Packard, Mark G; Duan, Yunsuo; Kangarlu, Alayar; Martinez, Diana; Peterson, Bradley S

2014-02-01

Dysfunctional learning systems are thought to be central to the pathogenesis of and impair recovery from addictions. The functioning of the brain circuits for episodic memory or learning that support goal-directed behavior has not been studied previously in persons with cocaine dependence (CD). Thirteen abstinent CD and 13 healthy participants underwent MRI scanning while performing a task that requires the use of spatial cues to navigate a virtual-reality environment and find monetary rewards, allowing the functional assessment of the brain systems for spatial learning, a form of episodic memory. Whereas both groups performed similarly on the reward-based spatial learning task, we identified disturbances in brain regions involved in learning and reward in CD participants. In particular, CD was associated with impaired functioning of medial temporal lobe (MTL), a brain region that is crucial for spatial learning (and episodic memory) with concomitant recruitment of striatum (which normally participates in stimulus-response, or habit, learning), and prefrontal cortex. CD was also associated with enhanced sensitivity of the ventral striatum to unexpected rewards but not to expected rewards earned during spatial learning. We provide evidence that spatial learning in CD is characterized by disturbances in functioning of an MTL-based system for episodic memory and a striatum-based system for stimulus-response learning and reward. We have found additional abnormalities in distributed cortical regions. Consistent with findings from animal studies, we provide the first evidence in humans describing the disruptive effects of cocaine on the coordinated functioning of multiple neural systems for learning and memory.

Road Short-Term Travel Time Prediction Method Based on Flow Spatial Distribution and the Relations

Directory of Open Access Journals (Sweden)

Mingjun Deng

2016-01-01

Full Text Available There are many short-term road travel time forecasting studies based on time series, but indeed, road travel time not only relies on the historical travel time series, but also depends on the road and its adjacent sections history flow. However, few studies have considered that. This paper is based on the correlation of flow spatial distribution and the road travel time series, applying nearest neighbor and nonparametric regression method to build a forecasting model. In aspect of spatial nearest neighbor search, three different space distances are defined. In addition, two forecasting functions are introduced: one combines the forecasting value by mean weight and the other uses the reciprocal of nearest neighbors distance as combined weight. Three different distances are applied in nearest neighbor search, which apply to the two forecasting functions. For travel time series, the nearest neighbor and nonparametric regression are applied too. Then minimizing forecast error variance is utilized as an objective to establish the combination model. The empirical results show that the combination model can improve the forecast performance obviously. Besides, the experimental results of the evaluation for the computational complexity show that the proposed method can satisfy the real-time requirement.

The spatial distribution of LGR5+ cells correlates with gastric cancer progression.

Directory of Open Access Journals (Sweden)

Eva Simon

Full Text Available In this study we tested the prevalence, histoanatomical distribution and tumour biological significance of the Wnt target protein and cancer stem cell marker LGR5 in tumours of the human gastrointestinal tract. Differential expression of LGR5 was studied on transcriptional (real-time polymerase chain reaction and translational level (immunohistochemistry in malignant and corresponding non-malignant tissues of 127 patients comprising six different primary tumour sites, i.e. oesophagus, stomach, liver, pancreas, colon and rectum. The clinico-pathological significance of LGR5 expression was studied in 100 patients with gastric carcinoma (GC. Non-neoplastic tissue usually harboured only very few scattered LGR5(+ cells. The corresponding carcinomas of the oesophagus, stomach, liver, pancreas, colon and rectum showed significantly more LGR5(+ cells as well as significantly higher levels of LGR5-mRNA compared with the corresponding non-neoplastic tissue. Double staining experiments revealed a coexpression of LGR5 with the putative stem cell markers CD44, Musashi-1 and ADAM17. Next we tested the hypothesis that the sequential changes of gastric carcinogenesis, i.e. chronic atrophic gastritis, intestinal metaplasia and invasive carcinoma, are associated with a reallocation of the LGR5(+ cells. Interestingly, the spatial distribution of LGR5 changed: in non-neoplastic stomach mucosa, LGR5(+ cells were found predominantly in the mucous neck region; in intestinal metaplasia LGR5(+ cells were localized at the crypt base, and in GC LGR5(+ cells were present at the luminal surface, the tumour centre and the invasion front. The expression of LGR5 in the tumour centre and invasion front of GC correlated significantly with the local tumour growth (T-category and the nodal spread (N-category. Furthermore, patients with LGR5(+ GCs had a shorter median survival (28.0±8.6 months than patients with LGR5(- GCs (54.5±6.3 months. Our results show that LGR5 is

Predictive geochemical mapping using environmental correlation

International Nuclear Information System (INIS)

Wilford, John; Caritat, Patrice de; Bui, Elisabeth

2016-01-01

The distribution of chemical elements at and near the Earth's surface, the so-called critical zone, is complex and reflects the geochemistry and mineralogy of the original substrate modified by environmental factors that include physical, chemical and biological processes over time. Geochemical data typically is illustrated in the form of plan view maps or vertical cross-sections, where the composition of regolith, soil, bedrock or any other material is represented. These are primarily point observations that frequently are interpolated to produce rasters of element distributions. Here we propose the application of environmental or covariate regression modelling to predict and better understand the controls on major and trace element geochemistry within the regolith. Available environmental covariate datasets (raster or vector) representing factors influencing regolith or soil composition are intersected with the geochemical point data in a spatial statistical correlation model to develop a system of multiple linear correlations. The spatial resolution of the environmental covariates, which typically is much finer (e.g. ∼90 m pixel) than that of geochemical surveys (e.g. 1 sample per 10-10,000 km 2 ), carries over to the predictions. Therefore the derived predictive models of element concentrations take the form of continuous geochemical landscape representations that are potentially much more informative than geostatistical interpolations. Environmental correlation is applied to the Sir Samuel 1:250,000 scale map sheet in Western Australia to produce distribution models of individual elements describing the geochemical composition of the regolith and exposed bedrock. As an example we model the distribution of two elements – chromium and sodium. We show that the environmental correlation approach generates high resolution predictive maps that are statistically more accurate and effective than ordinary kriging and inverse distance weighting interpolation

Poverty, health and satellite-derived vegetation indices: their inter-spatial relationship in West Africa

Science.gov (United States)

Sedda, Luigi; Tatem, Andrew J.; Morley, David W.; Atkinson, Peter M.; Wardrop, Nicola A.; Pezzulo, Carla; Sorichetta, Alessandro; Kuleszo, Joanna; Rogers, David J.

2015-01-01

Background Previous analyses have shown the individual correlations between poverty, health and satellite-derived vegetation indices such as the normalized difference vegetation index (NDVI). However, generally these analyses did not explore the statistical interconnections between poverty, health outcomes and NDVI. Methods In this research aspatial methods (principal component analysis) and spatial models (variography, factorial kriging and cokriging) were applied to investigate the correlations and spatial relationships between intensity of poverty, health (expressed as child mortality and undernutrition), and NDVI for a large area of West Africa. Results This research showed that the intensity of poverty (and hence child mortality and nutrition) varies inversely with NDVI. From the spatial point-of-view, similarities in the spatial variation of intensity of poverty and NDVI were found. Conclusions These results highlight the utility of satellite-based metrics for poverty models including health and ecological components and, in general for large scale analysis, estimation and optimisation of multidimensional poverty metrics. However, it also stresses the need for further studies on the causes of the association between NDVI, health and poverty. Once these relationships are confirmed and better understood, the presence of this ecological component in poverty metrics has the potential to facilitate the analysis of the impacts of climate change on the rural populations afflicted by poverty and child mortality. PMID:25733559

The spatial and temporal behavior of brightness temperature in Tel-Aviv and its application to air temperature monitoring

Science.gov (United States)

Pelta, Ran; Chudnovsky, A. Alexandra; Schwarts, Joel

2016-01-01

This study applies remote sensing technology to assess and examine the spatial and temporal Brightness Temperature (BT) profile in the city of Tel-Aviv, Israel over the last 30 years using Landsat imagery. The location of warmest and coldest zones are constant over the studied period. Distinct diurnal and temporal BT behavior divide the city into four different segments. As an example of future application, we applied mixed regression models with daily random slopes to correlate Landsat BT data with monitored air temperature (Tair) measurements using 14 images for 1989–2014. Our preliminary results show a good model performance with R2 = 0.81. Furthermore, based on the model’s results, we analyzed the spatial profile of Tair within the study domain for representative days. PMID:26499933

The Spatial Relationship between Apparent Diffusion Coefficient and Standardized Uptake Value of 18F-Fluorodeoxyglucose Has a Crucial Influence on the Numeric Correlation of Both Parameters in PET/MRI of Lung Tumors.

Science.gov (United States)

Sauter, Alexander W; Stieltjes, Bram; Weikert, Thomas; Gatidis, Sergios; Wiese, Mark; Klarhöfer, Markus; Wild, Damian; Lardinois, Didier; Bremerich, Jens; Sommer, Gregor

2017-01-01

The minimum apparent diffusion coefficient (ADC min ) derived from diffusion-weighted MRI (DW-MRI) and the maximum standardized uptake value (SUV max ) of FDG-PET are markers of aggressiveness in lung cancer. The numeric correlation of the two parameters has been extensively studied, but their spatial interplay is not well understood. After FDG-PET and DW-MRI coregistration, values and location of ADC min - and SUV max -voxels were analyzed. The upper limit of the 95% confidence interval for registration accuracy of sequential PET/MRI was 12 mm, and the mean distance ( D ) between ADC min - and SUV max -voxels was 14.0 mm (average of two readers). Spatial mismatch ( D > 12 mm) between ADC min and SUV max was found in 9/25 patients. A considerable number of mismatch cases (65%) was also seen in a control group that underwent simultaneous PET/MRI. In the entire patient cohort, no statistically significant correlation between SUV max and ADC min was seen, while a moderate negative linear relationship ( r = -0.5) between SUV max and ADC min was observed in tumors with a spatial match ( D ≤ 12 mm). In conclusion, spatial mismatch between ADC min and SUV max is found in a considerable percentage of patients. The spatial connection of the two parameters SUV max and ADC min has a crucial influence on their numeric correlation.

Decomposition of variance for spatial Cox processes

DEFF Research Database (Denmark)

Jalilian, Abdollah; Guan, Yongtao; Waagepetersen, Rasmus

Spatial Cox point processes is a natural framework for quantifying the various sources of variation governing the spatial distribution of rain forest trees. We introduce a general criterion for variance decomposition for spatial Cox processes and apply it to specific Cox process models...

Decomposition of variance for spatial Cox processes

DEFF Research Database (Denmark)

Jalilian, Abdollah; Guan, Yongtao; Waagepetersen, Rasmus

2013-01-01

Spatial Cox point processes is a natural framework for quantifying the various sources of variation governing the spatial distribution of rain forest trees. We introduce a general criterion for variance decomposition for spatial Cox processes and apply it to specific Cox process models...

The effect of spatial confinement on the noble-gas HArF molecule: structure and electric properties

International Nuclear Information System (INIS)

Kozłowska, Justyna; Bartkowiak, Wojciech

2014-01-01

Highlights: • The structure and electrical properties of HArF in spatial confinement are analyzed. • Orbital compression leads to decrease of bond lengths in the HArF molecule. • Spatial restriction causes a drop of the molecular (hyper)polarizabilities. • Spatial confinement reduces the electron correlation contribution to μ, α and β. - Abstract: A systematic study on the dipole moment and (hyper)polarizabilities of argon fluorohydride under spatial restriction was performed. Detailed analysis of the confinement induced changes in the structure of HArF is also presented. In order to render the influence of chemical compression on the properties in question a two-dimensional harmonic oscillator potential, mimicking a cylindrical confinement, was applied. Through the comparison of the results obtained for HArF with those of HF the effect of Ar insertion on the above properties was discussed. A hierarchy of ab initio methods including HF, MP2, CCSD and CCSD(T), has been employed to investigate the effect of orbital compression on the electron correlation contribution to the studied electric properties. It was observed that the external confining potential modifies the electronic contributions to the dipole moment and (hyper)polarizabilities of HArF. In particular, the first hyperpolarizability of HArF is remarkably smaller than that of the unconfined HArF molecule

The effect of spatial confinement on the noble-gas HArF molecule: structure and electric properties

Energy Technology Data Exchange (ETDEWEB)

Kozłowska, Justyna; Bartkowiak, Wojciech, E-mail: wojciech.bartkowiak@pwr.edu.pl

2014-09-30

Highlights: • The structure and electrical properties of HArF in spatial confinement are analyzed. • Orbital compression leads to decrease of bond lengths in the HArF molecule. • Spatial restriction causes a drop of the molecular (hyper)polarizabilities. • Spatial confinement reduces the electron correlation contribution to μ, α and β. - Abstract: A systematic study on the dipole moment and (hyper)polarizabilities of argon fluorohydride under spatial restriction was performed. Detailed analysis of the confinement induced changes in the structure of HArF is also presented. In order to render the influence of chemical compression on the properties in question a two-dimensional harmonic oscillator potential, mimicking a cylindrical confinement, was applied. Through the comparison of the results obtained for HArF with those of HF the effect of Ar insertion on the above properties was discussed. A hierarchy of ab initio methods including HF, MP2, CCSD and CCSD(T), has been employed to investigate the effect of orbital compression on the electron correlation contribution to the studied electric properties. It was observed that the external confining potential modifies the electronic contributions to the dipole moment and (hyper)polarizabilities of HArF. In particular, the first hyperpolarizability of HArF is remarkably smaller than that of the unconfined HArF molecule.

The velocity correlation function in cosmic-ray diffusion theory

International Nuclear Information System (INIS)

Forman, M.A.

1977-01-01

The concept of velocity correlation functions is introduced and applied to the calculation of cosmic ray spatial diffusion coefficients. It is assumed that the pitch angle scattering coefficient is already known from some other theory, and is reasonably well-behaved. Previous results for the coefficient for diffusion parallel to the mean field are recovered when the velocity-changing mechanism is artificially restricted to pitch angle scattering. The velocity correlation method is then applied to the more general case where there are fluctuations in the local mean field. It is found that the parallel diffusion coefficient is reduced in proportion to the amplitude of the field fluctuations, and that the ratio of the perpendicular to parallel diffusion coefficients cannot be greater than 2 >/B 0 2 . It is shown in the appendix that the Liouville form of the scattering equation implies that the Fokker-Planck coefficients (Δμ 2 )/Δt=2Dsub(μμ) and (Δμ)/Δt=deltaDsub(μμ)/deltaμ, and that all higher-order coefficients are identically zero. (Auth.)

Spatial Analysis of the National Evaluation of Scholastic Achievement (ENLACE in Schools of the Municipality of Juarez, Chihuahua

Directory of Open Access Journals (Sweden)

Luis Ernesto Cervera Gómez

2008-05-01

Full Text Available This research was focused on analyzing the results of the first National Assessment of Academic Achievement for Scholar Centers (ENLACE; acronym in Spanish applied during the year 2006 in the Municipality of Juarez (State of Chihuahua, Mexico. In order to conduct the spatial analysis a geographical information system (GIS was used to make a georeferenced database were all variables were connected to a point representing a school. Results of the examinations expressed as deficient, elemental, good en excellent were spatially distributed over the urban area of Ciudad Juárez. Apparently there is a high spatial correlation between ENLACE’s results with the socioeconomic level of people. In this way results going from good to excellent were spatially located over the sectors more developed of the city. Poor results going from Insufficient to Elemental were spatially located at places with higher deficits of infrastructure and low socioeconomic levels.

Short- and long-range correlated motion observed in colloidal glasses and liquids

International Nuclear Information System (INIS)

Weeks, Eric R; Crocker, John C; Weitz, D A

2007-01-01

We use a confocal microscope to examine the motion of individual particles in a dense colloidal suspension. Close to the glass transition, particle motion is strongly spatially correlated. The correlations decay exponentially with particle separation, yielding a dynamic length scale of O(2-3σ) (in terms of particle diameter σ). This length scale grows modestly as the glass transition is approached. Further, the correlated motion exhibits a strong spatial dependence on the pair correlation function g(r). Motion within glassy samples is weakly correlated, but with a larger spatial scale for this correlation

The spatial analysis on hemorrhagic fever with renal syndrome in Jiangsu province, China based on geographic information system.

Science.gov (United States)

Bao, Changjun; Liu, Wanwan; Zhu, Yefei; Liu, Wendong; Hu, Jianli; Liang, Qi; Cheng, Yuejia; Wu, Ying; Yu, Rongbin; Zhou, Minghao; Shen, Hongbing; Chen, Feng; Tang, Fenyang; Peng, Zhihang

2014-01-01

Hemorrhagic fever with renal syndrome (HFRS) is endemic in mainland China, accounting for 90% of total reported cases worldwide, and Jiangsu is one of the most severely affected provinces. In this study, the authors conducted GIS-based spatial analyses in order to determine the spatial distribution of the HFRS cases, identify key areas and explore risk factors for public health planning and resource allocation. Interpolation maps by inverse distance weighting were produced to detect the spatial distribution of HFRS cases in Jiangsu from 2001 to 2011. Spatio-temporal clustering was applied to identify clusters at the county level. Spatial correlation analysis was conducted to detect influencing factors of HFRS in Jiangsu. HFRS cases in Jiangsu from 2001 to 2011 were mapped and the results suggested that cases in Jiangsu were not distributed randomly. Cases were mainly distributed in northeastern and southwestern Jiangsu, especially in Dafeng and Sihong counties. It was notable that prior to this study, Sihong county had rarely been reported as a high-risk area of HFRS. With the maximum spatial size of 50% of the total population and the maximum temporal size of 50% of the total population, spatio-temporal clustering showed that there was one most likely cluster (LLR = 624.52, Phighways, railways, rivers and lakes. The application of GIS together with spatial interpolation, spatio-temporal clustering and spatial correlation analysis can effectively identify high-risk areas and factors influencing HFRS incidence to lay a foundation for researching its pathogenesis.

Decomposition of variance for spatial Cox processes

DEFF Research Database (Denmark)

Jalilian, Abdollah; Guan, Yongtao; Waagepetersen, Rasmus

Spatial Cox point processes is a natural framework for quantifying the various sources of variation governing the spatial distribution of rain forest trees. We introducea general criterion for variance decomposition for spatial Cox processes and apply it to specific Cox process models with additive...

Applying Spatial Indicators to Support Sustainable Urban Futures

DEFF Research Database (Denmark)

Petrov, Laura Oana; Shahumyan, Harutyun; Williams, Brendan

2013-01-01

structural analysis, FRAGSTATS, and ArcGIS software packages. The developed indicators form a valuable and complementary addition to the planning and policy process due to their interdisciplinary and practical nature. They were elaborated based on discussions with scientists, policy-makers and stakeholders......Indicators are helpful tools for land use management, particularly in the context of sustainable urban development. Together with scenarios they are a key requirement in order to produce information for stakeholders and policy-makers and aid their understanding of development processes. Using...... these information products and tools, policy-makers can be given the opportunity to spatially interrogate the driving forces and the current state of urban development. Understanding how trends will develop in the future and the possible impacts of their decisions on the development process is vital...

Collective behavior in the spatial spreading of obesity

Science.gov (United States)

Gallos, Lazaros K.; Barttfeld, Pablo; Havlin, Shlomo; Sigman, Mariano; Makse, Hernán A.

2012-06-01

Obesity prevalence is increasing in many countries at alarming levels. A difficulty in the conception of policies to reverse these trends is the identification of the drivers behind the obesity epidemics. Here, we implement a spatial spreading analysis to investigate whether obesity shows spatial correlations, revealing the effect of collective and global factors acting above individual choices. We find a regularity in the spatial fluctuations of their prevalence revealed by a pattern of scale-free long-range correlations. The fluctuations are anomalous, deviating in a fundamental way from the weaker correlations found in the underlying population distribution indicating the presence of collective behavior, i.e., individual habits may have negligible influence in shaping the patterns of spreading. Interestingly, we find the same scale-free correlations in economic activities associated with food production. These results motivate future interventions to investigate the causality of this relation providing guidance for the implementation of preventive health policies.

Quantitative analysis of spatial variability of geotechnical parameters

Science.gov (United States)

Fang, Xing

2018-04-01

Geotechnical parameters are the basic parameters of geotechnical engineering design, while the geotechnical parameters have strong regional characteristics. At the same time, the spatial variability of geotechnical parameters has been recognized. It is gradually introduced into the reliability analysis of geotechnical engineering. Based on the statistical theory of geostatistical spatial information, the spatial variability of geotechnical parameters is quantitatively analyzed. At the same time, the evaluation of geotechnical parameters and the correlation coefficient between geotechnical parameters are calculated. A residential district of Tianjin Survey Institute was selected as the research object. There are 68 boreholes in this area and 9 layers of mechanical stratification. The parameters are water content, natural gravity, void ratio, liquid limit, plasticity index, liquidity index, compressibility coefficient, compressive modulus, internal friction angle, cohesion and SP index. According to the principle of statistical correlation, the correlation coefficient of geotechnical parameters is calculated. According to the correlation coefficient, the law of geotechnical parameters is obtained.

Spatial-temporal-spectral EEG patterns of BOLD functional network connectivity dynamics

Science.gov (United States)

Lamoš, Martin; Mareček, Radek; Slavíček, Tomáš; Mikl, Michal; Rektor, Ivan; Jan, Jiří

2018-06-01

Objective. Growing interest in the examination of large-scale brain network functional connectivity dynamics is accompanied by an effort to find the electrophysiological correlates. The commonly used constraints applied to spatial and spectral domains during electroencephalogram (EEG) data analysis may leave part of the neural activity unrecognized. We propose an approach that blindly reveals multimodal EEG spectral patterns that are related to the dynamics of the BOLD functional network connectivity. Approach. The blind decomposition of EEG spectrogram by parallel factor analysis has been shown to be a useful technique for uncovering patterns of neural activity. The simultaneously acquired BOLD fMRI data were decomposed by independent component analysis. Dynamic functional connectivity was computed on the component’s time series using a sliding window correlation, and between-network connectivity states were then defined based on the values of the correlation coefficients. ANOVA tests were performed to assess the relationships between the dynamics of between-network connectivity states and the fluctuations of EEG spectral patterns. Main results. We found three patterns related to the dynamics of between-network connectivity states. The first pattern has dominant peaks in the alpha, beta, and gamma bands and is related to the dynamics between the auditory, sensorimotor, and attentional networks. The second pattern, with dominant peaks in the theta and low alpha bands, is related to the visual and default mode network. The third pattern, also with peaks in the theta and low alpha bands, is related to the auditory and frontal network. Significance. Our previous findings revealed a relationship between EEG spectral pattern fluctuations and the hemodynamics of large-scale brain networks. In this study, we suggest that the relationship also exists at the level of functional connectivity dynamics among large-scale brain networks when no standard spatial and spectral

Two-dimensional optical correlation spectroscopy applied to liquid/glass dynamics

OpenAIRE

Lazonder, Kees; Pshenichnikov, Maxim S.; Wiersma, Douwe A.; Corkum, Paul; Jonas, David M.; Miller, R.J. Dwayne.; Weiner, Andrew M.

2007-01-01

Correlation spectroscopy was used to study the effects of temperature and phase changes on liquid and glass solvent dynamics. By assessing the eccentricity of the elliptic shape of a 2D optical correlation spectrum the value of the underlying frequency-frequency correlation function can be retrieved through a very simple relationship. This method yielded both intuitive clues and a quantitative measure of the dynamics of the system.

The Smoothing Artifact of Spatially Constrained Canonical Correlation Analysis in Functional MRI

Directory of Open Access Journals (Sweden)

Dietmar Cordes

2012-01-01

Full Text Available A wide range of studies show the capacity of multivariate statistical methods for fMRI to improve mapping of brain activations in a noisy environment. An advanced method uses local canonical correlation analysis (CCA to encompass a group of neighboring voxels instead of looking at the single voxel time course. The value of a suitable test statistic is used as a measure of activation. It is customary to assign the value to the center voxel; however, this is a choice of convenience and without constraints introduces artifacts, especially in regions of strong localized activation. To compensate for these deficiencies, different spatial constraints in CCA have been introduced to enforce dominance of the center voxel. However, even if the dominance condition for the center voxel is satisfied, constrained CCA can still lead to a smoothing artifact, often called the “bleeding artifact of CCA”, in fMRI activation patterns. In this paper a new method is introduced to measure and correct for the smoothing artifact for constrained CCA methods. It is shown that constrained CCA methods corrected for the smoothing artifact lead to more plausible activation patterns in fMRI as shown using data from a motor task and a memory task.

Parameterizing the Spatial Markov Model From Breakthrough Curve Data Alone

Science.gov (United States)

Sherman, Thomas; Fakhari, Abbas; Miller, Savannah; Singha, Kamini; Bolster, Diogo

2017-12-01

The spatial Markov model (SMM) is an upscaled Lagrangian model that effectively captures anomalous transport across a diverse range of hydrologic systems. The distinct feature of the SMM relative to other random walk models is that successive steps are correlated. To date, with some notable exceptions, the model has primarily been applied to data from high-resolution numerical simulations and correlation effects have been measured from simulated particle trajectories. In real systems such knowledge is practically unattainable and the best one might hope for is breakthrough curves (BTCs) at successive downstream locations. We introduce a novel methodology to quantify velocity correlation from BTC data alone. By discretizing two measured BTCs into a set of arrival times and developing an inverse model, we estimate velocity correlation, thereby enabling parameterization of the SMM in studies where detailed Lagrangian velocity statistics are unavailable. The proposed methodology is applied to two synthetic numerical problems, where we measure all details and thus test the veracity of the approach by comparison of estimated parameters with known simulated values. Our results suggest that our estimated transition probabilities agree with simulated values and using the SMM with this estimated parameterization accurately predicts BTCs downstream. Our methodology naturally allows for estimates of uncertainty by calculating lower and upper bounds of velocity correlation, enabling prediction of a range of BTCs. The measured BTCs fall within the range of predicted BTCs. This novel method to parameterize the SMM from BTC data alone is quite parsimonious, thereby widening the SMM's practical applicability.

An examination of gender bias on the eighth-grade MEAP science test as it relates to the Hunter Gatherer Theory of Spatial Sex Differences

Science.gov (United States)

Armstrong-Hall, Judy Gail

The purpose of this study was to apply the Hunter-Gatherer Theory of sex spatial skills to responses to individual questions by eighth grade students on the Science component of the Michigan Educational Assessment Program (MEAP) to determine if sex bias was inherent in the test. The Hunter-Gatherer Theory on Spatial Sex Differences, an original theory, that suggested a spatial dimorphism concept with female spatial skill of pattern recall of unconnected items and male spatial skills requiring mental movement. This is the first attempt to apply the Hunter-Gatherer Theory on Spatial Sex Differences to a standardized test. An overall hypothesis suggested that the Hunter-Gatherer Theory of Spatial Sex Differences could predict that males would perform better on problems involving mental movement and females would do better on problems involving the pattern recall of unconnected items. Responses to questions on the 1994-95 MEAP requiring the use of male spatial skills and female spatial skills were analyzed for 5,155 eighth grade students. A panel composed of five educators and a theory developer determined which test items involved the use of male and female spatial skills. A MANOVA, using a random sample of 20% of the 5,155 students to compare male and female correct scores, was statistically significant, with males having higher scores on male spatial skills items and females having higher scores on female spatial skills items. Pearson product moment correlation analyses produced a positive correlation for both male and female performance on both types of spatial skills. The Hunter-Gatherer Theory of Spatial Sex Differences appears to be able to predict that males could perform better on the problems involving mental movement and females could perform better on problems involving the pattern recall of unconnected items. Recommendations for further research included: examination of male/female spatial skill differences at early elementary and high school levels to

An alternative to the standard spatial econometric approaches in hedonic house price models

DEFF Research Database (Denmark)

Veie, Kathrine Lausted; Panduro, Toke Emil

Hedonic models are subject to spatially correlated errors which are a symptom of omitted spatial variables, mis-specification or mismeasurement. Methods have been developed to address this problem through the use of spatial econometrics or spatial fixed effects. However, often spatial correlation is...... varying characteristics markedly. This suggests that omitted variable bias may remain an important problem. We advocate for an increased use of sensitivity analysis to determine robustness of estimates to different models of the (omitted) spatial processes....

Spatial correlation analysis of seismic noise for STAR X-ray infrastructure design

Science.gov (United States)

D'Alessandro, Antonino; Agostino, Raffaele; Festa, Lorenzo; Gervasi, Anna; Guerra, Ignazio; Palmer, Dennis T.; Serafini, Luca

2014-05-01

. For this reason, we performed some measurements of seismic noise in order to characterize the environmental noise in the site in which the X-ray accelerator arise. For the characterization of the site, we carried out several passive seismic monitoring experiments at different times of the day and in different weather conditions. We recorded microtremor using an array of broadband 3C seismic sensors arranged along the linear accelerator. For each measurement point, we determined the displacement, velocity and acceleration spectrogram and power spectral density of both horizontal and vertical components. We determined also the microtremor horizontal to vertical spectral ratio as function of azimuth to individuate the main ground vibration direction and detect the existence of site or building resonance frequencies. We applied a rotation matrix to transform the North-South and East-West signal components in transversal and radial components, respect to the direction of the linear accelerator. Subsequently, for each couple of seismic stations we determined the coherence function to analyze the seismic noise spatial correlation. These analyses have allowed us to exhaustively characterize the seismic noise of the study area, from the point of view of the power and space-time variability, both in frequency and wavelength.

Irregular Liesegang-type patterns in gas phase revisited. II. Statistical correlation analysis

Science.gov (United States)

Torres-Guzmán, José C.; Martínez-Mekler, Gustavo; Müller, Markus F.

2016-05-01

We present a statistical analysis of Liesegang-type patterns formed in a gaseous HCl-NH3 system by ammonium chloride precipitation along glass tubes, as described in Paper I [J. C. Torres-Guzmán et al., J. Chem. Phys. 144, 174701 (2016)] of this work. We focus on the detection and characterization of short and long-range correlations within the non-stationary sequence of apparently irregular precipitation bands. To this end we applied several techniques to estimate spatial correlations stemming from different fields, namely, linear auto-correlation via the power spectral density, detrended fluctuation analysis (DFA), and methods developed in the context of random matrix theory (RMT). In particular RMT methods disclose well pronounced long-range correlations over at least 40 bands in terms of both, band positions and intensity values. By using a variant of the DFA we furnish proof of the nonlinear nature of the detected long-range correlations.

Spatial clustering of metal and metalloid mixtures in unregulated water sources on the Navajo Nation - Arizona, New Mexico, and Utah, USA.

Science.gov (United States)

Hoover, Joseph H; Coker, Eric; Barney, Yolanda; Shuey, Chris; Lewis, Johnnye

2018-08-15

Contaminant mixtures are identified regularly in public and private drinking water supplies throughout the United States; however, the complex and often correlated nature of mixtures makes identification of relevant combinations challenging. This study employed a Bayesian clustering method to identify subgroups of water sources with similar metal and metalloid profiles. Additionally, a spatial scan statistic assessed spatial clustering of these subgroups and a human health metric was applied to investigate potential for human toxicity. These methods were applied to a dataset comprised of metal and metalloid measurements from unregulated water sources located on the Navajo Nation, in the southwest United States. Results indicated distinct subgroups of water sources with similar contaminant profiles and that some of these subgroups were spatially clustered. Several profiles had metal and metalloid concentrations that may have potential for human toxicity including arsenic, uranium, lead, manganese, and selenium. This approach may be useful for identifying mixtures in water sources, spatially evaluating the clusters, and help inform toxicological research investigating mixtures. Copyright © 2018 The Authors. Published by Elsevier B.V. All rights reserved.

The Determinants of VAT Introduction : A Spatial Duration Analysis

NARCIS (Netherlands)

Cizek, P.; Lei, J.; Ligthart, J.E.

2012-01-01

Abstract: The spatial survival models typically impose frailties, which characterize unobserved heterogeneity, to be spatially correlated. This specification relies highly on a pre-determinate covariance structure of the errors. However, the spatial effect may not only exist in the unobserved

Regional Convergence of Income: Spatial Analysis

Directory of Open Access Journals (Sweden)

Vera Ivanovna Ivanova

2014-12-01

Full Text Available Russia has a huge territory and a strong interregional heterogeneity, so we can assume that geographical factors have a significant impact on the pace of economic growth in Russian regions. Therefore the article is focused on the following issues: 1 correlation between comparative advantages of geographical location and differences in growth rates; 2 impact of more developed regions on their neighbors and 3 correlation between economic growth of regions and their spatial interaction. The article is devoted to the empirical analysis of regional per capita incomes from 1996 to 2012 and explores the dynamics of the spatial autocorrelation of regional development indicator. It is shown that there is a problem of measuring the intensity of spatial dependence: factor value of Moran’s index varies greatly depending on the choice of the matrix of distances. In addition, with the help of spatial econometrics the author tests the following hypotheses: 1 there is convergence between regions for a specified period; 2 the process of beta convergence is explained by the spatial arrangement of regions and 3 there is positive impact of market size on regional growth. The author empirically confirmed all three hypotheses

Implication of the first decision on visual information-sampling in the spatial frequency domain in pulmonary nodule recognition

Science.gov (United States)

Pietrzyk, Mariusz W.; Manning, David; Donovan, Tim; Dix, Alan

2010-02-01

Aim: To investigate the impact on visual sampling strategy and pulmonary nodule recognition of image-based properties of background locations in dwelled regions where the first overt decision was made. . Background: Recent studies in mammography show that the first overt decision (TP or FP) has an influence on further image reading including the correctness of the following decisions. Furthermore, the correlation between the spatial frequency properties of the local background following decision sites and the first decision correctness has been reported. Methods: Subjects with different radiological experience were eye tracked during detection of pulmonary nodules from PA chest radiographs. Number of outcomes and the overall quality of performance are analysed in terms of the cases where correct or incorrect decisions were made. JAFROC methodology is applied. The spatial frequency properties of selected local backgrounds related to a certain decisions were studied. ANOVA was used to compare the logarithmic values of energy carried by non redundant stationary wavelet packet coefficients. Results: A strong correlation has been found between the number of TP as a first decision and the JAFROC score (r = 0.74). The number of FP as a first decision was found negatively correlated with JAFROC (r = -0.75). Moreover, the differential spatial frequency profiles outcomes depend on the first choice correctness.

An investigation of the validity of the virtual spatial navigation assessment

Directory of Open Access Journals (Sweden)

Matthew eVentura

2013-12-01

Full Text Available This correlational study investigated a new measure of environmental spatial ability (i.e., large scale spatial ability called the Virtual Spatial Navigation Assessment (VSNA. In the VSNA, participants must find a set of gems in a virtual 3D environment using a first person avatar on a computer. The VSNA runs in a web browser and automatically collects the time taken to find each gem. The time taken to collect gems in the VSNA was significantly correlated to three oth-er spatial ability measures, math standardized test scores, and choice to be in a STEM (science, technology, engineering, or math career. These findings support the validity of the VSNA as a measure of environmental spatial ability. Finally, self-report video game experience was also significantly correlated to the VSNA suggesting that video game may improve environmental spatial ability. Recommendations are made for how the VSNA can be used to help guide individuals toward STEM career paths and identify weaknesses that might be addressed with large scale spatial navigation training.

A Robust and Multi-Weighted Approach to Estimating Topographically Correlated Tropospheric Delays in Radar Interferograms

Directory of Open Access Journals (Sweden)

Bangyan Zhu

2016-07-01

Full Text Available Spatial and temporal variations in the vertical stratification of the troposphere introduce significant propagation delays in interferometric synthetic aperture radar (InSAR observations. Observations of small amplitude surface deformations and regional subsidence rates are plagued by tropospheric delays, and strongly correlated with topographic height variations. Phase-based tropospheric correction techniques assuming a linear relationship between interferometric phase and topography have been exploited and developed, with mixed success. Producing robust estimates of tropospheric phase delay however plays a critical role in increasing the accuracy of InSAR measurements. Meanwhile, few phase-based correction methods account for the spatially variable tropospheric delay over lager study regions. Here, we present a robust and multi-weighted approach to estimate the correlation between phase and topography that is relatively insensitive to confounding processes such as regional subsidence over larger regions as well as under varying tropospheric conditions. An expanded form of robust least squares is introduced to estimate the spatially variable correlation between phase and topography by splitting the interferograms into multiple blocks. Within each block, correlation is robustly estimated from the band-filtered phase and topography. Phase-elevation ratios are multiply- weighted and extrapolated to each persistent scatter (PS pixel. We applied the proposed method to Envisat ASAR images over the Southern California area, USA, and found that our method mitigated the atmospheric noise better than the conventional phase-based method. The corrected ground surface deformation agreed better with those measured from GPS.

Neural correlates of spatial navigation changes in mild cognitive impairment and Alzheimer’s disease

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Kamil eVlček

2014-03-01

Full Text Available Although the memory impairment is a hallmark of Alzheimer’s disease (AD, AD has also been characterized by spatial disorientation, which is present from its early stages. Spatial disorientation in AD manifests itself in getting lost in familiar and unfamiliar places and have been characterized more specifically using spatial navigation tests in both real space and virtual environments as an impairment in multiple spatial abilities, including allocentric and egocentric navigation strategies, visuospatial perception or selection of relevant information for successful navigation. Patients suffering mild cognitive impairment (MCI, who are at a high risk of development of dementia, show impairment in a subset of these abilities, mainly connected with allocentric and egocentric processing. While spatial disorientation in typical AD patients probably reflects neurodegenerative changes in medial and posterior temporal, parietal and frontal lobes and retrosplenial cortex, the impairment of spatial navigation in MCI seem to be connected mainly with the medial temporal and also parietal brain changes. In this review we will summarize the signs of brain disease in most MCI and AD patients showing in various tasks of spatial memory and navigation.

Correlation analysis of fracture arrangement in space

Science.gov (United States)

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.

Information Theory for Correlation Analysis and Estimation of Uncertainty Reduction in Maps and Models

Directory of Open Access Journals (Sweden)

J. Florian Wellmann

2013-04-01

Full Text Available The quantification and analysis of uncertainties is important in all cases where maps and models of uncertain properties are the basis for further decisions. Once these uncertainties are identified, the logical next step is to determine how they can be reduced. Information theory provides a framework for the analysis of spatial uncertainties when different subregions are considered as random variables. In the work presented here, joint entropy, conditional entropy, and mutual information are applied for a detailed analysis of spatial uncertainty correlations. The aim is to determine (i which areas in a spatial analysis share information, and (ii where, and by how much, additional information would reduce uncertainties. As an illustration, a typical geological example is evaluated: the case of a subsurface layer with uncertain depth, shape and thickness. Mutual information and multivariate conditional entropies are determined based on multiple simulated model realisations. Even for this simple case, the measures not only provide a clear picture of uncertainties and their correlations but also give detailed insights into the potential reduction of uncertainties at each position, given additional information at a different location. The methods are directly applicable to other types of spatial uncertainty evaluations, especially where multiple realisations of a model simulation are analysed. In summary, the application of information theoretic measures opens up the path to a better understanding of spatial uncertainties, and their relationship to information and prior knowledge, for cases where uncertain property distributions are spatially analysed and visualised in maps and models.

Spatial pattern of Amazonian timber species using cartesian and spatial coordinates method

Directory of Open Access Journals (Sweden)

Tiago Monteiro Condé

2016-06-01

Full Text Available Geographic information system (GIS applied to forest analysis permit the recognition and analysis of spatial patterns of species in two and three dimensional. The aim of this study to demonstrate the efficiency of cartesian and spatial coordinates method (MCCE, method of correcting UTM coordinates of trees location in accordance with the location of field or Cartesian (X ,Y, combined with natural neighbor index (ANND in recognition and analysis of spatial distribution patterns of four commercial timber species in forest management in Caracaraí, Roraima State, Brazil. Simulations were performed on 9 ha, divided into 100 plots of 100 m2 each. Collected data were DBH > 10 cm, commercial and total heights, cartesian coordinates (X,Y and spatial coordinates (UTM. Random spatial patterns were observed in Eschweilera bracteosa and Manilkara huberi. The dispersed and rare spatial patterns were observed in Dinizia excelsa and Cedrelinga cateniformis. MCCE proved to be an efficient method in the recognition and analysis of spatial patterns of native species from Amazon rain forest, as forest planning becomes easier by 2D and 3D simulations.

Clustering Coefficients for Correlation Networks

Directory of Open Access Journals (Sweden)

Naoki Masuda

2018-03-01

Full Text Available Graph theory is a useful tool for deciphering structural and functional networks of the brain on various spatial and temporal scales. The clustering coefficient quantifies the abundance of connected triangles in a network and is a major descriptive statistics of networks. For example, it finds an application in the assessment of small-worldness of brain networks, which is affected by attentional and cognitive conditions, age, psychiatric disorders and so forth. However, it remains unclear how the clustering coefficient should be measured in a correlation-based network, which is among major representations of brain networks. In the present article, we propose clustering coefficients tailored to correlation matrices. The key idea is to use three-way partial correlation or partial mutual information to measure the strength of the association between the two neighboring nodes of a focal node relative to the amount of pseudo-correlation expected from indirect paths between the nodes. Our method avoids the difficulties of previous applications of clustering coefficient (and other measures in defining correlational networks, i.e., thresholding on the correlation value, discarding of negative correlation values, the pseudo-correlation problem and full partial correlation matrices whose estimation is computationally difficult. For proof of concept, we apply the proposed clustering coefficient measures to functional magnetic resonance imaging data obtained from healthy participants of various ages and compare them with conventional clustering coefficients. We show that the clustering coefficients decline with the age. The proposed clustering coefficients are more strongly correlated with age than the conventional ones are. We also show that the local variants of the proposed clustering coefficients (i.e., abundance of triangles around a focal node are useful in characterizing individual nodes. In contrast, the conventional local clustering coefficients

Clustering Coefficients for Correlation Networks.

Science.gov (United States)

Masuda, Naoki; Sakaki, Michiko; Ezaki, Takahiro; Watanabe, Takamitsu

2018-01-01

Graph theory is a useful tool for deciphering structural and functional networks of the brain on various spatial and temporal scales. The clustering coefficient quantifies the abundance of connected triangles in a network and is a major descriptive statistics of networks. For example, it finds an application in the assessment of small-worldness of brain networks, which is affected by attentional and cognitive conditions, age, psychiatric disorders and so forth. However, it remains unclear how the clustering coefficient should be measured in a correlation-based network, which is among major representations of brain networks. In the present article, we propose clustering coefficients tailored to correlation matrices. The key idea is to use three-way partial correlation or partial mutual information to measure the strength of the association between the two neighboring nodes of a focal node relative to the amount of pseudo-correlation expected from indirect paths between the nodes. Our method avoids the difficulties of previous applications of clustering coefficient (and other) measures in defining correlational networks, i.e., thresholding on the correlation value, discarding of negative correlation values, the pseudo-correlation problem and full partial correlation matrices whose estimation is computationally difficult. For proof of concept, we apply the proposed clustering coefficient measures to functional magnetic resonance imaging data obtained from healthy participants of various ages and compare them with conventional clustering coefficients. We show that the clustering coefficients decline with the age. The proposed clustering coefficients are more strongly correlated with age than the conventional ones are. We also show that the local variants of the proposed clustering coefficients (i.e., abundance of triangles around a focal node) are useful in characterizing individual nodes. In contrast, the conventional local clustering coefficients were strongly

Clustering Coefficients for Correlation Networks

Science.gov (United States)

Masuda, Naoki; Sakaki, Michiko; Ezaki, Takahiro; Watanabe, Takamitsu

2018-01-01

Graph theory is a useful tool for deciphering structural and functional networks of the brain on various spatial and temporal scales. The clustering coefficient quantifies the abundance of connected triangles in a network and is a major descriptive statistics of networks. For example, it finds an application in the assessment of small-worldness of brain networks, which is affected by attentional and cognitive conditions, age, psychiatric disorders and so forth. However, it remains unclear how the clustering coefficient should be measured in a correlation-based network, which is among major representations of brain networks. In the present article, we propose clustering coefficients tailored to correlation matrices. The key idea is to use three-way partial correlation or partial mutual information to measure the strength of the association between the two neighboring nodes of a focal node relative to the amount of pseudo-correlation expected from indirect paths between the nodes. Our method avoids the difficulties of previous applications of clustering coefficient (and other) measures in defining correlational networks, i.e., thresholding on the correlation value, discarding of negative correlation values, the pseudo-correlation problem and full partial correlation matrices whose estimation is computationally difficult. For proof of concept, we apply the proposed clustering coefficient measures to functional magnetic resonance imaging data obtained from healthy participants of various ages and compare them with conventional clustering coefficients. We show that the clustering coefficients decline with the age. The proposed clustering coefficients are more strongly correlated with age than the conventional ones are. We also show that the local variants of the proposed clustering coefficients (i.e., abundance of triangles around a focal node) are useful in characterizing individual nodes. In contrast, the conventional local clustering coefficients were strongly

Evaluating spatial and temporal variability in growth and mortality for recreational fisheries with limited catch data

Science.gov (United States)

Li, Yan; Wagner, Tyler; Jiao, Yan; Lorantas, Robert M.; Murphy, Cheryl

2018-01-01

Understanding the spatial and temporal variability in life-history traits among populations is essential for the management of recreational fisheries. However, valuable freshwater recreational fish species often suffer from a lack of catch information. In this study, we demonstrated the use of an approach to estimate the spatial and temporal variability in growth and mortality in the absence of catch data and apply the method to riverine smallmouth bass (Micropterus dolomieu) populations in Pennsylvania, USA. Our approach included a growth analysis and a length-based analysis that estimates mortality. Using a hierarchical Bayesian approach, we examined spatial variability in growth and mortality by assuming parameters vary spatially but remain constant over time and temporal variability by assuming parameters vary spatially and temporally. The estimated growth and mortality of smallmouth bass showed substantial variability over time and across rivers. We explored the relationships of the estimated growth and mortality with spring water temperature and spring flow. Growth rate was likely to be positively correlated with these two factors, while young mortality was likely to be positively correlated with spring flow. The spatially and temporally varying growth and mortality suggest that smallmouth bass populations across rivers may respond differently to management plans and disturbance such as environmental contamination and land-use change. The analytical approach can be extended to other freshwater recreational species that also lack of catch data. The approach could also be useful in developing population assessments with erroneous catch data or be used as a model sensitivity scenario to verify traditional models even when catch data are available.

Diffuse correlation tomography in the transport regime: A theoretical study of the sensitivity to Brownian motion

Science.gov (United States)

Tricoli, Ugo; Macdonald, Callum M.; Durduran, Turgut; Da Silva, Anabela; Markel, Vadim A.

2018-02-01

Diffuse correlation tomography (DCT) uses the electric-field temporal autocorrelation function to measure the mean-square displacement of light-scattering particles in a turbid medium over a given exposure time. The movement of blood particles is here estimated through a Brownian-motion-like model in contrast to ordered motion as in blood flow. The sensitivity kernel relating the measurable field correlation function to the mean-square displacement of the particles can be derived by applying a perturbative analysis to the correlation transport equation (CTE). We derive an analytical expression for the CTE sensitivity kernel in terms of the Green's function of the radiative transport equation, which describes the propagation of the intensity. We then evaluate the kernel numerically. The simulations demonstrate that, in the transport regime, the sensitivity kernel provides sharper spatial information about the medium as compared with the correlation diffusion approximation. Also, the use of the CTE allows one to explore some additional degrees of freedom in the data such as the collimation direction of sources and detectors. Our results can be used to improve the spatial resolution of DCT, in particular, with applications to blood flow imaging in regions where the Brownian motion is dominant.

Spatial vision is superior in musicians when memory plays a role.

Science.gov (United States)

Weiss, Atalia H; Biron, Tali; Lieder, Itay; Granot, Roni Y; Ahissar, Merav

2014-08-21

Musicians' perceptual advantage in the acoustic domain is well established. Recent studies show that musicians' verbal working memory is also superior. Additionally, some studies report that musicians' visuospatial skills are enhanced although others failed to find this enhancement. We now examined whether musicians' spatial vision is superior, and if so, whether this superiority reflects refined visual skills or a general superiority of working memory. We examined spatial frequency discrimination among musicians and nonmusician university students using two presentation conditions: simultaneous (spatial forced choice) and sequential (temporal forced choice). Musicians' performance was similar to that of nonmusicians in the simultaneous condition. However, their performance in the sequential condition was superior, suggesting an advantage only when stimuli need to be retained, i.e., working memory. Moreover, the two groups showed a different pattern of correlations: Musicians' visual thresholds were correlated, and neither was correlated with their verbal memory. By contrast, among nonmusicians, the visual thresholds were not correlated, but sequential thresholds were correlated with verbal memory scores, suggesting that a general working memory component limits their performance in this condition. We propose that musicians' superiority in spatial frequency discrimination reflects an advantage in a domain-general aspect of working memory rather than a general enhancement in spatial-visual skills. © 2014 ARVO.

Effect of intranasal manganese administration on neurotransmission and spatial learning in rats

Energy Technology Data Exchange (ETDEWEB)

Blecharz-Klin, Kamilla; Piechal, Agnieszka; Joniec-Maciejak, Ilona; Pyrzanowska, Justyna; Widy-Tyszkiewicz, Ewa, E-mail: etyszkiewicz@wum.edu.pl

2012-11-15

The effect of intranasal manganese chloride (MnCl{sub 2}·4H{sub 2}O) exposure on spatial learning, memory and motor activity was estimated in Morris water maze task in adult rats. Three-month-old male Wistar rats received for 2 weeks MnCl{sub 2}·4H{sub 2}O at two doses the following: 0.2 mg/kg b.w. (Mn0.2) or 0.8 mg/kg b.w. (Mn0.8) per day. Control (Con) and manganese-exposed groups were observed for behavioral performance and learning in water maze. ANOVA for repeated measurements did not show any significant differences in acquisition in the water maze between the groups. However, the results of the probe trial on day 5, exhibited spatial memory deficits following manganese treatment. After completion of the behavioral experiment, the regional brain concentrations of neurotransmitters and their metabolites were determined via HPLC in selected brain regions, i.e. prefrontal cortex, hippocampus and striatum. ANOVA demonstrated significant differences in the content of monoamines and metabolites between the treatment groups compared to the controls. Negative correlations between platform crossings on the previous platform position in Southeast (SE) quadrant during the probe trial and neurotransmitter turnover suggest that impairment of spatial memory and cognitive performance after manganese (Mn) treatment is associated with modulation of the serotonergic, noradrenergic and dopaminergic neurotransmission in the brain. These findings show that intranasally applied Mn can impair spatial memory with significant changes in the tissue level and metabolism of monoamines in several brain regions. -- Highlights: ► Intranasal exposure to manganese in rats impairs spatial memory in the water maze. ► Regional changes in levels of neurotransmitters in the brain have been identified. ► Cognitive disorder correlates with modulation of 5-HT, NA and DA neurotransmission.

Effect of intranasal manganese administration on neurotransmission and spatial learning in rats

International Nuclear Information System (INIS)

Blecharz-Klin, Kamilla; Piechal, Agnieszka; Joniec-Maciejak, Ilona; Pyrzanowska, Justyna; Widy-Tyszkiewicz, Ewa

2012-01-01

The effect of intranasal manganese chloride (MnCl 2 ·4H 2 O) exposure on spatial learning, memory and motor activity was estimated in Morris water maze task in adult rats. Three-month-old male Wistar rats received for 2 weeks MnCl 2 ·4H 2 O at two doses the following: 0.2 mg/kg b.w. (Mn0.2) or 0.8 mg/kg b.w. (Mn0.8) per day. Control (Con) and manganese-exposed groups were observed for behavioral performance and learning in water maze. ANOVA for repeated measurements did not show any significant differences in acquisition in the water maze between the groups. However, the results of the probe trial on day 5, exhibited spatial memory deficits following manganese treatment. After completion of the behavioral experiment, the regional brain concentrations of neurotransmitters and their metabolites were determined via HPLC in selected brain regions, i.e. prefrontal cortex, hippocampus and striatum. ANOVA demonstrated significant differences in the content of monoamines and metabolites between the treatment groups compared to the controls. Negative correlations between platform crossings on the previous platform position in Southeast (SE) quadrant during the probe trial and neurotransmitter turnover suggest that impairment of spatial memory and cognitive performance after manganese (Mn) treatment is associated with modulation of the serotonergic, noradrenergic and dopaminergic neurotransmission in the brain. These findings show that intranasally applied Mn can impair spatial memory with significant changes in the tissue level and metabolism of monoamines in several brain regions. -- Highlights: ► Intranasal exposure to manganese in rats impairs spatial memory in the water maze. ► Regional changes in levels of neurotransmitters in the brain have been identified. ► Cognitive disorder correlates with modulation of 5-HT, NA and DA neurotransmission.

Applying big data technologies in the financial sector – using sentiment analysis to identify correlations in the stock market

Directory of Open Access Journals (Sweden)

Eszter Katalin Bognár

2016-06-01

Full Text Available The aim of this article is to introduce a system that is capable of collecting and analyzing different types of financial data to support traders in their decision - making. Oracle’s Big Data platform Oracle Advanced Analytics was utilized, which extends the Oracle Database with Oracle R, thus providing the opportunity to run embedded R scripts on the database server to speed up data processing. The extract, transform and load (ETL process was combined with a dictionary - based sentiment analysis module to examine cross - correlation and causality between numerical and textual financial data for a 10 week period. A notable correlation (0.42 was found between daily news sentiment scores and daily stock returns. By applying cross - correlation analysis and Granger causality testing, the results show that the news’ impact is incorporated into stock prices rapidly, having the highest correlation on the first day, while the returns’ impact on market sentiment is seen only after a few days.

Correlation diagnostics of random spatially nonuniform optical fields

International Nuclear Information System (INIS)

Angel'skii, O.V.

1992-01-01

This review examines some questions concerning the capabilities of interference and polarization-interference correlation diagnostics of the amplitude-phase characteristics of random optical fields for the purpose of identifying these fields and then studying the corresponding objects. The diagnostics of random phase objects is discussed separately in the case in which the phase dispersion of the inhomogeneities is less than and greater than one. The outlook is promising for the use of the correlation dimensionality of chaos in a field as a diagnostic parameter. It is also shown that the use of interference principles for a parallel processing of large data files can substantially increase the speed of processing systems. 32 refs., 8 figs

Speckle and fringe dynamics in imagingspeckle-pattern interferometry for spatial-filtering velocimetry

DEFF Research Database (Denmark)

Jakobsen, Michael Linde; Iversen, Theis F. Q.; Yura, Harold T.

2011-01-01

This paper analyzes the dynamics of laser speckles and fringes, formed in an imaging-speckle-pattern interferometer with the purpose of sensing linear three-dimensional motion and out-of-plane components of rotation in real time, using optical spatial-filtering-velocimetry techniques. The ensemble......-average definition of the cross-correlation function is applied to the intensity distributions, obtained in the observation plane at two positions of the object. The theoretical analysis provides a description for the dynamics of both the speckles and the fringes. The analysis reveals that both the magnitude...... and direction of all three linear displacement components of the object movement can be determined. Simultaneously, out-ofplane rotation of the object including the corresponding directions can be determined from the spatial gradient of the in-plane fringe motion throughout the observation plane. The theory...

Eigenstructures of MIMO Fading Channel Correlation Matrices and Optimum Linear Precoding Designs for Maximum Ergodic Capacity

Directory of Open Access Journals (Sweden)

Hamid Reza Bahrami

2007-01-01

Full Text Available The ergodic capacity of MIMO frequency-flat and -selective channels depends greatly on the eigenvalue distribution of spatial correlation matrices. Knowing the eigenstructure of correlation matrices at the transmitter is very important to enhance the capacity of the system. This fact becomes of great importance in MIMO wireless systems where because of the fast changing nature of the underlying channel, full channel knowledge is difficult to obtain at the transmitter. In this paper, we first investigate the effect of eigenvalues distribution of spatial correlation matrices on the capacity of frequency-flat and -selective channels. Next, we introduce a practical scheme known as linear precoding that can enhance the ergodic capacity of the channel by changing the eigenstructure of the channel by applying a linear transformation. We derive the structures of precoders using eigenvalue decomposition and linear algebra techniques in both cases and show their similarities from an algebraic point of view. Simulations show the ability of this technique to change the eigenstructure of the channel, and hence enhance the ergodic capacity considerably.

Pair and triplet approximation of a spatial lattice population model with multiscale dispersal using Markov chains for estimating spatial autocorrelation.

Science.gov (United States)

Hiebeler, David E; Millett, Nicholas E

2011-06-21

We investigate a spatial lattice model of a population employing dispersal to nearest and second-nearest neighbors, as well as long-distance dispersal across the landscape. The model is studied via stochastic spatial simulations, ordinary pair approximation, and triplet approximation. The latter method, which uses the probabilities of state configurations of contiguous blocks of three sites as its state variables, is demonstrated to be greatly superior to pair approximations for estimating spatial correlation information at various scales. Correlations between pairs of sites separated by arbitrary distances are estimated by constructing spatial Markov processes using the information from both approximations. These correlations demonstrate why pair approximation misses basic qualitative features of the model, such as decreasing population density as a large proportion of offspring are dropped on second-nearest neighbors, and why triplet approximation is able to include them. Analytical and numerical results show that, excluding long-distance dispersal, the initial growth rate of an invading population is maximized and the equilibrium population density is also roughly maximized when the population spreads its offspring evenly over nearest and second-nearest neighboring sites. Copyright © 2011 Elsevier Ltd. All rights reserved.

Boundary Information Inflow Enhances Correlation in Flocking

Science.gov (United States)

Cavagna, Andrea; Giardina, Irene; Ginelli, Francesco

2013-04-01

The most conspicuous trait of collective animal behavior is the emergence of highly ordered structures. Less obvious to the eye, but perhaps more profound a signature of self-organization, is the presence of long-range spatial correlations. Experimental data on starling flocks in 3D show that the exponent ruling the decay of the velocity correlation function, C(r)˜1/rγ, is extremely small, γ≪1. This result can neither be explained by equilibrium field theory nor by off-equilibrium theories and simulations of active systems. Here, by means of numerical simulations and theoretical calculations, we show that a dynamical field applied to the boundary of a set of Heisenberg spins on a 3D lattice gives rise to a vanishing exponent γ, as in starling flocks. The effect of the dynamical field is to create an information inflow from border to bulk that triggers long-range spin-wave modes, thus giving rise to an anomalously long-ranged correlation. The biological origin of this phenomenon can be either exogenous—information produced by environmental perturbations is transferred from boundary to bulk of the flock—or endogenous—the flock keeps itself in a constant state of dynamical excitation that is beneficial to correlation and collective response.

Nonlinear correlations in the hydrophobicity and average flexibility along the glycolytic enzymes sequences

Energy Technology Data Exchange (ETDEWEB)

Ciorsac, Alecu, E-mail: aleciorsac@yahoo.co [Politehnica University of Timisoara, Department of Physical Education and Sport, 2 P-ta Victoriei, 300006, Timisoara (Romania); Craciun, Dana, E-mail: craciundana@gmail.co [Teacher Training Department, West University of Timisoara, 4 Boulevard V. Pirvan, Timisoara, 300223 (Romania); Ostafe, Vasile, E-mail: vostafe@cbg.uvt.r [Department of Chemistry, West University of Timisoara, 16 Pestallozi, 300115, Timisoara (Romania); Laboratory of Advanced Researches in Environmental Protection, Nicholas Georgescu-Roegen Interdisciplinary Research and Formation Platform, 4 Oituz, Timisoara, 300086 (Romania); Isvoran, Adriana, E-mail: aisvoran@cbg.uvt.r [Department of Chemistry, West University of Timisoara, 16 Pestallozi, 300115, Timisoara (Romania); Laboratory of Advanced Researches in Environmental Protection, Nicholas Georgescu-Roegen Interdisciplinary Research and Formation Platform, 4 Oituz, Timisoara, 300086 (Romania)

2011-04-15

Research highlights: lights: We focus our study on the glycolytic enzymes. We reveal correlation of hydrophobicity and flexibility along their chains. We also reveal fractal aspects of the glycolytic enzymes structures and surfaces. The glycolytic enzyme sequences are not random. Creation of fractal structures requires the operation of nonlinear dynamics. - Abstract: Nonlinear methods widely used for time series analysis were applied to glycolytic enzyme sequences to derive information concerning the correlation of hydrophobicity and average flexibility along their chains. The 20 sequences of different types of the 10 human glycolytic enzymes were considered as spatial series and were analyzed by spectral analysis, detrended fluctuations analysis and Hurst coefficient calculation. The results agreed that there are both short range and long range correlations of hydrophobicity and average flexibility within investigated sequences, the short range correlations being stronger and indicating that local interactions are the most important for the protein folding. This correlation is also reflected by the fractal nature of the structures of investigated proteins.

Spatial modeling of households' knowledge about arsenic pollution in Bangladesh.

Science.gov (United States)

Sarker, M Mizanur Rahman

2012-04-01

Arsenic in drinking water is an important public health issue in Bangladesh, which is affected by households' knowledge about arsenic threats from their drinking water. In this study, spatial statistical models were used to investigate the determinants and spatial dependence of households' knowledge about arsenic risk. The binary join matrix/binary contiguity matrix and inverse distance spatial weight matrix techniques are used to capture spatial dependence in the data. This analysis extends the spatial model by allowing spatial dependence to vary across divisions and regions. A positive spatial correlation was found in households' knowledge across neighboring districts at district, divisional and regional levels, but the strength of this spatial correlation varies considerably by spatial weight. Literacy rate, daily wage rate of agricultural labor, arsenic status, and percentage of red mark tube well usage in districts were found to contribute positively and significantly to households' knowledge. These findings have policy implications both at regional and national levels in mitigating the present arsenic crisis and to ensure arsenic-free water in Bangladesh. Copyright © 2012 Elsevier Ltd. All rights reserved.

StereoGene: rapid estimation of genome-wide correlation of continuous or interval feature data.

Science.gov (United States)

Stavrovskaya, Elena D; Niranjan, Tejasvi; Fertig, Elana J; Wheelan, Sarah J; Favorov, Alexander V; Mironov, Andrey A

2017-10-15

Genomics features with similar genome-wide distributions are generally hypothesized to be functionally related, for example, colocalization of histones and transcription start sites indicate chromatin regulation of transcription factor activity. Therefore, statistical algorithms to perform spatial, genome-wide correlation among genomic features are required. Here, we propose a method, StereoGene, that rapidly estimates genome-wide correlation among pairs of genomic features. These features may represent high-throughput data mapped to reference genome or sets of genomic annotations in that reference genome. StereoGene enables correlation of continuous data directly, avoiding the data binarization and subsequent data loss. Correlations are computed among neighboring genomic positions using kernel correlation. Representing the correlation as a function of the genome position, StereoGene outputs the local correlation track as part of the analysis. StereoGene also accounts for confounders such as input DNA by partial correlation. We apply our method to numerous comparisons of ChIP-Seq datasets from the Human Epigenome Atlas and FANTOM CAGE to demonstrate its wide applicability. We observe the changes in the correlation between epigenomic features across developmental trajectories of several tissue types consistent with known biology and find a novel spatial correlation of CAGE clusters with donor splice sites and with poly(A) sites. These analyses provide examples for the broad applicability of StereoGene for regulatory genomics. The StereoGene C ++ source code, program documentation, Galaxy integration scripts and examples are available from the project homepage http://stereogene.bioinf.fbb.msu.ru/. favorov@sensi.org. Supplementary data are available at Bioinformatics online. © The Author 2017. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com

Co-occurrence correlations of heavy metals in sediments revealed using network analysis.

Science.gov (United States)

Liu, Lili; Wang, Zhiping; Ju, Feng; Zhang, Tong

2015-01-01

In this study, the correlation-based study was used to identify the co-occurrence correlations among metals in marine sediment of Hong Kong, based on the long-term (from 1991 to 2011) temporal and spatial monitoring data. 14 stations out of the total 45 marine sediment monitoring stations were selected from three representative areas, including Deep Bay, Victoria Harbour and Mirs Bay. Firstly, Spearman's rank correlation-based network analysis was conducted as the first step to identify the co-occurrence correlations of metals from raw metadata, and then for further analysis using the normalized metadata. The correlations patterns obtained by network were consistent with those obtained by the other statistic normalization methods, including annual ratios, R-squared coefficient and Pearson correlation coefficient. Both Deep Bay and Victoria Harbour have been polluted by heavy metals, especially for Pb and Cu, which showed strong co-occurrence with other heavy metals (e.g. Cr, Ni, Zn and etc.) and little correlations with the reference parameters (Fe or Al). For Mirs Bay, which has better marine sediment quality compared with Deep Bay and Victoria Harbour, the co-occurrence patterns revealed by network analysis indicated that the metals in sediment dominantly followed the natural geography process. Besides the wide applications in biology, sociology and informatics, it is the first time to apply network analysis in the researches of environment pollutions. This study demonstrated its powerful application for revealing the co-occurrence correlations among heavy metals in marine sediments, which could be further applied for other pollutants in various environment systems. Copyright © 2014 Elsevier Ltd. All rights reserved.

Nanoscale protein diffusion by STED-based pair correlation analysis.

Directory of Open Access Journals (Sweden)

Paolo Bianchini

Full Text Available We describe for the first time the combination between cross-pair correlation function analysis (pair correlation analysis or pCF and stimulated emission depletion (STED to obtain diffusion maps at spatial resolution below the optical diffraction limit (super-resolution. Our approach was tested in systems characterized by high and low signal to noise ratio, i.e. Capsid Like Particles (CLPs bearing several (>100 active fluorescent proteins and monomeric fluorescent proteins transiently expressed in living Chinese Hamster Ovary cells, respectively. The latter system represents the usual condition encountered in living cell studies on fluorescent protein chimeras. Spatial resolution of STED-pCF was found to be about 110 nm, with a more than twofold improvement over conventional confocal acquisition. We successfully applied our method to highlight how the proximity to nuclear envelope affects the mobility features of proteins actively imported into the nucleus in living cells. Remarkably, STED-pCF unveiled the existence of local barriers to diffusion as well as the presence of a slow component at distances up to 500-700 nm from either sides of nuclear envelope. The mobility of this component is similar to that previously described for transport complexes. Remarkably, all these features were invisible in conventional confocal mode.

Spatial Temporal Image Correlation Spectroscopy (STICS) for Flow Analysis with Application for Blood Flow Mapping

International Nuclear Information System (INIS)

Rossow, Molly; Gratton, Enrico; Mantulin, William M.

2009-01-01

It is important for surgeons to be able to measure blood flow in exposed arterioles during surgery. We report our progress in the development of an optical technique that will measure blood flow in surgically exposed blood vessels and enable previously difficult measurements. By monitoring optical fluctuations, the optical technique, based on Spatial Temporal Image Correlation (STICS), will directly measure the velocity of micron-scale particles--such as red blood cells. It will complement existing technology and provide qualitative measurements that were not previously possible. It relies on the concept that blood, when viewed on a small enough scale, is an inhomogeneous substance. Individual blood cells passing between a near-infrared light source and a detector will cause fluctuations in the transmitted optical signal. The speed, direction, and flow pattern of blood cells can be determined from these optical fluctuations. We present a series of computer simulations and experiments on phantom and animal systems to test this technique's ability to map complex flow patterns.

Characterization of Impact Damage in Ultra-High Performance Concrete Using Spatially Correlated Nanoindentation/SEM/EDX

Science.gov (United States)

Moser, R. D.; Allison, P. G.; Chandler, M. Q.

2013-12-01

Little work has been done to study the fundamental material behaviors and failure mechanisms of cement-based materials including ordinary Portland cement concrete and ultra-high performance concretes (UHPCs) under high strain impact and penetration loads at lower length scales. These high strain rate loadings have many possible effects on UHPCs at the microscale and nanoscale, including alterations in the hydration state and bonding present in phases such as calcium silicate hydrate, in addition to fracture and debonding. In this work, the possible chemical and physical changes in UHPCs subjected to high strain rate impact and penetration loads were investigated using a novel technique wherein nanoindentation measurements were spatially correlated with images using scanning electron microscopy and chemical composition using energy dispersive x-ray microanalysis. Results indicate that impact degrades both the elastic modulus and indentation hardness of UHPCs, and in particular hydrated phases, with damage likely occurring due to microfracturing and debonding.

Correlates of biological soil crust abundance across a continuum of spatial scales: Support for a hierarchical conceptual model

Science.gov (United States)

Bowker, M.A.; Belnap, J.; Davidson, D.W.; Goldstein, H.

2006-01-01

1. Desertification negatively impacts a large proportion of the global human population and > 30% of the terrestrial land surface. Better methods are needed to detect areas that are at risk of desertification and to ameliorate desertified areas. Biological soil crusts are an important soil lichen-moss-microbial community that can be used toward these goals, as (i) bioindicators of desertification damage and (ii) promoters of soil stability and fertility. 2. We identified environmental factors that correlate with soil crust occurrence on the landscape and might be manipulated to assist recovery of soil crusts in degraded areas. We conducted three studies on the Colorado Plateau, USA, to investigate the hypotheses that soil fertility [particularly phosphorus (P), manganese (Mn) and zinc (Zn)] and/or moisture limit soil crust lichens and mosses at four spatial scales. 3. In support of the soil fertility hypothesis, we found that lichen-moss crusts were positively correlated with several nutrients [Mn, Zn, potassium (K) and magnesium (Mg) were most consistent] at three of four spatial scales ranging from 3.5 cm2 in area to c. 800 km2. In contrast, P was negatively correlated with lichen-moss crusts at three scales. 4. Community composition varied with micro-aspect on ridges in the soil crust. Three micro-aspects [north-north-west (NNW), east-north-east (ENE) and TOP] supported greater lichen and moss cover than the warmer, windward and more xeric micro-aspects [west-south-west (WSW) and south-south-east (SSE)]. This pattern was poorly related to soil fertility; rather, it was consistent with the moisture limitation hypothesis. 5. Synthesis and application. Use of crusts as desertification bioindicators requires knowledge of a site's potential for crust cover in the absence of desertification. We present a multi-scale model of crust potential as a function of site properties. Future quantitative studies can use this model to guide sampling efforts. Also, our results

Correlation of gravestone decay and air quality 1960-2010

Science.gov (United States)

Mooers, H. D.; Carlson, M. J.; Harrison, R. M.; Inkpen, R. J.; Loeffler, S.

2017-03-01

Evaluation of spatial and temporal variability in surface recession of lead-lettered Carrara marble gravestones provides a quantitative measure of acid flux to the stone surfaces and is closely related to local land use and air quality. Correlation of stone decay, land use, and air quality for the period after 1960 when reliable estimates of atmospheric pollution are available is evaluated. Gravestone decay and SO2 measurements are interpolated spatially using deterministic and geostatistical techniques. A general lack of spatial correlation was identified and therefore a land-use-based technique for correlation of stone decay and air quality is employed. Decadally averaged stone decay is highly correlated with land use averaged spatially over an optimum radius of ≈7 km even though air quality, determined by records from the UK monitoring network, is not highly correlated with gravestone decay. The relationships among stone decay, air-quality, and land use is complicated by the relatively low spatial density of both gravestone decay and air quality data and the fact that air quality data is available only as annual averages and therefore seasonal dependence cannot be evaluated. However, acid deposition calculated from gravestone decay suggests that the deposition efficiency of SO2 has increased appreciably since 1980 indicating an increase in the SO2 oxidation process possibly related to reactions with ammonia.

The spatial prediction of landslide susceptibility applying artificial neural network and logistic regression models: A case study of Inje, Korea

Science.gov (United States)

Saro, Lee; Woo, Jeon Seong; Kwan-Young, Oh; Moung-Jin, Lee

2016-02-01

The aim of this study is to predict landslide susceptibility caused using the spatial analysis by the application of a statistical methodology based on the GIS. Logistic regression models along with artificial neutral network were applied and validated to analyze landslide susceptibility in Inje, Korea. Landslide occurrence area in the study were identified based on interpretations of optical remote sensing data (Aerial photographs) followed by field surveys. A spatial database considering forest, geophysical, soil and topographic data, was built on the study area using the Geographical Information System (GIS). These factors were analysed using artificial neural network (ANN) and logistic regression models to generate a landslide susceptibility map. The study validates the landslide susceptibility map by comparing them with landslide occurrence areas. The locations of landslide occurrence were divided randomly into a training set (50%) and a test set (50%). A training set analyse the landslide susceptibility map using the artificial network along with logistic regression models, and a test set was retained to validate the prediction map. The validation results revealed that the artificial neural network model (with an accuracy of 80.10%) was better at predicting landslides than the logistic regression model (with an accuracy of 77.05%). Of the weights used in the artificial neural network model, `slope' yielded the highest weight value (1.330), and `aspect' yielded the lowest value (1.000). This research applied two statistical analysis methods in a GIS and compared their results. Based on the findings, we were able to derive a more effective method for analyzing landslide susceptibility.

The spatial prediction of landslide susceptibility applying artificial neural network and logistic regression models: A case study of Inje, Korea

Directory of Open Access Journals (Sweden)

Saro Lee

2016-02-01

Full Text Available The aim of this study is to predict landslide susceptibility caused using the spatial analysis by the application of a statistical methodology based on the GIS. Logistic regression models along with artificial neutral network were applied and validated to analyze landslide susceptibility in Inje, Korea. Landslide occurrence area in the study were identified based on interpretations of optical remote sensing data (Aerial photographs followed by field surveys. A spatial database considering forest, geophysical, soil and topographic data, was built on the study area using the Geographical Information System (GIS. These factors were analysed using artificial neural network (ANN and logistic regression models to generate a landslide susceptibility map. The study validates the landslide susceptibility map by comparing them with landslide occurrence areas. The locations of landslide occurrence were divided randomly into a training set (50% and a test set (50%. A training set analyse the landslide susceptibility map using the artificial network along with logistic regression models, and a test set was retained to validate the prediction map. The validation results revealed that the artificial neural network model (with an accuracy of 80.10% was better at predicting landslides than the logistic regression model (with an accuracy of 77.05%. Of the weights used in the artificial neural network model, ‘slope’ yielded the highest weight value (1.330, and ‘aspect’ yielded the lowest value (1.000. This research applied two statistical analysis methods in a GIS and compared their results. Based on the findings, we were able to derive a more effective method for analyzing landslide susceptibility.

Study of optoelectronic properties of thin film solar cell materials Cu2ZnSn(S,Se)4 using multiple correlative spatially-resolved spectroscopy techniques

Science.gov (United States)

Chen, Qiong

Containing only earth abundant and environmental friendly elements, quaternary compounds Cu2ZnSnS4 (CZTS) and Cu2ZnSnSe 4 (CZTSe) are considered as promising absorber materials for thin film solar cells. The best record efficiency for this type of thin film solar cell is now 12.6%. As a promising photovoltaic (PV) material, the electrical and optical properties of CZTS(Se) have not been well studied. In this work, an effort has been made to understand the optoelectronic and structural properties, in particular the spatial variations, of CZTS(Se) materials and devices by correlating multiple spatially resolved characterization techniques with sub-micron resolution. Micro-Raman (micro-Raman) spectroscopy was used to analyze the chemistry compositions in CZTS(Se) film; Micro-Photoluminescence (micro-PL) was used to determine the band gap and possible defects. Micro-Laser-Beam-Induced-Current (micro-LBIC) was used to examine the photo-response of CZTS(Se) solar cell in different illumination conditions. Micro-reflectance was used to estimate the reflectance loss. And Micro-I-V measurement was used to compare important electrical parameters from CZTS(Se) solar cells with different device structure or absorber compositions. Scanning electron microscopy and atomic force microscopy were used to characterize the surface morphology. Successfully integrating and correlating these techniques was first demonstrated during the course of this work in our laboratory, and this level of integration and correlation has been rare in the field of PV research. This effort is significant not only for this particular project and also for a wide range of research topics. Applying this approach, in conjunction with high-temperature and high-excitation-power optical spectroscopy, we have been able to reveal the microscopic scale variations among samples and devices that appeared to be very similar from macroscopic material and device characterizations, and thus serve as a very powerful tool

Unimodal and crossmodal gradients of spatial attention

DEFF Research Database (Denmark)

Föcker, J.; Hötting, K.; Gondan, Matthias

2010-01-01

Behavioral and event-related potential (ERP) studies have shown that spatial attention is gradually distributed around the center of the attentional focus. The present study compared uni- and crossmodal gradients of spatial attention to investigate whether the orienting of auditory and visual...... spatial attention is based on modality specific or supramodal representations of space. Auditory and visual stimuli were presented from five speaker locations positioned in the right hemifield. Participants had to attend to the innermost or outmost right position in order to detect either visual...... or auditory deviant stimuli. Detection rates and event-related potentials (ERPs) indicated that spatial attention is distributed as a gradient. Unimodal spatial ERP gradients correlated with the spatial resolution of the modality. Crossmodal spatial gradients were always broader than the corresponding...

Analysing earthquake slip models with the spatial prediction comparison test

KAUST Repository

Zhang, L.; Mai, Paul Martin; Thingbaijam, Kiran Kumar; Razafindrakoto, H. N. T.; Genton, Marc G.

2014-01-01

Earthquake rupture models inferred from inversions of geophysical and/or geodetic data exhibit remarkable variability due to uncertainties in modelling assumptions, the use of different inversion algorithms, or variations in data selection and data processing. A robust statistical comparison of different rupture models obtained for a single earthquake is needed to quantify the intra-event variability, both for benchmark exercises and for real earthquakes. The same approach may be useful to characterize (dis-)similarities in events that are typically grouped into a common class of events (e.g. moderate-size crustal strike-slip earthquakes or tsunamigenic large subduction earthquakes). For this purpose, we examine the performance of the spatial prediction comparison test (SPCT), a statistical test developed to compare spatial (random) fields by means of a chosen loss function that describes an error relation between a 2-D field (‘model’) and a reference model. We implement and calibrate the SPCT approach for a suite of synthetic 2-D slip distributions, generated as spatial random fields with various characteristics, and then apply the method to results of a benchmark inversion exercise with known solution. We find the SPCT to be sensitive to different spatial correlations lengths, and different heterogeneity levels of the slip distributions. The SPCT approach proves to be a simple and effective tool for ranking the slip models with respect to a reference model.

Analysing earthquake slip models with the spatial prediction comparison test

KAUST Repository

Zhang, L.

2014-11-10

Earthquake rupture models inferred from inversions of geophysical and/or geodetic data exhibit remarkable variability due to uncertainties in modelling assumptions, the use of different inversion algorithms, or variations in data selection and data processing. A robust statistical comparison of different rupture models obtained for a single earthquake is needed to quantify the intra-event variability, both for benchmark exercises and for real earthquakes. The same approach may be useful to characterize (dis-)similarities in events that are typically grouped into a common class of events (e.g. moderate-size crustal strike-slip earthquakes or tsunamigenic large subduction earthquakes). For this purpose, we examine the performance of the spatial prediction comparison test (SPCT), a statistical test developed to compare spatial (random) fields by means of a chosen loss function that describes an error relation between a 2-D field (‘model’) and a reference model. We implement and calibrate the SPCT approach for a suite of synthetic 2-D slip distributions, generated as spatial random fields with various characteristics, and then apply the method to results of a benchmark inversion exercise with known solution. We find the SPCT to be sensitive to different spatial correlations lengths, and different heterogeneity levels of the slip distributions. The SPCT approach proves to be a simple and effective tool for ranking the slip models with respect to a reference model.

Antenna Correlation From Input Parameters for Arbitrary Topologies and Terminations

DEFF Research Database (Denmark)

Alrabadi, Osama; Andersen, Jørgen Bach; Pedersen, Gert Frølund

2012-01-01

The spatial correlation between pairs of antennas in a system comprised of N RF ports is found by extending the N × N scattering matrix to (N + 1)×(N + 1) spatial scattering matrix, where the extra space dimension accounts for the reference port patterns. The lossless property of the spatial...... scattering matrix in a 3D uniform field is employed for expressing the spatial correlation between the port patterns at arbitrary complex terminations merely from the reference scattering parameters and the complex terminations without any far-field calculation....

Creating a spatial multi-criteria decision support system for energy related integrated environmental impact assessment

International Nuclear Information System (INIS)

Wanderer, Thomas; Herle, Stefan

2015-01-01

By their spatially very distributed nature, profitability and impacts of renewable energy resources are highly correlated with the geographic locations of power plant deployments. A web-based Spatial Decision Support System (SDSS) based on a Multi-Criteria Decision Analysis (MCDA) approach has been implemented for identifying preferable locations for solar power plants based on user preferences. The designated areas found serve for the input scenario development for a subsequent integrated Environmental Impact Assessment. The capabilities of the SDSS service get showcased for Concentrated Solar Power (CSP) plants in the region of Andalusia, Spain. The resulting spatial patterns of possible power plant sites are an important input to the procedural chain of assessing impacts of renewable energies in an integrated effort. The applied methodology and the implemented SDSS are applicable for other renewable technologies as well. - Highlights: • The proposed tool facilitates well-founded CSP plant siting decisions. • Spatial MCDA methods are implemented in a WebGIS environment. • GIS-based SDSS can contribute to a modern integrated impact assessment workflow. • The conducted case study proves the suitability of the methodology

Creating a spatial multi-criteria decision support system for energy related integrated environmental impact assessment

Energy Technology Data Exchange (ETDEWEB)

Wanderer, Thomas, E-mail: thomas.wanderer@dlr.de; Herle, Stefan, E-mail: stefan.herle@rwth-aachen.de

2015-04-15

By their spatially very distributed nature, profitability and impacts of renewable energy resources are highly correlated with the geographic locations of power plant deployments. A web-based Spatial Decision Support System (SDSS) based on a Multi-Criteria Decision Analysis (MCDA) approach has been implemented for identifying preferable locations for solar power plants based on user preferences. The designated areas found serve for the input scenario development for a subsequent integrated Environmental Impact Assessment. The capabilities of the SDSS service get showcased for Concentrated Solar Power (CSP) plants in the region of Andalusia, Spain. The resulting spatial patterns of possible power plant sites are an important input to the procedural chain of assessing impacts of renewable energies in an integrated effort. The applied methodology and the implemented SDSS are applicable for other renewable technologies as well. - Highlights: • The proposed tool facilitates well-founded CSP plant siting decisions. • Spatial MCDA methods are implemented in a WebGIS environment. • GIS-based SDSS can contribute to a modern integrated impact assessment workflow. • The conducted case study proves the suitability of the methodology.

Do neighbours influence value-added-tax introduction? A spatial duration analysis

NARCIS (Netherlands)

Cizek, Pavel; Lei, J.; Ligthart, J.E.

The spatial survival models typically impose frailties, which characterize unobserved heterogeneity, to be spatially correlated. However, the spatial effect may not only exist in the unobserved errors, but it can also be present in the baseline hazards and the dependent variables. A new spatial

Discrete quantum dot like emitters in monolayer MoSe{sub 2}: Spatial mapping, magneto-optics, and charge tuning

Energy Technology Data Exchange (ETDEWEB)

Branny, Artur; Kumar, Santosh; Gerardot, Brian D., E-mail: b.d.gerardot@hw.ac.uk [Institute of Photonics and Quantum Sciences, SUPA, Heriot-Watt University, Edinburgh EH14 4AS (United Kingdom); Wang, Gang; Robert, Cedric; Lassagne, Benjamin; Marie, Xavier; Urbaszek, Bernhard, E-mail: urbaszek@insa-toulouse.fr [Université de Toulouse, INSA-CNRS-UPS, LPCNO, 135 Av. Rangueil, 31077 Toulouse (France)

2016-04-04

Transition metal dichalcogenide monolayers such as MoSe{sub 2}, MoS{sub 2}, and WSe{sub 2} are direct bandgap semiconductors with original optoelectronic and spin-valley properties. Here we report on spectrally sharp, spatially localized emission in monolayer MoSe{sub 2}. We find this quantum dot-like emission in samples exfoliated onto gold substrates and also suspended flakes. Spatial mapping shows a correlation between the location of emitters and the existence of wrinkles (strained regions) in the flake. We tune the emission properties in magnetic and electric fields applied perpendicular to the monolayer plane. We extract an exciton g-factor of the discrete emitters close to −4, as for 2D excitons in this material. In a charge tunable sample, we record discrete jumps on the meV scale as charges are added to the emitter when changing the applied voltage.

Fano lineshapes of 'Peak-tracking chip' spatial profiles analyzed with correlation analysis for bioarray imaging and refractive index sensing

KAUST Repository

Bougot-Robin, K.

2013-05-22

The asymmetric Fano resonance lineshapes, resulting from interference between background and a resonant scattering, is archetypal in resonant waveguide grating (RWG) reflectivity. Resonant profile shift resulting from a change of refractive index (from fluid medium or biomolecules at the chip surface) is classically used to perform label-free sensing. Lineshapes are sometimes sampled at discretized “detuning” values to relax instrumental demands, the highest reflectivity element giving a coarse resonance estimate. A finer extraction, needed to increase sensor sensitivity, can be obtained using a correlation approach, correlating the sensed signal to a zero-shifted reference signal. Fabrication process is presented leading to discrete Fano profiles. Our findings are illustrated with resonance profiles from silicon nitride RWGs operated at visible wavelengths. We recently demonstrated that direct imaging multi-assay RWGs sensing may be rendered more reliable using “chirped” RWG chips, by varying a RWG structure parameter. Then, the spatial reflectivity profiles of tracks composed of RWGs units with slowly varying filling factor (thus slowly varying resonance condition) are measured under monochromatic conditions. Extracting the resonance location using spatial Fano profiles allows multiplex refractive index based sensing. Discretization and sensitivity are discussed both through simulation and experiment for different filling factor variation, here Δf=0.0222 and Δf=0.0089. This scheme based on a “Peak-tracking chip” demonstrates a new technique for bioarray imaging using a simpler set-up that maintains high performance with cheap lenses, with down to Δn=2×10-5 RIU sensitivity for the highest sampling of Fano lineshapes. © (2013) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.

Fano lineshapes of 'Peak-tracking chip' spatial profiles analyzed with correlation analysis for bioarray imaging and refractive index sensing

KAUST Repository

Bougot-Robin, K.; Li, S.; Yue, W.; Chen, L. Q.; Zhang, Xixiang; Wen, W. J.; Benisty, H.

2013-01-01

The asymmetric Fano resonance lineshapes, resulting from interference between background and a resonant scattering, is archetypal in resonant waveguide grating (RWG) reflectivity. Resonant profile shift resulting from a change of refractive index (from fluid medium or biomolecules at the chip surface) is classically used to perform label-free sensing. Lineshapes are sometimes sampled at discretized “detuning” values to relax instrumental demands, the highest reflectivity element giving a coarse resonance estimate. A finer extraction, needed to increase sensor sensitivity, can be obtained using a correlation approach, correlating the sensed signal to a zero-shifted reference signal. Fabrication process is presented leading to discrete Fano profiles. Our findings are illustrated with resonance profiles from silicon nitride RWGs operated at visible wavelengths. We recently demonstrated that direct imaging multi-assay RWGs sensing may be rendered more reliable using “chirped” RWG chips, by varying a RWG structure parameter. Then, the spatial reflectivity profiles of tracks composed of RWGs units with slowly varying filling factor (thus slowly varying resonance condition) are measured under monochromatic conditions. Extracting the resonance location using spatial Fano profiles allows multiplex refractive index based sensing. Discretization and sensitivity are discussed both through simulation and experiment for different filling factor variation, here Δf=0.0222 and Δf=0.0089. This scheme based on a “Peak-tracking chip” demonstrates a new technique for bioarray imaging using a simpler set-up that maintains high performance with cheap lenses, with down to Δn=2×10-5 RIU sensitivity for the highest sampling of Fano lineshapes. © (2013) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.

Improving correlations between MODIS aerosol optical thickness and ground-based PM 2.5 observations through 3D spatial analyses

Science.gov (United States)

Hutchison, Keith D.; Faruqui, Shazia J.; Smith, Solar

The Center for Space Research (CSR) continues to focus on developing methods to improve correlations between satellite-based aerosol optical thickness (AOT) values and ground-based, air pollution observations made at continuous ambient monitoring sites (CAMS) operated by the Texas commission on environmental quality (TCEQ). Strong correlations and improved understanding of the relationships between satellite and ground observations are needed to formulate reliable real-time predictions of air quality using data accessed from the moderate resolution imaging spectroradiometer (MODIS) at the CSR direct-broadcast ground station. In this paper, improvements in these correlations are demonstrated first as a result of the evolution in the MODIS retrieval algorithms. Further improvement is then shown using procedures that compensate for differences in horizontal spatial scales between the nominal 10-km MODIS AOT products and CAMS point measurements. Finally, airborne light detection and ranging (lidar) observations, collected during the Texas Air Quality Study of 2000, are used to examine aerosol profile concentrations, which may vary greatly between aerosol classes as a result of the sources, chemical composition, and meteorological conditions that govern transport processes. Further improvement in correlations is demonstrated with this limited dataset using insights into aerosol profile information inferred from the vertical motion vectors in a trajectory-based forecast model. Analyses are ongoing to verify these procedures on a variety of aerosol classes using data collected by the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite (Calipso) lidar.

Space, race, and poverty: Spatial inequalities in walkable neighborhood amenities?

Directory of Open Access Journals (Sweden)

John Whalen

2012-05-01

Full Text Available BACKGROUND Multiple and varied benefits have been suggested for increased neighborhood walkability. However, spatial inequalities in neighborhood walkability likely exist and may be attributable, in part, to residential segregation. OBJECTIVE Utilizing a spatial demographic perspective, we evaluated potential spatial inequalities in walkable neighborhood amenities across census tracts in Boston, MA (US. METHODS The independent variables included minority racial/ethnic population percentages and percent of families in poverty. Walkable neighborhood amenities were assessed with a composite measure. Spatial autocorrelation in key study variables were first calculated with the Global Moran's I statistic. Then, Spearman correlations between neighborhood socio-demographic characteristics and walkable neighborhood amenities were calculated as well as Spearman correlations accounting for spatial autocorrelation. We fit ordinary least squares (OLS regression and spatial autoregressive models when appropriate as a final step. RESULTS Significant positive spatial autocorrelation was found in neighborhood socio-demographic characteristics (e.g. census tract percent Black, but not walkable neighborhood amenities or in the OLS regression residuals. Spearman correlations between neighborhood socio-demographic characteristics and walkable neighborhood amenities were not statistically significant, nor were neighborhood socio-demographic characteristics significantly associated with walkable neighborhood amenities in OLS regression models. CONCLUSIONS Our results suggest that there is residential segregation in Boston and that spatial inequalities do not necessarily show up using a composite measure. COMMENTS Future research in other geographic areas (including international contexts and using different definitions of neighborhoods (including small-area definitions should evaluate if spatial inequalities are found using composite measures, but also should

Visual-Spatial Thinking in Hypertexts.

Science.gov (United States)

Johnson-Sheehan, Richard; Baehr, Craig

2001-01-01

Explores what it means to think visually and spatially in hypertexts and how users react and maneuver in real and virtual three-dimensional spaces. Offers four principles of visual thinking that can be applied when developing hypertexts. Applies these principles to actual hypertexts, demonstrating how selectivity, fixation, depth discernment, and…

Synthesis of dynamic phase profile by the correlation technique for spatial control of optical beams in multiplexing and switching

Science.gov (United States)

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.

Neural correlates of the spatial and expectancy components of endogenous and stimulus-driven orienting of attention in the Posner task.

Science.gov (United States)

Doricchi, Fabrizio; Macci, Enrica; Silvetti, Massimo; Macaluso, Emiliano

2010-07-01

Voluntary orienting of visual attention is conventionally measured in tasks with predictive central cues followed by frequent valid targets at the cued location and by infrequent invalid targets at the uncued location. This implies that invalid targets entail both spatial reorienting of attention and breaching of the expected spatial congruency between cues and targets. Here, we used event-related functional magnetic resonance imaging (fMRI) to separate the neural correlates of the spatial and expectancy components of both endogenous orienting and stimulus-driven reorienting of attention. We found that during endogenous orienting with predictive cues, there was a significant deactivation of the right Temporal-Parietal Junction (TPJ). We also discovered that the lack of an equivalent deactivation with nonpredictive cues was matched to drop in attentional costs and preservation of attentional benefits. The right TPJ showed equivalent responses to invalid targets following predictive and nonpredictive cues. On the contrary, infrequent-unexpected invalid targets following predictive cues specifically activated the right Middle and Inferior Frontal Gyrus (MFG-IFG). Additional comparisons with spatially neutral trials demonstrated that, independently of cue predictiveness, valid targets activate the left TPJ, whereas invalid targets activate both the left and right TPJs. These findings show that the selective right TPJ activation that is found in the comparison between invalid and valid trials results from the reciprocal cancelling of the different activations that in the left TPJ are related to the processing of valid and invalid targets. We propose that left and right TPJs provide "matching and mismatching to attentional template" signals. These signals enable reorienting of attention and play a crucial role in the updating of the statistical contingency between cues and targets.

Binary joint transform correlation using error-diffusion techniques

Science.gov (United States)

Inbar, Hanni; Marom, Emanuel; Konforti, Naim

1993-08-01

Optical pattern recognition techniques based on the optical joint transform correlator (JTC) scheme are attractive due to their simplicity. Recent improvements in spatial light modulators (SLM) increased the popularity of the JTC, providing means for real time operation. Using a binary SLM for the display of the Fourier spectrum, first requires binarization of the joint power spectrum distribution. Although hard-clipping is the simplest and most common binarization method used, we suggest to apply error-diffusion as an improved binarization technique. The performance of a binary JTC, whose input image is considered to contain additive zero-mean white Gaussian noise, is investigated. Various ways for nonlinearly modifying the joint power spectrum prior to the binarization step, which is based on either error-diffusion or hard-clipping techniques, are discussed. These nonlinear modifications aim at increasing the contrast of the interference fringes at the joint power spectrum plane, leading to better definition of the correlation signal. Mathematical analysis, computer simulations and experimental results are presented.

Neural correlates of spatial navigation changes in mild cognitive impairment and Alzheimer's disease

Czech Academy of Sciences Publication Activity Database

Vlček, Kamil; Laczó, J.

2014-01-01

Roč. 8, Mar 17 (2014), s. 89 ISSN 1662-5153 R&D Projects: GA MZd(CZ) NT13386 Grant - others:GA MŠk(CZ) ED1.100/02/0123 Institutional support: RVO:67985823 Keywords : spatial navigation * Alzheimer’s disease * spatial disorientation * brain changes * mild cognitive impairment Subject RIV: FH - Neurology Impact factor: 3.270, year: 2014

Relationship Study on Land Use Spatial Distribution Structure and Energy-Related Carbon Emission Intensity in Different Land Use Types of Guangdong, China, 1996–2008

Directory of Open Access Journals (Sweden)

Yi Huang

2013-01-01

Full Text Available 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.

Exploring the effects of photon correlations from thermal sources on bacterial photosynthesis

Directory of Open Access Journals (Sweden)

Pedro D. Manrique

Full Text Available Thermal light sources can produce photons with strong spatial correlations. We study the role that these correlations might potentially play in bacterial photosynthesis. Our findings show a relationship between the transversal distance between consecutive absorptions and the efficiency of the photosynthetic process. Furthermore, membranes where the clustering of core complexes (so-called RC-LH1 is high, display a range where the organism profits maximally from the spatial correlation of the incoming light. By contrast, no maximum is found for membranes with low core-core clustering. We employ a detailed membrane model with state-of-the-art empirical inputs. Our results suggest that the organization of the membrane’s antenna complexes may be well-suited to the spatial correlations present in an natural light source. Future experiments will be needed to test this prediction. Keywords: Photo-bunching, Spatial correlation, Photosynthesis, Purple bacteria

Hinges of Correlation: Spatial Devices of Social Coexistence

DEFF Research Database (Denmark)

Lunde Nielsen, Espen

2015-01-01

This project investigates the coexistence of and the correlation between the inhabitants within my apartment building, using artistic practices and my own lived experience. These everyday spaces form the primary interface between the individual and the larger social entity of the city. Consciously...

Spatial pattern of 2009 dengue distribution in Kuala Lumpur using GIS application.

Science.gov (United States)

Aziz, S; Ngui, R; Lim, Y A L; Sholehah, I; Nur Farhana, J; Azizan, A S; Wan Yusoff, W S

2012-03-01

In the last few years in Malaysia, dengue fever has increased dramatically and has caused huge public health concerns. The present study aimed to establish a spatial distribution of dengue cases in the city of Kuala Lumpur using a combination of Geographic Information System (GIS) and spatial statistical tools. Collation of data from 1,618 dengue cases in 2009 was obtained from Kuala Lumpur City Hall (DBKL). These data were processed and then converted into GIS format. Information on the average monthly rainfall was also used to correlate with the distribution pattern of dengue cases. To asses the spatial distribution of dengue cases, Average Nearest Neighbor (ANN) Analysis was applied together with spatial analysis with the ESRI ArcGIS V9.3 programme. Results indicated that the distribution of dengue cases in Kuala Lumpur for the year 2009 was spatially clustered with R value less than 1 (R = 0.42; z-scores = - 4.47; p 1) between August and November. In addition, the mean monthly rainfall has not influenced the distribution pattern of the dengue cases. Implementation of control measures is more difficult for dispersed pattern compared to clustered pattern. From this study, it was found that distribution pattern of dengue cases in Kuala Lumpur in 2009 was spatially distributed (dispersed or clustered) rather than cases occurring randomly. It was proven that by using GIS and spatial statistic tools, we can determine the spatial distribution between dengue and population. Utilization of GIS tools is vital in assisting health agencies, epidemiologist, public health officer, town planner and relevant authorities in developing efficient control measures and contingency programmes to effectively combat dengue fever.

Almeria spatial memory recognition test (ASMRT): Gender differences emerged in a new passive spatial task.

Science.gov (United States)

Tascón, Laura; García-Moreno, Luis Miguel; Cimadevilla, Jose Manuel

2017-06-09

Many different human spatial memory tasks were developed in the last two decades. Virtual reality based tasks make possible developing different scenarios and situations to assess spatial orientation but sometimes these tasks are complex for specific populations like children and older-adults. A new spatial task with a very limited technological requirement was developed in this study. It demanded the use of spatial memory for an accurate solution. It also proved to be sensitive to gender differences, with men outperforming women under high specific difficulty levels. Thanks to its simplicity it could be applied as a screening test and is easy to combine with EEG and fMRI studies. Copyright © 2017 Elsevier B.V. All rights reserved.

The spatial spread of schistosomiasis: A multidimensional network model applied to Saint-Louis region, Senegal

Science.gov (United States)

Ciddio, Manuela; Mari, Lorenzo; Sokolow, Susanne H.; De Leo, Giulio A.; Casagrandi, Renato; Gatto, Marino

2017-10-01

Schistosomiasis is a parasitic, water-related disease that is prevalent in tropical and subtropical areas of the world, causing severe and chronic consequences especially among children. Here we study the spatial spread of this disease within a network of connected villages in the endemic region of the Lower Basin of the Senegal River, in Senegal. The analysis is performed by means of a spatially explicit metapopulation model that couples local-scale eco-epidemiological dynamics with spatial mechanisms related to human mobility (estimated from anonymized mobile phone records), snail dispersal and hydrological transport of schistosome larvae along the main water bodies of the region. Results show that the model produces epidemiological patterns consistent with field observations, and point out the key role of spatial connectivity on the spread of the disease. These findings underline the importance of considering different transport pathways in order to elaborate disease control strategies that can be effective within a network of connected populations.

A catchment-scale model to predict spatial and temporal burden of E. coli on pasture from grazing livestock.

Science.gov (United States)

Oliver, David M; Bartie, Phil J; Louise Heathwaite, A; Reaney, Sim M; Parnell, Jared A Q; Quilliam, Richard S

2018-03-01

Effective management of diffuse microbial water pollution from agriculture requires a fundamental understanding of how spatial patterns of microbial pollutants, e.g. E. coli, vary over time at the landscape scale. The aim of this study was to apply the Visualising Pathogen &Environmental Risk (ViPER) model, developed to predict E. coli burden on agricultural land, in a spatially distributed manner to two contrasting catchments in order to map and understand changes in E. coli burden contributed to land from grazing livestock. The model was applied to the River Ayr and Lunan Water catchments, with significant correlations observed between area of improved grassland and the maximum total E. coli per 1km 2 grid cell (Ayr: r=0.57; pE. coli burden between seasons in both catchments, with summer and autumn predicted to accrue higher E. coli contributions relative to spring and winter (PE. coli loading to land as driven by stocking density and livestock grazing regimes. Resulting risk maps therefore provide the underpinning evidence to inform spatially-targeted decision-making with respect to managing sources of E. coli in agricultural environments. Copyright © 2017 The Author(s). Published by Elsevier B.V. All rights reserved.

Measurement of turbulent spatial structure and kinetic energy spectrum by exact temporal-to-spatial mapping

Science.gov (United States)

Buchhave, Preben; Velte, Clara M.

2017-08-01

We present a method for converting a time record of turbulent velocity measured at a point in a flow to a spatial velocity record consisting of consecutive convection elements. The spatial record allows computation of dynamic statistical moments such as turbulent kinetic wavenumber spectra and spatial structure functions in a way that completely bypasses the need for Taylor's hypothesis. The spatial statistics agree with the classical counterparts, such as the total kinetic energy spectrum, at least for spatial extents up to the Taylor microscale. The requirements for applying the method are access to the instantaneous velocity magnitude, in addition to the desired flow quantity, and a high temporal resolution in comparison to the relevant time scales of the flow. We map, without distortion and bias, notoriously difficult developing turbulent high intensity flows using three main aspects that distinguish these measurements from previous work in the field: (1) The measurements are conducted using laser Doppler anemometry and are therefore not contaminated by directional ambiguity (in contrast to, e.g., frequently employed hot-wire anemometers); (2) the measurement data are extracted using a correctly and transparently functioning processor and are analysed using methods derived from first principles to provide unbiased estimates of the velocity statistics; (3) the exact mapping proposed herein has been applied to the high turbulence intensity flows investigated to avoid the significant distortions caused by Taylor's hypothesis. The method is first confirmed to produce the correct statistics using computer simulations and later applied to measurements in some of the most difficult regions of a round turbulent jet—the non-equilibrium developing region and the outermost parts of the developed jet. The proposed mapping is successfully validated using corresponding directly measured spatial statistics in the fully developed jet, even in the difficult outer regions of

Parameterizing the Spatial Markov Model from Breakthrough Curve Data Alone

Science.gov (United States)

Sherman, T.; Bolster, D.; Fakhari, A.; Miller, S.; Singha, K.

2017-12-01

The spatial Markov model (SMM) uses a correlated random walk and has been shown to effectively capture anomalous transport in porous media systems; in the SMM, particles' future trajectories are correlated to their current velocity. It is common practice to use a priori Lagrangian velocity statistics obtained from high resolution simulations to determine a distribution of transition probabilities (correlation) between velocity classes that govern predicted transport behavior; however, this approach is computationally cumbersome. Here, we introduce a methodology to quantify velocity correlation from Breakthrough (BTC) curve data alone; discretizing two measured BTCs into a set of arrival times and reverse engineering the rules of the SMM allows for prediction of velocity correlation, thereby enabling parameterization of the SMM in studies where Lagrangian velocity statistics are not available. The introduced methodology is applied to estimate velocity correlation from BTCs measured in high resolution simulations, thus allowing for a comparison of estimated parameters with known simulated values. Results show 1) estimated transition probabilities agree with simulated values and 2) using the SMM with estimated parameterization accurately predicts BTCs downstream. Additionally, we include uncertainty measurements by calculating lower and upper estimates of velocity correlation, which allow for prediction of a range of BTCs. The simulated BTCs fall in the range of predicted BTCs. This research proposes a novel method to parameterize the SMM from BTC data alone, thereby reducing the SMM's computational costs and widening its applicability.

Quantum correlations induced by multiple scattering of quadrature squeezed light

DEFF Research Database (Denmark)

Lodahl, Peter

2006-01-01

Propagating quadrature squeezed light through a multiple scattering random medium is found to induce pronounced spatial quantum correlations that have no classical analogue. The correlations are revealed in the number of photons transported through the sample that can be measured from the intensity...... fluctuations of the total transmission or reflection. In contrast, no pronounced spatial quantum correlations appear in the quadrature amplitudes where excess noise above the shot noise level is found....

Emerging Correlation Optics

DEFF Research Database (Denmark)

Angelsky, Oleg V.; Gbur, Gregory J.; Polyanskii, Peter

2012-01-01

This feature issue of Applied Optics contains a series of selected papers reflecting the state-of-the-art of correlation optics and showing synergetics between the theoretical background and experimental techniques.......This feature issue of Applied Optics contains a series of selected papers reflecting the state-of-the-art of correlation optics and showing synergetics between the theoretical background and experimental techniques....

Spatial Distribution Analysis of Scrub Typhus in Korea

OpenAIRE

Jin, Hong Sung; Chu, Chaeshin; Han, Dong Yeob

2013-01-01

Objective: This study analyzes the spatial distribution of scrub typhus in Korea. Methods: A spatial distribution of Orientia tsutsugamushi occurrence using a geographic information system (GIS) is presented, and analyzed by means of spatial clustering and correlations. Results: The provinces of Gangwon-do and Gyeongsangbuk-do show a low incidence throughout the year. Some districts have almost identical environmental conditions of scrub typhus incidence. The land use change of districts does...

Residual analysis for spatial point processes

DEFF Research Database (Denmark)

Baddeley, A.; Turner, R.; Møller, Jesper

We define residuals for point process models fitted to spatial point pattern data, and propose diagnostic plots based on these residuals. The techniques apply to any Gibbs point process model, which may exhibit spatial heterogeneity, interpoint interaction and dependence on spatial covariates. Ou...... or covariate effects. Q-Q plots of the residuals are effective in diagnosing interpoint interaction. Some existing ad hoc statistics of point patterns (quadrat counts, scan statistic, kernel smoothed intensity, Berman's diagnostic) are recovered as special cases....

Spatial ability in computer-aided design courses

OpenAIRE

Torner Ribé, Jordi; Alpiste Penalba, Francesc; Brigos Hermida, Miguel Ángel

2014-01-01

Many studies have demonstrated that spatial ability is an important factor in the study of Industrial Engineering. Spatial ability is fundamentally important to the work of an engineer, as it is vital for project design. Among other elements, spatial ability correlates with factors such as good academic results and a natural ability to learn how to use I.T systems and computer programs. Furthermore, the new framework drawn up by the European Higher Education Area (EHEA) guides us as to the...

Novel probabilistic models of spatial genetic ancestry with applications to stratification correction in genome-wide association studies.

Science.gov (United States)

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

Toward seamless hydrologic predictions across spatial scales

NARCIS (Netherlands)

Samaniego, Luis; Kumar, Rohini; Thober, Stephan; Rakovec, Oldrich; Zink, Matthias; Wanders, Niko; Eisner, Stephanie; Müller Schmied, Hannes; Sutanudjaja, Edwin; Warrach-Sagi, Kirsten; Attinger, Sabine

2017-01-01

Land surface and hydrologic models (LSMs/HMs) are used at diverse spatial resolutions ranging from catchment-scale (1-10 km) to global-scale (over 50 km) applications. Applying the same model structure at different spatial scales requires that the model estimates similar fluxes independent of the

From micro-correlations to macro-correlations

International Nuclear Information System (INIS)

Eliazar, Iddo

2016-01-01

Random vectors with a symmetric correlation structure share a common value of pair-wise correlation between their different components. The symmetric correlation structure appears in a multitude of settings, e.g. mixture models. In a mixture model the components of the random vector are drawn independently from a general probability distribution that is determined by an underlying parameter, and the parameter itself is randomized. In this paper we study the overall correlation of high-dimensional random vectors with a symmetric correlation structure. Considering such a random vector, and terming its pair-wise correlation “micro-correlation”, we use an asymptotic analysis to derive the random vector’s “macro-correlation” : a score that takes values in the unit interval, and that quantifies the random vector’s overall correlation. The method of obtaining macro-correlations from micro-correlations is then applied to a diverse collection of frameworks that demonstrate the method’s wide applicability.

Spatial Temporal Image Correlation Spectroscopy (STICS) for Flow Analysis with Application for Blood Flow Mapping (abstract)

Science.gov (United States)

Rossow, Molly; Mantulin, William M.; Gratton, Enrico

2009-04-01

It is important for surgeons to be able to measure blood flow in exposed arterioles during surgery. We report our progress in the development of an optical technique that will measure blood flow in surgically exposed blood vessels and enable previously difficult measurements. By monitoring optical fluctuations, the optical technique, based on Spatial Temporal Image Correlation (STICS), will directly measure the velocity of micron-scale particles-such as red blood cells. It will complement existing technology and provide qualitative measurements that were not previously possible. It relies on the concept that blood, when viewed on a small enough scale, is an inhomogeneous substance. Individual blood cells passing between a near-infrared light source and a detector will cause fluctuations in the transmitted optical signal. The speed, direction, and flow pattern of blood cells can be determined from these optical fluctuations. We present a series of computer simulations and experiments on phantom and animal systems to test this technique's ability to map complex flow patterns.

Minimum Wages and Teen Employment: A Spatial Panel Approach

OpenAIRE

Charlene Kalenkoski; Donald Lacombe

2011-01-01

The authors employ spatial econometrics techniques and Annual Averages data from the U.S. Bureau of Labor Statistics for 1990-2004 to examine how changes in the minimum wage affect teen employment. Spatial econometrics techniques account for the fact that employment is correlated across states. Such correlation may exist if a change in the minimum wage in a state affects employment not only in its own state but also in other, neighboring states. The authors show that state minimum wages negat...

China's Air Quality and Respiratory Disease Mortality Based on the Spatial Panel Model.

Science.gov (United States)

Cao, Qilong; Liang, Ying; Niu, Xueting

2017-09-18

Background : Air pollution has become an important factor restricting China's economic development and has subsequently brought a series of social problems, including the impact of air pollution on the health of residents, which is a topical issue in China. Methods : Taking into account this spatial imbalance, the paper is based on the spatial panel data model PM 2.5 . Respiratory disease mortality in 31 Chinese provinces from 2004 to 2008 is taken as the main variable to study the spatial effect and impact of air quality and respiratory disease mortality on a large scale. Results : It was found that there is a spatial correlation between the mortality of respiratory diseases in Chinese provinces. The spatial correlation can be explained by the spatial effect of PM 2.5 pollutions in the control of other variables. Conclusions : Compared with the traditional non-spatial model, the spatial model is better for describing the spatial relationship between variables, ensuring the conclusions are scientific and can measure the spatial effect between variables.

Nonlinear correlations in the hydrophobicity and average flexibility along the glycolytic enzymes sequences

International Nuclear Information System (INIS)

Ciorsac, Alecu; Craciun, Dana; Ostafe, Vasile; Isvoran, Adriana

2011-01-01

Research highlights: → We focus our study on the glycolytic enzymes. → We reveal correlation of hydrophobicity and flexibility along their chains. → We also reveal fractal aspects of the glycolytic enzymes structures and surfaces. → The glycolytic enzyme sequences are not random. → Creation of fractal structures requires the operation of nonlinear dynamics. - Abstract: Nonlinear methods widely used for time series analysis were applied to glycolytic enzyme sequences to derive information concerning the correlation of hydrophobicity and average flexibility along their chains. The 20 sequences of different types of the 10 human glycolytic enzymes were considered as spatial series and were analyzed by spectral analysis, detrended fluctuations analysis and Hurst coefficient calculation. The results agreed that there are both short range and long range correlations of hydrophobicity and average flexibility within investigated sequences, the short range correlations being stronger and indicating that local interactions are the most important for the protein folding. This correlation is also reflected by the fractal nature of the structures of investigated proteins.

Correlations of plasticity in sheared glasses

NARCIS (Netherlands)

Varnik, F.; Mandal, S.; Chikkadi, V.; Denisov, D.; Olsson, P.; Vågberg, D.; Raabe, D.; Schall, P.

2014-01-01

n a recent paper [Mandal et al., Phys. Rev. E 88, 022129 (2013)], the nature of spatial correlations of plasticity in hard-sphere glasses was addressed both via computer simulations and in experiments. It was found that the experimentally obtained correlations obey a power law, whereas the

Spatial displacement of numbers on a vertical number line in spatial neglect

Directory of Open Access Journals (Sweden)

Urszula eMihulowicz

2015-04-01

Full Text Available Previous studies that investigated the association of numbers and space in humans came to contradictory conclusions about the spatial character of the mental number magnitude representation and about how it may be influenced by unilateral spatial neglect. The present study aimed to disentangle the debated influence of perceptual versus representational aspects via explicit mapping of numbers onto space by applying the number line estimation paradigm with vertical orientation of stimulus lines. Thirty-five acute right-brain damaged stroke patients (6 with neglect were asked to place two-digit numbers on vertically oriented lines with 0 marked at the bottom and 100 at the top. In contrast to the expected, nearly linear mapping in the control patient group, patients with spatial neglect overestimated the position of numbers in the lower middle range. The results corroborate spatial characteristics of the number magnitude representation. In neglect patients, this representation seems to be biased towards the ipsilesional side, independent of the physical orientation of the task stimuli.

Faster processing of multiple spatially-heterodyned direct to digital holograms

Science.gov (United States)

Hanson, Gregory R [Clinton, TN; Bingham, Philip R [Knoxville, TN

2008-09-09

Systems and methods are described for faster processing of multiple spatially-heterodyned direct to digital holograms. A method includes of obtaining multiple spatially-heterodyned holograms, includes: digitally recording a first spatially-heterodyned hologram including spatial heterodyne fringes for Fourier analysis; digitally recording a second spatially-heterodyned hologram including spatial heterodyne fringes for Fourier analysis; Fourier analyzing the recorded first spatially-heterodyned hologram by shifting a first original origin of the recorded first spatially-heterodyned hologram including spatial heterodyne fringes in Fourier space to sit on top of a spatial-heterodyne carrier frequency defined as a first angle between a first reference beam and a first object beam; applying a first digital filter to cut off signals around the first original origin and performing an inverse Fourier transform on the result; Fourier analyzing the recorded second spatially-heterodyned hologram by shifting a second original origin of the recorded second spatially-heterodyned hologram including spatial heterodyne fringes in Fourier space to sit on top of a spatial-heterodyne carrier frequency defined as a second angle between a second reference beam and a second object beam; and applying a second digital filter to cut off signals around the second original origin and performing an inverse Fourier transform on the result, wherein digitally recording the first spatially-heterodyned hologram is completed before digitally recording the second spatially-heterodyned hologram and a single digital image includes both the first spatially-heterodyned hologram and the second spatially-heterodyned hologram.

Spatial dependence of extreme rainfall

Science.gov (United States)

Radi, Noor Fadhilah Ahmad; Zakaria, Roslinazairimah; Satari, Siti Zanariah; Azman, Muhammad Az-zuhri

2017-05-01

This study aims to model the spatial extreme daily rainfall process using the max-stable model. The max-stable model is used to capture the dependence structure of spatial properties of extreme rainfall. Three models from max-stable are considered namely Smith, Schlather and Brown-Resnick models. The methods are applied on 12 selected rainfall stations in Kelantan, Malaysia. Most of the extreme rainfall data occur during wet season from October to December of 1971 to 2012. This period is chosen to assure the available data is enough to satisfy the assumption of stationarity. The dependence parameters including the range and smoothness, are estimated using composite likelihood approach. Then, the bootstrap approach is applied to generate synthetic extreme rainfall data for all models using the estimated dependence parameters. The goodness of fit between the observed extreme rainfall and the synthetic data is assessed using the composite likelihood information criterion (CLIC). Results show that Schlather model is the best followed by Brown-Resnick and Smith models based on the smallest CLIC's value. Thus, the max-stable model is suitable to be used to model extreme rainfall in Kelantan. The study on spatial dependence in extreme rainfall modelling is important to reduce the uncertainties of the point estimates for the tail index. If the spatial dependency is estimated individually, the uncertainties will be large. Furthermore, in the case of joint return level is of interest, taking into accounts the spatial dependence properties will improve the estimation process.

Early Warning Signals of Ecological Transitions: Methods for Spatial Patterns

Science.gov (United States)

Brock, William A.; Carpenter, Stephen R.; Ellison, Aaron M.; Livina, Valerie N.; Seekell, David A.; Scheffer, Marten; van Nes, Egbert H.; Dakos, Vasilis

2014-01-01

A number of ecosystems can exhibit abrupt shifts between alternative stable states. Because of their important ecological and economic consequences, recent research has focused on devising early warning signals for anticipating such abrupt ecological transitions. In particular, theoretical studies show that changes in spatial characteristics of the system could provide early warnings of approaching transitions. However, the empirical validation of these indicators lag behind their theoretical developments. Here, we summarize a range of currently available spatial early warning signals, suggest potential null models to interpret their trends, and apply them to three simulated spatial data sets of systems undergoing an abrupt transition. In addition to providing a step-by-step methodology for applying these signals to spatial data sets, we propose a statistical toolbox that may be used to help detect approaching transitions in a wide range of spatial data. We hope that our methodology together with the computer codes will stimulate the application and testing of spatial early warning signals on real spatial data. PMID:24658137

Geo-Spatial Support for Assessment of Anthropic Impact on Biodiversity

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Marco Piragnolo

2014-04-01

Full Text Available This paper discusses a methodology where geo-spatial analysis tools are used to quantify risk derived from anthropic activities on habitats and species. The method has been developed with a focus on simplification and the quality of standard procedures set on flora and fauna protected by the European Directives. In this study case, the DPSIR (Drivers, Pressures, State, Impacts, Responses is applied using spatial procedures in a geographical information system (GIS framework. This approach can be inserted in a multidimensional space as the analysis is applied to each threat, pressure and activity and also to each habitat and species, at the spatial and temporal scale. Threats, pressures and activities, stress and indicators can be managed by means of a geo-database and analyzed using spatial analysis functions in a tested GIS workflow environment. The method applies a matrix with risk values, and the final product is a geo-spatial representation of impact indicators, which can be used as a support for decision-makers at various levels (regional, national and European.

Spatial correlation of action potential duration and diastolic dysfunction in transgenic and drug-induced LQT2 rabbits.

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Odening, Katja E; Jung, Bernd A; Lang, Corinna N; Cabrera Lozoya, Rocio; Ziupa, David; Menza, Marius; Relan, Jatin; Franke, Gerlind; Perez Feliz, Stefanie; Koren, Gideon; Zehender, Manfred; Bode, Christoph; Brunner, Michael; Sermesant, Maxime; Föll, Daniela

2013-10-01

Enhanced dispersion of action potential duration (APD) is a major contributor to long QT syndrome (LQTS)-related arrhythmias. To investigate spatial correlations of regional heterogeneities in cardiac repolarization and mechanical function in LQTS. Female transgenic LQTS type 2 (LQT2; n = 11) and wild-type littermate control (LMC) rabbits (n = 9 without E4031 and n = 10 with E4031) were subjected to phase contrast magnetic resonance imaging to assess regional myocardial velocities. In the same rabbits' hearts, monophasic APDs were assessed in corresponding segments. In LQT2 and E4031-treated rabbits, APD was longer in all left ventricular segments (P < .01) and APD dispersion was greater than that in LMC rabbits (P < .01). In diastole, peak radial velocities (Vr) were reduced in LQT2 and E4031-treated compared to LMC rabbits in LV base and mid (LQT2: -3.36 ± 0.4 cm/s, P < .01; E4031-treated: -3.24 ± 0.6 cm/s, P < .0001; LMC: -4.42 ± 0.5 cm/s), indicating an impaired diastolic function. Regionally heterogeneous diastolic Vr correlated with APD (LQT2: correlation coefficient [CC] 0.38, P = .01; E4031-treated: CC 0.42, P < .05). Time-to-diastolic peak Vr were prolonged in LQT2 rabbits (LQT2: 196.8 ± 2.9 ms, P < .001; E4031-treated: 199.5 ± 2.2 ms, P < .0001, LMC 183.1 ± 1.5), indicating a prolonged contraction duration. Moreover, in transgenic LQT2 rabbits, diastolic time-to-diastolic peak Vr correlated with APD (CC 0.47, P = .001). In systole, peak Vr were reduced in LQT2 and E4031-treated rabbits (P < .01) but longitudinal velocities or ejection fraction did not differ. Finally, random forest machine learning algorithms enabled a differentiation between LQT2, E4031-treated, and LMC rabbits solely based on "mechanical" magnetic resonance imaging data. The prolongation of APD led to impaired diastolic and systolic function in transgenic and drug-induced LQT2 rabbits. APD correlated with regional diastolic dysfunction, indicating that LQTS is not purely an

Optimization of spatial light distribution through genetic algorithms for vision systems applied to quality control

International Nuclear Information System (INIS)

Castellini, P; Cecchini, S; Stroppa, L; Paone, N

2015-01-01

The paper presents an adaptive illumination system for image quality enhancement in vision-based quality control systems. In particular, a spatial modulation of illumination intensity is proposed in order to improve image quality, thus compensating for different target scattering properties, local reflections and fluctuations of ambient light. The desired spatial modulation of illumination is obtained by a digital light projector, used to illuminate the scene with an arbitrary spatial distribution of light intensity, designed to improve feature extraction in the region of interest. The spatial distribution of illumination is optimized by running a genetic algorithm. An image quality estimator is used to close the feedback loop and to stop iterations once the desired image quality is reached. The technique proves particularly valuable for optimizing the spatial illumination distribution in the region of interest, with the remarkable capability of the genetic algorithm to adapt the light distribution to very different target reflectivity and ambient conditions. The final objective of the proposed technique is the improvement of the matching score in the recognition of parts through matching algorithms, hence of the diagnosis of machine vision-based quality inspections. The procedure has been validated both by a numerical model and by an experimental test, referring to a significant problem of quality control for the washing machine manufacturing industry: the recognition of a metallic clamp. Its applicability to other domains is also presented, specifically for the visual inspection of shoes with retro-reflective tape and T-shirts with paillettes. (paper)

Spatial Economics: The Evolution of Approaches and Methodology

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Minakir P. A.

2010-06-01

Full Text Available The evolution of theoretical principles and approaches to the study of spatial organization of the economy is set forth. The changes in the content of the category «economic region» are analyzed. A comparative assessment is given of theoretical approaches to studying spatial aspects of the economy. The limited character of theoretical and applied regional economic tools in studying spatial organization and spatial interactions between economic agents of the modern economy is shown

A GIS-Based Evaluation of the Effectiveness and Spatial Coverage of Public Transport Networks in Tourist Destinations

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Antoni Domènech

2017-03-01

Full Text Available This article develops a methodology for evaluating the effectiveness and spatial coverage of public transport in tourist cities. The proposed methodology is applied and validated in Cambrils municipality, in the central part of the Costa Daurada in Catalonia, a coastal destination characterised by the concentration of tourism flows during summer. The application of GIS spatial analysis tools allows for the development of a system of territorial indicators that spatially correlate the public transport network and the distribution of the population. The main novelty of our work is that this analysis not only includes the registered resident population, but also incorporates the population that temporarily inhabits the municipality (tourists. The results of the study firstly permit the detection of unequal spatial accessibility and coverage in terms of public transport in the municipality, with significant differences between central neighbourhoods and peripheral urban areas of lower population density. Secondly, they allow observation of how the degree of public transport coverage differs significantly in areas with a higher concentration of tourist accommodation establishments.

Detecting spatial patterns with the cumulant function – Part 2: An application to El Niño

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P. Yiou

2008-02-01

Full Text Available The spatial coherence of a measured variable (e.g. temperature or pressure is often studied to determine the regions of high variability or to find teleconnections, i.e. correlations between specific regions. While usual methods to find spatial patterns, such as Principal Components Analysis (PCA, are constrained by linear symmetries, the dependence of variables such as temperature or pressure at different locations is generally nonlinear. In particular, large deviations from the sample mean are expected to be strongly affected by such nonlinearities. Here we apply a newly developed nonlinear technique (Maxima of Cumulant Function, MCF for detection of typical spatial patterns that largely deviate from the mean. In order to test the technique and to introduce the methodology, we focus on the El Niño/Southern Oscillation and its spatial patterns. We find nonsymmetric temperature patterns corresponding to El Niño and La Niña, and we compare the results of MCF with other techniques, such as the symmetric solutions of PCA, and the nonsymmetric solutions of Nonlinear PCA (NLPCA. We found that MCF solutions are more reliable than the NLPCA fits, and can capture mixtures of principal components. Finally, we apply Extreme Value Theory on the temporal variations extracted from our methodology. We find that the tails of the distribution of extreme temperatures during La Niña episodes is bounded, while the tail during El Niños is less likely to be bounded. This implies that the mean spatial patterns of the two phases are asymmetric, as well as the behaviour of their extremes.

Understanding the amplitudes of noise correlation measurements

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Tsai, Victor C.

2011-01-01

Cross correlation of ambient seismic noise is known to result in time series from which station-station travel-time measurements can be made. Part of the reason that these cross-correlation travel-time measurements are reliable is that there exists a theoretical framework that quantifies how these travel times depend on the features of the ambient noise. However, corresponding theoretical results do not currently exist to describe how the amplitudes of the cross correlation depend on such features. For example, currently it is not possible to take a given distribution of noise sources and calculate the cross correlation amplitudes one would expect from such a distribution. Here, we provide a ray-theoretical framework for calculating cross correlations. This framework differs from previous work in that it explicitly accounts for attenuation as well as the spatial distribution of sources and therefore can address the issue of quantifying amplitudes in noise correlation measurements. After introducing the general framework, we apply it to two specific problems. First, we show that we can quantify the amplitudes of coherency measurements, and find that the decay of coherency with station-station spacing depends crucially on the distribution of noise sources. We suggest that researchers interested in performing attenuation measurements from noise coherency should first determine how the dominant sources of noise are distributed. Second, we show that we can quantify the signal-to-noise ratio of noise correlations more precisely than previous work, and that these signal-to-noise ratios can be estimated for given situations prior to the deployment of seismometers. It is expected that there are applications of the theoretical framework beyond the two specific cases considered, but these applications await future work.

Spatial network surrogates for disentangling complex system structure from spatial embedding of nodes

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Wiedermann, Marc; Donges, Jonathan F.; Kurths, Jürgen; Donner, Reik V.

2016-04-01

Networks with nodes embedded in a metric space have gained increasing interest in recent years. The effects of spatial embedding on the networks' structural characteristics, however, are rarely taken into account when studying their macroscopic properties. Here, we propose a hierarchy of null models to generate random surrogates from a given spatially embedded network that can preserve certain global and local statistics associated with the nodes' embedding in a metric space. Comparing the original network's and the resulting surrogates' global characteristics allows one to quantify to what extent these characteristics are already predetermined by the spatial embedding of the nodes and links. We apply our framework to various real-world spatial networks and show that the proposed models capture macroscopic properties of the networks under study much better than standard random network models that do not account for the nodes' spatial embedding. Depending on the actual performance of the proposed null models, the networks are categorized into different classes. Since many real-world complex networks are in fact spatial networks, the proposed approach is relevant for disentangling the underlying complex system structure from spatial embedding of nodes in many fields, ranging from social systems over infrastructure and neurophysiology to climatology.

Spatial Domain Adaptive Control of Nonlinear Rotary Systems Subject to Spatially Periodic Disturbances

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Yen-Hsiu Yang

2012-01-01

Full Text Available We propose a generic spatial domain control scheme for a class of nonlinear rotary systems of variable speeds and subject to spatially periodic disturbances. The nonlinear model of the rotary system in time domain is transformed into one in spatial domain employing a coordinate transformation with respect to angular displacement. Under the circumstances that measurement of the system states is not available, a nonlinear state observer is established for providing the estimated states. A two-degree-of-freedom spatial domain control configuration is then proposed to stabilize the system and improve the tracking performance. The first control module applies adaptive backstepping with projected parametric update and concentrates on robust stabilization of the closed-loop system. The second control module introduces an internal model of the periodic disturbances cascaded with a loop-shaping filter, which not only further reduces the tracking error but also improves parametric adaptation. The overall spatial domain output feedback adaptive control system is robust to model uncertainties and state estimated error and capable of rejecting spatially periodic disturbances under varying system speeds. Stability proof of the overall system is given. A design example with simulation demonstrates the applicability of the proposed design.

Concept of spatial channel theory applied to reactor shielding analysis

International Nuclear Information System (INIS)

Williams, M.L.; Engle, W.W. Jr.