Interannual Variability of OLR as Observed by AIRS and CERES

NASA Technical Reports Server (NTRS)

Susskind, Joel; Molnar, Gyula; Iredell, Lena; Loeb, Norman G.

2012-01-01

This paper compares spatial anomaly time series of OLR (Outgoing Longwave Radiation) and OLR(sub CLR) (Clear Sky OLR) as determined using observations from CERES Terra and AIRS over the time period September 2002 through June 2011. Both AIRS and CERES show a significant decrease in global mean and tropical mean OLR over this time period. We find excellent agreement of the anomaly time-series of the two OLR data sets in almost every detail, down to 1 deg X 1 deg spatial grid point level. The extremely close agreement of OLR anomaly time series derived from observations by two different instruments implies that both sets of results must be highly stable. This agreement also validates to some extent the anomaly time series of the AIRS derived products used in the computation of the AIRS OLR product. The paper also examines the correlations of anomaly time series of AIRS and CERES OLR, on different spatial scales, as well as those of other AIRS derived products, with that of the NOAA Sea Surface Temperature (SST) product averaged over the NOAA Nino-4 spatial region. We refer to these SST anomalies as the El Nino Index. Large spatially coherent positive and negative correlations of OLR anomaly time series with that of the El Nino Index are found in different spatial regions. Anomalies of global mean, and especially tropical mean, OLR are highly positively correlated with the El Nino Index. These correlations explain that the recent global and tropical mean decreases in OLR over the period September 2002 through June 2011, as observed by both AIRS and CERES, are primarily the result of a transition from an El Nino condition at the beginning of the data record to La Nina conditions toward the end of the data period. We show that the close correlation of global mean, and especially tropical mean, OLR anomalies with the El Nino Index can be well accounted for by temporal changes of OLR within two spatial regions which lie outside the NOAA Nino-4 region, in which anomalies of cloud cover and mid-tropospheric water vapor are both highly negatively correlated with the El Nino Index. Agreement of the AIRS and CERES OLR(sub CLR) anomaly time series is less good, which may be a result of the large sampling differences in the ensemble of cases included in each OLR(sub CLR) data set.

Regional nutrient trends in streams and rivers of the United States, 1993-2003

USGS Publications Warehouse

Sprague, Lori A.; Lorenz, David L.

2009-01-01

Trends in flow-adjusted concentrations (indicators of anthropogenic changes) and observed concentrations (indicators of natural and anthropogenic changes) of total phosphorus and total nitrogen from 1993 to 2003 were evaluated in the eastern, central, and western United States by adapting the Regional Kendall trend test to account for seasonality and spatial correlation. The only significant regional trend was an increase in flow-adjusted concentrations of total phosphorus in the central United States, which corresponded to increases in phosphorus inputs from fertilizer in the region, particularly west of the Mississippi River. A similar upward regional trend in observed total phosphorus concentrations in the central United States was not found, likely because precipitation and runoff decreased during drought conditions in the region, offsetting the increased source loading on the land surface. A greater number of regional trends would have been significant if spatial correlation had been disregarded, indicating the importance of spatial correlation modifications in regional trend assessments when sites are not spatially independent.

Capturing spatial heterogeneity of soil organic carbon under changing climate

NASA Astrophysics Data System (ADS)

Mishra, U.; Fan, Z.; Jastrow, J. D.; Matamala, R.; Vitharana, U.

2015-12-01

The spatial heterogeneity of the land surface affects water, energy, and greenhouse gas exchanges with the atmosphere. Designing observation networks that capture land surface spatial heterogeneity is a critical scientific challenge. Here, we present a geospatial approach to capture the existing spatial heterogeneity of soil organic carbon (SOC) stocks across Alaska, USA. We used the standard deviation of 556 georeferenced SOC profiles previously compiled in Mishra and Riley (2015, Biogeosciences, 12:3993-4004) to calculate the number of observations that would be needed to reliably estimate Alaskan SOC stocks. This analysis indicated that 906 randomly distributed observation sites would be needed to quantify the mean value of SOC stocks across Alaska at a confidence interval of ± 5 kg m-2. We then used soil-forming factors (climate, topography, land cover types, surficial geology) to identify the locations of appropriately distributed observation sites by using the conditioned Latin hypercube sampling approach. Spatial correlation and variogram analyses demonstrated that the spatial structures of soil-forming factors were adequately represented by these 906 sites. Using the spatial correlation length of existing SOC observations, we identified 484 new observation sites would be needed to provide the best estimate of the present status of SOC stocks in Alaska. We then used average decadal projections (2020-2099) of precipitation, temperature, and length of growing season for three representative concentration pathway (RCP 4.5, 6.0, and 8.5) scenarios of the Intergovernmental Panel on Climate Change to investigate whether the location of identified observation sites will shift/change under future climate. Our results showed 12-41 additional observation sites (depending on emission scenarios) will be required to capture the impact of projected climatic conditions by 2100 on the spatial heterogeneity of Alaskan SOC stocks. Our results represent an ideal distribution of observation sites across Alaska that captures the land surface spatial heterogeneity and can be used in efforts to quantify SOC stocks, monitor greenhouse gas emissions, and benchmark Earth System Model results.

Uncertainty Analysis of Downscaled CMIP5 Precipitation Data for Louisiana, USA

NASA Astrophysics Data System (ADS)

Sumi, S. J.; Tamanna, M.; Chivoiu, B.; Habib, E. H.

2014-12-01

The downscaled CMIP3 and CMIP5 Climate and Hydrology Projections dataset contains fine spatial resolution translations of climate projections over the contiguous United States developed using two downscaling techniques (monthly Bias Correction Spatial Disaggregation (BCSD) and daily Bias Correction Constructed Analogs (BCCA)). The objective of this study is to assess the uncertainty of the CMIP5 downscaled general circulation models (GCM). We performed an analysis of the daily, monthly, seasonal and annual variability of precipitation downloaded from the Downscaled CMIP3 and CMIP5 Climate and Hydrology Projections website for the state of Louisiana, USA at 0.125° x 0.125° resolution. A data set of daily gridded observations of precipitation of a rectangular boundary covering Louisiana is used to assess the validity of 21 downscaled GCMs for the 1950-1999 period. The following statistics are computed using the CMIP5 observed dataset with respect to the 21 models: the correlation coefficient, the bias, the normalized bias, the mean absolute error (MAE), the mean absolute percentage error (MAPE), and the root mean square error (RMSE). A measure of variability simulated by each model is computed as the ratio of its standard deviation, in both space and time, to the corresponding standard deviation of the observation. The correlation and MAPE statistics are also computed for each of the nine climate divisions of Louisiana. Some of the patterns that we observed are: 1) Average annual precipitation rate shows similar spatial distribution for all the models within a range of 3.27 to 4.75 mm/day from Northwest to Southeast. 2) Standard deviation of summer (JJA) precipitation (mm/day) for the models maintains lower value than the observation whereas they have similar spatial patterns and range of values in winter (NDJ). 3) Correlation coefficients of annual precipitation of models against observation have a range of -0.48 to 0.36 with variable spatial distribution by model. 4) Most of the models show negative correlation coefficients in summer and positive in winter. 5) MAE shows similar spatial distribution for all the models within a range of 5.20 to 7.43 mm/day from Northwest to Southeast of Louisiana. 6) Highest values of correlation coefficients are found at seasonal scale within a range of 0.36 to 0.46.

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

PubMed

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.

Analysis of suicide mortality in Brazil: spatial distribution and socioeconomic context.

PubMed

Dantas, Ana P; Azevedo, Ulicélia N de; Nunes, Aryelly D; Amador, Ana E; Marques, Marilane V; Barbosa, Isabelle R

2018-01-01

To perform a spatial analysis of suicide mortality and its correlation with socioeconomic indicators in Brazilian municipalities. This is an ecological study with Brazilian municipalities as a unit of analysis. Data on deaths from suicide and contextual variables were analyzed. The spatial distribution, intensity and significance of the clusters were analyzed with the global Moran index, MoranMap and local indicators of spatial association (LISA), seeking to identify patterns through geostatistical analysis. A total of 50,664 deaths from suicide were registered in Brazil between 2010 and 2014. The average suicide mortality rate in Brazil was 5.23/100,000 population. The Brazilian municipalities presenting the highest rates were Taipas do Tocantins, state of Tocantins (79.68 deaths per 100,000 population), Itaporã, state of Mato Grosso do Sul (75.15 deaths per 100,000 population), Mampituba, state of Rio Grande do Sul (52.98 deaths per 100,000 population), Paranhos, state of Mato Grosso do Sul (52.41 deaths per 100,000 population), and Monjolos, state of Minas Gerais (52.08 deaths per 100,000 population). Although weak spatial autocorrelation was observed for suicide mortality (I = 0.2608), there was a formation of clusters in the South. In the bivariate spatial and classical analysis, no correlation was observed between suicide mortality and contextual variables. Suicide mortality in Brazil presents a weak spatial correlation and low or no spatial relationship with socioeconomic factors.

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

PubMed Central

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

Interannual Variability of OLR as Observed by AIRS and CERES

NASA Technical Reports Server (NTRS)

Susskind, Joel; Molnar, Gyula I.; Iredell, Lena F.; Loeb, Norman G.

2012-01-01

The paper examines spatial anomaly time series of Outgoing Longwave Radiation (OLR) and Clear Sky OLR (OLR(sub CLR)) as determined using observations from CERES Terra and AIRS over the time period September 2002 through June 2011. We find excellent agreement of the two OLR data sets in almost every detail down to the x11deg spatial grid point level. The extremely close agreement of OLR anomaly time series derived from observations by two different instruments implies high stability of both sets of results. Anomalies of global mean, and especially tropical mean, OLR are shown to be strongly correlated with an El Nino index. These correlations explain that the recent global and tropical mean decreases in OLR over the time period studied are primarily the result of a transition from an El Nino condition at the beginning of the data record to La Nina conditions toward the end of the data period. We show that the close correlation of mean OLR anomalies with the El Nino Index can be well accounted for by temporal changes of OLR within two spatial regions, one to the east of, and one to the west of, the NOAA Nino-4 region. Anomalies of OLR in these two spatial regions are both strongly correlated with the El Nino Index as a result of the strong anti-correlation of anomalies of cloud cover and mid-tropospheric water vapor in these two regions with the El Nino Index.

CRISM/HiRISE Correlative Spectroscopy

NASA Astrophysics Data System (ADS)

Seelos, F. P.; Murchie, S. L.; McGovern, A.; Milazzo, M. P.; Herkenhoff, K. E.

2011-12-01

The Mars Reconnaissance Orbiter (MRO) Compact Reconnaissance Imaging Spectrometer for Mars (CRISM) and High Resolution Imaging Science Experiment (HiRISE) are complementary investigations with high spectral resolution and broad wavelength coverage (CRISM ~20 m/pxl; ~400 - 4000 nm, 6.55 nm sampling) and high spatial resolution with broadband color capability (HiRISE ~25 cm/pxl; ~500, 700, 900 nm band centers, ~200-300 nm FWHM). Over the course of the MRO mission it has become apparent that spectral variations in the IR detected by CRISM (~1000 nm - 4000 nm) sometimes correlate spatially with visible and near infrared 3-band color variations observed by HiRISE. We have developed a data processing procedure that establishes a numerical mapping between HiRISE color and CRISM VNIR and IR spectral data and provides a statistical evaluation of the uncertainty in the mapping, with the objective of extrapolating CRISM-inferred mineralogy to the HiRISE spatial scale. The MRO mission profile, spacecraft capabilities, and science planning process emphasize coordinated observations - the simultaneous observation of a common target by multiple instruments. The commonalities of CRISM/HiRISE coordinated observations present a unique opportunity for tandem data analysis. Recent advances in the systematic processing of CRISM hyperspectral targeted observations account for gimbal-induced photometric variations and transform the data to a synthetic nadir acquisition geometry. The CRISM VNIR (~400 nm - 1000 nm) data can then be convolved to the HiRISE Infrared, Red, and Blue/Green (IRB) response functions to generate a compatible CRISM IRB product. Statistical evaluation of the CRISM/HiRISE spatial overlap region establishes a quantitative link between the data sets. IRB spectral similarity mapping for each HiRISE color spatial pixel with respect to the CRISM IRB product allows a given HiRISE pixel to be populated with information derived from the coordinated CRISM observation, including correlative VNIR or IR spectral data, spectral summary parameters, or browse products. To properly characterize the quality and fidelity of the IRB correlation, a series of ancillary information bands that record the numerical behavior of the procedure are also generated. Prototype CRISM/HiRISE correlative data products have been generated for a small number of coordinated observation pairs. The resulting products have the potential to support integrated spectral and morphological mapping at sub-meter spatial scales. Such data products would be invaluable for strategic and tactical science operations on landed missions, and would allow observations from a landed platform to be evaluated in a CRISM-based spectral and mineralogical context.

Statistics of natural scenes and cortical color processing.

PubMed

Cecchi, Guillermo A; Rao, A Ravishankar; Xiao, Youping; Kaplan, Ehud

2010-09-01

We investigate the spatial correlations of orientation and color information in natural images. We find that the correlation of orientation information falls off rapidly with increasing distance, while color information is more highly correlated over longer distances. We show that orientation and color information are statistically independent in natural images and that the spatial correlation of jointly encoded orientation and color information decays faster than that of color alone. Our findings suggest that: (a) orientation and color information should be processed in separate channels and (b) the organization of cortical color and orientation selectivity at low spatial frequencies is a reflection of the cortical adaptation to the statistical structure of the visual world. These findings are in agreement with biological observations, as form and color are thought to be represented by different classes of neurons in the primary visual cortex, and the receptive fields of color-selective neurons are larger than those of orientation-selective neurons. The agreement between our findings and biological observations supports the ecological theory of perception.

A Twin Study of Spatial and Non-Spatial Delayed Response Performance in Middle Age

ERIC Educational Resources Information Center

Kremen, William S.; Mai, Tuan; Panizzon, Matthew S.; Franz, Carol E.; Blankfeld, Howard M.; Xian, Hong; Eisen, Seth A.; Tsuang, Ming T.; Lyons, Michael J.

2011-01-01

Delayed alternation and object alternation are classic spatial and non-spatial delayed response tasks. We tested 632 middle-aged male veteran twins on variants of these tasks in order to compare test difficulty, measure their inter-correlation, test order effects, and estimate heritabilities (proportion of observed variance due to genetic…

Prediction of Spatiotemporal Patterns of Neural Activity from Pairwise Correlations

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

Marre, O.; El Boustani, S.; Fregnac, Y.

We designed a model-based analysis to predict the occurrence of population patterns in distributed spiking activity. Using a maximum entropy principle with a Markovian assumption, we obtain a model that accounts for both spatial and temporal pairwise correlations among neurons. This model is tested on data generated with a Glauber spin-glass system and is shown to correctly predict the occurrence probabilities of spatiotemporal patterns significantly better than Ising models only based on spatial correlations. This increase of predictability was also observed on experimental data recorded in parietal cortex during slow-wave sleep. This approach can also be used to generate surrogatesmore » that reproduce the spatial and temporal correlations of a given data set.« less

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

NASA Astrophysics Data System (ADS)

Gay-Balmaz, François; Holm, Darryl D.

2018-01-01

Inspired by spatiotemporal observations from satellites of the trajectories of objects drifting near the surface of the ocean in the National Oceanic and Atmospheric Administration's "Global Drifter Program", this paper develops data-driven stochastic models of geophysical fluid dynamics (GFD) with non-stationary spatial correlations representing the dynamical behaviour of oceanic currents. Three models are considered. Model 1 from Holm (Proc R Soc A 471:20140963, 2015) is reviewed, in which the spatial correlations are time independent. Two new models, called Model 2 and Model 3, introduce two different symmetry breaking mechanisms by which the spatial correlations may be advected by the flow. These models are derived using reduction by symmetry of stochastic variational principles, leading to stochastic Hamiltonian systems, whose momentum maps, conservation laws and Lie-Poisson bracket structures are used in developing the new stochastic Hamiltonian models of GFD.

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

NASA Astrophysics Data System (ADS)

Gay-Balmaz, François; Holm, Darryl D.

2018-06-01

Inspired by spatiotemporal observations from satellites of the trajectories of objects drifting near the surface of the ocean in the National Oceanic and Atmospheric Administration's "Global Drifter Program", this paper develops data-driven stochastic models of geophysical fluid dynamics (GFD) with non-stationary spatial correlations representing the dynamical behaviour of oceanic currents. Three models are considered. Model 1 from Holm (Proc R Soc A 471:20140963, 2015) is reviewed, in which the spatial correlations are time independent. Two new models, called Model 2 and Model 3, introduce two different symmetry breaking mechanisms by which the spatial correlations may be advected by the flow. These models are derived using reduction by symmetry of stochastic variational principles, leading to stochastic Hamiltonian systems, whose momentum maps, conservation laws and Lie-Poisson bracket structures are used in developing the new stochastic Hamiltonian models of GFD.

Approximate degeneracy of J =1 spatial correlators in high temperature QCD

NASA Astrophysics Data System (ADS)

Rohrhofer, C.; Aoki, Y.; Cossu, G.; Fukaya, H.; Glozman, L. Ya.; Hashimoto, S.; Lang, C. B.; Prelovsek, S.

2017-11-01

We study spatial isovector meson correlators in Nf=2 QCD with dynamical domain-wall fermions on 3 23×8 lattices at temperatures T =220 - 380 MeV . We measure the correlators of spin-one (J =1 ) operators including vector, axial-vector, tensor and axial-tensor. Restoration of chiral U (1 )A and S U (2 )L×S U (2 )R symmetries of QCD implies degeneracies in vector-axial-vector (S U (2 )L×S U (2 )R) and tensor-axial-tensor (U (1 )A) pairs, which are indeed observed at temperatures above Tc. Moreover, we observe an approximate degeneracy of all J =1 correlators with increasing temperature. This approximate degeneracy suggests emergent S U (2 )CS and S U (4 ) symmetries at high temperatures, that mix left- and right-handed quarks.

Correlation of Spatially Filtered Dynamic Speckles in Distance Measurement Application

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

Semenov, Dmitry V.; Nippolainen, Ervin; Kamshilin, Alexei A.

2008-04-15

In this paper statistical properties of spatially filtered dynamic speckles are considered. This phenomenon was not sufficiently studied yet while spatial filtering is an important instrument for speckles velocity measurements. In case of spatial filtering speckle velocity information is derived from the modulation frequency of filtered light power which is measured by photodetector. Typical photodetector output is represented by a narrow-band random noise signal which includes non-informative intervals. Therefore more or less precious frequency measurement requires averaging. In its turn averaging implies uncorrelated samples. However, conducting research we found that correlation is typical property not only of dynamic speckle patternsmore » but also of spatially filtered speckles. Using spatial filtering the correlation is observed as a response of measurements provided to the same part of the object surface or in case of simultaneously using several adjacent photodetectors. Found correlations can not be explained using just properties of unfiltered dynamic speckles. As we demonstrate the subject of this paper is important not only from pure theoretical point but also from the point of applied speckle metrology. E.g. using single spatial filter and an array of photodetector can greatly improve accuracy of speckle velocity measurements.« less

Percolation of spatially constrained Erdős-Rényi networks with degree correlations.

PubMed

Schmeltzer, C; Soriano, J; Sokolov, I M; Rüdiger, S

2014-01-01

Motivated by experiments on activity in neuronal cultures [ J. Soriano, M. Rodríguez Martínez, T. Tlusty and E. Moses Proc. Natl. Acad. Sci. 105 13758 (2008)], we investigate the percolation transition and critical exponents of spatially embedded Erdős-Rényi networks with degree correlations. In our model networks, nodes are randomly distributed in a two-dimensional spatial domain, and the connection probability depends on Euclidian link length by a power law as well as on the degrees of linked nodes. Generally, spatial constraints lead to higher percolation thresholds in the sense that more links are needed to achieve global connectivity. However, degree correlations favor or do not favor percolation depending on the connectivity rules. We employ two construction methods to introduce degree correlations. In the first one, nodes stay homogeneously distributed and are connected via a distance- and degree-dependent probability. We observe that assortativity in the resulting network leads to a decrease of the percolation threshold. In the second construction methods, nodes are first spatially segregated depending on their degree and afterwards connected with a distance-dependent probability. In this segregated model, we find a threshold increase that accompanies the rising assortativity. Additionally, when the network is constructed in a disassortative way, we observe that this property has little effect on the percolation transition.

GIS-based spatial regression and prediction of water quality in river networks: A case study in Iowa

USGS Publications Warehouse

Yang, X.; Jin, W.

2010-01-01

Nonpoint source pollution is the leading cause of the U.S.'s water quality problems. One important component of nonpoint source pollution control is an understanding of what and how watershed-scale conditions influence ambient water quality. This paper investigated the use of spatial regression to evaluate the impacts of watershed characteristics on stream NO3NO2-N concentration in the Cedar River Watershed, Iowa. An Arc Hydro geodatabase was constructed to organize various datasets on the watershed. Spatial regression models were developed to evaluate the impacts of watershed characteristics on stream NO3NO2-N concentration and predict NO3NO2-N concentration at unmonitored locations. Unlike the traditional ordinary least square (OLS) method, the spatial regression method incorporates the potential spatial correlation among the observations in its coefficient estimation. Study results show that NO3NO2-N observations in the Cedar River Watershed are spatially correlated, and by ignoring the spatial correlation, the OLS method tends to over-estimate the impacts of watershed characteristics on stream NO3NO2-N concentration. In conjunction with kriging, the spatial regression method not only makes better stream NO3NO2-N concentration predictions than the OLS method, but also gives estimates of the uncertainty of the predictions, which provides useful information for optimizing the design of stream monitoring network. It is a promising tool for better managing and controlling nonpoint source pollution. ?? 2010 Elsevier Ltd.

Blob-hole correlation model for edge turbulence and comparisons with NSTX gas puff imaging data

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

Myra, J. R.; Zweben, S. J.; Russell, D. A.

We report that gas puff imaging (GPI) observations made in NSTX [Zweben S J, et al., 2017 Phys. Plasmas 24 102509] have revealed two-point spatial correlations of edge and scrape-off layer turbulence in the plane perpendicular to the magnetic field. A common feature is the occurrence of dipole-like patterns with significant regions of negative correlation. In this paper, we explore the possibility that these dipole patterns may be due to blob-hole pairs. Statistical methods are applied to determine the two-point spatial correlation that results from a model of blob-hole pair formation. It is shown that the model produces dipole correlationmore » patterns that are qualitatively similar to the GPI data in several respects. Effects of the reference location (confined surfaces or scrape-off layer), a superimposed random background, hole velocity and lifetime, and background sheared flows are explored and discussed with respect to experimental observations. Additional analysis of the experimental GPI dataset is performed to further test this blob-hole correlation model. A time delay two-point spatial correlation study did not reveal inward propagation of the negative correlation structures that were postulated to correspond to holes in the data nor did it suggest that the negative correlation structures are due to neutral shadowing. However, tracking of the highest and lowest values (extrema) of the normalized GPI fluctuations shows strong evidence for mean inward propagation of minima and outward propagation of maxima, in qualitative agreement with theoretical expectations. Finally, other properties of the experimentally observed extrema are discussed.« less

Blob-hole correlation model for edge turbulence and comparisons with NSTX gas puff imaging data

DOE PAGES

Myra, J. R.; Zweben, S. J.; Russell, D. A.

2018-05-15

We report that gas puff imaging (GPI) observations made in NSTX [Zweben S J, et al., 2017 Phys. Plasmas 24 102509] have revealed two-point spatial correlations of edge and scrape-off layer turbulence in the plane perpendicular to the magnetic field. A common feature is the occurrence of dipole-like patterns with significant regions of negative correlation. In this paper, we explore the possibility that these dipole patterns may be due to blob-hole pairs. Statistical methods are applied to determine the two-point spatial correlation that results from a model of blob-hole pair formation. It is shown that the model produces dipole correlationmore » patterns that are qualitatively similar to the GPI data in several respects. Effects of the reference location (confined surfaces or scrape-off layer), a superimposed random background, hole velocity and lifetime, and background sheared flows are explored and discussed with respect to experimental observations. Additional analysis of the experimental GPI dataset is performed to further test this blob-hole correlation model. A time delay two-point spatial correlation study did not reveal inward propagation of the negative correlation structures that were postulated to correspond to holes in the data nor did it suggest that the negative correlation structures are due to neutral shadowing. However, tracking of the highest and lowest values (extrema) of the normalized GPI fluctuations shows strong evidence for mean inward propagation of minima and outward propagation of maxima, in qualitative agreement with theoretical expectations. Finally, other properties of the experimentally observed extrema are discussed.« less

Observations and statistical simulations of a proposed solar cycle/QBO/weather relationship

NASA Technical Reports Server (NTRS)

Baldwin, Mark P.; Dunkerton, Timothy J.

1989-01-01

The 10.7-cm solar flux is observed to be highly correlated with North Pole stratospheric temperatures when partitioned according to the phase of the equatorial stratospheric winds (the quasi-biennial oscillation, or QBO). Calculations show that temperatures over most of the Northern Hemisphere are highly correlated or anticorrelated with North Pole temperatures. The observed spatial pattern of solar-cycle correlations at high latitudes is shown to be not unique to the solar cycle.

Spatial correlation of auroral zone geomagnetic variations

NASA Astrophysics Data System (ADS)

Jackel, B. J.; Davalos, A.

2016-12-01

Magnetic field perturbations in the auroral zone are produced by a combination of distant ionospheric and local ground induced currents. Spatial and temporal structure of these currents is scientifically interesting and can also have a significant influence on critical infrastructure.Ground-based magnetometer networks are an essential tool for studying these phenomena, with the existing complement of instruments in Canada providing extended local time coverage. In this study we examine the spatial correlation between magnetic field observations over a range of scale lengths. Principal component and canonical correlation analysis are used to quantify relationships between multiple sites. Results could be used to optimize network configurations, validate computational models, and improve methods for empirical interpolation.

Radon emanation from the moon - Spatial and temporal variability.

NASA Technical Reports Server (NTRS)

Gorenstein, P.; Golub, L.; Bjorkholm, P.

1973-01-01

Observations of Rn-222 and Po-210 on the lunar surface with the orbiting Apollo alpha particle spectrometer reveal a number of features in their spatial distribution and indicate the existence of time variations in lunar radon emission. Localized Rn-222 or Po-210 around the craters Aristarchus and Grimaldi and the edges of virtually all maria indicates time varying radon emission and suggests a correlation between alpha 'hot spots' and sites of transient optical events observed from the earth. In a gross sense, the slower variations of Rn-222 seem to correlate with the distribution of gamma activity.

Experimental observation of spatial quantum noise reduction below the standard quantum limit with bright twin beams of light

NASA Astrophysics Data System (ADS)

Kumar, Ashok; Nunley, Hayden; Marino, Alberto

2016-05-01

Quantum noise reduction (QNR) below the standard quantum limit (SQL) has been a subject of interest for the past two to three decades due to its wide range of applications in quantum metrology and quantum information processing. To date, most of the attention has focused on the study of QNR in the temporal domain. However, many areas in quantum optics, specifically in quantum imaging, could benefit from QNR not only in the temporal domain but also in the spatial domain. With the use of a high quantum efficiency electron multiplier charge coupled device (EMCCD) camera, we have observed spatial QNR below the SQL in bright narrowband twin light beams generated through a four-wave mixing (FWM) process in hot rubidium atoms. Owing to momentum conservation in this process, the twin beams are momentum correlated. This leads to spatial quantum correlations and spatial QNR. Our preliminary results show a spatial QNR of over 2 dB with respect to the SQL. Unlike previous results on spatial QNR with faint and broadband photon pairs from parametric down conversion (PDC), we demonstrate spatial QNR with spectrally and spatially narrowband bright light beams. The results obtained will be useful for atom light interaction based quantum protocols and quantum imaging. Work supported by the W.M. Keck Foundation.

Catching ghosts with a coarse net: use and abuse of spatial sampling data in detecting synchronization

PubMed Central

2017-01-01

Synchronization of population dynamics in different habitats is a frequently observed phenomenon. A common mathematical tool to reveal synchronization is the (cross)correlation coefficient between time courses of values of the population size of a given species where the population size is evaluated from spatial sampling data. The corresponding sampling net or grid is often coarse, i.e. it does not resolve all details of the spatial configuration, and the evaluation error—i.e. the difference between the true value of the population size and its estimated value—can be considerable. We show that this estimation error can make the value of the correlation coefficient very inaccurate or even irrelevant. We consider several population models to show that the value of the correlation coefficient calculated on a coarse sampling grid rarely exceeds 0.5, even if the true value is close to 1, so that the synchronization is effectively lost. We also observe ‘ghost synchronization’ when the correlation coefficient calculated on a coarse sampling grid is close to 1 but in reality the dynamics are not correlated. Finally, we suggest a simple test to check the sampling grid coarseness and hence to distinguish between the true and artifactual values of the correlation coefficient. PMID:28202589

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

Wang, Jiali; Swati, F. N. U.; Stein, Michael L.

Regional climate models (RCMs) are a standard tool for downscaling climate forecasts to finer spatial scales. The evaluation of RCMs against observational data is an important step in building confidence in the use of RCMs for future prediction. In addition to model performance in climatological means and marginal distributions, a model’s ability to capture spatio-temporal relationships is important. This study develops two approaches: (1) spatial correlation/variogram for a range of spatial lags, with total monthly precipitation and non-seasonal precipitation components used to assess the spatial variations of precipitation; and (2) spatio-temporal correlation for a wide range of distances, directions, andmore » time lags, with daily precipitation occurrence used to detect the dynamic features of precipitation. These measures of spatial and spatio-temporal dependence are applied to a high-resolution RCM run and to the National Center for Environmental Prediction (NCEP)-U.S. Department of Energy (DOE) AMIP II reanalysis data (NCEP-R2), which provides initial and lateral boundary conditions for the RCM. The RCM performs better than NCEP-R2 in capturing both the spatial variations of total and non-seasonal precipitation components and the spatio-temporal correlations of daily precipitation occurrences, which are related to dynamic behaviors of precipitating systems. The improvements are apparent not just at resolutions finer than that of NCEP-R2, but also when the RCM and observational data are aggregated to the resolution of NCEP-R2.« less

Spatial variability of the Black Sea surface temperature from high resolution modeling and satellite measurements

NASA Astrophysics Data System (ADS)

Mizyuk, Artem; Senderov, Maxim; Korotaev, Gennady

2016-04-01

Large number of numerical ocean models were implemented for the Black Sea basin during last two decades. They reproduce rather similar structure of synoptical variability of the circulation. Since 00-s numerical studies of the mesoscale structure are carried out using high performance computing (HPC). With the growing capacity of computing resources it is now possible to reconstruct the Black Sea currents with spatial resolution of several hundreds meters. However, how realistic these results can be? In the proposed study an attempt is made to understand which spatial scales are reproduced by ocean model in the Black Sea. Simulations are made using parallel version of NEMO (Nucleus for European Modelling of the Ocean). A two regional configurations with spatial resolutions 5 km and 2.5 km are described. Comparison of the SST from simulations with two spatial resolutions shows rather qualitative difference of the spatial structures. Results of high resolution simulation are compared also with satellite observations and observation-based products from Copernicus using spatial correlation and spectral analysis. Spatial scales of correlations functions for simulated and observed SST are rather close and differs much from satellite SST reanalysis. Evolution of spectral density for modelled SST and reanalysis showed agreed time periods of small scales intensification. Using of the spectral analysis for satellite measurements is complicated due to gaps. The research leading to this results has received funding from Russian Science Foundation (project № 15-17-20020)

Challenging Hydrological Panaceas: Water poverty governance accounting for spatial scale in the Niger River Basin

NASA Astrophysics Data System (ADS)

Ward, John; Kaczan, David

2014-11-01

Water poverty in the Niger River Basin is a function of physical constraints affecting access and supply, and institutional arrangements affecting the ability to utilise the water resource. This distinction reflects the complexity of water poverty and points to the need to look beyond technical and financial means alone to reduce its prevalence and severity. Policy decisions affecting water resources are generally made at a state or national level. Hydrological and socio-economic evaluations at these levels, or at the basin level, cannot be presumed to be concordant with the differentiation of poverty or livelihood vulnerability at more local levels. We focus on three objectives: first, the initial mapping of observed poverty, using two health metrics and a household assets metric; second, the estimation of factors which potentially influence the observed poverty patterns; and third, a consideration of spatial non-stationarity, which identifies spatial correlates of poverty in the places where their effects appear most severe. We quantify the extent to which different levels of analysis influence these results. Comparative analysis of correlates of poverty at basin, national and local levels shows limited congruence. Variation in water quantity, and the presence of irrigation and dams had either limited or no significant correlation with observed variation in poverty measures across levels. Education and access to improved water quality were the only variables consistently significant and spatially stable across the entire basin. At all levels, education is the most consistent non-water correlate of poverty while access to protected water sources is the strongest water related correlate. The analysis indicates that landscape and scale matter for understanding water-poverty linkages and for devising policy concerned with alleviating water poverty. Interactions between environmental, social and institutional factors are complex and consequently a comprehensive understanding of poverty and its causes requires analysis at multiple spatial resolutions.

Rainfall Observed Over Bangladesh 2000-2008: A Comparison of Spatial Interpolation Methods

NASA Astrophysics Data System (ADS)

Pervez, M.; Henebry, G. M.

2010-12-01

In preparation for a hydrometeorological study of freshwater resources in the greater Ganges-Brahmaputra region, we compared the results of four methods of spatial interpolation applied to point measurements of daily rainfall over Bangladesh during a seven year period (2000-2008). Two univariate (inverse distance weighted and spline-regularized and tension) and two multivariate geostatistical (ordinary kriging and kriging with external drift) methods were used to interpolate daily observations from a network of 221 rain gauges across Bangladesh spanning an area of 143,000 sq km. Elevation and topographic index were used as the covariates in the geostatistical methods. The validity of the interpolated maps was analyzed through cross-validation. The quality of the methods was assessed through the Pearson and Spearman correlations and root mean square error measurements of accuracy in cross-validation. Preliminary results indicated that the univariate methods performed better than the geostatistical methods at daily scales, likely due to the relatively dense sampled point measurements and a weak correlation between the rainfall and covariates at daily scales in this region. Inverse distance weighted produced the better results than the spline. For the days with extreme or high rainfall—spatially and quantitatively—the correlation between observed and interpolated estimates appeared to be high (r2 ~ 0.6 RMSE ~ 10mm), although for low rainfall days the correlations were poor (r2 ~ 0.1 RMSE ~ 3mm). The performance quality of these methods was influenced by the density of the sample point measurements, the quantity of the observed rainfall along with spatial extent, and an appropriate search radius defining the neighboring points. Results indicated that interpolated rainfall estimates at daily scales may introduce uncertainties in the successive hydrometeorological analysis. Interpolations at 5-day, 10-day, 15-day, and monthly time scales are currently under investigation.

Correlated tuning of the speckle pattern in an interferometer based on a multimode fiber-optic waveguide

NASA Astrophysics Data System (ADS)

Bykovskii, Iu. A.; Kul'Chin, Iu. N.; Obukh, V. F.; Smirnov, V. L.

1990-08-01

The correlated tuning of the speckle pattern in the radiation field of a single-fiber multimode interferometer is investigated experimentally and analytically in the presence of external action. It is found that correlated changes in the speckle pattern are observed in both the near and the far emission fields of the waveguide. An expression is obtained which provides a way to determine the maximum size of the speckle correlation region. The use of spatial filtering for isolating the effect of correlated speckle pattern tuning is suggested. It is shown that the use of a spatial filter makes it possible to increase the efficiency of fiber-optic transducers.

North Polar Radiative Flux Variability from 2002 Through 2014

NASA Technical Reports Server (NTRS)

Rutan, David; Rose, Fred; Doelling, David; Kato, Seiji; Smith, Bill, Jr.

2017-01-01

NASA's Clouds and the Earth's Radiant Energy System (CERES) project produces the SYN1Deg data product. SYN1deg provides global, 1deg gridded, hourly estimates of Top of Atmosphere (TOA) (CERES observations and calculations) and atmospheric and surface radiative flux (calculations). Examples of 12 year North Polar averages of some variables are shown to the right. Given recent interest in polar science we focus here on TOA and Surface validation of calculated irradiant fluxes. TOA upward longwave irradiance calculations match the CERES observations well both spatially and temporally with correlations remaining strong through PC 6. Compare SYN1Deg Calculations & Meteorological Teleconnections. TOA reflected shortwave irradiance calculations match the CERES observations well both spatially and temporally with correlations remaining string through PC 7. Comparing SYN1Deg calculations to teleconnection patterns requires expanding the area to 30N for EOF analyses. Correlating the Principal Components of various variables to teleconnection time series indicates which variable is most highly correlated with which teleconnection signal. The tables indicate the Pacific North American Oscillation is most correlated to the OLR EOF 1, and the North American Oscillation is correlated most closely to surface LW flux down EOF 1.

Detecting Spatial Patterns in Biological Array Experiments

PubMed Central

ROOT, DAVID E.; KELLEY, BRIAN P.; STOCKWELL, BRENT R.

2005-01-01

Chemical genetic screening and DNA and protein microarrays are among a number of increasingly important and widely used biological research tools that involve large numbers of parallel experiments arranged in a spatial array. It is often difficult to ensure that uniform experimental conditions are present throughout the entire array, and as a result, one often observes systematic spatially correlated errors, especially when array experiments are performed using robots. Here, the authors apply techniques based on the discrete Fourier transform to identify and quantify spatially correlated errors superimposed on a spatially random background. They demonstrate that these techniques are effective in identifying common spatially systematic errors in high-throughput 384-well microplate assay data. In addition, the authors employ a statistical test to allow for automatic detection of such errors. Software tools for using this approach are provided. PMID:14567791

Evolution of spatial and temporal correlations in the solar wind - Observations and interpretation

NASA Technical Reports Server (NTRS)

Klein, L. W.; Matthaeus, W. H.; Roberts, D. A.; Goldstein, M. L.

1992-01-01

Observations of solar wind magnetic field spectra from 1-22 AU indicate a distinctive structure in frequency which evolves with increasing heliocentric distance. At 1 AU extremely low frequency correlations are associated with temporal variations at the solar period and its first few harmonics. For periods of l2-96 hours, a l/f distribution is observed, which we interpret as an aggregate of uncorrelated coronal structures which have not dynamically interacted by 1 AU. At higher frequencies the familiar Kolmogorov-like power law is seen. Farther from the sun the frequency break point between the shallow l/f and the steeper Kolmogorov spectrum evolves systematically towards lower frequencies. We suggest that the Kolmogorov-like spectra emerge due to in situ turbulence that generates spatial correlations associated with the turbulent cascade and that the background l/f noise is a largely temporal phenomenon, not associated with in situ dynamical processes. In this paper we discuss these ideas from the standpoint of observations from several interplanetary spacecraft.

Temporal and spatial distribution of Microcystis biomass and genotype in bloom areas of Lake Taihu.

PubMed

Guan, Dong-Xing; Wang, Xingyu; Xu, Huacheng; Chen, Li; Li, Pengfu; Ma, Lena Q

2018-06-26

Cyanobacterial blooms as a global environmental issue are of public health concern. In this study, we investigated the spatial (10 sites) and temporal (June, August and October) variations in: 1) their biomass based on chlorophyll-a (chl-a) concentration, 2) their toxic genotype based on gene copy ratio of mcyJ to cpcBA, and 3) their cpcBA genotype composition of Microcystis during cyanobacterial bloom in Lake Taihu. While spatial-temporal variations were found in chl-a and mcyJ/cpcBA ratio, only spatial variation was observed in cpcBA genotype composition. Samples from northwestern part had a higher chl-a, but mcyJ/cpcBA ratio didn't vary among the sites. High chl-a was observed in August, while mcyJ/cpcBA ratio and genotypic richness increased with time. The spatial variations in chl-a and mcyJ/cpcBA ratio and temporal variation in cpcBA genotype were correlated negatively with dissolved N and positively with dissolved P. Spatial distribution of Microcystis biomass was positively correlated with nitrite and P excluding October, but no correlation was found for spatial distribution of mcyJ/cpcBA ratio and cpcBA genotype. Spatial distribution of toxic and cpcBA genotypes may result from horizontal transport of Microcystis colonies, while spatial variation in Microcystis biomass was probably controlled by both nutrient-mediated growth and horizontal transport of Microcystis. The temporal variation in Microcystis biomass, toxic genotype and cpcBA genotype composition were related to nutrient levels, but cause-and-effect relationships require further study. Copyright © 2018 Elsevier Ltd. All rights reserved.

Quantum Liquid Crystal Phases in Strongly Correlated Fermionic Systems

ERIC Educational Resources Information Center

Sun, Kai

2009-01-01

This thesis is devoted to the investigation of the quantum liquid crystal phases in strongly correlated electronic systems. Such phases are characterized by their partially broken spatial symmetries and are observed in various strongly correlated systems as being summarized in Chapter 1. Although quantum liquid crystal phases often involve…

Nonequilibrium relaxations within the ground-state manifold in the antiferromagnetic Ising model on a triangular lattice.

PubMed

Kim, Eunhye; Lee, Sung Jong; Kim, Bongsoo

2007-02-01

We present an extensive Monte Carlo simulation study on the nonequilibrium kinetics of triangular antiferromagnetic Ising model within the ground state ensemble which consists of sectors, each of which is characterized by a unique value of the string density p through a dimer covering method. Building upon our recent work [Phys. Rev. E 68, 066127 (2003)] where we considered the nonequilibrium relaxation observed within the dominant sector with p=2/3, we here focus on the nonequilibrium kinetics within the minor sectors with p<2/3. The initial configurations are chosen as those in which the strings are straight and evenly distributed. In the minor sectors, we observe a characteristic spatial anisotropy in both equilibrium and nonequilibrium spatial correlations. We observe emergence of a critical relaxation region (in the spatial and temporal domain) which grows as p deviates from p=2/3. Spatial anisotropy appears in the equilibrium spatial correlation with the characteristic length scale xi(e,V)(p) diverging with vanishing string density as xi(e,V)(p) approximately p(-2) along the vertical direction, while along the horizontal direction the spatial length scale diverges as xi(e,H) approximately p(-1). Analytic forms for the anisotropic equilibrium correlation functions are given. We also find that the spin autocorrelation function A(t) shows a simple scaling behavior A(t)=A(t/tau(A)(p)), where the time scale tau(A)(p) shows a power-law divergence with vanishing p as tau(A)(p) approximately p(-phi) with phi approximately or equal to 4. These features can be understood in terms of random walk nature of the fluctuations of the strings within the typical separation between neighboring strings.

Spatial entanglement patterns and Einstein-Podolsky-Rosen steering in Bose-Einstein condensates

NASA Astrophysics Data System (ADS)

Fadel, Matteo; Zibold, Tilman; Décamps, Boris; Treutlein, Philipp

2018-04-01

Many-particle entanglement is a fundamental concept of quantum physics that still presents conceptual challenges. Although nonclassical states of atomic ensembles were used to enhance measurement precision in quantum metrology, the notion of entanglement in these systems was debated because the correlations among the indistinguishable atoms were witnessed by collective measurements only. Here, we use high-resolution imaging to directly measure the spin correlations between spatially separated parts of a spin-squeezed Bose-Einstein condensate. We observe entanglement that is strong enough for Einstein-Podolsky-Rosen steering: We can predict measurement outcomes for noncommuting observables in one spatial region on the basis of corresponding measurements in another region with an inferred uncertainty product below the Heisenberg uncertainty bound. This method could be exploited for entanglement-enhanced imaging of electromagnetic field distributions and quantum information tasks.

On the Character and Mitigation of Atmospheric Noise in InSAR Time Series Analysis (Invited)

NASA Astrophysics Data System (ADS)

Barnhart, W. D.; Fielding, E. J.; Fishbein, E.

2013-12-01

Time series analysis of interferometric synthetic aperture radar (InSAR) data, with its broad spatial coverage and ability to image regions that are sometimes very difficult to access, is a powerful tool for characterizing continental surface deformation and its temporal variations. With the impending launch of dedicated SAR missions such as Sentinel-1, ALOS-2, and the planned NASA L-band SAR mission, large volume data sets will allow researchers to further probe ground displacement processes with increased fidelity. Unfortunately, the precision of measurements in individual interferograms is impacted by several sources of noise, notably spatially correlated signals caused by path delays through the stratified and turbulent atmosphere and ionosphere. Spatial and temporal variations in atmospheric water vapor often introduce several to tens of centimeters of apparent deformation in the radar line-of-sight, correlated over short spatial scales (<10 km). Signals resulting from atmospheric path delays are particularly problematic because, like the subsidence and uplift signals associated with tectonic deformation, they are often spatially correlated with topography. In this talk, we provide an overview of the effects of spatially correlated tropospheric noise in individual interferograms and InSAR time series analysis, and we highlight where common assumptions of the temporal and spatial characteristics of tropospheric noise fail. Next, we discuss two classes of methods for mitigating the effects of tropospheric water vapor noise in InSAR time series analysis and single interferograms: noise estimation and characterization with independent observations from multispectral sensors such as MODIS and MERIS; and noise estimation and removal with weather models, multispectral sensor observations, and GPS. Each of these techniques can provide independent assessments of the contribution of water vapor in interferograms, but each technique also suffers from several pitfalls that we outline. The multispectral near-infrared (NIR) sensors provide high spatial resolution (~1 km) estimates of total column tropospheric water vapor by measuring the absorption of reflected solar illumination and provide may excellent estimates of wet delay. The Online Services for Correcting Atmosphere in Radar (OSCAR) project currently provides water vapor products through web services (http://oscar.jpl.nasa.gov). Unfortunately, such sensors require daytime and cloudless observations. Global and regional numerical weather models can provide an additional estimate of both the dry and atmospheric delays with spatial resolution of (3-100 km) and time scales of 1-3 hours, though these models are of lower accuracy than imaging observations and are benefited by independent observations from independent observations of atmospheric water vapor. Despite these issues, the integration of these techniques for InSAR correction and uncertainty estimation may contribute substantially to the reduction and rigorous characterization of uncertainty in InSAR time series analysis - helping to expand the range of tectonic displacements imaged with InSAR, to robustly constrain geophysical models, and to generate a-priori assessments of satellite acquisitions goals.

A New Methodology of Spatial Cross-Correlation Analysis

PubMed Central

Chen, Yanguang

2015-01-01

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

A new methodology of spatial cross-correlation analysis.

PubMed

Chen, Yanguang

2015-01-01

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

Observations and statistical simulations of a proposed solar cycle/QBO/weather relationship

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

Baldwin, M.P.; Dunkerton, T.J.

1989-08-01

The 10.7 cm solar flux is observed to be highly correlated with north pole stratospheric temperatures when partitioned according to the phase of the equatorial stratospheric winds (the quasi-biennial oscillation, or QBO). The authors supplement observations with calculations showing that temperatures over most of the northern hemisphere are highly correlated or anticorrelated with north pole temperatures. The observed spatial pattern of solar cycle correlations at high latitudes is shown to be not unique to the solar cycle. The authors present results, similar to the observed solar cycle correlations, with simulated harmonics of various periods replacing the solar cycle. These calculationsmore » demonstrate the correlations at least as high as those for the solar cycle results may be obtained using simulated harmonics.« less

Quantifying spatial and temporal variabilities of microwave brightness temperature over the U.S. Southern Great Plains

NASA Technical Reports Server (NTRS)

Choudhury, B. J.; Owe, M.; Ormsby, J. P.; Chang, A. T. C.; Wang, J. R.; Goward, S. N.; Golus, R. E.

1987-01-01

Spatial and temporal variabilities of microwave brightness temperature over the U.S. Southern Great Plains are quantified in terms of vegetation and soil wetness. The brightness temperatures (TB) are the daytime observations from April to October for five years (1979 to 1983) obtained by the Nimbus-7 Scanning Multichannel Microwave Radiometer at 6.6 GHz frequency, horizontal polarization. The spatial and temporal variabilities of vegetation are assessed using visible and near-infrared observations by the NOAA-7 Advanced Very High Resolution Radiometer (AVHRR), while an Antecedent Precipitation Index (API) model is used for soil wetness. The API model was able to account for more than 50 percent of the observed variability in TB, although linear correlations between TB and API were generally significant at the 1 percent level. The slope of the linear regression between TB and API is found to correlate linearly with an index for vegetation density derived from AVHRR data.

Roles of Spatial Scale and Rarity on the Relationship between Butterfly Species Richness and Human Density in South Africa

PubMed Central

Mecenero, Silvia; Altwegg, Res; Colville, Jonathan F.; Beale, Colin M.

2015-01-01

Wildlife and humans tend to prefer the same productive environments, yet high human densities often lead to reduced biodiversity. Species richness is often positively correlated with human population density at broad scales, but this correlation could also be caused by unequal sampling effort leading to higher species tallies in areas of dense human activity. We examined the relationships between butterfly species richness and human population density at five spatial resolutions ranging from 2' to 60' across South Africa. We used atlas-type data and spatial interpolation techniques aimed at reducing the effect of unequal spatial sampling. Our results confirm the general positive correlation between total species richness and human population density. Contrary to our expectations, the strength of this positive correlation did not weaken at finer spatial resolutions. The patterns observed using total species richness were driven mostly by common species. The richness of threatened and restricted range species was not correlated to human population density. None of the correlations we examined were particularly strong, with much unexplained variance remaining, suggesting that the overlap between butterflies and humans is not strong compared to other factors not accounted for in our analyses. Special consideration needs to be made regarding conservation goals and variables used when investigating the overlap between species and humans for biodiversity conservation. PMID:25915899

Roles of Spatial Scale and Rarity on the Relationship between Butterfly Species Richness and Human Density in South Africa.

PubMed

Mecenero, Silvia; Altwegg, Res; Colville, Jonathan F; Beale, Colin M

2015-01-01

Wildlife and humans tend to prefer the same productive environments, yet high human densities often lead to reduced biodiversity. Species richness is often positively correlated with human population density at broad scales, but this correlation could also be caused by unequal sampling effort leading to higher species tallies in areas of dense human activity. We examined the relationships between butterfly species richness and human population density at five spatial resolutions ranging from 2' to 60' across South Africa. We used atlas-type data and spatial interpolation techniques aimed at reducing the effect of unequal spatial sampling. Our results confirm the general positive correlation between total species richness and human population density. Contrary to our expectations, the strength of this positive correlation did not weaken at finer spatial resolutions. The patterns observed using total species richness were driven mostly by common species. The richness of threatened and restricted range species was not correlated to human population density. None of the correlations we examined were particularly strong, with much unexplained variance remaining, suggesting that the overlap between butterflies and humans is not strong compared to other factors not accounted for in our analyses. Special consideration needs to be made regarding conservation goals and variables used when investigating the overlap between species and humans for biodiversity conservation.

Experimental determination of the correlation properties of plasma turbulence using 2D BES systems

NASA Astrophysics Data System (ADS)

Fox, M. F. J.; Field, A. R.; van Wyk, F.; Ghim, Y.-c.; Schekochihin, A. A.; the MAST Team

2017-04-01

A procedure is presented to map from the spatial correlation parameters of a turbulent density field (the radial and binormal correlation lengths and wavenumbers, and the fluctuation amplitude) to correlation parameters that would be measured by a beam emission spectroscopy (BES) diagnostic. The inverse mapping is also derived, which results in resolution criteria for recovering correct correlation parameters, depending on the spatial response of the instrument quantified in terms of point-spread functions (PSFs). Thus, a procedure is presented that allows for a systematic comparison between theoretical predictions and experimental observations. This procedure is illustrated using the Mega-Ampere Spherical Tokamak BES system and the validity of the underlying assumptions is tested on fluctuating density fields generated by direct numerical simulations using the gyrokinetic code GS2. The measurement of the correlation time, by means of the cross-correlation time-delay method, is also investigated and is shown to be sensitive to the fluctuating radial component of velocity, as well as to small variations in the spatial properties of the PSFs.

Infrared Spectroscopy of Pa-beta and [Fe II] Emission in NGC 4151

NASA Technical Reports Server (NTRS)

Knop, R. A.; Armus, L.; Larkin, J. E.; Matthews, K.; Shupe, D. L.; Soifer, B. T.

1996-01-01

We present spatially resolved 1.24-1.30 micron spectroscopy with a resolution of 240 km/s of the Seyfert 1.5 galaxy NGC 4151. Broad Pa-beta, narrow Pa-beta, and narrow [Fe II] (lambda = 1.2567 micron) emission lines are identified in the spectrum. Additionally, a spatially unresolved narrow component probably due to [S ix] (lambda = 1.25235 micron) is observed on the nucleus. The narrow Pa-beta and [Fe II] lines are observed to be extended over a scale of 5 sec. The spatial variation of the velocity centers of the Pa-beta and [Fe II] lines show remarkable similarity, and additionally show similarities to the velocity structure previously observed in ground based spectroscopy of [O III] emission in NGC 4151. This leads to the conclusion that the [Fe II] emission arises in clouds in the Seyfert narrow line region that are physically correlated with those narrow line clouds responsible for the optical emission. The [Fe II] emission line, however, is significantly wider than the Pa-beta emission line along the full spatial extent of the observed emission. This result suggests that despite the correlation between the bulk kinematics of Pa-beta and [Fe II], there is an additional process, perhaps fast shocks from a wind in the Seyfert nucleus, contributing to the [Fe II] emission.

A resampling procedure for generating conditioned daily weather sequences

USGS Publications Warehouse

Clark, Martyn P.; Gangopadhyay, Subhrendu; Brandon, David; Werner, Kevin; Hay, Lauren E.; Rajagopalan, Balaji; Yates, David

2004-01-01

A method is introduced to generate conditioned daily precipitation and temperature time series at multiple stations. The method resamples data from the historical record “nens” times for the period of interest (nens = number of ensemble members) and reorders the ensemble members to reconstruct the observed spatial (intersite) and temporal correlation statistics. The weather generator model is applied to 2307 stations in the contiguous United States and is shown to reproduce the observed spatial correlation between neighboring stations, the observed correlation between variables (e.g., between precipitation and temperature), and the observed temporal correlation between subsequent days in the generated weather sequence. The weather generator model is extended to produce sequences of weather that are conditioned on climate indices (in this case the Niño 3.4 index). Example illustrations of conditioned weather sequences are provided for a station in Arizona (Petrified Forest, 34.8°N, 109.9°W), where El Niño and La Niña conditions have a strong effect on winter precipitation. The conditioned weather sequences generated using the methods described in this paper are appropriate for use as input to hydrologic models to produce multiseason forecasts of streamflow.

A Statistical Model for Estimation of Fish Density Including Correlation in Size, Space, Time and between Species from Research Survey Data

PubMed Central

Bastardie, Francois

2014-01-01

Trawl survey data with high spatial and seasonal coverage were analysed using a variant of the Log Gaussian Cox Process (LGCP) statistical model to estimate unbiased relative fish densities. The model estimates correlations between observations according to time, space, and fish size and includes zero observations and over-dispersion. The model utilises the fact the correlation between numbers of fish caught increases when the distance in space and time between the fish decreases, and the correlation between size groups in a haul increases when the difference in size decreases. Here the model is extended in two ways. Instead of assuming a natural scale size correlation, the model is further developed to allow for a transformed length scale. Furthermore, in the present application, the spatial- and size-dependent correlation between species was included. For cod (Gadus morhua) and whiting (Merlangius merlangus), a common structured size correlation was fitted, and a separable structure between the time and space-size correlation was found for each species, whereas more complex structures were required to describe the correlation between species (and space-size). The within-species time correlation is strong, whereas the correlations between the species are weaker over time but strong within the year. PMID:24911631

Cross-comparison and evaluation of air pollution field estimation methods

NASA Astrophysics Data System (ADS)

Yu, Haofei; Russell, Armistead; Mulholland, James; Odman, Talat; Hu, Yongtao; Chang, Howard H.; Kumar, Naresh

2018-04-01

Accurate estimates of human exposure is critical for air pollution health studies and a variety of methods are currently being used to assign pollutant concentrations to populations. Results from these methods may differ substantially, which can affect the outcomes of health impact assessments. Here, we applied 14 methods for developing spatiotemporal air pollutant concentration fields of eight pollutants to the Atlanta, Georgia region. These methods include eight methods relying mostly on air quality observations (CM: central monitor; SA: spatial average; IDW: inverse distance weighting; KRIG: kriging; TESS-D: discontinuous tessellation; TESS-NN: natural neighbor tessellation with interpolation; LUR: land use regression; AOD: downscaled satellite-derived aerosol optical depth), one using the RLINE dispersion model, and five methods using a chemical transport model (CMAQ), with and without using observational data to constrain results. The derived fields were evaluated and compared. Overall, all methods generally perform better at urban than rural area, and for secondary than primary pollutants. We found the CM and SA methods may be appropriate only for small domains, and for secondary pollutants, though the SA method lead to large negative spatial correlations when using data withholding for PM2.5 (spatial correlation coefficient R = -0.81). The TESS-D method was found to have major limitations. Results of the IDW, KRIG and TESS-NN methods are similar. They are found to be better suited for secondary pollutants because of their satisfactory temporal performance (e.g. average temporal R2 > 0.85 for PM2.5 but less than 0.35 for primary pollutant NO2). In addition, they are suitable for areas with relatively dense monitoring networks due to their inability to capture spatial concentration variabilities, as indicated by the negative spatial R (lower than -0.2 for PM2.5 when assessed using data withholding). The performance of LUR and AOD methods were similar to kriging. Using RLINE and CMAQ fields without fusing observational data led to substantial errors and biases, though the CMAQ model captured spatial gradients reasonably well (spatial R = 0.45 for PM2.5). Two unique tests conducted here included quantifying autocorrelation of method biases (which can be important in time series analyses) and how well the methods capture the observed interspecies correlations (which would be of particular importance in multipollutant health assessments). Autocorrelation of method biases lasted longest and interspecies correlations of primary pollutants was higher than observations when air quality models were used without data fusing. Use of hybrid methods that combine air quality model outputs with observational data overcome some of these limitations and is better suited for health studies. Results from this study contribute to better understanding the strengths and weaknesses of different methods for estimating human exposures.

A comparison of correlation-length estimation methods for the objective analysis of surface pollutants at Environment and Climate Change Canada.

PubMed

Ménard, Richard; Deshaies-Jacques, Martin; Gasset, Nicolas

2016-09-01

An objective analysis is one of the main components of data assimilation. By combining observations with the output of a predictive model we combine the best features of each source of information: the complete spatial and temporal coverage provided by models, with a close representation of the truth provided by observations. The process of combining observations with a model output is called an analysis. To produce an analysis requires the knowledge of observation and model errors, as well as its spatial correlation. This paper is devoted to the development of methods of estimation of these error variances and the characteristic length-scale of the model error correlation for its operational use in the Canadian objective analysis system. We first argue in favor of using compact support correlation functions, and then introduce three estimation methods: the Hollingsworth-Lönnberg (HL) method in local and global form, the maximum likelihood method (ML), and the [Formula: see text] diagnostic method. We perform one-dimensional (1D) simulation studies where the error variance and true correlation length are known, and perform an estimation of both error variances and correlation length where both are non-uniform. We show that a local version of the HL method can capture accurately the error variances and correlation length at each observation site, provided that spatial variability is not too strong. However, the operational objective analysis requires only a single and globally valid correlation length. We examine whether any statistics of the local HL correlation lengths could be a useful estimate, or whether other global estimation methods such as by the global HL, ML, or [Formula: see text] should be used. We found in both 1D simulation and using real data that the ML method is able to capture physically significant aspects of the correlation length, while most other estimates give unphysical and larger length-scale values. This paper describes a proposed improvement of the objective analysis of surface pollutants at Environment and Climate Change Canada (formerly known as Environment Canada). Objective analyses are essentially surface maps of air pollutants that are obtained by combining observations with an air quality model output, and are thought to provide a complete and more accurate representation of the air quality. The highlight of this study is an analysis of methods to estimate the model (or background) error correlation length-scale. The error statistics are an important and critical component to the analysis scheme.

Spatial Imaging of Strongly Interacting Rydberg Atoms

NASA Astrophysics Data System (ADS)

Thaicharoen, Nithiwadee

The strong interactions between Rydberg excitations can result in spatial correlations between the excitations. The ability to control the interaction strength and the correlations between Rydberg atoms is applicable in future technological implementations of quantum computation. In this thesis, I investigates how both the character of the Rydberg-Rydberg interactions and the details of the excitation process affect the nature of the spatial correlations and the evolution of those correlations in time. I first describes the experimental apparatus and methods used to perform high-magnification Rydberg-atom imaging, as well as three experiments in which these methods play an important role. The obtained Rydberg-atom positions reveal the correlations in the many-body Rydberg-atom system and their time dependence with sub-micron spatial resolution. In the first experiment, atoms are excited to a Rydberg state that experiences a repulsive van der Waals interaction. The Rydberg excitations are prepared with a well-defined initial separation, and the effect of van der Waals forces is observed by tracking the interatomic distance between the Rydberg atoms. The atom trajectories and thereby the interaction coefficient C6 are extracted from the pair correlation functions of the Rydberg atom positions. In the second experiment, the Rydberg atoms are prepared in a highly dipolar state by using adiabatic state transformation. The atom-pair kinetics that follow from the strong dipole-dipole interactions are observed. The pair correlation results provide the first direct visualization of the electric-dipole interaction and clearly exhibit its anisotropic nature. In both the first and the second experiment, results of semi-classical simulations of the atom-pair trajectories agree well with the experimental data. In the analysis, I use energy conservation and measurements of the initial positions and the terminal velocities of the atom pairs to extract the C6 and C 3 interaction coefficients. The final experiment demonstrates the ability to enhance or suppress the degree of spatial correlation in a system of Rydberg excitations, using a rotary-echo excitation process in concert with particular excitation laser detunings. The work in this thesis demonstrates an ability to control long-range interactions between Rydberg atoms, which paves the way towards preparing and studying increasingly complex many-body systems.

A class of covariate-dependent spatiotemporal covariance functions

PubMed Central

Reich, Brian J; Eidsvik, Jo; Guindani, Michele; Nail, Amy J; Schmidt, Alexandra M.

2014-01-01

In geostatistics, it is common to model spatially distributed phenomena through an underlying stationary and isotropic spatial process. However, these assumptions are often untenable in practice because of the influence of local effects in the correlation structure. Therefore, it has been of prolonged interest in the literature to provide flexible and effective ways to model non-stationarity in the spatial effects. Arguably, due to the local nature of the problem, we might envision that the correlation structure would be highly dependent on local characteristics of the domain of study, namely the latitude, longitude and altitude of the observation sites, as well as other locally defined covariate information. In this work, we provide a flexible and computationally feasible way for allowing the correlation structure of the underlying processes to depend on local covariate information. We discuss the properties of the induced covariance functions and discuss methods to assess its dependence on local covariate information by means of a simulation study and the analysis of data observed at ozone-monitoring stations in the Southeast United States. PMID:24772199

Mode analysis of higher-order transverse-mode correlation beams in a turbulent atmosphere.

PubMed

Avetisyan, H; Monken, C H

2017-01-01

Due to the transfer of the angular spectrum of the pump beam to the two-photon state in spontaneous parametric downconversion, the generated twin photons are entangled in their spatial degrees of freedom. This spatial entanglement can be observed through correlation measurements in any set of modes in which one may choose to perform measurements. Choosing, e.g., a Hermite-Gaussian (HG) set of spatial modes as a basis, one can observe correlations present in their spatial degrees of freedom. In addition, these modes can be used as alphabets for quantum communication. For global quantum communication purposes, we derive an analytic expression for two-photon detection probability in terms of HG modes, taking into account the effects of the turbulent atmosphere. Our result is more general as it accounts for the propagation of both signal and idler photons through the atmosphere, as opposed to other works considering one photon's propagation in vacuum. We show that while the restrictions on both the parity and order of the downconverted HG fields no longer hold, due to the crosstalk between modes when propagating in the atmosphere, the crosstalk is not uniform: there are more robust modes that tend to keep the photons in them. These modes can be employed in order to increase the fidelity of quantum communication.

Neurobiological and Endocrine Correlates of Individual Differences in Spatial Learning Ability

PubMed Central

Sandi, Carmen; Cordero, M. Isabel; Merino, José J.; Kruyt, Nyika D.; Regan, Ciaran M.; Murphy, Keith J.

2004-01-01

The polysialylated neural cell adhesion molecule (PSA-NCAM) has been implicated in activity-dependent synaptic remodeling and memory formation. Here, we questioned whether training-induced modulation of PSA-NCAM expression might be related to individual differences in spatial learning abilities. At 12 h posttraining, immunohistochemical analyses revealed a learning-induced up-regulation of PSA-NCAM in the hippocampal dentate gyrus that was related to the spatial learning abilities displayed by rats during training. Specifically, a positive correlation was found between latency to find the platform and subsequent activated PSA levels, indicating that greater induction of polysialylation was observed in rats with the slower acquisition curve. At posttraining times when no learning-associated activation of PSA was observed, no such correlation was found. Further experiments revealed that performance in the massed water maze training is related to a pattern of spatial learning and memory abilities, and to learning-related glucocorticoid responsiveness. Taken together, our findings suggest that the learning-related neural circuits of fast learners are better suited to solving the water maze task than those of slow learners, the latter relying more on structural reorganization to form memory, rather than the relatively economic mechanism of altering synaptic efficacy that is likely used by the former. PMID:15169853

Neurobiological and endocrine correlates of individual differences in spatial learning ability.

PubMed

Sandi, Carmen; Cordero, M Isabel; Merino, José J; Kruyt, Nyika D; Regan, Ciaran M; Murphy, Keith J

2004-01-01

The polysialylated neural cell adhesion molecule (PSA-NCAM) has been implicated in activity-dependent synaptic remodeling and memory formation. Here, we questioned whether training-induced modulation of PSA-NCAM expression might be related to individual differences in spatial learning abilities. At 12 h posttraining, immunohistochemical analyses revealed a learning-induced up-regulation of PSA-NCAM in the hippocampal dentate gyrus that was related to the spatial learning abilities displayed by rats during training. Specifically, a positive correlation was found between latency to find the platform and subsequent activated PSA levels, indicating that greater induction of polysialylation was observed in rats with the slower acquisition curve. At posttraining times when no learning-associated activation of PSA was observed, no such correlation was found. Further experiments revealed that performance in the massed water maze training is related to a pattern of spatial learning and memory abilities, and to learning-related glucocorticoid responsiveness. Taken together, our findings suggest that the learning-related neural circuits of fast learners are better suited to solving the water maze task than those of slow learners, the latter relying more on structural reorganization to form memory, rather than the relatively economic mechanism of altering synaptic efficacy that is likely used by the former.

Spatial and spectral interpolation of ground-motion intensity measure observations

USGS Publications Warehouse

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.

Application of spatial Poisson process models to air mass thunderstorm rainfall

NASA Technical Reports Server (NTRS)

Eagleson, P. S.; Fennessy, N. M.; Wang, Qinliang; Rodriguez-Iturbe, I.

1987-01-01

Eight years of summer storm rainfall observations from 93 stations in and around the 154 sq km Walnut Gulch catchment of the Agricultural Research Service, U.S. Department of Agriculture, in Arizona are processed to yield the total station depths of 428 storms. Statistical analysis of these random fields yields the first two moments, the spatial correlation and variance functions, and the spatial distribution of total rainfall for each storm. The absolute and relative worth of three Poisson models are evaluated by comparing their prediction of the spatial distribution of storm rainfall with observations from the second half of the sample. The effect of interstorm parameter variation is examined.

Spatial variations in a.c. susceptibility and microstructure for the YBa2Cu3O(7-x) superconductor and their correlation with room-temperature ultrasonic measurements

NASA Technical Reports Server (NTRS)

Roth, Don J.; Hepp, Aloysius F.; Deguire, Mark R.; Dolhert, Leonard E.

1991-01-01

The spatial (within-sample) uniformity of superconducting behavior and microstructure in YBa2Cu30(7-x) specimens over the pore fraction range of 0.10 to 0.25 was examined. The viability of using a room-temperature, nondestructive characterization method (ultrasonic velocity imaging) to predict spatial variability was determined. Spatial variations in superconductor properties were observed for specimens containing 0.10 pore fraction. An ultrasonic velocity image constructed from measurements at 1 mm increments across one such specimen revealed microstructural variation between edge and center locations that correlated with variations in alternating-current shielding and loss behavior. Optical quantitative image analysis on sample cross-sections revealed pore fraction to be the varying microstructural feature.

Spatial variations in ac susceptibility and microstructure for the YBa2Cu3O(7-x) superconductor and their correlation with room-temperature ultrasonic measurements

NASA Technical Reports Server (NTRS)

Roth, Don J.; Deguire, Mark R.; Dolhert, Leonard E.; Hepp, Aloysius F.

1991-01-01

The spatial (within-sample) uniformity of superconducting behavior and microstructure in YBa2Cu3O(7-x) specimens over the pore fraction range of 0.10 to 0.25 was examined. The viability of using a room-temperature, nondestructive characterization method (ultrasonic velocity imaging) to predict spatial variability was determined. Spatial variations in superconductor properties were observed for specimens containing 0.10 pore fraction. An ultrasonic velocity image constructed from measurements at 1 mm increments across one such specimen revealed microstructural variation between edge and center locations that correlated with variations in alternating-current shielding and loss behavior. Optical quantitative image analysis on sample cross-sections revealed pore fraction to be the varying microstructural feature.

Task relevance modulates the behavioural and neural effects of sensory predictions

PubMed Central

Friston, Karl J.; Nobre, Anna C.

2017-01-01

The brain is thought to generate internal predictions to optimize behaviour. However, it is unclear whether predictions signalling is an automatic brain function or depends on task demands. Here, we manipulated the spatial/temporal predictability of visual targets, and the relevance of spatial/temporal information provided by auditory cues. We used magnetoencephalography (MEG) to measure participants’ brain activity during task performance. Task relevance modulated the influence of predictions on behaviour: spatial/temporal predictability improved spatial/temporal discrimination accuracy, but not vice versa. To explain these effects, we used behavioural responses to estimate subjective predictions under an ideal-observer model. Model-based time-series of predictions and prediction errors (PEs) were associated with dissociable neural responses: predictions correlated with cue-induced beta-band activity in auditory regions and alpha-band activity in visual regions, while stimulus-bound PEs correlated with gamma-band activity in posterior regions. Crucially, task relevance modulated these spectral correlates, suggesting that current goals influence PE and prediction signalling. PMID:29206225

The ENSO Effect on the Temporal and Spatial Distribution of Global Lightning Activity

NASA Technical Reports Server (NTRS)

Chronis, Themis G.; Goodman, Steven J.; Cecil, Dan; Buechler, Dennis; Pittman, Jasna; Robertson, Franklin R.; Blakeslee, Richard J.

2007-01-01

The recently reprocessed (1997-2006) OTD/LIS database is used to investigate the global lightning climatology in response to the ENSO cycle. A linear correlation map between lightning anomalies and ENSO (NINO3.4) identifies areas that generally follow patterns similar to precipitation anomalies. We also observed areas where significant lightning/ENSO correlations are found and are not accompanied of significant precipitation/ENSO correlations. An extreme case of the strong decoupling between lightning and precipitation is observed over the Indonesian peninsula (Sumatra) where positive lightning/NINO3.4 correlations are collocated with negative precipitation/NINO3.4 correlations. Evidence of linear relationships between the spatial extent of thunderstorm distribution and the respective NINO3.4 magnitude are presented for different regions on the Earth. Strong coupling is found over areas remote to the main ENSO axis of influence and both during warm and cold ENSO phases. Most of the resulted relationships agree with the tendencies of precipitation related to ENSO empirical maps or documented teleconnection patterns. Over the Australian continent, opposite behavior in terms of thunderstorm activity is noted for warm ENSO phases with NINO3.4 magnitudes with NINO3.4>+l.08 and 0

Social and spatial processes associated with childhood diarrheal disease in Matlab, Bangladesh.

PubMed

Perez-Heydrich, Carolina; Furgurson, Jill M; Giebultowicz, Sophia; Winston, Jennifer J; Yunus, Mohammad; Streatfield, Peter Kim; Emch, Michael

2013-01-01

We develop novel methods for conceptualizing geographic space and social networks to evaluate their respective and combined contributions to childhood diarrheal incidence. After defining maternal networks according to direct familial linkages between females, and road networks using satellite imagery of the study area, we use a spatial econometrics model to evaluate the significance of correlation terms relating childhood diarrheal incidence to the incidence observed within respective networks. Disease was significantly clustered within road networks across time, but only inconsistently correlated within maternal networks. These methods could be widely applied to systems in which both social and spatial processes jointly influence health outcomes. Copyright © 2012 Elsevier Ltd. All rights reserved.

Spatiotemporal correlation structure of the Earth's surface temperature

NASA Astrophysics Data System (ADS)

Fredriksen, Hege-Beate; Rypdal, Kristoffer; Rypdal, Martin

2015-04-01

We investigate the spatiotemporal temperature variability for several gridded instrumental and climate model data sets. The temporal variability is analysed by estimating the power spectral density and studying the differences between local and global temperatures, land and sea, and among local temperature records at different locations. The spatiotemporal correlation structure is analysed through cross-spectra that allow us to compute frequency-dependent spatial autocorrelation functions (ACFs). Our results are then compared to theoretical spectra and frequency-dependent spatial ACFs derived from a fractional stochastic-diffusive energy balance model (FEBM). From the FEBM we expect both local and global temperatures to have a long-range persistent temporal behaviour, and the spectral exponent (β) is expected to increase by a factor of two when going from local to global scales. Our comparison of the average local spectrum and the global spectrum shows good agreement with this model, although the FEBM has so far only been studied for a pure land planet and a pure ocean planet, respectively, with no seasonal forcing. Hence it cannot capture the substantial variability among the local spectra, in particular between the spectra for land and sea, and for equatorial and non-equatorial temperatures. Both models and observation data show that land temperatures in general have a low persistence, while sea surface temperatures show a higher, and also more variable degree of persistence. Near the equator the spectra deviate from the power-law shape expected from the FEBM. Instead we observe large variability at time scales of a few years due to ENSO, and a flat spectrum at longer time scales, making the spectrum more reminiscent of that of a red noise process. From the frequency-dependent spatial ACFs we observe that the spatial correlation length increases with increasing time scale, which is also consistent with the FEBM. One consequence of this is that longer-lasting structures must also be wider in space. The spatial correlation length is also observed to be longer for land than for sea. The climate model simulations studied are mainly CMIP5 control runs of length 500-1000 yr. On time scales up to several centuries we do not observe that the difference between the local and global spectral exponents vanish. This also follows from the FEBM and shows that the dynamics is spatiotemporal (not just temporal) even on these time scales.

Implementation of a direct-imaging and FX correlator for the BEST-2 array

NASA Astrophysics Data System (ADS)

Foster, G.; Hickish, J.; Magro, A.; Price, D.; Zarb Adami, K.

2014-04-01

A new digital backend has been developed for the Basic Element for SKA Training II (BEST-2) array at Radiotelescopi di Medicina, INAF-IRA, Italy, which allows concurrent operation of an FX correlator, and a direct-imaging correlator and beamformer. This backend serves as a platform for testing some of the spatial Fourier transform concepts which have been proposed for use in computing correlations on regularly gridded arrays. While spatial Fourier transform-based beamformers have been implemented previously, this is, to our knowledge, the first time a direct-imaging correlator has been deployed on a radio astronomy array. Concurrent observations with the FX and direct-imaging correlator allow for direct comparison between the two architectures. Additionally, we show the potential of the direct-imaging correlator for time-domain astronomy, by passing a subset of beams though a pulsar and transient detection pipeline. These results provide a timely verification for spatial Fourier transform-based instruments that are currently in commissioning. These instruments aim to detect highly redshifted hydrogen from the epoch of reionization and/or to perform wide-field surveys for time-domain studies of the radio sky. We experimentally show the direct-imaging correlator architecture to be a viable solution for correlation and beamforming.

Spatial Representativeness of PM2.5 Concentrations Obtained Using Observations From Network Stations

NASA Astrophysics Data System (ADS)

Shi, Xiaoqin; Zhao, Chuanfeng; Jiang, Jonathan H.; Wang, Chunying; Yang, Xin; Yung, Yuk L.

2018-03-01

Haze has been a focused air pollution phenomenon in China, and its characterization is highly desired. Aerosol properties obtained from a single station are frequently used to represent the haze condition over a large domain, such as tens of kilometers, which could result in high uncertainties due to their spatial variation. Using a high-resolution network observation over an urban city in North China from November 2015 to February 2016, this study examines the spatial representativeness of ground station observations of particulate matter with diameters less than 2.5 μm (PM2.5). We developed a new method to determine the representative area of PM2.5 measurements from limited stations. The key idea is to determine the PM2.5 spatial representative area using its spatial variability and temporal correlation. We also determine stations with large representative area using two grid networks with different resolutions. Based on the high spatial resolution measurements, the representative area of PM2.5 at one station can be determined from the grids with high correlations and small differences of PM2.5. The representative area for a single station in the study period ranges from 0.25 to 16.25 km2 but is less than 3 km2 for more than half of the stations. The representative area varies with locations, and observation at 10 optimal stations would have a good representativeness of those obtained from 169 stations for the 4 month time scale studied. Both evaluations with an empirical orthogonal function analysis and with independent data set corroborate the validity of the results found in this study.

Latent spatial models and sampling design for landscape genetics

USGS Publications Warehouse

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.

Spatial Representativeness of Surface-Measured Variations of Downward Solar Radiation

NASA Astrophysics Data System (ADS)

Schwarz, M.; Folini, D.; Hakuba, M. Z.; Wild, M.

2017-12-01

When using time series of ground-based surface solar radiation (SSR) measurements in combination with gridded data, the spatial and temporal representativeness of the point observations must be considered. We use SSR data from surface observations and high-resolution (0.05°) satellite-derived data to infer the spatiotemporal representativeness of observations for monthly and longer time scales in Europe. The correlation analysis shows that the squared correlation coefficients (R2) between SSR times series decrease linearly with increasing distance between the surface observations. For deseasonalized monthly mean time series, R2 ranges from 0.85 for distances up to 25 km between the stations to 0.25 at distances of 500 km. A decorrelation length (i.e., the e-folding distance of R2) on the order of 400 km (with spread of 100-600 km) was found. R2 from correlations between point observations and colocated grid box area means determined from satellite data were found to be 0.80 for a 1° grid. To quantify the error which arises when using a point observation as a surrogate for the area mean SSR of larger surroundings, we calculated a spatial sampling error (SSE) for a 1° grid of 8 (3) W/m2 for monthly (annual) time series. The SSE based on a 1° grid, therefore, is of the same magnitude as the measurement uncertainty. The analysis generally reveals that monthly mean (or longer temporally aggregated) point observations of SSR capture the larger-scale variability well. This finding shows that comparing time series of SSR measurements with gridded data is feasible for those time scales.

Experimental realization of spatially separated entanglement with continuous variables using laser pulse trains

PubMed Central

Zhang, Yun; Okubo, Ryuhi; Hirano, Mayumi; Eto, Yujiro; Hirano, Takuya

2015-01-01

Spatially separated entanglement is demonstrated by interfering two high-repetition squeezed pulse trains. The entanglement correlation of the quadrature amplitudes between individual pulses is interrogated. It is characterized in terms of the sufficient inseparability criterion with an optimum result of in the frequency domain and in the time domain. The quantum correlation is also observed when the two measurement stations are separated by a physical distance of 4.5 m, which is sufficiently large to demonstrate the space-like separation, after accounting for the measurement time. PMID:26278478

Spatial characteristics of observed precipitation fields: A catalog of summer storms in Arizona, Volume 1

NASA Technical Reports Server (NTRS)

Fennessey, N. M.; Eagleson, P. S.; Qinliang, W.; Rodrigues-Iturbe, I.

1986-01-01

Eight years of summer raingage observations are analyzed for a dense, 93 gage, network operated by the U. S. Department of Agriculture, Agricultural Research Service, in their 150 sq km Walnut Gulch catchment near Tucson, Arizona. Storms are defined by the total depths collected at each raingage during the noon to noon period for which there was depth recorded at any of the gages. For each of the resulting 428 storms, the 93 gage depths are interpolated onto a dense grid and the resulting random field is anlyzed. Presented are: storm depth isohyets at 2 mm contour intervals, first three moments of point storm depth, spatial correlation function, spatial variance function, and the spatial distribution of total rainstorm depth.

COSMIC INFRARED BACKGROUND FLUCTUATIONS AND ZODIACAL LIGHT

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

Arendt, Richard G.; Kashlinsky, A.; Moseley, S. H.

We performed a specific observational test to measure the effect that the zodiacal light can have on measurements of the spatial fluctuations of the near-IR background. Previous estimates of possible fluctuations caused by zodiacal light have often been extrapolated from observations of the thermal emission at longer wavelengths and low angular resolution or from IRAC observations of high-latitude fields where zodiacal light is faint and not strongly varying with time. The new observations analyzed here target the COSMOS field at low ecliptic latitude where the zodiacal light intensity varies by factors of ∼2 over the range of solar elongations atmore » which the field can be observed. We find that the white-noise component of the spatial power spectrum of the background is correlated with the modeled zodiacal light intensity. Roughly half of the measured white noise is correlated with the zodiacal light, but a more detailed interpretation of the white noise is hampered by systematic uncertainties that are evident in the zodiacal light model. At large angular scales (≳100″) where excess power above the white noise is observed, we find no correlation of the power with the modeled intensity of the zodiacal light. This test clearly indicates that the large-scale power in the infrared background is not being caused by the zodiacal light.« less

Cosmic Infrared Background Fluctuations and Zodiacal Light

NASA Astrophysics Data System (ADS)

Arendt, Richard G.; Kashlinsky, A.; Moseley, S. H.; Mather, J.

2016-06-01

We performed a specific observational test to measure the effect that the zodiacal light can have on measurements of the spatial fluctuations of the near-IR background. Previous estimates of possible fluctuations caused by zodiacal light have often been extrapolated from observations of the thermal emission at longer wavelengths and low angular resolution or from IRAC observations of high-latitude fields where zodiacal light is faint and not strongly varying with time. The new observations analyzed here target the COSMOS field at low ecliptic latitude where the zodiacal light intensity varies by factors of ˜2 over the range of solar elongations at which the field can be observed. We find that the white-noise component of the spatial power spectrum of the background is correlated with the modeled zodiacal light intensity. Roughly half of the measured white noise is correlated with the zodiacal light, but a more detailed interpretation of the white noise is hampered by systematic uncertainties that are evident in the zodiacal light model. At large angular scales (≳100″) where excess power above the white noise is observed, we find no correlation of the power with the modeled intensity of the zodiacal light. This test clearly indicates that the large-scale power in the infrared background is not being caused by the zodiacal light.

Confronting weather and climate models with observational data from soil moisture networks over the United States

PubMed Central

Dirmeyer, Paul A.; Wu, Jiexia; Norton, Holly E.; Dorigo, Wouter A.; Quiring, Steven M.; Ford, Trenton W.; Santanello, Joseph A.; Bosilovich, Michael G.; Ek, Michael B.; Koster, Randal D.; Balsamo, Gianpaolo; Lawrence, David M.

2018-01-01

Four land surface models in uncoupled and coupled configurations are compared to observations of daily soil moisture from 19 networks in the conterminous United States to determine the viability of such comparisons and explore the characteristics of model and observational data. First, observations are analyzed for error characteristics and representation of spatial and temporal variability. Some networks have multiple stations within an area comparable to model grid boxes; for those we find that aggregation of stations before calculation of statistics has little effect on estimates of variance, but soil moisture memory is sensitive to aggregation. Statistics for some networks stand out as unlike those of their neighbors, likely due to differences in instrumentation, calibration and maintenance. Buried sensors appear to have less random error than near-field remote sensing techniques, and heat dissipation sensors show less temporal variability than other types. Model soil moistures are evaluated using three metrics: standard deviation in time, temporal correlation (memory) and spatial correlation (length scale). Models do relatively well in capturing large-scale variability of metrics across climate regimes, but poorly reproduce observed patterns at scales of hundreds of kilometers and smaller. Uncoupled land models do no better than coupled model configurations, nor do reanalyses outperform free-running models. Spatial decorrelation scales are found to be difficult to diagnose. Using data for model validation, calibration or data assimilation from multiple soil moisture networks with different types of sensors and measurement techniques requires great caution. Data from models and observations should be put on the same spatial and temporal scales before comparison. PMID:29645013

Confronting Weather and Climate Models with Observational Data from Soil Moisture Networks over the United States

NASA Technical Reports Server (NTRS)

Dirmeyer, Paul A.; Wu, Jiexia; Norton, Holly E.; Dorigo, Wouter A.; Quiring, Steven M.; Ford, Trenton W.; Santanello, Joseph A., Jr.; Bosilovich, Michael G.; Ek, Michael B.; Koster, Randal Dean;

Confronting weather and climate models with observational data from soil moisture networks over the United States.

PubMed

Dirmeyer, Paul A; Wu, Jiexia; Norton, Holly E; Dorigo, Wouter A; Quiring, Steven M; Ford, Trenton W; Santanello, Joseph A; Bosilovich, Michael G; Ek, Michael B; Koster, Randal D; Balsamo, Gianpaolo; Lawrence, David M

2016-04-01

Four land surface models in uncoupled and coupled configurations are compared to observations of daily soil moisture from 19 networks in the conterminous United States to determine the viability of such comparisons and explore the characteristics of model and observational data. First, observations are analyzed for error characteristics and representation of spatial and temporal variability. Some networks have multiple stations within an area comparable to model grid boxes; for those we find that aggregation of stations before calculation of statistics has little effect on estimates of variance, but soil moisture memory is sensitive to aggregation. Statistics for some networks stand out as unlike those of their neighbors, likely due to differences in instrumentation, calibration and maintenance. Buried sensors appear to have less random error than near-field remote sensing techniques, and heat dissipation sensors show less temporal variability than other types. Model soil moistures are evaluated using three metrics: standard deviation in time, temporal correlation (memory) and spatial correlation (length scale). Models do relatively well in capturing large-scale variability of metrics across climate regimes, but poorly reproduce observed patterns at scales of hundreds of kilometers and smaller. Uncoupled land models do no better than coupled model configurations, nor do reanalyses outperform free-running models. Spatial decorrelation scales are found to be difficult to diagnose. Using data for model validation, calibration or data assimilation from multiple soil moisture networks with different types of sensors and measurement techniques requires great caution. Data from models and observations should be put on the same spatial and temporal scales before comparison.

Method for spatially distributing a population

DOEpatents

Bright, Edward A [Knoxville, TN; Bhaduri, Budhendra L [Knoxville, TN; Coleman, Phillip R [Knoxville, TN; Dobson, Jerome E [Lawrence, KS

2007-07-24

A process for spatially distributing a population count within a geographically defined area can include the steps of logically correlating land usages apparent from a geographically defined area to geospatial features in the geographically defined area and allocating portions of the population count to regions of the geographically defined area having the land usages, according to the logical correlation. The process can also include weighing the logical correlation for determining the allocation of portions of the population count and storing the allocated portions within a searchable data store. The logically correlating step can include the step of logically correlating time-based land usages to geospatial features of the geographically defined area. The process can also include obtaining a population count for the geographically defined area, organizing the geographically defined area into a plurality of sectors, and verifying the allocated portions according to direct observation.

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

NASA Technical Reports Server (NTRS)

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.

Analysis of thrips distribution: application of spatial statistics and Kriging

Treesearch

John Aleong; Bruce L. Parker; Margaret Skinner; Diantha Howard

1991-01-01

Kriging is a statistical technique that provides predictions for spatially and temporally correlated data. Observations of thrips distribution and density in Vermont soils are made in both space and time. Traditional statistical analysis of such data assumes that the counts taken over space and time are independent, which is not necessarily true. Therefore, to analyze...

Global spectroscopic survey of cloud thermodynamic phase at high spatial resolution, 2005-2015

NASA Astrophysics Data System (ADS)

Thompson, David R.; Kahn, Brian H.; Green, Robert O.; Chien, Steve A.; Middleton, Elizabeth M.; Tran, Daniel Q.

2018-02-01

The distribution of ice, liquid, and mixed phase clouds is important for Earth's planetary radiation budget, impacting cloud optical properties, evolution, and solar reflectivity. Most remote orbital thermodynamic phase measurements observe kilometer scales and are insensitive to mixed phases. This under-constrains important processes with outsize radiative forcing impact, such as spatial partitioning in mixed phase clouds. To date, the fine spatial structure of cloud phase has not been measured at global scales. Imaging spectroscopy of reflected solar energy from 1.4 to 1.8 µm can address this gap: it directly measures ice and water absorption, a robust indicator of cloud top thermodynamic phase, with spatial resolution of tens to hundreds of meters. We report the first such global high spatial resolution survey based on data from 2005 to 2015 acquired by the Hyperion imaging spectrometer onboard NASA's Earth Observer 1 (EO-1) spacecraft. Seasonal and latitudinal distributions corroborate observations by the Atmospheric Infrared Sounder (AIRS). For extratropical cloud systems, just 25 % of variance observed at GCM grid scales of 100 km was related to irreducible measurement error, while 75 % was explained by spatial correlations possible at finer resolutions.

Spatial correlations of interdecadal variation in global surface temperatures

NASA Technical Reports Server (NTRS)

Mann, Michael E.; Park, Jeffrey

1993-01-01

We have analyzed spatial correlation patterns of interdecadal global surface temperature variability from an empirical perspective. Using multitaper coherence estimates from 140-yr records, we find that correlations between hemispheres are significant at about 95 percent confidence for nonrandomness for most of the frequency band in the 0.06-0.24 cyc/yr range. Coherence estimates of pairs of 100-yr grid-point temperature data series near 5-yr period reveal teleconnection patterns consistent with known patterns of ENSO variability. Significant correlated variability is observed near 15 year period, with the dominant teleconnection pattern largely confined to the Northern Hemisphere. Peak-to-peak Delta-T is at about 0.5 deg, with simultaneous warming and cooling of discrete patches on the earth's surface. A global average of this pattern would largely cancel.

Using SMOS brightness temperature and derived surface-soil moisture to characterize surface conditions and validate land surface models.

NASA Astrophysics Data System (ADS)

Polcher, Jan; Barella-Ortiz, Anaïs; Piles, Maria; Gelati, Emiliano; de Rosnay, Patricia

2017-04-01

The SMOS satellite, operated by ESA, observes the surface in the L-band. On continental surface these observations are sensitive to moisture and in particular surface-soil moisture (SSM). In this presentation we will explore how the observations of this satellite can be exploited over the Iberian Peninsula by comparing its results with two land surface models : ORCHIDEE and HTESSEL. Measured and modelled brightness temperatures show a good agreement in their temporal evolution, but their spatial structures are not consistent. An empirical orthogonal function analysis of the brightness temperature's error identifies a dominant structure over the south-west of the Iberian Peninsula which evolves during the year and is maximum in autumn and winter. Hypotheses concerning forcing-induced biases and assumptions made in the radiative transfer model are analysed to explain this inconsistency, but no candidate is found to be responsible for the weak spatial correlations. The analysis of spatial inconsistencies between modelled and measured TBs is important, as these can affect the estimation of geophysical variables and TB assimilation in operational models, as well as result in misleading validation studies. When comparing the surface-soil moisture of the models with the product derived operationally by ESA from SMOS observations similar results are found. The spatial correlation over the IP between SMOS and ORCHIDEE SSM estimates is poor (ρ 0.3). A single value decomposition (SVD) analysis of rainfall and SSM shows that the co-varying patterns of these variables are in reasonable agreement between both products. Moreover the first three SVD soil moisture patterns explain over 80% of the SSM variance simulated by the model while the explained fraction is only 52% of the remotely sensed values. These results suggest that the rainfall-driven soil moisture variability may not account for the poor spatial correlation between SMOS and ORCHIDEE products. Other reasons have to be sought to explain the poor agreement in spatial patterns between satellite derived and modelled SSM. This presentation will hopefully contribute to the discussion of how SMOS and other observations can be used to prepare, carry-out and exploit a field campaign over the Iberian Peninsula which aims at improving our understanding of semi-arid land surface processes.

Errors on interrupter tasks presented during spatial and verbal working memory performance are linearly linked to large-scale functional network connectivity in high temporal resolution resting state fMRI.

PubMed

Magnuson, Matthew Evan; Thompson, Garth John; Schwarb, Hillary; Pan, Wen-Ju; McKinley, Andy; Schumacher, Eric H; Keilholz, Shella Dawn

2015-12-01

The brain is organized into networks composed of spatially separated anatomical regions exhibiting coherent functional activity over time. Two of these networks (the default mode network, DMN, and the task positive network, TPN) have been implicated in the performance of a number of cognitive tasks. To directly examine the stable relationship between network connectivity and behavioral performance, high temporal resolution functional magnetic resonance imaging (fMRI) data were collected during the resting state, and behavioral data were collected from 15 subjects on different days, exploring verbal working memory, spatial working memory, and fluid intelligence. Sustained attention performance was also evaluated in a task interleaved between resting state scans. Functional connectivity within and between the DMN and TPN was related to performance on these tasks. Decreased TPN resting state connectivity was found to significantly correlate with fewer errors on an interrupter task presented during a spatial working memory paradigm and decreased DMN/TPN anti-correlation was significantly correlated with fewer errors on an interrupter task presented during a verbal working memory paradigm. A trend for increased DMN resting state connectivity to correlate to measures of fluid intelligence was also observed. These results provide additional evidence of the relationship between resting state networks and behavioral performance, and show that such results can be observed with high temporal resolution fMRI. Because cognitive scores and functional connectivity were collected on nonconsecutive days, these results highlight the stability of functional connectivity/cognitive performance coupling.

Spatial entanglement patterns and Einstein-Podolsky-Rosen steering in Bose-Einstein condensates.

PubMed

Fadel, Matteo; Zibold, Tilman; Décamps, Boris; Treutlein, Philipp

2018-04-27

Many-particle entanglement is a fundamental concept of quantum physics that still presents conceptual challenges. Although nonclassical states of atomic ensembles were used to enhance measurement precision in quantum metrology, the notion of entanglement in these systems was debated because the correlations among the indistinguishable atoms were witnessed by collective measurements only. Here, we use high-resolution imaging to directly measure the spin correlations between spatially separated parts of a spin-squeezed Bose-Einstein condensate. We observe entanglement that is strong enough for Einstein-Podolsky-Rosen steering: We can predict measurement outcomes for noncommuting observables in one spatial region on the basis of corresponding measurements in another region with an inferred uncertainty product below the Heisenberg uncertainty bound. This method could be exploited for entanglement-enhanced imaging of electromagnetic field distributions and quantum information tasks. Copyright © 2018 The Authors, some rights reserved; exclusive licensee American Association for the Advancement of Science. No claim to original U.S. Government Works.

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

PubMed Central

Zhu, Bangyan; Li, Jiancheng; Chu, Zhengwei; Tang, Wei; Wang, Bin; Li, Dawei

2016-01-01

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. PMID:27420066

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

PubMed

Zhu, Bangyan; Li, Jiancheng; Chu, Zhengwei; Tang, Wei; Wang, Bin; Li, Dawei

2016-07-12

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.

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

PubMed Central

Stieltjes, Bram; Weikert, Thomas; Gatidis, Sergios; Wiese, Mark; Wild, Damian; Lardinois, Didier

2017-01-01

The minimum apparent diffusion coefficient (ADCmin) derived from diffusion-weighted MRI (DW-MRI) and the maximum standardized uptake value (SUVmax) 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 ADCmin- and SUVmax-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 ADCmin- and SUVmax-voxels was 14.0 mm (average of two readers). Spatial mismatch (D > 12 mm) between ADCmin and SUVmax 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 SUVmax and ADCmin was seen, while a moderate negative linear relationship (r = −0.5) between SUVmax and ADCmin was observed in tumors with a spatial match (D ≤ 12 mm). In conclusion, spatial mismatch between ADCmin and SUVmax is found in a considerable percentage of patients. The spatial connection of the two parameters SUVmax and ADCmin has a crucial influence on their numeric correlation. PMID:29391862

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.

PubMed

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.

Comparison of Adjacency and Distance-Based Approaches for Spatial Analysis of Multimodal Traffic Crash Data

NASA Astrophysics Data System (ADS)

Gill, G.; Sakrani, T.; Cheng, W.; Zhou, J.

2017-09-01

Many studies have utilized the spatial correlations among traffic crash data to develop crash prediction models with the aim to investigate the influential factors or predict crash counts at different sites. The spatial correlation have been observed to account for heterogeneity in different forms of weight matrices which improves the estimation performance of models. But very rarely have the weight matrices been compared for the prediction accuracy for estimation of crash counts. This study was targeted at the comparison of two different approaches for modelling the spatial correlations among crash data at macro-level (County). Multivariate Full Bayesian crash prediction models were developed using Decay-50 (distance-based) and Queen-1 (adjacency-based) weight matrices for simultaneous estimation crash counts of four different modes: vehicle, motorcycle, bike, and pedestrian. The goodness-of-fit and different criteria for accuracy at prediction of crash count reveled the superiority of Decay-50 over Queen-1. Decay-50 was essentially different from Queen-1 with the selection of neighbors and more robust spatial weight structure which rendered the flexibility to accommodate the spatially correlated crash data. The consistently better performance of Decay-50 at prediction accuracy further bolstered its superiority. Although the data collection efforts to gather centroid distance among counties for Decay-50 may appear to be a downside, but the model has a significant edge to fit the crash data without losing the simplicity of computation of estimated crash count.

Spatial Characteristics of Tree Diameter Distributions in a Temperate Old-Growth Forest

PubMed Central

Zhao, Xiuhai; von Gadow, Klaus

2013-01-01

This contribution identifies spatial characteristics of tree diameter in a temperate forest in north-eastern China, based on a fully censused observational study area covering 500×600 m. Mark correlation analysis with three null hypothesis models was used to determine departure from expectations at different neighborhood distances. Tree positions are clumped at all investigated scales in all 37 studied species, while the diameters of most species are spatially negatively correlated, especially at short distances. Interestingly, all three cases showing short-distance attraction of dbh marks are associated with light-demanding shrub species. The short-distance attraction of dbh marks indicates spatially aggregated cohorts of stems of similar size. The percentage of species showing significant dbh suppression peaked at a 4 m distance under the heterogeneous Poisson model. At scales exceeding the peak distance, the percentage of species showing significant dbh suppression decreases sharply with increasing distances. The evidence from this large observational study shows that some of the variation of the spatial characteristics of tree diameters is related variations of topography and soil chemistry. However, an obvious interpretation of this result is still lacking. Thus, removing competitors surrounding the target trees is an effective way to avoid neighboring competition effects reducing the growth of valuable target trees in forest management practice. PMID:23527066

Spatial characteristics of tree diameter distributions in a temperate old-growth forest.

PubMed

Zhang, Chunyu; Wei, Yanbo; Zhao, Xiuhai; von Gadow, Klaus

2013-01-01

This contribution identifies spatial characteristics of tree diameter in a temperate forest in north-eastern China, based on a fully censused observational study area covering 500×600 m. Mark correlation analysis with three null hypothesis models was used to determine departure from expectations at different neighborhood distances. Tree positions are clumped at all investigated scales in all 37 studied species, while the diameters of most species are spatially negatively correlated, especially at short distances. Interestingly, all three cases showing short-distance attraction of dbh marks are associated with light-demanding shrub species. The short-distance attraction of dbh marks indicates spatially aggregated cohorts of stems of similar size. The percentage of species showing significant dbh suppression peaked at a 4 m distance under the heterogeneous Poisson model. At scales exceeding the peak distance, the percentage of species showing significant dbh suppression decreases sharply with increasing distances. The evidence from this large observational study shows that some of the variation of the spatial characteristics of tree diameters is related variations of topography and soil chemistry. However, an obvious interpretation of this result is still lacking. Thus, removing competitors surrounding the target trees is an effective way to avoid neighboring competition effects reducing the growth of valuable target trees in forest management practice.

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

NASA Astrophysics Data System (ADS)

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.

Linking parasite populations in hosts to parasite populations in space through Taylor's law and the negative binomial distribution

PubMed Central

Poulin, Robert; Lagrue, Clément

2017-01-01

The spatial distribution of individuals of any species is a basic concern of ecology. The spatial distribution of parasites matters to control and conservation of parasites that affect human and nonhuman populations. This paper develops a quantitative theory to predict the spatial distribution of parasites based on the distribution of parasites in hosts and the spatial distribution of hosts. Four models are tested against observations of metazoan hosts and their parasites in littoral zones of four lakes in Otago, New Zealand. These models differ in two dichotomous assumptions, constituting a 2 × 2 theoretical design. One assumption specifies whether the variance function of the number of parasites per host individual is described by Taylor's law (TL) or the negative binomial distribution (NBD). The other assumption specifies whether the numbers of parasite individuals within each host in a square meter of habitat are independent or perfectly correlated among host individuals. We find empirically that the variance–mean relationship of the numbers of parasites per square meter is very well described by TL but is not well described by NBD. Two models that posit perfect correlation of the parasite loads of hosts in a square meter of habitat approximate observations much better than two models that posit independence of parasite loads of hosts in a square meter, regardless of whether the variance–mean relationship of parasites per host individual obeys TL or NBD. We infer that high local interhost correlations in parasite load strongly influence the spatial distribution of parasites. Local hotspots could influence control and conservation of parasites. PMID:27994156

Slope topography-induced spatial variation correlation with observed building damages in Corso during the May 21, 2003, M w 6.8, Boumerdes earthquake (Algeria)

NASA Astrophysics Data System (ADS)

Messaoudi, Akila; Laouami, Nasser; Mezouar, Nourredine

2017-07-01

During the May 21, 2003 M w 6.8 Boumerdes earthquake, in the "Cité des 102 Logements" built on a hilltop, in Corso, heavy damages were observed: near the crest, a four-story RC building collapsed while others experienced severe structural damage and far from the crest, slight damage was observed. In the present paper, we perform a 2D slope topography seismic analysis and investigate its effects on the response at the plateau as well as the correlation with the observed damage distribution. A site-specific seismic scenario is used involving seismological, geological, and geotechnical data. 2D finite element numerical seismic study of the idealized Corso site subjected to vertical SV wave propagation is carried out by the universal code FLUSH. The results highlighted the main factors that explain the causes of block collapse, located 8-26 m far from the crest. These are as follows: (i) a significant spatial variation of ground response along the plateau due to the topographic effect, (ii) this spatial variation presents high loss of coherence, (iii) the seismic ground responses (PGA and response spectra) reach their maxima, and (iv) the fundamental frequency of the collapsed blocks coincides with the frequency content of the topographic component. For distances far from the crest where slight damages were observed, the topographic contribution is found negligible. On the basis of these results, it is important to take into account the topographic effect and the induced spatial variability in the seismic design of structures sited near the crest of slope.

Regression methods for spatially correlated data: an example using beetle attacks in a seed orchard

Treesearch

Preisler Haiganoush; Nancy G. Rappaport; David L. Wood

1997-01-01

We present a statistical procedure for studying the simultaneous effects of observed covariates and unmeasured spatial variables on responses of interest. The procedure uses regression type analyses that can be used with existing statistical software packages. An example using the rate of twig beetle attacks on Douglas-fir trees in a seed orchard illustrates the...

Human Plague Risk: Spatial-Temporal Models

NASA Technical Reports Server (NTRS)

Pinzon, Jorge E.

2010-01-01

This chpater reviews the use of spatial-temporal models in identifying potential risks of plague outbreaks into the human population. Using earth observations by satellites remote sensing there has been a systematic analysis and mapping of the close coupling between the vectors of the disease and climate variability. The overall result is that incidence of plague is correlated to positive El Nino/Southem Oscillation (ENSO).

Generation of Nonclassical Biphoton States through Cascaded Quantum Walks on a Nonlinear Chip

NASA Astrophysics Data System (ADS)

Solntsev, Alexander S.; Setzpfandt, Frank; Clark, Alex S.; Wu, Che Wen; Collins, Matthew J.; Xiong, Chunle; Schreiber, Andreas; Katzschmann, Fabian; Eilenberger, Falk; Schiek, Roland; Sohler, Wolfgang; Mitchell, Arnan; Silberhorn, Christine; Eggleton, Benjamin J.; Pertsch, Thomas; Sukhorukov, Andrey A.; Neshev, Dragomir N.; Kivshar, Yuri S.

2014-07-01

We demonstrate a nonlinear optical chip that generates photons with reconfigurable nonclassical spatial correlations. We employ a quadratic nonlinear waveguide array, where photon pairs are generated through spontaneous parametric down-conversion and simultaneously spread through quantum walks between the waveguides. Because of the quantum interference of these cascaded quantum walks, the emerging photons can become entangled over multiple waveguide positions. We experimentally observe highly nonclassical photon-pair correlations, confirming the high fidelity of on-chip quantum interference. Furthermore, we demonstrate biphoton-state tunability by spatial shaping and frequency tuning of the classical pump beam.

The relationship between hue discrimination and contrast sensitivity deficits in patients with diabetes mellitus.

PubMed

Trick, G L; Burde, R M; Gordon, M O; Santiago, J V; Kilo, C

1988-05-01

In an attempt to elucidate more fully the pathophysiologic basis of early visual dysfunction in patients with diabetes mellitus, color vision (hue discrimination) and spatial resolution (contrast sensitivity) were tested in diabetic patients with little or no retinopathy (n = 57) and age-matched visual normals (n = 35). Some evidence of visual dysfunction was observed in 37.8% of the diabetics with no retinopathy and 60.0% of the diabetics with background retinopathy. Although significant hue discrimination and contrast sensitivity deficits were observed in both groups of diabetic patients, contrast sensitivity was abnormal more frequently than hue discrimination. However, only 5.4% of the diabetics with no retinopathy and 10.0% of the diabetics with background retinopathy exhibited both abnormal hue discrimination and abnormal contrast sensitivity. Contrary to previous reports, blue-yellow (B-Y) and red-green (R-G) hue discrimination deficits were observed with approximately equal frequency. In the diabetic group, contrast sensitivity was reduced at all spatial frequencies tested, but for individual diabetic patients, significant deficits were only evident for the mid-range spatial frequencies. Among diabetic patients, the hue discrimination deficits, but not the contrast sensitivity abnormalities, were correlated with the patients' hemoglobin A1 level. A negative correlation between contrast sensitivity at 6.0 cpd and the duration of diabetes also was observed.

Water vapor variation and the effect of aerosols in China

NASA Astrophysics Data System (ADS)

Gui, Ke; Che, Huizheng; Chen, Quanliang; Zeng, Zhaoliang; Zheng, Yu; Long, Qichao; Sun, Tianze; Liu, Xinyu; Wang, Yaqiang; Liao, Tingting; Yu, Jie; Wang, Hong; Zhang, Xiaoye

2017-09-01

This study analyzes the annual and seasonal trends in precipitable water vapor (PWV) and surface temperature (Ts) over China from 1979 to 2015, and the relationships between PWV and Ts and between PWV and aerosol absorption optical depth (AAOD), using data from radiosonde stations, weather stations and multiple satellite observations. The results revealed a positive PWV trend between 1979 and 1999, and a negative PWV trend between 2000 and 2015. Analysis of the differences in the PWV trend among different stations types showed that the magnitude of the trends were in the order main urban stations > provincial capital stations > suburb stations, suggesting that anthropogenic activities have a strong influence on the PWV trend. The AAOD exhibited a significant positive trend in most regions of China from 2005 to 2015 (confidence level 95%). Using spatial correlation analysis, we showed that PWV trend derived from Moderate Resolution Imaging Spectroradiometer (MODIS) satellite observations is correlated with Ts, with an annual correlation coefficient of 0.596. In addition, the spatial correlation between PWV and AAOD showed a negative relationship, with the highest correlation coefficients of -0.76 and -0.71 observed in mid-eastern China and central northwest China, respectively, suggesting that the increase in AAOD in recent years may be one of the reasons for the decrease in PWV since the 2000s in China.

Developing Vs30 site-condition maps by combining observations with geologic and topographic constraints

USGS Publications Warehouse

Thompson, E.M.; Wald, D.J.

2012-01-01

Despite obvious limitations as a proxy for site amplification, the use of time-averaged shear-wave velocity over the top 30 m (VS30) remains widely practiced, most notably through its use as an explanatory variable in ground motion prediction equations (and thus hazard maps and ShakeMaps, among other applications). As such, we are developing an improved strategy for producing VS30 maps given the common observational constraints. Using the abundant VS30 measurements in Taiwan, we compare alternative mapping methods that combine topographic slope, surface geology, and spatial correlation structure. The different VS30 mapping algorithms are distinguished by the way that slope and geology are combined to define a spatial model of VS30. We consider the globally applicable slope-only model as a baseline to which we compare two methods of combining both slope and geology. For both hybrid approaches, we model spatial correlation structure of the residuals using the kriging-with-a-trend technique, which brings the map into closer agreement with the observations. Cross validation indicates that we can reduce the uncertainty of the VS30 map by up to 16% relative to the slope-only approach.

Accounting for spatial correlation errors in the assimilation of GRACE into hydrological models through localization

NASA Astrophysics Data System (ADS)

Khaki, M.; Schumacher, M.; Forootan, E.; Kuhn, M.; Awange, J. L.; van Dijk, A. I. J. M.

2017-10-01

Assimilation of terrestrial water storage (TWS) information from the Gravity Recovery And Climate Experiment (GRACE) satellite mission can provide significant improvements in hydrological modelling. However, the rather coarse spatial resolution of GRACE TWS and its spatially correlated errors pose considerable challenges for achieving realistic assimilation results. Consequently, successful data assimilation depends on rigorous modelling of the full error covariance matrix of the GRACE TWS estimates, as well as realistic error behavior for hydrological model simulations. In this study, we assess the application of local analysis (LA) to maximize the contribution of GRACE TWS in hydrological data assimilation. For this, we assimilate GRACE TWS into the World-Wide Water Resources Assessment system (W3RA) over the Australian continent while applying LA and accounting for existing spatial correlations using the full error covariance matrix. GRACE TWS data is applied with different spatial resolutions including 1° to 5° grids, as well as basin averages. The ensemble-based sequential filtering technique of the Square Root Analysis (SQRA) is applied to assimilate TWS data into W3RA. For each spatial scale, the performance of the data assimilation is assessed through comparison with independent in-situ ground water and soil moisture observations. Overall, the results demonstrate that LA is able to stabilize the inversion process (within the implementation of the SQRA filter) leading to less errors for all spatial scales considered with an average RMSE improvement of 54% (e.g., 52.23 mm down to 26.80 mm) for all the cases with respect to groundwater in-situ measurements. Validating the assimilated results with groundwater observations indicates that LA leads to 13% better (in terms of RMSE) assimilation results compared to the cases with Gaussian errors assumptions. This highlights the great potential of LA and the use of the full error covariance matrix of GRACE TWS estimates for improved data assimilation results.

Two-particle microrheology of quasi-2D viscous systems.

PubMed

Prasad, V; Koehler, S A; Weeks, Eric R

2006-10-27

We study the spatially correlated motions of colloidal particles in a quasi-2D system (human serum albumin protein molecules at an air-water interface) for different surface viscosities eta s. We observe a transition in the behavior of the correlated motion, from 2D interface dominated at high eta s to bulk fluid dependent at low eta s. The correlated motions can be scaled onto a master curve which captures the features of this transition. This master curve also characterizes the spatial dependence of the flow field of a viscous interface in response to a force. The scale factors used for the master curve allow for the calculation of the surface viscosity eta s that can be compared to one-particle measurements.

Improving the City-scale Emission Inventory of Anthropogenic Air Pollutants: A Case Study of Nanjing

NASA Astrophysics Data System (ADS)

Qiu, L.; Zhao, Y.; Xu, R.; Xie, F.; Wang, H.; Qin, H.; Wu, X.; Zhang, J.

2014-12-01

To evaluate the improvement of city-scale emission inventory, a high-resolution emission inventory of air pollutants for Nanjing is first developed combining detailed source information, and then justified through quantitative analysis with observations. The best available domestic emission factors and unit-/facility-based activity level data were compiled based on a thorough field survey on major emission sources. Totally 1089 individual emission sources were identified as point sources and all the emission-related parameters including burner type, combustion technology, fuel quality, and removal efficiency of pollution control devices, are carefully investigated and analyzed. Some new data such as detailed information of city fueling-gas stations, construction sites, monthly activity level, data from continuous emission monitoring systems and traffic flow information were combined to improve spatiotemporal distribution of this inventory. For SO2, NOX and CO, good spatial correlations were found between ground observation (9 state controlling air sampling sites in Nanjing) and city-scale emission inventory (R2=0.34, 0.38 and 0.74, respectively). For TSP, PM10 and PM2.5, however, poorer correlation was found due to relatively weaker accuracy in emission estimation and spatial distribution of road dust. The mixing ratios between specific pollutants including OC/EC, BC/CO and CO2/CO, are well correlated between those from ground observation and emission. Compared to MEIC (Multi-resolution Emission Inventory for China), there is a better spatial consistence between this city-scale emission inventory and NO2 measured by OMI (Ozone Monitoring Instrument). In particular, the city-scale emission inventory still correlated well with satellite observations (R2=0.28) while the regional emission inventory showed little correlation with satellite observations (R2=0.09) when grids containing power plants are excluded. It thus confirms the improvement of city-scale emission inventory on industrial and transportation sources other than big power plants. Through the inventory evaluation, the necessity to develop high-resolution emission inventory with comprehensive emission source information is revealed for atmospheric science studies and air quality improvement at local scale.

Spatial Characteristics of F/A-18 Vertical Tail Buffet Pressures Measured in Flight

NASA Technical Reports Server (NTRS)

Moses, Robert W.; Shah, Gautam H.

1998-01-01

Buffeting is an aeroelastic phenomenon which plagues high performance aircraft, especially those with twin vertical tails, at high angles of attack. Previous wind-tunnel and flight tests were conducted to characterize the buffet loads on the vertical tails by measuring surface pressures, bending moments, and accelerations. Following these tests, buffeting estimates were computed using the measured buffet pressures and compared to the measured responses. The estimates did not match the measured data because the assumed spatial correlation of the buffet pressures was not correct. A better understanding of the partial (spatial) correlation of the differential buffet pressures on the tail was necessary to improve the buffeting estimates. Several wind-tunnel investigations were conducted for this purpose. When combined and compared, the results of these tests show that the partial correlation depends on and scales with flight conditions. One of the remaining questions is whether the windtunnel data is consistent with flight data. Presented herein, cross-spectra and coherence functions calculated from pressures that were measured on the high alpha research vehicle (HARV) indicate that the partial correlation of the buffet pressures in flight agrees with the partial correlation observed in the wind tunnel.

Cosmic Infrared Background Fluctuations and Zodiacal Light

NASA Technical Reports Server (NTRS)

Arendt, Richard G.; Kashlinsky, A.; Moseley, S. H.; Mather, J.

2017-01-01

We performed a specific observational test to measure the effect that the zodiacal light can have on measurements of the spatial fluctuations of the near-IR (near-infrared)background. Previous estimates of possible fluctuations caused by zodiacal light have often been extrapolated from observations of the thermal emission at longer wavelengths and low angular resolution or from IRAC (Infrared Array Camera) observations of high-latitude fields where zodiacal light is faint and not strongly varying with time. The new observations analyzed here target the COSMOS (Cosmic Evolution Survey) field at low ecliptic latitude where the zodiacal light intensity varies by factors of approximately 2 over the range of solar elongations at which the field can be observed. We find that the white-noise component of the spatial power spectrum of the background is correlated with the modeled zodiacal light intensity. Roughly half of the measured white noise is correlated with the zodiacal light, but a more detailed interpretation of the white noise is hampered by systematic uncertainties that are evident in the zodiacal light model. At large angular scales (greater than or approximately equal to 100 arcseconds) where excess power above the white noise is observed, we find no correlation of the power with the modeled intensity of the zodiacal light. This test clearly indicates that the large-scale power in the infrared background is not being caused by the zodiacal light.

Spatial and temporal agreement in climate model simulations of the Interdecadal Pacific Oscillation

DOE PAGES

Henley, Benjamin J.; Meehl, Gerald; Power, Scott B.; ...

2017-01-31

Accelerated warming and hiatus periods in the long-term rise of Global Mean Surface Temperature (GMST) have, in recent decades, been associated with the Interdecadal Pacific Oscillation (IPO). Critically, decadal climate prediction relies on the skill of state-of-the-art climate models to reliably represent these low-frequency climate variations. We undertake a systematic evaluation of the simulation of the IPO in the suite of Coupled Model Intercomparison Project 5 (CMIP5) models. We track the IPO in pre-industrial (control) and all-forcings (historical) experiments using the IPO tripole index (TPI). The TPI is explicitly aligned with the observed spatial pattern of the IPO, and circumventsmore » assumptions about the nature of global warming. We find that many models underestimate the ratio of decadal-to-total variance in sea surface temperatures (SSTs). However, the basin-wide spatial pattern of positive and negative phases of the IPO are simulated reasonably well, with spatial pattern correlation coefficients between observations and models spanning the range 0.4–0.8. Deficiencies are mainly in the extratropical Pacific. Models that better capture the spatial pattern of the IPO also tend to more realistically simulate the ratio of decadal to total variance. Of the 13% of model centuries that have a fractional bias in the decadal-to-total TPI variance of 0.2 or less, 84% also have a spatial pattern correlation coefficient with the observed pattern exceeding 0.5. This result is highly consistent across both IPO positive and negative phases. This is evidence that the IPO is related to one or more inherent dynamical mechanisms of the climate system.« less

Spatial and temporal agreement in climate model simulations of the Interdecadal Pacific Oscillation

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

Henley, Benjamin J.; Meehl, Gerald; Power, Scott B.

Accelerated warming and hiatus periods in the long-term rise of Global Mean Surface Temperature (GMST) have, in recent decades, been associated with the Interdecadal Pacific Oscillation (IPO). Critically, decadal climate prediction relies on the skill of state-of-the-art climate models to reliably represent these low-frequency climate variations. We undertake a systematic evaluation of the simulation of the IPO in the suite of Coupled Model Intercomparison Project 5 (CMIP5) models. We track the IPO in pre-industrial (control) and all-forcings (historical) experiments using the IPO tripole index (TPI). The TPI is explicitly aligned with the observed spatial pattern of the IPO, and circumventsmore » assumptions about the nature of global warming. We find that many models underestimate the ratio of decadal-to-total variance in sea surface temperatures (SSTs). However, the basin-wide spatial pattern of positive and negative phases of the IPO are simulated reasonably well, with spatial pattern correlation coefficients between observations and models spanning the range 0.4–0.8. Deficiencies are mainly in the extratropical Pacific. Models that better capture the spatial pattern of the IPO also tend to more realistically simulate the ratio of decadal to total variance. Of the 13% of model centuries that have a fractional bias in the decadal-to-total TPI variance of 0.2 or less, 84% also have a spatial pattern correlation coefficient with the observed pattern exceeding 0.5. This result is highly consistent across both IPO positive and negative phases. This is evidence that the IPO is related to one or more inherent dynamical mechanisms of the climate system.« less

Observational Constraints on the Identification of Shallow Lunar Magmatism: Insights from Floor-Fractured Craters

NASA Technical Reports Server (NTRS)

Jozwiak, L. M.; Head, J. W., III; Neumann, G. A.; Wilson, L.

2016-01-01

Floor-fractured craters are a class of lunar crater hypothesized to form in response to the emplacement of a shallow magmatic intrusion beneath the crater floor. The emplacement of a shallow magmatic body should result in a positive Bouguer anomaly relative to unaltered complex craters, a signal which is observed for the average Bouguer anomaly interior to the crater walls. We observe the Bouguer anomaly of floor-fractured craters on an individual basis using the unfiltered Bouguer gravity solution from GRAIL and also a degree 100-600 band-filtered Bouguer gravity solution. The low-magnitude of anomalies arising from shallow magmatic intrusions makes identification using unfiltered Bouguer gravity solutions inconclusive. The observed anomalies in the degree 100-600 Bouguer gravity solution are spatially heterogeneous, although there is spatial correlation between volcanic surface morphologies and positive Bouguer anomalies. We interpret these observations to mean that the spatial heterogeneity observed in the Bouguer signal is the result of variable degrees of magmatic degassing within the intrusions.

Statistical and Economic Techniques for Site-specific Nematode Management.

PubMed

Liu, Zheng; Griffin, Terry; Kirkpatrick, Terrence L

2014-03-01

Recent advances in precision agriculture technologies and spatial statistics allow realistic, site-specific estimation of nematode damage to field crops and provide a platform for the site-specific delivery of nematicides within individual fields. This paper reviews the spatial statistical techniques that model correlations among neighboring observations and develop a spatial economic analysis to determine the potential of site-specific nematicide application. The spatial econometric methodology applied in the context of site-specific crop yield response contributes to closing the gap between data analysis and realistic site-specific nematicide recommendations and helps to provide a practical method of site-specifically controlling nematodes.

Spatial correlation in the ambient core noise field of a turbofan engine.

PubMed

Miles, Jeffrey Hilton

2012-06-01

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 NO(x) 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.

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

PubMed

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.

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

USGS Publications Warehouse

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 3m 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.

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

USGS Publications Warehouse

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.

Generating daily high spatial land surface temperatures by combining ASTER and MODIS land surface temperature products for environmental process monitoring.

PubMed

Wu, Mingquan; Li, Hua; Huang, Wenjiang; Niu, Zheng; Wang, Changyao

2015-08-01

There is a shortage of daily high spatial land surface temperature (LST) data for use in high spatial and temporal resolution environmental process monitoring. To address this shortage, this work used the Spatial and Temporal Adaptive Reflectance Fusion Model (STARFM), Enhanced Spatial and Temporal Adaptive Reflectance Fusion Model (ESTARFM), and the Spatial and Temporal Data Fusion Approach (STDFA) to estimate high spatial and temporal resolution LST by combining Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) LST and Moderate Resolution Imaging Spectroradiometer (MODIS) LST products. The actual ASTER LST products were used to evaluate the precision of the combined LST images using the correlation analysis method. This method was tested and validated in study areas located in Gansu Province, China. The results show that all the models can generate daily synthetic LST image with a high correlation coefficient (r) of 0.92 between the synthetic image and the actual ASTER LST observations. The ESTARFM has the best performance, followed by the STDFA and the STARFM. Those models had better performance in desert areas than in cropland. The STDFA had better noise immunity than the other two models.

Spatial distribution of ammonia-oxidizing bacteria and archaea across a 44-hectare farm related to ecosystem functioning

PubMed Central

Wessén, Ella; Söderström, Mats; Stenberg, Maria; Bru, David; Hellman, Maria; Welsh, Allana; Thomsen, Frida; Klemedtson, Leif; Philippot, Laurent; Hallin, Sara

2011-01-01

Characterization of spatial patterns of functional microbial communities could facilitate the understanding of the relationships between the ecology of microbial communities, the biogeochemical processes they perform and the corresponding ecosystem functions. Because of the important role the ammonia-oxidizing bacteria (AOB) and archaea (AOA) have in nitrogen cycling and nitrate leaching, we explored the spatial distribution of their activity, abundance and community composition across a 44-ha large farm divided into an organic and an integrated farming system. The spatial patterns were mapped by geostatistical modeling and correlations to soil properties and ecosystem functioning in terms of nitrate leaching were determined. All measured community components for both AOB and AOA exhibited spatial patterns at the hectare scale. The patchy patterns of community structures did not reflect the farming systems, but the AOB community was weakly related to differences in soil pH and moisture, whereas the AOA community to differences in soil pH and clay content. Soil properties related differently to the size of the communities, with soil organic carbon and total nitrogen correlating positively to AOB abundance, while clay content and pH showed a negative correlation to AOA abundance. Contrasting spatial patterns were observed for the abundance distributions of the two groups indicating that the AOB and AOA may occupy different niches in agro-ecosystems. In addition, the two communities correlated differently to community and ecosystem functions. Our results suggest that the AOA, not the AOB, were contributing to nitrate leaching at the site by providing substrate for the nitrite oxidizers. PMID:21228891

Representation of spatial cross correlations in large stochastic seasonal streamflow models

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

Oliveira, G.C.; Kelman, J.; Pereira, M.V.F.

1988-05-01

Pereira et al. (1984) presented a special disaggregation procedure for generating cross-correlated monthly flows at many sites while using what are essentially univariate disaggregation models for the flows at each site. This was done by using a nonparametric procedure for constructing residual innovations or noise vectors with cross-correlated components. This note considers the theoretical underpinnings of that streamflow disaggregation procedure and a proposed variation and their ability to reproduce the observed historical cross correlations among concurrent monthly flows at nine Brazilian stations.

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

NASA Astrophysics Data System (ADS)

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.

VizieR Online Data Catalog: W49A JCMT Spectral Legacy Survey spectroscopy (Nagy+, 2015)

NASA Astrophysics Data System (ADS)

Nagy, Z.; van der Tak, F. F. S.; Fuller, G. A.; Plume, R.

2015-08-01

We carried out the SLS observations using the 16-receptor (spatial pixel) Heterodyne Array Receiver Programme B (HARP-B, 325-375GHz) and the Auto-Correlation Spectral Imaging System (ACSIS) correlator at the James Clerk Maxwell Telescope1 (JCMT) on Mauna Kea, Hawaii. We carried out the observations in jiggle position switch mode, sampled every 7.5" for a 2x2-arcmin field centered on RA=19:10:13.4; DE=09:06:14 (J2000). (1 data file).

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

PubMed

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

2018-08-01

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

Computing aerodynamic sound using advanced statistical turbulence theories

NASA Technical Reports Server (NTRS)

Hecht, A. M.; Teske, M. E.; Bilanin, A. J.

1981-01-01

It is noted that the calculation of turbulence-generated aerodynamic sound requires knowledge of the spatial and temporal variation of Q sub ij (xi sub k, tau), the two-point, two-time turbulent velocity correlations. A technique is presented to obtain an approximate form of these correlations based on closure of the Reynolds stress equations by modeling of higher order terms. The governing equations for Q sub ij are first developed for a general flow. The case of homogeneous, stationary turbulence in a unidirectional constant shear mean flow is then assumed. The required closure form for Q sub ij is selected which is capable of qualitatively reproducing experimentally observed behavior. This form contains separation time dependent scale factors as parameters and depends explicitly on spatial separation. The approximate forms of Q sub ij are used in the differential equations and integral moments are taken over the spatial domain. The velocity correlations are used in the Lighthill theory of aerodynamic sound by assuming normal joint probability.

Non-flow correlations and elliptic flow fluctuations in Au+Au collisions at sNN=200 GeV

NASA Astrophysics Data System (ADS)

Alver, B.; Back, B. B.; Baker, M. D.; Ballintijn, M.; Barton, D. S.; Betts, R. R.; Bickley, A. A.; Bindel, R.; Busza, W.; Carroll, A.; Chai, Z.; Decowski, M. P.; García, E.; Gburek, T.; George, N.; Gulbrandsen, K.; Halliwell, C.; Hamblen, J.; Hauer, M.; Henderson, C.; Hofman, D. J.; Hollis, R. S.; Hołyński, R.; Holzman, B.; Iordanova, A.; Johnson, E.; Kane, J. L.; Khan, N.; Kulinich, P.; Kuo, C. M.; Li, W.; Lin, W. T.; Loizides, C.; Manly, S.; Mignerey, A. C.; Nouicer, R.; Olszewski, A.; Pak, R.; Reed, C.; Roland, C.; Roland, G.; Sagerer, J.; Seals, H.; Sedykh, I.; Smith, C. E.; Stankiewicz, M. A.; Steinberg, P.; Stephans, G. S. F.; Sukhanov, A.; Tonjes, M. B.; Trzupek, A.; Vale, C.; van Nieuwenhuizen, G. J.; Vaurynovich, S. S.; Verdier, R.; Veres, G. I.; Walters, P.; Wenger, E.; Wolfs, F. L. H.; Wosiek, B.; Woźniak, K.; Wysłouch, B.

2010-03-01

This article presents results on event-by-event elliptic flow fluctuations in Au+Au collisions at sNN= 200 GeV, where the contribution from non-flow correlations has been subtracted. An analysis method is introduced to measure non-flow correlations, relying on the assumption that non-flow correlations are most prominent at short ranges (|Δη|<2). Assuming that non-flow correlations are of the order that is observed in p+p collisions for long-range correlations (|Δη|>2), relative elliptic flow fluctuations of approximately 30-40% are observed. These results are consistent with predictions based on spatial fluctuations of the participating nucleons in the initial nuclear overlap region. It is found that the long-range non-flow correlations in Au+Au collisions would have to be more than an order of magnitude stronger compared to the p+p data to lead to the observed azimuthal anisotropy fluctuations with no intrinsic elliptic flow fluctuations.

The neural correlates of highly iconic structures and topographic discourse in French Sign Language as observed in six hearing native signers.

PubMed

Courtin, C; Hervé, P-Y; Petit, L; Zago, L; Vigneau, M; Beaucousin, V; Jobard, G; Mazoyer, B; Mellet, E; Tzourio-Mazoyer, N

2010-09-01

"Highly iconic" structures in Sign Language enable a narrator to act, switch characters, describe objects, or report actions in four-dimensions. This group of linguistic structures has no real spoken-language equivalent. Topographical descriptions are also achieved in a sign-language specific manner via the use of signing-space and spatial-classifier signs. We used functional magnetic resonance imaging (fMRI) to compare the neural correlates of topographic discourse and highly iconic structures in French Sign Language (LSF) in six hearing native signers, children of deaf adults (CODAs), and six LSF-naïve monolinguals. LSF materials consisted of videos of a lecture excerpt signed without spatially organized discourse or highly iconic structures (Lect LSF), a tale signed using highly iconic structures (Tale LSF), and a topographical description using a diagrammatic format and spatial-classifier signs (Topo LSF). We also presented texts in spoken French (Lect French, Tale French, Topo French) to all participants. With both languages, the Topo texts activated several different regions that are involved in mental navigation and spatial working memory. No specific correlate of LSF spatial discourse was evidenced. The same regions were more activated during Tale LSF than Lect LSF in CODAs, but not in monolinguals, in line with the presence of signing-space structure in both conditions. Motion processing areas and parts of the fusiform gyrus and precuneus were more active during Tale LSF in CODAs; no such effect was observed with French or in LSF-naïve monolinguals. These effects may be associated with perspective-taking and acting during personal transfers. 2010 Elsevier Inc. All rights reserved.

Spatial Reasoning and Understanding the Particulate Nature of Matter: A Middle School Perspective

NASA Astrophysics Data System (ADS)

Cole, Merryn L.

This dissertation employed a mixed-methods approach to examine the relationship between spatial reasoning ability and understanding of chemistry content for both middle school students and their science teachers. Spatial reasoning has been linked to success in learning STEM subjects (Wai, Lubinski, & Benbow, 2009). Previous studies have shown a correlation between understanding of chemistry content and spatial reasoning ability (e.g., Pribyl & Bodner, 1987; Wu & Shah, 2003: Stieff, 2013), raising the importance of developing the spatial reasoning ability of both teachers and students. Few studies examine middle school students' or in-service middle school teachers' understanding of chemistry concepts or its relation to spatial reasoning ability. The first paper in this dissertation addresses the quantitative relationship between mental rotation, a type of spatial reasoning ability, and understanding a fundamental concept in chemistry, the particulate nature of matter. The data showed a significant, positive correlation between scores on the Purdue Spatial Visualization Test of Rotations (PSVT; Bodner & Guay, 1997) and the Particulate Nature of Matter Assessment (ParNoMA; Yezierski, 2003) for middle school students prior to and after chemistry instruction. A significant difference in spatial ability among students choosing different answer choices on ParNoMA questions was also found. The second paper examined the ways in which students of different spatial abilities talked about matter and chemicals differently. Students with higher spatial ability tended to provide more of an explanation, though not necessarily in an articulate matter. In contrast, lower spatial ability students tended to use any keywords that seemed relevant, but provided little or no explanation. The third paper examined the relationship between mental reasoning and understanding chemistry for middle school science teachers. Similar to their students, a significant, positive correlation between scores on the PSVT and the ParNoMA was observed. Teachers who used consistent reasoning in providing definitions and examples for matter and chemistry tended to have higher spatial abilities than those teachers who used inconsistent reasoning on the same questions. This is the first study to explore the relationship between spatial reasoning and understanding of chemistry concepts at the middle school level. Though we are unable to infer cause and effect relationship from correlational data, these results illustrate a need to further investigate this relationship as well as identify the relationship between different spatial abilities (not just mental rotation) and other chemistry concepts.

Accounting for irregular support in spatial interpolation - analysing the effect of using alternative distance measures

NASA Astrophysics Data System (ADS)

Skøien, J. O.; Gottschalk, L.; Leblois, E.

2009-04-01

Whereas geostatistical and objective methods mostly have been developed for observations with point support or a regular support, e.g. runoff related data can be assumed to have an irregular support in space, and sometimes also a temporal support. The correlations between observations and between observations and the prediction location are found through an integration of a point variogram or point correlation function, a method known as regularisation. Being a relatively simple method for observations with equal and regular support, it can be computationally demanding if the observations have irregular support. With improved speed of computers, solving such integrations has become easier, but there can still be numerical problems that are not easily solved even with high-resolution computations. This can particularly be a problem in hydrological sciences where catchments are overlapping, the correlations are high, and small numerical errors can give ill-posed covariance matrices. The problem increases with increasing number of spatial and/or temporal dimensions. Gottschalk [1993a; 1993b] suggested to replace the integration by a Taylor expansion, hence reducing the computation time considerably, and also expecting less numerical problems with the covariance matrices. In practice, the integrated correlation/semivariance between observations are replaced by correlations/semivariances using the so called Ghosh-distance. Although Gottschalk and collaborators have used the Ghosh-distance also in other papers [Sauquet, et al., 2000a; Sauquet, et al., 2000b], the properties of the simplification have not been examined in detail. Hence, we will here analyse the replacement of the integration by the use of Ghosh-distances, both in sense of the ability to reproduce regularised semivariogram and correlation values, and the influence on the final interpolated maps. Comparisons will be performed both for real observations with a support (hydrological data) and for more hypothetical observations with regular supports where analytical expressions for the regularised semivariances/correlations in some cases can be derived. The results indicate that the simplification is useful for spatial interpolation when the support of the observations has to be taken into account. The difference in semivariogram value or correlation value between the simplified method and the full integration is limited on short distances, increasing for larger distances. However, this is to some degree taken into account while fitting a model for the point process, so that the results after interpolation are less affected by the simplification. The method is of particular use if computation time is of importance, e.g. in the case of real-time mapping procedures. Gottschalk, L. (1993a) Correlation and covariance of runoff, Stochastic Hydrology and Hydraulics, 7, 85-101. Gottschalk, L. (1993b) Interpolation of runoff applying objective methods, Stochastic Hydrology and Hydraulics, 7, 269-281. Sauquet, E., L. Gottschalk, and E. Leblois (2000a) Mapping average annual runoff: a hierarchical approach applying a stochastic interpolation scheme, Hydrological Sciences Journal, 45, 799-815. Sauquet, E., I. Krasovskaia, and E. Leblois (2000b) Mapping mean monthly runoff pattern using EOF analysis, Hydrology and Earth System Sciences, 4, 79-93.

Emotional cues enhance the attentional effects on spatial and temporal resolution.

PubMed

Bocanegra, Bruno R; Zeelenberg, René

2011-12-01

In the present study, we demonstrated that the emotional significance of a spatial cue enhances the effect of covert attention on spatial and temporal resolution (i.e., our ability to discriminate small spatial details and fast temporal flicker). Our results indicated that fearful face cues, as compared with neutral face cues, enhanced the attentional benefits in spatial resolution but also enhanced the attentional deficits in temporal resolution. Furthermore, we observed that the overall magnitudes of individuals' attentional effects correlated strongly with the magnitude of the emotion × attention interaction effect. Combined, these findings provide strong support for the idea that emotion enhances the strength of a cue's attentional response.

An observational assessment of the influence of mesoscale and submesoscale heterogeneity on ocean biogeochemical reactions

NASA Astrophysics Data System (ADS)

Martin, Adrian P.; Lévy, Marina; van Gennip, Simon; Pardo, Silvia; Srokosz, Meric; Allen, John; Painter, Stuart C.; Pidcock, Roz

2015-09-01

Numerous observations demonstrate that considerable spatial variability exists in components of the marine planktonic ecosystem at the mesoscale and submesoscale (100 km-1 km). The causes and consequences of physical processes at these scales ("eddy advection") influencing biogeochemistry have received much attention. Less studied, the nonlinear nature of most ecological and biogeochemical interactions means that such spatial variability has consequences for regional estimates of processes including primary production and grazing, independent of the physical processes. This effect has been termed "eddy reactions." Models remain our most powerful tools for extrapolating hypotheses for biogeochemistry to global scales and to permit future projections. The spatial resolution of most climate and global biogeochemical models means that processes at the mesoscale and submesoscale are poorly resolved. Modeling work has previously suggested that the neglected eddy reactions may be almost as large as the mean field estimates in some cases. This study seeks to quantify the relative size of eddy and mean reactions observationally, using in situ and satellite data. For primary production, grazing, and zooplankton mortality the eddy reactions are between 7% and 15% of the mean reactions. These should be regarded as preliminary estimates to encourage further observational estimates and not taken as a justification for ignoring eddy reactions. Compared to modeling estimates, there are inconsistencies in the relative magnitude of eddy reactions and in correlations which are a major control on their magnitude. One possibility is that models exhibit much stronger spatial correlations than are found in reality, effectively amplifying the magnitude of eddy reactions.

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

NASA Astrophysics Data System (ADS)

Porzycki, Jakub; WÄ s, Jarosław; Hedayatifar, Leila; Hassanibesheli, Forough; Kułakowski, Krzysztof

2017-08-01

The aim of the paper is an analysis of self-organization patterns observed in the unidirectional flow of pedestrians. On the basis of experimental data from Zhang et al. [J. Zhang et al., J. Stat. Mech. (2011) P06004, 10.1088/1742-5468/2011/06/P06004], we analyze the mutual positions and velocity correlations between pedestrians when walking along a corridor. The angular and spatial dependencies of the mutual positions reveal a spatial structure that remains stable during the crowd motion. This structure differs depending on the value of n , for the consecutive n th -nearest-neighbor position set. The preferred position for the first-nearest neighbor is on the side of the pedestrian, while for further neighbors, this preference shifts to the axis of movement. The velocity correlations vary with the angle formed by the pair of neighboring pedestrians and the direction of motion and with the time delay between pedestrians' movements. The delay dependence of the correlations shows characteristic oscillations, produced by the velocity oscillations when striding; however, a filtering of the main frequency of individual striding out reduces the oscillations only partially. We conclude that pedestrians select their path directions so as to evade the necessity of continuously adjusting their speed to their neighbors'. They try to keep a given distance, but follow the person in front of them, as well as accepting and observing pedestrians on their sides. Additionally, we show an empirical example that illustrates the shape of a pedestrian's personal space during movement.

Emergent Archetype Hydrological-Biogeochemical Response Patterns in Heterogeneous Catchments

NASA Astrophysics Data System (ADS)

Jawitz, J. W.; Gall, H. E.; Rao, P.

2013-12-01

What can spatiotemporally integrated patterns observed in stream hydrologic and biogeochemical signals generated in response to transient hydro-climatic and anthropogenic forcing tell us about the interactions between spatially heterogeneous soil-mediated hydrological and biogeochemical processes? We seek to understand how the spatial structure of solute sources coupled with hydrologic responses affect observed concentration-discharge (C-Q) patterns. These patterns are expressions of the spatiotemporal structure of solute loads exported from managed catchments, and their likely ecological consequences manifested in receiving water bodies (e.g., wetlands, rivers, lakes, and coastal waters). We investigated the following broad questions: (1) How does the correlation between flow-generating areas and biogeochemical source areas across a catchment evolve under stochastic hydro-climatic forcing? (2) What are the feasible hydrologic and biogeochemical responses that lead to the emergence of the observed archetype C-Q patterns? and; (3) What implications do these coupled dynamics have for catchment monitoring and implementation of management practices? We categorize the observed temporal signals into three archetypical C-Q patterns: dilution; accretion, and constant concentration. We introduce a parsimonious stochastic model of heterogeneous catchments, which act as hydrologic and biogeochemical filters, to examine the relationship between spatial heterogeneity and temporal history of solute export signals. The core concept of the modeling framework is considering the types and degree of spatial correlation between solute source zones and flow generating zones, and activation of different portions of the catchments during rainfall events. Our overarching hypothesis is that each of the archetype C-Q patterns can be generated by explicitly linking landscape-scale hydrologic responses and spatial distributions of solute source properties within a catchment. The model simulations reproduce the three major C-Q patterns observed in published data, offering valuable insight into coupled catchment processes. The findings have important implications for effective catchment management for water quality improvement, and stream monitoring strategies.

Functional Additive Mixed Models

PubMed Central

Scheipl, Fabian; Staicu, Ana-Maria; Greven, Sonja

2014-01-01

We propose an extensive framework for additive regression models for correlated functional responses, allowing for multiple partially nested or crossed functional random effects with flexible correlation structures for, e.g., spatial, temporal, or longitudinal functional data. Additionally, our framework includes linear and nonlinear effects of functional and scalar covariates that may vary smoothly over the index of the functional response. It accommodates densely or sparsely observed functional responses and predictors which may be observed with additional error and includes both spline-based and functional principal component-based terms. Estimation and inference in this framework is based on standard additive mixed models, allowing us to take advantage of established methods and robust, flexible algorithms. We provide easy-to-use open source software in the pffr() function for the R-package refund. Simulations show that the proposed method recovers relevant effects reliably, handles small sample sizes well and also scales to larger data sets. Applications with spatially and longitudinally observed functional data demonstrate the flexibility in modeling and interpretability of results of our approach. PMID:26347592

Functional Additive Mixed Models.

PubMed

Scheipl, Fabian; Staicu, Ana-Maria; Greven, Sonja

2015-04-01

We propose an extensive framework for additive regression models for correlated functional responses, allowing for multiple partially nested or crossed functional random effects with flexible correlation structures for, e.g., spatial, temporal, or longitudinal functional data. Additionally, our framework includes linear and nonlinear effects of functional and scalar covariates that may vary smoothly over the index of the functional response. It accommodates densely or sparsely observed functional responses and predictors which may be observed with additional error and includes both spline-based and functional principal component-based terms. Estimation and inference in this framework is based on standard additive mixed models, allowing us to take advantage of established methods and robust, flexible algorithms. We provide easy-to-use open source software in the pffr() function for the R-package refund. Simulations show that the proposed method recovers relevant effects reliably, handles small sample sizes well and also scales to larger data sets. Applications with spatially and longitudinally observed functional data demonstrate the flexibility in modeling and interpretability of results of our approach.

Satellite measurements reveal strong anisotropy in spatial coherence of climate variations over the Tibet Plateau.

PubMed

Chen, Deliang; Tian, Yudong; Yao, Tandong; Ou, Tinghai

2016-08-24

This study uses high-resolution, long-term satellite observations to evaluate the spatial scales of the climate variations across the Tibet Plateau (TP). Both land surface temperature and precipitation observations of more than 10 years were analysed with a special attention to eight existing ice-core sites in the TP. The temporal correlation for the monthly or annual anomalies between any two points decreases exponentially with their spatial distance, and we used the e-folding decay constant to quantify the spatial scales. We found that the spatial scales are strongly direction-dependent, with distinctive patterns in the west-east and south-north orientations, for example. Meanwhile, in the same directions the scales are largely symmetric backward and forward. Focusing on the west-east and south-north directions, we found the spatial coherence in the first is generally stronger than in the second. The annual surface temperature had typical spatial scales of 302-480 km, while the annual precipitation showed smaller scales of 111-182 km. The majority of the eight ice-core sites exhibit scales much smaller than the typical scales over the TP as a whole. These results provide important observational basis for the selection of appropriate downscaling strategies, deployment of climate-data collection networks, and interpreting paleoclimate reconstructions.

Satellite measurements reveal strong anisotropy in spatial coherence of climate variations over the Tibet Plateau

NASA Astrophysics Data System (ADS)

Chen, Deliang; Tian, Yudong; Yao, Tandong; Ou, Tinghai

2016-08-01

This study uses high-resolution, long-term satellite observations to evaluate the spatial scales of the climate variations across the Tibet Plateau (TP). Both land surface temperature and precipitation observations of more than 10 years were analysed with a special attention to eight existing ice-core sites in the TP. The temporal correlation for the monthly or annual anomalies between any two points decreases exponentially with their spatial distance, and we used the e-folding decay constant to quantify the spatial scales. We found that the spatial scales are strongly direction-dependent, with distinctive patterns in the west-east and south-north orientations, for example. Meanwhile, in the same directions the scales are largely symmetric backward and forward. Focusing on the west-east and south-north directions, we found the spatial coherence in the first is generally stronger than in the second. The annual surface temperature had typical spatial scales of 302-480 km, while the annual precipitation showed smaller scales of 111-182 km. The majority of the eight ice-core sites exhibit scales much smaller than the typical scales over the TP as a whole. These results provide important observational basis for the selection of appropriate downscaling strategies, deployment of climate-data collection networks, and interpreting paleoclimate reconstructions.

Satellite measurements reveal strong anisotropy in spatial coherence of climate variations over the Tibet Plateau

PubMed Central

Chen, Deliang; Tian, Yudong; Yao, Tandong; Ou, Tinghai

2016-01-01

This study uses high-resolution, long-term satellite observations to evaluate the spatial scales of the climate variations across the Tibet Plateau (TP). Both land surface temperature and precipitation observations of more than 10 years were analysed with a special attention to eight existing ice-core sites in the TP. The temporal correlation for the monthly or annual anomalies between any two points decreases exponentially with their spatial distance, and we used the e-folding decay constant to quantify the spatial scales. We found that the spatial scales are strongly direction-dependent, with distinctive patterns in the west-east and south-north orientations, for example. Meanwhile, in the same directions the scales are largely symmetric backward and forward. Focusing on the west-east and south-north directions, we found the spatial coherence in the first is generally stronger than in the second. The annual surface temperature had typical spatial scales of 302–480 km, while the annual precipitation showed smaller scales of 111–182 km. The majority of the eight ice-core sites exhibit scales much smaller than the typical scales over the TP as a whole. These results provide important observational basis for the selection of appropriate downscaling strategies, deployment of climate-data collection networks, and interpreting paleoclimate reconstructions. PMID:27553388

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

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

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

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 resultsmore » of numerical experiments. (laser applications and other topics in quantum electronics)« less

Space-time modeling of soil moisture

NASA Astrophysics Data System (ADS)

Chen, Zijuan; Mohanty, Binayak P.; Rodriguez-Iturbe, Ignacio

2017-11-01

A physically derived space-time mathematical representation of the soil moisture field is carried out via the soil moisture balance equation driven by stochastic rainfall forcing. The model incorporates spatial diffusion and in its original version, it is shown to be unable to reproduce the relative fast decay in the spatial correlation functions observed in empirical data. This decay resulting from variations in local topography as well as in local soil and vegetation conditions is well reproduced via a jitter process acting multiplicatively over the space-time soil moisture field. The jitter is a multiplicative noise acting on the soil moisture dynamics with the objective to deflate its correlation structure at small spatial scales which are not embedded in the probabilistic structure of the rainfall process that drives the dynamics. These scales of order of several meters to several hundred meters are of great importance in ecohydrologic dynamics. Properties of space-time correlation functions and spectral densities of the model with jitter are explored analytically, and the influence of the jitter parameters, reflecting variabilities of soil moisture at different spatial and temporal scales, is investigated. A case study fitting the derived model to a soil moisture dataset is presented in detail.

Spatial frequency characteristics at image decision-point locations for observers with different radiological backgrounds in lung nodule detection

NASA Astrophysics Data System (ADS)

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

2009-02-01

Aim: The goal of the study is to determine the spatial frequency characteristics at locations in the image of overt and covert observers' decisions and find out if there are any similarities in different observers' groups: the same radiological experience group or the same accuracy scored level. Background: The radiological task is described as a visual searching decision making procedure involving visual perception and cognitive processing. Humans perceive the world through a number of spatial frequency channels, each sensitive to visual information carried by different spatial frequency ranges and orientations. Recent studies have shown that particular physical properties of local and global image-based elements are correlated with the performance and the level of experience of human observers in breast cancer and lung nodule detections. Neurological findings in visual perception were an inspiration for wavelet applications in vision research because the methodology tries to mimic the brain processing algorithms. Methods: The wavelet approach to the set of postero-anterior chest radiographs analysis has been used to characterize perceptual preferences observers with different levels of experience in the radiological task. Psychophysical methodology has been applied to track eye movements over the image, where particular ROIs related to the observers' fixation clusters has been analysed in the spaces frame by Daubechies functions. Results: Significance differences have been found between the spatial frequency characteristics at the location of different decisions.

Spatially-correlated Site Occupancy in the Nonstoichiometric Meta-stable ε -Al 60Sm 11 Phase during Devitrification of Al-10.2 at.% Sm Glasses

DOE PAGES

Yang, Lin; Zhang, Feng; Meng, Fan -Qiang; ...

2018-05-12

A metastable ε-Al 60Sm 11 phase appears during the initial devitrification of as-quenched Al-10.2 at.% Sm glasses. The ε phase is nonstoichiometric in nature since Al occupation is observed on the 16 f Sm lattice sites. Scanning transmission electron microscopic images reveal profound spatial correlation of Sm content on these sites, which cannot be explained by the “average crystal” description from Rietveld analysis of diffraction data. Thermodynamically favorable configurations, established by Monte Carlo (MC) simulations based on a cluster-expansion model, also give qualitatively different correlation functions from experimental observations. On the other hand, molecular dynamics simulations of the growth ofmore » ε-Al 60Sm 11 in undercooled liquid show that when the diffusion range of Sm is limited to ~4 Å, the correlation function of the as-grown crystal structure agrees well with that of the scanning transmission electronic microscopy (STEM) images. Furthermore, our results show that kinetic effects, especially the limited diffusivity of Sm atoms plays the fundamental role in determining the nonstoichiometric site occupancies of the ε-Al 60Sm 11 phase during the crystallization process.« less

Spatially-correlated Site Occupancy in the Nonstoichiometric Meta-stable ε -Al 60Sm 11 Phase during Devitrification of Al-10.2 at.% Sm Glasses

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

Yang, Lin; Zhang, Feng; Meng, Fan -Qiang

A metastable ε-Al 60Sm 11 phase appears during the initial devitrification of as-quenched Al-10.2 at.% Sm glasses. The ε phase is nonstoichiometric in nature since Al occupation is observed on the 16 f Sm lattice sites. Scanning transmission electron microscopic images reveal profound spatial correlation of Sm content on these sites, which cannot be explained by the “average crystal” description from Rietveld analysis of diffraction data. Thermodynamically favorable configurations, established by Monte Carlo (MC) simulations based on a cluster-expansion model, also give qualitatively different correlation functions from experimental observations. On the other hand, molecular dynamics simulations of the growth ofmore » ε-Al 60Sm 11 in undercooled liquid show that when the diffusion range of Sm is limited to ~4 Å, the correlation function of the as-grown crystal structure agrees well with that of the scanning transmission electronic microscopy (STEM) images. Furthermore, our results show that kinetic effects, especially the limited diffusivity of Sm atoms plays the fundamental role in determining the nonstoichiometric site occupancies of the ε-Al 60Sm 11 phase during the crystallization process.« less

Position-sensitive scanning fluorescence correlation spectroscopy.

PubMed

Skinner, Joseph P; Chen, Yan; Müller, Joachim D

2005-08-01

Fluorescence correlation spectroscopy (FCS) uses a stationary laser beam to illuminate a small sample volume and analyze the temporal behavior of the fluorescence fluctuations within the stationary observation volume. In contrast, scanning FCS (SFCS) collects the fluorescence signal from a moving observation volume by scanning the laser beam. The fluctuations now contain both temporal and spatial information about the sample. To access the spatial information we synchronize scanning and data acquisition. Synchronization allows us to evaluate correlations for every position along the scanned trajectory. We use a circular scan trajectory in this study. Because the scan radius is constant, the phase angle is sufficient to characterize the position of the beam. We introduce position-sensitive SFCS (PSFCS), where correlations are calculated as a function of lag time and phase. We present the theory of PSFCS and derive expressions for diffusion, diffusion in the presence of flow, and for immobilization. To test PSFCS we compare experimental data with theory. We determine the direction and speed of a flowing dye solution and the position of an immobilized particle. To demonstrate the feasibility of the technique for applications in living cells we present data of enhanced green fluorescent protein measured in the nucleus of COS cells.

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

PubMed

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

2017-03-01

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

A hierarchical spatial model of avian abundance with application to Cerulean Warblers

USGS Publications Warehouse

Thogmartin, Wayne E.; Sauer, John R.; Knutson, Melinda G.

2004-01-01

Surveys collecting count data are the primary means by which abundance is indexed for birds. These counts are confounded, however, by nuisance effects including observer effects and spatial correlation between counts. Current methods poorly accommodate both observer and spatial effects because modeling these spatially autocorrelated counts within a hierarchical framework is not practical using standard statistical approaches. We propose a Bayesian approach to this problem and provide as an example of its implementation a spatial model of predicted abundance for the Cerulean Warbler (Dendroica cerulea) in the Prairie-Hardwood Transition of the upper midwestern United States. We used an overdispersed Poisson regression with fixed and random effects, fitted by Markov chain Monte Carlo methods. We used 21 years of North American Breeding Bird Survey counts as the response in a loglinear function of explanatory variables describing habitat, spatial relatedness, year effects, and observer effects. The model included a conditional autoregressive term representing potential correlation between adjacent route counts. Categories of explanatory habitat variables in the model included land cover composition and configuration, climate, terrain heterogeneity, and human influence. The inherent hierarchy in the model was from counts occurring, in part, as a function of observers within survey routes within years. We found that the percentage of forested wetlands, an index of wetness potential, and an interaction between mean annual precipitation and deciduous forest patch size best described Cerulean Warbler abundance. Based on a map of relative abundance derived from the posterior parameter estimates, we estimated that only 15% of the species' population occurred on federal land, necessitating active engagement of public landowners and state agencies in the conservation of the breeding habitat for this species. Models of this type can be applied to any data in which the response is counts, such as animal counts, activity (e.g.,nest) counts, or species richness. The most noteworthy practical application of this spatial modeling approach is the ability to map relative species abundance. The functional relationships that we elucidated for the Cerulean Warbler provide a basis for the development of management programs and may serve to focus management and monitoring on areas and habitat variables important to Cerulean Warblers.

Multifaceted brain networks reconfiguration in disorders of consciousness uncovered by co-activation patterns.

PubMed

Di Perri, Carol; Amico, Enrico; Heine, Lizette; Annen, Jitka; Martial, Charlotte; Larroque, Stephen Karl; Soddu, Andrea; Marinazzo, Daniele; Laureys, Steven

2018-01-01

Given that recent research has shown that functional connectivity is not a static phenomenon, we aim to investigate the dynamic properties of the default mode network's (DMN) connectivity in patients with disorders of consciousness. Resting-state fMRI volumes of a convenience sample of 17 patients in unresponsive wakefulness syndrome (UWS) and controls were reduced to a spatiotemporal point process by selecting critical time points in the posterior cingulate cortex (PCC). Spatial clustering was performed on the extracted PCC time frames to obtain 8 different co-activation patterns (CAPs). We investigated spatial connectivity patterns positively and negatively correlated with PCC using both CAPs and standard stationary method. We calculated CAPs occurrences and the total number of frames. Compared to controls, patients showed (i) decreased within-network positive correlations and between-network negative correlations, (ii) emergence of "pathological" within-network negative correlations and between-network positive correlations (better defined with CAPs), and (iii) "pathological" increases in within-network positive correlations and between-network negative correlations (only detectable using CAPs). Patients showed decreased occurrence of DMN-like CAPs (1-2) compared to controls. No between-group differences were observed in the total number of frames CONCLUSION: CAPs reveal at a more fine-grained level the multifaceted spatial connectivity reconfiguration following the DMN disruption in UWS patients, which is more complex than previously thought and suggests alternative anatomical substrates for consciousness. BOLD fluctuations do not seem to differ between patients and controls, suggesting that BOLD response represents an intrinsic feature of the signal, and therefore that spatial configuration is more important for consciousness than BOLD activation itself. Hum Brain Mapp 39:89-103, 2018. © 2017 Wiley Periodicals, Inc. © 2017 Wiley Periodicals, Inc.

Violation of a Bell-like inequality in single-neutron interferometry.

PubMed

Hasegawa, Yuji; Loidl, Rudolf; Badurek, Gerald; Baron, Matthias; Rauch, Helmut

2003-09-04

Non-local correlations between spatially separated systems have been extensively discussed in the context of the Einstein, Podolsky and Rosen (EPR) paradox and Bell's inequalities. Many proposals and experiments designed to test hidden variable theories and the violation of Bell's inequalities have been reported; usually, these involve correlated photons, although recently an experiment was performed with (9)Be(+) ions. Nevertheless, it is of considerable interest to show that such correlations (arising from quantum mechanical entanglement) are not simply a peculiarity of photons. Here we measure correlations between two degrees of freedom (comprising spatial and spin components) of single neutrons; this removes the need for a source of entangled neutron pairs, which would present a considerable technical challenge. A Bell-like inequality is introduced to clarify the correlations that can arise between observables of otherwise independent degrees of freedom. We demonstrate the violation of this Bell-like inequality: our measured value is 2.051 +/- 0.019, clearly above the value of 2 predicted by classical hidden variable theories.

Modeling of blob-hole correlations in GPI edge turbulence data

NASA Astrophysics Data System (ADS)

Myra, J. R.; Russell, D. A.; Zweben, S. J.

2017-10-01

Gas-puff imaging (GPI) observations made on NSTX have revealed two-point spatial correlation patterns in the plane perpendicular to the magnetic field. A common feature is the occurrence of dipole-like patterns with significant regions of negative correlation. In this work, we explore the possibility that these dipole patterns may be due to blob-hole pairs. Statistical methods are applied to determine the two-point spatial correlation that results from a model of blob-hole pair formation. It is shown that the model produces dipole correlation patterns that are qualitatively similar to the GPI data in many respects. Effects of the reference location (confined surfaces or scrape-off layer), a superimposed random background, hole velocity and lifetime, and background sheared flows are explored. The possibility of using the model to ascertain new information about edge turbulence is discussed. Work supported by the U.S. Department of Energy Office of Science, Office of Fusion Energy Sciences under Award Number DE-FG02-02ER54678.

Large trench-parallel gravity variations predict seismogenic behavior in subduction zones.

PubMed

Song, Teh-Ru Alex; Simons, Mark

2003-08-01

We demonstrate that great earthquakes occur predominantly in regions with a strongly negative trench-parallel gravity anomaly (TPGA), whereas regions with strongly positive TPGA are relatively aseismic. These observations suggest that, over time scales up to at least 1 million years, spatial variations of seismogenic behavior within a given subduction zone are stationary and linked to the geological structure of the fore-arc. The correlations we observe are consistent with a model in which spatial variations in frictional properties on the plate interface control trench-parellel variations in fore-arc topography, gravity, and seismogenic behavior.

Geometry and scaling laws of excursion and iso-sets of enstrophy and dissipation in isotropic turbulence

NASA Astrophysics Data System (ADS)

Elsas, José Hugo; Szalay, Alexander S.; Meneveau, Charles

2018-04-01

Motivated by interest in the geometry of high intensity events of turbulent flows, we examine the spatial correlation functions of sets where turbulent events are particularly intense. These sets are defined using indicator functions on excursion and iso-value sets. Their geometric scaling properties are analysed by examining possible power-law decay of their radial correlation function. We apply the analysis to enstrophy, dissipation and velocity gradient invariants Q and R and their joint spatial distributions, using data from a direct numerical simulation of isotropic turbulence at Reλ ≈ 430. While no fractal scaling is found in the inertial range using box-counting in the finite Reynolds number flow considered here, power-law scaling in the inertial range is found in the radial correlation functions. Thus, a geometric characterisation in terms of these sets' correlation dimension is possible. Strong dependence on the enstrophy and dissipation threshold is found, consistent with multifractal behaviour. Nevertheless, the lack of scaling of the box-counting analysis precludes direct quantitative comparisons with earlier work based on multifractal formalism. Surprising trends, such as a lower correlation dimension for strong dissipation events compared to strong enstrophy events, are observed and interpreted in terms of spatial coherence of vortices in the flow.

Spatial patterns and broad-scale weather cues of beech mast seeding in Europe.

PubMed

Vacchiano, Giorgio; Hacket-Pain, Andrew; Turco, Marco; Motta, Renzo; Maringer, Janet; Conedera, Marco; Drobyshev, Igor; Ascoli, Davide

2017-07-01

Mast seeding is a crucial population process in many tree species, but its spatio-temporal patterns and drivers at the continental scale remain unknown . Using a large dataset (8000 masting observations across Europe for years 1950-2014) we analysed the spatial pattern of masting across the entire geographical range of European beech, how it is influenced by precipitation, temperature and drought, and the temporal and spatial stability of masting-weather correlations. Beech masting exhibited a general distance-dependent synchronicity and a pattern structured in three broad geographical groups consistent with continental climate regimes. Spearman's correlations and logistic regression revealed a general pattern of beech masting correlating negatively with temperature in the summer 2 yr before masting, and positively with summer temperature 1 yr before masting (i.e. 2T model). The temperature difference between the two previous summers (DeltaT model) was also a good predictor. Moving correlation analysis applied to the longest eight chronologies (74-114 yr) revealed stable correlations between temperature and masting, confirming consistency in weather cues across space and time. These results confirm widespread dependency of masting on temperature and lend robustness to the attempts to reconstruct and predict mast years using temperature data. © 2017 The Authors. New Phytologist © 2017 New Phytologist Trust.

A method to estimate the effect of deformable image registration uncertainties on daily dose mapping

PubMed Central

Murphy, Martin J.; Salguero, Francisco J.; Siebers, Jeffrey V.; Staub, David; Vaman, Constantin

2012-01-01

Purpose: To develop a statistical sampling procedure for spatially-correlated uncertainties in deformable image registration and then use it to demonstrate their effect on daily dose mapping. Methods: Sequential daily CT studies are acquired to map anatomical variations prior to fractionated external beam radiotherapy. The CTs are deformably registered to the planning CT to obtain displacement vector fields (DVFs). The DVFs are used to accumulate the dose delivered each day onto the planning CT. Each DVF has spatially-correlated uncertainties associated with it. Principal components analysis (PCA) is applied to measured DVF error maps to produce decorrelated principal component modes of the errors. The modes are sampled independently and reconstructed to produce synthetic registration error maps. The synthetic error maps are convolved with dose mapped via deformable registration to model the resulting uncertainty in the dose mapping. The results are compared to the dose mapping uncertainty that would result from uncorrelated DVF errors that vary randomly from voxel to voxel. Results: The error sampling method is shown to produce synthetic DVF error maps that are statistically indistinguishable from the observed error maps. Spatially-correlated DVF uncertainties modeled by our procedure produce patterns of dose mapping error that are different from that due to randomly distributed uncertainties. Conclusions: Deformable image registration uncertainties have complex spatial distributions. The authors have developed and tested a method to decorrelate the spatial uncertainties and make statistical samples of highly correlated error maps. The sample error maps can be used to investigate the effect of DVF uncertainties on daily dose mapping via deformable image registration. An initial demonstration of this methodology shows that dose mapping uncertainties can be sensitive to spatial patterns in the DVF uncertainties. PMID:22320766

Daily ambient air pollution metrics for five cities: Evaluation of data-fusion-based estimates and uncertainties

NASA Astrophysics Data System (ADS)

Friberg, Mariel D.; Kahn, Ralph A.; Holmes, Heather A.; Chang, Howard H.; Sarnat, Stefanie Ebelt; Tolbert, Paige E.; Russell, Armistead G.; Mulholland, James A.

2017-06-01

Spatiotemporal characterization of ambient air pollutant concentrations is increasingly relying on the combination of observations and air quality models to provide well-constrained, spatially and temporally complete pollutant concentration fields. Air quality models, in particular, are attractive, as they characterize the emissions, meteorological, and physiochemical process linkages explicitly while providing continuous spatial structure. However, such modeling is computationally intensive and has biases. The limitations of spatially sparse and temporally incomplete observations can be overcome by blending the data with estimates from a physically and chemically coherent model, driven by emissions and meteorological inputs. We recently developed a data fusion method that blends ambient ground observations and chemical-transport-modeled (CTM) data to estimate daily, spatially resolved pollutant concentrations and associated correlations. In this study, we assess the ability of the data fusion method to produce daily metrics (i.e., 1-hr max, 8-hr max, and 24-hr average) of ambient air pollution that capture spatiotemporal air pollution trends for 12 pollutants (CO, NO2, NOx, O3, SO2, PM10, PM2.5, and five PM2.5 components) across five metropolitan areas (Atlanta, Birmingham, Dallas, Pittsburgh, and St. Louis), from 2002 to 2008. Three sets of comparisons are performed: (1) the CTM concentrations are evaluated for each pollutant and metropolitan domain, (2) the data fusion concentrations are compared with the monitor data, (3) a comprehensive cross-validation analysis against observed data evaluates the quality of the data fusion model simulations across multiple metropolitan domains. The resulting daily spatial field estimates of air pollutant concentrations and uncertainties are not only consistent with observations, emissions, and meteorology, but substantially improve CTM-derived results for nearly all pollutants and all cities, with the exception of NO2 for Birmingham. The greatest improvements occur for O3 and PM2.5. Squared spatiotemporal correlation coefficients range between simulations and observations determined using cross-validation across all cities for air pollutants of secondary and mixed origins are R2 = 0.88-0.93 (O3), 0.81-0.89 (SO4), 0.67-0.83 (PM2.5), 0.52-0.72 (NO3), 0.43-0.80 (NH4), 0.32-0.51 (OC), and 0.14-0.71 (PM10). Results for relatively homogeneous pollutants of secondary origin, tend to be better than those for more spatially heterogeneous (larger spatial gradients) pollutants of primary origin (NOx, CO, SO2 and EC). Generally, background concentrations and spatial concentration gradients reflect interurban airshed complexity and the effects of regional transport, whereas daily spatial pattern variability shows intra-urban consistency in the fused data. With sufficiently high CTM spatial resolution, traffic-related pollutants exhibit gradual concentration gradients that peak toward the urban centers. Ambient pollutant concentration uncertainty estimates for the fused data are both more accurate and smaller than those for either the observations or the model simulations alone.

Simultaneous velocity and concentration field measurements of passive-scalar mixing in a confined rectangular jet

NASA Astrophysics Data System (ADS)

Feng, Hua; Olsen, Michael G.; Hill, James C.; Fox, Rodney O.

2007-06-01

Simultaneous velocity and concentration fields in a confined liquid-phase rectangular jet with a Reynolds number based on the hydraulic diameter of 50,000 (or 10,000 based on the velocity difference between streams and the jet exit dimension) and a Schmidt number of 1,250 were obtained by means of a combined particle image velocimetry (PIV) and planar laser-induced fluorescence (PLIF) system. Data were collected at the jet exit and six further downstream locations. The velocity and concentration field data were analyzed for flow statistics such as turbulent fluxes, turbulent viscosity and diffusivity, and turbulent Schmidt number ( Sc T ). The streamwise turbulent flux was found to be larger than the transverse turbulent flux, and the mean concentration gradient was not aligned with the turbulent flux vector. The average Sc T was found to vary both in streamwise and in cross stream directions and had a mean value around 0.8, a value consistent with the literature. Spatial correlation fields of turbulent fluxes and concentration were then determined. The R u'ϕ' correlation was elliptical in shape with a major axis tilted downward with respect to the streamwise axis, whereas the R v'ϕ' correlation was an ellipse with a major axis aligned with the cross-stream direction. Negative regions of R u'ϕ' were observed in the outer streams, and these negatively correlated regions decayed with downstream distance and finally disappeared altogether. The R ϕ'ϕ' correlation field was found to be an ellipse with the major axis inclined at about 45° with respect to the streamwise direction. Linear stochastic estimation was used to interpret spatial correlation data and to determine conditional flow structures. It is believed that a vortex street formed near the splitter plate is responsible for the negatively correlated region observed in the R u'ϕ' spatial correlations of turbulent fluxes. A positive concentration fluctuation event was observed to correspond to a finger of nearly uniform concentration fluid reaching out into the outer stream, whereas a negative event corresponds to a pocket of nearly uniform fluid being entrained from the outer stream into the center jet region. Large-scale vortical structures were observed in the conditional velocity fields with an elliptical shape and a streamwise major axis. The growth of the structure size increased linearly initially but then grew more slowly as the flow transitioned toward channel flow.

High-speed limnology: using advanced sensors to investigate spatial variability in biogeochemistry and hydrology.

PubMed

Crawford, John T; Loken, Luke C; Casson, Nora J; Smith, Colin; Stone, Amanda G; Winslow, Luke A

2015-01-06

Advanced sensor technology is widely used in aquatic monitoring and research. Most applications focus on temporal variability, whereas spatial variability has been challenging to document. We assess the capability of water chemistry sensors embedded in a high-speed water intake system to document spatial variability. This new sensor platform continuously samples surface water at a range of speeds (0 to >45 km h(-1)) resulting in high-density, mesoscale spatial data. These novel observations reveal previously unknown variability in physical, chemical, and biological factors in streams, rivers, and lakes. By combining multiple sensors into one platform, we were able to detect terrestrial-aquatic hydrologic connections in a small dystrophic lake, to infer the role of main-channel vs backwater nutrient processing in a large river and to detect sharp chemical changes across aquatic ecosystem boundaries in a stream/lake complex. Spatial sensor data were verified in our examples by comparing with standard lab-based measurements of selected variables. Spatial fDOM data showed strong correlation with wet chemistry measurements of DOC, and optical NO3 concentrations were highly correlated with lab-based measurements. High-frequency spatial data similar to our examples could be used to further understand aquatic biogeochemical fluxes, ecological patterns, and ecosystem processes, and will both inform and benefit from fixed-site data.

High-speed limnology: Using advanced sensors to investigate spatial variability in biogeochemistry and hydrology

USGS Publications Warehouse

Crawford, John T.; Loken, Luke C.; Casson, Nora J.; Smith, Collin; Stone, Amanda G.; Winslow, Luke A.

2015-01-01

Advanced sensor technology is widely used in aquatic monitoring and research. Most applications focus on temporal variability, whereas spatial variability has been challenging to document. We assess the capability of water chemistry sensors embedded in a high-speed water intake system to document spatial variability. This new sensor platform continuously samples surface water at a range of speeds (0 to >45 km h–1) resulting in high-density, mesoscale spatial data. These novel observations reveal previously unknown variability in physical, chemical, and biological factors in streams, rivers, and lakes. By combining multiple sensors into one platform, we were able to detect terrestrial–aquatic hydrologic connections in a small dystrophic lake, to infer the role of main-channel vs backwater nutrient processing in a large river and to detect sharp chemical changes across aquatic ecosystem boundaries in a stream/lake complex. Spatial sensor data were verified in our examples by comparing with standard lab-based measurements of selected variables. Spatial fDOM data showed strong correlation with wet chemistry measurements of DOC, and optical NO3 concentrations were highly correlated with lab-based measurements. High-frequency spatial data similar to our examples could be used to further understand aquatic biogeochemical fluxes, ecological patterns, and ecosystem processes, and will both inform and benefit from fixed-site data.

Correlation between magnetic and electric field perturbations in the field-aligned current regions deduced from DE 2 observations

NASA Technical Reports Server (NTRS)

Ishii, M.; Sugiura, M.; Iyemori, T.; Slavin, J. A.

1992-01-01

The satellite-observed high correlations between magnetic and electric field perturbations in the high-latitude field-aligned current regions are investigated by examining the dependence of the relationship between Delta-B and E on spatial scale, using the electric and magnetic field data obtained by DE 2 in the polar regions. The results are compared with the Pedersen conductivity inferred from the international reference ionosphere model and the Alfven wave velocity calculated from the in situ ion density and magnetic field measurements.

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

NASA Technical Reports Server (NTRS)

Kenny, Jeremy; Giacomoni, Clothilde

2016-01-01

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

Functional CAR models for large spatially correlated functional datasets.

PubMed

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

2016-01-01

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

Emergent spatial synaptic structure from diffusive plasticity.

PubMed

Sweeney, Yann; Clopath, Claudia

2017-04-01

Some neurotransmitters can diffuse freely across cell membranes, influencing neighbouring neurons regardless of their synaptic coupling. This provides a means of neural communication, alternative to synaptic transmission, which can influence the way in which neural networks process information. Here, we ask whether diffusive neurotransmission can also influence the structure of synaptic connectivity in a network undergoing plasticity. We propose a form of Hebbian synaptic plasticity which is mediated by a diffusive neurotransmitter. Whenever a synapse is modified at an individual neuron through our proposed mechanism, similar but smaller modifications occur in synapses connecting to neighbouring neurons. The effects of this diffusive plasticity are explored in networks of rate-based neurons. This leads to the emergence of spatial structure in the synaptic connectivity of the network. We show that this spatial structure can coexist with other forms of structure in the synaptic connectivity, such as with groups of strongly interconnected neurons that form in response to correlated external drive. Finally, we explore diffusive plasticity in a simple feedforward network model of receptive field development. We show that, as widely observed across sensory cortex, the preferred stimulus identity of neurons in our network become spatially correlated due to diffusion. Our proposed mechanism of diffusive plasticity provides an efficient mechanism for generating these spatial correlations in stimulus preference which can flexibly interact with other forms of synaptic organisation. © 2016 Federation of European Neuroscience Societies and John Wiley & Sons Ltd.

Joint transform correlators with spatially incoherent illumination

NASA Astrophysics Data System (ADS)

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

1997-03-01

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

Spatial fluctuations in transient creep deformation

NASA Astrophysics Data System (ADS)

Laurson, Lasse; Rosti, Jari; Koivisto, Juha; Miksic, Amandine; Alava, Mikko J.

2011-07-01

We study the spatial fluctuations of transient creep deformation of materials as a function of time, both by digital image correlation (DIC) measurements of paper samples and by numerical simulations of a crystal plasticity or discrete dislocation dynamics model. This model has a jamming or yielding phase transition, around which power law or Andrade creep is found. During primary creep, the relative strength of the strain rate fluctuations increases with time in both cases—the spatially averaged creep rate obeys the Andrade law epsilont ~ t - 0.7, while the time dependence of the spatial fluctuations of the local creep rates is given by Δepsilont ~ t - 0.5. A similar scaling for the fluctuations is found in the logarithmic creep regime that is typically observed for lower applied stresses. We review briefly some classical theories of Andrade creep from the point of view of such spatial fluctuations. We consider these phenomenological, time-dependent creep laws in terms of a description based on a non-equilibrium phase transition separating evolving and frozen states of the system when the externally applied load is varied. Such an interpretation is discussed further by the data collapse of the local deformations in the spirit of absorbing state/depinning phase transitions, as well as deformation-deformation correlations and the width of the cumulative strain distributions. The results are also compared with the order parameter fluctuations observed close to the depinning transition of the 2d linear interface model or the quenched Edwards-Wilkinson equation.

An insight on correlations between kinematic rupture parameters from dynamic ruptures on rough faults

NASA Astrophysics Data System (ADS)

Thingbijam, Kiran Kumar; Galis, Martin; Vyas, Jagdish; Mai, P. Martin

2017-04-01

We examine the spatial interdependence between kinematic parameters of earthquake rupture, which include slip, rise-time (total duration of slip), acceleration time (time-to-peak slip velocity), peak slip velocity, and rupture velocity. These parameters were inferred from dynamic rupture models obtained by simulating spontaneous rupture on faults with varying degree of surface-roughness. We observe that the correlations between these parameters are better described by non-linear correlations (that is, on logarithm-logarithm scale) than by linear correlations. Slip and rise-time are positively correlated while these two parameters do not correlate with acceleration time, peak slip velocity, and rupture velocity. On the other hand, peak slip velocity correlates positively with rupture velocity but negatively with acceleration time. Acceleration time correlates negatively with rupture velocity. However, the observed correlations could be due to weak heterogeneity of the slip distributions given by the dynamic models. Therefore, the observed correlations may apply only to those parts of rupture plane with weak slip heterogeneity if earthquake-rupture associate highly heterogeneous slip distributions. Our findings will help to improve pseudo-dynamic rupture generators for efficient broadband ground-motion simulations for seismic hazard studies.

Spatial variation in environmental noise and air pollution in New York City.

PubMed

Kheirbek, Iyad; Ito, Kazuhiko; Neitzel, Richard; Kim, Jung; Johnson, Sarah; Ross, Zev; Eisl, Holger; Matte, Thomas

2014-06-01

Exposure to environmental noise from traffic is common in urban areas and has been linked to increased risks of adverse health effects including cardiovascular disease. Because traffic sources also produce air pollutants that increase the risk of cardiovascular morbidity, associations between traffic exposures and health outcomes may involve confounding and/or synergisms between air pollution and noise. While prior studies have characterized intraurban spatial variation in air pollution in New York City (NYC), limited data exists on the levels and spatial variation in noise levels. We measured 1-week equivalent continuous sound pressure levels (Leq) at 56 sites during the fall of 2012 across NYC locations with varying traffic intensity and building density that are routinely monitored for combustion-related air pollutants. We evaluated correlations among several noise metrics used to characterize noise exposures, including Leq during different time periods (night, day, weekday, weekend), Ldn (day-night noise), and measures of intermittent noise defined as the ratio of peak levels to median and background levels. We also examined correlations between sound pressure levels and co-located simultaneous measures of nitric oxide (NO), nitrogen dioxide (NO2), fine particulate matter (PM2.5), and black carbon (BC) as well as estimates of traffic and building density around the monitoring sites. Noise levels varied widely across the 56 monitoring sites; 1-week Leq varied by 21.6 dBA (range 59.1-80.7 dBA) with the highest levels observed during the weekday, daytime hours. Indices of average noise were well correlated with each other (r > 0.83), while indices of intermittent noise were not well correlated with average noise levels (r < 0.41). One-week Leq correlated well with NO, NO2, and EC levels (r = 0.61 to 0.68) and less so with PM2.5 levels (r = 0.45). We observed associations between 1-week noise levels and traffic intensity within 100 m of the monitoring sites (r = 0.58). The high levels of noise observed in NYC often exceed recommended guidelines for outdoor and personal exposures, suggesting unhealthy levels in many locations. Associations between noise, traffic, and combustion air pollutants suggest the possibility for confounding and/or synergism in intraurban epidemiological studies of traffic-related health effects. The different spatial pattern of intermittent noise compared to average noise level may suggest different sources.

Wavevector multiplexed atomic quantum memory via spatially-resolved single-photon detection.

PubMed

Parniak, Michał; Dąbrowski, Michał; Mazelanik, Mateusz; Leszczyński, Adam; Lipka, Michał; Wasilewski, Wojciech

2017-12-15

Parallelized quantum information processing requires tailored quantum memories to simultaneously handle multiple photons. The spatial degree of freedom is a promising candidate to facilitate such photonic multiplexing. Using a single-photon resolving camera, we demonstrate a wavevector multiplexed quantum memory based on a cold atomic ensemble. Observation of nonclassical correlations between Raman scattered photons is confirmed by an average value of the second-order correlation function [Formula: see text] in 665 separated modes simultaneously. The proposed protocol utilizing the multimode memory along with the camera will facilitate generation of multi-photon states, which are a necessity in quantum-enhanced sensing technologies and as an input to photonic quantum circuits.

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

De Pontieu, B.; Martinez-Sykora, J.; McIntosh, S.

Spectral observations of the solar transition region (TR) and corona show broadening of spectral lines beyond what is expected from thermal and instrumental broadening. The remaining non-thermal broadening is significant (5–30 km s{sup −1}) and correlated with intensity. Here we study spectra of the TR Si iv 1403 Å line obtained at high resolution with the Interface Region Imaging Spectrograph (IRIS). We find that the large improvement in spatial resolution (0.″33) of IRIS compared to previous spectrographs (2″) does not resolve the non-thermal line broadening which, in most regions, remains at pre-IRIS levels of about 20 km s{sup −1}. Thismore » invariance to spatial resolution indicates that the processes behind the broadening occur along the line-of-sight (LOS) and/or on spatial scales (perpendicular to the LOS) smaller than 250 km. Both effects appear to play a role. Comparison with IRIS chromospheric observations shows that, in regions where the LOS is more parallel to the field, magneto-acoustic shocks driven from below impact the TR and can lead to significant non-thermal line broadening. This scenario is supported by MHD simulations. While these do not show enough non-thermal line broadening, they do reproduce the long-known puzzling correlation between non-thermal line broadening and intensity. This correlation is caused by the shocks, but only if non-equilibrium ionization is taken into account. In regions where the LOS is more perpendicular to the field, the prevalence of small-scale twist is likely to play a significant role in explaining the invariance and correlation with intensity. (letters)« less

Power-law decay of the spatial correlation function in exciton-polariton condensates

PubMed Central

Roumpos, Georgios; Lohse, Michael; Nitsche, Wolfgang H.; Keeling, Jonathan; Szymańska, Marzena Hanna; Littlewood, Peter B.; Löffler, Andreas; Höfling, Sven; Worschech, Lukas; Forchel, Alfred; Yamamoto, Yoshihisa

2012-01-01

We create a large exciton-polariton condensate and employ a Michelson interferometer setup to characterize the short- and long-distance behavior of the first order spatial correlation function. Our experimental results show distinct features of both the two-dimensional and nonequilibrium characters of the condensate. We find that the gaussian short-distance decay is followed by a power-law decay at longer distances, as expected for a two-dimensional condensate. The exponent of the power law is measured in the range 0.9–1.2, larger than is possible in equilibrium. We compare the experimental results to a theoretical model to understand the features required to observe a power law and to clarify the influence of external noise on spatial coherence in nonequilibrium phase transitions. Our results indicate that Berezinskii–Kosterlitz–Thouless-like phase order survives in open-dissipative systems. PMID:22496595

Spatial Variability in Enceladus' Plume Material: Convergence of Evidence or Coincidence?

NASA Astrophysics Data System (ADS)

Dhingra, Deepak; Hedman, Matthew M.; Clark, Roger Nelson

2016-10-01

Systematic spatial trends in the properties of the plume material emerging from Enceladus' tiger stripes can be observed in multiple observations from the Cassini mission. Subtle near infrared spectral differences within the plume have been reported across tiger stripes based on Visual and Infrared Mapping Spectrometer (VIMS) observations at high spatial resolution [1]. These spectral differences are likely due to variable water-ice grain size distribution along the source fissures (i.e. tiger stripes) and perhaps by the presence/absence of water vapor emission [2]. We now report a correlation of this spatial trend (along tiger stripes) with several other published results including (a) differences in the ice particle sizes across tiger stripes on Enceladus' surface [3, 4], (b) the surface abundance of organic material [3] and finally, (c) the relative proportion of type II grains (associated with organic/siliceous material) in the plume [5] from Damascus to Alexandria as measured by the Cosmic Dust Analyzer (CDA) instrument.The general trend indicates that at least some of the plume properties (viz. particle size, organic abundance) achieve a peak over Damascus and then become gradually subtle towards Alexandria. The observed differences between tiger stripes eruptions and the nature of correlations (trends from Damascus to Alexandria) hold important clues to the subsurface environment at Enceladus including differences in the geological setting of the individual tiger stripes [6]. The latter is a likely possibility given the large spatial spread of eruptions in Encealdus' South Polar Terrain (SPT).[1] Dhingra et al., (2015) 46th Lunar Planet. Sci. Conf., Abstract#1648[2] Dhingra et al. (2016) Icarus, submitted[3] Brown et al. (2006) Science, 311, 1425-1428[4] Jaumann et al. (2008) Icarus, 193, 407-419[5] Postberg et al. (2011) Nature, doi:10.1038/nature10175[6] Yin and Pappalardo (2015) Icarus, 260, 409-439

Velocity correlations in laboratory insect swarms

NASA Astrophysics Data System (ADS)

Ni, R.; Ouellette, N. T.

2015-12-01

In contrast to animal groups such as bird flocks or migratory herds that display net, directed motion, insect swarms do not possess global order. Without such order, it is difficult to define and characterize the transition to collective behavior in swarms; nevertheless, visual observation of swarms strongly suggests that swarming insects do behave collectively. It has recently been suggested that correlation rather than order is the hallmark of emergent collective behavior. Here, we report measurements of spatial velocity correlation functions in laboratory mating swarms of the non-biting midge Chironomus riparius. Although we find some correlation at short distances, our swarms are in general only weakly correlated, in contrast to what has been observed in field studies. Our results hint at the potentially important role of environmental conditions on collective behavior, and suggest that general indicators of the collective nature of swarming are still needed.

A model relating Eulerian spatial and temporal velocity correlations

NASA Astrophysics Data System (ADS)

Cholemari, Murali R.; Arakeri, Jaywant H.

2006-03-01

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

Trees grow on money: urban tree canopy cover and environmental justice.

PubMed

Schwarz, Kirsten; Fragkias, Michail; Boone, Christopher G; Zhou, Weiqi; McHale, Melissa; Grove, J Morgan; O'Neil-Dunne, Jarlath; McFadden, Joseph P; Buckley, Geoffrey L; Childers, Dan; Ogden, Laura; Pincetl, Stephanie; Pataki, Diane; Whitmer, Ali; Cadenasso, Mary L

2015-01-01

This study examines the distributional equity of urban tree canopy (UTC) cover for Baltimore, MD, Los Angeles, CA, New York, NY, Philadelphia, PA, Raleigh, NC, Sacramento, CA, and Washington, D.C. using high spatial resolution land cover data and census data. Data are analyzed at the Census Block Group levels using Spearman's correlation, ordinary least squares regression (OLS), and a spatial autoregressive model (SAR). Across all cities there is a strong positive correlation between UTC cover and median household income. Negative correlations between race and UTC cover exist in bivariate models for some cities, but they are generally not observed using multivariate regressions that include additional variables on income, education, and housing age. SAR models result in higher r-square values compared to the OLS models across all cities, suggesting that spatial autocorrelation is an important feature of our data. Similarities among cities can be found based on shared characteristics of climate, race/ethnicity, and size. Our findings suggest that a suite of variables, including income, contribute to the distribution of UTC cover. These findings can help target simultaneous strategies for UTC goals and environmental justice concerns.

Porous media flux sensitivity to pore-scale geostatistics: A bottom-up approach

NASA Astrophysics Data System (ADS)

Di Palma, P. R.; Guyennon, N.; Heße, F.; Romano, E.

2017-04-01

Macroscopic properties of flow through porous media can be directly computed by solving the Navier-Stokes equations at the scales related to the actual flow processes, while considering the porous structures in an explicit way. The aim of this paper is to investigate the effects of the pore-scale spatial distribution on seepage velocity through numerical simulations of 3D fluid flow performed by the lattice Boltzmann method. To this end, we generate multiple random Gaussian fields whose spatial correlation follows an assigned semi-variogram function. The Exponential and Gaussian semi-variograms are chosen as extreme-cases of correlation for short distances and statistical properties of the resulting porous media (indicator field) are described using the Matèrn covariance model, with characteristic lengths of spatial autocorrelation (pore size) varying from 2% to 13% of the linear domain. To consider the sensitivity of the modeling results to the geostatistical representativeness of the domain as well as to the adopted resolution, porous media have been generated repetitively with re-initialized random seeds and three different resolutions have been tested for each resulting realization. The main difference among results is observed between the two adopted semi-variograms, indicating that the roughness (short distances autocorrelation) is the property mainly affecting the flux. However, computed seepage velocities show additionally a wide variability (about three orders of magnitude) for each semi-variogram model in relation to the assigned correlation length, corresponding to pore sizes. The spatial resolution affects more the results for short correlation lengths (i.e., small pore sizes), resulting in an increasing underestimation of the seepage velocity with the decreasing correlation length. On the other hand, results show an increasing uncertainty as the correlation length approaches the domain size.

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

PubMed

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

2018-01-23

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 the bottom in deep ocean direct-arrival zones.

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

PubMed Central

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 the bottom in deep ocean direct-arrival zones. PMID:29360793

IUE's View of Callisto: Detection of an SO2 Absorption Correlated to Possible Torus Neutral Wind Alterations

NASA Technical Reports Server (NTRS)

Lane, Arthur L.; Domingue, Deborah L.

1997-01-01

Observations taken with the International Ultraviolet Explorer (IUE) detected a 0.28 micron absorption feature on Callisto's leading and Jupiter-facing hemispheres. This feature is similar to Europa's 0.28 micron feature, however it shows no correlation with magnetospheric ion bombardment. The strongest 0.28 micron signature is seen in the region containing the Valhalla impact. This absorption feature also shows some spatial correlation to possible neutral wind interactions, suggestive of S implantation (rather than S(sub x)) into Callisto's water ice surface, Indications of possible temporal variations (on the 10% level) are seen at other wavelengths between the 1984-1986 and the 1996 observations.

Stochastic Analysis and Probabilistic Downscaling of Soil Moisture

NASA Astrophysics Data System (ADS)

Deshon, J. P.; Niemann, J. D.; Green, T. R.; Jones, A. S.

2017-12-01

Soil moisture is a key variable for rainfall-runoff response estimation, ecological and biogeochemical flux estimation, and biodiversity characterization, each of which is useful for watershed condition assessment. These applications require not only accurate, fine-resolution soil-moisture estimates but also confidence limits on those estimates and soil-moisture patterns that exhibit realistic statistical properties (e.g., variance and spatial correlation structure). The Equilibrium Moisture from Topography, Vegetation, and Soil (EMT+VS) model downscales coarse-resolution (9-40 km) soil moisture from satellite remote sensing or land-surface models to produce fine-resolution (10-30 m) estimates. The model was designed to produce accurate deterministic soil-moisture estimates at multiple points, but the resulting patterns do not reproduce the variance or spatial correlation of observed soil-moisture patterns. The primary objective of this research is to generalize the EMT+VS model to produce a probability density function (pdf) for soil moisture at each fine-resolution location and time. Each pdf has a mean that is equal to the deterministic soil-moisture estimate, and the pdf can be used to quantify the uncertainty in the soil-moisture estimates and to simulate soil-moisture patterns. Different versions of the generalized model are hypothesized based on how uncertainty enters the model, whether the uncertainty is additive or multiplicative, and which distributions describe the uncertainty. These versions are then tested by application to four catchments with detailed soil-moisture observations (Tarrawarra, Satellite Station, Cache la Poudre, and Nerrigundah). The performance of the generalized models is evaluated by comparing the statistical properties of the simulated soil-moisture patterns to those of the observations and the deterministic EMT+VS model. The versions of the generalized EMT+VS model with normally distributed stochastic components produce soil-moisture patterns with more realistic statistical properties than the deterministic model. Additionally, the results suggest that the variance and spatial correlation of the stochastic soil-moisture variations do not vary consistently with the spatial-average soil moisture.

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.

PubMed

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.

Plasma fluctuations as Markovian noise.

PubMed

Li, B; Hazeltine, R D; Gentle, K W

2007-12-01

Noise theory is used to study the correlations of stationary Markovian fluctuations that are homogeneous and isotropic in space. The relaxation of the fluctuations is modeled by the diffusion equation. The spatial correlations of random fluctuations are modeled by the exponential decay. Based on these models, the temporal correlations of random fluctuations, such as the correlation function and the power spectrum, are calculated. We find that the diffusion process can give rise to the decay of the correlation function and a broad frequency spectrum of random fluctuations. We also find that the transport coefficients may be estimated by the correlation length and the correlation time. The theoretical results are compared with the observed plasma density fluctuations from the tokamak and helimak experiments.

Can trait patterns along gradients predict plant community responses to climate change?

PubMed

Guittar, John; Goldberg, Deborah; Klanderud, Kari; Telford, Richard J; Vandvik, Vigdis

2016-10-01

Plant functional traits vary consistently along climate gradients and are therefore potential predictors of plant community response to climate change. We test this space-for-time assumption by combining a spatial gradient study with whole-community turf transplantation along temperature and precipitation gradients in a network of 12 grassland sites in Southern Norway. Using data on eight traits for 169 species and annual vegetation censuses of 235 turfs over 5 yr, we quantify trait-based responses to climate change by comparing observed community dynamics in transplanted turfs to field-parameterized null model simulations. Three traits related to species architecture (maximum height, number of dormant meristems, and ramet-ramet connection persistence) varied consistently along spatial temperature gradients and also correlated to changes in species abundances in turfs transplanted to warmer climates. Two traits associated with resource acquisition strategy (SLA, leaf area) increased along spatial temperature gradients but did not correlate to changes in species abundances following warming. No traits correlated consistently with precipitation. Our study supports the hypothesis that spatial associations between plant traits and broad-scale climate variables can be predictive of community response to climate change, but it also suggests that not all traits with clear patterns along climate gradients will necessarily influence community response to an equal degree. © 2016 by the Ecological Society of America.

Origins of collectivity in small systems

NASA Astrophysics Data System (ADS)

Schenke, Björn

2017-11-01

We review recent developments in the theoretical description and understanding of multi-particle correlation measurements in collisions of small projectiles (p/d/3He) with heavy nuclei (Au, Pb) as well as proton+proton collisions. We focus on whether the physical processes responsible for the observed long range rapidity correlations and their azimuthal structure are the same in small systems as in heavy ion collisions. In the latter they are interpreted as generated by the initial spatial geometry being transformed into momentum correlations by strong final state interactions. However, explicit calculations show that also initial state momentum correlations are present and could contribute to observables in small systems. If strong final state interactions are present in small systems, recent developments show that results are sensitive to the shape of the proton and its fluctuations.

Validation of Clinical Observations of Mastication in Persons with ALS.

PubMed

Simione, Meg; Wilson, Erin M; Yunusova, Yana; Green, Jordan R

2016-06-01

Amyotrophic lateral sclerosis (ALS) is a progressive neurological disease that can result in difficulties with mastication leading to malnutrition, choking or aspiration, and reduced quality of life. When evaluating mastication, clinicians primarily observe spatial and temporal aspects of jaw motion. The reliability and validity of clinical observations for detecting jaw movement abnormalities is unknown. The purpose of this study is to determine the reliability and validity of clinician-based ratings of chewing performance in neuro-typical controls and persons with varying degrees of chewing impairments due to ALS. Adults chewed a solid food consistency while full-face video were recorded along with jaw kinematic data using a 3D optical motion capture system. Five experienced speech-language pathologists watched the videos and rated the spatial and temporal aspects of chewing performance. The jaw kinematic data served as the gold-standard for validating the clinicians' ratings. Results showed that the clinician-based rating of temporal aspects of chewing performance had strong inter-rater reliability and correlated well with comparable kinematic measures. In contrast, the reliability of rating the spatial and spatiotemporal aspects of chewing (i.e., range of motion of the jaw, consistency of the chewing pattern) was mixed. Specifically, ratings of range of motion were at best only moderately reliable. Ratings of chewing movement consistency were reliable but only weakly correlated with comparable measures of jaw kinematics. These findings suggest that clinician ratings of temporal aspects of chewing are appropriate for clinical use, whereas ratings of the spatial and spatiotemporal aspects of chewing may not be reliable or valid.

Long-term Observations of Intense Precipitation Small-scale Spatial Variability in a Semi-arid Catchment

NASA Astrophysics Data System (ADS)

Cropp, E. L.; Hazenberg, P.; Castro, C. L.; Demaria, E. M.

2017-12-01

In the southwestern US, the summertime North American Monsoon (NAM) provides about 60% of the region's annual precipitation. Recent research using high-resolution atmospheric model simulations and retrospective predictions has shown that since the 1950's, and more specifically in the last few decades, the mean daily precipitation in the southwestern U.S. during the NAM has followed a decreasing trend. Furthermore, days with more extreme precipitation have intensified. The current work focuses the impact of these long-term changes on the observed small-scale spatial variability of intense precipitation. Since limited long-term high-resolution observational data exist to support such climatological-induced spatial changes in precipitation frequency and intensity, the current work utilizes observations from the USDA-ARS Walnut Gulch Experimental Watershed (WGEW) in southeastern Arizona. Within this 150 km^2 catchment over 90 rain gauges have been installed since the 1950s, measuring at sub-hourly resolution. We have applied geospatial analyses and the kriging interpolation technique to identify long-term changes in the spatial and temporal correlation and anisotropy of intense precipitation. The observed results will be compared with the previously model simulated results, as well as related to large-scale variations in climate patterns, such as the El Niño Southern Oscillation (ENSO) and the Pacific Decadal Oscillation (PDO).

New insights into the interstellar medium of the dwarf galaxy IC 10: connection between magnetic fields, the radio-infrared correlation and star formation

NASA Astrophysics Data System (ADS)

Basu, Aritra; Roychowdhury, Sambit; Heesen, Volker; Beck, Rainer; Brinks, Elias; Westcott, Jonathan; Hindson, Luke

2017-10-01

We present the highest sensitivity and angular resolution study at 0.32 GHz of the dwarf irregular galaxy IC 10, observed using the Giant Metrewave Radio Telescope, probing ˜45 pc spatial scales. We find the galaxy-averaged radio continuum spectrum to be relatively flat, with a spectral index α = -0.34 ± 0.01 (Sν ∝ να), mainly due to a high contribution from free-free emission. At 0.32 GHz, some of the H II regions show evidence of free-free absorption as they become optically thick below ˜0.41 GHz with corresponding free electron densities of ˜ 11-22 cm- 3. After removing the free-free emission, we studied the radio-infrared (IR) relations on 55, 110 and 165 pc spatial scales. We find that on all scales the non-thermal emission at 0.32 and 6.2 GHz correlates better with far-infrared (FIR) emission at 70 μm than mid-IR emission at 24 μm. The dispersion of the radio-FIR relation arises due to variations in both magnetic field and dust temperature, and decreases systematically with increasing spatial scale. The effect of cosmic ray transport is negligible as cosmic ray electrons were only injected ≲5 Myr ago. The average magnetic field strength (B) of 12 μG in the disc is comparable to that of large star-forming galaxies. The local magnetic field is strongly correlated with local star formation rate (SFR) as B ∝ SFR0.35 ± 0.03, indicating a starburst-driven fluctuation dynamo to be efficient (˜10 per cent) in amplifying the field in IC 10. The high spatial resolution observations presented here suggest that the high efficiency of magnetic field amplification and strong coupling with SFR likely sets up the radio-FIR correlation in cosmologically young galaxies.

Populational fluctuation and spatial distribution of Alphitobius diaperinus (Panzer) (Coleoptera; Tenebrionidae) in a poultry house, Cascavel, Parana state, Brazil.

PubMed

Chernaki-Leffer, A M; Almeida, L M; Sosa-Gómez, D R; Anjos, A; Vogado, K M

2007-05-01

Knowledge of the population fluctuation and spatial distribution of pests is fundamental for establishing an appropriate control method. The population fluctuation and spatial distribution of the Alphitobius diaperinus in a poultry house in Cascavel, in the state of Parana, Brazil, was studied between October, 2001 and October 2002. Larvae and adults of the lesser mealworm were sampled weekly using Arends tube traps (n = 22) for six consecutive flock grow-outs. The temperature of the litter and of the poultry house was measured at the same locations of the tube traps. Beetle numbers increased continuously throughout all the sampling dates (average 5,137 in the first week and 18,494 insects on the sixth week). Significantly greater numbers of larvae were collected than adults (1 to 20 times in 95% of the sampling points). There was no correlation between temperature and the number of larvae and adults collected, therefore no fluctuation was observed during the sampling period. The population growth was correlated to litter re-use. The highest temperatures were observed in deep litter. The spatial distribution of larvae and adults in the poultry house was heterogeneous during the whole period of evaluation. Results suggest that monitoring in poultry houses is necessary prior to adopting and evaluating control measures due to the great variability of the insect distribution in the poultry house.

Decay and Spatial Diffusion of Turbulent Kinetic Energy In The Presence of a Linear Kinetic Energy Gradient

NASA Astrophysics Data System (ADS)

Meneveau, Charles

2015-11-01

A topic that elicited the interest of John Lumley is pressure transport in turbulence. In 1978 (JL, in Advances in Applied Mechanics, pages 123-176) he showed that pressure transport likely acts in the opposite direction to the spatial flux of kinetic energy due to triple velocity correlations. Here we examine a flow in which the interplay of turbulent decay and spatial transport is particularly relevant. Specifically, using a specially designed active grid and screens placed in the Corrsin wind tunnel, such a flow is realized. Data are acquired using X-wire thermal anemometry at different spanwise and downstream locations. In order to resolve the dissipation rate accurately, measurements are also acquired using the NSTAP probe developed and manufactured by Princeton researchers and kindly provided to us (M. Hultmark, Y. Fan, L. Smits). The results show power-law decay with downstream distance, with a decay exponent that becomes larger in the high kinetic energy side of the flow. Measurements of the dissipation enable us to obtain the spanwise gradient of the spatial flux. One possible explanation for the observations is upgrading transport of kinetic energy due to pressure-velocity correlations, although its magnitude required to close the budget appears very large. Absence of simultaneous pressure velocity measurement preclude us to fully elucidate the observed trends. In collaboration with Adrien Thormann, Johns Hopkins University. Financial support: National Science Foundation.

Noninvasive Spatially Offset and Transmission Raman Mapping of Breast Tissue: A Multimodal Approach Towards the In Vivo Assessment of Tissue Pathology

DTIC Science & Technology

2013-06-01

spectroscopy on tissue biopsies to correlate spectral bands with healthy and diseased breast tissue. Observed spectral changes are compared to infrared...capabilities and performance. Additionally, we conduct spectroscopy on tissue biopsies to correlate spectral bands with healthy and diseased ... disease states, ie hyperplasia, dysplasia, malignant, benign. The instrumentation has been built and characterized using archived tissue that was

Probing density and spin correlations in two-dimensional Hubbard model with ultracold fermions

NASA Astrophysics Data System (ADS)

Chan, Chun Fai; Drewes, Jan Henning; Gall, Marcell; Wurz, Nicola; Cocchi, Eugenio; Miller, Luke; Pertot, Daniel; Brennecke, Ferdinand; Koehl, Michael

2017-04-01

Quantum gases of interacting fermionic atoms in optical lattices is a promising candidate to study strongly correlated quantum phases of the Hubbard model such as the Mott-insulator, spin-ordered phases, or in particular d-wave superconductivity. We experimentally realise the two-dimensional Hubbard model by loading a quantum degenerate Fermi gas of 40 K atoms into a three-dimensional optical lattice geometry. High-resolution absorption imaging in combination with radiofrequency spectroscopy is applied to spatially resolve the atomic distribution in a single 2D layer. We investigate in local measurements of spatial correlations in both the density and spin sector as a function of filling, temperature and interaction strength. In the density sector, we compare the local density fluctuations and the global thermodynamic quantities, and in the spin sector, we observe the onset of non-local spin correlation, signalling the emergence of the anti-ferromagnetic phase. We would report our recent experimental endeavours to investigate further down in temperature in the spin sector.

Comparison of Urban Human Movements Inferring from Multi-Source Spatial-Temporal Data

NASA Astrophysics Data System (ADS)

Cao, Rui; Tu, Wei; Cao, Jinzhou; Li, Qingquan

2016-06-01

The quantification of human movements is very hard because of the sparsity of traditional data and the labour intensive of the data collecting process. Recently, much spatial-temporal data give us an opportunity to observe human movement. This research investigates the relationship of city-wide human movements inferring from two types of spatial-temporal data at traffic analysis zone (TAZ) level. The first type of human movement is inferred from long-time smart card transaction data recording the boarding actions. The second type of human movement is extracted from citywide time sequenced mobile phone data with 30 minutes interval. Travel volume, travel distance and travel time are used to measure aggregated human movements in the city. To further examine the relationship between the two types of inferred movements, the linear correlation analysis is conducted on the hourly travel volume. The obtained results show that human movements inferred from smart card data and mobile phone data have a correlation of 0.635. However, there are still some non-ignorable differences in some special areas. This research not only reveals the citywide spatial-temporal human dynamic but also benefits the understanding of the reliability of the inference of human movements with big spatial-temporal data.

[Analysis of influence on spatial distribution of fishing ground for Antarctic krill fishery in the northern South Shetland Islands based on GWR model].

PubMed

Chen, Lyu Feng; Zhu, Guo Ping

2018-03-01

Based on Antarctic krill fishery and marine environmental data collected by scientific observers, using geographically weighted regression (GWR) model, we analyzed the effects of the factors with spatial attributes, i.e., depth of krill swarm (DKS) and distance from fishing position to shore (DTS), and sea surface temperature (SST), on the spatial distribution of fishing ground in the northern South Shetland Islands. The results showed that there was no significant aggregation in spatial distribution of catch per unit fishing effort (CPUE). Spatial autocorrelations (positive) among three factors were observed in 2010 and 2013, but were not in 2012 and 2016. Results from GWR model showed that the extent for the impacts on spatial distribution of CPUEs varied among those three factors, following the order DKS>SST>DTS. Compared to the DKS and DTS, the impact of SST on the spatial distribution of CPUEs presented adverse trend in the eastern and western parts of the South Shetland Islands. Negative correlations occurred for the spatial effects of DKS and DTS on distribution of CPUEs, though with inter-annual and regional variation. Our results provide metho-dological reference for researches on the underlying mechanism for fishing ground formation for Antarctic krill fishery.

Using Structured Additive Regression Models to Estimate Risk Factors of Malaria: Analysis of 2010 Malawi Malaria Indicator Survey Data

PubMed Central

Chirombo, James; Lowe, Rachel; Kazembe, Lawrence

2014-01-01

Background After years of implementing Roll Back Malaria (RBM) interventions, the changing landscape of malaria in terms of risk factors and spatial pattern has not been fully investigated. This paper uses the 2010 malaria indicator survey data to investigate if known malaria risk factors remain relevant after many years of interventions. Methods We adopted a structured additive logistic regression model that allowed for spatial correlation, to more realistically estimate malaria risk factors. Our model included child and household level covariates, as well as climatic and environmental factors. Continuous variables were modelled by assuming second order random walk priors, while spatial correlation was specified as a Markov random field prior, with fixed effects assigned diffuse priors. Inference was fully Bayesian resulting in an under five malaria risk map for Malawi. Results Malaria risk increased with increasing age of the child. With respect to socio-economic factors, the greater the household wealth, the lower the malaria prevalence. A general decline in malaria risk was observed as altitude increased. Minimum temperatures and average total rainfall in the three months preceding the survey did not show a strong association with disease risk. Conclusions The structured additive regression model offered a flexible extension to standard regression models by enabling simultaneous modelling of possible nonlinear effects of continuous covariates, spatial correlation and heterogeneity, while estimating usual fixed effects of categorical and continuous observed variables. Our results confirmed that malaria epidemiology is a complex interaction of biotic and abiotic factors, both at the individual, household and community level and that risk factors are still relevant many years after extensive implementation of RBM activities. PMID:24991915

Using structured additive regression models to estimate risk factors of malaria: analysis of 2010 Malawi malaria indicator survey data.

PubMed

Chirombo, James; Lowe, Rachel; Kazembe, Lawrence

2014-01-01

After years of implementing Roll Back Malaria (RBM) interventions, the changing landscape of malaria in terms of risk factors and spatial pattern has not been fully investigated. This paper uses the 2010 malaria indicator survey data to investigate if known malaria risk factors remain relevant after many years of interventions. We adopted a structured additive logistic regression model that allowed for spatial correlation, to more realistically estimate malaria risk factors. Our model included child and household level covariates, as well as climatic and environmental factors. Continuous variables were modelled by assuming second order random walk priors, while spatial correlation was specified as a Markov random field prior, with fixed effects assigned diffuse priors. Inference was fully Bayesian resulting in an under five malaria risk map for Malawi. Malaria risk increased with increasing age of the child. With respect to socio-economic factors, the greater the household wealth, the lower the malaria prevalence. A general decline in malaria risk was observed as altitude increased. Minimum temperatures and average total rainfall in the three months preceding the survey did not show a strong association with disease risk. The structured additive regression model offered a flexible extension to standard regression models by enabling simultaneous modelling of possible nonlinear effects of continuous covariates, spatial correlation and heterogeneity, while estimating usual fixed effects of categorical and continuous observed variables. Our results confirmed that malaria epidemiology is a complex interaction of biotic and abiotic factors, both at the individual, household and community level and that risk factors are still relevant many years after extensive implementation of RBM activities.

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

NASA Astrophysics Data System (ADS)

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

2017-12-01

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

Perception of differences in naturalistic dynamic scenes, and a V1-based model.

PubMed

To, Michelle P S; Gilchrist, Iain D; Tolhurst, David J

2015-01-16

We investigate whether a computational model of V1 can predict how observers rate perceptual differences between paired movie clips of natural scenes. Observers viewed 198 pairs of movies clips, rating how different the two clips appeared to them on a magnitude scale. Sixty-six of the movie pairs were naturalistic and those remaining were low-pass or high-pass spatially filtered versions of those originals. We examined three ways of comparing a movie pair. The Spatial Model compared corresponding frames between each movie pairwise, combining those differences using Minkowski summation. The Temporal Model compared successive frames within each movie, summed those differences for each movie, and then compared the overall differences between the paired movies. The Ordered-Temporal Model combined elements from both models, and yielded the single strongest predictions of observers' ratings. We modeled naturalistic sustained and transient impulse functions and compared frames directly with no temporal filtering. Overall, modeling naturalistic temporal filtering improved the models' performance; in particular, the predictions of the ratings for low-pass spatially filtered movies were much improved by employing a transient impulse function. The correlations between model predictions and observers' ratings rose from 0.507 without temporal filtering to 0.759 (p = 0.01%) when realistic impulses were included. The sustained impulse function and the Spatial Model carried more weight in ratings for normal and high-pass movies, whereas the transient impulse function with the Ordered-Temporal Model was most important for spatially low-pass movies. This is consistent with models in which high spatial frequency channels with sustained responses primarily code for spatial details in movies, while low spatial frequency channels with transient responses code for dynamic events. © 2015 ARVO.

Examination about the Spatial Representation of PM2.5 Obtained from Limited Stations Using a Network Observation

NASA Astrophysics Data System (ADS)

Shi, X.; Zhao, C.

2017-12-01

Haze aerosol pollution has been a focus issue in China, and its characteristics is highly demanded. With limited observation sites, aerosol properties obtained from a single site is frequently used to represent the haze condition over a large domain, such as tens of kilometers. This could result in high uncertainties in the haze characteristics due to their spatial variation. Using a network observation from November 2015 to February 2016 over an urban city in North China with high spatial resolution, this study examines the spatial representation of ground site observations. A method is first developed to determine the representative area of measurements from limited stations. The key idea of this method is to determine the spatial variability of particulate matter with diameters less than 2.5 μm (PM2.5) concentration using a variance function in 2km x 2km grids. Based on the high spatial resolution (0.5km x 0.5km) measurements of PM2.5, the grids in which PM2.5 have high correlations and weak value differences are determined as the representation area of measurements at these grids. Note that the size representation area is not exactly a circle region. It shows that the size representation are for the study region and study period ranges from 0.25 km2 to 16.25 km2. The representation area varies with locations. For the 20 km x 20 km study region, 10 station observations would have a good representation of the PM2.5 observations obtained from current 169 stations at the four-month time scale.

Revisiting Geschwind's hypothesis on brain lateralisation: a functional MRI study of digit ratio (2D:4D) and sex interaction effects on spatial working memory.

PubMed

Kalmady, Sunil Vasu; Agarwal, Sri Mahavir; Shivakumar, Venkataram; Jose, Dania; Venkatasubramanian, Ganesan; Reddy, Y C Janardhan

2013-01-01

The Geschwind-Behan-Galaburda (GBG) hypothesis links cerebral lateralisation with prenatal testosterone exposure. Digit ratio measures in adults have been established as potential markers of foetal sex hormonal milieu. The aim of the study was to evaluate the sex-dependent interaction of digit ratio measures and cerebral lateralization as well as their neurohemodynamic correlates using functional MRI (fMRI). Digit ratio measures-ratio of index finger (2D) length to ring finger (4D) length (2D:4D) and difference between 2D:4D of two hands, i.e., right minus left (DR-L)-were calculated using high resolution digital images in 70 right-handed participants (42 men) based on reliable and valid method. fMRI was acquired during the performance of a spatial working memory task in a subset of 25 individuals (14 men), and analysed using Statistical Parametric Mapping 8 (SPM8) and the Laterality Index toolbox for SPM8. Men had significantly less bilateral 2D:4D than women. There was a significant negative correlation between right 2D:4D and 2-Back task accuracy (2BACC) in women. A significant sex-by-right 2D:4D interaction was observed in left parahippocampal gyrus activation. Additionally, sex-by-DR-L interaction was observed in left IPL activation. DR-L showed a significant positive correlation with the whole brain Laterality Index (LI), and LI, in turn, demonstrated a significant negative correlation with 2BACC. Our study observations suggest several novel sex-differential relationships between 2D:4D measures and fMRI activation during spatial working memory task performance. Given the pre-existing background data supporting digit ratio measures as putative indicator of prenatal sex hormonal milieu, our study findings add support to the Geschwind-Behan-Galaburda (GBG) hypothesis.

Assessing the significance of global and local correlations under spatial autocorrelation: a nonparametric approach.

PubMed

Viladomat, Júlia; Mazumder, Rahul; McInturff, Alex; McCauley, Douglas J; Hastie, Trevor

2014-06-01

We propose a method to test the correlation of two random fields when they are both spatially autocorrelated. In this scenario, the assumption of independence for the pair of observations in the standard test does not hold, and as a result we reject in many cases where there is no effect (the precision of the null distribution is overestimated). Our method recovers the null distribution taking into account the autocorrelation. It uses Monte-Carlo methods, and focuses on permuting, and then smoothing and scaling one of the variables to destroy the correlation with the other, while maintaining at the same time the initial autocorrelation. With this simulation model, any test based on the independence of two (or more) random fields can be constructed. This research was motivated by a project in biodiversity and conservation in the Biology Department at Stanford University. © 2014, The International Biometric Society.

Static and dynamic properties of two-dimensional Coulomb clusters.

PubMed

Ash, Biswarup; Chakrabarti, J; Ghosal, Amit

2017-10-01

We study the temperature dependence of static and dynamic responses of Coulomb interacting particles in two-dimensional confinements across the crossover from solid- to liquid-like behaviors. While static correlations that investigate the translational and bond orientational order in the confinements show the footprints of hexatic-like phase at low temperatures, dynamics of the particles slow down considerably in this phase, reminiscent of a supercooled liquid. Using density correlations, we probe long-lived heterogeneities arising from the interplay of the irregularity in the confinement and long-range Coulomb interactions. The relaxation at multiple time scales show stretched-exponential decay of spatial correlations in irregular traps. Temperature dependence of characteristic time scales, depicting the structural relaxation of the system, show striking similarities with those observed for the glassy systems, indicating that some of the key signatures of supercooled liquids emerge in confinements with lower spatial symmetries.

Spatial distributions of polyunsaturated aldehydes and their biogeochemical implications in the Pearl River Estuary and the adjacent northern South China Sea

NASA Astrophysics Data System (ADS)

Wu, Zhengchao; Li, Qian P.

2016-09-01

This study reports the first comprehensive exploration of the spatial patterns of dissolved and particulate polyunsaturated aldehydes (PUAs), their physical and biological controlling factors, and their potential biogeochemical influences in the Pearl River Estuary (PRE) of the northern South China Sea (NSCS). High levels of total particulate PUAs (0-41 nM) and dissolved PUAs (0.10-0.37 nM) were observed with substantial spatial variation during an intense summer phytoplankton bloom outside the PRE mouth. We found the particulate PUAs strongly correlated with temperature within the high chlorophyll bloom, while showing a generally positive correlation with chlorophyll-a for the entire region. Additionally, the Si/N ratio significantly correlated with the particulate PUAs along the estuary suggesting the important role of silica on PUA production in this region. The dissolved PUAs counterparts exhibited a positive correlation with chlorophyll-a within the high chlorophyll bloom, but a negatively one with temperature outside, reflecting the essential bio-physical coupling effects on the dissolved PUAs distributions in the ocean. Biogeochemical implications of PUAs on the coastal ecosystem include not only the deleterious restriction of high PUAs-producing diatom bloom on copepod population, but also the profound influence of particulate PUAs on the microbial cycling of organic carbon in the NSCS.

Comparing spatial tuning curves, spectral ripple resolution, and speech perception in cochlear implant users.

PubMed

Anderson, Elizabeth S; Nelson, David A; Kreft, Heather; Nelson, Peggy B; Oxenham, Andrew J

2011-07-01

Spectral ripple discrimination thresholds were measured in 15 cochlear-implant users with broadband (350-5600 Hz) and octave-band noise stimuli. The results were compared with spatial tuning curve (STC) bandwidths previously obtained from the same subjects. Spatial tuning curve bandwidths did not correlate significantly with broadband spectral ripple discrimination thresholds but did correlate significantly with ripple discrimination thresholds when the rippled noise was confined to an octave-wide passband, centered on the STC's probe electrode frequency allocation. Ripple discrimination thresholds were also measured for octave-band stimuli in four contiguous octaves, with center frequencies from 500 Hz to 4000 Hz. Substantial variations in thresholds with center frequency were found in individuals, but no general trends of increasing or decreasing resolution from apex to base were observed in the pooled data. Neither ripple nor STC measures correlated consistently with speech measures in noise and quiet in the sample of subjects in this study. Overall, the results suggest that spectral ripple discrimination measures provide a reasonable measure of spectral resolution that correlates well with more direct, but more time-consuming, measures of spectral resolution, but that such measures do not always provide a clear and robust predictor of performance in speech perception tasks. © 2011 Acoustical Society of America

Comparing spatial tuning curves, spectral ripple resolution, and speech perception in cochlear implant users

PubMed Central

Anderson, Elizabeth S.; Nelson, David A.; Kreft, Heather; Nelson, Peggy B.; Oxenham, Andrew J.

2011-01-01

Spectral ripple discrimination thresholds were measured in 15 cochlear-implant users with broadband (350–5600 Hz) and octave-band noise stimuli. The results were compared with spatial tuning curve (STC) bandwidths previously obtained from the same subjects. Spatial tuning curve bandwidths did not correlate significantly with broadband spectral ripple discrimination thresholds but did correlate significantly with ripple discrimination thresholds when the rippled noise was confined to an octave-wide passband, centered on the STC’s probe electrode frequency allocation. Ripple discrimination thresholds were also measured for octave-band stimuli in four contiguous octaves, with center frequencies from 500 Hz to 4000 Hz. Substantial variations in thresholds with center frequency were found in individuals, but no general trends of increasing or decreasing resolution from apex to base were observed in the pooled data. Neither ripple nor STC measures correlated consistently with speech measures in noise and quiet in the sample of subjects in this study. Overall, the results suggest that spectral ripple discrimination measures provide a reasonable measure of spectral resolution that correlates well with more direct, but more time-consuming, measures of spectral resolution, but that such measures do not always provide a clear and robust predictor of performance in speech perception tasks. PMID:21786905

Autocorrelation structure of convective rainfall in semiarid-arid climate derived from high-resolution X-Band radar estimates

NASA Astrophysics Data System (ADS)

Marra, Francesco; Morin, Efrat

2018-02-01

Small scale rainfall variability is a key factor driving runoff response in fast responding systems, such as mountainous, urban and arid catchments. In this paper, the spatial-temporal autocorrelation structure of convective rainfall is derived with extremely high resolutions (60 m, 1 min) using estimates from an X-Band weather radar recently installed in a semiarid-arid area. The 2-dimensional spatial autocorrelation of convective rainfall fields and the temporal autocorrelation of point-wise and distributed rainfall fields are examined. The autocorrelation structures are characterized by spatial anisotropy, correlation distances 1.5-2.8 km and rarely exceeding 5 km, and time-correlation distances 1.8-6.4 min and rarely exceeding 10 min. The observed spatial variability is expected to negatively affect estimates from rain gauges and microwave links rather than satellite and C-/S-Band radars; conversely, the temporal variability is expected to negatively affect remote sensing estimates rather than rain gauges. The presented results provide quantitative information for stochastic weather generators, cloud-resolving models, dryland hydrologic and agricultural models, and multi-sensor merging techniques.

Ten Years of Gamma-Ray Bursts Observations with BATSE

NASA Technical Reports Server (NTRS)

Fishman, Gerald J.; Rose, M. Franklin (Technical Monitor)

2000-01-01

The observed gamma-ray temporal, spectral, intensity and spatial distribution characteristics of GRBs from data obtained from BATSE/Compton Observatory, will be described. The talk will concentrate on recent studies of burst properties, correlations of GRB parameters and other statistical studies that have only recently come to light with the unprecedented sample of over 2700 GRBS. Recent studies of possible observational biases, un-triggered GRBs and threshold calculations for BATSE will also be described.

Space-Time Data Fusion

NASA Technical Reports Server (NTRS)

Braverman, Amy; Nguyen, Hai; Olsen, Edward; Cressie, Noel

2011-01-01

Space-time Data Fusion (STDF) is a methodology for combing heterogeneous remote sensing data to optimally estimate the true values of a geophysical field of interest, and obtain uncertainties for those estimates. The input data sets may have different observing characteristics including different footprints, spatial resolutions and fields of view, orbit cycles, biases, and noise characteristics. Despite these differences all observed data can be linked to the underlying field, and therefore the each other, by a statistical model. Differences in footprints and other geometric characteristics are accounted for by parameterizing pixel-level remote sensing observations as spatial integrals of true field values lying within pixel boundaries, plus measurement error. Both spatial and temporal correlations in the true field and in the observations are estimated and incorporated through the use of a space-time random effects (STRE) model. Once the models parameters are estimated, we use it to derive expressions for optimal (minimum mean squared error and unbiased) estimates of the true field at any arbitrary location of interest, computed from the observations. Standard errors of these estimates are also produced, allowing confidence intervals to be constructed. The procedure is carried out on a fine spatial grid to approximate a continuous field. We demonstrate STDF by applying it to the problem of estimating CO2 concentration in the lower-atmosphere using data from the Atmospheric Infrared Sounder (AIRS) and the Japanese Greenhouse Gasses Observing Satellite (GOSAT) over one year for the continental US.

Investigating local controls on temporal stability of soil water content using sensor network data and an inverse modeling approach

NASA Astrophysics Data System (ADS)

Qu, W.; Bogena, H. R.; Huisman, J. A.; Martinez, G.; Pachepsky, Y. A.; Vereecken, H.

2013-12-01

Soil water content is a key variable in the soil, vegetation and atmosphere continuum with high spatial and temporal variability. Temporal stability of soil water content (SWC) has been observed in multiple monitoring studies and the quantification of controls on soil moisture variability and temporal stability presents substantial interest. The objective of this work was to assess the effect of soil hydraulic parameters on the temporal stability. The inverse modeling based on large observed time series SWC with in-situ sensor network was used to estimate the van Genuchten-Mualem (VGM) soil hydraulic parameters in a small grassland catchment located in western Germany. For the inverse modeling, the shuffled complex evaluation (SCE) optimization algorithm was coupled with the HYDRUS 1D code. We considered two cases: without and with prior information about the correlation between VGM parameters. The temporal stability of observed SWC was well pronounced at all observation depths. Both the spatial variability of SWC and the robustness of temporal stability increased with depth. Calibrated models both with and without prior information provided reasonable correspondence between simulated and measured time series of SWC. Furthermore, we found a linear relationship between the mean relative difference (MRD) of SWC and the saturated SWC (θs). Also, the logarithm of saturated hydraulic conductivity (Ks), the VGM parameter n and logarithm of α were strongly correlated with the MRD of saturation degree for the prior information case, but no correlation was found for the non-prior information case except at the 50cm depth. Based on these results we propose that establishing relationships between temporal stability and spatial variability of soil properties presents a promising research avenue for a better understanding of the controls on soil moisture variability. Correlation between Mean Relative Difference of soil water content (or saturation degree) and inversely estimated soil hydraulic parameters (log10(Ks), log10(α), n, and θs) at 5-cm, 20-cm and 50-cm depths. Solid circles represent parameters estimated by using prior information; open circles represent parameters estimated without using prior information.

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

PubMed

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

2018-04-25

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

Correlation Analysis of Geomagnetic Data Synchronously Recorded by the INTERMAGNET Magnetic Laboratories

NASA Astrophysics Data System (ADS)

Vorobev, A. V.; Vorobeva, G. R.

2018-03-01

The results of the analysis of geomagnetic data synchronously recorded by the INTERMAGNET magnetic stations are presented. The goal of this research was to distinguish internal correlations between the data and to determine the optimal spatial interval of the geographical coordinates within which the efficient operation of only one magnetic observatory would be satisfactory in most occasions. The results of the observation of correlations between the geomagnetic data on a global scale are summarized and presented. Possible regions of application of these results are determined.

Comparison of retracked coastal altimetry sea levels against high frequency radar on the continental shelf of the Great Barrier Reef, Australia

NASA Astrophysics Data System (ADS)

Idris, Nurul Hazrina; Deng, Xiaoli; Idris, Nurul Hawani

2017-07-01

Comparison of Jason-1 altimetry retracked sea levels and high frequency (HF) radar velocity is examined within the region of the Great Barrier Reef, Australia. The comparison between both datasets is not direct because the altimetry derives only the geostrophic component, while the HF radar velocity includes information on both geostrophic and ageostrophic components, such as tides and winds. The comparison of altimetry and HF radar data is performed based on the parameter of surface velocity inferred from both datasets. The results show that 48% (10 out of 21 cases) of data have high (≥0.5) spatial correlation. The mean of spatial correlation for all 21 cases is 0.43. This value is within the range (0.42 to 0.5) observed by other studies. Low correlation is observed due to disagreement in the trend of velocity signals in which sometimes they have contradictions in the signal direction and the position of the peak is shifted. In terms of standard deviation of difference and root mean square error, both datasets show reasonable agreement with ≤2.5 cm s-1.

Modification of turbulence and turbulent transport associated with a confinement transition in LAPD

NASA Astrophysics Data System (ADS)

Carter, Troy

2009-11-01

Azimuthal flow is driven in the edge of the Large Plasma Device (LAPD) through biasing a section of the vacuum vessel relative to the plasma source cathode. As the applied bias exceeds a threshold, a transition in radial particle confinement is observed, evidenced by a dramatic steepening in the density profile, similar to the L- to H-mode transition in toroidal confinement devices. The threshold behavior and dynamic behavior of radial transport is related to flow penetration and the degree of spatial overlap between the flow shear and density gradient profiles. An investigation of the changes in turbulence and turbulent particle transport associated with the confinement transition is presented. Two-dimensional cross-correlation measurements show that the spatial coherence of edge turbulence in LAPD changes significantly with biasing. The azimuthal correlation in the turbulence increases dramatically, while the radial correlation length is little altered. Turbulent amplitude is reduced at the transition, particularly in electric field fluctuations, but the dominant change observed is in the cross-phase between density and electric field fluctuations. The changes in cross-phase lead to a suppression and then apparent reversal of turbulent particle flux as the threshold is exceeded.

An alternative way to evaluate chemistry-transport model variability

NASA Astrophysics Data System (ADS)

Menut, Laurent; Mailler, Sylvain; Bessagnet, Bertrand; Siour, Guillaume; Colette, Augustin; Couvidat, Florian; Meleux, Frédérik

2017-03-01

A simple and complementary model evaluation technique for regional chemistry transport is discussed. The methodology is based on the concept that we can learn about model performance by comparing the simulation results with observational data available for time periods other than the period originally targeted. First, the statistical indicators selected in this study (spatial and temporal correlations) are computed for a given time period, using colocated observation and simulation data in time and space. Second, the same indicators are used to calculate scores for several other years while conserving the spatial locations and Julian days of the year. The difference between the results provides useful insights on the model capability to reproduce the observed day-to-day and spatial variability. In order to synthesize the large amount of results, a new indicator is proposed, designed to compare several error statistics between all the years of validation and to quantify whether the period and area being studied were well captured by the model for the correct reasons.

Spatial path models with multiple indicators and multiple causes: mental health in US counties.

PubMed

Congdon, Peter

2011-06-01

This paper considers a structural model for the impact on area mental health outcomes (poor mental health, suicide) of spatially structured latent constructs: deprivation, social capital, social fragmentation and rurality. These constructs are measured by multiple observed effect indicators, with the constructs allowed to be correlated both between and within areas. However, in the scheme developed here, particular latent constructs may also be influenced by known variables, or, via path sequences, by other constructs, possibly nonlinearly. For example, area social capital may be measured by effect indicators (e.g. associational density, charitable activity), but influenced as causes by other constructs (e.g. area deprivation), and by observed features of the socio-ethnic structure of areas. A model incorporating these features is applied to suicide mortality and the prevalence of poor mental health in 3141 US counties, which are related to the latent spatial constructs and to observed variables (e.g. county ethnic mix). Copyright © 2011 Elsevier Ltd. All rights reserved.

Applying Metrological Techniques to Satellite Fundamental Climate Data Records

NASA Astrophysics Data System (ADS)

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.

Spatial Skill Profile of Mathematics Pre-Service Teachers

NASA Astrophysics Data System (ADS)

Putri, R. O. E.

2018-01-01

This study is aimed to investigate the spatial intelligence of mathematics pre-service teachers and find the best instructional strategy that facilitates this aspect. Data were collected from 35 mathematics pre-service teachers. The Purdue Spatial Visualization Test (PSVT) was used to identify the spatial skill of mathematics pre-service teachers. Statistical analysis indicate that more than 50% of the participants possessed spatial skill in intermediate level, whereas the other were in high and low level of spatial skill. The result also shows that there is a positive correlation between spatial skill and mathematics ability, especially in geometrical problem solving. High spatial skill students tend to have better mathematical performance compare to those in two other levels. Furthermore, qualitative analysis reveals that most students have difficulty in manipulating geometrical objects mentally. This problem mostly appears in intermediate and low-level spatial skill students. The observation revealed that 3-D geometrical figures is the best method that can overcome the mentally manipulation problem and develop the spatial visualization. Computer application can also be used to improve students’ spatial skill.

Spatial analysis of highway incident durations in the context of Hurricane Sandy.

PubMed

Xie, Kun; Ozbay, Kaan; Yang, Hong

2015-01-01

The objectives of this study are (1) to develop an incident duration model which can account for the spatial dependence of duration observations, and (2) to investigate the impacts of a hurricane on incident duration. Highway incident data from New York City and its surrounding regions before and after Hurricane Sandy was used for the study. Moran's I statistics confirmed that durations of the neighboring incidents were spatially correlated. Moreover, Lagrange Multiplier tests suggested that the spatial dependence should be captured in a spatial lag specification. A spatial error model, a spatial lag model and a standard model without consideration of spatial effects were developed. The spatial lag model is found to outperform the others by capturing the spatial dependence of incident durations via a spatially lagged dependent variable. It was further used to assess the effects of hurricane-related variables on incident duration. The results show that the incidents during and post the hurricane are expected to have 116.3% and 79.8% longer durations than those that occurred in the regular time. However, no significant increase in incident duration is observed in the evacuation period before Sandy's landfall. Results of temporal stability tests further confirm the existence of the significant changes in incident duration patterns during and post the hurricane. Those findings can provide insights to aid in the development of hurricane evacuation plans and emergency management strategies. Copyright © 2014 Elsevier Ltd. All rights reserved.

Soil Greenhouse Gas Emissions from a Subtropical Mangrove in Hong Kong

NASA Astrophysics Data System (ADS)

Lai, D. Y. F.; Xu, J.

2014-12-01

The concept of "blue carbon" has received increasing attention recently, which points to the potential role of vegetated coastal wetlands in carbon sequestration. Yet, the magnitude and controls of greenhouse gas emissions from coastal wetland ecosystems, especially mangroves in the subtropical regions, are still largely unknown. In this study, we conducted chamber measurements in the Mai Po Marshes Nature Reserve of Hong Kong at monthly intervals to characterize the spatial and temporal variability of the emission of greenhouse gases, including CO2, CH4 and N2O from mangrove soils, and examine the influence of environmental and biotic variables on greenhouse gas fluxes. We found the highest mean CH4 and N2O emissions in autumn and the highest CO2 flux in summer. Along the tidal gradient, we observed significantly higher CH4 and N2O emissions from the middle zones and landward zones, respectively, while no clear spatial variation of CO2 emissions was observed. There were significantly higher soil greenhouse gas emissions from sites dominated by Avicennia marina than those dominated by Kandelia obovata, which might be due to the presence of pneumatophores which facilitated gas transport. We found a significant, negative correlation between CH4 flux and soil NO3-N concentration, while CO2 flux was positively correlation with total Kjeldahl nitrogen content. Soil temperature was positively correlated with the emissions of all three greenhouse gases, while water table depth was positively and negatively correlated with CH4 and N2O emissions, respectively. Our findings demonstrate the high spatial and temporal variability of greenhouse gas emissions from mangrove soils which could be attributed in part to the differences in environmental conditions and dominant plant species.

Scaling relations for watersheds

NASA Astrophysics Data System (ADS)

Fehr, E.; Kadau, D.; Araújo, N. A. M.; Andrade, J. S., Jr.; Herrmann, H. J.

2011-09-01

We study the morphology of watersheds in two and three dimensional systems subjected to different degrees of spatial correlations. The response of these objects to small, local perturbations is also investigated with extensive numerical simulations. We find the fractal dimension of the watersheds to generally decrease with the Hurst exponent, which quantifies the degree of spatial correlations. Moreover, in two dimensions, our results match the range of fractal dimensions 1.10≤df≤1.15 observed for natural landscapes. We report that the watershed is strongly affected by local perturbations. For perturbed two and three dimensional systems, we observe a power-law scaling behavior for the distribution of areas (volumes) enclosed by the original and the displaced watershed and for the distribution of distances between outlets. Finite-size effects are analyzed and the resulting scaling exponents are shown to depend significantly on the Hurst exponent. The intrinsic relation between watershed and invasion percolation, as well as relations between exponents conjectured in previous studies with two dimensional systems, are now confirmed by our results in three dimensions.

A Spatial Perspective of Droughts and Pluvials in the Tropics and their Relationships to ENSO in CMIP5 Model Simulations

NASA Astrophysics Data System (ADS)

Perez Arango, J. D.; Lintner, B. R.; Lyon, B.

2016-12-01

Although many aspects of the tropical response to ENSO are well-known, the spatial characteristics of the rainfall response to ENSO remain relatively unexplored. Moreover, in current generation climate models, the spatial signatures of the ENSO tropical teleconnection are more uncertain than other aspects of ENSO variability, such as the amplitude of rainfall anomalies. Following the approach of Lyon (2004) and Lyon and Barnston (2005), we analyze here integrated measures of the spatial extent of drought and pluvial conditions in the tropics and their relationship to ENSO in observations as well as simulations of Phase 5 of the Coupled Model Intercomparison Project (CMIP5) with prescribed SST forcing. We compute diagnostics including the model ensemble-means and standard deviations of moderate, intermediate, and severe droughts and pluvials and the lagged correlations with respect to ENSO-based SST indices like NINO3. Overall, in a tropics-wide sense, the models generally capture the areal extent of observed droughts and pluvials and their phasing with respect to ENSO. However, at more local scales, e.g., tropical South America, the simulated metrics agree less strongly with observations, underscoring the role of errors in the spatial patterns of ENSO-induced rainfall anomalies.

Reconciling spatial and temporal soil moisture effects on afternoon rainfall

PubMed Central

Guillod, Benoit P.; Orlowsky, Boris; Miralles, Diego G.; Teuling, Adriaan J.; Seneviratne, Sonia I.

2015-01-01

Soil moisture impacts on precipitation have been strongly debated. Recent observational evidence of afternoon rain falling preferentially over land parcels that are drier than the surrounding areas (negative spatial effect), contrasts with previous reports of a predominant positive temporal effect. However, whether spatial effects relating to soil moisture heterogeneity translate into similar temporal effects remains unknown. Here we show that afternoon precipitation events tend to occur during wet and heterogeneous soil moisture conditions, while being located over comparatively drier patches. Using remote-sensing data and a common analysis framework, spatial and temporal correlations with opposite signs are shown to coexist within the same region and data set. Positive temporal coupling might enhance precipitation persistence, while negative spatial coupling tends to regionally homogenize land surface conditions. Although the apparent positive temporal coupling does not necessarily imply a causal relationship, these results reconcile the notions of moisture recycling with local, spatially negative feedbacks. PMID:25740589

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

PubMed Central

Chen, Xin; Wang, Fusheng

2016-01-01

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

Asymptotic correlation functions and FFLO signature for the one-dimensional attractive Hubbard model

NASA Astrophysics Data System (ADS)

Cheng, Song; Jiang, Yuzhu; Yu, Yi-Cong; Batchelor, Murray T.; Guan, Xi-Wen

2018-04-01

We study the long-distance asymptotic behavior of various correlation functions for the one-dimensional (1D) attractive Hubbard model in a partially polarized phase through the Bethe ansatz and conformal field theory approaches. We particularly find the oscillating behavior of these correlation functions with spatial power-law decay, of which the pair (spin) correlation function oscillates with a frequency ΔkF (2 ΔkF). Here ΔkF = π (n↑ -n↓) is the mismatch in the Fermi surfaces of spin-up and spin-down particles. Consequently, the pair correlation function in momentum space has peaks at the mismatch k = ΔkF, which has been observed in recent numerical work on this model. These singular peaks in momentum space together with the spatial oscillation suggest an analog of the Fulde-Ferrell-Larkin-Ovchinnikov (FFLO) state in the 1D Hubbard model. The parameter β representing the lattice effect becomes prominent in critical exponents which determine the power-law decay of all correlation functions. We point out that the backscattering of unpaired fermions and bound pairs within their own Fermi points gives a microscopic origin of the FFLO pairing in 1D.

Correlation of Fin Buffet Pressures on an F/A-18 with Scaled Wind-Tunnel Measurements

NASA Technical Reports Server (NTRS)

Moses, Robert W.; Shah, Gautam H.

1999-01-01

Buffeting is an aeroelastic phenomenon occurring at high angles of attack that plagues high performance aircraft, especially those with twin vertical tails. Previous wind-tunnel and flight tests were conducted to characterize the buffet loads on the vertical tails by measuring surface pressures, bending moments, and accelerations. Following these tests, buffeting responses were computed using the measured buffet pressures and compared to the measured buffeting responses. The calculated results did not match the measured data because the assumed spatial correlation of the buffet pressures was not correct. A better understanding of the partial (spatial) correlation of the differential buffet pressures on the tail was necessary to improve the buffeting predictions. Several wind-tunnel investigations were conducted for this purpose. When compared, the results of these tests show that the partial correlation scales with flight conditions. One of the remaining questions is whether the wind-tunnel data is consistent with flight data. Presented herein, cross-spectra and coherence functions calculated from pressures that were measured on the High Alpha Research Vehicle indicate that the partial correlation of the buffet pressures in flight agrees with the partial correlation observed in the wind tunnel.

Assessment and statistical modeling of the relationship between remotely sensed aerosol optical depth and PM2.5 in the eastern United States.

PubMed

Paciorek, Christopher J; Liu, Yang

2012-05-01

Research in scientific, public health, and policy disciplines relating to the environment increasingly makes use of high-dimensional remote sensing and the output of numerical models in conjunction with traditional observations. Given the public health and resultant public policy implications of the potential health effects of particulate matter (PM*) air pollution, specifically fine PM with an aerodynamic diameter < or = 2.5 pm (PM2.5), there has been substantial recent interest in the use of remote-sensing information, in particular aerosol optical depth (AOD) retrieved from satellites, to help characterize variability in ground-level PM2.5 concentrations in space and time. While the United States and some other developed countries have extensive PM monitoring networks, gaps in data across space and time necessarily occur; the hope is that remote sensing can help fill these gaps. In this report, we are particularly interested in using remote-sensing data to inform estimates of spatial patterns in ambient PM2.5 concentrations at monthly and longer time scales for use in epidemiologic analyses. However, we also analyzed daily data to better disentangle spatial and temporal relationships. For AOD to be helpful, it needs to add information beyond that available from the monitoring network. For analyses of chronic health effects, it needs to add information about the concentrations of long-term average PM2.5; therefore, filling the spatial gaps is key. Much recent evidence has shown that AOD is correlated with PM2.5 in the eastern United States, but the use of AOD in exposure analysis for epidemiologic work has been rare, in part because discrepancies necessarily exist between satellite-retrieved estimates of AOD, which is an atmospheric-column average, and ground-level PM2.5. In this report, we summarize the results of a number of empirical analyses and of the development of statistical models for the use of proxy information, in particular satellite AOD, in predicting PM2.5 concentrations in the eastern United States. We analyzed the spatiotemporal structure of the relationship between PM2.5 and AOD, first using simple correlations both before and after calibration based on meteorology, as well as large-scale spatial and temporal calibration to account for discrepancies between AOD and PM2.5. We then used both raw and calibrated AOD retrievals in statistical models to predict PM2.5 concentrations, accounting for AOD in two ways: primarily as a separate data source contributing a second likelihood to a Bayesian statistical model, as well as a data source on which we could directly regress. Previous consideration of satellite AOD has largely focused on the National Aeronautics and Space Administration (NASA) moderate resolution imaging spectroradiometer (MODIS) and multiangle imaging spectroradiometer (MISR) instruments. One contribution of our work is more extensive consideration of AOD derived from the Geostationary Operational Environmental Satellite East Aerosol/Smoke Product (GOES GASP) AOD and its relationship with PM2.5. In addition to empirically assessing the spatiotemporal relationship between GASP AOD and PM2.5, we considered new statistical techniques to screen anomalous GOES reflectance measurements and account for background surface reflectance. In our statistical work, we developed a new model structure that allowed for more flexible modeling of the proxy discrepancy than previous statistical efforts have had, with a computationally efficient implementation. We also suggested a diagnostic for assessing the scales of the spatial relationship between the proxy and the spatial process of interest (e.g., PM2.5). In brief, we had little success in improving predictions in our eastern-United States domain for use in epidemiologic applications. We found positive correlations of AOD with PM2.5 over time, but less correlation for long-term averages over space, unless we used calibration that adjusted for large-scale discrepancy between AOD and PM2.5 (see sections 3, 4, and 5). Statistical models that combined AOD, PM2.5 observations, and land-use and meteorologic variables were highly predictive of PM2.5 observations held out of the modeling, but AOD added little information beyond that provided by the other sources (see sections 5 and 6). When we used PM2.5 data estimates from the Community Multiscale Air Quality model (CMAQ) as the proxy instead of using AOD, we similarly found little improvement in predicting held-out observations of PM2.5, but when we regressed on CMAQ PM2.5 estimates, the predictions improved moderately in some cases. These results appeared to be caused in part by the fact that large-scale spatial patterns in PM2.5 could be predicted well by smoothing the monitor values, while small-scale spatial patterns in AOD appeared to weakly reflect the variation in PM2.5 inferred from the observations. Using a statistical model that allowed for potential proxy discrepancy at both large and small spatial scales was an important component of our modeling. In particular, when our models did not include a component to account for small-scale discrepancy, predictive performance decreased substantially. Even long-term averages of MISR AOD, considered the best, albeit most sparse, of the AOD products, were only weakly correlated with measured PM2.5 (see section 4). This might have been partly related to the fact that our analysis did not account for spatial variation in the vertical profile of the aerosol. Furthermore, we found evidence that some of the correlation between raw AOD and PM2.5 might have been a function of surface brightness related to land use, rather than having been driven by the detection of aerosol in the AOD retrieval algorithms (see sections 4 and 7). Difficulties in estimating the background surface reflectance in the retrieval algorithms likely explain this finding. With regard to GOES, we found moderate correlations of GASP AOD and PM2.5. The higher correlations of monthly and yearly averages after calibration reflected primarily the improved large-scale correlation, a necessary result of the calibration procedure (see section 3). While the results of this study's GOES reflectance screening and surface reflection correction appeared sensible, correlations of our proposed reflectance-based proxy with PM2.5 were no better than GASP AOD correlations with PM2.5 (see section 7). We had difficulty improving spatial prediction of monthly and yearly average PM2.5 using AOD in the eastern United States, which we attribute to the spatial discrepancy between AOD and measured PM2.5, particularly at smaller scales. This points to the importance of paying attention to the discrepancy structure of proxy information, both from remote-sensing and deterministic models. In particular, important statistical challenges arise in accounting for the discrepancy, given the difficulty in the face of sparse observations of distinguishing the discrepancy from the component of the proxy that is informative about the process of interest. Associations between adverse health outcomes and large-scale variation in PM2.5 (e.g., across regions) may be confounded by unmeasured spatial variation in factors such as diet. Therefore, one important goal was to use AOD to improve predictions of PM2.5 for use in epidemiologic analyses at small-to-moderate spatial scales (within urban areas and within regions). In addition, large-scale PM2.5 variation is well estimated from the monitoring data, at least in the United States. We found little evidence that current AOD products are helpful for improving prediction at small-to-moderate scales in the eastern United States and believe more evidence for the reliability of AOD as a proxy at such scales is needed before making use of AOD for PM2.5 prediction in epidemiologic contexts. While our results relied in part on relatively complicated statistical models, which may be sensitive to modeling assumptions, our exploratory correlation analyses (see sections 3 and 5) and relatively simple regression-style modeling of MISR AOD (see section 4) were consistent with the more complicated modeling results. When assessing the usefulness of AOD in the context of studying chronic health effects, we believe efforts need to focus on disentangling the temporal from the spatial correlations of AOD and PM2.5 and on understanding the spatial scale of correlation and of the discrepancy structure. While our results are discouraging, it is important to note that we attempted to make use of smaller-scale spatial variation in AOD to distinguish spatial variations of relatively small magnitude in long-term concentrations of ambient PM2.5. Our efforts pushed the limits of current technology in a spatial domain with relatively low PM2.5 levels and limited spatial variability. AOD may hold more promise in areas with higher aerosol levels, as the AOD signal would be stronger there relative to the background surface reflectance. Furthermore, for developing countries with high aerosol levels, it is difficult to build statistical models based on PM2.5 measurements and land-use covariates, so AOD may add more incremental information in those contexts. More generally, researchers in remote sensing are involved in ongoing efforts to improve AOD products and develop new approaches to using AOD, such as calibration with model-estimated vertical profiles and the use of speciation information in MISR AOD; these efforts warrant continued investigation of the usefulness of remotely sensed AOD for public health research.

Spatial analysis of storm depths from an Arizona raingage network

NASA Technical Reports Server (NTRS)

Fennessey, N. M.; Eagleson, P. S.; Qinliang, W.; Rodriguez-Iturbe, I.

1986-01-01

Eight years of summer rainstorm observations are analyzed by a dense network of 93 raingages operated by the U.S. Department of Agriculture, Agricultural Research Service, in the 150 km Walnut Gulch experimental catchment near Tucson, Arizona. Storms are defined by the total depths collected at each raingage during the noon-to-noon period for which there was depth recorded at any of the gages. For each of the resulting 428 storm days, the gage depths are interpolated onto a dense grid and the resulting random field analyzed to obtain moments, isohyetal plots, spatial correlation function, variance function, and the spatial distribution of storm depth.

High Concentrations of Hydrogen-bearing Volatiles at the Base of Poleward-facing slopes in the Moon's Large Southern Permanently Shadowed Regions.

NASA Astrophysics Data System (ADS)

McClanahan, T. P.; Mitrofanov, I. G.; Boynton, W. V.; Chin, G.; Livengood, T. A.; Litvak, M. L.; Sanin, A. B.; Starr, R. D.

2016-12-01

In this paper we review evidence that indicates that high concentrations of hydrogen-bearing volatiles are biased towards the base of poleward-facing slopes (PFS) in the Moon's large southern permanently shadowed regions (PSR). Results are derived from a correlated study of Lunar Reconnaissance Orbiter instrument maps of: epithermal neutron leakage flux observed by the Lunar Exploration Neutron Detector (LEND), topography derived from the Lunar Observing Laser Altimeter (LOLA) and surface thermal maps derived from the Diviner radiometer. Maximum concentrations of hydrogen-volatiles, likely as water ice, are observed in the Cabeus crater's PSR, 0.62 wght% water-equivalent-hydrogen. Detailed studies show that the occurrence of hydrogen-volatiles at the base of the (PFS) are correlated with the locations of low PSR temperatures of Cabeus, Haworth, Shoemaker and Faustini. LEND observations show no consistent correlation to smaller impact craters and the lowest temperatures within the PSR's. It is not presently known if the high volatile concentrations are due to downslope migration or thermal stability in the PFS breaks in slope. 15-km Full-width at Half-Maximum (FWHM) is shown to be an upper-bounds condition for the LEND collimated sensor's spatial resolution, derived from a cross-sectional profile, through the permanently shadowed region at Cabeus'. LEND's high-resolution spatial response is further illustrated in a 220-km long profile cut through the co-aligned permanently shadowed regions and partially-illuminated ridges of Haworth, Shoemaker, Faustini and Amundsen craters.

Exploring the spatial variability of soil properties in an Alfisol Catena

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

Rosemary, F.; Vitharana, U. W. A.; Indraratne, S. P.

Detailed digital soil maps showing the spatial heterogeneity of soil properties consistent with the landscape are required for site-specific management of plant nutrients, land use planning and process-based environmental modeling. We characterized the short-scale spatial heterogeneity of soil properties in an Alfisol catena in a tropical landscape of Sri Lanka. The impact of different land-uses (paddy, vegetable and un-cultivated) was examined to assess the impact of anthropogenic activities on the variability of soil properties at the catenary level. Conditioned Latin hypercube sampling was used to collect 58 geo-referenced topsoil samples (0–30 cm) from the study area. Soil samples were analyzedmore » for pH, electrical conductivity (EC), organic carbon (OC), cation exchange capacity (CEC) and texture. The spatial correlation between soil properties was analyzed by computing crossvariograms and subsequent fitting of theoretical model. Spatial distribution maps were developed using ordinary kriging. The range of soil properties, pH: 4.3–7.9; EC: 0.01–0.18 dS m –1 ; OC: 0.1–1.37%; CEC: 0.44– 11.51 cmol (+) kg –1 ; clay: 1.5–25% and sand: 59.1–84.4% and their coefficient of variations indicated a large variability in the study area. Electrical conductivity and pH showed a strong spatial correlation which was reflected by the cross-variogram close to the hull of the perfect correlation. Moreover, cross-variograms calculated for EC and Clay, CEC and OC, CEC and clay and CEC and pH indicated weak positive spatial correlation between these properties. Relative nugget effect (RNE) calculated from variograms showed strongly structured spatial variability for pH, EC and sand content (RNE < 25%) while CEC, organic carbon and clay content showed moderately structured spatial variability (25% < RNE < 75%). Spatial dependencies for examined soil properties ranged from 48 to 984 m. The mixed effects model fitting followed by Tukey's post-hoc test showed significant effect of land use on the spatial variability of EC. Our study revealed a structured variability of topsoil properties in the selected tropical Alfisol catena. Except for EC, observed variability was not modified by the land uses. Investigated soil properties showed distinct spatial structures at different scales and magnitudes of strength. Our results will be useful for digital soil mapping, site specific management of soil properties, developing appropriate land use plans and quantifying anthropogenic impacts on the soil system.« less

Nonmonotonic spatial structure of interneuronal correlations in prefrontal microcircuits

PubMed Central

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

2018-01-01

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

Observations of Electron Vorticity in the Inner Plasmasheet and Its Relationship to Reconnection

NASA Technical Reports Server (NTRS)

Gurgiolo, Chris A.; Goldstein, Melvyn L.; Matthaeus, William H.; Vinas, Adolfo -F.

2011-01-01

Spatial derivatives of the electron moments can be estimated using data from the four Cluster spacecraft. Using spatial derivatives of the velocity we have computed the vorticity in the plasmasheet for several crossings. What we have found is that vorticity appears to be a common feature in the inner plasmasheet. We will show a number of examples. In at least some of the observations the vorticity is well correlated with the passage of Cluster through the ion diffusion region of known reconnection events. That most of the vorticity events observed are reconnection related cannot be dismissed and in fact observations of vorticity may provide a means to locate times when the Cluster spacecraft are magnetically connected to regions where reconnection is taking place. Understanding the role and source of the vorticity should advance our understanding of the dissipation of the turbulence associated with reconnection. In the course of the presentation we will also touch on the methods used to estimate the spatial derivatives as well as the limitations and assumptions involved.

Development of Spatiotemporal Bias-Correction Techniques for Downscaling GCM Predictions

NASA Astrophysics Data System (ADS)

Hwang, S.; Graham, W. D.; Geurink, J.; Adams, A.; Martinez, C. J.

2010-12-01

Accurately representing the spatial variability of precipitation is an important factor for predicting watershed response to climatic forcing, particularly in small, low-relief watersheds affected by convective storm systems. Although Global Circulation Models (GCMs) generally preserve spatial relationships between large-scale and local-scale mean precipitation trends, most GCM downscaling techniques focus on preserving only observed temporal variability on point by point basis, not spatial patterns of events. Downscaled GCM results (e.g., CMIP3 ensembles) have been widely used to predict hydrologic implications of climate variability and climate change in large snow-dominated river basins in the western United States (Diffenbaugh et al., 2008; Adam et al., 2009). However fewer applications to smaller rain-driven river basins in the southeastern US (where preserving spatial variability of rainfall patterns may be more important) have been reported. In this study a new method was developed to bias-correct GCMs to preserve both the long term temporal mean and variance of the precipitation data, and the spatial structure of daily precipitation fields. Forty-year retrospective simulations (1960-1999) from 16 GCMs were collected (IPCC, 2007; WCRP CMIP3 multi-model database: https://esg.llnl.gov:8443/), and the daily precipitation data at coarse resolution (i.e., 280km) were interpolated to 12km spatial resolution and bias corrected using gridded observations over the state of Florida (Maurer et al., 2002; Wood et al, 2002; Wood et al, 2004). In this method spatial random fields which preserved the observed spatial correlation structure of the historic gridded observations and the spatial mean corresponding to the coarse scale GCM daily rainfall were generated. The spatiotemporal variability of the spatio-temporally bias-corrected GCMs were evaluated against gridded observations, and compared to the original temporally bias-corrected and downscaled CMIP3 data for the central Florida. The hydrologic response of two southwest Florida watersheds to the gridded observation data, the original bias corrected CMIP3 data, and the new spatiotemporally corrected CMIP3 predictions was compared using an integrated surface-subsurface hydrologic model developed by Tampa Bay Water.

Weather Types, temperature and relief relationship in the Iberian Peninsula: A regional adiabatic processes under directional weather types

NASA Astrophysics Data System (ADS)

Peña Angulo, Dhais; Trigo, Ricardo; Cortesi, Nicola; Gonzalez-Hidalgo, Jose Carlos

2016-04-01

We have analyzed at monthly scale the spatial distribution of Pearson correlation between monthly mean of maximum (Tmax) and minimum (Tmin) temperatures with weather types (WTs) in the Iberian Peninsula (IP), represent them in a high spatial resolution grid (10km x 10km) from MOTEDAS dataset (Gonzalez-Hidalgo et al., 2015a). The WT classification was that developed by Jenkinson and Collison, adapted to the Iberian Peninsula by Trigo and DaCamara, using Sea Level Pressure data from NCAR/NCEP Reanalysis dataset (period 1951-2010). The spatial distribution of Pearson correlations shows a clear zonal gradient in Tmax under the zonal advection produced in westerly (W) and easterly (E) flows, with negative correlation in the coastland where the air mass come from but positive correlation to the inland areas. The same is true under North-West (NW), North-East (NE), South-West (SW) and South-East (SE) WTs. These spatial gradients are coherent with the spatial distribution of the main mountain chain and offer an example of regional adiabatic phenomena that affect the entire IP (Peña-Angulo et al., 2015b). These spatial gradients have not been observed in Tmin. We suggest that Tmin values are less sensitive to changes in Sea Level Pressure and more related to local factors. These directional WT present a monthly frequency over 10 days and could be a valuable tool for downscaling processes. González-Hidalgo J.C., Peña-Angulo D., Brunetti M., Cortesi, C. (2015a): MOTEDAS: a new monthly temperature database for mainland Spain and the trend in temperature (1951-2010). International Journal of Climatology 31, 715-731. DOI: 10.1002/joc.4298 Peña-Angulo, D., Trigo, R., Cortesi, C., González-Hidalgo, J.C. (2015b): The influence of weather types on the monthly average maximum and minimum temperatures in the Iberian Peninsula. Submitted to Hydrology and Earth System Sciences.

Temporal and spatial characteristics of annual and seasonal rainfall in Malawi

NASA Astrophysics Data System (ADS)

Ngongondo, Cosmo; Xu, Chong-Yu; Gottschalk, Lars; Tallaksen, Lena M.; Alemaw, Berhanu

2010-05-01

An understanding of the temporal and spatial characteristics of rainfall is central to water resources planning and management. However, such information is often limited in many developing countries like Malawi. In an effort to bridge the information gap, this study examined the temporal and spatial charecteristics of rainfall in Malawi. Rainfall readings from 42 stations across Malawi from 1960 to 2006 were analysed at monthly, annual and seasonal scales. The Malawian rainfall season lasts from November to April. The data were firstly subjected to quality checks through the cumulative deviations test and the Standard Normal Homogeinity Test (SNHT). Monthly distribution in a typical year, called heterogeneity, was investigated using the Precipitation Concentration Index (PCI). Further, normalized precipitation anomaly series of annual rainfall series (AR) and the PCI (APCI) were used to test for interannual rainfall variability. Spatial variability was characterised by fitting the Spatial Correlation function (SCF). The nonparametric Mann-Kendall statistic was used to investigate the temporal trends of the various rainfall variables. The results showed that 40 of the stations passed both data quality tests. For the two stations that failed, the data were adjusted using nearby stations. Annual and seasonal rainfall were found to be characterised by high spatial variation. The country mean annual rainfall was 1095 mm with mean interannual variability of 26%. The highland areas to the north and southeast of the country exhibited the highest rainfall and lowest interannual variability. Lowest rainfall coupled with high interannual variability was found in the Lower Shire basin, in the southern part of Malawi. This simillarity is the pattern of annual and seasonal rainfall should be expected because all stations had over 90% of their observed annual rainfall in the six month period between November and April. Monthly rainfall was found to be highly variable both temporally and spatially. None of the stations have stable monthly rainfall regimes (mean PCI of less than 10). Stations with the highest mean rainfall were found to have a lower interannual variability. The rainfall stations showed low spatial correlations for annual, monthly as well as seasonal timescales indicating that the data may not be suitable for spatial interpolation. However, some structure (i.e. lower correlation with distance) could be observed when aggregating the data at 50 mile intervals. The annual and seasonal rainfall series were dominated by negative trends. The spatial distribution of the trends can be described as heterogeneous, although most of the stations in the southern region have negative trends. At the monthly timescale, 37 of the stations show a negative trend with four of the stations, all in the south, showing significant negative trends. On the other hand, only 5 stations show positive trends with only one significant trend in the south. Keywords: Malawi, rainfall trends, spatial variation

Comparison of spatial variability in visible and near-infrared spectral images

USGS Publications Warehouse

Chavez, P.S.

1992-01-01

The visible and near-infrared bands of the Landsat Thematic Mapper (TM) and the Satellite Pour l'Observation de la Terre (SPOT) were analyzed to determine which band contained more spatial variability. It is important for applications that require spatial information, such as those dealing with mapping linear features and automatic image-to-image correlation, to know which spectral band image should be used. Statistical and visual analyses were used in the project. The amount of variance in an 11 by 11 pixel spatial filter and in the first difference at the six spacings of 1, 5, 11, 23, 47, and 95 pixels was computed for the visible and near-infrared bands. The results indicate that the near-infrared band has more spatial variability than the visible band, especially in images covering densely vegetated areas. -Author

[Prediction and spatial distribution of recruitment trees of natural secondary forest based on geographically weighted Poisson model].

PubMed

Zhang, Ling Yu; Liu, Zhao Gang

2017-12-01

Based on the data collected from 108 permanent plots of the forest resources survey in Maoershan Experimental Forest Farm during 2004-2016, this study investigated the spatial distribution of recruitment trees in natural secondary forest by global Poisson regression and geographically weighted Poisson regression (GWPR) with four bandwidths of 2.5, 5, 10 and 15 km. The simulation effects of the 5 regressions and the factors influencing the recruitment trees in stands were analyzed, a description was given to the spatial autocorrelation of the regression residuals on global and local levels using Moran's I. The results showed that the spatial distribution of the number of natural secondary forest recruitment was significantly influenced by stands and topographic factors, especially average DBH. The GWPR model with small scale (2.5 km) had high accuracy of model fitting, a large range of model parameter estimates was generated, and the localized spatial distribution effect of the model parameters was obtained. The GWPR model at small scale (2.5 and 5 km) had produced a small range of model residuals, and the stability of the model was improved. The global spatial auto-correlation of the GWPR model residual at the small scale (2.5 km) was the lowe-st, and the local spatial auto-correlation was significantly reduced, in which an ideal spatial distribution pattern of small clusters with different observations was formed. The local model at small scale (2.5 km) was much better than the global model in the simulation effect on the spatial distribution of recruitment tree number.

Spatial correlation of probabilistic earthquake ground motion and loss

USGS Publications Warehouse

Wesson, R.L.; Perkins, D.M.

2001-01-01

Spatial correlation of annual earthquake ground motions and losses can be used to estimate the variance of annual losses to a portfolio of properties exposed to earthquakes A direct method is described for the calculations of the spatial correlation of earthquake ground motions and losses. Calculations for the direct method can be carried out using either numerical quadrature or a discrete, matrix-based approach. Numerical results for this method are compared with those calculated from a simple Monte Carlo simulation. Spatial correlation of ground motion and loss is induced by the systematic attenuation of ground motion with distance from the source, by common site conditions, and by the finite length of fault ruptures. Spatial correlation is also strongly dependent on the partitioning of the variability, given an event, into interevent and intraevent components. Intraevent variability reduces the spatial correlation of losses. Interevent variability increases spatial correlation of losses. The higher the spatial correlation, the larger the variance in losses to a port-folio, and the more likely extreme values become. This result underscores the importance of accurately determining the relative magnitudes of intraevent and interevent variability in ground-motion studies, because of the strong impact in estimating earthquake losses to a portfolio. The direct method offers an alternative to simulation for calculating the variance of losses to a portfolio, which may reduce the amount of calculation required.

Spatial learning in rats: correlation with cortical choline acetyltransferase and improvement with NGF following NBM damage.

PubMed

Mandel, R J; Gage, F H; Thal, L J

1989-06-01

Rats display an acquisition deficit in a circular water maze following excitotoxic lesions of the nucleus basalis magnocellularis (NBM). Experiments were therefore performed to determine if acquisition behavior on this task could predict the degree of cortical cholinergic deafferentation and if the acquisition deficit could be pharmacologically reversed. Performance on acquisition was highly correlated with the lesion-induced reduction in cortical choline acetyltransferase (ChAT) activity. Accuracy of spatial behavior was highly correlated to percentage ChAT depletion (r = 0.75). Neither lesioned rats nor controls displayed a retention deficit after a 9-day interval, nor did either group display a passive-avoidance retention deficit. To test the causal relationship between cholinergic dysfunction and spatial behavior, the central nervous system cholinergic enhancer nerve growth factor (NGF) was intraventricularly infused for 4 weeks. NGF infusion resulted in improved acquisition of the water maze task compared to NBM-lesioned rats receiving vehicle infusion and untreated rats with NBM lesions. These studies indicate that the decrease in cortical ChAT activity is likely to be responsible for the observed acquisition deficit and that pharmacological manipulations can be successfully used to improve behavior following NBM lesions.

Trees Grow on Money: Urban Tree Canopy Cover and Environmental Justice

PubMed Central

Schwarz, Kirsten; Fragkias, Michail; Boone, Christopher G.; Zhou, Weiqi; McHale, Melissa; Grove, J. Morgan; O’Neil-Dunne, Jarlath; McFadden, Joseph P.; Buckley, Geoffrey L.; Childers, Dan; Ogden, Laura; Pincetl, Stephanie; Pataki, Diane; Whitmer, Ali; Cadenasso, Mary L.

2015-01-01

This study examines the distributional equity of urban tree canopy (UTC) cover for Baltimore, MD, Los Angeles, CA, New York, NY, Philadelphia, PA, Raleigh, NC, Sacramento, CA, and Washington, D.C. using high spatial resolution land cover data and census data. Data are analyzed at the Census Block Group levels using Spearman’s correlation, ordinary least squares regression (OLS), and a spatial autoregressive model (SAR). Across all cities there is a strong positive correlation between UTC cover and median household income. Negative correlations between race and UTC cover exist in bivariate models for some cities, but they are generally not observed using multivariate regressions that include additional variables on income, education, and housing age. SAR models result in higher r-square values compared to the OLS models across all cities, suggesting that spatial autocorrelation is an important feature of our data. Similarities among cities can be found based on shared characteristics of climate, race/ethnicity, and size. Our findings suggest that a suite of variables, including income, contribute to the distribution of UTC cover. These findings can help target simultaneous strategies for UTC goals and environmental justice concerns. PMID:25830303

Spatial Correlations of Malaria Incidence Hotspots with Environmental Factors in Assam, North East India

NASA Astrophysics Data System (ADS)

Handique, Bijoy K.; Khan, Siraj A.; Dutta, Prafulla; Nath, Manash J.; Qadir, Abdul; Raju, P. L. N.

2016-06-01

Malaria is endemic and a major public health problem in north east (NE) region of India and contributes about 8-12 % of India's malaria positives cases. Historical morbidity pattern of malaria in terms of API (Annual Parasite Incidence) in the state of Assam has been used for delineating the malaria incidence hotspots at health sub centre (HSC) level. Strong spatial autocorrelation (p < 0.01) among the HSCs have been observed in terms of API (Annual Parasite Incidence). Malaria incidence hot spots in the state could be identified based on General G statistics and tested for statistical significance. Spatial correlation of malaria incidence hotspots with physiographic and climatic parameters across 6 agro-climatic zones of the state reveals the types of land cover pattern and the range of elevation contributing to the malaria outbreaks. Analysis shows that villages under malaria hotspots are having more agricultural land, evergreen/semi-evergreen forests with abundant waterbodies. Statistical and spatial analyses of malaria incidence showed a significant positive correlation with malaria incidence hotspots and the elevation (p < 0.05) with villages under malaria hotspots are having average elevation ranging between 17 to 240 MSL. This conforms to the characteristics of two dominant mosquito species in the state Anopheles minimus and An. baimai that prefers the habitat of slow flowing streams in the foot hills and in forest ecosystems respectively.

Spatial Variation of Soil Respiration in a Cropland under Winter Wheat and Summer Maize Rotation in the North China Plain.

PubMed

Huang, Ni; Wang, Li; Hu, Yongsen; Tian, Haifeng; Niu, Zheng

2016-01-01

Spatial variation of soil respiration (Rs) in cropland ecosystems must be assessed to evaluate the global terrestrial carbon budget. This study aims to explore the spatial characteristics and controlling factors of Rs in a cropland under winter wheat and summer maize rotation in the North China Plain. We collected Rs data from 23 sample plots in the cropland. At the late jointing stage, the daily mean Rs of summer maize (4.74 μmol CO2 m-2 s-1) was significantly higher than that of winter wheat (3.77μmol CO2 m-2 s-1). However, the spatial variation of Rs in summer maize (coefficient of variation, CV = 12.2%) was lower than that in winter wheat (CV = 18.5%). A similar trend in CV was also observed for environmental factors but not for biotic factors, such as leaf area index, aboveground biomass, and canopy chlorophyll content. Pearson's correlation analyses based on the sampling data revealed that the spatial variation of Rs was poorly explained by the spatial variations of biotic factors, environmental factors, or soil properties alone for winter wheat and summer maize. The similarly non-significant relationship was observed between Rs and the enhanced vegetation index (EVI), which was used as surrogate for plant photosynthesis. EVI was better correlated with field-measured leaf area index than the normalized difference vegetation index and red edge chlorophyll index. All the data from the 23 sample plots were categorized into three clusters based on the cluster analysis of soil carbon/nitrogen and soil organic carbon content. An apparent improvement was observed in the relationship between Rs and EVI in each cluster for both winter wheat and summer maize. The spatial variation of Rs in the cropland under winter wheat and summer maize rotation could be attributed to the differences in spatial variations of soil properties and biotic factors. The results indicate that applying cluster analysis to minimize differences in soil properties among different clusters can improve the role of remote sensing data as a proxy of plant photosynthesis in semi-empirical Rs models and benefit the acquisition of Rs in cropland ecosystems at large scales.

Cerebral Correlates of Emotional and Action Appraisals During Visual Processing of Emotional Scenes Depending on Spatial Frequency: A Pilot Study.

PubMed

Campagne, Aurélie; Fradcourt, Benoit; Pichat, Cédric; Baciu, Monica; Kauffmann, Louise; Peyrin, Carole

2016-01-01

Visual processing of emotional stimuli critically depends on the type of cognitive appraisal involved. The present fMRI pilot study aimed to investigate the cerebral correlates involved in the visual processing of emotional scenes in two tasks, one emotional, based on the appraisal of personal emotional experience, and the other motivational, based on the appraisal of the tendency to action. Given that the use of spatial frequency information is relatively flexible during the visual processing of emotional stimuli depending on the task's demands, we also explored the effect of the type of spatial frequency in visual stimuli in each task by using emotional scenes filtered in low spatial frequency (LSF) and high spatial frequencies (HSF). Activation was observed in the visual areas of the fusiform gyrus for all emotional scenes in both tasks, and in the amygdala for unpleasant scenes only. The motivational task induced additional activation in frontal motor-related areas (e.g. premotor cortex, SMA) and parietal regions (e.g. superior and inferior parietal lobules). Parietal regions were recruited particularly during the motivational appraisal of approach in response to pleasant scenes. These frontal and parietal activations, respectively, suggest that motor and navigation processes play a specific role in the identification of the tendency to action in the motivational task. Furthermore, activity observed in the motivational task, in response to both pleasant and unpleasant scenes, was significantly greater for HSF than for LSF scenes, suggesting that the tendency to action is driven mainly by the detailed information contained in scenes. Results for the emotional task suggest that spatial frequencies play only a small role in the evaluation of unpleasant and pleasant emotions. Our preliminary study revealed a partial distinction between visual processing of emotional scenes during identification of the tendency to action, and during identification of personal emotional experiences. It also illustrates flexible use of the spatial frequencies contained in scenes depending on their emotional valence and on task demands.

Soil moisture estimation by assimilating L-band microwave brightness temperature with geostatistics and observation localization.

PubMed

Han, Xujun; Li, Xin; Rigon, Riccardo; Jin, Rui; Endrizzi, Stefano

2015-01-01

The observation could be used to reduce the model uncertainties with data assimilation. If the observation cannot cover the whole model area due to spatial availability or instrument ability, how to do data assimilation at locations not covered by observation? Two commonly used strategies were firstly described: One is covariance localization (CL); the other is observation localization (OL). Compared with CL, OL is easy to parallelize and more efficient for large-scale analysis. This paper evaluated OL in soil moisture profile characterizations, in which the geostatistical semivariogram was used to fit the spatial correlated characteristics of synthetic L-Band microwave brightness temperature measurement. The fitted semivariogram model and the local ensemble transform Kalman filter algorithm are combined together to weight and assimilate the observations within a local region surrounding the grid cell of land surface model to be analyzed. Six scenarios were compared: 1_Obs with one nearest observation assimilated, 5_Obs with no more than five nearest local observations assimilated, and 9_Obs with no more than nine nearest local observations assimilated. The scenarios with no more than 16, 25, and 36 local observations were also compared. From the results we can conclude that more local observations involved in assimilation will improve estimations with an upper bound of 9 observations in this case. This study demonstrates the potentials of geostatistical correlation representation in OL to improve data assimilation of catchment scale soil moisture using synthetic L-band microwave brightness temperature, which cannot cover the study area fully in space due to vegetation effects.

Soil Moisture Estimation by Assimilating L-Band Microwave Brightness Temperature with Geostatistics and Observation Localization

PubMed Central

Han, Xujun; Li, Xin; Rigon, Riccardo; Jin, Rui; Endrizzi, Stefano

2015-01-01

The observation could be used to reduce the model uncertainties with data assimilation. If the observation cannot cover the whole model area due to spatial availability or instrument ability, how to do data assimilation at locations not covered by observation? Two commonly used strategies were firstly described: One is covariance localization (CL); the other is observation localization (OL). Compared with CL, OL is easy to parallelize and more efficient for large-scale analysis. This paper evaluated OL in soil moisture profile characterizations, in which the geostatistical semivariogram was used to fit the spatial correlated characteristics of synthetic L-Band microwave brightness temperature measurement. The fitted semivariogram model and the local ensemble transform Kalman filter algorithm are combined together to weight and assimilate the observations within a local region surrounding the grid cell of land surface model to be analyzed. Six scenarios were compared: 1_Obs with one nearest observation assimilated, 5_Obs with no more than five nearest local observations assimilated, and 9_Obs with no more than nine nearest local observations assimilated. The scenarios with no more than 16, 25, and 36 local observations were also compared. From the results we can conclude that more local observations involved in assimilation will improve estimations with an upper bound of 9 observations in this case. This study demonstrates the potentials of geostatistical correlation representation in OL to improve data assimilation of catchment scale soil moisture using synthetic L-band microwave brightness temperature, which cannot cover the study area fully in space due to vegetation effects. PMID:25635771

Measurement of clavicular length and shortening after a midshaft clavicular fracture: Spatial digitization versus planar roentgen photogrammetry.

PubMed

Stegeman, Sylvia A; de Witte, Pieter Bas; Boonstra, Sjoerd; de Groot, Jurriaan H; Nagels, Jochem; Krijnen, Pieta; Schipper, Inger B

2016-08-01

Clavicular shortening after fracture is deemed prognostic for clinical outcome and is therefore generally assessed on radiographs. It is used for clinical decision making regarding operative or non-operative treatment in the first 2weeks after trauma, although the reliability and accuracy of the measurements are unclear. This study aimed to assess the reliability of roentgen photogrammetry (2D) of clavicular length and shortening, and to compare these with 3D-spatial digitization measurements, obtained with an electromagnetic recording system (Flock of Birds). Thirty-two participants with a consolidated non-operatively treated two or multi-fragmented dislocated midshaft clavicular fracture were analysed. Two observers measured clavicular lengths and absolute and proportional clavicular shortening on radiographs taken before and after fracture consolidation. The clavicular lengths were also measured with spatial digitization. Inter-observer agreement on the radiographic measurements was assessed using the Intraclass Correlation Coefficient (ICC). Agreement between the radiographic and spatial digitization measurements was assessed using a Bland-Altman plot. The inter-observer agreement on clavicular length, and absolute and proportional shortening on trauma radiographs was almost perfect (ICC>0.90), but moderate for absolute shortening after consolidation (ICC=0.45). The Bland-Altman plot compared measurements of length on AP panorama radiographs with spatial digitization and showed that planar roentgen photogrammetry resulted in up to 37mm longer and 34mm shorter measurements than spatial digitization. Measurements of clavicular length on radiographs are highly reliable between observers, but may not reflect the actual length and shortening of the clavicle when compared to length measurements with spatial digitization. We recommend to use proportional shortening when measuring clavicular length or shortening on radiographs for clinical decision making. Copyright © 2015 Elsevier Ltd. All rights reserved.

Agricultural Decision Support Through Robust Assimilation of Satellite Derived Soil Moisture Estimates

NASA Astrophysics Data System (ADS)

Mishra, V.; Cruise, J.; Mecikalski, J. R.

2012-12-01

Soil Moisture is a key component in the hydrological process, affects surface and boundary layer energy fluxes and is the driving factor in agricultural production. Multiple in situ soil moisture measuring instruments such as Time-domain Reflectrometry (TDR), Nuclear Probes etc. are in use along with remote sensing methods like Active and Passive Microwave (PM) sensors. In situ measurements, despite being more accurate, can only be obtained at discrete points over small spatial scales. Remote sensing estimates, on the other hand, can be obtained over larger spatial domains with varying spatial and temporal resolutions. Soil moisture profiles derived from satellite based thermal infrared (TIR) imagery can overcome many of the problems associated with laborious in-situ observations over large spatial domains. An area where soil moisture observation and assimilation is receiving increasing attention is agricultural crop modeling. This study revolves around the use of the Decision Support System for Agrotechnology Transfer (DSSAT) crop model to simulate corn yields under various forcing scenarios. First, the model was run and calibrated using observed precipitation and model generated soil moisture dynamics. Next, the modeled soil moisture was updated using estimates derived from satellite based TIR imagery and the Atmospheric Land Exchange Inverse (ALEXI) model. We selected three climatically different locations to test the concept. Test Locations were selected to represent varied climatology. Bell Mina, Alabama - South Eastern United States, representing humid subtropical climate. Nabb, Indiana - Mid Western United States, representing humid continental climate. Lubbok, Texas - Southern United States, representing semiarid steppe climate. A temporal (2000-2009) correlation analysis of the soil moisture values from both DSSAT and ALEXI were performed and validated against the Land Information System (LIS) soil moisture dataset. The results clearly show strong correlation (R = 73%) between ALEXI and DSSAT at Bell Mina. At Nabb and Lubbock the correlation was 50-60%. Further, multiple experiments were conducted for each location: a) a DSSAT rain-fed 10 year sequential run forced with daymet precipitation; b) a DSSAT sequential run with no precipitation data; and c) a DSSAT run forced with ALEXI soil moisture estimates alone. The preliminary results of all the experiments are quantified through soil moisture correlations and yield comparisons. In general, the preliminary results strongly suggest that DSSAT forced with ALEXI can provide significant information especially at locations where no significant precipitation data exists.

Nonparametric Bayesian models for a spatial covariance.

PubMed

Reich, Brian J; Fuentes, Montserrat

2012-01-01

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

Application of Spectral Analysis Techniques in the Intercomparison of Aerosol Data. Part II: Using Maximum Covariance Analysis to Effectively Compare Spatiotemporal Variability of Satellite and AERONET Measured Aerosol Optical Depth

NASA Technical Reports Server (NTRS)

Li, Jing; Carlson, Barbara E.; Lacis, Andrew A.

2014-01-01

Moderate Resolution Imaging SpectroRadiometer (MODIS) and Multi-angle Imaging Spectroradiomater (MISR) provide regular aerosol observations with global coverage. It is essential to examine the coherency between space- and ground-measured aerosol parameters in representing aerosol spatial and temporal variability, especially in the climate forcing and model validation context. In this paper, we introduce Maximum Covariance Analysis (MCA), also known as Singular Value Decomposition analysis as an effective way to compare correlated aerosol spatial and temporal patterns between satellite measurements and AERONET data. This technique not only successfully extracts the variability of major aerosol regimes but also allows the simultaneous examination of the aerosol variability both spatially and temporally. More importantly, it well accommodates the sparsely distributed AERONET data, for which other spectral decomposition methods, such as Principal Component Analysis, do not yield satisfactory results. The comparison shows overall good agreement between MODIS/MISR and AERONET AOD variability. The correlations between the first three modes of MCA results for both MODIS/AERONET and MISR/ AERONET are above 0.8 for the full data set and above 0.75 for the AOD anomaly data. The correlations between MODIS and MISR modes are also quite high (greater than 0.9). We also examine the extent of spatial agreement between satellite and AERONET AOD data at the selected stations. Some sites with disagreements in the MCA results, such as Kanpur, also have low spatial coherency. This should be associated partly with high AOD spatial variability and partly with uncertainties in satellite retrievals due to the seasonally varying aerosol types and surface properties.

Functional imaging of the nonhuman primate Placenta with endogenous blood oxygen level-dependent contrast.

PubMed

Schabel, M C; Roberts, V H J; Lo, J O; Platt, S; Grant, K A; Frias, A E; Kroenke, C D

2016-11-01

To characterize spatial patterns of T2* in the placenta of the rhesus macaque (Macaca mulatta), to correlate these patterns with placental perfusion determined using dynamic contrast-enhanced MRI (DCE-MRI), and to evaluate the potential for using the blood oxygen level-dependent effect to quantify placental perfusion without the use of exogenous contrast reagent. MRI was performed on three pregnant rhesus macaques at gestational day 110. Multiecho spoiled gradient echo measurements were used to compute maps of T2*. Spatial maxima in these maps were compared with foci of early enhancement determined by DCE-MRI. Local maxima in T2* maps were strongly correlated with spiral arteries identified by DCE-MRI, with mean spatial separations ranging from 2.34 to 6.11 mm in the three animals studied. Spatial patterns of R2* ( = 1/ T2*) within individual placental lobules can be quantitatively analyzed using a simple model to estimate fetal arterial oxyhemoglobin concentration [Hbo,f] and a parameter viPS/Φ, reflecting oxygen transport to the fetus. Estimated mean values of [Hbo,f] ranged from 4.25 mM to 4.46 mM, whereas viPS/Φ ranged from 2.80 × 10 5 cm -3 to 1.61 × 10 6 cm -3 . Maternal spiral arteries show strong spatial correlation with foci of extended T2* observed in the primate placenta. A simple model of oxygen transport accurately describes the spatial dependence of R2* within placental lobules and enables assessment of placental function and oxygenation without requiring administration of an exogenous contrast reagent. Magn Reson Med 76:1551-1562, 2016. © 2015 International Society for Magnetic Resonance in Medicine. © 2015 International Society for Magnetic Resonance in Medicine.

The role of storm scale, position and movement in controlling urban flood response

NASA Astrophysics Data System (ADS)

ten Veldhuis, Marie-claire; Zhou, Zhengzheng; Yang, Long; Liu, Shuguang; Smith, James

2018-01-01

The impact of spatial and temporal variability of rainfall on hydrological response remains poorly understood, in particular in urban catchments due to their strong variability in land use, a high degree of imperviousness and the presence of stormwater infrastructure. In this study, we analyze the effect of storm scale, position and movement in relation to basin scale and flow-path network structure on urban hydrological response. A catalog of 279 peak events was extracted from a high-quality observational dataset covering 15 years of flow observations and radar rainfall data for five (semi)urbanized basins ranging from 7.0 to 111.1 km2 in size. Results showed that the largest peak flows in the event catalog were associated with storm core scales exceeding basin scale, for all except the largest basin. Spatial scale of flood-producing storm events in the smaller basins fell into two groups: storms of large spatial scales exceeding basin size or small, concentrated events, with storm core much smaller than basin size. For the majority of events, spatial rainfall variability was strongly smoothed by the flow-path network, increasingly so for larger basin size. Correlation analysis showed that position of the storm in relation to the flow-path network was significantly correlated with peak flow in the smallest and in the two more urbanized basins. Analysis of storm movement relative to the flow-path network showed that direction of storm movement, upstream or downstream relative to the flow-path network, had little influence on hydrological response. Slow-moving storms tend to be associated with higher peak flows and longer lag times. Unexpectedly, position of the storm relative to impervious cover within the basins had little effect on flow peaks. These findings show the importance of observation-based analysis in validating and improving our understanding of interactions between the spatial distribution of rainfall and catchment variability.

Continuous rainfall simulation for regional flood risk assessment - application in the Austrian Alps

NASA Astrophysics Data System (ADS)

Salinas, Jose Luis; Nester, Thomas; Komma, Jürgen; Blöschl, Günter

2017-04-01

Generation of realistic synthetic spatial rainfall is of pivotal importance for assessing regional hydroclimatic hazard as the input for long term rainfall-runoff simulations. The correct reproduction of the observed rainfall characteristics, such as regional intensity-duration-frequency curves, is necessary to adequately model the magnitude and frequency of the flood peaks. Furthermore, the replication of the observed rainfall spatial and temporal correlations allows to model important other hydrological features like antecedent soil moisture conditions before extreme rainfall events. In this work, we present an application in the Tirol region (Austrian alps) of a modification of the model presented by Bardossy and Platte (1992), where precipitation is modeled on a station basis as a mutivariate autoregressive model (mAr) in a Normal space, and then transformed to a Gamma-distributed space. For the sake of simplicity, the parameters of the Gamma distributions are assumed to vary monthly according to a sinusoidal function, and are calibrated trying to simultaneously reproduce i) mean annual rainfall, ii) mean daily rainfall amounts, iii) standard deviations of daily rainfall amounts, and iv) 24-hours intensity duration frequency curve. The calibration of the spatial and temporal correlation parameters is performed in a way that the intensity-duration-frequency curves aggregated at different spatial and temporal scales reproduce the measured ones. Bardossy, A., and E. J. Plate (1992), Space-time model for daily rainfall using atmospheric circulation patterns, Water Resour. Res., 28(5), 1247-1259, doi:10.1029/91WR02589.

Effects of long-term fluid injection on induced seismicity parameters and maximum magnitude in northwestern part of The Geysers geothermal field

NASA Astrophysics Data System (ADS)

Kwiatek, Grzegorz; Martínez-Garzón, Patricia; Dresen, Georg; Bohnhoff, Marco; Sone, Hiroki; Hartline, Craig

2015-10-01

The long-term temporal and spatial changes in statistical, source, and stress characteristics of one cluster of induced seismicity recorded at The Geysers geothermal field (U.S.) are analyzed in relation to the field operations, fluid migration, and constraints on the maximum likely magnitude. Two injection wells, Prati-9 and Prati-29, located in the northwestern part of the field and their associated seismicity composed of 1776 events recorded throughout a 7 year period were analyzed. The seismicity catalog was relocated, and the source characteristics including focal mechanisms and static source parameters were refined using first-motion polarity, spectral fitting, and mesh spectral ratio analysis techniques. The source characteristics together with statistical parameters (b value) and cluster dynamics were used to investigate and understand the details of fluid migration scheme in the vicinity of injection wells. The observed temporal, spatial, and source characteristics were clearly attributed to fluid injection and fluid migration toward greater depths, involving increasing pore pressure in the reservoir. The seasonal changes of injection rates were found to directly impact the shape and spatial extent of the seismic cloud. A tendency of larger seismic events to occur closer to injection wells and a correlation between the spatial extent of the seismic cloud and source sizes of the largest events was observed suggesting geometrical constraints on the maximum likely magnitude and its correlation to the average injection rate and volume of fluids present in the reservoir.

Diversity, composition, and geographical distribution of microbial communities in California salt marsh sediments

USGS Publications Warehouse

Cordova-Kreylos, A. L.; Cao, Y.; Green, P.G.; Hwang, H.-M.; Kuivila, K.M.; LaMontagne, M.G.; Van De Werfhorst, L. C.; Holden, P.A.; Scow, K.M.

2006-01-01

The Pacific Estuarine Ecosystem Indicators Research Consortium seeks to develop bioindicators of toxicant-induced stress and bioavailability for wetland biota. Within this framework, the effects of environmental and pollutant variables on microbial communities were studied at different spatial scales over a 2-year period. Six salt marshes along the California coastline were characterized using phospholipid fatty acid (PLFA) analysis and terminal restriction fragment length polymorphism (TRFLP) analysis. Additionally, 27 metals, six currently used pesticides, total polychlorinated biphenyls and polycyclic aromatic hydrocarbons, chlordanes, nonachlors, dichlorodiphenyldichloroethane, and dichlorodiphenyldichloroethylene were analyzed. Sampling was performed over large (between salt marshes), medium (stations within a marsh), and small (different channel depths) spatial scales. Regression and ordination analysis suggested that the spatial variation in microbial communities exceeded the variation attributable to pollutants. PLFA analysis and TRFLP canonical correspondence analysis (CCA) explained 74 and 43% of the variation, respectively, and both methods attributed 34% of the variation to tidal cycles, marsh, year, and latitude. After accounting for spatial variation using partial CCA, we found that metals had a greater effect on microbial community composition than organic pollutants had. Organic carbon and nitrogen contents were positively correlated with PLFA biomass, whereas total metal concentrations were positively correlated with biomass and diversity. Higher concentrations of heavy metals were negatively correlated with branched PLFAs and positively correlated with methyl- and cyclo-substituted PLFAs. The strong relationships observed between pollutant concentrations and some of the microbial indicators indicated the potential for using microbial community analyses in assessments of the ecosystem health of salt marshes. Copyright ?? 2006, American Society for Microbiology. All Rights Reserved.

Diversity, Composition, and Geographical Distribution of Microbial Communities in California Salt Marsh Sediments

PubMed Central

Córdova-Kreylos, Ana Lucía; Cao, Yiping; Green, Peter G.; Hwang, Hyun-Min; Kuivila, Kathryn M.; LaMontagne, Michael G.; Van De Werfhorst, Laurie C.; Holden, Patricia A.; Scow, Kate M.

2006-01-01

The Pacific Estuarine Ecosystem Indicators Research Consortium seeks to develop bioindicators of toxicant-induced stress and bioavailability for wetland biota. Within this framework, the effects of environmental and pollutant variables on microbial communities were studied at different spatial scales over a 2-year period. Six salt marshes along the California coastline were characterized using phospholipid fatty acid (PLFA) analysis and terminal restriction fragment length polymorphism (TRFLP) analysis. Additionally, 27 metals, six currently used pesticides, total polychlorinated biphenyls and polycyclic aromatic hydrocarbons, chlordanes, nonachlors, dichlorodiphenyldichloroethane, and dichlorodiphenyldichloroethylene were analyzed. Sampling was performed over large (between salt marshes), medium (stations within a marsh), and small (different channel depths) spatial scales. Regression and ordination analysis suggested that the spatial variation in microbial communities exceeded the variation attributable to pollutants. PLFA analysis and TRFLP canonical correspondence analysis (CCA) explained 74 and 43% of the variation, respectively, and both methods attributed 34% of the variation to tidal cycles, marsh, year, and latitude. After accounting for spatial variation using partial CCA, we found that metals had a greater effect on microbial community composition than organic pollutants had. Organic carbon and nitrogen contents were positively correlated with PLFA biomass, whereas total metal concentrations were positively correlated with biomass and diversity. Higher concentrations of heavy metals were negatively correlated with branched PLFAs and positively correlated with methyl- and cyclo-substituted PLFAs. The strong relationships observed between pollutant concentrations and some of the microbial indicators indicated the potential for using microbial community analyses in assessments of the ecosystem health of salt marshes. PMID:16672478

Spatial distribution of cloud droplets in a turbulent cloud-chamber flow

NASA Astrophysics Data System (ADS)

Jaczewski, A.; Malinowski, S. P.

2005-07-01

We present the results of a laboratory study of the spatial distribution of cloud droplets in a turbulent environment. An artificial, weakly turbulent cloud, consisting of droplets of diameter around 14 m, is observed in a laboratory chamber. Droplets on a vertical cross-section through the cloud interior are imaged using laser sheet photography. Images are digitized and numerically processed in order to retrieve droplet positions in a vertical plane. The spatial distribution of droplets in the range of scales, l, from 4 to 80 mm is characterized by: the clustering index CI(l), the volume averaged pair correlation function eta;(l) and a local density defined on a basis of correlation analysis. The results indicate that, even in weak turbulence in the chamber that is less intense and less intermittent than turbulence observed in clouds, droplets are not spread according to the Poisson distribution. The importance of this deviation from the Poisson distribution is unclear when looking at CI(l) and (l). The local density indicates that in small scales each droplet has, on average, more neighbours than expected from the average droplet concentration and gives a qualitative and intuitive measure of clustering.

Spatial patterns of mixing in the Solomon Sea

NASA Astrophysics Data System (ADS)

Alberty, M. S.; Sprintall, J.; MacKinnon, J.; Ganachaud, A.; Cravatte, S.; Eldin, G.; Germineaud, C.; Melet, A.

2017-05-01

The Solomon Sea is a marginal sea in the southwest Pacific that connects subtropical and equatorial circulation, constricting transport of South Pacific Subtropical Mode Water and Antarctic Intermediate Water through its deep, narrow channels. Marginal sea topography inhibits internal waves from propagating out and into the open ocean, making these regions hot spots for energy dissipation and mixing. Data from two hydrographic cruises and from Argo profiles are employed to indirectly infer mixing from observations for the first time in the Solomon Sea. Thorpe and finescale methods indirectly estimate the rate of dissipation of kinetic energy (ɛ) and indicate that it is maximum in the surface and thermocline layers and decreases by 2-3 orders of magnitude by 2000 m depth. Estimates of diapycnal diffusivity from the observations and a simple diffusive model agree in magnitude but have different depth structures, likely reflecting the combined influence of both diapycnal mixing and isopycnal stirring. Spatial variability of ɛ is large, spanning at least 2 orders of magnitude within isopycnal layers. Seasonal variability of ɛ reflects regional monsoonal changes in large-scale oceanic and atmospheric conditions with ɛ increased in July and decreased in March. Finally, tide power input and topographic roughness are well correlated with mean spatial patterns of mixing within intermediate and deep isopycnals but are not clearly correlated with thermocline mixing patterns.

Functional anatomy of visuo-spatial working memory during mental rotation is influenced by sex, menstrual cycle, and sex steroid hormones.

PubMed

Schöning, S; Engelien, A; Kugel, H; Schäfer, S; Schiffbauer, H; Zwitserlood, P; Pletziger, E; Beizai, P; Kersting, A; Ohrmann, P; Greb, R R; Lehmann, W; Heindel, W; Arolt, V; Konrad, C

2007-11-05

Recent observations indicate that sex and level of steroid hormones may influence cortical networks associated with specific cognitive functions, in particular visuo-spatial abilities. The present study probed the influence of sex, menstrual cycle, and sex steroid hormones on 3D mental rotation and brain function using 3-T fMRI. Twelve healthy women and 12 men were investigated. Menstrual cycle and hormone levels were assessed. The early follicular and midluteal phase of the menstrual cycle were chosen to examine short-term cyclical changes. Parietal and frontal areas were activated during mental rotation in both sexes. Significant differences between men and women were revealed in both phases of menstrual cycle. In men we observed a significant correlation of activation levels with testosterone levels in the left parietal lobe (BA 40). In women, a cycle-dependent correlation pattern was observed for testosterone: brain activation correlated with this male hormone only during the early follicular phase. In both cycle phases females' brain activation was significantly correlated with estradiol in frontal and parietal areas. Our study provides evidence that fMRI-related activity during performance of cognitive tasks varies across sex and phases of the menstrual cycle. The variation might be partly explained by better task performance in men, but our results indicate that further explanations like basic neuronal or neurovascular effects modulated by steroid hormones must be considered. Both estradiol and testosterone levels may influence fMRI signals of cognitive tasks, which should affect selection of subjects for future fMRI studies.

Linking Spatial Structure and Community-Level Biotic Interactions through Cooccurrence and Time Series Modeling of the Human Intestinal Microbiota.

PubMed

de Muinck, Eric J; Lundin, Knut E A; Trosvik, Pål

2017-01-01

The gastrointestinal (GI) microbiome is a densely populated ecosystem where dynamics are determined by interactions between microbial community members, as well as host factors. The spatial organization of this system is thought to be important in human health, yet this aspect of our resident microbiome is still poorly understood. In this study, we report significant spatial structure of the GI microbiota, and we identify general categories of spatial patterning in the distribution of microbial taxa along a healthy human GI tract. We further estimate the biotic interaction structure in the GI microbiota, both through time series and cooccurrence modeling of microbial community data derived from a large number of sequentially collected fecal samples. Comparison of these two approaches showed that species pairs involved in significant negative interactions had strong positive contemporaneous correlations and vice versa, while for species pairs without significant interactions, contemporaneous correlations were distributed around zero. We observed similar patterns when comparing these models to the spatial correlations between taxa identified in the adherent microbiota. This suggests that colocalization of microbial taxon pairs, and thus the spatial organization of the GI microbiota, is driven, at least in part, by direct or indirect biotic interactions. Thus, our study can provide a basis for an ecological interpretation of the biogeography of the human gut. IMPORTANCE The human gut microbiome is the subject of intense study due to its importance in health and disease. The majority of these studies have been based on the analysis of feces. However, little is known about how the microbial composition in fecal samples relates to the spatial distribution of microbial taxa along the gastrointestinal tract. By characterizing the microbial content both in intestinal tissue samples and in fecal samples obtained daily, we provide a conceptual framework for how the spatial structure relates to biotic interactions on the community level. We further describe general categories of spatial distribution patterns and identify taxa conforming to these categories. To our knowledge, this is the first study combining spatial and temporal analyses of the human gut microbiome. This type of analysis can be used for identifying candidate probiotics and designing strategies for clinical intervention.

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

NASA Astrophysics Data System (ADS)

Stephenson, D. B.

1997-10-01

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

Obesity and fast food in urban markets: a new approach using geo-referenced micro data.

PubMed

Chen, Susan Elizabeth; Florax, Raymond J; Snyder, Samantha D

2013-07-01

This paper presents a new method of assessing the relationship between features of the built environment and obesity, particularly in urban areas. Our empirical application combines georeferenced data on the location of fast-food restaurants with data about personal health, behavioral, and neighborhood characteristics. We define a 'local food environment' for every individual utilizing buffers around a person's home address. Individual food landscapes are potentially endogenous because of spatial sorting of the population and food outlets, and the body mass index (BMI) values for individuals living close to each other are likely to be spatially correlated because of observed and unobserved individual and neighborhood effects. The potential biases associated with endogeneity and spatial correlation are handled using spatial econometric estimation techniques. Our application provides quantitative estimates of the effect of proximity to fast-food restaurants on obesity in an urban food market. We also present estimates of a policy simulation that focuses on reducing the density of fast-food restaurants in urban areas. In the simulations, we account for spatial heterogeneity in both the policy instruments and individual neighborhoods and find a small effect for the hypothesized relationships between individual BMI values and the density of fast-food restaurants. Copyright © 2012 John Wiley & Sons, Ltd.

Cerebral morphology and dopamine D2/D3receptor distribution in humans: A combined [18F]fallypride and voxel-based morphometry study

PubMed Central

Woodward, Neil D.; Zald, David H.; Ding, Zhaohua; Riccardi, Patrizia; Ansari, M. Sib; Baldwin, Ronald M.; Cowan, Ronald L.; Li, Rui; Kessler, Robert M.

2009-01-01

The relationship between cerebral morphology and the expression of dopamine receptors has not been extensively studied in humans. Elucidation of such relationships may have important methodological implications for clinical studies of dopamine receptor ligand binding differences between control and patient groups. The association between cerebral morphology and dopamine receptor distribution was examined in 45 healthy subjects who completed T1-weighted structural MRI and PET scanning with the D2/D3 ligand [18F]fallypride. Optimized voxel-based morphometry was used to create grey matter volume and density images. Grey matter volume and density images were correlated with binding potential (BPND) images on a voxel-by-voxel basis using the Biological Parametric Mapping toolbox. Associations between cerebral morphology and BPND were also examined for selected regions-of-interest (ROIs) after spatial normalization. Voxel-wise analyses indicated that grey matter volume and density positively correlated with BPND throughout the midbrain, including the substantia nigra. Positive correlations were observed in medial cortical areas, including anterior cingulate and medial prefrontal cortex, and circumscribed regions of the temporal, frontal, and parietal lobes. ROI analyses revealed significant positive correlations between BPND and cerebral morphology in the caudate, thalamus, and amygdala. Few negative correlations between morphology and BPND were observed. Overall, grey matter density appeared more strongly correlated with BPND than grey matter volume. Cerebral morphology, particularly grey matter density, correlates with [18F]fallypride BPND in a regionally specific manner. Clinical studies comparing dopamine receptor availability between clinical and control groups may benefit by accounting for potential differences in cerebral morphology that exist even after spatial normalization. PMID:19457373

Cerebral morphology and dopamine D2/D3 receptor distribution in humans: a combined [18F]fallypride and voxel-based morphometry study.

PubMed

Woodward, Neil D; Zald, David H; Ding, Zhaohua; Riccardi, Patrizia; Ansari, M Sib; Baldwin, Ronald M; Cowan, Ronald L; Li, Rui; Kessler, Robert M

2009-05-15

The relationship between cerebral morphology and the expression of dopamine receptors has not been extensively studied in humans. Elucidation of such relationships may have important methodological implications for clinical studies of dopamine receptor ligand binding differences between control and patient groups. The association between cerebral morphology and dopamine receptor distribution was examined in 45 healthy subjects who completed T1-weighted structural MRI and PET scanning with the D(2)/D(3) ligand [(18)F]fallypride. Optimized voxel-based morphometry was used to create grey matter volume and density images. Grey matter volume and density images were correlated with binding potential (BP(ND)) images on a voxel-by-voxel basis using the Biological Parametric Mapping toolbox. Associations between cerebral morphology and BP(ND) were also examined for selected regions-of-interest (ROIs) after spatial normalization. Voxel-wise analyses indicated that grey matter volume and density positively correlated with BP(ND) throughout the midbrain, including the substantia nigra. Positive correlations were observed in medial cortical areas, including anterior cingulate and medial prefrontal cortex, and circumscribed regions of the temporal, frontal, and parietal lobes. ROI analyses revealed significant positive correlations between BP(ND) and cerebral morphology in the caudate, thalamus, and amygdala. Few negative correlations between morphology and BP(ND) were observed. Overall, grey matter density appeared more strongly correlated with BP(ND) than grey matter volume. Cerebral morphology, particularly grey matter density, correlates with [(18)F]fallypride BP(ND) in a regionally specific manner. Clinical studies comparing dopamine receptor availability between clinical and control groups may benefit by accounting for potential differences in cerebral morphology that exist even after spatial normalization.

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

Ren, Xiaochen; Singh, Arunima K.; Fang, Lei

Impurity doping in two-dimensional (2D) materials can provide a route to tuning electronic properties, so it is important to be able to determine the distribution of dopant atoms within and between layers. Here we report the totnographic mapping of dopants in layered 2D materials with atomic sensitivity and subnanometer spatial resolution using atom, probe tomography (APT). Also, APT analysis shows that Ag dopes both Bi 2Se 3 and PbSe layers in (PbSe) 5(Bi 2Se 3) 3, and correlations :in the position of Ag atoms suggest a pairing across neighboring Bi 2Se 3 and PbSe layers. Finally, density functional theory (DFT)more » calculations confirm the favorability of substitutional-doping for both Pb and Bi and provide insights into the,observed spatial correlations in dopant locations.« less

Hierarchical spatial models of abundance and occurrence from imperfect survey data

USGS Publications Warehouse

Royle, J. Andrew; Kery, M.; Gautier, R.; Schmid, Hans

2007-01-01

Many estimation and inference problems arising from large-scale animal surveys are focused on developing an understanding of patterns in abundance or occurrence of a species based on spatially referenced count data. One fundamental challenge, then, is that it is generally not feasible to completely enumerate ('census') all individuals present in each sample unit. This observation bias may consist of several components, including spatial coverage bias (not all individuals in the Population are exposed to sampling) and detection bias (exposed individuals may go undetected). Thus, observations are biased for the state variable (abundance, occupancy) that is the object of inference. Moreover, data are often sparse for most observation locations, requiring consideration of methods for spatially aggregating or otherwise combining sparse data among sample units. The development of methods that unify spatial statistical models with models accommodating non-detection is necessary to resolve important spatial inference problems based on animal survey data. In this paper, we develop a novel hierarchical spatial model for estimation of abundance and occurrence from survey data wherein detection is imperfect. Our application is focused on spatial inference problems in the Swiss Survey of Common Breeding Birds. The observation model for the survey data is specified conditional on the unknown quadrat population size, N(s). We augment the observation model with a spatial process model for N(s), describing the spatial variation in abundance of the species. The model includes explicit sources of variation in habitat structure (forest, elevation) and latent variation in the form of a correlated spatial process. This provides a model-based framework for combining the spatially referenced samples while at the same time yielding a unified treatment of estimation problems involving both abundance and occurrence. We provide a Bayesian framework for analysis and prediction based on the integrated likelihood, and we use the model to obtain estimates of abundance and occurrence maps for the European Jay (Garrulus glandarius), a widespread, elusive, forest bird. The naive national abundance estimate ignoring imperfect detection and incomplete quadrat coverage was 77 766 territories. Accounting for imperfect detection added approximately 18 000 territories, and adjusting for coverage bias added another 131 000 territories to yield a fully corrected estimate of the national total of about 227 000 territories. This is approximately three times as high as previous estimates that assume every territory is detected in each quadrat.

Assessment of the performance of CORDEX-SA experiments in simulating seasonal mean temperature over the Himalayan region for the present climate: Part I

NASA Astrophysics Data System (ADS)

Nengker, T.; Choudhary, A.; Dimri, A. P.

2018-04-01

The ability of an ensemble of five regional climate models (hereafter RCMs) under Coordinated Regional Climate Downscaling Experiments-South Asia (hereafter, CORDEX-SA) in simulating the key features of present day near surface mean air temperature (Tmean) climatology (1970-2005) over the Himalayan region is studied. The purpose of this paper is to understand the consistency in the performance of models across the ensemble, space and seasons. For this a number of statistical measures like trend, correlation, variance, probability distribution function etc. are applied to evaluate the performance of models against observation and simultaneously the underlying uncertainties between them for four different seasons. The most evident finding from the study is the presence of a large cold bias (-6 to -8 °C) which is systematically seen across all the models and across space and time over the Himalayan region. However, these RCMs with its fine resolution perform extremely well in capturing the spatial distribution of the temperature features as indicated by a consistently high spatial correlation (greater than 0.9) with the observation in all seasons. In spite of underestimation in simulated temperature and general intensification of cold bias with increasing elevation the models show a greater rate of warming than the observation throughout entire altitudinal stretch of study region. During winter, the simulated rate of warming gets even higher at high altitudes. Moreover, a seasonal response of model performance and its spatial variability to elevation is found.

An Investigation of Calculus Learning Using Factorial Modeling.

ERIC Educational Resources Information Center

Dick, Thomas P.; Balomenos, Richard H.

Structural covariance models that would explain the correlations observed among mathematics achievement and participation measures and related cognitive and affective variables were developed. A sample of college calculus students (N=268; 124 females and 144 males) was administered a battery of cognitive tests (including measures of spatial-visual…

Spatial analysis and high resolution mapping of the human whole-brain transcriptome for integrative analysis in neuroimaging.

PubMed

Gryglewski, Gregor; Seiger, René; James, Gregory Miles; Godbersen, Godber Mathis; Komorowski, Arkadiusz; Unterholzner, Jakob; Michenthaler, Paul; Hahn, Andreas; Wadsak, Wolfgang; Mitterhauser, Markus; Kasper, Siegfried; Lanzenberger, Rupert

2018-08-01

The quantification of big pools of diverse molecules provides important insights on brain function, but is often restricted to a limited number of observations, which impairs integration with other modalities. To resolve this issue, a method allowing for the prediction of mRNA expression in the entire brain based on microarray data provided in the Allen Human Brain Atlas was developed. Microarray data of 3702 samples from 6 brain donors was registered to MNI and cortical surface space using FreeSurfer. For each of 18,686 genes, spatial dependence of transcription was assessed using variogram modelling. Variogram models were employed in Gaussian process regression to calculate best linear unbiased predictions for gene expression at all locations represented in well-established imaging atlases for cortex, subcortical structures and cerebellum. For validation, predicted whole-brain transcription of the HTR1A gene was correlated with [carbonyl- 11 C]WAY-100635 positron emission tomography data collected from 30 healthy subjects. Prediction results showed minimal bias ranging within ±0.016 (cortical surface), ±0.12 (subcortical regions) and ±0.14 (cerebellum) in units of log2 expression intensity for all genes. Across genes, the correlation of predicted and observed mRNA expression in leave-one-out cross-validation correlated with the strength of spatial dependence (cortical surface: r = 0.91, subcortical regions: r = 0.85, cerebellum: r = 0.84). 816 out of 18,686 genes exhibited a high spatial dependence accounting for more than 50% of variance in the difference of gene expression on the cortical surface. In subcortical regions and cerebellum, different sets of genes were implicated by high spatially structured variability. For the serotonin 1A receptor, correlation between PET binding potentials and predicted comprehensive mRNA expression was markedly higher (Spearman ρ = 0.72 for cortical surface, ρ = 0.84 for subcortical regions) than correlation of PET and discrete samples only (ρ = 0.55 and ρ = 0.63, respectively). Prediction of mRNA expression in the entire human brain allows for intuitive visualization of gene transcription and seamless integration in multimodal analysis without bias arising from non-uniform distribution of available samples. Extension of this methodology promises to facilitate translation of omics research and enable investigation of human brain function at a systems level. Copyright © 2018 Elsevier Inc. All rights reserved.

Universal Spatial Correlation Functions for Describing and Reconstructing Soil Microstructure

PubMed Central

Skvortsova, Elena B.; Mallants, Dirk

2015-01-01

Structural features of porous materials such as soil define the majority of its physical properties, including water infiltration and redistribution, multi-phase flow (e.g. simultaneous water/air flow, or gas exchange between biologically active soil root zone and atmosphere) and solute transport. To characterize soil microstructure, conventional soil science uses such metrics as pore size and pore-size distributions and thin section-derived morphological indicators. However, these descriptors provide only limited amount of information about the complex arrangement of soil structure and have limited capability to reconstruct structural features or predict physical properties. We introduce three different spatial correlation functions as a comprehensive tool to characterize soil microstructure: 1) two-point probability functions, 2) linear functions, and 3) two-point cluster functions. This novel approach was tested on thin-sections (2.21×2.21 cm2) representing eight soils with different pore space configurations. The two-point probability and linear correlation functions were subsequently used as a part of simulated annealing optimization procedures to reconstruct soil structure. Comparison of original and reconstructed images was based on morphological characteristics, cluster correlation functions, total number of pores and pore-size distribution. Results showed excellent agreement for soils with isolated pores, but relatively poor correspondence for soils exhibiting dual-porosity features (i.e. superposition of pores and micro-cracks). Insufficient information content in the correlation function sets used for reconstruction may have contributed to the observed discrepancies. Improved reconstructions may be obtained by adding cluster and other correlation functions into reconstruction sets. Correlation functions and the associated stochastic reconstruction algorithms introduced here are universally applicable in soil science, such as for soil classification, pore-scale modelling of soil properties, soil degradation monitoring, and description of spatial dynamics of soil microbial activity. PMID:26010779

Universal spatial correlation functions for describing and reconstructing soil microstructure.

PubMed

Karsanina, Marina V; Gerke, Kirill M; Skvortsova, Elena B; Mallants, Dirk

2015-01-01

Structural features of porous materials such as soil define the majority of its physical properties, including water infiltration and redistribution, multi-phase flow (e.g. simultaneous water/air flow, or gas exchange between biologically active soil root zone and atmosphere) and solute transport. To characterize soil microstructure, conventional soil science uses such metrics as pore size and pore-size distributions and thin section-derived morphological indicators. However, these descriptors provide only limited amount of information about the complex arrangement of soil structure and have limited capability to reconstruct structural features or predict physical properties. We introduce three different spatial correlation functions as a comprehensive tool to characterize soil microstructure: 1) two-point probability functions, 2) linear functions, and 3) two-point cluster functions. This novel approach was tested on thin-sections (2.21×2.21 cm2) representing eight soils with different pore space configurations. The two-point probability and linear correlation functions were subsequently used as a part of simulated annealing optimization procedures to reconstruct soil structure. Comparison of original and reconstructed images was based on morphological characteristics, cluster correlation functions, total number of pores and pore-size distribution. Results showed excellent agreement for soils with isolated pores, but relatively poor correspondence for soils exhibiting dual-porosity features (i.e. superposition of pores and micro-cracks). Insufficient information content in the correlation function sets used for reconstruction may have contributed to the observed discrepancies. Improved reconstructions may be obtained by adding cluster and other correlation functions into reconstruction sets. Correlation functions and the associated stochastic reconstruction algorithms introduced here are universally applicable in soil science, such as for soil classification, pore-scale modelling of soil properties, soil degradation monitoring, and description of spatial dynamics of soil microbial activity.

Cholinergic parameters and the retrieval of learned and re-learned spatial information: a study using a model of Wernicke-Korsakoff Syndrome.

PubMed

Pires, Rita G W; Pereira, Silvia R C; Oliveira-Silva, Ieda F; Franco, Glaura C; Ribeiro, Angela M

2005-07-01

This is a factorial (2 x 2 x 2) spatial memory and cholinergic parameters study in which the factors are chronic ethanol, thiamine deficiency and naivety in Morris water maze task. Both learning and retention of the spatial version of the water maze were assessed. To assess retrograde retention of spatial information, half of the rats were pre-trained on the maze before the treatment manipulations of pyrithiamine (PT)-induced thiamine deficiency and post-tested after treatment (pre-trained group). The other half of the animals was only trained after treatment to assess anterograde amnesia (post-trained group). Thiamine deficiency, associated to chronic ethanol treatment, had a significant deleterious effect on spatial memory performance of post-trained animals. The biochemical data revealed that chronic ethanol treatment reduced acetylcholinesterase (AChE) activity in the hippocampus while leaving the neocortex unchanged, whereas thiamine deficiency reduced both cortical and hippocampal AChE activity. Regarding basal and stimulated cortical acetylcholine (ACh) release, both chronic ethanol and thiamine deficiency treatments had significant main effects. Significant correlations were found between both cortical and hippocampal AChE activity and behaviour parameters for pre-trained but not for post-trained animals. Also for ACh release, the correlation found was significant only for pre-trained animals. These biochemical parameters were decreased by thiamine deficiency and chronic ethanol treatment, both in pre-trained and post-trained animals. But the correlation with the behavioural parameters was observed only for pre-trained animals, that is, those that were retrained and assessed for retrograde retention.

Assessing comorbidity and correlates of wasting and stunting among children in Somalia using cross-sectional household surveys: 2007 to 2010

PubMed Central

Kinyoki, Damaris K; Kandala, Ngianga-Bakwin; Manda, Samuel O; Krainski, Elias T; Fuglstad, Geir-Arne; Moloney, Grainne M; Berkley, James A; Noor, Abdisalan M

2016-01-01

Objective Wasting and stunting may occur together at the individual child level; however, their shared geographic distribution and correlates remain unexplored. Understanding shared and separate correlates may inform interventions. We aimed to assess the spatial codistribution of wasting, stunting and underweight and investigate their shared correlates among children aged 6–59 months in Somalia. Setting Cross-sectional nutritional assessments surveys were conducted using structured interviews among communities in Somalia biannually from 2007 to 2010. A two-stage cluster sampling methodology was used to select children aged 6–59 months from households across three livelihood zones (pastoral, agropastoral and riverine). Using these data and environmental covariates, we implemented a multivariate spatial technique to estimate the codistribution and divergence of the risks and correlates of wasting and stunting at the 1×1 km spatial resolution. Participants 73 778 children aged 6–59 months from 1066 survey clusters in Somalia. Results Observed pairwise child level empirical correlations were 0.30, 0.70 and 0.73 between weight-for-height and height-for-age; height-for-age and weight-for-age, and weight-for-height and weight-for-age, respectively. Access to foods with high protein content and vegetation cover, a proxy of rainfall or drought, were associated with lower risk of wasting and stunting. Age, gender, illness, access to carbohydrates and temperature were correlates of all three indicators. The spatial codistribution was highest between stunting and underweight with relative risk values ranging between 0.15 and 6.20, followed by wasting and underweight (range: 0.18–5.18) and lowest between wasting and stunting (range: 0.26–4.32). Conclusions The determinants of wasting and stunting are largely shared, but their correlation is relatively variable in space. Significant hotspots of different forms of malnutrition occurred in the South Central regions of the country. Although nutrition response in Somalia has traditionally focused on wasting rather than stunting, integrated programming and interventions can effectively target both conditions to alleviate common risk factors. PMID:26962034

Assessing comorbidity and correlates of wasting and stunting among children in Somalia using cross-sectional household surveys: 2007 to 2010.

PubMed

Kinyoki, Damaris K; Kandala, Ngianga-Bakwin; Manda, Samuel O; Krainski, Elias T; Fuglstad, Geir-Arne; Moloney, Grainne M; Berkley, James A; Noor, Abdisalan M

2016-03-09

Wasting and stunting may occur together at the individual child level; however, their shared geographic distribution and correlates remain unexplored. Understanding shared and separate correlates may inform interventions. We aimed to assess the spatial codistribution of wasting, stunting and underweight and investigate their shared correlates among children aged 6-59 months in Somalia. Cross-sectional nutritional assessments surveys were conducted using structured interviews among communities in Somalia biannually from 2007 to 2010. A two-stage cluster sampling methodology was used to select children aged 6-59 months from households across three livelihood zones (pastoral, agropastoral and riverine). Using these data and environmental covariates, we implemented a multivariate spatial technique to estimate the codistribution and divergence of the risks and correlates of wasting and stunting at the 1 × 1 km spatial resolution. 73,778 children aged 6-59 months from 1066 survey clusters in Somalia. Observed pairwise child level empirical correlations were 0.30, 0.70 and 0.73 between weight-for-height and height-for-age; height-for-age and weight-for-age, and weight-for-height and weight-for-age, respectively. Access to foods with high protein content and vegetation cover, a proxy of rainfall or drought, were associated with lower risk of wasting and stunting. Age, gender, illness, access to carbohydrates and temperature were correlates of all three indicators. The spatial codistribution was highest between stunting and underweight with relative risk values ranging between 0.15 and 6.20, followed by wasting and underweight (range: 0.18-5.18) and lowest between wasting and stunting (range: 0.26-4.32). The determinants of wasting and stunting are largely shared, but their correlation is relatively variable in space. Significant hotspots of different forms of malnutrition occurred in the South Central regions of the country. Although nutrition response in Somalia has traditionally focused on wasting rather than stunting, integrated programming and interventions can effectively target both conditions to alleviate common risk factors. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://www.bmj.com/company/products-services/rights-and-licensing/

Proximal Soil Sensing – A Contribution for Species Habitat Distribution Modelling of Earthworms in Agricultural Soils?

PubMed Central

Schirrmann, Michael; Joschko, Monika; Gebbers, Robin; Kramer, Eckart; Zörner, Mirjam; Barkusky, Dietmar; Timmer, Jens

2016-01-01

Background Earthworms are important for maintaining soil ecosystem functioning and serve as indicators of soil fertility. However, detection of earthworms is time-consuming, which hinders the assessment of earthworm abundances with high sampling density over entire fields. Recent developments of mobile terrestrial sensor platforms for proximal soil sensing (PSS) provided new tools for collecting dense spatial information of soils using various sensing principles. Yet, the potential of PSS for assessing earthworm habitats is largely unexplored. This study investigates whether PSS data contribute to the spatial prediction of earthworm abundances in species distribution models of agricultural soils. Methodology/Principal Findings Proximal soil sensing data, e.g., soil electrical conductivity (EC), pH, and near infrared absorbance (NIR), were collected in real-time in a field with two management strategies (reduced tillage / conventional tillage) and sandy to loam soils. PSS was related to observations from a long-term (11 years) earthworm observation study conducted at 42 plots. Earthworms were sampled from 0.5 x 0.5 x 0.2 m³ soil blocks and identified to species level. Sensor data were highly correlated with earthworm abundances observed in reduced tillage but less correlated with earthworm abundances observed in conventional tillage. This may indicate that management influences the sensor-earthworm relationship. Generalized additive models and state-space models showed that modelling based on data fusion from EC, pH, and NIR sensors produced better results than modelling without sensor data or data from just a single sensor. Regarding the individual earthworm species, particular sensor combinations were more appropriate than others due to the different habitat requirements of the earthworms. Earthworm species with soil-specific habitat preferences were spatially predicted with higher accuracy by PSS than more ubiquitous species. Conclusions/Significance Our findings suggest that PSS contributes to the spatial modelling of earthworm abundances at field scale and that it will support species distribution modelling in the attempt to understand the soil-earthworm relationships in agroecosystems. PMID:27355340

Proximal Soil Sensing - A Contribution for Species Habitat Distribution Modelling of Earthworms in Agricultural Soils?

PubMed

Schirrmann, Michael; Joschko, Monika; Gebbers, Robin; Kramer, Eckart; Zörner, Mirjam; Barkusky, Dietmar; Timmer, Jens

2016-01-01

Earthworms are important for maintaining soil ecosystem functioning and serve as indicators of soil fertility. However, detection of earthworms is time-consuming, which hinders the assessment of earthworm abundances with high sampling density over entire fields. Recent developments of mobile terrestrial sensor platforms for proximal soil sensing (PSS) provided new tools for collecting dense spatial information of soils using various sensing principles. Yet, the potential of PSS for assessing earthworm habitats is largely unexplored. This study investigates whether PSS data contribute to the spatial prediction of earthworm abundances in species distribution models of agricultural soils. Proximal soil sensing data, e.g., soil electrical conductivity (EC), pH, and near infrared absorbance (NIR), were collected in real-time in a field with two management strategies (reduced tillage / conventional tillage) and sandy to loam soils. PSS was related to observations from a long-term (11 years) earthworm observation study conducted at 42 plots. Earthworms were sampled from 0.5 x 0.5 x 0.2 m³ soil blocks and identified to species level. Sensor data were highly correlated with earthworm abundances observed in reduced tillage but less correlated with earthworm abundances observed in conventional tillage. This may indicate that management influences the sensor-earthworm relationship. Generalized additive models and state-space models showed that modelling based on data fusion from EC, pH, and NIR sensors produced better results than modelling without sensor data or data from just a single sensor. Regarding the individual earthworm species, particular sensor combinations were more appropriate than others due to the different habitat requirements of the earthworms. Earthworm species with soil-specific habitat preferences were spatially predicted with higher accuracy by PSS than more ubiquitous species. Our findings suggest that PSS contributes to the spatial modelling of earthworm abundances at field scale and that it will support species distribution modelling in the attempt to understand the soil-earthworm relationships in agroecosystems.

Selecting a Separable Parametric Spatiotemporal Covariance Structure for Longitudinal Imaging Data

PubMed Central

George, Brandon; Aban, Inmaculada

2014-01-01

Longitudinal imaging studies allow great insight into how the structure and function of a subject’s internal anatomy changes over time. Unfortunately, the analysis of longitudinal imaging data is complicated by inherent spatial and temporal correlation: the temporal from the repeated measures, and the spatial from the outcomes of interest being observed at multiple points in a patients body. We propose the use of a linear model with a separable parametric spatiotemporal error structure for the analysis of repeated imaging data. The model makes use of spatial (exponential, spherical, and Matérn) and temporal (compound symmetric, autoregressive-1, Toeplitz, and unstructured) parametric correlation functions. A simulation study, inspired by a longitudinal cardiac imaging study on mitral regurgitation patients, compared different information criteria for selecting a particular separable parametric spatiotemporal correlation structure as well as the effects on Type I and II error rates for inference on fixed effects when the specified model is incorrect. Information criteria were found to be highly accurate at choosing between separable parametric spatiotemporal correlation structures. Misspecification of the covariance structure was found to have the ability to inflate the Type I error or have an overly conservative test size, which corresponded to decreased power. An example with clinical data is given illustrating how the covariance structure procedure can be done in practice, as well as how covariance structure choice can change inferences about fixed effects. PMID:25293361

Activation of parallel fiber feedback by spatially diffuse stimuli reduces signal and noise correlations via independent mechanisms in a cerebellum-like structure.

PubMed

Simmonds, Benjamin; Chacron, Maurice J

2015-01-01

Correlations between the activities of neighboring neurons are observed ubiquitously across systems and species and are dynamically regulated by several factors such as the stimulus' spatiotemporal extent as well as by the brain's internal state. Using the electrosensory system of gymnotiform weakly electric fish, we recorded the activities of pyramidal cell pairs within the electrosensory lateral line lobe (ELL) under spatially localized and diffuse stimulation. We found that both signal and noise correlations were markedly reduced (>40%) under the latter stimulation. Through a network model incorporating key anatomical features of the ELL, we reveal how activation of diffuse parallel fiber feedback from granule cells by spatially diffuse stimulation can explain both the reduction in signal as well as the reduction in noise correlations seen experimentally through independent mechanisms. First, we show that burst-timing dependent plasticity, which leads to a negative image of the stimulus and thereby reduces single neuron responses, decreases signal but not noise correlations. Second, we show trial-to-trial variability in the responses of single granule cells to sensory input reduces noise but not signal correlations. Thus, our model predicts that the same feedback pathway can simultaneously reduce both signal and noise correlations through independent mechanisms. To test this prediction experimentally, we pharmacologically inactivated parallel fiber feedback onto ELL pyramidal cells. In agreement with modeling predictions, we found that inactivation increased both signal and noise correlations but that there was no significant relationship between magnitude of the increase in signal correlations and the magnitude of the increase in noise correlations. The mechanisms reported in this study are expected to be generally applicable to the cerebellum as well as other cerebellum-like structures. We further discuss the implications of such decorrelation on the neural coding strategies used by the electrosensory and by other systems to process natural stimuli.

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

PubMed

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

2018-03-01

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

Improving Evapotranspiration Estimates Using Multi-Platform Remote Sensing

NASA Astrophysics Data System (ADS)

Knipper, Kyle; Hogue, Terri; Franz, Kristie; Scott, Russell

2016-04-01

Understanding the linkages between energy and water cycles through evapotranspiration (ET) is uniquely challenging given its dependence on a range of climatological parameters and surface/atmospheric heterogeneity. A number of methods have been developed to estimate ET either from primarily remote-sensing observations, in-situ measurements, or a combination of the two. However, the scale of many of these methods may be too large to provide needed information about the spatial and temporal variability of ET that can occur over regions with acute or chronic land cover change and precipitation driven fluxes. The current study aims to improve the spatial and temporal variability of ET utilizing only satellite-based observations by incorporating a potential evapotranspiration (PET) methodology with satellite-based down-scaled soil moisture estimates in southern Arizona, USA. Initially, soil moisture estimates from AMSR2 and SMOS are downscaled to 1km through a triangular relationship between MODIS land surface temperature (MYD11A1), vegetation indices (MOD13Q1/MYD13Q1), and brightness temperature. Downscaled soil moisture values are then used to scale PET to actual ET (AET) at a daily, 1km resolution. Derived AET estimates are compared to observed flux tower estimates, the North American Land Data Assimilation System (NLDAS) model output (i.e. Variable Infiltration Capacity (VIC) Macroscale Hydrologic Model, Mosiac Model, and Noah Model simulations), the Operational Simplified Surface Energy Balance Model (SSEBop), and a calibrated empirical ET model created specifically for the region. Preliminary results indicate a strong increase in correlation when incorporating the downscaling technique to original AMSR2 and SMOS soil moisture values, with the added benefit of being able to decipher small scale heterogeneity in soil moisture (riparian versus desert grassland). AET results show strong correlations with relatively low error and bias when compared to flux tower estimates. In addition, AET results show improved bias to those reported by SSEBop, with similar correlations and errors when compared to the empirical ET model. Spatial patterns of estimated AET display patterns representative of the basin's elevation and vegetation characteristics, with improved spatial resolution and temporal heterogeneity when compared to previous models.

The Influence of Mexican Hat Recurrent Connectivity on Noise Correlations and Stimulus Encoding

PubMed Central

Meyer, Robert; Ladenbauer, Josef; Obermayer, Klaus

2017-01-01

Noise correlations are a common feature of neural responses and have been observed in many cortical areas across different species. These correlations can influence information processing by enhancing or diminishing the quality of the neural code, but the origin of these correlations is still a matter of controversy. In this computational study we explore the hypothesis that noise correlations are the result of local recurrent excitatory and inhibitory connections. We simulated two-dimensional networks of adaptive spiking neurons with local connection patterns following Gaussian kernels. Noise correlations decay with distance between neurons but are only observed if the range of excitatory connections is smaller than the range of inhibitory connections (“Mexican hat” connectivity) and if the connection strengths are sufficiently strong. These correlations arise from a moving blob-like structure of evoked activity, which is absent if inhibitory interactions have a smaller range (“inverse Mexican hat” connectivity). Spatially structured external inputs fixate these blobs to certain locations and thus effectively reduce noise correlations. We further investigated the influence of these network configurations on stimulus encoding. On the one hand, the observed correlations diminish information about a stimulus encoded by a network. On the other hand, correlated activity allows for more precise encoding of stimulus information if the decoder has only access to a limited amount of neurons. PMID:28539881

Development of a local size hierarchy causes regular spacing of trees in an even-aged Abies forest: analyses using spatial autocorrelation and the mark correlation function.

PubMed

Suzuki, Satoshi N; Kachi, Naoki; Suzuki, Jun-Ichirou

2008-09-01

During the development of an even-aged plant population, the spatial distribution of individuals often changes from a clumped pattern to a random or regular one. The development of local size hierarchies in an Abies forest was analysed for a period of 47 years following a large disturbance in 1959. In 1980 all trees in an 8 x 8 m plot were mapped and their height growth after the disturbance was estimated. Their mortality and growth were then recorded at 1- to 4-year intervals between 1980 and 2006. Spatial distribution patterns of trees were analysed by the pair correlation function. Spatial correlations between tree heights were analysed with a spatial autocorrelation function and the mark correlation function. The mark correlation function was able to detect a local size hierarchy that could not be detected by the spatial autocorrelation function alone. The small-scale spatial distribution pattern of trees changed from clumped to slightly regular during the 47 years. Mortality occurred in a density-dependent manner, which resulted in regular spacing between trees after 1980. The spatial autocorrelation and mark correlation functions revealed the existence of tree patches consisting of large trees at the initial stage. Development of a local size hierarchy was detected within the first decade after the disturbance, although the spatial autocorrelation was not negative. Local size hierarchies that developed persisted until 2006, and the spatial autocorrelation became negative at later stages (after about 40 years). This is the first study to detect local size hierarchies as a prelude to regular spacing using the mark correlation function. The results confirm that use of the mark correlation function together with the spatial autocorrelation function is an effective tool to analyse the development of a local size hierarchy of trees in a forest.

Dissociable brain biomarkers of fluid intelligence.

PubMed

Paul, Erick J; Larsen, Ryan J; Nikolaidis, Aki; Ward, Nathan; Hillman, Charles H; Cohen, Neal J; Kramer, Arthur F; Barbey, Aron K

2016-08-15

Cognitive neuroscience has long sought to understand the biological foundations of human intelligence. Decades of research have revealed that general intelligence is correlated with two brain-based biomarkers: the concentration of the brain biochemical N-acetyl aspartate (NAA) measured by proton magnetic resonance spectroscopy (MRS) and total brain volume measured using structural MR imaging (MRI). However, the relative contribution of these biomarkers in predicting performance on core facets of human intelligence remains to be well characterized. In the present study, we sought to elucidate the role of NAA and brain volume in predicting fluid intelligence (Gf). Three canonical tests of Gf (BOMAT, Number Series, and Letter Sets) and three working memory tasks (Reading, Rotation, and Symmetry span tasks) were administered to a large sample of healthy adults (n=211). We conducted exploratory factor analysis to investigate the factor structure underlying Gf independent from working memory and observed two Gf components (verbal/spatial and quantitative reasoning) and one working memory component. Our findings revealed a dissociation between two brain biomarkers of Gf (controlling for age and sex): NAA concentration correlated with verbal/spatial reasoning, whereas brain volume correlated with quantitative reasoning and working memory. A follow-up analysis revealed that this pattern of findings is observed for males and females when analyzed separately. Our results provide novel evidence that distinct brain biomarkers are associated with specific facets of human intelligence, demonstrating that NAA and brain volume are independent predictors of verbal/spatial and quantitative facets of Gf. Copyright © 2016 The Authors. Published by Elsevier Inc. All rights reserved.

Characterizing and estimating noise in InSAR and InSAR time series with MODIS

USGS Publications Warehouse

Barnhart, William D.; Lohman, Rowena B.

2013-01-01

InSAR time series analysis is increasingly used to image subcentimeter displacement rates of the ground surface. The precision of InSAR observations is often affected by several noise sources, including spatially correlated noise from the turbulent atmosphere. Under ideal scenarios, InSAR time series techniques can substantially mitigate these effects; however, in practice the temporal distribution of InSAR acquisitions over much of the world exhibit seasonal biases, long temporal gaps, and insufficient acquisitions to confidently obtain the precisions desired for tectonic research. Here, we introduce a technique for constraining the magnitude of errors expected from atmospheric phase delays on the ground displacement rates inferred from an InSAR time series using independent observations of precipitable water vapor from MODIS. We implement a Monte Carlo error estimation technique based on multiple (100+) MODIS-based time series that sample date ranges close to the acquisitions times of the available SAR imagery. This stochastic approach allows evaluation of the significance of signals present in the final time series product, in particular their correlation with topography and seasonality. We find that topographically correlated noise in individual interferograms is not spatially stationary, even over short-spatial scales (<10 km). Overall, MODIS-inferred displacements and velocities exhibit errors of similar magnitude to the variability within an InSAR time series. We examine the MODIS-based confidence bounds in regions with a range of inferred displacement rates, and find we are capable of resolving velocities as low as 1.5 mm/yr with uncertainties increasing to ∼6 mm/yr in regions with higher topographic relief.

Calibration of a distributed hydrologic model using observed spatial patterns from MODIS data

NASA Astrophysics Data System (ADS)

Demirel, Mehmet C.; González, Gorka M.; Mai, Juliane; Stisen, Simon

2016-04-01

Distributed hydrologic models are typically calibrated against streamflow observations at the outlet of the basin. Along with these observations from gauging stations, satellite based estimates offer independent evaluation data such as remotely sensed actual evapotranspiration (aET) and land surface temperature. The primary objective of the study is to compare model calibrations against traditional downstream discharge measurements with calibrations against simulated spatial patterns and combinations of both types of observations. While the discharge based model calibration typically improves the temporal dynamics of the model, it seems to give rise to minimum improvement of the simulated spatial patterns. In contrast, objective functions specifically targeting the spatial pattern performance could potentially increase the spatial model performance. However, most modeling studies, including the model formulations and parameterization, are not designed to actually change the simulated spatial pattern during calibration. This study investigates the potential benefits of incorporating spatial patterns from MODIS data to calibrate the mesoscale hydrologic model (mHM). This model is selected as it allows for a change in the spatial distribution of key soil parameters through the optimization of pedo-transfer function parameters and includes options for using fully distributed daily Leaf Area Index (LAI) values directly as input. In addition the simulated aET can be estimated at a spatial resolution suitable for comparison to the spatial patterns observed with MODIS data. To increase our control on spatial calibration we introduced three additional parameters to the model. These new parameters are part of an empirical equation to the calculate crop coefficient (Kc) from daily LAI maps and used to update potential evapotranspiration (PET) as model inputs. This is done instead of correcting/updating PET with just a uniform (or aspect driven) factor used in the mHM model (version 5.3). We selected the 20 most important parameters out of 53 mHM parameters based on a comprehensive sensitivity analysis (Cuntz et al., 2015). We calibrated 1km-daily mHM for the Skjern basin in Denmark using the Shuffled Complex Evolution (SCE) algorithm and inputs at different spatial scales i.e. meteorological data at 10km and morphological data at 250 meters. We used correlation coefficients between observed monthly (summer months only) MODIS data calculated from cloud free days over the calibration period from 2001 to 2008 and simulated aET from mHM over the same period. Similarly other metrics, e.g mapcurves and fraction skill-score, are also included in our objective function to assess the co-location of the grid-cells. The preliminary results show that multi-objective calibration of mHM against observed streamflow and spatial patterns together does not significantly reduce the spatial errors in aET while it improves the streamflow simulations. This is a strong signal for further investigation of the multi parameter regionalization affecting spatial aET patterns and weighting the spatial metrics in the objective function relative to the streamflow metrics.

3D radiation belt diffusion model results using new empirical models of whistler chorus and hiss

NASA Astrophysics Data System (ADS)

Cunningham, G.; Chen, Y.; Henderson, M. G.; Reeves, G. D.; Tu, W.

2012-12-01

3D diffusion codes model the energization, radial transport, and pitch angle scattering due to wave-particle interactions. Diffusion codes are powerful but are limited by the lack of knowledge of the spatial & temporal distribution of waves that drive the interactions for a specific event. We present results from the 3D DREAM model using diffusion coefficients driven by new, activity-dependent, statistical models of chorus and hiss waves. Most 3D codes parameterize the diffusion coefficients or wave amplitudes as functions of magnetic activity indices like Kp, AE, or Dst. These functional representations produce the average value of the wave intensities for a given level of magnetic activity; however, the variability of the wave population at a given activity level is lost with such a representation. Our 3D code makes use of the full sample distributions contained in a set of empirical wave databases (one database for each wave type, including plasmaspheric hiss, lower and upper hand chorus) that were recently produced by our team using CRRES and THEMIS observations. The wave databases store the full probability distribution of observed wave intensity binned by AE, MLT, MLAT and L*. In this presentation, we show results that make use of the wave intensity sample probability distributions for lower-band and upper-band chorus by sampling the distributions stochastically during a representative CRRES-era storm. The sampling of the wave intensity probability distributions produces a collection of possible evolutions of the phase space density, which quantifies the uncertainty in the model predictions caused by the uncertainty of the chorus wave amplitudes for a specific event. A significant issue is the determination of an appropriate model for the spatio-temporal correlations of the wave intensities, since the diffusion coefficients are computed as spatio-temporal averages of the waves over MLT, MLAT and L*. The spatiotemporal correlations cannot be inferred from the wave databases. In this study we use a temporal correlation of ~1 hour for the sampled wave intensities that is informed by the observed autocorrelation in the AE index, a spatial correlation length of ~100 km in the two directions perpendicular to the magnetic field, and a spatial correlation length of 5000 km in the direction parallel to the magnetic field, according to the work of Santolik et al (2003), who used multi-spacecraft measurements from Cluster to quantify the correlation length scales for equatorial chorus . We find that, despite the small correlation length scale for chorus, there remains significant variability in the model outcomes driven by variability in the chorus wave intensities.

Plans for a new rio-imager experiment in Northern Scandinavia

NASA Astrophysics Data System (ADS)

Nielsen, E.; Hagfors, T.

1997-05-01

To observe the spatial variations and dynamics of charged particle precipitation in the high latitude ionosphere, a riometer experiment is planned, which from the ground will image the precipitation regions over an area of 300 × 300 km with a spatial resolution of 6 km in the zenith, increasing to 12 km at 60° zenith angle. The time resolution is one second. The spatial resolution represents a considerable improvement over existing imaging systems. The experiment employs a Mill's Cross technique not used before in riometer work: two 32 element rows of antennas form the antenna array, two 32 element Butler Matrices achieve directionality, and cross-correlation yield the directional intensities.

Coincident Occurrences of Tropical Individual Cirrus Clouds and Deep Convective Systems Derived from TRMM Observations

NASA Technical Reports Server (NTRS)

Lin, Bing; Xu, Kuan-Man; Minnis, Patrick; Wielicki, Bruce A.; Hu, Yongxiang; Chambers, Lin; Fan, Alice; Sun, Wenbo

2007-01-01

Measurements of cloud properties and atmospheric radiation taken between January and August 1998 by the Tropical Rainfall Measuring Mission (TRMM) satellite were used to investigate the effect of spatial and temporal scales on the coincident occurrences of tropical individual cirrus clouds (ICCs) and deep convective systems (DCSs). It is found that there is little or even negative correlation between instantaneous occurrences of ICC and DCS in small areas, in which both types of clouds cannot grow and expand simultaneously. When spatial and temporal domains are increased, ICCs become more dependent on DCSs due to the origination of many ICCs from DCSs and moisture supply from the DCS in the upper troposphere for the ICCs to grow, resulting in significant positive correlation between the two types of tropical high clouds in large spatial and long temporal scales. This result may suggest that the decrease of tropical high clouds with SST from model simulations is likely caused by restricted spatial domains and limited temporal periods. Finally, the radiative feedback due to the change in tropical high cloud area coverage with sea surface temperature appears small and about -0.14 W/sq m per degree Kelvin.

A nonlinear controlling function of geological features on magmatic–hydrothermal mineralization

PubMed Central

Zuo, Renguang

2016-01-01

This paper reports a nonlinear controlling function of geological features on magmatic–hydrothermal mineralization, and proposes an alternative method to measure the spatial relationships between geological features and mineral deposits using multifractal singularity theory. It was observed that the greater the proximity to geological controlling features, the greater the number of mineral deposits developed, indicating a nonlinear spatial relationship between these features and mineral deposits. This phenomenon can be quantified using the relationship between the numbers of mineral deposits N(ε) of a D-dimensional set and the scale of ε. The density of mineral deposits can be expressed as ρ(ε) = Cε−(De−a), where ε is the buffer width of geological controlling features, De is Euclidean dimension of space (=2 in this case), a is singularity index, and C is a constant. The expression can be rewritten as ρ = Cεa−2. When a < 2, there is a significant spatial correlation between specific geological features and mineral deposits; lower a values indicate a more significant spatial correlation. This nonlinear relationship and the advantages of this method were illustrated using a case study from Fujian Province in China and a case study from Baguio district in Philippines. PMID:27255794

Electrophysiological correlates of predictive coding of auditory location in the perception of natural audiovisual events.

PubMed

Stekelenburg, Jeroen J; Vroomen, Jean

2012-01-01

In many natural audiovisual events (e.g., a clap of the two hands), the visual signal precedes the sound and thus allows observers to predict when, where, and which sound will occur. Previous studies have reported that there are distinct neural correlates of temporal (when) versus phonetic/semantic (which) content on audiovisual integration. Here we examined the effect of visual prediction of auditory location (where) in audiovisual biological motion stimuli by varying the spatial congruency between the auditory and visual parts. Visual stimuli were presented centrally, whereas auditory stimuli were presented either centrally or at 90° azimuth. Typical sub-additive amplitude reductions (AV - V < A) were found for the auditory N1 and P2 for spatially congruent and incongruent conditions. The new finding is that this N1 suppression was greater for the spatially congruent stimuli. A very early audiovisual interaction was also found at 40-60 ms (P50) in the spatially congruent condition, while no effect of congruency was found on the suppression of the P2. This indicates that visual prediction of auditory location can be coded very early in auditory processing.

A nonlinear controlling function of geological features on magmatic-hydrothermal mineralization.

PubMed

Zuo, Renguang

2016-06-03

This paper reports a nonlinear controlling function of geological features on magmatic-hydrothermal mineralization, and proposes an alternative method to measure the spatial relationships between geological features and mineral deposits using multifractal singularity theory. It was observed that the greater the proximity to geological controlling features, the greater the number of mineral deposits developed, indicating a nonlinear spatial relationship between these features and mineral deposits. This phenomenon can be quantified using the relationship between the numbers of mineral deposits N(ε) of a D-dimensional set and the scale of ε. The density of mineral deposits can be expressed as ρ(ε) = Cε(-(De-a)), where ε is the buffer width of geological controlling features, De is Euclidean dimension of space (=2 in this case), a is singularity index, and C is a constant. The expression can be rewritten as ρ = Cε(a-2). When a < 2, there is a significant spatial correlation between specific geological features and mineral deposits; lower a values indicate a more significant spatial correlation. This nonlinear relationship and the advantages of this method were illustrated using a case study from Fujian Province in China and a case study from Baguio district in Philippines.

The spatial pattern of suicide in the US in relation to deprivation, fragmentation and rurality.

PubMed

Congdon, Peter

2011-01-01

Analysis of geographical patterns of suicide and psychiatric morbidity has demonstrated the impact of latent ecological variables (such as deprivation, rurality). Such latent variables may be derived by conventional multivariate techniques from sets of observed indices (for example, by principal components), by composite variable methods or by methods which explicitly consider the spatial framework of areas and, in particular, the spatial clustering of latent risks and outcomes. This article considers a latent random variable approach to explaining geographical contrasts in suicide in the US; and it develops a spatial structural equation model incorporating deprivation, social fragmentation and rurality. The approach allows for such latent spatial constructs to be correlated both within and between areas. Potential effects of area ethnic mix are also included. The model is applied to male and female suicide deaths over 2002–06 in 3142 US counties.

Spatial mapping of lead, arsenic, iron, and polycyclic aromatic hydrocarbon soil contamination in Sydney, Nova Scotia: community impact from the coke ovens and steel plant.

PubMed

Lambert, Timothy W; Boehmer, Jennifer; Feltham, Jason; Guyn, Lindsay; Shahid, Rizwan

2011-01-01

This paper presents spatial maps of the arsenic, lead, and polycyclic aromatic hydrocarbon (PAH) soil contamination in Sydney, Nova Scotia, Canada. The spatial maps were designed to create exposure cohorts to help understand the observed increase in health effects. To assess whether contamination can be a proxy for exposures, the following hypothesis was tested: residential soils were impacted by the coke oven and steel plant industrial complex. The spatial map showed contaminants are centered on the industrial facility, significantly correlated, and exceed Canadian health risk-based soil quality guidelines. Core samples taken at 5-cm intervals suggest a consistent deposition over time. The concentrations in Sydney significantly exceed background Sydney soil concentrations, and are significantly elevated compared with North Sydney, an adjacent industrial community. The contaminant spatial maps will also be useful for developing cohorts of exposure and guiding risk management decisions.

A study on assimilating potential vorticity data

NASA Astrophysics Data System (ADS)

Li, Yong; Ménard, Richard; Riishøjgaard, Lars Peter; Cohn, Stephen E.; Rood, Richard B.

1998-08-01

The correlation that exists between the potential vorticity (PV) field and the distribution of chemical tracers such as ozone suggests the possibility of using tracer observations as proxy PV data in atmospheric data assimilation systems. Especially in the stratosphere, there are plentiful tracer observations but a general lack of reliable wind observations, and the correlation is most pronounced. The issue investigated in this study is how model dynamics would respond to the assimilation of PV data. First, numerical experiments of identical-twin type were conducted with a simple univariate nuding algorithm and a global shallow water model based on PV and divergence (PV-D model). All model fields are successfully reconstructed through the insertion of complete PV data alone if an appropriate value for the nudging coefficient is used. A simple linear analysis suggests that slow modes are recovered rapidly, at a rate nearly independent of spatial scale. In a more realistic experiment, appropriately scaled total ozone data from the NIMBUS-7 TOMS instrument were assimilated as proxy PV data into the PV-D model over a 10-day period. The resulting model PV field matches the observed total ozone field relatively well on large spatial scales, and the PV, geopotential and divergence fields are dynamically consistent. These results indicate the potential usefulness that tracer observations, as proxy PV data, may offer in a data assimilation system.

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

Treesearch

John Hof; Curtis H. Flather

1996-01-01

This paper investigates optimization approaches to simultaneously modelling habitat fragmentation and spatial correlation between patch populations. The problem is formulated with habitat connectivity affecting population means and variances, with spatial correlations accounted for in covariance calculations. Population with a pre-specifled confidence level is then...

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

NASA Astrophysics Data System (ADS)

Wang, Huiqin; Wang, Xue; Cao, Minghua

2017-02-01

The spatial correlation extensively exists in the multiple-input multiple-output (MIMO) free space optical (FSO) communication systems due to the channel fading and the antenna space limitation. Wilkinson's method was utilized to investigate the impact of spatial correlation on the MIMO FSO communication system employing multipulse pulse-position modulation. Simulation results show that the existence of spatial correlation reduces the ergodic channel capacity, and the reception diversity is more competent to resist this kind of performance degradation.

A novel spatial performance metric for robust pattern optimization of distributed hydrological models

NASA Astrophysics Data System (ADS)

Stisen, S.; Demirel, C.; Koch, J.

2017-12-01

Evaluation of performance is an integral part of model development and calibration as well as it is of paramount importance when communicating modelling results to stakeholders and the scientific community. There exists a comprehensive and well tested toolbox of metrics to assess temporal model performance in the hydrological modelling community. On the contrary, the experience to evaluate spatial performance is not corresponding 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 aims at making a contribution towards advancing spatial pattern oriented model evaluation for distributed hydrological models. This is achieved by introducing a novel spatial performance metric which provides robust pattern performance during model calibration. The promoted SPAtial EFficiency (spaef) metric reflects three equally weighted components: correlation, coefficient of variation and histogram overlap. This multi-component approach is necessary in order to adequately compare spatial patterns. spaef, its three components individually and two alternative spatial performance metrics, i.e. connectivity analysis and fractions skill score, are tested in a spatial pattern oriented model calibration of a catchment model in Denmark. The calibration is constrained by a remote sensing based spatial pattern of evapotranspiration and discharge timeseries at two stations. Our results stress that stand-alone metrics tend to fail to provide holistic pattern information to the optimizer which underlines the importance of multi-component metrics. The three spaef components are independent which allows them to complement each other in a meaningful way. This study promotes the use of bias insensitive metrics which allow comparing variables which are related but may differ in unit in order to optimally exploit spatial observations made available by remote sensing platforms. We see great potential of spaef across environmental disciplines dealing with spatially distributed modelling.

Contrasting spatial structures of Atlantic Multidecadal Oscillation between observations and slab ocean model simulations

NASA Astrophysics Data System (ADS)

Sun, Cheng; Li, Jianping; Kucharski, Fred; Xue, Jiaqing; Li, Xiang

2018-04-01

The spatial structure of Atlantic multidecadal oscillation (AMO) is analyzed and compared between the observations and simulations from slab ocean models (SOMs) and fully coupled models. The observed sea surface temperature (SST) pattern of AMO is characterized by a basin-wide monopole structure, and there is a significantly high degree of spatial coherence of decadal SST variations across the entire North Atlantic basin. The observed SST anomalies share a common decadal-scale signal, corresponding to the basin-wide average (i. e., the AMO). In contrast, the simulated AMO in SOMs (AMOs) exhibits a tripole-like structure, with the mid-latitude North Atlantic SST showing an inverse relationship with other parts of the basin, and the SOMs fail to reproduce the observed strong spatial coherence of decadal SST variations associated with the AMO. The observed spatial coherence of AMO SST anomalies is identified as a key feature that can be used to distinguish the AMO mechanism. The tripole-like SST pattern of AMOs in SOMs can be largely explained by the atmosphere-forced thermodynamics mechanism due to the surface heat flux changes associated with the North Atlantic Oscillation (NAO). The thermodynamic forcing of AMOs by the NAO gives rise to a simultaneous inverse NAO-AMOs relationship at both interannual and decadal timescales and a seasonal phase locking of the AMOs variability to the cold season. However, the NAO-forced thermodynamics mechanism cannot explain the observed NAO-AMO relationship and the seasonal phase locking of observed AMO variability to the warm season. At decadal timescales, a strong lagged relationship between NAO and AMO is observed, with the NAO leading by up to two decades, while the simultaneous correlation of NAO with AMO is weak. This lagged relationship and the spatial coherence of AMO can be well understood from the view point of ocean dynamics. A time-integrated NAO index, which reflects the variations in Atlantic meridional overturning circulation (AMOC) and northward ocean heat transport caused by the accumulated effect of NAO forcing, reasonably well captures the observed multidecadal fluctuations in the AMO. Further analysis using the fully coupled model simulations provides direct modeling evidence that the observed spatial coherence of decadal SST variations across North Atlantic basin can be reproduced only by including the AMOC-related ocean dynamics, and the AMOC acts as a common forcing signal that results in a spatially coherent variation of North Atlantic SST.

The cluster-cluster correlation function. [of galaxies

NASA Technical Reports Server (NTRS)

Postman, M.; Geller, M. J.; Huchra, J. P.

1986-01-01

The clustering properties of the Abell and Zwicky cluster catalogs are studied using the two-point angular and spatial correlation functions. The catalogs are divided into eight subsamples to determine the dependence of the correlation function on distance, richness, and the method of cluster identification. It is found that the Corona Borealis supercluster contributes significant power to the spatial correlation function to the Abell cluster sample with distance class of four or less. The distance-limited catalog of 152 Abell clusters, which is not greatly affected by a single system, has a spatial correlation function consistent with the power law Xi(r) = 300r exp -1.8. In both the distance class four or less and distance-limited samples the signal in the spatial correlation function is a power law detectable out to 60/h Mpc. The amplitude of Xi(r) for clusters of richness class two is about three times that for richness class one clusters. The two-point spatial correlation function is sensitive to the use of estimated redshifts.

A method to classify schizophrenia using inter-task spatial correlations of functional brain images.

PubMed

Michael, Andrew M; Calhoun, Vince D; Andreasen, Nancy C; Baum, Stefi A

2008-01-01

The clinical heterogeneity of schizophrenia (scz) and the overlap of self reported and observed symptoms with other mental disorders makes its diagnosis a difficult task. At present no laboratory-based or image-based diagnostic tool for scz exists and such tools are desired to support existing methods for more precise diagnosis. Functional magnetic resonance imaging (fMRI) is currently employed to identify and correlate cognitive processes related to scz and its symptoms. Fusion of multiple fMRI tasks that probe different cognitive processes may help to better understand hidden networks of this complex disorder. In this paper we utilize three different fMRI tasks and introduce an approach to classify subjects based on inter-task spatial correlations of brain activation. The technique was applied to groups of patients and controls and its validity was checked with the leave-one-out method. We show that the classification rate increases when information from multiple tasks are combined.

Analysis of precipitation teleconnections in CMIP models as a measure of model fidelity in simulating precipitation

NASA Astrophysics Data System (ADS)

Langenbrunner, B.; Neelin, J.; Meyerson, J.

2011-12-01

The accurate representation of precipitation is a recurring issue in global climate models, especially in the tropics. Poor skill in modeling the variability and climate teleconnections associated with El Niño/Southern Oscillation (ENSO) also persisted in the latest Climate Model Intercomparison Project (CMIP) campaigns. Observed ENSO precipitation teleconnections provide a standard by which we can judge a given model's ability to reproduce precipitation and dynamic feedback processes originating in the tropical Pacific. Using CMIP3 Atmospheric Model Intercomparison Project (AMIP) runs as a baseline, we compare precipitation teleconnections between models and observations, and we evaluate these results against available CMIP5 historical and AMIP runs. Using AMIP simulations restricts evaluation to the atmospheric response, as sea surface temperatures (SSTs) in AMIP are prescribed by observations. We use a rank correlation between ENSO SST indices and precipitation to define teleconnections, since this method is robust to outliers and appropriate for non-Gaussian data. Spatial correlations of the modeled and observed teleconnections are then evaluated. We look at these correlations in regions of strong precipitation teleconnections, including equatorial S. America, the "horseshoe" region in the western tropical Pacific, and southern N. America. For each region and season, we create a "normalized projection" of a given model's teleconnection pattern onto that of the observations, a metric that assesses the quality of regional pattern simulations while rewarding signals of correct sign over the region. Comparing this to an area-averaged (i.e., more generous) metric suggests models do better when restrictions on exact spatial dependence are loosened and conservation constraints apply. Model fidelity in regional measures remains far from perfect, suggesting intrinsic issues with the models' regional sensitivities in moist processes.

Effects of a cognitive training on spatial learning and associated functional brain activations

PubMed Central

2013-01-01

Background Both cognitive and physical exercise have been discussed as promising interventions for healthy cognitive aging. The present study assessed the effects of cognitive training (spatial vs. perceptual training) and physical training (endurance training vs. non-endurance training) on spatial learning and associated brain activation in 33 adults (40–55 years). Spatial learning was assessed with a virtual maze task, and at the same time neural correlates were measured with functional magnetic resonance imaging (fMRI). Results Only the spatial training improved performance in the maze task. These behavioral gains were accompanied by a decrease in frontal and temporal lobe activity. At posttest, participants of the spatial training group showed lower activity than participants of the perceptual training group in a network of brain regions associated with spatial learning, including the hippocampus and parahippocampal gyrus. No significant differences were observed between the two physical intervention groups. Conclusions Functional changes in neural systems associated with spatial navigation can be induced by cognitive interventions and seem to be stronger than effects of physical exercise in middle-aged adults. PMID:23870447

Velocity-vorticity correlation structures (VVCS) in spatially developing compressible turbulent boundary layer

NASA Astrophysics Data System (ADS)

Li, Shi-Yao; She, Zhen-Su; Chen, Jun

2017-11-01

A velocity-vorticity correlation structure (VVCS) analysis is applied to the direct numerical simulation (DNS) of compressible turbulent boundary layer (CTBL) at Mach numbers, Ma = 2.25 , 4.50 and 6.0 . It is shown that the VVCS analysis captures the geometry variation in the streamwise direction during the transition and in the wall-normal direction in the fully developed regime. Specifically, before transition, the VVCS captures the instability wave number, while in the transition region it displays a distinct scaling change of the dimensions. The fully developed turbulence regime is characterized by a nearly constant spatial extension of the VVCS. Particularly, after turbulence is well developed, a multi-layer structure in the wall normal direction is observed in the maximum correlation coefficient and in the length scales of the VVCS, as expected from a recent symmetry-based theory, the ensemble structure dynamics (SED). The most interesting outcome is an observed linear dependence of the length scale of the VVCS from y+ 50 to 200, which is a direct support to Townsend's attached-eddy theory. In conclusion, the VVCS analysis quantifies the geometrical characteristics of the coherent structures in turbulent compressible shear flows throughout the whole domain. Supported by NSFC (11172006, 11221062, 11452002) and by MOST (China) 973 project (2009CB724100).

Temperature properties in the tropical tropopause layer and their correlations with Outgoing Longwave Radiation: FORMOSAT-3/COSMIC observations

NASA Astrophysics Data System (ADS)

Wang, Kaiti; Wu, Yi-chao; Lin, Jia-Ting; Tan, Pei-Hua

2018-06-01

The properties of temperature at the level of lapse rate minimum (LRM) in the tropical tropopause layer between 20°S and 20°N are investigated using 3-year radio occultation observations based on the FORMOSAT-3/COSMIC mission from November of 2006 to October of 2009. The correlations between this LRM temperature and Outgoing Longwave Radiation (OLR) are analyzed by 5° × 5° grids in longitude and latitude. Two primary regions, one from 60°E to 180°E and the other from 90°W to 30°E, are found to have higher correlations and can be associated with regions of lower OLR values. The patterns of this spatial distributions of regions with higher correlations begin to change more obviously when the altitude ascends to the level of Cold Point Tropopause (CPT). This correlation at the LRM altitude in annual and seasonal scales also shows spatial distributions associated with OLR intensities. The altitudinal dependence of the correlations between temperature and OLR is further analyzed based on grids of high correlations with significance at LRM altitude, for the two primary regions. The results show that for the different time scales in this analysis (3-year, annual, and seasonal), the correlations all gradually decrease above the LRM levels but maintain a significant level to as high as 2.5-3.5 km. Below the LRM level, the correlation decreases with a slower rate as the altitude descends and still keeps significant at the deep 5 km level. These suggest that the vertical temperature profiles could be affected by the convection mechanism for a wide range of altitudes in the troposphere even above LRM altitude. Applying the same analysis on one complete La Niña event during the survey period also reveals similar features.

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

NASA Astrophysics Data System (ADS)

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.

Statistical Quality Control of Moisture Data in GEOS DAS

NASA Technical Reports Server (NTRS)

Dee, D. P.; Rukhovets, L.; Todling, R.

1999-01-01

A new statistical quality control algorithm was recently implemented in the Goddard Earth Observing System Data Assimilation System (GEOS DAS). The final step in the algorithm consists of an adaptive buddy check that either accepts or rejects outlier observations based on a local statistical analysis of nearby data. A basic assumption in any such test is that the observed field is spatially coherent, in the sense that nearby data can be expected to confirm each other. However, the buddy check resulted in excessive rejection of moisture data, especially during the Northern Hemisphere summer. The analysis moisture variable in GEOS DAS is water vapor mixing ratio. Observational evidence shows that the distribution of mixing ratio errors is far from normal. Furthermore, spatial correlations among mixing ratio errors are highly anisotropic and difficult to identify. Both factors contribute to the poor performance of the statistical quality control algorithm. To alleviate the problem, we applied the buddy check to relative humidity data instead. This variable explicitly depends on temperature and therefore exhibits a much greater spatial coherence. As a result, reject rates of moisture data are much more reasonable and homogeneous in time and space.

[Temporal and spatial characteristics of ecological risk in Shunyi, Beijing, China based on landscape structure.

PubMed

Qing, Feng Ting; Peng, Yu

2016-05-01

Based on the remote sensing data in 1997, 2001, 2005, 2009 and 2013, this article classified the landscape types of Shunyi, and the ecological risk index was built based on landscape disturbance index and landscape fragility. The spatial auto-correlation and geostatistical analysis by GS + and ArcGIS was used to study temporal and spatial changes of ecological risk. The results showed that eco-risk degree in the study region had positive spatial correlation which decreased with the increasing grain size. Within a certain grain range (<12 km), the spatial auto-correlation had an obvious dependence on scale. The random variation of spatial heterogeneity was less than spatial auto-correlation variation from 1997 to 2013, which meant the auto-correlation had a dominant role in spatial heterogeneity. The ecological risk of Shunyi was mainly at moderate level during the study period. The area of the district with higher and lower ecological risk increased, while that of mode-rate ecological risk decreased. The area with low ecological risk was mainly located in the airport region and forest of southeast Shunyi, while that with high ecological risk was mainly concentrated in the water landscape, such as the banks of Chaobai River.

Comparing observer models and feature selection methods for a task-based statistical assessment of digital breast tomsynthesis in reconstruction space

NASA Astrophysics Data System (ADS)

Park, Subok; Zhang, George Z.; Zeng, Rongping; Myers, Kyle J.

2014-03-01

A task-based assessment of image quality1 for digital breast tomosynthesis (DBT) can be done in either the projected or reconstructed data space. As the choice of observer models and feature selection methods can vary depending on the type of task and data statistics, we previously investigated the performance of two channelized- Hotelling observer models in conjunction with 2D Laguerre-Gauss (LG) and two implementations of partial least squares (PLS) channels along with that of the Hotelling observer in binary detection tasks involving DBT projections.2, 3 The difference in these observers lies in how the spatial correlation in DBT angular projections is incorporated in the observer's strategy to perform the given task. In the current work, we extend our method to the reconstructed data space of DBT. We investigate how various model observers including the aforementioned compare for performing the binary detection of a spherical signal embedded in structured breast phantoms with the use of DBT slices reconstructed via filtered back projection. We explore how well the model observers incorporate the spatial correlation between different numbers of reconstructed DBT slices while varying the number of projections. For this, relatively small and large scan angles (24° and 96°) are used for comparison. Our results indicate that 1) given a particular scan angle, the number of projections needed to achieve the best performance for each observer is similar across all observer/channel combinations, i.e., Np = 25 for scan angle 96° and Np = 13 for scan angle 24°, and 2) given these sufficient numbers of projections, the number of slices for each observer to achieve the best performance differs depending on the channel/observer types, which is more pronounced in the narrow scan angle case.

A twin study of spatial and non-spatial delayed response performance in middle age.

PubMed

Kremen, William S; Mai, Tuan; Panizzon, Matthew S; Franz, Carol E; Blankfeld, Howard M; Xian, Hong; Eisen, Seth A; Tsuang, Ming T; Lyons, Michael J

2011-06-01

Delayed alternation and object alternation are classic spatial and non-spatial delayed response tasks. We tested 632 middle-aged male veteran twins on variants of these tasks in order to compare test difficulty, measure their inter-correlation, test order effects, and estimate heritabilities (proportion of observed variance due to genetic influences). Non-spatial alternation (NSA), which may involve greater reliance on processing of subgoals, was significantly more difficult than spatial alternation (SA). Despite their similarities, NSA and SA scores were uncorrelated. NSA performance was worse when administered second; there was no SA order effect. NSA scores were modestly heritable (h(2)=.25; 26); SA was not. There was shared genetic variance between NSA scores and general intellectual ability (r(g)=.55; .67), but this also suggests genetic influences specific to NSA. Compared with findings from small, selected control samples, high "failure" rates in this community-based sample raise concerns about interpretation of brain dysfunction in elderly or patient samples. Copyright © 2011 Elsevier Inc. All rights reserved.

A Twin Study of Spatial and Non-Spatial Delayed Response Performance in Middle Age

PubMed Central

Kremen, William S.; Mai, Tuan; Panizzon, Matthew S.; Franz, Carol E.; Blankfeld, Howard M.; Xian, Hong; Eisen, Seth A.; Tsuang, Ming T.; Lyons, Michael J.

2011-01-01

Delayed alternation and object alternation are classic spatial and non-spatial delayed response tasks. We tested 632 middle-aged male veteran twins on variants of these tasks in order to compare test difficulty, measure their inter-correlation, test order effects, and estimate heritabilities (proportion of observed variance due to genetic influences). Non-spatial alternation (NSA), which may involve greater reliance on processing of subgoals, was significantly more difficult than spatial alternation (SA). Despite their similarities, NSA and SA scores were uncorrelated. NSA performance was worse when administered second; there was no SA order effect. NSA scores were modestly heritable (h2=.25; 26); SA was not. There was shared genetic variance between NSA scores and general intellectual ability (rg=.55; .67), but this also suggests genetic influences specific to NSA. Compared with findings from small, selected control samples, high “failure” rates in this community-based sample raise concerns about interpretation of brain dysfunction in elderly or patient samples. PMID:21477911

Spatial variations in mortality in pelagic early life stages of a marine fish (Gadus morhua)

NASA Astrophysics Data System (ADS)

Langangen, Øystein; Stige, Leif C.; Yaragina, Natalia A.; Ottersen, Geir; Vikebø, Frode B.; Stenseth, Nils Chr.

2014-09-01

Mortality of pelagic eggs and larvae of marine fish is often assumed to be constant both in space and time due to lacking information. This may, however, be a gross oversimplification, as early life stages are likely to experience large variations in mortality both in time and space. In this paper we develop a method for estimating the spatial variability in mortality of eggs and larvae. The method relies on survey data and physical-biological particle-drift models to predict the drift of ichthyoplankton. Furthermore, the method was used to estimate the spatially resolved mortality field in the egg and larval stages of Barents Sea cod (Gadus morhua). We analyzed data from the Barents Sea for the period between 1959 and 1993 when there are two surveys available: a spring and a summer survey. An individual-based physical-biological particle-drift model, tailored to the egg and larval stages of Barents Sea cod, was used to predict the drift trajectories from the observed stage-specific distributions in spring to the time of observation in the summer, a drift time of approximately 45 days. We interpreted the spatial patterns in the differences between the predicted and observed abundance distributions in summer as reflecting the spatial patterns in mortality over the drift period. Using the estimated mortality fields, we show that the spatial variations in mortality might have a significant impact on survival to later life stages and we suggest that there may be trade-offs between increased early survival in off shore regions and reduced probability of ending up in the favorable nursing grounds in the Barents Sea. In addition, we show that accounting for the estimated mortality field, improves the correlation between a simulated recruitment index and observation-based indices of juvenile abundance.

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

Thampy, V.; Chen, X. M.; Cao, Y.

Charge-density-wave (CDW) correlations feature prominently in the phase diagram of the cuprates, motivating competing theories of whether fluctuating CDW correlations aid superconductivity or whether static CDW order coexists with superconductivity in inhomogeneous or spatially modulated states. Here we report Cu L-edge resonant x-ray photon correlation spectroscopy measurements of CDW correlations in superconducting La 2–xBa xCuO 4, x = 0.11. Static CDW order is shown to exist in the superconducting state at low temperatures and to persist up to at least 85% of the CDW transition temperature. As a result, we discuss the implications of our observations for how nominally competingmore » order parameters can coexist in the cuprates.« less

Goal-oriented sensitivity analysis for lattice kinetic Monte Carlo simulations

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

Arampatzis, Georgios, E-mail: garab@math.uoc.gr; Department of Mathematics and Statistics, University of Massachusetts, Amherst, Massachusetts 01003; Katsoulakis, Markos A., E-mail: markos@math.umass.edu

2014-03-28

In this paper we propose a new class of coupling methods for the sensitivity analysis of high dimensional stochastic systems and in particular for lattice Kinetic Monte Carlo (KMC). Sensitivity analysis for stochastic systems is typically based on approximating continuous derivatives with respect to model parameters by the mean value of samples from a finite difference scheme. Instead of using independent samples the proposed algorithm reduces the variance of the estimator by developing a strongly correlated-“coupled”- stochastic process for both the perturbed and unperturbed stochastic processes, defined in a common state space. The novelty of our construction is that themore » new coupled process depends on the targeted observables, e.g., coverage, Hamiltonian, spatial correlations, surface roughness, etc., hence we refer to the proposed method as goal-oriented sensitivity analysis. In particular, the rates of the coupled Continuous Time Markov Chain are obtained as solutions to a goal-oriented optimization problem, depending on the observable of interest, by considering the minimization functional of the corresponding variance. We show that this functional can be used as a diagnostic tool for the design and evaluation of different classes of couplings. Furthermore, the resulting KMC sensitivity algorithm has an easy implementation that is based on the Bortz–Kalos–Lebowitz algorithm's philosophy, where events are divided in classes depending on level sets of the observable of interest. Finally, we demonstrate in several examples including adsorption, desorption, and diffusion Kinetic Monte Carlo that for the same confidence interval and observable, the proposed goal-oriented algorithm can be two orders of magnitude faster than existing coupling algorithms for spatial KMC such as the Common Random Number approach. We also provide a complete implementation of the proposed sensitivity analysis algorithms, including various spatial KMC examples, in a supplementary MATLAB source code.« less

Executive Function, Visual Attention and the Cocktail Party Problem in Musicians and Non-Musicians.

PubMed

Clayton, Kameron K; Swaminathan, Jayaganesh; Yazdanbakhsh, Arash; Zuk, Jennifer; Patel, Aniruddh D; Kidd, Gerald

2016-01-01

The goal of this study was to investigate how cognitive factors influence performance in a multi-talker, "cocktail-party" like environment in musicians and non-musicians. This was achieved by relating performance in a spatial hearing task to cognitive processing abilities assessed using measures of executive function (EF) and visual attention in musicians and non-musicians. For the spatial hearing task, a speech target was presented simultaneously with two intelligible speech maskers that were either colocated with the target (0° azimuth) or were symmetrically separated from the target in azimuth (at ±15°). EF assessment included measures of cognitive flexibility, inhibition control and auditory working memory. Selective attention was assessed in the visual domain using a multiple object tracking task (MOT). For the MOT task, the observers were required to track target dots (n = 1,2,3,4,5) in the presence of interfering distractor dots. Musicians performed significantly better than non-musicians in the spatial hearing task. For the EF measures, musicians showed better performance on measures of auditory working memory compared to non-musicians. Furthermore, across all individuals, a significant correlation was observed between performance on the spatial hearing task and measures of auditory working memory. This result suggests that individual differences in performance in a cocktail party-like environment may depend in part on cognitive factors such as auditory working memory. Performance in the MOT task did not differ between groups. However, across all individuals, a significant correlation was found between performance in the MOT and spatial hearing tasks. A stepwise multiple regression analysis revealed that musicianship and performance on the MOT task significantly predicted performance on the spatial hearing task. Overall, these findings confirm the relationship between musicianship and cognitive factors including domain-general selective attention and working memory in solving the "cocktail party problem".

Dynamic hydro-climatic networks in pristine and regulated rivers

NASA Astrophysics Data System (ADS)

Botter, G.; Basso, S.; Lazzaro, G.; Doulatyari, B.; Biswal, B.; Schirmer, M.; Rinaldo, A.

2014-12-01

Flow patterns observed at-a-station are the dynamical byproduct of a cascade of processes involving different compartments of the hydro-climatic network (e.g., climate, rainfall, soil, vegetation) that regulates the transformation of rainfall into streamflows. In complex branching rivers, flow regimes result from the heterogeneous arrangement around the stream network of multiple hydrologic cascades that simultaneously occur within distinct contributing areas. As such, flow regimes are seen as the integrated output of a complex "network of networks", which can be properly characterized by its degree of temporal variability and spatial heterogeneity. Hydrologic networks that generate river flow regimes are dynamic in nature. In pristine rivers, the time-variance naturally emerges at multiple timescales from climate variability (namely, seasonality and inter-annual fluctuations), implying that the magnitude (and the features) of the water flow between two nodes may be highly variable across different seasons and years. Conversely, the spatial distribution of river flow regimes within pristine rivers involves scale-dependent transport features, as well as regional climatic and soil use gradients, which in small and meso-scale catchments (A < 103 km2) are usually mild enough to guarantee quite uniform flow regimes and high spatial correlations. Human-impacted rivers, instead, constitute hybrid networks where observed spatio-temporal patterns are dominated by anthropogenic shifts, such as landscape alterations and river regulation. In regulated rivers, the magnitude and the features of water flows from node to node may change significantly through time due to damming and withdrawals. However, regulation may impact river regimes in a spatially heterogeneous manner (e.g. in localized river reaches), with a significant decrease of spatial correlations and network connectivity. Provided that the spatial and temporal dynamics of flow regimes in complex rivers may strongly impact important biotic processes involved in the river food web (e.g. biofilm and riparian vegetation dynamics), the study of rivers as dynamic networks provides important clues to water management strategies and freshwater ecosystem studies.

Executive Function, Visual Attention and the Cocktail Party Problem in Musicians and Non-Musicians

PubMed Central

Clayton, Kameron K.; Swaminathan, Jayaganesh; Yazdanbakhsh, Arash; Zuk, Jennifer; Patel, Aniruddh D.; Kidd, Gerald

2016-01-01

The goal of this study was to investigate how cognitive factors influence performance in a multi-talker, “cocktail-party” like environment in musicians and non-musicians. This was achieved by relating performance in a spatial hearing task to cognitive processing abilities assessed using measures of executive function (EF) and visual attention in musicians and non-musicians. For the spatial hearing task, a speech target was presented simultaneously with two intelligible speech maskers that were either colocated with the target (0° azimuth) or were symmetrically separated from the target in azimuth (at ±15°). EF assessment included measures of cognitive flexibility, inhibition control and auditory working memory. Selective attention was assessed in the visual domain using a multiple object tracking task (MOT). For the MOT task, the observers were required to track target dots (n = 1,2,3,4,5) in the presence of interfering distractor dots. Musicians performed significantly better than non-musicians in the spatial hearing task. For the EF measures, musicians showed better performance on measures of auditory working memory compared to non-musicians. Furthermore, across all individuals, a significant correlation was observed between performance on the spatial hearing task and measures of auditory working memory. This result suggests that individual differences in performance in a cocktail party-like environment may depend in part on cognitive factors such as auditory working memory. Performance in the MOT task did not differ between groups. However, across all individuals, a significant correlation was found between performance in the MOT and spatial hearing tasks. A stepwise multiple regression analysis revealed that musicianship and performance on the MOT task significantly predicted performance on the spatial hearing task. Overall, these findings confirm the relationship between musicianship and cognitive factors including domain-general selective attention and working memory in solving the “cocktail party problem”. PMID:27384330

Analysis of parenchymal patterns using conspicuous spatial frequency features in mammograms applied to the BI-RADS density rating scheme

NASA Astrophysics Data System (ADS)

Perconti, Philip; Loew, Murray

2006-03-01

Automatic classification of the density of breast parenchyma is shown using a measure that is correlated to the human observer performance, and compared against the BI-RADS density rating. Increasingly popular in the United States, the Breast Imaging Reporting and Data System (BI-RADS) is used to draw attention to the increased screening difficulty associated with greater breast density; however, the BI-RADS rating scheme is subjective and is not intended as an objective measure of breast density. So, while popular, BI-RADS does not define density classes using a standardized measure, which leads to increased variability among observers. The adaptive thresholding technique is a more quantitative approach for assessing the percentage breast density, but considerable reader interaction is required. We calculate an objective density rating that is derived using a measure of local feature salience. Previously, this measure was shown to correlate well with radiologists' localization and discrimination of true positive and true negative regions-of-interest. Using conspicuous spatial frequency features, an objective density rating is obtained and correlated with adaptive thresholding, and the subjectively ascertained BI-RADS density ratings. Using 100 cases, obtained from the University of South Florida's DDSM database, we show that an automated breast density measure can be derived that is correlated with the interactive thresholding method for continuous percentage breast density, but not with the BI-RADS density rating categories for the selected cases. Comparison between interactive thresholding and the new salience percentage density resulted in a Pearson correlation of 76.7%. Using a four-category scale equivalent to the BI-RADS density categories, a Spearman correlation coefficient of 79.8% was found.

Satellite remote sensing data can be used to model marine microbial metabolite turnover

PubMed Central

Larsen, Peter E; Scott, Nicole; Post, Anton F; Field, Dawn; Knight, Rob; Hamada, Yuki; Gilbert, Jack A

2015-01-01

Sampling ecosystems, even at a local scale, at the temporal and spatial resolution necessary to capture natural variability in microbial communities are prohibitively expensive. We extrapolated marine surface microbial community structure and metabolic potential from 72 16S rRNA amplicon and 8 metagenomic observations using remotely sensed environmental parameters to create a system-scale model of marine microbial metabolism for 5904 grid cells (49 km2) in the Western English Chanel, across 3 years of weekly averages. Thirteen environmental variables predicted the relative abundance of 24 bacterial Orders and 1715 unique enzyme-encoding genes that encode turnover of 2893 metabolites. The genes' predicted relative abundance was highly correlated (Pearson Correlation 0.72, P-value <10−6) with their observed relative abundance in sequenced metagenomes. Predictions of the relative turnover (synthesis or consumption) of CO2 were significantly correlated with observed surface CO2 fugacity. The spatial and temporal variation in the predicted relative abundances of genes coding for cyanase, carbon monoxide and malate dehydrogenase were investigated along with the predicted inter-annual variation in relative consumption or production of ∼3000 metabolites forming six significant temporal clusters. These spatiotemporal distributions could possibly be explained by the co-occurrence of anaerobic and aerobic metabolisms associated with localized plankton blooms or sediment resuspension, which facilitate the presence of anaerobic micro-niches. This predictive model provides a general framework for focusing future sampling and experimental design to relate biogeochemical turnover to microbial ecology. PMID:25072414

Satellite remote sensing data can be used to model marine microbial metabolite turnover

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

Larsen, Peter E.; Scott, Nicole; Post, Anton F.

Sampling ecosystems, even at a local scale, at the temporal and spatial resolution necessary to capture natural variability in microbial communities are prohibitively expensive. We extrapolated marine surface microbial community structure and metabolic potential from 72 16S rRNA amplicon and 8 metagenomic observations using remotely sensed environmental parameters to create a system-scale model of marine microbial metabolism for 5904 grid cells (49 km2) in the Western English Chanel, across 3 years of weekly averages. Thirteen environmental variables predicted the relative abundance of 24 bacterial Orders and 1715 unique enzyme-encoding genes that encode turnover of 2893 metabolites. The genes’ predicted relativemore » abundance was highly correlated (Pearson Correlation 0.72, P-value <10-6) with their observed relative abundance in sequenced metagenomes. Predictions of the relative turnover (synthesis or consumption) of CO2 were significantly correlated with observed surface CO2 fugacity. The spatial and temporal variation in the predicted relative abundances of genes coding for cyanase, carbon monoxide and malate dehydrogenase were investigated along with the predicted inter-annual variation in relative consumption or production of ~3000 metabolites forming six significant temporal clusters. These spatiotemporal distributions could possibly be explained by the co-occurrence of anaerobic and aerobic metabolisms associated with localized plankton blooms or sediment resuspension, which facilitate the presence of anaerobic micro-niches. This predictive model provides a general framework for focusing future sampling and experimental design to relate biogeochemical turnover to microbial ecology.« less

Gravitational-wave localization alone can probe origin of stellar-mass black hole mergers.

PubMed

Bartos, I; Haiman, Z; Marka, Z; Metzger, B D; Stone, N C; Marka, S

2017-10-10

The recent discovery of gravitational waves from stellar-mass binary black hole mergers by the Laser Interferometer Gravitational-wave Observatory opened the door to alternative probes of stellar and galactic evolution, cosmology and fundamental physics. Probing the origin of binary black hole mergers will be difficult due to the expected lack of electromagnetic emission and limited localization accuracy. Associations with rare host galaxy types-such as active galactic nuclei-can nevertheless be identified statistically through spatial correlation. Here we establish the feasibility of statistically proving the connection between binary black hole mergers and active galactic nuclei as hosts, even if only a sub-population of mergers originate from active galactic nuclei. Our results are the demonstration that the limited localization of gravitational waves, previously written off as not useful to distinguish progenitor channels, can in fact contribute key information, broadening the range of astrophysical questions probed by binary black hole observations.Binary black hole mergers have recently been observed through the detection of gravitational wave signatures. The authors demonstrate that their association with active galactic nuclei can be made through a statistical spatial correlation.

Structuring Stokes correlation functions using vector-vortex beam

NASA Astrophysics Data System (ADS)

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

2018-01-01

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

Evaluating Multipollutant Exposure and Urban Air Quality: Pollutant Interrelationships, Neighborhood Variability, and Nitrogen Dioxide as a Proxy Pollutant

PubMed Central

Levy, Ilan; Mihele, Cristian; Lu, Gang; Narayan, Julie; Brook, Jeffrey R.

2013-01-01

Background: Although urban air pollution is a complex mix containing multiple constituents, studies of the health effects of long-term exposure often focus on a single pollutant as a proxy for the entire mixture. A better understanding of the component pollutant concentrations and interrelationships would be useful in epidemiological studies that exploit spatial differences in exposure by clarifying the extent to which measures of individual pollutants, particularly nitrogen dioxide (NO2), represent spatial patterns in the multipollutant mixture. Objectives: We examined air pollutant concentrations and interrelationships at the intraurban scale to obtain insight into the nature of the urban mixture of air pollutants. Methods: Mobile measurements of 23 air pollutants were taken systematically at high resolution in Montreal, Quebec, Canada, over 34 days in the winter, summer, and autumn of 2009. Results: We observed variability in pollution levels and in the statistical correlations between different pollutants according to season and neighborhood. Nitrogen oxide species (nitric oxide, NO2, nitrogen oxides, and total oxidized nitrogen species) had the highest overall spatial correlations with the suite of pollutants measured. Ultrafine particles and hydrocarbon-like organic aerosol concentration, a derived measure used as a specific indicator of traffic particles, also had very high correlations. Conclusions: Our findings indicate that the multipollutant mix varies considerably throughout the city, both in time and in space, and thus, no single pollutant would be a perfect proxy measure for the entire mix under all circumstances. However, based on overall average spatial correlations with the suite of pollutants measured, nitrogen oxide species appeared to be the best available indicators of spatial variation in exposure to the outdoor urban air pollutant mixture. Citation: Levy I, Mihele C, Lu G, Narayan J, Brook JR. 2014. Evaluating multipollutant exposure and urban air quality: pollutant interrelationships, neighborhood variability, and nitrogen dioxide as a proxy pollutant. Environ Health Perspect 122:65–72; http://dx.doi.org/10.1289/ehp.1306518 PMID:24225648

PROBING THE IONIZATION STATES OF POLYCYCLIC AROMATIC HYDROCARBONS VIA THE 15–20 μm EMISSION BANDS

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

Shannon, M. J.; Stock, D. J.; Peeters, E., E-mail: mshann3@uwo.ca

2015-10-01

We report new correlations between ratios of band intensities of the 15–20 μm emission bands of polycyclic aromatic hydrocarbons (PAHs) in a sample of 57 sources observed with the Spitzer/Infrared Spectrograph. This sample includes Large Magellanic Cloud point sources from the SAGE-Spec survey, nearby galaxies from the Spitzer Infrared Nearby Galaxies Survey survey, two Galactic interstellar medium cirrus sources, and the spectral maps of the Galactic reflection nebulae NGC 2023 and NGC 7023. We find that the 16.4, 17.4, and 17.8 μm band intensities are inter-correlated in all environments. In NGC 2023 and NGC 7023 these bands also correlate withmore » the 11.0 and 12.7 μm band intensities. The 15.8 μm band correlates only with the 15–18 μm plateau and the 11.2 μm emission. We examine the spatial morphology of these bands and introduce radial cuts. We find that these bands can be spatially organized into three sets: the 12.7, 16.4, and 17.8 μm bands; the 11.2, 15.8 μm bands and the 15–18 μm plateau; and the 11.0 and 17.4 μm bands. We also find that the spatial distribution of the 12.7, 16.4, and 17.8 μm bands can be reconstructed by averaging the spatial distributions of the cationic 11.0 μm and neutral 11.2 μm bands. We conclude that the 17.4 μm band is dominated by cations, the 15.8 μm band by neutral species, and the 12.7, 16.4, and 17.8 μm bands by a combination of the two. These results highlight the importance of PAH ionization for spatially differentiating sub-populations by their 15–20 μm emission variability.« less

Spatial correlation in precipitation trends in the Brazilian Amazon

NASA Astrophysics Data System (ADS)

Buarque, Diogo Costa; Clarke, Robin T.; Mendes, Carlos Andre Bulhoes

2010-06-01

A geostatistical analysis of variables derived from Amazon daily precipitation records (trends in annual precipitation totals, trends in annual maximum precipitation accumulated over 1-5 days, trend in length of dry spell, trend in number of wet days per year) gave results that are consistent with those previously reported. Averaged over the Brazilian Amazon region as a whole, trends in annual maximum precipitations were slightly negative, the trend in the length of dry spell was slightly positive, and the trend in the number of wet days in the year was slightly negative. For trends in annual maximum precipitation accumulated over 1-5 days, spatial correlation between trends was found to extend up to a distance equivalent to at least half a degree of latitude or longitude, with some evidence of anisotropic correlation. Time trends in annual precipitation were found to be spatially correlated up to at least ten degrees of separation, in both W-E and S-N directions. Anisotropic spatial correlation was strongly evident in time trends in length of dry spell with much stronger evidence of spatial correlation in the W-E direction, extending up to at least five degrees of separation, than in the S-N. Because the time trends analyzed are shown to be spatially correlated, it is argued that methods at present widely used to test the statistical significance of climate trends over time lead to erroneous conclusions if spatial correlation is ignored, because records from different sites are assumed to be statistically independent.

Bent dark soliton dynamics in two spatial dimensions beyond the mean field approximation

NASA Astrophysics Data System (ADS)

Mistakidis, Simeon; Katsimiga, Garyfallia; Koutentakis, Georgios; Kevrekidis, Panagiotis; Schmelcher, Peter; Theory Group of Fundamental Processes in Quantum Physics Team

2017-04-01

The dynamics of a bented dark soliton embedded in two spatial dimensions beyond the mean-field approximation is explored. We examine the case of a single bented dark soliton comparing the mean-field approximation to a correlated approach that involves multiple orbitals. Fragmentation is generally present and significantly affects the dynamics, especially in the case of stronger interparticle interactions and in that of lower atom numbers. It is shown that the presence of fragmentation allows for the appearance of solitonic and vortex structures in the higher-orbital dynamics. In particular, a variety of excitations including dark solitons in multiple orbitals and vortex-antidark complexes is observed to arise spontaneously within the beyond mean-field dynamics. Deutsche Forschungsgemeinschaft (DFG) in the framework of the SFB 925 ``Light induced dynamics and control of correlated quantum systems''.

Reporting Recommended Patch Density from Vehicle Panel Vibration Convergence Studies using both DAF and TBL Fits of the Spatial Correlation Function

NASA Technical Reports Server (NTRS)

Smith, Andrew M.; Davis, Robert Ben; LaVerde, Bruce T.; Jones, Douglas C.; Band, Jonathon L.

2012-01-01

Using the patch method to represent the continuous spatial correlation function of a phased pressure field over a structural surface is an approximation. The approximation approaches the continuous function as patches become smaller. Plotting comparisons of the approximation vs the continuous function may provide insight revealing: (1) For what patch size/density should the approximation be very good? (2) What the approximation looks like when it begins to break down? (3) What the approximation looks like when the patch size is grossly too large. Following these observations with a convergence study using one FEM may allow us to see the importance of patch density. We may develop insights that help us to predict sufficient patch density to provide adequate convergence for the intended purpose frequency range of interest

[Features of brain biopotentials' spatial organization in adolescents].

PubMed

Kruchinina, O V; Gal'perina, E I; Shepoval'nikov, A N

2014-01-01

Adolescence is characterized by an intensive formation of inter-regional cortical fields interaction, in this period significantly reorganized the activities of deep brain structures and cortical-subcortical interaction are enhanced. Our objectives were to evaluate the nature of changes in the spatial organization of brain bioelectric potentials with age and characteristics of such an organization in adolescents. For this purpose, EEG studies have been conducted in 230 subjects of both sexes aged 4 to 35 years. We estimated interdependent changes of biopotentials correlations fluctuations in 20-lead EEG, using the integral index Vol. Analyzed age-related changes of EEG correlations in rest condition and during verbal activity (Russian and English texts audition). Verbal tasks were sued in subjects over 8 years. It was found that the spatial synchronization of the EEG both in background and verbal activity increases with age, but after 20 years the rate of change is significantly reduced. In adolescence (12-17 years old), sex differences appear between the degree of EEG coherence processes occurring in the left and right hemispheres in subjects performing verbal tasks. In males 12 to 14 years nonlinear changes in overall correlation (indicators VOL) was observed, whereas in females of this age systemic reorganization of the brain interrelations occurs more smoothly, ahead of 1.5-2 years.

Beta Oscillatory Dynamics in the Prefrontal and Superior Temporal Cortices Predict Spatial Working Memory Performance.

PubMed

Proskovec, Amy L; Wiesman, Alex I; Heinrichs-Graham, Elizabeth; Wilson, Tony W

2018-05-31

The oscillatory dynamics serving spatial working memory (SWM), and how such dynamics relate to performance, are poorly understood. To address these topics, the present study recruited 22 healthy adults to perform a SWM task during magnetoencephalography (MEG). The resulting MEG data were transformed into the time-frequency domain, and significant oscillatory responses were imaged using a beamformer. Voxel time series data were extracted from the cluster peaks to quantify the dynamics, while whole-brain partial correlation maps were computed to identify regions where oscillatory strength varied with accuracy on the SWM task. The results indicated transient theta oscillations in spatially distinct subregions of the prefrontal cortices at the onset of encoding and maintenance, which may underlie selection of goal-relevant information. Additionally, strong and persistent decreases in alpha and beta oscillations were observed throughout encoding and maintenance in parietal, temporal, and occipital regions, which could serve sustained attention and maintenance processes during SWM performance. The neuro-behavioral correlations revealed that beta activity within left dorsolateral prefrontal control regions and bilateral superior temporal integration regions was negatively correlated with SWM accuracy. Notably, this is the first study to employ a whole-brain approach to significantly link neural oscillations to behavioral performance in the context of SWM.

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

NASA Astrophysics Data System (ADS)

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

2018-05-01

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

Spatial characteristics of observed precipitation fields: A catalog of summer storms in Arizona, Volume 2

NASA Technical Reports Server (NTRS)

Fennessey, N. M.; Eagleson, P. S.; Qinliang, W.; Rodriguez-Iturbe, I.

1986-01-01

The parameters of the conceptual model are evaluated from the analysis of eight years of summer rainstorm data from the dense raingage network in the Walnut Gulch catchment near Tucson, Arizona. The occurrence of measurable rain at any one of the 93 gages during a noon to noon day defined a storm. The total rainfall at each of the gages during a storm day constituted the data set for a single storm. The data are interpolated onto a fine grid and analyzed to obtain: an isohyetal plot at 2 mm intervals, the first three moments of point storm depth, the spatial correlation function, the spatial variance function, and the spatial distribution of the total storm depth. The description of the data analysis and the computer programs necessary to read the associated data tapes are presented.

Memory Influences on Hippocampal and Striatal Neural Codes: Effects of a Shift Between Task Rules

PubMed Central

Yeshenko, Oxana; Mizumori, Sheri J.Y.

2007-01-01

Interactions with neocortical memory systems may facilitate flexible information processing by hippocampus. We sought direct evidence for such memory influences by recording hippocampal neural responses to a change in cognitive strategy. Well trained rats switched (within a single recording session) between the use of place and response strategies to solve a plus maze task. Maze and extramaze environments were constant throughout testing. Place fields demonstrated (in-field) firing rate and location based reorganization (Leutgeb, Leutgeb, Barnes, Moser, McNaughton, & Moser, 2005) after a task switch, suggesting that hippocampus encoded each phase of testing as a different context, or episode. The task switch also resulted in qualitative and quantitative changes to discharge that were correlated with an animal's velocity or acceleration of movement. Thus, the effects of a strategy switch extended beyond the spatial domain, and the movement correlates were not passive reflections of the current behavioral state. To determine whether hippocampal neural responses were unique, striatal place and movement-correlated neurons were simultaneously recorded with hippocampal neurons. Striatal place and movement cells exhibited a response profile that was similar, but not identical, to that observed for hippocampus after a strategy switch. Thus, retrieval of a different memory led both neural systems to represent a different context. However, hippocampus may play a special (though not exclusive) role in flexible spatial processing since correlated firing amongst cell pairs was highest when rats successfully switched between two spatial tasks. Correlated firing by striatal cell pairs increased following any strategy switch, supporting the view that striatum codes changes in reinforcement contingencies. PMID:17240173

Spatiotemporal Context Awareness for Urban Traffic Modeling and Prediction: Sparse Representation Based Variable Selection.

PubMed

Yang, Su; Shi, Shixiong; Hu, Xiaobing; Wang, Minjie

2015-01-01

Spatial-temporal correlations among the data play an important role in traffic flow prediction. Correspondingly, traffic modeling and prediction based on big data analytics emerges due to the city-scale interactions among traffic flows. A new methodology based on sparse representation is proposed to reveal the spatial-temporal dependencies among traffic flows so as to simplify the correlations among traffic data for the prediction task at a given sensor. Three important findings are observed in the experiments: (1) Only traffic flows immediately prior to the present time affect the formation of current traffic flows, which implies the possibility to reduce the traditional high-order predictors into an 1-order model. (2) The spatial context relevant to a given prediction task is more complex than what is assumed to exist locally and can spread out to the whole city. (3) The spatial context varies with the target sensor undergoing prediction and enlarges with the increment of time lag for prediction. Because the scope of human mobility is subject to travel time, identifying the varying spatial context against time lag is crucial for prediction. Since sparse representation can capture the varying spatial context to adapt to the prediction task, it outperforms the traditional methods the inputs of which are confined as the data from a fixed number of nearby sensors. As the spatial-temporal context for any prediction task is fully detected from the traffic data in an automated manner, where no additional information regarding network topology is needed, it has good scalability to be applicable to large-scale networks.

Spatiotemporal Context Awareness for Urban Traffic Modeling and Prediction: Sparse Representation Based Variable Selection

PubMed Central

Yang, Su; Shi, Shixiong; Hu, Xiaobing; Wang, Minjie

2015-01-01

Spatial-temporal correlations among the data play an important role in traffic flow prediction. Correspondingly, traffic modeling and prediction based on big data analytics emerges due to the city-scale interactions among traffic flows. A new methodology based on sparse representation is proposed to reveal the spatial-temporal dependencies among traffic flows so as to simplify the correlations among traffic data for the prediction task at a given sensor. Three important findings are observed in the experiments: (1) Only traffic flows immediately prior to the present time affect the formation of current traffic flows, which implies the possibility to reduce the traditional high-order predictors into an 1-order model. (2) The spatial context relevant to a given prediction task is more complex than what is assumed to exist locally and can spread out to the whole city. (3) The spatial context varies with the target sensor undergoing prediction and enlarges with the increment of time lag for prediction. Because the scope of human mobility is subject to travel time, identifying the varying spatial context against time lag is crucial for prediction. Since sparse representation can capture the varying spatial context to adapt to the prediction task, it outperforms the traditional methods the inputs of which are confined as the data from a fixed number of nearby sensors. As the spatial-temporal context for any prediction task is fully detected from the traffic data in an automated manner, where no additional information regarding network topology is needed, it has good scalability to be applicable to large-scale networks. PMID:26496370

On hierarchical solutions to the BBGKY hierarchy

NASA Technical Reports Server (NTRS)

Hamilton, A. J. S.

1988-01-01

It is thought that the gravitational clustering of galaxies in the universe may approach a scale-invariant, hierarchical form in the small separation, large-clustering regime. Past attempts to solve the Born-Bogoliubov-Green-Kirkwood-Yvon (BBGKY) hierarchy in this regime have assumed a certain separable hierarchical form for the higher order correlation functions of galaxies in phase space. It is shown here that such separable solutions to the BBGKY equations must satisfy the condition that the clustered component of the solution has cluster-cluster correlations equal to galaxy-galaxy correlations to all orders. The solutions also admit the presence of an arbitrary unclustered component, which plays no dyamical role in the large-clustering regime. These results are a particular property of the specific separable model assumed for the correlation functions in phase space, not an intrinsic property of spatially hierarchical solutions to the BBGKY hierarchy. The observed distribution of galaxies does not satisfy the required conditions. The disagreement between theory and observation may be traced, at least in part, to initial conditions which, if Gaussian, already have cluster correlations greater than galaxy correlations.

Spring green-up date derived from GIMMS3g and SPOT-VGT NDVI of winter wheat cropland in the North China Plain

NASA Astrophysics Data System (ADS)

Liu, Zhengjia; Wu, Chaoyang; Liu, Yansui; Wang, Xiaoyue; Fang, Bin; Yuan, Wenping; Ge, Quansheng

2017-08-01

Satellite temporal resolution affects the fitting accuracy of vegetation growth curves. However, there are few studies that evaluate the impact of different satellite data (including temporal resolution and time series change) on spring green-up date (GUD) extraction. In this study, four GUD algorithms and two different temporal resolution satellite data (GIMMS3g during 1982-2013 and SPOT-VGT during 1999-2013) were used to investigate winter wheat GUD in the North China Plain. Four GUD algorithms included logistic-NDVI (normalized difference vegetation index), logistic-cumNDVI (cumulative NDVI), polynomial-NDVI and polynomial-cumNDVI algorithms. All algorithms and data were first regrouped into eight controlled cases. At site scale, we evaluated the performance of each case using correlation coefficient (r), bias and root mean square error (RMSE). We further compared spatial patterns and inter-annual trends of GUD inferred from different algorithms, and then analyzed the difference between GIMMS3g-based GUD and SPOT-VGT-based GUD. Our results showed that all satellite-based GUD were correlated with observations with r ranging from 0.32 to 0.57 (p < 0.01). SPOT-VGT-based GUD generally had better correlations with observed GUD than those of GIMMS3g. Spatially, SPOT-VGT-based GUD performed more reasonable spatial distributions. Inter-annual regional averaged satellite-based GUD presented overall advanced trends during 1982-2013 (0.3-2.0 days/decade) while delayed trends were observed during 1999-2013 (1.7-7.4 days/decade for GIMMS3g and 3.8-7.4 days/decade for SPOT-VGT). However, their significance levels were highly dependent on the data and algorithms used. Our findings suggest cautions on previous results of inter-annual variability of phenology from a single data/method.

Parameter estimation for a cohesive sediment transport model by assimilating satellite observations in the Hangzhou Bay: Temporal variations and spatial distributions

NASA Astrophysics Data System (ADS)

Wang, Daosheng; Zhang, Jicai; He, Xianqiang; Chu, Dongdong; Lv, Xianqing; Wang, Ya Ping; Yang, Yang; Fan, Daidu; Gao, Shu

2018-01-01

Model parameters in the suspended cohesive sediment transport models are critical for the accurate simulation of suspended sediment concentrations (SSCs). Difficulties in estimating the model parameters still prevent numerical modeling of the sediment transport from achieving a high level of predictability. Based on a three-dimensional cohesive sediment transport model and its adjoint model, the satellite remote sensing data of SSCs during both spring tide and neap tide, retrieved from Geostationary Ocean Color Imager (GOCI), are assimilated to synchronously estimate four spatially and temporally varying parameters in the Hangzhou Bay in China, including settling velocity, resuspension rate, inflow open boundary conditions and initial conditions. After data assimilation, the model performance is significantly improved. Through several sensitivity experiments, the spatial and temporal variation tendencies of the estimated model parameters are verified to be robust and not affected by model settings. The pattern for the variations of the estimated parameters is analyzed and summarized. The temporal variations and spatial distributions of the estimated settling velocity are negatively correlated with current speed, which can be explained using the combination of flocculation process and Stokes' law. The temporal variations and spatial distributions of the estimated resuspension rate are also negatively correlated with current speed, which are related to the grain size of the seabed sediments under different current velocities. Besides, the estimated inflow open boundary conditions reach the local maximum values near the low water slack conditions and the estimated initial conditions are negatively correlated with water depth, which is consistent with the general understanding. The relationships between the estimated parameters and the hydrodynamic fields can be suggestive for improving the parameterization in cohesive sediment transport models.

Grid cell spatial tuning reduced following systemic muscarinic receptor blockade

PubMed Central

Newman, Ehren L.; Climer, Jason R.; Hasselmo, Michael E.

2014-01-01

Grid cells of the medial entorhinal cortex exhibit a periodic and stable pattern of spatial tuning that may reflect the output of a path integration system. This grid pattern has been hypothesized to serve as a spatial coordinate system for navigation and memory function. The mechanisms underlying the generation of this characteristic tuning pattern remain poorly understood. Systemic administration of the muscarinic antagonist scopolamine flattens the typically positive correlation between running speed and entorhinal theta frequency in rats. The loss of this neural correlate of velocity, an important signal for the calculation of path integration, raises the question of what influence scopolamine has on the grid cell tuning as a read out of the path integration system. To test this, the spatial tuning properties of grid cells were compared before and after systemic administration of scopolamine as rats completed laps on a circle track for food rewards. The results show that the spatial tuning of the grid cells was reduced following scopolamine administration. The tuning of head direction cells, in contrast, was not reduced by scopolamine. This is the first report to demonstrate a link between cholinergic function and grid cell tuning. This work suggests that the loss of tuning in the grid cell network may underlie the navigational disorientation observed in Alzheimer's patients and elderly individuals with reduced cholinergic tone. PMID:24493379

Emergence of increased frequency and severity of multiple infections by viruses due to spatial clustering of hosts

NASA Astrophysics Data System (ADS)

Taylor, Bradford P.; Penington, Catherine J.; Weitz, Joshua S.

2016-12-01

Multiple virus particles can infect a target host cell. Such multiple infections (MIs) have significant and varied ecological and evolutionary consequences for both virus and host populations. Yet, the in situ rates and drivers of MIs in virus-microbe systems remain largely unknown. Here, we develop an individual-based model (IBM) of virus-microbe dynamics to probe how spatial interactions drive the frequency and nature of MIs. In our IBMs, we identify increasingly spatially correlated clusters of viruses given sufficient decreases in viral movement. We also identify increasingly spatially correlated clusters of viruses and clusters of hosts given sufficient increases in viral infectivity. The emergence of clusters is associated with an increase in multiply infected hosts as compared to expectations from an analogous mean field model. We also observe long-tails in the distribution of the multiplicity of infection in contrast to mean field expectations that such events are exponentially rare. We show that increases in both the frequency and severity of MIs occur when viruses invade a cluster of uninfected microbes. We contend that population-scale enhancement of MI arises from an aggregate of invasion dynamics over a distribution of microbe cluster sizes. Our work highlights the need to consider spatially explicit interactions as a potentially key driver underlying the ecology and evolution of virus-microbe communities.

Performance on a virtual reality angled laparoscope task correlates with spatial ability of trainees.

PubMed

Rosenthal, Rachel; Hamel, Christian; Oertli, Daniel; Demartines, Nicolas; Gantert, Walter A

2010-08-01

The aim of the present study was to investigate whether trainees' performance on a virtual reality angled laparoscope navigation task correlates with scores obtained on a validated conventional test of spatial ability. 56 participants of a surgery workshop performed an angled laparoscope navigation task on the Xitact LS 500 virtual reality Simulator. Performance parameters were correlated with the score of a validated paper-and-pencil test of spatial ability. Performance at the conventional spatial ability test significantly correlated with performance at the virtual reality task for overall task score (p < 0.001), task completion time (p < 0.001) and economy of movement (p = 0.035), not for endoscope travel speed (p = 0.947). In conclusion, trainees' performance in a standardized virtual reality camera navigation task correlates with their innate spatial ability. This VR session holds potential to serve as an assessment tool for trainees.

The power spectrum of solar convection flows from high-resolution observations and 3D simulations

NASA Astrophysics Data System (ADS)

Yelles Chaouche, L.; Moreno-Insertis, F.; Bonet, J. A.

2014-03-01

Context. Understanding solar surface magnetoconvection requires the study of the Fourier spectra of the velocity fields. Nowadays, observations are available that resolve very small spatial scales, well into the subgranular range, almost reaching the scales routinely resolved in numerical magnetoconvection simulations. Comparison of numerical and observational data at present can provide an assessment of the validity of the observational proxies. Aims: Our aims are: (1) to obtain Fourier spectra for the photospheric velocity fields using the spectropolarimetric observations with the highest spatial resolution so far (~120 km), thus reaching for the first time spatial scales well into the subgranular range; (2) to calculate corresponding Fourier spectra from realistic 3D numerical simulations of magnetoconvection and carry out a proper comparison with their observational counterparts considering the residual instrumental degradation in the observational data; and (3) to test the observational proxies on the basis of the numerical data alone, by comparing the actual velocity field in the simulations with synthetic observations obtained from the numerical boxes. Methods: (a) For the observations, data from the SUNRISE/IMaX spectropolarimeter are used. (b) For the simulations, we use four series of runs obtained with the STAGGER code for different average signed vertical magnetic field values (0, 50, 100, and 200 G). Spectral line profiles are synthesized from the numerical boxes for the same line observed by IMaX (Fe I 5250.2 Å) and degraded to match the performance of the IMaX instrument. Proxies for the velocity field are obtained via Dopplergrams (vertical component) and local correlation tracking (LCT, for the horizontal component). Fourier power spectra are calculated and a comparison between the synthetic and observational data sets carried out. (c) For the internal comparison of the numerical data, velocity values on constant optical depth surfaces are used instead of on horizontal planes. Results: A very good match between observational and simulated Fourier power spectra is obtained for the vertical velocity data for scales between 200 km and 6 Mm. Instead, a clear vertical shift is obtained when the synthetic observations are not degraded to emulate the degradation in the IMaX data. The match for the horizontal velocity data is much less impressive because of the inaccuracies of the LCT procedure. Concerning the internal comparison of the direct velocity values of the numerical boxes with those from the synthetic observations, a high correlation (0.96) is obtained for the vertical component when using the velocity values on the log τ500 = -1 surface in the box. The corresponding Fourier spectra are near each other. A lower maximum correlation (0.5) is reached (at log τ500 = 0) for the horizontal velocities as a result of the coarseness of the LCT procedure. Correspondingly, the Fourier spectra for the LCT-determined velocities is well below that from the actual velocity components. Conclusions: As measured by the Fourier spectra, realistic numerical simulations of surface magnetoconvection provide a very good match to the observational proxies for the photospheric velocity fields at least on scales from several Mm down to around 200 km. Taking into account the spatial and spectral instrumental blurring is essential for the comparison between simulations and observations. Dopplergrams are an excellent proxy for the vertical velocities on constant-τ isosurfaces, while LCT is a much less reliable method of determining the horizontal velocities.

Spatial patterns and climate drivers of carbon fluxes in terrestrial ecosystems of China.

PubMed

Yu, Gui-Rui; Zhu, Xian-Jin; Fu, Yu-Ling; He, Hong-Lin; Wang, Qiu-Feng; Wen, Xue-Fa; Li, Xuan-Ran; Zhang, Lei-Ming; Zhang, Li; Su, Wen; Li, Sheng-Gong; Sun, Xiao-Min; Zhang, Yi-Ping; Zhang, Jun-Hui; Yan, Jun-Hua; Wang, Hui-Min; Zhou, Guang-Sheng; Jia, Bing-Rui; Xiang, Wen-Hua; Li, Ying-Nian; Zhao, Liang; Wang, Yan-Fen; Shi, Pei-Li; Chen, Shi-Ping; Xin, Xiao-Ping; Zhao, Feng-Hua; Wang, Yu-Ying; Tong, Cheng-Li

2013-03-01

Understanding the dynamics and underlying mechanism of carbon exchange between terrestrial ecosystems and the atmosphere is one of the key issues in global change research. In this study, we quantified the carbon fluxes in different terrestrial ecosystems in China, and analyzed their spatial variation and environmental drivers based on the long-term observation data of ChinaFLUX sites and the published data from other flux sites in China. The results indicate that gross ecosystem productivity (GEP), ecosystem respiration (ER), and net ecosystem productivity (NEP) of terrestrial ecosystems in China showed a significantly latitudinal pattern, declining linearly with the increase of latitude. However, GEP, ER, and NEP did not present a clear longitudinal pattern. The carbon sink functional areas of terrestrial ecosystems in China were mainly located in the subtropical and temperate forests, coastal wetlands in eastern China, the temperate meadow steppe in the northeast China, and the alpine meadow in eastern edge of Qinghai-Tibetan Plateau. The forest ecosystems had stronger carbon sink than grassland ecosystems. The spatial patterns of GEP and ER in China were mainly determined by mean annual precipitation (MAP) and mean annual temperature (MAT), whereas the spatial variation in NEP was largely explained by MAT. The combined effects of MAT and MAP explained 79%, 62%, and 66% of the spatial variations in GEP, ER, and NEP, respectively. The GEP, ER, and NEP in different ecosystems in China exhibited 'positive coupling correlation' in their spatial patterns. Both ER and NEP were significantly correlated with GEP, with 68% of the per-unit GEP contributed to ER and 29% to NEP. MAT and MAP affected the spatial patterns of ER and NEP mainly by their direct effects on the spatial pattern of GEP. © 2012 Blackwell Publishing Ltd.

Sampling design for spatially distributed hydrogeologic and environmental processes

USGS Publications Warehouse

Christakos, G.; Olea, R.A.

1992-01-01

A methodology for the design of sampling networks over space is proposed. The methodology is based on spatial random field representations of nonhomogeneous natural processes, and on optimal spatial estimation techniques. One of the most important results of random field theory for physical sciences is its rationalization of correlations in spatial variability of natural processes. This correlation is extremely important both for interpreting spatially distributed observations and for predictive performance. The extent of site sampling and the types of data to be collected will depend on the relationship of subsurface variability to predictive uncertainty. While hypothesis formulation and initial identification of spatial variability characteristics are based on scientific understanding (such as knowledge of the physics of the underlying phenomena, geological interpretations, intuition and experience), the support offered by field data is statistically modelled. This model is not limited by the geometric nature of sampling and covers a wide range in subsurface uncertainties. A factorization scheme of the sampling error variance is derived, which possesses certain atttactive properties allowing significant savings in computations. By means of this scheme, a practical sampling design procedure providing suitable indices of the sampling error variance is established. These indices can be used by way of multiobjective decision criteria to obtain the best sampling strategy. Neither the actual implementation of the in-situ sampling nor the solution of the large spatial estimation systems of equations are necessary. The required values of the accuracy parameters involved in the network design are derived using reference charts (readily available for various combinations of data configurations and spatial variability parameters) and certain simple yet accurate analytical formulas. Insight is gained by applying the proposed sampling procedure to realistic examples related to sampling problems in two dimensions. ?? 1992.

Teacher spatial skills are linked to differences in geometry instruction.

PubMed

Otumfuor, Beryl Ann; Carr, Martha

2017-12-01

Spatial skills have been linked to better performance in mathematics. The purpose of this study was to examine the relationship between teacher spatial skills and their instruction, including teacher content and pedagogical knowledge, use of pictorial representations, and use of gestures during geometry instruction. Fifty-six middle school teachers participated in the study. The teachers were administered spatial measures of mental rotations and spatial visualization. Next, a single geometry class was videotaped. Correlational analyses revealed that spatial skills significantly correlate with teacher's use of representational gestures and content and pedagogical knowledge during instruction of geometry. Spatial skills did not independently correlate with the use of pointing gestures or the use of pictorial representations. However, an interaction term between spatial skills and content and pedagogical knowledge did correlate significantly with the use of pictorial representations. Teacher experience as measured by the number of years of teaching and highest degree did not appear to affect the relationships among the variables with the exception of the relationship between spatial skills and teacher content and pedagogical knowledge. Teachers with better spatial skills are also likely to use representational gestures and to show better content and pedagogical knowledge during instruction. Spatial skills predict pictorial representation use only as a function of content and pedagogical knowledge. © 2017 The British Psychological Society.

The Non-Gaussian Nature of Prostate Motion Based on Real-Time Intrafraction Tracking

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

Lin, Yuting; Liu, Tian; Yang, Wells

2013-10-01

Purpose: The objective of this work is to test the validity of the Gaussian approximation for prostate motion through characterization of its spatial distribution. Methods and Materials: Real-time intrafraction prostate motion was observed using Calypso 4-dimensional (4D) nonradioactive electromagnetic tracking system. We report the results from a total of 1024 fractions from 31 prostate cancer patients. First, the correlation of prostate motion in right/left (RL), anteroposterior (AP), and superoinferior (SI) direction were determined using Pearson's correlation of coefficient. Then the spatial distribution of prostate motion was analyzed for individual fraction, individual patient including all fractions, and all patients including allmore » fractions. The displacement in RL, AP, SI, oblique, or total direction is fitted into a Gaussian distribution, and a Lilliefors test was used to evaluate the validity of the hypothesis that the displacement is normally distributed. Results: There is high correlation in AP/SI direction (61% of fractions with medium or strong correlation). This is consistent with the longitudinal oblique motion of the prostate, and likely the effect from respiration on an organ confined within the genitourinary diaphragm with the rectum sitting posteriorly and bladder sitting superiorly. In all directions, the non-Gaussian distribution is more common for individual fraction, individual patient including all fractions, and all patients including all fractions. The spatial distribution of prostate motion shows an elongated shape in oblique direction, indicating a higher range of motion in the AP and SI directions. Conclusions: Our results showed that the prostate motion is highly correlated in AP and SI direction, indicating an oblique motion preference. In addition, the spatial distribution of prostate motion is elongated in an oblique direction, indicating that the organ motion dosimetric modeling using Gaussian kernel may need to be modified to account for the particular organ motion character of prostate.« less

The non-Gaussian nature of prostate motion based on real-time intrafraction tracking.

PubMed

Lin, Yuting; Liu, Tian; Yang, Wells; Yang, Xiaofeng; Khan, Mohammad K

2013-10-01

The objective of this work is to test the validity of the Gaussian approximation for prostate motion through characterization of its spatial distribution. Real-time intrafraction prostate motion was observed using Calypso 4-dimensional (4D) nonradioactive electromagnetic tracking system. We report the results from a total of 1024 fractions from 31 prostate cancer patients. First, the correlation of prostate motion in right/left (RL), anteroposterior (AP), and superoinferior (SI) direction were determined using Pearson's correlation of coefficient. Then the spatial distribution of prostate motion was analyzed for individual fraction, individual patient including all fractions, and all patients including all fractions. The displacement in RL, AP, SI, oblique, or total direction is fitted into a Gaussian distribution, and a Lilliefors test was used to evaluate the validity of the hypothesis that the displacement is normally distributed. There is high correlation in AP/SI direction (61% of fractions with medium or strong correlation). This is consistent with the longitudinal oblique motion of the prostate, and likely the effect from respiration on an organ confined within the genitourinary diaphragm with the rectum sitting posteriorly and bladder sitting superiorly. In all directions, the non-Gaussian distribution is more common for individual fraction, individual patient including all fractions, and all patients including all fractions. The spatial distribution of prostate motion shows an elongated shape in oblique direction, indicating a higher range of motion in the AP and SI directions. Our results showed that the prostate motion is highly correlated in AP and SI direction, indicating an oblique motion preference. In addition, the spatial distribution of prostate motion is elongated in an oblique direction, indicating that the organ motion dosimetric modeling using Gaussian kernel may need to be modified to account for the particular organ motion character of prostate. Copyright © 2013 Elsevier Inc. All rights reserved.

Species composition and morphologic variation of Porites in the Gulf of California

NASA Astrophysics Data System (ADS)

López-Pérez, R. A.

2013-09-01

Morphometric analysis of corallite calices confirmed that from the late Miocene to the Recent, four species of Porites have inhabited the Gulf of California: the extinct Porites carrizensis, the locally extirpated Porites lobata and the extant Porites sverdrupi and Porites panamensis. Furthermore, large-scale spatial and temporal phenotypic plasticity was observed in the dominant species P. panamensis. Canonical discriminant analysis and ANOVA demonstrated that the calice structures of P. panamensis experienced size reduction between the late Pleistocene and Recent. Similarly, PERMANOVA, regression and correlation analyses demonstrated that across the 800 km north to south in the gulf, P. panamensis populations displayed a similar reduction in calice structures. Based on correlation analysis with environmental data, these large spatial changes are likely related to changes in nutrient concentration and sea surface temperature. As such, the large-scale spatial and temporal phenotypic variation recorded in populations of P. panamensis in the Gulf of California is likely related to optimization of corallite performance (energy acquisition) within various environmental scenarios. These findings may have relevance to modern conservation efforts within this ecological dominant genus.

Retrieving accurate temporal and spatial information about Taylor slug flows from non-invasive NIR photometry measurements

NASA Astrophysics Data System (ADS)

Helmers, Thorben; Thöming, Jorg; Mießner, Ulrich

2017-11-01

In this article, we introduce a novel approach to retrieve spatial- and time-resolved Taylor slug flow information from a single non-invasive photometric flow sensor. The presented approach uses disperse phase surface properties to retrieve the instantaneous velocity information from a single sensor's time-scaled signal. For this purpose, a photometric sensor system is simulated using a ray-tracing algorithm to calculate spatially resolved near-infrared transmission signals. At the signal position corresponding to the rear droplet cap, a correlation factor of the droplet's geometric properties is retrieved and used to extract the instantaneous droplet velocity from the real sensor's temporal transmission signal. Furthermore, a correlation for the rear cap geometry based on the a priori known total superficial flow velocity is developed, because the cap curvature is velocity sensitive itself. Our model for velocity derivation is validated, and measurements of a first prototype showcase the capability of the device. Long-term measurements visualize systematic fluctuations in droplet lengths, velocities, and frequencies that could otherwise, without the observation on a larger timescale, have been identified as measurement errors and not systematic phenomenas.

Spatial cognitive deficits in an animal model of Wernicke-Korsakoff syndrome are related to changes in thalamic VDAC protein concentrations.

PubMed

Bueno, K O; de Souza Resende, L; Ribeiro, A F; Dos Santos, D M; Gonçalves, E C; Vigil, F A B; de Oliveira Silva, I F; Ferreira, L F; de Castro Pimenta, A M; Ribeiro, A M

2015-05-21

Proteomic profiles of the thalamus and the correlation between the rats' performance on a spatial learning task and differential protein expression were assessed in the thiamine deficiency (TD) rat model of Wernicke-Korsakoff syndrome. Two-dimensional gel-electrophoresis detected 320 spots and a significant increase or decrease in seven proteins. Four proteins were correlated to rat behavioral performance in the Morris Water Maze. One of the four proteins was identified by mass spectrometry as Voltage-Dependent Anion Channels (VDACs). The association of VDAC is evident in trials in which the rats' performance was worst, in which the VDAC protein was reduced, as confirmed by Western blot. No difference was observed on the mRNA of Vdac genes, indicating that the decreased VDAC expression may be related to a post-transcriptional process. The results show that TD neurodegeneration involves changes in thalamic proteins and suggest that VDAC protein activity might play an important role in an initial stage of the spatial learning process. Copyright © 2015 IBRO. Published by Elsevier Ltd. All rights reserved.

[Spatial point patterns of Antarctic krill fishery in the northern Antarctic Peninsula].

PubMed

Yang, Xiao Ming; Li, Yi Xin; Zhu, Guo Ping

2016-12-01

As a key species in the Antarctic ecosystem, the spatial distribution of Antarctic krill (thereafter krill) often tends to present aggregation characteristics, which therefore reflects the spatial patterns of krill fishing operation. Based on the fishing data collected from Chinese krill fishing vessels, of which vessel A was professional krill fishing vessel and Vessel B was a fishing vessel which shifted between Chilean jack mackerel (Trachurus murphyi) fishing ground and krill fishing ground. In order to explore the characteristics of spatial distribution pattern and their ecological effects of two obvious different fishing fleets under a high and low nominal catch per unit effort (CPUE), from the viewpoint of spatial point pattern, the present study analyzed the spatial distribution characteristics of krill fishery in the northern Antarctic Peninsula from three aspects: (1) the two vessels' point pattern characteristics of higher CPUEs and lower CPUEs at different scales; (2) correlation of the bivariate point patterns between these points of higher CPUE and lower CPUE; and (3) correlation patterns of CPUE. Under the analysis derived from the Ripley's L function and mark correlation function, the results showed that the point patterns of the higher/lo-wer catch available were similar, both showing an aggregation distribution in this study windows at all scale levels. The aggregation intensity of krill fishing was nearly maximum at 15 km spatial scale, and kept stably higher values at the scale of 15-50 km. The aggregation intensity of krill fishery point patterns could be described in order as higher CPUE of vessel A > lower CPUE of vessel B >higher CPUE of vessel B > higher CPUE of vessel B. The relationship of the higher and lo-wer CPUEs of vessel A showed positive correlation at the spatial scale of 0-75 km, and presented stochastic relationship after 75 km scale, whereas vessel B showed positive correlation at all spatial scales. The point events of higher and lower CPUEs were synchronized, showing significant correlations at most of spatial scales because of the dynamics nature and complex of krill aggregation patterns. The distribution of vessel A's CPUEs was positively correlated at scales of 0-44 km, but negatively correlated at the scales of 44-80 km. The distribution of vessel B's CPUEs was negatively correlated at the scales of 50-70 km, but no significant correlations were found at other scales. The CPUE mark point patterns showed a negative correlation, which indicated that intraspecific competition for space and prey was significant. There were significant differences in spatial point pattern distribution between vessel A with higher fishing capacity and vessel B with lower fishing capacity. The results showed that the professional krill fishing vessel is suitable to conduct the analysis of spatial point pattern and scientific fishery survey.

The relationships between spatial ability, logical thinking, mathematics performance and kinematics graph interpretation skills of 12th grade physics students

NASA Astrophysics Data System (ADS)

Bektasli, Behzat

Graphs have a broad use in science classrooms, especially in physics. In physics, kinematics is probably the topic for which graphs are most widely used. The participants in this study were from two different grade-12 physics classrooms, advanced placement and calculus-based physics. The main purpose of this study was to search for the relationships between student spatial ability, logical thinking, mathematical achievement, and kinematics graphs interpretation skills. The Purdue Spatial Visualization Test, the Middle Grades Integrated Process Skills Test (MIPT), and the Test of Understanding Graphs in Kinematics (TUG-K) were used for quantitative data collection. Classroom observations were made to acquire ideas about classroom environment and instructional techniques. Factor analysis, simple linear correlation, multiple linear regression, and descriptive statistics were used to analyze the quantitative data. Each instrument has two principal components. The selection and calculation of the slope and of the area were the two principal components of TUG-K. MIPT was composed of a component based upon processing text and a second component based upon processing symbolic information. The Purdue Spatial Visualization Test was composed of a component based upon one-step processing and a second component based upon two-step processing of information. Student ability to determine the slope in a kinematics graph was significantly correlated with spatial ability, logical thinking, and mathematics aptitude and achievement. However, student ability to determine the area in a kinematics graph was only significantly correlated with student pre-calculus semester 2 grades. Male students performed significantly better than female students on the slope items of TUG-K. Also, male students performed significantly better than female students on the PSAT mathematics assessment and spatial ability. This study found that students have different levels of spatial ability, logical thinking, and mathematics aptitude and achievement levels. These different levels were related to student learning of kinematics and they need to be considered when kinematics is being taught. It might be easier for students to understand the kinematics graphs if curriculum developers include more activities related to spatial ability and logical thinking.

Selecting a separable parametric spatiotemporal covariance structure for longitudinal imaging data.

PubMed

George, Brandon; Aban, Inmaculada

2015-01-15

Longitudinal imaging studies allow great insight into how the structure and function of a subject's internal anatomy changes over time. Unfortunately, the analysis of longitudinal imaging data is complicated by inherent spatial and temporal correlation: the temporal from the repeated measures and the spatial from the outcomes of interest being observed at multiple points in a patient's body. We propose the use of a linear model with a separable parametric spatiotemporal error structure for the analysis of repeated imaging data. The model makes use of spatial (exponential, spherical, and Matérn) and temporal (compound symmetric, autoregressive-1, Toeplitz, and unstructured) parametric correlation functions. A simulation study, inspired by a longitudinal cardiac imaging study on mitral regurgitation patients, compared different information criteria for selecting a particular separable parametric spatiotemporal correlation structure as well as the effects on types I and II error rates for inference on fixed effects when the specified model is incorrect. Information criteria were found to be highly accurate at choosing between separable parametric spatiotemporal correlation structures. Misspecification of the covariance structure was found to have the ability to inflate the type I error or have an overly conservative test size, which corresponded to decreased power. An example with clinical data is given illustrating how the covariance structure procedure can be performed in practice, as well as how covariance structure choice can change inferences about fixed effects. Copyright © 2014 John Wiley & Sons, Ltd.

CORRELATED AND ZONAL ERRORS OF GLOBAL ASTROMETRIC MISSIONS: A SPHERICAL HARMONIC SOLUTION

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

Makarov, V. V.; Dorland, B. N.; Gaume, R. A.

We propose a computer-efficient and accurate method of estimating spatially correlated errors in astrometric positions, parallaxes, and proper motions obtained by space- and ground-based astrometry missions. In our method, the simulated observational equations are set up and solved for the coefficients of scalar and vector spherical harmonics representing the output errors rather than for individual objects in the output catalog. Both accidental and systematic correlated errors of astrometric parameters can be accurately estimated. The method is demonstrated on the example of the JMAPS mission, but can be used for other projects in space astrometry, such as SIM or JASMINE.

Correlated Optical Spectroscopy and Transmission Electron Microscopy of Individual Hollow Nanoparticles and their Dimers

PubMed Central

Yang, Linglu; Yan, Bo; Reinhard, Björn M.

2009-01-01

The optical spectra of individual Ag-Au alloy hollow particles were correlated with the particles’ structures obtained by transmission electron microscopy (TEM). The TEM provided direct experimental access to the dimension of the cavity, thickness of the metal shell, and the interparticle distance of hollow particle dimers with high spatial resolution. The analysis of correlated spectral and structural information enabled the quantification of the influence of the core-shell structure on the resonance energy, plasmon lifetime, and plasmon coupling efficiency. Electron beam exposure during TEM inspection was observed to affect plasmon wavelength and lifetime, making optical inspection prior to structural characterization mandatory. PMID:19768108

Correlated and Zonal Errors of Global Astrometric Missions: A Spherical Harmonic Solution

NASA Astrophysics Data System (ADS)

Makarov, V. V.; Dorland, B. N.; Gaume, R. A.; Hennessy, G. S.; Berghea, C. T.; Dudik, R. P.; Schmitt, H. R.

2012-07-01

We propose a computer-efficient and accurate method of estimating spatially correlated errors in astrometric positions, parallaxes, and proper motions obtained by space- and ground-based astrometry missions. In our method, the simulated observational equations are set up and solved for the coefficients of scalar and vector spherical harmonics representing the output errors rather than for individual objects in the output catalog. Both accidental and systematic correlated errors of astrometric parameters can be accurately estimated. The method is demonstrated on the example of the JMAPS mission, but can be used for other projects in space astrometry, such as SIM or JASMINE.

Failure criterion for materials with spatially correlated mechanical properties

NASA Astrophysics Data System (ADS)

Faillettaz, J.; Or, D.

2015-03-01

The role of spatially correlated mechanical elements in the failure behavior of heterogeneous materials represented by fiber bundle models (FBMs) was evaluated systematically for different load redistribution rules. Increasing the range of spatial correlation for FBMs with local load sharing is marked by a transition from ductilelike failure characteristics into brittlelike failure. The study identified a global failure criterion based on macroscopic properties (external load and cumulative damage) that is independent of spatial correlation or load redistribution rules. This general metric could be applied to assess the mechanical stability of complex and heterogeneous systems and thus provide an important component for early warning of a class of geophysical ruptures.

Preserved and attenuated electrophysiological correlates of visual spatial attention in elderly subjects.

PubMed

van der Waal, Marjolein; Farquhar, Jason; Fasotti, Luciano; Desain, Peter

2017-01-15

Healthy aging is associated with changes in many neurocognitive functions. While on the behavioral level, visual spatial attention capacities are relatively stable with increasing age, the underlying neural processes change. In this study, we investigated attention-related modulations of the stimulus-locked event-related potential (ERP) and occipital oscillations in the alpha band (8-14Hz) in young and elderly participants. Both groups performed a visual attention task equally well and the ERP showed comparable attention-related modulations in both age groups. However, in elderly subjects, oscillations in the alpha band were massively reduced both during the task and in the resting state and the typical task-related lateralized pattern of alpha activity was not observed. These differences between young and elderly participants were observed on the group level as well as on the single trial level. The results indicate that younger and older adults use different neural strategies to reach the same performance in a covert visual spatial attention task. Copyright © 2016 Elsevier B.V. All rights reserved.

Spatial trends in tidal flat shape and associated environmental parameters in South San Francisco Bay

USGS Publications Warehouse

Bearman, J.A.; Friedrichs, Carl T.; Jaffe, B.E.; Foxgrover, A.C.

2010-01-01

Spatial trends in the shape of profiles of South San Francisco Bay (SSFB) tidal flats are examined using bathymetric and lidar data collected in 2004 and 2005. Eigenfunction analysis reveals a dominant mode of morphologic variability related to the degree of convexity or concavity in the cross-shore profileindicative of (i) depositional, tidally dominant or (ii) erosional, wave impacted conditions. Two contrasting areas of characteristic shapenorth or south of a constriction in estuary width located near the Dumbarton Bridgeare recognized. This pattern of increasing or decreasing convexity in the inner or outer estuary is correlated to spatial variability in external and internal environmental parameters, and observational results are found to be largely consistent with theoretical expectations. Tidal flat convexity in SSFB is observed to increase (in decreasing order of significance) in response to increased deposition, increased tidal range, decreased fetch length, decreased sediment grain size, and decreased tidal flat width. ?? 2010 Coastal Education and Research Foundation.

Extreme events following bifurcation to spatiotemporal chaos in a spatially extended microcavity laser

NASA Astrophysics Data System (ADS)

Coulibaly, S.; Clerc, M. G.; Selmi, F.; Barbay, S.

2017-02-01

The occurrence of extreme events in a spatially extended microcavity laser has been recently reported [Selmi et al., Phys. Rev. Lett. 116, 013901 (2016), 10.1103/PhysRevLett.116.013901] to be correlated to emergence of spatiotemporal chaos. In this dissipative system, the role of spatial coupling through diffraction is essential to observe the onset of spatiotemporal complexity. We investigate further the formation mechanism of extreme events by comparing the statistical and dynamical analyses. Experimental measurements together with numerical simulations allow us to assign the quasiperiodicity mechanism as the route to spatiotemporal chaos in this system. Moreover, by investigating the fine structure of the maximum Lyapunov exponent, of the Lyapunov spectrum, and of the Kaplan-Yorke dimension of the chaotic attractor, we are able to deduce that intermittency plays a key role in the proportion of extreme events measured. We assign the observed mechanism of generation of extreme events to quasiperiodic extended spatiotemporal intermittency.

Development of a socio-ecological environmental justice model for watershed-based management

NASA Astrophysics Data System (ADS)

Sanchez, Georgina M.; Nejadhashemi, A. Pouyan; Zhang, Zhen; Woznicki, Sean A.; Habron, Geoffrey; Marquart-Pyatt, Sandra; Shortridge, Ashton

2014-10-01

The dynamics and relationships between society and nature are complex and difficult to predict. Anthropogenic activities affect the ecological integrity of our natural resources, specifically our streams. Further, it is well-established that the costs of these activities are born unequally by different human communities. This study considered the utility of integrating stream health metrics, based on stream health indicators, with socio-economic measures of communities, to better characterize these effects. This study used a spatial multi-factor model and bivariate mapping to produce a novel assessment for watershed management, identification of vulnerable areas, and allocation of resources. The study area is the Saginaw River watershed located in Michigan. In-stream hydrological and water quality data were used to predict fish and macroinvertebrate measures of stream health. These measures include the Index of Biological Integrity (IBI), Hilsenhoff Biotic Index (HBI), Family IBI, and total number of Ephemeroptera, Plecoptera, and Trichoptera (EPT) taxa. Stream health indicators were then compared to spatially coincident socio-economic data, obtained from the United States Census Bureau (2010), including race, income, education, housing, and population size. Statistical analysis including spatial regression and cluster analysis were used to examine the correlation between vulnerable human populations and environmental conditions. Overall, limited correlation was observed between the socio-economic data and ecological measures of stream health, with the highest being a negative correlation of 0.18 between HBI and the social parameter household size. Clustering was observed in the datasets with urban areas representing a second order clustering effect over the watershed. Regions with the worst stream health and most vulnerable social populations were most commonly located nearby or down-stream to highly populated areas and agricultural lands.

Incorporating microbial dormancy dynamics into soil decomposition models to improve quantification of soil carbon dynamics of northern temperate forests

NASA Astrophysics Data System (ADS)

He, Yujie; Yang, Jinyan; Zhuang, Qianlai; Harden, Jennifer W.; McGuire, Anthony D.; Liu, Yaling; Wang, Gangsheng; Gu, Lianhong

2015-12-01

Soil carbon dynamics of terrestrial ecosystems play a significant role in the global carbon cycle. Microbial-based decomposition models have seen much growth recently for quantifying this role, yet dormancy as a common strategy used by microorganisms has not usually been represented and tested in these models against field observations. Here we developed an explicit microbial-enzyme decomposition model and examined model performance with and without representation of microbial dormancy at six temperate forest sites of different forest types. We then extrapolated the model to global temperate forest ecosystems to investigate biogeochemical controls on soil heterotrophic respiration and microbial dormancy dynamics at different temporal-spatial scales. The dormancy model consistently produced better match with field-observed heterotrophic soil CO2 efflux (RH) than the no dormancy model. Our regional modeling results further indicated that models with dormancy were able to produce more realistic magnitude of microbial biomass (<2% of soil organic carbon) and soil RH (7.5 ± 2.4 Pg C yr-1). Spatial correlation analysis showed that soil organic carbon content was the dominating factor (correlation coefficient = 0.4-0.6) in the simulated spatial pattern of soil RH with both models. In contrast to strong temporal and local controls of soil temperature and moisture on microbial dormancy, our modeling results showed that soil carbon-to-nitrogen ratio (C:N) was a major regulating factor at regional scales (correlation coefficient = -0.43 to -0.58), indicating scale-dependent biogeochemical controls on microbial dynamics. Our findings suggest that incorporating microbial dormancy could improve the realism of microbial-based decomposition models and enhance the integration of soil experiments and mechanistically based modeling.

Incorporating microbial dormancy dynamics into soil decomposition models to improve quantification of soil carbon dynamics of northern temperate forests

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

He, Yujie; Yang, Jinyan; Zhuang, Qianlai

Soil carbon dynamics of terrestrial ecosystems play a significant role in the global carbon cycle. Microbial-based decomposition models have seen much growth recently for quantifying this role, yet dormancy as a common strategy used by microorganisms has not usually been represented and tested in these models against field observations. Here in this study we developed an explicit microbial-enzyme decomposition model and examined model performance with and without representation of microbial dormancy at six temperate forest sites of different forest types. We then extrapolated the model to global temperate forest ecosystems to investigate biogeochemical controls on soil heterotrophic respiration and microbialmore » dormancy dynamics at different temporal-spatial scales. The dormancy model consistently produced better match with field-observed heterotrophic soil CO 2 efflux (R H) than the no dormancy model. Our regional modeling results further indicated that models with dormancy were able to produce more realistic magnitude of microbial biomass (<2% of soil organic carbon) and soil R H (7.5 ± 2.4 PgCyr -1). Spatial correlation analysis showed that soil organic carbon content was the dominating factor (correlation coefficient = 0.4-0.6) in the simulated spatial pattern of soil R H with both models. In contrast to strong temporal and local controls of soil temperature and moisture on microbial dormancy, our modeling results showed that soil carbon-to-nitrogen ratio (C:N) was a major regulating factor at regional scales (correlation coefficient = -0.43 to -0.58), indicating scale-dependent biogeochemical controls on microbial dynamics. Our findings suggest that incorporating microbial dormancy could improve the realism of microbial-based decomposition models and enhance the integration of soil experiments and mechanistically based modeling.« less

Incorporating microbial dormancy dynamics into soil decomposition models to improve quantification of soil carbon dynamics of northern temperate forests

USGS Publications Warehouse

He, Yujie; Yang, Jinyan; Zhuang, Qianlai; Harden, Jennifer W.; McGuire, A. David; Liu, Yaling; Wang, Gangsheng; Gu, Lianhong

2015-01-01

Soil carbon dynamics of terrestrial ecosystems play a significant role in the global carbon cycle. Microbial-based decomposition models have seen much growth recently for quantifying this role, yet dormancy as a common strategy used by microorganisms has not usually been represented and tested in these models against field observations. Here we developed an explicit microbial-enzyme decomposition model and examined model performance with and without representation of microbial dormancy at six temperate forest sites of different forest types. We then extrapolated the model to global temperate forest ecosystems to investigate biogeochemical controls on soil heterotrophic respiration and microbial dormancy dynamics at different temporal-spatial scales. The dormancy model consistently produced better match with field-observed heterotrophic soil CO2 efflux (RH) than the no dormancy model. Our regional modeling results further indicated that models with dormancy were able to produce more realistic magnitude of microbial biomass (<2% of soil organic carbon) and soil RH (7.5 ± 2.4 Pg C yr−1). Spatial correlation analysis showed that soil organic carbon content was the dominating factor (correlation coefficient = 0.4–0.6) in the simulated spatial pattern of soil RHwith both models. In contrast to strong temporal and local controls of soil temperature and moisture on microbial dormancy, our modeling results showed that soil carbon-to-nitrogen ratio (C:N) was a major regulating factor at regional scales (correlation coefficient = −0.43 to −0.58), indicating scale-dependent biogeochemical controls on microbial dynamics. Our findings suggest that incorporating microbial dormancy could improve the realism of microbial-based decomposition models and enhance the integration of soil experiments and mechanistically based modeling.

Coexistence of species with different dispersal across landscapes: a critical role of spatial correlation in disturbance.

PubMed

Liao, Jinbao; Ying, Zhixia; Woolnough, Daelyn A; Miller, Adam D; Li, Zhenqing; Nijs, Ivan

2016-05-11

Disturbance is key to maintaining species diversity in plant communities. Although the effects of disturbance frequency and extent on species diversity have been studied, we do not yet have a mechanistic understanding of how these aspects of disturbance interact with spatial structure of disturbance to influence species diversity. Here we derive a novel pair approximation model to explore competitive outcomes in a two-species system subject to spatially correlated disturbance. Generally, spatial correlation in disturbance favoured long-range dispersers, while distance-limited dispersers were greatly suppressed. Interestingly, high levels of spatial aggregation of disturbance promoted long-term species coexistence that is not possible in the absence of disturbance, but only when the local disperser was intrinsically competitively superior. However, spatial correlation in disturbance led to different competitive outcomes, depending on the disturbed area. Concerning ecological conservation and management, we theoretically demonstrate that introducing a spatially correlated disturbance to the system or altering an existing disturbance regime can be a useful strategy either to control species invasion or to promote species coexistence. Disturbance pattern analysis may therefore provide new insights into biodiversity conservation. © 2016 The Author(s).

Effects of Spatial Variability of Soil Properties on the Triggering of Rainfall-Induced Shallow Landslides

NASA Astrophysics Data System (ADS)

Fan, Linfeng; Lehmann, Peter; Or, Dani

2015-04-01

Naturally-occurring spatial variations in soil properties (e.g., soil depth, moisture, and texture) affect key hydrological processes and potentially the mechanical response of soil to hydromechanical loading (relative to the commonly-assumed uniform soil mantle). We quantified the effects of soil spatial variability on the triggering of rainfall-induced shallow landslides at the hillslope- and catchment-scales, using a physically-based landslide triggering model that considers interacting soil columns with mechanical strength thresholds (represented by the Fiber Bundle Model). The spatial variations in soil properties are represented as Gaussian random distributions and the level of variation is characterized by the coefficient of variation and correlation lengths of soil properties (i.e., soil depth, soil texture and initial water content in this study). The impacts of these spatial variations on landslide triggering characteristics were measured by comparing the times to triggering and landslide volumes for heterogeneous soil properties and homogeneous cases. Results at hillslope scale indicate that for spatial variations of an individual property (without cross correlation), the increasing of coefficient of variation introduces weak spots where mechanical damage is accelerated and leads to earlier onset of landslide triggering and smaller volumes. Increasing spatial correlation length of soil texture and initial water content also induces early landslide triggering and small released volumes due to the transition of failure mode from brittle to ductile failure. In contrast, increasing spatial correlation length of soil depth "reduces" local steepness and postpones landslide triggering. Cross-correlated soil properties generally promote landslide initiation, but depending on the internal structure of spatial distribution of each soil property, landslide triggering may be reduced. The effects of cross-correlation between initial water content and soil texture were investigated in detail at the catchment scale by incorporating correlations of both variables with topography. Results indicate that the internal structure of the spatial distribution of each soil property together with their interplays determine the overall performance of the coupled spatial variability. This study emphasizes the importance of both the randomness and spatial structure of soil properties on landslide triggering and characteristics.

Pair correlation functions for identifying spatial correlation in discrete domains

NASA Astrophysics Data System (ADS)

Gavagnin, Enrico; Owen, Jennifer P.; Yates, Christian A.

2018-06-01

Identifying and quantifying spatial correlation are important aspects of studying the collective behavior of multiagent systems. Pair correlation functions (PCFs) are powerful statistical tools that can provide qualitative and quantitative information about correlation between pairs of agents. Despite the numerous PCFs defined for off-lattice domains, only a few recent studies have considered a PCF for discrete domains. Our work extends the study of spatial correlation in discrete domains by defining a new set of PCFs using two natural and intuitive definitions of distance for a square lattice: the taxicab and uniform metric. We show how these PCFs improve upon previous attempts and compare between the quantitative data acquired. We also extend our definitions of the PCF to other types of regular tessellation that have not been studied before, including hexagonal, triangular, and cuboidal. Finally, we provide a comprehensive PCF for any tessellation and metric, allowing investigation of spatial correlation in irregular lattices for which recognizing correlation is less intuitive.

Cavitation occurrence around ultrasonic dental scalers.

PubMed

Felver, Bernhard; King, David C; Lea, Simon C; Price, Gareth J; Damien Walmsley, A

2009-06-01

Ultrasonic scalers are used in dentistry to remove calculus and other contaminants from teeth. One mechanism which may assist in the cleaning is cavitation generated in cooling water around the scaler. The vibratory motion of three designs of scaler tip in a water bath has been characterised by laser vibrometry, and compared with the spatial distribution of cavitation around the scaler tips observed using sonochemiluminescence from a luminol solution. The type of cavitation was confirmed by acoustic emission analysed by a 'Cavimeter' supplied by NPL. A node/antinode vibration pattern was observed, with the maximum displacement of each type of tip occurring at the free end. High levels of cavitation activity occurred in areas surrounding the vibration antinodes, although minimal levels were observed at the free end of the tip. There was also good correlation between vibration amplitude and sonochemiluminescence at other points along the scaler tip. 'Cavimeter' analysis correlated well with luminol observations, suggesting the presence of primarily transient cavitation.

Study of Spatial Interrelationship of Long-term River Runoff Variability

NASA Astrophysics Data System (ADS)

Jouk, V.; Romanova, H.; Polianin, V.

To do a number of practical tasks related to water resources management, planning a hydrological monitoring network, estimation of economic activity influence on river runoff, recollection of runoff rows for rivers with short period of observation and other, it is necessary to know about spatial distribution of an annual river runoff. Most of the methods including optimal interpolation that are being used nowadays to solve such problems can deal only with homogeneous and isotropic fields what isn't true in case of an annual river runoff. To find the causes that make an annual river runoff non- isotropic, first of all it is necessary to learn the field structure of its main climatic factors such as precipitation and air humidity deficit. The analyses of anisotropy of these fields can be performed by using unrolled spatially-correlation functions (USCF): Ri,j =f(Si,j;a), Ri,j - empirical correlation of observed rows; Si,j - distance between meteorological stations; a - an anngle between a parallel and the lines that join the centers of river catchments. The form of lines of equal level of USCF shows the direction of bigger or smaller spa- tial interrelationship of the field. In this work an annual river runoff field, precipitation and air humidity deficit fields were studied. The data of 55 meteorological stations was used and the data on water discharge of more than 255 rivers within the East-Europe plain was processed (a period of runoff observation for every river is about 60 years and a catchment area varies from 1 to 20 thousand sq. km.). Joint analyses of the USCFs shows that anisotropy of an annual river runoff field de- pends strongly on anisotropy of the fields of precipitation forming river runoff. In other words, stronger interrelationship of annual river runoff is observed in the direction of dominant moisture transfer. Landscape features of a catchment also have considerable influence on interrelation- ship between annual runoff values of different rivers. This influence was studied by us- ing conditional spatially-correlation functions or CSCF (i.e. spatially-correlation func- 1 tions constructed according to certain conditions applied to some landscape features). The following factors that affect annual river runoff were studied: catchment area, slope, mean elevation of a catchment, percentage of a forest cover of a catchment. As the study shows, the last factor mentioned above is the most important one which affects spatial interrelationship of an annual river runoff. It can be explained by the fact that the forest is a considerable seasonal and annual runoff redistributor. Moreover a forested area of river catchments varies greatly over the studied region. The influence of elevation occurred to be less obvious than that of the forest because of its small variation within the territory. The use of interpolation schemes taking into account anisotropy and heterogeneity of the field made it possible to improve quality of recollection of runoff rows. So considering heterogeneity of an annual runoff field using the information of percent- age of forest cover of a river catchment and mean elevation of a catchment lessened inaccuracy of runoff rows recollection by more than 7%. In principle, quality of in- terpolation can be enhanced more by taking into consideration not only the factors mentioned above, but also all possible landscape features of a river catchment.But this is the task of further researches. 2

Cerebral Correlates of Emotional and Action Appraisals During Visual Processing of Emotional Scenes Depending on Spatial Frequency: A Pilot Study

PubMed Central

Campagne, Aurélie; Fradcourt, Benoit; Pichat, Cédric; Baciu, Monica; Kauffmann, Louise; Peyrin, Carole

2016-01-01

Visual processing of emotional stimuli critically depends on the type of cognitive appraisal involved. The present fMRI pilot study aimed to investigate the cerebral correlates involved in the visual processing of emotional scenes in two tasks, one emotional, based on the appraisal of personal emotional experience, and the other motivational, based on the appraisal of the tendency to action. Given that the use of spatial frequency information is relatively flexible during the visual processing of emotional stimuli depending on the task’s demands, we also explored the effect of the type of spatial frequency in visual stimuli in each task by using emotional scenes filtered in low spatial frequency (LSF) and high spatial frequencies (HSF). Activation was observed in the visual areas of the fusiform gyrus for all emotional scenes in both tasks, and in the amygdala for unpleasant scenes only. The motivational task induced additional activation in frontal motor-related areas (e.g. premotor cortex, SMA) and parietal regions (e.g. superior and inferior parietal lobules). Parietal regions were recruited particularly during the motivational appraisal of approach in response to pleasant scenes. These frontal and parietal activations, respectively, suggest that motor and navigation processes play a specific role in the identification of the tendency to action in the motivational task. Furthermore, activity observed in the motivational task, in response to both pleasant and unpleasant scenes, was significantly greater for HSF than for LSF scenes, suggesting that the tendency to action is driven mainly by the detailed information contained in scenes. Results for the emotional task suggest that spatial frequencies play only a small role in the evaluation of unpleasant and pleasant emotions. Our preliminary study revealed a partial distinction between visual processing of emotional scenes during identification of the tendency to action, and during identification of personal emotional experiences. It also illustrates flexible use of the spatial frequencies contained in scenes depending on their emotional valence and on task demands. PMID:26757433

Spatially Resolved Sensitivity of Single-Particle Plasmon Sensors

PubMed Central

2018-01-01

The high sensitivity of localized surface plasmon resonance sensors to the local refractive index allows for the detection of single-molecule binding events. Though binding events of single objects can be detected by their induced plasmon shift, the broad distribution of observed shifts remains poorly understood. Here, we perform a single-particle study wherein single nanospheres bind to a gold nanorod, and relate the observed plasmon shift to the binding location using correlative microscopy. To achieve this we combine atomic force microscopy to determine the binding location, and single-particle spectroscopy to determine the corresponding plasmon shift. As expected, we find a larger plasmon shift for nanospheres binding at the tip of a rod compared to its sides, in good agreement with numerical calculations. However, we also find a broad distribution of shifts even for spheres that were bound at a similar location to the nanorod. Our correlative approach allows us to disentangle effects of nanoparticle dimensions and binding location, and by comparison to numerical calculations we find that the biggest contributor to this observed spread is the dispersion in nanosphere diameter. These experiments provide insight into the spatial sensitivity and signal-heterogeneity of single-particle plasmon sensors and provides a framework for signal interpretation in sensing applications. PMID:29520315

OBSERVATIONAL EVIDENCE AGAINST LONG-LIVED SPIRAL ARMS IN GALAXIES

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

Foyle, K.; Rix, H.-W.; Walter, F.

2011-07-10

We test whether the spiral patterns apparent in many large disk galaxies should be thought of as dynamical features that are stationary in a corotating frame for {approx}> t{sub dyn}, as implied by the density wave approach for explaining spiral arms. If such spiral arms have enhanced star formation (SF), observational tracers for different stages of the SF sequence should show a spatial ordering, from upstream to downstream in the corotating frame: dense H I, CO, tracing molecular hydrogen gas, 24 {mu}m emission tracing enshrouded SF, and UV emission tracing unobscured young stars. We argue that such a spatial orderingmore » should be reflected in the angular cross-correlation (CC, in polar coordinates) using all azimuthal positions among pairs of these tracers; the peak of the CC should be offset from zero, in different directions inside and outside the corotation radius. Recent spiral SF simulations by Dobbs and Pringle show explicitly that for the case of a stationary spiral arm potential such angular offsets between gas and young stars of differing ages should be observable as cross-correlation offsets. We calculate the angular cross-correlations for different observational SF sequence tracers in 12 nearby spiral galaxies, drawing on a data set with high-quality maps of the neutral gas (H I, THINGS) and molecular gas (CO, HERACLES), along with 24 {mu}m emission (Spitzer, SINGS); we include FUV images (GALEX) and 3.6 {mu}m emission (Spitzer, IRAC) for some galaxies, tracing aging stars and longer timescales. In none of the resulting tracer cross-correlations for this sample do we find systematic angular offsets, which would be expected for a stationary dynamical spiral pattern of well-defined pattern speed. This result indicates that spiral density waves in their simplest form are not an important aspect of explaining spirals in large disk galaxies.« less

Intercomparisons of Marine Boundary Layer Cloud Properties from the ARM CAP-MBL Campaign and Two MODIS Cloud Products

NASA Technical Reports Server (NTRS)

Zhang, Zhibo; Dong, Xiquan; Xi, Baike; Song, Hua; Ma, Po-Lun; Ghan, Steven J.; Platnick, Steven; Minnis, Patrick

2017-01-01

From April 2009 to December 2010, the Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) program carried out an observational field campaign on Graciosa Island, targeting the marine boundary layer (MBL) clouds over the Azores region. In this paper, we present an inter-comparison of the MBL cloud properties, namely, cloud liquid water path (LWP), cloud optical thickness (COT) and cloud-droplet effective radius (CER), among retrievals from the ARM mobile facility (AMF) and two Moderate Resolution Spectroradiometer (MODIS) cloud products (GSFC-MODIS and CERES-MODIS). A total of 63 daytime single-layer MBL cloud cases are selected for inter-comparison. Comparison of collocated retrievals indicates that the two MODIS cloud products agree well on both COT and CER retrievals, with the correlation coefficient R greater than 0.95 despite their significant difference in spatial sampling. In both MODIS products, the CER retrievals based on the 2.1 micrometers band (CER(sub 2.1)) is significantly smaller than that based on the 3.7 micrometers band (CER(sub 3.7)). The GSFC-MODIS cloud product is collocated and compared with ground-based ARM observations at several temporal spatial scales. In general, the correlation increases with more precise collocation. For the 63 selected MBL cloud cases, the GSFC-MODIS LWP and COT retrievals agree reasonably well with the ground-based observations with no apparent bias and correlation coefficient R around 0.85 and 0.70, respectively. However, GSFC-MODIS CER(sub 3.7) and CER(sub 2.1) retrievals have a lower correlation (R is approximately 0.5) with the ground-based retrievals. For the 63 selected cases, they are on average larger than ground observations by about 1.5 micrometers and 3.0 micrometers, respectively. Taking into account that the MODIS CER retrievals are only sensitive to cloud top reduces the bias only by 0.5 micrometers.

Satellite observations of atmosphere-ionosphere vertical coupling by gravity waves

NASA Astrophysics Data System (ADS)

Trinh, Thai; Ern, Manfred; Preusse, Peter; Riese, Martin

2017-04-01

The Earth's thermosphere/ionosphere (T/I) is strongly influenced by various processes from above as well as from below. One of the most important processes from below is vertical coupling by atmospheric waves. Among these waves, gravity waves (GWs) excited in the lower atmosphere, mainly in the troposphere and tropopause region, are likely essential for the mean state of the T/I system. The penetration of GWs into the T/I system is however not well understood in modeling as well as observations. In this work, we analyze the correlation between different GW parameters at lower altitudes (below 90 km) and GW induced perturbations in the T/I. At lower altitudes, GW parameters are derived from temperature observations of the Sounding of the Atmosphere using Broadband Emission Radiometry (SABER). In the T/I, GW induced perturbations of neutral density measured by Gravity field and Ocean Circulation Explorer (GOCE) and CHAllenging Minisatellite Payload (CHAMP) are analyzed. Interestingly, we find positive correlations between the spatial distributions at low altitudes (i.e. below 90km) and the spatial distributions of GW-induced density fluctuations in the T/I (at 200km and above), which suggests that many waves seen in the T/I have their origins in the troposphere or lower stratosphere. It is also indicated that mountain waves generated near the Andes and Antarctic Peninsula propagate up to the T/I. Strong positive correlations between GW perturbations in the T/I and GW parameters at 30 km are mainly found at mid latitudes, which may be an indicator of propagation of convectively generated GWs. Increase of correlation starting from 70 km in many cases shows that filtering of the GW distribution by the background atmosphere is very important. Processes that are likely involved are GW dissipation, generation of secondary GWs, as well as horizontal propagation of GWs. Limitations of our method and of the observations are also discussed.

Intercomparisons of marine boundary layer cloud properties from the ARM CAP-MBL campaign and two MODIS cloud products

NASA Astrophysics Data System (ADS)

Zhang, Zhibo; Dong, Xiquan; Xi, Baike; Song, Hua; Ma, Po-Lun; Ghan, Steven J.; Platnick, Steven; Minnis, Patrick

2017-02-01

From April 2009 to December 2010, the Department of Energy Atmospheric Radiation Measurement (ARM) program carried out an observational field campaign on Graciosa Island, targeting the marine boundary layer (MBL) clouds over the Azores region. In this paper, we present an intercomparison of the MBL cloud properties, namely, cloud liquid water path (LWP), cloud optical thickness (COT), and cloud-droplet effective radius (CER), among retrievals from the ARM mobile facility and two Moderate Resolution Imaging Spectroradiometer (MODIS) cloud products (Goddard Space Flight Center (GSFC)-MODIS and Clouds and Earth's Radiant Energy System-MODIS). A total of 63 daytime single-layer MBL cloud cases are selected for intercomparison. Comparison of collocated retrievals indicates that the two MODIS cloud products agree well on both COT and CER retrievals, with the correlation coefficient R > 0.95, despite their significant difference in spatial sampling. In both MODIS products, the CER retrievals based on the 2.1 µm band (CER2.1) are significantly larger than those based on the 3.7 µm band (CER3.7). The GSFC-MODIS cloud product is collocated and compared with ground-based ARM observations at several temporal-spatial scales. In general, the correlation increases with more precise collocation. For the 63 selected MBL cloud cases, the GSFC-MODIS LWP and COT retrievals agree reasonably well with the ground-based observations with no apparent bias and correlation coefficient R around 0.85 and 0.70, respectively. However, GSFC-MODIS CER3.7 and CER2.1 retrievals have a lower correlation (R 0.5) with the ground-based retrievals. For the 63 selected cases, they are on average larger than ground observations by about 1.5 µm and 3.0 µm, respectively. Taking into account that the MODIS CER retrievals are only sensitive to cloud top reduces the bias only by 0.5 µm.

Many-Body Subradiant Excitations in Metamaterial Arrays: Experiment and Theory.

PubMed

Jenkins, Stewart D; Ruostekoski, Janne; Papasimakis, Nikitas; Savo, Salvatore; Zheludev, Nikolay I

2017-08-04

Subradiant excitations, originally predicted by Dicke, have posed a long-standing challenge in physics owing to their weak radiative coupling to environment. Here we engineer massive coherently driven classical subradiance in planar metamaterial arrays as a spatially extended eigenmode comprising over 1000 metamolecules. By comparing the near- and far-field response in large-scale numerical simulations with those in experimental observations we identify strong evidence for classically correlated multimetamolecule subradiant states that dominate the total excitation energy. We show that similar spatially extended many-body subradiance can also exist in plasmonic metamaterial arrays at optical frequencies.

Spatial variability in acoustic backscatter as an indicator of tissue homogenate production in pulsed cavitational ultrasound therapy.

PubMed

Parsons, Jessica E; Cain, Charles A; Fowlkes, J Brian

2007-03-01

Spatial variability in acoustic backscatter is investigated as a potential feedback metric for assessment of lesion morphology during cavitation-mediated mechanical tissue disruption ("histotripsy"). A 750-kHz annular array was aligned confocally with a 4.5 MHz passive backscatter receiver during ex vivo insonation of porcine myocardium. Various exposure conditions were used to elicit a range of damage morphologies and backscatter characteristics [pulse duration = 14 micros, pulse repetition frequency (PRF) = 0.07-3.1 kHz, average I(SPPA) = 22-44 kW/cm2]. Variability in backscatter spatial localization was quantified by tracking the lag required to achieve peak correlation between sequential RF A-lines received. Mean spatial variability was observed to be significantly higher when damage morphology consisted of mechanically disrupted tissue homogenate versus mechanically intact coagulation necrosis (2.35 +/- 1.59 mm versus 0.067 +/- 0.054 mm, p < 0.025). Statistics from these variability distributions were used as the basis for selecting a threshold variability level to identify the onset of homogenate formation via an abrupt, sustained increase in spatially dynamic backscatter activity. Specific indices indicative of the state of the homogenization process were quantified as a function of acoustic input conditions. The prevalence of backscatter spatial variability was observed to scale with the amount of homogenate produced for various PRFs and acoustic intensities.

Detection of Linear Polarization from SNR Cassiopeia A at Low Radio Frequencies

NASA Astrophysics Data System (ADS)

Raja, Wasim; Deshpande, Avinash A.

2015-03-01

We report detection of the weak but significant linear polarization from the Supernova Remnant Cas A at low radio frequencies (327 MHz) using the GMRT. The spectro-polarimetric data (16 MHz bandwidth with 256 spectral channels) was analyzed using the technique of Faraday Tomography. Ascertaining association of this weak polarization to the source is non-trivial in the presence of the remnant instrumental polarization (<1% in our case) - the expected anti-correlation ρlp,x, between the linear polarized intensity and the soft X-ray counts gets masked by the correlation between the Stokes-I dependent instrumental leakage and the X-radiation that is spatially correlated with Stokes-I, if ρ lp,x is computed naively. Hence, we compute ρ lp,x using pixels within ultra narrow bins of Stokes-I within which the instrumental leakage is expected to remain constant, and establish the anti-correlation as well as the correspondence of this correlation with the mean X-ray profile (Figure 1). Given the angular and RM-resolution in our data, the observed depolarization relative to that at higher frequencies, implies that the mixing of thermal and non-thermal plasma within the source might be occurring on spatial scales ~ 1000 AU, assuming random superposition of polarization states.

The effect of the dynamic wet troposphere on radio interferometric measurements

NASA Technical Reports Server (NTRS)

Treuhaft, R. N.; Lanyi, G. E.

1987-01-01

A statistical model of water vapor fluctuations is used to describe the effect of the dynamic wet troposphere on radio interferometric measurements. It is assumed that the spatial structure of refractivity is approximated by Kolmogorov turbulence theory, and that the temporal fluctuations are caused by spatial patterns moved over a site by the wind, and these assumptions are examined for the VLBI delay and delay rate observables. The results suggest that the delay rate measurement error is usually dominated by water vapor fluctuations, and water vapor induced VLBI parameter errors and correlations are determined as a function of the delay observable errors. A method is proposed for including the water vapor fluctuations in the parameter estimation method to obtain improved parameter estimates and parameter covariances.

Electric currents and coronal heating in NOAA active region 6952

NASA Technical Reports Server (NTRS)

Metcalf, T. R.; Canfield, R. C.; Hudson, H. S.; Mickey, D. L.; Wulser, J. -P.; Martens, P. C. H.; Tsuneta, S.

1994-01-01

We examine the spatial and temporal relationship between coronal structures observed with the soft X-ray telescope (SXT) on board the Yohkoh spacecraft and the vertical electric current density derived from photospheric vector magnetograms obtained using the Stokes Polarimeter at the Mees Solar Observatory. We focus on a single active region: AR 6952 which we observed on 7 days during 1991 December. For 11 independent maps of the vertical electric current density co-aligned with non-flaring X-ray images, we search for a morphological relationship between sites of high vertical current density in the photosphere and enhanced X-ray emission in the overlying corona. We find no compelling spatial or temporal correlation between the sites of vertical current and the bright X-ray structures in this active region.

Right Visual Field Advantage for Perceived Contrast: Correlation with an Auditory Bias and Handedness

ERIC Educational Resources Information Center

Railo, H.; Tallus, J.; Hamalainen, H.

2011-01-01

Studies have suggested that supramodal attentional resources are biased rightward due to asymmetric spatial fields of the two hemispheres. This bias has been observed especially in right-handed subjects. We presented left and right-handed subjects with brief uniform grey visual stimuli in either the left or right visual hemifield. Consistent with…

Insights into the Nature of Mercury's Exosphere: Early Results from the MESSENGER Orbital Mission Phase

NASA Technical Reports Server (NTRS)

McClintock, William E.; Burger, Matthew H.; Killen, Rosemary M.; Merkel, Aimee W.; Sarantos, Menelaos; Sprague, Ann L.; Solomon, Sean C.; Vervack, Ronald J., Jr.

2011-01-01

The Ultraviolet and Visible Spectrometer aboard the MESSENGER spacecraft has been making routine observations of Mercury's exosphere since March 29, 2011. Correlations of the spatial distributions of Ca, Mg, and Na with MESSENGER magnetic field and energetic particle distribution data provide insight into the processes that populate the neutral exosphere

Co-variability of smoke and fire in the Amazon basin

NASA Astrophysics Data System (ADS)

Mishra, Amit Kumar; Lehahn, Yoav; Rudich, Yinon; Koren, Ilan

2015-05-01

The Amazon basin is a hot spot of anthropogenically-driven biomass burning, accounting for approximately 15% of total global fire emissions. It is essential to accurately measure these fires for robust regional and global modeling of key environmental processes. Here we have explored the link between spatio-temporal variability patterns in the Amazon basin's fires and the resulting smoke loading using 11 years (2002-2012) of data from the Moderate Resolution Imaging Spectroradiometer (MODIS) and the Aerosol Robotic Network (AERONET) observations. Focusing on the peak burning season (July-October), our analysis shows strong inter-annual correlation between aerosol optical depth (AOD) and two MODIS fire products: fire radiative power (FRP) and fire pixel counts (FC). Among these two fire products, the FC better indicates the amount of smoke in the basin, as represented in remotely sensed AOD data. This fire product is significantly correlated both with regional AOD retrievals from MODIS and with point AOD measurements from the AERONET stations, pointing to spatial homogenization of the smoke over the basin on a seasonal time scale. However, MODIS AODs are found better than AERONET AODs observation for linking between smoke and fire. Furthermore, MODIS AOD measurements are strongly correlated with number of fires ∼10-20 to the east, most likely due to westward advection of smoke by the wind. These results can be rationalized by the regional topography and the wind regimes. Our analysis can improve data assimilation of satellite and ground-based observations into regional and global model studies, thus improving the assessment of the environmental and climatic impacts of frequency and distribution variability of the Amazon basin's fires. We also provide the optimal spatial and temporal scales for ground-based observations, which could be used for such applications.

Possible future changes in South East Australian frost frequency: an inter-comparison of statistical downscaling approaches

NASA Astrophysics Data System (ADS)

Crimp, Steven; Jin, Huidong; Kokic, Philip; Bakar, Shuvo; Nicholls, Neville

2018-04-01

Anthropogenic climate change has already been shown to effect the frequency, intensity, spatial extent, duration and seasonality of extreme climate events. Understanding these changes is an important step in determining exposure, vulnerability and focus for adaptation. In an attempt to support adaptation decision-making we have examined statistical modelling techniques to improve the representation of global climate model (GCM) derived projections of minimum temperature extremes (frosts) in Australia. We examine the spatial changes in minimum temperature extreme metrics (e.g. monthly and seasonal frost frequency etc.), for a region exhibiting the strongest station trends in Australia, and compare these changes with minimum temperature extreme metrics derived from 10 GCMs, from the Coupled Model Inter-comparison Project Phase 5 (CMIP 5) datasets, and via statistical downscaling. We compare the observed trends with those derived from the "raw" GCM minimum temperature data as well as examine whether quantile matching (QM) or spatio-temporal (spTimerQM) modelling with Quantile Matching can be used to improve the correlation between observed and simulated extreme minimum temperatures. We demonstrate, that the spTimerQM modelling approach provides correlations with observed daily minimum temperatures for the period August to November of 0.22. This represents an almost fourfold improvement over either the "raw" GCM or QM results. The spTimerQM modelling approach also improves correlations with observed monthly frost frequency statistics to 0.84 as opposed to 0.37 and 0.81 for the "raw" GCM and QM results respectively. We apply the spatio-temporal model to examine future extreme minimum temperature projections for the period 2016 to 2048. The spTimerQM modelling results suggest the persistence of current levels of frost risk out to 2030, with the evidence of continuing decadal variation.

Status update: is smoke on your mind? Using social media to assess smoke exposure

NASA Astrophysics Data System (ADS)

Ford, Bonne; Burke, Moira; Lassman, William; Pfister, Gabriele; Pierce, Jeffrey R.

2017-06-01

Exposure to wildland fire smoke is associated with negative effects on human health. However, these effects are poorly quantified. Accurately attributing health endpoints to wildland fire smoke requires determining the locations, concentrations, and durations of smoke events. Most current methods for assessing these smoke events (ground-based measurements, satellite observations, and chemical transport modeling) are limited temporally, spatially, and/or by their level of accuracy. In this work, we explore using daily social media posts from Facebook regarding smoke, haze, and air quality to assess population-level exposure for the summer of 2015 in the western US. We compare this de-identified, aggregated Facebook dataset to several other datasets that are commonly used for estimating exposure, such as satellite observations (MODIS aerosol optical depth and Hazard Mapping System smoke plumes), daily (24 h) average surface particulate matter measurements, and model-simulated (WRF-Chem) surface concentrations. After adding population-weighted spatial smoothing to the Facebook data, this dataset is well correlated (R2 generally above 0.5) with the other methods in smoke-impacted regions. The Facebook dataset is better correlated with surface measurements of PM2. 5 at a majority of monitoring sites (163 of 293 sites) than the satellite observations and our model simulation. We also present an example case for Washington state in 2015, for which we combine this Facebook dataset with MODIS observations and WRF-Chem-simulated PM2. 5 in a regression model. We show that the addition of the Facebook data improves the regression model's ability to predict surface concentrations. This high correlation of the Facebook data with surface monitors and our Washington state example suggests that this social-media-based proxy can be used to estimate smoke exposure in locations without direct ground-based particulate matter measurements.

Species extinction thresholds in the face of spatially correlated periodic disturbance.

PubMed

Liao, Jinbao; Ying, Zhixia; Hiebeler, David E; Wang, Yeqiao; Takada, Takenori; Nijs, Ivan

2015-10-20

The spatial correlation of disturbance is gaining attention in landscape ecology, but knowledge is still lacking on how species traits determine extinction thresholds under spatially correlated disturbance regimes. Here we develop a pair approximation model to explore species extinction risk in a lattice-structured landscape subject to aggregated periodic disturbance. Increasing disturbance extent and frequency accelerated population extinction irrespective of whether dispersal was local or global. Spatial correlation of disturbance likewise increased species extinction risk, but only for local dispersers. This indicates that models based on randomly simulated disturbances (e.g., mean-field or non-spatial models) may underestimate real extinction rates. Compared to local dispersal, species with global dispersal tolerated more severe disturbance, suggesting that the spatial correlation of disturbance favors long-range dispersal from an evolutionary perspective. Following disturbance, intraspecific competition greatly enhanced the extinction risk of distance-limited dispersers, while it surprisingly did not influence the extinction thresholds of global dispersers, apart from decreasing population density to some degree. As species respond differently to disturbance regimes with different spatiotemporal properties, different regimes may accommodate different species.

Observations of faint comets at McDonald Observatory: 1978-1980

NASA Technical Reports Server (NTRS)

Barker, E. S.; Cochran, A. L.; Rybski, P. M.

1981-01-01

Modern observational techniques, developed for spectroscopy and photometry of faint galaxies and quasars, successfully applied to faint comets on the 2.7 m telescope. The periodic comets Van Biesbrock, Ashbrook-Jackson, Schwassmann-Wachmann 1, Tempel 2, Encke, Forbes, Brooks 2, Stephan-Oterma and the new comets Bradfield (19791), Bowell (1980b), Chernis-Petrauskas (1980k) were observed. The comets ranged in magnitude from 10th to 20th magnitude. For comets fainter than 19th magnitude, reflectance spectra at 100A resolution and area photometry were obtained. On comets of 17th or 18th magnitude, spectrometric scans (6A resolution) of the nucleus or inner coma region. On those comets which are brighter than 16th magnitude spatial spectrophotometric (6A resolution) studies of the inner and extended comae were done. An extensive spatial study of the comae of P/Encke and P/Stephen-Oterma, correlated with heliocentric distance is taking place. The observing process used is described and examples of the results obtained to date are discussed.

Collocation mismatch uncertainties in satellite aerosol retrieval validation

NASA Astrophysics Data System (ADS)

Virtanen, Timo H.; Kolmonen, Pekka; Sogacheva, Larisa; Rodríguez, Edith; Saponaro, Giulia; de Leeuw, Gerrit

2018-02-01

Satellite-based aerosol products are routinely validated against ground-based reference data, usually obtained from sun photometer networks such as AERONET (AEROsol RObotic NETwork). In a typical validation exercise a spatial sample of the instantaneous satellite data is compared against a temporal sample of the point-like ground-based data. The observations do not correspond to exactly the same column of the atmosphere at the same time, and the representativeness of the reference data depends on the spatiotemporal variability of the aerosol properties in the samples. The associated uncertainty is known as the collocation mismatch uncertainty (CMU). The validation results depend on the sampling parameters. While small samples involve less variability, they are more sensitive to the inevitable noise in the measurement data. In this paper we study systematically the effect of the sampling parameters in the validation of AATSR (Advanced Along-Track Scanning Radiometer) aerosol optical depth (AOD) product against AERONET data and the associated collocation mismatch uncertainty. To this end, we study the spatial AOD variability in the satellite data, compare it against the corresponding values obtained from densely located AERONET sites, and assess the possible reasons for observed differences. We find that the spatial AOD variability in the satellite data is approximately 2 times larger than in the ground-based data, and the spatial variability correlates only weakly with that of AERONET for short distances. We interpreted that only half of the variability in the satellite data is due to the natural variability in the AOD, and the rest is noise due to retrieval errors. However, for larger distances (˜ 0.5°) the correlation is improved as the noise is averaged out, and the day-to-day changes in regional AOD variability are well captured. Furthermore, we assess the usefulness of the spatial variability of the satellite AOD data as an estimate of CMU by comparing the retrieval errors to the total uncertainty estimates including the CMU in the validation. We find that accounting for CMU increases the fraction of consistent observations.

Correlated motion in the bulk of dense granular flows.

PubMed

Staron, Lydie

2008-05-01

Numerical simulations of two-dimensional stationary dense granular flows are performed. We check that the system obeys the h_{stop} phenomenology. Focusing on the spatial correlations of the instantaneous velocity fluctuations of the grains, we give evidence of the existence of correlated motion over several grain diameters in the bulk of the flow. Investigating the role of contact friction and restitution, we show that the associated typical length scale lambda is essentially independent of the grain properties. Moreover, we show that lambda is not controlled by the packing compacity. However, in agreement with previous experimental work, we observe that the correlation length decreases with the shear rate. Computing the flows inertia number I , we show a first-order dependence of lambda on I .

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

Cable, J.W.

The diffuse scattering of neutrons from magnetic materials provides unique and important information regarding the spatial correlations of the atoms and the spins. Such measurements have been extensively applied to magnetically ordered systems, such as the ferromagnetic binary alloys, for which the observed correlations describe the magnetic moment fluctuations associated with local environment effects. With the advent of polarization analysis, these techniques are increasingly being applied to study disordered paramagnetic systems such as the spin-glasses and the diluted magnetic semiconductors. The spin-pair correlations obtained are essential in understanding the exchange interactions of such systems. In this paper, we describe recentmore » neutron diffuse scattering results on the atom-pair and spin-pair correlations in some of these disordered magnetic systems. 56 refs.« less

Aperture synthesis for microwave radiometers in space

NASA Technical Reports Server (NTRS)

Levine, D. M.; Good, J. C.

1983-01-01

A technique is described for obtaining passive microwave measurements from space with high spatial resolution for remote sensing applications. The technique involves measuring the product of the signal from pairs of antennas at many different antenna spacings, thereby mapping the correlation function of antenna voltage. The intensity of radiation at the source can be obtained from the Fourier transform of this correlation function. Theory is presented to show how the technique can be applied to large extended sources such as the Earth when observed from space. Details are presented for a system with uniformly spaced measurements.

Widespread correlation patterns of fMRI signal across visual cortex reflect eccentricity organization.

PubMed

Arcaro, Michael J; Honey, Christopher J; Mruczek, Ryan E B; Kastner, Sabine; Hasson, Uri

2015-02-19

The human visual system can be divided into over two-dozen distinct areas, each of which contains a topographic map of the visual field. A fundamental question in vision neuroscience is how the visual system integrates information from the environment across different areas. Using neuroimaging, we investigated the spatial pattern of correlated BOLD signal across eight visual areas on data collected during rest conditions and during naturalistic movie viewing. The correlation pattern between areas reflected the underlying receptive field organization with higher correlations between cortical sites containing overlapping representations of visual space. In addition, the correlation pattern reflected the underlying widespread eccentricity organization of visual cortex, in which the highest correlations were observed for cortical sites with iso-eccentricity representations including regions with non-overlapping representations of visual space. This eccentricity-based correlation pattern appears to be part of an intrinsic functional architecture that supports the integration of information across functionally specialized visual areas.

Relative distribution of cosmic rays and magnetic fields

NASA Astrophysics Data System (ADS)

Seta, Amit; Shukurov, Anvar; Wood, Toby S.; Bushby, Paul J.; Snodin, Andrew P.

2018-02-01

Synchrotron radiation from cosmic rays is a key observational probe of the galactic magnetic field. Interpreting synchrotron emission data requires knowledge of the cosmic ray number density, which is often assumed to be in energy equipartition (or otherwise tightly correlated) with the magnetic field energy. However, there is no compelling observational or theoretical reason to expect such a tight correlation to hold across all scales. We use test particle simulations, tracing the propagation of charged particles (protons) through a random magnetic field, to study the cosmic ray distribution at scales comparable to the correlation scale of the turbulent flow in the interstellar medium (≃100 pc in spiral galaxies). In these simulations, we find that there is no spatial correlation between the cosmic ray number density and the magnetic field energy density. In fact, their distributions are approximately statistically independent. We find that low-energy cosmic rays can become trapped between magnetic mirrors, whose location depends more on the structure of the field lines than on the field strength.

OSO 8 X-ray spectra of clusters of galaxies. II - Discussion

NASA Technical Reports Server (NTRS)

Smith, B. W.; Mushotzky, R. F.; Serlemitsos, P. J.

1979-01-01

An observational description of X-ray clusters of galaxies is given based on OSO 8 X-ray results for spatially integrated spectra of 20 such clusters and various correlations obtained from these results. It is found from a correlation between temperature and velocity dispersion that the X-ray core radius should be less than the galaxy core radius or, alternatively, that the polytropic index is about 1.1 for most of the 20 clusters. Analysis of a correlation between temperature and emission integral yields evidence that more massive clusters accumulate a larger fraction of their mass as intracluster gas. Galaxy densities and optical morphology, as they correlate with X-ray properties, are reexamined for indications as to how mass injection by galaxies affects the density structure of the gas. The physical arguments used to derive iron abundances from observed equivalent widths of iron line features in X-ray spectra are critically evaluated, and the associated uncertainties in abundances derived in this manner are estimated to be quite large.

Synchrony, Waves, and Spatial Hierarchies in the Spread of Influenza

NASA Astrophysics Data System (ADS)

Viboud, Cécile; Bjørnstad, Ottar N.; Smith, David L.; Simonsen, Lone; Miller, Mark A.; Grenfell, Bryan T.

2006-04-01

Quantifying long-range dissemination of infectious diseases is a key issue in their dynamics and control. Here, we use influenza-related mortality data to analyze the between-state progression of interpandemic influenza in the United States over the past 30 years. Outbreaks show hierarchical spatial spread evidenced by higher pairwise synchrony between more populous states. Seasons with higher influenza mortality are associated with higher disease transmission and more rapid spread than are mild ones. The regional spread of infection correlates more closely with rates of movement of people to and from their workplaces (workflows) than with geographical distance. Workflows are described in turn by a gravity model, with a rapid decay of commuting up to around 100 km and a long tail of rare longer range flow. A simple epidemiological model, based on the gravity formulation, captures the observed increase of influenza spatial synchrony with transmissibility; high transmission allows influenza to spread rapidly beyond local spatial constraints.

Spatial distribution of FIR rotationally excited CH+ and OH emission lines in the Orion Bar PDR⋆

PubMed Central

Parikka, A.; Habart, E.; Bernard-Salas, J.; Goicoechea, J. R.; Abergel, A.; Pilleri, P.; Dartois, E.; Joblin, C.; Gerin, M.; Godard, B.

2016-01-01

Context The methylidyne cation (CH+) and hydroxyl (OH) are key molecules in the warm interstellar chemistry, but their formation and excitation mechanisms are not well understood. Their abundance and excitation are predicted to be enhanced by the presence of vibrationally excited H2 or hot gas (~500–1000 K) in photodissociation regions with high incident FUV radiation field. The excitation may also originate in dense gas (> 105 cm−3) followed by nonreactive collisions with H2, H, and electrons. Previous observations of the Orion Bar suggest that the rotationally excited CH+ and OH correlate with the excited CO, a tracer of dense and warm gas, and formation pumping contributes to CH+ excitation. Aims Our goal is to examine the spatial distribution of the rotationally excited CH+ and OH emission lines in the Orion Bar in order to establish their physical origin and main formation and excitation mechanisms. Methods We present spatially sampled maps of the CH+ J=3-2 transition at 119.8 µm and the OH Λ-doublet at 84 µm in the Orion Bar over an area of 110″×110″ with Herschel (PACS). We compare the spatial distribution of these molecules with those of their chemical precursors, C+, O and H2, and tracers of warm and dense gas (high-J CO). We assess the spatial variation of CH+ J=2-1 velocity-resolved line profile at 1669 GHz with Herschel HIFI spectrometer observations. Results The OH and especially CH+ lines correlate well with the high-J CO emission and delineate the warm and dense molecular region at the edge of the Bar. While notably similar, the differences in the CH+ and OH morphologies indicate that CH+ formation and excitation are strongly related to the observed vibrationally excited H2. This, together with the observed broad CH+ line widths, indicates that formation pumping contributes to the excitation of this reactive molecular ion. Interestingly, the peak of the rotationally excited OH 84 µm emission coincides with a bright young object, proplyd 244-440, which shows that OH can be an excellent tracer of UV-irradiated dense gas. Conclusions The spatial distribution of CH+ and OH revealed in our maps is consistent with previous modeling studies. Both formation pumping and nonreactive collisions in a UV-irradiated dense gas are important CH+ J=3-2 excitation processes. The excitation of the OH Λ-doublet at 84 µm is mainly sensitive to the temperature and density. PMID:28260804

The need for psychiatric care in England: a spatial factor methodology

NASA Astrophysics Data System (ADS)

Congdon, Peter

2008-09-01

To ensure health resources are equitably distributed, composite indices of population morbidity or “health need” are often used. Measures of the dimensions of population morbidity (e.g. socioeconomic deprivation) relevant to health need are typically not directly available but indirectly measured through census or other sources. This paper considers measurement of latent population morbidity constructs using both health outcomes (e.g. hospital admissions, mortality) and observed area social and demographic indicators (e.g. census data). The constructs are allowed to be spatially correlated between areas, as well as correlated with one another within areas. The health outcomes may depend both on the latent constructs and on other relevant covariates (e.g. bed supply), with some covariates possibly measured only at higher (regional) scales. A case study considers variations in psychiatric admissions in 354 English local authority areas in relation to two latent constructs: area deprivation and social fragmentation.

Volcanic eruptions, lightning, and a waterfall: Differentiating the menagerie of infrasound in the Ecuadorian jungle

NASA Astrophysics Data System (ADS)

Johnson, Jeffrey B.; Lees, Jonathan M.; Yepes, Hugo

2006-03-01

In northeastern Ecuador, near Reventador Volcano, the airwaves are filled with infrasound. Here we identify the locations and characterize three distinct sources of local infrasound, including two types of infrasonic sources, which are not commonly discussed in the literature. The first of these novel sources is an intense and continuous radiator with a fixed location corresponding to San Rafael Waterfall. The signal from the river exhibits a tremor-like envelope that is well correlated across the 3-element infrasound network. Beyond the river, we also observe and map spatially variable sources corresponding to thunder. These transient signals have impulsive onsets, but are not well correlated across the network and are attributable to spatially-distributed source regions. Finally, we identify plentiful infrasound corresponding to Reventador's volcanic vent that is associated with unrest. This study demonstrates the utility of dispersed infrasound networks for distinguishing variable sources and improving interpretation of mechanisms of infrasound radiators.

Atom Probe Tomography Analysis of Ag Doping in 2D Layered Material (PbSe) 5(Bi 2Se 3) 3

DOE PAGES

Ren, Xiaochen; Singh, Arunima K.; Fang, Lei; ...

2016-09-07

Impurity doping in two-dimensional (2D) materials can provide a route to tuning electronic properties, so it is important to be able to determine the distribution of dopant atoms within and between layers. Here we report the totnographic mapping of dopants in layered 2D materials with atomic sensitivity and subnanometer spatial resolution using atom, probe tomography (APT). Also, APT analysis shows that Ag dopes both Bi 2Se 3 and PbSe layers in (PbSe) 5(Bi 2Se 3) 3, and correlations :in the position of Ag atoms suggest a pairing across neighboring Bi 2Se 3 and PbSe layers. Finally, density functional theory (DFT)more » calculations confirm the favorability of substitutional-doping for both Pb and Bi and provide insights into the,observed spatial correlations in dopant locations.« less

Analyses and assessments of span wise gust gradient data from NASA B-57B aircraft

NASA Technical Reports Server (NTRS)

Frost, Walter; Chang, Ho-Pen; Ringnes, Erik A.

1987-01-01

Analysis of turbulence measured across the airfoil of a Cambera B-57 aircraft is reported. The aircraft is instrumented with probes for measuring wind at both wing tips and at the nose. Statistical properties of the turbulence are reported. These consist of the standard deviations of turbulence measured by each individual probe, standard deviations and probability distribution of differences in turbulence measured between probes and auto- and two-point spatial correlations and spectra. Procedures associated with calculations of two-point spatial correlations and spectra utilizing data were addressed. Methods and correction procedures for assuring the accuracy of aircraft measured winds are also described. Results are found, in general, to agree with correlations existing in the literature. The velocity spatial differences fit a Gaussian/Bessel type probability distribution. The turbulence agrees with the von Karman turbulence correlation and with two-point spatial correlations developed from the von Karman correlation.

Modeling space-time correlations of velocity fluctuations in wind farms

NASA Astrophysics Data System (ADS)

Lukassen, Laura J.; Stevens, Richard J. A. M.; Meneveau, Charles; Wilczek, Michael

2018-07-01

An analytical model for the streamwise velocity space-time correlations in turbulent flows is derived and applied to the special case of velocity fluctuations in large wind farms. The model is based on the Kraichnan-Tennekes random sweeping hypothesis, capturing the decorrelation in time while including a mean wind velocity in the streamwise direction. In the resulting model, the streamwise velocity space-time correlation is expressed as a convolution of the pure space correlation with an analytical temporal decorrelation kernel. Hence, the spatio-temporal structure of velocity fluctuations in wind farms can be derived from the spatial correlations only. We then explore the applicability of the model to predict spatio-temporal correlations in turbulent flows in wind farms. Comparisons of the model with data from a large eddy simulation of flow in a large, spatially periodic wind farm are performed, where needed model parameters such as spatial and temporal integral scales and spatial correlations are determined from the large eddy simulation. Good agreement is obtained between the model and large eddy simulation data showing that spatial data may be used to model the full temporal structure of fluctuations in wind farms.

Spatial resolution of pace mapping of idiopathic ventricular tachycardia/ectopy originating in the right ventricular outflow tract.

PubMed

Bogun, Frank; Taj, Majid; Ting, Michael; Kim, Hyungjin Myra; Reich, Stephen; Good, Eric; Jongnarangsin, Krit; Chugh, Aman; Pelosi, Frank; Oral, Hakan; Morady, Fred

2008-03-01

Pace mapping has been used to identify the site of origin of focal ventricular arrhythmias. The spatial resolution of pace mapping has not been adequately quantified using currently available three-dimensional mapping systems. The purpose of this study was to determine the spatial resolution of pace mapping in patients with idiopathic ventricular tachycardia or premature ventricular contractions originating in the right ventricular outflow tract. In 16 patients with idiopathic ventricular tachycardia/ectopy from the right ventricular outflow tract, comparisons and classifications of pace maps were performed by two observers (good pace map: match >10/12 leads; inadequate pace map: match < or =10/12 leads) and a customized MATLAB 6.0 program (assessing correlation coefficient and normalized root mean square of the difference (nRMSd) between test and template signals). With an electroanatomic mapping system, the correlation coefficient of each pace map was correlated with the distance between the pacing site and the effective ablation site. The endocardial area within the 10-ms activation isochrone was measured. The ablation procedure was effective in all patients. Sites with good pace maps had a higher correlation coefficient and lower nRMSd than sites with inadequate pace maps (correlation coefficient: 0.96 +/- 0.03 vs 0.76 +/- 0.18, P <.0001; nRMSd: 0.41 +/- 0.16 vs 0.89 +/- 0.39, P <.0001). Using receiver operating characteristic curves, appropriate cutoff values were >0.94 for correlation coefficient (sensitivity 81%, specificity 89%) and < or =0.54 for nRMSd (sensitivity 76%, specificity 80%). Good pace maps were located a mean of 7.3 +/- 5.0 mm from the effective ablation site and had a mean activation time of -24 +/- 7 ms. However, in 3 (18%) of 16 patients, the best pace map was inadequate at the effective ablation site, with an endocardial activation time at these sites of -25 +/- 12 ms. Pace maps with correlation coefficient > or =0.94 were confined to an area of 1.8 +/- 0.6 cm2. The 10-ms isochrone measured 1.2 +/- 0.7 cm2. The spatial resolution of a good pace map for targeting ventricular tachycardia/ectopy is 1.8 cm2 in the right ventricular outflow tract and therefore is inferior to the spatial resolution of activation mapping as assessed by isochronal activation. In approximately 20% of patients, pace mapping is unreliable in identifying the site of origin, possibly due a deeper site of origin and preferential conduction via fibers connecting the focus to the endocardial surface.

Geophysical and solar activity indices

NASA Astrophysics Data System (ADS)

Bossy, L.; Lemaire, J.

1984-04-01

A large number of geophysicists try to correlate their observations with one or even a series of different geophysical or solar activity indices. Yet the right choice of the most appropriate index with which to correlate depends mainly on our understanding of the physical cause-effect relationship between the new set of observations and the index chosen. This best choice will therefore depend on our good understanding of the methods of measurement and derivation of the adopted index in such correlative studies. It relies also on our awareness of the range of applicability of the indices presently available as well as on our understanding of their limitations. It was to achieve these goals that a series of general lectures on geophysical and solar activity indices was organized by L. Bossy and J. Lemaire (Institut d'Aeronomie Spatiale de Belgique (IASB), Brussels), March 26-29, 1984 at Han-sur-Lesse, Belgium.

Hierarchical additive modeling of nonlinear association with spatial correlations--an application to relate alcohol outlet density and neighborhood assault rates.

PubMed

Yu, Qingzhao; Li, Bin; Scribner, Richard Allen

2009-06-30

Previous studies have suggested a link between alcohol outlets and assaults. In this paper, we explore the effects of alcohol availability on assaults at the census tract level over time. In addition, we use a natural experiment to check whether a sudden loss of alcohol outlets is associated with deeper decreasing in assault violence. Several features of the data raise statistical challenges: (1) the association between covariates (for example, the alcohol outlet density of each census tract) and the assault rates may be complex and therefore cannot be described using a linear model without covariates transformation, (2) the covariates may be highly correlated with each other, (3) there are a number of observations that have missing inputs, and (4) there is spatial association in assault rates at the census tract level. We propose a hierarchical additive model, where the nonlinear correlations and the complex interaction effects are modeled using the multiple additive regression trees and the residual spatial association in the assault rates that cannot be explained in the model are smoothed using a conditional autoregressive (CAR) method. We develop a two-stage algorithm that connects the nonparametric trees with CAR to look for important covariates associated with the assault rates, while taking into account the spatial association of assault rates in adjacent census tracts. The proposed method is applied to the Los Angeles assault data (1990-1999). To assess the efficiency of the method, the results are compared with those obtained from a hierarchical linear model. Copyright (c) 2009 John Wiley & Sons, Ltd.

Age-related change in renal corticomedullary differentiation: evaluation with noncontrast-enhanced steady-state free precession (SSFP) MRI with spatially selective inversion pulse using variable inversion time.

PubMed

Noda, Yasufumi; Kanki, Akihiko; Yamamoto, Akira; Higashi, Hiroki; Tanimoto, Daigo; Sato, Tomohiro; Higaki, Atsushi; Tamada, Tsutomu; Ito, Katsuyoshi

2014-07-01

To evaluate age-related change in renal corticomedullary differentiation and renal cortical thickness by means of noncontrast-enhanced steady-state free precession (SSFP) magnetic resonance imaging (MRI) with spatially selective inversion recovery (IR) pulse. The Institutional Review Board of our hospital approved this retrospective study and patient informed consent was waived. This study included 48 patients without renal diseases who underwent noncontrast-enhanced SSFP MRI with spatially selective IR pulse using variable inversion times (TIs) (700-1500 msec). The signal intensity of renal cortex and medulla were measured to calculate renal corticomedullary contrast ratio. Additionally, renal cortical thickness was measured. The renal corticomedullary junction was clearly depicted in all patients. The mean cortical thickness was 3.9 ± 0.83 mm. The mean corticomedullary contrast ratio was 4.7 ± 1.4. There was a negative correlation between optimal TI for the best visualization of renal corticomedullary differentiation and age (r = -0.378; P = 0.001). However, there was no significant correlation between renal corticomedullary contrast ratio and age (r = 0.187; P = 0.20). Similarly, no significant correlation was observed between renal cortical thickness and age (r = 0.054; P = 0.712). In the normal kidney, noncontrast-enhanced SSFP MRI with spatially selective IR pulse can be used to assess renal corticomedullary differentiation and cortical thickness without the influence of aging, although optimal TI values for the best visualization of renal corticomedullary junction were shortened with aging. © 2013 Wiley Periodicals, Inc.

Analysis of field-scale spatial correlations and variations of soil nutrients using geostatistics.

PubMed

Liu, Ruimin; Xu, Fei; Yu, Wenwen; Shi, Jianhan; Zhang, Peipei; Shen, Zhenyao

2016-02-01

Spatial correlations and soil nutrient variations are important for soil nutrient management. They help to reduce the negative impacts of agricultural nonpoint source pollution. Based on the sampled available nitrogen (AN), available phosphorus (AP), and available potassium (AK), soil nutrient data from 2010, the spatial correlation, was analyzed, and the probabilities of the nutrient's abundance or deficiency were discussed. This paper presents a statistical approach to spatial analysis, the spatial correlation analysis (SCA), which was originally developed for describing heterogeneity in the presence of correlated variation and based on ordinary kriging (OK) results. Indicator kriging (IK) was used to assess the susceptibility of excess of soil nutrients based on crop needs. The kriged results showed there was a distinct spatial variability in the concentration of all three soil nutrients. High concentrations of these three soil nutrients were found near Anzhou. As the distance from the center of town increased, the concentration of the soil nutrients gradually decreased. Spatially, the relationship between AN and AP was negative, and the relationship between AP and AK was not clear. The IK results showed that there were few areas with a risk of AN and AP overabundance. However, almost the entire study region was at risk of AK overabundance. Based on the soil nutrient distribution results, it is clear that the spatial variability of the soil nutrients differed throughout the study region. This spatial soil nutrient variability might be caused by different fertilizer types and different fertilizing practices.

Sparse orthogonal population representation of spatial context in the retrosplenial cortex.

PubMed

Mao, Dun; Kandler, Steffen; McNaughton, Bruce L; Bonin, Vincent

2017-08-15

Sparse orthogonal coding is a key feature of hippocampal neural activity, which is believed to increase episodic memory capacity and to assist in navigation. Some retrosplenial cortex (RSC) neurons convey distributed spatial and navigational signals, but place-field representations such as observed in the hippocampus have not been reported. Combining cellular Ca 2+ imaging in RSC of mice with a head-fixed locomotion assay, we identified a population of RSC neurons, located predominantly in superficial layers, whose ensemble activity closely resembles that of hippocampal CA1 place cells during the same task. Like CA1 place cells, these RSC neurons fire in sequences during movement, and show narrowly tuned firing fields that form a sparse, orthogonal code correlated with location. RSC 'place' cell activity is robust to environmental manipulations, showing partial remapping similar to that observed in CA1. This population code for spatial context may assist the RSC in its role in memory and/or navigation.Neurons in the retrosplenial cortex (RSC) encode spatial and navigational signals. Here the authors use calcium imaging to show that, similar to the hippocampus, RSC neurons also encode place cell-like activity in a sparse orthogonal representation, partially anchored to the allocentric cues on the linear track.

Spatial organization and Synchronization in collective swimming of Hemigrammus bleheri

NASA Astrophysics Data System (ADS)

Ashraf, Intesaaf; Ha, Thanh-Tung; Godoy-Diana, Ramiro; Thiria, Benjamin; Halloy, Jose; Collignon, Bertrand; Laboratoire de Physique et Mécanique des Milieux Hétérogènes (PMMH) Team; Laboratoire Interdisciplinaire des Energies de Demain (LIED) Team

2016-11-01

In this work, we study the collective swimming of Hemigrammus bleheri fish using experiments in a shallow swimming channel. We use high-speed video recordings to track the midline kinematics and the spatial organization of fish pairs and triads. Synchronizations are characterized by observance of "out of phase" and "in phase" configurations. We show that the synchronization state is highly correlated to swimming speed. The increase in synchronization led to efficient swimming based on Strouhal number. In case of fish pairs, the collective swimming is 2D and the spatial organization is characterized by two characteristic lengths: the lateral and longitudinal separation distances between fish pairs.For fish triads, different swimming patterns or configurations are observed having three dimensional structures. We performed 3D kinematic analysis by employing 3D reconstruction using the Direct Linear Transformation (DLT). We show that fish still keep their nearest neighbor distance (NND) constant irrespective of swimming speeds and configuration. We also point out characteristic angles between neighbors, hence imposing preferred patterns. At last we will give some perspectives on spatial organization for larger population. Sorbonne Paris City College of Doctoral Schools. European Union Information and Communication Technologies project ASSISIbf, FP7-ICT-FET-601074.

Polarized vortices in optical speckle field: observation of rare polarization singularities.

PubMed

Dupont, Jan; Orlik, Xavier

2015-03-09

Using a recent method able to characterize the polarimetry of a random field with high polarimetric and spatial accuracy even near places of destructive interference, we study polarized optical vortices at a scale below the transverse correlation width of a speckle field. We perform high accuracy polarimetric measurements of known singularities described with an half-integer topological index and we study rare integer index singularities which have, to our knowledge, never been observed in a speckle field.

Solar Wind/Magnetosphere/Ionosphere Coupling and the Temporal and Spatial Evolution of Boundary Layers using Cluster, Polar and other ISTP Satellites

NASA Technical Reports Server (NTRS)

Maynard, Nelson C.

2004-01-01

Our analysis concerns macro and meso-scale aspects of coupling between the IMF and the magnetosphere-ionosphere system, as opposed to the microphysics of determining how electron gyrotropy is broken and merging actually occurs. We correlate observed behaviors at Cluster and at Polar with temporal variations in other regions, such as in the ionosphere as measured by SuperDARN. Addressing problems with simultaneous observations from diverse locations properly constrains our interpretations.

Role of Aedes aegypti (Linnaeus) and Aedes albopictus (Skuse) in local dengue epidemics in Taiwan.

PubMed

Tsai, Pui-Jen; Teng, Hwa-Jen

2016-11-09

Aedes mosquitoes in Taiwan mainly comprise Aedes albopictus and Ae. aegypti. However, the species contributing to autochthonous dengue spread and the extent at which it occurs remain unclear. Thus, in this study, we spatially analyzed real data to determine spatial features related to local dengue incidence and mosquito density, particularly that of Ae. albopictus and Ae. aegypti. We used bivariate Moran's I statistic and geographically weighted regression (GWR) spatial methods to analyze the globally spatial dependence and locally regressed relationship between (1) imported dengue incidences and Breteau indices (BIs) of Ae. albopictus, (2) imported dengue incidences and BI of Ae. aegypti, (3) autochthonous dengue incidences and BI of Ae. albopictus, (4) autochthonous dengue incidences and BI of Ae. aegypti, (5) all dengue incidences and BI of Ae. albopictus, (6) all dengue incidences and BI of Ae. aegypti, (7) BI of Ae. albopictus and human population density, and (8) BI of Ae. aegypti and human population density in 348 townships in Taiwan. In the GWR models, regression coefficients of spatially regressed relationships between the incidence of autochthonous dengue and vector density of Ae. aegypti were significant and positive in most townships in Taiwan. However, Ae. albopictus had significant but negative regression coefficients in clusters of dengue epidemics. In the global bivariate Moran's index, spatial dependence between the incidence of autochthonous dengue and vector density of Ae. aegypti was significant and exhibited positive correlation in Taiwan (bivariate Moran's index = 0.51). However, Ae. albopictus exhibited positively significant but low correlation (bivariate Moran's index = 0.06). Similar results were observed in the two spatial methods between all dengue incidences and Aedes mosquitoes (Ae. aegypti and Ae. albopictus). The regression coefficients of spatially regressed relationships between imported dengue cases and Aedes mosquitoes (Ae. aegypti and Ae. albopictus) were significant in 348 townships in Taiwan. The results indicated that local Aedes mosquitoes do not contribute to the dengue incidence of imported cases. The density of Ae. aegypti positively correlated with the density of human population. By contrast, the density of Ae. albopictus negatively correlated with the density of human population in the areas of southern Taiwan. The results indicated that Ae. aegypti has more opportunities for human-mosquito contact in dengue endemic areas in southern Taiwan. Ae. aegypti, but not Ae. albopictus, and human population density in southern Taiwan are closely associated with an increased risk of autochthonous dengue incidence.

Spatial Autocorrelation Approaches to Testing Residuals from Least Squares Regression.

PubMed

Chen, Yanguang

2016-01-01

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

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

PubMed Central

NAMAYANDE, Motahareh Sadat; NEJADKOORKI, Farhad; NAMAYANDE, Seyedeh Mahdieh; DEHGHAN, Hamidreza

2016-01-01

Background: 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. Methods: 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. Results: 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). Conclusion: 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. PMID:27057527

Spatiotemporal analysis of tumor uptake patterns in dynamic (18)FDG-PET and dynamic contrast enhanced CT.

PubMed

Malinen, Eirik; Rødal, Jan; Knudtsen, Ingerid Skjei; Søvik, Åste; Skogmo, Hege Kippenes

2011-08-01

Molecular and functional imaging techniques such as dynamic positron emission tomography (DPET) and dynamic contrast enhanced computed tomography (DCECT) may provide improved characterization of tumors compared to conventional anatomic imaging. The purpose of the current work was to compare spatiotemporal uptake patterns in DPET and DCECT images. A PET/CT protocol comprising DCECT with an iodine based contrast agent and DPET with (18)F-fluorodeoxyglucose was set up. The imaging protocol was used for examination of three dogs with spontaneous tumors of the head and neck at sessions prior to and after fractionated radiotherapy. Software tools were developed for downsampling the DCECT image series to the PET image dimensions, for segmentation of tracer uptake pattern in the tumors and for spatiotemporal correlation analysis of DCECT and DPET images. DCECT images evaluated one minute post injection qualitatively resembled the DPET images at most imaging sessions. Segmentation by region growing gave similar tumor extensions in DCECT and DPET images, with a median Dice similarity coefficient of 0.81. A relatively high correlation (median 0.85) was found between temporal tumor uptake patterns from DPET and DCECT. The heterogeneity in tumor uptake was not significantly different in the DPET and DCECT images. The median of the spatial correlation was 0.72. DCECT and DPET gave similar temporal wash-in characteristics, and the images also showed a relatively high spatial correlation. Hence, if the limited spatial resolution of DPET is considered adequate, a single DPET scan only for assessing both tumor perfusion and metabolic activity may be considered. However, further work on a larger number of cases is needed to verify the correlations observed in the present study.

Frontiers in Fluctuation Spectroscopy: Measuring protein dynamics and protein spatio-temporal connectivity

NASA Astrophysics Data System (ADS)

Digman, Michelle

Fluorescence fluctuation spectroscopy has evolved from single point detection of molecular diffusion to a family of microscopy imaging correlation tools (i.e. ICS, RICS, STICS, and kICS) useful in deriving spatial-temporal dynamics of proteins in living cells The advantage of the imaging techniques is the simultaneous measurement of all points in an image with a frame rate that is increasingly becoming faster with better sensitivity cameras and new microscopy modalities such as the sheet illumination technique. A new frontier in this area is now emerging towards a high level of mapping diffusion rates and protein dynamics in the 2 and 3 dimensions. In this talk, I will discuss the evolution of fluctuation analysis from the single point source to mapping diffusion in whole cells and the technology behind this technique. In particular, new methods of analysis exploit correlation of molecular fluctuations originating from measurement of fluctuation correlations at distant points (pair correlation analysis) and methods that exploit spatial averaging of fluctuations in small regions (iMSD). For example the pair correlation fluctuation (pCF) analyses done between adjacent pixels in all possible radial directions provide a window into anisotropic molecular diffusion. Similar to the connectivity atlas of neuronal connections from the MRI diffusion tensor imaging these new tools will be used to map the connectome of protein diffusion in living cells. For biological reaction-diffusion systems, live single cell spatial-temporal analysis of protein dynamics provides a mean to observe stochastic biochemical signaling in the context of the intracellular environment which may lead to better understanding of cancer cell invasion, stem cell differentiation and other fundamental biological processes. National Institutes of Health Grant P41-RRO3155.

The spatial diffusion of norovirus epidemics over three seasons in Tokyo.

PubMed

Inaida, S; Shobugawa, Y; Matsuno, S; Saito, R; Suzuki, H

2015-02-01

We studied the spatial trend of norovirus (NoV) epidemics using sentinel gastroenteritis surveillance data for patients aged <15 years (n = 140) in the Tokyo area for the 2006-2007 to 2008-2009 seasons utilizing the kriging method of geographical information system (GIS). This is the first study of the spreading pattern of NoV epidemics using sentinel surveillance data. Correlations of sentinel cases between the seasons and with demographic data were examined to identify the trend and related factors. A similar pattern of diffusion was observed over the seasons, and its mean correlation between seasons was significantly high. A higher number of cases were found in the peripheral area, which surrounds the most populated central area, and showed a correlation with the ratio of the children population (r = 0·321, P < 0·01) and the ratio of residents in larger families (r = 0·263, P < 0·01). While NoV susceptibility remained, the results suggest a transmission route in the local community as a possible epidemic factor. Prevention with focus on the peripheral area is desirable.

The cerebral correlates of subliminal emotions: an eleoencephalographic study with emotional hybrid faces.

PubMed

Prete, Giulia; Capotosto, Paolo; Zappasodi, Filippo; Laeng, Bruno; Tommasi, Luca

2015-12-01

In a high-resolution electroencephalographic study, participants evaluated the friendliness level of upright and inverted 'hybrid faces', i.e. facial photos containing a subliminal emotional core in the low spatial frequencies (< 6 cycles/image), superimposed on a neutral expression in the rest of the spatial frequencies. Upright happy and angry faces were judged as more friendly or less friendly than neutral faces, respectively. We observed the time course of cerebral correlates of these stimuli with event-related potentials (ERPs), confirming that hybrid faces elicited the posterior emotion-related and face-related components (P1, N170 and P2), previously shown to be engaged by non-subliminal emotional stimuli. In addition, these components were stronger in the right hemisphere and were both enhanced and delayed by face inversion. A frontal positivity (210-300 ms) was stronger for emotional than for neutral faces, and for upright than for inverted faces. Hence, hybrid faces represent an original approach in the study of subliminal emotions, which appears promising for investigating their electrophysiological correlates. © 2015 Federation of European Neuroscience Societies and John Wiley & Sons Ltd.

Quantum measurement-induced antiferromagnetic order and density modulations in ultracold Fermi gases in optical lattices

NASA Astrophysics Data System (ADS)

Mazzucchi, Gabriel; Caballero-Benitez, Santiago F.; Mekhov, Igor B.

2016-08-01

Ultracold atomic systems offer a unique tool for understanding behavior of matter in the quantum degenerate regime, promising studies of a vast range of phenomena covering many disciplines from condensed matter to quantum information and particle physics. Coupling these systems to quantized light fields opens further possibilities of observing delicate effects typical of quantum optics in the context of strongly correlated systems. Measurement backaction is one of the most funda- mental manifestations of quantum mechanics and it is at the core of many famous quantum optics experiments. Here we show that quantum backaction of weak measurement can be used for tailoring long-range correlations of ultracold fermions, realizing quantum states with spatial modulations of the density and magnetization, thus overcoming usual requirement for a strong interatomic interactions. We propose detection schemes for implementing antiferromagnetic states and density waves. We demonstrate that such long-range correlations cannot be realized with local addressing, and they are a consequence of the competition between global but spatially structured backaction of weak quantum measurement and unitary dynamics of fermions.

Four-Photon Imaging with Thermal Light

NASA Astrophysics Data System (ADS)

Wen, Feng; Xue, Xinxin; Zhang, Xun; Yuan, Chenzhi; Sun, Jia; Song, Jianping; Zhang, Yanpeng

2014-10-01

In a near-field four-photon correlation measurement, ghost imaging with classical incoherent light is investigated. By applying the Klyshko advanced-wave picture, we consider the properties of four-photon spatial correlation and find that the fourth-order spatial correlation function can be decomposed into multiple lower-order correlation functions. On the basis of the spatial correlation properties, a proof-of-principle four-photon ghost imaging is proposed, and the effect of each part in a fourth-order correlation function on imaging is also analyzed. In addition, the similarities and differences among ghost imaging by fourth-, second-, and third-order correlations are also discussed. It is shown that the contrast and visibility of fourth-order correlated imaging are improved significantly, while the resolution is unchanged. Such studies can be very useful in better understanding multi photon interference and multi-channel correlation imaging.

Correlation analysis of fracture arrangement in space

NASA Astrophysics Data System (ADS)

Marrett, Randall; Gale, Julia F. W.; Gómez, Leonel A.; Laubach, Stephen E.

2018-03-01

We present new techniques that overcome limitations of standard approaches to documenting spatial arrangement. The new techniques directly quantify spatial arrangement by normalizing to expected values for randomly arranged fractures. The techniques differ in terms of computational intensity, robustness of results, ability to detect anti-correlation, and use of fracture size data. Variation of spatial arrangement across a broad range of length scales facilitates distinguishing clustered and periodic arrangements-opposite forms of organization-from random arrangements. Moreover, self-organized arrangements can be distinguished from arrangements due to extrinsic organization. Traditional techniques for analysis of fracture spacing are hamstrung because they account neither for the sequence of fracture spacings nor for possible coordination between fracture size and position, attributes accounted for by our methods. All of the new techniques reveal fractal clustering in a test case of veins, or cement-filled opening-mode fractures, in Pennsylvanian Marble Falls Limestone. The observed arrangement is readily distinguishable from random and periodic arrangements. Comparison of results that account for fracture size with results that ignore fracture size demonstrates that spatial arrangement is dominated by the sequence of fracture spacings, rather than coordination of fracture size with position. Fracture size and position are not completely independent in this example, however, because large fractures are more clustered than small fractures. Both spatial and size organization of veins here probably emerged from fracture interaction during growth. The new approaches described here, along with freely available software to implement the techniques, can be applied with effect to a wide range of structures, or indeed many other phenomena such as drilling response, where spatial heterogeneity is an issue.

Spatial Autocorrelation Can Generate Stronger Correlations between Range Size and Climatic Niches Than the Biological Signal - A Demonstration Using Bird and Mammal Range Maps.

PubMed

Boucher-Lalonde, Véronique; Currie, David J

2016-01-01

Species' geographic ranges could primarily be physiological tolerances drawn in space. Alternatively, geographic ranges could be only broadly constrained by physiological climatic tolerances: there could generally be much more proximate constraints on species' ranges (dispersal limitation, biotic interactions, etc.) such that species often occupy a small and unpredictable subset of tolerable climates. In the literature, species' climatic tolerances are typically estimated from the set of conditions observed within their geographic range. Using this method, studies have concluded that broader climatic niches permit larger ranges. Similarly, other studies have investigated the biological causes of incomplete range filling. But, when climatic constraints are measured directly from species' ranges, are correlations between species' range size and climate necessarily consistent with a causal link? We evaluated the extent to which variation in range size among 3277 bird and 1659 mammal species occurring in the Americas is statistically related to characteristics of species' realized climatic niches. We then compared how these relationships differed from the ones expected in the absence of a causal link. We used a null model that randomizes the predictor variables (climate), while retaining their broad spatial autocorrelation structure, thereby removing any causal relationship between range size and climate. We found that, although range size is strongly positively related to climatic niche breadth, range filling and, to a lesser extent, niche position in nature, the observed relationships are not always stronger than expected from spatial autocorrelation alone. Thus, we conclude that equally strong relationships between range size and climate would result from any processes causing ranges to be highly spatially autocorrelated.

Spatial Autocorrelation Can Generate Stronger Correlations between Range Size and Climatic Niches Than the Biological Signal — A Demonstration Using Bird and Mammal Range Maps

PubMed Central

Boucher-Lalonde, Véronique; Currie, David J.

2016-01-01

Species’ geographic ranges could primarily be physiological tolerances drawn in space. Alternatively, geographic ranges could be only broadly constrained by physiological climatic tolerances: there could generally be much more proximate constraints on species’ ranges (dispersal limitation, biotic interactions, etc.) such that species often occupy a small and unpredictable subset of tolerable climates. In the literature, species’ climatic tolerances are typically estimated from the set of conditions observed within their geographic range. Using this method, studies have concluded that broader climatic niches permit larger ranges. Similarly, other studies have investigated the biological causes of incomplete range filling. But, when climatic constraints are measured directly from species’ ranges, are correlations between species’ range size and climate necessarily consistent with a causal link? We evaluated the extent to which variation in range size among 3277 bird and 1659 mammal species occurring in the Americas is statistically related to characteristics of species’ realized climatic niches. We then compared how these relationships differed from the ones expected in the absence of a causal link. We used a null model that randomizes the predictor variables (climate), while retaining their broad spatial autocorrelation structure, thereby removing any causal relationship between range size and climate. We found that, although range size is strongly positively related to climatic niche breadth, range filling and, to a lesser extent, niche position in nature, the observed relationships are not always stronger than expected from spatial autocorrelation alone. Thus, we conclude that equally strong relationships between range size and climate would result from any processes causing ranges to be highly spatially autocorrelated. PMID:27855201

A variance-decomposition approach to investigating multiscale habitat associations

USGS Publications Warehouse

Lawler, J.J.; Edwards, T.C.

2006-01-01

The recognition of the importance of spatial scale in ecology has led many researchers to take multiscale approaches to studying habitat associations. However, few of the studies that investigate habitat associations at multiple spatial scales have considered the potential effects of cross-scale correlations in measured habitat variables. When cross-scale correlations in such studies are strong, conclusions drawn about the relative strength of habitat associations at different spatial scales may be inaccurate. Here we adapt and demonstrate an analytical technique based on variance decomposition for quantifying the influence of cross-scale correlations on multiscale habitat associations. We used the technique to quantify the variation in nest-site locations of Red-naped Sapsuckers (Sphyrapicus nuchalis) and Northern Flickers (Colaptes auratus) associated with habitat descriptors at three spatial scales. We demonstrate how the method can be used to identify components of variation that are associated only with factors at a single spatial scale as well as shared components of variation that represent cross-scale correlations. Despite the fact that no explanatory variables in our models were highly correlated (r < 0.60), we found that shared components of variation reflecting cross-scale correlations accounted for roughly half of the deviance explained by the models. These results highlight the importance of both conducting habitat analyses at multiple spatial scales and of quantifying the effects of cross-scale correlations in such analyses. Given the limits of conventional analytical techniques, we recommend alternative methods, such as the variance-decomposition technique demonstrated here, for analyzing habitat associations at multiple spatial scales. ?? The Cooper Ornithological Society 2006.

Symmetric cumulants as a probe of the proton substructure at LHC energies

NASA Astrophysics Data System (ADS)

Albacete, Javier L.; Petersen, Hannah; Soto-Ontoso, Alba

2018-03-01

We present a systematic study of the normalized symmetric cumulants, NSC(n,m), at the eccentricity level in proton-proton interactions at √{ s } = 13TeV within a wounded hot spot approach. We focus our attention on the influence of spatial correlations between the proton constituents, in our case gluonic hot spots, on this observable. We notice that the presence of short-range repulsive correlations between the hot spots systematically decreases the values of NSC (2 , 3) and NSC (2 , 4) in mid- to ultra-central collisions while increases them in peripheral interactions. In the case of NSC (2 , 3) we find that, as suggested by data, an anti-correlation of ε2 and ε3 in ultra-central collisions, i.e. NSC (2 , 3) < 0, is possible within the correlated scenario while it never occurs without correlations when the number of gluonic hot spots is set to three. We attribute this fact to the decisive role of correlations on enlarging the probability of interaction topologies that reduce the value of NSC (2 , 3) and, eventually, make it negative. Further, we explore the dependence of our conclusions on the number of hot spots, the values of the hot spot radius and the repulsive core distance. Our results add evidence to the idea that considering spatial correlations between the subnucleonic degrees of freedom of the proton may have a strong impact on the initial state properties of proton-proton interactions [1].

Impact of spatial proxies on the representation of bottom-up emission inventories: A satellite-based analysis

NASA Astrophysics Data System (ADS)

Geng, Guannan; Zhang, Qiang; Martin, Randall V.; Lin, Jintai; Huo, Hong; Zheng, Bo; Wang, Siwen; He, Kebin

2017-03-01

Spatial proxies used in bottom-up emission inventories to derive the spatial distributions of emissions are usually empirical and involve additional levels of uncertainty. Although uncertainties in current emission inventories have been discussed extensively, uncertainties resulting from improper spatial proxies have rarely been evaluated. In this work, we investigate the impact of spatial proxies on the representation of gridded emissions by comparing six gridded NOx emission datasets over China developed from the same magnitude of emissions and different spatial proxies. GEOS-Chem-modeled tropospheric NO2 vertical columns simulated from different gridded emission inventories are compared with satellite-based columns. The results show that differences between modeled and satellite-based NO2 vertical columns are sensitive to the spatial proxies used in the gridded emission inventories. The total population density is less suitable for allocating NOx emissions than nighttime light data because population density tends to allocate more emissions to rural areas. Determining the exact locations of large emission sources could significantly strengthen the correlation between modeled and observed NO2 vertical columns. Using vehicle population and an updated road network for the on-road transport sector could substantially enhance urban emissions and improve the model performance. When further applying industrial gross domestic product (IGDP) values for the industrial sector, modeled NO2 vertical columns could better capture pollution hotspots in urban areas and exhibit the best performance of the six cases compared to satellite-based NO2 vertical columns (slope = 1.01 and R2 = 0. 85). This analysis provides a framework for information from satellite observations to inform bottom-up inventory development. In the future, more effort should be devoted to the representation of spatial proxies to improve spatial patterns in bottom-up emission inventories.

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

PubMed

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

On the discrepancy between observed and CMIP5 multi-model simulated Barents Sea winter sea ice decline

NASA Astrophysics Data System (ADS)

Li, Dawei; Zhang, Rong; Knutson, Thomas R.

2017-04-01

This study aims to understand the relative roles of external forcing versus internal climate variability in causing the observed Barents Sea winter sea ice extent (SIE) decline since 1979. We identify major discrepancies in the spatial patterns of winter Northern Hemisphere sea ice concentration trends over the satellite period between observations and CMIP5 multi-model mean externally forced response. The CMIP5 externally forced decline in Barents Sea winter SIE is much weaker than that observed. Across CMIP5 ensemble members, March Barents Sea SIE trends have little correlation with global mean surface air temperature trends, but are strongly anti-correlated with trends in Atlantic heat transport across the Barents Sea Opening (BSO). Further comparison with control simulations from coupled climate models suggests that enhanced Atlantic heat transport across the BSO associated with regional internal variability may have played a leading role in the observed decline in winter Barents Sea SIE since 1979.

Method and system for spatially variable rate application of agricultural chemicals based on remotely sensed vegetation data

NASA Technical Reports Server (NTRS)

Lewis, Mark David (Inventor); Seal, Michael R. (Inventor); Hood, Kenneth Brown (Inventor); Johnson, James William (Inventor)

2007-01-01

Remotely sensed spectral image data are used to develop a Vegetation Index file which represents spatial variations of actual crop vigor throughout a field that is under cultivation. The latter information is processed to place it in a format that can be used by farm personnel to correlate and calibrate it with actually observed crop conditions existing at control points within the field. Based on the results, farm personnel formulate a prescription request, which is forwarded via email or FTP to a central processing site, where the prescription is prepared. The latter is returned via email or FTP to on-side farm personnel, who can load it into a controller on a spray rig that directly applies inputs to the field at a spatially variable rate.

Method and apparatus for spatially variable rate application of agricultural chemicals based on remotely sensed vegetation data

NASA Technical Reports Server (NTRS)

Hood, Kenneth Brown (Inventor); Johnson, James William (Inventor); Seal, Michael R. (Inventor); Lewis, Mark David (Inventor)

2004-01-01

Remotely sensed spectral image data are used to develop a Vegetation Index file which represents spatial variations of actual crop vigor throughout a field that is under cultivation. The latter information is processed to place it in a format that can be used by farm personnel to correlate and calibrate it with actually observed crop conditions existing at control points within the field. Based on the results, farm personnel formulate a prescription request, which is forwarded via email or FTP to a central processing site, where the prescription is prepared. The latter is returned via email or FTP to on-side farm personnel, who can load it into a controller on a spray rig that directly applies inputs to the field at a spatially variable rate.

Measurement of nanoscale three-dimensional diffusion in the interior of living cells by STED-FCS.

PubMed

Lanzanò, Luca; Scipioni, Lorenzo; Di Bona, Melody; Bianchini, Paolo; Bizzarri, Ranieri; Cardarelli, Francesco; Diaspro, Alberto; Vicidomini, Giuseppe

2017-07-06

The observation of molecular diffusion at different spatial scales, and in particular below the optical diffraction limit (<200 nm), can reveal details of the subcellular topology and its functional organization. Stimulated-emission depletion microscopy (STED) has been previously combined with fluorescence correlation spectroscopy (FCS) to investigate nanoscale diffusion (STED-FCS). However, stimulated-emission depletion fluorescence correlation spectroscopy has only been used successfully to reveal functional organization in two-dimensional space, such as the plasma membrane, while, an efficient implementation for measurements in three-dimensional space, such as the cellular interior, is still lacking. Here we integrate the STED-FCS method with two analytical approaches, the recent separation of photons by lifetime tuning and the fluorescence lifetime correlation spectroscopy, to simultaneously probe diffusion in three dimensions at different sub-diffraction scales. We demonstrate that this method efficiently provides measurement of the diffusion of EGFP at spatial scales tunable from the diffraction size down to ∼80 nm in the cytoplasm of living cells.The measurement of molecular diffusion at sub-diffraction scales has been achieved in 2D space using STED-FCS, but an implementation for 3D diffusion is lacking. Here the authors present an analytical approach to probe diffusion in 3D space using STED-FCS and measure the diffusion of EGFP at different spatial scales.

Neural Correlates of Object-Associated Choice Behavior in the Perirhinal Cortex of Rats

PubMed Central

Ahn, Jae-Rong

2015-01-01

The perirhinal cortex (PRC) is reportedly important for object recognition memory, with supporting physiological evidence obtained largely from primate studies. Whether neurons in the rodent PRC also exhibit similar physiological correlates of object recognition, however, remains to be determined. We recorded single units from the PRC in a PRC-dependent, object-cued spatial choice task in which, when cued by an object image, the rat chose the associated spatial target from two identical discs appearing on a touchscreen monitor. The firing rates of PRC neurons were significantly modulated by critical events in the task, such as object sampling and choice response. Neuronal firing in the PRC was correlated primarily with the conjunctive relationships between an object and its associated choice response, although some neurons also responded to the choice response alone. However, we rarely observed a PRC neuron that represented a specific object exclusively regardless of spatial response in rats, although the neurons were influenced by the perceptual ambiguity of the object at the population level. Some PRC neurons fired maximally after a choice response, and this post-choice feedback signal significantly enhanced the neuronal specificity for the choice response in the subsequent trial. Our findings suggest that neurons in the rat PRC may not participate exclusively in object recognition memory but that their activity may be more dynamically modulated in conjunction with other variables, such as choice response and its outcomes. PMID:25632144

Association analysis between spatiotemporal variation of vegetation greenness and precipitation/temperature in the Yangtze River Basin (China).

PubMed

Cui, Lifang; Wang, Lunche; Singh, Ramesh P; Lai, Zhongping; Jiang, Liangliang; Yao, Rui

2018-05-23

The variation in vegetation greenness provides good understanding of the sustainable management and monitoring of land surface ecosystems. The present paper discusses the spatial-temporal changes in vegetation and controlling factors in the Yangtze River Basin (YRB) using Global Inventory Modeling and Mapping Studies (GIMMS) Normalized Difference Vegetation Index (NDVI) for the period 2001-2013. Theil-Sen Median trend analysis, Pearson correlation coefficients, and residual analysis have been used, which shows decreasing trend of the annual mean NDVI over the whole YRB. Spatially, the regions with significant decreasing trends were mainly located in parts of central YRB, and pronounced increasing trends were observed in parts of the eastern and western YRB. The mean NDVI during spring and summer seasons increased, while it decreased during autumn and winter seasons. The seasonal mean NDVI shows spatial heterogeneity due to the vegetation types. The correlation analysis shows a positive relation between NDVI and temperature over most of the YRB, whereas NDVI and precipitation show a negative correlation. The residual analysis shows an increase in NDVI in parts of eastern and western YRB and the decrease in NDVI in the small part of Yangtze River Delta (YRD) and the mid-western YRB due to human activities. In general, climate factors were the principal drivers of NDVI variation in YRB in recent years.

Collagen Organization in Facet Capsular Ligaments Varies With Spinal Region and With Ligament Deformation.

PubMed

Ban, Ehsan; Zhang, Sijia; Zarei, Vahhab; Barocas, Victor H; Winkelstein, Beth A; Picu, Catalin R

2017-07-01

The spinal facet capsular ligament (FCL) is primarily comprised of heterogeneous arrangements of collagen fibers. This complex fibrous structure and its evolution under loading play a critical role in determining the mechanical behavior of the FCL. A lack of analytical tools to characterize the spatial anisotropy and heterogeneity of the FCL's microstructure has limited the current understanding of its structure-function relationships. Here, the collagen organization was characterized using spatial correlation analysis of the FCL's optically obtained fiber orientation field. FCLs from the cervical and lumbar spinal regions were characterized in terms of their structure, as was the reorganization of collagen in stretched cervical FCLs. Higher degrees of intra- and intersample heterogeneity were found in cervical FCLs than in lumbar specimens. In the cervical FCLs, heterogeneity was manifested in the form of curvy patterns formed by collections of collagen fibers or fiber bundles. Tensile stretch, a common injury mechanism for the cervical FCL, significantly increased the spatial correlation length in the stretch direction, indicating an elongation of the observed structural features. Finally, an affine estimation for the change of correlation length under loading was performed which gave predictions very similar to the actual values. These findings provide structural insights for multiscale mechanical analyses of the FCLs from various spinal regions and also suggest methods for quantitative characterization of complex tissue patterns.

Observations of the Winter Thermal Structure of Lake Superior

NASA Astrophysics Data System (ADS)

Titze, Daniel James

Moored thermistor strings that span the water column have been deployed at up to seven locations throughout Lake Superior from 2005 through present, producing a unique year-round record of the thermal structure of a large lake. This extensive temperature record reveals significant interannual and spatial variability in Lake Superior's winter heat content, thermocline depth, and phenology. Of particular mention is a stark contrast in thermal structure between the cold, icy winter of 2009 and the much warmer winter of 2012, during which especially strong and weak negative stratification was observed, respectively. Significant interannual and spatial variability was also observed in Lake Superior ice cover, as shown through data extracted from Ice Mapping System satellite imagery (NOAA/NESDIS 2004). When water column heat content was estimated from temperature data and analyzed in concert with lake ice-cover data, it was found that ice cover can inhibit heat flux between the lake and the atmosphere, and that spatial variability in ice cover can translate into spatial variability in end-of-winter heat content. Such variability in end-of-winter heat content is found to be preserved through the spring warming season, and is strongly correlated with variability in the timing of the onset of summer stratification, with regions that have warmer end-of-winter water columns stratifying earlier than regions with colder end-of-winter water-columns.

Pluto: Distribution of ices and coloring agents from New Horizons LEISA observations

NASA Astrophysics Data System (ADS)

Cruikshank, Dale P.; Grundy, William M.; Stern, S. Alan; Olkin, Catherine B.; Cook, Jason C.; Dalle Ore, Cristina M.; Binzel, Richard P.; Earle, Alissa M.; Ennico, Kimberly; Jennings, Donald E.; Howett, Carly J. A.; Linscott, Ivan R.; Lunsford, Allen W.; Parker, Alex H.; Parker, Joel W.; Protopapa, Silvia; Reuter, Dennis C.; Singer, Kelsi N.; Spencer, John R.; Tsang, Constantine C. C.; Verbiscer, Anne J.; Weaver, Harold A.; Young, Leslie A.

2015-11-01

Pluto was observed at high spatial resolution (maximum ~3 km/px) by the New Horizons LEISA imaging spectrometer. LEISA is a component of the Ralph instrument (Reuter, D.C., Stern, S.A., Scherrer, J., et al. 2008, Space Sci. Rev. 140, 129) and affords a spectral resolving power of 240 in the wavelength range 1.25-2.5 µm, and 560 in the range 2.1-2.25 µm. Spatially resolved spectra with LEISA are used to map the distributions of the known ices on Pluto (N2, CH4, CO) and to search for other surface components. The spatial distribution of volatile ices is compared with the distribution of the coloring agent(s) on Pluto's surface. The correlation of ice abundance and the degree of color (ranging from yellow to orange to dark red) is consistent with the presence of tholins, which are refractory organic solids of complex structure and high molecular weight, with colors consistent with those observed on Pluto. Tholins are readily synthesized in the laboratory by energetic processing of mixtures of the ices (N2, CH4, CO) known on Pluto's surface. We present results returned from the spacecraft to date obtained from the analysis of the high spatial resolution dataset obtained near the time of closest approach to the planet. Supported by NASA’s New Horizons project.

Revisiting crash spatial heterogeneity: A Bayesian spatially varying coefficients approach.

PubMed

Xu, Pengpeng; Huang, Helai; Dong, Ni; Wong, S C

2017-01-01

This study was performed to investigate the spatially varying relationships between crash frequency and related risk factors. A Bayesian spatially varying coefficients model was elaborately introduced as a methodological alternative to simultaneously account for the unstructured and spatially structured heterogeneity of the regression coefficients in predicting crash frequencies. The proposed method was appealing in that the parameters were modeled via a conditional autoregressive prior distribution, which involved a single set of random effects and a spatial correlation parameter with extreme values corresponding to pure unstructured or pure spatially correlated random effects. A case study using a three-year crash dataset from the Hillsborough County, Florida, was conducted to illustrate the proposed model. Empirical analysis confirmed the presence of both unstructured and spatially correlated variations in the effects of contributory factors on severe crash occurrences. The findings also suggested that ignoring spatially structured heterogeneity may result in biased parameter estimates and incorrect inferences, while assuming the regression coefficients to be spatially clustered only is probably subject to the issue of over-smoothness. Copyright © 2016 Elsevier Ltd. All rights reserved.

Spatial variability of soil carbon stock in the Urucu river basin, Central Amazon-Brazil.

PubMed

Ceddia, Marcos Bacis; Villela, André Luis Oliveira; Pinheiro, Érika Flávia Machado; Wendroth, Ole

2015-09-01

The Amazon Forest plays a major role in C sequestration and release. However, few regional estimates of soil organic carbon (SOC) stock in this ecoregion exist. One of the barriers to improve SOC estimates is the lack of recent soil data at high spatial resolution, which hampers the application of new methods for mapping SOC stock. The aims of this work were: (i) to quantify SOC stock under undisturbed vegetation for the 0-30 and the 0-100 cm under Amazon Forest; (ii) to correlate the SOC stock with soil mapping units and relief attributes and (iii) to evaluate three geostatistical techniques to generate maps of SOC stock (ordinary, isotopic and heterotopic cokriging). The study site is located in the Central region of Amazon State, Brazil. The soil survey covered the study site that has an area of 80 km(2) and resulted in a 1:10,000 soil map. It consisted of 315 field observations (96 complete soil profiles and 219 boreholes). SOC stock was calculated by summing C stocks by horizon, determined as a product of BD, SOC and the horizon thickness. For each one of the 315 soil observations, relief attributes were derived from a topographic map to understand SOC dynamics. The SOC stocks across 30 and 100 cm soil depth were 3.28 and 7.32 kg C m(-2), respectively, which is, 34 and 16%, lower than other studies. The SOC stock is higher in soils developed in relief forms exhibiting well-drained soils, which are covered by Upland Dense Tropical Rainforest. Only SOC stock in the upper 100 cm exhibited spatial dependence allowing the generation of spatial variability maps based on spatial (co)-regionalization. The CTI was inversely correlated with SOC stock and was the only auxiliary variable feasible to be used in cokriging interpolation. The heterotopic cokriging presented the best performance for mapping SOC stock. Copyright © 2015 Elsevier B.V. All rights reserved.

Comparisons of Anvil Cirrus Spatial Characteristics between Airborne Observations in DC3 Campaign and WRF Simulations

NASA Astrophysics Data System (ADS)

D'Alessandro, J.; Diao, M.; Chen, M.

2015-12-01

John D'Alessandro1, Minghui Diao1, Ming Chen2, George Bryan2, Hugh Morrison21. Department of Meteorology and Climate Science, San Jose State University2. Mesoscale & Microscale Meteorology Division, National Center for Atmospheric Research, Boulder, CO, 80301 Ice crystal formation requires the prerequisite condition of ice supersaturation, i.e., relative humidity with respect to ice (RHi) greater than 100%. The formation and evolution of ice supersaturated regions (ISSRs) has large impact on the subsequent formation of ice clouds. To examine the characteristics of simulated ice supersaturated regions at various model spatial resolutions, case studies between airborne in-situ measurements in the NSF Deep Convective, Clouds and Chemistry (DC3) campaign (May - June 2012) and WRF simulations are conducted in this work. Recent studies using ~200 m in-situ observations showed that ice supersaturated regions are mostly around 1 km in horizontal scale (Diao et al. 2014). Yet it is still unclear if such observed characteristics can be represented by WRF simulations at various spatial resolutions. In this work, we compare the WRF simulated anvil cirrus spatial characteristics with those observed in the DC3 campaign over the southern great plains in US. The WRF model is run at 1 km and 3 km horizontal grid spacing with a recent update of Thompson microphysics scheme. Our comparisons focus on the spatial characteristics of ISSRs and cirrus clouds, including the distributions of their horizontal scales, the maximum relative humidity with respect to ice (RHi) and the relationship between RHi and temperature. Our previous work on the NCAR CM1 cloud-resolving model shows that the higher resolution runs (i.e., 250m and 1km) generally have better agreement with observations than the coarser resolution (4km) runs. We will examine if similar trend exists for WRF simulations in deep convection cases. In addition, we will compare the simulation results between WRF and CM1, particularly for spatial correlations between ISSRs and cirrus and their evolution (based on the method of Diao et al. 2013). Overall, our work will help to assess the representation of ISSRs and cirrus in WRF simulation based on comparisons with in-situ observations.

Correlation Length of Energy-Containing Structures in the Base of the Solar Corona

NASA Astrophysics Data System (ADS)

Abramenko, V.; Zank, G. P.; Dosch, A. M.; Yurchyshyn, V.

2013-12-01

An essential parameter for models of coronal heating and fast solar wind acceleration that relay on the dissipation of MHD turbulence is the characteristic energy-containing length of the squared velocity and magnetic field fluctuations transverse to the mean magnetic field inside a coronal hole (CH) at the base of the corona. The characteristic length scale defines directly the heating rate. Rather surprisingly, almost nothing is known observationally about this critical parameter. Currently, only a very rough estimate of characteristic length was obtained based on the fact that the network spacing is about 30000 km. We attempted estimation of this parameter from observations of photospheric random motions and magnetic fields measured in the photosphere inside coronal holes. We found that the characteristic length scale in the photosphere is about 600-2000 km, which is much smaller than that adopted in previous models. Our results provide a critical input parameter for current models of coronal heating and should yield an improved understanding of fast solar wind acceleration. Fig. 1-- Plotted is the natural logarithm of the correlation function of the transverse velocity fluctuations u^2 versus the spatial lag r for the two CHs. The color code refers to the accumulation time intervals of 2 (blue), 5 (green), 10 (red), and 20 (black) minutes. The values of the Batchelor integral length λ the correlation length ς and the e-folding length L in km are shown. Fig. 2-- Plot of the natural logarithm of the correlation function of magnetic fluctuations b^2 versus the spatial lag r. The insert shows this plot with linear axes.

Interannual variations in surface urban heat island intensity and associated drivers in China.

PubMed

Yao, Rui; Wang, Lunche; Huang, Xin; Zhang, Wenwen; Li, Junli; Niu, Zigeng

2018-09-15

The spatial, diurnal and seasonal variations of surface urban heat islands (SUHIs) have been investigated in many places, but we still have limited understanding of the interannual variations of SUHIs and associated drivers. In this study, the interannual variations in SUHI intensity (SUHII, derived from MODIS land surface temperature (LST) data (8-day composites of twice-daily observations), urban LST minus rural) and their relationships with climate variability and urbanization were analyzed in 31 cities in China for the period 2001-2015. Significant increasing trends of SUHII were observed in 71.0%, 58.1%, 25.8% and 54.8% the cities in summer days (SDs), summer nights (SNs), winter days (WDs) and winter nights (WNs), respectively. Pearson's correlation analyses were first performed from a temporal perspective, which were different from a spatial perspective as previous studies. The results showed that the SUHII in SDs and WDs was negatively correlated with the background LST and mean air temperature in most of the cities. The nighttime SUHII in most cities was negatively and positively correlated with total precipitation and total sunshine duration, respectively. Average wind speed has little effect on SUHII. Decreasing vegetation and increased population were the main factors that contributed to the increased SUHII in SDs and SNs, while albedo only influenced the SUHII in WDs. In addition, Pearson's correlation analyses across cities showed that cities with higher decreasing rates of vegetation exhibited higher increasing rates of the SUHII in SDs and WDs. Cities with larger population growth rates do not necessarily have higher increasing rates of SUHII. Copyright © 2018 Elsevier Ltd. All rights reserved.

[Explore the spatial and temporal patterns of water pollution in the Yincungang canal of the Lake Taihu basin, China].

PubMed

Yang, Xiao-Ying; Luo, Xing-Zhang; Zheng, Zheng; Fang, Shu-Bo

2012-09-01

Two high-density snap-shot samplings were conducted along the Yincungang canal, one important tributary of the Lake Tai, in April (low flow period) and June (high flow period) of 2010. Geostatistical analysis based on the river network distance was used to analyze the spatial and temporal patterns of the pollutant concentrations along the canal with an emphasis on chemical oxygen demand (COD) and total nitrogen (TN). Study results have indicated: (1) COD and TN concentrations display distinctly different spatial and temporal patterns between the low and high flow periods. COD concentration in June is lower than that in April, while TN concentration has the contrary trend. (2) COD load is relatively constant during the period between the two monitoring periods. The spatial correlation structure of COD is exponential for both April and June, and the change of COD concentration is mainly influenced by hydrological conditions. (3) Nitrogen load from agriculture increased significantly during the period between the two monitoring periods. Large amount of chaotic fertilizing by individual farmers has led to the loss of the spatial correlation among the observed TN concentrations. Hence, changes of TN concentration in June are under the dual influence of agricultural fertilizing and hydrological conditions. In the view of the complex hydrological conditions and serious water pollution in the Lake Taihu region, geostatistical analysis is potentially a useful tool for studying the characteristics of pollutant distribution and making predictions in the region.

A Proposal for Phase 4 of the Forest Inventory and Analysis Program

Treesearch

Ronald E. McRoberts

2005-01-01

Maps of forest cover were constructed using observations from forest inventory plots, Landsat Thematic Mapper satellite imagery, and a logistic regression model. Estimates of mean proportion forest area and the variance of the mean were calculated for circular study areas with radii ranging from 1 km to 15 km. The spatial correlation among pixel predictions was...

Multisite rainfall downscaling and disaggregation in a tropical urban area

NASA Astrophysics Data System (ADS)

Lu, Y.; Qin, X. S.

2014-02-01

A systematic downscaling-disaggregation study was conducted over Singapore Island, with an aim to generate high spatial and temporal resolution rainfall data under future climate-change conditions. The study consisted of two major components. The first part was to perform an inter-comparison of various alternatives of downscaling and disaggregation methods based on observed data. This included (i) single-site generalized linear model (GLM) plus K-nearest neighbor (KNN) (S-G-K) vs. multisite GLM (M-G) for spatial downscaling, (ii) HYETOS vs. KNN for single-site disaggregation, and (iii) KNN vs. MuDRain (Multivariate Rainfall Disaggregation tool) for multisite disaggregation. The results revealed that, for multisite downscaling, M-G performs better than S-G-K in covering the observed data with a lower RMSE value; for single-site disaggregation, KNN could better keep the basic statistics (i.e. standard deviation, lag-1 autocorrelation and probability of wet hour) than HYETOS; for multisite disaggregation, MuDRain outperformed KNN in fitting interstation correlations. In the second part of the study, an integrated downscaling-disaggregation framework based on M-G, KNN, and MuDRain was used to generate hourly rainfall at multiple sites. The results indicated that the downscaled and disaggregated rainfall data based on multiple ensembles from HadCM3 for the period from 1980 to 2010 could well cover the observed mean rainfall amount and extreme data, and also reasonably keep the spatial correlations both at daily and hourly timescales. The framework was also used to project future rainfall conditions under HadCM3 SRES A2 and B2 scenarios. It was indicated that the annual rainfall amount could reduce up to 5% at the end of this century, but the rainfall of wet season and extreme hourly rainfall could notably increase.

Etiological Distinction of Working Memory Components in Relation to Mathematics

PubMed Central

Lukowski, Sarah L.; Soden, Brooke; Hart, Sara A.; Thompson, Lee A.; Kovas, Yulia; Petrill, Stephen A.

2014-01-01

Working memory has been consistently associated with mathematics achievement, although the etiology of these relations remains poorly understood. The present study examined the genetic and environmental underpinnings of math story problem solving, timed calculation, and untimed calculation alongside working memory components in 12-year-old monozygotic (n = 105) and same-sex dizygotic (n = 143) twin pairs. Results indicated significant phenotypic correlation between each working memory component and all mathematics outcomes (r = 0.18 – 0.33). Additive genetic influences shared between the visuo-spatial sketchpad and mathematics achievement was significant, accounting for roughly 89% of the observed correlation. In addition, genetic covariance was found between the phonological loop and math story problem solving. In contrast, despite there being a significant observed relationship between phonological loop and timed and untimed calculation, there was no significant genetic or environmental covariance between the phonological loop and timed or untimed calculation skills. Further analyses indicated that genetic overlap between the visuo-spatial sketchpad and math story problem solving and math fluency was distinct from general genetic factors, whereas g, phonological loop, and mathematics shared generalist genes. Thus, although each working memory component was related to mathematics, the etiology of their relationships may be distinct. PMID:25477699

Resolution of the EPR Paradox for Fermion Spin Correlations

NASA Astrophysics Data System (ADS)

Close, Robert

2011-10-01

The EPR paradox addresses the question of whether a physical system can have a definite state independent of its measurement. Bell's Theorem places limits on correlations between local measurements of particles whose properties are established prior to measurement. Experimental violation of Bell's theorem has been regarded as evidence against the existence of a definite state prior to measurement. We model fermions as having a spatial distribution of spin values, so that a Stern-Gerlach device samples the spin distribution differently at different orientations. The computed correlations agree with quantum mechanical predictions and experimental observations. Bell's Theorem is not applicable because for any sampling of angles, different points on the sphere have different density of states.

Pre-Processed Recursive Lattice Reduction for Complexity Reduction in Spatially and Temporally Correlated MIMO Channels

NASA Astrophysics Data System (ADS)

An, Chan-Ho; Yang, Janghoon; Jang, Seunghun; Kim, Dong Ku

In this letter, a pre-processed lattice reduction (PLR) scheme is developed for the lattice reduction aided (LRA) detection of multiple input multiple-output (MIMO) systems in spatially correlated channel. The PLR computes the LLL-reduced matrix of the equivalent matrix, which is the product of the present channel matrix and unimodular transformation matrix for LR of spatial correlation matrix, rather than the present channel matrix itself. In conjunction with PLR followed by recursive lattice reduction (RLR) scheme [7], pre-processed RLR (PRLR) is shown to efficiently carry out the LR of the channel matrix, especially for the burst packet message in spatially and temporally correlated channel while matching the performance of conventional LRA detection.

Removing the Impact of Correlated PSF Uncertainties in Weak Lensing

NASA Astrophysics Data System (ADS)

Lu, Tianhuan; Zhang, Jun; Dong, Fuyu; Li, Yingke; Liu, Dezi; Fu, Liping; Li, Guoliang; Fan, Zuhui

2018-05-01

Accurate reconstruction of the spatial distributions of the point-spread function (PSF) is crucial for high precision cosmic shear measurements. Nevertheless, current methods are not good at recovering the PSF fluctuations of high spatial frequencies. In general, the residual PSF fluctuations are spatially correlated, and therefore can significantly contaminate the correlation functions of the weak lensing signals. We propose a method to correct for this contamination statistically, without any assumptions on the PSF and galaxy morphologies or their spatial distribution. We demonstrate our idea with the data from the W2 field of CFHTLenS.

Recent recovery of surface wind speed after decadal decrease: a focus on South Korea

NASA Astrophysics Data System (ADS)

Kim, JongChun; Paik, Kyungrock

2015-09-01

We investigate the multi-decadal variability of observed surface wind speed around South Korea. It is found that surface wind speed exhibits decreasing trend from mid-1950s until 2003, which is similar with the trends reported for other parts of the world. However, the decreasing trend ceases and becomes unclear since then. It is revealed that decreasing wind speed until 2003 is strongly associated with the decreasing trend of the spatial variance in both atmospheric pressure and air temperature across the East Asia for the same period. On the contrary, break of decreasing trend in surface wind speed since 2003 is associated with increasing spatial variance in surface temperature over the East Asia. Ground observation shows that surface wind speed and air temperature exhibit highly negative correlations for both summer and winter prior to 2003. However, since 2003, the correlations differ between seasons. We suggest that mechanisms behind the recent wind speed trend are different between summer and winter. This is on the basis of an interesting finding that air temperature has decreased while surface temperature has increased during winter months since 2003. We hypothesize that such contrasting temperature trends indicate more frequent movement of external cold air mass into the region since 2003. We also hypothesize that increasing summer wind speed is driven by intrusion of warm air mass into the region which is witnessed via increasing spatial variance in surface temperature across East Asia and the fact that both air and surface temperature rise together.

Investigation of Influential Factors for Bicycle Crashes Using a Spatiotemporal Model

NASA Astrophysics Data System (ADS)

Gill, G.; Sakrani, T.; Cheng, W.; Zhou, J.

2017-09-01

Despite the numerous potential advantages of indulging in bicycling, such as elevation of health and environment along with mitigation of congestion, the cyclists are a vulnerable group of commuters which is exposed to safety risks. This study aims to investigate the explanatory variables at transportation planning level which have a significant impact on the bicycle crashes. To account for the serial changes around the built environment, the linear time trend as well as time-varying coefficients are utilized for the covariates. These model modifications help account for the variations in the environment which may escape the incorporated variables due to lack of robustness in data. Also, to incorporate the interaction of roadway, demographic, and socioeconomic features within a Traffic Analysis Zone (TAZ), with the bicycle crashes of that area, a spatial correlation is integrated. This spatial correlation accounts for the spatially structured random effects which capture the unobserved heterogeneity and add towards building more comprehensive model with relatively precise estimates. Two different age groups, the student population in the TAZs, the presence of arterial roads and bike lanes, were observed to be statistically significant variables related with bicycle crashes. These observations will guide the transportation planning organizations which focus on the entity of TAZ while developing policies. The results of the current study establish a quantifies relationship between the significant factors and the crash count which will enable the planners to choose the most cost-efficient, yet most productive, factors which needs to be addressed for mitigation of crashes.

Broadband Radio Polarimetry of Fornax A. I. Depolarized Patches Generated by Advected Thermal Material from NGC 1316

NASA Astrophysics Data System (ADS)

Anderson, C. S.; Gaensler, B. M.; Heald, G. H.; O’Sullivan, S. P.; Kaczmarek, J. F.; Feain, I. J.

2018-03-01

We present observations and analysis of the polarized radio emission from the nearby radio galaxy Fornax A over 1.28–3.1 GHz, using data from the Australia Telescope Compact Array. In this, the first of two associated papers, we use modern broadband polarimetric techniques to examine the nature and origin of conspicuous low-polarization (low-p) patches in the lobes. We resolve the (low-p) patches and find that their low fractional polarization is associated with complicated frequency-dependent interference in the polarized signal generated by Faraday effects along the line of sight (LOS). The low-p patches are spatially correlated with interfaces in the magnetic structure of the lobe, across which the LOS-projected magnetic field changes direction. Spatial correlations with the sky-projected magnetic field orientation and structure in total intensity are also identified and discussed. We argue that the (low-p) patches, along with associated reversals in the LOS magnetic field and other related phenomena, are best explained by the presence of { \\mathcal O }({10}9) {M}ȯ of magnetized thermal plasma in the lobes, structured in shells or filaments, and likely advected from the interstellar medium of NCG 1316 or its surrounding intracluster medium. Our study underscores the power and utility of spatially resolved, broadband, full-polarization radio observations to reveal new facets of flow behaviors and magneto-ionic structure in radio lobes and their interplay with the surrounding environment.

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

Yun, Youngjoo; Cho, Se-Hyung; Kim, Jaeheon

We present the first images of the v = 1 and v = 2 J = 1 → 0 SiO maser lines taken with KaVA, i.e., the combined array of the Korean Very Long Baseline Interferometry (VLBI) Network and the VLBI Exploration of Radio Astrometry (VERA), toward the OH/IR star WX Psc. The combination of long and short antenna baselines enabled us to detect a large number of maser spots, which exhibit a typical ring-like structure in both the v = 1 and v = 2 J = 1 → 0 SiO masers as those that have been found inmore » previous VLBI observational results of WX Psc. The relative alignment of the v = 1 and v = 2 SiO maser spots are precisely derived from astrometric analysis, due to the absolute coordinates of the reference maser spot that were well determined in an independent astrometric observation with VERA. The superposition of the v = 1 and v = 2 maser spot maps shows a good spatial correlation between the v = 1 and v = 2 SiO maser features. Nevertheless, it is also shown that the v = 2 SiO maser spot is distributed in an inner region compared to the v = 1 SiO maser by about 0.5 mas on average. These results provide good support for the recent theoretical studies of the SiO maser pumping, in which both the collisional and the radiative pumping predict the strong spatial correlation and the small spatial discrepancy between the v = 1 and v = 2 SiO maser.« less

Relationship between synoptic scale weather systems and column averaged atmospheric CO2

NASA Astrophysics Data System (ADS)

Naja, M.; Yaremchuk, A.; Onishi, R.; Maksyutov, S.; Inoue, G.

2005-12-01

Analysis of the atmospheric CO2 observations with transport models contributes to the understanding of the geographical distributions of CO2 sources and sinks. Space-borne sensors could be advantageous for CO2 measurements as they can provide wider spatial and temporal coverage. Inversion studies have suggested requirement of better than 1% precision for the space-borne observations. Since sources and sinks are inferred from spatial and temporal gradients in CO2, the space-borne observations must have no significant geographically varying biases. To study the dynamical biases in column CO2 due to possible correlation between clouds and atmospheric CO2 at synoptic scale, we have made simulations of CO2 (1988-2003) using NIES tracer transport model. Model resolution is 2.5o x 2.5o in horizontal and it has 15 vertical sigma-layers. Fluxes for (1) fossil fuels, (2) terrestrial biosphere (CASA NEP), (3) the oceans, and (4) inverse model derived monthly regional fluxes from 11 land and 11 ocean regions are used. SVD truncation is used to filter out noise in the inverse model flux time series. Model reproduces fairly well CO2 global trend and observed time series at monitoring sites around the globe. Lower column CO2 concentration is simulated inside cyclonic systems in summer over North hemispheric continental areas. Surface pressure is used as a proxy for dynamics and it is demonstrated that anomalies in column averaged CO2 has fairly good correlation with the anomalies in surface pressure. Positive correlation, as high as 0.7, has been estimated over parts of Siberia and N. America in summer time. Our explanation is based on that the low-pressure system is associated the upward motion, which leads to lower column CO2 values over these regions due to lifting of CO2-depleted summertime PBL air, and higher column CO2 over source areas. A sensitivity study without inverse model fluxes shows same correlation. The low-pressure systems' induced negative biases are 0.4-0.6 ppmv in summer over Siberia. Therefore it is essential to consider this bias due to covariance with vertical motion, while analyzing the column CO2 from space-borne observations together with in-situ observations, because most optical observations are not available under cloudy conditions typical for the low-pressure system.

The neural correlates of volitional attention: A combined fMRI and ERP study.

PubMed

Bengson, Jesse J; Kelley, Todd A; Mangun, George R

2015-07-01

Studies of visual-spatial attention typically use instructional cues to direct attention to a relevant location, but in everyday vision, attention is often focused volitionally, in the absence of external signals. Although investigations of cued attention comprise hundreds of behavioral and physiological studies, remarkably few studies of voluntary attention have addressed the challenging question of how spatial attention is initiated and controlled in the absence of external instructions, which we refer to as willed attention. To explore this question, we employed a trial-by-trial spatial attention task using electroencephalography and functional magnetic resonance imaging (fMRI). The fMRI results reveal a unique network of brain regions for willed attention that includes the anterior cingulate cortex, left middle frontal gyrus (MFG), and the left and right anterior insula (AI). We also observed two event-related potentials (ERPs) associated with willed attention; one with a frontal distribution occurring 250-350 ms postdecision cue onset (EWAC: Early Willed Attention Component), and another occurring between 400 and 800 ms postdecision-cue onset (WAC: Willed Attention Component). In addition, each ERP component uniquely correlated across subjects with different willed attention-specific sites of BOLD activation. The EWAC was correlated with the willed attention-specific left AI and left MFG activations and the later WAC was correlated only with left AI. These results offer a comprehensive and novel view of the electrophysiological and anatomical profile of willed attention and further illustrate the relationship between scalp-recorded ERPs and the BOLD response. © 2015 Wiley Periodicals, Inc.

A Spatial Correlation Model of Permeability on the Columbia River Plateau

NASA Astrophysics Data System (ADS)

Jayne, R., Jr.; Pollyea, R. M.

2017-12-01

This study presents a spatial correlation model of regional scale permeability variability within the Columbia River Basalt Group (CRBG). The data were compiled from the literature, and include 893 aquifer test results from 598 individual wells. In order to quantify the spatial variation of permeability within the CRBG, three experimental variograms (two horizontal and one vertical) are calculated and then fit with a linear combination of mathematical models. The horizontal variograms show there is a 4.5:1 anisotropy ratio for the permeability correlation structure with a long-range correlation of 35 km at N40°E. The km-scale range of these variograms suggests that there is regional control on permeability within the CRBG. One plausible control on the permeability distribution is that rapid crustal loading during CRBG emplacement ( 80% over 1M years) resulted in an isostatic response where the Columbia Plateau had previously undergone subsidence. To support this hypothesis, we calculate a 200 m moving average of all permeability values with depth. This calculation shows that permeability generally follows a systematic decay until 1,100 m depth, beyond which the 200 m moving average permeability increases 3 orders of magnitude. Since basalt fracture networks govern permeability on Columbia River Plateau, this observation is consistent with basal flexure causing tensile stress that counteract lithostatic loading, thus maintaining higher than expected permeability at depth within the Columbia River Basalt Group. These results may have important implications for regional CRBG groundwater management, as well as engineered reservoirs for carbon capture and sequestration and nuclear waste storage.

Temporal and spatial correlation patterns of air pollutants in Chinese cities

PubMed Central

Dai, Yue-Hua

2017-01-01

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

Effect of fatigue/ageing on the lithium distribution in cylinder-type Li-ion batteries

NASA Astrophysics Data System (ADS)

Mühlbauer, M. J.; Dolotko, O.; Hofmann, M.; Ehrenberg, H.; Senyshyn, A.

2017-04-01

The lithium concentration in the graphite anode of fatigued (cycled 1000 times at 25 °C) Li-ion cell of 18650-type has been probed non-destructively by spatially resolved neutron diffraction. The amount x of Li in LixC6 has been determined in a central plane of a cylinder-type Li-ion cell. A radial mesh with a gauge volume of 2 × 2 × 20 mm3 was used. Besides the evidently lower lithiation grade, caused by a lack of free movable lithium and a loss of electrolyte, a development of fatigue-driven spatial lithium inhomogeneities has been observed in radial direction. Observed changes have been discussed in light of their correlations to an increase of the internal cell resistance and to a change of the electrolyte concentration.

Monitoring arid lands using AVHRR-observed visible reflectance and SMMR37-GHz polarization difference

NASA Technical Reports Server (NTRS)

Choudhury, B. J.

1990-01-01

Visible reflectance along a transect through the Sahel and Sudan zones of Africa has been derived from observations by the AVHRR on the NOAA-7 and NOAA-9 satellites and compared with concurrent observations of the 37-GHz polarization difference by the SMMR on the Nimbus-7 satellite. The study period was January 1982 to December 1986, which included an unprecedented drought during 1984 over the Sahel zone. While spatial and temporal patterns of these two data sets are found to be highly correlated, there are also quantitative differences which need to be understood.

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

NASA Technical Reports Server (NTRS)

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

2013-01-01

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

Kinematics of [CII] Emission in Trumpler 14 & Carina I Probed with Stratospheric Terahertz Observatory

NASA Astrophysics Data System (ADS)

Seo, Youngmin; Goldsmith, Paul; Walker, Christopher; Kulesa, Craig; STO2 Team

2018-01-01

We present observations of the Trumpler 14 / Carina I regions carried out with the Stratospheric Terahertz Observatory 2 (STO2). The Trumpler 14 / Carina I region is in the west part of the Carina Nebula, which is one of the most active star-forming regions in the Milky Way. The Trumpler 14 / Carina I region is a promising place to study multiple, interacting phases of the ISM, including photon-dominated regions, HII regions, and dense molecular clouds. We observed Trumpler 14 / Carina I in the 158 μm transition of [CII] with a spatial resolution of 48 arcseconds and a velocity resolution of 0.17 km/s. The observations cover a 0.25°by 0.28°area with the center position at l= 297.33° b= -0.60°. We found that the [CII] emission is extended covering roughly 80% of the observed area with >5 K intensity. The peak intensity of [CII] is located four arcminutes southwest of Trumpler 14 and one arcminute east of the CO peak intensity of Carina I. The kinematics show that [CII] structures are spatially and spectrally correlated with the surfaces of CO clumps illuminated by Eta Carinae and Trumpler 14. The [CII] emission also shows a good correlation with dust continuum emission at 160 μm, which is typically originating from heated dust grains to ~20 K. Our results show layered structures of photon-dominated regions in the Trumpler 14 / Carina I region.

Increases in tropical rainfall driven by changes in frequency of organized deep convection.

PubMed

Tan, Jackson; Jakob, Christian; Rossow, William B; Tselioudis, George

2015-03-26

Increasing global precipitation has been associated with a warming climate resulting from a strengthening of the hydrological cycle. This increase, however, is not spatially uniform. Observations and models have found that changes in rainfall show patterns characterized as 'wet-gets-wetter' and 'warmer-gets-wetter'. These changes in precipitation are largely located in the tropics and hence are probably associated with convection. However, the underlying physical processes for the observed changes are not entirely clear. Here we show from observations that most of the regional increase in tropical precipitation is associated with changes in the frequency of organized deep convection. By assessing the contributions of various convective regimes to precipitation, we find that the spatial patterns of change in the frequency of organized deep convection are strongly correlated with observed change in rainfall, both positive and negative (correlation of 0.69), and can explain most of the patterns of increase in rainfall. In contrast, changes in less organized forms of deep convection or changes in precipitation within organized deep convection contribute less to changes in precipitation. Our results identify organized deep convection as the link between changes in rainfall and in the dynamics of the tropical atmosphere, thus providing a framework for obtaining a better understanding of changes in rainfall. Given the lack of a distinction between the different degrees of organization of convection in climate models, our results highlight an area of priority for future climate model development in order to achieve accurate rainfall projections in a warming climate.

Static charge-density-wave order in the superconducting state of La 2 - x Ba x CuO 4

DOE PAGES

Thampy, V.; Chen, X. M.; Cao, Y.; ...

2017-06-15

Charge-density-wave (CDW) correlations feature prominently in the phase diagram of the cuprates, motivating competing theories of whether fluctuating CDW correlations aid superconductivity or whether static CDW order coexists with superconductivity in inhomogeneous or spatially modulated states. Here we report Cu L-edge resonant x-ray photon correlation spectroscopy measurements of CDW correlations in superconducting La 2–xBa xCuO 4, x = 0.11. Static CDW order is shown to exist in the superconducting state at low temperatures and to persist up to at least 85% of the CDW transition temperature. As a result, we discuss the implications of our observations for how nominally competingmore » order parameters can coexist in the cuprates.« less

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

NASA Astrophysics Data System (ADS)

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.

Thermal behaviour of nanofluids confined in nanochannels

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

Frank, Michael, E-mail: d.drikakis@cranfield.ac.uk; Drikakis, Dimitris, E-mail: d.drikakis@cranfield.ac.uk; Asproulis, Nikolaos, E-mail: d.drikakis@cranfield.ac.uk

2015-02-17

This work investigates the effect of spatial restriction on the thermal properties of nanofluids. Using Molecular Dynamics simulations, a Copper-Argon nanofluid is restricted within idealized walls. The thermal conductivity of the suspension is calculated using the Green-Kubo relations and is correlated with the volume fraction of the copper particles within the system as well as the channel width. The thermal conductivity is further broken down into its individual components in the three dimensions, revealing anisotropy between the directions parallel and normal to the channel walls. The observed thermodynamic patterns are justified by considering how the spatial restriction affects the liquidmore » structure around the nanoparticle.« less

Two-dimensional mapping of polarizations of rhombohedral nanostructures in the orthorhombic phase of KNbO3 by the combined use of scanning transmission electron microscopy and convergent-beam electron diffraction

NASA Astrophysics Data System (ADS)

Tsuda, Kenji; Tanaka, Michiyoshi

2015-08-01

Rhombohedral nanostructures previously found in the orthorhombic phase of KNbO3, by convergent-beam electron diffraction [Tsuda et al., Appl. Phys. Lett. 102, 051913 (2013)], have been investigated by the combined use of scanning transmission electron microscopy and convergent-beam electron diffraction. Two-dimensional distributions of the rhombohedral nanostructures, or nanometer-scale spatial fluctuations of polarization clusters, have been successfully visualized. The correlation length of the observed spatial fluctuations of local polarizations is related to the cpc/apc ratio and the transition entropy.

Temporal, Spatial, and Spectral Variability at Ivanpah Playa Vicarious Calibration Site

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

Villa-Aleman, E.

2003-01-07

The Savannah River Technology Center (SRTC) conducted four reflectance vicarious calibrations at Ivanpah Playa, California since July 2000 in support of the MTI satellite. The multi-year study shows temporal, spatial and spectral variability at the playa. The temporal variability in the wavelength dependent reflectance and emissivity across the playa suggests a dependency with precipitation during the winter and early spring seasons. Satellite imagery acquired on September and November 2000, May 2001 and March 2002 in conjunction with ground truth during the September, May and March campaigns and water precipitation records were used to demonstrate the correlation observed at the playa

Structure identification within a transitioning swept-wing boundary layer

NASA Astrophysics Data System (ADS)

Chapman, Keith Lance

1997-08-01

Extensive measurements are made in a transitioning swept-wing boundary layer using hot-film, hot-wire and cross-wire anemometry. The crossflow-dominated flow contains stationary vortices that breakdown near mid-chord. The most amplified vortex wavelength is forced by the use of artificial roughness elements near the leading edge. Two-component velocity and spanwise surface shear-stress correlation measurements are made at two constant chord locations, before and after transition. Streamwise surface shear stresses are also measured through the entire transition region. Correlation techniques are used to identify stationary structures in the laminar regime and coherent structures in the turbulent regime. Basic techniques include observation of the spatial correlations and the spatially distributed auto-spectra. The primary and secondary instability mechanisms are identified in the spectra in all measured fields. The primary mechanism is seen to grow, cause transition and produce large-scale turbulence. The secondary mechanism grows through the entire transition region and produces the small-scale turbulence. Advanced techniques use linear stochastic estimation (LSE) and proper orthogonal decomposition (POD) to identify the spatio-temporal evolutions of structures in the boundary layer. LSE is used to estimate the instantaneous velocity fields using temporal data from just two spatial locations and the spatial correlations. Reference locations are selected using maximum RMS values to provide the best available estimates. POD is used to objectively determine modes characteristic of the measured flow based on energy. The stationary vortices are identified in the first laminar modes of each velocity component and shear component. Experimental evidence suggests that neighboring vortices interact and produce large coherent structures with spanwise periodicity at double the stationary vortex wavelength. An objective transition region detection method is developed using streamwise spatial POD solutions which isolate the growth of the primary and secondary instability mechanisms in the first and second modes, respectively. Temporal evolutions of dominant POD modes in all measured fields are calculated. These scalar POD coefficients contain the integrated characteristics of the entire field, greatly reducing the amount of data to characterize the instantaneous field. These modes may then be used to train future flow control algorithms based on neural networks.

Variability of Relative Sea Level Rise: Spatial and Temporal Correlations in Northwest Gulf of Mexico

NASA Astrophysics Data System (ADS)

Tissot, P.; Reisinger, A. S.; Besonen, M. R.

2017-12-01

While our understanding of global sea level rise and its budget has made great progress over the past decade, the spatial and temporal variability of relative sea level rise along the coasts still needs to be better understood and quantified. We developed a technique to reduce the confidence intervals associated with relative sea level rise (RSLR) estimates for 15 tide gauges located along the Texas coast for the period 1993-2016. Seasonally detrended monthly mean water levels are highly correlated after removal of station-specific RSLR trends, which allows for the quantification of a common, low frequency oceanic signal. RSLR confidence intervals are reduced from over 1.9 mm/yr, on average 2.3mm, to less than 1.1 mm/yr, on average 0.7 mm/yr after removing this common signal. The resulting RSLR rates range from 3.0 to 8.4 mm/yr. The range is wider than the longer-term rates of 5.3, 3.8 and 1.9 mm/yr measured from north to south by the three National Water Level Observation Network (NWLON) stations covering the study area (over different and longer time spans). The results emphasize the importance of the spatial variability of the vertical land motion component of RSLR. The temporal variability of the coherent oceanic signal is not significantly correlated to the ENSO signal for the study period and is only weakly correlated to the AMO and PDO climate indices. The coherence of the signal is further investigated by comparison with other locations along the Gulf of Mexico and along the Northeast Atlantic coast. The results are discussed while considering strong local processes along the Northwest Gulf of Mexico, such as wind forcing and intermittent eddies and the spatially broader influence of the Gulf Stream. The local significance of the RSLR spatial and temporal differences are discussed in terms of the differences in inundation frequency for nuisance type flooding including comparing the time span to reach a probability of at least one nuisance flood event per year.

Structure Identification Within a Transitioning Swept-Wing Boundary Layer

NASA Technical Reports Server (NTRS)

Chapman, Keith; Glauser, Mark

1996-01-01

Extensive measurements are made in a transitioning swept-wing boundary layer using hot-film, hot-wire and cross-wire anemometry. The crossflow-dominated flow contains stationary vortices that breakdown near mid-chord. The most amplified vortex wavelength is forced by the use of artificial roughness elements near the leading edge. Two-component velocity and spanwise surface shear-stress correlation measurements are made at two constant chord locations, before and after transition. Streamwise surface shear stresses are also measured through the entire transition region. Correlation techniques are used to identify stationary structures in the laminar regime and coherent structures in the turbulent regime. Basic techniques include observation of the spatial correlations and the spatially distributed auto-spectra. The primary and secondary instability mechanisms are identified in the spectra in all measured fields. The primary mechanism is seen to grow, cause transition and produce large-scale turbulence. The secondary mechanism grows through the entire transition region and produces the small-scale turbulence. Advanced techniques use Linear Stochastic Estimation (LSE) and Proper Orthogonal Decomposition (POD) to identify the spatio-temporal evolutions of structures in the boundary layer. LSE is used to estimate the instantaneous velocity fields using temporal data from just two spatial locations and the spatial correlations. Reference locations are selected using maximum RMS values to provide the best available estimates. POD is used to objectively determine modes characteristic of the measured flow based on energy. The stationary vortices are identified in the first laminar modes of each velocity component and shear component. Experimental evidence suggests that neighboring vortices interact and produce large coherent structures with spanwise periodicity at double the stationary vortex wavelength. An objective transition region detection method is developed using streamwise spatial POD solutions which isolate the growth of the primary and secondary instability mechanisms in the first and second modes, respectively. Temporal evolutions of dominant POD modes in all measured fields are calculated. These scalar POD coefficients contain the integrated characteristics of the entire field, greatly reducing the amount of data to characterize the instantaneous field. These modes may then be used to train future flow control algorithms based on neural networks.

An underestimated role of precipitation frequency in regulating summer soil moisture

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

Wu, Chaoyang; Chen, Jing M.; Pumpanen, Jukka

2012-04-26

Soil moisture induced droughts are expected to become more frequent under future global climate change. Precipitation has been previously assumed to be mainly responsible for variability in summer soil moisture. However, little is known about the impacts of precipitation frequency on summer soil moisture, either interannually or spatially. To better understand the temporal and spatial drivers of summer drought, 415 site yr measurements observed at 75 flux sites world wide were used to analyze the temporal and spatial relationships between summer soil water content (SWC) and the precipitation frequencies at various temporal scales, i.e., from half-hourly, 3, 6, 12 andmore » 24 h measurements. Summer precipitation was found to be an indicator of interannual SWC variability with r of 0.49 (p < 0.001) for the overall dataset. However, interannual variability in summer SWC was also significantly correlated with the five precipitation frequencies and the sub-daily precipitation frequencies seemed to explain the interannual SWC variability better than the total of precipitation. Spatially, all these precipitation frequencies were better indicators of summer SWC than precipitation totals, but these better performances were only observed in non-forest ecosystems. Our results demonstrate that precipitation frequency may play an important role in regulating both interannual and spatial variations of summer SWC, which has probably been overlooked or underestimated. However, the spatial interpretation should carefully consider other factors, such as the plant functional types and soil characteristics of diverse ecoregions.« less

Estimating planktonic diversity through spatial dominance patterns in a model ocean.

PubMed

Soccodato, Alice; d'Ovidio, Francesco; Lévy, Marina; Jahn, Oliver; Follows, Michael J; De Monte, Silvia

2016-10-01

In the open ocean, the observation and quantification of biodiversity patterns is challenging. Marine ecosystems are indeed largely composed by microbial planktonic communities whose niches are affected by highly dynamical physico-chemical conditions, and whose observation requires advanced methods for morphological and molecular classification. Optical remote sensing offers an appealing complement to these in-situ techniques. Global-scale coverage at high spatiotemporal resolution is however achieved at the cost of restrained information on the local assemblage. Here, we use a coupled physical and ecological model ocean simulation to explore one possible metrics for comparing measures performed on such different scales. We show that a large part of the local diversity of the virtual plankton ecosystem - corresponding to what accessible by genomic methods - can be inferred from crude, but spatially extended, information - as conveyed by remote sensing. Shannon diversity of the local community is indeed highly correlated to a 'seascape' index, which quantifies the surrounding spatial heterogeneity of the most abundant functional group. The error implied in drastically reducing the resolution of the plankton community is shown to be smaller in frontal regions as well as in regions of intermediate turbulent energy. On the spatial scale of hundreds of kms, patterns of virtual plankton diversity are thus largely sustained by mixing communities that occupy adjacent niches. We provide a proof of principle that in the open ocean information on spatial variability of communities can compensate for limited local knowledge, suggesting the possibility of integrating in-situ and satellite observations to monitor biodiversity distribution at the global scale. Copyright © 2016 Elsevier B.V. All rights reserved.

Intercomparison of Recent Anomaly Time-Series of OLR as Observed by CERES and Computed Using AIRS Products

NASA Technical Reports Server (NTRS)

Susskind, Joel; Molnar, Gyula; Iredell, Lena; Loeb, Norman G.

2011-01-01

This paper compares recent spatial and temporal anomaly time series of OLR as observed by CERES and computed based on AIRS retrieved surface and atmospheric geophysical parameters over the 7 year time period September 2002 through February 2010. This time period is marked by a substantial decrease of OLR, on the order of +/-0.1 W/sq m/yr, averaged over the globe, and very large spatial variations of changes in OLR in the tropics, with local values ranging from -2.8 W/sq m/yr to +3.1 W/sq m/yr. Global and Tropical OLR both began to decrease significantly at the onset of a strong La Ni a in mid-2007. Late 2009 is characterized by a strong El Ni o, with a corresponding change in sign of both Tropical and Global OLR anomalies. The spatial patterns of the 7 year short term changes in AIRS and CERES OLR have a spatial correlation of 0.97 and slopes of the linear least squares fits of anomaly time series averaged over different spatial regions agree on the order of +/-0.01 W/sq m/yr. This essentially perfect agreement of OLR anomaly time series derived from observations by two different instruments, determined in totally independent and different manners, implies that both sets of results must be highly stable. This agreement also validates the anomaly time series of the AIRS derived products used to compute OLR and furthermore indicates that anomaly time series of AIRS derived products can be used to explain the factors contributing to anomaly time series of OLR.

Near-surface tomography of southern California from noise cross-correlation H/V measurements

NASA Astrophysics Data System (ADS)

Muir, J. B.; Tsai, V. C.

2016-12-01

The development of noise cross-correlation techniques constitutes one of the major advances in observational seismology in the past 15 years. The first data derived from noise cross correlations were surface wave phase velocities, but as the technique matures many more observables of noise cross-correlations are being used in seismic studies. One such observable is the horizontal-to-vertical amplitude ratio (H/V) of noise cross-correlations. We interpret the H/V ratio of noise cross correlations in terms of Rayleigh wave ellipticity. We have inverted the H/V of Rayleigh waves observed in noise cross-correlation signals to develop a 3D tomogram of Southern California. This technique has recently been employed (e.g. Lin et al. 2014) on a continental scale, using data from the Transportable Array in the period range of 8-24s. The finer inter-station spacing of the SCSN allows retrieval of high signal-to-noise ratio Rayleigh waves at a period of as low as 2s, significantly improving the vertical resolution of the resulting tomography. In addition, horizontal resolution is naturally improved by increased station density. This study constitutes a useful addition to traditional phase-velocity based tomographic inversions due to the localized sensitivity of H/V measurements to the near surface of the measurement station site. The continuous data of 222 permanent broadband stations of the Southern California Seismic Network (SCSN) were used in production of noise cross-correlation waveforms, resulting in a spatially dense set of measurements for the Southern California region in the 2-15s period band. Tectonic sub-regions including the LA Basin and Salton Trough are clearly visible due to their high short-period H/V ratios, whilst the Transverse and Peninsular ranges exhibit low H/V at all periods.

From broadscale patterns to fine-scale processes: habitat structure influences genetic differentiation in the pitcher plant midge across multiple spatial scales.

PubMed

Rasic, Gordana; Keyghobadi, Nusha

2012-01-01

The spatial scale at which samples are collected and analysed influences the inferences that can be drawn from landscape genetic studies. We examined genetic structure and its landscape correlates in the pitcher plant midge, Metriocnemus knabi, an inhabitant of the purple pitcher plant, Sarracenia purpurea, across several spatial scales that are naturally delimited by the midge's habitat (leaf, plant, cluster of plants, bog and system of bogs). We analysed 11 microsatellite loci in 710 M. knabi larvae from two systems of bogs in Algonquin Provincial Park (Canada) and tested the hypotheses that variables related to habitat structure are associated with genetic differentiation in this midge. Up to 54% of variation in individual-based genetic distances at several scales was explained by broadscale landscape variables of bog size, pitcher plant density within bogs and connectivity of pitcher plant clusters. Our results indicate that oviposition behaviour of females at fine scales, as inferred from the spatial locations of full-sib larvae, and spatially limited gene flow at broad scales represent the important processes underlying observed genetic patterns in M. knabi. Broadscale landscape features (bog size and plant density) appear to influence oviposition behaviour of midges, which in turn influences the patterns of genetic differentiation observed at both fine and broad scales. Thus, we inferred linkages among genetic patterns, landscape patterns and ecological processes across spatial scales in M. knabi. Our results reinforce the value of exploring such links simultaneously across multiple spatial scales and landscapes when investigating genetic diversity within a species. © 2011 Blackwell Publishing Ltd.

Spatially patterned matrix elasticity directs stem cell fate

NASA Astrophysics Data System (ADS)

Yang, Chun; DelRio, Frank W.; Ma, Hao; Killaars, Anouk R.; Basta, Lena P.; Kyburz, Kyle A.; Anseth, Kristi S.

2016-08-01

There is a growing appreciation for the functional role of matrix mechanics in regulating stem cell self-renewal and differentiation processes. However, it is largely unknown how subcellular, spatial mechanical variations in the local extracellular environment mediate intracellular signal transduction and direct cell fate. Here, the effect of spatial distribution, magnitude, and organization of subcellular matrix mechanical properties on human mesenchymal stem cell (hMSCs) function was investigated. Exploiting a photodegradation reaction, a hydrogel cell culture substrate was fabricated with regions of spatially varied and distinct mechanical properties, which were subsequently mapped and quantified by atomic force microscopy (AFM). The variations in the underlying matrix mechanics were found to regulate cellular adhesion and transcriptional events. Highly spread, elongated morphologies and higher Yes-associated protein (YAP) activation were observed in hMSCs seeded on hydrogels with higher concentrations of stiff regions in a dose-dependent manner. However, when the spatial organization of the mechanically stiff regions was altered from a regular to randomized pattern, lower levels of YAP activation with smaller and more rounded cell morphologies were induced in hMSCs. We infer from these results that irregular, disorganized variations in matrix mechanics, compared with regular patterns, appear to disrupt actin organization, and lead to different cell fates; this was verified by observations of lower alkaline phosphatase (ALP) activity and higher expression of CD105, a stem cell marker, in hMSCs in random versus regular patterns of mechanical properties. Collectively, this material platform has allowed innovative experiments to elucidate a novel spatial mechanical dosing mechanism that correlates to both the magnitude and organization of spatial stiffness.

Temporal changes of spatial soil moisture patterns: controlling factors explained with a multidisciplinary approach

NASA Astrophysics Data System (ADS)

Martini, Edoardo; Wollschläger, Ute; Kögler, Simon; Behrens, Thorsten; Dietrich, Peter; Reinstorf, Frido; Schmidt, Karsten; Weiler, Markus; Werban, Ulrike; Zacharias, Steffen

2016-04-01

Characterizing the spatial patterns of soil moisture is critical for hydrological and meteorological models, as soil moisture is a key variable that controls matter and energy fluxes and soil-vegetation-atmosphere exchange processes. Deriving detailed process understanding at the hillslope scale is not trivial, because of the temporal variability of local soil moisture dynamics. Nevertheless, it remains a challenge to provide adequate information on the temporal variability of soil moisture and its controlling factors. Recent advances in wireless sensor technology allow monitoring of soil moisture dynamics with high temporal resolution at varying scales. In addition, mobile geophysical methods such as electromagnetic induction (EMI) have been widely used for mapping soil water content at the field scale with high spatial resolution, as being related to soil apparent electrical conductivity (ECa). The objective of this study was to characterize the spatial and temporal pattern of soil moisture at the hillslope scale and to infer the controlling hydrological processes, integrating well established and innovative sensing techniques, as well as new statistical methods. We combined soil hydrological and pedological expertise with geophysical measurements and methods from digital soil mapping for designing a wireless soil moisture monitoring network. For a hillslope site within the Schäfertal catchment (Central Germany), soil water dynamics were observed during 14 months, and soil ECa was mapped on seven occasions whithin this period of time using an EM38-DD device. Using the Spearman rank correlation coefficient, we described the temporal persistence of a dry and a wet characteristic state of soil moisture as well as the switching mechanisms, inferring the local properties that control the observed spatial patterns and the hydrological processes driving the transitions. Based on this, we evaluated the use of EMI for mapping the spatial pattern of soil moisture under different hydrologic conditions and the factors controlling the temporal variability of the ECa-soil moisture relationship. The approach provided valuable insight into the time-varying contribution of local and nonlocal factors to the characteristic spatial patterns of soil moisture and the transition mechanisms. The spatial organization of soil moisture was controlled by different processes in different soil horizons, and the topsoil's moisture did not mirror processes that take place within the soil profile. Results show that, for the Schäfertal hillslope site which is presumed to be representative for non-intensively managed soils with moderate clay content, local soil properties (e.g., soil texture and porosity) are the major control on the spatial pattern of ECa. In contrast, the ECa-soil moisture relationship is small and varies over time indicating that ECa is not a good proxy for soil moisture estimation at the investigated site.Occasionally observed stronger correlations between ECa and soil moisture may be explained by background dependencies of ECa to other state variables such as pore water electrical conductivity. The results will help to improve conceptual understanding for hydrological model studies at similar or smaller scales, and to transfer observation concepts and process understanding to larger or less instrumented sites, as well as to constrain the use of EMI-based ECa data for hydrological applications.

Using Neural Networks to Describe Tracer Correlations

NASA Technical Reports Server (NTRS)

Lary, D. J.; Mueller, M. D.; Mussa, H. Y.

2003-01-01

Neural networks are ideally suited to describe the spatial and temporal dependence of tracer-tracer correlations. The neural network performs well even in regions where the correlations are less compact and normally a family of correlation curves would be required. For example, the CH4-N2O correlation can be well described using a neural network trained with the latitude, pressure, time of year, and CH4 volume mixing ratio (v.m.r.). In this study a neural network using Quickprop learning and one hidden layer with eight nodes was able to reproduce the CH4-N2O correlation with a correlation co- efficient of 0.9995. Such an accurate representation of tracer-tracer correlations allows more use to be made of long-term datasets to constrain chemical models. Such as the dataset from the Halogen Occultation Experiment (HALOE) which has continuously observed CH4, (but not N2O) from 1991 till the present. The neural network Fortran code used is available for download.

Analysis of a mesoscale infiltration and water seepage test in unsaturated fractured rock: Spatial variabilities and discrete fracture patterns

USGS Publications Warehouse

Zhou, Q.; Salve, R.; Liu, H.-H.; Wang, J.S.Y.; Hudson, D.

2006-01-01

A mesoscale (21??m in flow distance) infiltration and seepage test was recently conducted in a deep, unsaturated fractured rock system at the crossover point of two underground tunnels. Water was released from a 3??m ?? 4??m infiltration plot on the floor of an alcove in the upper tunnel, and seepage was collected from the ceiling of a niche in the lower tunnel. Significant temporal and (particularly) spatial variabilities were observed in both measured infiltration and seepage rates. To analyze the test results, a three-dimensional unsaturated flow model was used. A column-based scheme was developed to capture heterogeneous hydraulic properties reflected by these spatial variabilities observed. Fracture permeability and van Genuchten ?? parameter [van Genuchten, M.T., 1980. A closed-form equation for predicting the hydraulic conductivity of unsaturated soils. Soil Sci. Soc. Am. J. 44, 892-898] were calibrated for each rock column in the upper and lower hydrogeologic units in the test bed. The calibrated fracture properties for the infiltration and seepage zone enabled a good match between simulated and measured (spatially varying) seepage rates. The numerical model was also able to capture the general trend of the highly transient seepage processes through a discrete fracture network. The calibrated properties and measured infiltration/seepage rates were further compared with mapped discrete fracture patterns at the top and bottom boundaries. The measured infiltration rates and calibrated fracture permeability of the upper unit were found to be partially controlled by the fracture patterns on the infiltration plot (as indicated by their positive correlations with fracture density). However, no correlation could be established between measured seepage rates and density of fractures mapped on the niche ceiling. This lack of correlation indicates the complexity of (preferential) unsaturated flow within the discrete fracture network. This also indicates that continuum-based modeling of unsaturated flow in fractured rock at mesoscale or a larger scale is not necessarily conditional explicitly on discrete fracture patterns. ?? 2006 Elsevier B.V. All rights reserved.

An initial assessment of a SMAP soil moisture disaggregation scheme using TIR surface evaporation data over the continental United States

NASA Astrophysics Data System (ADS)

Mishra, Vikalp; Ellenburg, W. Lee; Griffin, Robert E.; Mecikalski, John R.; Cruise, James F.; Hain, Christopher R.; Anderson, Martha C.

2018-06-01

The Soil Moisture Active Passive (SMAP) mission is dedicated toward global soil moisture mapping. Typically, an L-band microwave radiometer has spatial resolution on the order of 36-40 km, which is too coarse for many specific hydro-meteorological and agricultural applications. With the failure of the SMAP active radar within three months of becoming operational, an intermediate (9-km) and finer (3-km) scale soil moisture product solely from the SMAP mission is no longer possible. Therefore, the focus of this study is a disaggregation of the 36-km resolution SMAP passive-only surface soil moisture (SSM) using the Soil Evaporative Efficiency (SEE) approach to spatial scales of 3-km and 9-km. The SEE was computed using thermal-infrared (TIR) estimation of surface evaporation over Continental U.S. (CONUS). The disaggregation results were compared with the 3 months of SMAP-Active (SMAP-A) and Active/Passive (AP) products, while comparisons with SMAP-Enhanced (SMAP-E), SMAP-Passive (SMAP-P), as well as with more than 180 Soil Climate Analysis Network (SCAN) stations across CONUS were performed for a 19 month period. At the 9-km spatial scale, the TIR-Downscaled data correlated strongly with the SMAP-E SSM both spatially (r = 0.90) and temporally (r = 0.87). In comparison with SCAN observations, overall correlations of 0.49 and 0.47; bias of -0.022 and -0.019 and unbiased RMSD of 0.105 and 0.100 were found for SMAP-E and TIR-Downscaled SSM across the Continental U.S., respectively. At 3-km scale, TIR-Downscaled and SMAP-A had a mean temporal correlation of only 0.27. In terms of gain statistics, the highest percentage of SCAN sites with positive gains (>55%) was observed with the TIR-Downscaled SSM at 9-km. Overall, the TIR-based downscaled SSM showed strong correspondence with SMAP-E; compared to SCAN, and overall both SMAP-E and TIR-Downscaled performed similarly, however, gain statistics show that TIR-Downscaled SSM slightly outperformed SMAP-E.

Pattern does not equal process: what does patch occupancy really tell us about metapopulation dynamics?

PubMed

Clinchy, Michael; Haydon, Daniel T; Smith, Andrew T

2002-04-01

Patch occupancy surveys are commonly used to parameterize metapopulation models. If isolation predicts patch occupancy, this is generally attributed to a balance between distance-dependent recolonization and spatially independent extinctions. We investigated whether similar patterns could also be generated by a process of spatially correlated extinctions following a unique colonization event (analogous to nonequilibrium processes in island biogeography). We simulated effects of spatially correlated extinctions on patterns of patch occupancy among pikas (Ochotona princeps) at Bodie, California, using randomly located extinction disks to represent the likely effects of predation. Our simulations produced similar patterns to those cited as evidence of balanced metapopulation dynamics. Simulations using a variety of disk sizes and patch configurations confirmed that our results are potentially applicable to a broad range of species and sites. Analyses of the observed patterns of patch occupancy at Bodie revealed little evidence of rescue effects and strong evidence that most recolonizations are ephemeral in nature. Persistence will be overestimated if static or declining patterns of patch occupancy are mistakenly attributed to dynamically stable metapopulation processes. Consequently, simple patch occupancy surveys should not be considered as substitutes for detailed experimental tests of hypothesized population processes, particularly when conservation concerns are involved.

Study of satellite retrieved aerosol optical depth spatial resolution effect on particulate matter concentration prediction

NASA Astrophysics Data System (ADS)

Strandgren, J.; Mei, L.; Vountas, M.; Burrows, J. P.; Lyapustin, A.; Wang, Y.

2014-10-01

The Aerosol Optical Depth (AOD) spatial resolution effect is investigated for the linear correlation between satellite retrieved AOD and ground level particulate matter concentrations (PM2.5). The Multi-Angle Implementation of Atmospheric Correction (MAIAC) algorithm was developed for the Moderate Resolution Imaging Spectroradiometer (MODIS) for obtaining AOD with a high spatial resolution of 1 km and provides a good dataset for the study of the AOD spatial resolution effect on the particulate matter concentration prediction. 946 Environmental Protection Agency (EPA) ground monitoring stations across the contiguous US have been used to investigate the linear correlation between AOD and PM2.5 using AOD at different spatial resolutions (1, 3 and 10 km) and for different spatial scales (urban scale, meso-scale and continental scale). The main conclusions are: (1) for both urban, meso- and continental scale the correlation between PM2.5 and AOD increased significantly with increasing spatial resolution of the AOD, (2) the correlation between AOD and PM2.5 decreased significantly as the scale of study region increased for the eastern part of the US while vice versa for the western part of the US, (3) the correlation between PM2.5 and AOD is much more stable and better over the eastern part of the US compared to western part due to the surface characteristics and atmospheric conditions like the fine mode fraction.

Long-term geomagnetically induced current observations in New Zealand: Earth return corrections and geomagnetic field driver

NASA Astrophysics Data System (ADS)

Mac Manus, Daniel H.; Rodger, Craig J.; Dalzell, Michael; Thomson, Alan W. P.; Clilverd, Mark A.; Petersen, Tanja; Wolf, Moritz M.; Thomson, Neil R.; Divett, Tim

2017-08-01

Transpower New Zealand Limited has measured DC currents in transformer neutrals in the New Zealand electrical network at multiple South Island locations. Near-continuous archived DC current data exist since 2001, starting with 12 different substations and expanding from 2009 to include 17 substations. From 2001 to 2015 up to 58 individual transformers were simultaneously monitored. Primarily, the measurements were intended to monitor the impact of the high-voltage DC system linking the North and South Islands when it is operating in "Earth return" mode. However, after correcting for Earth return operation, as described here, the New Zealand measurements provide an unusually long and spatially detailed set of geomagnetically induced current (GIC) measurements. We examine the peak GIC magnitudes observed from these observations during two large geomagnetic storms on 6 November 2001 and 2 October 2013. Currents of 30-50 A are observed, depending on the measurement location. There are large spatial variations in the GIC observations over comparatively small distances, which likely depend upon network layout and ground conductivity. We then go on to examine the GIC in transformers throughout the South Island during more than 151 h of geomagnetic storm conditions. We compare the GIC to the various magnitude and rate of change components of the magnetic field. Our results show that there is a strong correlation between the magnitude of the GIC and the rate of change of the horizontal magnetic field (H'). This correlation is particularly clear for transformers that show large GIC current during magnetic storms.

Spatial Autocorrelation Approaches to Testing Residuals from Least Squares Regression

PubMed Central

Chen, Yanguang

2016-01-01

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

Neural correlates of abnormal sensory discrimination in laryngeal dystonia.

PubMed

Termsarasab, Pichet; Ramdhani, Ritesh A; Battistella, Giovanni; Rubien-Thomas, Estee; Choy, Melissa; Farwell, Ian M; Velickovic, Miodrag; Blitzer, Andrew; Frucht, Steven J; Reilly, Richard B; Hutchinson, Michael; Ozelius, Laurie J; Simonyan, Kristina

2016-01-01

Aberrant sensory processing plays a fundamental role in the pathophysiology of dystonia; however, its underpinning neural mechanisms in relation to dystonia phenotype and genotype remain unclear. We examined temporal and spatial discrimination thresholds in patients with isolated laryngeal form of dystonia (LD), who exhibited different clinical phenotypes (adductor vs. abductor forms) and potentially different genotypes (sporadic vs. familial forms). We correlated our behavioral findings with the brain gray matter volume and functional activity during resting and symptomatic speech production. We found that temporal but not spatial discrimination was significantly altered across all forms of LD, with higher frequency of abnormalities seen in familial than sporadic patients. Common neural correlates of abnormal temporal discrimination across all forms were found with structural and functional changes in the middle frontal and primary somatosensory cortices. In addition, patients with familial LD had greater cerebellar involvement in processing of altered temporal discrimination, whereas sporadic LD patients had greater recruitment of the putamen and sensorimotor cortex. Based on the clinical phenotype, adductor form-specific correlations between abnormal discrimination and brain changes were found in the frontal cortex, whereas abductor form-specific correlations were observed in the cerebellum and putamen. Our behavioral and neuroimaging findings outline the relationship of abnormal sensory discrimination with the phenotype and genotype of isolated LD, suggesting the presence of potentially divergent pathophysiological pathways underlying different manifestations of this disorder.

Aridity changes in the Tibetan Plateau in a warming climate

DOE PAGES

Gao, Yanhong; Li, Xia; Leung, Lai-Yung R.; ...

2015-03-10

Desertification in the Tibetan Plateau (TP) has drawn increasing attention in the recent decades. It has been postulated as a consequence of climate aridity due to the observed warming. This study quantifies the aridity changes in the TP and attributes the changes to different climatic factors. Using the ratio of P/PET (precipitation to potential evapotranspiration) as an aridity index to indicate changes in dryness and wetness in a given area, P/PET was calculated using observed records at 83 stations in the TP, with PET calculated using the Penman–Monteith (PM) algorithm. Spatial and temporal changes of P/PET in 1979-2011 are analyzed.more » Results show that stations located in the arid and semi-arid northwestern TP are becoming significantly wetter and stations in the semi-humid southeastern TP are becoming drier, though not significantly, in the recent three decades. The aridity change patterns are significantly correlated with precipitation, sunshine duration and diurnal temperature range changes at confidence level of 99.9% from two-tail t-test. Temporal correlations also confirm the significant correlation between aridity changes with the three variables, with precipitation being the most dominant driver of P/PET changes at interannual time scale. PET changes are insignificant but negatively correlated with P/PET in the cold season. In the warm season, however, correlation between PET changes and P/PET changes are significant at confidence level of 99.9% when the cryosphere melts near the surface. Significant correlation between wind speed changes and aridity changes occurs in limited locations and months. Consistency in the climatology pattern and linear trends in surface air temperature and precipitation calculated using station data, gridded data, and nearest grid-to-stations for the TP average and across sub-basins indicate the robustness of the trends despite the large spatial heterogeneity in the TP that challenge climate monitoring.« less

Assessing the role of spatial correlations during collective cell spreading

PubMed Central

Treloar, Katrina K.; Simpson, Matthew J.; Binder, Benjamin J.; McElwain, D. L. Sean; Baker, Ruth E.

2014-01-01

Spreading cell fronts are essential features of development, repair and disease processes. Many mathematical models used to describe the motion of cell fronts, such as Fisher's equation, invoke a mean–field assumption which implies that there is no spatial structure, such as cell clustering, present. Here, we examine the presence of spatial structure using a combination of in vitro circular barrier assays, discrete random walk simulations and pair correlation functions. In particular, we analyse discrete simulation data using pair correlation functions to show that spatial structure can form in a spreading population of cells either through sufficiently strong cell–to–cell adhesion or sufficiently rapid cell proliferation. We analyse images from a circular barrier assay describing the spreading of a population of MM127 melanoma cells using the same pair correlation functions. Our results indicate that the spreading melanoma cell populations remain very close to spatially uniform, suggesting that the strength of cell–to–cell adhesion and the rate of cell proliferation are both sufficiently small so as not to induce any spatial patterning in the spreading populations. PMID:25026987

Spatial Correlations in Natural Scenes Modulate Response Reliability in Mouse Visual Cortex

PubMed Central

Rikhye, Rajeev V.

2015-01-01

Intrinsic neuronal variability significantly limits information encoding in the primary visual cortex (V1). Certain stimuli can suppress this intertrial variability to increase the reliability of neuronal responses. In particular, responses to natural scenes, which have broadband spatiotemporal statistics, are more reliable than responses to stimuli such as gratings. However, very little is known about which stimulus statistics modulate reliable coding and how this occurs at the neural ensemble level. Here, we sought to elucidate the role that spatial correlations in natural scenes play in reliable coding. We developed a novel noise-masking method to systematically alter spatial correlations in natural movies, without altering their edge structure. Using high-speed two-photon calcium imaging in vivo, we found that responses in mouse V1 were much less reliable at both the single neuron and population level when spatial correlations were removed from the image. This change in reliability was due to a reorganization of between-neuron correlations. Strongly correlated neurons formed ensembles that reliably and accurately encoded visual stimuli, whereas reducing spatial correlations reduced the activation of these ensembles, leading to an unreliable code. Together with an ensemble-specific normalization model, these results suggest that the coordinated activation of specific subsets of neurons underlies the reliable coding of natural scenes. SIGNIFICANCE STATEMENT The natural environment is rich with information. To process this information with high fidelity, V1 neurons have to be robust to noise and, consequentially, must generate responses that are reliable from trial to trial. While several studies have hinted that both stimulus attributes and population coding may reduce noise, the details remain unclear. Specifically, what features of natural scenes are important and how do they modulate reliability? This study is the first to investigate the role of spatial correlations, which are a fundamental attribute of natural scenes, in shaping stimulus coding by V1 neurons. Our results provide new insights into how stimulus spatial correlations reorganize the correlated activation of specific ensembles of neurons to ensure accurate information processing in V1. PMID:26511254

Spectral characteristics of background error covariance and multiscale data assimilation

DOE PAGES

Li, Zhijin; Cheng, Xiaoping; Gustafson, Jr., William I.; ...

2016-05-17

The steady increase of the spatial resolutions of numerical atmospheric and oceanic circulation models has occurred over the past decades. Horizontal grid spacing down to the order of 1 km is now often used to resolve cloud systems in the atmosphere and sub-mesoscale circulation systems in the ocean. These fine resolution models encompass a wide range of temporal and spatial scales, across which dynamical and statistical properties vary. In particular, dynamic flow systems at small scales can be spatially localized and temporarily intermittent. Difficulties of current data assimilation algorithms for such fine resolution models are numerically and theoretically examined. Ourmore » analysis shows that the background error correlation length scale is larger than 75 km for streamfunctions and is larger than 25 km for water vapor mixing ratios, even for a 2-km resolution model. A theoretical analysis suggests that such correlation length scales prevent the currently used data assimilation schemes from constraining spatial scales smaller than 150 km for streamfunctions and 50 km for water vapor mixing ratios. Moreover, our results highlight the need to fundamentally modify currently used data assimilation algorithms for assimilating high-resolution observations into the aforementioned fine resolution models. Lastly, within the framework of four-dimensional variational data assimilation, a multiscale methodology based on scale decomposition is suggested and challenges are discussed.« less

Using spatial information about recurrence risk for robust optimization of dose-painting prescription functions

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

Bender, Edward T.

Purpose: To develop a robust method for deriving dose-painting prescription functions using spatial information about the risk for disease recurrence. Methods: Spatial distributions of radiobiological model parameters are derived from distributions of recurrence risk after uniform irradiation. These model parameters are then used to derive optimal dose-painting prescription functions given a constant mean biologically effective dose. Results: An estimate for the optimal dose distribution can be derived based on spatial information about recurrence risk. Dose painting based on imaging markers that are moderately or poorly correlated with recurrence risk are predicted to potentially result in inferior disease control when comparedmore » the same mean biologically effective dose delivered uniformly. A robust optimization approach may partially mitigate this issue. Conclusions: The methods described here can be used to derive an estimate for a robust, patient-specific prescription function for use in dose painting. Two approximate scaling relationships were observed: First, the optimal choice for the maximum dose differential when using either a linear or two-compartment prescription function is proportional to R, where R is the Pearson correlation coefficient between a given imaging marker and recurrence risk after uniform irradiation. Second, the predicted maximum possible gain in tumor control probability for any robust optimization technique is nearly proportional to the square of R.« less

Space-time codependence of retinal ganglion cells can be explained by novel and separable components of their receptive fields.

PubMed

Cowan, Cameron S; Sabharwal, Jasdeep; Wu, Samuel M

2016-09-01

Reverse correlation methods such as spike-triggered averaging consistently identify the spatial center in the linear receptive fields (RFs) of retinal ganglion cells (GCs). However, the spatial antagonistic surround observed in classical experiments has proven more elusive. Tests for the antagonistic surround have heretofore relied on models that make questionable simplifying assumptions such as space-time separability and radial homogeneity/symmetry. We circumvented these, along with other common assumptions, and observed a linear antagonistic surround in 754 of 805 mouse GCs. By characterizing the RF's space-time structure, we found the overall linear RF's inseparability could be accounted for both by tuning differences between the center and surround and differences within the surround. Finally, we applied this approach to characterize spatial asymmetry in the RF surround. These results shed new light on the spatiotemporal organization of GC linear RFs and highlight a major contributor to its inseparability. © 2016 The Authors. Physiological Reports published by Wiley Periodicals, Inc. on behalf of the American Physiological Society and The Physiological Society.

Correlations of trace elements in breast human tissues: Evaluation of spatial distribution using μ-XRF

NASA Astrophysics Data System (ADS)

Silva, Marina Piacenti da; Silva, Deisy Mara da; Ribeiro-Silva, Alfredo; Poletti, Martin Eduardo

2012-05-01

The aim of this work is to investigate microscopic correlations between trace elements in breast human tissues. A synchrotron X-ray fluorescence microprobe system (μ-XRF) was used to obtain two-dimensional distribution of trace element Ca, Fe, Cu and Zn in normal (6 samples) and malignant (14 samples) breast tissues. The experiment was performed in X-ray Fluorescence beam line at Laboratório Nacional de Luz Síncrotron (LNLS), Campinas, Brazil. The white microbeam was generated with a fine conical capillary with a 20 μm output diameter. The samples were supported on a XYZ table. An optical microscope with motorized zoom was used for sample positioning and choice the area to be scanned. Automatic two-dimensional scans were programmed and performed with steps of 30 μm in each direction (x, y) on the selected area. The fluorescence signals were recorded using a Si(Li) detector, positioned at 90 degrees with respect to the incident beam, with a collection time of 10 s per point. The elemental maps obtained from each sample were overlap to observe correlation between trace elements. Qualitative results showed that the pairs of elements Ca-Zn and Fe-Cu could to be correlated in malignant breast tissues. Quantitative results, achieved by Spearman correlation tests, indicate that there is a spatial correlation between these pairs of elements (p < 0.001) suggesting the importance of these elements in metabolic processes associated with the development of the tumor.

An Improved GRACE Terrestrial Water Storage Assimilation System For Estimating Large-Scale Soil Moisture and Shallow Groundwater

NASA Astrophysics Data System (ADS)

Girotto, M.; De Lannoy, G. J. M.; Reichle, R. H.; Rodell, M.

2015-12-01

The Gravity Recovery And Climate Experiment (GRACE) mission is unique because it provides highly accurate column integrated estimates of terrestrial water storage (TWS) variations. Major limitations of GRACE-based TWS observations are related to their monthly temporal and coarse spatial resolution (around 330 km at the equator), and to the vertical integration of the water storage components. These challenges can be addressed through data assimilation. To date, it is still not obvious how best to assimilate GRACE-TWS observations into a land surface model, in order to improve hydrological variables, and many details have yet to be worked out. This presentation discusses specific recent features of the assimilation of gridded GRACE-TWS data into the NASA Goddard Earth Observing System (GEOS-5) Catchment land surface model to improve soil moisture and shallow groundwater estimates at the continental scale. The major recent advancements introduced by the presented work with respect to earlier systems include: 1) the assimilation of gridded GRACE-TWS data product with scaling factors that are specifically derived for data assimilation purposes only; 2) the assimilation is performed through a 3D assimilation scheme, in which reasonable spatial and temporal error standard deviations and correlations are exploited; 3) the analysis step uses an optimized calculation and application of the analysis increments; 4) a poor-man's adaptive estimation of a spatially variable measurement error. This work shows that even if they are characterized by a coarse spatial and temporal resolution, the observed column integrated GRACE-TWS data have potential for improving our understanding of soil moisture and shallow groundwater variations.

Estimating Morning Change in Land Surface Temperature from MODIS Day/Night Observations: Applications for Surface Energy Balance Modeling.

PubMed

Hain, Christopher R; Anderson, Martha C

2017-10-16

Observations of land surface temperature (LST) are crucial for the monitoring of surface energy fluxes from satellite. Methods that require high temporal resolution LST observations (e.g., from geostationary orbit) can be difficult to apply globally because several geostationary sensors are required to attain near-global coverage (60°N to 60°S). While these LST observations are available from polar-orbiting sensors, providing global coverage at higher spatial resolutions, the temporal sampling (twice daily observations) can pose significant limitations. For example, the Atmosphere Land Exchange Inverse (ALEXI) surface energy balance model, used for monitoring evapotranspiration and drought, requires an observation of the morning change in LST - a quantity not directly observable from polar-orbiting sensors. Therefore, we have developed and evaluated a data-mining approach to estimate the mid-morning rise in LST from a single sensor (2 observations per day) of LST from the Moderate Resolution Imaging Spectroradiometer (MODIS) sensor on the Aqua platform. In general, the data-mining approach produced estimates with low relative error (5 to 10%) and statistically significant correlations when compared against geostationary observations. This approach will facilitate global, near real-time applications of ALEXI at higher spatial and temporal coverage from a single sensor than currently achievable with current geostationary datasets.

The Potential for Spatial Distribution Indices to Signal Thresholds in Marine Fish Biomass

PubMed Central

Reuchlin-Hugenholtz, Emilie

2015-01-01

The frequently observed positive relationship between fish population abundance and spatial distribution suggests that changes in distribution can be indicative of trends in abundance. If contractions in spatial distribution precede declines in spawning stock biomass (SSB), spatial distribution reference points could complement the SSB reference points that are commonly used in marine conservation biology and fisheries management. When relevant spatial distribution information is integrated into fisheries management and recovery plans, risks and uncertainties associated with a plan based solely on the SSB criterion would be reduced. To assess the added value of spatial distribution data, we examine the relationship between SSB and four metrics of spatial distribution intended to reflect changes in population range, concentration, and density for 10 demersal populations (9 species) inhabiting the Scotian Shelf, Northwest Atlantic. Our primary purpose is to assess their potential to serve as indices of SSB, using fisheries independent survey data. We find that metrics of density offer the best correlate of spawner biomass. A decline in the frequency of encountering high density areas is associated with, and in a few cases preceded by, rapid declines in SSB in 6 of 10 populations. Density-based indices have considerable potential to serve both as an indicator of SSB and as spatially based reference points in fisheries management. PMID:25789624

Improving Genomic Prediction in Cassava Field Experiments Using Spatial Analysis.

PubMed

Elias, Ani A; Rabbi, Ismail; Kulakow, Peter; Jannink, Jean-Luc

2018-01-04

Cassava ( Manihot esculenta Crantz) is an important staple food in sub-Saharan Africa. Breeding experiments were conducted at the International Institute of Tropical Agriculture in cassava to select elite parents. Taking into account the heterogeneity in the field while evaluating these trials can increase the accuracy in estimation of breeding values. We used an exploratory approach using the parametric spatial kernels Power, Spherical, and Gaussian to determine the best kernel for a given scenario. The spatial kernel was fit simultaneously with a genomic kernel in a genomic selection model. Predictability of these models was tested through a 10-fold cross-validation method repeated five times. The best model was chosen as the one with the lowest prediction root mean squared error compared to that of the base model having no spatial kernel. Results from our real and simulated data studies indicated that predictability can be increased by accounting for spatial variation irrespective of the heritability of the trait. In real data scenarios we observed that the accuracy can be increased by a median value of 3.4%. Through simulations, we showed that a 21% increase in accuracy can be achieved. We also found that Range (row) directional spatial kernels, mostly Gaussian, explained the spatial variance in 71% of the scenarios when spatial correlation was significant. Copyright © 2018 Elias et al.

Coarse-Grained Theory of Biological Charge Transfer with Spatially and Temporally Correlated Noise.

PubMed

Liu, Chaoren; Beratan, David N; Zhang, Peng

2016-04-21

System-environment interactions are essential in determining charge-transfer (CT) rates and mechanisms. We developed a computationally accessible method, suitable to simulate CT in flexible molecules (i.e., DNA) with hundreds of sites, where the system-environment interactions are explicitly treated with numerical noise modeling of time-dependent site energies and couplings. The properties of the noise are tunable, providing us a flexible tool to investigate the detailed effects of correlated thermal fluctuations on CT mechanisms. The noise is parametrizable by molecular simulation and quantum calculation results of specific molecular systems, giving us better molecular resolution in simulating the system-environment interactions than sampling fluctuations from generic spectral density functions. The spatially correlated thermal fluctuations among different sites are naturally built-in in our method but are not readily incorporated using approximate spectral densities. Our method has quantitative accuracy in systems with small redox potential differences (