Estimating the Spatial Distribution of Groundwater Age Using Synoptic Surveys of Environmental Tracers in Streams

NASA Astrophysics Data System (ADS)

Gardner, W. P.

2017-12-01

A model which simulates tracer concentration in surface water as a function the age distribution of groundwater discharge is used to characterize groundwater flow systems at a variety of spatial scales. We develop the theory behind the model and demonstrate its application in several groundwater systems of local to regional scale. A 1-D stream transport model, which includes: advection, dispersion, gas exchange, first-order decay and groundwater inflow is coupled a lumped parameter model that calculates the concentration of environmental tracers in discharging groundwater as a function of the groundwater residence time distribution. The lumped parameters, which describe the residence time distribution, are allowed to vary spatially, and multiple environmental tracers can be simulated. This model allows us to calculate the longitudinal profile of tracer concentration in streams as a function of the spatially variable groundwater age distribution. By fitting model results to observations of stream chemistry and discharge, we can then estimate the spatial distribution of groundwater age. The volume of groundwater discharge to streams can be estimated using a subset of environmental tracers, applied tracers, synoptic stream gauging or other methods, and the age of groundwater then estimated using the previously calculated groundwater discharge and observed environmental tracer concentrations. Synoptic surveys of SF6, CFC's, 3H and 222Rn, along with measured stream discharge are used to estimate the groundwater inflow distribution and mean age for regional scale surveys of the Berland River in west-central Alberta. We find that groundwater entering the Berland has observable age, and that the age estimated using our stream survey is of similar order to limited samples from groundwater wells in the region. Our results show that the stream can be used as an easily accessible location to constrain the regional scale spatial distribution of groundwater age.

Unifying distribution functions: some lesser known distributions.

PubMed

Moya-Cessa, J R; Moya-Cessa, H; Berriel-Valdos, L R; Aguilar-Loreto, O; Barberis-Blostein, P

2008-08-01

We show that there is a way to unify distribution functions that describe simultaneously a classical signal in space and (spatial) frequency and position and momentum for a quantum system. Probably the most well known of them is the Wigner distribution function. We show how to unify functions of the Cohen class, Rihaczek's complex energy function, and Husimi and Glauber-Sudarshan distribution functions. We do this by showing how they may be obtained from ordered forms of creation and annihilation operators and by obtaining them in terms of expectation values in different eigenbases.

Environmental filtering structures tree functional traits combination and lineages across space in tropical tree assemblages.

PubMed

Asefa, Mengesha; Cao, Min; Zhang, Guocheng; Ci, Xiuqin; Li, Jie; Yang, Jie

2017-03-09

Environmental filtering consistently shapes the functional and phylogenetic structure of species across space within diverse forests. However, poor descriptions of community functional and lineage distributions across space hamper the accurate understanding of coexistence mechanisms. We combined environmental variables and geographic space to explore how traits and lineages are filtered by environmental factors using extended RLQ and fourth-corner analyses across different spatial scales. The dispersion patterns of traits and lineages were also examined in a 20-ha tropical rainforest dynamics plot in southwest China. We found that environmental filtering was detected across all spatial scales except the largest scale (100 × 100 m). Generally, the associations between functional traits and environmental variables were more or less consistent across spatial scales. Species with high resource acquisition-related traits were associated with the resource-rich part of the plot across the different spatial scales, whereas resource-conserving functional traits were distributed in limited-resource environments. Furthermore, we found phylogenetic and functional clustering at all spatial scales. Similar functional strategies were also detected among distantly related species, suggesting that phylogenetic distance is not necessarily a proxy for functional distance. In summary, environmental filtering considerably structured the trait and lineage assemblages in this species-rich tropical rainforest.

The interaction between the spatial distribution of resource patches and population density: consequences for intraspecific growth and morphology.

PubMed

Jacobson, Bailey; Grant, James W A; Peres-Neto, Pedro R

2015-07-01

How individuals within a population distribute themselves across resource patches of varying quality has been an important focus of ecological theory. The ideal free distribution predicts equal fitness amongst individuals in a 1 : 1 ratio with resources, whereas resource defence theory predicts different degrees of monopolization (fitness variance) as a function of temporal and spatial resource clumping and population density. One overlooked landscape characteristic is the spatial distribution of resource patches, altering the equitability of resource accessibility and thereby the effective number of competitors. While much work has investigated the influence of morphology on competitive ability for different resource types, less is known regarding the phenotypic characteristics conferring relative ability for a single resource type, particularly when exploitative competition predominates. Here we used young-of-the-year rainbow trout (Oncorhynchus mykiss) to test whether and how the spatial distribution of resource patches and population density interact to influence the level and variance of individual growth, as well as if functional morphology relates to competitive ability. Feeding trials were conducted within stream channels under three spatial distributions of nine resource patches (distributed, semi-clumped and clumped) at two density levels (9 and 27 individuals). Average trial growth was greater in high-density treatments with no effect of resource distribution. Within-trial growth variance had opposite patterns across resource distributions. Here, variance decreased at low-population, but increased at high-population densities as patches became increasingly clumped as the result of changes in the levels of interference vs. exploitative competition. Within-trial growth was related to both pre- and post-trial morphology where competitive individuals were those with traits associated with swimming capacity and efficiency: larger heads/bodies/caudal fins and less angled pectoral fins. The different degrees of within-population growth variance at the same density level found here, as a function of spatial resource distribution, provide an explanation for the inconsistencies in within-site growth variance and population regulation often noted with regard to density dependence in natural landscapes. © 2015 The Authors. Journal of Animal Ecology © 2015 British Ecological Society.

Spatial differences between stars and brown dwarfs: a dynamical origin?

NASA Astrophysics Data System (ADS)

Parker, Richard J.; Andersen, Morten

2014-06-01

We use N-body simulations to compare the evolution of spatial distributions of stars and brown dwarfs in young star-forming regions. We use three different diagnostics: the ratio of stars to brown dwarfs as a function of distance from the region's centre, {R}_SSR, the local surface density of stars compared to brown dwarfs, ΣLDR, and we compare the global spatial distributions using the ΛMSR method. From a suite of 20 initially statistically identical simulations, 6/20 attain {R}_SSR ≪ 1 and ΣLDR ≪ 1 and ΛMSR ≪ 1, indicating that dynamical interactions could be responsible for observed differences in the spatial distributions of stars and brown dwarfs in star-forming regions. However, many simulations also display apparently contradictory results - for example, in some cases the brown dwarfs have much lower local densities than stars (ΣLDR ≪ 1), but their global spatial distributions are indistinguishable (ΛMSR = 1) and the relative proportion of stars and brown dwarfs remains constant across the region ({R}_SSR = 1). Our results suggest that extreme caution should be exercised when interpreting any observed difference in the spatial distribution of stars and brown dwarfs, and that a much larger observational sample of regions/clusters (with complete mass functions) is necessary to investigate whether or not brown dwarfs form through similar mechanisms to stars.

Effects of Spatial Gradients on Electron Runaway Acceleration

NASA Technical Reports Server (NTRS)

MacNeice, Peter; Ljepojevic, N. N.

1996-01-01

The runaway process is known to accelerate electrons in many laboratory plasmas and has been suggested as an acceleration mechanism in some astrophysical plasmas, including solar flares. Current calculations of the electron velocity distributions resulting from the runaway process are greatly restricted because they impose spatial homogeneity on the distribution. We have computed runaway distributions which include consistent development of spatial gradients in the energetic tail. Our solution for the electron velocity distribution is presented as a function of distance along a finite length acceleration region, and is compared with the equivalent distribution for the infinitely long homogenous system (i.e., no spatial gradients), as considered in the existing literature. All these results are for the weak field regime. We also discuss the severe restrictiveness of this weak field assumption.

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

Analyzing Protein Clusters on the Plasma Membrane: Application of Spatial Statistical Analysis Methods on Super-Resolution Microscopy Images.

PubMed

Paparelli, Laura; Corthout, Nikky; Pavie, Benjamin; Annaert, Wim; Munck, Sebastian

2016-01-01

The spatial distribution of proteins within the cell affects their capability to interact with other molecules and directly influences cellular processes and signaling. At the plasma membrane, multiple factors drive protein compartmentalization into specialized functional domains, leading to the formation of clusters in which intermolecule interactions are facilitated. Therefore, quantifying protein distributions is a necessity for understanding their regulation and function. The recent advent of super-resolution microscopy has opened up the possibility of imaging protein distributions at the nanometer scale. In parallel, new spatial analysis methods have been developed to quantify distribution patterns in super-resolution images. In this chapter, we provide an overview of super-resolution microscopy and summarize the factors influencing protein arrangements on the plasma membrane. Finally, we highlight methods for analyzing clusterization of plasma membrane proteins, including examples of their applications.

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.

Effects of spatial grouping on the functional response of predators

USGS Publications Warehouse

Cosner, C.; DeAngelis, D.L.; Ault, J.S.; Olson, D.B.

1999-01-01

A unified mechanistic approach is given for the derivation of various forms of functional response in predator-prey models. The derivation is based on the principle-of-mass action but with the crucial refinement that the nature of the spatial distribution of predators and/or opportunities for predation are taken into account in an implicit way. If the predators are assumed to have a homogeneous spatial distribution, then the derived functional response is prey-dependent. If the predators are assumed to form a dense colony or school in a single (possibly moving) location, or if the region where predators can encounter prey is assumed to be of limited size, then the functional response depends on both predator and prey densities in a manner that reflects feeding interference between predators. Depending on the specific assumptions, the resulting functional response may be of Beddington-DeAngelis type, of Hassell-Varley type, or ratio-dependent.

The Two-Dimensional Gabor Function Adapted to Natural Image Statistics: A Model of Simple-Cell Receptive Fields and Sparse Structure in Images.

PubMed

Loxley, P N

2017-10-01

The two-dimensional Gabor function is adapted to natural image statistics, leading to a tractable probabilistic generative model that can be used to model simple cell receptive field profiles, or generate basis functions for sparse coding applications. Learning is found to be most pronounced in three Gabor function parameters representing the size and spatial frequency of the two-dimensional Gabor function and characterized by a nonuniform probability distribution with heavy tails. All three parameters are found to be strongly correlated, resulting in a basis of multiscale Gabor functions with similar aspect ratios and size-dependent spatial frequencies. A key finding is that the distribution of receptive-field sizes is scale invariant over a wide range of values, so there is no characteristic receptive field size selected by natural image statistics. The Gabor function aspect ratio is found to be approximately conserved by the learning rules and is therefore not well determined by natural image statistics. This allows for three distinct solutions: a basis of Gabor functions with sharp orientation resolution at the expense of spatial-frequency resolution, a basis of Gabor functions with sharp spatial-frequency resolution at the expense of orientation resolution, or a basis with unit aspect ratio. Arbitrary mixtures of all three cases are also possible. Two parameters controlling the shape of the marginal distributions in a probabilistic generative model fully account for all three solutions. The best-performing probabilistic generative model for sparse coding applications is found to be a gaussian copula with Pareto marginal probability density functions.

Remote-sensing based approach to forecast habitat quality under climate change scenarios.

PubMed

Requena-Mullor, Juan M; López, Enrique; Castro, Antonio J; Alcaraz-Segura, Domingo; Castro, Hermelindo; Reyes, Andrés; Cabello, Javier

2017-01-01

As climate change is expected to have a significant impact on species distributions, there is an urgent challenge to provide reliable information to guide conservation biodiversity policies. In addressing this challenge, we propose a remote sensing-based approach to forecast the future habitat quality for European badger, a species not abundant and at risk of local extinction in the arid environments of southeastern Spain, by incorporating environmental variables related with the ecosystem functioning and correlated with climate and land use. Using ensemble prediction methods, we designed global spatial distribution models for the distribution range of badger using presence-only data and climate variables. Then, we constructed regional models for an arid region in the southeast Spain using EVI (Enhanced Vegetation Index) derived variables and weighting the pseudo-absences with the global model projections applied to this region. Finally, we forecast the badger potential spatial distribution in the time period 2071-2099 based on IPCC scenarios incorporating the uncertainty derived from the predicted values of EVI-derived variables. By including remotely sensed descriptors of the temporal dynamics and spatial patterns of ecosystem functioning into spatial distribution models, results suggest that future forecast is less favorable for European badgers than not including them. In addition, change in spatial pattern of habitat suitability may become higher than when forecasts are based just on climate variables. Since the validity of future forecast only based on climate variables is currently questioned, conservation policies supported by such information could have a biased vision and overestimate or underestimate the potential changes in species distribution derived from climate change. The incorporation of ecosystem functional attributes derived from remote sensing in the modeling of future forecast may contribute to the improvement of the detection of ecological responses under climate change scenarios.

Remote-sensing based approach to forecast habitat quality under climate change scenarios

PubMed Central

Requena-Mullor, Juan M.; López, Enrique; Castro, Antonio J.; Alcaraz-Segura, Domingo; Castro, Hermelindo; Reyes, Andrés; Cabello, Javier

2017-01-01

As climate change is expected to have a significant impact on species distributions, there is an urgent challenge to provide reliable information to guide conservation biodiversity policies. In addressing this challenge, we propose a remote sensing-based approach to forecast the future habitat quality for European badger, a species not abundant and at risk of local extinction in the arid environments of southeastern Spain, by incorporating environmental variables related with the ecosystem functioning and correlated with climate and land use. Using ensemble prediction methods, we designed global spatial distribution models for the distribution range of badger using presence-only data and climate variables. Then, we constructed regional models for an arid region in the southeast Spain using EVI (Enhanced Vegetation Index) derived variables and weighting the pseudo-absences with the global model projections applied to this region. Finally, we forecast the badger potential spatial distribution in the time period 2071–2099 based on IPCC scenarios incorporating the uncertainty derived from the predicted values of EVI-derived variables. By including remotely sensed descriptors of the temporal dynamics and spatial patterns of ecosystem functioning into spatial distribution models, results suggest that future forecast is less favorable for European badgers than not including them. In addition, change in spatial pattern of habitat suitability may become higher than when forecasts are based just on climate variables. Since the validity of future forecast only based on climate variables is currently questioned, conservation policies supported by such information could have a biased vision and overestimate or underestimate the potential changes in species distribution derived from climate change. The incorporation of ecosystem functional attributes derived from remote sensing in the modeling of future forecast may contribute to the improvement of the detection of ecological responses under climate change scenarios. PMID:28257501

Analyzing spatial coherence using a single mobile field sensor.

PubMed

Fridman, Peter

2007-04-01

According to the Van Cittert-Zernike theorem, the intensity distribution of a spatially incoherent source and the mutual coherence function of the light impinging on two wave sensors are related. It is the comparable relationship using a single mobile sensor moving at a certain velocity relative to the source that is calculated in this paper. The auto-corelation function of the electric field at the sensor contains information about the intensity distribution. This expression could be employed in aperture synthesis.

Statistical Analysis of 3D Images Detects Regular Spatial Distributions of Centromeres and Chromocenters in Animal and Plant Nuclei

PubMed Central

Biot, Eric; Adenot, Pierre-Gaël; Hue-Beauvais, Cathy; Houba-Hérin, Nicole; Duranthon, Véronique; Devinoy, Eve; Beaujean, Nathalie; Gaudin, Valérie; Maurin, Yves; Debey, Pascale

2010-01-01

In eukaryotes, the interphase nucleus is organized in morphologically and/or functionally distinct nuclear “compartments”. Numerous studies highlight functional relationships between the spatial organization of the nucleus and gene regulation. This raises the question of whether nuclear organization principles exist and, if so, whether they are identical in the animal and plant kingdoms. We addressed this issue through the investigation of the three-dimensional distribution of the centromeres and chromocenters. We investigated five very diverse populations of interphase nuclei at different differentiation stages in their physiological environment, belonging to rabbit embryos at the 8-cell and blastocyst stages, differentiated rabbit mammary epithelial cells during lactation, and differentiated cells of Arabidopsis thaliana plantlets. We developed new tools based on the processing of confocal images and a new statistical approach based on G- and F- distance functions used in spatial statistics. Our original computational scheme takes into account both size and shape variability by comparing, for each nucleus, the observed distribution against a reference distribution estimated by Monte-Carlo sampling over the same nucleus. This implicit normalization allowed similar data processing and extraction of rules in the five differentiated nuclei populations of the three studied biological systems, despite differences in chromosome number, genome organization and heterochromatin content. We showed that centromeres/chromocenters form significantly more regularly spaced patterns than expected under a completely random situation, suggesting that repulsive constraints or spatial inhomogeneities underlay the spatial organization of heterochromatic compartments. The proposed technique should be useful for identifying further spatial features in a wide range of cell types. PMID:20628576

Real-time distribution of pelagic fish: combining hydroacoustics, GIS and spatial modelling at a fine spatial scale.

PubMed

Muška, Milan; Tušer, Michal; Frouzová, Jaroslava; Mrkvička, Tomáš; Ricard, Daniel; Seďa, Jaromír; Morelli, Federico; Kubečka, Jan

2018-03-29

Understanding spatial distribution of organisms in heterogeneous environment remains one of the chief issues in ecology. Spatial organization of freshwater fish was investigated predominantly on large-scale, neglecting important local conditions and ecological processes. However, small-scale processes are of an essential importance for individual habitat preferences and hence structuring trophic cascades and species coexistence. In this work, we analysed the real-time spatial distribution of pelagic freshwater fish in the Římov Reservoir (Czechia) observed by hydroacoustics in relation to important environmental predictors during 48 hours at 3-h interval. Effect of diurnal cycle was revealed of highest significance in all spatial models with inverse trends between fish distribution and predictors in day and night in general. Our findings highlighted daytime pelagic fish distribution as highly aggregated, with general fish preferences for central, deep and highly illuminated areas, whereas nighttime distribution was more disperse and fish preferred nearshore steep sloped areas with higher depth. This turnover suggests prominent movements of significant part of fish assemblage between pelagic and nearshore areas on a diel basis. In conclusion, hydroacoustics, GIS and spatial modelling proved as valuable tool for predicting local fish distribution and elucidate its drivers, which has far reaching implications for understanding freshwater ecosystem functioning.

Interacting Social and Environmental Predictors for the Spatial Distribution of Conservation Lands

PubMed Central

Baldwin, Robert F.; Leonard, Paul B.

2015-01-01

Conservation decisions should be evaluated for how they meet conservation goals at multiple spatial extents. Conservation easements are land use decisions resulting from a combination of social and environmental conditions. An emerging area of research is the evaluation of spatial distribution of easements and their spatial correlates. We tested the relative influence of interacting social and environmental variables on the spatial distribution of conservation easements by ownership category and conservation status. For the Appalachian region of the United States, an area with a long history of human occupation and complex land uses including public-private conservation, we found that settlement, economic, topographic, and environmental data associated with spatial distribution of easements (N = 4813). Compared to random locations, easements were more likely to be found in lower elevations, in areas of greater agricultural productivity, farther from public protected areas, and nearer other human features. Analysis of ownership and conservation status revealed sources of variation, with important differences between local and state government ownerships relative to non-governmental organizations (NGOs), and among U.S. Geological Survey (USGS) GAP program status levels. NGOs were more likely to have easements nearer protected areas, and higher conservation status, while local governments held easements closer to settlement, and on lands of greater agricultural potential. Logistic interactions revealed environmental variables having effects modified by social correlates, and the strongest predictors overall were social (distance to urban area, median household income, housing density, distance to land trust office). Spatial distribution of conservation lands may be affected by geographic area of influence of conservation groups, suggesting that multi-scale conservation planning strategies may be necessary to satisfy local and regional needs for reserve networks. Our results support previous findings and provide an ecoregion-scale view that conservation easements may provide, at local scales, conservation functions on productive, more developable lands. Conservation easements may complement functions of public protected areas but more research should examine relative landscape-level ecological functions of both forms of protection. PMID:26465155

Interacting Social and Environmental Predictors for the Spatial Distribution of Conservation Lands.

PubMed

Baldwin, Robert F; Leonard, Paul B

2015-01-01

Conservation decisions should be evaluated for how they meet conservation goals at multiple spatial extents. Conservation easements are land use decisions resulting from a combination of social and environmental conditions. An emerging area of research is the evaluation of spatial distribution of easements and their spatial correlates. We tested the relative influence of interacting social and environmental variables on the spatial distribution of conservation easements by ownership category and conservation status. For the Appalachian region of the United States, an area with a long history of human occupation and complex land uses including public-private conservation, we found that settlement, economic, topographic, and environmental data associated with spatial distribution of easements (N = 4813). Compared to random locations, easements were more likely to be found in lower elevations, in areas of greater agricultural productivity, farther from public protected areas, and nearer other human features. Analysis of ownership and conservation status revealed sources of variation, with important differences between local and state government ownerships relative to non-governmental organizations (NGOs), and among U.S. Geological Survey (USGS) GAP program status levels. NGOs were more likely to have easements nearer protected areas, and higher conservation status, while local governments held easements closer to settlement, and on lands of greater agricultural potential. Logistic interactions revealed environmental variables having effects modified by social correlates, and the strongest predictors overall were social (distance to urban area, median household income, housing density, distance to land trust office). Spatial distribution of conservation lands may be affected by geographic area of influence of conservation groups, suggesting that multi-scale conservation planning strategies may be necessary to satisfy local and regional needs for reserve networks. Our results support previous findings and provide an ecoregion-scale view that conservation easements may provide, at local scales, conservation functions on productive, more developable lands. Conservation easements may complement functions of public protected areas but more research should examine relative landscape-level ecological functions of both forms of protection.

Spatiotemporal reconstruction of list-mode PET data.

PubMed

Nichols, Thomas E; Qi, Jinyi; Asma, Evren; Leahy, Richard M

2002-04-01

We describe a method for computing a continuous time estimate of tracer density using list-mode positron emission tomography data. The rate function in each voxel is modeled as an inhomogeneous Poisson process whose rate function can be represented using a cubic B-spline basis. The rate functions are estimated by maximizing the likelihood of the arrival times of detected photon pairs over the control vertices of the spline, modified by quadratic spatial and temporal smoothness penalties and a penalty term to enforce nonnegativity. Randoms rate functions are estimated by assuming independence between the spatial and temporal randoms distributions. Similarly, scatter rate functions are estimated by assuming spatiotemporal independence and that the temporal distribution of the scatter is proportional to the temporal distribution of the trues. A quantitative evaluation was performed using simulated data and the method is also demonstrated in a human study using 11C-raclopride.

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

Spatially orthogonal chemical functionalization of a hierarchical pore network for catalytic cascade reactions

NASA Astrophysics Data System (ADS)

Parlett, Christopher M. A.; Isaacs, Mark A.; Beaumont, Simon K.; Bingham, Laura M.; Hondow, Nicole S.; Wilson, Karen; Lee, Adam F.

2016-02-01

The chemical functionality within porous architectures dictates their performance as heterogeneous catalysts; however, synthetic routes to control the spatial distribution of individual functions within porous solids are limited. Here we report the fabrication of spatially orthogonal bifunctional porous catalysts, through the stepwise template removal and chemical functionalization of an interconnected silica framework. Selective removal of polystyrene nanosphere templates from a lyotropic liquid crystal-templated silica sol-gel matrix, followed by extraction of the liquid crystal template, affords a hierarchical macroporous-mesoporous architecture. Decoupling of the individual template extractions allows independent functionalization of macropore and mesopore networks on the basis of chemical and/or size specificity. Spatial compartmentalization of, and directed molecular transport between, chemical functionalities affords control over the reaction sequence in catalytic cascades; herein illustrated by the Pd/Pt-catalysed oxidation of cinnamyl alcohol to cinnamic acid. We anticipate that our methodology will prompt further design of multifunctional materials comprising spatially compartmentalized functions.

Considering spatial heterogeneity in the distributed lag non-linear model when analyzing spatiotemporal data.

PubMed

Chien, Lung-Chang; Guo, Yuming; Li, Xiao; Yu, Hwa-Lung

2018-01-01

The distributed lag non-linear (DLNM) model has been frequently used in time series environmental health research. However, its functionality for assessing spatial heterogeneity is still restricted, especially in analyzing spatiotemporal data. This study proposed a solution to take a spatial function into account in the DLNM, and compared the influence with and without considering spatial heterogeneity in a case study. This research applied the DLNM to investigate non-linear lag effect up to 7 days in a case study about the spatiotemporal impact of fine particulate matter (PM 2.5 ) on preschool children's acute respiratory infection in 41 districts of northern Taiwan during 2005 to 2007. We applied two spatiotemporal methods to impute missing air pollutant data, and included the Markov random fields to analyze district boundary data in the DLNM. When analyzing the original data without a spatial function, the overall PM 2.5 effect accumulated from all lag-specific effects had a slight variation at smaller PM 2.5 measurements, but eventually decreased to relative risk significantly <1 when PM 2.5 increased. While analyzing spatiotemporal imputed data without a spatial function, the overall PM 2.5 effect did not decrease but increased in monotone as PM 2.5 increased over 20 μg/m 3 . After adding a spatial function in the DLNM, spatiotemporal imputed data conducted similar results compared with the overall effect from the original data. Moreover, the spatial function showed a clear and uneven pattern in Taipei, revealing that preschool children living in 31 districts of Taipei were vulnerable to acute respiratory infection. Our findings suggest the necessity of including a spatial function in the DLNM to make a spatiotemporal analysis available and to conduct more reliable and explainable research. This study also revealed the analytical impact if spatial heterogeneity is ignored.

BATSE analysis techniques for probing the GRB spatial and luminosity distributions

NASA Technical Reports Server (NTRS)

Hakkila, Jon; Meegan, Charles A.

1992-01-01

The Burst And Transient Source Experiment (BATSE) has measured homogeneity and isotropy parameters from an increasingly large sample of observed gamma-ray bursts (GRBs), while also maintaining a summary of the way in which the sky has been sampled. Measurement of both of these are necessary for any study of the BATSE data statistically, as they take into account the most serious observational selection effects known in the study of GRBs: beam-smearing and inhomogeneous, anisotropic sky sampling. Knowledge of these effects is important to analysis of GRB angular and intensity distributions. In addition to determining that the bursts are local, it is hoped that analysis of such distributions will allow boundaries to be placed on the true GRB spatial distribution and luminosity function. The technique for studying GRB spatial and luminosity distributions is direct. Results of BATSE analyses are compared to Monte Carlo models parameterized by a variety of spatial and luminosity characteristics.

Spatial distribution of nuclei in progressive nucleation: Modeling and application

NASA Astrophysics Data System (ADS)

Tomellini, Massimo

2018-04-01

Phase transformations ruled by non-simultaneous nucleation and growth do not lead to random distribution of nuclei. Since nucleation is only allowed in the untransformed portion of space, positions of nuclei are correlated. In this article an analytical approach is presented for computing pair-correlation function of nuclei in progressive nucleation. This quantity is further employed for characterizing the spatial distribution of nuclei through the nearest neighbor distribution function. The modeling is developed for nucleation in 2D space with power growth law and it is applied to describe electrochemical nucleation where correlation effects are significant. Comparison with both computer simulations and experimental data lends support to the model which gives insights into the transition from Poissonian to correlated nearest neighbor probability density.

Small-scale spatial variability of soil microbial community composition and functional diversity in a mixed forest

NASA Astrophysics Data System (ADS)

Wang, Qiufeng; Tian, Jing; Yu, Guirui

2014-05-01

Patterns in the spatial distribution of organisms provide important information about mechanisms that regulate the diversity and complexity of soil ecosystems. Therefore, information on spatial distribution of microbial community composition and functional diversity is urgently necessary. The spatial variability on a 26×36 m plot and vertical distribution (0-10 cm and 10-20 cm) of soil microbial community composition and functional diversity were studied in a natural broad-leaved Korean pine (Pinus koraiensis) mixed forest soil in Changbai Mountain. The phospholipid fatty acid (PLFA) pattern was used to characterize the soil microbial community composition and was compared with the community substrate utilization pattern using Biolog. Bacterial biomass dominated and showed higher variability than fungal biomass at all scales examined. The microbial biomass decreased with soil depths increased and showed less variability in lower 10-20 cm soil layer. The Shannon-Weaver index value for microbial functional diversity showed higher variability in upper 0-10 cm than lower 10-20 cm soil layer. Carbohydrates, carboxylic acids, polymers and amino acids are the main carbon sources possessing higher utilization efficiency or utilization intensity. At the same time, the four carbon source types contributed to the differentiation of soil microbial communities. This study suggests the higher diversity and complexity for this mix forest ecosystem. To determine the driving factors that affect this spatial variability of microorganism is the next step for our study.

Scheduling policies of intelligent sensors and sensor/actuators in flexible structures

NASA Astrophysics Data System (ADS)

Demetriou, Michael A.; Potami, Raffaele

2006-03-01

In this note, we revisit the problem of actuator/sensor placement in large civil infrastructures and flexible space structures within the context of spatial robustness. The positioning of these devices becomes more important in systems employing wireless sensor and actuator networks (WSAN) for improved control performance and for rapid failure detection. The ability of the sensing and actuating devices to possess the property of spatial robustness results in reduced control energy and therefore the spatial distribution of disturbances is integrated into the location optimization measures. In our studies, the structure under consideration is a flexible plate clamped at all sides. First, we consider the case of sensor placement and the optimization scheme attempts to produce those locations that minimize the effects of the spatial distribution of disturbances on the state estimation error; thus the sensor locations produce state estimators with minimized disturbance-to-error transfer function norms. A two-stage optimization procedure is employed whereby one first considers the open loop system and the spatial distribution of disturbances is found that produces the maximal effects on the entire open loop state. Once this "worst" spatial distribution of disturbances is found, the optimization scheme subsequently finds the locations that produce state estimators with minimum transfer function norms. In the second part, we consider the collocated actuator/sensor pairs and the optimization scheme produces those locations that result in compensators with the smallest norms of the disturbance-to-state transfer functions. Going a step further, an intelligent control scheme is presented which, at each time interval, activates a subset of the actuator/sensor pairs in order provide robustness against spatiotemporally moving disturbances and minimize power consumption by keeping some sensor/actuators in sleep mode.

Detection of smoothly distributed spatial outliers, with applications to identifying the distribution of parenchymal hyperinflation following an airway challenge in asthmatics.

PubMed

Thurman, Andrew L; Choi, Jiwoong; Choi, Sanghun; Lin, Ching-Long; Hoffman, Eric A; Lee, Chang Hyun; Chan, Kung-Sik

2017-05-10

Methacholine challenge tests are used to measure changes in pulmonary function that indicate symptoms of asthma. In addition to pulmonary function tests, which measure global changes in pulmonary function, computed tomography images taken at full inspiration before and after administration of methacholine provide local air volume changes (hyper-inflation post methacholine) at individual acinar units, indicating local airway hyperresponsiveness. Some of the acini may have extreme air volume changes relative to the global average, indicating hyperresponsiveness, and those extreme values may occur in clusters. We propose a Gaussian mixture model with a spatial smoothness penalty to improve prediction of hyperresponsive locations that occur in spatial clusters. A simulation study provides evidence that the spatial smoothness penalty improves prediction under different data-generating mechanisms. We apply this method to computed tomography data from Seoul National University Hospital on five healthy and ten asthmatic subjects. Copyright © 2017 John Wiley & Sons, Ltd. Copyright © 2017 John Wiley & Sons, Ltd.

Exploratory study and application of the angular wavelet analysis for assessing the spatial distribution of breakdown spots in Pt/HfO2/Pt structures

NASA Astrophysics Data System (ADS)

Muñoz-Gorriz, J.; Monaghan, S.; Cherkaoui, K.; Suñé, J.; Hurley, P. K.; Miranda, E.

2017-12-01

The angular wavelet analysis is applied for assessing the spatial distribution of breakdown spots in Pt/HfO2/Pt capacitors with areas ranging from 104 to 105 μm2. The breakdown spot lateral sizes are in the range from 1 to 3 μm, and they appear distributed on the top metal electrode as a point pattern. The spots are generated by ramped and constant voltage stresses and are the consequence of microexplosions caused by the formation of shorts spanning the dielectric film. This kind of pattern was analyzed in the past using the conventional spatial analysis tools such as intensity plots, distance histograms, pair correlation function, and nearest neighbours. Here, we show that the wavelet analysis offers an alternative and complementary method for testing whether or not the failure site distribution departs from a complete spatial randomness process in the angular domain. The effect of using different wavelet functions, such as the Haar, Sine, French top hat, Mexican hat, and Morlet, as well as the roles played by the process intensity, the location of the voltage probe, and the aspect ratio of the device, are all discussed.

Spatial distribution of citizen science casuistic observations for different taxonomic groups.

PubMed

Tiago, Patrícia; Ceia-Hasse, Ana; Marques, Tiago A; Capinha, César; Pereira, Henrique M

2017-10-16

Opportunistic citizen science databases are becoming an important way of gathering information on species distributions. These data are temporally and spatially dispersed and could have limitations regarding biases in the distribution of the observations in space and/or time. In this work, we test the influence of landscape variables in the distribution of citizen science observations for eight taxonomic groups. We use data collected through a Portuguese citizen science database (biodiversity4all.org). We use a zero-inflated negative binomial regression to model the distribution of observations as a function of a set of variables representing the landscape features plausibly influencing the spatial distribution of the records. Results suggest that the density of paths is the most important variable, having a statistically significant positive relationship with number of observations for seven of the eight taxa considered. Wetland coverage was also identified as having a significant, positive relationship, for birds, amphibians and reptiles, and mammals. Our results highlight that the distribution of species observations, in citizen science projects, is spatially biased. Higher frequency of observations is driven largely by accessibility and by the presence of water bodies. We conclude that efforts are required to increase the spatial evenness of sampling effort from volunteers.

Modelling and predicting the spatial distribution of tree root density in heterogeneous forest ecosystems

PubMed Central

Mao, Zhun; Saint-André, Laurent; Bourrier, Franck; Stokes, Alexia; Cordonnier, Thomas

2015-01-01

Background and Aims In mountain ecosystems, predicting root density in three dimensions (3-D) is highly challenging due to the spatial heterogeneity of forest communities. This study presents a simple and semi-mechanistic model, named ChaMRoots, that predicts root interception density (RID, number of roots m–2). ChaMRoots hypothesizes that RID at a given point is affected by the presence of roots from surrounding trees forming a polygon shape. Methods The model comprises three sub-models for predicting: (1) the spatial heterogeneity – RID of the finest roots in the top soil layer as a function of tree basal area at breast height, and the distance between the tree and a given point; (2) the diameter spectrum – the distribution of RID as a function of root diameter up to 50 mm thick; and (3) the vertical profile – the distribution of RID as a function of soil depth. The RID data used for fitting in the model were measured in two uneven-aged mountain forest ecosystems in the French Alps. These sites differ in tree density and species composition. Key Results In general, the validation of each sub-model indicated that all sub-models of ChaMRoots had good fits. The model achieved a highly satisfactory compromise between the number of aerial input parameters and the fit to the observed data. Conclusions The semi-mechanistic ChaMRoots model focuses on the spatial distribution of root density at the tree cluster scale, in contrast to the majority of published root models, which function at the level of the individual. Based on easy-to-measure characteristics, simple forest inventory protocols and three sub-models, it achieves a good compromise between the complexity of the case study area and that of the global model structure. ChaMRoots can be easily coupled with spatially explicit individual-based forest dynamics models and thus provides a highly transferable approach for modelling 3-D root spatial distribution in complex forest ecosystems. PMID:26173892

Derivation of spatial patterns of soil hydraulic properties based on pedotransfer functions

USDA-ARS?s Scientific Manuscript database

Spatial patterns in soil hydrology are the product of the spatial distribution of soil hydraulic properties. These properties are notorious for the difficulties and high labor costs involved in measuring them. Often, there is a need to resort to estimating these parameters from other, more readily a...

Spatial distribution and longitudinal development of deep cortical sulcal landmarks in infants.

PubMed

Meng, Yu; Li, Gang; Lin, Weili; Gilmore, John H; Shen, Dinggang

2014-10-15

Sulcal pits, the locally deepest points in sulci of the highly convoluted and variable cerebral cortex, are found to be spatially consistent across human adult individuals. It is suggested that sulcal pits are genetically controlled and have close relationships with functional areas. To date, the existing imaging studies of sulcal pits are mainly focused on adult brains, yet little is known about the spatial distribution and temporal development of sulcal pits in the first 2 years of life, which is the most dynamic and critical period of postnatal brain development. Studying sulcal pits during this period would greatly enrich our limited understandings of the origins and developmental trajectories of sulcal pits, and would also provide important insights into many neurodevelopmental disorders associated with abnormal cortical foldings. In this paper, by using surface-based morphometry, for the first time, we systemically investigated the spatial distribution and temporal development of sulcal pits in major cortical sulci from 73 healthy infants, each with three longitudinal 3T MR scans at term birth, 1 year, and 2 years of age. Our results suggest that the spatially consistent distributions of sulcal pits in major sulci across individuals have already existed at term birth and this spatial distribution pattern keeps relatively stable in the first 2 years of life, despite that the cerebral cortex expands dramatically and the sulcal depth increases considerably during this period. Specially, the depth of sulcal pits increases regionally heterogeneously, with more rapid growth in the high-order association cortex, including the prefrontal and temporal cortices, than the sensorimotor cortex in the first 2 years of life. Meanwhile, our results also suggest that there exist hemispheric asymmetries of the spatial distributions of sulcal pits in several cortical regions, such as the central, superior temporal and postcentral sulci, consistently from birth to 2 years of age, which likely has close relationships with the lateralization of brain functions of these regions. This study provides detailed insights into the spatial distribution and temporal development of deep sulcal landmarks in infants. Copyright © 2014 Elsevier Inc. All rights reserved.

Three-dimensional analytical model for the spatial variation of the foreshock electron distribution function - Systematics and comparisons with ISEE observations

NASA Technical Reports Server (NTRS)

Fitzenreiter, R. J.; Scudder, J. D.; Klimas, A. J.

1990-01-01

A model which is consistent with the solar wind and shock surface boundary conditions for the foreshock electron distribution in the absence of wave-particle effects is formulated for an arbitrary location behind the magnetic tangent to the earth's bow shock. Variations of the gyrophase-averaged velocity distribution are compared and contrasted with in situ ISEE observations. It is found that magnetic mirroring of solar wind electrons is the most important process by which nonmonotonic reduced electron distributions in the foreshock are produced. Leakage of particles from the magnetosheath is shown to be relatively unimportant in determining reduced distributions that are nonmonotonic. The two-dimensional distribution function off the magnetic field direction is the crucial contribution in producing reduced distributions which have beams. The time scale for modification of the electron velocity distribution in velocity space can be significantly influenced by steady state spatial gradients in the background imposed by the curved shock geometry.

Interpolating Non-Parametric Distributions of Hourly Rainfall Intensities Using Random Mixing

NASA Astrophysics Data System (ADS)

Mosthaf, Tobias; Bárdossy, András; Hörning, Sebastian

2015-04-01

The correct spatial interpolation of hourly rainfall intensity distributions is of great importance for stochastical rainfall models. Poorly interpolated distributions may lead to over- or underestimation of rainfall and consequently to wrong estimates of following applications, like hydrological or hydraulic models. By analyzing the spatial relation of empirical rainfall distribution functions, a persistent order of the quantile values over a wide range of non-exceedance probabilities is observed. As the order remains similar, the interpolation weights of quantile values for one certain non-exceedance probability can be applied to the other probabilities. This assumption enables the use of kernel smoothed distribution functions for interpolation purposes. Comparing the order of hourly quantile values over different gauges with the order of their daily quantile values for equal probabilities, results in high correlations. The hourly quantile values also show high correlations with elevation. The incorporation of these two covariates into the interpolation is therefore tested. As only positive interpolation weights for the quantile values assure a monotonically increasing distribution function, the use of geostatistical methods like kriging is problematic. Employing kriging with external drift to incorporate secondary information is not applicable. Nonetheless, it would be fruitful to make use of covariates. To overcome this shortcoming, a new random mixing approach of spatial random fields is applied. Within the mixing process hourly quantile values are considered as equality constraints and correlations with elevation values are included as relationship constraints. To profit from the dependence of daily quantile values, distribution functions of daily gauges are used to set up lower equal and greater equal constraints at their locations. In this way the denser daily gauge network can be included in the interpolation of the hourly distribution functions. The applicability of this new interpolation procedure will be shown for around 250 hourly rainfall gauges in the German federal state of Baden-Württemberg. The performance of the random mixing technique within the interpolation is compared to applicable kriging methods. Additionally, the interpolation of kernel smoothed distribution functions is compared with the interpolation of fitted parametric distributions.

Spatio-temporal patterns of key exploited marine species in the Northwestern Mediterranean Sea.

PubMed

Morfin, Marie; Fromentin, Jean-Marc; Jadaud, Angélique; Bez, Nicolas

2012-01-01

This study analyzes the temporal variability/stability of the spatial distributions of key exploited species in the Gulf of Lions (Northwestern Mediterranean Sea). To do so, we analyzed data from the MEDITS bottom-trawl scientific surveys from 1994 to 2010 at 66 fixed stations and selected 12 key exploited species. We proposed a geostatistical approach to handle zero-inflated and non-stationary distributions and to test for the temporal stability of the spatial structures. Empirical Orthogonal Functions and other descriptors were then applied to investigate the temporal persistence and the characteristics of the spatial patterns. The spatial structure of the distribution (i.e. the pattern of spatial autocorrelation) of the 12 key species studied remained highly stable over the time period sampled. The spatial distributions of all species obtained through kriging also appeared to be stable over time, while each species displayed a specific spatial distribution. Furthermore, adults were generally more densely concentrated than juveniles and occupied areas included in the distribution of juveniles. Despite the strong persistence of spatial distributions, we also observed that the area occupied by each species was correlated to its abundance: the more abundant the species, the larger the occupation area. Such a result tends to support MacCall's basin theory, according to which density-dependence responses would drive the expansion of those 12 key species in the Gulf of Lions. Further analyses showed that these species never saturated their habitats, suggesting that they are below their carrying capacity; an assumption in agreement with the overexploitation of several of these species. Finally, the stability of their spatial distributions over time and their potential ability to diffuse outside their main habitats give support to Marine Protected Areas as a potential pertinent management tool.

Direct numerical solution of the Ornstein-Zernike integral equation and spatial distribution of water around hydrophobic molecules

NASA Astrophysics Data System (ADS)

Ikeguchi, Mitsunori; Doi, Junta

1995-09-01

The Ornstein-Zernike integral equation (OZ equation) has been used to evaluate the distribution function of solvents around solutes, but its numerical solution is difficult for molecules with a complicated shape. This paper proposes a numerical method to directly solve the OZ equation by introducing the 3D lattice. The method employs no approximation the reference interaction site model (RISM) equation employed. The method enables one to obtain the spatial distribution of spherical solvents around solutes with an arbitrary shape. Numerical accuracy is sufficient when the grid-spacing is less than 0.5 Å for solvent water. The spatial water distribution around a propane molecule is demonstrated as an example of a nonspherical hydrophobic molecule using iso-value surfaces. The water model proposed by Pratt and Chandler is used. The distribution agrees with the molecular dynamics simulation. The distribution increases offshore molecular concavities. The spatial distribution of water around 5α-cholest-2-ene (C27H46) is visualized using computer graphics techniques and a similar trend is observed.

Documentation of programs that compute 1) static tilts for a spatially variable slip distribution, and 2) quasi-static tilts produced by an expanding dislocation loop with a spatially variable slip distribution

USGS Publications Warehouse

McHugh, Stuart

1976-01-01

The material in this report is concerned with the effects of a vertically oriented rectangular dislocation loop on the tilts observed at the free surface of an elastic half-space. Part I examines the effect of a spatially variable static strike-slip distribution across the slip surface. The tilt components as a function of distance parallel, or perpendicular, to the strike of the slip surface are displayed for different slip-versus-distance profiles. Part II examines the effect of spatially and temporally variable slip distributions across the dislocation loop on the quasi-static tilts at the free surface of an elastic half space. The model discussed in part II may be used to generate theoretical tilt versus time curves produced by creep events.

Double Wigner distribution function of a first-order optical system with a hard-edge aperture.

PubMed

Pan, Weiqing

2008-01-01

The effect of an apertured optical system on Wigner distribution can be expressed as a superposition integral of the input Wigner distribution function and the double Wigner distribution function of the apertured optical system. By introducing a hard aperture function into a finite sum of complex Gaussian functions, the double Wigner distribution functions of a first-order optical system with a hard aperture outside and inside it are derived. As an example of application, the analytical expressions of the Wigner distribution for a Gaussian beam passing through a spatial filtering optical system with an internal hard aperture are obtained. The analytical results are also compared with the numerical integral results, and they show that the analytical results are proper and ascendant.

Statistical characteristics of the spatial distribution of territorial contamination by radionuclides from the Chernobyl accident

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

Arutyunyan, R.V.; Bol`shov, L.A.; Vasil`ev, S.K.

1994-06-01

The objective of this study was to clarify a number of issues related to the spatial distribution of contaminants from the Chernobyl accident. The effects of local statistics were addressed by collecting and analyzing (for Cesium 137) soil samples from a number of regions, and it was found that sample activity differed by a factor of 3-5. The effect of local non-uniformity was estimated by modeling the distribution of the average activity of a set of five samples for each of the regions, with the spread in the activities for a {+-}2 range being equal to 25%. The statistical characteristicsmore » of the distribution of contamination were then analyzed and found to be a log-normal distribution with the standard deviation being a function of test area. All data for the Bryanskaya Oblast area were analyzed statistically and were adequately described by a log-normal function.« less

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.

Potential and flux field landscape theory. I. Global stability and dynamics of spatially dependent non-equilibrium systems.

PubMed

Wu, Wei; Wang, Jin

2013-09-28

We established a potential and flux field landscape theory to quantify the global stability and dynamics of general spatially dependent non-equilibrium deterministic and stochastic systems. We extended our potential and flux landscape theory for spatially independent non-equilibrium stochastic systems described by Fokker-Planck equations to spatially dependent stochastic systems governed by general functional Fokker-Planck equations as well as functional Kramers-Moyal equations derived from master equations. Our general theory is applied to reaction-diffusion systems. For equilibrium spatially dependent systems with detailed balance, the potential field landscape alone, defined in terms of the steady state probability distribution functional, determines the global stability and dynamics of the system. The global stability of the system is closely related to the topography of the potential field landscape in terms of the basins of attraction and barrier heights in the field configuration state space. The effective driving force of the system is generated by the functional gradient of the potential field alone. For non-equilibrium spatially dependent systems, the curl probability flux field is indispensable in breaking detailed balance and creating non-equilibrium condition for the system. A complete characterization of the non-equilibrium dynamics of the spatially dependent system requires both the potential field and the curl probability flux field. While the non-equilibrium potential field landscape attracts the system down along the functional gradient similar to an electron moving in an electric field, the non-equilibrium flux field drives the system in a curly way similar to an electron moving in a magnetic field. In the small fluctuation limit, the intrinsic potential field as the small fluctuation limit of the potential field for spatially dependent non-equilibrium systems, which is closely related to the steady state probability distribution functional, is found to be a Lyapunov functional of the deterministic spatially dependent system. Therefore, the intrinsic potential landscape can characterize the global stability of the deterministic system. The relative entropy functional of the stochastic spatially dependent non-equilibrium system is found to be the Lyapunov functional of the stochastic dynamics of the system. Therefore, the relative entropy functional quantifies the global stability of the stochastic system with finite fluctuations. Our theory offers an alternative general approach to other field-theoretic techniques, to study the global stability and dynamics of spatially dependent non-equilibrium field systems. It can be applied to many physical, chemical, and biological spatially dependent non-equilibrium systems.

Understanding the brain through its spatial structure

NASA Astrophysics Data System (ADS)

Morrison, Will Zachary

The spatial location of cells in neural tissue can be easily extracted from many imaging modalities, but the information contained in spatial relationships between cells is seldom utilized. This is because of a lack of recognition of the importance of spatial relationships to some aspects of brain function, and the reflection in spatial statistics of other types of information. The mathematical tools necessary to describe spatial relationships are also unknown to many neuroscientists, and biologists in general. We analyze two cases, and show that spatial relationships can be used to understand the role of a particular type of cell, the astrocyte, in Alzheimer's disease, and that the geometry of axons in the brain's white matter sheds light on the process of establishing connectivity between areas of the brain. Astrocytes provide nutrients for neuronal metabolism, and regulate the chemical environment of the brain, activities that require manipulation of spatial distributions (of neurotransmitters, for example). We first show, through the use of a correlation function, that inter-astrocyte forces determine the size of independent regulatory domains in the cortex. By examining the spatial distribution of astrocytes in a mouse model of Alzheimer's Disease, we determine that astrocytes are not actively transported to fight the disease, as was previously thought. The paths axons take through the white matter determine which parts of the brain are connected, and how quickly signals are transmitted. The rules that determine these paths (i.e. shortest distance) are currently unknown. By measurement of axon orientation distributions using three-point correlation functions and the statistics of axon turning and branching, we reveal that axons are restricted to growth in three directions, like a taxicab traversing city blocks, albeit in three-dimensions. We show how geometric restrictions at the small scale are related to large-scale trajectories. Finally we discuss the implications of this finding for experimental and theoretical connectomics.

Numerical Simulation of Abandoned Gob Methane Drainage through Surface Vertical Wells

PubMed Central

Hu, Guozhong

2015-01-01

The influence of the ventilation system on the abandoned gob weakens, so the gas seepage characteristics in the abandoned gob are significantly different from those in a normal mining gob. In connection with this, this study physically simulated the movement of overlying rock strata. A spatial distribution function for gob permeability was derived. A numerical model using FLUENT for abandoned gob methane drainage through surface wells was established, and the derived spatial distribution function for gob permeability was imported into the numerical model. The control range of surface wells, flow patterns and distribution rules for static pressure in the abandoned gob under different well locations were determined using the calculated results from the numerical model. PMID:25955438

A spatial scan statistic for survival data based on Weibull distribution.

PubMed

Bhatt, Vijaya; Tiwari, Neeraj

2014-05-20

The spatial scan statistic has been developed as a geographical cluster detection analysis tool for different types of data sets such as Bernoulli, Poisson, ordinal, normal and exponential. We propose a scan statistic for survival data based on Weibull distribution. It may also be used for other survival distributions, such as exponential, gamma, and log normal. The proposed method is applied on the survival data of tuberculosis patients for the years 2004-2005 in Nainital district of Uttarakhand, India. Simulation studies reveal that the proposed method performs well for different survival distribution functions. Copyright © 2013 John Wiley & Sons, Ltd.

Particle Size Distributions in Atmospheric Clouds

NASA Technical Reports Server (NTRS)

Paoli, Roberto; Shariff, Karim

2003-01-01

In this note, we derive a transport equation for a spatially integrated distribution function of particles size that is suitable for sparse particle systems, such as in atmospheric clouds. This is done by integrating a Boltzmann equation for a (local) distribution function over an arbitrary but finite volume. A methodology for evolving the moments of the integrated distribution is presented. These moments can be either tracked for a finite number of discrete populations ('clusters') or treated as continuum variables.

Spatial Preference Modelling for equitable infrastructure provision: an application of Sen's Capability Approach

NASA Astrophysics Data System (ADS)

Wismadi, Arif; Zuidgeest, Mark; Brussel, Mark; van Maarseveen, Martin

2014-01-01

To determine whether the inclusion of spatial neighbourhood comparison factors in Preference Modelling allows spatial decision support systems (SDSSs) to better address spatial equity, we introduce Spatial Preference Modelling (SPM). To evaluate the effectiveness of this model in addressing equity, various standardisation functions in both Non-Spatial Preference Modelling and SPM are compared. The evaluation involves applying the model to a resource location-allocation problem for transport infrastructure in the Special Province of Yogyakarta in Indonesia. We apply Amartya Sen's Capability Approach to define opportunity to mobility as a non-income indicator. Using the extended Moran's I interpretation for spatial equity, we evaluate the distribution output regarding, first, `the spatial distribution patterns of priority targeting for allocation' (SPT) and, second, `the effect of new distribution patterns after location-allocation' (ELA). The Moran's I index of the initial map and its comparison with six patterns for SPT as well as ELA consistently indicates that the SPM is more effective for addressing spatial equity. We conclude that the inclusion of spatial neighbourhood comparison factors in Preference Modelling improves the capability of SDSS to address spatial equity. This study thus proposes a new formal method for SDSS with specific attention on resource location-allocation to address spatial equity.

Spatial Point Pattern Analysis of Neurons Using Ripley's K-Function in 3D

PubMed Central

Jafari-Mamaghani, Mehrdad; Andersson, Mikael; Krieger, Patrik

2010-01-01

The aim of this paper is to apply a non-parametric statistical tool, Ripley's K-function, to analyze the 3-dimensional distribution of pyramidal neurons. Ripley's K-function is a widely used tool in spatial point pattern analysis. There are several approaches in 2D domains in which this function is executed and analyzed. Drawing consistent inferences on the underlying 3D point pattern distributions in various applications is of great importance as the acquisition of 3D biological data now poses lesser of a challenge due to technological progress. As of now, most of the applications of Ripley's K-function in 3D domains do not focus on the phenomenon of edge correction, which is discussed thoroughly in this paper. The main goal is to extend the theoretical and practical utilization of Ripley's K-function and corresponding tests based on bootstrap resampling from 2D to 3D domains. PMID:20577588

Chord-length and free-path distribution functions for many-body systems

NASA Astrophysics Data System (ADS)

Lu, Binglin; Torquato, S.

1993-04-01

We study fundamental morphological descriptors of disordered media (e.g., heterogeneous materials, liquids, and amorphous solids): the chord-length distribution function p(z) and the free-path distribution function p(z,a). For concreteness, we will speak in the language of heterogeneous materials composed of two different materials or ``phases.'' The probability density function p(z) describes the distribution of chord lengths in the sample and is of great interest in stereology. For example, the first moment of p(z) is the ``mean intercept length'' or ``mean chord length.'' The chord-length distribution function is of importance in transport phenomena and problems involving ``discrete free paths'' of point particles (e.g., Knudsen diffusion and radiative transport). The free-path distribution function p(z,a) takes into account the finite size of a simple particle of radius a undergoing discrete free-path motion in the heterogeneous material and we show that it is actually the chord-length distribution function for the system in which the ``pore space'' is the space available to a finite-sized particle of radius a. Thus it is shown that p(z)=p(z,0). We demonstrate that the functions p(z) and p(z,a) are related to another fundamentally important morphological descriptor of disordered media, namely, the so-called lineal-path function L(z) studied by us in previous work [Phys. Rev. A 45, 922 (1992)]. The lineal path function gives the probability of finding a line segment of length z wholly in one of the ``phases'' when randomly thrown into the sample. We derive exact series representations of the chord-length and free-path distribution functions for systems of spheres with a polydispersivity in size in arbitrary dimension D. For the special case of spatially uncorrelated spheres (i.e., fully penetrable spheres) we evaluate exactly the aforementioned functions, the mean chord length, and the mean free path. We also obtain corresponding analytical formulas for the case of mutually impenetrable (i.e., spatially correlated) polydispersed spheres.

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

NASA Astrophysics Data System (ADS)

Erfanifard, Y.; Rezayan, F.

2014-10-01

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

Spatially distributed modal signals of free shallow membrane shell structronic system

NASA Astrophysics Data System (ADS)

Yue, H. H.; Deng, Z. Q.; Tzou, H. S.

2008-11-01

Based on the smart material and structronics technology, distributed sensor and control of shell structures have been rapidly developed for the last 20 years. This emerging technology has been utilized in aerospace, telecommunication, micro-electromechanical systems and other engineering applications. However, distributed monitoring technique and its resulting global spatially distributed sensing signals of shallow paraboloidal membrane shells are not clearly understood. In this paper, modeling of free flexible paraboloidal shell with spatially distributed sensor, micro-sensing signal characteristics, and location of distributed piezoelectric sensor patches are investigated based on a new set of assumed mode shape functions. Parametric analysis indicates that the signal generation depends on modal membrane strains in the meridional and circumferential directions in which the latter is more significant than the former, when all bending strains vanish in membrane shells. This study provides a modeling and analysis technique for distributed sensors laminated on lightweight paraboloidal flexible structures and identifies critical components and regions that generate significant signals.

Delineating Hydrofacies Spatial Distribution by Integrating Ensemble Data Assimilation and Indicator Geostatistics

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

Song, Xuehang; Chen, Xingyuan; Ye, Ming

2015-07-01

This study develops a new framework of facies-based data assimilation for characterizing spatial distribution of hydrofacies and estimating their associated hydraulic properties. This framework couples ensemble data assimilation with transition probability-based geostatistical model via a parameterization based on a level set function. The nature of ensemble data assimilation makes the framework efficient and flexible to be integrated with various types of observation data. The transition probability-based geostatistical model keeps the updated hydrofacies distributions under geological constrains. The framework is illustrated by using a two-dimensional synthetic study that estimates hydrofacies spatial distribution and permeability in each hydrofacies from transient head data.more » Our results show that the proposed framework can characterize hydrofacies distribution and associated permeability with adequate accuracy even with limited direct measurements of hydrofacies. Our study provides a promising starting point for hydrofacies delineation in complex real problems.« less

Measurement of the Spatial Distribution of the Spectral Response Variation in the Field of View of the ASD Spectrometer Input Optics

DTIC Science & Technology

2014-12-01

development. It will be used for the measurement of the spectro-polarimetric BRDF (Bidirectional Reflectance Distribution function). For practical reasons...goniomètre est en développement. Il sera utilisé pour les mesures de BRDF (fonction de distribution de réflectance bidirectionnelle) spectrales et...by the independent measurements of the spectral and Bidirectional Reflectance Distribution Function ( BRDF ). The BRDF is the measurement of the

[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.

Spatial and temporal structure of typhoid outbreaks in Washington, D.C., 1906–1909: evaluating local clustering with the Gi* statistic

PubMed Central

Hinman, Sarah E; Blackburn, Jason K; Curtis, Andrew

2006-01-01

Background To better understand the distribution of typhoid outbreaks in Washington, D.C., the U.S. Public Health Service (PHS) conducted four investigations of typhoid fever. These studies included maps of cases reported between 1 May – 31 October 1906 – 1909. These data were entered into a GIS database and analyzed using Ripley's K-function followed by the Gi* statistic in yearly intervals to evaluate spatial clustering, the scale of clustering, and the temporal stability of these clusters. Results The Ripley's K-function indicated no global spatial autocorrelation. The Gi* statistic indicated clustering of typhoid at multiple scales across the four year time period, refuting the conclusions drawn in all four PHS reports concerning the distribution of cases. While the PHS reports suggested an even distribution of the disease, this study quantified both areas of localized disease clustering, as well as mobile larger regions of clustering. Thus, indicating both highly localized and periodic generalized sources of infection within the city. Conclusion The methodology applied in this study was useful for evaluating the spatial distribution and annual-level temporal patterns of typhoid outbreaks in Washington, D.C. from 1906 to 1909. While advanced spatial analyses of historical data sets must be interpreted with caution, this study does suggest that there is utility in these types of analyses and that they provide new insights into the urban patterns of typhoid outbreaks during the early part of the twentieth century. PMID:16566830

Spatial and temporal structure of typhoid outbreaks in Washington, D.C., 1906-1909: evaluating local clustering with the Gi* statistic.

PubMed

Hinman, Sarah E; Blackburn, Jason K; Curtis, Andrew

2006-03-27

To better understand the distribution of typhoid outbreaks in Washington, D.C., the U.S. Public Health Service (PHS) conducted four investigations of typhoid fever. These studies included maps of cases reported between 1 May - 31 October 1906 - 1909. These data were entered into a GIS database and analyzed using Ripley's K-function followed by the Gi* statistic in yearly intervals to evaluate spatial clustering, the scale of clustering, and the temporal stability of these clusters. The Ripley's K-function indicated no global spatial autocorrelation. The Gi* statistic indicated clustering of typhoid at multiple scales across the four year time period, refuting the conclusions drawn in all four PHS reports concerning the distribution of cases. While the PHS reports suggested an even distribution of the disease, this study quantified both areas of localized disease clustering, as well as mobile larger regions of clustering. Thus, indicating both highly localized and periodic generalized sources of infection within the city. The methodology applied in this study was useful for evaluating the spatial distribution and annual-level temporal patterns of typhoid outbreaks in Washington, D.C. from 1906 to 1909. While advanced spatial analyses of historical data sets must be interpreted with caution, this study does suggest that there is utility in these types of analyses and that they provide new insights into the urban patterns of typhoid outbreaks during the early part of the twentieth century.

Spatial distribution of filament elasticity determines the migratory behaviors of a cell

PubMed Central

Harn, Hans I-Chen; Hsu, Chao-Kai; Wang, Yang-Kao; Huang, Yi-Wei; Chiu, Wen-Tai; Lin, Hsi-Hui; Cheng, Chao-Min; Tang, Ming-Jer

2016-01-01

ABSTRACT Any cellular response leading to morphological changes is highly tuned to balance the force generated from structural reorganization, provided by actin cytoskeleton. Actin filaments serve as the backbone of intracellular force, and transduce external mechanical signal via focal adhesion complex into the cell. During migration, cells not only undergo molecular changes but also rapid mechanical modulation. Here we focus on determining, the role of spatial distribution of mechanical changes of actin filaments in epithelial, mesenchymal, fibrotic and cancer cells with non-migration, directional migration, and non-directional migration behaviors using the atomic force microscopy. We found 1) non-migratory cells only generated one type of filament elasticity, 2) cells generating spatially distributed two types of filament elasticity showed directional migration, and 3) pathologic cells that autonomously generated two types of filament elasticity without spatial distribution were actively migrating non-directionally. The demonstration of spatial regulation of filament elasticity of different cell types at the nano-scale highlights the coupling of cytoskeletal function with physical characters at the sub-cellular level, and provides new research directions for migration related disease. PMID:26919488

Secure and Resilient Functional Modeling for Navy Cyber-Physical Systems

DTIC Science & Technology

2017-05-24

Functional Modeling Compiler (SCCT) FM Compiler and Key Performance Indicators (KPI) May 2018 Pending. Model Management Backbone (SCCT) MMB Demonstration...implement the agent- based distributed runtime. - KPIs for single/multicore controllers and temporal/spatial domains. - Integration of the model management ...Distributed Runtime (UCI) Not started. Model Management Backbone (SCCT) Not started. Siemens Corporation Corporate Technology Unrestricted

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.

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

PubMed

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

2011-03-01

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

Arc_Mat: a Matlab-based spatial data analysis toolbox

NASA Astrophysics Data System (ADS)

Liu, Xingjian; Lesage, James

2010-03-01

This article presents an overview of Arc_Mat, a Matlab-based spatial data analysis software package whose source code has been placed in the public domain. An earlier version of the Arc_Mat toolbox was developed to extract map polygon and database information from ESRI shapefiles and provide high quality mapping in the Matlab software environment. We discuss revisions to the toolbox that: utilize enhanced computing and graphing capabilities of more recent versions of Matlab, restructure the toolbox with object-oriented programming features, and provide more comprehensive functions for spatial data analysis. The Arc_Mat toolbox functionality includes basic choropleth mapping; exploratory spatial data analysis that provides exploratory views of spatial data through various graphs, for example, histogram, Moran scatterplot, three-dimensional scatterplot, density distribution plot, and parallel coordinate plots; and more formal spatial data modeling that draws on the extensive Spatial Econometrics Toolbox functions. A brief review of the design aspects of the revised Arc_Mat is described, and we provide some illustrative examples that highlight representative uses of the toolbox. Finally, we discuss programming with and customizing the Arc_Mat toolbox functionalities.

Orbit Tomography: A Method for Determining the Population of Individual Fast-ion Orbits from Experimental Measurements

NASA Astrophysics Data System (ADS)

Stagner, L.; Heidbrink, W. W.

2017-10-01

Due to the complicated nature of the fast-ion distribution function, diagnostic velocity-space weight functions are used to analyze experimental data. In a technique known as Velocity-space Tomography (VST), velocity-space weight functions are combined with experimental measurements to create a system of linear equations that can be solved. However, VST (which by definition ignores spatial dependencies) is restricted, both by the accuracy of its forward model and also by the availability of spatially overlapping diagnostics. In this work we extend velocity-space weight functions to a full 6D generalized coordinate system and then show how to reduce them to a 3D orbit-space without loss of generality using an action-angle formulation. Furthermore, we show how diagnostic orbit-weight functions can be used to infer the full fast-ion distribution function, i.e. Orbit Tomography. Examples of orbit weights functions for different diagnostics and reconstructions of fast-ion distributions are shown for DIII-D experiments. This work was supported by the U.S. Department of Energy under DE-AC02-09CH11466 and DE-FC02-04ER54698.

Parasitism alters three power laws of scaling in a metazoan community: Taylor’s law, density-mass allometry, and variance-mass allometry

PubMed Central

Lagrue, Clément; Poulin, Robert; Cohen, Joel E.

2015-01-01

How do the lifestyles (free-living unparasitized, free-living parasitized, and parasitic) of animal species affect major ecological power-law relationships? We investigated this question in metazoan communities in lakes of Otago, New Zealand. In 13,752 samples comprising 1,037,058 organisms, we found that species of different lifestyles differed in taxonomic distribution and body mass and were well described by three power laws: a spatial Taylor’s law (the spatial variance in population density was a power-law function of the spatial mean population density); density-mass allometry (the spatial mean population density was a power-law function of mean body mass); and variance-mass allometry (the spatial variance in population density was a power-law function of mean body mass). To our knowledge, this constitutes the first empirical confirmation of variance-mass allometry for any animal community. We found that the parameter values of all three relationships differed for species with different lifestyles in the same communities. Taylor's law and density-mass allometry accurately predicted the form and parameter values of variance-mass allometry. We conclude that species of different lifestyles in these metazoan communities obeyed the same major ecological power-law relationships but did so with parameters specific to each lifestyle, probably reflecting differences among lifestyles in population dynamics and spatial distribution. PMID:25550506

Parasitism alters three power laws of scaling in a metazoan community: Taylor's law, density-mass allometry, and variance-mass allometry.

PubMed

Lagrue, Clément; Poulin, Robert; Cohen, Joel E

2015-02-10

How do the lifestyles (free-living unparasitized, free-living parasitized, and parasitic) of animal species affect major ecological power-law relationships? We investigated this question in metazoan communities in lakes of Otago, New Zealand. In 13,752 samples comprising 1,037,058 organisms, we found that species of different lifestyles differed in taxonomic distribution and body mass and were well described by three power laws: a spatial Taylor's law (the spatial variance in population density was a power-law function of the spatial mean population density); density-mass allometry (the spatial mean population density was a power-law function of mean body mass); and variance-mass allometry (the spatial variance in population density was a power-law function of mean body mass). To our knowledge, this constitutes the first empirical confirmation of variance-mass allometry for any animal community. We found that the parameter values of all three relationships differed for species with different lifestyles in the same communities. Taylor's law and density-mass allometry accurately predicted the form and parameter values of variance-mass allometry. We conclude that species of different lifestyles in these metazoan communities obeyed the same major ecological power-law relationships but did so with parameters specific to each lifestyle, probably reflecting differences among lifestyles in population dynamics and spatial distribution.

Optical filter highlighting spectral features part II: quantitative measurements of cosmetic foundation and assessment of their spatial distributions under realistic facial conditions.

PubMed

Nishino, Ken; Nakamura, Mutsuko; Matsumoto, Masayuki; Tanno, Osamu; Nakauchi, Shigeki

2011-03-28

We previously proposed a filter that could detect cosmetic foundations with high discrimination accuracy [Opt. Express 19, 6020 (2011)]. This study extends the filter's functionality to the quantification of the amount of foundation and applies the filter for the assessment of spatial distributions of foundation under realistic facial conditions. Human faces that are applied with quantitatively controlled amounts of cosmetic foundations were measured using the filter. A calibration curve between pixel values of the image and the amount of foundation was created. The optical filter was applied to visualize spatial foundation distributions under realistic facial conditions, which clearly indicated areas on the face where foundation remained even after cleansing. Results confirm that the proposed filter could visualize and nondestructively inspect the foundation distributions.

Revealing the spatial region of a future fracture nucleation in heterogeneous materials at the initial deformation stage

NASA Astrophysics Data System (ADS)

Damaskinskaya, Ekaterina; Hilarov, Vladimir; Frolov, Dmitriy

2016-11-01

The energy distributions of acoustic emission (AE) signals have been analyzed on two scaling levels corresponding to deformation of granite samples and processes on a commercial mining enterprise. It is established that, in cases of localized fracture, the energy distribution of AE signals has shape described by a power law, while a dispersed fracture is characterized by an exponential energy distribution of the AE signals. Analysis of the functional form of the energy distribution performed at the initial stage of loading allows one to recognize a spatial region in the sample where localization of the defect formation will subsequently take place.

Quantitative Mapping of the Spatial Distribution of Nanoparticles in Endo-Lysosomes by Local pH.

PubMed

Wang, Jing; MacEwan, Sarah R; Chilkoti, Ashutosh

2017-02-08

Understanding the intracellular distribution and trafficking of nanoparticle drug carriers is necessary to elucidate their mechanisms of drug delivery and is helpful in the rational design of novel nanoparticle drug delivery systems. The traditional immunofluorescence method to study intracellular distribution of nanoparticles using organelle-specific antibodies is laborious and subject to artifacts. As an alternative, we developed a new method that exploits ratiometric fluorescence imaging of a pH-sensitive Lysosensor dye to visualize and quantify the spatial distribution of nanoparticles in the endosomes and lysosomes of live cells. Using this method, we compared the endolysosomal distribution of cell-penetrating peptide (CPP)-functionalized micelles to unfunctionalized micelles and found that CPP-functionalized micelles exhibited faster endosome-to-lysosome trafficking than unfunctionalized micelles. Ratiometric fluorescence imaging of pH-sensitive Lysosensor dye allows rapid quantitative mapping of nanoparticle distribution in endolysosomes in live cells while minimizing artifacts caused by extensive sample manipulation typical of alternative approaches. This new method can thus serve as an alternative to traditional immunofluorescence approaches to study the intracellular distribution and trafficking of nanoparticles within endosomes and lysosomes.

Variable optical attenuator and dynamic mode group equalizer for few mode fibers.

PubMed

Blau, Miri; Weiss, Israel; Gerufi, Jonathan; Sinefeld, David; Bin-Nun, Moran; Lingle, Robert; Grüner-Nielsen, Lars; Marom, Dan M

2014-12-15

Variable optical attenuation (VOA) for three-mode fiber is experimentally presented, utilizing an amplitude spatial light modulator (SLM), achieving up to -28dB uniform attenuation for all modes. Using the ability to spatially vary the attenuation distribution with the SLM, we also achieve up to 10dB differential attenuation between the fiber's two supported mode group (LP₀₁ and LP₁₁). The spatially selective attenuation serves as the basis of a dynamic mode-group equalizer (DME), potentially gain-balancing mode dependent optical amplification. We extend the experimental three mode DME functionality with a performance analysis of a fiber supporting 6 spatial modes in four mode groups. The spatial modes' distribution and overlap limit the available dynamic range and performance of the DME in the higher mode count case.

Discrete distributed strain sensing of intelligent structures

NASA Technical Reports Server (NTRS)

Anderson, Mark S.; Crawley, Edward F.

1992-01-01

Techniques are developed for the design of discrete highly distributed sensor systems for use in intelligent structures. First the functional requirements for such a system are presented. Discrete spatially averaging strain sensors are then identified as satisfying the functional requirements. A variety of spatial weightings for spatially averaging sensors are examined, and their wave number characteristics are determined. Preferable spatial weightings are identified. Several numerical integration rules used to integrate such sensors in order to determine the global deflection of the structure are discussed. A numerical simulation is conducted using point and rectangular sensors mounted on a cantilevered beam under static loading. Gage factor and sensor position uncertainties are incorporated to assess the absolute error and standard deviation of the error in the estimated tip displacement found by numerically integrating the sensor outputs. An experiment is carried out using a statically loaded cantilevered beam with five point sensors. It is found that in most cases the actual experimental error is within one standard deviation of the absolute error as found in the numerical simulation.

A spatial scaling relationship for soil moisture in a semiarid landscape, using spatial scaling relationships for pedology

NASA Astrophysics Data System (ADS)

Willgoose, G. R.; Chen, M.; Cohen, S.; Saco, P. M.; Hancock, G. R.

2013-12-01

In humid areas it is generally considered that soil moisture scales spatially according to the wetness index of the landscape. This scaling arises from lateral flow downslope of ground water within the soil zone. However, in semi-arid and drier regions, this lateral flow is small and fluxes are dominated by vertical flows driven by infiltration and evapotranspiration. Thus, in the absence of runon processes, soil moisture at a location is more driven by local factors such as soil and vegetation properties at that location rather than upstream processes draining to that point. The 'apparent' spatial randomness of soil and vegetation properties generally suggests that soil moisture for semi-arid regions is spatially random. In this presentation a new analysis of neutron probe data during summer from the Tarrawarra site near Melbourne, Australia shows persistent spatial organisation of soil moisture over several years. This suggests a link between permanent features of the catchment (e.g. soil properties) and soil moisture distribution, even though the spatial pattern of soil moisture during the 4 summers monitored appears spatially random. This and other data establishes a prima facie case that soil variations drive spatial variation in soil moisture. Accordingly, we used a previously published spatial scaling relationship for soil properties derived using the mARM pedogenesis model to simulate the spatial variation of soil grading. This soil grading distribution was used in the Rosetta pedotransfer model to derive a spatial distribution of soil functional properties (e.g. saturated hydraulic conductivity, porosity). These functional properties were then input into the HYDRUS-1D soil moisture model and soil moisture simulated for 3 years at daily resolution. The HYDRUS model used had previously been calibrated to field observed soil moisture data at our SASMAS field site. The scaling behaviour of soil moisture derived from this modelling will be discussed and compared with observed data from our SASMAS field sites.

Spatial Distribution Patterns in the Very Rare and Species-Rich Picea chihuahuana Tree Community (Mexico).

PubMed

Wehenkel, Christian; Brazão-Protázio, João Marcelo; Carrillo-Parra, Artemio; Martínez-Guerrero, José Hugo; Crecente-Campo, Felipe

2015-01-01

The very rare Mexican Picea chihuahuana tree community covers an area of no more than 300 ha in the Sierra Madre Occidental. This special tree community has been the subject of several studies aimed at learning more about the genetic structure and ecology of the species and the potential effects of climate change. The spatial distribution of trees is a result of many ecological processes and can affect the degree of competition between neighbouring trees, tree density, variability in size and distribution, regeneration, survival, growth, mortality, crown formation and the biological diversity within forest communities. Numerous scale-dependent measures have been established in order to describe spatial forest structure. The overall aim of most of these studies has been to obtain data to help design preservation and conservation strategies. In this study, we examined the spatial distribution pattern of trees in the P. chihuahuana tree community in 12 localities, in relation to i) tree stand density, ii) diameter distribution (vertical structure), iii) tree species diversity, iv) geographical latitude and v) tree dominance at a fine scale (in 0.25 ha plots), with the aim of obtaining a better understanding of the complex ecosystem processes and biological diversity. Because of the strongly mixed nature of this tree community, which often produces low population densities of each tree species and random tree fall gaps caused by tree death, we expect aggregated patterns in individual Picea chihuahuana trees and in the P. chihuahuana tree community, repulsive Picea patterns to other tree species and repulsive patterns of young to adult trees. Each location was represented by one plot of 50 x 50 m (0.25 ha) established in the centre of the tree community. The findings demonstrate that the hypothesis of aggregated tree pattern is not applicable to the mean pattern measured by Clark-Evans index, Uniform Angle index and Mean Directional index of the uneven-aged P. chihuahuana trees and P. chihuahuana tree community and but to specific spatial scales measured by the univariate L-function. The spatial distribution pattern of P. chihuahuana trees was found to be independent of patches of other tree species measured by the bivariate L-function. The spatial distribution was not significantly related to tree density, diameter distribution or tree species diversity. The index of Clark and Evans decreased significantly from the southern to northern plots containing all tree species. Self-thinning due to intra and inter-specific competition-induced mortality is probably the main cause of the decrease in aggregation intensity during the course of population development in this tree community. We recommend the use of larger sampling plots (> 0.25 ha) in uneven-aged and species-rich forest ecosystems to detect less obvious, but important, relationships between spatial tree pattern and functioning and diversity in these forests.

Spatial Distribution Patterns in the Very Rare and Species-Rich Picea chihuahuana Tree Community (Mexico)

PubMed Central

Wehenkel, Christian; Brazão-Protázio, João Marcelo; Carrillo-Parra, Artemio; Martínez-Guerrero, José Hugo; Crecente-Campo, Felipe

2015-01-01

The very rare Mexican Picea chihuahuana tree community covers an area of no more than 300 ha in the Sierra Madre Occidental. This special tree community has been the subject of several studies aimed at learning more about the genetic structure and ecology of the species and the potential effects of climate change. The spatial distribution of trees is a result of many ecological processes and can affect the degree of competition between neighbouring trees, tree density, variability in size and distribution, regeneration, survival, growth, mortality, crown formation and the biological diversity within forest communities. Numerous scale-dependent measures have been established in order to describe spatial forest structure. The overall aim of most of these studies has been to obtain data to help design preservation and conservation strategies. In this study, we examined the spatial distribution pattern of trees in the P. chihuahuana tree community in 12 localities, in relation to i) tree stand density, ii) diameter distribution (vertical structure), iii) tree species diversity, iv) geographical latitude and v) tree dominance at a fine scale (in 0.25 ha plots), with the aim of obtaining a better understanding of the complex ecosystem processes and biological diversity. Because of the strongly mixed nature of this tree community, which often produces low population densities of each tree species and random tree fall gaps caused by tree death, we expect aggregated patterns in individual Picea chihuahuana trees and in the P. chihuahuana tree community, repulsive Picea patterns to other tree species and repulsive patterns of young to adult trees. Each location was represented by one plot of 50 x 50 m (0.25 ha) established in the centre of the tree community. The findings demonstrate that the hypothesis of aggregated tree pattern is not applicable to the mean pattern measured by Clark-Evans index, Uniform Angle index and Mean Directional index of the uneven-aged P. chihuahuana trees and P. chihuahuana tree community and but to specific spatial scales measured by the univariate L-function. The spatial distribution pattern of P. chihuahuana trees was found to be independent of patches of other tree species measured by the bivariate L-function. The spatial distribution was not significantly related to tree density, diameter distribution or tree species diversity. The index of Clark and Evans decreased significantly from the southern to northern plots containing all tree species. Self-thinning due to intra and inter-specific competition-induced mortality is probably the main cause of the decrease in aggregation intensity during the course of population development in this tree community. We recommend the use of larger sampling plots (> 0.25 ha) in uneven-aged and species-rich forest ecosystems to detect less obvious, but important, relationships between spatial tree pattern and functioning and diversity in these forests. PMID:26496189

Spatial Signal Characteristics of Shallow Paraboloidal Shell Structronic Systems

NASA Astrophysics Data System (ADS)

Yue, H. H.; Deng, Z. Q.; Tzou, H. S.

Based on the smart material and structronics technology, distributed sensor and control of shell structures have been rapidly developed for the last twenty years. This emerging technology has been utilized in aerospace, telecommunication, micro-electromechanical systems and other engineering applications. However, distributed monitoring technique and its resulting global spatially distributed sensing signals of thin flexible membrane shells are not clearly understood. In this paper, modeling of free thin paraboloidal shell with spatially distributed sensor, micro-sensing signal characteristics, and location of distributed piezoelectric sensor patches are investigated based on a new set of assumed mode shape functions. Parametric analysis indicates that the signal generation depends on modal membrane strains in the meridional and circumferential directions in which the latter is more significant than the former, when all bending strains vanish in membrane shells. This study provides a modeling and analysis technique for distributed sensors laminated on lightweight paraboloidal flexible structures and identifies critical components and regions that generate significant signals.

Interpretation of heavy rainfall spatial distribution in mountain watersheds by copula functions

NASA Astrophysics Data System (ADS)

Grossi, Giovanna; Balistrocchi, Matteo

2016-04-01

The spatial distribution of heavy rainfalls can strongly influence flood dynamics in mountain watersheds, depending on their geomorphologic features, namely orography, slope, land covers and soil types. Unfortunately, the direct observation of rainfall fields by meteorological radar is very difficult in this situation, so that interpolation of rain gauge observations or downscaling of meteorological predictions must be adopted to derive spatial rainfall distributions. To do so, various stochastic and physically based approaches are already available, even though the first one is the most familiar in hydrology. Indeed, Kriging interpolation procedures represent very popular techniques to face this problem by means of a stochastic approach. A certain number of restrictive assumptions and parameter uncertainties however affects Kriging. Many alternative formulations and additional procedures were therefore developed during the last decades. More recently, copula functions (Joe, 1997; Nelsen, 2006; Salvadori et al. 2007) were suggested to provide a more straightforward solution to carry out spatial interpolations of hydrologic variables (Bardossy & Pegram; 2009). Main advantages lie in the possibility of i) assessing the dependence structure relating to rainfall variables independently of marginal distributions, ii) expressing the association degree through rank correlation coefficients, iii) implementing marginal distributions and copula functions belonging to different models to develop complex joint distribution functions, iv) verifying the model reliability by effective statistical tests (Genest et al., 2009). A suitable case study to verify these potentialities is provided by the Taro River, a right-bank tributary of the Po River (northern Italy), whose contributing area amounts to about 2˙000 km2. The mountain catchment area is divided into two similar watersheds, so that spatial distribution is crucial in extreme flood event generation. A quite well diffused hydro-meteorological network, consisting of about 30 rain gauges and 10 hydrometers, monitors this medium-size watershed. A decade of rainfall-runoff event observations are available. Severe rainfall events were identified with reference to a main raingauge station, by using an interevent time definition and a depth threshold. Rainfall depths were thus derived and the spatial variability of their association degree was represented by using the Kendall coefficient. A unique copula model based on Gumbel copula function was finally found to be suitable to represent the dependence structure relating to rainfall depths observed in distinct raingauges. Bardossy A., Pegram G. (2009), Copula based multisite model for daily precipitation simulation, Hydrol. Earth Syst. Sci., 13, 2299-2314. Genest C., Rémilland B., Beaudoin D. (2009), Goodness-of-fit tests for copulas: a review and a power study, Insur. Math. Econ., 44(2), 199-213. Joe H. (1997), Multivariate models and dependence concepts, Chapman and Hall, London. Nelsen R. B. (2006), An introduction to copulas, second ed., Springer, New York. Salvadori G., De Michele C., Kottegoda N. T., Rosso R. (2007), Extremes in nature: an approach using copulas, Springer, Dordrecht, The Nederlands.

Benefits of incorporating spatial organisation of catchments for a semi-distributed hydrological model

NASA Astrophysics Data System (ADS)

Schumann, Andreas; Oppel, Henning

2017-04-01

To represent the hydrological behaviour of catchments a model should reproduce/reflect the hydrologically most relevant catchment characteristics. These are heterogeneously distributed within a watershed but often interrelated and subject of a certain spatial organisation. Since common models are mostly based on fundamental assumptions about hydrological processes, the reduction of variance of catchment properties as well as the incorporation of the spatial organisation of the catchment is desirable. We have developed a method that combines the idea of the width-function used for determination of the geomorphologic unit hydrograph with information about soil or topography. With this method we are able to assess the spatial organisation of selected catchment characteristics. An algorithm was developed that structures a watershed into sub-basins and other spatial units to minimise its heterogeneity. The outcomes of this algorithm are used for the spatial setup of a semi-distributed model. Since the spatial organisation of a catchment is not bound to a single characteristic, we have to embed information of multiple catchment properties. For this purpose we applied a fuzzy-based method to combine the spatial setup for multiple single characteristics into a union, optimal spatial differentiation. Utilizing this method, we are able to propose a spatial structure for a semi-distributed hydrological model, comprising the definition of sub-basins and a zonal classification within each sub-basin. Besides the improved spatial structuring, the performed analysis ameliorates modelling in another way. The spatial variability of catchment characteristics, which is considered by a minimum of heterogeneity in the zones, can be considered in a parameter constrained calibration scheme in a case study both options were used to explore the benefits of incorporating the spatial organisation and derived parameter constraints for the parametrisation of a HBV-96 model. We use two benchmark model setups (lumped and semi-distributed by common approaches) to address the benefits for different time and spatial scales. Moreover, the benefits for calibration effort, model performance in validation periods and process extrapolation are shown.

Modes in light wave propagating in semiconductor laser

NASA Technical Reports Server (NTRS)

Manko, Margarita A.

1994-01-01

The study of semiconductor laser based on an analogy of the Schrodinger equation and an equation describing light wave propagation in nonhomogeneous medium is developed. The active region of semiconductor laser is considered as optical waveguide confining the electromagnetic field in the cross-section (x,y) and allowing waveguide propagation along the laser resonator (z). The mode structure is investigated taking into account the transversal and what is the important part of the suggested consideration longitudinal nonhomogeneity of the optical waveguide. It is shown that the Gaussian modes in the case correspond to spatial squeezing and correlation. Spatially squeezed two-mode structure of nonhomogeneous optical waveguide is given explicitly. Distribution of light among the laser discrete modes is presented. Properties of the spatially squeezed two-mode field are described. The analog of Franck-Condon principle for finding the maxima of the distribution function and the analog of Ramsauer effect for control of spatial distribution of laser emission are discussed.

Spatial Variability of CCN Sized Aerosol Particles

NASA Astrophysics Data System (ADS)

Asmi, A.; Väänänen, R.

2014-12-01

The computational limitations restrict the grid size used in GCM models, and for many cloud types they are too large when compared to the scale of the cloud formation processes. Several parameterizations for e.g. convective cloud formation exist, but information on spatial subgrid variation of the cloud condensation nuclei (CCNs) sized aerosol concentration is not known. We quantify this variation as a function of the spatial scale by using datasets from airborne aerosol measurement campaigns around the world including EUCAARI LONGREX, ATAR, INCA, INDOEX, CLAIRE, PEGASOS and several regional airborne campaigns in Finland. The typical shapes of the distributions are analyzed. When possible, we use information obtained by CCN counters. In some other cases, we use particle size distribution measured by for example SMPS to get approximated CCN concentration. Other instruments used include optical particle counters or condensational particle counters. When using the GCM models, the CCN concentration used for each the grid-box is often considered to be either flat, or as an arithmetic mean of the concentration inside the grid-box. However, the aircraft data shows that the concentration values are often lognormal distributed. This, combined with the subgrid variations in the land use and atmospheric properties, might cause that the aerosol-cloud interactions calculated by using mean values to vary significantly from the true effects both temporary and spatially. This, in turn, can cause non-linear bias into the GCMs. We calculate the CCN aerosol concentration distribution as a function of different spatial scales. The measurements allow us to study the variation of these distributions within from hundreds of meters up to hundreds of kilometers. This is used to quantify the potential error when mean values are used in GCMs.

Mapping local and global variability in plant trait distributions

DOE PAGES

Butler, Ethan E.; Datta, Abhirup; Flores-Moreno, Habacuc; ...

2017-12-01

Accurate trait-environment relationships and global maps of plant trait distributions represent a needed stepping stone in global biogeography and are critical constraints of key parameters for land models. Here, we use a global data set of plant traits to map trait distributions closely coupled to photosynthesis and foliar respiration: specific leaf area (SLA), and dry mass-based concentrations of leaf nitrogen (Nm) and phosphorus (Pm); We propose two models to extrapolate geographically sparse point data to continuous spatial surfaces. The first is a categorical model using species mean trait values, categorized into plant functional types (PFTs) and extrapolating to PFT occurrencemore » ranges identified by remote sensing. The second is a Bayesian spatial model that incorporates information about PFT, location and environmental covariates to estimate trait distributions. Both models are further stratified by varying the number of PFTs; The performance of the models was evaluated based on their explanatory and predictive ability. The Bayesian spatial model leveraging the largest number of PFTs produced the best maps; The interpolation of full trait distributions enables a wider diversity of vegetation to be represented across the land surface. These maps may be used as input to Earth System Models and to evaluate other estimates of functional diversity.« less

Mapping local and global variability in plant trait distributions

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

Butler, Ethan E.; Datta, Abhirup; Flores-Moreno, Habacuc

Accurate trait-environment relationships and global maps of plant trait distributions represent a needed stepping stone in global biogeography and are critical constraints of key parameters for land models. Here, we use a global data set of plant traits to map trait distributions closely coupled to photosynthesis and foliar respiration: specific leaf area (SLA), and dry mass-based concentrations of leaf nitrogen (Nm) and phosphorus (Pm); We propose two models to extrapolate geographically sparse point data to continuous spatial surfaces. The first is a categorical model using species mean trait values, categorized into plant functional types (PFTs) and extrapolating to PFT occurrencemore » ranges identified by remote sensing. The second is a Bayesian spatial model that incorporates information about PFT, location and environmental covariates to estimate trait distributions. Both models are further stratified by varying the number of PFTs; The performance of the models was evaluated based on their explanatory and predictive ability. The Bayesian spatial model leveraging the largest number of PFTs produced the best maps; The interpolation of full trait distributions enables a wider diversity of vegetation to be represented across the land surface. These maps may be used as input to Earth System Models and to evaluate other estimates of functional diversity.« less

Are fractal dimensions of the spatial distribution of mineral deposits meaningful?

USGS Publications Warehouse

Raines, G.L.

2008-01-01

It has been proposed that the spatial distribution of mineral deposits is bifractal. An implication of this property is that the number of deposits in a permissive area is a function of the shape of the area. This is because the fractal density functions of deposits are dependent on the distance from known deposits. A long thin permissive area with most of the deposits in one end, such as the Alaskan porphyry permissive area, has a major portion of the area far from known deposits and consequently a low density of deposits associated with most of the permissive area. On the other hand, a more equi-dimensioned permissive area, such as the Arizona porphyry permissive area, has a more uniform density of deposits. Another implication of the fractal distribution is that the Poisson assumption typically used for estimating deposit numbers is invalid. Based on datasets of mineral deposits classified by type as inputs, the distributions of many different deposit types are found to have characteristically two fractal dimensions over separate non-overlapping spatial scales in the range of 5-1000 km. In particular, one typically observes a local dimension at spatial scales less than 30-60 km, and a regional dimension at larger spatial scales. The deposit type, geologic setting, and sample size influence the fractal dimensions. The consequence of the geologic setting can be diminished by using deposits classified by type. The crossover point between the two fractal domains is proportional to the median size of the deposit type. A plot of the crossover points for porphyry copper deposits from different geologic domains against median deposit sizes defines linear relationships and identifies regions that are significantly underexplored. Plots of the fractal dimension can also be used to define density functions from which the number of undiscovered deposits can be estimated. This density function is only dependent on the distribution of deposits and is independent of the definition of the permissive area. Density functions for porphyry copper deposits appear to be significantly different for regions in the Andes, Mexico, United States, and western Canada. Consequently, depending on which regional density function is used, quite different estimates of numbers of undiscovered deposits can be obtained. These fractal properties suggest that geologic studies based on mapping at scales of 1:24,000 to 1:100,000 may not recognize processes that are important in the formation of mineral deposits at scales larger than the crossover points at 30-60 km. ?? 2008 International Association for Mathematical Geology.

Spatial distribution of organic functional groups supported on mesoporous silica nanoparticles: A study by conventional and DNP-enhanced 29Si solid-state NMR

DOE PAGES

Kobayashi, Takeshi; Singappuli-Arachchige, Dilini; Wang, Zhuoran; ...

2016-12-23

Solid-state NMR spectroscopy, both conventional and dynamic nuclear polarization (DNP)-enhanced, was employed to study the spatial distribution of organic functional groups attached to the surface of mesoporous silica nanoparticles via co-condensation and grafting. The most revealing information was provided by DNP-enhanced two-dimensional 29Si– 29Si correlation measurements, which unambiguously showed that post-synthesis grafting leads to a more homogeneous dispersion of propyl and mercaptopropyl functionalities than co-condensation. Furthermore, during the anhydrous grafting process, the organosilane precursors do not self-condense and are unlikely to bond to the silica surface in close proximity (less than 4 Å) due to the limited availability of suitablymore » arranged hydroxyl groups.« less

Information hidden in the velocity distribution of ions and the exact kinetic Bohm criterion

NASA Astrophysics Data System (ADS)

Tsankov, Tsanko V.; Czarnetzki, Uwe

2017-05-01

Non-equilibrium distribution functions of electrons and ions play an important role in plasma physics. A prominent example is the kinetic Bohm criterion. Since its first introduction it has been controversial for theoretical reasons and due to the lack of experimental data, in particular on the ion distribution function. Here we resolve the theoretical as well as the experimental difficulties by an exact solution of the kinetic Boltzmann equation including charge exchange collisions and ionization. This also allows for the first time non-invasive measurement of spatially resolved ion velocity distributions, absolute values of the ion and electron densities, temperatures, and mean energies as well as the electric field and the plasma potential in the entire plasma. The non-invasive access to the spatially resolved distribution functions of electrons and ions is applied to the problem of the kinetic Bohm criterion. Theoretically a so far missing term in the criterion is derived and shown to be of key importance. With the new term the validity of the kinetic criterion at high collisionality and its agreement with the fluid picture are restored. All findings are supported by experimental data, theory and a numerical model with excellent agreement throughout.

Spatial Distribution of Cellular Function: The Partitioning of Proteins between Mitochondria and the Nucleus in MCF7 Breast Cancer Cells

PubMed Central

Qattan, Amal T.; Radulovic, Marko; Crawford, Mark; Godovac-Zimmermann, Jasminka

2014-01-01

Concurrent proteomics analysis of the nuclei and mitochondria of MCF7 breast cancer cells identified 985 proteins (40% of all detected proteins) present in both organelles. Numerous proteins from all five complexes involved in oxidative phosphorylation (e.g., NDUFA5, NDUFB10, NDUFS1, NDUF2, SDHA, UQRB, UQRC2, UQCRH, COX5A, COX5B, MT-CO2, ATP5A1, ATP5B, ATP5H, etc.), from the TCA-cycle (DLST, IDH2, IDH3A, OGDH, SUCLAG2, etc.), and from glycolysis (ALDOA, ENO1, FBP1, GPI, PGK1, TALDO1, etc.) were distributed to both the nucleus and mitochondria. In contrast, proteins involved in nuclear/mitochondrial RNA processing/translation and Ras/Rab signaling showed different partitioning patterns. The identity of the OxPhos, TCA-cycle, and glycolysis proteins distributed to both the nucleus and mitochondria provides evidence for spatio-functional integration of these processes over the two different subcellular organelles. We suggest that there are unrecognized aspects of functional coordination between the nucleus and mitochondria, that integration of core functional processes via wide subcellular distribution of constituent proteins is a common characteristic of cells, and that subcellular spatial integration of function may be a vital aspect of cancer. PMID:23051583

Alternative measures of spatial distribution and availability of health facilities for the delivery of emergency obstetric services in island communities.

PubMed

Oyerinde, Koyejo; Baravilala, Wame

2014-12-01

International guidelines and recommendations for availability and spatial distribution of emergency obstetric care services do not adequately address the challenges of providing emergency health services in island communities. The isolation and small population sizes that are typical of islands and remote populations limit the applicability of international guidelines in such communities. Universal access to emergency obstetric care services, when pregnant women encounter complications, is one of the three key strategies for reducing maternal and newborn mortality; the other two being family planning and skilled care during labor. The performance of selected lifesaving clinical interventions (signal functions) over a 3-month period is commonly used to assess and assign performance categories to health facilities but island communities might not have a large enough population to generate demand for all the signal functions over a 3-month period. Similarly, availability and spatial distribution recommendations are typically based on the size of catchment populations, but the populations of island communities tend to be sparsely distributed. With illustrations from six South Pacific Island states, we argue that the recommendation for availability of health facilities, that there should be at least five emergency obstetric care facilities (including at least one comprehensive facility) for every 500,000 population, and the recommendation for equitable distribution of health facilities, that all subnational areas meet the availability recommendation, can be substituted with a focus on access to blood transfusion and obstetric surgical care within 2 hours for all pregnant residents of islands. Island communities could replace the performance of signal functions over a 3-month period with a demonstrated capacity to perform signal functions if the need arises.

Adaptation to stimulus statistics in the perception and neural representation of auditory space.

PubMed

Dahmen, Johannes C; Keating, Peter; Nodal, Fernando R; Schulz, Andreas L; King, Andrew J

2010-06-24

Sensory systems are known to adapt their coding strategies to the statistics of their environment, but little is still known about the perceptual implications of such adjustments. We investigated how auditory spatial processing adapts to stimulus statistics by presenting human listeners and anesthetized ferrets with noise sequences in which interaural level differences (ILD) rapidly fluctuated according to a Gaussian distribution. The mean of the distribution biased the perceived laterality of a subsequent stimulus, whereas the distribution's variance changed the listeners' spatial sensitivity. The responses of neurons in the inferior colliculus changed in line with these perceptual phenomena. Their ILD preference adjusted to match the stimulus distribution mean, resulting in large shifts in rate-ILD functions, while their gain adapted to the stimulus variance, producing pronounced changes in neural sensitivity. Our findings suggest that processing of auditory space is geared toward emphasizing relative spatial differences rather than the accurate representation of absolute position.

Using rank-order geostatistics for spatial interpolation of highly skewed data in a heavy-metal contaminated site.

PubMed

Juang, K W; Lee, D Y; Ellsworth, T R

2001-01-01

The spatial distribution of a pollutant in contaminated soils is usually highly skewed. As a result, the sample variogram often differs considerably from its regional counterpart and the geostatistical interpolation is hindered. In this study, rank-order geostatistics with standardized rank transformation was used for the spatial interpolation of pollutants with a highly skewed distribution in contaminated soils when commonly used nonlinear methods, such as logarithmic and normal-scored transformations, are not suitable. A real data set of soil Cd concentrations with great variation and high skewness in a contaminated site of Taiwan was used for illustration. The spatial dependence of ranks transformed from Cd concentrations was identified and kriging estimation was readily performed in the standardized-rank space. The estimated standardized rank was back-transformed into the concentration space using the middle point model within a standardized-rank interval of the empirical distribution function (EDF). The spatial distribution of Cd concentrations was then obtained. The probability of Cd concentration being higher than a given cutoff value also can be estimated by using the estimated distribution of standardized ranks. The contour maps of Cd concentrations and the probabilities of Cd concentrations being higher than the cutoff value can be simultaneously used for delineation of hazardous areas of contaminated soils.

Reconfiguration of acute care hospitals in post-socialist Serbia: spatial distribution of hospital beds.

PubMed

Matejic, Marko

2017-04-01

In the context of healthcare reforms in post-socialist Serbia, this research analyses the reconfiguration of acute care hospitals from the aspect of the spatial distribution of hospital beds among and within state-owned hospitals. The research builds a relationship between the macro or national level and the micro or hospital level of the spatial distribution of hospital beds. The aim of the study is to point out that a high level of efficiency in hospital functionality is difficult to achieve within the current hospital network and architectural-urban patterns of hospitals, and to draw attention to the necessity of a strategically planned hospital spatial reconfiguration, conducted simultaneously with other segments of the healthcare system reform. The research analyses published and unpublished data presented in tables and diagrams. The theoretical platform of the research covers earlier discussions of the Yugoslav healthcare system, its post-socialist reforms and the experiences of developed countries. The results show that the hospital bed distribution has not undergone significant changes, while the hospital spatial reconfiguration has either not been carried out at all or, if it has, only on a small scale. All this has contributed to overall inadequate, inflexible, inefficient, defragmented and unequal bed distribution. Copyright © 2016 John Wiley & Sons, Ltd. Copyright © 2016 John Wiley & Sons, Ltd.

A data-model integration approach toward improved understanding on wetland functions and hydrological benefits at the catchment scale

NASA Astrophysics Data System (ADS)

Yeo, I. Y.; Lang, M.; Lee, S.; Huang, C.; Jin, H.; McCarty, G.; Sadeghi, A.

2017-12-01

The wetland ecosystem plays crucial roles in improving hydrological function and ecological integrity for the downstream water and the surrounding landscape. However, changing behaviours and functioning of wetland ecosystems are poorly understood and extremely difficult to characterize. Improved understanding on hydrological behaviours of wetlands, considering their interaction with surrounding landscapes and impacts on downstream waters, is an essential first step toward closing the knowledge gap. We present an integrated wetland-catchment modelling study that capitalizes on recently developed inundation maps and other geospatial data. The aim of the data-model integration is to improve spatial prediction of wetland inundation and evaluate cumulative hydrological benefits at the catchment scale. In this paper, we highlight problems arising from data preparation, parameterization, and process representation in simulating wetlands within a distributed catchment model, and report the recent progress on mapping of wetland dynamics (i.e., inundation) using multiple remotely sensed data. We demonstrate the value of spatially explicit inundation information to develop site-specific wetland parameters and to evaluate model prediction at multi-spatial and temporal scales. This spatial data-model integrated framework is tested using Soil and Water Assessment Tool (SWAT) with improved wetland extension, and applied for an agricultural watershed in the Mid-Atlantic Coastal Plain, USA. This study illustrates necessity of spatially distributed information and a data integrated modelling approach to predict inundation of wetlands and hydrologic function at the local landscape scale, where monitoring and conservation decision making take place.

Solving Large-scale Spatial Optimization Problems in Water Resources Management through Spatial Evolutionary Algorithms

NASA Astrophysics Data System (ADS)

Wang, J.; Cai, X.

2007-12-01

A water resources system can be defined as a large-scale spatial system, within which distributed ecological system interacts with the stream network and ground water system. Water resources management, the causative factors and hence the solutions to be developed have a significant spatial dimension. This motivates a modeling analysis of water resources management within a spatial analytical framework, where data is usually geo- referenced and in the form of a map. One of the important functions of Geographic information systems (GIS) is to identify spatial patterns of environmental variables. The role of spatial patterns in water resources management has been well established in the literature particularly regarding how to design better spatial patterns for satisfying the designated objectives of water resources management. Evolutionary algorithms (EA) have been demonstrated to be successful in solving complex optimization models for water resources management due to its flexibility to incorporate complex simulation models in the optimal search procedure. The idea of combining GIS and EA motivates the development and application of spatial evolutionary algorithms (SEA). SEA assimilates spatial information into EA, and even changes the representation and operators of EA. In an EA used for water resources management, the mathematical optimization model should be modified to account the spatial patterns; however, spatial patterns are usually implicit, and it is difficult to impose appropriate patterns to spatial data. Also it is difficult to express complex spatial patterns by explicit constraints included in the EA. The GIS can help identify the spatial linkages and correlations based on the spatial knowledge of the problem. These linkages are incorporated in the fitness function for the preference of the compatible vegetation distribution. Unlike a regular GA for spatial models, the SEA employs a special hierarchical hyper-population and spatial genetic operators to represent spatial variables in a more efficient way. The hyper-population consists of a set of populations, which correspond to the spatial distributions of the individual agents (organisms). Furthermore spatial crossover and mutation operators are designed in accordance with the tree representation and then applied to both organisms and populations. This study applies the SEA to a specific problem of water resources management- maximizing the riparian vegetation coverage in accordance with the distributed groundwater system in an arid region. The vegetation coverage is impacted greatly by the nonlinear feedbacks and interactions between vegetation and groundwater and the spatial variability of groundwater. The SEA is applied to search for an optimal vegetation configuration compatible to the groundwater flow. The results from this example demonstrate the effectiveness of the SEA. Extension of the algorithm for other water resources management problems is discussed.

Decoupled ARX and RBF Neural Network Modeling Using PCA and GA Optimization for Nonlinear Distributed Parameter Systems.

PubMed

Zhang, Ridong; Tao, Jili; Lu, Renquan; Jin, Qibing

2018-02-01

Modeling of distributed parameter systems is difficult because of their nonlinearity and infinite-dimensional characteristics. Based on principal component analysis (PCA), a hybrid modeling strategy that consists of a decoupled linear autoregressive exogenous (ARX) model and a nonlinear radial basis function (RBF) neural network model are proposed. The spatial-temporal output is first divided into a few dominant spatial basis functions and finite-dimensional temporal series by PCA. Then, a decoupled ARX model is designed to model the linear dynamics of the dominant modes of the time series. The nonlinear residual part is subsequently parameterized by RBFs, where genetic algorithm is utilized to optimize their hidden layer structure and the parameters. Finally, the nonlinear spatial-temporal dynamic system is obtained after the time/space reconstruction. Simulation results of a catalytic rod and a heat conduction equation demonstrate the effectiveness of the proposed strategy compared to several other methods.

Analytic solution of the Spencer-Lewis angular-spatial moments equations

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

Filippone, W.L.

A closed-form solution for the angular-spatial moments of the Spencer-Lewis equation is presented that is valid for infinite homogeneous media. From the moments, the electron density distribution as a function of position and path length (energy) is reconstructed for several sample problems involving plane isotropic sources of electrons in aluminium. The results are in excellent agreement with those determined numerically using the streaming ray method. The primary use of the closed form solution will most likely be to generate accurate electron transport benchmark solutions. In principle, the electron density as a function of space, path length, and direction can bemore » determined for planar sources of arbitrary angular distribution.« less

Spatial distributions ofC3 and C4 grass functional types in the U.S. great plains and their despendency on inter-annual climate variability

USDA-ARS?s Scientific Manuscript database

Grassland ecosystems in North America are primarily composed of C3 and C4 plant functional types (PFTs) with their relative cover varying spatially and temporally. This study used 500-m MODIS surface reflectance products (MOD09A1) from 2000 to 2009 to extract an NDVI time series of C3 and C4 PFTs in...

Coupling fine-scale root and canopy structure using ground-based remote sensing

Treesearch

Brady Hardiman; Christopher Gough; John Butnor; Gil Bohrer; Matteo Detto; Peter Curtis

2017-01-01

Ecosystem physical structure, defined by the quantity and spatial distribution of biomass, influences a range of ecosystem functions. Remote sensing tools permit the non-destructive characterization of canopy and root features, potentially providing opportunities to link above- and belowground structure at fine spatial resolution in...

Spatial pattern of Baccharis platypoda shrub as determined by sex and life stages

NASA Astrophysics Data System (ADS)

Fonseca, Darliana da Costa; de Oliveira, Marcio Leles Romarco; Pereira, Israel Marinho; Gonzaga, Anne Priscila Dias; de Moura, Cristiane Coelho; Machado, Evandro Luiz Mendonça

2017-11-01

Spatial patterns of dioecious species can be determined by their nutritional requirements and intraspecific competition, apart from being a response to environmental heterogeneity. The aim of the study was to evaluate the spatial pattern of populations of a dioecious shrub reporting to sex and reproductive stage patterns of individuals. Sampling was carried out in three areas located in the meridional portion of Serra do Espinhaço, where in individuals of the studied species were mapped. The spatial pattern was determined through O-ring analysis and Ripley's K-function and the distribution of individuals' frequencies was verified through x2 test. Populations in two areas showed an aggregate spatial pattern tending towards random or uniform according to the observed scale. Male and female adults presented an aggregate pattern at smaller scales, while random and uniform patterns were verified above 20 m for individuals of both sexes of the areas A2 and A3. Young individuals presented an aggregate pattern in all areas and spatial independence in relation to adult individuals, especially female plants. The interactions between individuals of both genders presented spatial independence with respect to spatial distribution. Baccharis platypoda showed characteristics in accordance with the spatial distribution of savannic and dioecious species, whereas the population was aggregated tending towards random at greater spatial scales. Young individuals showed an aggregated pattern at different scales compared to adults, without positive association between them. Female and male adult individuals presented similar characteristics, confirming that adult individuals at greater scales are randomly distributed despite their distinct preferences for environments with moisture variation.

Determinants of pulmonary blood flow distribution.

PubMed

Glenny, Robb W; Robertson, H Thomas

2011-01-01

The primary function of the pulmonary circulation is to deliver blood to the alveolar capillaries to exchange gases. Distributing blood over a vast surface area facilitates gas exchange, yet the pulmonary vascular tree must be constrained to fit within the thoracic cavity. In addition, pressures must remain low within the circulatory system to protect the thin alveolar capillary membranes that allow efficient gas exchange. The pulmonary circulation is engineered for these unique requirements and in turn these special attributes affect the spatial distribution of blood flow. As the largest organ in the body, the physical characteristics of the lung vary regionally, influencing the spatial distribution on large-, moderate-, and small-scale levels. © 2011 American Physiological Society.

SPATIAL NEGLECT AND ATTENTION NETWORKS

PubMed Central

Corbetta, Maurizio; Shulman, Gordon L.

2013-01-01

Unilateral spatial neglect is a common neurological syndrome following predominantly right hemisphere injuries to ventral fronto-parietal cortex. We propose that neglect reflects deficits in the coding of saliency, control of spatial attention, and representation within an egocentric frame of reference, in conjunction with non-spatial deficits of reorienting, target detection, and arousal/vigilance. In contrast to theories that link spatial neglect to structural damage of specific brain regions, we argue that neglect is better explained by the physiological dysfunction of distributed cortical networks. The ventral lesions in right parietal, temporal, and frontal cortex that cause neglect directly impair non-spatial functions and hypoactivate the right hemisphere, inducing abnormalities in task-evoked activity and functional connectivity of a dorsal frontal-parietal network that controls spatial attention. The anatomy and right hemisphere dominance of neglect follows from the anatomy and laterality of the ventral regions that interact with the dorsal attention network. PMID:21692662

A Bayesian kriging approach for blending satellite and ground precipitation observations

USGS Publications Warehouse

Verdin, Andrew P.; Rajagopalan, Balaji; Kleiber, William; Funk, Christopher C.

2015-01-01

Drought and flood management practices require accurate estimates of precipitation. Gauge observations, however, are often sparse in regions with complicated terrain, clustered in valleys, and of poor quality. Consequently, the spatial extent of wet events is poorly represented. Satellite-derived precipitation data are an attractive alternative, though they tend to underestimate the magnitude of wet events due to their dependency on retrieval algorithms and the indirect relationship between satellite infrared observations and precipitation intensities. Here we offer a Bayesian kriging approach for blending precipitation gauge data and the Climate Hazards Group Infrared Precipitation satellite-derived precipitation estimates for Central America, Colombia, and Venezuela. First, the gauge observations are modeled as a linear function of satellite-derived estimates and any number of other variables—for this research we include elevation. Prior distributions are defined for all model parameters and the posterior distributions are obtained simultaneously via Markov chain Monte Carlo sampling. The posterior distributions of these parameters are required for spatial estimation, and thus are obtained prior to implementing the spatial kriging model. This functional framework is applied to model parameters obtained by sampling from the posterior distributions, and the residuals of the linear model are subject to a spatial kriging model. Consequently, the posterior distributions and uncertainties of the blended precipitation estimates are obtained. We demonstrate this method by applying it to pentadal and monthly total precipitation fields during 2009. The model's performance and its inherent ability to capture wet events are investigated. We show that this blending method significantly improves upon the satellite-derived estimates and is also competitive in its ability to represent wet events. This procedure also provides a means to estimate a full conditional distribution of the “true” observed precipitation value at each grid cell.

Organismal and spatial partitioning of energy and macronutrient transformations within a hypersaline mat

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

Mobberley, Jennifer M.; Lindemann, Stephen R.; Bernstein, Hans C.

2017-03-21

Phototrophic mat communities are model ecosystems for studying energy cycling and elemental transformations because complete biogeochemical cycles occur over millimeter-to-centimeter scales. Characterization of energy and nutrient capture within hypersaline phototrophic mats has focused on specific processes and organisms, however little is known about community-wide distribution of and linkages between these processes. To investigate energy and macronutrient capture and flow through a structured community, the spatial and organismal distribution of metabolic functions within a compact hypersaline mat community from Hot Lake have been broadly elucidated through species-resolved metagenomics and geochemical, microbial diversity, and metabolic gradient measurements. Draft reconstructed genomes of abundantmore » organisms revealed three dominant cyanobacterial populations differentially distributed across the top layers of the mat suggesting niche separation along light and oxygen gradients. Many organisms contained diverse functional profiles, allowing for metabolic response to changing conditions within the mat. Organisms with partial nitrogen and sulfur metabolisms were widespread indicating dependence upon metabolite exchange. In addition, changes in community spatial structure were observed over the diel. These results indicate that organisms within the mat community have adapted to the temporally dynamic environmental gradients in this hypersaline mat through metabolic flexibility and fluid syntrophic interactions, including shifts in spatial arrangements.« less

A three-dimensional point process model for the spatial distribution of disease occurrence in relation to an exposure source.

PubMed

Grell, Kathrine; Diggle, Peter J; Frederiksen, Kirsten; Schüz, Joachim; Cardis, Elisabeth; Andersen, Per K

2015-10-15

We study methods for how to include the spatial distribution of tumours when investigating the relation between brain tumours and the exposure from radio frequency electromagnetic fields caused by mobile phone use. Our suggested point process model is adapted from studies investigating spatial aggregation of a disease around a source of potential hazard in environmental epidemiology, where now the source is the preferred ear of each phone user. In this context, the spatial distribution is a distribution over a sample of patients rather than over multiple disease cases within one geographical area. We show how the distance relation between tumour and phone can be modelled nonparametrically and, with various parametric functions, how covariates can be included in the model and how to test for the effect of distance. To illustrate the models, we apply them to a subset of the data from the Interphone Study, a large multinational case-control study on the association between brain tumours and mobile phone use. Copyright © 2015 John Wiley & Sons, Ltd.

Monitoring Method of Cow Anthrax Based on Gis and Spatial Statistical Analysis

NASA Astrophysics Data System (ADS)

Li, Lin; Yang, Yong; Wang, Hongbin; Dong, Jing; Zhao, Yujun; He, Jianbin; Fan, Honggang

Geographic information system (GIS) is a computer application system, which possesses the ability of manipulating spatial information and has been used in many fields related with the spatial information management. Many methods and models have been established for analyzing animal diseases distribution models and temporal-spatial transmission models. Great benefits have been gained from the application of GIS in animal disease epidemiology. GIS is now a very important tool in animal disease epidemiological research. Spatial analysis function of GIS can be widened and strengthened by using spatial statistical analysis, allowing for the deeper exploration, analysis, manipulation and interpretation of spatial pattern and spatial correlation of the animal disease. In this paper, we analyzed the cow anthrax spatial distribution characteristics in the target district A (due to the secret of epidemic data we call it district A) based on the established GIS of the cow anthrax in this district in combination of spatial statistical analysis and GIS. The Cow anthrax is biogeochemical disease, and its geographical distribution is related closely to the environmental factors of habitats and has some spatial characteristics, and therefore the correct analysis of the spatial distribution of anthrax cow for monitoring and the prevention and control of anthrax has a very important role. However, the application of classic statistical methods in some areas is very difficult because of the pastoral nomadic context. The high mobility of livestock and the lack of enough suitable sampling for the some of the difficulties in monitoring currently make it nearly impossible to apply rigorous random sampling methods. It is thus necessary to develop an alternative sampling method, which could overcome the lack of sampling and meet the requirements for randomness. The GIS computer application software ArcGIS9.1 was used to overcome the lack of data of sampling sites.Using ArcGIS 9.1 and GEODA to analyze the cow anthrax spatial distribution of district A. we gained some conclusions about cow anthrax' density: (1) there is a spatial clustering model. (2) there is an intensely spatial autocorrelation. We established a prediction model to estimate the anthrax distribution based on the spatial characteristic of the density of cow anthrax. Comparing with the true distribution, the prediction model has a well coincidence and is feasible to the application. The method using a GIS tool facilitates can be implemented significantly in the cow anthrax monitoring and investigation, and the space statistics - related prediction model provides a fundamental use for other study on space-related animal diseases.

Spatial analysis of soil organic carbon in Zhifanggou catchment of the Loess Plateau.

PubMed

Li, Mingming; Zhang, Xingchang; Zhen, Qing; Han, Fengpeng

2013-01-01

Soil organic carbon (SOC) reflects soil quality and plays a critical role in soil protection, food safety, and global climate changes. This study involved grid sampling at different depths (6 layers) between 0 and 100 cm in a catchment. A total of 1282 soil samples were collected from 215 plots over 8.27 km(2). A combination of conventional analytical methods and geostatistical methods were used to analyze the data for spatial variability and soil carbon content patterns. The mean SOC content in the 1282 samples from the study field was 3.08 g · kg(-1). The SOC content of each layer decreased with increasing soil depth by a power function relationship. The SOC content of each layer was moderately variable and followed a lognormal distribution. The semi-variograms of the SOC contents of the six different layers were fit with the following models: exponential, spherical, exponential, Gaussian, exponential, and exponential, respectively. A moderate spatial dependence was observed in the 0-10 and 10-20 cm layers, which resulted from stochastic and structural factors. The spatial distribution of SOC content in the four layers between 20 and 100 cm exhibit were mainly restricted by structural factors. Correlations within each layer were observed between 234 and 562 m. A classical Kriging interpolation was used to directly visualize the spatial distribution of SOC in the catchment. The variability in spatial distribution was related to topography, land use type, and human activity. Finally, the vertical distribution of SOC decreased. Our results suggest that the ordinary Kriging interpolation can directly reveal the spatial distribution of SOC and the sample distance about this study is sufficient for interpolation or plotting. More research is needed, however, to clarify the spatial variability on the bigger scale and better understand the factors controlling spatial variability of soil carbon in the Loess Plateau region.

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

Development of a distributed air pollutant dry deposition modeling framework

Treesearch

Satoshi Hirabayashi; Charles N. Kroll; David J. Nowak

2012-01-01

A distributed air pollutant dry deposition modeling systemwas developed with a geographic information system (GIS) to enhance the functionality of i-Tree Eco (i-Tree, 2011). With the developed system, temperature, leaf area index (LAI) and air pollutant concentration in a spatially distributed form can be estimated, and based on these and other input variables, dry...

Analysis of the spatial distribution of prostate cancer obtained from histopathological images

NASA Astrophysics Data System (ADS)

Diaz, Kristians; Castaneda, Benjamin; Montero, Maria Luisa; Yao, Jorge; Joseph, Jean; Rubens, Deborah; Parker, Kevin J.

2013-03-01

Understanding the spatial distribution of prostate cancer and how it changes according to prostate specific antigen (PSA) values, Gleason score, and other clinical parameters may help comprehend the disease and increase the overall success rate of biopsies. This work aims to build 3D spatial distributions of prostate cancer and examine the extent and location of cancer as a function of independent clinical parameters. The border of the gland and cancerous regions from wholemount histopathological images are used to reconstruct 3D models showing the localization of tumor. This process utilizes color segmentation and interpolation based on mathematical morphological distance. 58 glands are deformed into one prostate atlas using a combination of rigid, affine, and b-spline deformable registration techniques. Spatial distribution is developed by counting the number of occurrences in a given position in 3D space from each registered prostate cancer. Finally a difference between proportions is used to compare different spatial distributions. Results show that prostate cancer has a significant difference (SD) in the right zone of the prostate between populations with PSA greater and less than 5ng/ml. Age does not have any impact in the spatial distribution of the disease. Positive and negative capsule-penetrated cases show a SD in the right posterior zone. There is SD in almost all the glands between cases with tumors larger and smaller than 10% of the whole prostate. A larger database is needed to improve the statistical validity of the test. Finally, information from whole-mount histopathological images may provide better insight into prostate cancer.

The contribution of reserves and anthropogenic habitat for functional connectivity and resilience of ephemeral wetland networks

NASA Astrophysics Data System (ADS)

Allen, C. R.; Uden, D.; Angeler, D.; Hellman, M.

2015-12-01

Functional connectivity of reserves and other suitable habitat patches is crucial for persistence of spatially structured populations, and therefore for resilience. To maintain or increase connectivity at spatial scales larger than individual patches, conservation actions may focus on creating and maintaining reserves or influencing management actions taken on non-reserves. We assess functional connectivity of isolated wetlands within an intensively managed agricultural matrix. Using a graph-theoretic approach, we assessed the functional connectivity and spatial distribution of wetlands in the Rainwater Basins, Nebraska, U.S.A. at four assumed anuran dispersal distances. We compare the contemporary wetlands landscape to the historical landscape and putative future landscapes and evaluate the importance of individual and aggregated reserve and non-reserve wetlands for maintaining connectivity. Connectivity was greatest in the historical landscape, where wetlands were also the most densely distributed. The construction of irrigation reuse pits for water storage has substantially increased connectivity in the current landscape, but because their distribution is more uniform than historical wetlands, larger and longer-dispersing species may be favored over smaller, shorter-dispersing species. Because of their relatively low number, wetland reserves did not affect connectivity as greatly as non-reserve wetlands or irrigation reuse pits; however, they provide the highest-quality anuran habitat. Future levels of connectivity in the region will be directly impacted by the planned removal of irrigation reuse pits, and on non-reserve wetlands. Multi-scale spatial and temporal assessments of the effects of landuse change and conservation actions on landscape connectivity may be used to direct and prioritize conservation actions, and should also be useful for reserve network and landscape resilience assessments.

Global survey of star clusters in the Milky Way. VI. Age distribution and cluster formation history

NASA Astrophysics Data System (ADS)

Piskunov, A. E.; Just, A.; Kharchenko, N. V.; Berczik, P.; Scholz, R.-D.; Reffert, S.; Yen, S. X.

2018-06-01

Context. The all-sky Milky Way Star Clusters (MWSC) survey provides uniform and precise ages, along with other relevant parameters, for a wide variety of clusters in the extended solar neighbourhood. Aims: In this study we aim to construct the cluster age distribution, investigate its spatial variations, and discuss constraints on cluster formation scenarios of the Galactic disk during the last 5 Gyrs. Methods: Due to the spatial extent of the MWSC, we have considered spatial variations of the age distribution along galactocentric radius RG, and along Z-axis. For the analysis of the age distribution we used 2242 clusters, which all lie within roughly 2.5 kpc of the Sun. To connect the observed age distribution to the cluster formation history we built an analytical model based on simple assumptions on the cluster initial mass function and on the cluster mass-lifetime relation, fit it to the observations, and determined the parameters of the cluster formation law. Results: Comparison with the literature shows that earlier results strongly underestimated the number of evolved clusters with ages t ≳ 100 Myr. Recent studies based on all-sky catalogues agree better with our data, but still lack the oldest clusters with ages t ≳ 1 Gyr. We do not observe a strong variation in the age distribution along RG, though we find an enhanced fraction of older clusters (t > 1 Gyr) in the inner disk. In contrast, the distribution strongly varies along Z. The high altitude distribution practically does not contain clusters with t < 1 Gyr. With simple assumptions on the cluster formation history, the cluster initial mass function and the cluster lifetime we can reproduce the observations. The cluster formation rate and the cluster lifetime are strongly degenerate, which does not allow us to disentangle different formation scenarios. In all cases the cluster formation rate is strongly declining with time, and the cluster initial mass function is very shallow at the high mass end.

Implementing an SIG based platform of application and service for city spatial information in Shanghai

NASA Astrophysics Data System (ADS)

Yu, Bailang; Wu, Jianping

2006-10-01

Spatial Information Grid (SIG) is an infrastructure that has the ability to provide the services for spatial information according to users' needs by means of collecting, sharing, organizing and processing the massive distributed spatial information resources. This paper presents the architecture, technologies and implementation of the Shanghai City Spatial Information Application and Service System, a SIG based platform, which is an integrated platform that serves for administration, planning, construction and development of the city. In the System, there are ten categories of spatial information resources, including city planning, land-use, real estate, river system, transportation, municipal facility construction, environment protection, sanitation, urban afforestation and basic geographic information data. In addition, spatial information processing services are offered as a means of GIS Web Services. The resources and services are all distributed in different web-based nodes. A single database is created to store the metadata of all the spatial information. A portal site is published as the main user interface of the System. There are three main functions in the portal site. First, users can search the metadata and consequently acquire the distributed data by using the searching results. Second, some spatial processing web applications that developed with GIS Web Services, such as file format conversion, spatial coordinate transfer, cartographic generalization and spatial analysis etc, are offered to use. Third, GIS Web Services currently available in the System can be searched and new ones can be registered. The System has been working efficiently in Shanghai Government Network since 2005.

Disturbance Impacts on Thermal Hot Spots and Hot Moments at the Peatland-Atmosphere Interface

NASA Astrophysics Data System (ADS)

Leonard, R. M.; Kettridge, N.; Devito, K. J.; Petrone, R. M.; Mendoza, C. A.; Waddington, J. M.; Krause, S.

2018-01-01

Soil-surface temperature acts as a master variable driving nonlinear terrestrial ecohydrological, biogeochemical, and micrometeorological processes, inducing short-lived or spatially isolated extremes across heterogeneous landscape surfaces. However, subcanopy soil-surface temperatures have been, to date, characterized through isolated, spatially discrete measurements. Using spatially complex forested northern peatlands as an exemplar ecosystem, we explore the high-resolution spatiotemporal thermal behavior of this critical interface and its response to disturbances by using Fiber-Optic Distributed Temperature Sensing. Soil-surface thermal patterning was identified from 1.9 million temperature measurements under undisturbed, trees removed and vascular subcanopy removed conditions. Removing layers of the structurally diverse vegetation canopy not only increased mean temperatures but it shifted the spatial and temporal distribution, range, and longevity of thermal hot spots and hot moments. We argue that linking hot spots and/or hot moments with spatially variable ecosystem processes and feedbacks is key for predicting ecosystem function and resilience.

The biogeodynamics of microbial landscapes

NASA Astrophysics Data System (ADS)

Battin, T. J.; Hödl, I.; Bertuzzo, E.; Mari, L.; Suweis, S. S.; Rinaldo, A.

2011-12-01

Spatial configuration is fundamental in defining the structural and functional properties of biological systems. Biofilms, surface-attached and matrix-enclosed microorganisms, are a striking example of spatial organisation. Coupled biotic and abiotic processes shape the spatial organisation across scales of the landscapes formed by these benthic biofilms in streams and rivers. Experimenting with such biofilms in streams, we found that, depending on the streambed topography and the related hydrodynamic microenvironment, biofilm landscapes form increasingly diverging spatial patterns as they grow. Strikingly, however, cluster size distributions tend to converge even in contrasting hydrodynamic microenvironments. To reproduce the observed cluster size distributions we used a continuous, size-structured population model. The model accounts for the formation, growth, erosion and merging of biofilm clusters. Our results suggest not only that hydrodynamic forcing induce the diverging patterning of the microbial landscape, but also that microorganisms have developed strategies to equally exploit spatial resources independently of the physical structure of the microenvironment where they live.

A composite likelihood approach for spatially correlated survival data

PubMed Central

Paik, Jane; Ying, Zhiliang

2013-01-01

The aim of this paper is to provide a composite likelihood approach to handle spatially correlated survival data using pairwise joint distributions. With e-commerce data, a recent question of interest in marketing research has been to describe spatially clustered purchasing behavior and to assess whether geographic distance is the appropriate metric to describe purchasing dependence. We present a model for the dependence structure of time-to-event data subject to spatial dependence to characterize purchasing behavior from the motivating example from e-commerce data. We assume the Farlie-Gumbel-Morgenstern (FGM) distribution and then model the dependence parameter as a function of geographic and demographic pairwise distances. For estimation of the dependence parameters, we present pairwise composite likelihood equations. We prove that the resulting estimators exhibit key properties of consistency and asymptotic normality under certain regularity conditions in the increasing-domain framework of spatial asymptotic theory. PMID:24223450

A composite likelihood approach for spatially correlated survival data.

PubMed

Paik, Jane; Ying, Zhiliang

2013-01-01

The aim of this paper is to provide a composite likelihood approach to handle spatially correlated survival data using pairwise joint distributions. With e-commerce data, a recent question of interest in marketing research has been to describe spatially clustered purchasing behavior and to assess whether geographic distance is the appropriate metric to describe purchasing dependence. We present a model for the dependence structure of time-to-event data subject to spatial dependence to characterize purchasing behavior from the motivating example from e-commerce data. We assume the Farlie-Gumbel-Morgenstern (FGM) distribution and then model the dependence parameter as a function of geographic and demographic pairwise distances. For estimation of the dependence parameters, we present pairwise composite likelihood equations. We prove that the resulting estimators exhibit key properties of consistency and asymptotic normality under certain regularity conditions in the increasing-domain framework of spatial asymptotic theory.

Analysis of stratocumulus cloud fields using LANDSAT imagery: Size distributions and spatial separations

NASA Technical Reports Server (NTRS)

Welch, R. M.; Sengupta, S. K.; Chen, D. W.

1990-01-01

Stratocumulus cloud fields in the FIRE IFO region are analyzed using LANDSAT Thematic Mapper imagery. Structural properties such as cloud cell size distribution, cell horizontal aspect ratio, fractional coverage and fractal dimension are determined. It is found that stratocumulus cloud number densities are represented by a power law. Cell horizontal aspect ratio has a tendency to increase at large cell sizes, and cells are bi-fractal in nature. Using LANDSAT Multispectral Scanner imagery for twelve selected stratocumulus scenes acquired during previous years, similar structural characteristics are obtained. Cloud field spatial organization also is analyzed. Nearest-neighbor spacings are fit with a number of functions, with Weibull and Gamma distributions providing the best fits. Poisson tests show that the spatial separations are not random. Second order statistics are used to examine clustering.

The correlation function for density perturbations in an expanding universe. III The three-point and predictions of the four-point and higher order correlation functions

NASA Technical Reports Server (NTRS)

Mcclelland, J.; Silk, J.

1978-01-01

Higher-order correlation functions for the large-scale distribution of galaxies in space are investigated. It is demonstrated that the three-point correlation function observed by Peebles and Groth (1975) is not consistent with a distribution of perturbations that at present are randomly distributed in space. The two-point correlation function is shown to be independent of how the perturbations are distributed spatially, and a model of clustered perturbations is developed which incorporates a nonuniform perturbation distribution and which explains the three-point correlation function. A model with hierarchical perturbations incorporating the same nonuniform distribution is also constructed; it is found that this model also explains the three-point correlation function, but predicts different results for the four-point and higher-order correlation functions than does the model with clustered perturbations. It is suggested that the model of hierarchical perturbations might be explained by the single assumption of having density fluctuations or discrete objects all of the same mass randomly placed at some initial epoch.

Wigner functions for evanescent waves.

PubMed

Petruccelli, Jonathan C; Tian, Lei; Oh, Se Baek; Barbastathis, George

2012-09-01

We propose phase space distributions, based on an extension of the Wigner distribution function, to describe fields of any state of coherence that contain evanescent components emitted into a half-space. The evanescent components of the field are described in an optical phase space of spatial position and complex-valued angle. Behavior of these distributions upon propagation is also considered, where the rapid decay of the evanescent components is associated with the exponential decay of the associated phase space distributions. To demonstrate the structure and behavior of these distributions, we consider the fields generated from total internal reflection of a Gaussian Schell-model beam at a planar interface.

The Impact of Spatial and Temporal Resolutions in Tropical Summer Rainfall Distribution: Preliminary Results

NASA Astrophysics Data System (ADS)

Liu, Q.; Chiu, L. S.; Hao, X.

2017-10-01

The abundance or lack of rainfall affects peoples' life and activities. As a major component of the global hydrological cycle (Chokngamwong & Chiu, 2007), accurate representations at various spatial and temporal scales are crucial for a lot of decision making processes. Climate models show a warmer and wetter climate due to increases of Greenhouse Gases (GHG). However, the models' resolutions are often too coarse to be directly applicable to local scales that are useful for mitigation purposes. Hence disaggregation (downscaling) procedures are needed to transfer the coarse scale products to higher spatial and temporal resolutions. The aim of this paper is to examine the changes in the statistical parameters of rainfall at various spatial and temporal resolutions. The TRMM Multi-satellite Precipitation Analysis (TMPA) at 0.25 degree, 3 hourly grid rainfall data for a summer is aggregated to 0.5,1.0, 2.0 and 2.5 degree and at 6, 12, 24 hourly, pentad (five days) and monthly resolutions. The probability distributions (PDF) and cumulative distribution functions(CDF) of rain amount at these resolutions are computed and modeled as a mixed distribution. Parameters of the PDFs are compared using the Kolmogrov-Smironov (KS) test, both for the mixed and the marginal distribution. These distributions are shown to be distinct. The marginal distributions are fitted with Lognormal and Gamma distributions and it is found that the Gamma distributions fit much better than the Lognormal.

Distribution of the anticancer drugs doxorubicin, mitoxantrone and topotecan in tumors and normal tissues.

PubMed

Patel, Krupa J; Trédan, Olivier; Tannock, Ian F

2013-07-01

Pharmacokinetic analyses estimate the mean concentration of drug within a given tissue as a function of time, but do not give information about the spatial distribution of drugs within that tissue. Here, we compare the time-dependent spatial distribution of three anticancer drugs within tumors, heart, kidney, liver and brain. Mice bearing various xenografts were treated with doxorubicin, mitoxantrone or topotecan. At various times after injection, tumors and samples of heart, kidney, liver and brain were excised. Within solid tumors, the distribution of doxorubicin, mitoxantrone and topotecan was limited to perivascular regions at 10 min after administration and the distance from blood vessels at which drug intensity fell to half was ~25-75 μm. Although drug distribution improved after 3 and 24 h, there remained a significant decrease in drug fluorescence with increasing distance from tumor blood vessels. Drug distribution was relatively uniform in the heart, kidney and liver with substantially greater perivascular drug uptake than in tumors. There was significantly higher total drug fluorescence in the liver than in tumors after 10 min, 3 and 24 h. Little to no drug fluorescence was observed in the brain. There are marked differences in the spatial distributions of three anticancer drugs within tumor tissue and normal tissues over time, with greater exposure to most normal tissues and limited drug distribution to many cells in tumors. Studies of the spatial distribution of drugs are required to complement pharmacokinetic data in order to better understand and predict drug effects and toxicities.

Generating Within-Plant Spatial Distributions of an Insect Herbivore Based on Aggregation Patterns and Per-Node Infestation Probabilities.

PubMed

Rincon, Diego F; Hoy, Casey W; Cañas, Luis A

2015-04-01

Most predator-prey models extrapolate functional responses from small-scale experiments assuming spatially uniform within-plant predator-prey interactions. However, some predators focus their search in certain plant regions, and herbivores tend to select leaves to balance their nutrient uptake and exposure to plant defenses. Individual-based models that account for heterogeneous within-plant predator-prey interactions can be used to scale-up functional responses, but they would require the generation of explicit prey spatial distributions within-plant architecture models. The silverleaf whitefly, Bemisia tabaci biotype B (Gennadius) (Hemiptera: Aleyrodidae), is a significant pest of tomato crops worldwide that exhibits highly aggregated populations at several spatial scales, including within the plant. As part of an analytical framework to understand predator-silverleaf whitefly interactions, the objective of this research was to develop an algorithm to generate explicit spatial counts of silverleaf whitefly nymphs within tomato plants. The algorithm requires the plant size and the number of silverleaf whitefly individuals to distribute as inputs, and includes models that describe infestation probabilities per leaf nodal position and the aggregation pattern of the silverleaf whitefly within tomato plants and leaves. The output is a simulated number of silverleaf whitefly individuals for each leaf and leaflet on one or more plants. Parameter estimation was performed using nymph counts per leaflet censused from 30 artificially infested tomato plants. Validation revealed a substantial agreement between algorithm outputs and independent data that included the distribution of counts of both eggs and nymphs. This algorithm can be used in simulation models that explore the effect of local heterogeneity on whitefly-predator dynamics. © The Authors 2015. Published by Oxford University Press on behalf of Entomological Society of America. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Robustness of spatial micronetworks

NASA Astrophysics Data System (ADS)

McAndrew, Thomas C.; Danforth, Christopher M.; Bagrow, James P.

2015-04-01

Power lines, roadways, pipelines, and other physical infrastructure are critical to modern society. These structures may be viewed as spatial networks where geographic distances play a role in the functionality and construction cost of links. Traditionally, studies of network robustness have primarily considered the connectedness of large, random networks. Yet for spatial infrastructure, physical distances must also play a role in network robustness. Understanding the robustness of small spatial networks is particularly important with the increasing interest in microgrids, i.e., small-area distributed power grids that are well suited to using renewable energy resources. We study the random failures of links in small networks where functionality depends on both spatial distance and topological connectedness. By introducing a percolation model where the failure of each link is proportional to its spatial length, we find that when failures depend on spatial distances, networks are more fragile than expected. Accounting for spatial effects in both construction and robustness is important for designing efficient microgrids and other network infrastructure.

A Kinetic Study of Microwave Start-up of Tokamak Plasmas

NASA Astrophysics Data System (ADS)

du Toit, E. J.; O'Brien, M. R.; Vann, R. G. L.

2017-07-01

A kinetic model for studying the time evolution of the distribution function for microwave startup is presented. The model for the distribution function is two dimensional in momentum space, but, for simplicity and rapid calculations, has no spatial dependence. Experiments on the Mega Amp Spherical Tokamak have shown that the plasma current is carried mainly by electrons with energies greater than 70 keV, and effects thought to be important in these experiments are included, i.e. particle sources, orbital losses, the loop voltage and microwave heating, with suitable volume averaging where necessary to give terms independent of spatial dimensions. The model predicts current carried by electrons with the same energies as inferred from the experiments, though the current drive efficiency is smaller.

Time-dependent density functional theory (TD-DFT) coupled with reference interaction site model self-consistent field explicitly including spatial electron density distribution (RISM-SCF-SEDD)

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

Yokogawa, D., E-mail: d.yokogawa@chem.nagoya-u.ac.jp; Institute of Transformative Bio-Molecules

2016-09-07

Theoretical approach to design bright bio-imaging molecules is one of the most progressing ones. However, because of the system size and computational accuracy, the number of theoretical studies is limited to our knowledge. To overcome the difficulties, we developed a new method based on reference interaction site model self-consistent field explicitly including spatial electron density distribution and time-dependent density functional theory. We applied it to the calculation of indole and 5-cyanoindole at ground and excited states in gas and solution phases. The changes in the optimized geometries were clearly explained with resonance structures and the Stokes shift was correctly reproduced.

Spatially explicit spectral analysis of point clouds and geospatial data

USGS Publications Warehouse

Buscombe, Daniel D.

2015-01-01

The increasing use of spatially explicit analyses of high-resolution spatially distributed data (imagery and point clouds) for the purposes of characterising spatial heterogeneity in geophysical phenomena necessitates the development of custom analytical and computational tools. In recent years, such analyses have become the basis of, for example, automated texture characterisation and segmentation, roughness and grain size calculation, and feature detection and classification, from a variety of data types. In this work, much use has been made of statistical descriptors of localised spatial variations in amplitude variance (roughness), however the horizontal scale (wavelength) and spacing of roughness elements is rarely considered. This is despite the fact that the ratio of characteristic vertical to horizontal scales is not constant and can yield important information about physical scaling relationships. Spectral analysis is a hitherto under-utilised but powerful means to acquire statistical information about relevant amplitude and wavelength scales, simultaneously and with computational efficiency. Further, quantifying spatially distributed data in the frequency domain lends itself to the development of stochastic models for probing the underlying mechanisms which govern the spatial distribution of geological and geophysical phenomena. The software packagePySESA (Python program for Spatially Explicit Spectral Analysis) has been developed for generic analyses of spatially distributed data in both the spatial and frequency domains. Developed predominantly in Python, it accesses libraries written in Cython and C++ for efficiency. It is open source and modular, therefore readily incorporated into, and combined with, other data analysis tools and frameworks with particular utility for supporting research in the fields of geomorphology, geophysics, hydrography, photogrammetry and remote sensing. The analytical and computational structure of the toolbox is described, and its functionality illustrated with an example of a high-resolution bathymetric point cloud data collected with multibeam echosounder.

A simple method for correcting spatially resolved solar intensity oscillation observations for variations in scattered light

NASA Technical Reports Server (NTRS)

Jefferies, S. M.; Duvall, T. L., Jr.

1991-01-01

A measurement of the intensity distribution in an image of the solar disk will be corrupted by a spatial redistribution of the light that is caused by the earth's atmosphere and the observing instrument. A simple correction method is introduced here that is applicable for solar p-mode intensity observations obtained over a period of time in which there is a significant change in the scattering component of the point spread function. The method circumvents the problems incurred with an accurate determination of the spatial point spread function and its subsequent deconvolution from the observations. The method only corrects the spherical harmonic coefficients that represent the spatial frequencies present in the image and does not correct the image itself.

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.

The interpoint distance distribution as a descriptor of point patterns, with an application to spatial disease clustering.

PubMed

Bonetti, Marco; Pagano, Marcello

2005-03-15

The topic of this paper is the distribution of the distance between two points distributed independently in space. We illustrate the use of this interpoint distance distribution to describe the characteristics of a set of points within some fixed region. The properties of its sample version, and thus the inference about this function, are discussed both in the discrete and in the continuous setting. We illustrate its use in the detection of spatial clustering by application to a well-known leukaemia data set, and report on the results of a simulation experiment designed to study the power characteristics of the methods within that study region and in an artificial homogenous setting. Copyright (c) 2004 John Wiley & Sons, Ltd.

THE DEPENDENCE OF PRESTELLAR CORE MASS DISTRIBUTIONS ON THE STRUCTURE OF THE PARENTAL CLOUD

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

Parravano, Antonio; Sanchez, Nestor; Alfaro, Emilio J.

2012-08-01

The mass distribution of prestellar cores is obtained for clouds with arbitrary internal mass distributions using a selection criterion based on the thermal and turbulent Jeans mass and applied hierarchically from small to large scales. We have checked this methodology by comparing our results for a log-normal density probability distribution function with the theoretical core mass function (CMF) derived by Hennebelle and Chabrier, namely a power law at large scales and a log-normal cutoff at low scales, but our method can be applied to any mass distributions representing a star-forming cloud. This methodology enables us to connect the parental cloudmore » structure with the mass distribution of the cores and their spatial distribution, providing an efficient tool for investigating the physical properties of the molecular clouds that give rise to the prestellar core distributions observed. Simulated fractional Brownian motion (fBm) clouds with the Hurst exponent close to the value H = 1/3 give the best agreement with the theoretical CMF derived by Hennebelle and Chabrier and Chabrier's system initial mass function. Likewise, the spatial distribution of the cores derived from our methodology shows a surface density of companions compatible with those observed in Trapezium and Ophiucus star-forming regions. This method also allows us to analyze the properties of the mass distribution of cores for different realizations. We found that the variations in the number of cores formed in different realizations of fBm clouds (with the same Hurst exponent) are much larger than the expected root N statistical fluctuations, increasing with H.« less

The Dependence of Prestellar Core Mass Distributions on the Structure of the Parental Cloud

NASA Astrophysics Data System (ADS)

Parravano, Antonio; Sánchez, Néstor; Alfaro, Emilio J.

2012-08-01

The mass distribution of prestellar cores is obtained for clouds with arbitrary internal mass distributions using a selection criterion based on the thermal and turbulent Jeans mass and applied hierarchically from small to large scales. We have checked this methodology by comparing our results for a log-normal density probability distribution function with the theoretical core mass function (CMF) derived by Hennebelle & Chabrier, namely a power law at large scales and a log-normal cutoff at low scales, but our method can be applied to any mass distributions representing a star-forming cloud. This methodology enables us to connect the parental cloud structure with the mass distribution of the cores and their spatial distribution, providing an efficient tool for investigating the physical properties of the molecular clouds that give rise to the prestellar core distributions observed. Simulated fractional Brownian motion (fBm) clouds with the Hurst exponent close to the value H = 1/3 give the best agreement with the theoretical CMF derived by Hennebelle & Chabrier and Chabrier's system initial mass function. Likewise, the spatial distribution of the cores derived from our methodology shows a surface density of companions compatible with those observed in Trapezium and Ophiucus star-forming regions. This method also allows us to analyze the properties of the mass distribution of cores for different realizations. We found that the variations in the number of cores formed in different realizations of fBm clouds (with the same Hurst exponent) are much larger than the expected root {\\cal N} statistical fluctuations, increasing with H.

Functional resilience of microbial ecosystems in soil: How important is a spatial analysis?

NASA Astrophysics Data System (ADS)

König, Sara; Banitz, Thomas; Centler, Florian; Frank, Karin; Thullner, Martin

2015-04-01

Microbial life in soil is exposed to fluctuating environmental conditions influencing the performance of microbially mediated ecosystem services such as biodegradation of contaminants. However, as this environment is typically very heterogeneous, spatial aspects can be expected to play a major role for the ability to recover from a stress event. To determine key processes for functional resilience, simple scenarios with varying stress intensities were simulated within a microbial simulation model and the biodegradation rate in the recovery phase monitored. Parameters including microbial growth and dispersal rates were varied over a typical range to consider microorganisms with varying properties. Besides an aggregated temporal monitoring, the explicit observation of the spatio-temporal dynamics proved essential to understand the recovery process. For a mechanistic understanding of the model system, scenarios were also simulated with selected processes being switched-off. Results of the mechanistic and the spatial view show that the key factors for functional recovery with respect to biodegradation after a simple stress event depend on the location of the observed habitats. The limiting factors near unstressed areas are spatial processes - the mobility of the bacteria as well as substrate diffusion - the longer the distance to the unstressed region the more important becomes the process growth. Furthermore, recovery depends on the stress intensity - after a low stress event the spatial configuration has no influence on the key factors for functional resilience. To confirm these results, we repeated the stress scenarios but this time including an additional dispersal network representing a fungal network in soil. The system benefits from an increased spatial performance due to the higher mobility of the degrading microorganisms. However, this effect appears only in scenarios where the spatial distribution of the stressed area plays a role. With these simulations we show that spatial aspects play a main role for recovering after a severe stress event in a highly heterogeneous environment such as soil, and thus the relevance of the exact distribution of the stressed area. In consequence a spatial-mechanistic view is necessary for examining the functional resilience as the aggregated temporal view alone could not have led to these conclusions. Further research should explore the importance of a spatial view for quantifying the recovery of the ecosystem service also after more complex stress regimes.

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.

Scale-Dependence of Processes Structuring Dung Beetle Metacommunities Using Functional Diversity and Community Deconstruction Approaches

PubMed Central

da Silva, Pedro Giovâni; Hernández, Malva Isabel Medina

2015-01-01

Community structure is driven by mechanisms linked to environmental, spatial and temporal processes, which have been successfully addressed using metacommunity framework. The relative importance of processes shaping community structure can be identified using several different approaches. Two approaches that are increasingly being used are functional diversity and community deconstruction. Functional diversity is measured using various indices that incorporate distinct community attributes. Community deconstruction is a way to disentangle species responses to ecological processes by grouping species with similar traits. We used these two approaches to determine whether they are improvements over traditional measures (e.g., species composition, abundance, biomass) for identification of the main processes driving dung beetle (Scarabaeinae) community structure in a fragmented mainland-island landscape in southern Brazilian Atlantic Forest. We sampled five sites in each of four large forest areas, two on the mainland and two on the island. Sampling was performed in 2012 and 2013. We collected abundance and biomass data from 100 sampling points distributed over 20 sampling sites. We studied environmental, spatial and temporal effects on dung beetle community across three spatial scales, i.e., between sites, between areas and mainland-island. The γ-diversity based on species abundance was mainly attributed to β-diversity as a consequence of the increase in mean α- and β-diversity between areas. Variation partitioning on abundance, biomass and functional diversity showed scale-dependence of processes structuring dung beetle metacommunities. We identified two major groups of responses among 17 functional groups. In general, environmental filters were important at both local and regional scales. Spatial factors were important at the intermediate scale. Our study supports the notion of scale-dependence of environmental, spatial and temporal processes in the distribution and functional organization of Scarabaeinae beetles. We conclude that functional diversity may be used as a complementary approach to traditional measures, and that community deconstruction allows sufficient disentangling of responses of different trait-based groups. PMID:25822150

An Introduction to Macro- Level Spatial Nonstationarity: a Geographically Weighted Regression Analysis of Diabetes and Poverty

PubMed Central

Siordia, Carlos; Saenz, Joseph; Tom, Sarah E.

2014-01-01

Type II diabetes is a growing health problem in the United States. Understanding geographic variation in diabetes prevalence will inform where resources for management and prevention should be allocated. Investigations of the correlates of diabetes prevalence have largely ignored how spatial nonstationarity might play a role in the macro-level distribution of diabetes. This paper introduces the reader to the concept of spatial nonstationarity—variance in statistical relationships as a function of geographical location. Since spatial nonstationarity means different predictors can have varying effects on model outcomes, we make use of a geographically weighed regression to calculate correlates of diabetes as a function of geographic location. By doing so, we demonstrate an exploratory example in which the diabetes-poverty macro-level statistical relationship varies as a function of location. In particular, we provide evidence that when predicting macro-level diabetes prevalence, poverty is not always positively associated with diabetes PMID:25414731

An Introduction to Macro- Level Spatial Nonstationarity: a Geographically Weighted Regression Analysis of Diabetes and Poverty.

PubMed

Siordia, Carlos; Saenz, Joseph; Tom, Sarah E

2012-01-01

Type II diabetes is a growing health problem in the United States. Understanding geographic variation in diabetes prevalence will inform where resources for management and prevention should be allocated. Investigations of the correlates of diabetes prevalence have largely ignored how spatial nonstationarity might play a role in the macro-level distribution of diabetes. This paper introduces the reader to the concept of spatial nonstationarity-variance in statistical relationships as a function of geographical location. Since spatial nonstationarity means different predictors can have varying effects on model outcomes, we make use of a geographically weighed regression to calculate correlates of diabetes as a function of geographic location. By doing so, we demonstrate an exploratory example in which the diabetes-poverty macro-level statistical relationship varies as a function of location. In particular, we provide evidence that when predicting macro-level diabetes prevalence, poverty is not always positively associated with diabetes.

Functional Resistance to Recurrent Spatially Heterogeneous Disturbances Is Facilitated by Increased Activity of Surviving Bacteria in a Virtual Ecosystem

PubMed Central

König, Sara; Worrich, Anja; Banitz, Thomas; Harms, Hauke; Kästner, Matthias; Miltner, Anja; Wick, Lukas Y.; Frank, Karin; Thullner, Martin; Centler, Florian

2018-01-01

Bacterial degradation of organic compounds is an important ecosystem function with relevance to, e.g., the cycling of elements or the degradation of organic contaminants. It remains an open question, however, to which extent ecosystems are able to maintain such biodegradation function under recurrent disturbances (functional resistance) and how this is related to the bacterial biomass abundance. In this paper, we use a numerical simulation approach to systematically analyze the dynamic response of a microbial population to recurrent disturbances of different spatial distribution. The spatially explicit model considers microbial degradation, growth, dispersal, and spatial networks that facilitate bacterial dispersal mimicking effects of mycelial networks in nature. We find: (i) There is a certain capacity for high resistance of biodegradation performance to recurrent disturbances. (ii) If this resistance capacity is exceeded, spatial zones of different biodegradation performance develop, ranging from no or reduced to even increased performance. (iii) Bacterial biomass and biodegradation dynamics respond inversely to the spatial fragmentation of disturbances: overall biodegradation performance improves with increasing fragmentation, but bacterial biomass declines. (iv) Bacterial dispersal networks can enhance functional resistance against recurrent disturbances, mainly by reactivating zones in the core of disturbed areas, even though this leads to an overall reduction of bacterial biomass. PMID:29696013

Trace element distribution in the rat cerebellum

NASA Astrophysics Data System (ADS)

Kwiatek, W. M.; Long, G. J.; Pounds, J. G.; Reuhl, K. R.; Hanson, A. L.; Jones, K. W.

1990-04-01

Spatial distributions and concentrations of trace elements (TE) in the brain are important because TE perform catalytic and structural functions in enzymes which regulate brain function and development. We have investigated the distributions of TE in rat cerebellum. Structures were sectioned and analyzed by the Synchrotron Radiation Induced X-ray Emission (SRIXE) method using the NSLS X-26 white-light microprobe facility. Advantages important for TE analysis of biological specimens with X-ray microscopy include short time of measurement, high brightness and flux, good spatial resolution, multielemental detection, good sensitivity, and nondestructive irradiation. Trace elements were measured in thin rat brain sections of 20 μm thickness. The analyses were performed on sample volumes as small as 0.2 nl with Minimum Detectable Limits (MDL) of 50 ppb wet weight for Fe, 100 ppb wet weight for Cu, and Zn, and 1 ppm wet weight for Pb. The distribution of TE in the molecular cell layer, granule cell layer and fiber tract of rat cerebella was investigated. Both point analyses and two-dimensional semiquantitative mapping of the TE distribution in a section were used. All analyzed elements were observed in each structure of the cerebellum except mercury which was not observed in granule cell layer or fiber tract. This approach permits an exacting correlation of the TE distribution in complex structure with the diet, toxic elements, and functional status of the animal.

Fast-ion D(alpha) measurements and simulations in DIII-D

NASA Astrophysics Data System (ADS)

Luo, Yadong

The fast-ion Dalpha diagnostic measures the Doppler-shifted Dalpha light emitted by neutralized fast ions. For a favorable viewing geometry, the bright interferences from beam neutrals, halo neutrals, and edge neutrals span over a small wavelength range around the Dalpha rest wavelength and are blocked by a vertical bar at the exit focal plane of the spectrometer. Background subtraction and fitting techniques eliminate various contaminants in the spectrum. Fast-ion data are acquired with a time evolution of ˜1 ms, spatial resolution of ˜5 cm, and energy resolution of ˜10 keV. A weighted Monte Carlo simulation code models the fast-ion Dalpha spectra based on the fast-ion distribution function from other sources. In quiet plasmas, the spectral shape is in excellent agreement and absolute magnitude also has reasonable agreement. The fast-ion D alpha signal has the expected dependencies on plasma and neutral beam parameters. The neutral particle diagnostic and neutron diagnostic corroborate the fast-ion Dalpha measurements. The relative spatial profile is in agreement with the simulated profile based on the fast-ion distribution function from the TRANSP analysis code. During ion cyclotron heating, fast ions with high perpendicular energy are accelerated, while those with low perpendicular energy are barely affected. The spatial profile is compared with the simulated profiles based on the fast-ion distribution functions from the CQL Fokker-Planck code. In discharges with Alfven instabilities, both the spatial profile and spectral shape suggests that fast ions are redistributed. The flattened fast-ion Dalpha profile is in agreement with the fast-ion pressure profile.

Surface Wave Tomography with Spatially Varying Smoothing Based on Continuous Model Regionalization

NASA Astrophysics Data System (ADS)

Liu, Chuanming; Yao, Huajian

2017-03-01

Surface wave tomography based on continuous regionalization of model parameters is widely used to invert for 2-D phase or group velocity maps. An inevitable problem is that the distribution of ray paths is far from homogeneous due to the spatially uneven distribution of stations and seismic events, which often affects the spatial resolution of the tomographic model. We present an improved tomographic method with a spatially varying smoothing scheme that is based on the continuous regionalization approach. The smoothness of the inverted model is constrained by the Gaussian a priori model covariance function with spatially varying correlation lengths based on ray path density. In addition, a two-step inversion procedure is used to suppress the effects of data outliers on tomographic models. Both synthetic and real data are used to evaluate this newly developed tomographic algorithm. In the synthetic tests, when the contrived model has different scales of anomalies but with uneven ray path distribution, we compare the performance of our spatially varying smoothing method with the traditional inversion method, and show that the new method is capable of improving the recovery in regions of dense ray sampling. For real data applications, the resulting phase velocity maps of Rayleigh waves in SE Tibet produced using the spatially varying smoothing method show similar features to the results with the traditional method. However, the new results contain more detailed structures and appears to better resolve the amplitude of anomalies. From both synthetic and real data tests we demonstrate that our new approach is useful to achieve spatially varying resolution when used in regions with heterogeneous ray path distribution.

Multisite-multivariable sensitivity analysis of distributed watershed models: enhancing the perceptions from computationally frugal methods

USDA-ARS?s Scientific Manuscript database

This paper assesses the impact of different likelihood functions in identifying sensitive parameters of the highly parameterized, spatially distributed Soil and Water Assessment Tool (SWAT) watershed model for multiple variables at multiple sites. The global one-factor-at-a-time (OAT) method of Morr...

Effect of Spatial Distribution and Connectivity of Urban Impervious Areas on Hydrologic Response

NASA Astrophysics Data System (ADS)

Khoshouei, F.; Basu, N. B.; Schnoor, J. L.

2012-12-01

Urbanization alters the hydrology of a watershed by increasing impervious areas which results in decreased infiltration and increased runoff. Total Impervious Area (TIA) has been extensively used as a metric to describe this impact. It has recently been recognized, however, that TIA is a necessary but not sufficient attribute to describe the hydrologic response of a watershed. The connectivity and spatial placement of the impervious areas play a significant role in altering streamflow distributions. While the importance of spatial metrics is well recognized, the actual magnitude of their impact has not been adequately quantified in a systematic manner. We assess the effect of the spatial distribution of impervious area on hydrologic response in six peri-urban watersheds with areas in the order of 15 sq km in Midwest. We use the Gridded Surface Subsurface Hydrologic Analysis (GSSHA) model from the Army Corp of Engineers for our exploration. GSSHA is a grid-based two-dimensional hydrologic model with 2D overland flow and 1D streamflow and infiltration. The models for the watersheds were calibrated and validated using discharge data from USGS streamflow database. The models were then used in a virtual experimentation mode to understand the variability in hydrologic response as a function of different patterns of urban expansion. A new metric, "Impervious Area Width Function- IAWF" was developed that captured the distribution of flow path lengths from impervious areas. This metric captured the difference in hydrologic response between two watersheds with the same total impervious area but different distributions. The results suggest that urban development in areas with longer travel time (far from outlet) results in higher peak flows.

Electron and ion distribution functions in magnetopause reconnection

NASA Astrophysics Data System (ADS)

Wang, S.; Chen, L. J.; Bessho, N.; Hesse, M.; Kistler, L. M.; Torbert, R. B.; Mouikis, C.; Pollock, C. J.

2015-12-01

We investigate electron and ion velocity distribution functions in dayside magnetopause reconnection events observed by the Cluster and MMS spacecraft. The goal is to build a spatial map of electron and ion distribution features to enable the indication of the spacecraft location in the reconnection structure, and to understand plasma energization processes. Distribution functions, together with electromagnetic field structures, plasma densities, and bulk velocities, are organized and compared with particle-in-cell simulation results to indicate the proximities to the reconnection X-line. Anisotropic features in the distributions of magnetospheric- and magnetosheath- origin electrons at different locations in the reconnection inflow and exhaust are identified. In particular, parallel electron heating is observed in both the magnetosheath and magnetosphere inflow regions. Possible effects of the guide field strength, waves, and upstream density and temperature asymmetries on the distribution features will be discussed.

Evidence for hubs in human functional brain networks

PubMed Central

Power, Jonathan D; Schlaggar, Bradley L; Lessov-Schlaggar, Christina N; Petersen, Steven E

2013-01-01

Summary Hubs integrate and distribute information in powerful ways due to the number and positioning of their contacts in a network. Several resting state functional connectivity MRI reports have implicated regions of the default mode system as brain hubs; we demonstrate that previous degree-based approaches to hub identification may have identified portions of large brain systems rather than critical nodes of brain networks. We utilize two methods to identify hub-like brain regions: 1) finding network nodes that participate in multiple sub-networks of the brain, and 2) finding spatial locations where several systems are represented within a small volume. These methods converge on a distributed set of regions that differ from previous reports on hubs. This work identifies regions that support multiple systems, leading to spatially constrained predictions about brain function that may be tested in terms of lesions, evoked responses, and dynamic patterns of activity. PMID:23972601

Interrogating Surface Functional Group Heterogeneity of Activated Thermoplastics Using Super-Resolution Fluorescence Microscopy.

PubMed

ONeil, Colleen E; Jackson, Joshua M; Shim, Sang-Hee; Soper, Steven A

2016-04-05

We present a novel approach for characterizing surfaces utilizing super-resolution fluorescence microscopy with subdiffraction limit spatial resolution. Thermoplastic surfaces were activated by UV/O3 or O2 plasma treatment under various conditions to generate pendant surface-confined carboxylic acids (-COOH). These surface functional groups were then labeled with a photoswitchable dye and interrogated using single-molecule, localization-based, super-resolution fluorescence microscopy to elucidate the surface heterogeneity of these functional groups across the activated surface. Data indicated nonuniform distributions of these functional groups for both COC and PMMA thermoplastics with the degree of heterogeneity being dose dependent. In addition, COC demonstrated relative higher surface density of functional groups compared to PMMA for both UV/O3 and O2 plasma treatment. The spatial distribution of -COOH groups secured from super-resolution imaging were used to simulate nonuniform patterns of electroosmotic flow in thermoplastic nanochannels. Simulations were compared to single-particle tracking of fluorescent nanoparticles within thermoplastic nanoslits to demonstrate the effects of surface functional group heterogeneity on the electrokinetic transport process.

Electron temperature profiles in axial field 2.45 GHz ECR ion source with a ceramic chamber

NASA Astrophysics Data System (ADS)

Abe, K.; Tamura, R.; Kasuya, T.; Wada, M.

2017-08-01

An array of electrostatic probes was arranged on the plasma electrode of a 2.45 GHz microwave driven axial magnetic filter field type negative hydrogen (H-) ion source to clarify the spatial plasma distribution near the electrode. The measured spatial distribution of electron temperature indicated the lower temperature near the extraction hole of the plasma electrode corresponding to the effectiveness of the axial magnetic filter field geometry. When the ratio of electron saturation current to the ion saturation current was plotted as a function of position, the obtained distribution showed a higher ratio near the hydrogen gas inlet through which ground state hydrogen molecules are injected into the source. Though the efficiency in producing H- ions is smaller for a 2.45 GHz source than a source operated at 14 GHz, it gives more volume to measure spatial distributions of various plasma parameters to understand fundamental processes that are influential on H- production in this type of ion sources.

Spatial heterogeneity and air pollution removal by an urban forest

Treesearch

Francisco J. Escobedo; David J. Nowak

2009-01-01

Estimates of air pollution removal by the urban forest have mostly been based on mean values of forest structure variables for an entire city. However, the urban forest is not uniformly distributed across a city because of biophysical and social factors. Consequently, air pollution removal function by urban vegetation should vary because of this spatial heterogeneity....

High spatiotemporal resolution monitoring of hydrological function across degraded peatlands in the south west UK.

NASA Astrophysics Data System (ADS)

Ashe, Josie; Luscombe, David; Grand-Clement, Emilie; Gatis, Naomi; Anderson, Karen; Brazier, Richard

2014-05-01

The Exmoor/Dartmoor Mires Project is a peatland restoration programme focused on the geoclimatically marginal blanket bogs of South West England. In order to better understand the hydrological functioning of degraded/restored peatlands and support land management decisions across these uplands, this study is providing robust spatially distributed, hydrological monitoring at a high temporal resolution and in near real time. This paper presents the conceptual framework and experimental design for three hydrological monitoring arrays situated in headwater catchments dominated by eroding and drained blanket peatland. Over 250 individual measurements are collected at a high temporal resolution (15 minute time-step) via sensors integrated within a remote telemetry system. These are sent directly to a dedicated server over VHF and GPRS mobile networks. Sensors arrays are distributed at varying spatial scales throughout the studied catchments and record multiple parameters including: water table depth, channel flow, temperature, conductivity and pH measurements. A full suite of meteorological sensors and ten spatially distributed automatic flow based water samplers are also connected to the telemetry system and controlled remotely. This paper will highlight the challenges and solutions to obtaining these data in exceptionally remote and harsh field conditions over long (multi annual) temporal scales.

The role of biotic interactions in shaping distributions and realised assemblages of species: implications for species distribution modelling

PubMed Central

Wisz, Mary Susanne; Pottier, Julien; Kissling, W Daniel; Pellissier, Loïc; Lenoir, Jonathan; Damgaard, Christian F; Dormann, Carsten F; Forchhammer, Mads C; Grytnes, John-Arvid; Guisan, Antoine; Heikkinen, Risto K; Høye, Toke T; Kühn, Ingolf; Luoto, Miska; Maiorano, Luigi; Nilsson, Marie-Charlotte; Normand, Signe; Öckinger, Erik; Schmidt, Niels M; Termansen, Mette; Timmermann, Allan; Wardle, David A; Aastrup, Peter; Svenning, Jens-Christian

2013-01-01

Predicting which species will occur together in the future, and where, remains one of the greatest challenges in ecology, and requires a sound understanding of how the abiotic and biotic environments interact with dispersal processes and history across scales. Biotic interactions and their dynamics influence species' relationships to climate, and this also has important implications for predicting future distributions of species. It is already well accepted that biotic interactions shape species' spatial distributions at local spatial extents, but the role of these interactions beyond local extents (e.g. 10 km2 to global extents) are usually dismissed as unimportant. In this review we consolidate evidence for how biotic interactions shape species distributions beyond local extents and review methods for integrating biotic interactions into species distribution modelling tools. Drawing upon evidence from contemporary and palaeoecological studies of individual species ranges, functional groups, and species richness patterns, we show that biotic interactions have clearly left their mark on species distributions and realised assemblages of species across all spatial extents. We demonstrate this with examples from within and across trophic groups. A range of species distribution modelling tools is available to quantify species environmental relationships and predict species occurrence, such as: (i) integrating pairwise dependencies, (ii) using integrative predictors, and (iii) hybridising species distribution models (SDMs) with dynamic models. These methods have typically only been applied to interacting pairs of species at a single time, require a priori ecological knowledge about which species interact, and due to data paucity must assume that biotic interactions are constant in space and time. To better inform the future development of these models across spatial scales, we call for accelerated collection of spatially and temporally explicit species data. Ideally, these data should be sampled to reflect variation in the underlying environment across large spatial extents, and at fine spatial resolution. Simplified ecosystems where there are relatively few interacting species and sometimes a wealth of existing ecosystem monitoring data (e.g. arctic, alpine or island habitats) offer settings where the development of modelling tools that account for biotic interactions may be less difficult than elsewhere. PMID:22686347

Spatio-Temporal Characteristics of Resident Trip Based on Poi and OD Data of Float CAR in Beijing

NASA Astrophysics Data System (ADS)

Mou, N.; Li, J.; Zhang, L.; Liu, W.; Xu, Y.

2017-09-01

Due to the influence of the urban inherent regional functional distribution, the daily activities of the residents presented some spatio-temporal patterns (periodic patterns, gathering patterns, etc.). In order to further understand the spatial and temporal characteristics of urban residents, this paper research takes the taxi trajectory data of Beijing as a sample data and studies the spatio-temporal characteristics of the residents' activities on the weekdays. At first, according to the characteristics of the taxi trajectory data distributed along the road network, it takes the Voronoi generated by the road nodes as the research unit. This paper proposes a hybrid clustering method - based on grid density, which is used to cluster the OD (origin and destination) data of taxi at different times. Then combining with the POI data of Beijing, this research calculated the density of the POI data in the clustering results, and analyzed the relationship between the activities of residents in different periods and the functional types of the region. The final results showed that the residents were mainly commuting on weekdays. And it found that the distribution of travel density showed a concentric circle of the characteristics, focusing on residential areas and work areas. The results of cluster analysis and POI analysis showed that the residents' travel had experienced the process of "spatial relative dispersion - spatial aggregation - spatial relative dispersion" in one day.

A fast integrated mobility spectrometer for rapid measurement of sub-micrometer aerosol size distribution, Part I: Design and model evaluation

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

Wang, Jian; Pikridas, Michael; Spielman, Steven R.

This study discusses, a fast integrated mobility spectrometer (FIMS) was previously developed to characterize submicron aerosol size distributions at a frequency of 1 Hz and with high size resolution and counting statistics. However, the dynamic size range of the FIMS was limited to one decade in particle electrical mobility. It was proposed that the FIMS dynamic size range can be greatly increased by using a spatially varying electric field. This electric field creates regions with drastically different field strengths in the separator, such that particles of a wide diameter range can be simultaneously classified and subsequently measured. A FIMS incorporatingmore » this spatially varying electric field is developed. This paper describes the theoretical frame work and numerical simulations of the FIMS with extended dynamic size range, including the spatially varying electric field, particle trajectories, activation of separated particles in the condenser, and the transfer function, transmission efficiency, and mobility resolution. The influences of the particle Brownian motion on FIMS transfer function and mobility resolution are examined. The simulation results indicate that the FIMS incorporating the spatially varying electric field is capable of measuring aerosol size distribution from 8 to 600 nm with high time resolution. As a result, the experimental characterization of the FIMS is presented in an accompanying paper.« less

A fast integrated mobility spectrometer for rapid measurement of sub-micrometer aerosol size distribution, Part I: Design and model evaluation

DOE PAGES

Wang, Jian; Pikridas, Michael; Spielman, Steven R.; ...

2017-06-01

This study discusses, a fast integrated mobility spectrometer (FIMS) was previously developed to characterize submicron aerosol size distributions at a frequency of 1 Hz and with high size resolution and counting statistics. However, the dynamic size range of the FIMS was limited to one decade in particle electrical mobility. It was proposed that the FIMS dynamic size range can be greatly increased by using a spatially varying electric field. This electric field creates regions with drastically different field strengths in the separator, such that particles of a wide diameter range can be simultaneously classified and subsequently measured. A FIMS incorporatingmore » this spatially varying electric field is developed. This paper describes the theoretical frame work and numerical simulations of the FIMS with extended dynamic size range, including the spatially varying electric field, particle trajectories, activation of separated particles in the condenser, and the transfer function, transmission efficiency, and mobility resolution. The influences of the particle Brownian motion on FIMS transfer function and mobility resolution are examined. The simulation results indicate that the FIMS incorporating the spatially varying electric field is capable of measuring aerosol size distribution from 8 to 600 nm with high time resolution. As a result, the experimental characterization of the FIMS is presented in an accompanying paper.« less

Three-dimensional spatial modeling of spines along dendritic networks in human cortical pyramidal neurons

PubMed Central

Larrañaga, Pedro; Benavides-Piccione, Ruth; Fernaud-Espinosa, Isabel; DeFelipe, Javier; Bielza, Concha

2017-01-01

We modeled spine distribution along the dendritic networks of pyramidal neurons in both basal and apical dendrites. To do this, we applied network spatial analysis because spines can only lie on the dendritic shaft. We expanded the existing 2D computational techniques for spatial analysis along networks to perform a 3D network spatial analysis. We analyzed five detailed reconstructions of adult human pyramidal neurons of the temporal cortex with a total of more than 32,000 spines. We confirmed that there is a spatial variation in spine density that is dependent on the distance to the cell body in all dendrites. Considering the dendritic arborizations of each pyramidal cell as a group of instances of the same observation (the neuron), we used replicated point patterns together with network spatial analysis for the first time to search for significant differences in the spine distribution of basal dendrites between different cells and between all the basal and apical dendrites. To do this, we used a recent variant of Ripley’s K function defined to work along networks. The results showed that there were no significant differences in spine distribution along basal arbors of the same neuron and along basal arbors of different pyramidal neurons. This suggests that dendritic spine distribution in basal dendritic arbors adheres to common rules. However, we did find significant differences in spine distribution along basal versus apical networks. Therefore, not only do apical and basal dendritic arborizations have distinct morphologies but they also obey different rules of spine distribution. Specifically, the results suggested that spines are more clustered along apical than in basal dendrites. Collectively, the results further highlighted that synaptic input information processing is different between these two dendritic domains. PMID:28662210

Three-dimensional spatial modeling of spines along dendritic networks in human cortical pyramidal neurons.

PubMed

Anton-Sanchez, Laura; Larrañaga, Pedro; Benavides-Piccione, Ruth; Fernaud-Espinosa, Isabel; DeFelipe, Javier; Bielza, Concha

2017-01-01

We modeled spine distribution along the dendritic networks of pyramidal neurons in both basal and apical dendrites. To do this, we applied network spatial analysis because spines can only lie on the dendritic shaft. We expanded the existing 2D computational techniques for spatial analysis along networks to perform a 3D network spatial analysis. We analyzed five detailed reconstructions of adult human pyramidal neurons of the temporal cortex with a total of more than 32,000 spines. We confirmed that there is a spatial variation in spine density that is dependent on the distance to the cell body in all dendrites. Considering the dendritic arborizations of each pyramidal cell as a group of instances of the same observation (the neuron), we used replicated point patterns together with network spatial analysis for the first time to search for significant differences in the spine distribution of basal dendrites between different cells and between all the basal and apical dendrites. To do this, we used a recent variant of Ripley's K function defined to work along networks. The results showed that there were no significant differences in spine distribution along basal arbors of the same neuron and along basal arbors of different pyramidal neurons. This suggests that dendritic spine distribution in basal dendritic arbors adheres to common rules. However, we did find significant differences in spine distribution along basal versus apical networks. Therefore, not only do apical and basal dendritic arborizations have distinct morphologies but they also obey different rules of spine distribution. Specifically, the results suggested that spines are more clustered along apical than in basal dendrites. Collectively, the results further highlighted that synaptic input information processing is different between these two dendritic domains.

Statistical analysis of the surface figure of the James Webb Space Telescope

NASA Astrophysics Data System (ADS)

Lightsey, Paul A.; Chaney, David; Gallagher, Benjamin B.; Brown, Bob J.; Smith, Koby; Schwenker, John

2012-09-01

The performance of an optical system is best characterized by either the point spread function (PSF) or the optical transfer function (OTF). However, for system budgeting purposes, it is convenient to use a single scalar metric, or a combination of a few scalar metrics to track performance. For the James Webb Space Telescope, the Observatory level requirements were expressed in metrics of Strehl Ratio, and Encircled Energy. These in turn were converted to the metrics of total rms WFE and rms WFE within spatial frequency domains. The 18 individual mirror segments for the primary mirror segment assemblies (PMSA), the secondary mirror (SM), tertiary mirror (TM), and Fine Steering Mirror have all been fabricated. They are polished beryllium mirrors with a protected gold reflective coating. The statistical analysis of the resulting Surface Figure Error of these mirrors has been analyzed. The average spatial frequency distribution and the mirror-to-mirror consistency of the spatial frequency distribution are reported. The results provide insight to system budgeting processes for similar optical systems.

One-loop gravitational wave spectrum in de Sitter spacetime

NASA Astrophysics Data System (ADS)

Fröb, Markus B.; Roura, Albert; Verdaguer, Enric

2012-08-01

The two-point function for tensor metric perturbations around de Sitter spacetime including one-loop corrections from massless conformally coupled scalar fields is calculated exactly. We work in the Poincaré patch (with spatially flat sections) and employ dimensional regularization for the renormalization process. Unlike previous studies we obtain the result for arbitrary time separations rather than just equal times. Moreover, in contrast to existing results for tensor perturbations, ours is manifestly invariant with respect to the subgroup of de Sitter isometries corresponding to a simultaneous time translation and rescaling of the spatial coordinates. Having selected the right initial state for the interacting theory via an appropriate iepsilon prescription is crucial for that. Finally, we show that although the two-point function is a well-defined spacetime distribution, the equal-time limit of its spatial Fourier transform is divergent. Therefore, contrary to the well-defined distribution for arbitrary time separations, the power spectrum is strictly speaking ill-defined when loop corrections are included.

Coordination of genomic structure and transcription by the main bacterial nucleoid-associated protein HU

PubMed Central

Berger, Michael; Farcas, Anca; Geertz, Marcel; Zhelyazkova, Petya; Brix, Klaudia; Travers, Andrew; Muskhelishvili, Georgi

2010-01-01

The histone-like protein HU is a highly abundant DNA architectural protein that is involved in compacting the DNA of the bacterial nucleoid and in regulating the main DNA transactions, including gene transcription. However, the coordination of the genomic structure and function by HU is poorly understood. Here, we address this question by comparing transcript patterns and spatial distributions of RNA polymerase in Escherichia coli wild-type and hupA/B mutant cells. We demonstrate that, in mutant cells, upregulated genes are preferentially clustered in a large chromosomal domain comprising the ribosomal RNA operons organized on both sides of OriC. Furthermore, we show that, in parallel to this transcription asymmetry, mutant cells are also impaired in forming the transcription foci—spatially confined aggregations of RNA polymerase molecules transcribing strong ribosomal RNA operons. Our data thus implicate HU in coordinating the global genomic structure and function by regulating the spatial distribution of RNA polymerase in the nucleoid. PMID:20010798

Proton Energy Optimization and Spatial Distribution Analysis from a Thickness Study Using Liquid Crystal Targets

NASA Astrophysics Data System (ADS)

Willis, Christopher; Poole, Patrick; Schumacher, Douglas; Freeman, Richard; van Woerkom, Linn

2016-10-01

Laser-accelerated ions from thin targets have been widely studied for applications including secondary radiation sources and cancer therapy, with recent studies trending towards thinner targets which can provide improved ion energies and yields. Here we discuss results from an experiment on the Scarlet laser at OSU using variable thickness liquid crystal targets. On this experiment, the spatial and spectral distributions of accelerated ions were measured along target normal and laser axes at varying thicknesses from 150nm to 2000nm at a laser intensity of 1 ×1020W /cm2 . Maximum ion energy was observed for targets in the 600 - 800nm thickness range, with proton energies reaching 24MeV . The ions were further characterized using radiochromic film, revealing an unusual spatial distribution on many laser shots. Here, the peak ion yield falls in an annular ring surrounding the target normal, with an increasing divergence angle as a function of ion energy. Details of these spatial and spectral ion distributions will be presented, including spectral deconvolution of the RCF data, revealing additional trends in the accelerated ion distributions. Supported by the DARPA PULSE program through a Grant from AMRDEC, and by the NNSA under contract DE-NA0001976.

Fast Gated EPR Imaging of the Beating Heart: Spatiotemporally-Resolved 3D Imaging of Free Radical Distribution during the Cardiac Cycle

PubMed Central

Chen, Zhiyu; Reyes, Levy A.; Johnson, David H.; Velayutham, Murugesan; Yang, Changjun; Samouilov, Alexandre; Zweier, Jay L.

2012-01-01

In vivo or ex vivo electron paramagnetic resonance imaging (EPRI) is a powerful technique for determining the spatial distribution of free radicals and other paramagnetic species in living organs and tissues. However, applications of EPRI have been limited by long projection acquisition times and the consequent fact that rapid gated EPRI was not possible. Hence in vivo EPRI typically provided only time-averaged information. In order to achieve direct gated EPRI, a fast EPR acquisition scheme was developed to decrease EPR projection acquisition time down to 10 – 20 ms, along with corresponding software and instrumentation to achieve fast gated EPRI of the isolated beating heart with submillimeter spatial resolution in as little as 2 to 3 minutes. Reconstructed images display temporal and spatial variations of the free radical distribution, anatomical structure, and contractile function within the rat heart during the cardiac cycle. PMID:22473660

Spatial MEG laterality maps for language: clinical applications in epilepsy.

PubMed

D'Arcy, Ryan C N; Bardouille, Timothy; Newman, Aaron J; McWhinney, Sean R; Debay, Drew; Sadler, R Mark; Clarke, David B; Esser, Michael J

2013-08-01

Functional imaging is increasingly being used to provide a noninvasive alternative to intracarotid sodium amobarbitol testing (i.e., the Wada test). Although magnetoencephalography (MEG) has shown significant potential in this regard, the resultant output is often reduced to a simplified estimate of laterality. Such estimates belie the richness of functional imaging data and consequently limit the potential value. We present a novel approach that utilizes MEG data to compute "complex laterality vectors" and consequently "laterality maps" for a given function. Language function was examined in healthy controls and in people with epilepsy. When compared with traditional laterality index (LI) approaches, the resultant maps provided critical information about the magnitude and spatial characteristics of lateralized function. Specifically, it was possible to more clearly define low LI scores resulting from strong bilateral activation, high LI scores resulting from weak unilateral activation, and most importantly, the spatial distribution of lateralized activation. We argue that the laterality concept is better presented with the inherent spatial sensitivity of activation maps, rather than being collapsed into a one-dimensional index. Copyright © 2012 Wiley Periodicals, Inc.

Spatial Pattern of Standing Timber Value across the Brazilian Amazon

PubMed Central

Ahmed, Sadia E.; Ewers, Robert M.

2012-01-01

The Amazon is a globally important system, providing a host of ecosystem services from climate regulation to food sources. It is also home to a quarter of all global diversity. Large swathes of forest are removed each year, and many models have attempted to predict the spatial patterns of this forest loss. The spatial patterns of deforestation are determined largely by the patterns of roads that open access to frontier areas and expansion of the road network in the Amazon is largely determined by profit seeking logging activities. Here we present predictions for the spatial distribution of standing value of timber across the Amazon. We show that the patterns of timber value reflect large-scale ecological gradients, determining the spatial distribution of functional traits of trees which are, in turn, correlated with timber values. We expect that understanding the spatial patterns of timber value across the Amazon will aid predictions of logging movements and thus predictions of potential future road developments. These predictions in turn will be of great use in estimating the spatial patterns of deforestation in this globally important biome. PMID:22590520

Alcohol beverage control, privatization and the geographic distribution of alcohol outlets

PubMed Central

2012-01-01

Background With Pennsylvania currently considering a move away from an Alcohol Beverage Control state to a privatized alcohol distribution system, this study uses a spatial analytical approach to examine potential impacts of privatization on the number and spatial distribution of alcohol outlets in the city of Philadelphia over a long time horizon. Methods A suite of geospatial data were acquired for Philadelphia, including 1,964 alcohol outlet locations, 569,928 land parcels, and school, church, hospital, park and playground locations. These data were used as inputs for exploratory spatial analysis to estimate the expected number of outlets that would eventually operate in Philadelphia. Constraints included proximity restrictions (based on current ordinances regulating outlet distribution) of at least 200 feet between alcohol outlets and at least 300 feet between outlets and schools, churches, hospitals, parks and playgrounds. Results Findings suggest that current state policies on alcohol outlet distributions in Philadelphia are loosely enforced, with many areas exhibiting extremely high spatial densities of outlets that violate existing proximity restrictions. The spatial model indicates that an additional 1,115 outlets could open in Philadelphia if privatization was to occur and current proximity ordinances were maintained. Conclusions The study reveals that spatial analytical approaches can function as an excellent tool for contingency-based “what-if” analysis, providing an objective snapshot of potential policy outcomes prior to implementation. In this case, the likely outcome is a tremendous increase in alcohol outlets in Philadelphia, with concomitant negative health, crime and quality of life outcomes that accompany such an increase. PMID:23170899

Protic ammonium carboxylate ionic liquids: insight into structure, dynamics and thermophysical properties by alkyl group functionalization.

PubMed

Reddy, Th Dhileep N; Mallik, Bhabani S

2017-04-19

This study is aimed at characterising the structure, dynamics and thermophysical properties of five alkylammonium carboxylate ionic liquids (ILs) from classical molecular dynamics simulations. The structural features of these ILs were characterised by calculating the site-site radial distribution functions, g(r), spatial distribution functions and structure factors. The structural properties demonstrate that ILs show greater interaction between cations and anions when alkyl chain length increases on the cation or anion. In all ILs, spatial distribution functions show that the anion is close to the acidic hydrogen atoms of the ammonium cation. We determined the role of alkyl group functionalization of the charged entities, cations and anions, in the dynamical behavior and the transport coefficients of this family of ionic liquids. The dynamics of ILs are described by studying the mean square displacement (MSD) of the centres of mass of the ions, diffusion coefficients, ionic conductivities and hydrogen bonds as well as residence dynamics. The diffusion coefficients and ionic conductivity decrease with an increase in the size of the cation or anion. The effect of alkyl chain length on ionic conductivity calculated in this article is consistent with the findings of other experimental studies. Hydrogen bond lifetimes and residence times along with structure factors were also calculated, and are related to alkyl chain length.

Effects of calcium leaching on diffusion properties of hardened and altered cement pastes

NASA Astrophysics Data System (ADS)

Kurumisawa, Kiyofumi; Haga, Kazuko; Hayashi, Daisuke; Owada, Hitoshi

2017-06-01

It is very important to predict alterations in the concrete used for fabricating disposal containers for radioactive waste. Therefore, it is necessary to understand the alteration of cementitious materials caused by calcium leaching when they are in contact with ground water in the long term. To evaluate the long-term transport characteristics of cementitious materials, the microstructural behavior of these materials should be considered. However, many predictive models of transport characteristics focus on the pore structure, while only few such models consider both, the spatial distribution of calcium silicate hydrate (C-S-H), portlandite, and the pore spaces. This study focused on the spatial distribution of these cement phases. The auto-correlation function of each phase of cementitious materials was calculated from two-dimensional backscattered electron imaging, and the three-dimensional spatial image of the cementitious material was produced using these auto-correlation functions. An attempt was made to estimate the diffusion coefficient of chloride from the three-dimensional spatial image. The estimated diffusion coefficient of the altered sample from the three-dimensional spatial image was found to be comparable to the measured value. This demonstrated that it is possible to predict the diffusion coefficient of the altered cement paste by using the proposed model.

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

NASA Astrophysics Data System (ADS)

Berryman, James G.

1998-02-01

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

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

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

Berryman, J.G.

1998-02-01

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

Quantification of spatial distribution and spread of bacteria in soil at microscale

NASA Astrophysics Data System (ADS)

Juyal, Archana; Eickhorst, Thilo; Falconer, Ruth; Baveye, Philippe; Otten, Wilfred

2015-04-01

Soil bacteria play an essential role in functioning of ecosystems and maintaining of biogeochemical cycles. Soil is a complex heterogeneous environment comprising of highly variable and dynamic micro-habitats that have significant impacts on the growth and activity of resident microbiota including bacteria and fungi. Bacteria occupy a very small portion of available pore space in soil which demonstrates that their spatial arrangement in soil has a huge impact on the contact to their target and on the way they interact to carry out their functions. Due to limitation of techniques, there is scant information on spatial distribution of indigenous or introduced bacteria at microhabitat scale. There is a need to understand the interaction between soil structure and microorganisms including fungi for ecosystem-level processes such as carbon sequestration and improving the predictive models for soil management. In this work, a combination of techniques was used including X-ray CT to characterize the soil structure and in-situ detection via fluorescence microscopy to visualize and quantify bacteria in soil thin sections. Pseudomonas fluorescens bacteria were introduced in sterilized soil of aggregate size 1-2 mm and packed at bulk-densities 1.3 g cm-3 and 1.5 g cm-3. A subset of samples was fixed with paraformaldehyde and subsequently impregnated with resin. DAPI and fluorescence in situ hybridization (FISH) were used to visualize bacteria in thin sections of soil cores by epifluorescence microscopy to enumerate spatial distribution of bacteria in soil. The pore geometry of soil was quantified after X-ray microtomography scanning. The distribution of bacteria introduced locally reduced significantly (P

Vegetation function and non-uniqueness of the hydrological response

NASA Astrophysics Data System (ADS)

Ivanov, V. Y.; Fatichi, S.; Kampf, S. K.; Caporali, E.

2012-04-01

Through local moisture uptake vegetation exerts seasonal and longer-term impacts on the watershed hydrological response. However, the role of vegetation may go beyond the conventionally implied and well-understood "sink" function in the basin soil moisture storage equation. We argue that vegetation function imposes a "homogenizing" effect on pre-event soil moisture spatial storage, decreasing the likelihood that a rainfall event will result in a topographically-driven redistribution of soil water and the consequent formation of variable source areas. In combination with vegetation temporal dynamics, this may lead to the non-uniqueness of the hydrological response with respect to the mean basin wetness. This study designs a set of relevant numerical experiments carried out with two physically-based models; one of the models, HYDRUS, resolves variably saturated subsurface flow using a fully three-dimensional formulation, while the other model, tRIBS+VEGGIE, uses a one-dimensional formulation applied in a quasi-three-dimensional framework in combination with the model of vegetation dynamics. We demonstrate that (1) vegetation function modifies spatial heterogeneity in moisture spatial storage by imposing different degrees of subsurface flow connectivity; explore mechanistically (2) how and why a basin with the same mean soil moisture can have distinctly different spatial soil moisture distributions; and demonstrate (2) how these distinct moisture distributions result in a hysteretic runoff response to precipitation. Furthermore, the study argues that near-surface soil moisture is an insufficient indicator of the initial moisture state of a catchment with the implication of its limited effect on hydrological predictability.

Connection between two statistical approaches for the modelling of particle velocity and concentration distributions in turbulent flow: The mesoscopic Eulerian formalism and the two-point probability density function method

NASA Astrophysics Data System (ADS)

Simonin, Olivier; Zaichik, Leonid I.; Alipchenkov, Vladimir M.; Février, Pierre

2006-12-01

The objective of the paper is to elucidate a connection between two approaches that have been separately proposed for modelling the statistical spatial properties of inertial particles in turbulent fluid flows. One of the approaches proposed recently by Février, Simonin, and Squires [J. Fluid Mech. 533, 1 (2005)] is based on the partitioning of particle turbulent velocity field into spatially correlated (mesoscopic Eulerian) and random-uncorrelated (quasi-Brownian) components. The other approach stems from a kinetic equation for the two-point probability density function of the velocity distributions of two particles [Zaichik and Alipchenkov, Phys. Fluids 15, 1776 (2003)]. Comparisons between these approaches are performed for isotropic homogeneous turbulence and demonstrate encouraging agreement.

Modulation of Kekulé adatom ordering due to strain in graphene

NASA Astrophysics Data System (ADS)

González-Árraga, L.; Guinea, F.; San-Jose, P.

2018-04-01

Intervalley scattering of carriers in graphene at "top" adatoms may give rise to a hidden Kekulé ordering pattern in the adatom positions. This ordering is the result of a rapid modulation in the electron-mediated interaction between adatoms at the wave vector K -K' , which has been shown experimentally and theoretically to dominate their spatial distribution. Here we show that the adatom interaction is extremely sensitive to strain in the supporting graphene, which leads to a characteristic spatial modulation of the Kekulé order as a function of adatom distance. Our results suggest that the spatial distributions of adatoms could provide a way to measure the type and magnitude of strain in graphene and the associated pseudogauge field with high accuracy.

[Spatial point pattern analysis of main trees and flowering Fargesia qinlingensis in Abies fargesii forests in Mt Taibai of the Qinling Mountains, China].

PubMed

Li, Guo Chun; Song, Hua Dong; Li, Qi; Bu, Shu Hai

2017-11-01

In Abies fargesii forests of the giant panda's habitats in Mt. Taibai, the spatial distribution patterns and interspecific associations of main tree species and their spatial associations with the understory flowering Fargesia qinlingensis were analyzed at multiple scales by univariate and bivaria-te O-ring function in point pattern analysis. The results showed that in the A. fargesii forest, the number of A. fargesii was largest but its population structure was in decline. The population of Betula platyphylla was relatively young, with a stable population structure, while the population of B. albo-sinensis declined. The three populations showed aggregated distributions at small scales and gradually showed random distributions with increasing spatial scales. Spatial associations among tree species were mainly showed at small scales and gradually became not spatially associated with increasing scale. A. fargesii and B. platyphylla were positively associated with flowering F. qinlingensis at large and medium scales, whereas B. albo-sinensis showed negatively associated with flowering F. qinlingensis at large and medium scales. The interaction between trees and F. qinlingensis in the habitats of giant panda promoted the dynamic succession and development of forests, which changed the environment of giant panda's habitats in Qinling.

Structural and functional properties of spatially embedded scale-free networks.

PubMed

Emmerich, Thorsten; Bunde, Armin; Havlin, Shlomo

2014-06-01

Scale-free networks have been studied mostly as non-spatially embedded systems. However, in many realistic cases, they are spatially embedded and these constraints should be considered. Here, we study the structural and functional properties of a model of scale-free (SF) spatially embedded networks. In our model, both the degree and the length of links follow power law distributions as found in many real networks. We show that not all SF networks can be embedded in space and that the largest degree of a node in the network is usually smaller than in nonembedded SF networks. Moreover, the spatial constraints (each node has only few neighboring nodes) introduce degree-degree anticorrelations (disassortativity) since two high degree nodes cannot stay close in space. We also find significant effects of space embedding on the hopping distances (chemical distance) and the vulnerability of the networks.

Bound-Preserving Discontinuous Galerkin Methods for Conservative Phase Space Advection in Curvilinear Coordinates

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

Mezzacappa, Anthony; Endeve, Eirik; Hauck, Cory D.

We extend the positivity-preserving method of Zhang & Shu [49] to simulate the advection of neutral particles in phase space using curvilinear coordinates. The ability to utilize these coordinates is important for non-equilibrium transport problems in general relativity and also in science and engineering applications with specific geometries. The method achieves high-order accuracy using Discontinuous Galerkin (DG) discretization of phase space and strong stabilitypreserving, Runge-Kutta (SSP-RK) time integration. Special care in taken to ensure that the method preserves strict bounds for the phase space distribution function f; i.e., f ϵ [0, 1]. The combination of suitable CFL conditions and themore » use of the high-order limiter proposed in [49] is su cient to ensure positivity of the distribution function. However, to ensure that the distribution function satisfies the upper bound, the discretization must, in addition, preserve the divergencefree property of the phase space ow. Proofs that highlight the necessary conditions are presented for general curvilinear coordinates, and the details of these conditions are worked out for some commonly used coordinate systems (i.e., spherical polar spatial coordinates in spherical symmetry and cylindrical spatial coordinates in axial symmetry, both with spherical momentum coordinates). Results from numerical experiments - including one example in spherical symmetry adopting the Schwarzschild metric - demonstrate that the method achieves high-order accuracy and that the distribution function satisfies the maximum principle.« less

Modelling population distribution using remote sensing imagery and location-based data

NASA Astrophysics Data System (ADS)

Song, J.; Prishchepov, A. V.

2017-12-01

Detailed spatial distribution of population density is essential for city studies such as urban planning, environmental pollution and city emergency, even estimate pressure on the environment and human exposure and risks to health. However, most of the researches used census data as the detailed dynamic population distribution are difficult to acquire, especially in microscale research. This research describes a method using remote sensing imagery and location-based data to model population distribution at the function zone level. Firstly, urban functional zones within a city were mapped by high-resolution remote sensing images and POIs. The workflow of functional zones extraction includes five parts: (1) Urban land use classification. (2) Segmenting images in built-up area. (3) Identification of functional segments by POIs. (4) Identification of functional blocks by functional segmentation and weight coefficients. (5) Assessing accuracy by validation points. The result showed as Fig.1. Secondly, we applied ordinary least square and geographically weighted regression to assess spatial nonstationary relationship between light digital number (DN) and population density of sampling points. The two methods were employed to predict the population distribution over the research area. The R²of GWR model were in the order of 0.7 and typically showed significant variations over the region than traditional OLS model. The result showed as Fig.2.Validation with sampling points of population density demonstrated that the result predicted by the GWR model correlated well with light value. The result showed as Fig.3. Results showed: (1) Population density is not linear correlated with light brightness using global model. (2) VIIRS night-time light data could estimate population density integrating functional zones at city level. (3) GWR is a robust model to map population distribution, the adjusted R2 of corresponding GWR models were higher than the optimal OLS models, confirming that GWR models demonstrate better prediction accuracy. So this method provide detailed population density information for microscale citizen studies.

Spatially distributed effects of mental exhaustion on resting-state FMRI networks.

PubMed

Esposito, Fabrizio; Otto, Tobias; Zijlstra, Fred R H; Goebel, Rainer

2014-01-01

Brain activity during rest is spatially coherent over functional connectivity networks called resting-state networks. In resting-state functional magnetic resonance imaging, independent component analysis yields spatially distributed network representations reflecting distinct mental processes, such as intrinsic (default) or extrinsic (executive) attention, and sensory inhibition or excitation. These aspects can be related to different treatments or subjective experiences. Among these, exhaustion is a common psychological state induced by prolonged mental performance. Using repeated functional magnetic resonance imaging sessions and spatial independent component analysis, we explored the effect of several hours of sustained cognitive performances on the resting human brain. Resting-state functional magnetic resonance imaging was performed on the same healthy volunteers in two days, with and without, and before, during and after, an intensive psychological treatment (skill training and sustained practice with a flight simulator). After each scan, subjects rated their level of exhaustion and performed an N-back task to evaluate eventual decrease in cognitive performance. Spatial maps of selected resting-state network components were statistically evaluated across time points to detect possible changes induced by the sustained mental performance. The intensive treatment had a significant effect on exhaustion and effort ratings, but no effects on N-back performances. Significant changes in the most exhausted state were observed in the early visual processing and the anterior default mode networks (enhancement) and in the fronto-parietal executive networks (suppression), suggesting that mental exhaustion is associated with a more idling brain state and that internal attention processes are facilitated to the detriment of more extrinsic processes. The described application may inspire future indicators of the level of fatigue in the neural attention system.

Solar Wind Five

NASA Technical Reports Server (NTRS)

Neugebauer, M. (Editor)

1983-01-01

Topics of discussion were: solar corona, MHD waves and turbulence, acceleration of the solar wind, stellar coronae and winds, long term variations, energetic particles, plasma distribution functions and waves, spatial dependences, and minor ions.

NMR relaxation in natural soils: Fast Field Cycling and T1-T2 Determination by IR-MEMS

NASA Astrophysics Data System (ADS)

Haber-Pohlmeier, S.; Pohlmeier, A.; Stapf, S.; van Dusschoten, D.

2009-04-01

Soils are natural porous media of highest importance for food production and sustainment of water resources. For these functions, prominent properties are their ability of water retainment and transport, which are mainly controlled by pore size distribution. The latter is related to NMR relaxation times of water molecules, of which the longitudinal relaxation time can be determined non-invasively by fast-field cycling relaxometry (FFC) and both are obtainable by inversion recovery - multi-echo- imaging (IR-MEMS) methods. The advantage of the FFC method is the determination of the field dependent dispersion of the spin-lattice relaxation rate, whereas MRI at high field is capable of yielding spatially resolved T1 and T2 times. Here we present results of T1- relaxation time distributions of water in three natural soils, obtained by the analysis of FFC data by means of the inverse Laplace transformation (CONTIN)1. Kaldenkirchen soil shows relatively broad bimodal distribution functions D(T1) which shift to higher relaxation rates with increasing relaxation field. These data are compared to spatially resolved T1- and T2 distributions, obtained by IR-MEMS. The distribution of T1 corresponds well to that obtained by FFC.

The Angular Three-Point Correlation Function in the Quasi-linear Regime

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

Buchalter, Ari; Kamionkowski, Marc; Jaffe, Andrew H.

2000-02-10

We calculate the normalized angular three-point correlation function (3PCF), q, as well as the normalized angular skewness, s{sub 3}, assuming the small-angle approximation, for a biased mass distribution in flat and open cold dark matter (CDM) models with Gaussian initial conditions. The leading-order perturbative results incorporate the explicit dependence on the cosmological parameters, the shape of the CDM transfer function, the linear evolution of the power spectrum, the form of the assumed redshift distribution function, and linear and nonlinear biasing, which may be evolving. Results are presented for different redshift distributions, including that appropriate for the APM Galaxy Survey, asmore » well as for a survey with a mean redshift of z{approx_equal}1 (such as the VLA FIRST Survey). Qualitatively, many of the results found for s{sub 3} and q are similar to those obtained in a related treatment of the spatial skewness and 3PCF, such as a leading-order correction to the standard result for s{sub 3} in the case of nonlinear bias (as defined for unsmoothed density fields), and the sensitivity of the configuration dependence of q to both cosmological and biasing models. We show that since angular correlation functions (CFs) are sensitive to clustering over a range of redshifts, the various evolutionary dependences included in our predictions imply that measurements of q in a deep survey might better discriminate between models with different histories, such as evolving versus nonevolving bias, that can have similar spatial CFs at low redshift. Our calculations employ a derived equation, valid for open, closed, and flat models, to obtain the angular bispectrum from the spatial bispectrum in the small-angle approximation. (c) (c) 2000. The American Astronomical Society.« less

A Modified Kriging Method to Interpolate the Soil Moisture Measured by Wireless Sensor Network with the Aid of Remote Sensing Images

NASA Astrophysics Data System (ADS)

Zhang, J.; Liu, Q.; Li, X.; Niu, H.; Cai, E.

2015-12-01

In recent years, wireless sensor network (WSN) emerges to collect Earth observation data at relatively low cost and light labor load, while its observations are still point-data. To learn the spatial distribution of a land surface parameter, interpolating the point data is necessary. Taking soil moisture (SM) for example, its spatial distribution is critical information for agriculture management, hydrological and ecological researches. This study developed a method to interpolate the WSN-measured SM to acquire the spatial distribution in a 5km*5km study area, located in the middle reaches of HEIHE River, western China. As SM is related to many factors such as topology, soil type, vegetation and etc., even the WSN observation grid is not dense enough to reflect the SM distribution pattern. Our idea is to revise the traditional Kriging algorithm, introducing spectral variables, i.e., vegetation index (VI) and abledo, from satellite imagery as supplementary information to aid the interpolation. Thus, the new Extended-Kriging algorithm operates on the spatial & spectral combined space. To run the algorithm, first we need to estimate the SM variance function, which is also extended to the combined space. As the number of WSN samples in the study area is not enough to gather robust statistics, we have to assume that the SM variance function is invariant over time. So, the variance function is estimated from a SM map, derived from the airborne CASI/TASI images acquired in July 10, 2012, and then applied to interpolate WSN data in that season. Data analysis indicates that the new algorithm can provide more details to the variation of land SM. Then, the Leave-one-out cross-validation is adopted to estimate the interpolation accuracy. Although a reasonable accuracy can be achieved, the result is not yet satisfactory. Besides improving the algorithm, the uncertainties in WSN measurements may also need to be controlled in our further work.

Benthic Habitat-Based Framework for Ecological Production Functions: Case Study for Utilization by Estuarine Birds in a Northeast Pacific Estuary

EPA Science Inventory

Habitat-based frameworks have been proposed for developing Ecological Production Functions (EPFs) to describe the spatial distribution of ecosystem services. As proof of concept, we generated EPFs that compared bird use patterns among intertidal benthic habitats for Yaquina estu...

Canopies to Continents: What spatial scales are needed to represent landcover distributions in earth system models?

NASA Astrophysics Data System (ADS)

Guenther, A. B.; Duhl, T.

2011-12-01

Increasing computational resources have enabled a steady improvement in the spatial resolution used for earth system models. Land surface models and landcover distributions have kept ahead by providing higher spatial resolution than typically used in these models. Satellite observations have played a major role in providing high resolution landcover distributions over large regions or the entire earth surface but ground observations are needed to calibrate these data and provide accurate inputs for models. As our ability to resolve individual landscape components improves, it is important to consider what scale is sufficient for providing inputs to earth system models. The required spatial scale is dependent on the processes being represented and the scientific questions being addressed. This presentation will describe the development a contiguous U.S. landcover database using high resolution imagery (1 to 1000 meters) and surface observations of species composition and other landcover characteristics. The database includes plant functional types and species composition and is suitable for driving land surface models (CLM and MEGAN) that predict land surface exchange of carbon, water, energy and biogenic reactive gases (e.g., isoprene, sesquiterpenes, and NO). We investigate the sensitivity of model results to landcover distributions with spatial scales ranging over six orders of magnitude (1 meter to 1000000 meters). The implications for predictions of regional climate and air quality will be discussed along with recommendations for regional and global earth system modeling.

Essays on the Impacts of Geography and Institutions on Access to Energy and Public Infrastructure Services

NASA Astrophysics Data System (ADS)

Archibong, Belinda

While previous literature has emphasized the importance of energy and public infrastructure services for economic development, questions surrounding the implications of unequal spatial distribution in access to these resources remain, particularly in the developing country context. This dissertation provides evidence on the nature, origins and implications of this distribution uniting three strands of research from the development and political economy, regional science and energy economics fields. The dissertation unites three papers on the nature of spatial inequality of access to energy and infrastructure with further implications for conflict risk , the historical institutional and biogeographical determinants of current distribution of access to energy and public infrastructure services and the response of households to fuel price changes over time. Chapter 2 uses a novel survey dataset to provide evidence for spatial clustering of public infrastructure non-functionality at schools by geopolitical zone in Nigeria with further implications for armed conflict risk in the region. Chapter 3 investigates the drivers of the results in chapter 2, exploiting variation in the spatial distribution of precolonial institutions and geography in the region, to provide evidence for the long-term impacts of these factors on current heterogeneity of access to public services. Chapter 4 addresses the policy implications of energy access, providing the first multi-year evidence on firewood demand elasticities in India, using the spatial variation in prices for estimation.

[Downscaling research of spatial distribution of incidence of hand foot and mouth disease based on area-to-area Poisson Kriging method].

PubMed

Wang, J X; Hu, M G; Yu, S C; Xiao, G X

2017-09-10

Objective: To understand the spatial distribution of incidence of hand foot and mouth disease (HFMD) at scale of township and provide evidence for the better prevention and control of HFMD and allocation of medical resources. Methods: The incidence data of HFMD in 108 counties (district) in Shandong province in 2010 were collected. Downscaling interpolation was conducted by using area-to-area Poisson Kriging method. The interpolation results were visualized by using geographic information system (GIS). The county (district) incidence was interpolated into township incidence to get the distribution of spatial distribution of incidence of township. Results: In the downscaling interpolation, the range of the fitting semi-variance equation was 20.38 km. Within the range, the incidence had correlation with each other. The fitting function of scatter diagram of estimated and actual incidence of HFMD at country level was y =1.053 1 x , R (2)=0.99. The incidences at different scale were consistent. Conclusions: The incidence of HFMD had spatial autocorrelation within 20.38 km. When HFMD occurs in one place, it is necessary to strengthen the surveillance and allocation of medical resource in the surrounding area within 20.38 km. Area to area Poisson Kriging method based downscaling research can be used in spatial visualization of HFMD incidence.

Spatial mismatch analysis among hotspots of alien plant species, road and railway networks in Germany and Austria

PubMed Central

Morelli, Federico

2017-01-01

Road and railway networks are pervasive elements of all environments, which have expanded intensively over the last century in all European countries. These transportation infrastructures have major impacts on the surrounding landscape, representing a threat to biodiversity. Roadsides and railways may function as corridors for dispersal of alien species in fragmented landscapes. However, only few studies have explored the spread of invasive species in relationship to transport network at large spatial scales. We performed a spatial mismatch analysis, based on a spatially explicit correlation test, to investigate whether alien plant species hotspots in Germany and Austria correspond to areas of high density of roads and railways. We tested this independently of the effects of dominant environments in each spatial unit, in order to focus just on the correlation between occurrence of alien species and density of linear transportation infrastructures. We found a significant spatial association between alien plant species hotspots distribution and roads and railways density in both countries. As expected, anthropogenic landscapes, such as urban areas, harbored more alien plant species, followed by water bodies. However, our findings suggested that the distribution of neobiota is strongest correlated to road/railways density than to land use composition. This study provides new evidence, from a transnational scale, that alien plants can use roadsides and rail networks as colonization corridors. Furthermore, our approach contributes to the understanding on alien plant species distribution at large spatial scale by the combination with spatial modeling procedures. PMID:28829818

The effects of prey patchiness, predator aggregation, and mutual interference on the functional response of Phytoseiulus persimilis feeding on Tetranychus urticae (Acari: Phytoseiidae, Tetranychidae).

PubMed

Nachman, Gösta

2006-01-01

The spatial distributions of two-spotted spider mites Tetranychus urticae and their natural enemy, the phytoseiid predator Phytoseiulus persimilis, were studied on six full-grown cucumber plants. Both mite species were very patchily distributed and P. persimilis tended to aggregate on leaves with abundant prey. The effects of non-homogenous distributions and degree of spatial overlap between prey and predators on the per capita predation rate were studied by means of a stage-specific predation model that averages the predation rates over all the local populations inhabiting the individual leaves. The empirical predation rates were compared with predictions assuming random predator search and/or an even distribution of prey. The analysis clearly shows that the ability of the predators to search non-randomly increases their predation rate. On the other hand, the prey may gain if it adopts a more even distribution when its density is low and a more patchy distribution when density increases. Mutual interference between searching predators reduces the predation rate, but the effect is negligible. The stage-specific functional response model was compared with two simpler models without explicit stage structure. Both unstructured models yielded predictions that were quite similar to those of the stage-structured model.

Accounting for Non-Gaussian Sources of Spatial Correlation in Parametric Functional Magnetic Resonance Imaging Paradigms II: A Method to Obtain First-Level Analysis Residuals with Uniform and Gaussian Spatial Autocorrelation Function and Independent and Identically Distributed Time-Series.

PubMed

Gopinath, Kaundinya; Krishnamurthy, Venkatagiri; Lacey, Simon; Sathian, K

2018-02-01

In a recent study Eklund et al. have shown that cluster-wise family-wise error (FWE) rate-corrected inferences made in parametric statistical method-based functional magnetic resonance imaging (fMRI) studies over the past couple of decades may have been invalid, particularly for cluster defining thresholds less stringent than p < 0.001; principally because the spatial autocorrelation functions (sACFs) of fMRI data had been modeled incorrectly to follow a Gaussian form, whereas empirical data suggest otherwise. Hence, the residuals from general linear model (GLM)-based fMRI activation estimates in these studies may not have possessed a homogenously Gaussian sACF. Here we propose a method based on the assumption that heterogeneity and non-Gaussianity of the sACF of the first-level GLM analysis residuals, as well as temporal autocorrelations in the first-level voxel residual time-series, are caused by unmodeled MRI signal from neuronal and physiological processes as well as motion and other artifacts, which can be approximated by appropriate decompositions of the first-level residuals with principal component analysis (PCA), and removed. We show that application of this method yields GLM residuals with significantly reduced spatial correlation, nearly Gaussian sACF and uniform spatial smoothness across the brain, thereby allowing valid cluster-based FWE-corrected inferences based on assumption of Gaussian spatial noise. We further show that application of this method renders the voxel time-series of first-level GLM residuals independent, and identically distributed across time (which is a necessary condition for appropriate voxel-level GLM inference), without having to fit ad hoc stochastic colored noise models. Furthermore, the detection power of individual subject brain activation analysis is enhanced. This method will be especially useful for case studies, which rely on first-level GLM analysis inferences.

Using Common Spatial Distributions of Atoms to Relate Functionally Divergent Influenza Virus N10 and N11 Protein Structures to Functionally Characterized Neuraminidase Structures, Toxin Cell Entry Domains, and Non-Influenza Virus Cell Entry Domains

PubMed Central

Weininger, Arthur; Weininger, Susan

2015-01-01

The ability to identify the functional correlates of structural and sequence variation in proteins is a critical capability. We related structures of influenza A N10 and N11 proteins that have no established function to structures of proteins with known function by identifying spatially conserved atoms. We identified atoms with common distributed spatial occupancy in PDB structures of N10 protein, N11 protein, an influenza A neuraminidase, an influenza B neuraminidase, and a bacterial neuraminidase. By superposing these spatially conserved atoms, we aligned the structures and associated molecules. We report spatially and sequence invariant residues in the aligned structures. Spatially invariant residues in the N6 and influenza B neuraminidase active sites were found in previously unidentified spatially equivalent sites in the N10 and N11 proteins. We found the corresponding secondary and tertiary structures of the aligned proteins to be largely identical despite significant sequence divergence. We found structural precedent in known non-neuraminidase structures for residues exhibiting structural and sequence divergence in the aligned structures. In N10 protein, we identified staphylococcal enterotoxin I-like domains. In N11 protein, we identified hepatitis E E2S-like domains, SARS spike protein-like domains, and toxin components shared by alpha-bungarotoxin, staphylococcal enterotoxin I, anthrax lethal factor, clostridium botulinum neurotoxin, and clostridium tetanus toxin. The presence of active site components common to the N6, influenza B, and S. pneumoniae neuraminidases in the N10 and N11 proteins, combined with the absence of apparent neuraminidase function, suggests that the role of neuraminidases in H17N10 and H18N11 emerging influenza A viruses may have changed. The presentation of E2S-like, SARS spike protein-like, or toxin-like domains by the N10 and N11 proteins in these emerging viruses may indicate that H17N10 and H18N11 sialidase-facilitated cell entry has been supplemented or replaced by sialidase-independent receptor binding to an expanded cell population that may include neurons and T-cells. PMID:25706124

Improving Estimations of Spatial Distribution of Soil Respiration Using the Bayesian Maximum Entropy Algorithm and Soil Temperature as Auxiliary Data.

PubMed

Hu, Junguo; Zhou, Jian; Zhou, Guomo; Luo, Yiqi; Xu, Xiaojun; Li, Pingheng; Liang, Junyi

2016-01-01

Soil respiration inherently shows strong spatial variability. It is difficult to obtain an accurate characterization of soil respiration with an insufficient number of monitoring points. However, it is expensive and cumbersome to deploy many sensors. To solve this problem, we proposed employing the Bayesian Maximum Entropy (BME) algorithm, using soil temperature as auxiliary information, to study the spatial distribution of soil respiration. The BME algorithm used the soft data (auxiliary information) effectively to improve the estimation accuracy of the spatiotemporal distribution of soil respiration. Based on the functional relationship between soil temperature and soil respiration, the BME algorithm satisfactorily integrated soil temperature data into said spatial distribution. As a means of comparison, we also applied the Ordinary Kriging (OK) and Co-Kriging (Co-OK) methods. The results indicated that the root mean squared errors (RMSEs) and absolute values of bias for both Day 1 and Day 2 were the lowest for the BME method, thus demonstrating its higher estimation accuracy. Further, we compared the performance of the BME algorithm coupled with auxiliary information, namely soil temperature data, and the OK method without auxiliary information in the same study area for 9, 21, and 37 sampled points. The results showed that the RMSEs for the BME algorithm (0.972 and 1.193) were less than those for the OK method (1.146 and 1.539) when the number of sampled points was 9 and 37, respectively. This indicates that the former method using auxiliary information could reduce the required number of sampling points for studying spatial distribution of soil respiration. Thus, the BME algorithm, coupled with soil temperature data, can not only improve the accuracy of soil respiration spatial interpolation but can also reduce the number of sampling points.

Improving Estimations of Spatial Distribution of Soil Respiration Using the Bayesian Maximum Entropy Algorithm and Soil Temperature as Auxiliary Data

PubMed Central

Hu, Junguo; Zhou, Jian; Zhou, Guomo; Luo, Yiqi; Xu, Xiaojun; Li, Pingheng; Liang, Junyi

2016-01-01

Soil respiration inherently shows strong spatial variability. It is difficult to obtain an accurate characterization of soil respiration with an insufficient number of monitoring points. However, it is expensive and cumbersome to deploy many sensors. To solve this problem, we proposed employing the Bayesian Maximum Entropy (BME) algorithm, using soil temperature as auxiliary information, to study the spatial distribution of soil respiration. The BME algorithm used the soft data (auxiliary information) effectively to improve the estimation accuracy of the spatiotemporal distribution of soil respiration. Based on the functional relationship between soil temperature and soil respiration, the BME algorithm satisfactorily integrated soil temperature data into said spatial distribution. As a means of comparison, we also applied the Ordinary Kriging (OK) and Co-Kriging (Co-OK) methods. The results indicated that the root mean squared errors (RMSEs) and absolute values of bias for both Day 1 and Day 2 were the lowest for the BME method, thus demonstrating its higher estimation accuracy. Further, we compared the performance of the BME algorithm coupled with auxiliary information, namely soil temperature data, and the OK method without auxiliary information in the same study area for 9, 21, and 37 sampled points. The results showed that the RMSEs for the BME algorithm (0.972 and 1.193) were less than those for the OK method (1.146 and 1.539) when the number of sampled points was 9 and 37, respectively. This indicates that the former method using auxiliary information could reduce the required number of sampling points for studying spatial distribution of soil respiration. Thus, the BME algorithm, coupled with soil temperature data, can not only improve the accuracy of soil respiration spatial interpolation but can also reduce the number of sampling points. PMID:26807579

Processing and statistical analysis of soil-root images

NASA Astrophysics Data System (ADS)

Razavi, Bahar S.; Hoang, Duyen; Kuzyakov, Yakov

2016-04-01

Importance of the hotspots such as rhizosphere, the small soil volume that surrounds and is influenced by plant roots, calls for spatially explicit methods to visualize distribution of microbial activities in this active site (Kuzyakov and Blagodatskaya, 2015). Zymography technique has previously been adapted to visualize the spatial dynamics of enzyme activities in rhizosphere (Spohn and Kuzyakov, 2014). Following further developing of soil zymography -to obtain a higher resolution of enzyme activities - we aimed to 1) quantify the images, 2) determine whether the pattern (e.g. distribution of hotspots in space) is clumped (aggregated) or regular (dispersed). To this end, we incubated soil-filled rhizoboxes with maize Zea mays L. and without maize (control box) for two weeks. In situ soil zymography was applied to visualize enzymatic activity of β-glucosidase and phosphatase at soil-root interface. Spatial resolution of fluorescent images was improved by direct application of a substrate saturated membrane to the soil-root system. Furthermore, we applied "spatial point pattern analysis" to determine whether the pattern (e.g. distribution of hotspots in space) is clumped (aggregated) or regular (dispersed). Our results demonstrated that distribution of hotspots at rhizosphere is clumped (aggregated) compare to control box without plant which showed regular (dispersed) pattern. These patterns were similar in all three replicates and for both enzymes. We conclude that improved zymography is promising in situ technique to identify, analyze, visualize and quantify spatial distribution of enzyme activities in the rhizosphere. Moreover, such different patterns should be considered in assessments and modeling of rhizosphere extension and the corresponding effects on soil properties and functions. Key words: rhizosphere, spatial point pattern, enzyme activity, zymography, maize.

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.

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.

Action-angle formulation of generalized, orbit-based, fast-ion diagnostic weight functions

NASA Astrophysics Data System (ADS)

Stagner, L.; Heidbrink, W. W.

2017-09-01

Due to the usually complicated and anisotropic nature of the fast-ion distribution function, diagnostic velocity-space weight functions, which indicate the sensitivity of a diagnostic to different fast-ion velocities, are used to facilitate the analysis of experimental data. Additionally, when velocity-space weight functions are discretized, a linear equation relating the fast-ion density and the expected diagnostic signal is formed. In a technique known as velocity-space tomography, many measurements can be combined to create an ill-conditioned system of linear equations that can be solved using various computational methods. However, when velocity-space weight functions (which by definition ignore spatial dependencies) are used, velocity-space tomography is restricted, both by the accuracy of its forward model and also by the availability of spatially overlapping diagnostic measurements. In this work, we extend velocity-space weight functions to a full 6D generalized coordinate system and then show how to reduce them to a 3D orbit-space without loss of generality using an action-angle formulation. Furthermore, we show how diagnostic orbit-weight functions can be used to infer the full fast-ion distribution function, i.e., orbit tomography. In depth derivations of orbit weight functions for the neutron, neutral particle analyzer, and fast-ion D-α diagnostics are also shown.

The Influence of Sex and Season on Conspecific Spatial Overlap in a Large, Actively-Foraging Colubrid Snake

PubMed Central

Bauder, Javan M.; Breininger, David R.; Bolt, M. Rebecca; Legare, Michael L.; Jenkins, Christopher L.; Rothermel, Betsie B.; McGarigal, Kevin

2016-01-01

Understanding the factors influencing the degree of spatial overlap among conspecifics is important for understanding multiple ecological processes. Compared to terrestrial carnivores, relatively little is known about the factors influencing conspecific spatial overlap in snakes, although across snake taxa there appears to be substantial variation in conspecific spatial overlap. In this study, we described conspecific spatial overlap of eastern indigo snakes (Drymarchon couperi) in peninsular Florida and examined how conspecific spatial overlap varied by sex and season (breeding season vs. non-breeding season). We calculated multiple indices of spatial overlap using 6- and 3-month utilization distributions (UD) of dyads of simultaneously adjacent telemetered snakes. We also measured conspecific UD density values at each telemetry fix and modeled the distribution of those values as a function of overlap type, sex, and season using generalized Pareto distributions. Home range overlap between males and females was significantly greater than overlap between individuals of the same sex and male home ranges often completely contained female home ranges. Male home ranges overlapped little during both seasons, whereas females had higher levels of overlap during the non-breeding season. The spatial patterns observed in our study are consistent with those seen in many mammalian carnivores, in which low male-male overlap and high inter-sexual overlap provides males with greater access to females. We encourage additional research on the influence of prey availability on conspecific spatial overlap in snakes as well as the behavioral mechanisms responsible for maintaining the low levels of overlap we observed. PMID:27490346

Anticipatory control of xenon in a pressurized water reactor

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

Impink, A.J. Jr.

1987-02-10

A method is described for automatically dampening xenon-135 spatial transients in the core of a pressurized water reactor having control rods which regulate reactor power level, comprising the steps of: measuring the neutron flu in the reactor core at a plurality of axially spaced locations on a real-time, on-line basis; repetitively generating from the neutron flux measurements, on a point-by-point basis, signals representative of the current axial distribution of xenon-135, and signals representative of the current rate of change of the axial distribution of xenon-135; generating from the xenon-135 distribution signals and the rate of change of xenon distribution signals,more » control signals for reducing the xenon transients; and positioning the control rods as a function of the control signals to dampen the xenon-135 spatial transients.« less

Conditional sampling technique to test the applicability of the Taylor hypothesis for the large-scale coherent structures

NASA Technical Reports Server (NTRS)

Hussain, A. K. M. F.

1980-01-01

Comparisons of the distributions of large scale structures in turbulent flow with distributions based on time dependent signals from stationary probes and the Taylor hypothesis are presented. The study investigated an area in the near field of a 7.62 cm circular air jet at a Re of 32,000, specifically having coherent structures through small-amplitude controlled excitation and stable vortex pairing in the jet column mode. Hot-wire and X-wire anemometry were employed to establish phase averaged spatial distributions of longitudinal and lateral velocities, coherent Reynolds stress and vorticity, background turbulent intensities, streamlines and pseudo-stream functions. The Taylor hypothesis was used to calculate spatial distributions of the phase-averaged properties, with results indicating that the usage of the local time-average velocity or streamwise velocity produces large distortions.

A class of Fourier integrals based on the electric potential of an elongated dipole.

PubMed

Skianis, Georgios Aim

2014-01-01

In the present paper the closed expressions of a class of non tabulated Fourier integrals are derived. These integrals are associated with a group of functions at space domain, which represent the electric potential of a distribution of elongated dipoles which are perpendicular to a flat surface. It is shown that the Fourier integrals are produced by the Fourier transform of the Green's function of the potential of the dipole distribution, times a definite integral in which the distribution of the polarization is involved. Therefore the form of this distribution controls the expression of the Fourier integral. Introducing various dipole distributions, the respective Fourier integrals are derived. These integrals may be useful in the quantitative interpretation of electric potential anomalies produced by elongated dipole distributions, at spatial frequency domain.

Contrasting distribution patterns of invasive and naturalized non-native species along environmental gradients in a semi-arid montane ecosystem

Treesearch

Kelly M. Andersen; Bridgett J. Naylor; Bryan A. Endress; Catherine G. Parks

2015-01-01

Questions: Mountain systems have high abiotic heterogeneity over local spatial scales, offering natural experiments for examining plant species invasions. We ask whether functional groupings explain non-native species spread into native vegetation and up elevation gradients.We examine whether non-native species distribution patterns are related to environmental...

Integrating depth functions and hyper-scale terrain analysis for 3D soil organic carbon modeling in agricultural fields at regional scale

NASA Astrophysics Data System (ADS)

Ramirez-Lopez, L.; van Wesemael, B.; Stevens, A.; Doetterl, S.; Van Oost, K.; Behrens, T.; Schmidt, K.

2012-04-01

Soil Organic Carbon (SOC) represents a key component in the global C cycle and has an important influence on the global CO2 fluxes between terrestrial biosphere and atmosphere. In the context of agricultural landscapes, SOC inventories are important since soil management practices have a strong influence on CO2 fluxes and SOC stocks. However, there is lack of accurate and cost-effective methods for producing high spatial resolution of SOC information. In this respect, our work is focused on the development of a three dimensional modeling approach for SOC monitoring in agricultural fields. The study area comprises ~420 km2 and includes 4 of the 5 agro-geological regions of the Grand-Duchy of Luxembourg. The soil dataset consist of 172 profiles (1033 samples) which were not sampled specifically for this study. This dataset is a combination of profile samples collected in previous soil surveys and soil profiles sampled for other research purposes. The proposed strategy comprises two main steps. In the first step the SOC distribution within each profile (vertical distribution) is modeled. Depth functions for are fitted in order to summarize the information content in the profile. By using these functions the SOC can be interpolated at any depth within the profiles. The second step involves the use of contextual terrain (ConMap) features (Behrens et al., 2010). These features are based on the differences in elevation between a given point location in the landscape and its circular neighbourhoods at a given set of different radius. One of the main advantages of this approach is that it allows the integration of several spatial scales (eg. local and regional) for soil spatial analysis. In this work the ConMap features are derived from a digital elevation model of the area and are used as predictors for spatial modeling of the parameters of the depth functions fitted in the previous step. In this poster we present some preliminary results in which we analyze: i. The use of different depth functions, ii. The use of different machine learning approaches for modeling the parameters of the fitted depth functions using the ConMap features and iii. The influence of different spatial scales on the SOC profile distribution variability. Keywords: 3D modeling, Digital soil mapping, Depth functions, Terrain analysis. Reference Behrens, T., K. Schmidt, K., Zhu, A.X. Scholten, T. 2010. The ConMap approach for terrain-based digital soil mapping. European Journal of Soil Science, v. 61, p.133-143.

Spatial distribution of enzyme activities along the root and in the rhizosphere of different plants

NASA Astrophysics Data System (ADS)

Razavi, Bahar S.; Zarebanadkouki, Mohsen; Blagodatskaya, Evgenia; Kuzyakov, Yakov

2015-04-01

Extracellular enzymes are important for decomposition of many biological macromolecules abundant in soil such as cellulose, hemicelluloses and proteins. Activities of enzymes produced by both plant roots and microbes are the primary biological drivers of organic matter decomposition and nutrient cycling. So far acquisition of in situ data about local activity of different enzymes in soil has been challenged. That is why there is an urgent need in spatially explicit methods such as 2-D zymography to determine the variation of enzymes along the roots in different plants. Here, we developed further the zymography technique in order to quantitatively visualize the enzyme activities (Spohn and Kuzyakov, 2013), with a better spatial resolution We grew Maize (Zea mays L.) and Lentil (Lens culinaris) in rhizoboxes under optimum conditions for 21 days to study spatial distribution of enzyme activity in soil and along roots. We visualized the 2D distribution of the activity of three enzymes:β-glucosidase, leucine amino peptidase and phosphatase, using fluorogenically labelled substrates. Spatial resolution of fluorescent images was improved by direct application of a substrate saturated membrane to the soil-root system. The newly-developed direct zymography shows different pattern of spatial distribution of enzyme activity along roots and soil of different plants. We observed a uniform distribution of enzyme activities along the root system of Lentil. However, root system of Maize demonstrated inhomogeneity of enzyme activities. The apical part of an individual root (root tip) in maize showed the highest activity. The activity of all enzymes was the highest at vicinity of the roots and it decreased towards the bulk soil. Spatial patterns of enzyme activities as a function of distance from the root surface were enzyme specific, with highest extension for phosphatase. We conclude that improved zymography is promising in situ technique to analyze, visualize and quantify spatial distribution of enzyme activities in the rhizosphere hotspots. References Spohn, M., Kuzyakov, Y., 2013. Phosphorus mineralization can be driven by microbial need for carbon. Soil Biology & Biochemistry 61: 69-75

Comparison of the common spatial interpolation methods used to analyze potentially toxic elements surrounding mining regions.

PubMed

Ding, Qian; Wang, Yong; Zhuang, Dafang

2018-04-15

The appropriate spatial interpolation methods must be selected to analyze the spatial distributions of Potentially Toxic Elements (PTEs), which is a precondition for evaluating PTE pollution. The accuracy and effect of different spatial interpolation methods, which include inverse distance weighting interpolation (IDW) (power = 1, 2, 3), radial basis function interpolation (RBF) (basis function: thin-plate spline (TPS), spline with tension (ST), completely regularized spline (CRS), multiquadric (MQ) and inverse multiquadric (IMQ)) and ordinary kriging interpolation (OK) (semivariogram model: spherical, exponential, gaussian and linear), were compared using 166 unevenly distributed soil PTE samples (As, Pb, Cu and Zn) in the Suxian District, Chenzhou City, Hunan Province as the study subject. The reasons for the accuracy differences of the interpolation methods and the uncertainties of the interpolation results are discussed, then several suggestions for improving the interpolation accuracy are proposed, and the direction of pollution control is determined. The results of this study are as follows: (i) RBF-ST and OK (exponential) are the optimal interpolation methods for As and Cu, and the optimal interpolation method for Pb and Zn is RBF-IMQ. (ii) The interpolation uncertainty is positively correlated with the PTE concentration, and higher uncertainties are primarily distributed around mines, which is related to the strong spatial variability of PTE concentrations caused by human interference. (iii) The interpolation accuracy can be improved by increasing the sample size around the mines, introducing auxiliary variables in the case of incomplete sampling and adopting the partition prediction method. (iv) It is necessary to strengthen the prevention and control of As and Pb pollution, particularly in the central and northern areas. The results of this study can provide an effective reference for the optimization of interpolation methods and parameters for unevenly distributed soil PTE data in mining areas. Copyright © 2018 Elsevier Ltd. All rights reserved.

The role of biotic interactions in shaping distributions and realised assemblages of species: implications for species distribution modelling.

PubMed

Wisz, Mary Susanne; Pottier, Julien; Kissling, W Daniel; Pellissier, Loïc; Lenoir, Jonathan; Damgaard, Christian F; Dormann, Carsten F; Forchhammer, Mads C; Grytnes, John-Arvid; Guisan, Antoine; Heikkinen, Risto K; Høye, Toke T; Kühn, Ingolf; Luoto, Miska; Maiorano, Luigi; Nilsson, Marie-Charlotte; Normand, Signe; Öckinger, Erik; Schmidt, Niels M; Termansen, Mette; Timmermann, Allan; Wardle, David A; Aastrup, Peter; Svenning, Jens-Christian

2013-02-01

Predicting which species will occur together in the future, and where, remains one of the greatest challenges in ecology, and requires a sound understanding of how the abiotic and biotic environments interact with dispersal processes and history across scales. Biotic interactions and their dynamics influence species' relationships to climate, and this also has important implications for predicting future distributions of species. It is already well accepted that biotic interactions shape species' spatial distributions at local spatial extents, but the role of these interactions beyond local extents (e.g. 10 km(2) to global extents) are usually dismissed as unimportant. In this review we consolidate evidence for how biotic interactions shape species distributions beyond local extents and review methods for integrating biotic interactions into species distribution modelling tools. Drawing upon evidence from contemporary and palaeoecological studies of individual species ranges, functional groups, and species richness patterns, we show that biotic interactions have clearly left their mark on species distributions and realised assemblages of species across all spatial extents. We demonstrate this with examples from within and across trophic groups. A range of species distribution modelling tools is available to quantify species environmental relationships and predict species occurrence, such as: (i) integrating pairwise dependencies, (ii) using integrative predictors, and (iii) hybridising species distribution models (SDMs) with dynamic models. These methods have typically only been applied to interacting pairs of species at a single time, require a priori ecological knowledge about which species interact, and due to data paucity must assume that biotic interactions are constant in space and time. To better inform the future development of these models across spatial scales, we call for accelerated collection of spatially and temporally explicit species data. Ideally, these data should be sampled to reflect variation in the underlying environment across large spatial extents, and at fine spatial resolution. Simplified ecosystems where there are relatively few interacting species and sometimes a wealth of existing ecosystem monitoring data (e.g. arctic, alpine or island habitats) offer settings where the development of modelling tools that account for biotic interactions may be less difficult than elsewhere. © 2012 The Authors. Biological Reviews © 2012 Cambridge Philosophical Society.

Hydrological-niche models predict water plant functional group distributions in diverse wetland types.

PubMed

Deane, David C; Nicol, Jason M; Gehrig, Susan L; Harding, Claire; Aldridge, Kane T; Goodman, Abigail M; Brookes, Justin D

2017-06-01

Human use of water resources threatens environmental water supplies. If resource managers are to develop policies that avoid unacceptable ecological impacts, some means to predict ecosystem response to changes in water availability is necessary. This is difficult to achieve at spatial scales relevant for water resource management because of the high natural variability in ecosystem hydrology and ecology. Water plant functional groups classify species with similar hydrological niche preferences together, allowing a qualitative means to generalize community responses to changes in hydrology. We tested the potential for functional groups in making quantitative prediction of water plant functional group distributions across diverse wetland types over a large geographical extent. We sampled wetlands covering a broad range of hydrogeomorphic and salinity conditions in South Australia, collecting both hydrological and floristic data from 687 quadrats across 28 wetland hydrological gradients. We built hydrological-niche models for eight water plant functional groups using a range of candidate models combining different surface inundation metrics. We then tested the predictive performance of top-ranked individual and averaged models for each functional group. Cross validation showed that models achieved acceptable predictive performance, with correct classification rates in the range 0.68-0.95. Model predictions can be made at any spatial scale that hydrological data are available and could be implemented in a geographical information system. We show the response of water plant functional groups to inundation is consistent enough across diverse wetland types to quantify the probability of hydrological impacts over regional spatial scales. © 2017 by the Ecological Society of America.

Biodistribution and Efficacy of Targeted Pulmonary Delivery of a Protein Kinase C-δ Inhibitory Peptide: Impact on Indirect Lung Injury

PubMed Central

Mondrinos, Mark J.; Knight, Linda C.; Kennedy, Paul A.; Wu, Jichuan; Kauffman, Matthew; Baker, Sandy T.; Wolfson, Marla R.

2015-01-01

Sepsis and sepsis-induced lung injury remain a leading cause of death in intensive care units. We identified protein kinase C-δ (PKCδ) as a critical regulator of the acute inflammatory response and demonstrated that PKCδ inhibition was lung-protective in a rodent sepsis model, suggesting that targeting PKCδ is a potential strategy for preserving pulmonary function in the setting of indirect lung injury. In this study, whole-body organ biodistribution and pulmonary cellular distribution of a transactivator of transcription (TAT)–conjugated PKCδ inhibitory peptide (PKCδ-TAT) was determined following intratracheal (IT) delivery in control and septic [cecal ligation and puncture (CLP)] rats to ascertain the impact of disease pathology on biodistribution and efficacy. There was negligible lung uptake of radiolabeled peptide upon intravenous delivery [<1% initial dose (ID)], whereas IT administration resulted in lung retention of >65% ID with minimal uptake in liver or kidney (<2% ID). IT delivery of a fluorescent-tagged (tetramethylrhodamine-PKCδ-TAT) peptide demonstrated uniform spatial distribution and cellular uptake throughout the peripheral lung. IT delivery of PKCδ-TAT at the time of CLP surgery significantly reduced PKCδ activation (tyrosine phosphorylation, nuclear translocation and cleavage) and acute lung inflammation, resulting in improved lung function and gas exchange. Importantly, peptide efficacy was similar when delivered at 4 hours post-CLP, demonstrating therapeutic relevance. Conversely, spatial lung distribution and efficacy were significantly impaired at 8 hours post-CLP, which corresponded to marked histopathological progression of lung injury. These studies establish a functional connection between peptide spatial distribution, inflammatory histopathology in the lung, and efficacy of this anti-inflammatory peptide. PMID:26243739

Species richness effects on ecosystem multifunctionality depend on evenness, composition and spatial pattern

USGS Publications Warehouse

Maestre, F.T.; Castillo-Monroy, A. P.; Bowker, M.A.; Ochoa-Hueso, R.

2012-01-01

1. Recent studies have suggested that the simultaneous maintenance of multiple ecosystem functions (multifunctionality) is positively supported by species richness. However, little is known regarding the relative importance of other community attributes (e.g. spatial pattern, species evenness) as drivers of multifunctionality. 2. We conducted two microcosm experiments using model biological soil crust communities dominated by lichens to: (i) evaluate the joint effects and relative importance of changes in species composition, spatial pattern (clumped and random distribution of lichens), evenness (maximal and low evenness) and richness (from two to eight species) on soil functions related to nutrient cycling (β-glucosidase, urease and acid phosphatase enzymes, in situ N availability, total N, organic C, and N fixation), and (ii) assess how these community attributes affect multifunctionality. 3. Species richness, composition and spatial pattern affected multiple ecosystem functions (e.g. organic C, total N, N availability, β-glucosidase activity), albeit the magnitude and direction of their effects varied with the particular function, experiment and soil depth considered. Changes in species composition had effects on organic C, total N and the activity of β-glucosidase. Significant species richness × evenness and spatial pattern × evenness interactions were found when analysing functions such as organic C, total N and the activity of phosphatase. 4. The probability of sustaining multiple ecosystem functions increased with species richness, but this effect was largely modulated by attributes such as species evenness, composition and spatial pattern. Overall, we found that model communities with high species richness, random spatial pattern and low evenness increased multifunctionality. 5. Synthesis. Our results illustrate how different community attributes have a diverse impact on ecosystem functions related to nutrient cycling, and provide new experimental evidence illustrating the importance of the spatial pattern of organisms on ecosystem functioning. They also indicate that species richness is not the only biotic driver of multifunctionality, and that particular combinations of community attributes may be required to maximize it.

Spatially Resolved Measurement of the Stress Tensor in Thin Membranes Using Bending Waves

NASA Astrophysics Data System (ADS)

Waitz, Reimar; Lutz, Carolin; Nößner, Stephan; Hertkorn, Michael; Scheer, Elke

2015-04-01

The mode shape of bending waves in thin silicon and silicon-carbide membranes is measured as a function of space and time, using a phase-shift interferometer with stroboscopic light. The mode shapes hold information about all the relevant mechanical parameters of the samples, including the spatial distribution of static prestress. We present a simple algorithm to obtain a map of the lateral tensor components of the prestress, with a spatial resolution much better than the wavelength of the bending waves. The method is not limited to measuring the stress of bending waves. It is applicable in almost any situation, where the fields determining the state of the system can be measured as a function of space and time.

A novel approach for introducing cloud spatial structure into cloud radiative transfer parameterizations

NASA Astrophysics Data System (ADS)

Huang, Dong; Liu, Yangang

2014-12-01

Subgrid-scale variability is one of the main reasons why parameterizations are needed in large-scale models. Although some parameterizations started to address the issue of subgrid variability by introducing a subgrid probability distribution function for relevant quantities, the spatial structure has been typically ignored and thus the subgrid-scale interactions cannot be accounted for physically. Here we present a new statistical-physics-like approach whereby the spatial autocorrelation function can be used to physically capture the net effects of subgrid cloud interaction with radiation. The new approach is able to faithfully reproduce the Monte Carlo 3D simulation results with several orders less computational cost, allowing for more realistic representation of cloud radiation interactions in large-scale models.

Spatial distribution of intermingling pools of projection neurons with distinct targets: A 3D analysis of the commissural ganglia in Cancer borealis.

PubMed

Follmann, Rosangela; Goldsmith, Christopher John; Stein, Wolfgang

2017-06-01

Projection neurons play a key role in carrying long-distance information between spatially distant areas of the nervous system and in controlling motor circuits. Little is known about how projection neurons with distinct anatomical targets are organized, and few studies have addressed their spatial organization at the level of individual cells. In the paired commissural ganglia (CoGs) of the stomatogastric nervous system of the crab Cancer borealis, projection neurons convey sensory, motor, and modulatory information to several distinct anatomical regions. While the functions of descending projection neurons (dPNs) which control downstream motor circuits in the stomatogastric ganglion are well characterized, their anatomical distribution as well as that of neurons projecting to the labrum, brain, and thoracic ganglion have received less attention. Using cell membrane staining, we investigated the spatial distribution of CoG projection neurons in relation to all CoG neurons. Retrograde tracing revealed that somata associated with different axonal projection pathways were not completely spatially segregated, but had distinct preferences within the ganglion. Identified dPNs had diameters larger than 70% of CoG somata and were restricted to the most medial and anterior 25% of the ganglion. They were contained within a cluster of motor neurons projecting through the same nerve to innervate the labrum, indicating that soma position was independent of function and target area. Rather, our findings suggest that CoG neurons projecting to a variety of locations follow a generalized rule: for all nerve pathway origins, the soma cluster centroids in closest proximity are those whose axons project down that pathway. © 2017 Wiley Periodicals, Inc.

Spatial arrangement and size distribution of normal faults, Buckskin detachment upper plate, Western Arizona

NASA Astrophysics Data System (ADS)

Laubach, S. E.; Hundley, T. H.; Hooker, J. N.; Marrett, R. A.

2018-03-01

Fault arrays typically include a wide range of fault sizes and those faults may be randomly located, clustered together, or regularly or periodically located in a rock volume. Here, we investigate size distribution and spatial arrangement of normal faults using rigorous size-scaling methods and normalized correlation count (NCC). Outcrop data from Miocene sedimentary rocks in the immediate upper plate of the regional Buckskin detachment-low angle normal-fault, have differing patterns of spatial arrangement as a function of displacement (offset). Using lower size-thresholds of 1, 0.1, 0.01, and 0.001 m, displacements range over 5 orders of magnitude and have power-law frequency distributions spanning ∼ four orders of magnitude from less than 0.001 m to more than 100 m, with exponents of -0.6 and -0.9. The largest faults with >1 m displacement have a shallower size-distribution slope and regular spacing of about 20 m. In contrast, smaller faults have steep size-distribution slopes and irregular spacing, with NCC plateau patterns indicating imposed clustering. Cluster widths are 15 m for the 0.1-m threshold, 14 m for 0.01-m, and 1 m for 0.001-m displacement threshold faults. Results demonstrate normalized correlation count effectively characterizes the spatial arrangement patterns of these faults. Our example from a high-strain fault pattern above a detachment is compatible with size and spatial organization that was influenced primarily by boundary conditions such as fault shape, mechanical unit thickness and internal stratigraphy on a range of scales rather than purely by interaction among faults during their propagation.

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

PubMed

Ni, Jianhua; Qian, Tianlu; Xi, Changbai; Rui, Yikang; Wang, Jiechen

2016-08-18

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

Spatial patterns of a tropical tree species growing under an eucalyptus plantation in South-East Brazil.

PubMed

Higuchi, P; Silva, A C; Louzada, J N C; Machado, E L M

2010-05-01

The objectives of this study were to evaluate the influence of propagules source and the implication of tree size class on the spatial pattern of Xylopia brasiliensis Spreng. individuals growing under the canopy of an experimental plantation of eucalyptus. To this end, all individuals of Xylopia brasiliensis with diameter at soil height (dsh) > 1 cm were mapped in the understory of a 3.16 ha Eucalyptus spp. and Corymbia spp. plantation, located in the municipality of Lavras, SE Brazil. The largest nearby mature tree of X. brasiliensis was considered as the propagules source. Linear regressions were used to assess the influence of the distance of propagules source on the population parameters (density, basal area and height). The spatial pattern of trees was assessed through the Ripley K function. The overall pattern showed that the propagules source distance had strong influence over spatial distribution of trees, mainly the small ones, indicating that the closer the distance from the propagules source, the higher the tree density and the lower the mean tree height. The population showed different spatial distribution patterns according to the spatial scale and diameter class considered. While small trees tended to be aggregated up to around 80 m, the largest individuals were randomly distributed in the area. A plausible explanation for observed patterns might be limited seed rain and intra-population competition.

A hierarchical model for estimating the spatial distribution and abundance of animals detected by continuous-time recorders

USGS Publications Warehouse

Dorazio, Robert; Karanth, K. Ullas

2017-01-01

MotivationSeveral spatial capture-recapture (SCR) models have been developed to estimate animal abundance by analyzing the detections of individuals in a spatial array of traps. Most of these models do not use the actual dates and times of detection, even though this information is readily available when using continuous-time recorders, such as microphones or motion-activated cameras. Instead most SCR models either partition the period of trap operation into a set of subjectively chosen discrete intervals and ignore multiple detections of the same individual within each interval, or they simply use the frequency of detections during the period of trap operation and ignore the observed times of detection. Both practices make inefficient use of potentially important information in the data.Model and data analysisWe developed a hierarchical SCR model to estimate the spatial distribution and abundance of animals detected with continuous-time recorders. Our model includes two kinds of point processes: a spatial process to specify the distribution of latent activity centers of individuals within the region of sampling and a temporal process to specify temporal patterns in the detections of individuals. We illustrated this SCR model by analyzing spatial and temporal patterns evident in the camera-trap detections of tigers living in and around the Nagarahole Tiger Reserve in India. We also conducted a simulation study to examine the performance of our model when analyzing data sets of greater complexity than the tiger data.BenefitsOur approach provides three important benefits: First, it exploits all of the information in SCR data obtained using continuous-time recorders. Second, it is sufficiently versatile to allow the effects of both space use and behavior of animals to be specified as functions of covariates that vary over space and time. Third, it allows both the spatial distribution and abundance of individuals to be estimated, effectively providing a species distribution model, even in cases where spatial covariates of abundance are unknown or unavailable. We illustrated these benefits in the analysis of our data, which allowed us to quantify differences between nocturnal and diurnal activities of tigers and to estimate their spatial distribution and abundance across the study area. Our continuous-time SCR model allows an analyst to specify many of the ecological processes thought to be involved in the distribution, movement, and behavior of animals detected in a spatial trapping array of continuous-time recorders. We plan to extend this model to estimate the population dynamics of animals detected during multiple years of SCR surveys.

Evaluation of Denoising Strategies to Address Motion-Correlated Artifacts in Resting-State Functional Magnetic Resonance Imaging Data from the Human Connectome Project

PubMed Central

Kandala, Sridhar; Nolan, Dan; Laumann, Timothy O.; Power, Jonathan D.; Adeyemo, Babatunde; Harms, Michael P.; Petersen, Steven E.; Barch, Deanna M.

2016-01-01

Abstract Like all resting-state functional connectivity data, the data from the Human Connectome Project (HCP) are adversely affected by structured noise artifacts arising from head motion and physiological processes. Functional connectivity estimates (Pearson's correlation coefficients) were inflated for high-motion time points and for high-motion participants. This inflation occurred across the brain, suggesting the presence of globally distributed artifacts. The degree of inflation was further increased for connections between nearby regions compared with distant regions, suggesting the presence of distance-dependent spatially specific artifacts. We evaluated several denoising methods: censoring high-motion time points, motion regression, the FMRIB independent component analysis-based X-noiseifier (FIX), and mean grayordinate time series regression (MGTR; as a proxy for global signal regression). The results suggest that FIX denoising reduced both types of artifacts, but left substantial global artifacts behind. MGTR significantly reduced global artifacts, but left substantial spatially specific artifacts behind. Censoring high-motion time points resulted in a small reduction of distance-dependent and global artifacts, eliminating neither type. All denoising strategies left differences between high- and low-motion participants, but only MGTR substantially reduced those differences. Ultimately, functional connectivity estimates from HCP data showed spatially specific and globally distributed artifacts, and the most effective approach to address both types of motion-correlated artifacts was a combination of FIX and MGTR. PMID:27571276

Development of a distributed air pollutant dry deposition modeling framework.

PubMed

Hirabayashi, Satoshi; Kroll, Charles N; Nowak, David J

2012-12-01

A distributed air pollutant dry deposition modeling system was developed with a geographic information system (GIS) to enhance the functionality of i-Tree Eco (i-Tree, 2011). With the developed system, temperature, leaf area index (LAI) and air pollutant concentration in a spatially distributed form can be estimated, and based on these and other input variables, dry deposition of carbon monoxide (CO), nitrogen dioxide (NO(2)), sulfur dioxide (SO(2)), and particulate matter less than 10 microns (PM10) to trees can be spatially quantified. Employing nationally available road network, traffic volume, air pollutant emission/measurement and meteorological data, the developed system provides a framework for the U.S. city managers to identify spatial patterns of urban forest and locate potential areas for future urban forest planting and protection to improve air quality. To exhibit the usability of the framework, a case study was performed for July and August of 2005 in Baltimore, MD. Copyright © 2012 Elsevier Ltd. All rights reserved.

Forecasting the impact of transport improvements on commuting and residential choice

NASA Astrophysics Data System (ADS)

Elhorst, J. Paul; Oosterhaven, Jan

2006-03-01

This paper develops a probabilistic, competing-destinations, assignment model that predicts changes in the spatial pattern of the working population as a result of transport improvements. The choice of residence is explained by a new non-parametric model, which represents an alternative to the popular multinominal logit model. Travel times between zones are approximated by a normal distribution function with different mean and variance for each pair of zones, whereas previous models only use average travel times. The model’s forecast error of the spatial distribution of the Dutch working population is 7% when tested on 1998 base-year data. To incorporate endogenous changes in its causal variables, an almost ideal demand system is estimated to explain the choice of transport mode, and a new economic geography inter-industry model (RAEM) is estimated to explain the spatial distribution of employment. In the application, the model is used to forecast the impact of six mutually exclusive Dutch core-periphery railway proposals in the projection year 2020.

Study of diffusion and local structure of sodium-silicate liquid: the molecular dynamic simulation

NASA Astrophysics Data System (ADS)

Hung, Pham Khac; Noritake, Fumiya; San, Luyen Thi; Van, To Ba; Vinh, Le The

2017-10-01

A systematic analysis on sodium-silicate melt with various silica contents was carried out. The simulation revealed two diffusion mechanisms occurred in the melt: the bond-breaking and hopping between sites. The local structure was analyzed through T-simplexes. It was revealed that T-clusters have a non-spherical shape and represent the diffusion channel, in which Na atoms are dominant, but no any O atoms are located. The SiO2-poor melt acquires a long channel. In contrast, the SiO2-rich melt consists of unconnected short channels. The simulation also revealed the immobile and mobile regions which differ in local structure and constituent composition. We propose a new CL-function to characterizing the spatial distribution of different atom component. The spatial distribution of mobile and immobile atoms is found quite different. In particular, the immobile atoms are concentrated in high-density regions possessing very large density of immobile atoms. The spatial distribution of mobile atoms in contrast is more homogeneous.

Spatial Patterns in Herbivory on a Coral Reef Are Influenced by Structural Complexity but Not by Algal Traits

PubMed Central

Vergés, Adriana; Vanderklift, Mathew A.; Doropoulos, Christopher; Hyndes, Glenn A.

2011-01-01

Background Patterns of herbivory can alter the spatial structure of ecosystems, with important consequences for ecosystem functions and biodiversity. While the factors that drive spatial patterns in herbivory in terrestrial systems are well established, comparatively less is known about what influences the distribution of herbivory in coral reefs. Methodology and Principal Findings We quantified spatial patterns of macroalgal consumption in a cross-section of Ningaloo Reef (Western Australia). We used a combination of descriptive and experimental approaches to assess the influence of multiple macroalgal traits and structural complexity in establishing the observed spatial patterns in macroalgal herbivory, and to identify potential feedback mechanisms between herbivory and macroalgal nutritional quality. Spatial patterns in macroalgal consumption were best explained by differences in structural complexity among habitats. The biomass of herbivorous fish, and rates of herbivory were always greater in the structurally-complex coral-dominated outer reef and reef flat habitats, which were also characterised by high biomass of herbivorous fish, low cover and biomass of macroalgae and the presence of unpalatable algae species. Macroalgal consumption decreased to undetectable levels within 75 m of structurally-complex reef habitat, and algae were most abundant in the structurally-simple lagoon habitats, which were also characterised by the presence of the most palatable algae species. In contrast to terrestrial ecosystems, herbivory patterns were not influenced by the distribution, productivity or nutritional quality of resources (macroalgae), and we found no evidence of a positive feedback between macroalgal consumption and the nitrogen content of algae. Significance This study highlights the importance of seascape-scale patterns in structural complexity in determining spatial patterns of macroalgal consumption by fish. Given the importance of herbivory in maintaining the ability of coral reefs to reorganise and retain ecosystem functions following disturbance, structural complexity emerges as a critical feature that is essential for the healthy functioning of these ecosystems. PMID:21347254

Endogenous spatial attention: evidence for intact functioning in adults with autism

PubMed Central

Grubb, Michael A.; Behrmann, Marlene; Egan, Ryan; Minshew, Nancy J.; Carrasco, Marisa; Heeger, David J.

2012-01-01

Lay Abstract Attention allows us to selectively process the vast amount of information with which we are confronted. Focusing on a certain location of the visual scene (visual spatial attention) enables the prioritization of some aspects of information while ignoring others. Rapid manipulation of the attention field (i.e., the location and spread of visual spatial attention) is a critical aspect of human cognition, and previous research on spatial attention in individuals with autism spectrum disorders (ASD) has produced inconsistent results. In a series of three experiments, we evaluated claims in the literature that individuals with ASD exhibit a deficit in voluntarily controlling the deployment and size of the spatial attention field. We measured how well participants perform a visual discrimination task (accuracy) and how quickly they do so (reaction time), with and without spatial uncertainty (i.e., the lack of predictability concerning the spatial position of the upcoming stimulus). We found that high–functioning adults with autism exhibited slower reactions times overall with spatial uncertainty, but the effects of attention on performance accuracies and reaction times were indistinguishable between individuals with autism and typically developing individuals, in all three experiments. These results provide evidence of intact endogenous spatial attention function in high–functioning adults with ASD, suggesting that atypical endogenous spatial attention cannot be a latent characteristic of autism in general. Scientific Abstract Rapid manipulation of the attention field (i.e., the location and spread of visual spatial attention) is a critical aspect of human cognition, and previous research on spatial attention in individuals with autism spectrum disorders (ASD) has produced inconsistent results. In a series of three psychophysical experiments, we evaluated claims in the literature that individuals with ASD exhibit a deficit in voluntarily controlling the deployment and size of the spatial attention field. We measured the spatial distribution of performance accuracies and reaction times to quantify the sizes and locations of the attention field, with and without spatial uncertainty (i.e., the lack of predictability concerning the spatial position of the upcoming stimulus). We found that high–functioning adults with autism exhibited slower reactions times overall with spatial uncertainty, but the effects of attention on performance accuracies and reaction times were indistinguishable between individuals with autism and typically developing individuals, in all three experiments. These results provide evidence of intact endogenous spatial attention function in high–functioning adults with ASD, suggesting that atypical endogenous attention cannot be a latent characteristic of autism in general. PMID:23427075

Estimating spatially distributed soil texture using time series of thermal remote sensing - a case study in central Europe

NASA Astrophysics Data System (ADS)

Müller, Benjamin; Bernhardt, Matthias; Jackisch, Conrad; Schulz, Karsten

2016-09-01

For understanding water and solute transport processes, knowledge about the respective hydraulic properties is necessary. Commonly, hydraulic parameters are estimated via pedo-transfer functions using soil texture data to avoid cost-intensive measurements of hydraulic parameters in the laboratory. Therefore, current soil texture information is only available at a coarse spatial resolution of 250 to 1000 m. Here, a method is presented to derive high-resolution (15 m) spatial topsoil texture patterns for the meso-scale Attert catchment (Luxembourg, 288 km2) from 28 images of ASTER (advanced spaceborne thermal emission and reflection radiometer) thermal remote sensing. A principle component analysis of the images reveals the most dominant thermal patterns (principle components, PCs) that are related to 212 fractional soil texture samples. Within a multiple linear regression framework, distributed soil texture information is estimated and related uncertainties are assessed. An overall root mean squared error (RMSE) of 12.7 percentage points (pp) lies well within and even below the range of recent studies on soil texture estimation, while requiring sparser sample setups and a less diverse set of basic spatial input. This approach will improve the generation of spatially distributed topsoil maps, particularly for hydrologic modeling purposes, and will expand the usage of thermal remote sensing products.

Bridging Numerical and Analytical Models of Transient Travel Time Distributions: Challenges and Opportunities

NASA Astrophysics Data System (ADS)

Danesh Yazdi, M.; Klaus, J.; Condon, L. E.; Maxwell, R. M.

2017-12-01

Recent advancements in analytical solutions to quantify water and solute time-variant travel time distributions (TTDs) and the related StorAge Selection (SAS) functions synthesize catchment complexity into a simplified, lumped representation. While these analytical approaches are easy and efficient in application, they require high frequency hydrochemical data for parameter estimation. Alternatively, integrated hydrologic models coupled to Lagrangian particle-tracking approaches can directly simulate age under different catchment geometries and complexity at a greater computational expense. Here, we compare and contrast the two approaches by exploring the influence of the spatial distribution of subsurface heterogeneity, interactions between distinct flow domains, diversity of flow pathways, and recharge rate on the shape of TTDs and the relating SAS functions. To this end, we use a parallel three-dimensional variably saturated groundwater model, ParFlow, to solve for the velocity fields in the subsurface. A particle-tracking model, SLIM, is then implemented to determine the age distributions at every real time and domain location, facilitating a direct characterization of the SAS functions as opposed to analytical approaches requiring calibration of such functions. Steady-state results reveal that the assumption of random age sampling scheme might only hold in the saturated region of homogeneous catchments resulting in an exponential TTD. This assumption is however violated when the vadose zone is included as the underlying SAS function gives a higher preference to older ages. The dynamical variability of the true SAS functions is also shown to be largely masked by the smooth analytical SAS functions. As the variability of subsurface spatial heterogeneity increases, the shape of TTD approaches a power-law distribution function, including a broader distribution of shorter and longer travel times. We further found that larger (smaller) magnitude of effective precipitation shifts the scale of TTD towards younger (older) travel times, while the shape of the TTD remains untouched. This work constitutes a first step in linking a numerical transport model and analytical solutions of TTD to study their assumptions and limitations, providing physical inferences for empirical parameters.

An analytical method for assessing the spatial and temporal variation of juvenile Atlantic salmon habitat in an upland Scottish river.

NASA Astrophysics Data System (ADS)

Buddendorf, B.; Fabris, L.; Malcolm, I.; Lazzaro, G.; Tetzlaff, D.; Botter, G.; Soulsby, C.

2016-12-01

Wild Atlantic salmon populations in Scottish rivers constitute an important economic and recreational resource, as well as being a key component of biodiversity. Salmon have specific habitat requirements at different life stages and their distribution is therefore strongly influenced by a complex suite of biological and physical controls. Stream hydrodynamics have a strong influence on habitat quality and affect the distribution and density of juvenile salmon. As stream hydrodynamics directly relate to stream flow variability and channel morphology, the effects of hydroclimatic drivers on the spatial and temporal variability of habitat suitability can be assessed. Critical Displacement Velocity (CDV), which describes the velocity at which fish can no longer hold station, is one potential approach for characterising habitat suitability. CDV is obtained using an empirical formula that depends on fish size and stream temperature. By characterising the proportion of a reach below CDV it is possible to assess the suitable area. We demonstrate that a generic analytical approach based on field survey and hydraulic modelling can provide insights on the interactions between flow regime and average suitable area (SA) for juvenile salmon that could be extended to other aquatic species. Analytical functions are used to model the pdf of stream flow p(q) and the relationship between flow and suitable area SA(q). Theoretically these functions can assume any form. Here we used a gamma distribution to model p(q) and a gamma function to model SA(q). Integrating the product of these functions we obtain an analytical expression of SA. Since parameters of p(q) can be estimated from meteorological and flow measurements, they can be used directly to predict the effect of flow regime on SA. We show the utility of the approach with reference to 6 electrofishing sites in a single river system where long term (50 years) data on spatially distributed juvenile salmon densities are available.

Investigating distribution pattern of species in a warm-temperate conifer-broadleaved-mixed forest in China for sustainably utilizing forest and soils.

PubMed

Song, Houjuan; Xu, Yudan; Hao, Jing; Zhao, Bingqing; Guo, Donggang; Shao, Hongbo

2017-02-01

The maintaining mechanisms and potential ecological processes of species diversity in warm temperate- conifer-broadleaved-mixed forest are far from clear understanding. In this paper, the relative neighborhood density Ω was used to analyze the spatial distribution patterns of 34 species with ≥11 individuals in a warm- temperate-conifer-broadleaved-mixed forest, northern China. Then we used canonical correspondence analysis (CCA) and Torus-translation test (TTT) to explain the distribution of observed species. Our results show that aggregated distribution is the dominant pattern in warm-temperate natural forest and four species regular distribution at the spatial scale >30m. The aggregated percentage and intensity decline with spatial scale, abundance and size classes increasing. Rare species are aggregated more than intermediate and abundant species. These results prove sufficiently the effects existence of scale separation, self-thinning and Janzen-Connell hypothesis. In addition, functional traits (dispersal modes and shade tolerance) also have a significant influence on distribution of species. The results of CCA confirm that slope and convexity are the most important factors affecting the distribution of tree species distribution, elevation and slope of shrub species though the combination of topographic variables only explained 1% of distribution of tree species and 2% of shrub species. Most species don't have habitat preference; however 47.1% (16/34) species including absolutely dominant tree (Pinus tabulaeformis and Quercus wutaishanica) and shrub species (Rosa xanthina) and most other species with important value in the front, are strongly positively or negatively associated with at least one habitat. The valley and ridge are most distinct habitat with association of 12 species in the plot. However, high elevation slope with 257 quadrats is the most extensive habitat with only four species. Therefore, there is obvious evidence that habitat heterogeneity play an important role on shaping spatial distribution of species in warm temperate forest. Our research results provide significant evidence that dispersal limitation and habitat heterogeneity have a contribution jointly to regulating the spatial distribution pattern of species in warm-temperate-forest in China. Copyright © 2016 Elsevier B.V. All rights reserved.

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

PubMed

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

2014-02-01

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

Two stochastic models useful in petroleum exploration

NASA Technical Reports Server (NTRS)

Kaufman, G. M.; Bradley, P. G.

1972-01-01

A model of the petroleum exploration process that tests empirically the hypothesis that at an early stage in the exploration of a basin, the process behaves like sampling without replacement is proposed along with a model of the spatial distribution of petroleum reserviors that conforms to observed facts. In developing the model of discovery, the following topics are discussed: probabilitistic proportionality, likelihood function, and maximum likelihood estimation. In addition, the spatial model is described, which is defined as a stochastic process generating values of a sequence or random variables in a way that simulates the frequency distribution of areal extent, the geographic location, and shape of oil deposits

Abnormal functional specialization within medial prefrontal cortex in high-functioning autism: a multi-voxel similarity analysis

PubMed Central

Meuwese, Julia D.I.; Towgood, Karren J.; Frith, Christopher D.; Burgess, Paul W.

2009-01-01

Multi-voxel pattern analyses have proved successful in ‘decoding’ mental states from fMRI data, but have not been used to examine brain differences associated with atypical populations. We investigated a group of 16 (14 males) high-functioning participants with autism spectrum disorder (ASD) and 16 non-autistic control participants (12 males) performing two tasks (spatial/verbal) previously shown to activate medial rostral prefrontal cortex (mrPFC). Each task manipulated: (i) attention towards perceptual versus self-generated information and (ii) reflection on another person's mental state (‘mentalizing'versus ‘non-mentalizing’) in a 2 × 2 design. Behavioral performance and group-level fMRI results were similar between groups. However, multi-voxel similarity analyses revealed strong differences. In control participants, the spatial distribution of activity generalized significantly between task contexts (spatial/verbal) when examining the same function (attention/mentalizing) but not when comparing different functions. This pattern was disrupted in the ASD group, indicating abnormal functional specialization within mrPFC, and demonstrating the applicability of multi-voxel pattern analysis to investigations of atypical populations. PMID:19174370

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

NASA Astrophysics Data System (ADS)

Massoudieh, A.; Dentz, M.; Le Borgne, T.

2017-12-01

In heterogeneous media, the velocity distribution and the spatial correlation structure of velocity for solute particles determine the breakthrough curves and how they evolve as one moves away from the solute source. The ability to predict such evolution can help relating the spatio-statistical hydraulic properties of the media to the transport behavior and travel time distributions. While commonly used non-local transport models such as anomalous dispersion and classical continuous time random walk (CTRW) can reproduce breakthrough curve successfully by adjusting the model parameter values, they lack the ability to relate model parameters to the spatio-statistical properties of the media. This in turns limits the transferability of these models. In the research to be presented, we express concentration or flux of solutes as a distribution over their velocity. We then derive an integrodifferential equation that governs the evolution of the particle distribution over velocity at given times and locations for a particle ensemble, based on a presumed velocity correlation structure and an ergodic cross-sectional velocity distribution. This way, the spatial evolution of breakthrough curves away from the source is predicted based on cross-sectional velocity distribution and the connectivity, which is expressed by the velocity transition probability density. The transition probability is specified via a copula function that can help construct a joint distribution with a given correlation and given marginal velocities. Using this approach, we analyze the breakthrough curves depending on the velocity distribution and correlation properties. The model shows how the solute transport behavior evolves from ballistic transport at small spatial scales to Fickian dispersion at large length scales relative to the velocity correlation length.

Spatial pattern enhances ecosystem functioning in an African savanna.

PubMed

Pringle, Robert M; Doak, Daniel F; Brody, Alison K; Jocqué, Rudy; Palmer, Todd M

2010-05-25

The finding that regular spatial patterns can emerge in nature from local interactions between organisms has prompted a search for the ecological importance of these patterns. Theoretical models have predicted that patterning may have positive emergent effects on fundamental ecosystem functions, such as productivity. We provide empirical support for this prediction. In dryland ecosystems, termite mounds are often hotspots of plant growth (primary productivity). Using detailed observations and manipulative experiments in an African savanna, we show that these mounds are also local hotspots of animal abundance (secondary and tertiary productivity): insect abundance and biomass decreased with distance from the nearest termite mound, as did the abundance, biomass, and reproductive output of insect-eating predators. Null-model analyses indicated that at the landscape scale, the evenly spaced distribution of termite mounds produced dramatically greater abundance, biomass, and reproductive output of consumers across trophic levels than would be obtained in landscapes with randomly distributed mounds. These emergent properties of spatial pattern arose because the average distance from an arbitrarily chosen point to the nearest feature in a landscape is minimized in landscapes where the features are hyper-dispersed (i.e., uniformly spaced). This suggests that the linkage between patterning and ecosystem functioning will be common to systems spanning the range of human management intensities. The centrality of spatial pattern to system-wide biomass accumulation underscores the need to conserve pattern-generating organisms and mechanisms, and to incorporate landscape patterning in efforts to restore degraded habitats and maximize the delivery of ecosystem services.

Estimating neighborhood variability with a binary comparison matrix.

USGS Publications Warehouse

Murphy, D.L.

1985-01-01

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

Intrapixel measurement techniques on large focal plane arrays for astronomical applications: a comparative study

NASA Astrophysics Data System (ADS)

Ketchazo, C.; Viale, T.; Boulade, O.; de la Barrière, F.; Dubreuil, D.; Mugnier, L.; Moreau, V.; Guérineau, N.; Mulet, P.; Druart, G.; Delisle, C.

2017-09-01

The intrapixel response is the signal detected by a single pixel illuminated by a Dirac distribution as a function of the position of this Dirac inside this pixel. It is also known as the pixel response function (PRF). This function measures the sensitivity variation at the subpixel scale and gives a spatial map of the sensitivity across a pixel.

Mass Spectrometry Imaging of low Molecular Weight Compounds in Garlic (Allium sativum L.) with Gold Nanoparticle Enhanced Target.

PubMed

Misiorek, Maria; Sekuła, Justyna; Ruman, Tomasz

2017-11-01

Garlic (Allium sativum) is the subject of many studies due to its numerous beneficial properties. Although compounds of garlic have been studied by various analytical methods, their tissue distributions are still unclear. Mass spectrometry imaging (MSI) appears to be a very powerful tool for the identification of the localisation of compounds within a garlic clove. Visualisation of the spatial distribution of garlic low-molecular weight compounds with nanoparticle-based MSI. Compounds occurring on the cross-section of sprouted garlic has been transferred to gold-nanoparticle enhanced target (AuNPET) by imprinting. The imprint was then subjected to MSI analysis. The results suggest that low molecular weight compounds, such as amino acids, dipeptides, fatty acids, organosulphur and organoselenium compounds are distributed within the garlic clove in a characteristic manner. It can be connected with their biological functions and metabolic properties in the plant. New methodology for the visualisation of low molecular weight compounds allowed a correlation to be made between their spatial distribution within a sprouted garlic clove and their biological function. Copyright © 2017 John Wiley & Sons, Ltd. Copyright © 2017 John Wiley & Sons, Ltd.

Reconstruction of atmospheric pollutant concentrations from remote sensing data - An application of distributed parameter observer theory

NASA Technical Reports Server (NTRS)

Koda, M.; Seinfeld, J. H.

1982-01-01

The reconstruction of a concentration distribution from spatially averaged and noise-corrupted data is a central problem in processing atmospheric remote sensing data. Distributed parameter observer theory is used to develop reconstructibility conditions for distributed parameter systems having measurements typical of those in remote sensing. The relation of the reconstructibility condition to the stability of the distributed parameter observer is demonstrated. The theory is applied to a variety of remote sensing situations, and it is found that those in which concentrations are measured as a function of altitude satisfy the conditions of distributed state reconstructibility.

Using special functions to model the propagation of airborne diseases

NASA Astrophysics Data System (ADS)

Bolaños, Daniela

2014-06-01

Some special functions of the mathematical physics are using to obtain a mathematical model of the propagation of airborne diseases. In particular we study the propagation of tuberculosis in closed rooms and we model the propagation using the error function and the Bessel function. In the model, infected individual emit pathogens to the environment and this infect others individuals who absorb it. The evolution in time of the concentration of pathogens in the environment is computed in terms of error functions. The evolution in time of the number of susceptible individuals is expressed by a differential equation that contains the error function and it is solved numerically for different parametric simulations. The evolution in time of the number of infected individuals is plotted for each numerical simulation. On the other hand, the spatial distribution of the pathogen around the source of infection is represented by the Bessel function K0. The spatial and temporal distribution of the number of infected individuals is computed and plotted for some numerical simulations. All computations were made using software Computer algebra, specifically Maple. It is expected that the analytical results that we obtained allow the design of treatment rooms and ventilation systems that reduce the risk of spread of tuberculosis.

Probability and the changing shape of response distributions for orientation.

PubMed

Anderson, Britt

2014-11-18

Spatial attention and feature-based attention are regarded as two independent mechanisms for biasing the processing of sensory stimuli. Feature attention is held to be a spatially invariant mechanism that advantages a single feature per sensory dimension. In contrast to the prediction of location independence, I found that participants were able to report the orientation of a briefly presented visual grating better for targets defined by high probability conjunctions of features and locations even when orientations and locations were individually uniform. The advantage for high-probability conjunctions was accompanied by changes in the shape of the response distributions. High-probability conjunctions had error distributions that were not normally distributed but demonstrated increased kurtosis. The increase in kurtosis could be explained as a change in the variances of the component tuning functions that comprise a population mixture. By changing the mixture distribution of orientation-tuned neurons, it is possible to change the shape of the discrimination function. This prompts the suggestion that attention may not "increase" the quality of perceptual processing in an absolute sense but rather prioritizes some stimuli over others. This results in an increased number of highly accurate responses to probable targets and, simultaneously, an increase in the number of very inaccurate responses. © 2014 ARVO.

Controlled manipulation of oxygen vacancies using nanoscale flexoelectricity

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

Das, Saikat; Wang, Bo; Cao, Ye

Oxygen vacancies, especially their distribution, are directly coupled to the electromagnetic properties of oxides and related emergent functionalities that have implications for device applications. Here using a homoepitaxial strontium titanate thin film, we demonstrate a controlled manipulation of the oxygen vacancy distribution using the mechanical force from a scanning probe microscope tip. By combining Kelvin probe force microscopy imaging and phase-field simulations, we show that oxygen vacancies can move under a stress-gradient-induced depolarisation field. When tailored, this nanoscale flexoelectric effect enables a controlled spatial modulation. In motion, the scanning probe tip thereby deterministically reconfigures the spatial distribution of vacancies. Finally,more » the ability to locally manipulate oxygen vacancies on-demand provides a tool for the exploration of mesoscale quantum phenomena and engineering multifunctional oxide devices.« less

Chain end distribution of block copolymer in two-dimensional microphase-separated structure studied by scanning near-field optical microscopy.

PubMed

Sekine, Ryojun; Aoki, Hiroyuki; Ito, Shinzaburo

2009-10-01

The chain end distribution of a block copolymer in a two-dimensional microphase-separated structure was studied by scanning near-field optical microscopy (SNOM). In the monolayer of poly(octadecyl methacrylate)-block-poly(isobutyl methacrylate) (PODMA-b-PiBMA), the free end of the PiBMA subchain was directly observed by SNOM, and the spatial distributions of the whole block and the chain end are examined and compared with the convolution of the point spread function of the microscope and distribution function of the model structures. It was found that the chain end distribution of the block copolymer confined in two dimensions has a peak near the domain center, being concentrated in the narrower region, as compared with three-dimensional systems.

GRID3D-v2: An updated version of the GRID2D/3D computer program for generating grid systems in complex-shaped three-dimensional spatial domains

NASA Technical Reports Server (NTRS)

Steinthorsson, E.; Shih, T. I-P.; Roelke, R. J.

1991-01-01

In order to generate good quality systems for complicated three-dimensional spatial domains, the grid-generation method used must be able to exert rather precise controls over grid-point distributions. Several techniques are presented that enhance control of grid-point distribution for a class of algebraic grid-generation methods known as the two-, four-, and six-boundary methods. These techniques include variable stretching functions from bilinear interpolation, interpolating functions based on tension splines, and normalized K-factors. The techniques developed in this study were incorporated into a new version of GRID3D called GRID3D-v2. The usefulness of GRID3D-v2 was demonstrated by using it to generate a three-dimensional grid system in the coolent passage of a radial turbine blade with serpentine channels and pin fins.

Time-dependent landslide probability mapping

USGS Publications Warehouse

Campbell, Russell H.; Bernknopf, Richard L.; ,

1993-01-01

Case studies where time of failure is known for rainfall-triggered debris flows can be used to estimate the parameters of a hazard model in which the probability of failure is a function of time. As an example, a time-dependent function for the conditional probability of a soil slip is estimated from independent variables representing hillside morphology, approximations of material properties, and the duration and rate of rainfall. If probabilities are calculated in a GIS (geomorphic information system ) environment, the spatial distribution of the result for any given hour can be displayed on a map. Although the probability levels in this example are uncalibrated, the method offers a potential for evaluating different physical models and different earth-science variables by comparing the map distribution of predicted probabilities with inventory maps for different areas and different storms. If linked with spatial and temporal socio-economic variables, this method could be used for short-term risk assessment.

Cytosol-dependent membrane fusion in ER, nuclear envelope and nuclear pore assembly: biological implications.

PubMed

Rafikova, Elvira R; Melikov, Kamran; Chernomordik, Leonid V

2010-01-01

Endoplasmic reticulum and nuclear envelope rearrangements after mitosis are often studied in the reconstitution system based on Xenopus egg extract. In our recent work we partially replaced the membrane vesicles in the reconstitution mix with protein-free liposomes to explore the relative contributions of cytosolic and transmembrane proteins. Here we discuss our finding that cytosolic proteins mediate fusion between membranes lacking functional transmembrane proteins and the role of membrane fusion in endoplasmic reticulum and nuclear envelope reorganization. Cytosol-dependent liposome fusion has allowed us to restore, without adding transmembrane nucleoporins, functionality of nuclear pores, their spatial distribution and chromatin decondensation in nuclei formed at insufficient amounts of membrane material and characterized by only partial decondensation of chromatin and lack of nuclear transport. Both the mechanisms and the biological implications of the discovered coupling between spatial distribution of nuclear pores, chromatin decondensation and nuclear transport are discussed.

Spatial frequency spectrum of the x-ray scatter distribution in CBCT projections

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

Bootsma, G. J.; Verhaegen, F.; Department of Oncology, Medical Physics Unit, McGill University, Montreal, Quebec H3G 1A4

2013-11-15

Purpose: X-ray scatter is a source of significant image quality loss in cone-beam computed tomography (CBCT). The use of Monte Carlo (MC) simulations separating primary and scattered photons has allowed the structure and nature of the scatter distribution in CBCT to become better elucidated. This work seeks to quantify the structure and determine a suitable basis function for the scatter distribution by examining its spectral components using Fourier analysis.Methods: The scatter distribution projection data were simulated using a CBCT MC model based on the EGSnrc code. CBCT projection data, with separated primary and scatter signal, were generated for a 30.6more » cm diameter water cylinder [single angle projection with varying axis-to-detector distance (ADD) and bowtie filters] and two anthropomorphic phantoms (head and pelvis, 360 projections sampled every 1°, with and without a compensator). The Fourier transform of the resulting scatter distributions was computed and analyzed both qualitatively and quantitatively. A novel metric called the scatter frequency width (SFW) is introduced to determine the scatter distribution's frequency content. The frequency content results are used to determine a set basis functions, consisting of low-frequency sine and cosine functions, to fit and denoise the scatter distribution generated from MC simulations using a reduced number of photons and projections. The signal recovery is implemented using Fourier filtering (low-pass Butterworth filter) and interpolation. Estimates of the scatter distribution are used to correct and reconstruct simulated projections.Results: The spatial and angular frequencies are contained within a maximum frequency of 0.1 cm{sup −1} and 7/(2π) rad{sup −1} for the imaging scenarios examined, with these values varying depending on the object and imaging setup (e.g., ADD and compensator). These data indicate spatial and angular sampling every 5 cm and π/7 rad (∼25°) can be used to properly capture the scatter distribution, with reduced sampling possible depending on the imaging scenario. Using a low-pass Butterworth filter, tuned with the SFW values, to denoise the scatter projection data generated from MC simulations using 10{sup 6} photons resulted in an error reduction of greater than 85% for the estimating scatter in single and multiple projections. Analysis showed that the use of a compensator helped reduce the error in estimating the scatter distribution from limited photon simulations by more than 37% when compared to the case without a compensator for the head and pelvis phantoms. Reconstructions of simulated head phantom projections corrected by the filtered and interpolated scatter estimates showed improvements in overall image quality.Conclusions: The spatial frequency content of the scatter distribution in CBCT is found to be contained within the low frequency domain. The frequency content is modulated both by object and imaging parameters (ADD and compensator). The low-frequency nature of the scatter distribution allows for a limited set of sine and cosine basis functions to be used to accurately represent the scatter signal in the presence of noise and reduced data sampling decreasing MC based scatter estimation time. Compensator induced modulation of the scatter distribution reduces the frequency content and improves the fitting results.« less

Significance tests for functional data with complex dependence structure.

PubMed

Staicu, Ana-Maria; Lahiri, Soumen N; Carroll, Raymond J

2015-01-01

We propose an L 2 -norm based global testing procedure for the null hypothesis that multiple group mean functions are equal, for functional data with complex dependence structure. Specifically, we consider the setting of functional data with a multilevel structure of the form groups-clusters or subjects-units, where the unit-level profiles are spatially correlated within the cluster, and the cluster-level data are independent. Orthogonal series expansions are used to approximate the group mean functions and the test statistic is estimated using the basis coefficients. The asymptotic null distribution of the test statistic is developed, under mild regularity conditions. To our knowledge this is the first work that studies hypothesis testing, when data have such complex multilevel functional and spatial structure. Two small-sample alternatives, including a novel block bootstrap for functional data, are proposed, and their performance is examined in simulation studies. The paper concludes with an illustration of a motivating experiment.

Spatial exposure-hazard and landscape models for assessing the impact of GM crops on non-target organisms.

PubMed

Leclerc, Melen; Walker, Emily; Messéan, Antoine; Soubeyrand, Samuel

2018-05-15

The cultivation of Genetically Modified (GM) crops may have substantial impacts on populations of non-target organisms (NTOs) in agroecosystems. These impacts should be assessed at larger spatial scales than the cultivated field, and, as landscape-scale experiments are difficult, if not impossible, modelling approaches are needed to address landscape risk management. We present an original stochastic and spatially explicit modelling framework for assessing the risk at the landscape level. We use techniques from spatial statistics for simulating simplified landscapes made up of (aggregated or non-aggregated) GM fields, neutral fields and NTO's habitat areas. The dispersal of toxic pollen grains is obtained by convolving the emission of GM plants and validated dispersal kernel functions while the locations of exposed individuals are drawn from a point process. By taking into account the adherence of the ambient pollen on plants, the loss of pollen due to climatic events, and, an experimentally-validated mortality-dose function we predict risk maps and provide a distribution giving how the risk varies within exposed individuals in the landscape. Then, we consider the impact of the Bt maize on Inachis io in worst-case scenarii where exposed individuals are located in the vicinity of GM fields and pollen shedding overlaps with larval emergence. We perform a Global Sensitivity Analysis (GSA) to explore numerically how our input parameters influence the risk. Our results confirm the important effects of pollen emission and loss. Most interestingly they highlight that the optimal spatial distribution of GM fields that mitigates the risk depends on our knowledge of the habitats of NTOs, and finally, moderate the influence of the dispersal kernel function. Copyright © 2017 Elsevier B.V. All rights reserved.

Simulating the Daylight Performance of Complex Fenestration Systems Using Bidirectional Scattering Distribution Functions within Radiance

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

Ward, Gregory; Mistrick, Ph.D., Richard; Lee, Eleanor

2011-01-21

We describe two methods which rely on bidirectional scattering distribution functions (BSDFs) to model the daylighting performance of complex fenestration systems (CFS), enabling greater flexibility and accuracy in evaluating arbitrary assemblies of glazing, shading, and other optically-complex coplanar window systems. Two tools within Radiance enable a) efficient annual performance evaluations of CFS, and b) accurate renderings of CFS despite the loss of spatial resolution associated with low-resolution BSDF datasets for inhomogeneous systems. Validation, accuracy, and limitations of the methods are discussed.

Progress on Discrete Fracture Network models with implications on the predictions of permeability and flow channeling structure

NASA Astrophysics Data System (ADS)

Darcel, C.; Davy, P.; Le Goc, R.; Maillot, J.; Selroos, J. O.

2017-12-01

We present progress on Discrete Fracture Network (DFN) flow modeling, including realistic advanced DFN spatial structures and local fracture transmissivity properties, through an application to the Forsmark site in Sweden. DFN models are a framework to combine fracture datasets from different sources and scales and to interpolate them in combining statistical distributions and stereological relations. The resulting DFN upscaling function - size density distribution - is a model component key to extrapolating fracture size densities between data gaps, from borehole core up to site scale. Another important feature of DFN models lays in the spatial correlations between fractures, with still unevaluated consequences on flow predictions. Indeed, although common Poisson (i.e. spatially random) models are widely used, they do not reflect these geological evidences for more complex structures. To model them, we define a DFN growth process from kinematic rules for nucleation, growth and stopping conditions. It mimics in a simplified way the geological fracturing processes and produces DFN characteristics -both upscaling function and spatial correlations- fully consistent with field observations. DFN structures are first compared for constant transmissivities. Flow simulations for the kinematic and equivalent Poisson DFN models show striking differences: with the kinematic DFN, connectivity and permeability are significantly smaller, down to a difference of one order of magnitude, and flow is much more channelized. Further flow analyses are performed with more realistic transmissivity distribution conditions (sealed parts, relations to fracture sizes, orientations and in-situ stress field). The relative importance of the overall DFN structure in the final flow predictions is discussed.

Spatial distribution of enzyme driven reactions at micro-scales

NASA Astrophysics Data System (ADS)

Kandeler, Ellen; Boeddinghaus, Runa; Nassal, Dinah; Preusser, Sebastian; Marhan, Sven; Poll, Christian

2017-04-01

Studies of microbial biogeography can often provide key insights into the physiologies, environmental tolerances, and ecological strategies of soil microorganisms that dominate in natural environments. In comparison with aquatic systems, soils are particularly heterogeneous. Soil heterogeneity results from the interaction of a hierarchical series of interrelated variables that fluctuate at many different spatial and temporal scales. Whereas spatial dependence of chemical and physical soil properties is well known at scales ranging from decimetres to several hundred metres, the spatial structure of soil enzymes is less clear. Previous work has primarily focused on spatial heterogeneity at a single analytical scale using the distribution of individual cells, specific types of organisms or collective parameters such as bacterial abundance or total microbial biomass. There are fewer studies that have considered variations in community function and soil enzyme activities. This presentation will give an overview about recent studies focusing on spatial pattern of different soil enzymes in the terrestrial environment. Whereas zymography allows the visualization of enzyme pattern in the close vicinity of roots, micro-sampling strategies followed by MUF analyses clarify micro-scale pattern of enzymes associated to specific microhabitats (micro-aggregates, organo-mineral complexes, subsoil compartments).

Ablation of SNX6 leads to defects in synaptic function of CA1 pyramidal neurons and spatial memory

PubMed Central

Niu, Yang; Dai, Zhonghua; Liu, Wenxue; Zhang, Cheng; Yang, Yanrui; Guo, Zhenzhen; Li, Xiaoyu; Xu, Chenchang; Huang, Xiahe; Wang, Yingchun; Shi, Yun S; Liu, Jia-Jia

2017-01-01

SNX6 is a ubiquitously expressed PX-BAR protein that plays important roles in retromer-mediated retrograde vesicular transport from endosomes. Here we report that CNS-specific Snx6 knockout mice exhibit deficits in spatial learning and memory, accompanied with loss of spines from distal dendrites of hippocampal CA1 pyramidal cells. SNX6 interacts with Homer1b/c, a postsynaptic scaffold protein crucial for the synaptic distribution of other postsynaptic density (PSD) proteins and structural integrity of dendritic spines. We show that SNX6 functions independently of retromer to regulate distribution of Homer1b/c in the dendritic shaft. We also find that Homer1b/c translocates from shaft to spines by protein diffusion, which does not require SNX6. Ablation of SNX6 causes reduced distribution of Homer1b/c in distal dendrites, decrease in surface levels of AMPAR and impaired AMPAR-mediated synaptic transmission. These findings reveal a physiological role of SNX6 in CNS excitatory neurons. DOI: http://dx.doi.org/10.7554/eLife.20991.001 PMID:28134614

A novel approach for introducing cloud spatial structure into cloud radiative transfer parameterizations

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

Huang, Dong; Liu, Yangang

2014-12-18

Subgrid-scale variability is one of the main reasons why parameterizations are needed in large-scale models. Although some parameterizations started to address the issue of subgrid variability by introducing a subgrid probability distribution function for relevant quantities, the spatial structure has been typically ignored and thus the subgrid-scale interactions cannot be accounted for physically. Here we present a new statistical-physics-like approach whereby the spatial autocorrelation function can be used to physically capture the net effects of subgrid cloud interaction with radiation. The new approach is able to faithfully reproduce the Monte Carlo 3D simulation results with several orders less computational cost,more » allowing for more realistic representation of cloud radiation interactions in large-scale models.« less

Towards real-time diffuse optical tomography for imaging brain functions cooperated with Kalman estimator

NASA Astrophysics Data System (ADS)

Wang, Bingyuan; Zhang, Yao; Liu, Dongyuan; Ding, Xuemei; Dan, Mai; Pan, Tiantian; Wang, Yihan; Li, Jiao; Zhou, Zhongxing; Zhang, Limin; Zhao, Huijuan; Gao, Feng

2018-02-01

Functional near-infrared spectroscopy (fNIRS) is a non-invasive neuroimaging method to monitor the cerebral hemodynamic through the optical changes measured at the scalp surface. It has played a more and more important role in psychology and medical imaging communities. Real-time imaging of brain function using NIRS makes it possible to explore some sophisticated human brain functions unexplored before. Kalman estimator has been frequently used in combination with modified Beer-Lamber Law (MBLL) based optical topology (OT), for real-time brain function imaging. However, the spatial resolution of the OT is low, hampering the application of OT in exploring some complicated brain functions. In this paper, we develop a real-time imaging method combining diffuse optical tomography (DOT) and Kalman estimator, much improving the spatial resolution. Instead of only presenting one spatially distributed image indicating the changes of the absorption coefficients at each time point during the recording process, one real-time updated image using the Kalman estimator is provided. Its each voxel represents the amplitude of the hemodynamic response function (HRF) associated with this voxel. We evaluate this method using some simulation experiments, demonstrating that this method can obtain more reliable spatial resolution images. Furthermore, a statistical analysis is also conducted to help to decide whether a voxel in the field of view is activated or not.

On the synchrotron emission in kinetic simulations of runaway electrons in magnetic confinement fusion plasmas

NASA Astrophysics Data System (ADS)

Carbajal, L.; del-Castillo-Negrete, D.

2017-12-01

Developing avoidance or mitigation strategies of runaway electrons (REs) in magnetic confinement fusion (MCF) plasmas is of crucial importance for the safe operation of ITER. In order to develop these strategies, an accurate diagnostic capability that allows good estimates of the RE distribution function in these plasmas is needed. Synchrotron radiation (SR) of RE in MCF, besides of being one of the main damping mechanisms for RE in the high energy relativistic regime, is routinely used in current MCF experiments to infer the parameters of RE energy and pitch angle distribution functions. In the present paper we address the long standing question about what are the relationships between different REs distribution functions and their corresponding synchrotron emission simultaneously including: full-orbit effects, information of the spectral and angular distribution of SR of each electron, and basic geometric optics of a camera. We study the spatial distribution of the SR on the poloidal plane, and the statistical properties of the expected value of the synchrotron spectra of REs. We observe a strong dependence of the synchrotron emission measured by the camera on the pitch angle distribution of runaways, namely we find that crescent shapes of the spatial distribution of the SR as measured by the camera relate to RE distributions with small pitch angles, while ellipse shapes relate to distributions of runaways with larger the pitch angles. A weak dependence of the synchrotron emission measured by the camera with the RE energy, value of the q-profile at the edge, and the chosen range of wavelengths is observed. Furthermore, we find that oversimplifying the angular dependence of the SR changes the shape of the synchrotron spectra, and overestimates its amplitude by approximately 20 times for avalanching runaways and by approximately 60 times for mono-energetic distributions of runaways1.

Seasonal Variability of Middle Latitude Ozone in the Lowermost Stratosphere Derived from Probability Distribution Functions

NASA Technical Reports Server (NTRS)

Cerniglia, M. C.; Douglass, A. R.; Rood, R. B.; Sparling, L. C..; Nielsen, J. E.

1999-01-01

We present a study of the distribution of ozone in the lowermost stratosphere with the goal of understanding the relative contribution to the observations of air of either distinctly tropospheric or stratospheric origin. The air in the lowermost stratosphere is divided into two population groups based on Ertel's potential vorticity at 300 hPa. High [low] potential vorticity at 300 hPa suggests that the tropopause is low [high], and the identification of the two groups helps to account for dynamic variability. Conditional probability distribution functions are used to define the statistics of the mix from both observations and model simulations. Two data sources are chosen. First, several years of ozonesonde observations are used to exploit the high vertical resolution. Second, observations made by the Halogen Occultation Experiment [HALOE] on the Upper Atmosphere Research Satellite [UARS] are used to understand the impact on the results of the spatial limitations of the ozonesonde network. The conditional probability distribution functions are calculated at a series of potential temperature surfaces spanning the domain from the midlatitude tropopause to surfaces higher than the mean tropical tropopause [about 380K]. Despite the differences in spatial and temporal sampling, the probability distribution functions are similar for the two data sources. Comparisons with the model demonstrate that the model maintains a mix of air in the lowermost stratosphere similar to the observations. The model also simulates a realistic annual cycle. By using the model, possible mechanisms for the maintenance of mix of air in the lowermost stratosphere are revealed. The relevance of the results to the assessment of the environmental impact of aircraft effluence is discussed.

Seasonal Variability of Middle Latitude Ozone in the Lowermost Stratosphere Derived from Probability Distribution Functions

NASA Technical Reports Server (NTRS)

Cerniglia, M. C.; Douglass, A. R.; Rood, R. B.; Sparling, L. C.; Nielsen, J. E.

1999-01-01

We present a study of the distribution of ozone in the lowermost stratosphere with the goal of understanding the relative contribution to the observations of air of either distinctly tropospheric or stratospheric origin. The air in the lowermost stratosphere is divided into two population groups based on Ertel's potential vorticity at 300 hPa. High [low] potential vorticity at 300 hPa suggests that the tropopause is low [high], and the identification of the two groups helps to account for dynamic variability. Conditional probability distribution functions are used to define the statistics of the mix from both observations and model simulations. Two data sources are chosen. First, several years of ozonesonde observations are used to exploit the high vertical resolution. Second, observations made by the Halogen Occultation Experiment [HALOE) on the Upper Atmosphere Research Satellite [UARS] are used to understand the impact on the results of the spatial limitations of the ozonesonde network. The conditional probability distribution functions are calculated at a series of potential temperature surfaces spanning the domain from the midlatitude tropopause to surfaces higher than the mean tropical tropopause [approximately 380K]. Despite the differences in spatial and temporal sampling, the probability distribution functions are similar for the two data sources. Comparisons with the model demonstrate that the model maintains a mix of air in the lowermost stratosphere similar to the observations. The model also simulates a realistic annual cycle. By using the model, possible mechanisms for the maintenance of mix of air in the lowermost stratosphere are revealed. The relevance of the results to the assessment of the environmental impact of aircraft effluence is discussed.

Entropy of spatial network ensembles

NASA Astrophysics Data System (ADS)

Coon, Justin P.; Dettmann, Carl P.; Georgiou, Orestis

2018-04-01

We analyze complexity in spatial network ensembles through the lens of graph entropy. Mathematically, we model a spatial network as a soft random geometric graph, i.e., a graph with two sources of randomness, namely nodes located randomly in space and links formed independently between pairs of nodes with probability given by a specified function (the "pair connection function") of their mutual distance. We consider the general case where randomness arises in node positions as well as pairwise connections (i.e., for a given pair distance, the corresponding edge state is a random variable). Classical random geometric graph and exponential graph models can be recovered in certain limits. We derive a simple bound for the entropy of a spatial network ensemble and calculate the conditional entropy of an ensemble given the node location distribution for hard and soft (probabilistic) pair connection functions. Under this formalism, we derive the connection function that yields maximum entropy under general constraints. Finally, we apply our analytical framework to study two practical examples: ad hoc wireless networks and the US flight network. Through the study of these examples, we illustrate that both exhibit properties that are indicative of nearly maximally entropic ensembles.

Spatio-temporal models of mental processes from fMRI.

PubMed

Janoos, Firdaus; Machiraju, Raghu; Singh, Shantanu; Morocz, Istvan Ákos

2011-07-15

Understanding the highly complex, spatially distributed and temporally organized phenomena entailed by mental processes using functional MRI is an important research problem in cognitive and clinical neuroscience. Conventional analysis methods focus on the spatial dimension of the data discarding the information about brain function contained in the temporal dimension. This paper presents a fully spatio-temporal multivariate analysis method using a state-space model (SSM) for brain function that yields not only spatial maps of activity but also its temporal structure along with spatially varying estimates of the hemodynamic response. Efficient algorithms for estimating the parameters along with quantitative validations are given. A novel low-dimensional feature-space for representing the data, based on a formal definition of functional similarity, is derived. Quantitative validation of the model and the estimation algorithms is provided with a simulation study. Using a real fMRI study for mental arithmetic, the ability of this neurophysiologically inspired model to represent the spatio-temporal information corresponding to mental processes is demonstrated. Moreover, by comparing the models across multiple subjects, natural patterns in mental processes organized according to different mental abilities are revealed. Copyright © 2011 Elsevier Inc. All rights reserved.

Competition between plant functional types in the Canadian Terrestrial Ecosystem Model (CTEM) v. 2.0

NASA Astrophysics Data System (ADS)

Melton, J. R.; Arora, V. K.

2015-06-01

The Canadian Terrestrial Ecosystem Model (CTEM) is the interactive vegetation component in the Earth system model of the Canadian Centre for Climate Modelling and Analysis. CTEM models land-atmosphere exchange of CO2 through the response of carbon in living vegetation, and dead litter and soil pools, to changes in weather and climate at timescales of days to centuries. Version 1.0 of CTEM uses prescribed fractional coverage of plant functional types (PFTs) although, in reality, vegetation cover continually adapts to changes in climate, atmospheric composition, and anthropogenic forcing. Changes in the spatial distribution of vegetation occur on timescales of years to centuries as vegetation distributions inherently have inertia. Here, we present version 2.0 of CTEM which includes a representation of competition between PFTs based on a modified version of the Lotka-Volterra (L-V) predator-prey equations. Our approach is used to dynamically simulate the fractional coverage of CTEM's seven natural, non-crop PFTs which are then compared with available observation-based estimates. Results from CTEM v. 2.0 show the model is able to represent the broad spatial distributions of its seven PFTs at the global scale. However, differences remain between modelled and observation-based fractional coverages of PFTs since representing the multitude of plant species globally, with just seven non-crop PFTs, only captures the large scale climatic controls on PFT distributions. As expected, PFTs that exist in climate niches are difficult to represent either due to the coarse spatial resolution of the model, and the corresponding driving climate, or the limited number of PFTs used. We also simulate the fractional coverages of PFTs using unmodified L-V equations to illustrate its limitations. The geographic and zonal distributions of primary terrestrial carbon pools and fluxes from the versions of CTEM that use prescribed and dynamically simulated fractional coverage of PFTs compare reasonably well with each other and observation-based estimates. The parametrization of competition between PFTs in CTEM v. 2.0 based on the modified L-V equations behaves in a reasonably realistic manner and yields a tool with which to investigate the changes in spatial distribution of vegetation in response to future changes in climate.

Competition between plant functional types in the Canadian Terrestrial Ecosystem Model (CTEM) v. 2.0

NASA Astrophysics Data System (ADS)

Melton, J. R.; Arora, V. K.

2016-01-01

The Canadian Terrestrial Ecosystem Model (CTEM) is the interactive vegetation component in the Earth system model of the Canadian Centre for Climate Modelling and Analysis. CTEM models land-atmosphere exchange of CO2 through the response of carbon in living vegetation, and dead litter and soil pools, to changes in weather and climate at timescales of days to centuries. Version 1.0 of CTEM uses prescribed fractional coverage of plant functional types (PFTs) although, in reality, vegetation cover continually adapts to changes in climate, atmospheric composition and anthropogenic forcing. Changes in the spatial distribution of vegetation occur on timescales of years to centuries as vegetation distributions inherently have inertia. Here, we present version 2.0 of CTEM, which includes a representation of competition between PFTs based on a modified version of the Lotka-Volterra (L-V) predator-prey equations. Our approach is used to dynamically simulate the fractional coverage of CTEM's seven natural, non-crop PFTs, which are then compared with available observation-based estimates. Results from CTEM v. 2.0 show the model is able to represent the broad spatial distributions of its seven PFTs at the global scale. However, differences remain between modelled and observation-based fractional coverage of PFTs since representing the multitude of plant species globally, with just seven non-crop PFTs, only captures the large-scale climatic controls on PFT distributions. As expected, PFTs that exist in climate niches are difficult to represent either due to the coarse spatial resolution of the model, and the corresponding driving climate, or the limited number of PFTs used. We also simulate the fractional coverage of PFTs using unmodified L-V equations to illustrate its limitations. The geographic and zonal distributions of primary terrestrial carbon pools and fluxes from the versions of CTEM that use prescribed and dynamically simulated fractional coverage of PFTs compare reasonably well with each other and observation-based estimates. The parametrization of competition between PFTs in CTEM v. 2.0 based on the modified L-V equations behaves in a reasonably realistic manner and yields a tool with which to investigate the changes in spatial distribution of vegetation in response to future changes in climate.

Transport lattice models of heat transport in skin with spatially heterogeneous, temperature-dependent perfusion.

PubMed

Gowrishankar, T R; Stewart, Donald A; Martin, Gregory T; Weaver, James C

2004-11-17

Investigation of bioheat transfer problems requires the evaluation of temporal and spatial distributions of temperature. This class of problems has been traditionally addressed using the Pennes bioheat equation. Transport of heat by conduction, and by temperature-dependent, spatially heterogeneous blood perfusion is modeled here using a transport lattice approach. We represent heat transport processes by using a lattice that represents the Pennes bioheat equation in perfused tissues, and diffusion in nonperfused regions. The three layer skin model has a nonperfused viable epidermis, and deeper regions of dermis and subcutaneous tissue with perfusion that is constant or temperature-dependent. Two cases are considered: (1) surface contact heating and (2) spatially distributed heating. The model is relevant to the prediction of the transient and steady state temperature rise for different methods of power deposition within the skin. Accumulated thermal damage is estimated by using an Arrhenius type rate equation at locations where viable tissue temperature exceeds 42 degrees C. Prediction of spatial temperature distributions is also illustrated with a two-dimensional model of skin created from a histological image. The transport lattice approach was validated by comparison with an analytical solution for a slab with homogeneous thermal properties and spatially distributed uniform sink held at constant temperatures at the ends. For typical transcutaneous blood gas sensing conditions the estimated damage is small, even with prolonged skin contact to a 45 degrees C surface. Spatial heterogeneity in skin thermal properties leads to a non-uniform temperature distribution during a 10 GHz electromagnetic field exposure. A realistic two-dimensional model of the skin shows that tissue heterogeneity does not lead to a significant local temperature increase when heated by a hot wire tip. The heat transport system model of the skin was solved by exploiting the mathematical analogy between local thermal models and local electrical (charge transport) models, thereby allowing robust, circuit simulation software to obtain solutions to Kirchhoff's laws for the system model. Transport lattices allow systematic introduction of realistic geometry and spatially heterogeneous heat transport mechanisms. Local representations for both simple, passive functions and more complex local models can be easily and intuitively included into the system model of a tissue.

Subgrid spatial variability of soil hydraulic functions for hydrological modelling

NASA Astrophysics Data System (ADS)

Kreye, Phillip; Meon, Günter

2016-07-01

State-of-the-art hydrological applications require a process-based, spatially distributed hydrological model. Runoff characteristics are demanded to be well reproduced by the model. Despite that, the model should be able to describe the processes at a subcatchment scale in a physically credible way. The objective of this study is to present a robust procedure to generate various sets of parameterisations of soil hydraulic functions for the description of soil heterogeneity on a subgrid scale. Relations between Rosetta-generated values of saturated hydraulic conductivity (Ks) and van Genuchten's parameters of soil hydraulic functions were statistically analysed. An universal function that is valid for the complete bandwidth of Ks values could not be found. After concentrating on natural texture classes, strong correlations were identified for all parameters. The obtained regression results were used to parameterise sets of hydraulic functions for each soil class. The methodology presented in this study is applicable on a wide range of spatial scales and does not need input data from field studies. The developments were implemented into a hydrological modelling system.

Visualizing Time-Varying Distribution Data in EOS Application

NASA Technical Reports Server (NTRS)

Shen, Han-Wei

2004-01-01

In this research, we have developed several novel visualization methods for spatial probability density function data. Our focus has been on 2D spatial datasets, where each pixel is a random variable, and has multiple samples which are the results of experiments on that random variable. We developed novel clustering algorithms as a means to reduce the information contained in these datasets; and investigated different ways of interpreting and clustering the data.

Spatial frequency performance limitations of radiation dose optimization and beam positioning

NASA Astrophysics Data System (ADS)

Stewart, James M. P.; Stapleton, Shawn; Chaudary, Naz; Lindsay, Patricia E.; Jaffray, David A.

2018-06-01

The flexibility and sophistication of modern radiotherapy treatment planning and delivery methods have advanced techniques to improve the therapeutic ratio. Contemporary dose optimization and calculation algorithms facilitate radiotherapy plans which closely conform the three-dimensional dose distribution to the target, with beam shaping devices and image guided field targeting ensuring the fidelity and accuracy of treatment delivery. Ultimately, dose distribution conformity is limited by the maximum deliverable dose gradient; shallow dose gradients challenge techniques to deliver a tumoricidal radiation dose while minimizing dose to surrounding tissue. In this work, this ‘dose delivery resolution’ observation is rigorously formalized for a general dose delivery model based on the superposition of dose kernel primitives. It is proven that the spatial resolution of a delivered dose is bounded by the spatial frequency content of the underlying dose kernel, which in turn defines a lower bound in the minimization of a dose optimization objective function. In addition, it is shown that this optimization is penalized by a dose deposition strategy which enforces a constant relative phase (or constant spacing) between individual radiation beams. These results are further refined to provide a direct, analytic method to estimate the dose distribution arising from the minimization of such an optimization function. The efficacy of the overall framework is demonstrated on an image guided small animal microirradiator for a set of two-dimensional hypoxia guided dose prescriptions.

Sensor Location Problem Optimization for Traffic Network with Different Spatial Distributions of Traffic Information.

PubMed

Bao, Xu; Li, Haijian; Qin, Lingqiao; Xu, Dongwei; Ran, Bin; Rong, Jian

2016-10-27

To obtain adequate traffic information, the density of traffic sensors should be sufficiently high to cover the entire transportation network. However, deploying sensors densely over the entire network may not be realistic for practical applications due to the budgetary constraints of traffic management agencies. This paper describes several possible spatial distributions of traffic information credibility and proposes corresponding different sensor information credibility functions to describe these spatial distribution properties. A maximum benefit model and its simplified model are proposed to solve the traffic sensor location problem. The relationships between the benefit and the number of sensors are formulated with different sensor information credibility functions. Next, expanding models and algorithms in analytic results are performed. For each case, the maximum benefit, the optimal number and spacing of sensors are obtained and the analytic formulations of the optimal sensor locations are derived as well. Finally, a numerical example is proposed to verify the validity and availability of the proposed models for solving a network sensor location problem. The results show that the optimal number of sensors of segments with different model parameters in an entire freeway network can be calculated. Besides, it can also be concluded that the optimal sensor spacing is independent of end restrictions but dependent on the values of model parameters that represent the physical conditions of sensors and roads.

Sensor Location Problem Optimization for Traffic Network with Different Spatial Distributions of Traffic Information

PubMed Central

Bao, Xu; Li, Haijian; Qin, Lingqiao; Xu, Dongwei; Ran, Bin; Rong, Jian

2016-01-01

To obtain adequate traffic information, the density of traffic sensors should be sufficiently high to cover the entire transportation network. However, deploying sensors densely over the entire network may not be realistic for practical applications due to the budgetary constraints of traffic management agencies. This paper describes several possible spatial distributions of traffic information credibility and proposes corresponding different sensor information credibility functions to describe these spatial distribution properties. A maximum benefit model and its simplified model are proposed to solve the traffic sensor location problem. The relationships between the benefit and the number of sensors are formulated with different sensor information credibility functions. Next, expanding models and algorithms in analytic results are performed. For each case, the maximum benefit, the optimal number and spacing of sensors are obtained and the analytic formulations of the optimal sensor locations are derived as well. Finally, a numerical example is proposed to verify the validity and availability of the proposed models for solving a network sensor location problem. The results show that the optimal number of sensors of segments with different model parameters in an entire freeway network can be calculated. Besides, it can also be concluded that the optimal sensor spacing is independent of end restrictions but dependent on the values of model parameters that represent the physical conditions of sensors and roads. PMID:27801794

Total Water-Vapor Distribution in the Summer Cloudless Atmosphere over the South of Western Siberia

NASA Astrophysics Data System (ADS)

Troshkin, D. N.; Bezuglova, N. N.; Kabanov, M. V.; Pavlov, V. E.; Sokolov, K. I.; Sukovatov, K. Yu.

2017-12-01

The spatial distribution of the total water vapor in different climatic zones of the south of Western Siberia in summer of 2008-2011 is studied on the basis of Envisat data. The correlation analysis of the water-vapor time series from the Envisat data W and radiosonde observations w for the territory of Omsk aerological station show that the absolute values of W and w are linearly correlated with a coefficient of 0.77 (significance level p < 0.05). The distribution functions of the total water vapor are calculated based on the number of its measurements by Envisat for a cloudless sky of three zones with different physical properties of the underlying surface, in particular, steppes to the south of the Vasyugan Swamp and forests to the northeast of the Swamp. The distribution functions are bimodal; each mode follows the lognormal law. The parameters of these functions are given.

Uncertainty in determining extreme precipitation thresholds

NASA Astrophysics Data System (ADS)

Liu, Bingjun; Chen, Junfan; Chen, Xiaohong; Lian, Yanqing; Wu, Lili

2013-10-01

Extreme precipitation events are rare and occur mostly on a relatively small and local scale, which makes it difficult to set the thresholds for extreme precipitations in a large basin. Based on the long term daily precipitation data from 62 observation stations in the Pearl River Basin, this study has assessed the applicability of the non-parametric, parametric, and the detrended fluctuation analysis (DFA) methods in determining extreme precipitation threshold (EPT) and the certainty to EPTs from each method. Analyses from this study show the non-parametric absolute critical value method is easy to use, but unable to reflect the difference of spatial rainfall distribution. The non-parametric percentile method can account for the spatial distribution feature of precipitation, but the problem with this method is that the threshold value is sensitive to the size of rainfall data series and is subjected to the selection of a percentile thus make it difficult to determine reasonable threshold values for a large basin. The parametric method can provide the most apt description of extreme precipitations by fitting extreme precipitation distributions with probability distribution functions; however, selections of probability distribution functions, the goodness-of-fit tests, and the size of the rainfall data series can greatly affect the fitting accuracy. In contrast to the non-parametric and the parametric methods which are unable to provide information for EPTs with certainty, the DFA method although involving complicated computational processes has proven to be the most appropriate method that is able to provide a unique set of EPTs for a large basin with uneven spatio-temporal precipitation distribution. The consistency between the spatial distribution of DFA-based thresholds with the annual average precipitation, the coefficient of variation (CV), and the coefficient of skewness (CS) for the daily precipitation further proves that EPTs determined by the DFA method are more reasonable and applicable for the Pearl River Basin.

Predictive modelling of grain-size distributions from marine electromagnetic profiling data using end-member analysis and a radial basis function network

NASA Astrophysics Data System (ADS)

Baasch, B.; Müller, H.; von Dobeneck, T.

2018-07-01

In this work, we present a new methodology to predict grain-size distributions from geophysical data. Specifically, electric conductivity and magnetic susceptibility of seafloor sediments recovered from electromagnetic profiling data are used to predict grain-size distributions along shelf-wide survey lines. Field data from the NW Iberian shelf are investigated and reveal a strong relation between the electromagnetic properties and grain-size distribution. The here presented workflow combines unsupervised and supervised machine-learning techniques. Non-negative matrix factorization is used to determine grain-size end-members from sediment surface samples. Four end-members were found, which well represent the variety of sediments in the study area. A radial basis function network modified for prediction of compositional data is then used to estimate the abundances of these end-members from the electromagnetic properties. The end-members together with their predicted abundances are finally back transformed to grain-size distributions. A minimum spatial variation constraint is implemented in the training of the network to avoid overfitting and to respect the spatial distribution of sediment patterns. The predicted models are tested via leave-one-out cross-validation revealing high prediction accuracy with coefficients of determination (R2) between 0.76 and 0.89. The predicted grain-size distributions represent the well-known sediment facies and patterns on the NW Iberian shelf and provide new insights into their distribution, transition and dynamics. This study suggests that electromagnetic benthic profiling in combination with machine learning techniques is a powerful tool to estimate grain-size distribution of marine sediments.

Predictive modelling of grain size distributions from marine electromagnetic profiling data using end-member analysis and a radial basis function network

NASA Astrophysics Data System (ADS)

Baasch, B.; M"uller, H.; von Dobeneck, T.

2018-04-01

In this work we present a new methodology to predict grain-size distributions from geophysical data. Specifically, electric conductivity and magnetic susceptibility of seafloor sediments recovered from electromagnetic profiling data are used to predict grain-size distributions along shelf-wide survey lines. Field data from the NW Iberian shelf are investigated and reveal a strong relation between the electromagnetic properties and grain-size distribution. The here presented workflow combines unsupervised and supervised machine learning techniques. Nonnegative matrix factorisation is used to determine grain-size end-members from sediment surface samples. Four end-members were found which well represent the variety of sediments in the study area. A radial-basis function network modified for prediction of compositional data is then used to estimate the abundances of these end-members from the electromagnetic properties. The end-members together with their predicted abundances are finally back transformed to grain-size distributions. A minimum spatial variation constraint is implemented in the training of the network to avoid overfitting and to respect the spatial distribution of sediment patterns. The predicted models are tested via leave-one-out cross-validation revealing high prediction accuracy with coefficients of determination (R2) between 0.76 and 0.89. The predicted grain-size distributions represent the well-known sediment facies and patterns on the NW Iberian shelf and provide new insights into their distribution, transition and dynamics. This study suggests that electromagnetic benthic profiling in combination with machine learning techniques is a powerful tool to estimate grain-size distribution of marine sediments.

Spatio-temporal reconstruction of brain dynamics from EEG with a Markov prior.

PubMed

Hansen, Sofie Therese; Hansen, Lars Kai

2017-03-01

Electroencephalography (EEG) can capture brain dynamics in high temporal resolution. By projecting the scalp EEG signal back to its origin in the brain also high spatial resolution can be achieved. Source localized EEG therefore has potential to be a very powerful tool for understanding the functional dynamics of the brain. Solving the inverse problem of EEG is however highly ill-posed as there are many more potential locations of the EEG generators than EEG measurement points. Several well-known properties of brain dynamics can be exploited to alleviate this problem. More short ranging connections exist in the brain than long ranging, arguing for spatially focal sources. Additionally, recent work (Delorme et al., 2012) argues that EEG can be decomposed into components having sparse source distributions. On the temporal side both short and long term stationarity of brain activation are seen. We summarize these insights in an inverse solver, the so-called "Variational Garrote" (Kappen and Gómez, 2013). Using a Markov prior we can incorporate flexible degrees of temporal stationarity. Through spatial basis functions spatially smooth distributions are obtained. Sparsity of these are inherent to the Variational Garrote solver. We name our method the MarkoVG and demonstrate its ability to adapt to the temporal smoothness and spatial sparsity in simulated EEG data. Finally a benchmark EEG dataset is used to demonstrate MarkoVG's ability to recover non-stationary brain dynamics. Copyright © 2016 Elsevier Inc. All rights reserved.

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.

Spatially Resolved Quantification of the Surface Reactivity of Solid Catalysts.

PubMed

Huang, Bing; Xiao, Li; Lu, Juntao; Zhuang, Lin

2016-05-17

A new property is reported that accurately quantifies and spatially describes the chemical reactivity of solid surfaces. The core idea is to create a reactivity weight function peaking at the Fermi level, thereby determining a weighted summation of the density of states of a solid surface. When such a weight function is defined as the derivative of the Fermi-Dirac distribution function at a certain non-zero temperature, the resulting property is the finite-temperature chemical softness, termed Fermi softness (SF ), which turns out to be an accurate descriptor of the surface reactivity. The spatial image of SF maps the reactive domain of a heterogeneous surface and even portrays morphological details of the reactive sites. SF analyses reveal that the reactive zones on a Pt3 Y(111) surface are the platinum sites rather than the seemingly active yttrium sites, and the reactivity of the S-dimer edge of MoS2 is spatially anisotropic. Our finding is of fundamental and technological significance to heterogeneous catalysis and industrial processes demanding rational design of solid catalysts. © 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Mapping Thermal Habitat of Ectotherms Based on Behavioral Thermoregulation in a Controlled Thermal Environment

NASA Astrophysics Data System (ADS)

Fei, T.; Skidmore, A.; Liu, Y.

2012-07-01

Thermal environment is especially important to ectotherm because a lot of physiological functions rely on the body temperature such as thermoregulation. The so-called behavioural thermoregulation function made use of the heterogeneity of the thermal properties within an individual's habitat to sustain the animal's physiological processes. This function links the spatial utilization and distribution of individual ectotherm with the thermal properties of habitat (thermal habitat). In this study we modelled the relationship between the two by a spatial explicit model that simulates the movements of a lizard in a controlled environment. The model incorporates a lizard's transient body temperatures with a cellular automaton algorithm as a way to link the physiology knowledge of the animal with the spatial utilization of its microhabitat. On a larger spatial scale, 'thermal roughness' of the habitat was defined and used to predict the habitat occupancy of the target species. The results showed the habitat occupancy can be modelled by the cellular automaton based algorithm at a smaller scale, and can be modelled by the thermal roughness index at a larger scale.

Estimating riparian understory vegetation cover with beta regression and copula models

USGS Publications Warehouse

Eskelson, Bianca N.I.; Madsen, Lisa; Hagar, Joan C.; Temesgen, Hailemariam

2011-01-01

Understory vegetation communities are critical components of forest ecosystems. As a result, the importance of modeling understory vegetation characteristics in forested landscapes has become more apparent. Abundance measures such as shrub cover are bounded between 0 and 1, exhibit heteroscedastic error variance, and are often subject to spatial dependence. These distributional features tend to be ignored when shrub cover data are analyzed. The beta distribution has been used successfully to describe the frequency distribution of vegetation cover. Beta regression models ignoring spatial dependence (BR) and accounting for spatial dependence (BRdep) were used to estimate percent shrub cover as a function of topographic conditions and overstory vegetation structure in riparian zones in western Oregon. The BR models showed poor explanatory power (pseudo-R2 ≤ 0.34) but outperformed ordinary least-squares (OLS) and generalized least-squares (GLS) regression models with logit-transformed response in terms of mean square prediction error and absolute bias. We introduce a copula (COP) model that is based on the beta distribution and accounts for spatial dependence. A simulation study was designed to illustrate the effects of incorrectly assuming normality, equal variance, and spatial independence. It showed that BR, BRdep, and COP models provide unbiased parameter estimates, whereas OLS and GLS models result in slightly biased estimates for two of the three parameters. On the basis of the simulation study, 93–97% of the GLS, BRdep, and COP confidence intervals covered the true parameters, whereas OLS and BR only resulted in 84–88% coverage, which demonstrated the superiority of GLS, BRdep, and COP over OLS and BR models in providing standard errors for the parameter estimates in the presence of spatial dependence.

Dependence of B1+ and B1- Field Patterns of Surface Coils on the Electrical Properties of the Sample and the MR Operating Frequency.

PubMed

Vaidya, Manushka V; Collins, Christopher M; Sodickson, Daniel K; Brown, Ryan; Wiggins, Graham C; Lattanzi, Riccardo

2016-02-01

In high field MRI, the spatial distribution of the radiofrequency magnetic ( B 1 ) field is usually affected by the presence of the sample. For hardware design and to aid interpretation of experimental results, it is important both to anticipate and to accurately simulate the behavior of these fields. Fields generated by a radiofrequency surface coil were simulated using dyadic Green's functions, or experimentally measured over a range of frequencies inside an object whose electrical properties were varied to illustrate a variety of transmit [Formula: see text] and receive [Formula: see text] field patterns. In this work, we examine how changes in polarization of the field and interference of propagating waves in an object can affect the B 1 spatial distribution. Results are explained conceptually using Maxwell's equations and intuitive illustrations. We demonstrate that the electrical conductivity alters the spatial distribution of distinct polarized components of the field, causing "twisted" transmit and receive field patterns, and asymmetries between [Formula: see text] and [Formula: see text]. Additionally, interference patterns due to wavelength effects are observed at high field in samples with high relative permittivity and near-zero conductivity, but are not present in lossy samples due to the attenuation of propagating EM fields. This work provides a conceptual framework for understanding B 1 spatial distributions for surface coils and can provide guidance for RF engineers.

Exploring the Spatial and Temporal Organization of a Cell’s Proteome

PubMed Central

Beck, Martin; Topf, Maya; Frazier, Zachary; Tjong, Harianto; Xu, Min; Zhang, Shihua; Alber, Frank

2013-01-01

To increase our current understanding of cellular processes, such as cell signaling and division, knowledge is needed about the spatial and temporal organization of the proteome at different organizational levels. These levels cover a wide range of length and time scales: from the atomic structures of macromolecules for inferring their molecular function, to the quantitative description of their abundance, and distribution in the cell. Emerging new experimental technologies are greatly increasing the availability of such spatial information on the molecular organization in living cells. This review addresses three fields that have significantly contributed to our understanding of the proteome’s spatial and temporal organization: first, methods for the structure determination of individual macromolecular assemblies, specifically the fitting of atomic structures into density maps generated from electron microscopy techniques; second, research that visualizes the spatial distributions of these complexes within the cellular context using cryo electron tomography techniques combined with computational image processing; and third, methods for the spatial modeling of the dynamic organization of the proteome, specifically those methods for simulating reaction and diffusion of proteins and complexes in crowded intracellular fluids. The long-term goal is to integrate the varied data about a proteome’s organization into a spatially explicit, predictive model of cellular processes. PMID:21094684

Pickup Ion Distributions from Three Dimensional Neutral Exospheres

NASA Technical Reports Server (NTRS)

Hartle, R. E.; Sarantos, M.; Sittler, E. C., Jr.

2011-01-01

Pickup ions formed from ionized neutral exospheres in flowing plasmas have phase space distributions that reflect their source's spatial distributions. Phase space distributions of the ions are derived from the Vlasov equation with a delta function source using three.dimensional neutral exospheres. The ExB drift produced by plasma motion picks up the ions while the effects of magnetic field draping, mass loading, wave particle scattering, and Coulomb collisions near a planetary body are ignored. Previously, one.dimensional exospheres were treated, resulting in closed form pickup ion distributions that explicitly depend on the ratio rg/H, where rg is the ion gyroradius and H is the neutral scale height at the exobase. In general, the pickup ion distributions, based on three.dimensional neutral exospheres, cannot be written in closed form, but can be computed numerically. They continue to reflect their source's spatial distributions in an implicit way. These ion distributions and their moments are applied to several bodies, including He(+) and Na(+) at the Moon, H(+2) and CH(+4) at Titan, and H+ at Venus. The best places to use these distributions are upstream of the Moon's surface, the ionopause of Titan, and the bow shock of Venus.

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

NASA Astrophysics Data System (ADS)

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

2006-07-01

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

Perturbative matching of continuum and lattice quasi-distributions

NASA Astrophysics Data System (ADS)

Ishikawa, Tomomi

2018-03-01

Matching of the quasi parton distribution functions between continuum and lattice is addressed using lattice perturbation theory specifically withWilson-type fermions. The matching is done for nonlocal quark bilinear operators with a straightWilson line in a spatial direction. We also investigate operator mixing in the renormalization and possible O(a) operators for the nonlocal operators based on a symmetry argument on lattice.

Web-services-based spatial decision support system to facilitate nuclear waste siting

NASA Astrophysics Data System (ADS)

Huang, L. Xinglai; Sheng, Grant

2006-10-01

The availability of spatial web services enables data sharing among managers, decision and policy makers and other stakeholders in much simpler ways than before and subsequently has created completely new opportunities in the process of spatial decision making. Though generally designed for a certain problem domain, web-services-based spatial decision support systems (WSDSS) can provide a flexible problem-solving environment to explore the decision problem, understand and refine problem definition, and generate and evaluate multiple alternatives for decision. This paper presents a new framework for the development of a web-services-based spatial decision support system. The WSDSS is comprised of distributed web services that either have their own functions or provide different geospatial data and may reside in different computers and locations. WSDSS includes six key components, namely: database management system, catalog, analysis functions and models, GIS viewers and editors, report generators, and graphical user interfaces. In this study, the architecture of a web-services-based spatial decision support system to facilitate nuclear waste siting is described as an example. The theoretical, conceptual and methodological challenges and issues associated with developing web services-based spatial decision support system are described.

Breakdown in the temporal and spatial organization of spontaneous brain activity during general anesthesia.

PubMed

Zhang, Jianfeng; Huang, Zirui; Chen, Yali; Zhang, Jun; Ghinda, Diana; Nikolova, Yuliya; Wu, Jinsong; Xu, Jianghui; Bai, Wenjie; Mao, Ying; Yang, Zhong; Duncan, Niall; Qin, Pengmin; Wang, Hao; Chen, Bing; Weng, Xuchu; Northoff, Georg

2018-05-01

Which temporal features that can characterize different brain states (i.e., consciousness or unconsciousness) is a fundamental question in the neuroscience of consciousness. Using resting-state functional magnetic resonance imaging (rs-fMRI), we investigated the spatial patterns of two temporal features: the long-range temporal correlations (LRTCs), measured by power-law exponent (PLE), and temporal variability, measured by standard deviation (SD) during wakefulness and anesthetic-induced unconsciousness. We found that both PLE and SD showed global reductions across the whole brain during anesthetic state comparing to wakefulness. Importantly, the relationship between PLE and SD was altered in anesthetic state, in terms of a spatial "decoupling." This decoupling was mainly driven by a spatial pattern alteration of the PLE, rather than the SD, in the anesthetic state. Our results suggest differential physiological grounds of PLE and SD and highlight the functional importance of the topographical organization of LRTCs in maintaining an optimal spatiotemporal configuration of the neural dynamics during normal level of consciousness. The central role of the spatial distribution of LRTCs, reflecting temporo-spatial nestedness, may support the recently introduced temporo-spatial theory of consciousness (TTC). © 2018 Wiley Periodicals, Inc.

Multi-scale variation in spatial heterogeneity for microbial community structure in an eastern Virginia agricultural field

NASA Technical Reports Server (NTRS)

Franklin, Rima B.; Mills, Aaron L.

2003-01-01

To better understand the distribution of soil microbial communities at multiple spatial scales, a survey was conducted to examine the spatial organization of community structure in a wheat field in eastern Virginia (USA). Nearly 200 soil samples were collected at a variety of separation distances ranging from 2.5 cm to 11 m. Whole-community DNA was extracted from each sample, and community structure was compared using amplified fragment length polymorphism (AFLP) DNA fingerprinting. Relative similarity was calculated between each pair of samples and compared using geostatistical variogram analysis to study autocorrelation as a function of separation distance. Spatial autocorrelation was found at scales ranging from 30 cm to more than 6 m, depending on the sampling extent considered. In some locations, up to four different correlation length scales were detected. The presence of nested scales of variability suggests that the environmental factors regulating the development of the communities in this soil may operate at different scales. Kriging was used to generate maps of the spatial organization of communities across the plot, and the results demonstrated that bacterial distributions can be highly structured, even within a habitat that appears relatively homogeneous at the plot and field scale. Different subsets of the microbial community were distributed differently across the plot, and this is thought to be due to the variable response of individual populations to spatial heterogeneity associated with soil properties. c2003 Federation of European Microbiological Societies. Published by Elsevier Science B.V. All rights reserved.

The significance of spatial variability of rainfall on streamflow: A synthetic analysis at the Upper Lee catchment, UK

NASA Astrophysics Data System (ADS)

Pechlivanidis, Ilias; McIntyre, Neil; Wheater, Howard

2017-04-01

Rainfall, one of the main inputs in hydrological modeling, is a highly heterogeneous process over a wide range of scales in space, and hence the ignorance of the spatial rainfall information could affect the simulated streamflow. Calibration of hydrological model parameters is rarely a straightforward task due to parameter equifinality and parameters' 'nature' to compensate for other uncertainties, i.e. structural and forcing input. In here, we analyse the significance of spatial variability of rainfall on streamflow as a function of catchment scale and type, and antecedent conditions using the continuous time, semi-distributed PDM hydrological model at the Upper Lee catchment, UK. The impact of catchment scale and type is assessed using 11 nested catchments ranging in scale from 25 to 1040 km2, and further assessed by artificially changing the catchment characteristics and translating these to model parameters with uncertainty using model regionalisation. Synthetic rainfall events are introduced to directly relate the change in simulated streamflow to the spatial variability of rainfall. Overall, we conclude that the antecedent catchment wetness and catchment type play an important role in controlling the significance of the spatial distribution of rainfall on streamflow. Results show a relationship between hydrograph characteristics (streamflow peak and volume) and the degree of spatial variability of rainfall for the impermeable catchments under dry antecedent conditions, although this decreases at larger scales; however this sensitivity is significantly undermined under wet antecedent conditions. Although there is indication that the impact of spatial rainfall on streamflow varies as a function of catchment scale, the variability of antecedent conditions between the synthetic catchments seems to mask this significance. Finally, hydrograph responses to different spatial patterns in rainfall depend on assumptions used for model parameter estimation and also the spatial variation in parameters indicating the need of an uncertainty framework in such investigation.

[Human body meridian spatial decision support system for clinical treatment and teaching of acupuncture and moxibustion].

PubMed

Wu, Dehua

2016-01-01

The spatial position and distribution of human body meridian are expressed limitedly in the decision support system (DSS) of acupuncture and moxibustion at present, which leads to the failure to give the effective quantitative analysis on the spatial range and the difficulty for the decision-maker to provide a realistic spatial decision environment. Focusing on the limit spatial expression in DSS of acupuncture and moxibustion, it was proposed that on the basis of the geographic information system, in association of DSS technology, the design idea was developed on the human body meridian spatial DSS. With the 4-layer service-oriented architecture adopted, the data center integrated development platform was taken as the system development environment. The hierarchical organization was done for the spatial data of human body meridian via the directory tree. The structured query language (SQL) server was used to achieve the unified management of spatial data and attribute data. The technologies of architecture, configuration and plug-in development model were integrated to achieve the data inquiry, buffer analysis and program evaluation of the human body meridian spatial DSS. The research results show that the human body meridian spatial DSS could reflect realistically the spatial characteristics of the spatial position and distribution of human body meridian and met the constantly changeable demand of users. It has the powerful spatial analysis function and assists with the scientific decision in clinical treatment and teaching of acupuncture and moxibustion. It is the new attempt to the informatization research of human body meridian.

Feasibility of automated dropsize distributions from holographic data using digital image processing techniques. [particle diameter measurement technique

NASA Technical Reports Server (NTRS)

Feinstein, S. P.; Girard, M. A.

1979-01-01

An automated technique for measuring particle diameters and their spatial coordinates from holographic reconstructions is being developed. Preliminary tests on actual cold-flow holograms of impinging jets indicate that a suitable discriminant algorithm consists of a Fourier-Gaussian noise filter and a contour thresholding technique. This process identifies circular as well as noncircular objects. The desired objects (in this case, circular or possibly ellipsoidal) are then selected automatically from the above set and stored with their parametric representations. From this data, dropsize distributions as a function of spatial coordinates can be generated and combustion effects due to hardware and/or physical variables studied.

Chimera proteins with affinity for membranes and microtubule tips polarize in the membrane of fission yeast cells.

PubMed

Recouvreux, Pierre; Sokolowski, Thomas R; Grammoustianou, Aristea; ten Wolde, Pieter Rein; Dogterom, Marileen

2016-02-16

Cell polarity refers to a functional spatial organization of proteins that is crucial for the control of essential cellular processes such as growth and division. To establish polarity, cells rely on elaborate regulation networks that control the distribution of proteins at the cell membrane. In fission yeast cells, a microtubule-dependent network has been identified that polarizes the distribution of signaling proteins that restricts growth to cell ends and targets the cytokinetic machinery to the middle of the cell. Although many molecular components have been shown to play a role in this network, it remains unknown which molecular functionalities are minimally required to establish a polarized protein distribution in this system. Here we show that a membrane-binding protein fragment, which distributes homogeneously in wild-type fission yeast cells, can be made to concentrate at cell ends by attaching it to a cytoplasmic microtubule end-binding protein. This concentration results in a polarized pattern of chimera proteins with a spatial extension that is very reminiscent of natural polarity patterns in fission yeast. However, chimera levels fluctuate in response to microtubule dynamics, and disruption of microtubules leads to disappearance of the pattern. Numerical simulations confirm that the combined functionality of membrane anchoring and microtubule tip affinity is in principle sufficient to create polarized patterns. Our chimera protein may thus represent a simple molecular functionality that is able to polarize the membrane, onto which additional layers of molecular complexity may be built to provide the temporal robustness that is typical of natural polarity patterns.

Distribution of runup heights of the December 26, 2004 tsunami in the Indian Ocean

NASA Astrophysics Data System (ADS)

Choi, Byung Ho; Hong, Sung Jin; Pelinovsky, Efim

2006-07-01

A massive earthquake with magnitude 9.3 occurred on December 26, 2004 off the northern Sumatra generated huge tsunami waves affected many coastal countries in the Indian Ocean. A number of field surveys have been performed after this tsunami event; in particular, several surveys in the south/east coast of India, Andaman and Nicobar Islands, Sri Lanka, Sumatra, Malaysia, and Thailand have been organized by the Korean Society of Coastal and Ocean Engineers from January to August 2005. Spatial distribution of the tsunami runup is used to analyze the distribution function of the wave heights on different coasts. Theoretical interpretation of this distribution is associated with random coastal bathymetry and coastline led to the log-normal functions. Observed data also are in a very good agreement with log-normal distribution confirming the important role of the variable ocean bathymetry in the formation of the irregular wave height distribution along the coasts.

Study on light scattering characterization for polishing surface of optical elements

NASA Astrophysics Data System (ADS)

Zhang, Yingge; Tian, Ailing; Wang, Chunhui; Wang, Dasen; Liu, Weiguo

2017-02-01

Based on the principle of bidirectional reflectance distribution function (BRDF), the relationship between the surface roughness and the spatial scattering distribution of the optical elements were studied. First, a series of optical components with different surface roughness was obtained by the traditional polishing processing, and measured by Talysurf CCI 3000. Secondly, the influences of different factors on the scattering characteristics were simulated and analyzed, such as different surface roughness, incident wavelength and incident angle. Finally, the experimental device was built, and the spatial distribution of scattered light was measured with the different conditions, and then the data curve variation was analyzed. It was shown that the experimental method was reliable by comparing the simulation and experimental results. Base on this to know, many studies on light scattering characteristics for optical element polishing surface can try later.

Limited spatial response to direct predation risk by African herbivores following predator reintroduction.

PubMed

Davies, Andrew B; Tambling, Craig J; Kerley, Graham I H; Asner, Gregory P

2016-08-01

Predators affect ecosystems not only through direct mortality of prey, but also through risk effects on prey behavior, which can exert strong influences on ecosystem function and prey fitness. However, how functionally different prey species respond to predation risk and how prey strategies vary across ecosystems and in response to predator reintroduction are poorly understood. We investigated the spatial distributions of six African herbivores varying in foraging strategy and body size in response to environmental factors and direct predation risk by recently reintroduced lions in the thicket biome of the Addo Elephant National Park, South Africa, using camera trap surveys, GPS telemetry, kill site locations and Light Detection and Ranging. Spatial distributions of all species, apart from buffalo, were driven primarily by environmental factors, with limited responses to direct predation risk. Responses to predation risk were instead indirect, with species distributions driven by environmental factors, and diel patterns being particularly pronounced. Grazers were more responsive to the measured variables than browsers, with more observations in open areas. Terrain ruggedness was a stronger predictor of browser distributions than was vegetation density. Buffalo was the only species to respond to predator encounter risk, avoiding areas with higher lion utilization. Buffalo therefore behaved in similar ways to when lions were absent from the study area. Our results suggest that direct predation risk effects are relatively weak when predator densities are low and the time since reintroduction is short and emphasize the need for robust, long-term monitoring of predator reintroductions to place such events in the broader context of predation risk effects.

Exploring the parahippocampal cortex response to high and low spatial frequency spaces.

PubMed

Zeidman, Peter; Mullally, Sinéad L; Schwarzkopf, Dietrich Samuel; Maguire, Eleanor A

2012-05-30

The posterior parahippocampal cortex (PHC) supports a range of cognitive functions, in particular scene processing. However, it has recently been suggested that PHC engagement during functional MRI simply reflects the representation of three-dimensional local space. If so, PHC should respond to space in the absence of scenes, geometric layout, objects or contextual associations. It has also been reported that PHC activation may be influenced by low-level visual properties of stimuli such as spatial frequency. Here, we tested whether PHC was responsive to the mere sense of space in highly simplified stimuli, and whether this was affected by their spatial frequency distribution. Participants were scanned using functional MRI while viewing depictions of simple three-dimensional space, and matched control stimuli that did not depict a space. Half the stimuli were low-pass filtered to ascertain the impact of spatial frequency. We observed a significant interaction between space and spatial frequency in bilateral PHC. Specifically, stimuli depicting space (more than nonspatial stimuli) engaged the right PHC when they featured high spatial frequencies. In contrast, the interaction in the left PHC did not show a preferential response to space. We conclude that a simple depiction of three-dimensional space that is devoid of objects, scene layouts or contextual associations is sufficient to robustly engage the right PHC, at least when high spatial frequencies are present. We suggest that coding for the presence of space may be a core function of PHC, and could explain its engagement in a range of tasks, including scene processing, where space is always present.

Spatial distribution of planktonic bacterial and archaeal communities in the upper section of the tidal reach in Yangtze River

PubMed Central

Fan, Limin; Song, Chao; Meng, Shunlong; Qiu, Liping; Zheng, Yao; Wu, Wei; Qu, Jianhong; Li, Dandan; Zhang, Cong; Hu, Gengdong; Chen, Jiazhang

2016-01-01

Bacterioplankton and archaeaplankton communities play key roles in the biogeochemical processes of water, and they may be affected by many factors. In this study, we used high-throughput 16S rRNA gene sequencing to profile planktonic bacterial and archaeal community compositions in the upper section of the tidal reach in Yangtze River. We found that the predominant bacterial phyla in this river section were Proteobacteria, Firmicutes, and Actinobacteria, whereas the predominant archaeal classes were Halobacteria, Methanomicrobia, and unclassified Euryarchaeota. Additionally, the bacterial and archaeal community compositions, richnesses, functional profiles, and ordinations were affected by the spatial heterogeneity related to the concentration changes of sulphate or nitrate. Notably, the bacterial community was more sensitive than the archaeal community to changes in the spatial characteristics of this river section. These findings provide important insights into the distributions of bacterial and archaeal communities in natural water habitats. PMID:27966673

Evaluating the impact of sea surface temperature (SST) on spatial distribution of chlorophyll-a concentration in the East China Sea

NASA Astrophysics Data System (ADS)

Ji, Chenxu; Zhang, Yuanzhi; Cheng, Qiuming; Tsou, JinYeu; Jiang, Tingchen; Liang, X. San

2018-06-01

In this study, we analyze spatial and temporal sea surface temperature (SST) and chlorophylla (Chl-a) concentration in the East China Sea (ECS) during the period 2003-2016. Level 3 (4 km) monthly SST and Chl-a data from the Moderate Resolution Imaging Spectroradiometer Satellite (MODIS-Aqua) were reconstructed using the data interpolation empirical orthogonal function (DINEOF) method and used to evaluated the relationship between the two variables. The approaches employed included correlation analysis, regression analysis, and so forth. Our results show that certain strong oceanic SSTs affect Chl-a concentration, with particularly high correlation seen in the coastal area of Jiangsu and Zhejiang provinces. The mean temperature of the high correlated region was 18.67 °C. This finding may suggest that the SST has an important impact on the spatial distribution of Chl-a concentration in the ECS.

Insights into a spatially embedded social network from a large-scale snowball sample

NASA Astrophysics Data System (ADS)

Illenberger, J.; Kowald, M.; Axhausen, K. W.; Nagel, K.

2011-12-01

Much research has been conducted to obtain insights into the basic laws governing human travel behaviour. While the traditional travel survey has been for a long time the main source of travel data, recent approaches to use GPS data, mobile phone data, or the circulation of bank notes as a proxy for human travel behaviour are promising. The present study proposes a further source of such proxy-data: the social network. We collect data using an innovative snowball sampling technique to obtain details on the structure of a leisure-contacts network. We analyse the network with respect to its topology, the individuals' characteristics, and its spatial structure. We further show that a multiplication of the functions describing the spatial distribution of leisure contacts and the frequency of physical contacts results in a trip distribution that is consistent with data from the Swiss travel survey.

Spatial distribution of planktonic bacterial and archaeal communities in the upper section of the tidal reach in Yangtze River

NASA Astrophysics Data System (ADS)

Fan, Limin; Song, Chao; Meng, Shunlong; Qiu, Liping; Zheng, Yao; Wu, Wei; Qu, Jianhong; Li, Dandan; Zhang, Cong; Hu, Gengdong; Chen, Jiazhang

2016-12-01

Bacterioplankton and archaeaplankton communities play key roles in the biogeochemical processes of water, and they may be affected by many factors. In this study, we used high-throughput 16S rRNA gene sequencing to profile planktonic bacterial and archaeal community compositions in the upper section of the tidal reach in Yangtze River. We found that the predominant bacterial phyla in this river section were Proteobacteria, Firmicutes, and Actinobacteria, whereas the predominant archaeal classes were Halobacteria, Methanomicrobia, and unclassified Euryarchaeota. Additionally, the bacterial and archaeal community compositions, richnesses, functional profiles, and ordinations were affected by the spatial heterogeneity related to the concentration changes of sulphate or nitrate. Notably, the bacterial community was more sensitive than the archaeal community to changes in the spatial characteristics of this river section. These findings provide important insights into the distributions of bacterial and archaeal communities in natural water habitats.

Visualizing Distributions from Multi-Return Lidar Data to Understand Forest Structure

NASA Technical Reports Server (NTRS)

Kao, David L.; Kramer, Marc; Luo, Alison; Dungan, Jennifer; Pang, Alex

2004-01-01

Spatially distributed probability density functions (pdfs) are becoming relevant to the Earth scientists and ecologists because of stochastic models and new sensors that provide numerous realizations or data points per unit area. One source of these data is from multi-return airborne lidar, a type of laser that records multiple returns for each pulse of light sent towards the ground. Data from multi-return lidar is a vital tool in helping us understand the structure of forest canopies over large extents. This paper presents several new visualization tools that allow scientists to rapidly explore, interpret and discover characteristic distributions within the entire spatial field. The major contribution from-this work is a paradigm shift which allows ecologists to think of and analyze their data in terms of the distribution. This provides a way to reveal information on the modality and shape of the distribution previously not possible. The tools allow the scientists to depart from traditional parametric statistical analyses and to associate multimodal distribution characteristics to forest structures. Examples are given using data from High Island, southeast Alaska.

Estimation of Snow Parameters Based on Passive Microwave Remote Sensing and Meteorological Information

NASA Technical Reports Server (NTRS)

Tsang, Leung; Hwang, Jenq-Neng

1996-01-01

A method to incorporate passive microwave remote sensing measurements within a spatially distributed snow hydrology model to provide estimates of the spatial distribution of Snow Water Equivalent (SWE) as a function of time is implemented. The passive microwave remote sensing measurements are at 25 km resolution. However, in mountain regions the spatial variability of SWE over a 25 km footprint is large due to topographic influences. On the other hand, the snow hydrology model has built-in topographic information and the capability to estimate SWE at a 1 km resolution. In our work, the snow hydrology SWE estimates are updated and corrected using SSM/I passive microwave remote sensing measurements. The method is applied to the Upper Rio Grande River Basin in the mountains of Colorado. The change in prediction of SWE from hydrology modeling with and without updating is compared with measurements from two SNOTEL sites in and near the basin. The results indicate that the method incorporating the remote sensing measurements into the hydrology model is able to more closely estimate the temporal evolution of the measured values of SWE as a function of time.

The Area Coverage of Geophysical Fields as a Function of Sensor Field-of View

NASA Technical Reports Server (NTRS)

Key, Jeffrey R.

1994-01-01

In many remote sensing studies of geophysical fields such as clouds, land cover, or sea ice characteristics, the fractional area coverage of the field in an image is estimated as the proportion of pixels that have the characteristic of interest (i.e., are part of the field) as determined by some thresholding operation. The effect of sensor field-of-view on this estimate is examined by modeling the unknown distribution of subpixel area fraction with the beta distribution, whose two parameters depend upon the true fractional area coverage, the pixel size, and the spatial structure of the geophysical field. Since it is often not possible to relate digital number, reflectance, or temperature to subpixel area fraction, the statistical models described are used to determine the effect of pixel size and thresholding operations on the estimate of area fraction for hypothetical geophysical fields. Examples are given for simulated cumuliform clouds and linear openings in sea ice, whose spatial structures are described by an exponential autocovariance function. It is shown that the rate and direction of change in total area fraction with changing pixel size depends on the true area fraction, the spatial structure, and the thresholding operation used.

Role of the Euclidean signature in lattice calculations of quasidistributions and other nonlocal matrix elements

NASA Astrophysics Data System (ADS)

Briceño, Raúl A.; Hansen, Maxwell T.; Monahan, Christopher J.

2017-07-01

Lattice quantum chromodynamics (QCD) provides the only known systematic, nonperturbative method for first-principles calculations of nucleon structure. However, for quantities such as light-front parton distribution functions (PDFs) and generalized parton distributions (GPDs), the restriction to Euclidean time prevents direct calculation of the desired observable. Recently, progress has been made in relating these quantities to matrix elements of spatially nonlocal, zero-time operators, referred to as quasidistributions. Still, even for these time-independent matrix elements, potential subtleties have been identified in the role of the Euclidean signature. In this work, we investigate the analytic behavior of spatially nonlocal correlation functions and demonstrate that the matrix elements obtained from Euclidean lattice QCD are identical to those obtained using the Lehmann-Symanzik-Zimmermann reduction formula in Minkowski space. After arguing the equivalence on general grounds, we also show that it holds in a perturbative calculation, where special care is needed to identify the lattice prediction. Finally we present a proof of the uniqueness of the matrix elements obtained from Minkowski and Euclidean correlation functions to all order in perturbation theory.

Role of the Euclidean signature in lattice calculations of quasidistributions and other nonlocal matrix elements

DOE PAGES

Briceno, Raul A.; Hansen, Maxwell T.; Monahan, Christopher J.

2017-07-11

Lattice quantum chromodynamics (QCD) provides the only known systematic, nonperturbative method for first-principles calculations of nucleon structure. However, for quantities such as light-front parton distribution functions (PDFs) and generalized parton distributions (GPDs), the restriction to Euclidean time prevents direct calculation of the desired observable. Recently, progress has been made in relating these quantities to matrix elements of spatially nonlocal, zero-time operators, referred to as quasidistributions. Still, even for these time-independent matrix elements, potential subtleties have been identified in the role of the Euclidean signature. In this work, we investigate the analytic behavior of spatially nonlocal correlation functions and demonstrate thatmore » the matrix elements obtained from Euclidean lattice QCD are identical to those obtained using the Lehmann-Symanzik-Zimmermann reduction formula in Minkowski space. After arguing the equivalence on general grounds, we also show that it holds in a perturbative calculation, where special care is needed to identify the lattice prediction. Lastly, we present a proof of the uniqueness of the matrix elements obtained from Minkowski and Euclidean correlation functions to all order in perturbation theory.« less

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

Briceno, Raul A.; Hansen, Maxwell T.; Monahan, Christopher J.

Lattice quantum chromodynamics (QCD) provides the only known systematic, nonperturbative method for first-principles calculations of nucleon structure. However, for quantities such as light-front parton distribution functions (PDFs) and generalized parton distributions (GPDs), the restriction to Euclidean time prevents direct calculation of the desired observable. Recently, progress has been made in relating these quantities to matrix elements of spatially nonlocal, zero-time operators, referred to as quasidistributions. Still, even for these time-independent matrix elements, potential subtleties have been identified in the role of the Euclidean signature. In this work, we investigate the analytic behavior of spatially nonlocal correlation functions and demonstrate thatmore » the matrix elements obtained from Euclidean lattice QCD are identical to those obtained using the Lehmann-Symanzik-Zimmermann reduction formula in Minkowski space. After arguing the equivalence on general grounds, we also show that it holds in a perturbative calculation, where special care is needed to identify the lattice prediction. Lastly, we present a proof of the uniqueness of the matrix elements obtained from Minkowski and Euclidean correlation functions to all order in perturbation theory.« less

The role of reserves and anthropogenic elements for functional connectivity and resilience of ephemeral habitats

USGS Publications Warehouse

Uden, Daniel R.; Hellman, Michelle L.; Angeler, David G.; Allen, Craig R.

2014-01-01

Ecological reserves provide important wildlife habitat in many landscapes, and the functional connectivity of reserves and other suitable habitat patches is crucial for the persistence and resilience of spatially structured populations. To maintain or increase connectivity at spatial scales larger than individual patches, conservation actions may focus on creating and maintaining reserves and/or influencing management on non-reserves. Using a graph-theoretic approach, we assessed the functional connectivity and spatial distribution of wetlands in the Rainwater Basin of Nebraska, USA, an intensively cultivated agricultural matrix, at four assumed, but ecologically realistic, anuran dispersal distances. We compared connectivity in the current landscape to the historical landscape and putative future landscapes, and evaluated the importance of individual and aggregated reserve and non-reserve wetlands for maintaining connectivity. Connectivity was greatest in the historical landscape, where wetlands were also the most densely distributed. The construction of irrigation reuse pits for water storage has maintained connectivity in the current landscape by replacing destroyed wetlands, but these pits likely provide suboptimal habitat. Also, because there are fewer total wetlands (i.e., wetlands and irrigation reuse pits) in the current landscape than the historical landscape, and because the distribution of current wetlands is less clustered than that of historical wetlands, larger and longer dispersing, sometimes nonnative species may be favored over smaller, shorter dispersing species of conservation concern. Because of their relatively low number, wetland reserves do not affect connectivity as greatly as non-reserve wetlands or irrigation reuse pits; however, they likely provide the highest quality anuran habitat. To improve future levels of resilience in this wetland habitat network, management could focus on continuing to improve the conservation status of non-reserve wetlands, restoring wetlands at spatial scales that promote movements of shorter dispersing species, and further scrutinizing irrigation reuse pit removal by considering effects on functional connectivity for anurans, an emblematic and threatened group of organisms. However, broader conservation plans will need to give consideration to other wetland-dependent species, incorporate invasive species management, and address additional challenges arising from global change in social-ecological systems like the Rainwater Basin.

Enhancing Spatial Attention and Working Memory in Younger and Older Adults

PubMed Central

Rolle, Camarin E.; Anguera, Joaquin A.; Skinner, Sasha N.; Voytek, Bradley; Gazzaley, Adam

2018-01-01

Daily experiences demand both focused and broad allocation of attention for us to interact efficiently with our complex environments. Many types of attention have shown age-related decline, although there is also evidence that such deficits may be remediated with cognitive training. However, spatial attention abilities have shown inconsistent age-related differences, and the extent of potential enhancement of these abilities remains unknown. Here, we assessed spatial attention in both healthy younger and older adults and trained this ability in both age groups for 5 hr over the course of 2 weeks using a custom-made, computerized mobile training application. We compared training-related gains on a spatial attention assessment and spatial working memory task to age-matched controls who engaged in expectancy-matched, active placebo computerized training. Age-related declines in spatial attention abilities were observed regardless of task difficulty. Spatial attention training led to improved focused and distributed attention abilities as well as improved spatial working memory in both younger and older participants. No such improvements were observed in either of the age-matched control groups. Note that these findings were not a function of improvements in simple response time, as basic motoric function did not change after training. Furthermore, when using change in simple response time as a covariate, all findings remained significant. These results suggest that spatial attention training can lead to enhancements in spatial working memory regardless of age. PMID:28654361

Enhancing Spatial Attention and Working Memory in Younger and Older Adults.

PubMed

Rolle, Camarin E; Anguera, Joaquin A; Skinner, Sasha N; Voytek, Bradley; Gazzaley, Adam

2017-09-01

Daily experiences demand both focused and broad allocation of attention for us to interact efficiently with our complex environments. Many types of attention have shown age-related decline, although there is also evidence that such deficits may be remediated with cognitive training. However, spatial attention abilities have shown inconsistent age-related differences, and the extent of potential enhancement of these abilities remains unknown. Here, we assessed spatial attention in both healthy younger and older adults and trained this ability in both age groups for 5 hr over the course of 2 weeks using a custom-made, computerized mobile training application. We compared training-related gains on a spatial attention assessment and spatial working memory task to age-matched controls who engaged in expectancy-matched, active placebo computerized training. Age-related declines in spatial attention abilities were observed regardless of task difficulty. Spatial attention training led to improved focused and distributed attention abilities as well as improved spatial working memory in both younger and older participants. No such improvements were observed in either of the age-matched control groups. Note that these findings were not a function of improvements in simple response time, as basic motoric function did not change after training. Furthermore, when using change in simple response time as a covariate, all findings remained significant. These results suggest that spatial attention training can lead to enhancements in spatial working memory regardless of age.

Structure and Dynamics of Hydroxyl-Functionalized Protic Ammonium Carboxylate Ionic Liquids.

PubMed

Thummuru, Dhileep Nagi Reddy; Mallik, Bhabani S

2017-10-26

We performed classical molecular dynamics simulations to investigate the structure and dynamics of protic ionic liquids, 2-hydroxy ethylammonium acetate, ethylammonium hydroxyacetate, and 2-hydroxyethylammonium hydroxyacetate at ambient conditions. Structural properties such as density, radial distribution functions, spatial distribution functions, and structure factors have been calculated. Dynamic properties such as mean square displacements, as well as residence and hydrogen bond dynamics have also been calculated. Hydrogen bond lifetimes and residence times change with the addition of hydroxyl groups. We observe that when a hydroxyl group is present on the cation, dynamics become very slow and it forms a strong hydrogen bond with carboxylate oxygen atoms of the anion. The hydroxyl functionalized ILs show more dynamic diversity than structurally similar ILs.

Ectomycorrhizal-dominated boreal and tropical forests have distinct fungal communities, but analogous spatial patterns across soil horizons.

PubMed

McGuire, Krista L; Allison, Steven D; Fierer, Noah; Treseder, Kathleen K

2013-01-01

Fungi regulate key nutrient cycling processes in many forest ecosystems, but their diversity and distribution within and across ecosystems are poorly understood. Here, we examine the spatial distribution of fungi across a boreal and tropical ecosystem, focusing on ectomycorrhizal fungi. We analyzed fungal community composition across litter (organic horizons) and underlying soil horizons (0-20 cm) using 454 pyrosequencing and clone library sequencing. In both forests, we found significant clustering of fungal communities by site and soil horizons with analogous patterns detected by both sequencing technologies. Free-living saprotrophic fungi dominated the recently-shed leaf litter and ectomycorrhizal fungi dominated the underlying soil horizons. This vertical pattern of fungal segregation has also been found in temperate and European boreal forests, suggesting that these results apply broadly to ectomycorrhizal-dominated systems, including tropical rain forests. Since ectomycorrhizal and free-living saprotrophic fungi have different influences on soil carbon and nitrogen dynamics, information on the spatial distribution of these functional groups will improve our understanding of forest nutrient cycling.

Spatiotemporal dynamics and optical vortices in a photorefractive phase-conjugate resonator

NASA Technical Reports Server (NTRS)

Liu, Siuying Raymond; Indebetouw, Guy

1992-01-01

A truncated modal expansion approach is used to study the spatiotemporal dynamics of a phase-conjugate resonator as a function of Bragg detuning. The numerical results reveal a rich variety of behaviors. Emphasis is given to the spatial distribution of optical vortices, their trajectories and their relationship to the beam's spatial coherence. The limitations of the model are discussed and experimental results are presented for comparison with the model's predictions and assessment of its soundness.

GIS-based regionalized life cycle assessment: how big is small enough? Methodology and case study of electricity generation.

PubMed

Mutel, Christopher L; Pfister, Stephan; Hellweg, Stefanie

2012-01-17

We describe a new methodology for performing regionalized life cycle assessment and systematically choosing the spatial scale of regionalized impact assessment methods. We extend standard matrix-based calculations to include matrices that describe the mapping from inventory to impact assessment spatial supports. Uncertainty in inventory spatial data is modeled using a discrete spatial distribution function, which in a case study is derived from empirical data. The minimization of global spatial autocorrelation is used to choose the optimal spatial scale of impact assessment methods. We demonstrate these techniques on electricity production in the United States, using regionalized impact assessment methods for air emissions and freshwater consumption. Case study results show important differences between site-generic and regionalized calculations, and provide specific guidance for future improvements of inventory data sets and impact assessment methods.

Landscape-level movement patterns by lions in western Serengeti: comparing the influence of inter-specific competitors, habitat attributes and prey availability.

PubMed

Kittle, Andrew M; Bukombe, John K; Sinclair, Anthony R E; Mduma, Simon A R; Fryxell, John M

2016-01-01

Where apex predators move on the landscape influences ecosystem structure and function and is therefore key to effective landscape-level management and species-specific conservation. However the factors underlying predator distribution patterns within functional ecosystems are poorly understood. Predator movement should be sensitive to the spatial patterns of inter-specific competitors, spatial variation in prey density, and landscape attributes that increase individual prey vulnerability. We investigated the relative role of these fundamental factors on seasonal resource utilization by a globally endangered apex carnivore, the African lion (Panthera leo) in Tanzania's Serengeti National Park. Lion space use was represented by novel landscape-level, modified utilization distributions (termed "localized density distributions") created from telemetry relocations of individual lions from multiple neighbouring prides. Spatial patterns of inter-specific competitors were similarly determined from telemetry re-locations of spotted hyenas (Crocuta crocuta), this system's primary competitor for lions; prey distribution was derived from 18 months of detailed census data; and remote sensing data was used to represent relevant habitat attributes. Lion space use was consistently influenced by landscape attributes that increase individual prey vulnerability to predation. Wet season activity, when available prey were scarce, was concentrated near embankments, which provide ambush opportunities, and dry season activity, when available prey were abundant, near remaining water sources where prey occurrence is predictable. Lion space use patterns were positively associated with areas of high prey biomass, but only in the prey abundant dry season. Finally, at the broad scale of this analysis, lion and hyena space use was positively correlated in the comparatively prey-rich dry season and unrelated in the wet season, suggesting lion movement was unconstrained by the spatial patterns of their main inter-specific competitors. The availability of potential prey and vulnerability of that prey to predation both motivate lion movement decisions, with their relative importance apparently mediated by overall prey abundance. With practical and theoretical implications, these results suggest that while top carnivores are consistently cognizant of how landscape features influence individual prey vulnerability, they also adopt a flexible approach to range use by adjusting spatial behaviour according to fluctuations in local prey abundance.

Stars and Stripes in the Cerebellar Cortex: A Voltage Sensitive Dye Study

PubMed Central

Rokni, Dan; Llinas, Rodolfo; Yarom, Yosef

2007-01-01

The lattice-like structure of the cerebellar cortex and its anatomical organization in two perpendicular axes provided the foundations for many theories of cerebellar function. However, the functional organization does not always match the anatomical organization. Thus direct measurement of the functional organization is central to our understanding of cerebellar processing. Here we use voltage sensitive dye imaging in the isolated cerebellar preparation to characterize the spatio-temporal organization of the climbing and mossy fiber (MF) inputs to the cerebellar cortex. Spatial and temporal parameters were used to develop reliable criteria to distinguish climbing fiber (CF) responses from MF responses. CF activation excited postsynaptic neurons along a parasagittal cortical band. These responses were composed of slow (∼25 ms), monophasic depolarizing signals. Neither the duration nor the spatial distribution of CF responses were affected by inhibition. Activation of MF generated responses that were organized in radial patches, and were composed of a fast (∼5 ms) depolarizing phase followed by a prolonged (∼100 ms) negative wave. Application of a GABAA blocker eliminated the hyperpolarizing phase and prolonged the depolarizing phase, but did not affect the spatial distribution of the response, thus suggesting that it is not the inhibitory system that is responsible for the inability of the MF input to generate beams of activity that propagate along the parallel fiber system. PMID:18958242

A Molecular Investigation of Soil Organic Carbon Composition, Variability, and Spatial Distribution Across an Alpine Catchment

NASA Astrophysics Data System (ADS)

Hsu, H. T.; Lawrence, C. R.; Winnick, M.; Druhan, J. L.; Williams, K. H.; Maher, K.; Rainaldi, G. R.; McCormick, M. E.

2016-12-01

The cycling of carbon through soils is one of the least understood aspects of the global carbon cycle and represents a key uncertainty in the prediction of land-surface response to global warming. Thus, there is an urgent need for advanced characterization of soil organic carbon (SOC) to develop and evaluate a new generation of soil carbon models. We hypothesize that shifts in SOC composition and spatial distribution as a function of soil depth can be used to constrain rates of transformation between the litter layer and the deeper subsoil (extending to a depth of approximately 1 m). To evaluate the composition and distribution of SOC, we collected soil samples from East River, a shale-dominated watershed near Crested Butte, CO, and characterized relative changes in SOC species as a function of depth using elemental analysis (EA), Fourier transform infrared spectroscopy (FT-IR) and bulk C X-ray absorption spectroscopy (XAS). Our results show that total organic carbon (TOC) decreases with depth, and high total inorganic carbon (TIC) content was found in deeper soils (after 75 cm), a characteristic of the bedrock (shale). The distribution of aliphatic C relative to the parent material generally decreases with depth and that polysaccharide can be a substantial component of SOC at various depths. On the other hand, the relative distribution of aromatic C, traditionally viewed as recalcitrant, only makes up a very small part of SOC regardless of depth. These observations confirm that molecular structure is not the only determinant of SOC turnover rate. To study other contributors to SOC decomposition, we studied changes in the spatial correlation of SOC and minerals using X-ray fluorescence spectroscopy (XRF) and scanning transmission X-ray microscopy (STXM). We found that aromatics mostly locate on the surface of small soil aggregates (1-10 μm). Polysaccharides and proteins, both viewed as labile traditionally, are more evenly distributed over the interior of the particles, which could limit microbial access and thus decrease decomposition rate. The speciation and spatial distribution results can be compared to field-measured CO2-fluxes, soil moisture, and radiocarbon data to assess the factors that control SOC turnover rates in different environments across the catchment and enhance the development of SOC models.

Use of multiple functional traits of protozoa for bioassessment of marine pollution.

PubMed

Zhong, Xiaoxiao; Xu, Guangjian; Xu, Henglong

2017-06-30

Ecological parameters based on multiply functional traits have many advantages for monitoring programs by reducing "signal to noise" ratios of observed species data. To identify potential indicators for bioassessment of marine pollution in function space, the functional patterns of protozoan communities and relationships with environmental changes were studied in coastal waters of the Yellow Sea during a 1-year period. The results showed that: (1) the spatial variability in functional trait distributions of the protozoa was significantly associated with changes in environmental variables, especially chemical oxygen demand (COD) and nutrients on spatial scale; (2) the functional traits, especially food resources and feeding type, were significantly correlated with COD and nutrients; and (3) the functional diversity indices were generally related to nutrients or COD. Based on the results, we suggest that the functional traits and diversity indices of protozoan communities may be used as more effective indicators for bioassessment of marine pollution. Copyright © 2017 Elsevier Ltd. All rights reserved.

Detection of Spatially Unresolved (Nominally Sub-Pixel) Submerged and Surface Targets Using Hyperspectral Data

DTIC Science & Technology

2012-09-01

Feasibility (MT Modeling ) a. Continuum of mixture distributions interpolated b. Mixture infeasibilities calculated for each pixel c. Valid detections...Visible/Infrared Imaging Spectrometer BRDF Bidirectional Reflectance Distribution Function CASI Compact Airborne Spectrographic Imager CCD...filtering (MTMF), and was designed by Healey and Slater (1999) to use “a physical model to generate the set of sensor spectra for a target that will be

Genome-wide transcriptome study in wheat identified candidate genes related to processing quality, majority of them showing interaction (quality x development) and having temporal and spatial distributions.

PubMed

Singh, Anuradha; Mantri, Shrikant; Sharma, Monica; Chaudhury, Ashok; Tuli, Rakesh; Roy, Joy

2014-01-16

The cultivated bread wheat (Triticum aestivum L.) possesses unique flour quality, which can be processed into many end-use food products such as bread, pasta, chapatti (unleavened flat bread), biscuit, etc. The present wheat varieties require improvement in processing quality to meet the increasing demand of better quality food products. However, processing quality is very complex and controlled by many genes, which have not been completely explored. To identify the candidate genes whose expressions changed due to variation in processing quality and interaction (quality x development), genome-wide transcriptome studies were performed in two sets of diverse Indian wheat varieties differing for chapatti quality. It is also important to understand the temporal and spatial distributions of their expressions for designing tissue and growth specific functional genomics experiments. Gene-specific two-way ANOVA analysis of expression of about 55 K transcripts in two diverse sets of Indian wheat varieties for chapatti quality at three seed developmental stages identified 236 differentially expressed probe sets (10-fold). Out of 236, 110 probe sets were identified for chapatti quality. Many processing quality related key genes such as glutenin and gliadins, puroindolines, grain softness protein, alpha and beta amylases, proteases, were identified, and many other candidate genes related to cellular and molecular functions were also identified. The ANOVA analysis revealed that the expression of 56 of 110 probe sets was involved in interaction (quality x development). Majority of the probe sets showed differential expression at early stage of seed development i.e. temporal expression. Meta-analysis revealed that the majority of the genes expressed in one or a few growth stages indicating spatial distribution of their expressions. The differential expressions of a few candidate genes such as pre-alpha/beta-gliadin and gamma gliadin were validated by RT-PCR. Therefore, this study identified several quality related key genes including many other genes, their interactions (quality x development) and temporal and spatial distributions. The candidate genes identified for processing quality and information on temporal and spatial distributions of their expressions would be useful for designing wheat improvement programs for processing quality either by changing their expression or development of single nucleotide polymorphisms (SNPs) markers.

Genome-wide transcriptome study in wheat identified candidate genes related to processing quality, majority of them showing interaction (quality x development) and having temporal and spatial distributions

PubMed Central

2014-01-01

Background The cultivated bread wheat (Triticum aestivum L.) possesses unique flour quality, which can be processed into many end-use food products such as bread, pasta, chapatti (unleavened flat bread), biscuit, etc. The present wheat varieties require improvement in processing quality to meet the increasing demand of better quality food products. However, processing quality is very complex and controlled by many genes, which have not been completely explored. To identify the candidate genes whose expressions changed due to variation in processing quality and interaction (quality x development), genome-wide transcriptome studies were performed in two sets of diverse Indian wheat varieties differing for chapatti quality. It is also important to understand the temporal and spatial distributions of their expressions for designing tissue and growth specific functional genomics experiments. Results Gene-specific two-way ANOVA analysis of expression of about 55 K transcripts in two diverse sets of Indian wheat varieties for chapatti quality at three seed developmental stages identified 236 differentially expressed probe sets (10-fold). Out of 236, 110 probe sets were identified for chapatti quality. Many processing quality related key genes such as glutenin and gliadins, puroindolines, grain softness protein, alpha and beta amylases, proteases, were identified, and many other candidate genes related to cellular and molecular functions were also identified. The ANOVA analysis revealed that the expression of 56 of 110 probe sets was involved in interaction (quality x development). Majority of the probe sets showed differential expression at early stage of seed development i.e. temporal expression. Meta-analysis revealed that the majority of the genes expressed in one or a few growth stages indicating spatial distribution of their expressions. The differential expressions of a few candidate genes such as pre-alpha/beta-gliadin and gamma gliadin were validated by RT-PCR. Therefore, this study identified several quality related key genes including many other genes, their interactions (quality x development) and temporal and spatial distributions. Conclusions The candidate genes identified for processing quality and information on temporal and spatial distributions of their expressions would be useful for designing wheat improvement programs for processing quality either by changing their expression or development of single nucleotide polymorphisms (SNPs) markers. PMID:24433256

Clustering, randomness, and regularity in cloud fields. 4. Stratocumulus cloud fields

NASA Astrophysics Data System (ADS)

Lee, J.; Chou, J.; Weger, R. C.; Welch, R. M.

1994-07-01

To complete the analysis of the spatial distribution of boundary layer cloudiness, the present study focuses on nine stratocumulus Landsat scenes. The results indicate many similarities between stratocumulus and cumulus spatial distributions. Most notably, at full spatial resolution all scenes exhibit a decidedly clustered distribution. The strength of the clustering signal decreases with increasing cloud size; the clusters themselves consist of a few clouds (less than 10), occupy a small percentage of the cloud field area (less than 5%), contain between 20% and 60% of the cloud field population, and are randomly located within the scene. In contrast, stratocumulus in almost every respect are more strongly clustered than are cumulus cloud fields. For instance, stratocumulus clusters contain more clouds per cluster, occupy a larger percentage of the total area, and have a larger percentage of clouds participating in clusters than the corresponding cumulus examples. To investigate clustering at intermediate spatial scales, the local dimensionality statistic is introduced. Results obtained from this statistic provide the first direct evidence for regularity among large (>900 m in diameter) clouds in stratocumulus and cumulus cloud fields, in support of the inhibition hypothesis of Ramirez and Bras (1990). Also, the size compensated point-to-cloud cumulative distribution function statistic is found to be necessary to obtain a consistent description of stratocumulus cloud distributions. A hypothesis regarding the underlying physical mechanisms responsible for cloud clustering is presented. It is suggested that cloud clusters often arise from 4 to 10 triggering events localized within regions less than 2 km in diameter and randomly distributed within the cloud field. As the size of the cloud surpasses the scale of the triggering region, the clustering signal weakens and the larger cloud locations become more random.

Clustering, randomness, and regularity in cloud fields. 4: Stratocumulus cloud fields

NASA Technical Reports Server (NTRS)

Lee, J.; Chou, J.; Weger, R. C.; Welch, R. M.

1994-01-01

To complete the analysis of the spatial distribution of boundary layer cloudiness, the present study focuses on nine stratocumulus Landsat scenes. The results indicate many similarities between stratocumulus and cumulus spatial distributions. Most notably, at full spatial resolution all scenes exhibit a decidedly clustered distribution. The strength of the clustering signal decreases with increasing cloud size; the clusters themselves consist of a few clouds (less than 10), occupy a small percentage of the cloud field area (less than 5%), contain between 20% and 60% of the cloud field population, and are randomly located within the scene. In contrast, stratocumulus in almost every respect are more strongly clustered than are cumulus cloud fields. For instance, stratocumulus clusters contain more clouds per cluster, occupy a larger percentage of the total area, and have a larger percentage of clouds participating in clusters than the corresponding cumulus examples. To investigate clustering at intermediate spatial scales, the local dimensionality statistic is introduced. Results obtained from this statistic provide the first direct evidence for regularity among large (more than 900 m in diameter) clouds in stratocumulus and cumulus cloud fields, in support of the inhibition hypothesis of Ramirez and Bras (1990). Also, the size compensated point-to-cloud cumulative distribution function statistic is found to be necessary to obtain a consistent description of stratocumulus cloud distributions. A hypothesis regarding the underlying physical mechanisms responsible for cloud clustering is presented. It is suggested that cloud clusters often arise from 4 to 10 triggering events localized within regions less than 2 km in diameter and randomly distributed within the cloud field. As the size of the cloud surpasses the scale of the triggering region, the clustering signal weakens and the larger cloud locations become more random.

Statistical Considerations of Data Processing in Giovanni Online Tool

NASA Technical Reports Server (NTRS)

Suhung, Shen; Leptoukh, G.; Acker, J.; Berrick, S.

2005-01-01

The GES DISC Interactive Online Visualization and Analysis Infrastructure (Giovanni) is a web-based interface for the rapid visualization and analysis of gridded data from a number of remote sensing instruments. The GES DISC currently employs several Giovanni instances to analyze various products, such as Ocean-Giovanni for ocean products from SeaWiFS and MODIS-Aqua; TOMS & OM1 Giovanni for atmospheric chemical trace gases from TOMS and OMI, and MOVAS for aerosols from MODIS, etc. (http://giovanni.gsfc.nasa.gov) Foremost among the Giovanni statistical functions is data averaging. Two aspects of this function are addressed here. The first deals with the accuracy of averaging gridded mapped products vs. averaging from the ungridded Level 2 data. Some mapped products contain mean values only; others contain additional statistics, such as number of pixels (NP) for each grid, standard deviation, etc. Since NP varies spatially and temporally, averaging with or without weighting by NP will be different. In this paper, we address differences of various weighting algorithms for some datasets utilized in Giovanni. The second aspect is related to different averaging methods affecting data quality and interpretation for data with non-normal distribution. The present study demonstrates results of different spatial averaging methods using gridded SeaWiFS Level 3 mapped monthly chlorophyll a data. Spatial averages were calculated using three different methods: arithmetic mean (AVG), geometric mean (GEO), and maximum likelihood estimator (MLE). Biogeochemical data, such as chlorophyll a, are usually considered to have a log-normal distribution. The study determined that differences between methods tend to increase with increasing size of a selected coastal area, with no significant differences in most open oceans. The GEO method consistently produces values lower than AVG and MLE. The AVG method produces values larger than MLE in some cases, but smaller in other cases. Further studies indicated that significant differences between AVG and MLE methods occurred in coastal areas where data have large spatial variations and a log-bimodal distribution instead of log-normal distribution.

Intertidal habitat utilization patterns of birds in a Northeast Pacific estuary

EPA Science Inventory

A habitat-based framework is a practical method for developing models (or, ecological production functions, EPFs) to describe the spatial distribution of ecosystem services. To generate EPFs for Yaquina estuary, Oregon, USA, we compared bird use patterns among intertidal habitats...

Spatial and temporal study of nitrate concentration in groundwater by means of coregionalization

USGS Publications Warehouse

D'Agostino, V.; Greene, E.A.; Passarella, G.; Vurro, M.

1998-01-01

Spatial and temporal behavior of hydrochemical parameters in groundwater can be studied using tools provided by geostatistics. The cross-variogram can be used to measure the spatial increments between observations at two given times as a function of distance (spatial structure). Taking into account the existence of such a spatial structure, two different data sets (sampled at two different times), representing concentrations of the same hydrochemical parameter, can be analyzed by cokriging in order to reduce the uncertainty of the estimation. In particular, if one of the two data sets is a subset of the other (that is, an undersampled set), cokriging allows us to study the spatial distribution of the hydrochemical parameter at that time, while also considering the statistical characteristics of the full data set established at a different time. This paper presents an application of cokriging by using temporal subsets to study the spatial distribution of nitrate concentration in the aquifer of the Lucca Plain, central Italy. Three data sets of nitrate concentration in groundwater were collected during three different periods in 1991. The first set was from 47 wells, but the second and the third are undersampled and represent 28 and 27 wells, respectively. Comparing the result of cokriging with ordinary kriging showed an improvement of the uncertainty in terms of reducing the estimation variance. The application of cokriging to the undersampled data sets reduced the uncertainty in estimating nitrate concentration and at the same time decreased the cost of the field sampling and laboratory analysis.Spatial and temporal behavior of hydrochemical parameters in groundwater can be studied using tools provided by geostatistics. The cross-variogram can be used to measure the spatial increments between observations at two given times as a function of distance (spatial structure). Taking into account the existence of such a spatial structure, two different data sets (sampled at two different times), representing concentrations of the same hydrochemical parameter, can be analyzed by cokriging in order to reduce the uncertainty of the estimation. In particular, if one of the two data sets is a subset of the other (that is, an undersampled set), cokriging allows us to study the spatial distribution of the hydrochemical parameter at that time, while also considering the statistical characteristics of the full data set established at a different time. This paper presents an application of cokriging by using temporal subsets to study the spatial distribution of nitrate concentration in the aquifer of the Lucca Plain, central Italy. Three data sets of nitrate concentration in groundwater were collected during three different periods in 1991. The first set was from 47 wells, but the second and the third are undersampled and represent 28 and 27 wells, respectively. Comparing the result of cokriging with ordinary kriging showed an improvement of the uncertainty in terms of reducing the estimation variance. The application of cokriging to the undersampled data sets reduced the uncertainty in estimating nitrate concentration and at the same time decreased the cost of the field sampling and laboratory analysis.

Spatial Distributions of Young Stars

NASA Astrophysics Data System (ADS)

Kraus, Adam L.; Hillenbrand, Lynne A.

2008-10-01

We analyze the spatial distribution of young stars in Taurus-Auriga and Upper Sco, as determined from the two-point correlation function (i.e., the mean surface density of neighbors). The corresponding power-law fits allow us to determine the fractal dimensions of each association's spatial distribution, measure the stellar velocity dispersions, and distinguish between the bound binary population and chance alignments of members. We find that the fractal dimension of Taurus is D ~ 1.05, consistent with its filamentary structure. The fractal dimension of Upper Sco may be even shallower (D ~ 0.7), but this fit is uncertain due to the limited area and possible spatially variable incompleteness. We also find that random stellar motions have erased all primordial structure on scales of lsim0.07° in Taurus and lsim1.7° in Upper Sco; given ages of ~1 and ~5 Myr, the corresponding internal velocity dispersions are ~0.2 and ~1.0 km s-1, respectively. Finally, we find that binaries can be distinguished from chance alignments at separations of lsim120'' (17,000 AU) in Taurus and lsim75'' (11,000 AU) in Upper Sco. The binary populations in these associations that we previously studied, spanning separations of 3''-30'', is dominated by binary systems. However, the few lowest mass pairs (Mprim <~ 0.3 M⊙) might be chance alignments.

The Filtered Abel Transform and Its Application in Combustion Diagnostics

NASA Technical Reports Server (NTRS)

Simons, Stephen N. (Technical Monitor); Yuan, Zeng-Guang

2003-01-01

Many non-intrusive combustion diagnosis methods generate line-of-sight projections of a flame field. To reconstruct the spatial field of the measured properties, these projections need to be deconvoluted. When the spatial field is axisymmetric, commonly used deconvolution method include the Abel transforms, the onion peeling method and the two-dimensional Fourier transform method and its derivatives such as the filtered back projection methods. This paper proposes a new approach for performing the Abel transform method is developed, which possesses the exactness of the Abel transform and the flexibility of incorporating various filters in the reconstruction process. The Abel transform is an exact method and the simplest among these commonly used methods. It is evinced in this paper that all the exact reconstruction methods for axisymmetric distributions must be equivalent to the Abel transform because of its uniqueness and exactness. Detailed proof is presented to show that the two dimensional Fourier methods when applied to axisymmetric cases is identical to the Abel transform. Discrepancies among various reconstruction method stem from the different approximations made to perform numerical calculations. An equation relating the spectrum of a set of projection date to that of the corresponding spatial distribution is obtained, which shows that the spectrum of the projection is equal to the Abel transform of the spectrum of the corresponding spatial distribution. From the equation, if either the projection or the distribution is bandwidth limited, the other is also bandwidth limited, and both have the same bandwidth. If the two are not bandwidth limited, the Abel transform has a bias against low wave number components in most practical cases. This explains why the Abel transform and all exact deconvolution methods are sensitive to high wave number noises. The filtered Abel transform is based on the fact that the Abel transform of filtered projection data is equal to an integral transform of the original projection data with the kernel function being the Abel transform of the filtering function. The kernel function is independent of the projection data and can be obtained separately when the filtering function is selected. Users can select the best filtering function for a particular set of experimental data. When the kernal function is obtained, it can be used repeatedly to a number of projection data sets (rovs) from the same experiment. When an entire flame image that contains a large number of projection lines needs to be processed, the new approach significantly reduces computational effort in comparison with the conventional approach in which each projection data set is deconvoluted separately. Computer codes have been developed to perform the filter Abel transform for an entire flame field. Measured soot volume fraction data of a jet diffusion flame are processed as an example.

Magnetoacoustic tomography with magnetic induction for high-resolution bioimepedance imaging through vector source reconstruction under the static field of MRI magnet.

PubMed

Mariappan, Leo; Hu, Gang; He, Bin

2014-02-01

Magnetoacoustic tomography with magnetic induction (MAT-MI) is an imaging modality to reconstruct the electrical conductivity of biological tissue based on the acoustic measurements of Lorentz force induced tissue vibration. This study presents the feasibility of the authors' new MAT-MI system and vector source imaging algorithm to perform a complete reconstruction of the conductivity distribution of real biological tissues with ultrasound spatial resolution. In the present study, using ultrasound beamformation, imaging point spread functions are designed to reconstruct the induced vector source in the object which is used to estimate the object conductivity distribution. Both numerical studies and phantom experiments are performed to demonstrate the merits of the proposed method. Also, through the numerical simulations, the full width half maximum of the imaging point spread function is calculated to estimate of the spatial resolution. The tissue phantom experiments are performed with a MAT-MI imaging system in the static field of a 9.4 T magnetic resonance imaging magnet. The image reconstruction through vector beamformation in the numerical and experimental studies gives a reliable estimate of the conductivity distribution in the object with a ∼ 1.5 mm spatial resolution corresponding to the imaging system frequency of 500 kHz ultrasound. In addition, the experiment results suggest that MAT-MI under high static magnetic field environment is able to reconstruct images of tissue-mimicking gel phantoms and real tissue samples with reliable conductivity contrast. The results demonstrate that MAT-MI is able to image the electrical conductivity properties of biological tissues with better than 2 mm spatial resolution at 500 kHz, and the imaging with MAT-MI under a high static magnetic field environment is able to provide improved imaging contrast for biological tissue conductivity reconstruction.

[Three-dimension temporal and spatial dynamics of soil water for the artificial vegetation in the center of Taklimakan desert under saline water drip-irrigation].

PubMed

Ding, Xin-yuan; Zhou, Zhi-bin; Xu, Xin-wen; Lei, Jia-qiang; Lu, Jing-jing; Ma, Xue-xi; Feng, Xiao

2015-09-01

Three-dimension temporal and spatial dynamics of the soil water characteristics during four irrigating cycles of months from April to July for the artificial vegetation in the center of Taklimakan Desert under saline water drip-irrigation had been analyzed by timely measuring the soil water content in horizontal and vertical distances 60 cm and 120 cm away from the irrigating drips, respectively. Periodic spatial and temporal variations of soil water content were observed. When the precipitation effect was not considered, there were no significant differences in the characteristics of soil water among the irrigation intervals in different months, while discrepancies were obvious in the temporal and spatial changes of soil moisture content under the conditions of rainfall and non-rainfall. When it referred to the temporal changes of soil water, it was a little higher in April but a bit lower in July, and the soil water content in June was the highest among four months because some remarkable events of precipitation happened in this month. However, as a whole, the content of soil moisture was reduced as months (from April to July) went on and it took a decreasing tendency along with days (1-15 d) following a power function. Meanwhile, the characteristics of soil water content displayed three changeable stages in an irrigation interval. When it referred to the spatial distributions of soil water, the average content of soil moisture was reduced along with the horizontal distance following a linear regression function, and varied with double peaks along with the vertical distance. In addition, the spatial distribution characteristics of the soil water were not influenced by the factors of precipitation and irrigating time but the physical properties of soil.

Maxillofacial Injuries as Markers of Interpersonal Violence in Belo Horizonte-Brazil: Analysis of the Socio-Spatial Vulnerability of the Location of Victim’s Residences

PubMed Central

Silva, Carlos José de Paula; Moura, Ana Clara Mourão; Paiva, Paula Cristina Pelli; Ferreira, Raquel Conceição; Silvestrini, Rafaella Almeida; Vargas, Andréa Maria Duarte; de Paula, Liliam Pacheco Pinto; Naves, Marcelo Drummond; Ferreira, Efigênia Ferreira e

2015-01-01

The aim of the present study was to analyze the spatial pattern of cases of maxillofacial injuries caused by interpersonal violence, based on the location of the victim’s residence, and to investigate the existence of conditions of socio-spatial vulnerability in these areas. This is a cross-sectional study, using the data of victims attended in three emergency hospitals in Belo Horizonte-Brazil between January 2008 and December 2010. Based on the process of spatial signature, the socio-spatial condition of the victims was identified according to data from census tracts. The spatial distribution trends of the addresses of victims were analyzed using Kernel maps and Ripley’s K function. Multicriteria analysis was used to analyze the territorial insertion of victims, using a combination of variables to obtain the degree of socio-spatial vulnerability. The residences of the victims were distributed in an aggregated manner in urban areas, with a confidence level of 99%. The highest densities were found in areas of unfavorable socioeconomic conditions and, to a lesser extent, areas with worse residential and neighborhood infrastructure. Spatial clusters of households formed in slums with a significant level of socio-spatial vulnerability. Explanations of the living conditions in segregated urban areas and analysis of the concentration of more vulnerable populations should be a priority in the development of public health and safety policies. PMID:26274320

Bayesian hierarchical models for regional climate reconstructions of the last glacial maximum

NASA Astrophysics Data System (ADS)

Weitzel, Nils; Hense, Andreas; Ohlwein, Christian

2017-04-01

Spatio-temporal reconstructions of past climate are important for the understanding of the long term behavior of the climate system and the sensitivity to forcing changes. Unfortunately, they are subject to large uncertainties, have to deal with a complex proxy-climate structure, and a physically reasonable interpolation between the sparse proxy observations is difficult. Bayesian Hierarchical Models (BHMs) are a class of statistical models that is well suited for spatio-temporal reconstructions of past climate because they permit the inclusion of multiple sources of information (e.g. records from different proxy types, uncertain age information, output from climate simulations) and quantify uncertainties in a statistically rigorous way. BHMs in paleoclimatology typically consist of three stages which are modeled individually and are combined using Bayesian inference techniques. The data stage models the proxy-climate relation (often named transfer function), the process stage models the spatio-temporal distribution of the climate variables of interest, and the prior stage consists of prior distributions of the model parameters. For our BHMs, we translate well-known proxy-climate transfer functions for pollen to a Bayesian framework. In addition, we can include Gaussian distributed local climate information from preprocessed proxy records. The process stage combines physically reasonable spatial structures from prior distributions with proxy records which leads to a multivariate posterior probability distribution for the reconstructed climate variables. The prior distributions that constrain the possible spatial structure of the climate variables are calculated from climate simulation output. We present results from pseudoproxy tests as well as new regional reconstructions of temperatures for the last glacial maximum (LGM, ˜ 21,000 years BP). These reconstructions combine proxy data syntheses with information from climate simulations for the LGM that were performed in the PMIP3 project. The proxy data syntheses consist either of raw pollen data or of normally distributed climate data from preprocessed proxy records. Future extensions of our method contain the inclusion of other proxy types (transfer functions), the implementation of other spatial interpolation techniques, the use of age uncertainties, and the extension to spatio-temporal reconstructions of the last deglaciation. Our work is part of the PalMod project funded by the German Federal Ministry of Education and Science (BMBF).

Spatial Copula Model for Imputing Traffic Flow Data from Remote Microwave Sensors.

PubMed

Ma, Xiaolei; Luan, Sen; Du, Bowen; Yu, Bin

2017-09-21

Issues of missing data have become increasingly serious with the rapid increase in usage of traffic sensors. Analyses of the Beijing ring expressway have showed that up to 50% of microwave sensors pose missing values. The imputation of missing traffic data must be urgently solved although a precise solution that cannot be easily achieved due to the significant number of missing portions. In this study, copula-based models are proposed for the spatial interpolation of traffic flow from remote traffic microwave sensors. Most existing interpolation methods only rely on covariance functions to depict spatial correlation and are unsuitable for coping with anomalies due to Gaussian consumption. Copula theory overcomes this issue and provides a connection between the correlation function and the marginal distribution function of traffic flow. To validate copula-based models, a comparison with three kriging methods is conducted. Results indicate that copula-based models outperform kriging methods, especially on roads with irregular traffic patterns. Copula-based models demonstrate significant potential to impute missing data in large-scale transportation networks.

Computation of turbulent boundary layers employing the defect wall-function method. M.S. Thesis

NASA Technical Reports Server (NTRS)

Brown, Douglas L.

1994-01-01

In order to decrease overall computational time requirements of spatially-marching parabolized Navier-Stokes finite-difference computer code when applied to turbulent fluid flow, a wall-function methodology, originally proposed by R. Barnwell, was implemented. This numerical effort increases computational speed and calculates reasonably accurate wall shear stress spatial distributions and boundary-layer profiles. Since the wall shear stress is analytically determined from the wall-function model, the computational grid near the wall is not required to spatially resolve the laminar-viscous sublayer. Consequently, a substantially increased computational integration step size is achieved resulting in a considerable decrease in net computational time. This wall-function technique is demonstrated for adiabatic flat plate test cases from Mach 2 to Mach 8. These test cases are analytically verified employing: (1) Eckert reference method solutions, (2) experimental turbulent boundary-layer data of Mabey, and (3) finite-difference computational code solutions with fully resolved laminar-viscous sublayers. Additionally, results have been obtained for two pressure-gradient cases: (1) an adiabatic expansion corner and (2) an adiabatic compression corner.

Temporal and spatial characteristics of extreme precipitation events in the Midwest of Jilin Province based on multifractal detrended fluctuation analysis method and copula functions

NASA Astrophysics Data System (ADS)

Guo, Enliang; Zhang, Jiquan; Si, Ha; Dong, Zhenhua; Cao, Tiehua; Lan, Wu

2017-10-01

Environmental changes have brought about significant changes and challenges to water resources and management in the world; these include increasing climate variability, land use change, intensive agriculture, and rapid urbanization and industrial development, especially much more frequency extreme precipitation events. All of which greatly affect water resource and the development of social economy. In this study, we take extreme precipitation events in the Midwest of Jilin Province as an example; daily precipitation data during 1960-2014 are used. The threshold of extreme precipitation events is defined by multifractal detrended fluctuation analysis (MF-DFA) method. Extreme precipitation (EP), extreme precipitation ratio (EPR), and intensity of extreme precipitation (EPI) are selected as the extreme precipitation indicators, and then the Kolmogorov-Smirnov (K-S) test is employed to determine the optimal probability distribution function of extreme precipitation indicators. On this basis, copulas connect nonparametric estimation method and the Akaike Information Criterion (AIC) method is adopted to determine the bivariate copula function. Finally, we analyze the characteristics of single variable extremum and bivariate joint probability distribution of the extreme precipitation events. The results show that the threshold of extreme precipitation events in semi-arid areas is far less than that in subhumid areas. The extreme precipitation frequency shows a significant decline while the extreme precipitation intensity shows a trend of growth; there are significant differences in spatiotemporal of extreme precipitation events. The spatial variation trend of the joint return period gets shorter from the west to the east. The spatial distribution of co-occurrence return period takes on contrary changes and it is longer than the joint return period.

Spatial Distribution of Seismic Anisotropy in the Crust in the Northeast Front Zone of Tibetan Plateau

NASA Astrophysics Data System (ADS)

Gao, Y.; Wang, Q.; SHI, Y.

2017-12-01

There are orogenic belts and strong deformation in northeastern zone of Tibetan Plateau. The media in crust and in the upper mantle are seismic anisotropic there. This study uses seismic records by permanent seismic stations and portable seismic arrays, and adopts analysis techniques on body waves to obtain spatial anisotropic distribution in northeastern front zone of Tibetan Plateau. With seismic records of small local earthquakes, we study shear-wave splitting in the upper crust. The polarization of fast shear wave (PFS) can be obtained, and PFS is considered parallel to the strike of the cracks, as well as the direction of maximum horizontal compressive stress. However, the result shows the strong influence from tectonics, such as faults. It suggests multiple-influence including stress and fault. Spatial distribution of seismic anisotropy in study zone presents the effect in short range. PFS at the station on the strike-slip fault is quite different to PFS at station just hundreds of meters away from the fault. With seismic records of teleseismic waveforms, we obtained seismic anisotropy in the whole crust by receiver functions. The PFS directions from Pms receiver functions show consistency, generally in WNW. The time-delay of slow S phases is significant. With seismic records of SKS, PKS and SKKS phases, we can detect seismic anisotropy in the upper mantle by splitting analysis. The fast directions of these phases also show consistency, generally in WNW, similar to those of receiver functions, but larger time-delays. It suggests significant seismic anisotropy in the crust and crustal deformation is coherent to that in the upper mantle.Seismic anisotropy in the upper crust, in the whole crust and in the upper mantle are discussed both in difference and tectonic implications [Grateful to the support by NSFC Project 41474032].

Denitrification potential of riparian soils in relation to multiscale spatial environmental factors: a case study of a typical watershed, China.

PubMed

Wei, Jianbing; Feng, Hao; Cheng, Quanguo; Gao, Shiqian; Liu, Haiyan

2017-02-01

The objective of this study was to test the hypothesis that environmental regulators of riparian zone soil denitrification potential differ according to spatial scale within a watershed; consequently, a second objective was to provide spatial strategies for conserving and restoring the purification function of runoff in riparian ecosystems. The results show that soil denitrification in riparian zones was more heterogeneous at the profile scale than at the cross-section and landscape scales. At the profile scale, biogeochemical factors (including soil total organic carbon, total nitrogen, and nitrate-nitrogen) were the major direct regulators of the spatial distribution of soil denitrification enzyme activity (DEA). At the cross-section scale, factors included distance from river bank and vegetation density, while landscape-scale factors, including topographic index, elevation, and land use types, indirectly regulated the spatial distribution of DEA. At the profile scale, soil DEA was greatest in the upper soil layers. At the cross-section scale, maximum soil DEA occurred in the mid-part of the riparian zone. At the landscape scale, soil DEA showed an increasing trend towards downstream sites, except for those in urbanized areas.

Spatial averaging for small molecule diffusion in condensed phase environments

NASA Astrophysics Data System (ADS)

Plattner, Nuria; Doll, J. D.; Meuwly, Markus

2010-07-01

Spatial averaging is a new approach for sampling rare-event problems. The approach modifies the importance function which improves the sampling efficiency while keeping a defined relation to the original statistical distribution. In this work, spatial averaging is applied to multidimensional systems for typical problems arising in physical chemistry. They include (I) a CO molecule diffusing on an amorphous ice surface, (II) a hydrogen molecule probing favorable positions in amorphous ice, and (III) CO migration in myoglobin. The systems encompass a wide range of energy barriers and for all of them spatial averaging is found to outperform conventional Metropolis Monte Carlo. It is also found that optimal simulation parameters are surprisingly similar for the different systems studied, in particular, the radius of the point cloud over which the potential energy function is averaged. For H2 diffusing in amorphous ice it is found that facile migration is possible which is in agreement with previous suggestions from experiment. The free energy barriers involved are typically lower than 1 kcal/mol. Spatial averaging simulations for CO in myoglobin are able to locate all currently characterized metastable states. Overall, it is found that spatial averaging considerably improves the sampling of configurational space.

Atypical hemispheric dominance for attention: functional MRI topography.

PubMed

Flöel, Agnes; Jansen, Andreas; Deppe, Michael; Kanowski, Martin; Konrad, Carsten; Sommer, Jens; Knecht, Stefan

2005-09-01

The right hemisphere is predominantly involved in tasks associated with spatial attention. However, left hemispheric dominance for spatial attention can be found in healthy individuals, and both spatial attention and language can be lateralized to the same hemisphere. Little is known about the underlying regional distribution of neural activation in these 'atypical' individuals. Previously a large number of healthy subjects were screened for hemispheric dominance of visuospatial attention and language, using functional Doppler ultrasonography. From this group, subjects were chosen who were 'atypical' for hemispheric dominance of visuospatial attention and language, and their pattern of brain activation was studied with functional magnetic resonance imaging during a task probing spatial attention. Right-handed subjects with the 'typical' pattern of brain organization served as control subjects. It was found that subjects with an inverted lateralization of language and spatial attention (language right, attention left) recruited left-hemispheric areas in the attention task, homotopic to those recruited by control subjects in the right hemisphere. Subjects with lateralization of both language and attention to the right hemisphere activated an attentional network in the right hemisphere that was comparable to control subjects. The present findings suggest that not the hemispheric side, but the intrahemispheric pattern of activation is the distinct feature for the neural processes underlying language and attention.

The effects of plasma inhomogeneity on the nanoparticle coating in a low pressure plasma reactor

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

Pourali, N.; Foroutan, G.

2015-10-15

A self-consistent model is used to study the surface coating of a collection of charged nanoparticles trapped in the sheath region of a low pressure plasma reactor. The model consists of multi-fluid plasma sheath module, including nanoparticle dynamics, as well as the surface deposition and particle heating modules. The simulation results show that the mean particle radius increases with time and the nanoparticle size distribution is broadened. The mean radius is a linear function of time, while the variance exhibits a quadratic dependence. The broadening in size distribution is attributed to the spatial inhomogeneity of the deposition rate which inmore » turn depends on the plasma inhomogeneity. The spatial inhomogeneity of the ions has strong impact on the broadening of the size distribution, as the ions contribute both in the nanoparticle charging and in direct film deposition. The distribution width also increases with increasing of the pressure, gas temperature, and the ambient temperature gradient.« less

The Biogeography of Putative Microbial Antibiotic Production

PubMed Central

Bryant, Jessica A.; Charkoudian, Louise K.; Docherty, Kathryn M.; Jones, Evan; Kembel, Steven W.; Green, Jessica L.; Bohannan, Brendan J. M.

2015-01-01

Understanding patterns in the distribution and abundance of functional traits across a landscape is of fundamental importance to ecology. Mapping these distributions is particularly challenging for species-rich groups with sparse trait measurement coverage, such as flowering plants, insects, and microorganisms. Here, we use likelihood-based character reconstruction to infer and analyze the spatial distribution of unmeasured traits. We apply this framework to a microbial dataset comprised of 11,732 ketosynthase alpha gene sequences extracted from 144 soil samples from three continents to document the spatial distribution of putative microbial polyketide antibiotic production. Antibiotic production is a key competitive strategy for soil microbial survival and performance. Additionally, novel antibiotic discovery is highly relevant to human health, making natural antibiotic production by soil microorganisms a major target for bioprospecting. Our comparison of trait-based biogeographical patterns to patterns based on taxonomy and phylogeny is relevant to our basic understanding of microbial biogeography as well as the pressing need for new antibiotics. PMID:26102275

Model-based optimization of near-field binary-pixelated beam shapers

DOE PAGES

Dorrer, C.; Hassett, J.

2017-01-23

The optimization of components that rely on spatially dithered distributions of transparent or opaque pixels and an imaging system with far-field filtering for transmission control is demonstrated. The binary-pixel distribution can be iteratively optimized to lower an error function that takes into account the design transmission and the characteristics of the required far-field filter. Simulations using a design transmission chosen in the context of high-energy lasers show that the beam-fluence modulation at an image plane can be reduced by a factor of 2, leading to performance similar to using a non-optimized spatial-dithering algorithm with pixels of size reduced by amore » factor of 2 without the additional fabrication complexity or cost. The optimization process preserves the pixel distribution statistical properties. Analysis shows that the optimized pixel distribution starting from a high-noise distribution defined by a random-draw algorithm should be more resilient to fabrication errors than the optimized pixel distributions starting from a low-noise, error-diffusion algorithm, while leading to similar beamshaping performance. Furthermore, this is confirmed by experimental results obtained with various pixel distributions and induced fabrication errors.« less

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

NASA Astrophysics Data System (ADS)

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

2018-07-01

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

Spatial patterns of native freshwater mussels in the Upper Mississippi River

USGS Publications Warehouse

Ries, Patricia R.; DeJager, Nathan R.; Zigler, Steven J.; Newton, Teresa

2016-01-01

Multiple physical and biological factors structure freshwater mussel communities in large rivers, and their distributions have been described as clumped or patchy. However, few surveys of mussel populations have been conducted over areas large enough and at resolutions fine enough to quantify spatial patterns in their distribution. We used global and local indicators of spatial autocorrelation (i.e., Moran’s I) to quantify spatial patterns of adult and juvenile (≤5 y of age) freshwater mussels across multiple scales based on survey data from 4 reaches (navigation pools 3, 5, 6, and 18) of the Upper Mississippi River, USA. Native mussel densities were sampled at a resolution of ∼300 m and across distances ranging from 21 to 37 km, making these some of the most spatially extensive surveys conducted in a large river. Patch density and the degree and scale of patchiness varied by river reach, age group, and the scale of analysis. In all 4 pools, some patches of adults overlapped patches of juveniles, suggesting spatial and temporal persistence of adequate habitat. In pools 3 and 5, patches of juveniles were found where there were few adults, suggesting recent emergence of positive structuring mechanisms. Last, in pools 3, 5, and 6, some patches of adults were found where there were few juveniles, suggesting that negative structuring mechanisms may have replaced positive ones, leading to a lack of localized recruitment. Our results suggest that: 1) the detection of patches of freshwater mussels requires a multiscaled approach, 2) insights into the spatial and temporal dynamics of structuring mechanisms can be gained by conducting independent analyses of adults and juveniles, and 3) maps of patch distributions can be used to guide restoration and management actions and identify areas where mussels are most likely to influence ecosystem function.

Spatial and temporal patterns of carbon storage and species richness in three South Carolina coastal plain riparian forests

Treesearch

Laura A. Giese; W. Michael Aust; Carl C. Trettin; Randall K. Kolka

2000-01-01

The distribution of organic matter within a floodplain is a controlling factor affecting water quality, habitat, and food webs. Accordingly, developn~ent of vegetation in the riparian zone can be expected to influence ecosystem functions, and organic matter storage patterns are believed to be indicators of functional recovery in disturbed riparian zones. Our objective...

Parameterized approximation of lacunarity functions derived from airborne laser scanning point clouds of forested areas

NASA Astrophysics Data System (ADS)

Székely, Balázs; Kania, Adam; Varga, Katalin; Heilmeier, Hermann

2017-04-01

Lacunarity, a measure of the spatial distribution of the empty space is found to be a useful descriptive quantity of the forest structure. Its calculation, based on laser-scanned point clouds, results in a four-dimensional data set. The evaluation of results needs sophisticated tools and visualization techniques. To simplify the evaluation, it is straightforward to use approximation functions fitted to the results. The lacunarity function L(r), being a measure of scale-independent structural properties, has a power-law character. Previous studies showed that log(log(L(r))) transformation is suitable for analysis of spatial patterns. Accordingly, transformed lacunarity functions can be approximated by appropriate functions either in the original or in the transformed domain. As input data we have used a number of laser-scanned point clouds of various forests. The lacunarity distribution has been calculated along a regular horizontal grid at various (relative) elevations. The lacunarity data cube then has been logarithm-transformed and the resulting values became the input of parameter estimation at each point (point of interest, POI). This way at each POI a parameter set is generated that is suitable for spatial analysis. The expectation is that the horizontal variation and vertical layering of the vegetation can be characterized by this procedure. The results show that the transformed L(r) functions can be typically approximated by exponentials individually, and the residual values remain low in most cases. However, (1) in most cases the residuals may vary considerably, and (2) neighbouring POIs often give rather differing estimates both in horizontal and in vertical directions, of them the vertical variation seems to be more characteristic. In the vertical sense, the distribution of estimates shows abrupt changes at places, presumably related to the vertical structure of the forest. In low relief areas horizontal similarity is more typical, in higher relief areas horizontal similarity fades out in short distances. Some of the input data have been acquired in the framework of the ChangeHabitats2 project financed by the European Union. BS contributed as an Alexander von Humboldt Research Fellow.

Delineating recurrent fish spawning habitats in the North Sea

NASA Astrophysics Data System (ADS)

Lelièvre, S.; Vaz, S.; Martin, C. S.; Loots, C.

2014-08-01

The functional value of spawning habitats makes them critically important for the completion of fish life cycles and spawning grounds are now considered to be “essential habitats”. Inter-annual fluctuations in spawning ground distributions of dab (Limanda Limanda), plaice (Pleuronectes platessa), cod (Gadus morhua) and whiting (Merlangius merlangus) were investigated in the southern North Sea and eastern English Channel, from 2006 to 2009. The preferential spawning habitats of these species were modelled using generalised linear models, with egg distribution being used as proxy of spawners' location. Egg spatial and temporal distributions were explored based on six environmental variables: sea surface temperature and salinity, chlorophyll a concentration, depth, bedstress and seabed sediment types. In most cases, egg density was found to be strongly related to these environmental variables. Egg densities were positively correlated with shallow to intermediate depths having low temperature and relatively high salinity. Habitat models were used to map annual, i.e. 2006 to 2009, winter spatial distributions of eggs, for each species separately. Then, annual maps were combined to explore the spatial variability of each species' spawning grounds, and define recurrent, occasional, rare and unfavourable spawning areas. The recurrent spawning grounds of all four species were located in the south-eastern part of the study area, mainly along the Dutch and German coasts. This study contributes knowledge necessary to the spatial management of fishery resources in the area, and may also be used to identify marine areas with particular habitat features that need to be preserved.

Material removal and surface figure during pad polishing of fused silica

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

Suratwala, T I; Feit, M D; Steele, W A

2009-05-04

The material removal and surface figure after ceria pad polishing of fused silica glass have been measured and analyzed as a function of kinematics, loading conditions, and polishing time. Also, the friction at the workpiece/lap interface, the slope of the workpiece relative to the lap plane, and lap viscoelastic properties have been measured and correlated to material removal. The results show that the relative velocity between the workpiece & lap (determined by the kinematics) and the pressure distribution determine the spatial and temporal material removal and hence the final surface figure of the workpiece. In the case where the appliedmore » loading and relative velocity distribution over the workpiece are spatially uniform, a significant non-uniform spatial material removal from the workpiece surface is observed. This is due to a non-uniform pressure distribution resulting from: (1) a moment caused by a pivot point and interface friction forces; (2) viscoelastic relaxation of the polyurethane lap; and (3) a physical workpiece/lap interface mismatch. Both the kinematics and these contributions to the pressure distribution are quantitatively described, and then combined to form a spatial and temporal Preston model & code for material removal (called Surface Figure or SurF{copyright}). The surface figure simulations are consistent with the experiment for a wide variety of polishing conditions. This study is an important step towards deterministic full-aperture polishing, which would allow optical glass fabrication to be performed in a more repeatable, less iterative, and hence more economical manner.« less

Thoron, radon and air ions spatial distribution in indoor air.

PubMed

Kolarž, Predrag; Vaupotič, Janja; Kobal, Ivan; Ujić, Predrag; Stojanovska, Zdenka; Žunić, Zora S

2017-07-01

Spatial distribution of radioactive gasses thoron (Tn) and radon (Rn) in indoor air of 9 houses mostly during winter period of 2013 has been studied. According to properties of alpha decay of both elements, air ionization was also measured. Simultaneous continual measurements using three Rn/Tn and three air-ion active instruments deployed on to three different distances from the wall surface have shown various outcomes. It has turned out that Tn and air ions concentrations decrease with the distance increase, while Rn remained uniformly distributed. Exponential fittings function for Tn variation with distance was used for the diffusion length and constant as well as the exhalation rate determination. The obtained values were similar with experimental data reported in the literature. Concentrations of air ions were found to be in relation with Rn and obvious, but to a lesser extent, with Tn. Copyright © 2016 Elsevier Ltd. All rights reserved.

Analysis and modeling of optical crosstalk in InP-based Geiger-mode avalanche photodiode FPAs

NASA Astrophysics Data System (ADS)

Chau, Quan; Jiang, Xudong; Itzler, Mark A.; Entwistle, Mark; Piccione, Brian; Owens, Mark; Slomkowski, Krystyna

2015-05-01

Optical crosstalk is a major factor limiting the performance of Geiger-mode avalanche photodiode (GmAPD) focal plane arrays (FPAs). This is especially true for arrays with increased pixel density and broader spectral operation. We have performed extensive experimental and theoretical investigations on the crosstalk effects in InP-based GmAPD FPAs for both 1.06-μm and 1.55-μm applications. Mechanisms responsible for intrinsic dark counts are Poisson processes, and their inter-arrival time distribution is an exponential function. In FPAs, intrinsic dark counts and cross talk events coexist, and the inter-arrival time distribution deviates from purely exponential behavior. From both experimental data and computer simulations, we show the dependence of this deviation on the crosstalk probability. The spatial characteristics of crosstalk are also demonstrated. From the temporal and spatial distribution of crosstalk, an efficient algorithm to identify and quantify crosstalk is introduced.

Uncertainty indication in soil function maps - transparent and easy-to-use information to support sustainable use of soil resources

NASA Astrophysics Data System (ADS)

Greiner, Lucie; Nussbaum, Madlene; Papritz, Andreas; Zimmermann, Stephan; Gubler, Andreas; Grêt-Regamey, Adrienne; Keller, Armin

2018-05-01

Spatial information on soil function fulfillment (SFF) is increasingly being used to inform decision-making in spatial planning programs to support sustainable use of soil resources. Soil function maps visualize soils abilities to fulfill their functions, e.g., regulating water and nutrient flows, providing habitats, and supporting biomass production based on soil properties. Such information must be reliable for informed and transparent decision-making in spatial planning programs. In this study, we add to the transparency of soil function maps by (1) indicating uncertainties arising from the prediction of soil properties generated by digital soil mapping (DSM) that are used for soil function assessment (SFA) and (2) showing the response of different SFA methods to the propagation of uncertainties through the assessment. For a study area of 170 km2 in the Swiss Plateau, we map 10 static soil sub-functions for agricultural soils for a spatial resolution of 20 × 20 m together with their uncertainties. Mapping the 10 soil sub-functions using simple ordinal assessment scales reveals pronounced spatial patterns with a high variability of SFF scores across the region, linked to the inherent properties of the soils and terrain attributes and climate conditions. Uncertainties in soil properties propagated through SFA methods generally lead to substantial uncertainty in the mapped soil sub-functions. We propose two types of uncertainty maps that can be readily understood by stakeholders. Cumulative distribution functions of SFF scores indicate that SFA methods respond differently to the propagated uncertainty of soil properties. Even where methods are comparable on the level of complexity and assessment scale, their comparability in view of uncertainty propagation might be different. We conclude that comparable uncertainty indications in soil function maps are relevant to enable informed and transparent decisions on the sustainable use of soil resources.

Spatial Distribution of a Large Herbivore Community at Waterholes: An Assessment of Its Stability over Years in Hwange National Park, Zimbabwe.

PubMed

Chamaillé-Jammes, Simon; Charbonnel, Anaïs; Dray, Stéphane; Madzikanda, Hillary; Fritz, Hervé

2016-01-01

The spatial structuring of populations or communities is an important driver of their functioning and their influence on ecosystems. Identifying the (in)stability of the spatial structure of populations is a first step towards understanding the underlying causes of these structures. Here we studied the relative importance of spatial vs. interannual variability in explaining the patterns of abundance of a large herbivore community (8 species) at waterholes in Hwange National Park (Zimbabwe). We analyzed census data collected over 13 years using multivariate methods. Our results showed that variability in the census data was mostly explained by the spatial structure of the community, as some waterholes had consistently greater herbivore abundance than others. Some temporal variability probably linked to Park-scale migration dependent on annual rainfall was noticeable, however. Once this was accounted for, little temporal variability remained to be explained, suggesting that other factors affecting herbivore abundance over time had a negligible effect at the scale of the study. The extent of spatial and temporal variability in census data was also measured for each species. This study could help in projecting the consequences of surface water management, and more generally presents a methodological framework to simultaneously address the relative importance of spatial vs. temporal effects in driving the distribution of organisms across landscapes.

SARANA: language, compiler and run-time system support for spatially aware and resource-aware mobile computing.

PubMed

Hari, Pradip; Ko, Kevin; Koukoumidis, Emmanouil; Kremer, Ulrich; Martonosi, Margaret; Ottoni, Desiree; Peh, Li-Shiuan; Zhang, Pei

2008-10-28

Increasingly, spatial awareness plays a central role in many distributed and mobile computing applications. Spatially aware applications rely on information about the geographical position of compute devices and their supported services in order to support novel functionality. While many spatial application drivers already exist in mobile and distributed computing, very little systems research has explored how best to program these applications, to express their spatial and temporal constraints, and to allow efficient implementations on highly dynamic real-world platforms. This paper proposes the SARANA system architecture, which includes language and run-time system support for spatially aware and resource-aware applications. SARANA allows users to express spatial regions of interest, as well as trade-offs between quality of result (QoR), latency and cost. The goal is to produce applications that use resources efficiently and that can be run on diverse resource-constrained platforms ranging from laptops to personal digital assistants and to smart phones. SARANA's run-time system manages QoR and cost trade-offs dynamically by tracking resource availability and locations, brokering usage/pricing agreements and migrating programs to nodes accordingly. A resource cost model permeates the SARANA system layers, permitting users to express their resource needs and QoR expectations in units that make sense to them. Although we are still early in the system development, initial versions have been demonstrated on a nine-node system prototype.

Spatial Distribution of a Large Herbivore Community at Waterholes: An Assessment of Its Stability over Years in Hwange National Park, Zimbabwe

PubMed Central

Chamaillé-Jammes, Simon; Charbonnel, Anaïs; Dray, Stéphane; Madzikanda, Hillary; Fritz, Hervé

2016-01-01

The spatial structuring of populations or communities is an important driver of their functioning and their influence on ecosystems. Identifying the (in)stability of the spatial structure of populations is a first step towards understanding the underlying causes of these structures. Here we studied the relative importance of spatial vs. interannual variability in explaining the patterns of abundance of a large herbivore community (8 species) at waterholes in Hwange National Park (Zimbabwe). We analyzed census data collected over 13 years using multivariate methods. Our results showed that variability in the census data was mostly explained by the spatial structure of the community, as some waterholes had consistently greater herbivore abundance than others. Some temporal variability probably linked to Park-scale migration dependent on annual rainfall was noticeable, however. Once this was accounted for, little temporal variability remained to be explained, suggesting that other factors affecting herbivore abundance over time had a negligible effect at the scale of the study. The extent of spatial and temporal variability in census data was also measured for each species. This study could help in projecting the consequences of surface water management, and more generally presents a methodological framework to simultaneously address the relative importance of spatial vs. temporal effects in driving the distribution of organisms across landscapes. PMID:27074044

Spatial dynamics of the vegetation community associated with an invasive emergent macrophyte in a regulated river.

USDA-ARS?s Scientific Manuscript database

Successful management of riverine ecosystems often requires mitigation of alien plant invasions. Understanding how environmental variation within watersheds influences distribution and spread of invasive plants is essential to restoring impacted ecological functions and conserving native plant commu...

Non-Local Diffusion of Energetic Electrons during Solar Flares

NASA Astrophysics Data System (ADS)

Bian, N. H.; Emslie, G.; Kontar, E.

2017-12-01

The transport of the energy contained in suprathermal electrons in solar flares plays a key role in our understanding of many aspects of flare physics, from the spatial distributions of hard X-ray emission and energy deposition in the ambient atmosphere to global energetics. Historically the transport of these particles has been largely treated through a deterministic approach, in which first-order secular energy loss to electrons in the ambient target is treated as the dominant effect, with second-order diffusive terms (in both energy and angle) generally being either treated as a small correction or even neglected. Here, we critically analyze this approach, and we show that spatial diffusion through pitch-angle scattering necessarily plays a very significant role in the transport of electrons. We further show that a satisfactory treatment of the diffusion process requires consideration of non-local effects, so that the electron flux depends not just on the local gradient of the electron distribution function but on the value of this gradient within an extended region encompassing a significant fraction of a mean free path. Our analysis applies generally to pitch-angle scattering by a variety of mechanisms, from Coulomb collisions to turbulent scattering. We further show that the spatial transport of electrons along the magnetic field of a flaring loop can be modeled as a Continuous Time Random Walk with velocity-dependent probability distribution functions of jump sizes and occurrences, both of which can be expressed in terms of the scattering mean free path.

A Development of Nonstationary Regional Frequency Analysis Model with Large-scale Climate Information: Its Application to Korean Watershed

NASA Astrophysics Data System (ADS)

Kim, Jin-Young; Kwon, Hyun-Han; Kim, Hung-Soo

2015-04-01

The existing regional frequency analysis has disadvantages in that it is difficult to consider geographical characteristics in estimating areal rainfall. In this regard, this study aims to develop a hierarchical Bayesian model based nonstationary regional frequency analysis in that spatial patterns of the design rainfall with geographical information (e.g. latitude, longitude and altitude) are explicitly incorporated. This study assumes that the parameters of Gumbel (or GEV distribution) are a function of geographical characteristics within a general linear regression framework. Posterior distribution of the regression parameters are estimated by Bayesian Markov Chain Monte Carlo (MCMC) method, and the identified functional relationship is used to spatially interpolate the parameters of the distributions by using digital elevation models (DEM) as inputs. The proposed model is applied to derive design rainfalls over the entire Han-river watershed. It was found that the proposed Bayesian regional frequency analysis model showed similar results compared to L-moment based regional frequency analysis. In addition, the model showed an advantage in terms of quantifying uncertainty of the design rainfall and estimating the area rainfall considering geographical information. Finally, comprehensive discussion on design rainfall in the context of nonstationary will be presented. KEYWORDS: Regional frequency analysis, Nonstationary, Spatial information, Bayesian Acknowledgement This research was supported by a grant (14AWMP-B082564-01) from Advanced Water Management Research Program funded by Ministry of Land, Infrastructure and Transport of Korean government.

Self-consistent Langmuir waves in resonantly driven thermal plasmas

NASA Astrophysics Data System (ADS)

Lindberg, R. R.; Charman, A. E.; Wurtele, J. S.

2007-12-01

The longitudinal dynamics of a resonantly driven Langmuir wave are analyzed in the limit that the growth of the electrostatic wave is slow compared to the bounce frequency. Using simple physical arguments, the nonlinear distribution function is shown to be nearly invariant in the canonical particle action, provided both a spatially uniform term and higher-order spatial harmonics are included along with the fundamental in the longitudinal electric field. Requirements of self-consistency with the electrostatic potential yield the basic properties of the nonlinear distribution function, including a frequency shift that agrees closely with driven, electrostatic particle simulations over a range of temperatures. This extends earlier work on nonlinear Langmuir waves by Morales and O'Neil [G. J. Morales and T. M. O'Neil, Phys. Rev. Lett. 28, 417 (1972)] and Dewar [R. L. Dewar, Phys. Plasmas 15, 712 (1972)], and could form the basis of a reduced kinetic treatment of plasma dynamics for accelerator applications or Raman backscatter.

Theoretical limit of spatial resolution in diffuse optical tomography using a perturbation model

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

Konovalov, A B; Vlasov, V V

2014-03-28

We have assessed the limit of spatial resolution of timedomain diffuse optical tomography (DOT) based on a perturbation reconstruction model. From the viewpoint of the structure reconstruction accuracy, three different approaches to solving the inverse DOT problem are compared. The first approach involves reconstruction of diffuse tomograms from straight lines, the second – from average curvilinear trajectories of photons and the third – from total banana-shaped distributions of photon trajectories. In order to obtain estimates of resolution, we have derived analytical expressions for the point spread function and modulation transfer function, as well as have performed a numerical experiment onmore » reconstruction of rectangular scattering objects with circular absorbing inhomogeneities. It is shown that in passing from reconstruction from straight lines to reconstruction using distributions of photon trajectories we can improve resolution by almost an order of magnitude and exceed the accuracy of reconstruction of multi-step algorithms used in DOT. (optical tomography)« less

Measuring spatially varying, multispectral, ultraviolet bidirectional reflectance distribution function with an imaging spectrometer

NASA Astrophysics Data System (ADS)

Li, Hongsong; Lyu, Hang; Liao, Ningfang; Wu, Wenmin

2016-12-01

The bidirectional reflectance distribution function (BRDF) data in the ultraviolet (UV) band are valuable for many applications including cultural heritage, material analysis, surface characterization, and trace detection. We present a BRDF measurement instrument working in the near- and middle-UV spectral range. The instrument includes a collimated UV light source, a rotation stage, a UV imaging spectrometer, and a control computer. The data captured by the proposed instrument describe spatial, spectral, and angular variations of the light scattering from a sample surface. Such a multidimensional dataset of an example sample is captured by the proposed instrument and analyzed by a k-mean clustering algorithm to separate surface regions with same material but different surface roughnesses. The clustering results show that the angular dimension of the dataset can be exploited for surface roughness characterization. The two clustered BRDFs are fitted to a theoretical BRDF model. The fitting results show good agreement between the measurement data and the theoretical model.

Transit time distributions to assess present and future contamination risk of karst aquifers over Europe and the Mediterranean

NASA Astrophysics Data System (ADS)

Hartmann, Andreas; Gleeson, Tom; Wada, Yoshihide; Wagener, Thorsten

2016-04-01

Karst develops through the dissolution of carbonate rock. Karst groundwater in Europe is a major source of fresh water contributing up to half of the total drinking water supply in some countries. Climate model projections suggest that in the next 100 years, karst regions will experience a strong increase in temperature and a serious decrease of precipitation - especially in the Mediterranean region. Previous work showed that the karstic preferential recharge processes result in enhanced recharge rates and future climate sensitivity. But as there is fast water flow form the surface to the aquifer, there is also an enhanced risk of groundwater contamination. In this study we will assess the contamination risk of karst aquifers over Europe and the Mediterranean using simulated transit time distributions. Using a new type of semi-distributed model that considers the spatial heterogeneity of the karst system by distribution functions we simulated a range of spatially variable pathways of karstic groundwater recharge. The model is driven by the bias-corrected 5 GCMs of the ISI-MIP project (RCP8.5). Transit time distributions are calculated by virtual tracer experiments. These are repeated several times in the present (1991-2010) and the future (2080-2099). We can show that regions with larger fractions of preferential recharge show higher risks of contamination and that spatial patterns of contamination risk change towards the future.

Spatial uncertainty analysis: Propagation of interpolation errors in spatially distributed models

USGS Publications Warehouse

Phillips, D.L.; Marks, D.G.

1996-01-01

In simulation modelling, it is desirable to quantify model uncertainties and provide not only point estimates for output variables but confidence intervals as well. Spatially distributed physical and ecological process models are becoming widely used, with runs being made over a grid of points that represent the landscape. This requires input values at each grid point, which often have to be interpolated from irregularly scattered measurement sites, e.g., weather stations. Interpolation introduces spatially varying errors which propagate through the model We extended established uncertainty analysis methods to a spatial domain for quantifying spatial patterns of input variable interpolation errors and how they propagate through a model to affect the uncertainty of the model output. We applied this to a model of potential evapotranspiration (PET) as a demonstration. We modelled PET for three time periods in 1990 as a function of temperature, humidity, and wind on a 10-km grid across the U.S. portion of the Columbia River Basin. Temperature, humidity, and wind speed were interpolated using kriging from 700- 1000 supporting data points. Kriging standard deviations (SD) were used to quantify the spatially varying interpolation uncertainties. For each of 5693 grid points, 100 Monte Carlo simulations were done, using the kriged values of temperature, humidity, and wind, plus random error terms determined by the kriging SDs and the correlations of interpolation errors among the three variables. For the spring season example, kriging SDs averaged 2.6??C for temperature, 8.7% for relative humidity, and 0.38 m s-1 for wind. The resultant PET estimates had coefficients of variation (CVs) ranging from 14% to 27% for the 10-km grid cells. Maps of PET means and CVs showed the spatial patterns of PET with a measure of its uncertainty due to interpolation of the input variables. This methodology should be applicable to a variety of spatially distributed models using interpolated inputs.

Analysis and attenuation of artifacts caused by spatially and temporally correlated noise sources in Green's function estimates

NASA Astrophysics Data System (ADS)

Martin, E. R.; Dou, S.; Lindsey, N.; Chang, J. P.; Biondi, B. C.; Ajo Franklin, J. B.; Wagner, A. M.; Bjella, K.; Daley, T. M.; Freifeld, B. M.; Robertson, M.; Ulrich, C.; Williams, E. F.

2016-12-01

Localized strong sources of noise in an array have been shown to cause artifacts in Green's function estimates obtained via cross-correlation. Their effect is often reduced through the use of cross-coherence. Beyond independent localized sources, temporally or spatially correlated sources of noise frequently occur in practice but violate basic assumptions of much of the theory behind ambient noise Green's function retrieval. These correlated noise sources can occur in urban environments due to transportation infrastructure, or in areas around industrial operations like pumps running at CO2 sequestration sites or oil and gas drilling sites. Better understanding of these artifacts should help us develop and justify methods for their automatic removal from Green's function estimates. We derive expected artifacts in cross-correlations from several distributions of correlated noise sources including point sources that are exact time-lagged repeats of each other and Gaussian-distributed in space and time with covariance that exponentially decays. Assuming the noise distribution stays stationary over time, the artifacts become more coherent as more ambient noise is included in the Green's function estimates. We support our results with simple computational models. We observed these artifacts in Green's function estimates from a 2015 ambient noise study in Fairbanks, AK where a trenched distributed acoustic sensing (DAS) array was deployed to collect ambient noise alongside a road with the goal of developing a permafrost thaw monitoring system. We found that joints in the road repeatedly being hit by cars travelling at roughly the speed limit led to artifacts similar to those expected when several points are time-lagged copies of each other. We also show test results of attenuating the effects of these sources during time-lapse monitoring of an active thaw test in the same location with noise detected by a 2D trenched DAS array.

Procedures for the Systematic Evaluation of Remote Sensor Performance and Quantitative Mission Planning

DTIC Science & Technology

1976-08-01

bare soil and grass areas, Vicksburg, Mississippi . ....... .. 101 25 Schematic of typical thermal IR scanner system . . . . 103 26 Sensor spatial...following categories: a. Soils b. Vegetation S. Topography d. Bedrock It is the knowledge of these characteristics and their distribution within the...necessary to know the changes in soil , vegetation, topography, and bedrock characteristics as a function of time as well as their spa- tial distribution at

Patterned graphene functionalization via mask-free scanning of micro-plasma jet under ambient condition

NASA Astrophysics Data System (ADS)

Ye, Dong; Wu, Shu-Qun; Yu, Yao; Liu, Lin; Lu, Xin-Pei; Wu, Yue

2014-03-01

In this work, a mask-free method is introduced for patterned nitrogen doping of graphene using a micro-plasma jet under ambient condition. Raman and X-ray photoelectron spectroscopy spectra indicate that nitrogen atoms are incorporated into the graphene lattice with the two-dimensional spatial distribution precisely controlled in the range of mm down to 10 μm. Since the chemistry of the micro-plasma jet can be controlled by the choice of the gas mixture, this direct writing process with micro-plasma jet can be a versatile approach for patterned functionalization of graphene with high spatial resolution. This could have promising applications in graphene-based electronics.

Generalized Pearson distributions for charged particles interacting with an electric and/or a magnetic field

NASA Astrophysics Data System (ADS)

Rossani, A.; Scarfone, A. M.

2009-06-01

The linear Boltzmann equation for elastic and/or inelastic scattering is applied to derive the distribution function of a spatially homogeneous system of charged particles spreading in a host medium of two-level atoms and subjected to external electric and/or magnetic fields. We construct a Fokker-Planck approximation to the kinetic equations and derive the most general class of distributions for the given problem by discussing in detail some physically meaningful cases. The equivalence with the transport theory of electrons in a phonon background is also discussed.

Gas and Dust Structures of the Protoplanetary Disk around HD 142527

NASA Astrophysics Data System (ADS)

Momose, M.; Muto, T.; Hanawa, T.; Fukagawa, M.; Tsukagoshi, T.; Saigo, K.; Kataoka, A.; Nomura, H.; Takeuchi, T.; Akiyama, E.; Ohashi, N.; Fujiwara, H.; Shibai, H.; Kitamura, Y.; Inutsuka, S.; Kobayashi, H.; Honda, M.; Aso, Y.; Takahashi, S. Z.

2015-12-01

HD142527 is a Herbig Fe star accompanied by a disk with ring-like structure. We derive the distributions of dust and gas separately by model fitting and discuss the spatial variation of gas-to-dust mass ratio in the disk. The radial distribution of dust is well approximated by a Gaussian function, while the gas is roughly followed by a power-law distribution between 110 and 400 AU in radius, which is significantly more extended than dust. G/d may reach the order of unity at the northern peak.

Transport lattice models of heat transport in skin with spatially heterogeneous, temperature-dependent perfusion

PubMed Central

Gowrishankar, TR; Stewart, Donald A; Martin, Gregory T; Weaver, James C

2004-01-01

Background Investigation of bioheat transfer problems requires the evaluation of temporal and spatial distributions of temperature. This class of problems has been traditionally addressed using the Pennes bioheat equation. Transport of heat by conduction, and by temperature-dependent, spatially heterogeneous blood perfusion is modeled here using a transport lattice approach. Methods We represent heat transport processes by using a lattice that represents the Pennes bioheat equation in perfused tissues, and diffusion in nonperfused regions. The three layer skin model has a nonperfused viable epidermis, and deeper regions of dermis and subcutaneous tissue with perfusion that is constant or temperature-dependent. Two cases are considered: (1) surface contact heating and (2) spatially distributed heating. The model is relevant to the prediction of the transient and steady state temperature rise for different methods of power deposition within the skin. Accumulated thermal damage is estimated by using an Arrhenius type rate equation at locations where viable tissue temperature exceeds 42°C. Prediction of spatial temperature distributions is also illustrated with a two-dimensional model of skin created from a histological image. Results The transport lattice approach was validated by comparison with an analytical solution for a slab with homogeneous thermal properties and spatially distributed uniform sink held at constant temperatures at the ends. For typical transcutaneous blood gas sensing conditions the estimated damage is small, even with prolonged skin contact to a 45°C surface. Spatial heterogeneity in skin thermal properties leads to a non-uniform temperature distribution during a 10 GHz electromagnetic field exposure. A realistic two-dimensional model of the skin shows that tissue heterogeneity does not lead to a significant local temperature increase when heated by a hot wire tip. Conclusions The heat transport system model of the skin was solved by exploiting the mathematical analogy between local thermal models and local electrical (charge transport) models, thereby allowing robust, circuit simulation software to obtain solutions to Kirchhoff's laws for the system model. Transport lattices allow systematic introduction of realistic geometry and spatially heterogeneous heat transport mechanisms. Local representations for both simple, passive functions and more complex local models can be easily and intuitively included into the system model of a tissue. PMID:15548324

Turbulent transport with intermittency: Expectation of a scalar concentration.

PubMed

Rast, Mark Peter; Pinton, Jean-François; Mininni, Pablo D

2016-04-01

Scalar transport by turbulent flows is best described in terms of Lagrangian parcel motions. Here we measure the Eulerian distance travel along Lagrangian trajectories in a simple point vortex flow to determine the probabilistic impulse response function for scalar transport in the absence of molecular diffusion. As expected, the mean squared Eulerian displacement scales ballistically at very short times and diffusively for very long times, with the displacement distribution at any given time approximating that of a random walk. However, significant deviations in the displacement distributions from Rayleigh are found. The probability of long distance transport is reduced over inertial range time scales due to spatial and temporal intermittency. This can be modeled as a series of trapping events with durations uniformly distributed below the Eulerian integral time scale. The probability of long distance transport is, on the other hand, enhanced beyond that of the random walk for both times shorter than the Lagrangian integral time and times longer than the Eulerian integral time. The very short-time enhancement reflects the underlying Lagrangian velocity distribution, while that at very long times results from the spatial and temporal variation of the flow at the largest scales. The probabilistic impulse response function, and with it the expectation value of the scalar concentration at any point in space and time, can be modeled using only the evolution of the lowest spatial wave number modes (the mean and the lowest harmonic) and an eddy based constrained random walk that captures the essential velocity phase relations associated with advection by vortex motions. Preliminary examination of Lagrangian tracers in three-dimensional homogeneous isotropic turbulence suggests that transport in that setting can be similarly modeled.

Anatomical and functional assemblies of brain BOLD oscillations

PubMed Central

Baria, Alexis T.; Baliki, Marwan N.; Parrish, Todd; Apkarian, A. Vania

2011-01-01

Brain oscillatory activity has long been thought to have spatial properties, the details of which are unresolved. Here we examine spatial organizational rules for the human brain oscillatory activity as measured by blood oxygen level-dependent (BOLD). Resting state BOLD signal was transformed into frequency space (Welch’s method), averaged across subjects, and its spatial distribution studied as a function of four frequency bands, spanning the full bandwidth of BOLD. The brain showed anatomically constrained distribution of power for each frequency band. This result was replicated on a repository dataset of 195 subjects. Next, we examined larger-scale organization by parceling the neocortex into regions approximating Brodmann Areas (BAs). This indicated that BAs of simple function/connectivity (unimodal), vs. complex properties (transmodal), are dominated by low frequency BOLD oscillations, and within the visual ventral stream we observe a graded shift of power to higher frequency bands for BAs further removed from the primary visual cortex (increased complexity), linking frequency properties of BOLD to hodology. Additionally, BOLD oscillation properties for the default mode network demonstrated that it is composed of distinct frequency dependent regions. When the same analysis was performed on a visual-motor task, frequency-dependent global and voxel-wise shifts in BOLD oscillations could be detected at brain sites mostly outside those identified with general linear modeling. Thus, analysis of BOLD oscillations in full bandwidth uncovers novel brain organizational rules, linking anatomical structures and functional networks to characteristic BOLD oscillations. The approach also identifies changes in brain intrinsic properties in relation to responses to external inputs. PMID:21613505

Experimental triplet and quadruplet fluctuation densities and spatial distribution function integrals for pure liquids.

PubMed

Ploetz, Elizabeth A; Karunaweera, Sadish; Smith, Paul E

2015-01-28

Fluctuation solution theory has provided an alternative view of many liquid mixture properties in terms of particle number fluctuations. The particle number fluctuations can also be related to integrals of the corresponding two body distribution functions between molecular pairs in order to provide a more physical picture of solution behavior and molecule affinities. Here, we extend this type of approach to provide expressions for higher order triplet and quadruplet fluctuations, and thereby integrals over the corresponding distribution functions, all of which can be obtained from available experimental thermodynamic data. The fluctuations and integrals are then determined using the International Association for the Properties of Water and Steam Formulation 1995 (IAPWS-95) equation of state for the liquid phase of pure water. The results indicate small, but significant, deviations from a Gaussian distribution for the molecules in this system. The pressure and temperature dependence of the fluctuations and integrals, as well as the limiting behavior as one approaches both the triple point and the critical point, are also examined.

Experimental triplet and quadruplet fluctuation densities and spatial distribution function integrals for pure liquids

NASA Astrophysics Data System (ADS)

Ploetz, Elizabeth A.; Karunaweera, Sadish; Smith, Paul E.

2015-01-01

Fluctuation solution theory has provided an alternative view of many liquid mixture properties in terms of particle number fluctuations. The particle number fluctuations can also be related to integrals of the corresponding two body distribution functions between molecular pairs in order to provide a more physical picture of solution behavior and molecule affinities. Here, we extend this type of approach to provide expressions for higher order triplet and quadruplet fluctuations, and thereby integrals over the corresponding distribution functions, all of which can be obtained from available experimental thermodynamic data. The fluctuations and integrals are then determined using the International Association for the Properties of Water and Steam Formulation 1995 (IAPWS-95) equation of state for the liquid phase of pure water. The results indicate small, but significant, deviations from a Gaussian distribution for the molecules in this system. The pressure and temperature dependence of the fluctuations and integrals, as well as the limiting behavior as one approaches both the triple point and the critical point, are also examined.

Global Land Carbon Uptake from Trait Distributions

NASA Astrophysics Data System (ADS)

Butler, E. E.; Datta, A.; Flores-Moreno, H.; Fazayeli, F.; Chen, M.; Wythers, K. R.; Banerjee, A.; Atkin, O. K.; Kattge, J.; Reich, P. B.

2016-12-01

Historically, functional diversity in land surface models has been represented through a range of plant functional types (PFTs), each of which has a single value for all of its functional traits. Here we expand the diversity of the land surface by using a distribution of trait values for each PFT. The data for these trait distributions is from a sub-set of the global database of plant traits, TRY, and this analysis uses three leaf traits: mass based nitrogen and phosphorus content and specific leaf area, which influence both photosynthesis and respiration. The data are extrapolated into continuous surfaces through two methodologies. The first, a categorical method, classifies the species observed in TRY into satellite estimates of their plant functional type abundances - analogous to how traits are currently assigned to PFTs in land surface models. Second, a Bayesian spatial method which additionally estimates how the distribution of a trait changes in accord with both climate and soil covariates. These two methods produce distinct patterns of diversity which are incorporated into a land surface model to estimate how the range of trait values affects the global land carbon budget.

Sparsely-distributed organization of face and limb activations in human ventral temporal cortex

PubMed Central

Weiner, Kevin S.; Grill-Spector, Kalanit

2011-01-01

Functional magnetic resonance imaging (fMRI) has identified face- and body part-selective regions, as well as distributed activation patterns for object categories across human ventral temporal cortex (VTC), eliciting a debate regarding functional organization in VTC and neural coding of object categories. Using high-resolution fMRI, we illustrate that face- and limb-selective activations alternate in a series of largely nonoverlapping clusters in lateral VTC along the inferior occipital gyrus (IOG), fusiform gyrus (FG), and occipitotemporal sulcus (OTS). Both general linear model (GLM) and multivoxel pattern (MVP) analyses show that face- and limb-selective activations minimally overlap and that this organization is consistent across experiments and days. We provide a reliable method to separate two face-selective clusters on the middle and posterior FG (mFus and pFus), and another on the IOG using their spatial relation to limb-selective activations and retinotopic areas hV4, VO-1/2, and hMT+. Furthermore, these activations show a gradient of increasing face selectivity and decreasing limb selectivity from the IOG to the mFus. Finally, MVP analyses indicate that there is differential information for faces in lateral VTC (containing weakly- and highly-selective voxels) relative to non-selective voxels in medial VTC. These findings suggest a sparsely-distributed organization where sparseness refers to the presence of several face- and limb-selective clusters in VTC, and distributed refers to the presence of different amounts of information in highly-, weakly-, and non-selective voxels. Consequently, theories of object recognition should consider the functional and spatial constraints of neural coding across a series of nonoverlapping category-selective clusters that are themselves distributed. PMID:20457261

Risk assessment of salinity and turbidity in Victoria (Australia) to stream insects' community structure does not always protect functional traits.

PubMed

Kefford, Ben J; Schäfer, Ralf B; Metzeling, Leon

2012-01-15

Ecological risk assessments mostly consider measures of community composition (structure) across large spatial scales. These assessments, using species sensitivity distributions (SSDs) or the relative species retention (RSR), may not be protective of ecosystem functions and services at smaller spatial scales. Here we examine how changes in biological traits, as proxy for ecosystem functions/services, at a fine spatial scale relate to larger scale assessment of structure. We use functional traits of stream insect species in south-east Australia in two habitats (riffle and edge/pool). We find that the protection of community structure in terms of 95% of species over multiple sites against adverse effects of salinity (as electrical conductivity) and turbidity will mostly, but not always, protect traits at smaller scales. Considering different combinations of trait modalities, contaminants and habitat, a mean of 17.5% (range 0%-36.8) of cases would result in under-protection of trait modalities despite protecting species composition (in terms of Jaccard's Index). This under-protection of trait modalities is only because of the different spatial scales that community structure and the traits were considered. We recommend that where the protection of biological traits, ecosystem functions or ecosystem services from stressors is a management goal, protective targets should not be solely set using measures of community structure such as SSDs or RSR. To protect both structural and functional attributes separate risk assessments should be done. Copyright © 2011 Elsevier B.V. All rights reserved.

Measurements of neutral and ion velocity distribution functions in a Hall thruster

NASA Astrophysics Data System (ADS)

Svarnas, Panagiotis; Romadanov, Iavn; Diallo, Ahmed; Raitses, Yevgeny

2015-11-01

Hall thruster is a plasma device for space propulsion. It utilizes a cross-field discharge to generate a partially ionized weakly collisional plasma with magnetized electrons and non-magnetized ions. The ions are accelerated by the electric field to produce the thrust. There is a relatively large number of studies devoted to characterization of accelerated ions, including measurements of ion velocity distribution function using laser-induced fluorescence diagnostic. Interactions of these accelerated ions with neutral atoms in the thruster and the thruster plume is a subject of on-going studies, which require combined monitoring of ion and neutral velocity distributions. Herein, laser-induced fluorescence technique has been employed to study neutral and single-charged ion velocity distribution functions in a 200 W cylindrical Hall thruster operating with xenon propellant. An optical system is installed in the vacuum chamber enabling spatially resolved axial velocity measurements. The fluorescence signals are well separated from the plasma background emission by modulating the laser beam and using lock-in detectors. Measured velocity distribution functions of neutral atoms and ions at different operating parameters of the thruster are reported and analyzed. This work was supported by DOE contract DE-AC02-09CH11466.

Correlation functions in first-order phase transitions

NASA Astrophysics Data System (ADS)

Garrido, V.; Crespo, D.

1997-09-01

Most of the physical properties of systems underlying first-order phase transitions can be obtained from the spatial correlation functions. In this paper, we obtain expressions that allow us to calculate all the correlation functions from the droplet size distribution. Nucleation and growth kinetics is considered, and exact solutions are obtained for the case of isotropic growth by using self-similarity properties. The calculation is performed by using the particle size distribution obtained by a recently developed model (populational Kolmogorov-Johnson-Mehl-Avrami model). Since this model is less restrictive than that used in previously existing theories, the result is that the correlation functions can be obtained for any dependence of the kinetic parameters. The validity of the method is tested by comparison with the exact correlation functions, which had been obtained in the available cases by the time-cone method. Finally, the correlation functions corresponding to the microstructure developed in partitioning transformations are obtained.

Spatial Molecular Architecture of the Microbial Community of a Peltigera Lichen.

PubMed

Garg, Neha; Zeng, Yi; Edlund, Anna; Melnik, Alexey V; Sanchez, Laura M; Mohimani, Hosein; Gurevich, Alexey; Miao, Vivian; Schiffler, Stefan; Lim, Yan Wei; Luzzatto-Knaan, Tal; Cai, Shengxin; Rohwer, Forest; Pevzner, Pavel A; Cichewicz, Robert H; Alexandrov, Theodore; Dorrestein, Pieter C

2016-01-01

Microbes are commonly studied as individual species, but they exist as mixed assemblages in nature. At present, we know very little about the spatial organization of the molecules, including natural products that are produced within these microbial networks. Lichens represent a particularly specialized type of symbiotic microbial assemblage in which the component microorganisms exist together. These composite microbial assemblages are typically comprised of several types of microorganisms representing phylogenetically diverse life forms, including fungi, photosymbionts, bacteria, and other microbes. Here, we employed matrix-assisted laser desorption ionization-time of flight (MALDI-TOF) imaging mass spectrometry to characterize the distributions of small molecules within a Peltigera lichen. In order to probe how small molecules are organized and localized within the microbial consortium, analytes were annotated and assigned to their respective producer microorganisms using mass spectrometry-based molecular networking and metagenome sequencing. The spatial analysis of the molecules not only reveals an ordered layering of molecules within the lichen but also supports the compartmentalization of unique functions attributed to various layers. These functions include chemical defense (e.g., antibiotics), light-harvesting functions associated with the cyanobacterial outer layer (e.g., chlorophyll), energy transfer (e.g., sugars) surrounding the sun-exposed cyanobacterial layer, and carbohydrates that may serve a structural or storage function and are observed with higher intensities in the non-sun-exposed areas (e.g., complex carbohydrates). IMPORTANCE Microbial communities have evolved over centuries to live symbiotically. The direct visualization of such communities at the chemical and functional level presents a challenge. Overcoming this challenge may allow one to visualize the spatial distributions of specific molecules involved in symbiosis and to define their functional roles in shaping the community structure. In this study, we examined the diversity of microbial genes and taxa and the presence of biosynthetic gene clusters by metagenomic sequencing and the compartmentalization of organic chemical components within a lichen using mass spectrometry. This approach allowed the identification of chemically distinct sections within this composite organism. Using our multipronged approach, various fungal natural products, not previously reported from lichens, were identified and two different fungal layers were visualized at the chemical level.

Spatial Molecular Architecture of the Microbial Community of a Peltigera Lichen

PubMed Central

Garg, Neha; Zeng, Yi; Edlund, Anna; Melnik, Alexey V.; Mohimani, Hosein; Gurevich, Alexey; Miao, Vivian; Schiffler, Stefan; Lim, Yan Wei; Luzzatto-Knaan, Tal; Cai, Shengxin; Rohwer, Forest; Pevzner, Pavel A.; Cichewicz, Robert H.; Alexandrov, Theodore

2016-01-01

ABSTRACT Microbes are commonly studied as individual species, but they exist as mixed assemblages in nature. At present, we know very little about the spatial organization of the molecules, including natural products that are produced within these microbial networks. Lichens represent a particularly specialized type of symbiotic microbial assemblage in which the component microorganisms exist together. These composite microbial assemblages are typically comprised of several types of microorganisms representing phylogenetically diverse life forms, including fungi, photosymbionts, bacteria, and other microbes. Here, we employed matrix-assisted laser desorption ionization–time of flight (MALDI-TOF) imaging mass spectrometry to characterize the distributions of small molecules within a Peltigera lichen. In order to probe how small molecules are organized and localized within the microbial consortium, analytes were annotated and assigned to their respective producer microorganisms using mass spectrometry-based molecular networking and metagenome sequencing. The spatial analysis of the molecules not only reveals an ordered layering of molecules within the lichen but also supports the compartmentalization of unique functions attributed to various layers. These functions include chemical defense (e.g., antibiotics), light-harvesting functions associated with the cyanobacterial outer layer (e.g., chlorophyll), energy transfer (e.g., sugars) surrounding the sun-exposed cyanobacterial layer, and carbohydrates that may serve a structural or storage function and are observed with higher intensities in the non-sun-exposed areas (e.g., complex carbohydrates). IMPORTANCE Microbial communities have evolved over centuries to live symbiotically. The direct visualization of such communities at the chemical and functional level presents a challenge. Overcoming this challenge may allow one to visualize the spatial distributions of specific molecules involved in symbiosis and to define their functional roles in shaping the community structure. In this study, we examined the diversity of microbial genes and taxa and the presence of biosynthetic gene clusters by metagenomic sequencing and the compartmentalization of organic chemical components within a lichen using mass spectrometry. This approach allowed the identification of chemically distinct sections within this composite organism. Using our multipronged approach, various fungal natural products, not previously reported from lichens, were identified and two different fungal layers were visualized at the chemical level. PMID:28028548

Discriminating topology in galaxy distributions using network analysis

NASA Astrophysics Data System (ADS)

Hong, Sungryong; Coutinho, Bruno C.; Dey, Arjun; Barabási, Albert-L.; Vogelsberger, Mark; Hernquist, Lars; Gebhardt, Karl

2016-07-01

The large-scale distribution of galaxies is generally analysed using the two-point correlation function. However, this statistic does not capture the topology of the distribution, and it is necessary to resort to higher order correlations to break degeneracies. We demonstrate that an alternate approach using network analysis can discriminate between topologically different distributions that have similar two-point correlations. We investigate two galaxy point distributions, one produced by a cosmological simulation and the other by a Lévy walk. For the cosmological simulation, we adopt the redshift z = 0.58 slice from Illustris and select galaxies with stellar masses greater than 108 M⊙. The two-point correlation function of these simulated galaxies follows a single power law, ξ(r) ˜ r-1.5. Then, we generate Lévy walks matching the correlation function and abundance with the simulated galaxies. We find that, while the two simulated galaxy point distributions have the same abundance and two-point correlation function, their spatial distributions are very different; most prominently, filamentary structures, absent in Lévy fractals. To quantify these missing topologies, we adopt network analysis tools and measure diameter, giant component, and transitivity from networks built by a conventional friends-of-friends recipe with various linking lengths. Unlike the abundance and two-point correlation function, these network quantities reveal a clear separation between the two simulated distributions; therefore, the galaxy distribution simulated by Illustris is not a Lévy fractal quantitatively. We find that the described network quantities offer an efficient tool for discriminating topologies and for comparing observed and theoretical distributions.

Vlasov dynamics of periodically driven systems

NASA Astrophysics Data System (ADS)

Banerjee, Soumyadip; Shah, Kushal

2018-04-01

Analytical solutions of the Vlasov equation for periodically driven systems are of importance in several areas of plasma physics and dynamical systems and are usually approximated using ponderomotive theory. In this paper, we derive the plasma distribution function predicted by ponderomotive theory using Hamiltonian averaging theory and compare it with solutions obtained by the method of characteristics. Our results show that though ponderomotive theory is relatively much easier to use, its predictions are very restrictive and are likely to be very different from the actual distribution function of the system. We also analyse all possible initial conditions which lead to periodic solutions of the Vlasov equation for periodically driven systems and conjecture that the irreducible polynomial corresponding to the initial condition must only have squares of the spatial and momentum coordinate. The resulting distribution function for other initial conditions is aperiodic and can lead to complex relaxation processes within the plasma.

Arctic Tundra Vegetation Functional Types Based on Photosynthetic Physiology and Optical Properties

NASA Technical Reports Server (NTRS)

Huemmrich, Karl Fred; Gamon, John A.; Tweedie, Craig E.; Campbell, Petya K. Entcheva; Landis, David R.; Middleton, Elizabeth M.

2013-01-01

Non-vascular plants (lichens and mosses) are significant components of tundra landscapes and may respond to climate change differently from vascular plants affecting ecosystem carbon balance. Remote sensing provides critical tools for monitoring plant cover types, as optical signals provide a way to scale from plot measurements to regional estimates of biophysical properties, for which spatial-temporal patterns may be analyzed. Gas exchange measurements were collected for pure patches of key vegetation functional types (lichens, mosses, and vascular plants) in sedge tundra at Barrow, AK. These functional types were found to have three significantly different values of light use efficiency (LUE) with values of 0.013 plus or minus 0.0002, 0.0018 plus or minus 0.0002, and 0.0012 plus or minus 0.0001 mol C mol (exp -1) absorbed quanta for vascular plants, mosses and lichens, respectively. Discriminant analysis of the spectra reflectance of these patches identified five spectral bands that separated each of these vegetation functional types as well as nongreen material (bare soil, standing water, and dead leaves). These results were tested along a 100 m transect where midsummer spectral reflectance and vegetation coverage were measured at one meter intervals. Along the transect, area-averaged canopy LUE estimated from coverage fractions of the three functional types varied widely, even over short distances. The patch-level statistical discriminant functions applied to in situ hyperspectral reflectance data collected along the transect successfully unmixed cover fractions of the vegetation functional types. The unmixing functions, developed from the transect data, were applied to 30 m spatial resolution Earth Observing-1 Hyperion imaging spectrometer data to examine variability in distribution of the vegetation functional types for an area near Barrow, AK. Spatial variability of LUE was derived from the observed functional type distributions. Across this landscape, a fivefold variation in tundra LUE was observed. LUE calculated from the functional type cover fractions was also correlated to a spectral vegetation index developed to detect vegetation chlorophyll content. The concurrence of these alternate methods suggest that hyperspectral remote sensing can distinguish functionally distinct vegetation types and can be used to develop regional estimates of photosynthetic LUE in tundra landscapes.

Spatial patterns of distribution and abundance of Harrisia portoricensis, an endangered Caribbean cactus

Treesearch

J. Rojas-Sandoval; E. J. Melendez-Ackerman; NO-VALUE

2013-01-01

Aims The spatial distribution of biotic and abiotic factors may play a dominant role in determining the distribution and abundance of plants in arid and semiarid environments. In this study, we evaluated how spatial patterns of microhabitat variables and the degree of spatial dependence of these variables influence the distribution and abundance of the endangered...

[Spatial distribution pattern of Chilo suppressalis analyzed by classical method and geostatistics].

PubMed

Yuan, Zheming; Fu, Wei; Li, Fangyi

2004-04-01

Two original samples of Chilo suppressalis and their grid, random and sequence samples were analyzed by classical method and geostatistics to characterize the spatial distribution pattern of C. suppressalis. The limitations of spatial distribution analysis with classical method, especially influenced by the original position of grid, were summarized rather completely. On the contrary, geostatistics characterized well the spatial distribution pattern, congregation intensity and spatial heterogeneity of C. suppressalis. According to geostatistics, the population was up to Poisson distribution in low density. As for higher density population, its distribution was up to aggregative, and the aggregation intensity and dependence range were 0.1056 and 193 cm, respectively. Spatial heterogeneity was also found in the higher density population. Its spatial correlativity in line direction was more closely than that in row direction, and the dependence ranges in line and row direction were 115 and 264 cm, respectively.

Importance of spatial autocorrelation in modeling bird distributions at a continental scale

USGS Publications Warehouse

Bahn, V.; O'Connor, R.J.; Krohn, W.B.

2006-01-01

Spatial autocorrelation in species' distributions has been recognized as inflating the probability of a type I error in hypotheses tests, causing biases in variable selection, and violating the assumption of independence of error terms in models such as correlation or regression. However, it remains unclear whether these problems occur at all spatial resolutions and extents, and under which conditions spatially explicit modeling techniques are superior. Our goal was to determine whether spatial models were superior at large extents and across many different species. In addition, we investigated the importance of purely spatial effects in distribution patterns relative to the variation that could be explained through environmental conditions. We studied distribution patterns of 108 bird species in the conterminous United States using ten years of data from the Breeding Bird Survey. We compared the performance of spatially explicit regression models with non-spatial regression models using Akaike's information criterion. In addition, we partitioned the variance in species distributions into an environmental, a pure spatial and a shared component. The spatially-explicit conditional autoregressive regression models strongly outperformed the ordinary least squares regression models. In addition, partialling out the spatial component underlying the species' distributions showed that an average of 17% of the explained variation could be attributed to purely spatial effects independent of the spatial autocorrelation induced by the underlying environmental variables. We concluded that location in the range and neighborhood play an important role in the distribution of species. Spatially explicit models are expected to yield better predictions especially for mobile species such as birds, even in coarse-grained models with a large extent. ?? Ecography.

Plasma Indicator Dispersion in Arteries of the Human Leg

PubMed Central

Bassingthwaighte, James B.

2010-01-01

Indicator-dilution curves were recorded from the femoral and dorsalis pedis arteries of five normal men after injections of indocyanine green into the superior vena cava or thoracic aorta. By considering the femoral curves as inputs to a mathematically linear system and the dorsalis pedis curves as outputs, transfer functions (the distribution of transit times) for the arterial segment between these sites were obtained in terms of a four-parameter model, the lagged normal density curve, over a sixfold range of flow rates. The parameters of the spread (dispersion) of 57 transfer functions were proportional to the mean transit time. The mean difference between transit time and appearance time was 0.30 t̄; the square root of the variances was 0.18 t̄. These linear relationships suggest that flow rate has no significant influence on dispersion and that, since no transition from laminar to turbulent flow was apparent, arterial flow characteristics were not significantly changed over a wide range of flow rates. The secondary implication is that the rate of spatial longitudinal spreading of indicator with distance traveled is primarily a function of the geometry of the arterial system, not of the rate of flow, and, therefore, that the spatial distribution at any instant is a function of this rate and of the distance traveled through the system. PMID:5330717

Determination of the Point-Spread Function for the FERMI Large Area Telescope from On-Orbit Data and Limits on Pair Halos of Active Galactic Nuclei

DOE PAGES

Ackermann, M.; Ajello, M.; Allafort, A.; ...

2013-02-15

We present the Large Area Telescope (LAT) on the Fermi Gamma-ray Space Telescope is a pair-conversion telescope designed to detect photons with energies from ≈20 MeV to >300 GeV. The pre-launch response functions of the LAT were determined through extensive Monte Carlo simulations and beam tests. The point-spread function (PSF) characterizing the angular distribution of reconstructed photons as a function of energy and geometry in the detector is determined here from two years of on-orbit data by examining the distributions of γ rays from pulsars and active galactic nuclei (AGNs). Above 3 GeV, the PSF is found to be broadermore » than the pre-launch PSF. We checked for dependence of the PSF on the class of γ-ray source and observation epoch and found none. We also investigated several possible spatial models for pair-halo emission around BL Lac AGNs. Finally, we found no evidence for a component with spatial extension larger than the PSF and set upper limits on the amplitude of halo emission in stacked images of low- and high-redshift BL Lac AGNs and the TeV blazars 1ES0229+200 and 1ES0347–121.« less

Nucleon localization and fragment formation in nuclear fission

DOE PAGES

Zhang, C. L.; Schuetrumpf, B.; Nazarewicz, W.

2016-12-27

An electron localization measure was originally introduced to characterize chemical bond structures in molecules. Recently, a nucleon localization based on Hartree-Fock densities has been introduced to investigate α-cluster structures in light nuclei. Compared to the local nucleonic densities, the nucleon localization function has been shown to be an excellent indicator of shell effects and cluster correlations. In this work, using the spatial nucleon localization measure, we investigated the emergence of fragments in fissioning heavy nuclei using the self-consistent energy density functional method with a quantified energy density functional optimized for fission studies. We studied the particle densities and spatial nucleonmore » localization distributions along the fission pathways of 264Fm, 232Th, and 240Pu. We demonstrated that the fission fragments were formed fairly early in the evolution, well before scission. To illustrate the usefulness of the localization measure, we showed how the hyperdeformed state of 232Th could be understood in terms of a quasimolecular state made of 132Sn and 100Zr fragments. Compared to nucleonic distributions, the nucleon localization function more effectively quantifies nucleonic clustering: its characteristic oscillating pattern, traced back to shell effects, is a clear fingerprint of cluster/fragment configurations. This is of particular interest for studies of fragment formation and fragment identification in fissioning nuclei.« less

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

Zhang, C. L.; Schuetrumpf, B.; Nazarewicz, W.

An electron localization measure was originally introduced to characterize chemical bond structures in molecules. Recently, a nucleon localization based on Hartree-Fock densities has been introduced to investigate α-cluster structures in light nuclei. Compared to the local nucleonic densities, the nucleon localization function has been shown to be an excellent indicator of shell effects and cluster correlations. In this work, using the spatial nucleon localization measure, we investigated the emergence of fragments in fissioning heavy nuclei using the self-consistent energy density functional method with a quantified energy density functional optimized for fission studies. We studied the particle densities and spatial nucleonmore » localization distributions along the fission pathways of 264Fm, 232Th, and 240Pu. We demonstrated that the fission fragments were formed fairly early in the evolution, well before scission. To illustrate the usefulness of the localization measure, we showed how the hyperdeformed state of 232Th could be understood in terms of a quasimolecular state made of 132Sn and 100Zr fragments. Compared to nucleonic distributions, the nucleon localization function more effectively quantifies nucleonic clustering: its characteristic oscillating pattern, traced back to shell effects, is a clear fingerprint of cluster/fragment configurations. This is of particular interest for studies of fragment formation and fragment identification in fissioning nuclei.« less

HABSEED: a Simple Spatially Explicit Meta-Populations Model Using Remote Sensing Derived Habitat Quality Data

NASA Astrophysics Data System (ADS)

Heumann, B. W.; Guichard, F.; Seaquist, J. W.

2005-05-01

The HABSEED model uses remote sensing derived NPP as a surrogate for habitat quality as the driving mechanism for population growth and local seed dispersal. The model has been applied to the Sahel region of Africa. Results show that the functional response of plants to habitat quality alters population distribution. Plants more tolerant of medium quality habitat have greater distributions to the North while plants requiring only the best habitat are limited to the South. For all functional response types, increased seed production results in diminishing returns. Functional response types have been related to life history tradeoffs and r-K strategies based on the results. Results are compared to remote sensing derived vegetation land cover.

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

NASA Astrophysics Data System (ADS)

Žukovič, Milan; Hristopulos, Dionissios T.

2009-02-01

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

Spatially Distributed Characterization of Catchment Dynamics Using Travel-Time Distributions

NASA Astrophysics Data System (ADS)

Heße, F.; Zink, M.; Attinger, S.

2015-12-01

The description of storage and transport of both water and solved contaminants in catchments is very difficult due to the high heterogeneity of the subsurface properties that govern their fate. This heterogeneity, combined with a generally limited knowledge about the subsurface, results in high degrees of uncertainty. As a result, stochastic methods are increasingly applied, where the relevant processes are modeled as being random. Within these methods, quantities like the catchment travel or residence time of a water parcel are described using probability density functions (PDF). The derivation of these PDF's is typically done by using the water fluxes and states of the catchment. A successful application of such frameworks is therefore contingent on a good quantification of these fluxes and states across the different spatial scales. The objective of this study is to use travel times for the characterization of an ca. 1000 square kilometer, humid catchment in Central Germany. To determine the states and fluxes, we apply the mesoscale Hydrological Model mHM, a spatially distributed hydrological model to the catchment. Using detailed data of precipitation, land cover, morphology and soil type as inputs, mHM is able to determine fluxes like recharge and evapotranspiration and states like soil moisture as outputs. Using these data, we apply the above theoretical framework to our catchment. By virtue of the aforementioned properties of mHM, we are able to describe the storage and release of water with a high spatial resolution. This allows for a comprehensive description of the flow and transport dynamics taking place in the catchment. The spatial distribution of such dynamics is then compared with land cover and soil moisture maps as well as driving forces like precipitation and temperature to determine the most predictive factors. In addition, we investigate how non-local data like the age distribution of discharge flows are impacted by, and therefore allow to infer, local properties of the catchment.

From chemotaxis to the cognitive map: The function of olfaction

PubMed Central

Jacobs, Lucia F.

2012-01-01

A paradox of vertebrate brain evolution is the unexplained variability in the size of the olfactory bulb (OB), in contrast to other brain regions, which scale predictably with brain size. Such variability appears to be the result of selection for olfactory function, yet there is no obvious concordance that would predict the causal relationship between OB size and behavior. This discordance may derive from assuming the primary function of olfaction is odorant discrimination and acuity. If instead the primary function of olfaction is navigation, i.e., predicting odorant distributions in time and space, variability in absolute OB size could be ascribed and explained by variability in navigational demand. This olfactory spatial hypothesis offers a single functional explanation to account for patterns of olfactory system scaling in vertebrates, the primacy of olfaction in spatial navigation, even in visual specialists, and proposes an evolutionary scenario to account for the convergence in olfactory structure and function across protostomes and deuterostomes. In addition, the unique percepts of olfaction may organize odorant information in a parallel map structure. This could have served as a scaffold for the evolution of the parallel map structure of the mammalian hippocampus, and possibly the arthropod mushroom body, and offers an explanation for similar flexible spatial navigation strategies in arthropods and vertebrates. PMID:22723365

Cardiac neuronal hierarchy in health and disease.

PubMed

Armour, J Andrew

2004-08-01

The cardiac neuronal hierarchy can be represented as a redundant control system made up of spatially distributed cell stations comprising afferent, efferent, and interconnecting neurons. Its peripheral and central neurons are in constant communication with one another such that, for the most part, it behaves as a stochastic control system. Neurons distributed throughout this hierarchy interconnect via specific linkages such that each neuronal cell station is involved in temporally dependent cardio-cardiac reflexes that control overlapping, spatially organized cardiac regions. Its function depends primarily, but not exclusively, on inputs arising from afferent neurons transducing the cardiovascular milieu to directly or indirectly (via interconnecting neurons) modify cardiac motor neurons coordinating regional cardiac behavior. As the function of the whole is greater than that of its individual parts, stable cardiac control occurs most of the time in the absence of direct cause and effect. During altered cardiac status, its redundancy normally represents a stabilizing feature. However, in the presence of regional myocardial ischemia, components within the intrinsic cardiac nervous system undergo pathological change. That, along with any consequent remodeling of the cardiac neuronal hierarchy, alters its spatially and temporally organized reflexes such that populations of neurons, acting in isolation, may destabilize efferent neuronal control of regional cardiac electrical and/or mechanical events.

Random field assessment of nanoscopic inhomogeneity of bone

PubMed Central

Dong, X. Neil; Luo, Qing; Sparkman, Daniel M.; Millwater, Harry R.; Wang, Xiaodu

2010-01-01

Bone quality is significantly correlated with the inhomogeneous distribution of material and ultrastructural properties (e.g., modulus and mineralization) of the tissue. Current techniques for quantifying inhomogeneity consist of descriptive statistics such as mean, standard deviation and coefficient of variation. However, these parameters do not describe the spatial variations of bone properties. The objective of this study was to develop a novel statistical method to characterize and quantitatively describe the spatial variation of bone properties at ultrastructural levels. To do so, a random field defined by an exponential covariance function was used to present the spatial uncertainty of elastic modulus by delineating the correlation of the modulus at different locations in bone lamellae. The correlation length, a characteristic parameter of the covariance function, was employed to estimate the fluctuation of the elastic modulus in the random field. Using this approach, two distribution maps of the elastic modulus within bone lamellae were generated using simulation and compared with those obtained experimentally by a combination of atomic force microscopy and nanoindentation techniques. The simulation-generated maps of elastic modulus were in close agreement with the experimental ones, thus validating the random field approach in defining the inhomogeneity of elastic modulus in lamellae of bone. Indeed, generation of such random fields will facilitate multi-scale modeling of bone in more pragmatic details. PMID:20817128

Geotechnical parameter spatial distribution stochastic analysis based on multi-precision information assimilation

NASA Astrophysics Data System (ADS)

Wang, C.; Rubin, Y.

2014-12-01

Spatial distribution of important geotechnical parameter named compression modulus Es contributes considerably to the understanding of the underlying geological processes and the adequate assessment of the Es mechanics effects for differential settlement of large continuous structure foundation. These analyses should be derived using an assimilating approach that combines in-situ static cone penetration test (CPT) with borehole experiments. To achieve such a task, the Es distribution of stratum of silty clay in region A of China Expo Center (Shanghai) is studied using the Bayesian-maximum entropy method. This method integrates rigorously and efficiently multi-precision of different geotechnical investigations and sources of uncertainty. Single CPT samplings were modeled as a rational probability density curve by maximum entropy theory. Spatial prior multivariate probability density function (PDF) and likelihood PDF of the CPT positions were built by borehole experiments and the potential value of the prediction point, then, preceding numerical integration on the CPT probability density curves, the posterior probability density curve of the prediction point would be calculated by the Bayesian reverse interpolation framework. The results were compared between Gaussian Sequential Stochastic Simulation and Bayesian methods. The differences were also discussed between single CPT samplings of normal distribution and simulated probability density curve based on maximum entropy theory. It is shown that the study of Es spatial distributions can be improved by properly incorporating CPT sampling variation into interpolation process, whereas more informative estimations are generated by considering CPT Uncertainty for the estimation points. Calculation illustrates the significance of stochastic Es characterization in a stratum, and identifies limitations associated with inadequate geostatistical interpolation techniques. This characterization results will provide a multi-precision information assimilation method of other geotechnical parameters.

Geographical ecology of the palms (Arecaceae): determinants of diversity and distributions across spatial scales

PubMed Central

Eiserhardt, Wolf L.; Svenning, Jens-Christian; Kissling, W. Daniel; Balslev, Henrik

2011-01-01

Background The palm family occurs in all tropical and sub-tropical regions of the world. Palms are of high ecological and economical importance, and display complex spatial patterns of species distributions and diversity. Scope This review summarizes empirical evidence for factors that determine palm species distributions, community composition and species richness such as the abiotic environment (climate, soil chemistry, hydrology and topography), the biotic environment (vegetation structure and species interactions) and dispersal. The importance of contemporary vs. historical impacts of these factors and the scale at which they function is discussed. Finally a hierarchical scale framework is developed to guide predictor selection for future studies. Conclusions Determinants of palm distributions, composition and richness vary with spatial scale. For species distributions, climate appears to be important at landscape and broader scales, soil, topography and vegetation at landscape and local scales, hydrology at local scales, and dispersal at all scales. For community composition, soil appears important at regional and finer scales, hydrology, topography and vegetation at landscape and local scales, and dispersal again at all scales. For species richness, climate and dispersal appear to be important at continental to global scales, soil at landscape and broader scales, and topography at landscape and finer scales. Some scale–predictor combinations have not been studied or deserve further attention, e.g. climate on regional to finer scales, and hydrology and topography on landscape and broader scales. The importance of biotic interactions – apart from general vegetation structure effects – for the geographic ecology of palms is generally underexplored. Future studies should target scale–predictor combinations and geographic domains not studied yet. To avoid biased inference, one should ideally include at least all predictors previously found important at the spatial scale of investigation. PMID:21712297

Confined active Brownian particles: theoretical description of propulsion-induced accumulation

NASA Astrophysics Data System (ADS)

Das, Shibananda; Gompper, Gerhard; Winkler, Roland G.

2018-01-01

The stationary-state distribution function of confined active Brownian particles (ABPs) is analyzed by computer simulations and analytical calculations. We consider a radial harmonic as well as an anharmonic confinement potential. In the simulations, the ABP is propelled with a prescribed velocity along a body-fixed direction, which is changing in a diffusive manner. For the analytical approach, the Cartesian components of the propulsion velocity are assumed to change independently; active Ornstein-Uhlenbeck particle (AOUP). This results in very different velocity distribution functions. The analytical solution of the Fokker-Planck equation for an AOUP in a harmonic potential is presented and a conditional distribution function is provided for the radial particle distribution at a given magnitude of the propulsion velocity. This conditional probability distribution facilitates the description of the coupling of the spatial coordinate and propulsion, which yields activity-induced accumulation of particles. For the anharmonic potential, a probability distribution function is derived within the unified colored noise approximation. The comparison of the simulation results with theoretical predictions yields good agreement for large rotational diffusion coefficients, e.g. due to tumbling, even for large propulsion velocities (Péclet numbers). However, we find significant deviations already for moderate Péclet number, when the rotational diffusion coefficient is on the order of the thermal one.

Generic patterns in the evolution of urban water networks: Evidence from a large Asian city

NASA Astrophysics Data System (ADS)

Krueger, Elisabeth; Klinkhamer, Christopher; Urich, Christian; Zhan, Xianyuan; Rao, P. Suresh C.

2017-03-01

We examine high-resolution urban infrastructure data using every pipe for the water distribution network (WDN) and sanitary sewer network (SSN) in a large Asian city (≈4 million residents) to explore the structure as well as the spatial and temporal evolution of these infrastructure networks. Network data were spatially disaggregated into multiple subnets to examine intracity topological differences for functional zones of the WDN and SSN, and time-stamped SSN data were examined to understand network evolution over several decades as the city expanded. Graphs were generated using a dual-mapping technique (Hierarchical Intersection Continuity Negotiation), which emphasizes the functional attributes of these networks. Network graphs for WDNs and SSNs are characterized by several network topological metrics, and a double Pareto (power-law) model approximates the node-degree distributions of both water infrastructure networks (WDN and SSN), across spatial and hierarchical scales relevant to urban settings, and throughout their temporal evolution over several decades. These results indicate that generic mechanisms govern the networks' evolution, similar to those of scale-free networks found in nature. Deviations from the general topological patterns are indicative of (1) incomplete establishment of network hierarchies and functional network evolution, (2) capacity for growth (expansion) or densification (e.g., in-fill), and (3) likely network vulnerabilities. We discuss the implications of our findings for the (re-)design of urban infrastructure networks to enhance their resilience to external and internal threats.

Geostatistical Interpolation of Particle-Size Curves in Heterogeneous Aquifers

NASA Astrophysics Data System (ADS)

Guadagnini, A.; Menafoglio, A.; Secchi, P.

2013-12-01

We address the problem of predicting the spatial field of particle-size curves (PSCs) from measurements associated with soil samples collected at a discrete set of locations within an aquifer system. Proper estimates of the full PSC are relevant to applications related to groundwater hydrology, soil science and geochemistry and aimed at modeling physical and chemical processes occurring in heterogeneous earth systems. Hence, we focus on providing kriging estimates of the entire PSC at unsampled locations. To this end, we treat particle-size curves as cumulative distribution functions, model their densities as functional compositional data and analyze them by embedding these into the Hilbert space of compositional functions endowed with the Aitchison geometry. On this basis, we develop a new geostatistical methodology for the analysis of spatially dependent functional compositional data. Our functional compositional kriging (FCK) approach allows providing predictions at unsampled location of the entire particle-size curve, together with a quantification of the associated uncertainty, by fully exploiting both the functional form of the data and their compositional nature. This is a key advantage of our approach with respect to traditional methodologies, which treat only a set of selected features (e.g., quantiles) of PSCs. Embedding the full PSC into a geostatistical analysis enables one to provide a complete characterization of the spatial distribution of lithotypes in a reservoir, eventually leading to improved predictions of soil hydraulic attributes through pedotransfer functions as well as of soil geochemical parameters which are relevant in sorption/desorption and cation exchange processes. We test our new method on PSCs sampled along a borehole located within an alluvial aquifer near the city of Tuebingen, Germany. The quality of FCK predictions is assessed through leave-one-out cross-validation. A comparison between hydraulic conductivity estimates obtained via FCK approach and those predicted by classical kriging of effective particle diameters (i.e., quantiles of the PSCs) is finally performed.

Delineating ecological regions in marine systems: Integrating physical structure and community composition to inform spatial management in the eastern Bering Sea

NASA Astrophysics Data System (ADS)

Baker, Matthew R.; Hollowed, Anne B.

2014-11-01

Characterizing spatial structure and delineating meaningful spatial boundaries have useful applications to understanding regional dynamics in marine systems, and are integral to ecosystem approaches to fisheries management. Physical structure and drivers combine with biological responses and interactions to organize marine systems in unique ways at multiple scales. We apply multivariate statistical methods to define spatially coherent ecological units or ecoregions in the eastern Bering Sea. We also illustrate a practical approach to integrate data on species distribution, habitat structure and physical forcing mechanisms to distinguish areas with distinct biogeography as one means to define management units in large marine ecosystems. We use random forests to quantify the relative importance of habitat and environmental variables to the distribution of individual species, and to quantify shifts in multispecies assemblages or community composition along environmental gradients. Threshold shifts in community composition are used to identify regions with distinct physical and biological attributes, and to evaluate the relative importance of predictor variables to determining regional boundaries. Depth, bottom temperature and frontal boundaries were dominant factors delineating distinct biological communities in this system, with a latitudinal divide at approximately 60°N. Our results indicate that distinct climatic periods will shift habitat gradients and that dynamic physical variables such as temperature and stratification are important to understanding temporal stability of ecoregion boundaries. We note distinct distribution patterns among functional guilds and also evidence for resource partitioning among individual species within each guild. By integrating physical and biological data to determine spatial patterns in community composition, we partition ecosystems along ecologically significant gradients. This may provide a basis for defining spatial management units or serve as a baseline index for analyses of structural shifts in the physical environment, species abundance and distribution, and community dynamics over time.

Molecular dynamics simulation of the ionic liquid N-octylpyridinium tetrafluoroborate and acetonitrile: Thermodynamic and structural properties

NASA Astrophysics Data System (ADS)

Zhou, Siwen; Zhu, Guanglai; Kang, Xianqu; Li, Qiang; Sha, Maolin; Cui, Zhifeng; Xu, Xinsheng

2018-06-01

Using molecular dynamics simulation, the research obtained the thermodynamic properties and microstructures of the mixture of N-octylpyridinium tetrafluoroborate and acetonitrile, including density, self-diffusion coefficients, excess properties, radial distribution functions (RDFs) and spatial distribution functions (SDFs). Both RDFs and SDFs indicate that the local microstructure of the polar region is different from the nonpolar region with different mole fraction of ionic liquids. Acetonitrile could increase the order of the polar regions. While with acetonitrile increasing, the orderliness of the nonpolar region increases firstly and then decreases. In relatively dilute solution, ionic liquids were dispersed to form small aggregates wrapped by acetonitrile.

Development of optimal models of porous media by combining static and dynamic data: the permeability and porosity distributions.

PubMed

Hamzehpour, Hossein; Rasaei, M Reza; Sahimi, Muhammad

2007-05-01

We describe a method for the development of the optimal spatial distributions of the porosity phi and permeability k of a large-scale porous medium. The optimal distributions are constrained by static and dynamic data. The static data that we utilize are limited data for phi and k, which the method honors in the optimal model and utilizes their correlation functions in the optimization process. The dynamic data include the first-arrival (FA) times, at a number of receivers, of seismic waves that have propagated in the porous medium, and the time-dependent production rates of a fluid that flows in the medium. The method combines the simulated-annealing method with a simulator that solves numerically the three-dimensional (3D) acoustic wave equation and computes the FA times, and a second simulator that solves the 3D governing equation for the fluid's pressure as a function of time. To our knowledge, this is the first time that an optimization method has been developed to determine simultaneously the global minima of two distinct total energy functions. As a stringent test of the method's accuracy, we solve for flow of two immiscible fluids in the same porous medium, without using any data for the two-phase flow problem in the optimization process. We show that the optimal model, in addition to honoring the data, also yields accurate spatial distributions of phi and k, as well as providing accurate quantitative predictions for the single- and two-phase flow problems. The efficiency of the computations is discussed in detail.

Deducing Electron Properties from Hard X-Ray Observations

NASA Technical Reports Server (NTRS)

Kontar, E. P.; Brown, J. C.; Emslie, A. G.; Hajdas, W.; Holman, G. D.; Hurford, G. J.; Kasparova, J.; Mallik, P. C. V.; Massone, A. M.; McConnell, M. L.;

Oceanic protists with different forms of acquired phototrophy display contrasting biogeographies and abundance.

PubMed

Leles, S G; Mitra, A; Flynn, K J; Stoecker, D K; Hansen, P J; Calbet, A; McManus, G B; Sanders, R W; Caron, D A; Not, F; Hallegraeff, G M; Pitta, P; Raven, J A; Johnson, M D; Glibert, P M; Våge, S

2017-08-16

This first comprehensive analysis of the global biogeography of marine protistan plankton with acquired phototrophy shows these mixotrophic organisms to be ubiquitous and abundant; however, their biogeography differs markedly between different functional groups. These mixotrophs, lacking a constitutive capacity for photosynthesis (i.e. non-constitutive mixotrophs, NCMs), acquire their phototrophic potential through either integration of prey-plastids or through endosymbiotic associations with photosynthetic microbes. Analysis of field data reveals that 40-60% of plankton traditionally labelled as (non-phototrophic) microzooplankton are actually NCMs, employing acquired phototrophy in addition to phagotrophy. Specialist NCMs acquire chloroplasts or endosymbionts from specific prey, while generalist NCMs obtain chloroplasts from a variety of prey. These contrasting functional types of NCMs exhibit distinct seasonal and spatial global distribution patterns. Mixotrophs reliant on 'stolen' chloroplasts, controlled by prey diversity and abundance, dominate in high-biomass areas. Mixotrophs harbouring intact symbionts are present in all waters and dominate particularly in oligotrophic open ocean systems. The contrasting temporal and spatial patterns of distribution of different mixotroph functional types across the oceanic provinces, as revealed in this study, challenges traditional interpretations of marine food web structures. Mixotrophs with acquired phototrophy (NCMs) warrant greater recognition in marine research. © 2017 The Author(s).

Geomorphic effectiveness of a long profile shape and the role of inherent geological controls in the Himalayan hinterland area of the Ganga River basin, India

NASA Astrophysics Data System (ADS)

Sonam; Jain, Vikrant

2018-03-01

Long profiles of rivers provide a platform to analyse interaction between geological and geomorphic processes operating at different time scales. Identification of an appropriate model for river long profile becomes important in order to establish a quantitative relationship between the profile shape, its geomorphic effectiveness, and inherent geological characteristics. This work highlights the variability in the long profile shape of the Ganga River and its major tributaries, its impact on stream power distribution pattern, and role of the geological controls on it. Long profile shapes are represented by the sum of two exponential functions through the curve fitting method. We have shown that coefficients of river long profile equations are governed by the geological characteristics of subbasins. These equations further define the spatial distribution pattern of stream power and help to understand stream power variability in different geological terrains. Spatial distribution of stream power in different geological terrains successfully explains spatial variability in geomorphic processes within the Himalayan hinterland area. In general, the stream power peaks of larger rivers lie in the Higher Himalaya, and rivers in the eastern hinterland area are characterised by the highest magnitude of stream power.

The Node Deployment of Intelligent Sensor Networks Based on the Spatial Difference of Farmland Soil.

PubMed

Liu, Naisen; Cao, Weixing; Zhu, Yan; Zhang, Jingchao; Pang, Fangrong; Ni, Jun

2015-11-11

Considering that agricultural production is characterized by vast areas, scattered fields and long crop growth cycles, intelligent wireless sensor networks (WSNs) are suitable for monitoring crop growth information. Cost and coverage are the most key indexes for WSN applications. The differences in crop conditions are influenced by the spatial distribution of soil nutrients. If the nutrients are distributed evenly, the crop conditions are expected to be approximately uniform with little difference; on the contrary, there will be great differences in crop conditions. In accordance with the differences in the spatial distribution of soil information in farmland, fuzzy c-means clustering was applied to divide the farmland into several areas, where the soil fertility of each area is nearly uniform. Then the crop growth information in the area could be monitored with complete coverage by deploying a sensor node there, which could greatly decrease the deployed sensor nodes. Moreover, in order to accurately judge the optimal cluster number of fuzzy c-means clustering, a discriminant function for Normalized Intra-Cluster Coefficient of Variation (NICCV) was established. The sensitivity analysis indicates that NICCV is insensitive to the fuzzy weighting exponent, but it shows a strong sensitivity to the number of clusters.

Spatial Interpolation of Rain-field Dynamic Time-Space Evolution in Hong Kong

NASA Astrophysics Data System (ADS)

Liu, P.; Tung, Y. K.

2017-12-01

Accurate and reliable measurement and prediction of spatial and temporal distribution of rain-field over a wide range of scales are important topics in hydrologic investigations. In this study, geostatistical treatment of precipitation field is adopted. To estimate the rainfall intensity over a study domain with the sample values and the spatial structure from the radar data, the cumulative distribution functions (CDFs) at all unsampled locations were estimated. Indicator Kriging (IK) was used to estimate the exceedance probabilities for different pre-selected cutoff levels and a procedure was implemented for interpolating CDF values between the thresholds that were derived from the IK. Different interpolation schemes of the CDF were proposed and their influences on the performance were also investigated. The performance measures and visual comparison between the observed rain-field and the IK-based estimation suggested that the proposed method can provide fine results of estimation of indicator variables and is capable of producing realistic image.

Effects of polymers on the spatial structure of turbulent flows

NASA Astrophysics Data System (ADS)

Sinhuber, Michael; Ballouz, Joseph G.; Ouellette, Nicholas T.

2017-11-01

It is well known that the addition of minor amounts of polymers to a turbulent water flow can significantly change its properties. One of the most prominent effects is the observed drastic reduction of drag in wall-bounded flows that is utilized in many engineering applications. Much of the research on polymers in turbulence has focused on their influence on the turbulent energy cascade and their interaction with the energy transfer processes. Much less investigated are their effects on the spatial structure of turbulent flows. In a classical von-Kárman swirling flow setup, we used Lagrangian particle tracking to obtain three-dimensional particle trajectories, velocities, and accelerations and find that polymers have a significant effect on Lagrangian measures of the turbulence structure such as radial distribution functions and the curvature of particle trajectories. We find that not only do the statistical distributions change, but also that polymers appear to affect the spatial statistics well beyond the size of the polymers themselves.

Spatially-Dependent Modelling of Pulsar Wind Nebula G0.9+0.1

NASA Astrophysics Data System (ADS)

van Rensburg, C.; Krüger, P. P.; Venter, C.

2018-03-01

We present results from a leptonic emission code that models the spectral energy distribution of a pulsar wind nebula by solving a Fokker-Planck-type transport equation and calculating inverse Compton and synchrotron emissivities. We have created this time-dependent, multi-zone model to investigate changes in the particle spectrum as they traverse the pulsar wind nebula, by considering a time and spatially-dependent B-field, spatially-dependent bulk particle speed implying convection and adiabatic losses, diffusion, as well as radiative losses. Our code predicts the radiation spectrum at different positions in the nebula, yielding the surface brightness versus radius and the nebular size as function of energy. We compare our new model against more basic models using the observed spectrum of pulsar wind nebula G0.9+0.1, incorporating data from H.E.S.S. as well as radio and X-ray experiments. We show that simultaneously fitting the spectral energy distribution and the energy-dependent source size leads to more stringent constraints on several model parameters.

Spatially dependent modelling of pulsar wind nebula G0.9+0.1

NASA Astrophysics Data System (ADS)

van Rensburg, C.; Krüger, P. P.; Venter, C.

2018-07-01

We present results from a leptonic emission code that models the spectral energy distribution of a pulsar wind nebula by solving a Fokker-Planck-type transport equation and calculating inverse Compton and synchrotron emissivities. We have created this time-dependent, multizone model to investigate changes in the particle spectrum as they traverse the pulsar wind nebula, by considering a time and spatially dependent B-field, spatially dependent bulk particle speed implying convection and adiabatic losses, diffusion, as well as radiative losses. Our code predicts the radiation spectrum at different positions in the nebula, yielding the surface brightness versus radius and the nebular size as function of energy. We compare our new model against more basic models using the observed spectrum of pulsar wind nebula G0.9+0.1, incorporating data from H.E.S.S. as well as radio and X-ray experiments. We show that simultaneously fitting the spectral energy distribution and the energy-dependent source size leads to more stringent constraints on several model parameters.

Zipf's law from scale-free geometry.

PubMed

Lin, Henry W; Loeb, Abraham

2016-03-01

The spatial distribution of people exhibits clustering across a wide range of scales, from household (∼10(-2) km) to continental (∼10(4) km) scales. Empirical data indicate simple power-law scalings for the size distribution of cities (known as Zipf's law) and the population density fluctuations as a function of scale. Using techniques from random field theory and statistical physics, we show that these power laws are fundamentally a consequence of the scale-free spatial clustering of human populations and the fact that humans inhabit a two-dimensional surface. In this sense, the symmetries of scale invariance in two spatial dimensions are intimately connected to urban sociology. We test our theory by empirically measuring the power spectrum of population density fluctuations and show that the logarithmic slope α=2.04 ± 0.09, in excellent agreement with our theoretical prediction α=2. The model enables the analytic computation of many new predictions by importing the mathematical formalism of random fields.

The influence of competition between plant functional types in the Canadian Terrestrial Ecosystem Model (CTEM) v. 2.0

NASA Astrophysics Data System (ADS)

Melton, Joe; Arora, Vivek

2015-04-01

The Canadian Terrestrial Ecosystem Model (CTEM) is the interactive vegetation component in the earth system modelling framework of the Canadian Centre for Climate Modelling and Analysis (CCCma). In its current framework, CTEM uses prescribed fractional coverage of plant functional types (PFTs) in each grid cell. In reality, vegetation cover is continually adjusting to changes in climate, atmospheric composition, and anthropogenic forcing, for example, through human-caused fires and CO2 fertilization. These changes in vegetation spatial patterns occur over timescales of years to centuries as tree migration is a slow process and vegetation distributions inherently have inertia. Here, we present version 2.0 of CTEM that includes a representation of competition between PFTs through a modified version of the Lotka-Volterra (L-V) predator-prey equations. The simulated areal extents of CTEM's seven non-crop PFTs are compared with available observation-based estimates, and simulations using unmodified L-V equations (similar to other models like TRIFFID), to demonstrate that the model is able to represent the broad spatial distributions of its seven PFTs at the global scale. Differences remain, however, since representing the multitude of plant species with just seven non-crop PFTs only allows the large scale climatic controls on the distributions of PFTs to be captured. As expected, PFTs that exist in climate niches are difficult to represent either due to the coarse spatial resolution of the model and the corresponding driving climate or the limited number of PFTs used to model the terrestrial ecosystem processes. The geographic and zonal distributions of primary terrestrial carbon pools and fluxes from the versions of CTEM that use prescribed and dynamically simulated fractional coverage of PFTs compare reasonably with each other and observation-based estimates. These results illustrate that the parametrization of competition between PFTs in CTEM behaves in a reasonably realistic manner while the use of unmodified L-V equations results in unrealistic plant distributions.

Improved simulation of river water and groundwater exchange in an alluvial plain using the SWAT model

USDA-ARS?s Scientific Manuscript database

Hydrological interaction between surface and subsurface water systems has a significant impact on water quality, ecosystems and biogeochemistry cycling of both systems. Distributed models have been developed to simulate this function, but they require detailed spatial inputs and extensive computati...

Spatial distribution of hemlock woolly adelgid induced hemlock mortality in the Southern Appalachians

Treesearch

Tuula Kantola; Päivi Lyytikäinen-Saarenmaa; Robert N. Coulson; Sheryl Strauch; Maria D. Tchakerian; Markus Holopainen; Hannu Saarenmaa; Douglas A. Streett

2014-01-01

Hemlock woolly adelgid (Adelges tsugae Annand, HWA) outbreaks are posing a major threat to eastern hemlock (Tsuga canadensis L. Carr.) and Carolina hemlock (Tsuga caroliniana Engelm.) forest landscapes in the eastern USA. As foundation species, hemlocks play a variety of functional roles in forest landscapes....

Housing is positively associated with invasive exotic plant species richness in New England, USA

Treesearch

Gregorio I. Gavier-Pizarro; Volker C. Radeloff; Susan I. Stewart; Cynthia D. Huebner; Nicholas S. Keuler

2010-01-01

Understanding the factors related to invasive exotic species distributions at broad spatial scales has important theoretical and management implications, because biological invasions are detrimental to many ecosystem functions and processes. Housing development facilitates invasions by disturbing land cover, introducing nonnative landscaping plants, and facilitating...

Tidal wetland plant and algal assemblages in Oregon: spatial patterns of composition and vulnerability to climate change

EPA Science Inventory

Tidal wetlands support important ecosystem functions along the coast of the Pacific Northwest such as primary production and nutrient transformation. Sea-level rise (SLR) and elevated salinity due to climate change may affect the abundance, distribution, and diversity of plants a...

Development of a Heterogenic Distributed Environment for Spatial Data Processing Using Cloud Technologies

NASA Astrophysics Data System (ADS)

Garov, A. S.; Karachevtseva, I. P.; Matveev, E. V.; Zubarev, A. E.; Florinsky, I. V.

2016-06-01

We are developing a unified distributed communication environment for processing of spatial data which integrates web-, desktop- and mobile platforms and combines volunteer computing model and public cloud possibilities. The main idea is to create a flexible working environment for research groups, which may be scaled according to required data volume and computing power, while keeping infrastructure costs at minimum. It is based upon the "single window" principle, which combines data access via geoportal functionality, processing possibilities and communication between researchers. Using an innovative software environment the recently developed planetary information system (http://cartsrv.mexlab.ru/geoportal) will be updated. The new system will provide spatial data processing, analysis and 3D-visualization and will be tested based on freely available Earth remote sensing data as well as Solar system planetary images from various missions. Based on this approach it will be possible to organize the research and representation of results on a new technology level, which provides more possibilities for immediate and direct reuse of research materials, including data, algorithms, methodology, and components. The new software environment is targeted at remote scientific teams, and will provide access to existing spatial distributed information for which we suggest implementation of a user interface as an advanced front-end, e.g., for virtual globe system.

Spatial Metrics of Tumour Vascular Organisation Predict Radiation Efficacy in a Computational Model

PubMed Central

Scott, Jacob G.

2016-01-01

Intratumoural heterogeneity is known to contribute to poor therapeutic response. Variations in oxygen tension in particular have been correlated with changes in radiation response in vitro and at the clinical scale with overall survival. Heterogeneity at the microscopic scale in tumour blood vessel architecture has been described, and is one source of the underlying variations in oxygen tension. We seek to determine whether histologic scale measures of the erratic distribution of blood vessels within a tumour can be used to predict differing radiation response. Using a two-dimensional hybrid cellular automaton model of tumour growth, we evaluate the effect of vessel distribution on cell survival outcomes of simulated radiation therapy. Using the standard equations for the oxygen enhancement ratio for cell survival probability under differing oxygen tensions, we calculate average radiation effect over a range of different vessel densities and organisations. We go on to quantify the vessel distribution heterogeneity and measure spatial organization using Ripley’s L function, a measure designed to detect deviations from complete spatial randomness. We find that under differing regimes of vessel density the correlation coefficient between the measure of spatial organization and radiation effect changes sign. This provides not only a useful way to understand the differences seen in radiation effect for tissues based on vessel architecture, but also an alternate explanation for the vessel normalization hypothesis. PMID:26800503

Statistical analysis of mesoscale rainfall: Dependence of a random cascade generator on large-scale forcing

NASA Technical Reports Server (NTRS)

Over, Thomas, M.; Gupta, Vijay K.

1994-01-01

Under the theory of independent and identically distributed random cascades, the probability distribution of the cascade generator determines the spatial and the ensemble properties of spatial rainfall. Three sets of radar-derived rainfall data in space and time are analyzed to estimate the probability distribution of the generator. A detailed comparison between instantaneous scans of spatial rainfall and simulated cascades using the scaling properties of the marginal moments is carried out. This comparison highlights important similarities and differences between the data and the random cascade theory. Differences are quantified and measured for the three datasets. Evidence is presented to show that the scaling properties of the rainfall can be captured to the first order by a random cascade with a single parameter. The dependence of this parameter on forcing by the large-scale meteorological conditions, as measured by the large-scale spatial average rain rate, is investigated for these three datasets. The data show that this dependence can be captured by a one-to-one function. Since the large-scale average rain rate can be diagnosed from the large-scale dynamics, this relationship demonstrates an important linkage between the large-scale atmospheric dynamics and the statistical cascade theory of mesoscale rainfall. Potential application of this research to parameterization of runoff from the land surface and regional flood frequency analysis is briefly discussed, and open problems for further research are presented.

Critical thresholds in species` responses to landscape structure

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

With, K.A.; Crist, T.O.

1995-12-01

Critical thresholds are transition ranges across which small changes in spatial pattern produce abrupt shifts in ecological responses. Habitat fragmentation provides a familiar example of a critical threshold. As the landscape becomes dissected into smaller parcels of habitat. landscape connectivity-the functional linkage among habitat patches - may suddenly become disrupted, which may have important consequences for the distribution and persistence of populations. Landscape connectivity depends not only on the abundance and spatial patterning of habitat. but also on the habitat specificity and dispersal abilities of species. Habitat specialists with limited dispersal capabilities presumably have a much lower threshold to habitatmore » fragmentation than highly vagile species, which may perceive the landscape as functionally connected across a greater range of fragmentation severity. To determine where threshold effects in species, responses to landscape structure are likely to occur, a simulation model modified from percolation theory was developed. Our simulations predicted the distributional patterns of populations in different landscape mosaics, which we tested empirically using two grasshopper species (Orthoptera: Acrididae) that occur in the shortgrass prairie of north-central Colorado. The distribution of these two species in this grassland mosaic matched the predictions from our simulations. By providing quantitative predictions of threshold effects, this modelling approach may prove useful in the formulation of conservation strategies and assessment of land-use changes on species` distributional patterns and persistence.« less

Spatial variation in the bacterial and denitrifying bacterial community in a biofilter treating subsurface agricultural drainage.

PubMed

Andrus, J Malia; Porter, Matthew D; Rodríguez, Luis F; Kuehlhorn, Timothy; Cooke, Richard A C; Zhang, Yuanhui; Kent, Angela D; Zilles, Julie L

2014-02-01

Denitrifying biofilters can remove agricultural nitrates from subsurface drainage, reducing nitrate pollution that contributes to coastal hypoxic zones. The performance and reliability of natural and engineered systems dependent upon microbially mediated processes, such as the denitrifying biofilters, can be affected by the spatial structure of their microbial communities. Furthermore, our understanding of the relationship between microbial community composition and function is influenced by the spatial distribution of samples.In this study we characterized the spatial structure of bacterial communities in a denitrifying biofilter in central Illinois. Bacterial communities were assessed using automated ribosomal intergenic spacer analysis for bacteria and terminal restriction fragment length polymorphism of nosZ for denitrifying bacteria.Non-metric multidimensional scaling and analysis of similarity (ANOSIM) analyses indicated that bacteria showed statistically significant spatial structure by depth and transect,while denitrifying bacteria did not exhibit significant spatial structure. For determination of spatial patterns, we developed a package of automated functions for the R statistical environment that allows directional analysis of microbial community composition data using either ANOSIM or Mantel statistics.Applying this package to the biofilter data, the flow path correlation range for the bacterial community was 6.4 m at the shallower, periodically in undated depth and 10.7 m at the deeper, continually submerged depth. These spatial structures suggest a strong influence of hydrology on the microbial community composition in these denitrifying biofilters. Understanding such spatial structure can also guide optimal sample collection strategies for microbial community analyses.

Mapping the spatial and temporal progression of human dental enamel biomineralization using synchrotron X-ray diffraction.

PubMed

Simmons, Lisa M; Montgomery, Janet; Beaumont, Julia; Davis, Graham R; Al-Jawad, Maisoon

2013-11-01

The complex biological, physicochemical process of human dental enamel formation begins in utero and for most teeth takes several years to complete. Lost enamel tissue cannot regenerate, therefore a better understanding of the spatial and temporal progression of mineralization of this tissue is needed in order to design improved in vivo mineral growth processes for regenerative dentistry and allow the possibility to grow a synthetic whole or partial tooth. Human dental enamel samples across a range of developmental stages available through archaeological collections have been used to explore the spatial and temporal progression of enamel biomineralization. Position sensitive synchrotron X-ray diffraction was used to quantify spatial and temporal variations in crystallite organization, lattice parameters and crystallite thickness at three different stages in enamel maturation. In addition X-ray microtomography was used to study mineral content distributions. An inverse correlation was found between the spatial variation in mineral content and the distribution of crystallite organization and thickness as a function of time during enamel maturation. Combined X-ray microtomography and synchrotron X-ray diffraction results show that as enamel matures the mineral content increases and the mineral density distribution becomes more homogeneous. Starting concurrently but proceeding at a slower rate, the enamel crystallites become more oriented and larger; and the crystallite organization becomes spatially more complex and heterogeneous. During the mineralization of human dental enamel, the rate of mineral formation and mineral organization are not identical. Whilst the processes start simultaneously, full mineral content is achieved earlier, and crystallite organization is slower and continues for longer. These findings provide detailed insights into mineral development in human dental enamel which can inform synthetic biomimetic approaches for the benefit of clinical dentistry. Copyright © 2013 Elsevier Ltd. All rights reserved.

Controls on the spatial variability of key soil properties: comparing field data with a mechanistic soilscape evolution model

NASA Astrophysics Data System (ADS)

Vanwalleghem, T.; Román, A.; Giraldez, J. V.

2016-12-01

There is a need for better understanding the processes influencing soil formation and the resulting distribution of soil properties. Soil properties can exhibit strong spatial variation, even at the small catchment scale. Especially soil carbon pools in semi-arid, mountainous areas are highly uncertain because bulk density and stoniness are very heterogeneous and rarely measured explicitly. In this study, we explore the spatial variability in key soil properties (soil carbon stocks, stoniness, bulk density and soil depth) as a function of processes shaping the critical zone (weathering, erosion, soil water fluxes and vegetation patterns). We also compare the potential of a geostatistical versus a mechanistic soil formation model (MILESD) for predicting these key soil properties. Soil core samples were collected from 67 locations at 6 depths. Total soil organic carbon stocks were 4.38 kg m-2. Solar radiation proved to be the key variable controlling soil carbon distribution. Stone content was mostly controlled by slope, indicating the importance of erosion. Spatial distribution of bulk density was found to be highly random. Finally, total carbon stocks were predicted using a random forest model whose main covariates were solar radiation and NDVI. The model predicts carbon stocks that are double as high on north versus south-facing slopes. However, validation showed that these covariates only explained 25% of the variation in the dataset. Apparently, present-day landscape and vegetation properties are not sufficient to fully explain variability in the soil carbon stocks in this complex terrain under natural vegetation. This is attributed to a high spatial variability in bulk density and stoniness, key variables controlling carbon stocks. Similar results were obtained with the mechanistic soil formation model MILESD, suggesting that more complex models might be needed to further explore this high spatial variability.

The spatial study of unplanned settlements on the coastal of Belawan Medan fishermen village

NASA Astrophysics Data System (ADS)

Marpaung, B. O. Y.; Winny Silaban, Nadia

2018-03-01

One of the determining factors that formed informal settlements is the high demand for homes that are not comparable with the homes that were provided by the government. The settlement of Fisherman Village in Belawan Medan was built without a plan by settlers and was not involve government interference so that the spatial pattern formed uncontrollable. The shape of space that stretches represents the distribution of unplanned space. The purpose of this study is to find the structure of settlement and the relationship between the space structures with the spatial pattern in Belawan Medan Fishermen Village. In the process of collecting data, the researcher makes the maps of the observation area, the structure of the space, and the relationship between one space function with the other space functions. Also, the researchers identify the spacing pattern and the effect of one spatial element against the other. This study found a similar spatial pattern between one unplanned settlement and another unplanned settlement and there are also some tendencies of Belawan Medan Fishermen Village settlers when building the built environment in the relationship between building masses and the road network.

Apodization of two-dimensional pupils with aberrations

NASA Astrophysics Data System (ADS)

Reddy, Andra Naresh Kumar; Hashemi, Mahdieh; Khonina, Svetlana Nikolaevna

2018-06-01

The technique proposed to enhance the resolution of the point spread function (PSF) of an optical system underneath defocussing and spherical aberrations. The method of approach is based on the amplitude and phase masking in a ring aperture for modifying the light intensity distribution in the Gaussian focal plane (YD = 0) and in the defocussed planes (YD= π and YD= 2π ). The width of the annulus modifies the distribution of the light intensity in the side lobes of the resultant PSF. In the presence of an asymmetry in the phase of the annulus, the Hanning amplitude apodizer [cos(π β ρ )] employed in the pupil function can modify the spatial distribution of light in the maximum defocussed plane ({Y}D = 2π ), results in PSF with improved resolution.

Stochastic transformation of points in polygons according to the Voronoi tessellation: microstructural description.

PubMed

Di Vito, Alessia; Fanfoni, Massimo; Tomellini, Massimo

2010-12-01

Starting from a stochastic two-dimensional process we studied the transformation of points in disks and squares following a protocol according to which at any step the island size increases proportionally to the corresponding Voronoi tessera. Two interaction mechanisms among islands have been dealt with: coalescence and impingement. We studied the evolution of the island density and of the island size distribution functions, in dependence on island collision mechanisms for both Poissonian and correlated spatial distributions of points. The island size distribution functions have been found to be invariant with the fraction of transformed phase for a given stochastic process. The n(Θ) curve describing the island decay has been found to be independent of the shape (apart from high correlation degrees) and interaction mechanism.

Spatial distribution and optimal harvesting of an age-structured population in a fluctuating environment.

PubMed

Engen, Steinar; Lee, Aline Magdalena; Sæther, Bernt-Erik

2018-02-01

We analyze a spatial age-structured model with density regulation, age specific dispersal, stochasticity in vital rates and proportional harvesting. We include two age classes, juveniles and adults, where juveniles are subject to logistic density dependence. There are environmental stochastic effects with arbitrary spatial scales on all birth and death rates, and individuals of both age classes are subject to density independent dispersal with given rates and specified distributions of dispersal distances. We show how to simulate the joint density fields of the age classes and derive results for the spatial scales of all spatial autocovariance functions for densities. A general result is that the squared scale has an additive term equal to the squared scale of the environmental noise, corresponding to the Moran effect, as well as additive terms proportional to the dispersal rate and variance of dispersal distance for the age classes and approximately inversely proportional to the strength of density regulation. We show that the optimal harvesting strategy in the deterministic case is to harvest only juveniles when their relative value (e.g. financial) is large, and otherwise only adults. With increasing environmental stochasticity there is an interval of increasing length of values of juveniles relative to adults where both age classes should be harvested. Harvesting generally tends to increase all spatial scales of the autocovariances of densities. Copyright © 2017. Published by Elsevier Inc.

Development of Pseudorandom Binary Arrays for Calibration of Surface Profile Metrology Tools

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

Barber, S.K.; Takacs, P.; Soldate, P.

2009-12-01

Optical metrology tools, especially for short wavelengths (extreme ultraviolet and x-ray), must cover a wide range of spatial frequencies from the very low, which affects figure, to the important mid-spatial frequencies and the high spatial frequency range, which produces undesirable scattering. A major difficulty in using surface profilometers arises due to the unknown point-spread function (PSF) of the instruments [G. D. Boreman, Modulation Transfer Function in Optical and Electro-Optical Systems (SPIE, Bellingham, WA, 2001)] that is responsible for distortion of the measured surface profile. Generally, the distortion due to the PSF is difficult to account for because the PSF ismore » a complex function that comes to the measurement via the convolution operation, while the measured profile is described with a real function. Accounting for instrumental PSF becomes significantly simpler if the result of measurement of a profile is presented in the spatial frequency domain as a power spectral density (PSD) distribution [J. W. Goodman, Introduction to Fourier Optics, 3rd ed. (Roberts and Company, Englewood, CO, 2005)]. For example, measured PSD distributions provide a closed set of data necessary for three-dimensional calculations of scattering of light by the optical surfaces [E. L. Church et al., Opt. Eng. (Bellingham) 18, 125 (1979); J. C. Stover, Optical Scattering, 2nd ed. (SPIE Optical Engineering Press, Bellingham, WA, 1995)]. The distortion of the surface PSD distribution due to the PSF can be modeled with the modulation transfer function (MTF), which is defined over the spatial frequency bandwidth of the instrument. The measured PSD distribution can be presented as a product of the squared MTF and the ideal PSD distribution inherent for the system under test. Therefore, the instrumental MTF can be evaluated by comparing a measured PSD distribution of a known test surface with the corresponding ideal numerically simulated PSD. The square root of the ratio of the measured and simulated PSD distributions gives the MTF of the instrument. The applicability of the MTF concept to phase map measurements with optical interferometric microscopes needs to be experimentally verified as the optical tool and algorithms may introduce nonlinear artifacts into the process. In previous work [V. V. Yashchuk et al., Proc. SPIE 6704, 670408 (2007); Valeriy V. Yashchuk et al., Opt. Eng. (Bellingham) 47, 073602 (2008)] the instrumental MTF of a surface profiler was precisely measured using reference test surfaces based on binary pseudorandom (BPR) gratings. Here, the authors present results of fabricating and using two-dimensional (2D) BPR arrays that allow for a direct 2D calibration of the instrumental MTF. BPR sequences are widely used in engineering and communication applications such as global position systems and wireless communication protocols. The ideal BPR pattern has a flat 'white noise' response over the entire range of spatial frequencies of interest. The BPR array used here is based on the uniformly redundant array (URA) prescription [E. E. Fenimore and T. M. Cannon, Appl. Opt. 17, 337 (1978)] initially used for x-ray and gamma ray astronomy applications. The URA's superior imaging capability originates from the fact that its cyclical autocorrelation function very closely approximates a delta function, which produces a flat PSD. Three different size BPR array patterns were fabricated by electron beam lithography and induction coupled plasma etching of silicon. The basic size units were 200, 400, and 600 nm. Two different etch processes were used, CF{sub 4}/Ar and HBr, which resulted in undercut and vertical sidewall profiles, respectively. The 2D BPR arrays were used as standard test surfaces for MTF calibration of the MicroMap{trademark}-570 interferometric microscope using all available objectives. The MicroMap{trademark}-570 interferometric microscope uses incoherent illumination from a tungsten filament source and common path modulated phase shifting interference to produce a set of interferograms detected on a change coupled device. Mathematical algorithms applied to the datasets yield the surface phase map. The HBr etched two-dimensional BPR arrays have proven to be a very effective calibration standard making possible direct calibration corrections without the need of additional calculation considerations, while departures from the ideal vertical sidewall require an additional correction term for the CF{sub 4}/Ar etched samples [Samuel K. Barber et al., Abstract to Optics and Photonics 2009: Optical Engineering and Applications Symposium, San Diego, CA, 2-6 August 2009]. Initial surface roughness of low cost 'prime' wafers limits low magnification calibration but should not be a limitation if better polished samples are used.« less

Species, functional groups, and thresholds in ecological resilience

USGS Publications Warehouse

Sundstrom, Shana M.; Allen, Craig R.; Barichievy, Chris

2012-01-01

The cross-scale resilience model states that ecological resilience is generated in part from the distribution of functions within and across scales in a system. Resilience is a measure of a system's ability to remain organized around a particular set of mutually reinforcing processes and structures, known as a regime. We define scale as the geographic extent over which a process operates and the frequency with which a process occurs. Species can be categorized into functional groups that are a link between ecosystem processes and structures and ecological resilience. We applied the cross-scale resilience model to avian species in a grassland ecosystem. A species’ morphology is shaped in part by its interaction with ecological structure and pattern, so animal body mass reflects the spatial and temporal distribution of resources. We used the log-transformed rank-ordered body masses of breeding birds associated with grasslands to identify aggregations and discontinuities in the distribution of those body masses. We assessed cross-scale resilience on the basis of 3 metrics: overall number of functional groups, number of functional groups within an aggregation, and the redundancy of functional groups across aggregations. We assessed how the loss of threatened species would affect cross-scale resilience by removing threatened species from the data set and recalculating values of the 3 metrics. We also determined whether more function was retained than expected after the loss of threatened species by comparing observed loss with simulated random loss in a Monte Carlo process. The observed distribution of function compared with the random simulated loss of function indicated that more functionality in the observed data set was retained than expected. On the basis of our results, we believe an ecosystem with a full complement of species can sustain considerable species losses without affecting the distribution of functions within and across aggregations, although ecological resilience is reduced. We propose that the mechanisms responsible for shaping discontinuous distributions of body mass and the nonrandom distribution of functions may also shape species losses such that local extinctions will be nonrandom with respect to the retention and distribution of functions and that the distribution of function within and across aggregations will be conserved despite extinctions.

Terrestrial gross carbon dioxide uptake: global distribution and covariation with climate.

PubMed

Beer, Christian; Reichstein, Markus; Tomelleri, Enrico; Ciais, Philippe; Jung, Martin; Carvalhais, Nuno; Rödenbeck, Christian; Arain, M Altaf; Baldocchi, Dennis; Bonan, Gordon B; Bondeau, Alberte; Cescatti, Alessandro; Lasslop, Gitta; Lindroth, Anders; Lomas, Mark; Luyssaert, Sebastiaan; Margolis, Hank; Oleson, Keith W; Roupsard, Olivier; Veenendaal, Elmar; Viovy, Nicolas; Williams, Christopher; Woodward, F Ian; Papale, Dario

2010-08-13

Terrestrial gross primary production (GPP) is the largest global CO(2) flux driving several ecosystem functions. We provide an observation-based estimate of this flux at 123 +/- 8 petagrams of carbon per year (Pg C year(-1)) using eddy covariance flux data and various diagnostic models. Tropical forests and savannahs account for 60%. GPP over 40% of the vegetated land is associated with precipitation. State-of-the-art process-oriented biosphere models used for climate predictions exhibit a large between-model variation of GPP's latitudinal patterns and show higher spatial correlations between GPP and precipitation, suggesting the existence of missing processes or feedback mechanisms which attenuate the vegetation response to climate. Our estimates of spatially distributed GPP and its covariation with climate can help improve coupled climate-carbon cycle process models.

Distributed temperature and strain discrimination with stimulated brillouin scattering and rayleigh backscatter in an optical fiber.

PubMed

Zhou, Da-Peng; Li, Wenhai; Chen, Liang; Bao, Xiaoyi

2013-01-31

A distributed optical fiber sensor with the capability of simultaneously measuring temperature and strain is proposed using a large effective area non-zero dispersion shifted fiber (LEAF) with sub-meter spatial resolution. The Brillouin frequency shift is measured using Brillouin optical time-domain analysis (BOTDA) with differential pulse-width pair technique, while the spectrum shift of the Rayleigh backscatter is measured using optical frequency-domain reflectometry (OFDR). These shifts are the functions of both temperature and strain, and can be used as two independent parameters for the discrimination of temperature and strain. A 92 m measurable range with the spatial resolution of 50 cm is demonstrated experimentally, and accuracies of ±1.2 °C in temperature and ±15 με in strain could be achieved.

Spatial analysis of cities using Renyi entropy and fractal parameters

NASA Astrophysics Data System (ADS)

Chen, Yanguang; Feng, Jian

2017-12-01

The spatial distributions of cities fall into two groups: one is the simple distribution with characteristic scale (e.g. exponential distribution), and the other is the complex distribution without characteristic scale (e.g. power-law distribution). The latter belongs to scale-free distributions, which can be modeled with fractal geometry. However, fractal dimension is not suitable for the former distribution. In contrast, spatial entropy can be used to measure any types of urban distributions. This paper is devoted to generalizing multifractal parameters by means of dual relation between Euclidean and fractal geometries. The main method is mathematical derivation and empirical analysis, and the theoretical foundation is the discovery that the normalized fractal dimension is equal to the normalized entropy. Based on this finding, a set of useful spatial indexes termed dummy multifractal parameters are defined for geographical analysis. These indexes can be employed to describe both the simple distributions and complex distributions. The dummy multifractal indexes are applied to the population density distribution of Hangzhou city, China. The calculation results reveal the feature of spatio-temporal evolution of Hangzhou's urban morphology. This study indicates that fractal dimension and spatial entropy can be combined to produce a new methodology for spatial analysis of city development.

Comparison of 3D ion velocity distribution measurements and models in the vicinity of an absorbing boundary oriented obliquely to a magnetic field

NASA Astrophysics Data System (ADS)

Henriquez, Miguel F.; Thompson, Derek S.; Kenily, Shane; Khaziev, Rinat; Good, Timothy N.; McIlvain, Julianne; Siddiqui, M. Umair; Curreli, Davide; Scime, Earl E.

2016-10-01

Understanding particle distributions in plasma boundary regions is critical to predicting plasma-surface interactions. Ions in the presheath exhibit complex behavior because of collisions and due to the presence of boundary-localized electric fields. Complete understanding of particle dynamics is necessary for understanding the critical problems of tokamak wall loading and Hall thruster channel wall erosion. We report measurements of 3D argon ion velocity distribution functions (IVDFs) in the vicinity of an absorbing boundary oriented obliquely to a background magnetic field. Measurements were obtained via argon ion laser induced fluorescence throughout a spatial volume upstream of the boundary. These distribution functions reveal kinetic details that provide a point-to-point check on particle-in-cell and 1D3V Boltzmann simulations. We present the results of this comparison and discuss some implications for plasma boundary interaction physics.

What are the Shapes of Response Time Distributions in Visual Search?

PubMed Central

Palmer, Evan M.; Horowitz, Todd S.; Torralba, Antonio; Wolfe, Jeremy M.

2011-01-01

Many visual search experiments measure reaction time (RT) as their primary dependent variable. Analyses typically focus on mean (or median) RT. However, given enough data, the RT distribution can be a rich source of information. For this paper, we collected about 500 trials per cell per observer for both target-present and target-absent displays in each of three classic search tasks: feature search, with the target defined by color; conjunction search, with the target defined by both color and orientation; and spatial configuration search for a 2 among distractor 5s. This large data set allows us to characterize the RT distributions in detail. We present the raw RT distributions and fit several psychologically motivated functions (ex-Gaussian, ex-Wald, Gamma, and Weibull) to the data. We analyze and interpret parameter trends from these four functions within the context of theories of visual search. PMID:21090905

Modelling Spatial Dependence Structures Between Climate Variables by Combining Mixture Models with Copula Models

NASA Astrophysics Data System (ADS)

Khan, F.; Pilz, J.; Spöck, G.

2017-12-01

Spatio-temporal dependence structures play a pivotal role in understanding the meteorological characteristics of a basin or sub-basin. This further affects the hydrological conditions and consequently will provide misleading results if these structures are not taken into account properly. In this study we modeled the spatial dependence structure between climate variables including maximum, minimum temperature and precipitation in the Monsoon dominated region of Pakistan. For temperature, six, and for precipitation four meteorological stations have been considered. For modelling the dependence structure between temperature and precipitation at multiple sites, we utilized C-Vine, D-Vine and Student t-copula models. For temperature, multivariate mixture normal distributions and for precipitation gamma distributions have been used as marginals under the copula models. A comparison was made between C-Vine, D-Vine and Student t-copula by observational and simulated spatial dependence structure to choose an appropriate model for the climate data. The results show that all copula models performed well, however, there are subtle differences in their performances. The copula models captured the patterns of spatial dependence structures between climate variables at multiple meteorological sites, however, the t-copula showed poor performance in reproducing the dependence structure with respect to magnitude. It was observed that important statistics of observed data have been closely approximated except of maximum values for temperature and minimum values for minimum temperature. Probability density functions of simulated data closely follow the probability density functions of observational data for all variables. C and D-Vines are better tools when it comes to modelling the dependence between variables, however, Student t-copulas compete closely for precipitation. Keywords: Copula model, C-Vine, D-Vine, Spatial dependence structure, Monsoon dominated region of Pakistan, Mixture models, EM algorithm.

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.

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

Modeling the isotopic evolution of snowpack and snowmelt: Testing a spatially distributed parsimonious approach.

PubMed

Ala-Aho, Pertti; Tetzlaff, Doerthe; McNamara, James P; Laudon, Hjalmar; Kormos, Patrick; Soulsby, Chris

2017-07-01

Use of stable water isotopes has become increasingly popular in quantifying water flow paths and travel times in hydrological systems using tracer-aided modeling. In snow-influenced catchments, snowmelt produces a traceable isotopic signal, which differs from original snowfall isotopic composition because of isotopic fractionation in the snowpack. These fractionation processes in snow are relatively well understood, but representing their spatiotemporal variability in tracer-aided studies remains a challenge. We present a novel, parsimonious modeling method to account for the snowpack isotope fractionation and estimate isotope ratios in snowmelt water in a fully spatially distributed manner. Our model introduces two calibration parameters that alone account for the isotopic fractionation caused by sublimation from interception and ground snow storage, and snowmelt fractionation progressively enriching the snowmelt runoff. The isotope routines are linked to a generic process-based snow interception-accumulation-melt model facilitating simulation of spatially distributed snowmelt runoff. We use a synthetic modeling experiment to demonstrate the functionality of the model algorithms in different landscape locations and under different canopy characteristics. We also provide a proof-of-concept model test and successfully reproduce isotopic ratios in snowmelt runoff sampled with snowmelt lysimeters in two long-term experimental catchment with contrasting winter conditions. To our knowledge, the method is the first such tool to allow estimation of the spatially distributed nature of isotopic fractionation in snowpacks and the resulting isotope ratios in snowmelt runoff. The method can thus provide a useful tool for tracer-aided modeling to better understand the integrated nature of flow, mixing, and transport processes in snow-influenced catchments.

Do morphometric parameters and geological conditions determine chemistry of glacier surface ice? Spatial distribution of contaminants present in the surface ice of Spitsbergen glaciers (European Arctic).

PubMed

Lehmann, Sara; Gajek, Grzegorz; Chmiel, Stanisław; Polkowska, Żaneta

2016-12-01

The chemism of the glaciers is strongly determined by long-distance transport of chemical substances and their wet and dry deposition on the glacier surface. This paper concerns spatial distribution of metals, ions, and dissolved organic carbon, as well as the differentiation of physicochemical parameters (pH, electrical conductivity) determined in ice surface samples collected from four Arctic glaciers during the summer season in 2012. The studied glaciers represent three different morphological types: ground based (Blomlibreen and Scottbreen), tidewater which evolved to ground based (Renardbreen), and typical tidewater glacier (Recherchebreen). All of the glaciers are functioning as a glacial system and hence are subject to the same physical processes (melting, freezing) and the process of ice flowing resulting from the cross-impact force of gravity and topographic conditions. According to this hypothesis, the article discusses the correlation between morphometric parameters, changes in mass balance, geological characteristics of the glaciers and the spatial distribution of analytes on the surface of ice. A strong correlation (r = 0.63) is recorded between the aspect of glaciers and values of pH and ions, whereas dissolved organic carbon (DOC) depends on the minimum elevation of glaciers (r = 0.55) and most probably also on the development of the accumulation area. The obtained results suggest that although certain morphometric parameters largely determine the spatial distribution of analytes, also the geology of the bed of glaciers strongly affects the chemism of the surface ice of glaciers in the phase of strong recession.

Design and implementation of a distributed large-scale spatial database system based on J2EE

NASA Astrophysics Data System (ADS)

Gong, Jianya; Chen, Nengcheng; Zhu, Xinyan; Zhang, Xia

2003-03-01

With the increasing maturity of distributed object technology, CORBA, .NET and EJB are universally used in traditional IT field. However, theories and practices of distributed spatial database need farther improvement in virtue of contradictions between large scale spatial data and limited network bandwidth or between transitory session and long transaction processing. Differences and trends among of CORBA, .NET and EJB are discussed in details, afterwards the concept, architecture and characteristic of distributed large-scale seamless spatial database system based on J2EE is provided, which contains GIS client application, web server, GIS application server and spatial data server. Moreover the design and implementation of components of GIS client application based on JavaBeans, the GIS engine based on servlet, the GIS Application server based on GIS enterprise JavaBeans(contains session bean and entity bean) are explained.Besides, the experiments of relation of spatial data and response time under different conditions are conducted, which proves that distributed spatial database system based on J2EE can be used to manage, distribute and share large scale spatial data on Internet. Lastly, a distributed large-scale seamless image database based on Internet is presented.

Conversion of woodlands changes soil related ecosystem services in Subsaharan Africa

NASA Astrophysics Data System (ADS)

Groengroeft, Alexander; Landschreiber, Lars; Luther-Mosebach, Jona; Masamba, Wellington; Zimmermann, Ibo; Eschenbach, Annette

2015-04-01

In remote areas of Subsaharan Africa, growing population, changes in consumption patterns and increasing global influences are leading to a strong pressure on the land resources. Smallholders convert woodlands by fire, grazing and clearing in different intensities thus changing soil properties and their ecosystem functioning. As the extraction of ecosystem services forms the basis of local wellbeing for many communities, the role of soils in providing ecosystem services is of high importance. Since 2010, "The Future Okavango" project investigates the quantification of ecosystem functions and services at four core research sites along the Okavango river basin (Angola, Namibia, Botswana, see http://www.future-okavango.org/). These research sites have an extent of 100 km2 each. Within our subproject the soil functions underlying ecosystem services are studied: The amount and spatial variation of soil nutrient reserves in woodland and their changes by land use activities, the water storage function as a basis for plant growth, and their effect on groundwater recharge and the carbon storage function. The scientific framework consists of four major parts including soil survey and mapping, lab analysis, field measurements and modeling approaches on different scales. A detailed soil survey leads to a measure of the spatial distribution, extent and heterogeneity of soil types for each research site. For generalization purposes, geomorphological and pedological characteristics are merged to derive landscape units. These landscape units have been overlaid by recent land use types to stratify the research site for subsequent soil sampling. On the basis of field and laboratory analysis, spatial distribution of soil properties as well as boundaries between neighboring landscape units are derived. The parameters analysed describe properties according to grain size distribution, organic carbon content, saturated and unsaturated hydraulic conductivity as well as pore space distribution. At nine selected sites, soil water contents and pressure heads are logged throughout the year with a 12 hour resolution in depth of 10 to 160 cm. This monitoring gives information about soil water dynamics at point scale and the database is used to evaluate model outputs of soil water balances later on. To derive point scale soil water balances for each landscape unit the one dimensional and physically based model SWAP 3.2 is applied. The presentation will demonstrate the conceptual framework, exemplary results and will discuss, if the ecosystem service approach can help to avoid future land degradation. Key word: Okavango catchment, soil functions, conceptual approach

Decoupling function and anatomy in atlases of functional connectivity patterns: language mapping in tumor patients.

PubMed

Langs, Georg; Sweet, Andrew; Lashkari, Danial; Tie, Yanmei; Rigolo, Laura; Golby, Alexandra J; Golland, Polina

2014-12-01

In this paper we construct an atlas that summarizes functional connectivity characteristics of a cognitive process from a population of individuals. The atlas encodes functional connectivity structure in a low-dimensional embedding space that is derived from a diffusion process on a graph that represents correlations of fMRI time courses. The functional atlas is decoupled from the anatomical space, and thus can represent functional networks with variable spatial distribution in a population. In practice the atlas is represented by a common prior distribution for the embedded fMRI signals of all subjects. We derive an algorithm for fitting this generative model to the observed data in a population. Our results in a language fMRI study demonstrate that the method identifies coherent and functionally equivalent regions across subjects. The method also successfully maps functional networks from a healthy population used as a training set to individuals whose language networks are affected by tumors. Copyright © 2014. Published by Elsevier Inc.

Regional risk assessment for contaminated sites part 2: ranking of potentially contaminated sites.

PubMed

Pizzol, Lisa; Critto, Andrea; Agostini, Paola; Marcomini, Antonio

2011-11-01

Environmental risks are traditionally assessed and presented in non spatial ways although the heterogeneity of the contaminants spatial distributions, the spatial positions and relations between receptors and stressors, as well as the spatial distribution of the variables involved in the risk assessment, strongly influence exposure estimations and hence risks. Taking into account spatial variability is increasingly being recognized as a further and essential step in sound exposure and risk assessment. To address this issue an innovative methodology which integrates spatial analysis and a relative risk approach was developed. The purpose of this methodology is to prioritize sites at regional scale where a preliminary site investigation may be required. The methodology aimed at supporting the inventory of contaminated sites was implemented within the spatial decision support sYstem for Regional rIsk Assessment of DEgraded land, SYRIADE, and was applied to the case-study of the Upper Silesia region (Poland). The developed methodology and tool are both flexible and easy to adapt to different regional contexts, allowing the user to introduce the regional relevant parameters identified on the basis of user expertise and regional data availability. Moreover, the used GIS functionalities, integrated with mathematical approaches, allow to take into consideration, all at once, the multiplicity of sources and impacted receptors within the region of concern, to assess the risks posed by all contaminated sites in the region and, finally, to provide a risk-based ranking of the potentially contaminated sites. Copyright © 2011. Published by Elsevier Ltd.

Incorporating Human Movement Behavior into the Analysis of Spatially Distributed Infrastructure.

PubMed

Wu, Lihua; Leung, Henry; Jiang, Hao; Zheng, Hong; Ma, Li

2016-01-01

For the first time in human history, the majority of the world's population resides in urban areas. Therefore, city managers are faced with new challenges related to the efficiency, equity and quality of the supply of resources, such as water, food and energy. Infrastructure in a city can be viewed as service points providing resources. These service points function together as a spatially collaborative system to serve an increasing population. To study the spatial collaboration among service points, we propose a shared network according to human's collective movement and resource usage based on data usage detail records (UDRs) from the cellular network in a city in western China. This network is shown to be not scale-free, but exhibits an interesting triangular property governed by two types of nodes with very different link patterns. Surprisingly, this feature is consistent with the urban-rural dualistic context of the city. Another feature of the shared network is that it consists of several spatially separated communities that characterize local people's active zones but do not completely overlap with administrative areas. According to these features, we propose the incorporation of human movement into infrastructure classification. The presence of well-defined spatially separated clusters confirms the effectiveness of this approach. In this paper, our findings reveal the spatial structure inside a city, and the proposed approach provides a new perspective on integrating human movement into the study of a spatially distributed system.

Spatial data analysis for exploration of regional scale geothermal resources

NASA Astrophysics Data System (ADS)

Moghaddam, Majid Kiavarz; Noorollahi, Younes; Samadzadegan, Farhad; Sharifi, Mohammad Ali; Itoi, Ryuichi

2013-10-01

Defining a comprehensive conceptual model of the resources sought is one of the most important steps in geothermal potential mapping. In this study, Fry analysis as a spatial distribution method and 5% well existence, distance distribution, weights of evidence (WofE), and evidential belief function (EBFs) methods as spatial association methods were applied comparatively to known geothermal occurrences, and to publicly-available regional-scale geoscience data in Akita and Iwate provinces within the Tohoku volcanic arc, in northern Japan. Fry analysis and rose diagrams revealed similar directional patterns of geothermal wells and volcanoes, NNW-, NNE-, NE-trending faults, hotsprings and fumaroles. Among the spatial association methods, WofE defined a conceptual model correspondent with the real world situations, approved with the aid of expert opinion. The results of the spatial association analyses quantitatively indicated that the known geothermal occurrences are strongly spatially-associated with geological features such as volcanoes, craters, NNW-, NNE-, NE-direction faults and geochemical features such as hotsprings, hydrothermal alteration zones and fumaroles. Geophysical data contains temperature gradients over 100 °C/km and heat flow over 100 mW/m2. In general, geochemical and geophysical data were better evidence layers than geological data for exploring geothermal resources. The spatial analyses of the case study area suggested that quantitative knowledge from hydrothermal geothermal resources was significantly useful for further exploration and for geothermal potential mapping in the case study region. The results can also be extended to the regions with nearly similar characteristics.

Versatile application of indirect Fourier transformation to structure factor analysis: from X-ray diffraction of molecular liquids to small angle scattering of protein solutions.

PubMed

Fukasawa, Toshiko; Sato, Takaaki

2011-02-28

We highlight versatile applicability of a structure-factor indirect Fourier transformation (IFT) technique, hereafter called SQ-IFT. The original IFT aims at the pair distance distribution function, p(r), of colloidal particles from small angle scattering of X-rays (SAXS) and neutrons (SANS), allowing the conversion of the experimental form factor, P(q), into a more intuitive real-space spatial autocorrelation function. Instead, SQ-IFT is an interaction potential model-free approach to the 'effective' or 'experimental' structure factor to yield the pair correlation functions (PCFs), g(r), of colloidal dispersions like globular protein solutions for small-angle scattering data as well as the radial distribution functions (RDFs) of molecular liquids in liquid diffraction (LD) experiments. We show that SQ-IFT yields accurate RDFs of liquid H(2)O and monohydric alcohol reflecting their local intermolecular structures, in which q-weighted structure function, qH(q), conventionally utilized in many LD studies out of necessity of performing direct Fourier transformation, is no longer required. We also show that SQ-IFT applied to theoretically calculated structure factors for uncharged and charged colloidal dispersions almost perfectly reproduces g(r) obtained as a solution of the Ornstein-Zernike (OZ) equation. We further demonstrate the relevance of SQ-IFT in its practical applications, using SANS effective structure factors of lysozyme solutions reported in recent literatures which revealed the equilibrium cluster formation due to coexisting long range electrostatic repulsion and short range attraction between the proteins. Finally, we present SAXS experiments on human serum albumin (HSA) at different ionic strength and protein concentration, in which we discuss the real space picture of spatial distributions of the proteins via the interaction potential model-free route.

Patterns in spatial distribution and root trait syndromes for ecto and arbuscular mycorrhizal temperate trees in a mixed broadleaf forest.

PubMed

Valverde-Barrantes, Oscar J; Smemo, Kurt A; Feinstein, Larry M; Kershner, Mark W; Blackwood, Christopher B

2018-03-01

Functional differences between trees with arbuscular (AM) or ectomycorrhizal (ECM) partnerships influence important ecological processes including nutrient cycling, community assembly, and biomass allocation patterns. Although most broadleaf temperate forests show both mycorrhizal types, relatively few studies have addressed functional difference among coexisting mycorrhizal tree species. The maintenance of ECM associations usually requires higher C investment than AM, leading to (A) lower root biomass and (B) more conservative root trait syndromes in ECM tree species compared to AM species. Here we quantified the representation and trait syndromes of 14 canopy tree species associated with either AM or ECM fungi in a natural forest community. Our results showed that, whereas species root abundance was proportional to basal area, some ECM tree roots were largely under-represented (up to ~ 33%). Most of the under-representation was due to lower than expected root abundance of Quercus rubra and Fagus grandifolia. Functional root traits in tree species were similar, with the exception of higher tissue density in ECM species. Moreover, closely related AM and ECM exhibited similar traits, suggesting inherited trait syndrome from a common ancestor. Thus, we found little evidence of divergent functional root trait syndromes between mycorrhizal types. Cores dominated by ECM species influenced trait distribution at the community level, but not total biomass, suggesting that mycorrhizal affiliation may have a stronger effect on the spatial distribution of traits but not on biomass stocks. Our results present an important step toward relating belowground carbon dynamics to species traits, including mycorrhizal type, in broadleaf temperate forests.

The development of the rhizosphere: simulation of root exudation for two contrasting exudates: citrate and mucilage

NASA Astrophysics Data System (ADS)

Sheng, Cheng; Bol, Roland; Vetterlein, Doris; Vanderborght, Jan; Schnepf, Andrea

2017-04-01

Different types of root exudates and their effect on soil/rhizosphere properties have received a lot of attention. Since their influence of rhizosphere properties and processes depends on their concentration in the soil, the assessment of the spatial-temporal exudate concentration distribution around roots is of key importance for understanding the functioning of the rhizosphere. Different root systems have different root architectures. Different types of root exudates diffuse in the rhizosphere with different diffusion coefficient. Both of them are responsible for the dynamics of exudate concentration distribution in the rhizosphere. Hence, simulations of root exudation involving four kinds of plant root systems (Vicia faba, Lupinus albus, Triticum aestivum and Zea mays) and two kinds of root exudates (citrate and mucilage) were conducted. We consider a simplified root architecture where each root is represented by a straight line. Assuming that root tips move at a constant velocity and that mucilage transport is linear, concentration distributions can be obtained from a convolution of the analytical solution of the transport equation in a stationary flow field for an instantaneous point source injection with the spatial-temporal distribution of the source strength. By coupling the analytical equation with a root growth model that delivers the spatial-temporal source term, we simulated exudate concentration distributions for citrate and mucilage with MATLAB. From the simulation results, we inferred the following information about the rhizosphere: (a) the dynamics of the root architecture development is the main effect of exudate distribution in the root zone; (b) a steady rhizosphere with constant width is more likely to develop for individual roots when the diffusion coefficient is small. The simulations suggest that rhizosphere development depends in the following way on the root and exudate properties: the dynamics of the root architecture result in various development patterns of the rhizosphere. Meanwhile, Results improve our understanding of the impact of the spatial and temporal heterogeneity of exudate input on rhizosphere development for different root system types and substances. In future work, we will use the simulation tool to infer critical parameters that determine the spatial-temporal extent of the rhizosphere from experimental data.

Spatial Copula Model for Imputing Traffic Flow Data from Remote Microwave Sensors

PubMed Central

Ma, Xiaolei; Du, Bowen; Yu, Bin

2017-01-01

Issues of missing data have become increasingly serious with the rapid increase in usage of traffic sensors. Analyses of the Beijing ring expressway have showed that up to 50% of microwave sensors pose missing values. The imputation of missing traffic data must be urgently solved although a precise solution that cannot be easily achieved due to the significant number of missing portions. In this study, copula-based models are proposed for the spatial interpolation of traffic flow from remote traffic microwave sensors. Most existing interpolation methods only rely on covariance functions to depict spatial correlation and are unsuitable for coping with anomalies due to Gaussian consumption. Copula theory overcomes this issue and provides a connection between the correlation function and the marginal distribution function of traffic flow. To validate copula-based models, a comparison with three kriging methods is conducted. Results indicate that copula-based models outperform kriging methods, especially on roads with irregular traffic patterns. Copula-based models demonstrate significant potential to impute missing data in large-scale transportation networks. PMID:28934164

Distributions of ectomycorrhizal and foliar endophytic fungal communities associated with Pinus ponderosa along a spatially constrained elevation gradient.

PubMed

Bowman, Elizabeth A; Arnold, A Elizabeth

2018-04-01

Understanding distributions of plant-symbiotic fungi is important for projecting responses to environmental change. Many coniferous trees host ectomycorrhizal fungi (EM) in association with roots and foliar endophytic fungi (FE) in leaves. We examined how EM and FE associated with Pinus ponderosa each vary in abundance, diversity, and community structure over a spatially constrained elevation gradient that traverses four plant communities, 4°C in mean annual temperature, and 15 cm in mean annual precipitation. We sampled 63 individuals of Pinus ponderosa in 10 sites along a 635 m elevation gradient that encompassed a geographic distance of 9.8 km. We used standard methods to characterize each fungal group (amplified and sequenced EM from root tips; isolated and sequenced FE from leaves). Abundance and diversity of EM were similar across sites, but community composition and distributions of the most common EM differed with elevation (i.e., with climate, soil chemistry, and plant communities). Abundance and composition of FE did not differ with elevation, but diversity peaked in mid-to-high elevations. Our results suggest relatively tight linkages between EM and climate, soil chemistry, and plant communities. That FE appear less linked with these factors may speak to limitations of a culture-based approach, but more likely reflects the small spatial scale encompassed by our study. Future work should consider comparable methods for characterizing these functional groups, and additional transects to understand relationships of EM and FE to environmental factors that are likely to shift as a function of climate change. © 2018 Botanical Society of America.

Wave propagation model of heat conduction and group speed

NASA Astrophysics Data System (ADS)

Zhang, Long; Zhang, Xiaomin; Peng, Song

2018-03-01

In view of the finite relaxation model of non-Fourier's law, the Cattaneo and Vernotte (CV) model and Fourier's law are presented in this work for comparing wave propagation modes. Independent variable translation is applied to solve the partial differential equation. Results show that the general form of the time spatial distribution of temperature for the three media comprises two solutions: those corresponding to the positive and negative logarithmic heating rates. The former shows that a group of heat waves whose spatial distribution follows the exponential function law propagates at a group speed; the speed of propagation is related to the logarithmic heating rate. The total speed of all the possible heat waves can be combined to form the group speed of the wave propagation. The latter indicates that the spatial distribution of temperature, which follows the exponential function law, decays with time. These features show that propagation accelerates when heated and decelerates when cooled. For the model media that follow Fourier's law and correspond to the positive heat rate of heat conduction, the propagation mode is also considered the propagation of a group of heat waves because the group speed has no upper bound. For the finite relaxation model with non-Fourier media, the interval of group speed is bounded and the maximum speed can be obtained when the logarithmic heating rate is exactly the reciprocal of relaxation time. And for the CV model with a non-Fourier medium, the interval of group speed is also bounded and the maximum value can be obtained when the logarithmic heating rate is infinite.

The Role of Diffusion in the Transport of Energetic Electrons during Solar Flares

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

Bian, Nicolas H.; Kontar, Eduard P.; Emslie, A. Gordon, E-mail: nicolas.bian@glasgow.gla.ac.uk, E-mail: emslieg@wku.edu

2017-02-01

The transport of the energy contained in suprathermal electrons in solar flares plays a key role in our understanding of many aspects of flare physics, from the spatial distributions of hard X-ray emission and energy deposition in the ambient atmosphere to global energetics. Historically the transport of these particles has been largely treated through a deterministic approach, in which first-order secular energy loss to electrons in the ambient target is treated as the dominant effect, with second-order diffusive terms (in both energy and angle) generally being either treated as a small correction or even neglected. Here, we critically analyze thismore » approach, and we show that spatial diffusion through pitch-angle scattering necessarily plays a very significant role in the transport of electrons. We further show that a satisfactory treatment of the diffusion process requires consideration of non-local effects, so that the electron flux depends not just on the local gradient of the electron distribution function but on the value of this gradient within an extended region encompassing a significant fraction of a mean free path. Our analysis applies generally to pitch-angle scattering by a variety of mechanisms, from Coulomb collisions to turbulent scattering. We further show that the spatial transport of electrons along the magnetic field of a flaring loop can be modeled rather effectively as a Continuous Time Random Walk with velocity-dependent probability distribution functions of jump sizes and occurrences, both of which can be expressed in terms of the scattering mean free path.« less

Features of influence of spatially inhomogeneous geomagnetic field on a humans heart rhythm variability

NASA Astrophysics Data System (ADS)

Tuzhilkin, D. A.; Borodin, A. S.; Shitov, A. V.

2017-11-01

The results of a study of the functioning of the human cardiovascular system in the epicentral zone of the Chui earthquake on a tectonic fault characterized by a sharp gradient zone of a regional magnetic field are presented. It is shown that in the dynamics of the daily distribution of RR-intervals, events corresponding to the time of visit by volunteers of sites characterized by the presence of a spatially inhomogeneous geomagnetic field are singled out. In particular, there is a decrease in the average period of cardiac contractions.

Thermally induced optical deformation of a Nd:YVO4 active disk under the action of multi-beam spatially periodic diode pumping

NASA Astrophysics Data System (ADS)

Guryev, D. A.; Nikolaev, D. A.; Tsvetkov, V. B.; Shcherbakov, I. A.

2018-05-01

A study of how the transverse distribution of an optical path changes in a Nd:YVO4 active disk was carried out in a ten-beam spatially periodic diode pumping in the one-dimensional case. The pumping beams’ transverse dimensions were comparable with the distances between them. The investigations were carried out using laser interferometry methods. It was found that the optical thickness changing in the active disk along the line of pumping spots was well described by a Gaussian function.

Statistical characterization of spatial patterns of rainfall cells in extratropical cyclones

NASA Astrophysics Data System (ADS)

Bacchi, Baldassare; Ranzi, Roberto; Borga, Marco

1996-11-01

The assumption of a particular type of distribution of rainfall cells in space is needed for the formulation of several space-time rainfall models. In this study, weather radar-derived rain rate maps are employed to evaluate different types of spatial organization of rainfall cells in storms through the use of distance functions and second-moment measures. In particular the spatial point patterns of the local maxima of rainfall intensity are compared to a completely spatially random (CSR) point process by applying an objective distance measure. For all the analyzed radar maps the CSR assumption is rejected, indicating that at the resolution of the observation considered, rainfall cells are clustered. Therefore a theoretical framework for evaluating and fitting alternative models to the CSR is needed. This paper shows how the "reduced second-moment measure" of the point pattern can be employed to estimate the parameters of a Neyman-Scott model and to evaluate the degree of adequacy to the experimental data. Some limitations of this theoretical framework, and also its effectiveness, in comparison to the use of scaling functions, are discussed.

Optimizing the Hydrological and Biogeochemical Simulations on a Hillslope with Stony Soil

NASA Astrophysics Data System (ADS)

Zhu, Q.

2017-12-01

Stony soils are widely distributed in the hilly area. However, traditional pedotransfer functions are not reliable in predicting the soil hydraulic parameters for these soils due to the impacts of rock fragments. Therefore, large uncertainties and errors may exist in the hillslope hydrological and biogeochemical simulations in stony soils due to poor estimations of soil hydraulic parameters. In addition, homogenous soil hydraulic parameters are usually used in traditional hillslope simulations. However, soil hydraulic parameters are spatially heterogeneous on the hillslope. This may also cause the unreliable simulations. In this study, we obtained soil hydraulic parameters using five different approaches on a tea hillslope in Taihu Lake basin, China. These five approaches included (1) Rossetta predicted and spatially homogenous, (2) Rossetta predicted and spatially heterogeneous), (3) Rossetta predicted, rock fragment corrected and spatially homogenous, (4) Rossetta predicted, rock fragment corrected and spatially heterogeneous, and (5) extracted from observed soil-water retention curves fitted by dual-pore function and spatially heterogeneous (observed). These five sets of soil hydraulic properties were then input into Hydrus-3D and DNDC to simulate the soil hydrological and biogeochemical processes. The aim of this study is testing two hypotheses. First, considering the spatial heterogeneity of soil hydraulic parameters will improve the simulations. Second, considering the impact of rock fragment on soil hydraulic parameters will improve the simulations.

[Brain mapping in verbal and spatial thinking].

PubMed

Ivanitskiĭ, A M; Portnova, G V; Martynova, O V; Maĭorova, L A; Fedina, O N; Petrushevskiĭ, A G

2013-01-01

The goal of this study was to describe the topography of the active cortical areas and subcortical structuresin verbal and spatial thinking. The method of functional magnetic resonance imaging (fMRI) was used. 18 right-handed subjects participated in the study. Four types of tasks were presented: two experimental tasks--verbal (anagram) and spatial (search for a piece to complement a square), and two types of control tasks (written words and a spatial task, where all the pieces are identical). In solving verbal tasks the greater volume of activation was observed in the left hemisphere involving Broca's area, while the right middle frontal gyrus was activated in solving the spatial tasks. For occipital region an activation of the visual field 18 was more explicitin solving spatial problems, while the solution of anagrams caused an activation of the field 19 associated with higher levels of visual processing. The cerebellum was active bilaterally in both tasks with predominance in the second. The obtained fMRI data indicate that the verbal and spatial types of thinking are provided by an activation of narrow specific sets of brain structures, while the previous electrophysiological studies indicate the distributed nature of the brain processes in thinking. Combining these two approaches, it can be concluded that cognitive functions are supported by the systemic brain processes with a distinct location of the particular salient structures.

Analysis of skin tissues spatial fluorescence distribution by the Monte Carlo simulation

NASA Astrophysics Data System (ADS)

Y Churmakov, D.; Meglinski, I. V.; Piletsky, S. A.; Greenhalgh, D. A.

2003-07-01

A novel Monte Carlo technique of simulation of spatial fluorescence distribution within the human skin is presented. The computational model of skin takes into account the spatial distribution of fluorophores, which would arise due to the structure of collagen fibres, compared to the epidermis and stratum corneum where the distribution of fluorophores is assumed to be homogeneous. The results of simulation suggest that distribution of auto-fluorescence is significantly suppressed in the near-infrared spectral region, whereas the spatial distribution of fluorescence sources within a sensor layer embedded in the epidermis is localized at an `effective' depth.

How urban system vulnerabilities to flooding could be assessed to improve resilience and adaptation in spatial planning

NASA Astrophysics Data System (ADS)

Pasi, Riccardo; Viavattene, Christophe; La Loggia, Goffredo

2016-04-01

Natural hazards damage assets and infrastructure inducing disruptions to urban functions and key daily services. These disruptions may be short or long with a variable spatial scale of impact. From an urban planning perspective, measuring these disruptions and their consequences at an urban scale is fundamental in order to develop more resilient cities. Whereas the assessment of physical vulnerabilities and direct damages is commonly addressed, new methodologies for assessing the systemic vulnerability at the urban scale are required to reveal these disruptions and their consequences. Physical and systemic vulnerability should be measured in order to reflect the multifaceted fragility of cities in the face of external stress, both in terms of the natural/built environment and socio-economic sphere. Additionally, a systemic approach allows the consideration of vulnerability across different spatial scales, as impacts may vary and be transmitted across local, regional or national levels. Urban systems are spatially distributed and the nature of this can have significant effects on flood impacts. The proposed approach identifies the vulnerabilities of flooding within urban contexts, including both in terms of single elementary units (buildings, infrastructures, people, etc.) and systemic functioning (urban functions and daily life networks). Direct losses are appraised initially using conventional methodologies (e.g. depth-damage functions). This aims to both understand the spatial distribution of physical vulnerability and associated losses and, secondly, to identify the most vulnerable building types and ways to improve the physical adaptation of our cities, proposing changes to building codes, design principles and other municipal regulation tools. The subsequent systemic approach recognises the city as a collection of sub-systems or functional units (such as neighbourhoods and suburbs) providing key daily services for inhabitants (e.g. healthcare facilities, schools, administration offices, food shops, leisure and cultural services etc.) and which are interconnected through transport networks. Moreover, each city is part of broader systems - which may or may not follow administrative boundaries - and, as such, need to be connected to its wider surroundings, in a multi-scalar perspective. The systemic analysis, herein limited to residential households, evaluates the presence, the distribution among functional units and the redundancy of key daily services. As such, systemic interdependences between neighbourhoods/suburbs and municipalities emerge, highlighting how systemic vulnerability spreads beyond the flooded areas. This aims to understand which planning patterns and existing mixed-use developments are more flood resilient (thereby informing future urban development/regeneration) and which infrastructure and assets have a key role within the urban system (and have therefore to be prioritised for protection). The methodology is currently developed through an extensive use of Geographic Information Systems (GIS) and applied to an Italian case study (Noale municipality, Venice). Current developments and on-going issues in its application and in the data collection (including the use of aerial survey data) will be discussed in the presentation.

Land cover mapping at sub-pixel scales

NASA Astrophysics Data System (ADS)

Makido, Yasuyo Kato

One of the biggest drawbacks of land cover mapping from remotely sensed images relates to spatial resolution, which determines the level of spatial details depicted in an image. Fine spatial resolution images from satellite sensors such as IKONOS and QuickBird are now available. However, these images are not suitable for large-area studies, since a single image is very small and therefore it is costly for large area studies. Much research has focused on attempting to extract land cover types at sub-pixel scale, and little research has been conducted concerning the spatial allocation of land cover types within a pixel. This study is devoted to the development of new algorithms for predicting land cover distribution using remote sensory imagery at sub-pixel level. The "pixel-swapping" optimization algorithm, which was proposed by Atkinson for predicting sub-pixel land cover distribution, is investigated in this study. Two limitations of this method, the arbitrary spatial range value and the arbitrary exponential model of spatial autocorrelation, are assessed. Various weighting functions, as alternatives to the exponential model, are evaluated in order to derive the optimum weighting function. Two different simulation models were employed to develop spatially autocorrelated binary class maps. In all tested models, Gaussian, Exponential, and IDW, the pixel swapping method improved classification accuracy compared with the initial random allocation of sub-pixels. However the results suggested that equal weight could be used to increase accuracy and sub-pixel spatial autocorrelation instead of using these more complex models of spatial structure. New algorithms for modeling the spatial distribution of multiple land cover classes at sub-pixel scales are developed and evaluated. Three methods are examined: sequential categorical swapping, simultaneous categorical swapping, and simulated annealing. These three methods are applied to classified Landsat ETM+ data that has been resampled to 210 meters. The result suggested that the simultaneous method can be considered as the optimum method in terms of accuracy performance and computation time. The case study employs remote sensing imagery at the following sites: tropical forests in Brazil and temperate multiple land mosaic in East China. Sub-areas for both sites are used to examine how the characteristics of the landscape affect the ability of the optimum technique. Three types of measurement: Moran's I, mean patch size (MPS), and patch size standard deviation (STDEV), are used to characterize the landscape. All results suggested that this technique could increase the classification accuracy more than traditional hard classification. The methods developed in this study can benefit researchers who employ coarse remote sensing imagery but are interested in detailed landscape information. In many cases, the satellite sensor that provides large spatial coverage has insufficient spatial detail to identify landscape patterns. Application of the super-resolution technique described in this dissertation could potentially solve this problem by providing detailed land cover predictions from the coarse resolution satellite sensor imagery.

Density-functional theory based on the electron distribution on the energy coordinate

NASA Astrophysics Data System (ADS)

Takahashi, Hideaki

2018-03-01

We developed an electronic density functional theory utilizing a novel electron distribution n(ɛ) as a basic variable to compute ground state energy of a system. n(ɛ) is obtained by projecting the electron density n({\\boldsymbol{r}}) defined on the space coordinate {\\boldsymbol{r}} onto the energy coordinate ɛ specified with the external potential {\\upsilon }ext}({\\boldsymbol{r}}) of interest. It was demonstrated that the Kohn-Sham equation can also be formulated with the exchange-correlation functional E xc[n(ɛ)] that employs the density n(ɛ) as an argument. It turned out an exchange functional proposed in our preliminary development suffices to describe properly the potential energies of several types of chemical bonds with comparable accuracies to the corresponding functional based on local density approximation. As a remarkable feature of the distribution n(ɛ) it inherently involves the spatially non-local information of the exchange hole at the bond dissociation limit in contrast to conventional approximate functionals. By taking advantage of this property we also developed a prototype of the static correlation functional E sc including no empirical parameters, which showed marked improvements in describing the dissociations of covalent bonds in {{{H}}}2,{{{C}}}2{{{H}}}4 and {CH}}4 molecules.

Investigating the relationship between a soils classification and the spatial parameters of a conceptual catchment-scale hydrological model

NASA Astrophysics Data System (ADS)

Dunn, S. M.; Lilly, A.

2001-10-01

There are now many examples of hydrological models that utilise the capabilities of Geographic Information Systems to generate spatially distributed predictions of behaviour. However, the spatial variability of hydrological parameters relating to distributions of soils and vegetation can be hard to establish. In this paper, the relationship between a soil hydrological classification Hydrology of Soil Types (HOST) and the spatial parameters of a conceptual catchment-scale model is investigated. A procedure involving inverse modelling using Monte-Carlo simulations on two catchments is developed to identify relative values for soil related parameters of the DIY model. The relative values determine the internal variability of hydrological processes as a function of the soil type. For three out of the four soil parameters studied, the variability between HOST classes was found to be consistent across two catchments when tested independently. Problems in identifying values for the fourth 'fast response distance' parameter have highlighted a potential limitation with the present structure of the model. The present assumption that this parameter can be related simply to soil type rather than topography appears to be inadequate. With the exclusion of this parameter, calibrated parameter sets from one catchment can be converted into equivalent parameter sets for the alternate catchment on the basis of their HOST distributions, to give a reasonable simulation of flow. Following further testing on different catchments, and modifications to the definition of the fast response distance parameter, the technique provides a methodology whereby it is possible to directly derive spatial soil parameters for new catchments.

Thermal equilibrium and statistical thermometers in special relativity.

PubMed

Cubero, David; Casado-Pascual, Jesús; Dunkel, Jörn; Talkner, Peter; Hänggi, Peter

2007-10-26

There is an intense debate in the recent literature about the correct generalization of Maxwell's velocity distribution in special relativity. The most frequently discussed candidate distributions include the Jüttner function as well as modifications thereof. Here we report results from fully relativistic one-dimensional molecular dynamics simulations that resolve the ambiguity. The numerical evidence unequivocally favors the Jüttner distribution. Moreover, our simulations illustrate that the concept of "thermal equilibrium" extends naturally to special relativity only if a many-particle system is spatially confined. They make evident that "temperature" can be statistically defined and measured in an observer frame independent way.

Geospatial assessment of ecological functions and flood-related risks on floodplains along major rivers in the Puget Sound Basin, Washington

USGS Publications Warehouse

Konrad, Christopher P.

2015-01-01

Ecological functions and flood-related risks were assessed for floodplains along the 17 major rivers flowing into Puget Sound Basin, Washington. The assessment addresses five ecological functions, five components of flood-related risks at two spatial resolutions—fine and coarse. The fine-resolution assessment compiled spatial attributes of floodplains from existing, publically available sources and integrated the attributes into 10-meter rasters for each function, hazard, or exposure. The raster values generally represent different types of floodplains with regard to each function, hazard, or exposure rather than the degree of function, hazard, or exposure. The coarse-resolution assessment tabulates attributes from the fine-resolution assessment for larger floodplain units, which are floodplains associated with 0.1 to 21-kilometer long segments of major rivers. The coarse-resolution assessment also derives indices that can be used to compare function or risk among different floodplain units and to develop normative (based on observed distributions) standards. The products of the assessment are available online as geospatial datasets (Konrad, 2015; http://dx.doi.org/10.5066/F7DR2SJC).

Functionally independent components of the late positive event-related potential during visual spatial attention.

PubMed

Makeig, S; Westerfield, M; Jung, T P; Covington, J; Townsend, J; Sejnowski, T J; Courchesne, E

1999-04-01

Human event-related potentials (ERPs) were recorded from 10 subjects presented with visual target and nontarget stimuli at five screen locations and responding to targets presented at one of the locations. The late positive response complexes of 25-75 ERP average waveforms from the two task conditions were simultaneously analyzed with Independent Component Analysis, a new computational method for blindly separating linearly mixed signals. Three spatially fixed, temporally independent, behaviorally relevant, and physiologically plausible components were identified without reference to peaks in single-channel waveforms. A novel frontoparietal component (P3f) began at approximately 140 msec and peaked, in faster responders, at the onset of the motor command. The scalp distribution of P3f appeared consistent with brain regions activated during spatial orienting in functional imaging experiments. A longer-latency large component (P3b), positive over parietal cortex, was followed by a postmotor potential (Pmp) component that peaked 200 msec after the button press and reversed polarity near the central sulcus. A fourth component associated with a left frontocentral nontarget positivity (Pnt) was evoked primarily by target-like distractors presented in the attended location. When no distractors were presented, responses of five faster-responding subjects contained largest P3f and smallest Pmp components; when distractors were included, a Pmp component appeared only in responses of the five slower-responding subjects. Direct relationships between component amplitudes, latencies, and behavioral responses, plus similarities between component scalp distributions and regional activations reported in functional brain imaging experiments suggest that P3f, Pmp, and Pnt measure the time course and strength of functionally distinct brain processes.

Distributed Lag Models: Examining Associations between the Built Environment and Health

PubMed Central

Baek, Jonggyu; Sánchez, Brisa N.; Berrocal, Veronica J.; Sanchez-Vaznaugh, Emma V.

2016-01-01

Built environment factors constrain individual level behaviors and choices, and thus are receiving increasing attention to assess their influence on health. Traditional regression methods have been widely used to examine associations between built environment measures and health outcomes, where a fixed, pre-specified spatial scale (e.g., 1 mile buffer) is used to construct environment measures. However, the spatial scale for these associations remains largely unknown and misspecifying it introduces bias. We propose the use of distributed lag models (DLMs) to describe the association between built environment features and health as a function of distance from the locations of interest and circumvent a-priori selection of a spatial scale. Based on simulation studies, we demonstrate that traditional regression models produce associations biased away from the null when there is spatial correlation among the built environment features. Inference based on DLMs is robust under a range of scenarios of the built environment. We use this innovative application of DLMs to examine the association between the availability of convenience stores near California public schools, which may affect children’s dietary choices both through direct access to junk food and exposure to advertisement, and children’s body mass index z-scores (BMIz). PMID:26414942

Application of spatial time domain reflectometry measurements in heterogeneous, rocky substrates

NASA Astrophysics Data System (ADS)

Gonzales, C.; Scheuermann, A.; Arnold, S.; Baumgartl, T.

2016-10-01

Measurement of soil moisture across depths using sensors is currently limited to point measurements or remote sensing technologies. Point measurements have limitations on spatial resolution, while the latter, although covering large areas may not represent real-time hydrologic processes, especially near the surface. The objective of the study was to determine the efficacy of elongated soil moisture probes—spatial time domain reflectometry (STDR)—and to describe transient soil moisture dynamics of unconsolidated mine waste rock materials. The probes were calibrated under controlled conditions in the glasshouse. Transient soil moisture content was measured using the gravimetric method and STDR. Volumetric soil moisture content derived from weighing was compared with values generated from a numerical model simulating the drying process. A calibration function was generated and applied to STDR field data sets. The use of elongated probes effectively assists in the real-time determination of the spatial distribution of soil moisture. It also allows hydrologic processes to be uncovered in the unsaturated zone, especially for water balance calculations that are commonly based on point measurements. The elongated soil moisture probes can potentially describe transient substrate processes and delineate heterogeneity in terms of the pore size distribution in a seasonally wet but otherwise arid environment.

Intercommunications in Real Time, Redundant, Distributed Computer System

NASA Technical Reports Server (NTRS)

Zanger, H.

1980-01-01

An investigation into the applicability of fiber optic communication techniques to real time avionic control systems, in particular the total automatic flight control system used for the VSTOL aircraft is presented. The system consists of spatially distributed microprocessors. The overall control function is partitioned to yield a unidirectional data flow between the processing elements (PE). System reliability is enhanced by the use of triple redundancy. Some general overall system specifications are listed here to provide the necessary background for the requirements of the communications system.

Inverse analysis of non-uniform temperature distributions using multispectral pyrometry

NASA Astrophysics Data System (ADS)

Fu, Tairan; Duan, Minghao; Tian, Jibin; Shi, Congling

2016-05-01

Optical diagnostics can be used to obtain sub-pixel temperature information in remote sensing. A multispectral pyrometry method was developed using multiple spectral radiation intensities to deduce the temperature area distribution in the measurement region. The method transforms a spot multispectral pyrometer with a fixed field of view into a pyrometer with enhanced spatial resolution that can give sub-pixel temperature information from a "one pixel" measurement region. A temperature area fraction function was defined to represent the spatial temperature distribution in the measurement region. The method is illustrated by simulations of a multispectral pyrometer with a spectral range of 8.0-13.0 μm measuring a non-isothermal region with a temperature range of 500-800 K in the spot pyrometer field of view. The inverse algorithm for the sub-pixel temperature distribution (temperature area fractions) in the "one pixel" verifies this multispectral pyrometry method. The results show that an improved Levenberg-Marquardt algorithm is effective for this ill-posed inverse problem with relative errors in the temperature area fractions of (-3%, 3%) for most of the temperatures. The analysis provides a valuable reference for the use of spot multispectral pyrometers for sub-pixel temperature distributions in remote sensing measurements.

An Intrinsic Algorithm for Parallel Poisson Disk Sampling on Arbitrary Surfaces.

PubMed

Ying, Xiang; Xin, Shi-Qing; Sun, Qian; He, Ying

2013-03-08

Poisson disk sampling plays an important role in a variety of visual computing, due to its useful statistical property in distribution and the absence of aliasing artifacts. While many effective techniques have been proposed to generate Poisson disk distribution in Euclidean space, relatively few work has been reported to the surface counterpart. This paper presents an intrinsic algorithm for parallel Poisson disk sampling on arbitrary surfaces. We propose a new technique for parallelizing the dart throwing. Rather than the conventional approaches that explicitly partition the spatial domain to generate the samples in parallel, our approach assigns each sample candidate a random and unique priority that is unbiased with regard to the distribution. Hence, multiple threads can process the candidates simultaneously and resolve conflicts by checking the given priority values. It is worth noting that our algorithm is accurate as the generated Poisson disks are uniformly and randomly distributed without bias. Our method is intrinsic in that all the computations are based on the intrinsic metric and are independent of the embedding space. This intrinsic feature allows us to generate Poisson disk distributions on arbitrary surfaces. Furthermore, by manipulating the spatially varying density function, we can obtain adaptive sampling easily.

Automated aberration compensation in high numerical aperture systems for arbitrary laser modes (Conference Presentation)

NASA Astrophysics Data System (ADS)

Hering, Julian; Waller, Erik H.; von Freymann, Georg

2017-02-01

Since a large number of optical systems and devices are based on differently shaped focal intensity distributions (point-spread-functions, PSF), the PSF's quality is crucial for the application's performance. E.g., optical tweezers, optical potentials for trapping of ultracold atoms as well as stimulated-emission-depletion (STED) based microscopy and lithography rely on precisely controlled intensity distributions. However, especially in high numerical aperture (NA) systems, such complex laser modes are easily distorted by aberrations leading to performance losses. Although different approaches addressing phase retrieval algorithms have been recently presented[1-3], fast and automated aberration compensation for a broad variety of complex shaped PSFs in high NA systems is still missing. Here, we report on a Gerchberg-Saxton[4] based algorithm (GSA) for automated aberration correction of arbitrary PSFs, especially for high NA systems. Deviations between the desired target intensity distribution and the three-dimensionally (3D) scanned experimental focal intensity distribution are used to calculate a correction phase pattern. The target phase distribution plus the correction pattern are displayed on a phase-only spatial-light-modulator (SLM). Focused by a high NA objective, experimental 3D scans of several intensity distributions allow for characterization of the algorithms performance: aberrations are reliably identified and compensated within less than 10 iterations. References 1. B. M. Hanser, M. G. L. Gustafsson, D. A. Agard, and J. W. Sedat, "Phase-retrieved pupil functions in wide-field fluorescence microscopy," J. of Microscopy 216(1), 32-48 (2004). 2. A. Jesacher, A. Schwaighofer, S. Frhapter, C. Maurer, S. Bernet, and M. Ritsch-Marte, "Wavefront correction of spatial light modulators using an optical vortex image," Opt. Express 15(9), 5801-5808 (2007). 3. A. Jesacher and M. J. Booth, "Parallel direct laser writing in three dimensions with spatially dependent aberration correction," Opt. Express 18(20), 21090-21099 (2010). 4. R. W. Gerchberg and W. O. Saxton, "A practical algorithm for the determination of the phase from image and diffraction plane pictures," Optik 35(2), 237-246 (1972).

Phase Distribution and Selection of Partially Correlated Persistent Scatterers

NASA Astrophysics Data System (ADS)

Lien, J.; Zebker, H. A.

2012-12-01

Interferometric synthetic aperture radar (InSAR) time-series methods can effectively estimate temporal surface changes induced by geophysical phenomena. However, such methods are susceptible to decorrelation due to spatial and temporal baselines (radar pass separation), changes in orbital geometries, atmosphere, and noise. These effects limit the number of interferograms that can be used for differential analysis and obscure the deformation signal. InSAR decorrelation effects may be ameliorated by exploiting pixels that exhibit phase stability across the stack of interferograms. These so-called persistent scatterer (PS) pixels are dominated by a single point-like scatterer that remains phase-stable over the spatial and temporal baseline. By identifying a network of PS pixels for use in phase unwrapping, reliable deformation measurements may be obtained even in areas of low correlation, where traditional InSAR techniques fail to produce useful observations. Many additional pixels can be added to the PS list if we are able to identify those in which a dominant scatterer exhibits partial, rather than complete, correlation across all radar scenes. In this work, we quantify and exploit the phase stability of partially correlated PS pixels. We present a new system model for producing interferometric pixel values from a complex surface backscatter function characterized by signal-to-clutter ratio (SCR). From this model, we derive the joint probabilistic distribution for PS pixel phases in a stack of interferograms as a function of SCR and spatial baselines. This PS phase distribution generalizes previous results that assume the clutter phase contribution is uncorrelated between radar passes. We verify the analytic distribution through a series of radar scattering simulations. We use the derived joint PS phase distribution with maximum-likelihood SCR estimation to analyze an area of the Hayward Fault Zone in the San Francisco Bay Area. We obtain a series of 38 interferometric images of the area from C-band ERS radar satellite passes between May 1995 and December 2000. We compare the estimated SCRs to those calculated with previously derived PS phase distributions. Finally, we examine the PS network density resulting from varying selection thresholds of SCR and compare to other PS identification techniques.

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

PubMed

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

2015-03-01

Acute exacerbations of COPD (AECOPD) are important events during disease procedure. AECOPD have negative effect on patients' quality of life, symptoms and lung function, and result in high socioeconomic costs. Though previous studies have demonstrated the significant association between outdoor air pollution and AECOPD hospitalizations, little is known about the spatial relationship utilized a spatial analyzing technique- Geographical Information System (GIS). Using GIS to investigate the spatial association between ambient air pollution and AECOPD hospitalizations in Jinan City, 2009. 414 AECOPD hospitalization cases in Jinan, 2009 were enrolled in our analysis. Monthly concentrations of five monitored air pollutants (NO2, SO2, PM10, O3, CO) during January 2009-December 2009 were provided by Environmental Protection Agency of Shandong Province. Each individual was geocoded in ArcGIS10.0 software. The spatial distribution of five pollutants and the temporal-spatial specific air pollutants exposure level for each individual was estimated by ordinary Kriging model. Spatial autocorrelation (Global Moran's I) was employed to explore the spatial association between ambient air pollutants and AECOPD hospitalizations. A generalized linear model (GLM) using a Poisson distribution with log-link function was used to construct a core model. At residence, concentrations of SO2, PM10, NO2, CO, O3 and AECOPD hospitalization cases showed statistical significant spatially clustered. The Z-score of SO2, PM10, CO, O3, NO2 at residence is 15.88, 13.93, 12.60, 4.02, 2.44 respectively, while at workplace, concentrations of PM10, SO2, O3, CO and AECOPD hospitalization cases showed statistical significant spatially clustered. The Z-score of PM10, SO2, O3, CO at workplace is 11.39, 8.07, 6.10, and 5.08 respectively. After adjusting for potential confounders in the model, only the PM10 concentrations at workplace showed statistical significance, with a 10 μg/m(3) increase of PM10 at workplace associated with a 7% (95%CI: [3.3%, 10%]) increase of hospitalizations due to AECOPD. Ambient air pollution is correlated with AECOPD hospitalizations spatially. A 10 μg/m(3) increase of PM10 at workplace was associated with a 7% (95%CI: [3.3%, 10%]) increase of hospitalizations due to AECOPD in Jinan, 2009. As a spatial data processing tool, GIS has novel and great potential on air pollutants exposure assessment and spatial analysis in AECOPD research. Copyright © 2015 Elsevier Ltd. All rights reserved.

NEON terrestrial field observations: designing continental scale, standardized sampling

Treesearch

R. H. Kao; C.M. Gibson; R. E. Gallery; C. L. Meier; D. T. Barnett; K. M. Docherty; K. K. Blevins; P. D. Travers; E. Azuaje; Y. P. Springer; K. M. Thibault; V. J. McKenzie; M. Keller; L. F. Alves; E. L. S. Hinckley; J. Parnell; D. Schimel

2012-01-01

Rapid changes in climate and land use and the resulting shifts in species distributions and ecosystem functions have motivated the development of the National Ecological Observatory Network (NEON). Integrating across spatial scales from ground sampling to remote sensing, NEON will provide data for users to address ecological responses to changes in climate, land use,...

Attentional Control in Visual Signal Detection: Effects of Abrupt-Onset and No-Onset Stimuli

ERIC Educational Resources Information Center

Sewell, David K.; Smith, Philip L.

2012-01-01

The attention literature distinguishes two general mechanisms by which attention can benefit performance: gain (or resource) models and orienting (or switching) models. In gain models, processing efficiency is a function of a spatial distribution of capacity or resources; in orienting models, an attentional spotlight must be aligned with the…

Spatial Distribution of Oxygen Chemical Potential under Potential Gradients and Theoretical Maximum Power Density with 8YSZ Electrolyte

NASA Astrophysics Data System (ADS)

Lim, Dae-Kwang; Im, Ha-Ni; Song, Sun-Ju

2016-01-01

The maximum power density of SOFC with 8YSZ electrolyte as the function of thickness was calculated by integrating partial conductivities of charge carriers under various DC bias conditions at a fixed oxygen chemical potential gradient at both sides of the electrolyte. The partial conductivities were successfully taken using the Hebb-Wagner polarization method as a function of temperature and oxygen partial pressure, and the spatial distribution of oxygen partial pressure across the electrolyte was calculated based on Choudhury and Patterson’s model by considering zero electrode polarization. At positive voltage conditions corresponding to SOFC and SOEC, the high conductivity region was expanded, but at negative cell voltage condition, the low conductivity region near n-type to p-type transition was expanded. In addition, the maximum power density calculated from the current-voltage characteristic showed approximately 5.76 W/cm2 at 700 oC with 10 μm thick-8YSZ, while the oxygen partial pressure of the cathode and anode sides maintained ≈0.21 and 10-22 atm.

Global Warming Induced Changes in Rainfall Characteristics in IPCC AR5 Models

NASA Technical Reports Server (NTRS)

Lau, William K. M.; Wu, Jenny, H.-T.; Kim, Kyu-Myong

2012-01-01

Changes in rainfall characteristic induced by global warming are examined from outputs of IPCC AR5 models. Different scenarios of climate warming including a high emissions scenario (RCP 8.5), a medium mitigation scenario (RCP 4.5), and 1% per year CO2 increase are compared to 20th century simulations (historical). Results show that even though the spatial distribution of monthly rainfall anomalies vary greatly among models, the ensemble mean from a sizable sample (about 10) of AR5 models show a robust signal attributable to GHG warming featuring a shift in the global rainfall probability distribution function (PDF) with significant increase (>100%) in very heavy rain, reduction (10-20% ) in moderate rain and increase in light to very light rains. Changes in extreme rainfall as a function of seasons and latitudes are also examined, and are similar to the non-seasonal stratified data, but with more specific spatial dependence. These results are consistent from TRMM and GPCP rainfall observations suggesting that extreme rainfall events are occurring more frequently with wet areas getting wetter and dry-area-getting drier in a GHG induced warmer climate.

Skyshine study for next generation of fusion devices

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

Gohar, Y.; Yang, S.

1987-02-01

A shielding analysis for next generation of fusion devices (ETR/INTOR) was performed to study the dose equivalent outside the reactor building during operation including the contribution from neutrons and photons scattered back by collisions with air nuclei (skyshine component). Two different three-dimensional geometrical models for a tokamak fusion reactor based on INTOR design parameters were developed for this study. In the first geometrical model, the reactor geometry and the spatial distribution of the deuterium-tritium neutron source were simplified for a parametric survey. The second geometrical model employed an explicit representation of the toroidal geometry of the reactor chamber and themore » spatial distribution of the neutron source. The MCNP general Monte Carlo code for neutron and photon transport was used to perform all the calculations. The energy distribution of the neutron source was used explicitly in the calculations with ENDF/B-V data. The dose equivalent results were analyzed as a function of the concrete roof thickness of the reactor building and the location outside the reactor building.« less

Developing a Hierarchical Model for the Spatial Analysis of PM10 Pollution Extremes in the Mexico City Metropolitan Area.

PubMed

Aguirre-Salado, Alejandro Ivan; Vaquera-Huerta, Humberto; Aguirre-Salado, Carlos Arturo; Reyes-Mora, Silvia; Olvera-Cervantes, Ana Delia; Lancho-Romero, Guillermo Arturo; Soubervielle-Montalvo, Carlos

2017-07-06

We implemented a spatial model for analysing PM 10 maxima across the Mexico City metropolitan area during the period 1995-2016. We assumed that these maxima follow a non-identical generalized extreme value (GEV) distribution and modeled the trend by introducing multivariate smoothing spline functions into the probability GEV distribution. A flexible, three-stage hierarchical Bayesian approach was developed to analyse the distribution of the PM 10 maxima in space and time. We evaluated the statistical model's performance by using a simulation study. The results showed strong evidence of a positive correlation between the PM 10 maxima and the longitude and latitude. The relationship between time and the PM 10 maxima was negative, indicating a decreasing trend over time. Finally, a high risk of PM 10 maxima presenting levels above 1000 μ g/m 3 (return period: 25 yr) was observed in the northwestern region of the study area.

Developing a Hierarchical Model for the Spatial Analysis of PM10 Pollution Extremes in the Mexico City Metropolitan Area

PubMed Central

Aguirre-Salado, Alejandro Ivan; Vaquera-Huerta, Humberto; Aguirre-Salado, Carlos Arturo; Reyes-Mora, Silvia; Olvera-Cervantes, Ana Delia; Lancho-Romero, Guillermo Arturo; Soubervielle-Montalvo, Carlos

2017-01-01

We implemented a spatial model for analysing PM10 maxima across the Mexico City metropolitan area during the period 1995–2016. We assumed that these maxima follow a non-identical generalized extreme value (GEV) distribution and modeled the trend by introducing multivariate smoothing spline functions into the probability GEV distribution. A flexible, three-stage hierarchical Bayesian approach was developed to analyse the distribution of the PM10 maxima in space and time. We evaluated the statistical model’s performance by using a simulation study. The results showed strong evidence of a positive correlation between the PM10 maxima and the longitude and latitude. The relationship between time and the PM10 maxima was negative, indicating a decreasing trend over time. Finally, a high risk of PM10 maxima presenting levels above 1000 μg/m3 (return period: 25 yr) was observed in the northwestern region of the study area. PMID:28684720

A New Perspective: Assessing the Spatial Distribution of Coral Bleaching with Unmanned Low Altitude Remote Sensing Systems

NASA Astrophysics Data System (ADS)

Levy, J.; Franklin, E. C.; Hunter, C. L.

2016-12-01

Coral reefs are biodiversity hotspots that are vital to the function of global economic and biological processes. Coral bleaching is a significant contributor to the global decline of reefs and can impact an expansive reef area over short timescales. In order to understand the dynamics of coral bleaching and how these stress events impact reef ecosystems, it is important to conduct rapid bleaching surveys at functionally important spatial scales. Due to the inherent heterogeneity, size, and in some cases, remoteness of coral reefs, it is difficult to routinely monitor coral bleaching dynamics before, during, and after bleaching. Additionally, current in situ survey methods only collect snippets of discrete reef data over small reef areas, which are unable to accurately represent the reef as a whole. We present a new technique using small unmanned aerial systems (sUAS) as cost effective, efficient monitoring tools that target small to intermediate-scale reef dynamics to understand the spatial distribution of bleached coral colonies during the 2015 bleaching event on patch reefs in Kaneohe Bay, Oahu. Overlapping low altitude aerial images were collected at four reefs during the bleaching period and processed using Structure-from-Motion techniques to produce georeferenced and spatially accurate orthomosaics of complete reef areas. Mosaics were analyzed using manual and heuristic neural network classification schemes to identify comprehensive populations of bleached and live coral on each patch reef. We found that bleached colonies had random and clumped distributions on patch reefs in Kaneohe Bay depending on local environmental conditions. Our work demonstrates that sUAS provide a low cost, efficient platform that can rapidly and repeatedly collect high-resolution imagery (1 cm/pixel) and map large areas of shallow reef ecosystems (5 hectares). This study proves the feasibility of utilizing sUAS as a tool to collect spatially rich reef data that will provide reef scientists a new perspective on meso-scale coral reef dynamics. We envision that similar low altitude aerial surveys will be incorporated as a standard component of shallow-water reef studies, especially on reefs too dangerous or remote for in situ surveys.

Wigner distribution function and kurtosis parameter of vortex beams propagating through turbulent atmosphere

NASA Astrophysics Data System (ADS)

Suo, Qiangbo; Han, Yiping; Cui, Zhiwei

2017-09-01

Based on the extended Huygens-Fresnel integral, the analytical expressions for the Wigner distribution function (WDF) and kurtosis parameter of partially coherent flat-topped vortex (PCFTV) beams propagating through atmospheric turbulence and free space are derived. The WDF and kurtosis parameter of PCFTV beams through turbulent atmosphere are discussed with numerical examples. The numerical results show that the beam quality depends on the structure constants, the inner scale turbulence, the outer scale turbulence, the spatial correlation length, the wave length and the beam order. PCFTV beams are less affected by turbulence than partially flat-topped coherent (PCFT) beams under the same conditions, and will be useful in free-space optical communications.

Mixtures of amino-acid based ionic liquids and water.

PubMed

Chaban, Vitaly V; Fileti, Eudes Eterno

2015-09-01

New ionic liquids (ILs) involving increasing numbers of organic and inorganic ions are continuously being reported. We recently developed a new force field; in the present work, we applied that force field to investigate the structural properties of a few novel imidazolium-based ILs in aqueous mixtures via molecular dynamics (MD) simulations. Using cluster analysis, radial distribution functions, and spatial distribution functions, we argue that organic ions (imidazolium, deprotonated alanine, deprotonated methionine, deprotonated tryptophan) are well dispersed in aqueous media, irrespective of the IL content. Aqueous dispersions exhibit desirable properties for chemical engineering. The ILs exist as ion pairs in relatively dilute aqueous mixtures (10 mol%), while more concentrated mixtures feature a certain amount of larger ionic aggregates.

The investigation of the lateral interaction effect's on traffic flow behavior under open boundaries

NASA Astrophysics Data System (ADS)

Bouadi, M.; Jetto, K.; Benyoussef, A.; El Kenz, A.

2017-11-01

In this paper, an open boundaries traffic flow system is studied by taking into account the lateral interaction with spatial defects. For a random defects distribution, if the vehicles velocities are weakly correlated, the traffic phases can be predicted by considering the corresponding inflow and outflow functions. Conversely, if the vehicles velocities are strongly correlated, a phase segregation appears inside the system's bulk which induces the maximum current appearance. Such velocity correlation depends mainly on the defects densities and the probabilities of lateral deceleration. However, for a compact defects distribution, the traffic phases are predictable by using the inflow in the system beginning, the inflow entering the defects zone and the outflow function.

Influence of surface modification of halloysite nanotubes on their dispersion in epoxy matrix: Mesoscopic DPD simulation

NASA Astrophysics Data System (ADS)

Komarov, P.; Markina, A.; Ivanov, V.

2016-06-01

The problems of constructing of a meso-scale model of composites based on polymers and aluminosilicate nanotubes for prediction of the filler's spatial distribution at early stages of material formation have been considered. As a test system for the polymer matrix, the mixture of 3,4-epoxycyclohexylmethyl-3,4-epoxycyclohexanecarboxylate as epoxy resin monomers and 4-methylhexahydrophthalic anhydride as curing agent has been used. It is shown that the structure of a mixture of uncured epoxy resin and nanotubes is (mainly) determined by the surface functionalization of nanotubes. The results indicate that only nanotubes with maximum functionalization can preserve a uniform distribution in space.

Magnetoacoustic tomography with magnetic induction for high-resolution bioimepedance imaging through vector source reconstruction under the static field of MRI magnet

PubMed Central

Mariappan, Leo; Hu, Gang; He, Bin

2014-01-01

Purpose: Magnetoacoustic tomography with magnetic induction (MAT-MI) is an imaging modality to reconstruct the electrical conductivity of biological tissue based on the acoustic measurements of Lorentz force induced tissue vibration. This study presents the feasibility of the authors' new MAT-MI system and vector source imaging algorithm to perform a complete reconstruction of the conductivity distribution of real biological tissues with ultrasound spatial resolution. Methods: In the present study, using ultrasound beamformation, imaging point spread functions are designed to reconstruct the induced vector source in the object which is used to estimate the object conductivity distribution. Both numerical studies and phantom experiments are performed to demonstrate the merits of the proposed method. Also, through the numerical simulations, the full width half maximum of the imaging point spread function is calculated to estimate of the spatial resolution. The tissue phantom experiments are performed with a MAT-MI imaging system in the static field of a 9.4 T magnetic resonance imaging magnet. Results: The image reconstruction through vector beamformation in the numerical and experimental studies gives a reliable estimate of the conductivity distribution in the object with a ∼1.5 mm spatial resolution corresponding to the imaging system frequency of 500 kHz ultrasound. In addition, the experiment results suggest that MAT-MI under high static magnetic field environment is able to reconstruct images of tissue-mimicking gel phantoms and real tissue samples with reliable conductivity contrast. Conclusions: The results demonstrate that MAT-MI is able to image the electrical conductivity properties of biological tissues with better than 2 mm spatial resolution at 500 kHz, and the imaging with MAT-MI under a high static magnetic field environment is able to provide improved imaging contrast for biological tissue conductivity reconstruction. PMID:24506649

Cerebral White Matter Integrity and Cognitive Aging: Contributions from Diffusion Tensor Imaging

PubMed Central

Madden, David J.; Bennett, Ilana J.; Song, Allen W.

2009-01-01

The integrity of cerebral white matter is critical for efficient cognitive functioning, but little is known regarding the role of white matter integrity in age-related differences in cognition. Diffusion tensor imaging (DTI) measures the directional displacement of molecular water and as a result can characterize the properties of white matter that combine to restrict diffusivity in a spatially coherent manner. This review considers DTI studies of aging and their implications for understanding adult age differences in cognitive performance. Decline in white matter integrity contributes to a disconnection among distributed neural systems, with a consistent effect on perceptual speed and executive functioning. The relation between white matter integrity and cognition varies across brain regions, with some evidence suggesting that age-related effects exhibit an anterior-posterior gradient. With continued improvements in spatial resolution and integration with functional brain imaging, DTI holds considerable promise, both for theories of cognitive aging and for translational application. PMID:19705281

Electrophysiological Source Imaging: A Noninvasive Window to Brain Dynamics.

PubMed

He, Bin; Sohrabpour, Abbas; Brown, Emery; Liu, Zhongming

2018-06-04

Brain activity and connectivity are distributed in the three-dimensional space and evolve in time. It is important to image brain dynamics with high spatial and temporal resolution. Electroencephalography (EEG) and magnetoencephalography (MEG) are noninvasive measurements associated with complex neural activations and interactions that encode brain functions. Electrophysiological source imaging estimates the underlying brain electrical sources from EEG and MEG measurements. It offers increasingly improved spatial resolution and intrinsically high temporal resolution for imaging large-scale brain activity and connectivity on a wide range of timescales. Integration of electrophysiological source imaging and functional magnetic resonance imaging could further enhance spatiotemporal resolution and specificity to an extent that is not attainable with either technique alone. We review methodological developments in electrophysiological source imaging over the past three decades and envision its future advancement into a powerful functional neuroimaging technology for basic and clinical neuroscience applications.

Discriminative analysis of non-linear brain connectivity for leukoaraiosis with resting-state fMRI

NASA Astrophysics Data System (ADS)

Lai, Youzhi; Xu, Lele; Yao, Li; Wu, Xia

2015-03-01

Leukoaraiosis (LA) describes diffuse white matter abnormalities on CT or MR brain scans, often seen in the normal elderly and in association with vascular risk factors such as hypertension, or in the context of cognitive impairment. The mechanism of cognitive dysfunction is still unclear. The recent clinical studies have revealed that the severity of LA was not corresponding to the cognitive level, and functional connectivity analysis is an appropriate method to detect the relation between LA and cognitive decline. However, existing functional connectivity analyses of LA have been mostly limited to linear associations. In this investigation, a novel measure utilizing the extended maximal information coefficient (eMIC) was applied to construct non-linear functional connectivity in 44 LA subjects (9 dementia, 25 mild cognitive impairment (MCI) and 10 cognitively normal (CN)). The strength of non-linear functional connections for the first 1% of discriminative power increased in MCI compared with CN and dementia, which was opposed to its linear counterpart. Further functional network analysis revealed that the changes of the non-linear and linear connectivity have similar but not completely the same spatial distribution in human brain. In the multivariate pattern analysis with multiple classifiers, the non-linear functional connectivity mostly identified dementia, MCI and CN from LA with a relatively higher accuracy rate than the linear measure. Our findings revealed the non-linear functional connectivity provided useful discriminative power in classification of LA, and the spatial distributed changes between the non-linear and linear measure may indicate the underlying mechanism of cognitive dysfunction in LA.

Inner membrane fusion mediates spatial distribution of axonal mitochondria

PubMed Central

Yu, Yiyi; Lee, Hao-Chih; Chen, Kuan-Chieh; Suhan, Joseph; Qiu, Minhua; Ba, Qinle; Yang, Ge

2016-01-01

In eukaryotic cells, mitochondria form a dynamic interconnected network to respond to changing needs at different subcellular locations. A fundamental yet unanswered question regarding this network is whether, and if so how, local fusion and fission of individual mitochondria affect their global distribution. To address this question, we developed high-resolution computational image analysis techniques to examine the relations between mitochondrial fusion/fission and spatial distribution within the axon of Drosophila larval neurons. We found that stationary and moving mitochondria underwent fusion and fission regularly but followed different spatial distribution patterns and exhibited different morphology. Disruption of inner membrane fusion by knockdown of dOpa1, Drosophila Optic Atrophy 1, not only increased the spatial density of stationary and moving mitochondria but also changed their spatial distributions and morphology differentially. Knockdown of dOpa1 also impaired axonal transport of mitochondria. But the changed spatial distributions of mitochondria resulted primarily from disruption of inner membrane fusion because knockdown of Milton, a mitochondrial kinesin-1 adapter, caused similar transport velocity impairment but different spatial distributions. Together, our data reveals that stationary mitochondria within the axon interconnect with moving mitochondria through fusion and fission and that local inner membrane fusion between individual mitochondria mediates their global distribution. PMID:26742817

Spatiotemporal Stability of Cu-ATSM and FLT Positron Emission Tomography Distributions During Radiation Therapy

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

Bradshaw, Tyler J.; Yip, Stephen; Jallow, Ngoneh

2014-06-01

Purpose: In dose painting, in which functional imaging is used to define biological targets for radiation therapy dose escalation, changes in spatial distributions of biological properties during treatment can compromise the quality of therapy. The goal of this study was to assess the spatiotemporal stability of 2 potential dose painting targets—hypoxia and proliferation—in canine tumors during radiation therapy. Methods and Materials: Twenty-two canine patients with sinonasal tumors (14 carcinoma and 8 sarcoma) were imaged before hypofractionated radiation therapy with copper(II)-diacetyl-bis(N4-methylthiosemicarbazone) (Cu-ATSM) positron emission tomography/computed tomography (PET/CT) for hypoxia and 3′-deoxy-3′-{sup 18}F-fluorothymidine (FLT) PET/CT for proliferation. The FLT scans were repeatedmore » after 2 fractions and the Cu-ATSM scans after 3 fractions. Midtreatment PET/CT images were deformably registered to pretreatment PET/CT images. Voxel-based Spearman correlation coefficients quantified the spatial stability of Cu-ATSM and FLT uptake distributions between pretreatment and midtreatment scans. Paired t tests determined significant differences between the patients' respective Cu-ATSM and FLT correlations coefficients. Standardized uptake value measures were also compared between pretreatment and midtreatment scans by use of paired t tests. Results: Spatial distributions of Cu-ATSM and FLT uptake were stable through midtreatment for both sarcomas and carcinomas: the population mean ± standard deviation in Spearman correlation coefficient was 0.88 ± 0.07 for Cu-ATSM and 0.79 ± 0.13 for FLT. The patients' Cu-ATSM correlation coefficients were significantly higher than their respective FLT correlation coefficients (P=.001). Changes in Cu-ATSM SUV measures from pretreatment to midtreatment were histology dependent: carcinomas experienced significant decreases in Cu-ATSM uptake (P<.05), whereas sarcomas did not (P>.20). Both histologies experienced significant decreases in FLT uptake (P<.05). Conclusions: Spatial distributions of Cu-ATSM were very stable after a few fractions of radiation therapy. FLT spatial distributions were generally stable early in therapy, although they were significantly less stable than Cu-ATSM distributions. Canine tumors had significantly lower proliferative activity at midtreatment than at pretreatment, and they experienced histology-dependent changes in Cu-ATSM uptake.« less

Factors controlling spatial distribution patterns of biocrusts in a heterogeneous and topographically complex semiarid area

NASA Astrophysics Data System (ADS)

Chamizo, Sonia; Rodríguez-Caballero, Emilio; Roncero, Beatriz; Raúl Román, José; Cantón, Yolanda

2016-04-01

Biocrusts are widespread soil components in drylands all over the world. They are known to play key roles in the functioning of these regions by fixing carbon and nitrogen, regulating hydrological processes, and preventing from water and wind erosion, thus reducing the loss of soil resources and increasing soil fertility. The rate and magnitude of services provided by biocrusts greatly depend on their composition and developmental stage. Late-successional biocrusts such as lichens and mosses have higher carbon and nitrogen fixation rates, and confer greater protection against erosion and the loss of sediments and nutrients than early-successional algae and cyanobacteria biocrusts. Knowledge of spatial distribution patterns of different biocrust types and the factors that control their distribution is important to assess ecosystem services provided by biocrusts at large spatial scales and to improve modelling of biogeochemical processes and water and carbon balance in drylands. Some of the factors that condition biocrust cover and composition are incoming solar radiation, terrain attributes, vegetation distribution patterns, microclimatic variables and soil properties such as soil pH, texture, soil organic matter, soil nutrients and gypsum and CaCO3 content. However, the factors that govern biocrust distribution may vary from one site to another depending on site characteristics. In this study, we examined the influence of abiotic attributes on the spatial distribution of biocrust types in a complex heterogeneous badland system (Tabernas, SE Spain) where biocrust cover up to 50% of the soil surface. From the analysis of relationships between terrain attributes and proportional abundance of biocrust types, it was found that topography exerted a main control on the spatial distribution of biocrust types in this area. SW-facing slopes were dominated by physical soil crusts and were practically devoid of vegetation and biocrusts. Biocrusts mainly occupied the pediments and NE-facing slopes. Cyanobacteria biocrusts were predominant in the pediments, probably because of their higher capacity to produce UV-protective pigments such as carotenoids and survive in zones of higher incident solar radiation. Lichen biocrusts showed preference for NE-facing slopes that, despite being less stable than the pediments, were exposed to less insolation and probably maintained moisture availability longer. Moreover, some differences were observed between lichen species. While Diploschistes diacapsis and Squamarina lentigera were widely distributed from gentle to steep NE-facing slopes, Lepraria sp. distribution was restricted to steep N-facing slopes, where shade predominance extended the periods of soil moisture availability.

Characterizing multiscale variability of zero intermittency in spatial rainfall

NASA Technical Reports Server (NTRS)

Kumar, Praveen; Foufoula-Georgiou, Efi

1994-01-01

In this paper the authors study how zero intermittency in spatial rainfall, as described by the fraction of area covered by rainfall, changes with spatial scale of rainfall measurement or representation. A statistical measure of intermittency that describes the size distribution of 'voids' (nonrainy areas imbedded inside rainy areas) as a function of scale is also introduced. Morphological algorithms are proposed for reconstructing rainfall intermittency at fine scales given the intermittency at coarser scales. These algorithms are envisioned to be useful in hydroclimatological studies where the rainfall spatial variability at the subgrid scale needs to be reconstructed from the results of synoptic- or mesoscale meteorological numerical models. The developed methodologies are demsonstrated and tested using data from a severe springtime midlatitude squall line and a mild midlatitude winter storm monitored by a meteorological radar in Norman, Oklahoma.

Long-time behavior of the momentum distribution during the sudden expansion of a spin-imbalanced Fermi gas in one dimension.

PubMed

Bolech, C J; Heidrich-Meisner, F; Langer, S; McCulloch, I P; Orso, G; Rigol, M

2012-09-14

We study the sudden expansion of spin-imbalanced ultracold lattice fermions with attractive interactions in one dimension after turning off the longitudinal confining potential. We show that the momentum distribution functions of majority and minority fermions quickly approach stationary values due to a quantum distillation mechanism that results in a spatial separation of pairs and majority fermions. As a consequence, Fulde-Ferrell-Larkin-Ovchinnikov (FFLO) correlations are lost during the expansion. Furthermore, we argue that the shape of the stationary momentum distribution functions can be understood by relating them to the integrals of motion in this integrable quantum system. We discuss our results in the context of proposals to observe FFLO correlations, related to recent experiments by Liao et al., Nature (London) 467, 567 (2010).

Temporal and spatial distribution of phytoplankton functional groups and role of environment factors in a deep subtropical reservoir

NASA Astrophysics Data System (ADS)

Li, Lei; Li, Qiuhua; Chen, Jing'an; Wang, Jingfu; Jiao, Shulin; Chen, Fengfeng

2017-09-01

Phytoplankton and environment factors were investigated in 2015 and phytoplankton functional groups were used to understand their temporal and spatial distribution and their driving factors in Wanfeng Reservoir. Seventeen functional groups (B, D, E, F, G, J, Lo, MP, P, S1, T, W1, W2, X1, X2, Xph, Y) were identified based on 34 species. The dominant groups were: J/B/P/D in dry season, X1/J/Xph/G/T in normal season and J in flood season. Phytoplankton abundance ranged from 5.33×104 cells/L to 3.65×107 cells/L, with the highest value occurring in flood season and lowest in dry season. The vertical profile of dominant groups showed little differentiation except for P, which dominated surface layers over 20 m as a result of mixing water masses and higher transparency during dry season. However, the surface waters presented higher values of phytoplankton abundance than other layers, possibly because of greater irradiance. The significant explaining variables and their ability to describe the spatial distribution of the phytoplankton community in RDA differed seasonally as follows: dry season, NH4-N, NO3-N, NO2-N, TN:TP ratio and transparency (SD); normal season, temperature (WT), water depth, TN, NH4-N and NO3-N; flood season, WT, water depth, NO3-N and NO2-N. Furthermore, nitrogen, water temperature, SD and water depth were significant variables explaining the variance of phytoplankton communities when datasets included all samples. The results indicated that water physical conditions and hydrology were important in phytoplankton community dynamics, and nitrogen was more important than phosphorus in modifying phytoplankton communities. Seasonal differences in the relationship between the environment and phytoplankton community should be considered in water quality management.

Distribution of late gadolinium enhancement in various types of cardiomyopathies: Significance in differential diagnosis, clinical features and prognosis.

PubMed

Satoh, Hiroshi; Sano, Makoto; Suwa, Kenichiro; Saitoh, Takeji; Nobuhara, Mamoru; Saotome, Masao; Urushida, Tsuyoshi; Katoh, Hideki; Hayashi, Hideharu

2014-07-26

The recent development of cardiac magnetic resonance (CMR) techniques has allowed detailed analyses of cardiac function and tissue characterization with high spatial resolution. We review characteristic CMR features in ischemic and non-ischemic cardiomyopathies (ICM and NICM), especially in terms of the location and distribution of late gadolinium enhancement (LGE). CMR in ICM shows segmental wall motion abnormalities or wall thinning in a particular coronary arterial territory, and the subendocardial or transmural LGE. LGE in NICM generally does not correspond to any particular coronary artery distribution and is located mostly in the mid-wall to subepicardial layer. The analysis of LGE distribution is valuable to differentiate NICM with diffusely impaired systolic function, including dilated cardiomyopathy, end-stage hypertrophic cardiomyopathy (HCM), cardiac sarcoidosis, and myocarditis, and those with diffuse left ventricular (LV) hypertrophy including HCM, cardiac amyloidosis and Anderson-Fabry disease. A transient low signal intensity LGE in regions of severe LV dysfunction is a particular feature of stress cardiomyopathy. In arrhythmogenic right ventricular cardiomyopathy/dysplasia, an enhancement of right ventricular (RV) wall with functional and morphological changes of RV becomes apparent. Finally, the analyses of LGE distribution have potentials to predict cardiac outcomes and response to treatments.