A comparison of adaptive sampling designs and binary spatial models: A simulation study using a census of Bromus inermis

USGS Publications Warehouse

Irvine, Kathryn M.; Thornton, Jamie; Backus, Vickie M.; Hohmann, Matthew G.; Lehnhoff, Erik A.; Maxwell, Bruce D.; Michels, Kurt; Rew, Lisa

2013-01-01

Commonly in environmental and ecological studies, species distribution data are recorded as presence or absence throughout a spatial domain of interest. Field based studies typically collect observations by sampling a subset of the spatial domain. We consider the effects of six different adaptive and two non-adaptive sampling designs and choice of three binary models on both predictions to unsampled locations and parameter estimation of the regression coefficients (species–environment relationships). Our simulation study is unique compared to others to date in that we virtually sample a true known spatial distribution of a nonindigenous plant species, Bromus inermis. The census of B. inermis provides a good example of a species distribution that is both sparsely (1.9 % prevalence) and patchily distributed. We find that modeling the spatial correlation using a random effect with an intrinsic Gaussian conditionally autoregressive prior distribution was equivalent or superior to Bayesian autologistic regression in terms of predicting to un-sampled areas when strip adaptive cluster sampling was used to survey B. inermis. However, inferences about the relationships between B. inermis presence and environmental predictors differed between the two spatial binary models. The strip adaptive cluster designs we investigate provided a significant advantage in terms of Markov chain Monte Carlo chain convergence when trying to model a sparsely distributed species across a large area. In general, there was little difference in the choice of neighborhood, although the adaptive king was preferred when transects were randomly placed throughout the spatial domain.

The model of drugs distribution dynamics in biological tissue

NASA Astrophysics Data System (ADS)

Ginevskij, D. A.; Izhevskij, P. V.; Sheino, I. N.

2017-09-01

The dose distribution by Neutron Capture Therapy follows the distribution of 10B in the tissue. The modern models of pharmacokinetics of drugs describe the processes occurring in conditioned "chambers" (blood-organ-tumor), but fail to describe the spatial distribution of the drug in the tumor and in normal tissue. The mathematical model of the spatial distribution dynamics of drugs in the tissue, depending on the concentration of the drug in the blood, was developed. The modeling method is the representation of the biological structure in the form of a randomly inhomogeneous medium in which the 10B distribution occurs. The parameters of the model, which cannot be determined rigorously in the experiment, are taken as the quantities subject to the laws of the unconnected random processes. The estimates of 10B distribution preparations in the tumor and healthy tissue, inside/outside the cells, are obtained.

Rupture Propagation for Stochastic Fault Models

NASA Astrophysics Data System (ADS)

Favreau, P.; Lavallee, D.; Archuleta, R.

2003-12-01

The inversion of strong motion data of large earhquakes give the spatial distribution of pre-stress on the ruptured faults and it can be partially reproduced by stochastic models, but a fundamental question remains: how rupture propagates, constrained by the presence of spatial heterogeneity? For this purpose we investigate how the underlying random variables, that control the pre-stress spatial variability, condition the propagation of the rupture. Two stochastic models of prestress distributions are considered, respectively based on Cauchy and Gaussian random variables. The parameters of the two stochastic models have values corresponding to the slip distribution of the 1979 Imperial Valley earthquake. We use a finite difference code to simulate the spontaneous propagation of shear rupture on a flat fault in a 3D continuum elastic body. The friction law is the slip dependent friction law. The simulations show that the propagation of the rupture front is more complex, incoherent or snake-like for a prestress distribution based on Cauchy random variables. This may be related to the presence of a higher number of asperities in this case. These simulations suggest that directivity is stronger in the Cauchy scenario, compared to the smoother rupture of the Gauss scenario.

Relevance of anisotropy and spatial variability of gas diffusivity for soil-gas transport

NASA Astrophysics Data System (ADS)

Schack-Kirchner, Helmer; Kühne, Anke; Lang, Friederike

2017-04-01

Models of soil gas transport generally do not consider neither direction dependence of gas diffusivity, nor its small-scale variability. However, in a recent study, we could provide evidence for anisotropy favouring vertical gas diffusion in natural soils. We hypothesize that gas transport models based on gas diffusion data measured with soil rings are strongly influenced by both, anisotropy and spatial variability and the use of averaged diffusivities could be misleading. To test this we used a 2-dimensional model of soil gas transport to under compacted wheel tracks to model the soil-air oxygen distribution in the soil. The model was parametrized with data obtained from soil-ring measurements with its central tendency and variability. The model includes vertical parameter variability as well as variation perpendicular to the elongated wheel track. Different parametrization types have been tested: [i)]Averaged values for wheel track and undisturbed. em [ii)]Random distribution of soil cells with normally distributed variability within the strata. em [iii)]Random distributed soil cells with uniformly distributed variability within the strata. All three types of small-scale variability has been tested for [j)] isotropic gas diffusivity and em [jj)]reduced horizontal gas diffusivity (constant factor), yielding in total six models. As expected the different parametrizations had an important influence to the aeration state under wheel tracks with the strongest oxygen depletion in case of uniformly distributed variability and anisotropy towards higher vertical diffusivity. The simple simulation approach clearly showed the relevance of anisotropy and spatial variability in case of identical central tendency measures of gas diffusivity. However, until now it did not consider spatial dependency of variability, that could even aggravate effects. To consider anisotropy and spatial variability in gas transport models we recommend a) to measure soil-gas transport parameters spatially explicit including different directions and b) to use random-field stochastic models to assess the possible effects for gas-exchange models.

Spatial versus sequential correlations for random access coding

NASA Astrophysics Data System (ADS)

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

2016-03-01

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

Properties of a new small-world network with spatially biased random shortcuts

NASA Astrophysics Data System (ADS)

Matsuzawa, Ryo; Tanimoto, Jun; Fukuda, Eriko

2017-11-01

This paper introduces a small-world (SW) network with a power-law distance distribution that differs from conventional models in that it uses completely random shortcuts. By incorporating spatial constraints, we analyze the divergence of the proposed model from conventional models in terms of fundamental network properties such as clustering coefficient, average path length, and degree distribution. We find that when the spatial constraint more strongly prohibits a long shortcut, the clustering coefficient is improved and the average path length increases. We also analyze the spatial prisoner's dilemma (SPD) games played on our new SW network in order to understand its dynamical characteristics. Depending on the basis graph, i.e., whether it is a one-dimensional ring or a two-dimensional lattice, and the parameter controlling the prohibition of long-distance shortcuts, the emergent results can vastly differ.

Stochastical analysis of surfactant-enhanced remediation of denser-than-water nonaqueous phase liquid (DNAPL)-contaminated soils.

PubMed

Zhang, Renduo; Wood, A Lynn; Enfield, Carl G; Jeong, Seung-Woo

2003-01-01

Stochastical analysis was performed to assess the effect of soil spatial variability and heterogeneity on the recovery of denser-than-water nonaqueous phase liquids (DNAPL) during the process of surfactant-enhanced remediation. UTCHEM, a three-dimensional, multicomponent, multiphase, compositional model, was used to simulate water flow and chemical transport processes in heterogeneous soils. Soil spatial variability and heterogeneity were accounted for by considering the soil permeability as a spatial random variable and a geostatistical method was used to generate random distributions of the permeability. The randomly generated permeability fields were incorporated into UTCHEM to simulate DNAPL transport in heterogeneous media and stochastical analysis was conducted based on the simulated results. From the analysis, an exponential relationship between average DNAPL recovery and soil heterogeneity (defined as the standard deviation of log of permeability) was established with a coefficient of determination (r2) of 0.991, which indicated that DNAPL recovery decreased exponentially with increasing soil heterogeneity. Temporal and spatial distributions of relative saturations in the water phase, DNAPL, and microemulsion in heterogeneous soils were compared with those in homogeneous soils and related to soil heterogeneity. Cleanup time and uncertainty to determine DNAPL distributions in heterogeneous soils were also quantified. The study would provide useful information to design strategies for the characterization and remediation of nonaqueous phase liquid-contaminated soils with spatial variability and heterogeneity.

The Temporal and Spatial Distribution of Filbert Weevil Infested Acorns in an Oak Woodland in Marin County, California

Treesearch

Vernard R. Lewis

1991-01-01

Two-hundred shoots contained within randomly selected locations from each of thirty-six coast live oak, Quercus agrifolia, trees were sampled to determine the abundance and spatial distribution of acorns infested by the filbert weevil, Curculio occidentis in northern California during 1989. The seasonal abundance of infested acorns...

Three-Dimensional Spatial Distribution of Synapses in the Neocortex: A Dual-Beam Electron Microscopy Study

PubMed Central

Merchán-Pérez, Angel; Rodríguez, José-Rodrigo; González, Santiago; Robles, Víctor; DeFelipe, Javier; Larrañaga, Pedro; Bielza, Concha

2014-01-01

In the cerebral cortex, most synapses are found in the neuropil, but relatively little is known about their 3-dimensional organization. Using an automated dual-beam electron microscope that combines focused ion beam milling and scanning electron microscopy, we have been able to obtain 10 three-dimensional samples with an average volume of 180 µm3 from the neuropil of layer III of the young rat somatosensory cortex (hindlimb representation). We have used specific software tools to fully reconstruct 1695 synaptic junctions present in these samples and to accurately quantify the number of synapses per unit volume. These tools also allowed us to determine synapse position and to analyze their spatial distribution using spatial statistical methods. Our results indicate that the distribution of synaptic junctions in the neuropil is nearly random, only constrained by the fact that synapses cannot overlap in space. A theoretical model based on random sequential absorption, which closely reproduces the actual distribution of synapses, is also presented. PMID:23365213

Three-dimensional spatial distribution of synapses in the neocortex: a dual-beam electron microscopy study.

PubMed

Merchán-Pérez, Angel; Rodríguez, José-Rodrigo; González, Santiago; Robles, Víctor; Defelipe, Javier; Larrañaga, Pedro; Bielza, Concha

2014-06-01

In the cerebral cortex, most synapses are found in the neuropil, but relatively little is known about their 3-dimensional organization. Using an automated dual-beam electron microscope that combines focused ion beam milling and scanning electron microscopy, we have been able to obtain 10 three-dimensional samples with an average volume of 180 µm(3) from the neuropil of layer III of the young rat somatosensory cortex (hindlimb representation). We have used specific software tools to fully reconstruct 1695 synaptic junctions present in these samples and to accurately quantify the number of synapses per unit volume. These tools also allowed us to determine synapse position and to analyze their spatial distribution using spatial statistical methods. Our results indicate that the distribution of synaptic junctions in the neuropil is nearly random, only constrained by the fact that synapses cannot overlap in space. A theoretical model based on random sequential absorption, which closely reproduces the actual distribution of synapses, is also presented.

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.

Anomalous transport in disordered fracture networks: Spatial Markov model for dispersion with variable injection modes

NASA Astrophysics Data System (ADS)

Kang, Peter K.; Dentz, Marco; Le Borgne, Tanguy; Lee, Seunghak; Juanes, Ruben

2017-08-01

We investigate tracer transport on random discrete fracture networks that are characterized by the statistics of the fracture geometry and hydraulic conductivity. While it is well known that tracer transport through fractured media can be anomalous and particle injection modes can have major impact on dispersion, the incorporation of injection modes into effective transport modeling has remained an open issue. The fundamental reason behind this challenge is that-even if the Eulerian fluid velocity is steady-the Lagrangian velocity distribution experienced by tracer particles evolves with time from its initial distribution, which is dictated by the injection mode, to a stationary velocity distribution. We quantify this evolution by a Markov model for particle velocities that are equidistantly sampled along trajectories. This stochastic approach allows for the systematic incorporation of the initial velocity distribution and quantifies the interplay between velocity distribution and spatial and temporal correlation. The proposed spatial Markov model is characterized by the initial velocity distribution, which is determined by the particle injection mode, the stationary Lagrangian velocity distribution, which is derived from the Eulerian velocity distribution, and the spatial velocity correlation length, which is related to the characteristic fracture length. This effective model leads to a time-domain random walk for the evolution of particle positions and velocities, whose joint distribution follows a Boltzmann equation. Finally, we demonstrate that the proposed model can successfully predict anomalous transport through discrete fracture networks with different levels of heterogeneity and arbitrary tracer injection modes.

Landscape-scale spatial abundance distributions discriminate core from random components of boreal lake bacterioplankton.

PubMed

Niño-García, Juan Pablo; Ruiz-González, Clara; Del Giorgio, Paul A

2016-12-01

Aquatic bacterial communities harbour thousands of coexisting taxa. To meet the challenge of discriminating between a 'core' and a sporadically occurring 'random' component of these communities, we explored the spatial abundance distribution of individual bacterioplankton taxa across 198 boreal lakes and their associated fluvial networks (188 rivers). We found that all taxa could be grouped into four distinct categories based on model statistical distributions (normal like, bimodal, logistic and lognormal). The distribution patterns across lakes and their associated river networks showed that lake communities are composed of a core of taxa whose distribution appears to be linked to in-lake environmental sorting (normal-like and bimodal categories), and a large fraction of mostly rare bacteria (94% of all taxa) whose presence appears to be largely random and linked to downstream transport in aquatic networks (logistic and lognormal categories). These rare taxa are thus likely to reflect species sorting at upstream locations, providing a perspective of the conditions prevailing in entire aquatic networks rather than only in lakes. © 2016 John Wiley & Sons Ltd/CNRS.

Evaluating Bayesian spatial methods for modelling species distributions with clumped and restricted occurrence data.

PubMed

Redding, David W; Lucas, Tim C D; Blackburn, Tim M; Jones, Kate E

2017-01-01

Statistical approaches for inferring the spatial distribution of taxa (Species Distribution Models, SDMs) commonly rely on available occurrence data, which is often clumped and geographically restricted. Although available SDM methods address some of these factors, they could be more directly and accurately modelled using a spatially-explicit approach. Software to fit models with spatial autocorrelation parameters in SDMs are now widely available, but whether such approaches for inferring SDMs aid predictions compared to other methodologies is unknown. Here, within a simulated environment using 1000 generated species' ranges, we compared the performance of two commonly used non-spatial SDM methods (Maximum Entropy Modelling, MAXENT and boosted regression trees, BRT), to a spatial Bayesian SDM method (fitted using R-INLA), when the underlying data exhibit varying combinations of clumping and geographic restriction. Finally, we tested how any recommended methodological settings designed to account for spatially non-random patterns in the data impact inference. Spatial Bayesian SDM method was the most consistently accurate method, being in the top 2 most accurate methods in 7 out of 8 data sampling scenarios. Within high-coverage sample datasets, all methods performed fairly similarly. When sampling points were randomly spread, BRT had a 1-3% greater accuracy over the other methods and when samples were clumped, the spatial Bayesian SDM method had a 4%-8% better AUC score. Alternatively, when sampling points were restricted to a small section of the true range all methods were on average 10-12% less accurate, with greater variation among the methods. Model inference under the recommended settings to account for autocorrelation was not impacted by clumping or restriction of data, except for the complexity of the spatial regression term in the spatial Bayesian model. Methods, such as those made available by R-INLA, can be successfully used to account for spatial autocorrelation in an SDM context and, by taking account of random effects, produce outputs that can better elucidate the role of covariates in predicting species occurrence. Given that it is often unclear what the drivers are behind data clumping in an empirical occurrence dataset, or indeed how geographically restricted these data are, spatially-explicit Bayesian SDMs may be the better choice when modelling the spatial distribution of target species.

Three-dimensional distribution of cortical synapses: a replicated point pattern-based analysis

PubMed Central

Anton-Sanchez, Laura; Bielza, Concha; Merchán-Pérez, Angel; Rodríguez, José-Rodrigo; DeFelipe, Javier; Larrañaga, Pedro

2014-01-01

The biggest problem when analyzing the brain is that its synaptic connections are extremely complex. Generally, the billions of neurons making up the brain exchange information through two types of highly specialized structures: chemical synapses (the vast majority) and so-called gap junctions (a substrate of one class of electrical synapse). Here we are interested in exploring the three-dimensional spatial distribution of chemical synapses in the cerebral cortex. Recent research has showed that the three-dimensional spatial distribution of synapses in layer III of the neocortex can be modeled by a random sequential adsorption (RSA) point process, i.e., synapses are distributed in space almost randomly, with the only constraint that they cannot overlap. In this study we hypothesize that RSA processes can also explain the distribution of synapses in all cortical layers. We also investigate whether there are differences in both the synaptic density and spatial distribution of synapses between layers. Using combined focused ion beam milling and scanning electron microscopy (FIB/SEM), we obtained three-dimensional samples from the six layers of the rat somatosensory cortex and identified and reconstructed the synaptic junctions. A total volume of tissue of approximately 4500μm3 and around 4000 synapses from three different animals were analyzed. Different samples, layers and/or animals were aggregated and compared using RSA replicated spatial point processes. The results showed no significant differences in the synaptic distribution across the different rats used in the study. We found that RSA processes described the spatial distribution of synapses in all samples of each layer. We also found that the synaptic distribution in layers II to VI conforms to a common underlying RSA process with different densities per layer. Interestingly, the results showed that synapses in layer I had a slightly different spatial distribution from the other layers. PMID:25206325

Three-dimensional distribution of cortical synapses: a replicated point pattern-based analysis.

PubMed

Anton-Sanchez, Laura; Bielza, Concha; Merchán-Pérez, Angel; Rodríguez, José-Rodrigo; DeFelipe, Javier; Larrañaga, Pedro

2014-01-01

The biggest problem when analyzing the brain is that its synaptic connections are extremely complex. Generally, the billions of neurons making up the brain exchange information through two types of highly specialized structures: chemical synapses (the vast majority) and so-called gap junctions (a substrate of one class of electrical synapse). Here we are interested in exploring the three-dimensional spatial distribution of chemical synapses in the cerebral cortex. Recent research has showed that the three-dimensional spatial distribution of synapses in layer III of the neocortex can be modeled by a random sequential adsorption (RSA) point process, i.e., synapses are distributed in space almost randomly, with the only constraint that they cannot overlap. In this study we hypothesize that RSA processes can also explain the distribution of synapses in all cortical layers. We also investigate whether there are differences in both the synaptic density and spatial distribution of synapses between layers. Using combined focused ion beam milling and scanning electron microscopy (FIB/SEM), we obtained three-dimensional samples from the six layers of the rat somatosensory cortex and identified and reconstructed the synaptic junctions. A total volume of tissue of approximately 4500μm(3) and around 4000 synapses from three different animals were analyzed. Different samples, layers and/or animals were aggregated and compared using RSA replicated spatial point processes. The results showed no significant differences in the synaptic distribution across the different rats used in the study. We found that RSA processes described the spatial distribution of synapses in all samples of each layer. We also found that the synaptic distribution in layers II to VI conforms to a common underlying RSA process with different densities per layer. Interestingly, the results showed that synapses in layer I had a slightly different spatial distribution from the other layers.

Mosquito-producing containers, spatial distribution, and relationship between Aedes aegypti population indices on the southern boundary of its distribution in South America (Salto, Uruguay).

PubMed

Basso, César; Caffera, Ruben M; García da Rosa, Elsa; Lairihoy, Rosario; González, Cristina; Norbis, Walter; Roche, Ingrid

2012-12-01

A study was conducted in the city of Salto, Uruguay, to identify mosquito-producing containers, the spatial distribution of mosquitoes and the relationship between the different population indices of Aedes aegypti. On each of 312 premises visited, water-filled containers and immature Ae. aegypti mosquitoes were identified. The containers were counted and classified into six categories. Pupae per person and Stegomyia indices were calculated. Pupae per person were represented spatially. The number of each type of container and number of mosquitoes in each were analyzed and compared, and their spatial distribution was analyzed. No significant differences in the number of the different types of containers with mosquitoes or in the number of mosquitoes in each were found. The distribution of the containers with mosquito was random and the distribution of mosquitoes by type of container was aggregated or highly aggregated.

Mosquito-Producing Containers, Spatial Distribution, and Relationship between Aedes aegypti Population Indices on the Southern Boundary of its Distribution in South America (Salto, Uruguay)

PubMed Central

Basso, César; Caffera, Ruben M.; García da Rosa, Elsa; Lairihoy, Rosario; González, Cristina; Norbis, Walter; Roche, Ingrid

2012-01-01

A study was conducted in the city of Salto, Uruguay, to identify mosquito-producing containers, the spatial distribution of mosquitoes and the relationship between the different population indices of Aedes aegypti. On each of 312 premises visited, water-filled containers and immature Ae. aegypti mosquitoes were identified. The containers were counted and classified into six categories. Pupae per person and Stegomyia indices were calculated. Pupae per person were represented spatially. The number of each type of container and number of mosquitoes in each were analyzed and compared, and their spatial distribution was analyzed. No significant differences in the number of the different types of containers with mosquitoes or in the number of mosquitoes in each were found. The distribution of the containers with mosquito was random and the distribution of mosquitoes by type of container was aggregated or highly aggregated. PMID:23128295

Parallelization of a spatial random field characterization process using the Method of Anchored Distributions and the HTCondor high throughput computing system

NASA Astrophysics Data System (ADS)

Osorio-Murillo, C. A.; Over, M. W.; Frystacky, H.; Ames, D. P.; Rubin, Y.

2013-12-01

A new software application called MAD# has been coupled with the HTCondor high throughput computing system to aid scientists and educators with the characterization of spatial random fields and enable understanding the spatial distribution of parameters used in hydrogeologic and related modeling. MAD# is an open source desktop software application used to characterize spatial random fields using direct and indirect information through Bayesian inverse modeling technique called the Method of Anchored Distributions (MAD). MAD relates indirect information with a target spatial random field via a forward simulation model. MAD# executes inverse process running the forward model multiple times to transfer information from indirect information to the target variable. MAD# uses two parallelization profiles according to computational resources available: one computer with multiple cores and multiple computers - multiple cores through HTCondor. HTCondor is a system that manages a cluster of desktop computers for submits serial or parallel jobs using scheduling policies, resources monitoring, job queuing mechanism. This poster will show how MAD# reduces the time execution of the characterization of random fields using these two parallel approaches in different case studies. A test of the approach was conducted using 1D problem with 400 cells to characterize saturated conductivity, residual water content, and shape parameters of the Mualem-van Genuchten model in four materials via the HYDRUS model. The number of simulations evaluated in the inversion was 10 million. Using the one computer approach (eight cores) were evaluated 100,000 simulations in 12 hours (10 million - 1200 hours approximately). In the evaluation on HTCondor, 32 desktop computers (132 cores) were used, with a processing time of 60 hours non-continuous in five days. HTCondor reduced the processing time for uncertainty characterization by a factor of 20 (1200 hours reduced to 60 hours.)

Spectral statistics of random geometric graphs

NASA Astrophysics Data System (ADS)

Dettmann, C. P.; Georgiou, O.; Knight, G.

2017-04-01

We use random matrix theory to study the spectrum of random geometric graphs, a fundamental model of spatial networks. Considering ensembles of random geometric graphs we look at short-range correlations in the level spacings of the spectrum via the nearest-neighbour and next-nearest-neighbour spacing distribution and long-range correlations via the spectral rigidity Δ3 statistic. These correlations in the level spacings give information about localisation of eigenvectors, level of community structure and the level of randomness within the networks. We find a parameter-dependent transition between Poisson and Gaussian orthogonal ensemble statistics. That is the spectral statistics of spatial random geometric graphs fits the universality of random matrix theory found in other models such as Erdős-Rényi, Barabási-Albert and Watts-Strogatz random graphs.

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.

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.

The coalescent process in models with selection and recombination.

PubMed

Hudson, R R; Kaplan, N L

1988-11-01

The statistical properties of the process describing the genealogical history of a random sample of genes at a selectively neutral locus which is linked to a locus at which natural selection operates are investigated. It is found that the equations describing this process are simple modifications of the equations describing the process assuming that the two loci are completely linked. Thus, the statistical properties of the genealogical process for a random sample at a neutral locus linked to a locus with selection follow from the results obtained for the selected locus. Sequence data from the alcohol dehydrogenase (Adh) region of Drosophila melanogaster are examined and compared to predictions based on the theory. It is found that the spatial distribution of nucleotide differences between Fast and Slow alleles of Adh is very similar to the spatial distribution predicted if balancing selection operates to maintain the allozyme variation at the Adh locus. The spatial distribution of nucleotide differences between different Slow alleles of Adh do not match the predictions of this simple model very well.

Geologic map of the Agnesi quadrangle (V-45), Venus

USGS Publications Warehouse

Hansen, Vicki L.; Tharalson, Erik R.

2014-01-01

Two general classes of hypotheses have emerged to address the near random spatial distribution of ~970 apparently pristine impact craters across the surface of Venus: (1) catastrophic/episodic resurfacing and (2) equilibrium/evolutionary resurfacing. Catastrophic/episodic hypotheses propose that a global-scale, temporally punctuated event or events dominated Venus’ evolution and that the generally uniform impact crater distribution (Schaber and others, 1992; Phillips and others, 1992; Herrick and others, 1997) reflects craters that accumulated during relative global quiescence since that event (for example, Strom and others, 1994; Herrick, 1994; Turcotte and others, 1999). Equilibrium/evolutionary hypotheses suggest instead that the near random crater distribution results from relatively continuous, but spatially localized, resurfacing in which volcanic and (or) tectonic processes occur across the planet through time, although the style of operative processes may have varied temporally and spatially (for example, Phillips and others, 1992; Guest and Stofan, 1999; Hansen and Young, 2007). Geologic relations within the map area allow us to test the catastrophic/episodic versus equilibrium/evolutionary resurfacing hypotheses.

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

Spatial distribution of impact craters on Deimos

NASA Astrophysics Data System (ADS)

Hirata, Naoyuki

2017-05-01

Deimos, one of the Martian moons, has numerous impact craters. However, it is unclear whether crater saturation has been reached on this satellite. To address this issue, we apply a statistical test known as nearest-neighbor analysis to analyze the crater distribution of Deimos. When a planetary surface such as the Moon is saturated with impact craters, the spatial distribution of craters is generally changed from random to more ordered. We measured impact craters on Deimos from Viking and HiRISE images and found (1) that the power law of the size-frequency distribution of the craters is approximately -1.7, which is significantly shallower than those of potential impactors, and (2) that the spatial distribution of craters over 30 m in diameter cannot be statistically distinguished from completely random distribution, which indicates that the surface of Deimos is inconsistent with a surface saturated with impact craters. Although a crater size-frequency distribution curve with a slope of -2 is generally interpreted as indicating saturation equilibrium, it is here proposed that two competing mechanisms, seismic shaking and ejecta emplacement, have played a major role in erasing craters on Deimos and are therefore responsible for the shallow slope of this curve. The observed crater density may have reached steady state owing to the obliterations induced by the two competing mechanisms. Such an occurrence indicates that the surface is saturated with impact craters despite the random distribution of craters on Deimos. Therefore, this work proposes that the age determined by the current craters on Deimos reflects neither the age of Deimos itself nor that of the formation of the large concavity centered at its south pole because craters should be removed by later impacts. However, a few of the largest craters on Deimos may be indicative of the age of the south pole event.

Channel doping concentration and cell program state dependence on random telegraph noise spatial and statistical distribution in 30 nm NAND flash memory

NASA Astrophysics Data System (ADS)

Tomita, Toshihiro; Miyaji, Kousuke

2015-04-01

The dependence of spatial and statistical distribution of random telegraph noise (RTN) in a 30 nm NAND flash memory on channel doping concentration NA and cell program state Vth is comprehensively investigated using three-dimensional Monte Carlo device simulation considering random dopant fluctuation (RDF). It is found that single trap RTN amplitude ΔVth is larger at the center of the channel region in the NAND flash memory, which is closer to the jellium (uniform) doping results since NA is relatively low to suppress junction leakage current. In addition, ΔVth peak at the center of the channel decreases in the higher Vth state due to the current concentration at the shallow trench isolation (STI) edges induced by the high vertical electrical field through the fringing capacitance between the channel and control gate. In such cases, ΔVth distribution slope λ cannot be determined by only considering RDF and single trap.

[Prevalence and spatial distribution of trachoma among schoolchildren in Botucatu, São Paulo - Brazil].

PubMed

Schellini, Silvana Artioli; Lavezzo, Marcelo Mendes; Ferraz, Lucieni Barbarini; Olbrich Neto, Jaime; Medina, Norma Hellen; Padovani, Carlos Roberto

2010-01-01

To assess the prevalence of trachoma in schoolchildren of Botucatu/ SP-Brazil and its spatial distribution. Cross-sectional study in children aged from 7 to 14 years, who attended elementary schools in Botucatu/SP in November/2005. The sample size was estimated in 2,092 children, considering the 11.2% historic prevalence of trachoma, accepting an estimation error of 10% and confidence level of 95%. The sample was random, weighted and increased by 20%, because of the possible occurrence of losses. The total number of children examined was 2,692. The diagnosis was clinical, based on WHO guidelines. For the evaluation of spatial data, the CartaLinx program (v1.2) was used, and the school demand sectors digitized according to the planning divisions of the Department of Education. The data were statistically analyzed, and the analysis of the spatial structure of events calculated using the Geode program. The prevalence of trachoma in schoolchildren of Botucatu was 2.9% and there were cases of follicular trachoma. The exploratory spatial analysis failed to reject the null hypothesis of randomness (R= -0.45, p>0.05), with no significant demand sectors. The analysis for the Thiessen polygons also showed that the overall pattern was random (I= -0.07, p=0.49). However, local indicators pointed to a group of low-low type for a polygon to the north of the urban area. The prevalence of trachoma in schoolchildren in Botucatu was 2.9%. The analysis of the spatial distribution did not reveal areas of greater clustering of cases. Although the overall pattern of the disease does not reproduce the socio-economic conditions of the population, the lower prevalence of trachoma was found in areas of lower social vulnerability.

Delineating Facies Spatial Distribution by Integrating Ensemble Data Assimilation and Indicator Geostatistics with Level Set Transformation.

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

Hammond, Glenn Edward; Song, Xuehang; Ye, Ming

A new approach is developed to delineate the spatial distribution of discrete facies (geological units that have unique distributions of hydraulic, physical, and/or chemical properties) conditioned not only on direct data (measurements directly related to facies properties, e.g., grain size distribution obtained from borehole samples) but also on indirect data (observations indirectly related to facies distribution, e.g., hydraulic head and tracer concentration). Our method integrates for the first time ensemble data assimilation with traditional transition probability-based geostatistics. The concept of level set is introduced to build shape parameterization that allows transformation between discrete facies indicators and continuous random variables. Themore » spatial structure of different facies is simulated by indicator models using conditioning points selected adaptively during the iterative process of data assimilation. To evaluate the new method, a two-dimensional semi-synthetic example is designed to estimate the spatial distribution and permeability of two distinct facies from transient head data induced by pumping tests. The example demonstrates that our new method adequately captures the spatial pattern of facies distribution by imposing spatial continuity through conditioning points. The new method also reproduces the overall response in hydraulic head field with better accuracy compared to data assimilation with no constraints on spatial continuity on facies.« less

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.

Linking movement and oviposition behaviour to spatial population distribution in the tree hole mosquito Ochlerotatus triseriatus.

PubMed

Ellis, Alicia M

2008-01-01

1. Researchers often use the spatial distribution of insect offspring as a measure of adult oviposition preferences, and then make conclusions about the consequences of these preferences for population growth and the relationship between life-history traits (e.g. oviposition preference and offspring performance). However, several processes other than oviposition preference can generate spatial patterns of offspring density (e.g. dispersal limitations, spatially heterogeneous mortality rates). Incorrectly assuming that offspring distributions reflect oviposition preferences may therefore compromise our ability to understand the mechanisms determining population distributions and the relationship between life-history traits. 2. The purpose of this study was to perform an empirical study at the whole-system scale to examine the movement and oviposition behaviours of the eastern tree hole mosquito Ochlerotatus triseriatus (Say) and test the importance of these behaviours in determining population distribution relative to other mechanisms. 3. A mark-release-recapture experiment was performed to distinguish among the following alternative hypotheses that may explain a previously observed aggregated distribution of tree hole mosquito offspring: (H(1)) mosquitoes prefer habitats with particular vegetation characteristics and these preferences determine the distribution of their offspring; (H(2)) mosquitoes distribute their eggs randomly or evenly throughout their environment, but spatial differences in developmental success generate an aggregated pattern of larval density; (H(3)) mosquitoes randomly colonize habitats, but have limited dispersal capability causing them to distribute offspring where founder populations were established; (H(4)) wind or other environmental factors may lead to passive aggregation, or spatial heterogeneity in adult mortality (H(5)), rather than dispersal, generates clumped offspring distributions. 4. Results indicate that the distribution of tree hole mosquito larvae is determined in part by adult habitat selection (H(1)), but do not exclude additional effects from passive aggregation (H(4)), or spatial patterns in adult mortality (H(5)). 5. This research illustrates the importance of studying oviposition behaviour at the population scale to better evaluate its relative importance in determining population distribution and dynamics. Moreover, this study demonstrates the importance of linking behavioural and population dynamics for understanding evolutionary relationships among life-history traits (e.g. preference and offspring performance) and predicting when behaviour will be important in determining population phenomena.

Spatial distribution of random velocity inhomogeneities in the western part of Nankai subduction zone

NASA Astrophysics Data System (ADS)

Takahashi, T.; Obana, K.; Yamamoto, Y.; Nakanishi, A.; Kodaira, S.; Kaneda, Y.

2011-12-01

In the Nankai trough, there are three seismogenic zones of megathrust earthquakes (Tokai, Tonankai and Nankai earthquakes). Lithospheric structures in and around these seismogenic zones are important for the studies on mutual interactions and synchronization of their fault ruptures. Recent studies on seismic wave scattering at high frequencies (>1Hz) make it possible to estimate 3D distributions of random inhomogeneities (or scattering coefficient) in the lithosphere, and clarified that random inhomogeneity is one of the important medium properties related to microseismicity and damaged structure near the fault zone [Asano & Hasegawa, 2004; Takahashi et al. 2009]. This study estimates the spatial distribution of the power spectral density function (PSDF) of random inhomogeneities the western part of Nankai subduction zone, and examines the relations with crustal velocity structure and seismic activity. Seismic waveform data used in this study are those recorded at seismic stations of Hi-net & F-net operated by NIED, and 160 ocean bottom seismographs (OBSs) deployed at Hyuga-nada region from Dec. 2008 to Jan. 2009. This OBS observation was conducted by JAMSTEC as a part of "Research concerning Interaction Between the Tokai, Tonankai and Nankai Earthquakes" funded by Ministry of Education, Culture, Sports, Science and Technology, Japan. Spatial distribution of random inhomogeneities is estimated by the inversion analysis of the peak delay time of small earthquakes [Takahashi et al. 2009], where the peak delay time is defined as the time lag from the S-wave onset to its maximal amplitude arrival. We assumed the von Karman type functional form for the PSDF. Peak delay times are measured from root mean squared envelopes at 4-8Hz, 8-16Hz and 16-32Hz. Inversion result can be summarized as follows. Random inhomogeneities beneath the Quaternary volcanoes are characterized by strong inhomogeneities at small spatial scale (~ a few hundreds meter) and weak spectral gradient. Those in the Hyuga-nada region are characterized by the strong inhomogeneities at large spatial wavelength and steep spectral gradient. Random inhomogeneities in the Hyuga-nada region are similar with those in the frontal arc high in northern Izu-Bonin arc, which is thought to be a remnant arc that is presently inactive [Takahashi et al. 2011]. This coincidence implies the existence of subducted Kyushu-Palau ridge in this anomaly of random inhomogeneities, which is also suggested by the seismic refraction survey in this region [Nakanishi et al. 2010 AGU Fall Mtg.]. Source rupture areas of large earthquakes (M>6) in Hyuga-nada regions tend to locate around this anomaly of inhomogeneities. We may say that this anomalously inhomogeneous region is a structural factor affecting the seismic activity in Hyuga-nada region.

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.

Identification of Volcanic Landforms and Processes on Earth and Mars using Geospatial Analysis (Invited)

NASA Astrophysics Data System (ADS)

Fagents, S. A.; Hamilton, C. W.

2009-12-01

Nearest neighbor (NN) analysis enables the identification of landforms using non-morphological parameters and can be useful for constraining the geological processes contributing to observed patterns of spatial distribution. Explosive interactions between lava and water can generate volcanic rootless cone (VRC) groups that are well suited to geospatial analyses because they consist of a large number of landforms that share a common formation mechanism. We have applied NN analysis tools to quantitatively compare the spatial distribution of VRCs in the Laki lava flow in Iceland to analogous landforms in the Tartarus Colles Region of eastern Elysium Planitia, Mars. Our results show that rootless eruption sites on both Earth and Mars exhibit systematic variations in spatial organization that are related to variations in the distribution of resources (lava and water) at different scales. Field observations in Iceland reveal that VRC groups are composite structures formed by the emplacement of chronologically and spatially distinct domains. Regionally, rootless cones cluster into groups and domains, but within domains NN distances exhibit random to repelled distributions. This suggests that on regional scales VRCs cluster in locations that contain sufficient resources, whereas on local scales rootless eruption sites tend to self-organize into distributions that maximize the utilization of limited resources (typically groundwater). Within the Laki lava flow, near-surface water is abundant and pre-eruption topography appears to exert the greatest control on both lava inundation regions and clustering of rootless eruption sites. In contrast, lava thickness appears to be the controlling factor in the formation of rootless eruption sites in the Tartarus Colles Region. A critical lava thickness may be required to initiate rootless eruptions on Mars because the lava flows must contain sufficient heat for transferred thermal energy to reach the underlying cryosphere and volatilize buried ground ice. In both environments, the spatial distribution of rootless eruption sites on local scales may either be random, which indicates that rootless eruption sites form independently of one another, or repelled, which implies resource limitation. Where competition for limited groundwater causes rootless eruption sites to develop greater than random NN separation, rootless eruption sites can be modeled as a system of pumping wells that extract water from a shared aquifer, thereby generating repelled distributions due to non-initiation or early cessation of rootless explosive activity at sites with insufficient access to groundwater. Thus statistical NN analyses can be combined with field observations and remote sensing to obtain information about self-organization processes within geological systems and the effects of environmental resource limitation on the spatial distribution of volcanic landforms. NN analyses may also be used to quantitatively compare the spatial distribution of landforms in different planetary environments and for supplying non-morphological evidence to discriminate between feature identities and geological formation mechanisms.

Quantifying Rock Weakening Due to Decreasing Calcite Mineral Content by Numerical Simulations

PubMed Central

2018-01-01

The quantification of changes in geomechanical properties due to chemical reactions is of paramount importance for geological subsurface utilisation, since mineral dissolution generally reduces rock stiffness. In the present study, the effective elastic moduli of two digital rock samples, the Fontainebleau and Bentheim sandstones, are numerically determined based on micro-CT images. Reduction in rock stiffness due to the dissolution of 10% calcite cement by volume out of the pore network is quantified for three synthetic spatial calcite distributions (coating, partial filling and random) using representative sub-cubes derived from the digital rock samples. Due to the reduced calcite content, bulk and shear moduli decrease by 34% and 38% in maximum, respectively. Total porosity is clearly the dominant parameter, while spatial calcite distribution has a minor impact, except for a randomly chosen cement distribution within the pore network. Moreover, applying an initial stiffness reduced by 47% for the calcite cement results only in a slightly weaker mechanical behaviour. Using the quantitative approach introduced here substantially improves the accuracy of predictions in elastic rock properties compared to general analytical methods, and further enables quantification of uncertainties related to spatial variations in porosity and mineral distribution. PMID:29614776

Quantifying Rock Weakening Due to Decreasing Calcite Mineral Content by Numerical Simulations.

PubMed

Wetzel, Maria; Kempka, Thomas; Kühn, Michael

2018-04-01

The quantification of changes in geomechanical properties due to chemical reactions is of paramount importance for geological subsurface utilisation, since mineral dissolution generally reduces rock stiffness. In the present study, the effective elastic moduli of two digital rock samples, the Fontainebleau and Bentheim sandstones, are numerically determined based on micro-CT images. Reduction in rock stiffness due to the dissolution of 10% calcite cement by volume out of the pore network is quantified for three synthetic spatial calcite distributions (coating, partial filling and random) using representative sub-cubes derived from the digital rock samples. Due to the reduced calcite content, bulk and shear moduli decrease by 34% and 38% in maximum, respectively. Total porosity is clearly the dominant parameter, while spatial calcite distribution has a minor impact, except for a randomly chosen cement distribution within the pore network. Moreover, applying an initial stiffness reduced by 47% for the calcite cement results only in a slightly weaker mechanical behaviour. Using the quantitative approach introduced here substantially improves the accuracy of predictions in elastic rock properties compared to general analytical methods, and further enables quantification of uncertainties related to spatial variations in porosity and mineral distribution.

Declines in moose population density at Isle Royle National Park, MI, USA and accompanied changes in landscape patterns

USGS Publications Warehouse

De Jager, N. R.; Pastor, J.

2009-01-01

Ungulate herbivores create patterns of forage availability, plant species composition, and soil fertility as they range across large landscapes and consume large quantities of plant material. Over time, herbivore populations fluctuate, producing great potential for spatio-temporal landscape dynamics. In this study, we extend the spatial and temporal extent of a long-term investigation of the relationship of landscape patterns to moose foraging behavior at Isle Royale National Park, MI. We examined how patterns of browse availability and consumption, plant basal area, and soil fertility changed during a recent decline in the moose population. We used geostatistics to examine changes in the nature of spatial patterns in two valleys over 18 years and across short-range and long-range distance scales. Landscape patterns of available and consumed browse changed from either repeated patches or randomly distributed patches in 1988-1992 to random point distributions by 2007 after a recent record high peak followed by a rapid decline in the moose population. Patterns of available and consumed browse became decoupled during the moose population low, which is in contrast to coupled patterns during the earlier high moose population. Distributions of plant basal area and soil nitrogen availability also switched from repeated patches to randomly distributed patches in one valley and to random point distributions in the other valley. Rapid declines in moose population density may release vegetation and soil fertility from browsing pressure and in turn create random landscape patterns. ?? Springer Science+Business Media B.V. 2009.

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

NASA Astrophysics Data System (ADS)

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

2017-09-01

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

Random field assessment of nanoscopic inhomogeneity of bone.

PubMed

Dong, X Neil; Luo, Qing; Sparkman, Daniel M; Millwater, Harry R; Wang, Xiaodu

2010-12-01

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 represent 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. Copyright © 2010 Elsevier Inc. All rights reserved.

Automated feature extraction and spatial organization of seafloor pockmarks, Belfast Bay, Maine, USA

USGS Publications Warehouse

Andrews, Brian D.; Brothers, Laura L.; Barnhardt, Walter A.

2010-01-01

Seafloor pockmarks occur worldwide and may represent millions of m3 of continental shelf erosion, but few numerical analyses of their morphology and spatial distribution of pockmarks exist. We introduce a quantitative definition of pockmark morphology and, based on this definition, propose a three-step geomorphometric method to identify and extract pockmarks from high-resolution swath bathymetry. We apply this GIS-implemented approach to 25 km2 of bathymetry collected in the Belfast Bay, Maine USA pockmark field. Our model extracted 1767 pockmarks and found a linear pockmark depth-to-diameter ratio for pockmarks field-wide. Mean pockmark depth is 7.6 m and mean diameter is 84.8 m. Pockmark distribution is non-random, and nearly half of the field's pockmarks occur in chains. The most prominent chains are oriented semi-normal to the steepest gradient in Holocene sediment thickness. A descriptive model yields field-wide spatial statistics indicating that pockmarks are distributed in non-random clusters. Results enable quantitative comparison of pockmarks in fields worldwide as well as similar concave features, such as impact craters, dolines, or salt pools.

Spatial distribution, temporal variation and specificity of microhabitat of Tropisternus species (Coleoptera: Hydrophilidae) in permanent ponds.

PubMed

Gómez Lutz, M C; Kehr, A I; Fernández, L A

2015-06-01

The spatial distribution and temporal variation of 11 species of Tropisternus were analyzed in two permanent ponds located in the province of Corrientes, Argentina. Samples were collected every 15 days, between October 2010 and March 2011. The species recorded were Tropisternus collaris (Fabricius), Tropisternus ovalis Castelnau, Tropisternus laevis (Sturm), Tropisternus lateralis limbatus (Brullé), Tropisternus longispina Fernández & Bachmann, Tropisternus carinispina Orchymont, Tropisternus bourmeisteri Fernández & Bachmann, Tropisternus apicipalpis (Chevrolat), Tropisternus dilatatus Bruch, Tropisternus obesus Bruch, and Tropisternus ignoratus Knisch. The first four were present in higher proportions than the remaining during most of the study period. The spatial distribution of individuals was mostly related to the homogeneity or heterogeneity of the ecosystem in relation to microhabitats with aquatic vegetation: In ponds with different microhabitats, individuals were mainly aggregated, whereas in ponds with homogenous features, individuals were randomly distributed. However, when species were analyzed individually, the spatial distribution and the use of microhabitat by each species were different with respect to preference and behavior.

Determination of the Spatial Distribution in Hydraulic Conductivity Using Genetic Algorithm Optimization

NASA Astrophysics Data System (ADS)

Aksoy, A.; Lee, J. H.; Kitanidis, P. K.

2016-12-01

Heterogeneity in hydraulic conductivity (K) impacts the transport and fate of contaminants in subsurface as well as design and operation of managed aquifer recharge (MAR) systems. Recently, improvements in computational resources and availability of big data through electrical resistivity tomography (ERT) and remote sensing have provided opportunities to better characterize the subsurface. Yet, there is need to improve prediction and evaluation methods in order to obtain information from field measurements for better field characterization. In this study, genetic algorithm optimization, which has been widely used in optimal aquifer remediation designs, was used to determine the spatial distribution of K. A hypothetical 2 km by 2 km aquifer was considered. A genetic algorithm library, PGAPack, was linked with a fast Fourier transform based random field generator as well as a groundwater flow and contaminant transport simulation model (BIO2D-KE). The objective of the optimization model was to minimize the total squared error between measured and predicted field values. It was assumed measured K values were available through ERT. Performance of genetic algorithm in predicting the distribution of K was tested for different cases. In the first one, it was assumed that observed K values were evaluated using the random field generator only as the forward model. In the second case, as well as K-values obtained through ERT, measured head values were incorporated into evaluation in which BIO2D-KE and random field generator were used as the forward models. Lastly, tracer concentrations were used as additional information in the optimization model. Initial results indicated enhanced performance when random field generator and BIO2D-KE are used in combination in predicting the spatial distribution in K.

Distribution of randomly diffusing particles in inhomogeneous media

NASA Astrophysics Data System (ADS)

Li, Yiwei; Kahraman, Osman; Haselwandter, Christoph A.

2017-09-01

Diffusion can be conceptualized, at microscopic scales, as the random hopping of particles between neighboring lattice sites. In the case of diffusion in inhomogeneous media, distinct spatial domains in the system may yield distinct particle hopping rates. Starting from the master equations (MEs) governing diffusion in inhomogeneous media we derive here, for arbitrary spatial dimensions, the deterministic lattice equations (DLEs) specifying the average particle number at each lattice site for randomly diffusing particles in inhomogeneous media. We consider the case of free (Fickian) diffusion with no steric constraints on the maximum particle number per lattice site as well as the case of diffusion under steric constraints imposing a maximum particle concentration. We find, for both transient and asymptotic regimes, excellent agreement between the DLEs and kinetic Monte Carlo simulations of the MEs. The DLEs provide a computationally efficient method for predicting the (average) distribution of randomly diffusing particles in inhomogeneous media, with the number of DLEs associated with a given system being independent of the number of particles in the system. From the DLEs we obtain general analytic expressions for the steady-state particle distributions for free diffusion and, in special cases, diffusion under steric constraints in inhomogeneous media. We find that, in the steady state of the system, the average fraction of particles in a given domain is independent of most system properties, such as the arrangement and shape of domains, and only depends on the number of lattice sites in each domain, the particle hopping rates, the number of distinct particle species in the system, and the total number of particles of each particle species in the system. Our results provide general insights into the role of spatially inhomogeneous particle hopping rates in setting the particle distributions in inhomogeneous media.

Spatial effects in discrete generation population models.

PubMed

Carrillo, C; Fife, P

2005-02-01

A framework is developed for constructing a large class of discrete generation, continuous space models of evolving single species populations and finding their bifurcating patterned spatial distributions. Our models involve, in separate stages, the spatial redistribution (through movement laws) and local regulation of the population; and the fundamental properties of these events in a homogeneous environment are found. Emphasis is placed on the interaction of migrating individuals with the existing population through conspecific attraction (or repulsion), as well as on random dispersion. The nature of the competition of these two effects in a linearized scenario is clarified. The bifurcation of stationary spatially patterned population distributions is studied, with special attention given to the role played by that competition.

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.

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.

A simplified analytical random walk model for proton dose calculation

NASA Astrophysics Data System (ADS)

Yao, Weiguang; Merchant, Thomas E.; Farr, Jonathan B.

2016-10-01

We propose an analytical random walk model for proton dose calculation in a laterally homogeneous medium. A formula for the spatial fluence distribution of primary protons is derived. The variance of the spatial distribution is in the form of a distance-squared law of the angular distribution. To improve the accuracy of dose calculation in the Bragg peak region, the energy spectrum of the protons is used. The accuracy is validated against Monte Carlo simulation in water phantoms with either air gaps or a slab of bone inserted. The algorithm accurately reflects the dose dependence on the depth of the bone and can deal with small-field dosimetry. We further applied the algorithm to patients’ cases in the highly heterogeneous head and pelvis sites and used a gamma test to show the reasonable accuracy of the algorithm in these sites. Our algorithm is fast for clinical use.

Spatiotemporal dynamics of the Southern California Asian citrus psyllid (Diaphorina citri) invasion.

PubMed

Bayles, Brett R; Thomas, Shyam M; Simmons, Gregory S; Grafton-Cardwell, Elizabeth E; Daugherty, Mathew P

2017-01-01

Biological invasions are governed by spatial processes that tend to be distributed in non-random ways across landscapes. Characterizing the spatial and temporal heterogeneities of the introduction, establishment, and spread of non-native insect species is a key aspect of effectively managing their geographic expansion. The Asian citrus psyllid (Diaphorina citri), a vector of the bacterium associated with huanglongbing (HLB), poses a serious threat to commercial and residential citrus trees. In 2008, D. citri first began expanding northward from Mexico into parts of Southern California. Using georeferenced D. citri occurrence data from 2008-2014, we sought to better understand the extent of the geographic expansion of this invasive vector species. Our objectives were to: 1) describe the spatial and temporal distribution of D. citri in Southern California, 2) identify the locations of statistically significant D. citri hotspots, and 3) quantify the dynamics of anisotropic spread. We found clear evidence that the spatial and temporal distribution of D. citri in Southern California is non-random. Further, we identified the existence of statistically significant hotspots of D. citri occurrence and described the anisotropic dispersion across the Southern California landscape. For example, the dominant hotspot surrounding Los Angeles showed rapid and strongly asymmetric spread to the south and east. Our study demonstrates the feasibility of quantitative invasive insect risk assessment with the application of a spatial epidemiology framework.

Spatiotemporal dynamics of the Southern California Asian citrus psyllid (Diaphorina citri) invasion

PubMed Central

Thomas, Shyam M.; Simmons, Gregory S.; Grafton-Cardwell, Elizabeth E.; Daugherty, Mathew P.

2017-01-01

Biological invasions are governed by spatial processes that tend to be distributed in non-random ways across landscapes. Characterizing the spatial and temporal heterogeneities of the introduction, establishment, and spread of non-native insect species is a key aspect of effectively managing their geographic expansion. The Asian citrus psyllid (Diaphorina citri), a vector of the bacterium associated with huanglongbing (HLB), poses a serious threat to commercial and residential citrus trees. In 2008, D. citri first began expanding northward from Mexico into parts of Southern California. Using georeferenced D. citri occurrence data from 2008–2014, we sought to better understand the extent of the geographic expansion of this invasive vector species. Our objectives were to: 1) describe the spatial and temporal distribution of D. citri in Southern California, 2) identify the locations of statistically significant D. citri hotspots, and 3) quantify the dynamics of anisotropic spread. We found clear evidence that the spatial and temporal distribution of D. citri in Southern California is non-random. Further, we identified the existence of statistically significant hotspots of D. citri occurrence and described the anisotropic dispersion across the Southern California landscape. For example, the dominant hotspot surrounding Los Angeles showed rapid and strongly asymmetric spread to the south and east. Our study demonstrates the feasibility of quantitative invasive insect risk assessment with the application of a spatial epidemiology framework. PMID:28278188

Fine-scale spatial distribution of the common lugworm Arenicola marina, and effects of intertidal clam fishing

NASA Astrophysics Data System (ADS)

Boldina, Inna; Beninger, Peter G.

2014-04-01

Despite its ubiquity and its role as an ecosystem engineer on temperate intertidal mudflats, little is known of the spatial ecology of the lugworm Arenicola marina. We estimated lugworm densities and analyzed the spatial distribution of A. marina on a French Atlantic mudflat subjected to long-term clam digging activities, and compared these to a nearby pristine reference mudflat, using a combination of geostatistical techniques: point-pattern analysis, autocorrelation, and wavelet analysis. Lugworm densities were an order of magnitude greater at the reference site. Although A. marina showed an aggregative spatial distribution at both sites, the characteristics and intensity of aggregation differed markedly between sites. The reference site showed an inhibition process (regular distribution) at distances <7.5 cm, whereas the impacted site showed a random distribution at this scale. At distances from 15 cm to several tens of meters, the spatial distribution of A. marina was clearly aggregated at both sites; however, the autocorrelation strength was much weaker at the impacted site. In addition, the non-impacted site presented multi-scale spatial distribution, which was not evident at the impacted site. The differences observed between the spatial distributions of the fishing-impacted vs. the non-impacted site reflect similar findings for other components of these two mudflat ecosystems, suggesting common community-level responses to prolonged mechanical perturbation: a decrease in naturally-occurring aggregation. This change may have consequences for basic biological characteristics such as reproduction, recruitment, growth, and feeding.

[Spatial patterns of dominant tree species in sub-alpine Betula-Abies forest in West Sichuan of China].

PubMed

Miao, Ning; Liu, Shi-Rong; Shi, Zuo-Min; Yu, Hong; Liu, Xing-Liang

2009-06-01

Based on the investigation in a 4 hm2 Betula-Abies forest plot in sub-alpine area in West Sichuan of China, and by using point pattern analysis method in terms of O-ring statistics, the spatial patterns of dominant species Betula albo-sinensis and Abies faxoniana in different age classes in study area were analyzed, and the intra- and inter-species associations between these age classes were studied. B. albo-sinensis had a unimodal distribution of its DBH frequency, indicating a declining population, while A. faxoniana had a reverse J-shaped pattern, showing an increasing population. All the big trees of B. albo-sinensis and A. faxoniana were spatially in random at all scales, while the medium age and small trees were spatially clumped at small scales and tended to be randomly or evenly distributed with increasing spatial scale. The maximum aggregation degree decreased with increasing age class. Spatial association mainly occurred at small scales. A. faxoniana generally showed positive intra-specific association, while B. albo-sinensis generally showed negative intra-specific association. For the two populations, big and small trees had no significant spatial association, but middle age trees had negative spatial association. Negative inter-specific associations of the two populations were commonly found in different age classes. The larger the difference of age class, the stronger the negative inter-specific association.

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.

Effect of random inhomogeneities in the spatial distribution of radiation-induced defect clusters on carrier transport through the thin base of a heterojunction bipolar transistor upon neutron irradiation

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

Puzanov, A. S.; Obolenskiy, S. V., E-mail: obolensk@rf.unn.ru; Kozlov, V. A.

We analyze the electron transport through the thin base of a GaAs heterojunction bipolar transistor with regard to fluctuations in the spatial distribution of defect clusters induced by irradiation with a fissionspectrum fast neutron flux. We theoretically demonstrate that the homogeneous filling of the working region with radiation-induced defect clusters causes minimum degradation of the dc gain of the heterojunction bipolar transistor.

The causes of spatial patterning of mounds of a fungus-cultivating termite: results from nearest-neighbour analysis and ecological studies.

PubMed

Korb, Judith; Linsenmair, Karl Eduard

2001-05-01

Little is known about processes regulating population dynamics in termites. We investigated the distribution of mound-colonies of the fungus-cultivating termite Macrotermes bellicosus (Smeathman) in two habitats in the Comoé National Park (Côte d'Ivoire) with nearest-neighbour analysis differentiating between different age classes. These results were compared with ecological data on processes influencing population dynamics. High mound densities were recorded in shrub savannah while only a few mounds were found in gallery forest. Mounds were distributed randomly in both habitats when all mounds were considered together, and when inhabited and uninhabited mounds were treated separately. However, distinctive non-random patterns were revealed in the savannah when we distinguished between different age classes. Small, young colonies were aggregated when they coexisted with larger, older colonies, which were more regularly distributed. This indicates that the distribution of older colonies is influenced by intraspecific competition whereas that of younger colonies is influenced by opposing factors that lead to aggregation. This is in accordance with ecological data. Food is a limiting resource for large colonies, while patchily distributed appropriate microclimatic conditions seem to be more important for young colonies. Colonies that had formerly coexisted (i.e. living colonies and recently dead colonies) showed aggregated, random and regular distribution patterns, suggesting several causes of mortality. Colonies that had never had contact with each other were randomly distributed and no specific regulation mechanism was implicated. These results show that different age classes seem to be regulated by different processes and that separation between age classes is necessary to reveal indicative spatial patterns in nearest-neighbour analysis.

Visibility graphs of random scalar fields and spatial data

NASA Astrophysics Data System (ADS)

Lacasa, Lucas; Iacovacci, Jacopo

2017-07-01

We extend the family of visibility algorithms to map scalar fields of arbitrary dimension into graphs, enabling the analysis of spatially extended data structures as networks. We introduce several possible extensions and provide analytical results on the topological properties of the graphs associated to different types of real-valued matrices, which can be understood as the high and low disorder limits of real-valued scalar fields. In particular, we find a closed expression for the degree distribution of these graphs associated to uncorrelated random fields of generic dimension. This result holds independently of the field's marginal distribution and it directly yields a statistical randomness test, applicable in any dimension. We showcase its usefulness by discriminating spatial snapshots of two-dimensional white noise from snapshots of a two-dimensional lattice of diffusively coupled chaotic maps, a system that generates high dimensional spatiotemporal chaos. The range of potential applications of this combinatorial framework includes image processing in engineering, the description of surface growth in material science, soft matter or medicine, and the characterization of potential energy surfaces in chemistry, disordered systems, and high energy physics. An illustration on the applicability of this method for the classification of the different stages involved in carcinogenesis is briefly discussed.

Detecting changes in the spatial distribution of nitrate contamination in ground water

USGS Publications Warehouse

Liu, Z.-J.; Hallberg, G.R.; Zimmerman, D.L.; Libra, R.D.

1997-01-01

Many studies of ground water pollution in general and nitrate contamination in particular have often relied on a one-time investigation, tracking of individual wells, or aggregate summaries. Studies of changes in spatial distribution of contaminants over time are lacking. This paper presents a method to compare spatial distributions for possible changes over time. The large-scale spatial distribution at a given time can be considered as a surface over the area (a trend surface). The changes in spatial distribution from period to period can be revealed by the differences in the shape and/or height of surfaces. If such a surface is described by a polynomial function, changes in surfaces can be detected by testing statistically for differences in their corresponding polynomial functions. This method was applied to nitrate concentration in a population of wells in an agricultural drainage basin in Iowa, sampled in three different years. For the period of 1981-1992, the large-scale spatial distribution of nitrate concentration did not show significant change in the shape of spatial surfaces; while the magnitude of nitrate concentration in the basin, or height of the computed surfaces showed significant fluctuations. The change in magnitude of nitrate concentration is closely related to climatic variations, especially in precipitation. The lack of change in the shape of spatial surfaces means that either the influence of land use/nitrogen management was overshadowed by climatic influence, or the changes in land use/management occurred in a random fashion.

A Random Forest Approach to Predict the Spatial Distribution of Sediment Pollution in an Estuarine System

EPA Science Inventory

Modeling the magnitude and distribution of sediment-bound pollutants in estuaries is often limited by incomplete knowledge of the site and inadequate sample density. To address these modeling limitations, a decision-support tool framework was conceived that predicts sediment cont...

Predicting the Spatial Distribution of Organic Contaminants in an Estuarine System using a Random Forest Approach

EPA Science Inventory

Modeling the magnitude and distribution of estuarine sediment contamination by pollutants of historic (e.g. PCB) and emerging concern (e.g., personal care products, PCP) is often limited by incomplete site knowledge and inadequate sediment contamination sampling. We tested a mode...

Revisiting crash spatial heterogeneity: A Bayesian spatially varying coefficients approach.

PubMed

Xu, Pengpeng; Huang, Helai; Dong, Ni; Wong, S C

2017-01-01

This study was performed to investigate the spatially varying relationships between crash frequency and related risk factors. A Bayesian spatially varying coefficients model was elaborately introduced as a methodological alternative to simultaneously account for the unstructured and spatially structured heterogeneity of the regression coefficients in predicting crash frequencies. The proposed method was appealing in that the parameters were modeled via a conditional autoregressive prior distribution, which involved a single set of random effects and a spatial correlation parameter with extreme values corresponding to pure unstructured or pure spatially correlated random effects. A case study using a three-year crash dataset from the Hillsborough County, Florida, was conducted to illustrate the proposed model. Empirical analysis confirmed the presence of both unstructured and spatially correlated variations in the effects of contributory factors on severe crash occurrences. The findings also suggested that ignoring spatially structured heterogeneity may result in biased parameter estimates and incorrect inferences, while assuming the regression coefficients to be spatially clustered only is probably subject to the issue of over-smoothness. Copyright © 2016 Elsevier Ltd. All rights reserved.

A Complex Network Theory Approach for the Spatial Distribution of Fire Breaks in Heterogeneous Forest Landscapes for the Control of Wildland Fires

PubMed Central

Russo, Lucia; Russo, Paola; Siettos, Constantinos I.

2016-01-01

Based on complex network theory, we propose a computational methodology which addresses the spatial distribution of fuel breaks for the inhibition of the spread of wildland fires on heterogeneous landscapes. This is a two-level approach where the dynamics of fire spread are modeled as a random Markov field process on a directed network whose edge weights are determined by a Cellular Automata model that integrates detailed GIS, landscape and meteorological data. Within this framework, the spatial distribution of fuel breaks is reduced to the problem of finding network nodes (small land patches) which favour fire propagation. Here, this is accomplished by exploiting network centrality statistics. We illustrate the proposed approach through (a) an artificial forest of randomly distributed density of vegetation, and (b) a real-world case concerning the island of Rhodes in Greece whose major part of its forest was burned in 2008. Simulation results show that the proposed methodology outperforms the benchmark/conventional policy of fuel reduction as this can be realized by selective harvesting and/or prescribed burning based on the density and flammability of vegetation. Interestingly, our approach reveals that patches with sparse density of vegetation may act as hubs for the spread of the fire. PMID:27780249

What Is Better Than Coulomb Failure Stress? A Ranking of Scalar Static Stress Triggering Mechanisms from 105 Mainshock-Aftershock Pairs

NASA Astrophysics Data System (ADS)

Meade, Brendan J.; DeVries, Phoebe M. R.; Faller, Jeremy; Viegas, Fernanda; Wattenberg, Martin

2017-11-01

Aftershocks may be triggered by the stresses generated by preceding mainshocks. The temporal frequency and maximum size of aftershocks are well described by the empirical Omori and Bath laws, but spatial patterns are more difficult to forecast. Coulomb failure stress is perhaps the most common criterion invoked to explain spatial distributions of aftershocks. Here we consider the spatial relationship between patterns of aftershocks and a comprehensive list of 38 static elastic scalar metrics of stress (including stress tensor invariants, maximum shear stress, and Coulomb failure stress) from 213 coseismic slip distributions worldwide. The rates of true-positive and false-positive classification of regions with and without aftershocks are assessed with receiver operating characteristic analysis. We infer that the stress metrics that are most consistent with observed aftershock locations are maximum shear stress and the magnitude of the second and third invariants of the stress tensor. These metrics are significantly better than random assignment at a significance level of 0.005 in over 80% of the slip distributions. In contrast, the widely used Coulomb failure stress criterion is distinguishable from random assignment in only 51-64% of the slip distributions. These results suggest that a number of alternative scalar metrics are better predictors of aftershock locations than classic Coulomb failure stress change.

A Complex Network Theory Approach for the Spatial Distribution of Fire Breaks in Heterogeneous Forest Landscapes for the Control of Wildland Fires.

PubMed

Russo, Lucia; Russo, Paola; Siettos, Constantinos I

2016-01-01

Based on complex network theory, we propose a computational methodology which addresses the spatial distribution of fuel breaks for the inhibition of the spread of wildland fires on heterogeneous landscapes. This is a two-level approach where the dynamics of fire spread are modeled as a random Markov field process on a directed network whose edge weights are determined by a Cellular Automata model that integrates detailed GIS, landscape and meteorological data. Within this framework, the spatial distribution of fuel breaks is reduced to the problem of finding network nodes (small land patches) which favour fire propagation. Here, this is accomplished by exploiting network centrality statistics. We illustrate the proposed approach through (a) an artificial forest of randomly distributed density of vegetation, and (b) a real-world case concerning the island of Rhodes in Greece whose major part of its forest was burned in 2008. Simulation results show that the proposed methodology outperforms the benchmark/conventional policy of fuel reduction as this can be realized by selective harvesting and/or prescribed burning based on the density and flammability of vegetation. Interestingly, our approach reveals that patches with sparse density of vegetation may act as hubs for the spread of the fire.

Marine protected areas and the value of spatially optimized fishery management

PubMed Central

Rassweiler, Andrew; Costello, Christopher; Siegel, David A.

2012-01-01

There is a growing focus around the world on marine spatial planning, including spatial fisheries management. Some spatial management approaches are quite blunt, as when marine protected areas (MPAs) are established to restrict fishing in specific locations. Other management tools, such as zoning or spatial user rights, will affect the distribution of fishing effort in a more nuanced manner. Considerable research has focused on the ability of MPAs to increase fishery returns, but the potential for the broader class of spatial management approaches to outperform MPAs has received far less attention. We use bioeconomic models of seven nearshore fisheries in Southern California to explore the value of optimized spatial management in which the distribution of fishing is chosen to maximize profits. We show that fully optimized spatial management can substantially increase fishery profits relative to optimal nonspatial management but that the magnitude of this increase depends on characteristics of the fishing fleet and target species. Strategically placed MPAs can also increase profits substantially compared with nonspatial management, particularly if fishing costs are low, although profit increases available through optimal MPA-based management are roughly half those from fully optimized spatial management. However, if the same total area is protected by randomly placing MPAs, starkly contrasting results emerge: most random MPA designs reduce expected profits. The high value of spatial management estimated here supports continued interest in spatially explicit fisheries regulations but emphasizes that predicted increases in profits can only be achieved if the fishery is well understood and the regulations are strategically designed. PMID:22753469

Marine protected areas and the value of spatially optimized fishery management.

PubMed

Rassweiler, Andrew; Costello, Christopher; Siegel, David A

2012-07-17

There is a growing focus around the world on marine spatial planning, including spatial fisheries management. Some spatial management approaches are quite blunt, as when marine protected areas (MPAs) are established to restrict fishing in specific locations. Other management tools, such as zoning or spatial user rights, will affect the distribution of fishing effort in a more nuanced manner. Considerable research has focused on the ability of MPAs to increase fishery returns, but the potential for the broader class of spatial management approaches to outperform MPAs has received far less attention. We use bioeconomic models of seven nearshore fisheries in Southern California to explore the value of optimized spatial management in which the distribution of fishing is chosen to maximize profits. We show that fully optimized spatial management can substantially increase fishery profits relative to optimal nonspatial management but that the magnitude of this increase depends on characteristics of the fishing fleet and target species. Strategically placed MPAs can also increase profits substantially compared with nonspatial management, particularly if fishing costs are low, although profit increases available through optimal MPA-based management are roughly half those from fully optimized spatial management. However, if the same total area is protected by randomly placing MPAs, starkly contrasting results emerge: most random MPA designs reduce expected profits. The high value of spatial management estimated here supports continued interest in spatially explicit fisheries regulations but emphasizes that predicted increases in profits can only be achieved if the fishery is well understood and the regulations are strategically designed.

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.

[Spatial differentiation and impact factors of Yutian Oasis's soil surface salt based on GWR model].

PubMed

Yuan, Yu Yun; Wahap, Halik; Guan, Jing Yun; Lu, Long Hui; Zhang, Qin Qin

2016-10-01

In this paper, topsoil salinity data gathered from 24 sampling sites in the Yutian Oasis were used, nine different kinds of environmental variables closely related to soil salinity were selec-ted as influencing factors, then, the spatial distribution characteristics of topsoil salinity and spatial heterogeneity of influencing factors were analyzed by combining the spatial autocorrelation with traditional regression analysis and geographically weighted regression model. Results showed that the topsoil salinity in Yutian Oasis was not of random distribution but had strong spatial dependence, and the spatial autocorrelation index for topsoil salinity was 0.479. Groundwater salinity, groundwater depth, elevation and temperature were the main factors influencing topsoil salt accumulation in arid land oases and they were spatially heterogeneous. The nine selected environmental variables except soil pH had significant influences on topsoil salinity with spatial disparity. GWR model was superior to the OLS model on interpretation and estimation of spatial non-stationary data, also had a remarkable advantage in visualization of modeling parameters.

Chemical Continuous Time Random Walks

NASA Astrophysics Data System (ADS)

Aquino, T.; Dentz, M.

2017-12-01

Traditional methods for modeling solute transport through heterogeneous media employ Eulerian schemes to solve for solute concentration. More recently, Lagrangian methods have removed the need for spatial discretization through the use of Monte Carlo implementations of Langevin equations for solute particle motions. While there have been recent advances in modeling chemically reactive transport with recourse to Lagrangian methods, these remain less developed than their Eulerian counterparts, and many open problems such as efficient convergence and reconstruction of the concentration field remain. We explore a different avenue and consider the question: In heterogeneous chemically reactive systems, is it possible to describe the evolution of macroscopic reactant concentrations without explicitly resolving the spatial transport? Traditional Kinetic Monte Carlo methods, such as the Gillespie algorithm, model chemical reactions as random walks in particle number space, without the introduction of spatial coordinates. The inter-reaction times are exponentially distributed under the assumption that the system is well mixed. In real systems, transport limitations lead to incomplete mixing and decreased reaction efficiency. We introduce an arbitrary inter-reaction time distribution, which may account for the impact of incomplete mixing. This process defines an inhomogeneous continuous time random walk in particle number space, from which we derive a generalized chemical Master equation and formulate a generalized Gillespie algorithm. We then determine the modified chemical rate laws for different inter-reaction time distributions. We trace Michaelis-Menten-type kinetics back to finite-mean delay times, and predict time-nonlocal macroscopic reaction kinetics as a consequence of broadly distributed delays. Non-Markovian kinetics exhibit weak ergodicity breaking and show key features of reactions under local non-equilibrium.

Forest fire spatial pattern analysis in Galicia (NW Spain).

PubMed

Fuentes-Santos, I; Marey-Pérez, M F; González-Manteiga, W

2013-10-15

Knowledge of fire behaviour is of key importance in forest management. In the present study, we analysed the spatial structure of forest fire with spatial point pattern analysis and inference techniques recently developed in the Spatstat package of R. Wildfires have been the primary threat to Galician forests in recent years. The district of Fonsagrada-Ancares is one of the most seriously affected by fire in the region and, therefore, the central focus of the study. Our main goal was to determine the spatial distribution of ignition points to model and predict fire occurrence. These data are of great value in establishing enhanced fire prevention and fire fighting plans. We found that the spatial distribution of wildfires is not random and that fire occurrence may depend on ownership conflicts. We also found positive interaction between small and large fires and spatial independence between wildfires in consecutive years. Copyright © 2013 Elsevier Ltd. All rights reserved.

The cosmological principle is not in the sky

NASA Astrophysics Data System (ADS)

Park, Chan-Gyung; Hyun, Hwasu; Noh, Hyerim; Hwang, Jai-chan

2017-08-01

The homogeneity of matter distribution at large scales, known as the cosmological principle, is a central assumption in the standard cosmological model. The case is testable though, thus no longer needs to be a principle. Here we perform a test for spatial homogeneity using the Sloan Digital Sky Survey Luminous Red Galaxies (LRG) sample by counting galaxies within a specified volume with the radius scale varying up to 300 h-1 Mpc. We directly confront the large-scale structure data with the definition of spatial homogeneity by comparing the averages and dispersions of galaxy number counts with allowed ranges of the random distribution with homogeneity. The LRG sample shows significantly larger dispersions of number counts than the random catalogues up to 300 h-1 Mpc scale, and even the average is located far outside the range allowed in the random distribution; the deviations are statistically impossible to be realized in the random distribution. This implies that the cosmological principle does not hold even at such large scales. The same analysis of mock galaxies derived from the N-body simulation, however, suggests that the LRG sample is consistent with the current paradigm of cosmology, thus the simulation is also not homogeneous in that scale. We conclude that the cosmological principle is neither in the observed sky nor demanded to be there by the standard cosmological world model. This reveals the nature of the cosmological principle adopted in the modern cosmology paradigm, and opens a new field of research in theoretical cosmology.

On the Clustering of Europa's Small Craters

NASA Technical Reports Server (NTRS)

Bierhaus, E. B.; Chapman, C. R.; Merline, W. J.

2001-01-01

We analyze the spatial distribution of Europa's small craters and find that many are too tightly clustered to result from random, primary impacts. Additional information is contained in the original extended abstract.

A Dasymetric-Based Monte Carlo Simulation Approach to the Probabilistic Analysis of Spatial Variables

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

Morton, April M; Piburn, Jesse O; McManamay, Ryan A

2017-01-01

Monte Carlo simulation is a popular numerical experimentation technique used in a range of scientific fields to obtain the statistics of unknown random output variables. Despite its widespread applicability, it can be difficult to infer required input probability distributions when they are related to population counts unknown at desired spatial resolutions. To overcome this challenge, we propose a framework that uses a dasymetric model to infer the probability distributions needed for a specific class of Monte Carlo simulations which depend on population counts.

A multivariate spatial mixture model for areal data: examining regional differences in standardized test scores

PubMed Central

Neelon, Brian; Gelfand, Alan E.; Miranda, Marie Lynn

2013-01-01

Summary Researchers in the health and social sciences often wish to examine joint spatial patterns for two or more related outcomes. Examples include infant birth weight and gestational length, psychosocial and behavioral indices, and educational test scores from different cognitive domains. We propose a multivariate spatial mixture model for the joint analysis of continuous individual-level outcomes that are referenced to areal units. The responses are modeled as a finite mixture of multivariate normals, which accommodates a wide range of marginal response distributions and allows investigators to examine covariate effects within subpopulations of interest. The model has a hierarchical structure built at the individual level (i.e., individuals are nested within areal units), and thus incorporates both individual- and areal-level predictors as well as spatial random effects for each mixture component. Conditional autoregressive (CAR) priors on the random effects provide spatial smoothing and allow the shape of the multivariate distribution to vary flexibly across geographic regions. We adopt a Bayesian modeling approach and develop an efficient Markov chain Monte Carlo model fitting algorithm that relies primarily on closed-form full conditionals. We use the model to explore geographic patterns in end-of-grade math and reading test scores among school-age children in North Carolina. PMID:26401059

Clustering, randomness and regularity in cloud fields. I - Theoretical considerations. II - Cumulus cloud fields

NASA Technical Reports Server (NTRS)

Weger, R. C.; Lee, J.; Zhu, Tianri; Welch, R. M.

1992-01-01

The current controversy existing in reference to the regularity vs. clustering in cloud fields is examined by means of analysis and simulation studies based upon nearest-neighbor cumulative distribution statistics. It is shown that the Poisson representation of random point processes is superior to pseudorandom-number-generated models and that pseudorandom-number-generated models bias the observed nearest-neighbor statistics towards regularity. Interpretation of this nearest-neighbor statistics is discussed for many cases of superpositions of clustering, randomness, and regularity. A detailed analysis is carried out of cumulus cloud field spatial distributions based upon Landsat, AVHRR, and Skylab data, showing that, when both large and small clouds are included in the cloud field distributions, the cloud field always has a strong clustering signal.

Spatially random mortality in old-growth red pine forests of northern Minnesota

Treesearch

Tuomas ​Aakala; Shawn Fraver; Brian J. Palik; Anthony W. D' Amato

2012-01-01

Characterizing the spatial distribution of tree mortality is critical to understanding forest dynamics, but empirical studies on these patterns under old-growth conditions are rare. This rarity is due in part to low mortality rates in old-growth forests, the study of which necessitates long observation periods, and the confounding influence of tree in-growth during...

Sampling in health geography: reconciling geographical objectives and probabilistic methods. An example of a health survey in Vientiane (Lao PDR)

PubMed Central

Vallée, Julie; Souris, Marc; Fournet, Florence; Bochaton, Audrey; Mobillion, Virginie; Peyronnie, Karine; Salem, Gérard

2007-01-01

Background Geographical objectives and probabilistic methods are difficult to reconcile in a unique health survey. Probabilistic methods focus on individuals to provide estimates of a variable's prevalence with a certain precision, while geographical approaches emphasise the selection of specific areas to study interactions between spatial characteristics and health outcomes. A sample selected from a small number of specific areas creates statistical challenges: the observations are not independent at the local level, and this results in poor statistical validity at the global level. Therefore, it is difficult to construct a sample that is appropriate for both geographical and probability methods. Methods We used a two-stage selection procedure with a first non-random stage of selection of clusters. Instead of randomly selecting clusters, we deliberately chose a group of clusters, which as a whole would contain all the variation in health measures in the population. As there was no health information available before the survey, we selected a priori determinants that can influence the spatial homogeneity of the health characteristics. This method yields a distribution of variables in the sample that closely resembles that in the overall population, something that cannot be guaranteed with randomly-selected clusters, especially if the number of selected clusters is small. In this way, we were able to survey specific areas while minimising design effects and maximising statistical precision. Application We applied this strategy in a health survey carried out in Vientiane, Lao People's Democratic Republic. We selected well-known health determinants with unequal spatial distribution within the city: nationality and literacy. We deliberately selected a combination of clusters whose distribution of nationality and literacy is similar to the distribution in the general population. Conclusion This paper describes the conceptual reasoning behind the construction of the survey sample and shows that it can be advantageous to choose clusters using reasoned hypotheses, based on both probability and geographical approaches, in contrast to a conventional, random cluster selection strategy. PMID:17543100

Sampling in health geography: reconciling geographical objectives and probabilistic methods. An example of a health survey in Vientiane (Lao PDR).

PubMed

Vallée, Julie; Souris, Marc; Fournet, Florence; Bochaton, Audrey; Mobillion, Virginie; Peyronnie, Karine; Salem, Gérard

2007-06-01

Geographical objectives and probabilistic methods are difficult to reconcile in a unique health survey. Probabilistic methods focus on individuals to provide estimates of a variable's prevalence with a certain precision, while geographical approaches emphasise the selection of specific areas to study interactions between spatial characteristics and health outcomes. A sample selected from a small number of specific areas creates statistical challenges: the observations are not independent at the local level, and this results in poor statistical validity at the global level. Therefore, it is difficult to construct a sample that is appropriate for both geographical and probability methods. We used a two-stage selection procedure with a first non-random stage of selection of clusters. Instead of randomly selecting clusters, we deliberately chose a group of clusters, which as a whole would contain all the variation in health measures in the population. As there was no health information available before the survey, we selected a priori determinants that can influence the spatial homogeneity of the health characteristics. This method yields a distribution of variables in the sample that closely resembles that in the overall population, something that cannot be guaranteed with randomly-selected clusters, especially if the number of selected clusters is small. In this way, we were able to survey specific areas while minimising design effects and maximising statistical precision. We applied this strategy in a health survey carried out in Vientiane, Lao People's Democratic Republic. We selected well-known health determinants with unequal spatial distribution within the city: nationality and literacy. We deliberately selected a combination of clusters whose distribution of nationality and literacy is similar to the distribution in the general population. This paper describes the conceptual reasoning behind the construction of the survey sample and shows that it can be advantageous to choose clusters using reasoned hypotheses, based on both probability and geographical approaches, in contrast to a conventional, random cluster selection strategy.

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.

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.

Spatial Distribution of Adult Anthonomus grandis Boheman (Coleoptera: Curculionidae) and Damage to Cotton Flower Buds Due to Feeding and Oviposition.

PubMed

Grigolli, J F J; Souza, L A; Fernandes, M G; Busoli, A C

2017-08-01

The cotton boll weevil Anthonomus grandis Boheman (Coleoptera: Curculionidae) is the main pest in cotton crop around the world, directly affecting cotton production. In order to establish a sequential sampling plan, it is crucial to understand the spatial distribution of the pest population and the damage it causes to the crop through the different developmental stages of cotton plants. Therefore, this study aimed to investigate the spatial distribution of adults in the cultivation area and their oviposition and feeding behavior throughout the development of the cotton plants. The experiment was conducted in Maracaju, Mato Grosso do Sul, Brazil, in the 2012/2013 and 2013/2014 growing seasons, in an area of 10,000 m 2 , planted with the cotton cultivar FM 993. The experimental area was divided into 100 plots of 100 m 2 (10 × 10 m) each, and five plants per plot were sampled weekly throughout the crop cycle. The number of flower buds with feeding and oviposition punctures and of adult A. grandis was recorded throughout the crop cycle in five plants per plot. After determining the aggregation indices (variance/mean ratio, Morisita's index, exponent k of the negative binomial distribution, and Green's coefficient) and adjusting the frequencies observed in the field to the distribution of frequencies (Poisson, negative binomial, and positive binomial) using the chi-squared test, it was observed that flower buds with punctures derived from feeding, oviposition, and feeding + oviposition showed an aggregated distribution in the cultivation area until 85 days after emergence and a random distribution after this stage. The adults of A. grandis presented a random distribution in the cultivation area.

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.

Spatial and Temporal Distribution of Tuberculosis in the State of Mexico, Mexico

PubMed Central

Zaragoza Bastida, Adrian; Hernández Tellez, Marivel; Bustamante Montes, Lilia P.; Medina Torres, Imelda; Jaramillo Paniagua, Jaime Nicolás; Mendoza Martínez, Germán David; Ramírez Durán, Ninfa

2012-01-01

Tuberculosis (TB) is one of the oldest human diseases that still affects large population groups. According to the World Health Organization (WHO), there were approximately 9.4 million new cases worldwide in the year 2010. In Mexico, there were 18,848 new cases of TB of all clinical variants in 2010. The identification of clusters in space-time is of great interest in epidemiological studies. The objective of this research was to identify the spatial and temporal distribution of TB during the period 2006–2010 in the State of Mexico, using geographic information system (GIS) and SCAN statistics program. Nine significant clusters (P < 0.05) were identified using spatial and space-time analysis. The conclusion is that TB in the State of Mexico is not randomly distributed but is concentrated in areas close to Mexico City. PMID:22919337

Effects of Spatial Variability of Soil Properties on the Triggering of Rainfall-Induced Shallow Landslides

NASA Astrophysics Data System (ADS)

Fan, Linfeng; Lehmann, Peter; Or, Dani

2015-04-01

Naturally-occurring spatial variations in soil properties (e.g., soil depth, moisture, and texture) affect key hydrological processes and potentially the mechanical response of soil to hydromechanical loading (relative to the commonly-assumed uniform soil mantle). We quantified the effects of soil spatial variability on the triggering of rainfall-induced shallow landslides at the hillslope- and catchment-scales, using a physically-based landslide triggering model that considers interacting soil columns with mechanical strength thresholds (represented by the Fiber Bundle Model). The spatial variations in soil properties are represented as Gaussian random distributions and the level of variation is characterized by the coefficient of variation and correlation lengths of soil properties (i.e., soil depth, soil texture and initial water content in this study). The impacts of these spatial variations on landslide triggering characteristics were measured by comparing the times to triggering and landslide volumes for heterogeneous soil properties and homogeneous cases. Results at hillslope scale indicate that for spatial variations of an individual property (without cross correlation), the increasing of coefficient of variation introduces weak spots where mechanical damage is accelerated and leads to earlier onset of landslide triggering and smaller volumes. Increasing spatial correlation length of soil texture and initial water content also induces early landslide triggering and small released volumes due to the transition of failure mode from brittle to ductile failure. In contrast, increasing spatial correlation length of soil depth "reduces" local steepness and postpones landslide triggering. Cross-correlated soil properties generally promote landslide initiation, but depending on the internal structure of spatial distribution of each soil property, landslide triggering may be reduced. The effects of cross-correlation between initial water content and soil texture were investigated in detail at the catchment scale by incorporating correlations of both variables with topography. Results indicate that the internal structure of the spatial distribution of each soil property together with their interplays determine the overall performance of the coupled spatial variability. This study emphasizes the importance of both the randomness and spatial structure of soil properties on landslide triggering and characteristics.

A highly distributed Bragg stack with unique geometry provides effective camouflage for Loliginid squid eyes

PubMed Central

Holt, Amanda L.; Sweeney, Alison M.; Johnsen, Sönke; Morse, Daniel E.

2011-01-01

Cephalopods possess a sophisticated array of mechanisms to achieve camouflage in dynamic underwater environments. While active mechanisms such as chromatophore patterning and body posturing are well known, passive mechanisms such as manipulating light with highly evolved reflectors may also play an important role. To explore the contribution of passive mechanisms to cephalopod camouflage, we investigated the optical and biochemical properties of the silver layer covering the eye of the California fishery squid, Loligo opalescens. We discovered a novel nested-spindle geometry whose correlated structure effectively emulates a randomly distributed Bragg reflector (DBR), with a range of spatial frequencies resulting in broadband visible reflectance, making it a nearly ideal passive camouflage material for the depth at which these animals live. We used the transfer-matrix method of optical modelling to investigate specular reflection from the spindle structures, demonstrating that a DBR with widely distributed thickness variations of high refractive index elements is sufficient to yield broadband reflectance over visible wavelengths, and that unlike DBRs with one or a few spatial frequencies, this broadband reflectance occurs from a wide range of viewing angles. The spindle shape of the cells may facilitate self-assembly of a random DBR to achieve smooth spatial distributions in refractive indices. This design lends itself to technological imitation to achieve a DBR with wide range of smoothly varying layer thicknesses in a facile, inexpensive manner. PMID:21325315

Dynamic laser speckle analyzed considering inhomogeneities in the biological sample

NASA Astrophysics Data System (ADS)

Braga, Roberto A.; González-Peña, Rolando J.; Viana, Dimitri Campos; Rivera, Fernando Pujaico

2017-04-01

Dynamic laser speckle phenomenon allows a contactless and nondestructive way to monitor biological changes that are quantified by second-order statistics applied in the images in time using a secondary matrix known as time history of the speckle pattern (THSP). To avoid being time consuming, the traditional way to build the THSP restricts the data to a line or column. Our hypothesis is that the spatial restriction of the information could compromise the results, particularly when undesirable and unexpected optical inhomogeneities occur, such as in cell culture media. It tested a spatial random approach to collect the points to form a THSP. Cells in a culture medium and in drying paint, representing homogeneous samples in different levels, were tested, and a comparison with the traditional method was carried out. An alternative random selection based on a Gaussian distribution around a desired position was also presented. The results showed that the traditional protocol presented higher variation than the outcomes using the random method. The higher the inhomogeneity of the activity map, the higher the efficiency of the proposed method using random points. The Gaussian distribution proved to be useful when there was a well-defined area to monitor.

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.

Neither biased sex ratio nor spatial segregation of the sexes in the subtropical dioecious tree Eurycorymbus cavaleriei (Sapindaceae).

PubMed

Gao, Puxin; Kang, Ming; Wang, Jing; Ye, Qigang; Huang, Hongwen

2009-06-01

Knowledge of sex ratio and spatial distribution of males and females of dioecious species is both of evolutionary interest and of crucial importance for biological conservation. Eurycorymbus cavaleriei, the only species in the genus Eurycorymbus (Sapindaceae), is a dioecious tree endemic to subtropical montane forest in South China. Sex ratios were investigated in 15 natural populations for the two defined ages (young and old). Spatial distribution of males and females was further studied in six large populations occurring in different habitats (fragmented and continuous). The study revealed a slight trend of male-biased sex ratio in both ages of E. cavaleriei, but sex ratio of most populations (13 out of 15) did not display statistically significant deviation from equality. All of the four significantly male-biased populations in the young class shifted to equality or even female-biased. The Ripley's K analysis of the distribution of males with respect to females suggested that individuals of the opposite sexes were more randomly distributed rather than spatially structured. These results suggest that the male-biased sex ratio in E. cavaleriei may result from the precocity of males and habitat heterogeneity. The sex ratio and the sex spatial distribution pattern are unlikely to constitute a serious threat to the survival of the species.

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.

Modelling the spatial distribution of Fasciola hepatica in dairy cattle in Europe.

PubMed

Ducheyne, Els; Charlier, Johannes; Vercruysse, Jozef; Rinaldi, Laura; Biggeri, Annibale; Demeler, Janina; Brandt, Christina; De Waal, Theo; Selemetas, Nikolaos; Höglund, Johan; Kaba, Jaroslaw; Kowalczyk, Slawomir J; Hendrickx, Guy

2015-03-26

A harmonized sampling approach in combination with spatial modelling is required to update current knowledge of fasciolosis in dairy cattle in Europe. Within the scope of the EU project GLOWORM, samples from 3,359 randomly selected farms in 849 municipalities in Belgium, Germany, Ireland, Poland and Sweden were collected and their infection status assessed using an indirect bulk tank milk (BTM) enzyme-linked immunosorbent assay (ELISA). Dairy farms were considered exposed when the optical density ratio (ODR) exceeded the 0.3 cut-off. Two ensemble-modelling techniques, Random Forests (RF) and Boosted Regression Trees (BRT), were used to obtain the spatial distribution of the probability of exposure to Fasciola hepatica using remotely sensed environmental variables (1-km spatial resolution) and interpolated values from meteorological stations as predictors. The median ODRs amounted to 0.31, 0.12, 0.54, 0.25 and 0.44 for Belgium, Germany, Ireland, Poland and southern Sweden, respectively. Using the 0.3 threshold, 571 municipalities were categorized as positive and 429 as negative. RF was seen as capable of predicting the spatial distribution of exposure with an area under the receiver operation characteristic (ROC) curve (AUC) of 0.83 (0.96 for BRT). Both models identified rainfall and temperature as the most important factors for probability of exposure. Areas of high and low exposure were identified by both models, with BRT better at discriminating between low-probability and high-probability exposure; this model may therefore be more useful in practise. Given a harmonized sampling strategy, it should be possible to generate robust spatial models for fasciolosis in dairy cattle in Europe to be used as input for temporal models and for the detection of deviations in baseline probability. Further research is required for model output in areas outside the eco-climatic range investigated.

Mapping the distribution of the main host for plague in a complex landscape in Kazakhstan: An object-based approach using SPOT-5 XS, Landsat 7 ETM+, SRTM and multiple Random Forests

NASA Astrophysics Data System (ADS)

Wilschut, L. I.; Addink, E. A.; Heesterbeek, J. A. P.; Dubyanskiy, V. M.; Davis, S. A.; Laudisoit, A.; Begon, M.; Burdelov, L. A.; Atshabar, B. B.; de Jong, S. M.

2013-08-01

Plague is a zoonotic infectious disease present in great gerbil populations in Kazakhstan. Infectious disease dynamics are influenced by the spatial distribution of the carriers (hosts) of the disease. The great gerbil, the main host in our study area, lives in burrows, which can be recognized on high resolution satellite imagery. In this study, using earth observation data at various spatial scales, we map the spatial distribution of burrows in a semi-desert landscape. The study area consists of various landscape types. To evaluate whether identification of burrows by classification is possible in these landscape types, the study area was subdivided into eight landscape units, on the basis of Landsat 7 ETM+ derived Tasselled Cap Greenness and Brightness, and SRTM derived standard deviation in elevation. In the field, 904 burrows were mapped. Using two segmented 2.5 m resolution SPOT-5 XS satellite scenes, reference object sets were created. Random Forests were built for both SPOT scenes and used to classify the images. Additionally, a stratified classification was carried out, by building separate Random Forests per landscape unit. Burrows were successfully classified in all landscape units. In the ‘steppe on floodplain’ areas, classification worked best: producer's and user's accuracy in those areas reached 88% and 100%, respectively. In the ‘floodplain’ areas with a more heterogeneous vegetation cover, classification worked least well; there, accuracies were 86 and 58% respectively. Stratified classification improved the results in all landscape units where comparison was possible (four), increasing kappa coefficients by 13, 10, 9 and 1%, respectively. In this study, an innovative stratification method using high- and medium resolution imagery was applied in order to map host distribution on a large spatial scale. The burrow maps we developed will help to detect changes in the distribution of great gerbil populations and, moreover, serve as a unique empirical data set which can be used as input for epidemiological plague models. This is an important step in understanding the dynamics of plague.

Modeling Invasion Dynamics with Spatial Random-Fitness Due to Micro-Environment

PubMed Central

Manem, V. S. K.; Kaveh, K.; Kohandel, M.; Sivaloganathan, S.

2015-01-01

Numerous experimental studies have demonstrated that the microenvironment is a key regulator influencing the proliferative and migrative potentials of species. Spatial and temporal disturbances lead to adverse and hazardous microenvironments for cellular systems that is reflected in the phenotypic heterogeneity within the system. In this paper, we study the effect of microenvironment on the invasive capability of species, or mutants, on structured grids (in particular, square lattices) under the influence of site-dependent random proliferation in addition to a migration potential. We discuss both continuous and discrete fitness distributions. Our results suggest that the invasion probability is negatively correlated with the variance of fitness distribution of mutants (for both advantageous and neutral mutants) in the absence of migration of both types of cells. A similar behaviour is observed even in the presence of a random fitness distribution of host cells in the system with neutral fitness rate. In the case of a bimodal distribution, we observe zero invasion probability until the system reaches a (specific) proportion of advantageous phenotypes. Also, we find that the migrative potential amplifies the invasion probability as the variance of fitness of mutants increases in the system, which is the exact opposite in the absence of migration. Our computational framework captures the harsh microenvironmental conditions through quenched random fitness distributions and migration of cells, and our analysis shows that they play an important role in the invasion dynamics of several biological systems such as bacterial micro-habitats, epithelial dysplasia, and metastasis. We believe that our results may lead to more experimental studies, which can in turn provide further insights into the role and impact of heterogeneous environments on invasion dynamics. PMID:26509572

[Stochastic characteristics of daily precipitation and its spatiotemporal difference over China based on information entropy].

PubMed

Li, Xin Xin; Sang, Yan Fang; Xie, Ping; Liu, Chang Ming

2018-04-01

Daily precipitation process in China showed obvious randomness and spatiotemporal variation. It is important to accurately understand the influence of precipitation changes on control of flood and waterlogging disaster. Using the daily precipitation data measured at 520 stations in China during 1961-2013, we quantified the stochastic characteristics of daily precipitation over China based on the index of information entropy. Results showed that the randomness of daily precipitation in the southeast region were larger than that in the northwest region. Moreover, the spatial distribution of stochastic characteristics of precipitation was different at various grades. Stochastic characteri-stics of P 0 (precipitation at 0.1-10 mm) was large, but the spatial variation was not obvious. The stochastic characteristics of P 10 (precipitation at 10-25 mm) and P 25 (precipitation at 25-50 mm) were the largest and their spatial difference was obvious. P 50 (precipitation ≥50 mm) had the smallest stochastic characteristics and the most obviously spatial difference. Generally, the entropy values of precipitation obviously increased over the last five decades, indicating more significantly stochastic characteristics of precipitation (especially the obvious increase of heavy precipitation events) in most region over China under the scenarios of global climate change. Given that the spatial distribution and long-term trend of entropy values of daily precipitation could reflect thespatial distribution of stochastic characteristics of precipitation, our results could provide scientific basis for the control of flood and waterlogging disaster, the layout of agricultural planning, and the planning of ecological environment.

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.

Pure random search for ambient sensor distribution optimisation in a smart home environment.

PubMed

Poland, Michael P; Nugent, Chris D; Wang, Hui; Chen, Liming

2011-01-01

Smart homes are living spaces facilitated with technology to allow individuals to remain in their own homes for longer, rather than be institutionalised. Sensors are the fundamental physical layer with any smart home, as the data they generate is used to inform decision support systems, facilitating appropriate actuator actions. Positioning of sensors is therefore a fundamental characteristic of a smart home. Contemporary smart home sensor distribution is aligned to either a) a total coverage approach; b) a human assessment approach. These methods for sensor arrangement are not data driven strategies, are unempirical and frequently irrational. This Study hypothesised that sensor deployment directed by an optimisation method that utilises inhabitants' spatial frequency data as the search space, would produce more optimal sensor distributions vs. the current method of sensor deployment by engineers. Seven human engineers were tasked to create sensor distributions based on perceived utility for 9 deployment scenarios. A Pure Random Search (PRS) algorithm was then tasked to create matched sensor distributions. The PRS method produced superior distributions in 98.4% of test cases (n=64) against human engineer instructed deployments when the engineers had no access to the spatial frequency data, and in 92.0% of test cases (n=64) when engineers had full access to these data. These results thus confirmed the hypothesis.

Modeling the spatial distribution of Chagas disease vectors using environmental variables and people´s knowledge.

PubMed

Hernández, Jaime; Núñez, Ignacia; Bacigalupo, Antonella; Cattan, Pedro E

2013-05-31

Chagas disease is caused by the protozoan Trypanosoma cruzi, which is transmitted to mammal hosts by triatomine insect vectors. The goal of this study was to model the spatial distribution of triatomine species in an endemic area. Vector's locations were obtained with a rural householders' survey. This information was combined with environmental data obtained from remote sensors, land use maps and topographic SRTM data, using the machine learning algorithm Random Forests to model species distribution. We analysed the combination of variables on three scales: 10 km, 5 km and 2.5 km cell size grids. The best estimation, explaining 46.2% of the triatomines spatial distribution, was obtained for 5 km of spatial resolution. Presence probability distribution increases from central Chile towards the north, tending to cover the central-coastal region and avoiding areas of the Andes range. The methodology presented here was useful to model the distribution of triatomines in an endemic area; it is best explained using 5 km of spatial resolution, and their presence increases in the northern part of the study area. This study's methodology can be replicated in other countries with Chagas disease or other vectorial transmitted diseases, and be used to locate high risk areas and to optimize resource allocation, for prevention and control of vectorial diseases.

Modeling the spatial distribution of Chagas disease vectors using environmental variables and people´s knowledge

PubMed Central

2013-01-01

Background Chagas disease is caused by the protozoan Trypanosoma cruzi, which is transmitted to mammal hosts by triatomine insect vectors. The goal of this study was to model the spatial distribution of triatomine species in an endemic area. Methods Vector’s locations were obtained with a rural householders’ survey. This information was combined with environmental data obtained from remote sensors, land use maps and topographic SRTM data, using the machine learning algorithm Random Forests to model species distribution. We analysed the combination of variables on three scales: 10 km, 5 km and 2.5 km cell size grids. Results The best estimation, explaining 46.2% of the triatomines spatial distribution, was obtained for 5 km of spatial resolution. Presence probability distribution increases from central Chile towards the north, tending to cover the central-coastal region and avoiding areas of the Andes range. Conclusions The methodology presented here was useful to model the distribution of triatomines in an endemic area; it is best explained using 5 km of spatial resolution, and their presence increases in the northern part of the study area. This study’s methodology can be replicated in other countries with Chagas disease or other vectorial transmitted diseases, and be used to locate high risk areas and to optimize resource allocation, for prevention and control of vectorial diseases. PMID:23724993

Towards the Development of a More Accurate Monitoring Procedure for Invertebrate Populations, in the Presence of an Unknown Spatial Pattern of Population Distribution in the Field

PubMed Central

Petrovskaya, Natalia B.; Forbes, Emily; Petrovskii, Sergei V.; Walters, Keith F. A.

2018-01-01

Studies addressing many ecological problems require accurate evaluation of the total population size. In this paper, we revisit a sampling procedure used for the evaluation of the abundance of an invertebrate population from assessment data collected on a spatial grid of sampling locations. We first discuss how insufficient information about the spatial population density obtained on a coarse sampling grid may affect the accuracy of an evaluation of total population size. Such information deficit in field data can arise because of inadequate spatial resolution of the population distribution (spatially variable population density) when coarse grids are used, which is especially true when a strongly heterogeneous spatial population density is sampled. We then argue that the average trap count (the quantity routinely used to quantify abundance), if obtained from a sampling grid that is too coarse, is a random variable because of the uncertainty in sampling spatial data. Finally, we show that a probabilistic approach similar to bootstrapping techniques can be an efficient tool to quantify the uncertainty in the evaluation procedure in the presence of a spatial pattern reflecting a patchy distribution of invertebrates within the sampling grid. PMID:29495513

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

PubMed

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

2014-06-01

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

Stochastic transport in the presence of spatial disorder: Fluctuation-induced corrections to homogenization

NASA Astrophysics Data System (ADS)

Russell, Matthew J.; Jensen, Oliver E.; Galla, Tobias

2016-10-01

Motivated by uncertainty quantification in natural transport systems, we investigate an individual-based transport process involving particles undergoing a random walk along a line of point sinks whose strengths are themselves independent random variables. We assume particles are removed from the system via first-order kinetics. We analyze the system using a hierarchy of approaches when the sinks are sparsely distributed, including a stochastic homogenization approximation that yields explicit predictions for the extrinsic disorder in the stationary state due to sink strength fluctuations. The extrinsic noise induces long-range spatial correlations in the particle concentration, unlike fluctuations due to the intrinsic noise alone. Additionally, the mean concentration profile, averaged over both intrinsic and extrinsic noise, is elevated compared with the corresponding profile from a uniform sink distribution, showing that the classical homogenization approximation can be a biased estimator of the true mean.

Epidemiological characteristics of cases of death from tuberculosis and vulnerable territories1

PubMed Central

Yamamura, Mellina; Santos-Neto, Marcelino; dos Santos, Rebeca Augusto Neman; Garcia, Maria Concebida da Cunha; Nogueira, Jordana de Almeida; Arcêncio, Ricardo Alexandre

2015-01-01

Objective: to characterize the differences in the clinical and epidemiological profile of cases of death that had tuberculosis as an immediate or associated cause, and to analyze the spatial distribution of the cases of death from tuberculosis within the territories of Ribeirão Preto, Brazil. Method: an ecological study, in which the population consisted of 114 cases of death from tuberculosis. Bivariate analysis was carried out, as well as point density analysis, defined with the Kernel estimate. Results: of the cases of death from tuberculosis, 50 were the immediate cause and 64 an associated cause. Age (p=.008) and sector responsible for the death certificate (p=.003) were the variables that presented statistically significant associations with the cause of death. The spatial distribution, in both events, did not occur randomly, forming clusters in areas of the municipality. Conclusion: the difference in the profiles of the cases of death from tuberculosis, as a basic cause and as an associated cause, was governed by the age and the sector responsible for the completion of the death certificate. The non-randomness of the spatial distribution of the cases suggests areas that are vulnerable to these events. Knowing these areas can contribute to the choice of disease control strategies. PMID:26487142

Comparison of five modelling techniques to predict the spatial distribution and abundance of seabirds

USGS Publications Warehouse

O'Connell, Allan F.; Gardner, Beth; Oppel, Steffen; Meirinho, Ana; Ramírez, Iván; Miller, Peter I.; Louzao, Maite

2012-01-01

Knowledge about the spatial distribution of seabirds at sea is important for conservation. During marine conservation planning, logistical constraints preclude seabird surveys covering the complete area of interest and spatial distribution of seabirds is frequently inferred from predictive statistical models. Increasingly complex models are available to relate the distribution and abundance of pelagic seabirds to environmental variables, but a comparison of their usefulness for delineating protected areas for seabirds is lacking. Here we compare the performance of five modelling techniques (generalised linear models, generalised additive models, Random Forest, boosted regression trees, and maximum entropy) to predict the distribution of Balearic Shearwaters (Puffinus mauretanicus) along the coast of the western Iberian Peninsula. We used ship transect data from 2004 to 2009 and 13 environmental variables to predict occurrence and density, and evaluated predictive performance of all models using spatially segregated test data. Predicted distribution varied among the different models, although predictive performance varied little. An ensemble prediction that combined results from all five techniques was robust and confirmed the existence of marine important bird areas for Balearic Shearwaters in Portugal and Spain. Our predictions suggested additional areas that would be of high priority for conservation and could be proposed as protected areas. Abundance data were extremely difficult to predict, and none of five modelling techniques provided a reliable prediction of spatial patterns. We advocate the use of ensemble modelling that combines the output of several methods to predict the spatial distribution of seabirds, and use these predictions to target separate surveys assessing the abundance of seabirds in areas of regular use.

Spatial Light Modulators as Optical Crossbar Switches

NASA Technical Reports Server (NTRS)

Juday, Richard

2003-01-01

A proposed method of implementing cross connections in an optical communication network is based on the use of a spatial light modulator (SLM) to form controlled diffraction patterns that connect inputs (light sources) and outputs (light sinks). Sources would typically include optical fibers and/or light-emitting diodes; sinks would typically include optical fibers and/or photodetectors. The sources and/or sinks could be distributed in two dimensions; that is, on planes. Alternatively or in addition, sources and/or sinks could be distributed in three dimensions -- for example, on curved surfaces or in more complex (including random) three-dimensional patterns.

Exploring the effect of the spatial scale of fishery management.

PubMed

Takashina, Nao; Baskett, Marissa L

2016-02-07

For any spatially explicit management, determining the appropriate spatial scale of management decisions is critical to success at achieving a given management goal. Specifically, managers must decide how much to subdivide a given managed region: from implementing a uniform approach across the region to considering a unique approach in each of one hundred patches and everything in between. Spatially explicit approaches, such as the implementation of marine spatial planning and marine reserves, are increasingly used in fishery management. Using a spatially explicit bioeconomic model, we quantify how the management scale affects optimal fishery profit, biomass, fishery effort, and the fraction of habitat in marine reserves. We find that, if habitats are randomly distributed, the fishery profit increases almost linearly with the number of segments. However, if habitats are positively autocorrelated, then the fishery profit increases with diminishing returns. Therefore, the true optimum in management scale given cost to subdivision depends on the habitat distribution pattern. Copyright © 2015 Elsevier Ltd. All rights reserved.

Performance analysis of MIMO wireless optical communication system with Q-ary PPM over correlated log-normal fading channel

NASA Astrophysics Data System (ADS)

Wang, Huiqin; Wang, Xue; Lynette, Kibe; Cao, Minghua

2018-06-01

The performance of multiple-input multiple-output wireless optical communication systems that adopt Q-ary pulse position modulation over spatial correlated log-normal fading channel is analyzed in terms of its un-coded bit error rate and ergodic channel capacity. The analysis is based on the Wilkinson's method which approximates the distribution of a sum of correlated log-normal random variables to a log-normal random variable. The analytical and simulation results corroborate the increment of correlation coefficients among sub-channels lead to system performance degradation. Moreover, the receiver diversity has better performance in resistance of spatial correlation caused channel fading.

Analysis of security of optical encryption with spatially incoherent illumination technique

NASA Astrophysics Data System (ADS)

Cheremkhin, Pavel A.; Evtikhiev, Nikolay N.; Krasnov, Vitaly V.; Rodin, Vladislav G.; Shifrina, Anna V.

2017-03-01

Applications of optical methods for encryption purposes have been attracting interest of researchers for decades. The first and the most popular is double random phase encoding (DRPE) technique. There are many optical encryption techniques based on DRPE. Main advantage of DRPE based techniques is high security due to transformation of spectrum of image to be encrypted into white spectrum via use of first phase random mask which allows for encrypted images with white spectra. Downsides are necessity of using holographic registration scheme in order to register not only light intensity distribution but also its phase distribution, and speckle noise occurring due to coherent illumination. Elimination of these disadvantages is possible via usage of incoherent illumination instead of coherent one. In this case, phase registration no longer matters, which means that there is no need for holographic setup, and speckle noise is gone. This technique does not have drawbacks inherent to coherent methods, however, as only light intensity distribution is considered, mean value of image to be encrypted is always above zero which leads to intensive zero spatial frequency peak in image spectrum. Consequently, in case of spatially incoherent illumination, image spectrum, as well as encryption key spectrum, cannot be white. This might be used to crack encryption system. If encryption key is very sparse, encrypted image might contain parts or even whole unhidden original image. Therefore, in this paper analysis of security of optical encryption with spatially incoherent illumination depending on encryption key size and density is conducted.

A random forest approach for predicting the presence of Echinococcus multilocularis intermediate host Ochotona spp. presence in relation to landscape characteristics in western China

PubMed Central

Marston, Christopher G.; Danson, F. Mark; Armitage, Richard P.; Giraudoux, Patrick; Pleydell, David R.J.; Wang, Qian; Qui, Jiamin; Craig, Philip S.

2014-01-01

Understanding distribution patterns of hosts implicated in the transmission of zoonotic disease remains a key goal of parasitology. Here, random forests are employed to model spatial patterns of the presence of the plateau pika (Ochotona spp.) small mammal intermediate host for the parasitic tapeworm Echinococcus multilocularis which is responsible for a significant burden of human zoonoses in western China. Landsat ETM+ satellite imagery and digital elevation model data were utilized to generate quantified measures of environmental characteristics across a study area in Sichuan Province, China. Land cover maps were generated identifying the distribution of specific land cover types, with landscape metrics employed to describe the spatial organisation of land cover patches. Random forests were used to model spatial patterns of Ochotona spp. presence, enabling the relative importance of the environmental characteristics in relation to Ochotona spp. presence to be ranked. An index of habitat aggregation was identified as the most important variable in influencing Ochotona spp. presence, with area of degraded grassland the most important land cover class variable. 71% of the variance in Ochotona spp. presence was explained, with a 90.98% accuracy rate as determined by ‘out-of-bag’ error assessment. Identification of the environmental characteristics influencing Ochotona spp. presence enables us to better understand distribution patterns of hosts implicated in the transmission of Em. The predictive mapping of this Em host enables the identification of human populations at increased risk of infection, enabling preventative strategies to be adopted. PMID:25386042

Spatial Downscaling of Alien Species Presences using Machine Learning

NASA Astrophysics Data System (ADS)

Daliakopoulos, Ioannis N.; Katsanevakis, Stelios; Moustakas, Aristides

2017-07-01

Large scale, high-resolution data on alien species distributions are essential for spatially explicit assessments of their environmental and socio-economic impacts, and management interventions for mitigation. However, these data are often unavailable. This paper presents a method that relies on Random Forest (RF) models to distribute alien species presence counts at a finer resolution grid, thus achieving spatial downscaling. A sufficiently large number of RF models are trained using random subsets of the dataset as predictors, in a bootstrapping approach to account for the uncertainty introduced by the subset selection. The method is tested with an approximately 8×8 km2 grid containing floral alien species presence and several indices of climatic, habitat, land use covariates for the Mediterranean island of Crete, Greece. Alien species presence is aggregated at 16×16 km2 and used as a predictor of presence at the original resolution, thus simulating spatial downscaling. Potential explanatory variables included habitat types, land cover richness, endemic species richness, soil type, temperature, precipitation, and freshwater availability. Uncertainty assessment of the spatial downscaling of alien species’ occurrences was also performed and true/false presences and absences were quantified. The approach is promising for downscaling alien species datasets of larger spatial scale but coarse resolution, where the underlying environmental information is available at a finer resolution than the alien species data. Furthermore, the RF architecture allows for tuning towards operationally optimal sensitivity and specificity, thus providing a decision support tool for designing a resource efficient alien species census.

LiDAR based prediction of forest biomass using hierarchical models with spatially varying coefficients

USGS Publications Warehouse

Babcock, Chad; Finley, Andrew O.; Bradford, John B.; Kolka, Randall K.; Birdsey, Richard A.; Ryan, Michael G.

2015-01-01

Many studies and production inventory systems have shown the utility of coupling covariates derived from Light Detection and Ranging (LiDAR) data with forest variables measured on georeferenced inventory plots through regression models. The objective of this study was to propose and assess the use of a Bayesian hierarchical modeling framework that accommodates both residual spatial dependence and non-stationarity of model covariates through the introduction of spatial random effects. We explored this objective using four forest inventory datasets that are part of the North American Carbon Program, each comprising point-referenced measures of above-ground forest biomass and discrete LiDAR. For each dataset, we considered at least five regression model specifications of varying complexity. Models were assessed based on goodness of fit criteria and predictive performance using a 10-fold cross-validation procedure. Results showed that the addition of spatial random effects to the regression model intercept improved fit and predictive performance in the presence of substantial residual spatial dependence. Additionally, in some cases, allowing either some or all regression slope parameters to vary spatially, via the addition of spatial random effects, further improved model fit and predictive performance. In other instances, models showed improved fit but decreased predictive performance—indicating over-fitting and underscoring the need for cross-validation to assess predictive ability. The proposed Bayesian modeling framework provided access to pixel-level posterior predictive distributions that were useful for uncertainty mapping, diagnosing spatial extrapolation issues, revealing missing model covariates, and discovering locally significant parameters.

[Assessment on ecological security spatial differences of west areas of Liaohe River based on GIS].

PubMed

Wang, Geng; Wu, Wei

2005-09-01

Ecological security assessment and early warning research have spatiality; non-linearity; randomicity, it is needed to deal with much spatial information. Spatial analysis and data management are advantages of GIS, it can define distribution trend and spatial relations of environmental factors, and show ecological security pattern graphically. The paper discusses the method of ecological security spatial differences of west areas of Liaohe River based on GIS and ecosystem non-health. First, studying on pressure-state-response (P-S-R) assessment indicators system, investigating in person and gathering information; Second, digitizing the river, applying fuzzy AHP to put weight, quantizing and calculating by fuzzy comparing; Last, establishing grid data-base; expounding spatial differences of ecological security by GIS Interpolate and Assembly.

Distribution of Large Wood Within River Corridors in Relation to Flow Regime in the Semiarid Western US

NASA Astrophysics Data System (ADS)

Wohl, Ellen; Cadol, Daniel; Pfeiffer, Andrew; Jackson, Karen; Laurel, DeAnna

2018-03-01

The cumulative volume and spatial distribution of large wood (LW) along river corridors (channels and floodplains) reflect interactions between rates and volumes of LW recruitment and channel transport capacity through time. Rivers of the semiarid interior western US can have relatively low-magnitude disturbances associated with annual snowmelt or relatively high-magnitude disturbances associated with episodic rainfall runoff, especially following wildfires. We use characteristics of LW from 25 river segments in four regions of New Mexico and Colorado to analyze wood loads and spatial patterns of wood distribution in relation to disturbance regime. High-magnitude disturbances move LW onto floodplains and create longitudinally nonuniform LW distributions with aggregated (closer together than random) LW pieces and abundant LW jams in the floodplain. Sites with low-magnitude disturbances have a greater proportion of LW in the channel and much of this wood is within segregated (farther apart than random) jams. These results imply that river management, which typically focuses on LW within channels, should focus on floodplain as well as in-channel LW in rivers with high-magnitude disturbances. The results also indicate that the proportions of LW loads in channels versus floodplains can differ significantly among rivers with different disturbance regimes that are otherwise similar in terms of forest type or drainage area. This is particularly relevant to mountainous regions with elevation-related changes in flow and disturbance regime. River management that reintroduces LW to river corridors will be most effective if it incorporates the mobility and spatial distribution of LW.

Geostatistical Sampling Methods for Efficient Uncertainty Analysis in Flow and Transport Problems

NASA Astrophysics Data System (ADS)

Liodakis, Stylianos; Kyriakidis, Phaedon; Gaganis, Petros

2015-04-01

In hydrogeological applications involving flow and transport of in heterogeneous porous media the spatial distribution of hydraulic conductivity is often parameterized in terms of a lognormal random field based on a histogram and variogram model inferred from data and/or synthesized from relevant knowledge. Realizations of simulated conductivity fields are then generated using geostatistical simulation involving simple random (SR) sampling and are subsequently used as inputs to physically-based simulators of flow and transport in a Monte Carlo framework for evaluating the uncertainty in the spatial distribution of solute concentration due to the uncertainty in the spatial distribution of hydraulic con- ductivity [1]. Realistic uncertainty analysis, however, calls for a large number of simulated concentration fields; hence, can become expensive in terms of both time and computer re- sources. A more efficient alternative to SR sampling is Latin hypercube (LH) sampling, a special case of stratified random sampling, which yields a more representative distribution of simulated attribute values with fewer realizations [2]. Here, term representative implies realizations spanning efficiently the range of possible conductivity values corresponding to the lognormal random field. In this work we investigate the efficiency of alternative methods to classical LH sampling within the context of simulation of flow and transport in a heterogeneous porous medium. More precisely, we consider the stratified likelihood (SL) sampling method of [3], in which attribute realizations are generated using the polar simulation method by exploring the geometrical properties of the multivariate Gaussian distribution function. In addition, we propose a more efficient version of the above method, here termed minimum energy (ME) sampling, whereby a set of N representative conductivity realizations at M locations is constructed by: (i) generating a representative set of N points distributed on the surface of a M-dimensional, unit radius hyper-sphere, (ii) relocating the N points on a representative set of N hyper-spheres of different radii, and (iii) transforming the coordinates of those points to lie on N different hyper-ellipsoids spanning the multivariate Gaussian distribution. The above method is applied in a dimensionality reduction context by defining flow-controlling points over which representative sampling of hydraulic conductivity is performed, thus also accounting for the sensitivity of the flow and transport model to the input hydraulic conductivity field. The performance of the various stratified sampling methods, LH, SL, and ME, is compared to that of SR sampling in terms of reproduction of ensemble statistics of hydraulic conductivity and solute concentration for different sample sizes N (numbers of realizations). The results indicate that ME sampling constitutes an equally if not more efficient simulation method than LH and SL sampling, as it can reproduce to a similar extent statistics of the conductivity and concentration fields, yet with smaller sampling variability than SR sampling. References [1] Gutjahr A.L. and Bras R.L. Spatial variability in subsurface flow and transport: A review. Reliability Engineering & System Safety, 42, 293-316, (1993). [2] Helton J.C. and Davis F.J. Latin hypercube sampling and the propagation of uncertainty in analyses of complex systems. Reliability Engineering & System Safety, 81, 23-69, (2003). [3] Switzer P. Multiple simulation of spatial fields. In: Heuvelink G, Lemmens M (eds) Proceedings of the 4th International Symposium on Spatial Accuracy Assessment in Natural Resources and Environmental Sciences, Coronet Books Inc., pp 629?635 (2000).

Spatial distribution of end-stage renal disease (ESRD) and social inequalities in mixed urban and rural areas: a study in the Bretagne administrative region of France.

PubMed

Kihal-Talantikite, Wahida; Deguen, Séverine; Padilla, Cindy; Siebert, Muriel; Couchoud, Cécile; Vigneau, Cécile; Bayat, Sahar

2015-02-01

Several studies have investigated the implication of biological and environmental factors on geographic variations of end-stage renal disease (ESRD) incidence at large area scales, but none of them assessed the implication of neighbourhood characteristics (healthcare supply, socio-economic level and urbanization degree) on spatial repartition of ESRD. We evaluated the spatial implications of adjustment for neighbourhood characteristics on the spatial distribution of ESRD incidence at the smallest geographic unit in France. All adult patients living in Bretagne and beginning renal replacement therapy during the 2004-09 period were included. Their residential address was geocoded at the census block level. Each census block was characterized by socio-economic deprivation index, healthcare supply and rural/urban typology. Using a spatial scan statistic, we examined whether there were significant clusters of high risk of ESRD incidence. The ESRD incidence was non-randomly spatially distributed, with a cluster of high risk in the western Bretagne region (relative risk, RR = 1.28, P-value = 0.0003). Adjustment for sex, age and neighbourhood characteristics induced cluster shifts. After these adjustments, a significant cluster (P = 0.013) persisted. Our spatial analysis of ESRD incidence at a fine scale, across a mixed rural/urban area, indicated that, beyond age and sex, neighbourhood characteristics explained a great part of spatial distribution of ESRD incidence. However, to better understand spatial variation of ESRD incidence, it would be necessary to research and adjust for other determinants of ESRD.

Analysis of the spatio-temporal distribution of Eurygaster integriceps (Hemiptera: Scutelleridae) by using spatial analysis by distance indices and geostatistics.

PubMed

Karimzadeh, R; Hejazi, M J; Helali, H; Iranipour, S; Mohammadi, S A

2011-10-01

Eurygaster integriceps Puton (Hemiptera: Scutelleridae) is the most serious insect pest of wheat (Triticum aestivum L.) and barley (Hordeum vulgare L.) in Iran. In this study, spatio-temporal distribution of this pest was determined in wheat by using spatial analysis by distance indices (SADIE) and geostatistics. Global positioning and geographic information systems were used for spatial sampling and mapping the distribution of this insect. The study was conducted for three growing seasons in Gharamalek, an agricultural region to the west of Tabriz, Iran. Weekly sampling began when E. integriceps adults migrated to wheat fields from overwintering sites and ended when the new generation adults appeared at the end of season. The adults were sampled using 1- by 1-m quadrat and distance-walk methods. A sweep net was used for sampling the nymphs, and five 180° sweeps were considered as the sampling unit. The results of spatial analyses by using geostatistics and SADIE indicated that E. integriceps adults were clumped after migration to fields and had significant spatial dependency. The second- and third-instar nymphs showed aggregated spatial structure in the middle of growing season. At the end of the season, population distribution changed toward random or regular patterns; and fourth and fifth instars had weaker spatial structure compared with younger nymphs. In Iran, management measures for E. integriceps in wheat fields are mainly applied against overwintering adults, as well as second and third instars. Because of the aggregated distribution of these life stages, site-specific spraying of chemicals is feasible in managing E. integriceps.

A continuous time random walk model for Darcy-scale anomalous transport in heterogeneous porous media.

NASA Astrophysics Data System (ADS)

Comolli, Alessandro; Hakoun, Vivien; Dentz, Marco

2017-04-01

Achieving the understanding of the process of solute transport in heterogeneous porous media is of crucial importance for several environmental and social purposes, ranging from aquifers contamination and remediation, to risk assessment in nuclear waste repositories. The complexity of this aim is mainly ascribable to the heterogeneity of natural media, which can be observed at all the scales of interest, from pore scale to catchment scale. In fact, the intrinsic heterogeneity of porous media is responsible for the arising of the well-known non-Fickian footprints of transport, including heavy-tailed breakthrough curves, non-Gaussian spatial density profiles and the non-linear growth of the mean squared displacement. Several studies investigated the processes through which heterogeneity impacts the transport properties, which include local modifications to the advective-dispersive motion of solutes, mass exchanges between some mobile and immobile phases (e.g. sorption/desorption reactions or diffusion into solid matrix) and spatial correlation of the flow field. In the last decades, the continuous time random walk (CTRW) model has often been used to describe solute transport in heterogenous conditions and to quantify the impact of point heterogeneity, spatial correlation and mass transfer on the average transport properties [1]. Open issues regarding this approach are the possibility to relate measurable properties of the medium to the parameters of the model, as well as its capability to provide predictive information. In a recent work [2] the authors have shed new light on understanding the relationship between Lagrangian and Eulerian dynamics as well as on their evolution from arbitrary initial conditions. On the basis of these results, we derive a CTRW model for the description of Darcy-scale transport in d-dimensional media characterized by spatially random permeability fields. The CTRW approach models particle velocities as a spatial Markov process, which is characterized by a velocity transition probability and the steady state velocity distribution. These are related to the Eulerian velocity distribution and the distribution and spatial organization of hydraulic conductivity. The CTRW model is used for the prediction of transport data (particle dispersion and breakthrough curves) from direct numerical flow and transport simulations in heterogeneous hydraulic conductivity fields. References: [1] Comolli, A., Hidalgo, J. J., Moussey, C., & Dentz, M. (2016). Non-Fickian Transport Under Heterogeneous Advection and Mobile-Immobile Mass Transfer. Transport in Porous Media, 1-25. [2] Dentz, M., Kang, P. K., Comolli, A., Le Borgne, T., & Lester, D. R. (2016). Continuous time random walks for the evolution of Lagrangian velocities. Physical Review Fluids, 1(7), 074004.

Sampling design for spatially distributed hydrogeologic and environmental processes

USGS Publications Warehouse

Christakos, G.; Olea, R.A.

1992-01-01

A methodology for the design of sampling networks over space is proposed. The methodology is based on spatial random field representations of nonhomogeneous natural processes, and on optimal spatial estimation techniques. One of the most important results of random field theory for physical sciences is its rationalization of correlations in spatial variability of natural processes. This correlation is extremely important both for interpreting spatially distributed observations and for predictive performance. The extent of site sampling and the types of data to be collected will depend on the relationship of subsurface variability to predictive uncertainty. While hypothesis formulation and initial identification of spatial variability characteristics are based on scientific understanding (such as knowledge of the physics of the underlying phenomena, geological interpretations, intuition and experience), the support offered by field data is statistically modelled. This model is not limited by the geometric nature of sampling and covers a wide range in subsurface uncertainties. A factorization scheme of the sampling error variance is derived, which possesses certain atttactive properties allowing significant savings in computations. By means of this scheme, a practical sampling design procedure providing suitable indices of the sampling error variance is established. These indices can be used by way of multiobjective decision criteria to obtain the best sampling strategy. Neither the actual implementation of the in-situ sampling nor the solution of the large spatial estimation systems of equations are necessary. The required values of the accuracy parameters involved in the network design are derived using reference charts (readily available for various combinations of data configurations and spatial variability parameters) and certain simple yet accurate analytical formulas. Insight is gained by applying the proposed sampling procedure to realistic examples related to sampling problems in two dimensions. ?? 1992.

Spatial and simultaneous seroepidemiology of anti-Leishmania spp. antibodies in dog owners and their dogs from randomly selected households in a major city of southern Brazil.

PubMed

Benitez, Aline do Nascimento; Martins, Felippe Danyel Cardoso; Mareze, Marcelle; Nino, Beatriz de Souza Lima; Caldart, Eloiza Teles; Ferreira, Fernanda Pinto; Mitsuka-Breganó, Regina; Freire, Roberta Lemos; Galhardo, Juliana Arena; Martins, Camila Marinelli; Biondo, Alexander Welker; Navarro, Italmar Teodorico

2018-06-01

Although leishmaniasis has been described as a classic example of a zoonosis requiring a comprehensive approach for control, to date, no study has been conducted on the spatial distribution of simultaneous Leishmania spp. seroprevalence in dog owners and dogs from randomly selected households in urban settings. Accordingly, the present study aimed to simultaneously identify the seroprevalence, spatial distribution and associated factors of infection with Leishmania spp. in dog owners and their dogs in the city of Londrina, a county seat in southern Brazil with a population of half a million people and ranked 18th in population and 145th in the human development index (HDI) out of 5570 Brazilian cities. Overall, 564 households were surveyed and included 597 homeowners and their 729 dogs. Anti-Leishmania spp. antibodies were detected by ELISA in 9/597 (1.50%) dog owners and in 32/729 (4.38%) dogs, with significantly higher prevalence (p = 0.0042) in dogs. Spatial analysis revealed associations between seropositive dogs and households located up to 500 m from the local railway. No clusters were found for either owner or dog case distributions. In summary, the seroepidemiological and spatial results collectively show a lack of association of the factors for infection, and the results demonstrated higher exposure for dogs than their owners. However, railway areas may provide favorable conditions for the maintenance of infected phlebotomines, thereby causing infection in nearby domiciled dogs. In such an urban scenario, local sanitary barriers should be focused on the terrestrial routes of people and surrounding areas, particularly railways, via continuous vector surveillance and identification of phlebotomines infected by Leishmania spp. Copyright © 2018. Published by Elsevier B.V.

Dynamic Analysis and Research on Environmental Pollution in China from 1992 to 2014

NASA Astrophysics Data System (ADS)

Sun, Fei; Yuan, Peng; Li, Huiting; Zhang, Moli

2018-01-01

The regular pattern of development of the environmental pollution events was analyzed from the perspective of statistical analysis of pollution events in recent years. The Moran, s I and spatial center-of-gravity shift curve of China, s environmental emergencies were calculated by ARCGIS software. And the method is global spatial analysis and spatial center of gravity shift. The results showed that the trend of China, s environmental pollution events from 1992 to 2014 was the first dynamic growth and then gradually reduced. Environmental pollution events showed spatial aggregation distribution in 1992-1994, 2001-2006, 2008-2014, and the rest of year was a random distribution of space. There were two stages in China, s environmental pollution events: The transition to the southwest from 1992 to 2006 and the transition to the northeast from the year of 2006 to 2014.

Advanced analysis of forest fire clustering

NASA Astrophysics Data System (ADS)

Kanevski, Mikhail; Pereira, Mario; Golay, Jean

2017-04-01

Analysis of point pattern clustering is an important topic in spatial statistics and for many applications: biodiversity, epidemiology, natural hazards, geomarketing, etc. There are several fundamental approaches used to quantify spatial data clustering using topological, statistical and fractal measures. In the present research, the recently introduced multi-point Morisita index (mMI) is applied to study the spatial clustering of forest fires in Portugal. The data set consists of more than 30000 fire events covering the time period from 1975 to 2013. The distribution of forest fires is very complex and highly variable in space. mMI is a multi-point extension of the classical two-point Morisita index. In essence, mMI is estimated by covering the region under study by a grid and by computing how many times more likely it is that m points selected at random will be from the same grid cell than it would be in the case of a complete random Poisson process. By changing the number of grid cells (size of the grid cells), mMI characterizes the scaling properties of spatial clustering. From mMI, the data intrinsic dimension (fractal dimension) of the point distribution can be estimated as well. In this study, the mMI of forest fires is compared with the mMI of random patterns (RPs) generated within the validity domain defined as the forest area of Portugal. It turns out that the forest fires are highly clustered inside the validity domain in comparison with the RPs. Moreover, they demonstrate different scaling properties at different spatial scales. The results obtained from the mMI analysis are also compared with those of fractal measures of clustering - box counting and sand box counting approaches. REFERENCES Golay J., Kanevski M., Vega Orozco C., Leuenberger M., 2014: The multipoint Morisita index for the analysis of spatial patterns. Physica A, 406, 191-202. Golay J., Kanevski M. 2015: A new estimator of intrinsic dimension based on the multipoint Morisita index. Pattern Recognition, 48, 4070-4081.

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.

Using a spatially-distributed hydrologic biogeochemistry model with nitrogen transport to study the spatial variation of carbon stocks and fluxes in a Critical Zone Observatory

NASA Astrophysics Data System (ADS)

Shi, Y.; Eissenstat, D. M.; He, Y.; Davis, K. J.

2017-12-01

Most current biogeochemical models are 1-D and represent one point in space. Therefore, they cannot resolve topographically driven land surface heterogeneity (e.g., lateral water flow, soil moisture, soil temperature, solar radiation) or the spatial pattern of nutrient availability. A spatially distributed forest biogeochemical model with nitrogen transport, Flux-PIHM-BGC, has been developed by coupling a 1-D mechanistic biogeochemical model Biome-BGC (BBGC) with a spatially distributed land surface hydrologic model, Flux-PIHM, and adding an advection dominated nitrogen transport module. Flux-PIHM is a coupled physically based model, which incorporates a land-surface scheme into the Penn State Integrated Hydrologic Model (PIHM). The land surface scheme is adapted from the Noah land surface model, and is augmented by adding a topographic solar radiation module. Flux-PIHM is able to represent the link between groundwater and the surface energy balance, as well as land surface heterogeneities caused by topography. In the coupled Flux-PIHM-BGC model, each Flux-PIHM model grid couples a 1-D BBGC model, while nitrogen is transported among model grids via surface and subsurface water flow. In each grid, Flux-PIHM provides BBGC with soil moisture, soil temperature, and solar radiation, while BBGC provides Flux-PIHM with spatially-distributed leaf area index. The coupled Flux-PIHM-BGC model has been implemented at the Susquehanna/Shale Hills Critical Zone Observatory. The model-predicted aboveground vegetation carbon and soil carbon distributions generally agree with the macro patterns observed within the watershed. The importance of abiotic variables (including soil moisture, soil temperature, solar radiation, and soil mineral nitrogen) in predicting aboveground carbon distribution is calculated using a random forest. The result suggests that the spatial pattern of aboveground carbon is controlled by the distribution of soil mineral nitrogen. A Flux-PIHM-BGC simulation without the nitrogen transport module is also executed. The model without nitrogen transport fails in predicting the spatial patterns of vegetation carbon, which indicates the importance of having a nitrogen transport module in spatially distributed ecohydrologic modeling.

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

Modeling spatial effects of PM{sub 2.5} on term low birth weight in Los Angeles County

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

Coker, Eric, E-mail: cokerer@onid.orst.edu; Ghosh, Jokay; Jerrett, Michael

Air pollution epidemiological studies suggest that elevated exposure to fine particulate matter (PM{sub 2.5}) is associated with higher prevalence of term low birth weight (TLBW). Previous studies have generally assumed the exposure–response of PM{sub 2.5} on TLBW to be the same throughout a large geographical area. Health effects related to PM{sub 2.5} exposures, however, may not be uniformly distributed spatially, creating a need for studies that explicitly investigate the spatial distribution of the exposure–response relationship between individual-level exposure to PM{sub 2.5} and TLBW. Here, we examine the overall and spatially varying exposure–response relationship between PM{sub 2.5} and TLBW throughout urbanmore » Los Angeles (LA) County, California. We estimated PM{sub 2.5} from a combination of land use regression (LUR), aerosol optical depth from remote sensing, and atmospheric modeling techniques. Exposures were assigned to LA County individual pregnancies identified from electronic birth certificates between the years 1995-2006 (N=1,359,284) provided by the California Department of Public Health. We used a single pollutant multivariate logistic regression model, with multilevel spatially structured and unstructured random effects set in a Bayesian framework to estimate global and spatially varying pollutant effects on TLBW at the census tract level. Overall, increased PM{sub 2.5} level was associated with higher prevalence of TLBW county-wide. The spatial random effects model, however, demonstrated that the exposure–response for PM{sub 2.5} and TLBW was not uniform across urban LA County. Rather, the magnitude and certainty of the exposure–response estimates for PM{sub 2.5} on log odds of TLBW were greatest in the urban core of Central and Southern LA County census tracts. These results suggest that the effects may be spatially patterned, and that simply estimating global pollutant effects obscures disparities suggested by spatial patterns of effects. Studies that incorporate spatial multilevel modeling with random coefficients allow us to identify areas where air pollutant effects on adverse birth outcomes may be most severe and policies to further reduce air pollution might be most effective. - Highlights: • We model the spatial dependency of PM{sub 2.5} effects on term low birth weight (TLBW). • PM{sub 2.5} effects on TLBW are shown to vary spatially across urban LA County. • Modeling spatial dependency of PM{sub 2.5} health effects may identify effect 'hotspots'. • Birth outcomes studies should consider the spatial dependency of PM{sub 2.5} effects.« less

Uncertainty in Random Forests: What does it mean in a spatial context?

NASA Astrophysics Data System (ADS)

Klump, Jens; Fouedjio, Francky

2017-04-01

Geochemical surveys are an important part of exploration for mineral resources and in environmental studies. The samples and chemical analyses are often laborious and difficult to obtain and therefore come at a high cost. As a consequence, these surveys are characterised by datasets with large numbers of variables but relatively few data points when compared to conventional big data problems. With more remote sensing platforms and sensor networks being deployed, large volumes of auxiliary data of the surveyed areas are becoming available. The use of these auxiliary data has the potential to improve the prediction of chemical element concentrations over the whole study area. Kriging is a well established geostatistical method for the prediction of spatial data but requires significant pre-processing and makes some basic assumptions about the underlying distribution of the data. Some machine learning algorithms, on the other hand, may require less data pre-processing and are non-parametric. In this study we used a dataset provided by Kirkwood et al. [1] to explore the potential use of Random Forest in geochemical mapping. We chose Random Forest because it is a well understood machine learning method and has the advantage that it provides us with a measure of uncertainty. By comparing Random Forest to Kriging we found that both methods produced comparable maps of estimated values for our variables of interest. Kriging outperformed Random Forest for variables of interest with relatively strong spatial correlation. The measure of uncertainty provided by Random Forest seems to be quite different to the measure of uncertainty provided by Kriging. In particular, the lack of spatial context can give misleading results in areas without ground truth data. In conclusion, our preliminary results show that the model driven approach in geostatistics gives us more reliable estimates for our target variables than Random Forest for variables with relatively strong spatial correlation. However, in cases of weak spatial correlation Random Forest, as a nonparametric method, may give the better results once we have a better understanding of the meaning of its uncertainty measures in a spatial context. References [1] Kirkwood, C., M. Cave, D. Beamish, S. Grebby, and A. Ferreira (2016), A machine learning approach to geochemical mapping, Journal of Geochemical Exploration, 163, 28-40, doi:10.1016/j.gexplo.2016.05.003.

Relative importance of management, meteorological and environmental factors in the spatial distribution of Fasciola hepatica in dairy cattle in a temperate climate zone.

PubMed

Bennema, S C; Ducheyne, E; Vercruysse, J; Claerebout, E; Hendrickx, G; Charlier, J

2011-02-01

Fasciola hepatica, a trematode parasite with a worldwide distribution, is the cause of important production losses in the dairy industry. Diagnosis is hampered by the fact that the infection is mostly subclinical. To increase awareness and develop regionally adapted control methods, knowledge on the spatial distribution of economically important infection levels is needed. Previous studies modelling the spatial distribution of F. hepatica are mostly based on single cross-sectional samplings and have focussed on climatic and environmental factors, often ignoring management factors. This study investigated the associations between management, climatic and environmental factors affecting the spatial distribution of infection with F. hepatica in dairy herds in a temperate climate zone (Flanders, Belgium) over three consecutive years. A bulk-tank milk antibody ELISA was used to measure F. hepatica infection levels in a random sample of 1762 dairy herds in the autumns of 2006, 2007 and 2008. The infection levels were included in a Geographic Information System together with meteorological, environmental and management parameters. Logistic regression models were used to determine associations between possible risk factors and infection levels. The prevalence and spatial distribution of F. hepatica was relatively stable, with small interannual differences in prevalence and location of clusters. The logistic regression model based on both management and climatic/environmental factors included the factors: annual rainfall, mowing of pastures, proportion of grazed grass in the diet and length of grazing season as significant predictors and described the spatial distribution of F. hepatica better than the model based on climatic/environmental factors only (annual rainfall, elevation and slope, soil type), with an Area Under the Curve of the Receiver Operating Characteristic of 0.68 compared with 0.62. The results indicate that in temperate climate zones without large climatic and environmental variation, management factors affect the spatial distribution of F. hepatica, and should be included in future spatial distribution models. Copyright © 2010 Australian Society for Parasitology Inc. Published by Elsevier Ltd. All rights reserved.

Tropical forest carbon balance: effects of field- and satellite-based mortality regimes on the dynamics and the spatial structure of Central Amazon forest biomass

NASA Astrophysics Data System (ADS)

Di Vittorio, Alan V.; Negrón-Juárez, Robinson I.; Higuchi, Niro; Chambers, Jeffrey Q.

2014-03-01

Debate continues over the adequacy of existing field plots to sufficiently capture Amazon forest dynamics to estimate regional forest carbon balance. Tree mortality dynamics are particularly uncertain due to the difficulty of observing large, infrequent disturbances. A recent paper (Chambers et al 2013 Proc. Natl Acad. Sci. 110 3949-54) reported that Central Amazon plots missed 9-17% of tree mortality, and here we address ‘why’ by elucidating two distinct mortality components: (1) variation in annual landscape-scale average mortality and (2) the frequency distribution of the size of clustered mortality events. Using a stochastic-empirical tree growth model we show that a power law distribution of event size (based on merged plot and satellite data) is required to generate spatial clustering of mortality that is consistent with forest gap observations. We conclude that existing plots do not sufficiently capture losses because their placement, size, and longevity assume spatially random mortality, while mortality is actually distributed among differently sized events (clusters of dead trees) that determine the spatial structure of forest canopies.

[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.

Concise biomarker for spatial-temporal change in three-dimensional ultrasound measurement of carotid vessel wall and plaque thickness based on a graph-based random walk framework: Towards sensitive evaluation of response to therapy.

PubMed

Chiu, Bernard; Chen, Weifu; Cheng, Jieyu

2016-12-01

Rapid progression in total plaque area and volume measured from ultrasound images has been shown to be associated with an elevated risk of cardiovascular events. Since atherosclerosis is focal and predominantly occurring at the bifurcation, biomarkers that are able to quantify the spatial distribution of vessel-wall-plus-plaque thickness (VWT) change may allow for more sensitive detection of treatment effect. The goal of this paper is to develop simple and sensitive biomarkers to quantify the responsiveness to therapies based on the spatial distribution of VWT-Change on the entire 2D carotid standardized map previously described. Point-wise VWT-Changes computed for each patient were reordered lexicographically to a high-dimensional data node in a graph. A graph-based random walk framework was applied with the novel Weighted Cosine (WCos) similarity function introduced, which was tailored for quantification of responsiveness to therapy. The converging probability of each data node to the VWT regression template in the random walk process served as a scalar descriptor for VWT responsiveness to treatment. The WCos-based biomarker was 14 times more sensitive than the mean VWT-Change in discriminating responsive and unresponsive subjects based on the p-values obtained in T-tests. The proposed framework was extended to quantify where VWT-Change occurred by including multiple VWT-Change distribution templates representing focal changes at different regions. Experimental results show that the framework was effective in classifying carotid arteries with focal VWT-Change at different locations and may facilitate future investigations to correlate risk of cardiovascular events with the location where focal VWT-Change occurs. Copyright © 2016 Elsevier Ltd. All rights reserved.

A New Global LAI Product and Its Use for Terrestrial Carbon Cycle Estimation

NASA Astrophysics Data System (ADS)

Chen, J. M.; Liu, R.; Ju, W.; Liu, Y.

2014-12-01

For improving the estimation of the spatio-temporal dynamics of the terrestrial carbon cycle, a new time series of the leaf area index (LAI) is generated for the global land surface at 8 km resolution from 1981 to 2012 by combining AVHRR and MODIS satellite data. This product differs from existing LAI products in the following two aspects: (1) the non-random spatial distribution of leaves with the canopy is considered, and (2) the seasonal variation of the vegetation background is included. The non-randomness of the leaf spatial distribution in the canopy is considered using the second vegetation structural parameter named clumping index (CI), which quantifies the deviation of the leaf spatial distribution from the random case. Using the MODIS Bidirectional Reflectance Distribution Function product, a global map of CI is produced at 500 m resolution. In our LAI algorithm, CI is used to convert the effective LAI obtained from mono-angle remote sensing into the true LAI, otherwise LAI would be considerably underestimated. The vegetation background is soil in crop, grass and shrub but includes soil, grass, moss, and litter in forests. Through processing a large volume of MISR data from 2000 to 2010, monthly red and near-infrared reflectances of the vegetation background is mapped globally at 1 km resolution. This new LAI product has been validated extensively using ground-based LAI measurements distributed globally. In carbon cycle modeling, the use of CI in addition to LAI allows for accurate separation of sunlit and shaded leaves as an important step in terrestrial photosynthesis and respiration modeling. Carbon flux measurements over 100 sites over the globe are used to validate an ecosystem model named Boreal Ecosystem Productivity Simulator (BEPS). The validated model is run globally at 8 km resolution for the period from 1981 to 2012 using the LAI product and other spatial datasets. The modeled results suggest that changes in vegetation structure as quantified by LAI do not contribute significantly to the increasing trend in carbon sink over the last 32 years. The increases in atmospheric CO2 concentration and nitrogen deposition are found to be the major causes for the increases in plant productivity and carbon sink over the last 32 years.

Spatial distribution of soil contaminated with Toxoplasma gondii oocysts in relation to the distribution and use of domestic cat defecation sites on dairy farms.

PubMed

Simon, J A; Kurdzielewicz, S; Jeanniot, E; Dupuis, E; Marnef, F; Aubert, D; Villena, I; Poulle, M-L

2017-05-01

Little information is available on the relationship between the spatial distribution of zoonotic parasites in soil and the pattern of hosts' faeces deposition at a local scale. In this study, the spatial distribution of soil contaminated by the parasite Toxoplasma gondii was investigated in relation to the distribution and use of the defecation sites of its definitive host, the domestic cat (Felis catus). The study was conducted on six dairy farms with a high number of cats (seven to 30 cats). During regular visits to the farms over a 10month period, the cat population and cat defecation sites (latrines and sites of scattered faeces) on each farm were systematically surveyed. During the last visit, 561 soil samples were collected from defecation sites and random points, and these samples were searched for T. gondii DNA using real-time quantitative PCR. Depending on the farm, T. gondii DNA was detected in 37.7-66.3% of the soil samples. The proportion of contaminated samples at a farm was positively correlated with the rate of new cat latrines replacing former cat latrines, suggesting that inconstancy in use of a latrine by cats affects the distribution of T. gondii in soil. On the farms, known cat defecation sites were significantly more often contaminated than random points, but 25-62.5% of the latter were also found to be contaminated. Lastly, the proportion of positive T. gondii samples in latrines was related to the proximity of the cats' main feeding and resting sites on the farms. This study demonstrates that T. gondii can be widely distributed in farm soil despite the heterogeneous distribution of cat faeces. This supports the hypothesis that farms are hotspot areas for the risk of T. gondii oocyst-induced infection in rural environments. Copyright © 2017 Australian Society for Parasitology. Published by Elsevier Ltd. All rights reserved.

Analysis of a Spatial Point Pattern: Examining the Damage to Pavement and Pipes in Santa Clara Valley Resulting from the Loma Prieta Earthquake

USGS Publications Warehouse

Phelps, G.A.

2008-01-01

This report describes some simple spatial statistical methods to explore the relationships of scattered points to geologic or other features, represented by points, lines, or areas. It also describes statistical methods to search for linear trends and clustered patterns within the scattered point data. Scattered points are often contained within irregularly shaped study areas, necessitating the use of methods largely unexplored in the point pattern literature. The methods take advantage of the power of modern GIS toolkits to numerically approximate the null hypothesis of randomly located data within an irregular study area. Observed distributions can then be compared with the null distribution of a set of randomly located points. The methods are non-parametric and are applicable to irregularly shaped study areas. Patterns within the point data are examined by comparing the distribution of the orientation of the set of vectors defined by each pair of points within the data with the equivalent distribution for a random set of points within the study area. A simple model is proposed to describe linear or clustered structure within scattered data. A scattered data set of damage to pavement and pipes, recorded after the 1989 Loma Prieta earthquake, is used as an example to demonstrate the analytical techniques. The damage is found to be preferentially located nearer a set of mapped lineaments than randomly scattered damage, suggesting range-front faulting along the base of the Santa Cruz Mountains is related to both the earthquake damage and the mapped lineaments. The damage also exhibit two non-random patterns: a single cluster of damage centered in the town of Los Gatos, California, and a linear alignment of damage along the range front of the Santa Cruz Mountains, California. The linear alignment of damage is strongest between 45? and 50? northwest. This agrees well with the mean trend of the mapped lineaments, measured as 49? northwest.

A Geostatistical Scaling Approach for the Generation of Non Gaussian Random Variables and Increments

NASA Astrophysics Data System (ADS)

Guadagnini, Alberto; Neuman, Shlomo P.; Riva, Monica; Panzeri, Marco

2016-04-01

We address manifestations of non-Gaussian statistical scaling displayed by many variables, Y, and their (spatial or temporal) increments. Evidence of such behavior includes symmetry of increment distributions at all separation distances (or lags) with sharp peaks and heavy tails which tend to decay asymptotically as lag increases. Variables reported to exhibit such distributions include quantities of direct relevance to hydrogeological sciences, e.g. porosity, log permeability, electrical resistivity, soil and sediment texture, sediment transport rate, rainfall, measured and simulated turbulent fluid velocity, and other. No model known to us captures all of the documented statistical scaling behaviors in a unique and consistent manner. We recently proposed a generalized sub-Gaussian model (GSG) which reconciles within a unique theoretical framework the probability distributions of a target variable and its increments. We presented an algorithm to generate unconditional random realizations of statistically isotropic or anisotropic GSG functions and illustrated it in two dimensions. In this context, we demonstrated the feasibility of estimating all key parameters of a GSG model underlying a single realization of Y by analyzing jointly spatial moments of Y data and corresponding increments. Here, we extend our GSG model to account for noisy measurements of Y at a discrete set of points in space (or time), present an algorithm to generate conditional realizations of corresponding isotropic or anisotropic random field, and explore them on one- and two-dimensional synthetic test cases.

Fourier transform infrared spectroscopy microscopic imaging classification based on spatial-spectral features

NASA Astrophysics Data System (ADS)

Liu, Lian; Yang, Xiukun; Zhong, Mingliang; Liu, Yao; Jing, Xiaojun; Yang, Qin

2018-04-01

The discrete fractional Brownian incremental random (DFBIR) field is used to describe the irregular, random, and highly complex shapes of natural objects such as coastlines and biological tissues, for which traditional Euclidean geometry cannot be used. In this paper, an anisotropic variable window (AVW) directional operator based on the DFBIR field model is proposed for extracting spatial characteristics of Fourier transform infrared spectroscopy (FTIR) microscopic imaging. Probabilistic principal component analysis first extracts spectral features, and then the spatial features of the proposed AVW directional operator are combined with the former to construct a spatial-spectral structure, which increases feature-related information and helps a support vector machine classifier to obtain more efficient distribution-related information. Compared to Haralick’s grey-level co-occurrence matrix, Gabor filters, and local binary patterns (e.g. uniform LBPs, rotation-invariant LBPs, uniform rotation-invariant LBPs), experiments on three FTIR spectroscopy microscopic imaging datasets show that the proposed AVW directional operator is more advantageous in terms of classification accuracy, particularly for low-dimensional spaces of spatial characteristics.

Retention capacity of correlated surfaces.

PubMed

Schrenk, K J; Araújo, N A M; Ziff, R M; Herrmann, H J

2014-06-01

We extend the water retention model [C. L. Knecht et al., Phys. Rev. Lett. 108, 045703 (2012)] to correlated random surfaces. We find that the retention capacity of discrete random landscapes is strongly affected by spatial correlations among the heights. This phenomenon is related to the emergence of power-law scaling in the lake volume distribution. We also solve the uncorrelated case exactly for a small lattice and present bounds on the retention of uncorrelated landscapes.

A geometric theory for Lévy distributions

NASA Astrophysics Data System (ADS)

Eliazar, Iddo

2014-08-01

Lévy distributions are of prime importance in the physical sciences, and their universal emergence is commonly explained by the Generalized Central Limit Theorem (CLT). However, the Generalized CLT is a geometry-less probabilistic result, whereas physical processes usually take place in an embedding space whose spatial geometry is often of substantial significance. In this paper we introduce a model of random effects in random environments which, on the one hand, retains the underlying probabilistic structure of the Generalized CLT and, on the other hand, adds a general and versatile underlying geometric structure. Based on this model we obtain geometry-based counterparts of the Generalized CLT, thus establishing a geometric theory for Lévy distributions. The theory explains the universal emergence of Lévy distributions in physical settings which are well beyond the realm of the Generalized CLT.

A geometric theory for Lévy distributions

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

Eliazar, Iddo, E-mail: eliazar@post.tau.ac.il

2014-08-15

Lévy distributions are of prime importance in the physical sciences, and their universal emergence is commonly explained by the Generalized Central Limit Theorem (CLT). However, the Generalized CLT is a geometry-less probabilistic result, whereas physical processes usually take place in an embedding space whose spatial geometry is often of substantial significance. In this paper we introduce a model of random effects in random environments which, on the one hand, retains the underlying probabilistic structure of the Generalized CLT and, on the other hand, adds a general and versatile underlying geometric structure. Based on this model we obtain geometry-based counterparts ofmore » the Generalized CLT, thus establishing a geometric theory for Lévy distributions. The theory explains the universal emergence of Lévy distributions in physical settings which are well beyond the realm of the Generalized CLT.« less

Temporal and spatial variability in thalweg profiles of a gravel-bed river

USGS Publications Warehouse

Madej, Mary Ann

1999-01-01

This study used successive longitudinal thalweg profiles in gravel-bed rivers to monitor changes in bed topography following floods and associated large sediment inputs. Variations in channel bed elevations, distributions of residual water depths, percentage of channel length occupied by riffles, and a spatial autocorrelation coefficient (Moran's I) were used to quantify changes in morphological diversity and spatial structure in Redwood Creek basin, northwestern California. Bed topography in Redwood Creek and its major tributaries consists primarily of a series of pools and riffles. The size, frequency and spatial distribution of the pools and riffles have changed significantly during the past 20 years. Following large floods and high sediment input in Redwood Creek and its tributaries in 1975, variation in channel bed elevations was low and the percentage of the channel length occupied by riffles was high. Over the next 20 years, variation in bed elevations increased while the length of channel occupied by riffles decreased. An index [(standard deviation of residual water depth/bankfull depth) × 100] was developed to compare variations in bed elevation over a range of stream sizes, with a higher index being indicative of greater morphological diversity. Spatial autocorrelation in the bed elevation data was apparent at both fine and coarse scales in many of the thalweg profiles and the observed spatial pattern of bed elevations was found to be related to the dominant channel material and the time since disturbance. River reaches in which forced pools dominated, and in which large woody debris and bed particles could not be easily mobilized, exhibited a random distribution of bed elevations. In contrast, in reaches where alternate bars dominated, and both wood and gravel were readily transported, regularly spaced bed topography developed at a spacing that increased with time since disturbance. This pattern of regularly spaced bed features was reversed following a 12-year flood when bed elevations became more randomly arranged.

Inverse modelling of fluvial sediment connectivity identifies characteristics and spatial distribution of sediment sources in a large river network.

NASA Astrophysics Data System (ADS)

Schmitt, R. J. P.; Bizzi, S.; Kondolf, G. M.; Rubin, Z.; Castelletti, A.

2016-12-01

Field and laboratory evidence indicates that the spatial distribution of transport in both alluvial and bedrock rivers is an adaptation to sediment supply. Sediment supply, in turn, depends on spatial distribution and properties (e.g., grain sizes and supply rates) of individual sediment sources. Analyzing the distribution of transport capacity in a river network could hence clarify the spatial distribution and properties of sediment sources. Yet, challenges include a) identifying magnitude and spatial distribution of transport capacity for each of multiple grain sizes being simultaneously transported, and b) estimating source grain sizes and supply rates, both at network scales. Herein, we approach the problem of identifying the spatial distribution of sediment sources and the resulting network sediment fluxes in a major, poorly monitored tributary (80,000 km2) of the Mekong. Therefore, we apply the CASCADE modeling framework (Schmitt et al. (2016)). CASCADE calculates transport capacities and sediment fluxes for multiple grainsizes on the network scale based on remotely-sensed morphology and modelled hydrology. CASCADE is run in an inverse Monte Carlo approach for 7500 random initializations of source grain sizes. In all runs, supply of each source is inferred from the minimum downstream transport capacity for the source grain size. Results for each realization are compared to sparse available sedimentary records. Only 1 % of initializations reproduced the sedimentary record. Results for these realizations revealed a spatial pattern in source supply rates, grain sizes, and network sediment fluxes that correlated well with map-derived patterns in lithology and river-morphology. Hence, we propose that observable river hydro-morphology contains information on upstream source properties that can be back-calculated using an inverse modeling approach. Such an approach could be coupled to more detailed models of hillslope processes in future to derive integrated models of hillslope production and fluvial transport processes, which is particularly useful to identify sediment provenance in poorly monitored river basins.

Data-driven mapping of the potential mountain permafrost distribution.

PubMed

Deluigi, Nicola; Lambiel, Christophe; Kanevski, Mikhail

2017-07-15

Existing mountain permafrost distribution models generally offer a good overview of the potential extent of this phenomenon at a regional scale. They are however not always able to reproduce the high spatial discontinuity of permafrost at the micro-scale (scale of a specific landform; ten to several hundreds of meters). To overcome this lack, we tested an alternative modelling approach using three classification algorithms belonging to statistics and machine learning: Logistic regression, Support Vector Machines and Random forests. These supervised learning techniques infer a classification function from labelled training data (pixels of permafrost absence and presence) with the aim of predicting the permafrost occurrence where it is unknown. The research was carried out in a 588km 2 area of the Western Swiss Alps. Permafrost evidences were mapped from ortho-image interpretation (rock glacier inventorying) and field data (mainly geoelectrical and thermal data). The relationship between selected permafrost evidences and permafrost controlling factors was computed with the mentioned techniques. Classification performances, assessed with AUROC, range between 0.81 for Logistic regression, 0.85 with Support Vector Machines and 0.88 with Random forests. The adopted machine learning algorithms have demonstrated to be efficient for permafrost distribution modelling thanks to consistent results compared to the field reality. The high resolution of the input dataset (10m) allows elaborating maps at the micro-scale with a modelled permafrost spatial distribution less optimistic than classic spatial models. Moreover, the probability output of adopted algorithms offers a more precise overview of the potential distribution of mountain permafrost than proposing simple indexes of the permafrost favorability. These encouraging results also open the way to new possibilities of permafrost data analysis and mapping. Copyright © 2017 Elsevier B.V. All rights reserved.

Spatial organization of surface nanobubbles and its implications in their formation process.

PubMed

Lhuissier, Henri; Lohse, Detlef; Zhang, Xuehua

2014-02-21

We study the size and spatial distribution of surface nanobubbles formed by the solvent exchange method to gain insight into the mechanism of their formation. The analysis of Atomic Force Microscopy (AFM) images of nanobubbles formed on a hydrophobic surface reveals that the nanobubbles are not randomly located, which we attribute to the role of the history of nucleation during the formation. Moreover, the size of each nanobubble is found to be strongly correlated with the area of the bubble-depleted zone around it. The precise correlation suggests that the nanobubbles grow by diffusion of the gas from the bulk rather than by diffusion of the gas adsorbed on the surface. Lastly, the size distribution of the nanobubbles is found to be well described by a log-normal distribution.

Community-wide spatial and temporal discordances of seed-seedling shadows in a tropical rainforest.

PubMed

Rother, Débora Cristina; Pizo, Marco Aurélio; Siqueira, Tadeu; Rodrigues, Ricardo Ribeiro; Jordano, Pedro

2015-01-01

Several factors decrease plant survival throughout their lifecycles. Among them, seed dispersal limitation may play a major role by resulting in highly aggregated (contagious) seed and seedling distributions entailing increased mortality. The arrival of seeds, furthermore, may not match suitable environments for seed survival and, consequently, for seedling establishment. In this study, we investigated spatio-temporal patterns of seed and seedling distribution in contrasting microhabitats (bamboo and non-bamboo stands) from the Brazilian Atlantic Forest. Spatial distribution patterns, spatial concordance between seed rain and seedling recruitment between subsequent years in two fruiting seasons (2004-2005 and 2007-2009), and the relation between seeds and seedlings with environmental factors were examined within a spatially-explicit framework. Density and species richness of both seeds and seedlings were randomly distributed in non-bamboo stands, but showed significant clustering in bamboo stands. Seed and seedling distributions showed across-year inconsistency, suggesting a marked spatial decoupling of the seed and seedling stages. Generalized linear mixed effects models indicated that only seed density and seed species richness differed between stand types while accounting for variation in soil characteristics. Our analyses provide evidence of marked recruitment limitation as a result of the interplay between biotic and abiotic factors. Because bamboo stands promote heterogeneity in the forest, they are important components of the landscape. However, at high densities, bamboos may limit recruitment for the plant community by imposing marked discordances of seed arrival and early seedling recruitment.

Quantifying evenly distributed states in exclusion and nonexclusion processes

NASA Astrophysics Data System (ADS)

Binder, Benjamin J.; Landman, Kerry A.

2011-04-01

Spatial-point data sets, generated from a wide range of physical systems and mathematical models, can be analyzed by counting the number of objects in equally sized bins. We find that the bin counts are related to the Pólya distribution. New measures are developed which indicate whether or not a spatial data set, generated from an exclusion process, is at its most evenly distributed state, the complete spatial randomness (CSR) state. To this end, we define an index in terms of the variance between the bin counts. Limiting values of the index are determined when objects have access to the entire domain and when there are subregions of the domain that are inaccessible to objects. Using three case studies (Lagrangian fluid particles in chaotic laminar flows, cellular automata agents in discrete models, and biological cells within colonies), we calculate the indexes and verify that our theoretical CSR limit accurately predicts the state of the system. These measures should prove useful in many biological applications.

[Spatial structural characteristics of natural Populus davidiana - Betula platyphylla secondary forest].

PubMed

Shao, Fang-Li; Yu, Xin-Xiao; Song, Si-Ming; Zhao, Yang

2011-11-01

This paper analyzed the spatial structural characteristics of natural Populus davidiana - Betula platyphylla secondary forest in a 4 hm2 plot of Mulan Paddock, based on the diameter distribution and the spatial structure parameters mingling degree, neighborhood comparison, and angle index. In the forest, the diameter distribution of the stands presented as an inverse 'J' curve, the average mingling degree was 0.4, with the individuals at weak and zero mingling degree reached 51.6%, and the average mingling degree of P. davidiana and B. platyphylla was 0.25 and 0.39, respectively. The neighborhood comparison based on the diameter at breast height (DBH) and tree height was almost the same, suggesting that the P. davidiana and B. platyphylla were in the transition state from subdominant to middle. The horizontal distribution pattern had a close relation to the minimum measured DBH, being clustered when the DBH was > or = 1 cm and < 6 cm, and random when the DBH was > or = 6 cm.

Anisotropy in Fracking: A Percolation Model for Observed Microseismicity

NASA Astrophysics Data System (ADS)

Norris, J. Quinn; Turcotte, Donald L.; Rundle, John B.

2015-01-01

Hydraulic fracturing (fracking), using high pressures and a low viscosity fluid, allow the extraction of large quantiles of oil and gas from very low permeability shale formations. The initial production of oil and gas at depth leads to high pressures and an extensive distribution of natural fractures which reduce the pressures. With time these fractures heal, sealing the remaining oil and gas in place. High volume fracking opens the healed fractures allowing the oil and gas to flow to horizontal production wells. We model the injection process using invasion percolation. We use a 2D square lattice of bonds to model the sealed natural fractures. The bonds are assigned random strengths and the fluid, injected at a point, opens the weakest bond adjacent to the growing cluster of opened bonds. Our model exhibits burst dynamics in which the clusters extend rapidly into regions with weak bonds. We associate these bursts with the microseismic activity generated by fracking injections. A principal object of this paper is to study the role of anisotropic stress distributions. Bonds in the y-direction are assigned higher random strengths than bonds in the x-direction. We illustrate the spatial distribution of clusters and the spatial distribution of bursts (small earthquakes) for several degrees of anisotropy. The results are compared with observed distributions of microseismicity in a fracking injection. Both our bursts and the observed microseismicity satisfy Gutenberg-Richter frequency-size statistics.

Random Distribution Pattern and Non-adaptivity of Genome Size in a Highly Variable Population of Festuca pallens

PubMed Central

Šmarda, Petr; Bureš, Petr; Horová, Lucie

2007-01-01

Background and Aims The spatial and statistical distribution of genome sizes and the adaptivity of genome size to some types of habitat, vegetation or microclimatic conditions were investigated in a tetraploid population of Festuca pallens. The population was previously documented to vary highly in genome size and is assumed as a model for the study of the initial stages of genome size differentiation. Methods Using DAPI flow cytometry, samples were measured repeatedly with diploid Festuca pallens as the internal standard. Altogether 172 plants from 57 plots (2·25 m2), distributed in contrasting habitats over the whole locality in South Moravia, Czech Republic, were sampled. The differences in DNA content were confirmed by the double peaks of simultaneously measured samples. Key Results At maximum, a 1·115-fold difference in genome size was observed. The statistical distribution of genome sizes was found to be continuous and best fits the extreme (Gumbel) distribution with rare occurrences of extremely large genomes (positive-skewed), as it is similar for the log-normal distribution of the whole Angiosperms. Even plants from the same plot frequently varied considerably in genome size and the spatial distribution of genome sizes was generally random and unautocorrelated (P > 0·05). The observed spatial pattern and the overall lack of correlations of genome size with recognized vegetation types or microclimatic conditions indicate the absence of ecological adaptivity of genome size in the studied population. Conclusions These experimental data on intraspecific genome size variability in Festuca pallens argue for the absence of natural selection and the selective non-significance of genome size in the initial stages of genome size differentiation, and corroborate the current hypothetical model of genome size evolution in Angiosperms (Bennetzen et al., 2005, Annals of Botany 95: 127–132). PMID:17565968

Prevalence and spatial distribution of Theileria parva in cattle under crop-livestock farming systems in Tororo District, Eastern Uganda

PubMed Central

2014-01-01

Background Tick-borne diseases (TBDs) present a major economic burden to communities across East Africa. Farmers in East Africa must use acaracides to target ticks and prevent transmission of tick-borne diseases such as anaplasmosis, babesiosis, cowdriosis and theileriosis; the major causes of cattle mortality and morbidity. The costs of controlling East Coast Fever (ECF), caused by Theileria parva, in Uganda are significant and measures taken to control ticks, to be cost-effective, should take into account the burden of disease. The aim of the present work was to estimate the burden presented by T. parva and its spatial distribution in a crop-livestock production system in Eastern Uganda. Methods A cross sectional study was carried out to determine the prevalence and spatial distribution of T. parva in Tororo District, Uganda. Blood samples were taken from all cattle (n: 2,658) in 22 randomly selected villages across Tororo District from September to December 2011. Samples were analysed by PCR and T. parva prevalence and spatial distribution determined. Results The overall prevalence of T. parva was found to be 5.3%. Herd level prevalence ranged from 0% to 21% with majority of the infections located in the North, North-Eastern and South-Eastern parts of Tororo District. No statistically significant differences in risk of infection were found between age classes, sex and cattle breed. Conclusions T. parva infection is widely distributed in Tororo District, Uganda. The prevalence and distribution of T. parva is most likely determined by spatial distribution of R. appendiculatus, restricted grazing of calves and preferential tick control targeting draft animals. PMID:24589227

Geographic Distribution of Trauma Centers and Injury Related Mortality in the United States

PubMed Central

Brown, Joshua B.; Rosengart, Matthew R.; Billiar, Timothy R.; Peitzman, Andrew B.; Sperry, Jason L.

2015-01-01

Background Regionalized trauma care improves outcomes; however access to care is not uniform across the US. The objective was to evaluate whether geographic distribution of trauma centers correlates with injury mortality across state trauma systems. Methods Level I/II trauma centers in the contiguous US were mapped. State-level age-adjusted injury fatality rates/100,000people were obtained and evaluated for spatial autocorrelation. Nearest neighbor ratios (NNR) were generated for each state. A NNR<1 indicates clustering, while NNR>1 indicates dispersion. NNR were tested for difference from random geographic distribution. Fatality rates and NNR were examined for correlation. Fatality rates were compared between states with trauma center clustering versus dispersion. Trauma center distribution and population density were evaluated. Spatial-lag regression determined the association between fatality rate and NNR, controlling for state-level demographics, population density, injury severity, trauma system resources, and socioeconomic factors. Results Fatality rates were spatially autocorrelated (Moran's I=0.35, p<0.01). Nine states had a clustered pattern (median NNR 0.55, IQR 0.48–0.60), 22 had a dispersed pattern (median NNR 2.00, IQR 1.68–3.99), and 10 had a random pattern (median NNR 0.90, IQR 0.85–1.00) of trauma center distribution. Fatality rate and NNR were correlated (ρ=0.34, p=0.03). Clustered states had a lower median injury fatality rate compared to dispersed states (56.9 [IQR 46.5–58.9] versus 64.9 [IQR 52.5–77.1], p=0.04). Dispersed compared to clustered states had more counties without a trauma center that had higher population density than counties with a trauma center (5.7% versus 1.2%, p<0.01). Spatial-lag regression demonstrated fatality rates increased 0.02/100,000persons for each unit increase in NNR (p<0.01). Conclusions Geographic distribution of trauma centers correlates with injury mortality, with more clustered state trauma centers associated with lower fatality rates. This may be a result of access relative to population density. These results may have implications for trauma system planning and requires further study to investigate underlying mechanisms PMID:26517780

Synchronization of an ensemble of oscillators regulated by their spatial movement.

PubMed

Sarkar, Sumantra; Parmananda, P

2010-12-01

Synchronization for a collection of oscillators residing in a finite two dimensional plane is explored. The coupling between any two oscillators in this array is unidirectional, viz., master-slave configuration. Initially the oscillators are distributed randomly in space and their autonomous time-periods follow a Gaussian distribution. The duty cycles of these oscillators, which work under an on-off scenario, are normally distributed as well. It is realized that random hopping of oscillators is a necessary condition for observing global synchronization in this ensemble of oscillators. Global synchronization in the context of the present work is defined as the state in which all the oscillators are rendered identical. Furthermore, there exists an optimal amplitude of random hopping for which the attainment of this global synchronization is the fastest. The present work is deemed to be of relevance to the synchronization phenomena exhibited by pulse coupled oscillators such as a collection of fireflies. © 2010 American Institute of Physics.

Spatial study of homicide rates in the state of Bahia, Brazil, 1996-2010

PubMed Central

de Souza, Tiago Oliveira; Pinto, Liana Wernersbach; de Souza, Edinilsa Ramos

2014-01-01

OBJECTIVE To analyze the spatial distribution of homicide mortality in the state of Bahia, Northeastern Brazil. METHODS Ecological study of the 15 to 39-year old male population in the state of Bahia in the period 1996-2010. Data from the Mortality Information System, relating to homicide (X85-Y09) and population estimates from the Brazilian Institute of Geography and Statistics were used. The existence of spatial correlation, the presence of clusters and critical areas of the event studied were analyzed using Moran’s I Global and Local indices. RESULTS A non-random spatial pattern was observed in the distribution of rates, as was the presence of three clusters, the first in the north health district, the second in the eastern region, and the third cluster included townships in the south and the far south of Bahia. CONCLUSIONS The homicide mortality in the three different critical areas requires further studies that consider the socioeconomic, cultural and environmental characteristics in order to guide specific preventive and interventionist practices. PMID:25119942

Examining reference frame interaction in spatial memory using a distribution analysis.

PubMed

Street, Whitney N; Wang, Ranxiao Frances

2016-02-01

Previous research showed competition among reference frames in spatial attention and language. The present studies developed a new distribution analysis to examine reference frame interactions in spatial memory. Participants viewed virtual arrays of colored pegs and were instructed to remember them either from their own perspective or from the perspective aligned with the rectangular floor. Then they made judgments of relative directions from their respective encoding orientation. Those taking the floor-axis perspective showed systematic bias in the signed errors toward their egocentric perspective, while those taking their own perspective showed no systematic bias, both for random and symmetrical object arrays. The bias toward the egocentric perspective was observed when learning a real symmetric regular object array with strong environmental cues for the aligned axis. These results indicate automatic processing of the self reference while taking the floor-axis perspective but not vice versa, and suggest that research on spatial memory needs to consider the implications of competition effects in reference frame use.

Spatial analysis of the distribution of Spodoptera frugiperda (J.E. Smith) (Lepidoptera: Noctuidae) and losses in maize crop productivity using geostatistics.

PubMed

Farias, Paulo R S; Barbosa, José C; Busoli, Antonio C; Overal, William L; Miranda, Vicente S; Ribeiro, Susane M

2008-01-01

The fall armyworm, Spodoptera frugiperda (J.E. Smith), is one of the chief pests of maize in the Americas. The study of its spatial distribution is fundamental for designing correct control strategies, improving sampling methods, determining actual and potential crop losses, and adopting precise agricultural techniques. In São Paulo state, Brazil, a maize field was sampled at weekly intervals, from germination through harvest, for caterpillar densities, using quadrates. In each of 200 quadrates, 10 plants were sampled per week. Harvest weights were obtained in the field for each quadrate, and ear diameters and lengths were also sampled (15 ears per quadrate) and used to estimate potential productivity of the quadrate. Geostatistical analyses of caterpillar densities showed greatest ranges for small caterpillars when semivariograms were adjusted for a spherical model that showed greatest fit. As the caterpillars developed in the field, their spatial distribution became increasingly random, as shown by a model adjusted to a straight line, indicating a lack of spatial dependence among samples. Harvest weight and ear length followed the spherical model, indicating the existence of spatial variability of the production parameters in the maize field. Geostatistics shows promise for the application of precise methods in the integrated control of pests.

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

PubMed Central

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

2012-01-01

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

Discovery of Non-random Spatial Distribution of Impacts in the Stardust Cometary Collector

NASA Technical Reports Server (NTRS)

Horz, Friedrich; Westphal, Andrew J.; Gainsforth, Zack; Borg, Janet; Djouadi, Zahia; Bridges, John; Franchi, Ian; Brownlee, Donald E.; Cheng. Andrew F.; Clark, Benton C.;

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.

Characterizing spatial heterogeneity based on the b-value and fractal analyses of the 2015 Nepal earthquake sequence

NASA Astrophysics Data System (ADS)

Nampally, Subhadra; Padhy, Simanchal; Dimri, Vijay P.

2018-01-01

The nature of spatial distribution of heterogeneities in the source area of the 2015 Nepal earthquake is characterized based on the seismic b-value and fractal analysis of its aftershocks. The earthquake size distribution of aftershocks gives a b-value of 1.11 ± 0.08, possibly representing the highly heterogeneous and low stress state of the region. The aftershocks exhibit a fractal structure characterized by a spectrum of generalized dimensions, Dq varying from D2 = 1.66 to D22 = 0.11. The existence of a fractal structure suggests that the spatial distribution of aftershocks is not a random phenomenon, but it self-organizes into a critical state, exhibiting a scale-independent structure governed by a power-law scaling, where a small perturbation in stress is sufficient enough to trigger aftershocks. In order to obtain the bias in fractal dimensions resulting from finite data size, we compared the multifractal spectrum for the real data and random simulations. On comparison, we found that the lower limit of bias in D2 is 0.44. The similarity in their multifractal spectra suggests the lack of long-range correlation in the data, with an only weakly multifractal or a monofractal with a single correlation dimension D2 characterizing the data. The minimum number of events required for a multifractal process with an acceptable error is discussed. We also tested for a possible correlation between changes in D2 and energy released during the earthquakes. The values of D2 rise during the two largest earthquakes (M > 7.0) in the sequence. The b- and D2 values are related by D2 = 1.45 b that corresponds to the intermediate to large earthquakes. Our results provide useful constraints on the spatial distribution of b- and D2-values, which are useful for seismic hazard assessment in the aftershock area of a large earthquake.

An intrinsic algorithm for parallel Poisson disk sampling on arbitrary surfaces.

PubMed

Ying, Xiang; Xin, Shi-Qing; Sun, Qian; He, Ying

2013-09-01

Poisson disk sampling has excellent spatial and spectral properties, and plays an important role in a variety of visual computing. Although many promising algorithms have been proposed for multidimensional sampling in euclidean space, very few studies have been reported with regard to the problem of generating Poisson disks on surfaces due to the complicated nature of the surface. This paper presents an intrinsic algorithm for parallel Poisson disk sampling on arbitrary surfaces. In sharp contrast to the conventional parallel approaches, our method neither partitions the given surface into small patches nor uses any spatial data structure to maintain the voids in the sampling domain. Instead, 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. Our algorithm guarantees that the generated Poisson disks are uniformly and randomly distributed without bias. It is worth noting that our method is intrinsic and independent of the embedding space. This intrinsic feature allows us to generate Poisson disk patterns on arbitrary surfaces in IR(n). To our knowledge, this is the first intrinsic, parallel, and accurate algorithm for surface Poisson disk sampling. Furthermore, by manipulating the spatially varying density function, we can obtain adaptive sampling easily.

Statistical parameters of random heterogeneity estimated by analysing coda waves based on finite difference method

NASA Astrophysics Data System (ADS)

Emoto, K.; Saito, T.; Shiomi, K.

2017-12-01

Short-period (<1 s) seismograms are strongly affected by small-scale (<10 km) heterogeneities in the lithosphere. In general, short-period seismograms are analysed based on the statistical method by considering the interaction between seismic waves and randomly distributed small-scale heterogeneities. Statistical properties of the random heterogeneities have been estimated by analysing short-period seismograms. However, generally, the small-scale random heterogeneity is not taken into account for the modelling of long-period (>2 s) seismograms. We found that the energy of the coda of long-period seismograms shows a spatially flat distribution. This phenomenon is well known in short-period seismograms and results from the scattering by small-scale heterogeneities. We estimate the statistical parameters that characterize the small-scale random heterogeneity by modelling the spatiotemporal energy distribution of long-period seismograms. We analyse three moderate-size earthquakes that occurred in southwest Japan. We calculate the spatial distribution of the energy density recorded by a dense seismograph network in Japan at the period bands of 8-16 s, 4-8 s and 2-4 s and model them by using 3-D finite difference (FD) simulations. Compared to conventional methods based on statistical theories, we can calculate more realistic synthetics by using the FD simulation. It is not necessary to assume a uniform background velocity, body or surface waves and scattering properties considered in general scattering theories. By taking the ratio of the energy of the coda area to that of the entire area, we can separately estimate the scattering and the intrinsic absorption effects. Our result reveals the spectrum of the random inhomogeneity in a wide wavenumber range including the intensity around the corner wavenumber as P(m) = 8πε2a3/(1 + a2m2)2, where ε = 0.05 and a = 3.1 km, even though past studies analysing higher-frequency records could not detect the corner. Finally, we estimate the intrinsic attenuation by modelling the decay rate of the energy. The method proposed in this study is suitable for quantifying the statistical properties of long-wavelength subsurface random inhomogeneity, which leads the way to characterizing a wider wavenumber range of spectra, including the corner wavenumber.

A spatial individual-based model predicting a great impact of copious sugar sources and resting sites on survival of Anopheles gambiae and malaria parasite transmission

USGS Publications Warehouse

Zhu, Lin; Qualls, Whitney A.; Marshall, John M; Arheart, Kris L.; DeAngelis, Donald L.; McManus, John W.; Traore, Sekou F.; Doumbia, Seydou; Schlein, Yosef; Muller, Gunter C.; Beier, John C.

2015-01-01

BackgroundAgent-based modelling (ABM) has been used to simulate mosquito life cycles and to evaluate vector control applications. However, most models lack sugar-feeding and resting behaviours or are based on mathematical equations lacking individual level randomness and spatial components of mosquito life. Here, a spatial individual-based model (IBM) incorporating sugar-feeding and resting behaviours of the malaria vector Anopheles gambiae was developed to estimate the impact of environmental sugar sources and resting sites on survival and biting behaviour.MethodsA spatial IBM containing An. gambiae mosquitoes and humans, as well as the village environment of houses, sugar sources, resting sites and larval habitat sites was developed. Anopheles gambiae behaviour rules were attributed at each step of the IBM: resting, host seeking, sugar feeding and breeding. Each step represented one second of time, and each simulation was set to run for 60 days and repeated 50 times. Scenarios of different densities and spatial distributions of sugar sources and outdoor resting sites were simulated and compared.ResultsWhen the number of natural sugar sources was increased from 0 to 100 while the number of resting sites was held constant, mean daily survival rate increased from 2.5% to 85.1% for males and from 2.5% to 94.5% for females, mean human biting rate increased from 0 to 0.94 bites per human per day, and mean daily abundance increased from 1 to 477 for males and from 1 to 1,428 for females. When the number of outdoor resting sites was increased from 0 to 50 while the number of sugar sources was held constant, mean daily survival rate increased from 77.3% to 84.3% for males and from 86.7% to 93.9% for females, mean human biting rate increased from 0 to 0.52 bites per human per day, and mean daily abundance increased from 62 to 349 for males and from 257 to 1120 for females. All increases were significant (P < 0.01). Survival was greater when sugar sources were randomly distributed in the whole village compared to clustering around outdoor resting sites or houses.ConclusionsIncreases in densities of sugar sources or outdoor resting sites significantly increase the survival and human biting rates of An. gambiae mosquitoes. Survival of An. gambiae is more supported by random distribution of sugar sources than clustering of sugar sources around resting sites or houses. Density and spatial distribution of natural sugar sources and outdoor resting sites modulate vector populations and human biting rates, and thus malaria parasite transmission.

A spatial individual-based model predicting a great impact of copious sugar sources and resting sites on survival of Anopheles gambiae and malaria parasite transmission.

PubMed

Zhu, Lin; Qualls, Whitney A; Marshall, John M; Arheart, Kris L; DeAngelis, Donald L; McManus, John W; Traore, Sekou F; Doumbia, Seydou; Schlein, Yosef; Müller, Günter C; Beier, John C

2015-02-05

Agent-based modelling (ABM) has been used to simulate mosquito life cycles and to evaluate vector control applications. However, most models lack sugar-feeding and resting behaviours or are based on mathematical equations lacking individual level randomness and spatial components of mosquito life. Here, a spatial individual-based model (IBM) incorporating sugar-feeding and resting behaviours of the malaria vector Anopheles gambiae was developed to estimate the impact of environmental sugar sources and resting sites on survival and biting behaviour. A spatial IBM containing An. gambiae mosquitoes and humans, as well as the village environment of houses, sugar sources, resting sites and larval habitat sites was developed. Anopheles gambiae behaviour rules were attributed at each step of the IBM: resting, host seeking, sugar feeding and breeding. Each step represented one second of time, and each simulation was set to run for 60 days and repeated 50 times. Scenarios of different densities and spatial distributions of sugar sources and outdoor resting sites were simulated and compared. When the number of natural sugar sources was increased from 0 to 100 while the number of resting sites was held constant, mean daily survival rate increased from 2.5% to 85.1% for males and from 2.5% to 94.5% for females, mean human biting rate increased from 0 to 0.94 bites per human per day, and mean daily abundance increased from 1 to 477 for males and from 1 to 1,428 for females. When the number of outdoor resting sites was increased from 0 to 50 while the number of sugar sources was held constant, mean daily survival rate increased from 77.3% to 84.3% for males and from 86.7% to 93.9% for females, mean human biting rate increased from 0 to 0.52 bites per human per day, and mean daily abundance increased from 62 to 349 for males and from 257 to 1120 for females. All increases were significant (P < 0.01). Survival was greater when sugar sources were randomly distributed in the whole village compared to clustering around outdoor resting sites or houses. Increases in densities of sugar sources or outdoor resting sites significantly increase the survival and human biting rates of An. gambiae mosquitoes. Survival of An. gambiae is more supported by random distribution of sugar sources than clustering of sugar sources around resting sites or houses. Density and spatial distribution of natural sugar sources and outdoor resting sites modulate vector populations and human biting rates, and thus malaria parasite transmission.

Electronic holography using binary phase modulation

NASA Astrophysics Data System (ADS)

Matoba, Osamu

2014-06-01

A 3D display system by using a phase-only distribution is presented. Especially, binary phase distribution is used to reconstruct a 3D object for wide viewing zone angle. To obtain the phase distribution to be displayed on a phase-mode spatial light modulator, both of experimental and numerical processes are available. In this paper, we present a numerical process by using a computer graphics data. A random phase distribution is attached to all polygons of an input 3D object to reconstruct a 3D object well from the binary phase distribution. Numerical and experimental results are presented to show the effectiveness of the proposed system.

Nuclear test ban treaty verification: Improving test ban monitoring with empirical and model-based signal processing

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

Harris, David B.; Gibbons, Steven J.; Rodgers, Arthur J.

In this approach, small scale-length medium perturbations not modeled in the tomographic inversion might be described as random fields, characterized by particular distribution functions (e.g., normal with specified spatial covariance). Conceivably, random field parameters (scatterer density or scale length) might themselves be the targets of tomographic inversions of the scattered wave field. As a result, such augmented models may provide processing gain through the use of probabilistic signal sub spaces rather than deterministic waveforms.

Nuclear test ban treaty verification: Improving test ban monitoring with empirical and model-based signal processing

DOE PAGES

Harris, David B.; Gibbons, Steven J.; Rodgers, Arthur J.; ...

2012-05-01

In this approach, small scale-length medium perturbations not modeled in the tomographic inversion might be described as random fields, characterized by particular distribution functions (e.g., normal with specified spatial covariance). Conceivably, random field parameters (scatterer density or scale length) might themselves be the targets of tomographic inversions of the scattered wave field. As a result, such augmented models may provide processing gain through the use of probabilistic signal sub spaces rather than deterministic waveforms.

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.

Monte Carlo computer simulations of Venus equilibrium and global resurfacing models

NASA Technical Reports Server (NTRS)

Dawson, D. D.; Strom, R. G.; Schaber, G. G.

1992-01-01

Two models have been proposed for the resurfacing history of Venus: (1) equilibrium resurfacing and (2) global resurfacing. The equilibrium model consists of two cases: in case 1, areas less than or equal to 0.03 percent of the planet are spatially randomly resurfaced at intervals of less than or greater than 150,000 yr to produce the observed spatially random distribution of impact craters and average surface age of about 500 m.y.; and in case 2, areas greater than or equal to 10 percent of the planet are resurfaced at intervals of greater than or equal to 50 m.y. The global resurfacing model proposes that the entire planet was resurfaced about 500 m.y. ago, destroying the preexisting crater population and followed by significantly reduced volcanism and tectonism. The present crater population has accumulated since then with only 4 percent of the observed craters having been embayed by more recent lavas. To test the equilibrium resurfacing model we have run several Monte Carlo computer simulations for the two proposed cases. It is shown that the equilibrium resurfacing model is not a valid model for an explanation of the observed crater population characteristics or Venus' resurfacing history. The global resurfacing model is the most likely explanation for the characteristics of Venus' cratering record. The amount of resurfacing since that event, some 500 m.y. ago, can be estimated by a different type of Monte Carolo simulation. To date, our initial simulation has only considered the easiest case to implement. In this case, the volcanic events are randomly distributed across the entire planet and, therefore, contrary to observation, the flooded craters are also randomly distributed across the planet.

Color selectivity of the spatial congruency effect: evidence from the focused attention paradigm.

PubMed

Makovac, Elena; Gerbino, Walter

2014-01-01

The multisensory response enhancement (MRE), occurring when the response to a visual target integrated with a spatially congruent sound is stronger than the response to the visual target alone, is believed to be mediated by the superior colliculus (SC) (Stein & Meredith, 1993). Here, we used a focused attention paradigm to show that the spatial congruency effect occurs with red (SC-effective) but not blue (SC-ineffective) visual stimuli, when presented with spatially congruent sounds. To isolate the chromatic component of SC-ineffective targets and to demonstrate the selectivity of the spatial congruency effect we used the random luminance modulation technique (Experiment 1) and the tritanopic technique (Experiment 2). Our results indicate that the spatial congruency effect does not require the distribution of attention over different sensory modalities and provide correlational evidence that the SC mediates the effect.

Can Process Understanding Help Elucidate The Structure Of The Critical Zone? Comparing Process-Based Soil Formation Models With Digital Soil Mapping.

NASA Astrophysics Data System (ADS)

Vanwalleghem, T.; Román, A.; Peña, A.; Laguna, A.; Giráldez, J. V.

2017-12-01

There is a need for better understanding the processes influencing soil formation and the resulting distribution of soil properties in the critical zone. 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 traditional digital soil mapping 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.

A New Stratified Sampling Procedure which Decreases Error Estimation of Varroa Mite Number on Sticky Boards.

PubMed

Kretzschmar, A; Durand, E; Maisonnasse, A; Vallon, J; Le Conte, Y

2015-06-01

A new procedure of stratified sampling is proposed in order to establish an accurate estimation of Varroa destructor populations on sticky bottom boards of the hive. It is based on the spatial sampling theory that recommends using regular grid stratification in the case of spatially structured process. The distribution of varroa mites on sticky board being observed as spatially structured, we designed a sampling scheme based on a regular grid with circles centered on each grid element. This new procedure is then compared with a former method using partially random sampling. Relative error improvements are exposed on the basis of a large sample of simulated sticky boards (n=20,000) which provides a complete range of spatial structures, from a random structure to a highly frame driven structure. The improvement of varroa mite number estimation is then measured by the percentage of counts with an error greater than a given level. © 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.

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

Dendritic growth model of multilevel marketing

NASA Astrophysics Data System (ADS)

Pang, James Christopher S.; Monterola, Christopher P.

2017-02-01

Biologically inspired dendritic network growth is utilized to model the evolving connections of a multilevel marketing (MLM) enterprise. Starting from agents at random spatial locations, a network is formed by minimizing a distance cost function controlled by a parameter, termed the balancing factor bf, that weighs the wiring and the path length costs of connection. The paradigm is compared to an actual MLM membership data and is shown to be successful in statistically capturing the membership distribution, better than the previously reported agent based preferential attachment or analytic branching process models. Moreover, it recovers the known empirical statistics of previously studied MLM, specifically: (i) a membership distribution characterized by the existence of peak levels indicating limited growth, and (ii) an income distribution obeying the 80 - 20 Pareto principle. Extensive types of income distributions from uniform to Pareto to a "winner-take-all" kind are also modeled by varying bf. Finally, the robustness of our dendritic growth paradigm to random agent removals is explored and its implications to MLM income distributions are discussed.

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.

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.

The spatial distributions of large gap-like structure on Fe(Se,Te) single crystals observed by STM/STS

NASA Astrophysics Data System (ADS)

Sugimoto, Akira; Sakai, Yuta; Nagasaka, Kouhei; Ekino, Toshikazu

2015-11-01

The nanoscale spatial distributions of large gap-like structure on superconducting FeSe1-xTex were investigated by scanning tunneling microscopy/spectroscopy (STM/STS). The STM topography shows regular atomic lattice arrangements with the lattice spacing ∼0.38 nm, together with the randomly distributed large spots due to the excess Fe atoms. From the STS measurements, the small gap structures of Δ ∼ 7 meV were partly observed. On the other hand, the high-bias dI/dV curves exhibit the broad peak structures at the negative biases of VPG = -200 to -400 mV in the measured whole surface area. The average of these large gaps is |VPGave| ∼ 305 mV with the standard deviation of σ ∼ 48 mV. The spatial distributions of the VPG exhibit the domain structures consisting of the relatively smaller gaps (<250 meV), which correspond to the excess Fe positions. The small gap Δ ∼ 7 meV is also observed at those positions, suggesting that the excess Fe affects the electronic structures of FeSe1-xTex.

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 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.

Geometrical effects on the electron residence time in semiconductor nano-particles.

PubMed

Koochi, Hakimeh; Ebrahimi, Fatemeh

2014-09-07

We have used random walk (RW) numerical simulations to investigate the influence of the geometry on the statistics of the electron residence time τ(r) in a trap-limited diffusion process through semiconductor nano-particles. This is an important parameter in coarse-grained modeling of charge carrier transport in nano-structured semiconductor films. The traps have been distributed randomly on the surface (r(2) model) or through the whole particle (r(3) model) with a specified density. The trap energies have been taken from an exponential distribution and the traps release time is assumed to be a stochastic variable. We have carried out (RW) simulations to study the effect of coordination number, the spatial arrangement of the neighbors and the size of nano-particles on the statistics of τ(r). It has been observed that by increasing the coordination number n, the average value of electron residence time, τ̅(r) rapidly decreases to an asymptotic value. For a fixed coordination number n, the electron's mean residence time does not depend on the neighbors' spatial arrangement. In other words, τ̅(r) is a porosity-dependence, local parameter which generally varies remarkably from site to site, unless we are dealing with highly ordered structures. We have also examined the effect of nano-particle size d on the statistical behavior of τ̅(r). Our simulations indicate that for volume distribution of traps, τ̅(r) scales as d(2). For a surface distribution of traps τ(r) increases almost linearly with d. This leads to the prediction of a linear dependence of the diffusion coefficient D on the particle size d in ordered structures or random structures above the critical concentration which is in accordance with experimental observations.

Modeling species distribution and change using random forest [Chapter 8

Treesearch

Jeffrey S. Evans; Melanie A. Murphy; Zachary A. Holden; Samuel A. Cushman

2011-01-01

Although inference is a critical component in ecological modeling, the balance between accurate predictions and inference is the ultimate goal in ecological studies (Peters 1991; De’ath 2007). Practical applications of ecology in conservation planning, ecosystem assessment, and bio-diversity are highly dependent on very accurate spatial predictions of...

Habitat fragmentation and the Burrowing Owls (Speotyto cunicularia) in Saskatchewan

Treesearch

Robert G. Warnock; Paul C. James

1997-01-01

The relationship between landscape (125,664 ha circular plots) fragmentation patterns and the spatial distribution of Burrowing Owls (Speotyto cunicularia) was investigated in the heavily fragmented grasslands of Saskatchewan. Data were collected from 152 Burrowing Owl sites and 250 random sites located on 1990 LANDSAT-TM satellite images and 1:250,...

Metal-superconductor transition in low-dimensional superconducting clusters embedded in two-dimensional electron systems

NASA Astrophysics Data System (ADS)

Bucheli, D.; Caprara, S.; Castellani, C.; Grilli, M.

2013-02-01

Motivated by recent experimental data on thin film superconductors and oxide interfaces, we propose a random-resistor network apt to describe the occurrence of a metal-superconductor transition in a two-dimensional electron system with disorder on the mesoscopic scale. We consider low-dimensional (e.g. filamentary) structures of a superconducting cluster embedded in the two-dimensional network and we explore the separate effects and the interplay of the superconducting structure and of the statistical distribution of local critical temperatures. The thermal evolution of the resistivity is determined by a numerical calculation of the random-resistor network and, for comparison, a mean-field approach called effective medium theory (EMT). Our calculations reveal the relevance of the distribution of critical temperatures for clusters with low connectivity. In addition, we show that the presence of spatial correlations requires a modification of standard EMT to give qualitative agreement with the numerical results. Applying the present approach to an LaTiO3/SrTiO3 oxide interface, we find that the measured resistivity curves are compatible with a network of spatially dense but loosely connected superconducting islands.

Mathematical models application for mapping soils spatial distribution on the example of the farm from the North of Udmurt Republic of Russia

NASA Astrophysics Data System (ADS)

Dokuchaev, P. M.; Meshalkina, J. L.; Yaroslavtsev, A. M.

2018-01-01

Comparative analysis of soils geospatial modeling using multinomial logistic regression, decision trees, random forest, regression trees and support vector machines algorithms was conducted. The visual interpretation of the digital maps obtained and their comparison with the existing map, as well as the quantitative assessment of the individual soil groups detection overall accuracy and of the models kappa showed that multiple logistic regression, support vector method, and random forest models application with spatial prediction of the conditional soil groups distribution can be reliably used for mapping of the study area. It has shown the most accurate detection for sod-podzolics soils (Phaeozems Albic) lightly eroded and moderately eroded soils. In second place, according to the mean overall accuracy of the prediction, there are sod-podzolics soils - non-eroded and warp one, as well as sod-gley soils (Umbrisols Gleyic) and alluvial soils (Fluvisols Dystric, Umbric). Heavy eroded sod-podzolics and gray forest soils (Phaeozems Albic) were detected by methods of automatic classification worst of all.

Random motor generation in a finger tapping task: influence of spatial contingency and of cortical and subcortical hemispheric brain lesions

PubMed Central

Annoni, J.; Pegna, A.

1997-01-01

OBJECTIVE—To test the hypothesis that, during random motor generation, the spatial contingencies inherent to the task would induce additional preferences in normal subjects, shifting their performances farther from randomness. By contrast, perceptual or executive dysfunction could alter these task related biases in patients with brain damage.
METHODS—Two groups of patients, with right and left focal brain lesions, as well as 25 right handed subjects matched for age and handedness were asked to execute a random choice motor task—namely, to generate a random series of 180 button presses from a set of 10 keys placed vertically in front of them.
RESULTS—In the control group, as in the left brain lesion group, motor generation was subject to deviations from theoretical expected randomness, similar to those when numbers are generated mentally, as immediate repetitions (successive presses on the same key) are avoided. However, the distribution of button presses was also contingent on the topographic disposition of the keys: the central keys were chosen more often than those placed at extreme positions. Small distances were favoured, particularly with the left hand. These patterns were influenced by implicit strategies and task related contingencies.
 By contrast, right brain lesion patients with frontal involvement tended to show a more square distribution of key presses—that is, the number of key presses tended to be more equally distributed. The strategies were also altered by brain lesions: the number of immediate repetitions was more frequent when the lesion involved the right frontal areas yielding a random generation nearer to expected theoretical randomness. The frequency of adjacent key presses was increased by right anterior and left posterior cortical as well as by right subcortical lesions, but decreased by left subcortical lesions.
CONCLUSIONS—Depending on the side of the lesion and the degree of cortical-subcortical involvement, the deficits take on a different aspect and direct repetions and adjacent key presses have different patterns of alterations. Motor random generation is therefore a complex task which seems to necessitate the participation of numerous cerebral structures, among which those situated in the right frontal, left posterior, and subcortical regions have a predominant role.

 PMID:9408109

Quantifying the morphodynamics of river restoration schemes using Unmanned Aerial Vehicles (UAVs)

NASA Astrophysics Data System (ADS)

Williams, Richard; Byrne, Patrick; Gilles, Eric; Hart, John; Hoey, Trevor; Maniatis, George; Moir, Hamish; Reid, Helen; Ves, Nikolas

2017-04-01

River restoration schemes are particularly sensitive to morphological adjustment during the first set of high-flow events that they are subjected to. Quantifying elevation change associated with morphological adjustment can contribute to improved adaptive decision making to ensure river restoration scheme objectives are achieved. To date the relatively high cost, technical demands and challenging logistics associated with acquiring repeat, high-resolution topographic surveys has resulted in a significant barrier to monitoring the three-dimensional morphodynamics of river restoration schemes. The availability of low-cost, consumer grade Unmanned Aerial Vehicles that are capable of acquiring imagery for processing using Structure-from-Motion Multi-View Stereo (SfM MVS) photogrammetry has the potential to transform the survey the morphodynamics of river restoration schemes. Application guidance does, however, need to be developed to fully exploit the advances of UAV technology and SfM MVS processing techniques. In particular, there is a need to quantify the effect of the number and spatial distribution of ground targets on vertical error. This is particularly significant because vertical errors propagate when mapping morphological change, and thus determine the evidence that is available for decision making. This presentation presents results from a study that investigated how the number and spatial distribution of targets influenced vertical error, and then used the findings to determine survey protocols for a monitoring campaign that has quantified morphological change across a number of restoration schemes. At the Swindale river restoration scheme, Cumbria, England, 31 targets were distributed across a 700 m long reach and the centre of each target was surveyed using RTK-GPS. Using the targets as General Control Points (GCPs) or checkpoints, they were divided into three different spatial patterns (centre, edge and random) and used for processing images acquired from a SenseFly Swinglet CAM UAV with a Canon IXUS 240 HS camera. Results indicate that if targets were distributed centrally then vertical distortions would be most notable in outer region of the processing domain; if an edge pattern was used then vertical errors were greatest in the central region of the processing domain; if targets were distributed randomly then errors were more evenly distributed. For this optimal random layout, vertical errors were lowest when 15 to 23 targets were used as GCPs. The best solution achieved planimetric (XY) errors of 0.006 m and vertical (Z) errors of 0.05 m. This result was used to determine target density and distribution for repeat surveys on two other restoration schemes, Whit Beck (Cumbria, England) and Allt Lorgy (Highlands, Scotland). These repeat surveys have been processed to produce DEMs of Difference (DoDs). The DoDs have been used to quantify the spatial distribution of erosion and deposition of these schemes due to high-flow events. Broader interpretation enables insight into patterns of morphological sensitivity that are related to scheme design.

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.

Spatial vs. individual variability with inheritance in a stochastic Lotka-Volterra system

NASA Astrophysics Data System (ADS)

Dobramysl, Ulrich; Tauber, Uwe C.

2012-02-01

We investigate a stochastic spatial Lotka-Volterra predator-prey model with randomized interaction rates that are either affixed to the lattice sites and quenched, and / or specific to individuals in either population. In the latter situation, we include rate inheritance with mutations from the particles' progenitors. Thus we arrive at a simple model for competitive evolution with environmental variability and selection pressure. We employ Monte Carlo simulations in zero and two dimensions to study the time evolution of both species' densities and their interaction rate distributions. The predator and prey concentrations in the ensuing steady states depend crucially on the environmental variability, whereas the temporal evolution of the individualized rate distributions leads to largely neutral optimization. Contrary to, e.g., linear gene expression models, this system does not experience fixation at extreme values. An approximate description of the resulting data is achieved by means of an effective master equation approach for the interaction rate distribution.

Spatial epidemiology of bovine tuberculosis in Mexico.

PubMed

Martínez, Horacio Zendejas; Suazo, Feliciano Milián; Cuador Gil, José Quintín; Bello, Gustavo Cruz; Anaya Escalera, Ana María; Márquez, Gabriel Huitrón; Casanova, Leticia García

2007-01-01

The purpose of this study was to use geographic information systems (GIS) and geo-statistical methods of ordinary kriging to predict the prevalence and distribution of bovine tuberculosis (TB) in Jalisco, Mexico. A random sample of 2 287 herds selected from a set of 48 766 was used for the analysis. Spatial location of herds was obtained by either a personal global positioning system (GPS), a database from the Instituto Nacional de Estadìstica Geografìa e Informàtica (INEGI) or Google Earth. Information on TB prevalence was provided by the Jalisco Commission for the Control and Eradication of Tuberculosis (COEETB). Prediction of TB was obtained using ordinary kriging in the geostatistical analyst module in ArcView8. A predicted high prevalence area of TB matching the distribution of dairy cattle was observed. This prediction was in agreement with the prevalence calculated on the total 48 766 herds. Validation was performed taking estimated values of TB prevalence at each municipality, extracted from the kriging surface and then compared with the real prevalence values using a correlation test, giving a value of 0.78, indicating that GIS and kriging are reliable tools for the estimation of TB distribution based on a random sample. This resulted in a significant savings of resources.

Response of moderately thick laminated cross-ply composite shells subjected to random excitation

NASA Technical Reports Server (NTRS)

Elishakoff, Isaak; Cederbaum, Gabriel; Librescu, Liviu

1989-01-01

This study deals with the dynamic response of transverse shear deformable laminated shells subjected to random excitation. The analysis encompasses the following problems: (1) the dynamic response of circular cylindrical shells of finite length excited by an axisymmetric uniform ring loading, stationary in time, and (2) the response of spherical and cylindrical panels subjected to stationary random loadings with uniform spatial distribution. The associated equations governing the structural theory of shells are derived upon discarding the classical Love-Kirchhoff (L-K) assumptions. In this sense, the theory is formulated in the framework of the first-order transverse shear deformation theory (FSDT).

Do bioclimate variables improve performance of climate envelope models?

USGS Publications Warehouse

Watling, James I.; Romañach, Stephanie S.; Bucklin, David N.; Speroterra, Carolina; Brandt, Laura A.; Pearlstine, Leonard G.; Mazzotti, Frank J.

2012-01-01

Climate envelope models are widely used to forecast potential effects of climate change on species distributions. A key issue in climate envelope modeling is the selection of predictor variables that most directly influence species. To determine whether model performance and spatial predictions were related to the selection of predictor variables, we compared models using bioclimate variables with models constructed from monthly climate data for twelve terrestrial vertebrate species in the southeastern USA using two different algorithms (random forests or generalized linear models), and two model selection techniques (using uncorrelated predictors or a subset of user-defined biologically relevant predictor variables). There were no differences in performance between models created with bioclimate or monthly variables, but one metric of model performance was significantly greater using the random forest algorithm compared with generalized linear models. Spatial predictions between maps using bioclimate and monthly variables were very consistent using the random forest algorithm with uncorrelated predictors, whereas we observed greater variability in predictions using generalized linear models.

Temporal complexity in emission from Anderson localized lasers

NASA Astrophysics Data System (ADS)

Kumar, Randhir; Balasubrahmaniyam, M.; Alee, K. Shadak; Mujumdar, Sushil

2017-12-01

Anderson localization lasers exploit resonant cavities formed due to structural disorder. The inherent randomness in the structure of these cavities realizes a probability distribution in all cavity parameters such as quality factors, mode volumes, mode structures, and so on, implying resultant statistical fluctuations in the temporal behavior. Here we provide direct experimental measurements of temporal width distributions of Anderson localization lasing pulses in intrinsically and extrinsically disordered coupled-microresonator arrays. We first illustrate signature exponential decays in the spatial intensity distributions of the lasing modes that quantify their localized character, and then measure the temporal width distributions of the pulsed emission over several configurations. We observe a dependence of temporal widths on the disorder strength, wherein the widths show a single-peaked, left-skewed distribution in extrinsic disorder and a dual-peaked distribution in intrinsic disorder. We propose a model based on coupled rate equations for an emitter and an Anderson cavity with a random mode structure, which gives excellent quantitative and qualitative agreement with the experimental observations. The experimental and theoretical analyses bring to the fore the temporal complexity in Anderson-localization-based lasing systems.

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.

Inhomogeneity Based Characterization of Distribution Patterns on the Plasma Membrane

PubMed Central

Paparelli, Laura; Corthout, Nikky; Wakefield, Devin L.; Sannerud, Ragna; Jovanovic-Talisman, Tijana; Annaert, Wim; Munck, Sebastian

2016-01-01

Cell surface protein and lipid molecules are organized in various patterns: randomly, along gradients, or clustered when segregated into discrete micro- and nano-domains. Their distribution is tightly coupled to events such as polarization, endocytosis, and intracellular signaling, but challenging to quantify using traditional techniques. Here we present a novel approach to quantify the distribution of plasma membrane proteins and lipids. This approach describes spatial patterns in degrees of inhomogeneity and incorporates an intensity-based correction to analyze images with a wide range of resolutions; we have termed it Quantitative Analysis of the Spatial distributions in Images using Mosaic segmentation and Dual parameter Optimization in Histograms (QuASIMoDOH). We tested its applicability using simulated microscopy images and images acquired by widefield microscopy, total internal reflection microscopy, structured illumination microscopy, and photoactivated localization microscopy. We validated QuASIMoDOH, successfully quantifying the distribution of protein and lipid molecules detected with several labeling techniques, in different cell model systems. We also used this method to characterize the reorganization of cell surface lipids in response to disrupted endosomal trafficking and to detect dynamic changes in the global and local organization of epidermal growth factor receptors across the cell surface. Our findings demonstrate that QuASIMoDOH can be used to assess protein and lipid patterns, quantifying distribution changes and spatial reorganization at the cell surface. An ImageJ/Fiji plugin of this analysis tool is provided. PMID:27603951

Experimental Study of the Effect of the Initial Spectrum Width on the Statistics of Random Wave Groups

NASA Astrophysics Data System (ADS)

Shemer, L.; Sergeeva, A.

2009-12-01

The statistics of random water wave field determines the probability of appearance of extremely high (freak) waves. This probability is strongly related to the spectral wave field characteristics. Laboratory investigation of the spatial variation of the random wave-field statistics for various initial conditions is thus of substantial practical importance. Unidirectional nonlinear random wave groups are investigated experimentally in the 300 m long Large Wave Channel (GWK) in Hannover, Germany, which is the biggest facility of its kind in Europe. Numerous realizations of a wave field with the prescribed frequency power spectrum, yet randomly-distributed initial phases of each harmonic, were generated by a computer-controlled piston-type wavemaker. Several initial spectral shapes with identical dominant wave length but different width were considered. For each spectral shape, the total duration of sampling in all realizations was long enough to yield sufficient sample size for reliable statistics. Through all experiments, an effort had been made to retain the characteristic wave height value and thus the degree of nonlinearity of the wave field. Spatial evolution of numerous statistical wave field parameters (skewness, kurtosis and probability distributions) is studied using about 25 wave gauges distributed along the tank. It is found that, depending on the initial spectral shape, the frequency spectrum of the wave field may undergo significant modification in the course of its evolution along the tank; the values of all statistical wave parameters are strongly related to the local spectral width. A sample of the measured wave height probability functions (scaled by the variance of surface elevation) is plotted in Fig. 1 for the initially narrow rectangular spectrum. The results in Fig. 1 resemble findings obtained in [1] for the initial Gaussian spectral shape. The probability of large waves notably surpasses that predicted by the Rayleigh distribution and is the highest at the distance of about 100 m. Acknowledgement This study is carried out in the framework of the EC supported project "Transnational access to large-scale tests in the Large Wave Channel (GWK) of Forschungszentrum Küste (Contract HYDRALAB III - No. 022441). [1] L. Shemer and A. Sergeeva, J. Geophys. Res. Oceans 114, C01015 (2009). Figure 1. Variation along the tank of the measured wave height distribution for rectangular initial spectral shape, the carrier wave period T0=1.5 s.

Keyword extraction by nonextensivity measure.

PubMed

Mehri, Ali; Darooneh, Amir H

2011-05-01

The presence of a long-range correlation in the spatial distribution of a relevant word type, in spite of random occurrences of an irrelevant word type, is an important feature of human-written texts. We classify the correlation between the occurrences of words by nonextensive statistical mechanics for the word-ranking process. In particular, we look at the nonextensivity parameter as an alternative metric to measure the spatial correlation in the text, from which the words may be ranked in terms of this measure. Finally, we compare different methods for keyword extraction. © 2011 American Physical Society

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

Spatial Variability of Soil-Water Storage in the Southern Sierra Critical Zone Observatory: Measurement and Prediction

NASA Astrophysics Data System (ADS)

Oroza, C.; Bales, R. C.; Zheng, Z.; Glaser, S. D.

2017-12-01

Predicting the spatial distribution of soil moisture in mountain environments is confounded by multiple factors, including complex topography, spatial variably of soil texture, sub-surface flow paths, and snow-soil interactions. While remote-sensing tools such as passive-microwave monitoring can measure spatial variability of soil moisture, they only capture near-surface soil layers. Large-scale sensor networks are increasingly providing soil-moisture measurements at high temporal resolution across a broader range of depths than are accessible from remote sensing. It may be possible to combine these in-situ measurements with high-resolution LIDAR topography and canopy cover to estimate the spatial distribution of soil moisture at high spatial resolution at multiple depths. We study the feasibility of this approach using six years (2009-2014) of daily volumetric water content measurements at 10-, 30-, and 60-cm depths from the Southern Sierra Critical Zone Observatory. A non-parametric, multivariate regression algorithm, Random Forest, was used to predict the spatial distribution of depth-integrated soil-water storage, based on the in-situ measurements and a combination of node attributes (topographic wetness, northness, elevation, soil texture, and location with respect to canopy cover). We observe predictable patterns of predictor accuracy and independent variable ranking during the six-year study period. Predictor accuracy is highest during the snow-cover and early recession periods but declines during the dry period. Soil texture has consistently high feature importance. Other landscape attributes exhibit seasonal trends: northness peaks during the wet-up period, and elevation and topographic-wetness index peak during the recession and dry period, respectively.

Using spatial patterns in illegal wildlife uses to reveal connections between subsistence hunting and trade.

PubMed

Sánchez-Mercado, Ada; Asmüssen, Marianne; Rodríguez-Clark, Kathryn M; Rodríguez, Jon Paul; Jedrzejewski, Wlodzimierz

2016-12-01

Although most often considered independently, subsistence hunting, domestic trade, and international trade as components of illegal wildlife use (IWU) may be spatially correlated. Understanding how and where subsistence and commercial uses may co-occur has important implications for the design and implementation of effective conservation actions. We analyzed patterns in the joint geographical distribution of illegal commercial and subsistence use of multiple wildlife species in Venezuela and evaluated whether available data were sufficient to provide accurate estimates of the magnitude, scope, and detectability of IWU. We compiled records of illegal subsistence hunting and trade from several sources and fitted a random-forest classification model to predict the spatial distribution of IWUs. From 1969 to 2014, 404 species and 8,340,921 specimens were involved in IWU, for a mean extraction rate of 185,354 individuals/year. Birds were the most speciose group involved (248 spp.), but reptiles had the highest extraction rates (126,414 individuals/year vs. 3,133 individuals/year for birds). Eighty-eight percent of international trade records spatially overlapped with domestic trade, especially in the north and along the coast but also in western inland areas. The distribution of domestic trade was broadly distributed along roads, suggesting that domestic trade does not depend on large markets in cities. Seventeen percent of domestic trade records overlapped with subsistence hunting, but the spatial distribution of this overlap covered a much larger area than between commercial uses. Domestic trade seems to respond to demand from rural more than urban communities. Our approach will be useful for understanding how IWU works at national scales in other parts of the world. © 2016 Society for Conservation Biology.

Spatial distribution of solute leaching with snowmelt and irrigation: measurements and simulations

NASA Astrophysics Data System (ADS)

Schotanus, D.; van der Ploeg, M. J.; van der Zee, S. E. A. T. M.

2013-04-01

Transport of a tracer and a degradable solute in a heterogeneous soil was measured in the field, and simulated with several transient and steady state infiltration rates. Leaching surfaces were used to investigate the solute leaching in space and time simultaneously. In the simulations, a random field for the scaling factor in the retention curve was used for the heterogeneous soil, which was based on the spatial distribution of drainage in an experiment with a multi-compartment sampler. As a criterion to compare the results from simulations and observations, the sorted and cumulative total drainage in a cell was used. The effect of the ratio of the infiltration rate over the degradation rate on leaching of degradable solutes was investigated. Furthermore, the spatial distribution of the leaching of degradable and non-degradable solutes was compared. The infiltration rate determines the amount of leaching of the degradable solute. This can be partly explained by a decreasing travel time with an increasing infiltration rate. The spatial distribution of the leaching also depends on the infiltration rate. When the infiltration rate is high compared to the degradation rate, the leaching of the degradable solute is similar as for the tracer. The fraction of the pore space of the soil that contributes to solute leaching increases with an increasing infiltration rate. This fraction is similar for a tracer and a degradable solute. With increasing depth, the leaching becomes more homogeneous, as a result of dispersion. The spatial distribution of the solute leaching is different under different transient infiltration rates, therefore, also the amount of leaching is different. With independent stream tube approaches, this effect would be ignored.

Spatial distribution of solute leaching with snowmelt and irrigation: measurements and simulations

NASA Astrophysics Data System (ADS)

Schotanus, D.; van der Ploeg, M. J.; van der Zee, S. E. A. T. M.

2012-12-01

Transport of a tracer and a degradable solute in a heterogeneous soil was measured in the field, and simulated with several transient and steady state infiltration rates. Leaching surfaces were used to investigate the solute leaching in space and time simultaneously. In the simulations, a random field for the scaling factor in the retention curve was used for the heterogeneous soil, which was based on the spatial distribution of drainage in an experiment with a multi-compartment sampler. As a criterion to compare the results from simulations and observations, the sorted and cumulative total drainage in a cell was used. The effect of the ratio of the infiltration rate over the degradation rate on leaching of degradable solutes was investigated. Furthermore, the spatial distribution of the leaching of degradable and non-degradable solutes was compared. The infiltration rate determines the amount of leaching of the degradable solute. This can be partly explained by a decreasing travel time with an increasing infiltration rate. The spatial distribution of the leaching also depends on the infiltration rate. When the infiltration rate is high compared to the degradation rate, the leaching of the degradable solute is similar as for the tracer. The fraction of the soil that contributes to solute leaching increases with an increasing infiltration rate. This fraction is similar for a tracer and a degradable solute. With increasing depth, the leaching becomes more homogeneous, as a result of dispersion. The spatial distribution of the solute leaching is different under different transient infiltration rates, therefore also the amount of leaching is different. With independent stream tube approaches, this effect would be ignored.

A polymer, random walk model for the size-distribution of large DNA fragments after high linear energy transfer radiation

NASA Technical Reports Server (NTRS)

Ponomarev, A. L.; Brenner, D.; Hlatky, L. R.; Sachs, R. K.

2000-01-01

DNA double-strand breaks (DSBs) produced by densely ionizing radiation are not located randomly in the genome: recent data indicate DSB clustering along chromosomes. Stochastic DSB clustering at large scales, from > 100 Mbp down to < 0.01 Mbp, is modeled using computer simulations and analytic equations. A random-walk, coarse-grained polymer model for chromatin is combined with a simple track structure model in Monte Carlo software called DNAbreak and is applied to data on alpha-particle irradiation of V-79 cells. The chromatin model neglects molecular details but systematically incorporates an increase in average spatial separation between two DNA loci as the number of base-pairs between the loci increases. Fragment-size distributions obtained using DNAbreak match data on large fragments about as well as distributions previously obtained with a less mechanistic approach. Dose-response relations, linear at small doses of high linear energy transfer (LET) radiation, are obtained. They are found to be non-linear when the dose becomes so large that there is a significant probability of overlapping or close juxtaposition, along one chromosome, for different DSB clusters from different tracks. The non-linearity is more evident for large fragments than for small. The DNAbreak results furnish an example of the RLC (randomly located clusters) analytic formalism, which generalizes the broken-stick fragment-size distribution of the random-breakage model that is often applied to low-LET data.

[Geostatistics analyzing to cause of formation of circle distribution of plant communities in Horqin Sandy Land].

PubMed

He, Xingdong; Gao, Yubao; Zhao, Wenzhi; Cong, Zili

2004-09-01

Investigation results in the present study showed that plant communities took typical concentric circles distribution patterns along habitat gradient from top, slope to interdune on a few large fixed dunes in middle part of Korqin Sandy Land. In order to explain this phenomenon, analysis of water content and its spatial heterogeneity in sand layers on different locations of dunes was conducted. In these dunes, water contents in sand layers of the tops were lower than those of the slopes; both of them were lower than those of the interdunes. According to the results of geostatistics analysis, whether shifting dune or fixed dune, spatial heterogeneity of water contents in sand layers took on regular changes, such as ratios between nugget and sill and ranges reduced gradually, fractal dimension increased gradually, the regular changes of these parameters indicated that random spatial heterogeneity reduced gradually, and autocorrelation spatial heterogeneity increased gradually from the top, the slope to the interdune. The regular changes of water contents in sand layers and their spatial heterogeneity of different locations of the dunes, thus, might be an important cause resulted in the formation of the concentric circles patterns of the plant communities on these fixed dunes.

Geographic distribution of trauma centers and injury-related mortality in the United States.

PubMed

Brown, Joshua B; Rosengart, Matthew R; Billiar, Timothy R; Peitzman, Andrew B; Sperry, Jason L

2016-01-01

Regionalized trauma care improves outcomes; however, access to care is not uniform across the United States. The objective was to evaluate whether geographic distribution of trauma centers correlates with injury mortality across state trauma systems. Level I or II trauma centers in the contiguous United States were mapped. State-level age-adjusted injury fatality rates per 100,000 people were obtained and evaluated for spatial autocorrelation. Nearest neighbor ratios (NNRs) were generated for each state. A NNR less than 1 indicates clustering, while a NNR greater than 1 indicates dispersion. NNRs were tested for difference from random geographic distribution. Fatality rates and NNRs were examined for correlation. Fatality rates were compared between states with trauma center clustering versus dispersion. Trauma center distribution and population density were evaluated. Spatial-lag regression determined the association between fatality rate and NNR, controlling for state-level demographics, population density, injury severity, trauma system resources, and socioeconomic factors. Fatality rates were spatially autocorrelated (Moran's I = 0.35, p < 0.01). Nine states had a clustered pattern (median NNR, 0.55; interquartile range [IQR], 0.48-0.60), 22 had a dispersed pattern (median NNR, 2.00; IQR, 1.68-3.99), and 10 had a random pattern (median NNR, 0.90; IQR, 0.85-1.00) of trauma center distribution. Fatality rate and NNR were correlated (ρ = 0.34, p = 0.03). Clustered states had a lower median injury fatality rate compared with dispersed states (56.9 [IQR, 46.5-58.9] vs. 64.9 [IQR, 52.5-77.1]; p = 0.04). Dispersed compared with clustered states had more counties without a trauma center that had higher population density than counties with a trauma center (5.7% vs. 1.2%, p < 0.01). Spatial-lag regression demonstrated that fatality rates increased by 0.02 per 100,000 persons for each unit increase in NNR (p < 0.01). Geographic distribution of trauma centers correlates with injury mortality, with more clustered state trauma centers associated with lower fatality rates. This may be a result of access relative to population density. These results may have implications for trauma system planning and require further study to investigate underlying mechanisms. Therapeutic/care management study, level IV.

Spatial and seasonal dynamic of abundance and distribution of guanaco and livestock: insights from using density surface and null models.

PubMed

Schroeder, Natalia M; Matteucci, Silvia D; Moreno, Pablo G; Gregorio, Pablo; Ovejero, Ramiro; Taraborelli, Paula; Carmanchahi, Pablo D

2014-01-01

Monitoring species abundance and distribution is a prerequisite when assessing species status and population viability, a difficult task to achieve for large herbivores at ecologically meaningful scales. Co-occurrence patterns can be used to infer mechanisms of community organization (such as biotic interactions), although it has been traditionally applied to binary presence/absence data. Here, we combine density surface and null models of abundance data as a novel approach to analyze the spatial and seasonal dynamics of abundance and distribution of guanacos (Lama guanicoe) and domestic herbivores in northern Patagonia, in order to visually and analytically compare the dispersion and co-occurrence pattern of ungulates. We found a marked seasonal pattern in abundance and spatial distribution of L. guanicoe. The guanaco population reached its maximum annual size and spatial dispersion in spring-summer, decreasing up to 6.5 times in size and occupying few sites of the study area in fall-winter. These results are evidence of the seasonal migration process of guanaco populations, an increasingly rare event for terrestrial mammals worldwide. The maximum number of guanacos estimated for spring (25,951) is higher than the total population size (10,000) 20 years ago, probably due to both counting methodology and population growth. Livestock were mostly distributed near human settlements, as expected by the sedentary management practiced by local people. Herbivore distribution was non-random; i.e., guanaco and livestock abundances co-varied negatively in all seasons, more than expected by chance. Segregation degree of guanaco and small-livestock (goats and sheep) was comparatively stronger than that of guanaco and large-livestock, suggesting a competition mechanism between ecologically similar herbivores, although various environmental factors could also contribute to habitat segregation. The new and compelling combination of methods used here is highly useful for researchers who conduct counts of animals to simultaneously estimate population sizes, distributions, assess temporal trends and characterize multi-species spatial interactions.

A Heavy Tailed Expectation Maximization Hidden Markov Random Field Model with Applications to Segmentation of MRI

PubMed Central

Castillo-Barnes, Diego; Peis, Ignacio; Martínez-Murcia, Francisco J.; Segovia, Fermín; Illán, Ignacio A.; Górriz, Juan M.; Ramírez, Javier; Salas-Gonzalez, Diego

2017-01-01

A wide range of segmentation approaches assumes that intensity histograms extracted from magnetic resonance images (MRI) have a distribution for each brain tissue that can be modeled by a Gaussian distribution or a mixture of them. Nevertheless, intensity histograms of White Matter and Gray Matter are not symmetric and they exhibit heavy tails. In this work, we present a hidden Markov random field model with expectation maximization (EM-HMRF) modeling the components using the α-stable distribution. The proposed model is a generalization of the widely used EM-HMRF algorithm with Gaussian distributions. We test the α-stable EM-HMRF model in synthetic data and brain MRI data. The proposed methodology presents two main advantages: Firstly, it is more robust to outliers. Secondly, we obtain similar results than using Gaussian when the Gaussian assumption holds. This approach is able to model the spatial dependence between neighboring voxels in tomographic brain MRI. PMID:29209194

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.

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

Origin and evolution of circular waves and spirals in Dictyostelium discoideum territories.

PubMed

Pálsson, E; Cox, E C

1996-02-06

Randomly distributed Dictyostelium discoideum cells form cooperative territories by signaling to each other with cAMP. Cells initiate the process by sending out pulsatile signals, which propagate as waves. With time, circular and spiral patterns form. We show that by adding spatial and temporal noise to the levels of an important regulator of external cAMP levels, the cAMP phosphodiesterase inhibitor, we can explain the natural progression of the system from randomly firing cells to circular waves whose symmetries break to form double- and single- or multi-armed spirals. When phosphodiesterase inhibitor is increased with time, mimicking experimental data, the wavelength of the spirals shortens, and a proportion of them evolve into pairs of connected spirals. We compare these results to recent experiments, finding that the temporal and spatial correspondence between experiment and model is very close.

Transition in the decay rates of stationary distributions of Lévy motion in an energy landscape.

PubMed

Kaleta, Kamil; Lőrinczi, József

2016-02-01

The time evolution of random variables with Lévy statistics has the ability to develop jumps, displaying very different behaviors from continuously fluctuating cases. Such patterns appear in an ever broadening range of examples including random lasers, non-Gaussian kinetics, or foraging strategies. The penalizing or reinforcing effect of the environment, however, has been little explored so far. We report a new phenomenon which manifests as a qualitative transition in the spatial decay behavior of the stationary measure of a jump process under an external potential, occurring on a combined change in the characteristics of the process and the lowest eigenvalue resulting from the effect of the potential. This also provides insight into the fundamental question of what is the mechanism of the spatial decay of a ground state.

Bayesian spatial transformation models with applications in neuroimaging data

PubMed Central

Miranda, Michelle F.; Zhu, Hongtu; Ibrahim, Joseph G.

2013-01-01

Summary The aim of this paper is to develop a class of spatial transformation models (STM) to spatially model the varying association between imaging measures in a three-dimensional (3D) volume (or 2D surface) and a set of covariates. Our STMs include a varying Box-Cox transformation model for dealing with the issue of non-Gaussian distributed imaging data and a Gaussian Markov Random Field model for incorporating spatial smoothness of the imaging data. Posterior computation proceeds via an efficient Markov chain Monte Carlo algorithm. Simulations and real data analysis demonstrate that the STM significantly outperforms the voxel-wise linear model with Gaussian noise in recovering meaningful geometric patterns. Our STM is able to reveal important brain regions with morphological changes in children with attention deficit hyperactivity disorder. PMID:24128143

Modelling of Space-Time Soil Moisture in Savannas and its Relation to Vegetation Patterns

NASA Astrophysics Data System (ADS)

Rodriguez-Iturbe, I.; Mohanty, B.; Chen, Z.

2017-12-01

A physically derived space-time representation of the soil moisture field is presented. It includes the incorporation of a "jitter" process acting over the space-time soil moisture field and accounting for the short distance heterogeneities in topography, soil, and vegetation characteristics. The modelling scheme allows for the representation of spatial random fluctuations of soil moisture at small spatial scales and reproduces quite well the space-time correlation structure of soil moisture from a field study in Oklahoma. It is shown that the islands of soil moisture above different thresholds have sizes which follow power distributions over an extended range of scales. A discussion is provided about the possible links of this feature with the observed power law distributions of the clusters of trees in savannas.

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.

Nematode distributions as spatial null models for macroinvertebrate species richness across environmental gradients: A case from mountain lakes.

PubMed

de Mendoza, Guillermo; Traunspurger, Walter; Palomo, Alejandro; Catalan, Jordi

2017-05-01

Nematode species are widely tolerant of environmental conditions and disperse passively. Therefore, the species richness distribution in this group might largely depend on the topological distribution of the habitats and main aerial and aquatic dispersal pathways connecting them. If so, the nematode species richness distributions may serve as null models for evaluating that of other groups more affected by environmental gradients. We investigated this hypothesis in lakes across an altitudinal gradient in the Pyrenees. We compared the altitudinal distribution, environmental tolerance, and species richness, of nematodes with that of three other invertebrate groups collected during the same sampling: oligochaetes, chironomids, and nonchironomid insects. We tested the altitudinal bias in distributions with t -tests and the significance of narrow-ranging altitudinal distributions with randomizations. We compared results between groups with Fisher's exact tests. We then explored the influence of environmental factors on species assemblages in all groups with redundancy analysis (RDA), using 28 environmental variables. And, finally, we analyzed species richness patterns across altitude with simple linear and quadratic regressions. Nematode species were rarely biased from random distributions (5% of species) in contrast with other groups (35%, 47%, and 50%, respectively). The altitudinal bias most often shifted toward low altitudes (85% of biased species). Nematodes showed a lower portion of narrow-ranging species than any other group, and differed significantly from nonchironomid insects (10% and 43%, respectively). Environmental variables barely explained nematode assemblages (RDA adjusted R 2  = 0.02), in contrast with other groups (0.13, 0.19 and 0.24). Despite these substantial differences in the response to environmental factors, species richness across altitude was unimodal, peaking at mid elevations, in all groups. This similarity indicates that the spatial distribution of lakes across altitude is a primary driver of invertebrate richness. Provided that nematodes are ubiquitous, their distribution offers potential null models to investigate species richness across environmental gradients in other ecosystem types and biogeographic regions.

Tectonic resurfacing of Venus

NASA Technical Reports Server (NTRS)

Malin, Michael C.; Grimm, Robert E.; Herrick, Robert R.

1993-01-01

Impact crater distributions and morphologies have traditionally played an important role in unraveling the geologic histories of terrestrial objects, and Venus has proved no exception. The key observations are: mean crater retention age about 500 Ma; apparently random spatial distribution; modest proportion (17 percent) of modified craters; and preferential association of modified craters with areas of low crater density. The simplest interpretation of these data alone is that Venus experienced global resurfacing (assumed to be largely volcanic) prior to 500 Ma, after which time resurfacing rates decreased dramatically. This scenario does not totally exclude present geological activity: some resurfacing and crater obliteration is occurring on part of the planet, but at rates much smaller than on Earth. An alternative endmember model holds that resurfacing is also spatially randomly distributed. Resurfacing of about 1 sq km/yr eliminates craters such that a typical portion of the surface has an age of 500 Ma, but actual ages range from zero to about 1000 Ma. Monte Carlo simulation indicates that the typical resurfacing 'patch' cannot exceed about 500 km in diameter without producing a crater distribution more heterogeneous than observed. Volcanic or tectonic processes within these patches must be locally intense to be able to obliterate craters completely and leave few modified. In this abstract, we describe how global geologic mapping may be used to test resurfacing hypotheses. We present preliminary evidence that the dominant mode of resurfacing on Venus is tectonism, not volcanism, and that this process must be ongoing today. Lastly, we outline a conceptual model in which to understand the relationship between global tectonics and crater distribution and preservation.

Spatial analysis and characteristics of pig farming in Thailand.

PubMed

Thanapongtharm, Weerapong; Linard, Catherine; Chinson, Pornpiroon; Kasemsuwan, Suwicha; Visser, Marjolein; Gaughan, Andrea E; Epprech, Michael; Robinson, Timothy P; Gilbert, Marius

2016-10-06

In Thailand, pig production intensified significantly during the last decade, with many economic, epidemiological and environmental implications. Strategies toward more sustainable future developments are currently investigated, and these could be informed by a detailed assessment of the main trends in the pig sector, and on how different production systems are geographically distributed. This study had two main objectives. First, we aimed to describe the main trends and geographic patterns of pig production systems in Thailand in terms of pig type (native, breeding, and fattening pigs), farm scales (smallholder and large-scale farming systems) and type of farming systems (farrow-to-finish, nursery, and finishing systems) based on a very detailed 2010 census. Second, we aimed to study the statistical spatial association between these different types of pig farming distribution and a set of spatial variables describing access to feed and markets. Over the last decades, pig population gradually increased, with a continuously increasing number of pigs per holder, suggesting a continuing intensification of the sector. The different pig-production systems showed very contrasted geographical distributions. The spatial distribution of large-scale pig farms corresponds with that of commercial pig breeds, and spatial analysis conducted using Random Forest distribution models indicated that these were concentrated in lowland urban or peri-urban areas, close to means of transportation, facilitating supply to major markets such as provincial capitals and the Bangkok Metropolitan region. Conversely the smallholders were distributed throughout the country, with higher densities located in highland, remote, and rural areas, where they supply local rural markets. A limitation of the study was that pig farming systems were defined from the number of animals per farm, resulting in their possible misclassification, but this should have a limited impact on the main patterns revealed by the analysis. The very contrasted distribution of different pig production systems present opportunities for future regionalization of pig production. More specifically, the detailed geographical analysis of the different production systems will be used to spatially-inform planning decisions for pig farming accounting for the specific health, environment and economical implications of the different pig production systems.

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

PubMed

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

2008-09-01

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

Time-fractional characterization of brine reaction and precipitation in porous media

NASA Astrophysics Data System (ADS)

Xu, Jianping; Jiang, Guancheng

2018-04-01

Brine reaction and precipitation in porous media sometimes occur in the presence of a strong fluid flowing field, which induces the mobilization of the precipitated salts and distorts their spatial distribution. It is interesting to investigate how the distribution responds to such mobilization. We view these precipitates as random walkers in the complex inner space of the porous media, where they make stochastic jumps among locations and possibly wait between successive transitions. In consideration of related experimental results, the waiting time of the precipitates at a particular position is allowed to range widely from short sojourn to permanent residence. Through the model of a continuous-time random walk, a class of time-fractional equations for the precipitate's concentration profile is derived, including that in the Riemann-Liouville formalism and the Prabhakar formalism. The solutions to these equations show the general pattern of the precipitate's spatiotemporal evolution: a coupling of mass accumulation and mass transport. And the degree to which the mass is mobilized turns out to be monotonically correlated to the fractional exponent α . Moreover, to keep the completeness of the model, we further discuss how the interaction among the precipitates influences the precipitation process. In doing so, a time-fractional non-linear Fokker-Planck equation with source term is introduced and solved. It is shown that the interaction among the precipitates slightly perturbs their spatial distribution. This distribution is largely dominated by the brine reaction itself and the interaction between the precipitates and the porous media.

The Importance of Spatial Reasoning Skills in Undergraduate Geology Students and the Effect of Weekly Spatial Skill Trainings

NASA Astrophysics Data System (ADS)

Gold, Anne; Pendergast, Philip; Stempien, Jennifer; Ormand, Carol

2016-04-01

Spatial reasoning is a key skill for student success in STEM disciplines in general and for students in geosciences in particular. However, spatial reasoning is neither explicitly trained, nor evenly distributed, among students and by gender. This uneven playing field allows some students to perform geoscience tasks easily while others struggle. A lack of spatial reasoning skills has been shown to be a barrier to success in the geosciences, and for STEM disciplines in general. Addressing spatial abilities early in the college experience might therefore be effective in retaining students, especially females, in STEM disciplines. We have developed and implemented a toolkit for testing and training undergraduate student spatial reasoning skills in the classroom. In the academic year 2014/15, we studied the distribution of spatial abilities in more than 700 undergraduate Geology students from 4 introductory and 2 upper level courses. Following random assignment, four treatment groups received weekly online training and intermittent hands-on trainings in spatial thinking while four control groups only participated in a pre- and a posttest of spatial thinking skills. In this presentation we summarize our results and describe the distribution of spatial skills in undergraduate students enrolled in geology courses. We first discuss the factors that best account for differences in baseline spatial ability levels, including general intelligence (using standardized test scores as a proxy), major, video gaming, and other childhood play experiences, which help to explain the gender gap observed in most research. We found a statistically significant improvement of spatial thinking still with large effect sizes for the students who received the weekly trainings. Self-report data further shows that students improve their spatial thinking skills and report that their improved spatial thinking skills increase their performance in geoscience courses. We conclude by discussing the effects of the training modules on development of spatial skills, which helps to shed light on what types of interventions may be useful in leveling the playing field for students going into the geosciences and other STEM fields.

Distribution of Orientation Selectivity in Recurrent Networks of Spiking Neurons with Different Random Topologies

PubMed Central

Sadeh, Sadra; Rotter, Stefan

2014-01-01

Neurons in the primary visual cortex are more or less selective for the orientation of a light bar used for stimulation. A broad distribution of individual grades of orientation selectivity has in fact been reported in all species. A possible reason for emergence of broad distributions is the recurrent network within which the stimulus is being processed. Here we compute the distribution of orientation selectivity in randomly connected model networks that are equipped with different spatial patterns of connectivity. We show that, for a wide variety of connectivity patterns, a linear theory based on firing rates accurately approximates the outcome of direct numerical simulations of networks of spiking neurons. Distance dependent connectivity in networks with a more biologically realistic structure does not compromise our linear analysis, as long as the linearized dynamics, and hence the uniform asynchronous irregular activity state, remain stable. We conclude that linear mechanisms of stimulus processing are indeed responsible for the emergence of orientation selectivity and its distribution in recurrent networks with functionally heterogeneous synaptic connectivity. PMID:25469704

Environmental determinants of the spatial distribution of Echinococcus multilocularis in Hungary.

PubMed

Tolnai, Z; Széll, Z; Sréter, T

2013-12-06

Human alveolar echinococcosis, caused by the metacestode stage of Echinococcus multilocularis, is one of the most pathogenic zoonoses in the temperate and arctic region of the Northern Hemisphere. To investigate the spatial distribution of E. multilocularis and the factors influencing this distribution in the recently identified endemic area of Hungary, 1612 red fox (Vulpes vulpes) carcasses were randomly collected from the whole Hungarian territory from November 2008 to February 2009 and from November 2012 to February 2013. The topographic positions of foxes were recorded in geographic information system database. The digitized home ranges and the vector data were used to calculate the altitude, mean annual temperature, annual precipitation, soil water retention, soil permeability, areas of land cover types and the presence and buffer zone of permanent water bodies within the fox territories. The intestinal mucosa from all the foxes was tested by sedimentation and counting technique. Multiple regression analysis was performed with environmental parameter values and E. multilocularis counts. The spatial distribution of the parasite was clumped. Based on statistical analysis, mean annual temperature and annual precipitation were the major determinants of the spatial distribution of E. multilocularis in Hungary. It can be attributed to the sensitivity of E. multilocularis eggs to high temperatures and desiccation. Although spreading and emergence of the parasite was observed in Hungary before 2009, the prevalence and intensity of infection did not change significantly between the two collection periods. It can be explained by the considerably lower annual precipitation before the second collection period. Copyright © 2013 Elsevier B.V. All rights reserved.

Spatial and temporal assessment of cumulative disturbance impacts due to military training, burning, haying, and their interactions on land condition of Fort Riley.

PubMed

Wang, Guangxing; Murphy, Dana; Oller, Adam; Howard, Heidi R; Anderson, Alan B; Rijal, Santosh; Myers, Natalie R; Woodford, Philip

2014-07-01

The effects of military training activities on the land condition of Army installations vary spatially and temporally. Training activities observably degrade land condition while also increasing biodiversity and stabilizing ecosystems. Moreover, other anthropogenic activities regularly occur on military lands such as prescribed burns and agricultural haying-adding to the dynamics of land condition. Thus, spatially and temporally assessing the impacts of military training, prescribed burning, agricultural haying, and their interactions is critical to the management of military lands. In this study, the spatial distributions and patterns of military training-induced disturbance frequency were derived using plot observation and point observation-based method, at Fort Riley, Kansas from 1989 to 2001. Moreover, spatial and variance analysis of cumulative impacts due to military training, burning, haying, and their interactions on the land condition of Fort Riley were conducted. The results showed that: (1) low disturbance intensity dominated the majority of the study area with exception of concentrated training within centralized areas; (2) high and low values of disturbance frequency were spatially clustered and had spatial patterns that differed significantly from a random distribution; and (3) interactions between prescribed burning and agricultural haying were not significant in terms of either soil erosion or disturbance intensity although their means and variances differed significantly between the burned and non-burned areas and between the hayed and non-hayed areas.

N-mixture models for estimating population size from spatially replicated counts

USGS Publications Warehouse

Royle, J. Andrew

2004-01-01

Spatial replication is a common theme in count surveys of animals. Such surveys often generate sparse count data from which it is difficult to estimate population size while formally accounting for detection probability. In this article, i describe a class of models (n-mixture models) which allow for estimation of population size from such data. The key idea is to view site-specific population sizes, n, as independent random variables distributed according to some mixing distribution (e.g., Poisson). Prior parameters are estimated from the marginal likelihood of the data, having integrated over the prior distribution for n. Carroll and lombard (1985, journal of american statistical association 80, 423-426) proposed a class of estimators based on mixing over a prior distribution for detection probability. Their estimator can be applied in limited settings, but is sensitive to prior parameter values that are fixed a priori. Spatial replication provides additional information regarding the parameters of the prior distribution on n that is exploited by the n-mixture models and which leads to reasonable estimates of abundance from sparse data. A simulation study demonstrates superior operating characteristics (bias, confidence interval coverage) of the n-mixture estimator compared to the caroll and lombard estimator. Both estimators are applied to point count data on six species of birds illustrating the sensitivity to choice of prior on p and substantially different estimates of abundance as a consequence.

Point process statistics in atom probe tomography.

PubMed

Philippe, T; Duguay, S; Grancher, G; Blavette, D

2013-09-01

We present a review of spatial point processes as statistical models that we have designed for the analysis and treatment of atom probe tomography (APT) data. As a major advantage, these methods do not require sampling. The mean distance to nearest neighbour is an attractive approach to exhibit a non-random atomic distribution. A χ(2) test based on distance distributions to nearest neighbour has been developed to detect deviation from randomness. Best-fit methods based on first nearest neighbour distance (1 NN method) and pair correlation function are presented and compared to assess the chemical composition of tiny clusters. Delaunay tessellation for cluster selection has been also illustrated. These statistical tools have been applied to APT experiments on microelectronics materials. Copyright © 2012 Elsevier B.V. All rights reserved.

Center of mass perception and inertial frames of reference.

PubMed

Bingham, G P; Muchisky, M M

1993-11-01

Center of mass perception was investigated by varying the shape, size, and orientation of planar objects. Shape was manipulated to investigate symmetries as information. The number of reflective symmetry axes, the amount of rotational symmetry, and the presence of radial symmetry were varied. Orientation affected systematic errors. Judgments tended to undershoot the center of mass. Random errors increased with size and decreased with symmetry. Size had no effect on random errors for maximally symmetric objects, although orientation did. The spatial distributions of judgments were elliptical. Distribution axes were found to align with the principle moments of inertia. Major axes tended to align with gravity in maximally symmetric objects. A functional and physical account was given in terms of the repercussions of error. Overall, judgments were very accurate.

Verifying the Dependence of Fractal Coefficients on Different Spatial Distributions

NASA Astrophysics Data System (ADS)

Gospodinov, Dragomir; Marekova, Elisaveta; Marinov, Alexander

2010-01-01

A fractal distribution requires that the number of objects larger than a specific size r has a power-law dependence on the size N(r) = C/rD∝r-D where D is the fractal dimension. Usually the correlation integral is calculated to estimate the correlation fractal dimension of epicentres. A `box-counting' procedure could also be applied giving the `capacity' fractal dimension. The fractal dimension can be an integer and then it is equivalent to a Euclidean dimension (it is zero of a point, one of a segment, of a square is two and of a cube is three). In general the fractal dimension is not an integer but a fractional dimension and there comes the origin of the term `fractal'. The use of a power-law to statistically describe a set of events or phenomena reveals the lack of a characteristic length scale, that is fractal objects are scale invariant. Scaling invariance and chaotic behavior constitute the base of a lot of natural hazards phenomena. Many studies of earthquakes reveal that their occurrence exhibits scale-invariant properties, so the fractal dimension can characterize them. It has first been confirmed that both aftershock rate decay in time and earthquake size distribution follow a power law. Recently many other earthquake distributions have been found to be scale-invariant. The spatial distribution of both regional seismicity and aftershocks show some fractal features. Earthquake spatial distributions are considered fractal, but indirectly. There are two possible models, which result in fractal earthquake distributions. The first model considers that a fractal distribution of faults leads to a fractal distribution of earthquakes, because each earthquake is characteristic of the fault on which it occurs. The second assumes that each fault has a fractal distribution of earthquakes. Observations strongly favour the first hypothesis. The fractal coefficients analysis provides some important advantages in examining earthquake spatial distribution, which are:—Simple way to quantify scale-invariant distributions of complex objects or phenomena by a small number of parameters.—It is becoming evident that the applicability of fractal distributions to geological problems could have a more fundamental basis. Chaotic behaviour could underlay the geotectonic processes and the applicable statistics could often be fractal. The application of fractal distribution analysis has, however, some specific aspects. It is usually difficult to present an adequate interpretation of the obtained values of fractal coefficients for earthquake epicenter or hypocenter distributions. That is why in this paper we aimed at other goals—to verify how a fractal coefficient depends on different spatial distributions. We simulated earthquake spatial data by generating randomly points first in a 3D space - cube, then in a parallelepiped, diminishing one of its sides. We then continued this procedure in 2D and 1D space. For each simulated data set we calculated the points' fractal coefficient (correlation fractal dimension of epicentres) and then checked for correlation between the coefficients values and the type of spatial distribution. In that way one can obtain a set of standard fractal coefficients' values for varying spatial distributions. These then can be used when real earthquake data is analyzed by comparing the real data coefficients values to the standard fractal coefficients. Such an approach can help in interpreting the fractal analysis results through different types of spatial distributions.

Bayesian spatio-temporal discard model in a demersal trawl fishery

NASA Astrophysics Data System (ADS)

Grazia Pennino, M.; Muñoz, Facundo; Conesa, David; López-Quílez, Antonio; Bellido, José M.

2014-07-01

Spatial management of discards has recently been proposed as a useful tool for the protection of juveniles, by reducing discard rates and can be used as a buffer against management errors and recruitment failure. In this study Bayesian hierarchical spatial models have been used to analyze about 440 trawl fishing operations of two different metiers, sampled between 2009 and 2012, in order to improve our understanding of factors that influence the quantity of discards and to identify their spatio-temporal distribution in the study area. Our analysis showed that the relative importance of each variable was different for each metier, with a few similarities. In particular, the random vessel effect and seasonal variability were identified as main driving variables for both metiers. Predictive maps of the abundance of discards and maps of the posterior mean of the spatial component show several hot spots with high discard concentration for each metier. We argue how the seasonal/spatial effects, and the knowledge about the factors influential to discarding, could potentially be exploited as potential mitigation measures for future fisheries management strategies. However, misidentification of hotspots and uncertain predictions can culminate in inappropriate mitigation practices which can sometimes be irreversible. The proposed Bayesian spatial method overcomes these issues, since it offers a unified approach which allows the incorporation of spatial random-effect terms, spatial correlation of the variables and the uncertainty of the parameters in the modeling process, resulting in a better quantification of the uncertainty and accurate predictions.

Residual Defect Density in Random Disks Deposits.

PubMed

Topic, Nikola; Pöschel, Thorsten; Gallas, Jason A C

2015-08-03

We investigate the residual distribution of structural defects in very tall packings of disks deposited randomly in large channels. By performing simulations involving the sedimentation of up to 50 × 10(9) particles we find all deposits to consistently show a non-zero residual density of defects obeying a characteristic power-law as a function of the channel width. This remarkable finding corrects the widespread belief that the density of defects should vanish algebraically with growing height. A non-zero residual density of defects implies a type of long-range spatial order in the packing, as opposed to only local ordering. In addition, we find deposits of particles to involve considerably less randomness than generally presumed.

Qualitatively Assessing Randomness in SVD Results

NASA Astrophysics Data System (ADS)

Lamb, K. W.; Miller, W. P.; Kalra, A.; Anderson, S.; Rodriguez, A.

2012-12-01

Singular Value Decomposition (SVD) is a powerful tool for identifying regions of significant co-variability between two spatially distributed datasets. SVD has been widely used in atmospheric research to define relationships between sea surface temperatures, geopotential height, wind, precipitation and streamflow data for myriad regions across the globe. A typical application for SVD is to identify leading climate drivers (as observed in the wind or pressure data) for a particular hydrologic response variable such as precipitation, streamflow, or soil moisture. One can also investigate the lagged relationship between a climate variable and the hydrologic response variable using SVD. When performing these studies it is important to limit the spatial bounds of the climate variable to reduce the chance of random co-variance relationships being identified. On the other hand, a climate region that is too small may ignore climate signals which have more than a statistical relationship to a hydrologic response variable. The proposed research seeks to identify a qualitative method of identifying random co-variability relationships between two data sets. The research identifies the heterogeneous correlation maps from several past results and compares these results with correlation maps produced using purely random and quasi-random climate data. The comparison identifies a methodology to determine if a particular region on a correlation map may be explained by a physical mechanism or is simply statistical chance.

Tigers on trails: occupancy modeling for cluster sampling.

PubMed

Hines, J E; Nichols, J D; Royle, J A; MacKenzie, D I; Gopalaswamy, A M; Kumar, N Samba; Karanth, K U

2010-07-01

Occupancy modeling focuses on inference about the distribution of organisms over space, using temporal or spatial replication to allow inference about the detection process. Inference based on spatial replication strictly requires that replicates be selected randomly and with replacement, but the importance of these design requirements is not well understood. This paper focuses on an increasingly popular sampling design based on spatial replicates that are not selected randomly and that are expected to exhibit Markovian dependence. We develop two new occupancy models for data collected under this sort of design, one based on an underlying Markov model for spatial dependence and the other based on a trap response model with Markovian detections. We then simulated data under the model for Markovian spatial dependence and fit the data to standard occupancy models and to the two new models. Bias of occupancy estimates was substantial for the standard models, smaller for the new trap response model, and negligible for the new spatial process model. We also fit these models to data from a large-scale tiger occupancy survey recently conducted in Karnataka State, southwestern India. In addition to providing evidence of a positive relationship between tiger occupancy and habitat, model selection statistics and estimates strongly supported the use of the model with Markovian spatial dependence. This new model provides another tool for the decomposition of the detection process, which is sometimes needed for proper estimation and which may also permit interesting biological inferences. In addition to designs employing spatial replication, we note the likely existence of temporal Markovian dependence in many designs using temporal replication. The models developed here will be useful either directly, or with minor extensions, for these designs as well. We believe that these new models represent important additions to the suite of modeling tools now available for occupancy estimation in conservation monitoring. More generally, this work represents a contribution to the topic of cluster sampling for situations in which there is a need for specific modeling (e.g., reflecting dependence) for the distribution of the variable(s) of interest among subunits.

[Distribution patterns of canopy and understory tree species at local scale in a Tierra Firme forest, the Colombian Amazonia].

PubMed

Barreto-Silva, Juan Sebastian; López, Dairon Cárdenas; Montoya, Alvaro Javier Duque

2014-03-01

The effect of environmental variation on the structure of tree communities in tropical forests is still under debate. There is evidence that in landscapes like Tierra Firme forest, where the environmental gradient decreases at a local level, the effect of soil on the distribution patterns of plant species is minimal, happens to be random or is due to biological processes. In contrast, in studies with different kinds of plants from tropical forests, a greater effect on floristic composition of varying soil and topography has been reported. To assess this, the current study was carried out in a permanent plot of ten hectares in the Amacayacu National Park, Colombian Amazonia. To run the analysis, floristic and environmental variations were obtained according to tree species abundance categories and growth forms. In order to quantify the role played by both environmental filtering and dispersal limitation, the variation of the spatial configuration was included. We used Detrended Correspondence Analysis and Canonical Correspondence Analysis, followed by a variation partitioning, to analyze the species distribution patterns. The spatial template was evaluated using the Principal Coordinates of Neighbor Matrix method. We recorded 14 074 individuals from 1 053 species and 80 families. The most abundant families were Myristicaceae, Moraceae, Meliaceae, Arecaceae and Lecythidaceae, coinciding with other studies from Northwest Amazonia. Beta diversity was relatively low within the plot. Soils were very poor, had high aluminum concentration and were predominantly clayey. The floristic differences explained along the ten hectares plot were mainly associated to biological processes, such as dispersal limitation. The largest proportion of community variation in our dataset was unexplained by either environmental or spatial data. In conclusion, these results support random processes as the major drivers of the spatial variation of tree species at a local scale on Tierra Firme forests of Amacayacu National Park, and suggest reserve's size as a key element to ensure the conservation of plant diversity at both regional and local levels.

Spatial distribution of neurons innervated by chandelier cells.

PubMed

Blazquez-Llorca, Lidia; Woodruff, Alan; Inan, Melis; Anderson, Stewart A; Yuste, Rafael; DeFelipe, Javier; Merchan-Perez, Angel

2015-09-01

Chandelier (or axo-axonic) cells are a distinct group of GABAergic interneurons that innervate the axon initial segments of pyramidal cells and are thus thought to have an important role in controlling the activity of cortical circuits. To examine the circuit connectivity of chandelier cells (ChCs), we made use of a genetic targeting strategy to label neocortical ChCs in upper layers of juvenile mouse neocortex. We filled individual ChCs with biocytin in living brain slices and reconstructed their axonal arbors from serial semi-thin sections. We also reconstructed the cell somata of pyramidal neurons that were located inside the ChC axonal trees and determined the percentage of pyramidal neurons whose axon initial segments were innervated by ChC terminals. We found that the total percentage of pyramidal neurons that were innervated by a single labeled ChC was 18-22 %. Sholl analysis showed that this percentage peaked at 22-35 % for distances between 30 and 60 µm from the ChC soma, decreasing to lower percentages with increasing distances. We also studied the three-dimensional spatial distribution of the innervated neurons inside the ChC axonal arbor using spatial statistical analysis tools. We found that innervated pyramidal neurons are not distributed at random, but show a clustered distribution, with pockets where almost all cells are innervated and other regions within the ChC axonal tree that receive little or no innervation. Thus, individual ChCs may exert a strong, widespread influence on their local pyramidal neighbors in a spatially heterogeneous fashion.

Naming games in two-dimensional and small-world-connected random geometric networks.

PubMed

Lu, Qiming; Korniss, G; Szymanski, B K

2008-01-01

We investigate a prototypical agent-based model, the naming game, on two-dimensional random geometric networks. The naming game [Baronchelli, J. Stat. Mech.: Theory Exp. (2006) P06014] is a minimal model, employing local communications that captures the emergence of shared communication schemes (languages) in a population of autonomous semiotic agents. Implementing the naming games with local broadcasts on random geometric graphs, serves as a model for agreement dynamics in large-scale, autonomously operating wireless sensor networks. Further, it captures essential features of the scaling properties of the agreement process for spatially embedded autonomous agents. Among the relevant observables capturing the temporal properties of the agreement process, we investigate the cluster-size distribution and the distribution of the agreement times, both exhibiting dynamic scaling. We also present results for the case when a small density of long-range communication links are added on top of the random geometric graph, resulting in a "small-world"-like network and yielding a significantly reduced time to reach global agreement. We construct a finite-size scaling analysis for the agreement times in this case.

The Spatial Pattern and Interactions of Woody Plants on the Temperate Savanna of Inner Mongolia, China: The Effects of Alternating Seasonal Grazing-Mowing Regimes

PubMed Central

2015-01-01

Ulmus pumila tree-dominated temperate savanna, which is distributed widely throughout the forest-steppe ecotone on the Mongolian Plateau, is a relatively stable woody-herbaceous complex ecosystem in northern China. Relatively more attention has been paid to the degradation of typical steppe areas, whereas less focus has been placed on the succession of this typical temperate savanna under the present management regime. In this study, we established 3 sample plots 100 m×100 m in size along a gradient of fixed distances from one herder’s stationary site and then surveyed all the woody plants in these plots. A spatial point pattern analysis was employed to clarify the spatial distribution and interaction of these woody plants. The results indicated that old U. pumila trees (DBH ≥ 20 cm) showed a random distribution and that medium U. pumila trees (5 cm ≤ DBH < 20 cm) showed an aggregated distribution at a smaller scale and a random distribution at a larger scale; few or no juvenile trees (DBH < 5 cm) were present, and seedlings (without DBH) formed aggregations in all 3 plots. These findings can be explained by an alternate seasonal grazing-mowing regime (exclosure in summer, mowing in autumn and grazing in winter and spring); the shrubs in all 3 plots exist along a grazing gradient that harbors xerophytic and mesophytic shrubs. Of these shrubs, xerophytic shrubs show significant aggregation at a smaller scale (0-5.5 m), whereas mesophytic shrubs show significant aggregation at a larger scale (0-25 m), which may be the result of the dual effects of grazing pressure and climate change. Medium trees and seedlings significantly facilitate the distributions of xerophytic shrubs and compete significantly with mesophytic shrubs due to differences in water use strategies. We conclude that the implementation of an alternative grazing-mowing regime results in xerophytic shrub encroachment or existence, breaking the chain of normal succession in a U. pumila tree community in this typical temperate savanna ecosystem. This might eventually result in the degradation of the original tree-dominated savanna to a xerophytic shrub-dominated savanna. PMID:26196956

Development of population structure and spatial distribution patterns of a restored forest during 17-year succession (1993-2010) in Pingshuo opencast mine spoil, China.

PubMed

Zhao, Zhongqiu; Wang, Lianhua; Bai, Zhongke; Pan, Ziguan; Wang, Yun

2015-07-01

Afforestation of native tree species is often recommended for ecological restoration in mining areas, but the understanding of the ecological processes of restored vegetation is quite limited. In order to provide insight of the ecological processes of restored vegetation, in this study, we investigate the development of the population structure and spatial distribution patterns of restored Robinia pseudoacacia (ROPS) and Pinus tabuliformis (PITA) mixed forests during the 17 years of the mine spoil period of the Pingshuo opencast mine, Shanxi Province, China. After a 17-year succession, apart from the two planted species, Ulmus pumila (ULPU), as an invasive species, settled in the plot along with a large number of small diameter at breast height (DBH) size. In total, there are 10,062 living individual plants, much more than that at the plantation (5105), and ROPS had become the dominant species with a section area with a breast height of 9.40 m(2) hm(-2) and a mean DBH of 6.72 cm, much higher than both PITA and ULPU. The DBH size classes of all the total species showed inverted J-shaped distributions, which may have been a result of the large number of small regenerated ULPU trees. The DBH size classes of both ROPS and PITA showed peak-type structures with individuals mainly gathering in the moderate DBH size class, indicating a relatively healthy DBH size class structure. Meanwhile, invasive ULPU were distributed in a clear L shape, concentrating on the small DBH size class, indicating a relatively low survival rate for adult trees. Both ROPS and PITA species survival in the plantation showed uniform and aggregated distribution at small scales and random with scales increasing. ULPU showed a strong aggregation at small scales as well as random with scales increasing. Both the population structure and spatial distribution indicated that ROPS dominates and will continue to dominate the community in the future succession, which should be continuously monitored.

Actual distribution of Cronobacter spp. in industrial batches of powdered infant formula and consequences for performance of sampling strategies.

PubMed

Jongenburger, I; Reij, M W; Boer, E P J; Gorris, L G M; Zwietering, M H

2011-11-15

The actual spatial distribution of microorganisms within a batch of food influences the results of sampling for microbiological testing when this distribution is non-homogeneous. In the case of pathogens being non-homogeneously distributed, it markedly influences public health risk. This study investigated the spatial distribution of Cronobacter spp. in powdered infant formula (PIF) on industrial batch-scale for both a recalled batch as well a reference batch. Additionally, local spatial occurrence of clusters of Cronobacter cells was assessed, as well as the performance of typical sampling strategies to determine the presence of the microorganisms. The concentration of Cronobacter spp. was assessed in the course of the filling time of each batch, by taking samples of 333 g using the most probable number (MPN) enrichment technique. The occurrence of clusters of Cronobacter spp. cells was investigated by plate counting. From the recalled batch, 415 MPN samples were drawn. The expected heterogeneous distribution of Cronobacter spp. could be quantified from these samples, which showed no detectable level (detection limit of -2.52 log CFU/g) in 58% of samples, whilst in the remainder concentrations were found to be between -2.52 and 2.75 log CFU/g. The estimated average concentration in the recalled batch was -2.78 log CFU/g and a standard deviation of 1.10 log CFU/g. The estimated average concentration in the reference batch was -4.41 log CFU/g, with 99% of the 93 samples being below the detection limit. In the recalled batch, clusters of cells occurred sporadically in 8 out of 2290 samples of 1g taken. The two largest clusters contained 123 (2.09 log CFU/g) and 560 (2.75 log CFU/g) cells. Various sampling strategies were evaluated for the recalled batch. Taking more and smaller samples and keeping the total sampling weight constant, considerably improved the performance of the sampling plans to detect such a type of contaminated batch. Compared to random sampling, stratified random sampling improved the probability to detect the heterogeneous contamination. Copyright © 2011 Elsevier B.V. All rights reserved.

Chromosome Model reveals Dynamic Redistribution of DNA Damage into Nuclear Sub-domains

NASA Technical Reports Server (NTRS)

Costes, Sylvain V.; Ponomarev, Artem; Chen, James L.; Cucinotta, Francis A.; Barcellos-Hoff, Helen

2007-01-01

Several proteins involved in the response to DNA double strand breaks (DSB) form microscopically visible nuclear domains, or foci, after exposure to ionizing radiation. Radiation-induced foci (RIF) are believed to be located where DNA damage is induced. To test this assumption, we analyzed the spatial distribution of 53BP1, phosphorylated ATM and gammaH2AX RIF in cells irradiated with high linear energy transfer (LET) radiation. Since energy is randomly deposited along high-LET particle paths, RIF along these paths should also be randomly distributed. The probability to induce DSB can be derived from DNA fragment data measured experimentally by pulsed-field gel electrophoresis. We used this probability in Monte Carlo simulations to predict DSB locations in synthetic nuclei geometrically described by a complete set of human chromosomes, taking into account microscope optics from real experiments. As expected, simulations produced DNA-weighted random (Poisson) distributions. In contrast, the distributions of RIF obtained as early as 5 min after exposure to high LET (1 GeV/amu Fe) were non-random. This deviation from the expected DNA-weighted random pattern can be further characterized by relative DNA image measurements. This novel imaging approach shows that RIF were located preferentially at the interface between high and low DNA density regions, and were more frequent in regions with lower density DNA than predicted. This deviation from random behavior was more pronounced within the first 5 min following irradiation for phosphorylated ATM RIF, while gammaH2AX and 53BP1 RIF showed very pronounced deviation up to 30 min after exposure. These data suggest the existence of repair centers in mammalian epithelial cells. These centers would be nuclear sub-domains where DNA lesions would be collected for more efficient repair.

Fluid-driven fracture propagation in heterogeneous media: Probability distributions of fracture trajectories

NASA Astrophysics Data System (ADS)

Santillán, David; Mosquera, Juan-Carlos; Cueto-Felgueroso, Luis

2017-11-01

Hydraulic fracture trajectories in rocks and other materials are highly affected by spatial heterogeneity in their mechanical properties. Understanding the complexity and structure of fluid-driven fractures and their deviation from the predictions of homogenized theories is a practical problem in engineering and geoscience. We conduct a Monte Carlo simulation study to characterize the influence of heterogeneous mechanical properties on the trajectories of hydraulic fractures propagating in elastic media. We generate a large number of random fields of mechanical properties and simulate pressure-driven fracture propagation using a phase-field model. We model the mechanical response of the material as that of an elastic isotropic material with heterogeneous Young modulus and Griffith energy release rate, assuming that fractures propagate in the toughness-dominated regime. Our study shows that the variance and the spatial covariance of the mechanical properties are controlling factors in the tortuousness of the fracture paths. We characterize the deviation of fracture paths from the homogenous case statistically, and conclude that the maximum deviation grows linearly with the distance from the injection point. Additionally, fracture path deviations seem to be normally distributed, suggesting that fracture propagation in the toughness-dominated regime may be described as a random walk.

Onset of natural convection in a continuously perturbed system

NASA Astrophysics Data System (ADS)

Ghorbani, Zohreh; Riaz, Amir

2017-11-01

The convective mixing triggered by gravitational instability plays an important role in CO2 sequestration in saline aquifers. The linear stability analysis and the numerical simulation concerning convective mixing in porous media requires perturbations of small amplitude to be imposed on the concentration field in the form of an initial shape function. In aquifers, however, the instability is triggered by local porosity and permeability. In this work, we consider a canonical 2D homogeneous system where perturbations arise due to spatial variation of porosity in the system. The advantage of this approach is not only the elimination of the required initial shape function, but it also serves as a more realistic approach. Using a reduced nonlinear method, we first explore the effect of harmonic variations of porosity in the transverse and streamwise direction on the onset time of convection and late time behavior. We then obtain the optimal porosity structure that minimizes the convection onset. We further examine the effect of a random porosity distribution, that is independent of the spatial mode of porosity structure, on the convection onset. Using high-order pseudospectral DNS, we explore how the random distribution differs from the modal approach in predicting the onset time.

Fluid-driven fracture propagation in heterogeneous media: Probability distributions of fracture trajectories.

PubMed

Santillán, David; Mosquera, Juan-Carlos; Cueto-Felgueroso, Luis

2017-11-01

Hydraulic fracture trajectories in rocks and other materials are highly affected by spatial heterogeneity in their mechanical properties. Understanding the complexity and structure of fluid-driven fractures and their deviation from the predictions of homogenized theories is a practical problem in engineering and geoscience. We conduct a Monte Carlo simulation study to characterize the influence of heterogeneous mechanical properties on the trajectories of hydraulic fractures propagating in elastic media. We generate a large number of random fields of mechanical properties and simulate pressure-driven fracture propagation using a phase-field model. We model the mechanical response of the material as that of an elastic isotropic material with heterogeneous Young modulus and Griffith energy release rate, assuming that fractures propagate in the toughness-dominated regime. Our study shows that the variance and the spatial covariance of the mechanical properties are controlling factors in the tortuousness of the fracture paths. We characterize the deviation of fracture paths from the homogenous case statistically, and conclude that the maximum deviation grows linearly with the distance from the injection point. Additionally, fracture path deviations seem to be normally distributed, suggesting that fracture propagation in the toughness-dominated regime may be described as a random walk.

Clustering Effect on the Dynamics in a Spatial Rock-Paper-Scissors System

NASA Astrophysics Data System (ADS)

Hashimoto, Tsuyoshi; Sato, Kazunori; Ichinose, Genki; Miyazaki, Rinko; Tainaka, Kei-ichi

2018-01-01

The lattice dynamics for rock-paper-scissors games is related to population theories in ecology. In most cases, simulations are performed by local and global interactions. It is known in the former case that the dynamics is usually stable. We find two types of non-random distributions in the stationary state. One is a cluster formation of endangered species: when the density of a species approaches zero, its clumping degree diverges to infinity. The other is the strong aggregations of high-density species. Such spatial pattern formations play important roles in population dynamics.

Seed-deposition and recruitment patterns of Clusia species in a disturbed tropical montane forest in Bolivia

NASA Astrophysics Data System (ADS)

Saavedra, Francisco; Hensen, Isabell; Apaza Quevedo, Amira; Neuschulz, Eike Lena; Schleuning, Matthias

2017-11-01

Spatial patterns of seed dispersal and recruitment of fleshy-fruited plants in tropical forests are supposed to be driven by the activity of animal seed dispersers, but the spatial patterns of seed dispersal, seedlings and saplings have rarely been analyzed simultaneously. We studied seed deposition and recruitment patterns of three Clusia species in a tropical montane forest of the Bolivian Andes and tested whether these patterns changed between habitat types (forest edge vs. forest interior), distance to the fruiting tree and consecutive recruitment stages of the seedlings. We recorded the number of seeds deposited in seed traps to assess the local seed-deposition pattern and the abundance and distribution of seedlings and saplings to evaluate the spatial pattern of recruitment. More seeds were removed and deposited at the forest edge than in the interior. The number of deposited seeds decreased with distance from the fruiting tree and was spatially clustered in both habitat types. The density of 1-yr-old seedlings and saplings was higher at forest edges, whereas the density of 2-yr-old seedlings was similar in both habitat types. While seedlings were almost randomly distributed, seeds and saplings were spatially clustered in both habitat types. Our findings demonstrate systematic changes in spatial patterns of recruits across the plant regeneration cycle and suggest that the differential effects of biotic and abiotic factors determine plant recruitment at the edges and in the interior of tropical montane forests. These differences in the spatial distribution of individuals across recruitment stages may have strong effects on plant community dynamics and influence plant species coexistence in disturbed tropical forests.

Geostatistical Characterization of Cereal Leaf Beetle (Coleoptera: Chrysomelidae) Distributions in Wheat.

PubMed

Reay-Jones, Francis P F

2017-08-01

A 3-yr study was conducted in wheat, Triticum aestivum L., in South Carolina to characterize the spatial distribution of Oulema melanopus (L.) adults, eggs, and larvae using semivariograms, which provides a measure of spatial dependence among sampling data. Moran's I coefficients for peak densities of each life stage indicated significant positive autocorrelation for seven (two for eggs, one for larvae, and four for adults) of the 16 datasets. Aggregation was detected in 13 of these 16 datasets when analyzed by semivariogram modeling, with spherical, Gaussian, and exponential models best fitting for eight, four, and one dataset, respectively, and with models for two datasets having only one parameter (nugget) significantly different from zero. The nugget-to-sill ratios ranged from 0.043 to 0.774, and indicated strong spatial dependence in six models (three for adults, two for eggs, and one for larvae), moderate spatial dependence in six models (three for adults and six for eggs), and weak spatial dependence in one model (adults). Range values varied from 39.1 m to 234.1 m, with an average of 120.1 ± 14.0 m. Average range values were 104.9, 135.2, and 161.2 m for adults, eggs, and larvae, respectively. Because the majority of semivariogram models in our study indicated aggregated distributions, spatial sampling will provide more information than nonspatial random sampling. Developing our understanding of spatial dependence of crop pests is needed to optimize sampling plans and can provide a basis for exploring site-specific management tactics. © The Authors 2017. Published by Oxford University Press on behalf of Entomological Society of America. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Brain MR image segmentation based on an improved active contour model

PubMed Central

Meng, Xiangrui; Gu, Wenya; Zhang, Jianwei

2017-01-01

It is often a difficult task to accurately segment brain magnetic resonance (MR) images with intensity in-homogeneity and noise. This paper introduces a novel level set method for simultaneous brain MR image segmentation and intensity inhomogeneity correction. To reduce the effect of noise, novel anisotropic spatial information, which can preserve more details of edges and corners, is proposed by incorporating the inner relationships among the neighbor pixels. Then the proposed energy function uses the multivariate Student's t-distribution to fit the distribution of the intensities of each tissue. Furthermore, the proposed model utilizes Hidden Markov random fields to model the spatial correlation between neigh-boring pixels/voxels. The means of the multivariate Student's t-distribution can be adaptively estimated by multiplying a bias field to reduce the effect of intensity inhomogeneity. In the end, we reconstructed the energy function to be convex and calculated it by using the Split Bregman method, which allows our framework for random initialization, thereby allowing fully automated applications. Our method can obtain the final result in less than 1 second for 2D image with size 256 × 256 and less than 300 seconds for 3D image with size 256 × 256 × 171. The proposed method was compared to other state-of-the-art segmentation methods using both synthetic and clinical brain MR images and increased the accuracies of the results more than 3%. PMID:28854235

Predicting active-layer soil thickness using topographic variables at a small watershed scale

PubMed Central

Li, Aidi; Tan, Xing; Wu, Wei; Liu, Hongbin; Zhu, Jie

2017-01-01

Knowledge about the spatial distribution of active-layer (AL) soil thickness is indispensable for ecological modeling, precision agriculture, and land resource management. However, it is difficult to obtain the details on AL soil thickness by using conventional soil survey method. In this research, the objective is to investigate the possibility and accuracy of mapping the spatial distribution of AL soil thickness through random forest (RF) model by using terrain variables at a small watershed scale. A total of 1113 soil samples collected from the slope fields were randomly divided into calibration (770 soil samples) and validation (343 soil samples) sets. Seven terrain variables including elevation, aspect, relative slope position, valley depth, flow path length, slope height, and topographic wetness index were derived from a digital elevation map (30 m). The RF model was compared with multiple linear regression (MLR), geographically weighted regression (GWR) and support vector machines (SVM) approaches based on the validation set. Model performance was evaluated by precision criteria of mean error (ME), mean absolute error (MAE), root mean square error (RMSE), and coefficient of determination (R2). Comparative results showed that RF outperformed MLR, GWR and SVM models. The RF gave better values of ME (0.39 cm), MAE (7.09 cm), and RMSE (10.85 cm) and higher R2 (62%). The sensitivity analysis demonstrated that the DEM had less uncertainty than the AL soil thickness. The outcome of the RF model indicated that elevation, flow path length and valley depth were the most important factors affecting the AL soil thickness variability across the watershed. These results demonstrated the RF model is a promising method for predicting spatial distribution of AL soil thickness using terrain parameters. PMID:28877196

Introducing Perception and Modelling of Spatial Randomness in Classroom

ERIC Educational Resources Information Center

De Nóbrega, José Renato

2017-01-01

A strategy to facilitate understanding of spatial randomness is described, using student activities developed in sequence: looking at spatial patterns, simulating approximate spatial randomness using a grid of equally-likely squares, using binomial probabilities for approximations and predictions and then comparing with given Poisson…

The distribution of catchment coverage by stationary rainstorms

NASA Technical Reports Server (NTRS)

Eagleson, P. S.

1984-01-01

The occurrence of wetted rainstorm area within a catchment is modeled as a Poisson arrival process in which each storm is composed of stationary, nonoverlapping, independent random cell clusters whose centers are Poisson-distributed in space and whose areas are fractals. The two Poisson parameters and hence the first two moments of the wetted fraction are derived in terms of catchment average characteristics of the (observable) station precipitation. The model is used to estimate spatial properties of tropical air mass thunderstorms on six tropical catchments in the Sudan.

Bayesian spatial transformation models with applications in neuroimaging data.

PubMed

Miranda, Michelle F; Zhu, Hongtu; Ibrahim, Joseph G

2013-12-01

The aim of this article is to develop a class of spatial transformation models (STM) to spatially model the varying association between imaging measures in a three-dimensional (3D) volume (or 2D surface) and a set of covariates. The proposed STM include a varying Box-Cox transformation model for dealing with the issue of non-Gaussian distributed imaging data and a Gaussian Markov random field model for incorporating spatial smoothness of the imaging data. Posterior computation proceeds via an efficient Markov chain Monte Carlo algorithm. Simulations and real data analysis demonstrate that the STM significantly outperforms the voxel-wise linear model with Gaussian noise in recovering meaningful geometric patterns. Our STM is able to reveal important brain regions with morphological changes in children with attention deficit hyperactivity disorder. © 2013, The International Biometric Society.

Hyperspectral Image Classification With Markov Random Fields and a Convolutional Neural Network

NASA Astrophysics Data System (ADS)

Cao, Xiangyong; Zhou, Feng; Xu, Lin; Meng, Deyu; Xu, Zongben; Paisley, John

2018-05-01

This paper presents a new supervised classification algorithm for remotely sensed hyperspectral image (HSI) which integrates spectral and spatial information in a unified Bayesian framework. First, we formulate the HSI classification problem from a Bayesian perspective. Then, we adopt a convolutional neural network (CNN) to learn the posterior class distributions using a patch-wise training strategy to better use the spatial information. Next, spatial information is further considered by placing a spatial smoothness prior on the labels. Finally, we iteratively update the CNN parameters using stochastic gradient decent (SGD) and update the class labels of all pixel vectors using an alpha-expansion min-cut-based algorithm. Compared with other state-of-the-art methods, the proposed classification method achieves better performance on one synthetic dataset and two benchmark HSI datasets in a number of experimental settings.

[Studies on main interspecific association of rare and endangered medicinal plant Sinopodophyllum hexandrum community in Kangding Zheduo mountain of Sichuan province].

PubMed

Liu, Xiang; Zhao, Ji-Feng; Wang, Chang-Hua; Zhang, Zhi-Wei; Qin, Song-Yun; Zhong, Guo-Yue

2014-07-01

Based on the 2 x 2 contingency table, by using multi-species relevance (variance ratio, VR), chi2-test, Ochiai index, Dice index, Jaccard index, t-test of v/x and F-test of Morisita, s index, the interspecific relationships and the spatial distribution pattern between 20 dominants in Kangding Zheduo Mountain of Sichuan province were studied. The results indicated that the interspecific association between dominants of Sinopodophyllum hexandrum community in this area did not show significant association, which suggested that the S. hexandrum community was in mature stage, and showed stronger independency, among total 190 pairs in 20 dominant species, 2 species pairs exhibited extremely significantly positive association, 12 species pairs showed significantly positive association, 6 species pairs exhibited significantly negative association and there were no pairs showed extremely significantly negative association. S. hexandrum in community did not show significant association, which indicates they are independent in community, the spatial distribution pattern of S. hexandrum is characterized by random distribution.

Low LET proton microbeam to understand high-LET RBE by shaping spatial dose distribution

NASA Astrophysics Data System (ADS)

Greubel, Christoph; Ilicic, Katarina; Rösch, Thomas; Reindl, Judith; Siebenwirth, Christian; Moser, Marcus; Girst, Stefanie; Walsh, Dietrich W. M.; Schmid, Thomas E.; Dollinger, Günther

2017-08-01

High LET radiation, like heavy ions, are known to have a higher biological effectiveness (RBE) compared to low LET radiation, like X- or γ -rays. Theories and models attribute these higher effectiveness mostly to their extremely inhomogeneous dose deposition, which is concentrated in only a few micron sized spots. At the ion microprobe SNAKE, low LET 20 MeV protons (LET in water of 2.6 keV/μm) can be applied to cells either randomly distributed or focused to submicron spots, approximating heavy ion dose deposition. Thus, the transition between low and high LET energy deposition is experimentally accessible and the effect of different spatial dose distributions can be analysed. Here, we report on the technical setup to cultivate and irradiate 104 cells with submicron spots of low LET protons to measure cell survival in unstained cells. In addition we have taken special care to characterise the beam spot of the 20 MeV proton microbeam with fluorescent nuclear track detectors.

Valley s'Asymmetric Characteristics of the Loess Plateau in Northwestern Shanxi Based on DEM

NASA Astrophysics Data System (ADS)

Duan, J.

2016-12-01

The valleys of the Loess Plateau in northwestern Shanxi show great asymmetry. This study using multi-scale DEMs, high-resolution satellite images and digital terrain analysis method, put forward a quantitative index to describe the asymmetric morphology. Several typical areas are selected to test and verify the spatial variability. Results show: (1) Considering the difference of spatial distribution, Pianguanhe basin, Xianchuanhe basin and Yangjiachuan basin are the areas where show most significant asymmetric characteristics . (2) Considering the difference of scale, the shape of large-scale valleys represents three characteristics: randomness, equilibrium and relative symmetry, while small-scale valleys show directionality and asymmetry. (3) Asymmetric morphology performs orientation, and the east-west valleys extremely obvious. Combined with field survey, its formation mechanism can be interpreted as follows :(1)Loess uneven distribution in the valleys. (2) The distribution diversities of vegetation, water , heat conditions and other factors, make a difference in water erosion capability which leads to asymmetric characteristics.

How selection structures species abundance distributions

PubMed Central

Magurran, Anne E.; Henderson, Peter A.

2012-01-01

How do species divide resources to produce the characteristic species abundance distributions seen in nature? One way to resolve this problem is to examine how the biomass (or capacity) of the spatial guilds that combine to produce an abundance distribution is allocated among species. Here we argue that selection on body size varies across guilds occupying spatially distinct habitats. Using an exceptionally well-characterized estuarine fish community, we show that biomass is concentrated in large bodied species in guilds where habitat structure provides protection from predators, but not in those guilds associated with open habitats and where safety in numbers is a mechanism for reducing predation risk. We further demonstrate that while there is temporal turnover in the abundances and identities of species that comprise these guilds, guild rank order is conserved across our 30-year time series. These results demonstrate that ecological communities are not randomly assembled but can be decomposed into guilds where capacity is predictably allocated among species. PMID:22787020

Time-variant Lagrangian transport formulation reduces aggregation bias of water and solute mean travel time in heterogeneous catchments

NASA Astrophysics Data System (ADS)

Danesh-Yazdi, Mohammad; Botter, Gianluca; Foufoula-Georgiou, Efi

2017-05-01

Lack of hydro-bio-chemical data at subcatchment scales necessitates adopting an aggregated system approach for estimating water and solute transport properties, such as residence and travel time distributions, at the catchment scale. In this work, we show that within-catchment spatial heterogeneity, as expressed in spatially variable discharge-storage relationships, can be appropriately encapsulated within a lumped time-varying stochastic Lagrangian formulation of transport. This time (variability) for space (heterogeneity) substitution yields mean travel times (MTTs) that are not significantly biased to the aggregation of spatial heterogeneity. Despite the significant variability of MTT at small spatial scales, there exists a characteristic scale above which the MTT is not impacted by the aggregation of spatial heterogeneity. Extensive simulations of randomly generated river networks reveal that the ratio between the characteristic scale and the mean incremental area is on average independent of river network topology and the spatial arrangement of incremental areas.

Clustering, randomness, and regularity in cloud fields: 2. Cumulus cloud fields

NASA Astrophysics Data System (ADS)

Zhu, T.; Lee, J.; Weger, R. C.; Welch, R. M.

1992-12-01

During the last decade a major controversy has been brewing concerning the proper characterization of cumulus convection. The prevailing view has been that cumulus clouds form in clusters, in which cloud spacing is closer than that found for the overall cloud field and which maintains its identity over many cloud lifetimes. This "mutual protection hypothesis" of Randall and Huffman (1980) has been challenged by the "inhibition hypothesis" of Ramirez et al. (1990) which strongly suggests that the spatial distribution of cumuli must tend toward a regular distribution. A dilemma has resulted because observations have been reported to support both hypotheses. The present work reports a detailed analysis of cumulus cloud field spatial distributions based upon Landsat, Advanced Very High Resolution Radiometer, and Skylab data. Both nearest-neighbor and point-to-cloud cumulative distribution function statistics are investigated. The results show unequivocally that when both large and small clouds are included in the cloud field distribution, the cloud field always has a strong clustering signal. The strength of clustering is largest at cloud diameters of about 200-300 m, diminishing with increasing cloud diameter. In many cases, clusters of small clouds are found which are not closely associated with large clouds. As the small clouds are eliminated from consideration, the cloud field typically tends towards regularity. Thus it would appear that the "inhibition hypothesis" of Ramirez and Bras (1990) has been verified for the large clouds. However, these results are based upon the analysis of point processes. A more exact analysis also is made which takes into account the cloud size distributions. Since distinct clouds are by definition nonoverlapping, cloud size effects place a restriction upon the possible locations of clouds in the cloud field. The net effect of this analysis is that the large clouds appear to be randomly distributed, with only weak tendencies towards regularity. For clouds less than 1 km in diameter, the average nearest-neighbor distance is equal to 3-7 cloud diameters. For larger clouds, the ratio of cloud nearest-neighbor distance to cloud diameter increases sharply with increasing cloud diameter. This demonstrates that large clouds inhibit the growth of other large clouds in their vicinity. Nevertheless, this leads to random distributions of large clouds, not regularity.

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

Measuring forest landscape patterns in the Cascade Range of Oregon, USA

NASA Technical Reports Server (NTRS)

Ripple, William J.; Bradshaw, G. A.; Spies, Thomas A.

1995-01-01

This paper describes the use of a set of spatial statistics to quantify the landscape pattern caused by the patchwork of clearcuts made over a 15-year period in the western Cascades of Oregon. Fifteen areas were selected at random to represent a diversity of landscape fragmentation patterns. Managed forest stands (patches) were digitized and analyzed to produce both tabular and mapped information describing patch size, shape, abundance and spacing, and matrix characteristics of a given area. In addition, a GIS fragmentation index was developed which was found to be sensitive to patch abundance and to the spatial distribution of patches. Use of the GIS-derived index provides an automated method of determining the level of forest fragmentation and can be used to facilitate spatial analysis of the landscape for later coordination with field and remotely sensed data. A comparison of the spatial statistics calculated for the two years indicates an increase in forest fragmentation as characterized by an increase in mean patch abundance and a decrease in interpatch distance, amount of interior natural forest habitat, and the GIS fragmentation index. Such statistics capable of quantifying patch shape and spatial distribution may prove important in the evaluation of the changing character of interior and edge habitats for wildlife.

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.

Capturing spatial heterogeneity of soil organic carbon under changing climate

NASA Astrophysics Data System (ADS)

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

2015-12-01

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

Tensor Minkowski Functionals for random fields on the sphere

NASA Astrophysics Data System (ADS)

Chingangbam, Pravabati; Yogendran, K. P.; Joby, P. K.; Ganesan, Vidhya; Appleby, Stephen; Park, Changbom

2017-12-01

We generalize the translation invariant tensor-valued Minkowski Functionals which are defined on two-dimensional flat space to the unit sphere. We apply them to level sets of random fields. The contours enclosing boundaries of level sets of random fields give a spatial distribution of random smooth closed curves. We outline a method to compute the tensor-valued Minkowski Functionals numerically for any random field on the sphere. Then we obtain analytic expressions for the ensemble expectation values of the matrix elements for isotropic Gaussian and Rayleigh fields. The results hold on flat as well as any curved space with affine connection. We elucidate the way in which the matrix elements encode information about the Gaussian nature and statistical isotropy (or departure from isotropy) of the field. Finally, we apply the method to maps of the Galactic foreground emissions from the 2015 PLANCK data and demonstrate their high level of statistical anisotropy and departure from Gaussianity.

Inflation with a graceful exit in a random landscape

NASA Astrophysics Data System (ADS)

Pedro, F. G.; Westphal, A.

2017-03-01

We develop a stochastic description of small-field inflationary histories with a graceful exit in a random potential whose Hessian is a Gaussian random matrix as a model of the unstructured part of the string landscape. The dynamical evolution in such a random potential from a small-field inflation region towards a viable late-time de Sitter (dS) minimum maps to the dynamics of Dyson Brownian motion describing the relaxation of non-equilibrium eigenvalue spectra in random matrix theory. We analytically compute the relaxation probability in a saddle point approximation of the partition function of the eigenvalue distribution of the Wigner ensemble describing the mass matrices of the critical points. When applied to small-field inflation in the landscape, this leads to an exponentially strong bias against small-field ranges and an upper bound N ≪ 10 on the number of light fields N participating during inflation from the non-observation of negative spatial curvature.

A phylogenetic perspective on the individual species-area relationship in temperate and tropical tree communities.

PubMed

Yang, Jie; Swenson, Nathan G; Cao, Min; Chuyong, George B; Ewango, Corneille E N; Howe, Robert; Kenfack, David; Thomas, Duncan; Wolf, Amy; Lin, Luxiang

2013-01-01

Ecologists have historically used species-area relationships (SARs) as a tool to understand the spatial distribution of species. Recent work has extended SARs to focus on individual-level distributions to generate individual species area relationships (ISARs). The ISAR approach quantifies whether individuals of a species tend have more or less species richness surrounding them than expected by chance. By identifying richness 'accumulators' and 'repellers', respectively, the ISAR approach has been used to infer the relative importance of abiotic and biotic interactions and neutrality. A clear limitation of the SAR and ISAR approaches is that all species are treated as evolutionarily independent and that a large amount of work has now shown that local tree neighborhoods exhibit non-random phylogenetic structure given the species richness. Here, we use nine tropical and temperate forest dynamics plots to ask: (i) do ISARs change predictably across latitude?; (ii) is the phylogenetic diversity in the neighborhood of species accumulators and repellers higher or lower than that expected given the observed species richness?; and (iii) do species accumulators, repellers distributed non-randomly on the community phylogenetic tree? The results indicate no clear trend in ISARs from the temperate zone to the tropics and that the phylogenetic diversity surrounding the individuals of species is generally only non-random on very local scales. Interestingly the distribution of species accumulators and repellers was non-random on the community phylogenies suggesting the presence of phylogenetic signal in the ISAR across latitude.

Stimulated luminescence emission from localized recombination in randomly distributed defects.

PubMed

Jain, Mayank; Guralnik, Benny; Andersen, Martin Thalbitzer

2012-09-26

We present a new kinetic model describing localized electronic recombination through the excited state of the donor (d) to an acceptor (a) centre in luminescent materials. In contrast to the existing models based on the localized transition model (LTM) of Halperin and Braner (1960 Phys. Rev. 117 408-15) which assumes a fixed d → a tunnelling probability for the entire crystal, our model is based on nearest-neighbour recombination within randomly distributed centres. Such a random distribution can occur through the entire volume or within the defect complexes of the dosimeter, and implies that the tunnelling probability varies with the donor-acceptor (d-a) separation distance. We first develop an 'exact kinetic model' that incorporates this variation in tunnelling probabilities, and evolves both in spatial as well as temporal domains. We then develop a simplified one-dimensional, semi-analytical model that evolves only in the temporal domain. An excellent agreement is observed between thermally and optically stimulated luminescence (TL and OSL) results produced from the two models. In comparison to the first-order kinetic behaviour of the LTM of Halperin and Braner (1960 Phys. Rev. 117 408-15), our model results in a highly asymmetric TL peak; this peak can be understood to derive from a continuum of several first-order TL peaks. Our model also shows an extended power law behaviour for OSL (or prompt luminescence), which is expected from localized recombination mechanisms in materials with random distribution of centres.

SU-F-BRD-09: A Random Walk Model Algorithm for Proton Dose Calculation

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

Yao, W; Farr, J

2015-06-15

Purpose: To develop a random walk model algorithm for calculating proton dose with balanced computation burden and accuracy. Methods: Random walk (RW) model is sometimes referred to as a density Monte Carlo (MC) simulation. In MC proton dose calculation, the use of Gaussian angular distribution of protons due to multiple Coulomb scatter (MCS) is convenient, but in RW the use of Gaussian angular distribution requires an extremely large computation and memory. Thus, our RW model adopts spatial distribution from the angular one to accelerate the computation and to decrease the memory usage. From the physics and comparison with the MCmore » simulations, we have determined and analytically expressed those critical variables affecting the dose accuracy in our RW model. Results: Besides those variables such as MCS, stopping power, energy spectrum after energy absorption etc., which have been extensively discussed in literature, the following variables were found to be critical in our RW model: (1) inverse squared law that can significantly reduce the computation burden and memory, (2) non-Gaussian spatial distribution after MCS, and (3) the mean direction of scatters at each voxel. In comparison to MC results, taken as reference, for a water phantom irradiated by mono-energetic proton beams from 75 MeV to 221.28 MeV, the gamma test pass rate was 100% for the 2%/2mm/10% criterion. For a highly heterogeneous phantom consisting of water embedded by a 10 cm cortical bone and a 10 cm lung in the Bragg peak region of the proton beam, the gamma test pass rate was greater than 98% for the 3%/3mm/10% criterion. Conclusion: We have determined key variables in our RW model for proton dose calculation. Compared with commercial pencil beam algorithms, our RW model much improves the dose accuracy in heterogeneous regions, and is about 10 times faster than MC simulations.« less

Geometrical effects on the electron residence time in semiconductor nano-particles

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

Koochi, Hakimeh; Ebrahimi, Fatemeh, E-mail: f-ebrahimi@birjand.ac.ir; Solar Energy Research Group, University of Birjand, Birjand

2014-09-07

We have used random walk (RW) numerical simulations to investigate the influence of the geometry on the statistics of the electron residence time τ{sub r} in a trap-limited diffusion process through semiconductor nano-particles. This is an important parameter in coarse-grained modeling of charge carrier transport in nano-structured semiconductor films. The traps have been distributed randomly on the surface (r{sup 2} model) or through the whole particle (r{sup 3} model) with a specified density. The trap energies have been taken from an exponential distribution and the traps release time is assumed to be a stochastic variable. We have carried out (RW)more » simulations to study the effect of coordination number, the spatial arrangement of the neighbors and the size of nano-particles on the statistics of τ{sub r}. It has been observed that by increasing the coordination number n, the average value of electron residence time, τ{sup ¯}{sub r} rapidly decreases to an asymptotic value. For a fixed coordination number n, the electron's mean residence time does not depend on the neighbors' spatial arrangement. In other words, τ{sup ¯}{sub r} is a porosity-dependence, local parameter which generally varies remarkably from site to site, unless we are dealing with highly ordered structures. We have also examined the effect of nano-particle size d on the statistical behavior of τ{sup ¯}{sub r}. Our simulations indicate that for volume distribution of traps, τ{sup ¯}{sub r} scales as d{sup 2}. For a surface distribution of traps τ{sup ¯}{sub r} increases almost linearly with d. This leads to the prediction of a linear dependence of the diffusion coefficient D on the particle size d in ordered structures or random structures above the critical concentration which is in accordance with experimental observations.« less

Sampling procedures for inventory of commercial volume tree species in Amazon Forest.

PubMed

Netto, Sylvio P; Pelissari, Allan L; Cysneiros, Vinicius C; Bonazza, Marcelo; Sanquetta, Carlos R

2017-01-01

The spatial distribution of tropical tree species can affect the consistency of the estimators in commercial forest inventories, therefore, appropriate sampling procedures are required to survey species with different spatial patterns in the Amazon Forest. For this, the present study aims to evaluate the conventional sampling procedures and introduce the adaptive cluster sampling for volumetric inventories of Amazonian tree species, considering the hypotheses that the density, the spatial distribution and the zero-plots affect the consistency of the estimators, and that the adaptive cluster sampling allows to obtain more accurate volumetric estimation. We use data from a census carried out in Jamari National Forest, Brazil, where trees with diameters equal to or higher than 40 cm were measured in 1,355 plots. Species with different spatial patterns were selected and sampled with simple random sampling, systematic sampling, linear cluster sampling and adaptive cluster sampling, whereby the accuracy of the volumetric estimation and presence of zero-plots were evaluated. The sampling procedures applied to species were affected by the low density of trees and the large number of zero-plots, wherein the adaptive clusters allowed concentrating the sampling effort in plots with trees and, thus, agglutinating more representative samples to estimate the commercial volume.

Discriminative Random Field Models for Subsurface Contamination Uncertainty Quantification

NASA Astrophysics Data System (ADS)

Arshadi, M.; Abriola, L. M.; Miller, E. L.; De Paolis Kaluza, C.

2017-12-01

Application of flow and transport simulators for prediction of the release, entrapment, and persistence of dense non-aqueous phase liquids (DNAPLs) and associated contaminant plumes is a computationally intensive process that requires specification of a large number of material properties and hydrologic/chemical parameters. Given its computational burden, this direct simulation approach is particularly ill-suited for quantifying both the expected performance and uncertainty associated with candidate remediation strategies under real field conditions. Prediction uncertainties primarily arise from limited information about contaminant mass distributions, as well as the spatial distribution of subsurface hydrologic properties. Application of direct simulation to quantify uncertainty would, thus, typically require simulating multiphase flow and transport for a large number of permeability and release scenarios to collect statistics associated with remedial effectiveness, a computationally prohibitive process. The primary objective of this work is to develop and demonstrate a methodology that employs measured field data to produce equi-probable stochastic representations of a subsurface source zone that capture the spatial distribution and uncertainty associated with key features that control remediation performance (i.e., permeability and contamination mass). Here we employ probabilistic models known as discriminative random fields (DRFs) to synthesize stochastic realizations of initial mass distributions consistent with known, and typically limited, site characterization data. Using a limited number of full scale simulations as training data, a statistical model is developed for predicting the distribution of contaminant mass (e.g., DNAPL saturation and aqueous concentration) across a heterogeneous domain. Monte-Carlo sampling methods are then employed, in conjunction with the trained statistical model, to generate realizations conditioned on measured borehole data. Performance of the statistical model is illustrated through comparisons of generated realizations with the `true' numerical simulations. Finally, we demonstrate how these realizations can be used to determine statistically optimal locations for further interrogation of the subsurface.

A Game of Hide and Seek: Expectations of Clumpy Resources Influence Hiding and Searching Patterns

PubMed Central

Wilke, Andreas; Minich, Steven; Panis, Megane; Langen, Tom A.; Skufca, Joseph D.; Todd, Peter M.

2015-01-01

Resources are often distributed in clumps or patches in space, unless an agent is trying to protect them from discovery and theft using a dispersed distribution. We uncover human expectations of such spatial resource patterns in collaborative and competitive settings via a sequential multi-person game in which participants hid resources for the next participant to seek. When collaborating, resources were mostly hidden in clumpy distributions, but when competing, resources were hidden in more dispersed (random or hyperdispersed) patterns to increase the searching difficulty for the other player. More dispersed resource distributions came at the cost of higher overall hiding (as well as searching) times, decreased payoffs, and an increased difficulty when the hider had to recall earlier hiding locations at the end of the experiment. Participants’ search strategies were also affected by their underlying expectations, using a win-stay lose-shift strategy appropriate for clumpy resources when searching for collaboratively-hidden items, but moving equally far after finding or not finding an item in competitive settings, as appropriate for dispersed resources. Thus participants showed expectations for clumpy versus dispersed spatial resources that matched the distributions commonly found in collaborative versus competitive foraging settings. PMID:26154661

Gradients estimation from random points with volumetric tensor in turbulence

NASA Astrophysics Data System (ADS)

Watanabe, Tomoaki; Nagata, Koji

2017-12-01

We present an estimation method of fully-resolved/coarse-grained gradients from randomly distributed points in turbulence. The method is based on a linear approximation of spatial gradients expressed with the volumetric tensor, which is a 3 × 3 matrix determined by a geometric distribution of the points. The coarse grained gradient can be considered as a low pass filtered gradient, whose cutoff is estimated with the eigenvalues of the volumetric tensor. The present method, the volumetric tensor approximation, is tested for velocity and passive scalar gradients in incompressible planar jet and mixing layer. Comparison with a finite difference approximation on a Cartesian grid shows that the volumetric tensor approximation computes the coarse grained gradients fairly well at a moderate computational cost under various conditions of spatial distributions of points. We also show that imposing the solenoidal condition improves the accuracy of the present method for solenoidal vectors, such as a velocity vector in incompressible flows, especially when the number of the points is not large. The volumetric tensor approximation with 4 points poorly estimates the gradient because of anisotropic distribution of the points. Increasing the number of points from 4 significantly improves the accuracy. Although the coarse grained gradient changes with the cutoff length, the volumetric tensor approximation yields the coarse grained gradient whose magnitude is close to the one obtained by the finite difference. We also show that the velocity gradient estimated with the present method well captures the turbulence characteristics such as local flow topology, amplification of enstrophy and strain, and energy transfer across scales.

Shade tree spatial structure and pod production explain frosty pod rot intensity in cacao agroforests, Costa Rica.

PubMed

Gidoin, Cynthia; Avelino, Jacques; Deheuvels, Olivier; Cilas, Christian; Bieng, Marie Ange Ngo

2014-03-01

Vegetation composition and plant spatial structure affect disease intensity through resource and microclimatic variation effects. The aim of this study was to evaluate the independent effect and relative importance of host composition and plant spatial structure variables in explaining disease intensity at the plot scale. For that purpose, frosty pod rot intensity, a disease caused by Moniliophthora roreri on cacao pods, was monitored in 36 cacao agroforests in Costa Rica in order to assess the vegetation composition and spatial structure variables conducive to the disease. Hierarchical partitioning was used to identify the most causal factors. Firstly, pod production, cacao tree density and shade tree spatial structure had significant independent effects on disease intensity. In our case study, the amount of susceptible tissue was the most relevant host composition variable for explaining disease intensity by resource dilution. Indeed, cacao tree density probably affected disease intensity more by the creation of self-shading rather than by host dilution. Lastly, only regularly distributed forest trees, and not aggregated or randomly distributed forest trees, reduced disease intensity in comparison to plots with a low forest tree density. A regular spatial structure is probably crucial to the creation of moderate and uniform shade as recommended for frosty pod rot management. As pod production is an important service expected from these agroforests, shade tree spatial structure may be a lever for integrated management of frosty pod rot in cacao agroforests.

Simulating Pre-Asymptotic, Non-Fickian Transport Although Doing Simple Random Walks - Supported By Empirical Pore-Scale Velocity Distributions and Memory Effects

NASA Astrophysics Data System (ADS)

Most, S.; Jia, N.; Bijeljic, B.; Nowak, W.

2016-12-01

Pre-asymptotic characteristics are almost ubiquitous when analyzing solute transport processes in porous media. These pre-asymptotic aspects are caused by spatial coherence in the velocity field and by its heterogeneity. For the Lagrangian perspective of particle displacements, the causes of pre-asymptotic, non-Fickian transport are skewed velocity distribution, statistical dependencies between subsequent increments of particle positions (memory) and dependence between the x, y and z-components of particle increments. Valid simulation frameworks should account for these factors. We propose a particle tracking random walk (PTRW) simulation technique that can use empirical pore-space velocity distributions as input, enforces memory between subsequent random walk steps, and considers cross dependence. Thus, it is able to simulate pre-asymptotic non-Fickian transport phenomena. Our PTRW framework contains an advection/dispersion term plus a diffusion term. The advection/dispersion term produces time-series of particle increments from the velocity CDFs. These time series are equipped with memory by enforcing that the CDF values of subsequent velocities change only slightly. The latter is achieved through a random walk on the axis of CDF values between 0 and 1. The virtual diffusion coefficient for that random walk is our only fitting parameter. Cross-dependence can be enforced by constraining the random walk to certain combinations of CDF values between the three velocity components in x, y and z. We will show that this modelling framework is capable of simulating non-Fickian transport by comparison with a pore-scale transport simulation and we analyze the approach to asymptotic behavior.

Generalized index for spatial data sets as a measure of complete spatial randomness

NASA Astrophysics Data System (ADS)

Hackett-Jones, Emily J.; Davies, Kale J.; Binder, Benjamin J.; Landman, Kerry A.

2012-06-01

Spatial data sets, generated from a wide range of physical systems can be analyzed by counting the number of objects in a set of bins. Previous work has been limited to equal-sized bins, which are inappropriate for some domains (e.g., circular). We consider a nonequal size bin configuration whereby overlapping or nonoverlapping bins cover the domain. A generalized index, defined in terms of a variance between bin counts, is developed to indicate whether or not a spatial data set, generated from exclusion or nonexclusion processes, is at the complete spatial randomness (CSR) state. Limiting values of the index are determined. Using examples, we investigate trends in the generalized index as a function of density and compare the results with those using equal size bins. The smallest bin size must be much larger than the mean size of the objects. We can determine whether a spatial data set is at the CSR state or not by comparing the values of a generalized index for different bin configurations—the values will be approximately the same if the data is at the CSR state, while the values will differ if the data set is not at the CSR state. In general, the generalized index is lower than the limiting value of the index, since objects do not have access to the entire region due to blocking by other objects. These methods are applied to two applications: (i) spatial data sets generated from a cellular automata model of cell aggregation in the enteric nervous system and (ii) a known plant data distribution.

Spatially patterned matrix elasticity directs stem cell fate

NASA Astrophysics Data System (ADS)

Yang, Chun; DelRio, Frank W.; Ma, Hao; Killaars, Anouk R.; Basta, Lena P.; Kyburz, Kyle A.; Anseth, Kristi S.

2016-08-01

There is a growing appreciation for the functional role of matrix mechanics in regulating stem cell self-renewal and differentiation processes. However, it is largely unknown how subcellular, spatial mechanical variations in the local extracellular environment mediate intracellular signal transduction and direct cell fate. Here, the effect of spatial distribution, magnitude, and organization of subcellular matrix mechanical properties on human mesenchymal stem cell (hMSCs) function was investigated. Exploiting a photodegradation reaction, a hydrogel cell culture substrate was fabricated with regions of spatially varied and distinct mechanical properties, which were subsequently mapped and quantified by atomic force microscopy (AFM). The variations in the underlying matrix mechanics were found to regulate cellular adhesion and transcriptional events. Highly spread, elongated morphologies and higher Yes-associated protein (YAP) activation were observed in hMSCs seeded on hydrogels with higher concentrations of stiff regions in a dose-dependent manner. However, when the spatial organization of the mechanically stiff regions was altered from a regular to randomized pattern, lower levels of YAP activation with smaller and more rounded cell morphologies were induced in hMSCs. We infer from these results that irregular, disorganized variations in matrix mechanics, compared with regular patterns, appear to disrupt actin organization, and lead to different cell fates; this was verified by observations of lower alkaline phosphatase (ALP) activity and higher expression of CD105, a stem cell marker, in hMSCs in random versus regular patterns of mechanical properties. Collectively, this material platform has allowed innovative experiments to elucidate a novel spatial mechanical dosing mechanism that correlates to both the magnitude and organization of spatial stiffness.

Rationalizing spatial exploration patterns of wild animals and humans through a temporal discounting framework.

PubMed

Namboodiri, Vijay Mohan K; Levy, Joshua M; Mihalas, Stefan; Sims, David W; Hussain Shuler, Marshall G

2016-08-02

Understanding the exploration patterns of foragers in the wild provides fundamental insight into animal behavior. Recent experimental evidence has demonstrated that path lengths (distances between consecutive turns) taken by foragers are well fitted by a power law distribution. Numerous theoretical contributions have posited that "Lévy random walks"-which can produce power law path length distributions-are optimal for memoryless agents searching a sparse reward landscape. It is unclear, however, whether such a strategy is efficient for cognitively complex agents, from wild animals to humans. Here, we developed a model to explain the emergence of apparent power law path length distributions in animals that can learn about their environments. In our model, the agent's goal during search is to build an internal model of the distribution of rewards in space that takes into account the cost of time to reach distant locations (i.e., temporally discounting rewards). For an agent with such a goal, we find that an optimal model of exploration in fact produces hyperbolic path lengths, which are well approximated by power laws. We then provide support for our model by showing that humans in a laboratory spatial exploration task search space systematically and modify their search patterns under a cost of time. In addition, we find that path length distributions in a large dataset obtained from free-ranging marine vertebrates are well described by our hyperbolic model. Thus, we provide a general theoretical framework for understanding spatial exploration patterns of cognitively complex foragers.

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.

Seasonal changes in spatial patterns of two annual plants in the Chihuahuan Desert, USA

USGS Publications Warehouse

Yin, Z.-Y.; Guo, Q.; Ren, H.; Peng, S.-L.

2005-01-01

Spatial pattern of a biotic population may change over time as its component individuals grow or die out, but whether this is the case for desert annual plants is largely unknown. Here we examined seasonal changes in spatial patterns of two annuals, Eriogonum abertianum and Haplopappus gracilis, in initial (winter) and final (summer) densities. The density was measured as the number of individuals from 384 permanent quadrats (each 0.5 m × 0.5 m) in the Chihuahuan Desert near Portal, Arizona, USA. We used three probability distributions (binomial, Poisson, and negative binomial or NB) that represent three basic spatial patterns (regular, random, and clumped) to fit the observed frequency distributions of densities of the two annuals. Both species showed clear clumped patterns as characterized by the NB and had similar inverse J-shaped frequency distribution curves in two density categories. Also, both species displayed a reduced degree of aggregation from winter to summer after the spring drought (massive die-off), as indicated by the increased k-parameter of the NB and decreased values of another NB parameter p, variance/mean ratio, Lloyd’s Index of Patchiness, and David and Moore’s Index of Clumping. Further, we hypothesized that while the NB (i.e., Poisson-logarithmic) well fits the distribution of individuals per quadrat, its components, the Poisson and logarithmic, may describe the distributions of clumps per quadrat and of individuals per clump, respectively. We thus obtained the means and variances for (1) individuals per quadrat, (2) clumps per quadrat, and (3) individuals per clump. The results showed that the decrease of the density from winter to summer for each plant resulted from the decrease of individuals per clump, rather than from the decrease of clumps per quadrat. The great similarities between the two annuals indicate that our observed temporal changes in spatial patterns may be common among desert annual plants.

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.

Volcanoes Distribution in Linear Segmentation of Mariana Arc

NASA Astrophysics Data System (ADS)

Andikagumi, H.; Macpherson, C.; McCaffrey, K. J. W.

2016-12-01

A new method has been developed to describe better volcanoes distribution pattern within Mariana Arc. A previous study assumed the distribution of volcanoes in the Mariana Arc is described by a small circle distribution which reflects the melting processes in a curved subduction zone. The small circle fit to this dataset used in the study, comprised 12 -mainly subaerial- volcanoes from Smithsonian Institute Global Volcanism Program, was reassessed by us to have a root-mean-square misfit of 2.5 km. The same method applied to a more complete dataset from Baker et al. (2008), consisting 37 subaerial and submarine volcanoes, resulted in an 8.4 km misfit. However, using the Hough Transform method on the larger dataset, lower misfits of great circle segments were achieved (3.1 and 3.0 km) for two possible segments combination. The results indicate that the distribution of volcanoes in the Mariana Arc is better described by a great circle pattern, instead of small circle. Variogram and cross-variogram analysis on volcano spacing and volume shows that there is spatial correlation between volcanoes between 420 and 500 km which corresponds to the maximum segmentation lengths from Hough Transform (320 km). Further analysis of volcano spacing by the coefficient of variation (Cv), shows a tendency toward not-random distribution as the Cv values are closer to zero than one. These distributions are inferred to be associated with the development of normal faults at the back arc as their Cv values also tend towards zero. To analyse whether volcano spacing is random or not, Cv values were simulated using a Monte Carlo method with random input. Only the southernmost segment has allowed us to reject the null hypothesis that volcanoes are randomly spaced at 95% confidence level by 0.007 estimated probability. This result shows infrequent regularity in volcano spacing by chance so that controlling factor in lithospheric scale should be analysed with different approach (not from random number generator). Sunda Arc which has been studied to have en enchelon segmentation and larger number of volcanoes will be further studied to understand particular upper plate influence in volcanoes distribution.

Prediction of hourly PM2.5 using a space-time support vector regression model

NASA Astrophysics Data System (ADS)

Yang, Wentao; Deng, Min; Xu, Feng; Wang, Hang

2018-05-01

Real-time air quality prediction has been an active field of research in atmospheric environmental science. The existing methods of machine learning are widely used to predict pollutant concentrations because of their enhanced ability to handle complex non-linear relationships. However, because pollutant concentration data, as typical geospatial data, also exhibit spatial heterogeneity and spatial dependence, they may violate the assumptions of independent and identically distributed random variables in most of the machine learning methods. As a result, a space-time support vector regression model is proposed to predict hourly PM2.5 concentrations. First, to address spatial heterogeneity, spatial clustering is executed to divide the study area into several homogeneous or quasi-homogeneous subareas. To handle spatial dependence, a Gauss vector weight function is then developed to determine spatial autocorrelation variables as part of the input features. Finally, a local support vector regression model with spatial autocorrelation variables is established for each subarea. Experimental data on PM2.5 concentrations in Beijing are used to verify whether the results of the proposed model are superior to those of other methods.

Modeling Transport of Cesium in Grimsel Granodiorite With Micrometer Scale Heterogeneities and Dynamic Update of Kd

NASA Astrophysics Data System (ADS)

Voutilainen, Mikko; Kekäläinen, Pekka; Siitari-Kauppi, Marja; Sardini, Paul; Muuri, Eveliina; Timonen, Jussi; Martin, Andrew

2017-11-01

Transport and retardation of cesium in Grimsel granodiorite taking into account heterogeneity of mineral and pore structure was studied using rock samples overcored from an in situ diffusion test at the Grimsel Test Site. The field test was part of the Long-Term Diffusion (LTD) project designed to characterize retardation properties (diffusion and distribution coefficients) under in situ conditions. Results of the LTD experiment for cesium showed that in-diffusion profiles and spatial concentration distributions were strongly influenced by the heterogeneous pore structure and mineral distribution. In order to study the effect of heterogeneity on the in-diffusion profile and spatial concentration distribution, a Time Domain Random Walk (TDRW) method was applied along with a feature for modeling chemical sorption in geological materials. A heterogeneous mineral structure of Grimsel granodiorite was constructed using X-ray microcomputed tomography (X-μCT) and the map was linked to previous results for mineral specific porosities and distribution coefficients (Kd) that were determined using C-14-PMMA autoradiography and batch sorption experiments, respectively. After this the heterogeneous structure contains information on local porosity and Kd in 3-D. It was found that the heterogeneity of the mineral structure on the micrometer scale affects significantly the diffusion and sorption of cesium in Grimsel granodiorite at the centimeter scale. Furthermore, the modeled in-diffusion profiles and spatial concentration distributions show similar shape and pattern to those from the LTD experiment. It was concluded that the use of detailed structure characterization and quantitative data on heterogeneity can significantly improve the interpretation and evaluation of transport experiments.

Spatial Distribution and Sampling Plans for Grapevine Plant Canopy-Inhabiting Scaphoideus titanus (Hemiptera: Cicadellidae) Nymphs.

PubMed

Rigamonti, Ivo E; Brambilla, Carla; Colleoni, Emanuele; Jermini, Mauro; Trivellone, Valeria; Baumgärtner, Johann

2016-04-01

The paper deals with the study of the spatial distribution and the design of sampling plans for estimating nymph densities of the grape leafhopper Scaphoideus titanus Ball in vine plant canopies. In a reference vineyard sampled for model parameterization, leaf samples were repeatedly taken according to a multistage, stratified, random sampling procedure, and data were subjected to an ANOVA. There were no significant differences in density neither among the strata within the vineyard nor between the two strata with basal and apical leaves. The significant differences between densities on trunk and productive shoots led to the adoption of two-stage (leaves and plants) and three-stage (leaves, shoots, and plants) sampling plans for trunk shoots- and productive shoots-inhabiting individuals, respectively. The mean crowding to mean relationship used to analyze the nymphs spatial distribution revealed aggregated distributions. In both the enumerative and the sequential enumerative sampling plans, the number of leaves of trunk shoots, and of leaves and shoots of productive shoots, was kept constant while the number of plants varied. In additional vineyards data were collected and used to test the applicability of the distribution model and the sampling plans. The tests confirmed the applicability 1) of the mean crowding to mean regression model on the plant and leaf stages for representing trunk shoot-inhabiting distributions, and on the plant, shoot, and leaf stages for productive shoot-inhabiting nymphs, 2) of the enumerative sampling plan, and 3) of the sequential enumerative sampling plan. In general, sequential enumerative sampling was more cost efficient than enumerative sampling.

The Effect of Stereoscopic ("3D") vs. 2D Presentation on Learning through Video and Film

NASA Astrophysics Data System (ADS)

Price, Aaron; Kasal, E.

2014-01-01

Two Eyes, 3D is a NSF-funded research project into the effects of stereoscopy on learning of highly spatial concepts. We report final results on one study of the project which tested the effect of stereoscopic presentation on learning outcomes of two short films about Type 1a supernovae and the morphology of the Milky Way. 986 adults watched either film, randomly distributed between stereoscopic and 2D presentation. They took a pre-test and post-test that included multiple choice and drawing tasks related to the spatial nature of the topics in the film. Orientation of the answering device was also tracked and a spatial cognition pre-test was given to control for prior spatial ability. Data collection took place at the Adler Planetarium's Space Visualization Lab and the project is run through the AAVSO.

Experiments with central-limit properties of spatial samples from locally covariant random fields

USGS Publications Warehouse

Barringer, T.H.; Smith, T.E.

1992-01-01

When spatial samples are statistically dependent, the classical estimator of sample-mean standard deviation is well known to be inconsistent. For locally dependent samples, however, consistent estimators of sample-mean standard deviation can be constructed. The present paper investigates the sampling properties of one such estimator, designated as the tau estimator of sample-mean standard deviation. In particular, the asymptotic normality properties of standardized sample means based on tau estimators are studied in terms of computer experiments with simulated sample-mean distributions. The effects of both sample size and dependency levels among samples are examined for various value of tau (denoting the size of the spatial kernel for the estimator). The results suggest that even for small degrees of spatial dependency, the tau estimator exhibits significantly stronger normality properties than does the classical estimator of standardized sample means. ?? 1992.

Geostatistical and GIS analysis of the spatial variability of alluvial gold content in Ngoura-Colomines area, Eastern Cameroon: Implications for the exploration of primary gold deposit

NASA Astrophysics Data System (ADS)

Takodjou Wambo, Jonas Didero; Ganno, Sylvestre; Djonthu Lahe, Yannick Sthopira; Kouankap Nono, Gus Djibril; Fossi, Donald Hermann; Tchouatcha, Milan Stafford; Nzenti, Jean Paul

2018-06-01

Linear and nonlinear geostatistic is commonly used in ore grade estimation and seldom used in Geographical Information System (GIS) technology. In this study, we suggest an approach based on geostatistic linear ordinary kriging (OK) and Geographical Information System (GIS) techniques to investigate the spatial distribution of alluvial gold content, mineralized and gangue layers thicknesses from 73 pits at the Ngoura-Colomines area with the aim to determine controlling factors for the spatial distribution of mineralization and delineate the most prospective area for primary gold mineralization. Gold content varies between 0.1 and 4.6 g/m3 and has been broadly grouped into three statistical classes. These classes have been spatially subdivided into nine zones using ordinary kriging model based on physical and topographical characteristics. Both mineralized and barren layer thicknesses show randomly spatial distribution, and there is no correlation between these parameters and the gold content. This approach has shown that the Ngoura-Colomines area is located in a large shear zone compatible with the Riedel fault system composed of P and P‧ fractures oriented NE-SW and NNE-SSW respectively; E-W trending R fractures and R‧ fractures with NW-SE trends that could have contributed significantly to the establishment of this gold mineralization. The combined OK model and GIS analysis have led to the delineation of Colomines, Tissongo, Madubal and Boutou villages as the most prospective areas for the exploration of primary gold deposit in the study area.

Spatial ecology of refuge selection by an herbivore under risk of predation

USGS Publications Warehouse

Wilson, Tammy L.; Rayburn, Andrew P.; Edwards, Thomas C.

2012-01-01

Prey species use structures such as burrows to minimize predation risk. The spatial arrangement of these resources can have important implications for individual and population fitness. For example, there is evidence that clustered resources can benefit individuals by reducing predation risk and increasing foraging opportunity concurrently, which leads to higher population density. However, the scale of clustering that is important in these processes has been ignored during theoretical and empirical development of resource models. Ecological understanding of refuge exploitation by prey can be improved by spatial analysis of refuge use and availability that incorporates the effect of scale. We measured the spatial distribution of pygmy rabbit (Brachylagus idahoensis) refugia (burrows) through censuses in four 6-ha sites. Point pattern analyses were used to evaluate burrow selection by comparing the spatial distribution of used and available burrows. The presence of food resources and additional overstory cover resources was further examined using logistic regression. Burrows were spatially clustered at scales up to approximately 25 m, and then regularly spaced at distances beyond ~40 m. Pygmy rabbit exploitation of burrows did not match availability. Burrows used by pygmy rabbits were likely to be located in areas with high overall burrow density (resource clusters) and high overstory cover, which together minimized predation risk. However, in some cases we observed an interaction between either overstory cover (safety) or understory cover (forage) and burrow density. The interactions show that pygmy rabbits will use burrows in areas with low relative burrow density (high relative predation risk) if understory food resources are high. This points to a potential trade-off whereby rabbits must sacrifice some safety afforded by additional nearby burrows to obtain ample forage resources. Observed patterns of clustered burrows and non-random burrow use improve understanding of the importance of spatial distribution of refugia for burrowing herbivores. The analyses used allowed for the estimation of the spatial scale where subtle trade-offs between predation avoidance and foraging opportunity are likely to occur in a natural system.

Segregation process and phase transition in cyclic predator-prey models with an even number of species.

PubMed

Szabó, György; Szolnoki, Attila; Sznaider, Gustavo Ariel

2007-11-01

We study a spatial cyclic predator-prey model with an even number of species (for n=4, 6, and 8) that allows the formation of two defensive alliances consisting of the even and odd label species. The species are distributed on the sites of a square lattice. The evolution of spatial distribution is governed by iteration of two elementary processes on neighboring sites chosen randomly: if the sites are occupied by a predator-prey pair then the predator invades the prey's site; otherwise the species exchange their sites with a probability X . For low X values, a self-organizing pattern is maintained by cyclic invasions. If X exceeds a threshold value, then two types of domain grow up that are formed by the odd and even label species, respectively. Monte Carlo simulations indicate the blocking of this segregation process within a range of X for n=8.

Dynamic design of ecological monitoring networks for non-Gaussian spatio-temporal data

USGS Publications Warehouse

Wikle, C.K.; Royle, J. Andrew

2005-01-01

Many ecological processes exhibit spatial structure that changes over time in a coherent, dynamical fashion. This dynamical component is often ignored in the design of spatial monitoring networks. Furthermore, ecological variables related to processes such as habitat are often non-Gaussian (e.g. Poisson or log-normal). We demonstrate that a simulation-based design approach can be used in settings where the data distribution is from a spatio-temporal exponential family. The key random component in the conditional mean function from this distribution is then a spatio-temporal dynamic process. Given the computational burden of estimating the expected utility of various designs in this setting, we utilize an extended Kalman filter approximation to facilitate implementation. The approach is motivated by, and demonstrated on, the problem of selecting sampling locations to estimate July brood counts in the prairie pothole region of the U.S.

Subjective randomness as statistical inference.

PubMed

Griffiths, Thomas L; Daniels, Dylan; Austerweil, Joseph L; Tenenbaum, Joshua B

2018-06-01

Some events seem more random than others. For example, when tossing a coin, a sequence of eight heads in a row does not seem very random. Where do these intuitions about randomness come from? We argue that subjective randomness can be understood as the result of a statistical inference assessing the evidence that an event provides for having been produced by a random generating process. We show how this account provides a link to previous work relating randomness to algorithmic complexity, in which random events are those that cannot be described by short computer programs. Algorithmic complexity is both incomputable and too general to capture the regularities that people can recognize, but viewing randomness as statistical inference provides two paths to addressing these problems: considering regularities generated by simpler computing machines, and restricting the set of probability distributions that characterize regularity. Building on previous work exploring these different routes to a more restricted notion of randomness, we define strong quantitative models of human randomness judgments that apply not just to binary sequences - which have been the focus of much of the previous work on subjective randomness - but also to binary matrices and spatial clustering. Copyright © 2018 Elsevier Inc. All rights reserved.

Shallow plumbing systems inferred from spatial analysis of pockmark arrays

NASA Astrophysics Data System (ADS)

Maia, A.; Cartwright, J. A.; Andersen, E.

2016-12-01

This study describes and analyses an extraordinary array of pockmarks at the modern seabed of the Lower Congo Basin (offshore Angola), in order to understand the fluid migration routes and shallow plumbing system of the area. The 3D seismic visualization of feeding conduits (pipes) allowed the identification of the source interval for the fluids expelled during pockmark formation. Spatial statistics are used to show the relationship between the underlying (polarised) polygonal fault (PPFs) patterns and seabed pockmarks distributions. Our results show PPFs control the linear arrangement of pockmarks and feeder pipes along fault strike, but faults do not act as conduits. Spatial statistics also revealed pockmark occurrence is not considered to be random, especially at short distances to nearest neighbours (<200m) where anti-clustering distributions suggest the presence of an exclusion zone around each pockmark in which no other pockmark will form. The results of this study are relevant for the understanding of shallow fluid plumbing systems in offshore settings, with implications on our current knowledge of overall fluid flow systems in hydrocarbon-rich continental margins.

Using remote sensing and machine learning for the spatial modelling of a bluetongue virus vector

NASA Astrophysics Data System (ADS)

Van doninck, J.; Peters, J.; De Baets, B.; Ducheyne, E.; Verhoest, N. E. C.

2012-04-01

Bluetongue is a viral vector-borne disease transmitted between hosts, mostly cattle and small ruminants, by some species of Culicoides midges. Within the Mediterranean basin, C. imicola is the main vector of the bluetongue virus. The spatial distribution of this species is limited by a number of environmental factors, including temperature, soil properties and land cover. The identification of zones at risk of bluetongue outbreaks thus requires detailed information on these environmental factors, as well as appropriate epidemiological modelling techniques. We here give an overview of the environmental factors assumed to be constraining the spatial distribution of C. imicola, as identified in different studies. Subsequently, remote sensing products that can be used as proxies for these environmental constraints are presented. Remote sensing data are then used together with species occurrence data from the Spanish Bluetongue National Surveillance Programme to calibrate a supervised learning model, based on Random Forests, to model the probability of occurrence of the C. imicola midge. The model will then be applied for a pixel-based prediction over the Iberian peninsula using remote sensing products for habitat characterization.

Using sequential self-calibration method to identify conductivity distribution: Conditioning on tracer test data

USGS Publications Warehouse

Hu, B.X.; He, C.

2008-01-01

An iterative inverse method, the sequential self-calibration method, is developed for mapping spatial distribution of a hydraulic conductivity field by conditioning on nonreactive tracer breakthrough curves. A streamline-based, semi-analytical simulator is adopted to simulate solute transport in a heterogeneous aquifer. The simulation is used as the forward modeling step. In this study, the hydraulic conductivity is assumed to be a deterministic or random variable. Within the framework of the streamline-based simulator, the efficient semi-analytical method is used to calculate sensitivity coefficients of the solute concentration with respect to the hydraulic conductivity variation. The calculated sensitivities account for spatial correlations between the solute concentration and parameters. The performance of the inverse method is assessed by two synthetic tracer tests conducted in an aquifer with a distinct spatial pattern of heterogeneity. The study results indicate that the developed iterative inverse method is able to identify and reproduce the large-scale heterogeneity pattern of the aquifer given appropriate observation wells in these synthetic cases. ?? International Association for Mathematical Geology 2008.

Inelastic collapse and near-wall localization of randomly accelerated particles.

PubMed

Belan, S; Chernykh, A; Lebedev, V; Falkovich, G

2016-05-01

Inelastic collapse of stochastic trajectories of a randomly accelerated particle moving in half-space z>0 has been discovered by McKean [J. Math. Kyoto Univ. 2, 227 (1963)] and then independently rediscovered by Cornell et al. [Phys. Rev. Lett. 81, 1142 (1998)PRLTAO0031-900710.1103/PhysRevLett.81.1142]. The essence of this phenomenon is that the particle arrives at the wall at z=0 with zero velocity after an infinite number of inelastic collisions if the restitution coefficient β of particle velocity is smaller than the critical value β_{c}=exp(-π/sqrt[3]). We demonstrate that inelastic collapse takes place also in a wide class of models with spatially inhomogeneous random forcing and, what is more, that the critical value β_{c} is universal. That class includes an important case of inertial particles in wall-bounded random flows. To establish how inelastic collapse influences the particle distribution, we derive the exact equilibrium probability density function ρ(z,v) for the particle position and velocity. The equilibrium distribution exists only at β<β_{c} and indicates that inelastic collapse does not necessarily imply near-wall localization.

SAS procedures for designing and analyzing sample surveys

USGS Publications Warehouse

Stafford, Joshua D.; Reinecke, Kenneth J.; Kaminski, Richard M.

2003-01-01

Complex surveys often are necessary to estimate occurrence (or distribution), density, and abundance of plants and animals for purposes of re-search and conservation. Most scientists are familiar with simple random sampling, where sample units are selected from a population of interest (sampling frame) with equal probability. However, the goal of ecological surveys often is to make inferences about populations over large or complex spatial areas where organisms are not homogeneously distributed or sampling frames are in-convenient or impossible to construct. Candidate sampling strategies for such complex surveys include stratified,multistage, and adaptive sampling (Thompson 1992, Buckland 1994).

Boundary-layer receptivity due to distributed surface imperfections of a deterministic or random nature

NASA Technical Reports Server (NTRS)

Choudhari, Meelan

1992-01-01

Acoustic receptivity of a Blasius boundary layer in the presence of distributed surface irregularities is investigated analytically. It is shown that, out of the entire spatial spectrum of the surface irregularities, only a small band of Fourier components can lead to an efficient conversion of the acoustic input at any given frequency to an unstable eigenmode of the boundary layer flow. The location, and width, of this most receptive band of wavenumbers corresponds to a relative detuning of O(R sub l.b.(exp -3/8)) with respect to the lower-neutral instability wavenumber at the frequency under consideration, R sub l.b. being the Reynolds number based on a typical boundary-layer thickness at the lower branch of the neutral stability curve. Surface imperfections in the form of discrete mode waviness in this range of wavenumbers lead to initial instability amplitudes which are O(R sub l.b.(exp 3/8)) larger than those caused by a single, isolated roughness element. In contrast, irregularities with a continuous spatial spectrum produce much smaller instability amplitudes, even compared to the isolated case, since the increase due to the resonant nature of the response is more than that compensated for by the asymptotically small band-width of the receptivity process. Analytical expressions for the maximum possible instability amplitudes, as well as their expectation for an ensemble of statistically irregular surfaces with random phase distributions, are also presented.

Analyzing Molecular Clouds with the Spectral Correlation Function

NASA Astrophysics Data System (ADS)

Rosolowsky, E. W.; Goodman, A. A.; Williams, J. P.; Wilner, D. J.

1997-12-01

The Spectral Correlation Function (SCF) is a new data analysis algorithm that measures how the properites of spectra vary from position to position in a spectral-line map. For each spectrum in a data cube, the SCF measures the ``difference" between that spectrum and a specified subset of its neighbors. This algorithm is intended for use on both simulated and observed position-position-velocity data cubes. In initial tests of the SCF, we have shown that a histogram of the SCF for a map is a good descriptor of the spatial-velocity distribution of material. In one test, we compare the SCF distributions for: 1) a real data cube; 2) a cube made from the real cube's spectra with randomized positions; and 3) the results of a preliminary MHD simulation by Gammie, Ostriker, and Stone. The results of the test show that the real cloud and the simulation are much closer to each other in their SCF distributions than is either to the randomized cube. We are now in the process of applying the SCF to a larger set of observed and simulated data cubes. Our ultimate aim is to use the SCF both on its own, as a descriptor of the spatial-kinetic properties of interstellar gas, and also as a tool for evaluating how well simulations resemble observations. Our expectation is that the SCF will be more discriminatory (less likely to produce a false match) than the data cube descriptors currently available.

Spatial-temporal variation in orchid bee communities (Hymenoptera: Apidae) in remnants of arboreal Caatinga in the Chapada Diamantina region, state of Bahia, Brazil.

PubMed

Andrade-Silva, A C R; Nemésio, A; de Oliveira, F F; Nascimento, F S

2012-08-01

The spatial and temporal distribution of organisms is a fundamental aspect of biological communities. The present study focused on three remnants of arboreal Caatinga in northeastern Brazil between May, 2009 and April, 2010. A total of 627 euglossine males were captured in traps baited with artificial aromatic compounds. The specimens belonged to 14 species and four genera: Euglossa Latreille, Eulaema Lepeletier, Eufriesea Cockerell, and Exaerete Hoffmannsegg. Eulaema nigrita Lepeletier (41.6), Euglossa carolina Nemésio (15.3%), Eulaema marcii Nemésio (13.6%), and Euglossa melanotricha Moure (12.8%) were the most common species sampled. The distribution of collected specimens per fragment was as follows: Braúna (280 ha)--259 individuals belonging to 14 species; Cambuí (179 ha)--161 individuals from eight species; and Pindoba (100 ha)--207 individuals represented by seven species. Braúna had the highest diversity (H' = 1.91) and estimated species richness. The largest fragment was the main source of the observed variation in species richness and abundance, indicating a non-random pattern of spatial distribution. The analysis of environmental factors indicated that seasonal variation in these factors was the principal determinant of species occurrence and abundance.

Spatial distribution of psychotic disorders in an urban area of France: an ecological study.

PubMed

Pignon, Baptiste; Schürhoff, Franck; Baudin, Grégoire; Ferchiou, Aziz; Richard, Jean-Romain; Saba, Ghassen; Leboyer, Marion; Kirkbride, James B; Szöke, Andrei

2016-05-18

Previous analyses of neighbourhood variations of non-affective psychotic disorders (NAPD) have focused mainly on incidence. However, prevalence studies provide important insights on factors associated with disease evolution as well as for healthcare resource allocation. This study aimed to investigate the distribution of prevalent NAPD cases in an urban area in France. The number of cases in each neighbourhood was modelled as a function of potential confounders and ecological variables, namely: migrant density, economic deprivation and social fragmentation. This was modelled using statistical models of increasing complexity: frequentist models (using Poisson and negative binomial regressions), and several Bayesian models. For each model, assumptions validity were checked and compared as to how this fitted to the data, in order to test for possible spatial variation in prevalence. Data showed significant overdispersion (invalidating the Poisson regression model) and residual autocorrelation (suggesting the need to use Bayesian models). The best Bayesian model was Leroux's model (i.e. a model with both strong correlation between neighbouring areas and weaker correlation between areas further apart), with economic deprivation as an explanatory variable (OR = 1.13, 95% CI [1.02-1.25]). In comparison with frequentist methods, the Bayesian model showed a better fit. The number of cases showed non-random spatial distribution and was linked to economic deprivation.

The impact of resource quality on the evolution of virulence in spatially heterogeneous environments.

PubMed

Su, Min; Boots, Mike

2017-03-07

Understanding the drivers of parasite evolution and in particular disease virulence remains a major focus of evolutionary theory. Here, we examine the role of resource quality and in particular spatial environmental heterogeneity in the distribution of these resources on the evolution of virulence. There may be direct effects of resources on host susceptibility and pathogenicity alongside effects on reproduction that indirectly impact host-parasite population dynamics. Therefore, we assume that high resource quality may lead to both increased host reproduction and/or increased disease resistance. In completely mixed populations there is no effect of resource quality on the outcome of disease evolution. However, when there are local interactions higher resource quality generally selects for higher virulence/transmission for both linear and saturating transmission-virulence trade-off assumptions. The exception is that in castrators (i.e., infected hosts have no reproduction), higher virulence is selected for both low and high resource qualities at mixed local and global infection. Heterogeneity in the distribution of environment resources only has an effect on the outcome in castrators where random distributions generally select for higher virulence. Overall, our results further underline the importance of considering spatial structure in order to understand evolutionary processes. Copyright © 2016 Elsevier Ltd. All rights reserved.

A Skew-t space-varying regression model for the spectral analysis of resting state brain activity.

PubMed

Ismail, Salimah; Sun, Wenqi; Nathoo, Farouk S; Babul, Arif; Moiseev, Alexader; Beg, Mirza Faisal; Virji-Babul, Naznin

2013-08-01

It is known that in many neurological disorders such as Down syndrome, main brain rhythms shift their frequencies slightly, and characterizing the spatial distribution of these shifts is of interest. This article reports on the development of a Skew-t mixed model for the spatial analysis of resting state brain activity in healthy controls and individuals with Down syndrome. Time series of oscillatory brain activity are recorded using magnetoencephalography, and spectral summaries are examined at multiple sensor locations across the scalp. We focus on the mean frequency of the power spectral density, and use space-varying regression to examine associations with age, gender and Down syndrome across several scalp regions. Spatial smoothing priors are incorporated based on a multivariate Markov random field, and the markedly non-Gaussian nature of the spectral response variable is accommodated by the use of a Skew-t distribution. A range of models representing different assumptions on the association structure and response distribution are examined, and we conduct model selection using the deviance information criterion. (1) Our analysis suggests region-specific differences between healthy controls and individuals with Down syndrome, particularly in the left and right temporal regions, and produces smoothed maps indicating the scalp topography of the estimated differences.

Spatial variability of soil moisture retrieved by SMOS satellite

NASA Astrophysics Data System (ADS)

Lukowski, Mateusz; Marczewski, Wojciech; Usowicz, Boguslaw; Rojek, Edyta; Slominski, Jan; Lipiec, Jerzy

2015-04-01

Standard statistical methods assume that the analysed variables are independent. Since the majority of the processes observed in the nature are continuous in space and time, this assumption introduces a significant limitation for understanding the examined phenomena. In classical approach, valuable information about the locations of examined observations is completely lost. However, there is a branch of statistics, called geostatistics, which is the study of random variables, but taking into account the space where they occur. A common example of so-called "regionalized variable" is soil moisture. Using in situ methods it is difficult to estimate soil moisture distribution because it is often significantly diversified. Thanks to the geostatistical methods, by employing semivariance analysis, it is possible to get the information about the nature of spatial dependences and their lengths. Since the Soil Moisture and Ocean Salinity mission launch in 2009, the estimation of soil moisture spatial distribution for regional up to continental scale started to be much easier. In this study, the SMOS L2 data for Central and Eastern Europe were examined. The statistical and geostatistical features of moisture distributions of this area were studied for selected natural soil phenomena for 2010-2014 including: freezing, thawing, rainfalls (wetting), drying and drought. Those soil water "states" were recognized employing ground data from the agro-meteorological network of ground-based stations SWEX and SMUDP2 data from SMOS. After pixel regularization, without any upscaling, the geostatistical methods were applied directly on Discrete Global Grid (15-km resolution) in ISEA 4H9 projection, on which SMOS observations are reported. Analysis of spatial distribution of SMOS soil moisture, carried out for each data set, in most cases did not show significant trends. It was therefore assumed that each of the examined distributions of soil moisture in the adopted scale satisfies ergodicity and quasi-stationarity assumptions, required for geostatistical analysis. The semivariograms examinations revealed that spatial dependences occurring in the surface soil moisture distributions for the selected area were more or less 200 km. The exception was the driest of the studied days, when the spatial correlations of soil moisture were not disturbed for a long time by any rainfall. Spatial correlation length on that day was about 400 km. Because of zonal character of frost, the spatial dependences in the examined surface soil moisture distributions during freezing/thawing found to be disturbed. Probably, the amount of water remains the same, but it is not detected by SMOS, hence analysing dielectric constant instead of soil moisture would be more appropriate. Some spatial relations of soil moisture and freezing distribution with existing maps of soil granulometric fractions and soil specific surface area for Poland have also been found. The work was partially funded under the ELBARA_PD (Penetration Depth) project No. 4000107897/13/NL/KML. ELBARA_PD project is funded by the Government of Poland through an ESA (European Space Agency) Contract under the PECS (Plan for European Cooperating States).

A tale of two "forests": random forest machine learning AIDS tropical forest carbon mapping.

PubMed

Mascaro, Joseph; Asner, Gregory P; Knapp, David E; Kennedy-Bowdoin, Ty; Martin, Roberta E; Anderson, Christopher; Higgins, Mark; Chadwick, K Dana

2014-01-01

Accurate and spatially-explicit maps of tropical forest carbon stocks are needed to implement carbon offset mechanisms such as REDD+ (Reduced Deforestation and Degradation Plus). The Random Forest machine learning algorithm may aid carbon mapping applications using remotely-sensed data. However, Random Forest has never been compared to traditional and potentially more reliable techniques such as regionally stratified sampling and upscaling, and it has rarely been employed with spatial data. Here, we evaluated the performance of Random Forest in upscaling airborne LiDAR (Light Detection and Ranging)-based carbon estimates compared to the stratification approach over a 16-million hectare focal area of the Western Amazon. We considered two runs of Random Forest, both with and without spatial contextual modeling by including--in the latter case--x, and y position directly in the model. In each case, we set aside 8 million hectares (i.e., half of the focal area) for validation; this rigorous test of Random Forest went above and beyond the internal validation normally compiled by the algorithm (i.e., called "out-of-bag"), which proved insufficient for this spatial application. In this heterogeneous region of Northern Peru, the model with spatial context was the best preforming run of Random Forest, and explained 59% of LiDAR-based carbon estimates within the validation area, compared to 37% for stratification or 43% by Random Forest without spatial context. With the 60% improvement in explained variation, RMSE against validation LiDAR samples improved from 33 to 26 Mg C ha(-1) when using Random Forest with spatial context. Our results suggest that spatial context should be considered when using Random Forest, and that doing so may result in substantially improved carbon stock modeling for purposes of climate change mitigation.

A Tale of Two “Forests”: Random Forest Machine Learning Aids Tropical Forest Carbon Mapping

PubMed Central

Mascaro, Joseph; Asner, Gregory P.; Knapp, David E.; Kennedy-Bowdoin, Ty; Martin, Roberta E.; Anderson, Christopher; Higgins, Mark; Chadwick, K. Dana

2014-01-01

Accurate and spatially-explicit maps of tropical forest carbon stocks are needed to implement carbon offset mechanisms such as REDD+ (Reduced Deforestation and Degradation Plus). The Random Forest machine learning algorithm may aid carbon mapping applications using remotely-sensed data. However, Random Forest has never been compared to traditional and potentially more reliable techniques such as regionally stratified sampling and upscaling, and it has rarely been employed with spatial data. Here, we evaluated the performance of Random Forest in upscaling airborne LiDAR (Light Detection and Ranging)-based carbon estimates compared to the stratification approach over a 16-million hectare focal area of the Western Amazon. We considered two runs of Random Forest, both with and without spatial contextual modeling by including—in the latter case—x, and y position directly in the model. In each case, we set aside 8 million hectares (i.e., half of the focal area) for validation; this rigorous test of Random Forest went above and beyond the internal validation normally compiled by the algorithm (i.e., called “out-of-bag”), which proved insufficient for this spatial application. In this heterogeneous region of Northern Peru, the model with spatial context was the best preforming run of Random Forest, and explained 59% of LiDAR-based carbon estimates within the validation area, compared to 37% for stratification or 43% by Random Forest without spatial context. With the 60% improvement in explained variation, RMSE against validation LiDAR samples improved from 33 to 26 Mg C ha−1 when using Random Forest with spatial context. Our results suggest that spatial context should be considered when using Random Forest, and that doing so may result in substantially improved carbon stock modeling for purposes of climate change mitigation. PMID:24489686

Spatiotemporal hurdle models for zero-inflated count data: Exploring trends in emergency department visits.

PubMed

Neelon, Brian; Chang, Howard H; Ling, Qiang; Hastings, Nicole S

2016-12-01

Motivated by a study exploring spatiotemporal trends in emergency department use, we develop a class of two-part hurdle models for the analysis of zero-inflated areal count data. The models consist of two components-one for the probability of any emergency department use and one for the number of emergency department visits given use. Through a hierarchical structure, the models incorporate both patient- and region-level predictors, as well as spatially and temporally correlated random effects for each model component. The random effects are assigned multivariate conditionally autoregressive priors, which induce dependence between the components and provide spatial and temporal smoothing across adjacent spatial units and time periods, resulting in improved inferences. To accommodate potential overdispersion, we consider a range of parametric specifications for the positive counts, including truncated negative binomial and generalized Poisson distributions. We adopt a Bayesian inferential approach, and posterior computation is handled conveniently within standard Bayesian software. Our results indicate that the negative binomial and generalized Poisson hurdle models vastly outperform the Poisson hurdle model, demonstrating that overdispersed hurdle models provide a useful approach to analyzing zero-inflated spatiotemporal data. © The Author(s) 2014.

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

PubMed

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

2014-01-01

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

A probabilistic model of a porous heat exchanger

NASA Technical Reports Server (NTRS)

Agrawal, O. P.; Lin, X. A.

1995-01-01

This paper presents a probabilistic one-dimensional finite element model for heat transfer processes in porous heat exchangers. The Galerkin approach is used to develop the finite element matrices. Some of the submatrices are asymmetric due to the presence of the flow term. The Neumann expansion is used to write the temperature distribution as a series of random variables, and the expectation operator is applied to obtain the mean and deviation statistics. To demonstrate the feasibility of the formulation, a one-dimensional model of heat transfer phenomenon in superfluid flow through a porous media is considered. Results of this formulation agree well with the Monte-Carlo simulations and the analytical solutions. Although the numerical experiments are confined to parametric random variables, a formulation is presented to account for the random spatial variations.

Collision Models for Particle Orbit Code on SSX

NASA Astrophysics Data System (ADS)

Fisher, M. W.; Dandurand, D.; Gray, T.; Brown, M. R.; Lukin, V. S.

2011-10-01

Coulomb collision models are being developed and incorporated into the Hamiltonian particle pushing code (PPC) for applications to the Swarthmore Spheromak eXperiment (SSX). A Monte Carlo model based on that of Takizuka and Abe [JCP 25, 205 (1977)] performs binary collisions between test particles and thermal plasma field particles randomly drawn from a stationary Maxwellian distribution. A field-based electrostatic fluctuation model scatters particles from a spatially uniform random distribution of positive and negative spherical potentials generated throughout the plasma volume. The number, radii, and amplitude of these potentials are chosen to mimic the correct particle diffusion statistics without the use of random particle draws or collision frequencies. An electromagnetic fluctuating field model will be presented, if available. These numerical collision models will be benchmarked against known analytical solutions, including beam diffusion rates and Spitzer resistivity, as well as each other. The resulting collisional particle orbit models will be used to simulate particle collection with electrostatic probes in the SSX wind tunnel, as well as particle confinement in typical SSX fields. This work has been supported by US DOE, NSF and ONR.

A geometric exploration of stress in deformed liquid foams

NASA Astrophysics Data System (ADS)

Evans, Myfanwy E.; Schröder-Turk, Gerd E.; Kraynik, Andrew M.

2017-03-01

We explore an alternate way of looking at the rheological response of a yield stress fluid: using discrete geometry to probe the heterogeneous distribution of stress in soap froth. We present quasi-static, uniaxial, isochoric compression and extension of three-dimensional random monodisperse soap froth in periodic boundary conditions and examine the stress and geometry that result. The stress and shape anisotropy of individual cells is quantified by Q, a scalar measure derived from the interface tensor that gauges each cell’s contribution to the global stress. Cumulatively, the spatial distribution of highly deformed cells allows us to examine how stress is internally distributed. The topology of highly deformed cells, how they arrange relative to one another in space, gives insight into the heterogeneous distribution of stress.

Spatial distribution and cluster analysis of retail drug shop characteristics and antimalarial behaviors as reported by private medicine retailers in western Kenya: informing future interventions.

PubMed

Rusk, Andria; Highfield, Linda; Wilkerson, J Michael; Harrell, Melissa; Obala, Andrew; Amick, Benjamin

2016-02-19

Efforts to improve malaria case management in sub-Saharan Africa have shifted focus to private antimalarial retailers to increase access to appropriate treatment. Demands to decrease intervention cost while increasing efficacy requires interventions tailored to geographic regions with demonstrated need. Cluster analysis presents an opportunity to meet this demand, but has not been applied to the retail sector or antimalarial retailer behaviors. This research conducted cluster analysis on medicine retailer behaviors in Kenya, to improve malaria case management and inform future interventions. Ninety-seven surveys were collected from medicine retailers working in the Webuye Health and Demographic Surveillance Site. Survey items included retailer training, education, antimalarial drug knowledge, recommending behavior, sales, and shop characteristics, and were analyzed using Kulldorff's spatial scan statistic. The Bernoulli purely spatial model for binomial data was used, comparing cases to controls. Statistical significance of found clusters was tested with a likelihood ratio test, using the null hypothesis of no clustering, and a p value based on 999 Monte Carlo simulations. The null hypothesis was rejected with p values of 0.05 or less. A statistically significant cluster of fewer than expected pharmacy-trained retailers was found (RR = .09, p = .001) when compared to the expected random distribution. Drug recommending behavior also yielded a statistically significant cluster, with fewer than expected retailers recommending the correct antimalarial medication to adults (RR = .018, p = .01), and fewer than expected shops selling that medication more often than outdated antimalarials when compared to random distribution (RR = 0.23, p = .007). All three of these clusters were co-located, overlapping in the northwest of the study area. Spatial clustering was found in the data. A concerning amount of correlation was found in one specific region in the study area where multiple behaviors converged in space, highlighting a prime target for interventions. These results also demonstrate the utility of applying geospatial methods in the study of medicine retailer behaviors, making the case for expanding this approach to other regions.

A spatially resolved network spike in model neuronal cultures reveals nucleation centers, circular traveling waves and drifting spiral waves.

PubMed

Paraskevov, A V; Zendrikov, D K

2017-03-23

We show that in model neuronal cultures, where the probability of interneuronal connection formation decreases exponentially with increasing distance between the neurons, there exists a small number of spatial nucleation centers of a network spike, from where the synchronous spiking activity starts propagating in the network typically in the form of circular traveling waves. The number of nucleation centers and their spatial locations are unique and unchanged for a given realization of neuronal network but are different for different networks. In contrast, if the probability of interneuronal connection formation is independent of the distance between neurons, then the nucleation centers do not arise and the synchronization of spiking activity during a network spike occurs spatially uniform throughout the network. Therefore one can conclude that spatial proximity of connections between neurons is important for the formation of nucleation centers. It is also shown that fluctuations of the spatial density of neurons at their random homogeneous distribution typical for the experiments in vitro do not determine the locations of the nucleation centers. The simulation results are qualitatively consistent with the experimental observations.

A spatially resolved network spike in model neuronal cultures reveals nucleation centers, circular traveling waves and drifting spiral waves

NASA Astrophysics Data System (ADS)

Paraskevov, A. V.; Zendrikov, D. K.

2017-04-01

We show that in model neuronal cultures, where the probability of interneuronal connection formation decreases exponentially with increasing distance between the neurons, there exists a small number of spatial nucleation centers of a network spike, from where the synchronous spiking activity starts propagating in the network typically in the form of circular traveling waves. The number of nucleation centers and their spatial locations are unique and unchanged for a given realization of neuronal network but are different for different networks. In contrast, if the probability of interneuronal connection formation is independent of the distance between neurons, then the nucleation centers do not arise and the synchronization of spiking activity during a network spike occurs spatially uniform throughout the network. Therefore one can conclude that spatial proximity of connections between neurons is important for the formation of nucleation centers. It is also shown that fluctuations of the spatial density of neurons at their random homogeneous distribution typical for the experiments in vitro do not determine the locations of the nucleation centers. The simulation results are qualitatively consistent with the experimental observations.

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.

Image-Based Modeling Reveals Dynamic Redistribution of DNA Damage into Nuclear Sub-Domains

PubMed Central

Costes, Sylvain V; Ponomarev, Artem; Chen, James L; Nguyen, David; Cucinotta, Francis A; Barcellos-Hoff, Mary Helen

2007-01-01

Several proteins involved in the response to DNA double strand breaks (DSB) form microscopically visible nuclear domains, or foci, after exposure to ionizing radiation. Radiation-induced foci (RIF) are believed to be located where DNA damage occurs. To test this assumption, we analyzed the spatial distribution of 53BP1, phosphorylated ATM, and γH2AX RIF in cells irradiated with high linear energy transfer (LET) radiation and low LET. Since energy is randomly deposited along high-LET particle paths, RIF along these paths should also be randomly distributed. The probability to induce DSB can be derived from DNA fragment data measured experimentally by pulsed-field gel electrophoresis. We used this probability in Monte Carlo simulations to predict DSB locations in synthetic nuclei geometrically described by a complete set of human chromosomes, taking into account microscope optics from real experiments. As expected, simulations produced DNA-weighted random (Poisson) distributions. In contrast, the distributions of RIF obtained as early as 5 min after exposure to high LET (1 GeV/amu Fe) were non-random. This deviation from the expected DNA-weighted random pattern can be further characterized by “relative DNA image measurements.” This novel imaging approach shows that RIF were located preferentially at the interface between high and low DNA density regions, and were more frequent than predicted in regions with lower DNA density. The same preferential nuclear location was also measured for RIF induced by 1 Gy of low-LET radiation. This deviation from random behavior was evident only 5 min after irradiation for phosphorylated ATM RIF, while γH2AX and 53BP1 RIF showed pronounced deviations up to 30 min after exposure. These data suggest that DNA damage–induced foci are restricted to certain regions of the nucleus of human epithelial cells. It is possible that DNA lesions are collected in these nuclear sub-domains for more efficient repair. PMID:17676951

Spatial heterogeneity study of vegetation coverage at Heihe River Basin

NASA Astrophysics Data System (ADS)

Wu, Lijuan; Zhong, Bo; Guo, Liyu; Zhao, Xiangwei

2014-11-01

Spatial heterogeneity of the animal-landscape system has three major components: heterogeneity of resource distributions in the physical environment, heterogeneity of plant tissue chemistry, heterogeneity of movement modes by the animal. Furthermore, all three different types of heterogeneity interact each other and can either reinforce or offset one another, thereby affecting system stability and dynamics. In previous studies, the study areas are investigated by field sampling, which costs a large amount of manpower. In addition, uncertain in sampling affects the quality of field data, which leads to unsatisfactory results during the entire study. In this study, remote sensing data is used to guide the sampling for research on heterogeneity of vegetation coverage to avoid errors caused by randomness of field sampling. Semi-variance and fractal dimension analysis are used to analyze the spatial heterogeneity of vegetation coverage at Heihe River Basin. The spherical model with nugget is used to fit the semivariogram of vegetation coverage. Based on the experiment above, it is found, (1)there is a strong correlation between vegetation coverage and distance of vegetation populations within the range of 0-28051.3188m at Heihe River Basin, but the correlation loses suddenly when the distance greater than 28051.3188m. (2)The degree of spatial heterogeneity of vegetation coverage at Heihe River Basin is medium. (3)Spatial distribution variability of vegetation occurs mainly on small scales. (4)The degree of spatial autocorrelation is 72.29% between 25% and 75%, which means that spatial correlation of vegetation coverage at Heihe River Basin is medium high.

Evaluation of high-resolution sea ice models on the basis of statistical and scaling properties of Arctic sea ice drift and deformation

NASA Astrophysics Data System (ADS)

Girard, L.; Weiss, J.; Molines, J. M.; Barnier, B.; Bouillon, S.

2009-08-01

Sea ice drift and deformation from models are evaluated on the basis of statistical and scaling properties. These properties are derived from two observation data sets: the RADARSAT Geophysical Processor System (RGPS) and buoy trajectories from the International Arctic Buoy Program (IABP). Two simulations obtained with the Louvain-la-Neuve Ice Model (LIM) coupled to a high-resolution ocean model and a simulation obtained with the Los Alamos Sea Ice Model (CICE) were analyzed. Model ice drift compares well with observations in terms of large-scale velocity field and distributions of velocity fluctuations although a significant bias on the mean ice speed is noted. On the other hand, the statistical properties of ice deformation are not well simulated by the models: (1) The distributions of strain rates are incorrect: RGPS distributions of strain rates are power law tailed, i.e., exhibit "wild randomness," whereas models distributions remain in the Gaussian attraction basin, i.e., exhibit "mild randomness." (2) The models are unable to reproduce the spatial and temporal correlations of the deformation fields: In the observations, ice deformation follows spatial and temporal scaling laws that express the heterogeneity and the intermittency of deformation. These relations do not appear in simulated ice deformation. Mean deformation in models is almost scale independent. The statistical properties of ice deformation are a signature of the ice mechanical behavior. The present work therefore suggests that the mechanical framework currently used by models is inappropriate. A different modeling framework based on elastic interactions could improve the representation of the statistical and scaling properties of ice deformation.

Spatial embedding of structural similarity in the cerebral cortex

PubMed Central

Song, H. Francis; Kennedy, Henry; Wang, Xiao-Jing

2014-01-01

Recent anatomical tracing studies have yielded substantial amounts of data on the areal connectivity underlying distributed processing in cortex, yet the fundamental principles that govern the large-scale organization of cortex remain unknown. Here we show that functional similarity between areas as defined by the pattern of shared inputs or outputs is a key to understanding the areal network of cortex. In particular, we report a systematic relation in the monkey, human, and mouse cortex between the occurrence of connections from one area to another and their similarity distance. This characteristic relation is rooted in the wiring distance dependence of connections in the brain. We introduce a weighted, spatially embedded random network model that robustly gives rise to this structure, as well as many other spatial and topological properties observed in cortex. These include features that were not accounted for in any previous model, such as the wide range of interareal connection weights. Connections in the model emerge from an underlying distribution of spatially embedded axons, thereby integrating the two scales of cortical connectivity—individual axons and interareal pathways—into a common geometric framework. These results provide insights into the origin of large-scale connectivity in cortex and have important implications for theories of cortical organization. PMID:25368200

A Random Forest Approach to Predict the Spatial Distribution ...

EPA Pesticide Factsheets

Modeling the magnitude and distribution of sediment-bound pollutants in estuaries is often limited by incomplete knowledge of the site and inadequate sample density. To address these modeling limitations, a decision-support tool framework was conceived that predicts sediment contamination from the sub-estuary to broader estuary extent. For this study, a Random Forest (RF) model was implemented to predict the distribution of a model contaminant, triclosan (5-chloro-2-(2,4-dichlorophenoxy)phenol) (TCS), in Narragansett Bay, Rhode Island, USA. TCS is an unregulated contaminant used in many personal care products. The RF explanatory variables were associated with TCS transport and fate (proxies) and direct and indirect environmental entry. The continuous RF TCS concentration predictions were discretized into three levels of contamination (low, medium, and high) for three different quantile thresholds. The RF model explained 63% of the variance with a minimum number of variables. Total organic carbon (TOC) (transport and fate proxy) was a strong predictor of TCS contamination causing a mean squared error increase of 59% when compared to permutations of randomized values of TOC. Additionally, combined sewer overflow discharge (environmental entry) and sand (transport and fate proxy) were strong predictors. The discretization models identified a TCS area of greatest concern in the northern reach of Narragansett Bay (Providence River sub-estuary), which was validated wi

The Role of Landscape in the Distribution of Deer-Vehicle Collisions in South Mississippi

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

McKee, Jacob J; Cochran, David

2012-01-01

Deer-vehicle collisions (DVCs) have a negative impact on the economy, traffic safety, and the general well-being of otherwise healthy deer. To mitigate DVCs, it is imperative to gain a better understanding of factors that play a role in their spatial distribution. Much of the existing research on DVCs in the United States has been inconclusive, pointing to a variety of causal factors that seem more specific to study site and region than indicative of broad patterns. Little DVC research has been conducted in the southern United States, making the region particularly important with regard to this issue. In this study,more » we evaluate landscape factors that contributed to the distribution of 347 DVCs that occurred in Forrest and Lamar Counties of south Mississippi, from 2006 to 2009. Using nearest-neighbor and discriminant analysis, we demonstrate that DVCs in south Mississippi are not random spatial phenomena. We also develop a classification model that identified seven landscape metrics, explained 100% of the variance, and could distinguish DVCs from control sites with an accuracy of 81.3 percent.« less

Complex Network Simulation of Forest Network Spatial Pattern in Pearl River Delta

NASA Astrophysics Data System (ADS)

Zeng, Y.

2017-09-01

Forest network-construction uses for the method and model with the scale-free features of complex network theory based on random graph theory and dynamic network nodes which show a power-law distribution phenomenon. The model is suitable for ecological disturbance by larger ecological landscape Pearl River Delta consistent recovery. Remote sensing and GIS spatial data are available through the latest forest patches. A standard scale-free network node distribution model calculates the area of forest network's power-law distribution parameter value size; The recent existing forest polygons which are defined as nodes can compute the network nodes decaying index value of the network's degree distribution. The parameters of forest network are picked up then make a spatial transition to GIS real world models. Hence the connection is automatically generated by minimizing the ecological corridor by the least cost rule between the near nodes. Based on scale-free network node distribution requirements, select the number compared with less, a huge point of aggregation as a future forest planning network's main node, and put them with the existing node sequence comparison. By this theory, the forest ecological projects in the past avoid being fragmented, scattered disorderly phenomena. The previous regular forest networks can be reduced the required forest planting costs by this method. For ecological restoration of tropical and subtropical in south China areas, it will provide an effective method for the forest entering city project guidance and demonstration with other ecological networks (water, climate network, etc.) for networking a standard and base datum.

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

NASA Astrophysics Data System (ADS)

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

2018-03-01

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

Statistical analysis of dendritic spine distributions in rat hippocampal cultures

PubMed Central

2013-01-01

Background Dendritic spines serve as key computational structures in brain plasticity. Much remains to be learned about their spatial and temporal distribution among neurons. Our aim in this study was to perform exploratory analyses based on the population distributions of dendritic spines with regard to their morphological characteristics and period of growth in dissociated hippocampal neurons. We fit a log-linear model to the contingency table of spine features such as spine type and distance from the soma to first determine which features were important in modeling the spines, as well as the relationships between such features. A multinomial logistic regression was then used to predict the spine types using the features suggested by the log-linear model, along with neighboring spine information. Finally, an important variant of Ripley’s K-function applicable to linear networks was used to study the spatial distribution of spines along dendrites. Results Our study indicated that in the culture system, (i) dendritic spine densities were "completely spatially random", (ii) spine type and distance from the soma were independent quantities, and most importantly, (iii) spines had a tendency to cluster with other spines of the same type. Conclusions Although these results may vary with other systems, our primary contribution is the set of statistical tools for morphological modeling of spines which can be used to assess neuronal cultures following gene manipulation such as RNAi, and to study induced pluripotent stem cells differentiated to neurons. PMID:24088199

The Spatial Distribution of the Young Stellar Clusters in the Star-forming Galaxy NGC 628

NASA Astrophysics Data System (ADS)

Grasha, K.; Calzetti, D.; Adamo, A.; Kim, H.; Elmegreen, B. G.; Gouliermis, D. A.; Aloisi, A.; Bright, S. N.; Christian, C.; Cignoni, M.; Dale, D. A.; Dobbs, C.; Elmegreen, D. M.; Fumagalli, M.; Gallagher, J. S., III; Grebel, E. K.; Johnson, K. E.; Lee, J. C.; Messa, M.; Smith, L. J.; Ryon, J. E.; Thilker, D.; Ubeda, L.; Wofford, A.

2015-12-01

We present a study of the spatial distribution of the stellar cluster populations in the star-forming galaxy NGC 628. Using Hubble Space Telescope broadband WFC3/UVIS UV and optical images from the Treasury Program LEGUS (Legacy ExtraGalactic UV Survey), we have identified 1392 potential young (≲ 100 Myr) stellar clusters within the galaxy using a combination of visual inspection and automatic selection. We investigate the clustering of these young stellar clusters and quantify the strength and change of clustering strength with scale using the two-point correlation function. We also investigate how image boundary conditions and dust lanes affect the observed clustering. The distribution of the clusters is well fit by a broken power law with negative exponent α. We recover a weighted mean index of α ∼ -0.8 for all spatial scales below the break at 3.″3 (158 pc at a distance of 9.9 Mpc) and an index of α ∼ -0.18 above 158 pc for the accumulation of all cluster types. The strength of the clustering increases with decreasing age and clusters older than 40 Myr lose their clustered structure very rapidly and tend to be randomly distributed in this galaxy, whereas the mass of the star cluster has little effect on the clustering strength. This is consistent with results from other studies that the morphological hierarchy in stellar clustering resembles the same hierarchy as the turbulent interstellar medium.

Hierarchical Bayesian spatial models for alcohol availability, drug "hot spots" and violent crime.

PubMed

Zhu, Li; Gorman, Dennis M; Horel, Scott

2006-12-07

Ecologic studies have shown a relationship between alcohol outlet densities, illicit drug use and violence. The present study examined this relationship in the City of Houston, Texas, using a sample of 439 census tracts. Neighborhood sociostructural covariates, alcohol outlet density, drug crime density and violent crime data were collected for the year 2000, and analyzed using hierarchical Bayesian models. Model selection was accomplished by applying the Deviance Information Criterion. The counts of violent crime in each census tract were modelled as having a conditional Poisson distribution. Four neighbourhood explanatory variables were identified using principal component analysis. The best fitted model was selected as the one considering both unstructured and spatial dependence random effects. The results showed that drug-law violation explained a greater amount of variance in violent crime rates than alcohol outlet densities. The relative risk for drug-law violation was 2.49 and that for alcohol outlet density was 1.16. Of the neighbourhood sociostructural covariates, males of age 15 to 24 showed an effect on violence, with a 16% decrease in relative risk for each increase the size of its standard deviation. Both unstructured heterogeneity random effect and spatial dependence need to be included in the model. The analysis presented suggests that activity around illicit drug markets is more strongly associated with violent crime than is alcohol outlet density. Unique among the ecological studies in this field, the present study not only shows the direction and magnitude of impact of neighbourhood sociostructural covariates as well as alcohol and illicit drug activities in a neighbourhood, it also reveals the importance of applying hierarchical Bayesian models in this research field as both spatial dependence and heterogeneity random effects need to be considered simultaneously.

The Ciliate Paramecium Shows Higher Motility in Non-Uniform Chemical Landscapes

PubMed Central

Giuffre, Carl; Hinow, Peter; Vogel, Ryan; Ahmed, Tanvir; Stocker, Roman; Consi, Thomas R.; Strickler, J. Rudi

2011-01-01

We study the motility behavior of the unicellular protozoan Paramecium tetraurelia in a microfluidic device that can be prepared with a landscape of attracting or repelling chemicals. We investigate the spatial distribution of the positions of the individuals at different time points with methods from spatial statistics and Poisson random point fields. This makes quantitative the informal notion of “uniform distribution” (or lack thereof). Our device is characterized by the absence of large systematic biases due to gravitation and fluid flow. It has the potential to be applied to the study of other aquatic chemosensitive organisms as well. This may result in better diagnostic devices for environmental pollutants. PMID:21494596

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

Characterization and Upscaling of Pore Scale Hydrodynamic Mass Transfer

NASA Astrophysics Data System (ADS)

Gouze, P.; Roubinet, D.; Dentz, M.; Planes, V.; Russian, A.

2017-12-01

Imaging reservoir rocks in 3D using X-ray microtomography with spatial resolution ranging from about 1 to 10 mm provides us a unique opportunity not only to characterize pore space geometry but also for simulating hydrodynamical processes. Yet, pores and throats displaying sizes smaller than the resolution cannot be distinguished on the images and must be assigned to a so called microporous phase during the process of image segmentation. Accordingly one simulated mass transfers caused by advection and diffusion in the connected pores (mobile domain) and diffusion in the microporous clusters (immobile domain) using Time Domain Random Walk (TDRW) and developed a set of metrics that can be used to monitor the different mechanisms of transport in the sample, the final objective being of proposing a simple but accurate upscaled 1D model in which the particle travel times in the mobile and immobile domain and the number of mobile-immobile transfer events (called trapping events) are independently distributed random variables characterized by PDFs. For TDRW the solute concentration is represented by the density distribution of non-interacting point-like solute particles which move due to advection and dispersion. The set of metrics derives from different spatial and temporal statistical analyses of the particle motion, and is used for characterizing the particles transport (i) in the mobile domain in relation with the velocity field properties, (ii) in the immobile domain in relation with the structure and the properties of microporous phase and at the mobile-immobile interface. We specifically focused on how to model the trapping frequency and rate into the immobile domain in relation with the structure and the spatial distribution of the mobile-immobile domain interface. This thorough analysis of the particle motion for both simple artificial structures and real rock images allowed us to derive the parametrization of the upscaled 1D model.

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

Hudson, W.G.

Scapteriscus vicinus is the most important pest of turf and pasture grasses in Florida. This study develops a method of correlating sample results with true population density and provides the first quantitative information on spatial distribution and movement patterns of mole crickets. Three basic techniques for sampling mole crickets were compared: soil flushes, soil corer, and pitfall trapping. No statistical difference was found between the soil corer and soil flushing. Soil flushing was shown to be more sensitive to changes in population density than pitfall trapping. No technique was effective for sampling adults. Regression analysis provided a means of adjustingmore » for the effects of soil moisture and showed soil temperature to be unimportant in predicting efficiency of flush sampling. Cesium-137 was used to label females for subsequent location underground. Comparison of mean distance to nearest neighbor with the distance predicted by a random distribution model showed that the observed distance in the spring was significantly greater than hypothesized (Student's T-test, p < 0.05). Fall adult nearest neighbor distance was not different than predicted by the random distribution hypothesis.« less

Understanding spatial connectivity of individuals with non-uniform population density.

PubMed

Wang, Pu; González, Marta C

2009-08-28

We construct a two-dimensional geometric graph connecting individuals placed in space within a given contact distance. The individuals are distributed using a measured country's density of population. We observe that while large clusters (group of individuals connected) emerge within some regions, they are trapped in detached urban areas owing to the low population density of the regions bordering them. To understand the emergence of a giant cluster that connects the entire population, we compare the empirical geometric graph with the one generated by placing the same number of individuals randomly in space. We find that, for small contact distances, the empirical distribution of population dominates the growth of connected components, but no critical percolation transition is observed in contrast to the graph generated by a random distribution of population. Our results show that contact distances from real-world situations as for WIFI and Bluetooth connections drop in a zone where a fully connected cluster is not observed, hinting that human mobility must play a crucial role in contact-based diseases and wireless viruses' large-scale spreading.

Fish depth distributions in the Lower Mississippi River

USGS Publications Warehouse

Killgore, K. J.; Miranda, Leandro E.

2014-01-01

A substantial body of literature exists about depth distribution of fish in oceans, lakes and reservoirs, but less is known about fish depth distribution in large rivers. Most of the emphasis on fish distributions in rivers has focused on longitudinal and latitudinal spatial distributions. Knowledge on depth distribution is necessary to understand species and community habitat needs. Considering this void, our goal was to identify patterns in fish benthic distribution along depth gradients in the Lower Mississippi River. Fish were collected over 14 years in depths down to 27 m. Fish exhibited non-random depth distributions that varied seasonally and according to species. Species richness was highest in shallow water, with about 50% of the 62 species detected no longer collected in water deeper than 8 m and about 75% no longer collected in water deeper than 12 m. Although richness was highest in shallow water, most species were not restricted to shallow water. Rather, most species used a wide range of depths. A weak depth zonation occurred, not as strong as that reported for deep oceans and lakes. Larger fish tended to occur in deeper water during the high-water period of an annual cycle, but no correlation was evident during the low-water period. The advent of landscape ecology has guided river research to search for spatial patterns along the length of the river and associated floodplains. Our results suggest that fish assemblages in large rivers are also structured vertically. 

Calculation of Dose Deposition in 3D Voxels by Heavy Ions and Simulation of gamma-H2AX Experiments

NASA Technical Reports Server (NTRS)

Plante, I.; Ponomarev, A. L.; Wang, M.; Cucinotta, F. A.

2011-01-01

The biological response to high-LET radiation is different from low-LET radiation due to several factors, notably difference in energy deposition and formation of radiolytic species. Of particular importance in radiobiology is the formation of double-strand breaks (DSB), which can be detected by -H2AX foci experiments. These experiments has revealed important differences in the spatial distribution of DSB induced by low- and high-LET radiations [1,2]. To simulate -H2AX experiments, models based on amorphous track with radial dose are often combined with random walk chromosome models [3,4]. In this work, a new approach using the Monte-Carlo track structure code RITRACKS [5] and chromosome models have been used to simulate DSB formation. At first, RITRACKS have been used to simulate the irradiation of a cubic volume of 5 m by 1) 450 1H+ ions of 300 MeV (LET 0.3 keV/ m) and 2) by 1 56Fe26+ ion of 1 GeV/amu (LET 150 keV/ m). All energy deposition events are recorded to calculate dose in voxels of 20 m. The dose voxels are distributed randomly and scattered uniformly within the volume irradiated by low-LET radiation. Many differences are found in the spatial distribution of dose voxels for the 56Fe26+ ion. The track structure can be distinguished, and voxels with very high dose are found in the region corresponding to the track "core". These high-dose voxels are not found in the low-LET irradiation simulation and indicate clustered energy deposition, which may be responsible for complex DSB. In the second step, assuming that DSB will be found only in voxels where energy is deposited by the radiation, the intersection points between voxels with dose > 0 and simulated chromosomes were obtained. The spatial distribution of the intersection points is similar to -H2AX foci experiments. These preliminary results suggest that combining stochastic track structure and chromosome models could be a good approach to understand radiation-induced DSB and chromosome aberrations.

"Anticlumping" and Other Combinatorial Effects on Clumped Isotopes: Implications for Tracing Biogeochemical Cycling

NASA Astrophysics Data System (ADS)

Yeung, L.

2015-12-01

I present a mode of isotopic ordering that has purely combinatorial origins. It can be important when identical rare isotopes are paired by coincidence (e.g., they are neighbors on the same molecule), or when extrinsic factors govern the isotopic composition of the two atoms that share a chemical bond. By itself, combinatorial isotope pairing yields products with isotopes either randomly distributed or with a deficit relative to a random distribution of isotopes. These systematics arise because of an unconventional coupling between the formation of singly- and multiply-substituted isotopic moieties. In a random distribution, rare isotopes are symmetrically distributed: Single isotopic substitutions (e.g., H‒D and D‒H in H2) occur with equal probability, and double isotopic substitutions (e.g., D2) occur according to random chance. The absence of symmetry in a bond-making complex can yield unequal numbers of singly-substituted molecules (e.g., more H‒D than D‒H in H2), which is recorded in the product molecule as a deficit in doubly-substituted moieties and an "anticlumped" isotope distribution (i.e., Δn < 0). Enzymatic isotope pairing reactions, which can have site-specific isotopic fractionation factors and atom reservoirs, should express this class of combinatorial isotope effect. Chemical-kinetic isotope effects, which are related to the bond-forming transition state, arise independently and express second-order combinatorial effects. In general, both combinatorial and chemical factors are important for calculating and interpreting clumped-isotope signatures of individual reactions. In many reactions relevant to geochemical oxygen, carbon, and nitrogen cycling, combinatorial isotope pairing likely plays a strong role in the clumped isotope distribution of the products. These isotopic signatures, manifest as either directly bound isotope clumps or as features of a molecule's isotopic anatomy, could be exploited as tracers of biogeochemistry that can relate molecular mechanisms to signals observable at environmentally relevant spatial scales.

Spatial effects in meta-foodwebs.

PubMed

Barter, Edmund; Gross, Thilo

2017-08-30

In ecology it is widely recognised that many landscapes comprise a network of discrete patches of habitat. The species that inhabit the patches interact with each other through a foodweb, the network of feeding interactions. The meta-foodweb model proposed by Pillai et al. combines the feeding relationships at each patch with the dispersal of species between patches, such that the whole system is represented by a network of networks. Previous work on meta-foodwebs has focussed on landscape networks that do not have an explicit spatial embedding, but in real landscapes the patches are usually distributed in space. Here we compare the dispersal of a meta-foodweb on Erdős-Rényi networks, that do not have a spatial embedding, and random geometric networks, that do have a spatial embedding. We found that local structure and large network distances in spatially embedded networks, lead to meso-scale patterns of patch occupation by both specialist and omnivorous species. In particular, we found that spatial separations make the coexistence of competing species more likely. Our results highlight the effects of spatial embeddings for meta-foodweb models, and the need for new analytical approaches to them.

A spatial error model with continuous random effects and an application to growth convergence

NASA Astrophysics Data System (ADS)

Laurini, Márcio Poletti

2017-10-01

We propose a spatial error model with continuous random effects based on Matérn covariance functions and apply this model for the analysis of income convergence processes (β -convergence). The use of a model with continuous random effects permits a clearer visualization and interpretation of the spatial dependency patterns, avoids the problems of defining neighborhoods in spatial econometrics models, and allows projecting the spatial effects for every possible location in the continuous space, circumventing the existing aggregations in discrete lattice representations. We apply this model approach to analyze the economic growth of Brazilian municipalities between 1991 and 2010 using unconditional and conditional formulations and a spatiotemporal model of convergence. The results indicate that the estimated spatial random effects are consistent with the existence of income convergence clubs for Brazilian municipalities in this period.

Theory and generation of conditional, scalable sub-Gaussian random fields

NASA Astrophysics Data System (ADS)

Panzeri, M.; Riva, M.; Guadagnini, A.; Neuman, S. P.

2016-03-01

Many earth and environmental (as well as a host of other) variables, Y, and their spatial (or temporal) increments, ΔY, exhibit non-Gaussian statistical scaling. Previously we were able to capture key aspects of such non-Gaussian scaling by treating Y and/or ΔY as sub-Gaussian random fields (or processes). This however left unaddressed the empirical finding that whereas sample frequency distributions of Y tend to display relatively mild non-Gaussian peaks and tails, those of ΔY often reveal peaks that grow sharper and tails that become heavier with decreasing separation distance or lag. Recently we proposed a generalized sub-Gaussian model (GSG) which resolves this apparent inconsistency between the statistical scaling behaviors of observed variables and their increments. We presented an algorithm to generate unconditional random realizations of statistically isotropic or anisotropic GSG functions and illustrated it in two dimensions. Most importantly, we demonstrated the feasibility of estimating all parameters of a GSG model underlying a single realization of Y by analyzing jointly spatial moments of Y data and corresponding increments, ΔY. Here, we extend our GSG model to account for noisy measurements of Y at a discrete set of points in space (or time), present an algorithm to generate conditional realizations of corresponding isotropic or anisotropic random fields, introduce two approximate versions of this algorithm to reduce CPU time, and explore them on one and two-dimensional synthetic test cases.

Simulation and analysis of scalable non-Gaussian statistically anisotropic random functions

NASA Astrophysics Data System (ADS)

Riva, Monica; Panzeri, Marco; Guadagnini, Alberto; Neuman, Shlomo P.

2015-12-01

Many earth and environmental (as well as other) variables, Y, and their spatial or temporal increments, ΔY, exhibit non-Gaussian statistical scaling. Previously we were able to capture some key aspects of such scaling by treating Y or ΔY as standard sub-Gaussian random functions. We were however unable to reconcile two seemingly contradictory observations, namely that whereas sample frequency distributions of Y (or its logarithm) exhibit relatively mild non-Gaussian peaks and tails, those of ΔY display peaks that grow sharper and tails that become heavier with decreasing separation distance or lag. Recently we overcame this difficulty by developing a new generalized sub-Gaussian model which captures both behaviors in a unified and consistent manner, exploring it on synthetically generated random functions in one dimension (Riva et al., 2015). Here we extend our generalized sub-Gaussian model to multiple dimensions, present an algorithm to generate corresponding random realizations of statistically isotropic or anisotropic sub-Gaussian functions and illustrate it in two dimensions. We demonstrate the accuracy of our algorithm by comparing ensemble statistics of Y and ΔY (such as, mean, variance, variogram and probability density function) with those of Monte Carlo generated realizations. We end by exploring the feasibility of estimating all relevant parameters of our model by analyzing jointly spatial moments of Y and ΔY obtained from a single realization of Y.

Pathogen-Host Associations and Predicted Range Shifts of Human Monkeypox in Response to Climate Change in Central Africa

PubMed Central

Thomassen, Henri A.; Fuller, Trevon; Asefi-Najafabady, Salvi; Shiplacoff, Julia A. G.; Mulembakani, Prime M.; Blumberg, Seth; Johnston, Sara C.; Kisalu, Neville K.; Kinkela, Timothée L.; Fair, Joseph N.; Wolfe, Nathan D.; Shongo, Robert L.; LeBreton, Matthew; Meyer, Hermann; Wright, Linda L.; Muyembe, Jean-Jacques; Buermann, Wolfgang; Okitolonda, Emile; Hensley, Lisa E.; Lloyd-Smith, James O.; Smith, Thomas B.; Rimoin, Anne W.

2013-01-01

Climate change is predicted to result in changes in the geographic ranges and local prevalence of infectious diseases, either through direct effects on the pathogen, or indirectly through range shifts in vector and reservoir species. To better understand the occurrence of monkeypox virus (MPXV), an emerging Orthopoxvirus in humans, under contemporary and future climate conditions, we used ecological niche modeling techniques in conjunction with climate and remote-sensing variables. We first created spatially explicit probability distributions of its candidate reservoir species in Africa's Congo Basin. Reservoir species distributions were subsequently used to model current and projected future distributions of human monkeypox (MPX). Results indicate that forest clearing and climate are significant driving factors of the transmission of MPX from wildlife to humans under current climate conditions. Models under contemporary climate conditions performed well, as indicated by high values for the area under the receiver operator curve (AUC), and tests on spatially randomly and non-randomly omitted test data. Future projections were made on IPCC 4th Assessment climate change scenarios for 2050 and 2080, ranging from more conservative to more aggressive, and representing the potential variation within which range shifts can be expected to occur. Future projections showed range shifts into regions where MPX has not been recorded previously. Increased suitability for MPX was predicted in eastern Democratic Republic of Congo. Models developed here are useful for identifying areas where environmental conditions may become more suitable for human MPX; targeting candidate reservoir species for future screening efforts; and prioritizing regions for future MPX surveillance efforts. PMID:23935820

Photon event distribution sampling: an image formation technique for scanning microscopes that permits tracking of sub-diffraction particles with high spatial and temporal resolutions.

PubMed

Larkin, J D; Publicover, N G; Sutko, J L

2011-01-01

In photon event distribution sampling, an image formation technique for scanning microscopes, the maximum likelihood position of origin of each detected photon is acquired as a data set rather than binning photons in pixels. Subsequently, an intensity-related probability density function describing the uncertainty associated with the photon position measurement is applied to each position and individual photon intensity distributions are summed to form an image. Compared to pixel-based images, photon event distribution sampling images exhibit increased signal-to-noise and comparable spatial resolution. Photon event distribution sampling is superior to pixel-based image formation in recognizing the presence of structured (non-random) photon distributions at low photon counts and permits use of non-raster scanning patterns. A photon event distribution sampling based method for localizing single particles derived from a multi-variate normal distribution is more precise than statistical (Gaussian) fitting to pixel-based images. Using the multi-variate normal distribution method, non-raster scanning and a typical confocal microscope, localizations with 8 nm precision were achieved at 10 ms sampling rates with acquisition of ~200 photons per frame. Single nanometre precision was obtained with a greater number of photons per frame. In summary, photon event distribution sampling provides an efficient way to form images when low numbers of photons are involved and permits particle tracking with confocal point-scanning microscopes with nanometre precision deep within specimens. © 2010 The Authors Journal of Microscopy © 2010 The Royal Microscopical Society.

Not to put too fine a point on it - does increasing precision of geographic referencing improve species distribution models for a wide-ranging migratory bat?

USGS Publications Warehouse

Hayes, Mark A.; Ozenberger, Katharine; Cryan, Paul M.; Wunder, Michael B.

2015-01-01

Bat specimens held in natural history museum collections can provide insights into the distribution of species. However, there are several important sources of spatial error associated with natural history specimens that may influence the analysis and mapping of bat species distributions. We analyzed the importance of geographic referencing and error correction in species distribution modeling (SDM) using occurrence records of hoary bats (Lasiurus cinereus). This species is known to migrate long distances and is a species of increasing concern due to fatalities documented at wind energy facilities in North America. We used 3,215 museum occurrence records collected from 1950–2000 for hoary bats in North America. We compared SDM performance using five approaches: generalized linear models, multivariate adaptive regression splines, boosted regression trees, random forest, and maximum entropy models. We evaluated results using three SDM performance metrics (AUC, sensitivity, and specificity) and two data sets: one comprised of the original occurrence data, and a second data set consisting of these same records after the locations were adjusted to correct for identifiable spatial errors. The increase in precision improved the mean estimated spatial error associated with hoary bat records from 5.11 km to 1.58 km, and this reduction in error resulted in a slight increase in all three SDM performance metrics. These results provide insights into the importance of geographic referencing and the value of correcting spatial errors in modeling the distribution of a wide-ranging bat species. We conclude that the considerable time and effort invested in carefully increasing the precision of the occurrence locations in this data set was not worth the marginal gains in improved SDM performance, and it seems likely that gains would be similar for other bat species that range across large areas of the continent, migrate, and are habitat generalists.

Environmental determinants of the spatial distribution of Alaria alata in Hungary.

PubMed

Széll, Z; Tolnai, Z; Sréter, T

2013-11-15

Alaria alata is a potential zoonotic parasite, which is widely distributed in Eurasia. To assess the risk of human infection, it is important to know the spatial distribution pattern of the parasite and factors influencing this pattern. To investigate these relationships, 1612 red fox (Vulpes vulpes) carcasses were randomly collected from the whole Hungarian territory, and the intestines were examined by sedimentation and counting technique. The spatial distribution of the parasite was highly clumped. The topographic positions where the foxes had been shot and the intensity of infections were recorded in geographic information system database. Digitized home ranges of infected and uninfected foxes were analysed on the background of geographic vector data of altitude, land cover types, permanent waters, mean annual temperature, annual precipitation and soil permeability. Multiple regression analysis was performed with environmental parameter values and A. alata scores. Based on the statistical analysis, lack of permanent waters, mean annual temperature, annual precipitation and soil permeability were the major determinants of the spatial distribution of A. alata. It can be explained by the use of biotopes by the intermediate hosts. The lack of permanent waters results in the use of temporary waters by the second intermediate hosts, frogs. The higher temperature, the lower precipitation and the higher soil permeability lead to earlier desiccation of temporary waters, and tadpoles and frogs infected with mesocercariae can be more easily predated by the final hosts (e.g., red foxes). Moreover, temporary waters are more easily contaminated with the faeces of the final hosts containing eggs than permanent waters. Therefore, high infection rate with A. alata can be expected mainly in lowland areas, where the hydrogeography of permanent waters is less complex, the precipitation is lower, the mean temperature and the soil permeability are higher than in highland areas. Copyright © 2013 Elsevier B.V. All rights reserved.

The mutation-drift balance in spatially structured populations.

PubMed

Schneider, David M; Martins, Ayana B; de Aguiar, Marcus A M

2016-08-07

In finite populations the action of neutral mutations is balanced by genetic drift, leading to a stationary distribution of alleles that displays a transition between two different behaviors. For small mutation rates most individuals will carry the same allele at equilibrium, whereas for high mutation rates of the alleles will be randomly distributed with frequencies close to one half for a biallelic gene. For well-mixed haploid populations the mutation threshold is μc=1/2N, where N is the population size. In this paper we study how spatial structure affects this mutation threshold. Specifically, we study the stationary allele distribution for populations placed on regular networks where connected nodes represent potential mating partners. We show that the mutation threshold is sensitive to spatial structure only if the number of potential mates is very small. In this limit, the mutation threshold decreases substantially, increasing the diversity of the population at considerably low mutation rates. Defining kc as the degree of the network for which the mutation threshold drops to half of its value in well-mixed populations we show that kc grows slowly as a function of the population size, following a power law. Our calculations and simulations are based on the Moran model and on a mapping between the Moran model with mutations and the voter model with opinion makers. Copyright © 2016 Elsevier Ltd. All rights reserved.

Random walks of colloidal probes in viscoelastic materials

NASA Astrophysics Data System (ADS)

Khan, Manas; Mason, Thomas G.

2014-04-01

To overcome limitations of using a single fixed time step in random walk simulations, such as those that rely on the classic Wiener approach, we have developed an algorithm for exploring random walks based on random temporal steps that are uniformly distributed in logarithmic time. This improvement enables us to generate random-walk trajectories of probe particles that span a highly extended dynamic range in time, thereby facilitating the exploration of probe motion in soft viscoelastic materials. By combining this faster approach with a Maxwell-Voigt model (MVM) of linear viscoelasticity, based on a slowly diffusing harmonically bound Brownian particle, we rapidly create trajectories of spherical probes in soft viscoelastic materials over more than 12 orders of magnitude in time. Appropriate windowing of these trajectories over different time intervals demonstrates that random walk for the MVM is neither self-similar nor self-affine, even if the viscoelastic material is isotropic. We extend this approach to spatially anisotropic viscoelastic materials, using binning to calculate the anisotropic mean square displacements and creep compliances along different orthogonal directions. The elimination of a fixed time step in simulations of random processes, including random walks, opens up interesting possibilities for modeling dynamics and response over a highly extended temporal dynamic range.

[Study on ecological suitability regionalization of Eucommia ulmoides in Guizhou].

PubMed

Kang, Chuan-Zhi; Wang, Qing-Qing; Zhou, Tao; Jiang, Wei-Ke; Xiao, Cheng-Hong; Xie, Yu

2014-05-01

To study the ecological suitability regionalization of Eucommia ulmoides, for selecting artificial planting base and high-quality industrial raw material purchase area of the herb in Guizhou. Based on the investigation of 14 Eucommia ulmoides producing areas, pinoresinol diglucoside content and ecological factors were obtained. Using spatial analysis method to carry on ecological suitability regionalization. Meanwhile, combining pinoresinol diglucoside content, the correlation of major active components and environmental factors were analyzed by statistical analysis. The most suitability planting area of Eucommia ulmoides was the northwest of Guizhou. The distribution of Eucommia ulmoides was mainly affected by the type and pH value of soil, and monthly precipitation. The spatial structure of major active components in Eucommia ulmoides were randomly distributed in global space, but had only one aggregation point which had a high positive correlation in local space. The major active components of Eucommia ulmoides had no correlation with altitude, longitude or latitude. Using the spatial analysis method and statistical analysis method, based on environmental factor and pinoresinol diglucoside content, the ecological suitability regionalization of Eucommia ulmoides can provide reference for the selection of suitable planting area, artificial planting base and directing production layout.

Image-Based Modeling Reveals Dynamic Redistribution of DNA Damageinto Nuclear Sub-Domains

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

Costes Sylvain V., Ponomarev Artem, Chen James L.; Nguyen, David; Cucinotta, Francis A.

2007-08-03

Several proteins involved in the response to DNA doublestrand breaks (DSB) f orm microscopically visible nuclear domains, orfoci, after exposure to ionizing radiation. Radiation-induced foci (RIF)are believed to be located where DNA damage occurs. To test thisassumption, we analyzed the spatial distribution of 53BP1, phosphorylatedATM, and gammaH2AX RIF in cells irradiated with high linear energytransfer (LET) radiation and low LET. Since energy is randomly depositedalong high-LET particle paths, RIF along these paths should also berandomly distributed. The probability to induce DSB can be derived fromDNA fragment data measured experimentally by pulsed-field gelelectrophoresis. We used this probability in Monte Carlo simulationsmore » topredict DSB locations in synthetic nuclei geometrically described by acomplete set of human chromosomes, taking into account microscope opticsfrom real experiments. As expected, simulations produced DNA-weightedrandom (Poisson) distributions. In contrast, the distributions of RIFobtained as early as 5 min after exposure to high LET (1 GeV/amu Fe) werenon-random. This deviation from the expected DNA-weighted random patterncan be further characterized by "relative DNA image measurements." Thisnovel imaging approach shows that RIF were located preferentially at theinterface between high and low DNA density regions, and were morefrequent than predicted in regions with lower DNA density. The samepreferential nuclear location was also measured for RIF induced by 1 Gyof low-LET radiation. This deviation from random behavior was evidentonly 5 min after irradiation for phosphorylated ATM RIF, while gammaH2AXand 53BP1 RIF showed pronounced deviations up to 30 min after exposure.These data suggest that DNA damage induced foci are restricted to certainregions of the nucleus of human epithelial cells. It is possible that DNAlesions are collected in these nuclear sub-domains for more efficientrepair.« less

The Distribution of Ice in Lunar Permanently Shadowed Regions: Science Enabling Exploration (Invited)

NASA Astrophysics Data System (ADS)

Hurley, D.; Elphic, R. C.; Bussey, B.; Hibbitts, C.; Lawrence, D. J.

2013-12-01

Recent prospecting indicates that water ice occurs in enhanced abundances in some lunar PSRs. That water constitutes a resource that enables lunar exploration if it can be harvested for fuel and life support. Future lunar exploration missions will need detailed information about the distribution of volatiles in lunar permanently shadowed regions (PSRs). In addition, the volatiles also offer key insights into the recent and distant past, as they have trapped volatiles delivered to the moon over ~2 Gyr. This comprises an unparalleled reservoir of past inner solar system volatiles, and future scientific missions are needed to make the measurements that will reveal the composition of those volatiles. These scientific missions will necessarily have to acquire and analyze samples of volatiles from the PSRs. For both exploration and scientific purposes, the precise location of volatiles will need to be known. However, data indicate that ice is distributed heterogeneously on the Moon. It is unlikely that the distribution will be known a priori with enough spatial resolution to guarantee access to volatiles using a single point sample. Some mechanism for laterally or vertically distributed access will increase the likelihood of acquiring a rich sample of volatiles. Trade studies will need to be conducted to anticipate the necessary range and duration of missions to lunar PSRs that will be needed to accomplish the mission objectives. We examine the spatial distribution of volatiles in lunar PSRs reported from data analyses and couple those with models of smaller scale processes. FUV and laser data from PSRs that indicate the average surface distribution is consistent with low abundances on the extreme surface in most PSRs. Neutron and radar data that probe the distribution at depth show heterogeneity at broad spatial resolution. We consider those data in conjunction with the model to understand the full, 3-D nature of the heterogeneity. A Monte Carlo technique simulates the stochastic process of impact gardening on a putative ice deposit. The model uses the crater production function as a basis for generating a random selection of impact craters over time. Impacts are implemented by modifying the topography, volatile content, and depth distribution in the simulation volume on a case by case basis. This technique will never be able to reproduce the exact impact history of a particular area. But by conducting multiple runs with the same initial conditions and a different seed to the random number generator, we are able to calculate the probability of situations occurring. Further, by repeating the simulations with varied initial conditions, we calculate the dependence of the expectation values on the inputs. We present findings regarding the heterogeneity of volatiles in PSRs as a function of age, initial ice thickness, and contributions from steady sources.

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.

Can we infer plant facilitation from remote sensing? A test across global drylands

PubMed Central

Xu, Chi; Holmgren, Milena; Van Nes, Egbert H.; Maestre, Fernando T.; Soliveres, Santiago; Berdugo, Miguel; Kéfi, Sonia; Marquet, Pablo A.; Abades, Sebastian; Scheffer, Marten

2016-01-01

Facilitation is a major force shaping the structure and diversity of plant communities in terrestrial ecosystems. Detecting positive plant-plant interactions relies on the combination of field experimentation and the demonstration of spatial association between neighboring plants. This has often restricted the study of facilitation to particular sites, limiting the development of systematic assessments of facilitation over regional and global scales. Here we explore whether the frequency of plant spatial associations detected from high-resolution remotely-sensed images can be used to infer plant facilitation at the community level in drylands around the globe. We correlated the information from remotely-sensed images freely available through Google Earth™ with detailed field assessments, and used a simple individual-based model to generate patch-size distributions using different assumptions about the type and strength of plant-plant interactions. Most of the patterns found from the remotely-sensed images were more right-skewed than the patterns from the null model simulating a random distribution. This suggests that the plants in the studied drylands show stronger spatial clustering than expected by chance. We found that positive plant co-occurrence, as measured in the field, was significantly related to the skewness of vegetation patch-size distribution measured using Google Earth™ images. Our findings suggest that the relative frequency of facilitation may be inferred from spatial pattern signals measured from remotely-sensed images, since facilitation often determines positive co-occurrence among neighboring plants. They pave the road for a systematic global assessment of the role of facilitation in terrestrial ecosystems. PMID:26552256

On the use of a PM2.5 exposure simulator to explain birthweight

PubMed Central

Berrocal, Veronica J.; Gelfand, Alan E.; Holland, David M.; Burke, Janet; Miranda, Marie Lynn

2010-01-01

In relating pollution to birth outcomes, maternal exposure has usually been described using monitoring data. Such characterization provides a misrepresentation of exposure as it (i) does not take into account the spatial misalignment between an individual’s residence and monitoring sites, and (ii) it ignores the fact that individuals spend most of their time indoors and typically in more than one location. In this paper, we break with previous studies by using a stochastic simulator to describe personal exposure (to particulate matter) and then relate simulated exposures at the individual level to the health outcome (birthweight) rather than aggregating to a selected spatial unit. We propose a hierarchical model that, at the first stage, specifies a linear relationship between birthweight and personal exposure, adjusting for individual risk factors and introduces random spatial effects for the census tract of maternal residence. At the second stage, our hierarchical model specifies the distribution of each individual’s personal exposure using the empirical distribution yielded by the stochastic simulator as well as a model for the spatial random effects. We have applied our framework to analyze birthweight data from 14 counties in North Carolina in years 2001 and 2002. We investigate whether there are certain aspects and time windows of exposure that are more detrimental to birthweight by building different exposure metrics which we incorporate, one by one, in our hierarchical model. To assess the difference in relating ambient exposure to birthweight versus personal exposure to birthweight, we compare estimates of the effect of air pollution obtained from hierarchical models that linearly relate ambient exposure and birthweight versus those obtained from our modeling framework. Our analysis does not show a significant effect of PM2.5 on birthweight for reasons which we discuss. However, our modeling framework serves as a template for analyzing the relationship between personal exposure and longer term health endpoints. PMID:21691413

Complex Spatial Structure in a Population of Didymopanax pittieri, A Tree of Wind-Exposed Lower Montane Rain Forest

NASA Technical Reports Server (NTRS)

Lawton, Robert M.; Lawton, Robert O.

2010-01-01

Didymopanax pittieri is a common shade-intolerant tree colonizing treefall gaps in the elfin forests on windswept ridgecrests in the lower montane rain forests of the Cordillera de Tilarain, Costa Rica. All D. pittieri taller than > 0.5 m in a 5.2-ha elfin forested portion of a gridded study watershed in the Monteverde Cloud Forest Preserve were located, mapped, and measured. This local population of D. pittieri is spatially inhomogeneous, in that density increases with increasing wind exposure; D. pittieri are more abundant near ridge crests than lower on windward slopes. The important and ubiquitous phenomenon of spatial inhomogeneity in population density is addressed and corrected for in spatial analyses by the application of the inhomogeneous version of Ripley's K. The spatial patterns of four size classes of D. pittieri (<5 cm dbh, 5-10 cm dbh, 10-20 cm dbh, and> 20 cm dbh) were investigated. Within the large-scale trend in density driven by wind exposure, D. pittieri saplings are clumped at the scale of treefall gaps and at the scale of patches of aggregated gaps. D. pittieri 5-10 cm dbh are randomly distributed, apparently due to competitive thinning of sapling clumps during the early stages of gap-phase regeneration. D. pittieri larger than 10 cm dbh are overdispersed at a scale larger than that of patches of gaps. Natural disturbance can influence the distribution of shade intolerant tree populations at several different spatial scales, and can have discordant effects at different life history stages.

Quantitative characterization of the regressive ecological succession by fractal analysis of plant spatial patterns

USGS Publications Warehouse

Alados, C.L.; Pueyo, Y.; Giner, M.L.; Navarro, T.; Escos, J.; Barroso, F.; Cabezudo, B.; Emlen, J.M.

2003-01-01

We studied the effect of grazing on the degree of regression of successional vegetation dynamic in a semi-arid Mediterranean matorral. We quantified the spatial distribution patterns of the vegetation by fractal analyses, using the fractal information dimension and spatial autocorrelation measured by detrended fluctuation analyses (DFA). It is the first time that fractal analysis of plant spatial patterns has been used to characterize the regressive ecological succession. Plant spatial patterns were compared over a long-term grazing gradient (low, medium and heavy grazing pressure) and on ungrazed sites for two different plant communities: A middle dense matorral of Chamaerops and Periploca at Sabinar-Romeral and a middle dense matorral of Chamaerops, Rhamnus and Ulex at Requena-Montano. The two communities differed also in the microclimatic characteristics (sea oriented at the Sabinar-Romeral site and inland oriented at the Requena-Montano site). The information fractal dimension increased as we moved from a middle dense matorral to discontinuous and scattered matorral and, finally to the late regressive succession, at Stipa steppe stage. At this stage a drastic change in the fractal dimension revealed a change in the vegetation structure, accurately indicating end successional vegetation stages. Long-term correlation analysis (DFA) revealed that an increase in grazing pressure leads to unpredictability (randomness) in species distributions, a reduction in diversity, and an increase in cover of the regressive successional species, e.g. Stipa tenacissima L. These comparisons provide a quantitative characterization of the successional dynamic of plant spatial patterns in response to grazing perturbation gradient. ?? 2002 Elsevier Science B.V. All rights reserved.

Incorporating geologic information into hydraulic tomography: A general framework based on geostatistical approach

NASA Astrophysics Data System (ADS)

Zha, Yuanyuan; Yeh, Tian-Chyi J.; Illman, Walter A.; Onoe, Hironori; Mok, Chin Man W.; Wen, Jet-Chau; Huang, Shao-Yang; Wang, Wenke

2017-04-01

Hydraulic tomography (HT) has become a mature aquifer test technology over the last two decades. It collects nonredundant information of aquifer heterogeneity by sequentially stressing the aquifer at different wells and collecting aquifer responses at other wells during each stress. The collected information is then interpreted by inverse models. Among these models, the geostatistical approaches, built upon the Bayesian framework, first conceptualize hydraulic properties to be estimated as random fields, which are characterized by means and covariance functions. They then use the spatial statistics as prior information with the aquifer response data to estimate the spatial distribution of the hydraulic properties at a site. Since the spatial statistics describe the generic spatial structures of the geologic media at the site rather than site-specific ones (e.g., known spatial distributions of facies, faults, or paleochannels), the estimates are often not optimal. To improve the estimates, we introduce a general statistical framework, which allows the inclusion of site-specific spatial patterns of geologic features. Subsequently, we test this approach with synthetic numerical experiments. Results show that this approach, using conditional mean and covariance that reflect site-specific large-scale geologic features, indeed improves the HT estimates. Afterward, this approach is applied to HT surveys at a kilometer-scale-fractured granite field site with a distinct fault zone. We find that by including fault information from outcrops and boreholes for HT analysis, the estimated hydraulic properties are improved. The improved estimates subsequently lead to better prediction of flow during a different pumping test at the site.

Patterns of mortality in a montane mixed-conifer forest in San Diego County, California.

PubMed

Freeman, Mary Pyott; Stow, Douglas A; An, Li

2017-10-01

We examine spatial patterns of conifer tree mortality and their changes over time for the montane mixed-conifer forests of San Diego County. These forest areas have recently experienced extensive tree mortality due to multiple factors. A spatial contextual image processing approach was utilized with high spatial resolution digital airborne imagery to map dead trees for the years 1997, 2000, 2002, and 2005 for three study areas: Palomar, Volcan, and Laguna mountains. Plot-based fieldwork was conducted to further assess mortality patterns. Mean mortality remained static from 1997 to 2002 (4, 2.2, and 4.2 trees/ha for Palomar, Volcan, and Laguna) and then increased by 2005 to 10.3, 9.7, and 5.2 trees/ha, respectively. The increase in mortality between 2002 and 2005 represents the temporal pattern of a discrete disturbance event, attributable to the 2002-2003 drought. Dead trees are significantly clustered for all dates, based on spatial cluster analysis, indicating that they form distinct groups, as opposed to spatially random single dead trees. Other tests indicate no directional shift or spread of mortality over time, but rather an increase in density. While general temporal and spatial mortality processes are uniform across all study areas, the plot-based species and quantity distribution of mortality, and diameter distributions of dead vs. living trees, vary by study area. The results of this study improve our understanding of stand- to landscape-level forest structure and dynamics, particularly by examining them from the multiple perspectives of field and remotely sensed data. © 2017 by the Ecological Society of America.

Summer spatial patterning of chukars in relation to free water in Western Utah

USGS Publications Warehouse

Larsen, R.T.; Bissonette, J.A.; Flinders, J.T.; Hooten, M.B.; Wilson, T.L.

2010-01-01

Free water is considered important to wildlife in arid regions. In the western United States, thousands of water developments have been built to benefit wildlife in arid landscapes. Agencies and researchers have yet to clearly demonstrate their effectiveness. We combined a spatial analysis of summer chukar (Alectoris chukar) covey locations with dietary composition analysis in western Utah. Our specific objectives were to determine if chukars showed a spatial pattern that suggested association with free water in four study areas and to document summer dietary moisture content in relation to average distance from water. The observed data for the Cedar Mountains study area fell within the middle of the random mean distance to water distribution suggesting no association with free water. The observed mean distance to water for the other three areas was much closer than expected compared to a random spatial process, suggesting the importance of free water to these populations. Dietary moisture content of chukar food items from the Cedar Mountains (59%) was significantly greater (P < 0.05) than that of birds from Box Elder (44%) and Keg-Dugway (44%). Water developments on the Cedar Mountains are likely ineffective for chukars. Spatial patterns on the other areas, however, suggest association with free water and our results demonstrate the need for site-specific considerations. Researchers should be aware of the potential to satisfy water demand with pre-formed and metabolic water for a variety of species in studies that address the effects of wildlife water developments. We encourage incorporation of spatial structure in model error components in future ecological research. ?? Springer Science+Business Media B.V. 2009.

Soil Bacteria And Fungi Respond On Different Spatial Scales To Invasion By The Legume Lespedeza Cuneata

DTIC Science & Technology

2011-06-03

Permutationalmultivariate analysis of variance ( PerMANOVA ; McArdle and Anderson, 2001) was used to test hypotheses regard- ing regions and invasion level...for the differences due to invasion level after removing any differences due to regions, soil texture, and habitat. The null distribution for PerMANOVA ...soil neigh- borhoods, PerMANOVA tests were carried out separately for each site. We did not use a stratified randomization scheme for these tests, under

THE EFFECTS OF SPATIAL SMOOTHING ON SOLAR MAGNETIC HELICITY PARAMETERS AND THE HEMISPHERIC HELICITY SIGN RULE

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

Ocker, Stella Koch; Petrie, Gordon, E-mail: socker@oberlin.edu, E-mail: gpetrie@nso.edu

The hemispheric preference for negative/positive helicity to occur in the northern/southern solar hemisphere provides clues to the causes of twisted, flaring magnetic fields. Previous studies on the hemisphere rule may have been affected by seeing from atmospheric turbulence. Using Hinode /SOT-SP data spanning 2006–2013, we studied the effects of two spatial smoothing tests that imitate atmospheric seeing: noise reduction by ignoring pixel values weaker than the estimated noise threshold, and Gaussian spatial smoothing. We studied in detail the effects of atmospheric seeing on the helicity distributions across various field strengths for active regions (ARs) NOAA 11158 and NOAA 11243, in addition tomore » studying the average helicities of 179 ARs with and without smoothing. We found that, rather than changing trends in the helicity distributions, spatial smoothing modified existing trends by reducing random noise and by regressing outliers toward the mean, or removing them altogether. Furthermore, the average helicity parameter values of the 179 ARs did not conform to the hemisphere rule: independent of smoothing, the weak-vertical-field values tended to be negative in both hemispheres, and the strong-vertical-field values tended to be positive, especially in the south. We conclude that spatial smoothing does not significantly affect the overall statistics for space-based data, and thus seeing from atmospheric turbulence seems not to have significantly affected previous studies’ ground-based results on the hemisphere rule.« less

Distribution of 'Candidatus Liberibacter asiaticus' Above and Below Ground in Texas Citrus.

PubMed

Louzada, Eliezer S; Vazquez, Omar Ed; Braswell, W Evan; Yanev, George; Devanaboina, Madhavi; Kunta, Madhurababu

2016-07-01

Detection of 'Candidatus Liberibacter asiaticus' represents one of the most difficult, yet critical, steps of controlling Huanglongbing disease. Efficient detection relies on understanding the underlying distribution of bacteria within trees. To that end, we studied the distribution of 'Ca. L. asiaticus' in leaves of 'Rio Red' grapefruit trees and in roots of 'Valencia' sweet orange trees grafted onto sour orange rootstock. We performed two sets of leaf collection on grapefruit trees; the first a selective sampling targeting symptomatic leaves and their neighbors and the second a systematic collection disregarding symptomology. From uprooted orange trees, we exhaustively sampled fibrous roots. In this study, the presence of 'Ca. L. asiaticus' was detected in leaves using real-time polymerase chain reaction (PCR) targeting the 16S ribosomal gene and in roots using the rpIJ/rpIL ribosomal protein genes and was confirmed with conventional PCR and sequencing of the rpIJ/rpIL gene in both tissues. Among randomly collected leaves, 'Ca. L. asiaticus' was distributed in a patchy fashion. Detection of 'Ca. L. asiaticus' varied with leaf symptomology with symptomatic leaves showing the highest frequency (74%) followed by their neighboring asymptomatic leaves (30%), while randomly distributed asymptomatic leaves had the lowest frequency (20%). Among symptomatic leaves, we found statistically significant differences in mean number of bacterial cells with respect to both increasing distance of the leaf from the trunk and cardinal direction. The titer of 'Ca. L. asiaticus' cells was significantly greater on the north side of trees than on the south and west sides. Moreover, these directions showed different spatial distributions of 'Ca. L. asiaticus' with higher titers near the trunk on the south and west sides as opposed to further from the trunk on the north side. Similarly, we found spatial variation in 'Ca. L. asiaticus' distribution among root samples. 'Ca. L. asiaticus' was detected more frequently and bacterial abundances were higher among horizontally growing roots just under the soil surface (96%) than among deeper vertically growing roots (78%). Bacterial abundance declined slightly with distance from the trunk. These results point to paths of research that will likely prove useful to combating this devastating disease.

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.

Investigation of Soil Erosion and Phosphorus Transport within an Agricultural Watershed

NASA Astrophysics Data System (ADS)

Klik, A.; Jester, W.; Muhar, A.; Peinsitt, A.; Rampazzo, N.; Mentler, A.; Staudinger, B.; Eder, M.

2003-04-01

In a 40 ha agricultural used watershed in Austria, surface runoff, soil erosion and nutrient losses are measured spatially distributed with 12 small erosion plots. Crops during growing season 2002 are canola, corn, sunflower, winter wheat, winter barley, rye, sugar beets, and pasture. Canopy height and canopy cover are observed in 14-day intervals. Four times per year soil water content, shear stress and random roughness of the surface are measured in a 25 x 25 m grid (140 points). The same raster is sampled for soil texture analyses and content of different phosphorus fractions in the 0-10 cm soil depth. Spatially distributed data are used for geostatistical analysis. Along three transects hydrologic conditions of the hillslope position (top, middle, foot) are investigated by measuring soil water content and soil matrix potential. After erosive events erosion features (rills, deposition, ...) are mapped using GPS. All measured data will be used as input parameters for the Limburg Soil Erosion Model (LISEM).

The Buildup of a Scale-free Photospheric Magnetic Network

NASA Astrophysics Data System (ADS)

Thibault, K.; Charbonneau, P.; Crouch, A. D.

2012-10-01

We use a global Monte Carlo simulation of the formation of the solar photospheric magnetic network to investigate the origin of the scale invariance characterizing magnetic flux concentrations visible on high-resolution magnetograms. The simulations include spatially and temporally homogeneous injection of small-scale magnetic elements over the whole photosphere, as well as localized episodic injection associated with the emergence and decay of active regions. Network elements form in response to cumulative pairwise aggregation or cancellation of magnetic elements, undergoing a random walk on the sphere and advected on large spatial scales by differential rotation and a poleward meridional flow. The resulting size distribution of simulated network elements is in very good agreement with observational inferences. We find that the fractal index and size distribution of network elements are determined primarily by these post-emergence surface mechanisms, and carry little or no memory of the scales at which magnetic flux is injected in the simulation. Implications for models of dynamo action in the Sun are briefly discussed.

Cellular automaton for migration in ecosystem: Application of traffic model to a predator-prey system

NASA Astrophysics Data System (ADS)

Nagatani, Takashi; Tainaka, Kei-ichi

2018-01-01

In most cases, physicists have studied the migration of biospecies by the use of random walk. In the present article, we apply cellular automaton of traffic model. For simplicity, we deal with an ecosystem contains a prey and predator, and use one-dimensional lattice with two layers. Preys stay on the first layer, but predators uni-directionally move on the second layer. The spatial and temporal evolution is numerically explored. It is shown that the migration has the important effect on populations of both prey and predator. Without migration, the phase transition between a prey-phase and coexisting-phase occurs. In contrast, the phase transition disappears by migration. This is because predator can survive due to migration. We find another phase transition for spatial distribution: in one phase, prey and predator form a stripe pattern of condensation and rarefaction, while in the other phase, they uniformly distribute. The self-organized stripe may be similar to the migration patterns in real ecosystems.

Single laser beam of spatial coherence from an array of GaAs lasers - Free-running mode

NASA Technical Reports Server (NTRS)

Philipp-Rutz, E. M.

1975-01-01

Spatially coherent radiation from a monolithic array of three GaAs lasers in a free-running mode is reported. The lasers, with their mirror faces antireflection coated, are operated in an external optical cavity built of spherical lenses and plane mirrors. The spatially coherent-beam formation makes use of the Fourier-transformation property of the internal lenses. Transverse mode control is accomplished by a spatial filter. The optical cavity is similar to that used for the phase-controlled mode of spatially coherent-beam formation; only the spatial filters are different. In the far field (when restored by an external lens), the intensities of the lasers in the array are concentrated in a single laser beam of spatial coherence, without any grating lobes. The far-field distribution of the laser array in the free-running mode differs significantly from the interference pattern of the phase-controlled mode. The modulation characteristics of the optical waveforms of the two modes are also quite different because modulation is related to the interaction of the spatial filter with the longitudinal modes of the laser array within the optical cavity. The modulation of the optical waveform of the free-running mode is nonperiodic, confirming that the fluctuations of the optical fields of the lasers are random.

Landsat phenological metrics and their relation to aboveground carbon in the Brazilian Savanna.

PubMed

Schwieder, M; Leitão, P J; Pinto, J R R; Teixeira, A M C; Pedroni, F; Sanchez, M; Bustamante, M M; Hostert, P

2018-05-15

The quantification and spatially explicit mapping of carbon stocks in terrestrial ecosystems is important to better understand the global carbon cycle and to monitor and report change processes, especially in the context of international policy mechanisms such as REDD+ or the implementation of Nationally Determined Contributions (NDCs) and the UN Sustainable Development Goals (SDGs). Especially in heterogeneous ecosystems, such as Savannas, accurate carbon quantifications are still lacking, where highly variable vegetation densities occur and a strong seasonality hinders consistent data acquisition. In order to account for these challenges we analyzed the potential of land surface phenological metrics derived from gap-filled 8-day Landsat time series for carbon mapping. We selected three areas located in different subregions in the central Brazil region, which is a prominent example of a Savanna with significant carbon stocks that has been undergoing extensive land cover conversions. Here phenological metrics from the season 2014/2015 were combined with aboveground carbon field samples of cerrado sensu stricto vegetation using Random Forest regression models to map the regional carbon distribution and to analyze the relation between phenological metrics and aboveground carbon. The gap filling approach enabled to accurately approximate the original Landsat ETM+ and OLI EVI values and the subsequent derivation of annual phenological metrics. Random Forest model performances varied between the three study areas with RMSE values of 1.64 t/ha (mean relative RMSE 30%), 2.35 t/ha (46%) and 2.18 t/ha (45%). Comparable relationships between remote sensing based land surface phenological metrics and aboveground carbon were observed in all study areas. Aboveground carbon distributions could be mapped and revealed comprehensible spatial patterns. Phenological metrics were derived from 8-day Landsat time series with a spatial resolution that is sufficient to capture gradual changes in carbon stocks of heterogeneous Savanna ecosystems. These metrics revealed the relationship between aboveground carbon and the phenology of the observed vegetation. Our results suggest that metrics relating to the seasonal minimum and maximum values were the most influential variables and bear potential to improve spatially explicit mapping approaches in heterogeneous ecosystems, where both spatial and temporal resolutions are critical.

Spatial and temporal variability of microgeographic genetic structure in white-tailed deer

USGS Publications Warehouse

Scribner, Kim T.; Smith, Michael H.; Chesser, Ronald K.

1997-01-01

Techniques are described that define contiguous genetic subpopulations of white-tailed deer (Odocoileus virginianus) based on the spatial dispersion of 4,749 individuals that possessed discrete character values (alleles or genotypes) during each of 6 years (1974-1979). White-tailed deer were not uniformly distributed in space, but exhibited considerable spatial genetic structuring. Significant non-random clusters of individuals were documented during each year based on specific alleles and genotypes at the Sdh locus. Considerable temporal variation was observed in the position and genetic composition of specific clusters, which reflected changes in allele frequency in small geographic areas. The position of clusters did not consistently correspond with traditional management boundaries based on major discontinuities in habitat (swamp versus upland) and hunt compartments that were defined by roads and streams. Spatio-temporal stability of observed genetic contiguous clusters was interpreted relative to method and intensity of harvest, movements, and breeding ecology.

Spatial patterns of phylogenetic diversity.

PubMed

Morlon, Hélène; Schwilk, Dylan W; Bryant, Jessica A; Marquet, Pablo A; Rebelo, Anthony G; Tauss, Catherine; Bohannan, Brendan J M; Green, Jessica L

2011-02-01

Ecologists and conservation biologists have historically used species-area and distance-decay relationships as tools to predict the spatial distribution of biodiversity and the impact of habitat loss on biodiversity. These tools treat each species as evolutionarily equivalent, yet the importance of species' evolutionary history in their ecology and conservation is becoming increasingly evident. Here, we provide theoretical predictions for phylogenetic analogues of the species-area and distance-decay relationships. We use a random model of community assembly and a spatially explicit flora dataset collected in four Mediterranean-type regions to provide theoretical predictions for the increase in phylogenetic diversity - the total phylogenetic branch-length separating a set of species - with increasing area and the decay in phylogenetic similarity with geographic separation. These developments may ultimately provide insights into the evolution and assembly of biological communities, and guide the selection of protected areas. © 2010 Blackwell Publishing Ltd/CNRS.

Spatial analysis of factors influencing long-term stress in the grizzly bear (Ursus arctos) population of Alberta, Canada.

PubMed

Bourbonnais, Mathieu L; Nelson, Trisalyn A; Cattet, Marc R L; Darimont, Chris T; Stenhouse, Gordon B

2013-01-01

Non-invasive measures for assessing long-term stress in free ranging mammals are an increasingly important approach for understanding physiological responses to landscape conditions. Using a spatially and temporally expansive dataset of hair cortisol concentrations (HCC) generated from a threatened grizzly bear (Ursus arctos) population in Alberta, Canada, we quantified how variables representing habitat conditions and anthropogenic disturbance impact long-term stress in grizzly bears. We characterized spatial variability in male and female HCC point data using kernel density estimation and quantified variable influence on spatial patterns of male and female HCC stress surfaces using random forests. Separate models were developed for regions inside and outside of parks and protected areas to account for substantial differences in anthropogenic activity and disturbance within the study area. Variance explained in the random forest models ranged from 55.34% to 74.96% for males and 58.15% to 68.46% for females. Predicted HCC levels were higher for females compared to males. Generally, high spatially continuous female HCC levels were associated with parks and protected areas while low-to-moderate levels were associated with increased anthropogenic disturbance. In contrast, male HCC levels were low in parks and protected areas and low-to-moderate in areas with increased anthropogenic disturbance. Spatial variability in gender-specific HCC levels reveal that the type and intensity of external stressors are not uniform across the landscape and that male and female grizzly bears may be exposed to, or perceive, potential stressors differently. We suggest observed spatial patterns of long-term stress may be the result of the availability and distribution of foods related to disturbance features, potential sexual segregation in available habitat selection, and may not be influenced by sources of mortality which represent acute traumas. In this wildlife system and others, conservation and management efforts can benefit by understanding spatial- and gender-based stress responses to landscape conditions.

Spatial Analysis of Factors Influencing Long-Term Stress in the Grizzly Bear (Ursus arctos) Population of Alberta, Canada

PubMed Central

Bourbonnais, Mathieu L.; Nelson, Trisalyn A.; Cattet, Marc R. L.; Darimont, Chris T.; Stenhouse, Gordon B.

2013-01-01

Non-invasive measures for assessing long-term stress in free ranging mammals are an increasingly important approach for understanding physiological responses to landscape conditions. Using a spatially and temporally expansive dataset of hair cortisol concentrations (HCC) generated from a threatened grizzly bear (Ursus arctos) population in Alberta, Canada, we quantified how variables representing habitat conditions and anthropogenic disturbance impact long-term stress in grizzly bears. We characterized spatial variability in male and female HCC point data using kernel density estimation and quantified variable influence on spatial patterns of male and female HCC stress surfaces using random forests. Separate models were developed for regions inside and outside of parks and protected areas to account for substantial differences in anthropogenic activity and disturbance within the study area. Variance explained in the random forest models ranged from 55.34% to 74.96% for males and 58.15% to 68.46% for females. Predicted HCC levels were higher for females compared to males. Generally, high spatially continuous female HCC levels were associated with parks and protected areas while low-to-moderate levels were associated with increased anthropogenic disturbance. In contrast, male HCC levels were low in parks and protected areas and low-to-moderate in areas with increased anthropogenic disturbance. Spatial variability in gender-specific HCC levels reveal that the type and intensity of external stressors are not uniform across the landscape and that male and female grizzly bears may be exposed to, or perceive, potential stressors differently. We suggest observed spatial patterns of long-term stress may be the result of the availability and distribution of foods related to disturbance features, potential sexual segregation in available habitat selection, and may not be influenced by sources of mortality which represent acute traumas. In this wildlife system and others, conservation and management efforts can benefit by understanding spatial- and gender-based stress responses to landscape conditions. PMID:24386273

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.

Distribution of epibenthic megafauna and lebensspuren on two central North Pacific seamounts

NASA Astrophysics Data System (ADS)

Kaufmann, Ronald S.; Wakefield, W. Waldo; Genin, Amatzia

1989-12-01

The abundance, composition and spatial distribution of megafaunal communities and lebensspuren assemblages at three sites on two deep seamounts in the central North Pacific were surveyed photographically using still cameras mounted on the research submersible Alvin. Photographic transects were made on the summit cap (˜1500 m depth) and summit perimeter (˜ 1800 m depth) of Horizon Guyot and on the summit cap (˜3100 m depth) of Magellan Rise. The summit caps of both seamounts were covered with foraminiferal sand, while the summit perimeter of Horizon Guyot was characterized by numerous rock outcroppings (basalt and chert encrusted with ferromanganese oxides) on which was situated a speciose assemblage of suspension-feeding organisms. The most abundant megafauna at all three sites were large, sediment-agglutinating protists belonging to the class Xenophyophorea. Among the three sites, the Horizon Guyot summit cap supported the highest densities of fishes and lebensspuren and the fewest echinoderms, while the Magellan Rise summit cap was populated by a diverse community of deposit-feeding echinoderms. Megafaunal abundances on Horizon Guyot were lower than those at equivalent depths on the western North Atlantic continental slope, while those on Magellan Rise were higher. The faunal differences observed between the two seamounts were attributed primarily to differences in hydrodynamic conditions, substrate availability and nutrient availability. Most of the lebensspuren on these seamounts appeared to be patchily distributed on spatial scales of 10-1000 m, while xenophyophore distributions were predominantly random on the same spatial scales. Biogeographically the species identified exhibited predominantly widespread to cosmopolitan distributions with Indo-West Pacific faunal affinities, typical of other seamounts in the same depth range and biogeographic province.

Spatial disaggregation of complex soil map units at regional scale based on soil-landscape relationships

NASA Astrophysics Data System (ADS)

Vincent, Sébastien; Lemercier, Blandine; Berthier, Lionel; Walter, Christian

2015-04-01

Accurate soil information over large extent is essential to manage agronomical and environmental issues. Where it exists, information on soil is often sparse or available at coarser resolution than required. Typically, the spatial distribution of soil at regional scale is represented as a set of polygons defining soil map units (SMU), each one describing several soil types not spatially delineated, and a semantic database describing these objects. Delineation of soil types within SMU, ie spatial disaggregation of SMU allows improved soil information's accuracy using legacy data. The aim of this study was to predict soil types by spatial disaggregation of SMU through a decision tree approach, considering expert knowledge on soil-landscape relationships embedded in soil databases. The DSMART (Disaggregation and Harmonization of Soil Map Units Through resampled Classification Trees) algorithm developed by Odgers et al. (2014) was used. It requires soil information, environmental covariates, and calibration samples, to build then extrapolate decision trees. To assign a soil type to a particular spatial position, a weighed random allocation approach is applied: each soil type in the SMU is weighted according to its assumed proportion of occurrence in the SMU. Thus soil-landscape relationships are not considered in the current version of DSMART. Expert rules on soil distribution considering the relief, parent material and wetlands location were proposed to drive the procedure of allocation of soil type to sampled positions, in order to integrate the soil-landscape relationships. Semantic information about spatial organization of soil types within SMU and exhaustive landscape descriptors were used. In the eastern part of Brittany (NW France), 171 soil types were described; their relative area in the SMU were estimated, geomorphological and geological contexts were recorded. The model predicted 144 soil types. An external validation was performed by comparing predicted with effectively observed soil types derived from available soil maps at scale of 1:25.000 or 1:50.000. Overall accuracies were 63.1% and 36.2%, respectively considering or not the adjacent pixels. The introduction of expert rules based on soil-landscape relationships to allocate soil types to calibration samples enhanced dramatically the results in comparison with a simple weighted random allocation procedure. It also enabled the production of a comprehensive soil map, retrieving expected spatial organization of soils. Estimation of soil properties for various depths is planned using disaggregated soil types, according to the GlobalSoilmap.net specifications. Odgers, N.P., Sun, W., McBratney, A.B., Minasny, B., Clifford, D., 2014. Disaggregating and harmonising soil map units through resampled classification trees. Geoderma 214, 91-100.

Off-Grid Direction of Arrival Estimation Based on Joint Spatial Sparsity for Distributed Sparse Linear Arrays

PubMed Central

Liang, Yujie; Ying, Rendong; Lu, Zhenqi; Liu, Peilin

2014-01-01

In the design phase of sensor arrays during array signal processing, the estimation performance and system cost are largely determined by array aperture size. In this article, we address the problem of joint direction-of-arrival (DOA) estimation with distributed sparse linear arrays (SLAs) and propose an off-grid synchronous approach based on distributed compressed sensing to obtain larger array aperture. We focus on the complex source distribution in the practical applications and classify the sources into common and innovation parts according to whether a signal of source can impinge on all the SLAs or a specific one. For each SLA, we construct a corresponding virtual uniform linear array (ULA) to create the relationship of random linear map between the signals respectively observed by these two arrays. The signal ensembles including the common/innovation sources for different SLAs are abstracted as a joint spatial sparsity model. And we use the minimization of concatenated atomic norm via semidefinite programming to solve the problem of joint DOA estimation. Joint calculation of the signals observed by all the SLAs exploits their redundancy caused by the common sources and decreases the requirement of array size. The numerical results illustrate the advantages of the proposed approach. PMID:25420150

Electron transport through triangular potential barriers with doping-induced disorder

NASA Astrophysics Data System (ADS)

Elpelt, R.; Wolst, O.; Willenberg, H.; Malzer, S.; Döhler, G. H.

2004-05-01

Electron transport through single-, double-, and triple-barrier structures created by the insertion of suitably δ-doped layers in GaAs is investigated. The results are compared with experiments on barriers of similar shape, but obtained by linear grading of the Al fraction x in AlxGa1-xAs structures. In the case of the doping-induced space-charge potential it is found that the effective barrier height for transport is much lower than expected from a simple model, in which uniform distribution of the doping charge within the doped layers is assumed. This reduction is quantitatively explained by taking into account the random distribution of the acceptor atoms within the δp-doped layers, which results in large spatial fluctuations of the barrier potential. The transport turns out to be dominated by small regions around the energetically lowest saddle points of the random space-charge potential. Additionally, independent on the dimensionality of the transport [three-dimensional (3D) to 3D in the single barrier, from 3D through 2D to 3D in the double barrier, and from 3D through 2D through 2D to 3D in the triple-barrier structure], fingerprints of 2D subband resonances are neither experimentally observed nor theoretically expected in the doping-induced structures. This is attributed to the disorder-induced random spatial fluctuations of the subband energies in the n layers which are uncorrelated for neighboring layers. Our interpretations of the temperature-dependent current-voltage characteristics are corroborated by comparison with the experimental and theoretical results obtained from the corresponding fluctuation-free AlxGa1-xAs structures. Quantitative agreement between theory and experiment is observed in both cases.

[Inequities in health: socio-demographic and spatial analysis of breast cancer in women from Córdoba, Argentina].

PubMed

Tumas, Natalia; Pou, Sonia Alejandra; Díaz, María Del Pilar

To identify sociodemographic determinants associated with the spatial distribution of the breast cancer incidence in the province of Córdoba, Argentina, in order to reveal underlying social inequities. An ecological study was developed in Córdoba (26 counties as geographical units of analysis). The spatial autocorrelation of the crude and standardised incidence rates of breast cancer, and the sociodemographic indicators of urbanization, fertility and population ageing were estimated using Moran's index. These variables were entered into a Geographic Information System for mapping. Poisson multilevel regression models were adjusted, establishing the breast cancer incidence rates as the response variable, and by selecting sociodemographic indicators as covariables and the percentage of households with unmet basic needs as adjustment variables. In Córdoba, Argentina, a non-random pattern in the spatial distribution of breast cancer incidence rates and in certain sociodemographic indicators was found. The mean increase in annual urban population was inversely associated with breast cancer, whereas the proportion of households with unmet basic needs was directly associated with this cancer. Our results define social inequity scenarios that partially explain the geographical differentials in the breast cancer burden in Córdoba, Argentina. Women residing in socioeconomically disadvantaged households and in less urbanized areas merit special attention in future studies and in breast cancer public health activities. Copyright © 2017 SESPAS. Publicado por Elsevier España, S.L.U. All rights reserved.

SDMtoolbox 2.0: the next generation Python-based GIS toolkit for landscape genetic, biogeographic and species distribution model analyses.

PubMed

Brown, Jason L; Bennett, Joseph R; French, Connor M

2017-01-01

SDMtoolbox 2.0 is a software package for spatial studies of ecology, evolution, and genetics. The release of SDMtoolbox 2.0 allows researchers to use the most current ArcGIS software and MaxEnt software, and reduces the amount of time that would be spent developing common solutions. The central aim of this software is to automate complicated and repetitive spatial analyses in an intuitive graphical user interface. One core tenant facilitates careful parameterization of species distribution models (SDMs) to maximize each model's discriminatory ability and minimize overfitting. This includes carefully processing of occurrence data, environmental data, and model parameterization. This program directly interfaces with MaxEnt, one of the most powerful and widely used species distribution modeling software programs, although SDMtoolbox 2.0 is not limited to species distribution modeling or restricted to modeling in MaxEnt. Many of the SDM pre- and post-processing tools have 'universal' analogs for use with any modeling software. The current version contains a total of 79 scripts that harness the power of ArcGIS for macroecology, landscape genetics, and evolutionary studies. For example, these tools allow for biodiversity quantification (such as species richness or corrected weighted endemism), generation of least-cost paths and corridors among shared haplotypes, assessment of the significance of spatial randomizations, and enforcement of dispersal limitations of SDMs projected into future climates-to only name a few functions contained in SDMtoolbox 2.0. Lastly, dozens of generalized tools exists for batch processing and conversion of GIS data types or formats, which are broadly useful to any ArcMap user.

Species distribution models predict temporal but not spatial variation in forest growth.

PubMed

van der Maaten, Ernst; Hamann, Andreas; van der Maaten-Theunissen, Marieke; Bergsma, Aldo; Hengeveld, Geerten; van Lammeren, Ron; Mohren, Frits; Nabuurs, Gert-Jan; Terhürne, Renske; Sterck, Frank

2017-04-01

Bioclimate envelope models have been widely used to illustrate the discrepancy between current species distributions and their potential habitat under climate change. However, the realism and correct interpretation of such projections has been the subject of considerable discussion. Here, we investigate whether climate suitability predictions correlate to tree growth, measured in permanent inventory plots and inferred from tree-ring records. We use the ensemble classifier RandomForest and species occurrence data from ~200,000 inventory plots to build species distribution models for four important European forestry species: Norway spruce, Scots pine, European beech, and pedunculate oak. We then correlate climate-based habitat suitability with volume measurements from ~50-year-old stands, available from ~11,000 inventory plots. Secondly, habitat projections based on annual historical climate are compared with ring width from ~300 tree-ring chronologies. Our working hypothesis is that habitat suitability projections from species distribution models should to some degree be associated with temporal or spatial variation in these growth records. We find that the habitat projections are uncorrelated with spatial growth records (inventory plot data), but they do predict interannual variation in tree-ring width, with an average correlation of .22. Correlation coefficients for individual chronologies range from values as high as .82 or as low as -.31. We conclude that tree responses to projected climate change are highly site-specific and that local suitability of a species for reforestation is difficult to predict. That said, projected increase or decrease in climatic suitability may be interpreted as an average expectation of increased or reduced growth over larger geographic scales.

Rationalizing spatial exploration patterns of wild animals and humans through a temporal discounting framework

PubMed Central

Namboodiri, Vijay Mohan K.; Levy, Joshua M.; Mihalas, Stefan; Sims, David W.; Hussain Shuler, Marshall G.

2016-01-01

Understanding the exploration patterns of foragers in the wild provides fundamental insight into animal behavior. Recent experimental evidence has demonstrated that path lengths (distances between consecutive turns) taken by foragers are well fitted by a power law distribution. Numerous theoretical contributions have posited that “Lévy random walks”—which can produce power law path length distributions—are optimal for memoryless agents searching a sparse reward landscape. It is unclear, however, whether such a strategy is efficient for cognitively complex agents, from wild animals to humans. Here, we developed a model to explain the emergence of apparent power law path length distributions in animals that can learn about their environments. In our model, the agent’s goal during search is to build an internal model of the distribution of rewards in space that takes into account the cost of time to reach distant locations (i.e., temporally discounting rewards). For an agent with such a goal, we find that an optimal model of exploration in fact produces hyperbolic path lengths, which are well approximated by power laws. We then provide support for our model by showing that humans in a laboratory spatial exploration task search space systematically and modify their search patterns under a cost of time. In addition, we find that path length distributions in a large dataset obtained from free-ranging marine vertebrates are well described by our hyperbolic model. Thus, we provide a general theoretical framework for understanding spatial exploration patterns of cognitively complex foragers. PMID:27385831

Effective pore-scale dispersion upscaling with a correlated continuous time random walk approach

NASA Astrophysics Data System (ADS)

Le Borgne, T.; Bolster, D.; Dentz, M.; de Anna, P.; Tartakovsky, A.

2011-12-01

We investigate the upscaling of dispersion from a pore-scale analysis of Lagrangian velocities. A key challenge in the upscaling procedure is to relate the temporal evolution of spreading to the pore-scale velocity field properties. We test the hypothesis that one can represent Lagrangian velocities at the pore scale as a Markov process in space. The resulting effective transport model is a continuous time random walk (CTRW) characterized by a correlated random time increment, here denoted as correlated CTRW. We consider a simplified sinusoidal wavy channel model as well as a more complex heterogeneous pore space. For both systems, the predictions of the correlated CTRW model, with parameters defined from the velocity field properties (both distribution and correlation), are found to be in good agreement with results from direct pore-scale simulations over preasymptotic and asymptotic times. In this framework, the nontrivial dependence of dispersion on the pore boundary fluctuations is shown to be related to the competition between distribution and correlation effects. In particular, explicit inclusion of spatial velocity correlation in the effective CTRW model is found to be important to represent incomplete mixing in the pore throats.

Spatial colonization of microbial cells on the rhizoplane.

NASA Astrophysics Data System (ADS)

Raynaud, Xavier; Eickhorst, Thilo; Nunan, Naoise; Kaiser, Christina; Woebken, Dagmar; Schmidt, Hannes

2017-04-01

The rhizoplane is the region where the root surface is in contact with soil and corresponds to the inner limit of the rhizosphere. At the rhizoplane level, plants exchange elements with the surrounding soil and the rhizoplane can therefore be considered as the region that drives nutrient movement and transformation in the rhizosphere. The rhizoplane differs in many respects from the bulk soil due to the far larger supply of substrates derived from the roots, with far greater microbial cell densities and reduced levels of diversity (Philippot et al., 2013). This is likely to result in completely different interaction profiles among microorganisms which may affect rhizosphere biogeochemistry. While the diversity of microorganisms associated with the rhizosphere and on the rhizoplane is getting increasing attention, knowledge on the spatial organisation of this diversity is still scarce. We therefore aimed at investigating the spatial arrangement of microbial rhizoplane colonization to increase our understanding of potential interaction dynamics within soil-microbe-plant interfaces. To study the spatial distribution of microbial cells on roots we cultivated rice plants in water-logged paddy soil. Root samples were taken three months after germination. After removing adhering rhizosphere soil the root samples were chemically fixed and prepared for CARD-FISH (Schmidt & Eickhorst, 2014). For hybridization, the oligonucleotide probes EUB I-III (Daims et al., 1999) were applied to cover the majority of bacteria colonizing the rhizoplane. Root segments were then subjected to confocal laser scanning microscopy where triplicate image stacks of 10 µm thickness (0.5 µm layer distance) were acquired per region of interest (ROI). ROIs were defined as distances from the root tip (0, 5, 10, 15 mm) and corresponded to the root tip, elongation zone, and zone of maturation. Image stacks were processed using ImageJ software to extract microbial cells spatial coordinates, as well as other features of the root (e.g. root cell walls). For all the images analysed, we found that microbial cell distributions were not distributed randomly and strongly associated to root cell walls. The spatial organization of root cell walls could be used to simulate microbial cell distribution that have similar spatial properties compared to the microscopic data. Root cell walls thus appear as a strong determinant for microbial cell colonization of the rhizoplane.

Assessing the spatial distribution of glyphosate-AMPA in an Argentinian farm field using a pedometric technique

NASA Astrophysics Data System (ADS)

Barbera, Agustin; Zamora, Martin; Domenech, Marisa; Vega-Becerra, Andres; Castro-Franco, Mauricio

2017-04-01

The cultivation of transgenic glyphosate-resistant crops has been the most rapidly adopted crop technology in Argentina since 1997. Thus, more than 180 million liters of the broad-spectrum herbicide glyphosate (N - phosphonomethylglicine) are applied every year. The intensive use of glyphosate combined with geomorphometrical characteristics of the Pampa region is a matter of environmental concern. An integral component of assessing the risk of soil contamination in farm fields is to describe the spatial distribution of the levels of contaminant agent. Application of pedometric techniques for this purpose has been scarcely demonstrated. These techniques could provide an estimate of the concentration at a given unsampled location, as well as the probability that concentration will exceed the critical threshold concentration. In this work, a pedometric technique for assessing the spatial distribution of glyphosate in farm fields was developed. A field located at INTA Barrow, Argentina (Lat: -38.322844, Lon: -60.25572) which has a great soil spatial variability, was divided by soil-specific zones using a pedometric technique. This was developed integrating INTA Soil Survey information and a digital elevation model (DEM) obtained from a DGPS. Firstly, 10 topographic indices derived from a DEM were computed in a Random Forest algorithm to obtain a classification model for soil map units (SMU). Secondly, a classification model was applied to those topographic indices but at a scale higher than 1:1000. Finally, a spatial principal component analysis and a clustering using Fuzzy K-means were used into each SMU. From this clustering, three soil-specific zones were determined which were also validated through apparent electrical conductivity (CEa) measurements. Three soil sample points were determined by zone. In each one, samples from 0-10, 10-20 and 20-40cm depth were taken. Glyphosate content and AMPA in each soil sample were analyzed using de UPLC-MS/MS ESI (+/-). Only AMPA at 10-20 cm depth had significant difference among soil-specific zones. However, marked trends for glyphosate content and AMPA were clearly shown among zones. These results suggest that (i) the presence of glyphosate and AMPA has spatial patterns distribution related to soil properties at field scale; and (ii) the proposed technique allowed to determine soil-specific zones related to the spatial distribution of glyphosate and AMPA fast, cost-effective and accurately. In further works, we would suggest adding new soil information sources to improve soil-specific zone delimitation.

NASA Radiation Track Image GUI for Assessing Space Radiation Biological Effects

NASA Technical Reports Server (NTRS)

Ponomarev, Artem L.; Cucinotta, Francis A.

2006-01-01

The high-charge high-energy (HZE) ion components of the galactic cosmic rays when compared to terrestrial forms of radiations present unique challenges to biological systems. In this paper we present a deoxyribonucleic acid (DNA) breakage model to visualize and analyze the impact of chromatin domains and DNA loops on clustering of DNA damage from X rays, protons, and HZE ions. Our model of DNA breakage is based on a stochastic process of DNA double-strand break (DSB) formulation that includes the amorphous model of the radiation track and a polymer model of DNA packed in the cell nucleus. Our model is a Monte-Carlo simulation based on a randomly located DSB cluster formulation that accomodates both high- and low-linear energy transfer radiations. We demonstrate that HZE ions have a strong impact on DSB clustering, both along the chromosome length and in the nucleus volume. The effects of chromosomal domains and DNA loops on the DSB fragment-size distribution and the spatial distribution of DSB in the nucleus were studied. We compare our model predictions with the spatial distribution of DSB obtained from experiments. The implications of our model predictions for radiation protection are discussed.

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

Masoumi, Ali; Vilenkin, Alexander; Yamada, Masaki, E-mail: ali@cosmos.phy.tufts.edu, E-mail: vilenkin@cosmos.phy.tufts.edu, E-mail: Masaki.Yamada@tufts.edu

In the landscape perspective, our Universe begins with a quantum tunneling from an eternally-inflating parent vacuum, followed by a period of slow-roll inflation. We investigate the tunneling process and calculate the probability distribution for the initial conditions and for the number of e-folds of slow-roll inflation, modeling the landscape by a small-field one-dimensional random Gaussian potential. We find that such a landscape is fully consistent with observations, but the probability for future detection of spatial curvature is rather low, P ∼ 10{sup −3}.

Safety assessment of a shallow foundation using the random finite element method

NASA Astrophysics Data System (ADS)

Zaskórski, Łukasz; Puła, Wojciech

2015-04-01

A complex structure of soil and its random character are reasons why soil modeling is a cumbersome task. Heterogeneity of soil has to be considered even within a homogenous layer of soil. Therefore an estimation of shear strength parameters of soil for the purposes of a geotechnical analysis causes many problems. In applicable standards (Eurocode 7) there is not presented any explicit method of an evaluation of characteristic values of soil parameters. Only general guidelines can be found how these values should be estimated. Hence many approaches of an assessment of characteristic values of soil parameters are presented in literature and can be applied in practice. In this paper, the reliability assessment of a shallow strip footing was conducted using a reliability index β. Therefore some approaches of an estimation of characteristic values of soil properties were compared by evaluating values of reliability index β which can be achieved by applying each of them. Method of Orr and Breysse, Duncan's method, Schneider's method, Schneider's method concerning influence of fluctuation scales and method included in Eurocode 7 were examined. Design values of the bearing capacity based on these approaches were referred to the stochastic bearing capacity estimated by the random finite element method (RFEM). Design values of the bearing capacity were conducted for various widths and depths of a foundation in conjunction with design approaches DA defined in Eurocode. RFEM was presented by Griffiths and Fenton (1993). It combines deterministic finite element method, random field theory and Monte Carlo simulations. Random field theory allows to consider a random character of soil parameters within a homogenous layer of soil. For this purpose a soil property is considered as a separate random variable in every element of a mesh in the finite element method with proper correlation structure between points of given area. RFEM was applied to estimate which theoretical probability distribution fits the empirical probability distribution of bearing capacity basing on 3000 realizations. Assessed probability distribution was applied to compute design values of the bearing capacity and related reliability indices β. Conducted analysis were carried out for a cohesion soil. Hence a friction angle and a cohesion were defined as a random parameters and characterized by two dimensional random fields. A friction angle was described by a bounded distribution as it differs within limited range. While a lognormal distribution was applied in case of a cohesion. Other properties - Young's modulus, Poisson's ratio and unit weight were assumed as deterministic values because they have negligible influence on the stochastic bearing capacity. Griffiths D. V., & Fenton G. A. (1993). Seepage beneath water retaining structures founded on spatially random soil. Géotechnique, 43(6), 577-587.

Optimizing random searches on three-dimensional lattices

NASA Astrophysics Data System (ADS)

Yang, Benhao; Yang, Shunkun; Zhang, Jiaquan; Li, Daqing

2018-07-01

Search is a universal behavior related to many types of intelligent individuals. While most studies have focused on search in two or infinite-dimensional space, it is still missing how search can be optimized in three-dimensional space. Here we study random searches on three-dimensional (3d) square lattices with periodic boundary conditions, and explore the optimal search strategy with a power-law step length distribution, p(l) ∼l-μ, known as Lévy flights. We find that compared to random searches on two-dimensional (2d) lattices, the optimal exponent μopt on 3d lattices is relatively smaller in non-destructive case and remains similar in destructive case. We also find μopt decreases as the lattice length in z direction increases under high target density. Our findings may help us to understand the role of spatial dimension in search behaviors.

Geographic analysis of vaccine uptake in a cluster-randomized controlled trial in Hue, Vietnam.

PubMed

Ali, Mohammad; Thiem, Vu Dinh; Park, Jin-Kyung; Ochiai, Rion Leon; Canh, Do Gia; Danovaro-Holliday, M Carolina; Kaljee, Linda M; Clemens, John D; Acosta, Camilo J

2007-09-01

This paper identifies spatial patterns and predictors of vaccine uptake in a cluster-randomized controlled trial in Hue, Vietnam. Data for this study result from the integration of demographic surveillance, vaccine record, and geographic data of the study area. A multi-level cross-classified (non-hierarchical) model was used for analyzing the non-nested nature of individual's ecological data. Vaccine uptake was unevenly distributed in space and there was spatial variability among predictors of vaccine uptake. Vaccine uptake was higher among students with younger, male, or not literate family heads. Students from households with higher per-capita income were less likely to participate in the trial. Residency south of the river or further from a hospital/polyclinic was associated with higher vaccine uptake. Younger students were more likely to be vaccinated than older students in high- or low-risk areas, but not in the entire study area. The findings are important for the management of vaccine campaigns during a trial and for interpretation of disease patterns during vaccine-efficacy evaluation.

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.

A quasi-static model of global atmospheric electricity. I - The lower atmosphere

NASA Technical Reports Server (NTRS)

Hays, P. B.; Roble, R. G.

1979-01-01

A quasi-steady model of global lower atmospheric electricity is presented. The model considers thunderstorms as dipole electric generators that can be randomly distributed in various regions and that are the only source of atmospheric electricity and includes the effects of orography and electrical coupling along geomagnetic field lines in the ionosphere and magnetosphere. The model is used to calculate the global distribution of electric potential and current for model conductivities and assumed spatial distributions of thunderstorms. Results indicate that large positive electric potentials are generated over thunderstorms and penetrate to ionospheric heights and into the conjugate hemisphere along magnetic field lines. The perturbation of the calculated electric potential and current distributions during solar flares and subsequent Forbush decreases is discussed, and future measurements of atmospheric electrical parameters and modifications of the model which would improve the agreement between calculations and measurements are suggested.

A Bayesian Framework of Uncertainties Integration in 3D Geological Model

NASA Astrophysics Data System (ADS)

Liang, D.; Liu, X.

2017-12-01

3D geological model can describe complicated geological phenomena in an intuitive way while its application may be limited by uncertain factors. Great progress has been made over the years, lots of studies decompose the uncertainties of geological model to analyze separately, while ignored the comprehensive impacts of multi-source uncertainties. Great progress has been made over the years, while lots of studies ignored the comprehensive impacts of multi-source uncertainties when analyzed them item by item from each source. To evaluate the synthetical uncertainty, we choose probability distribution to quantify uncertainty, and propose a bayesian framework of uncertainties integration. With this framework, we integrated data errors, spatial randomness, and cognitive information into posterior distribution to evaluate synthetical uncertainty of geological model. Uncertainties propagate and cumulate in modeling process, the gradual integration of multi-source uncertainty is a kind of simulation of the uncertainty propagation. Bayesian inference accomplishes uncertainty updating in modeling process. Maximum entropy principle makes a good effect on estimating prior probability distribution, which ensures the prior probability distribution subjecting to constraints supplied by the given information with minimum prejudice. In the end, we obtained a posterior distribution to evaluate synthetical uncertainty of geological model. This posterior distribution represents the synthetical impact of all the uncertain factors on the spatial structure of geological model. The framework provides a solution to evaluate synthetical impact on geological model of multi-source uncertainties and a thought to study uncertainty propagation mechanism in geological modeling.

Socio-ecological factors and hand, foot and mouth disease in dry climate regions: a Bayesian spatial approach in Gansu, China

NASA Astrophysics Data System (ADS)

Gou, Faxiang; Liu, Xinfeng; Ren, Xiaowei; Liu, Dongpeng; Liu, Haixia; Wei, Kongfu; Yang, Xiaoting; Cheng, Yao; Zheng, Yunhe; Jiang, Xiaojuan; Li, Juansheng; Meng, Lei; Hu, Wenbiao

2017-01-01

The influence of socio-ecological factors on hand, foot and mouth disease (HFMD) were explored in this study using Bayesian spatial modeling and spatial patterns identified in dry regions of Gansu, China. Notified HFMD cases and socio-ecological data were obtained from the China Information System for Disease Control and Prevention, Gansu Yearbook and Gansu Meteorological Bureau. A Bayesian spatial conditional autoregressive model was used to quantify the effects of socio-ecological factors on the HFMD and explore spatial patterns, with the consideration of its socio-ecological effects. Our non-spatial model suggests temperature (relative risk (RR) 1.15, 95 % CI 1.01-1.31), GDP per capita (RR 1.19, 95 % CI 1.01-1.39) and population density (RR 1.98, 95 % CI 1.19-3.17) to have a significant effect on HFMD transmission. However, after controlling for spatial random effects, only temperature (RR 1.25, 95 % CI 1.04-1.53) showed significant association with HFMD. The spatial model demonstrates temperature to play a major role in the transmission of HFMD in dry regions. Estimated residual variation after taking into account the socio-ecological variables indicated that high incidences of HFMD were mainly clustered in the northwest of Gansu. And, spatial structure showed a unique distribution after taking account of socio-ecological effects.

Keys and seats: Spatial response coding underlying the joint spatial compatibility effect.

PubMed

Dittrich, Kerstin; Dolk, Thomas; Rothe-Wulf, Annelie; Klauer, Karl Christoph; Prinz, Wolfgang

2013-11-01

Spatial compatibility effects (SCEs) are typically observed when participants have to execute spatially defined responses to nonspatial stimulus features (e.g., the color red or green) that randomly appear to the left and the right. Whereas a spatial correspondence of stimulus and response features facilitates response execution, a noncorrespondence impairs task performance. Interestingly, the SCE is drastically reduced when a single participant responds to one stimulus feature (e.g., green) by operating only one response key (individual go/no-go task), whereas a full-blown SCE is observed when the task is distributed between two participants (joint go/no-go task). This joint SCE (a.k.a. the social Simon effect) has previously been explained by action/task co-representation, whereas alternative accounts ascribe joint SCEs to spatial components inherent in joint go/no-go tasks that allow participants to code their responses spatially. Although increasing evidence supports the idea that spatial rather than social aspects are responsible for joint SCEs emerging, it is still unclear to which component(s) the spatial coding refers to: the spatial orientation of response keys, the spatial orientation of responding agents, or both. By varying the spatial orientation of the responding agents (Exp. 1) and of the response keys (Exp. 2), independent of the spatial orientation of the stimuli, in the present study we found joint SCEs only when both the seating and the response key alignment matched the stimulus alignment. These results provide evidence that spatial response coding refers not only to the response key arrangement, but also to the-often neglected-spatial orientation of the responding agents.

Physically Unclonable Cryptographic Primitives by Chemical Vapor Deposition of Layered MoS2.

PubMed

Alharbi, Abdullah; Armstrong, Darren; Alharbi, Somayah; Shahrjerdi, Davood

2017-12-26

Physically unclonable cryptographic primitives are promising for securing the rapidly growing number of electronic devices. Here, we introduce physically unclonable primitives from layered molybdenum disulfide (MoS 2 ) by leveraging the natural randomness of their island growth during chemical vapor deposition (CVD). We synthesize a MoS 2 monolayer film covered with speckles of multilayer islands, where the growth process is engineered for an optimal speckle density. Using the Clark-Evans test, we confirm that the distribution of islands on the film exhibits complete spatial randomness, hence indicating the growth of multilayer speckles is a spatial Poisson process. Such a property is highly desirable for constructing unpredictable cryptographic primitives. The security primitive is an array of 2048 pixels fabricated from this film. The complex structure of the pixels makes the physical duplication of the array impossible (i.e., physically unclonable). A unique optical response is generated by applying an optical stimulus to the structure. The basis for this unique response is the dependence of the photoemission on the number of MoS 2 layers, which by design is random throughout the film. Using a threshold value for the photoemission, we convert the optical response into binary cryptographic keys. We show that the proper selection of this threshold is crucial for maximizing combination randomness and that the optimal value of the threshold is linked directly to the growth process. This study reveals an opportunity for generating robust and versatile security primitives from layered transition metal dichalcogenides.

Optimizing placements of ground-based snow sensors for areal snow cover estimation using a machine-learning algorithm and melt-season snow-LiDAR data

NASA Astrophysics Data System (ADS)

Oroza, C.; Zheng, Z.; Glaser, S. D.; Bales, R. C.; Conklin, M. H.

2016-12-01

We present a structured, analytical approach to optimize ground-sensor placements based on time-series remotely sensed (LiDAR) data and machine-learning algorithms. We focused on catchments within the Merced and Tuolumne river basins, covered by the JPL Airborne Snow Observatory LiDAR program. First, we used a Gaussian mixture model to identify representative sensor locations in the space of independent variables for each catchment. Multiple independent variables that govern the distribution of snow depth were used, including elevation, slope, and aspect. Second, we used a Gaussian process to estimate the areal distribution of snow depth from the initial set of measurements. This is a covariance-based model that also estimates the areal distribution of model uncertainty based on the independent variable weights and autocorrelation. The uncertainty raster was used to strategically add sensors to minimize model uncertainty. We assessed the temporal accuracy of the method using LiDAR-derived snow-depth rasters collected in water-year 2014. In each area, optimal sensor placements were determined using the first available snow raster for the year. The accuracy in the remaining LiDAR surveys was compared to 100 configurations of sensors selected at random. We found the accuracy of the model from the proposed placements to be higher and more consistent in each remaining survey than the average random configuration. We found that a relatively small number of sensors can be used to accurately reproduce the spatial patterns of snow depth across the basins, when placed using spatial snow data. Our approach also simplifies sensor placement. At present, field surveys are required to identify representative locations for such networks, a process that is labor intensive and provides limited guarantees on the networks' representation of catchment independent variables.

Urban nuisance flooding and topographic wetness index: does excess runoff collect where we think it should in urban landscapes?

NASA Astrophysics Data System (ADS)

Kelleher, C.; McPhillips, L. E.

2017-12-01

Urban landscapes translate water in a variety of ways that diverge from more natural systems. In particular, due to the presence of impervious surfaces and alteration of topography, they are prone to nuisance flooding when it rains. To track the locations of areas of minor flooding and other complaints, many cities are now facilitating nuisance reports from residents via information technology services like 311. These reports provide useful information for tracking where in the landscape water may collect during rain events; we sought to use this information to test potential geospatial indices for predictively identifying locations prone to nuisance flooding in urban areas. In this study, we utilized a tool commonly applied in natural systems, topographic indices, to create spatially contiguous estimates of topographic wetness index (TWI), a value that can be used to identify areas within a watershed expected to be preferentially wetter or drier based on topographic slope and surface flow pathways. For several watersheds across Baltimore and New York City (USA), we tested three different resolutions of LiDAR-derived topography and two different methods of flow routing to calculate continuous distributions of TWI. When comparing these values to nuisance flooding locations, we found that distributions of TWI values within a radius of reported nuisance floods were higher, on average, than the distribution of TWI values across each watershed. We also employed a spatial Monte Carlo sampling strategy, randomly selecting grid cells within each watershed to determine if these randomly selected grid cells have preferentially lower TWI values than those near nuisance flooding locations. Overall, we demonstrate that topographic indices may be useful predictors of localized flooding within urban environments.

A random spatial network model based on elementary postulates

USGS Publications Warehouse

Karlinger, Michael R.; Troutman, Brent M.

1989-01-01

A model for generating random spatial networks that is based on elementary postulates comparable to those of the random topology model is proposed. In contrast to the random topology model, this model ascribes a unique spatial specification to generated drainage networks, a distinguishing property of some network growth models. The simplicity of the postulates creates an opportunity for potential analytic investigations of the probabilistic structure of the drainage networks, while the spatial specification enables analyses of spatially dependent network properties. In the random topology model all drainage networks, conditioned on magnitude (number of first-order streams), are equally likely, whereas in this model all spanning trees of a grid, conditioned on area and drainage density, are equally likely. As a result, link lengths in the generated networks are not independent, as usually assumed in the random topology model. For a preliminary model evaluation, scale-dependent network characteristics, such as geometric diameter and link length properties, and topologic characteristics, such as bifurcation ratio, are computed for sets of drainage networks generated on square and rectangular grids. Statistics of the bifurcation and length ratios fall within the range of values reported for natural drainage networks, but geometric diameters tend to be relatively longer than those for natural networks.

Modeling pluvial flooding damage in urban environments: spatial relationships between citizens' complaints and overland catchment areas

NASA Astrophysics Data System (ADS)

Gaitan, Santiago; ten Veldhuis, Marie-Claire; van de Giesen, Nick

2013-04-01

Extreme weather events such as floods and storms are expected to cause severe economic losses in The Netherlands. Cumulative damage due to pluvial flooding can be considerable, especially in lowland areas where this type of floods occurs relatively frequently. Currently, in The Netherlands, water-related damages to property and contents are covered through private insurance. As pluvial flooding is becoming heavier and more likely to occur, sound modelling of damages is required to ensure that insurance systems are able to stand as an adaptation measure. Current damage models based on rainfall intensity, registries of insurance claims, and classifications of building types are unable to fully explain damage variability. Further developments assessing additional explanatory factors and reducing uncertainties, are required in order to significantly explain damage. In this study, urban topography is used as an explanatory factor for modelling of urban pluvial flooding. Flood damage is evaluated based on complaints data, a valuable resource for assessing vulnerability to urban pluvial flooding. Though previous research has shown coincidences between the localization of high complaint counts and large size catchments areas in Rotterdam, additional research is needed to establish the precise spatial relationship of those two variables. This additional task is the focus of the presented work. To that end a data base of complaints, that was made available by the Municipality Administration of the City, will be analysed. It comprises close to 36800 complaints from 2004 to 2011. The geographical position of the registries is aggregated into 4 to 6-digit Postal Code zones, which represents entire streets or relative positions along a street, respectively. The Municipality also provided the DEM, characterized by a spatial resolution of 0.5 m × 0.5 m, a vertical precision of 5 cm, and an accuracy better than two standard deviations of 15 cm. First the localization of complaints will be tested for spatial randomness: the distribution of Global Moran's I will be used as a measure of spatial aggregation of complaints. We expect high values of spatial aggregation, that would confirm the existence of a spatial structure in the distribution of complaints. Then we will probe how much does the extent of catchment areas influence such distribution of complaints. That will be done through both an ordinary least squares regression and a geographically weighted regression. By contrasting the results from these two regressions, the relationship between complaints and size of catchment area across the urban environment will be evaluated. The results will confirm whether complaints have a spatial distribution pattern. Furthermore, the results will provide insight into the importance of the size of catchment areas as a significant factor for complaints distribution, and for the assessment of urban vulnerability to pluvial flooding in the City of Rotterdam.

Automated delineation and characterization of drumlins using a localized contour tree approach

NASA Astrophysics Data System (ADS)

Wang, Shujie; Wu, Qiusheng; Ward, Dylan

2017-10-01

Drumlins are ubiquitous landforms in previously glaciated regions, formed through a series of complex subglacial processes operating underneath the paleo-ice sheets. Accurate delineation and characterization of drumlins are essential for understanding the formation mechanism of drumlins as well as the flow behaviors and basal conditions of paleo-ice sheets. Automated mapping of drumlins is particularly important for examining the distribution patterns of drumlins across large spatial scales. This paper presents an automated vector-based approach to mapping drumlins from high-resolution light detection and ranging (LiDAR) data. The rationale is to extract a set of concentric contours by building localized contour trees and establishing topological relationships. This automated method can overcome the shortcomings of previously manual and automated methods for mapping drumlins, for instance, the azimuthal biases during the generation of shaded relief images. A case study was carried out over a portion of the New York Drumlin Field. Overall 1181 drumlins were identified from the LiDAR-derived DEM across the study region, which had been underestimated in previous literature. The delineation results were visually and statistically compared to the manual digitization results. The morphology of drumlins was characterized by quantifying the length, width, elongation ratio, height, area, and volume. Statistical and spatial analyses were conducted to examine the distribution pattern and spatial variability of drumlin size and form. The drumlins and the morphologic characteristics exhibit significant spatial clustering rather than randomly distributed patterns. The form of drumlins varies from ovoid to spindle shapes towards the downstream direction of paleo ice flows, along with the decrease in width, area, and volume. This observation is in line with previous studies, which may be explained by the variations in sediment thickness and/or the velocity increases of ice flows towards ice front.

Environmental drivers of spatial patterns of topsoil nitrogen and phosphorus under monsoon conditions in a complex terrain of South Korea

PubMed Central

Choi, Kwanghun; Spohn, Marie; Park, Soo Jin; Huwe, Bernd; Ließ, Mareike

2017-01-01

Nitrogen (N) and phosphorus (P) in topsoils are critical for plant nutrition. Relatively little is known about the spatial patterns of N and P in the organic layer of mountainous landscapes. Therefore, the spatial distributions of N and P in both the organic layer and the A horizon were analyzed using a light detection and ranging (LiDAR) digital elevation model and vegetation metrics. The objective of the study was to analyze the effect of vegetation and topography on the spatial patterns of N and P in a small watershed covered by forest in South Korea. Soil samples were collected using the conditioned latin hypercube method. LiDAR vegetation metrics, the normalized difference vegetation index (NDVI), and terrain parameters were derived as predictors. Spatial explicit predictions of N/P ratios were obtained using a random forest with uncertainty analysis. We tested different strategies of model validation (repeated 2-fold to 20-fold and leave-one-out cross validation). Repeated 10-fold cross validation was selected for model validation due to the comparatively high accuracy and low variance of prediction. Surface curvature was the best predictor of P contents in the organic layer and in the A horizon, while LiDAR vegetation metrics and NDVI were important predictors of N in the organic layer. N/P ratios increased with surface curvature and were higher on the convex upper slope than on the concave lower slope. This was due to P enrichment of the soil on the lower slope and a more even spatial distribution of N. Our digital soil maps showed that the topsoils on the upper slopes contained relatively little P. These findings are critical for understanding N and P dynamics in mountainous ecosystems. PMID:28837590

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.

Genetic Variability and Distribution of Mating Type Alleles in Field Populations of Leptosphaeria maculans from France

PubMed Central

Gout, Lilian; Eckert, Maria; Rouxel, Thierry; Balesdent, Marie-Hélène

2006-01-01

Leptosphaeria maculans is the most ubiquitous fungal pathogen of Brassica crops and causes the devastating stem canker disease of oilseed rape worldwide. We used minisatellite markers to determine the genetic structure of L. maculans in four field populations from France. Isolates were collected at three different spatial scales (leaf, 2-m2 field plot, and field) enabling the evaluation of spatial distribution of the mating type alleles and of genetic variability within and among field populations. Within each field population, no gametic disequilibrium between the minisatellite loci was detected and the mating type alleles were present at equal frequencies. Both sexual and asexual reproduction occur in the field, but the genetic structure of these populations is consistent with annual cycles of randomly mating sexual reproduction. All L. maculans field populations had a high level of gene diversity (H = 0.68 to 0.75) and genotypic diversity. Within each field population, the number of genotypes often was very close to the number of isolates. Analysis of molecular variance indicated that >99.5% of the total genetic variability was distributed at a small spatial scale, i.e., within 2-m2 field plots. Population differentiation among the four field populations was low (GST < 0.02), suggesting a high degree of gene exchange between these populations. The high gene flow evidenced here in French populations of L. maculans suggests a rapid countrywide diffusion of novel virulence alleles whenever novel resistance sources are used. PMID:16391041

The influence of rough surface thermal-infrared beaming on the Yarkovsky and YORP effects

NASA Astrophysics Data System (ADS)

Rozitis, B.; Green, S. F.

2012-06-01

It is now becoming widely accepted that photon recoil forces from the asymmetric reflection and thermal re-radiation of absorbed sunlight are, together with collisions and gravitational forces, primary mechanisms governing the dynamical and physical evolution of asteroids. The Yarkovsky effect causes orbital semimajor axis drift, and the Yarkovsky-O'Keefe-Radzievskii-Paddack (YORP) effect causes changes in the rotation rate and pole orientation. We present an adaptation of the Advanced Thermophysical Model to simultaneously predict the Yarkovsky and YORP effects in the presence of thermal-infrared beaming caused by surface roughness, which has been neglected or dismissed in all previous models. Tests on Gaussian random sphere shaped asteroids, and on the real shapes of asteroids (1620) Geographos and (6489) Golevka, show that rough surface thermal-infrared beaming enhances the Yarkovsky orbital drift by typically tens of per cent but it can be as much as a factor of 2. The YORP rotational acceleration is on average dampened by up to a third typically but can be as much as one-half. We find that the Yarkovsky orbital drift is only sensitive to the average degree, and not to the spatial distribution, of roughness across an asteroid surface. However, the YORP rotational acceleration is sensitive to the surface roughness spatial distribution, and can add significant uncertainties to the predictions for asteroids with relatively weak YORP effects. To accurately predict either effect the degree and spatial distribution of roughness across an asteroid surface must be known.

Generalized Bootstrap Method for Assessment of Uncertainty in Semivariogram Inference

USGS Publications Warehouse

Olea, R.A.; Pardo-Iguzquiza, E.

2011-01-01

The semivariogram and its related function, the covariance, play a central role in classical geostatistics for modeling the average continuity of spatially correlated attributes. Whereas all methods are formulated in terms of the true semivariogram, in practice what can be used are estimated semivariograms and models based on samples. A generalized form of the bootstrap method to properly model spatially correlated data is used to advance knowledge about the reliability of empirical semivariograms and semivariogram models based on a single sample. Among several methods available to generate spatially correlated resamples, we selected a method based on the LU decomposition and used several examples to illustrate the approach. The first one is a synthetic, isotropic, exhaustive sample following a normal distribution, the second example is also a synthetic but following a non-Gaussian random field, and a third empirical sample consists of actual raingauge measurements. Results show wider confidence intervals than those found previously by others with inadequate application of the bootstrap. Also, even for the Gaussian example, distributions for estimated semivariogram values and model parameters are positively skewed. In this sense, bootstrap percentile confidence intervals, which are not centered around the empirical semivariogram and do not require distributional assumptions for its construction, provide an achieved coverage similar to the nominal coverage. The latter cannot be achieved by symmetrical confidence intervals based on the standard error, regardless if the standard error is estimated from a parametric equation or from bootstrap. ?? 2010 International Association for Mathematical Geosciences.

Damage spreading in spatial and small-world random Boolean networks

NASA Astrophysics Data System (ADS)

Lu, Qiming; Teuscher, Christof

2014-02-01

The study of the response of complex dynamical social, biological, or technological networks to external perturbations has numerous applications. Random Boolean networks (RBNs) are commonly used as a simple generic model for certain dynamics of complex systems. Traditionally, RBNs are interconnected randomly and without considering any spatial extension and arrangement of the links and nodes. However, most real-world networks are spatially extended and arranged with regular, power-law, small-world, or other nonrandom connections. Here we explore the RBN network topology between extreme local connections, random small-world, and pure random networks, and study the damage spreading with small perturbations. We find that spatially local connections change the scaling of the Hamming distance at very low connectivities (K¯≪1) and that the critical connectivity of stability Ks changes compared to random networks. At higher K¯, this scaling remains unchanged. We also show that the Hamming distance of spatially local networks scales with a power law as the system size N increases, but with a different exponent for local and small-world networks. The scaling arguments for small-world networks are obtained with respect to the system sizes and strength of spatially local connections. We further investigate the wiring cost of the networks. From an engineering perspective, our new findings provide the key design trade-offs between damage spreading (robustness), the network's wiring cost, and the network's communication characteristics.

Recurrent patterning in the daily foraging routes of hamadryas baboons (Papio hamadryas): spatial memory in large-scale versus small-scale space.

PubMed

Schreier, Amy L; Grove, Matt

2014-05-01

The benefits of spatial memory for foraging animals can be assessed on two distinct spatial scales: small-scale space (travel within patches) and large-scale space (travel between patches). While the patches themselves may be distributed at low density, within patches resources are likely densely distributed. We propose, therefore, that spatial memory for recalling the particular locations of previously visited feeding sites will be more advantageous during between-patch movement, where it may reduce the distances traveled by animals that possess this ability compared to those that must rely on random search. We address this hypothesis by employing descriptive statistics and spectral analyses to characterize the daily foraging routes of a band of wild hamadryas baboons in Filoha, Ethiopia. The baboons slept on two main cliffs--the Filoha cliff and the Wasaro cliff--and daily travel began and ended on a cliff; thus four daily travel routes exist: Filoha-Filoha, Filoha-Wasaro, Wasaro-Wasaro, Wasaro-Filoha. We use newly developed partial sum methods and distribution-fitting analyses to distinguish periods of area-restricted search from more extensive movements. The results indicate a single peak in travel activity in the Filoha-Filoha and Wasaro-Filoha routes, three peaks of travel activity in the Filoha-Wasaro routes, and two peaks in the Wasaro-Wasaro routes; and are consistent with on-the-ground observations of foraging and ranging behavior of the baboons. In each of the four daily travel routes the "tipping points" identified by the partial sum analyses indicate transitions between travel in small- versus large-scale space. The correspondence between the quantitative analyses and the field observations suggest great utility for using these types of analyses to examine primate travel patterns and especially in distinguishing between movement in small versus large-scale space. Only the distribution-fitting analyses are inconsistent with the field observations, which may be due to the scale at which these analyses were conducted. © 2013 Wiley Periodicals, Inc.

Spatial analyses for nonoverlapping objects with size variations and their application to coral communities.

PubMed

Muko, Soyoka; Shimatani, Ichiro K; Nozawa, Yoko

2014-07-01

Spatial distributions of individuals are conventionally analysed by representing objects as dimensionless points, in which spatial statistics are based on centre-to-centre distances. However, if organisms expand without overlapping and show size variations, such as is the case for encrusting corals, interobject spacing is crucial for spatial associations where interactions occur. We introduced new pairwise statistics using minimum distances between objects and demonstrated their utility when examining encrusting coral community data. We also calculated the conventional point process statistics and the grid-based statistics to clarify the advantages and limitations of each spatial statistical method. For simplicity, coral colonies were approximated by disks in these demonstrations. Focusing on short-distance effects, the use of minimum distances revealed that almost all coral genera were aggregated at a scale of 1-25 cm. However, when fragmented colonies (ramets) were treated as a genet, a genet-level analysis indicated weak or no aggregation, suggesting that most corals were randomly distributed and that fragmentation was the primary cause of colony aggregations. In contrast, point process statistics showed larger aggregation scales, presumably because centre-to-centre distances included both intercolony spacing and colony sizes (radius). The grid-based statistics were able to quantify the patch (aggregation) scale of colonies, but the scale was strongly affected by the colony size. Our approach quantitatively showed repulsive effects between an aggressive genus and a competitively weak genus, while the grid-based statistics (covariance function) also showed repulsion although the spatial scale indicated from the statistics was not directly interpretable in terms of ecological meaning. The use of minimum distances together with previously proposed spatial statistics helped us to extend our understanding of the spatial patterns of nonoverlapping objects that vary in size and the associated specific scales. © 2013 The Authors. Journal of Animal Ecology © 2013 British Ecological Society.

Spatial phylogenetics of the native California flora.

PubMed

Thornhill, Andrew H; Baldwin, Bruce G; Freyman, William A; Nosratinia, Sonia; Kling, Matthew M; Morueta-Holme, Naia; Madsen, Thomas P; Ackerly, David D; Mishler, Brent D

2017-10-26

California is a world floristic biodiversity hotspot where the terms neo- and paleo-endemism were first applied. Using spatial phylogenetics, it is now possible to evaluate biodiversity from an evolutionary standpoint, including discovering significant areas of neo- and paleo-endemism, by combining spatial information from museum collections and DNA-based phylogenies. Here we used a distributional dataset of 1.39 million herbarium specimens, a phylogeny of 1083 operational taxonomic units (OTUs) and 9 genes, and a spatial randomization test to identify regions of significant phylogenetic diversity, relative phylogenetic diversity, and phylogenetic endemism (PE), as well as to conduct a categorical analysis of neo- and paleo-endemism (CANAPE). We found (1) extensive phylogenetic clustering in the South Coast Ranges, southern Great Valley, and deserts of California; (2) significant concentrations of short branches in the Mojave and Great Basin Deserts and the South Coast Ranges and long branches in the northern Great Valley, Sierra Nevada foothills, and the northwestern and southwestern parts of the state; (3) significant concentrations of paleo-endemism in Northwestern California, the northern Great Valley, and western Sonoran Desert, and neo-endemism in the White-Inyo Range, northern Mojave Desert, and southern Channel Islands. Multiple analyses were run to observe the effects on significance patterns of using different phylogenetic tree topologies (uncalibrated trees versus time-calibrated ultrametric trees) and using different representations of OTU ranges (herbarium specimen locations versus species distribution models). These analyses showed that examining the geographic distributions of branch lengths in a statistical framework adds a new dimension to California floristics that, in comparison with climatic data, helps to illuminate causes of endemism. In particular, the concentration of significant PE in more arid regions of California extends previous ideas about aridity as an evolutionary stimulus. The patterns seen are largely robust to phylogenetic uncertainty and time calibration but are sensitive to the use of occurrence data versus modeled ranges, indicating that special attention toward improving geographic distributional data should be top priority in the future for advancing understanding of spatial patterns of biodiversity.

Analysis of cardiac signals using spatial filling index and time-frequency domain

PubMed Central

Faust, Oliver; Acharya U, Rajendra; Krishnan, SM; Min, Lim Choo

2004-01-01

Background Analysis of heart rate variation (HRV) has become a popular noninvasive tool for assessing the activities of the autonomic nervous system (ANS). HRV analysis is based on the concept that fast fluctuations may specifically reflect changes of sympathetic and vagal activity. It shows that the structure generating the signal is not simply linear, but also involves nonlinear contributions. These signals are essentially non-stationary; may contain indicators of current disease, or even warnings about impending diseases. The indicators may be present at all times or may occur at random in the time scale. However, to study and pinpoint abnormalities in voluminous data collected over several hours is strenuous and time consuming. Methods This paper presents the spatial filling index and time-frequency analysis of heart rate variability signal for disease identification. Renyi's entropy is evaluated for the signal in the Wigner-Ville and Continuous Wavelet Transformation (CWT) domain. Results This Renyi's entropy gives lower 'p' value for scalogram than Wigner-Ville distribution and also, the contours of scalogram visually show the features of the diseases. And in the time-frequency analysis, the Renyi's entropy gives better result for scalogram than the Wigner-Ville distribution. Conclusion Spatial filling index and Renyi's entropy has distinct regions for various diseases with an accuracy of more than 95%. PMID:15361254

Upscaling mixing in porous media from an experimental quantification of pore scale Lagrangian deformation statistics

NASA Astrophysics Data System (ADS)

Turuban, R.; Jimenez-Martinez, J.; De Anna, P.; Tabuteau, H.; Meheust, Y.; Le Borgne, T.

2014-12-01

As dissolved chemical elements are transported in the subsurface, their mixing with other compounds and potential reactivity depends on the creation of local scale chemical gradients, which ultimately drive diffusive mass transfer and reaction. The distribution of concentration gradients is in turn shaped by the spatial gradients of flow velocity arising from the random distribution of solid grains. We present an experimental investigation of the relationship between the microscale flow stretching properties and the effective large scale mixing dynamics in porous media. We use a flow cell that models a horizontal quasi two-dimensional (2D) porous medium, the grains of which are cylinders randomly positioned between two glass plates [de Anna et al. 2013]. In this setup, we perform both non diffusive and diffusive transport tests, by injecting respectively microsphere solid tracers and a fluorescent dye. While the dye front propagates through the medium, it undergoes in time a kinematic stretching that is controlled by the flow heterogeneity, as it encounters stagnation zones and high velocity channels between the grains. The spatial distribution of the dye can then be described as a set of stretched lamellae whose rate of diffusive smoothing is locally enhanced by kinematic stretching [Le Borgne et al., 2013]. We show that this representation allows predicting the temporal evolution of the mixing rate and the probability distribution of concentration gradients for a range of Peclet numbers. This upscaling framework hence provides a quantification of the dynamics of effective mixing from the microscale Lagrangian velocity statistics. References:[1] P. de Anna, J. Jimenez-Martinez, H. Tabuteau, R. Turuban, T. Le Borgne, M. Derrien,and Yves Méheust, Mixing and reaction kinetics in porous media : an experimental pore scale quantification, Environ. Sci. Technol. 48, 508-516, 2014. [2] Le Borgne, T., M. Dentz, E. Villermaux, Stretching, coalescence and mixing in porous media, Phys. Rev. Lett., 110, 204501 (2013)

National Mosquito (Diptera: Culicidae) Survey in The Netherlands 2010-2013.

PubMed

Ibañez-Justicia, A; Stroo, A; Dik, M; Beeuwkes, J; Scholte, E J

2015-03-01

From 2010 onwards, a nationwide mosquito monitoring scheme has been conducted in The Netherlands with the aim of gaining crucial information about mosquito (Diptera: Culicidae) species composition, geographical distributions, biodiversity, and habitat preferences. The results of this study are based on 778 randomly sampled mosquito locations. These are divided into three main habitat types: urban, rural-agricultural, and natural areas. Twenty-seven mosquito species were found: 26 indigenous and 1 exotic, Aedes japonicus japonicus (Theobald, 1901). The preliminary results are presented here, with details of their species distribution and seasonality. Monitoring the temporal and spatial distribution of mosquitoes is an essential step in the risk analysis of emerging mosquito-borne diseases. © The Author 2015. Published by Oxford University Press on behalf of Entomological Society of America. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Discrimination of isotrigon textures using the Rényi entropy of Allan variances.

PubMed

Gabarda, Salvador; Cristóbal, Gabriel

2008-09-01

We present a computational algorithm for isotrigon texture discrimination. The aim of this method consists in discriminating isotrigon textures against a binary random background. The extension of the method to the problem of multitexture discrimination is considered as well. The method relies on the fact that the information content of time or space-frequency representations of signals, including images, can be readily analyzed by means of generalized entropy measures. In such a scenario, the Rényi entropy appears as an effective tool, given that Rényi measures can be used to provide information about a local neighborhood within an image. Localization is essential for comparing images on a pixel-by-pixel basis. Discrimination is performed through a local Rényi entropy measurement applied on a spatially oriented 1-D pseudo-Wigner distribution (PWD) of the test image. The PWD is normalized so that it may be interpreted as a probability distribution. Prior to the calculation of the texture's PWD, a preprocessing filtering step replaces the original texture with its localized spatially oriented Allan variances. The anisotropic structure of the textures, as revealed by the Allan variances, turns out to be crucial later to attain a high discrimination by the extraction of Rényi entropy measures. The method has been empirically evaluated with a family of isotrigon textures embedded in a binary random background. The extension to the case of multiple isotrigon mosaics has also been considered. Discrimination results are compared with other existing methods.

Determination of the stacking fault density in highly defective single GaAs nanowires by means of coherent diffraction imaging

NASA Astrophysics Data System (ADS)

Davtyan, Arman; Biermanns, Andreas; Loffeld, Otmar; Pietsch, Ullrich

2016-06-01

Coherent x-ray diffraction imaging is used to measure diffraction patterns from individual highly defective nanowires, showing a complex speckle pattern instead of well-defined Bragg peaks. The approach is tested for nanowires of 500 nm diameter and 500 nm height predominately composed by zinc-blende (ZB) and twinned zinc-blende (TZB) phase domains. Phase retrieval is used to reconstruct the measured 2-dimensional intensity patterns recorded from single nanowires with 3.48 nm and 0.98 nm spatial resolution. Whereas the speckle amplitudes and distribution are perfectly reconstructed, no unique solution could be obtained for the phase structure. The number of phase switches is found to be proportional to the number of measured speckles and follows a narrow number distribution. Using data with 0.98 nm spatial resolution the mean number of phase switches is in reasonable agreement with estimates taken from TEM. However, since the resolved phase domain still is 3-4 times larger than a single GaAs bilayer we explain the non-ambiguous phase reconstruction by the fact that depending on starting phase and sequence of subroutines used during the phase retrieval the retrieved phase domain host a different sequence of randomly stacked bilayers. Modelling possible arrangements of bilayer sequences within a phase domain demonstrate that the complex speckle patterns measured can indeed be explained by the random arrangement of the ZB and TZB phase domains.

A sero-survey of rinderpest in nomadic pastoral systems in central and southern Somalia from 2002 to 2003, using a spatially integrated random sampling approach.

PubMed

Tempia, S; Salman, M D; Keefe, T; Morley, P; Freier, J E; DeMartini, J C; Wamwayi, H M; Njeumi, F; Soumaré, B; Abdi, A M

2010-12-01

A cross-sectional sero-survey, using a two-stage cluster sampling design, was conducted between 2002 and 2003 in ten administrative regions of central and southern Somalia, to estimate the seroprevalence and geographic distribution of rinderpest (RP) in the study area, as well as to identify potential risk factors for the observed seroprevalence distribution. The study was also used to test the feasibility of the spatially integrated investigation technique in nomadic and semi-nomadic pastoral systems. In the absence of a systematic list of livestock holdings, the primary sampling units were selected by generating random map coordinates. A total of 9,216 serum samples were collected from cattle aged 12 to 36 months at 562 sampling sites. Two apparent clusters of RP seroprevalence were detected. Four potential risk factors associated with the observed seroprevalence were identified: the mobility of cattle herds, the cattle population density, the proximity of cattle herds to cattle trade routes and cattle herd size. Risk maps were then generated to assist in designing more targeted surveillance strategies. The observed seroprevalence in these areas declined over time. In subsequent years, similar seroprevalence studies in neighbouring areas of Kenya and Ethiopia also showed a very low seroprevalence of RP or the absence of antibodies against RP. The progressive decline in RP antibody prevalence is consistent with virus extinction. Verification of freedom from RP infection in the Somali ecosystem is currently in progress.

Relationship between gaseous N dynamics and the hydraulic state of hierarchically structured soils

NASA Astrophysics Data System (ADS)

Schlüter, Steffen; Dörsch, Peter; Vogel, Hans-Jörg

2017-04-01

The inherent spatial heterogeneity of soil generates spatially distributed micro-sites with different local N gas (NO, N2O, N2) production and release rates. Moreover, local micro-site conditions and the pathways between them depend on soil moisture which itself is highly dynamic close to the soil surface. These relationships need to be taken into account for a quantitative understanding of soil denitrification and associated N gas dynamics. Soil structure has been recognized as a key factor to understand the high spatial variability of N gas emissions. In particular gaseous N release from soils depends on: i) the total denitrification rate, which is related to the spatial extent and distribution of anaerobic sites and ii) the probability of N2O to escape from the soil without being further reduced to N2. This impact of soil structure is typically ignored in studies with soil slurries or repacked soil. In this project we run well-defined mesocosm experiments on N gas dynamics with hierarchically structured, artificial soils in which the spatial distribution of substrate and denitrifiers is known exactly. Sintered, porous glass pellets are inoculated with strains of Paracoccus denitrificans and/or Agrobacterium tumefaciens and amended with nutrient solution. These pellets are embedded in coarse-grained sand within gas-tight columns under O2/He atmosphere. The pellets are either places in layers or randomly to create different patterns of N gas production sites and diffusion pathways. Denitrification occurs in the anaerobic centers of the porous pellets, while the partially saturated sand matrix controls the diffusive transport of N gases towards the headspace, where all relevant gas concentrations are monitored with gas chromatography. Water saturations are adjusted such that the diffusive pathways are either fully continuous or partially discontinuous. Preliminary results indicate that the water content exert a major control on the magnitude of denitrification, whereas the onset and dynamics are mainly controlled by the position of the substrate and the denitrifiers.

Global mapping of highly pathogenic avian influenza H5N1 and H5Nx clade 2.3.4.4 viruses with spatial cross-validation

PubMed Central

Dhingra, Madhur S; Artois, Jean; Robinson, Timothy P; Linard, Catherine; Chaiban, Celia; Xenarios, Ioannis; Engler, Robin; Liechti, Robin; Kuznetsov, Dmitri; Xiao, Xiangming; Dobschuetz, Sophie Von; Claes, Filip; Newman, Scott H; Dauphin, Gwenaëlle; Gilbert, Marius

2016-01-01

Global disease suitability models are essential tools to inform surveillance systems and enable early detection. We present the first global suitability model of highly pathogenic avian influenza (HPAI) H5N1 and demonstrate that reliable predictions can be obtained at global scale. Best predictions are obtained using spatial predictor variables describing host distributions, rather than land use or eco-climatic spatial predictor variables, with a strong association with domestic duck and extensively raised chicken densities. Our results also support a more systematic use of spatial cross-validation in large-scale disease suitability modelling compared to standard random cross-validation that can lead to unreliable measure of extrapolation accuracy. A global suitability model of the H5 clade 2.3.4.4 viruses, a group of viruses that recently spread extensively in Asia and the US, shows in comparison a lower spatial extrapolation capacity than the HPAI H5N1 models, with a stronger association with intensively raised chicken densities and anthropogenic factors. DOI: http://dx.doi.org/10.7554/eLife.19571.001 PMID:27885988

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.

The use of crop rotation for mapping soil organic content in farmland

NASA Astrophysics Data System (ADS)

Yang, Lin; Song, Min; Zhu, A.-Xing; Qin, Chengzhi

2017-04-01

Most of the current digital soil mapping uses natural environmental covariates. However, human activities have significantly impacted the development of soil properties since half a century, and therefore become an important factor affecting soil spatial variability. Many researches have done field experiments to show how soil properties are impacted and changed by human activities, however, spatial variation data of human activities as environmental covariates have been rarely used in digital soil mapping. In this paper, we took crop rotation as an example of agricultural activities, and explored its effectiveness in characterizing and mapping the spatial variability of soil. The cultivated area of Xuanzhou city and Langxi County in Anhui Province was chosen as the study area. Three main crop rotations,including double-rice, wheat-rice,and oilseed rape-cotton were observed through field investigation in 2010. The spatial distribution of the three crop rotations in the study area was obtained by multi-phase remote sensing image interpretation using a supervised classification method. One-way analysis of variance (ANOVA) for topsoil organic content in the three crop rotation groups was performed. Factor importance of seven natural environmental covariates, crop rotation, Land use and NDVI were generated by variable importance criterion of Random Forest. Different combinations of environmental covariates were selected according to the importance rankings of environmental covariates for predicting SOC using Random Forest and Soil Landscape Inference Model (SOLIM). A cross validation was generated to evaluated the mapping accuracies. The results showed that there were siginificant differences of topsoil organic content among the three crop rotation groups. The crop rotation is more important than parent material, land use or NDVI according to the importance ranking calculated by Random Forest. In addition, crop rotation improved the mapping accuracy, especially for the flat clutivated area. This study demonstrates the usefulness of human activities in digital soil mapping and thus indicates the necessity for human activity factors in digital soil mapping studies.

Community turnover of wood-inhabiting fungi across hierarchical spatial scales.

PubMed

Abrego, Nerea; García-Baquero, Gonzalo; Halme, Panu; Ovaskainen, Otso; Salcedo, Isabel

2014-01-01

For efficient use of conservation resources it is important to determine how species diversity changes across spatial scales. In many poorly known species groups little is known about at which spatial scales the conservation efforts should be focused. Here we examined how the community turnover of wood-inhabiting fungi is realised at three hierarchical levels, and how much of community variation is explained by variation in resource composition and spatial proximity. The hierarchical study design consisted of management type (fixed factor), forest site (random factor, nested within management type) and study plots (randomly placed plots within each study site). To examine how species richness varied across the three hierarchical scales, randomized species accumulation curves and additive partitioning of species richness were applied. To analyse variation in wood-inhabiting species and dead wood composition at each scale, linear and Permanova modelling approaches were used. Wood-inhabiting fungal communities were dominated by rare and infrequent species. The similarity of fungal communities was higher within sites and within management categories than among sites or between the two management categories, and it decreased with increasing distance among the sampling plots and with decreasing similarity of dead wood resources. However, only a small part of community variation could be explained by these factors. The species present in managed forests were in a large extent a subset of those species present in natural forests. Our results suggest that in particular the protection of rare species requires a large total area. As managed forests have only little additional value complementing the diversity of natural forests, the conservation of natural forests is the key to ecologically effective conservation. As the dissimilarity of fungal communities increases with distance, the conserved natural forest sites should be broadly distributed in space, yet the individual conserved areas should be large enough to ensure local persistence.

Community Turnover of Wood-Inhabiting Fungi across Hierarchical Spatial Scales

PubMed Central

Abrego, Nerea; García-Baquero, Gonzalo; Halme, Panu; Ovaskainen, Otso; Salcedo, Isabel

2014-01-01

For efficient use of conservation resources it is important to determine how species diversity changes across spatial scales. In many poorly known species groups little is known about at which spatial scales the conservation efforts should be focused. Here we examined how the community turnover of wood-inhabiting fungi is realised at three hierarchical levels, and how much of community variation is explained by variation in resource composition and spatial proximity. The hierarchical study design consisted of management type (fixed factor), forest site (random factor, nested within management type) and study plots (randomly placed plots within each study site). To examine how species richness varied across the three hierarchical scales, randomized species accumulation curves and additive partitioning of species richness were applied. To analyse variation in wood-inhabiting species and dead wood composition at each scale, linear and Permanova modelling approaches were used. Wood-inhabiting fungal communities were dominated by rare and infrequent species. The similarity of fungal communities was higher within sites and within management categories than among sites or between the two management categories, and it decreased with increasing distance among the sampling plots and with decreasing similarity of dead wood resources. However, only a small part of community variation could be explained by these factors. The species present in managed forests were in a large extent a subset of those species present in natural forests. Our results suggest that in particular the protection of rare species requires a large total area. As managed forests have only little additional value complementing the diversity of natural forests, the conservation of natural forests is the key to ecologically effective conservation. As the dissimilarity of fungal communities increases with distance, the conserved natural forest sites should be broadly distributed in space, yet the individual conserved areas should be large enough to ensure local persistence. PMID:25058128

Two spatial light modulator system for laboratory simulation of random beam propagation in random media.

PubMed

Wang, Fei; Toselli, Italo; Korotkova, Olga

2016-02-10

An optical system consisting of a laser source and two independent consecutive phase-only spatial light modulators (SLMs) is shown to accurately simulate a generated random beam (first SLM) after interaction with a stationary random medium (second SLM). To illustrate the range of possibilities, a recently introduced class of random optical frames is examined on propagation in free space and several weak turbulent channels with Kolmogorov and non-Kolmogorov statistics.

Spatiotemporal analysis of Quaternary normal faults in the Northern Rocky Mountains, USA

NASA Astrophysics Data System (ADS)

Davarpanah, A.; Babaie, H. A.; Reed, P.

2010-12-01

The mid-Tertiary Basin-and-Range extensional tectonic event developed most of the normal faults that bound the ranges in the northern Rocky Mountains within Montana, Wyoming, and Idaho. The interaction of the thermally induced stress field of the Yellowstone hot spot with the existing Basin-and-Range fault blocks, during the last 15 my, has produced a new, spatially and temporally variable system of normal faults in these areas. The orientation and spatial distribution of the trace of these hot-spot induced normal faults, relative to earlier Basin-and-Range faults, have significant implications for the effect of the temporally varying and spatially propagating thermal dome on the growth of new hot spot related normal faults and reactivation of existing Basin-and-Range faults. Digitally enhanced LANDSAT 7 Enhanced Thematic Mapper Plus (ETM+) and Landsat 4 and 5 Thematic Mapper (TM) bands, with spatial resolution of 30 m, combined with analytical GIS and geological techniques helped in determining and analyzing the lineaments and traces of the Quaternary, thermally-induced normal faults in the study area. Applying the color composite (CC) image enhancement technique, the combination of bands 3, 2 and 1 of the ETM+ and TM images was chosen as the best statistical choice to create a color composite for lineament identification. The spatiotemporal analysis of the Quaternary normal faults produces significant information on the structural style, timing, spatial variation, spatial density, and frequency of the faults. The seismic Quaternary normal faults, in the whole study area, are divided, based on their age, into four specific sets, which from oldest to youngest include: Quaternary (>1.6 Ma), middle and late Quaternary (>750 ka), latest Quaternary (>15 ka), and the last 150 years. A density map for the Quaternary faults reveals that most active faults are near the current Yellowstone National Park area (YNP), where most seismically active faults, in the past 1.6 my, are located. The GIS based autocorrelation method, applied to the trace orientation, length, frequency, and spatial distribution for each age-defined fault set, revealed spatial homogeneity for each specific set. The results of the method of Moran`sI and Geary`s C show no spatial autocorrelation among the trend of the fault traces and their location. Our results suggest that while lineaments of similar age define a clustered pattern in each domain, the overall distribution pattern of lineaments with different ages seems to be non-uniform (random). The directional distribution analysis reveals a distinct range of variation for fault traces of different ages (i.e., some displaying ellipsis behavior). Among the Quaternary normal fault sets, the youngest lineament set (i.e., last 150 years) defines the greatest ellipticity (eccentricity) and the least lineaments distribution variation. The frequency rose diagram for the entire Quaternary normal faults, shows four major modes (around 360o, 330o, 300o, and 270o), and two minor modes (around 235 and 205).

Organic Matter Stabilization in Soil Microaggregates: Implications from Spatial Heterogeneity of Organic Carbon Contents and Carbon Forms

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

Lehmann,J.; Kinyangi, J.; Solomon, D.

2007-01-01

This study investigates the spatial distribution of organic carbon (C) in free stable microaggregates (20-250 {mu}m; not encapsulated within macroaggregates) from one Inceptisol and two Oxisols in relation to current theories of the mechanisms of their formation. Two-dimensional micro- and nano-scale observations using synchrotron-based Fourier-transform infrared (FTIR) and near-edge X-ray absorption fine structure (NEXAFS) spectroscopy yielded maps of the distribution of C amounts and chemical forms. Carbon deposits were unevenly distributed within microaggregates and did not show any discernable gradients between interior and exterior of aggregates. Rather, C deposits appeared to be patchy within the microaggregates. In contrast to themore » random location of C, there were micron-scale patterns in the spatial distribution of aliphatic C-H (2922 cm-1), aromatic C=C and N-H (1589 cm-1) and polysaccharide C-O (1035 cm-1). Aliphatic C forms and the ratio of aliphatic C/aromatic C were positively correlated (r 2 of 0.66-0.75 and 0.27-0.59, respectively) to the amount of O-H on kaolinite surfaces (3695 cm-1), pointing at a strong role for organo-mineral interactions in C stabilization within microaggregates and at a possible role for molecules containing aliphatic C-H groups in such interactions. This empirical relationship was supported by nanometer-scale observations using NEXAFS which showed that the organic matter in coatings on mineral surfaces had more aliphatic and carboxylic C with spectral characteristics resembling microbial metabolites than the organic matter of the entire microaggregate. Our observations thus support models of C stabilization in which the initially dominant process is adsorption of organics on mineral surfaces rather than occlusion of organic debris by adhering clay particles.« less

Global direct pressures on biodiversity by large-scale metal mining: Spatial distribution and implications for conservation.

PubMed

Murguía, Diego I; Bringezu, Stefan; Schaldach, Rüdiger

2016-09-15

Biodiversity loss is widely recognized as a serious global environmental change process. While large-scale metal mining activities do not belong to the top drivers of such change, these operations exert or may intensify pressures on biodiversity by adversely changing habitats, directly and indirectly, at local and regional scales. So far, analyses of global spatial dynamics of mining and its burden on biodiversity focused on the overlap between mines and protected areas or areas of high value for conservation. However, it is less clear how operating metal mines are globally exerting pressure on zones of different biodiversity richness; a similar gap exists for unmined but known mineral deposits. By using vascular plants' diversity as a proxy to quantify overall biodiversity, this study provides a first examination of the global spatial distribution of mines and deposits for five key metals across different biodiversity zones. The results indicate that mines and deposits are not randomly distributed, but concentrated within intermediate and high diversity zones, especially bauxite and silver. In contrast, iron, gold, and copper mines and deposits are closer to a more proportional distribution while showing a high concentration in the intermediate biodiversity zone. Considering the five metals together, 63% and 61% of available mines and deposits, respectively, are located in intermediate diversity zones, comprising 52% of the global land terrestrial surface. 23% of mines and 20% of ore deposits are located in areas of high plant diversity, covering 17% of the land. 13% of mines and 19% of deposits are in areas of low plant diversity, comprising 31% of the land surface. Thus, there seems to be potential for opening new mines in areas of low biodiversity in the future. Copyright © 2016 Elsevier Ltd. All rights reserved.

SDMtoolbox 2.0: the next generation Python-based GIS toolkit for landscape genetic, biogeographic and species distribution model analyses

PubMed Central

Bennett, Joseph R.; French, Connor M.

2017-01-01

SDMtoolbox 2.0 is a software package for spatial studies of ecology, evolution, and genetics. The release of SDMtoolbox 2.0 allows researchers to use the most current ArcGIS software and MaxEnt software, and reduces the amount of time that would be spent developing common solutions. The central aim of this software is to automate complicated and repetitive spatial analyses in an intuitive graphical user interface. One core tenant facilitates careful parameterization of species distribution models (SDMs) to maximize each model’s discriminatory ability and minimize overfitting. This includes carefully processing of occurrence data, environmental data, and model parameterization. This program directly interfaces with MaxEnt, one of the most powerful and widely used species distribution modeling software programs, although SDMtoolbox 2.0 is not limited to species distribution modeling or restricted to modeling in MaxEnt. Many of the SDM pre- and post-processing tools have ‘universal’ analogs for use with any modeling software. The current version contains a total of 79 scripts that harness the power of ArcGIS for macroecology, landscape genetics, and evolutionary studies. For example, these tools allow for biodiversity quantification (such as species richness or corrected weighted endemism), generation of least-cost paths and corridors among shared haplotypes, assessment of the significance of spatial randomizations, and enforcement of dispersal limitations of SDMs projected into future climates—to only name a few functions contained in SDMtoolbox 2.0. Lastly, dozens of generalized tools exists for batch processing and conversion of GIS data types or formats, which are broadly useful to any ArcMap user. PMID:29230356

Species distribution models: A comparison of statistical approaches for livestock and disease epidemics.

PubMed

Hollings, Tracey; Robinson, Andrew; van Andel, Mary; Jewell, Chris; Burgman, Mark

2017-01-01

In livestock industries, reliable up-to-date spatial distribution and abundance records for animals and farms are critical for governments to manage and respond to risks. Yet few, if any, countries can afford to maintain comprehensive, up-to-date agricultural census data. Statistical modelling can be used as a proxy for such data but comparative modelling studies have rarely been undertaken for livestock populations. Widespread species, including livestock, can be difficult to model effectively due to complex spatial distributions that do not respond predictably to environmental gradients. We assessed three machine learning species distribution models (SDM) for their capacity to estimate national-level farm animal population numbers within property boundaries: boosted regression trees (BRT), random forests (RF) and K-nearest neighbour (K-NN). The models were built from a commercial livestock database and environmental and socio-economic predictor data for New Zealand. We used two spatial data stratifications to test (i) support for decision making in an emergency response situation, and (ii) the ability for the models to predict to new geographic regions. The performance of the three model types varied substantially, but the best performing models showed very high accuracy. BRTs had the best performance overall, but RF performed equally well or better in many simulations; RFs were superior at predicting livestock numbers for all but very large commercial farms. K-NN performed poorly relative to both RF and BRT in all simulations. The predictions of both multi species and single species models for farms and within hypothetical quarantine zones were very close to observed data. These models are generally applicable for livestock estimation with broad applications in disease risk modelling, biosecurity, policy and planning.

Species distribution models: A comparison of statistical approaches for livestock and disease epidemics

PubMed Central

Robinson, Andrew; van Andel, Mary; Jewell, Chris; Burgman, Mark

2017-01-01

In livestock industries, reliable up-to-date spatial distribution and abundance records for animals and farms are critical for governments to manage and respond to risks. Yet few, if any, countries can afford to maintain comprehensive, up-to-date agricultural census data. Statistical modelling can be used as a proxy for such data but comparative modelling studies have rarely been undertaken for livestock populations. Widespread species, including livestock, can be difficult to model effectively due to complex spatial distributions that do not respond predictably to environmental gradients. We assessed three machine learning species distribution models (SDM) for their capacity to estimate national-level farm animal population numbers within property boundaries: boosted regression trees (BRT), random forests (RF) and K-nearest neighbour (K-NN). The models were built from a commercial livestock database and environmental and socio-economic predictor data for New Zealand. We used two spatial data stratifications to test (i) support for decision making in an emergency response situation, and (ii) the ability for the models to predict to new geographic regions. The performance of the three model types varied substantially, but the best performing models showed very high accuracy. BRTs had the best performance overall, but RF performed equally well or better in many simulations; RFs were superior at predicting livestock numbers for all but very large commercial farms. K-NN performed poorly relative to both RF and BRT in all simulations. The predictions of both multi species and single species models for farms and within hypothetical quarantine zones were very close to observed data. These models are generally applicable for livestock estimation with broad applications in disease risk modelling, biosecurity, policy and planning. PMID:28837685

Effect of heterogeneous investments on the evolution of cooperation in spatial public goods game.

PubMed

Huang, Keke; Wang, Tao; Cheng, Yuan; Zheng, Xiaoping

2015-01-01

Understanding the emergence of cooperation in spatial public goods game remains a grand challenge across disciplines. In most previous studies, it is assumed that the investments of all the cooperators are identical, and often equal to 1. However, it is worth mentioning that players are diverse and heterogeneous when choosing actions in the rapidly developing modern society and researchers have shown more interest to the heterogeneity of players recently. For modeling the heterogeneous players without loss of generality, it is assumed in this work that the investment of a cooperator is a random variable with uniform distribution, the mean value of which is equal to 1. The results of extensive numerical simulations convincingly indicate that heterogeneous investments can promote cooperation. Specifically, a large value of the variance of the random variable can decrease the two critical values for the result of behavioral evolution effectively. Moreover, the larger the variance is, the better the promotion effect will be. In addition, this article has discussed the impact of heterogeneous investments when the coevolution of both strategy and investment is taken into account. Comparing the promotion effect of coevolution of strategy and investment with that of strategy imitation only, we can conclude that the coevolution of strategy and investment decreases the asymptotic fraction of cooperators by weakening the heterogeneity of investments, which further demonstrates that heterogeneous investments can promote cooperation in spatial public goods game.

Cluster: A New Application for Spatial Analysis of Pixelated Data for Epiphytotics.

PubMed

Nelson, Scot C; Corcoja, Iulian; Pethybridge, Sarah J

2017-12-01

Spatial analysis of epiphytotics is essential to develop and test hypotheses about pathogen ecology, disease dynamics, and to optimize plant disease management strategies. Data collection for spatial analysis requires substantial investment in time to depict patterns in various frames and hierarchies. We developed a new approach for spatial analysis of pixelated data in digital imagery and incorporated the method in a stand-alone desktop application called Cluster. The user isolates target entities (clusters) by designating up to 24 pixel colors as nontargets and moves a threshold slider to visualize the targets. The app calculates the percent area occupied by targeted pixels, identifies the centroids of targeted clusters, and computes the relative compass angle of orientation for each cluster. Users can deselect anomalous clusters manually and/or automatically by specifying a size threshold value to exclude smaller targets from the analysis. Up to 1,000 stochastic simulations randomly place the centroids of each cluster in ranked order of size (largest to smallest) within each matrix while preserving their calculated angles of orientation for the long axes. A two-tailed probability t test compares the mean inter-cluster distances for the observed versus the values derived from randomly simulated maps. This is the basis for statistical testing of the null hypothesis that the clusters are randomly distributed within the frame of interest. These frames can assume any shape, from natural (e.g., leaf) to arbitrary (e.g., a rectangular or polygonal field). Cluster summarizes normalized attributes of clusters, including pixel number, axis length, axis width, compass orientation, and the length/width ratio, available to the user as a downloadable spreadsheet. Each simulated map may be saved as an image and inspected. Provided examples demonstrate the utility of Cluster to analyze patterns at various spatial scales in plant pathology and ecology and highlight the limitations, trade-offs, and considerations for the sensitivities of variables and the biological interpretations of results. The Cluster app is available as a free download for Apple computers at iTunes, with a link to a user guide website.

Stepwise magnetic-geochemical approach for efficient assessment of heavy metal polluted sites

NASA Astrophysics Data System (ADS)

Appel, E.; Rösler, W.; Ojha, G.

2012-04-01

Previous studies have shown that magnetometry can outline the distribution of fly ash deposition in the surroundings of coal-burning power plants and steel industries. Especially the easy-to-measure magnetic susceptibility (MS) is capable to act as a proxy for heavy metal (HM) pollution caused by such kind of point source pollution. Here we present a demonstration project around the coal-burning power plant complex "Schwarze Pumpe" in eastern Germany. Before reunification of West and East Germany huge amounts of HM pollutants were emitted from the "Schwarze Pumpe" into the environment by both fly ash emission and dumped clinker. The project has been conducted as part of the TASK Centre of Competence which aims at bringing new innovative techniques closer to the market. Our project combines in situ and laboratory MS measurements and HM analyses in order to demonstrate the efficiency of a stepwise approach for site assessment of HM pollution around point sources of fly-ash emission and deposition into soil. The following scenario is played through: We assume that the "true" spatial distribution of HM pollution (given by the pollution load index PLI comprising Fe, Zn, Pb, and Cu) is represented by our entire set of 85 measured samples (XRF analyses) from forest sites around the "Schwarze Pumpe". Surface MS data (collected with a Bartington MS2D) and in situ vertical MS sections (logged by an SM400 instrument) are used to determine a qualitative overview of potentially higher and lower polluted areas. A suite of spatial HM distribution maps obtained by random selections of 30 out of the 85 analysed sites is compared to the HM map obtained from a targeted 30-sites-selection based on pre-information from the MS results. The PLI distribution map obtained from the targeted 30-sites-selection shows all essential details of the "true" pollution map, while the different random 30-sites-selections miss important features. This comparison shows that, for the same cost investment, a stepwise combined magnetic-geochemical site assessment leads to a clearly more significant characterization of soil pollution than by a common approach with exclusively random sampling for geochemical analysis, or alternatively to an equal quality result for lower costs.

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.

The Migration Matrix: Marine Vertebrate Movements in Magnetic Coordinate Space

NASA Astrophysics Data System (ADS)

Horton, T. W.; Holdaway, R. N.; Clapham, P. J.; Zerbini, A. N.; Andriolo, A.; Hays, G. C.; Egevang, C.; Domeier, M. L.; Lucas, N.

2011-12-01

Determining how vertebrates navigate during their long-distance migrations remains one of the most enduring and fundamental challenges of behavioral ecology. It is widely accepted that spatial orientation relative to a reference datum is a fundamental requirement of long-distance return migration between seasonal habitats, and a variety of viable positional and directional orientation cues, including the sun, stars, and magnetic field, have been documented experimentally. However, a fundamental question remains unanswered: Are empirically observed migratory movements compatible with modern theoretical frameworks of spatial orientation? To address this question, we analysed leatherback turtle (Dermochelys coriacea), arctic tern (Sterna paradisaea), humpback whale (Megaptera novaeangliae), and great white shark (Carcharodon carcharias) track maps, frequency distribution diagrams and time-series plots of animal locations in spherical magnetic coordinate space. Our analyses indicates that, although individual migration tracks are spatially and temporally distinct, vertebrate movements are non-randomly distributed in all three spherical magnetic coordinates (i.e. intensity, inclination, and declination). Stop-over locations, migratory destinations, and re-orientation points occur at similar magnetic coordinate locations, relative to tagging areas, in all four species, suggesting that a common system of magnetic orientation likely informs the navigational behaviors of these phylogenetically diverse taxa. Although our analyses demonstrate that the experiment-derived 'magnetic map' goal orientation theoretical framework of animal navigation is compatible with remotely-sensed migration track data, they also indicate that magnetic information is complemented by spatially and temporally contingent celestial stimuli during navigation.

Disease Mapping of Zero-excessive Mesothelioma Data in Flanders

PubMed Central

Neyens, Thomas; Lawson, Andrew B.; Kirby, Russell S.; Nuyts, Valerie; Watjou, Kevin; Aregay, Mehreteab; Carroll, Rachel; Nawrot, Tim S.; Faes, Christel

2016-01-01

Purpose To investigate the distribution of mesothelioma in Flanders using Bayesian disease mapping models that account for both an excess of zeros and overdispersion. Methods The numbers of newly diagnosed mesothelioma cases within all Flemish municipalities between 1999 and 2008 were obtained from the Belgian Cancer Registry. To deal with overdispersion, zero-inflation and geographical association, the hurdle combined model was proposed, which has three components: a Bernoulli zero-inflation mixture component to account for excess zeros, a gamma random effect to adjust for overdispersion and a normal conditional autoregressive random effect to attribute spatial association. This model was compared with other existing methods in literature. Results The results indicate that hurdle models with a random effects term accounting for extra-variance in the Bernoulli zero-inflation component fit the data better than hurdle models that do not take overdispersion in the occurrence of zeros into account. Furthermore, traditional models that do not take into account excessive zeros but contain at least one random effects term that models extra-variance in the counts have better fits compared to their hurdle counterparts. In other words, the extra-variability, due to an excess of zeros, can be accommodated by spatially structured and/or unstructured random effects in a Poisson model such that the hurdle mixture model is not necessary. Conclusions Models taking into account zero-inflation do not always provide better fits to data with excessive zeros than less complex models. In this study, a simple conditional autoregressive model identified a cluster in mesothelioma cases near a former asbestos processing plant (Kapelle-op-den-Bos). This observation is likely linked with historical local asbestos exposures. Future research will clarify this. PMID:27908590

Disease mapping of zero-excessive mesothelioma data in Flanders.

PubMed

Neyens, Thomas; Lawson, Andrew B; Kirby, Russell S; Nuyts, Valerie; Watjou, Kevin; Aregay, Mehreteab; Carroll, Rachel; Nawrot, Tim S; Faes, Christel

2017-01-01

To investigate the distribution of mesothelioma in Flanders using Bayesian disease mapping models that account for both an excess of zeros and overdispersion. The numbers of newly diagnosed mesothelioma cases within all Flemish municipalities between 1999 and 2008 were obtained from the Belgian Cancer Registry. To deal with overdispersion, zero inflation, and geographical association, the hurdle combined model was proposed, which has three components: a Bernoulli zero-inflation mixture component to account for excess zeros, a gamma random effect to adjust for overdispersion, and a normal conditional autoregressive random effect to attribute spatial association. This model was compared with other existing methods in literature. The results indicate that hurdle models with a random effects term accounting for extra variance in the Bernoulli zero-inflation component fit the data better than hurdle models that do not take overdispersion in the occurrence of zeros into account. Furthermore, traditional models that do not take into account excessive zeros but contain at least one random effects term that models extra variance in the counts have better fits compared to their hurdle counterparts. In other words, the extra variability, due to an excess of zeros, can be accommodated by spatially structured and/or unstructured random effects in a Poisson model such that the hurdle mixture model is not necessary. Models taking into account zero inflation do not always provide better fits to data with excessive zeros than less complex models. In this study, a simple conditional autoregressive model identified a cluster in mesothelioma cases near a former asbestos processing plant (Kapelle-op-den-Bos). This observation is likely linked with historical local asbestos exposures. Future research will clarify this. Copyright © 2016 Elsevier Inc. All rights reserved.

Hyperuniformity, quasi-long-range correlations, and void-space constraints in maximally random jammed particle packings. I. Polydisperse spheres.

PubMed

Zachary, Chase E; Jiao, Yang; Torquato, Salvatore

2011-05-01

Hyperuniform many-particle distributions possess a local number variance that grows more slowly than the volume of an observation window, implying that the local density is effectively homogeneous beyond a few characteristic length scales. Previous work on maximally random strictly jammed sphere packings in three dimensions has shown that these systems are hyperuniform and possess unusual quasi-long-range pair correlations decaying as r(-4), resulting in anomalous logarithmic growth in the number variance. However, recent work on maximally random jammed sphere packings with a size distribution has suggested that such quasi-long-range correlations and hyperuniformity are not universal among jammed hard-particle systems. In this paper, we show that such systems are indeed hyperuniform with signature quasi-long-range correlations by characterizing the more general local-volume-fraction fluctuations. We argue that the regularity of the void space induced by the constraints of saturation and strict jamming overcomes the local inhomogeneity of the disk centers to induce hyperuniformity in the medium with a linear small-wave-number nonanalytic behavior in the spectral density, resulting in quasi-long-range spatial correlations scaling with r(-(d+1)) in d Euclidean space dimensions. A numerical and analytical analysis of the pore-size distribution for a binary maximally random jammed system in addition to a local characterization of the n-particle loops governing the void space surrounding the inclusions is presented in support of our argument. This paper is the first part of a series of two papers considering the relationships among hyperuniformity, jamming, and regularity of the void space in hard-particle packings.

Level statistics of words: Finding keywords in literary texts and symbolic sequences

NASA Astrophysics Data System (ADS)

Carpena, P.; Bernaola-Galván, P.; Hackenberg, M.; Coronado, A. V.; Oliver, J. L.

2009-03-01

Using a generalization of the level statistics analysis of quantum disordered systems, we present an approach able to extract automatically keywords in literary texts. Our approach takes into account not only the frequencies of the words present in the text but also their spatial distribution along the text, and is based on the fact that relevant words are significantly clustered (i.e., they self-attract each other), while irrelevant words are distributed randomly in the text. Since a reference corpus is not needed, our approach is especially suitable for single documents for which no a priori information is available. In addition, we show that our method works also in generic symbolic sequences (continuous texts without spaces), thus suggesting its general applicability.

Distributed optical fiber-based monitoring approach of spatial seepage behavior in dike engineering

NASA Astrophysics Data System (ADS)

Su, Huaizhi; Ou, Bin; Yang, Lifu; Wen, Zhiping

2018-07-01

The failure caused by seepage is the most common one in dike engineering. As to the characteristics of seepage in dike, such as longitudinal extension engineering, the randomness, strong concealment and small initial quantity order, by means of distributed fiber temperature sensor system (DTS), adopting an improved optical fiber layer layout scheme, the location of initial interpolation point of the saturation line is obtained. With the barycentric Lagrange interpolation collocation method (BLICM), the infiltrated surface of dike full-section is generated. Combined with linear optical fiber monitoring seepage method, BLICM is applied in an engineering case, which shows that a real-time seepage monitoring technique is presented in full-section of dike based on the combination method.

Operator Spreading in Random Unitary Circuits

NASA Astrophysics Data System (ADS)

Nahum, Adam; Vijay, Sagar; Haah, Jeongwan

2018-04-01

Random quantum circuits yield minimally structured models for chaotic quantum dynamics, which are able to capture, for example, universal properties of entanglement growth. We provide exact results and coarse-grained models for the spreading of operators by quantum circuits made of Haar-random unitaries. We study both 1 +1 D and higher dimensions and argue that the coarse-grained pictures carry over to operator spreading in generic many-body systems. In 1 +1 D , we demonstrate that the out-of-time-order correlator (OTOC) satisfies a biased diffusion equation, which gives exact results for the spatial profile of the OTOC and determines the butterfly speed vB. We find that in 1 +1 D , the "front" of the OTOC broadens diffusively, with a width scaling in time as t1 /2. We address fluctuations in the OTOC between different realizations of the random circuit, arguing that they are negligible in comparison to the broadening of the front within a realization. Turning to higher dimensions, we show that the averaged OTOC can be understood exactly via a remarkable correspondence with a purely classical droplet growth problem. This implies that the width of the front of the averaged OTOC scales as t1 /3 in 2 +1 D and as t0.240 in 3 +1 D (exponents of the Kardar-Parisi-Zhang universality class). We support our analytic argument with simulations in 2 +1 D . We point out that, in two or higher spatial dimensions, the shape of the spreading operator at late times is affected by underlying lattice symmetries and, in general, is not spherical. However, when full spatial rotational symmetry is present in 2 +1 D , our mapping implies an exact asymptotic form for the OTOC, in terms of the Tracy-Widom distribution. For an alternative perspective on the OTOC in 1 +1 D , we map it to the partition function of an Ising-like statistical mechanics model. As a result of special structure arising from unitarity, this partition function reduces to a random walk calculation which can be performed exactly. We also use this mapping to give exact results for entanglement growth in 1 +1 D circuits.

Cloud Macroscopic Organization: Order Emerging from Randomness

NASA Technical Reports Server (NTRS)

Yuan, Tianle

2011-01-01

Clouds play a central role in many aspects of the climate system and their forms and shapes are remarkably diverse. Appropriate representation of clouds in climate models is a major challenge because cloud processes span at least eight orders of magnitude in spatial scales. Here we show that there exists order in cloud size distribution of low-level clouds, and that it follows a power-law distribution with exponent gamma close to 2. gamma is insensitive to yearly variations in environmental conditions, but has regional variations and land-ocean contrasts. More importantly, we demonstrate this self-organizing behavior of clouds emerges naturally from a complex network model with simple, physical organizing principles: random clumping and merging. We also demonstrate symmetry between clear and cloudy skies in terms of macroscopic organization because of similar fundamental underlying organizing principles. The order in the apparently complex cloud-clear field thus has its root in random local interactions. Studying cloud organization with complex network models is an attractive new approach that has wide applications in climate science. We also propose a concept of cloud statistic mechanics approach. This approach is fully complementary to deterministic models, and the two approaches provide a powerful framework to meet the challenge of representing clouds in our climate models when working in tandem.

Continuous representation of tumor microvessel density and detection of angiogenic hotspots in histological whole-slide images.

PubMed

Kather, Jakob Nikolas; Marx, Alexander; Reyes-Aldasoro, Constantino Carlos; Schad, Lothar R; Zöllner, Frank Gerrit; Weis, Cleo-Aron

2015-08-07

Blood vessels in solid tumors are not randomly distributed, but are clustered in angiogenic hotspots. Tumor microvessel density (MVD) within these hotspots correlates with patient survival and is widely used both in diagnostic routine and in clinical trials. Still, these hotspots are usually subjectively defined. There is no unbiased, continuous and explicit representation of tumor vessel distribution in histological whole slide images. This shortcoming distorts angiogenesis measurements and may account for ambiguous results in the literature. In the present study, we describe and evaluate a new method that eliminates this bias and makes angiogenesis quantification more objective and more efficient. Our approach involves automatic slide scanning, automatic image analysis and spatial statistical analysis. By comparing a continuous MVD function of the actual sample to random point patterns, we introduce an objective criterion for hotspot detection: An angiogenic hotspot is defined as a clustering of blood vessels that is very unlikely to occur randomly. We evaluate the proposed method in N=11 images of human colorectal carcinoma samples and compare the results to a blinded human observer. For the first time, we demonstrate the existence of statistically significant hotspots in tumor images and provide a tool to accurately detect these hotspots.

Classification of coronary artery tissues using optical coherence tomography imaging in Kawasaki disease

NASA Astrophysics Data System (ADS)

Abdolmanafi, Atefeh; Prasad, Arpan Suravi; Duong, Luc; Dahdah, Nagib

2016-03-01

Intravascular imaging modalities, such as Optical Coherence Tomography (OCT) allow nowadays improving diagnosis, treatment, follow-up, and even prevention of coronary artery disease in the adult. OCT has been recently used in children following Kawasaki disease (KD), the most prevalent acquired coronary artery disease during childhood with devastating complications. The assessment of coronary artery layers with OCT and early detection of coronary sequelae secondary to KD is a promising tool for preventing myocardial infarction in this population. More importantly, OCT is promising for tissue quantification of the inner vessel wall, including neo intima luminal myofibroblast proliferation, calcification, and fibrous scar deposits. The goal of this study is to classify the coronary artery layers of OCT imaging obtained from a series of KD patients. Our approach is focused on developing a robust Random Forest classifier built on the idea of randomly selecting a subset of features at each node and based on second- and higher-order statistical texture analysis which estimates the gray-level spatial distribution of images by specifying the local features of each pixel and extracting the statistics from their distribution. The average classification accuracy for intima and media are 76.36% and 73.72% respectively. Random forest classifier with texture analysis promises for classification of coronary artery tissue.

Non-random distribution of DNA double-strand breaks induced by particle irradiation

NASA Technical Reports Server (NTRS)

Lobrich, M.; Cooper, P. K.; Rydberg, B.; Chatterjee, A. (Principal Investigator)

1996-01-01

Induction of DNA double-strand breaks (dsbs) in mammalian cells is dependent on the spatial distribution of energy deposition from the ionizing radiation. For high LET particle radiations the primary ionization sites occur in a correlated manner along the track of the particles, while for X-rays these sites are much more randomly distributed throughout the volume of the cell. It can therefore be expected that the distribution of dsbs linearly along the DNA molecule also varies with the type of radiation and the ionization density. Using pulsed-field gel and conventional gel techniques, we measured the size distribution of DNA molecules from irradiated human fibroblasts in the total range of 0.1 kbp-10 Mbp for X-rays and high LET particles (N ions, 97 keV/microns and Fe ions, 150 keV/microns). On a mega base pair scale we applied conventional pulsed-field gel electrophoresis techniques such as measurement of the fraction of DNA released from the well (FAR) and measurement of breakage within a specific NotI restriction fragment (hybridization assay). The induction rate for widely spaced breaks was found to decrease with LET. However, when the entire distribution of radiation-induced fragments was analysed, we detected an excess of fragments with sizes below about 200 kbp for the particles compared with X-irradiation. X-rays are thus more effective than high LET radiations in producing large DNA fragments but less effective in the production of smaller fragments. We determined the total induction rate of dsbs for the three radiations based on a quantitative analysis of all the measured radiation-induced fragments and found that the high LET particles were more efficient than X-rays at inducing dsbs, indicating an increasing total efficiency with LET. Conventional assays that are based only on the measurement of large fragments are therefore misleading when determining total dsb induction rates of high LET particles. The possible biological significance of this non-randomness for dsb induction is discussed.

Metastable dynamical patterns and their stabilization in arrays of bidirectionally coupled sigmoidal neurons

NASA Astrophysics Data System (ADS)

Horikawa, Yo

2013-12-01

Transient patterns in a bistable ring of bidirectionally coupled sigmoidal neurons were studied. When the system had a pair of spatially uniform steady solutions, the instability of unstable spatially nonuniform steady solutions decreased exponentially with the number of neurons because of the symmetry of the system. As a result, transient spatially nonuniform patterns showed dynamical metastability: Their duration increased exponentially with the number of neurons and the duration of randomly generated patterns obeyed a power-law distribution. However, these metastable dynamical patterns were easily stabilized in the presence of small variations in coupling strength. Metastable rotating waves and their pinning in the presence of asymmetry in the direction of coupling and the disappearance of metastable dynamical patterns due to asymmetry in the output function of a neuron were also examined. Further, in a two-dimensional array of neurons with nearest-neighbor coupling, intrinsically one-dimensional patterns were dominant in transients, and self-excitation in these neurons affected the metastable dynamical patterns.

Macroscopic Spatial Complexity of the Game of Life Cellular Automaton: A Simple Data Analysis

NASA Astrophysics Data System (ADS)

Hernández-Montoya, A. R.; Coronel-Brizio, H. F.; Rodríguez-Achach, M. E.

In this chapter we present a simple data analysis of an ensemble of 20 time series, generated by averaging the spatial positions of the living cells for each state of the Game of Life Cellular Automaton (GoL). We show that at the macroscopic level described by these time series, complexity properties of GoL are also presented and the following emergent properties, typical of data extracted complex systems such as financial or economical come out: variations of the generated time series following an asymptotic power law distribution, large fluctuations tending to be followed by large fluctuations, and small fluctuations tending to be followed by small ones, and fast decay of linear correlations, however, the correlations associated to their absolute variations exhibit a long range memory. Finally, a Detrended Fluctuation Analysis (DFA) of the generated time series, indicates that the GoL spatial macro states described by the time series are not either completely ordered or random, in a measurable and very interesting way.

Critical Infrastructure Vulnerability to Spatially Localized Failures with Applications to Chinese Railway System.

PubMed

Ouyang, Min; Tian, Hui; Wang, Zhenghua; Hong, Liu; Mao, Zijun

2017-01-17

This article studies a general type of initiating events in critical infrastructures, called spatially localized failures (SLFs), which are defined as the failure of a set of infrastructure components distributed in a spatially localized area due to damage sustained, while other components outside the area do not directly fail. These failures can be regarded as a special type of intentional attack, such as bomb or explosive assault, or a generalized modeling of the impact of localized natural hazards on large-scale systems. This article introduces three SLFs models: node centered SLFs, district-based SLFs, and circle-shaped SLFs, and proposes a SLFs-induced vulnerability analysis method from three aspects: identification of critical locations, comparisons of infrastructure vulnerability to random failures, topologically localized failures and SLFs, and quantification of infrastructure information value. The proposed SLFs-induced vulnerability analysis method is finally applied to the Chinese railway system and can be also easily adapted to analyze other critical infrastructures for valuable protection suggestions. © 2017 Society for Risk Analysis.

Spatial self-organization favors heterotypic cooperation over cheating.

PubMed

Momeni, Babak; Waite, Adam James; Shou, Wenying

2013-11-12

Heterotypic cooperation-two populations exchanging distinct benefits that are costly to produce-is widespread. Cheaters, exploiting benefits while evading contribution, can undermine cooperation. Two mechanisms can stabilize heterotypic cooperation. In 'partner choice', cooperators recognize and choose cooperating over cheating partners; in 'partner fidelity feedback', fitness-feedback from repeated interactions ensures that aiding your partner helps yourself. How might a spatial environment, which facilitates repeated interactions, promote fitness-feedback? We examined this process through mathematical models and engineered Saccharomyces cerevisiae strains incapable of recognition. Here, cooperators and their heterotypic cooperative partners (partners) exchanged distinct essential metabolites. Cheaters exploited partner-produced metabolites without reciprocating, and were competitively superior to cooperators. Despite initially random spatial distributions, cooperators gained more partner neighbors than cheaters did. The less a cheater contributed, the more it was excluded and disfavored. This self-organization, driven by asymmetric fitness effects of cooperators and cheaters on partners during cell growth into open space, achieves assortment. DOI: http://dx.doi.org/10.7554/eLife.00960.001.

Spatial self-organization favors heterotypic cooperation over cheating

PubMed Central

Momeni, Babak; Waite, Adam James; Shou, Wenying

2013-01-01

Heterotypic cooperation—two populations exchanging distinct benefits that are costly to produce—is widespread. Cheaters, exploiting benefits while evading contribution, can undermine cooperation. Two mechanisms can stabilize heterotypic cooperation. In ‘partner choice’, cooperators recognize and choose cooperating over cheating partners; in ‘partner fidelity feedback’, fitness-feedback from repeated interactions ensures that aiding your partner helps yourself. How might a spatial environment, which facilitates repeated interactions, promote fitness-feedback? We examined this process through mathematical models and engineered Saccharomyces cerevisiae strains incapable of recognition. Here, cooperators and their heterotypic cooperative partners (partners) exchanged distinct essential metabolites. Cheaters exploited partner-produced metabolites without reciprocating, and were competitively superior to cooperators. Despite initially random spatial distributions, cooperators gained more partner neighbors than cheaters did. The less a cheater contributed, the more it was excluded and disfavored. This self-organization, driven by asymmetric fitness effects of cooperators and cheaters on partners during cell growth into open space, achieves assortment. DOI: http://dx.doi.org/10.7554/eLife.00960.001 PMID:24220506

Modeling the spatial distribution of African buffalo (Syncerus caffer) in the Kruger National Park, South Africa

PubMed Central

Hughes, Kristen; Budke, Christine M.; Ward, Michael P.; Kerry, Ruth; Ingram, Ben

2017-01-01

The population density of wildlife reservoirs contributes to disease transmission risk for domestic animals. The objective of this study was to model the African buffalo distribution of the Kruger National Park. A secondary objective was to collect field data to evaluate models and determine environmental predictors of buffalo detection. Spatial distribution models were created using buffalo census information and archived data from previous research. Field data were collected during the dry (August 2012) and wet (January 2013) seasons using a random walk design. The fit of the prediction models were assessed descriptively and formally by calculating the root mean square error (rMSE) of deviations from field observations. Logistic regression was used to estimate the effects of environmental variables on the detection of buffalo herds and linear regression was used to identify predictors of larger herd sizes. A zero-inflated Poisson model produced distributions that were most consistent with expected buffalo behavior. Field data confirmed that environmental factors including season (P = 0.008), vegetation type (P = 0.002), and vegetation density (P = 0.010) were significant predictors of buffalo detection. Bachelor herds were more likely to be detected in dense vegetation (P = 0.005) and during the wet season (P = 0.022) compared to the larger mixed-sex herds. Static distribution models for African buffalo can produce biologically reasonable results but environmental factors have significant effects and therefore could be used to improve model performance. Accurate distribution models are critical for the evaluation of disease risk and to model disease transmission. PMID:28902858

Why choose Random Forest to predict rare species distribution with few samples in large undersampled areas? Three Asian crane species models provide supporting evidence.

PubMed

Mi, Chunrong; Huettmann, Falk; Guo, Yumin; Han, Xuesong; Wen, Lijia

2017-01-01

Species distribution models (SDMs) have become an essential tool in ecology, biogeography, evolution and, more recently, in conservation biology. How to generalize species distributions in large undersampled areas, especially with few samples, is a fundamental issue of SDMs. In order to explore this issue, we used the best available presence records for the Hooded Crane ( Grus monacha , n  = 33), White-naped Crane ( Grus vipio , n  = 40), and Black-necked Crane ( Grus nigricollis , n  = 75) in China as three case studies, employing four powerful and commonly used machine learning algorithms to map the breeding distributions of the three species: TreeNet (Stochastic Gradient Boosting, Boosted Regression Tree Model), Random Forest, CART (Classification and Regression Tree) and Maxent (Maximum Entropy Models). In addition, we developed an ensemble forecast by averaging predicted probability of the above four models results. Commonly used model performance metrics (Area under ROC (AUC) and true skill statistic (TSS)) were employed to evaluate model accuracy. The latest satellite tracking data and compiled literature data were used as two independent testing datasets to confront model predictions. We found Random Forest demonstrated the best performance for the most assessment method, provided a better model fit to the testing data, and achieved better species range maps for each crane species in undersampled areas. Random Forest has been generally available for more than 20 years and has been known to perform extremely well in ecological predictions. However, while increasingly on the rise, its potential is still widely underused in conservation, (spatial) ecological applications and for inference. Our results show that it informs ecological and biogeographical theories as well as being suitable for conservation applications, specifically when the study area is undersampled. This method helps to save model-selection time and effort, and allows robust and rapid assessments and decisions for efficient conservation.

Why choose Random Forest to predict rare species distribution with few samples in large undersampled areas? Three Asian crane species models provide supporting evidence

PubMed Central

Mi, Chunrong; Huettmann, Falk; Han, Xuesong; Wen, Lijia

2017-01-01

Species distribution models (SDMs) have become an essential tool in ecology, biogeography, evolution and, more recently, in conservation biology. How to generalize species distributions in large undersampled areas, especially with few samples, is a fundamental issue of SDMs. In order to explore this issue, we used the best available presence records for the Hooded Crane (Grus monacha, n = 33), White-naped Crane (Grus vipio, n = 40), and Black-necked Crane (Grus nigricollis, n = 75) in China as three case studies, employing four powerful and commonly used machine learning algorithms to map the breeding distributions of the three species: TreeNet (Stochastic Gradient Boosting, Boosted Regression Tree Model), Random Forest, CART (Classification and Regression Tree) and Maxent (Maximum Entropy Models). In addition, we developed an ensemble forecast by averaging predicted probability of the above four models results. Commonly used model performance metrics (Area under ROC (AUC) and true skill statistic (TSS)) were employed to evaluate model accuracy. The latest satellite tracking data and compiled literature data were used as two independent testing datasets to confront model predictions. We found Random Forest demonstrated the best performance for the most assessment method, provided a better model fit to the testing data, and achieved better species range maps for each crane species in undersampled areas. Random Forest has been generally available for more than 20 years and has been known to perform extremely well in ecological predictions. However, while increasingly on the rise, its potential is still widely underused in conservation, (spatial) ecological applications and for inference. Our results show that it informs ecological and biogeographical theories as well as being suitable for conservation applications, specifically when the study area is undersampled. This method helps to save model-selection time and effort, and allows robust and rapid assessments and decisions for efficient conservation. PMID:28097060

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.

Morphological evolution of Ge/Si(001) quantum dot rings formed at the rim of wet-etched pits.

PubMed

Grydlik, Martyna; Brehm, Moritz; Schäffler, Friedrich

2012-10-30

We demonstrate the formation of Ge quantum dots in ring-like arrangements around predefined {111}-faceted pits in the Si(001) substrate. We report on the complex morphological evolution of the single quantum dots contributing to the rings by means of atomic force microscopy and demonstrate that by careful adjustment of the epitaxial growth parameters, such rings containing densely squeezed islands can be grown with large spatial distances of up to 5 μm without additional nucleation of randomly distributed quantum dots between the rings.

Topological patterns in street networks of self-organized urban settlements

NASA Astrophysics Data System (ADS)

Buhl, J.; Gautrais, J.; Reeves, N.; Solé, R. V.; Valverde, S.; Kuntz, P.; Theraulaz, G.

2006-02-01

Many urban settlements result from a spatially distributed, decentralized building process. Here we analyze the topological patterns of organization of a large collection of such settlements using the approach of complex networks. The global efficiency (based on the inverse of shortest-path lengths), robustness to disconnections and cost (in terms of length) of these graphs is studied and their possible origins analyzed. A wide range of patterns is found, from tree-like settlements (highly vulnerable to random failures) to meshed urban patterns. The latter are shown to be more robust and efficient.

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

NASA Astrophysics Data System (ADS)

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

2011-12-01

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

Optical encryption interface

NASA Technical Reports Server (NTRS)

Jackson, Deborah J. (Inventor)

1998-01-01

An analog optical encryption system based on phase scrambling of two-dimensional optical images and holographic transformation for achieving large encryption keys and high encryption speed. An enciphering interface uses a spatial light modulator for converting a digital data stream into a two dimensional optical image. The optical image is further transformed into a hologram with a random phase distribution. The hologram is converted into digital form for transmission over a shared information channel. A respective deciphering interface at a receiver reverses the encrypting process by using a phase conjugate reconstruction of the phase scrambled hologram.

Mathematics of Failures in Complex Systems: Characterization and Mitigation of Service Failures in Complex Dynamic Systems

DTIC Science & Technology

2007-06-30

fractal dimensions and Lyapunov exponents . Fractal dimensions characterize geometri- cal complexity of dynamics (e.g., spatial distribution of points along...ant classi3ers (e.g., Lyapunov exponents , and fractal dimensions). The 3rst three steps show how chaotic systems may be separated from stochastic...correlated random walk in which a ¼ 2H, where H is the Hurst exponen interval 0pHp1 with the case H ¼ 0:5 corresponding to a simple rando This model has been

Spatiotemporal Determinants of Urban Leptospirosis Transmission: Four-Year Prospective Cohort Study of Slum Residents in Brazil.

PubMed

Hagan, José E; Moraga, Paula; Costa, Federico; Capian, Nicolas; Ribeiro, Guilherme S; Wunder, Elsio A; Felzemburgh, Ridalva D M; Reis, Renato B; Nery, Nivison; Santana, Francisco S; Fraga, Deborah; Dos Santos, Balbino L; Santos, Andréia C; Queiroz, Adriano; Tassinari, Wagner; Carvalho, Marilia S; Reis, Mitermayer G; Diggle, Peter J; Ko, Albert I

2016-01-01

Rat-borne leptospirosis is an emerging zoonotic disease in urban slum settlements for which there are no adequate control measures. The challenge in elucidating risk factors and informing approaches for prevention is the complex and heterogeneous environment within slums, which vary at fine spatial scales and influence transmission of the bacterial agent. We performed a prospective study of 2,003 slum residents in the city of Salvador, Brazil during a four-year period (2003-2007) and used a spatiotemporal modelling approach to delineate the dynamics of leptospiral transmission. Household interviews and Geographical Information System surveys were performed annually to evaluate risk exposures and environmental transmission sources. We completed annual serosurveys to ascertain leptospiral infection based on serological evidence. Among the 1,730 (86%) individuals who completed at least one year of follow-up, the infection rate was 35.4 (95% CI, 30.7-40.6) per 1,000 annual follow-up events. Male gender, illiteracy, and age were independently associated with infection risk. Environmental risk factors included rat infestation (OR 1.46, 95% CI, 1.00-2.16), contact with mud (OR 1.57, 95% CI 1.17-2.17) and lower household elevation (OR 0.92 per 10m increase in elevation, 95% CI 0.82-1.04). The spatial distribution of infection risk was highly heterogeneous and varied across small scales. Fixed effects in the spatiotemporal model accounted for the majority of the spatial variation in risk, but there was a significant residual component that was best explained by the spatial random effect. Although infection risk varied between years, the spatial distribution of risk associated with fixed and random effects did not vary temporally. Specific "hot-spots" consistently had higher transmission risk during study years. The risk for leptospiral infection in urban slums is determined in large part by structural features, both social and environmental. Our findings indicate that topographic factors such as household elevation and inadequate drainage increase risk by promoting contact with mud and suggest that the soil-water interface serves as the environmental reservoir for spillover transmission. The use of a spatiotemporal approach allowed the identification of geographic outliers with unexplained risk patterns. This approach, in addition to guiding targeted community-based interventions and identifying new hypotheses, may have general applicability towards addressing environmentally-transmitted diseases that have emerged in complex urban slum settings.

Shapes, spectra and new methods in nonlinear spatial optics

NASA Astrophysics Data System (ADS)

Sun, Can

For a myriad of optical applications, the quality of the light source is poor and the beam is inherently spatially partially-coherent. For this broad class of systems, wave dynamics depends not only on the wave intensity, but also on its distribution of spatial frequencies. Unfortunately, this entire spectrum of problems has often been overlooked - for reasons of theoretical ease or experimental difficulties. Here, we remedy this by demonstrating a novel experimental setup which, for the first time, allows arbitrarily modulation of the spatial spectra of light to obtain any distribution of interest. Using modulation instability as an example, we isolate the effect of different spectral shapes and observe distinct beam dynamics. Next, we turn to a thermodynamic description of the long-term evolution of statistical fields. For quantum systems, a major consequence is Bose-Einstein Condensation. However, recent theoretical studies have suggested that quantum mechanics is not necessary for the condensation process: classical waves with random phases can also self-organize into a coherent state. Starting from a random ensemble, nonlinear interactions can lead to a turbulent energy cascade towards longer spatial scales. In complete analogy with the kinetics of a gas system, there is a statistical dynamics of waves in which particle velocities map to wavepacket k-vectors while collisions are mimicked by four-wave mixing. As with collisions, each wave interaction is formally reversible, yet entropy principles mandate that the ensemble evolves towards an equilibrium state of maximum disorder. The result is an equipartition of energy, in the form of a Rayleigh-Jeans spectrum, with information about the condensation process recorded in small-scale fluctuations. Here, we give the first experimental observation of the condensation of classical waves in any media. Using classical light in a self-defocusing photorefractive, we observe all aspects of the condensation process, including the population of a coherent state, spectral redistribution towards the Rayleigh-Jeans spectrum, and formal reversibility of the interactions. The latter is proved experimentally by introducing a digital "Maxwell's Demon" to reverse (phase-conjugate) the momentum of each wavepacket and recover the original "thermal cloud". The results integrate digital and physical methods of nonlinear processing, confirm fundamental ideas in wave turbulence, and greatly extend the range of Bose-Einstein theory.

Microfracture spacing distributions and the evolution of fracture patterns in sandstones

NASA Astrophysics Data System (ADS)

Hooker, J. N.; Laubach, S. E.; Marrett, R.

2018-03-01

Natural fracture patterns in sandstone were sampled using scanning electron microscope-based cathodoluminescence (SEM-CL) imaging. All fractures are opening-mode and are fully or partially sealed by quartz cement. Most sampled fractures are too small to be height-restricted by sedimentary layers. At very low strains (<∼0.001), fracture spatial distributions are indistinguishable from random, whereas at higher strains, fractures are generally statistically clustered. All 12 large (N > 100) datasets show spacings that are best fit by log-normal size distributions, compared to exponential, power law, or normal distributions. The clustering of fractures suggests that the locations of natural factures are not determined by a random process. To investigate natural fracture localization, we reconstructed the opening history of a cluster of fractures within the Huizachal Group in northeastern Mexico, using fluid inclusions from synkinematic cements and thermal-history constraints. The largest fracture, which is the only fracture in the cluster visible to the naked eye, among 101 present, opened relatively late in the sequence. This result suggests that the growth of sets of fractures is a self-organized process, in which small, initially isolated fractures grow and progressively interact, with preferential growth of a subset of fractures developing at the expense of growth of the rest. Size-dependent sealing of fractures within sets suggests that synkinematic cementation may contribute to fracture clustering.

Spatial analysis of ecosystem service relationships to improve targeting of payments for hydrological services

PubMed Central

Manson, Robert H.; Ricketts, Taylor H.; Geissert, Daniel

2018-01-01

Payment for hydrological services (PHS) are popular tools for conserving ecosystems and their water-related services. However, improving the spatial targeting and impacts of PHS, as well as their ability to foster synergies with other ecosystem services (ES), remain challenging. We aimed at using spatial analyses to evaluate the targeting performance of México’s National PHS program in central Veracruz. We quantified the effectiveness of areas targeted for PHS in actually covering areas of high HS provision and social priority during 2003–2013. First, we quantified provisioning and spatial distributions of two target (water yield and soil retention), and one non-target ES (carbon storage) using InVEST. Subsequently, pairwise relationships among ES were quantified by using spatial correlation and overlap analyses. Finally, we evaluated targeting by: (i) prioritizing areas of individual and overlapping ES; (ii) quantifying spatial co-occurrences of these priority areas with those targeted by PHS; (iii) evaluating the extent to which PHS directly contribute to HS delivery; and (iv), testing if PHS targeted areas disproportionately covered areas with high ecological and social priority. We found that modelled priority areas exhibited non-random distributions and distinct spatial patterns. Our results show significant pairwise correlations between all ES suggesting synergistic relationships. However, our analysis showed a significantly lower overlap than expected and thus significant mismatches between PHS targeted areas and all types of priority areas. These findings suggest that the targeting of areas with high HS provisioning and social priority by Mexico’s PHS program could be improved significantly. This study underscores: (1) the importance of using maps of HS provisioning as main targeting criteria in PHS design to channel payments towards areas that require future conservation, and (2) the need for future research that helps balance ecological and socioeconomic targeting criteria. PMID:29462205

Simulation of polycyclic aromatic hydrocarbons transport in multimedia

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

Chen, L.; Chu, C.J.

1999-07-01

Many studies have indicated that the threat from toxic air pollutants such as VOCs comes not through inhalation by humans while the pollutants are in a gaseous state but through absorption when the pollutants are in a solid state such as in an aerosol or particulate form. Pollutants such as Polycyclic Aromatic Hydrocarbons (PAHs) usually exist in a semi-volatile state. To assess the risk of the PAHs, one needs to estimate the dose of the pollutants to which a human would be exposed through various pathways. In this study, the authors modified a Spatial Multimedia Compartmental Model (SMCM) originally developedmore » by UCLA Professor Cohen to predict the PAHs distribution among multimedia such as air, water, soil and sediment in the Taipei metropolitan area. Three PAHs were considered in this study. They are Benzo(a)pyrene, Pyrene and Chrysene. When PAHs are emitted into atmosphere, physical and chemical mechanisms may redistribute the PAHs among multimedia. Five cases of PAHs distribution in multimedia were simulated: (1) PAHs distribution in a dry condition, (2) PAHs distribution when there are different dry deposition velocities, (3) PAHs distribution under a single rainfall event, (4) PAHs distribution when there are different soil properties, (5) PAHs distribution under a random rainfall case. The simulation results are concluded: (1) In the dry case, the PAHs accumulate mostly in soil and air compartments, (2) Different dry depositing velocities will affect the PAHs distribution among compartments. (3) Different soil properties affect the PAHs concentration in the soil and sediment compartments, (4) The soil PAHs concentrations usually increase for those PAHs with a high solid/gas ratio. (5) The random rainfall only affects the PAHs concentration in the soil.« less

Microscopic Distributions of Defect Luminescence From Subgrain Boundaries in Multicrystalline Silicon Wafers

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

Nguyen, Hieu T.; Jensen, Mallory A.; Li, Li

We investigate the microscopic distributions of sub-band-gap luminescence emission (the so-called D-lines D1/D2/D3/D4) and the band-to-band luminescence intensity, near recombination-active sub-grain boundaries in multicrystalline silicon wafers for solar cells. We find that the sub-band-gap luminescence from decorating defects/impurities (D1/D2) and from intrinsic dislocations (D3/D4) have distinctly different spatial distributions, and are asymmetric across the sub-grain boundaries. The presence of D1/D2 is correlated with a strong reduction in the band-to-band luminescence, indicating a higher recombination activity. In contrast, D3/D4 emissions are not strongly correlated with the band-to-band intensity. Based on spatially-resolved, synchrotron-based micro-X-ray fluorescence measurements of metal impurities, we confirm thatmore » high densities of metal impurities are present at locations with strong D1/D2 emission but low D3/D4 emission. Finally, we show that the observed asymmetry of the sub-band-gap luminescence across the sub-grain boundaries is due to their inclination below the wafer surface. Based on the luminescence asymmetries, the sub-grain boundaries are shown to share a common inclination locally, rather than be orientated randomly.« less

Scale-invariant puddles in graphene: Geometric properties of electron-hole distribution at the Dirac point.

PubMed

Najafi, M N; Nezhadhaghighi, M Ghasemi

2017-03-01

We characterize the carrier density profile of the ground state of graphene in the presence of particle-particle interaction and random charged impurity in zero gate voltage. We provide detailed analysis on the resulting spatially inhomogeneous electron gas, taking into account the particle-particle interaction and the remote Coulomb disorder on an equal footing within the Thomas-Fermi-Dirac theory. We present some general features of the carrier density probability measure of the graphene sheet. We also show that, when viewed as a random surface, the electron-hole puddles at zero chemical potential show peculiar self-similar statistical properties. Although the disorder potential is chosen to be Gaussian, we show that the charge field is non-Gaussian with unusual Kondev relations, which can be regarded as a new class of two-dimensional random-field surfaces. Using Schramm-Loewner (SLE) evolution, we numerically demonstrate that the ungated graphene has conformal invariance and the random zero-charge density contours are SLE_{κ} with κ=1.8±0.2, consistent with c=-3 conformal field theory.

Estimation of beam material random field properties via sensitivity-based model updating using experimental frequency response functions

NASA Astrophysics Data System (ADS)

Machado, M. R.; Adhikari, S.; Dos Santos, J. M. C.; Arruda, J. R. F.

2018-03-01

Structural parameter estimation is affected not only by measurement noise but also by unknown uncertainties which are present in the system. Deterministic structural model updating methods minimise the difference between experimentally measured data and computational prediction. Sensitivity-based methods are very efficient in solving structural model updating problems. Material and geometrical parameters of the structure such as Poisson's ratio, Young's modulus, mass density, modal damping, etc. are usually considered deterministic and homogeneous. In this paper, the distributed and non-homogeneous characteristics of these parameters are considered in the model updating. The parameters are taken as spatially correlated random fields and are expanded in a spectral Karhunen-Loève (KL) decomposition. Using the KL expansion, the spectral dynamic stiffness matrix of the beam is expanded as a series in terms of discretized parameters, which can be estimated using sensitivity-based model updating techniques. Numerical and experimental tests involving a beam with distributed bending rigidity and mass density are used to verify the proposed method. This extension of standard model updating procedures can enhance the dynamic description of structural dynamic models.

Random forest classification of stars in the Galactic Centre

NASA Astrophysics Data System (ADS)

Plewa, P. M.

2018-05-01

Near-infrared high-angular resolution imaging observations of the Milky Way's nuclear star cluster have revealed all luminous members of the existing stellar population within the central parsec. Generally, these stars are either evolved late-type giants or massive young, early-type stars. We revisit the problem of stellar classification based on intermediate-band photometry in the K band, with the primary aim of identifying faint early-type candidate stars in the extended vicinity of the central massive black hole. A random forest classifier, trained on a subsample of spectroscopically identified stars, performs similarly well as competitive methods (F1 = 0.85), without involving any model of stellar spectral energy distributions. Advantages of using such a machine-trained classifier are a minimum of required calibration effort, a predictive accuracy expected to improve as more training data become available, and the ease of application to future, larger data sets. By applying this classifier to archive data, we are also able to reproduce the results of previous studies of the spatial distribution and the K-band luminosity function of both the early- and late-type stars.

A stochastic-geometric model of soil variation in Pleistocene patterned ground

NASA Astrophysics Data System (ADS)

Lark, Murray; Meerschman, Eef; Van Meirvenne, Marc

2013-04-01

In this paper we examine the spatial variability of soil in parent material with complex spatial structure which arises from complex non-linear geomorphic processes. We show that this variability can be better-modelled by a stochastic-geometric model than by a standard Gaussian random field. The benefits of the new model are seen in the reproduction of features of the target variable which influence processes like water movement and pollutant dispersal. Complex non-linear processes in the soil give rise to properties with non-Gaussian distributions. Even under a transformation to approximate marginal normality, such variables may have a more complex spatial structure than the Gaussian random field model of geostatistics can accommodate. In particular the extent to which extreme values of the variable are connected in spatially coherent regions may be misrepresented. As a result, for example, geostatistical simulation generally fails to reproduce the pathways for preferential flow in an environment where coarse infill of former fluvial channels or coarse alluvium of braided streams creates pathways for rapid movement of water. Multiple point geostatistics has been developed to deal with this problem. Multiple point methods proceed by sampling from a set of training images which can be assumed to reproduce the non-Gaussian behaviour of the target variable. The challenge is to identify appropriate sources of such images. In this paper we consider a mode of soil variation in which the soil varies continuously, exhibiting short-range lateral trends induced by local effects of the factors of soil formation which vary across the region of interest in an unpredictable way. The trends in soil variation are therefore only apparent locally, and the soil variation at regional scale appears random. We propose a stochastic-geometric model for this mode of soil variation called the Continuous Local Trend (CLT) model. We consider a case study of soil formed in relict patterned ground with pronounced lateral textural variations arising from the presence of infilled ice-wedges of Pleistocene origin. We show how knowledge of the pedogenetic processes in this environment, along with some simple descriptive statistics, can be used to select and fit a CLT model for the apparent electrical conductivity (ECa) of the soil. We use the model to simulate realizations of the CLT process, and compare these with realizations of a fitted Gaussian random field. We show how statistics that summarize the spatial coherence of regions with small values of ECa, which are expected to have coarse texture and so larger saturated hydraulic conductivity, are better reproduced by the CLT model than by the Gaussian random field. This suggests that the CLT model could be used to generate an unlimited supply of training images to allow multiple point geostatistical simulation or prediction of this or similar variables.

Spatial distribution of traffic in a cellular mobile data network

NASA Astrophysics Data System (ADS)

Linnartz, J. P. M. G.

1987-02-01

The use of integral transforms of the probability density function for the received power to analyze the relation between the spatial distributions of offered and throughout packet traffic in a mobile radio network with Rayleigh fading channels and ALOHA multiple access was assessed. A method to obtain the spatial distribution of throughput traffic from a prescribed spatial distribution of offered traffic is presented. Incoherent and coherent addition of interference signals is considered. The channel behavior for heavy traffic loads is studied. In both the incoherent and coherent case, the spatial distribution of offered traffic required to ensure a prescribed spatially uniform throughput is synthesized numerically.

Geomasking sensitive health data and privacy protection: an evaluation using an E911 database.

PubMed

Allshouse, William B; Fitch, Molly K; Hampton, Kristen H; Gesink, Dionne C; Doherty, Irene A; Leone, Peter A; Serre, Marc L; Miller, William C

2010-10-01

Geomasking is used to provide privacy protection for individual address information while maintaining spatial resolution for mapping purposes. Donut geomasking and other random perturbation geomasking algorithms rely on the assumption of a homogeneously distributed population to calculate displacement distances, leading to possible under-protection of individuals when this condition is not met. Using household data from 2007, we evaluated the performance of donut geomasking in Orange County, North Carolina. We calculated the estimated k-anonymity for every household based on the assumption of uniform household distribution. We then determined the actual k-anonymity by revealing household locations contained in the county E911 database. Census block groups in mixed-use areas with high population distribution heterogeneity were the most likely to have privacy protection below selected criteria. For heterogeneous populations, we suggest tripling the minimum displacement area in the donut to protect privacy with a less than 1% error rate.

Geomasking sensitive health data and privacy protection: an evaluation using an E911 database

PubMed Central

Allshouse, William B; Fitch, Molly K; Hampton, Kristen H; Gesink, Dionne C; Doherty, Irene A; Leone, Peter A; Serre, Marc L; Miller, William C

2010-01-01

Geomasking is used to provide privacy protection for individual address information while maintaining spatial resolution for mapping purposes. Donut geomasking and other random perturbation geomasking algorithms rely on the assumption of a homogeneously distributed population to calculate displacement distances, leading to possible under-protection of individuals when this condition is not met. Using household data from 2007, we evaluated the performance of donut geomasking in Orange County, North Carolina. We calculated the estimated k-anonymity for every household based on the assumption of uniform household distribution. We then determined the actual k-anonymity by revealing household locations contained in the county E911 database. Census block groups in mixed-use areas with high population distribution heterogeneity were the most likely to have privacy protection below selected criteria. For heterogeneous populations, we suggest tripling the minimum displacement area in the donut to protect privacy with a less than 1% error rate. PMID:20953360

Probabilistic measures of persistence and extinction in measles (meta)populations.

PubMed

Gunning, Christian E; Wearing, Helen J

2013-08-01

Persistence and extinction are fundamental processes in ecological systems that are difficult to accurately measure due to stochasticity and incomplete observation. Moreover, these processes operate on multiple scales, from individual populations to metapopulations. Here, we examine an extensive new data set of measles case reports and associated demographics in pre-vaccine era US cities, alongside a classic England & Wales data set. We first infer the per-population quasi-continuous distribution of log incidence. We then use stochastic, spatially implicit metapopulation models to explore the frequency of rescue events and apparent extinctions. We show that, unlike critical community size, the inferred distributions account for observational processes, allowing direct comparisons between metapopulations. The inferred distributions scale with population size. We use these scalings to estimate extinction boundary probabilities. We compare these predictions with measurements in individual populations and random aggregates of populations, highlighting the importance of medium-sized populations in metapopulation persistence. © 2013 John Wiley & Sons Ltd/CNRS.

Spatial patterns of arrests, police assault and addiction treatment center locations in Tijuana, Mexico.

PubMed

Werb, Dan; Strathdee, Steffanie A; Vera, Alicia; Arredondo, Jaime; Beletsky, Leo; Gonzalez-Zuniga, Patricia; Gaines, Tommi

2016-07-01

In the context of a public health-oriented drug policy reform in Mexico, we assessed the spatial distribution of police encounters among people who inject drugs (PWID) in Tijuana, determined the association between these encounters and the location of addiction treatment centers and explored the association between police encounters and treatment access. Geographically weighted regression (GWR) and logistic regression analysis using prospective spatial data from a community-recruited cohort of PWID in Tijuana and official geographical arrest data from the Tijuana Municipal Police Department. Tijuana, Mexico. A total of 608 participants (median age 37; 28.4% female) in the prospective Proyecto El Cuete cohort study recruited between January and December 2011. We compared the mean distance of police encounters and a randomly distributed set of events to treatment centers. GWR was undertaken to model the spatial relationship between police interactions and treatment centers. Logistic regression analysis was used to investigate factors associated with reporting police interactions. During the study period, 27.5% of police encounters occurred within 500 m of treatment centers. The GWR model suggested spatial correlation between encounters and treatment centers (global R(2)  = 0.53). Reporting a need for addiction treatment was associated with reporting arrest and police assault [adjusted odds ratio = 2.74, 95% confidence interval (CI) = 1.25-6.02, P = 0.012]. A geospatial analysis suggests that, in Mexico, people who inject drugs are at greater risk of being a victim of police violence if they consider themselves in need of addiction treatment, and their interactions with police appear to be more frequent around treatment centers. © 2016 Society for the Study of Addiction.

SPATIAL PATTERNS OF ARRESTS, POLICE ASSAULT, AND ADDICTION TREATMENT CENTER LOCATIONS IN TIJUANA, MEXICO

PubMed Central

Werb, D; Strathdee, SA; Vera, A; Arredondo, J; Beletsky, L; Gonzalez-Zuniga, P; Gaines, T

2016-01-01

Aims In the context of a public health-oriented drug policy reform in Mexico, we assessed the spatial distribution of police encounters among people who inject drugs (PWID) in Tijuana; determined the association between these encounters and the location of addiction treatment centers; and explored the association between police encounters and treatment access. Design Geographically weighted regression (GWR) and logistic regression analysis using prospective spatial data from a community-recruited cohort of PWID in Tijuana and official geographic arrest data from the Tijuana Municipal Police Department. Setting Tijuana, Mexico. Participants 608 participants (median age 37; 28.4% female) in the prospective Proyecto El Cuete cohort study recruited between January and December 2011. Measurements We compared the mean distance of police encounters and a randomly distributed set of events to treatment centers. GWR was undertaken to model the spatial relationship between police interactions and treatment centers. Logistic regression analysis was used to investigate factors associated with reporting police interactions. Findings During the study period, 27.5% of police encounters occurred within 500 meters of treatment centers. The GWR model suggested spatial correlation between encounters and treatment centers (Global R2 = 0.53). Reporting a need for addiction treatment was associated with reporting arrest and police assault (Adjusted Odds Ratio = 2.74, 95% Confidence Interval [CI]: 1.25–6.02, p = 0.012). Conclusions A geospatial analysis suggests that in Mexico, people who inject drugs are at greater risk of being a victim of police violence if they consider themselves in need of addiction treatment, and their interactions with police appear to be more frequent around treatment centres. PMID:26879179

Spatial Analysis of Hospital Incidence and in Hospital Mortality of Abdominal Aortic Aneurysms in Germany: Secondary Data Analysis of Nationwide Hospital Episode (DRG) Data.

PubMed

Kuehnl, Andreas; Salvermoser, Michael; Erk, Alexander; Trenner, Matthias; Schmid, Volker; Eckstein, Hans-Henning

2018-06-01

This study aimed to analyze the spatial distribution and regional variation of the hospital incidence and in hospital mortality of abdominal aortic aneurysms (AAA) in Germany. German DRG statistics (2011-2014) were analysed. Patients with ruptured AAA (rAAA, I71.3, treated or not) and patients with non-ruptured AAA (nrAAA, I71.4, treated by open or endovascular aneurysm repair) were included. Age, sex, and risk standardisation was done using standard statistical procedures. Regional variation was quantified using systematic component of variation. To analyse spatial auto-correlation and spatial pattern, global Moran's I and Getis-Ord Gi* were calculated. A total of 50,702 cases were included. Raw hospital incidence of AAA was 15.7 per 100,000 inhabitants (nrAAA 13.1; all rAAA 2.7; treated rAAA 1.6). The standardised hospital incidence of AAA ranged from 6.3 to 30.3 per 100,000. Systematic component of variation proportion was 96% in nrAAA and 55% in treated rAAA. Incidence rates of all AAA were significantly clustered with above average values in the northwestern parts of Germany and below average values in the south and eastern regions. Standardised mortality of nrAAA ranged from 1.7% to 4.3%, with that of treated rAAA ranging from 28% to 52%. Regional variation and spatial distribution of standardised mortality was not different from random. There was significant regional variation and clustering of the hospital incidence of AAA in Germany, with higher rates in the northwest and lower rates in the southeast. There was no significant variation in standardised (age/sex/risk) mortality between counties. Copyright © 2018. Published by Elsevier B.V.

Spatial distribution and cluster analysis of risky sexual behaviours and STDs reported by Chinese adults in Guangzhou, China: a representative population-based study

PubMed Central

Chen, Wen; Zhou, Fangjing; Hall, Brian J; Wang, Yu; Latkin, Carl; Ling, Li; Tucker, Joseph D

2016-01-01

Objectives To assess associations between residences location, risky sexual behaviours and sexually transmitted diseases (STDs) among adults living in Guangzhou, China. Methods Data were obtained from 751 Chinese adults aged 18–59 years in Guangzhou, China, using stratified random sampling by using spatial epidemiological methods. Face-to-face household interviews were conducted to collect self-report data on risky sexual behaviours and diagnosed STDs. Kulldorff’s spatial scan statistic was implemented to identify and detect spatial distribution and clusters of risky sexual behaviours and STDs. The presence and location of statistically significant clusters were mapped in the study areas using ArcGIS software. Results The prevalence of self-reported risky sexual behaviours was between 5.1% and 50.0%. The self-reported lifetime prevalence of diagnosed STDs was 7.06%. Anal intercourse clustered in an area located along the border within the rural–urban continuum (p=0.001). High rate clusters for alcohol or other drugs using before sex (p=0.008) and migrants who lived in Guangzhou <1 year (p=0.007) overlapped this cluster. Excess cases for unprotected sex (p=0.031) overlapped the cluster for college students (p<0.001). Five of nine (55.6%) students who had sexual experience during the last 12 months located in the cluster of unprotected sex. Conclusions Short-term migrants and college students reported greater risky sexual behaviours. Programmes to increase safer sex within these communities to reduce the risk of STDs are warranted in Guangzhou. Spatial analysis identified geographical clusters of risky sexual behaviours, which is critical for optimising surveillance and targeting control measures for these locations in the future. PMID:26843400

A dynamic spatio-temporal model for spatial data

USGS Publications Warehouse

Hefley, Trevor J.; Hooten, Mevin B.; Hanks, Ephraim M.; Russell, Robin; Walsh, Daniel P.

2017-01-01

Analyzing spatial data often requires modeling dependencies created by a dynamic spatio-temporal data generating process. In many applications, a generalized linear mixed model (GLMM) is used with a random effect to account for spatial dependence and to provide optimal spatial predictions. Location-specific covariates are often included as fixed effects in a GLMM and may be collinear with the spatial random effect, which can negatively affect inference. We propose a dynamic approach to account for spatial dependence that incorporates scientific knowledge of the spatio-temporal data generating process. Our approach relies on a dynamic spatio-temporal model that explicitly incorporates location-specific covariates. We illustrate our approach with a spatially varying ecological diffusion model implemented using a computationally efficient homogenization technique. We apply our model to understand individual-level and location-specific risk factors associated with chronic wasting disease in white-tailed deer from Wisconsin, USA and estimate the location the disease was first introduced. We compare our approach to several existing methods that are commonly used in spatial statistics. Our spatio-temporal approach resulted in a higher predictive accuracy when compared to methods based on optimal spatial prediction, obviated confounding among the spatially indexed covariates and the spatial random effect, and provided additional information that will be important for containing disease outbreaks.

A Fixed-Precision Sequential Sampling Plan for the Potato Tuberworm Moth, Phthorimaea operculella Zeller (Lepidoptera: Gelechidae), on Potato Cultivars.

PubMed

Shahbi, M; Rajabpour, A

2017-08-01

Phthorimaea operculella Zeller is an important pest of potato in Iran. Spatial distribution and fixed-precision sequential sampling for population estimation of the pest on two potato cultivars, Arinda ® and Sante ® , were studied in two separate potato fields during two growing seasons (2013-2014 and 2014-2015). Spatial distribution was investigated by Taylor's power law and Iwao's patchiness. Results showed that the spatial distribution of eggs and larvae was random. In contrast to Iwao's patchiness, Taylor's power law provided a highly significant relationship between variance and mean density. Therefore, fixed-precision sequential sampling plan was developed by Green's model at two precision levels of 0.25 and 0.1. The optimum sample size on Arinda ® and Sante ® cultivars at precision level of 0.25 ranged from 151 to 813 and 149 to 802 leaves, respectively. At 0.1 precision level, the sample sizes varied from 5083 to 1054 and 5100 to 1050 leaves for Arinda ® and Sante ® cultivars, respectively. Therefore, the optimum sample sizes for the cultivars, with different resistance levels, were not significantly different. According to the calculated stop lines, the sampling must be continued until cumulative number of eggs + larvae reached to 15-16 or 96-101 individuals at precision levels of 0.25 or 0.1, respectively. The performance of the sampling plan was validated by resampling analysis using resampling for validation of sampling plans software. The sampling plant provided in this study can be used to obtain a rapid estimate of the pest density with minimal effort.

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

Caustics and Rogue Waves in an Optical Sea.

PubMed

Mathis, Amaury; Froehly, Luc; Toenger, Shanti; Dias, Frédéric; Genty, Goëry; Dudley, John M

2015-08-06

There are many examples in physics of systems showing rogue wave behaviour, the generation of high amplitude events at low probability. Although initially studied in oceanography, rogue waves have now been seen in many other domains, with particular recent interest in optics. Although most studies in optics have focussed on how nonlinearity can drive rogue wave emergence, purely linear effects have also been shown to induce extreme wave amplitudes. In this paper, we report a detailed experimental study of linear rogue waves in an optical system, using a spatial light modulator to impose random phase structure on a coherent optical field. After free space propagation, different random intensity patterns are generated, including partially-developed speckle, a broadband caustic network, and an intermediate pattern with characteristics of both speckle and caustic structures. Intensity peaks satisfying statistical criteria for rogue waves are seen especially in the case of the caustic network, and are associated with broader spatial spectra. In addition, the electric field statistics of the intermediate pattern shows properties of an "optical sea" with near-Gaussian statistics in elevation amplitude, and trough-to-crest statistics that are near-Rayleigh distributed but with an extended tail where a number of rogue wave events are observed.

Caustics and Rogue Waves in an Optical Sea

PubMed Central

Mathis, Amaury; Froehly, Luc; Toenger, Shanti; Dias, Frédéric; Genty, Goëry; Dudley, John M.

2015-01-01

There are many examples in physics of systems showing rogue wave behaviour, the generation of high amplitude events at low probability. Although initially studied in oceanography, rogue waves have now been seen in many other domains, with particular recent interest in optics. Although most studies in optics have focussed on how nonlinearity can drive rogue wave emergence, purely linear effects have also been shown to induce extreme wave amplitudes. In this paper, we report a detailed experimental study of linear rogue waves in an optical system, using a spatial light modulator to impose random phase structure on a coherent optical field. After free space propagation, different random intensity patterns are generated, including partially-developed speckle, a broadband caustic network, and an intermediate pattern with characteristics of both speckle and caustic structures. Intensity peaks satisfying statistical criteria for rogue waves are seen especially in the case of the caustic network, and are associated with broader spatial spectra. In addition, the electric field statistics of the intermediate pattern shows properties of an “optical sea” with near-Gaussian statistics in elevation amplitude, and trough-to-crest statistics that are near-Rayleigh distributed but with an extended tail where a number of rogue wave events are observed. PMID:26245864

Numerical Modeling Describing the Effects of Heterogeneous Distributions of Asperities on the Quasi-static Evolution of Frictional Slip

NASA Astrophysics Data System (ADS)

Selvadurai, P. A.; Parker, J. M.; Glaser, S. D.

2017-12-01

A better understanding of how slip accumulates along faults and its relation to the breakdown of shear stress is beneficial to many engineering disciplines, such as, hydraulic fracture and understanding induced seismicity (among others). Asperities forming along a preexisting fault resist the relative motion of the two sides of the interface and occur due to the interaction of the surface topographies. Here, we employ a finite element model to simulate circular partial slip asperities along a nominally flat frictional interface. Shear behavior of our partial slip asperity model closely matched the theory described by Cattaneo. The asperity model was employed to simulate a small section of an experimental fault formed between two bodies of polymethyl methacrylate, which consisted of multiple asperities whose location and sizes were directly measured using a pressure sensitive film. The quasi-static shear behavior of the interface was modeled for cyclical loading conditions, and the frictional dissipation (hysteresis) was normal stress dependent. We further our understanding by synthetically modeling lognormal size distributions of asperities that were randomly distributed in space. Synthetic distributions conserved the real contact area and aspects of the size distributions from the experimental case, allowing us to compare the constitutive behaviors based solely on spacing effects. Traction-slip behavior of the experimental interface appears to be considerably affected by spatial clustering of asperities that was not present in the randomly spaced, synthetic asperity distributions. Estimates of bulk interfacial shear stiffness were determined from the constitutive traction-slip behavior and were comparable to the theoretical estimates of multi-contact interfaces with non-interacting asperities.

Snow depth spatial structure from hillslope to basin scale

NASA Astrophysics Data System (ADS)

Deems, J. S.

2017-12-01

Knowledge of spatial patterns of snow accumulation is required for understanding the hydrology, climatology, and ecology of mountain regions. Spatial structure in snow accumulation patterns changes with the scale of observation, a feature that has been characterized using fractal dimensions calculated from lidar-derived snow depth maps: fractal scaling structure at short length scales, with a `scale break' transition to more stochastic patterns at longer separation distances. Previous work has shown that this fractal structure of snow depth distributions differs between sites with different vegetation and terrain characteristics. Forested areas showed a transition to a nearly random spatial distribution at a much shorter lag distance than do unforested sites, enabling a statistical characterization. Alpine areas, however, showed strong spatial structure for a much wider scale range, and were the source of the dominant spatial pattern observable over a wider area. These spatial structure characteristics suggest that the choice of measurement or model resolution (satellite sensor, DEM, field survey point spacing, etc.) will strongly affect the estimates of snow volume or mass, as well as the magnitude of spatial variability. These prior efforts used data sets that were high resolution ( 1 m laser point spacing) but of limited extent ( 1 km2), constraining detection of scale features such as fractal dimension or scale breaks to areas of relatively similar characteristics and to lag distances of under 500 m. New datasets available from the NASA JPL Airborne Snow Observatory (ASO) provide similar resolution but over large areas, enabling assessment of snow spatial structure across an entire watershed, or in similar vegetation or physiography but in different parts of the basin. Additionally, the multi-year ASO time series allows an investigation into the temporal stability of these scale characteristics, within a single snow season and between seasons of strongly varying accumulation totals and patterns. This presentation will explore initial results from this study, using data from the Tuolumne River Basin in California, USA. Fractal scaling characteristics derived from ASO lidar snow depth measurements are examined at the basin scale, as well as in varying topographic and forest cover environments.

Beyond Flory theory: Distribution functions for interacting lattice trees

NASA Astrophysics Data System (ADS)

Rosa, Angelo; Everaers, Ralf

2017-01-01

While Flory theories [J. Isaacson and T. C. Lubensky, J. Physique Lett. 41, 469 (1980), 10.1051/jphyslet:019800041019046900; M. Daoud and J. F. Joanny, J. Physique 42, 1359 (1981), 10.1051/jphys:0198100420100135900; A. M. Gutin et al., Macromolecules 26, 1293 (1993), 10.1021/ma00058a016] provide an extremely useful framework for understanding the behavior of interacting, randomly branching polymers, the approach is inherently limited. Here we use a combination of scaling arguments and computer simulations to go beyond a Gaussian description. We analyze distribution functions for a wide variety of quantities characterizing the tree connectivities and conformations for the four different statistical ensembles, which we have studied numerically in [A. Rosa and R. Everaers, J. Phys. A: Math. Theor. 49, 345001 (2016), 10.1088/1751-8113/49/34/345001 and J. Chem. Phys. 145, 164906 (2016), 10.1063/1.4965827]: (a) ideal randomly branching polymers, (b) 2 d and 3 d melts of interacting randomly branching polymers, (c) 3 d self-avoiding trees with annealed connectivity, and (d) 3 d self-avoiding trees with quenched ideal connectivity. In particular, we investigate the distributions (i) pN(n ) of the weight, n , of branches cut from trees of mass N by severing randomly chosen bonds; (ii) pN(l ) of the contour distances, l , between monomers; (iii) pN(r ⃗) of spatial distances, r ⃗, between monomers, and (iv) pN(r ⃗|l ) of the end-to-end distance of paths of length l . Data for different tree sizes superimpose, when expressed as functions of suitably rescaled observables x ⃗=r ⃗/√{ } or x =l / . In particular, we observe a generalized Kramers relation for the branch weight distributions (i) and find that all the other distributions (ii-iv) are of Redner-des Cloizeaux type, q (x ⃗) =C |x| θexp(-(K|x |) t) . We propose a coherent framework, including generalized Fisher-Pincus relations, relating most of the RdC exponents to each other and to the contact and Flory exponents for interacting trees.

An Effective Post-Filtering Framework for 3-D PET Image Denoising Based on Noise and Sensitivity Characteristics

NASA Astrophysics Data System (ADS)

Kim, Ji Hye; Ahn, Il Jun; Nam, Woo Hyun; Ra, Jong Beom

2015-02-01

Positron emission tomography (PET) images usually suffer from a noticeable amount of statistical noise. In order to reduce this noise, a post-filtering process is usually adopted. However, the performance of this approach is limited because the denoising process is mostly performed on the basis of the Gaussian random noise. It has been reported that in a PET image reconstructed by the expectation-maximization (EM), the noise variance of each voxel depends on its mean value, unlike in the case of Gaussian noise. In addition, we observe that the variance also varies with the spatial sensitivity distribution in a PET system, which reflects both the solid angle determined by a given scanner geometry and the attenuation information of a scanned object. Thus, if a post-filtering process based on the Gaussian random noise is applied to PET images without consideration of the noise characteristics along with the spatial sensitivity distribution, the spatially variant non-Gaussian noise cannot be reduced effectively. In the proposed framework, to effectively reduce the noise in PET images reconstructed by the 3-D ordinary Poisson ordered subset EM (3-D OP-OSEM), we first denormalize an image according to the sensitivity of each voxel so that the voxel mean value can represent its statistical properties reliably. Based on our observation that each noisy denormalized voxel has a linear relationship between the mean and variance, we try to convert this non-Gaussian noise image to a Gaussian noise image. We then apply a block matching 4-D algorithm that is optimized for noise reduction of the Gaussian noise image, and reconvert and renormalize the result to obtain a final denoised image. Using simulated phantom data and clinical patient data, we demonstrate that the proposed framework can effectively suppress the noise over the whole region of a PET image while minimizing degradation of the image resolution.

Spatially-Distributed Cost–Effectiveness Analysis Framework to Control Phosphorus from Agricultural Diffuse Pollution

PubMed Central

Geng, Runzhe; Wang, Xiaoyan; Sharpley, Andrew N.; Meng, Fande

2015-01-01

Best management practices (BMPs) for agricultural diffuse pollution control are implemented at the field or small-watershed scale. However, the benefits of BMP implementation on receiving water quality at multiple spatial is an ongoing challenge. In this paper, we introduce an integrated approach that combines risk assessment (i.e., Phosphorus (P) index), model simulation techniques (Hydrological Simulation Program–FORTRAN), and a BMP placement tool at various scales to identify the optimal location for implementing multiple BMPs and estimate BMP effectiveness after implementation. A statistically significant decrease in nutrient discharge from watersheds is proposed to evaluate the effectiveness of BMPs, strategically targeted within watersheds. Specifically, we estimate two types of cost-effectiveness curves (total pollution reduction and proportion of watersheds improved) for four allocation approaches. Selection of a ‘‘best approach” depends on the relative importance of the two types of effectiveness, which involves a value judgment based on the random/aggregated degree of BMP distribution among and within sub-watersheds. A statistical optimization framework is developed and evaluated in Chaohe River Watershed located in the northern mountain area of Beijing. Results show that BMP implementation significantly (p >0.001) decrease P loss from the watershed. Remedial strategies where BMPs were targeted to areas of high risk of P loss, deceased P loads compared with strategies where BMPs were randomly located across watersheds. Sensitivity analysis indicated that aggregated BMP placement in particular watershed is the most cost-effective scenario to decrease P loss. The optimization approach outlined in this paper is a spatially hierarchical method for targeting nonpoint source controls across a range of scales from field to farm, to watersheds, to regions. Further, model estimates showed targeting at multiple scales is necessary to optimize program efficiency. The integrated model approach described that selects and places BMPs at varying levels of implementation, provides a new theoretical basis and technical guidance for diffuse pollution management in agricultural watersheds. PMID:26313561

Optimal marker placement in hadrontherapy: intelligent optimization strategies with augmented Lagrangian pattern search.

PubMed

Altomare, Cristina; Guglielmann, Raffaella; Riboldi, Marco; Bellazzi, Riccardo; Baroni, Guido

2015-02-01

In high precision photon radiotherapy and in hadrontherapy, it is crucial to minimize the occurrence of geometrical deviations with respect to the treatment plan in each treatment session. To this end, point-based infrared (IR) optical tracking for patient set-up quality assessment is performed. Such tracking depends on external fiducial points placement. The main purpose of our work is to propose a new algorithm based on simulated annealing and augmented Lagrangian pattern search (SAPS), which is able to take into account prior knowledge, such as spatial constraints, during the optimization process. The SAPS algorithm was tested on data related to head and neck and pelvic cancer patients, and that were fitted with external surface markers for IR optical tracking applied for patient set-up preliminary correction. The integrated algorithm was tested considering optimality measures obtained with Computed Tomography (CT) images (i.e. the ratio between the so-called target registration error and fiducial registration error, TRE/FRE) and assessing the marker spatial distribution. Comparison has been performed with randomly selected marker configuration and with the GETS algorithm (Genetic Evolutionary Taboo Search), also taking into account the presence of organs at risk. The results obtained with SAPS highlight improvements with respect to the other approaches: (i) TRE/FRE ratio decreases; (ii) marker distribution satisfies both marker visibility and spatial constraints. We have also investigated how the TRE/FRE ratio is influenced by the number of markers, obtaining significant TRE/FRE reduction with respect to the random configurations, when a high number of markers is used. The SAPS algorithm is a valuable strategy for fiducial configuration optimization in IR optical tracking applied for patient set-up error detection and correction in radiation therapy, showing that taking into account prior knowledge is valuable in this optimization process. Further work will be focused on the computational optimization of the SAPS algorithm toward fast point-of-care applications. Copyright © 2014 Elsevier Inc. All rights reserved.

Spatially-Distributed Cost-Effectiveness Analysis Framework to Control Phosphorus from Agricultural Diffuse Pollution.

PubMed

Geng, Runzhe; Wang, Xiaoyan; Sharpley, Andrew N; Meng, Fande

2015-01-01

Best management practices (BMPs) for agricultural diffuse pollution control are implemented at the field or small-watershed scale. However, the benefits of BMP implementation on receiving water quality at multiple spatial is an ongoing challenge. In this paper, we introduce an integrated approach that combines risk assessment (i.e., Phosphorus (P) index), model simulation techniques (Hydrological Simulation Program-FORTRAN), and a BMP placement tool at various scales to identify the optimal location for implementing multiple BMPs and estimate BMP effectiveness after implementation. A statistically significant decrease in nutrient discharge from watersheds is proposed to evaluate the effectiveness of BMPs, strategically targeted within watersheds. Specifically, we estimate two types of cost-effectiveness curves (total pollution reduction and proportion of watersheds improved) for four allocation approaches. Selection of a ''best approach" depends on the relative importance of the two types of effectiveness, which involves a value judgment based on the random/aggregated degree of BMP distribution among and within sub-watersheds. A statistical optimization framework is developed and evaluated in Chaohe River Watershed located in the northern mountain area of Beijing. Results show that BMP implementation significantly (p >0.001) decrease P loss from the watershed. Remedial strategies where BMPs were targeted to areas of high risk of P loss, deceased P loads compared with strategies where BMPs were randomly located across watersheds. Sensitivity analysis indicated that aggregated BMP placement in particular watershed is the most cost-effective scenario to decrease P loss. The optimization approach outlined in this paper is a spatially hierarchical method for targeting nonpoint source controls across a range of scales from field to farm, to watersheds, to regions. Further, model estimates showed targeting at multiple scales is necessary to optimize program efficiency. The integrated model approach described that selects and places BMPs at varying levels of implementation, provides a new theoretical basis and technical guidance for diffuse pollution management in agricultural watersheds.

Compactness of viral genomes: effect of disperse and localized random mutations

NASA Astrophysics Data System (ADS)

Lošdorfer Božič, Anže; Micheletti, Cristian; Podgornik, Rudolf; Tubiana, Luca

2018-02-01

Genomes of single-stranded RNA viruses have evolved to optimize several concurrent properties. One of them is the architecture of their genomic folds, which must not only feature precise structural elements at specific positions, but also allow for overall spatial compactness. The latter was shown to be disrupted by random synonymous mutations, a disruption which can consequently negatively affect genome encapsidation. In this study, we use three mutation schemes with different degrees of locality to mutate the genomes of phage MS2 and Brome Mosaic virus in order to understand the observed sensitivity of the global compactness of their folds. We find that mutating local stretches of their genomes’ sequence or structure is less disruptive to their compactness compared to inducing randomly-distributed mutations. Our findings are indicative of a mechanism for the conservation of compactness acting on a global scale of the genomes, and have several implications for understanding the interplay between local and global architecture of viral RNA genomes.

First saccadic eye movement reveals persistent attentional guidance by implicit learning

PubMed Central

Jiang, Yuhong V.; Won, Bo-Yeong; Swallow, Khena M.

2014-01-01

Implicit learning about where a visual search target is likely to appear often speeds up search. However, whether implicit learning guides spatial attention or affects post-search decisional processes remains controversial. Using eye tracking, this study provides compelling evidence that implicit learning guides attention. In a training phase, participants often found the target in a high-frequency, “rich” quadrant of the display. When subsequently tested in a phase during which the target was randomly located, participants were twice as likely to direct the first saccadic eye movement to the previously rich quadrant than to any of the sparse quadrants. The attentional bias persisted for nearly 200 trials after training and was unabated by explicit instructions to distribute attention evenly. We propose that implicit learning guides spatial attention but in a qualitatively different manner than goal-driven attention. PMID:24512610

Stochastic description of geometric phase for polarized waves in random media

NASA Astrophysics Data System (ADS)

Boulanger, Jérémie; Le Bihan, Nicolas; Rossetto, Vincent

2013-01-01

We present a stochastic description of multiple scattering of polarized waves in the regime of forward scattering. In this regime, if the source is polarized, polarization survives along a few transport mean free paths, making it possible to measure an outgoing polarization distribution. We consider thin scattering media illuminated by a polarized source and compute the probability distribution function of the polarization on the exit surface. We solve the direct problem using compound Poisson processes on the rotation group SO(3) and non-commutative harmonic analysis. We obtain an exact expression for the polarization distribution which generalizes previous works and design an algorithm solving the inverse problem of estimating the scattering properties of the medium from the measured polarization distribution. This technique applies to thin disordered layers, spatially fluctuating media and multiple scattering systems and is based on the polarization but not on the signal amplitude. We suggest that it can be used as a non-invasive testing method.

Exact extreme-value statistics at mixed-order transitions.

PubMed

Bar, Amir; Majumdar, Satya N; Schehr, Grégory; Mukamel, David

2016-05-01

We study extreme-value statistics for spatially extended models exhibiting mixed-order phase transitions (MOT). These are phase transitions that exhibit features common to both first-order (discontinuity of the order parameter) and second-order (diverging correlation length) transitions. We consider here the truncated inverse distance squared Ising model, which is a prototypical model exhibiting MOT, and study analytically the extreme-value statistics of the domain lengths The lengths of the domains are identically distributed random variables except for the global constraint that their sum equals the total system size L. In addition, the number of such domains is also a fluctuating variable, and not fixed. In the paramagnetic phase, we show that the distribution of the largest domain length l_{max} converges, in the large L limit, to a Gumbel distribution. However, at the critical point (for a certain range of parameters) and in the ferromagnetic phase, we show that the fluctuations of l_{max} are governed by novel distributions, which we compute exactly. Our main analytical results are verified by numerical simulations.