Tsetse Fly (G.f. fuscipes) Distribution in the Lake Victoria Basin of Uganda

PubMed Central

Albert, Mugenyi; Wardrop, Nicola A; Atkinson, Peter M; Torr, Steve J; Welburn, Susan C

2015-01-01

Tsetse flies transmit trypanosomes, the causative agent of human and animal African trypanosomiasis. The tsetse vector is extensively distributed across sub-Saharan Africa. Trypanosomiasis maintenance is determined by the interrelationship of three elements: vertebrate host, parasite and the vector responsible for transmission. Mapping the distribution and abundance of tsetse flies assists in predicting trypanosomiasis distributions and developing rational strategies for disease and vector control. Given scarce resources to carry out regular full scale field tsetse surveys to up-date existing tsetse maps, there is a need to devise inexpensive means for regularly obtaining dependable area-wide tsetse data to guide control activities. In this study we used spatial epidemiological modelling techniques (logistic regression) involving 5000 field-based tsetse-data (G. f. fuscipes) points over an area of 40,000 km2, with satellite-derived environmental surrogates composed of precipitation, temperature, land cover, normalised difference vegetation index (NDVI) and elevation at the sub-national level. We used these extensive tsetse data to analyse the relationships between presence of tsetse (G. f. fuscipes) and environmental variables. The strength of the results was enhanced through the application of a spatial autologistic regression model (SARM). Using the SARM we showed that the probability of tsetse presence increased with proportion of forest cover and riverine vegetation. The key outputs are a predictive tsetse distribution map for the Lake Victoria basin of Uganda and an improved understanding of the association between tsetse presence and environmental variables. The predicted spatial distribution of tsetse in the Lake Victoria basin of Uganda will provide significant new information to assist with the spatial targeting of tsetse and trypanosomiasis control. PMID:25875201

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.

A distributed air index based on maximum boundary rectangle over grid-cells for wireless non-flat spatial data broadcast.

PubMed

Im, Seokjin; Choi, JinTak

2014-06-17

In the pervasive computing environment using smart devices equipped with various sensors, a wireless data broadcasting system for spatial data items is a natural way to efficiently provide a location dependent information service, regardless of the number of clients. A non-flat wireless broadcast system can support the clients in accessing quickly their preferred data items by disseminating the preferred data items more frequently than regular data on the wireless channel. To efficiently support the processing of spatial window queries in a non-flat wireless data broadcasting system, we propose a distributed air index based on a maximum boundary rectangle (MaxBR) over grid-cells (abbreviated DAIM), which uses MaxBRs for filtering out hot data items on the wireless channel. Unlike the existing index that repeats regular data items in close proximity to hot items at same frequency as hot data items in a broadcast cycle, DAIM makes it possible to repeat only hot data items in a cycle and reduces the length of the broadcast cycle. Consequently, DAIM helps the clients access the desired items quickly, improves the access time, and reduces energy consumption. In addition, a MaxBR helps the clients decide whether they have to access regular data items or not. Simulation studies show the proposed DAIM outperforms existing schemes with respect to the access time and energy consumption.

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.

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.

Discrete Regularization for Calibration of Geologic Facies Against Dynamic Flow Data

NASA Astrophysics Data System (ADS)

Khaninezhad, Mohammad-Reza; Golmohammadi, Azarang; Jafarpour, Behnam

2018-04-01

Subsurface flow model calibration involves many more unknowns than measurements, leading to ill-posed problems with nonunique solutions. To alleviate nonuniqueness, the problem is regularized by constraining the solution space using prior knowledge. In certain sedimentary environments, such as fluvial systems, the contrast in hydraulic properties of different facies types tends to dominate the flow and transport behavior, making the effect of within facies heterogeneity less significant. Hence, flow model calibration in those formations reduces to delineating the spatial structure and connectivity of different lithofacies types and their boundaries. A major difficulty in calibrating such models is honoring the discrete, or piecewise constant, nature of facies distribution. The problem becomes more challenging when complex spatial connectivity patterns with higher-order statistics are involved. This paper introduces a novel formulation for calibration of complex geologic facies by imposing appropriate constraints to recover plausible solutions that honor the spatial connectivity and discreteness of facies models. To incorporate prior connectivity patterns, plausible geologic features are learned from available training models. This is achieved by learning spatial patterns from training data, e.g., k-SVD sparse learning or the traditional Principal Component Analysis. Discrete regularization is introduced as a penalty functions to impose solution discreteness while minimizing the mismatch between observed and predicted data. An efficient gradient-based alternating directions algorithm is combined with variable splitting to minimize the resulting regularized nonlinear least squares objective function. Numerical results show that imposing learned facies connectivity and discreteness as regularization functions leads to geologically consistent solutions that improve facies calibration quality.

Lp-Norm Regularization in Volumetric Imaging of Cardiac Current Sources

PubMed Central

Rahimi, Azar; Xu, Jingjia; Wang, Linwei

2013-01-01

Advances in computer vision have substantially improved our ability to analyze the structure and mechanics of the heart. In comparison, our ability to observe and analyze cardiac electrical activities is much limited. The progress to computationally reconstruct cardiac current sources from noninvasive voltage data sensed on the body surface has been hindered by the ill-posedness and the lack of a unique solution of the reconstruction problem. Common L2- and L1-norm regularizations tend to produce a solution that is either too diffused or too scattered to reflect the complex spatial structure of current source distribution in the heart. In this work, we propose a general regularization with Lp-norm (1 < p < 2) constraint to bridge the gap and balance between an overly smeared and overly focal solution in cardiac source reconstruction. In a set of phantom experiments, we demonstrate the superiority of the proposed Lp-norm method over its L1 and L2 counterparts in imaging cardiac current sources with increasing extents. Through computer-simulated and real-data experiments, we further demonstrate the feasibility of the proposed method in imaging the complex structure of excitation wavefront, as well as current sources distributed along the postinfarction scar border. This ability to preserve the spatial structure of source distribution is important for revealing the potential disruption to the normal heart excitation. PMID:24348735

Pattern-Based Inverse Modeling for Characterization of Subsurface Flow Models with Complex Geologic Heterogeneity

NASA Astrophysics Data System (ADS)

Golmohammadi, A.; Jafarpour, B.; M Khaninezhad, M. R.

2017-12-01

Calibration of heterogeneous subsurface flow models leads to ill-posed nonlinear inverse problems, where too many unknown parameters are estimated from limited response measurements. When the underlying parameters form complex (non-Gaussian) structured spatial connectivity patterns, classical variogram-based geostatistical techniques cannot describe the underlying connectivity patterns. Modern pattern-based geostatistical methods that incorporate higher-order spatial statistics are more suitable for describing such complex spatial patterns. Moreover, when the underlying unknown parameters are discrete (geologic facies distribution), conventional model calibration techniques that are designed for continuous parameters cannot be applied directly. In this paper, we introduce a novel pattern-based model calibration method to reconstruct discrete and spatially complex facies distributions from dynamic flow response data. To reproduce complex connectivity patterns during model calibration, we impose a feasibility constraint to ensure that the solution follows the expected higher-order spatial statistics. For model calibration, we adopt a regularized least-squares formulation, involving data mismatch, pattern connectivity, and feasibility constraint terms. Using an alternating directions optimization algorithm, the regularized objective function is divided into a continuous model calibration problem, followed by mapping the solution onto the feasible set. The feasibility constraint to honor the expected spatial statistics is implemented using a supervised machine learning algorithm. The two steps of the model calibration formulation are repeated until the convergence criterion is met. Several numerical examples are used to evaluate the performance of the developed method.

A composite likelihood approach for spatially correlated survival data

PubMed Central

Paik, Jane; Ying, Zhiliang

2013-01-01

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

A composite likelihood approach for spatially correlated survival data.

PubMed

Paik, Jane; Ying, Zhiliang

2013-01-01

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

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.

Minimum Fisher regularization of image reconstruction for infrared imaging bolometer on HL-2A

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

Gao, J. M.; Liu, Y.; Li, W.

2013-09-15

An infrared imaging bolometer diagnostic has been developed recently for the HL-2A tokamak to measure the temporal and spatial distribution of plasma radiation. The three-dimensional tomography, reduced to a two-dimensional problem by the assumption of plasma radiation toroidal symmetry, has been performed. A three-dimensional geometry matrix is calculated with the one-dimensional pencil beam approximation. The solid angles viewed by the detector elements are taken into account in defining the chord brightness. And the local plasma emission is obtained by inverting the measured brightness with the minimum Fisher regularization method. A typical HL-2A plasma radiation model was chosen to optimize amore » regularization parameter on the criterion of generalized cross validation. Finally, this method was applied to HL-2A experiments, demonstrating the plasma radiated power density distribution in limiter and divertor discharges.« less

Spatial distribution patterns of soil mite communities and their relationships with edaphic factors in a 30-year tillage cornfield in northeast China.

PubMed

Liu, Jie; Gao, Meixiang; Liu, Jinwen; Guo, Yuxi; Liu, Dong; Zhu, Xinyu; Wu, Donghui

2018-01-01

Spatial distribution is an important topic in community ecology and a key to understanding the structure and dynamics of populations and communities. However, the available information related to the spatial patterns of soil mite communities in long-term tillage agroecosystems remains insufficient. In this study, we examined the spatial patterns of soil mite communities to explain the spatial relationships between soil mite communities and soil parameters. Soil fauna were sampled three times (August, September and October 2015) at 121 locations arranged regularly within a 400 m × 400 m monitoring plot. Additionally, we estimated the physical and chemical parameters of the same sampling locations. The distribution patterns of the soil mite community and the edaphic parameters were analyzed using a range of geostatistical tools. Moran's I coefficient showed that, during each sampling period, the total abundance of the soil mite communities and the abundance of the dominant mite populations were spatially autocorrelated. The soil mite communities demonstrated clear patchy distribution patterns within the study plot. These patterns were sampling period-specific. Cross-semivariograms showed both negative and positive cross-correlations between soil mite communities and environmental factors. Mantel tests showed a significant and positive relationship between soil mite community and soil organic matter and soil pH only in August. This study demonstrated that in the cornfield, the soil mite distribution exhibited strong or moderate spatial dependence, and the mites formed patches with sizes less than one hundred meters. In addition, in this long-term tillage agroecosystem, soil factors had less influence on the observed pattern of soil mite communities. Further experiments that take into account human activity and spatial factors should be performed to study the factors that drive the spatial distribution of soil microarthropods.

Modelling topographic potential for erosion and deposition using GIS

Treesearch

Helena Mitasova; Louis R. Iverson

1996-01-01

Modelling of erosion and deposition in complex terrain within a geographical information system (GIS) requires a high resolution digital elevation model (DEM), reliable estimation of topographic parameters, and formulation of erosion models adequate for digital representation of spatially distributed parameters. Regularized spline with tension was integrated within a...

Kolmogorov-Smirnov test for spatially correlated data

USGS Publications Warehouse

Olea, R.A.; Pawlowsky-Glahn, V.

2009-01-01

The Kolmogorov-Smirnov test is a convenient method for investigating whether two underlying univariate probability distributions can be regarded as undistinguishable from each other or whether an underlying probability distribution differs from a hypothesized distribution. Application of the test requires that the sample be unbiased and the outcomes be independent and identically distributed, conditions that are violated in several degrees by spatially continuous attributes, such as topographical elevation. A generalized form of the bootstrap method is used here for the purpose of modeling the distribution of the statistic D of the Kolmogorov-Smirnov test. The innovation is in the resampling, which in the traditional formulation of bootstrap is done by drawing from the empirical sample with replacement presuming independence. The generalization consists of preparing resamplings with the same spatial correlation as the empirical sample. This is accomplished by reading the value of unconditional stochastic realizations at the sampling locations, realizations that are generated by simulated annealing. The new approach was tested by two empirical samples taken from an exhaustive sample closely following a lognormal distribution. One sample was a regular, unbiased sample while the other one was a clustered, preferential sample that had to be preprocessed. Our results show that the p-value for the spatially correlated case is always larger that the p-value of the statistic in the absence of spatial correlation, which is in agreement with the fact that the information content of an uncorrelated sample is larger than the one for a spatially correlated sample of the same size. ?? Springer-Verlag 2008.

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.

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.

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.

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.

Direct Reconstruction of CT-Based Attenuation Correction Images for PET With Cluster-Based Penalties

NASA Astrophysics Data System (ADS)

Kim, Soo Mee; Alessio, Adam M.; De Man, Bruno; Kinahan, Paul E.

2017-03-01

Extremely low-dose (LD) CT acquisitions used for PET attenuation correction have high levels of noise and potential bias artifacts due to photon starvation. This paper explores the use of a priori knowledge for iterative image reconstruction of the CT-based attenuation map. We investigate a maximum a posteriori framework with cluster-based multinomial penalty for direct iterative coordinate decent (dICD) reconstruction of the PET attenuation map. The objective function for direct iterative attenuation map reconstruction used a Poisson log-likelihood data fit term and evaluated two image penalty terms of spatial and mixture distributions. The spatial regularization is based on a quadratic penalty. For the mixture penalty, we assumed that the attenuation map may consist of four material clusters: air + background, lung, soft tissue, and bone. Using simulated noisy sinogram data, dICD reconstruction was performed with different strengths of the spatial and mixture penalties. The combined spatial and mixture penalties reduced the root mean squared error (RMSE) by roughly two times compared with a weighted least square and filtered backprojection reconstruction of CT images. The combined spatial and mixture penalties resulted in only slightly lower RMSE compared with a spatial quadratic penalty alone. For direct PET attenuation map reconstruction from ultra-LD CT acquisitions, the combination of spatial and mixture penalties offers regularization of both variance and bias and is a potential method to reconstruct attenuation maps with negligible patient dose. The presented results, using a best-case histogram suggest that the mixture penalty does not offer a substantive benefit over conventional quadratic regularization and diminishes enthusiasm for exploring future application of the mixture penalty.

DEM generation from contours and a low-resolution DEM

NASA Astrophysics Data System (ADS)

Li, Xinghua; Shen, Huanfeng; Feng, Ruitao; Li, Jie; Zhang, Liangpei

2017-12-01

A digital elevation model (DEM) is a virtual representation of topography, where the terrain is established by the three-dimensional co-ordinates. In the framework of sparse representation, this paper investigates DEM generation from contours. Since contours are usually sparsely distributed and closely related in space, sparse spatial regularization (SSR) is enforced on them. In order to make up for the lack of spatial information, another lower spatial resolution DEM from the same geographical area is introduced. In this way, the sparse representation implements the spatial constraints in the contours and extracts the complementary information from the auxiliary DEM. Furthermore, the proposed method integrates the advantage of the unbiased estimation of kriging. For brevity, the proposed method is called the kriging and sparse spatial regularization (KSSR) method. The performance of the proposed KSSR method is demonstrated by experiments in Shuttle Radar Topography Mission (SRTM) 30 m DEM and Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) 30 m global digital elevation model (GDEM) generation from the corresponding contours and a 90 m DEM. The experiments confirm that the proposed KSSR method outperforms the traditional kriging and SSR methods, and it can be successfully used for DEM generation from contours.

Percolation of spatially constraint networks

NASA Astrophysics Data System (ADS)

Li, Daqing; Li, Guanliang; Kosmidis, Kosmas; Stanley, H. E.; Bunde, Armin; Havlin, Shlomo

2011-03-01

We study how spatial constraints are reflected in the percolation properties of networks embedded in one-dimensional chains and two-dimensional lattices. We assume long-range connections between sites on the lattice where two sites at distance r are chosen to be linked with probability p(r)~r-δ. Similar distributions have been found in spatially embedded real networks such as social and airline networks. We find that for networks embedded in two dimensions, with 2<δ<4, the percolation properties show new intermediate behavior different from mean field, with critical exponents that depend on δ. For δ<2, the percolation transition belongs to the universality class of percolation in Erdös-Rényi networks (mean field), while for δ>4 it belongs to the universality class of percolation in regular lattices. For networks embedded in one dimension, we find that, for δ<1, the percolation transition is mean field. For 1<δ<2, the critical exponents depend on δ, while for δ>2 there is no percolation transition as in regular linear chains.

Calibrating electromagnetic induction conductivities with time-domain reflectometry measurements

NASA Astrophysics Data System (ADS)

Dragonetti, Giovanna; Comegna, Alessandro; Ajeel, Ali; Piero Deidda, Gian; Lamaddalena, Nicola; Rodriguez, Giuseppe; Vignoli, Giulio; Coppola, Antonio

2018-02-01

This paper deals with the issue of monitoring the spatial distribution of bulk electrical conductivity, σb, in the soil root zone by using electromagnetic induction (EMI) sensors under different water and salinity conditions. To deduce the actual distribution of depth-specific σb from EMI apparent electrical conductivity (ECa) measurements, we inverted the data by using a regularized 1-D inversion procedure designed to manage nonlinear multiple EMI-depth responses. The inversion technique is based on the coupling of the damped Gauss-Newton method with truncated generalized singular value decomposition (TGSVD). The ill-posedness of the EMI data inversion is addressed by using a sharp stabilizer term in the objective function. This specific stabilizer promotes the reconstruction of blocky targets, thereby contributing to enhance the spatial resolution of the EMI results in the presence of sharp boundaries (otherwise smeared out after the application of more standard Occam-like regularization strategies searching for smooth solutions). Time-domain reflectometry (TDR) data are used as ground-truth data for calibration of the inversion results. An experimental field was divided into four transects 30 m long and 2.8 m wide, cultivated with green bean, and irrigated with water at two different salinity levels and using two different irrigation volumes. Clearly, this induces different salinity and water contents within the soil profiles. For each transect, 26 regularly spaced monitoring soundings (1 m apart) were selected for the collection of (i) Geonics EM-38 and (ii) Tektronix reflectometer data. Despite the original discrepancies in the EMI and TDR data, we found a significant correlation of the means and standard deviations of the two data series; in particular, after a low-pass spatial filtering of the TDR data. Based on these findings, this paper introduces a novel methodology to calibrate EMI-based electrical conductivities via TDR direct measurements. This calibration strategy consists of a linear mapping of the original inversion results into a new conductivity spatial distribution with the coefficients of the transformation uniquely based on the statistics of the two original measurement datasets (EMI and TDR conductivities).

Spatial Distribution of Socioeconomic Characteristics in Rural’s Java: A Case from Three Different Rural Areas in Central Java

NASA Astrophysics Data System (ADS)

Rudiarto, I.; Handayani, W.; Wijaya, H. B.; Insani, T. D.

2018-02-01

The intention of this paper is to combine the socio economic development into spatial aspect with the fact that the divided sub study areas are differed in its socio-economic characteristic. The research was conducted in three different rural areas, i.e.; coastal area in Sayung sub district - Demak Regency, plain area in Delanggu sub district - Klaten Regency, and mountain area in Kledung sub district - Temanggung regency. Spatial interpolation technique has been applied in order to identify the spatial distribution of socioeconomic data. The results show that socioeconomic characteristic in plain area and coastal area is more varied and regularly distributed as compared to the mountain area. Educated people are less found in the plain area while in coastal and mountain area the condition is better. Coastal area is identified as the prone area to the disaster issues and therefore socioeconomically vulnerable. The result of this research is very important to the development policies that need to undertake regarding to socioeconomic development in each associated location.

Spatial mapping of dynamic cerebral autoregulation by multichannel near-infrared spectroscopy in high-grade carotid artery disease

NASA Astrophysics Data System (ADS)

Reinhard, Matthias; Schumacher, F. Konrad; Rutsch, Sebastian; Oeinck, Maximilian; Timmer, Jens; Mader, Irina; Schelter, Björn; Weiller, Cornelius; Kaller, Christoph P.

2014-09-01

The exact spatial distribution of impaired cerebral autoregulation in carotid artery disease is unknown. In this pilot study, we present a new approach of multichannel near-infrared spectroscopy (mcNIRS) for noninvasive spatial mapping of dynamic autoregulation in carotid artery disease. In 15 patients with unilateral severe carotid artery stenosis or occlusion, cortical hemodynamics in the bilateral frontal cortex were assessed from changes in oxyhemoglobin concentration using 52-channel NIRS (spatial resolution ˜2 cm). Dynamic autoregulation was graded by the phase shift between respiratory-induced 0.1 Hz oscillations of blood pressure and oxyhemoglobin. Ten of 15 patients showed regular phase values in the expected (patho) physiological range. Five patients had clearly outlying irregular phase values mostly due to artifacts. In patients with a regular phase pattern, a significant side-to-side difference of dynamic autoregulation was observed for the cortical border zone area between the middle and anterior cerebral artery (p<0.05). In conclusion, dynamic cerebral autoregulation can be spatially assessed from slow hemodynamic oscillations with mcNIRS. In high-grade carotid artery disease, cortical dynamic autoregulation is affected mostly in the vascular border zone. Spatial mapping of dynamic autoregulation may serve as a powerful tool for identifying brain regions at specific risks for hemodynamic infarction.

A spatially adaptive total variation regularization method for electrical resistance tomography

NASA Astrophysics Data System (ADS)

Song, Xizi; Xu, Yanbin; Dong, Feng

2015-12-01

The total variation (TV) regularization method has been used to solve the ill-posed inverse problem of electrical resistance tomography (ERT), owing to its good ability to preserve edges. However, the quality of the reconstructed images, especially in the flat region, is often degraded by noise. To optimize the regularization term and the regularization factor according to the spatial feature and to improve the resolution of reconstructed images, a spatially adaptive total variation (SATV) regularization method is proposed. A kind of effective spatial feature indicator named difference curvature is used to identify which region is a flat or edge region. According to different spatial features, the SATV regularization method can automatically adjust both the regularization term and regularization factor. At edge regions, the regularization term is approximate to the TV functional to preserve the edges; in flat regions, it is approximate to the first-order Tikhonov (FOT) functional to make the solution stable. Meanwhile, the adaptive regularization factor determined by the spatial feature is used to constrain the regularization strength of the SATV regularization method for different regions. Besides, a numerical scheme is adopted for the implementation of the second derivatives of difference curvature to improve the numerical stability. Several reconstruction image metrics are used to quantitatively evaluate the performance of the reconstructed results. Both simulation and experimental results indicate that, compared with the TV (mean relative error 0.288, mean correlation coefficient 0.627) and FOT (mean relative error 0.295, mean correlation coefficient 0.638) regularization methods, the proposed SATV (mean relative error 0.259, mean correlation coefficient 0.738) regularization method can endure a relatively high level of noise and improve the resolution of reconstructed images.

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.

Complementary Density Measurements for the 200W Busek Hall Thruster (PREPRINT)

DTIC Science & Technology

2006-07-12

Hall thruster are presented. Both a Faraday probe and microwave interferometry system are used to examine the density distribution of the thruster plasma at regular spatial intervals. Both experiments are performed in situ under the same conditions. The resulting density distributions obtained from both experiments are presented. Advantages and uncertainties of both methods are presented, as well as how comparison between the two data sets can account for the uncertainties of each method

[Interdependence of plankton spatial distribution and plancton biomass temporal oscillations: mathematical simulation].

PubMed

Medvedinskiĭ, A B; Tikhonova, I A; Li, B L; Malchow, H

2003-01-01

The dynamics of aquatic biological communities in a patchy environment is of great interest in respect to interrelations between phenomena at various spatial and time scales. To study the complex plankton dynamics in relation to variations of such a biologically essential parameter as the fish predation rate, we use a simple reaction-diffusion model of trophic interactions between phytoplankton, zooplankton, and fish. We suggest that plankton is distributed between two habitats one of which is fish-free due to hydrological inhomogeneity, while the other is fish-populated. We show that temporal variations in the fish predation rate do not violate the strong correspondence between the character of spatial distribution of plankton and changes of plankton biomass in time: regular temporal oscillations of plankton biomass correspond to large-scale plankton patches, while chaotic oscillations correspond to small-scale plankton patterns. As in the case of the constant fish predation rate, the chaotic plankton dynamics is characterized by coexistence of the chaotic attractor and limit cycle.

Image-guided spatial localization of heterogeneous compartments for magnetic resonance

PubMed Central

An, Li; Shen, Jun

2015-01-01

Purpose: Image-guided localization SPectral Localization Achieved by Sensitivity Heterogeneity (SPLASH) allows rapid measurement of signals from irregularly shaped anatomical compartments without using phase encoding gradients. Here, the authors propose a novel method to address the issue of heterogeneous signal distribution within the localized compartments. Methods: Each compartment was subdivided into multiple subcompartments and their spectra were solved by Tikhonov regularization to enforce smoothness within each compartment. The spectrum of a given compartment was generated by combining the spectra of the components of that compartment. The proposed method was first tested using Monte Carlo simulations and then applied to reconstructing in vivo spectra from irregularly shaped ischemic stroke and normal tissue compartments. Results: Monte Carlo simulations demonstrate that the proposed regularized SPLASH method significantly reduces localization and metabolite quantification errors. In vivo results show that the intracompartment regularization results in ∼40% reduction of error in metabolite quantification. Conclusions: The proposed method significantly reduces localization errors and metabolite quantification errors caused by intracompartment heterogeneous signal distribution. PMID:26328977

High-resolution seismic data regularization and wavefield separation

NASA Astrophysics Data System (ADS)

Cao, Aimin; Stump, Brian; DeShon, Heather

2018-04-01

We present a new algorithm, non-equispaced fast antileakage Fourier transform (NFALFT), for irregularly sampled seismic data regularization. Synthetic tests from 1-D to 5-D show that the algorithm may efficiently remove leaked energy in the frequency wavenumber domain, and its corresponding regularization process is accurate and fast. Taking advantage of the NFALFT algorithm, we suggest a new method (wavefield separation) for the detection of the Earth's inner core shear wave with irregularly distributed seismic arrays or networks. All interfering seismic phases that propagate along the minor arc are removed from the time window around the PKJKP arrival. The NFALFT algorithm is developed for seismic data, but may also be used for other irregularly sampled temporal or spatial data processing.

Estimation and impact assessment of input and parameter uncertainty in predicting groundwater flow with a fully distributed model

NASA Astrophysics Data System (ADS)

Touhidul Mustafa, Syed Md.; Nossent, Jiri; Ghysels, Gert; Huysmans, Marijke

2017-04-01

Transient numerical groundwater flow models have been used to understand and forecast groundwater flow systems under anthropogenic and climatic effects, but the reliability of the predictions is strongly influenced by different sources of uncertainty. Hence, researchers in hydrological sciences are developing and applying methods for uncertainty quantification. Nevertheless, spatially distributed flow models pose significant challenges for parameter and spatially distributed input estimation and uncertainty quantification. In this study, we present a general and flexible approach for input and parameter estimation and uncertainty analysis of groundwater models. The proposed approach combines a fully distributed groundwater flow model (MODFLOW) with the DiffeRential Evolution Adaptive Metropolis (DREAM) algorithm. To avoid over-parameterization, the uncertainty of the spatially distributed model input has been represented by multipliers. The posterior distributions of these multipliers and the regular model parameters were estimated using DREAM. The proposed methodology has been applied in an overexploited aquifer in Bangladesh where groundwater pumping and recharge data are highly uncertain. The results confirm that input uncertainty does have a considerable effect on the model predictions and parameter distributions. Additionally, our approach also provides a new way to optimize the spatially distributed recharge and pumping data along with the parameter values under uncertain input conditions. It can be concluded from our approach that considering model input uncertainty along with parameter uncertainty is important for obtaining realistic model predictions and a correct estimation of the uncertainty bounds.

Existence, uniqueness and regularity of a time-periodic probability density distribution arising in a sedimentation-diffusion problem

NASA Technical Reports Server (NTRS)

Nitsche, Ludwig C.; Nitsche, Johannes M.; Brenner, Howard

1988-01-01

The sedimentation and diffusion of a nonneutrally buoyant Brownian particle in vertical fluid-filled cylinder of finite length which is instantaneously inverted at regular intervals are investigated analytically. A one-dimensional convective-diffusive equation is derived to describe the temporal and spatial evolution of the probability density; a periodicity condition is formulated; the applicability of Fredholm theory is established; and the parameter-space regions are determined within which the existence and uniqueness of solutions are guaranteed. Numerical results for sample problems are presented graphically and briefly characterized.

Spatial resolution properties of motion-compensated tomographic image reconstruction methods.

PubMed

Chun, Se Young; Fessler, Jeffrey A

2012-07-01

Many motion-compensated image reconstruction (MCIR) methods have been proposed to correct for subject motion in medical imaging. MCIR methods incorporate motion models to improve image quality by reducing motion artifacts and noise. This paper analyzes the spatial resolution properties of MCIR methods and shows that nonrigid local motion can lead to nonuniform and anisotropic spatial resolution for conventional quadratic regularizers. This undesirable property is akin to the known effects of interactions between heteroscedastic log-likelihoods (e.g., Poisson likelihood) and quadratic regularizers. This effect may lead to quantification errors in small or narrow structures (such as small lesions or rings) of reconstructed images. This paper proposes novel spatial regularization design methods for three different MCIR methods that account for known nonrigid motion. We develop MCIR regularization designs that provide approximately uniform and isotropic spatial resolution and that match a user-specified target spatial resolution. Two-dimensional PET simulations demonstrate the performance and benefits of the proposed spatial regularization design methods.

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.

The collagen structure of equine articular cartilage characterized using polarization-sensitive optical coherence tomography and non-linear microscopy

NASA Astrophysics Data System (ADS)

Mansfield, Jessica C.; Ugryumova, Nadya; Knapp, Karen M.; Matcher, Stephen J.

2006-09-01

Equine articular cartilage has been imaged using both polarization-sensitive optical coherence tomography (PS-OCT) and non-linear microscopy. PS-OCT has been used to spatially map the birefringence in the cartilage and we have found that in the vicinity of the lesion the images display a characteristic disruption in the regular birefringence bands shown by normal cartilage. We also note that significant (e.g. x2) variations in the apparent birefringence of samples taken from young (18 month) animals that otherwise appear visually homogeneous are found over spatial scales of a few millimeters. We have also imaged the cartilage using non-linear microscopy and compare the scans taken with second harmonic generation (SHG) light and the two photon fluorescence (TPF) light. SHG images collected using 800 nm excitation reveals the spatial distribution of collagen fibers, whilst TPF images clearly shows the distribution of intracellular and pericellular fluorophores.

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.

Uncertainties and implications of applying aggregated data for spatial modelling of atmospheric ammonia emissions.

PubMed

Hellsten, S; Dragosits, U; Place, C J; Dore, A J; Tang, Y S; Sutton, M A

2018-05-09

Ammonia emissions vary greatly at a local scale, and effects (eutrophication, acidification) occur primarily close to sources. Therefore it is important that spatially distributed emission estimates are located as accurately as possible. The main source of ammonia emissions is agriculture, and therefore agricultural survey statistics are the most important input data to an ammonia emission inventory alongside per activity estimates of emission potential. In the UK, agricultural statistics are collected at farm level, but are aggregated to parish level, NUTS-3 level or regular grid resolution for distribution to users. In this study, the Modifiable Areal Unit Problem (MAUP), associated with such amalgamation, is investigated in the context of assessing the spatial distribution of ammonia sources for emission inventories. England was used as a test area to study the effects of the MAUP. Agricultural survey data at farm level (point data) were obtained under license and amalgamated to different areal units or zones: regular 1-km, 5-km, 10-km grids and parish level, before they were imported into the emission model. The results of using the survey data at different levels of amalgamation were assessed to estimate the effects of the MAUP on the spatial inventory. The analysis showed that the size and shape of aggregation zones applied to the farm-level agricultural statistics strongly affect the location of the emissions estimated by the model. If the zones are too small, this may result in false emission "hot spots", i.e., artificially high emission values that are in reality not confined to the zone to which they are allocated. Conversely, if the zones are too large, detail may be lost and emissions smoothed out, which may give a false impression of the spatial patterns and magnitude of emissions in those zones. The results of the study indicate that the MAUP has a significant effect on the location and local magnitude of emissions in spatial inventories where amalgamated, zonal data are used. Copyright © 2018 Elsevier Ltd. All rights reserved.

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

PubMed

Kumar, Dushyant; Hariharan, Hari; Faizy, Tobias D; Borchert, Patrick; Siemonsen, Susanne; Fiehler, Jens; Reddy, Ravinder; Sedlacik, Jan

2018-05-12

We present a computationally feasible and iterative multi-voxel spatially regularized algorithm for myelin water fraction (MWF) reconstruction. This method utilizes 3D spatial correlations present in anatomical/pathological tissues and underlying B1 + -inhomogeneity or flip angle inhomogeneity to enhance the noise robustness of the reconstruction while intrinsically accounting for stimulated echo contributions using T2-distribution data alone. Simulated data and in vivo data acquired using 3D non-selective multi-echo spin echo (3DNS-MESE) were used to compare the reconstruction quality of the proposed approach against those of the popular algorithm (the method by Prasloski et al.) and our previously proposed 2D multi-slice spatial regularization spatial regularization approach. We also investigated whether the inter-sequence correlations and agreements improved as a result of the proposed approach. MWF-quantifications from two sequences, 3DNS-MESE vs 3DNS-gradient and spin echo (3DNS-GRASE), were compared for both reconstruction approaches to assess correlations and agreements between inter-sequence MWF-value pairs. MWF values from whole-brain data of six volunteers and two multiple sclerosis patients are being reported as well. In comparison with competing approaches such as Prasloski's method or our previously proposed 2D multi-slice spatial regularization method, the proposed method showed better agreements with simulated truths using regression analyses and Bland-Altman analyses. For 3DNS-MESE data, MWF-maps reconstructed using the proposed algorithm provided better depictions of white matter structures in subcortical areas adjoining gray matter which agreed more closely with corresponding contrasts on T2-weighted images than MWF-maps reconstructed with the method by Prasloski et al. We also achieved a higher level of correlations and agreements between inter-sequence (3DNS-MESE vs 3DNS-GRASE) MWF-value pairs. The proposed algorithm provides more noise-robust fits to T2-decay data and improves MWF-quantifications in white matter structures especially in the sub-cortical white matter and major white matter tract regions. Copyright © 2018 Elsevier Inc. All rights reserved.

Judging The Effectiveness Of Wool Combing By The Entropy Of The Images Of Wool Slivers

NASA Astrophysics Data System (ADS)

Rodrigues, F. Carvalho; Carvalho, Fernando D.; Peixoto, J. Pinto; Silva, M. Santos

1989-04-01

In general it can be said that the textile industry endeavours to render a bunch of fibers chaotically distributed in space into an ordered spatial distribution. This fact is independent of the nature the fibers, i.e., the aim of getting into higher order states in the spatial distribution of the fibers dictates different industrial processes depending on whether the fibers are wool, cotton or man made but the all effect is centred on obtaining at every step of any of the processes a more ordered state regarding the spatial distribution of the fibers. Thinking about the textile processes as a method of getting order out of chaos, the concept of entropy appears as the most appropriate judging parameter on the effectiveness of a step in the chain of an industrial process to produce a regular textile. In fact, entropy is the hidden parameter not only for the textile industry but also for the non woven and paper industrial processes. It happens that in these industries the state of order is linked with the spatial distribution of fibers and to obtain an image of a spatial distribution is an easy matter. To compute the image entropy from the grey level distribution requires only the use of the Shannon formula. In this paper to illustrate the usefulness of employing the entropy of an image concept to textiles the evolution of the entropy of wool slivers along the combing process is matched against the state of parallelization of the fibbers along the seven steps as measured by the existing method. The advantages of the entropy method over the previous method based on diffraction is also demonstrated.

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.

Measurement of the spatial distribution of atmospheric turbulence with SCINDAR on a mosaic of urban surfaces

NASA Astrophysics Data System (ADS)

Nguyen, K.-L.; Robert, C.; Conan, J.-M.; Mugnier, L. M.; Cohard, J.-M.; Irvine, M.; Lagouarde, J.-P.

2017-09-01

Two experiments of urban scintillometry were performed recently. Their objective was to study the SCINDAR Cn² profiler performance on a composite urbanforest ground. The SCINDAR provides horizontal Cn² profiles with a few hundred meter profile resolution. Several improvements in data processing are reported: the choice of the spatial resolution of the profile and the hyper-parameters adjustment for Cn² regularization. The distributed Cn² values along the optical path are estimated every minute with small error bars. Their non-uniformity is shown to be consistent with the differences of the line of sight to ground and the coverage of the terrain. The SCINDAR data are also in the same order of magnitude with the three scintillometer data that were simultaneously recorded.

Regular subwavelength surface structures induced by femtosecond laser pulses on stainless steel.

PubMed

Qi, Litao; Nishii, Kazuhiro; Namba, Yoshiharu

2009-06-15

In this research, we studied the formation of laser-induced periodic surface structures on the stainless steel surface using femtosecond laser pulses. A 780 nm wavelength femtosecond laser, through a 0.2 mm pinhole aperture for truncating fluence distribution, was focused onto the stainless steel surface. Under different experimental condition, low-spatial-frequency laser-induced periodic surface structures with a period of 526 nm and high-spatial-frequency laser-induced periodic surface structures with a period of 310 nm were obtained. The mechanism of the formation of laser-induced periodic surface structures on the stainless steel surface is discussed.

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

Akiyama, Kazunori; Fish, Vincent L.; Doeleman, Sheperd S.

We propose a new imaging technique for radio and optical/infrared interferometry. The proposed technique reconstructs the image from the visibility amplitude and closure phase, which are standard data products of short-millimeter very long baseline interferometers such as the Event Horizon Telescope (EHT) and optical/infrared interferometers, by utilizing two regularization functions: the ℓ {sub 1}-norm and total variation (TV) of the brightness distribution. In the proposed method, optimal regularization parameters, which represent the sparseness and effective spatial resolution of the image, are derived from data themselves using cross-validation (CV). As an application of this technique, we present simulated observations of M87more » with the EHT based on four physically motivated models. We confirm that ℓ {sub 1} + TV regularization can achieve an optimal resolution of ∼20%–30% of the diffraction limit λ / D {sub max}, which is the nominal spatial resolution of a radio interferometer. With the proposed technique, the EHT can robustly and reasonably achieve super-resolution sufficient to clearly resolve the black hole shadow. These results make it promising for the EHT to provide an unprecedented view of the event-horizon-scale structure in the vicinity of the supermassive black hole in M87 and also the Galactic center Sgr A*.« less

Rapid establishment of a regular distribution of adult tropical Drosophila parasitoids in a multi-patch environment by patch defence behaviour.

PubMed

de Jong, Peter W; Hemerik, Lia; Gort, Gerrit; van Alphen, Jacques J M

2011-01-01

Females of the larval parasitoid of Drosophila, Asobara citri, from sub-Saharan Africa, defend patches with hosts by fighting and chasing conspecific females upon encounter. Females of the closely related, palearctic species Asobara tabida do not defend patches and often search simultaneously in the same patch. The effect of patch defence by A. citri females on their distribution in a multi-patch environment was investigated, and their distributions were compared with those of A. tabida. For both species 20 females were released from two release-points in replicate experiments. Females of A. citri quickly reached a regular distribution across 16 patches, with a small variance/mean ratio per patch. Conversely, A. tabida females initially showed a clumped distribution, and after gradual dispersion, a more Poisson-like distribution across patches resulted (variance/mean ratio was closer to 1 and higher than for A. citri). The dispersion of A. tabida was most probably an effect of exploitation: these parasitoids increasingly made shorter visits to already exploited patches. We briefly discuss hypotheses on the adaptive significance of patch defence behaviour or its absence in the light of differences in the natural history of both parasitoid species, notably the spatial distribution of their hosts.

Markov chain Monte Carlo techniques and spatial-temporal modelling for medical EIT.

PubMed

West, Robert M; Aykroyd, Robert G; Meng, Sha; Williams, Richard A

2004-02-01

Many imaging problems such as imaging with electrical impedance tomography (EIT) can be shown to be inverse problems: that is either there is no unique solution or the solution does not depend continuously on the data. As a consequence solution of inverse problems based on measured data alone is unstable, particularly if the mapping between the solution distribution and the measurements is also nonlinear as in EIT. To deliver a practical stable solution, it is necessary to make considerable use of prior information or regularization techniques. The role of a Bayesian approach is therefore of fundamental importance, especially when coupled with Markov chain Monte Carlo (MCMC) sampling to provide information about solution behaviour. Spatial smoothing is a commonly used approach to regularization. In the human thorax EIT example considered here nonlinearity increases the difficulty of imaging, using only boundary data, leading to reconstructions which are often rather too smooth. In particular, in medical imaging the resistivity distribution usually contains substantial jumps at the boundaries of different anatomical regions. With spatial smoothing these boundaries can be masked by blurring. This paper focuses on the medical application of EIT to monitor lung and cardiac function and uses explicit geometric information regarding anatomical structure and incorporates temporal correlation. Some simple properties are assumed known, or at least reliably estimated from separate studies, whereas others are estimated from the voltage measurements. This structural formulation will also allow direct estimation of clinically important quantities, such as ejection fraction and residual capacity, along with assessment of precision.

On the spatial distribution of decameter‒scale subauroral ionospheric irregularities observed by SuperDARN radars

NASA Astrophysics Data System (ADS)

Larquier, S.; Ponomarenko, P.; Ribeiro, A. J.; Ruohoniemi, J. M.; Baker, J. B. H.; Sterne, K. T.; Lester, M.

2013-08-01

The midlatitude Super Dual Auroral Radar Network (SuperDARN) radars regularly observe nighttime low‒velocity Sub‒Auroral Ionospheric Scatter (SAIS) from decameter‒scale ionospheric density irregularities during quiet geomagnetic conditions. To establish the origin of the density irregularities responsible for low‒velocity SAIS, it is necessary to distinguish between the effects of high frequency (HF) propagation and irregularity occurrence itself on the observed backscatter distribution. We compare range, azimuth, and elevation data from the Blackstone SuperDARN radar with modeling results from ray tracing coupled with the International Reference Ionosphere assuming a uniform irregularity distribution. The observed and modeled distributions are shown to be very similar. The spatial distribution of backscattering is consistent with the requirement that HF rays propagate nearly perpendicular to the geomagnetic field lines (aspect angle ≤1°). For the first time, the irregularities responsible for low‒velocity SAIS are determined to extend between 200 and 300 km altitude, validating previous assumptions that low‒velocity SAIS is an F‒region phenomenon. We find that the limited spatial extent of this category of ionospheric backscatter within SuperDARN radars' fields‒of‒view is a consequence of HF propagation effects and the finite vertical extent of the scattering irregularities. We conclude that the density irregularities responsible for low‒velocity SAIS are widely distributed horizontally within the midlatitude ionosphere but are confined to the bottom‒side F‒region.

Statistical regularities of art images and natural scenes: spectra, sparseness and nonlinearities.

PubMed

Graham, Daniel J; Field, David J

2007-01-01

Paintings are the product of a process that begins with ordinary vision in the natural world and ends with manipulation of pigments on canvas. Because artists must produce images that can be seen by a visual system that is thought to take advantage of statistical regularities in natural scenes, artists are likely to replicate many of these regularities in their painted art. We have tested this notion by computing basic statistical properties and modeled cell response properties for a large set of digitized paintings and natural scenes. We find that both representational and non-representational (abstract) paintings from our sample (124 images) show basic similarities to a sample of natural scenes in terms of their spatial frequency amplitude spectra, but the paintings and natural scenes show significantly different mean amplitude spectrum slopes. We also find that the intensity distributions of paintings show a lower skewness and sparseness than natural scenes. We account for this by considering the range of luminances found in the environment compared to the range available in the medium of paint. A painting's range is limited by the reflective properties of its materials. We argue that artists do not simply scale the intensity range down but use a compressive nonlinearity. In our studies, modeled retinal and cortical filter responses to the images were less sparse for the paintings than for the natural scenes. But when a compressive nonlinearity was applied to the images, both the paintings' sparseness and the modeled responses to the paintings showed the same or greater sparseness compared to the natural scenes. This suggests that artists achieve some degree of nonlinear compression in their paintings. Because paintings have captivated humans for millennia, finding basic statistical regularities in paintings' spatial structure could grant insights into the range of spatial patterns that humans find compelling.

Disease Prediction based on Functional Connectomes using a Scalable and Spatially-Informed Support Vector Machine

PubMed Central

Watanabe, Takanori; Kessler, Daniel; Scott, Clayton; Angstadt, Michael; Sripada, Chandra

2014-01-01

Substantial evidence indicates that major psychiatric disorders are associated with distributed neural dysconnectivity, leading to strong interest in using neuroimaging methods to accurately predict disorder status. In this work, we are specifically interested in a multivariate approach that uses features derived from whole-brain resting state functional connectomes. However, functional connectomes reside in a high dimensional space, which complicates model interpretation and introduces numerous statistical and computational challenges. Traditional feature selection techniques are used to reduce data dimensionality, but are blind to the spatial structure of the connectomes. We propose a regularization framework where the 6-D structure of the functional connectome (defined by pairs of points in 3-D space) is explicitly taken into account via the fused Lasso or the GraphNet regularizer. Our method only restricts the loss function to be convex and margin-based, allowing non-differentiable loss functions such as the hinge-loss to be used. Using the fused Lasso or GraphNet regularizer with the hinge-loss leads to a structured sparse support vector machine (SVM) with embedded feature selection. We introduce a novel efficient optimization algorithm based on the augmented Lagrangian and the classical alternating direction method, which can solve both fused Lasso and GraphNet regularized SVM with very little modification. We also demonstrate that the inner subproblems of the algorithm can be solved efficiently in analytic form by coupling the variable splitting strategy with a data augmentation scheme. Experiments on simulated data and resting state scans from a large schizophrenia dataset show that our proposed approach can identify predictive regions that are spatially contiguous in the 6-D “connectome space,” offering an additional layer of interpretability that could provide new insights about various disease processes. PMID:24704268

Nonparametric Bayesian models for a spatial covariance.

PubMed

Reich, Brian J; Fuentes, Montserrat

2012-01-01

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

Validation of temporal and spatial consistency of facility- and speed-specific vehicle-specific power distributions for emission estimation: A case study in Beijing, China.

PubMed

Zhai, Zhiqiang; Song, Guohua; Lu, Hongyu; He, Weinan; Yu, Lei

2017-09-01

Vehicle-specific power (VSP) has been found to be highly correlated with vehicle emissions. It is used in many studies on emission modeling such as the MOVES (Motor Vehicle Emissions Simulator) model. The existing studies develop specific VSP distributions (or OpMode distribution in MOVES) for different road types and various average speeds to represent the vehicle operating modes on road. However, it is still not clear if the facility- and speed-specific VSP distributions are consistent temporally and spatially. For instance, is it necessary to update periodically the database of the VSP distributions in the emission model? Are the VSP distributions developed in the city central business district (CBD) area applicable to its suburb area? In this context, this study examined the temporal and spatial consistency of the facility- and speed-specific VSP distributions in Beijing. The VSP distributions in different years and in different areas are developed, based on real-world vehicle activity data. The root mean square error (RMSE) is employed to quantify the difference between the VSP distributions. The maximum differences of the VSP distributions between different years and between different areas are approximately 20% of that between different road types. The analysis of the carbon dioxide (CO 2 ) emission factor indicates that the temporal and spatial differences of the VSP distributions have no significant impact on vehicle emission estimation, with relative error of less than 3%. The temporal and spatial differences have no significant impact on the development of the facility- and speed-specific VSP distributions for the vehicle emission estimation. The database of the specific VSP distributions in the VSP-based emission models can maintain in terms of time. Thus, it is unnecessary to update the database regularly, and it is reliable to use the history vehicle activity data to forecast the emissions in the future. In one city, the areas with less data can still develop accurate VSP distributions based on better data from other areas.

One-loop gravitational wave spectrum in de Sitter spacetime

NASA Astrophysics Data System (ADS)

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

2012-08-01

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

A combined reconstruction-classification method for diffuse optical tomography.

PubMed

Hiltunen, P; Prince, S J D; Arridge, S

2009-11-07

We present a combined classification and reconstruction algorithm for diffuse optical tomography (DOT). DOT is a nonlinear ill-posed inverse problem. Therefore, some regularization is needed. We present a mixture of Gaussians prior, which regularizes the DOT reconstruction step. During each iteration, the parameters of a mixture model are estimated. These associate each reconstructed pixel with one of several classes based on the current estimate of the optical parameters. This classification is exploited to form a new prior distribution to regularize the reconstruction step and update the optical parameters. The algorithm can be described as an iteration between an optimization scheme with zeroth-order variable mean and variance Tikhonov regularization and an expectation-maximization scheme for estimation of the model parameters. We describe the algorithm in a general Bayesian framework. Results from simulated test cases and phantom measurements show that the algorithm enhances the contrast of the reconstructed images with good spatial accuracy. The probabilistic classifications of each image contain only a few misclassified pixels.

A class of renormalised meshless Laplacians for boundary value problems

NASA Astrophysics Data System (ADS)

Basic, Josip; Degiuli, Nastia; Ban, Dario

2018-02-01

A meshless approach to approximating spatial derivatives on scattered point arrangements is presented in this paper. Three various derivations of approximate discrete Laplace operator formulations are produced using the Taylor series expansion and renormalised least-squares correction of the first spatial derivatives. Numerical analyses are performed for the introduced Laplacian formulations, and their convergence rate and computational efficiency are examined. The tests are conducted on regular and highly irregular scattered point arrangements. The results are compared to those obtained by the smoothed particle hydrodynamics method and the finite differences method on a regular grid. Finally, the strong form of various Poisson and diffusion equations with Dirichlet or Robin boundary conditions are solved in two and three dimensions by making use of the introduced operators in order to examine their stability and accuracy for boundary value problems. The introduced Laplacian operators perform well for highly irregular point distribution and offer adequate accuracy for mesh and mesh-free numerical methods that require frequent movement of the grid or point cloud.

Disease Spread and Its Effect on Population Dynamics in Heterogeneous Environment

NASA Astrophysics Data System (ADS)

Upadhyay, Ranjit Kumar; Roy, Parimita

In this paper, an eco-epidemiological model in which both species diffuse along a spatial gradient has been shown to exhibit temporal chaos at a fixed point in space. The proposed model is a modification of the model recently presented by Upadhyay and Roy [2014]. The spatial interactions among the species have been represented in the form of reaction-diffusion equations. The model incorporates the intrinsic growth rate of fish population which varies linearly with the depth of water. Numerical results show that diffusion can drive otherwise stable system into aperiodic behavior with sensitivity to initial conditions. We show that spatially induced chaos plays an important role in spatial pattern formation in heterogeneous environment. Spatiotemporal distributions of species have been simulated using the diffusivity assumptions realistic for natural eco-epidemic systems. We found that in heterogeneous environment, the temporal dynamics of both the species are drastically different and show chaotic behavior. It was also found that the instability observed in the model is due to spatial heterogeneity and diffusion-driven. Cumulative death rate of predator has an appreciable effect on model dynamics as the spatial distribution of all constituent populations exhibit significant changes when this model parameter is changed and it acts as a regularizing factor.

Mesoscopic Effects in an Agent-Based Bargaining Model in Regular Lattices

PubMed Central

Poza, David J.; Santos, José I.; Galán, José M.; López-Paredes, Adolfo

2011-01-01

The effect of spatial structure has been proved very relevant in repeated games. In this work we propose an agent based model where a fixed finite population of tagged agents play iteratively the Nash demand game in a regular lattice. The model extends the multiagent bargaining model by Axtell, Epstein and Young [1] modifying the assumption of global interaction. Each agent is endowed with a memory and plays the best reply against the opponent's most frequent demand. We focus our analysis on the transient dynamics of the system, studying by computer simulation the set of states in which the system spends a considerable fraction of the time. The results show that all the possible persistent regimes in the global interaction model can also be observed in this spatial version. We also find that the mesoscopic properties of the interaction networks that the spatial distribution induces in the model have a significant impact on the diffusion of strategies, and can lead to new persistent regimes different from those found in previous research. In particular, community structure in the intratype interaction networks may cause that communities reach different persistent regimes as a consequence of the hindering diffusion effect of fluctuating agents at their borders. PMID:21408019

Mesoscopic effects in an agent-based bargaining model in regular lattices.

PubMed

Poza, David J; Santos, José I; Galán, José M; López-Paredes, Adolfo

2011-03-09

The effect of spatial structure has been proved very relevant in repeated games. In this work we propose an agent based model where a fixed finite population of tagged agents play iteratively the Nash demand game in a regular lattice. The model extends the multiagent bargaining model by Axtell, Epstein and Young modifying the assumption of global interaction. Each agent is endowed with a memory and plays the best reply against the opponent's most frequent demand. We focus our analysis on the transient dynamics of the system, studying by computer simulation the set of states in which the system spends a considerable fraction of the time. The results show that all the possible persistent regimes in the global interaction model can also be observed in this spatial version. We also find that the mesoscopic properties of the interaction networks that the spatial distribution induces in the model have a significant impact on the diffusion of strategies, and can lead to new persistent regimes different from those found in previous research. In particular, community structure in the intratype interaction networks may cause that communities reach different persistent regimes as a consequence of the hindering diffusion effect of fluctuating agents at their borders.

Novel Hyperspectral Anomaly Detection Methods Based on Unsupervised Nearest Regularized Subspace

NASA Astrophysics Data System (ADS)

Hou, Z.; Chen, Y.; Tan, K.; Du, P.

2018-04-01

Anomaly detection has been of great interest in hyperspectral imagery analysis. Most conventional anomaly detectors merely take advantage of spectral and spatial information within neighboring pixels. In this paper, two methods of Unsupervised Nearest Regularized Subspace-based with Outlier Removal Anomaly Detector (UNRSORAD) and Local Summation UNRSORAD (LSUNRSORAD) are proposed, which are based on the concept that each pixel in background can be approximately represented by its spatial neighborhoods, while anomalies cannot. Using a dual window, an approximation of each testing pixel is a representation of surrounding data via a linear combination. The existence of outliers in the dual window will affect detection accuracy. Proposed detectors remove outlier pixels that are significantly different from majority of pixels. In order to make full use of various local spatial distributions information with the neighboring pixels of the pixels under test, we take the local summation dual-window sliding strategy. The residual image is constituted by subtracting the predicted background from the original hyperspectral imagery, and anomalies can be detected in the residual image. Experimental results show that the proposed methods have greatly improved the detection accuracy compared with other traditional detection method.

The neglected nonlocal effects of deforestation

NASA Astrophysics Data System (ADS)

Winckler, Johannes; Reick, Christian; Pongratz, Julia

2017-04-01

Deforestation changes surface temperature locally via biogeophysical effects by changing the water, energy and momentum balance. Adding to these locally induced changes (local effects), deforestation at a given location can cause changes in temperature elsewhere (nonlocal effects). Most previous studies have not considered local and nonlocal effects separately, but investigated the total (local plus nonlocal) effects, for which global deforestation was found to cause a global mean cooling. Recent modeling and observational studies focused on the isolated local effects: The local effects are relevant for local living conditions, and they can be obtained from in-situ and satellite observations. Observational studies suggest that the local effects of potential deforestation cause a warming when averaged globally. This contrast between local warming and total cooling indicates that the nonlocal effects of deforestation are causing a cooling and thus counteract the local effects. It is still unclear how the nonlocal effects depend on the spatial scale of deforestation, and whether they still compensate the local warming in a more realistic spatial distribution of deforestation. To investigate this, we use a fully coupled climate model and separate local and nonlocal effects of deforestation in three steps: Starting from a forest world, we simulate deforestation in one out of four grid boxes using a regular spatial pattern and increase the number of deforestation grid boxes step-wise up to three out of four boxes in subsequent simulations. To compare these idealized spatial distributions of deforestation to a more realistic case, we separate local and nonlocal effects in a simulation where deforestation is applied in regions where it occurred historically. We find that the nonlocal effects scale nearly linearly with the number of deforested grid boxes, and the spatial distribution of the nonlocal effects is similar for the regular spatial distribution of deforestation and the more realistic pattern. Globally averaged, the deforestation-induced warming of the local effects is counteracted by the nonlocal effects, which are about three times as strong as the local effects (up to 0.1K local warming versus -0.3K nonlocal cooling). Thus, the nonlocal effects are more cooling than the local effects are warming, and this is valid not only for idealized simulations of large-scale deforestation, but also for a more realistic deforestation scenario. We conclude that the local effects of deforestation only yield an incomplete picture of the total climate effects by biogeophysical pathways. While the local effects capture the direct climatic response at the site of deforestation, the nonlocal effects have to be included if the biogeophysical effects of deforestation are considered for an implementation in climate policies.

Automated model selection in covariance estimation and spatial whitening of MEG and EEG signals.

PubMed

Engemann, Denis A; Gramfort, Alexandre

2015-03-01

Magnetoencephalography and electroencephalography (M/EEG) measure non-invasively the weak electromagnetic fields induced by post-synaptic neural currents. The estimation of the spatial covariance of the signals recorded on M/EEG sensors is a building block of modern data analysis pipelines. Such covariance estimates are used in brain-computer interfaces (BCI) systems, in nearly all source localization methods for spatial whitening as well as for data covariance estimation in beamformers. The rationale for such models is that the signals can be modeled by a zero mean Gaussian distribution. While maximizing the Gaussian likelihood seems natural, it leads to a covariance estimate known as empirical covariance (EC). It turns out that the EC is a poor estimate of the true covariance when the number of samples is small. To address this issue the estimation needs to be regularized. The most common approach downweights off-diagonal coefficients, while more advanced regularization methods are based on shrinkage techniques or generative models with low rank assumptions: probabilistic PCA (PPCA) and factor analysis (FA). Using cross-validation all of these models can be tuned and compared based on Gaussian likelihood computed on unseen data. We investigated these models on simulations, one electroencephalography (EEG) dataset as well as magnetoencephalography (MEG) datasets from the most common MEG systems. First, our results demonstrate that different models can be the best, depending on the number of samples, heterogeneity of sensor types and noise properties. Second, we show that the models tuned by cross-validation are superior to models with hand-selected regularization. Hence, we propose an automated solution to the often overlooked problem of covariance estimation of M/EEG signals. The relevance of the procedure is demonstrated here for spatial whitening and source localization of MEG signals. Copyright © 2015 Elsevier Inc. All rights reserved.

Increasing Accuracy of Tissue Shear Modulus Reconstruction Using Ultrasonic Strain Tensor Measurement

NASA Astrophysics Data System (ADS)

Sumi, C.

Previously, we developed three displacement vector measurement methods, i.e., the multidimensional cross-spectrum phase gradient method (MCSPGM), the multidimensional autocorrelation method (MAM), and the multidimensional Doppler method (MDM). To increase the accuracies and stabilities of lateral and elevational displacement measurements, we also developed spatially variant, displacement component-dependent regularization. In particular, the regularization of only the lateral/elevational displacements is advantageous for the lateral unmodulated case. The demonstrated measurements of the displacement vector distributions in experiments using an inhomogeneous shear modulus agar phantom confirm that displacement-component-dependent regularization enables more stable shear modulus reconstruction. In this report, we also review our developed lateral modulation methods that use Parabolic functions, Hanning windows, and Gaussian functions in the apodization function and the optimized apodization function that realizes the designed point spread function (PSF). The modulations significantly increase the accuracy of the strain tensor measurement and shear modulus reconstruction (demonstrated using an agar phantom).

Power-law regularities in human language

NASA Astrophysics Data System (ADS)

Mehri, Ali; Lashkari, Sahar Mohammadpour

2016-11-01

Complex structure of human language enables us to exchange very complicated information. This communication system obeys some common nonlinear statistical regularities. We investigate four important long-range features of human language. We perform our calculations for adopted works of seven famous litterateurs. Zipf's law and Heaps' law, which imply well-known power-law behaviors, are established in human language, showing a qualitative inverse relation with each other. Furthermore, the informational content associated with the words ordering, is measured by using an entropic metric. We also calculate fractal dimension of words in the text by using box counting method. The fractal dimension of each word, that is a positive value less than or equal to one, exhibits its spatial distribution in the text. Generally, we can claim that the Human language follows the mentioned power-law regularities. Power-law relations imply the existence of long-range correlations between the word types, to convey an especial idea.

Dynamics of Learning in Cultured Neuronal Networks with Antagonists of Glutamate Receptors

PubMed Central

Li, Yanling; Zhou, Wei; Li, Xiangning; Zeng, Shaoqun; Luo, Qingming

2007-01-01

Cognitive dysfunction may result from abnormality of ionotropic glutamate receptors. Although various forms of synaptic plasticity in learning that rely on altering of glutamate receptors have been considered, the evidence is insufficient from an informatics view. Dynamics could reflect neuroinformatics encoding, including temporal pattern encoding, spatial pattern encoding, and energy distribution. Discovering informatics encoding is fundamental and crucial to understanding the working principle of the neural system. In this article, we analyzed the dynamic characteristics of response activities during learning training in cultured hippocampal networks under normal and abnormal conditions of ionotropic glutamate receptors, respectively. The rate, which is one of the temporal configurations, was decreased markedly by inhibition of α-amino-3-hydroxy-5-methylisoxazole-4-proprionic acid (AMPA) receptors. Moreover, the energy distribution in different characteristic frequencies was changed markedly by inhibition of AMPA receptors. Spatial configurations, including regularization, correlation, and synchrony, were changed significantly by inhibition of N-methyl-d-aspartate receptors. These results suggest that temporal pattern encoding and energy distribution of response activities in cultured hippocampal neuronal networks during learning training are modulated by AMPA receptors, whereas spatial pattern encoding of response activities is modulated by N-methyl-d-aspartate receptors. PMID:17766359

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.

A space-time multiscale modelling of Earth's gravity field variations

NASA Astrophysics Data System (ADS)

Wang, Shuo; Panet, Isabelle; Ramillien, Guillaume; Guilloux, Frédéric

2017-04-01

The mass distribution within the Earth varies over a wide range of spatial and temporal scales, generating variations in the Earth's gravity field in space and time. These variations are monitored by satellites as the GRACE mission, with a 400 km spatial resolution and 10 days to 1 month temporal resolution. They are expressed in the form of gravity field models, often with a fixed spatial or temporal resolution. The analysis of these models allows us to study the mass transfers within the Earth system. Here, we have developed space-time multi-scale models of the gravity field, in order to optimize the estimation of gravity signals resulting from local processes at different spatial and temporal scales, and to adapt the time resolution of the model to its spatial resolution according to the satellites sampling. For that, we first build a 4D wavelet family combining spatial Poisson wavelets with temporal Haar wavelets. Then, we set-up a regularized inversion of inter-satellites gravity potential differences in a bayesian framework, to estimate the model parameters. To build the prior, we develop a spectral analysis, localized in time and space, of geophysical models of mass transport and associated gravity variations. Finally, we test our approach to the reconstruction of space-time variations of the gravity field due to hydrology. We first consider a global distribution of observations along the orbit, from a simplified synthetic hydrology signal comprising only annual variations at large spatial scales. Then, we consider a regional distribution of observations in Africa, and a larger number of spatial and temporal scales. We test the influence of an imperfect prior and discuss our results.

Quaternion Regularization of the Equations of the Perturbed Spatial Restricted Three-Body Problem: I

NASA Astrophysics Data System (ADS)

Chelnokov, Yu. N.

2017-11-01

We develop a quaternion method for regularizing the differential equations of the perturbed spatial restricted three-body problem by using the Kustaanheimo-Stiefel variables, which is methodologically closely related to the quaternion method for regularizing the differential equations of perturbed spatial two-body problem, which was proposed by the author of the present paper. A survey of papers related to the regularization of the differential equations of the two- and threebody problems is given. The original Newtonian equations of perturbed spatial restricted three-body problem are considered, and the problem of their regularization is posed; the energy relations and the differential equations describing the variations in the energies of the system in the perturbed spatial restricted three-body problem are given, as well as the first integrals of the differential equations of the unperturbed spatial restricted circular three-body problem (Jacobi integrals); the equations of perturbed spatial restricted three-body problem written in terms of rotating coordinate systems whose angular motion is described by the rotation quaternions (Euler (Rodrigues-Hamilton) parameters) are considered; and the differential equations for angular momenta in the restricted three-body problem are given. Local regular quaternion differential equations of perturbed spatial restricted three-body problem in the Kustaanheimo-Stiefel variables, i.e., equations regular in a neighborhood of the first and second body of finite mass, are obtained. The equations are systems of nonlinear nonstationary eleventhorder differential equations. These equations employ, as additional dependent variables, the energy characteristics of motion of the body under study (a body of a negligibly small mass) and the time whose derivative with respect to a new independent variable is equal to the distance from the body of negligibly small mass to the first or second body of finite mass. The equations obtained in the paper permit developing regular methods for determining solutions, in analytical or numerical form, of problems difficult for classicalmethods, such as the motion of a body of negligibly small mass in a neighborhood of the other two bodies of finite masses.

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

PubMed

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

2017-02-01

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

Spatial variability of soil available phosphorous and potassium at three different soils located in Pannonian Croatia

NASA Astrophysics Data System (ADS)

Bogunović, Igor; Pereira, Paulo; Đurđević, Boris

2017-04-01

Information on spatial distribution of soil nutrients in agroecosystems is critical for improving productivity and reducing environmental pressures in intensive farmed soils. In this context, spatial prediction of soil properties should be accurate. In this study we analyse 704 data of soil available phosphorus (AP) and potassium (AK); the data derive from soil samples collected across three arable fields in Baranja region (Croatia) in correspondence of different soil types: Cambisols (169 samples), Chernozems (131 samples) and Gleysoils (404 samples). The samples are collected in a regular sampling grid (distance 225 x 225 m). Several geostatistical techniques (Inverse Distance to a Weight (IDW) with the power of 1, 2 and 3; Radial Basis Functions (RBF) - Inverse Multiquadratic (IMT), Multiquadratic (MTQ), Completely Regularized Spline (CRS), Spline with Tension (SPT) and Thin Plate Spline (TPS); and Local Polynomial (LP) with the power of 1 and 2; two geostatistical techniques -Ordinary Kriging - OK and Simple Kriging - SK) were tested in order to evaluate the most accurate spatial variability maps using criteria of lowest RMSE during cross validation technique. Soil parameters varied considerably throughout the studied fields and their coefficient of variations ranged from 31.4% to 37.7% and from 19.3% to 27.1% for soil AP and AK, respectively. The experimental variograms indicate a moderate spatial dependence for AP and strong spatial dependence for all three locations. The best spatial predictor for AP at Chernozem field was Simple kriging (RMSE=61.711), and for AK inverse multiquadratic (RMSE=44.689). The least accurate technique was Thin plate spline (AP) and Inverse distance to a weight with a power of 1 (AK). Radial basis function models (Spline with Tension for AP at Gleysoil and Cambisol and Completely Regularized Spline for AK at Gleysol) were the best predictors, while Thin Plate Spline models were the least accurate in all three cases. The best interpolator for AK at Cambisol was the local polynomial with the power of 2 (RMSE=33.943), while the least accurate was Thin Plate Spline (RMSE=39.572).

Using Tikhonov Regularization for Spatial Projections from CSR Regularized Spherical Harmonic GRACE Solutions

NASA Astrophysics Data System (ADS)

Save, H.; Bettadpur, S. V.

2013-12-01

It has been demonstrated before that using Tikhonov regularization produces spherical harmonic solutions from GRACE that have very little residual stripes while capturing all the signal observed by GRACE within the noise level. This paper demonstrates a two-step process and uses Tikhonov regularization to remove the residual stripes in the CSR regularized spherical harmonic coefficients when computing the spatial projections. We discuss methods to produce mass anomaly grids that have no stripe features while satisfying the necessary condition of capturing all observed signal within the GRACE noise level.

Optimization of equivalent uniform dose using the L-curve criterion.

PubMed

Chvetsov, Alexei V; Dempsey, James F; Palta, Jatinder R

2007-10-07

Optimization of equivalent uniform dose (EUD) in inverse planning for intensity-modulated radiation therapy (IMRT) prevents variation in radiobiological effect between different radiotherapy treatment plans, which is due to variation in the pattern of dose nonuniformity. For instance, the survival fraction of clonogens would be consistent with the prescription when the optimized EUD is equal to the prescribed EUD. One of the problems in the practical implementation of this approach is that the spatial dose distribution in EUD-based inverse planning would be underdetermined because an unlimited number of nonuniform dose distributions can be computed for a prescribed value of EUD. Together with ill-posedness of the underlying integral equation, this may significantly increase the dose nonuniformity. To optimize EUD and keep dose nonuniformity within reasonable limits, we implemented into an EUD-based objective function an additional criterion which ensures the smoothness of beam intensity functions. This approach is similar to the variational regularization technique which was previously studied for the dose-based least-squares optimization. We show that the variational regularization together with the L-curve criterion for the regularization parameter can significantly reduce dose nonuniformity in EUD-based inverse planning.

Spatial Distribution and Sampling Plans With Fixed Level of Precision for Citrus Aphids (Hom., Aphididae) on Two Orange Species.

PubMed

Kafeshani, Farzaneh Alizadeh; Rajabpour, Ali; Aghajanzadeh, Sirous; Gholamian, Esmaeil; Farkhari, Mohammad

2018-04-02

Aphis spiraecola Patch, Aphis gossypii Glover, and Toxoptera aurantii Boyer de Fonscolombe are three important aphid pests of citrus orchards. In this study, spatial distributions of the aphids on two orange species, Satsuma mandarin and Thomson navel, were evaluated using Taylor's power law and Iwao's patchiness. In addition, a fixed-precision sequential sampling plant was developed for each species on the host plant by Green's model at precision levels of 0.25 and 0.1. The results revealed that spatial distribution parameters and therefore the sampling plan were significantly different according to aphid and host plant species. Taylor's power law provides a better fit for the data than Iwao's patchiness regression. Except T. aurantii on Thomson navel orange, spatial distribution patterns of the aphids were aggregative on both citrus. T. aurantii had regular dispersion pattern on Thomson navel orange. Optimum sample size of the aphids varied from 30-2061 and 1-1622 shoots on Satsuma mandarin and Thomson navel orange based on aphid species and desired precision level. Calculated stop lines of the aphid species on Satsuma mandarin and Thomson navel orange ranged from 0.48 to 19 and 0.19 to 80.4 aphids per 24 shoots according to aphid species and desired precision level. The performance of the sampling plan was validated by resampling analysis using resampling for validation of sampling plans (RVSP) software. This sampling program is useful for IPM program of the aphids in citrus orchards.

A Unified Fisher's Ratio Learning Method for Spatial Filter Optimization.

PubMed

Li, Xinyang; Guan, Cuntai; Zhang, Haihong; Ang, Kai Keng

To detect the mental task of interest, spatial filtering has been widely used to enhance the spatial resolution of electroencephalography (EEG). However, the effectiveness of spatial filtering is undermined due to the significant nonstationarity of EEG. Based on regularization, most of the conventional stationary spatial filter design methods address the nonstationarity at the cost of the interclass discrimination. Moreover, spatial filter optimization is inconsistent with feature extraction when EEG covariance matrices could not be jointly diagonalized due to the regularization. In this paper, we propose a novel framework for a spatial filter design. With Fisher's ratio in feature space directly used as the objective function, the spatial filter optimization is unified with feature extraction. Given its ratio form, the selection of the regularization parameter could be avoided. We evaluate the proposed method on a binary motor imagery data set of 16 subjects, who performed the calibration and test sessions on different days. The experimental results show that the proposed method yields improvement in classification performance for both single broadband and filter bank settings compared with conventional nonunified methods. We also provide a systematic attempt to compare different objective functions in modeling data nonstationarity with simulation studies.To detect the mental task of interest, spatial filtering has been widely used to enhance the spatial resolution of electroencephalography (EEG). However, the effectiveness of spatial filtering is undermined due to the significant nonstationarity of EEG. Based on regularization, most of the conventional stationary spatial filter design methods address the nonstationarity at the cost of the interclass discrimination. Moreover, spatial filter optimization is inconsistent with feature extraction when EEG covariance matrices could not be jointly diagonalized due to the regularization. In this paper, we propose a novel framework for a spatial filter design. With Fisher's ratio in feature space directly used as the objective function, the spatial filter optimization is unified with feature extraction. Given its ratio form, the selection of the regularization parameter could be avoided. We evaluate the proposed method on a binary motor imagery data set of 16 subjects, who performed the calibration and test sessions on different days. The experimental results show that the proposed method yields improvement in classification performance for both single broadband and filter bank settings compared with conventional nonunified methods. We also provide a systematic attempt to compare different objective functions in modeling data nonstationarity with simulation studies.

Collective behavior in the spatial spreading of obesity

PubMed Central

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

2012-01-01

Obesity prevalence is increasing in many countries at alarming levels. A difficulty in the conception of policies to reverse these trends is the identification of the drivers behind the obesity epidemics. Here, we implement a spatial spreading analysis to investigate whether obesity shows spatial correlations, revealing the effect of collective and global factors acting above individual choices. We find a regularity in the spatial fluctuations of their prevalence revealed by a pattern of scale-free long-range correlations. The fluctuations are anomalous, deviating in a fundamental way from the weaker correlations found in the underlying population distribution indicating the presence of collective behavior, i.e., individual habits may have negligible influence in shaping the patterns of spreading. Interestingly, we find the same scale-free correlations in economic activities associated with food production. These results motivate future interventions to investigate the causality of this relation providing guidance for the implementation of preventive health policies. PMID:22822425

Collective behavior in the spatial spreading of obesity

NASA Astrophysics Data System (ADS)

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

2012-06-01

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

Spatial variability of isoproturon mineralizing activity within an agricultural field: geostatistical analysis of simple physicochemical and microbiological soil parameters.

PubMed

El Sebai, T; Lagacherie, B; Soulas, G; Martin-Laurent, F

2007-02-01

We assessed the spatial variability of isoproturon mineralization in relation to that of physicochemical and biological parameters in fifty soil samples regularly collected along a sampling grid delimited across a 0.36 ha field plot (40 x 90 m). Only faint relationships were observed between isoproturon mineralization and the soil pH, microbial C biomass, and organic nitrogen. Considerable spatial variability was observed for six of the nine parameters tested (isoproturon mineralization rates, organic nitrogen, genetic structure of the microbial communities, soil pH, microbial biomass and equivalent humidity). The map of isoproturon mineralization rates distribution was similar to that of soil pH, microbial biomass, and organic nitrogen but different from those of structure of the microbial communities and equivalent humidity. Geostatistics revealed that the spatial heterogeneity in the rate of degradation of isoproturon corresponded to that of soil pH and microbial biomass.

Seismicity and source spectra analysis in Salton Sea Geothermal Field

NASA Astrophysics Data System (ADS)

Cheng, Y.; Chen, X.

2016-12-01

The surge of "man-made" earthquakes in recent years has led to considerable concerns about the associated hazards. Improved monitoring of small earthquakes would significantly help understand such phenomena and the underlying physical mechanisms. In the Salton Sea Geothermal field in southern California, open access of a local borehole network provides a unique opportunity to better understand the seismicity characteristics, the related earthquake hazards, and the relationship with the geothermal system, tectonic faulting and other physical conditions. We obtain high-resolution earthquake locations in the Salton Sea Geothermal Field, analyze characteristics of spatiotemporal isolated earthquake clusters, magnitude-frequency distributions and spatial variation of stress drops. The analysis reveals spatial coherent distributions of different types of clustering, b-value distributions, and stress drop distribution. The mixture type clusters (short-duration rapid bursts with high aftershock productivity) are predominately located within active geothermal field that correlate with high b-value, low stress drop microearthquake clouds, while regular aftershock sequences and swarms are distributed throughout the study area. The differences between earthquakes inside and outside of geothermal operation field suggest a possible way to distinguish directly induced seismicity due to energy operation versus typical seismic slip driven sequences. The spatial coherent b-value distribution enables in-situ estimation of probabilities for M≥3 earthquakes, and shows that the high large-magnitude-event (LME) probability zones with high stress drop are likely associated with tectonic faulting. The high stress drop in shallow (1-3 km) depth indicates the existence of active faults, while low stress drops near injection wells likely corresponds to the seismic response to fluid injection. I interpret the spatial variation of seismicity and source characteristics as the result of fluid circulation, the fracture network, and tectonic faulting.

Hyperspectral imagery super-resolution by compressive sensing inspired dictionary learning and spatial-spectral regularization.

PubMed

Huang, Wei; Xiao, Liang; Liu, Hongyi; Wei, Zhihui

2015-01-19

Due to the instrumental and imaging optics limitations, it is difficult to acquire high spatial resolution hyperspectral imagery (HSI). Super-resolution (SR) imagery aims at inferring high quality images of a given scene from degraded versions of the same scene. This paper proposes a novel hyperspectral imagery super-resolution (HSI-SR) method via dictionary learning and spatial-spectral regularization. The main contributions of this paper are twofold. First, inspired by the compressive sensing (CS) framework, for learning the high resolution dictionary, we encourage stronger sparsity on image patches and promote smaller coherence between the learned dictionary and sensing matrix. Thus, a sparsity and incoherence restricted dictionary learning method is proposed to achieve higher efficiency sparse representation. Second, a variational regularization model combing a spatial sparsity regularization term and a new local spectral similarity preserving term is proposed to integrate the spectral and spatial-contextual information of the HSI. Experimental results show that the proposed method can effectively recover spatial information and better preserve spectral information. The high spatial resolution HSI reconstructed by the proposed method outperforms reconstructed results by other well-known methods in terms of both objective measurements and visual evaluation.

Regularization design for high-quality cone-beam CT of intracranial hemorrhage using statistical reconstruction

NASA Astrophysics Data System (ADS)

Dang, H.; Stayman, J. W.; Xu, J.; Sisniega, A.; Zbijewski, W.; Wang, X.; Foos, D. H.; Aygun, N.; Koliatsos, V. E.; Siewerdsen, J. H.

2016-03-01

Intracranial hemorrhage (ICH) is associated with pathologies such as hemorrhagic stroke and traumatic brain injury. Multi-detector CT is the current front-line imaging modality for detecting ICH (fresh blood contrast 40-80 HU, down to 1 mm). Flat-panel detector (FPD) cone-beam CT (CBCT) offers a potential alternative with a smaller scanner footprint, greater portability, and lower cost potentially well suited to deployment at the point of care outside standard diagnostic radiology and emergency room settings. Previous studies have suggested reliable detection of ICH down to 3 mm in CBCT using high-fidelity artifact correction and penalized weighted least-squared (PWLS) image reconstruction with a post-artifact-correction noise model. However, ICH reconstructed by traditional image regularization exhibits nonuniform spatial resolution and noise due to interaction between the statistical weights and regularization, which potentially degrades the detectability of ICH. In this work, we propose three regularization methods designed to overcome these challenges. The first two compute spatially varying certainty for uniform spatial resolution and noise, respectively. The third computes spatially varying regularization strength to achieve uniform "detectability," combining both spatial resolution and noise in a manner analogous to a delta-function detection task. Experiments were conducted on a CBCT test-bench, and image quality was evaluated for simulated ICH in different regions of an anthropomorphic head. The first two methods improved the uniformity in spatial resolution and noise compared to traditional regularization. The third exhibited the highest uniformity in detectability among all methods and best overall image quality. The proposed regularization provides a valuable means to achieve uniform image quality in CBCT of ICH and is being incorporated in a CBCT prototype for ICH imaging.

Microparticles controllable accumulation, arrangement, and spatial shaping performed by tapered-fiber-based laser-induced convection flow.

PubMed

Zhang, Yu; Lei, Jiaojie; Zhang, Yaxun; Liu, Zhihai; Zhang, Jianzhong; Yang, Xinghua; Yang, Jun; Yuan, Libo

2017-10-30

The ability to arrange cells and/or microparticles into the desired pattern is critical in biological, chemical, and metamaterial studies and other applications. Researchers have developed a variety of patterning techniques, which either have a limited capacity to simultaneously trap massive particles or lack the spatial resolution necessary to manipulate individual particle. Several approaches have been proposed that combine both high spatial selectivity and high throughput simultaneously. However, those methods are complex and difficult to fabricate. In this article, we propose and demonstrate a simple method that combines the laser-induced convection flow and fiber-based optical trapping methods to perform both regular and special spatial shaping arrangement. Essentially, we combine a light field with a large optical intensity gradient distribution and a thermal field with a large temperature gradient distribution to perform the microparticles shaping arrangement. The tapered-fiber-based laser-induced convection flow provides not only the batch manipulation of massive particles, but also the finer manipulation of special one or several particles, which break out the limit of single-fiber-based massive/individual particles photothermal manipulation. The combination technique allows for microparticles quick accumulation, single-layer and multilayer arrangement; special spatial shaping arrangement/adjustment, and microparticles sorting.

A global analysis of bird plumage patterns reveals no association between habitat and camouflage

PubMed Central

Marshall, Kate L.A.; Gluckman, Thanh-Lan

2016-01-01

Evidence suggests that animal patterns (motifs) function in camouflage. Irregular mottled patterns can facilitate concealment when stationary in cluttered habitats, whereas regular patterns typically prevent capture during movement in open habitats. Bird plumage patterns have predominantly converged on just four types—mottled (irregular), scales, bars and spots (regular)—and habitat could be driving convergent evolution in avian patterning. Based on sensory ecology, we therefore predict that irregular patterns would be associated with visually noisy closed habitats and that regular patterns would be associated with open habitats. Regular patterns have also been shown to function in communication for sexually competing males to stand-out and attract females, so we predict that male breeding plumage patterns evolved in both open and closed habitats. Here, taking phylogenetic relatedness into account, we investigate ecological selection for bird plumage patterns across the class Aves. We surveyed plumage patterns in 80% of all avian species worldwide. Of these, 2,756 bird species have regular and irregular plumage patterns as well as habitat information. In this subset, we tested whether adult breeding/non-breeding plumages in each sex, and juvenile plumages, were associated with the habitat types found within the species’ geographical distributions. We found no evidence for an association between habitat and plumage patterns across the world’s birds and little phylogenetic signal. We also found that species with regular and irregular plumage patterns were distributed randomly across the world’s eco-regions without being affected by habitat type. These results indicate that at the global spatial and taxonomic scale, habitat does not predict convergent evolution in bird plumage patterns, contrary to the camouflage hypothesis. PMID:27867762

A global analysis of bird plumage patterns reveals no association between habitat and camouflage.

PubMed

Somveille, Marius; Marshall, Kate L A; Gluckman, Thanh-Lan

2016-01-01

Evidence suggests that animal patterns (motifs) function in camouflage. Irregular mottled patterns can facilitate concealment when stationary in cluttered habitats, whereas regular patterns typically prevent capture during movement in open habitats. Bird plumage patterns have predominantly converged on just four types-mottled (irregular), scales, bars and spots (regular)-and habitat could be driving convergent evolution in avian patterning. Based on sensory ecology, we therefore predict that irregular patterns would be associated with visually noisy closed habitats and that regular patterns would be associated with open habitats. Regular patterns have also been shown to function in communication for sexually competing males to stand-out and attract females, so we predict that male breeding plumage patterns evolved in both open and closed habitats. Here, taking phylogenetic relatedness into account, we investigate ecological selection for bird plumage patterns across the class Aves. We surveyed plumage patterns in 80% of all avian species worldwide. Of these, 2,756 bird species have regular and irregular plumage patterns as well as habitat information. In this subset, we tested whether adult breeding/non-breeding plumages in each sex, and juvenile plumages, were associated with the habitat types found within the species' geographical distributions. We found no evidence for an association between habitat and plumage patterns across the world's birds and little phylogenetic signal. We also found that species with regular and irregular plumage patterns were distributed randomly across the world's eco-regions without being affected by habitat type. These results indicate that at the global spatial and taxonomic scale, habitat does not predict convergent evolution in bird plumage patterns, contrary to the camouflage hypothesis.

A 20-year catalog comparing smooth and sharp estimates of slow slip events in Cascadia

NASA Astrophysics Data System (ADS)

Molitors Bergman, E. G.; Evans, E. L.; Loveless, J. P.

2017-12-01

Slow slip events (SSEs) are a form of aseismic strain release at subduction zones resulting in a temporary reversal in interseismic upper plate motion over a period of weeks, frequently accompanied in time and space by seismic tremor at the Cascadia subduction zone. Locating SSEs spatially along the subduction zone interface is essential to understanding the relationship between SSEs, earthquakes, and tremor and assessing megathrust earthquake hazard. We apply an automated slope comparison-based detection algorithm to single continuously recording GPS stations to determine dates and surface displacement vectors of SSEs, then apply network-based filters to eliminate false detections. The main benefits of this algorithm are its ability to detect SSEs while they are occurring and track the spatial migration of each event. We invert geodetic displacement fields for slip distributions on the subduction zone interface for SSEs between 1997 and 2017 using two estimation techniques: spatial smoothing and total variation regularization (TVR). Smoothing has been frequently used in determining the location of interseismic coupling, earthquake rupture, and SSE slip and yields spatially coherent but inherently blurred solutions. TVR yields compact, sharply bordered slip estimates of similar magnitude and along-strike extent to previously presented studied events, while fitting the constraining geodetic data as well as corresponding smoothing-based solutions. Slip distributions estimated using TVR have up-dip limits that align well with down-dip limits of interseismic coupling on the plate interface and spatial extents that approximately correspond to the distribution of tremor concurrent with each event. TVR gives a unique view of slow slip distributions that can contribute to understanding of the physical properties that govern megathrust slip processes.

Local/non-local regularized image segmentation using graph-cuts: application to dynamic and multispectral MRI.

PubMed

Hanson, Erik A; Lundervold, Arvid

2013-11-01

Multispectral, multichannel, or time series image segmentation is important for image analysis in a wide range of applications. Regularization of the segmentation is commonly performed using local image information causing the segmented image to be locally smooth or piecewise constant. A new spatial regularization method, incorporating non-local information, was developed and tested. Our spatial regularization method applies to feature space classification in multichannel images such as color images and MR image sequences. The spatial regularization involves local edge properties, region boundary minimization, as well as non-local similarities. The method is implemented in a discrete graph-cut setting allowing fast computations. The method was tested on multidimensional MRI recordings from human kidney and brain in addition to simulated MRI volumes. The proposed method successfully segment regions with both smooth and complex non-smooth shapes with a minimum of user interaction.

Semi-automated brain tumor segmentation on multi-parametric MRI using regularized non-negative matrix factorization.

PubMed

Sauwen, Nicolas; Acou, Marjan; Sima, Diana M; Veraart, Jelle; Maes, Frederik; Himmelreich, Uwe; Achten, Eric; Huffel, Sabine Van

2017-05-04

Segmentation of gliomas in multi-parametric (MP-)MR images is challenging due to their heterogeneous nature in terms of size, appearance and location. Manual tumor segmentation is a time-consuming task and clinical practice would benefit from (semi-) automated segmentation of the different tumor compartments. We present a semi-automated framework for brain tumor segmentation based on non-negative matrix factorization (NMF) that does not require prior training of the method. L1-regularization is incorporated into the NMF objective function to promote spatial consistency and sparseness of the tissue abundance maps. The pathological sources are initialized through user-defined voxel selection. Knowledge about the spatial location of the selected voxels is combined with tissue adjacency constraints in a post-processing step to enhance segmentation quality. The method is applied to an MP-MRI dataset of 21 high-grade glioma patients, including conventional, perfusion-weighted and diffusion-weighted MRI. To assess the effect of using MP-MRI data and the L1-regularization term, analyses are also run using only conventional MRI and without L1-regularization. Robustness against user input variability is verified by considering the statistical distribution of the segmentation results when repeatedly analyzing each patient's dataset with a different set of random seeding points. Using L1-regularized semi-automated NMF segmentation, mean Dice-scores of 65%, 74 and 80% are found for active tumor, the tumor core and the whole tumor region. Mean Hausdorff distances of 6.1 mm, 7.4 mm and 8.2 mm are found for active tumor, the tumor core and the whole tumor region. Lower Dice-scores and higher Hausdorff distances are found without L1-regularization and when only considering conventional MRI data. Based on the mean Dice-scores and Hausdorff distances, segmentation results are competitive with state-of-the-art in literature. Robust results were found for most patients, although careful voxel selection is mandatory to avoid sub-optimal segmentation.

Effects of oceanographic factors on spatial distribution of Whale Shark in Cendrawasih Bay National Park, West Papua

NASA Astrophysics Data System (ADS)

Ranintyari, Maulida; Sunarto; Syamsuddin, Mega L.; Astuty, Sri

2018-05-01

Whale sharks are a leading species in Cendrawasih Bay due to its benign nature and its regular appearance. Recently, whale sharks are vulnerable to scarcity and even extinction. One of the efforts to maintain the existence of the whale shark population is by knowing its spatial distribution. This study aims to analyze how the oceanographic factors affect the spatial distribution of whale sharks in Cendrawasih Bay National Park. The method used in this research is descriptive with the quantitative approach using the Generalized Additive Model (GAM) analysis. The data consisted of the whale shark monitoring data in TNTC taken by WWF-Indonesia, and image data of sea surface temperature (SST) and chlorophyll-a concentration of Aqua-MODIS, and also sea surface current from Aviso. Analyses were conducted for the period of January 2012 until March 2015. The GAM result indicated that sea surface current was better than the other environment (SST and chlorophyll-a concentration) as an oceanographic predictor of whale shark appearance. High probabilities of the whale shark’s to appear on the surface were observed in sea surface current velocities between 0.30-0.60 m/s, for SST ranged from 30.50-31.80 °C, and for chlorophyll-a concentration ranged from 0.20-0.40 mg/m3.

Retaining both discrete and smooth features in 1D and 2D NMR relaxation and diffusion experiments

NASA Astrophysics Data System (ADS)

Reci, A.; Sederman, A. J.; Gladden, L. F.

2017-11-01

A new method of regularization of 1D and 2D NMR relaxation and diffusion experiments is proposed and a robust algorithm for its implementation is introduced. The new form of regularization, termed the Modified Total Generalized Variation (MTGV) regularization, offers a compromise between distinguishing discrete and smooth features in the reconstructed distributions. The method is compared to the conventional method of Tikhonov regularization and the recently proposed method of L1 regularization, when applied to simulated data of 1D spin-lattice relaxation, T1, 1D spin-spin relaxation, T2, and 2D T1-T2 NMR experiments. A range of simulated distributions composed of two lognormally distributed peaks were studied. The distributions differed with regard to the variance of the peaks, which were designed to investigate a range of distributions containing only discrete, only smooth or both features in the same distribution. Three different signal-to-noise ratios were studied: 2000, 200 and 20. A new metric is proposed to compare the distributions reconstructed from the different regularization methods with the true distributions. The metric is designed to penalise reconstructed distributions which show artefact peaks. Based on this metric, MTGV regularization performs better than Tikhonov and L1 regularization in all cases except when the distribution is known to only comprise of discrete peaks, in which case L1 regularization is slightly more accurate than MTGV regularization.

Mapping fields of 137Cs contamination in soils in the context of their stability and hierarchical spatial structure

NASA Astrophysics Data System (ADS)

Korobova, E.; Romanov, S.

2009-04-01

Technogenic radioisotopes now dispersed in the environment are involved in natural and technogenic processes forming specific geochemical fields and serving as tracers of modern mass migration and geofield transformation. Cs-137 radioisotopes having a comparatively long life time are known for a fast fixation by the top soil layer; radiocesium activity can be measured in the surface layer in field conditions. This makes 137Cs rather convenient for the study and modeling a behavior of toxic elements in soils [1-3, 5] and for the investigation of relative stability and hierarchical fractal structures of the soil contamination of the atmospheric origin [2]. The objective of the experimental study performed on the test site in Bryansk region was to find and prove polycentric regularities in the structure of 137Cs contamination field formed after the Chernobyl accident in natural conditions. Such a character of spatial variability can be seen on the maps showing different soil parameters and chemical element distribution measured in grids [3-5]. The research was undertaken to support our idea of the regular patterns in the contamination field structure that enables to apply a mathematical theory of the field to the geochemical fields modeling on the basis of a limited number of direct measurements sufficient to reproduce the configuration and main parameters of the geochemical field structure on the level of the elementary landscape geochemical system (top-slope-bottom). Cs-137 field measurements were verified by a direct soil sampling. Soil cores dissected into subsamples with increments of 2, 5 and 10 cm, were taken to the depth of 40 cm at points with various surface activity located at different elements of relief. According to laboratory measurements 137Cs inventory in soils varied from 344 to 3448 kBq/m2 (983 kBq/m2 on the average). From 95,1% to 98,0% to of the total inventory was retained in the top 20-cm soil layer. This confirmed that field gamma spectrometry could be used to investigate patterns of 137Cs spatial redistribution in the top soil layers. The portion of 137Cs conserved in top layers corresponded to the meso- and micro relief elements. The character and stability of 137Cs spatial structure was studied by measuring its activity within nested plots with different steps of 5, 2, 1 and 0,2 m (the latter was a minimum resolution step for the field NaI detector). Performed measurements showed that the contamination field of 137Cs had a regular structure of polycentric character and exhibited a decrease in spatial variability of contamination with the decrease of the measured area. Repeated measurements of soil contamination in successive years of 2005-2008 along and cross the slopes provided with topographic survey proved the stability of contamination field (r=0, 915, n=121, r=0,912, n=30) and its relation to the meso- and microrelief features. Variation 137Cs activity in lateral direction (along the slopes and thalweg of the hollow)showed a regular character also. In our opinion the regularity in 137Cs spatial structure in the soil cover may result from radionuclide redistribution with the surface and subsurface water flow highly sensitive to the changes in elevation of different scale, and to the slope length and inclination. Cs-137 lateral distribution pattern was likely to reflect alternation of lateral and vertical water mass migration along the slopes. The performed study showing regularity in 137Cs redistribution seems to open new possibilities to develop the deterministic strategy in the study of contamination fields and modeling toxic elements spatial distribution in the soil cover on different scales. The authors are much obliged to Dr. V. Samsonov and Dr. F. Moiseenko for participation in the field work and to S. Kirov for the performance of the laboratory measurement of the soil and plant samples. References 1. Khomutinin, Yu.V., Kashparov, V.A., Zhebrovskaya, E.I., 2001. Optimization of sampling and measurement of the specimen for radioecological monitoring. UkrNIISKHR, Kiev. 2. Korobova, E.M., Romanov, S.L., Samsonov, V.L., Kirov, S.S., 2006. Experimental study of spatial 137Cs redistribution in paragenetic elementary landscapes, in: Kasimov, N.S. et al (Eds.), Geochemistry of biosphere (devoted to 90-th anniversary of A.I. Perelman), MSU, IGEM, RFFI, Moscow-Smolensk, pp.157-159. 3. Linnik, V.G., Saveliev, A.A., Govorun, A.P., Ivanitsky, O.M., Sokolov, A.V., 2006. Analysis of the Cs-137 contamination field on micro-landscape scale within the virgin meadows in the western part of the Bryansk region, in: Kasimov, N.S. et al (Eds.), Geochemistry of biosphere (devoted to 90-th anniversary of A.I. Perelman), MSU, IGEM, RFFI, Moscow-Smolensk, pp. 201-204. 4. Samsonova V.P. Spatial variability of the soil parameters. On example of soddy-podozolic soils. Moscow, LKI, 2008, 156 p. 5.Shcheglov, A.I., Tsvetnova, O.B., Klyashtorin, A.I., 2001. Biogeochemical migration of technogenic radionuclides in forest ecosystems. Nauka, Moscow.

Activation Time of Cardiac Tissue In Response to a Linear Array of Spatial Alternating Bipolar Electrodes

NASA Astrophysics Data System (ADS)

Mashburn, David; Wikswo, John

2007-11-01

Prevailing theories about the response of the heart to high field shocks predict that local regions of high resistivity distributed throughout the heart create multiple small virtual electrodes that hyperpolarize or depolarize tissue and lead to widespread activation. This resetting of bulk tissue is responsible for the successful functioning of cardiac defibrillators. By activating cardiac tissue with regular linear arrays of spatially alternating bipolar currents, we can simulate these potentials locally. We have studied the activation time due to distributed currents in both a 1D Beeler-Reuter model and on the surface of the whole heart, varying the strength of each source and the separation between them. By comparison with activation time data from actual field shock of a whole heart in a bath, we hope to better understand these transient virtual electrodes. Our work was done on rabbit RV using florescent optical imaging and our Phased Array Stimulator for driving the 16 current sources. Our model shows that for a total absolute current delivered to a region of tissue, the entire region activates faster if above-threshold sources are more distributed.

Polydomy in the ant Ectatomma opaciventre

PubMed Central

Tofolo, Viviane C.; Giannotti, Edilberto; Neves, Erika F.; Andrade, Luis H. C.; M. Lima, Sandro; Súarez, Yzel R.; Antonialli-Junior, William F.

2014-01-01

Abstract Tropical ants commonly exhibit a hyper-dispersed pattern of spatial distribution of nests. In polydomous species, nests may be satellites, that is, secondary structures of the main nest, where the queen is found. In order to evaluate whether the ant Ectatomma opaciventre Roger (Formicidae: Ectatomminae) uses the strategy of building polydomous nests, the spatial distribution pattern of 33 nests in a 1,800 m 2 degraded area located in Rio Claro, SP, Brazil, were investigated using the nearest neighbor method. To complement the results of this investigation, the cuticular chemical profile of eight colonies was analyzed using Fourier transform infrared photoacoustic spectrosco-py (FTIR-PAS). The nests of E. opaciventre presented a hyper-dispersed or regular distribution, which is the most common in ants. The analysis of the cuticular hydrocarbons apparently con-firmed the hypothesis that this species is polydomous, since the chemical profiles of all studied colonies with nests at different sites were very similar to the chemical signature of the single found queen and were also different from those of colonies used as control. PMID:25373168

An improved geographically weighted regression model for PM2.5 concentration estimation in large areas

NASA Astrophysics Data System (ADS)

Zhai, Liang; Li, Shuang; Zou, Bin; Sang, Huiyong; Fang, Xin; Xu, Shan

2018-05-01

Considering the spatial non-stationary contributions of environment variables to PM2.5 variations, the geographically weighted regression (GWR) modeling method has been using to estimate PM2.5 concentrations widely. However, most of the GWR models in reported studies so far were established based on the screened predictors through pretreatment correlation analysis, and this process might cause the omissions of factors really driving PM2.5 variations. This study therefore developed a best subsets regression (BSR) enhanced principal component analysis-GWR (PCA-GWR) modeling approach to estimate PM2.5 concentration by fully considering all the potential variables' contributions simultaneously. The performance comparison experiment between PCA-GWR and regular GWR was conducted in the Beijing-Tianjin-Hebei (BTH) region over a one-year-period. Results indicated that the PCA-GWR modeling outperforms the regular GWR modeling with obvious higher model fitting- and cross-validation based adjusted R2 and lower RMSE. Meanwhile, the distribution map of PM2.5 concentration from PCA-GWR modeling also clearly depicts more spatial variation details in contrast to the one from regular GWR modeling. It can be concluded that the BSR enhanced PCA-GWR modeling could be a reliable way for effective air pollution concentration estimation in the coming future by involving all the potential predictor variables' contributions to PM2.5 variations.

Spatial Distribution and Coexisting Patterns of Adults and Nymphs of Tibraca limbativentris (Hemiptera: Pentatomidae) in Paddy Rice Fields.

PubMed

Alves, Tavvs M; Maia, Aline H N; Barrigossi, José A F

2016-12-01

The rice stem stink bug, Tibraca limbativentris Stål (Hemiptera: Pentatomidae), is a primary insect pest of paddy rice in South America. Knowledge of its spatial distribution can support sampling plans needed for timely decisions about pest control. This study aimed to investigate the spatial distribution of adults and nymphs of T. limbativentris and determine the spatial coexistence of these stages of development. Fifteen paddy rice fields were scouted once each season to estimate insect densities. Scouting was performed on regular grids with sampling points separated by ∼50 m. Moran's I and semivariograms were used to determine spatial distribution patterns. Spatial coexistence of nymphs and adults was explored via spatial point process. Here, adults and nymphs had typically contrasting spatial distribution patterns within the same field; however, the frequency of aggregation was not different between these developmental stages. Adults and nymphs were aggregated in seven fields and randomly distributed in the other eight fields. Uniform distribution of adults or nymphs was not observed. The study-wide semivariogram ranges were ∼40 m for adults and ∼55 m for nymphs. Nymphs and adults spatially coexisted on 67% of the fields. Coexisting patterns were classified using one of the following processes: stage-independent, bidirectional attractive, unidirectional attractive, bidirectional inhibiting, or unidirectional inhibiting. The information presented herein can be important for developing sampling plans for decision-making, implementing tactics for site-specific management, and monitoring areas free of T. limbativentrisResumoO percevejo-do-colmo Tibraca limbativentris Stål (Hemiptera: Pentatomidae) é uma praga primária na cultura do arroz irrigado na América do Sul. O conhecimento de sua distribuição espacial é essencial para desenvolver planos de amostragem e para o controle desta praga. Nosso objetivo foi investigar a distribuição espacial de adultos e ninfas de T. limbativentris e determinar a coexistência espacial entre os estágios de desenvolvimento. As densidades de adultos e ninfas foram estimadas em quinze campos de arroz irrigado. A amostragem foi realizada em grades regulares com pontos de amostragem separados por ∼50 m. Moran's I e semivariogramas foram usados para determinar os padrões de distribuição espacial. A coexistência espacial foi explorada pela análise de processos pontuais. Foi observado que adultos e ninfas tiveram padrões contrastantes de distribuição espacial dentro do mesmo campo; no entanto, a frequência de agregação não foi diferente entre esses estágios de desenvolvimento. Adultos e ninfas estavam agregados em sete campos e distribuídos aleatoriamente nos outros oito campos. Não foi observada a distribuição uniforme de adultos ou ninfas. O alcance médio dos semivariogramas foi de ∼40 m para os adultos e ∼55 m para as ninfas. Ninfas e adultos coexistiram espacialmente em 67% dos campos. Os padrões de coexistência foram classificados usando um dos seguintes processos: independente do estágio de desenvolvimento, atração bilateral, atração unilateral, inibição bilateral, ou inibição unilateral. Nosso estudo poderá contribuir para o desenvolvimento de planos de amostragem para tomada de decisão e implementação de táticas para o manejo de sítios específicos. © The Authors 2016. Published by Oxford University Press on behalf of Entomological Society of America. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

The effect of thermomechanical treatment regimes on microstructure and mechanical properties of V–Me(Cr, W)–Zr–C alloys

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

Tyumentsev, A. N., E-mail: tyuments@phys.tsu.ru; Ditenberg, I. A.; Grinyaev, K. V.

2015-12-15

The regularities of the formation of a heterophase structure in dispersion-strengthened vanadium V–Me(Cr, W)–Zr–C alloys are studied as a function of the regimes of their thermomechanical treatment. The regimes of treatment providing a substantial increase in the dispersity and homogeneity of spatial distribution of ZrC particles, temperature of recrystallization, and high-temperature (at T = 800°C) short-time strength are found in comparison to conventional treatment regimes.

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.

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.

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

NASA Astrophysics Data System (ADS)

Wang, J.; Cai, X.

2007-12-01

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

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.

Limited angle CT reconstruction by simultaneous spatial and Radon domain regularization based on TV and data-driven tight frame

NASA Astrophysics Data System (ADS)

Zhang, Wenkun; Zhang, Hanming; Wang, Linyuan; Cai, Ailong; Li, Lei; Yan, Bin

2018-02-01

Limited angle computed tomography (CT) reconstruction is widely performed in medical diagnosis and industrial testing because of the size of objects, engine/armor inspection requirements, and limited scan flexibility. Limited angle reconstruction necessitates usage of optimization-based methods that utilize additional sparse priors. However, most of conventional methods solely exploit sparsity priors of spatial domains. When CT projection suffers from serious data deficiency or various noises, obtaining reconstruction images that meet the requirement of quality becomes difficult and challenging. To solve this problem, this paper developed an adaptive reconstruction method for limited angle CT problem. The proposed method simultaneously uses spatial and Radon domain regularization model based on total variation (TV) and data-driven tight frame. Data-driven tight frame being derived from wavelet transformation aims at exploiting sparsity priors of sinogram in Radon domain. Unlike existing works that utilize pre-constructed sparse transformation, the framelets of the data-driven regularization model can be adaptively learned from the latest projection data in the process of iterative reconstruction to provide optimal sparse approximations for given sinogram. At the same time, an effective alternating direction method is designed to solve the simultaneous spatial and Radon domain regularization model. The experiments for both simulation and real data demonstrate that the proposed algorithm shows better performance in artifacts depression and details preservation than the algorithms solely using regularization model of spatial domain. Quantitative evaluations for the results also indicate that the proposed algorithm applying learning strategy performs better than the dual domains algorithms without learning regularization model

In situ analysis of the organic framework in the prismatic layer of mollusc shell.

PubMed

Tong, Hua; Hu, Jiming; Ma, Wentao; Zhong, Guirong; Yao, Songnian; Cao, Nianxing

2002-06-01

A novel in situ analytic approach was constructed by means of ion sputtering, decalcification and deprotein techniques combining with scanning electron microscopy (SEM) and transmission electron microscope (TEM) ultrastructural analysis. The method was employed to determine the spatial distribution of the organic framework outside and the inner crystal and organic/inorganic interface spatial geometrical relationship in the prismatic layer of cristaris plicate (leach). The results show that there is a substructure of organic matrix in the intracrystalline region. The prismatic layer forms according to strict hierarchical configuration of regular pattern. Each unit of organic template of prismatic layer can uniquely determine the column crystal growth direction, spatial orientation and size. Cavity templates are responsible for supporting. limiting size and shape and determining the crystal growth spatial orientation, while the intracrystal organic matrix is responsible for providing nucleation point and inducing the nucleation process of calcite. The stereo hierarchical fabrication of prismatic layer was elucidated for the first time.

Osprey: worldwide sentinel species for assessing and monitoring environmental contamination in rivers, lakes, reservoirs, and estuaries.

PubMed

Grove, Robert A; Henny, Charles J; Kaiser, James L

2009-01-01

In the United States, many fish and wildlife species have been used nationwide to monitor environmental contaminant exposure and effects, including carcasses of the bald eagle (Haliaeetus leucocephalus), the only top avian predator regularly used in the past. Unfortunately, bald eagles are sensitive to investigator intrusion at the nest. Thus, the osprey (Pandion haliaetus) is evaluated as a potential sentinel species for aquatic ecosystems. Several characteristics support the choice of the osprey as a sentinel species, including: (1) fish-eating diet atop the aquatic food web, (2) long-lived with strong nest fidelity, (3) adapts to human landscapes (potentially the most contaminated), (4) tolerates short-term nest disturbance, (5) nests spatially distributed at regular intervals, (6) highly visible nests easily located for study, (7) ability to accumulate most, if not all, lipophilic contaminants, (8) known sensitivity to many contaminants, and (9) nearly a worldwide distribution. These osprey traits have been instrumental in successfully using the species to understand population distribution, abundance, and changes over time; the effects of various contaminants on reproductive success; how contaminants in prey (fish on biomass basis) contribute to egg concentrations (i.e., biomagnification factors); and spatial residue patterns. Data summarized include nesting population surveys, detailed nesting studies, and chemical analyses of osprey egg, organ, blood, and feather samples for contaminants that bioaccumulate and/or biomagnify in aquatic food webs; and biochemical evaluations of blood and various organs. Studies in the United States, Canada, Mexico, Europe, and elsewhere have shown the osprey to be a useful sentinel species for monitoring selected environmental contaminants, including some emerging contaminants in lakes, reservoirs, rivers, and estuaries.

Towards the mechanical characterization of abdominal wall by inverse analysis.

PubMed

Simón-Allué, R; Calvo, B; Oberai, A A; Barbone, P E

2017-02-01

The aim of this study is to characterize the passive mechanical behaviour of abdominal wall in vivo in an animal model using only external cameras and numerical analysis. The main objective lies in defining a methodology that provides in vivo information of a specific patient without altering mechanical properties. It is demonstrated in the mechanical study of abdomen for hernia purposes. Mechanical tests consisted on pneumoperitoneum tests performed on New Zealand rabbits, where inner pressure was varied from 0mmHg to 12mmHg. Changes in the external abdominal surface were recorded and several points were tracked. Based on their coordinates we reconstructed a 3D finite element model of the abdominal wall, considering an incompressible hyperelastic material model defined by two parameters. The spatial distributions of these parameters (shear modulus and non linear parameter) were calculated by inverse analysis, using two different types of regularization: Total Variation Diminishing (TVD) and Tikhonov (H 1 ). After solving the inverse problem, the distribution of the material parameters were obtained along the abdominal surface. Accuracy of the results was evaluated for the last level of pressure. Results revealed a higher value of the shear modulus in a wide stripe along the craneo-caudal direction, associated with the presence of linea alba in conjunction with fascias and rectus abdominis. Non linear parameter distribution was smoother and the location of higher values varied with the regularization type. Both regularizations proved to yield in an accurate predicted displacement field, but H 1 obtained a smoother material parameter distribution while TVD included some discontinuities. The methodology here presented was able to characterize in vivo the passive non linear mechanical response of the abdominal wall. Copyright © 2016 Elsevier Ltd. All rights reserved.

Statistical analysis of nonlinearly reconstructed near-infrared tomographic images: Part I--Theory and simulations.

PubMed

Pogue, Brian W; Song, Xiaomei; Tosteson, Tor D; McBride, Troy O; Jiang, Shudong; Paulsen, Keith D

2002-07-01

Near-infrared (NIR) diffuse tomography is an emerging method for imaging the interior of tissues to quantify concentrations of hemoglobin and exogenous chromophores non-invasively in vivo. It often exploits an optical diffusion model-based image reconstruction algorithm to estimate spatial property values from measurements of the light flux at the surface of the tissue. In this study, mean-squared error (MSE) over the image is used to evaluate methods for regularizing the ill-posed inverse image reconstruction problem in NIR tomography. Estimates of image bias and image standard deviation were calculated based upon 100 repeated reconstructions of a test image with randomly distributed noise added to the light flux measurements. It was observed that the bias error dominates at high regularization parameter values while variance dominates as the algorithm is allowed to approach the optimal solution. This optimum does not necessarily correspond to the minimum projection error solution, but typically requires further iteration with a decreasing regularization parameter to reach the lowest image error. Increasing measurement noise causes a need to constrain the minimum regularization parameter to higher values in order to achieve a minimum in the overall image MSE.

Three-dimensional ionospheric tomography reconstruction using the model function approach in Tikhonov regularization

NASA Astrophysics Data System (ADS)

Wang, Sicheng; Huang, Sixun; Xiang, Jie; Fang, Hanxian; Feng, Jian; Wang, Yu

2016-12-01

Ionospheric tomography is based on the observed slant total electron content (sTEC) along different satellite-receiver rays to reconstruct the three-dimensional electron density distributions. Due to incomplete measurements provided by the satellite-receiver geometry, it is a typical ill-posed problem, and how to overcome the ill-posedness is still a crucial content of research. In this paper, Tikhonov regularization method is used and the model function approach is applied to determine the optimal regularization parameter. This algorithm not only balances the weights between sTEC observations and background electron density field but also converges globally and rapidly. The background error covariance is given by multiplying background model variance and location-dependent spatial correlation, and the correlation model is developed by using sample statistics from an ensemble of the International Reference Ionosphere 2012 (IRI2012) model outputs. The Global Navigation Satellite System (GNSS) observations in China are used to present the reconstruction results, and measurements from two ionosondes are used to make independent validations. Both the test cases using artificial sTEC observations and actual GNSS sTEC measurements show that the regularization method can effectively improve the background model outputs.

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.

Probability density of spatially distributed soil moisture inferred from crosshole georadar traveltime measurements

NASA Astrophysics Data System (ADS)

Linde, N.; Vrugt, J. A.

2009-04-01

Geophysical models are increasingly used in hydrological simulations and inversions, where they are typically treated as an artificial data source with known uncorrelated "data errors". The model appraisal problem in classical deterministic linear and non-linear inversion approaches based on linearization is often addressed by calculating model resolution and model covariance matrices. These measures offer only a limited potential to assign a more appropriate "data covariance matrix" for future hydrological applications, simply because the regularization operators used to construct a stable inverse solution bear a strong imprint on such estimates and because the non-linearity of the geophysical inverse problem is not explored. We present a parallelized Markov Chain Monte Carlo (MCMC) scheme to efficiently derive the posterior spatially distributed radar slowness and water content between boreholes given first-arrival traveltimes. This method is called DiffeRential Evolution Adaptive Metropolis (DREAM_ZS) with snooker updater and sampling from past states. Our inverse scheme does not impose any smoothness on the final solution, and uses uniform prior ranges of the parameters. The posterior distribution of radar slowness is converted into spatially distributed soil moisture values using a petrophysical relationship. To benchmark the performance of DREAM_ZS, we first apply our inverse method to a synthetic two-dimensional infiltration experiment using 9421 traveltimes contaminated with Gaussian errors and 80 different model parameters, corresponding to a model discretization of 0.3 m × 0.3 m. After this, the method is applied to field data acquired in the vadose zone during snowmelt. This work demonstrates that fully non-linear stochastic inversion can be applied with few limiting assumptions to a range of common two-dimensional tomographic geophysical problems. The main advantage of DREAM_ZS is that it provides a full view of the posterior distribution of spatially distributed soil moisture, which is key to appropriately treat geophysical parameter uncertainty and infer hydrologic models.

Structural control of elastic moduli in ferrogels and the importance of non-affine deformations

NASA Astrophysics Data System (ADS)

Pessot, Giorgio; Cremer, Peet; Borin, Dmitry Y.; Odenbach, Stefan; Löwen, Hartmut; Menzel, Andreas M.

2014-09-01

One of the central appealing properties of magnetic gels and elastomers is that their elastic moduli can reversibly be adjusted from outside by applying magnetic fields. The impact of the internal magnetic particle distribution on this effect has been outlined and analyzed theoretically. In most cases, however, affine sample deformations are studied and often regular particle arrangements are considered. Here we challenge these two major simplifications by a systematic approach using a minimal dipole-spring model. Starting from different regular lattices, we take into account increasingly randomized structures, until we finally investigate an irregular texture taken from a real experimental sample. On the one hand, we find that the elastic tunability qualitatively depends on the structural properties, here in two spatial dimensions. On the other hand, we demonstrate that the assumption of affine deformations leads to increasingly erroneous results the more realistic the particle distribution becomes. Understanding the consequences of the assumptions made in the modeling process is important on our way to support an improved design of these fascinating materials.

MASS ESTIMATES OF RAPIDLY MOVING PROMINENCE MATERIAL FROM HIGH-CADENCE EUV IMAGES

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

Williams, David R.; Baker, Deborah; Van Driel-Gesztelyi, Lidia, E-mail: d.r.williams@ucl.ac.uk

We present a new method for determining the column density of erupting filament material using state-of-the-art multi-wavelength imaging data. Much of the prior work on filament/prominence structure can be divided between studies that use a polychromatic approach with targeted campaign observations and those that use synoptic observations, frequently in only one or two wavelengths. The superior time resolution, sensitivity, and near-synchronicity of data from the Solar Dynamics Observatory's Advanced Imaging Assembly allow us to combine these two techniques using photoionization continuum opacity to determine the spatial distribution of hydrogen in filament material. We apply the combined techniques to SDO/AIA observationsmore » of a filament that erupted during the spectacular coronal mass ejection on 2011 June 7. The resulting 'polychromatic opacity imaging' method offers a powerful way to track partially ionized gas as it erupts through the solar atmosphere on a regular basis, without the need for coordinated observations, thereby readily offering regular, realistic mass-distribution estimates for models of these erupting structures.« less

Accurate mask-based spatially regularized correlation filter for visual tracking

NASA Astrophysics Data System (ADS)

Gu, Xiaodong; Xu, Xinping

2017-01-01

Recently, discriminative correlation filter (DCF)-based trackers have achieved extremely successful results in many competitions and benchmarks. These methods utilize a periodic assumption of the training samples to efficiently learn a classifier. However, this assumption will produce unwanted boundary effects, which severely degrade the tracking performance. Correlation filters with limited boundaries and spatially regularized DCFs were proposed to reduce boundary effects. However, their methods used the fixed mask or predesigned weights function, respectively, which was unsuitable for large appearance variation. We propose an accurate mask-based spatially regularized correlation filter for visual tracking. Our augmented objective can reduce the boundary effect even in large appearance variation. In our algorithm, the masking matrix is converted into the regularized function that acts on the correlation filter in frequency domain, which makes the algorithm fast convergence. Our online tracking algorithm performs favorably against state-of-the-art trackers on OTB-2015 Benchmark in terms of efficiency, accuracy, and robustness.

Downscaling Satellite Precipitation with Emphasis on Extremes: A Variational ℓ1-Norm Regularization in the Derivative Domain

NASA Astrophysics Data System (ADS)

Foufoula-Georgiou, E.; Ebtehaj, A. M.; Zhang, S. Q.; Hou, A. Y.

2014-05-01

The increasing availability of precipitation observations from space, e.g., from the Tropical Rainfall Measuring Mission (TRMM) and the forthcoming Global Precipitation Measuring (GPM) Mission, has fueled renewed interest in developing frameworks for downscaling and multi-sensor data fusion that can handle large data sets in computationally efficient ways while optimally reproducing desired properties of the underlying rainfall fields. Of special interest is the reproduction of extreme precipitation intensities and gradients, as these are directly relevant to hazard prediction. In this paper, we present a new formalism for downscaling satellite precipitation observations, which explicitly allows for the preservation of some key geometrical and statistical properties of spatial precipitation. These include sharp intensity gradients (due to high-intensity regions embedded within lower-intensity areas), coherent spatial structures (due to regions of slowly varying rainfall), and thicker-than-Gaussian tails of precipitation gradients and intensities. Specifically, we pose the downscaling problem as a discrete inverse problem and solve it via a regularized variational approach (variational downscaling) where the regularization term is selected to impose the desired smoothness in the solution while allowing for some steep gradients (called ℓ1-norm or total variation regularization). We demonstrate the duality between this geometrically inspired solution and its Bayesian statistical interpretation, which is equivalent to assuming a Laplace prior distribution for the precipitation intensities in the derivative (wavelet) space. When the observation operator is not known, we discuss the effect of its misspecification and explore a previously proposed dictionary-based sparse inverse downscaling methodology to indirectly learn the observation operator from a data base of coincidental high- and low-resolution observations. The proposed method and ideas are illustrated in case studies featuring the downscaling of a hurricane precipitation field.

Downscaling Satellite Precipitation with Emphasis on Extremes: A Variational 1-Norm Regularization in the Derivative Domain

NASA Technical Reports Server (NTRS)

Foufoula-Georgiou, E.; Ebtehaj, A. M.; Zhang, S. Q.; Hou, A. Y.

2013-01-01

The increasing availability of precipitation observations from space, e.g., from the Tropical Rainfall Measuring Mission (TRMM) and the forthcoming Global Precipitation Measuring (GPM) Mission, has fueled renewed interest in developing frameworks for downscaling and multi-sensor data fusion that can handle large data sets in computationally efficient ways while optimally reproducing desired properties of the underlying rainfall fields. Of special interest is the reproduction of extreme precipitation intensities and gradients, as these are directly relevant to hazard prediction. In this paper, we present a new formalism for downscaling satellite precipitation observations, which explicitly allows for the preservation of some key geometrical and statistical properties of spatial precipitation. These include sharp intensity gradients (due to high-intensity regions embedded within lower-intensity areas), coherent spatial structures (due to regions of slowly varying rainfall),and thicker-than-Gaussian tails of precipitation gradients and intensities. Specifically, we pose the downscaling problem as a discrete inverse problem and solve it via a regularized variational approach (variational downscaling) where the regularization term is selected to impose the desired smoothness in the solution while allowing for some steep gradients(called 1-norm or total variation regularization). We demonstrate the duality between this geometrically inspired solution and its Bayesian statistical interpretation, which is equivalent to assuming a Laplace prior distribution for the precipitation intensities in the derivative (wavelet) space. When the observation operator is not known, we discuss the effect of its misspecification and explore a previously proposed dictionary-based sparse inverse downscaling methodology to indirectly learn the observation operator from a database of coincidental high- and low-resolution observations. The proposed method and ideas are illustrated in case studies featuring the downscaling of a hurricane precipitation field.

Staircase and saw-tooth field emission steps from nanopatterned n-type GaSb surfaces

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

Kildemo, M.; Levinsen, Y. Inntjore; Le Roy, S.

2009-09-15

High resolution field emission experiments from nanopatterned GaSb surfaces consisting of densely packed nanocones prepared by low ion-beam-energy sputtering are presented. Both uncovered and metal-covered nanopatterned surfaces were studied. Surprisingly, the field emission takes place by regular steps in the field emitted current. Depending on the field, the steps are either regular, flat, plateaus, or saw-tooth shaped. To the author's knowledge, this is the first time that such results have been reported. Each discrete jump in the field emission may be understood in terms of resonant tunneling through an extended surface space charge region in an n-type, high aspect ratio,more » single GaSb nanocone. The staircase shape may be understood from the spatial distribution of the aspect ratio of the cones.« less

Cabri 3D - assisted collaborative learning to enhance junior high school students’ spatial ability

NASA Astrophysics Data System (ADS)

Muntazhimah; Miatun, A.

2018-01-01

The main purpose of this quasi-experimental study was to determine the enhancement of spatial ability of junior high school students who learned through Cabri-3D assisted collaborative learning. The methodology of this study was the nonequivalent group that was conducted to students of the eighth grade in a junior high school as a population. Samples consisted one class of the experimental group who studied with Cabri-3D assisted collaborative learning and one class as a control group who got regular learning activity. The instrument used in this study was a spatial ability test. Analyzing normalized gain of students’ spatial ability based on mathemathical prior knowledge (MPK) and its interactions was tested by two-way ANOVA at a significance level of 5% then continued with using Post Hoc Scheffe test. The research results showed that there was significant difference in enhancement of the spatial ability between students who learnt with Cabri 3D assisted collaborative learning and students who got regular learning, there was significant difference in enhancement of the spatial ability between students who learnt with cabri 3D assisted collaborative learning and students who got regular learning in terms of MPK and there is no significant interaction between learning (Cabri-3D assisted collaborative learning and regular learning) with students’ MPK (high, medium, and low) toward the enhancement of students’ spatial abilities. From the above findings, it can be seen that cabri-3D assisted collaborative learning could enhance spatial ability of junior high school students.

Four millennia of woodland structure and dynamics at the Arctic treeline of eastern Canada.

PubMed

Auger, Sarah; Payette, Serge

2010-05-01

Paleoecological analysis using complementary indicators of vegetation and soil can provide spatially explicit information on ecological processes influencing trajectories of long-term ecosystem change. Here we document the structure and dynamics of an old-growth woodland before and after its inception 1000 years ago. We infer vegetation and soil characteristics from size and age distributions of black spruce (Picea mariana (Mill.) B.S.P.), soil properties, plant fossils, and paleosols. Radiocarbon ages of charcoal on the ground and in the soil indicate that the fire return interval was approximately 300 years between 2750 and 1000 cal. yr BP. No fire evidence was found before and after this period despite the presence of spruce since 4200 cal. yr BP. The size structures of living and dead spruce suggest that the woodland is in equilibrium with present climate in absence of fire. Tree establishment and mortality occurred regularly since the last fire event around 950 cal. yr BP. Both layering and occasional seeding have contributed to stabilize the spatial distribution of spruce over the past 1000 years. Since initial afforestation, soil development has been homogenized by the changing spatial distribution of spruce following each fire. We conclude that the history of the woodland is characterized by vegetation shifts associated with fire and soil disturbances and by millennial-scale maintenance of the woodland's structure despite changing climatic conditions.

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.

Direct Femtosecond Laser Surface Structuring with Optical Vortex Beams Generated by a q-plate

PubMed Central

JJ Nivas, Jijil; He, Shutong; Rubano, Andrea; Vecchione, Antonio; Paparo, Domenico; Marrucci, Lorenzo; Bruzzese, Riccardo; Amoruso, Salvatore

2015-01-01

Creation of patterns and structures on surfaces at the micro- and nano-scale is a field of growing interest. Direct femtosecond laser surface structuring with a Gaussian-like beam intensity profile has already distinguished itself as a versatile method to fabricate surface structures on metals and semiconductors. Here we present an approach for direct femtosecond laser surface structuring based on optical vortex beams with different spatial distributions of the state of polarization, which are easily generated by means of a q-plate. The different states of an optical vortex beam carrying an orbital angular momentum ℓ = ±1 are used to demonstrate the fabrication of various regular surface patterns on silicon. The spatial features of the regular rippled and grooved surface structures are correlated with the state of polarization of the optical vortex beam. Moreover, scattered surface wave theory approach is used to rationalize the dependence of the surface structures on the local state of the laser beam characteristics (polarization and fluence). The present approach can be further extended to fabricate even more complex and unconventional surface structures by exploiting the possibilities offered by femtosecond optical vector fields. PMID:26658307

Time for bed: associations with cognitive performance in 7-year-old children: a longitudinal population-based study

PubMed Central

Kelly, Yvonne; Kelly, John; Sacker, Amanda

2013-01-01

Background Little is known about the links between the time that young children go to bed and their cognitive development. In this paper we seek to examine whether bedtimes in early childhood are related to cognitive test scores in 7-year-olds. Methods We examined data on bedtimes and cognitive test (z-scores) for reading, maths and spatial abilities for 11 178 7-year-old children from the UK Millennium Cohort Study. Results At age 7, not having a regular bedtime was related to lower cognitive test scores in girls: reading (β: −0.22), maths (β: −0.26) and spatial (β: −0.15), but not for boys. Non-regular bedtimes at age 3 were independently associated, in girls and boys, with lower reading (β: −0.10, −0.20), maths (β: −0.16, −0.11) and spatial (β: −0.13, −0.16) scores. Cumulative relationships were apparent. Girls who never had regular bedtimes at ages 3, 5 and 7 had significantly lower reading (β: −0.36), maths (β: −0.51) and spatial (β: −0.40) scores, while for boys this was the case for those having non-regular bedtimes at any two ages (3, 5 or 7 years): reading (β: −0.28), maths (β: −0.22) and spatial (β: −0.26) scores. In boys having non-regular bedtimes at all three ages (3, 5 and 7 years) were non-significantly related to lower reading, maths and spatial scores. Conclusions The consistent nature of bedtimes during early childhood is related to cognitive performance. Given the importance of early child development, there may be knock on effects for health throughout life. PMID:23835763

Time for bed: associations with cognitive performance in 7-year-old children: a longitudinal population-based study.

PubMed

Kelly, Yvonne; Kelly, John; Sacker, Amanda

2013-11-01

Little is known about the links between the time that young children go to bed and their cognitive development. In this paper we seek to examine whether bedtimes in early childhood are related to cognitive test scores in 7-year-olds. We examined data on bedtimes and cognitive test (z-scores) for reading, maths and spatial abilities for 11 178 7-year-old children from the UK Millennium Cohort Study. At age 7, not having a regular bedtime was related to lower cognitive test scores in girls: reading (β: -0.22), maths (β: -0.26) and spatial (β: -0.15), but not for boys. Non-regular bedtimes at age 3 were independently associated, in girls and boys, with lower reading (β: -0.10, -0.20), maths (β: -0.16, -0.11) and spatial (β: -0.13, -0.16) scores. Cumulative relationships were apparent. Girls who never had regular bedtimes at ages 3, 5 and 7 had significantly lower reading (β: -0.36), maths (β: -0.51) and spatial (β: -0.40) scores, while for boys this was the case for those having non-regular bedtimes at any two ages (3, 5 or 7 years): reading (β: -0.28), maths (β: -0.22) and spatial (β: -0.26) scores. In boys having non-regular bedtimes at all three ages (3, 5 and 7 years) were non-significantly related to lower reading, maths and spatial scores. The consistent nature of bedtimes during early childhood is related to cognitive performance. Given the importance of early child development, there may be knock on effects for health throughout life.

Spatial Distribution of Soil Fauna In Long Term No Tillage

NASA Astrophysics Data System (ADS)

Corbo, J. Z. F.; Vieira, S. R.; Siqueira, G. M.

2012-04-01

The soil is a complex system constituted by living beings, organic and mineral particles, whose components define their physical, chemical and biological properties. Soil fauna plays an important role in soil and may reflect and interfere in its functionality. These organisms' populations may be influenced by management practices, fertilization, liming and porosity, among others. Such changes may reduce the composition and distribution of soil fauna community. Thus, this study aimed to determine the spatial variability of soil fauna in consolidated no-tillage system. The experimental area is located at Instituto Agronômico in Campinas (São Paulo, Brazil). The sampling was conducted in a Rhodic Eutrudox, under no tillage system and 302 points distributed in a 3.2 hectare area in a regular grid of 10.00 m x 10.00 m were sampled. The soil fauna was sampled with "Pitfall Traps" method and traps remained in the area for seven days. Data were analyzed using descriptive statistics to determine the main statistical moments (mean variance, coefficient of variation, standard deviation, skewness and kurtosis). Geostatistical tools were used to determine the spatial variability of the attributes using the experimental semivariogram. For the biodiversity analysis, Shannon and Pielou indexes and richness were calculated for each sample. Geostatistics has proven to be a great tool for mapping the spatial variability of groups from the soil epigeal fauna. The family Formicidae proved to be the most abundant and dominant in the study area. The parameters of descriptive statistics showed that all attributes studied showed lognormal frequency distribution for groups from the epigeal soil fauna. The exponential model was the most suited for the obtained data, for both groups of epigeal soil fauna (Acari, Araneae, Coleoptera, Formicidae and Coleoptera larva), and the other biodiversity indexes. The sampling scheme (10.00 m x 10.00 m) was not sufficient to detect the spatial variability for all groups of soil epigeal fauna found in this study.

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

PubMed

Ding, Qian; Wang, Yong; Zhuang, Dafang

2018-04-15

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

Estimating changes in urban land and urban population using refined areal interpolation techniques

NASA Astrophysics Data System (ADS)

Zoraghein, Hamidreza; Leyk, Stefan

2018-05-01

The analysis of changes in urban land and population is important because the majority of future population growth will take place in urban areas. U.S. Census historically classifies urban land using population density and various land-use criteria. This study analyzes the reliability of census-defined urban lands for delineating the spatial distribution of urban population and estimating its changes over time. To overcome the problem of incompatible enumeration units between censuses, regular areal interpolation methods including Areal Weighting (AW) and Target Density Weighting (TDW), with and without spatial refinement, are implemented. The goal in this study is to estimate urban population in Massachusetts in 1990 and 2000 (source zones), within tract boundaries of the 2010 census (target zones), respectively, to create a consistent time series of comparable urban population estimates from 1990 to 2010. Spatial refinement is done using ancillary variables such as census-defined urban areas, the National Land Cover Database (NLCD) and the Global Human Settlement Layer (GHSL) as well as different combinations of them. The study results suggest that census-defined urban areas alone are not necessarily the most meaningful delineation of urban land. Instead, it appears that alternative combinations of the above-mentioned ancillary variables can better depict the spatial distribution of urban land, and thus make it possible to reduce the estimation error in transferring the urban population from source zones to target zones when running spatially-refined temporal areal interpolation.

Changing Urbania: Estimating Changes in Urban Land and Urban Population Using Refined Areal Interpolation Techniques

NASA Astrophysics Data System (ADS)

Zoraghein, H.; Leyk, S.; Balk, D.

2017-12-01

The analysis of changes in urban land and population is important because the majority of future population growth will take place in urban areas. The U.S. Census historically classifies urban land using population density and various land-use criteria. This study analyzes the reliability of census-defined urban lands for delineating the spatial distribution of urban population and estimating its changes over time. To overcome the problem of incompatible enumeration units between censuses, regular areal interpolation methods including Areal Weighting (AW) and Target Density Weighting (TDW), with and without spatial refinement, are implemented. The goal in this study is to estimate urban population in Massachusetts in 1990 and 2000 (source zones), within tract boundaries of the 2010 census (target zones), respectively, to create a consistent time series of comparable urban population estimates from 1990 to 2010. Spatial refinement is done using ancillary variables such as census-defined urban areas, the National Land Cover Database (NLCD) and the Global Human Settlement Layer (GHSL) as well as different combinations of them. The study results suggest that census-defined urban areas alone are not necessarily the most meaningful delineation of urban land. Instead it appears that alternative combinations of the above-mentioned ancillary variables can better depict the spatial distribution of urban land, and thus make it possible to reduce the estimation error in transferring the urban population from source zones to target zones when running spatially-refined temporal areal interpolation.

Multi-Compartment T2 Relaxometry Using a Spatially Constrained Multi-Gaussian Model

PubMed Central

Raj, Ashish; Pandya, Sneha; Shen, Xiaobo; LoCastro, Eve; Nguyen, Thanh D.; Gauthier, Susan A.

2014-01-01

The brain’s myelin content can be mapped by T2-relaxometry, which resolves multiple differentially relaxing T2 pools from multi-echo MRI. Unfortunately, the conventional fitting procedure is a hard and numerically ill-posed problem. Consequently, the T2 distributions and myelin maps become very sensitive to noise and are frequently difficult to interpret diagnostically. Although regularization can improve stability, it is generally not adequate, particularly at relatively low signal to noise ratio (SNR) of around 100–200. The purpose of this study was to obtain a fitting algorithm which is able to overcome these difficulties and generate usable myelin maps from noisy acquisitions in a realistic scan time. To this end, we restrict the T2 distribution to only 3 distinct resolvable tissue compartments, modeled as Gaussians: myelin water, intra/extra-cellular water and a slow relaxing cerebrospinal fluid compartment. We also impose spatial smoothness expectation that volume fractions and T2 relaxation times of tissue compartments change smoothly within coherent brain regions. The method greatly improves robustness to noise, reduces spatial variations, improves definition of white matter fibers, and enhances detection of demyelinating lesions. Due to efficient design, the additional spatial aspect does not cause an increase in processing time. The proposed method was applied to fast spiral acquisitions on which conventional fitting gives uninterpretable results. While these fast acquisitions suffer from noise and inhomogeneity artifacts, our preliminary results indicate the potential of spatially constrained 3-pool T2 relaxometry. PMID:24896833

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).

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

NASA Astrophysics Data System (ADS)

Erfanifard, Y.; Rezayan, F.

2014-10-01

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

Evaluating the spatial distribution of pollutants and associated maintenance requirements in an 11 year-old bioretention cell in urban Charlotte, NC.

PubMed

Johnson, Jeffrey P; Hunt, William F

2016-12-15

Bioretention cells (BRCs) are an increasingly popular Stormwater Control Measure used to mitigate the hydrologic and water quality impacts of urbanization. Previous BRC research has demonstrated a strong capacity for pollutant removal; however, long-term sequestration of pollutants within soil media can elevate concentrations to levels fostering environmental and human health risks. Soil media samples were collected from an 11 year-old BRC in Charlotte, NC, and analyzed for the accumulation and spatial distribution of zinc, copper, and phosphorus. Pollutant distribution varied significantly with respect to depth and ordinate distance from the BRC inlet. Zinc concentrations (0.9-228.6 mg kg -1 soil) exceeded environmental thresholds and phosphorus concentrations (5.1-173.3 mg kg -1 soil) increased from initial levels by a factor of seven; however, notable accumulation was restricted to the BRC forebay. Maximum zinc and copper concentrations in soil media did not exceed 1% of mandatory cleanup levels and with regular maintenance of the forebay, the effective life of BRC media should exceed the life of the developments they treat. Copyright © 2016 Elsevier Ltd. All rights reserved.

Spatial distribution of the daily precipitation concentration index in Southern Russia

NASA Astrophysics Data System (ADS)

Vyshkvarkova, Elena; Voskresenskaya, Elena; Martin-Vide, Javier

2018-05-01

The territory of Southern Russia presents a great diversity of climates and complex orography that lead to a very different precipitation distribution. Annual precipitation amounts differ between 222 mm in the coast of the Caspian Sea and > 2000 mm in the highest parts of the Caucasus Mountains. In order to investigate the statistical structure of daily precipitation across the study region the daily precipitation Concentration Index (CI) was used. In present paper, the CI was calculated for 42 meteorological stations during the 1970-2010 period. The analysis of precipitation concentration identified that the distribution of daily precipitation is more regular over the west, north and south regions compared to the east (the Caspian Sea coast and the Caspian Depression). The Crimean peninsula is characterized by low CI values in the north and high values in the eastern part.

On the regularized fermionic projector of the vacuum

NASA Astrophysics Data System (ADS)

Finster, Felix

2008-03-01

We construct families of fermionic projectors with spherically symmetric regularization, which satisfy the condition of a distributional MP-product. The method is to analyze regularization tails with a power law or logarithmic scaling in composite expressions in the fermionic projector. The resulting regularizations break the Lorentz symmetry and give rise to a multilayer structure of the fermionic projector near the light cone. Furthermore, we construct regularizations which go beyond the distributional MP-product in that they yield additional distributional contributions supported at the origin. The remaining freedom for the regularization parameters and the consequences for the normalization of the fermionic states are discussed.

Neural signature of the conscious processing of auditory regularities

PubMed Central

Bekinschtein, Tristan A.; Dehaene, Stanislas; Rohaut, Benjamin; Tadel, François; Cohen, Laurent; Naccache, Lionel

2009-01-01

Can conscious processing be inferred from neurophysiological measurements? Some models stipulate that the active maintenance of perceptual representations across time requires consciousness. Capitalizing on this assumption, we designed an auditory paradigm that evaluates cerebral responses to violations of temporal regularities that are either local in time or global across several seconds. Local violations led to an early response in auditory cortex, independent of attention or the presence of a concurrent visual task, whereas global violations led to a late and spatially distributed response that was only present when subjects were attentive and aware of the violations. We could detect the global effect in individual subjects using functional MRI and both scalp and intracerebral event-related potentials. Recordings from 8 noncommunicating patients with disorders of consciousness confirmed that only conscious individuals presented a global effect. Taken together these observations suggest that the presence of the global effect is a signature of conscious processing, although it can be absent in conscious subjects who are not aware of the global auditory regularities. This simple electrophysiological marker could thus serve as a useful clinical tool. PMID:19164526

Mapping populations at risk: improving spatial demographic data for infectious disease modeling and metric derivation

PubMed Central

2012-01-01

The use of Global Positioning Systems (GPS) and Geographical Information Systems (GIS) in disease surveys and reporting is becoming increasingly routine, enabling a better understanding of spatial epidemiology and the improvement of surveillance and control strategies. In turn, the greater availability of spatially referenced epidemiological data is driving the rapid expansion of disease mapping and spatial modeling methods, which are becoming increasingly detailed and sophisticated, with rigorous handling of uncertainties. This expansion has, however, not been matched by advancements in the development of spatial datasets of human population distribution that accompany disease maps or spatial models. Where risks are heterogeneous across population groups or space or dependent on transmission between individuals, spatial data on human population distributions and demographic structures are required to estimate infectious disease risks, burdens, and dynamics. The disease impact in terms of morbidity, mortality, and speed of spread varies substantially with demographic profiles, so that identifying the most exposed or affected populations becomes a key aspect of planning and targeting interventions. Subnational breakdowns of population counts by age and sex are routinely collected during national censuses and maintained in finer detail within microcensus data. Moreover, demographic and health surveys continue to collect representative and contemporary samples from clusters of communities in low-income countries where census data may be less detailed and not collected regularly. Together, these freely available datasets form a rich resource for quantifying and understanding the spatial variations in the sizes and distributions of those most at risk of disease in low income regions, yet at present, they remain unconnected data scattered across national statistical offices and websites. In this paper we discuss the deficiencies of existing spatial population datasets and their limitations on epidemiological analyses. We review sources of detailed, contemporary, freely available and relevant spatial demographic data focusing on low income regions where such data are often sparse and highlight the value of incorporating these through a set of examples of their application in disease studies. Moreover, the importance of acknowledging, measuring, and accounting for uncertainty in spatial demographic datasets is outlined. Finally, a strategy for building an open-access database of spatial demographic data that is tailored to epidemiological applications is put forward. PMID:22591595

Influence of chewing behaviour on memory and spatial learning in albino BALB/c mice.

PubMed

Aguirre Siancas, E E

2017-05-01

Since the relationship between chewing and cognitive functions has not been fully elucidated, this study aimed to determine the impact of chewing behaviour on spatial learning and memory in albino male BALB/c mice. Twenty mice aged 8 weeks were divided into 2 equal groups. The regular chewing group was fed with uncrushed grains (the same diet given to all 20 mice since they were weaned) and the limited chewing group was fed with crushed grains. At 16 weeks of age, the mice were evaluated over 5 days, including a 4-day acquisition phase prior to a probe test of spatial learning and memory in the Morris water maze on the fifth day. A comparison of the regular chewing group and the limited chewing group found no significant differences in either the acquisition phase or the probe test. However, there were significant differences in the acquisition phase for just the regular chewing group when comparing results from the first day to those from the other 3 days. The results suggest that regular chewing affects spatial learning and memory since mice in the regular chewing group decreased their times to find the hidden platform during the acquisition phase. Copyright © 2015 Sociedad Española de Neurología. Publicado por Elsevier España, S.L.U. All rights reserved.

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.

Matching the quasiparton distribution in a momentum subtraction scheme

NASA Astrophysics Data System (ADS)

Stewart, Iain W.; Zhao, Yong

2018-03-01

The quasiparton distribution is a spatial correlation of quarks or gluons along the z direction in a moving nucleon which enables direct lattice calculations of parton distribution functions. It can be defined with a nonperturbative renormalization in a regularization independent momentum subtraction scheme (RI/MOM), which can then be perturbatively related to the collinear parton distribution in the MS ¯ scheme. Here we carry out a direct matching from the RI/MOM scheme for the quasi-PDF to the MS ¯ PDF, determining the non-singlet quark matching coefficient at next-to-leading order in perturbation theory. We find that the RI/MOM matching coefficient is insensitive to the ultraviolet region of convolution integral, exhibits improved perturbative convergence when converting between the quasi-PDF and PDF, and is consistent with a quasi-PDF that vanishes in the unphysical region as the proton momentum Pz→∞ , unlike other schemes. This direct approach therefore has the potential to improve the accuracy for converting quasidistribution lattice calculations to collinear distributions.

Changes of the time-varying percentiles of daily extreme temperature in China

NASA Astrophysics Data System (ADS)

Li, Bin; Chen, Fang; Xu, Feng; Wang, Xinrui

2017-11-01

Identifying the air temperature frequency distributions and evaluating the trends in time-varying percentiles are very important for climate change studies. In order to get a better understanding of the recent temporal and spatial pattern of the temperature changes in China, we have calculated the trends in temporal-varying percentiles of the daily extreme air temperature firstly. Then we divide all the stations to get the spatial patterns for the percentile trends using the average linkage cluster analysis method. To make a comparison, the shifts of trends percentile frequency distribution from 1961-1985 to 1986-2010 are also examined. Important results in three aspects have been achieved: (1) In terms of the trends in temporal-varying percentiles of the daily extreme air temperature, the most intense warming for daily maximum air temperature (Tmax) was detected in the upper percentiles with a significant increasing tendency magnitude (>2.5 °C/50year), and the greatest warming for daily minimum air temperature (Tmin) occurred with very strong trends exceeding 4 °C/50year. (2) The relative coherent spatial patterns for the percentile trends were found, and stations for the whole country had been divided into three clusters. The three primary clusters were distributed regularly to some extent from north to south, indicating the possible large influence of the latitude. (3) The most significant shifts of trends percentile frequency distribution from 1961-1985 to 1986-2010 was found in Tmax. More than half part of the frequency distribution show negative trends less than -0.5 °C/50year in 1961-1985, while showing trends less than 2.5 °C/50year in 1986-2010.

W-phase estimation of first-order rupture distribution for megathrust earthquakes

NASA Astrophysics Data System (ADS)

Benavente, Roberto; Cummins, Phil; Dettmer, Jan

2014-05-01

Estimating the rupture pattern for large earthquakes during the first hour after the origin time can be crucial for rapid impact assessment and tsunami warning. However, the estimation of coseismic slip distribution models generally involves complex methodologies that are difficult to implement rapidly. Further, while model parameter uncertainty can be crucial for meaningful estimation, they are often ignored. In this work we develop a finite fault inversion for megathrust earthquakes which rapidly generates good first order estimates and uncertainties of spatial slip distributions. The algorithm uses W-phase waveforms and a linear automated regularization approach to invert for rupture models of some recent megathrust earthquakes. The W phase is a long period (100-1000 s) wave which arrives together with the P wave. Because it is fast, has small amplitude and a long-period character, the W phase is regularly used to estimate point source moment tensors by the NEIC and PTWC, among others, within an hour of earthquake occurrence. We use W-phase waveforms processed in a manner similar to that used for such point-source solutions. The inversion makes use of 3 component W-phase records retrieved from the Global Seismic Network. The inverse problem is formulated by a multiple time window method, resulting in a linear over-parametrized problem. The over-parametrization is addressed by Tikhonov regularization and regularization parameters are chosen according to the discrepancy principle by grid search. Noise on the data is addressed by estimating the data covariance matrix from data residuals. The matrix is obtained by starting with an a priori covariance matrix and then iteratively updating the matrix based on the residual errors of consecutive inversions. Then, a covariance matrix for the parameters is computed using a Bayesian approach. The application of this approach to recent megathrust earthquakes produces models which capture the most significant features of their slip distributions. Also, reliable solutions are generally obtained with data in a 30-minute window following the origin time, suggesting that a real-time system could obtain solutions in less than one hour following the origin time.

DETECTION OF SMALL-SCALE GRANULAR STRUCTURES IN THE QUIET SUN WITH THE NEW SOLAR TELESCOPE

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

Abramenko, V. I.; Yurchyshyn, V. B.; Goode, P. R.

2012-09-10

Results of a statistical analysis of solar granulation are presented. A data set of 36 images of a quiet-Sun area on the solar disk center was used. The data were obtained with the 1.6 m clear aperture New Solar Telescope at Big Bear Solar Observatory and with a broadband filter centered at the TiO (705.7 nm) spectral line. The very high spatial resolution of the data (diffraction limit of 77 km and pixel scale of 0.''0375) augmented by the very high image contrast (15.5% {+-} 0.6%) allowed us to detect for the first time a distinct subpopulation of mini-granular structures.more » These structures are dominant on spatial scales below 600 km. Their size is distributed as a power law with an index of -1.8 (which is close to the Kolmogorov's -5/3 law) and no predominant scale. The regular granules display a Gaussian (normal) size distribution with a mean diameter of 1050 km. Mini-granular structures contribute significantly to the total granular area. They are predominantly confined to the wide dark lanes between regular granules and often form chains and clusters, but different from magnetic bright points. A multi-fractality test reveals that the structures smaller than 600 km represent a multi-fractal, whereas on larger scales the granulation pattern shows no multi-fractality and can be considered as a Gaussian random field. The origin, properties, and role of the population of mini-granular structures in the solar magnetoconvection are yet to be explored.« less

Spatial Aspects of Multi-Sensor Data Fusion: Aerosol Optical Thickness

NASA Technical Reports Server (NTRS)

Leptoukh, Gregory; Zubko, V.; Gopalan, A.

2007-01-01

The Goddard Earth Sciences Data and Information Services Center (GES DISC) investigated the applicability and limitations of combining multi-sensor data through data fusion, to increase the usefulness of the multitude of NASA remote sensing data sets, and as part of a larger effort to integrate this capability in the GES-DISC Interactive Online Visualization and Analysis Infrastructure (Giovanni). This initial study focused on merging daily mean Aerosol Optical Thickness (AOT), as measured by the Moderate Resolution Imaging Spectroradiometer (MODIS) onboard the Terra and Aqua satellites, to increase spatial coverage and produce complete fields to facilitate comparison with models and station data. The fusion algorithm used the maximum likelihood technique to merge the pixel values where available. The algorithm was applied to two regional AOT subsets (with mostly regular and irregular gaps, respectively) and a set of AOT fields that differed only in the size and location of artificially created gaps. The Cumulative Semivariogram (CSV) was found to be sensitive to the spatial distribution of gap areas and, thus, useful for assessing the sensitivity of the fused data to spatial gaps.

Enhanced spatial resolution in fluorescence molecular tomography using restarted L1-regularized nonlinear conjugate gradient algorithm.

PubMed

Shi, Junwei; Liu, Fei; Zhang, Guanglei; Luo, Jianwen; Bai, Jing

2014-04-01

Owing to the high degree of scattering of light through tissues, the ill-posedness of fluorescence molecular tomography (FMT) inverse problem causes relatively low spatial resolution in the reconstruction results. Unlike L2 regularization, L1 regularization can preserve the details and reduce the noise effectively. Reconstruction is obtained through a restarted L1 regularization-based nonlinear conjugate gradient (re-L1-NCG) algorithm, which has been proven to be able to increase the computational speed with low memory consumption. The algorithm consists of inner and outer iterations. In the inner iteration, L1-NCG is used to obtain the L1-regularized results. In the outer iteration, the restarted strategy is used to increase the convergence speed of L1-NCG. To demonstrate the performance of re-L1-NCG in terms of spatial resolution, simulation and physical phantom studies with fluorescent targets located with different edge-to-edge distances were carried out. The reconstruction results show that the re-L1-NCG algorithm has the ability to resolve targets with an edge-to-edge distance of 0.1 cm at a depth of 1.5 cm, which is a significant improvement for FMT.

Hydrologic controls on aperiodic spatial organization of the ridge-slough patterned landscape

NASA Astrophysics Data System (ADS)

Casey, Stephen T.; Cohen, Matthew J.; Acharya, Subodh; Kaplan, David A.; Jawitz, James W.

2016-11-01

A century of hydrologic modification has altered the physical and biological drivers of landscape processes in the Everglades (Florida, USA). Restoring the ridge-slough patterned landscape, a dominant feature of the historical system, is a priority but requires an understanding of pattern genesis and degradation mechanisms. Physical experiments to evaluate alternative pattern formation mechanisms are limited by the long timescales of peat accumulation and loss, necessitating model-based comparisons, where support for a particular mechanism is based on model replication of extant patterning and trajectories of degradation. However, multiple mechanisms yield a central feature of ridge-slough patterning (patch elongation in the direction of historical flow), limiting the utility of that characteristic for discriminating among alternatives. Using data from vegetation maps, we investigated the statistical features of ridge-slough spatial patterning (ridge density, patch perimeter, elongation, patch size distributions, and spatial periodicity) to establish more rigorous criteria for evaluating model performance and to inform controls on pattern variation across the contemporary system. Mean water depth explained significant variation in ridge density, total perimeter, and length : width ratios, illustrating an important pattern response to existing hydrologic gradients. Two independent analyses (2-D periodograms and patch size distributions) provide strong evidence against regular patterning, with the landscape exhibiting neither a characteristic wavelength nor a characteristic patch size, both of which are expected under conditions that produce regular patterns. Rather, landscape properties suggest robust scale-free patterning, indicating genesis from the coupled effects of local facilitation and a global negative feedback operating uniformly at the landscape scale. Critically, this challenges widespread invocation of scale-dependent negative feedbacks for explaining ridge-slough pattern origins. These results help discern among genesis mechanisms and provide an improved statistical description of the landscape that can be used to compare among model outputs, as well as to assess the success of future restoration projects.

Comparing two remote video survey methods for spatial predictions of the distribution and environmental niche suitability of demersal fishes.

PubMed

Galaiduk, Ronen; Radford, Ben T; Wilson, Shaun K; Harvey, Euan S

2017-12-15

Information on habitat associations from survey data, combined with spatial modelling, allow the development of more refined species distribution modelling which may identify areas of high conservation/fisheries value and consequentially improve conservation efforts. Generalised additive models were used to model the probability of occurrence of six focal species after surveys that utilised two remote underwater video sampling methods (i.e. baited and towed video). Models developed for the towed video method had consistently better predictive performance for all but one study species although only three models had a good to fair fit, and the rest were poor fits, highlighting the challenges associated with modelling habitat associations of marine species in highly homogenous, low relief environments. Models based on baited video dataset regularly included large-scale measures of structural complexity, suggesting fish attraction to a single focus point by bait. Conversely, models based on the towed video data often incorporated small-scale measures of habitat complexity and were more likely to reflect true species-habitat relationships. The cost associated with use of the towed video systems for surveying low-relief seascapes was also relatively low providing additional support for considering this method for marine spatial ecological modelling.

Network hydraulics inclusion in water quality event detection using multiple sensor stations data.

PubMed

Oliker, Nurit; Ostfeld, Avi

2015-09-01

Event detection is one of the current most challenging topics in water distribution systems analysis: how regular on-line hydraulic (e.g., pressure, flow) and water quality (e.g., pH, residual chlorine, turbidity) measurements at different network locations can be efficiently utilized to detect water quality contamination events. This study describes an integrated event detection model which combines multiple sensor stations data with network hydraulics. To date event detection modelling is likely limited to single sensor station location and dataset. Single sensor station models are detached from network hydraulics insights and as a result might be significantly exposed to false positive alarms. This work is aimed at decreasing this limitation through integrating local and spatial hydraulic data understanding into an event detection model. The spatial analysis complements the local event detection effort through discovering events with lower signatures by exploring the sensors mutual hydraulic influences. The unique contribution of this study is in incorporating hydraulic simulation information into the overall event detection process of spatially distributed sensors. The methodology is demonstrated on two example applications using base runs and sensitivity analyses. Results show a clear advantage of the suggested model over single-sensor event detection schemes. Copyright © 2015 Elsevier Ltd. All rights reserved.

Linking species abundance distributions in numerical abundance and biomass through simple assumptions about community structure.

PubMed

Henderson, Peter A; Magurran, Anne E

2010-05-22

Species abundance distributions (SADs) are widely used as a tool for summarizing ecological communities but may have different shapes, depending on the currency used to measure species importance. We develop a simple plotting method that links SADs in the alternative currencies of numerical abundance and biomass and is underpinned by testable predictions about how organisms occupy physical space. When log numerical abundance is plotted against log biomass, the species lie within an approximately triangular region. Simple energetic and sampling constraints explain the triangular form. The dispersion of species within this triangle is the key to understanding why SADs of numerical abundance and biomass can differ. Given regular or random species dispersion, we can predict the shape of the SAD for both currencies under a variety of sampling regimes. We argue that this dispersion pattern will lie between regular and random for the following reasons. First, regular dispersion patterns will result if communities are comprised groups of organisms that use different components of the physical space (e.g. open water, the sea bed surface or rock crevices in a marine fish assemblage), and if the abundance of species in each of these spatial guilds is linked to the way individuals of varying size use the habitat. Second, temporal variation in abundance and sampling error will tend to randomize this regular pattern. Data from two intensively studied marine ecosystems offer empirical support for these predictions. Our approach also has application in environmental monitoring and the recognition of anthropogenic disturbance, which may change the shape of the triangular region by, for example, the loss of large body size top predators that occur at low abundance.

Linking species abundance distributions in numerical abundance and biomass through simple assumptions about community structure

PubMed Central

Henderson, Peter A.; Magurran, Anne E.

2010-01-01

Species abundance distributions (SADs) are widely used as a tool for summarizing ecological communities but may have different shapes, depending on the currency used to measure species importance. We develop a simple plotting method that links SADs in the alternative currencies of numerical abundance and biomass and is underpinned by testable predictions about how organisms occupy physical space. When log numerical abundance is plotted against log biomass, the species lie within an approximately triangular region. Simple energetic and sampling constraints explain the triangular form. The dispersion of species within this triangle is the key to understanding why SADs of numerical abundance and biomass can differ. Given regular or random species dispersion, we can predict the shape of the SAD for both currencies under a variety of sampling regimes. We argue that this dispersion pattern will lie between regular and random for the following reasons. First, regular dispersion patterns will result if communities are comprised groups of organisms that use different components of the physical space (e.g. open water, the sea bed surface or rock crevices in a marine fish assemblage), and if the abundance of species in each of these spatial guilds is linked to the way individuals of varying size use the habitat. Second, temporal variation in abundance and sampling error will tend to randomize this regular pattern. Data from two intensively studied marine ecosystems offer empirical support for these predictions. Our approach also has application in environmental monitoring and the recognition of anthropogenic disturbance, which may change the shape of the triangular region by, for example, the loss of large body size top predators that occur at low abundance. PMID:20071388

Arbitrary numbers counter fair decisions: trails of markedness in card distribution.

PubMed

Schroeder, Philipp A; Pfister, Roland

2015-01-01

Converging evidence from controlled experiments suggests that the mere processing of a number and its attributes such as value or parity might affect free choice decisions between different actions. For example the spatial numerical associations of response codes (SNARC) effect indicates the magnitude of a digit to be associated with a spatial representation and might therefore affect spatial response choices (i.e., decisions between a "left" and a "right" option). At the same time, other (linguistic) features of a number such as parity are embedded into space and might likewise prime left or right responses through feature words [odd or even, respectively; markedness association of response codes (MARC) effect]. In this experiment we aimed at documenting such influences in a natural setting. We therefore assessed number-space and parity-space association effects by exposing participants to a fair distribution task in a card playing scenario. Participants drew cards, read out loud their number values, and announced their response choice, i.e., dealing it to a left vs. right player, indicated by Playmobil characters. Not only did participants prefer to deal more cards to the right player, the card's digits also affected response choices and led to a slightly but systematically unfair distribution, supported by a regular SNARC effect and counteracted by a reversed MARC effect. The experiment demonstrates the impact of SNARC- and MARC-like biases in free choice behavior through verbal and visual numerical information processing even in a setting with high external validity.

Spatial Distribution, Sources Apportionment and Health Risk of Metals in Topsoil in Beijing, China.

PubMed

Sun, Chunyuan; Zhao, Wenji; Zhang, Qianzhong; Yu, Xue; Zheng, Xiaoxia; Zhao, Jiayin; Lv, Ming

2016-07-20

In order to acquire the pollution feature and regularities of distribution of metals in the topsoil within the sixth ring road in Beijing, a total of 46 soil samples were collected, and the concentrations of twelve elements (Nickel, Ni, Lithium, Li, Vanadium, V, Cobalt, Co, Barium, Ba, Strontium, Sr, Chrome, Cr, Molybdenum, Mo, Copper, Cu, Cadmium, Cd, Zinc, Zn, Lead, Pb) were analyzed. Geostatistics and multivariate statistics were conducted to identify spatial distribution characteristics and sources. In addition, the health risk of the analyzed heavy metals to humans (adult) was evaluated by an U.S. Environmental Protection Agency health risk assessment model. The results indicate that these metals have notable variation in spatial scale. The concentration of Cr was high in the west and low in the east, while that of Mo was high in the north and low in the south. High concentrations of Cu, Cd, Zn, and Pb were found in the central part of the city. The average enrichment degree of Cd is 5.94, reaching the standard of significant enrichment. The accumulation of Cr, Mo, Cu, Cd, Zn, and Pb is influenced by anthropogenic activity, including vehicle exhaustion, coal burning, and industrial processes. Health risk assessment shows that both non-carcinogenic and carcinogenic risks of selected heavy metals are within the safety standard and the rank of the carcinogenic risk of the four heavy metals is Cr > Co > Ni > Cd.

Spatial Distribution, Sources Apportionment and Health Risk of Metals in Topsoil in Beijing, China

PubMed Central

Sun, Chunyuan; Zhao, Wenji; Zhang, Qianzhong; Yu, Xue; Zheng, Xiaoxia; Zhao, Jiayin; Lv, Ming

2016-01-01

In order to acquire the pollution feature and regularities of distribution of metals in the topsoil within the sixth ring road in Beijing, a total of 46 soil samples were collected, and the concentrations of twelve elements (Nickel, Ni, Lithium, Li, Vanadium, V, Cobalt, Co, Barium, Ba, Strontium, Sr, Chrome, Cr, Molybdenum, Mo, Copper, Cu, Cadmium, Cd, Zinc, Zn, Lead, Pb) were analyzed. Geostatistics and multivariate statistics were conducted to identify spatial distribution characteristics and sources. In addition, the health risk of the analyzed heavy metals to humans (adult) was evaluated by an U.S. Environmental Protection Agency health risk assessment model. The results indicate that these metals have notable variation in spatial scale. The concentration of Cr was high in the west and low in the east, while that of Mo was high in the north and low in the south. High concentrations of Cu, Cd, Zn, and Pb were found in the central part of the city. The average enrichment degree of Cd is 5.94, reaching the standard of significant enrichment. The accumulation of Cr, Mo, Cu, Cd, Zn, and Pb is influenced by anthropogenic activity, including vehicle exhaustion, coal burning, and industrial processes. Health risk assessment shows that both non-carcinogenic and carcinogenic risks of selected heavy metals are within the safety standard and the rank of the carcinogenic risk of the four heavy metals is Cr > Co > Ni > Cd. PMID:27447657

Visually Guided Avoidance in the Chameleon (Chamaeleo chameleon): Response Patterns and Lateralization

PubMed Central

Lustig, Avichai; Ketter-Katz, Hadas; Katzir, Gadi

2012-01-01

The common chameleon, Chamaeleo chameleon, is an arboreal lizard with highly independent, large-amplitude eye movements. In response to a moving threat, a chameleon on a perch responds with distinct avoidance movements that are expressed in its continuous positioning on the side of the perch distal to the threat. We analyzed body-exposure patterns during threat avoidance for evidence of lateralization, that is, asymmetry at the functional/behavioral levels. Chameleons were exposed to a threat approaching horizontally from the left or right, as they held onto a vertical pole that was either wider or narrower than the width of their head, providing, respectively, monocular or binocular viewing of the threat. We found two equal-sized sub-groups, each displaying lateralization of motor responses to a given direction of stimulus approach. Such an anti-symmetrical distribution of lateralization in a population may be indicative of situations in which organisms are regularly exposed to crucial stimuli from all spatial directions. This is because a bimodal distribution of responses to threat in a natural population will reduce the spatial advantage of predators. PMID:22685546

Visually guided avoidance in the chameleon (Chamaeleo chameleon): response patterns and lateralization.

PubMed

Lustig, Avichai; Ketter-Katz, Hadas; Katzir, Gadi

2012-01-01

The common chameleon, Chamaeleo chameleon, is an arboreal lizard with highly independent, large-amplitude eye movements. In response to a moving threat, a chameleon on a perch responds with distinct avoidance movements that are expressed in its continuous positioning on the side of the perch distal to the threat. We analyzed body-exposure patterns during threat avoidance for evidence of lateralization, that is, asymmetry at the functional/behavioral levels. Chameleons were exposed to a threat approaching horizontally from the left or right, as they held onto a vertical pole that was either wider or narrower than the width of their head, providing, respectively, monocular or binocular viewing of the threat. We found two equal-sized sub-groups, each displaying lateralization of motor responses to a given direction of stimulus approach. Such an anti-symmetrical distribution of lateralization in a population may be indicative of situations in which organisms are regularly exposed to crucial stimuli from all spatial directions. This is because a bimodal distribution of responses to threat in a natural population will reduce the spatial advantage of predators.

Pattern classification of fMRI data: applications for analysis of spatially distributed cortical networks.

PubMed

Yourganov, Grigori; Schmah, Tanya; Churchill, Nathan W; Berman, Marc G; Grady, Cheryl L; Strother, Stephen C

2014-08-01

The field of fMRI data analysis is rapidly growing in sophistication, particularly in the domain of multivariate pattern classification. However, the interaction between the properties of the analytical model and the parameters of the BOLD signal (e.g. signal magnitude, temporal variance and functional connectivity) is still an open problem. We addressed this problem by evaluating a set of pattern classification algorithms on simulated and experimental block-design fMRI data. The set of classifiers consisted of linear and quadratic discriminants, linear support vector machine, and linear and nonlinear Gaussian naive Bayes classifiers. For linear discriminant, we used two methods of regularization: principal component analysis, and ridge regularization. The classifiers were used (1) to classify the volumes according to the behavioral task that was performed by the subject, and (2) to construct spatial maps that indicated the relative contribution of each voxel to classification. Our evaluation metrics were: (1) accuracy of out-of-sample classification and (2) reproducibility of spatial maps. In simulated data sets, we performed an additional evaluation of spatial maps with ROC analysis. We varied the magnitude, temporal variance and connectivity of simulated fMRI signal and identified the optimal classifier for each simulated environment. Overall, the best performers were linear and quadratic discriminants (operating on principal components of the data matrix) and, in some rare situations, a nonlinear Gaussian naïve Bayes classifier. The results from the simulated data were supported by within-subject analysis of experimental fMRI data, collected in a study of aging. This is the first study that systematically characterizes interactions between analysis model and signal parameters (such as magnitude, variance and correlation) on the performance of pattern classifiers for fMRI. Copyright © 2014 Elsevier Inc. All rights reserved.

Joint reconstruction of dynamic PET activity and kinetic parametric images using total variation constrained dictionary sparse coding

NASA Astrophysics Data System (ADS)

Yu, Haiqing; Chen, Shuhang; Chen, Yunmei; Liu, Huafeng

2017-05-01

Dynamic positron emission tomography (PET) is capable of providing both spatial and temporal information of radio tracers in vivo. In this paper, we present a novel joint estimation framework to reconstruct temporal sequences of dynamic PET images and the coefficients characterizing the system impulse response function, from which the associated parametric images of the system macro parameters for tracer kinetics can be estimated. The proposed algorithm, which combines statistical data measurement and tracer kinetic models, integrates a dictionary sparse coding (DSC) into a total variational minimization based algorithm for simultaneous reconstruction of the activity distribution and parametric map from measured emission sinograms. DSC, based on the compartmental theory, provides biologically meaningful regularization, and total variation regularization is incorporated to provide edge-preserving guidance. We rely on techniques from minimization algorithms (the alternating direction method of multipliers) to first generate the estimated activity distributions with sub-optimal kinetic parameter estimates, and then recover the parametric maps given these activity estimates. These coupled iterative steps are repeated as necessary until convergence. Experiments with synthetic, Monte Carlo generated data, and real patient data have been conducted, and the results are very promising.

Extreme fluctuations in stochastic network coordination with time delays

NASA Astrophysics Data System (ADS)

Hunt, D.; Molnár, F.; Szymanski, B. K.; Korniss, G.

2015-12-01

We study the effects of uniform time delays on the extreme fluctuations in stochastic synchronization and coordination problems with linear couplings in complex networks. We obtain the average size of the fluctuations at the nodes from the behavior of the underlying modes of the network. We then obtain the scaling behavior of the extreme fluctuations with system size, as well as the distribution of the extremes on complex networks, and compare them to those on regular one-dimensional lattices. For large complex networks, when the delay is not too close to the critical one, fluctuations at the nodes effectively decouple, and the limit distributions converge to the Fisher-Tippett-Gumbel density. In contrast, fluctuations in low-dimensional spatial graphs are strongly correlated, and the limit distribution of the extremes is the Airy density. Finally, we also explore the effects of nonlinear couplings on the stability and on the extremes of the synchronization landscapes.

Visualization of drug distribution of topical minocycline in human facial skin with fluorescence microscopy (Conference Presentation)

NASA Astrophysics Data System (ADS)

Hermsmeier, Maiko; Sawant, Tanvee; Lac, Diana; Yamamoto, Akira; Chen, Xin; Nagavarapu, Usha; Evans, Conor L.; Chan, Kin Foong

2017-02-01

Minocycline is an antibiotic regularly prescribed to treat acne vulgaris. The only commercially available minocycline comes in an oral dosage form, which often results in systemic adverse effects. A topical minocycline composition (BPX-01) was developed to provide localized and targeted delivery to the epidermis and pilosebaceous unit where acne-related bacteria, Propionibacterium acnes (P. acnes), reside. As minocycline is a known fluorophore, fluorescence microscopy was performed to investigate its potential use in visualizing minocycline distribution within tissues. BPX-01 with various concentrations of minocycline, was applied topically to freshly excised human facial skin specimens. Spatial distribution of minocycline and its fluorescence intensity within the stratum corneum, epidermis, dermis, and pilosebaceous unit were assessed. The resulting fluorescence intensity data as a function of minocycline concentration may indicate clinically relevant therapeutic doses of topical BPX-01 needed to kill P. acnes and reduce inflammation for successful clinical outcomes.

Combining kernel matrix optimization and regularization to improve particle size distribution retrieval

NASA Astrophysics Data System (ADS)

Ma, Qian; Xia, Houping; Xu, Qiang; Zhao, Lei

2018-05-01

A new method combining Tikhonov regularization and kernel matrix optimization by multi-wavelength incidence is proposed for retrieving particle size distribution (PSD) in an independent model with improved accuracy and stability. In comparison to individual regularization or multi-wavelength least squares, the proposed method exhibited better anti-noise capability, higher accuracy and stability. While standard regularization typically makes use of the unit matrix, it is not universal for different PSDs, particularly for Junge distributions. Thus, a suitable regularization matrix was chosen by numerical simulation, with the second-order differential matrix found to be appropriate for most PSD types.

Geostatistical conditional simulation for the assessment of contaminated land by abandoned heavy metal mining.

PubMed

Ersoy, Adem; Yunsel, Tayfun Yusuf; Atici, Umit

2008-02-01

Abandoned mine workings can undoubtedly cause varying degrees of contamination of soil with heavy metals such as lead and zinc has occurred on a global scale. Exposure to these elements may cause to harm human health and environment. In the study, a total of 269 soil samples were collected at 1, 5, and 10 m regular grid intervals of 100 x 100 m area of Carsington Pasture in the UK. Cell declustering technique was applied to the data set due to no statistical representativity. Directional experimental semivariograms of the elements for the transformed data showed that both geometric and zonal anisotropy exists in the data. The most evident spatial dependence structure of the continuity for the directional experimental semivariogram, characterized by spherical and exponential models of Pb and Zn were obtained. This study reports the spatial distribution and uncertainty of Pb and Zn concentrations in soil at the study site using a probabilistic approach. The approach was based on geostatistical sequential Gaussian simulation (SGS), which is used to yield a series of conditional images characterized by equally probable spatial distributions of the heavy elements concentrations across the area. Postprocessing of many simulations allowed the mapping of contaminated and uncontaminated areas, and provided a model for the uncertainty in the spatial distribution of element concentrations. Maps of the simulated Pb and Zn concentrations revealed the extent and severity of contamination. SGS was validated by statistics, histogram, variogram reproduction, and simulation errors. The maps of the elements might be used in the remediation studies, help decision-makers and others involved in the abandoned heavy metal mining site in the world.

Computer Game Play as an Imaginary Stage for Reading: Implicit Spatial Effects of Computer Games Embedded in Hard Copy Books

ERIC Educational Resources Information Center

Smith, Glenn Gordon

2012-01-01

This study compared books with embedded computer games (via pentop computers with microdot paper and audio feedback) with regular books with maps, in terms of fifth graders' comprehension and retention of spatial details from stories. One group read a story in hard copy with embedded computer games, the other group read it in regular book format…

Understanding taxi travel patterns

NASA Astrophysics Data System (ADS)

Cai, Hua; Zhan, Xiaowei; Zhu, Ji; Jia, Xiaoping; Chiu, Anthony S. F.; Xu, Ming

2016-09-01

Taxis play important roles in modern urban transportation systems, especially in mega cities. While providing necessary amenities, taxis also significantly contribute to traffic congestion, urban energy consumption, and air pollution. Understanding the travel patterns of taxis is thus important for addressing many urban sustainability challenges. Previous research has primarily focused on examining the statistical properties of passenger trips, which include only taxi trips occupied with passengers. However, unoccupied trips are also important for urban sustainability issues because they represent potential opportunities to improve the efficiency of the transportation system. Therefore, we need to understand the travel patterns of taxis as an integrated system, instead of focusing only on the occupied trips. In this study we examine GPS trajectory data of 11,880 taxis in Beijing, China for a period of three weeks. Our results show that taxi travel patterns share similar traits with travel patterns of individuals but also exhibit differences. Trip displacement distribution of taxi travels is statistically greater than the exponential distribution and smaller than the truncated power-law distribution. The distribution of short trips (less than 30 miles) can be best fitted with power-law while long trips follow exponential decay. We use radius of gyration to characterize individual taxi's travel distance and find that it does not follow a truncated power-law as observed in previous studies. Spatial and temporal regularities exist in taxi travels. However, with increasing spatial coverage, taxi trips can exhibit dual high probability density centers.

Excitation of high density surface plasmon polariton vortex array

NASA Astrophysics Data System (ADS)

Kuo, Chun-Fu; Chu, Shu-Chun

2018-06-01

This study proposes a method to excite surface plasmon polariton (SPP) vortex array of high spatial density on metal/air interface. A doughnut vector beam was incident at four rectangularly arranged slits to excite SPP vortex array. The doughnut vector beam used in this study has the same field intensity distribution as the regular doughnut laser mode, TEM01* mode, but a different polarization distribution. The SPP vortex array is achieved through the matching of both polarization state and phase state of the incident doughnut vector beam with the four slits. The SPP field distribution excited in this study contains stable array-distributed time-varying optical vortices. Theoretical derivation, analytical calculation and numerical simulation were used to discuss the characteristics of the induced SPP vortex array. The period of the SPP vortex array induced by the proposed method had only half SPPs wavelength. In addition, the vortex number in an excited SPP vortex array can be increased by enlarging the structure.

Passive acoustic measurement of bedload grain size distribution using self-generated noise

NASA Astrophysics Data System (ADS)

Petrut, Teodor; Geay, Thomas; Gervaise, Cédric; Belleudy, Philippe; Zanker, Sebastien

2018-01-01

Monitoring sediment transport processes in rivers is of particular interest to engineers and scientists to assess the stability of rivers and hydraulic structures. Various methods for sediment transport process description were proposed using conventional or surrogate measurement techniques. This paper addresses the topic of the passive acoustic monitoring of bedload transport in rivers and especially the estimation of the bedload grain size distribution from self-generated noise. It discusses the feasibility of linking the acoustic signal spectrum shape to bedload grain sizes involved in elastic impacts with the river bed treated as a massive slab. Bedload grain size distribution is estimated by a regularized algebraic inversion scheme fed with the power spectrum density of river noise estimated from one hydrophone. The inversion methodology relies upon a physical model that predicts the acoustic field generated by the collision between rigid bodies. Here we proposed an analytic model of the acoustic energy spectrum generated by the impacts between a sphere and a slab. The proposed model computes the power spectral density of bedload noise using a linear system of analytic energy spectra weighted by the grain size distribution. The algebraic system of equations is then solved by least square optimization and solution regularization methods. The result of inversion leads directly to the estimation of the bedload grain size distribution. The inversion method was applied to real acoustic data from passive acoustics experiments realized on the Isère River, in France. The inversion of in situ measured spectra reveals good estimations of grain size distribution, fairly close to what was estimated by physical sampling instruments. These results illustrate the potential of the hydrophone technique to be used as a standalone method that could ensure high spatial and temporal resolution measurements for sediment transport in rivers.

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.

Regularities of Spatial and Temporal Distribution in Earthquakes in the Eastern Pacific Tectonic Belt

NASA Astrophysics Data System (ADS)

Maslov, L. A.; Choi, D. R.

2014-12-01

Earthquake epicenters in the Eastern Pacific Tectonic Belt (Pacific - North and South American continents tectonic margin) are distributed symmetrically about latitude with the following three minima: around the equator, at 35o N latitude, and at 35o S latitude, Figure 1a. In analysing the data, we looked at two characteristics - occurance dates, and epicenter latitudes. We calculated the power spectrum Sd(f) for occurance dates, and found that this spectrum can be approximated by the function Cfα, where α<0, Figure 1b. To interpret the data, we have also shown a graph of Ln(fα), Figure 1c. This graph shows that the exponent α is not a constant, but varies with the frequency. In addition, we calculated the power spectrum for epicenter latitudes Sl(f), Figure 1d, and found that this spectrum can be similarly approximated by the function Cfβ, where β<0. As with the occurance dates, we show a graph of Ln(fβ), Figure 1e, which indicates that β also varies with the frequency. This result is quite different from the well-known Gutenberg-Richter "frequency-magnitude" relation represented in bilogatithmic coordinates by a straight line. Coefficients α and β vary approximately from -2.5 to -1.5, depending on the "length" of the calculated spectrum subset used to plot the trend line. Based on the fact that the power spectrum has the form Cfα, -2.5<α<-1.5, we conclude that a long-time and long-distance correlation exists between earthquakes in the Eastern Pacific Tectonic Belt. In this work, we present an interpretation of the regularities in the spatial and temporal distribution of earthquakes in the Eastern Pacific Tectonic Belt. Earthquake data were taken from http://www.iris.edu/ieb/index.html.

Observations of IO hot-spots at coastal sites with the combination of a mobile CE- and LP- DOAS

NASA Astrophysics Data System (ADS)

Pöhler, D.; Horbanski, M.; Schmitt, S.; Anthofer, M.; Tschritter, J.; Platt, U.

2012-04-01

Reactive iodine species are emitted by seaweed in the intertidal zone of coastal sites during low tide. Beside their oxidation to iodine oxide (IO) and reduction of ozone, they act as precursors for particle formation and therefore have a potential impact on climate. A correlation between iodine oxide and particle formation could be observed in several field studies. However, modelling studies suggest that the so far observed mixing ratios of iodine oxide are too low to explain the observed particle formation. This may be caused by the so far applied measurement techniques which either average over a long measurement path of several km (LP-DOAS) or by immobile in-situ techniques (LIF or BB-CEAS) located typically few 10-100m of the intertidal area. Thus both techniques could not observe local "hot-spots", locations with locally elevated IO levels above the background with small spatial extend (e.g. above a source). We present a new developed Cavity Enhanced Differential Optical Absorption Spectroscopy (CE- DOAS) instrument for the direct identification of IO down to 1ppt. This technique gives the possibility to achieve long absorption light paths in a compact setup (<2.0m) and thus apply the DOAS principle to in-situ measurements. The resonator of the cavity is formed by two high reflective mirrors in the spectral window from 430-460nm. To avoid any interference of reactive iodine compounds with tubes, walls or filters, the resonator is open similar to a LP-DOAS setup. A blue LED is used as light source. The total instrument setup is relatively light (25kg) and can easily be located at different locations. Hence it is possible to setup this instrument directly over the macro algae in the intertidal area during low tide to investigate the IO spatial distribution and "hot-spots". As IO concentrations vary strongly due to different meteorological parameters, the CE-DOAS measurements are combined with LP-DOAS in the same area. Thus the combination allows deriving a spatial variability. The results from the first application during the HaloCave2010 campaign on Cape Verde will be presented. Opposite to former measurements both instruments could not observe IO at any coastal site close to the CVAO station. Recently measurements were performed along the Irish west coast (partly at the research station Mace Head during MaCloud field campaign) to investigate the IO levels emitted by macro algae. During low tide the CE-DOAS instrument was regularly set-up directly in the intertidal area above the macro algae. Results of different coastal sites will be presented in detail. Elevated IO concentrations up to several 10ppt could be observed with the CE-DOAS instrument regularly, but LP-DOAS concentrations are typically more than an order of magnitude lower. The data will be discussed according to the IO "hot-spot" theory. Even at unfavorable meteorological conditions (clouds, strong wind) the CE-DOAS instrument could regularly observe enhanced IO levels. Different coastal sites show different IO emission strength and spatial distribution. The spatial distribution of IO at different coastal sites and its impact on atmospheric chemistry will be discussed.

Accretion onto some well-known regular black holes

NASA Astrophysics Data System (ADS)

Jawad, Abdul; Shahzad, M. Umair

2016-03-01

In this work, we discuss the accretion onto static spherically symmetric regular black holes for specific choices of the equation of state parameter. The underlying regular black holes are charged regular black holes using the Fermi-Dirac distribution, logistic distribution, nonlinear electrodynamics, respectively, and Kehagias-Sftesos asymptotically flat regular black holes. We obtain the critical radius, critical speed, and squared sound speed during the accretion process near the regular black holes. We also study the behavior of radial velocity, energy density, and the rate of change of the mass for each of the regular black holes.

Altering spatial priority maps via statistical learning of target selection and distractor filtering.

PubMed

Ferrante, Oscar; Patacca, Alessia; Di Caro, Valeria; Della Libera, Chiara; Santandrea, Elisa; Chelazzi, Leonardo

2018-05-01

The cognitive system has the capacity to learn and make use of environmental regularities - known as statistical learning (SL), including for the implicit guidance of attention. For instance, it is known that attentional selection is biased according to the spatial probability of targets; similarly, changes in distractor filtering can be triggered by the unequal spatial distribution of distractors. Open questions remain regarding the cognitive/neuronal mechanisms underlying SL of target selection and distractor filtering. Crucially, it is unclear whether the two processes rely on shared neuronal machinery, with unavoidable cross-talk, or they are fully independent, an issue that we directly addressed here. In a series of visual search experiments, participants had to discriminate a target stimulus, while ignoring a task-irrelevant salient distractor (when present). We systematically manipulated spatial probabilities of either one or the other stimulus, or both. We then measured performance to evaluate the direct effects of the applied contingent probability distribution (e.g., effects on target selection of the spatial imbalance in target occurrence across locations) as well as its indirect or "transfer" effects (e.g., effects of the same spatial imbalance on distractor filtering across locations). By this approach, we confirmed that SL of both target and distractor location implicitly bias attention. Most importantly, we described substantial indirect effects, with the unequal spatial probability of the target affecting filtering efficiency and, vice versa, the unequal spatial probability of the distractor affecting target selection efficiency across locations. The observed cross-talk demonstrates that SL of target selection and distractor filtering are instantiated via (at least partly) shared neuronal machinery, as further corroborated by strong correlations between direct and indirect effects at the level of individual participants. Our findings are compatible with the notion that both kinds of SL adjust the priority of specific locations within attentional priority maps of space. Copyright © 2017 Elsevier Ltd. All rights reserved.

Composition and distribution of medically important phlebotomines (Diptera: Psychodidae) in the municipalities of Tierralta and Valencia (Córdoba, Colombia).

PubMed

Vivero, Rafael José; Quintero, Lina Salazar; Peña, Horacio Cadena; Alvar-Beltrán, Jorge; Tovar, Catalina; Atencia, Claudia M; Vélez, Iván Darío

2017-01-01

Ecoepidemiological studies of cutaneous leishmaniasis and regular monitoring of Lutzomyia species have generated a knowledge base that can be used for control and prevention strategies targeted at the disease transmission dynamics in focal areas of Colombia. In this study, the presence and spatial distribution of phlebotomines of medical importance in the municipalities of Tierralta (El Loro and Tuis Tuis villages) and Valencia (Guadua and Mieles villages) were determined. Entomological surveys were performed in 2015 (months of June, September and November) and samples were collected via CDC-traps located in intradomicilary and peridomiciliary areas in the municipalities of Tierralta and Valencia (Department of Córdoba, Colombia). Active searches were also carried out with a mouth aspirator to collect adult phlebotomines from resting sites. ANOVA and Kruskal-Wallis tests were performed to assess if the differences between the communities of phlebotomines. Spatial distribution maps of the Lutzomyia species were generated. A high species diversity of Lutzomyia was observed with a total of 1677 Lutzomyia individuals belonging to 12 species. Among these species, Lu. panamensis was the most abundant (80.18%). The composition of the intradomicilary and peridomiciliary phlebotomines varied significantly (F = 0.9962; df = 1; p = 0.02895). Species like Lu. carpenteri, Lu. camposi, Lu. dysponeta, Lu. atroclavata and Lu. yuilli yuilli were recorded for the first time in the Department of Córdoba, Colombia. The spatial distribution shows that Lu. panamensis and Lu. gomezi are predominant and present in areas with high concentration of houses. This study provides basic information on new records of phlebotomines in the Department of Córdoba. The results suggest that greater vector-human contact occurs in the peridomiciliary environment and that a high number of Lutzomyia species associated with the transmission of leishmaniasis are present in Colombia.

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.

Complex Epidemiology of a Zoonotic Disease in a Culturally Diverse Region: Phylogeography of Rabies Virus in the Middle East

PubMed Central

Horton, Daniel L.; McElhinney, Lorraine M.; Freuling, Conrad M.; Marston, Denise A.; Banyard, Ashley C.; Goharrriz, Hooman; Wise, Emma; Breed, Andrew C.; Saturday, Greg; Kolodziejek, Jolanta; Zilahi, Erika; Al-Kobaisi, Muhannad F.; Nowotny, Norbert; Mueller, Thomas; Fooks, Anthony R.

2015-01-01

The Middle East is a culturally and politically diverse region at the gateway between Europe, Africa and Asia. Spatial dynamics of the fatal zoonotic disease rabies among countries of the Middle East and surrounding regions is poorly understood. An improved understanding of virus distribution is necessary to direct control methods. Previous studies have suggested regular trans-boundary movement, but have been unable to infer direction. Here we address these issues, by investigating the evolution of 183 rabies virus isolates collected from over 20 countries between 1972 and 2014. We have undertaken a discrete phylogeographic analysis on a subset of 139 samples to infer where and when movements of rabies have occurred. We provide evidence for four genetically distinct clades with separate origins currently circulating in the Middle East and surrounding countries. Introductions of these viruses have been followed by regular and multidirectional trans-boundary movements in some parts of the region, but relative isolation in others. There is evidence for minimal regular incursion of rabies from Central and Eastern Asia. These data support current initiatives for regional collaboration that are essential for rabies elimination. PMID:25811659

A novel scatter-matrix eigenvalues-based total variation (SMETV) regularization for medical image restoration

NASA Astrophysics Data System (ADS)

Huang, Zhenghua; Zhang, Tianxu; Deng, Lihua; Fang, Hao; Li, Qian

2015-12-01

Total variation(TV) based on regularization has been proven as a popular and effective model for image restoration, because of its ability of edge preserved. However, as the TV favors a piece-wise constant solution, the processing results in the flat regions of the image are easily produced "staircase effects", and the amplitude of the edges will be underestimated; the underlying cause of the problem is that the regularization parameter can not be changeable with spatial local information of image. In this paper, we propose a novel Scatter-matrix eigenvalues-based TV(SMETV) regularization with image blind restoration algorithm for deblurring medical images. The spatial information in different image regions is incorporated into regularization by using the edge indicator called difference eigenvalue to distinguish edges from flat areas. The proposed algorithm can effectively reduce the noise in flat regions as well as preserve the edge and detailed information. Moreover, it becomes more robust with the change of the regularization parameter. Extensive experiments demonstrate that the proposed approach produces results superior to most methods in both visual image quality and quantitative measures.

Analysis of Biophysical Mechanisms of Gilgai Microrelief Formation in Dryland Swelling Soils Using Ultra-High Resolution Aerial Imagery

NASA Astrophysics Data System (ADS)

Krell, N.; DeCarlo, K. F.; Caylor, K. K.

2015-12-01

Microrelief formations ("gilgai"), which form due to successive wetting-drying cycles typical of swelling soils, provide ecological hotspots for local fauna and flora, including higher and more robust vegetative growth. The distribution of these gilgai suggests a remarkable degree of regularity. However, it is unclear to what extent the mechanisms that drive gilgai formation are physical, such as desiccation-induced fracturing, or biological in nature, namely antecedent vegetative clustering. We investigated gilgai genesis and pattern formation in a 100 x 100 meter study area with swelling soils in a semiarid grassland at the Mpala Research Center in central Kenya. Our ongoing experiment is composed of three 9m2 treatments: we removed gilgai and limited vegetative growth by herbicide application in one plot, allowed for unrestricted seed dispersal in another, and left gilgai unobstructed in a control plot. To estimate the spatial frequencies of the repeating patterns of gilgai, we obtained ultra-high resolution (0.01-0.03m/pixel) images with an unmanned aerial vehicle (UAV) from which digital elevation models were also generated. Geostatistical analyses using wavelet and fourier methods in 1- and 2-dimensions were employed to characterize gilgai size and distribution. Preliminary results support regular spatial patterning across the gilgaied landscape and heterogeneities may be related to local soil properties and biophysical influences. Local data on gilgai and fracture characteristics suggest that gilgai form at characteristic heights and spacing based on fracture morphology: deep, wide cracks result in large, highly vegetated mounds whereas shallow cracks, induced by animal trails, are less correlated with gilgai size and shape. Our experiments will help elucidate the links between shrink-swell processes and gilgai-vegetation patterning in high activity clay soils and advance our understanding of the mechanisms of gilgai formation in drylands.

Power Law Patch Scaling and Lack of Characteristic Wavelength Suggest "Scale-Free" Processes Drive Pattern Formation in the Florida Everglades

NASA Astrophysics Data System (ADS)

Kaplan, D. A.; Casey, S. T.; Cohen, M. J.; Acharya, S.; Jawitz, J. W.

2016-12-01

A century of hydrologic modification has altered the physical and biological drivers of landscape processes in the Everglades (Florida, USA). Restoring the ridge-slough patterned landscape, a dominant feature of the historical system, is a priority, but requires an understanding of pattern genesis and degradation mechanisms. Physical experiments to evaluate alternative pattern formation mechanisms are limited by the long time scales of peat accumulation and loss, necessitating model-based comparisons, where support for a particular mechanism is based on model replication of extant patterning and trajectories of degradation. However, multiple mechanisms yield patch elongation in the direction of historical flow (a central feature of ridge-slough patterning), limiting the utility of that characteristic for discriminating among alternatives. Using data from vegetation maps, we investigated the statistical features of ridge-slough spatial patterning (ridge density, patch perimeter, elongation, patch-size distributions, and spatial periodicity) to establish more rigorous criteria for evaluating model performance and to inform controls on pattern variation across the contemporary system. Two independent analyses (2-D periodograms and patch size distributions) provide strong evidence against regular patterning, with the landscape exhibiting neither a characteristic wavelength nor a characteristic patch size, both of which are expected under conditions that produce regular patterns. Rather, landscape properties suggest robust scale-free patterning, indicating genesis from the coupled effects of local facilitation and a global negative feedback operating uniformly at the landscape-scale. This finding challenges widespread invocation of scale-dependent negative feedbacks for explaining ridge-slough pattern origins. These results help discern among genesis mechanisms and provide an improved statistical description of the landscape that can be used to compare among model outputs, as well as to assess the success of future restoration projects.

Spatially adapted second-order total generalized variational image deblurring model under impulse noise

NASA Astrophysics Data System (ADS)

Zhong, Qiu-Xiang; Wu, Chuan-Sheng; Shu, Qiao-Ling; Liu, Ryan Wen

2018-04-01

Image deblurring under impulse noise is a typical ill-posed problem which requires regularization methods to guarantee high-quality imaging. L1-norm data-fidelity term and total variation (TV) regularizer have been combined to contribute the popular regularization method. However, the TV-regularized variational image deblurring model often suffers from the staircase-like artifacts leading to image quality degradation. To enhance image quality, the detailpreserving total generalized variation (TGV) was introduced to replace TV to eliminate the undesirable artifacts. The resulting nonconvex optimization problem was effectively solved using the alternating direction method of multipliers (ADMM). In addition, an automatic method for selecting spatially adapted regularization parameters was proposed to further improve deblurring performance. Our proposed image deblurring framework is able to remove blurring and impulse noise effects while maintaining the image edge details. Comprehensive experiments have been conducted to demonstrate the superior performance of our proposed method over several state-of-the-art image deblurring methods.

Production of Supra-regular Spatial Sequences by Macaque Monkeys.

PubMed

Jiang, Xinjian; Long, Tenghai; Cao, Weicong; Li, Junru; Dehaene, Stanislas; Wang, Liping

2018-06-18

Understanding and producing embedded sequences in language, music, or mathematics, is a central characteristic of our species. These domains are hypothesized to involve a human-specific competence for supra-regular grammars, which can generate embedded sequences that go beyond the regular sequences engendered by finite-state automata. However, is this capacity truly unique to humans? Using a production task, we show that macaque monkeys can be trained to produce time-symmetrical embedded spatial sequences whose formal description requires supra-regular grammars or, equivalently, a push-down stack automaton. Monkeys spontaneously generalized the learned grammar to novel sequences, including longer ones, and could generate hierarchical sequences formed by an embedding of two levels of abstract rules. Compared to monkeys, however, preschool children learned the grammars much faster using a chunking strategy. While supra-regular grammars are accessible to nonhuman primates through extensive training, human uniqueness may lie in the speed and learning strategy with which they are acquired. Copyright © 2018 Elsevier Ltd. All rights reserved.

Selection of Multiarmed Spiral Waves in a Regular Network of Neurons

PubMed Central

Hu, Bolin; Ma, Jun; Tang, Jun

2013-01-01

Formation and selection of multiarmed spiral wave due to spontaneous symmetry breaking are investigated in a regular network of Hodgkin-Huxley neuron by changing the excitability and imposing spatial forcing currents on the neurons in the network. The arm number of the multiarmed spiral wave is dependent on the distribution of spatial forcing currents and excitability diversity in the network, and the selection criterion for supporting multiarmed spiral waves is discussed. A broken spiral segment is measured by a short polygonal line connected by three adjacent points (controlled nodes), and a double-spiral wave can be developed from the spiral segment. Multiarmed spiral wave is formed when a group of double-spiral waves rotate in the same direction in the network. In the numerical studies, a group of controlled nodes are selected and spatial forcing currents are imposed on these nodes, and our results show that l-arm stable spiral wave (l = 2, 3, 4,...8) can be induced to occupy the network completely. It is also confirmed that low excitability is critical to induce multiarmed spiral waves while high excitability is important to propagate the multiarmed spiral wave outside so that distinct multiarmed spiral wave can occupy the network completely. Our results confirm that symmetry breaking of target wave in the media accounts for emergence of multiarmed spiral wave, which can be developed from a group of spiral waves with single arm under appropriate condition, thus the potential formation mechanism of multiarmed spiral wave in the media is explained. PMID:23935966

Scattering effects and high-spatial-frequency nanostructures on ultrafast laser irradiated surfaces of zirconium metallic alloys with nano-scaled topographies.

PubMed

Li, Chen; Cheng, Guanghua; Sedao, Xxx; Zhang, Wei; Zhang, Hao; Faure, Nicolas; Jamon, Damien; Colombier, Jean-Philippe; Stoian, Razvan

2016-05-30

The origin of high-spatial-frequency laser-induced periodic surface structures (HSFL) driven by incident ultrafast laser fields, with their ability to achieve structure resolutions below λ/2, is often obscured by the overlap with regular ripples patterns at quasi-wavelength periodicities. We experimentally demonstrate here employing defined surface topographies that these structures are intrinsically related to surface roughness in the nano-scale domain. Using Zr-based bulk metallic glass (Zr-BMG) and its crystalline alloy (Zr-CA) counterpart formed by thermal annealing from its glassy precursor, we prepared surfaces showing either smooth appearances on thermoplastic BMG or high-density nano-protuberances from randomly distributed embedded nano-crystallites with average sizes below 200 nm on the recrystallized alloy. Upon ultrashort pulse irradiation employing linearly polarized 50 fs, 800 nm laser pulses, the surfaces show a range of nanoscale organized features. The change of topology was then followed under multiple pulse irradiation at fluences around and below the single pulse threshold. While the former material (Zr-BMG) shows a specific high quality arrangement of standard ripples around the laser wavelength, the latter (Zr-CA) demonstrates strong predisposition to form high spatial frequency rippled structures (HSFL). We discuss electromagnetic scenarios assisting their formation based on near-field interaction between particles and field-enhancement leading to structure linear growth. Finite-difference-time-domain simulations outline individual and collective effects of nanoparticles on electromagnetic energy modulation and the feedback processes in the formation of HSFL structures with correlation to regular ripples (LSFL).

Mixed linear-non-linear inversion of crustal deformation data: Bayesian inference of model, weighting and regularization parameters

NASA Astrophysics Data System (ADS)

Fukuda, Jun'ichi; Johnson, Kaj M.

2010-06-01

We present a unified theoretical framework and solution method for probabilistic, Bayesian inversions of crustal deformation data. The inversions involve multiple data sets with unknown relative weights, model parameters that are related linearly or non-linearly through theoretic models to observations, prior information on model parameters and regularization priors to stabilize underdetermined problems. To efficiently handle non-linear inversions in which some of the model parameters are linearly related to the observations, this method combines both analytical least-squares solutions and a Monte Carlo sampling technique. In this method, model parameters that are linearly and non-linearly related to observations, relative weights of multiple data sets and relative weights of prior information and regularization priors are determined in a unified Bayesian framework. In this paper, we define the mixed linear-non-linear inverse problem, outline the theoretical basis for the method, provide a step-by-step algorithm for the inversion, validate the inversion method using synthetic data and apply the method to two real data sets. We apply the method to inversions of multiple geodetic data sets with unknown relative data weights for interseismic fault slip and locking depth. We also apply the method to the problem of estimating the spatial distribution of coseismic slip on faults with unknown fault geometry, relative data weights and smoothing regularization weight.

Blind estimation of blur in hyperspectral images

NASA Astrophysics Data System (ADS)

Zhang, Mo; Vozel, Benoit; Chehdi, Kacem; Uss, Mykhail; Abramov, Sergey; Lukin, Vladimir

2017-10-01

Hyperspectral images acquired by remote sensing systems are generally degraded by noise and can be sometimes more severely degraded by blur. When no knowledge is available about the degradations present on the original image, blind restoration methods can only be considered. By blind, we mean absolutely no knowledge neither of the blur point spread function (PSF) nor the original latent channel and the noise level. In this study, we address the blind restoration of the degraded channels component-wise, according to a sequential scheme. For each degraded channel, the sequential scheme estimates the blur point spread function (PSF) in a first stage and deconvolves the degraded channel in a second and final stage by means of using the PSF previously estimated. We propose a new component-wise blind method for estimating effectively and accurately the blur point spread function. This method follows recent approaches suggesting the detection, selection and use of sufficiently salient edges in the current processed channel for supporting the regularized blur PSF estimation. Several modifications are beneficially introduced in our work. A new selection of salient edges through thresholding adequately the cumulative distribution of their corresponding gradient magnitudes is introduced. Besides, quasi-automatic and spatially adaptive tuning of the involved regularization parameters is considered. To prove applicability and higher efficiency of the proposed method, we compare it against the method it originates from and four representative edge-sparsifying regularized methods of the literature already assessed in a previous work. Our attention is mainly paid to the objective analysis (via ݈l1-norm) of the blur PSF error estimation accuracy. The tests are performed on a synthetic hyperspectral image. This synthetic hyperspectral image has been built from various samples from classified areas of a real-life hyperspectral image, in order to benefit from realistic spatial distribution of reference spectral signatures to recover after synthetic degradation. The synthetic hyperspectral image has been successively degraded with eight real blurs taken from the literature, each of a different support size. Conclusions, practical recommendations and perspectives are drawn from the results experimentally obtained.

Biological Oceanography

NASA Technical Reports Server (NTRS)

Abbott, M. R.

1984-01-01

Within the framework of global biogeochemical cycles and ocean productivity, there are two areas that will be of particular interest to biological oceanography in the 1990s. The first is the mapping in space time of the biomass and productivity of phytoplankton in the world ocean. The second area is the coupling of biological and physical processes as it affects the distribution and growth rate of phytoplankton biomass. Certainly other areas will be of interest to biological oceanographers, but these two areas are amenable to observations from satellites. Temporal and spatial variability is a regular feature of marine ecosystems. The temporal and spatial variability of phytoplankton biomass and productivity which is ubiquitous at all time and space scales in the ocean must be characterized. Remote sensing from satellites addresses these problems with global observations of mesocale (2 to 20 days, 10 to 200 km) features over a long period of time.

Significance tests for functional data with complex dependence structure.

PubMed

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

2015-01-01

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

Maximum entropy deconvolution of the optical jet of 3C 273

NASA Technical Reports Server (NTRS)

Evans, I. N.; Ford, H. C.; Hui, X.

1989-01-01

The technique of maximum entropy image restoration is applied to the problem of deconvolving the point spread function from a deep, high-quality V band image of the optical jet of 3C 273. The resulting maximum entropy image has an approximate spatial resolution of 0.6 arcsec and has been used to study the morphology of the optical jet. Four regularly-spaced optical knots are clearly evident in the data, together with an optical 'extension' at each end of the optical jet. The jet oscillates around its center of gravity, and the spatial scale of the oscillations is very similar to the spacing between the optical knots. The jet is marginally resolved in the transverse direction and has an asymmetric profile perpendicular to the jet axis. The distribution of V band flux along the length of the jet, and accurate astrometry of the optical knot positions are presented.

A New Pansharpening Method Based on Spatial and Spectral Sparsity Priors.

PubMed

He, Xiyan; Condat, Laurent; Bioucas-Diaz, Jose; Chanussot, Jocelyn; Xia, Junshi

2014-06-27

The development of multisensor systems in recent years has led to great increase in the amount of available remote sensing data. Image fusion techniques aim at inferring high quality images of a given area from degraded versions of the same area obtained by multiple sensors. This paper focuses on pansharpening, which is the inference of a high spatial resolution multispectral image from two degraded versions with complementary spectral and spatial resolution characteristics: a) a low spatial resolution multispectral image; and b) a high spatial resolution panchromatic image. We introduce a new variational model based on spatial and spectral sparsity priors for the fusion. In the spectral domain we encourage low-rank structure, whereas in the spatial domain we promote sparsity on the local differences. Given the fact that both panchromatic and multispectral images are integrations of the underlying continuous spectra using different channel responses, we propose to exploit appropriate regularizations based on both spatial and spectral links between panchromatic and the fused multispectral images. A weighted version of the vector Total Variation (TV) norm of the data matrix is employed to align the spatial information of the fused image with that of the panchromatic image. With regard to spectral information, two different types of regularization are proposed to promote a soft constraint on the linear dependence between the panchromatic and the fused multispectral images. The first one estimates directly the linear coefficients from the observed panchromatic and low resolution multispectral images by Linear Regression (LR) while the second one employs the Principal Component Pursuit (PCP) to obtain a robust recovery of the underlying low-rank structure. We also show that the two regularizers are strongly related. The basic idea of both regularizers is that the fused image should have low-rank and preserve edge locations. We use a variation of the recently proposed Split Augmented Lagrangian Shrinkage (SALSA) algorithm to effectively solve the proposed variational formulations. Experimental results on simulated and real remote sensing images show the effectiveness of the proposed pansharpening method compared to the state-of-the-art.

Effects of Heterogeneous Diffuse Fibrosis on Arrhythmia Dynamics and Mechanism

PubMed Central

Kazbanov, Ivan V.; ten Tusscher, Kirsten H. W. J.; Panfilov, Alexander V.

2016-01-01

Myocardial fibrosis is an important risk factor for cardiac arrhythmias. Previous experimental and numerical studies have shown that the texture and spatial distribution of fibrosis may play an important role in arrhythmia onset. Here, we investigate how spatial heterogeneity of fibrosis affects arrhythmia onset using numerical methods. We generate various tissue textures that differ by the mean amount of fibrosis, the degree of heterogeneity and the characteristic size of heterogeneity. We study the onset of arrhythmias using a burst pacing protocol. We confirm that spatial heterogeneity of fibrosis increases the probability of arrhythmia induction. This effect is more pronounced with the increase of both the spatial size and the degree of heterogeneity. The induced arrhythmias have a regular structure with the period being mostly determined by the maximal local fibrosis level. We perform ablations of the induced fibrillatory patterns to classify their type. We show that in fibrotic tissue fibrillation is usually of the mother rotor type but becomes of the multiple wavelet type with increase in tissue size. Overall, we conclude that the most important factor determining the formation and dynamics of arrhythmia in heterogeneous fibrotic tissue is the value of maximal local fibrosis. PMID:26861111

Cortical dipole imaging using truncated total least squares considering transfer matrix error.

PubMed

Hori, Junichi; Takeuchi, Kosuke

2013-01-01

Cortical dipole imaging has been proposed as a method to visualize electroencephalogram in high spatial resolution. We investigated the inverse technique of cortical dipole imaging using a truncated total least squares (TTLS). The TTLS is a regularization technique to reduce the influence from both the measurement noise and the transfer matrix error caused by the head model distortion. The estimation of the regularization parameter was also investigated based on L-curve. The computer simulation suggested that the estimation accuracy was improved by the TTLS compared with Tikhonov regularization. The proposed method was applied to human experimental data of visual evoked potentials. We confirmed the TTLS provided the high spatial resolution of cortical dipole imaging.

A simple homogeneous model for regular and irregular metallic wire media samples

NASA Astrophysics Data System (ADS)

Kosulnikov, S. Y.; Mirmoosa, M. S.; Simovski, C. R.

2018-02-01

To simplify the solution of electromagnetic problems with wire media samples, it is reasonable to treat them as the samples of a homogeneous material without spatial dispersion. The account of spatial dispersion implies additional boundary conditions and makes the solution of boundary problems difficult especially if the sample is not an infinitely extended layer. Moreover, for a novel type of wire media - arrays of randomly tilted wires - a spatially dispersive model has not been developed. Here, we introduce a simplistic heuristic model of wire media samples shaped as bricks. Our model covers WM of both regularly and irregularly stretched wires.

Genetic analysis reveals efficient sexual spore dispersal at a fine spatial scale in Armillaria ostoyae, the causal agent of root-rot disease in conifers.

PubMed

Dutech, Cyril; Labbé, Frédéric; Capdevielle, Xavier; Lung-Escarmant, Brigitte

Armillaria ostoyae (sometimes named Armillaria solidipes) is a fungal species causing root diseases in numerous coniferous forests of the northern hemisphere. The importance of sexual spores for the establishment of new disease centres remains unclear, particularly in the large maritime pine plantations of southwestern France. An analysis of the genetic diversity of a local fungal population distributed over 500 ha in this French forest showed genetic recombination between genotypes to be frequent, consistent with regular sexual reproduction within the population. The estimated spatial genetic structure displayed a significant pattern of isolation by distance, consistent with the dispersal of sexual spores mostly at the spatial scale studied. Using these genetic data, we inferred an effective density of reproductive individuals of 0.1-0.3 individuals/ha, and a second moment of parent-progeny dispersal distance of 130-800 m, compatible with the main models of fungal spore dispersal. These results contrast with those obtained for studies of A. ostoyae over larger spatial scales, suggesting that inferences about mean spore dispersal may be best performed at fine spatial scales (i.e. a few kilometres) for most fungal species. Copyright © 2017 British Mycological Society. Published by Elsevier Ltd. All rights reserved.

Morphology and spatial patterns of Macrotermes mounds in the SE Katanga, D.R. Congo

NASA Astrophysics Data System (ADS)

Bazirake Mujinya, Basile; Mees, Florias; Erens, Hans; Baert, Geert; Van Ranst, Eric

2015-04-01

The spatial distribution patterns and morphological characteristics of Macrotermes falciger mounds were investigated in the Lubumbashi area, D.R. Congo. Examination of the spatial patterns of M. falciger mounds on high resolution satellite images reveals a mean areal number density of 2.9 ± 0.4 mounds ha-1. The high relative number of inactive mounds in the region, along with their regular distribution pattern, suggests that current termite mound occurrences are largely palaeostructures. Mound positions in the habitat are consistent with intraspecific competition rather than soil and substrate characteristics as controlling factor. Detailed morphological description of five deep termite-mound profiles (~7 m height/depth) shows that carbonate pedofeatures are present in all studied profiles, in contrast to the control soils. They mainly occur in the form of soft powdery masses, nodules and coatings on ped faces, all clearly pedogenic. Carbonate coatings occur mainly between 1 m above the soil surface and 1 m below that level in all mound profiles. Carbonate nodules do show a different distribution pattern at each site. Furthermore, when the studied profiles are considered to represent a toposequence, the stone layer occurs at greater depth in topographically low areas compared to crest and slope positions, which is mainly conditioned by erosion. The clay content of epigeal mounds increases from the summit to the toe slope, which can be largely related to differences in parent material. The Mn-Fe oxide concentrations occurring in all studied termite mound profiles reflect a seasonally high perched water table beneath the mound, which is more pronounced at the lower slope positions.

Spatial Pattern of Soil Salinity in Area Around the Yellow River Delta and Its Seasonal Dynamics over a 3-year Period

NASA Astrophysics Data System (ADS)

Lai, J.; Ouyang, Z.

2017-12-01

Salt-affected land varies spatially and seasonally in terms of soil salinity. "Bohai Granary" is a newly proposed national-level program which was aimed to improve soil quality and mining grain production potential of the salt-affected land in east China. In this work, soil samples were monthly taken at 11 sites within Wudi county in the Yellow river delta. The spatial distribution pattern of soil salinity were investigated and its seasonal variation over 36 months were discussed. Our findings indicate that the vertical distribution type of soil salinity was bottom-accumulating in the near coastal area while its gradually turned into a type of surface-accumulating as the sampling site moving towards the inner land. The peak of the soil salinity along the soil profile alternately moved upwards and downwards during the growing seasons. However, there was no evidence for the increasing of the total salt amount within the upper 100cm of soil. Moreover, the salt was mostly accumulated in the upper soil (0-40cm) during the late spring and early summer season; and winter wheat was tend to be affected severely at this stage. Therefore, special field practices (e.g. regular irrigation to leach salt, good maintenance of drainage system) should be taken to minimize the threat of soil salinity.

Phase separation driven by density-dependent movement: A novel mechanism for ecological patterns.

PubMed

Liu, Quan-Xing; Rietkerk, Max; Herman, Peter M J; Piersma, Theunis; Fryxell, John M; van de Koppel, Johan

2016-12-01

Many ecosystems develop strikingly regular spatial patterns because of small-scale interactions between organisms, a process generally referred to as spatial self-organization. Self-organized spatial patterns are important determinants of the functioning of ecosystems, promoting the growth and survival of the involved organisms, and affecting the capacity of the organisms to cope with changing environmental conditions. The predominant explanation for self-organized pattern formation is spatial heterogeneity in establishment, growth and mortality, resulting from the self-organization processes. A number of recent studies, however, have revealed that movement of organisms can be an important driving process creating extensive spatial patterning in many ecosystems. Here, we review studies that detail movement-based pattern formation in contrasting ecological settings. Our review highlights that a common principle, where movement of organisms is density-dependent, explains observed spatial regular patterns in all of these studies. This principle, well known to physics as the Cahn-Hilliard principle of phase separation, has so-far remained unrecognized as a general mechanism for self-organized complexity in ecology. Using the examples presented in this paper, we explain how this movement principle can be discerned in ecological settings, and clarify how to test this mechanism experimentally. Our study highlights that animal movement, both in isolation and in unison with other processes, is an important mechanism for regular pattern formation in ecosystems. Copyright © 2016 Elsevier B.V. All rights reserved.

High northern latitude temperature extremes, 1400-1999

NASA Astrophysics Data System (ADS)

Tingley, M. P.; Huybers, P.; Hughen, K. A.

2009-12-01

There is often an interest in determining which interval features the most extreme value of a reconstructed climate field, such as the warmest year or decade in a temperature reconstruction. Previous approaches to this type of question have not fully accounted for the spatial and temporal covariance in the climate field when assessing the significance of extreme values. Here we present results from applying BARSAT, a new, Bayesian approach to reconstructing climate fields, to a 600 year multiproxy temperature data set that covers land areas between 45N and 85N. The end result of the analysis is an ensemble of spatially and temporally complete realizations of the temperature field, each of which is consistent with the observations and the estimated values of the parameters that define the assumed spatial and temporal covariance functions. In terms of the spatial average temperature, 1990-1999 was the warmest decade in the 1400-1999 interval in each of 2000 ensemble members, while 1995 was the warmest year in 98% of the ensemble members. A similar analysis at each node of a regular 5 degree grid gives insight into the spatial distribution of warm temperatures, and reveals that 1995 was anomalously warm in Eurasia, whereas 1998 featured extreme warmth in North America. In 70% of the ensemble members, 1601 featured the coldest spatial average, indicating that the eruption of Huaynaputina in Peru in 1600 (with a volcanic explosivity index of 6) had a major cooling impact on the high northern latitudes. Repeating this analysis at each node reveals the varying impacts of major volcanic eruptions on the distribution of extreme cooling. Finally, we use the ensemble to investigate extremes in the time evolution of centennial temperature trends, and find that in more than half the ensemble members, the greatest rate of change in the spatial mean time series was a cooling centered at 1600. The largest rate of centennial scale warming, however, occurred in the 20th Century in more than 98% of the ensemble members.

Calibrating the Spatiotemporal Root Density Distribution for Macroscopic Water Uptake Models Using Tikhonov Regularization

NASA Astrophysics Data System (ADS)

Li, N.; Yue, X. Y.

2018-03-01

Macroscopic root water uptake models proportional to a root density distribution function (RDDF) are most commonly used to model water uptake by plants. As the water uptake is difficult and labor intensive to measure, these models are often calibrated by inverse modeling. Most previous inversion studies assume RDDF to be constant with depth and time or dependent on only depth for simplification. However, under field conditions, this function varies with type of soil and root growth and thus changes with both depth and time. This study proposes an inverse method to calibrate both spatially and temporally varying RDDF in unsaturated water flow modeling. To overcome the difficulty imposed by the ill-posedness, the calibration is formulated as an optimization problem in the framework of the Tikhonov regularization theory, adding additional constraint to the objective function. Then the formulated nonlinear optimization problem is numerically solved with an efficient algorithm on the basis of the finite element method. The advantage of our method is that the inverse problem is translated into a Tikhonov regularization functional minimization problem and then solved based on the variational construction, which circumvents the computational complexity in calculating the sensitivity matrix involved in many derivative-based parameter estimation approaches (e.g., Levenberg-Marquardt optimization). Moreover, the proposed method features optimization of RDDF without any prior form, which is applicable to a more general root water uptake model. Numerical examples are performed to illustrate the applicability and effectiveness of the proposed method. Finally, discussions on the stability and extension of this method are presented.

Interobject grouping facilitates visual awareness.

PubMed

Stein, Timo; Kaiser, Daniel; Peelen, Marius V

2015-01-01

In organizing perception, the human visual system takes advantage of regularities in the visual input to perceptually group related image elements. Simple stimuli that can be perceptually grouped based on physical regularities, for example by forming an illusory contour, have a competitive advantage in entering visual awareness. Here, we show that regularities that arise from the relative positioning of complex, meaningful objects in the visual environment also modulate visual awareness. Using continuous flash suppression, we found that pairs of objects that were positioned according to real-world spatial regularities (e.g., a lamp above a table) accessed awareness more quickly than the same object pairs shown in irregular configurations (e.g., a table above a lamp). This advantage was specific to upright stimuli and abolished by stimulus inversion, meaning that it did not reflect physical stimulus confounds or the grouping of simple image elements. Thus, knowledge of the spatial configuration of objects in the environment shapes the contents of conscious perception.

Enhancing Children's Spatial and Numerical Skills through a Dynamic Spatial Approach to Early Geometry Instruction: Effects of a 32-Week Intervention

ERIC Educational Resources Information Center

Hawes, Zachary; Moss, Joan; Caswell, Beverly; Naqvi, Sarah; MacKinnon, Sharla

2017-01-01

This study describes the implementation and effects of a 32-week teacher-led spatial reasoning intervention in K-2 classrooms. The intervention targeted spatial visualization skills as an integrated feature of regular mathematics instruction. Compared to an active control group, children in the spatial intervention demonstrated gains in spatial…

s-SMOOTH: Sparsity and Smoothness Enhanced EEG Brain Tomography

PubMed Central

Li, Ying; Qin, Jing; Hsin, Yue-Loong; Osher, Stanley; Liu, Wentai

2016-01-01

EEG source imaging enables us to reconstruct current density in the brain from the electrical measurements with excellent temporal resolution (~ ms). The corresponding EEG inverse problem is an ill-posed one that has infinitely many solutions. This is due to the fact that the number of EEG sensors is usually much smaller than that of the potential dipole locations, as well as noise contamination in the recorded signals. To obtain a unique solution, regularizations can be incorporated to impose additional constraints on the solution. An appropriate choice of regularization is critically important for the reconstruction accuracy of a brain image. In this paper, we propose a novel Sparsity and SMOOthness enhanced brain TomograpHy (s-SMOOTH) method to improve the reconstruction accuracy by integrating two recently proposed regularization techniques: Total Generalized Variation (TGV) regularization and ℓ1−2 regularization. TGV is able to preserve the source edge and recover the spatial distribution of the source intensity with high accuracy. Compared to the relevant total variation (TV) regularization, TGV enhances the smoothness of the image and reduces staircasing artifacts. The traditional TGV defined on a 2D image has been widely used in the image processing field. In order to handle 3D EEG source images, we propose a voxel-based Total Generalized Variation (vTGV) regularization that extends the definition of second-order TGV from 2D planar images to 3D irregular surfaces such as cortex surface. In addition, the ℓ1−2 regularization is utilized to promote sparsity on the current density itself. We demonstrate that ℓ1−2 regularization is able to enhance sparsity and accelerate computations than ℓ1 regularization. The proposed model is solved by an efficient and robust algorithm based on the difference of convex functions algorithm (DCA) and the alternating direction method of multipliers (ADMM). Numerical experiments using synthetic data demonstrate the advantages of the proposed method over other state-of-the-art methods in terms of total reconstruction accuracy, localization accuracy and focalization degree. The application to the source localization of event-related potential data further demonstrates the performance of the proposed method in real-world scenarios. PMID:27965529

HFT events - Shallow moonquakes. [High-Frequency Teleseismic

NASA Technical Reports Server (NTRS)

Nakamura, Y.

1977-01-01

A few large distant seismic events of distinctly high signal frequency, designated HFT (high-frequency teleseismic) events, are observed yearly by the Apollo lunar seismic network. Their sources are located on or near the surface of the moon, leaving a large gap in seismic activity between the zones of HFT sources and deep moonquakes. No strong regularities are found in either their spatial or temporal distributions. Several working hypotheses for the identity of these sources have advanced, but many characteristics of the events seem to favor a hypothesis that they are shallow moonquakes. Simultaneous observations of other lunar phenomena may eventually enable the determination of their true identity.

Spatial distribution of living (Rose Bengal stained) benthic foraminifera in the Loire estuary (western France)

NASA Astrophysics Data System (ADS)

Mojtahid, M.; Geslin, E.; Coynel, A.; Gorse, L.; Vella, C.; Davranche, A.; Zozzolo, L.; Blanchet, L.; Bénéteau, E.; Maillet, G.

2016-12-01

Ninety-seven surface sediment samples were collected in September 2012 from intertidal and subtidal areas along the Loire estuary (western France). The main objective of this work is to study the spatial distributional patterns of living benthic foraminifera and their link to the environmental parameters (distance to sea, elevation, grain size, total organic carbon, trace metals, sedimentary carbonates, and polycyclic aromatic hydrocarbons) in the Loire estuary. Foraminiferal analysis was also extended to the dead assemblages in thirty-three surface samples from the lower inner estuary. The highest absolute densities of living benthic foraminifera are found in the lower inner estuary within the polyhaline domain. This is attributed to the presence of mudflats with abundant food source, i.e. microphytobenthos. The low densities found in the outer estuary (euhaline domain) are attributed partly to the sandy nature of the sediments and the food source inhabiting this substrate. The near absence of foraminifera in the inner estuary (mesohaline and polyhaline domains) is inferred to the physical disturbance resulting from the regular dredging of the navigation channel. The living assemblages are dominated by three typical estuarine species: Ammonia tepida and Haynesina germanica in the intertidal mudflats of the lower inner estuary and Cribroelphidium excavatum in the sandy subtidal sediments of the lower inner and outer estuary. In the Loire estuary, H. germanica has an unusual intermediate geographical distribution along the estuary between A. tepida and C. excavatum while in most temperate estuaries this species is present upstream in the mesohaline domain. This is most likely the result of the regular dredging of the navigation channel damaging its natural habitat. This might be also the explanation for the total absence of agglutinated species usually dominating the oligohaline domain. The canonical correspondence analysis shows that elevation (and its link to time of emersion), distance to sea (and its correspondence with salinity), and organic carbon content appear to be the primary drivers of foraminiferal distribution. The present study provides for the first time ecological and distribution patterns of living benthic foraminiferal communities in the Loire estuary. This baseline knowledge is necessary for the future studies focusing on the use of benthic foraminifera as bio-indicators in the Loire estuary and in transitional environments in general.

Task specificity of attention training: the case of probability cuing

PubMed Central

Jiang, Yuhong V.; Swallow, Khena M.; Won, Bo-Yeong; Cistera, Julia D.; Rosenbaum, Gail M.

2014-01-01

Statistical regularities in our environment enhance perception and modulate the allocation of spatial attention. Surprisingly little is known about how learning-induced changes in spatial attention transfer across tasks. In this study, we investigated whether a spatial attentional bias learned in one task transfers to another. Most of the experiments began with a training phase in which a search target was more likely to be located in one quadrant of the screen than in the other quadrants. An attentional bias toward the high-probability quadrant developed during training (probability cuing). In a subsequent, testing phase, the target's location distribution became random. In addition, the training and testing phases were based on different tasks. Probability cuing did not transfer between visual search and a foraging-like task. However, it did transfer between various types of visual search tasks that differed in stimuli and difficulty. These data suggest that different visual search tasks share a common and transferrable learned attentional bias. However, this bias is not shared by high-level, decision-making tasks such as foraging. PMID:25113853

Redistribution population data across a regular spatial grid according to buildings characteristics

NASA Astrophysics Data System (ADS)

Calka, Beata; Bielecka, Elzbieta; Zdunkiewicz, Katarzyna

2016-12-01

Population data are generally provided by state census organisations at the predefined census enumeration units. However, these datasets very are often required at userdefined spatial units that differ from the census output levels. A number of population estimation techniques have been developed to address these problems. This article is one of those attempts aimed at improving county level population estimates by using spatial disaggregation models with support of buildings characteristic, derived from national topographic database, and average area of a flat. The experimental gridded population surface was created for Opatów county, sparsely populated rural region located in Central Poland. The method relies on geolocation of population counts in buildings, taking into account the building volume and structural building type and then aggregation the people total in 1 km quadrilateral grid. The overall quality of population distribution surface expressed by the mean of RMSE equals 9 persons, and the MAE equals 0.01. We also discovered that nearly 20% of total county area is unpopulated and 80% of people lived on 33% of the county territory.

Rotationally driven 'zebra stripes' in Earth's inner radiation belt.

PubMed

Ukhorskiy, A Y; Sitnov, M I; Mitchell, D G; Takahashi, K; Lanzerotti, L J; Mauk, B H

2014-03-20

Structured features on top of nominally smooth distributions of radiation-belt particles at Earth have been previously associated with particle acceleration and transport mechanisms powered exclusively by enhanced solar-wind activity. Although planetary rotation is considered to be important for particle acceleration at Jupiter and Saturn, the electric field produced in the inner magnetosphere by Earth's rotation can change the velocity of trapped particles by only about 1-2 kilometres per second, so rotation has been thought inconsequential for radiation-belt electrons with velocities of about 100,000 kilometres per second. Here we report that the distributions of energetic electrons across the entire spatial extent of Earth's inner radiation belt are organized in regular, highly structured and unexpected 'zebra stripes', even when the solar-wind activity is low. Modelling reveals that the patterns are produced by Earth's rotation. Radiation-belt electrons are trapped in Earth's dipole-like magnetic field, where they undergo slow longitudinal drift motion around the planet because of the gradient and curvature of the magnetic field. Earth's rotation induces global diurnal variations of magnetic and electric fields that resonantly interact with electrons whose drift period is close to 24 hours, modifying electron fluxes over a broad energy range into regular patterns composed of multiple stripes extending over the entire span of the inner radiation belt.

A climatology of ⁷Be in surface air in European Union.

PubMed

Hernández-Ceballos, M A; Cinelli, G; Ferrer, M Marín; Tollefsen, T; De Felice, L; Nweke, E; Tognoli, P V; Vanzo, S; De Cort, M

2015-03-01

This study presents a European-wide analysis of the spatial and temporal distribution of the cosmogenic isotope (7)Be in surface air. This is the first time that a long term database of 34 sampling sites that regularly provide data to the Radioactivity Environmental Monitoring (REM) network, managed by the Joint Research Centre (JRC) in Ispra, is used. While temporal coverage varies between stations, some of them have delivered data more or less continuously from 1984 to 2011. The station locations were considerably heterogeneous, both in terms of latitude and altitude, a range which should ensure a high degree of representativeness of the results. The mean values of (7)Be activity concentration presented a spatial distribution value ranging from 2.0 to 5.4 mBq/m(3) over the European Union. The results of the ANOVA analysis of all (7)Be data available indicated that its temporal and spatial distributions were mainly explained by the location and characteristic of the sampling sites rather than its temporal distribution (yearly, seasonal and monthly). Higher (7)Be concentrations were registered at the middle, compared to high-latitude, regions. However, there was no correlation with altitude, since all stations are sited within the atmospheric boundary layer. In addition, the total and yearly analyses of the data indicated a dynamic range of (7)Be activity for each solar cycle and phase (maximum or minimum), different impact on stations having been observed according to their location. Finally, the results indicated a significant seasonal and monthly variation for (7)Be activity concentration across the European Union, with maximum concentrations occurring in the summer and minimum in the winter, although with differences in the values reached. The knowledge of the horizontal and vertical distribution of this natural radionuclide in the atmosphere is a key parameter for modelling studies of atmospheric processes, which are important phenomena to be taken into account in the case of a nuclear accident. Copyright © 2014 The Authors. Published by Elsevier Ltd.. All rights reserved.

The Effects of Geography and Spatial Behavior on Health Care Utilization among the Residents of a Rural Region

PubMed Central

Arcury, Thomas A; Gesler, Wilbert M; Preisser, John S; Sherman, Jill; Spencer, John; Perin, Jamie

2005-01-01

Objective This analysis determines the importance of geography and spatial behavior as predisposing and enabling factors in rural health care utilization, controlling for demographic, social, cultural, and health status factors. Data Sources A survey of 1,059 adults in 12 rural Appalachian North Carolina counties. Study Design This cross-sectional study used a three-stage sampling design stratified by county and ethnicity. Preliminary analysis of health services utilization compared weighted proportions of number of health care visits in the previous 12 months for regular check-up care, chronic care, and acute care across geographic, sociodemographic, cultural, and health variables. Multivariable logistic models identified independent correlates of health services utilization. Data Collection Methods Respondents answered standard survey questions. They located places in which they engaged health related and normal day-to-day activities; these data were entered into a geographic information system for analysis. Principal Findings Several geographic and spatial behavior factors, including having a driver's license, use of provided rides, and distance for regular care, were significantly related to health care utilization for regular check-up and chronic care in the bivariate analysis. In the multivariate model, having a driver's license and distance for regular care remained significant, as did several predisposing (age, gender, ethnicity), enabling (household income), and need (physical and mental health measures, number of conditions). Geographic measures, as predisposing and enabling factors, were related to regular check-up and chronic care, but not to acute care visits. Conclusions These results show the importance of geographic and spatial behavior factors in rural health care utilization. They also indicate continuing inequity in rural health care utilization that must be addressed in public policy. PMID:15663706

From regular text to artistic writing and artworks: Fourier statistics of images with low and high aesthetic appeal

PubMed Central

Melmer, Tamara; Amirshahi, Seyed A.; Koch, Michael; Denzler, Joachim; Redies, Christoph

2013-01-01

The spatial characteristics of letters and their influence on readability and letter identification have been intensely studied during the last decades. There have been few studies, however, on statistical image properties that reflect more global aspects of text, for example properties that may relate to its aesthetic appeal. It has been shown that natural scenes and a large variety of visual artworks possess a scale-invariant Fourier power spectrum that falls off linearly with increasing frequency in log-log plots. We asked whether images of text share this property. As expected, the Fourier spectrum of images of regular typed or handwritten text is highly anisotropic, i.e., the spectral image properties in vertical, horizontal, and oblique orientations differ. Moreover, the spatial frequency spectra of text images are not scale-invariant in any direction. The decline is shallower in the low-frequency part of the spectrum for text than for aesthetic artworks, whereas, in the high-frequency part, it is steeper. These results indicate that, in general, images of regular text contain less global structure (low spatial frequencies) relative to fine detail (high spatial frequencies) than images of aesthetics artworks. Moreover, we studied images of text with artistic claim (ornate print and calligraphy) and ornamental art. For some measures, these images assume average values intermediate between regular text and aesthetic artworks. Finally, to answer the question of whether the statistical properties measured by us are universal amongst humans or are subject to intercultural differences, we compared images from three different cultural backgrounds (Western, East Asian, and Arabic). Results for different categories (regular text, aesthetic writing, ornamental art, and fine art) were similar across cultures. PMID:23554592

Patterns in the spatial distribution of Peruvian anchovy ( Engraulis ringens) revealed by spatially explicit fishing data

NASA Astrophysics Data System (ADS)

Bertrand, Sophie; Díaz, Erich; Lengaigne, Matthieu

2008-10-01

Peruvian anchovy ( Engraulis ringens) stock abundance is tightly driven by the high and unpredictable variability of the Humboldt Current Ecosystem. Management of the fishery therefore cannot rely on mid- or long-term management policy alone but needs to be adaptive at relatively short time scales. Regular acoustic surveys are performed on the stock at intervals of 2 to 4 times a year, but there is a need for more time continuous monitoring indicators to ensure that management can respond at suitable time scales. Existing literature suggests that spatially explicit data on the location of fishing activities could be used as a proxy for target stock distribution. Spatially explicit commercial fishing data could therefore guide adaptive management decisions at shorter time scales than is possible through scientific stock surveys. In this study we therefore aim to (1) estimate the position of fishing operations for the entire fleet of Peruvian anchovy purse-seiners using the Peruvian satellite vessel monitoring system (VMS), and (2) quantify the extent to which the distribution of purse-seine sets describes anchovy distribution. To estimate fishing set positions from vessel tracks derived from VMS data we developed a methodology based on artificial neural networks (ANN) trained on a sample of fishing trips with known fishing set positions (exact fishing positions are known for approximately 1.5% of the fleet from an at-sea observer program). The ANN correctly identified 83% of the real fishing sets and largely outperformed comparative linear models. This network is then used to forecast fishing operations for those trips where no observers were onboard. To quantify the extent to which fishing set distribution was correlated to stock distribution we compared three metrics describing features of the distributions (the mean distance to the coast, the total area of distribution, and a clustering index) for concomitant acoustic survey observations and fishing set positions identified from VMS. For two of these metrics (mean distance to the coast and clustering index), fishing and survey data were significantly correlated. We conclude that the location of purse-seine fishing sets yields significant and valuable information on the distribution of the Peruvian anchovy stock and ultimately on its vulnerability to the fishery. For example, a high concentration of sets in the near coastal zone could potentially be used as a warning signal of high levels of stock vulnerability and trigger appropriate management measures aimed at reducing fishing effort.

Bayesian explorations of fault slip evolution over the earthquake cycle

NASA Astrophysics Data System (ADS)

Duputel, Z.; Jolivet, R.; Benoit, A.; Gombert, B.

2017-12-01

The ever-increasing amount of geophysical data continuously opens new perspectives on fundamental aspects of the seismogenic behavior of active faults. In this context, the recent fleet of SAR satellites including Sentinel-1 and COSMO-SkyMED permits the use of InSAR for time-dependent slip modeling with unprecedented resolution in time and space. However, existing time-dependent slip models rely on spatial smoothing regularization schemes, which can produce unrealistically smooth slip distributions. In addition, these models usually do not include uncertainty estimates thereby reducing the utility of such estimates. Here, we develop an entirely new approach to derive probabilistic time-dependent slip models. This Markov-Chain Monte Carlo method involves a series of transitional steps to predict and update posterior Probability Density Functions (PDFs) of slip as a function of time. We assess the viability of our approach using various slow-slip event scenarios. Using a dense set of SAR images, we also use this method to quantify the spatial distribution and temporal evolution of slip along a creeping segment of the North Anatolian Fault. This allows us to track a shallow aseismic slip transient lasting for about a month with a maximum slip of about 2 cm.

Malaysia.

PubMed

1980-10-01

The official government policy in Malaysia is to reduce the rate of population growth through decreasing fertility levels and a program of economic and social restructuring. Population policy was conceived as encompassing wider dimensions than family planning, with emphasis on spatial distribution policies. The first Population and Housing Census was undertaken by the government in 1970. Regular decennial census taking occurred between 1891 and 1957. Birth and death registrations are considered incomplete. Population issues are integrated by various organizations into their ongoing programs such as those of the Ministries of Health, Education or Agriculture. The National Family Planning Board, an interministerial body in the Prime Minister's Department, has input from development planning units. A population studies group was established within the Economic Planning Unit. The total 1980 population was 13,640,000; the rate of population growth was 2.6 from 1975-80. Life expectancy was 61.3. Morbidity and mortality rates have dropped because of disease control and malnutrition reduction. 7.4% of the population are foreign born. Spatial distribution is to be adjusted through rural land development and resettlement; promotion of industrial development in low-income states; development of new growth centers and towns; and, urban development and renewal.

The orthographic sensitivity to written Chinese in the occipital-temporal cortex.

PubMed

Liu, Haicheng; Jiang, Yi; Zhang, Bo; Ma, Lifei; He, Sheng; Weng, Xuchu

2013-06-01

Previous studies have identified an area in the left lateral fusiform cortex that is highly responsive to written words and has been named the visual word form area (VWFA). However, there is disagreement on the specific functional role of this area in word recognition. Chinese characters, which are dramatically different from Roman alphabets in the visual form and in the form to phonological mapping, provide a unique opportunity to investigate the properties of the VWFA. Specifically, to clarify the orthographic sensitivity in the mid-fusiform cortex, we compared fMRI response amplitudes (Exp. 1) as well as the spatial patterns of response across multiple voxels (Exp. 2) between Chinese characters and stimuli derived from Chinese characters with different orthographic properties. The fMRI response amplitude results suggest the existence of orthographic sensitivity in the VWFA. The results from multi-voxel pattern analysis indicate that spatial distribution of the responses across voxels in the occipitotemporal cortex contained discriminative information between the different types of character-related stimuli. These results together suggest that the orthographic rules are likely represented in a distributed neural network with the VWFA containing the most specific information regarding a stimulus' orthographic regularity.

Distributed Kalman filtering compared to Fourier domain preconditioned conjugate gradient for laser guide star tomography on extremely large telescopes.

PubMed

Gilles, Luc; Massioni, Paolo; Kulcsár, Caroline; Raynaud, Henri-François; Ellerbroek, Brent

2013-05-01

This paper discusses the performance and cost of two computationally efficient Fourier-based tomographic wavefront reconstruction algorithms for wide-field laser guide star (LGS) adaptive optics (AO). The first algorithm is the iterative Fourier domain preconditioned conjugate gradient (FDPCG) algorithm developed by Yang et al. [Appl. Opt.45, 5281 (2006)], combined with pseudo-open-loop control (POLC). FDPCG's computational cost is proportional to N log(N), where N denotes the dimensionality of the tomography problem. The second algorithm is the distributed Kalman filter (DKF) developed by Massioni et al. [J. Opt. Soc. Am. A28, 2298 (2011)], which is a noniterative spatially invariant controller. When implemented in the Fourier domain, DKF's cost is also proportional to N log(N). Both algorithms are capable of estimating spatial frequency components of the residual phase beyond the wavefront sensor (WFS) cutoff frequency thanks to regularization, thereby reducing WFS spatial aliasing at the expense of more computations. We present performance and cost analyses for the LGS multiconjugate AO system under design for the Thirty Meter Telescope, as well as DKF's sensitivity to uncertainties in wind profile prior information. We found that, provided the wind profile is known to better than 10% wind speed accuracy and 20 deg wind direction accuracy, DKF, despite its spatial invariance assumptions, delivers a significantly reduced wavefront error compared to the static FDPCG minimum variance estimator combined with POLC. Due to its nonsequential nature and high degree of parallelism, DKF is particularly well suited for real-time implementation on inexpensive off-the-shelf graphics processing units.

Improvements in GRACE Gravity Fields Using Regularization

NASA Astrophysics Data System (ADS)

Save, H.; Bettadpur, S.; Tapley, B. D.

2008-12-01

The unconstrained global gravity field models derived from GRACE are susceptible to systematic errors that show up as broad "stripes" aligned in a North-South direction on the global maps of mass flux. These errors are believed to be a consequence of both systematic and random errors in the data that are amplified by the nature of the gravity field inverse problem. These errors impede scientific exploitation of the GRACE data products, and limit the realizable spatial resolution of the GRACE global gravity fields in certain regions. We use regularization techniques to reduce these "stripe" errors in the gravity field products. The regularization criteria are designed such that there is no attenuation of the signal and that the solutions fit the observations as well as an unconstrained solution. We have used a computationally inexpensive method, normally referred to as "L-ribbon", to find the regularization parameter. This paper discusses the characteristics and statistics of a 5-year time-series of regularized gravity field solutions. The solutions show markedly reduced stripes, are of uniformly good quality over time, and leave little or no systematic observation residuals, which is a frequent consequence of signal suppression from regularization. Up to degree 14, the signal in regularized solution shows correlation greater than 0.8 with the un-regularized CSR Release-04 solutions. Signals from large-amplitude and small-spatial extent events - such as the Great Sumatra Andaman Earthquake of 2004 - are visible in the global solutions without using special post-facto error reduction techniques employed previously in the literature. Hydrological signals as small as 5 cm water-layer equivalent in the small river basins, like Indus and Nile for example, are clearly evident, in contrast to noisy estimates from RL04. The residual variability over the oceans relative to a seasonal fit is small except at higher latitudes, and is evident without the need for de-striping or spatial smoothing.

A Novel Richardson-Lucy Model with Dictionary Basis and Spatial Regularization for Isolating Isotropic Signals.

PubMed

Xu, Tiantian; Feng, Yuanjing; Wu, Ye; Zeng, Qingrun; Zhang, Jun; He, Jianzhong; Zhuge, Qichuan

2017-01-01

Diffusion-weighted magnetic resonance imaging is a non-invasive imaging method that has been increasingly used in neuroscience imaging over the last decade. Partial volume effects (PVEs) exist in sampling signal for many physical and actual reasons, which lead to inaccurate fiber imaging. We overcome the influence of PVEs by separating isotropic signal from diffusion-weighted signal, which can provide more accurate estimation of fiber orientations. In this work, we use a novel response function (RF) and the correspondent fiber orientation distribution function (fODF) to construct different signal models, in which case the fODF is represented using dictionary basis function. We then put forward a new index Piso, which is a part of fODF to quantify white and gray matter. The classic Richardson-Lucy (RL) model is usually used in the field of digital image processing to solve the problem of spherical deconvolution caused by highly ill-posed least-squares algorithm. In this case, we propose an innovative model integrating RL model with spatial regularization to settle the suggested double-models, which improve noise resistance and accuracy of imaging. Experimental results of simulated and real data show that the proposal method, which we call iRL, can robustly reconstruct a more accurate fODF and the quantitative index Piso performs better than fractional anisotropy and general fractional anisotropy.

A Novel Richardson-Lucy Model with Dictionary Basis and Spatial Regularization for Isolating Isotropic Signals

PubMed Central

Feng, Yuanjing; Wu, Ye; Zeng, Qingrun; Zhang, Jun; He, Jianzhong; Zhuge, Qichuan

2017-01-01

Diffusion-weighted magnetic resonance imaging is a non-invasive imaging method that has been increasingly used in neuroscience imaging over the last decade. Partial volume effects (PVEs) exist in sampling signal for many physical and actual reasons, which lead to inaccurate fiber imaging. We overcome the influence of PVEs by separating isotropic signal from diffusion-weighted signal, which can provide more accurate estimation of fiber orientations. In this work, we use a novel response function (RF) and the correspondent fiber orientation distribution function (fODF) to construct different signal models, in which case the fODF is represented using dictionary basis function. We then put forward a new index Piso, which is a part of fODF to quantify white and gray matter. The classic Richardson-Lucy (RL) model is usually used in the field of digital image processing to solve the problem of spherical deconvolution caused by highly ill-posed least-squares algorithm. In this case, we propose an innovative model integrating RL model with spatial regularization to settle the suggested double-models, which improve noise resistance and accuracy of imaging. Experimental results of simulated and real data show that the proposal method, which we call iRL, can robustly reconstruct a more accurate fODF and the quantitative index Piso performs better than fractional anisotropy and general fractional anisotropy. PMID:28081561

Temporal sparsity exploiting nonlocal regularization for 4D computed tomography reconstruction

PubMed Central

Kazantsev, Daniil; Guo, Enyu; Kaestner, Anders; Lionheart, William R. B.; Bent, Julian; Withers, Philip J.; Lee, Peter D.

2016-01-01

X-ray imaging applications in medical and material sciences are frequently limited by the number of tomographic projections collected. The inversion of the limited projection data is an ill-posed problem and needs regularization. Traditional spatial regularization is not well adapted to the dynamic nature of time-lapse tomography since it discards the redundancy of the temporal information. In this paper, we propose a novel iterative reconstruction algorithm with a nonlocal regularization term to account for time-evolving datasets. The aim of the proposed nonlocal penalty is to collect the maximum relevant information in the spatial and temporal domains. With the proposed sparsity seeking approach in the temporal space, the computational complexity of the classical nonlocal regularizer is substantially reduced (at least by one order of magnitude). The presented reconstruction method can be directly applied to various big data 4D (x, y, z+time) tomographic experiments in many fields. We apply the proposed technique to modelled data and to real dynamic X-ray microtomography (XMT) data of high resolution. Compared to the classical spatio-temporal nonlocal regularization approach, the proposed method delivers reconstructed images of improved resolution and higher contrast while remaining significantly less computationally demanding. PMID:27002902

Ammonia concentration distribution measurements in the exhaust of a heavy duty diesel engine based on limited data absorption tomography.

PubMed

Stritzke, Felix; van der Kley, Sani; Feiling, Alexander; Dreizler, Andreas; Wagner, Steven

2017-04-03

A multichannel tunable diode laser absorption spectrometer is used to measure absolute ammonia concentrations and their distributions in exhaust gas applications with intense CO₂ and H₂O background. Designed for in situ diagnostics in SCR after treatment systems with temperatures up to 800 K, the system employs a fiber coupled near-infrared distributed feedback diode laser. With the laser split into eight coplanar beams crossing the exhaust pipe, the sensor provides eight concentration measurements simultaneously. Three ammonia ro-vibrational transitions coinciding near 2200.5 nm with rather weak temperature dependency and negligible CO₂/H₂O interference were probed during the measurements. The line-of-sight averaged channel concentrations are transformed into 2-D ammonia distributions using limited data IR species tomography based on Tikhonov regularization. This spectrometer was successfully applied in the exhaust system of a 340 kW heavy duty diesel engine operated without oxidation catalyst or particulate filter. In this harsh environment the multi-channel sensor achieved single path ammonia detection limits of 25 to 80 ppm_V with a temporal resolution of 1 Hz whereas, while operated as a single-channel sensor, these characteristics improved to 10 ppm_V and 100 Hz. Spatial averaging of the reconstructed 2-D ammonia distributions shows good agreement to cross-sectional extractive measurements. In contrast to extractive methods more information about spatial inhomogeneities and transient operating conditions can be derived from the new spectrometer.

Regularized Filters for L1-Norm-Based Common Spatial Patterns.

PubMed

Wang, Haixian; Li, Xiaomeng

2016-02-01

The l1 -norm-based common spatial patterns (CSP-L1) approach is a recently developed technique for optimizing spatial filters in the field of electroencephalogram (EEG)-based brain computer interfaces. The l1 -norm-based expression of dispersion in CSP-L1 alleviates the negative impact of outliers. In this paper, we further improve the robustness of CSP-L1 by taking into account noise which does not necessarily have as large a deviation as with outliers. The noise modelling is formulated by using the waveform length of the EEG time course. With the noise modelling, we then regularize the objective function of CSP-L1, in which the l1-norm is used in two folds: one is the dispersion and the other is the waveform length. An iterative algorithm is designed to resolve the optimization problem of the regularized objective function. A toy illustration and the experiments of classification on real EEG data sets show the effectiveness of the proposed method.

GIS-based evaluation and spatial distribution characteristics of land degradation in Bijiang watershed.

PubMed

Zhao, Xiaoqing; Dai, Jinhua; Wang, Jianping

2013-01-01

Land degradation is one of the significant issues the human beings are confronted with, which has become a bottleneck of restricting the sustainable development of the regional society and economy. In order to ascertain the root causes contributed to the land degradation and characteristics of land degradation, Bijiang watershed, the most important Lead-Zinc mine area of Lanping county of Yunnan Province, was selected as the study area. One evaluation index system for land degradation that consists of 5 single factors(water-soil erosion intensity, geological disaster risk, cultivation intensity of arable land, pollution of heavy metals in soil and biodiversity deterioration) was established and 13 indicators were chosen, and the entropy method was adopted to assign weights to each single factor. By using the tools of Geographic Information System (GIS), the land degradation degree was evaluated and one spatial distribution map for land degradation was accomplished. In this study, the land of the whole watershed was divided into 4 types, including extremely-severe degradation area, severely-degraded area, moderately-degraded area and slightly-degraded area, and some solutions for ecological restoration and rehabilitation were also put forward in this study. The study results indicated that: (1) Water-soil erosion intension and pollution of heavy metals in soil have made greater contribution to the comprehensive land degradation in Bijiang watershed; (2) There is an apparent difference regarding land degradation degree in Bijiang watershed. The moderately-degraded area accounts for the most part in the region, which covers 79.66% of the whole watershed. The severely-degraded area accounts for 15.98% and the slightly-degraded regions and extremely severe degradation area accounts for 1.08% and 3.28% respectively; (3) There is an evident regularity of spatial distribution in land degradation in Bijiang watershed. The moderately-degraded areas mainly distribute in the most part of the mid-stream and down-stream, the slightly-degraded areas distribute in the mid-stream, the severely-degraded areas distribute in the upstream and south-west part of down-stream, the extremely severe degradation areas distribute in the east and middle part of the upstream; (4)From the administrative division viewpoint, the slightly-degraded areas primarily distribute in Jiancao township, Baishi town and Nuodeng town. The moderately-degraded areas distribute in Changxin township, Baofeng township, Jiancao township, Baishi town and Nuodeng town. The severely-degraded areas distribute in Jinding town, Baofeng township and Lajing town. The extremely severe degradation areas distribute in Jinding town. By connecting the spatial distribution mode for land degradation with other natural, economical elements, we drew a conclusion that the pollution in heavy metals in soil, serious water erosion and geological disasters are the main causes of the land degradation in Bijiang watershed.

GIS-based environmental analysis of fox and canine lungworm distribution: an epidemiological study of Angiostrongylus vasorum and Crenosoma vulpis in red foxes from Slovakia.

PubMed

Čabanová, Viktória; Miterpáková, Martina; Druga, Michal; Hurníková, Zuzana; Valentová, Daniela

2018-02-01

Over a period of intervening years, the distribution of two canine cardiopulmonary metastrongylid nematodes, Angiostrongylus vasorum and Crenosoma vulpis, has been recognised in Central Europe. Here, we report the first epidemiological research conducted in red foxes from Slovakia and the potential influence of selected environmental variables on the parasites' occurrence, quantified by logistic regression. The environmental models revealed that distribution of C. vulpis is not significantly influenced by any environmental variables, and the parasite is present in the whole area under study. Models for A. vasorum revealed some weak influence of environmental variables, as it tends to occur in drier areas with lower proportion of forest. Moreover, A. vasorum shows a typical spatial clustering and occurs in endemic foci identified mainly in the eastern part of Slovakia. A cluster of A. vasorum infection foci was also found in the north-eastern region, where the average winter air temperature regularly falls below - 10 °C.

Spatial variability of soil carbon, pH, available phosphorous and potassium in organic farm located in Mediterranean Croatia

NASA Astrophysics Data System (ADS)

Bogunović, Igor; Pereira, Paulo; Šeput, Miranda

2016-04-01

Soil organic carbon (SOC), pH, available phosphorus (P), and potassium (K) are some of the most important factors to soil fertility. These soil parameters are highly variable in space and time, with implications to crop production. The aim of this work is study the spatial variability of SOC, pH, P and K in an organic farm located in river Rasa valley (Croatia). A regular grid (100 x 100 m) was designed and 182 samples were collected on Silty Clay Loam soil. P, K and SOC showed moderate heterogeneity with coefficient of variation (CV) of 21.6%, 32.8% and 51.9%, respectively. Soil pH record low spatial variability with CV of 1.5%. Soil pH, P and SOC did not follow normal distribution. Only after a Box-Cox transformation, data respected the normality requirements. Directional exponential models were the best fitted and used to describe spatial autocorrelation. Soil pH, P and SOC showed strong spatial dependence with nugget to sill ratio with 13.78%, 0.00% and 20.29%, respectively. Only K recorded moderate spatial dependence. Semivariogram ranges indicate that future sampling interval could be 150 - 200 m in order to reduce sampling costs. Fourteen different interpolation models for mapping soil properties were tested. The method with lowest Root Mean Square Error was the most appropriated to map the variable. The results showed that radial basis function models (Spline with Tension and Completely Regularized Spline) for P and K were the best predictors, while Thin Plate Spline and inverse distance weighting models were the least accurate. The best interpolator for pH and SOC was the local polynomial with the power of 1, while the least accurate were Thin Plate Spline. According to soil nutrient maps investigated area record very rich supply with K while P supply was insufficient on largest part of area. Soil pH maps showed mostly neutral reaction while individual parts of alkaline soil indicate the possibility of penetration of seawater and salt accumulation in the soil profile. Future research should focus on spatial patterns on soil pH, electrical conductivity and sodium adsorption ratio. Keywords: geostatistics, semivariogram, interpolation models, soil chemical properties

Regularization of the Perturbed Spatial Restricted Three-Body Problem by L-Transformations

NASA Astrophysics Data System (ADS)

Poleshchikov, S. M.

2018-03-01

Equations of motion for the perturbed circular restricted three-body problem have been regularized in canonical variables in a moving coordinate system. Two different L-matrices of the fourth order are used in the regularization. Conditions for generalized symplecticity of the constructed transform have been checked. In the unperturbed case, the regular equations have a polynomial structure. The regular equations have been numerically integrated using the Runge-Kutta-Fehlberg method. The results of numerical experiments are given for the Earth-Moon system parameters taking into account the perturbation of the Sun for different L-matrices.

Image processing techniques revealing the relationship between the field-measured ambient gamma dose equivalent rate and geological conditions at a granitic area, Velence Mountains, Hungary

NASA Astrophysics Data System (ADS)

Beltran Torres, Silvana; Petrik, Attila; Zsuzsanna Szabó, Katalin; Jordan, Gyozo; Szabó, Csaba

2017-04-01

In order to estimate the annual dose that the public receive from natural radioactivity, the identification of the potential risk areas is required which, in turn, necessitates understanding the relationship between the spatial distribution of natural radioactivity and the geogenic risk factors (e.g., rock types, dykes, faults, soil conditions, etc.). A detailed spatial analysis of ambient gamma dose equivalent rate was performed in the western side of Velence Mountains, the largest outcropped granitic area in Hungary. In order to assess the role of local geology in the spatial distribution of ambient gamma dose rates, field measurements were carried out at ground level at 300 sites along a 250 m x 250 m regular grid in a total surface of 14.7 km2. Digital image processing methods were applied to identify anomalies, heterogeneities and spatial patterns in the measured gamma dose rates, including local maxima and minima determination, digital cross sections, gradient magnitude and gradient direction, second derivative profile curvature, local variability, lineament density, 2D autocorrelation and directional variogram analyses. Statistical inference showed that different gamma dose rate levels are associated with the rock types (i.e., Carboniferous granite, Pleistocene colluvial, proluvial, deluvial sediments and talus, and Pannonian sand and pebble), with the highest level on the Carboniferous granite including outlying values. Moreover, digital image processing revealed that linear gamma dose rate spatial features are parallel to the SW-NE dyke system and possibly to the NW-SE main fractures. The results of this study underline the importance of understanding the role of geogenic risk factors influencing the ambient gamma dose rate received by public. The study also demonstrates the power of the image processing techniques for the identification of spatial pattern in field-measured geogenic radiation.

Fast Spatial Resolution Analysis of Quadratic Penalized Least-Squares Image Reconstruction With Separate Real and Imaginary Roughness Penalty: Application to fMRI.

PubMed

Olafsson, Valur T; Noll, Douglas C; Fessler, Jeffrey A

2018-02-01

Penalized least-squares iterative image reconstruction algorithms used for spatial resolution-limited imaging, such as functional magnetic resonance imaging (fMRI), commonly use a quadratic roughness penalty to regularize the reconstructed images. When used for complex-valued images, the conventional roughness penalty regularizes the real and imaginary parts equally. However, these imaging methods sometimes benefit from separate penalties for each part. The spatial smoothness from the roughness penalty on the reconstructed image is dictated by the regularization parameter(s). One method to set the parameter to a desired smoothness level is to evaluate the full width at half maximum of the reconstruction method's local impulse response. Previous work has shown that when using the conventional quadratic roughness penalty, one can approximate the local impulse response using an FFT-based calculation. However, that acceleration method cannot be applied directly for separate real and imaginary regularization. This paper proposes a fast and stable calculation for this case that also uses FFT-based calculations to approximate the local impulse responses of the real and imaginary parts. This approach is demonstrated with a quadratic image reconstruction of fMRI data that uses separate roughness penalties for the real and imaginary parts.

Unsupervised seismic facies analysis with spatial constraints using regularized fuzzy c-means

NASA Astrophysics Data System (ADS)

Song, Chengyun; Liu, Zhining; Cai, Hanpeng; Wang, Yaojun; Li, Xingming; Hu, Guangmin

2017-12-01

Seismic facies analysis techniques combine classification algorithms and seismic attributes to generate a map that describes main reservoir heterogeneities. However, most of the current classification algorithms only view the seismic attributes as isolated data regardless of their spatial locations, and the resulting map is generally sensitive to noise. In this paper, a regularized fuzzy c-means (RegFCM) algorithm is used for unsupervised seismic facies analysis. Due to the regularized term of the RegFCM algorithm, the data whose adjacent locations belong to same classification will play a more important role in the iterative process than other data. Therefore, this method can reduce the effect of seismic data noise presented in discontinuous regions. The synthetic data with different signal/noise values are used to demonstrate the noise tolerance ability of the RegFCM algorithm. Meanwhile, the fuzzy factor, the neighbour window size and the regularized weight are tested using various values, to provide a reference of how to set these parameters. The new approach is also applied to a real seismic data set from the F3 block of the Netherlands. The results show improved spatial continuity, with clear facies boundaries and channel morphology, which reveals that the method is an effective seismic facies analysis tool.

Heat exposure in cities: combining the dynamics of temperature and population

NASA Astrophysics Data System (ADS)

Hu, L.; Wilhelmi, O.; Uejio, C. K.

2017-12-01

Assessment of human exposure to extreme heat requires the distributions of temperature and population. However, both variables are dynamic, thus presenting many challenges in capturing temperature and population patterns spatially and over time in an urban context. This study aims to improve the understanding of spatiotemporal patterns of urban population exposure to heat, taking Chicago, USA as an example. We estimate the hourly, geographically variable, population distribution considering commute of workers and students in a regular weekday and analyze the diurnal air temperature patterns during different meteorological conditions from satellite observations. The results show a relatively larger temperature increase in less urbanized areas during extreme heat events (EHEs), resulting in a spatially homogeneous temperature distribution over Chicago Metropolitan area. A lake cooling effect is weaker during EHEs. Population dynamics due to daily commute determine higher population density in more urbanized areas during daytime. The city-wide analysis reveals that the exposure is more sensitive to the nighttime temperature increases, and EHEs enhance this sensitivity. The high exposure hotspots are identified at the northwest Chicago, Cicero and Oak Park areas, where the influence from Lake Michigan is weakened, while the spatial extent of high outdoor exposure areas varies diurnally. This study's findings have potential to better inform general heat mitigation strategies during hot summer months and facilitate emergency response during EHEs. Availability of remotely-sensed temperature observations as well as the workers and students commute-adjusted population data allows for the adoption of this study's methodology in other major metropolitan areas. A better understanding of space-time patterns of urban population's exposure to heat will further enable local decision makers to mitigate extreme heat health risks and develop more targeted heat preparedness and response strategies.

Discovering Structural Regularity in 3D Geometry

PubMed Central

Pauly, Mark; Mitra, Niloy J.; Wallner, Johannes; Pottmann, Helmut; Guibas, Leonidas J.

2010-01-01

We introduce a computational framework for discovering regular or repeated geometric structures in 3D shapes. We describe and classify possible regular structures and present an effective algorithm for detecting such repeated geometric patterns in point- or mesh-based models. Our method assumes no prior knowledge of the geometry or spatial location of the individual elements that define the pattern. Structure discovery is made possible by a careful analysis of pairwise similarity transformations that reveals prominent lattice structures in a suitable model of transformation space. We introduce an optimization method for detecting such uniform grids specifically designed to deal with outliers and missing elements. This yields a robust algorithm that successfully discovers complex regular structures amidst clutter, noise, and missing geometry. The accuracy of the extracted generating transformations is further improved using a novel simultaneous registration method in the spatial domain. We demonstrate the effectiveness of our algorithm on a variety of examples and show applications to compression, model repair, and geometry synthesis. PMID:21170292

Employing temporal self-similarity across the entire time domain in computed tomography reconstruction

PubMed Central

Kazantsev, D.; Van Eyndhoven, G.; Lionheart, W. R. B.; Withers, P. J.; Dobson, K. J.; McDonald, S. A.; Atwood, R.; Lee, P. D.

2015-01-01

There are many cases where one needs to limit the X-ray dose, or the number of projections, or both, for high frame rate (fast) imaging. Normally, it improves temporal resolution but reduces the spatial resolution of the reconstructed data. Fortunately, the redundancy of information in the temporal domain can be employed to improve spatial resolution. In this paper, we propose a novel regularizer for iterative reconstruction of time-lapse computed tomography. The non-local penalty term is driven by the available prior information and employs all available temporal data to improve the spatial resolution of each individual time frame. A high-resolution prior image from the same or a different imaging modality is used to enhance edges which remain stationary throughout the acquisition time while dynamic features tend to be regularized spatially. Effective computational performance together with robust improvement in spatial and temporal resolution makes the proposed method a competitive tool to state-of-the-art techniques. PMID:25939621

[Spatial and temporal dynamics of the weed community in the Zoysia matrella lawn].

PubMed

Liu, Jia-Qi; Li, You-Han; Zeng, Ying; Xie, Xin-Ming

2014-02-01

The heterogeneity of species composition is one of the main attributes in weed community dynamics. Based on species frequency and power law, this paper studied the variations of weed community species composition and spatial heterogeneity in a Zoysia matrella lawn in Guangzhou at different time. The results showed that there were 43 weed species belonging to 19 families in the Z. matrella lawn from 2007 to 2009, in which Gramineae, Compositae, Cyperaceae and Rubiaceae had a comparative advantage. Perennial weeds accounted for the largest proportion of weeds and increased gradually in the three years. Weed communities distributed in higher heterogeneity than in a random model. Dominant weeds varied with season and displayed regularity in the order of 'dicotyledon-monocotyledon-dicotyledon weeds' and 'perennial-annual-perennial weeds'. The spatial heterogeneity of weed community in Z. matrella lawn was higher in summer than in winter. The diversity and evenness of weed community were higher in summer and autumn than in winter and spring. The number of weed species with high heterogeneity in summer was higher than in the other seasons. The spatial heterogeneity and diversity of weed community had no significant change in the three years, while the evenness of weed community had the tendency to decline gradually.

Contextual cueing in 3D visual search depends on representations in planar-, not depth-defined space.

PubMed

Zang, Xuelian; Shi, Zhuanghua; Müller, Hermann J; Conci, Markus

2017-05-01

Learning of spatial inter-item associations can speed up visual search in everyday life, an effect referred to as contextual cueing (Chun & Jiang, 1998). Whereas previous studies investigated contextual cueing primarily using 2D layouts, the current study examined how 3D depth influences contextual learning in visual search. In two experiments, the search items were presented evenly distributed across front and back planes in an initial training session. In the subsequent test session, the search items were either swapped between the front and back planes (Experiment 1) or between the left and right halves (Experiment 2) of the displays. The results showed that repeated spatial contexts were learned efficiently under 3D viewing conditions, facilitating search in the training sessions, in both experiments. Importantly, contextual cueing remained robust and virtually unaffected following the swap of depth planes in Experiment 1, but it was substantially reduced (to nonsignificant levels) following the left-right side swap in Experiment 2. This result pattern indicates that spatial, but not depth, inter-item variations limit effective contextual guidance. Restated, contextual cueing (even under 3D viewing conditions) is primarily based on 2D inter-item associations, while depth-defined spatial regularities are probably not encoded during contextual learning. Hence, changing the depth relations does not impact the cueing effect.

Membrane related dynamics and the formation of actin in cells growing on micro-topographies: a spatial computational model.

PubMed

Bittig, Arne T; Matschegewski, Claudia; Nebe, J Barbara; Stählke, Susanne; Uhrmacher, Adelinde M

2014-09-09

Intra-cellular processes of cells at the interface to an implant surface are influenced significantly by their extra-cellular surrounding. Specifically, when growing osteoblasts on titanium surfaces with regular micro-ranged geometry, filaments are shorter, less aligned and they concentrate at the top of the geometric structures. Changes to the cytoskeleton network, i. e., its localization, alignment, orientation, and lengths of the filaments, as well as the overall concentration and distribution of key-actors are induced. For example, integrin is distributed homogeneously, whereas integrin in activated state and vinculin, both components of focal adhesions, have been found clustered on the micro-ranged geometries. Also, the concentration of Rho, an intracellular signaling protein related to focal adhesion regulation, was significantly lower. To explore whether regulations associated with the focal adhesion complex can be responsible for the changed actin filament patterns, a spatial computational model has been developed using ML-Space, a rule-based model description language, and its associated Brownian-motion-based simulator. The focus has been on the deactivation of cofilin in the vicinity of the focal adhesion complex. The results underline the importance of sensing mechanisms to support a clustering of actin filament nucleations on the micro-ranged geometries, and of intracellular diffusion processes, which lead to spatially heterogeneous distributions of active (dephosphorylated) cofilin, which in turn influences the organization of the actin network. We find, for example, that the spatial heterogeneity of key molecular actors can explain the difference in filament lengths in cells on different micro-geometries partly, but to explain the full extent, further model assumptions need to be added and experimentally validated. In particular, our findings and hypothesis referring to the role, distribution, and amount of active cofilin have still to be verified in wet-lab experiments. Letting cells grow on surface structures is a possibility to shed new light on the intricate mechanisms that relate membrane and actin related dynamics in the cell. Our results demonstrate the need for declarative expressive spatial modeling approaches that allow probing different hypotheses, and the central role of the focal adhesion complex not only for nucleating actin filaments, but also for regulating possible severing agents locally.

Membrane related dynamics and the formation of actin in cells growing on micro-topographies: a spatial computational model

PubMed Central

2014-01-01

Background Intra-cellular processes of cells at the interface to an implant surface are influenced significantly by their extra-cellular surrounding. Specifically, when growing osteoblasts on titanium surfaces with regular micro-ranged geometry, filaments are shorter, less aligned and they concentrate at the top of the geometric structures. Changes to the cytoskeleton network, i. e., its localization, alignment, orientation, and lengths of the filaments, as well as the overall concentration and distribution of key-actors are induced. For example, integrin is distributed homogeneously, whereas integrin in activated state and vinculin, both components of focal adhesions, have been found clustered on the micro-ranged geometries. Also, the concentration of Rho, an intracellular signaling protein related to focal adhesion regulation, was significantly lower. Results To explore whether regulations associated with the focal adhesion complex can be responsible for the changed actin filament patterns, a spatial computational model has been developed using ML-Space, a rule-based model description language, and its associated Brownian-motion-based simulator. The focus has been on the deactivation of cofilin in the vicinity of the focal adhesion complex. The results underline the importance of sensing mechanisms to support a clustering of actin filament nucleations on the micro-ranged geometries, and of intracellular diffusion processes, which lead to spatially heterogeneous distributions of active (dephosphorylated) cofilin, which in turn influences the organization of the actin network. We find, for example, that the spatial heterogeneity of key molecular actors can explain the difference in filament lengths in cells on different micro-geometries partly, but to explain the full extent, further model assumptions need to be added and experimentally validated. In particular, our findings and hypothesis referring to the role, distribution, and amount of active cofilin have still to be verified in wet-lab experiments. Conclusion Letting cells grow on surface structures is a possibility to shed new light on the intricate mechanisms that relate membrane and actin related dynamics in the cell. Our results demonstrate the need for declarative expressive spatial modeling approaches that allow probing different hypotheses, and the central role of the focal adhesion complex not only for nucleating actin filaments, but also for regulating possible severing agents locally. PMID:25200251

Increase of economy of torque flow pump with high specific speed

NASA Astrophysics Data System (ADS)

Gusak, A. G.; Krishtop, I. V.; German, V. F.; Baga, V. N.

2017-08-01

Torque flow pumps are widely spread types of energy machines, which are used in majority of modern branches of industry for pumping of dirty media. The main task of researchers of torque flow pumps is increase of such pumps effectiveness for higher feed. Hydraulic losses for torque flow pumps are caused by working process of such pumps and are inevitable. Decrease of losses can be obtained by means of optimization of hydraulic flow part geometry. Modern approach to design of pump outlet introduces new constructive solutions which can increase economy of torque flow pumps. The aim of this research is increase of economy of torque flow pumps by means of application of spatial outlet and investigation of its geometry on pump characteristics. Analytical and numerical methods of liquid flow research for hydraulic flow part of torque flow pump were used in this paper. Moreover, influence of hydraulic flow part geometry of different designs of “Turo” type torque flow pumps outlets on pump characteristics was investigated. Numerical research enabled to study process of energy transfer of torque flow pump and evaluate influence of geometrical dimensions of spatial spiral outlet on its characteristics. Besides numerical research confirmed introduced regularity of peripheral velocity distribution in outlet. Velocity moment distribution in outlet was obtained during implementation of numerical research. Implemented bench tests of torque flow pump prototypes enabled to obtain real characteristics of pump and confirm effectiveness of spatial geometry of outlet application for such pump.

Guidance of Spatial Attention by Incidental Learning and Endogenous Cuing

ERIC Educational Resources Information Center

Jiang, Yuhong V.; Swallow, Khena M.; Rosenbaum, Gail M.

2013-01-01

Our visual system is highly sensitive to regularities in the environment. Locations that were important in one's previous experience are often prioritized during search, even though observers may not be aware of the learning. In this study we characterized the guidance of spatial attention by incidental learning of a target's spatial probability,…

Temporal clustering of tropical cyclones on the Great Barrier Reef and its ecological importance

NASA Astrophysics Data System (ADS)

Wolff, Nicholas H.; Wong, Aaron; Vitolo, Renato; Stolberg, Kristin; Anthony, Kenneth R. N.; Mumby, Peter J.

2016-06-01

Tropical cyclones have been a major cause of reef coral decline during recent decades, including on the Great Barrier Reef (GBR). While cyclones are a natural element of the disturbance regime of coral reefs, the role of temporal clustering has previously been overlooked. Here, we examine the consequences of different types of cyclone temporal distributions (clustered, stochastic or regular) on reef ecosystems. We subdivided the GBR into 14 adjoining regions, each spanning roughly 300 km, and quantified both the rate and clustering of cyclones using dispersion statistics. To interpret the consequences of such cyclone variability for coral reef health, we used a model of observed coral population dynamics. Results showed that clustering occurs on the margins of the cyclone belt, being strongest in the southern reefs and the far northern GBR, which also has the lowest cyclone rate. In the central GBR, where rates were greatest, cyclones had a relatively regular temporal pattern. Modelled dynamics of the dominant coral genus, Acropora, suggest that the long-term average cover might be more than 13 % greater (in absolute cover units) under a clustered cyclone regime compared to stochastic or regular regimes. Thus, not only does cyclone clustering vary significantly along the GBR but such clustering is predicted to have a marked, and management-relevant, impact on the status of coral populations. Additionally, we use our regional clustering and rate results to sample from a library of over 7000 synthetic cyclone tracks for the GBR. This allowed us to provide robust reef-scale maps of annual cyclone frequency and cyclone impacts on Acropora. We conclude that assessments of coral reef vulnerability need to account for both spatial and temporal cyclone distributions.

Assessing the resolution-dependent utility of tomograms for geostatistics

USGS Publications Warehouse

Day-Lewis, F. D.; Lane, J.W.

2004-01-01

Geophysical tomograms are used increasingly as auxiliary data for geostatistical modeling of aquifer and reservoir properties. The correlation between tomographic estimates and hydrogeologic properties is commonly based on laboratory measurements, co-located measurements at boreholes, or petrophysical models. The inferred correlation is assumed uniform throughout the interwell region; however, tomographic resolution varies spatially due to acquisition geometry, regularization, data error, and the physics underlying the geophysical measurements. Blurring and inversion artifacts are expected in regions traversed by few or only low-angle raypaths. In the context of radar traveltime tomography, we derive analytical models for (1) the variance of tomographic estimates, (2) the spatially variable correlation with a hydrologic parameter of interest, and (3) the spatial covariance of tomographic estimates. Synthetic examples demonstrate that tomograms of qualitative value may have limited utility for geostatistics; moreover, the imprint of regularization may preclude inference of meaningful spatial statistics from tomograms.

Modeling α- and β-diversity in a tropical forest from remotely sensed and spatial data

NASA Astrophysics Data System (ADS)

Hernández-Stefanoni, J. Luis; Gallardo-Cruz, J. Alberto; Meave, Jorge A.; Rocchini, Duccio; Bello-Pineda, Javier; López-Martínez, J. Omar

2012-10-01

Comprehensive information on species distribution and species composition patterns of plant communities is required for effective conservation and management of biodiversity. Remote sensing offers an inexpensive means of attaining complete spatial coverage for large areas, at regular time intervals, and can therefore be extremely useful for estimating both species richness and spatial variation of species composition (α- and β-diversity). An essential step to map such attributes is to identify and understand their main drivers. We used remotely sensed data as a surrogate of plant productivity and habitat structure variables for explaining α- and β-diversity, and evaluated the relative roles of productivity-habitat structure and spatial variables in explaining observed patterns of α- and β-diversity by using a Principal Coordinates of Neighbor Matrices analysis. We also examined the relationship between remotely sensed and field data, in order to map α- and β-diversity at the landscape-level in the Yucatan Peninsula, using a regression kriging procedure. These two procedures integrate the relationship of species richness and spatial species turnover both with remotely sensed data and spatial structure. The empirical models so obtained can be used to predict species richness and variation in species composition, and they can be regarded as valuable tools not only for identifying areas with high local species richness (α-diversity), but also areas with high species turnover (β-diversity). Ultimately, information obtained in this way can help maximize the number of species preserved in a landscape.

Three-dimensional Fourier transform evaluation of sequences of spatially and temporally modulated speckle interferograms.

PubMed

Trillo, C; Doval, A F; López-Vázquez, J C

2010-07-05

Phase evaluation methods based on the 2D spatial Fourier transform of a speckle interferogram with spatial carrier usually assume that the Fourier spectrum of the interferogram has a trimodal distribution, i. e. that the side lobes corresponding to the interferential terms do not overlap the other two spectral terms, which are related to the intensity of the object and reference beams, respectively. Otherwise, part of the spectrum of the object beam is inside the inverse-transform window of the selected interference lobe and induces an error in the resultant phase map. We present a technique for the acquisition and processing of speckle interferogram sequences that separates the interference lobes from the other spectral terms when the aforementioned assumption does not apply and regardless of the temporal bandwidth of the phase signal. It requires the recording of a sequence of interferograms with spatial and temporal carriers, and their processing with a 3D Fourier transform. In the resultant 3D spectrum, the spatial and temporal carriers separate the conjugate interferential terms from each other and from the term related to the object beam. Experimental corroboration is provided through the measurement of the amplitude of surface acoustic waves in plates with a double-pulsed TV holography setup. The results obtained with the proposed method are compared to those obtained with the processing of individual interferograms with the regular spatial-carrier 2D Fourier transform method.

Capability of ERTS-1 imagery to investigate geological and structural features in a sedimentary basin (Bassin Parisien, France)

NASA Technical Reports Server (NTRS)

Cavelier, C.; Scanvic, J. Y.; Weecksteen, G.; Zizerman, A.

1973-01-01

A preliminary study of the MSS imagery of a sedimentary basin whose structure is regular is reported. Crops and natural vegetation are distributed all over the site located under temperate climate. Ground data available concern plant species geology and tectonic and are correlated with results from ERTS 1 imagery. This comparison shows a good correlation. The main geological units are detected or enhanced by way of agricultural land use and/or natural vegetation. Alluvial deposits are outlined by vegetation grass land and poplar trees. Some spatial relationship of geostructures, suspected until now, are identified or extended in associating results from different spectral bands.

Optimal Tikhonov regularization for DEER spectroscopy

NASA Astrophysics Data System (ADS)

Edwards, Thomas H.; Stoll, Stefan

2018-03-01

Tikhonov regularization is the most commonly used method for extracting distance distributions from experimental double electron-electron resonance (DEER) spectroscopy data. This method requires the selection of a regularization parameter, α , and a regularization operator, L. We analyze the performance of a large set of α selection methods and several regularization operators, using a test set of over half a million synthetic noisy DEER traces. These are generated from distance distributions obtained from in silico double labeling of a protein crystal structure of T4 lysozyme with the spin label MTSSL. We compare the methods and operators based on their ability to recover the model distance distributions from the noisy time traces. The results indicate that several α selection methods perform quite well, among them the Akaike information criterion and the generalized cross validation method with either the first- or second-derivative operator. They perform significantly better than currently utilized L-curve methods.

Image deblurring based on nonlocal regularization with a non-convex sparsity constraint

NASA Astrophysics Data System (ADS)

Zhu, Simiao; Su, Zhenming; Li, Lian; Yang, Yi

2018-04-01

In recent years, nonlocal regularization methods for image restoration (IR) have drawn more and more attention due to the promising results obtained when compared to the traditional local regularization methods. Despite the success of this technique, in order to obtain computational efficiency, a convex regularizing functional is exploited in most existing methods, which is equivalent to imposing a convex prior on the nonlocal difference operator output. However, our conducted experiment illustrates that the empirical distribution of the output of the nonlocal difference operator especially in the seminal work of Kheradmand et al. should be characterized with an extremely heavy-tailed distribution rather than a convex distribution. Therefore, in this paper, we propose a nonlocal regularization-based method with a non-convex sparsity constraint for image deblurring. Finally, an effective algorithm is developed to solve the corresponding non-convex optimization problem. The experimental results demonstrate the effectiveness of the proposed method.

An ecological mechanism to create regular patterns of surface dissolution in a low-relief carbonate landscape

NASA Astrophysics Data System (ADS)

Cohen, M. J.; Martin, J. B.; Mclaughlin, D. L.; Osborne, T.; Murray, A.; Watts, A. C.; Watts, D.; Heffernan, J. B.

2012-12-01

Development of karst landscapes is controlled by focused delivery of water undersaturated with respect to the soluble rock minerals. As that water comes to equilibrium with the rock, secondary porosity is incrementally reinforced creating a positive feedback that acts to augment the drainage network and subsequent water delivery. In most self-organizing systems, spatial positive feedbacks create features (in landscapes: patches; in karst aquifers: conduits) whose size-frequency relationship follows a power function, indicating a higher probability of large features than would occur with a random or Gaussian genesis process. Power functions describe several aspects of secondary porosity in the Upper Floridan Aquifer in north Florida. In contrast, a different pattern arises in the karst landscape in southwest Florida (Big Cypress National Preserve; BICY), where low-relief and a shallow aquiclude govern regional hydrology. There, the landscape pattern is highly regular (Fig. 1), with circular cypress-dominated wetlands occupying depressions that are hydrologically isolated and distributed evenly in a matrix of pine uplands. Regular landscape patterning results from spatially coupled feedbacks, one positive operating locally that expands patches coupled to another negative that operates at distance, eventually inhibiting patch expansion. The positive feedback in BICY is thought to derive from the presence of surface depressions, which sustain prolonged inundation in this low-relief setting, and facilitate wetland development that greatly augments dissolution potential of infiltrating water in response to ecosystem metabolic processes. In short, wetlands "drill" into the carbonate leading to both vertical and lateral basin expansion. Wetland expansion occurs at the expense of surrounding upland area, which is the local catchment that subsidizes water availability. A distal inhibitory feedback on basin expansion thus occurs as the water necessary to sustain prolonged inundation becomes limiting. The implied strong reciprocal coupling between surface production of organic matter and patterns of induced subsurface carbonate dissolution are a novel example of co-evolving biogeomorphic processes in the earth system. Fig. 1 - Regular patterned landscape in Big Cypress National Preserve showing cypress dominated wetlands (round features) embedded in a mosaic of pine and grass uplands. Exposed carbonate rings are evident at the margins of many of the wetland basins.

Targeting hunter distribution based on host resource selection and kill sites to manage disease risk.

PubMed

Dugal, Cherie J; van Beest, Floris M; Vander Wal, Eric; Brook, Ryan K

2013-10-01

Endemic and emerging diseases are rarely uniform in their spatial distribution or prevalence among cohorts of wildlife. Spatial models that quantify risk-driven differences in resource selection and hunter mortality of animals at fine spatial scales can assist disease management by identifying high-risk areas and individuals. We used resource selection functions (RSFs) and selection ratios (SRs) to quantify sex- and age-specific resource selection patterns of collared (n = 67) and hunter-killed (n = 796) nonmigratory elk (Cervus canadensis manitobensis) during the hunting season between 2002 and 2012, in southwestern Manitoba, Canada. Distance to protected area was the most important covariate influencing resource selection and hunter-kill sites of elk (AICw = 1.00). Collared adult males (which are most likely to be infected with bovine tuberculosis (Mycobacterium bovis) and chronic wasting disease) rarely selected for sites outside of parks during the hunting season in contrast to adult females and juvenile males. The RSFs showed selection by adult females and juvenile males to be negatively associated with landscape-level forest cover, high road density, and water cover, whereas hunter-kill sites of these cohorts were positively associated with landscape-level forest cover and increasing distance to streams and negatively associated with high road density. Local-level forest was positively associated with collared animal locations and hunter-kill sites; however, selection was stronger for collared juvenile males and hunter-killed adult females. In instances where disease infects a metapopulation and eradication is infeasible, a principle goal of management is to limit the spread of disease among infected animals. We map high-risk areas that are regularly used by potentially infectious hosts but currently underrepresented in the distribution of kill sites. We present a novel application of widely available data to target hunter distribution based on host resource selection and kill sites as a promising tool for applying selective hunting to the management of transmissible diseases in a game species.

Patterns of spatio-temporal distribution of winter chronic photoinhibition in leaves of three evergreen Mediterranean species with contrasting acclimation responses.

PubMed

Silva-Cancino, María Carolina; Esteban, Raquel; Artetxe, Unai; Plazaola, José Ignacio García

2012-03-01

High irradiance and relatively low temperature, which characterize Mediterranean winters, cause chilling stress in plants. Downregulation of photosynthetic efficiency is a mechanism that allows plants to survive these conditions. This study aims to address whether this process shows a regular spatial pattern across leaf surface or not. Three species (Buxus sempervirens, Cistus albidus and Arctostaphylos uva-ursi) with contrasting responses to winter stress were studied. During 7 days, macro and micro Fv/Fm spatial patterns were monitored by the use of chlorophyll fluorescence imaging techniques. In the field, the strongest photoinhibition was found in B. sempervirens, while there was almost no chronic photoinhibition in C. albidus. In leaves of the first species, Fv/Fm decreased from base to tip while in C. albidus it was uniform over the leaf lamina. An intermediate behavior is shown by A. uva-ursi leaves. Spatial heterogeneity distribution of Fv/Fm was found inside the leaves, resulting in greater Fv/Fm values in the inner layers than in the outer ones. Neither xanthophyll-linked downregulation of Fv/Fm nor protein remobilization were the reasons for such spatial patterns since pigment composition and nitrogen content did not reveal tip-base differences. During recovery from winter, photoinhibition changes occurred in Fv/Fm, pigments and chloroplast ultrastructure. This work shows for the first time that irrespective of physiological mechanisms responsible for development of winter photoinhibition, there is an acclimation response with strong spatio-temporal variability at leaf level in some species. This observation should be taken into account when modeling or scaling up photosynthetic responses. Copyright © Physiologia Plantarum 2011.

[Geographical distribution of left ventricular Tei index based on principal component analysis].

PubMed

Xu, Jinhui; Ge, Miao; He, Jinwei; Xue, Ranyin; Yang, Shaofang; Jiang, Jilin

2014-11-01

To provide a scientific standard of left ventricular Tei index for healthy people from various region of China, and to lay a reliable foundation for the evaluation of left ventricular diastolic and systolic function. The correlation and principal component analysis were used to explore the left ventricular Tei index, which based on the data of 3 562 samples from 50 regions of China by means of literature retrieval. Th e nine geographical factors were longitude(X₁), latitude(X₂), altitude(X₃), annual sunshine hours (X₄), the annual average temperature (X₅), annual average relative humidity (X₆), annual precipitation (X₇), annual temperature range (X₈) and annual average wind speed (X₉). ArcGIS soft ware was applied to calculate the spatial distribution regularities of left ventricular Tei index. There is a significant correlation between the healthy people's left ventricular Tei index and geographical factors, and the correlation coefficients were -0.107 (r₁), -0.301 (r₂), -0.029 (r₃), -0.277 (r₄), -0.256(r₅), -0.289(r₆), -0.320(r₇), -0.310 (r₈) and -0.117 (r₉), respectively. A linear equation between the Tei index and the geographical factor was obtained by regression analysis based on the three extracting principal components. The geographical distribution tendency chart for healthy people's left Tei index was fitted out by the ArcGIS spatial interpolation analysis. The geographical distribution for left ventricular Tei index in China follows certain pattern. The reference value in North is higher than that in South, while the value in East is higher than that in West.

Real-world spatial regularities affect visual working memory for objects.

PubMed

Kaiser, Daniel; Stein, Timo; Peelen, Marius V

2015-12-01

Traditional memory research has focused on measuring and modeling the capacity of visual working memory for simple stimuli such as geometric shapes or colored disks. Although these studies have provided important insights, it is unclear how their findings apply to memory for more naturalistic stimuli. An important aspect of real-world scenes is that they contain a high degree of regularity: For instance, lamps appear above tables, not below them. In the present study, we tested whether such real-world spatial regularities affect working memory capacity for individual objects. Using a delayed change-detection task with concurrent verbal suppression, we found enhanced visual working memory performance for objects positioned according to real-world regularities, as compared to irregularly positioned objects. This effect was specific to upright stimuli, indicating that it did not reflect low-level grouping, because low-level grouping would be expected to equally affect memory for upright and inverted displays. These results suggest that objects can be held in visual working memory more efficiently when they are positioned according to frequently experienced real-world regularities. We interpret this effect as the grouping of single objects into larger representational units.

An economic passive sampling method to detect particulate pollutants using magnetic measurements.

PubMed

Cao, Liwan; Appel, Erwin; Hu, Shouyun; Ma, Mingming

2015-10-01

Identifying particulate matter (PM) emitted from industrial processes into the atmosphere is an important issue in environmental research. This paper presents a passive sampling method using simple artificial samplers that maintains the advantage of bio-monitoring, but overcomes some of its disadvantages. The samplers were tested in a heavily polluted area (Linfen, China) and compared to results from leaf samples. Spatial variations of magnetic susceptibility from artificial passive samplers and leaf samples show very similar patterns. Scanning electron microscopy suggests that the collected PM are mostly in the range of 2-25 μm; frequent occurrence of spherical shape indicates industrial combustion dominates PM emission. Magnetic properties around power plants show different features than other plants. This sampling method provides a suitable and economic tool for semi-quantifying temporal and spatial distribution of air quality; they can be installed in a regular grid and calibrate the weight of PM. Copyright © 2015 Elsevier Ltd. All rights reserved.

Linear functional minimization for inverse modeling

DOE PAGES

Barajas-Solano, David A.; Wohlberg, Brendt Egon; Vesselinov, Velimir Valentinov; ...

2015-06-01

In this paper, we present a novel inverse modeling strategy to estimate spatially distributed parameters of nonlinear models. The maximum a posteriori (MAP) estimators of these parameters are based on a likelihood functional, which contains spatially discrete measurements of the system parameters and spatiotemporally discrete measurements of the transient system states. The piecewise continuity prior for the parameters is expressed via Total Variation (TV) regularization. The MAP estimator is computed by minimizing a nonquadratic objective equipped with the TV operator. We apply this inversion algorithm to estimate hydraulic conductivity of a synthetic confined aquifer from measurements of conductivity and hydraulicmore » head. The synthetic conductivity field is composed of a low-conductivity heterogeneous intrusion into a high-conductivity heterogeneous medium. Our algorithm accurately reconstructs the location, orientation, and extent of the intrusion from the steady-state data only. Finally, addition of transient measurements of hydraulic head improves the parameter estimation, accurately reconstructing the conductivity field in the vicinity of observation locations.« less

Coordinated and uncoordinated optimization of networks

NASA Astrophysics Data System (ADS)

Brede, Markus

2010-06-01

In this paper, we consider spatial networks that realize a balance between an infrastructure cost (the cost of wire needed to connect the network in space) and communication efficiency, measured by average shortest path length. A global optimization procedure yields network topologies in which this balance is optimized. These are compared with network topologies generated by a competitive process in which each node strives to optimize its own cost-communication balance. Three phases are observed in globally optimal configurations for different cost-communication trade offs: (i) regular small worlds, (ii) starlike networks, and (iii) trees with a center of interconnected hubs. In the latter regime, i.e., for very expensive wire, power laws in the link length distributions P(w)∝w-α are found, which can be explained by a hierarchical organization of the networks. In contrast, in the local optimization process the presence of sharp transitions between different network regimes depends on the dimension of the underlying space. Whereas for d=∞ sharp transitions between fully connected networks, regular small worlds, and highly cliquish periphery-core networks are found, for d=1 sharp transitions are absent and the power law behavior in the link length distribution persists over a much wider range of link cost parameters. The measured power law exponents are in agreement with the hypothesis that the locally optimized networks consist of multiple overlapping suboptimal hierarchical trees.

Distribution of Arsenic and Risk Assessment of Activities on Soccer Pitches Irrigated with Arsenic-Contaminated Water.

PubMed

Martínez-Villegas, Nadia; Hernández, Abraham; Meza-Figueroa, Diana; Sen Gupta, Bhaskar

2018-05-24

The aim of this research was to estimate the risk of human exposure to arsenic due to sporting activities in a private soccer club in Mexico, where arsenic-contaminated water was regularly used for irrigation. For this purpose, the total concentration in the topsoil was considered for risk assessment. This was accomplished through three main objectives: (1) measuring arsenic concentrations in irrigation water and irrigated soils, (2) determining arsenic spatial distribution in shallow soils with Geographical Information Systems (GIS) using geostatistical analysis, and (3) collecting field and survey data to develop a risk assessment calculation for soccer activities in the soccer club. The results showed that the average arsenic concentrations in shallow soils (138.1 mg/kg) were 6.2 times higher than the Mexican threshold for domestic soils (22 mg/kg). Furthermore, dermal contact between exposed users and contaminated soils accounted for a maximum carcinogenic risk value of 1.8 × 10 −5 , which is one order of magnitude higher than the recommended risk value, while arsenic concentrations in the irrigation water were higher (6 mg/L) than the WHO’s permissible threshold in drinking water, explaining the contamination of soils after irrigation. To the best of our knowledge, this is the first risk study regarding dermal contact with arsenic following regular grass irrigation with contaminated water in soccer pitches.

STED super-resolution microscopy reveals an array of MINOS clusters along human mitochondria

PubMed Central

Jans, Daniel C.; Wurm, Christian A.; Riedel, Dietmar; Wenzel, Dirk; Stagge, Franziska; Deckers, Markus; Rehling, Peter; Jakobs, Stefan

2013-01-01

The mitochondrial inner membrane organizing system (MINOS) is a conserved large hetero-oligomeric protein complex in the mitochondrial inner membrane, crucial for the maintenance of cristae morphology. MINOS has been suggested to represent the core of an extended protein network that controls mitochondrial function and structure, and has been linked to several human diseases. The spatial arrangement of MINOS within mitochondria is ill-defined, however. Using super-resolution stimulated emission depletion (STED) microscopy and immunogold electron microscopy, we determined the distribution of three known human MINOS subunits (mitofilin, MINOS1, and CHCHD3) in mammalian cells. Super-resolution microscopy revealed that all three subunits form similar clusters within mitochondria, and that MINOS is more abundant in mitochondria around the nucleus than in peripheral mitochondria. At the submitochondrial level, mitofilin, a core MINOS subunit, is preferentially localized at cristae junctions. In primary human fibroblasts, mitofilin labeling uncovered a regularly spaced pattern of clusters arranged in parallel to the cell growth surfaces. We suggest that this array of MINOS complexes might explain the observed phenomenon of largely horizontally arranged cristae junctions that connect the inner boundary membrane to lamellar cristae. The super-resolution images demonstrate an unexpectedly high level of regularity in the nanoscale distribution of the MINOS complex in human mitochondria, supporting an integrating role of MINOS in the structural organization of the organelle. PMID:23676277

Evidence for Intact Memory-Guided Attention in School-Aged Children

ERIC Educational Resources Information Center

Dixon, Matthew L.; Zelazo, Philip David; De Rosa, Eve

2010-01-01

Visual scenes contain many statistical regularities such as the likely identity and location of objects that are present; with experience, such regularities can be encoded and can ultimately facilitate the deployment of spatial attention to important locations. Memory-guided attention has been extensively examined in adults with the "contextual…

Fibonacci Grids

NASA Technical Reports Server (NTRS)

Swinbank, Richard; Purser, James

2006-01-01

Recent years have seen a resurgence of interest in a variety of non-standard computational grids for global numerical prediction. The motivation has been to reduce problems associated with the converging meridians and the polar singularities of conventional regular latitude-longitude grids. A further impetus has come from the adoption of massively parallel computers, for which it is necessary to distribute work equitably across the processors; this is more practicable for some non-standard grids. Desirable attributes of a grid for high-order spatial finite differencing are: (i) geometrical regularity; (ii) a homogeneous and approximately isotropic spatial resolution; (iii) a low proportion of the grid points where the numerical procedures require special customization (such as near coordinate singularities or grid edges). One family of grid arrangements which, to our knowledge, has never before been applied to numerical weather prediction, but which appears to offer several technical advantages, are what we shall refer to as "Fibonacci grids". They can be thought of as mathematically ideal generalizations of the patterns occurring naturally in the spiral arrangements of seeds and fruit found in sunflower heads and pineapples (to give two of the many botanical examples). These grids possess virtually uniform and highly isotropic resolution, with an equal area for each grid point. There are only two compact singular regions on a sphere that require customized numerics. We demonstrate the practicality of these grids in shallow water simulations, and discuss the prospects for efficiently using these frameworks in three-dimensional semi-implicit and semi-Lagrangian weather prediction or climate models.

Three-dimensional data interpolation for environmental purpose: lead in contaminated soils in southern Brazil.

PubMed

Piedade, Tales Campos; Melo, Vander Freitas; Souza, Luiz Cláudio Paula; Dieckow, Jeferson

2014-09-01

Monitoring of heavy metal contamination plume in soils can be helpful in establishing strategies to minimize its hazardous impacts to the environment. The objective of this study was to apply a new approach of visualization, based on tridimensional (3D) images, of pseudo-total (extracted with concentrated acids) and exchangeable (extracted with 0.5 mol L(-1) Ca(NO3)2) lead (Pb) concentrations in soils of a mining and metallurgy area to determine the spatial distribution of this pollutant and to estimate the most contaminated soil volumes. Tridimensional images were obtained after interpolation of Pb concentrations of 171 soil samples (57 points × 3 depths) with regularized spline with tension in a 3D function version. The tridimensional visualization showed great potential of use in environmental studies and allowed to determine the spatial 3D distribution of Pb contamination plume in the area and to establish relationships with soil characteristics, landscape, and pollution sources. The most contaminated soil volumes (10,001 to 52,000 mg Pb kg(-1)) occurred near the metallurgy factory. The main contamination sources were attributed to atmospheric emissions of particulate Pb through chimneys. The large soil volume estimated to be removed to industrial landfills or co-processing evidenced the difficulties related to this practice as a remediation strategy.

Landscape and Climate Adaptation Planning for the Mashel ...

EPA Pesticide Factsheets

Salmon are important to the economic, social, cultural, and aesthetic values of the people in the Nisqually River. The Mashel watershed is important to recovery of Chinook salmon (Oncorhynchus tshawytscha) and winter steelhead (O. mykiss), and long-term sustainability of coho salmon (O. kisutch) in the Nisqually basin. The Mashel is the second largest Nisqually subwatershed by area (84 square miles) and is the largest tributary by flow accessible to salmonids. It is mostly forested, a combination of regularly harvested state and private timberlands. The watershed and salmonids utilizing the Mashel are particularly vulnerable to changes in seasonal precipitation and temperature because of its hydrologic flashiness, low summer flows and potential for sediment transport.We analyzed fish habitat potential under alternative forest management and climate scenarios using a linked modeling framework. The modeling framework includes a spatially-distributed watershed simulator (VELMA - Visualizing Ecosystem Land Management Assessments). VELMA quantifies effects of forest management and climate scenarios on key flow variables affecting salmon habitat. Spatially distributed output from VELMA was input to the Ecosystem Diagnosis and Treatment (EDT) fish habitat model to evaluate salmonid habitat potential and population responses.We show how historic timber harvest is still affecting salmonid habitat potential and how a community forest based management plan could be more pr

Surface Structuring with Polarization-Singular Femtosecond Laser Beams Generated by a q-plate

PubMed Central

Nivas, Jijil JJ; Cardano, Filippo; Song, Zhenming; Rubano, Andrea; Fittipaldi, Rosalba; Vecchione, Antonio; Paparo, Domenico; Marrucci, Lorenzo; Bruzzese, Riccardo; Amoruso, Salvatore

2017-01-01

In the last few years femtosecond optical vortex beams with different spatial distributions of the state of polarization (e.g. azimuthal, radial, spiral, etc.) have been used to generate complex, regular surface patterns on different materials. Here we present an experimental investigation on direct femtosecond laser surface structuring based on a larger class of vector beams generated by means of a q-plate with topological charge q = +1/2. In fact, voltage tuning of q-plate optical retardation allows generating a family of ultrashort laser beams with a continuous spatial evolution of polarization and fluence distribution in the focal plane. These beams can be thought of as a controlled coherent superposition of a Gaussian beam with uniform polarization and a vortex beam with a radial or azimuthal state of polarization. The use of this family of ultrashort laser beams in surface structuring leads to a further extension of the achievable surface patterns. The comparison of theoretical predictions of the vector beam characteristics at the focal plane and the generated surface patterns is used to rationalize the dependence of the surface structures on the local state of the laser beam, thus offering an effective way to either design unconventional surface structures or diagnose complex ultrashort laser beams. PMID:28169342

Surface Structuring with Polarization-Singular Femtosecond Laser Beams Generated by a q-plate.

PubMed

Nivas, Jijil Jj; Cardano, Filippo; Song, Zhenming; Rubano, Andrea; Fittipaldi, Rosalba; Vecchione, Antonio; Paparo, Domenico; Marrucci, Lorenzo; Bruzzese, Riccardo; Amoruso, Salvatore

2017-02-07

In the last few years femtosecond optical vortex beams with different spatial distributions of the state of polarization (e.g. azimuthal, radial, spiral, etc.) have been used to generate complex, regular surface patterns on different materials. Here we present an experimental investigation on direct femtosecond laser surface structuring based on a larger class of vector beams generated by means of a q-plate with topological charge q = +1/2. In fact, voltage tuning of q-plate optical retardation allows generating a family of ultrashort laser beams with a continuous spatial evolution of polarization and fluence distribution in the focal plane. These beams can be thought of as a controlled coherent superposition of a Gaussian beam with uniform polarization and a vortex beam with a radial or azimuthal state of polarization. The use of this family of ultrashort laser beams in surface structuring leads to a further extension of the achievable surface patterns. The comparison of theoretical predictions of the vector beam characteristics at the focal plane and the generated surface patterns is used to rationalize the dependence of the surface structures on the local state of the laser beam, thus offering an effective way to either design unconventional surface structures or diagnose complex ultrashort laser beams.

Fluorescent silica nanoparticles with chemically reactive surface: Controlling spatial distribution in one-step synthesis.

PubMed

Vera, María L; Cánneva, Antonela; Huck-Iriart, Cristián; Requejo, Felix G; Gonzalez, Mónica C; Dell'Arciprete, María L; Calvo, Alejandra

2017-06-15

The encapsulation of fluorescent dyes inside silica nanoparticles is advantageous to improve their quality as probes. Inside the particle, the fluorophore is protected from the external conditions and its main emission parameters remains unchanged even in the presence of quenchers. On the other hand, the amine-functionalized nanoparticle surface enables a wide range of applications, as amino groups could be easily linked with different biomolecules for targeting purposes. This kind of nanoparticle is regularly synthesized by methods that employ templates, additional nanoparticle formation or multiple pathway process. However, a one-step synthesis will be an efficient approach in this sort of bifunctional hybrid nanoparticles. A co-condensation sol-gel synthesis of hybrid fluorescent silica nanoparticle where developed. The chemical and morphological characterization of the particles where investigated by DRIFTS, XPS, SEM and SAXS. The nanoparticle fluorescent properties were also assessed by excitation-emission matrices and time resolved experiments. We have developed a one-pot synthesis method that enables the simultaneous incorporation of functionalities, the fluorescent molecule and the amino group, by controlling co-condensation process. An exhaustive characterization allows the definition of the spatial distribution of the fluorescent probe, fluorescein isothiocyanate, inside the particle and reactive amino groups on the surface of the nanoparticle with diameter about 100nm. Copyright © 2017 Elsevier Inc. All rights reserved.

Surface Structuring with Polarization-Singular Femtosecond Laser Beams Generated by a q-plate

NASA Astrophysics Data System (ADS)

Nivas, Jijil Jj; Cardano, Filippo; Song, Zhenming; Rubano, Andrea; Fittipaldi, Rosalba; Vecchione, Antonio; Paparo, Domenico; Marrucci, Lorenzo; Bruzzese, Riccardo; Amoruso, Salvatore

2017-02-01

In the last few years femtosecond optical vortex beams with different spatial distributions of the state of polarization (e.g. azimuthal, radial, spiral, etc.) have been used to generate complex, regular surface patterns on different materials. Here we present an experimental investigation on direct femtosecond laser surface structuring based on a larger class of vector beams generated by means of a q-plate with topological charge q = +1/2. In fact, voltage tuning of q-plate optical retardation allows generating a family of ultrashort laser beams with a continuous spatial evolution of polarization and fluence distribution in the focal plane. These beams can be thought of as a controlled coherent superposition of a Gaussian beam with uniform polarization and a vortex beam with a radial or azimuthal state of polarization. The use of this family of ultrashort laser beams in surface structuring leads to a further extension of the achievable surface patterns. The comparison of theoretical predictions of the vector beam characteristics at the focal plane and the generated surface patterns is used to rationalize the dependence of the surface structures on the local state of the laser beam, thus offering an effective way to either design unconventional surface structures or diagnose complex ultrashort laser beams.

Hurricane frequency and landfall distribution for coastal wetlands of the Gulf coast, USA

USGS Publications Warehouse

Doyle, T.W.

2009-01-01

The regularity and severity of tropical storms are major determinants controlling ecosystem structure and succession for coastal ecosystems. Hurricane landfall rates vary greatly with high and low frequency for given coastal stretches of the southeastern United States. Site-specific meteorological data of hurricane wind speeds and direction, however, are only available for select populated cities of relatively sparse distribution and inland from the coast. A spatial simulation model of hurricane circulation, HURASIM, was applied to reconstruct chronologies of hurricane wind speeds and vectors for northern Gulf coast locations derived from historical tracking data of North Atlantic tropical storms dating back to 1851. Contrasts of storm frequencies showed that tropical storm incidence is nearly double for Florida coastal ecosystems than the westernmost stretches of Texas coastline. Finer-scale spatial simulations for the north-central Gulf coast exhibited sub-regional differences in storm strength and frequency with coastal position and latitude. The overall pattern of storm incidence in the Gulf basin indicates that the disturbance regime of coastal areas varies greatly along the coast, inland from the coast, and temporally over the period of record. Field and modeling studies of coastal ecosystems will benefit from this retrospective analysis of hurricane incidence and intensity both on a local or regional basis. ?? 2009 The Society of Wetland Scientists.

The Spatial-Temporal Characteristics of Air Pollution in China from 2001–2014

PubMed Central

Bao, Junzhe; Yang, Xiping; Zhao, Zhiyuan; Wang, Zhenkun; Yu, Chuanhua; Li, Xudong

2015-01-01

To provide some useful information about the control of air pollution in China, we studied the spatial-temporal characteristics of air pollution in China from 2001–2014. First, we drew several line charts and histograms of the Air Pollution Index (API) and Air Quality Index (AQI) of 31 capital cities and municipalities to research the distribution across different times and cities; then, we researched the spatial clustering of API and AQI; finally, we examined the shift of the gravity center of API and AQI in different years and months. The API values had a decreasing trend: the high values had a clustering trend in some northern cities, and the low values had a clustering trend in some southern cities. The AQI values were relatively low, from 15:00–17:00 during the day. The gravity center of API had a trend of moving south from 2001–2003, then fluctuated in an unordered pattern and moved north in the winter. The AQI gravity center did not have a regular shift during different months. In conclusion, the government should take action to mitigate air pollution in some typical cities, as well as air pollution during the winter. PMID:26694427

Effect of surface morphology on drag and roughness sublayer in flows over regular roughness elements

NASA Astrophysics Data System (ADS)

Placidi, Marco; Ganapathisubramani, Bharathram

2014-11-01

The effects of systematically varied roughness morphology on bulk drag and on the spatial structure of turbulent boundary layers are examined by performing a series of wind tunnel experiments. In this study, rough surfaces consisting of regularly and uniformly distributed LEGO™ bricks are employed. Twelve different patterns are adopted in order to methodically examine the individual effects of frontal solidity (λF, frontal area of the roughness elements per unit wall-parallel area) and plan solidity (λP, plan area of roughness elements per unit wall-parallel area), on both the bulk drag and the turbulence structure. A floating element friction balance based on Krogstad & Efros (2010) was designed and manufactured to measure the drag generated by the different surfaces. In parallel, high resolution planar and stereoscopic Particle Image Velocimetry (PIV) was applied to investigate the flow features. This talk will focus on the effects of each solidity parameter on the bulk drag and attempt to relate the observed trends to the flow structures in the roughness sublayer. Currently at City University London.

Multitask SVM learning for remote sensing data classification

NASA Astrophysics Data System (ADS)

Leiva-Murillo, Jose M.; Gómez-Chova, Luis; Camps-Valls, Gustavo

2010-10-01

Many remote sensing data processing problems are inherently constituted by several tasks that can be solved either individually or jointly. For instance, each image in a multitemporal classification setting could be taken as an individual task but relation to previous acquisitions should be properly considered. In such problems, different modalities of the data (temporal, spatial, angular) gives rise to changes between the training and test distributions, which constitutes a difficult learning problem known as covariate shift. Multitask learning methods aim at jointly solving a set of prediction problems in an efficient way by sharing information across tasks. This paper presents a novel kernel method for multitask learning in remote sensing data classification. The proposed method alleviates the dataset shift problem by imposing cross-information in the classifiers through matrix regularization. We consider the support vector machine (SVM) as core learner and two regularization schemes are introduced: 1) the Euclidean distance of the predictors in the Hilbert space; and 2) the inclusion of relational operators between tasks. Experiments are conducted in the challenging remote sensing problems of cloud screening from multispectral MERIS images and for landmine detection.

Research on the semi-distributed monthly rainfall runoff model at the Lancang River basin based on DEM

NASA Astrophysics Data System (ADS)

Liu, Gang; Zhao, Rong; Liu, Jiping; Zhang, Qingpu

2007-06-01

The Lancang River Basin is so narrow and its hydrological and meteorological information are so flexible. The Rainfall, evaporation, glacial melt water and groundwater affect the runoff whose replenishment forms changing notable with the season in different areas at the basin. Characters of different kind of distributed model and conceptual hydrological model are analyzed. A semi-distributed hydrological model of relation between monthly runoff and rainfall, temperate and soil type has been built in Changdu County based on Visual Basic and ArcObject. The way of discretization of distributed hydrological model was used in the model, and principles of conceptual model are taken into account. The sub-catchment of Changdu is divided into regular cells, and all kinds of hydrological and meteorological information and land use classes and slope extracted from 1:250000 digital elevation models are distributed in each cell. The model does not think of the rainfall-runoff hydro-physical process but use the conceptual model to simulate the whole contributes to the runoff of the area. The affection of evapotranspiration loss and underground water is taken into account at the same time. The spatial distribute characteristics of the monthly runoff in the area are simulated and analyzed with a few parameters.

[Effect of thinning intensities on fruiting regularities of Quercus liaotungensis forests in Huang-long and Qiaoshan mountains.

PubMed

Huang, Cai Zhi; Zhang, Wen Hui; Li, Gang; Yu, Shi Chuan; You, Jian Jian

2016-11-18

In order to clarify the impact of thinning intensities on fruiting regularity of Quercus liaotungensis forests, we took the Q. liaotungensis half-mature forests in Huanglong and Qiaoshan mountains on south of the Loess Plateau as the object of study, which were under close-to-natural management of different thinning intensities (CK, 10%, 20% and 30%). An analysis was made on stand density and percent of seed trees, seed number of sample tree and unit area, seed spatial distributions, seed characteristics of the Q. liaotungensis forests after 5 years of thinning. The results showed that, percent of seed trees, seed number per sample tree and percent of developed seeds of Q. liaotungensis forests increased with the increasing intensity, and showed a pattern of 30%>20%>10%>CK. Seed number per area reached the maximum number under 20% thinning, and showed a pattern of 20%>30%>CK>10%. From the seed spatial distribution in the canopy, the upper accounted for 73.6%, while the lower had 26.4%. The sunny side of canopy layer set relatively the most fruits of 65.8%, shady side only had 34.2%. Under thinning, further improving was geater under lower canopy than under upper canopy and so was on shady side than on sunny side. The seed long diameter, seed short diameter and 1000-seed mass of Q. liaotungensis forests increased with the increasing intensity, which reached the maximum under 30% thinning. 10% thinning did not significantly impact Q. liaotungensis fruiting, the thinning intensity of 20% was most conducive to the seed quantity and quality improvement of Q. liaotungensis, while the thinning intensity of 30% did not improve the fruiting, and lowered the total number of seeds. It was proposed that 20% thinning should be chosen (canopy density of 0.7) to effectively improve fruiting and quality of Q. liaotungensis.

4D-tomographic reconstruction of water vapor using the hybrid regularization technique with application to the North West of Iran

NASA Astrophysics Data System (ADS)

Adavi, Zohre; Mashhadi-Hossainali, Masoud

2015-04-01

Water vapor is considered as one of the most important weather parameter in meteorology. Its non-uniform distribution, which is due to the atmospheric phenomena above the surface of the earth, depends both on space and time. Due to the limited spatial and temporal coverage of observations, estimating water vapor is still a challenge in meteorology and related fields such as positioning and geodetic techniques. Tomography is a method for modeling the spatio-temporal variations of this parameter. By analyzing the impact of troposphere on the Global Navigation Satellite (GNSS) signals, inversion techniques are used for modeling the water vapor in this approach. Non-uniqueness and instability of solution are the two characteristic features of this problem. Horizontal and/or vertical constraints are usually used to compute a unique solution for this problem. Here, a hybrid regularization method is used for computing a regularized solution. The adopted method is based on the Least-Square QR (LSQR) and Tikhonov regularization techniques. This method benefits from the advantages of both the iterative and direct techniques. Moreover, it is independent of initial values. Based on this property and using an appropriate resolution for the model, firstly the number of model elements which are not constrained by GPS measurement are minimized and then; water vapor density is only estimated at the voxels which are constrained by these measurements. In other words, no constraint is added to solve the problem. Reconstructed profiles of water vapor are validated using radiosonde measurements.

Unfolding sphere size distributions with a density estimator based on Tikhonov regularization

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

Weese, J.; Korat, E.; Maier, D.

1997-12-01

This report proposes a method for unfolding sphere size distributions given a sample of radii that combines the advantages of a density estimator with those of Tikhonov regularization methods. The following topics are discusses in this report to achieve this method: the relation between the profile and the sphere size distribution; the method for unfolding sphere size distributions; the results based on simulations; and the experimental data comparison.

Using genetic and phenotypic comparisons to evaluate apparent segregation among Kokanee spawning groups

USGS Publications Warehouse

Whitlock, Steven L.; Campbell, Matthew R.; Quist, Michael C.; Dux, Andrew M.

2018-01-01

Genetic and phenotypic traits of spatially and temporally segregated kokanee Oncorhynchus nerka spawning groups in Lake Pend Oreille, Idaho, were compared to test for evidence of divergence on the basis of ecotype (stream spawners versus shoreline spawners) and spawn timing and to describe morphological, life history, and reproductive variation within and among groups. Early and late spawning runs were found to be reproductively isolated; however, there was no clear evidence of genetic differentiation between ecotypes. Spawning groups within the same ecotype differed in length, age distribution, mean length at age, fecundity, and egg size. Variation in reproductive attributes was due primarily to differences in length distributions. Larger‐bodied shore‐spawning kokanee were located in areas where egg survival is known to be enhanced by downwelling, suggesting that the distribution of shore‐spawning kokanee may be partly structured by competition for spawning habitats with groundwater influence. This study contributes to other research indicating that introduced kokanee populations are unlikely to undergo adaptive divergence if they have a history of population fluctuations and are supplemented regularly.

Spatially adaptive bases in wavelet-based coding of semi-regular meshes

NASA Astrophysics Data System (ADS)

Denis, Leon; Florea, Ruxandra; Munteanu, Adrian; Schelkens, Peter

2010-05-01

In this paper we present a wavelet-based coding approach for semi-regular meshes, which spatially adapts the employed wavelet basis in the wavelet transformation of the mesh. The spatially-adaptive nature of the transform requires additional information to be stored in the bit-stream in order to allow the reconstruction of the transformed mesh at the decoder side. In order to limit this overhead, the mesh is first segmented into regions of approximately equal size. For each spatial region, a predictor is selected in a rate-distortion optimal manner by using a Lagrangian rate-distortion optimization technique. When compared against the classical wavelet transform employing the butterfly subdivision filter, experiments reveal that the proposed spatially-adaptive wavelet transform significantly decreases the energy of the wavelet coefficients for all subbands. Preliminary results show also that employing the proposed transform for the lowest-resolution subband systematically yields improved compression performance at low-to-medium bit-rates. For the Venus and Rabbit test models the compression improvements add up to 1.47 dB and 0.95 dB, respectively.

General physical activity levels influence positive and negative priming effects in young adults.

PubMed

Kamijo, Keita; Takeda, Yuji

2009-03-01

To investigate the relationship between general physical activity level and the cognitive functions of executive control in young adults using behavioral measures and event-related brain potentials. Forty young adults (mean age=21.1 yrs; 19 females) were differentiated on the basis of their regular physical activity level into two groups: active and sedentary. They performed a spatial priming task consisting of three conditions: control, positive, and negative priming. Spatial priming effects, which are related to executive control and occur automatically, were assessed as indicators of cognitive functioning. Negative priming effects on reaction time and P3 latency in the active group were larger than in the sedentary group. By contrast, positive priming effects were only observed in the sedentary group. The cognitive effects of regular physical activity could be observed using a relatively simple paradigm. The results indicate that regular physical activity has a beneficial effect on the cognitive processes on executive control in young adults. The present study provides additional evidence of the beneficial effects of regular physical activity on cognitive functioning in young adults.

Dynamic Cross-Entropy.

PubMed

Aur, Dorian; Vila-Rodriguez, Fidel

2017-01-01

Complexity measures for time series have been used in many applications to quantify the regularity of one dimensional time series, however many dynamical systems are spatially distributed multidimensional systems. We introduced Dynamic Cross-Entropy (DCE) a novel multidimensional complexity measure that quantifies the degree of regularity of EEG signals in selected frequency bands. Time series generated by discrete logistic equations with varying control parameter r are used to test DCE measures. Sliding window DCE analyses are able to reveal specific period doubling bifurcations that lead to chaos. A similar behavior can be observed in seizures triggered by electroconvulsive therapy (ECT). Sample entropy data show the level of signal complexity in different phases of the ictal ECT. The transition to irregular activity is preceded by the occurrence of cyclic regular behavior. A significant increase of DCE values in successive order from high frequencies in gamma to low frequencies in delta band reveals several phase transitions into less ordered states, possible chaos in the human brain. To our knowledge there are no reliable techniques able to reveal the transition to chaos in case of multidimensional times series. In addition, DCE based on sample entropy appears to be robust to EEG artifacts compared to DCE based on Shannon entropy. The applied technique may offer new approaches to better understand nonlinear brain activity. Copyright © 2016 Elsevier B.V. All rights reserved.

Mixture of Segmenters with Discriminative Spatial Regularization and Sparse Weight Selection*

PubMed Central

Chen, Ting; Rangarajan, Anand; Eisenschenk, Stephan J.

2011-01-01

This paper presents a novel segmentation algorithm which automatically learns the combination of weak segmenters and builds a strong one based on the assumption that the locally weighted combination varies w.r.t. both the weak segmenters and the training images. We learn the weighted combination during the training stage using a discriminative spatial regularization which depends on training set labels. A closed form solution to the cost function is derived for this approach. In the testing stage, a sparse regularization scheme is imposed to avoid overfitting. To the best of our knowledge, such a segmentation technique has never been reported in literature and we empirically show that it significantly improves on the performances of the weak segmenters. After showcasing the performance of the algorithm in the context of atlas-based segmentation, we present comparisons to the existing weak segmenter combination strategies on a hippocampal data set. PMID:22003748

On linear Landau Damping for relativistic plasmas via Gevrey regularity

NASA Astrophysics Data System (ADS)

Young, Brent

2015-10-01

We examine the phenomenon of Landau Damping in relativistic plasmas via a study of the relativistic Vlasov-Poisson system (both on the torus and on R3) linearized around a sufficiently nice, spatially uniform kinetic equilibrium. We find that exponential decay of spatial Fourier modes is impossible under modest symmetry assumptions. However, by assuming the equilibrium and initial data are sufficiently regular functions of velocity for a given wavevector (in particular that they exhibit a kind of Gevrey regularity), we show that it is possible for the mode associated to this wavevector to decay like exp ⁡ (-| t | δ) (with 0 < δ < 1) if the magnitude of the wavevector exceeds a certain critical size which depends on the character of the interaction. We also give a heuristic argument why one should not expect such rapid decay for modes with wavevectors below this threshold.

Topological chaos of the spatial prisoner's dilemma game on regular networks.

PubMed

Jin, Weifeng; Chen, Fangyue

2016-02-21

The spatial version of evolutionary prisoner's dilemma on infinitely large regular lattice with purely deterministic strategies and no memories among players is investigated in this paper. Based on the statistical inferences, it is pertinent to confirm that the frequency of cooperation for characterizing its macroscopic behaviors is very sensitive to the initial conditions, which is the most practically significant property of chaos. Its intrinsic complexity is then justified on firm ground from the theory of symbolic dynamics; that is, this game is topologically mixing and possesses positive topological entropy on its subsystems. It is demonstrated therefore that its frequency of cooperation could not be adopted by simply averaging over several steps after the game reaches the equilibrium state. Furthermore, the chaotically changing spatial patterns via empirical observations can be defined and justified in view of symbolic dynamics. It is worth mentioning that the procedure proposed in this work is also applicable to other deterministic spatial evolutionary games therein. Copyright © 2015 Elsevier Ltd. All rights reserved.

Risk areas for hepatitis A, B and C in the municipality of Maringá, Paraná State, Brazil 2007-2010.

PubMed

Avanzi, Valéria Miranda; Fonzar, Udelysses Janete Veltrini; Silva, Eraldo Schunk; Teixeira, Jorge Juarez Vieira; Bertolini, Dennis Armando

2018-05-08

Viral hepatitis is a major public health problem in Brazil and worldwide. We retrospectively analyzed 338 cases of hepatitis A, B and C in Maringá, Paraná State from 2007 through 2010. The hepatitis A virus was present in 5.6% of the cases, hepatitis B in 44.7% and hepatitis C in 49.7%. Most of the patients affected were male (55.3%), white (79.6%) and had some primary education (42.9%). Of the 338 cases analyzed, 13.0% had comorbidities. The cases were concentrated in large-population census zones, but it was concluded that the spatial distribution of viral hepatitis in Maringá occurred randomly rather than show any regular pattern.

Radio Astronomy Explorer (RAE) 1 observations of terrestrial radio noise

NASA Technical Reports Server (NTRS)

Herman, J. R.; Caruso, J. A.

1971-01-01

Radio Astonomy Explorer (RAE) 1 data are analyzed to establish characteristics of HF terrestrial radio noise at an altitude of about 6000 km. Time and frequency variations in amplitude of the observed noise well above cosmic noise background are explained on the basis of temporal and spatial variations in ionospheric critical frequency coupled with those in noise source distributions. It is shown that terrestrial noise regularly breaks through the ionosphere and reaches RAE with magnitudes 15 or more db higher than cosmic noise background. Maximum terrestrial noise is observed when RAE is over the dark side of the Earth in the neighborhood of equatorial continental land masses where thunderstorms occur most frequently. The observed noise level is 30-40 db lower with RAE over oceans.

EIT image reconstruction with four dimensional regularization.

PubMed

Dai, Tao; Soleimani, Manuchehr; Adler, Andy

2008-09-01

Electrical impedance tomography (EIT) reconstructs internal impedance images of the body from electrical measurements on body surface. The temporal resolution of EIT data can be very high, although the spatial resolution of the images is relatively low. Most EIT reconstruction algorithms calculate images from data frames independently, although data are actually highly correlated especially in high speed EIT systems. This paper proposes a 4-D EIT image reconstruction for functional EIT. The new approach is developed to directly use prior models of the temporal correlations among images and 3-D spatial correlations among image elements. A fast algorithm is also developed to reconstruct the regularized images. Image reconstruction is posed in terms of an augmented image and measurement vector which are concatenated from a specific number of previous and future frames. The reconstruction is then based on an augmented regularization matrix which reflects the a priori constraints on temporal and 3-D spatial correlations of image elements. A temporal factor reflecting the relative strength of the image correlation is objectively calculated from measurement data. Results show that image reconstruction models which account for inter-element correlations, in both space and time, show improved resolution and noise performance, in comparison to simpler image models.

Species-driven phases and increasing structure in early-successional plant communities.

PubMed

Zaplata, Markus K; Winter, Susanne; Fischer, Anton; Kollmann, Johannes; Ulrich, Werner

2013-01-01

Successional phases describe changes in ecological communities that proceed in steps rather than continuously. Despite their importance for the understanding of ecosystem development, there still exists no reliable definition of phases and no quantitative measure of phase transitions. In order to obtain these data, we investigated primary succession in an artificial catchment (6 ha) in eastern Germany over a period of 6 years. The data set consists of records of plant species and their cover values, and initial substrate properties, both from plots in a regular grid (20 m × 20 m) suitable for spatial data analysis. Community assembly was studied by analyses of species co-occurrence and nestedness. Additionally, we correlated lognormal and log series distributions of species abundance to each community. We here introduce a new general method for detection of successional phases based on the degree of transient spatial homogeneity in the study system. Spatially coherent vegetation patterns revealed nonoverlapping partitions within this sequence of primary succession and were characterized as two distinct ecological phases. Patterns of species co-occurrence were increasingly less random, and hence the importance of demographic stochasticity and neutral community assembly decreased during the study period. Our findings highlight the spatial dimension of successional phases and quantify the degree of change between these steps. They are an element for advancing a more reliable terminology of ecological successions.

Dynamics of coherent states in regular and chaotic regimes of the non-integrable Dicke model

NASA Astrophysics Data System (ADS)

Lerma-Hernández, S.; Chávez-Carlos, J.; Bastarrachea-Magnani, M. A.; López-del-Carpio, B.; Hirsch, J. G.

2018-04-01

The quantum dynamics of initial coherent states is studied in the Dicke model and correlated with the dynamics, regular or chaotic, of their classical limit. Analytical expressions for the survival probability, i.e. the probability of finding the system in its initial state at time t, are provided in the regular regions of the model. The results for regular regimes are compared with those of the chaotic ones. It is found that initial coherent states in regular regions have a much longer equilibration time than those located in chaotic regions. The properties of the distributions for the initial coherent states in the Hamiltonian eigenbasis are also studied. It is found that for regular states the components with no negligible contribution are organized in sequences of energy levels distributed according to Gaussian functions. In the case of chaotic coherent states, the energy components do not have a simple structure and the number of participating energy levels is larger than in the regular cases.

Spatial pulses of water inputs in deciduous and hemlock forest stands

NASA Astrophysics Data System (ADS)

Guswa, A. J.; Mussehl, M.; Pecht, A.; Spence, C.

2010-12-01

Trees intercept and redistribute precipitation in time and space. While spatial patterns of throughfall are challenging to link to plant and canopy characteristics, many studies have shown that the spatial patterns persist through time. This persistence leads to wet and dry spots under the trees, creating spatial pulses of moisture that can affect infiltration, transpiration, and biogeochemical processes. In the northeast, the invasive hemlock woolly adelgid poses a significant threat to eastern hemlock (Tsuga canadensis), and replacement of hemlock forests by other species, such as birch, maple, and oak, has the potential to alter throughfall patterns and hydrologic processes. During the summers of 2009 and 2010, we measured throughfall in both hemlock and deciduous plots to assess its spatial distribution and temporal persistence. From 3 June to 25 July 2009, we measured throughfall in one hemlock and one deciduous plot over fourteen events with rainfall totaling 311 mm. From 8 June through 28 July 2010, we measured throughfall in the same two plots plus an additional hemlock stand and a young black birch stand, and rainfall totaled 148 mm over eight events. Averaged over space and time, throughfall was 81% of open precipitation in the hemlock stands, 88% in the mixed deciduous stand, and 100% in the young black birch stand. On an event basis, spatial coefficients of variation are similar among the stands and range from 11% to 49% for rain events greater than 5 mm. With the exception of very light events, coefficients of variation are insensitive to precipitation amount. Spatial patterns of throughfall persist through time, and seasonal coefficients of variation range from 13% to 33%. All stands indicate localized concentrations of water inputs, and there were individual collectors in the deciduous stands that regularly received more than twice the stand-average throughfall.

The role of contact angle on unstable flow formation during infiltration and drainage in wettable porous media

NASA Astrophysics Data System (ADS)

Wallach, Rony; Margolis, Michal; Graber, Ellen R.

2013-10-01

The impact of contact angle on 2-D spatial and temporal water-content distribution during infiltration and drainage was experimentally studied. The 0.3-0.5 mm fraction of a quartz dune sand was treated and turned subcritically repellent (contact angle of 33°, 48°, 56°, and 75° for S33, S48, S56, and S75, respectively). The media were packed uniformly in transparent flow chambers and water was supplied to the surface as a point source at different rates (1-20 ml/min). A sequence of gray-value images was taken by CCD camera during infiltration and subsequent drainage; gray values were converted to volumetric water content by water volume balance. Narrow and long plumes with water accumulation behind the downward moving wetting front (tip) and negative water gradient above it (tail) developed in the S56 and S75 media during infiltration at lower water application rates. The plumes became bulbous with spatially uniform water-content distribution as water application rates increased. All plumes in these media propagated downward at a constant rate during infiltration and did not change their shape during drainage. In contrast, regular plume shapes were observed in the S33 and S48 media at all flow rates, and drainage profiles were nonmonotonic with a transition plane at the depth that water reached during infiltration. Given that the studied media have similar pore-size distributions, the conclusion is that imbibition hindered by the nonzero contact angle induced pressure buildup at the wetting front (dynamic water-entry value) that controlled the plume shape and internal water-content distribution during infiltration and drainage.

Cookbook Recipe to Simulate Seawater Intrusion with Standard MODFLOW

NASA Astrophysics Data System (ADS)

Schaars, F.; Bakker, M.

2012-12-01

We developed a cookbook recipe to simulate steady interface flow in multi-layer coastal aquifers with regular groundwater codes such as standard MODFLOW. The main step in the recipe is a simple transformation of the hydraulic conductivities and thicknesses of the aquifers. Standard groundwater codes may be applied to compute the head distribution in the aquifer using the transformed parameters. For example, for flow in a single unconfined aquifer, the hydraulic conductivity needs to be multiplied with 41 and the base of the aquifer needs to be set to mean sea level (for a relative seawater density of 1.025). Once the head distribution is obtained, the Ghijben-Herzberg relationship is applied to compute the depth of the interface. The recipe may be applied to quite general settings, including spatially variable aquifer properties. Any standard groundwater code may be used, as long as it can simulate unconfined flow where the transmissivity is a linear function of the head. The proposed recipe is benchmarked successfully against a number of analytic and numerical solutions.

Model Calibration in Watershed Hydrology

NASA Technical Reports Server (NTRS)

Yilmaz, Koray K.; Vrugt, Jasper A.; Gupta, Hoshin V.; Sorooshian, Soroosh

2009-01-01

Hydrologic models use relatively simple mathematical equations to conceptualize and aggregate the complex, spatially distributed, and highly interrelated water, energy, and vegetation processes in a watershed. A consequence of process aggregation is that the model parameters often do not represent directly measurable entities and must, therefore, be estimated using measurements of the system inputs and outputs. During this process, known as model calibration, the parameters are adjusted so that the behavior of the model approximates, as closely and consistently as possible, the observed response of the hydrologic system over some historical period of time. This Chapter reviews the current state-of-the-art of model calibration in watershed hydrology with special emphasis on our own contributions in the last few decades. We discuss the historical background that has led to current perspectives, and review different approaches for manual and automatic single- and multi-objective parameter estimation. In particular, we highlight the recent developments in the calibration of distributed hydrologic models using parameter dimensionality reduction sampling, parameter regularization and parallel computing.

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.

Strongyloides stercoralis and hookworm co-infection: spatial distribution and determinants in Preah Vihear Province, Cambodia.

PubMed

Forrer, Armelle; Khieu, Virak; Schär, Fabian; Vounatsou, Penelope; Chammartin, Frédérique; Marti, Hanspeter; Muth, Sinuon; Odermatt, Peter

2018-01-12

Strongyloides stercoralis and hookworm are two soil-transmitted helminths (STH) that are highly prevalent in Cambodia. Strongyloides stercoralis causes long-lasting infections and significant morbidity but is largely neglected, while hookworm causes the highest public health burden among STH. The two parasites have the same infection route, i.e. skin penetration. The extent of co-distribution, which could result in potential high co-morbidities, is unknown in highly endemic settings like Cambodia. The aim of this study was to predict the spatial distribution of S. stercoralis-hookworm co-infection risk and to investigate determinants of co-infection in Preah Vihear Province, North Cambodia. A cross-sectional survey was conducted in 2010 in 60 villages of Preah Vihear Province. Diagnosis was performed on two stool samples, using combined Baermann technique and Koga agar culture plate for S. stercoralis and Kato-Katz technique for hookworm. Bayesian multinomial geostatistical models were used to assess demographic, socioeconomic, and behavioural determinants of S. stercoralis-hookworm co-infection and to predict co-infection risk at non-surveyed locations. Of the 2576 participants included in the study, 48.6% and 49.0% were infected with S. stercoralis and hookworm, respectively; 43.8% of the cases were co-infections. Females, preschool aged children, adults aged 19-49 years, and participants who reported regularly defecating in toilets, systematically boiling drinking water and having been treated with anthelmintic drugs had lower odds of co-infection. While S. stercoralis infection risk did not appear to be spatially structured, hookworm mono-infection and co-infection exhibited spatial correlation at about 20 km. Co-infection risk was positively associated with longer walking distances to a health centre and exhibited a small clustering tendency. The association was only partly explained by climatic variables, suggesting a role for underlying factors, such as living conditions and remoteness. Both parasites were ubiquitous in the province, with co-infections accounting for almost half of all cases. The high prevalence of S. stercoralis calls for control measures. Despite several years of school-based de-worming programmes, hookworm infection levels remain high. Mebendazole efficacy, as well as coverage of and compliance to STH control programmes should be investigated.

A method for spatial regularisation of a bunch of filaments in a femtosecond laser pulse

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

Kandidov, V P; Kosareva, O G; Nyakk, A V

A method for spatial regularisation of chaotically located filaments, which appear in a high-power femtosecond laser pulse, is proposed, numerically substantiated, and experimentally tested. This method is based on the introduction of regular light-field perturbations into the femtosecond-pulse cross section. (letters)

Fractal analysis of time varying data

DOEpatents

Vo-Dinh, Tuan; Sadana, Ajit

2002-01-01

Characteristics of time varying data, such as an electrical signal, are analyzed by converting the data from a temporal domain into a spatial domain pattern. Fractal analysis is performed on the spatial domain pattern, thereby producing a fractal dimension D.sub.F. The fractal dimension indicates the regularity of the time varying data.

Higher order total variation regularization for EIT reconstruction.

PubMed

Gong, Bo; Schullcke, Benjamin; Krueger-Ziolek, Sabine; Zhang, Fan; Mueller-Lisse, Ullrich; Moeller, Knut

2018-01-08

Electrical impedance tomography (EIT) attempts to reveal the conductivity distribution of a domain based on the electrical boundary condition. This is an ill-posed inverse problem; its solution is very unstable. Total variation (TV) regularization is one of the techniques commonly employed to stabilize reconstructions. However, it is well known that TV regularization induces staircase effects, which are not realistic in clinical applications. To reduce such artifacts, modified TV regularization terms considering a higher order differential operator were developed in several previous studies. One of them is called total generalized variation (TGV) regularization. TGV regularization has been successively applied in image processing in a regular grid context. In this study, we adapted TGV regularization to the finite element model (FEM) framework for EIT reconstruction. Reconstructions using simulation and clinical data were performed. First results indicate that, in comparison to TV regularization, TGV regularization promotes more realistic images. Graphical abstract Reconstructed conductivity changes located on selected vertical lines. For each of the reconstructed images as well as the ground truth image, conductivity changes located along the selected left and right vertical lines are plotted. In these plots, the notation GT in the legend stands for ground truth, TV stands for total variation method, and TGV stands for total generalized variation method. Reconstructed conductivity distributions from the GREIT algorithm are also demonstrated.

Delayed Acquisition of Non-Adjacent Vocalic Distributional Regularities

ERIC Educational Resources Information Center

Gonzalez-Gomez, Nayeli; Nazzi, Thierry

2016-01-01

The ability to compute non-adjacent regularities is key in the acquisition of a new language. In the domain of phonology/phonotactics, sensitivity to non-adjacent regularities between consonants has been found to appear between 7 and 10 months. The present study focuses on the emergence of a posterior-anterior (PA) bias, a regularity involving two…

Intensity of Territorial Marking Predicts Wolf Reproduction: Implications for Wolf Monitoring

PubMed Central

García, Emilio J.

2014-01-01

Background The implementation of intensive and complex approaches to monitor large carnivores is resource demanding, restricted to endangered species, small populations, or small distribution ranges. Wolf monitoring over large spatial scales is difficult, but the management of such contentious species requires regular estimations of abundance to guide decision-makers. The integration of wolf marking behaviour with simple sign counts may offer a cost-effective alternative to monitor the status of wolf populations over large spatial scales. Methodology/Principal Findings We used a multi-sampling approach, based on the collection of visual and scent wolf marks (faeces and ground scratching) and the assessment of wolf reproduction using howling and observation points, to test whether the intensity of marking behaviour around the pup-rearing period (summer-autumn) could reflect wolf reproduction. Between 1994 and 2007 we collected 1,964 wolf marks in a total of 1,877 km surveyed and we searched for the pups' presence (1,497 howling and 307 observations points) in 42 sampling sites with a regular presence of wolves (120 sampling sites/year). The number of wolf marks was ca. 3 times higher in sites with a confirmed presence of pups (20.3 vs. 7.2 marks). We found a significant relationship between the number of wolf marks (mean and maximum relative abundance index) and the probability of wolf reproduction. Conclusions/Significance This research establishes a real-time relationship between the intensity of wolf marking behaviour and wolf reproduction. We suggest a conservative cutting point of 0.60 for the probability of wolf reproduction to monitor wolves on a regional scale combined with the use of the mean relative abundance index of wolf marks in a given area. We show how the integration of wolf behaviour with simple sampling procedures permit rapid, real-time, and cost-effective assessments of the breeding status of wolf packs with substantial implications to monitor wolves at large spatial scales. PMID:24663068

Directional kriging implementation for gridded data interpolation and comparative study with common methods

NASA Astrophysics Data System (ADS)

Mahmoudabadi, H.; Briggs, G.

2016-12-01

Gridded data sets, such as geoid models or datum shift grids, are commonly used in coordinate transformation algorithms. Grid files typically contain known or measured values at regular fixed intervals. The process of computing a value at an unknown location from the values in the grid data set is called "interpolation". Generally, interpolation methods predict a value at a given point by computing a weighted average of the known values in the neighborhood of the point. Geostatistical Kriging is a widely used interpolation method for irregular networks. Kriging interpolation first analyzes the spatial structure of the input data, then generates a general model to describe spatial dependencies. This model is used to calculate values at unsampled locations by finding direction, shape, size, and weight of neighborhood points. Because it is based on a linear formulation for the best estimation, Kriging it the optimal interpolation method in statistical terms. The Kriging interpolation algorithm produces an unbiased prediction, as well as the ability to calculate the spatial distribution of uncertainty, allowing you to estimate the errors in an interpolation for any particular point. Kriging is not widely used in geospatial applications today, especially applications that run on low power devices or deal with large data files. This is due to the computational power and memory requirements of standard Kriging techniques. In this paper, improvements are introduced in directional kriging implementation by taking advantage of the structure of the grid files. The regular spacing of points simplifies finding the neighborhood points and computing their pairwise distances, reducing the the complexity and improving the execution time of the Kriging algorithm. Also, the proposed method iteratively loads small portion of interest areas in different directions to reduce the amount of required memory. This makes the technique feasible on almost any computer processor. Comparison between kriging and other standard interpolation methods demonstrated more accurate estimations in less denser data files.

Linking Pattern Formation and Alternative Stable States: Ecohydrologic Thresholds and Critical Transitions in the Everglades Peatlands

NASA Astrophysics Data System (ADS)

Heffernan, J. B.; Ross, M. S.; Sah, J. P.; Isherwood, E.; Cohen, M. J.

2015-12-01

Spatial patterning occurs in a variety of ecosystems, and is important for the functional properties of landscapes; for testing spatial models of ecological processes; and as an indicator of landscape condition and resilience. Theory suggests that regular patterns arise from coupled local- and landscape-scale feedbacks that can also create multiple stable landscape states. In the Florida Everglades, hydrologic modification has degraded much of the historically-extensive ridge-slough landscape, a patterned peatland mosaic with distinct, flow-parallel patches. However, in the Everglades and in general, the hypothesis that patterned landscapes have homogeneous alternative states has little direct empirical support. Here we use microtopographic and vegetative heterogeneity, and their relation to hydrologic conditions, to infer the existence of multiple landscape equilibria and identify the hydrologic thresholds for critical transitions between these states. Dual relationships between elevation variance and water depth, and bi-modal distributions of both elevation variance and plant community distinctness, are consistent with generic predictions of multiple states, and covariation between these measures suggests that microtopography is the leading indicator of landscape degradation. Furthermore, a simple ecohydrologic multiple-state model correctly predicts the hydrologic thresholds for persistence of distinct ridges and sloughs. Predicted ridge-slough elevation differences and their relation to water depth are much greater than observed in the contemporary Everglades, but correspond closely with historical observations of pre-drainage conditions. These multiple lines of evidence represent the broadest and most direct support for the link between regular spatial pattern and landscape-scale alternative states in any ecosystem, and suggest that other patterned landscapes could undergo sudden collapse in response to changing environmental conditions. Hydrologic thresholds and leading indicators of critical transitions should guide management of the Everglades ridge-slough landscape, whose preservation is a central goal of one of the world's largest ecosystem restoration efforts.

Investigation of water imbibition in porous stone by thermal neutron radiography

NASA Astrophysics Data System (ADS)

Hassanein, R.; Meyer, H. O.; Carminati, A.; Estermann, M.; Lehmann, E.; Vontobel, P.

2006-10-01

The understanding and modelling of the process of water imbibition is important for various applications of physics (e.g. building or soil physics). To measure the spatial distribution of the water content at arbitrary times is not trivial. Neutron radiography provides an appropriate tool for such investigations with excellent time and spatial resolution. Because of the high sensitivity to hydrogen, even small amounts of water in a porous structure can be detected in samples with dimensions up to 40 cm. Three different porous stones found in Indiana, USA, have been investigated (Mansfield sandstone, Salem limestone and Hindustan whetstone). The imbibition of deionized water and a NaCl solution in up- and downwards directions has been tracked during several hours and radiographed at regular intervals. A correction method to reduce the disturbing effects due to neutron scattering is applied. This allows a quantitative evaluation of the water content in addition to the visualization of the water distribution. The results agree well with theoretical models describing water infiltration and reproduce the water content with a pixel resolution of 272 µm in time steps of 1 min. The comparison with the radiographed structure of the dry stone explains variations in the conduction or retention of the water, respectively. The experimental and correction procedures described here can be applied to other porous media and their uptake and loss of fluids.

Prevalence and Spatial Distribution of Salmonella Infections in the Pennsylvania Raccoon (Procyon lotor).

PubMed

Very, K J; Kirchner, M K; Shariat, N; Cottrell, W; Sandt, C H; Dudley, E G; Kariyawasam, S; Jayarao, B M

2016-05-01

A study was conducted to determine the prevalence and spatial distribution of Salmonella infection in Pennsylvania raccoons (Procyon lotor), common wildlife mammals known to occupy overlapping habitats with humans and domestic food animals. The Pennsylvania Game Commission provided a total of 371 raccoon intestinal samples from trapped and road-killed raccoons collected between May and November 2011. Salmonella was isolated from the faeces of 56 (15.1%) of 371 raccoons in 35 (54%) of 65 counties across Pennsylvania. The five most frequently isolated serotypes were Newport (28.6%), Enteritidis (19.6%), Typhimurium (10.7%), Braenderup (8.9%) and Bareilly (7.1%). Pulsed-field gel electrophoresis (PFGE) analysis of the Salmonella isolates and subsequent comparison to the Pennsylvania Department of Health human Salmonella PFGE database revealed 16 different pulsetypes in Salmonella isolates recovered from raccoons that were indistinguishable from pulsetypes of Salmonella collected from clinically ill humans during the study period. The pulsetypes of seven raccoon Salmonella isolates matched those of 56 human Salmonella isolates by month and geographical region of sample collection. Results from Clustered Regularly Interspaced Short Palindromic Repeats and Multi-Virulence Locus Sequence Typing (CRISPR-MVLST) analysis corroborated the PFGE and serotyping data. The findings of this study show that several PFGE pulsetypes of Salmonella were shared between humans and raccoons in Pennsylvania, indicating that raccoons and humans might share the same source of Salmonella. © 2015 Blackwell Verlag GmbH.

Image processing for quantifying fracture orientation and length scale transitions during brittle deformation

NASA Astrophysics Data System (ADS)

Rizzo, R. E.; Healy, D.; Farrell, N. J.

2017-12-01

We have implemented a novel image processing tool, namely two-dimensional (2D) Morlet wavelet analysis, capable of detecting changes occurring in fracture patterns at different scales of observation, and able of recognising the dominant fracture orientations and the spatial configurations for progressively larger (or smaller) scale of analysis. Because of its inherited anisotropy, the Morlet wavelet is proved to be an excellent choice for detecting directional linear features, i.e. regions where the amplitude of the signal is regular along one direction and has sharp variation along the perpendicular direction. Performances of the Morlet wavelet are tested against the 'classic' Mexican hat wavelet, deploying a complex synthetic fracture network. When applied to a natural fracture network, formed triaxially (σ1>σ2=σ3) deforming a core sample of the Hopeman sandstone, the combination of 2D Morlet wavelet and wavelet coefficient maps allows for the detection of characteristic scale orientation and length transitions, associated with the shifts from distributed damage to the growth of localised macroscopic shear fracture. A complementary outcome arises from the wavelet coefficient maps produced by increasing the wavelet scale parameter. These maps can be used to chart the variations in the spatial distribution of the analysed entities, meaning that it is possible to retrieve information on the density of fracture patterns at specific length scales during deformation.

Distribution and regularity of injection from a multicylinder fuel-injection pump

NASA Technical Reports Server (NTRS)

Rothrock, A M; Marsh, E T

1936-01-01

This report presents the results of performance test conducted on a six-cylinder commercial fuel-injection pump that was adjusted to give uniform fuel distribution among the cylinders at a throttle setting of 0.00038 pound per injection and a pump speed of 750 revolutions per minute. The throttle setting and pump speed were then varied through the operating range to determine the uniformity of distribution and regularity of injection.

The Effect of TIMP-1 on the Cone Mosaic in the Retina of the Rat Model of Retinitis Pigmentosa

PubMed Central

Ji, Yerina; Yu, Wan-Qing; Eom, Yun Sung; Bruce, Farouk; Craft, Cheryl Mae; Grzywacz, Norberto M.; Lee, Eun-Jin

2015-01-01

Purpose. The array of photoreceptors found in normal retinas provides uniform and regular sampling of the visual space. In contrast, cones in retinas of the S334ter-line-3 rat model for RP migrate to form a mosaic of rings, leaving large holes with few or no photoreceptors. Similar mosaics appear in human patients with other forms of retinal dystrophy. In the current study, we aimed to investigate the effect of tissue inhibitor of metalloproteinase-1 (TIMP-1) on the mosaic of cones in S334ter-line-3 rat retinas. We focused on TIMP-1 because it is one of the regulators of the extracellular matrix important for cellular migration. Methods. Immunohistochemistry was performed to reveal M-opsin cone cells (M-cone) and the results were quantified to test statistically whether or not TIMP-1 restores the mosaics to normal. In particular, the tests focused on the Voronoi and nearest-neighbor distance analyses. Results. Our tests indicated that TIMP-1 led to significant disruption of the M-opsin cone rings in S334ter-line-3 rat retinas and resulted in almost complete homogeneous mosaics. In addition, TIMP-1 induced the M-cone spatial distribution to become closer to random with decreased regularity in S334ter-line-3 rat retinas. Conclusions. These findings confirm that TIMP-1 induced M-cone mosaics in S334ter-line-3 to gain homogeneity without reaching the degree of regularity seen in normal retinal mosaics. Even if TIMP-1 fails to promote regularity, the effects of this drug on homogeneity appear to be so dramatic that TIMP-1 may be a potential therapeutic agent. TIMP-1 improves sampling of the visual field simply by causing homogeneity. PMID:25515575

Modeling the Internal Kinematics (Rotation and Dispersion) of Distant Galaxies (z ~ 1.0) Using Multi-PA Keck DEIMOS Slit Spectra

NASA Astrophysics Data System (ADS)

Miao, Connie; Chen, Jerry; Torres Hernandez, Jose; Guhathakurta, Puragra; Jang, Hyerin

2017-01-01

The stark difference between the chaotic internal motion of distant galaxies and the ordered rotation of typical local spiral galaxies suggests that disordered galaxies at high redshifts (i.e., early times in the Universe's history) gradually settle into well ordered disk morphologies with ordered rotation. We have used slit spectra obtained with Keck DEIMOS at four different position angles for 133 distant objects (z ~ 1.0) in the GOODS-N field. The emission lines in the 2D spectra of the galaxies were used to calculate the redshift/velocity at each spatial location. For each slit row, the distribution of flux over velocity was modeled as a Gaussian curve from which we obtained the radial velocity and spread of radial velocity. Rotation curves and velocity dispersions for each galaxy at each slit angle were plotted at these values. We qualitatively classified galaxies as regularly rotating, merging, face-on, or unable to be determined by examining overlays of the rotation curves from the four slit angles. We found that regular rotating galaxies tended to have peak velocity dispersion at the center while mergers had fairly constant velocity dispersions. Face-on galaxies had chaotic and inconsistent velocity dispersions between different slit angles. Regularly rotation galaxies represented 45% of our sample and mergers represented 27%. The relative percentage of galaxies that were either regularly rotating or mergers roughly matched those of the literature. This research was supported by NASA and the National Science Foundation. Most of this work was carried out by high school students working under the auspices of the Science Internship Program at UC Santa Cruz.

Spatial distribution and concentration of sulfur in relation to vegetation cover and soil properties on a reclaimed sulfur mine site (Southern Poland).

PubMed

Likus-Cieślik, Justyna; Pietrzykowski, Marcin; Szostak, Marta; Szulczewski, Melanie

2017-02-01

This work aims to assess the spatial distribution and concentration of sulfur in the topsoil layer and to determine the relationships between sulfur concentration, soil pH, soil electrical conductivity, and plant cover at the reforested site of the former sulfur mine (Southern Poland). Soil samples were collected from 0 to 20 cm (topsoil) from a total of 86 sampling points in a regular square grid with sides of 150 m. Plant cover was assayed in circular plots with an area of 100 m 2 , divided into a woody plant layer and herbaceous plant layer. Soil properties such as particle size distribution, pH in KCl and H 2 O, soil electrical conductivity (EC), soil organic carbon (SOC), total nitrogen (N T ), and total sulfur (S T ) were determined. The degree of soil contamination with sulfur was assessed based on the guidelines of the Institute of Soil Science and Plant Cultivation (IUNG), Poland. The results indicate that remediation and application of lime were not fully effective in spatial variation, because 33 points with sulfur contamination above 500 mg kg -1 were observed. These spots occurred irregularly in the topsoil horizons. This high sulfur concentration in the soil did not result in severe acidification (below 4.5) in all cases, most likely due to neutralization from the application of high doses of flotation lime. High vegetative cover occurred at some points with high soil sulfur concentrations, with two points having S concentration above 40,000 mg kg -1 and tree cover about 60%. Numerous points with high soil EC above 1500 μS cm -1 as well as limited vegetation and high soil sulfur concentrations, however, indicate that the reclamation to forest is still not completely successful.

Learning spatially coherent properties of the visual world in connectionist networks

NASA Astrophysics Data System (ADS)

Becker, Suzanna; Hinton, Geoffrey E.

1991-10-01

In the unsupervised learning paradigm, a network of neuron-like units is presented with an ensemble of input patterns from a structured environment, such as the visual world, and learns to represent the regularities in that input. The major goal in developing unsupervised learning algorithms is to find objective functions that characterize the quality of the network's representation without explicitly specifying the desired outputs of any of the units. The sort of objective functions considered cause a unit to become tuned to spatially coherent features of visual images (such as texture, depth, shading, and surface orientation), by learning to predict the outputs of other units which have spatially adjacent receptive fields. Simulations show that using an information-theoretic algorithm called IMAX, a network can be trained to represent depth by observing random dot stereograms of surfaces with continuously varying disparities. Once a layer of depth-tuned units has developed, subsequent layers are trained to perform surface interpolation of curved surfaces, by learning to predict the depth of one image region based on depth measurements in surrounding regions. An extension of the basic model allows a population of competing neurons to learn a distributed code for disparity, which naturally gives rise to a representation of discontinuities.

Clusters in irregular areas and lattices.

PubMed

Wieczorek, William F; Delmerico, Alan M; Rogerson, Peter A; Wong, David W S

2012-01-01

Geographic areas of different sizes and shapes of polygons that represent counts or rate data are often encountered in social, economic, health, and other information. Often political or census boundaries are used to define these areas because the information is available only for those geographies. Therefore, these types of boundaries are frequently used to define neighborhoods in spatial analyses using geographic information systems and related approaches such as multilevel models. When point data can be geocoded, it is possible to examine the impact of polygon shape on spatial statistical properties, such as clustering. We utilized point data (alcohol outlets) to examine the issue of polygon shape and size on visualization and statistical properties. The point data were allocated to regular lattices (hexagons and squares) and census areas for zip-code tabulation areas and tracts. The number of units in the lattices was set to be similar to the number of tract and zip-code areas. A spatial clustering statistic and visualization were used to assess the impact of polygon shape for zip- and tract-sized units. Results showed substantial similarities and notable differences across shape and size. The specific circumstances of a spatial analysis that aggregates points to polygons will determine the size and shape of the areal units to be used. The irregular polygons of census units may reflect underlying characteristics that could be missed by large regular lattices. Future research to examine the potential for using a combination of irregular polygons and regular lattices would be useful.

Speckle-based three-dimensional velocity measurement using spatial filtering velocimetry.

PubMed

Iversen, Theis F Q; Jakobsen, Michael L; Hanson, Steen G

2011-04-10

We present an optical method for measuring the real-time three-dimensional (3D) translational velocity of a diffusely scattering rigid object observed through an imaging system. The method is based on a combination of the motion of random speckle patterns and regular fringe patterns. The speckle pattern is formed in the observation plane of the imaging system due to reflection from an area of the object illuminated by a coherent light source. The speckle pattern translates in response to in-plane translation of the object, and the presence of an angular offset reference wave coinciding with the speckle pattern in the observation plane gives rise to interference, resulting in a fringe pattern that translates in response to the out-of-plane translation of the object. Numerical calculations are performed to evaluate the dynamic properties of the intensity distribution and the response of realistic spatial filters designed to measure the three components of the object's translational velocity. Furthermore, experimental data are presented that demonstrate full 3D velocity measurement. © 2011 Optical Society of America

Multiplexed phase-space imaging for 3D fluorescence microscopy.

PubMed

Liu, Hsiou-Yuan; Zhong, Jingshan; Waller, Laura

2017-06-26

Optical phase-space functions describe spatial and angular information simultaneously; examples of optical phase-space functions include light fields in ray optics and Wigner functions in wave optics. Measurement of phase-space enables digital refocusing, aberration removal and 3D reconstruction. High-resolution capture of 4D phase-space datasets is, however, challenging. Previous scanning approaches are slow, light inefficient and do not achieve diffraction-limited resolution. Here, we propose a multiplexed method that solves these problems. We use a spatial light modulator (SLM) in the pupil plane of a microscope in order to sequentially pattern multiplexed coded apertures while capturing images in real space. Then, we reconstruct the 3D fluorescence distribution of our sample by solving an inverse problem via regularized least squares with a proximal accelerated gradient descent solver. We experimentally reconstruct a 101 Megavoxel 3D volume (1010×510×500µm with NA 0.4), demonstrating improved acquisition time, light throughput and resolution compared to scanning aperture methods. Our flexible patterning scheme further allows sparsity in the sample to be exploited for reduced data capture.

Scale-free correlations in the geographical spreading of obesity

NASA Astrophysics Data System (ADS)

Gallos, Lazaros; Barttfeld, Pablo; Havlin, Shlomo; Sigman, Mariano; Makse, Hernan

2012-02-01

Obesity levels have been universally increasing. A crucial problem is to determine the influence of global and local drivers behind the obesity epidemic, to properly guide effective policies. Despite the numerous factors that affect the obesity evolution, we show a remarkable regularity expressed in a predictable pattern of spatial long-range correlations in the geographical spreading of obesity. We study the spatial clustering of obesity and a number of related health and economic indicators, and we use statistical physics methods to characterize the growth of the resulting clusters. The resulting scaling exponents allow us to broadly classify these indicators into two separate universality classes, weakly or strongly correlated. Weak correlations are found in generic human activity such as population distribution and the growth of the whole economy. Strong correlations are recovered, among others, for obesity, diabetes, and the food industry sectors associated with food consumption. Obesity turns out to be a global problem where local details are of little importance. The long-range correlations suggest influence that extends to large scales, hinting that the physical model of obesity clustering can be mapped to a long-range correlated percolation process.

Sampling characteristics of satellite orbits

NASA Technical Reports Server (NTRS)

Wunsch, Carl

1989-01-01

The irregular space-time sampling of any finite region by an orbiting satellite raises difficult questions as to which frequencies and wavenumbers can be determined and which will alias into others. Conventional sampling theorems must be extended to account for both irregular data distributions and observational noise - the sampling irregularity making the system much more susceptible to noise than in regularly sampled cases. The problem is formulated here in terms of least-squares and applied to spacecraft in 10-day and 17-day repeating orbits. The 'diamond-pattern' laid down spatially in such repeating orbits means that either repeat period adequately samples the spatial variables, but the slow overall temporal coverage in the 17-day pattern leads to much greater uncertainty than in the shorter repeat cycle. The result is not definitive and it is not concluded that a 10-day orbit repeat is the most appropriate one. A major conclusion, however, is that different orbital choices have potentially quite different sampling characteristics which need to be analyzed in terms of the spectral characteristics of the moving sea surface.

Contrasting patterns of fine-scale herb layer species composition in temperate forests

NASA Astrophysics Data System (ADS)

Chudomelová, Markéta; Zelený, David; Li, Ching-Feng

2017-04-01

Although being well described at the landscape level, patterns in species composition of forest herb layer are rarely studied at smaller scales. Here, we examined fine-scale environmental determinants and spatial structures of herb layer communities in thermophilous oak- and hornbeam dominated forests of the south-eastern part of the Czech Republic. Species composition of herb layer vegetation and environmental variables were recorded within a fixed grid of 2 × 2 m subplots regularly distributed within 1-ha quadrate plots in three forest stands. For each site, environmental models best explaining species composition were constructed using constrained ordination analysis. Spatial eigenvector mapping was used to model and account for spatial structures in community variation. Mean Ellenberg indicator values calculated for each subplot were used for ecological interpretation of spatially structured residual variation. The amount of variation explained by environmental and spatial models as well as the selection of variables with the best explanatory power differed among sites. As an important environmental factor, relative elevation was common to all three sites, while pH and canopy openness were shared by two sites. Both environmental and community variation was mostly coarse-scaled, as was the spatially structured portion of residual variation. When corrected for bias due to spatial autocorrelation, those environmental factors with already weak explanatory power lost their significance. Only a weak evidence of possibly omitted environmental predictor was found for autocorrelated residuals of site models using mean Ellenberg indicator values. Community structure was determined by different factors at different sites. The relative importance of environmental filtering vs. spatial processes was also site specific, implying that results of fine-scale studies tend to be shaped by local conditions. Contrary to expectations based on other studies, overall dominance of spatial processes at fine scale has not been detected. Ecologists should keep this in mind when making generalizations about community dynamics.

Markov Chain Monte Carlo estimation of species distributions: a case study of the swift fox in western Kansas

USGS Publications Warehouse

Sargeant, Glen A.; Sovada, Marsha A.; Slivinski, Christiane C.; Johnson, Douglas H.

2005-01-01

Accurate maps of species distributions are essential tools for wildlife research and conservation. Unfortunately, biologists often are forced to rely on maps derived from observed occurrences recorded opportunistically during observation periods of variable length. Spurious inferences are likely to result because such maps are profoundly affected by the duration and intensity of observation and by methods used to delineate distributions, especially when detection is uncertain. We conducted a systematic survey of swift fox (Vulpes velox) distribution in western Kansas, USA, and used Markov chain Monte Carlo (MCMC) image restoration to rectify these problems. During 1997–1999, we searched 355 townships (ca. 93 km) 1–3 times each for an average cost of $7,315 per year and achieved a detection rate (probability of detecting swift foxes, if present, during a single search) of = 0.69 (95% Bayesian confidence interval [BCI] = [0.60, 0.77]). Our analysis produced an estimate of the underlying distribution, rather than a map of observed occurrences, that reflected the uncertainty associated with estimates of model parameters. To evaluate our results, we analyzed simulated data with similar properties. Results of our simulations suggest negligible bias and good precision when probabilities of detection on ≥1 survey occasions (cumulative probabilities of detection) exceed 0.65. Although the use of MCMC image restoration has been limited by theoretical and computational complexities, alternatives do not possess the same advantages. Image models accommodate uncertain detection, do not require spatially independent data or a census of map units, and can be used to estimate species distributions directly from observations without relying on habitat covariates or parameters that must be estimated subjectively. These features facilitate economical surveys of large regions, the detection of temporal trends in distribution, and assessments of landscape-level relations between species and habitats. Requirements for the use of MCMC image restoration include study areas that can be partitioned into regular grids of mapping units, spatially contagious species distributions, reliable methods for identifying target species, and cumulative probabilities of detection ≥0.65.

Markov chain Monte Carlo estimation of species distributions: A case study of the swift fox in western Kansas

USGS Publications Warehouse

Sargeant, G.A.; Sovada, M.A.; Slivinski, C.C.; Johnson, D.H.

2005-01-01

Accurate maps of species distributions are essential tools for wildlife research and conservation. Unfortunately, biologists often are forced to rely on maps derived from observed occurrences recorded opportunistically during observation periods of variable length. Spurious inferences are likely to result because such maps are profoundly affected by the duration and intensity of observation and by methods used to delineate distributions, especially when detection is uncertain. We conducted a systematic survey of swift fox (Vulpes velox) distribution in western Kansas, USA, and used Markov chain Monte Carlo (MCMC) image restoration to rectify these problems. During 1997-1999, we searched 355 townships (ca. 93 km2) 1-3 times each for an average cost of $7,315 per year and achieved a detection rate (probability of detecting swift foxes, if present, during a single search) of ?? = 0.69 (95% Bayesian confidence interval [BCI] = [0.60, 0.77]). Our analysis produced an estimate of the underlying distribution, rather than a map of observed occurrences, that reflected the uncertainty associated with estimates of model parameters. To evaluate our results, we analyzed simulated data with similar properties. Results of our simulations suggest negligible bias and good precision when probabilities of detection on ???1 survey occasions (cumulative probabilities of detection) exceed 0.65. Although the use of MCMC image restoration has been limited by theoretical and computational complexities, alternatives do not possess the same advantages. Image models accommodate uncertain detection, do not require spatially independent data or a census of map units, and can be used to estimate species distributions directly from observations without relying on habitat covariates or parameters that must be estimated subjectively. These features facilitate economical surveys of large regions, the detection of temporal trends in distribution, and assessments of landscape-level relations between species and habitats. Requirements for the use of MCMC image restoration include study areas that can be partitioned into regular grids of mapping units, spatially contagious species distributions, reliable methods for identifying target species, and cumulative probabilities of detection ???0.65.

Micro-polarimetry for pre-clinical diagnostics of pathological changes in human tissues

NASA Astrophysics Data System (ADS)

Golnik, Andrzej; Golnik, Natalia; Pałko, Tadeusz; Sołtysiński, Tomasz

2008-05-01

The paper presents a practical study of several methods of image analysis applied to polarimetric images of regular and malignant human tissues. The images of physiological and pathologically changed tissues from body and cervix of uterus, intestine, kidneys and breast were recorded in transmitted light of different polarization state. The set up of the conventional optical microscope with CCD camera and rotating polarizer's were used for analysis of the polarization state of the light transmitted through the tissue slice for each pixel of the camera image. The set of images corresponding to the different coefficients of the Stockes vectors, a 3×3 subset of the Mueller matrix as well as the maps of the magnitude and in-plane direction of the birefringent components in the sample were calculated. Then, the statistical analysis and the Fourier transform as well as the autocorrelation methods were used to analyze spatial distribution of birefringent elements in the tissue samples. For better recognition of tissue state we proposed a novel method that takes advantage of multiscale image data decomposition The results were used for selection of the optical characteristics with significantly different values for regular and malignant tissues.

On the acoustic radiation modes of compact regular polyhedral arrays of independent loudspeakers.

PubMed

Pasqual, Alexander Mattioli; Martin, Vincent

2011-09-01

Compact spherical loudspeaker arrays can be used to provide control over their directivity pattern. Usually, this is made by adjusting the gains of preprogrammed spatial filters corresponding to a finite set of spherical harmonics, or to the acoustic radiation modes of the loudspeaker array. Unlike the former, the latter are closely related to the radiation efficiency of the source and span the subspace of the directivities it can produce. However, the radiation modes depend on frequency for arbitrary distributions of transducers on the sphere, which yields complex directivity filters. This work focuses on the most common loudspeaker array configurations, those following the regular shape of the Platonic solids. It is shown that the radiation modes of these sources are frequency independent, and simple algebraic expressions are derived for their radiation efficiencies. In addition, since such modes are vibration patterns driven by electrical signals, the transduction mechanism of compact multichannel sources is also investigated, which is an important issue, especially if the transducers interact inside a shared cabinet. For Platonic solid loudspeakers, it is shown that the common enclosure does not lead to directivity filters that depend on frequency. © 2011 Acoustical Society of America

Efficient L1 regularization-based reconstruction for fluorescent molecular tomography using restarted nonlinear conjugate gradient.

PubMed

Shi, Junwei; Zhang, Bin; Liu, Fei; Luo, Jianwen; Bai, Jing

2013-09-15

For the ill-posed fluorescent molecular tomography (FMT) inverse problem, the L1 regularization can protect the high-frequency information like edges while effectively reduce the image noise. However, the state-of-the-art L1 regularization-based algorithms for FMT reconstruction are expensive in memory, especially for large-scale problems. An efficient L1 regularization-based reconstruction algorithm based on nonlinear conjugate gradient with restarted strategy is proposed to increase the computational speed with low memory consumption. The reconstruction results from phantom experiments demonstrate that the proposed algorithm can obtain high spatial resolution and high signal-to-noise ratio, as well as high localization accuracy for fluorescence targets.

Periodicity in spatial data and geostatistical models: autocorrelation between patches

Treesearch

Volker C. Radeloff; Todd F. Miller; Hong S. He; David J. Mladenoff

2000-01-01

Several recent studies in landscape ecology have found periodicity in correlograms or semi-variograms calculated, for instance, from spatial data of soils, forests, or animal populations. Some of the studies interpreted this as an indication of regular or periodic landscape patterns. This interpretation is in disagreement with other studies that doubt whether such...

Least squares reconstruction of non-linear RF phase encoded MR data.

PubMed

Salajeghe, Somaie; Babyn, Paul; Sharp, Jonathan C; Sarty, Gordon E

2016-09-01

The numerical feasibility of reconstructing MRI signals generated by RF coils that produce B1 fields with a non-linearly varying spatial phase is explored. A global linear spatial phase variation of B1 is difficult to produce from current confined to RF coils. Here we use regularized least squares inversion, in place of the usual Fourier transform, to reconstruct signals generated in B1 fields with non-linear phase variation. RF encoded signals were simulated for three RF coil configurations: ideal linear, parallel conductors and, circular coil pairs. The simulated signals were reconstructed by Fourier transform and by regularized least squares. The Fourier reconstruction of simulated RF encoded signals from the parallel conductor coil set showed minor distortions over the reconstruction of signals from the ideal linear coil set but the Fourier reconstruction of signals from the circular coil set produced severe geometric distortion. Least squares inversion in all cases produced reconstruction errors comparable to the Fourier reconstruction of the simulated signal from the ideal linear coil set. MRI signals encoded in B1 fields with non-linearly varying spatial phase may be accurately reconstructed using regularized least squares thus pointing the way to the use of simple RF coil designs for RF encoded MRI. Crown Copyright © 2016. Published by Elsevier Inc. All rights reserved.

Photoacoustic tomography guided diffuse optical tomography for small-animal model

NASA Astrophysics Data System (ADS)

Wang, Yihan; Gao, Feng; Wan, Wenbo; Zhang, Yan; Li, Jiao

2015-03-01

Diffuse optical tomography (DOT) is a biomedical imaging technology for noninvasive visualization of spatial variation about the optical properties of tissue, which can be applied to in vivo small-animal disease model. However, traditional DOT suffers low spatial resolution due to tissue scattering. To overcome this intrinsic shortcoming, multi-modal approaches that incorporate DOT with other imaging techniques have been intensively investigated, where a priori information provided by the other modalities is normally used to reasonably regularize the inverse problem of DOT. Nevertheless, these approaches usually consider the anatomical structure, which is different from the optical structure. Photoacoustic tomography (PAT) is an emerging imaging modality that is particularly useful for visualizing lightabsorbing structures embedded in soft tissue with higher spatial resolution compared with pure optical imaging. Thus, we present a PAT-guided DOT approach, to obtain the location a priori information of optical structure provided by PAT first, and then guide DOT to reconstruct the optical parameters quantitatively. The results of reconstruction of phantom experiments demonstrate that both quantification and spatial resolution of DOT could be highly improved by the regularization of feasible-region information provided by PAT.

A highly ordered mesostructured material containing regularly distributed phenols: preparation and characterization at a molecular level through ultra-fast magic angle spinning proton NMR spectroscopy.

PubMed

Roussey, Arthur; Gajan, David; Maishal, Tarun K; Mukerjee, Anhurada; Veyre, Laurent; Lesage, Anne; Emsley, Lyndon; Copéret, Christophe; Thieuleux, Chloé

2011-03-14

Highly ordered organic-inorganic mesostructured material containing regularly distributed phenols is synthesized by combining a direct synthesis of the functional material and a protection-deprotection strategy and characterized at a molecular level through ultra-fast magic angle spinning proton NMR spectroscopy.

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

NASA Technical Reports Server (NTRS)

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

2014-01-01

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

On Spatially Explicit Models of Cholera Epidemics: Hydrologic controls, environmental drivers, human-mediated transmissions (Invited)

NASA Astrophysics Data System (ADS)

Rinaldo, A.; Bertuzzo, E.; Mari, L.; Righetto, L.; Gatto, M.; Casagrandi, R.; Rodriguez-Iturbe, I.

2010-12-01

A recently proposed model for cholera epidemics is examined. The model accounts for local communities of susceptibles and infectives in a spatially explicit arrangement of nodes linked by networks having different topologies. The vehicle of infection (Vibrio cholerae) is transported through the network links which are thought of as hydrological connections among susceptible communities. The mathematical tools used are borrowed from general schemes of reactive transport on river networks acting as the environmental matrix for the circulation and mixing of water-borne pathogens. The results of a large-scale application to the Kwa Zulu (Natal) epidemics of 2001-2002 will be discussed. Useful theoretical results derived in the spatially-explicit context will also be reviewed (like e.g. the exact derivation of the speed of propagation for traveling fronts of epidemics on regular lattices endowed with uniform population density). Network effects will be discussed. The analysis of the limit case of uniformly distributed population density proves instrumental in establishing the overall conditions for the relevance of spatially explicit models. To that extent, it is shown that the ratio between spreading and disease outbreak timescales proves the crucial parameter. The relevance of our results lies in the major differences potentially arising between the predictions of spatially explicit models and traditional compartmental models of the SIR-like type. Our results suggest that in many cases of real-life epidemiological interest timescales of disease dynamics may trigger outbreaks that significantly depart from the predictions of compartmental models. Finally, a view on further developments includes: hydrologically improved aquatic reservoir models for pathogens; human mobility patterns affecting disease propagation; double-peak emergence and seasonality in the spatially explicit epidemic context.

Scale-free network provides an optimal pattern for knowledge transfer

NASA Astrophysics Data System (ADS)

Lin, Min; Li, Nan

2010-02-01

We study numerically the knowledge innovation and diffusion process on four representative network models, such as regular networks, small-world networks, random networks and scale-free networks. The average knowledge stock level as a function of time is measured and the corresponding growth diffusion time, τ is defined and computed. On the four types of networks, the growth diffusion times all depend linearly on the network size N as τ∼N, while the slope for scale-free network is minimal indicating the fastest growth and diffusion of knowledge. The calculated variance and spatial distribution of knowledge stock illustrate that optimal knowledge transfer performance is obtained on scale-free networks. We also investigate the transient pattern of knowledge diffusion on the four networks, and a qualitative explanation of this finding is proposed.

Simulation of noisy dynamical system by Deep Learning

NASA Astrophysics Data System (ADS)

Yeo, Kyongmin

2017-11-01

Deep learning has attracted huge attention due to its powerful representation capability. However, most of the studies on deep learning have been focused on visual analytics or language modeling and the capability of the deep learning in modeling dynamical systems is not well understood. In this study, we use a recurrent neural network to model noisy nonlinear dynamical systems. In particular, we use a long short-term memory (LSTM) network, which constructs internal nonlinear dynamics systems. We propose a cross-entropy loss with spatial ridge regularization to learn a non-stationary conditional probability distribution from a noisy nonlinear dynamical system. A Monte Carlo procedure to perform time-marching simulations by using the LSTM is presented. The behavior of the LSTM is studied by using noisy, forced Van der Pol oscillator and Ikeda equation.

Incoherent light-induced self-organization of molecules.

PubMed

Kandjani, S Ahmadi; Barille, R; Dabos-Seignon, S; Nunzi, J M; Ortyl, E; Kucharski, S

2005-12-01

Although coherent light is usually required for the self-organization of regular spatial patterns from optical beams, we show that peculiar light-matter interaction can break this evidence. In the traditional method of recording laser-induced periodic surface structures, a light intensity distribution is produced at the surface of a polymer film by an interference between two coherent optical beams. We report on the self-organization followed by propagation of a surface relief pattern. It is induced in a polymer film by using a low-power and small-size coherent beam assisted by a high-power and large-size incoherent and unpolarized beam. We demonstrate that we can obtain large size and well-organized patterns starting from a dissipative interaction. Our experiments open new directions to improving optical processing systems.

Patterns of Precipitation and Streamflow Responses to Moisture Fluxes during Atmospheric Rivers

NASA Astrophysics Data System (ADS)

Henn, B. M.; Wilson, A. M.; Asgari Lamjiri, M.; Ralph, M.

2017-12-01

Precipitation from landfalling atmospheric rivers (ARs) have been shown to dominate the hydroclimate of many parts of the world. ARs are associated with saturated, neutrally-stable profiles in the lower atmosphere, in which forced ascent by topography induces precipitation. Understanding the spatial and temporal variability of precipitation over complex terrain during AR-driven precipitation is critical for accurate forcing of distributed hydrologic models and streamflow forecasts. Past studies using radar wind profilers and radiosondes have demonstrated predictability of precipitation rates based on upslope water vapor flux over coastal terrain, with certain levels of moisture flux exhibiting the greatest influence on precipitation. Additionally, these relationships have been extended to show that streamflow in turn responds predictably to upslope vapor flux. However, past studies have focused on individual pairs of profilers and precipitation gauges; the question of how orographic precipitation in ARs is distributed spatially over complex terrain, at different topographic scales, is less well known. Here, we examine profiles of atmospheric moisture transport from radiosondes and wind profilers, against a relatively dense network of precipitation gauges, as well as stream gauges, to assess relationships between upslope moisture flux and the spatial response of precipitation and streamflow. We focus on California's Russian River watershed in the 2016-2017 cool season, when regular radiosonde launches were made at two locations during an active sequence of landfalling ARs. We examine how atmospheric water vapor flux results in precipitation patterns across gauges with different topographic relationships to the prevailing moisture-bearing winds, and conduct a similar comparison of runoff volume response from several unimpaired watersheds in the upper Russian watershed, taking into account antecedent soil moisture conditions that influence runoff generation. Finally, we compare observed spatial patterns of precipitation accumulations to those in a topographically-aided gridded precipitation dataset to understand how atmospheric moisture transport may inform methods to downscale precipitation to high resolution for use in hydrologic modeling.

Radiocesium distribution along the slope in the Iput river basin as a tracer of the contaminant secondary migration

NASA Astrophysics Data System (ADS)

Korobova, Elena; Romanov, Sergey; Beriozkin, Victor; Dogadkin, Nikolay

2016-04-01

The main goal of the study performed in 2014-2015 at the test site located in the abandoned zone of the Iput river basin was to study detailed patterns of Cs-137 redistribution along the terrace slope and the adjacent floodplain depression almost 30 years after the Chernobyl accident. Cs-137 surface activity was measured with the help of modified field gamma-spectrometer Violinist III (USA) in a grid 2 m x 2 m within the test plot sized 10 m x 24 m. Gamma-spectrometry was accompanied by topographical survey. Cs-137 depth distribution was studied by soil core sampling in increments of 2 cm and 5 cm down to 40 cm depth. Cs-137 activity in soil samples was measured in laboratory conditions by Nokia gamma-spectrometer. The results showed distinct natural dissimilarity of Cs-137 surface activity within the undisturbed soil of slope. Cs-137 depth migration in successive soil cores marked different patterns correlated with the position in relief. In particular cores Cs-137 depth variation correlated with water regime that shows that the processes of secondary distribution of Cs-137 along the slope obviously depend upon water migration. The finding is important for understanding of regularities in patterns of radiocesium spatial distribution.

Effect of variable soil texture, metal saturation of soil organic matter (SOM) and tree species composition on spatial distribution of SOM in forest soils in Poland.

PubMed

Gruba, Piotr; Socha, Jarosław; Błońska, Ewa; Lasota, Jarosław

2015-07-15

In this study we investigated the effect of fine (ϕ<0.05mm) fraction, i.e., silt+clay (FF) content in soils, site moisture, metal (Al and Fe) of soil organic matter (SOM) and forest species composition on the spatial distribution of carbon (C) pools in forest soils at the landscape scale. We established 275 plots in regular 200×200m grid in a forested area of 14.4km(2). Fieldwork included soil sampling of the organic horizon, mineral topsoil and subsoil down to 40cm deep. We analysed the vertical and horizontal distribution of soil organic carbon (SOC) stocks, as well as the quantity of physically separated fractions including the free light (fLF), occluded light (oLF) and mineral associated fractions (MAF) in the mineral topsoil (A, AE) horizons. Distribution of C in soils was predominantly affected by the variation in the FF content. In soils richer in the FF more SOC was accumulated in mineral horizons and less in the organic horizons. Accumulation of SOC in mineral soil was also positively affected by the degree of saturation of SOM with Al and Fe. The increasing share of beech influenced the distribution of C stock in soil profiles by reducing the depth of O horizon and increasing C stored in mineral soil. The content of FF was positively correlated with the content of C in MAF and fLF fractions. The content of oLF and MAF fractions was also positively influenced by a higher degree of metal saturation, particularly Al. Our results confirmed that Al plays an important role in the stabilization of SOM inside aggregates (CoLF) and as in CMAF fractions. We also found a significant, positive effect of beech on the CfLF and fir on the CoLF content. Copyright © 2015 Elsevier B.V. All rights reserved.

Regularity of a renewal process estimated from binary data.

PubMed

Rice, John D; Strawderman, Robert L; Johnson, Brent A

2017-10-09

Assessment of the regularity of a sequence of events over time is important for clinical decision-making as well as informing public health policy. Our motivating example involves determining the effect of an intervention on the regularity of HIV self-testing behavior among high-risk individuals when exact self-testing times are not recorded. Assuming that these unobserved testing times follow a renewal process, the goals of this work are to develop suitable methods for estimating its distributional parameters when only the presence or absence of at least one event per subject in each of several observation windows is recorded. We propose two approaches to estimation and inference: a likelihood-based discrete survival model using only time to first event; and a potentially more efficient quasi-likelihood approach based on the forward recurrence time distribution using all available data. Regularity is quantified and estimated by the coefficient of variation (CV) of the interevent time distribution. Focusing on the gamma renewal process, where the shape parameter of the corresponding interevent time distribution has a monotone relationship with its CV, we conduct simulation studies to evaluate the performance of the proposed methods. We then apply them to our motivating example, concluding that the use of text message reminders significantly improves the regularity of self-testing, but not its frequency. A discussion on interesting directions for further research is provided. © 2017, The International Biometric Society.

Multipole Vortex Blobs (MVB): Symplectic Geometry and Dynamics.

PubMed

Holm, Darryl D; Jacobs, Henry O

2017-01-01

Vortex blob methods are typically characterized by a regularization length scale, below which the dynamics are trivial for isolated blobs. In this article, we observe that the dynamics need not be trivial if one is willing to consider distributional derivatives of Dirac delta functionals as valid vorticity distributions. More specifically, a new singular vortex theory is presented for regularized Euler fluid equations of ideal incompressible flow in the plane. We determine the conditions under which such regularized Euler fluid equations may admit vorticity singularities which are stronger than delta functions, e.g., derivatives of delta functions. We also describe the symplectic geometry associated with these augmented vortex structures, and we characterize the dynamics as Hamiltonian. Applications to the design of numerical methods similar to vortex blob methods are also discussed. Such findings illuminate the rich dynamics which occur below the regularization length scale and enlighten our perspective on the potential for regularized fluid models to capture multiscale phenomena.

Ecological Vulnerability Assessment Based on Fuzzy Analytical Method and Analytic Hierarchy Process in Yellow River Delta.

PubMed

Wu, Chunsheng; Liu, Gaohuan; Huang, Chong; Liu, Qingsheng; Guan, Xudong

2018-04-25

The Yellow River Delta (YRD), located in Yellow River estuary, is characterized by rich ecological system types, and provides habitats or migration stations for wild birds, all of which makes the delta an ecological barrier or ecotone for inland areas. Nevertheless, the abundant natural resources of YRD have brought huge challenges to the area, and frequent human activities and natural disasters have damaged the ecological systems seriously, and certain ecological functions have been threatened. Therefore, it is necessary to determine the status of the ecological environment based on scientific methods, which can provide scientifically robust data for the managers or stakeholders to adopt timely ecological protection measures. The aim of this study was to obtain the spatial distribution of the ecological vulnerability (EV) in YRD based on 21 indicators selected from underwater status, soil condition, land use, landform, vegetation cover, meteorological conditions, ocean influence, and social economy. In addition, the fuzzy analytic hierarchy process (FAHP) method was used to obtain the weights of the selected indicators, and a fuzzy logic model was constructed to obtain the result. The result showed that the spatial distribution of the EV grades was regular, while the fuzzy membership of EV decreased gradually from the coastline to inland area, especially around the river crossing, where it had the lowest EV. Along the coastline, the dikes had an obviously protective effect for the inner area, while the EV was higher in the area where no dikes were built. This result also showed that the soil condition and groundwater status were highly related to the EV spatially, with the correlation coefficients −0.55 and −0.74 respectively, and human activities had exerted considerable pressure on the ecological environment.

Towards a consistent framework to oversample multi-sensors, multi-species satellite data into a common grid

NASA Astrophysics Data System (ADS)

Sun, K.; Zhu, L.; Gonzalez Abad, G.; Nowlan, C. R.; Miller, C. E.; Huang, G.; Liu, X.; Chance, K.; Yang, K.

2017-12-01

It has been well demonstrated that regridding Level 2 products (satellite observations from individual footprints, or pixels) from multiple sensors/species onto regular spatial and temporal grids makes the data more accessible for scientific studies and can even lead to additional discoveries. However, synergizing multiple species retrieved from multiple satellite sensors faces many challenges, including differences in spatial coverage, viewing geometry, and data filtering criteria. These differences will lead to errors and biases if not treated carefully. Operational gridded products are often at 0.25°×0.25° resolution with a global scale, which is too coarse for local heterogeneous emission sources (e.g., urban areas), and at fixed temporal intervals (e.g., daily or monthly). We propose a consistent framework to fully use and properly weight the information of all possible individual satellite observations. A key aspect of this work is an accurate knowledge of the spatial response function (SRF) of the satellite Level 2 pixels. We found that the conventional overlap-area-weighting method (tessellation) is accurate only when the SRF is homogeneous within the parameterized pixel boundary and zero outside the boundary. There will be a tessellation error if the SRF is a smooth distribution, and if this distribution is not properly considered. On the other hand, discretizing the SRF at the destination grid will also induce errors. By balancing these error sources, we found that the SRF should be used in gridding OMI data to 0.2° for fine resolutions. Case studies by merging multiple species and wind data into 0.01° grid will be shown in the presentation.

Statistical Exploration of Local Transmission Routes for African Swine Fever in Pigs in the Russian Federation, 2007-2014.

PubMed

Vergne, T; Gogin, A; Pfeiffer, D U

2017-04-01

African swine fever (ASF) is a devastating viral disease of swine that is present in both pigs and wild boar in the western part of the Russian Federation and the eastern part of the European Union. It represents a significant threat for the European pig production industry as neither treatment nor vaccine is available. This study analysed the spatial and spatio-temporal distributions of ASF cases that were reported in domestic pigs and wild boar for assessing the likelihood of wild boar-to-domestic pig and farm-to-farm transmission routes in the epidemic that occurred from 2007 to 2014 in the Krasnodar and the Tver regions, two of the most affected areas of the Russian Federation. Results suggest that in both regions, the spatial proximity to an infectious farm was a strong risk factor for infection of a susceptible farm. In the Krasnodar region, the results of the statistical analysis suggest that the epidemics in wild boar and in domestic pigs were independent from each other. In contrast, there seemed to be a dependence between the two epidemics in the Tver region. But because outbreaks in domestic pigs were not statistically significantly clustered around wild boar cases, the joint spatial distribution of wild boar cases and of outbreaks in domestic pigs in the Tver region may be explained by regular spillovers from the domestic pig to the wild boar population. These findings confirm the need to maintain high biosecurity standards on pig farms and justify strict control measures targeted at domestic pig production such as culling of infected herds and local movement restrictions. © 2015 Blackwell Verlag GmbH.

Classification mapping and species identification of salt marshes based on a short-time interval NDVI time-series from HJ-1 optical imagery

NASA Astrophysics Data System (ADS)

Sun, Chao; Liu, Yongxue; Zhao, Saishuai; Zhou, Minxi; Yang, Yuhao; Li, Feixue

2016-03-01

Salt marshes are seen as the most dynamic and valuable ecosystems in coastal zones, and in these areas, it is crucial to obtain accurate remote sensing information on the spatial distributions of species over time. However, discriminating various types of salt marsh is rather difficult because of their strong spectral similarities. Previous salt marsh mapping studies have focused mainly on high spatial and spectral (i.e., hyperspectral) resolution images combined with auxiliary information; however, the results are often limited to small regions. With a high temporal and moderate spatial resolution, the Chinese HuanJing-1 (HJ-1) satellite optical imagery can be used not only to monitor phenological changes of salt marsh vegetation over short-time intervals, but also to obtain coverage of large areas. Here, we apply HJ-1 satellite imagery to the middle coast of Jiangsu in east China to monitor changes in saltmarsh vegetation cover. First, we constructed a monthly NDVI time-series to classify various types of salt marsh and then we tested the possibility of using compressed time-series continuously, to broaden the applicability of this particular approach. Our principal findings are as follows: (1) the overall accuracy of salt marsh mapping based on the monthly NDVI time-series was 90.3%, which was ∼16.0% higher than the single-phase classification strategy; (2) a compressed time-series, including NDVI from six key months (April, June-September, and November), demonstrated very little reduction (2.3%) in overall accuracy but led to obvious improvements in unstable regions; and (3) a simple rule for Spartina alterniflora identification was established using a scene solely from November, which may provide an effective way for regularly monitoring its distribution.

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.

Task-based statistical image reconstruction for high-quality cone-beam CT

NASA Astrophysics Data System (ADS)

Dang, Hao; Webster Stayman, J.; Xu, Jennifer; Zbijewski, Wojciech; Sisniega, Alejandro; Mow, Michael; Wang, Xiaohui; Foos, David H.; Aygun, Nafi; Koliatsos, Vassilis E.; Siewerdsen, Jeffrey H.

2017-11-01

Task-based analysis of medical imaging performance underlies many ongoing efforts in the development of new imaging systems. In statistical image reconstruction, regularization is often formulated in terms to encourage smoothness and/or sharpness (e.g. a linear, quadratic, or Huber penalty) but without explicit formulation of the task. We propose an alternative regularization approach in which a spatially varying penalty is determined that maximizes task-based imaging performance at every location in a 3D image. We apply the method to model-based image reconstruction (MBIR—viz., penalized weighted least-squares, PWLS) in cone-beam CT (CBCT) of the head, focusing on the task of detecting a small, low-contrast intracranial hemorrhage (ICH), and we test the performance of the algorithm in the context of a recently developed CBCT prototype for point-of-care imaging of brain injury. Theoretical predictions of local spatial resolution and noise are computed via an optimization by which regularization (specifically, the quadratic penalty strength) is allowed to vary throughout the image to maximize local task-based detectability index ({{d}\\prime} ). Simulation studies and test-bench experiments were performed using an anthropomorphic head phantom. Three PWLS implementations were tested: conventional (constant) penalty; a certainty-based penalty derived to enforce constant point-spread function, PSF; and the task-based penalty derived to maximize local detectability at each location. Conventional (constant) regularization exhibited a fairly strong degree of spatial variation in {{d}\\prime} , and the certainty-based method achieved uniform PSF, but each exhibited a reduction in detectability compared to the task-based method, which improved detectability up to ~15%. The improvement was strongest in areas of high attenuation (skull base), where the conventional and certainty-based methods tended to over-smooth the data. The task-driven reconstruction method presents a promising regularization method in MBIR by explicitly incorporating task-based imaging performance as the objective. The results demonstrate improved ICH conspicuity and support the development of high-quality CBCT systems.

A Comparison of the Pencil-of-Function Method with Prony’s Method, Wiener Filters and Other Identification Techniques,

DTIC Science & Technology

1977-12-01

exponentials encountered are complex and zhey are approximately at harmonic frequencies. Moreover, the real parts of the complex exponencials are much...functions as a basis for expanding the current distribution on an antenna by the method of moments results in a regularized ill-posed problem with respect...to the current distribution on the antenna structure. However, the problem is not regularized with respect to chaoge because the chaPge distribution

Circulation controls of the spatial structure of maximum daily precipitation over Poland

NASA Astrophysics Data System (ADS)

Stach, Alfred

2015-04-01

Among forecasts made on the basis of global and regional climatic models is one of a high probability of an increase in the frequency and intensity of extreme precipitation events. Learning the regularities underlying the recurrence and spatial extent of extreme precipitation is obviously of great importance, both economic and social. The main goal of the study was to analyse regularities underlying spatial and temporal variations in monthly Maximum Daily Precipitation Totals (MDPTs) observed in Poland over the years 1956-1980. These data are specific because apart from being spatially discontinuous, which is typical of precipitation, they are also non-synchronic. The main aim of the study was accomplished via several detailed goals: • identification and typology of the spatial structure of monthly MDPTs, • determination of the character and probable origin of events generating MDPTs, and • quantitative assessment of the contribution of the particular events to the overall MDPT figures. The analysis of the spatial structure of MDPTs was based on 300 models of spatial structure, one for each of the analysed sets of monthly MDPTs. The models were built on the basis of empirical anisotropic semivariograms of normalised data. In spite of their spatial discontinuity and asynchronicity, the MDPT data from Poland display marked regularities in their spatial pattern that yield readily to mathematical modelling. The MDPT field in Poland is usually the sum of the outcomes of three types of processes operating at various spatial scales: local (<10-20 km), regional (50-150 km), and supra-regional (>200 km). The spatial scales are probably connected with a convective/ orographic, a frontal and a 'planetary waves' genesis of high precipitation. Their contributions are highly variable. Generally predominant, however, are high daily precipitation totals with a spatial extent of 50 to 150 km connected with mesoscale phenomena and the migration of atmospheric fronts (35-38%). The spatial extent of areas of high local-scale precipitation usually varies at random, especially in the warm season. At supra-local scales, structures of repetitive size predominate. Eight types of anisotropic structures of monthly MDPTs were distinguished. To identify them, an analysis was made of semivariance surface similarities. The types differ not only in the level and direction of anisotropy, but also in the number and type of elementary components, which is evidence of genetic differences in precipitation. Their appearance shows a significant seasonal variability, so the most probable supposition was that temporal variations in the MDPT pattern were connected with circulation conditions: the type and direction of inflow of air masses. This hypothesis was validated by testing differences in the frequency of occurrence of Grosswetterlagen circulation situations in the months belonging to the distinguished types of the spatial MDPT pattern.

High spatial resolution compressed sensing (HSPARSE) functional MRI.

PubMed

Fang, Zhongnan; Van Le, Nguyen; Choy, ManKin; Lee, Jin Hyung

2016-08-01

To propose a novel compressed sensing (CS) high spatial resolution functional MRI (fMRI) method and demonstrate the advantages and limitations of using CS for high spatial resolution fMRI. A randomly undersampled variable density spiral trajectory enabling an acceleration factor of 5.3 was designed with a balanced steady state free precession sequence to achieve high spatial resolution data acquisition. A modified k-t SPARSE method was then implemented and applied with a strategy to optimize regularization parameters for consistent, high quality CS reconstruction. The proposed method improves spatial resolution by six-fold with 12 to 47% contrast-to-noise ratio (CNR), 33 to 117% F-value improvement and maintains the same temporal resolution. It also achieves high sensitivity of 69 to 99% compared the original ground-truth, small false positive rate of less than 0.05 and low hemodynamic response function distortion across a wide range of CNRs. The proposed method is robust to physiological noise and enables detection of layer-specific activities in vivo, which cannot be resolved using the highest spatial resolution Nyquist acquisition. The proposed method enables high spatial resolution fMRI that can resolve layer-specific brain activity and demonstrates the significant improvement that CS can bring to high spatial resolution fMRI. Magn Reson Med 76:440-455, 2016. © 2015 The Authors. Magnetic Resonance in Medicine published by Wiley Periodicals, Inc. on behalf of International Society for Magnetic Resonance in Medicine. This is an open access article under the terms of the Creative Commons Attribution-NonCommercial-NoDerivs License, which permits use and distribution in any medium, provided the original work is properly cited, the use is non-commercial and no modifications or adaptations are made. © 2015 The Authors. Magnetic Resonance in Medicine published by Wiley Periodicals, Inc. on behalf of International Society for Magnetic Resonance in Medicine.

Use of Self-to-Object and Object-to-Object Spatial Relations in Locomotion

ERIC Educational Resources Information Center

Xiao, Chengli; Mou, Weimin; McNamara, Timothy P.

2009-01-01

In 8 experiments, the authors examined the use of representations of self-to-object or object-to-object spatial relations during locomotion. Participants learned geometrically regular or irregular layouts of objects while standing at the edge or in the middle and then pointed to objects while blindfolded in 3 conditions: before turning (baseline),…

Spatial optimization of the pattern of fuel management activities and subsequent effects on simulated wildfires

Treesearch

Young-Hwan Kim; Pete Bettinger; Mark Finney

2009-01-01

Methods for scheduling forest management activities in a spatial pattern (dispersed, clumped, random, and regular) are presented, with the intent to examine the effects of placement of activities on resulting simulated wildfire behavior. Both operational and fuel reduction management prescriptions are examined, and a heuristic was employed to schedule the activities....

Obtaining sparse distributions in 2D inverse problems.

PubMed

Reci, A; Sederman, A J; Gladden, L F

2017-08-01

The mathematics of inverse problems has relevance across numerous estimation problems in science and engineering. L 1 regularization has attracted recent attention in reconstructing the system properties in the case of sparse inverse problems; i.e., when the true property sought is not adequately described by a continuous distribution, in particular in Compressed Sensing image reconstruction. In this work, we focus on the application of L 1 regularization to a class of inverse problems; relaxation-relaxation, T 1 -T 2 , and diffusion-relaxation, D-T 2 , correlation experiments in NMR, which have found widespread applications in a number of areas including probing surface interactions in catalysis and characterizing fluid composition and pore structures in rocks. We introduce a robust algorithm for solving the L 1 regularization problem and provide a guide to implementing it, including the choice of the amount of regularization used and the assignment of error estimates. We then show experimentally that L 1 regularization has significant advantages over both the Non-Negative Least Squares (NNLS) algorithm and Tikhonov regularization. It is shown that the L 1 regularization algorithm stably recovers a distribution at a signal to noise ratio<20 and that it resolves relaxation time constants and diffusion coefficients differing by as little as 10%. The enhanced resolving capability is used to measure the inter and intra particle concentrations of a mixture of hexane and dodecane present within porous silica beads immersed within a bulk liquid phase; neither NNLS nor Tikhonov regularization are able to provide this resolution. This experimental study shows that the approach enables discrimination between different chemical species when direct spectroscopic discrimination is impossible, and hence measurement of chemical composition within porous media, such as catalysts or rocks, is possible while still being stable to high levels of noise. Copyright © 2017. Published by Elsevier Inc.

Obtaining sparse distributions in 2D inverse problems

NASA Astrophysics Data System (ADS)

Reci, A.; Sederman, A. J.; Gladden, L. F.

2017-08-01

The mathematics of inverse problems has relevance across numerous estimation problems in science and engineering. L1 regularization has attracted recent attention in reconstructing the system properties in the case of sparse inverse problems; i.e., when the true property sought is not adequately described by a continuous distribution, in particular in Compressed Sensing image reconstruction. In this work, we focus on the application of L1 regularization to a class of inverse problems; relaxation-relaxation, T1-T2, and diffusion-relaxation, D-T2, correlation experiments in NMR, which have found widespread applications in a number of areas including probing surface interactions in catalysis and characterizing fluid composition and pore structures in rocks. We introduce a robust algorithm for solving the L1 regularization problem and provide a guide to implementing it, including the choice of the amount of regularization used and the assignment of error estimates. We then show experimentally that L1 regularization has significant advantages over both the Non-Negative Least Squares (NNLS) algorithm and Tikhonov regularization. It is shown that the L1 regularization algorithm stably recovers a distribution at a signal to noise ratio < 20 and that it resolves relaxation time constants and diffusion coefficients differing by as little as 10%. The enhanced resolving capability is used to measure the inter and intra particle concentrations of a mixture of hexane and dodecane present within porous silica beads immersed within a bulk liquid phase; neither NNLS nor Tikhonov regularization are able to provide this resolution. This experimental study shows that the approach enables discrimination between different chemical species when direct spectroscopic discrimination is impossible, and hence measurement of chemical composition within porous media, such as catalysts or rocks, is possible while still being stable to high levels of noise.

Spectral methods for the spin-2 equation near the cylinder at spatial infinity

NASA Astrophysics Data System (ADS)

Macedo, Rodrigo P.; Valiente Kroon, Juan A.

2018-06-01

We solve, numerically, the massless spin-2 equations, written in terms of a gauge based on the properties of conformal geodesics, in a neighbourhood of spatial infinity using spectral methods in both space and time. This strategy allows us to compute the solutions to these equations up to the critical sets where null infinity intersects with spatial infinity. Moreover, we use the convergence rates of the numerical solutions to read-off their regularity properties.

Spatial point pattern analysis of human settlements and geographical associations in eastern coastal China - a case study.

PubMed

Zhang, Zhonghao; Xiao, Rui; Shortridge, Ashton; Wu, Jiaping

2014-03-10

Understanding the spatial point pattern of human settlements and their geographical associations are important for understanding the drivers of land use and land cover change and the relationship between environmental and ecological processes on one hand and cultures and lifestyles on the other. In this study, a Geographic Information System (GIS) approach, Ripley's K function and Monte Carlo simulation were used to investigate human settlement point patterns. Remotely sensed tools and regression models were employed to identify the effects of geographical determinants on settlement locations in the Wen-Tai region of eastern coastal China. Results indicated that human settlements displayed regular-random-cluster patterns from small to big scale. Most settlements located on the coastal plain presented either regular or random patterns, while those in hilly areas exhibited a clustered pattern. Moreover, clustered settlements were preferentially located at higher elevations with steeper slopes and south facing aspects than random or regular settlements. Regression showed that influences of topographic factors (elevation, slope and aspect) on settlement locations were stronger across hilly regions. This study demonstrated a new approach to analyzing the spatial patterns of human settlements from a wide geographical prospective. We argue that the spatial point patterns of settlements, in addition to the characteristics of human settlements, such as area, density and shape, should be taken into consideration in the future, and land planners and decision makers should pay more attention to city planning and management. Conceptual and methodological bridges linking settlement patterns to regional and site-specific geographical characteristics will be a key to human settlement studies and planning.

Spatially Regularized Machine Learning for Task and Resting-state fMRI

PubMed Central

Song, Xiaomu; Panych, Lawrence P.; Chen, Nan-kuei

2015-01-01

Background Reliable mapping of brain function across sessions and/or subjects in task- and resting-state has been a critical challenge for quantitative fMRI studies although it has been intensively addressed in the past decades. New Method A spatially regularized support vector machine (SVM) technique was developed for the reliable brain mapping in task- and resting-state. Unlike most existing SVM-based brain mapping techniques, which implement supervised classifications of specific brain functional states or disorders, the proposed method performs a semi-supervised classification for the general brain function mapping where spatial correlation of fMRI is integrated into the SVM learning. The method can adapt to intra- and inter-subject variations induced by fMRI nonstationarity, and identify a true boundary between active and inactive voxels, or between functionally connected and unconnected voxels in a feature space. Results The method was evaluated using synthetic and experimental data at the individual and group level. Multiple features were evaluated in terms of their contributions to the spatially regularized SVM learning. Reliable mapping results in both task- and resting-state were obtained from individual subjects and at the group level. Comparison with Existing Methods A comparison study was performed with independent component analysis, general linear model, and correlation analysis methods. Experimental results indicate that the proposed method can provide a better or comparable mapping performance at the individual and group level. Conclusions The proposed method can provide accurate and reliable mapping of brain function in task- and resting-state, and is applicable to a variety of quantitative fMRI studies. PMID:26470627

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.

High quality 4D cone-beam CT reconstruction using motion-compensated total variation regularization

NASA Astrophysics Data System (ADS)

Zhang, Hua; Ma, Jianhua; Bian, Zhaoying; Zeng, Dong; Feng, Qianjin; Chen, Wufan

2017-04-01

Four dimensional cone-beam computed tomography (4D-CBCT) has great potential clinical value because of its ability to describe tumor and organ motion. But the challenge in 4D-CBCT reconstruction is the limited number of projections at each phase, which result in a reconstruction full of noise and streak artifacts with the conventional analytical algorithms. To address this problem, in this paper, we propose a motion compensated total variation regularization approach which tries to fully explore the temporal coherence of the spatial structures among the 4D-CBCT phases. In this work, we additionally conduct motion estimation/motion compensation (ME/MC) on the 4D-CBCT volume by using inter-phase deformation vector fields (DVFs). The motion compensated 4D-CBCT volume is then viewed as a pseudo-static sequence, of which the regularization function was imposed on. The regularization used in this work is the 3D spatial total variation minimization combined with 1D temporal total variation minimization. We subsequently construct a cost function for a reconstruction pass, and minimize this cost function using a variable splitting algorithm. Simulation and real patient data were used to evaluate the proposed algorithm. Results show that the introduction of additional temporal correlation along the phase direction can improve the 4D-CBCT image quality.

Visuomotor adaptability in older adults with mild cognitive decline.

PubMed

Schaffert, Jeffrey; Lee, Chi-Mei; Neill, Rebecca; Bo, Jin

2017-02-01

The current study examined the augmentation of error feedback on visuomotor adaptability in older adults with varying degrees of cognitive decline (assessed by the Montreal Cognitive Assessment; MoCA). Twenty-three participants performed a center-out computerized visuomotor adaptation task when the visual feedback of their hand movement error was presented in a regular (ratio=1:1) or enhanced (ratio=1:2) error feedback schedule. Results showed that older adults with lower scores on the MoCA had less adaptability than those with higher MoCA scores during the regular feedback schedule. However, participants demonstrated similar adaptability during the enhanced feedback schedule, regardless of their cognitive ability. Furthermore, individuals with lower MoCA scores showed larger after-effects in spatial control during the enhanced schedule compared to the regular schedule, whereas individuals with higher MoCA scores displayed the opposite pattern. Additional neuro-cognitive assessments revealed that spatial working memory and processing speed were positively related to motor adaptability during the regular scheduled but negatively related to adaptability during the enhanced schedule. We argue that individuals with mild cognitive decline employed different adaptation strategies when encountering enhanced visual feedback, suggesting older adults with mild cognitive impairment (MCI) may benefit from enhanced visual error feedback during sensorimotor adaptation. Copyright © 2016 Elsevier B.V. All rights reserved.

Soil Moisture Monitoring using Surface Electrical Resistivity measurements

NASA Astrophysics Data System (ADS)

Calamita, Giuseppe; Perrone, Angela; Brocca, Luca; Straface, Salvatore

2017-04-01

The relevant role played by the soil moisture (SM) for global and local natural processes results in an explicit interest for its spatial and temporal estimation in the vadose zone coming from different scientific areas - i.e. eco-hydrology, hydrogeology, atmospheric research, soil and plant sciences, etc... A deeper understanding of natural processes requires the collection of data on a higher number of points at increasingly higher spatial scales in order to validate hydrological numerical simulations. In order to take the best advantage of the Electrical Resistivity (ER) data with their non-invasive and cost-effective properties, sequential Gaussian geostatistical simulations (sGs) can be applied to monitor the SM distribution into the soil by means of a few SM measurements and a densely regular ER grid of monitoring. With this aim, co-located SM measurements using mobile TDR probes (MiniTrase), and ER measurements, obtained by using a four-electrode device coupled with a geo-resistivimeter (Syscal Junior), were collected during two surveys carried out on a 200 × 60 m2 area. Two time surveys were carried out during which Data were collected at a depth of around 20 cm for more than 800 points adopting a regular grid sampling scheme with steps (5 m) varying according to logistic and soil compaction constrains. The results of this study are robust due to the high number of measurements available for either variables which strengthen the confidence in the covariance function estimated. Moreover, the findings obtained using sGs show that it is possible to estimate soil moisture variations in the pedological zone by means of time-lapse electrical resistivity and a few SM measurements.

Regularized joint inverse estimation of extreme rainfall amounts in ungauged coastal basins of El Salvador

USGS Publications Warehouse

Friedel, M.J.

2008-01-01

A regularized joint inverse procedure is presented and used to estimate the magnitude of extreme rainfall events in ungauged coastal river basins of El Salvador: Paz, Jiboa, Grande de San Miguel, and Goascoran. Since streamflow measurements reflect temporal and spatial rainfall information, peak-flow discharge is hypothesized to represent a similarity measure suitable for regionalization. To test this hypothesis, peak-flow discharge values determined from streamflow recurrence information (10-year, 25-year, and 100-year) collected outside the study basins are used to develop regional (country-wide) regression equations. Peak-flow discharge derived from these equations together with preferred spatial parameter relations as soft prior information are used to constrain the simultaneous calibration of 20 tributary basin models. The nonlinear range of uncertainty in estimated parameter values (1 curve number and 3 recurrent rainfall amounts for each model) is determined using an inverse calibration-constrained Monte Carlo approach. Cumulative probability distributions for rainfall amounts indicate differences among basins for a given return period and an increase in magnitude and range among basins with increasing return interval. Comparison of the estimated median rainfall amounts for all return periods were reasonable but larger (3.2-26%) than rainfall estimates computed using the frequency-duration (traditional) approach and individual rain gauge data. The observed 25-year recurrence rainfall amount at La Hachadura in the Paz River basin during Hurricane Mitch (1998) is similar in value to, but outside and slightly less than, the estimated rainfall confidence limits. The similarity in joint inverse and traditionally computed rainfall events, however, suggests that the rainfall observation may likely be due to under-catch and not model bias. ?? Springer Science+Business Media B.V. 2007.

Implicit learning of non-spatial sequences in schizophrenia

PubMed Central

MARVEL, CHERIE L.; SCHWARTZ, BARBARA L.; HOWARD, DARLENE V.; HOWARD, JAMES H.

2006-01-01

Recent studies have reported abnormal implicit learning of sequential patterns in patients with schizophrenia. Because these studies were based on visuospatial cues, the question remained whether patients were impaired simply due to the demands of spatial processing. This study examined implicit sequence learning in 24 patients with schizophrenia and 24 healthy controls using a non-spatial variation of the serial reaction time test (SRT) in which pattern stimuli alternated with random stimuli on every other trial. Both groups showed learning by responding faster and more accurately to pattern trials than to random trials. Patients, however, showed a smaller magnitude of sequence learning. Both groups were unable to demonstrate explicit knowledge of the nature of the pattern, confirming that learning occurred without awareness. Clinical variables were not correlated with the patients' learning deficits. Patients with schizophrenia have a decreased ability to develop sensitivity to regularly occurring sequences of events within their environment. This type of deficit may affect an array of cognitive and motor functions that rely on the perception of event regularity. PMID:16248901

Spatial constraints underlying the retinal mosaics of two types of horizontal cells in cat and macaque.

PubMed

Eglen, Stephen J; Wong, James C T

2008-01-01

Most types of retinal neurons are spatially positioned in non-random patterns, termed retinal mosaics. Several developmental mechanisms are thought to be important in the formation of these mosaics. Most evidence to date suggests that homotypic constraints within a type of neuron are dominant, and that heterotypic interactions between different types of neuron are rare. In an analysis of macaque H1 and H2 horizontal cell mosaics, Wässle et al. (2000) suggested that the high regularity index of the combined H1 and H2 mosaic might be caused by heterotypic interactions during development. Here we use computer modeling to suggest that the high regularity index of the combined H1 and H2 mosaic is a by-product of the basic constraint that two neurons cannot occupy the same space. The spatial arrangement of type A and type B horizontal cells in cat retina also follow this same principle.

The Evolution of Frequency Distributions: Relating Regularization to Inductive Biases through Iterated Learning

ERIC Educational Resources Information Center

Reali, Florencia; Griffiths, Thomas L.

2009-01-01

The regularization of linguistic structures by learners has played a key role in arguments for strong innate constraints on language acquisition, and has important implications for language evolution. However, relating the inductive biases of learners to regularization behavior in laboratory tasks can be challenging without a formal model. In this…

Determining origin in a migratory marine vertebrate: a novel method to integrate stable isotopes and satellite tracking

USGS Publications Warehouse

Vander Zanden, Hannah B.; Tucker, Anton D.; Hart, Kristen M.; Lamont, Margaret M.; Fujisaki, Ikuko; Addison, David S.; Mansfield, Katherine L.; Phillips, Katrina F.; Wunder, Michael B.; Bowen, Gabriel J.; Pajuelo, Mariela; Bolten, Alan B.; Bjorndal, Karen A.

2015-01-01

Stable isotope analysis is a useful tool to track animal movements in both terrestrial and marine environments. These intrinsic markers are assimilated through the diet and may exhibit spatial gradients as a result of biogeochemical processes at the base of the food web. In the marine environment, maps to predict the spatial distribution of stable isotopes are limited, and thus determining geographic origin has been reliant upon integrating satellite telemetry and stable isotope data. Migratory sea turtles regularly move between foraging and reproductive areas. Whereas most nesting populations can be easily accessed and regularly monitored, little is known about the demographic trends in foraging populations. The purpose of the present study was to examine migration patterns of loggerhead nesting aggregations in the Gulf of Mexico (GoM), where sea turtles have been historically understudied. Two methods of geographic assignment using stable isotope values in known-origin samples from satellite telemetry were compared: 1) a nominal approach through discriminant analysis and 2) a novel continuous-surface approach using bivariate carbon and nitrogen isoscapes (isotopic landscapes) developed for this study. Tissue samples for stable isotope analysis were obtained from 60 satellite-tracked individuals at five nesting beaches within the GoM. Both methodological approaches for assignment resulted in high accuracy of foraging area determination, though each has advantages and disadvantages. The nominal approach is more appropriate when defined boundaries are necessary, but up to 42% of the individuals could not be considered in this approach. All individuals can be included in the continuous-surface approach, and individual results can be aggregated to identify geographic hotspots of foraging area use, though the accuracy rate was lower than nominal assignment. The methodological validation provides a foundation for future sea turtle studies in the region to inexpensively determine geographic origin for large numbers of untracked individuals. Regular monitoring of sea turtle nesting aggregations with stable isotope sampling can be used to fill critical data gaps regarding habitat use and migration patterns. Probabilistic assignment to origin with isoscapes has not been previously used in the marine environment, but the methods presented here could also be applied to other migratory marine species.

Determining origin in a migratory marine vertebrate: a novel method to integrate stable isotopes and satellite tracking.

PubMed

Zanden, Hannah B Vander; Tucker, Anton D; Hart, Kristen M; Lamont, Margaret M; Fuisaki, Ikuko; Addison, David; Mansfield, Katherine L; Phillips, Katrina F; Wunder, Michael B; Bowen, Gabriel J; Pajuelo, Mariela; Bolten, Alan B; Bjorndal, Karen A

2015-03-01

Stable isotope analysis is a useful tool to track animal movements in both terrestrial and marine environments. These intrinsic markers are assimilated through the diet and may exhibit spatial gradients as a result of biogeochemical processes at the base of the food web. In the marine environment, maps to predict the spatial distribution of stable isotopes are limited, and thus determining geographic origin has been reliant upon integrating satellite telemetry and stable isotope data. Migratory sea turtles regularly move between foraging and reproductive areas. Whereas most nesting populations can be easily accessed and regularly monitored, little is known about the demographic trends in foraging populations. The purpose of the present study was to examine migration patterns of loggerhead nesting aggregations in the Gulf of Mexico (GoM), where sea turtles have been historically understudied. Two methods of geographic assignment using stable isotope values in known-origin samples from satellite telemetry were compared: (1) a nominal approach through discriminant analysis and (2) a novel continuous-surface approach using bivariate carbon and nitrogen isoscapes (isotopic landscapes) developed for this study. Tissue samples for stable isotope analysis were obtained from 60 satellite-tracked individuals at five nesting beaches within the GoM. Both methodological approaches for assignment resulted in high accuracy of foraging area determination, though each has advantages and disadvantages. The nominal approach is more appropriate when defined boundaries are necessary, but up to 42% of the individuals could not be considered in this approach. All individuals can be included in the continuous-surface approach, and individual results can be aggregated to identify geographic hotspots of foraging area use, though the accuracy rate was lower than nominal assignment. The methodological validation provides a foundation for future sea turtle studies in the region to inexpensively determine geographic origin for large numbers of untracked individuals. Regular monitoring of sea turtle nesting aggregations with stable isotope sampling can be used to fill critical data gaps regarding habitat use and migration patterns. Probabilistic assignment to origin with isoscapes has not been previously used in the marine environment, but the methods presented here could also be applied to other migratory marine species.

TRANSIENT LUNAR PHENOMENA: REGULARITY AND REALITY

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

Crotts, Arlin P. S.

2009-05-20

Transient lunar phenomena (TLPs) have been reported for centuries, but their nature is largely unsettled, and even their existence as a coherent phenomenon is controversial. Nonetheless, TLP data show regularities in the observations; a key question is whether this structure is imposed by processes tied to the lunar surface, or by terrestrial atmospheric or human observer effects. I interrogate an extensive catalog of TLPs to gauge how human factors determine the distribution of TLP reports. The sample is grouped according to variables which should produce differing results if determining factors involve humans, and not reflecting phenomena tied to the lunarmore » surface. Features dependent on human factors can then be excluded. Regardless of how the sample is split, the results are similar: {approx}50% of reports originate from near Aristarchus, {approx}16% from Plato, {approx}6% from recent, major impacts (Copernicus, Kepler, Tycho, and Aristarchus), plus several at Grimaldi. Mare Crisium produces a robust signal in some cases (however, Crisium is too large for a 'feature' as defined). TLP count consistency for these features indicates that {approx}80% of these may be real. Some commonly reported sites disappear from the robust averages, including Alphonsus, Ross D, and Gassendi. These reports begin almost exclusively after 1955, when TLPs became widely known and many more (and inexperienced) observers searched for TLPs. In a companion paper, we compare the spatial distribution of robust TLP sites to transient outgassing (seen by Apollo and Lunar Prospector instruments). To a high confidence, robust TLP sites and those of lunar outgassing correlate strongly, further arguing for the reality of TLPs.« less

Nongyrotropic electron orbits in collisionless magnetic reconnection

NASA Astrophysics Data System (ADS)

Zenitani, S.

2016-12-01

In order to study inner workings of magnetic reconnection, NASA has recently launched Magnetospheric MultiScale (MMS) spacecraft. It is expected to observe electron velocity distribution functions (VDFs) at high resolution in magnetotail reconnection sites in 2017. Since VDFs are outcomes of many particle orbits, it is important to understand the relation between electron orbits and VDFs. In this work, we study electron orbits and associated VDFs in the electron current layer in magnetic reconnection, by using a two-dimensional particle-in-cell (PIC) simulation. By analyzing millions of electron orbits, we discover several new orbits: (1) Figure-eight-shaped regular orbits inside the super-Alfvenic electron jet, (2) noncrossing Speiser orbits that do not cross the midplane, (3) noncrossing regular orbits on the jet flanks, and (4) nongyrotropic electrons in the downstream of the jet termination region. Properties of these orbits are organized by a theory on particle orbits (Buchner & Zelenyi 1989 JGR). The noncrossing orbits are mediated by the polarization electric field (Hall electric field E_z) near the midplane. These orbits can be understood as electrostatic extensions of the conventional theory. Properties of the super-Alfvenic electron jet are attributed to the traditional Speiser-orbit electrons. On the other hand, the noncrossing electrons are the majority in number density in the jet flanks. This raise a serious question to our present understanding of physics of collisionless magnetic reconnection, which only assumes crossing populations. We will also discuss spatial distribution of energetic electrons and observational signatures of noncrossing electrons. Reference: Zenitani & Nagai (2016), submitted to Phys. Plasmas.

Cardiac C-arm computed tomography using a 3D + time ROI reconstruction method with spatial and temporal regularization

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

Mory, Cyril, E-mail: cyril.mory@philips.com; Philips Research Medisys, 33 rue de Verdun, 92156 Suresnes; Auvray, Vincent

2014-02-15

Purpose: Reconstruction of the beating heart in 3D + time in the catheter laboratory using only the available C-arm system would improve diagnosis, guidance, device sizing, and outcome control for intracardiac interventions, e.g., electrophysiology, valvular disease treatment, structural or congenital heart disease. To obtain such a reconstruction, the patient's electrocardiogram (ECG) must be recorded during the acquisition and used in the reconstruction. In this paper, the authors present a 4D reconstruction method aiming to reconstruct the heart from a single sweep 10 s acquisition. Methods: The authors introduce the 4D RecOnstructiOn using Spatial and TEmporal Regularization (short 4D ROOSTER) method,more » which reconstructs all cardiac phases at once, as a 3D + time volume. The algorithm alternates between a reconstruction step based on conjugate gradient and four regularization steps: enforcing positivity, averaging along time outside a motion mask that contains the heart and vessels, 3D spatial total variation minimization, and 1D temporal total variation minimization. Results: 4D ROOSTER recovers the different temporal representations of a moving Shepp and Logan phantom, and outperforms both ECG-gated simultaneous algebraic reconstruction technique and prior image constrained compressed sensing on a clinical case. It generates 3D + time reconstructions with sharp edges which can be used, for example, to estimate the patient's left ventricular ejection fraction. Conclusions: 4D ROOSTER can be applied for human cardiac C-arm CT, and potentially in other dynamic tomography areas. It can easily be adapted to other problems as regularization is decoupled from projection and back projection.« less

Identification of nodal tissue in the living heart using rapid scanning fiber-optics confocal microscopy and extracellular fluorophores.

PubMed

Huang, Chao; Kaza, Aditya K; Hitchcock, Robert W; Sachse, Frank B

2013-09-01

Risks associated with pediatric reconstructive heart surgery include injury of the sinoatrial node (SAN) and atrioventricular node (AVN), requiring cardiac rhythm management using implantable pacemakers. These injuries are the result of difficulties in identifying nodal tissues intraoperatively. Here we describe an approach based on confocal microscopy and extracellular fluorophores to quantify tissue microstructure and identify nodal tissue. Using conventional 3-dimensional confocal microscopy we investigated the microstructural arrangement of SAN, AVN, and atrial working myocardium (AWM) in fixed rat heart. AWM exhibited a regular striated arrangement of the extracellular space. In contrast, SAN and AVN had an irregular, reticulated arrangement. AWM, SAN, and AVN tissues were beneath a thin surface layer of tissue that did not obstruct confocal microscopic imaging. Subsequently, we imaged tissues in living rat hearts with real-time fiber-optics confocal microscopy. Fiber-optics confocal microscopy images resembled images acquired with conventional confocal microscopy. We investigated spatial regularity of tissue microstructure from Fourier analysis and second-order image moments. Fourier analysis of fiber-optics confocal microscopy images showed that the spatial regularity of AWM was greater than that of nodal tissues (37.5 ± 5.0% versus 24.3 ± 3.9% for SAN and 23.8 ± 3.7% for AVN; P<0.05). Similar differences of spatial regularities were revealed from second-order image moments (50.0 ± 7.3% for AWM versus 29.3 ± 6.7% for SAN and 27.3 ± 5.5% for AVN; P<0.05). The study demonstrates feasibility of identifying nodal tissue in living heart using extracellular fluorophores and fiber-optics confocal microscopy. Application of the approach in pediatric reconstructive heart surgery may reduce risks of injuring nodal tissues.

Spatial patterns of distribution and abundance of Harrisia portoricensis, an endangered Caribbean cactus

Treesearch

J. Rojas-Sandoval; E. J. Melendez-Ackerman; NO-VALUE

2013-01-01

Aims The spatial distribution of biotic and abiotic factors may play a dominant role in determining the distribution and abundance of plants in arid and semiarid environments. In this study, we evaluated how spatial patterns of microhabitat variables and the degree of spatial dependence of these variables influence the distribution and abundance of the endangered...

[Spatial distribution pattern of Chilo suppressalis analyzed by classical method and geostatistics].

PubMed

Yuan, Zheming; Fu, Wei; Li, Fangyi

2004-04-01

Two original samples of Chilo suppressalis and their grid, random and sequence samples were analyzed by classical method and geostatistics to characterize the spatial distribution pattern of C. suppressalis. The limitations of spatial distribution analysis with classical method, especially influenced by the original position of grid, were summarized rather completely. On the contrary, geostatistics characterized well the spatial distribution pattern, congregation intensity and spatial heterogeneity of C. suppressalis. According to geostatistics, the population was up to Poisson distribution in low density. As for higher density population, its distribution was up to aggregative, and the aggregation intensity and dependence range were 0.1056 and 193 cm, respectively. Spatial heterogeneity was also found in the higher density population. Its spatial correlativity in line direction was more closely than that in row direction, and the dependence ranges in line and row direction were 115 and 264 cm, respectively.

Importance of spatial autocorrelation in modeling bird distributions at a continental scale

USGS Publications Warehouse

Bahn, V.; O'Connor, R.J.; Krohn, W.B.

2006-01-01

Spatial autocorrelation in species' distributions has been recognized as inflating the probability of a type I error in hypotheses tests, causing biases in variable selection, and violating the assumption of independence of error terms in models such as correlation or regression. However, it remains unclear whether these problems occur at all spatial resolutions and extents, and under which conditions spatially explicit modeling techniques are superior. Our goal was to determine whether spatial models were superior at large extents and across many different species. In addition, we investigated the importance of purely spatial effects in distribution patterns relative to the variation that could be explained through environmental conditions. We studied distribution patterns of 108 bird species in the conterminous United States using ten years of data from the Breeding Bird Survey. We compared the performance of spatially explicit regression models with non-spatial regression models using Akaike's information criterion. In addition, we partitioned the variance in species distributions into an environmental, a pure spatial and a shared component. The spatially-explicit conditional autoregressive regression models strongly outperformed the ordinary least squares regression models. In addition, partialling out the spatial component underlying the species' distributions showed that an average of 17% of the explained variation could be attributed to purely spatial effects independent of the spatial autocorrelation induced by the underlying environmental variables. We concluded that location in the range and neighborhood play an important role in the distribution of species. Spatially explicit models are expected to yield better predictions especially for mobile species such as birds, even in coarse-grained models with a large extent. ?? Ecography.

Spatial Distribution of Ammonia and its Contribution to Particulate Matter Formation in the Great Salt Lake Region in Winter

NASA Astrophysics Data System (ADS)

Moravek, A.; Murphy, J. G.; Baasandorj, M.; Fibiger, D. L.; Franchin, A.; Goldberger, L.; McDuffie, E. E.; McKeen, S. A.; Middlebrook, A. M.; Thornton, J. A.; Womack, C.; Brown, S. S.

2017-12-01

Winter air pollution in urban areas is a major global concern due to increased levels of fine particulate matter (PM) affecting public health. The Great Salt Lake region regularly experiences periods of high particulate matter during winter persistent cold air pool events (PCAPs), periods of atmospheric stagnation. Previous studies have shown that ammonium nitrate is responsible for up to 70% of PM2.5 (particulate matter with a diameter less than 2.5 microns) in the Great Salt Lake region during these periods. Ammonium nitrate is formed from ammonia (NH3) and nitric acid (HNO3); therefore understanding sources of NH3 and its role in the formation of particulate matter is crucial for mitigation of air pollution in this region. In this study, we measured NH3 aboard a Twin Otter aircraft within the Utah Winter Fine Particulate Study (UWFPS) using Quantum Cascade Laser Infrared Absorption Spectroscopy (QC-TILDAS). A total of 23 flights were performed in the period from 16 Jan to 12 Feb 2017 covering the Salt Lake City urban area, the Great Salt Lake and nearby valleys. The spatial distribution of NH3 during flights is presented and identifies major NH3 sources and their role in particle formation for the region. Substantial variation of NH3 was observed over the entire region with highest NH3 mixing ratios over agricultural areas and the lowest NH3 abundance over the Great Salt Lake. Regional WRF-Chem model simulations are used to compare the measurements to available NH3 emission inventories and to improve our understanding of the vertical distribution of NH3. The relative influence of the atmospheric stability for the formation of ammonium nitrate is investigated.

Earthquake damage history in Israel and its close surrounding - evaluation of spatial and temporal patterns

NASA Astrophysics Data System (ADS)

Zohar, Motti; Salamon, Amos; Rubin, Rehav

2017-01-01

Israel was hit by destructive earthquakes many times in the course of history. To properly understand the hazard and support effective preparedness towards future earthquakes, we examined the spatial and temporal distribution of the resulted damage. We described in detail our systematic approach to searching the available literature, collecting the data and screening the authenticity of that information. We used GIS (Geographic Information System) to map and evaluate the distribution of the damage and to search for recurring patterns. Overall, it is found that 186 localities were hit, 54 of them at least twice. We also found that Israel was affected by 4, 17, 8 and 2 damaging earthquakes that originated, respectively, from the southern, central, central-northern and northern parts of the Dead Sea Transform (DST). The temporal appearance of the northern earthquakes is clustered; the central earthquakes are more regular in time, whereas no damage from the north-central and the central quakes, with the exception of the year 363 earthquake, seems to have occurred south of the Dead Sea region. Analyzing the distribution of the damage, we realized that the number of the damage reports reflects only half of the incidents that actually happened, attesting to incompleteness of the historical catalogue. Jerusalem is the most reported city with 14 entries, followed by Akko (Acre), Tiberias, Nablus and Tyre with 8, 7, 7 and 6 reports, respectively. In general, localities in the Galilee and north of it suffered more severely than localities in central Israel with the exception of Nablus and the localities along the coastal plain of Israel, most probably due to local site effects. For the sake of hazard management, these observations should be considered for future planning and risk mitigation.

A method to deconvolve stellar rotational velocities II. The probability distribution function via Tikhonov regularization

NASA Astrophysics Data System (ADS)

Christen, Alejandra; Escarate, Pedro; Curé, Michel; Rial, Diego F.; Cassetti, Julia

2016-10-01

Aims: Knowing the distribution of stellar rotational velocities is essential for understanding stellar evolution. Because we measure the projected rotational speed v sin I, we need to solve an ill-posed problem given by a Fredholm integral of the first kind to recover the "true" rotational velocity distribution. Methods: After discretization of the Fredholm integral we apply the Tikhonov regularization method to obtain directly the probability distribution function for stellar rotational velocities. We propose a simple and straightforward procedure to determine the Tikhonov parameter. We applied Monte Carlo simulations to prove that the Tikhonov method is a consistent estimator and asymptotically unbiased. Results: This method is applied to a sample of cluster stars. We obtain confidence intervals using a bootstrap method. Our results are in close agreement with those obtained using the Lucy method for recovering the probability density distribution of rotational velocities. Furthermore, Lucy estimation lies inside our confidence interval. Conclusions: Tikhonov regularization is a highly robust method that deconvolves the rotational velocity probability density function from a sample of v sin I data directly without the need for any convergence criteria.

Quantifying and mapping spatial variability in simulated forest plots

Treesearch

Gavin R. Corral; Harold E. Burkhart

2016-01-01

We used computer simulations to test the efficacy of multivariate statistical methods to detect, quantify, and map spatial variability of forest stands. Simulated stands were developed of regularly-spaced plantations of loblolly pine (Pinus taeda L.). We assumed no affects of competition or mortality, but random variability was added to individual tree characteristics...

Gender and Racial Differences: Development of Sixth Grade Students' Geometric Spatial Visualization within an Earth/Space Unit

ERIC Educational Resources Information Center

Jackson, Christa; Wilhelm, Jennifer Anne; Lamar, Mary; Cole, Merryn

2015-01-01

This study investigated sixth-grade middle-level students' geometric spatial development by gender and race within and between control and experimental groups at two middle schools as they participated in an Earth/Space unit. The control group utilized a regular Earth/Space curriculum and the experimental group used a National Aeronautics and…

Extended generalized recurrence plot quantification of complex circular patterns

NASA Astrophysics Data System (ADS)

Riedl, Maik; Marwan, Norbert; Kurths, Jürgen

2017-03-01

The generalized recurrence plot is a modern tool for quantification of complex spatial patterns. Its application spans the analysis of trabecular bone structures, Turing patterns, turbulent spatial plankton patterns, and fractals. Determinism is a central measure in this framework quantifying the level of regularity of spatial structures. We show by basic examples of fully regular patterns of different symmetries that this measure underestimates the orderliness of circular patterns resulting from rotational symmetries. We overcome this crucial problem by checking additional structural elements of the generalized recurrence plot which is demonstrated with the examples. Furthermore, we show the potential of the extended quantity of determinism applying it to more irregular circular patterns which are generated by the complex Ginzburg-Landau-equation and which can be often observed in real spatially extended dynamical systems. So, we are able to reconstruct the main separations of the system's parameter space analyzing single snapshots of the real part only, in contrast to the use of the original quantity. This ability of the proposed method promises also an improved description of other systems with complicated spatio-temporal dynamics typically occurring in fluid dynamics, climatology, biology, ecology, social sciences, etc.

Sparsely sampling the sky: Regular vs. random sampling

NASA Astrophysics Data System (ADS)

Paykari, P.; Pires, S.; Starck, J.-L.; Jaffe, A. H.

2015-09-01

Aims: The next generation of galaxy surveys, aiming to observe millions of galaxies, are expensive both in time and money. This raises questions regarding the optimal investment of this time and money for future surveys. In a previous work, we have shown that a sparse sampling strategy could be a powerful substitute for the - usually favoured - contiguous observation of the sky. In our previous paper, regular sparse sampling was investigated, where the sparse observed patches were regularly distributed on the sky. The regularity of the mask introduces a periodic pattern in the window function, which induces periodic correlations at specific scales. Methods: In this paper, we use a Bayesian experimental design to investigate a "random" sparse sampling approach, where the observed patches are randomly distributed over the total sparsely sampled area. Results: We find that in this setting, the induced correlation is evenly distributed amongst all scales as there is no preferred scale in the window function. Conclusions: This is desirable when we are interested in any specific scale in the galaxy power spectrum, such as the matter-radiation equality scale. As the figure of merit shows, however, there is no preference between regular and random sampling to constrain the overall galaxy power spectrum and the cosmological parameters.

The new MOPREDAS database and the monthly precipitation trends in Spain (December 1945- November 2005)

NASA Astrophysics Data System (ADS)

Gonzalez-Hidalgo, Jose Carlos; Brunetti, Michele; Martin, De Luis

2010-05-01

Precipitation is one of the most important climate elements directly affecting human society, economic activities and natural systems; at the same time it is the most variable climate element, and its changes can be detected only if a spatially dense network of observations is used. Due to this, the last AR4 report renewed interest in the study of precipitation, and suggests focusing on detailed sub-regional studies, with a preference for those areas where water is a scarce resource with heavy demands placed on it. We have developed the new MOPREDAS database (MOnthly PREcipitation DAtabase of Spain) by exploiting the total amount of data available at Spanish Meteorological Agency (AEMET, formerly INM). These provide a total of 2670 complete and homogeneous series for the period 1946-2005 after exhaustive quality control and reconstruction processes, and at present is the most complete and extensive monthly precipitation dataset uptodated in Spain, including dense information up to 1500 m o.l.s.. MOPREDAS has been created with the aim of analyzing the behaviour of precipitation in the conterminous provinces of Spain, and to validate the downscaling of climate models on a detailed spatial level. To this end, the station data were also interpolated on a regular grid, at 1/10 of degree of resolution, over the whole Spain. Trend analysis (Mann-Kendall text, p <0,10) confirms great spatial and temporal variability in the behaviour of precipitation across Spain between 1946-2005. Except March, June and October, no generalized significant pattern have been found, but subregional areas with homogeneous trend were detected. MOPREDAS shows a global decrease of precipitation in March that affects 68.9% of Spain and 31.8% in June, while in October the area affected by positive trends is 33.7% of land (p<0.10). We detected numerous sub-regional coherent patterns well delineated by topographic factors, and passing unnoticed until now due to inadequate data density. These results suggest that both global and local factors affect the spatial distribution of trends in the Iberian Peninsula, being mountain chains the most significant geographical factor in determining the spatial distribution of monthly trends on a detailed, sub-regional spatial scale.

Nucleation and Growth of Ordered Arrays of Silver Nanoparticles on Peptide Nanofibers: Hybrid Nanostructures with Antimicrobial Properties

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

Pazos, Elena; Sleep, Eduard; Rubert Perez, Charles M.

Here, silver nanoparticles have been of great interest as plasmonic substrates for sensing and imaging, catalysts, or antimicrobial systems. Their physical properties are strongly dependent on parameters that remain challenging to control such as size, chemical composition, and spatial distribution. We report here on supramolecular assemblies of a novel peptide amphiphile containing aldehyde functionality in order to reduce silver ions and subsequently nucleate silver metal nanoparticles in water. This system spontaneously generates monodisperse silver particles at fairly regular distances along the length of the filamentous organic assemblies. The metal–organic hybrid structures exhibited antimicrobial activity and significantly less toxicity toward eukaryoticmore » cells. Metallized organic nanofibers of the type described here offer the possibility to create hydrogels, which integrate the useful functions of silver nanoparticles with controllable metallic content.« less

Nucleation and Growth of Ordered Arrays of Silver Nanoparticles on Peptide Nanofibers: Hybrid Nanostructures with Antimicrobial Properties

DOE PAGES

Pazos, Elena; Sleep, Eduard; Rubert Perez, Charles M.; ...

2016-04-22

Here, silver nanoparticles have been of great interest as plasmonic substrates for sensing and imaging, catalysts, or antimicrobial systems. Their physical properties are strongly dependent on parameters that remain challenging to control such as size, chemical composition, and spatial distribution. We report here on supramolecular assemblies of a novel peptide amphiphile containing aldehyde functionality in order to reduce silver ions and subsequently nucleate silver metal nanoparticles in water. This system spontaneously generates monodisperse silver particles at fairly regular distances along the length of the filamentous organic assemblies. The metal–organic hybrid structures exhibited antimicrobial activity and significantly less toxicity toward eukaryoticmore » cells. Metallized organic nanofibers of the type described here offer the possibility to create hydrogels, which integrate the useful functions of silver nanoparticles with controllable metallic content.« less

Nucleation and Growth of Ordered Arrays of Silver Nanoparticles on Peptide Nanofibers: Hybrid Nanostructures with Antimicrobial Properties.

PubMed

Pazos, Elena; Sleep, Eduard; Rubert Pérez, Charles M; Lee, Sungsoo S; Tantakitti, Faifan; Stupp, Samuel I

2016-05-04

Silver nanoparticles have been of great interest as plasmonic substrates for sensing and imaging, catalysts, or antimicrobial systems. Their physical properties are strongly dependent on parameters that remain challenging to control such as size, chemical composition, and spatial distribution. We report here on supramolecular assemblies of a novel peptide amphiphile containing aldehyde functionality in order to reduce silver ions and subsequently nucleate silver metal nanoparticles in water. This system spontaneously generates monodisperse silver particles at fairly regular distances along the length of the filamentous organic assemblies. The metal-organic hybrid structures exhibited antimicrobial activity and significantly less toxicity toward eukaryotic cells. Metallized organic nanofibers of the type described here offer the possibility to create hydrogels, which integrate the useful functions of silver nanoparticles with controllable metallic content.

Maxwell-Wagner relaxation in electrical imaging.

PubMed

Korjenevsky, A V

2005-04-01

The electric field tomography (EFT) method exploits interaction of high-frequency electric field with an inhomogeneous conductive medium without contact with the electrodes. The interaction is accompanied by a high-frequency redistribution of free charges inside the medium and leads to small and regular phase shifts of the field in the area surrounding an object. Such a kind of phenomenon is referred to as the Maxwell-Wagner relaxation. Measuring the perturbations of the field using the set of electrodes placed around the object enables us to reconstruct the internal structure of the medium, generally the spatial distribution of a nonlinear combination of permittivity and resistivity. In the case of biomedical applications the result of measurements is determined mainly by the resistivity of the tissues. Three-dimensional simulation based on the finite element method has demonstrated the feasibility of the technique.

Motion-adaptive spatio-temporal regularization for accelerated dynamic MRI.

PubMed

Asif, M Salman; Hamilton, Lei; Brummer, Marijn; Romberg, Justin

2013-09-01

Accelerated magnetic resonance imaging techniques reduce signal acquisition time by undersampling k-space. A fundamental problem in accelerated magnetic resonance imaging is the recovery of quality images from undersampled k-space data. Current state-of-the-art recovery algorithms exploit the spatial and temporal structures in underlying images to improve the reconstruction quality. In recent years, compressed sensing theory has helped formulate mathematical principles and conditions that ensure recovery of (structured) sparse signals from undersampled, incoherent measurements. In this article, a new recovery algorithm, motion-adaptive spatio-temporal regularization, is presented that uses spatial and temporal structured sparsity of MR images in the compressed sensing framework to recover dynamic MR images from highly undersampled k-space data. In contrast to existing algorithms, our proposed algorithm models temporal sparsity using motion-adaptive linear transformations between neighboring images. The efficiency of motion-adaptive spatio-temporal regularization is demonstrated with experiments on cardiac magnetic resonance imaging for a range of reduction factors. Results are also compared with k-t FOCUSS with motion estimation and compensation-another recently proposed recovery algorithm for dynamic magnetic resonance imaging. . Copyright © 2012 Wiley Periodicals, Inc.

Computational photoacoustic imaging with sparsity-based optimization of the initial pressure distribution

NASA Astrophysics Data System (ADS)

Shang, Ruibo; Archibald, Richard; Gelb, Anne; Luke, Geoffrey P.

2018-02-01

In photoacoustic (PA) imaging, the optical absorption can be acquired from the initial pressure distribution (IPD). An accurate reconstruction of the IPD will be very helpful for the reconstruction of the optical absorption. However, the image quality of PA imaging in scattering media is deteriorated by the acoustic diffraction, imaging artifacts, and weak PA signals. In this paper, we propose a sparsity-based optimization approach that improves the reconstruction of the IPD in PA imaging. A linear imaging forward model was set up based on time-and-delay method with the assumption that the point spread function (PSF) is spatial invariant. Then, an optimization equation was proposed with a regularization term to denote the sparsity of the IPD in a certain domain to solve this inverse problem. As a proof of principle, the approach was applied to reconstructing point objects and blood vessel phantoms. The resolution and signal-to-noise ratio (SNR) were compared between conventional back-projection and our proposed approach. Overall these results show that computational imaging can leverage the sparsity of PA images to improve the estimation of the IPD.

Structural organisation and dynamics in king penguin colonies

NASA Astrophysics Data System (ADS)

Gerum, Richard; Richter, Sebastian; Fabry, Ben; Le Bohec, Céline; Bonadonna, Francesco; Nesterova, Anna; Zitterbart, Daniel P.

2018-04-01

During breeding, king penguins do not build nests, however they show strong territorial behaviour and keep a pecking distance to neighbouring penguins. Penguin positions in breeding colonies are highly stable over weeks and appear regularly spaced, but thus far no quantitative analysis of the structural order inside a colony has been performed. In this study, we use the radial distribution function to analyse the spatial coordinates of penguin positions. Coordinates are obtained from aerial images of two colonies that were observed for several years. Our data demonstrate that the structural order in king penguin colonies resembles a 2D liquid of particles with a Lennard-Jones-type interaction potential. We verify this using a molecular dynamics simulation with thermally driven particles, whereby temperature corresponds to penguin movements, the energy well depth ɛ of the attractive potential corresponds to the strength of the colony-forming behaviour, and the repulsive zone corresponds to the pecking radius. We can recapitulate the liquid disorder of the colony, as measured by the radial distribution function, when the particles have a temperature of several (1.4–10) \

Influence of different rates of rainfall in the basin of the Uruguay River

NASA Astrophysics Data System (ADS)

Bohrer, M.; Zaparoli, B.; Saldanha, C. B.

2013-04-01

In the state of Rio Grande do Sul, the rainfall pattern is fairly regular and precipitation is well distributed throughout the year. The aim of this study was to evaluate the spatial and temporal distribution of precipitation in the Uruguay River basin from the determination of homogeneous regions based on the rainfall pattern. Values of 47 meteorological stations of the ANA (National Water Agency) from 1975 to 2005 were used, and values of Pacific sea surface temperature were collected from the National Oceanic and Atmospheric Administration, which is based on observed anomalies for different regions' niños (1 + niño 2, 3 niño, niño 4, niño 3 + 4). From the analysis of the results it was found that the study region showed five homogeneous regions. Knowing the time series of each region, it was possible to verify the regional variability in precipitation, indicating which regions have values above and below the climatological normal, and how the different indexes influence the rainfall pattern in the region.

Contrasting evolutionary patterns in two reef-corals and their possible relationship to life history traits

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

Foster, A.B.

1985-01-01

Multivariate statistical analyses have been used to redefine species within two genera of reef-corals (Porites and Montastraea) and to trace their evolutionary patterns through a continuous sequence from late Miocene to early Pliocene time. The material studied consists of populations sampled at regular intervals through four stratigraphic sections in the northern Dominican Republic. The results show that species in the first genus (Porites) have relatively short durations, morphologic stability, and narrow spatial distributions. Their overall evolutionary history is characterized by short periods of radiation and widespread extinction, separated by longer periods of stasis. In contrast, species in the second genusmore » (Montastraea) exhibit various different durations and distributions and directional morphologic trends. These differences in patterns may be related to the dissimilar life histories of the two genera. Patterns in the first genus appear more common in organisms having high larval recruitment, high mortality, high genetic variation, and less morphologic distance between species. Patterns in the second genus occur more frequently in slower growing, phenotypically plastic organisms experiencing less recruitment and mortality and showing more morphologic distance between species.« less

Description of waves in inhomogeneous domains using Heun's equation

NASA Astrophysics Data System (ADS)

Bednarik, M.; Cervenka, M.

2018-04-01

There are a number of model equations describing electromagnetic, acoustic or quantum waves in inhomogeneous domains and some of them are of the same type from the mathematical point of view. This isomorphism enables us to use a unified approach to solving the corresponding equations. In this paper, the inhomogeneity is represented by a trigonometric spatial distribution of a parameter determining the properties of an inhomogeneous domain. From the point of view of modeling, this trigonometric parameter function can be smoothly connected to neighboring constant-parameter regions. For this type of distribution, exact local solutions of the model equations are represented by the local Heun functions. As the interval for which the solution is sought includes two regular singular points. For this reason, a method is proposed which resolves this problem only based on the local Heun functions. Further, the transfer matrix for the considered inhomogeneous domain is determined by means of the proposed method. As an example of the applicability of the presented solutions the transmission coefficient is calculated for the locally periodic structure which is given by an array of asymmetric barriers.

Spatial Probability Dynamically Modulates Visual Target Detection in Chickens

PubMed Central

Sridharan, Devarajan; Ramamurthy, Deepa L.; Knudsen, Eric I.

2013-01-01

The natural world contains a rich and ever-changing landscape of sensory information. To survive, an organism must be able to flexibly and rapidly locate the most relevant sources of information at any time. Humans and non-human primates exploit regularities in the spatial distribution of relevant stimuli (targets) to improve detection at locations of high target probability. Is the ability to flexibly modify behavior based on visual experience unique to primates? Chickens (Gallus domesticus) were trained on a multiple alternative Go/NoGo task to detect a small, briefly-flashed dot (target) in each of the quadrants of the visual field. When targets were presented with equal probability (25%) in each quadrant, chickens exhibited a distinct advantage for detecting targets at lower, relative to upper, hemifield locations. Increasing the probability of presentation in the upper hemifield locations (to 80%) dramatically improved detection performance at these locations to be on par with lower hemifield performance. Finally, detection performance in the upper hemifield changed on a rapid timescale, improving with successive target detections, and declining with successive detections at the diagonally opposite location in the lower hemifield. These data indicate the action of a process that in chickens, as in primates, flexibly and dynamically modulates detection performance based on the spatial probabilities of sensory stimuli as well as on recent performance history. PMID:23734188

Coordinated Speed Oscillations in Schooling Killifish Enrich Social Communication

NASA Astrophysics Data System (ADS)

Swain, Daniel T.; Couzin, Iain D.; Leonard, Naomi Ehrich

2015-10-01

We examine the spatial dynamics of individuals in small schools of banded killifish ( Fundulus diaphanus) that exhibit rhythmic, oscillating speed, typically with sustained, coordinated, out-of-phase speed oscillations as they move around a shallow water tank. We show that the relative motion among the fish yields a periodically time-varying network of social interactions that enriches visually driven social communication. The oscillations lead to the regular making and breaking of occlusions, which we term "switching." We show that the rate of convergence to consensus (biologically, the capacity for individuals in groups to achieve effective coordinated motion) governed by the switching outperforms static alternatives, and performs as well as the less practical case of every fish sensing every other fish. We show further that the oscillations in speed yield oscillations in relative bearing between fish over a range that includes the angles previously predicted to be optimal for a fish to detect changes in heading and speed of its neighbors. To investigate systematically, we derive and analyze a dynamic model of interacting agents that move with oscillatory speed. We show that coordinated circular motion of the school leads to systematic cycling of spatial ordering of agents and possibilities for enriched spatial density of measurements of the external environment. Our results highlight the potential benefits of dynamic communication topologies in collective animal behavior, and suggest new, useful control laws for the distributed coordination of mobile robotic networks.

Evaluation of socio-spatial vulnerability of citydwellers and analysis of risk perception: industrial and seismic risks in Mulhouse

NASA Astrophysics Data System (ADS)

Glatron, S.; Beck, E.

2008-10-01

Social vulnerability has been studied for years with sociological, psychological and economical approaches. Our proposition focuses on perception and cognitive representations of risks by city dwellers living in a medium size urban area, namely Mulhouse (France). Perception, being part of the social vulnerability and resilience of the society to disasters, influences the potential damage; for example it leads to adequate or inadequate behaviour in the case of an emergency. As geographers, we assume that the spatial relationship to danger or hazard can be an important factor of vulnerability and we feel that the spatial dimension is a challenging question either for better knowledge or for operational reasons (e.g. management of preventive information). We interviewed 491 people, inhabitants and workers, regularly distributed within the urban area to get to know their opinion on hazards and security measures better. We designed and mapped a vulnerability index on the basis of their answers. The results show that the social vulnerability depends on the type of hazard, and that the distance to the source of danger influences the vulnerability, especially for hazards with a precise location (industrial for example). Moreover, the effectiveness of the information campaigns is doubtful, as the people living close to hazardous industries (target of specific preventive information) are surprisingly more vulnerable and less aware of industrial risk.

New central configurations of the (n + 1) -body problem

NASA Astrophysics Data System (ADS)

Fernandes, Antonio Carlos; Garcia, Braulio Augusto; Llibre, Jaume; Mello, Luis Fernando

2018-01-01

In this article we study central configurations of the (n + 1) -body problem. For the planar (n + 1) -body problem we study central configurations performed by n ≥ 2 bodies with equal masses at the vertices of a regular n-gon and one body with null mass. We also study spatial central configurations considering n bodies with equal masses at the vertices of a regular polyhedron and one body with null mass.

A fully Galerkin method for the recovery of stiffness and damping parameters in Euler-Bernoulli beam models

NASA Technical Reports Server (NTRS)

Smith, R. C.; Bowers, K. L.

1991-01-01

A fully Sinc-Galerkin method for recovering the spatially varying stiffness and damping parameters in Euler-Bernoulli beam models is presented. The forward problems are discretized with a sinc basis in both the spatial and temporal domains thus yielding an approximate solution which converges exponentially and is valid on the infinite time interval. Hence the method avoids the time-stepping which is characteristic of many of the forward schemes which are used in parameter recovery algorithms. Tikhonov regularization is used to stabilize the resulting inverse problem, and the L-curve method for determining an appropriate value of the regularization parameter is briefly discussed. Numerical examples are given which demonstrate the applicability of the method for both individual and simultaneous recovery of the material parameters.

Temporal and Spatial Diversity of Bacterial Communities in Coastal Waters of the South China Sea

PubMed Central

Du, Jikun; Xiao, Kai; Li, Li; Ding, Xian; Liu, Helu; Lu, Yongjun; Zhou, Shining

2013-01-01

Bacteria are recognized as important drivers of biogeochemical processes in all aquatic ecosystems. Temporal and geographical patterns in ocean bacterial communities have been observed in many studies, but the temporal and spatial patterns in the bacterial communities from the South China Sea remained unexplored. To determine the spatiotemporal patterns, we generated 16S rRNA datasets for 15 samples collected from the five regularly distributed sites of the South China Sea in three seasons (spring, summer, winter). A total of 491 representative sequences were analyzed by MOTHUR, yielding 282 operational taxonomic units (OTUs) grouped at 97% stringency. Significant temporal variations of bacterial diversity were observed. Richness and diversity indices indicated that summer samples were the most diverse. The main bacterial group in spring and summer samples was Alphaproteobacteria, followed by Cyanobacteria and Gammaproteobacteria, whereas Cyanobacteria dominated the winter samples. Spatial patterns in the samples were observed that samples collected from the coastal (D151, D221) waters and offshore (D157, D1512, D224) waters clustered separately, the coastal samples harbored more diverse bacterial communities. However, the temporal pattern of the coastal site D151 was contrary to that of the coastal site D221. The LIBSHUFF statistics revealed noticeable differences among the spring, summer and winter libraries collected at five sites. The UPGMA tree showed there were temporal and spatial heterogeneity of bacterial community composition in coastal waters of the South China Sea. The water salinity (P=0.001) contributed significantly to the bacteria-environment relationship. Our results revealed that bacterial community structures were influenced by environmental factors and community-level changes in 16S-based diversity were better explained by spatial patterns than by temporal patterns. PMID:23785512

Decision Support System for hydrological extremes

NASA Astrophysics Data System (ADS)

Bobée, Bernard; El Adlouni, Salaheddine

2014-05-01

The study of the tail behaviour of extreme event distributions is important in several applied statistical fields such as hydrology, finance, and telecommunications. For example in hydrology, it is important to estimate adequately extreme quantiles in order to build and manage safe and effective hydraulic structures (dams, for example). Two main classes of distributions are used in hydrological frequency analysis: the class D of sub-exponential (Gamma (G2), Gumbel, Halphen type A (HA), Halphen type B (HB)…) and the class C of regularly varying distributions (Fréchet, Log-Pearson, Halphen type IB …) with a heavier tail. A Decision Support System (DSS) based on the characterization of the right tail, corresponding low probability of excedence p (high return period T=1/p, in hydrology), has been developed. The DSS allows discriminating between the class C and D and in its last version, a new prior step is added in order to test Lognormality. Indeed, the right tail of the Lognormal distribution (LN) is between the tails of distributions of the classes C and D; studies indicated difficulty with the discrimination between LN and distributions of the classes C and D. Other tools are useful to discriminate between distributions of the same class D (HA, HB and G2; see other communication). Some numerical illustrations show that, the DSS allows discriminating between Lognormal, regularly varying and sub-exponential distributions; and lead to coherent conclusions. Key words: Regularly varying distributions, subexponential distributions, Decision Support System, Heavy tailed distribution, Extreme value theory

Regularization of soft-X-ray imaging in the DIII-D tokamak

DOE PAGES

Wingen, A.; Shafer, M. W.; Unterberg, E. A.; ...

2015-03-02

We developed an image inversion scheme for the soft X-ray imaging system (SXRIS) diagnostic at the DIII-D tokamak in order to obtain the local soft X-ray emission at a poloidal cross-section from the spatially line-integrated image taken by the SXRIS camera. The scheme uses the Tikhonov regularization method since the inversion problem is generally ill-posed. The regularization technique uses the generalized singular value decomposition to determine a solution that depends on a free regularization parameter. The latter has to be chosen carefully, and the so called {\\it L-curve} method to find the optimum regularization parameter is outlined. A representative testmore » image is used to study the properties of the inversion scheme with respect to inversion accuracy, amount/strength of regularization, image noise and image resolution. Moreover, the optimum inversion parameters are identified, while the L-curve method successfully computes the optimum regularization parameter. Noise is found to be the most limiting issue, but sufficient regularization is still possible at noise to signal ratios up to 10%-15%. Finally, the inversion scheme is applied to measured SXRIS data and the line-integrated SXRIS image is successfully inverted.« less

Spatial analysis of cities using Renyi entropy and fractal parameters

NASA Astrophysics Data System (ADS)

Chen, Yanguang; Feng, Jian

2017-12-01

The spatial distributions of cities fall into two groups: one is the simple distribution with characteristic scale (e.g. exponential distribution), and the other is the complex distribution without characteristic scale (e.g. power-law distribution). The latter belongs to scale-free distributions, which can be modeled with fractal geometry. However, fractal dimension is not suitable for the former distribution. In contrast, spatial entropy can be used to measure any types of urban distributions. This paper is devoted to generalizing multifractal parameters by means of dual relation between Euclidean and fractal geometries. The main method is mathematical derivation and empirical analysis, and the theoretical foundation is the discovery that the normalized fractal dimension is equal to the normalized entropy. Based on this finding, a set of useful spatial indexes termed dummy multifractal parameters are defined for geographical analysis. These indexes can be employed to describe both the simple distributions and complex distributions. The dummy multifractal indexes are applied to the population density distribution of Hangzhou city, China. The calculation results reveal the feature of spatio-temporal evolution of Hangzhou's urban morphology. This study indicates that fractal dimension and spatial entropy can be combined to produce a new methodology for spatial analysis of city development.

Size-distribution analysis of macromolecules by sedimentation velocity ultracentrifugation and lamm equation modeling.

PubMed

Schuck, P

2000-03-01

A new method for the size-distribution analysis of polymers by sedimentation velocity analytical ultracentrifugation is described. It exploits the ability of Lamm equation modeling to discriminate between the spreading of the sedimentation boundary arising from sample heterogeneity and from diffusion. Finite element solutions of the Lamm equation for a large number of discrete noninteracting species are combined with maximum entropy regularization to represent a continuous size-distribution. As in the program CONTIN, the parameter governing the regularization constraint is adjusted by variance analysis to a predefined confidence level. Estimates of the partial specific volume and the frictional ratio of the macromolecules are used to calculate the diffusion coefficients, resulting in relatively high-resolution sedimentation coefficient distributions c(s) or molar mass distributions c(M). It can be applied to interference optical data that exhibit systematic noise components, and it does not require solution or solvent plateaus to be established. More details on the size-distribution can be obtained than from van Holde-Weischet analysis. The sensitivity to the values of the regularization parameter and to the shape parameters is explored with the help of simulated sedimentation data of discrete and continuous model size distributions, and by applications to experimental data of continuous and discrete protein mixtures.

The Potential for Spatial Distribution Indices to Signal Thresholds in Marine Fish Biomass

PubMed Central

Reuchlin-Hugenholtz, Emilie

2015-01-01

The frequently observed positive relationship between fish population abundance and spatial distribution suggests that changes in distribution can be indicative of trends in abundance. If contractions in spatial distribution precede declines in spawning stock biomass (SSB), spatial distribution reference points could complement the SSB reference points that are commonly used in marine conservation biology and fisheries management. When relevant spatial distribution information is integrated into fisheries management and recovery plans, risks and uncertainties associated with a plan based solely on the SSB criterion would be reduced. To assess the added value of spatial distribution data, we examine the relationship between SSB and four metrics of spatial distribution intended to reflect changes in population range, concentration, and density for 10 demersal populations (9 species) inhabiting the Scotian Shelf, Northwest Atlantic. Our primary purpose is to assess their potential to serve as indices of SSB, using fisheries independent survey data. We find that metrics of density offer the best correlate of spawner biomass. A decline in the frequency of encountering high density areas is associated with, and in a few cases preceded by, rapid declines in SSB in 6 of 10 populations. Density-based indices have considerable potential to serve both as an indicator of SSB and as spatially based reference points in fisheries management. PMID:25789624

Design and implementation of a distributed large-scale spatial database system based on J2EE

NASA Astrophysics Data System (ADS)

Gong, Jianya; Chen, Nengcheng; Zhu, Xinyan; Zhang, Xia

2003-03-01

With the increasing maturity of distributed object technology, CORBA, .NET and EJB are universally used in traditional IT field. However, theories and practices of distributed spatial database need farther improvement in virtue of contradictions between large scale spatial data and limited network bandwidth or between transitory session and long transaction processing. Differences and trends among of CORBA, .NET and EJB are discussed in details, afterwards the concept, architecture and characteristic of distributed large-scale seamless spatial database system based on J2EE is provided, which contains GIS client application, web server, GIS application server and spatial data server. Moreover the design and implementation of components of GIS client application based on JavaBeans, the GIS engine based on servlet, the GIS Application server based on GIS enterprise JavaBeans(contains session bean and entity bean) are explained.Besides, the experiments of relation of spatial data and response time under different conditions are conducted, which proves that distributed spatial database system based on J2EE can be used to manage, distribute and share large scale spatial data on Internet. Lastly, a distributed large-scale seamless image database based on Internet is presented.

Spatial Point Pattern Analysis of Human Settlements and Geographical Associations in Eastern Coastal China — A Case Study

PubMed Central

Zhang, Zhonghao; Xiao, Rui; Shortridge, Ashton; Wu, Jiaping

2014-01-01

Understanding the spatial point pattern of human settlements and their geographical associations are important for understanding the drivers of land use and land cover change and the relationship between environmental and ecological processes on one hand and cultures and lifestyles on the other. In this study, a Geographic Information System (GIS) approach, Ripley’s K function and Monte Carlo simulation were used to investigate human settlement point patterns. Remotely sensed tools and regression models were employed to identify the effects of geographical determinants on settlement locations in the Wen-Tai region of eastern coastal China. Results indicated that human settlements displayed regular-random-cluster patterns from small to big scale. Most settlements located on the coastal plain presented either regular or random patterns, while those in hilly areas exhibited a clustered pattern. Moreover, clustered settlements were preferentially located at higher elevations with steeper slopes and south facing aspects than random or regular settlements. Regression showed that influences of topographic factors (elevation, slope and aspect) on settlement locations were stronger across hilly regions. This study demonstrated a new approach to analyzing the spatial patterns of human settlements from a wide geographical prospective. We argue that the spatial point patterns of settlements, in addition to the characteristics of human settlements, such as area, density and shape, should be taken into consideration in the future, and land planners and decision makers should pay more attention to city planning and management. Conceptual and methodological bridges linking settlement patterns to regional and site-specific geographical characteristics will be a key to human settlement studies and planning. PMID:24619117

Effective noise-suppressed and artifact-reduced reconstruction of SPECT data using a preconditioned alternating projection algorithm

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

Li, Si; Xu, Yuesheng, E-mail: yxu06@syr.edu; Zhang, Jiahan

Purpose: The authors have recently developed a preconditioned alternating projection algorithm (PAPA) with total variation (TV) regularizer for solving the penalized-likelihood optimization model for single-photon emission computed tomography (SPECT) reconstruction. This algorithm belongs to a novel class of fixed-point proximity methods. The goal of this work is to investigate how PAPA performs while dealing with realistic noisy SPECT data, to compare its performance with more conventional methods, and to address issues with TV artifacts by proposing a novel form of the algorithm invoking high-order TV regularization, denoted as HOTV-PAPA, which has been explored and studied extensively in the present work.more » Methods: Using Monte Carlo methods, the authors simulate noisy SPECT data from two water cylinders; one contains lumpy “warm” background and “hot” lesions of various sizes with Gaussian activity distribution, and the other is a reference cylinder without hot lesions. The authors study the performance of HOTV-PAPA and compare it with PAPA using first-order TV regularization (TV-PAPA), the Panin–Zeng–Gullberg one-step-late method with TV regularization (TV-OSL), and an expectation–maximization algorithm with Gaussian postfilter (GPF-EM). The authors select penalty-weights (hyperparameters) by qualitatively balancing the trade-off between resolution and image noise separately for TV-PAPA and TV-OSL. However, the authors arrived at the same penalty-weight value for both of them. The authors set the first penalty-weight in HOTV-PAPA equal to the optimal penalty-weight found for TV-PAPA. The second penalty-weight needed for HOTV-PAPA is tuned by balancing resolution and the severity of staircase artifacts. The authors adjust the Gaussian postfilter to approximately match the local point spread function of GPF-EM and HOTV-PAPA. The authors examine hot lesion detectability, study local spatial resolution, analyze background noise properties, estimate mean square errors (MSEs), and report the convergence speed and computation time. Results: HOTV-PAPA yields the best signal-to-noise ratio, followed by TV-PAPA and TV-OSL/GPF-EM. The local spatial resolution of HOTV-PAPA is somewhat worse than that of TV-PAPA and TV-OSL. Images reconstructed using HOTV-PAPA have the lowest local noise power spectrum (LNPS) amplitudes, followed by TV-PAPA, TV-OSL, and GPF-EM. The LNPS peak of GPF-EM is shifted toward higher spatial frequencies than those for the three other methods. The PAPA-type methods exhibit much lower ensemble noise, ensemble voxel variance, and image roughness. HOTV-PAPA performs best in these categories. Whereas images reconstructed using both TV-PAPA and TV-OSL are degraded by severe staircase artifacts; HOTV-PAPA substantially reduces such artifacts. It also converges faster than the other three methods and exhibits the lowest overall reconstruction error level, as measured by MSE. Conclusions: For high-noise simulated SPECT data, HOTV-PAPA outperforms TV-PAPA, GPF-EM, and TV-OSL in terms of hot lesion detectability, noise suppression, MSE, and computational efficiency. Unlike TV-PAPA and TV-OSL, HOTV-PAPA does not create sizable staircase artifacts. Moreover, HOTV-PAPA effectively suppresses noise, with only limited loss of local spatial resolution. Of the four methods, HOTV-PAPA shows the best lesion detectability, thanks to its superior noise suppression. HOTV-PAPA shows promise for clinically useful reconstructions of low-dose SPECT data.« less

Effective noise-suppressed and artifact-reduced reconstruction of SPECT data using a preconditioned alternating projection algorithm

PubMed Central

Li, Si; Zhang, Jiahan; Krol, Andrzej; Schmidtlein, C. Ross; Vogelsang, Levon; Shen, Lixin; Lipson, Edward; Feiglin, David; Xu, Yuesheng

2015-01-01

Purpose: The authors have recently developed a preconditioned alternating projection algorithm (PAPA) with total variation (TV) regularizer for solving the penalized-likelihood optimization model for single-photon emission computed tomography (SPECT) reconstruction. This algorithm belongs to a novel class of fixed-point proximity methods. The goal of this work is to investigate how PAPA performs while dealing with realistic noisy SPECT data, to compare its performance with more conventional methods, and to address issues with TV artifacts by proposing a novel form of the algorithm invoking high-order TV regularization, denoted as HOTV-PAPA, which has been explored and studied extensively in the present work. Methods: Using Monte Carlo methods, the authors simulate noisy SPECT data from two water cylinders; one contains lumpy “warm” background and “hot” lesions of various sizes with Gaussian activity distribution, and the other is a reference cylinder without hot lesions. The authors study the performance of HOTV-PAPA and compare it with PAPA using first-order TV regularization (TV-PAPA), the Panin–Zeng–Gullberg one-step-late method with TV regularization (TV-OSL), and an expectation–maximization algorithm with Gaussian postfilter (GPF-EM). The authors select penalty-weights (hyperparameters) by qualitatively balancing the trade-off between resolution and image noise separately for TV-PAPA and TV-OSL. However, the authors arrived at the same penalty-weight value for both of them. The authors set the first penalty-weight in HOTV-PAPA equal to the optimal penalty-weight found for TV-PAPA. The second penalty-weight needed for HOTV-PAPA is tuned by balancing resolution and the severity of staircase artifacts. The authors adjust the Gaussian postfilter to approximately match the local point spread function of GPF-EM and HOTV-PAPA. The authors examine hot lesion detectability, study local spatial resolution, analyze background noise properties, estimate mean square errors (MSEs), and report the convergence speed and computation time. Results: HOTV-PAPA yields the best signal-to-noise ratio, followed by TV-PAPA and TV-OSL/GPF-EM. The local spatial resolution of HOTV-PAPA is somewhat worse than that of TV-PAPA and TV-OSL. Images reconstructed using HOTV-PAPA have the lowest local noise power spectrum (LNPS) amplitudes, followed by TV-PAPA, TV-OSL, and GPF-EM. The LNPS peak of GPF-EM is shifted toward higher spatial frequencies than those for the three other methods. The PAPA-type methods exhibit much lower ensemble noise, ensemble voxel variance, and image roughness. HOTV-PAPA performs best in these categories. Whereas images reconstructed using both TV-PAPA and TV-OSL are degraded by severe staircase artifacts; HOTV-PAPA substantially reduces such artifacts. It also converges faster than the other three methods and exhibits the lowest overall reconstruction error level, as measured by MSE. Conclusions: For high-noise simulated SPECT data, HOTV-PAPA outperforms TV-PAPA, GPF-EM, and TV-OSL in terms of hot lesion detectability, noise suppression, MSE, and computational efficiency. Unlike TV-PAPA and TV-OSL, HOTV-PAPA does not create sizable staircase artifacts. Moreover, HOTV-PAPA effectively suppresses noise, with only limited loss of local spatial resolution. Of the four methods, HOTV-PAPA shows the best lesion detectability, thanks to its superior noise suppression. HOTV-PAPA shows promise for clinically useful reconstructions of low-dose SPECT data. PMID:26233214

SU-F-T-436: A Method to Evaluate Dosimetric Properties of SFGRT in Eclipse TPS

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

Xu, M; Tobias, R; Pankuch, M

Purpose: The objective was to develop a method for dose distribution calculation of spatially-fractionated-GRID-radiotherapy (SFGRT) in Eclipse treatment-planning-system (TPS). Methods: Patient treatment-plans with SFGRT for bulky tumors were generated in Varian Eclipse version11. A virtual structure based on the GRID pattern was created and registered to a patient CT image dataset. The virtual GRID structure was positioned on the iso-center level together with matching beam geometries to simulate a commercially available GRID block made of brass. This method overcame the difficulty in treatment-planning and dose-calculation due to the lack o-the option to insert a GRID block add-on in Eclipse TPS.more » The patient treatment-planning displayed GRID effects on the target, critical structures, and dose distribution. The dose calculations were compared to the measurement results in phantom. Results: The GRID block structure was created to follow the beam divergence to the patient CT images. The inserted virtual GRID block made it possible to calculate the dose distributions and profiles at various depths in Eclipse. The virtual GRID block was added as an option to TPS. The 3D representation of the isodose distribution of the spatially-fractionated beam was generated in axial, coronal, and sagittal planes. Physics of GRID can be different from that for fields shaped by regular blocks because the charge-particle-equilibrium cannot be guaranteed for small field openings. Output factor (OF) measurement was required to calculate the MU to deliver the prescribed dose. The calculated OF based on the virtual GRID agreed well with the measured OF in phantom. Conclusion: The method to create the virtual GRID block has been proposed for the first time in Eclipse TPS. The dosedistributions, in-plane and cross-plane profiles in PTV can be displayed in 3D-space. The calculated OF’s based on the virtual GRID model compare well to the measured OF’s for SFGRT clinical use.« less

Properties and spatial distribution of galaxy superclusters

NASA Astrophysics Data System (ADS)

Liivamägi, Lauri Juhan

2017-01-01

Astronomy is a science that can offer plenty of unforgettable imagery, and the large-scale distribution of galaxies is no exception. Among the first features the viewer's eye is likely to be drawn to, are large concentrations of galaxies - galaxy superclusters, contrasting to the seemingly empty regions beside them. Superclusters can extend from tens to over hundred megaparsecs, they contain from hundreds to thousands of galaxies, and many galaxy groups and clusters. Unlike galaxy clusters, superclusters are clearly unrelaxed systems, not gravitationally bound as crossing times exceed the age of the universe, and show little to no radial symmetry. Superclusters, as part of the large-scale structure, are sensitive to the initial power spectrum and the following evolution. They are massive enough to leave an imprint on the cosmic microwave background radiation. Superclusters can also provide an unique environment for their constituent galaxies and galaxy clusters. In this study we used two different observational and one simulated galaxy samples to create several catalogues of structures that, we think, correspond to what are generally considered galaxy superclusters. Superclusters were delineated as continuous over-dense regions in galaxy luminosity density fields. When calculating density fields several corrections were applied to remove small-scale redshift distortions and distance-dependent selection effects. Resulting catalogues of objects display robust statistical properties, showing that flux-limited galaxy samples can be used to create nearly volume-limited catalogues of superstructures. Generally, large superclusters can be regarded as massive, often branching filamentary structures, that are mainly characterised by their length. Smaller superclusters, on the other hand, can display a variety of shapes. Spatial distribution of superclusters shows large-scale variations, with high-density concentrations often found in semi-regularly spaced groups. Future studies are needed to quantify the relations between superclusters and finer details of the galaxy distribution. Supercluster catalogues from this thesis have already been used in numerous other studies.

Parrondo's games based on complex networks and the paradoxical effect.

PubMed

Ye, Ye; Wang, Lu; Xie, Nenggang

2013-01-01

Parrondo's games were first constructed using a simple tossing scenario, which demonstrates the following paradoxical situation: in sequences of games, a winning expectation may be obtained by playing the games in a random order, although each game (game A or game B) in the sequence may result in losing when played individually. The available Parrondo's games based on the spatial niche (the neighboring environment) are applied in the regular networks. The neighbors of each node are the same in the regular graphs, whereas they are different in the complex networks. Here, Parrondo's model based on complex networks is proposed, and a structure of game B applied in arbitrary topologies is constructed. The results confirm that Parrondo's paradox occurs. Moreover, the size of the region of the parameter space that elicits Parrondo's paradox depends on the heterogeneity of the degree distributions of the networks. The higher heterogeneity yields a larger region of the parameter space where the strong paradox occurs. In addition, we use scale-free networks to show that the network size has no significant influence on the region of the parameter space where the strong or weak Parrondo's paradox occurs. The region of the parameter space where the strong Parrondo's paradox occurs reduces slightly when the average degree of the network increases.

Combined ICA-LORETA analysis of mismatch negativity.

PubMed

Marco-Pallarés, J; Grau, C; Ruffini, G

2005-04-01

A major challenge for neuroscience is to map accurately the spatiotemporal patterns of activity of the large neuronal populations that are believed to underlie computing in the human brain. To study a specific example, we selected the mismatch negativity (MMN) brain wave (an event-related potential, ERP) because it gives an electrophysiological index of a "primitive intelligence" capable of detecting changes, even abstract ones, in a regular auditory pattern. ERPs have a temporal resolution of milliseconds but appear to result from mixed neuronal contributions whose spatial location is not fully understood. Thus, it is important to separate these sources in space and time. To tackle this problem, a two-step approach was designed combining the independent component analysis (ICA) and low-resolution tomography (LORETA) algorithms. Here we implement this approach to analyze the subsecond spatiotemporal dynamics of MMN cerebral sources using trial-by-trial experimental data. We show evidence that a cerebral computation mechanism underlies MMN. This mechanism is mediated by the orchestrated activity of several spatially distributed brain sources located in the temporal, frontal, and parietal areas, which activate at distinct time intervals and are grouped in six main statistically independent components.

A parallel implementation of an off-lattice individual-based model of multicellular populations

NASA Astrophysics Data System (ADS)

Harvey, Daniel G.; Fletcher, Alexander G.; Osborne, James M.; Pitt-Francis, Joe

2015-07-01

As computational models of multicellular populations include ever more detailed descriptions of biophysical and biochemical processes, the computational cost of simulating such models limits their ability to generate novel scientific hypotheses and testable predictions. While developments in microchip technology continue to increase the power of individual processors, parallel computing offers an immediate increase in available processing power. To make full use of parallel computing technology, it is necessary to develop specialised algorithms. To this end, we present a parallel algorithm for a class of off-lattice individual-based models of multicellular populations. The algorithm divides the spatial domain between computing processes and comprises communication routines that ensure the model is correctly simulated on multiple processors. The parallel algorithm is shown to accurately reproduce the results of a deterministic simulation performed using a pre-existing serial implementation. We test the scaling of computation time, memory use and load balancing as more processes are used to simulate a cell population of fixed size. We find approximate linear scaling of both speed-up and memory consumption on up to 32 processor cores. Dynamic load balancing is shown to provide speed-up for non-regular spatial distributions of cells in the case of a growing population.

How big should a mammal be? A macroecological look at mammalian body size over space and time

PubMed Central

Smith, Felisa A.; Lyons, S. Kathleen

2011-01-01

Macroecology was developed as a big picture statistical approach to the study of ecology and evolution. By focusing on broadly occurring patterns and processes operating at large spatial and temporal scales rather than on localized and/or fine-scaled details, macroecology aims to uncover general mechanisms operating at organism, population, and ecosystem levels of organization. Macroecological studies typically involve the statistical analysis of fundamental species-level traits, such as body size, area of geographical range, and average density and/or abundance. Here, we briefly review the history of macroecology and use the body size of mammals as a case study to highlight current developments in the field, including the increasing linkage with biogeography and other disciplines. Characterizing the factors underlying the spatial and temporal patterns of body size variation in mammals is a daunting task and moreover, one not readily amenable to traditional statistical analyses. Our results clearly illustrate remarkable regularities in the distribution and variation of mammalian body size across both geographical space and evolutionary time that are related to ecology and trophic dynamics and that would not be apparent without a broader perspective. PMID:21768152

Urban area thermal monitoring: Liepaja case study using satellite and aerial thermal data

NASA Astrophysics Data System (ADS)

Gulbe, Linda; Caune, Vairis; Korats, Gundars

2017-12-01

The aim of this study is to explore large (60 m/pixel) and small scale (individual building level) temperature distribution patterns from thermal remote sensing data and to conclude what kind of information could be extracted from thermal remote sensing on regular basis. Landsat program provides frequent large scale thermal images useful for analysis of city temperature patterns. During the study correlation between temperature patterns and vegetation content based on NDVI and building coverage based on OpenStreetMap data was studied. Landsat based temperature patterns were independent from the season, negatively correlated with vegetation content and positively correlated with building coverage. Small scale analysis included spatial and raster descriptor analysis for polygons corresponding to roofs of individual buildings for evaluating insulation of roofs. Remote sensing and spatial descriptors are poorly related to heat consumption data, however, thermal aerial data median and entropy can help to identify poorly insulated roofs. Automated quantitative roof analysis has high potential for acquiring city wide information about roof insulation, but quality is limited by reference data quality and information on building types, and roof materials would be crucial for further studies.

Salmonella Strains Isolated from Galápagos Iguanas Show Spatial Structuring of Serovar and Genomic Diversity

PubMed Central

Lankau, Emily W.; Cruz Bedon, Lenin; Mackie, Roderick I.

2012-01-01

It is thought that dispersal limitation primarily structures host-associated bacterial populations because host distributions inherently limit transmission opportunities. However, enteric bacteria may disperse great distances during food-borne outbreaks. It is unclear if such rapid long-distance dispersal events happen regularly in natural systems or if these events represent an anthropogenic exception. We characterized Salmonella enterica isolates from the feces of free-living Galápagos land and marine iguanas from five sites on four islands using serotyping and genomic fingerprinting. Each site hosted unique and nearly exclusive serovar assemblages. Genomic fingerprint analysis offered a more complex model of S. enterica biogeography, with evidence of both unique strain pools and of spatial population structuring along a geographic gradient. These findings suggest that even relatively generalist enteric bacteria may be strongly dispersal limited in a natural system with strong barriers, such as oceanic divides. Yet, these differing results seen on two typing methods also suggests that genomic variation is less dispersal limited, allowing for different ecological processes to shape biogeographical patterns of the core and flexible portions of this bacterial species' genome. PMID:22615968

Analysis of skin tissues spatial fluorescence distribution by the Monte Carlo simulation

NASA Astrophysics Data System (ADS)

Y Churmakov, D.; Meglinski, I. V.; Piletsky, S. A.; Greenhalgh, D. A.

2003-07-01

A novel Monte Carlo technique of simulation of spatial fluorescence distribution within the human skin is presented. The computational model of skin takes into account the spatial distribution of fluorophores, which would arise due to the structure of collagen fibres, compared to the epidermis and stratum corneum where the distribution of fluorophores is assumed to be homogeneous. The results of simulation suggest that distribution of auto-fluorescence is significantly suppressed in the near-infrared spectral region, whereas the spatial distribution of fluorescence sources within a sensor layer embedded in the epidermis is localized at an `effective' depth.

Olive cultivars adaptability in Southern Italy in present and future climate

NASA Astrophysics Data System (ADS)

Riccardi, M.; Alfieri, S.; Bonfante, A.; Basile, A.; Di Tommasi, P.; Menenti, M.; De Lorenzi, F.

2012-04-01

The intra-specific biodiversity of agricultural crops is very significant and likely to provide the single major opportunity to cope with the effects of the changing climate on agricultural ecosystems. Assessment of adaptive capacity must rely on quantitative descriptions of plant responses to environmental factors (e.g. soil water availability, temperature). Moreover climate scenario needs to be downscaled to the spatial scale relevant to crop and farm management. Distributed models of crop response to environmental forcing might be used for this purpose, but severely constrained by the very scarce knowledge on variety-specific values of model parameters, thus limiting the potential exploitation of intra-specific biodiversity towards adaptation. We have developed an approach towards this objective that relies on two complementary elements: a)a distributed model of the soil plant atmosphere system to downscale climate scenarios to landscape units, where generic model parameters for each species are used; b)a data base on climatic requirements of as many varieties as feasible for each species relevant to the agricultural production system of a given region. By means of this approach, the adaptability of some olive cultivars was evaluated in a composite (hills and plains) area of Southern Italy (Valle Telesina, Campania Region, about 20.000 ha). The yearly average temperature is 22.5 °C and rainfall ranges between 600 and 900 mm. Two different climate scenarios were considered: current climate (1961-1990) and future climate (2021-2050). Future climate scenarios at low spatial resolution were generated with general circulation models (AOGCM) and down-scaled by means of a statistical model (Tomozeiu et al., 2007). The climate was represented by daily observations of minimum, maximum temperature and precipitation on a regular grid with a spatial resolution of 35 km; 50 realizations were used for future climate. The soil water regime of 45 soil units was described for the two climate scenarios by using an hydrological distributed model (SWAP). For 11 olive cultivars, the yield response function to soil water regime was determined through the re-analysis of experimental data (unpublished or derived from scientific literature). According to these responses, cultivar-specific threshold values of soil water (or evapotranspiration) deficit were defined. The soil water regime calculated by the distributed model was compared with the threshold values to identify cultivars compatible with present and expected climates. The operation is repeated for a set of realizations of each climate scenario. This analysis is performed in a distributed manner, i.e. using the time series for each model grid to assess possible variations in the extent and spatial distribution of cultivated area of olive cultivars. In the study area future climate scenarios predict an increase of monthly minimum and maximum air temperature of about 2°C during the summer (June, July and August) and a reduction of rainfall in autumn. Spatial pattern of cultivars distribution, according their threshold values and soil water regime, was determined in the present and future climate scenarios, thus assessing variations in cultivars adaptability to future climate with respect to the present. Key words: climate change, biodiversity, water availability, yield response. The work was carried out within the Italian national project AGROSCENARI funded by the Ministry for Agricultural, Food and Forest Policies (MIPAAF, D.M. 8608/7303/2008).

Presence-only Species Distribution Modeling for King Mackerel (Scomberomorus cavalla) and its 31 Prey Species in the Gulf of Mexico

NASA Astrophysics Data System (ADS)

Cai, X.; Simons, J.; Carollo, C.; Sterba-Boatwright, B.; Sadovski, A.

2016-02-01

Ecosystem based fisheries management has been broadly recognized throughout the world as a way to achieve better conservation. Therefore, there is a strong need for mapping of multi-species interactions or spatial distributions. Species distribution models are widely applied since information regarding the presence of species is usually only available for limited locations due to the high cost of fisheries surveys. Instead of regular presence and absence records, a large proportion of the fisheries survey data have only presence records. This makes the modeling problem one of one-class classification (presence only), which is much more complex than the regular two-class classification (presence/absence). In this study, four different presence-only species distribution algorithms (Bioclim, Domain, Mahal and Maxent) were applied using 13 environmental parameters (e.g., depth, DO, bottom types) as predictors to model the distribution of king mackerel (Scomberomorus cavalla) and its 31 prey species in the Gulf of Mexico (a total of 13625 georeferenced presence records from OBIS and GBIF were used). Five-fold cross validations were applied for each of the 128 (4 algorithms × 32 species) models. Area under curve (AUC) and correlation coefficient (R) were used to evaluate the model performances. The AUC of the models based on these four algorithms were 0.83±0.14, 0.77±0.16, 0.94±0.06 and 0.94±0.06, respectively; while R for the models were 0.47±0.27, 0.43±0.24, 0.27±0.16 and 0.76±0.16, respectively. Post hoc with Tukey's test showed that AUC for the Maxent-based models were significantly (p<0.05) higher than those for Bioclim and Domain based models, but insignificantly different from those for Mahal-based models (p=0.955); while R for the Maxent-based models were significantly higher than those for all the other three types of models (p<0.05). Thus, we concluded that the Maxent-based models had the best performance. High AUC and R also indicated that Maxent-based models could provide robust and reliable results to model target species distributions, and they can be further used to model the king mackerel food web in the Gulf of Mexico to help managers better manage related fisheries resources.

Integrating satellite actual evapotranspiration patterns into distributed model parametrization and evaluation for a mesoscale catchment

NASA Astrophysics Data System (ADS)

Demirel, M. C.; Mai, J.; Stisen, S.; Mendiguren González, G.; Koch, J.; Samaniego, L. E.

2016-12-01

Distributed hydrologic models are traditionally calibrated and evaluated against observations of streamflow. Spatially distributed remote sensing observations offer a great opportunity to enhance spatial model calibration schemes. For that it is important to identify the model parameters that can change spatial patterns before the satellite based hydrologic model calibration. Our study is based on two main pillars: first we use spatial sensitivity analysis to identify the key parameters controlling the spatial distribution of actual evapotranspiration (AET). Second, we investigate the potential benefits of incorporating spatial patterns from MODIS data to calibrate the mesoscale Hydrologic Model (mHM). This distributed model is selected as it allows for a change in the spatial distribution of key soil parameters through the calibration of pedo-transfer function parameters and includes options for using fully distributed daily Leaf Area Index (LAI) directly as input. In addition the simulated AET can be estimated at the spatial resolution suitable for comparison to the spatial patterns observed using MODIS data. We introduce a new dynamic scaling function employing remotely sensed vegetation to downscale coarse reference evapotranspiration. In total, 17 parameters of 47 mHM parameters are identified using both sequential screening and Latin hypercube one-at-a-time sampling methods. The spatial patterns are found to be sensitive to the vegetation parameters whereas streamflow dynamics are sensitive to the PTF parameters. The results of multi-objective model calibration show that calibration of mHM against observed streamflow does not reduce the spatial errors in AET while they improve only the streamflow simulations. We will further examine the results of model calibration using only multi spatial objective functions measuring the association between observed AET and simulated AET maps and another case including spatial and streamflow metrics together.

Developing a Near Real-time System for Earthquake Slip Distribution Inversion

NASA Astrophysics Data System (ADS)

Zhao, Li; Hsieh, Ming-Che; Luo, Yan; Ji, Chen

2016-04-01

Advances in observational and computational seismology in the past two decades have enabled completely automatic and real-time determinations of the focal mechanisms of earthquake point sources. However, seismic radiations from moderate and large earthquakes often exhibit strong finite-source directivity effect, which is critically important for accurate ground motion estimations and earthquake damage assessments. Therefore, an effective procedure to determine earthquake rupture processes in near real-time is in high demand for hazard mitigation and risk assessment purposes. In this study, we develop an efficient waveform inversion approach for the purpose of solving for finite-fault models in 3D structure. Full slip distribution inversions are carried out based on the identified fault planes in the point-source solutions. To ensure efficiency in calculating 3D synthetics during slip distribution inversions, a database of strain Green tensors (SGT) is established for 3D structural model with realistic surface topography. The SGT database enables rapid calculations of accurate synthetic seismograms for waveform inversion on a regular desktop or even a laptop PC. We demonstrate our source inversion approach using two moderate earthquakes (Mw~6.0) in Taiwan and in mainland China. Our results show that 3D velocity model provides better waveform fitting with more spatially concentrated slip distributions. Our source inversion technique based on the SGT database is effective for semi-automatic, near real-time determinations of finite-source solutions for seismic hazard mitigation purposes.

On the Spatial Distribution of High Velocity Al-26 Near the Galactic Center

NASA Technical Reports Server (NTRS)

Sturner, Steven J.

2000-01-01

We present results of simulations of the distribution of 1809 keV radiation from the decay of Al-26 in the Galaxy. Recent observations of this emission line using the Gamma Ray Imaging Spectrometer (GRIS) have indicated that the bulk of the AL-26 must have a velocity of approx. 500 km/ s. We have previously shown that a velocity this large could be maintained over the 10(exp 6) year lifetime of the Al-26 if it is trapped in dust grains that are reaccelerated periodically in the ISM. Here we investigate whether a dust grain velocity of approx. 500 km/ s will produce a distribution of 1809 keV emission in latitude that is consistent with the narrow distribution seen by COMPTEL. We find that dust grain velocities in the range 275 - 1000 km/ s are able to reproduce the COMPTEL 1809 keV emission maps reconstructed using the Richardson-Lucy and Maximum Entropy image reconstruction methods while the emission map reconstructed using the Multiresolution Regularized Expectation Maximization algorithm is not well fit by any of our models. The Al-26 production rate that is needed to reproduce the observed 1809 keV intensity yields in a Galactic mass of Al-26 of approx. 1.5 - 2 solar mass which is in good agreement with both other observations and theoretical production rates.

Spatial self-organization in hybrid models of multicellular adhesion

NASA Astrophysics Data System (ADS)

Bonforti, Adriano; Duran-Nebreda, Salva; Montañez, Raúl; Solé, Ricard

2016-10-01

Spatial self-organization emerges in distributed systems exhibiting local interactions when nonlinearities and the appropriate propagation of signals are at work. These kinds of phenomena can be modeled with different frameworks, typically cellular automata or reaction-diffusion systems. A different class of dynamical processes involves the correlated movement of agents over space, which can be mediated through chemotactic movement or minimization of cell-cell interaction energy. A classic example of the latter is given by the formation of spatially segregated assemblies when cells display differential adhesion. Here, we consider a new class of dynamical models, involving cell adhesion among two stochastically exchangeable cell states as a minimal model capable of exhibiting well-defined, ordered spatial patterns. Our results suggest that a whole space of pattern-forming rules is hosted by the combination of physical differential adhesion and the value of probabilities modulating cell phenotypic switching, showing that Turing-like patterns can be obtained without resorting to reaction-diffusion processes. If the model is expanded allowing cells to proliferate and die in an environment where diffusible nutrient and toxic waste are at play, different phases are observed, characterized by regularly spaced patterns. The analysis of the parameter space reveals that certain phases reach higher population levels than other modes of organization. A detailed exploration of the mean-field theory is also presented. Finally, we let populations of cells with different adhesion matrices compete for reproduction, showing that, in our model, structural organization can improve the fitness of a given cell population. The implications of these results for ecological and evolutionary models of pattern formation and the emergence of multicellularity are outlined.

Core surface magnetic field evolution 2000-2010

NASA Astrophysics Data System (ADS)

Finlay, C. C.; Jackson, A.; Gillet, N.; Olsen, N.

2012-05-01

We present new dedicated core surface field models spanning the decade from 2000.0 to 2010.0. These models, called gufm-sat, are based on CHAMP, Ørsted and SAC-C satellite observations along with annual differences of processed observatory monthly means. A spatial parametrization of spherical harmonics up to degree and order 24 and a temporal parametrization of sixth-order B-splines with 0.25 yr knot spacing is employed. Models were constructed by minimizing an absolute deviation measure of misfit along with measures of spatial and temporal complexity at the core surface. We investigate traditional quadratic or maximum entropy regularization in space, and second or third time derivative regularization in time. Entropy regularization allows the construction of models with approximately constant spectral slope at the core surface, avoiding both the divergence characteristic of the crustal field and the unrealistic rapid decay typical of quadratic regularization at degrees above 12. We describe in detail aspects of the models that are relevant to core dynamics. Secular variation and secular acceleration are found to be of lower amplitude under the Pacific hemisphere where the core field is weaker. Rapid field evolution is observed under the eastern Indian Ocean associated with the growth and drift of an intense low latitude flux patch. We also find that the present axial dipole decay arises from a combination of subtle changes in the southern hemisphere field morphology.

Complex sparse spatial filter for decoding mixed frequency and phase coded steady-state visually evoked potentials.

PubMed

Morikawa, Naoki; Tanaka, Toshihisa; Islam, Md Rabiul

2018-07-01

Mixed frequency and phase coding (FPC) can achieve the significant increase of the number of commands in steady-state visual evoked potential-based brain-computer interface (SSVEP-BCI). However, the inconsistent phases of the SSVEP over channels in a trial and the existence of non-contributing channels due to noise effects can decrease accurate detection of stimulus frequency. We propose a novel command detection method based on a complex sparse spatial filter (CSSF) by solving ℓ 1 - and ℓ 2,1 -regularization problems for a mixed-coded SSVEP-BCI. In particular, ℓ 2,1 -regularization (aka group sparsification) can lead to the rejection of electrodes that are not contributing to the SSVEP detection. A calibration data based canonical correlation analysis (CCA) and CSSF with ℓ 1 - and ℓ 2,1 -regularization cases were demonstrated for a 16-target stimuli with eleven subjects. The results of statistical test suggest that the proposed method with ℓ 1 - and ℓ 2,1 -regularization significantly achieved the highest ITR. The proposed approaches do not need any reference signals, automatically select prominent channels, and reduce the computational cost compared to the other mixed frequency-phase coding (FPC)-based BCIs. The experimental results suggested that the proposed method can be usable implementing BCI effectively with reduce visual fatigue. Copyright © 2018 Elsevier B.V. All rights reserved.

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

Robinson, Judith; Johnson, Timothy C.; Slater, Lee D.

There is an increasing need to characterize discrete fractures away from boreholes to better define fracture distributions and monitor solute transport. We performed a 3D evaluation of static and time-lapse cross-borehole electrical resistivity tomography (ERT) data sets from a limestone quarry in which flow and transport are controlled by a bedding-plane feature. Ten boreholes were discretized using an unstructured tetrahedral mesh, and 2D panel measurements were inverted for a 3D distribution of conductivity. We evaluated the benefits of 3D versus 2.5D inversion of ERT data in fractured rock while including the use of borehole regularization disconnects (BRDs) and borehole conductivitymore » constraints. High-conductivity halos (inversion artifacts) surrounding boreholes were removed in static images when BRDs and borehole conductivity constraints were implemented. Furthermore, applying these constraints focused transient changes in conductivity resulting from solute transport on the bedding plane, providing a more physically reasonable model for conductivity changes associated with solute transport at this fractured rock site. Assuming bedding-plane continuity between fractures identified in borehole televiewer data, we discretized a planar region between six boreholes and applied a fracture regularization disconnect (FRD). Although the FRD appropriately focused conductivity changes on the bedding plane, the conductivity distribution within the discretized fracture was nonunique and dependent on the starting homogeneous model conductivity. Synthetic studies performed to better explain field observations showed that inaccurate electrode locations in boreholes resulted in low-conductivity halos surrounding borehole locations. These synthetic studies also showed that the recovery of the true conductivity within an FRD depended on the conductivity contrast between the host rock and fractures. Our findings revealed that the potential exists to improve imaging of fractured rock through 3D inversion and accurate modeling of boreholes. However, deregularization of localized features can result in significant electrical conductivity artifacts, especially when representing features with a high degree of spatial uncertainty.« less

Extracellular accumulations in the avian pituitary gland: histochemical analysis in two species of Indian wild birds.

PubMed

Mohanty, Banalata

2006-01-01

Extracellular accumulations of two distinct types, colloid-filled follicles and fibrous-material-containing cysts, were observed in the pituitary gland of two species of Indian wild birds, Halcyon smyrnensis perpulchra and Lonchura striata striata. Colloid follicles were regular structures and distributed throughout the pars distalis (PD). The fibrous cysts were irregular structures, bigger than the colloid follicles and mostly observed towards the ventral margin of the PD. Sometimes disruption of the outer margin with depletion of fibrous material from the cavity was observed. Hormone-secreting cells of various types, anti-adrenocorticotropic-hormone-, anti-prolactin-, anti-growth-hormone- and anti-luteinizing-hormone-immunoreactive cells were encountered bordering both the colloid follicles and fibrous cysts. Neither the colloid nor the fibrous material showed any immunoreaction to any of the pituitary hormone antisera. On histochemical staining colloid was positive to periodic acid-Schiff (PAS) and fibrous materials stained with Alcian blue-PAS-orange G staining. Colloid depositions in the pituitary gland of these two wild birds were correlated to age, more in numbers in the adult birds than in the young ones. Fibrous-material-containing cysts were elucidated in the pituitary gland of adult birds only. These were more prevalent in the pituitary of reproductively active birds. Regular morphology of the colloid follicles, overall distribution in the adenohypophysis and dense nature of deposition of the colloid suggest the accumulation of this type may be the secretory products of both granulated and agranulated pituitary cell types. Absence of immunoreactivity of the colloid against pituitary hormone antisera points out that the storage form may differ chemically from the bioactive hormones. The spatial distribution of fibrous-material-containing cysts mostly towards the ventral PD, observations of immunoreactive cell fragmentations inside the cysts, and their disrupted margins suggest these structures may have some role in discharging the intraglandular degradation products. 2006 S. Karger AG, Basel

Structural characterization of the packings of granular regular polygons.

PubMed

Wang, Chuncheng; Dong, Kejun; Yu, Aibing

2015-12-01

By using a recently developed method for discrete modeling of nonspherical particles, we simulate the random packings of granular regular polygons with three to 11 edges under gravity. The effects of shape and friction on the packing structures are investigated by various structural parameters, including packing fraction, the radial distribution function, coordination number, Voronoi tessellation, and bond-orientational order. We find that packing fraction is generally higher for geometrically nonfrustrated regular polygons, and can be increased by the increase of edge number and decrease of friction. The changes of packing fraction are linked with those of the microstructures, such as the variations of the translational and orientational orders and local configurations. In particular, the free areas of Voronoi tessellations (which are related to local packing fractions) can be described by log-normal distributions for all polygons. The quantitative analyses establish a clearer picture for the packings of regular polygons.

Bayesian soft X-ray tomography using non-stationary Gaussian Processes

NASA Astrophysics Data System (ADS)

Li, Dong; Svensson, J.; Thomsen, H.; Medina, F.; Werner, A.; Wolf, R.

2013-08-01

In this study, a Bayesian based non-stationary Gaussian Process (GP) method for the inference of soft X-ray emissivity distribution along with its associated uncertainties has been developed. For the investigation of equilibrium condition and fast magnetohydrodynamic behaviors in nuclear fusion plasmas, it is of importance to infer, especially in the plasma center, spatially resolved soft X-ray profiles from a limited number of noisy line integral measurements. For this ill-posed inversion problem, Bayesian probability theory can provide a posterior probability distribution over all possible solutions under given model assumptions. Specifically, the use of a non-stationary GP to model the emission allows the model to adapt to the varying length scales of the underlying diffusion process. In contrast to other conventional methods, the prior regularization is realized in a probability form which enhances the capability of uncertainty analysis, in consequence, scientists who concern the reliability of their results will benefit from it. Under the assumption of normally distributed noise, the posterior distribution evaluated at a discrete number of points becomes a multivariate normal distribution whose mean and covariance are analytically available, making inversions and calculation of uncertainty fast. Additionally, the hyper-parameters embedded in the model assumption can be optimized through a Bayesian Occam's Razor formalism and thereby automatically adjust the model complexity. This method is shown to produce convincing reconstructions and good agreements with independently calculated results from the Maximum Entropy and Equilibrium-Based Iterative Tomography Algorithm methods.

Bayesian soft X-ray tomography using non-stationary Gaussian Processes.

PubMed

Li, Dong; Svensson, J; Thomsen, H; Medina, F; Werner, A; Wolf, R

2013-08-01

In this study, a Bayesian based non-stationary Gaussian Process (GP) method for the inference of soft X-ray emissivity distribution along with its associated uncertainties has been developed. For the investigation of equilibrium condition and fast magnetohydrodynamic behaviors in nuclear fusion plasmas, it is of importance to infer, especially in the plasma center, spatially resolved soft X-ray profiles from a limited number of noisy line integral measurements. For this ill-posed inversion problem, Bayesian probability theory can provide a posterior probability distribution over all possible solutions under given model assumptions. Specifically, the use of a non-stationary GP to model the emission allows the model to adapt to the varying length scales of the underlying diffusion process. In contrast to other conventional methods, the prior regularization is realized in a probability form which enhances the capability of uncertainty analysis, in consequence, scientists who concern the reliability of their results will benefit from it. Under the assumption of normally distributed noise, the posterior distribution evaluated at a discrete number of points becomes a multivariate normal distribution whose mean and covariance are analytically available, making inversions and calculation of uncertainty fast. Additionally, the hyper-parameters embedded in the model assumption can be optimized through a Bayesian Occam's Razor formalism and thereby automatically adjust the model complexity. This method is shown to produce convincing reconstructions and good agreements with independently calculated results from the Maximum Entropy and Equilibrium-Based Iterative Tomography Algorithm methods.

Drinking Water Quality and the Geospatial Distribution of Notified Gastro-Intestinal Infections

PubMed Central

GRILC, Eva; GALE, Ivanka; VERŠIČ, Aleš; ŽAGAR, Tina; SOČAN, Maja

2015-01-01

Introduction Even brief episodes of fecal contamination of drinking water can lead directly to illness in the consumers. In water-borne outbreaks, the connection between poor microbial water quality and disease can be quickly identified. The impact of non-compliant drinking water samples due to E. coli taken for regular monitoring on the incidence of notified acute gastrointestinal infections has not yet been studied. Methods The objective of this study was to analyse the geographical distribution of notified acute gastrointestinal infections (AGI) in Slovenia in 2010, with hotspot identification. The second aim of the study was to correlate the fecal contamination of water supply system on the settlement level with the distribution of notified AGI cases. Spatial analysis using geo-information technology and other methods were used. Results Hot spots with the highest proportion of notified AGI cases were mainly identified in areas with small supply zones. The risk for getting AGI was drinking water contaminated with E. coli from supply zones with 50–1000 users: RR was 1.25 and significantly greater than one (p-value less than 0.001). Conclusion This study showed the correlation between the frequency of notified AGI cases and non-compliant results in drinking water monitoring. PMID:27646727

A karstic origin for the north polar lakes reveals a soluble Titan

NASA Astrophysics Data System (ADS)

Dhingra, Rajani; Barnes, Jason W.; Radebaugh, Jani; Hedman, Matthew M.

2017-10-01

We quantitatively test the karst hypothesis for the formation of Titan's lakes by comparing their morphometry to that of terrestrial karst lakes.Titan is the only place in our solar system other than the Earth known to harbor stable surface liquids. While much has been studied and predicted about the liquid composition and distribution, the origin of the lake basins remains unknown. We use spatial regularity derived from the morphology of these lakes to test the hypothesis that they could be karstic in origin. Earth’s karstic lakes are closed depressions that form when the bedrock is dissolved. Karstic depressions have several distinct features, such as their elongation index and their diameter distributions. These are lognormal, a relationship that holds under the assumption that these lakes originated and evolved over a comparatively short period of time. Furthermore, the spread in sizes of depressions is small, indicating tightly constrained formation processes. In our study, we use statistics to ascertain whether Titan’s lakes follow similar karstic geomorphometric patterns. Cassini RADAR and ISS observations of Titan’s north pole show that the equivalent radii of 224 lakes indeed follow a lognormal distribution just like Earth’s karstic lakes, thus suggesting Earth-like processes may be forming Titan’s lakes.

Impact of small-scale saline tracer heterogeneity on electrical resistivity monitoring in fully and partially saturated porous media: Insights from geoelectrical milli-fluidic experiments

NASA Astrophysics Data System (ADS)

Jougnot, Damien; Jiménez-Martínez, Joaquín; Legendre, Raphaël; Le Borgne, Tanguy; Méheust, Yves; Linde, Niklas

2018-03-01

Time-lapse electrical resistivity tomography (ERT) is a geophysical method widely used to remotely monitor the migration of electrically-conductive tracers and contaminant plumes in the subsurface. Interpretations of time-lapse ERT inversion results are generally based on the assumption of a homogeneous solute concentration below the resolution limits of the tomogram depicting inferred electrical conductivity variations. We suggest that ignoring small-scale solute concentration variability (i.e., at the sub-resolution scale) is a major reason for the often-observed apparent loss of solute mass in ERT tracer studies. To demonstrate this, we developed a geoelectrical milli-fluidic setup where the bulk electric conductivity of a 2D analogous porous medium, consisting of cylindrical grains positioned randomly inside a Hele-Shaw cell, is monitored continuously in time while saline tracer tests are performed through the medium under fully and partially saturated conditions. High resolution images of the porous medium are recorded with a camera at regular time intervals, and provide both the spatial distribution of the fluid phases (aqueous solution and air), and the saline solute concentration field (where the solute consists of a mixture of salt and fluorescein, the latter being used as a proxy for the salt concentration). Effective bulk electrical conductivities computed numerically from the measured solute concentration field and the spatial distributions of fluid phases agree well with the measured bulk conductivities. We find that the effective bulk electrical conductivity is highly influenced by the connectivity of high electrical conductivity regions. The spatial distribution of air, saline tracer fingering, and mixing phenomena drive temporal changes in the effective bulk electrical conductivity by creating preferential paths or barriers for electrical current at the pore-scale. The resulting heterogeneities in the solute concentrations lead to strong anisotropy of the effective bulk electrical conductivity, especially for partially saturated conditions. We highlight how these phenomena contribute to the typically large apparent mass loss observed when conducting field-scale time-lapse ERT.

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

NASA Astrophysics Data System (ADS)

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

2017-04-01

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

MRI Estimates of Brain Iron Concentration in Normal Aging Using Quantitative Susceptibility Mapping

PubMed Central

Bilgic, Berkin; Pfefferbaum, Adolf; Rohlfing, Torsten; Sullivan, Edith V.; Adalsteinsson, Elfar

2011-01-01

Quantifying tissue iron concentration in vivo is instrumental for understanding the role of iron in physiology and in neurological diseases associated with abnormal iron distribution. Herein, we use recently-developed Quantitative Susceptibility Mapping (QSM) methodology to estimate the tissue magnetic susceptibility based on MRI signal phase. To investigate the effect of different regularization choices, we implement and compare ℓ1 and ℓ2 norm regularized QSM algorithms. These regularized approaches solve for the underlying magnetic susceptibility distribution, a sensitive measure of the tissue iron concentration, that gives rise to the observed signal phase. Regularized QSM methodology also involves a pre-processing step that removes, by dipole fitting, unwanted background phase effects due to bulk susceptibility variations between air and tissue and requires data acquisition only at a single field strength. For validation, performances of the two QSM methods were measured against published estimates of regional brain iron from postmortem and in vivo data. The in vivo comparison was based on data previously acquired using Field-Dependent Relaxation Rate Increase (FDRI), an estimate of MRI relaxivity enhancement due to increased main magnetic field strength, requiring data acquired at two different field strengths. The QSM analysis was based on susceptibility-weighted images acquired at 1.5T, whereas FDRI analysis used Multi-Shot Echo-Planar Spin Echo images collected at 1.5T and 3.0T. Both datasets were collected in the same healthy young and elderly adults. The in vivo estimates of regional iron concentration comported well with published postmortem measurements; both QSM approaches yielded the same rank ordering of iron concentration by brain structure, with the lowest in white matter and the highest in globus pallidus. Further validation was provided by comparison of the in vivo measurements, ℓ1-regularized QSM versus FDRI and ℓ2-regularized QSM versus FDRI, which again yielded perfect rank ordering of iron by brain structure. The final means of validation was to assess how well each in vivo method detected known age-related differences in regional iron concentrations measured in the same young and elderly healthy adults. Both QSM methods and FDRI were consistent in identifying higher iron concentrations in striatal and brain stem ROIs (i.e., caudate nucleus, putamen, globus pallidus, red nucleus, and substantia nigra) in the older than in the young group. The two QSM methods appeared more sensitive in detecting age differences in brain stem structures as they revealed differences of much higher statistical significance between the young and elderly groups than did FDRI. However, QSM values are influenced by factors such as the myelin content, whereas FDRI is a more specific indicator of iron content. Hence, FDRI demonstrated higher specificity to iron yet yielded noisier data despite longer scan times and lower spatial resolution than QSM. The robustness, practicality, and demonstrated ability of predicting the change in iron deposition in adult aging suggest that regularized QSM algorithms using single-field-strength data are possible alternatives to tissue iron estimation requiring two field strengths. PMID:21925274

High-rise buildings in the structure of an urbanized landscape and their influence on the spatial composition and image of the city

NASA Astrophysics Data System (ADS)

Moor, Valery K.; Erysheva, Elena A.

2018-03-01

High-rise buildings play an important role in the spatial structure, composition and image of the city, as they are its spatial dominants and landmarks. The conditions of high-rise buildings perception in an urbanized landscape are changing in depending on the landscape-morphological conditions (the relief, the existence of the water area and the character of the coastline). Regularities of high-rise buildings' spatial organization in various natural-landscape situations are considered in the research; the basic principles of high-rise elements inclusion in structure of the urbanized landscape providing their harmonious interaction are formulated.

Sinc-Galerkin estimation of diffusivity in parabolic problems

NASA Technical Reports Server (NTRS)

Smith, Ralph C.; Bowers, Kenneth L.

1991-01-01

A fully Sinc-Galerkin method for the numerical recovery of spatially varying diffusion coefficients in linear partial differential equations is presented. Because the parameter recovery problems are inherently ill-posed, an output error criterion in conjunction with Tikhonov regularization is used to formulate them as infinite-dimensional minimization problems. The forward problems are discretized with a sinc basis in both the spatial and temporal domains thus yielding an approximate solution which displays an exponential convergence rate and is valid on the infinite time interval. The minimization problems are then solved via a quasi-Newton/trust region algorithm. The L-curve technique for determining an approximate value of the regularization parameter is briefly discussed, and numerical examples are given which show the applicability of the method both for problems with noise-free data as well as for those whose data contains white noise.

First-impression bias effects on mismatch negativity to auditory spatial deviants.

PubMed

Fitzgerald, Kaitlin; Provost, Alexander; Todd, Juanita

2018-04-01

Internal models of regularities in the world serve to facilitate perception as redundant input can be predicted and neural resources conserved for that which is new or unexpected. In the auditory system, this is reflected in an evoked potential component known as mismatch negativity (MMN). MMN is elicited by the violation of an established regularity to signal the inaccuracy of the current model and direct resources to the unexpected event. Prevailing accounts suggest that MMN amplitude will increase with stability in regularity; however, observations of first-impression bias contradict stability effects. If tones rotate probabilities as a rare deviant (p = .125) and common standard (p = .875), MMN elicited to the initial deviant tone reaches maximal amplitude faster than MMN to the first standard when later encountered as deviant-a differential pattern that persists throughout rotations. Sensory inference is therefore biased by longer-term contextual information beyond local probability statistics. Using the same multicontext sequence structure, we examined whether this bias generalizes to MMN elicited by spatial sound cues using monaural sounds (n = 19, right first deviant and n = 22, left first deviant) and binaural sounds (n = 19, right first deviant). The characteristic differential modulation of MMN to the two tones was observed in two of three groups, providing partial support for the generalization of first-impression bias to spatially deviant sounds. We discuss possible explanations for its absence when the initial deviant was delivered monaurally to the right ear. © 2017 Society for Psychophysiological Research.

Predicting durations of online collective actions based on Peaks' heights

NASA Astrophysics Data System (ADS)

Lu, Peng; Nie, Shizhao; Wang, Zheng; Jing, Ziwei; Yang, Jianwu; Qi, Zhongxiang; Pujia, Wangmo

2018-02-01

Capturing the whole process of collective actions, the peak model contains four stages, including Prepare, Outbreak, Peak, and Vanish. Based on the peak model, one of the key variables, factors and parameters are further investigated in this paper, which is the rate between peaks and spans. Although the durations or spans and peaks' heights are highly diversified, it seems that the ratio between them is quite stable. If the rate's regularity is discovered, we can predict how long the collective action lasts and when it ends based on the peak's height. In this work, we combined mathematical simulations and empirical big data of 148 cases to explore the regularity of ratio's distribution. It is indicated by results of simulations that the rate has some regularities of distribution, which is not normal distribution. The big data has been collected from the 148 online collective actions and the whole processes of participation are recorded. The outcomes of empirical big data indicate that the rate seems to be closer to being log-normally distributed. This rule holds true for both the total cases and subgroups of 148 online collective actions. The Q-Q plot is applied to check the normal distribution of the rate's logarithm, and the rate's logarithm does follow the normal distribution.

[Spatial distribution pattern of Pontania dolichura larvae and sampling technique].

PubMed

Zhang, Feng; Chen, Zhijie; Zhang, Shulian; Zhao, Huiyan

2006-03-01

In this paper, the spatial distribution pattern of Pontania dolichura larvae was analyzed with Taylor's power law, Iwao's distribution function, and six aggregation indexes. The results showed that the spatial distribution pattern of P. dolichura larvae was of aggregated, and the basic component of the distribution was individual colony, with the aggregation intensity increased with density. On branches, the aggregation was caused by the adult behavior of laying eggs and the spatial position of leaves, while on leaves, the aggregation was caused by the spatial position of news leaves in spring when m < 2.37, and by the spatial position of news leaves in spring and the behavior of eclosion and laying eggs when m > 2.37. By using the parameters alpha and beta in Iwao's m * -m regression equation, the optimal and sequential sampling numbers were determined.

Effect of Royal Jelly on spatial learning and memory in rat model of streptozotocin-induced sporadic Alzheimer's disease

PubMed Central

Zamani, Zohre; Reisi, Parham; Alaei, Hojjatallah; Pilehvarian, Ali Asghar

2012-01-01

Background: It has been recently demonstrated that Royal jelly (RJ) has a beneficial role on neural functions. Alzheimer's disease (AD) is associated with impairments of learning and memory. Therefore, the present study was designed to examine the effect of RJ on spatial learning and memory in rats after intracerebroventricular injection of streptozotocin (icv-STZ). Materials and Methods: Rats were infused bilaterally with an icv injection of STZ, while sham rats received vehicle only. The rats were feed with RJ-contained food (3% w/w) (lyophilized RJ mixed with powdered regular food) or regular food for 10 days. Then spatial learning and memory was tested in the rats by Morris water maze test. Results: Results showed that in icv-STZ group latency and path length were increased as compared to sham group, also icv-STZ rats less remembered the target quadrant that previously the platform was located; however, these were protected significantly in STZ group that received RJ-containing food. Conclusions: Our findings support the potential neuroprotective role of RJ and its helpful effects in AD. PMID:23210085

The role of retinal bipolar cell in early vision: an implication with analogue networks and regularization theory.

PubMed

Yagi, T; Ohshima, S; Funahashi, Y

1997-09-01

A linear analogue network model is proposed to describe the neuronal circuit of the outer retina consisting of cones, horizontal cells, and bipolar cells. The model reflects previous physiological findings on the spatial response properties of these neurons to dim illumination and is expressed by physiological mechanisms, i.e., membrane conductances, gap-junctional conductances, and strengths of chemical synaptic interactions. Using the model, we characterized the spatial filtering properties of the bipolar cell receptive field with the standard regularization theory, in which the early vision problems are attributed to minimization of a cost function. The cost function accompanying the present characterization is derived from the linear analogue network model, and one can gain intuitive insights on how physiological mechanisms contribute to the spatial filtering properties of the bipolar cell receptive field. We also elucidated a quantitative relation between the Laplacian of Gaussian operator and the bipolar cell receptive field. From the computational point of view, the dopaminergic modulation of the gap-junctional conductance between horizontal cells is inferred to be a suitable neural adaptation mechanism for transition between photopic and mesopic vision.

The intelligence of observation: improving high school students' spatial ability by means of intervention unit

NASA Astrophysics Data System (ADS)

Patkin, Dorit; Dayan, Ester

2013-03-01

This case study of one class versus a control group focused on the impact of an intervention unit, which is not part of the regular curriculum, on the improvement of spatial ability of high school students (forty-six 12th-graders, aged 17-18, both boys and girls) in general as well as from a gender perspective. The study explored three sub-abilities: mental rotation (MR), spatial visualization (VS) and spatial orientation (SO). Findings indicated that the spatial orientation of the experimental group students had considerably improved. The findings also illustrated a significant gender-based advantage in favour of the boys in some of the spatial abilities even before the implementation of the intervention unit. The hypothesis relating to the reduction of the gender differences was not corroborated.

Cluster-size entropy in the Axelrod model of social influence: Small-world networks and mass media

NASA Astrophysics Data System (ADS)

Gandica, Y.; Charmell, A.; Villegas-Febres, J.; Bonalde, I.

2011-10-01

We study the Axelrod's cultural adaptation model using the concept of cluster-size entropy Sc, which gives information on the variability of the cultural cluster size present in the system. Using networks of different topologies, from regular to random, we find that the critical point of the well-known nonequilibrium monocultural-multicultural (order-disorder) transition of the Axelrod model is given by the maximum of the Sc(q) distributions. The width of the cluster entropy distributions can be used to qualitatively determine whether the transition is first or second order. By scaling the cluster entropy distributions we were able to obtain a relationship between the critical cultural trait qc and the number F of cultural features in two-dimensional regular networks. We also analyze the effect of the mass media (external field) on social systems within the Axelrod model in a square network. We find a partially ordered phase whose largest cultural cluster is not aligned with the external field, in contrast with a recent suggestion that this type of phase cannot be formed in regular networks. We draw a q-B phase diagram for the Axelrod model in regular networks.

Cluster-size entropy in the Axelrod model of social influence: small-world networks and mass media.

PubMed

Gandica, Y; Charmell, A; Villegas-Febres, J; Bonalde, I

2011-10-01

We study the Axelrod's cultural adaptation model using the concept of cluster-size entropy S(c), which gives information on the variability of the cultural cluster size present in the system. Using networks of different topologies, from regular to random, we find that the critical point of the well-known nonequilibrium monocultural-multicultural (order-disorder) transition of the Axelrod model is given by the maximum of the S(c)(q) distributions. The width of the cluster entropy distributions can be used to qualitatively determine whether the transition is first or second order. By scaling the cluster entropy distributions we were able to obtain a relationship between the critical cultural trait q(c) and the number F of cultural features in two-dimensional regular networks. We also analyze the effect of the mass media (external field) on social systems within the Axelrod model in a square network. We find a partially ordered phase whose largest cultural cluster is not aligned with the external field, in contrast with a recent suggestion that this type of phase cannot be formed in regular networks. We draw a q-B phase diagram for the Axelrod model in regular networks.

The Intelligence of Observation: Improving High School Students' Spatial Ability by Means of Intervention Unit

ERIC Educational Resources Information Center

Patkin, Dorit; Dayan, Ester

2013-01-01

This case study of one class versus a control group focused on the impact of an intervention unit, which is not part of the regular curriculum, on the improvement of spatial ability of high school students (forty-six 12th-graders, aged 17-18, both boys and girls) in general as well as from a gender perspective. The study explored three…

Spatial gradients in action potential duration created by regional magnetofection of hERG are a substrate for wavebreak and turbulent propagation in cardiomyocyte monolayers.

PubMed

Campbell, Katherine; Calvo, Conrado J; Mironov, Sergey; Herron, Todd; Berenfeld, Omer; Jalife, José

2012-12-15

Spatial dispersion of action potential duration (APD) is a substrate for the maintenance of cardiac fibrillation, but the mechanisms are poorly understood. We investigated the role played by spatial APD dispersion in fibrillatory dynamics. We used an in vitro model in which spatial gradients in the expression of ether-à-go-go-related (hERG) protein, and thus rapid delayed rectifying K(+) current (I(Kr)) density, served to generate APD dispersion, high-frequency rotor formation, wavebreak and fibrillatory conduction. A unique adenovirus-mediated magnetofection technique generated well-controlled gradients in hERG and green fluorescent protein (GFP) expression in neonatal rat ventricular myocyte monolayers. Computer simulations using a realistic neonatal rat ventricular myocyte monolayer model provided crucial insight into the underlying mechanisms. Regional hERG overexpression shortened APD and increased rotor incidence in the hERG overexpressing region. An APD profile at 75 percent repolarization with a 16.6 ± 0.72 ms gradient followed the spatial profile of hERG-GFP expression; conduction velocity was not altered. Rotors in the infected region whose maximal dominant frequency was 12.9 Hz resulted in wavebreak at the interface (border zone) between infected and non-infected regions; dominant frequency distribution was uniform when the maximal dominant frequency was <12.9 Hz or the rotors resided in the uninfected region. Regularity at the border zone was lowest when rotors resided in the infected region. In simulations, a fivefold regional increase in I(Kr) abbreviated the APD and hyperpolarized the resting potential. However, the steep APD gradient at the border zone proved to be the primary mechanism of wavebreak and fibrillatory conduction. This study provides insight at the molecular level into the mechanisms by which spatial APD dispersion contributes to wavebreak, rotor stabilization and fibrillatory conduction.

Spatial gradients in action potential duration created by regional magnetofection of hERG are a substrate for wavebreak and turbulent propagation in cardiomyocyte monolayers

PubMed Central

Campbell, Katherine; Calvo, Conrado J; Mironov, Sergey; Herron, Todd; Berenfeld, Omer; Jalife, José

2012-01-01

Spatial dispersion of action potential duration (APD) is a substrate for the maintenance of cardiac fibrillation, but the mechanisms are poorly understood. We investigated the role played by spatial APD dispersion in fibrillatory dynamics. We used an in vitro model in which spatial gradients in the expression of ether-à-go-go-related (hERG) protein, and thus rapid delayed rectifying K+ current (IKr) density, served to generate APD dispersion, high-frequency rotor formation, wavebreak and fibrillatory conduction. A unique adenovirus-mediated magnetofection technique generated well-controlled gradients in hERG and green fluorescent protein (GFP) expression in neonatal rat ventricular myocyte monolayers. Computer simulations using a realistic neonatal rat ventricular myocyte monolayer model provided crucial insight into the underlying mechanisms. Regional hERG overexpression shortened APD and increased rotor incidence in the hERG overexpressing region. An APD profile at 75 percent repolarization with a 16.6 ± 0.72 ms gradient followed the spatial profile of hERG-GFP expression; conduction velocity was not altered. Rotors in the infected region whose maximal dominant frequency was ≥12.9 Hz resulted in wavebreak at the interface (border zone) between infected and non-infected regions; dominant frequency distribution was uniform when the maximal dominant frequency was <12.9 Hz or the rotors resided in the uninfected region. Regularity at the border zone was lowest when rotors resided in the infected region. In simulations, a fivefold regional increase in IKr abbreviated the APD and hyperpolarized the resting potential. However, the steep APD gradient at the border zone proved to be the primary mechanism of wavebreak and fibrillatory conduction. This study provides insight at the molecular level into the mechanisms by which spatial APD dispersion contributes to wavebreak, rotor stabilization and fibrillatory conduction. PMID:23090949

Stress regularity in quasi-static perfect plasticity with a pressure dependent yield criterion

NASA Astrophysics Data System (ADS)

Babadjian, Jean-François; Mora, Maria Giovanna

2018-04-01

This work is devoted to establishing a regularity result for the stress tensor in quasi-static planar isotropic linearly elastic - perfectly plastic materials obeying a Drucker-Prager or Mohr-Coulomb yield criterion. Under suitable assumptions on the data, it is proved that the stress tensor has a spatial gradient that is locally squared integrable. As a corollary, the usual measure theoretical flow rule is expressed in a strong form using the quasi-continuous representative of the stress.

Stationary scalar clouds around a BTZ black hole

NASA Astrophysics Data System (ADS)

Ferreira, Hugo R. C.; Herdeiro, Carlos A. R.

2017-10-01

We establish the existence of stationary clouds of massive test scalar fields around BTZ black holes. These clouds are zero-modes of the superradiant instability and are possible when Robin boundary conditions (RBCs) are considered at the AdS boundary. These boundary conditions are the most general ones that ensure the AdS space is an isolated system, and include, as a particular case, the commonly considered Dirichlet or Neumann-type boundary conditions (DBCs or NBCs). We obtain an explicit, closed form, resonance condition, relating the RBCs that allow the existence of normalizable (and regular on and outside the horizon) clouds to the system's parameters. Such RBCs never include pure DBCs or NBCs. We illustrate the spatial distribution of these clouds, their energy and angular momentum density for some cases. Our results show that BTZ black holes with scalar hair can be constructed, as the non-linear realization of these clouds.

Analyzing the spatial positioning of nuclei in polynuclear giant cells

NASA Astrophysics Data System (ADS)

Stange, Maike; Hintsche, Marius; Sachse, Kirsten; Gerhardt, Matthias; Valleriani, Angelo; Beta, Carsten

2017-11-01

How cells establish and maintain a well-defined size is a fundamental question of cell biology. Here we investigated to what extent the microtubule cytoskeleton can set a predefined cell size, independent of an enclosing cell membrane. We used electropulse-induced cell fusion to form giant multinuclear cells of the social amoeba Dictyostelium discoideum. Based on dual-color confocal imaging of cells that expressed fluorescent markers for the cell nucleus and the microtubules, we determined the subcellular distributions of nuclei and centrosomes in the giant cells. Our two- and three-dimensional imaging results showed that the positions of nuclei in giant cells do not fall onto a regular lattice. However, a comparison with model predictions for random positioning showed that the subcellular arrangement of nuclei maintains a low but still detectable degree of ordering. This can be explained by the steric requirements of the microtubule cytoskeleton, as confirmed by the effect of a microtubule degrading drug.

Power laws governing epidemics in isolated populations

NASA Astrophysics Data System (ADS)

Rhodes, C. J.; Anderson, R. M.

1996-06-01

TEMPORAL changes in the incidence of measles virus infection within large urban communities in the developed world have been the focus of much discussion in the context of the identification and analysis of nonlinear and chaotic patterns in biological time series1-11. In contrast, the measles records for small isolated island populations are highly irregular, because of frequent fade-outs of infection12-14, and traditional analysis15 does not yield useful insight. Here we use measurements of the distribution of epidemic sizes and duration to show that regularities in the dynamics of such systems do become apparent. Specifically, these biological systems are characterized by well-defined power laws in a manner reminiscent of other nonlinear, spatially extended dynamical systems in the physical sciences16-19. We further show that the observed power-law exponents are well described by a simple lattice-based model which reflects the social interaction between individual hosts.

NPP-VIIRS DNB-based reallocating subpopulations to mercury in Urumqi city cluster, central Asia

NASA Astrophysics Data System (ADS)

Zhou, X.; Feng, X. B.; Dai, W.; Li, P.; Ju, C. Y.; Bao, Z. D.; Han, Y. L.

2017-02-01

Accurate and update assignment of population-related environmental matters onto fine grid cells in oasis cities of arid areas remains challenging. We present the approach based on Suomi National Polar-orbiting Partnership (S-NPP) -Visible Infrared Imaging Radiometer Suite (VIIRS) Day/Night Band (DNB) to reallocate population onto a regular finer surface. The number of potential population to the mercury were reallocated onto 0.1x0.1 km reference grid in Urumqi city cluster of China’s Xinjiang, central Asia. The result of Monte Carlo modelling indicated that the range of 0.5 to 2.4 million people was reliable. The study highlights that the NPP-VIIRS DNB-based multi-layered, dasymetric, spatial method enhances our abilities to remotely estimate the distribution and size of target population at the street-level scale and has the potential to transform control strategies for epidemiology, public policy and other socioeconomic fields.

Summary of Terra and Aqua MODIS Long-Term Performance

NASA Technical Reports Server (NTRS)

Xiong, Xiaoxiong (Jack); Wenny, Brian N.; Angal, Amit; Barnes, William; Salomonson, Vincent

2011-01-01

Since launch in December 1999, the MODIS ProtoFlight Model (PFM) onboard the Terra spacecraft has successfully operated for more than 11 years. Its Flight Model (FM) onboard the Aqua spacecraft, launched in May 2002, has also successfully operated for over 9 years. MODIS observations are made in 36 spectral bands at three nadir spatial resolutions and are calibrated and characterized regularly by a set of on-board calibrators (OBC). Nearly 40 science products, supporting a variety of land, ocean, and atmospheric applications, are continuously derived from the calibrated reflectances and radiances of each MODIS instrument and widely distributed to the world-wide user community. Following an overview of MODIS instrument operation and calibration activities, this paper provides a summary of both Terra and Aqua MODIS long-term performance. Special considerations that are critical to maintaining MODIS data quality and beneficial for future missions are also discussed.

Glycosaminoglycans and fibrillar collagen in Priapulida: a histo- and cytochemical study.

PubMed

Welsch, U; Erlinger, R; Storch, V

1992-12-01

The distribution of glycosaminoglycans and fibrillar collagen was studied in various tissues of priapulids, which represent an ancient group of marine metazoa. Sulphated glycosaminoglycans, as demonstrated at the electron microscopical level by Cupromeronic blue, were predominantly found in the cuticle, in basement membranes and also in the narrow connective tissue space below epidermis and anterior intestine. On the basis of their morphology the Cupromeronic blue precipitates could be divided into several groups. Fibrillar collagen occurred in the connective tissue under the epidermis and the epithelium of the anterior intestine. The spatial interrelationship between fibrillar collagen and glycosaminoglycans lacked with some exceptions, the high regularity found in connective tissues of other invertebrates and of vertebrates. This might be related to the special skeletal system of priapulids, consisting mainly of a strong extracellular cuticle and the turgor of the fluid-filled body cavity. In such a system the usual supportive structures seem to be of less functional significance.

Multi-tissue partial volume quantification in multi-contrast MRI using an optimised spectral unmixing approach.

PubMed

Collewet, Guylaine; Moussaoui, Saïd; Deligny, Cécile; Lucas, Tiphaine; Idier, Jérôme

2018-06-01

Multi-tissue partial volume estimation in MRI images is investigated with a viewpoint related to spectral unmixing as used in hyperspectral imaging. The main contribution of this paper is twofold. It firstly proposes a theoretical analysis of the statistical optimality conditions of the proportion estimation problem, which in the context of multi-contrast MRI data acquisition allows to appropriately set the imaging sequence parameters. Secondly, an efficient proportion quantification algorithm based on the minimisation of a penalised least-square criterion incorporating a regularity constraint on the spatial distribution of the proportions is proposed. Furthermore, the resulting developments are discussed using empirical simulations. The practical usefulness of the spectral unmixing approach for partial volume quantification in MRI is illustrated through an application to food analysis on the proving of a Danish pastry. Copyright © 2018 Elsevier Inc. All rights reserved.

Metabolic Flexibility as a Major Predictor of Spatial Distribution in Microbial Communities

PubMed Central

Carbonero, Franck; Oakley, Brian B.; Purdy, Kevin J.

2014-01-01

A better understand the ecology of microbes and their role in the global ecosystem could be achieved if traditional ecological theories can be applied to microbes. In ecology organisms are defined as specialists or generalists according to the breadth of their niche. Spatial distribution is often used as a proxy measure of niche breadth; generalists have broad niches and a wide spatial distribution and specialists a narrow niche and spatial distribution. Previous studies suggest that microbial distribution patterns are contrary to this idea; a microbial generalist genus (Desulfobulbus) has a limited spatial distribution while a specialist genus (Methanosaeta) has a cosmopolitan distribution. Therefore, we hypothesise that this counter-intuitive distribution within generalist and specialist microbial genera is a common microbial characteristic. Using molecular fingerprinting the distribution of four microbial genera, two generalists, Desulfobulbus and the methanogenic archaea Methanosarcina, and two specialists, Methanosaeta and the sulfate-reducing bacteria Desulfobacter were analysed in sediment samples from along a UK estuary. Detected genotypes of both generalist genera showed a distinct spatial distribution, significantly correlated with geographic distance between sites. Genotypes of both specialist genera showed no significant differential spatial distribution. These data support the hypothesis that the spatial distribution of specialist and generalist microbes does not match that seen with specialist and generalist large organisms. It may be that generalist microbes, while having a wider potential niche, are constrained, possibly by intrageneric competition, to exploit only a small part of that potential niche while specialists, with far fewer constraints to their niche, are more capable of filling their potential niche more effectively, perhaps by avoiding intrageneric competition. We suggest that these counter-intuitive distribution patterns may be a common feature of microbes in general and represent a distinct microbial principle in ecology, which is a real challenge if we are to develop a truly inclusive ecology. PMID:24465487

The spatial distribution of cropland carbon transfer in Jilin province during 2014

NASA Astrophysics Data System (ADS)

Cai, Xintong; Meng, Jian; Li, Qiuhui; Gao, Shuang; Zhu, Xianjin

2018-01-01

Cropland carbon transfer (CCT, gC yr-1) is an important component in the carbon budget of terrestrial ecosystems. Analyzing the value of CCT and its spatial variation would provide a data basis for assessing the regional carbon balance. Based on the data from Jilin statistical yearbook 2015, we investigated the spatial variation of CCT in Jilin province during 2014. Results suggest that the CCT of Jilin province was 30.83 TgC, which exhibited a decreasing trend from the centre to the border but the west side was higher than the east. The magnitude of carbon transfer per area (MCT), which showed a similar spatial distribution with CCT, was the dominating component of CCT spatial distribution. The spatial distribution of MCT was jointly affected by that of the ratio of planting area to regional area (RPR) and carbon transfer per planting area (CTP), where RPR and CTP contributed 65.55% and 34.5% of MCT spatial distribution, respectively. Therefore, CCT in Jilin province spatially varied, which made it highly needed to consider the difference in CCT among regions when we assessing the regional carbon budget.

Multi-sensor satellite and in situ monitoring of phytoplankton development in a eutrophic-mesotrophic lake.

PubMed

Dörnhöfer, Katja; Klinger, Philip; Heege, Thomas; Oppelt, Natascha

2018-01-15

Phytoplankton indicated by its photosynthetic pigment chlorophyll-a is an important pointer on lake ecology and a regularly monitored parameter within the European Water Framework Directive. Along with eutrophication and global warming cyanobacteria gain increasing importance concerning human health aspects. Optical remote sensing may support both the monitoring of horizontal distribution of phytoplankton and cyanobacteria at the lake surface and the reduction of spatial uncertainties associated with limited water sample analyses. Temporal and spatial resolution of using only one satellite sensor, however, may constrain its information value. To discuss the advantages of a multi-sensor approach the sensor-independent, physically based model MIP (Modular Inversion and Processing System) was applied at Lake Kummerow, Germany, and lake surface chlorophyll-a was derived from 33 images of five different sensors (MODIS-Terra, MODIS-Aqua, Landsat 8, Landsat 7 and Sentinel-2A). Remotely sensed lake average chlorophyll-a concentration showed a reasonable development and varied between 2.3±0.4 and 35.8±2.0mg·m -3 from July to October 2015. Match-ups between in situ and satellite chlorophyll-a revealed varying performances of Landsat 8 (RMSE: 3.6 and 19.7mg·m -3 ), Landsat 7 (RMSE: 6.2mg·m -3 ), Sentinel-2A (RMSE: 5.1mg·m -3 ) and MODIS (RMSE: 12.8mg·m -3 ), whereas an in situ data uncertainty of 48% needs to be respected. The temporal development of an index on harmful algal blooms corresponded well with the cyanobacteria biomass development during summer months. Satellite chlorophyll-a maps allowed to follow spatial patterns of chlorophyll-a distribution during a phytoplankton bloom event. Wind conditions mainly explained spatial patterns. Integrating satellite chlorophyll-a into trophic state assessment resulted in different trophic classes. Our study endorsed a combined use of satellite and in situ chlorophyll-a data to alleviate weaknesses of both approaches and to better characterise and understand phytoplankton development in lakes. Copyright © 2017 Elsevier B.V. All rights reserved.

Iterative image reconstruction for PROPELLER-MRI using the nonuniform fast fourier transform.

PubMed

Tamhane, Ashish A; Anastasio, Mark A; Gui, Minzhi; Arfanakis, Konstantinos

2010-07-01

To investigate an iterative image reconstruction algorithm using the nonuniform fast Fourier transform (NUFFT) for PROPELLER (Periodically Rotated Overlapping ParallEL Lines with Enhanced Reconstruction) MRI. Numerical simulations, as well as experiments on a phantom and a healthy human subject were used to evaluate the performance of the iterative image reconstruction algorithm for PROPELLER, and compare it with that of conventional gridding. The trade-off between spatial resolution, signal to noise ratio, and image artifacts, was investigated for different values of the regularization parameter. The performance of the iterative image reconstruction algorithm in the presence of motion was also evaluated. It was demonstrated that, for a certain range of values of the regularization parameter, iterative reconstruction produced images with significantly increased signal to noise ratio, reduced artifacts, for similar spatial resolution, compared with gridding. Furthermore, the ability to reduce the effects of motion in PROPELLER-MRI was maintained when using the iterative reconstruction approach. An iterative image reconstruction technique based on the NUFFT was investigated for PROPELLER MRI. For a certain range of values of the regularization parameter, the new reconstruction technique may provide PROPELLER images with improved image quality compared with conventional gridding. (c) 2010 Wiley-Liss, Inc.

Depreciation of public goods in spatial public goods games

NASA Astrophysics Data System (ADS)

Shi, Dong-Mei; Zhuang, Yong; Li, Yu-Jian; Wang, Bing-Hong

2011-10-01

In real situations, the value of public goods will be reduced or even lost because of external factors or for intrinsic reasons. In this work, we investigate the evolution of cooperation by considering the effect of depreciation of public goods in spatial public goods games on a square lattice. It is assumed that each individual gains full advantage if the number of the cooperators nc within a group centered on that individual equals or exceeds the critical mass (CM). Otherwise, there is depreciation of the public goods, which is realized by rescaling the multiplication factor r to (nc/CM)r. It is shown that the emergence of cooperation is remarkably promoted for CM > 1 even at small values of r, and a global cooperative level is achieved at an intermediate value of CM = 4 at a small r. We further study the effect of depreciation of public goods on different topologies of a regular lattice, and find that the system always reaches global cooperation at a moderate value of CM = G - 1 regardless of whether or not there exist overlapping triangle structures on the regular lattice, where G is the group size of the associated regular lattice.

Iterative Image Reconstruction for PROPELLER-MRI using the NonUniform Fast Fourier Transform

PubMed Central

Tamhane, Ashish A.; Anastasio, Mark A.; Gui, Minzhi; Arfanakis, Konstantinos

2013-01-01

Purpose To investigate an iterative image reconstruction algorithm using the non-uniform fast Fourier transform (NUFFT) for PROPELLER (Periodically Rotated Overlapping parallEL Lines with Enhanced Reconstruction) MRI. Materials and Methods Numerical simulations, as well as experiments on a phantom and a healthy human subject were used to evaluate the performance of the iterative image reconstruction algorithm for PROPELLER, and compare it to that of conventional gridding. The trade-off between spatial resolution, signal to noise ratio, and image artifacts, was investigated for different values of the regularization parameter. The performance of the iterative image reconstruction algorithm in the presence of motion was also evaluated. Results It was demonstrated that, for a certain range of values of the regularization parameter, iterative reconstruction produced images with significantly increased SNR, reduced artifacts, for similar spatial resolution, compared to gridding. Furthermore, the ability to reduce the effects of motion in PROPELLER-MRI was maintained when using the iterative reconstruction approach. Conclusion An iterative image reconstruction technique based on the NUFFT was investigated for PROPELLER MRI. For a certain range of values of the regularization parameter the new reconstruction technique may provide PROPELLER images with improved image quality compared to conventional gridding. PMID:20578028

Relations between Spatial Distribution, Social Affiliations and Dominance Hierarchy in a Semi-Free Mandrill Population

PubMed Central

Naud, Alexandre; Chailleux, Eloise; Kestens, Yan; Bret, Céline; Desjardins, Dominic; Petit, Odile; Ngoubangoye, Barthélémy; Sueur, Cédric

2016-01-01

Although there exist advantages to group-living in comparison to a solitary lifestyle, costs and gains of group-living may be unequally distributed among group members. Predation risk, vigilance levels and food intake may be unevenly distributed across group spatial geometry and certain within-group spatial positions may be more or less advantageous depending on the spatial distribution of these factors. In species characterized with dominance hierarchy, high-ranking individuals are commonly observed in advantageous spatial position. However, in complex social systems, individuals can develop affiliative relationships that may balance the effect of dominance relationships in individual's spatial distribution. The objective of the present study is to investigate how the group spatial distribution of a semi-free ranging colony of Mandrills relates to its social organization. Using spatial observations in an area surrounding the feeding zone, we tested the three following hypothesis: (1) does dominance hierarchy explain being observed in proximity or far from a food patch? (2) Do affiliative associations also explain being observed in proximity or far from a food patch? (3) Do the differences in rank in the group hierarchy explain being co-observed in proximity of a food patch? Our results showed that high-ranking individuals were more observed in proximity of the feeding zone while low-ranking individuals were more observed at the boundaries of the observation area. Furthermore, we observed that affiliative relationships were also associated with individual spatial distributions and explain more of the total variance of the spatial distribution in comparison with dominance hierarchy. Finally, we found that individuals observed at a same moment in proximity of the feeding zone were more likely to be distant in the hierarchy while controlling for maternal kinship, age and sex similarity. This study brings some elements about how affiliative networks and dominance hierarchy are related to spatial positions in primates. PMID:27199845

Relations between Spatial Distribution, Social Affiliations and Dominance Hierarchy in a Semi-Free Mandrill Population.

PubMed

Naud, Alexandre; Chailleux, Eloise; Kestens, Yan; Bret, Céline; Desjardins, Dominic; Petit, Odile; Ngoubangoye, Barthélémy; Sueur, Cédric

2016-01-01

Although there exist advantages to group-living in comparison to a solitary lifestyle, costs and gains of group-living may be unequally distributed among group members. Predation risk, vigilance levels and food intake may be unevenly distributed across group spatial geometry and certain within-group spatial positions may be more or less advantageous depending on the spatial distribution of these factors. In species characterized with dominance hierarchy, high-ranking individuals are commonly observed in advantageous spatial position. However, in complex social systems, individuals can develop affiliative relationships that may balance the effect of dominance relationships in individual's spatial distribution. The objective of the present study is to investigate how the group spatial distribution of a semi-free ranging colony of Mandrills relates to its social organization. Using spatial observations in an area surrounding the feeding zone, we tested the three following hypothesis: (1) does dominance hierarchy explain being observed in proximity or far from a food patch? (2) Do affiliative associations also explain being observed in proximity or far from a food patch? (3) Do the differences in rank in the group hierarchy explain being co-observed in proximity of a food patch? Our results showed that high-ranking individuals were more observed in proximity of the feeding zone while low-ranking individuals were more observed at the boundaries of the observation area. Furthermore, we observed that affiliative relationships were also associated with individual spatial distributions and explain more of the total variance of the spatial distribution in comparison with dominance hierarchy. Finally, we found that individuals observed at a same moment in proximity of the feeding zone were more likely to be distant in the hierarchy while controlling for maternal kinship, age and sex similarity. This study brings some elements about how affiliative networks and dominance hierarchy are related to spatial positions in primates.

Geodesics in nonexpanding impulsive gravitational waves with Λ. II

NASA Astrophysics Data System (ADS)

Sämann, Clemens; Steinbauer, Roland

2017-11-01

We investigate all geodesics in the entire class of nonexpanding impulsive gravitational waves propagating in an (anti-)de Sitter universe using the distributional metric. We extend the regularization approach of part I [Sämann, C. et al., Classical Quantum Gravity 33(11), 115002 (2016)] to a full nonlinear distributional analysis within the geometric theory of generalized functions. We prove global existence and uniqueness of geodesics that cross the impulsive wave and hence geodesic completeness in full generality for this class of low regularity spacetimes. This, in particular, prepares the ground for a mathematically rigorous account on the "physical equivalence" of the continuous form with the distributional "form" of the metric.

Real-time passive acoustic detection of marine mammals from a variety of autonomous platforms

NASA Astrophysics Data System (ADS)

Baumgartner, M.; Van Parijs, S. M.; Hotchkin, C. F.; Gurnee, J.; Stafford, K.; Winsor, P.; Davies, K. T. A.; Taggart, C. T.

2016-02-01

Over the past two decades, passive acoustic monitoring has proven to be an effective means of estimating the occurrence of marine mammals. The vast majority of applications involve archival recordings from bottom-mounted instruments or towed hydrophones from moving ships; however, there is growing interest in assessing marine mammal occurrence from autonomous platforms, particularly in real time. The Woods Hole Oceanographic Institution has developed the capability to detect, classify, and remotely report in near real time the calls of marine mammals via passive acoustics from a variety of autonomous platforms, including Slocum gliders, wave gliders, and moored buoys. The mobile Slocum glider can simultaneously measure marine mammal occurrence and oceanographic conditions throughout the water column, making it well suited for studying both marine mammal distribution and habitat. Wave gliders and moored buoys provide complementary observations over much larger spatial scales and longer temporal scales, respectively. The near real-time reporting capability of these platforms enables follow-up visual observations, on-water research, or responsive management action. We have recently begun to use this technology to regularly monitor baleen whales off the coast of New England, USA and Nova Scotia, Canada, as well as baleen whales, beluga whales, and bearded seals in the Chukchi Sea off the northwest coast of Alaska, USA. Our long-range goal is to monitor occurrence over wide spatial and temporal extents as part of the regional and global ocean observatory initiatives to improve marine mammal conservation and management and to study changes in marine mammal distribution over multi-annual time scales in response to climate change.

Assessing Risks from Cyclones for Human Lives and Livelihoods in the Coastal Region of Bangladesh

PubMed Central

Khan, Amanat Ullah; Kervyn, Matthieu

2017-01-01

As a disaster prone country, Bangladesh is regularly hit by natural hazards, including devastating cyclones, such as in 1970, 1991 and 2007. Although the number of cyclones’ fatalities reduced from 0.3 million in 1970 to a few thousand or fewer in recent events, loss of lives and impact on livelihoods remains a concern. It depends on the meteorological characteristics of cyclone and the general vulnerability and capacity of the exposed population. In that perspective, a spatially explicit risk assessment is an essential step towards targeted disaster risk reduction. This study aims at analyzing the spatial variation of the different factors contributing to the risk for coastal communities at regional scale, including the distribution of the hazards, exposure, vulnerability and capacity. An exploratory factor analysis method is used to map vulnerability contrasts between local administrative units. Indexing and ranking using geospatial techniques are used to produce maps of exposure, hazard, vulnerability, capacities and risk. Results show that vulnerable populations and exposed areas are distributed along the land sea boundary, islands and major inland rivers. The hazard, assessed from the density of historical cyclone paths, is highest in the southwestern part of the coast. Whereas cyclones shelters are shown to properly serve the most vulnerable populations as priority evacuation centers, the overall pattern of capacity accounting for building quality and road network shows a more complex pattern. Resultant risk maps also provide a reasonable basis from which to take further structural measures to minimize loss of lives in the upcoming cyclones. PMID:28757550

Evaluation of Vertical Lacunarity Profiles in Forested Areas Using Airborne Laser Scanning Point Clouds

NASA Astrophysics Data System (ADS)

Székely, B.; Kania, A.; Standovár, T.; Heilmeier, H.

2016-06-01

The horizontal variation and vertical layering of the vegetation are important properties of the canopy structure determining the habitat; three-dimensional (3D) distribution of objects (shrub layers, understory vegetation, etc.) is related to the environmental factors (e.g., illumination, visibility). It has been shown that gaps in forests, mosaic-like structures are essential to biodiversity; various methods have been introduced to quantify this property. As the distribution of gaps in the vegetation is a multi-scale phenomenon, in order to capture it in its entirety, scale-independent methods are preferred; one of these is the calculation of lacunarity. We used Airborne Laser Scanning point clouds measured over a forest plantation situated in a former floodplain. The flat topographic relief ensured that the tree growth is independent of the topographic effects. The tree pattern in the plantation crops provided various quasi-regular and irregular patterns, as well as various ages of the stands. The point clouds were voxelized and layers of voxels were considered as images for two-dimensional input. These images calculated for a certain vicinity of reference points were taken as images for the computation of lacunarity curves, providing a stack of lacunarity curves for each reference points. These sets of curves have been compared to reveal spatial changes of this property. As the dynamic range of the lacunarity values is very large, the natural logarithms of the values were considered. Logarithms of lacunarity functions show canopy-related variations, we analysed these variations along transects. The spatial variation can be related to forest properties and ecology-specific aspects.

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.

Localized Spatio-Temporal Constraints for Accelerated CMR Perfusion

PubMed Central

Akçakaya, Mehmet; Basha, Tamer A.; Pflugi, Silvio; Foppa, Murilo; Kissinger, Kraig V.; Hauser, Thomas H.; Nezafat, Reza

2013-01-01

Purpose To develop and evaluate an image reconstruction technique for cardiac MRI (CMR)perfusion that utilizes localized spatio-temporal constraints. Methods CMR perfusion plays an important role in detecting myocardial ischemia in patients with coronary artery disease. Breath-hold k-t based image acceleration techniques are typically used in CMR perfusion for superior spatial/temporal resolution, and improved coverage. In this study, we propose a novel compressed sensing based image reconstruction technique for CMR perfusion, with applicability to free-breathing examinations. This technique uses local spatio-temporal constraints by regularizing image patches across a small number of dynamics. The technique is compared to conventional dynamic-by-dynamic reconstruction, and sparsity regularization using a temporal principal-component (pc) basis, as well as zerofilled data in multi-slice 2D and 3D CMR perfusion. Qualitative image scores are used (1=poor, 4=excellent) to evaluate the technique in 3D perfusion in 10 patients and 5 healthy subjects. On 4 healthy subjects, the proposed technique was also compared to a breath-hold multi-slice 2D acquisition with parallel imaging in terms of signal intensity curves. Results The proposed technique results in images that are superior in terms of spatial and temporal blurring compared to the other techniques, even in free-breathing datasets. The image scores indicate a significant improvement compared to other techniques in 3D perfusion (2.8±0.5 vs. 2.3±0.5 for x-pc regularization, 1.7±0.5 for dynamic-by-dynamic, 1.1±0.2 for zerofilled). Signal intensity curves indicate similar dynamics of uptake between the proposed method with a 3D acquisition and the breath-hold multi-slice 2D acquisition with parallel imaging. Conclusion The proposed reconstruction utilizes sparsity regularization based on localized information in both spatial and temporal domains for highly-accelerated CMR perfusion with potential utility in free-breathing 3D acquisitions. PMID:24123058

Wave actions and topography determine the small-scale spatial distribution of newly settled Asari clams Ruditapes philippinarum on a tidal flat

NASA Astrophysics Data System (ADS)

Nambu, Ryogen; Saito, Hajime; Tanaka, Yoshio; Higano, Junya; Kuwahara, Hisami

2012-03-01

There are many studies on spatial distributions of Asari clam Ruditapes philippinarum adults on tidal flats but few have dealt with spatial distributions of newly settled Asari clam (<0.3 mm shell length, indicative of settlement patterns) in relation to physical/topographical conditions on tidal flats. We examined small-scale spatial distributions of newly settled individuals on the Matsunase tidal flat, central Japan, during the low spring tides on two days 29th-30th June 2007, together with the shear stress from waves and currents on the flat. The characteristics of spatial distribution of newly settled Asari clam markedly varied depending on both of hydrodynamic and topographical conditions on the tidal flat. Using generalized linear models (GLMs), factors responsible for affecting newly settled Asari clam density and its spatial distribution were distinguished between sampling days, with "crest" sites always having a negative influence each on the density and the distribution on both sampling days. The continuously recorded data for the wave-current flows at the "crest" site on the tidal flat showed that newly settled Asari clam, as well as bottom sediment particles, at the "crest" site to be easily displaced. Small-scale spatial distributions of newly settled Asari clam changed with more advanced benthic stages in relation to the wave shear stress.

Spatial distributions of dose enhancement around a gold nanoparticle at several depths of proton Bragg peak

NASA Astrophysics Data System (ADS)

Kwon, Jihun; Sutherland, Kenneth; Hashimoto, Takayuki; Shirato, Hiroki; Date, Hiroyuki

2016-10-01

Gold nanoparticles (GNPs) have been recognized as a promising candidate for a radiation sensitizer. A proton beam incident on a GNP can produce secondary electrons, resulting in an enhancement of the dose around the GNP. However, little is known about the spatial distribution of dose enhancement around the GNP, especially in the direction along the incident proton. The purpose of this study is to determine the spatial distribution of dose enhancement by taking the incident direction into account. Two steps of calculation were conducted using the Geant4 Monte Carlo simulation toolkit. First, the energy spectra of 100 and 195 MeV protons colliding with a GNP were calculated at the Bragg peak and three other depths around the peak in liquid water. Second, the GNP was bombarded by protons with the obtained energy spectra. Radial dose distributions were computed along the incident beam direction. The spatial distributions of the dose enhancement factor (DEF) and subtracted dose (Dsub) were then evaluated. The spatial DEF distributions showed hot spots in the distal radial region from the proton beam axis. The spatial Dsub distribution isotropically spread out around the GNP. Low energy protons caused higher and wider dose enhancement. The macroscopic dose enhancement in clinical applications was also evaluated. The results suggest that the consideration of the spatial distribution of GNPs in treatment planning will maximize the potential of GNPs.

Spatial Distribution of Surface Soil Moisture in a Small Forested Catchment

EPA Science Inventory

Predicting the spatial distribution of soil moisture is an important hydrological question. We measured the spatial distribution of surface soil moisture (upper 6 cm) using an Amplitude Domain Reflectometry sensor at the plot scale (2 × 2 m) and small catchment scale (0.84 ha) in...

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

PubMed

Chen, Lyu Feng; Zhu, Guo Ping

2018-03-01

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

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

PubMed

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

2018-03-29

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

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

Methodology to study the three-dimensional spatial distribution of prostate cancer and their dependence on clinical parameters

PubMed Central

Rojas, Kristians Diaz; Montero, Maria L.; Yao, Jorge; Messing, Edward; Fazili, Anees; Joseph, Jean; Ou, Yangming; Rubens, Deborah J.; Parker, Kevin J.; Davatzikos, Christos; Castaneda, Benjamin

2015-01-01

Abstract. A methodology to study the relationship between clinical variables [e.g., prostate specific antigen (PSA) or Gleason score] and cancer spatial distribution is described. Three-dimensional (3-D) models of 216 glands are reconstructed from digital images of whole mount histopathological slices. The models are deformed into one prostate model selected as an atlas using a combination of rigid, affine, and B-spline deformable registration techniques. Spatial cancer distribution is assessed by counting the number of tumor occurrences among all glands in a given position of the 3-D registered atlas. Finally, a difference between proportions is used to compare different spatial distributions. As a proof of concept, we compare spatial distributions from patients with PSA greater and less than 5  ng/ml and from patients older and younger than 60 years. Results suggest that prostate cancer has a significant difference in the right zone of the prostate between populations with PSA greater and less than 5  ng/ml. Age does not have any impact in the spatial distribution of the disease. The proposed methodology can help to comprehend prostate cancer by understanding its spatial distribution and how it changes according to clinical parameters. Finally, this methodology can be easily adapted to other organs and pathologies. PMID:26236756

Quantifying specific capacity and salinity variability in Amman Zarqa Basin, Central Jordan, using empirical statistical and geostatistical techniques.

PubMed

Shaqour, F; Taany, R; Rimawi, O; Saffarini, G

2016-01-01

Modeling groundwater properties is an important tool by means of which water resources management can judge whether these properties are within the safe limits or not. This is usually done regularly and in the aftermath of crises that are expected to reflect negatively on groundwater properties, as occurred in Jordan due to crises in neighboring countries. In this study, specific capacity and salinity of groundwater of B2/A7 aquifer in Amman Zarqa Basin were evaluated to figure out the effect of population increase in this basin as a result of refugee flux from neighboring countries to this heavily populated basin after Gulf crises 1990 and 2003. Both properties were found to exhibit a three-parameter lognormal distribution. The empirically calculated β parameter of this distribution mounted up to 0.39 m(3)/h/min for specific capacity and 238 ppm for salinity. This parameter is suggested to account for the global changes that took place all over the basin during the entire period of observation and not for local changes at every well or at certain localities in the basin. It can be considered as an exploratory result of data analysis. Formal and implicit evaluation followed this step using structural analysis and construction of experimental semivariograms that represent the spatial variability of both properties. The adopted semivariograms were then used to construct maps to illustrate the spatial variability of the properties under consideration using kriging interpolation techniques. Semivariograms show that specific capacity and salinity values are spatially dependent within 14,529 and 16,309 m, respectively. Specific capacity semivariogram exhibit a nugget effect on a small scale (324 m). This can be attributed to heterogeneity or inadequacies in measurement. Specific capacity and salinity maps show that the major changes exhibit a northwest southeast trend, near As-Samra Wastewater Treatment Plant. The results of this study suggest proper management practices.

Shift in the microbial community composition of surface water and sediment along an urban river.

PubMed

Wang, Lan; Zhang, Jing; Li, Huilin; Yang, Hong; Peng, Chao; Peng, Zhengsong; Lu, Lu

2018-06-15

Urban rivers represent a unique ecosystem in which pollution occurs regularly, leading to significantly altered of chemical and biological characteristics of the surface water and sediments. However, the impact of urbanization on the diversity and structure of the river microbial community has not been well documented. As a major tributary of the Yangtze River, the Jialing River flows through many cities. Here, a comprehensive analysis of the spatial microbial distribution in the surface water and sediments in the Nanchong section of Jialing River and its two urban branches was conducted using 16S rRNA gene-based Illumina MiSeq sequencing. The results revealed distinct differences in surface water bacterial composition along the river with a differential distribution of Proteobacteria, Cyanobacteria, Actinobacteria, Bacteroidetes and Acidobacteria (P < 0.05). The bacterial diversity in sediments was significantly higher than their corresponding water samples. Additionally, archaeal communities showed obvious spatial variability in the surface water. The construction of the hydropower station resulted in increased Cyanobacteria abundance in the upstream (32.2%) compared to its downstream (10.3%). Several taxonomic groups of potential fecal indicator bacteria, like Flavobacteria and Bacteroidia, showed an increasing trend in the urban water. PICRUSt metabolic inference analysis revealed a growing number of genes associated with xenobiotic metabolism and nitrogen metabolism in the urban water, indicating that urban discharges might act as the dominant selective force to alter the microbial communities. Redundancy analysis suggested that the microbial community structure was influenced by several environmental factors. TP (P < 0.01) and NO 3 - (P < 0.05), and metals (Zn, Fe) (P < 0.05) were the most significant drivers determining the microbial community composition in the urban river. These results highlight that river microbial communities exhibit spatial variation in urban areas due to the joint influence of chemical variables associated with sewage discharging and construction of hydropower stations. Copyright © 2018 Elsevier B.V. All rights reserved.

Water mass changes inferred by gravity field variations with GRACE

NASA Astrophysics Data System (ADS)

Fagiolini, Elisa; Gruber, Christian; Apel, Heiko; Viet Dung, Nguyen; Güntner, Andreas

2013-04-01

Since 2002 the Gravity Recovery And Climate Experiment (GRACE) mission has been measuring temporal variations of Earth's gravity field depicting with extreme accuracy how mass is distributed and varies around the globe. Advanced signal separation techniques enable to isolate different sources of mass such as atmospheric and oceanic circulation or land hydrology. Nowadays thanks to GRACE, floods, droughts, and water resources monitoring are possible on a global scale. At GFZ Potsdam scientists have been involved since 2000 in the initiation and launch of the GRACE precursor CHAMP satellite mission, since 2002 in the GRACE Science Data System and since 2009 in the frame of ESÁs GOCE High Processing Facility as well as projected GRACE FOLLOW-ON for the continuation of time variable gravity field determination. Recently GFZ has reprocessed the complete GRACE time-series of monthly gravity field spherical harmonic solutions with improved standards and background models. This new release (RL05) already shows significantly less noise and spurious artifacts. In order to monitor water mass re-distribution and fast moving water, we still need to reach a higher resolution in both time and space. Moreover, in view of disaster management applications we need to act with a shorter latency (current latency standard is 2 months). For this purpose, we developed a regional method based on radial base functions that is capable to compute models in regional and global representation. This new method localizes the gravity observation to the closest regions and omits spatial correlations with farther regions. Additionally, we succeeded to increase the temporal resolution to sub-monthly time scales. Innovative concepts such as Kalman filtering and regularization, along with sophisticated regional modeling have shifted temporal and spatial resolution towards new frontiers. We expect global hydrological models as WHGM to profit from such accurate outcomes. First results comparing the mass changes over the Mekong Delta observed with GRACE with spatial explicit hydraulic simulations of the large scale annual inundation volume during the flood season are presented and discussed.

[Spatial arrangement of macro-, midi- and microchromosomes in transcriptionally active nuclei of growing oocytes in birds of the order galliformes].

PubMed

Maslova, A V; Krasikova, A V

2011-01-01

Three-dimensional genome organization in the cell nucleus reflects its functional state and is one of the regulatory levels of gene expression. Thus, a detailed exploration of the interrelations between the genome spatial organization and functioning is essential. In this work, three-dimensional genome organization in growing oocytes of Galliform birds, with giant transcriptionally active nucleus characterized by nearly absolute lack of structural constraints on chromosome decondensation, is analyzed in detail. Radial distribution of three groups of chromosomes with different size and gene density in the nuclei of chicken and Japanese quail oocytes was analyzed using confocal laser scanning microscopy followed by the 3D-reconstruction. The chromosome position relative to the nuclear center was estimated by analyzing its localization in the certain radial zones of the nucleus and direct distance measurements from the centre of the nucleus to the terminal regions and the center of gravity of the chromosome. It has been shown that, in the transcriptionally active nuclei of avian oocytes, chromosomes are located at a significant distance from the nuclear envelope and the gene-rich microchromosomes have no preferential location close to the center of the nucleus and are localized mainly at the periphery of the region occupied by the whole chromosome set. Therefore the radial distribution of lampbrush chromosomes in the oocyte nucleus does not obey the regularity of the spatial arrangement of chromosomes in the interphase nucleus according to which the gene-rich chromosome territories are located at the nuclear center and the gene-poor ones are at the nuclear periphery. With the help of visualization of 3D-preserved lampbrush chromosomes in the intact nucleus, we have confirmed the presence of the repulsion forces between the lateral loops of lampbrush half-bivalents and the lack of interactions between the heterochromatic segments of different bivalents at the lampbrush stage of oogenesis.

Taking a statistical approach

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

Wild, M.; Rouhani, S.

1995-02-01

A typical site investigation entails extensive sampling and monitoring. In the past, sampling plans have been designed on purely ad hoc bases, leading to significant expenditures and, in some cases, collection of redundant information. In many instances, sampling costs exceed the true worth of the collected data. The US Environmental Protection Agency (EPA) therefore has advocated the use of geostatistics to provide a logical framework for sampling and analysis of environmental data. Geostatistical methodology uses statistical techniques for the spatial analysis of a variety of earth-related data. The use of geostatistics was developed by the mining industry to estimate oremore » concentrations. The same procedure is effective in quantifying environmental contaminants in soils for risk assessments. Unlike classical statistical techniques, geostatistics offers procedures to incorporate the underlying spatial structure of the investigated field. Sample points spaced close together tend to be more similar than samples spaced further apart. This can guide sampling strategies and determine complex contaminant distributions. Geostatistic techniques can be used to evaluate site conditions on the basis of regular, irregular, random and even spatially biased samples. In most environmental investigations, it is desirable to concentrate sampling in areas of known or suspected contamination. The rigorous mathematical procedures of geostatistics allow for accurate estimates at unsampled locations, potentially reducing sampling requirements. The use of geostatistics serves as a decision-aiding and planning tool and can significantly reduce short-term site assessment costs, long-term sampling and monitoring needs, as well as lead to more accurate and realistic remedial design criteria.« less

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

PubMed

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

2012-01-01

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

Shaping highly regular glass architectures: A lesson from nature

PubMed Central

Schoeppler, Vanessa; Reich, Elke; Vacelet, Jean; Rosenthal, Martin; Pacureanu, Alexandra; Rack, Alexander; Zaslansky, Paul; Zolotoyabko, Emil; Zlotnikov, Igor

2017-01-01

Demospongiae is a class of marine sponges that mineralize skeletal elements, the glass spicules, made of amorphous silica. The spicules exhibit a diversity of highly regular three-dimensional branched morphologies that are a paradigm example of symmetry in biological systems. Current glass shaping technology requires treatment at high temperatures. In this context, the mechanism by which glass architectures are formed by living organisms remains a mystery. We uncover the principles of spicule morphogenesis. During spicule formation, the process of silica deposition is templated by an organic filament. It is composed of enzymatically active proteins arranged in a mesoscopic hexagonal crystal-like structure. In analogy to synthetic inorganic nanocrystals that show high spatial regularity, we demonstrate that the branching of the filament follows specific crystallographic directions of the protein lattice. In correlation with the symmetry of the lattice, filament branching determines the highly regular morphology of the spicules on the macroscale. PMID:29057327

Extended quantification of the generalized recurrence plot

NASA Astrophysics Data System (ADS)

Riedl, Maik; Marwan, Norbert; Kurths, Jürgen

2016-04-01

The generalized recurrence plot is a modern tool for quantification of complex spatial patterns. Its application spans the analysis of trabecular bone structures, Turing structures, turbulent spatial plankton patterns, and fractals. But, it is also successfully applied to the description of spatio-temporal dynamics and the detection of regime shifts, such as in the complex Ginzburg-Landau- equation. The recurrence plot based determinism is a central measure in this framework quantifying the level of regularities in temporal and spatial structures. We extend this measure for the generalized recurrence plot considering additional operations of symmetry than the simple translation. It is tested not only on two-dimensional regular patterns and noise but also on complex spatial patterns reconstructing the parameter space of the complex Ginzburg-Landau-equation. The extended version of the determinism resulted in values which are consistent to the original recurrence plot approach. Furthermore, the proposed method allows a split of the determinism into parts which based on laminar and non-laminar regions of the two-dimensional pattern of the complex Ginzburg-Landau-equation. A comparison of these parts with a standard method of image classification, the co-occurrence matrix approach, shows differences especially in the description of patterns associated with turbulence. In that case, it seems that the extended version of the determinism allows a distinction of phase turbulence and defect turbulence by means of their spatial patterns. This ability of the proposed method promise new insights in other systems with turbulent dynamics coming from climatology, biology, ecology, and social sciences, for example.

Gene expression based mouse brain parcellation using Markov random field regularized non-negative matrix factorization

NASA Astrophysics Data System (ADS)

Pathak, Sayan D.; Haynor, David R.; Thompson, Carol L.; Lein, Ed; Hawrylycz, Michael

2009-02-01

Understanding the geography of genetic expression in the mouse brain has opened previously unexplored avenues in neuroinformatics. The Allen Brain Atlas (www.brain-map.org) (ABA) provides genome-wide colorimetric in situ hybridization (ISH) gene expression images at high spatial resolution, all mapped to a common three-dimensional 200μm3 spatial framework defined by the Allen Reference Atlas (ARA) and is a unique data set for studying expression based structural and functional organization of the brain. The goal of this study was to facilitate an unbiased data-driven structural partitioning of the major structures in the mouse brain. We have developed an algorithm that uses nonnegative matrix factorization (NMF) to perform parts based analysis of ISH gene expression images. The standard NMF approach and its variants are limited in their ability to flexibly integrate prior knowledge, in the context of spatial data. In this paper, we introduce spatial connectivity as an additional regularization in NMF decomposition via the use of Markov Random Fields (mNMF). The mNMF algorithm alternates neighborhood updates with iterations of the standard NMF algorithm to exploit spatial correlations in the data. We present the algorithm and show the sub-divisions of hippocampus and somatosensory-cortex obtained via this approach. The results are compared with established neuroanatomic knowledge. We also highlight novel gene expression based sub divisions of the hippocampus identified by using the mNMF algorithm.

Biometric, microstructural, and high-resolution trace element studies in Crassostrea gigas of Cantabria (Bay of Biscay, Spain): Anthropogenic and seasonal influences

NASA Astrophysics Data System (ADS)

Higuera-Ruiz, R.; Elorza, J.

2009-04-01

Living Crassostrea gigas oysters of different ages and sizes were collected in three estuaries of Cantabria (Bay of Biscay, Spain): San Vicente de la Barquera Estuary, Santander Bay, and Marismas de Santoña Estuary. The main objective was to determine different shell responses to variable environmental parameters. A shell morphological study, based on three biometric indices, indicates that oysters of Santander Bay have two significant shell anomalies: abnormal thickening of the right valve and loss of vital cavity volume. These shell abnormalities are related with the presence in these waters of the chemical tributyltin. In the other two estuaries, the oysters show no detectable anomalies. Four shell microstructures have been distinguished: Regular Simple Prismatic, Regular Foliated, cone-Complex Cross Foliated, and Chalk. In Santander Bay oysters, the Chalk forms a "root-type" framework, whereas in the other two estuaries it forms a more compact microstructure. It is proposed that exposure to tributyltin has produced this modification. High-spatial-resolution geochemical transects have been carried out on the Regular Foliated microstructure in the umbo region in order to evaluate the distribution of Mg, Sr, and Na. The elements analysed exhibit clear cyclic variations in San Vicente de la Barquera Estuary and Marismas de Santoña Estuary oysters, related with seasonal periods, and characterised by broad maxima during months in which the waters are warmer and have higher salinity. These patterns are buffered in Santander Bay oysters. Our results demonstrate that biometric, microstructural, and high-resolution trace element studies in oyster shells can provide information about contaminants and seasonal variations in the estuarine environment.

On the role of working memory in spatial contextual cueing.

PubMed

Travis, Susan L; Mattingley, Jason B; Dux, Paul E

2013-01-01

The human visual system receives more information than can be consciously processed. To overcome this capacity limit, we employ attentional mechanisms to prioritize task-relevant (target) information over less relevant (distractor) information. Regularities in the environment can facilitate the allocation of attention, as demonstrated by the spatial contextual cueing paradigm. When observers are exposed repeatedly to a scene and invariant distractor information, learning from earlier exposures enhances the search for the target. Here, we investigated whether spatial contextual cueing draws on spatial working memory resources and, if so, at what level of processing working memory load has its effect. Participants performed 2 tasks concurrently: a visual search task, in which the spatial configuration of some search arrays occasionally repeated, and a spatial working memory task. Increases in working memory load significantly impaired contextual learning. These findings indicate that spatial contextual cueing utilizes working memory resources.

Relatedness in spatially structured populations with empty sites: An approach based on spatial moment equations.

PubMed

Lion, Sébastien

2009-09-07

Taking into account the interplay between spatial ecological dynamics and selection is a major challenge in evolutionary ecology. Although inclusive fitness theory has proven to be a very useful tool to unravel the interactions between spatial genetic structuring and selection, applications of the theory usually rely on simplifying demographic assumptions. In this paper, I attempt to bridge the gap between spatial demographic models and kin selection models by providing a method to compute approximations for relatedness coefficients in a spatial model with empty sites. Using spatial moment equations, I provide an approximation of nearest-neighbour relatedness on random regular networks, and show that this approximation performs much better than the ordinary pair approximation. I discuss the connection between the relatedness coefficients I define and those used in population genetics, and sketch some potential extensions of the theory.

What is the context of contextual cueing?

PubMed

Makovski, Tal

2016-12-01

People have a powerful ability to extract regularities from noisy environments and to utilize this knowledge to assist in visual search. Extensive research has shown that this ability, termed contextual cueing (CC), is robust and ubiquitous, but it is still unclear what exactly is the context that is being leaned. Researchers have typically focused on how people learn spatial configuration regularities and have hence used simplified, meaningless search stimuli. Here, observers performed visual search tasks using images of real-world objects. The results revealed that, contrary to past findings, the repetition of either arbitrary spatial information or identity information was not sufficient to produce context learning. Instead, learning was found only when both types of information were repeated together. These results were further replicated in hybrid search tasks, in which subjects looked for multiple target templates. Together, these data suggest that CC is more limited than typically assumed, yet this learning is highly robust.

Robust Kriged Kalman Filtering

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

Baingana, Brian; Dall'Anese, Emiliano; Mateos, Gonzalo

2015-11-11

Although the kriged Kalman filter (KKF) has well-documented merits for prediction of spatial-temporal processes, its performance degrades in the presence of outliers due to anomalous events, or measurement equipment failures. This paper proposes a robust KKF model that explicitly accounts for presence of measurement outliers. Exploiting outlier sparsity, a novel l1-regularized estimator that jointly predicts the spatial-temporal process at unmonitored locations, while identifying measurement outliers is put forth. Numerical tests are conducted on a synthetic Internet protocol (IP) network, and real transformer load data. Test results corroborate the effectiveness of the novel estimator in joint spatial prediction and outlier identification.

Spatial and temporal distribution of trunk-injected imidacloprid in apple tree canopies.

PubMed

Aćimović, Srđan G; VanWoerkom, Anthony H; Reeb, Pablo D; Vandervoort, Christine; Garavaglia, Thomas; Cregg, Bert M; Wise, John C

2014-11-01

Pesticide use in orchards creates drift-driven pesticide losses which contaminate the environment. Trunk injection of pesticides as a target-precise delivery system could greatly reduce pesticide losses. However, pesticide efficiency after trunk injection is associated with the underinvestigated spatial and temporal distribution of the pesticide within the tree crown. This study quantified the spatial and temporal distribution of trunk-injected imidacloprid within apple crowns after trunk injection using one, two, four or eight injection ports per tree. The spatial uniformity of imidacloprid distribution in apple crowns significantly increased with more injection ports. Four ports allowed uniform spatial distribution of imidacloprid in the crown. Uniform and non-uniform spatial distributions were established early and lasted throughout the experiment. The temporal distribution of imidacloprid was significantly non-uniform. Upper and lower crown positions did not significantly differ in compound concentration. Crown concentration patterns indicated that imidacloprid transport in the trunk occurred through radial diffusion and vertical uptake with a spiral pattern. By showing where and when a trunk-injected compound is distributed in the apple tree canopy, this study addresses a key knowledge gap in terms of explaining the efficiency of the compound in the crown. These findings allow the improvement of target-precise pesticide delivery for more sustainable tree-based agriculture. © 2014 Society of Chemical Industry.

Modeling evolution of spatially distributed bacterial communities: a simulation with the haploid evolutionary constructor

PubMed Central

2015-01-01

Background Multiscale approaches for integrating submodels of various levels of biological organization into a single model became the major tool of systems biology. In this paper, we have constructed and simulated a set of multiscale models of spatially distributed microbial communities and study an influence of unevenly distributed environmental factors on the genetic diversity and evolution of the community members. Results Haploid Evolutionary Constructor software http://evol-constructor.bionet.nsc.ru/ was expanded by adding the tool for the spatial modeling of a microbial community (1D, 2D and 3D versions). A set of the models of spatially distributed communities was built to demonstrate that the spatial distribution of cells affects both intensity of selection and evolution rate. Conclusion In spatially heterogeneous communities, the change in the direction of the environmental flow might be reflected in local irregular population dynamics, while the genetic structure of populations (frequencies of the alleles) remains stable. Furthermore, in spatially heterogeneous communities, the chemotaxis might dramatically affect the evolution of community members. PMID:25708911

A Tikhonov Regularization Scheme for Focus Rotations with Focused Ultrasound Phased Arrays

PubMed Central

Hughes, Alec; Hynynen, Kullervo

2016-01-01

Phased arrays have a wide range of applications in focused ultrasound therapy. By using an array of individually-driven transducer elements, it is possible to steer a focus through space electronically and compensate for acoustically heterogeneous media with phase delays. In this paper, the concept of focusing an ultrasound phased array is expanded to include a method to control the orientation of the focus using a Tikhonov regularization scheme. It is then shown that the Tikhonov regularization parameter used to solve the ill-posed focus rotation problem plays an important role in the balance between quality focusing and array efficiency. Finally, the technique is applied to the synthesis of multiple foci, showing that this method allows for multiple independent spatial rotations. PMID:27913323

A Tikhonov Regularization Scheme for Focus Rotations With Focused Ultrasound-Phased Arrays.

PubMed

Hughes, Alec; Hynynen, Kullervo

2016-12-01

Phased arrays have a wide range of applications in focused ultrasound therapy. By using an array of individually driven transducer elements, it is possible to steer a focus through space electronically and compensate for acoustically heterogeneous media with phase delays. In this paper, the concept of focusing an ultrasound-phased array is expanded to include a method to control the orientation of the focus using a Tikhonov regularization scheme. It is then shown that the Tikhonov regularization parameter used to solve the ill-posed focus rotation problem plays an important role in the balance between quality focusing and array efficiency. Finally, the technique is applied to the synthesis of multiple foci, showing that this method allows for multiple independent spatial rotations.

Regularity gradient estimates for weak solutions of singular quasi-linear parabolic equations

NASA Astrophysics Data System (ADS)

Phan, Tuoc

2017-12-01

This paper studies the Sobolev regularity for weak solutions of a class of singular quasi-linear parabolic problems of the form ut -div [ A (x , t , u , ∇u) ] =div [ F ] with homogeneous Dirichlet boundary conditions over bounded spatial domains. Our main focus is on the case that the vector coefficients A are discontinuous and singular in (x , t)-variables, and dependent on the solution u. Global and interior weighted W 1 , p (ΩT , ω)-regularity estimates are established for weak solutions of these equations, where ω is a weight function in some Muckenhoupt class of weights. The results obtained are even new for linear equations, and for ω = 1, because of the singularity of the coefficients in (x , t)-variables.

Decadal time-scale monitoring of forest fires in Similipal Biosphere Reserve, India using remote sensing and GIS.

PubMed

Saranya, K R L; Reddy, C Sudhakar; Rao, P V V Prasada; Jha, C S

2014-05-01

Analyzing the spatial extent and distribution of forest fires is essential for sustainable forest resource management. There is no comprehensive data existing on forest fires on a regular basis in Biosphere Reserves of India. The present work have been carried out to locate and estimate the spatial extent of forest burnt areas using Resourcesat-1 data and fire frequency covering decadal fire events (2004-2013) in Similipal Biosphere Reserve. The anomalous quantity of forest burnt area was recorded during 2009 as 1,014.7 km(2). There was inconsistency in the fire susceptibility across the different vegetation types. The spatial analysis of burnt area shows that an area of 34.2 % of dry deciduous forests, followed by tree savannah, shrub savannah, and grasslands affected by fires in 2013. The analysis based on decadal time scale satellite data reveals that an area of 2,175.9 km(2) (59.6 % of total vegetation cover) has been affected by varied rate of frequency of forest fires. Fire density pattern indicates low count of burnt area patches in 2013 estimated at 1,017 and high count at 1,916 in 2004. An estimate of fire risk area over a decade identifies 12.2 km(2) is experiencing an annual fire damage. Summing the fire frequency data across the grids (each 1 km(2)) indicates 1,211 (26 %) grids are having very high disturbance regimes due to repeated fires in all the 10 years, followed by 711 grids in 9 years and 418 in 8 years and 382 in 7 years. The spatial database offers excellent opportunities to understand the ecological impact of fires on biodiversity and is helpful in formulating conservation action plans.

Optimal Spatial Design of Capacity and Quantity of Rainwater Catchment Systems for Urban Flood Mitigation

NASA Astrophysics Data System (ADS)

Huang, C.; Hsu, N.

2013-12-01

This study imports Low-Impact Development (LID) technology of rainwater catchment systems into a Storm-Water runoff Management Model (SWMM) to design the spatial capacity and quantity of rain barrel for urban flood mitigation. This study proposes a simulation-optimization model for effectively searching the optimal design. In simulation method, we design a series of regular spatial distributions of capacity and quantity of rainwater catchment facilities, and thus the reduced flooding circumstances using a variety of design forms could be simulated by SWMM. Moreover, we further calculate the net benefit that is equal to subtract facility cost from decreasing inundation loss and the best solution of simulation method would be the initial searching solution of the optimization model. In optimizing method, first we apply the outcome of simulation method and Back-Propagation Neural Network (BPNN) for developing a water level simulation model of urban drainage system in order to replace SWMM which the operating is based on a graphical user interface and is hard to combine with optimization model and method. After that we embed the BPNN-based simulation model into the developed optimization model which the objective function is minimizing the negative net benefit. Finally, we establish a tabu search-based algorithm to optimize the planning solution. This study applies the developed method in Zhonghe Dist., Taiwan. Results showed that application of tabu search and BPNN-based simulation model into the optimization model not only can find better solutions than simulation method in 12.75%, but also can resolve the limitations of previous studies. Furthermore, the optimized spatial rain barrel design can reduce 72% of inundation loss according to historical flood events.

Surprise responses in the human brain demonstrate statistical learning under high concurrent cognitive demand

NASA Astrophysics Data System (ADS)

Garrido, Marta Isabel; Teng, Chee Leong James; Taylor, Jeremy Alexander; Rowe, Elise Genevieve; Mattingley, Jason Brett

2016-06-01

The ability to learn about regularities in the environment and to make predictions about future events is fundamental for adaptive behaviour. We have previously shown that people can implicitly encode statistical regularities and detect violations therein, as reflected in neuronal responses to unpredictable events that carry a unique prediction error signature. In the real world, however, learning about regularities will often occur in the context of competing cognitive demands. Here we asked whether learning of statistical regularities is modulated by concurrent cognitive load. We compared electroencephalographic metrics associated with responses to pure-tone sounds with frequencies sampled from narrow or wide Gaussian distributions. We showed that outliers evoked a larger response than those in the centre of the stimulus distribution (i.e., an effect of surprise) and that this difference was greater for physically identical outliers in the narrow than in the broad distribution. These results demonstrate an early neurophysiological marker of the brain's ability to implicitly encode complex statistical structure in the environment. Moreover, we manipulated concurrent cognitive load by having participants perform a visual working memory task while listening to these streams of sounds. We again observed greater prediction error responses in the narrower distribution under both low and high cognitive load. Furthermore, there was no reliable reduction in prediction error magnitude under high-relative to low-cognitive load. Our findings suggest that statistical learning is not a capacity limited process, and that it proceeds automatically even when cognitive resources are taxed by concurrent demands.

Research on the optimization of air quality monitoring station layout based on spatial grid statistical analysis method.

PubMed

Li, Tianxin; Zhou, Xing Chen; Ikhumhen, Harrison Odion; Difei, An

2018-05-01

In recent years, with the significant increase in urban development, it has become necessary to optimize the current air monitoring stations to reflect the quality of air in the environment. Highlighting the spatial representation of some air monitoring stations using Beijing's regional air monitoring station data from 2012 to 2014, the monthly mean particulate matter concentration (PM10) in the region was calculated and through the IDW interpolation method and spatial grid statistical method using GIS, the spatial distribution of PM10 concentration in the whole region was deduced. The spatial distribution variation of districts in Beijing using the gridding model was performed, and through the 3-year spatial analysis, PM10 concentration data including the variation and spatial overlay (1.5 km × 1.5 km cell resolution grid), the spatial distribution result obtained showed that the total PM10 concentration frequency variation exceeded the standard. It is very important to optimize the layout of the existing air monitoring stations by combining the concentration distribution of air pollutants with the spatial region using GIS.

On the persistence of spatiotemporal oscillations generated by invasion

NASA Astrophysics Data System (ADS)

Kay, A. L.; Sherratt, J. A.

1999-10-01

Many systems in biology and chemistry are oscillatory, with a stable, spatially homogeneous steady state which consists of periodic temporal oscillations in the interacting species, and such systems have been extensively studied on infinite or semi-infinite spatial domains. We consider the effect of a finite domain, with zero-flux boundary conditions, on the behaviour of solutions to oscillatory reaction-diffusion equations after invasion. We begin by considering numerical simulations of various oscillatory predatory-prey systems. We conclude that when regular spatiotemporal oscillations are left in the wake of invasion, these die out, beginning with a decrease in the spatial frequency of the oscillations at one boundary, which then propagates across the domain. The long-time solution in this case is purely temporal oscillations, corresponding to the limit cycle of the kinetics. Contrastingly, when irregular spatiotemporal oscillations are left in the wake of invasion, they persist, even in very long time simulations. To study this phenomenon in more detail, we consider the {lambda}-{omega} class of reaction-diffusion systems. Numerical simulations show that these systems also exhibit die-out of regular spatiotemporal oscillations and persistence of irregular spatiotemporal oscillations. Exploiting the mathematical simplicity of the {lambda}-{omega} form, we derive analytically an approximation to the transition fronts in r and {theta}x which occur during the die-out of the regular oscillations. We then use this approximation to describe how the die-out occurs, and to derive a measure of its rate, as a function of parameter values. We discuss applications of our results to ecology, calcium signalling and chemistry.

Rogue waves and large deviations in deep sea.

PubMed

Dematteis, Giovanni; Grafke, Tobias; Vanden-Eijnden, Eric

2018-01-30

The appearance of rogue waves in deep sea is investigated by using the modified nonlinear Schrödinger (MNLS) equation in one spatial dimension with random initial conditions that are assumed to be normally distributed, with a spectrum approximating realistic conditions of a unidirectional sea state. It is shown that one can use the incomplete information contained in this spectrum as prior and supplement this information with the MNLS dynamics to reliably estimate the probability distribution of the sea surface elevation far in the tail at later times. Our results indicate that rogue waves occur when the system hits unlikely pockets of wave configurations that trigger large disturbances of the surface height. The rogue wave precursors in these pockets are wave patterns of regular height, but with a very specific shape that is identified explicitly, thereby allowing for early detection. The method proposed here combines Monte Carlo sampling with tools from large deviations theory that reduce the calculation of the most likely rogue wave precursors to an optimization problem that can be solved efficiently. This approach is transferable to other problems in which the system's governing equations contain random initial conditions and/or parameters.

Understanding the Spatio-Temporal Pattern of Fire Disturbance in the Eastern Mongolia Using Modis Product

NASA Astrophysics Data System (ADS)

Wurihan; Zhang, H.; Zhang, Z.; Guo, X.; Zhao, J.; Duwala; Shan, Y.; Hongying

2018-04-01

Fire disturbance plays an important role in maintaining ecological balance, biodiversity and self-renewal. In this paper, the spatio-temporal pattern of fire disturbances in eastern Mongolia are studied by using the ArcGIS spatial analysis method, using the MCD45A1 data of MODIS fire products with long time series. It provides scientific basis and reference for the regional ecological environment security construction and international ecological security. Research indicates: (1) The fire disturbance in eastern Mongolia has obvious high and low peak interleaving phenomenon in the year, and the seasonal change is obvious. (2) The distribution pattern of fire disturbance in eastern Mongolia is aggregated, which indicates that the fire disturbance is not random and it is caused by certain influence. (3) Fire disturbance is mainly distributed in the eastern province of Mongolia, the border between China and Mongolia and the northern forest area of Sukhbaatar province. (4) The fire disturbance in the eastern part of the study area is strong and the southwest is weaker. The spreading regularity of fire disturbances in eastern Mongolia is closer to the natural level of ecosystem.

The privileged spectrum of cnoidal ion holes and its extension by imperfect ion trapping

NASA Astrophysics Data System (ADS)

Schamel, Hans; Das, Nilakshi; Borah, Prathana

2018-01-01

The fundamental properties of nonlinear ion hole modes propagating in current-driven collisionless plasmas are derived. Making use of Schamel's alternative method their spatial structure ϕ (x) and phase velocities u0 are analyzed and found to depend crucially on the used trapped ion distribution fit. A regular fit represents a continuous spectrum, which is called privileged or perfect since it yields a definite u0 and appears most realistic. A singular fit, on the other hand, involving jumps and moderate slope singularities at the separatrix, does reveal further classes of hole equilibria at the cost, however, of a well-defined u0. This explains why Bernstein, Greene, Kruskal (BGK)-solutions of the Vlasov-Poisson system, exhibiting a strong slope singularity of their derived trapped particle distribution, can principally not provide definite u0 s. The nonlinear dispersion relation (or u0) of privileged ion holes, on the other hand, is equivalent with that of cnoidal electron holes, i.e. in addition to the ordinary ion acoustic branch there exists a correspondence to the "Langmuir" branch and to the multiple "slow electron acoustic" branches, reflecting different trapping scenarios.

Molecular dynamics simulation of temperature effects on low energy near-surface cascades and surface damage in Cu

NASA Astrophysics Data System (ADS)

Zhu, Guo; Sun, Jiangping; Guo, Xiongxiong; Zou, Xixi; Zhang, Libin; Gan, Zhiyin

2017-06-01

The temperature effects on near-surface cascades and surface damage in Cu(0 0 1) surface under 500 eV argon ion bombardment were studied using molecular dynamics (MD) method. In present MD model, substrate system was fully relaxed for 1 ns and a read-restart scheme was introduced to save total computation time. The temperature dependence of damage production was calculated. The evolution of near-surface cascades and spatial distribution of adatoms at varying temperature were analyzed and compared. It was found that near-surface vacancies increased with temperature, which was mainly due to the fact that more atoms initially located in top two layers became adatoms with the decrease of surface binding energy. Moreover, with the increase of temperature, displacement cascades altered from channeling-like structure to branching structure, and the length of collision sequence decreased gradually, because a larger portion of energy of primary knock-on atom (PKA) was scattered out of focused chain. Furthermore, increasing temperature reduced the anisotropy of distribution of adatoms, which can be ascribed to that regular registry of surface lattice atoms was changed with the increase of thermal vibration amplitude of surface atoms.

Surface rupture and slip distribution of the 2016 Mw7.8 Kaikoura earthquake (New Zealand) from optical satellite image correlation using MicMac

NASA Astrophysics Data System (ADS)

Champenois, Johann; Klinger, Yann; Grandin, Raphaël; Satriano, Claudio; Baize, Stéphane; Delorme, Arthur; Scotti, Oona

2017-04-01

Remote sensing techniques, like optical satellite image correlation, are very efficient methods to localize and quantify surface displacements due to earthquakes. In this study, we use the french sub-pixel correlator MicMac (Multi Images Correspondances par Méthodes Automatiques de Corrélation). This free open-source software, developed by IGN, was recently adapted to process satellite images. This correlator uses regularization, and that provides good results especially in near-fault area with a high spatial resolution. We use co-seismic pair of ortho-images to measure the horizontal displacement field during the recent 2016 Mw7.8 Kaikoura earthquake. Optical satellite images from different satellites are processed (Sentinel-2A, Landsat8, etc.) to present a dense map of the surface ruptures and to analyze high density slip distribution along all major ruptures. We also provide a detail pattern of deformation along these main surface ruptures. Moreover, 2D displacement from optical correlation is compared to co-seismic measurements from GPS, static displacement from accelerometric records, geodetic marks and field investigations. Last but not least, we investigate the reconstruction of 3D displacement from combining InSAR, GPS and optic.

MEG Connectivity and Power Detections with Minimum Norm Estimates Require Different Regularization Parameters.

PubMed

Hincapié, Ana-Sofía; Kujala, Jan; Mattout, Jérémie; Daligault, Sebastien; Delpuech, Claude; Mery, Domingo; Cosmelli, Diego; Jerbi, Karim

2016-01-01

Minimum Norm Estimation (MNE) is an inverse solution method widely used to reconstruct the source time series that underlie magnetoencephalography (MEG) data. MNE addresses the ill-posed nature of MEG source estimation through regularization (e.g., Tikhonov regularization). Selecting the best regularization parameter is a critical step. Generally, once set, it is common practice to keep the same coefficient throughout a study. However, it is yet to be known whether the optimal lambda for spectral power analysis of MEG source data coincides with the optimal regularization for source-level oscillatory coupling analysis. We addressed this question via extensive Monte-Carlo simulations of MEG data, where we generated 21,600 configurations of pairs of coupled sources with varying sizes, signal-to-noise ratio (SNR), and coupling strengths. Then, we searched for the Tikhonov regularization coefficients (lambda) that maximize detection performance for (a) power and (b) coherence. For coherence, the optimal lambda was two orders of magnitude smaller than the best lambda for power. Moreover, we found that the spatial extent of the interacting sources and SNR, but not the extent of coupling, were the main parameters affecting the best choice for lambda. Our findings suggest using less regularization when measuring oscillatory coupling compared to power estimation.