Micro-scale Spatial Clustering of Cholera Risk Factors in Urban Bangladesh.

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Bi, Qifang; Azman, Andrew S; Satter, Syed Moinuddin; Khan, Azharul Islam; Ahmed, Dilruba; Riaj, Altaf Ahmed; Gurley, Emily S; Lessler, Justin

2016-02-01

Close interpersonal contact likely drives spatial clustering of cases of cholera and diarrhea, but spatial clustering of risk factors may also drive this pattern. Few studies have focused specifically on how exposures for disease cluster at small spatial scales. Improving our understanding of the micro-scale clustering of risk factors for cholera may help to target interventions and power studies with cluster designs. We selected sets of spatially matched households (matched-sets) near cholera case households between April and October 2013 in a cholera endemic urban neighborhood of Tongi Township in Bangladesh. We collected data on exposures to suspected cholera risk factors at the household and individual level. We used intra-class correlation coefficients (ICCs) to characterize clustering of exposures within matched-sets and households, and assessed if clustering depended on the geographical extent of the matched-sets. Clustering over larger spatial scales was explored by assessing the relationship between matched-sets. We also explored whether different exposures tended to appear together in individuals, households, and matched-sets. Household level exposures, including: drinking municipal supplied water (ICC = 0.97, 95%CI = 0.96, 0.98), type of latrine (ICC = 0.88, 95%CI = 0.71, 1.00), and intermittent access to drinking water (ICC = 0.96, 95%CI = 0.87, 1.00) exhibited strong clustering within matched-sets. As the geographic extent of matched-sets increased, the concordance of exposures within matched-sets decreased. Concordance between matched-sets of exposures related to water supply was elevated at distances of up to approximately 400 meters. Household level hygiene practices were correlated with infrastructure shown to increase cholera risk. Co-occurrence of different individual level exposures appeared to mostly reflect the differing domestic roles of study participants. Strong spatial clustering of exposures at a small spatial scale in a cholera endemic

Micro-scale Spatial Clustering of Cholera Risk Factors in Urban Bangladesh.

Directory of Open Access Journals (Sweden)

Qifang Bi

2016-02-01

Full Text Available Close interpersonal contact likely drives spatial clustering of cases of cholera and diarrhea, but spatial clustering of risk factors may also drive this pattern. Few studies have focused specifically on how exposures for disease cluster at small spatial scales. Improving our understanding of the micro-scale clustering of risk factors for cholera may help to target interventions and power studies with cluster designs. We selected sets of spatially matched households (matched-sets near cholera case households between April and October 2013 in a cholera endemic urban neighborhood of Tongi Township in Bangladesh. We collected data on exposures to suspected cholera risk factors at the household and individual level. We used intra-class correlation coefficients (ICCs to characterize clustering of exposures within matched-sets and households, and assessed if clustering depended on the geographical extent of the matched-sets. Clustering over larger spatial scales was explored by assessing the relationship between matched-sets. We also explored whether different exposures tended to appear together in individuals, households, and matched-sets. Household level exposures, including: drinking municipal supplied water (ICC = 0.97, 95%CI = 0.96, 0.98, type of latrine (ICC = 0.88, 95%CI = 0.71, 1.00, and intermittent access to drinking water (ICC = 0.96, 95%CI = 0.87, 1.00 exhibited strong clustering within matched-sets. As the geographic extent of matched-sets increased, the concordance of exposures within matched-sets decreased. Concordance between matched-sets of exposures related to water supply was elevated at distances of up to approximately 400 meters. Household level hygiene practices were correlated with infrastructure shown to increase cholera risk. Co-occurrence of different individual level exposures appeared to mostly reflect the differing domestic roles of study participants. Strong spatial clustering of exposures at a small spatial scale in a

GraphTeams: a method for discovering spatial gene clusters in Hi-C sequencing data.

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Schulz, Tizian; Stoye, Jens; Doerr, Daniel

2018-05-08

Hi-C sequencing offers novel, cost-effective means to study the spatial conformation of chromosomes. We use data obtained from Hi-C experiments to provide new evidence for the existence of spatial gene clusters. These are sets of genes with associated functionality that exhibit close proximity to each other in the spatial conformation of chromosomes across several related species. We present the first gene cluster model capable of handling spatial data. Our model generalizes a popular computational model for gene cluster prediction, called δ-teams, from sequences to graphs. Following previous lines of research, we subsequently extend our model to allow for several vertices being associated with the same label. The model, called δ-teams with families, is particular suitable for our application as it enables handling of gene duplicates. We develop algorithmic solutions for both models. We implemented the algorithm for discovering δ-teams with families and integrated it into a fully automated workflow for discovering gene clusters in Hi-C data, called GraphTeams. We applied it to human and mouse data to find intra- and interchromosomal gene cluster candidates. The results include intrachromosomal clusters that seem to exhibit a closer proximity in space than on their chromosomal DNA sequence. We further discovered interchromosomal gene clusters that contain genes from different chromosomes within the human genome, but are located on a single chromosome in mouse. By identifying δ-teams with families, we provide a flexible model to discover gene cluster candidates in Hi-C data. Our analysis of Hi-C data from human and mouse reveals several known gene clusters (thus validating our approach), but also few sparsely studied or possibly unknown gene cluster candidates that could be the source of further experimental investigations.

The spatial evaluation of neighborhood clusters of birth defects

Energy Technology Data Exchange (ETDEWEB)

Frisch, J.D.

1990-04-16

Spatial statistics have recently been applied in epidemiology to evaluate clusters of cancer and birth defects. Their use requires a comparison population, drawn from the population at risk for disease, that may not always be readily available. In this dissertation the plausibility of using data on all birth defects, available from birth defects registries, as a surrogate for the spatial distribution of all live births in the analysis of clusters is assessed. Three spatial statistics that have been applied in epidemiologic investigations of clusters, nearest neighbor distance, average interpoint distance, and average distance to a fixed point, were evaluated by computer simulation for their properties in a unit square, and in a zip code region. Comparison of spatial distributions of live births and birth defects was performed by drawing samples of live births and birth defects from Santa Clara County, determining the street address at birth, geocoding this address and evaluating the resultant maps using various statistical techniques. The proposed method was then demonstrated on a previously confirmed cluster of oral cleft cases. All live births for the neighborhood were geocoded, as were all birth defects. Evaluation of this cluster using the nearest neighbor and average interpoint distance statistics was performed using randomization techniques with both the live births population and the birth defect population as comparison groups. 113 refs., 36 figs., 16 tabs.

A scan statistic for binary outcome based on hypergeometric probability model, with an application to detecting spatial clusters of Japanese encephalitis.

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Zhao, Xing; Zhou, Xiao-Hua; Feng, Zijian; Guo, Pengfei; He, Hongyan; Zhang, Tao; Duan, Lei; Li, Xiaosong

2013-01-01

As a useful tool for geographical cluster detection of events, the spatial scan statistic is widely applied in many fields and plays an increasingly important role. The classic version of the spatial scan statistic for the binary outcome is developed by Kulldorff, based on the Bernoulli or the Poisson probability model. In this paper, we apply the Hypergeometric probability model to construct the likelihood function under the null hypothesis. Compared with existing methods, the likelihood function under the null hypothesis is an alternative and indirect method to identify the potential cluster, and the test statistic is the extreme value of the likelihood function. Similar with Kulldorff's methods, we adopt Monte Carlo test for the test of significance. Both methods are applied for detecting spatial clusters of Japanese encephalitis in Sichuan province, China, in 2009, and the detected clusters are identical. Through a simulation to independent benchmark data, it is indicated that the test statistic based on the Hypergeometric model outweighs Kulldorff's statistics for clusters of high population density or large size; otherwise Kulldorff's statistics are superior.

Spatial Cluster Detection for Repeatedly Measured Outcomes while Accounting for Residential History

OpenAIRE

Cook, Andrea J.; Gold, Diane R.; Li, Yi

2009-01-01

Spatial cluster detection has become an important methodology in quantifying the effect of hazardous exposures. Previous methods have focused on cross-sectional outcomes that are binary or continuous. There are virtually no spatial cluster detection methods proposed for longitudinal outcomes. This paper proposes a new spatial cluster detection method for repeated outcomes using cumulative geographic residuals. A major advantage of this method is its ability to readily incorporate information ...

Spatial clustering and local risk of leprosy in São Paulo, Brazil.

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Antônio Carlos Vieira Ramos

2017-02-01

Full Text Available Although the detection rate is decreasing, the proportion of new cases with WHO grade 2 disability (G2D is increasing, creating concern among policy makers and the Brazilian government. This study aimed to identify spatial clustering of leprosy and classify high-risk areas in a major leprosy cluster using the SatScan method.Data were obtained including all leprosy cases diagnosed between January 2006 and December 2013. In addition to the clinical variable, information was also gathered regarding the G2D of the patient at diagnosis and after treatment. The Scan Spatial statistic test, developed by Kulldorff e Nagarwalla, was used to identify spatial clustering and to measure the local risk (Relative Risk-RR of leprosy. Maps considering these risks and their confidence intervals were constructed.A total of 434 cases were identified, including 188 (43.31% borderline leprosy and 101 (23.28% lepromatous leprosy cases. There was a predominance of males, with ages ranging from 15 to 59 years, and 51 patients (11.75% presented G2D. Two significant spatial clusters and three significant spatial-temporal clusters were also observed. The main spatial cluster (p = 0.000 contained 90 census tracts, a population of approximately 58,438 inhabitants, detection rate of 22.6 cases per 100,000 people and RR of approximately 3.41 (95%CI = 2.721-4.267. Regarding the spatial-temporal clusters, two clusters were observed, with RR ranging between 24.35 (95%CI = 11.133-52.984 and 15.24 (95%CI = 10.114-22.919.These findings could contribute to improvements in policies and programming, aiming for the eradication of leprosy in Brazil. The Spatial Scan statistic test was found to be an interesting resource for health managers and healthcare professionals to map the vulnerability of areas in terms of leprosy transmission risk and areas of underreporting.

Spatial clustering and local risk of leprosy in São Paulo, Brazil.

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Ramos, Antônio Carlos Vieira; Yamamura, Mellina; Arroyo, Luiz Henrique; Popolin, Marcela Paschoal; Chiaravalloti Neto, Francisco; Palha, Pedro Fredemir; Uchoa, Severina Alice da Costa; Pieri, Flávia Meneguetti; Pinto, Ione Carvalho; Fiorati, Regina Célia; Queiroz, Ana Angélica Rêgo de; Belchior, Aylana de Souza; Dos Santos, Danielle Talita; Garcia, Maria Concebida da Cunha; Crispim, Juliane de Almeida; Alves, Luana Seles; Berra, Thaís Zamboni; Arcêncio, Ricardo Alexandre

2017-02-01

Although the detection rate is decreasing, the proportion of new cases with WHO grade 2 disability (G2D) is increasing, creating concern among policy makers and the Brazilian government. This study aimed to identify spatial clustering of leprosy and classify high-risk areas in a major leprosy cluster using the SatScan method. Data were obtained including all leprosy cases diagnosed between January 2006 and December 2013. In addition to the clinical variable, information was also gathered regarding the G2D of the patient at diagnosis and after treatment. The Scan Spatial statistic test, developed by Kulldorff e Nagarwalla, was used to identify spatial clustering and to measure the local risk (Relative Risk-RR) of leprosy. Maps considering these risks and their confidence intervals were constructed. A total of 434 cases were identified, including 188 (43.31%) borderline leprosy and 101 (23.28%) lepromatous leprosy cases. There was a predominance of males, with ages ranging from 15 to 59 years, and 51 patients (11.75%) presented G2D. Two significant spatial clusters and three significant spatial-temporal clusters were also observed. The main spatial cluster (p = 0.000) contained 90 census tracts, a population of approximately 58,438 inhabitants, detection rate of 22.6 cases per 100,000 people and RR of approximately 3.41 (95%CI = 2.721-4.267). Regarding the spatial-temporal clusters, two clusters were observed, with RR ranging between 24.35 (95%CI = 11.133-52.984) and 15.24 (95%CI = 10.114-22.919). These findings could contribute to improvements in policies and programming, aiming for the eradication of leprosy in Brazil. The Spatial Scan statistic test was found to be an interesting resource for health managers and healthcare professionals to map the vulnerability of areas in terms of leprosy transmission risk and areas of underreporting.

Measuring the stellar luminosity function and spatial density profile of the inner 0.5 pc of the Milky Way nuclear star cluster

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Do, Tuan; Ghez, Andrea; Lu, Jessica R.; Morris, Mark R.; Yelda, Sylvana; Martinez, Gregory D.; Peter, Annika H. G.; Wright, Shelley; Bullock, James; Kaplinghat, Manoj; Matthews, K.

2012-07-01

We report on measurements of the luminosity function of early (young) and late-type (old) stars in the central 0.5 pc of the Milky Way nuclear star cluster as well as the density profiles of both components. The young (~ 6 Myr) and old stars (> 1 Gyr) in this region provide different physical probes of the environment around a supermassive black hole; the luminosity function of the young stars offers us a way to measure the initial mass function from star formation in an extreme environment, while the density profile of the old stars offers us a probe of the dynamical interaction of a star cluster with a massive black hole. The two stellar populations are separated through a near-infrared spectroscopic survey using the integral-field spectrograph OSIRIS on Keck II behind the laser guide star adaptive optics system. This spectroscopic survey is able to separate early-type (young) and late-type (old) stars with a completeness of 50% at K' = 15.5. We describe our method of completeness correction using a combination of star planting simulations and Bayesian inference. The completeness corrected luminosity function of the early-type stars contains significantly more young stars at faint magnitudes compared to previous surveys with similar depth. In addition, by using proper motion and radial velocity measurements along with anisotropic spherical Jeans modeling of the cluster, it is possible to measure the spatial density profile of the old stars, which has been difficult to constrain with number counts alone. The most probable model shows that the spatial density profile, n(r) propto r-γ, to be shallow with γ = 0.4 ± 0.2, which is much flatter than the dynamically relaxed case of γ = 3/2 to 7/4, but does rule out a 'hole' in the distribution of old stars. We show, for the first time, that the spatial density profile, the black hole mass, and velocity anisotropy can be fit simultaneously to obtain a black hole mass that is consistent with that derived from

Spatial and space-time clustering of tuberculosis in Gurage Zone, Southern Ethiopia.

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Tadesse, Sebsibe; Enqueselassie, Fikre; Hagos, Seifu

2018-01-01

Spatial targeting is advocated as an effective method that contributes for achieving tuberculosis control in high-burden countries. However, there is a paucity of studies clarifying the spatial nature of the disease in these countries. This study aims to identify the location, size and risk of purely spatial and space-time clusters for high occurrence of tuberculosis in Gurage Zone, Southern Ethiopia during 2007 to 2016. A total of 15,805 patient data that were retrieved from unit TB registers were included in the final analyses. The spatial and space-time cluster analyses were performed using the global Moran's I, Getis-Ord [Formula: see text] and Kulldorff's scan statistics. Eleven purely spatial and three space-time clusters were detected (P <0.001).The clusters were concentrated in border areas of the Gurage Zone. There were considerable spatial variations in the risk of tuberculosis by year during the study period. This study showed that tuberculosis clusters were mainly concentrated at border areas of the Gurage Zone during the study period, suggesting that there has been sustained transmission of the disease within these locations. The findings may help intensify the implementation of tuberculosis control activities in these locations. Further study is warranted to explore the roles of various ecological factors on the observed spatial distribution of tuberculosis.

Using Spatial Clustering in Forecasting Groundwater Quality Parameters by ANFIS

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MohammadTaghi Alami

2016-07-01

Full Text Available Groundwater is a major source of water supply for domestic, agricultural, and industrial uses; hence, its quality modeling is an important task in hydro-environmental studies. While many data-based models have been developed for this purpose, the performance of such data-based models can be drastically enhanced if they are based on temporal and spatial pre-processing. In this study, geostatistics tools (e.g., Co-Kriging, as spatial estimators, and self-organizing map (SOM, as a clustering technique, were employed in conjunction with Adaptive Neuro-Fuzzy Inference System (ANFIS for the temporal forecasting of such quality parameters as electrical conductivity (EC and total dissolved solids (TDS of the groundwater in Ardabil Plain. Using the results thus obtained, the impact of spatial data clustering was also investigated on the same parameters. The results showed that, if propoer input data are selected, the proposed spatial clustering technique is capable of imporving groundwater quality forecasts made by ANFIS.

Hierarchical clustering using correlation metric and spatial continuity constraint

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Stork, Christopher L.; Brewer, Luke N.

2012-10-02

Large data sets are analyzed by hierarchical clustering using correlation as a similarity measure. This provides results that are superior to those obtained using a Euclidean distance similarity measure. A spatial continuity constraint may be applied in hierarchical clustering analysis of images.

Spatial cluster detection for repeatedly measured outcomes while accounting for residential history.

Science.gov (United States)

Cook, Andrea J; Gold, Diane R; Li, Yi

2009-10-01

Spatial cluster detection has become an important methodology in quantifying the effect of hazardous exposures. Previous methods have focused on cross-sectional outcomes that are binary or continuous. There are virtually no spatial cluster detection methods proposed for longitudinal outcomes. This paper proposes a new spatial cluster detection method for repeated outcomes using cumulative geographic residuals. A major advantage of this method is its ability to readily incorporate information on study participants relocation, which most cluster detection statistics cannot. Application of these methods will be illustrated by the Home Allergens and Asthma prospective cohort study analyzing the relationship between environmental exposures and repeated measured outcome, occurrence of wheeze in the last 6 months, while taking into account mobile locations.

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

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Wen-Yen Lin

2016-09-01

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

Identifying clusters of active transportation using spatial scan statistics.

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Huang, Lan; Stinchcomb, David G; Pickle, Linda W; Dill, Jennifer; Berrigan, David

2009-08-01

There is an intense interest in the possibility that neighborhood characteristics influence active transportation such as walking or biking. The purpose of this paper is to illustrate how a spatial cluster identification method can evaluate the geographic variation of active transportation and identify neighborhoods with unusually high/low levels of active transportation. Self-reported walking/biking prevalence, demographic characteristics, street connectivity variables, and neighborhood socioeconomic data were collected from respondents to the 2001 California Health Interview Survey (CHIS; N=10,688) in Los Angeles County (LAC) and San Diego County (SDC). Spatial scan statistics were used to identify clusters of high or low prevalence (with and without age-adjustment) and the quantity of time spent walking and biking. The data, a subset from the 2001 CHIS, were analyzed in 2007-2008. Geographic clusters of significantly high or low prevalence of walking and biking were detected in LAC and SDC. Structural variables such as street connectivity and shorter block lengths are consistently associated with higher levels of active transportation, but associations between active transportation and socioeconomic variables at the individual and neighborhood levels are mixed. Only one cluster with less time spent walking and biking among walkers/bikers was detected in LAC, and this was of borderline significance. Age-adjustment affects the clustering pattern of walking/biking prevalence in LAC, but not in SDC. The use of spatial scan statistics to identify significant clustering of health behaviors such as active transportation adds to the more traditional regression analysis that examines associations between behavior and environmental factors by identifying specific geographic areas with unusual levels of the behavior independent of predefined administrative units.

A flexible spatial scan statistic with a restricted likelihood ratio for detecting disease clusters.

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Tango, Toshiro; Takahashi, Kunihiko

2012-12-30

Spatial scan statistics are widely used tools for detection of disease clusters. Especially, the circular spatial scan statistic proposed by Kulldorff (1997) has been utilized in a wide variety of epidemiological studies and disease surveillance. However, as it cannot detect noncircular, irregularly shaped clusters, many authors have proposed different spatial scan statistics, including the elliptic version of Kulldorff's scan statistic. The flexible spatial scan statistic proposed by Tango and Takahashi (2005) has also been used for detecting irregularly shaped clusters. However, this method sets a feasible limitation of a maximum of 30 nearest neighbors for searching candidate clusters because of heavy computational load. In this paper, we show a flexible spatial scan statistic implemented with a restricted likelihood ratio proposed by Tango (2008) to (1) eliminate the limitation of 30 nearest neighbors and (2) to have surprisingly much less computational time than the original flexible spatial scan statistic. As a side effect, it is shown to be able to detect clusters with any shape reasonably well as the relative risk of the cluster becomes large via Monte Carlo simulation. We illustrate the proposed spatial scan statistic with data on mortality from cerebrovascular disease in the Tokyo Metropolitan area, Japan. Copyright © 2012 John Wiley & Sons, Ltd.

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

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Curtis Andrew

2006-03-01

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

Cluster: A New Application for Spatial Analysis of Pixelated Data for Epiphytotics.

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Nelson, Scot C; Corcoja, Iulian; Pethybridge, Sarah J

2017-12-01

Spatial analysis of epiphytotics is essential to develop and test hypotheses about pathogen ecology, disease dynamics, and to optimize plant disease management strategies. Data collection for spatial analysis requires substantial investment in time to depict patterns in various frames and hierarchies. We developed a new approach for spatial analysis of pixelated data in digital imagery and incorporated the method in a stand-alone desktop application called Cluster. The user isolates target entities (clusters) by designating up to 24 pixel colors as nontargets and moves a threshold slider to visualize the targets. The app calculates the percent area occupied by targeted pixels, identifies the centroids of targeted clusters, and computes the relative compass angle of orientation for each cluster. Users can deselect anomalous clusters manually and/or automatically by specifying a size threshold value to exclude smaller targets from the analysis. Up to 1,000 stochastic simulations randomly place the centroids of each cluster in ranked order of size (largest to smallest) within each matrix while preserving their calculated angles of orientation for the long axes. A two-tailed probability t test compares the mean inter-cluster distances for the observed versus the values derived from randomly simulated maps. This is the basis for statistical testing of the null hypothesis that the clusters are randomly distributed within the frame of interest. These frames can assume any shape, from natural (e.g., leaf) to arbitrary (e.g., a rectangular or polygonal field). Cluster summarizes normalized attributes of clusters, including pixel number, axis length, axis width, compass orientation, and the length/width ratio, available to the user as a downloadable spreadsheet. Each simulated map may be saved as an image and inspected. Provided examples demonstrate the utility of Cluster to analyze patterns at various spatial scales in plant pathology and ecology and highlight the

Universal Spatial Correlation Functions for Describing and Reconstructing Soil Microstructure

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Skvortsova, Elena B.; Mallants, Dirk

2015-01-01

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

A novel artificial immune algorithm for spatial clustering with obstacle constraint and its applications.

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Sun, Liping; Luo, Yonglong; Ding, Xintao; Zhang, Ji

2014-01-01

An important component of a spatial clustering algorithm is the distance measure between sample points in object space. In this paper, the traditional Euclidean distance measure is replaced with innovative obstacle distance measure for spatial clustering under obstacle constraints. Firstly, we present a path searching algorithm to approximate the obstacle distance between two points for dealing with obstacles and facilitators. Taking obstacle distance as similarity metric, we subsequently propose the artificial immune clustering with obstacle entity (AICOE) algorithm for clustering spatial point data in the presence of obstacles and facilitators. Finally, the paper presents a comparative analysis of AICOE algorithm and the classical clustering algorithms. Our clustering model based on artificial immune system is also applied to the case of public facility location problem in order to establish the practical applicability of our approach. By using the clone selection principle and updating the cluster centers based on the elite antibodies, the AICOE algorithm is able to achieve the global optimum and better clustering effect.

A Novel Artificial Immune Algorithm for Spatial Clustering with Obstacle Constraint and Its Applications

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Liping Sun

2014-01-01

Full Text Available An important component of a spatial clustering algorithm is the distance measure between sample points in object space. In this paper, the traditional Euclidean distance measure is replaced with innovative obstacle distance measure for spatial clustering under obstacle constraints. Firstly, we present a path searching algorithm to approximate the obstacle distance between two points for dealing with obstacles and facilitators. Taking obstacle distance as similarity metric, we subsequently propose the artificial immune clustering with obstacle entity (AICOE algorithm for clustering spatial point data in the presence of obstacles and facilitators. Finally, the paper presents a comparative analysis of AICOE algorithm and the classical clustering algorithms. Our clustering model based on artificial immune system is also applied to the case of public facility location problem in order to establish the practical applicability of our approach. By using the clone selection principle and updating the cluster centers based on the elite antibodies, the AICOE algorithm is able to achieve the global optimum and better clustering effect.

Mining Co-Location Patterns with Clustering Items from Spatial Data Sets

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Zhou, G.; Li, Q.; Deng, G.; Yue, T.; Zhou, X.

2018-05-01

The explosive growth of spatial data and widespread use of spatial databases emphasize the need for the spatial data mining. Co-location patterns discovery is an important branch in spatial data mining. Spatial co-locations represent the subsets of features which are frequently located together in geographic space. However, the appearance of a spatial feature C is often not determined by a single spatial feature A or B but by the two spatial features A and B, that is to say where A and B appear together, C often appears. We note that this co-location pattern is different from the traditional co-location pattern. Thus, this paper presents a new concept called clustering terms, and this co-location pattern is called co-location patterns with clustering items. And the traditional algorithm cannot mine this co-location pattern, so we introduce the related concept in detail and propose a novel algorithm. This algorithm is extended by join-based approach proposed by Huang. Finally, we evaluate the performance of this algorithm.

A Comparison between Standard and Functional Clustering Methodologies: Application to Agricultural Fields for Yield Pattern Assessment

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Simone Pascucci

2018-04-01

Full Text Available The recognition of spatial patterns within agricultural fields, presenting similar yield potential areas, stable through time, is very important for optimizing agricultural practices. This study proposes the evaluation of different clustering methodologies applied to multispectral satellite time series for retrieving temporally stable (constant patterns in agricultural fields, related to within-field yield spatial distribution. The ability of different clustering procedures for the recognition and mapping of constant patterns in fields of cereal crops was assessed. Crop vigor patterns, considered to be related to soils characteristics, and possibly indicative of yield potential, were derived by applying the different clustering algorithms to time series of Landsat images acquired on 94 agricultural fields near Rome (Italy. Two different approaches were applied and validated using Landsat 7 and 8 archived imagery. The first approach automatically extracts and calculates for each field of interest (FOI the Normalized Difference Vegetation Index (NDVI, then exploits the standard K-means clustering algorithm to derive constant patterns at the field level. The second approach applies novel clustering procedures directly to spectral reflectance time series, in particular: (1 standard K-means; (2 functional K-means; (3 multivariate functional principal components clustering analysis; (4 hierarchical clustering. The different approaches were validated through cluster accuracy estimates on a reference set of FOIs for which yield maps were available for some years. Results show that multivariate functional principal components clustering, with an a priori determination of the optimal number of classes for each FOI, provides a better accuracy than those of standard clustering algorithms. The proposed novel functional clustering methodologies are effective and efficient for constant pattern retrieval and can be used for a sustainable management of

Spatial cluster analysis of human cases of Crimean Congo hemorrhagic fever reported in Pakistan.

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Abbas, Tariq; Younus, Muhammad; Muhammad, Sayyad Aun

2015-01-01

Crimean Congo hemorrhagic fever (CCHF) is a tick-borne viral zoonotic disease that has been reported in almost all geographic regions in Pakistan. The aim of this study was to identify spatial clusters of human cases of CCHF reported in country. Kulldorff's spatial scan statisitc, Anselin's Local Moran's I and Getis Ord Gi* tests were applied on data (i.e. number of laboratory confirmed cases reported from each district during year 2013). The analyses revealed a large multi-district cluster of high CCHF incidence in the uplands of Balochistan province near it border with Afghanistan. The cluster comprised the following districts: Qilla Abdullah; Qilla Saifullah; Loralai, Quetta, Sibi, Chagai, and Mastung. Another cluster was detected in Punjab and included Rawalpindi district and a part of Islamabad. We provide empirical evidence of spatial clustering of human CCHF cases in the country. The districts in the clusters should be given priority in surveillance, control programs, and further research.

Spatial clustering of childhood cancer in Great Britain during the period 1969-1993.

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McNally, Richard J Q; Alexander, Freda E; Vincent, Tim J; Murphy, Michael F G

2009-02-15

The aetiology of childhood cancer is poorly understood. Both genetic and environmental factors are likely to be involved. The presence of spatial clustering is indicative of a very localized environmental component to aetiology. Spatial clustering is present when there are a small number of areas with greatly increased incidence or a large number of areas with moderately increased incidence. To determine whether localized environmental factors may play a part in childhood cancer aetiology, we analyzed for spatial clustering using a large set of national population-based data from Great Britain diagnosed 1969-1993. The Potthoff-Whittinghill method was used to test for extra-Poisson variation (EPV). Thirty-two thousand three hundred and twenty-three cases were allocated to 10,444 wards using diagnosis addresses. Analyses showed statistically significant evidence of clustering for acute lymphoblastic leukaemia (ALL) over the whole age range (estimate of EPV = 0.05, p = 0.002) and for ages 1-4 years (estimate of EPV = 0.03, p = 0.015). Soft-tissue sarcoma (estimate of EPV = 0.03, p = 0.04) and Wilms tumours (estimate of EPV = 0.04, p = 0.007) also showed significant clustering. Clustering tended to persist across different time periods for cases of ALL (estimate of between-time period EPV = 0.04, p =0.003). In conclusion, we observed low level spatial clustering that is attributable to a limited number of cases. This suggests that environmental factors, which in some locations display localized clustering, may be important aetiological agents in these diseases. For ALL and soft tissue sarcoma, but not Wilms tumour, common infectious agents may be likely candidates.

Optimizing the maximum reported cluster size in the spatial scan statistic for ordinal data.

Science.gov (United States)

Kim, Sehwi; Jung, Inkyung

2017-01-01

The spatial scan statistic is an important tool for spatial cluster detection. There have been numerous studies on scanning window shapes. However, little research has been done on the maximum scanning window size or maximum reported cluster size. Recently, Han et al. proposed to use the Gini coefficient to optimize the maximum reported cluster size. However, the method has been developed and evaluated only for the Poisson model. We adopt the Gini coefficient to be applicable to the spatial scan statistic for ordinal data to determine the optimal maximum reported cluster size. Through a simulation study and application to a real data example, we evaluate the performance of the proposed approach. With some sophisticated modification, the Gini coefficient can be effectively employed for the ordinal model. The Gini coefficient most often picked the optimal maximum reported cluster sizes that were the same as or smaller than the true cluster sizes with very high accuracy. It seems that we can obtain a more refined collection of clusters by using the Gini coefficient. The Gini coefficient developed specifically for the ordinal model can be useful for optimizing the maximum reported cluster size for ordinal data and helpful for properly and informatively discovering cluster patterns.

Spatial and temporal clustering of dengue virus transmission in Thai villages.

Science.gov (United States)

Mammen, Mammen P; Pimgate, Chusak; Koenraadt, Constantianus J M; Rothman, Alan L; Aldstadt, Jared; Nisalak, Ananda; Jarman, Richard G; Jones, James W; Srikiatkhachorn, Anon; Ypil-Butac, Charity Ann; Getis, Arthur; Thammapalo, Suwich; Morrison, Amy C; Libraty, Daniel H; Green, Sharone; Scott, Thomas W

2008-11-04

Transmission of dengue viruses (DENV), the leading cause of arboviral disease worldwide, is known to vary through time and space, likely owing to a combination of factors related to the human host, virus, mosquito vector, and environment. An improved understanding of variation in transmission patterns is fundamental to conducting surveillance and implementing disease prevention strategies. To test the hypothesis that DENV transmission is spatially and temporally focal, we compared geographic and temporal characteristics within Thai villages where DENV are and are not being actively transmitted. Cluster investigations were conducted within 100 m of homes where febrile index children with (positive clusters) and without (negative clusters) acute dengue lived during two seasons of peak DENV transmission. Data on human infection and mosquito infection/density were examined to precisely (1) define the spatial and temporal dimensions of DENV transmission, (2) correlate these factors with variation in DENV transmission, and (3) determine the burden of inapparent and symptomatic infections. Among 556 village children enrolled as neighbors of 12 dengue-positive and 22 dengue-negative index cases, all 27 DENV infections (4.9% of enrollees) occurred in positive clusters (p availability of piped water in negative clusters (p < 0.01) and greater number of Ae. aegypti pupae per person in positive clusters (p = 0.04). During primarily DENV-4 transmission seasons, the ratio of inapparent to symptomatic infections was nearly 1:1 among child enrollees. Study limitations included inability to sample all children and mosquitoes within each cluster and our reliance on serologic rather than virologic evidence of interval infections in enrollees given restrictions on the frequency of blood collections in children. Our data reveal the remarkably focal nature of DENV transmission within a hyperendemic rural area of Thailand. These data suggest that active school-based dengue case detection

Shifting patterns of Aedes aegypti fine scale spatial clustering in Iquitos, Peru.

Science.gov (United States)

LaCon, Genevieve; Morrison, Amy C; Astete, Helvio; Stoddard, Steven T; Paz-Soldan, Valerie A; Elder, John P; Halsey, Eric S; Scott, Thomas W; Kitron, Uriel; Vazquez-Prokopec, Gonzalo M

2014-08-01

Empiric evidence shows that Aedes aegypti abundance is spatially heterogeneous and that some areas and larval habitats produce more mosquitoes than others. There is a knowledge gap, however, with regards to the temporal persistence of such Ae. aegypti abundance hotspots. In this study, we used a longitudinal entomologic dataset from the city of Iquitos, Peru, to (1) quantify the spatial clustering patterns of adult Ae. aegypti and pupae counts per house, (2) determine overlap between clusters, (3) quantify the temporal stability of clusters over nine entomologic surveys spaced four months apart, and (4) quantify the extent of clustering at the household and neighborhood levels. Data from 13,662 household entomological visits performed in two Iquitos neighborhoods differing in Ae. aegypti abundance and dengue virus transmission was analyzed using global and local spatial statistics. The location and extent of Ae. aegypti pupae and adult hotspots (i.e., small groups of houses with significantly [pentomologic surveys. The extent of clustering was used to quantify the probability of finding spatially correlated populations. Our analyses indicate that Ae. aegypti distribution was highly focal (most clusters do not extend beyond 30 meters) and that hotspots of high vector abundance were common on every survey date, but they were temporally unstable over the period of study. Our findings have implications for understanding Ae. aegypti distribution and for the design of surveillance and control activities relying on household-level data. In settings like Iquitos, where there is a relatively low percentage of Ae. aegypti in permanent water-holding containers, identifying and targeting key premises will be significantly challenged by shifting hotspots of Ae. aegypti infestation. Focusing efforts in large geographic areas with historically high levels of transmission may be more effective than targeting Ae. aegypti hotspots.

Shifting patterns of Aedes aegypti fine scale spatial clustering in Iquitos, Peru.

Directory of Open Access Journals (Sweden)

Genevieve LaCon

2014-08-01

Full Text Available Empiric evidence shows that Aedes aegypti abundance is spatially heterogeneous and that some areas and larval habitats produce more mosquitoes than others. There is a knowledge gap, however, with regards to the temporal persistence of such Ae. aegypti abundance hotspots. In this study, we used a longitudinal entomologic dataset from the city of Iquitos, Peru, to (1 quantify the spatial clustering patterns of adult Ae. aegypti and pupae counts per house, (2 determine overlap between clusters, (3 quantify the temporal stability of clusters over nine entomologic surveys spaced four months apart, and (4 quantify the extent of clustering at the household and neighborhood levels.Data from 13,662 household entomological visits performed in two Iquitos neighborhoods differing in Ae. aegypti abundance and dengue virus transmission was analyzed using global and local spatial statistics. The location and extent of Ae. aegypti pupae and adult hotspots (i.e., small groups of houses with significantly [p<0.05] high mosquito abundance were calculated for each of the 9 entomologic surveys. The extent of clustering was used to quantify the probability of finding spatially correlated populations. Our analyses indicate that Ae. aegypti distribution was highly focal (most clusters do not extend beyond 30 meters and that hotspots of high vector abundance were common on every survey date, but they were temporally unstable over the period of study.Our findings have implications for understanding Ae. aegypti distribution and for the design of surveillance and control activities relying on household-level data. In settings like Iquitos, where there is a relatively low percentage of Ae. aegypti in permanent water-holding containers, identifying and targeting key premises will be significantly challenged by shifting hotspots of Ae. aegypti infestation. Focusing efforts in large geographic areas with historically high levels of transmission may be more effective than

The correlation functions for the clustering of galaxies and Abell clusters

International Nuclear Information System (INIS)

Jones, B.J.T.; Jones, J.E.; Copenhagen Univ.

1985-01-01

The difference in amplitudes between the galaxy-galaxy correlation function and the correlation function between Abell clusters is a consequence of two facts. Firstly, most Abell clusters with z<0.08 lie in a relatively small volume of the sampled space, and secondly, the fraction of galaxies lying in Abell clusters differs considerably inside and outside of this volume. (The Abell clusters are confined to a smaller volume of space than are the galaxies.) We discuss the implications of this interpretation of the clustering correlation functions and present a simple model showing how such a situation may arise quite naturally in standard theories for galaxy formation. (orig.)

An Examination of Three Spatial Event Cluster Detection Methods

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Hensley H. Mariathas

2015-03-01

Full Text Available In spatial disease surveillance, geographic areas with large numbers of disease cases are to be identified, so that targeted investigations can be pursued. Geographic areas with high disease rates are called disease clusters and statistical cluster detection tests are used to identify geographic areas with higher disease rates than expected by chance alone. In some situations, disease-related events rather than individuals are of interest for geographical surveillance, and methods to detect clusters of disease-related events are called event cluster detection methods. In this paper, we examine three distributional assumptions for the events in cluster detection: compound Poisson, approximate normal and multiple hypergeometric (exact. The methods differ on the choice of distributional assumption for the potentially multiple correlated events per individual. The methods are illustrated on emergency department (ED presentations by children and youth (age < 18 years because of substance use in the province of Alberta, Canada, during 1 April 2007, to 31 March 2008. Simulation studies are conducted to investigate Type I error and the power of the clustering methods.

Stability-integrated Fuzzy C means segmentation for spatial ...

Indian Academy of Sciences (India)

V ROYNA DAISY

2018-03-16

Mar 16, 2018 ... clusters and including spatial information to basic Fuzzy C Means clustering are done in .... modify the objective function with Kernel distance function .... spatial information, thus making it sensitive to noise and outliers.

A Self-Organizing Spatial Clustering Approach to Support Large-Scale Network RTK Systems.

Science.gov (United States)

Shen, Lili; Guo, Jiming; Wang, Lei

2018-06-06

The network real-time kinematic (RTK) technique can provide centimeter-level real time positioning solutions and play a key role in geo-spatial infrastructure. With ever-increasing popularity, network RTK systems will face issues in the support of large numbers of concurrent users. In the past, high-precision positioning services were oriented towards professionals and only supported a few concurrent users. Currently, precise positioning provides a spatial foundation for artificial intelligence (AI), and countless smart devices (autonomous cars, unmanned aerial-vehicles (UAVs), robotic equipment, etc.) require precise positioning services. Therefore, the development of approaches to support large-scale network RTK systems is urgent. In this study, we proposed a self-organizing spatial clustering (SOSC) approach which automatically clusters online users to reduce the computational load on the network RTK system server side. The experimental results indicate that both the SOSC algorithm and the grid algorithm can reduce the computational load efficiently, while the SOSC algorithm gives a more elastic and adaptive clustering solution with different datasets. The SOSC algorithm determines the cluster number and the mean distance to cluster center (MDTCC) according to the data set, while the grid approaches are all predefined. The side-effects of clustering algorithms on the user side are analyzed with real global navigation satellite system (GNSS) data sets. The experimental results indicate that 10 km can be safely used as the cluster radius threshold for the SOSC algorithm without significantly reducing the positioning precision and reliability on the user side.

Spatial and temporal clustering of dengue virus transmission in Thai villages.

Directory of Open Access Journals (Sweden)

Mammen P Mammen

2008-11-01

Full Text Available Transmission of dengue viruses (DENV, the leading cause of arboviral disease worldwide, is known to vary through time and space, likely owing to a combination of factors related to the human host, virus, mosquito vector, and environment. An improved understanding of variation in transmission patterns is fundamental to conducting surveillance and implementing disease prevention strategies. To test the hypothesis that DENV transmission is spatially and temporally focal, we compared geographic and temporal characteristics within Thai villages where DENV are and are not being actively transmitted.Cluster investigations were conducted within 100 m of homes where febrile index children with (positive clusters and without (negative clusters acute dengue lived during two seasons of peak DENV transmission. Data on human infection and mosquito infection/density were examined to precisely (1 define the spatial and temporal dimensions of DENV transmission, (2 correlate these factors with variation in DENV transmission, and (3 determine the burden of inapparent and symptomatic infections. Among 556 village children enrolled as neighbors of 12 dengue-positive and 22 dengue-negative index cases, all 27 DENV infections (4.9% of enrollees occurred in positive clusters (p < 0.01; attributable risk [AR] = 10.4 per 100; 95% confidence interval 1-19.8 per 100]. In positive clusters, 12.4% of enrollees became infected in a 15-d period and DENV infections were aggregated centrally near homes of index cases. As only 1 of 217 pairs of serologic specimens tested in positive clusters revealed a recent DENV infection that occurred prior to cluster initiation, we attribute the observed DENV transmission subsequent to cluster investigation to recent DENV transmission activity. Of the 1,022 female adult Ae. aegypti collected, all eight (0.8% dengue-infected mosquitoes came from houses in positive clusters; none from control clusters or schools. Distinguishing features between

The next generation Virgo cluster survey. VIII. The spatial distribution of globular clusters in the Virgo cluster

Energy Technology Data Exchange (ETDEWEB)

Durrell, Patrick R.; Accetta, Katharine [Department of Physics and Astronomy, Youngstown State University, Youngstown, OH 44555 (United States); Côté, Patrick; Blakeslee, John P.; Ferrarese, Laura; McConnachie, Alan; Gwyn, Stephen [Herzberg Astronomy and Astrophysics, National Research Council, 5071 West Saanich Road, Victoria, BC V9E 2E7 (Canada); Peng, Eric W.; Zhang, Hongxin [Department of Astronomy, Peking University, Beijing 100871 (China); Mihos, J. Christopher [Department of Astronomy, Case Western Reserve University, Cleveland, OH 44106 (United States); Puzia, Thomas H.; Jordán, Andrés [Institute of Astrophysics, Pontificia Universidad Catolica, Av. Vicu' a Mackenna 4860, Macul 7820436, Santiago (Chile); Lançon, Ariane [Observatoire astronomique de Strasbourg, Université de Strasbourg, CNRS, UMR 7550, 11 rue de l' Université, F-67000 Strasbourg (France); Liu, Chengze [Center for Astronomy and Astrophysics, Department of Physics and Astronomy, Shanghai Jiao Tong University, 800 Dongchuan Road, Shanghai 200240 (China); Cuillandre, Jean-Charles [Canada-France-Hawaii Telescope Corporation, Kamuela, HI 96743 (United States); Boissier, Samuel; Boselli, Alessandro [Aix Marseille Université, CNRS, LAM (Laboratoire d' Astrophysique de Marseille) UMR 7326, F-13388 Marseille (France); Courteau, Stéphane [Department of Physics, Engineering Physics and Astronomy, Queen' s University, Kingston, ON K7L 3N6 (Canada); Duc, Pierre-Alain [AIM Paris Saclay, CNRS/INSU, CEA/Irfu, Université Paris Diderot, Orme des Merisiers, F-91191 Gif sur Yvette cedex (France); Emsellem, Eric [Université de Lyon 1, CRAL, Observatoire de Lyon, 9 av. Charles André, F-69230 Saint-Genis Laval (France); CNRS, UMR 5574, ENS de Lyon (France); and others

2014-10-20

We report on a large-scale study of the distribution of globular clusters (GCs) throughout the Virgo cluster, based on photometry from the Next Generation Virgo Cluster Survey (NGVS), a large imaging survey covering Virgo's primary subclusters (Virgo A = M87 and Virgo B = M49) out to their virial radii. Using the g{sub o}{sup ′}, (g' – i') {sub o} color-magnitude diagram of unresolved and marginally resolved sources within the NGVS, we have constructed two-dimensional maps of the (irregular) GC distribution over 100 deg{sup 2} to a depth of g{sub o}{sup ′} = 24. We present the clearest evidence to date showing the difference in concentration between red and blue GCs over the full extent of the cluster, where the red (more metal-rich) GCs are largely located around the massive early-type galaxies in Virgo, while the blue (metal-poor) GCs have a much more extended spatial distribution with significant populations still present beyond 83' (∼215 kpc) along the major axes of both M49 and M87. A comparison of our GC maps to the diffuse light in the outermost regions of M49 and M87 show remarkable agreement in the shape, ellipticity, and boxiness of both luminous systems. We also find evidence for spatial enhancements of GCs surrounding M87 that may be indicative of recent interactions or an ongoing merger history. We compare the GC map to that of the locations of Virgo galaxies and the X-ray intracluster gas, and find generally good agreement between these various baryonic structures. We calculate the Virgo cluster contains a total population of N {sub GC} = 67, 300 ± 14, 400, of which 35% are located in M87 and M49 alone. For the first time, we compute a cluster-wide specific frequency S {sub N,} {sub CL} = 2.8 ± 0.7, after correcting for Virgo's diffuse light. We also find a GC-to-baryonic mass fraction ε {sub b} = 5.7 ± 1.1 × 10{sup –4} and a GC-to-total cluster mass formation efficiency ε {sub t} = 2.9 ± 0.5 × 10{sup –5

A spatial hazard model for cluster detection on continuous indicators of disease: application to somatic cell score.

Science.gov (United States)

Gay, Emilie; Senoussi, Rachid; Barnouin, Jacques

2007-01-01

Methods for spatial cluster detection dealing with diseases quantified by continuous variables are few, whereas several diseases are better approached by continuous indicators. For example, subclinical mastitis of the dairy cow is evaluated using a continuous marker of udder inflammation, the somatic cell score (SCS). Consequently, this study proposed to analyze spatialized risk and cluster components of herd SCS through a new method based on a spatial hazard model. The dataset included annual SCS for 34 142 French dairy herds for the year 2000, and important SCS risk factors: mean parity, percentage of winter and spring calvings, and herd size. The model allowed the simultaneous estimation of the effects of known risk factors and of potential spatial clusters on SCS, and the mapping of the estimated clusters and their range. Mean parity and winter and spring calvings were significantly associated with subclinical mastitis risk. The model with the presence of 3 clusters was highly significant, and the 3 clusters were attractive, i.e. closeness to cluster center increased the occurrence of high SCS. The three localizations were the following: close to the city of Troyes in the northeast of France; around the city of Limoges in the center-west; and in the southwest close to the city of Tarbes. The semi-parametric method based on spatial hazard modeling applies to continuous variables, and takes account of both risk factors and potential heterogeneity of the background population. This tool allows a quantitative detection but assumes a spatially specified form for clusters.

A Self-Organizing Spatial Clustering Approach to Support Large-Scale Network RTK Systems

Directory of Open Access Journals (Sweden)

Lili Shen

2018-06-01

Full Text Available The network real-time kinematic (RTK technique can provide centimeter-level real time positioning solutions and play a key role in geo-spatial infrastructure. With ever-increasing popularity, network RTK systems will face issues in the support of large numbers of concurrent users. In the past, high-precision positioning services were oriented towards professionals and only supported a few concurrent users. Currently, precise positioning provides a spatial foundation for artificial intelligence (AI, and countless smart devices (autonomous cars, unmanned aerial-vehicles (UAVs, robotic equipment, etc. require precise positioning services. Therefore, the development of approaches to support large-scale network RTK systems is urgent. In this study, we proposed a self-organizing spatial clustering (SOSC approach which automatically clusters online users to reduce the computational load on the network RTK system server side. The experimental results indicate that both the SOSC algorithm and the grid algorithm can reduce the computational load efficiently, while the SOSC algorithm gives a more elastic and adaptive clustering solution with different datasets. The SOSC algorithm determines the cluster number and the mean distance to cluster center (MDTCC according to the data set, while the grid approaches are all predefined. The side-effects of clustering algorithms on the user side are analyzed with real global navigation satellite system (GNSS data sets. The experimental results indicate that 10 km can be safely used as the cluster radius threshold for the SOSC algorithm without significantly reducing the positioning precision and reliability on the user side.

Evolution of the stellar mass function in multiple-population globular clusters

Science.gov (United States)

Vesperini, Enrico; Hong, Jongsuk; Webb, Jeremy J.; D'Antona, Franca; D'Ercole, Annibale

2018-05-01

We present the results of a survey of N-body simulations aimed at studying the effects of the long-term dynamical evolution on the stellar mass function (MF) of multiple stellar populations in globular clusters. Our simulations show that if first-(1G) and second-generation (2G) stars have the same initial MF (IMF), the global MFs of the two populations are affected similarly by dynamical evolution and no significant differences between the 1G and 2G MFs arise during the cluster's evolution. If the two populations have different IMFs, dynamical effects do not completely erase memory of the initial differences. Should observations find differences between the global 1G and 2G MFs, these would reveal the fingerprints of differences in their IMFs. Irrespective of whether the 1G and 2G populations have the same global IMF or not, dynamical effects can produce differences between the local (measured at various distances from the cluster centre) 1G and 2G MFs; these differences are a manifestation of the process of mass segregation in populations with different initial structural properties. In dynamically old and spatially mixed clusters, however, differences between the local 1G and 2G MFs can reveal differences between the 1G and 2G global MFs. In general, for clusters with any dynamical age, large differences between the local 1G and 2G MFs are more likely to be associated with differences in the global MF. Our study also reveals a dependence of the spatial mixing rate on the stellar mass, another dynamical consequence of the multiscale nature of multiple-population clusters.

Clustering aspects in nuclear structure functions

International Nuclear Information System (INIS)

Hirai, M.; Saito, K.; Watanabe, T.; Kumano, S.

2011-01-01

For understanding an anomalous nuclear effect experimentally observed for the beryllium-9 nucleus at the Thomas Jefferson National Accelerator Facility, clustering aspects are studied in structure functions of deep inelastic lepton-nucleus scattering by using momentum distributions calculated in antisymmetrized (or fermionic) molecular dynamics (AMD) and also in a simple shell model for comparison. According to AMD, the 9 Be nucleus consists of two α-like clusters with a surrounding neutron. The clustering produces high-momentum components in nuclear wave functions, which affects nuclear modifications of the structure functions. We investigated whether clustering features could appear in the structure function F 2 of 9 Be along with studies for other light nuclei. We found that nuclear modifications of F 2 are similar in both AMD and shell models within our simple convolution description although there are slight differences in 9 Be. It indicates that the anomalous 9 Be result should be explained by a different mechanism from the nuclear binding and Fermi motion. If nuclear-modification slopes d(F 2 A /F 2 D )/dx are shown by the maximum local densities, the 9 Be anomaly can be explained by the AMD picture, namely by the clustering structure, whereas it certainly cannot be described in the simple shell model. This fact suggests that the large nuclear modification in 9 Be should be explained by large densities in the clusters. For example, internal nucleon structure could be modified in the high-density clusters. The clustering aspect of nuclear structure functions is an unexplored topic which is interesting for future investigations.

Spatial and kinematic distributions of transition populations in intermediate redshift galaxy clusters

International Nuclear Information System (INIS)

Crawford, Steven M.; Wirth, Gregory D.; Bershady, Matthew A.

2014-01-01

We analyze the spatial and velocity distributions of confirmed members in five massive clusters of galaxies at intermediate redshift (0.5 < z < 0.9) to investigate the physical processes driving galaxy evolution. Based on spectral classifications derived from broad- and narrow-band photometry, we define four distinct galaxy populations representing different evolutionary stages: red sequence (RS) galaxies, blue cloud (BC) galaxies, green valley (GV) galaxies, and luminous compact blue galaxies (LCBGs). For each galaxy class, we derive the projected spatial and velocity distribution and characterize the degree of subclustering. We find that RS, BC, and GV galaxies in these clusters have similar velocity distributions, but that BC and GV galaxies tend to avoid the core of the two z ≈ 0.55 clusters. GV galaxies exhibit subclustering properties similar to RS galaxies, but their radial velocity distribution is significantly platykurtic compared to the RS galaxies. The absence of GV galaxies in the cluster cores may explain their somewhat prolonged star-formation history. The LCBGs appear to have recently fallen into the cluster based on their larger velocity dispersion, absence from the cores of the clusters, and different radial velocity distribution than the RS galaxies. Both LCBG and BC galaxies show a high degree of subclustering on the smallest scales, leading us to conclude that star formation is likely triggered by galaxy-galaxy interactions during infall into the cluster.

Decreasing child mortality, spatial clustering and decreasing disparity in North-Western Burkina Faso.

Science.gov (United States)

Becher, Heiko; Müller, Olaf; Dambach, Peter; Gabrysch, Sabine; Niamba, Louis; Sankoh, Osman; Simboro, Seraphin; Schoeps, Anja; Stieglbauer, Gabriele; Yé, Yazoume; Sié, Ali

2016-04-01

Within relatively small areas, there exist high spatial variations of mortality between villages. In rural Burkina Faso, with data from 1993 to 1998, clusters of particularly high child mortality were identified in the population of the Nouna Health and Demographic Surveillance System (HDSS), a member of the INDEPTH Network. In this paper, we report child mortality with respect to temporal trends, spatial clustering and disparity in this HDSS from 1993 to 2012. Poisson regression was used to describe village-specific child mortality rates and time trends in mortality. The spatial scan statistic was used to identify villages or village clusters with higher child mortality. Clustering of mortality in the area is still present, but not as strong as before. The disparity of child mortality between villages has decreased. The decrease occurred in the context of an overall halving of child mortality in the rural area of Nouna HDSS between 1993 and 2012. Extrapolated to the Millennium Development Goals target period 1990-2015, this yields an estimated reduction of 54%, which is not too far off the aim of a two-thirds reduction. © 2016 John Wiley & Sons Ltd.

Identifying spatial clustering properties of the 1997-2003 Liguria (Northern Italy) forest-fire sequence

International Nuclear Information System (INIS)

Telesca, Luciano; Amatulli, Giuseppe; Lasaponara, Rosa; Lovallo, Michele; Santulli, Adriano

2007-01-01

The spatial clustering of the forest-fire sequence (1997-2003) of Liguria Region (Northern Italy) has been analysed using the correlation dimension D C , calculated by means of the correlation integral method. Studying the variations of this parameter, we recognize the presence of a strong variability of the spatial clusterization, modulated by seasonal cycles. Furthermore, we found that the larger fires (size >400 ha) mark the cyclic behaviour of the correlation dimension

Clustering Vehicle Temporal and Spatial Travel Behavior Using License Plate Recognition Data

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Huiyu Chen

2017-01-01

Full Text Available Understanding travel patterns of vehicle can support the planning and design of better services. In addition, vehicle clustering can improve management efficiency through more targeted access to groups of interest and facilitate planning by more specific survey design. This paper clustered 854,712 vehicles in a week using K-means clustering algorithm based on license plate recognition (LPR data obtained in Shenzhen, China. Firstly, several travel characteristics related to temporal and spatial variability and activity patterns are used to identify homogeneous clusters. Then, Davies-Bouldin index (DBI and Silhouette Coefficient (SC are applied to capture the optimal number of groups and, consequently, six groups are classified in weekdays and three groups are sorted in weekends, including commuting vehicles and some other occasional leisure travel vehicles. Moreover, a detailed analysis of the characteristics of each group in terms of spatial travel patterns and temporal changes are presented. This study highlights the possibility of applying LPR data for discovering the underlying factor in vehicle travel patterns and examining the characteristic of some groups specifically.

A Comparative Study of Spatially Clustered Distribution of Jumbo Flying Squid (Dosidicus gigas) Offshore Peru

Institute of Scientific and Technical Information of China (English)

FENG Yongjiu; CUI Li; CHEN Xinjun; LIU Yu

2017-01-01

We examined spatially clustered distribution of jumbo flying squid (Dosidicus gigas) in the offshore waters of Peru bounded by 78°-86°W and 8°-20°S under 0.5°×0.5° fishing grid.The study is based on the catch-per-unit-effort (CPUE) and fishing effort from Chinese mainland squid jigging fleet in 2003-2004 and 2006-2013.The data for all years as well as the eight years (excluding E1 Ni(n)o events) were studied to examine the effect of climate variation on the spatial distribution of D.gigas.Five spatial clusters reflecting the spatial distribution were computed using K-means and Getis-Ord Gi* for a detailed comparative study.Our results showed that clusters identified by the two methods were quite different in terms of their spatial patterns,and K-means was not as accurate as Getis-Ord Gi*,as inferred from the agreement degree and receiver operating characteristic.There were more areas of hot and cold spots in years without the impact of El Ni(n)o,suggesting that such large-scale climate variations could reduce the clustering level ofD.gigas.The catches also showed that warm E1 Ni(n)o conditions and high water temperature were less favorable for D.gigas offshore Peru.The results suggested that the use of K-means is preferable if the aim is to discover the spatial distribution of each sub-region (cluster) of the study area,while Getis-Ord Gi* is preferable if the aim is to identify statistically significant hot spots that may indicate the central fishing ground.

A comparative study of spatially clustered distribution of jumbo flying squid ( Dosidicus gigas) offshore Peru

Science.gov (United States)

Feng, Yongjiu; Cui, Li; Chen, Xinjun; Liu, Yu

2017-06-01

We examined spatially clustered distribution of jumbo flying squid ( Dosidicus gigas) in the offshore waters of Peru bounded by 78°-86°W and 8°-20°S under 0.5°×0.5° fishing grid. The study is based on the catch-per-unit-effort (CPUE) and fishing effort from Chinese mainland squid jigging fleet in 2003-2004 and 2006-2013. The data for all years as well as the eight years (excluding El Niño events) were studied to examine the effect of climate variation on the spatial distribution of D. gigas. Five spatial clusters reflecting the spatial distribution were computed using K-means and Getis-Ord Gi* for a detailed comparative study. Our results showed that clusters identified by the two methods were quite different in terms of their spatial patterns, and K-means was not as accurate as Getis-Ord Gi*, as inferred from the agreement degree and receiver operating characteristic. There were more areas of hot and cold spots in years without the impact of El Niño, suggesting that such large-scale climate variations could reduce the clustering level of D. gigas. The catches also showed that warm El Niño conditions and high water temperature were less favorable for D. gigas offshore Peru. The results suggested that the use of K-means is preferable if the aim is to discover the spatial distribution of each sub-region (cluster) of the study area, while Getis-Ord Gi* is preferable if the aim is to identify statistically significant hot spots that may indicate the central fishing ground.

Sunlight Modulates Fruit Metabolic Profile and Shapes the Spatial Pattern of Compound Accumulation within the Grape Cluster.

Science.gov (United States)

Reshef, Noam; Walbaum, Natasha; Agam, Nurit; Fait, Aaron

2017-01-01

correlations between metabolites in both pulp and skin. This integrated study of micrometeorology and metabolomics provided insights into the grape-cluster pattern of accumulation of 70 primary and secondary metabolites as a function of spatial variations in SI. Studying compound-specific responses against an extended gradient of quantified conditions improved our knowledge regarding the modulation of berry metabolism by SI, with the aim of using sunlight regulation to accurately modulate fruit composition in warm and arid/semi-arid regions.

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

Science.gov (United States)

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

2018-06-01

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

MODEL EVALUATION OF THE SPATIAL DEVELOPMENT OF THE REGION THROUGH THE DEVELOPMENT OF REGIONAL ECONOMIC CLUSTERS

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Чингис Дашидалаевич Дашицыренов

2013-12-01

Full Text Available The article describes a model of evaluation of effectiveness of spatial development of a region. Main approaches and criteria to assess effectiveness of socio-economic development of a region based on use of regional economic cluster are identified.The author believes that clusterization allows to eliminate or localize mentioned above restrictions which are characteristic of specific activity of entities. Effect in this case can be measured by increase in productivity obtained from cluster’s resources use  in regard to specific form of enterprises’ existence.The article also focused on definition of idea of synergic effect and the model of effectiveness of clusters. Cluster integration’s essence is considered – it is pointed out that a new structure is formed, which has emergent characteristics.Thus, main approach to spatial socio-economic development of a region proposed by the author is diversification of organizational and economic forms into regional economic clusters.Proposed by the author model allows to assess effectiveness of clusterization for spatial socio-economic development of any region. DOI: http://dx.doi.org/10.12731/2218-7405-2013-10-14

Spatial clustering of amyotrophic lateral sclerosis in Finland at place of birth and place of death

DEFF Research Database (Denmark)

Sabel, Clive E.; Boyle, P. J.; Löytönen, M.

2003-01-01

location at the time of death as the basis for cluster detection, rather than exploring clusters at other points in the life cycle. In this study, the authors examine 1,000 cases of amyotrophic lateral sclerosis distributed throughout Finland who died between June 1985 and December 1995. Using a spatial......Previous evidence for spatial clustering of amyotrophic lateral sclerosis is inconclusive. Studies that have identified apparent clusters have often been based on a small number of cases, which means the results may have occurred by chance processes. Also, most studies have used the geographic...... stages of the cases' life cycle, different conclusions about where potential risk factors may exist might result....

A Socio-spatial Dimension of Local Creative Industry Development in Semarang and Kudus Batik Clusters

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Nugroho, P.

2018-02-01

Creative industries existence is inseparable from the underlying social construct which provides sources for creativity and innovation. The working of social capital in a society facilitates information exchange, knowledge transfer and technology acquisition within the industry through social networks. As a result, a socio-spatial divide exists in directing the growth of the creative industries. This paper aims to examine how such a socio-spatial divide contributes to the local creative industry development in Semarang and Kudus batik clusters. Explanatory sequential mixed methods approach covering a quantitative approach followed by a qualitative approach is chosen to understand better the interplay between tangible and intangible variables in the local batik clusters. Surveys on secondary data taken from the government statistics and reports, previous studies, and media exposures are completed in the former approach to identify clustering pattern of the local batik industry and the local embeddedness factors which have shaped the existing business environment. In-depth interviews, content analysis, and field observations are engaged in the latter approach to explore reciprocal relationships between the elements of social capital and the local batik cluster development. The result demonstrates that particular social ties have determined the forms of spatial proximity manifested in forward and backward business linkages. Trust, shared norms, and inherited traditions are the key social capital attributes that lead to such a socio-spatial divide. Therefore, the intermediating roles of the bridging actors are necessary to encouraging cooperation among the participating stakeholders for a better cluster development.

SPATIAL CLUSTER AND OUTLIER IDENTIFICATION OF GEOCHEMICAL ASSOCIATION OF ELEMENTS: A CASE STUDY IN JUIRUI COPPER MINING AREA

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Tien Thanh NGUYEN

2016-12-01

Full Text Available Spatial clusters and spatial outliers play an important role in the study of the spatial distribution patterns of geochemical data. They characterize the fundamental properties of mineralization processes, the spatial distribution of mineral deposits, and ore element concentrations in mineral districts. In this study, a new method for the study of spatial distribution patterns of multivariate data is proposed based on a combination of robust Mahalanobis distance and local Moran’s Ii. In order to construct the spatial matrix, the Moran's I spatial correlogram was first used to determine the range. The robust Mahalanobis distances were then computed for an association of elements. Finally, local Moran’s Ii statistics was used to measure the degree of spatial association and discover the spatial distribution patterns of associations of Cu, Au, Mo, Ag, Pb, Zn, As, and Sb elements including spatial clusters and spatial outliers. Spatial patterns were analyzed at six different spatial scales (2km, 4 km, 6 km, 8 km, 10 km and 12 km for both the raw data and Box-Cox transformed data. The results show that identified spatial cluster and spatial outlier areas using local Moran’s Ii and the robust Mahalanobis accord the objective reality and have a good conformity with known deposits in the study area.

Identification of alterations associated with age in the clustering structure of functional brain networks.

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Guzman, Grover E C; Sato, Joao R; Vidal, Maciel C; Fujita, Andre

2018-01-01

Initial studies using resting-state functional magnetic resonance imaging on the trajectories of the brain network from childhood to adulthood found evidence of functional integration and segregation over time. The comprehension of how healthy individuals' functional integration and segregation occur is crucial to enhance our understanding of possible deviations that may lead to brain disorders. Recent approaches have focused on the framework wherein the functional brain network is organized into spatially distributed modules that have been associated with specific cognitive functions. Here, we tested the hypothesis that the clustering structure of brain networks evolves during development. To address this hypothesis, we defined a measure of how well a brain region is clustered (network fitness index), and developed a method to evaluate its association with age. Then, we applied this method to a functional magnetic resonance imaging data set composed of 397 males under 31 years of age collected as part of the Autism Brain Imaging Data Exchange Consortium. As results, we identified two brain regions for which the clustering change over time, namely, the left middle temporal gyrus and the left putamen. Since the network fitness index is associated with both integration and segregation, our finding suggests that the identified brain region plays a role in the development of brain systems.

A spatial cluster analysis of tractor overturns in Kentucky from 1960 to 2002.

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Daniel M Saman

Full Text Available Agricultural tractor overturns without rollover protective structures are the leading cause of farm fatalities in the United States. To our knowledge, no studies have incorporated the spatial scan statistic in identifying high-risk areas for tractor overturns. The aim of this study was to determine whether tractor overturns cluster in certain parts of Kentucky and identify factors associated with tractor overturns.A spatial statistical analysis using Kulldorff's spatial scan statistic was performed to identify county clusters at greatest risk for tractor overturns. A regression analysis was then performed to identify factors associated with tractor overturns.The spatial analysis revealed a cluster of higher than expected tractor overturns in four counties in northern Kentucky (RR = 2.55 and 10 counties in eastern Kentucky (RR = 1.97. Higher rates of tractor overturns were associated with steeper average percent slope of pasture land by county (p = 0.0002 and a greater percent of total tractors with less than 40 horsepower by county (p<0.0001.This study reveals that geographic hotspots of tractor overturns exist in Kentucky and identifies factors associated with overturns. This study provides policymakers a guide to targeted county-level interventions (e.g., roll-over protective structures promotion interventions with the intention of reducing tractor overturns in the highest risk counties in Kentucky.

Spatially explicit population estimates for black bears based on cluster sampling

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Humm, J.; McCown, J. Walter; Scheick, B.K.; Clark, Joseph D.

2017-01-01

We estimated abundance and density of the 5 major black bear (Ursus americanus) subpopulations (i.e., Eglin, Apalachicola, Osceola, Ocala-St. Johns, Big Cypress) in Florida, USA with spatially explicit capture-mark-recapture (SCR) by extracting DNA from hair samples collected at barbed-wire hair sampling sites. We employed a clustered sampling configuration with sampling sites arranged in 3 × 3 clusters spaced 2 km apart within each cluster and cluster centers spaced 16 km apart (center to center). We surveyed all 5 subpopulations encompassing 38,960 km2 during 2014 and 2015. Several landscape variables, most associated with forest cover, helped refine density estimates for the 5 subpopulations we sampled. Detection probabilities were affected by site-specific behavioral responses coupled with individual capture heterogeneity associated with sex. Model-averaged bear population estimates ranged from 120 (95% CI = 59–276) bears or a mean 0.025 bears/km2 (95% CI = 0.011–0.44) for the Eglin subpopulation to 1,198 bears (95% CI = 949–1,537) or 0.127 bears/km2 (95% CI = 0.101–0.163) for the Ocala-St. Johns subpopulation. The total population estimate for our 5 study areas was 3,916 bears (95% CI = 2,914–5,451). The clustered sampling method coupled with information on land cover was efficient and allowed us to estimate abundance across extensive areas that would not have been possible otherwise. Clustered sampling combined with spatially explicit capture-recapture methods has the potential to provide rigorous population estimates for a wide array of species that are extensive and heterogeneous in their distribution.

Uncertainty of a detected spatial cluster in 1D: quantification and visualization

KAUST Repository

Lee, Junho; Gangnon, Ronald E.; Zhu, Jun; Liang, Jingjing

2017-01-01

Spatial cluster detection is an important problem in a variety of scientific disciplines such as environmental sciences, epidemiology and sociology. However, there appears to be very limited statistical methodology for quantifying the uncertainty of a detected cluster. In this paper, we develop a new method for the quantification and visualization of uncertainty associated with a detected cluster. Our approach is defining a confidence set for the true cluster and visualizing the confidence set, based on the maximum likelihood, in time or in one-dimensional space. We evaluate the pivotal property of the statistic used to construct the confidence set and the coverage rate for the true cluster via empirical distributions. For illustration, our methodology is applied to both simulated data and an Alaska boreal forest dataset. Copyright © 2017 John Wiley & Sons, Ltd.

Uncertainty of a detected spatial cluster in 1D: quantification and visualization

KAUST Repository

Lee, Junho

2017-10-19

Spatial cluster detection is an important problem in a variety of scientific disciplines such as environmental sciences, epidemiology and sociology. However, there appears to be very limited statistical methodology for quantifying the uncertainty of a detected cluster. In this paper, we develop a new method for the quantification and visualization of uncertainty associated with a detected cluster. Our approach is defining a confidence set for the true cluster and visualizing the confidence set, based on the maximum likelihood, in time or in one-dimensional space. We evaluate the pivotal property of the statistic used to construct the confidence set and the coverage rate for the true cluster via empirical distributions. For illustration, our methodology is applied to both simulated data and an Alaska boreal forest dataset. Copyright © 2017 John Wiley & Sons, Ltd.

The stellar and substellar mass function in central region of the old open cluster Praesepe from deep LBT observations

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Goldman B.

2011-07-01

Full Text Available Studies of the mass function of open clusters of different ages allow us to study the efficiency with which brown dwarfs are evaporated from clusters to populate the field. Surveys in relatively old clusters (age ≳100 Myr do not suffer from problems found in young clusters, such as intra-cluster extinction and large uncertainties in brown dwarf models. In this paper, we present the results of a photometric survey to study the mass function of the old open cluster Praesepe (age of ~590 Myr and distance of ~190 pc, down to the substellar regime. We have performed optical (riz and Y-band photometric survey of Praesepe with the Large Binocular Telescope Camera, for a spatial coverage of 0.61 deg2 from ~90 MJ down to a 5σ detection limit at 40 MJ.

Cluster Detection Tests in Spatial Epidemiology: A Global Indicator for Performance Assessment.

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Aline Guttmann

Full Text Available In cluster detection of disease, the use of local cluster detection tests (CDTs is current. These methods aim both at locating likely clusters and testing for their statistical significance. New or improved CDTs are regularly proposed to epidemiologists and must be subjected to performance assessment. Because location accuracy has to be considered, performance assessment goes beyond the raw estimation of type I or II errors. As no consensus exists for performance evaluations, heterogeneous methods are used, and therefore studies are rarely comparable. A global indicator of performance, which assesses both spatial accuracy and usual power, would facilitate the exploration of CDTs behaviour and help between-studies comparisons. The Tanimoto coefficient (TC is a well-known measure of similarity that can assess location accuracy but only for one detected cluster. In a simulation study, performance is measured for many tests. From the TC, we here propose two statistics, the averaged TC and the cumulated TC, as indicators able to provide a global overview of CDTs performance for both usual power and location accuracy. We evidence the properties of these two indicators and the superiority of the cumulated TC to assess performance. We tested these indicators to conduct a systematic spatial assessment displayed through performance maps.

Cluster Detection Tests in Spatial Epidemiology: A Global Indicator for Performance Assessment

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Guttmann, Aline; Li, Xinran; Feschet, Fabien; Gaudart, Jean; Demongeot, Jacques; Boire, Jean-Yves; Ouchchane, Lemlih

2015-01-01

In cluster detection of disease, the use of local cluster detection tests (CDTs) is current. These methods aim both at locating likely clusters and testing for their statistical significance. New or improved CDTs are regularly proposed to epidemiologists and must be subjected to performance assessment. Because location accuracy has to be considered, performance assessment goes beyond the raw estimation of type I or II errors. As no consensus exists for performance evaluations, heterogeneous methods are used, and therefore studies are rarely comparable. A global indicator of performance, which assesses both spatial accuracy and usual power, would facilitate the exploration of CDTs behaviour and help between-studies comparisons. The Tanimoto coefficient (TC) is a well-known measure of similarity that can assess location accuracy but only for one detected cluster. In a simulation study, performance is measured for many tests. From the TC, we here propose two statistics, the averaged TC and the cumulated TC, as indicators able to provide a global overview of CDTs performance for both usual power and location accuracy. We evidence the properties of these two indicators and the superiority of the cumulated TC to assess performance. We tested these indicators to conduct a systematic spatial assessment displayed through performance maps. PMID:26086911

New method for reconstruction of star spatial distribution in globular clusters and its application to flare stars in Pleiades

International Nuclear Information System (INIS)

Kosarev, E.L.

1980-01-01

A new method to reconstruct spatial star distribution in globular clusters is presented. The method gives both the estimation of unknown spatial distribution and the probable reconstruction error. This error has statistical origin and depends only on the number of stars in a cluster. The method is applied to reconstruct the spatial density of 441 flare stars in Pleiades. The spatial density has a maximum in the centre of the cluster of about 1.6-2.5 pc -3 and with increasing distance from the center smoothly falls down to zero approximately with the Gaussian law with a scale parameter of 3.5 pc

Functional Clustering of the Human Inferior Parietal Lobule by Whole-Brain Connectivity Mapping of Resting-State Functional Magnetic Resonance Imaging Signals

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Li, Chiang-Shan R.

2014-01-01

Abstract The human inferior parietal lobule (IPL) comprised the lateral bank of the intraparietal sulcus, angular gyrus, and supramarginal gyrus, defined on the basis of anatomical landmarks and cytoarchitectural organization of neurons. However, it is not clear as to whether the three areas represent functional subregions within the IPL. For instance, imaging studies frequently identified clusters of activities that cut across areal boundaries. Here, we used resting-state functional magnetic resonance imaging (fMRI) data to examine how individual voxels within the IPL are best clustered according to their connectivity to the whole brain. The results identified a best estimate of seven clusters that are hierarchically arranged as the anterior, middle, and posterior subregions. The anterior, middle, and posterior IPL are each significantly connected to the somatomotor areas, superior/middle/inferior frontal gyri, and regions of the default mode network. This functional segregation is supported by recent cytoarchitechtonics and tractography studies. IPL showed hemispheric differences in connectivity that accord with a predominantly left parietal role in tool use and language processing and a right parietal role in spatial attention and mathematical cognition. The functional clusters may also provide a more parsimonious and perhaps even accurate account of regional activations of the IPL during a variety of cognitive challenges, as reported in earlier fMRI studies. PMID:24308753

Spatially Compact Neural Clusters in the Dorsal Striatum Encode Locomotion Relevant Information.

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Barbera, Giovanni; Liang, Bo; Zhang, Lifeng; Gerfen, Charles R; Culurciello, Eugenio; Chen, Rong; Li, Yun; Lin, Da-Ting

2016-10-05

An influential striatal model postulates that neural activities in the striatal direct and indirect pathways promote and inhibit movement, respectively. Normal behavior requires coordinated activity in the direct pathway to facilitate intended locomotion and indirect pathway to inhibit unwanted locomotion. In this striatal model, neuronal population activity is assumed to encode locomotion relevant information. Here, we propose a novel encoding mechanism for the dorsal striatum. We identified spatially compact neural clusters in both the direct and indirect pathways. Detailed characterization revealed similar cluster organization between the direct and indirect pathways, and cluster activities from both pathways were correlated with mouse locomotion velocities. Using machine-learning algorithms, cluster activities could be used to decode locomotion relevant behavioral states and locomotion velocity. We propose that neural clusters in the dorsal striatum encode locomotion relevant information and that coordinated activities of direct and indirect pathway neural clusters are required for normal striatal controlled behavior. VIDEO ABSTRACT. Published by Elsevier Inc.

Exploring the Structure of Spatial Representations

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Madl, Tamas; Franklin, Stan; Chen, Ke; Trappl, Robert; Montaldi, Daniela

2016-01-01

It has been suggested that the map-like representations that support human spatial memory are fragmented into sub-maps with local reference frames, rather than being unitary and global. However, the principles underlying the structure of these ‘cognitive maps’ are not well understood. We propose that the structure of the representations of navigation space arises from clustering within individual psychological spaces, i.e. from a process that groups together objects that are close in these spaces. Building on the ideas of representational geometry and similarity-based representations in cognitive science, we formulate methods for learning dissimilarity functions (metrics) characterizing participants’ psychological spaces. We show that these learned metrics, together with a probabilistic model of clustering based on the Bayesian cognition paradigm, allow prediction of participants’ cognitive map structures in advance. Apart from insights into spatial representation learning in human cognition, these methods could facilitate novel computational tools capable of using human-like spatial concepts. We also compare several features influencing spatial memory structure, including spatial distance, visual similarity and functional similarity, and report strong correlations between these dimensions and the grouping probability in participants’ spatial representations, providing further support for clustering in spatial memory. PMID:27347681

Spatial clustering of knowledge-based industries in the Helsinki Metropolitan Area

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Juan Eduardo Chica

2016-01-01

Full Text Available The central locations of metropolitan areas have some specific attributes, leading to an accumulation of large knowledge exchanges and extensive knowledge externalities, which encourage the concentration of various economic activities, especially knowledge-based industries (KBI. Other agglomeration economies found in metropolitan areas – such as telecommunications and transport infrastructures connected to global productive circuits and complementary labour markets – are key factors for KBI employment growth. This paper explores the Helsinki Metropolitan Area’s (HMA spatial clustering of KBI at the sub-district level, and the role played by agglomeration economies (both specialization and diversity economies in fostering this process. The results reveal that KBI employment shows patterns of concentration in the core and adjacent areas. The specialization and diversity economies found in the metropolitan core and the specialization economies found in others areas lead to KBI spatial clustering in the HMA. Public policies regarding the promotion of science parks have also played a decisive role.

Cluster-cluster correlations in the two-dimensional stationary Ising-model

International Nuclear Information System (INIS)

Klassmann, A.

1997-01-01

In numerical integration of the Cahn-Hillard equation, which describes Oswald rising in a two-phase matrix, N. Masbaum showed that spatial correlations between clusters scale with respect to the mean cluster size (itself a function of time). T. B. Liverpool showed by Monte Carlo simulations for the Ising model that the analogous correlations have a similar form. Both demonstrated that immediately around each cluster there is some depletion area followed by something like a ring of clusters of the same size as the original one. More precisely, it has been shown that the distribution of clusters around a given cluster looks like a sinus-curve decaying exponentially with respect to the distance to a constant value

Implications for gravitational lensing and the dark matter content in clusters of galaxies from spatially resolved x-ray spectra

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Loewenstein, M.

1994-01-01

A simple method for deriving well-behaved temperature solutions to the equation of hydrostatic equilibrium for intracluster media with X-ray imaging observations is presented and applied to a series of generalized models as well as to observations of the Perseus cluster and Abell 2256. In these applications the allowed range in the ratio of nonbaryons to baryons as a function of radius is derived, taking into account the uncertainties and crude spatial resolution of the X-ray spectra and considering a range of physically reasonable mass models with various scale heights. Particular attention is paid to the central regions of the cluster, and it is found that the dark matter can be sufficiently concentrated to be consistent with the high central mass surface densities for moderate-redshift clusters from their gravitational lensing properties.

Spatial Field Variability Mapping of Rice Crop using Clustering Technique from Space Borne Hyperspectral Data

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Moharana, S.; Dutta, S.

2015-12-01

Precision farming refers to field-specific management of an agricultural crop at a spatial scale with an aim to get the highest achievable yield and to achieve this spatial information on field variability is essential. The difficulty in mapping of spatial variability occurring within an agriculture field can be revealed by employing spectral techniques in hyperspectral imagery rather than multispectral imagery. However an advanced algorithm needs to be developed to fully make use of the rich information content in hyperspectral data. In the present study, potential of hyperspectral data acquired from space platform was examined to map the field variation of paddy crop and its species discrimination. This high dimensional data comprising 242 spectral narrow bands with 30m ground resolution Hyperion L1R product acquired for Assam, India (30th Sept and 3rd Oct, 2014) were allowed for necessary pre-processing steps followed by geometric correction using Hyperion L1GST product. Finally an atmospherically corrected and spatially deduced image consisting of 112 band was obtained. By employing an advanced clustering algorithm, 12 different clusters of spectral waveforms of the crop were generated from six paddy fields for each images. The findings showed that, some clusters were well discriminated representing specific rice genotypes and some clusters were mixed treating as a single rice genotype. As vegetation index (VI) is the best indicator of vegetation mapping, three ratio based VI maps were also generated and unsupervised classification was performed for it. The so obtained 12 clusters of paddy crop were mapped spatially to the derived VI maps. From these findings, the existence of heterogeneity was clearly captured in one of the 6 rice plots (rice plot no. 1) while heterogeneity was observed in rest of the 5 rice plots. The degree of heterogeneous was found more in rice plot no.6 as compared to other plots. Subsequently, spatial variability of paddy field was

Filling- and interaction-driven Mott transition. Quantum cluster calculations within self-energy-functional theory

International Nuclear Information System (INIS)

Balzer, Matthias

2008-01-01

The central goal of this thesis is the examination of strongly correlated electron systems on the basis of the two-dimensional Hubbard model. We analyze how the properties of the Mott insulator change upon doping and with interaction strength. The numerical evaluation is done using quantum cluster approximations, which allow for a thermodynamically consistent description of the ground state properties. The framework of self-energy-functional theory offers great flexibility for the construction of cluster approximations. A detailed analysis sheds light on the quality and the convergence properties of different cluster approximations within the self-energy-functional theory. We use the one-dimensional Hubbard model for these examinations and compare our results with the exact solution. In two dimensions the ground state of the particle-hole symmetric model at half-filling is an antiferromagnetic insulator, independent of the interaction strength. The inclusion of short-range spatial correlations by our cluster approach leads to a considerable improvement of the antiferromagnetic order parameter as compared to dynamical mean-field theory. In the paramagnetic phase we furthermore observe a metal-insulator transition as a function of the interaction strength, which qualitatively differs from the pure mean-field scenario. Starting from the antiferromagnetic Mott insulator a filling-controlled metal-insulator transition in a paramagnetic metallic phase can be observed. Depending on the cluster approximation used an antiferromagnetic metallic phase may occur at first. In addition to long-range antiferromagnetic order, we also considered superconductivity in our calculations. The superconducting order parameter as a function of doping is in good agreement with other numerical methods, as well as with experimental results. (orig.)

Mass functions for eight galactic clusters in the solar neighborhood

International Nuclear Information System (INIS)

Francic, S.P.

1989-01-01

Mass functions for eight galactic clusters in the solar neighborhood have been obtained. The mass functions have been determined from proper motion membership probabilities and unlike similar investigations, corrected for outlying cluster stars. The membership probabilities have been determined from the joint proper motion and surface density distributions for the field and clusters stars. They have also been corrected for any magnitude dependences. Comparison of the mass functions with the Salpeter IMF shows that the older clusters tend to be deficient in the number of low mass stars, while the younger clusters tend to have more. Analysis of the relaxation times shows that the deficiency of faint stars in the older clusters is likely due to their evaporation from the cluster. The combined mass function for six of the cluster results in a power law with a power law index of -1.97 ± 0.17 for 1.1 < M/Mass of sun < 2.5. This agrees with a recent determination of the field star IMF where the power law index is -2.00 ± 0.18 for 0.8 < M/Mass of sun < 18. If the older clusters are not considered, then comparison of the combined mass function with the individual cluster mass functions shows that the universality hypothesis cannot be denied

Analyzing the Effects of Spatial Interaction among City Clusters on Urban Growth—Case of Wuhan Urban Agglomeration

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Ronghui Tan

2016-08-01

Full Text Available For the past two decades, China’s urbanization has attracted increasing attention from scholars around the world. Numerous insightful studies have attempted to determine the socioeconomic causes of the rapid urban growth in Chinese cities. However, most of these studies regarded each city as a single entity, with few considering inter-city relationships. The present study uses a gravity-based model to measure the spatial interaction among city clusters in the Wuhan urban agglomeration (WUA, which is one of China’s most rapidly urbanizing regions. The effects of spatial interaction on urban growth area were also analyzed. Empirical results indicate that, similar to urban population or employment in secondary and tertiary industries in the WUA from 2000 to 2005, the spatial interaction among city clusters is one of the main drivers of urban growth. In fact, this study finds the effects of spatial interaction as the only socioeconomic factor that affected the spatial expansion from 2005 to 2010. This finding suggests that population migration and information and commodity flows showed greater influence than the socioeconomic drivers of each city did on promoting urbanization in the WUA during this period. We thus argue that spatial interaction among city clusters should be a consideration in future regional planning.

Spatial abundance and clustering of Culicoides (Diptera: Ceratopogonidae) on a local scale

DEFF Research Database (Denmark)

Kirkeby, Carsten; Bødker, Rene; Stockmarr, Anders

2013-01-01

, and cluster locations shifted between catch nights. No significant temporal autocorrelation was detected. CAR models for both species groups identified a significant positive impact of humidity and significant negative impacts of precipitation and wind turbulence. Temperature was also found to be significant...... abundance pattern of these two species groups in the field by intensive sampling with a grid of light traps on 16 catch nights. Neighboring trap catches can be spatially dependent on each other, hence we developed a conditional autoregressive (CAR) model framework to test a number of spatial and non...... of Culicoides moved around in a dynamic pattern varying between catch nights. This conforms with the modeling but was not explained by any of the tested covariates. The mean abundance within these clusters was up to 11 times higher for the Obsoletus group and 4 times higher for the Pulicaris group compared...

Persistent Spatial Clusters of Prescribed Antimicrobials among Danish Pig Farms - A Register-Based Study

DEFF Research Database (Denmark)

Fertner, Mette Ely; Sanchez, Javier; Boklund, Anette

2015-01-01

The emergence of pathogens resistant to antimicrobials has prompted political initiatives targeting a reduction in the use of veterinary antimicrobials in Denmark, especially for pigs. This study elucidates the tendency of pig farms with a significantly higher antimicrobial use to remain...... in clusters in certain geographical regions of Denmark. Animal Daily Doses/100 pigs/day were calculated for all three age groups of pigs (weaners, finishers and sows) for each quarter during 2012-13 in 6,143 commercial indoor pig producing farms. The data were split into four time periods of six months....... Repeated spatial cluster analyses were performed to identify persistent clusters, i.e. areas included in a significant cluster throughout all four time periods. Antimicrobials prescribed for weaners did not result in any persistent clusters. In contrast, antimicrobial use in finishers clustered...

Race, deprivation, and immigrant isolation: The spatial demography of air-toxic clusters in the continental United States.

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Liévanos, Raoul S

2015-11-01

This article contributes to environmental inequality outcomes research on the spatial and demographic factors associated with cumulative air-toxic health risks at multiple geographic scales across the United States. It employs a rigorous spatial cluster analysis of census tract-level 2005 estimated lifetime cancer risk (LCR) of ambient air-toxic emissions from stationary (e.g., facility) and mobile (e.g., vehicular) sources to locate spatial clusters of air-toxic LCR risk in the continental United States. It then tests intersectional environmental inequality hypotheses on the predictors of tract presence in air-toxic LCR clusters with tract-level principal component factor measures of economic deprivation by race and immigrant status. Logistic regression analyses show that net of controls, isolated Latino immigrant-economic deprivation is the strongest positive demographic predictor of tract presence in air-toxic LCR clusters, followed by black-economic deprivation and isolated Asian/Pacific Islander immigrant-economic deprivation. Findings suggest scholarly and practical implications for future research, advocacy, and policy. Copyright © 2015 Elsevier Inc. All rights reserved.

Spatial expression of Hox cluster genes in the ontogeny of a sea urchin

Science.gov (United States)

Arenas-Mena, C.; Cameron, A. R.; Davidson, E. H.

2000-01-01

The Hox cluster of the sea urchin Strongylocentrous purpuratus contains ten genes in a 500 kb span of the genome. Only two of these genes are expressed during embryogenesis, while all of eight genes tested are expressed during development of the adult body plan in the larval stage. We report the spatial expression during larval development of the five 'posterior' genes of the cluster: SpHox7, SpHox8, SpHox9/10, SpHox11/13a and SpHox11/13b. The five genes exhibit a dynamic, largely mesodermal program of expression. Only SpHox7 displays extensive expression within the pentameral rudiment itself. A spatially sequential and colinear arrangement of expression domains is found in the somatocoels, the paired posterior mesodermal structures that will become the adult perivisceral coeloms. No such sequential expression pattern is observed in endodermal, epidermal or neural tissues of either the larva or the presumptive juvenile sea urchin. The spatial expression patterns of the Hox genes illuminate the evolutionary process by which the pentameral echinoderm body plan emerged from a bilateral ancestor.

Attosecond extreme ultraviolet generation in cluster by using spatially inhomogeneous field

Energy Technology Data Exchange (ETDEWEB)

Feng, Liqiang, E-mail: lqfeng-lngy@126.com [College of Science, Liaoning University of Technology, Jinzhou, 121000 (China); State Key Laboratory of Molecular Reaction Dynamics, Dalian Institute of Chemical Physics Chinese Academy of Sciences, Dalian 116023 (China); Liu, Hang [School of Chemical and Environmental Engineering, Liaoning University of Technology, Jinzhou 121000 (China)

2015-01-15

A promising method to generate the attosecond extreme ultraviolet (XUV) sources has been theoretically investigated emerging from the two-dimensional Ar{sup +} cluster driven by the spatially inhomogeneous field. The results show that with the introduction of the Ar{sup +} cluster model, not only the harmonic cutoffs are enhanced, but also the harmonic yields are reinforced. Furthermore, by properly moderating the inhomogeneity as well as the laser parameters of the inhomogeneous field, the harmonic cutoff can be further extended. As a result, three almost linearly polarized XUV pulses with durations of 40 as, 42 as, and 45 as can be obtained.

New Constraints on Spatial Variations of the Fine Structure Constant from Clusters of Galaxies

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Ivan De Martino

2016-12-01

Full Text Available We have constrained the spatial variation of the fine structure constant using multi-frequency measurements of the thermal Sunyaev-Zeldovich effect of 618 X-ray selected clusters. Although our results are not competitive with the ones from quasar absorption lines, we improved by a factor 10 and ∼2.5 previous results from Cosmic Microwave Background power spectrum and from galaxy clusters, respectively.

Undergraduate ALFALFA Team: Analysis of Spatially-Resolved Star-Formation in Nearby Galaxy Groups and Clusters

Science.gov (United States)

Finn, Rose; Collova, Natasha; Spicer, Sandy; Whalen, Kelly; Koopmann, Rebecca A.; Durbala, Adriana; Haynes, Martha P.; Undergraduate ALFALFA Team

2017-01-01

As part of the Undergraduate ALFALFA Team, we are conducting a survey of the gas and star-formation properties of galaxies in 36 groups and clusters in the local universe. The galaxies in our sample span a large range of galactic environments, from the centers of galaxy groups and clusters to the surrounding infall regions. One goal of the project is to map the spatial distribution of star-formation; the relative extent of the star-forming and stellar disks provides important information about the internal and external processes that deplete gas and thus drive galaxy evolution. We obtained wide-field H-alpha observations with the WIYN 0.9m telescope at Kitt Peak National Observatory for galaxies in the vicinity of the MKW11 and NRGb004 galaxy groups and the Abell 1367 cluster. We present a preliminary analysis of the relative size of the star-forming and stellar disks as a function of galaxy morphology and local galaxy density, and we calculate gas depletion times using star-formation rates and HI gas mass. We will combine these results with those from other UAT members to determine if and how environmentally-driven gas depletion varies with the mass and X-ray properties of the host group or cluster. This work has supported by NSF grants AST-0847430, AST-1211005 and AST-1637339.

A two-stage approach to estimate spatial and spatio-temporal disease risks in the presence of local discontinuities and clusters.

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Adin, A; Lee, D; Goicoa, T; Ugarte, María Dolores

2018-01-01

Disease risk maps for areal unit data are often estimated from Poisson mixed models with local spatial smoothing, for example by incorporating random effects with a conditional autoregressive prior distribution. However, one of the limitations is that local discontinuities in the spatial pattern are not usually modelled, leading to over-smoothing of the risk maps and a masking of clusters of hot/coldspot areas. In this paper, we propose a novel two-stage approach to estimate and map disease risk in the presence of such local discontinuities and clusters. We propose approaches in both spatial and spatio-temporal domains, where for the latter the clusters can either be fixed or allowed to vary over time. In the first stage, we apply an agglomerative hierarchical clustering algorithm to training data to provide sets of potential clusters, and in the second stage, a two-level spatial or spatio-temporal model is applied to each potential cluster configuration. The superiority of the proposed approach with regard to a previous proposal is shown by simulation, and the methodology is applied to two important public health problems in Spain, namely stomach cancer mortality across Spain and brain cancer incidence in the Navarre and Basque Country regions of Spain.

Comparison of tests for spatial heterogeneity on data with global clustering patterns and outliers

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Hachey Mark

2009-10-01

Full Text Available Abstract Background The ability to evaluate geographic heterogeneity of cancer incidence and mortality is important in cancer surveillance. Many statistical methods for evaluating global clustering and local cluster patterns are developed and have been examined by many simulation studies. However, the performance of these methods on two extreme cases (global clustering evaluation and local anomaly (outlier detection has not been thoroughly investigated. Methods We compare methods for global clustering evaluation including Tango's Index, Moran's I, and Oden's I*pop; and cluster detection methods such as local Moran's I and SaTScan elliptic version on simulated count data that mimic global clustering patterns and outliers for cancer cases in the continental United States. We examine the power and precision of the selected methods in the purely spatial analysis. We illustrate Tango's MEET and SaTScan elliptic version on a 1987-2004 HIV and a 1950-1969 lung cancer mortality data in the United States. Results For simulated data with outlier patterns, Tango's MEET, Moran's I and I*pop had powers less than 0.2, and SaTScan had powers around 0.97. For simulated data with global clustering patterns, Tango's MEET and I*pop (with 50% of total population as the maximum search window had powers close to 1. SaTScan had powers around 0.7-0.8 and Moran's I has powers around 0.2-0.3. In the real data example, Tango's MEET indicated the existence of global clustering patterns in both the HIV and lung cancer mortality data. SaTScan found a large cluster for HIV mortality rates, which is consistent with the finding from Tango's MEET. SaTScan also found clusters and outliers in the lung cancer mortality data. Conclusion SaTScan elliptic version is more efficient for outlier detection compared with the other methods evaluated in this article. Tango's MEET and Oden's I*pop perform best in global clustering scenarios among the selected methods. The use of SaTScan for

Cluster size statistic and cluster mass statistic: two novel methods for identifying changes in functional connectivity between groups or conditions.

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Ing, Alex; Schwarzbauer, Christian

2014-01-01

Functional connectivity has become an increasingly important area of research in recent years. At a typical spatial resolution, approximately 300 million connections link each voxel in the brain with every other. This pattern of connectivity is known as the functional connectome. Connectivity is often compared between experimental groups and conditions. Standard methods used to control the type 1 error rate are likely to be insensitive when comparisons are carried out across the whole connectome, due to the huge number of statistical tests involved. To address this problem, two new cluster based methods--the cluster size statistic (CSS) and cluster mass statistic (CMS)--are introduced to control the family wise error rate across all connectivity values. These methods operate within a statistical framework similar to the cluster based methods used in conventional task based fMRI. Both methods are data driven, permutation based and require minimal statistical assumptions. Here, the performance of each procedure is evaluated in a receiver operator characteristic (ROC) analysis, utilising a simulated dataset. The relative sensitivity of each method is also tested on real data: BOLD (blood oxygen level dependent) fMRI scans were carried out on twelve subjects under normal conditions and during the hypercapnic state (induced through the inhalation of 6% CO2 in 21% O2 and 73%N2). Both CSS and CMS detected significant changes in connectivity between normal and hypercapnic states. A family wise error correction carried out at the individual connection level exhibited no significant changes in connectivity.

Merger and Acquisition Activity as Driver of Spatial Clustering : The Spatial Evolution of the Dutch Banking Industry, 1850-1993

NARCIS (Netherlands)

Boschma, Ron; Hartog, Matté

2014-01-01

This article investigates the extent to which merger and acquisition (M&A) activity contributed to the spatial clustering of the Dutch banking industry in Amsterdam. This analysis is based on a unique database of all banks in the Netherlands that existed in the period 1850-1993. We found that

The Not So Simple Globular Cluster ω Cen. I. Spatial Distribution of the Multiple Stellar Populations

Energy Technology Data Exchange (ETDEWEB)

Calamida, A.; Saha, A. [National Optical Astronomy Observatory—AURA, 950 N Cherry Avenue, Tucson, AZ, 85719 (United States); Strampelli, G.; Rest, A. [Space Telescope Science Institute—AURA, 3700 San Martin Drive, Baltimore, MD 21218 (United States); Bono, G.; Ferraro, I.; Iannicola, G. [INAF—Osservatorio Astronomico di Roma—Via Frascati 33, I-00040, Monteporzio Catone, Rome (Italy); Scolnic, D. [The University of Chicago, The Kavli Institute for Cosmological Physics, William Eckhardt Research Center—Suite 499, 5640 South Ellis Avenue, Chicago, IL 60637 (United States); James, D.; Smith, C.; Zenteno, A., E-mail: calamida@noao.edu [Cerro Tololo Inter-American Observatory, Casilla 603, La Serena (Chile)

2017-04-01

We present a multi-band photometric catalog of ≈1.7 million cluster members for a field of view of ≈2° × 2° across ω Cen. Photometry is based on images collected with the Dark Energy Camera on the 4 m Blanco telescope and the Advanced Camera for Surveys on the Hubble Space Telescope . The unprecedented photometric accuracy and field coverage allowed us, for the first time, to investigate the spatial distribution of ω Cen multiple populations from the core to the tidal radius, confirming its very complex structure. We found that the frequency of blue main-sequence stars is increasing compared to red main-sequence stars starting from a distance of ≈25′ from the cluster center. Blue main-sequence stars also show a clumpy spatial distribution, with an excess in the northeast quadrant of the cluster pointing toward the direction of the Galactic center. Stars belonging to the reddest and faintest red-giant branch also show a more extended spatial distribution in the outskirts of ω Cen, a region never explored before. Both these stellar sub-populations, according to spectroscopic measurements, are more metal-rich compared to the cluster main stellar population. These findings, once confirmed, make ω Cen the only stellar system currently known where metal-rich stars have a more extended spatial distribution compared to metal-poor stars. Kinematic and chemical abundance measurements are now needed for stars in the external regions of ω Cen to better characterize the properties of these sub-populations.

Improved Density Functional Tight Binding Potentials for Metalloid Aluminum Clusters

Science.gov (United States)

2016-06-01

unlimited IMPROVED DENSITY-FUNCTIONAL TIGHT BINDING POTENTIALS FOR METALLOID ALUMINUM CLUSTERS by Joon H. Kim June 2016 Thesis Advisor...DATES COVERED Master’s thesis 4. TITLE AND SUBTITLE IMPROVED DENSITY-FUNCTIONAL TIGHT BINDING POTENTIALS FOR METALLOID ALUMINUM CLUSTERS 5. FUNDING...repulsive potentials for use in density-functional tight binding (DFTB) simulations of low-valence aluminum metalloid clusters . These systems are under

An Efficient Data Compression Model Based on Spatial Clustering and Principal Component Analysis in Wireless Sensor Networks

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Yihang Yin

2015-08-01

Full Text Available Wireless sensor networks (WSNs have been widely used to monitor the environment, and sensors in WSNs are usually power constrained. Because inner-node communication consumes most of the power, efficient data compression schemes are needed to reduce the data transmission to prolong the lifetime of WSNs. In this paper, we propose an efficient data compression model to aggregate data, which is based on spatial clustering and principal component analysis (PCA. First, sensors with a strong temporal-spatial correlation are grouped into one cluster for further processing with a novel similarity measure metric. Next, sensor data in one cluster are aggregated in the cluster head sensor node, and an efficient adaptive strategy is proposed for the selection of the cluster head to conserve energy. Finally, the proposed model applies principal component analysis with an error bound guarantee to compress the data and retain the definite variance at the same time. Computer simulations show that the proposed model can greatly reduce communication and obtain a lower mean square error than other PCA-based algorithms.

An Efficient Data Compression Model Based on Spatial Clustering and Principal Component Analysis in Wireless Sensor Networks.

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Yin, Yihang; Liu, Fengzheng; Zhou, Xiang; Li, Quanzhong

2015-08-07

Wireless sensor networks (WSNs) have been widely used to monitor the environment, and sensors in WSNs are usually power constrained. Because inner-node communication consumes most of the power, efficient data compression schemes are needed to reduce the data transmission to prolong the lifetime of WSNs. In this paper, we propose an efficient data compression model to aggregate data, which is based on spatial clustering and principal component analysis (PCA). First, sensors with a strong temporal-spatial correlation are grouped into one cluster for further processing with a novel similarity measure metric. Next, sensor data in one cluster are aggregated in the cluster head sensor node, and an efficient adaptive strategy is proposed for the selection of the cluster head to conserve energy. Finally, the proposed model applies principal component analysis with an error bound guarantee to compress the data and retain the definite variance at the same time. Computer simulations show that the proposed model can greatly reduce communication and obtain a lower mean square error than other PCA-based algorithms.

Spatial Substructure in the M87 Globular Cluster System

Science.gov (United States)

Feng, Yuting; Zhang, Yunhao; Guhathakurta, Puragra; Peng, Eric; Lim, Sungsoon

2018-01-01

Based on the observation of Next Generation Virgo Cluster Survey (NGVS) project, we obtained the u,g,r,i,z and Ks band photometric information of all the objects in the 2 degree × 2 degree area (Pilot Region) around M87, the major subcluster of Virgo. By adapting an Extreme Deconvolution method, which classifies objects into Globular Clusters (GCs), galaxies and foreground stars with their color and morphology data, we got a purer-than-ever GC distribution map with a depth to gmag=25 in Pilot Region. After masking galaxy GCs, smoothing with a 10arcmin Gaussian kernel and performing a flat field correction, we show the GC density map of M87, and got a good sersic fitting of GC radial distribution with a sersic index~2.2 in the central ellipse part (45arcmin semi major axis area of M87). We quantitatively compared our GC sample with a substructure-free mock data set, which was generated from the smoothed density map as well as the sersic fitting, by calculating the 2 point correlation function (TPCF) value in different parts of the map. After separately performing such comparison with mocks based on different galaxy masking radii which vary from 4 times g band effective radius to 10, we found signals of remarkable spatial enhancement in certain directions in the central ellipse of M87, as well as halo substructures shown as lumpiness and holes in the outer region. We present the estimated scales of these substructures from the TPCF results, and, managed to locate them with a statistical analysis of the pixelized GC map. Apart from all results listed above, we discuss the constant, extra-galactic substructure signal at a scale of ~3kpc, which does not diminish with masking sizes, as the evidence of merging and accretion history of M87.

Accounting for regional background and population size in the detection of spatial clusters and outliers using geostatistical filtering and spatial neutral models: the case of lung cancer in Long Island, New York

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Goovaerts Pierre

2004-07-01

Full Text Available Abstract Background Complete Spatial Randomness (CSR is the null hypothesis employed by many statistical tests for spatial pattern, such as local cluster or boundary analysis. CSR is however not a relevant null hypothesis for highly complex and organized systems such as those encountered in the environmental and health sciences in which underlying spatial pattern is present. This paper presents a geostatistical approach to filter the noise caused by spatially varying population size and to generate spatially correlated neutral models that account for regional background obtained by geostatistical smoothing of observed mortality rates. These neutral models were used in conjunction with the local Moran statistics to identify spatial clusters and outliers in the geographical distribution of male and female lung cancer in Nassau, Queens, and Suffolk counties, New York, USA. Results We developed a typology of neutral models that progressively relaxes the assumptions of null hypotheses, allowing for the presence of spatial autocorrelation, non-uniform risk, and incorporation of spatially heterogeneous population sizes. Incorporation of spatial autocorrelation led to fewer significant ZIP codes than found in previous studies, confirming earlier claims that CSR can lead to over-identification of the number of significant spatial clusters or outliers. Accounting for population size through geostatistical filtering increased the size of clusters while removing most of the spatial outliers. Integration of regional background into the neutral models yielded substantially different spatial clusters and outliers, leading to the identification of ZIP codes where SMR values significantly depart from their regional background. Conclusion The approach presented in this paper enables researchers to assess geographic relationships using appropriate null hypotheses that account for the background variation extant in real-world systems. In particular, this new

Research of the Space Clustering Method for the Airport Noise Data Minings

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Jiwen Xie

2014-03-01

Full Text Available Mining the distribution pattern and evolution of the airport noise from the airport noise data and the geographic information of the monitoring points is of great significance for the scientific and rational governance of airport noise pollution problem. However, most of the traditional clustering methods are based on the closeness of space location or the similarity of non-spatial features, which split the duality of space elements, resulting in that the clustering result has difficult in satisfying both the closeness of space location and the similarity of non-spatial features. This paper, therefore, proposes a spatial clustering algorithm based on dual-distance. This algorithm uses a distance function as the similarity measure function in which spatial features and non-spatial features are combined. The experimental results show that the proposed algorithm can discover the noise distribution pattern around the airport effectively.

Spatial cluster analysis of nanoscopically mapped serotonin receptors for classification of fixed brain tissue

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Sams, Michael; Silye, Rene; Göhring, Janett; Muresan, Leila; Schilcher, Kurt; Jacak, Jaroslaw

2014-01-01

We present a cluster spatial analysis method using nanoscopic dSTORM images to determine changes in protein cluster distributions within brain tissue. Such methods are suitable to investigate human brain tissue and will help to achieve a deeper understanding of brain disease along with aiding drug development. Human brain tissue samples are usually treated postmortem via standard fixation protocols, which are established in clinical laboratories. Therefore, our localization microscopy-based method was adapted to characterize protein density and protein cluster localization in samples fixed using different protocols followed by common fluorescent immunohistochemistry techniques. The localization microscopy allows nanoscopic mapping of serotonin 5-HT1A receptor groups within a two-dimensional image of a brain tissue slice. These nanoscopically mapped proteins can be confined to clusters by applying the proposed statistical spatial analysis. Selected features of such clusters were subsequently used to characterize and classify the tissue. Samples were obtained from different types of patients, fixed with different preparation methods, and finally stored in a human tissue bank. To verify the proposed method, samples of a cryopreserved healthy brain have been compared with epitope-retrieved and paraffin-fixed tissues. Furthermore, samples of healthy brain tissues were compared with data obtained from patients suffering from mental illnesses (e.g., major depressive disorder). Our work demonstrates the applicability of localization microscopy and image analysis methods for comparison and classification of human brain tissues at a nanoscopic level. Furthermore, the presented workflow marks a unique technological advance in the characterization of protein distributions in brain tissue sections.

Filling- and interaction-driven Mott transition. Quantum cluster calculations within self-energy-functional theory; Fuellungs- und wechselwirkungsabhaengiger Mott-Uebergang. Quanten-Cluster-Rechnungen im Rahmen der Selbstenergiefunktional-Theorie

Energy Technology Data Exchange (ETDEWEB)

Balzer, Matthias

2008-07-01

The central goal of this thesis is the examination of strongly correlated electron systems on the basis of the two-dimensional Hubbard model. We analyze how the properties of the Mott insulator change upon doping and with interaction strength. The numerical evaluation is done using quantum cluster approximations, which allow for a thermodynamically consistent description of the ground state properties. The framework of self-energy-functional theory offers great flexibility for the construction of cluster approximations. A detailed analysis sheds light on the quality and the convergence properties of different cluster approximations within the self-energy-functional theory. We use the one-dimensional Hubbard model for these examinations and compare our results with the exact solution. In two dimensions the ground state of the particle-hole symmetric model at half-filling is an antiferromagnetic insulator, independent of the interaction strength. The inclusion of short-range spatial correlations by our cluster approach leads to a considerable improvement of the antiferromagnetic order parameter as compared to dynamical mean-field theory. In the paramagnetic phase we furthermore observe a metal-insulator transition as a function of the interaction strength, which qualitatively differs from the pure mean-field scenario. Starting from the antiferromagnetic Mott insulator a filling-controlled metal-insulator transition in a paramagnetic metallic phase can be observed. Depending on the cluster approximation used an antiferromagnetic metallic phase may occur at first. In addition to long-range antiferromagnetic order, we also considered superconductivity in our calculations. The superconducting order parameter as a function of doping is in good agreement with other numerical methods, as well as with experimental results. (orig.)

Parental Action and Referral Patterns in Spatial Clusters of Childhood Autism Spectrum Disorder

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Schelly, David; Jiménez González, Patricia; Solís, Pedro J.

2018-01-01

Sociodemographic factors have long been associated with disparities in autism spectrum disorder (ASD) diagnosis. Studies that identified spatial clustering of cases have suggested the importance of information about ASD moving through social networks of parents. Yet there is no direct evidence of this mechanism. This study explores the…

Spatial Region Estimation for Autonomous CoT Clustering Using Hidden Markov Model

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Joon‐young Jung

2018-02-01

Full Text Available This paper proposes a hierarchical dual filtering (HDF algorithm to estimate the spatial region between a Cloud of Things (CoT gateway and an Internet of Things (IoT device. The accuracy of the spatial region estimation is important for autonomous CoT clustering. We conduct spatial region estimation using a hidden Markov model (HMM with a raw Bluetooth received signal strength indicator (RSSI. However, the accuracy of the region estimation using the validation data is only 53.8%. To increase the accuracy of the spatial region estimation, the HDF algorithm removes the high‐frequency signals hierarchically, and alters the parameters according to whether the IoT device moves. The accuracy of spatial region estimation using a raw RSSI, Kalman filter, and HDF are compared to evaluate the effectiveness of the HDF algorithm. The success rate and root mean square error (RMSE of all regions are 0.538, 0.622, and 0.75, and 0.997, 0.812, and 0.5 when raw RSSI, a Kalman filter, and HDF are used, respectively. The HDF algorithm attains the best results in terms of the success rate and RMSE of spatial region estimation using HMM.

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

Science.gov (United States)

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

2018-08-15

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

Dynamics of spatial clustering of schistosomiasis in the Yangtze River Valley at the end of and following the World Bank Loan Project.

Science.gov (United States)

Hu, Yi; Xiong, Chenglong; Zhang, Zhijie; Luo, Can; Ward, Michael; Gao, Jie; Zhang, Lijuan; Jiang, Qingwu

2014-06-01

The 10-year (1992-2001) World Bank Loan Project (WBLP) contributed greatly to schistosomiasis control in China. However, the re-emergence of schistosomiasis in recent years challenged the long-term progress of the WBLP strategy. In order to gain insight in the long-term progress of the WBLP, the spatial pattern of the epidemic was investigated in the Yangtze River Valley between 1999-2001 and 2007-2008. Two spatial cluster methods were jointly used to identify spatial clusters of cases. The magnitude and number of clusters varied during 1999-2001. It was found that prevalence of schistosomiasis had been greatly reduced and maintained at a low level during 2007-2008, with little change. Besides, spatial clusters most frequently occurred within 16 counties in the Dongting Lake region and within 5 counties in the Poyang Lake region. These findings precisely pointed out the prior places for future public health planning and resource allocation of schistosomiasis. Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.

Spatial and temporal characteristics of poloidal waves in the terrestrial plasmasphere: a CLUSTER case study

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S. Schäfer

2007-05-01

Full Text Available Oscillating magnetic field lines are frequently observed by spacecraft in the terrestrial and other planetary magnetospheres. The CLUSTER mission is a very suitable tool to further study these Alfvén waves as the four CLUSTER spacecraft provide for an opportunity to separate spatial and temporal structures in the terrestrial magnetosphere. Using a large scaled configuration formed by the four spacecraft we are able to detect a poloidal Ultra-Low-Frequency (ULF pulsation of the magnetic and electric field in order to analyze its temporal and spatial structures. For this purpose the measurements are transformed into a specific field line related coordinate system to investigate their specific amplitude pattern depending on the path of the CLUSTER spacecraft across oscillating field lines. These measurements are then compared with modeled spacecraft observations across a localized poloidal wave resonator in the dayside plasmasphere. A detailed investigation of theoretically expected poloidal eigenfrequencies allows us to specify the observed 16 mHz pulsation as a third harmonic oscillation. Based on this we perform a case study providing a clear identification of wave properties such as an spatial scale structure of about 0.67 R_E, the azimuthal wave number m≈30, temporal evolution, and energy transport in the detected ULF pulsations.

Topological Properties of Spatial Coherence Function

International Nuclear Information System (INIS)

Ji-Rong, Ren; Tao, Zhu; Yi-Shi, Duan

2008-01-01

The topological properties of the spatial coherence function are investigated rigorously. The phase singular structures (coherence vortices) of coherence function can be naturally deduced from the topological current, which is an abstract mathematical object studied previously. We find that coherence vortices are characterized by the Hopf index and Brouwer degree in topology. The coherence flux quantization and the linking of the closed coherence vortices are also studied from the topological properties of the spatial coherence function

Photometric studies of globular clusters in the Andromeda Nebula. Luminosity function for old globular clusters

International Nuclear Information System (INIS)

Sharov, A.S.; Lyutyj, V.M.

1989-01-01

The luminosity function for old globular clusters in M 31 is presented. The objects were selected according to their structural and photometric properties. At the usually accepted normal (Gaussian) distribution, the luminosity function is characterized by the following parameters: the mean magnitude, corrected for the extinction inside M 31, V-bar 0 =16 m ,38±0 m .08, and the absolute magnitude M-bar v =-8 m .29 assuming )m-M) v =23 m .67, standard deviation σ M v =1 m .16±0 m .08 and total object number N=300±17. Old globular clusters in M 31 are in the average about one magnitude more luminous then those in our Galaxy (M v ≅ -7 m .3). Intrinsic luminosity dispersions of globular clusters are nearly the same in both galaxies. Available data on globular clusters in the Local Group galaxies against the universality of globular luminosity function with identical parameters M v and σ M v

Spatial clustering of toxic trace elements in adolescents around the Torreón, Mexico lead–zinc smelter

Science.gov (United States)

Garcia-Vargas, Gonzalo G.; Rothenberg, Stephen J.; Silbergeld, Ellen K.; Weaver, Virginia; Zamoiski, Rachel; Resnick, Carol; Rubio-Andrade, Marisela; Parsons, Patrick J.; Steuerwald, Amy J.; Navas-Acién, Ana; Guallar, Eliseo

2016-01-01

High blood lead (BPb) levels in children and elevated soil and dust arsenic, cadmium, and lead were previously found in Torreón, northern Mexico, host to the world’s fourth largest lead–zinc metal smelter. The objectives of this study were to determine spatial distributions of adolescents with higher BPb and creatinine-corrected urine total arsenic, cadmium, molybdenum, thallium, and uranium around the smelter. Cross-sectional study of 512 male and female subjects 12–15 years of age was conducted. We measured BPb by graphite furnace atomic absorption spectrometry and urine trace elements by inductively coupled plasma-mass spectrometry, with dynamic reaction cell mode for arsenic. We constructed multiple regression models including sociodemographic variables and adjusted for subject residence spatial correlation with spatial lag or error terms. We applied local indicators of spatial association statistics to model residuals to identify hot spots of significant spatial clusters of subjects with higher trace elements. We found spatial clusters of subjects with elevated BPb (range 3.6–14.7 µg/dl) and urine cadmium (0.18–1.14 µg/g creatinine) adjacent to and downwind of the smelter and elevated urine thallium (0.28–0.93 µg/g creatinine) and uranium (0.07–0.13 µg/g creatinine) near ore transport routes, former waste, and industrial discharge sites. The conclusion derived from this study was that spatial clustering of adolescents with high BPb and urine cadmium adjacent to and downwind of the smelter and residual waste pile, areas identified over a decade ago with high lead and cadmium in soil and dust, suggests that past and/or present plant operations continue to present health risks to children in those neighborhoods. PMID:24549228

Clustering environments of BL Lac objects

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Wurtz, Ronald; Ellingson, Erica; Stocke, John T.; Yee, H. K. C.

1993-01-01

We report measurements of the amplitude of the BL Lac galaxy spatial covariance function, B(gb), for the fields of five BL Lacertae objects. We present evidence for rich clusters around MS 1207+39 and MS 1407+59, and confirm high richness for the cluster containing H0414+009. We discuss the ease of 3C 66 A and find evidence for a poor cluster based on an uncertain redshift of z = 0.444. These data suggest that at least some BL Lac objects are consistent with being FR 1 radio galaxies in rich clusters.

INTERSECTION DETECTION BASED ON QUALITATIVE SPATIAL REASONING ON STOPPING POINT CLUSTERS

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S. Zourlidou

2016-06-01

Full Text Available The purpose of this research is to propose and test a method for detecting intersections by analysing collectively acquired trajectories of moving vehicles. Instead of solely relying on the geometric features of the trajectories, such as heading changes, which may indicate turning points and consequently intersections, we extract semantic features of the trajectories in form of sequences of stops and moves. Under this spatiotemporal prism, the extracted semantic information which indicates where vehicles stop can reveal important locations, such as junctions. The advantage of the proposed approach in comparison with existing turning-points oriented approaches is that it can detect intersections even when not all the crossing road segments are sampled and therefore no turning points are observed in the trajectories. The challenge with this approach is that first of all, not all vehicles stop at the same location – thus, the stop-location is blurred along the direction of the road; this, secondly, leads to the effect that nearby junctions can induce similar stop-locations. As a first step, a density-based clustering is applied on the layer of stop observations and clusters of stop events are found. Representative points of the clusters are determined (one per cluster and in a last step the existence of an intersection is clarified based on spatial relational cluster reasoning, with which less informative geospatial clusters, in terms of whether a junction exists and where its centre lies, are transformed in more informative ones. Relational reasoning criteria, based on the relative orientation of the clusters with their adjacent ones are discussed for making sense of the relation that connects them, and finally for forming groups of stop events that belong to the same junction.

Clustering of near clusters versus cluster compactness

International Nuclear Information System (INIS)

Yu Gao; Yipeng Jing

1989-01-01

The clustering properties of near Zwicky clusters are studied by using the two-point angular correlation function. The angular correlation functions for compact and medium compact clusters, for open clusters, and for all near Zwicky clusters are estimated. The results show much stronger clustering for compact and medium compact clusters than for open clusters, and that open clusters have nearly the same clustering strength as galaxies. A detailed study of the compactness-dependence of correlation function strength is worth investigating. (author)

HIV Clustering in Mississippi: Spatial Epidemiological Study to Inform Implementation Science in the Deep South.

Science.gov (United States)

Stopka, Thomas J; Brinkley-Rubinstein, Lauren; Johnson, Kendra; Chan, Philip A; Hutcheson, Marga; Crosby, Richard; Burke, Deirdre; Mena, Leandro; Nunn, Amy

2018-04-03

In recent years, more than half of new HIV infections in the United States occur among African Americans in the Southeastern United States. Spatial epidemiological analyses can inform public health responses in the Deep South by identifying HIV hotspots and community-level factors associated with clustering. The goal of this study was to identify and characterize HIV clusters in Mississippi through analysis of state-level HIV surveillance data. We used a combination of spatial epidemiology and statistical modeling to identify and characterize HIV hotspots in Mississippi census tracts (n=658) from 2008 to 2014. We conducted spatial analyses of all HIV infections, infections among men who have sex with men (MSM), and infections among African Americans. Multivariable logistic regression analyses identified community-level sociodemographic factors associated with HIV hotspots considering all cases. There were HIV hotspots for the entire population, MSM, and African American MSM identified in the Mississippi Delta region, Southern Mississippi, and in greater Jackson, including surrounding rural counties (PHIV cases, HIV hotspots were significantly more likely to include urban census tracts (adjusted odds ratio [AOR] 2.01, 95% CI 1.20-3.37) and census tracts that had a higher proportion of African Americans (AOR 3.85, 95% CI 2.23-6.65). The HIV hotspots were less likely to include census tracts with residents who had less than a high school education (AOR 0.95, 95% CI 0.92-0.98), census tracts with residents belonging to two or more racial/ethnic groups (AOR 0.46, 95% CI 0.30-0.70), and census tracts that had a higher percentage of the population living below the poverty level (AOR 0.51, 95% CI 0.28-0.92). We used spatial epidemiology and statistical modeling to identify and characterize HIV hotspots for the general population, MSM, and African Americans. HIV clusters concentrated in Jackson and the Mississippi Delta. African American race and urban location were

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

Science.gov (United States)

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

2018-02-01

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

Lithuanian medical tourism cluster: conditions and background for functioning

Directory of Open Access Journals (Sweden)

Korol A. N.

2017-10-01

Full Text Available as the global economy develops, more and more attention is paid to the creation of tourist clusters, which are extremely important for the economy and national competitiveness. This article analyzes the cluster of medical tourism in Lithuania, and explores the conditions for its successful functioning. The creation of the medical tourism cluster is highly influenced by a number of factors: the regulation of tourist and medical services, the level of entrepreneurial activity, human resources, the experience of partnership. In addition, the article analyzes the structure of the medical tourism cluster, determines the prerequisites for the functioning of the Lithuanian medical tourism cluster, including a wide range of services, European standards for the provision of medical services, high qualification of specialists, etc. When writing the article, the methods of systematic and logical analysis of scientific literature were used.

Temporal Data-Driven Sleep Scheduling and Spatial Data-Driven Anomaly Detection for Clustered Wireless Sensor Networks

Directory of Open Access Journals (Sweden)

Gang Li

2016-09-01

Full Text Available The spatial–temporal correlation is an important feature of sensor data in wireless sensor networks (WSNs. Most of the existing works based on the spatial–temporal correlation can be divided into two parts: redundancy reduction and anomaly detection. These two parts are pursued separately in existing works. In this work, the combination of temporal data-driven sleep scheduling (TDSS and spatial data-driven anomaly detection is proposed, where TDSS can reduce data redundancy. The TDSS model is inspired by transmission control protocol (TCP congestion control. Based on long and linear cluster structure in the tunnel monitoring system, cooperative TDSS and spatial data-driven anomaly detection are then proposed. To realize synchronous acquisition in the same ring for analyzing the situation of every ring, TDSS is implemented in a cooperative way in the cluster. To keep the precision of sensor data, spatial data-driven anomaly detection based on the spatial correlation and Kriging method is realized to generate an anomaly indicator. The experiment results show that cooperative TDSS can realize non-uniform sensing effectively to reduce the energy consumption. In addition, spatial data-driven anomaly detection is quite significant for maintaining and improving the precision of sensor data.

Spatial-functional organization of settlements in Vojvodina

Directory of Open Access Journals (Sweden)

Krunić Nikola

2012-01-01

Full Text Available This paper summarizes the results of recent exploration of spatial and functional organization of Autonomous Province of Vojvodina in the Republic of Serbia (hereinafter referred to as “Vojvodina” based on identification of the level of development of spatial and functional connections and relationships within its settlement network. The research is theoretically and methodically based on principles of regionalization and recent doctrines of regional development, contemporary spatial planning and social and economics disciplines of social geography. Results to a great extent identify and scientifically explain problems of the development of spatial and functional organization of settlement network in Vojvodina. Based on these results, a recommendation for a possible model of a sustainable settlement network in Vojvodina has been given.

Spatial clustering of all-cause and HIV-related mortality in a rural South African population (2000-2006.

Directory of Open Access Journals (Sweden)

Elias Namosha

Full Text Available Sub-Saharan Africa bears a disproportionate burden of HIV infection. Knowledge of the spatial distribution of HIV outcomes is vital so that appropriate public health interventions can be directed at locations most in need. In this regard, spatial clustering analysis of HIV-related mortality events has not been performed in a rural sub-Saharan African setting.Kulldorff's spatial scan statistic was used to identify HIV-related and all-cause mortality clusters (p<0.05 in a population-based demographic surveillance survey in rural KwaZulu Natal, South Africa (2000-2006. The analysis was split pre (2000-2003 and post (2004-2006 rollout of antiretroviral therapy, respectively. Between 2000-2006 a total of 86,175 resident individuals ≥15 years of age were under surveillance and 5,875 deaths were recorded (of which 2,938 were HIV-related over 343,060 person-years of observation (crude all-cause mortality rate 17.1/1000. During both time periods a cluster of high HIV-related (RR = 1.46/1.51, p = 0.001 and high all-cause mortality (RR = 1.35/1.38, p = 0.001 was identified in peri-urban communities near the National Road. A consistent low-risk cluster was detected in the urban township in both time periods (RR = 0.60/0.39, p = 0.003/0.005 and in the first time period (2000-2003 a large cluster of low HIV-related and all-cause mortality in a remote rural area was identified.HIV-related and all-cause mortality exhibit strong spatial clustering tendencies in this population. Highest HIV-related mortality and all-cause mortality occurred in the peri-urban communities along the National Road and was lowest in the urban township and remote rural communities. The geography of HIV-related mortality corresponded closely to the geography of HIV prevalence, with the notable exception of the urban township where high HIV-related mortality would have been expected on the basis of the high HIV prevalence. Our results suggest that HIV treatment

Cranked cluster wave function for molecular states

International Nuclear Information System (INIS)

Horiuchi, Hisashi; Yabana, Kazuhiro; Wada, Takahiro.

1986-01-01

Construction of the cranked cluster wave function is discussed by focussing on three problems; the self-consistency between the potential and the density distribution, the properties of the rotational angular frequency which is strongly influenced by the inter-cluster Pauli principle and by the parity projection, and the spin alignment along the rotation axis with the resulting structure-change of the molecular state. (author)

Bivariate functional data clustering: grouping streams based on a varying coefficient model of the stream water and air temperature relationship

Science.gov (United States)

H. Li; X. Deng; Andy Dolloff; E. P. Smith

2015-01-01

A novel clustering method for bivariate functional data is proposed to group streams based on their water–air temperature relationship. A distance measure is developed for bivariate curves by using a time-varying coefficient model and a weighting scheme. This distance is also adjusted by spatial correlation of streams via the variogram. Therefore, the proposed...

Use of a spatial scan statistic to identify clusters of births occurring outside Ghanaian health facilities for targeted intervention.

Science.gov (United States)

Bosomprah, Samuel; Dotse-Gborgbortsi, Winfred; Aboagye, Patrick; Matthews, Zoe

2016-11-01

To identify and evaluate clusters of births that occurred outside health facilities in Ghana for targeted intervention. A retrospective study was conducted using a convenience sample of live births registered in Ghanaian health facilities from January 1 to December 31, 2014. Data were extracted from the district health information system. A spatial scan statistic was used to investigate clusters of home births through a discrete Poisson probability model. Scanning with a circular spatial window was conducted only for clusters with high rates of such deliveries. The district was used as the geographic unit of analysis. The likelihood P value was estimated using Monte Carlo simulations. Ten statistically significant clusters with a high rate of home birth were identified. The relative risks ranged from 1.43 ("least likely" cluster; P=0.001) to 1.95 ("most likely" cluster; P=0.001). The relative risks of the top five "most likely" clusters ranged from 1.68 to 1.95; these clusters were located in Ashanti, Brong Ahafo, and the Western, Eastern, and Greater regions of Accra. Health facility records, geospatial techniques, and geographic information systems provided locally relevant information to assist policy makers in delivering targeted interventions to small geographic areas. Copyright © 2016 International Federation of Gynecology and Obstetrics. Published by Elsevier Ireland Ltd. All rights reserved.

Inelastic electron scattering as an indicator of clustering in wave functions

International Nuclear Information System (INIS)

1998-01-01

While the shell model is the most fundamental of nuclear structure models, states in light nuclei also have been described successfully in terms of clusters. Indeed, Wildemuth and Tang have shown a correspondence between the cluster and shell models, the clusters arising naturally as correlations out of the shell model Hamiltonian. For light nuclei, the cluster model reduces the many-body problem to a few-body one, with interactions occurring between the clusters. These interactions involve particle exchanges, since the nucleons may still be considered somewhat freely moving, with their motion not strictly confined to the clusters themselves. Such is the relation of the cluster model to the shell model. For a realistic shell model then, one may expect some evidence of clustering in the wave functions for those systems in which the cluster model is valid. The results obtained using the multi-ℎωshell model wave functions are closer in agreement with experiment than the results obtained using the 0ℎωwave functions. Yet in all cases, that level of agreement is not good, with the calculations underpredicting the measured values by at least a factor of two. This indicates that the shell model wave functions do not exhibit clustering behavior, which is expected to manifest itself at small momentum transfer. The exception is the transition to the 7 - /2 state in 7 Li, for which the value obtained from the γ-decay width is in agreement with the value obtained from the MK3W and (0 + 2 + 4)ℎωshell model calculations

Evolution of the cluster X-ray luminosity function

DEFF Research Database (Denmark)

Mullis, C.R.; Vikhlinin, A.; Henry, J.P.

2004-01-01

We report measurements of the cluster X-ray luminosity function out to z = 0.8 based on the final sample of 201 galaxy systems from the 160 Square Degree ROSAT Cluster Survey. There is little evidence for any measurable change in cluster abundance out to z similar to 0.6 at luminosities of less...... than a few times 10(44) h(50)(-2) ergs s(-1) (0.5 - 2.0 keV). However, for 0.6 cluster deficit using integrated number counts...... independently confirm the presence of evolution. Whereas the bulk of the cluster population does not evolve, the most luminous and presumably most massive structures evolve appreciably between z = 0.8 and the present. Interpreted in the context of hierarchical structure formation, we are probing sufficiently...

[Spatial and temporal clustering characteristics of typhoid and paratyphoid fever and its change pattern in 3 provinces in southwestern China, 2001-2012].

Science.gov (United States)

Wang, L X; Yang, B; Yan, M Y; Tang, Y Q; Liu, Z C; Wang, R Q; Li, S; Ma, L; Kan, B

2017-11-10

Objective: To analyze the spatial and temporal clustering characteristics of typhoid and paratyphoid fever and its change pattern in Yunnan, Guizhou and Guangxi provinces in southwestern China in recent years. Methods: The incidence data of typhoid and paratyphoid fever cases at county level in 3 provinces during 2001-2012 were collected from China Information System for Diseases Control and Prevention and analyzed by the methods of descriptive epidemiology and geographic informatics. And the map showing the spatial and temporal clustering characters of typhoid and paratyphoid fever cases in three provinces was drawn. SaTScan statistics was used to identify the typhoid and paratyphoid fever clustering areas of three provinces in each year from 2001 to 2012. Results: During the study period, the reported cases of typhoid and paratyphoid fever declined with year. The reported incidence decreased from 30.15 per 100 000 in 2001 to 10.83 per 100 000 in 2006(annual incidence 21.12 per 100 000); while during 2007-2012, the incidence became stable, ranging from 4.75 per 100 000 to 6.83 per 100 000 (annual incidence 5.73 per 100 000). The seasonal variation of the incidence was consistent in three provinces, with majority of cases occurred in summer and autumn. The spatial and temporal clustering of typhoid and paratyphoid fever was demonstrated by the incidence map. Most high-incidence counties were located in a zonal area extending from Yuxi of Yunnan to Guiyang of Guizhou, but were concentrated in Guilin in Guangxi. Temporal and spatial scan statistics identified the positional shifting of class Ⅰ clustering area from Guizhou to Yunnan. Class Ⅰ clustering area was located around the central and western areas (Zunyi and Anshun) of Guizhou during 2001-2003, and moved to the central area of Yunnan during 2004-2012. Conclusion: Spatial and temporal clustering of typhoid and paratyphoid fever existed in the endemic areas of southwestern China, and the clustering area

The smart cluster method. Adaptive earthquake cluster identification and analysis in strong seismic regions

Science.gov (United States)

Schaefer, Andreas M.; Daniell, James E.; Wenzel, Friedemann

2017-07-01

Earthquake clustering is an essential part of almost any statistical analysis of spatial and temporal properties of seismic activity. The nature of earthquake clusters and subsequent declustering of earthquake catalogues plays a crucial role in determining the magnitude-dependent earthquake return period and its respective spatial variation for probabilistic seismic hazard assessment. This study introduces the Smart Cluster Method (SCM), a new methodology to identify earthquake clusters, which uses an adaptive point process for spatio-temporal cluster identification. It utilises the magnitude-dependent spatio-temporal earthquake density to adjust the search properties, subsequently analyses the identified clusters to determine directional variation and adjusts its search space with respect to directional properties. In the case of rapid subsequent ruptures like the 1992 Landers sequence or the 2010-2011 Darfield-Christchurch sequence, a reclassification procedure is applied to disassemble subsequent ruptures using near-field searches, nearest neighbour classification and temporal splitting. The method is capable of identifying and classifying earthquake clusters in space and time. It has been tested and validated using earthquake data from California and New Zealand. A total of more than 1500 clusters have been found in both regions since 1980 with M m i n = 2.0. Utilising the knowledge of cluster classification, the method has been adjusted to provide an earthquake declustering algorithm, which has been compared to existing methods. Its performance is comparable to established methodologies. The analysis of earthquake clustering statistics lead to various new and updated correlation functions, e.g. for ratios between mainshock and strongest aftershock and general aftershock activity metrics.

Spatial clusters of suicide in the municipality of São Paulo 1996-2005: an ecological study.

Science.gov (United States)

Bando, Daniel H; Moreira, Rafael S; Pereira, Julio C R; Barrozo, Ligia V

2012-08-23

In a classical study, Durkheim mapped suicide rates, wealth, and low family density and realized that they clustered in northern France. Assessing others variables, such as religious society, he constructed a framework for the analysis of the suicide, which still allows international comparisons using the same basic methodology. The present study aims to identify possible significantly clusters of suicide in the city of São Paulo, and then, verify their statistical associations with socio-economic and cultural characteristics. A spatial scan statistical test was performed to analyze the geographical pattern of suicide deaths of residents in the city of São Paulo by Administrative District, from 1996 to 2005. Relative risks and high and/or low clusters were calculated accounting for gender and age as co-variates, were analyzed using spatial scan statistics to identify geographical patterns. Logistic regression was used to estimate associations with socioeconomic variables, considering, the spatial cluster of high suicide rates as the response variable. Drawing from Durkheim's original work, current World Health Organization (WHO) reports and recent reviews, the following independent variables were considered: marital status, income, education, religion, and migration. The mean suicide rate was 4.1/100,000 inhabitant-years. Against this baseline, two clusters were identified: the first, of increased risk (RR=1.66), comprising 18 districts in the central region; the second, of decreased risk (RR=0.78), including 14 districts in the southern region. The downtown area toward the southwestern region of the city displayed the highest risk for suicide, and though the overall risk may be considered low, the rate climbs up to an intermediate level in this region. One logistic regression analysis contrasted the risk cluster (18 districts) against the other remaining 78 districts, testing the effects of socioeconomic-cultural variables. The following categories of proportion

Inelastic electron scattering as an indicator of clustering in wave functions

Energy Technology Data Exchange (ETDEWEB)

NONE

1998-09-01

While the shell model is the most fundamental of nuclear structure models, states in light nuclei also have been described successfully in terms of clusters. Indeed, Wildemuth and Tang have shown a correspondence between the cluster and shell models, the clusters arising naturally as correlations out of the shell model Hamiltonian. For light nuclei, the cluster model reduces the many-body problem to a few-body one, with interactions occurring between the clusters. These interactions involve particle exchanges, since the nucleons may still be considered somewhat freely moving, with their motion not strictly confined to the clusters themselves. Such is the relation of the cluster model to the shell model. For a realistic shell model then, one may expect some evidence of clustering in the wave functions for those systems in which the cluster model is valid. The results obtained using the multi-{Dirac_h}{omega}shell model wave functions are closer in agreement with experiment than the results obtained using the 0{Dirac_h}{omega}wave functions. Yet in all cases, that level of agreement is not good, with the calculations underpredicting the measured values by at least a factor of two. This indicates that the shell model wave functions do not exhibit clustering behavior, which is expected to manifest itself at small momentum transfer. The exception is the transition to the 7{sup -}/2 state in {sup 7}Li, for which the value obtained from the {gamma}-decay width is in agreement with the value obtained from the MK3W and (0 + 2 + 4){Dirac_h}{omega}shell model calculations 17 refs., 1 tab., 2 figs.

Big Data GPU-Driven Parallel Processing Spatial and Spatio-Temporal Clustering Algorithms

Science.gov (United States)

Konstantaras, Antonios; Skounakis, Emmanouil; Kilty, James-Alexander; Frantzeskakis, Theofanis; Maravelakis, Emmanuel

2016-04-01

Diamantaras, K.: 'Programming and architecture of parallel processing systems', 1st Edition, Eds. Kleidarithmos, 2011 [4] NVIDIA.: 'NVidia CUDA C Programming Guide', version 5.0, NVidia (reference book) [5] Konstantaras, A.: 'Classification of Distinct Seismic Regions and Regional Temporal Modelling of Seismicity in the Vicinity of the Hellenic Seismic Arc', IEEE Selected Topics in Applied Earth Observations and Remote Sensing, vol. 6 (4), pp. 1857-1863, 2013 [6] Konstantaras, A. Varley, M.R.,. Valianatos, F., Collins, G. and Holifield, P.: 'Recognition of electric earthquake precursors using neuro-fuzzy models: methodology and simulation results', Proc. IASTED International Conference on Signal Processing Pattern Recognition and Applications (SPPRA 2002), Crete, Greece, 2002, pp 303-308, 2002 [7] Konstantaras, A., Katsifarakis, E., Maravelakis, E., Skounakis, E., Kokkinos, E. and Karapidakis, E.: 'Intelligent Spatial-Clustering of Seismicity in the Vicinity of the Hellenic Seismic Arc', Earth Science Research, vol. 1 (2), pp. 1-10, 2012 [8] Georgoulas, G., Konstantaras, A., Katsifarakis, E., Stylios, C.D., Maravelakis, E. and Vachtsevanos, G.: '"Seismic-Mass" Density-based Algorithm for Spatio-Temporal Clustering', Expert Systems with Applications, vol. 40 (10), pp. 4183-4189, 2013 [9] Konstantaras, A. J.: 'Expert knowledge-based algorithm for the dynamic discrimination of interactive natural clusters', Earth Science Informatics, 2015 (In Press, see: www.scopus.com) [10] Drakatos, G. and Latoussakis, J.: 'A catalog of aftershock sequences in Greece (1971-1997): Their spatial and temporal characteristics', Journal of Seismology, vol. 5, pp. 137-145, 2001

Changing patterns of spatial clustering of schistosomiasis in Southwest China between 1999-2001 and 2007-2008: assessing progress toward eradication after the World Bank Loan Project.

Science.gov (United States)

Hu, Yi; Xiong, Chenglong; Zhang, Zhijie; Luo, Can; Cohen, Ted; Gao, Jie; Zhang, Lijuan; Jiang, Qingwu

2014-01-03

We compared changes in the spatial clustering of schistosomiasis in Southwest China at the conclusion of and six years following the end of the World Bank Loan Project (WBLP), the control strategy of which was focused on the large-scale use of chemotherapy. Parasitological data were obtained through standardized surveys conducted in 1999-2001 and again in 2007-2008. Two alternate spatial cluster methods were used to identify spatial clusters of cases: Anselin's Local Moran's I test and Kulldorff's spatial scan statistic. Substantial reductions in the burden of schistosomiasis were found after the end of the WBLP, but the spatial extent of schistosomiasis was not reduced across the study area. Spatial clusters continued to occur in three regions: Chengdu Plain, Yangtze River Valley, and Lancang River Valley during the two periods, and regularly involved five counties. These findings suggest that despite impressive reductions in burden, the hilly and mountainous regions of Southwest China remain at risk of schistosome re-emergence. Our results help to highlight specific locations where integrated control programs can focus to speed the elimination of schistosomiasis in China.

Persistent Spatial Clusters of Prescribed Antimicrobials among Danish Pig Farms – A Register-Based Study

Science.gov (United States)

Fertner, Mette; Sanchez, Javier; Boklund, Anette; Stryhn, Henrik; Dupont, Nana; Toft, Nils

2015-01-01

The emergence of pathogens resistant to antimicrobials has prompted political initiatives targeting a reduction in the use of veterinary antimicrobials in Denmark, especially for pigs. This study elucidates the tendency of pig farms with a significantly higher antimicrobial use to remain in clusters in certain geographical regions of Denmark. Animal Daily Doses/100 pigs/day were calculated for all three age groups of pigs (weaners, finishers and sows) for each quarter during 2012–13 in 6,143 commercial indoor pig producing farms. The data were split into four time periods of six months. Repeated spatial cluster analyses were performed to identify persistent clusters, i.e. areas included in a significant cluster throughout all four time periods. Antimicrobials prescribed for weaners did not result in any persistent clusters. In contrast, antimicrobial use in finishers clustered persistently in two areas (157 farms), while those issued for sows clustered in one area (51 farms). A multivariate analysis including data on antimicrobial use for weaners, finishers and sows as three separate outcomes resulted in three persistent clusters (551 farms). Compared to farms outside the clusters during this period, weaners, finishers and sows on farms within these clusters had 19%, 104% and 4% higher use of antimicrobials, respectively. Production type, farm type and farm size seemed to have some bearing on the clustering effect. Adding these factors as categorical covariates one at a time in the multivariate analysis reduced the persistent clusters by 24.3%, 30.5% and 34.1%, respectively. PMID:26317206

Evolution of the cluster x-ray luminosity function slope

International Nuclear Information System (INIS)

Henry, J.P.; Soltan, A.; Briel, U.; Gunn, J.E.

1982-01-01

We report the results of an X-ray survey of 58 clusters of galaxies at moderate and high redshifts. Using a luminosity-limited subsample of 25 objects, we find that to a redshift of 0.5 the slope (i.e., power-law index) of the luminosity function of distant clusters is independent of redshift and consistent with that of nearby clusters. The time scale for change in the slope must be greater than 9 billion years. We cannot measure the normalization of the luminosity function because our sample is not complete. We discuss the implications of our data for theoretical models. In particular, Perrenod's models with high Ω are excluded by the present data

Spatial clustering by disease severity among reported Rocky Mountain spotted fever cases in the United States, 2001-2005.

Science.gov (United States)

Adjemian, Jennifer Zipser; Krebs, John; Mandel, Eric; McQuiston, Jennifer

2009-01-01

Rocky Mountain spotted fever (RMSF) occurs throughout much of the United States, ranging in clinical severity from moderate to fatal infection. Yet, little is known about possible differences among severity levels across geographic locations. To identify significant spatial clusters of severe and non-severe disease, RMSF cases reported to Centers for Disease Control and Prevention (CDC) were geocoded by county and classified by severity level. The statistical software program SaTScan was used to detect significant spatial clusters. Of 4,533 RMSF cases reported, 1,089 hospitalizations (168 with complications) and 23 deaths occurred. Significant clusters of 6 deaths (P = 0.05, RR = 11.4) and 19 hospitalizations with complications (P = 0.02, RR = 3.45) were detected in southwestern Tennessee. Two geographic areas were identified in north-central North Carolina with unusually low rates of severity (P = 0.001, RR = 0.62 and P = 0.001, RR = 0.45, respectively). Of all hospitalizations, 20% were clustered in central Oklahoma (P = 0.02, RR = 1.43). Significant geographic differences in severity were observed, suggesting that biologic and/or anthropogenic factors may be impacting RMSF epidemiology in the United States.

Functional region prediction with a set of appropriate homologous sequences-an index for sequence selection by integrating structure and sequence information with spatial statistics

Science.gov (United States)

2012-01-01

Background The detection of conserved residue clusters on a protein structure is one of the effective strategies for the prediction of functional protein regions. Various methods, such as Evolutionary Trace, have been developed based on this strategy. In such approaches, the conserved residues are identified through comparisons of homologous amino acid sequences. Therefore, the selection of homologous sequences is a critical step. It is empirically known that a certain degree of sequence divergence in the set of homologous sequences is required for the identification of conserved residues. However, the development of a method to select homologous sequences appropriate for the identification of conserved residues has not been sufficiently addressed. An objective and general method to select appropriate homologous sequences is desired for the efficient prediction of functional regions. Results We have developed a novel index to select the sequences appropriate for the identification of conserved residues, and implemented the index within our method to predict the functional regions of a protein. The implementation of the index improved the performance of the functional region prediction. The index represents the degree of conserved residue clustering on the tertiary structure of the protein. For this purpose, the structure and sequence information were integrated within the index by the application of spatial statistics. Spatial statistics is a field of statistics in which not only the attributes but also the geometrical coordinates of the data are considered simultaneously. Higher degrees of clustering generate larger index scores. We adopted the set of homologous sequences with the highest index score, under the assumption that the best prediction accuracy is obtained when the degree of clustering is the maximum. The set of sequences selected by the index led to higher functional region prediction performance than the sets of sequences selected by other sequence

Substructure in clusters of galaxies

International Nuclear Information System (INIS)

Fitchett, M.J.

1988-01-01

Optical observations suggesting the existence of substructure in clusters of galaxies are examined. Models of cluster formation and methods used to detect substructure in clusters are reviewed. Consideration is given to classification schemes based on a departure of bright cluster galaxies from a spherically symmetric distribution, evidence for statistically significant substructure, and various types of substructure, including velocity, spatial, and spatial-velocity substructure. The substructure observed in the galaxy distribution in clusters is discussed, focusing on observations from general cluster samples, the Virgo cluster, the Hydra cluster, Centaurus, the Coma cluster, and the Cancer cluster. 88 refs

a Three-Step Spatial-Temporal Clustering Method for Human Activity Pattern Analysis

Science.gov (United States)

Huang, W.; Li, S.; Xu, S.

2016-06-01

How people move in cities and what they do in various locations at different times form human activity patterns. Human activity pattern plays a key role in in urban planning, traffic forecasting, public health and safety, emergency response, friend recommendation, and so on. Therefore, scholars from different fields, such as social science, geography, transportation, physics and computer science, have made great efforts in modelling and analysing human activity patterns or human mobility patterns. One of the essential tasks in such studies is to find the locations or places where individuals stay to perform some kind of activities before further activity pattern analysis. In the era of Big Data, the emerging of social media along with wearable devices enables human activity data to be collected more easily and efficiently. Furthermore, the dimension of the accessible human activity data has been extended from two to three (space or space-time) to four dimensions (space, time and semantics). More specifically, not only a location and time that people stay and spend are collected, but also what people "say" for in a location at a time can be obtained. The characteristics of these datasets shed new light on the analysis of human mobility, where some of new methodologies should be accordingly developed to handle them. Traditional methods such as neural networks, statistics and clustering have been applied to study human activity patterns using geosocial media data. Among them, clustering methods have been widely used to analyse spatiotemporal patterns. However, to our best knowledge, few of clustering algorithms are specifically developed for handling the datasets that contain spatial, temporal and semantic aspects all together. In this work, we propose a three-step human activity clustering method based on space, time and semantics to fill this gap. One-year Twitter data, posted in Toronto, Canada, is used to test the clustering-based method. The results show that the

Non-flipping 13C spins near an NV center in diamond: hyperfine and spatial characteristics by density functional theory simulation of the C510[NV]H252 cluster

Science.gov (United States)

Nizovtsev, A. P.; Kilin, S. Ya; Pushkarchuk, A. L.; Pushkarchuk, V. A.; Kuten, S. A.; Zhikol, O. A.; Schmitt, S.; Unden, T.; Jelezko, F.

2018-02-01

Single NV centers in diamond coupled by hyperfine interaction (hfi) to neighboring 13C nuclear spins are now widely used in emerging quantum technologies as elements of quantum memory adjusted to a nitrogen-vacancy (NV) center electron spin qubit. For nuclear spins with low flip-flop rate, single shot readout was demonstrated under ambient conditions. Here we report on a systematic search for such stable NV-13C systems using density functional theory to simulate the hfi and spatial characteristics of all possible NV-13C complexes in the H-terminated cluster C510[NV]-H252 hosting the NV center. Along with the expected stable ‘NV-axial-13C’ systems wherein the 13C nuclear spin is located on the NV axis, we found for the first time new families of positions for the 13C nuclear spin exhibiting negligible hfi-induced flipping rates due to near-symmetric local spin density distribution. Spatially, these positions are located in the diamond bilayer passing through the vacancy of the NV center and being perpendicular to the NV axis. Analysis of available publications showed that, apparently, some of the predicted non-axial near-stable NV-13C systems have already been observed experimentally. A special experiment performed on one of these systems confirmed the prediction made.

Estimation of cluster stability using the theory of electron density functional

International Nuclear Information System (INIS)

Borisov, Yu.A.

1985-01-01

Prospects of using simple versions of the electron density functional for studying the energy characteristics of cluster compounds Was discussed. These types of cluster compounds were considered: clusters of Cs, Be, B, Sr, Cd, Sc, In, V, Tl, I elements as intermediate form between molecule and solid body, metalloorganic Mo, W, Tc, Re, Rn clusters and elementoorganic compounds of nido-cluster type. The problem concerning changes in the binding energy of homoatomic clusters depending on their size and three-dimensional structure was analysed

The pair correlation function of spatial Hawkes processes

DEFF Research Database (Denmark)

Møller, Jesper; Torrisi, Giovanni Luca

2007-01-01

Spatial Hawkes processes can be considered as spatial versions of classical Hawkes processes. We derive the pair correlation function of stationary spatial Hawkes processes and discuss the connection to the Bartlett spectrum and other summary statistics. Particularly, results for Gaussian fertility...... rates and the extension to spatial Hawkes processes with random fertility rates are discussed....

New spatial clustering-based models for optimal urban facility location considering geographical obstacles

Science.gov (United States)

Javadi, Maryam; Shahrabi, Jamal

2014-03-01

The problems of facility location and the allocation of demand points to facilities are crucial research issues in spatial data analysis and urban planning. It is very important for an organization or governments to best locate its resources and facilities and efficiently manage resources to ensure that all demand points are covered and all the needs are met. Most of the recent studies, which focused on solving facility location problems by performing spatial clustering, have used the Euclidean distance between two points as the dissimilarity function. Natural obstacles, such as mountains and rivers, can have drastic impacts on the distance that needs to be traveled between two geographical locations. While calculating the distance between various supply chain entities (including facilities and demand points), it is necessary to take such obstacles into account to obtain better and more realistic results regarding location-allocation. In this article, new models were presented for location of urban facilities while considering geographical obstacles at the same time. In these models, three new distance functions were proposed. The first function was based on the analysis of shortest path in linear network, which was called SPD function. The other two functions, namely PD and P2D, were based on the algorithms that deal with robot geometry and route-based robot navigation in the presence of obstacles. The models were implemented in ArcGIS Desktop 9.2 software using the visual basic programming language. These models were evaluated using synthetic and real data sets. The overall performance was evaluated based on the sum of distance from demand points to their corresponding facilities. Because of the distance between the demand points and facilities becoming more realistic in the proposed functions, results indicated desired quality of the proposed models in terms of quality of allocating points to centers and logistic cost. Obtained results show promising

Microseismic Monitoring of Stimulating Shale Gas Reservoir in SW China: 2. Spatial Clustering Controlled by the Preexisting Faults and Fractures

Science.gov (United States)

Chen, Haichao; Meng, Xiaobo; Niu, Fenglin; Tang, Youcai; Yin, Chen; Wu, Furong

2018-02-01

Microseismic monitoring is crucial to improving stimulation efficiency of hydraulic fracturing treatment, as well as to mitigating potential induced seismic hazard. We applied an improved matching and locating technique to the downhole microseismic data set during one treatment stage along a horizontal well within the Weiyuan shale gas play inside Sichuan Basin in SW China, resulting in 3,052 well-located microseismic events. We employed this expanded catalog to investigate the spatiotemporal evolution of the microseismicity in order to constrain migration of the injected fluids and the associated dynamic processes. The microseismicity is generally characterized by two distinctly different clusters, both of which are highly correlated with the injection activity spatially and temporarily. The distant and well-confined cluster (cluster A) is featured by relatively large-magnitude events, with 40 events of M -1 or greater, whereas the cluster in the immediate vicinity of the wellbore (cluster B) includes two apparent lineations of seismicity with a NE-SW trending, consistent with the predominant orientation of natural fractures. We calculated the b-value and D-value, an index of fracture complexity, and found significant differences between the two seismicity clusters. Particularly, the distant cluster showed an extremely low b-value ( 0.47) and D-value ( 1.35). We speculate that the distant cluster is triggered by reactivation of a preexisting critically stressed fault, whereas the two lineations are induced by shear failures of optimally oriented natural fractures associated with fluid diffusion. In both cases, the spatially clustered microseismicity related to hydraulic stimulation is strongly controlled by the preexisting faults and fractures.

Photoluminescence quenching of chemically functionalized porous silicon by a ruthenium cluster

Energy Technology Data Exchange (ETDEWEB)

Boukherroub, R.; Wayner, D.D.M. [Steacie Institute for Molecular Sciences, National Research Council of Canada, Ottawa, Ontario (Canada); Lockwood, D.J. [Institute for Microstructural Sciences, National Research Council of Canada, Ottawa, Ontario (Canada); Zargarian, D. [Chemistry Department, University of Montreal, C.P. 6128, succursale, Centre-ville, Montreal QC (Canada)

2003-05-01

This paper describes photoluminescence (PL) quenching of hydrogen-terminated and chemically derivatized porous silicon (PSi) nanostructures by a green ruthenium cluster (I). Chemisorption of freshly prepared PSi surfaces in a hexane solution of the Ru cluster for several days at room temperature led to a complete quenching of the PSi PL. The only visible PL was due to the original PL of the cluster. When the PSi surface functionalized with undecylenic acid was immersed in the same hexane solution of (I), the PSi PL was completely quenched and accompanied with a shift to a lower energy of the cluster PL. This shift was assigned to the formation of an ester linkage resulting from the nucleophilic attack of the PO anion of the cluster on the terminal acid functional group. (Abstract Copyright [2003], Wiley Periodicals, Inc.)

Photoluminescence quenching of chemically functionalized porous silicon by a ruthenium cluster

Science.gov (United States)

Boukherroub, R.; Wayner, D. D. M.; Lockwood, D. J.; Zargarian, D.

2003-05-01

This paper describes photoluminescence (PL) quenching of hydrogen-terminated and chemically derivatized porous silicon (PSi) nanostructures by a green ruthenium cluster (I). Chemisorption of freshly prepared PSi surfaces in a hexane solution of the Ru cluster for several days at room temperature led to a complete quenching of the PSi PL. The only visible PL was due to the original PL of the cluster. When the PSi surface functionalized with undecylenic acid was immersed in the same hexane solution of (I), the PSi PL was completely quenched and accompanied with a shift to a lower energy of the cluster PL. This shift was assigned to the formation of an ester linkage resulting from the nucleophilic attack of the PO anion of the cluster on the terminal acid functional group.

AIDEN: A Density Conscious Artificial Immune System for Automatic Discovery of Arbitrary Shape Clusters in Spatial Patterns

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Vishwambhar Pathak

2012-11-01

Full Text Available Recent efforts in modeling of dynamics of the natural immune cells leading to artificial immune systems (AIS have ignited contemporary research interest in finding out its analogies to real world problems. The AIS models have been vastly exploited to develop dependable robust
solutions to clustering. Most of the traditional clustering methods bear limitations in their capability to detect clusters of arbitrary shapes in a fully unsupervised manner. In this paper the recognition and communication dynamics of T Cell Receptors, the recognizing elements in innate immune
system, has been modeled with a kernel density estimation method. The model has been shown to successfully discover non spherical clusters in spatial patterns. Modeling the cohesion of the antibodies and pathogens with ‘local influence’ measure inducts comprehensive extension of the
antibody representation ball (ARB, which in turn corresponds to controlled expansion of clusters and prevents overfitting.

The Pattern of Spatially Concentrated Industries in East Germany - A Contribution to the Discussion on Economic "Clusters"

OpenAIRE

Rosenfeld, Martin T.W.; Franz, Peter; Heimpold, Gerhard

2005-01-01

Throughout the literature in regional economics, most authors agree that spatially concentrated industrial activities are important for regional economic growth. Agglomeration economies, which may occur in the context of spatial concentration and "clusters", may lead to lower costs of production and may reduce transaction costs of all kind, e. g. information costs, including the costs for R&D activities. There is much less agreement on (and: knowledge about) the empirical identification of ex...

Mathematical model for research and analyze relations and functions between enterprises, members of cluster

Science.gov (United States)

Angelov, Kiril; Kaynakchieva, Vesela

2017-12-01

The aim of the current study is to research and analyze Mathematical model for research and analyze of relations and functions between enterprises, members of cluster, and its approbation in given cluster. Subject of the study are theoretical mechanisms for the definition of mathematical models for research and analyze of relations and functions between enterprises, members of cluster. Object of the study are production enterprises, members of cluster. Results of this study show that described theoretical mathematical model is applicable for research and analyze of functions and relations between enterprises, members of cluster from different industrial sectors. This circumstance creates alternatives for election of cluster, where is experimented this model for interaction improvement between enterprises, members of cluster.

Cluster analysis of activity-time series in motor learning

DEFF Research Database (Denmark)

Balslev, Daniela; Nielsen, Finn Å; Futiger, Sally A

2002-01-01

Neuroimaging studies of learning focus on brain areas where the activity changes as a function of time. To circumvent the difficult problem of model selection, we used a data-driven analytic tool, cluster analysis, which extracts representative temporal and spatial patterns from the voxel......-time series. The optimal number of clusters was chosen using a cross-validated likelihood method, which highlights the clustering pattern that generalizes best over the subjects. Data were acquired with PET at different time points during practice of a visuomotor task. The results from cluster analysis show...

Development of New Open-Shell Perturbation and Coupled-Cluster Theories Based on Symmetric Spin Orbitals

Science.gov (United States)

Lee, Timothy J.; Arnold, James O. (Technical Monitor)

1994-01-01

A new spin orbital basis is employed in the development of efficient open-shell coupled-cluster and perturbation theories that are based on a restricted Hartree-Fock (RHF) reference function. The spin orbital basis differs from the standard one in the spin functions that are associated with the singly occupied spatial orbital. The occupied orbital (in the spin orbital basis) is assigned the delta(+) = 1/square root of 2(alpha+Beta) spin function while the unoccupied orbital is assigned the delta(-) = 1/square root of 2(alpha-Beta) spin function. The doubly occupied and unoccupied orbitals (in the reference function) are assigned the standard alpha and Beta spin functions. The coupled-cluster and perturbation theory wave functions based on this set of "symmetric spin orbitals" exhibit much more symmetry than those based on the standard spin orbital basis. This, together with interacting space arguments, leads to a dramatic reduction in the computational cost for both coupled-cluster and perturbation theory. Additionally, perturbation theory based on "symmetric spin orbitals" obeys Brillouin's theorem provided that spin and spatial excitations are both considered. Other properties of the coupled-cluster and perturbation theory wave functions and models will be discussed.

Elucidating the underlying causes of oral cancer through spatial clustering in high-risk areas of Taiwan with a distinct gender ratio of incidence

Directory of Open Access Journals (Sweden)

Chi-Ting Chiang

2010-05-01

Full Text Available This study aimed to elucidate whether or not high-risk clusters of oral cancer (OC incidence spatially correlate with the prevalence rates of betel quid chewing (BQC and cigarette smoking (CS in Taiwan. The spatial autocorrelation and potential clusters of OC incidence among the 307 townships and heavy metal content of soil throughout Taiwan were identified using the Anselin’s local Moran test. Additionally, the spatial correlations among the incidence of OC, the prevalence of BQC and CS and heavy metal content of soil were determined based on a comparison of spatial clusters. High-risk OC (Moran’s I = 0.638, P <0.001 clusters were located in central and eastern Taiwan, while “hot spots” of BQC and CS prevalence were located mainly in eastern Taiwan. The distributions of BQC and CS lifestyle factors (P <0.001 were spatially autocorrelated. The “hot spots” of OC largely coincided with the “hot spots” of BQC, except for the Changhua and Yunlin counties, which are located in central Taiwan. However, high soil contents of nickel and chromium (P <0.001 in central Taiwan also coincided with the high-risk areas of OC incidence. In particular, Changhua county has incurred several decades of serious heavy-metal pollution, with inhabitants living in polluted areas having high-risk exposure to these metals. Results of this study suggest that, in addition to BQC and CS, anthropogenic pollution may profoundly impact the complexity of OC aetiology in central Taiwan.

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

Science.gov (United States)

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

2018-01-01

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

X-ray cluster Abell 744

International Nuclear Information System (INIS)

Kurtz, M.J.; Huchra, J.P.; Beers, T.C.; Geller, M.J.; Gioia, I.M.

1985-01-01

X-ray and optical observations of the cluster of galaxies Abell 744 are presented. The X-ray flux (assuming H(0) = 100 km/s per Mpc) is about 9 x 10 to the 42nd erg/s. The X-ray source is extended, but shows no other structure. Photographic photometry (in Kron-Cousins R), calibrated by deep CCD frames, is presented for all galaxies brighter than 19th magnitude within 0.75 Mpc of the cluster center. The luminosity function is normal, and the isopleths show little evidence of substructure near the cluster center. The cluster has a dominant central galaxy, which is classified as a normal brightest-cluster elliptical on the basis of its luminosity profile. New redshifts were obtained for 26 galaxies in the vicinity of the cluster center; 20 appear to be cluster members. The spatial distribution of redshifts is peculiar; the dispersion within the 150 kpc core radius is much greater than outside. Abell 744 is similar to the nearby cluster Abell 1060. 31 references

Spatial clustering of pixels of a multispectral image

Science.gov (United States)

Conger, James Lynn

2014-08-19

A method and system for clustering the pixels of a multispectral image is provided. A clustering system computes a maximum spectral similarity score for each pixel that indicates the similarity between that pixel and the most similar neighboring. To determine the maximum similarity score for a pixel, the clustering system generates a similarity score between that pixel and each of its neighboring pixels and then selects the similarity score that represents the highest similarity as the maximum similarity score. The clustering system may apply a filtering criterion based on the maximum similarity score so that pixels with similarity scores below a minimum threshold are not clustered. The clustering system changes the current pixel values of the pixels in a cluster based on an averaging of the original pixel values of the pixels in the cluster.

A new multidimensional population health indicator for policy makers: absolute level, inequality and spatial clustering - an empirical application using global sub-national infant mortality data

Directory of Open Access Journals (Sweden)

Benn K.D. Sartorius

2014-11-01

Full Text Available The need for a multidimensional measure of population health that accounts for its distribution remains a central problem to guide the allocation of limited resources. Absolute proxy measures, like the infant mortality rate (IMR, are limi- ted because they ignore inequality and spatial clustering. We propose a novel, three-part, multidimensional mortality indi- cator that can be used as the first step to differentiate interventions in a region or country. The three-part indicator (MortalityABC index combines absolute mortality rate, the Theil Index to calculate mortality inequality and the Getis-Ord G statistic to determine the degree of spatial clustering. The analysis utilises global sub-national IMR data to empirically illu- strate the proposed indicator. The three-part indicator is mapped globally to display regional/country variation and further highlight its potential application. Developing countries (e.g. in sub-Saharan Africa display high levels of absolute mortality as well as variable mortality inequality with evidence of spatial clustering within certain sub-national units (“hotspots”. Although greater inequality is observed outside developed regions, high mortality inequality and spatial clustering are com- mon in both developed and developing countries. Significant positive correlation was observed between the degree of spatial clustering and absolute mortality. The proposed multidimensional indicator should prove useful for spatial allocation of healthcare resources within a country, because it can prompt a wide range of policy options and prioritise high-risk areas. The new indicator demonstrates the inadequacy of IMR as a single measure of population health, and it can also be adapted to lower administrative levels within a country and other population health measures.

Functional clustering of time series gene expression data by Granger causality

Science.gov (United States)

2012-01-01

Background A common approach for time series gene expression data analysis includes the clustering of genes with similar expression patterns throughout time. Clustered gene expression profiles point to the joint contribution of groups of genes to a particular cellular process. However, since genes belong to intricate networks, other features, besides comparable expression patterns, should provide additional information for the identification of functionally similar genes. Results In this study we perform gene clustering through the identification of Granger causality between and within sets of time series gene expression data. Granger causality is based on the idea that the cause of an event cannot come after its consequence. Conclusions This kind of analysis can be used as a complementary approach for functional clustering, wherein genes would be clustered not solely based on their expression similarity but on their topological proximity built according to the intensity of Granger causality among them. PMID:23107425

Novel Functions of MicroRNA-17-92 Cluster in the Endocrine System.

Science.gov (United States)

Wan, Shan; Chen, Xiang; He, Yuedong; Yu, Xijie

2018-01-01

MiR-17-92 cluster is coded by MIR17HG in chromosome 13, which is highly conserved in vertebrates. Published literatures have proved that miR-17-92 cluster critically regulates tumorigenesis and metastasis. Recent researches showed that the miR-17-92 cluster also plays novel functions in the endocrine system. To summarize recent findings on the physiological and pathological roles of miR-17-92 cluster in bone, lipid and glucose metabolisms. MiR-17-92 cluster plays significant regulatory roles in bone development and metabolism through regulating the differentiation and function of osteoblasts and osteoclasts. In addition, miR-17- 92 cluster is nearly involved in every aspect of lipid metabolism. Last but not the least, the miR-17-92 cluster is closely bound up with pancreatic beta cell function, development of type 1 diabetes and insulin resistance. However, whether miR-17-92 cluster is involved in the communication among bone, fat and glucose metabolisms remains unknown. Growing evidence indicates that miR-17-92 cluster plays significant roles in bone, lipid and glucose metabolisms through a variety of signaling pathways. Fully understanding its modulating mechanisms may necessarily facilitate to comprehend the clinical and molecule features of some metabolic disorders such as osteoporosis, arthrosclerosis and diabetes mellitus. It may provide new drug targets to prevent and cure these disorders. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.

Spatial clusters of suicide in the municipality of São Paulo 1996–2005: an ecological study

Directory of Open Access Journals (Sweden)

Bando Daniel H

2012-08-01

Full Text Available Abstract Background In a classical study, Durkheim mapped suicide rates, wealth, and low family density and realized that they clustered in northern France. Assessing others variables, such as religious society, he constructed a framework for the analysis of the suicide, which still allows international comparisons using the same basic methodology. The present study aims to identify possible significantly clusters of suicide in the city of São Paulo, and then, verify their statistical associations with socio-economic and cultural characteristics. Methods A spatial scan statistical test was performed to analyze the geographical pattern of suicide deaths of residents in the city of São Paulo by Administrative District, from 1996 to 2005. Relative risks and high and/or low clusters were calculated accounting for gender and age as co-variates, were analyzed using spatial scan statistics to identify geographical patterns. Logistic regression was used to estimate associations with socioeconomic variables, considering, the spatial cluster of high suicide rates as the response variable. Drawing from Durkheim’s original work, current World Health Organization (WHO reports and recent reviews, the following independent variables were considered: marital status, income, education, religion, and migration. Results The mean suicide rate was 4.1/100,000 inhabitant-years. Against this baseline, two clusters were identified: the first, of increased risk (RR = 1.66, comprising 18 districts in the central region; the second, of decreased risk (RR = 0.78, including 14 districts in the southern region. The downtown area toward the southwestern region of the city displayed the highest risk for suicide, and though the overall risk may be considered low, the rate climbs up to an intermediate level in this region. One logistic regression analysis contrasted the risk cluster (18 districts against the other remaining 78 districts, testing the effects of

Changing Patterns of Spatial Clustering of Schistosomiasis in Southwest China between 1999–2001 and 2007–2008: Assessing Progress toward Eradication after the World Bank Loan Project

Science.gov (United States)

Hu, Yi; Xiong, Chenglong; Zhang, Zhijie; Luo, Can; Cohen, Ted; Gao, Jie; Zhang, Lijuan; Jiang, Qingwu

2014-01-01

We compared changes in the spatial clustering of schistosomiasis in Southwest China at the conclusion of and six years following the end of the World Bank Loan Project (WBLP), the control strategy of which was focused on the large-scale use of chemotherapy. Parasitological data were obtained through standardized surveys conducted in 1999–2001 and again in 2007–2008. Two alternate spatial cluster methods were used to identify spatial clusters of cases: Anselin’s Local Moran’s I test and Kulldorff’s spatial scan statistic. Substantial reductions in the burden of schistosomiasis were found after the end of the WBLP, but the spatial extent of schistosomiasis was not reduced across the study area. Spatial clusters continued to occur in three regions: Chengdu Plain, Yangtze River Valley, and Lancang River Valley during the two periods, and regularly involved five counties. These findings suggest that despite impressive reductions in burden, the hilly and mountainous regions of Southwest China remain at risk of schistosome re-emergence. Our results help to highlight specific locations where integrated control programs can focus to speed the elimination of schistosomiasis in China. PMID:24394217

Extensive polycistronism and antisense transcription in the mammalian Hox clusters.

Directory of Open Access Journals (Sweden)

Gaëll Mainguy

Full Text Available The Hox clusters play a crucial role in body patterning during animal development. They encode both Hox transcription factor and micro-RNA genes that are activated in a precise temporal and spatial sequence that follows their chromosomal order. These remarkable collinear properties confer functional unit status for Hox clusters. We developed the TranscriptView platform to establish high resolution transcriptional profiling and report here that transcription in the Hox clusters is far more complex than previously described in both human and mouse. Unannotated transcripts can represent up to 60% of the total transcriptional output of a cluster. In particular, we identified 14 non-coding Transcriptional Units antisense to Hox genes, 10 of which (70% have a detectable mouse homolog. Most of these Transcriptional Units in both human and mouse present conserved sizeable sequences (>40 bp overlapping Hox transcripts, suggesting that these Hox antisense transcripts are functional. Hox clusters also display at least seven polycistronic clusters, i.e., different genes being co-transcribed on long isoforms (up to 30 kb. This work provides a reevaluated framework for understanding Hox gene function and dys-function. Such extensive transcriptions may provide a structural explanation for Hox clustering.

Cluster-cluster clustering

International Nuclear Information System (INIS)

Barnes, J.; Dekel, A.; Efstathiou, G.; Frenk, C.S.; Yale Univ., New Haven, CT; California Univ., Santa Barbara; Cambridge Univ., England; Sussex Univ., Brighton, England)

1985-01-01

The cluster correlation function xi sub c(r) is compared with the particle correlation function, xi(r) in cosmological N-body simulations with a wide range of initial conditions. The experiments include scale-free initial conditions, pancake models with a coherence length in the initial density field, and hybrid models. Three N-body techniques and two cluster-finding algorithms are used. In scale-free models with white noise initial conditions, xi sub c and xi are essentially identical. In scale-free models with more power on large scales, it is found that the amplitude of xi sub c increases with cluster richness; in this case the clusters give a biased estimate of the particle correlations. In the pancake and hybrid models (with n = 0 or 1), xi sub c is steeper than xi, but the cluster correlation length exceeds that of the points by less than a factor of 2, independent of cluster richness. Thus the high amplitude of xi sub c found in studies of rich clusters of galaxies is inconsistent with white noise and pancake models and may indicate a primordial fluctuation spectrum with substantial power on large scales. 30 references

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

Science.gov (United States)

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

1994-01-01

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

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

Science.gov (United States)

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

1994-07-01

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

A scale invariant clustering of genes on human chromosome 7

Directory of Open Access Journals (Sweden)

Kendal Wayne S

2004-01-01

Full Text Available Abstract Background Vertebrate genes often appear to cluster within the background of nontranscribed genomic DNA. Here an analysis of the physical distribution of gene structures on human chromosome 7 was performed to confirm the presence of clustering, and to elucidate possible underlying statistical and biological mechanisms. Results Clustering of genes was confirmed by virtue of a variance of the number of genes per unit physical length that exceeded the respective mean. Further evidence for clustering came from a power function relationship between the variance and mean that possessed an exponent of 1.51. This power function implied that the spatial distribution of genes on chromosome 7 was scale invariant, and that the underlying statistical distribution had a Poisson-gamma (PG form. A PG distribution for the spatial scattering of genes was validated by stringent comparisons of both the predicted variance to mean power function and its cumulative distribution function to data derived from chromosome 7. Conclusion The PG distribution was consistent with at least two different biological models: In the microrearrangement model, the number of genes per unit length of chromosome represented the contribution of a random number of smaller chromosomal segments that had originated by random breakage and reconstruction of more primitive chromosomes. Each of these smaller segments would have necessarily contained (on average a gamma distributed number of genes. In the gene cluster model, genes would be scattered randomly to begin with. Over evolutionary timescales, tandem duplication, mutation, insertion, deletion and rearrangement could act at these gene sites through a stochastic birth death and immigration process to yield a PG distribution. On the basis of the gene position data alone it was not possible to identify the biological model which best explained the observed clustering. However, the underlying PG statistical model implicated neutral

Conjugation of colloidal clusters and chains by capillary condensation.

Science.gov (United States)

Li, Fan; Stein, Andreas

2009-07-29

Capillary condensation was used to establish connections in colloidal clusters and 1D colloidal chains with high regional selectivity. This vapor-phase process produced conjugated clusters and chains with anisotropic functionality. The capillary condensation method is simple and can be applied to a wide range of materials. It can tolerate geometric variations and even permits conjugation of spatially separated particles. The selective deposition was also used to modulate the functionality on the colloid surfaces, producing tip-tethered nanosized building blocks that may be suitable for further assembly via directional interactions.

Modeling Temporal-Spatial Earthquake and Volcano Clustering at Yucca Mountain, Nevada

International Nuclear Information System (INIS)

T. Parsons; G.A. Thompson; A.H. Cogbill

2006-01-01

The proposed national high-level nuclear repository at Yucca Mountain is close to Quaternary faults and cinder cones. The frequency of these events is low, with indications of spatial and temporal clustering, making probabilistic assessments difficult. In an effort to identify the most likely intrusion sites, we based a 3D finite element model on the expectation that faulting and basalt intrusions are primarily sensitive to the magnitude and orientation of the least principal stress in extensional terranes. We found that in the absence of fault slip, variation in overburden pressure caused a stress state that preferentially favored intrusions at Crater Flat. However, when we allowed central Yucca Mountain faults to slip in the model, we found that magmatic clustering was not favored at Crater Flat or in the central Yucca Mountain block. Instead, we calculated that the stress field was most encouraging to intrusions near fault terminations, consistent with the location of the most recent volcanism at Yucca Mountain, the Lathrop Wells cone. We found this linked fault and magmatic system to be mutually reinforcing in the model in that dike inflation favored renewed fault slip

A THREE-STEP SPATIAL-TEMPORAL-SEMANTIC CLUSTERING METHOD FOR HUMAN ACTIVITY PATTERN ANALYSIS

Directory of Open Access Journals (Sweden)

W. Huang

2016-06-01

Full Text Available How people move in cities and what they do in various locations at different times form human activity patterns. Human activity pattern plays a key role in in urban planning, traffic forecasting, public health and safety, emergency response, friend recommendation, and so on. Therefore, scholars from different fields, such as social science, geography, transportation, physics and computer science, have made great efforts in modelling and analysing human activity patterns or human mobility patterns. One of the essential tasks in such studies is to find the locations or places where individuals stay to perform some kind of activities before further activity pattern analysis. In the era of Big Data, the emerging of social media along with wearable devices enables human activity data to be collected more easily and efficiently. Furthermore, the dimension of the accessible human activity data has been extended from two to three (space or space-time to four dimensions (space, time and semantics. More specifically, not only a location and time that people stay and spend are collected, but also what people “say” for in a location at a time can be obtained. The characteristics of these datasets shed new light on the analysis of human mobility, where some of new methodologies should be accordingly developed to handle them. Traditional methods such as neural networks, statistics and clustering have been applied to study human activity patterns using geosocial media data. Among them, clustering methods have been widely used to analyse spatiotemporal patterns. However, to our best knowledge, few of clustering algorithms are specifically developed for handling the datasets that contain spatial, temporal and semantic aspects all together. In this work, we propose a three-step human activity clustering method based on space, time and semantics to fill this gap. One-year Twitter data, posted in Toronto, Canada, is used to test the clustering-based method. The

Risk Factors and Spatial Clusters of Cryptosporidium Infection among School-Age Children in a Rural Region of Eastern China.

Science.gov (United States)

Zheng, Hao; He, Jianfeng; Wang, Li; Zhang, Rong; Ding, Zhen; Hu, Wenbiao

2018-05-06

The epidemiological features of Cryptosporidium infection among school-age children in China still remain unclear. Hereby, a cross-sectional study of 1637 children aged 3⁻9 years was designed to investigate the risk factors and spatial clusters of Cryptosporidium infection in a rural region of Eastern China. Stool specimens collected from participants were examined using the auramine-phenol and modified acid-fast staining. Univariable and multivariable analyses were performed to identify the risk factors of Cryptospordium infection. The spatial clusters were analyzed by a discrete Poisson model using SaTScan software. Our results showed that the overall prevalence of Cryptosporidium infection was 11‰ in the research region. At the age of 3⁻6 years (odds ratios (OR) = 3.072, 95% confidence intervals (CI) : 1.001⁻9.427), not washing hands before eating and after defecation (OR = 3.003, 95% CI: 1.060⁻8.511) were recognized as risk factors. Furthermore, a high-risk spatial cluster (relative risk = 4.220, p = 0.025) was identified. These findings call for effective sustainable interventions including family and school-based hygienic education to reduce the prevalence of Cryptosporidium infection. Therefore, an early warning system based spatiotemporal models with risk factors is required to further improve the effectiveness and efficiency of cryptosporidiosis control in the future.

The Mass Function of Young Star Clusters in the "Antennae" Galaxies.

Science.gov (United States)

Zhang; Fall

1999-12-20

We determine the mass function of young star clusters in the merging galaxies known as the "Antennae" (NGC 4038/9) from deep images taken with the Wide Field Planetary Camera 2 on the refurbished Hubble Space Telescope. This is accomplished by means of reddening-free parameters and a comparison with stellar population synthesis tracks to estimate the intrinsic luminosity and age, and hence the mass, of each cluster. We find that the mass function of the young star clusters (with ages less, similar160 Myr) is well represented by a power law of the form psi&parl0;M&parr0;~M-2 over the range 104 less, similarM less, similar106 M middle dot in circle. This result may have important implications for our understanding of the origin of globular clusters during the early phases of galactic evolution.

Hanseniaspora uvarum from winemaking environments show spatial and temporal genetic clustering

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Warren eAlbertin

2016-01-01

Full Text Available Hanseniaspora uvarum is one of the most abundant yeast species found on grapes and in grape must, at least before the onset of alcoholic fermentation which is usually performed by Saccharomyces species. The aim of this study was to characterise the genetic and phenotypic variability within the H. uvarum species. One hundred and fifteen strains isolated from winemaking environments in different geographical origins were analysed using 11 microsatellite markers and a subset of 47 strains were analysed by AFLP. H. uvarum isolates clustered mainly on the basis of their geographical localisation as revealed by microsatellites. In addition, a strong clustering based on year of isolation was evidenced, indicating that the genetic diversity of Hanseniaspora uvarum isolates was related to both spatial and temporal variations. Conversely, clustering analysis based on AFLP data provided a different picture with groups showing no particular characteristics, but provided higher strain discrimination. This result indicated that AFLP approaches are inadequate to establish the genetic relationship between individuals, but allowed good strain discrimination. At the phenotypic level, several extracellular enzymatic activities of enological relevance (pectinase, chitinase, protease, β-glucosidase were measured but showed low diversity. The impact of environmental factors of enological interest (temperature, anaerobia and copper addition on growth was also assessed and showed poor variation. Altogether, this work provided both new analytical tool (microsatellites and new insights into the genetic and phenotypic diversity of H. uvarum, a yeast species that has previously been identified as a potential candidate for co-inoculation in grape must, but whose intraspecific variability had never been fully assessed.

Analysing the spatial patterns of livestock anthrax in Kazakhstan in relation to environmental factors: a comparison of local (Gi* and morphology cluster statistics

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Ian T. Kracalik

2012-11-01

Full Text Available We compared a local clustering and a cluster morphology statistic using anthrax outbreaks in large (cattle and small (sheep and goats domestic ruminants across Kazakhstan. The Getis-Ord (Gi* statistic and a multidirectional optimal ecotope algorithm (AMOEBA were compared using 1st, 2nd and 3rd order Rook contiguity matrices. Multivariate statistical tests were used to evaluate the environmental signatures between clusters and non-clusters from the AMOEBA and Gi* tests. A logistic regression was used to define a risk surface for anthrax outbreaks and to compare agreement between clustering methodologies. Tests revealed differences in the spatial distribution of clusters as well as the total number of clusters in large ruminants for AMOEBA (n = 149 and for small ruminants (n = 9. In contrast, Gi* revealed fewer large ruminant clusters (n = 122 and more small ruminant clusters (n = 61. Significant environmental differences were found between groups using the Kruskall-Wallis and Mann- Whitney U tests. Logistic regression was used to model the presence/absence of anthrax outbreaks and define a risk surface for large ruminants to compare with cluster analyses. The model predicted 32.2% of the landscape as high risk. Approximately 75% of AMOEBA clusters corresponded to predicted high risk, compared with ~64% of Gi* clusters. In general, AMOEBA predicted more irregularly shaped clusters of outbreaks in both livestock groups, while Gi* tended to predict larger, circular clusters. Here we provide an evaluation of both tests and a discussion of the use of each to detect environmental conditions associated with anthrax outbreak clusters in domestic livestock. These findings illustrate important differences in spatial statistical methods for defining local clusters and highlight the importance of selecting appropriate levels of data aggregation.

Diffusion Geometry Unravels the Emergence of Functional Clusters in Collective Phenomena

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De Domenico, Manlio

2017-04-01

Collective phenomena emerge from the interaction of natural or artificial units with a complex organization. The interplay between structural patterns and dynamics might induce functional clusters that, in general, are different from topological ones. In biological systems, like the human brain, the overall functionality is often favored by the interplay between connectivity and synchronization dynamics, with functional clusters that do not coincide with anatomical modules in most cases. In social, sociotechnical, and engineering systems, the quest for consensus favors the emergence of clusters. Despite the unquestionable evidence for mesoscale organization of many complex systems and the heterogeneity of their interconnectivity, a way to predict and identify the emergence of functional modules in collective phenomena continues to elude us. Here, we propose an approach based on random walk dynamics to define the diffusion distance between any pair of units in a networked system. Such a metric allows us to exploit the underlying diffusion geometry to provide a unifying framework for the intimate relationship between metastable synchronization, consensus, and random search dynamics in complex networks, pinpointing the functional mesoscale organization of synthetic and biological systems.

Testing dark energy and dark matter cosmological models with clusters of galaxies

Energy Technology Data Exchange (ETDEWEB)

Boehringer, Hans [Max-Planck-Institut fuer Extraterrestrische Physik, Garching (Germany)

2008-07-01

Galaxy clusters are, as the largest building blocks of our Universe, ideal probes to study the large-scale structure and to test cosmological models. The principle approach und the status of this research is reviewed. Clusters lend themselves for tests in serveral ways: the cluster mass function, the spatial clustering, the evolution of both functions with reshift, and the internal composition can be used to constrain cosmological parameters. X-ray observations are currently the best means of obtaining the relevant data on the galaxy cluster population. We illustrate in particular all the above mentioned methods with our ROSAT based cluster surveys. The mass calibration of clusters is an important issue, that is currently solved with XMM-Newton and Chandra studies. Based on the current experience we provide an outlook for future research, especially with eROSITA.

Clustering Coefficients for Correlation Networks

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Naoki Masuda

2018-03-01

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

Clustering Coefficients for Correlation Networks.

Science.gov (United States)

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

2018-01-01

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

Clustering Coefficients for Correlation Networks

Science.gov (United States)

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

2018-01-01

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

A Spatially Explicit Dual-Isotope Approach to Map Regions of Plant-Plant Interaction after Exotic Plant Invasion.

Directory of Open Access Journals (Sweden)

Christine Hellmann

Full Text Available Understanding interactions between native and invasive plant species in field settings and quantifying the impact of invaders in heterogeneous native ecosystems requires resolving the spatial scale on which these processes take place. Therefore, functional tracers are needed that enable resolving the alterations induced by exotic plant invasion in contrast to natural variation in a spatially explicit way. 15N isoscapes, i.e., spatially referenced representations of stable nitrogen isotopic signatures, have recently provided such a tracer. However, different processes, e.g. water, nitrogen or carbon cycles, may be affected at different spatial scales. Thus multi-isotope studies, by using different functional tracers, can potentially return a more integrated picture of invader impact. This is particularly true when isoscapes are submitted to statistical methods suitable to find homogeneous subgroups in multivariate data such as cluster analysis. Here, we used model-based clustering of spatially explicit foliar δ15N and δ13C isoscapes together with N concentration of a native indicator species, Corema album, to map regions of influence in a Portuguese dune ecosystem invaded by the N2-fixing Acacia longifolia. Cluster analysis identified regions with pronounced alterations in N budget and water use efficiency in the native species, with a more than twofold increase in foliar N, and δ13C and δ15N enrichment of up to 2‰ and 8‰ closer to the invader, respectively. Furthermore, clusters of multiple functional tracers indicated a spatial shift from facilitation through N addition in the proximity of the invader to competition for resources other than N in close contact. Finding homogeneous subgroups in multi-isotope data by means of model-based cluster analysis provided an effective tool for detecting spatial structure in processes affecting plant physiology and performance. The proposed method can give an objective measure of the spatial extent

Antisymmetrized four-body wave function and coexistence of single particle and cluster structures

International Nuclear Information System (INIS)

Sasakawa, T.

1979-01-01

It is shown that each Yakubovski component of the totally antisymmetric four-body wave function satisfies the same equation as the unantisymmetric wave function. In the antisymmetric total wave function, the wave functions belonging to the same kind of partition are totally antisymmetric among themselves. This leads to the coexistence of cluster models, including the single particle model as a special case of the cluster model, as a sum

Statistical analysis of the spatial distribution of galaxies and clusters

International Nuclear Information System (INIS)

Cappi, Alberto

1993-01-01

This thesis deals with the analysis of the distribution of galaxies and clusters, describing some observational problems and statistical results. First chapter gives a theoretical introduction, aiming to describe the framework of the formation of structures, tracing the history of the Universe from the Planck time, t_p = 10"-"4"3 sec and temperature corresponding to 10"1"9 GeV, to the present epoch. The most usual statistical tools and models of the galaxy distribution, with their advantages and limitations, are described in chapter two. A study of the main observed properties of galaxy clustering, together with a detailed statistical analysis of the effects of selecting galaxies according to apparent magnitude or diameter, is reported in chapter three. Chapter four delineates some properties of groups of galaxies, explaining the reasons of discrepant results on group distributions. Chapter five is a study of the distribution of galaxy clusters, with different statistical tools, like correlations, percolation, void probability function and counts in cells; it is found the same scaling-invariant behaviour of galaxies. Chapter six describes our finding that rich galaxy clusters too belong to the fundamental plane of elliptical galaxies, and gives a discussion of its possible implications. Finally chapter seven reviews the possibilities offered by multi-slit and multi-fibre spectrographs, and I present some observational work on nearby and distant galaxy clusters. In particular, I show the opportunities offered by ongoing surveys of galaxies coupled with multi-object fibre spectrographs, focusing on the ESO Key Programme A galaxy redshift survey in the south galactic pole region to which I collaborate and on MEFOS, a multi-fibre instrument with automatic positioning. Published papers related to the work described in this thesis are reported in the last appendix. (author) [fr

PHAT STELLAR CLUSTER SURVEY. I. YEAR 1 CATALOG AND INTEGRATED PHOTOMETRY

International Nuclear Information System (INIS)

Johnson, L. Clifton; Dalcanton, Julianne J.; Fouesneau, Morgan; Hodge, Paul W.; Weisz, Daniel R.; Williams, Benjamin F.; Beerman, Lori C.; Seth, Anil C.; Caldwell, Nelson; Gouliermis, Dimitrios A.; Larsen, Søren S.; Olsen, Knut A. G.; San Roman, Izaskun; Sarajedini, Ata; Bianchi, Luciana; Dolphin, Andrew E.; Girardi, Léo; Guhathakurta, Puragra; Kalirai, Jason; Lang, Dustin

2012-01-01

The Panchromatic Hubble Andromeda Treasury (PHAT) survey is an ongoing Hubble Space Telescope (HST) multi-cycle program to obtain high spatial resolution imaging of one-third of the M31 disk at ultraviolet through near-infrared wavelengths. In this paper, we present the first installment of the PHAT stellar cluster catalog. When completed, the PHAT cluster catalog will be among the largest and most comprehensive surveys of resolved star clusters in any galaxy. The exquisite spatial resolution achieved with HST has allowed us to identify hundreds of new clusters that were previously inaccessible with existing ground-based surveys. We identify 601 clusters in the Year 1 sample, representing more than a factor of four increase over previous catalogs within the current survey area (390 arcmin 2 ). This work presents results derived from the first ∼25% of the survey data; we estimate that the final sample will include ∼2500 clusters. For the Year 1 objects, we present a catalog with positions, radii, and six-band integrated photometry. Along with a general characterization of the cluster luminosities and colors, we discuss the cluster luminosity function, the cluster size distributions, and highlight a number of individually interesting clusters found in the Year 1 search.

PHAT STELLAR CLUSTER SURVEY. I. YEAR 1 CATALOG AND INTEGRATED PHOTOMETRY

Energy Technology Data Exchange (ETDEWEB)

Johnson, L. Clifton; Dalcanton, Julianne J.; Fouesneau, Morgan; Hodge, Paul W.; Weisz, Daniel R.; Williams, Benjamin F.; Beerman, Lori C. [Department of Astronomy, University of Washington, Box 351580, Seattle, WA 98195 (United States); Seth, Anil C. [Department of Physics and Astronomy, University of Utah, Salt Lake City, UT 84112 (United States); Caldwell, Nelson [Harvard-Smithsonian Center for Astrophysics, 60 Garden Street, Cambridge, MA 02138 (United States); Gouliermis, Dimitrios A. [Institut fuer Theoretische Astrophysik, Zentrum fuer Astronomie der Universitaet Heidelberg, Albert-Ueberle-Strasse 2, D-69120 Heidelberg (Germany); Larsen, Soren S. [Department of Astrophysics, IMAPP, Radboud University Nijmegen, P.O. Box 9010, 6500 GL Nijmegen (Netherlands); Olsen, Knut A. G. [National Optical Astronomy Observatory, 950 North Cherry Avenue, Tucson, AZ 85719 (United States); San Roman, Izaskun; Sarajedini, Ata [Department of Astronomy, University of Florida, 211 Bryant Space Science Center, Gainesville, FL 32611-2055 (United States); Bianchi, Luciana [Department of Physics and Astronomy, Johns Hopkins University, 3400 North Charles Street, Baltimore, MD 21218 (United States); Dolphin, Andrew E. [Raytheon Company, 1151 East Hermans Road, Tucson, AZ 85756 (United States); Girardi, Leo [Osservatorio Astronomico di Padova-INAF, Vicolo dell' Osservatorio 5, I-35122 Padova (Italy); Guhathakurta, Puragra [Department of Astronomy and Astrophysics, University of California Observatories/Lick Observatory, University of California, 1156 High Street, Santa Cruz, CA 95064 (United States); Kalirai, Jason [Space Telescope Science Institute, 3700 San Martin Drive, Baltimore, MD 21218 (United States); Lang, Dustin, E-mail: lcjohnso@astro.washington.edu [Department of Astrophysical Sciences, Princeton University, Princeton, NJ 08544 (United States); and others

2012-06-20

The Panchromatic Hubble Andromeda Treasury (PHAT) survey is an ongoing Hubble Space Telescope (HST) multi-cycle program to obtain high spatial resolution imaging of one-third of the M31 disk at ultraviolet through near-infrared wavelengths. In this paper, we present the first installment of the PHAT stellar cluster catalog. When completed, the PHAT cluster catalog will be among the largest and most comprehensive surveys of resolved star clusters in any galaxy. The exquisite spatial resolution achieved with HST has allowed us to identify hundreds of new clusters that were previously inaccessible with existing ground-based surveys. We identify 601 clusters in the Year 1 sample, representing more than a factor of four increase over previous catalogs within the current survey area (390 arcmin{sup 2}). This work presents results derived from the first {approx}25% of the survey data; we estimate that the final sample will include {approx}2500 clusters. For the Year 1 objects, we present a catalog with positions, radii, and six-band integrated photometry. Along with a general characterization of the cluster luminosities and colors, we discuss the cluster luminosity function, the cluster size distributions, and highlight a number of individually interesting clusters found in the Year 1 search.

Functional Interference Clusters in Cancer Patients With Bone Metastases: A Secondary Analysis of RTOG 9714

International Nuclear Information System (INIS)

Chow, Edward; James, Jennifer; Barsevick, Andrea; Hartsell, William; Ratcliffe, Sarah; Scarantino, Charles; Ivker, Robert; Roach, Mack; Suh, John; Petersen, Ivy; Konski, Andre; Demas, William; Bruner, Deborah

2010-01-01

Purpose: To explore the relationships (clusters) among the functional interference items in the Brief Pain Inventory (BPI) in patients with bone metastases. Methods: Patients enrolled in the Radiation Therapy Oncology Group (RTOG) 9714 bone metastases study were eligible. Patients were assessed at baseline and 4, 8, and 12 weeks after randomization for the palliative radiotherapy with the BPI, which consists of seven functional items: general activity, mood, walking ability, normal work, relations with others, sleep, and enjoyment of life. Principal component analysis with varimax rotation was used to determine the clusters between the functional items at baseline and the follow-up. Cronbach's alpha was used to determine the consistency and reliability of each cluster at baseline and follow-up. Results: There were 448 male and 461 female patients, with a median age of 67 years. There were two functional interference clusters at baseline, which accounted for 71% of the total variance. The first cluster (physical interference) included normal work and walking ability, which accounted for 58% of the total variance. The second cluster (psychosocial interference) included relations with others and sleep, which accounted for 13% of the total variance. The Cronbach's alpha statistics were 0.83 and 0.80, respectively. The functional clusters changed at week 12 in responders but persisted through week 12 in nonresponders. Conclusion: Palliative radiotherapy is effective in reducing bone pain. Functional interference component clusters exist in patients treated for bone metastases. These clusters changed over time in this study, possibly attributable to treatment. Further research is needed to examine these effects.

Statistical measures of galaxy clustering

International Nuclear Information System (INIS)

Porter, D.H.

1988-01-01

Consideration is given to the large-scale distribution of galaxies and ways in which this distribution may be statistically measured. Galaxy clustering is hierarchical in nature, so that the positions of clusters of galaxies are themselves spatially clustered. A simple identification of groups of galaxies would be an inadequate description of the true richness of galaxy clustering. Current observations of the large-scale structure of the universe and modern theories of cosmology may be studied with a statistical description of the spatial and velocity distributions of galaxies. 8 refs

Clustering of fast-food restaurants around schools: a novel application of spatial statistics to the study of food environments.

Science.gov (United States)

Austin, S Bryn; Melly, Steven J; Sanchez, Brisa N; Patel, Aarti; Buka, Stephen; Gortmaker, Steven L

2005-09-01

We examined the concentration of fast food restaurants in areas proximal to schools to characterize school neighborhood food environments. We used geocoded databases of restaurant and school addresses to examine locational patterns of fast-food restaurants and kindergartens and primary and secondary schools in Chicago. We used the bivariate K function statistical method to quantify the degree of clustering (spatial dependence) of fast-food restaurants around school locations. The median distance from any school in Chicago to the nearest fast-food restaurant was 0.52 km, a distance that an adult can walk in little more than 5 minutes, and 78% of schools had at least 1 fast-food restaurant within 800 m. Fast-food restaurants were statistically significantly clustered in areas within a short walking distance from schools, with an estimated 3 to 4 times as many fast-food restaurants within 1.5 km from schools than would be expected if the restaurants were distributed throughout the city in a way unrelated to school locations. Fast-food restaurants are concentrated within a short walking distance from schools, exposing children to poor-quality food environments in their school neighborhoods.

Spectroscopic constraints on the form of the stellar cluster mass function

Science.gov (United States)

Bastian, N.; Konstantopoulos, I. S.; Trancho, G.; Weisz, D. R.; Larsen, S. S.; Fouesneau, M.; Kaschinski, C. B.; Gieles, M.

2012-05-01

This contribution addresses the question of whether the initial cluster mass function (ICMF) has a fundamental limit (or truncation) at high masses. The shape of the ICMF at high masses can be studied using the most massive young (advantages are that more clusters can be used and that the ICMF leaves a distinct pattern on the global relation between the cluster luminosity and median age within a population. If a truncation is present, a generic prediction (nearly independent of the cluster disruption law adopted) is that the median age of bright clusters should be younger than that of fainter clusters. In the case of an non-truncated ICMF, the median age should be independent of cluster luminosity. Here, we present optical spectroscopy of twelve young stellar clusters in the face-on spiral galaxy NGC 2997. The spectra are used to estimate the age of each cluster, and the brightness of the clusters is taken from the literature. The observations are compared with the model expectations of Larsen (2009, A&A, 494, 539) for various ICMF forms and both mass dependent and mass independent cluster disruption. While there exists some degeneracy between the truncation mass and the amount of mass independent disruption, the observations favour a truncated ICMF. For low or modest amounts of mass independent disruption, a truncation mass of 5-6 × 105 M⊙ is estimated, consistent with previous determinations. Additionally, we investigate possible truncations in the ICMF in the spiral galaxy M 83, the interacting Antennae galaxies, and the collection of spiral and dwarf galaxies present in Larsen (2009, A&A, 494, 539) based on photometric catalogues taken from the literature, and find that all catalogues are consistent with having a truncation in the cluster mass functions. However for the case of the Antennae, we find a truncation mass of a few × 106M⊙ , suggesting a dependence on the environment, as has been previously suggested.

Spatial patterns and links between microbial community composition and function in cyanobacterial mats

KAUST Repository

Alnajjar, Mohammad Ahmad; Ramette, Alban; Kü hl, Michael; Hamza, Waleed; Klatt, Judith M.; Polerecky, Lubos

2014-01-01

We imaged reflectance and variable fluorescence in 25 cyanobacterial mats from four distant sites around the globe to assess, at different scales of resolution, spatial variabilities in the physiological parameters characterizing their photosynthetic capacity, including the absorptivity by chlorophyll a (Achl), maximum quantum yield of photosynthesis (Ymax), and light acclimation irradiance (Ik). Generally, these parameters significantly varied within individual mats on a sub-millimeter scale, with about 2-fold higher variability in the vertical than in the horizontal direction. The average vertical profiles of Ymax and Ik decreased with depth in the mat, while Achl exhibited a sub-surface maximum. The within-mat variability was comparable to, but often larger than, the between-sites variability, whereas the within-site variabilities (i.e., between samples from the same site) were generally lowest. When compared based on averaged values of their photosynthetic parameters, mats clustered according to their site of origin. Similar clustering was found when the community composition of the mats' cyanobacterial layers were compared by automated ribosomal intergenic spacer analysis (ARISA), indicating a significant link between the microbial community composition and function. Although this link is likely the result of community adaptation to the prevailing site-specific environmental conditions, our present data is insufficient to identify the main factors determining these patterns. Nevertheless, this study demonstrates that the spatial variability in the photosynthetic capacity and light acclimation of benthic phototrophic microbial communities is at least as large on a sub-millimeter scale as it is on a global scale, and suggests that this pattern of variability scaling is similar for the microbial community composition. © 2014 Al-Najjar, Ramette, Kühl, Hamza, Klatt and Polerecky.

Spatial patterns and links between microbial community composition and function in cyanobacterial mats

KAUST Repository

Alnajjar, Mohammad Ahmad

2014-08-06

We imaged reflectance and variable fluorescence in 25 cyanobacterial mats from four distant sites around the globe to assess, at different scales of resolution, spatial variabilities in the physiological parameters characterizing their photosynthetic capacity, including the absorptivity by chlorophyll a (Achl), maximum quantum yield of photosynthesis (Ymax), and light acclimation irradiance (Ik). Generally, these parameters significantly varied within individual mats on a sub-millimeter scale, with about 2-fold higher variability in the vertical than in the horizontal direction. The average vertical profiles of Ymax and Ik decreased with depth in the mat, while Achl exhibited a sub-surface maximum. The within-mat variability was comparable to, but often larger than, the between-sites variability, whereas the within-site variabilities (i.e., between samples from the same site) were generally lowest. When compared based on averaged values of their photosynthetic parameters, mats clustered according to their site of origin. Similar clustering was found when the community composition of the mats\\' cyanobacterial layers were compared by automated ribosomal intergenic spacer analysis (ARISA), indicating a significant link between the microbial community composition and function. Although this link is likely the result of community adaptation to the prevailing site-specific environmental conditions, our present data is insufficient to identify the main factors determining these patterns. Nevertheless, this study demonstrates that the spatial variability in the photosynthetic capacity and light acclimation of benthic phototrophic microbial communities is at least as large on a sub-millimeter scale as it is on a global scale, and suggests that this pattern of variability scaling is similar for the microbial community composition. © 2014 Al-Najjar, Ramette, Kühl, Hamza, Klatt and Polerecky.

Comparison of two schemes for automatic keyword extraction from MEDLINE for functional gene clustering.

Science.gov (United States)

Liu, Ying; Ciliax, Brian J; Borges, Karin; Dasigi, Venu; Ram, Ashwin; Navathe, Shamkant B; Dingledine, Ray

2004-01-01

One of the key challenges of microarray studies is to derive biological insights from the unprecedented quatities of data on gene-expression patterns. Clustering genes by functional keyword association can provide direct information about the nature of the functional links among genes within the derived clusters. However, the quality of the keyword lists extracted from biomedical literature for each gene significantly affects the clustering results. We extracted keywords from MEDLINE that describes the most prominent functions of the genes, and used the resulting weights of the keywords as feature vectors for gene clustering. By analyzing the resulting cluster quality, we compared two keyword weighting schemes: normalized z-score and term frequency-inverse document frequency (TFIDF). The best combination of background comparison set, stop list and stemming algorithm was selected based on precision and recall metrics. In a test set of four known gene groups, a hierarchical algorithm correctly assigned 25 of 26 genes to the appropriate clusters based on keywords extracted by the TDFIDF weighting scheme, but only 23 og 26 with the z-score method. To evaluate the effectiveness of the weighting schemes for keyword extraction for gene clusters from microarray profiles, 44 yeast genes that are differentially expressed during the cell cycle were used as a second test set. Using established measures of cluster quality, the results produced from TFIDF-weighted keywords had higher purity, lower entropy, and higher mutual information than those produced from normalized z-score weighted keywords. The optimized algorithms should be useful for sorting genes from microarray lists into functionally discrete clusters.

Assessment of tuberculosis spatial hotspot areas in Antananarivo, Madagascar, by combining spatial analysis and genotyping.

Science.gov (United States)

Ratovonirina, Noël Harijaona; Rakotosamimanana, Niaina; Razafimahatratra, Solohery Lalaina; Raherison, Mamy Serge; Refrégier, Guislaine; Sola, Christophe; Rakotomanana, Fanjasoa; Rasolofo Razanamparany, Voahangy

2017-08-14

Tuberculosis (TB) remains a public health problem in Madagascar. A crucial element of TB control is the development of an easy and rapid method for the orientation of TB control strategies in the country. Our main objective was to develop a TB spatial hotspot identification method by combining spatial analysis and TB genotyping method in Antananarivo. Sputa of new pulmonary TB cases from 20 TB diagnosis and treatment centers (DTCs) in Antananarivo were collected from August 2013 to May 2014 for culture. Mycobacterium tuberculosis complex (MTBC) clinical isolates were typed by spoligotyping on a Luminex® 200 platform. All TB patients were respectively localized according to their neighborhood residence and the spatial distribution of all pulmonary TB patients and patients with genotypic clustered isolates were scanned respectively by the Kulldorff spatial scanning method for identification of significant spatial clustering. Areas exhibiting spatial clustering of patients with genotypic clustered isolates were considered as hotspot TB areas for transmission. Overall, 467 new cases were included in the study, and 394 spoligotypes were obtained (84.4%). New TB cases were distributed in 133 of the 192 Fokontany (administrative neighborhoods) of Antananarivo (1 to 15 clinical patients per Fokontany) and patients with genotypic clustered isolates were distributed in 127 of the 192 Fokontany (1 to 13 per Fokontany). A single spatial focal point of epidemics was detected when ignoring genotypic data (p = 0.039). One Fokontany of this focal point and three additional ones were detected to be spatially clustered when taking genotypes into account (p Madagascar and will allow better TB control strategies by public health authorities.

The luminosity function for globular clusters, 4: M3

International Nuclear Information System (INIS)

Simoda, Mahiro; Fukuoka, Takashi

1976-01-01

The subgiant-turnoff portion (V = 17.2 - 20.0 mag) of the luminosity function for the globular cluster M3 has been determined from photometry of the stars within the annuli 3'-8' and 6'-8' for V = 17.2 - 19.0 mag and 19.0 - 20.0 mag, respectively, by using plates taken with the Kitt Peak 2.1-m reflector. Our result shows that the luminosity function for M3 has a similar steep rise in the subgiant portion as other clusters so far studied (M5, M13, and M92), in direct conflict with the result by SANDAGE (1954, 1957). A probable cause of this discrepancy is given. Comparison with theoretical luminosity functions by SIMODA and IBEN (1970) suggests that theory and observation are not inconsistent if the initial helium abundance of M3 stars is taken to be about 20 percent. It is suggested that M13 has a larger helium abundance than M3 and M92 from the intercomparison of their luminosity functions and color-magnitude diagrams. (auth.)

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

Science.gov (United States)

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

2012-01-01

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

Indexing, Query Processing, and Clustering of Spatio-Temporal Text Objects

DEFF Research Database (Denmark)

Skovsgaard, Anders

With the increasing mobile use of the web from geo-positioned devices, the Internet is increasingly acquiring a spatial aspect, with still more types of content being geo-tagged. As a result of this development, a wide range of location-aware queries and applications have emerged. The large amounts...... of data available coupled with the increasing number of location-aware queries calls for efficient indexing and query processing techniques. This dissertation investigates how to manage geo-tagged text content to support these workloads in three specific areas: (i) grouping of spatio-textual objects, (ii......, the grouping of spatio-textual objects is done without considering query locations, and a clustering approach is proposed that takes into account both the spatial and textual attributes of the objects. The technique expands clusters based on a proposed quality function that enables clusters of arbitrary shape...

The galaxy cluster mid-infrared luminosity function at 1.3 < z < 3.2

Energy Technology Data Exchange (ETDEWEB)

Wylezalek, Dominika; Vernet, Joël; De Breuck, Carlos [European Southern Observatory, Karl-Schwarzschildstr.2, D-85748 Garching bei München (Germany); Stern, Daniel [Jet Propulsion Laboratory, California Institute of Technology, 4800 Oak Grove Drive, Pasadena, CA 91109 (United States); Brodwin, Mark [Department of Physics and Astronomy, University of Missouri, 5110 Rockhill Road, Kansas City, MO 64110 (United States); Galametz, Audrey [INAF-Osservatorio di Roma, Via Frascati 33, I-00040, Monteporzio (Italy); Gonzalez, Anthony H. [Department of Astronomy, University of Florida, Gainesville, FL 32611 (United States); Jarvis, Matt [Astrophysics, Department of Physics, Keble Road, Oxford OX1 3RH (United Kingdom); Hatch, Nina [School of Physics and Astronomy, University of Nottingham, University Park, Nottingham, NG7 2RD (United Kingdom); Seymour, Nick [CASS, P.O. Box 76, Epping, NSW, 1710 (Australia); Stanford, Spencer A. [Physics Department, University of California, Davis, CA 95616 (United States)

2014-05-01

We present 4.5 μm luminosity functions for galaxies identified in 178 candidate galaxy clusters at 1.3 < z < 3.2. The clusters were identified as Spitzer/Infrared Array Camera (IRAC) color-selected overdensities in the Clusters Around Radio-Loud AGN project, which imaged 420 powerful radio-loud active galactic nuclei (RLAGNs) at z > 1.3. The luminosity functions are derived for different redshift and richness bins, and the IRAC imaging reaches depths of m* + 2, allowing us to measure the faint end slopes of the luminosity functions. We find that α = –1 describes the luminosity function very well in all redshift bins and does not evolve significantly. This provides evidence that the rate at which the low mass galaxy population grows through star formation gets quenched and is replenished by in-falling field galaxies does not have a major net effect on the shape of the luminosity function. Our measurements for m* are consistent with passive evolution models and high formation redshifts (z{sub f} ∼ 3). We find a slight trend toward fainter m* for the richest clusters, implying that the most massive clusters in our sample could contain older stellar populations, yet another example of cosmic downsizing. Modeling shows that a contribution of a star-forming population of up to 40% cannot be ruled out. This value, found from our targeted survey, is significantly lower than the values found for slightly lower redshift, z ∼ 1, clusters found in wide-field surveys. The results are consistent with cosmic downsizing, as the clusters studied here were all found in the vicinity of RLAGNs—which have proven to be preferentially located in massive dark matter halos in the richest environments at high redshift—and they may therefore be older and more evolved systems than the general protocluster population.

The galaxy cluster mid-infrared luminosity function at 1.3 < z < 3.2

International Nuclear Information System (INIS)

Wylezalek, Dominika; Vernet, Joël; De Breuck, Carlos; Stern, Daniel; Brodwin, Mark; Galametz, Audrey; Gonzalez, Anthony H.; Jarvis, Matt; Hatch, Nina; Seymour, Nick; Stanford, Spencer A.

2014-01-01

We present 4.5 μm luminosity functions for galaxies identified in 178 candidate galaxy clusters at 1.3 < z < 3.2. The clusters were identified as Spitzer/Infrared Array Camera (IRAC) color-selected overdensities in the Clusters Around Radio-Loud AGN project, which imaged 420 powerful radio-loud active galactic nuclei (RLAGNs) at z > 1.3. The luminosity functions are derived for different redshift and richness bins, and the IRAC imaging reaches depths of m* + 2, allowing us to measure the faint end slopes of the luminosity functions. We find that α = –1 describes the luminosity function very well in all redshift bins and does not evolve significantly. This provides evidence that the rate at which the low mass galaxy population grows through star formation gets quenched and is replenished by in-falling field galaxies does not have a major net effect on the shape of the luminosity function. Our measurements for m* are consistent with passive evolution models and high formation redshifts (z f ∼ 3). We find a slight trend toward fainter m* for the richest clusters, implying that the most massive clusters in our sample could contain older stellar populations, yet another example of cosmic downsizing. Modeling shows that a contribution of a star-forming population of up to 40% cannot be ruled out. This value, found from our targeted survey, is significantly lower than the values found for slightly lower redshift, z ∼ 1, clusters found in wide-field surveys. The results are consistent with cosmic downsizing, as the clusters studied here were all found in the vicinity of RLAGNs—which have proven to be preferentially located in massive dark matter halos in the richest environments at high redshift—and they may therefore be older and more evolved systems than the general protocluster population.

A-dependence of structure functions and multiquark clusters in nuclei

International Nuclear Information System (INIS)

Kondratyuk, L.; Shmatikov, M.

1984-01-01

Assuming existence of 12q-clusters (bags) in nuclei the structure functions of deep inelastic scattering of leptons on nuclei are discussed. Universal momentum distribution of quarks in a multiquark cluster is used with high-momentum component falling exponentially PHIsub(q)sup(2)(k) approximately esup(-k/ksub(0)) with k 0 approximately equal to 50-60 MeV/c. The admixture of 12q-cluster W required for the description of SLAG data increases from 10% for 4 He to 30% for Au. The A-dependence of W agrees well with the A-dependence of cumulative particle spectra

Novel Ordered Stepped-Wedge Cluster Trial Designs for Detecting Ebola Vaccine Efficacy Using a Spatially Structured Mathematical Model.

Directory of Open Access Journals (Sweden)

Ibrahim Diakite

2016-08-01

Full Text Available During the 2014 Ebola virus disease (EVD outbreak, policy-makers were confronted with difficult decisions on how best to test the efficacy of EVD vaccines. On one hand, many were reluctant to withhold a vaccine that might prevent a fatal disease from study participants randomized to a control arm. On the other, regulatory bodies called for rigorous placebo-controlled trials to permit direct measurement of vaccine efficacy prior to approval of the products. A stepped-wedge cluster study (SWCT was proposed as an alternative to a more traditional randomized controlled vaccine trial to address these concerns. Here, we propose novel "ordered stepped-wedge cluster trial" (OSWCT designs to further mitigate tradeoffs between ethical concerns, logistics, and statistical rigor.We constructed a spatially structured mathematical model of the EVD outbreak in Sierra Leone. We used the output of this model to simulate and compare a series of stepped-wedge cluster vaccine studies. Our model reproduced the observed order of first case occurrence within districts of Sierra Leone. Depending on the infection risk within the trial population and the trial start dates, the statistical power to detect a vaccine efficacy of 90% varied from 14% to 32% for standard SWCT, and from 67% to 91% for OSWCTs for an alpha error of 5%. The model's projection of first case occurrence was robust to changes in disease natural history parameters.Ordering clusters in a step-wedge trial based on the cluster's underlying risk of infection as predicted by a spatial model can increase the statistical power of a SWCT. In the event of another hemorrhagic fever outbreak, implementation of our proposed OSWCT designs could improve statistical power when a step-wedge study is desirable based on either ethical concerns or logistical constraints.

Malaria prevalence, spatial clustering and risk factors in a low endemic area of Eastern Rwanda: a cross sectional study

NARCIS (Netherlands)

Rulisa, Stephen; Kateera, Fredrick; Bizimana, Jean Pierre; Agaba, Steven; Dukuzumuremyi, Javier; Baas, Lisette; de Dieu Harelimana, Jean; Mens, Petra F.; Boer, Kimberly R.; de Vries, Peter J.

2013-01-01

Rwanda reported significant reductions in malaria burden following scale up of control intervention from 2005 to 2010. This study sought to; measure malaria prevalence, describe spatial malaria clustering and investigate for malaria risk factors among health-centre-presumed malaria cases and their

Measurement of spatial correlation functions using image processing techniques

International Nuclear Information System (INIS)

Berryman, J.G.

1985-01-01

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

A spectral scheme for Kohn-Sham density functional theory of clusters

Science.gov (United States)

Banerjee, Amartya S.; Elliott, Ryan S.; James, Richard D.

2015-04-01

Starting from the observation that one of the most successful methods for solving the Kohn-Sham equations for periodic systems - the plane-wave method - is a spectral method based on eigenfunction expansion, we formulate a spectral method designed towards solving the Kohn-Sham equations for clusters. This allows for efficient calculation of the electronic structure of clusters (and molecules) with high accuracy and systematic convergence properties without the need for any artificial periodicity. The basis functions in this method form a complete orthonormal set and are expressible in terms of spherical harmonics and spherical Bessel functions. Computation of the occupied eigenstates of the discretized Kohn-Sham Hamiltonian is carried out using a combination of preconditioned block eigensolvers and Chebyshev polynomial filter accelerated subspace iterations. Several algorithmic and computational aspects of the method, including computation of the electrostatics terms and parallelization are discussed. We have implemented these methods and algorithms into an efficient and reliable package called ClusterES (Cluster Electronic Structure). A variety of benchmark calculations employing local and non-local pseudopotentials are carried out using our package and the results are compared to the literature. Convergence properties of the basis set are discussed through numerical examples. Computations involving large systems that contain thousands of electrons are demonstrated to highlight the efficacy of our methodology. The use of our method to study clusters with arbitrary point group symmetries is briefly discussed.

Topological defect clustering and plastic deformation mechanisms in functionalized graphene

Science.gov (United States)

Nunes, Ricardo; Araujo, Joice; Chacham, Helio

2011-03-01

We present ab initio results suggesting that strain plays a central role in the clustering of topological defects in strained and functionalized graphene models. We apply strain onto the topological-defect graphene networks from our previous work, and obtain topological-defect clustering patterns which are in excellent agreement with recent observations in samples of reduced graphene oxide. In our models, the graphene layer, containing an initial concentration of isolated topological defects, is covered by hydrogen or hydroxyl groups. Our results also suggest a rich variety of plastic deformation mechanism in functionalized graphene systems. We acknowledge support from the Brazilian agencies: CNPq, Fapemig, and INCT-Materiais de Carbono.

Density functional study of the bonding in small silicon clusters

International Nuclear Information System (INIS)

Fournier, R.; Sinnott, S.B.; DePristo, A.E.

1992-01-01

We report the ground electronic state, equilibrium geometry, vibrational frequencies, and binding energy for various isomers of Si n (n = 2--8) obtained with the linear combination of atomic orbitals-density functional method. We used both a local density approximation approach and one with gradient corrections. Our local density approximation results concerning the relative stability of electronic states and isomers are in agreement with Hartree--Fock and Moller--Plesset (MP2) calculations [K. Raghavachari and C. M. Rohlfing, J. Chem. Phys. 89, 2219 (1988)]. The binding energies calculated with the gradient corrected functional are in good agreement with experiment (Si 2 and Si 3 ) and with the best theoretical estimates. Our analysis of the bonding reveals two limiting modes of bonding and classes of silicon clusters. One class of clusters is characterized by relatively large s atomic populations and a large number of weak bonds, while the other class of clusters is characterized by relatively small s atomic populations and a small number of strong bonds

Three-Dimensional Hermite—Bessel—Gaussian Soliton Clusters in Strongly Nonlocal Media

International Nuclear Information System (INIS)

Jin Hai-Qin; Yi Lin; Liang Jian-Chu; Cai Ze-Bin; Liu Fei

2012-01-01

We analytically and numerically demonstrate the existence of Hermite—Bessel—Gaussian spatial soliton clusters in three-dimensional strongly nonlocal media. It is found that the soliton clusters display the vortex, dipole azimuthon and quadrupole azimuthon in geometry, and the total number of solitons in the necklaces depends on the quantum number n and m of the Hermite functions and generalized Bessel polynomials. The numerical simulation is basically identical to the analytical solution, and white noise does not lead to collapse of the soliton, which confirms the stability of the soliton waves. The theoretical predictions may give new insights into low-energetic spatial soliton transmission with high fidelity

Foot and mouth disease in Zambia: Spatial and temporal distributions of outbreaks, assessment of clusters and implications for control

Directory of Open Access Journals (Sweden)

Yona Sinkala

2014-04-01

Full Text Available Zambia has been experiencing low livestock productivity as well as trade restrictions owing to the occurrence of foot and mouth disease (FMD, but little is known about the epidemiology of the disease in these endemic settings. The fundamental questions relate to the spatio-temporal distribution of FMD cases and what determines their occurrence. A retrospective review of FMD cases in Zambia from 1981 to 2012 was conducted using geographical information systems and the SaTScan software package. Information was collected from peer-reviewed journal articles, conference proceedings, laboratory reports, unpublished scientific reports and grey literature. A space–time permutation probability model using a varying time window of one year was used to scan for areas with high infection rates. The spatial scan statistic detected a significant purely spatial cluster around the Mbala–Isoka area between 2009 and 2012, with secondary clusters in Sesheke–Kazungula in 2007 and 2008, the Kafue flats in 2004 and 2005 and Livingstone in 2012. This study provides evidence of the existence of statistically significant FMD clusters and an increase in occurrence in Zambia between 2004 and 2012. The identified clusters agree with areas known to be at high risk of FMD. The FMD virus transmission dynamics and the heterogeneous variability in risk within these locations may need further investigation.

The Magellanic Bridge Cluster NGC 796: Deep Optical AO Imaging Reveals the Stellar Content and Initial Mass Function of a Massive Open Cluster

Science.gov (United States)

Kalari, Venu M.; Carraro, Giovanni; Evans, Christopher J.; Rubio, Monica

2018-04-01

NGC 796 is a massive young cluster located 59 kpc from us in the diffuse intergalactic medium of the 1/5–1/10 Z⊙ Magellanic Bridge, allowing us to probe variations in star formation and stellar evolution processes as a function of metallicity in a resolved fashion, and providing a link between resolved studies of nearby solar-metallicity and unresolved distant metal-poor clusters located in high-redshift galaxies. In this paper, we present adaptive optics griHα imaging of NGC 796 (at 0.″5, which is ∼0.14 pc at the cluster distance) along with optical spectroscopy of two bright members to quantify the cluster properties. Our aim is to explore whether star formation and stellar evolution vary as a function of metallicity by comparing the properties of NGC 796 to higher-metallicity clusters. We find an age of {20}-5+12 Myr from isochronal fitting of the cluster main sequence in the color–magnitude diagram. Based on the cluster luminosity function, we derive a top-heavy stellar initial mass function (IMF) with a slope α = 1.99 ± 0.2, hinting at a metallicity and/or environmental dependence of the IMF, which may lead to a top-heavy IMF in the early universe. Study of the Hα emission-line stars reveals that classical Be stars constitute a higher fraction of the total B-type stars when compared with similar clusters at greater metallicity, providing some support to the chemically homogeneous theory of stellar evolution. Overall, NGC 796 has a total estimated mass of 990 ± 200 M⊙, and a core radius of 1.4 ± 0.3 pc, which classifies it as a massive young open cluster, unique in the diffuse interstellar medium of the Magellanic Bridge.

POTENTIAL CLUSTERS IN BANAT AND THEIR ROLE IN REGIONAL ECONOMIC DEVELOPMENT

Directory of Open Access Journals (Sweden)

Ramona IŞFĂNESCU

2010-06-01

Full Text Available The interest in the study of clusters and their role in the economic development of certain regions has constantly grown in the past years. This interest has also been emphasized by the emergence of successful clusters in many regions; these are clusters that have visibly and they have determined the increase in competitiveness of those particular regions. Clusters are geographic gatherings of firms and institutions, connected to each other and specialized in certain fields of activity. In Romania, due to the low cooperation level among enterprises we cannot say that proper clusters exists, but just some “spatial gatherings” of firms activating in certain domains, connected by the need of using certain natural resources and the existence of a specialized workforce in that particular domain. Natural “clusters” can be identified by means of quantitative analyses, these indicating the possibility to identify certain spatial assemblies of firms in a certain economic sector. Starting from these quantitative analyses, for Banat region have been identified some important spatial gatherings of firms activating in certain domains which could represent potential clusters in this area. As clusters function on the principle of cooperation among enterprises, a strong point of the region is the presence of foreign investors which promoted the model of enterprise cooperation through sub-contracting local enterprises. Among these, we mention the Italian investors which brought to Banat, especially to Timiş County the Italian cluster model. Are there in Banat premises for the emergence of clusters? Which are the fields of activity in which these clusters can emerge? What role will these clusters play in the economic development of the region? These are just some of the questions that we aim answering to through this study.

Evaluating patterns of a white-band disease (WBD outbreak in Acropora palmata using spatial analysis: a comparison of transect and colony clustering.

Directory of Open Access Journals (Sweden)

Jennifer A Lentz

Full Text Available BACKGROUND: Despite being one of the first documented, there is little known of the causative agent or environmental stressors that promote white-band disease (WBD, a major disease of Caribbean Acropora palmata. Likewise, there is little known about the spatiality of outbreaks. We examined the spatial patterns of WBD during a 2004 outbreak at Buck Island Reef National Monument in the US Virgin Islands. METHODOLOGY/PRINCIPAL FINDINGS: Ripley's K statistic was used to measure spatial dependence of WBD across scales. Localized clusters of WBD were identified using the DMAP spatial filtering technique. Statistics were calculated for colony- (number of A. palmata colonies with and without WBD within each transect and transect-level (presence/absence of WBD within transects data to evaluate differences in spatial patterns at each resolution of coral sampling. The Ripley's K plots suggest WBD does cluster within the study area, and approached statistical significance (p = 0.1 at spatial scales of 1100 m or less. Comparisons of DMAP results suggest the transect-level overestimated the prevalence and spatial extent of the outbreak. In contrast, more realistic prevalence estimates and spatial patterns were found by weighting each transect by the number of individual A. palmata colonies with and without WBD. CONCLUSIONS: As the search for causation continues, surveillance and proper documentation of the spatial patterns may inform etiology, and at the same time assist reef managers in allocating resources to tracking the disease. Our results indicate that the spatial scale of data collected can drastically affect the calculation of prevalence and spatial distribution of WBD outbreaks. Specifically, we illustrate that higher resolution sampling resulted in more realistic disease estimates. This should assist in selecting appropriate sampling designs for future outbreak investigations. The spatial techniques used here can be used to facilitate other

Evaluating patterns of a white-band disease (WBD) outbreak in Acropora palmata using spatial analysis: a comparison of transect and colony clustering.

Science.gov (United States)

Lentz, Jennifer A; Blackburn, Jason K; Curtis, Andrew J

2011-01-01

Despite being one of the first documented, there is little known of the causative agent or environmental stressors that promote white-band disease (WBD), a major disease of Caribbean Acropora palmata. Likewise, there is little known about the spatiality of outbreaks. We examined the spatial patterns of WBD during a 2004 outbreak at Buck Island Reef National Monument in the US Virgin Islands. Ripley's K statistic was used to measure spatial dependence of WBD across scales. Localized clusters of WBD were identified using the DMAP spatial filtering technique. Statistics were calculated for colony- (number of A. palmata colonies with and without WBD within each transect) and transect-level (presence/absence of WBD within transects) data to evaluate differences in spatial patterns at each resolution of coral sampling. The Ripley's K plots suggest WBD does cluster within the study area, and approached statistical significance (p = 0.1) at spatial scales of 1100 m or less. Comparisons of DMAP results suggest the transect-level overestimated the prevalence and spatial extent of the outbreak. In contrast, more realistic prevalence estimates and spatial patterns were found by weighting each transect by the number of individual A. palmata colonies with and without WBD. As the search for causation continues, surveillance and proper documentation of the spatial patterns may inform etiology, and at the same time assist reef managers in allocating resources to tracking the disease. Our results indicate that the spatial scale of data collected can drastically affect the calculation of prevalence and spatial distribution of WBD outbreaks. Specifically, we illustrate that higher resolution sampling resulted in more realistic disease estimates. This should assist in selecting appropriate sampling designs for future outbreak investigations. The spatial techniques used here can be used to facilitate other coral disease studies, as well as, improve reef conservation and management.

WebGimm: An integrated web-based platform for cluster analysis, functional analysis, and interactive visualization of results.

Science.gov (United States)

Joshi, Vineet K; Freudenberg, Johannes M; Hu, Zhen; Medvedovic, Mario

2011-01-17

Cluster analysis methods have been extensively researched, but the adoption of new methods is often hindered by technical barriers in their implementation and use. WebGimm is a free cluster analysis web-service, and an open source general purpose clustering web-server infrastructure designed to facilitate easy deployment of integrated cluster analysis servers based on clustering and functional annotation algorithms implemented in R. Integrated functional analyses and interactive browsing of both, clustering structure and functional annotations provides a complete analytical environment for cluster analysis and interpretation of results. The Java Web Start client-based interface is modeled after the familiar cluster/treeview packages making its use intuitive to a wide array of biomedical researchers. For biomedical researchers, WebGimm provides an avenue to access state of the art clustering procedures. For Bioinformatics methods developers, WebGimm offers a convenient avenue to deploy their newly developed clustering methods. WebGimm server, software and manuals can be freely accessed at http://ClusterAnalysis.org/.

A logistic regression estimating function for spatial Gibbs point processes

DEFF Research Database (Denmark)

Baddeley, Adrian; Coeurjolly, Jean-François; Rubak, Ege

We propose a computationally efficient logistic regression estimating function for spatial Gibbs point processes. The sample points for the logistic regression consist of the observed point pattern together with a random pattern of dummy points. The estimating function is closely related to the p......We propose a computationally efficient logistic regression estimating function for spatial Gibbs point processes. The sample points for the logistic regression consist of the observed point pattern together with a random pattern of dummy points. The estimating function is closely related...

Creating biomaterials with spatially organized functionality.

Science.gov (United States)

Chow, Lesley W; Fischer, Jacob F

2016-05-01

Biomaterials for tissue engineering provide scaffolds to support cells and guide tissue regeneration. Despite significant advances in biomaterials design and fabrication techniques, engineered tissue constructs remain functionally inferior to native tissues. This is largely due to the inability to recreate the complex and dynamic hierarchical organization of the extracellular matrix components, which is intimately linked to a tissue's biological function. This review discusses current state-of-the-art strategies to control the spatial presentation of physical and biochemical cues within a biomaterial to recapitulate native tissue organization and function. © 2016 by the Society for Experimental Biology and Medicine.

Significance tests for functional data with complex dependence structure.

Science.gov (United States)

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.

Significance tests for functional data with complex dependence structure

KAUST Repository

Staicu, Ana-Maria

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.

Likelihood-based inference for clustered line transect data

DEFF Research Database (Denmark)

Waagepetersen, Rasmus Plenge; Schweder, Tore

The uncertainty in estimation of spatial animal density from line transect surveys depends on the degree of spatial clustering in the animal population. To quantify the clustering we model line transect data as independent thinnings of spatial shot-noise Cox processes. Likelihood-based inference...

Likelihood-based inference for clustered line transect data

DEFF Research Database (Denmark)

Waagepetersen, Rasmus; Schweder, Tore

2006-01-01

The uncertainty in estimation of spatial animal density from line transect surveys depends on the degree of spatial clustering in the animal population. To quantify the clustering we model line transect data as independent thinnings of spatial shot-noise Cox processes. Likelihood-based inference...

A spectral scheme for Kohn–Sham density functional theory of clusters

Energy Technology Data Exchange (ETDEWEB)

Banerjee, Amartya S., E-mail: baner041@umn.edu; Elliott, Ryan S., E-mail: relliott@umn.edu; James, Richard D., E-mail: james@umn.edu

2015-04-15

Starting from the observation that one of the most successful methods for solving the Kohn–Sham equations for periodic systems – the plane-wave method – is a spectral method based on eigenfunction expansion, we formulate a spectral method designed towards solving the Kohn–Sham equations for clusters. This allows for efficient calculation of the electronic structure of clusters (and molecules) with high accuracy and systematic convergence properties without the need for any artificial periodicity. The basis functions in this method form a complete orthonormal set and are expressible in terms of spherical harmonics and spherical Bessel functions. Computation of the occupied eigenstates of the discretized Kohn–Sham Hamiltonian is carried out using a combination of preconditioned block eigensolvers and Chebyshev polynomial filter accelerated subspace iterations. Several algorithmic and computational aspects of the method, including computation of the electrostatics terms and parallelization are discussed. We have implemented these methods and algorithms into an efficient and reliable package called ClusterES (Cluster Electronic Structure). A variety of benchmark calculations employing local and non-local pseudopotentials are carried out using our package and the results are compared to the literature. Convergence properties of the basis set are discussed through numerical examples. Computations involving large systems that contain thousands of electrons are demonstrated to highlight the efficacy of our methodology. The use of our method to study clusters with arbitrary point group symmetries is briefly discussed.

A spectral scheme for Kohn–Sham density functional theory of clusters

International Nuclear Information System (INIS)

Banerjee, Amartya S.; Elliott, Ryan S.; James, Richard D.

2015-01-01

Starting from the observation that one of the most successful methods for solving the Kohn–Sham equations for periodic systems – the plane-wave method – is a spectral method based on eigenfunction expansion, we formulate a spectral method designed towards solving the Kohn–Sham equations for clusters. This allows for efficient calculation of the electronic structure of clusters (and molecules) with high accuracy and systematic convergence properties without the need for any artificial periodicity. The basis functions in this method form a complete orthonormal set and are expressible in terms of spherical harmonics and spherical Bessel functions. Computation of the occupied eigenstates of the discretized Kohn–Sham Hamiltonian is carried out using a combination of preconditioned block eigensolvers and Chebyshev polynomial filter accelerated subspace iterations. Several algorithmic and computational aspects of the method, including computation of the electrostatics terms and parallelization are discussed. We have implemented these methods and algorithms into an efficient and reliable package called ClusterES (Cluster Electronic Structure). A variety of benchmark calculations employing local and non-local pseudopotentials are carried out using our package and the results are compared to the literature. Convergence properties of the basis set are discussed through numerical examples. Computations involving large systems that contain thousands of electrons are demonstrated to highlight the efficacy of our methodology. The use of our method to study clusters with arbitrary point group symmetries is briefly discussed

Uniform functional structure across spatial scales in an intertidal benthic assemblage.

Science.gov (United States)

Barnes, R S K; Hamylton, Sarah

2015-05-01

To investigate the causes of the remarkable similarity of emergent assemblage properties that has been demonstrated across disparate intertidal seagrass sites and assemblages, this study examined whether their emergent functional-group metrics are scale related by testing the null hypothesis that functional diversity and the suite of dominant functional groups in seagrass-associated macrofauna are robust structural features of such assemblages and do not vary spatially across nested scales within a 0.4 ha area. This was carried out via a lattice of 64 spatially referenced stations. Although densities of individual components were patchily dispersed across the locality, rank orders of importance of the 14 functional groups present, their overall functional diversity and evenness, and the proportions of the total individuals contained within each showed, in contrast, statistically significant spatial uniformity, even at areal scales functional groups in their geospatial context also revealed weaker than expected levels of spatial autocorrelation, and then only at the smaller scales and amongst the most dominant groups, and only a small number of negative correlations occurred between the proportional importances of the individual groups. In effect, such patterning was a surface veneer overlying remarkable stability of assemblage functional composition across all spatial scales. Although assemblage species composition is known to be homogeneous in some soft-sediment marine systems over equivalent scales, this combination of patchy individual components yet basically constant functional-group structure seems as yet unreported. Copyright © 2015 Elsevier Ltd. All rights reserved.

Simulation of the K-function in the analysis of spatial clustering for non-randomly distributed locations-Exemplified by bovine virus diarrhoea virus (BVDV) infection in Denmark

DEFF Research Database (Denmark)

Ersbøll, Annette Kjær; Ersbøll, Bjarne Kjær

2009-01-01

-infected (N-N+)). The differences between the empirical and the estimated null-hypothesis version of the K-function are plotted together with the 95% simulation envelopes versus the distance, h. In this way we test if the spatial distribution of the infected herds differs from the spatial distribution...

Theoretical stellar luminosity functions and globular cluster ages and compositions

International Nuclear Information System (INIS)

Ratcliff, S.J.

1985-01-01

The ages and chemical compositions of the stars in globular clusters are of great interest, particularly because age estimates from the well-known exercise of fitting observed color-magnitude diagrams to theoretical predictions tend to yield ages in excess of the Hubble time (an estimate to the age of the Universe) in standard cosmological models, for currently proposed high values of Hubble's constant (VandenBerg 1983). Relatively little use has been made of stellar luminosity functions of the globular clusters, for which reliable observations are now becoming available, to constrain the ages or compositions. The comparison of observed luminosity functions to theoretical ones allows one to take advantage of information not usually used, and has the advantage of being relatively insensitive to our lack of knowledge of the detailed structure of stellar envelopes and atmospheres. A computer program was developed to apply standard stellar evolutionary theory, using the most recently available input physics (opacities, nuclear reaction rates), to the calculation of the evolution of low-mass Population II stars. An algorithm for computing luminosity functions from the evolutionary tracks was applied to sets of tracks covering a broad range of chemical compositions and ages, such as may be expected for globular clusters

Density functional study of structural and electronic properties of bimetallic silver-gold clusters: Comparison with pure gold and silver clusters

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Bonacic-Koutecky, Vlasta; Burda, Jaroslav; Mitric, Roland; Ge, Maofa; Zampella, Giuseppe; Fantucci, Piercarlo

2002-08-01

Bimetallic silver-gold clusters offer an excellent opportunity to study changes in metallic versus "ionic" properties involving charge transfer as a function of the size and the composition, particularly when compared to pure silver and gold clusters. We have determined structures, ionization potentials, and vertical detachment energies for neutral and charged bimetallic AgmAun 3[less-than-or-equal](m+n)[less-than-or-equal]5 clusters. Calculated VDE values compare well with available experimental data. In the stable structures of these clusters Au atoms assume positions which favor the charge transfer from Ag atoms. Heteronuclear bonding is usually preferred to homonuclear bonding in clusters with equal numbers of hetero atoms. In fact, stable structures of neutral Ag2Au2, Ag3Au3, and Ag4Au4 clusters are characterized by the maximum number of hetero bonds and peripheral positions of Au atoms. Bimetallic tetramer as well as hexamer are planar and have common structural properties with corresponding one-component systems, while Ag4Au4 and Ag8 have 3D forms in contrast to Au8 which assumes planar structure. At the density functional level of theory we have shown that this is due to participation of d electrons in bonding of pure Aun clusters while s electrons dominate bonding in pure Agm as well as in bimetallic clusters. In fact, Aun clusters remain planar for larger sizes than Agm and AgnAun clusters. Segregation between two components in bimetallic systems is not favorable, as shown in the example of Ag5Au5 cluster. We have found that the structures of bimetallic clusters with 20 atoms Ag10Au10 and Ag12Au8 are characterized by negatively charged Au subunits embedded in Ag environment. In the latter case, the shape of Au8 is related to a pentagonal bipyramid capped by one atom and contains three exposed negatively charged Au atoms. They might be suitable for activating reactions relevant to catalysis. According to our findings the charge transfer in bimetallic

Regional zooplankton dispersal provides spatial insurance for ecosystem function.

Science.gov (United States)

Symons, Celia C; Arnott, Shelley E

2013-05-01

Changing environmental conditions are affecting diversity and ecosystem function globally. Theory suggests that dispersal from a regional species pool may buffer against changes in local community diversity and ecosystem function after a disturbance through the establishment of functionally redundant tolerant species. The spatial insurance provided by dispersal may decrease through time after environmental change as the local community monopolizes resources and reduces community invasibility. To test for evidence of the spatial insurance hypothesis and to determine the role dispersal timing plays in this response we conducted a field experiment using crustacean zooplankton communities in a subarctic region that is expected to be highly impacted by climate change - Churchill, Canada. Three experiments were conducted where nutrients, salt, and dispersal were manipulated. The three experiments differed in time-since-disturbance that the dispersers were added. We found that coarse measures of diversity (i.e. species richness, evenness, and Shannon-Weiner diversity) were generally resistant to large magnitude disturbances, and that dispersal had the most impact on diversity when dispersers were added shortly after disturbance. Ecosystem functioning (chl-a) was degraded in disturbed communities, but dispersal recovered ecosystem function to undisturbed levels. This spatial insurance for ecosystem function was mediated through changes in community composition and the relative abundance of functional groups. Results suggest that regional diversity and habitat connectivity will be important in the future to maintain ecosystem function by introducing functionally redundant species to promote compensatory dynamics. © 2012 Blackwell Publishing Ltd.

The food, GI tract functionality and human health cluster

NARCIS (Netherlands)

Mattila-Sandholm, T.; Blaut, M.; Daly, C.; Vuyst, de L.; Dore, J.; Gibson, G.; Goossens, H.; Knorr, D.; Lucas, J.; Lahteenmaki, L.; Mercenier, A.M.E.; Saarela, M.; Shanahan, F.; Vos, de W.M.

2002-01-01

The Food, GI-tract Functionality and Human Health (PROEUHEALTH) Cluster brings together eight complementary, multicentre interdisciplinary research projects. All have the common aim of improving the health and quality of life of European comsumers. The collaboration involves 64 different research

Spatial clustering of Borrelia burgdorferi sensu lato within populations of Allen's chipmunks and dusky-footed woodrats in northwestern California.

Science.gov (United States)

Hacker, Gregory M; Brown, Richard N; Fedorova, Natalia; Girard, Yvette A; Higley, Mark; Clueit, Bernadette; Lane, Robert S

2018-01-01

The ecology of Lyme borreliosis is complex in northwestern California, with several potential reservoir hosts, tick vectors, and genospecies of Borrelia burgdorferi sensu lato. The primary objective of this study was to determine the fine-scale spatial distribution of different genospecies in four rodent species, the California ground squirrel (Otospermophilus beecheyi), northern flying squirrel (Glaucomys sabrinus), dusky-footed woodrat (Neotoma fuscipes), and Allen's chipmunk (Neotamias senex). Rodents were live-trapped between June 2004 and May 2005 at the Hoopa Valley Tribal Reservation (HVTR) in Humboldt County, California. Ear-punch biopsies obtained from each rodent were tested by polymerase chain reaction (PCR) and sequencing analysis. The programs ArcGIS and SaTScan were used to examine the spatial distribution of genospecies. Multinomial log-linear models were used to model habitat and host-specific characteristics and their effect on the presence of each borrelial genospecies. The Akaike information criterion (AICc) was used to compare models and determine model fit. Borrelia burgdorferi sensu stricto was primarily associated with chipmunks and B. bissettiae largely with woodrats. The top model included the variables "host species", "month", and "elevation" (weight = 0.84). Spatial clustering of B. bissettiae was detected in the northwestern section of the HVTR, whereas B. burgdorferi sensu stricto was clustered in the southeastern section. We conclude that the spatial distribution of these borreliae are driven at least in part by host species, time-of-year, and elevation.

Using Spatial Semantics and Interactions to Identify Urban Functional Regions

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Yandong Wang

2018-03-01

Full Text Available The spatial structures of cities have changed dramatically with rapid socio-economic development in ways that are not well understood. To support urban structural analysis and rational planning, we propose a framework to identify urban functional regions and quantitatively explore the intensity of the interactions between them, thus increasing the understanding of urban structures. A method for the identification of functional regions via spatial semantics is proposed, which involves two steps: (1 the study area is classified into three types of functional regions using taxi origin/destination (O/D flows; and (2 the spatial semantics for the three types of functional regions are demonstrated based on point-of-interest (POI categories. To validate the existence of urban functional regions, we explored the intensity of interactions quantitatively between them. A case study using POI data and taxi trajectory data from Beijing validates the proposed framework. The results show that the proposed framework can be used to identify urban functional regions and promotes an enhanced understanding of urban structures.

Approximate inference for spatial functional data on massively parallel processors

DEFF Research Database (Denmark)

Raket, Lars Lau; Markussen, Bo

2014-01-01

With continually increasing data sizes, the relevance of the big n problem of classical likelihood approaches is greater than ever. The functional mixed-effects model is a well established class of models for analyzing functional data. Spatial functional data in a mixed-effects setting...... in linear time. An extremely efficient GPU implementation is presented, and the proposed methods are illustrated by conducting a classical statistical analysis of 2D chromatography data consisting of more than 140 million spatially correlated observation points....

Statistical indicators of collective behavior and functional clusters in gene networks of yeast

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Živković, J.; Tadić, B.; Wick, N.; Thurner, S.

2006-03-01

We analyze gene expression time-series data of yeast (S. cerevisiae) measured along two full cell-cycles. We quantify these data by using q-exponentials, gene expression ranking and a temporal mean-variance analysis. We construct gene interaction networks based on correlation coefficients and study the formation of the corresponding giant components and minimum spanning trees. By coloring genes according to their cell function we find functional clusters in the correlation networks and functional branches in the associated trees. Our results suggest that a percolation point of functional clusters can be identified on these gene expression correlation networks.

Nearest Neighbor Networks: clustering expression data based on gene neighborhoods

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Olszewski Kellen L

2007-07-01

Full Text Available Abstract Background The availability of microarrays measuring thousands of genes simultaneously across hundreds of biological conditions represents an opportunity to understand both individual biological pathways and the integrated workings of the cell. However, translating this amount of data into biological insight remains a daunting task. An important initial step in the analysis of microarray data is clustering of genes with similar behavior. A number of classical techniques are commonly used to perform this task, particularly hierarchical and K-means clustering, and many novel approaches have been suggested recently. While these approaches are useful, they are not without drawbacks; these methods can find clusters in purely random data, and even clusters enriched for biological functions can be skewed towards a small number of processes (e.g. ribosomes. Results We developed Nearest Neighbor Networks (NNN, a graph-based algorithm to generate clusters of genes with similar expression profiles. This method produces clusters based on overlapping cliques within an interaction network generated from mutual nearest neighborhoods. This focus on nearest neighbors rather than on absolute distance measures allows us to capture clusters with high connectivity even when they are spatially separated, and requiring mutual nearest neighbors allows genes with no sufficiently similar partners to remain unclustered. We compared the clusters generated by NNN with those generated by eight other clustering methods. NNN was particularly successful at generating functionally coherent clusters with high precision, and these clusters generally represented a much broader selection of biological processes than those recovered by other methods. Conclusion The Nearest Neighbor Networks algorithm is a valuable clustering method that effectively groups genes that are likely to be functionally related. It is particularly attractive due to its simplicity, its success in the

Two-step estimation for inhomogeneous spatial point processes

DEFF Research Database (Denmark)

Waagepetersen, Rasmus; Guan, Yongtao

This paper is concerned with parameter estimation for inhomogeneous spatial point processes with a regression model for the intensity function and tractable second order properties (K-function). Regression parameters are estimated using a Poisson likelihood score estimating function and in a second...... step minimum contrast estimation is applied for the residual clustering parameters. Asymptotic normality of parameter estimates is established under certain mixing conditions and we exemplify how the results may be applied in ecological studies of rain forests....

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

Science.gov (United States)

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

2016-02-19

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

Constraints on Ωm and σ8 from the potential-based cluster temperature function

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Angrick, Christian; Pace, Francesco; Bartelmann, Matthias; Roncarelli, Mauro

2015-12-01

The abundance of galaxy clusters is in principle a powerful tool to constrain cosmological parameters, especially Ωm and σ8, due to the exponential dependence in the high-mass regime. While the best observables are the X-ray temperature and luminosity, the abundance of galaxy clusters, however, is conventionally predicted as a function of mass. Hence, the intrinsic scatter and the uncertainties in the scaling relations between mass and either temperature or luminosity lower the reliability of galaxy clusters to constrain cosmological parameters. In this article, we further refine the X-ray temperature function for galaxy clusters by Angrick et al., which is based on the statistics of perturbations in the cosmic gravitational potential and proposed to replace the classical mass-based temperature function, by including a refined analytic merger model and compare the theoretical prediction to results from a cosmological hydrodynamical simulation. Although we find already a good agreement if we compare with a cluster temperature function based on the mass-weighted temperature, including a redshift-dependent scaling between mass-based and spectroscopic temperature yields even better agreement between theoretical model and numerical results. As a proof of concept, incorporating this additional scaling in our model, we constrain the cosmological parameters Ωm and σ8 from an X-ray sample of galaxy clusters and tentatively find agreement with the recent cosmic microwave background based results from the Planck mission at 1σ-level.

Spatial access method for urban geospatial database management: An efficient approach of 3D vector data clustering technique

DEFF Research Database (Denmark)

Azri, Suhaibah; Ujang, Uznir; Rahman, Alias Abdul

2014-01-01

In the last few years, 3D urban data and its information are rapidly increased due to the growth of urban area and urbanization phenomenon. These datasets are then maintain and manage in 3D spatial database system. However, performance deterioration is likely to happen due to the massiveness of 3D...... datasets. As a solution, 3D spatial index structure is used as a booster to increase the performance of data retrieval. In commercial database, commonly and widely used index structure for 3D spatial database is 3D R-Tree. This is due to its simplicity and promising method in handling spatial data. However......D geospatial data clustering to be used in the construction of 3D R-Tree and respectively could reduce the overlapping among nodes. The proposed method is tested on 3D urban dataset for the application of urban infill development. By using several cases of data updating operations such as building...

Density functional theory and surface reactivity study of bimetallic AgnYm (n+m = 10) clusters

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Hussain, Riaz; Hussain, Abdullah Ijaz; Chatha, Shahzad Ali Shahid; Hussain, Riaz; Hanif, Usman; Ayub, Khurshid

2018-06-01

Density functional theory calculations have been performed on pure silver (Agn), yttrium (Ym) and bimetallic silver yttrium clusters AgnYm (n + m = 2-10) for reactivity descriptors in order to realize sites for nucleophilic and electrophilic attack. The reactivity descriptors of the clusters, studied as a function of cluster size and shape, reveal the presence of different type of reactive sites in a cluster. The size and shape of the pure silver, yttrium and bimetallic silver yttrium cluster (n = 2-10) strongly influences the number and position of active sites for an electrophilic and/or nucleophilic attack. The trends of reactivities through reactivity descriptors are confirmed through comparison with experimental data for CO binding with silver clusters. Moreover, the adsorption of CO on bimetallic silver yttrium clusters is also evaluated. The trends of binding energies support the reactivity descriptors values. Doping of pure cluster with the other element also influence the hardness, softness and chemical reactivity of the clusters. The softness increases as we increase the number of silver atoms in the cluster, whereas the hardness decreases. The chemical reactivity increases with silver doping whereas it decreases by increasing yttrium concentration. Silver atoms are nucleophilic in small clusters but changed to electrophilic in large clusters.

Managing distance and covariate information with point-based clustering

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Peter A. Whigham

2016-09-01

Full Text Available Abstract Background Geographic perspectives of disease and the human condition often involve point-based observations and questions of clustering or dispersion within a spatial context. These problems involve a finite set of point observations and are constrained by a larger, but finite, set of locations where the observations could occur. Developing a rigorous method for pattern analysis in this context requires handling spatial covariates, a method for constrained finite spatial clustering, and addressing bias in geographic distance measures. An approach, based on Ripley’s K and applied to the problem of clustering with deliberate self-harm (DSH, is presented. Methods Point-based Monte-Carlo simulation of Ripley’s K, accounting for socio-economic deprivation and sources of distance measurement bias, was developed to estimate clustering of DSH at a range of spatial scales. A rotated Minkowski L1 distance metric allowed variation in physical distance and clustering to be assessed. Self-harm data was derived from an audit of 2 years’ emergency hospital presentations (n = 136 in a New Zealand town (population ~50,000. Study area was defined by residential (housing land parcels representing a finite set of possible point addresses. Results Area-based deprivation was spatially correlated. Accounting for deprivation and distance bias showed evidence for clustering of DSH for spatial scales up to 500 m with a one-sided 95 % CI, suggesting that social contagion may be present for this urban cohort. Conclusions Many problems involve finite locations in geographic space that require estimates of distance-based clustering at many scales. A Monte-Carlo approach to Ripley’s K, incorporating covariates and models for distance bias, are crucial when assessing health-related clustering. The case study showed that social network structure defined at the neighbourhood level may account for aspects of neighbourhood clustering of DSH. Accounting for

Spatially Selective Functionalization of Conducting Polymers by "Electroclick" Chemistry

DEFF Research Database (Denmark)

Hansen, Thomas Steen; Daugaard, Anders Egede; Hvilsted, Søren

2009-01-01

Conducting polymer microelectrodes can electrochemically generate the catalyst required for their own functionalization by "click chemistry" with high spatial resolution. Interdigitated microelectrodes prepared from an azide-containing conducting polymer are selectively functionalized in sequence...

Burstiness in Viral Bursts: How Stochasticity Affects Spatial Patterns in Virus-Microbe Dynamics

Science.gov (United States)

Lin, Yu-Hui; Taylor, Bradford P.; Weitz, Joshua S.

Spatial patterns emerge in living systems at the scale of microbes to metazoans. These patterns can be driven, in part, by the stochasticity inherent to the birth and death of individuals. For microbe-virus systems, infection and lysis of hosts by viruses results in both mortality of hosts and production of viral progeny. Here, we study how variation in the number of viral progeny per lysis event affects the spatial clustering of both viruses and microbes. Each viral ''burst'' is initially localized at a near-cellular scale. The number of progeny in a single lysis event can vary in magnitude between tens and thousands. These perturbations are not accounted for in mean-field models. Here we developed individual-based models to investigate how stochasticity affects spatial patterns in virus-microbe systems. We measured the spatial clustering of individuals using pair correlation functions. We found that increasing the burst size of viruses while maintaining the same production rate led to enhanced clustering. In this poster we also report on preliminary analysis on the evolution of the burstiness of viral bursts given a spatially distributed host community.

Spatial-temporal cluster analysis of mortality from road traffic injuries using geographic information systems in West of Iran during 2009-2014.

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Zangeneh, Alireza; Najafi, Farid; Karimi, Saeed; Saeidi, Shahram; Izadi, Neda

2018-04-01

Road traffic injuries (RTIs) are considered as one of the most important health problems endangering people's life. The examination of the geographical distribution of RTIs could help policymakers in better planning to reduce RTIs. This study, therefore, aimed to determine the spatial-temporal clustering of mortality from RTIs in West of Iran. Deaths from RTIs, registered in Forensic Medicine Organization of Kermanshah province over a period of six years (2009-2014), were used. Using negative binomial regression, the mortality trend was investigated. In order to investigate the spatial distribution of RTIs, we used ArcGIS. (Version 10.3). The median age of the 3231 people died in RTIs was 37 (IQR = 31) year, 78.4% were male. The 6-year average mortality rate from RTIs was 27.8/100,000 deaths, and the average rate had a declining trend. The dispersion of RTIs showed that most deaths occurred in Kermanshah, Islamabad, Bisotun, and Harsin road axes, respectively. The mean center of all deaths from RTIs occurred in Kermanshah province, the central area of Kermanshah district. The spatial trend of such deaths has moved to the northeast-southwest, and such deaths were geographically centralized. Results of Moran's I with respect to cluster analysis also indicated positive spatial autocorrelations. The results showed that the mortality rate from RTIs, despite the decline in recent years, is still high when compared with other countries. The clustering of accidents raises the concern that road infrastructure in certain locations may also be a factor. Regarding the results related to the temporal analysis, it is suggested that the enforcement of traffic rules be stricter at rush hours. Copyright © 2018 Elsevier Ltd and Faculty of Forensic and Legal Medicine. All rights reserved.

Defective functional connectivity between posterior hypothalamus and regions of the diencephalic-mesencephalic junction in chronic cluster headache.

Science.gov (United States)

Ferraro, Stefania; Nigri, Anna; Bruzzone, Maria Grazia; Brivio, Luca; Proietti Cecchini, Alberto; Verri, Mattia; Chiapparini, Luisa; Leone, Massimo

2018-01-01

Objective We tested the hypothesis of a defective functional connectivity between the posterior hypothalamus and diencephalic-mesencephalic regions in chronic cluster headache based on: a) clinical and neuro-endocrinological findings in cluster headache patients; b) neuroimaging findings during cluster headache attacks; c) neuroimaging findings in drug-refractory chronic cluster headache patients improved after successful deep brain stimulation. Methods Resting state functional magnetic resonance imaging, associated with a seed-based approach, was employed to investigate the functional connectivity of the posterior hypothalamus in chronic cluster headache patients (n = 17) compared to age and sex-matched healthy subjects (n = 16). Random-effect analyses were performed to study differences between patients and controls in ipsilateral and contralateral-to-the-pain posterior hypothalamus functional connectivity. Results Cluster headache patients showed an increased functional connectivity between the ipsilateral posterior hypothalamus and a number of diencephalic-mesencephalic structures, comprising ventral tegmental area, dorsal nuclei of raphe, and bilateral substantia nigra, sub-thalamic nucleus, and red nucleus ( p cluster headache patients mainly involves structures that are part of (i.e. ventral tegmental area, substantia nigra) or modulate (dorsal nuclei of raphe, sub-thalamic nucleus) the midbrain dopaminergic systems. The midbrain dopaminergic systems could play a role in cluster headache pathophysiology and in particular in the chronicization process. Future studies are needed to better clarify if this finding is specific to cluster headache or if it represents an unspecific response to chronic pain.

Modulated modularity clustering as an exploratory tool for functional genomic inference.

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Eric A Stone

2009-05-01

Full Text Available In recent years, the advent of high-throughput assays, coupled with their diminishing cost, has facilitated a systems approach to biology. As a consequence, massive amounts of data are currently being generated, requiring efficient methodology aimed at the reduction of scale. Whole-genome transcriptional profiling is a standard component of systems-level analyses, and to reduce scale and improve inference clustering genes is common. Since clustering is often the first step toward generating hypotheses, cluster quality is critical. Conversely, because the validation of cluster-driven hypotheses is indirect, it is critical that quality clusters not be obtained by subjective means. In this paper, we present a new objective-based clustering method and demonstrate that it yields high-quality results. Our method, modulated modularity clustering (MMC, seeks community structure in graphical data. MMC modulates the connection strengths of edges in a weighted graph to maximize an objective function (called modularity that quantifies community structure. The result of this maximization is a clustering through which tightly-connected groups of vertices emerge. Our application is to systems genetics, and we quantitatively compare MMC both to the hierarchical clustering method most commonly employed and to three popular spectral clustering approaches. We further validate MMC through analyses of human and Drosophila melanogaster expression data, demonstrating that the clusters we obtain are biologically meaningful. We show MMC to be effective and suitable to applications of large scale. In light of these features, we advocate MMC as a standard tool for exploration and hypothesis generation.

Contextual Learning Induces Dendritic Spine Clustering in Retrosplenial Cortex

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Adam C Frank

2014-03-01

Full Text Available Molecular and electrophysiological studies find convergent evidence suggesting that plasticity within a dendritic tree is not randomly dispersed, but rather clustered into functional groups. Further, results from in silico neuronal modeling show that clustered plasticity is able to increase storage capacity 45 times compared to dispersed plasticity. Recent in vivo work utilizing chronic 2-photon microscopy tested the clustering hypothesis and showed that repetitive motor learning is able to induce clustered addition of new dendritic spines on apical dendrites of L5 neurons in primary motor cortex; moreover, clustered spines were found to be more stable than non-clustered spines, suggesting a physiological role for spine clustering. To further test this hypothesis we used in vivo 2-photon imaging in Thy1-YFP-H mice to chronically examine dendritic spine dynamics in retrosplenial cortex (RSC during spatial learning. RSC is a key component of an extended spatial learning and memory circuit that includes hippocampus and entorhinal cortex. Importantly, RSC is known from both lesion and immediate early gene studies to be critically involved in spatial learning and more specifically in contextual fear conditioning. We utilized a modified contextual fear conditioning protocol wherein animals received a mild foot shock each day for five days; this protocol induces gradual increases in context freezing over several days before the animals reach a behavioral plateau. We coupled behavioral training with four separate in vivo imaging sessions, two before training begins, one early in training, and a final session after training is complete. This allowed us to image spine dynamics before training as well as early in learning and after animals had reached behavioral asymptote. We find that this contextual learning protocol induces a statistically significant increase in the formation of clusters of new dendritic spines in trained animals when compared to home

Cluster analysis of typhoid cases in Kota Bharu, Kelantan, Malaysia

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Nazarudin Safian

2008-09-01

Full Text Available Typhoid fever is still a major public health problem globally as well as in Malaysia. This study was done to identify the spatial epidemiology of typhoid fever in the Kota Bharu District of Malaysia as a first step to developing more advanced analysis of the whole country. The main characteristic of the epidemiological pattern that interested us was whether typhoid cases occurred in clusters or whether they were evenly distributed throughout the area. We also wanted to know at what spatial distances they were clustered. All confirmed typhoid cases that were reported to the Kota Bharu District Health Department from the year 2001 to June of 2005 were taken as the samples. From the home address of the cases, the location of the house was traced and a coordinate was taken using handheld GPS devices. Spatial statistical analysis was done to determine the distribution of typhoid cases, whether clustered, random or dispersed. The spatial statistical analysis was done using CrimeStat III software to determine whether typhoid cases occur in clusters, and later on to determine at what distances it clustered. From 736 cases involved in the study there was significant clustering for cases occurring in the years 2001, 2002, 2003 and 2005. There was no significant clustering in year 2004. Typhoid clustering also occurred strongly for distances up to 6 km. This study shows that typhoid cases occur in clusters, and this method could be applicable to describe spatial epidemiology for a specific area. (Med J Indones 2008; 17: 175-82Keywords: typhoid, clustering, spatial epidemiology, GIS

The Pattern of Spatially Concentrated Industries in East Germany - A Contribution to the Discussion on Economic “Clusters“

OpenAIRE

Martin T.W. Rosenfeld; Peter Franz; Gerhard Heimpold

2005-01-01

Throughout the literature in regional economics, most authors agree that spatially concentrated industrial activities are important for regional economic growth. Agglomeration economies, which may occur in the context of spatial concentration and “clusters“, may lead to lower costs of production and may reduce transaction costs of all kind, e. g. information costs, including the costs for R&D activities. There is much less agreement on (and: knowledge about) the empirical identification of ...

Effect of functionalization of boron nitride flakes by main group metal clusters on their optoelectronic properties

Science.gov (United States)

Chakraborty, Debdutta; Chattaraj, Pratim Kumar

2017-10-01

The possibility of functionalizing boron nitride flakes (BNFs) with some selected main group metal clusters, viz. OLi4, NLi5, CLi6, BLI7 and Al12Be, has been analyzed with the aid of density functional theory (DFT) based computations. Thermochemical as well as energetic considerations suggest that all the metal clusters interact with the BNF moiety in a favorable fashion. As a result of functionalization, the static (first) hyperpolarizability (β ) values of the metal cluster supported BNF moieties increase quite significantly as compared to that in the case of pristine BNF. Time dependent DFT analysis reveals that the metal clusters can lower the transition energies associated with the dominant electronic transitions quite significantly thereby enabling the metal cluster supported BNF moieties to exhibit significant non-linear optical activity. Moreover, the studied systems demonstrate broad band absorption capability spanning the UV-visible as well as infra-red domains. Energy decomposition analysis reveals that the electrostatic interactions principally stabilize the metal cluster supported BNF moieties.

Two-step estimation for inhomogeneous spatial point processes

DEFF Research Database (Denmark)

Waagepetersen, Rasmus; Guan, Yongtao

2009-01-01

The paper is concerned with parameter estimation for inhomogeneous spatial point processes with a regression model for the intensity function and tractable second-order properties (K-function). Regression parameters are estimated by using a Poisson likelihood score estimating function and in the ...... and in the second step minimum contrast estimation is applied for the residual clustering parameters. Asymptotic normality of parameter estimates is established under certain mixing conditions and we exemplify how the results may be applied in ecological studies of rainforests....

A spatial scan statistic for compound Poisson data.

Science.gov (United States)

Rosychuk, Rhonda J; Chang, Hsing-Ming

2013-12-20

The topic of spatial cluster detection gained attention in statistics during the late 1980s and early 1990s. Effort has been devoted to the development of methods for detecting spatial clustering of cases and events in the biological sciences, astronomy and epidemiology. More recently, research has examined detecting clusters of correlated count data associated with health conditions of individuals. Such a method allows researchers to examine spatial relationships of disease-related events rather than just incident or prevalent cases. We introduce a spatial scan test that identifies clusters of events in a study region. Because an individual case may have multiple (repeated) events, we base the test on a compound Poisson model. We illustrate our method for cluster detection on emergency department visits, where individuals may make multiple disease-related visits. Copyright © 2013 John Wiley & Sons, Ltd.

Clustering Trajectories by Relevant Parts for Air Traffic Analysis.

Science.gov (United States)

Andrienko, Gennady; Andrienko, Natalia; Fuchs, Georg; Garcia, Jose Manuel Cordero

2018-01-01

Clustering of trajectories of moving objects by similarity is an important technique in movement analysis. Existing distance functions assess the similarity between trajectories based on properties of the trajectory points or segments. The properties may include the spatial positions, times, and thematic attributes. There may be a need to focus the analysis on certain parts of trajectories, i.e., points and segments that have particular properties. According to the analysis focus, the analyst may need to cluster trajectories by similarity of their relevant parts only. Throughout the analysis process, the focus may change, and different parts of trajectories may become relevant. We propose an analytical workflow in which interactive filtering tools are used to attach relevance flags to elements of trajectories, clustering is done using a distance function that ignores irrelevant elements, and the resulting clusters are summarized for further analysis. We demonstrate how this workflow can be useful for different analysis tasks in three case studies with real data from the domain of air traffic. We propose a suite of generic techniques and visualization guidelines to support movement data analysis by means of relevance-aware trajectory clustering.

Seismogenic structure behaviour revealed by spatial clustering of seismicity in the Umbria-Marche Region (Central Italy

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P. Tosi

1998-06-01

Full Text Available Time variations in the spatial distribution of earthquake epicentres are analyzed by application of the fractal correlation dimension method. The zone under investigation is located in Central Italy, bounded in longitude by 12.0 and 14.4 degrees east and in latitude by 42.0 and 43.6 degrees north. From 1st January 1978 to 5th October 1997, 2028 events with a magnitude above Ml= 2.5 constitute the database.Evolution of the spatial fractal dimension Ds permits the identification of seismic cycles that are connected to the occurrence of main earthquakes.In particular, it is possible to recognize a division within each cycle, between a period of random background seismicity and a spatial clustering of events where shocks of magnitude Ml ³occur. Moreover, the decrease in Ds prior to such events, evidences a structural relationship between foreshocks and the occurrence of a main shock, even if not in close territorial proximity.This feature indicates a new, more extensive definition of seismogenic structure which can includes several interconnected structures within a large area.

Spatial memory and hippocampal function: Where are we now?

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Mark Good

2002-01-01

Full Text Available The main aim of this paper is to provide an overview of current debates concerning the role of the mammalian hippocampus in learning with a particular emphasis on spatial learning. The review discusses recent debates on (1 the role of the primate hippocampus in recognition memory and object-in-place memory, (2 the role of the hippocampus in spatial navigation in both rats and humans, and (3 the effects of hippocampal damage on processing contextual information. Evidence from these lines of research have led many current theories to posit a function for the hippocampus that has as its organizing principle the association or binding of stimulus representations. Based on this principle, recent theories of hippocampal function have extended their application beyond the spatial domain to capture features of declarative and episodic memory processes.

Noise reduction and functional maps image quality improvement in dynamic CT perfusion using a new k-means clustering guided bilateral filter (KMGB).

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Pisana, Francesco; Henzler, Thomas; Schönberg, Stefan; Klotz, Ernst; Schmidt, Bernhard; Kachelrieß, Marc

2017-07-01

Dynamic CT perfusion (CTP) consists in repeated acquisitions of the same volume in different time steps, slightly before, during and slightly afterwards the injection of contrast media. Important functional information can be derived for each voxel, which reflect the local hemodynamic properties and hence the metabolism of the tissue. Different approaches are being investigated to exploit data redundancy and prior knowledge for noise reduction of such datasets, ranging from iterative reconstruction schemes to high dimensional filters. We propose a new spatial bilateral filter which makes use of the k-means clustering algorithm and of an optimal calculated guiding image. We named the proposed filter as k-means clustering guided bilateral filter (KMGB). In this study, the KMGB filter is compared with the partial temporal non-local means filter (PATEN), with the time-intensity profile similarity (TIPS) filter, and with a new version derived from it, by introducing the guiding image (GB-TIPS). All the filters were tested on a digital in-house developed brain CTP phantom, were noise was added to simulate 80 kV and 200 mAs (default scanning parameters), 100 mAs and 30 mAs. Moreover, the filters performances were tested on 7 noisy clinical datasets with different pathologies in different body regions. The original contribution of our work is two-fold: first we propose an efficient algorithm to calculate a guiding image to improve the results of the TIPS filter, secondly we propose the introduction of the k-means clustering step and demonstrate how this can potentially replace the TIPS part of the filter obtaining better results at lower computational efforts. As expected, in the GB-TIPS, the introduction of the guiding image limits the over-smoothing of the TIPS filter, improving spatial resolution by more than 50%. Furthermore, replacing the time-intensity profile similarity calculation with a fuzzy k-means clustering strategy (KMGB) allows to control the edge preserving

Isomers of Cu6 cluster: a density function theory study

International Nuclear Information System (INIS)

Jia Yanhui; Wang Shanshan; Li Gongping

2008-01-01

The possible structure of Cu 6 cluster has been given with the GaussView that is a graphical user interface software. The structure optimization was performed on the B3LYP functional and SDD basic set of the quantum computational software of Gaussian03. And eight isomers of Cu 6 cluster were calculated. The binding energy and the structure of eight isomers have been investigated in detail. The result showed that the value of the binding energy was in reasonable agreement with available experimental data, as well as with other theoretical results, and the most stable structure was the triangle of plane. Three new isomers of the Cu 6 cluster have been got in our work, which would be the valuable data for the further theoretical and experimental study. (authors)

Effect of Spatial Alignment Transformations in PCA and ICA of Functional Neuroimages

DEFF Research Database (Denmark)

Lukic, Ana S.; Wernick, Miles N.; Yang, Yongui

2007-01-01

this observation is true, not only for spatial ICA, but also for temporal ICA and for principal component analysis (PCA). In each case we find conditions that the spatial alignment operator must satisfy to ensure invariance of the results. We illustrate our findings using functional magnetic-resonance imaging (f......It has been previously observed that spatial independent component analysis (ICA), if applied to data pooled in a particular way, may lessen the need for spatial alignment of scans in a functional neuroimaging study. In this paper we seek to determine analytically the conditions under which...

Spatial Statistics and Spatio-Temporal Data Covariance Functions and Directional Properties

CERN Document Server

Sherman, Michael

2010-01-01

In the spatial or space-time context, specifying the correct covariance function is important to obtain efficient predictions and to understand the underlying physical process of interest. There have been several books in recent years in the general area of spatial statistics. This book focuses on covariance and variogram functions, their role in prediction, and the proper choice of these functions in data applications. Presenting recent methods from 2004-2007 alongside more established methodology of assessing the usual assumptions on such functions such as isotropy, separability and symmetry

Joint entropy for space and spatial frequency domains estimated from psychometric functions of achromatic discrimination.

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Silveira, Vladímir de Aquino; Souza, Givago da Silva; Gomes, Bruno Duarte; Rodrigues, Anderson Raiol; Silveira, Luiz Carlos de Lima

2014-01-01

We used psychometric functions to estimate the joint entropy for space discrimination and spatial frequency discrimination. Space discrimination was taken as discrimination of spatial extent. Seven subjects were tested. Gábor functions comprising unidimensionalsinusoidal gratings (0.4, 2, and 10 cpd) and bidimensionalGaussian envelopes (1°) were used as reference stimuli. The experiment comprised the comparison between reference and test stimulithat differed in grating's spatial frequency or envelope's standard deviation. We tested 21 different envelope's standard deviations around the reference standard deviation to study spatial extent discrimination and 19 different grating's spatial frequencies around the reference spatial frequency to study spatial frequency discrimination. Two series of psychometric functions were obtained for 2%, 5%, 10%, and 100% stimulus contrast. The psychometric function data points for spatial extent discrimination or spatial frequency discrimination were fitted with Gaussian functions using the least square method, and the spatial extent and spatial frequency entropies were estimated from the standard deviation of these Gaussian functions. Then, joint entropy was obtained by multiplying the square root of space extent entropy times the spatial frequency entropy. We compared our results to the theoretical minimum for unidimensional Gábor functions, 1/4π or 0.0796. At low and intermediate spatial frequencies and high contrasts, joint entropy reached levels below the theoretical minimum, suggesting non-linear interactions between two or more visual mechanisms. We concluded that non-linear interactions of visual pathways, such as the M and P pathways, could explain joint entropy values below the theoretical minimum at low and intermediate spatial frequencies and high contrasts. These non-linear interactions might be at work at intermediate and high contrasts at all spatial frequencies once there was a substantial decrease in joint

Structure and Stability of GeAun, n = 1-10 clusters: A Density Functional Study

International Nuclear Information System (INIS)

Priyanka,; Dharamvir, Keya; Sharma, Hitesh

2011-01-01

The structures of Germanium doped gold clusters GeAu n (n = 1-10) have been investigated using ab initio calculations based on density functional theory (DFT). We have obtained ground state geometries of GeAu n clusters and have it compared with Silicon doped gold clusters and pure gold clusters. The ground state geometries of the GeAu n clusters show patterns similar to silicon doped gold clusters except for n = 5, 6 and 9. The introduction of germanium atom increases the binding energy of gold clusters. The binding energy per atom of germanium doped cluster is smaller than the corresponding silicon doped gold cluster. The HUMO-LOMO gap for Au n Ge clusters have been found to vary between 0.46 eV-2.09 eV. The mullikan charge analysis indicates that charge of order of 0.1e always transfers from germanium atom to gold atom.

Transfer function synthesis for reactor spatial dynamics using the modal approach

Energy Technology Data Exchange (ETDEWEB)

Guppy, C B [Control and Instrumentation Division, Atomic Energy Establishment, Winfrith, Dorchester, Dorset (United Kingdom)

1962-08-15

Techniques are developed below which will enable the construction of transfer functions relating changes in variables such as power or neutron flux with reactivity perturbations when there is a need for taking into account spatial effects within a reactor. Initially each of the transfer functions derived comprises the sum of a series of harmonics each of which has a laplace transform with associated spatial eigenfunction. Series of this kind can then be reduced to pure polynomial form (numerators on denominators) the coefficients of which have implicit allowance for spatial effects. The existence of large reactors having several independent controllers make necessary knowledge of transfer functions of this form. The technique will allow the characteristics of each controlled sector to be obtained as well as the characteristics of the complete control system with its couplings through the reactor core. In addition, the developing use of frequency response testing of reactors makes necessary a knowledge of the spatial behaviour to be expected of a reactor under test. (author)

Regionalizing Aquatic Ecosystems Based on the River Subbasin Taxonomy Concept and Spatial Clustering Techniques

Directory of Open Access Journals (Sweden)

Jiahu Zhao

2011-11-01

Full Text Available Aquatic ecoregions were increasingly used as spatial units for aquatic ecosystem management at the watershed scale. In this paper, the principle of including land area, comprehensiveness and dominance, conjugation and hierarchy were selected as regionalizing principles. Elevation and drainage density were selected as the regionalizing indicators for the delineation of level I aquatic ecoregions, and percent of construction land area, percent of cultivated land area, soil type and slope for the level II. Under the support of GIS technology, the spatial distribution maps of the two indicators for level I and the four indicators for level II aquatic ecoregion delineation were generated from the raster data based on the 1,107 subwatersheds. River subbasin taxonomy concept, two-step spatial clustering analysis approach and manual-assisted method were used to regionalize aquatic ecosystems in the Taihu Lake watershed. Then the Taihu Lake watershed was divided into two level I aquatic ecoregions, including Ecoregion I1 and Ecoregion I2, and five level II aquatic subecoregions, including Subecoregion II11, Subecoregion II12, Subecoregion II21, Subecoregion II22 and Subecoregion II23. Moreover, the characteristics of the two level I aquatic ecoregions and five level II aquatic subecoregions in the Taihu Lake watershed were summarized, showing that there were significant differences in topography, socio-economic development, water quality and aquatic ecology, etc. The results of quantitative comparison of aquatic life also indicated that the dominant species of fish, benthic density, biomass, dominant species, Shannon-Wiener diversity index, Margalef species richness index, Pielou evenness index and ecological dominance showed great spatial variability between the two level I aquatic ecoregions and five level II aquatic subecoregions. It reflected the spatial heterogeneities and the uneven natures of aquatic ecosystems in the Taihu Lake watershed.

Manual hierarchical clustering of regional geochemical data using a Bayesian finite mixture model

International Nuclear Information System (INIS)

Ellefsen, Karl J.; Smith, David B.

2016-01-01

Interpretation of regional scale, multivariate geochemical data is aided by a statistical technique called “clustering.” We investigate a particular clustering procedure by applying it to geochemical data collected in the State of Colorado, United States of America. The clustering procedure partitions the field samples for the entire survey area into two clusters. The field samples in each cluster are partitioned again to create two subclusters, and so on. This manual procedure generates a hierarchy of clusters, and the different levels of the hierarchy show geochemical and geological processes occurring at different spatial scales. Although there are many different clustering methods, we use Bayesian finite mixture modeling with two probability distributions, which yields two clusters. The model parameters are estimated with Hamiltonian Monte Carlo sampling of the posterior probability density function, which usually has multiple modes. Each mode has its own set of model parameters; each set is checked to ensure that it is consistent both with the data and with independent geologic knowledge. The set of model parameters that is most consistent with the independent geologic knowledge is selected for detailed interpretation and partitioning of the field samples. - Highlights: • We evaluate a clustering procedure by applying it to geochemical data. • The procedure generates a hierarchy of clusters. • Different levels of the hierarchy show geochemical processes at different spatial scales. • The clustering method is Bayesian finite mixture modeling. • Model parameters are estimated with Hamiltonian Monte Carlo sampling.

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

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Cheng-Xiang Wang

2007-02-01

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

Low-mass stars in globular clusters. III. The mass function of 47 Tucanae.

Science.gov (United States)

de Marchi, G.; Paresce, F.

1995-12-01

We have used the WFPC2 on board HST to investigate the stellar population in a field located 4'6 E of the center of the globular cluster 47 Tuc (NGC 104), close to the half-mass radius, through wide band imaging at 606 and 812nm. A total of ~3000 stars are accurately classified by two-color photometry to form a color-magnitude diagram extending down to a limiting magnitude m_814_=~m_I_=~24. A rich cluster main sequence is detected spanning the range from m_814_=~18 through m_814_=~23, where it spreads considerably due to the increasing photometric uncertainty and galaxy contamination. A secondary sequence of objects is also detected, parallel to the main sequence, as expected for a population of binary stars. The measured binary fraction in the range 195%. The main sequence luminosity function obtained from the observed CMD increases with decreasing luminosity following a power-law trend with index α=~0.15 in the range 5crowding. On the basis of the available mass-luminosity relation for this metallicity, the resultant mass function shows a power-law increase in numbers for decreasing masses in the range 0.8-0.3Msun_ with a slope α=~1.5, but then flattens out in the 0.3-0.15Msun_ range. The comparison of the mass function of 47 Tuc with that of NGC 6397 (Paper I) and of M 15 (Paper II), previously investigated with the same instrumentation, suggests that the stellar population near the half-mass radius of these clusters should not be very sensitive to either internal or externally-driven dynamical processes. The difference between their mass functions could then be attributed to metallicity, reflecting an intrinsic difference in their initial mass functions, unless mass-segregation is stronger in 47 Tuc than in the other two clusters. This latter circumstance could be due, for instance, to the large number of binaries discovered in 47 Tuc. In all cases, however, the mass function is found to flatten below 0.3Msun_ and the flattening is most likely an intrinsic

Study on Adaptive Parameter Determination of Cluster Analysis in Urban Management Cases

Science.gov (United States)

Fu, J. Y.; Jing, C. F.; Du, M. Y.; Fu, Y. L.; Dai, P. P.

2017-09-01

The fine management for cities is the important way to realize the smart city. The data mining which uses spatial clustering analysis for urban management cases can be used in the evaluation of urban public facilities deployment, and support the policy decisions, and also provides technical support for the fine management of the city. Aiming at the problem that DBSCAN algorithm which is based on the density-clustering can not realize parameter adaptive determination, this paper proposed the optimizing method of parameter adaptive determination based on the spatial analysis. Firstly, making analysis of the function Ripley's K for the data set to realize adaptive determination of global parameter MinPts, which means setting the maximum aggregation scale as the range of data clustering. Calculating every point object's highest frequency K value in the range of Eps which uses K-D tree and setting it as the value of clustering density to realize the adaptive determination of global parameter MinPts. Then, the R language was used to optimize the above process to accomplish the precise clustering of typical urban management cases. The experimental results based on the typical case of urban management in XiCheng district of Beijing shows that: The new DBSCAN clustering algorithm this paper presents takes full account of the data's spatial and statistical characteristic which has obvious clustering feature, and has a better applicability and high quality. The results of the study are not only helpful for the formulation of urban management policies and the allocation of urban management supervisors in XiCheng District of Beijing, but also to other cities and related fields.

STUDY ON ADAPTIVE PARAMETER DETERMINATION OF CLUSTER ANALYSIS IN URBAN MANAGEMENT CASES

Directory of Open Access Journals (Sweden)

J. Y. Fu

2017-09-01

Full Text Available The fine management for cities is the important way to realize the smart city. The data mining which uses spatial clustering analysis for urban management cases can be used in the evaluation of urban public facilities deployment, and support the policy decisions, and also provides technical support for the fine management of the city. Aiming at the problem that DBSCAN algorithm which is based on the density-clustering can not realize parameter adaptive determination, this paper proposed the optimizing method of parameter adaptive determination based on the spatial analysis. Firstly, making analysis of the function Ripley's K for the data set to realize adaptive determination of global parameter MinPts, which means setting the maximum aggregation scale as the range of data clustering. Calculating every point object’s highest frequency K value in the range of Eps which uses K-D tree and setting it as the value of clustering density to realize the adaptive determination of global parameter MinPts. Then, the R language was used to optimize the above process to accomplish the precise clustering of typical urban management cases. The experimental results based on the typical case of urban management in XiCheng district of Beijing shows that: The new DBSCAN clustering algorithm this paper presents takes full account of the data’s spatial and statistical characteristic which has obvious clustering feature, and has a better applicability and high quality. The results of the study are not only helpful for the formulation of urban management policies and the allocation of urban management supervisors in XiCheng District of Beijing, but also to other cities and related fields.

Daily urban systems in function of the spatial organisation in Serbia

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Tošić Dragutin

2009-01-01

Full Text Available In the form of theoretical discussion, this paper makes a brief analysis of relevant methodological steps for determination of Daily Urban Systems and the approach for their spatial-functional representation. The potential of using Daily Urban Systems as instruments for regional planning and regional development has been indicated. A model for determining Daily Urban Systems in Serbia has been proposed according to our socio-economic conditions. The experience thus far in reference to research of demographic, spatial and functional components of Daily Urban Systems demonstrates that for definition of their spatial and temporal manifestation and continuity models, the most relevant indicators are those which relate to distribution and functional specialization of work centers and places of living, and those which relate to quantitative-qualitative characteristics of daily migrants. Daily Urban Systems of Serbia have been developed under the conditions of continuous redistribution of population from rural to urban settlements and more or less synchronized processes of deagrarisation, deindustrialisation and urbanization with general socioeconomic flows. According to the dynamics of development in functions of work, living, education, service activities and public-social facilities in the urban regions, there have been formed Daily Urban Systems with appropriate hierarchy. The paper presents results of the latest research of Daily Urban Systems in Serbia, driven by scientific and appreciative reasons (preparation of the Regional spatial plans for municipalities of Južno pomoravlje and for Timočka krajina, and determination of the nodal systems in Zlatibor county. Daily Urban Systems, especially their regional role and implication, are proposed for instruments of rational spatial-functional organization of Serbia. According to the relevant theoretical-methodological approach and presented empirical evidence, the model of Daily Urban Systems

Advanced analysis of forest fire clustering

Science.gov (United States)

Kanevski, Mikhail; Pereira, Mario; Golay, Jean

2017-04-01

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

Differential Retention of Gene Functions in a Secondary Metabolite Cluster.

Science.gov (United States)

Reynolds, Hannah T; Slot, Jason C; Divon, Hege H; Lysøe, Erik; Proctor, Robert H; Brown, Daren W

2017-08-01

In fungi, distribution of secondary metabolite (SM) gene clusters is often associated with host- or environment-specific benefits provided by SMs. In the plant pathogen Alternaria brassicicola (Dothideomycetes), the DEP cluster confers an ability to synthesize the SM depudecin, a histone deacetylase inhibitor that contributes weakly to virulence. The DEP cluster includes genes encoding enzymes, a transporter, and a transcription regulator. We investigated the distribution and evolution of the DEP cluster in 585 fungal genomes and found a wide but sporadic distribution among Dothideomycetes, Sordariomycetes, and Eurotiomycetes. We confirmed DEP gene expression and depudecin production in one fungus, Fusarium langsethiae. Phylogenetic analyses suggested 6-10 horizontal gene transfers (HGTs) of the cluster, including a transfer that led to the presence of closely related cluster homologs in Alternaria and Fusarium. The analyses also indicated that HGTs were frequently followed by loss/pseudogenization of one or more DEP genes. Independent cluster inactivation was inferred in at least four fungal classes. Analyses of transitions among functional, pseudogenized, and absent states of DEP genes among Fusarium species suggest enzyme-encoding genes are lost at higher rates than the transporter (DEP3) and regulatory (DEP6) genes. The phenotype of an experimentally-induced DEP3 mutant of Fusarium did not support the hypothesis that selective retention of DEP3 and DEP6 protects fungi from exogenous depudecin. Together, the results suggest that HGT and gene loss have contributed significantly to DEP cluster distribution, and that some DEP genes provide a greater fitness benefit possibly due to a differential tendency to form network connections. Published by Oxford University Press on behalf of the Society for Molecular Biology and Evolution 2017. This work is written by US Government employees and is in the public domain in the US.

The externally corrected coupled cluster approach with four- and five-body clusters from the CASSCF wave function.

Science.gov (United States)

Xu, Enhua; Li, Shuhua

2015-03-07

An externally corrected CCSDt (coupled cluster with singles, doubles, and active triples) approach employing four- and five-body clusters from the complete active space self-consistent field (CASSCF) wave function (denoted as ecCCSDt-CASSCF) is presented. The quadruple and quintuple excitation amplitudes within the active space are extracted from the CASSCF wave function and then fed into the CCSDt-like equations, which can be solved in an iterative way as the standard CCSDt equations. With a size-extensive CASSCF reference function, the ecCCSDt-CASSCF method is size-extensive. When the CASSCF wave function is readily available, the computational cost of the ecCCSDt-CASSCF method scales as the popular CCSD method (if the number of active orbitals is small compared to the total number of orbitals). The ecCCSDt-CASSCF approach has been applied to investigate the potential energy surface for the simultaneous dissociation of two O-H bonds in H2O, the equilibrium distances and spectroscopic constants of 4 diatomic molecules (F2(+), O2(+), Be2, and NiC), and the reaction barriers for the automerization reaction of cyclobutadiene and the Cl + O3 → ClO + O2 reaction. In most cases, the ecCCSDt-CASSCF approach can provide better results than the CASPT2 (second order perturbation theory with a CASSCF reference function) and CCSDT methods.

Information processing architecture of functionally defined clusters in the macaque cortex.

Science.gov (United States)

Shen, Kelly; Bezgin, Gleb; Hutchison, R Matthew; Gati, Joseph S; Menon, Ravi S; Everling, Stefan; McIntosh, Anthony R

2012-11-28

Computational and empirical neuroimaging studies have suggested that the anatomical connections between brain regions primarily constrain their functional interactions. Given that the large-scale organization of functional networks is determined by the temporal relationships between brain regions, the structural limitations may extend to the global characteristics of functional networks. Here, we explored the extent to which the functional network community structure is determined by the underlying anatomical architecture. We directly compared macaque (Macaca fascicularis) functional connectivity (FC) assessed using spontaneous blood oxygen level-dependent functional magnetic resonance imaging (BOLD-fMRI) to directed anatomical connectivity derived from macaque axonal tract tracing studies. Consistent with previous reports, FC increased with increasing strength of anatomical connection, and FC was also present between regions that had no direct anatomical connection. We observed moderate similarity between the FC of each region and its anatomical connectivity. Notably, anatomical connectivity patterns, as described by structural motifs, were different within and across functional modules: partitioning of the functional network was supported by dense bidirectional anatomical connections within clusters and unidirectional connections between clusters. Together, our data directly demonstrate that the FC patterns observed in resting-state BOLD-fMRI are dictated by the underlying neuroanatomical architecture. Importantly, we show how this architecture contributes to the global organizational principles of both functional specialization and integration.

Comparison of Three Plot Selection Methods for Estimating Change in Temporally Variable, Spatially Clustered Populations.

Energy Technology Data Exchange (ETDEWEB)

Thompson, William L. [Bonneville Power Administration, Portland, OR (US). Environment, Fish and Wildlife

2001-07-01

Monitoring population numbers is important for assessing trends and meeting various legislative mandates. However, sampling across time introduces a temporal aspect to survey design in addition to the spatial one. For instance, a sample that is initially representative may lose this attribute if there is a shift in numbers and/or spatial distribution in the underlying population that is not reflected in later sampled plots. Plot selection methods that account for this temporal variability will produce the best trend estimates. Consequently, I used simulation to compare bias and relative precision of estimates of population change among stratified and unstratified sampling designs based on permanent, temporary, and partial replacement plots under varying levels of spatial clustering, density, and temporal shifting of populations. Permanent plots produced more precise estimates of change than temporary plots across all factors. Further, permanent plots performed better than partial replacement plots except for high density (5 and 10 individuals per plot) and 25% - 50% shifts in the population. Stratified designs always produced less precise estimates of population change for all three plot selection methods, and often produced biased change estimates and greatly inflated variance estimates under sampling with partial replacement. Hence, stratification that remains fixed across time should be avoided when monitoring populations that are likely to exhibit large changes in numbers and/or spatial distribution during the study period. Key words: bias; change estimation; monitoring; permanent plots; relative precision; sampling with partial replacement; temporary plots.

Density functional studies: First principles and semiempirical calculations of clusters and surfaces

International Nuclear Information System (INIS)

Sinnott, S.B.

1993-01-01

In the research presented here, various theoretical electronic structure techniques are utilized to analyze widely different systems from silicon clusters to transition metal solids and surfaces. For the silicon clusters, first principles density functional methods are used to investigate Si N for N = 2-8. The goal is to understand the different types of bonding that can occur in such small clusters where the coordination of the atoms differs substantially from that of the stable bulk tetrahedral bonding. Such uncoordinated structures can provide a good test of more approximate theories that can be used eventually to model silicon surfaces, of obvious technological importance. For the transition metal systems, non-self-consistent electronic structure methods are used to provide an understanding of the driving force for surface relaxations. An in-depth analysis of the results is presented and the physical basis of surface relaxation within the theory is discussed. In addition, the limitations inherent in calculations of metal surface relaxation are addressed. Finally, in an effort to increase understanding of approximate methods, a novel non-self-consistent density functional electronic structure method is developed that is ∼1000 times faster computationally than more sophisticated methods. This new method is tested for a variety of systems including diatomics, mixed clusters, surfaces and bulk lattices. The strengths and weaknesses of the new theory are discussed in detail, leading to greater understanding of non-self-consistent density functional theories as a whole

Spatial and functional city structure with examples of Valjevo, Bor and Knjaževac

Directory of Open Access Journals (Sweden)

Spasić Nenad

2005-01-01

Full Text Available Cities represent such social environments which develop under the influence of their resource hinterland, yet at the same time they vigorously affect changes in their immediate or broader surroundings, depending on dynamics of city limits change. From city origins to the present day, interdependences between its spatial and functional structures can be noticed. Historical context plays a significant role in city development, both in terms of its spatial structure formation as well as in terms of development of city functions and territorial distribution of urban services. Spatial structure of a city is also defined by a set of geographical, economic, social functional and other features in their interdependency. Functional structure of a city depends on its size and position it takes in the functional distribution on a regional level as well as it is related to the functional capacity of a city. This paper analyses concrete examples of spatial and functional structures featuring three Serbian towns: Valjevo, Bor and Knjaževac. From the analysis of their common attributes in this respect, the following can be noticed: formation of the case study towns happened around inherited historical city cores, which even now perform a number of public functions; basic road networks significantly influenced formation of spatial patterns of these towns; spatial development of the towns in the last decade or so was slowed down because of economic and social stagnation, which didn't show major influence on change of spatial and functional structures of the towns involved.

Spatial distribution measured by the modulation transfer function

International Nuclear Information System (INIS)

Rossi, P.; Brice, D.K.; Doyle, B.L.

2003-01-01

Spatial distributions in ion micro-beam and IBA experimental practice are regularly characterized through the parameters of FWHM and tail area percentage (TF, tail fraction). Linear and stationary transducer theory allows these distributions to be described in the Fourier-dual frequency space, and provides an indirect method to evaluate them through measurement of the modulation transfer function (MTF). We suggest direct measurement of MTF by employing bar pattern grids, similar to those used for calibration of radiological equipment. Assuming spatial distributions of the form exp(-(|αx|) η ), we are able to relate the MTF measurements to the more popular FWHM and TF. This new approach to determine spatial resolution can become a standard for use by the micro-beam community

The Luminosity Functions of Old and Intermediate-Age Globular Clusters in NGC 3610

OpenAIRE

Whitmore, B. C.; Schweizer, F.; Kundu, A.; Miller, B. W.

2002-01-01

The WFPC2 Camera on board HST has been used to obtain high-resolution images of NGC 3610, a dynamically young elliptical galaxy. These observations supersede shorter, undithered HST observations where an intermediate-age population of globular clusters was first discovered. The new observations show the bimodal color distribution of globular clusters more clearly, with peaks at (V-I)o = 0.95 and 1.17. The luminosity function (LF) of the blue, metal-poor population of clusters in NGC 3610 turn...

Diversity among galaxy clusters

International Nuclear Information System (INIS)

Struble, M.F.; Rood, H.J.

1988-01-01

The classification of galaxy clusters is discussed. Consideration is given to the classification scheme of Abell (1950's), Zwicky (1950's), Morgan, Matthews, and Schmidt (1964), and Morgan-Bautz (1970). Galaxies can be classified based on morphology, chemical composition, spatial distribution, and motion. The correlation between a galaxy's environment and morphology is examined. The classification scheme of Rood-Sastry (1971), which is based on clusters's morphology and galaxy population, is described. The six types of clusters they define include: (1) a cD-cluster dominated by a single large galaxy, (2) a cluster dominated by a binary, (3) a core-halo cluster, (4) a cluster dominated by several bright galaxies, (5) a cluster appearing flattened, and (6) an irregularly shaped cluster. Attention is also given to the evolution of cluster structures, which is related to initial density and cluster motion

Symmetrized partial-wave method for density-functional cluster calculations

International Nuclear Information System (INIS)

Averill, F.W.; Painter, G.S.

1994-01-01

The computational advantage and accuracy of the Harris method is linked to the simplicity and adequacy of the reference-density model. In an earlier paper, we investigated one way the Harris functional could be extended to systems outside the limits of weakly interacting atoms by making the charge density of the interacting atoms self-consistent within the constraints of overlapping spherical atomic densities. In the present study, a method is presented for augmenting the interacting atom charge densities with symmetrized partial-wave expansions on each atomic site. The added variational freedom of the partial waves leads to a scheme capable of giving exact results within a given exchange-correlation approximation while maintaining many of the desirable convergence and stability properties of the original Harris method. Incorporation of the symmetry of the cluster in the partial-wave construction further reduces the level of computational effort. This partial-wave cluster method is illustrated by its application to the dimer C 2 , the hypothetical atomic cluster Fe 6 Al 8 , and the benzene molecule

Anchoring selenido-carbonyl ruthenium clusters to functionalized silica xerogels

International Nuclear Information System (INIS)

Cauzzi, Daniele; Graiff, Claudia; Pattacini, Roberto; Predieri, Giovanni; Tiripicchio, Antonio

2003-01-01

Silica Xerogels containing carbonyl Ru 3 Se 2 nido clusters were prepared in three different ways. The simple dispersion of [Ru 3 (μ 3 -Se) 2 (CO) 7 (PPh 3 ) 2 ] via sol gel process produces an inhomogeneous material; by contrast, homogeneous xerogels were obtained by reaction of [Ru 3 (μ 3 -Se) 2 (CO) 8 (PPh 3 )] with functionalized xerogels containing grafted diphenylphosphine moieties and by reaction of [Ru 3 (CO) 12 ] with a xerogel containing grafted phosphine-selenide groups. The reaction between [Ru 3 (CO) 12 ] and dodecyl diphenylphosphine selenide led to the formation of four selenido carbonyl clusters, which are soluble in hydrocarbon solvents and can be deposited as thin films from their solution by slow evaporation. (author)

Estimating functions for inhomogeneous spatial point processes with incomplete covariate data

DEFF Research Database (Denmark)

Waagepetersen, Rasmus

and this leads to parameter estimation error which is difficult to quantify. In this paper we introduce a Monte Carlo version of the estimating function used in "spatstat" for fitting inhomogeneous Poisson processes and certain inhomogeneous cluster processes. For this modified estimating function it is feasible...

Estimating functions for inhomogeneous spatial point processes with incomplete covariate data

DEFF Research Database (Denmark)

Waagepetersen, Rasmus

2008-01-01

and this leads to parameter estimation error which is difficult to quantify. In this paper, we introduce a Monte Carlo version of the estimating function used in spatstat for fitting inhomogeneous Poisson processes and certain inhomogeneous cluster processes. For this modified estimating function, it is feasible...

Functional Principal Component Analysis and Randomized Sparse Clustering Algorithm for Medical Image Analysis

Science.gov (United States)

Lin, Nan; Jiang, Junhai; Guo, Shicheng; Xiong, Momiao

2015-01-01

Due to the advancement in sensor technology, the growing large medical image data have the ability to visualize the anatomical changes in biological tissues. As a consequence, the medical images have the potential to enhance the diagnosis of disease, the prediction of clinical outcomes and the characterization of disease progression. But in the meantime, the growing data dimensions pose great methodological and computational challenges for the representation and selection of features in image cluster analysis. To address these challenges, we first extend the functional principal component analysis (FPCA) from one dimension to two dimensions to fully capture the space variation of image the signals. The image signals contain a large number of redundant features which provide no additional information for clustering analysis. The widely used methods for removing the irrelevant features are sparse clustering algorithms using a lasso-type penalty to select the features. However, the accuracy of clustering using a lasso-type penalty depends on the selection of the penalty parameters and the threshold value. In practice, they are difficult to determine. Recently, randomized algorithms have received a great deal of attentions in big data analysis. This paper presents a randomized algorithm for accurate feature selection in image clustering analysis. The proposed method is applied to both the liver and kidney cancer histology image data from the TCGA database. The results demonstrate that the randomized feature selection method coupled with functional principal component analysis substantially outperforms the current sparse clustering algorithms in image cluster analysis. PMID:26196383

Locating irregularly shaped clusters of infection intensity

Directory of Open Access Journals (Sweden)

Niko Yiannakoulias

2010-05-01

Full Text Available Patterns of disease may take on irregular geographic shapes, especially when features of the physical environment influence risk. Identifying these patterns can be important for planning, and also identifying new environmental or social factors associated with high or low risk of illness. Until recently, cluster detection methods were limited in their ability to detect irregular spatial patterns, and limited to finding clusters that were roughly circular in shape. This approach has less power to detect irregularly-shaped, yet important spatial anomalies, particularly at high spatial resolutions. We employ a new method of finding irregularly-shaped spatial clusters at micro-geographical scales using both simulated and real data on Schistosoma mansoni and hookworm infection intensities. This method, which we refer to as the “greedy growth scan”, is a modification of the spatial scan method for cluster detection. Real data are based on samples of hookworm and S. mansoni from Kitengei, Makueni district, Kenya. Our analysis of simulated data shows how methods able to find irregular shapes are more likely to identify clusters along rivers than methods constrained to fixed geometries. Our analysis of infection intensity identifies two small areas within the study region in which infection intensity is elevated, possibly due to local features of the physical or social environment. Collectively, our results show that the “greedy growth scan” is a suitable method for exploratory geographical analysis of infection intensity data when irregular shapes are suspected, especially at micro-geographical scales.

Accurate density-functional calculations on large systems: Fullerenes and magnetic clusters

International Nuclear Information System (INIS)

Dunlap, B.I.

1996-01-01

Efforts to accurately compute all-electron density-functional energies for large molecules and clusters using Gaussian basis sets will be reviewed. The foundation of this effort, variational fitting, will be described and followed by three applications of the method. The first application concerns fullerenes. When first discovered, C 60 is quite unstable relative to the higher fullerenes. In addition, to raising questions about the relative abundance of the various fullerenes, this work conflicted with the then state-of-the art density-funcitonal calculations on crystalline graphite. Now high accuracy molecular and band structure calculations are in fairly good agreement. Second, we have used these methods to design transition metal clusters having the highest magnetic moment by maximizing the symmetry-required degeneracy of the one-electron orbitals. Most recently, we have developed accurate, variational generalized-gradient approximation (GGA) forces for use in geometry optimization of clusters and in molecular-dynamics simulations of friction. The GGA optimized geometries of a number of large clusters will be given

THE EXTENDED VIRGO CLUSTER CATALOG

Energy Technology Data Exchange (ETDEWEB)

Kim, Suk; Rey, Soo-Chang; Lee, Youngdae; Chung, Jiwon; Pak, Mina; Yi, Wonhyeong; Lee, Woong [Department of Astronomy and Space Science, Chungnam National University, 99 Daehak-ro, Daejeon 305-764 (Korea, Republic of); Jerjen, Helmut [Research School of Astronomy and Astrophysics, The Australian National University, Cotter Road, Weston, ACT 2611 (Australia); Lisker, Thorsten [Astronomisches Rechen-Institut, Zentrum für Astronomie der Universität Heidelberg (ZAH), Mönchhofstraße 12-14, D-69120 Heidelberg (Germany); Sung, Eon-Chang [Korea Astronomy and Space Science institute, 776 Daedeokdae-ro, Daejeon 305-348 (Korea, Republic of)

2015-01-01

We present a new catalog of galaxies in the wider region of the Virgo cluster, based on the Sloan Digital Sky Survey (SDSS) Data Release 7. The Extended Virgo Cluster Catalog (EVCC) covers an area of 725 deg{sup 2} or 60.1 Mpc{sup 2}. It is 5.2 times larger than the footprint of the classical Virgo Cluster Catalog (VCC) and reaches out to 3.5 times the virial radius of the Virgo cluster. We selected 1324 spectroscopically targeted galaxies with radial velocities less than 3000 km s{sup –1}. In addition, 265 galaxies that have been overlooked in the SDSS spectroscopic survey but have available redshifts in the NASA Extragalactic Database are also included. Our selection process secured a total of 1589 galaxies, 676 of which are not included in the VCC. The certain and possible cluster members are defined by means of redshift comparison with a cluster infall model. We employed two independent and complementary galaxy classification schemes: the traditional morphological classification based on the visual inspection of optical images and a characterization of galaxies from their spectroscopic features. SDSS u, g, r, i, and z passband photometry of all EVCC galaxies was performed using Source Extractor. We compare the EVCC galaxies with the VCC in terms of morphology, spatial distribution, and luminosity function. The EVCC defines a comprehensive galaxy sample covering a wider range in galaxy density that is significantly different from the inner region of the Virgo cluster. It will be the foundation for forthcoming galaxy evolution studies in the extended Virgo cluster region, complementing ongoing and planned Virgo cluster surveys at various wavelengths.

The Hierarchical Distribution of the Young Stellar Clusters in Six Local Star-forming Galaxies

Energy Technology Data Exchange (ETDEWEB)

Grasha, K.; Calzetti, D. [Astronomy Department, University of Massachusetts, Amherst, MA 01003 (United States); Adamo, A.; Messa, M. [Dept. of Astronomy, The Oskar Klein Centre, Stockholm University, Stockholm (Sweden); Kim, H. [Gemini Observatory, La Serena (Chile); Elmegreen, B. G. [IBM Research Division, T.J. Watson Research Center, Yorktown Hts., NY (United States); Gouliermis, D. A. [Zentrum für Astronomie der Universität Heidelberg, Institut für Theoretische Astrophysik, Albert-Ueberle-Str. 2, D-69120 Heidelberg (Germany); Dale, D. A. [Dept. of Physics and Astronomy, University of Wyoming, Laramie, WY (United States); Fumagalli, M. [Institute for Computational Cosmology and Centre for Extragalactic Astronomy, Durham University, Durham (United Kingdom); Grebel, E. K.; Shabani, F. [Astronomisches Rechen-Institut, Zentrum für Astronomie der Universität Heidelberg, Mönchhofstr. 12-14, D-69120 Heidelberg (Germany); Johnson, K. E. [Dept. of Astronomy, University of Virginia, Charlottesville, VA (United States); Kahre, L. [Dept. of Astronomy, New Mexico State University, Las Cruces, NM (United States); Kennicutt, R. C. [Institute of Astronomy, University of Cambridge, Cambridge (United Kingdom); Pellerin, A. [Dept. of Physics and Astronomy, State University of New York at Geneseo, Geneseo NY (United States); Ryon, J. E.; Ubeda, L. [Space Telescope Science Institute, Baltimore, MD (United States); Smith, L. J. [European Space Agency/Space Telescope Science Institute, Baltimore, MD (United States); Thilker, D., E-mail: kgrasha@astro.umass.edu [Dept. of Physics and Astronomy, The Johns Hopkins University, Baltimore, MD (United States)

2017-05-10

We present a study of the hierarchical clustering of the young stellar clusters in six local (3–15 Mpc) star-forming galaxies using Hubble Space Telescope broadband WFC3/UVIS UV and optical images from the Treasury Program LEGUS (Legacy ExtraGalactic UV Survey). We identified 3685 likely clusters and associations, each visually classified by their morphology, and we use the angular two-point correlation function to study the clustering of these stellar systems. We find that the spatial distribution of the young clusters and associations are clustered with respect to each other, forming large, unbound hierarchical star-forming complexes that are in general very young. The strength of the clustering decreases with increasing age of the star clusters and stellar associations, becoming more homogeneously distributed after ∼40–60 Myr and on scales larger than a few hundred parsecs. In all galaxies, the associations exhibit a global behavior that is distinct and more strongly correlated from compact clusters. Thus, populations of clusters are more evolved than associations in terms of their spatial distribution, traveling significantly from their birth site within a few tens of Myr, whereas associations show evidence of disruption occurring very quickly after their formation. The clustering of the stellar systems resembles that of a turbulent interstellar medium that drives the star formation process, correlating the components in unbound star-forming complexes in a hierarchical manner, dispersing shortly after formation, suggestive of a single, continuous mode of star formation across all galaxies.

The Hierarchical Distribution of the Young Stellar Clusters in Six Local Star-forming Galaxies

Science.gov (United States)

Grasha, K.; Calzetti, D.; Adamo, A.; Kim, H.; Elmegreen, B. G.; Gouliermis, D. A.; Dale, D. A.; Fumagalli, M.; Grebel, E. K.; Johnson, K. E.; Kahre, L.; Kennicutt, R. C.; Messa, M.; Pellerin, A.; Ryon, J. E.; Smith, L. J.; Shabani, F.; Thilker, D.; Ubeda, L.

2017-05-01

We present a study of the hierarchical clustering of the young stellar clusters in six local (3-15 Mpc) star-forming galaxies using Hubble Space Telescope broadband WFC3/UVIS UV and optical images from the Treasury Program LEGUS (Legacy ExtraGalactic UV Survey). We identified 3685 likely clusters and associations, each visually classified by their morphology, and we use the angular two-point correlation function to study the clustering of these stellar systems. We find that the spatial distribution of the young clusters and associations are clustered with respect to each other, forming large, unbound hierarchical star-forming complexes that are in general very young. The strength of the clustering decreases with increasing age of the star clusters and stellar associations, becoming more homogeneously distributed after ˜40-60 Myr and on scales larger than a few hundred parsecs. In all galaxies, the associations exhibit a global behavior that is distinct and more strongly correlated from compact clusters. Thus, populations of clusters are more evolved than associations in terms of their spatial distribution, traveling significantly from their birth site within a few tens of Myr, whereas associations show evidence of disruption occurring very quickly after their formation. The clustering of the stellar systems resembles that of a turbulent interstellar medium that drives the star formation process, correlating the components in unbound star-forming complexes in a hierarchical manner, dispersing shortly after formation, suggestive of a single, continuous mode of star formation across all galaxies.

The Hierarchical Distribution of the Young Stellar Clusters in Six Local Star-forming Galaxies

International Nuclear Information System (INIS)

Grasha, K.; Calzetti, D.; Adamo, A.; Messa, M.; Kim, H.; Elmegreen, B. G.; Gouliermis, D. A.; Dale, D. A.; Fumagalli, M.; Grebel, E. K.; Shabani, F.; Johnson, K. E.; Kahre, L.; Kennicutt, R. C.; Pellerin, A.; Ryon, J. E.; Ubeda, L.; Smith, L. J.; Thilker, D.

2017-01-01

We present a study of the hierarchical clustering of the young stellar clusters in six local (3–15 Mpc) star-forming galaxies using Hubble Space Telescope broadband WFC3/UVIS UV and optical images from the Treasury Program LEGUS (Legacy ExtraGalactic UV Survey). We identified 3685 likely clusters and associations, each visually classified by their morphology, and we use the angular two-point correlation function to study the clustering of these stellar systems. We find that the spatial distribution of the young clusters and associations are clustered with respect to each other, forming large, unbound hierarchical star-forming complexes that are in general very young. The strength of the clustering decreases with increasing age of the star clusters and stellar associations, becoming more homogeneously distributed after ∼40–60 Myr and on scales larger than a few hundred parsecs. In all galaxies, the associations exhibit a global behavior that is distinct and more strongly correlated from compact clusters. Thus, populations of clusters are more evolved than associations in terms of their spatial distribution, traveling significantly from their birth site within a few tens of Myr, whereas associations show evidence of disruption occurring very quickly after their formation. The clustering of the stellar systems resembles that of a turbulent interstellar medium that drives the star formation process, correlating the components in unbound star-forming complexes in a hierarchical manner, dispersing shortly after formation, suggestive of a single, continuous mode of star formation across all galaxies.

Determination of spectral, structural and energetic properties of small lithium clusters, within the density functional theory formalism

International Nuclear Information System (INIS)

Gardet, G.

1995-01-01

A systematic study of small lithium clusters (with size less than 19), within the Density Functional Theory (DFT) formalism is presented. We examine structural properties of the so called local level of approximation. For clusters with size smaller than 8, the conformations are well known from ab initio calculations and are found here at much lower computational cost, with only small differences. For bigger clusters, two growth pattern have been used, based upon the increase of the number of pentagonal subunits in the clusters by absorption of one or two Li atoms. Several new stable structures are proposed. Then DFT gradient-corrected functionals have been used for relative stability determination of these clusters. Ionisation potentials and binding energies are also investigated in regard to clusters size and geometry. Calculations of excited states of lithium clusters (with size less than 9) have been performed within two different approaches. Using a set of Kohn-Sham orbitals to construct wave functions, oscillator strengths calculation of the electric dipole transitions is performed. Transition energies, oscillator strengths and optical absorption presented here are generally in reasonable agreement with the experimental data and the Configuration Interaction calculations. (author)

IntroductionThe Cluster mission

Directory of Open Access Journals (Sweden)

M. Fehringer

Full Text Available The Cluster mission, ESA’s first cornerstone project, together with the SOHO mission, dating back to the first proposals in 1982, was finally launched in the summer of 2000. On 16 July and 9 August, respectively, two Russian Soyuz rockets blasted off from the Russian cosmodrome in Baikonour to deliver two Cluster spacecraft, each into their proper orbit. By the end of August 2000, the four Cluster satellites had reached their final tetrahedral constellation. The commissioning of 44 instruments, both individually and as an ensemble of complementary tools, was completed five months later to ensure the optimal use of their combined observational potential. On 1 February 2001, the mission was declared operational. The main goal of the Cluster mission is to study the small-scale plasma structures in three dimensions in key plasma regions, such as the solar wind, bow shock, magnetopause, polar cusps, magnetotail and the auroral zones. With its unique capabilities of three-dimensional spatial resolution, Cluster plays a major role in the International Solar Terrestrial Program (ISTP, where Cluster and the Solar and Heliospheric Observatory (SOHO are the European contributions. Cluster’s payload consists of state-of-the-art plasma instrumentation to measure electric and magnetic fields from the quasi-static up to high frequencies, and electron and ion distribution functions from energies of nearly 0 eV to a few MeV. The science operations are coordinated by the Joint Science Operations Centre (JSOC, at the Rutherford Appleton Laboratory (UK, and implemented by the European Space Operations Centre (ESOC, in Darmstadt, Germany. A network of eight national data centres has been set up for raw data processing, for the production of physical parameters, and their distribution to end users all over the world. The latest information on the Cluster mission can be found at http://sci.esa.int/cluster/.

IntroductionThe Cluster mission

Directory of Open Access Journals (Sweden)

C. P. Escoubet

2001-09-01

Full Text Available The Cluster mission, ESA’s first cornerstone project, together with the SOHO mission, dating back to the first proposals in 1982, was finally launched in the summer of 2000. On 16 July and 9 August, respectively, two Russian Soyuz rockets blasted off from the Russian cosmodrome in Baikonour to deliver two Cluster spacecraft, each into their proper orbit. By the end of August 2000, the four Cluster satellites had reached their final tetrahedral constellation. The commissioning of 44 instruments, both individually and as an ensemble of complementary tools, was completed five months later to ensure the optimal use of their combined observational potential. On 1 February 2001, the mission was declared operational. The main goal of the Cluster mission is to study the small-scale plasma structures in three dimensions in key plasma regions, such as the solar wind, bow shock, magnetopause, polar cusps, magnetotail and the auroral zones. With its unique capabilities of three-dimensional spatial resolution, Cluster plays a major role in the International Solar Terrestrial Program (ISTP, where Cluster and the Solar and Heliospheric Observatory (SOHO are the European contributions. Cluster’s payload consists of state-of-the-art plasma instrumentation to measure electric and magnetic fields from the quasi-static up to high frequencies, and electron and ion distribution functions from energies of nearly 0 eV to a few MeV. The science operations are coordinated by the Joint Science Operations Centre (JSOC, at the Rutherford Appleton Laboratory (UK, and implemented by the European Space Operations Centre (ESOC, in Darmstadt, Germany. A network of eight national data centres has been set up for raw data processing, for the production of physical parameters, and their distribution to end users all over the world. The latest information on the Cluster mission can be found at http://sci.esa.int/cluster/.

Diametrical clustering for identifying anti-correlated gene clusters.

Science.gov (United States)

Dhillon, Inderjit S; Marcotte, Edward M; Roshan, Usman

2003-09-01

Clustering genes based upon their expression patterns allows us to predict gene function. Most existing clustering algorithms cluster genes together when their expression patterns show high positive correlation. However, it has been observed that genes whose expression patterns are strongly anti-correlated can also be functionally similar. Biologically, this is not unintuitive-genes responding to the same stimuli, regardless of the nature of the response, are more likely to operate in the same pathways. We present a new diametrical clustering algorithm that explicitly identifies anti-correlated clusters of genes. Our algorithm proceeds by iteratively (i). re-partitioning the genes and (ii). computing the dominant singular vector of each gene cluster; each singular vector serving as the prototype of a 'diametric' cluster. We empirically show the effectiveness of the algorithm in identifying diametrical or anti-correlated clusters. Testing the algorithm on yeast cell cycle data, fibroblast gene expression data, and DNA microarray data from yeast mutants reveals that opposed cellular pathways can be discovered with this method. We present systems whose mRNA expression patterns, and likely their functions, oppose the yeast ribosome and proteosome, along with evidence for the inverse transcriptional regulation of a number of cellular systems.

Data-driven inference for the spatial scan statistic.

Science.gov (United States)

Almeida, Alexandre C L; Duarte, Anderson R; Duczmal, Luiz H; Oliveira, Fernando L P; Takahashi, Ricardo H C

2011-08-02

Kulldorff's spatial scan statistic for aggregated area maps searches for clusters of cases without specifying their size (number of areas) or geographic location in advance. Their statistical significance is tested while adjusting for the multiple testing inherent in such a procedure. However, as is shown in this work, this adjustment is not done in an even manner for all possible cluster sizes. A modification is proposed to the usual inference test of the spatial scan statistic, incorporating additional information about the size of the most likely cluster found. A new interpretation of the results of the spatial scan statistic is done, posing a modified inference question: what is the probability that the null hypothesis is rejected for the original observed cases map with a most likely cluster of size k, taking into account only those most likely clusters of size k found under null hypothesis for comparison? This question is especially important when the p-value computed by the usual inference process is near the alpha significance level, regarding the correctness of the decision based in this inference. A practical procedure is provided to make more accurate inferences about the most likely cluster found by the spatial scan statistic.

Defining functioning levels in patients with schizophrenia: A combination of a novel clustering method and brain SPECT analysis.

Science.gov (United States)

Catherine, Faget-Agius; Aurélie, Vincenti; Eric, Guedj; Pierre, Michel; Raphaëlle, Richieri; Marine, Alessandrini; Pascal, Auquier; Christophe, Lançon; Laurent, Boyer

2017-12-30

This study aims to define functioning levels of patients with schizophrenia by using a method of interpretable clustering based on a specific functioning scale, the Functional Remission Of General Schizophrenia (FROGS) scale, and to test their validity regarding clinical and neuroimaging characterization. In this observational study, patients with schizophrenia have been classified using a hierarchical top-down method called clustering using unsupervised binary trees (CUBT). Socio-demographic, clinical, and neuroimaging SPECT perfusion data were compared between the different clusters to ensure their clinical relevance. A total of 242 patients were analyzed. A four-group functioning level structure has been identified: 54 are classified as "minimal", 81 as "low", 64 as "moderate", and 43 as "high". The clustering shows satisfactory statistical properties, including reproducibility and discriminancy. The 4 clusters consistently differentiate patients. "High" functioning level patients reported significantly the lowest scores on the PANSS and the CDSS, and the highest scores on the GAF, the MARS and S-QoL 18. Functioning levels were significantly associated with cerebral perfusion of two relevant areas: the left inferior parietal cortex and the anterior cingulate. Our study provides relevant functioning levels in schizophrenia, and may enhance the use of functioning scale. Copyright © 2017 Elsevier B.V. All rights reserved.

The evolution of the global stellar mass function of star clusters: an analytic description

NARCIS (Netherlands)

Lamers, H.J.G.L.M.; Baumgardt, H.; Gieles, M.

2013-01-01

The evolution of the global stellar mass function of star clusters is studied based on a large set of N-body simulations of clusters with a range of initial masses, initial concentrations, in circular or elliptical orbits in different tidal environments. Models with and without initial mass

Quantitative Imaging of Cholinergic Interneurons Reveals a Distinctive Spatial Organization and a Functional Gradient across the Mouse Striatum.

Directory of Open Access Journals (Sweden)

Miriam Matamales

Full Text Available Information processing in the striatum requires the postsynaptic integration of glutamatergic and dopaminergic signals, which are then relayed to the output nuclei of the basal ganglia to influence behavior. Although cellularly homogeneous in appearance, the striatum contains several rare interneuron populations which tightly modulate striatal function. Of these, cholinergic interneurons (CINs have been recently shown to play a critical role in the control of reward-related learning; however how the striatal cholinergic network is functionally organized at the mesoscopic level and the way this organization influences striatal function remains poorly understood. Here, we systematically mapped and digitally reconstructed the entire ensemble of CINs in the mouse striatum and quantitatively assessed differences in densities, spatial arrangement and neuropil content across striatal functional territories. This approach demonstrated that the rostral portion of the striatum contained a higher concentration of CINs than the caudal striatum and that the cholinergic content in the core of the ventral striatum was significantly lower than in the rest of the regions. Additionally, statistical comparison of spatial point patterns in the striatal cholinergic ensemble revealed that only a minor portion of CINs (17% aggregated into cluster and that they were predominantly organized in a random fashion. Furthermore, we used a fluorescence reporter to estimate the activity of over two thousand CINs in naïve mice and found that there was a decreasing gradient of CIN overall function along the dorsomedial-to-ventrolateral axis, which appeared to be independent of their propensity to aggregate within the striatum. Altogether this work suggests that the regulation of striatal function by acetylcholine across the striatum is highly heterogeneous, and that signals originating in external afferent systems may be principally determining the function of CINs in the

Cluster Physics with Merging Galaxy Clusters

Directory of Open Access Journals (Sweden)

Sandor M. Molnar

2016-02-01

Full Text Available Collisions between galaxy clusters provide a unique opportunity to study matter in a parameter space which cannot be explored in our laboratories on Earth. In the standard LCDM model, where the total density is dominated by the cosmological constant ($Lambda$ and the matter density by cold dark matter (CDM, structure formation is hierarchical, and clusters grow mostly by merging.Mergers of two massive clusters are the most energetic events in the universe after the Big Bang,hence they provide a unique laboratory to study cluster physics.The two main mass components in clusters behave differently during collisions:the dark matter is nearly collisionless, responding only to gravity, while the gas is subject to pressure forces and dissipation, and shocks and turbulenceare developed during collisions. In the present contribution we review the different methods used to derive the physical properties of merging clusters. Different physical processes leave their signatures on different wavelengths, thusour review is based on a multifrequency analysis. In principle, the best way to analyze multifrequency observations of merging clustersis to model them using N-body/HYDRO numerical simulations. We discuss the results of such detailed analyses.New high spatial and spectral resolution ground and space based telescopeswill come online in the near future. Motivated by these new opportunities,we briefly discuss methods which will be feasible in the near future in studying merging clusters.

Dyadic Green's function of a cluster of spheres.

Science.gov (United States)

Moneda, Angela P; Chrissoulidis, Dimitrios P

2007-11-01

The electric dyadic Green's function (dGf) of a cluster of spheres is obtained by application of the superposition principle, dyadic algebra, and the indirect mode-matching method. The analysis results in a set of linear equations for the unknown, vector, wave amplitudes of the dGf; that set is solved by truncation and matrix inversion. The theory is exact in the sense that no simplifying assumptions are made in the analytical steps leading to the dGf, and it is general in the sense that any number, position, size and electrical properties can be considered for the spheres that cluster together. The point source can be anywhere, even within one of the spheres. Energy conservation, reciprocity, and other tests prove that this solution is correct. Numerical results are presented for an electric Hertz dipole radiating in the presence of an array of rexolite spheres, which manifests lensing and beam-forming capabilities.

A theoretical study of lithium-doped gallium clusters by density functional theory

Energy Technology Data Exchange (ETDEWEB)

Sentuerk, Suekrue; Ekincioglu, Yavuz [Dumlupinar Univ., Kutahya (Turkey). Dept. of Physics

2012-05-15

The geometrical structures, stabilities, and electronic properties of Ga{sub n}Li (n = 1-13) clusters were investigated within the density functional theory (DFT). The impurity lithium atom enhances the stability of Ga{sub n}Li (n = 1-13) clusters, especially Ga{sub n}Li (n = 9-13) compared to Ga{sub n} (n = 9-14), that is at either apex position or side position. The dissociation energy, second-order energy differences, and the energy gaps between highest occupied and lowest unoccupied molecular orbital (HOMO-LUMO) indicate that the Ga{sub 7}Li, Ga{sub 9}Li, and Ga{sub 11}Li clusters are more stable within the studied cluster range. Moreover, the variation of the average bond length of Ga - Li is due to the surface effect, and the binding strength increases resulting from the increase of charge amount. (orig.)

Evolution of the spherical clusters

International Nuclear Information System (INIS)

Surdin, V.G.

1978-01-01

The possible processes of the Galaxy spherical clusters formation and evolution are described on a popular level. The orbits of spherical cluster motion and their spatial velocities are determined. Given are the distrbutions of spherical cluster stars according to their velocities and the observed distribution of spherical clusters in the area of the Galaxy slow evolution. The dissipation and dynamic friction processes destructing clusters with the mass less than 10 4 of solar mass and bringing about the reduction of clusters in the Galaxy are considered. The paradox of forming mainly X-ray sources in spherical clusters is explained. The schematic image of possible ways of forming X-ray sources in spherical clusters is given

An Archival Search For Young Globular Clusters in Galaxies

Science.gov (United States)

Whitmore, Brad

1995-07-01

One of the most intriguing results from HST has been the discovery of ultraluminous star clusters in interacting and merging galaxies. These clusters have the luminosities, colors, and sizes that would be expected of young globular clusters produced by the interaction. We propose to use the data in the HST Archive to determine how prevalent this phenomena is, and to determine whether similar clusters are produced in other environments. Three samples will be extracted and studied in a systematic and consistent manner: 1} interacting and merging galaxies, 2} starburst galaxies, 3} a control sample of ``normal'' galaxies. A preliminary search of the archives shows that there are at least 20 galaxies in each of these samples, and the number will grow by about 50 observations become available. The data will be used to determine the luminosity function, color histogram , spatial distribution, and structural properties of the clusters using the same techniques employed in our study of NGC 7252 {``Atoms -for-Peace'' galaxy} and NGC 4038/4039 {``The Antennae''}. Our ultimate goals are: 1} to understand how globular clusters form, and 2} to use the clusters as evolutionary tracers to unravel the histories of interacting galaxies.

Evaluating spatial and temporal relationships between an earthquake cluster near Entiat, central Washington, and the large December 1872 Entiat earthquake

Science.gov (United States)

Brocher, Thomas M.; Blakely, Richard J.; Sherrod, Brian

2017-01-01

We investigate spatial and temporal relations between an ongoing and prolific seismicity cluster in central Washington, near Entiat, and the 14 December 1872 Entiat earthquake, the largest historic crustal earthquake in Washington. A fault scarp produced by the 1872 earthquake lies within the Entiat cluster; the locations and areas of both the cluster and the estimated 1872 rupture surface are comparable. Seismic intensities and the 1–2 m of coseismic displacement suggest a magnitude range between 6.5 and 7.0 for the 1872 earthquake. Aftershock forecast models for (1) the first several hours following the 1872 earthquake, (2) the largest felt earthquakes from 1900 to 1974, and (3) the seismicity within the Entiat cluster from 1976 through 2016 are also consistent with this magnitude range. Based on this aftershock modeling, most of the current seismicity in the Entiat cluster could represent aftershocks of the 1872 earthquake. Other earthquakes, especially those with long recurrence intervals, have long‐lived aftershock sequences, including the Mw">MwMw 7.5 1891 Nobi earthquake in Japan, with aftershocks continuing 100 yrs after the mainshock. Although we do not rule out ongoing tectonic deformation in this region, a long‐lived aftershock sequence can account for these observations.

Spatial distribution of ion energy related on electron density in a plasma channel generated in gas clusters by a femtosecond laser

International Nuclear Information System (INIS)

Nam, S. M.; Han, J. M.; Cha, Y. H.; Lee, Y. W.; Rhee, Y. J.; Cha, H. K.

2008-01-01

Neutron generation through Coulomb explosion of deuterium contained gas clusters is known as one of the very effective methods to produce fusion neutrons using a table top terawatt laser. The energy of ions produced through Coulomb explosions is very important factor to generate neutrons efficiently. Until the ion energy reaches around∼MeV level, the D D fusion reaction probability increases exponentially. The understanding of laser beam propagation and laser energy deposition in clusters is very important to improve neutron yields. As the laser beam propagates through clusters medium, laser energy is absorbed in clusters by ionization of molecules consisting clusters. When the backing pressure of gas increases, the average size of clusters increases and which results in higher energy absorption and earlier termination of laser propagation. We first installed a Michelson interferometer to view laser beam traces in a cluster plume and to measure spatial electron density profiles of a plasma channel which was produced by a laser beam. And then we measured the energy of ions distributed along the plasma channel with a translating slit to select ions from narrow parts of a plasma channel. In our experiments, methane gas was used to produce gas clusters at a room temperature and the energy distribution of proton ions for different gas backing pressure were measured by the time of flight method using dual micro channel plates. By comparing the distribution of ion energies and electron densities, we could understand the condition for effective laser energy delivery to clusters

Separate and unequal: the influence of neighborhood and school characteristics on spatial proximity between fast food and schools.

Science.gov (United States)

Kwate, Naa Oyo A; Loh, Ji Meng

2010-08-01

Social science and health literature have identified residential segregation as a critical factor in exposure to health-related resources, including food environments. Differential spatial patterning of food environments surrounding schools has significant import for youth. We examined whether fast food restaurants clustered around schools in New York City, and whether any observed clustering varied as a function of school type, school racial demographics, and area racial and socioeconomic demographics. We geocoded fast food locations from 2006 (n=817) and schools from 2004-2005 (n=2096; public and private, elementary and secondary) in the five boroughs of New York City. A point process model (inhomogeneous cross-K function) examined spatial clustering. A minimum of 25% of schools had a fast food restaurant within 400 m. High schools had higher fast food clustering than elementary schools. Public elementary and high schools with large proportions of Black students or in block groups with large proportions of Black residents had higher clustering than White counterparts. Finally, public high schools had higher clustering than private counterparts, with 1.25 to 2 times as many restaurants than expected by chance. The results suggest that the geography of opportunity as it relates to school food environments is unequal in New York City. Copyright 2010 Elsevier Inc. All rights reserved.

Functional Equivalence of Spatial Images from Touch and Vision: Evidence from Spatial Updating in Blind and Sighted Individuals

Science.gov (United States)

Giudice, Nicholas A.; Betty, Maryann R.; Loomis, Jack M.

2011-01-01

This research examined whether visual and haptic map learning yield functionally equivalent spatial images in working memory, as evidenced by similar encoding bias and updating performance. In 3 experiments, participants learned 4-point routes either by seeing or feeling the maps. At test, blindfolded participants made spatial judgments about the…

Density functional calculations on 13-atom Pd12M (M = Sc—Ni) bimetallic clusters

International Nuclear Information System (INIS)

Tang Chun-Mei; Chen Sheng-Wei; Zhu Wei-Hua; Tao Cheng-Jun; Zhang Ai-Mei; Gong Jiang-Feng; Zou Hua; Liu Ming-Yi; Zhu Feng

2012-01-01

The geometric structures, electronic and magnetic properties of the 3d transition metal doped clusters Pd 12 M (M = Sc—Ni) are studied using the semi-core pseudopots density functional theory. The groundstate geometric structure of the Pd 12 M cluster is probably of pseudoicosahedron. The I h -Pd 12 M cluster has the most thermodynamic stability in five different symmetric isomers. The energy gap shows that Pd 12 M cluster is partly metallic. Both the absolutely predominant metal bond and very weak covalent bond might exist in the Pd 12 M cluster. The magnetic moment of Pd 12 M varies from 0 to 5 μ B , implying that it has a potential application in new nanomaterials with tunable magnetic properties

Spatial model of the gecko foot hair: functional significance of highly specialized non-uniform geometry.

Science.gov (United States)

Filippov, Alexander E; Gorb, Stanislav N

2015-02-06

One of the important problems appearing in experimental realizations of artificial adhesives inspired by gecko foot hair is so-called clusterization. If an artificially produced structure is flexible enough to allow efficient contact with natural rough surfaces, after a few attachment-detachment cycles, the fibres of the structure tend to adhere one to another and form clusters. Normally, such clusters are much larger than original fibres and, because they are less flexible, form much worse adhesive contacts especially with the rough surfaces. Main problem here is that the forces responsible for the clusterization are the same intermolecular forces which attract fibres to fractal surface of the substrate. However, arrays of real gecko setae are much less susceptible to this problem. One of the possible reasons for this is that ends of the seta have more sophisticated non-uniformly distributed three-dimensional structure than that of existing artificial systems. In this paper, we simulated three-dimensional spatial geometry of non-uniformly distributed branches of nanofibres of the setal tip numerically, studied its attachment-detachment dynamics and discussed its advantages versus uniformly distributed geometry.

Machine learning etudes in astrophysics: selection functions for mock cluster catalogs

Energy Technology Data Exchange (ETDEWEB)

Hajian, Amir; Alvarez, Marcelo A.; Bond, J. Richard, E-mail: ahajian@cita.utoronto.ca, E-mail: malvarez@cita.utoronto.ca, E-mail: bond@cita.utoronto.ca [Canadian Institute for Theoretical Astrophysics, University of Toronto, Toronto, ON M5S 3H8 (Canada)

2015-01-01

Making mock simulated catalogs is an important component of astrophysical data analysis. Selection criteria for observed astronomical objects are often too complicated to be derived from first principles. However the existence of an observed group of objects is a well-suited problem for machine learning classification. In this paper we use one-class classifiers to learn the properties of an observed catalog of clusters of galaxies from ROSAT and to pick clusters from mock simulations that resemble the observed ROSAT catalog. We show how this method can be used to study the cross-correlations of thermal Sunya'ev-Zeldovich signals with number density maps of X-ray selected cluster catalogs. The method reduces the bias due to hand-tuning the selection function and is readily scalable to large catalogs with a high-dimensional space of astrophysical features.

Machine learning etudes in astrophysics: selection functions for mock cluster catalogs

International Nuclear Information System (INIS)

Hajian, Amir; Alvarez, Marcelo A.; Bond, J. Richard

2015-01-01

Making mock simulated catalogs is an important component of astrophysical data analysis. Selection criteria for observed astronomical objects are often too complicated to be derived from first principles. However the existence of an observed group of objects is a well-suited problem for machine learning classification. In this paper we use one-class classifiers to learn the properties of an observed catalog of clusters of galaxies from ROSAT and to pick clusters from mock simulations that resemble the observed ROSAT catalog. We show how this method can be used to study the cross-correlations of thermal Sunya'ev-Zeldovich signals with number density maps of X-ray selected cluster catalogs. The method reduces the bias due to hand-tuning the selection function and is readily scalable to large catalogs with a high-dimensional space of astrophysical features

Data-driven inference for the spatial scan statistic

Directory of Open Access Journals (Sweden)

Duczmal Luiz H

2011-08-01

Full Text Available Abstract Background Kulldorff's spatial scan statistic for aggregated area maps searches for clusters of cases without specifying their size (number of areas or geographic location in advance. Their statistical significance is tested while adjusting for the multiple testing inherent in such a procedure. However, as is shown in this work, this adjustment is not done in an even manner for all possible cluster sizes. Results A modification is proposed to the usual inference test of the spatial scan statistic, incorporating additional information about the size of the most likely cluster found. A new interpretation of the results of the spatial scan statistic is done, posing a modified inference question: what is the probability that the null hypothesis is rejected for the original observed cases map with a most likely cluster of size k, taking into account only those most likely clusters of size k found under null hypothesis for comparison? This question is especially important when the p-value computed by the usual inference process is near the alpha significance level, regarding the correctness of the decision based in this inference. Conclusions A practical procedure is provided to make more accurate inferences about the most likely cluster found by the spatial scan statistic.

Gender differences in associations between DSM-5 posttraumatic stress disorder symptom clusters and functional impairment in war veterans.

Science.gov (United States)

Meyer, Eric C; Konecky, Brian; Kimbrel, Nathan A; DeBeer, Bryann B; Marx, Brian P; Schumm, Jeremiah; Penk, Walter E; Gulliver, Suzy Bird; Morissette, Sandra B

2018-05-01

Understanding the links between posttraumatic stress disorder (PTSD) symptoms and functional impairment is essential for assisting veterans in transitioning to civilian life. Moreover, there may be differences between men and women in the relationships between PTSD symptoms and functional impairment. However, no prior studies have examined the links between functional impairment and the revised symptom clusters as defined in the Diagnostic and Statistical Manual of Mental Disorders, 5th ed. (DSM-5; American Psychiatric Association, 2013) or whether the associations between PTSD symptom clusters and functional impairment differ by gender. We examined the associations between the DSM-5 PTSD symptom clusters and functional impairment in 252 trauma-exposed Iraq and Afghanistan war veterans (79 females). Regression analyses included demographic factors and exposure to both combat and military sexual trauma as covariates. In the total sample, both the intrusions cluster (β = .18, p = .045) and the negative alterations in cognition and mood cluster (β = .45, p < .001) were associated with global functional impairment. Among male veterans, global functional impairment was associated only with negative alterations in cognition and mood (β = .52, p < .001). However, by contrast, among female veterans, only marked alterations in arousal and reactivity were associated with global functional impairment (β = .35, p = .027). These findings suggest that there may be important gender differences with respect to the relationship between PTSD symptoms and functional impairment. (PsycINFO Database Record (c) 2018 APA, all rights reserved).

Galaxy clusters in the cosmic web

Science.gov (United States)

Acebrón, A.; Durret, F.; Martinet, N.; Adami, C.; Guennou, L.

2014-12-01

Simulations of large scale structure formation in the universe predict that matter is essentially distributed along filaments at the intersection of which lie galaxy clusters. We have analysed 9 clusters in the redshift range 0.4DAFT/FADA survey, which combines deep large field multi-band imaging and spectroscopic data, in order to detect filaments and/or structures around these clusters. Based on colour-magnitude diagrams, we have selected the galaxies likely to be in the cluster redshift range and studied their spatial distribution. We detect a number of structures and filaments around several clusters, proving that colour-magnitude diagrams are a reliable method to detect filaments around galaxy clusters. Since this method excludes blue (spiral) galaxies at the cluster redshift, we also apply the LePhare software to compute photometric redshifts from BVRIZ images to select galaxy cluster members and study their spatial distribution. We then find that, if only galaxies classified as early-type by LePhare are considered, we obtain the same distribution than with a red sequence selection, while taking into account late-type galaxies just pollutes the background level and deteriorates our detections. The photometric redshift based method therefore does not provide any additional information.

Benchmark CCSD(T) and DFT study of binding energies in Be7 - 12: in search of reliable DFT functional for beryllium clusters

Science.gov (United States)

Labanc, Daniel; Šulka, Martin; Pitoňák, Michal; Černušák, Ivan; Urban, Miroslav; Neogrády, Pavel

2018-05-01

We present a computational study of the stability of small homonuclear beryllium clusters Be7 - 12 in singlet electronic states. Our predictions are based on highly correlated CCSD(T) coupled cluster calculations. Basis set convergence towards the complete basis set limit as well as the role of the 1s core electron correlation are carefully examined. Our CCSD(T) data for binding energies of Be7 - 12 clusters serve as a benchmark for performance assessment of several density functional theory (DFT) methods frequently used in beryllium cluster chemistry. We observe that, from Be10 clusters on, the deviation from CCSD(T) benchmarks is stable with respect to size, and fluctuating within 0.02 eV error bar for most examined functionals. This opens up the possibility of scaling the DFT binding energies for large Be clusters using CCSD(T) benchmark values for smaller clusters. We also tried to find analogies between the performance of DFT functionals for Be clusters and for the valence-isoelectronic Mg clusters investigated recently in Truhlar's group. We conclude that it is difficult to find DFT functionals that perform reasonably well for both beryllium and magnesium clusters. Out of 12 functionals examined, only the M06-2X functional gives reasonably accurate and balanced binding energies for both Be and Mg clusters.

CytoCluster: A Cytoscape Plugin for Cluster Analysis and Visualization of Biological Networks.

Science.gov (United States)

Li, Min; Li, Dongyan; Tang, Yu; Wu, Fangxiang; Wang, Jianxin

2017-08-31

Nowadays, cluster analysis of biological networks has become one of the most important approaches to identifying functional modules as well as predicting protein complexes and network biomarkers. Furthermore, the visualization of clustering results is crucial to display the structure of biological networks. Here we present CytoCluster, a cytoscape plugin integrating six clustering algorithms, HC-PIN (Hierarchical Clustering algorithm in Protein Interaction Networks), OH-PIN (identifying Overlapping and Hierarchical modules in Protein Interaction Networks), IPCA (Identifying Protein Complex Algorithm), ClusterONE (Clustering with Overlapping Neighborhood Expansion), DCU (Detecting Complexes based on Uncertain graph model), IPC-MCE (Identifying Protein Complexes based on Maximal Complex Extension), and BinGO (the Biological networks Gene Ontology) function. Users can select different clustering algorithms according to their requirements. The main function of these six clustering algorithms is to detect protein complexes or functional modules. In addition, BinGO is used to determine which Gene Ontology (GO) categories are statistically overrepresented in a set of genes or a subgraph of a biological network. CytoCluster can be easily expanded, so that more clustering algorithms and functions can be added to this plugin. Since it was created in July 2013, CytoCluster has been downloaded more than 9700 times in the Cytoscape App store and has already been applied to the analysis of different biological networks. CytoCluster is available from http://apps.cytoscape.org/apps/cytocluster.

Interplay between experiments and calculations for organometallic clusters and caged clusters

International Nuclear Information System (INIS)

Nakajima, Atsushi

2015-01-01

Clusters consisting of 10-1000 atoms exhibit size-dependent electronic and geometric properties. In particular, composite clusters consisting of several elements and/or components provide a promising way for a bottom-up approach for designing functional advanced materials, because the functionality of the composite clusters can be optimized not only by the cluster size but also by their compositions. In the formation of composite clusters, their geometric symmetry and dimensionality are emphasized to control the physical and chemical properties, because selective and anisotropic enhancements for optical, chemical, and magnetic properties can be expected. Organometallic clusters and caged clusters are demonstrated as a representative example of designing the functionality of the composite clusters. Organometallic vanadium-benzene forms a one dimensional sandwich structure showing ferromagnetic behaviors and anomalously large HOMO-LUMO gap differences of two spin orbitals, which can be regarded as spin-filter components for cluster-based spintronic devices. Caged clusters of aluminum (Al) are well stabilized both geometrically and electronically at Al 12 X, behaving as a “superatom”

THE REST-FRAME OPTICAL LUMINOSITY FUNCTION OF CLUSTER GALAXIES AT z < 0.8 AND THE ASSEMBLY OF THE CLUSTER RED SEQUENCE

International Nuclear Information System (INIS)

Rudnick, Gregory; Von der Linden, Anja; De Lucia, Gabriella; White, Simon; Pello, Roser; Aragon-Salamanca, Alfonso; Marchesini, Danilo; Clowe, Douglas; Halliday, Claire; Jablonka, Pascale; Milvang-Jensen, Bo; Poggianti, Bianca; Saglia, Roberto; Simard, Luc; Zaritsky, Dennis

2009-01-01

We present the rest-frame optical luminosity function (LF) of red-sequence galaxies in 16 clusters at 0.4 < z < 0.8 drawn from the ESO Distant Cluster Survey (EDisCS). We compare our clusters to an analogous sample from the Sloan Digital Sky Survey (SDSS) and match the EDisCS clusters to their most likely descendants. We measure all LFs down to M ∼ M * + (2.5-3.5). At z < 0.8, the bright end of the LF is consistent with passive evolution but there is a significant buildup of the faint end of the red sequence toward lower redshift. There is a weak dependence of the LF on cluster velocity dispersion for EDisCS but no such dependence for the SDSS clusters. We find tentative evidence that red-sequence galaxies brighter than a threshold magnitude are already in place, and that this threshold evolves to fainter magnitudes toward lower redshifts. We compare the EDisCS LFs with the LF of coeval red-sequence galaxies in the field and find that the bright end of the LFs agree. However, relative to the number of bright red galaxies, the field has more faint red galaxies than clusters at 0.6 < z < 0.8 but fewer at 0.4 < z < 0.6, implying differential evolution. We compare the total light in the EDisCS cluster red sequences to the total red-sequence light in our SDSS cluster sample. Clusters at 0.4 < z < 0.8 must increase their luminosity on the red sequence (and therefore stellar mass in red galaxies) by a factor of 1-3 by z = 0. The necessary processes that add mass to the red sequence in clusters predict local clusters that are overluminous as compared to those observed in the SDSS. The predicted cluster luminosities can be reconciled with observed local cluster luminosities by combining multiple previously known effects.

Monte Carlo power iteration: Entropy and spatial correlations

International Nuclear Information System (INIS)

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

2016-01-01

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

Spatial clustering of fatal, and non-fatal, suicide in new South Wales, Australia: implications for evidence-based prevention.

Science.gov (United States)

Torok, Michelle; Konings, Paul; Batterham, Philip J; Christensen, Helen

2017-10-06

Rates of suicide appear to be increasing, indicating a critical need for more effective prevention initiatives. To increase the efficacy of future prevention initiatives, we examined the spatial distribution of suicide deaths and suicide attempts in New South Wales (NSW), Australia, to identify where high incidence 'suicide clusters' were occurring. Such clusters represent candidate regions where intervention is critically needed, and likely to have the greatest impact, thus providing an evidence-base for the targeted prioritisation of resources. Analysis is based on official suicide mortality statistics for NSW, provided by the Australian Bureau of Statistics, and hospital separations for non-fatal intentional self-harm, provided through the NSW Health Admitted Patient Data Collection at a Statistical Area 2 (SA2) geography. Geographical Information System (GIS) techniques were applied to detect suicide clusters occurring between 2005 and 2013 (aggregated), for persons aged over 5 years. The final dataset contained 5466 mortality and 86,017 non-fatal intentional self-harm cases. In total, 25 Local Government Areas were identified as primary or secondary likely candidate regions for intervention. Together, these regions contained approximately 200 SA2 level suicide clusters, which represented 46% (n = 39,869) of hospital separations and 43% (n = 2330) of suicide deaths between 2005 and 2013. These clusters primarily converged on the Eastern coastal fringe of NSW. Crude rates of suicide deaths and intentional self-harm differed at the Local Government Areas (LGA) level in NSW. There was a tendency for primary suicide clusters to occur within metropolitan and coastal regions, rather than rural areas. The findings demonstrate the importance of taking geographical variation of suicidal behaviour into account, prior to development and implementation of prevention initiatives, so that such initiatives can target key problem areas where they are likely to have

Modification of response functions of cat visual cortical cells by spatially congruent perturbing stimuli.

Science.gov (United States)

Kabara, J F; Bonds, A B

2001-12-01

Responses of cat striate cortical cells to a drifting sinusoidal grating were modified by the superimposition of a second, perturbing grating (PG) that did not excite the cell when presented alone. One consequence of the presence of a PG was a shift in the tuning curves. The orientation tuning of all 41 cells exposed to a PG and the spatial frequency tuning of 83% of the 23 cells exposed to a PG showed statistically significant dislocations of both the response function peak and center of mass from their single grating values. As found in earlier reports, the presence of PGs suppressed responsiveness. However, reductions measured at the single grating optimum orientation or spatial frequency were on average 1.3 times greater than the suppression found at the peak of the response function modified by the presence of the PG. Much of the loss in response seen at the single grating optimum is thus a result of a shift in the tuning function rather than outright suppression. On average orientation shifts were repulsive and proportional (approximately 0.10 deg/deg) to the angle between the perturbing stimulus and the optimum single grating orientation. Shifts in the spatial frequency response function were both attractive and repulsive, resulting in an overall average of zero. For both simple and complex cells, PGs generally broadened orientation response function bandwidths. Similarly, complex cell spatial frequency response function bandwidths broadened. Simple cell spatial frequency response functions usually did not change, and those that did broadened only 4% on average. These data support the hypothesis that additional sinusoidal components in compound stimuli retune cells' response functions for orientation and spatial frequency.

Second-order analysis of inhomogeneous spatial point processes with proportional intensity functions

DEFF Research Database (Denmark)

Guan, Yongtao; Waagepetersen, Rasmus; Beale, Colin M.

2008-01-01

of the intensity functions. The first approach is based on nonparametric kernel-smoothing, whereas the second approach uses a conditional likelihood estimation approach to fit a parametric model for the pair correlation function. A great advantage of the proposed methods is that they do not require the often...... to two spatial point patterns regarding the spatial distributions of birds in the U.K.'s Peak District in 1990 and 2004....

A Cluster of CO2 Change Characteristics with GOSAT Observations for Viewing the Spatial Pattern of CO2 Emission and Absorption

Directory of Open Access Journals (Sweden)

Da Liu

2015-11-01

Full Text Available Satellite observations can be used to detect the changes of CO2 concentration at global and regional scales. With the column-averaged CO2 dry-air mole fraction (Xco2 data derived from satellite observations, the issue is how to extract and assess these changes, which are related to anthropogenic emissions and biosphere absorptions. We propose a k-means cluster analysis to extract the temporally changing features of Xco2 in the Central-Eastern Asia using the data from 2009 to 2013 obtained by Greenhouse Gases Observing Satellite (GOSAT, and assess the effects of anthropogenic emissions and biosphere absorptions on CO2 changes combining with the data of emission and vegetation net primary production (NPP. As a result, 14 clusters, which are 14 types of Xco2 seasonal changing patterns, are obtained in the study area by using the optimal clustering parameters. These clusters are generally in agreement with the spatial pattern of underlying anthropogenic emissions and vegetation absorptions. According to correlation analysis with emission and NPP, these 14 clusters are divided into three groups: strong emission, strong absorption, and a tendency of balancing between emission and absorption. The proposed clustering approach in this study provides us with a potential way to better understand how the seasonal changes of CO2 concentration depend on underlying anthropogenic emissions and vegetation absorptions.

Enhancing spatial detection accuracy for syndromic surveillance with street level incidence data

Directory of Open Access Journals (Sweden)

Alemi Farrokh

2010-01-01

Full Text Available Abstract Background The Department of Defense Military Health System operates a syndromic surveillance system that monitors medical records at more than 450 non-combat Military Treatment Facilities (MTF worldwide. The Electronic Surveillance System for Early Notification of Community-based Epidemics (ESSENCE uses both temporal and spatial algorithms to detect disease outbreaks. This study focuses on spatial detection and attempts to improve the effectiveness of the ESSENCE implementation of the spatial scan statistic by increasing the spatial resolution of incidence data from zip codes to street address level. Methods Influenza-Like Illness (ILI was used as a test syndrome to develop methods to improve the spatial accuracy of detected alerts. Simulated incident clusters of various sizes were superimposed on real ILI incidents from the 2008/2009 influenza season. Clusters were detected using the spatial scan statistic and their displacement from simulated loci was measured. Detected cluster size distributions were also evaluated for compliance with simulated cluster sizes. Results Relative to the ESSENCE zip code based method, clusters detected using street level incidents were displaced on average 65% less for 2 and 5 mile radius clusters and 31% less for 10 mile radius clusters. Detected cluster size distributions for the street address method were quasi normal and sizes tended to slightly exceed simulated radii. ESSENCE methods yielded fragmented distributions and had high rates of zero radius and oversized clusters. Conclusions Spatial detection accuracy improved notably with regard to both location and size when incidents were geocoded to street addresses rather than zip code centroids. Since street address geocoding success rates were only 73.5%, zip codes were still used for more than one quarter of ILI cases. Thus, further advances in spatial detection accuracy are dependant on systematic improvements in the collection of individual

Segmentation of confocal Raman microspectroscopic imaging data using edge-preserving denoising and clustering.

Science.gov (United States)

Alexandrov, Theodore; Lasch, Peter

2013-06-18

Over the past decade, confocal Raman microspectroscopic (CRM) imaging has matured into a useful analytical tool to obtain spatially resolved chemical information on the molecular composition of biological samples and has found its way into histopathology, cytology, and microbiology. A CRM imaging data set is a hyperspectral image in which Raman intensities are represented as a function of three coordinates: a spectral coordinate λ encoding the wavelength and two spatial coordinates x and y. Understanding CRM imaging data is challenging because of its complexity, size, and moderate signal-to-noise ratio. Spatial segmentation of CRM imaging data is a way to reveal regions of interest and is traditionally performed using nonsupervised clustering which relies on spectral domain-only information with the main drawback being the high sensitivity to noise. We present a new pipeline for spatial segmentation of CRM imaging data which combines preprocessing in the spectral and spatial domains with k-means clustering. Its core is the preprocessing routine in the spatial domain, edge-preserving denoising (EPD), which exploits the spatial relationships between Raman intensities acquired at neighboring pixels. Additionally, we propose to use both spatial correlation to identify Raman spectral features colocalized with defined spatial regions and confidence maps to assess the quality of spatial segmentation. For CRM data acquired from midsagittal Syrian hamster ( Mesocricetus auratus ) brain cryosections, we show how our pipeline benefits from the complex spatial-spectral relationships inherent in the CRM imaging data. EPD significantly improves the quality of spatial segmentation that allows us to extract the underlying structural and compositional information contained in the Raman microspectra.

Cluster evolution

International Nuclear Information System (INIS)

Schaeffer, R.

1987-01-01

The galaxy and cluster luminosity functions are constructed from a model of the mass distribution based on hierarchical clustering at an epoch where the matter distribution is non-linear. These luminosity functions are seen to reproduce the present distribution of objects as can be inferred from the observations. They can be used to deduce the redshift dependence of the cluster distribution and to extrapolate the observations towards the past. The predicted evolution of the cluster distribution is quite strong, although somewhat less rapid than predicted by the linear theory

Triggered cluster formation in the RMC

Science.gov (United States)

Li, Jin Zeng; Smith, Michael D.

An investigation based on data from the spatially complete 2MASS Survey reveals that a remarkable burst of clustered star formation is taking place throughout the south-east quadrant of the Rosette Molecular Cloud. Compact clusters are forming in a multi-seeded mode, in parallel and at various places. In addition, sparse aggregates of embedded young stars are extensively distributed. Here we present the primary results and implications for high-mass and clustered star formation in this giant molecular cloud. In particular, we incorporate for the first time the birth of medium to low-mass stars into the scenario of sequential formation of OB clusters. Following the emergence of the young OB cluster NGC 2244, a variety of manifestations of forming clusters of medium to high mass appear in the vicinity of the swept-up layer of the H II region as well as further into the molecular cloud. The embedded clusters appear to form in a structured manner, which suggests they follow tracks laid out by the decay of macroturbulence. We address the possible origins of the turbulence. This leads us to propose a tree model to interpret the neat spatial distribution of clusters within a large section of the Rosette complex. Prominent new generation OB clusters are identified at the root of the tree pattern.

The Seven Sisters DANCe. I. Empirical isochrones, luminosity, and mass functions of the Pleiades cluster

Science.gov (United States)

Bouy, H.; Bertin, E.; Sarro, L. M.; Barrado, D.; Moraux, E.; Bouvier, J.; Cuillandre, J.-C.; Berihuete, A.; Olivares, J.; Beletsky, Y.

2015-05-01

Context. The DANCe survey provides photometric and astrometric (position and proper motion) measurements for approximately 2 million unique sources in a region encompassing ~80 deg2 centered on the Pleiades cluster. Aims: We aim at deriving a complete census of the Pleiades and measure the mass and luminosity functions of the cluster. Methods: Using the probabilistic selection method previously described, we identified high probability members in the DANCe (i ≥ 14 mag) and Tycho-2 (V ≲ 12 mag) catalogues and studied the properties of the cluster over the corresponding luminosity range. Results: We find a total of 2109 high-probability members, of which 812 are new, making it the most extensive and complete census of the cluster to date. The luminosity and mass functions of the cluster are computed from the most massive members down to ~0.025 M⊙. The size, sensitivity, and quality of the sample result in the most precise luminosity and mass functions observed to date for a cluster. Conclusions: Our census supersedes previous studies of the Pleiades cluster populations, in terms of both sensitivity and accuracy. Based on service observations made with the William Herschel Telescope operated on the island of La Palma by the Isaac Newton Group in the Spanish Observatorio del Roque de los Muchachos of the Instituto de Astrofísica de Canarias.Table 1 and Appendices are available in electronic form at http://www.aanda.orgDANCe catalogs (Tables 6 and 7) and full Tables 2-5 are only available at the CDS via anonymous ftp to http://cdsarc.u-strasbg.fr (ftp://130.79.128.5) or via http://cdsarc.u-strasbg.fr/viz-bin/qcat?J/A+A/577/A148

Multi-scale Clustering of Points Synthetically Considering Lines and Polygons Distribution

Directory of Open Access Journals (Sweden)

YU Li

2015-10-01

Full Text Available Considering the complexity and discontinuity of spatial data distribution, a clustering algorithm of points was proposed. To accurately identify and express the spatial correlation among points,lines and polygons, a Voronoi diagram that is generated by all spatial features is introduced. According to the distribution characteristics of point's position, an area threshold used to control clustering granularity was calculated. Meanwhile, judging scale convergence by constant area threshold, the algorithm classifies spatial features based on multi-scale, with an O(n log n running time.Results indicate that spatial scale converges self-adaptively according with distribution of points.Without the custom parameters, the algorithm capable to discover arbitrary shape clusters which be bound by lines and polygons, and is robust for outliers.

Observation of the inhomogeneous spatial distribution of MeV ions accelerated by the hydrodynamic ambipolar expansion of clusters

International Nuclear Information System (INIS)

Kanasaki, Masato; Jinno, Satoshi; Sakaki, Hironao; Faenov, Anatoly Ya.; Pikuz, Tatiana A.; Nishiuchi, Mamiko; Kiriyama, Hiromitsu; Kando, Masaki; Sugiyama, Akira; Kondo, Kiminori; Matsui, Ryutaro; Kishimoto, Yasuaki; Morishima, Kunihiro; Watanabe, Yukinobu; Scullion, Clare; Smyth, Ashley G.; Alejo, Aaron; Doria, Domenico; Kar, Satyabrata; Borghesi, Marco

2015-01-01

An inhomogeneous spatial distribution of laser accelerated carbon/oxygen ions produced via the hydrodynamic ambipolar expansion of CO_2 clusters has been measured by using CR-39 detectors. An inhomogeneous etch pits spatial distribution has appeared on the etched CR-39 detector installed on the laser propagation direction, while homogeneous ones are appeared on those installed at 45° and 90° from the laser propagation direction. From the range of ions in CR-39 obtained by using the multi-step etching technique, the averaged energies of carbon/oxygen ions for all directions are determined as 0.78 ± 0.09 MeV/n. The number of ions in the laser propagation direction is about 1.5 times larger than those in other directions. The inhomogeneous etch pits spatial distribution in the laser propagation direction could originate from an ion beam collimation and modulation by the effect of electromagnetic structures created in the laser plasma. - Highlights: • A spatial distribution of ions due to hydrodynamic ambipolar expansion is measured. • The homogeneous ion energy distribution of 0.78 ± 0.09 MeV/n is measured by CR-39. • The number of ions in the laser axis is about 1.5 times larger than other directions.

Spatial scan statistics using elliptic windows

DEFF Research Database (Denmark)

Christiansen, Lasse Engbo; Andersen, Jens Strodl; Wegener, Henrik Caspar

The spatial scan statistic is widely used to search for clusters in epidemiologic data. This paper shows that the usually applied elimination of secondary clusters as implemented in SatScan is sensitive to smooth changes in the shape of the clusters. We present an algorithm for generation of set...

flowPeaks: a fast unsupervised clustering for flow cytometry data via K-means and density peak finding.

Science.gov (United States)

Ge, Yongchao; Sealfon, Stuart C

2012-08-01

For flow cytometry data, there are two common approaches to the unsupervised clustering problem: one is based on the finite mixture model and the other on spatial exploration of the histograms. The former is computationally slow and has difficulty to identify clusters of irregular shapes. The latter approach cannot be applied directly to high-dimensional data as the computational time and memory become unmanageable and the estimated histogram is unreliable. An algorithm without these two problems would be very useful. In this article, we combine ideas from the finite mixture model and histogram spatial exploration. This new algorithm, which we call flowPeaks, can be applied directly to high-dimensional data and identify irregular shape clusters. The algorithm first uses K-means algorithm with a large K to partition the cell population into many small clusters. These partitioned data allow the generation of a smoothed density function using the finite mixture model. All local peaks are exhaustively searched by exploring the density function and the cells are clustered by the associated local peak. The algorithm flowPeaks is automatic, fast and reliable and robust to cluster shape and outliers. This algorithm has been applied to flow cytometry data and it has been compared with state of the art algorithms, including Misty Mountain, FLOCK, flowMeans, flowMerge and FLAME. The R package flowPeaks is available at https://github.com/yongchao/flowPeaks. yongchao.ge@mssm.edu Supplementary data are available at Bioinformatics online.

Comparing Residue Clusters from Thermophilic and Mesophilic Enzymes Reveals Adaptive Mechanisms.

Science.gov (United States)

Sammond, Deanne W; Kastelowitz, Noah; Himmel, Michael E; Yin, Hang; Crowley, Michael F; Bomble, Yannick J

2016-01-01

Understanding how proteins adapt to function at high temperatures is important for deciphering the energetics that dictate protein stability and folding. While multiple principles important for thermostability have been identified, we lack a unified understanding of how internal protein structural and chemical environment determine qualitative or quantitative impact of evolutionary mutations. In this work we compare equivalent clusters of spatially neighboring residues between paired thermophilic and mesophilic homologues to evaluate adaptations under the selective pressure of high temperature. We find the residue clusters in thermophilic enzymes generally display improved atomic packing compared to mesophilic enzymes, in agreement with previous research. Unlike residue clusters from mesophilic enzymes, however, thermophilic residue clusters do not have significant cavities. In addition, anchor residues found in many clusters are highly conserved with respect to atomic packing between both thermophilic and mesophilic enzymes. Thus the improvements in atomic packing observed in thermophilic homologues are not derived from these anchor residues but from neighboring positions, which may serve to expand optimized protein core regions.

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

Directory of Open Access Journals (Sweden)

Angelo Mazza

2016-07-01

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

Hot spots, cluster detection and spatial outlier analysis of teen birth rates in the U.S., 2003-2012.

Science.gov (United States)

Khan, Diba; Rossen, Lauren M; Hamilton, Brady E; He, Yulei; Wei, Rong; Dienes, Erin

2017-06-01

Teen birth rates have evidenced a significant decline in the United States over the past few decades. Most of the states in the US have mirrored this national decline, though some reports have illustrated substantial variation in the magnitude of these decreases across the U.S. Importantly, geographic variation at the county level has largely not been explored. We used National Vital Statistics Births data and Hierarchical Bayesian space-time interaction models to produce smoothed estimates of teen birth rates at the county level from 2003-2012. Results indicate that teen birth rates show evidence of clustering, where hot and cold spots occur, and identify spatial outliers. Findings from this analysis may help inform efforts targeting the prevention efforts by illustrating how geographic patterns of teen birth rates have changed over the past decade and where clusters of high or low teen birth rates are evident. Published by Elsevier Ltd.

Covalent functionalization of octagraphene with magnetic octahedral B6- and non-planar C6- clusters

Science.gov (United States)

Chigo-Anota, E.; Cárdenas-Jirón, G.; Salazar Villanueva, M.; Bautista Hernández, A.; Castro, M.

2017-10-01

The interaction between the magnetic boron octahedral (B6-) and non-planar (C6-) carbon clusters with semimetal nano-sheet of octa-graphene (C64H24) in the gas phase is studied by means of DFT calculations. These results reveal that non-planar-1 (anion) carbon cluster exhibits structural stability, low chemical reactivity, magnetic (1.0 magneton bohr) and semiconductor behavior. On the other hand, there is chemisorption phenomena when the stable B6- and C6- clusters are absorbed on octa-graphene nanosheets. Such absorption generates high polarity and the low-reactivity remains as on the individual pristine cases. Electronic charge transference occurs from the clusters toward the nanosheets, producing a reduction of the work function for the complexes and also induces a magnetic behavior on the functionalized sheets. The quantum descriptors obtained for these systems reveal that they are feasible candidates for the design of molecular circuits, magnetic devices, and nano-vehicles for drug delivery.

A temporal analysis of the spatial clustering of food outlets around schools in Christchurch, New Zealand, 1966 to 2006.

Science.gov (United States)

Day, Peter L; Pearce, Jamie R; Pearson, Amber L

2015-01-01

To explore changes in urban food environments near schools, as potential contributors to the rising prevalence of overweight and obesity among children. Addresses of food premises and schools in 1966, 1976, 1986, 1996 and 2006 were geo-coded. For each year, the number and proportion of outlets by category (supermarket/grocery; convenience; fast-food outlet) within 800 m of schools were calculated. The degree of spatial clustering of outlets was assessed using a bivariate K-function analysis. Food outlet categories, school level and school social deprivation quintiles were compared. Christchurch, New Zealand. All schools and food outlets at 10-year snapshots from 1966 to 2006. Between 1966 and 2006, the median number of supermarkets/grocery stores within 800 m of schools decreased from 5 to 1, convenience stores decreased from 2 to 1, and fast-food outlets increased from 1 to 4. The ratio of fast-food outlets to total outlets increased from 0·10 to 0·67. The clustering of fast-food outlets was greatest within 800 m of schools and around the most socially deprived schools. Over the 40-year study period, school food environments in Christchurch can be characterized by increased densities of fast-food outlets within walking distance of schools, especially around the most deprived schools. Since the 1960s, there have been substantial changes to the food environments around schools which may increasingly facilitate away-from-home food consumption for children and provide easily accessible, cheap energy-dense foods, a recognized contributor to the rise in prevalence of overweight and obesity among young people.

Spatial scan statistics using elliptic windows

DEFF Research Database (Denmark)

Christiansen, Lasse Engbo; Andersen, Jens Strodl; Wegener, Henrik Caspar

2006-01-01

The spatial scan statistic is widely used to search for clusters. This article shows that the usually applied elimination of secondary clusters as implemented in SatScan is sensitive to smooth changes in the shape of the clusters. We present an algorithm for generation of a set of confocal elliptic...

A full scale approximation of covariance functions for large spatial data sets

KAUST Repository

Sang, Huiyan

2011-10-10

Gaussian process models have been widely used in spatial statistics but face tremendous computational challenges for very large data sets. The model fitting and spatial prediction of such models typically require O(n 3) operations for a data set of size n. Various approximations of the covariance functions have been introduced to reduce the computational cost. However, most existing approximations cannot simultaneously capture both the large- and the small-scale spatial dependence. A new approximation scheme is developed to provide a high quality approximation to the covariance function at both the large and the small spatial scales. The new approximation is the summation of two parts: a reduced rank covariance and a compactly supported covariance obtained by tapering the covariance of the residual of the reduced rank approximation. Whereas the former part mainly captures the large-scale spatial variation, the latter part captures the small-scale, local variation that is unexplained by the former part. By combining the reduced rank representation and sparse matrix techniques, our approach allows for efficient computation for maximum likelihood estimation, spatial prediction and Bayesian inference. We illustrate the new approach with simulated and real data sets. © 2011 Royal Statistical Society.

A full scale approximation of covariance functions for large spatial data sets

KAUST Repository

Sang, Huiyan; Huang, Jianhua Z.

2011-01-01

Gaussian process models have been widely used in spatial statistics but face tremendous computational challenges for very large data sets. The model fitting and spatial prediction of such models typically require O(n 3) operations for a data set of size n. Various approximations of the covariance functions have been introduced to reduce the computational cost. However, most existing approximations cannot simultaneously capture both the large- and the small-scale spatial dependence. A new approximation scheme is developed to provide a high quality approximation to the covariance function at both the large and the small spatial scales. The new approximation is the summation of two parts: a reduced rank covariance and a compactly supported covariance obtained by tapering the covariance of the residual of the reduced rank approximation. Whereas the former part mainly captures the large-scale spatial variation, the latter part captures the small-scale, local variation that is unexplained by the former part. By combining the reduced rank representation and sparse matrix techniques, our approach allows for efficient computation for maximum likelihood estimation, spatial prediction and Bayesian inference. We illustrate the new approach with simulated and real data sets. © 2011 Royal Statistical Society.

Spatial structure of a natural mixed topodeme of subalpine Sorbus taxa

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Dušan Gömöry

2011-01-01

Full Text Available Spatial distribution and genetic variation of a population of Sorbus chamaemespilus (L. Crantz and putative hybrids between S. chamaemespilus, S. aria and S. aucuparia growing in the nature reserve Skalnä Alpa (central Slovakia were studied. The analysis of spatial patterns using Ripley's K-function revealed a significant clustering of the adults of both S. chamaemespilus and hybrid taxa at distances up to ~15 m and a strong affinity between both taxonomical groups, indicating similar ecological requirements. Bivariate point-pattern analysis considering cardinal direction showed that juvenile individuals of S. chamaemespilus are clustered around the adults up to the distance of ~2 m, whereas in hybrid taxa with larger and more dense crowns, juveniles are clustered at distances more than ~3 m from the adults. The analysis of genetic variation in a subset of adult shrubs using 4 nuclear microsatellite loci revealed that unlike expected, there was no variation in S. chamaemespilus but several genotypes were found in the group of hybrid taxa. Implications for the reproduction system and conservation of the investigated taxa are discussed.

Selective memory generalization by spatial patterning of protein synthesis.

Science.gov (United States)

O'Donnell, Cian; Sejnowski, Terrence J

2014-04-16

Protein synthesis is crucial for both persistent synaptic plasticity and long-term memory. De novo protein expression can be restricted to specific neurons within a population, and to specific dendrites within a single neuron. Despite its ubiquity, the functional benefits of spatial protein regulation for learning are unknown. We used computational modeling to study this problem. We found that spatially patterned protein synthesis can enable selective consolidation of some memories but forgetting of others, even for simultaneous events that are represented by the same neural population. Key factors regulating selectivity include the functional clustering of synapses on dendrites, and the sparsity and overlap of neural activity patterns at the circuit level. Based on these findings, we proposed a two-step model for selective memory generalization during REM and slow-wave sleep. The pattern-matching framework we propose may be broadly applicable to spatial protein signaling throughout cortex and hippocampus. Copyright © 2014 Elsevier Inc. All rights reserved.

Which Density Functional Should Be Used to Describe Protonated Water Clusters?

Science.gov (United States)

Shi, Ruili; Huang, Xiaoming; Su, Yan; Lu, Hai-Gang; Li, Si-Dian; Tang, Lingli; Zhao, Jijun

2017-04-27

Protonated water cluster is one of the most important hydrogen-bond network systems. Finding an appropriate DFT method to study the properties of protonated water clusters can substantially improve the economy in computational resources without sacrificing the accuracy compared to high-level methods. Using high-level MP2 and CCSD(T) methods as well as experimental results as benchmark, we systematically examined the effect of seven exchange-correlation GGA functionals (with BLYP, B3LYP, X3LYP, PBE0, PBE1W, M05-2X, and B97-D parametrizations) in describing the geometric parameters, interaction energies, dipole moments, and vibrational properties of protonated water clusters H + (H 2 O) 2-9,12 . The overall performance of all these functionals is acceptable, and each of them has its advantage in certain aspects. X3LYP is the best to describe the interaction energies, and PBE0 and M05-2X are also recommended to investigate interaction energies. PBE0 gives the best anharmonic frequencies, followed by PBE1W, B97-D and BLYP methods. PBE1W, B3LYP, B97-D, and X3LYP can yield better geometries. The capability of B97-D to distinguish the relative energies between isomers is the best among all the seven methods, followed by M05-2X and PBE0.

Traveling cluster approximation for uncorrelated amorphous systems

International Nuclear Information System (INIS)

Kaplan, T.; Sen, A.K.; Gray, L.J.; Mills, R.

1985-01-01

In this paper, the authors apply the TCA concepts to spatially disordered, uncorrelated systems (e.g., fluids or amorphous metals without short-range order). This is the first approximation scheme for amorphous systems that takes cluster effects into account while preserving the Herglotz property for any amount of disorder. They have performed some computer calculations for the pair TCA, for the model case of delta-function potentials on a one-dimensional random chain. These results are compared with exact calculations (which, in principle, taken into account all cluster effects) and with the CPA, which is the single-site TCA. The density of states for the pair TCA clearly shows some improvement over the CPA, and yet, apparently, the pair approximation distorts some of the features of the exact results. They conclude that the effects of large clusters are much more important in an uncorrelated liquid metal than in a substitutional alloy. As a result, the pair TCA, which does quite a nice job for alloys, is not adequate for the liquid. Larger clusters must be treated exactly, and therefore an n-TCA with n > 2 must be used

Clusters of Insomnia Disorder: An Exploratory Cluster Analysis of Objective Sleep Parameters Reveals Differences in Neurocognitive Functioning, Quantitative EEG, and Heart Rate Variability

Science.gov (United States)

Miller, Christopher B.; Bartlett, Delwyn J.; Mullins, Anna E.; Dodds, Kirsty L.; Gordon, Christopher J.; Kyle, Simon D.; Kim, Jong Won; D'Rozario, Angela L.; Lee, Rico S.C.; Comas, Maria; Marshall, Nathaniel S.; Yee, Brendon J.; Espie, Colin A.; Grunstein, Ronald R.

2016-01-01

Study Objectives: To empirically derive and evaluate potential clusters of Insomnia Disorder through cluster analysis from polysomnography (PSG). We hypothesized that clusters would differ on neurocognitive performance, sleep-onset measures of quantitative (q)-EEG and heart rate variability (HRV). Methods: Research volunteers with Insomnia Disorder (DSM-5) completed a neurocognitive assessment and overnight PSG measures of total sleep time (TST), wake time after sleep onset (WASO), and sleep onset latency (SOL) were used to determine clusters. Results: From 96 volunteers with Insomnia Disorder, cluster analysis derived at least two clusters from objective sleep parameters: Insomnia with normal objective sleep duration (I-NSD: n = 53) and Insomnia with short sleep duration (I-SSD: n = 43). At sleep onset, differences in HRV between I-NSD and I-SSD clusters suggest attenuated parasympathetic activity in I-SSD (P insomnia clusters derived from cluster analysis differ in sleep onset HRV. Preliminary data suggest evidence for three clusters in insomnia with differences for sustained attention and sleep-onset q-EEG. Clinical Trial Registration: Insomnia 100 sleep study: Australia New Zealand Clinical Trials Registry (ANZCTR) identification number 12612000049875. URL: https://www.anzctr.org.au/Trial/Registration/TrialReview.aspx?id=347742. Citation: Miller CB, Bartlett DJ, Mullins AE, Dodds KL, Gordon CJ, Kyle SD, Kim JW, D'Rozario AL, Lee RS, Comas M, Marshall NS, Yee BJ, Espie CA, Grunstein RR. Clusters of Insomnia Disorder: an exploratory cluster analysis of objective sleep parameters reveals differences in neurocognitive functioning, quantitative EEG, and heart rate variability. SLEEP 2016;39(11):1993–2004. PMID:27568796

Socio-Spatial Typology In Karanrang Island

Directory of Open Access Journals (Sweden)

Amin Ishak Rahmi

2018-01-01

Full Text Available The phenomenon of community life on the small island is influenced by the stimulating factor of harmonious social interaction system through cooperation, kinship, economic activity, children playing, transportation system, religion and other social activities. The social dynamics of small island communities appear in the layout and environment in which they live, how they manage and utilize space, both indoors and outdoors. The purpose of this paper is to describe the socio-spatial typology of settlements on Karanrang Island, including a description of the spatial pattern of communalenvironments. Research approaches through spatial similarities and differences in the classification of behavioral setting, including physical, non-physical, socio-spatial arrangements. Karanrang Island as a research focus which has an area of 7.8 Ha is one of small islands inhabited in cluster PangkajeneIslands (Pangkep South Sulawesi, with characteristic of dense settlement, and diversity of tribe, also inhabited by 434 families. The method of this research is observation, data collection through field survey with descriptive analysis based on empirical data on meso / environment which is divided into:1 inter building space; 2 Space in the building; 3 Open space, and; 4 Environmental facilities. The results showed that classification of socio-spatial typology of communal environment is divided into four types of socio-spatial models based on the configuration of social interaction activities, namely:1 Type of Linear Centripetal, at the inter buildings space; 2 Type of Centripetal Cluster, space on the building; 3 Type of Centrifugal Cluster, at green open space/field; 4 Type of cluster Centripetal, at environmental facilities. The socio-spatial type based on actor’s activities, occupancy, and territory, can be distinguished on: 1 Type of children’s activity; 2 Type of mother’sactivity; 3 Type of father’s activity, and 4 Type of combination activity.

Spatial-Temporal Event Detection from Geo-Tagged Tweets

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Yuqian Huang

2018-04-01

Full Text Available As one of the most popular social networking services in the world, Twitter allows users to post messages along with their current geographic locations. Such georeferenced or geo-tagged Twitter datasets can benefit location-based services, targeted advertising and geosocial studies. Our study focused on the detection of small-scale spatial-temporal events and their textual content. First, we used Spatial-Temporal Density-Based Spatial Clustering of Applications with Noise (ST-DBSCAN to spatially-temporally cluster the tweets. Then, the word frequencies were summarized for each cluster and the potential topics were modeled by the Latent Dirichlet Allocation (LDA algorithm. Using two years of Twitter data from four college cities in the U.S., we were able to determine the spatial-temporal patterns of two known events, two unknown events and one recurring event, which then were further explored and modeled to identify the semantic content about the events. This paper presents our process and recommendations for both finding event-related tweets as well as understanding the spatial-temporal behaviors and semantic natures of the detected events.

Partitioning the impact of environment and spatial structure on alpha and beta components of taxonomic, functional, and phylogenetic diversity in European ants.

Science.gov (United States)

Arnan, Xavier; Cerdá, Xim; Retana, Javier

2015-01-01

We analyze the relative contribution of environmental and spatial variables to the alpha and beta components of taxonomic (TD), phylogenetic (PD), and functional (FD) diversity in ant communities found along different climate and anthropogenic disturbance gradients across western and central Europe, in order to assess the mechanisms structuring ant biodiversity. To this aim we calculated alpha and beta TD, PD, and FD for 349 ant communities, which included a total of 155 ant species; we examined 10 functional traits and phylogenetic relatedness. Variation partitioning was used to examine how much variation in ant diversity was explained by environmental and spatial variables. Autocorrelation in diversity measures and each trait's phylogenetic signal were also analyzed. We found strong autocorrelation in diversity measures. Both environmental and spatial variables significantly contributed to variation in TD, PD, and FD at both alpha and beta scales; spatial structure had the larger influence. The different facets of diversity showed similar patterns along environmental gradients. Environment explained a much larger percentage of variation in FD than in TD or PD. All traits demonstrated strong phylogenetic signals. Our results indicate that environmental filtering and dispersal limitations structure all types of diversity in ant communities. Strong dispersal limitations appear to have led to clustering of TD, PD, and FD in western and central Europe, probably because different historical and evolutionary processes generated different pools of species. Remarkably, these three facets of diversity showed parallel patterns along environmental gradients. Trait-mediated species sorting and niche conservatism appear to structure ant diversity, as evidenced by the fact that more variation was explained for FD and that all traits had strong phylogenetic signals. Since environmental variables explained much more variation in FD than in PD, functional diversity should be a

The Spatial Distribution of Galaxies of Different Spectral Types in the Massive Intermediate-Redshift Cluster MACS J0717.5+3745

Science.gov (United States)

Ma, Cheng-Jiun; Ebeling, Harald; Donovan, David; Barrett, Elizabeth

2008-09-01

We present the results of a wide-field spectroscopic analysis of the galaxy population of the massive cluster MACS J0717.5+3745 and the surrounding filamentary structure (z = 0.55), as part of our systematic study of the 12 most distant clusters in the MACS sample. Of 1368 galaxies spectroscopically observed in this field, 563 are identified as cluster members; of those, 203 are classified as emission-line galaxies, 260 as absorption-line galaxies, and 17 as E+A galaxies (defined by (H δ + H γ )/2 > 6 Å and no detection of [O II] and Hβ in emission). The variation of the fraction of emission- and absorption-line galaxies as a function of local projected galaxy density confirms the well-known morphology-density relation, and becomes flat at projected galaxy densities less than ~20 Mpc-2. Interestingly, 16 out of 17 E+A galaxies lie (in projection) within the ram-pressure stripping radius around the cluster core, which we take to be direct evidence that ram-pressure stripping is the primary mechanism that terminates star formation in the E+A population of galaxy clusters. This conclusion is supported by the rarity of E+A galaxies in the filament, which rules out galaxy mergers as the dominant driver of evolution for E+A galaxies in clusters. In addition, we find that the 42 e(a) and 27 e(b) member galaxies, i.e., the dusty-starburst and starburst galaxies respectively, are spread out across almost the entire study area. Their spatial distribution, which shows a strong preference for the filament region, suggests that starbursts are triggered in relatively low-density environments as galaxies are accreted from the field population. Based in part on data collected at Subaru Telescope, which is operated by the National Astronomical Observatory of Japan. Based also in part on observations obtained with MegaPrime/MegaCam, a joint project of CFHT and CEA/DAPNIA, at the Canada-France-Hawaii Telescope (CFHT), which is operated by the National Research Council (NRC) of

Cosmological constraints from Chandra observations of galaxy clusters.

Science.gov (United States)

Allen, Steven W

2002-09-15

Chandra observations of rich, relaxed galaxy clusters allow the properties of the X-ray gas and the total gravitating mass to be determined precisely. Here, we present results for a sample of the most X-ray luminous, dynamically relaxed clusters known. We show that the Chandra data and independent gravitational lensing studies provide consistent answers on the mass distributions in the clusters. The mass profiles exhibit a form in good agreement with the predictions from numerical simulations. Combining Chandra results on the X-ray gas mass fractions in the clusters with independent measurements of the Hubble constant and the mean baryonic matter density in the Universe, we obtain a tight constraint on the mean total matter density of the Universe, Omega(m), and an interesting constraint on the cosmological constant, Omega(Lambda). We also describe the 'virial relations' linking the masses, X-ray temperatures and luminosities of galaxy clusters. These relations provide a key step in linking the observed number density and spatial distribution of clusters to the predictions from cosmological models. The Chandra data confirm the presence of a systematic offset of ca. 40% between the normalization of the observed mass-temperature relation and the predictions from standard simulations. This finding leads to a significant revision of the best-fit value of sigma(8) inferred from the observed temperature and luminosity functions of clusters.

One- and two-particle correlation functions in the dynamical quantum cluster approach

International Nuclear Information System (INIS)

Hochkeppel, Stephan

2008-01-01

This thesis is dedicated to a theoretical study of the 1-band Hubbard model in the strong coupling limit. The investigation is based on the Dynamical Cluster Approximation (DCA) which systematically restores non-local corrections to the Dynamical Mean Field approximation (DMFA). The DCA is formulated in momentum space and is characterised by a patching of the Brillouin zone where momentum conservation is only recovered between two patches. The approximation works well if k-space correlation functions show a weak momentum dependence. In order to study the temperature and doping dependence of the spin- and charge excitation spectra, we explicitly extend the Dynamical Cluster Approximation to two-particle response functions. The full irreducible two-particle vertex with three momenta and frequencies is approximated by an effective vertex dependent on the momentum and frequency of the spin and/or charge excitations. The effective vertex is calculated by using the Quantum Monte Carlo method on the finite cluster whereas the analytical continuation of dynamical quantities is performed by a stochastic version of the maximum entropy method. A comparison with high temperature auxiliary field quantum Monte Carlo data serves as a benchmark for our approach to two-particle correlation functions. Our method can reproduce basic characteristics of the spin- and charge excitation spectrum. Near and beyond optimal doping, our results provide a consistent overall picture of the interplay between charge, spin and single-particle excitations: a collective spin mode emerges at optimal doping and sufficiently low temperatures in the spin response spectrum and exhibits the energy scale of the magnetic exchange interaction J. Simultaneously, the low energy single-particle excitations are characterised by a coherent quasiparticle with bandwidth J. The origin of the quasiparticle can be quite well understood in a picture of a more or less antiferromagnetic ordered background in which holes

SPATIAL ANISOTROPY OF GALAXY KINEMATICS IN SLOAN DIGITAL SKY SURVEY GALAXY CLUSTERS

International Nuclear Information System (INIS)

Skielboe, Andreas; Wojtak, Radosław; Pedersen, Kristian; Rozo, Eduardo; Rykoff, Eli S.

2012-01-01

Measurements of galaxy cluster kinematics are important in understanding the dynamical state and evolution of clusters of galaxies, as well as constraining cosmological models. While it is well established that clusters exhibit non-spherical geometries, evident in the distribution of galaxies on the sky, azimuthal variations of galaxy kinematics within clusters have yet to be observed. Here we measure the azimuthal dependence of the line-of-sight velocity dispersion profile in a stacked sample of 1743 galaxy clusters from the Sloan Digital Sky Survey (SDSS). The clusters are drawn from the SDSS DR8 redMaPPer catalog. We find that the line-of-sight velocity dispersion of galaxies lying along the major axis of the central galaxy is larger than those that lie along the minor axis. This is the first observational detection of anisotropic kinematics of galaxies in clusters. We show that the result is consistent with predictions from numerical simulations. Furthermore, we find that the degree of projected anisotropy is strongly dependent on the line-of-sight orientation of the galaxy cluster, opening new possibilities for assessing systematics in optical cluster finding.

The Fornax Cluster VLT Spectroscopic Survey II - Planetary Nebulae kinematics within 200 kpc of the cluster core

Science.gov (United States)

Spiniello, C.; Napolitano, N. R.; Arnaboldi, M.; Tortora, C.; Coccato, L.; Capaccioli, M.; Gerhard, O.; Iodice, E.; Spavone, M.; Cantiello, M.; Peletier, R.; Paolillo, M.; Schipani, P.

2018-06-01

We present the largest and most spatially extended planetary nebulae (PNe) catalogue ever obtained for the Fornax cluster. We measured velocities of 1452 PNe out to 200 kpc in the cluster core using a counter-dispersed slitless spectroscopic technique with data from FORS2 on the Very Large Telescope (VLT). With such an extended spatial coverage, we can study separately the stellar haloes of some of the cluster main galaxies and the intracluster light. In this second paper of the Fornax Cluster VLT Spectroscopic Survey, we identify and classify the emission-line sources, describe the method to select PNe, and calculate their coordinates and velocities from the dispersed slitless images. From the PN 2D velocity map, we identify stellar streams that are possibly tracing the gravitational interaction of NGC 1399 with NGC 1404 and NGC 1387. We also present the velocity dispersion profile out to ˜200 kpc radii, which shows signatures of a superposition of the bright central galaxy and the cluster potential, with the latter clearly dominating the regions outside R ˜ 1000 arcsec (˜100 kpc).

Tucker tensor analysis of Matern functions in spatial statistics

KAUST Repository

Litvinenko, Alexander

2018-04-20

Low-rank Tucker tensor methods in spatial statistics 1. Motivation: improve statistical models 2. Motivation: disadvantages of matrices 3. Tools: Tucker tensor format 4. Tensor approximation of Matern covariance function via FFT 5. Typical statistical operations in Tucker tensor format 6. Numerical experiments

A Novel Joint Spatial-Code Clustered Interference Alignment Scheme for Large-Scale Wireless Sensor Networks

Directory of Open Access Journals (Sweden)

Zhilu Wu

2015-01-01

Full Text Available Interference alignment (IA has been put forward as a promising technique which can mitigate interference and effectively increase the throughput of wireless sensor networks (WSNs. However, the number of users is strictly restricted by the IA feasibility condition, and the interference leakage will become so strong that the quality of service will degrade significantly when there are more users than that IA can support. In this paper, a novel joint spatial-code clustered (JSCC-IA scheme is proposed to solve this problem. In the proposed scheme, the users are clustered into several groups so that feasible IA can be achieved within each group. In addition, each group is assigned a pseudo noise (PN code in order to suppress the inter-group interference via the code dimension. The analytical bit error rate (BER expressions of the proposed JSCC-IA scheme are formulated for the systems with identical and different propagation delays, respectively. To further improve the performance of the JSCC-IA scheme in asymmetric networks, a random grouping selection (RGS algorithm is developed to search for better grouping combinations. Numerical results demonstrate that the proposed JSCC-IA scheme is capable of accommodating many more users to communicate simultaneously in the same frequency band with better performance.

Functional equivalence of spatial images from touch and vision: evidence from spatial updating in blind and sighted individuals.

Science.gov (United States)

Giudice, Nicholas A; Betty, Maryann R; Loomis, Jack M

2011-05-01

This research examined whether visual and haptic map learning yield functionally equivalent spatial images in working memory, as evidenced by similar encoding bias and updating performance. In 3 experiments, participants learned 4-point routes either by seeing or feeling the maps. At test, blindfolded participants made spatial judgments about the maps from imagined perspectives that were either aligned or misaligned with the maps as represented in working memory. Results from Experiments 1 and 2 revealed a highly similar pattern of latencies and errors between visual and haptic conditions. These findings extend the well-known alignment biases for visual map learning to haptic map learning, provide further evidence of haptic updating, and most important, show that learning from the 2 modalities yields very similar performance across all conditions. Experiment 3 found the same encoding biases and updating performance with blind individuals, demonstrating that functional equivalence cannot be due to visual recoding and is consistent with an amodal hypothesis of spatial images.

Equilibrium Structures and Absorption Spectra for SixOy Molecular Clusters using Density Functional Theory

Science.gov (United States)

2017-05-05

Naval Research Laboratory Washington, DC 20375-5320 NRL/MR/6390--17-9724 Equilibrium Structures and Absorption Spectra for SixOy Molecular Clusters...TELEPHONE NUMBER (include area code) b. ABSTRACT c. THIS PAGE 18. NUMBER OF PAGES 17. LIMITATION OF ABSTRACT Equilibrium Structures and Absorption...and electronic excited-state absorption spectra for eqilibrium structures of SixOy molecular clusters using density function theory (DFT) and time

Identification of Flood Reactivity Regions via the Functional Clustering of Hydrographs

Science.gov (United States)

Brunner, Manuela I.; Viviroli, Daniel; Furrer, Reinhard; Seibert, Jan; Favre, Anne-Catherine

2018-03-01

Flood hydrograph shapes contain valuable information on the flood-generation mechanisms of a catchment. To make good use of this information, we express flood hydrograph shapes as continuous functions using a functional data approach. We propose a clustering approach based on functional data for flood hydrograph shapes to identify a set of representative hydrograph shapes on a catchment scale and use these catchment-specific sets of representative hydrographs to establish regions of catchments with similar flood reactivity on a regional scale. We applied this approach to flood samples of 163 medium-size Swiss catchments. The results indicate that three representative hydrograph shapes sufficiently describe the hydrograph shape variability within a catchment and therefore can be used as a proxy for the flood behavior of a catchment. These catchment-specific sets of three hydrographs were used to group the catchments into three reactivity regions of similar flood behavior. These regions were not only characterized by similar hydrograph shapes and reactivity but also by event magnitudes and triggering event conditions. We envision these regions to be useful in regionalization studies, regional flood frequency analyses, and to allow for the construction of synthetic design hydrographs in ungauged catchments. The clustering approach based on functional data which establish these regions is very flexible and has the potential to be extended to other geographical regions or toward the use in climate impact studies.

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

Energy Technology Data Exchange (ETDEWEB)

Puzanov, A. S.; Obolenskiy, S. V., E-mail: obolensk@rf.unn.ru; Kozlov, V. A. [Lobachevsky State University of Nizhny Novgorod (NNSU) (Russian Federation)

2016-12-15

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

Guided basin-hopping search of small boron clusters with density functional theory

Energy Technology Data Exchange (ETDEWEB)

Ng, Wei Chun; Yoon, Tiem Leong [School of Physics, Universiti Sains Malaysia, 11800 USM, Penang (Malaysia); Lim, Thong Leng [Faculty of Engineering and Technology, Multimedia University, Melacca Campus, 75450 Melaka (Malaysia)

2015-04-24

The search for the ground state structures of Boron clusters has been a difficult computational task due to the unique metalloid nature of Boron atom. Previous research works had overcome the problem in the search of the Boron ground-state structures by adding symmetry constraints prior to the process of locating the local minima in the potential energy surface (PES) of the Boron clusters. In this work, we shown that, with the deployment of a novel computational approach that incorporates density functional theory (DFT) into a guided global optimization search algorithm based on basin-hopping, it is possible to directly locate the local minima of small Boron clusters in the PES at the DFT level. The ground-state structures search algorithm as proposed in this work is initiated randomly and needs not a priori symmetry constraint artificially imposed throughout the search process. Small sized Boron clusters so obtained compare well to the results obtained by similar calculations in the literature. The electronic properties of each structures obtained are calculated within the DFT framework.

Guided basin-hopping search of small boron clusters with density functional theory

International Nuclear Information System (INIS)

Ng, Wei Chun; Yoon, Tiem Leong; Lim, Thong Leng

2015-01-01

The search for the ground state structures of Boron clusters has been a difficult computational task due to the unique metalloid nature of Boron atom. Previous research works had overcome the problem in the search of the Boron ground-state structures by adding symmetry constraints prior to the process of locating the local minima in the potential energy surface (PES) of the Boron clusters. In this work, we shown that, with the deployment of a novel computational approach that incorporates density functional theory (DFT) into a guided global optimization search algorithm based on basin-hopping, it is possible to directly locate the local minima of small Boron clusters in the PES at the DFT level. The ground-state structures search algorithm as proposed in this work is initiated randomly and needs not a priori symmetry constraint artificially imposed throughout the search process. Small sized Boron clusters so obtained compare well to the results obtained by similar calculations in the literature. The electronic properties of each structures obtained are calculated within the DFT framework

A Missing Link in Galaxy Evolution: The Mysteries of Dissolving Star Clusters

Science.gov (United States)

Pellerin, Anne; Meyer, Martin; Harris, Jason; Calzetti, Daniela

2007-05-01

Star-forming events in starbursts and normal galaxies have a direct impact on the global stellar content of galaxies. These events create numerous compact clusters where stars are produced in great number. These stars eventually end up in the star field background where they are smoothly distributed. However, due to instrumental limitations such as spatial resolution and sensitivity, the processes involved during the transition phase from the compact clusters to the star field background as well as the impact of the environment (spiral waves, bars, starburst) on the lifetime of clusters are still poorly constrained observationally. I will present our latest results on the physical properties of dissolving clusters directly detected in HST/ACS archival images of the three nearby galaxies IC 2574, NGC 1313, and IC 10 (D detect and spatially resolve individual stars in nearby galaxies within a large field-of-view. For all ACS images obtained in three filters (F435W, F555W or F606W, and F814W), we performed PSF stellar photometry in crowded field. Color-magnitude diagrams (CMD) allow us to identify the most massive stars more likely to be part of dissolving clusters (A-type and earlier), and to isolate them from the star field background. We then adapt and use a clustering algorithm on the selected stars to find groups of stars to reveal and quantify the properties of all star clusters (compactness, size, age, mass). With this algorithm, even the less compact clusters are revealed while they are being destroyed. Our sample of three galaxies covers an interesting range in gravitational potential well and explores a variety of galaxy morphological types, which allows us to discuss the dissolving cluster properties as a function of the host galaxy characteristics. The properties of the star field background will also be discussed.

Spatial prediction of near surface soil water retention functions using hydrogeophysics and empirical orthogonal functions

Science.gov (United States)

Gibson, Justin; Franz, Trenton E.

2018-06-01

The hydrological community often turns to widely available spatial datasets such as the NRCS Soil Survey Geographic database (SSURGO) to characterize the spatial variability of soil properties. When used to spatially characterize and parameterize watershed models, this has served as a reasonable first approximation when lacking localized or incomplete soil data. Within agriculture, soil data has been left relatively coarse when compared to numerous other data sources measured. This is because localized soil sampling is both expensive and time intense, thus a need exists in better connecting spatial datasets with ground observations. Given that hydrogeophysics is data-dense, rapid, non-invasive, and relatively easy to adopt, it is a promising technique to help dovetail localized soil sampling with spatially exhaustive datasets. In this work, we utilize two common near surface geophysical methods, cosmic-ray neutron probe and electromagnetic induction, to identify temporally stable spatial patterns of measured geophysical properties in three 65 ha agricultural fields in western Nebraska. This is achieved by repeat geophysical observations of the same study area across a range of wet to dry field conditions in order to evaluate with an empirical orthogonal function. Shallow cores were then extracted within each identified zone and water retention functions were generated in the laboratory. Using EOF patterns as a covariate, we quantify the predictive skill of estimating soil hydraulic properties in areas without measurement using a bootstrap validation analysis. Results indicate that sampling locations informed via repeat hydrogeophysical surveys, required only five cores to reduce the cross-validation root mean squared error by an average of 64% as compared to soil parameters predicted by a commonly used benchmark, SSURGO and ROSETTA. The reduction to five strategically located samples within the 65 ha fields reduces sampling efforts by up to ∼90% as compared to

Cluster analysis of track structure

International Nuclear Information System (INIS)

Michalik, V.

1991-01-01

One of the possibilities of classifying track structures is application of conventional partition techniques of analysis of multidimensional data to the track structure. Using these cluster algorithms this paper attempts to find characteristics of radiation reflecting the spatial distribution of ionizations in the primary particle track. An absolute frequency distribution of clusters of ionizations giving the mean number of clusters produced by radiation per unit of deposited energy can serve as this characteristic. General computation techniques used as well as methods of calculations of distributions of clusters for different radiations are discussed. 8 refs.; 5 figs

Investigating Spatial Patterns of Persistent Scatterer Interferometry Point Targets and Landslide Occurrences in the Arno River Basin

Directory of Open Access Journals (Sweden)

Ping Lu

2014-07-01

Full Text Available Persistent Scatterer Interferometry (PSI has been widely used for landslide studies in recent years. This paper investigated the spatial patterns of PSI point targets and landslide occurrences in the Arno River basin in Central Italy. The main purpose is to analyze whether spatial patterns of Persistent Scatterers (PS can be recognized as indicators of landslide occurrences throughout the whole basin. The bivariate K-function was employed to assess spatial relationships between PS and landslides. The PSI point targets were acquired from almost 4 years (from March 2003 to January 2007 of RADARSAT-1 images. The landslide inventory was collected from 15 years (from 1992–2007 of surveying and mapping data, mainly including remote sensing data, topographic maps and field investigations. The proposed approach is able to assess spatial patterns between a variety of PS and landslides, in particular, to understand if PSI point targets are spatially clustered (spatial attraction or randomly distributed (spatial independency on various types of landslides across the basin. Additionally, the degree and scale distances of PS clustering on a variety of landslides can be characterized. The results rejected the null hypothesis that PSI point targets appear to cluster similarly on four types of landslides (slides, flows, falls and creeps in the Arno River basin. Significant influence of PS velocities and acquisition orbits can be noticed on detecting landslides with different states of activities. Despite that the assessment may be influenced by the quality of landslide inventory and Synthetic Aperture Radar (SAR images, the proposed approach is expected to provide guidelines for studies trying to detect and investigate landslide occurrences at a regional scale through spatial statistical analysis of PS, for which an advanced understanding of the impact of scale distances on landslide clustering is fundamentally needed.

Spatial clustering analysis in neuroanatomy: Applications of different approaches to motor nerve fiber distribution

NARCIS (Netherlands)

Crunelli, V.; Prodanov, D.P.; Nagelkerke, Nico; Marani, Enrico

2007-01-01

Spatial organization of the nerve fibers in the peripheral nerves may be important for the studies of axonal regeneration, the degenerative nerve diseases and the construction of interfaces with peripheral nerves, such as nerve prostheses. Functional topography of motor axons related to the

A density functional study of structures and stability of SinCN clusters

International Nuclear Information System (INIS)

Gai Zhigang; Yang Li; Zhao Jie; Chu Shibo

2011-01-01

In this paper, density functional theory (DFT) B3LYP method with 6-311G * basis set has been used to investigate geometric configurations, vibrational frequencies and ground state energies of Si n CN (n = 2 ∼ 6) clusters. The energies and spin multiplicities of ground states and substable states have been discussed, respectively. Harmonic frequencies and infrared spectra intensity for these clusters are given in order to aid in the characterization of the stable structures. The results show that the zero point energy (ZPE), thermocapacity and entropies are nearly in proportion to increased n, whose average enhancement are 0.80 kcal/mol, 5.20 cal/mol · K and 12.72 cal/ mol · K, respectively. The stability of Si n CN (n = 2 ∼ 6) clusters with even n are greater than that with odd n. (authors)

Spread of porcine circovirus associated disease (PCVAD in Ontario (Canada swine herds: Part I. Exploratory spatial analysis

Directory of Open Access Journals (Sweden)

Young Beth

2010-12-01

Full Text Available Abstract Background The systemic form of porcine circovirus associated disease (PCVAD, also known as postweaning multisystemic wasting syndrome (PMWS was initially detected in the early 1990s. Starting in 2004, the Canadian swine industry experienced considerable losses due to PCVAD, concurrent with a shift in genotype of porcine circovirus type 2 (PCV2. Objectives of the current study were to explore spatial characteristics of self-reported PCVAD distribution in Ontario between 2004 and 2008, and to investigate the existence and nature of local spread. Results The study included 278 swine herds from a large disease-monitoring project that included porcine reproductive and respiratory syndrome (PRRS virus-positive herds identified by the diagnostic laboratory, and PRRS virus-negative herds directly from the target population. Herds were included if they had growing pigs present on-site and available geographical coordinates for the sampling site. Furthermore, herds were defined as PCVAD-positive if a producer reported an outbreak of circovirus associated disease, or as PCVAD-negative if no outbreak was noted. Spatial trend was investigated using generalized additive models and time to PCVAD outbreak in a herd using Cox's proportional hazard model; spatial and spatio-temporal clustering was explored using K-functions; and location of most likely spatial and spatio-temporal clusters was investigated using scan statistics. Over the study period, the risk of reporting a PCVAD-positive herd tended to be higher in the eastern part of the province after adjustment for herd PRRS status (P = 0.05. This was partly confirmed for spread (Partial P P = 0.06 existence of spatio-temporal clustering of PCVAD and detection of a spatio-temporal cluster (P = 0.04. Conclusions In Ontario, PCVAD has shown a general trend, spreading from east-to-west. We interpret the existence of spatio-temporal clustering as evidence of spatio-temporal aggregation of PCVAD

Problems of spatial-functional organization of Južno Pomoravlje region’s network of settlements

Directory of Open Access Journals (Sweden)

Krunić Nikola

2009-01-01

Full Text Available During the elaboration of the Regional spatial plan of the municipalities of Južno Pomoravlje (Region Južno Pomoravlje a special attention was paid to its network of settlements. Demographical and functional determinants of this network were analyzed based on the relevant theoretical-methodological concepts and qualitative-quantitative indicators. Settlement network of Južno Pomoravlje was considered as a subsystem of the Republic of Serbia’s settlements’ system. Correlation and causality between processes of spatial and socio-economic migration of population and functional transformation of settlements have been highlighted, which caused differentiation of the Region’s municipalities to: urban cores - peri-urban rings - suburban more or less urbanized villages and rural surroundings. Models of decentralized concentration and micro-developing nuclei are proposed as instruments for decentralization of the Region or its municipalities. Based on the level of spatial-functional integration of settlements, regional as well as municipal and micro-functional - micro-regional structures have been identified. This paper gives conceptual and strategic proposals of spatial-functional organization of Južno Pomoravlje, which are based on settlements’ determinants. Authors suggest that functional premises define determinants for the Regional spatial plan and steer the sectoral and strategic decisions.

PRIMUS: Galaxy clustering as a function of luminosity and color at 0.2 < z < 1

Energy Technology Data Exchange (ETDEWEB)

Skibba, Ramin A.; Smith, M. Stephen M.; Coil, Alison L.; Mendez, Alexander J. [Department of Physics, Center for Astrophysics and Space Sciences, University of California, 9500 Gilman Drive, La Jolla, San Diego, CA 92093 (United States); Moustakas, John [Department of Physics and Astronomy, Siena College, 515 Loudon Road, Loudonville, NY 12211 (United States); Aird, James [Department of Physics, Durham University, Durham DH1 3LE (United Kingdom); Blanton, Michael R. [Center for Cosmology and Particle Physics, Department of Physics, New York University, 4 Washington Place, New York, NY 10003 (United States); Bray, Aaron D.; Eisenstein, Daniel J. [Harvard-Smithsonian Center for Astrophysics, 60 Garden Street, Cambridge, MA 02138 (United States); Cool, Richard J. [MMT Observatory, 1540 E Second Street, University of Arizona, Tucson, AZ 85721 (United States); Wong, Kenneth C. [Steward Observatory, The University of Arizona, 933 North Cherry Avenue, Tucson, AZ 85721 (United States); Zhu, Guangtun, E-mail: rskibba@ucsd.edu [Department of Physics and Astronomy, Johns Hopkins University, 3400 North Charles Street, Baltimore, MD 21218 (United States)

2014-04-01

We present measurements of the luminosity and color-dependence of galaxy clustering at 0.2 < z < 1.0 in the Prism Multi-object Survey. We quantify the clustering with the redshift-space and projected two-point correlation functions, ξ(r{sub p} , π) and w{sub p} (r{sub p} ), using volume-limited samples constructed from a parent sample of over ∼130, 000 galaxies with robust redshifts in seven independent fields covering 9 deg{sup 2} of sky. We quantify how the scale-dependent clustering amplitude increases with increasing luminosity and redder color, with relatively small errors over large volumes. We find that red galaxies have stronger small-scale (0.1 Mpc h {sup –1} < r{sub p} < 1 Mpc h {sup –1}) clustering and steeper correlation functions compared to blue galaxies, as well as a strong color dependent clustering within the red sequence alone. We interpret our measured clustering trends in terms of galaxy bias and obtain values of b {sub gal} ≈ 0.9-2.5, quantifying how galaxies are biased tracers of dark matter depending on their luminosity and color. We also interpret the color dependence with mock catalogs, and find that the clustering of blue galaxies is nearly constant with color, while redder galaxies have stronger clustering in the one-halo term due to a higher satellite galaxy fraction. In addition, we measure the evolution of the clustering strength and bias, and we do not detect statistically significant departures from passive evolution. We argue that the luminosity- and color-environment (or halo mass) relations of galaxies have not significantly evolved since z ∼ 1. Finally, using jackknife subsampling methods, we find that sampling fluctuations are important and that the COSMOS field is generally an outlier, due to having more overdense structures than other fields; we find that 'cosmic variance' can be a significant source of uncertainty for high-redshift clustering measurements.

A Variational Level Set Model Combined with FCMS for Image Clustering Segmentation

Directory of Open Access Journals (Sweden)

Liming Tang

2014-01-01

Full Text Available The fuzzy C means clustering algorithm with spatial constraint (FCMS is effective for image segmentation. However, it lacks essential smoothing constraints to the cluster boundaries and enough robustness to the noise. Samson et al. proposed a variational level set model for image clustering segmentation, which can get the smooth cluster boundaries and closed cluster regions due to the use of level set scheme. However it is very sensitive to the noise since it is actually a hard C means clustering model. In this paper, based on Samson’s work, we propose a new variational level set model combined with FCMS for image clustering segmentation. Compared with FCMS clustering, the proposed model can get smooth cluster boundaries and closed cluster regions due to the use of level set scheme. In addition, a block-based energy is incorporated into the energy functional, which enables the proposed model to be more robust to the noise than FCMS clustering and Samson’s model. Some experiments on the synthetic and real images are performed to assess the performance of the proposed model. Compared with some classical image segmentation models, the proposed model has a better performance for the images contaminated by different noise levels.