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Sample records for advanced spatial analysis

  1. Advances in diagnosis and spatial analysis of cysticercosis and taeniasis.

    PubMed

    Raoul, Francis; Li, Tiaoying; Sako, Yasuhito; Chen, Xingwang; Long, Changping; Yanagida, Tetsuya; Wu, Yunfei; Nakao, Minoru; Okamoto, Munehiro; Craig, Philip S; Giraudoux, Patrick; Ito, Akira

    2013-11-01

    Human cysticercosis, caused by accidental ingestion of eggs of Taenia solium, is one of the most pathogenic helminthiases and is listed among the 17 WHO Neglected Tropical Diseases. Controlling the life-cycle of T. solium between humans and pigs is essential for eradication of cysticercosis. One difficulty for the accurate detection and identification of T. solium species is the possible co-existence of two other human Taenia tapeworms (T. saginata and T. asiatica, which do not cause cysticercosis in humans). Several key issues for taeniasis/cysticercosis (T/C) evidence-based epidemiology and control are reviewed: (1) advances in immunological and molecular tools for screening of human and animals hosts and identification of Taenia species, with a focus on real-time detection of taeniasis carriers and infected animals in field community screenings, and (2) spatial ecological approaches that have been used to detect geospatial patterns of case distributions and to monitor pig activity and behaviour. Most recent eco-epidemiological studies undertaken in Sichuan province, China, are introduced and reviewed. PMID:23985371

  2. Spatial and Temporal Dust Source Variability in Northern China Identified Using Advanced Remote Sensing Analysis

    NASA Technical Reports Server (NTRS)

    Taramelli, A.; Pasqui, M.; Barbour, J.; Kirschbaum, D.; Bottai, L.; Busillo, C.; Calastrini, F.; Guarnieri, F.; Small, C.

    2013-01-01

    The aim of this research is to provide a detailed characterization of spatial patterns and temporal trends in the regional and local dust source areas within the desert of the Alashan Prefecture (Inner Mongolia, China). This problem was approached through multi-scale remote sensing analysis of vegetation changes. The primary requirements for this regional analysis are high spatial and spectral resolution data, accurate spectral calibration and good temporal resolution with a suitable temporal baseline. Landsat analysis and field validation along with the low spatial resolution classifications from MODIS and AVHRR are combined to provide a reliable characterization of the different potential dust-producing sources. The representation of intra-annual and inter-annual Normalized Difference Vegetation Index (NDVI) trend to assess land cover discrimination for mapping potential dust source using MODIS and AVHRR at larger scale is enhanced by Landsat Spectral Mixing Analysis (SMA). The combined methodology is to determine the extent to which Landsat can distinguish important soils types in order to better understand how soil reflectance behaves at seasonal and inter-annual timescales. As a final result mapping soil surface properties using SMA is representative of responses of different land and soil cover previously identified by NDVI trend. The results could be used in dust emission models even if they are not reflecting aggregate formation, soil stability or particle coatings showing to be critical for accurately represent dust source over different regional and local emitting areas.

  3. Geologic spatial analysis

    SciTech Connect

    Thiessen, R.L.; Eliason, J.R.

    1989-01-01

    This report describes the development of geologic spatial analysis research which focuses on conducting comprehensive three-dimensional analysis of regions using geologic data sets that can be referenced by latitude, longitude, and elevation/depth. (CBS)

  4. Spatial Data Analysis.

    PubMed

    Banerjee, Sudipto

    2016-03-18

    With increasing accessibility to geographic information systems (GIS) software, statisticians and data analysts routinely encounter scientific data sets with geocoded locations. This has generated considerable interest in statistical modeling for location-referenced spatial data. In public health, spatial data routinely arise as aggregates over regions, such as counts or rates over counties, census tracts, or some other administrative delineation. Such data are often referred to as areal data. This review article provides a brief overview of statistical models that account for spatial dependence in areal data. It does so in the context of two applications: disease mapping and spatial survival analysis. Disease maps are used to highlight geographic areas with high and low prevalence, incidence, or mortality rates of a specific disease and the variability of such rates over a spatial domain. They can also be used to detect hot spots or spatial clusters that may arise owing to common environmental, demographic, or cultural effects shared by neighboring regions. Spatial survival analysis refers to the modeling and analysis for geographically referenced time-to-event data, where a subject is followed up to an event (e.g., death or onset of a disease) or is censored, whichever comes first. Spatial survival analysis is used to analyze clustered survival data when the clustering arises from geographical regions or strata. Illustrations are provided in these application domains. PMID:26789381

  5. Spatial analysis of hyperspectral vegetation index

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Advanced remote sensing technologies provide researchers an innovative way of collecting spatial data for use in precision agriculture. Sensor information and spatial analysis together allow for a completely understanding of the spatial complexity of a field and its crop. The objective of the study ...

  6. Analysis of bending wave transmission using beam tracing with advanced statistical energy analysis for periodic box-like structures affected by spatial filtering

    NASA Astrophysics Data System (ADS)

    Wilson, D.; Hopkins, C.

    2015-04-01

    For bending wave transmission across periodic box-like arrangements of plates, the effects of spatial filtering can be significant and this needs to be considered in the choice of prediction model. This paper investigates the errors that can occur with Statistical Energy Analysis (SEA) and the potential of using Advanced SEA (ASEA) to improve predictions. The focus is on the low- and mid-frequency range where plates only support local modes with low mode counts and the in situ modal overlap is relatively high. To increase the computational efficiency when using ASEA on large systems, a beam tracing method is introduced which groups together all rays with the same heading into a single beam. Based on a diffuse field on the source plate, numerical experiments are used to determine the angular distribution of incident power on receiver plate edges on linear and cuboid box-like structures. These show that on receiver plates which do not share a boundary with the source plate, the angular distribution on the receiver plate boundaries differs significantly from a diffuse field. SEA and ASEA predictions are assessed through comparison with finite element models. With rain-on-the-roof excitation on the source plate, the results show that compared to SEA, ASEA provides significantly better estimates of the receiver plate energy, but only where there are at least one or two bending modes in each one-third octave band. Whilst ASEA provides better accuracy than SEA, discrepancies still exist which become more apparent when the direct propagation path crosses more than three nominally identical structural junctions.

  7. Geographic representation in spatial analysis

    NASA Astrophysics Data System (ADS)

    Miller, Harvey J.

    Spatial analysis mostly developed in an era when data was scarce and computational power was expensive. Consequently, traditional spatial analysis greatly simplifies its representations of geography. The rise of geographic information science (GISci) and the changing nature of scientific questions at the end of the 20th century suggest a comprehensive re-examination of geographic representation in spatial analysis. This paper reviews the potential for improved representations of geography in spatial analysis. Existing tools in spatial analysis and new tools available from GISci have tremendous potential for bringing more sophisticated representations of geography to the forefront of spatial analysis theory and application.

  8. Spatial and Spatiotemporal Data Mining: Recent Advances

    SciTech Connect

    Shekhar, Shashi; Vatsavai, Raju; Celik, Mete

    2008-01-01

    Explosive growth in geospatial data and the emergence of new spatial technologies emphasize the need for automated discovery of spatial knowledge. Spatial data mining is the process of discovering interesting and previously unknown, but potentially useful patterns from large spatial databases. The complexity of spatial data and intrinsic spatial relationships limits the usefulness of conventional data mining techniques for extracting spatial patterns. In this chapter we explore the emerging field of spatial data mining, focusing on four major topics: prediction and classification, outlier detection, co-location mining, and clustering. Spatiotemporal data mining is also briefly discussed.

  9. Spatial analysis of NDVI readings with difference sampling density

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Advanced remote sensing technologies provide research an innovative way of collecting spatial data for use in precision agriculture. Sensor information and spatial analysis together allow for a complete understanding of the spatial complexity of a field and its crop. The objective of the study was...

  10. Part 2 The Link between GIS and spatial analysis . GIS, spatial econometrics and social science research

    NASA Astrophysics Data System (ADS)

    Anselin, Luc

    Some ideas are formulated on the challenges presented to GIS, spatial analysis and spatial econometrics that result from recent trends in social science research. These new developments are characterized by a focus on the geography of phenomena. Particular emphasis is placed on the need to extend concepts of space, to broaden the analytical toolbox and to develop software and advance education.

  11. A New Methodology of Spatial Cross-Correlation Analysis

    PubMed Central

    Chen, Yanguang

    2015-01-01

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

  12. Spatial analysis of news sources.

    PubMed

    Mehler, Andrew; Bao, Yunfan; Li, Xin; Wang, Yue; Skiena, Steven

    2006-01-01

    People in different places talk about different things. This interest distribution is reflected by the newspaper articles circulated in a particular area. We use data from our large-scale newspaper analysis system (Lydia) to make entity datamaps, a spatial visualization of the interest in a given named entity. Our goal is to identify entities which display regional biases. We develop a model of estimating the frequency of reference of an entity in any given city from the reference frequency centered in surrounding cities, and techniques for evaluating the spatial significance of this distribution. PMID:17080798

  13. Advanced PFBC transient analysis

    SciTech Connect

    White, J.S.; Bonk, D.L.

    1997-05-01

    Transient modeling and analysis of advanced Pressurized Fluidized Bed Combustion (PFBC) systems is a research area that is currently under investigation by the US Department of Energy`s Federal Energy Technology Center (FETC). The object of the effort is to identify key operating parameters that affect plant performance and then quantify the basic response of major sub-systems to changes in operating conditions. PC-TRAX{trademark}, a commercially available dynamic software program, was chosen and applied in this modeling and analysis effort. This paper describes the development of a series of TRAX-based transient models of advanced PFBC power plants. These power plants burn coal or other suitable fuel in a PFBC, and the high temperature flue gas supports low-Btu fuel gas or natural gas combustion in a gas turbine topping combustor. When it is utilized, the low-Btu fuel gas is produced in a bubbling bed carbonizer. High temperature, high pressure combustion products exiting the topping combustor are expanded in a modified gas turbine to generate electrical power. Waste heat from the system is used to raise and superheat steam for a reheat steam turbine bottoming cycle that generates additional electrical power. Basic control/instrumentation models were developed and modeled in PC-TRAX and used to investigate off-design plant performance. System performance for various transient conditions and control philosophies was studied.

  14. Advances in Spectral-Spatial Classification of Hyperspectral Images

    NASA Technical Reports Server (NTRS)

    Fauvel, Mathieu; Tarabalka, Yuliya; Benediktsson, Jon Atli; Chanussot, Jocelyn; Tilton, James C.

    2012-01-01

    Recent advances in spectral-spatial classification of hyperspectral images are presented in this paper. Several techniques are investigated for combining both spatial and spectral information. Spatial information is extracted at the object (set of pixels) level rather than at the conventional pixel level. Mathematical morphology is first used to derive the morphological profile of the image, which includes characteristics about the size, orientation and contrast of the spatial structures present in the image. Then the morphological neighborhood is defined and used to derive additional features for classification. Classification is performed with support vector machines using the available spectral information and the extracted spatial information. Spatial post-processing is next investigated to build more homogeneous and spatially consistent thematic maps. To that end, three presegmentation techniques are applied to define regions that are used to regularize the preliminary pixel-wise thematic map. Finally, a multiple classifier system is defined to produce relevant markers that are exploited to segment the hyperspectral image with the minimum spanning forest algorithm. Experimental results conducted on three real hyperspectral images with different spatial and spectral resolutions and corresponding to various contexts are presented. They highlight the importance of spectral-spatial strategies for the accurate classification of hyperspectral images and validate the proposed methods.

  15. Optical spatial solitons: historical overview and recent advances

    NASA Astrophysics Data System (ADS)

    Chen, Zhigang; Segev, Mordechai; Christodoulides, Demetrios N.

    2012-08-01

    Solitons, nonlinear self-trapped wavepackets, have been extensively studied in many and diverse branches of physics such as optics, plasmas, condensed matter physics, fluid mechanics, particle physics and even astrophysics. Interestingly, over the past two decades, the field of solitons and related nonlinear phenomena has been substantially advanced and enriched by research and discoveries in nonlinear optics. While optical solitons have been vigorously investigated in both spatial and temporal domains, it is now fair to say that much soliton research has been mainly driven by the work on optical spatial solitons. This is partly due to the fact that although temporal solitons as realized in fiber optic systems are fundamentally one-dimensional entities, the high dimensionality associated with their spatial counterparts has opened up altogether new scientific possibilities in soliton research. Another reason is related to the response time of the nonlinearity. Unlike temporal optical solitons, spatial solitons have been realized by employing a variety of noninstantaneous nonlinearities, ranging from the nonlinearities in photorefractive materials and liquid crystals to the nonlinearities mediated by the thermal effect, thermophoresis and the gradient force in colloidal suspensions. Such a diversity of nonlinear effects has given rise to numerous soliton phenomena that could otherwise not be envisioned, because for decades scientists were of the mindset that solitons must strictly be the exact solutions of the cubic nonlinear Schrödinger equation as established for ideal Kerr nonlinear media. As such, the discoveries of optical spatial solitons in different systems and associated new phenomena have stimulated broad interest in soliton research. In particular, the study of incoherent solitons and discrete spatial solitons in optical periodic media not only led to advances in our understanding of fundamental processes in nonlinear optics and photonics, but also had a

  16. Optical spatial solitons: historical overview and recent advances.

    PubMed

    Chen, Zhigang; Segev, Mordechai; Christodoulides, Demetrios N

    2012-08-01

    Solitons, nonlinear self-trapped wavepackets, have been extensively studied in many and diverse branches of physics such as optics, plasmas, condensed matter physics, fluid mechanics, particle physics and even astrophysics. Interestingly, over the past two decades, the field of solitons and related nonlinear phenomena has been substantially advanced and enriched by research and discoveries in nonlinear optics. While optical solitons have been vigorously investigated in both spatial and temporal domains, it is now fair to say that much soliton research has been mainly driven by the work on optical spatial solitons. This is partly due to the fact that although temporal solitons as realized in fiber optic systems are fundamentally one-dimensional entities, the high dimensionality associated with their spatial counterparts has opened up altogether new scientific possibilities in soliton research. Another reason is related to the response time of the nonlinearity. Unlike temporal optical solitons, spatial solitons have been realized by employing a variety of noninstantaneous nonlinearities, ranging from the nonlinearities in photorefractive materials and liquid crystals to the nonlinearities mediated by the thermal effect, thermophoresis and the gradient force in colloidal suspensions. Such a diversity of nonlinear effects has given rise to numerous soliton phenomena that could otherwise not be envisioned, because for decades scientists were of the mindset that solitons must strictly be the exact solutions of the cubic nonlinear Schrödinger equation as established for ideal Kerr nonlinear media. As such, the discoveries of optical spatial solitons in different systems and associated new phenomena have stimulated broad interest in soliton research. In particular, the study of incoherent solitons and discrete spatial solitons in optical periodic media not only led to advances in our understanding of fundamental processes in nonlinear optics and photonics, but also had a

  17. Advanced Economic Analysis

    NASA Technical Reports Server (NTRS)

    Greenberg, Marc W.; Laing, William

    2013-01-01

    An Economic Analysis (EA) is a systematic approach to the problem of choosing the best method of allocating scarce resources to achieve a given objective. An EA helps guide decisions on the "worth" of pursuing an action that departs from status quo ... an EA is the crux of decision-support.

  18. Resource materials for a GIS spatial analysis course

    USGS Publications Warehouse

    Raines, Gary L.

    2001-01-01

    This report consists of materials prepared for a GIS spatial analysis course offered as part of the Geography curriculum at the University of Nevada, Reno and the University of California at Santa Barbara in the spring of 2000. The report is intended to share information with instructors preparing spatial-modeling training and scientists with advanced GIS expertise. The students taking this class had completed each universities GIS curriculum and had a foundation in statistics as part of a science major. This report is organized into chapters that contain the following: Slides used during lectures, Guidance on the use of Arcview, Introduction to filtering in Arcview, Conventional and spatial correlation in Arcview, Tools for fuzzification in Arcview, Data and instructions for creating using ArcSDM for simple weights-of-evidence, fuzzy logic, and neural network models for Carlin-type gold deposits in central Nevada, Reading list on spatial modeling, and Selected student spatial-modeling posters from the laboratory exercises.

  19. Spatial uncertainty analysis of population models

    SciTech Connect

    Jager, Yetta; King, Anthony Wayne; Schumaker, Nathan; Ashwood, Tom L; Jackson, Barbara L

    2004-01-01

    This paper describes an approach for conducting spatial uncertainty analysis of spatial population models, and illustrates the ecological consequences of spatial uncertainty for landscapes with different properties. Spatial population models typically simulate birth, death, and migration on an input map that describes habitat. Typically, only a single reference map is available, but we can imagine that a collection of other, slightly different, maps could be drawn to represent a particular species' habitat. As a first approximation, our approach assumes that spatial uncertainty (i.e., the variation among values assigned to a location by such a collection of maps) is constrained by characteristics of the reference map, regardless of how the map was produced. Our approach produces lower levels of uncertainty than alternative methods used in landscape ecology because we condition our alternative landscapes on local properties of the reference map. Simulated spatial uncertainty was higher near the borders of patches. Consequently, average uncertainty was highest for reference maps with equal proportions of suitable and unsuitable habitat, and no spatial autocorrelation. We used two population viability models to evaluate the ecological consequences of spatial uncertainty for landscapes with different properties. Spatial uncertainty produced larger variation among predictions of a spatially explicit model than those of a spatially implicit model. Spatially explicit model predictions of final female population size varied most among landscapes with enough clustered habitat to allow persistence. In contrast, predictions of population growth rate varied most among landscapes with only enough clustered habitat to support a small population, i.e., near a spatially mediated extinction threshold. We conclude that spatial uncertainty has the greatest effect on persistence when the amount and arrangement of suitable habitat are such that habitat capacity is near the minimum

  20. Spatial Autocorrelation Analysis of Migration and Selection

    PubMed Central

    Sokal, R. R.; Jacquez, G. M.; Wooten, M. C.

    1989-01-01

    We test various assumptions necessary for the interpretation of spatial autocorrelation analysis of gene frequency surfaces, using simulations of Wright's isolation-by-distance model with migration or selection superimposed. Increasing neighborhood size enhances spatial autocorrelation, which is reduced again for the largest neighborhood sizes. Spatial correlograms are independent of the mean gene frequency of the surface. Migration affects surfaces and correlograms when immigrant gene frequency differentials are substantial. Multiple directions of migration are reflected in the correlograms. Selection gradients yield clinal correlograms; other selection patterns are less clearly reflected in their correlograms. Sequential migration from different directions and at different gene frequencies can be disaggregated into component migration vectors by means of principal components analysis. This encourages analysis by such methods of gene frequency surfaces in nature. The empirical results of these findings lend support to the inference structure developed earlier for spatial autocorrelation analysis. PMID:2721935

  1. Advances in total scattering analysis

    SciTech Connect

    Proffen, Thomas E; Kim, Hyunjeong

    2008-01-01

    In recent years the analysis of the total scattering pattern has become an invaluable tool to study disordered crystalline and nanocrystalline materials. Traditional crystallographic structure determination is based on Bragg intensities and yields the long range average atomic structure. By including diffuse scattering into the analysis, the local and medium range atomic structure can be unravelled. Here we give an overview of recent experimental advances, using X-rays as well as neutron scattering as well as current trends in modelling of total scattering data.

  2. Design and implementation of spatial knowledge grid for integrated spatial analysis

    NASA Astrophysics Data System (ADS)

    Liu, Xiangnan; Guan, Li; Wang, Ping

    2006-10-01

    Supported by spatial information grid(SIG), the spatial knowledge grid (SKG) for integrated spatial analysis utilizes the middleware technology in constructing the spatial information grid computation environment and spatial information service system, develops spatial entity oriented spatial data organization technology, carries out the profound computation of the spatial structure and spatial process pattern on the basis of Grid GIS infrastructure, spatial data grid and spatial information grid (specialized definition). At the same time, it realizes the complex spatial pattern expression and the spatial function process simulation by taking the spatial intelligent agent as the core to establish space initiative computation. Moreover through the establishment of virtual geographical environment with man-machine interactivity and blending, complex spatial modeling, network cooperation work and spatial community decision knowledge driven are achieved. The framework of SKG is discussed systematically in this paper. Its implement flow and the key technology with examples of overlay analysis are proposed as well.

  3. Spatial analysis to support geographic targeting of genotypes to environments.

    PubMed

    Hyman, Glenn; Hodson, Dave; Jones, Peter

    2013-01-01

    Crop improvement efforts have benefited greatly from advances in available data, computing technology, and methods for targeting genotypes to environments. These advances support the analysis of genotype by environment interactions (GEI) to understand how well a genotype adapts to environmental conditions. This paper reviews the use of spatial analysis to support crop improvement research aimed at matching genotypes to their most appropriate environmental niches. Better data sets are now available on soils, weather and climate, elevation, vegetation, crop distribution, and local conditions where genotypes are tested in experimental trial sites. The improved data are now combined with spatial analysis methods to compare environmental conditions across sites, create agro-ecological region maps, and assess environment change. Climate, elevation, and vegetation data sets are now widely available, supporting analyses that were much more difficult even 5 or 10 years ago. While detailed soil data for many parts of the world remains difficult to acquire for crop improvement studies, new advances in digital soil mapping are likely to improve our capacity. Site analysis and matching and regional targeting methods have advanced in parallel to data and technology improvements. All these developments have increased our capacity to link genotype to phenotype and point to a vast potential to improve crop adaptation efforts. PMID:23515351

  4. Spatial analysis to support geographic targeting of genotypes to environments

    PubMed Central

    Hyman, Glenn; Hodson, Dave; Jones, Peter

    2013-01-01

    Crop improvement efforts have benefited greatly from advances in available data, computing technology, and methods for targeting genotypes to environments. These advances support the analysis of genotype by environment interactions (GEI) to understand how well a genotype adapts to environmental conditions. This paper reviews the use of spatial analysis to support crop improvement research aimed at matching genotypes to their most appropriate environmental niches. Better data sets are now available on soils, weather and climate, elevation, vegetation, crop distribution, and local conditions where genotypes are tested in experimental trial sites. The improved data are now combined with spatial analysis methods to compare environmental conditions across sites, create agro-ecological region maps, and assess environment change. Climate, elevation, and vegetation data sets are now widely available, supporting analyses that were much more difficult even 5 or 10 years ago. While detailed soil data for many parts of the world remains difficult to acquire for crop improvement studies, new advances in digital soil mapping are likely to improve our capacity. Site analysis and matching and regional targeting methods have advanced in parallel to data and technology improvements. All these developments have increased our capacity to link genotype to phenotype and point to a vast potential to improve crop adaptation efforts. PMID:23515351

  5. Geostatistics and spatial analysis in biological anthropology.

    PubMed

    Relethford, John H

    2008-05-01

    A variety of methods have been used to make evolutionary inferences based on the spatial distribution of biological data, including reconstructing population history and detection of the geographic pattern of natural selection. This article provides an examination of geostatistical analysis, a method used widely in geology but which has not often been applied in biological anthropology. Geostatistical analysis begins with the examination of a variogram, a plot showing the relationship between a biological distance measure and the geographic distance between data points and which provides information on the extent and pattern of spatial correlation. The results of variogram analysis are used for interpolating values of unknown data points in order to construct a contour map, a process known as kriging. The methods of geostatistical analysis and discussion of potential problems are applied to a large data set of anthropometric measures for 197 populations in Ireland. The geostatistical analysis reveals two major sources of spatial variation. One pattern, seen for overall body and craniofacial size, shows an east-west cline most likely reflecting the combined effects of past population dispersal and settlement. The second pattern is seen for craniofacial height and shows an isolation by distance pattern reflecting rapid spatial changes in the midlands region of Ireland, perhaps attributable to the genetic impact of the Vikings. The correspondence of these results with other analyses of these data and the additional insights generated from variogram analysis and kriging illustrate the potential utility of geostatistical analysis in biological anthropology. PMID:18257009

  6. Computer Programming in a Spatial Analysis Course.

    ERIC Educational Resources Information Center

    Gesler, Wilbert; Kaplan, Abram

    1993-01-01

    Contends that students in spatial analysis courses generally are familiar with computer use and programs but lack basic computer programing skills. Describes four exercises in which students learn programing using BASIC and dBASE. Asserts that programming exercises help students clarify concepts, understand the rationale behind calculations, use…

  7. Sex differences in spatial cognition: advancing the conversation.

    PubMed

    Levine, Susan C; Foley, Alana; Lourenco, Stella; Ehrlich, Stacy; Ratliff, Kristin

    2016-01-01

    The existence of a sex difference in spatial thinking, notably on tasks involving mental rotation, has been a topic of considerable research and debate. We review this literature, with a particular focus on the development of this sex difference, and consider four key questions: (1) When does the sex difference emerge developmentally and does the magnitude of this difference change across development? (2) What are the biological and environmental factors that contribute to sex differences in spatial skill and how might they interact? (3) How malleable are spatial skills, and is the sex difference reduced as a result of training? and (4) Does 'spatializing' the curriculum raise the level of spatial thinking in all students and hold promise for increasing and diversifying the STEM pipeline? Throughout the review, we consider promising avenues for future research. PMID:26825049

  8. Providing Spatial Data for Secondary Analysis

    PubMed Central

    Gutmann, Myron; Witkowski, Kristine; Colyer, Corey; O’Rourke, JoAnne McFarland; McNally, James

    2008-01-01

    Spatially explicit data pose a series of opportunities and challenges for all the actors involved in providing data for long-term preservation and secondary analysis -- the data producer, the data archive, and the data user. We report on opportunities and challenges for each of the three players, and then turn to a summary of current thinking about how best to prepare, archive, disseminate, and make use of social science data that have spatially explicit identification. The core issue that runs through the paper is the risk of the disclosure of the identity of respondents. If we know where they live, where they work, or where they own property, it is possible to find out who they are. Those involved in collecting, archiving, and using data need to be aware of the risks of disclosure and become familiar with best practices to avoid disclosures that will be harmful to respondents. PMID:19122860

  9. Incorporating spatial dependence in regional frequency analysis

    PubMed Central

    Wang, Zhuo; Yan, Jun; Zhang, Xuebin

    2014-01-01

    The efficiency of regional frequency analysis (RFA) is undermined by intersite dependence, which is usually ignored in parameter estimation. We propose a spatial index flood model where marginal generalized extreme value distributions are joined by an extreme-value copula characterized by a max-stable process for the spatial dependence. The parameters are estimated with a pairwise likelihood constructed from bivariate marginal generalized extreme value distributions. The estimators of model parameters and return levels can be more efficient than those from the traditional index flood model when the max-stable process fits the intersite dependence well. Through simulation, we compared the pairwise likelihood method with an L-moment method and an independence likelihood method under various spatial dependence models and dependence levels. The pairwise likelihood method was found to be the most efficient in mean squared error if the dependence model was correctly specified. When the dependence model was misspecified within the max-stable models, the pairwise likelihood method was still competitive relative to the other two methods. When the dependence model was not a max-stable model, the pairwise likelihood method led to serious bias in estimating the shape parameter and return levels, especially when the dependence was strong. In an illustration with annual maximum precipitation data from Switzerland, the pairwise likelihood method yielded remarkable reduction in the standard errors of return level estimates in comparison to the L-moment method. PMID:25745273

  10. Spatial data analysis and environmental justice

    SciTech Connect

    Bahadur, R.; Samuels, W.B.; Williams, J.W.; Zeitoun, A.H.

    1997-08-01

    Evaluations of environmental justice for government actions concerned with the transportation of hazardous materials over cross country routes presents a significant challenge in spatial data analysis. The sheer volume of data required for accurate identification of minority and low-income populations along the routes and at the endpoints can be formidable. Managing and integrating large volumes of information with state-of-the-art tools is essential in the analysis of environmental justice and equity concerns surrounding transportation of hazardous materials. This paper discusses the role and limitations of geographical information systems in the analysis and visualization of populations potentially affected by the transportation of hazardous materials over transcontinental ground and water routes. Case studies are used to demonstrate the types of data and analyses needed for evaluations of environmental justice for cross country routes and end points. Inherent capabilities and limitations in spatial resolution are evaluated for environmental assessments in which potentially affected areas are quantified based on the physical characteristics of the hazardous cargo.

  11. ADVANCED POWER SYSTEMS ANALYSIS TOOLS

    SciTech Connect

    Robert R. Jensen; Steven A. Benson; Jason D. Laumb

    2001-08-31

    The use of Energy and Environmental Research Center (EERC) modeling tools and improved analytical methods has provided key information in optimizing advanced power system design and operating conditions for efficiency, producing minimal air pollutant emissions and utilizing a wide range of fossil fuel properties. This project was divided into four tasks: the demonstration of the ash transformation model, upgrading spreadsheet tools, enhancements to analytical capabilities using the scanning electron microscopy (SEM), and improvements to the slag viscosity model. The ash transformation model, Atran, was used to predict the size and composition of ash particles, which has a major impact on the fate of the combustion system. To optimize Atran key factors such as mineral fragmentation and coalescence, the heterogeneous and homogeneous interaction of the organically associated elements must be considered as they are applied to the operating conditions. The resulting model's ash composition compares favorably to measured results. Enhancements to existing EERC spreadsheet application included upgrading interactive spreadsheets to calculate the thermodynamic properties for fuels, reactants, products, and steam with Newton Raphson algorithms to perform calculations on mass, energy, and elemental balances, isentropic expansion of steam, and gasifier equilibrium conditions. Derivative calculations can be performed to estimate fuel heating values, adiabatic flame temperatures, emission factors, comparative fuel costs, and per-unit carbon taxes from fuel analyses. Using state-of-the-art computer-controlled scanning electron microscopes and associated microanalysis systems, a method to determine viscosity using the incorporation of grey-scale binning acquired by the SEM image was developed. The image analysis capabilities of a backscattered electron image can be subdivided into various grey-scale ranges that can be analyzed separately. Since the grey scale's intensity is

  12. Advanced Extraction of Spatial Information from High Resolution Satellite Data

    NASA Astrophysics Data System (ADS)

    Pour, T.; Burian, J.; Miřijovský, J.

    2016-06-01

    In this paper authors processed five satellite image of five different Middle-European cities taken by five different sensors. The aim of the paper was to find methods and approaches leading to evaluation and spatial data extraction from areas of interest. For this reason, data were firstly pre-processed using image fusion, mosaicking and segmentation processes. Results going into the next step were two polygon layers; first one representing single objects and the second one representing city blocks. In the second step, polygon layers were classified and exported into Esri shapefile format. Classification was partly hierarchical expert based and partly based on the tool SEaTH used for separability distinction and thresholding. Final results along with visual previews were attached to the original thesis. Results are evaluated visually and statistically in the last part of the paper. In the discussion author described difficulties of working with data of large size, taken by different sensors and different also thematically.

  13. Advanced materials: Information and analysis needs

    SciTech Connect

    Curlee, T.R.; Das, S.; Lee, R.; Trumble, D.

    1990-09-01

    This report presents the findings of a study to identify the types of information and analysis that are needed for advanced materials. The project was sponsored by the US Bureau of Mines (BOM). It includes a conceptual description of information needs for advanced materials and the development and implementation of a questionnaire on the same subject. This report identifies twelve fundamental differences between advanced and traditional materials and discusses the implications of these differences for data and analysis needs. Advanced and traditional materials differ significantly in terms of physical and chemical properties. Advanced material properties can be customized more easily. The production of advanced materials may differ from traditional materials in terms of inputs, the importance of by-products, the importance of different processing steps (especially fabrication), and scale economies. The potential for change in advanced materials characteristics and markets is greater and is derived from the marriage of radically different materials and processes. In addition to the conceptual study, a questionnaire was developed and implemented to assess the opinions of people who are likely users of BOM information on advanced materials. The results of the questionnaire, which was sent to about 1000 people, generally confirm the propositions set forth in the conceptual part of the study. The results also provide data on the categories of advanced materials and the types of information that are of greatest interest to potential users. 32 refs., 1 fig., 12 tabs.

  14. ANALYSIS OF COVARIANCE WITH SPATIALLY CORRELATED SECONDARY VARIABLES

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Data sets which contain measurements on a spatially referenced response and covariate are analyzed using either co-kriging or spatial analysis of covariance. While co-kriging accounts for the correlation structure of the covariate, it is purely a predictive tool. Alternatively, spatial analysis of c...

  15. Spatial Analysis of Colorectal Cancer in Iran.

    PubMed

    Pakzad, Reza; Moudi, Asieh; Pournamdar, Zahra; Pakzad, Iraj; Mohammadian-Hashejani, Abdollah; Momenimovahed, Zohre; Salehiniya, Hamid; Towhidi, Farhad; Makhsosi, Behnam Reza

    2016-01-01

    Colorectal cancer is one of the most common cancers. Due to demographic changes, it is predicted that the incidence of this cancer will increase. Variations of its incidence rate among geographical areas are due to various contributing factors. Since there have been a lack of studies on this topic in our country, the present assessment of spatial patterns of colorectal cancer incidence in Iran was performed. In this ecological study, the new cases of colon cancer were extracted from Cancer Registry Center report of the Health Deputy of Iran in 2009. The reported incidences of the disease were standardized on the basis of the World Health Organization population and the direct method. Then the data were inserted into the GIS software, and finally, using the analysis of hot spots (Getis-Ord Gi) high-risk areas were drawn. Provinces that are higher or lower than the national average (1.9 SD) were considered hot spots or cold spots, significant at the level of 0.05. A total of 6,210 cases of colorectal cancer were registered in Iran in 2009, of which 3,727 were in men and 2,783 in women (age-standardized rates of 11.3 and 10.9 per 100,000 population, respectively). The results showed that in central and northern Iran including Isfahan, Qom, Tehran, Qazvin and Mazandaran significant hot spots in men were present (p <0.05). In women also we have high incidence in northern and central states: Mazandaran province (p<0.01) and the province of Tehran (p<0.05) had higher incidences than the national average and were apparent as significant hot spots. Analysis of the spatial distribution of colorectal cancer showed significant differences between different areas pointing to the necessity for further epidemiological studies into the etiology and early detection. PMID:27165208

  16. Spatial Uncertainty Analysis of Ecological Models

    SciTech Connect

    Jager, H.I.; Ashwood, T.L.; Jackson, B.L.; King, A.W.

    2000-09-02

    The authors evaluated the sensitivity of a habitat model and a source-sink population model to spatial uncertainty in landscapes with different statistical properties and for hypothetical species with different habitat requirements. Sequential indicator simulation generated alternative landscapes from a source map. Their results showed that spatial uncertainty was highest for landscapes in which suitable habitat was rare and spatially uncorrelated. Although, they were able to exert some control over the degree of spatial uncertainty by varying the sampling density drawn from the source map, intrinsic spatial properties (i.e., average frequency and degree of spatial autocorrelation) played a dominant role in determining variation among realized maps. To evaluate the ecological significance of landscape variation, they compared the variation in predictions from a simple habitat model to variation among landscapes for three species types. Spatial uncertainty in predictions of the amount of source habitat depended on both the spatial life history characteristics of the species and the statistical attributes of the synthetic landscapes. Species differences were greatest when the landscape contained a high proportion of suitable habitat. The predicted amount of source habitat was greater for edge-dependent (interior) species in landscapes with spatially uncorrelated(correlated) suitable habitat. A source-sink model demonstrated that, although variation among landscapes resulted in relatively little variation in overall population growth rate, this spatial uncertainty was sufficient in some situations, to produce qualitatively different predictions about population viability (i.e., population decline vs. increase).

  17. Advanced Signal Analysis for Forensic Applications of Ground Penetrating Radar

    SciTech Connect

    Steven Koppenjan; Matthew Streeton; Hua Lee; Michael Lee; Sashi Ono

    2004-06-01

    Ground penetrating radar (GPR) systems have traditionally been used to image subsurface objects. The main focus of this paper is to evaluate an advanced signal analysis technique. Instead of compiling spatial data for the analysis, this technique conducts object recognition procedures based on spectral statistics. The identification feature of an object type is formed from the training vectors by a singular-value decomposition procedure. To illustrate its capability, this procedure is applied to experimental data and compared to the performance of the neural-network approach.

  18. Advanced analysis methods in particle physics

    SciTech Connect

    Bhat, Pushpalatha C.; /Fermilab

    2010-10-01

    Each generation of high energy physics experiments is grander in scale than the previous - more powerful, more complex and more demanding in terms of data handling and analysis. The spectacular performance of the Tevatron and the beginning of operations of the Large Hadron Collider, have placed us at the threshold of a new era in particle physics. The discovery of the Higgs boson or another agent of electroweak symmetry breaking and evidence of new physics may be just around the corner. The greatest challenge in these pursuits is to extract the extremely rare signals, if any, from huge backgrounds arising from known physics processes. The use of advanced analysis techniques is crucial in achieving this goal. In this review, I discuss the concepts of optimal analysis, some important advanced analysis methods and a few examples. The judicious use of these advanced methods should enable new discoveries and produce results with better precision, robustness and clarity.

  19. Advanced Power System Analysis Capabilities

    NASA Technical Reports Server (NTRS)

    1997-01-01

    As a continuing effort to assist in the design and characterization of space power systems, the NASA Lewis Research Center's Power and Propulsion Office developed a powerful computerized analysis tool called System Power Analysis for Capability Evaluation (SPACE). This year, SPACE was used extensively in analyzing detailed operational timelines for the International Space Station (ISS) program. SPACE was developed to analyze the performance of space-based photovoltaic power systems such as that being developed for the ISS. It is a highly integrated tool that combines numerous factors in a single analysis, providing a comprehensive assessment of the power system's capability. Factors particularly critical to the ISS include the orientation of the solar arrays toward the Sun and the shadowing of the arrays by other portions of the station.

  20. An Empirical Bayes Approach to Spatial Analysis

    NASA Technical Reports Server (NTRS)

    Morris, C. N.; Kostal, H.

    1983-01-01

    Multi-channel LANDSAT data are collected in several passes over agricultural areas during the growing season. How empirical Bayes modeling can be used to develop crop identification and discrimination techniques that account for spatial correlation in such data is considered. The approach models the unobservable parameters and the data separately, hoping to take advantage of the fact that the bulk of spatial correlation lies in the parameter process. The problem is then framed in terms of estimating posterior probabilities of crop types for each spatial area. Some empirical Bayes spatial estimation methods are used to estimate the logits of these probabilities.

  1. Spatial Pattern Analysis of Heavy Metals in Beijing Agricultural Soils Based on Spatial Autocorrelation Statistics

    PubMed Central

    Huo, Xiao-Ni; Zhang, Wei-Wei; Sun, Dan-Feng; Li, Hong; Zhou, Lian-Di; Li, Bao-Guo

    2011-01-01

    This study explored the spatial pattern of heavy metals in Beijing agricultural soils using Moran’s I statistic of spatial autocorrelation. The global Moran’s I result showed that the spatial dependence of Cr, Ni, Zn, and Hg changed with different spatial weight matrixes, and they had significant and positive global spatial correlations based on distance weight. The spatial dependence of the four metals was scale-dependent on distance, but these scale effects existed within a threshold distance of 13 km, 32 km, 50 km, and 29 km, respectively for Cr, Ni, Zn, and Hg. The maximal spatial positive correlation range was 57 km, 70 km, 57 km, and 55 km for Cr, Ni, Zn, and Hg, respectively and these were not affected by sampling density. Local spatial autocorrelation analysis detected the locations of spatial clusters and spatial outliers and revealed that the pollution of these four metals occurred in significant High-high spatial clusters, Low-high, or even High-low spatial outliers. Thus, three major areas were identified and should be receiving more attention: the first was the northeast region of Beijing, where Cr, Zn, Ni, and Hg had significant increases. The second was the southeast region of Beijing where wastewater irrigation had strongly changed the content of metals, particularly of Cr and Zn, in soils. The third area was the urban fringe around city, where Hg showed a significant increase. PMID:21776217

  2. Incorporating Load Balancing Spatial Analysis Into Xml-Based Webgis

    NASA Astrophysics Data System (ADS)

    Huang, H.

    2012-07-01

    This article aims to introduce load balancing spatial analysis into XML-based WebGIS. In contrast to other approaches that implement spatial queries and analyses solely on server or browser sides, load balancing spatial analysis carries out spatial analysis on either the server or the browser sides depending on the execution costs (i.e., network transmission costs and computational costs). In this article, key elements of load balancing middlewares are investigated, and relevant solution is proposed. The comparison with server-side solution, browse-side solution, and our former solution shows that the proposed solution can optimize the execution of spatial analysis, greatly ease the network transmission load between the server and the browser sides, and therefore lead to a better performance. The proposed solution enables users to access high-performance spatial analysis simply via a web browser.

  3. Robust geostatistical analysis of spatial data

    NASA Astrophysics Data System (ADS)

    Papritz, Andreas; Künsch, Hans Rudolf; Schwierz, Cornelia; Stahel, Werner A.

    2013-04-01

    Most of the geostatistical software tools rely on non-robust algorithms. This is unfortunate, because outlying observations are rather the rule than the exception, in particular in environmental data sets. Outliers affect the modelling of the large-scale spatial trend, the estimation of the spatial dependence of the residual variation and the predictions by kriging. Identifying outliers manually is cumbersome and requires expertise because one needs parameter estimates to decide which observation is a potential outlier. Moreover, inference after the rejection of some observations is problematic. A better approach is to use robust algorithms that prevent automatically that outlying observations have undue influence. Former studies on robust geostatistics focused on robust estimation of the sample variogram and ordinary kriging without external drift. Furthermore, Richardson and Welsh (1995) proposed a robustified version of (restricted) maximum likelihood ([RE]ML) estimation for the variance components of a linear mixed model, which was later used by Marchant and Lark (2007) for robust REML estimation of the variogram. We propose here a novel method for robust REML estimation of the variogram of a Gaussian random field that is possibly contaminated by independent errors from a long-tailed distribution. It is based on robustification of estimating equations for the Gaussian REML estimation (Welsh and Richardson, 1997). Besides robust estimates of the parameters of the external drift and of the variogram, the method also provides standard errors for the estimated parameters, robustified kriging predictions at both sampled and non-sampled locations and kriging variances. Apart from presenting our modelling framework, we shall present selected simulation results by which we explored the properties of the new method. This will be complemented by an analysis a data set on heavy metal contamination of the soil in the vicinity of a metal smelter. Marchant, B.P. and Lark, R

  4. Spatial and temporal epidemiological analysis in the Big Data era.

    PubMed

    Pfeiffer, Dirk U; Stevens, Kim B

    2015-11-01

    Concurrent with global economic development in the last 50 years, the opportunities for the spread of existing diseases and emergence of new infectious pathogens, have increased substantially. The activities associated with the enormously intensified global connectivity have resulted in large amounts of data being generated, which in turn provides opportunities for generating knowledge that will allow more effective management of animal and human health risks. This so-called Big Data has, more recently, been accompanied by the Internet of Things which highlights the increasing presence of a wide range of sensors, interconnected via the Internet. Analysis of this data needs to exploit its complexity, accommodate variation in data quality and should take advantage of its spatial and temporal dimensions, where available. Apart from the development of hardware technologies and networking/communication infrastructure, it is necessary to develop appropriate data management tools that make this data accessible for analysis. This includes relational databases, geographical information systems and most recently, cloud-based data storage such as Hadoop distributed file systems. While the development in analytical methodologies has not quite caught up with the data deluge, important advances have been made in a number of areas, including spatial and temporal data analysis where the spectrum of analytical methods ranges from visualisation and exploratory analysis, to modelling. While there used to be a primary focus on statistical science in terms of methodological development for data analysis, the newly emerged discipline of data science is a reflection of the challenges presented by the need to integrate diverse data sources and exploit them using novel data- and knowledge-driven modelling methods while simultaneously recognising the value of quantitative as well as qualitative analytical approaches. Machine learning regression methods, which are more robust and can handle

  5. Advanced Placement: Model Policy Components. Policy Analysis

    ERIC Educational Resources Information Center

    Zinth, Jennifer

    2016-01-01

    Advanced Placement (AP), launched in 1955 by the College Board as a program to offer gifted high school students the opportunity to complete entry-level college coursework, has since expanded to encourage a broader array of students to tackle challenging content. This Education Commission of the State's Policy Analysis identifies key components of…

  6. Spatial Distribution Analysis of Scrub Typhus in Korea

    PubMed Central

    Jin, Hong Sung; Chu, Chaeshin; Han, Dong Yeob

    2013-01-01

    Objective: This study analyzes the spatial distribution of scrub typhus in Korea. Methods: A spatial distribution of Orientia tsutsugamushi occurrence using a geographic information system (GIS) is presented, and analyzed by means of spatial clustering and correlations. Results: The provinces of Gangwon-do and Gyeongsangbuk-do show a low incidence throughout the year. Some districts have almost identical environmental conditions of scrub typhus incidence. The land use change of districts does not directly affect the incidence rate. Conclusion: GIS analysis shows the spatial characteristics of scrub typhus. This research can be used to construct a spatial-temporal model to understand the epidemic tsutsugamushi. PMID:24159523

  7. Statistical Software for spatial analysis of stratigraphic data sets

    SciTech Connect

    2003-04-08

    Stratistics s a tool for statistical analysis of spatially explicit data sets and model output for description and for model-data comparisons. lt is intended for the analysis of data sets commonly used in geology, such as gamma ray logs and lithologic sequences, as well as 2-D data such as maps. Stratistics incorporates a far wider range of spatial analysis methods drawn from multiple disciplines, than are currently available in other packages. These include incorporation of techniques from spatial and landscape ecology, fractal analysis, and mathematical geology. Its use should substantially reduce the risk associated with the use of predictive models

  8. Statistical Software for spatial analysis of stratigraphic data sets

    2003-04-08

    Stratistics s a tool for statistical analysis of spatially explicit data sets and model output for description and for model-data comparisons. lt is intended for the analysis of data sets commonly used in geology, such as gamma ray logs and lithologic sequences, as well as 2-D data such as maps. Stratistics incorporates a far wider range of spatial analysis methods drawn from multiple disciplines, than are currently available in other packages. These include incorporation ofmore » techniques from spatial and landscape ecology, fractal analysis, and mathematical geology. Its use should substantially reduce the risk associated with the use of predictive models« less

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

    PubMed

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

    2015-01-01

    Advanced sensor technology is widely used in aquatic monitoring and research. Most applications focus on temporal variability, whereas spatial variability has been challenging to document. We assess the capability of water chemistry sensors embedded in a high-speed water intake system to document spatial variability. This new sensor platform continuously samples surface water at a range of speeds (0 to >45 km h(-1)) resulting in high-density, mesoscale spatial data. These novel observations reveal previously unknown variability in physical, chemical, and biological factors in streams, rivers, and lakes. By combining multiple sensors into one platform, we were able to detect terrestrial-aquatic hydrologic connections in a small dystrophic lake, to infer the role of main-channel vs backwater nutrient processing in a large river and to detect sharp chemical changes across aquatic ecosystem boundaries in a stream/lake complex. Spatial sensor data were verified in our examples by comparing with standard lab-based measurements of selected variables. Spatial fDOM data showed strong correlation with wet chemistry measurements of DOC, and optical NO3 concentrations were highly correlated with lab-based measurements. High-frequency spatial data similar to our examples could be used to further understand aquatic biogeochemical fluxes, ecological patterns, and ecosystem processes, and will both inform and benefit from fixed-site data. PMID:25406073

  10. Advanced techniques for the storage and use of very large, heterogeneous spatial databases

    NASA Technical Reports Server (NTRS)

    Peuquet, Donna J.

    1987-01-01

    Progress is reported in the development of a prototype knowledge-based geographic information system. The overall purpose of this project is to investigate and demonstrate the use of advanced methods in order to greatly improve the capabilities of geographic information system technology in the handling of large, multi-source collections of spatial data in an efficient manner, and to make these collections of data more accessible and usable for the Earth scientist.

  11. Analysis of a spatially deconvolved solar pore

    NASA Astrophysics Data System (ADS)

    Quintero Noda, C.; Shimizu, T.; Ruiz Cobo, B.; Suematsu, Y.; Katsukawa, Y.; Ichimoto, K.

    2016-08-01

    Solar pores are active regions with large magnetic field strengths and apparent simple magnetic configurations. Their properties resemble the ones found for the sunspot umbra although pores do not show penumbra. Therefore, solar pores present themselves as an intriguing phenomenon that is not completely understood. We examine in this work a solar pore observed with Hinode/SP using two state of the art techniques. The first one is the spatial deconvolution of the spectropolarimetric data that allows removing the stray light contamination induced by the spatial point spread function of the telescope. The second one is the inversion of the Stokes profiles assuming local thermodynamic equilibrium that let us to infer the atmospheric physical parameters. After applying these techniques, we found that the spatial deconvolution method does not introduce artefacts, even at the edges of the magnetic structure, where large horizontal gradients are detected on the atmospheric parameters. Moreover, we also describe the physical properties of the magnetic structure at different heights finding that, in the inner part of the solar pore, the temperature is lower than outside, the magnetic field strength is larger than 2 kG and unipolar, and the line-of-sight velocity is almost null. At neighbouring pixels, we found low magnetic field strengths of same polarity and strong downward motions that only occur at the low photosphere, below the continuum optical depth log τ = -1. Finally, we studied the spatial relation between different atmospheric parameters at different heights corroborating the physical properties described before.

  12. Experimental Analysis of Spatial Learning in Goldfish

    ERIC Educational Resources Information Center

    Saito, Kotaro; Watanabe, Shigeru

    2005-01-01

    The present study examined spatial learning in goldfish using a new apparatus that was an open-field circular pool with latticed holes. The subjects were motivated to reach the baited hole. We examined gustatory cues, intramaze cues, the possibility that the subject could see the food, etc. In Experiment 1, the position of the baited hole was…

  13. Analysis of a spatially deconvolved solar pore

    NASA Astrophysics Data System (ADS)

    Quintero Noda, C.; Shimizu, T.; Cobo, B. Ruiz; Suematsu, Y.; Katsukawa, Y.; Ichimoto, K.

    2016-05-01

    Solar pores are active regions with large magnetic field strengths and apparent simple magnetic configurations. Their properties resemble the ones found for the sunspot umbra although pores do not show penumbra. Therefore, solar pores present themselves as an intriguing phenomenon that is not completely understood. We examine in this work a solar pore observed with Hinode/SP using two state of the art techniques. The first one is the spatial deconvolution of the spectropolarimetric data that allows removing the stray light contamination induced by the spatial point spread function of the telescope. The second one is the inversion of the Stokes profiles assuming local thermodynamic equilibrium that let us to infer the atmospheric physical parameters. After applying these techniques, we found that the spatial deconvolution method does not introduce artefacts, even at the edges of the magnetic structure, where large horizontal gradients are detected on the atmospheric parameters. Moreover, we also describe the physical properties of the magnetic structure at different heights finding that, in the inner part of the solar pore, the temperature is lower than outside, the magnetic field strength is larger than 2 kG and unipolar, and the LOS velocity is almost null. At neighbouring pixels, we found low magnetic field strengths of same polarity and strong downward motions that only occur at the low photosphere, below the continuum optical depth log τ = -1. Finally, we studied the spatial relation between different atmospheric parameters at different heights corroborating the physical properties described before.

  14. Recent advances in morphological cell image analysis.

    PubMed

    Chen, Shengyong; Zhao, Mingzhu; Wu, Guang; Yao, Chunyan; Zhang, Jianwei

    2012-01-01

    This paper summarizes the recent advances in image processing methods for morphological cell analysis. The topic of morphological analysis has received much attention with the increasing demands in both bioinformatics and biomedical applications. Among many factors that affect the diagnosis of a disease, morphological cell analysis and statistics have made great contributions to results and effects for a doctor. Morphological cell analysis finds the cellar shape, cellar regularity, classification, statistics, diagnosis, and so forth. In the last 20 years, about 1000 publications have reported the use of morphological cell analysis in biomedical research. Relevant solutions encompass a rather wide application area, such as cell clumps segmentation, morphological characteristics extraction, 3D reconstruction, abnormal cells identification, and statistical analysis. These reports are summarized in this paper to enable easy referral to suitable methods for practical solutions. Representative contributions and future research trends are also addressed. PMID:22272215

  15. Analysis of DOA estimation spatial resolution using MUSIC algorithm

    NASA Astrophysics Data System (ADS)

    Guo, Yue; Wang, Hongyuan; Luo, Bin

    2005-11-01

    This paper presents a performance analysis of the spatial resolution of the direction of arrival (DOA) estimates attained by the multiple signal classification (MUSIC) algorithm for uncorrelated sources. The confidence interval of estimation angle which is much more intuitionistic will be considered as the new evaluation standard for the spatial resolution. Then, based on the statistic method, the qualitative analysis reveals the factors influencing the performance of the MUSIC algorithm. At last, quantitative simulations prove the theoretical analysis result exactly.

  16. Application of adaptive optics in complicated and integrated spatial multisensor system and its measurement analysis

    NASA Astrophysics Data System (ADS)

    Ding, Quanxin; Guo, Chunjie; Cai, Meng; Liu, Hua

    2007-12-01

    Adaptive Optics Expand System is a kind of new concept spatial equipment, which concerns system, cybernetics and informatics deeply, and is key way to improve advanced sensors ability. Traditional Zernike Phase Contrast Method is developed, and Accelerated High-level Phase Contrast Theory is established. Integration theory and mathematical simulation is achieved. Such Equipment, which is based on some crucial components, such as, core optical system, multi mode wavefront sensor and so on, is established for AOES advantageous configuration and global design. Studies on Complicated Spatial Multisensor System Integratation and measurement Analysis including error analysis are carried out.

  17. Spatial Analysis of China Province-level Perinatal Mortality

    PubMed Central

    XIANG, Kun; SONG, Deyong

    2016-01-01

    Background: Using spatial analysis tools to determine the spatial patterns of China province-level perinatal mortality and using spatial econometric model to examine the impacts of health care resources and different socio-economic factors on perinatal mortality. Methods: The Global Moran’s I index is used to examine whether the spatial autocorrelation exists in selected regions and Moran’s I scatter plot to examine the spatial clustering among regions. Spatial econometric models are used to investigate the spatial relationships between perinatal mortality and contributing factors. Results: The overall Moran’s I index indicates that perinatal mortality displays positive spatial autocorrelation. Moran’s I scatter plot analysis implies that there is a significant clustering of mortality in both high-rate regions and low-rate regions. The spatial econometric models analyses confirm the existence of a direct link between perinatal mortality and health care resources, socio-economic factors. Conclusions: Since a positive spatial autocorrelation has been detected in China province-level perinatal mortality, the upgrading of regional economic development and medical service level will affect the mortality not only in region itself but also its adjacent regions. PMID:27398334

  18. Spatial frequency analysis of multispectral data.

    NASA Technical Reports Server (NTRS)

    Ramapriyan, H. K.

    1972-01-01

    This paper presents the definitions of texture dependent features which can be obtained in terms of the spatial frequencies of small sections of remotely sensed multispectral data. The features are made independent of the direction of view by defining them as symmetric functions of the spatial frequencies sensed with various viewing directions. Several textural features are defined and experimental results indicating existence of signatures in these features are presented. Preliminary experiments have been performed on the classification of 60 samples, 10 from each of the following 6 categories - grass, trees, water, staked tomatoes, treated ground tomatoes, and untreated ground tomatoes. Classifications of the training samples using only one feature at a time indicate that several of the features yield classification efficiencies higher than 65%. The efficiency increases considerably when combinations of these features are used.

  19. Exploiting spatial descriptions in visual scene analysis.

    PubMed

    Ziegler, Leon; Johannsen, Katrin; Swadzba, Agnes; De Ruiter, Jan P; Wachsmuth, Sven

    2012-08-01

    The reliable automatic visual recognition of indoor scenes with complex object constellations using only sensor data is a nontrivial problem. In order to improve the construction of an accurate semantic 3D model of an indoor scene, we exploit human-produced verbal descriptions of the relative location of pairs of objects. This requires the ability to deal with different spatial reference frames (RF) that humans use interchangeably. In German, both the intrinsic and relative RF are used frequently, which often leads to ambiguities in referential communication. We assume that there are certain regularities that help in specific contexts. In a first experiment, we investigated how speakers of German describe spatial relationships between different pieces of furniture. This gave us important information about the distribution of the RFs used for furniture-predicate combinations, and by implication also about the preferred spatial predicate. The results of this experiment are compiled into a computational model that extracts partial orderings of spatial arrangements between furniture items from verbal descriptions. In the implemented system, the visual scene is initially scanned by a 3D camera system. From the 3D point cloud, we extract point clusters that suggest the presence of certain furniture objects. We then integrate the partial orderings extracted from the verbal utterances incrementally and cumulatively with the estimated probabilities about the identity and location of objects in the scene, and also estimate the probable orientation of the objects. This allows the system to significantly improve both the accuracy and richness of its visual scene representation. PMID:22806654

  20. Discrete analysis of spatial-sensitivity models

    NASA Technical Reports Server (NTRS)

    Nielsen, Kenneth R. K.; Wandell, Brian A.

    1988-01-01

    Procedures for reducing the computational burden of current models of spatial vision are described, the simplifications being consistent with the prediction of the complete model. A method for using pattern-sensitivity measurements to estimate the initial linear transformation is also proposed which is based on the assumption that detection performance is monotonic with the vector length of the sensor responses. It is shown how contrast-threshold data can be used to estimate the linear transformation needed to characterize threshold performance.

  1. APPLICATION OF SPATIAL INFORMATION TECHNOLOGY TO PETROLEUM RESOURCE ASSESSMENT ANALYSIS.

    USGS Publications Warehouse

    Miller, Betty M.; Domaratz, Michael A.

    1984-01-01

    Petroleum resource assessment procedures require the analysis of a large volume of spatial data. The US Geological Survey (USGS) has developed and applied spatial information handling procedures and digital cartographic techniques to a recent study involving the assessment of oil and gas resource potential for 74 million acres of designated and proposed wilderness lands in the western United States. The part of the study which dealt with the application of spatial information technology to petroleum resource assessment procedures is reviewed. A method was designed to expedite the gathering, integrating, managing, manipulating and plotting of spatial data from multiple data sources that are essential in modern resource assessment procedures.

  2. Advanced Fuel Cycle Economic Sensitivity Analysis

    SciTech Connect

    David Shropshire; Kent Williams; J.D. Smith; Brent Boore

    2006-12-01

    A fuel cycle economic analysis was performed on four fuel cycles to provide a baseline for initial cost comparison using the Gen IV Economic Modeling Work Group G4 ECON spreadsheet model, Decision Programming Language software, the 2006 Advanced Fuel Cycle Cost Basis report, industry cost data, international papers, the nuclear power related cost study from MIT, Harvard, and the University of Chicago. The analysis developed and compared the fuel cycle cost component of the total cost of energy for a wide range of fuel cycles including: once through, thermal with fast recycle, continuous fast recycle, and thermal recycle.

  3. Advanced Analysis Methods in High Energy Physics

    SciTech Connect

    Pushpalatha C. Bhat

    2001-10-03

    During the coming decade, high energy physics experiments at the Fermilab Tevatron and around the globe will use very sophisticated equipment to record unprecedented amounts of data in the hope of making major discoveries that may unravel some of Nature's deepest mysteries. The discovery of the Higgs boson and signals of new physics may be around the corner. The use of advanced analysis techniques will be crucial in achieving these goals. The author discusses some of the novel methods of analysis that could prove to be particularly valuable for finding evidence of any new physics, for improving precision measurements and for exploring parameter spaces of theoretical models.

  4. Eigenvector spatial filtering for image analysis: An efficient algorithm

    NASA Astrophysics Data System (ADS)

    Rura, Melissa J.

    Eigenvector Spatial Filtering (ESF) is an established method in social science literature for incorporating spatial information in model specifications. ESF computes spatial eigenvectors, which are defined by the spatial structure associated with a variable. One important limitation of this technique is that it becomes computationally intensive in image analysis because of the massive number of image pixels. This research develops an algorithm, which makes ESF more efficient, by using the analytical solution for the eigenvalues and spatial eigenvectors, which are essentially a series of orthogonal, uncorrelated map patterns that describe positively spatial autocorrelated patterns through negatively spatially autocorrelated patterns, and global, regional, and local patterns of spatial dependencies in a surface. A reformulation of the analytical solution reduces the required computations and allows the eigenvectors to be computed sequentially. Finally, a series of sampling methods are explored. This algorithm is applied to three example multispectral images of different sizes: small (i.e., ˜200,000 pixels), medium (i.e., ˜1,000,000 pixels) and large (i.e., ˜110,000,000 pixels) and is evaluated in terms of output for each sampling technique and the complete spectral information. The output spatial filters of these sampling techniques compare to the filter generated with the complete spectral information. In terms of efficiency evaluation, the time is required to construct filters through sampling versus through analysis of the complete image surface is evaluated and the complexity of set-up and execution of the sampled and distributed algorithms are assessed.

  5. Spatially Weighted Principal Component Analysis for Imaging Classification

    PubMed Central

    Guo, Ruixin; Ahn, Mihye; Zhu, Hongtu

    2014-01-01

    The aim of this paper is to develop a supervised dimension reduction framework, called Spatially Weighted Principal Component Analysis (SWPCA), for high dimensional imaging classification. Two main challenges in imaging classification are the high dimensionality of the feature space and the complex spatial structure of imaging data. In SWPCA, we introduce two sets of novel weights including global and local spatial weights, which enable a selective treatment of individual features and incorporation of the spatial structure of imaging data and class label information. We develop an e cient two-stage iterative SWPCA algorithm and its penalized version along with the associated weight determination. We use both simulation studies and real data analysis to evaluate the finite-sample performance of our SWPCA. The results show that SWPCA outperforms several competing principal component analysis (PCA) methods, such as supervised PCA (SPCA), and other competing methods, such as sparse discriminant analysis (SDA). PMID:26089629

  6. SPATIAL ANALYSIS AND DECISION ASSISTANCE (SADA) TRAINING COURSE

    EPA Science Inventory

    Spatial Analysis and Decision Assistance (SADA) is a Windows freeware program that incorporates tools from environmental assessment into an effective problem-solving environment. SADA was developed by the Institute for Environmental Modeling at the University of Tennessee and inc...

  7. Analysis of spatially deconvolved polar faculae

    NASA Astrophysics Data System (ADS)

    Quintero Noda, C.; Suematsu, Y.; Ruiz Cobo, B.; Shimizu, T.; Asensio Ramos, A.

    2016-07-01

    Polar faculae are bright features that can be detected in solar limb observations and they are related to magnetic field concentrations. Although there are a large number of works studying them, some questions about their nature as their magnetic properties at different heights are still open. Thus, we aim to improve the understanding of solar polar faculae. In that sense, we infer the vertical stratification of the temperature, gas pressure, line-of-sight velocity and magnetic field vector of polar faculae regions. We performed inversions of the Stokes profiles observed with Hinode/Spectropolarimeter after removing the stray light contamination produced by the spatial point spread function of the telescope. Moreover, after solving the azimuth ambiguity, we transform the magnetic field vector to local solar coordinates. The obtained results reveal that the polar faculae are constituted by hot plasma with low line-of-sight velocities and single polarity magnetic fields in the kilogauss range that are nearly perpendicular to the solar surface. We also found that the spatial location of these magnetic fields is slightly shifted respect to the continuum observations towards the disc centre. We believe that this is due to the hot wall effect that allows detecting photons that come from deeper layers located closer to the solar limb.

  8. Local spatial frequency analysis for computer vision

    NASA Technical Reports Server (NTRS)

    Krumm, John; Shafer, Steven A.

    1990-01-01

    A sense of vision is a prerequisite for a robot to function in an unstructured environment. However, real-world scenes contain many interacting phenomena that lead to complex images which are difficult to interpret automatically. Typical computer vision research proceeds by analyzing various effects in isolation (e.g., shading, texture, stereo, defocus), usually on images devoid of realistic complicating factors. This leads to specialized algorithms which fail on real-world images. Part of this failure is due to the dichotomy of useful representations for these phenomena. Some effects are best described in the spatial domain, while others are more naturally expressed in frequency. In order to resolve this dichotomy, we present the combined space/frequency representation which, for each point in an image, shows the spatial frequencies at that point. Within this common representation, we develop a set of simple, natural theories describing phenomena such as texture, shape, aliasing and lens parameters. We show these theories lead to algorithms for shape from texture and for dealiasing image data. The space/frequency representation should be a key aid in untangling the complex interaction of phenomena in images, allowing automatic understanding of real-world scenes.

  9. Analysis of spatially deconvolved polar faculae

    NASA Astrophysics Data System (ADS)

    Quintero Noda, C.; Suematsu, Y.; Cobo, B. Ruiz; Shimizu, T.; Asensio Ramos, A.

    2016-05-01

    Polar faculae are bright features that can be detected in solar limb observations and they are related to magnetic field concentrations. Although there is a large number of works studying them, some questions about their nature as their magnetic properties at different heights are still open. Thus, we aim to improve the understanding of solar polar faculae. In that sense, we infer the vertical stratification of the temperature, gas pressure, line of sight velocity and magnetic field vector of polar faculae regions. We performed inversions of the Stokes profiles observed with Hinode/SP after removing the stray light contamination produced by the spatial point spread function of the telescope. Moreover, after solving the azimuth ambiguity, we transform the magnetic field vector to local solar coordinates. The obtained results reveal that the polar faculae are constituted by hot plasma with low line of sight velocities and single polarity magnetic fields in the kilogauss range that are nearly perpendicular to the solar surface. We also found that the spatial location of these magnetic fields is slightly shifted respect to the continuum observations towards the disc centre. We believe that this is due to the hot wall effect that allows detecting photons that come from deeper layers located closer to the solar limb.

  10. Asymptotic analysis of spatial discretizations in implicit Monte Carlo

    SciTech Connect

    Densmore, Jeffery D

    2008-01-01

    We perform an asymptotic analysis of spatial discretizations in Implicit Monte Carlo (IMC). We consider two asymptotic scalings: one that represents a time step that resolves the mean-free time, and one that corresponds to a fixed, optically large time step. We show that only the latter scaling results in a valid spatial discretization of the proper diffusion equation, and thus we conclude that IMC only yields accurate solutions when using optically large spatial cells if time steps are also optically large, We demonstrate the validity of our analysis with a set of numerical examples.

  11. Asymptotic analysis of spatial discretizations in implicit Monte Carlo

    SciTech Connect

    Densmore, Jeffery D

    2009-01-01

    We perform an asymptotic analysis of spatial discretizations in Implicit Monte Carlo (IMC). We consider two asymptotic scalings: one that represents a time step that resolves the mean-free time, and one that corresponds to a fixed, optically large time step. We show that only the latter scaling results in a valid spatial discretization of the proper diffusion equation, and thus we conclude that IMC only yields accurate solutions when using optically large spatial cells if time steps are also optically large. We demonstrate the validity of our analysis with a set of numerical examples.

  12. Advanced Power Plant Development and Analysis Methodologies

    SciTech Connect

    A.D. Rao; G.S. Samuelsen; F.L. Robson; B. Washom; S.G. Berenyi

    2006-06-30

    Under the sponsorship of the U.S. Department of Energy/National Energy Technology Laboratory, a multi-disciplinary team led by the Advanced Power and Energy Program of the University of California at Irvine is defining the system engineering issues associated with the integration of key components and subsystems into advanced power plant systems with goals of achieving high efficiency and minimized environmental impact while using fossil fuels. These power plant concepts include 'Zero Emission' power plants and the 'FutureGen' H2 co-production facilities. The study is broken down into three phases. Phase 1 of this study consisted of utilizing advanced technologies that are expected to be available in the 'Vision 21' time frame such as mega scale fuel cell based hybrids. Phase 2 includes current state-of-the-art technologies and those expected to be deployed in the nearer term such as advanced gas turbines and high temperature membranes for separating gas species and advanced gasifier concepts. Phase 3 includes identification of gas turbine based cycles and engine configurations suitable to coal-based gasification applications and the conceptualization of the balance of plant technology, heat integration, and the bottoming cycle for analysis in a future study. Also included in Phase 3 is the task of acquiring/providing turbo-machinery in order to gather turbo-charger performance data that may be used to verify simulation models as well as establishing system design constraints. The results of these various investigations will serve as a guide for the U. S. Department of Energy in identifying the research areas and technologies that warrant further support.

  13. Imaging spectroscopic analysis at the Advanced Light Source

    SciTech Connect

    MacDowell, A. A.; Warwick, T.; Anders, S.; Lamble, G.M.; Martin, M.C.; McKinney, W.R.; Padmore, H.A.

    1999-05-12

    One of the major advances at the high brightness third generation synchrotrons is the dramatic improvement of imaging capability. There is a large multi-disciplinary effort underway at the ALS to develop imaging X-ray, UV and Infra-red spectroscopic analysis on a spatial scale from. a few microns to 10nm. These developments make use of light that varies in energy from 6meV to 15KeV. Imaging and spectroscopy are finding applications in surface science, bulk materials analysis, semiconductor structures, particulate contaminants, magnetic thin films, biology and environmental science. This article is an overview and status report from the developers of some of these techniques at the ALS. The following table lists all the currently available microscopes at the. ALS. This article will describe some of the microscopes and some of the early applications.

  14. The role of the society of Latin American specialists on remote sensing (SELPER) in the analysis and actions related to the main advances and needs of spatial remote sensing for Latin America

    NASA Astrophysics Data System (ADS)

    Araya, Mauricio F.

    The existence of SELPER (Sociedad de Especialistas Latinoamericanos en Percepción Remota / Society of Latinamerican Specialists on Remote Sensing) has filled a great gap among latinamerican countries. SELPER was formed in 1980 and several important activities, having international support, have been performed and are planned in the near future. SELPER consolidation will help develop several important regional cooperation programs and the next years look very promisory in this sense. Different steps are planned but the most important is related with the formation of such a Latin American Council on Remote Sensing, having official support from different countries of the region; SELPER can help this important objective. Main advances and needs are summarized in this paper and it is possible to conclude that SELPER will be important for regional and inter-regional scientific and technical cooperation on remote sensing.

  15. Channels of synthesis forty years on: integrated analysis of spatial economic systems

    NASA Astrophysics Data System (ADS)

    Hewings, Geoffrey J. D.; Nazara, Suahasil; Dridi, Chokri

    . Isard's vision of integrated modeling that was laid out in the 1960s book Methods of Regional Science provided a road map for the development of more sophisticated analysis of spatial economic systems. Some forty years later, we look back at this vision and trace developments in a sample of three areas - demographic-econometric integrated modeling, spatial interaction modeling, and environmental-economic modeling. Attention will be focused on methodological advances and their motivation by new developments in theory as well as innovations in the applications of these models to address new policy challenges. Underlying the discussion will be an evaluation of the way in which spatial issues have been addressed, ranging from concerns with regionalization to issues of spillovers and spatial correlation.

  16. Advanced Remote-Sensing Imaging Emission Spectrometer (ARIES): AIRS Spectral Resolution with MODIS Spatial Resolution

    NASA Technical Reports Server (NTRS)

    Pagano, Thomas S.; Chahine, Moustafa T.; Aumann, Hartmut H.; OCallaghan, Fred

    2006-01-01

    The Advanced Remote-sensing Imaging Emission Spectrometer (ARIES) will measure a wide range of earth quantities fundamental to the study of global climate change. It will build upon the success of the Moderate Resolution Imaging Spectroradiometer (MODIS) and the Atmospheric Infrared Sounder (AIRS) instruments currently flying on the EOS Aqua Spacecraft. Both instruments are facility instruments for NASA providing data to thousands of scientists investigating land, ocean and atmospheric Earth System processes. ARIES will meet all the requirements of AIRS and MODIS in a single compact instrument, while providing the next-generation capability of improved spatial resolution for AIRS and improved spectral resolution for MODIS.

  17. [Spatial analysis on land use in Xishuangbanna].

    PubMed

    Song, Guobao; Li, Zhenghai; Gao, Jixi; Wang, Haimei

    2006-06-01

    Based on remote image and GIS technology, this paper analyzed the relationships between land use system and natural topographic factors such as elevation, slope, and river system in Xishuangbanna. The results showed that the land use system in the study region was dominated by forestland, cropland and grassland. The area of forestland was 13 420 km, accounting for 74% of the total, and that of cropland and grassland was 3 251 km2 and 2 332 km2, accounting for 13% and 18% of the total, respectively. The areas of these three land use types varied with elevation in single-peaked curve. Forestland mainly distributed around the elevation of 1 000 - 1 200 m, while cropland and grassland centralized at the elevation of 900 m. Urban land and cropland, which were greatly influenced by human activity, had lower slope index than forestland and grassland. Besides elevation and slope, river system in valley had effects on land use condition. With increasing buffer distance in valley, a strong spatial pattern of land use type was presented, i. e. , cropland, urban land and unused land concentrated greatly adjacent to water, while forestland and grassland were far away from valley. A landscape with relatively primary status, which was comprised of forestland as matrix, river as corridor, and cropland as patch, would come into being. PMID:16964932

  18. Spatial analysis of IRAS observations of nearby spirals

    NASA Technical Reports Server (NTRS)

    Ball, Roger; Lo, R. Y.

    1990-01-01

    The unbiased survey of the infrared sky carried out by the Infrared Astronomy Satellite (IRAS) satellite has greatly accelerated advances in understanding the dust component of our own and external galaxies. However, most extragalactic studies to date have been based on the IRAS Point Source Catalog (PSC), which has two serious limitations. First, in sources where a significant fraction of the flux is extended, significant errors may result from using PSC fluxes in comparative studies, and these errors could be systematic if the tendency to be non-pointlike depends on physical properties of the galaxy. Additionally, use of PSC fluxes rules out any direct investigation of the spatial distribution of the IRAS emission from disks in external galaxies. Since work on the Galactic IRAS results has shown that very different physical processes can make varying contributions to the observed flux, it is important to look at a wide sample of galaxies with some spatial resolution to study the relative dominance of these processes under a variety of conditions. Here, researchers report on work they are doing to carry out this program for many nearby spirals, using an analysis package that was developed for this purpose. Researchers carried out analysis for a sample of 121 nearby spirals. The fraction of the flux contained in a point source varies from 0 to 1 across the sample, all of which are well resolved at their nominal optical diameters. There is no evidence that the galaxies of smaller angular size are less likely to be resolved by IRAS at this level. The program gives results which are quite repeatable from scan to scan; the fraction f (point source flux over total flux) at 60 microns has typical errors of 0.03 when different scans are combined. Approximately two-thirds of the sample have more flux in the extended than in the nuclear component. There is a tendency for earlier-type spirals to be less centrally concentrated, but this effect is slight and the degree of

  19. Spatially explicit spectral analysis of point clouds and geospatial data

    NASA Astrophysics Data System (ADS)

    Buscombe, Daniel

    2016-01-01

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

  20. Spatially explicit spectral analysis of point clouds and geospatial data

    USGS Publications Warehouse

    Buscombe, Daniel D.

    2015-01-01

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

  1. Integrated safety analysis based on spatial kinetics

    SciTech Connect

    Finnemann, H.; Drescher, G.

    1994-12-31

    The continuing progress in computer technology, characterized by the ever-increasing calculational speed of various computer architectures, enables the direct coupling of up to recently separate code systems. As a consequence different areas of analysis like reactor physics, core thermal hydraulics, and plant dynamics can be integrated to increase the accuracy of simulation over that obtained from imposing conservative boundary conditions at the interfaces. The coupling of thermal-hydraulic subchannel analysis with nodal space-time kinetics calculations is an important step toward an even more extensive integration of complex code systems. In this paper we present some results of a transient departure from nucleate boiling ratio (DNBR) calculation integrated in the nodal kinetics code PANBOX.

  2. Recent advances in flow injection analysis.

    PubMed

    Trojanowicz, Marek; Kołacińska, Kamila

    2016-04-01

    A dynamic development of methodologies of analytical flow injection measurements during four decades since their invention has reinforced the solid position of flow analysis in the arsenal of techniques and instrumentation of contemporary chemical analysis. With the number of published scientific papers exceeding 20 000, and advanced instrumentation available for environmental, food, and pharmaceutical analysis, flow analysis is well established as an extremely vital field of modern flow chemistry, which is developed simultaneously with methods of chemical synthesis carried out under flow conditions. This review work is based on almost 300 original papers published mostly in the last decade, with special emphasis put on presenting novel achievements from the most recent 2-3 years in order to indicate current development trends of this methodology. Besides the evolution of the design of whole measuring systems, and including especially new applications of various detections methods, several aspects of implications of progress in nanotechnology, and miniaturization of measuring systems for application in different field of modern chemical analysis are also discussed. PMID:26906258

  3. Advancing Behavior Analysis in Zoos and Aquariums.

    PubMed

    Maple, Terry L; Segura, Valerie D

    2015-05-01

    Zoos, aquariums, and other captive animal facilities offer promising opportunities to advance the science and practice of behavior analysis. Zoos and aquariums are necessarily concerned with the health and well-being of their charges and are held to a high standard by their supporters (visitors, members, and donors), organized critics, and the media. Zoos and aquariums offer unique venues for teaching and research and a locus for expanding the footprint of behavior analysis. In North America, Europe, and the UK, formal agreements between zoos, aquariums, and university graduate departments have been operating successfully for decades. To expand on this model, it will be necessary to help zoo and aquarium managers throughout the world to recognize the value of behavior analysis in the delivery of essential animal health and welfare services. Academic institutions, administrators, and invested faculty should consider the utility of training students to meet the growing needs of applied behavior analysis in zoos and aquariums and other animal facilities such as primate research centers, sanctuaries, and rescue centers. PMID:27540508

  4. Spatial uncertainty analysis: Propagation of interpolation errors in spatially distributed models

    USGS Publications Warehouse

    Phillips, D.L.; Marks, D.G.

    1996-01-01

    In simulation modelling, it is desirable to quantify model uncertainties and provide not only point estimates for output variables but confidence intervals as well. Spatially distributed physical and ecological process models are becoming widely used, with runs being made over a grid of points that represent the landscape. This requires input values at each grid point, which often have to be interpolated from irregularly scattered measurement sites, e.g., weather stations. Interpolation introduces spatially varying errors which propagate through the model We extended established uncertainty analysis methods to a spatial domain for quantifying spatial patterns of input variable interpolation errors and how they propagate through a model to affect the uncertainty of the model output. We applied this to a model of potential evapotranspiration (PET) as a demonstration. We modelled PET for three time periods in 1990 as a function of temperature, humidity, and wind on a 10-km grid across the U.S. portion of the Columbia River Basin. Temperature, humidity, and wind speed were interpolated using kriging from 700- 1000 supporting data points. Kriging standard deviations (SD) were used to quantify the spatially varying interpolation uncertainties. For each of 5693 grid points, 100 Monte Carlo simulations were done, using the kriged values of temperature, humidity, and wind, plus random error terms determined by the kriging SDs and the correlations of interpolation errors among the three variables. For the spring season example, kriging SDs averaged 2.6??C for temperature, 8.7% for relative humidity, and 0.38 m s-1 for wind. The resultant PET estimates had coefficients of variation (CVs) ranging from 14% to 27% for the 10-km grid cells. Maps of PET means and CVs showed the spatial patterns of PET with a measure of its uncertainty due to interpolation of the input variables. This methodology should be applicable to a variety of spatially distributed models using interpolated

  5. Modeling the usefulness of spatial correlation analysis on karst systems.

    PubMed

    Budge, Trevor J; Sharp, John M

    2009-01-01

    Cross-correlation analyses on field data collected in karst aquifer systems can be used to develop a conceptual understanding of the aquifer. This includes the use of many data sets from the same aquifer to develop an understanding of how properties vary spatially. We focus on a method for characterizing the distribution of recharge, which is becoming increasingly important in regions where urban development encroaches on these important sources of water. Spatially varying precipitation data and cross-correlation analysis provide a means of spatially characterizing recharge locations on a karst aquifer. Our work expands on the numerical experiments conducted by Padilla and Pulido-Bosch (1995) using the numerical ground water model MODFLOW to introduce spatially varying parameters. The numerical experiments include conduit-controlled, matrix-controlled, and mixed karst systems with more than one precipitation time series input. The results show that spatially varying parameters can be inferred based on the cross-correlation of precipitation data and spring discharge. Simulations were completed using aquifer parameters derived from studies of the Barton Springs segment of the Edwards Aquifer. The simulations indicate that spatial variability within an aquifer can be inferred using cross-correlation analysis. A field study using these methods is summarized for Barton Springs near Austin, Texas. PMID:19462525

  6. Spatial data analysis for exploration of regional scale geothermal resources

    NASA Astrophysics Data System (ADS)

    Moghaddam, Majid Kiavarz; Noorollahi, Younes; Samadzadegan, Farhad; Sharifi, Mohammad Ali; Itoi, Ryuichi

    2013-10-01

    Defining a comprehensive conceptual model of the resources sought is one of the most important steps in geothermal potential mapping. In this study, Fry analysis as a spatial distribution method and 5% well existence, distance distribution, weights of evidence (WofE), and evidential belief function (EBFs) methods as spatial association methods were applied comparatively to known geothermal occurrences, and to publicly-available regional-scale geoscience data in Akita and Iwate provinces within the Tohoku volcanic arc, in northern Japan. Fry analysis and rose diagrams revealed similar directional patterns of geothermal wells and volcanoes, NNW-, NNE-, NE-trending faults, hotsprings and fumaroles. Among the spatial association methods, WofE defined a conceptual model correspondent with the real world situations, approved with the aid of expert opinion. The results of the spatial association analyses quantitatively indicated that the known geothermal occurrences are strongly spatially-associated with geological features such as volcanoes, craters, NNW-, NNE-, NE-direction faults and geochemical features such as hotsprings, hydrothermal alteration zones and fumaroles. Geophysical data contains temperature gradients over 100 °C/km and heat flow over 100 mW/m2. In general, geochemical and geophysical data were better evidence layers than geological data for exploring geothermal resources. The spatial analyses of the case study area suggested that quantitative knowledge from hydrothermal geothermal resources was significantly useful for further exploration and for geothermal potential mapping in the case study region. The results can also be extended to the regions with nearly similar characteristics.

  7. Selection of neutrino burst candidates by pulse spatial distribution analysis

    NASA Astrophysics Data System (ADS)

    Ryasny, V. G.

    1996-02-01

    The method of analysis and possibilities of identification of neutrino bursts from collapsing stars using a spatial distribution of pulses in the multimodular installations, like the Large Volume Detector at the Gran Sasso Laboratory, Liquid Scintillation Detector (Mont Blanc) and Baksan Scintillation Telescope, are discussed. The method could be applicable for any position sensitive detector. By the spatial distribution analysis the burst imitation probability can be decreased by at least 2 orders of magnitude, without significant loss of sensitivity, for currently predicted number of the neutrino interactions.

  8. NASTRAN flutter analysis of advanced turbopropellers

    NASA Technical Reports Server (NTRS)

    Elchuri, V.; Smith, G. C. C.

    1982-01-01

    An existing capability developed to conduct modal flutter analysis of tuned bladed-shrouded discs in NASTRAN was modified and applied to investigate the subsonic unstalled flutter characteristics of advanced turbopropellers. The modifications pertain to the inclusion of oscillatory modal aerodynamic loads of blades with large (backward and forward) variable sweep. The two dimensional subsonic cascade unsteady aerodynamic theory was applied in a strip theory manner with appropriate modifications for the sweep effects. Each strip is associated with a chord selected normal to any spanwise reference curve such as the blade leading edge. The stability of three operating conditions of a 10-bladed propeller is analyzed. Each of these operating conditions is iterated once to determine the flutter boundary. A 5-bladed propeller is also analyzed at one operating condition to investigate stability. Analytical results obtained are in very good agreement with those from wind tunnel tests.

  9. Advanced development in chemical analysis of Cordyceps.

    PubMed

    Zhao, J; Xie, J; Wang, L Y; Li, S P

    2014-01-01

    Cordyceps sinensis, also called DongChongXiaCao (winter worm summer grass) in Chinese, is a well-known and valued traditional Chinese medicine. In 2006, we wrote a review for discussing the markers and analytical methods in quality control of Cordyceps (J. Pharm. Biomed. Anal. 41 (2006) 1571-1584). Since then this review has been cited by others for more than 60 times, which suggested that scientists have great interest in this special herbal material. Actually, the number of publications related to Cordyceps after 2006 is about 2-fold of that in two decades before 2006 according to the data from Web of Science. Therefore, it is necessary to review and discuss the advanced development in chemical analysis of Cordyceps since then. PMID:23688494

  10. Advanced Technology Lifecycle Analysis System (ATLAS)

    NASA Technical Reports Server (NTRS)

    O'Neil, Daniel A.; Mankins, John C.

    2004-01-01

    Developing credible mass and cost estimates for space exploration and development architectures require multidisciplinary analysis based on physics calculations, and parametric estimates derived from historical systems. Within the National Aeronautics and Space Administration (NASA), concurrent engineering environment (CEE) activities integrate discipline oriented analysis tools through a computer network and accumulate the results of a multidisciplinary analysis team via a centralized database or spreadsheet Each minute of a design and analysis study within a concurrent engineering environment is expensive due the size of the team and supporting equipment The Advanced Technology Lifecycle Analysis System (ATLAS) reduces the cost of architecture analysis by capturing the knowledge of discipline experts into system oriented spreadsheet models. A framework with a user interface presents a library of system models to an architecture analyst. The analyst selects models of launchers, in-space transportation systems, and excursion vehicles, as well as space and surface infrastructure such as propellant depots, habitats, and solar power satellites. After assembling the architecture from the selected models, the analyst can create a campaign comprised of missions spanning several years. The ATLAS controller passes analyst specified parameters to the models and data among the models. An integrator workbook calls a history based parametric analysis cost model to determine the costs. Also, the integrator estimates the flight rates, launched masses, and architecture benefits over the years of the campaign. An accumulator workbook presents the analytical results in a series of bar graphs. In no way does ATLAS compete with a CEE; instead, ATLAS complements a CEE by ensuring that the time of the experts is well spent Using ATLAS, an architecture analyst can perform technology sensitivity analysis, study many scenarios, and see the impact of design decisions. When the analyst is

  11. Kinematic analysis of a spatial mechanism for estimating shaking effects

    NASA Astrophysics Data System (ADS)

    Murthy, P. S. S.; Satyadevi, A.; Gopala Krishna, A.; Eswaraiah, K.

    2015-12-01

    Spatial mechanisms are the most general category of kinematic devices. They offer the greatest capability to accomplish any desired kinematic task. A mechanism exerts forces and moments on its supporting frame, which result in vibration. Besides of its effect on efficiency, reducing vibration has become inevitable in the current industrial environment where stern standards on noise and vibration prevail. Balancing of shaking forces and shaking moments in mechanisms is important in order to improve their dynamic performance and fatigue life by reducing vibration, noise and wear. The analysis and synthesis of spatial mechanisms which involves extensive vector mathematics and linear algebra is to be simplified to be taught to engineers in undergraduate education. In the present paper the kinematic analysis of a spatial four-link RSCR mechanism is done to get the velocities and accelerations of its various links which is necessary for the estimation of inertia forces in a mechanism.

  12. Macroscopic spatial analysis of pedestrian and bicycle crashes.

    PubMed

    Siddiqui, Chowdhury; Abdel-Aty, Mohamed; Choi, Keechoo

    2012-03-01

    This study investigates the effect of spatial correlation using a Bayesian spatial framework to model pedestrian and bicycle crashes in Traffic Analysis Zones (TAZs). Aggregate models for pedestrian and bicycle crashes were estimated as a function of variables related to roadway characteristics, and various demographic and socio-economic factors. It was found that significant differences were present between the predictor sets for pedestrian and bicycle crashes. The Bayesian Poisson-lognormal model accounting for spatial correlation for pedestrian crashes in the TAZs of the study counties retained nine variables significantly different from zero at 95% Bayesian credible interval. These variables were - total roadway length with 35 mph posted speed limit, total number of intersections per TAZ, median household income, total number of dwelling units, log of population per square mile of a TAZ, percentage of households with non-retired workers but zero auto, percentage of households with non-retired workers and one auto, long term parking cost, and log of total number of employment in a TAZ. A separate distinct set of predictors were found for the bicycle crash model. In all cases the Bayesian models with spatial correlation performed better than the models that did not account for spatial correlation among TAZs. This finding implies that spatial correlation should be considered while modeling pedestrian and bicycle crashes at the aggregate or macro-level. PMID:22269522

  13. Variability of Soil Temperature: A Spatial and Temporal Analysis.

    ERIC Educational Resources Information Center

    Walsh, Stephen J.; And Others

    1991-01-01

    Discusses an analysis of the relationship of soil temperatures at 3 depths to various climatic variables along a 200-kilometer transect in west-central Oklahoma. Reports that temperature readings increased from east to west. Concludes that temperature variations were explained by a combination of spatial, temporal, and biophysical factors. (SG)

  14. Visuo-Spatial Performance in Autism: A Meta-Analysis

    ERIC Educational Resources Information Center

    Muth, Anne; Hönekopp, Johannes; Falter, Christine M.

    2014-01-01

    Visuo-spatial skills are believed to be enhanced in autism spectrum disorders (ASDs). This meta-analysis tests the current state of evidence for Figure Disembedding, Block Design, Mental Rotation and Navon tasks in ASD and neurotypicals. Block Design (d = 0.32) and Figure Disembedding (d = 0.26) showed superior performance for ASD with large…

  15. Spatial regression analysis of traffic crashes in Seoul.

    PubMed

    Rhee, Kyoung-Ah; Kim, Joon-Ki; Lee, Young-ihn; Ulfarsson, Gudmundur F

    2016-06-01

    Traffic crashes can be spatially correlated events and the analysis of the distribution of traffic crash frequency requires evaluation of parameters that reflect spatial properties and correlation. Typically this spatial aspect of crash data is not used in everyday practice by planning agencies and this contributes to a gap between research and practice. A database of traffic crashes in Seoul, Korea, in 2010 was developed at the traffic analysis zone (TAZ) level with a number of GIS developed spatial variables. Practical spatial models using available software were estimated. The spatial error model was determined to be better than the spatial lag model and an ordinary least squares baseline regression. A geographically weighted regression model provided useful insights about localization of effects. The results found that an increased length of roads with speed limit below 30 km/h and a higher ratio of residents below age of 15 were correlated with lower traffic crash frequency, while a higher ratio of residents who moved to the TAZ, more vehicle-kilometers traveled, and a greater number of access points with speed limit difference between side roads and mainline above 30 km/h all increased the number of traffic crashes. This suggests, for example, that better control or design for merging lower speed roads with higher speed roads is important. A key result is that the length of bus-only center lanes had the largest effect on increasing traffic crashes. This is important as bus-only center lanes with bus stop islands have been increasingly used to improve transit times. Hence the potential negative safety impacts of such systems need to be studied further and mitigated through improved design of pedestrian access to center bus stop islands. PMID:26994374

  16. Multi-spatial analysis of aeolian dune-field patterns

    NASA Astrophysics Data System (ADS)

    Ewing, Ryan C.; McDonald, George D.; Hayes, Alex G.

    2015-07-01

    Aeolian dune-fields are composed of different spatial scales of bedform patterns that respond to changes in environmental boundary conditions over a wide range of time scales. This study examines how variations in spatial scales of dune and ripple patterns found within dune fields are used in environmental reconstructions on Earth, Mars and Titan. Within a single bedform type, different spatial scales of bedforms emerge as a pattern evolves from an initial state into a well-organized pattern, such as with the transition from protodunes to dunes. Additionally, different types of bedforms, such as ripples, coarse-grained ripples and dunes, coexist at different spatial scales within a dune-field. Analysis of dune-field patterns at the intersection of different scales and types of bedforms at different stages of development provides a more comprehensive record of sediment supply and wind regime than analysis of a single scale and type of bedform. Interpretations of environmental conditions from any scale of bedform, however, are limited to environmental signals associated with the response time of that bedform. Large-scale dune-field patterns integrate signals over long-term climate cycles and reveal little about short-term variations in wind or sediment supply. Wind ripples respond instantly to changing conditions, but reveal little about longer-term variations in wind or sediment supply. Recognizing the response time scales across different spatial scales of bedforms maximizes environmental interpretations from dune-field patterns.

  17. Fiber-Based, Spatially and Temporally Shaped Picosecond UV Laser for Advanced RF Gun Applications

    SciTech Connect

    Shverdin, M Y; Anderson, S G; Betts, S M; Gibson, D J; Hartemann, F V; Hernandez, J E; Johnson, M; Jovanovic, I; Messerly, M; Pruet, J; Tremaine, A M; McNabb, D P; Siders, C W; Barty, C J

    2007-06-08

    The fiber-based, spatially and temporally shaped, picosecond UV laser system described here has been specifically designed for advanced rf gun applications, with a special emphasis on the production of high-brightness electron beams for free-electron lasers and Compton scattering light sources. The laser pulse can be shaped to a flat-top in both space and time with a duration of 10 ps at full width of half-maximum (FWHM) and rise and fall times under 1 ps. The expected pulse energy is 50 {micro}J at 261.75 nm and the spot size diameter of the beam at the photocathode is 2 mm. A fiber oscillator and amplifier system generates a chirped pump pulse at 1047 nm; stretching is achieved in a chirped fiber Bragg grating. A single multi-layer dielectric grating based compressor recompresses the input pulse to 250 fs FWHM and a two stage harmonic converter frequency quadruples the beam. Temporal shaping is achieved with a Michelson-based ultrafast pulse stacking device with nearly 100% throughput. Spatial shaping is achieved by truncating the beam at the 20% energy level with an iris and relay-imaging the resulting beam profile onto the photocathode. The integration of the system, as well as preliminary laser measurements will be presented.

  18. Spatial organization of cell-adhesive ligands for advanced cell culture

    PubMed Central

    Ekerdt, Barbara L; Segalman, Rachel A; Schaffer, David V

    2013-01-01

    Interaction between biomaterials and cells is a critical aspect for successful application of tissue engineering research. Technological advances within the past decade have enabled a number of studies to investigate how the spatial organization of cell-adhesive ligands impacts complex and rich cell behaviors ranging from adhesion to differentiation. Cells in their native environment are surrounded by chemical and physical factors spanning a range of length scales from nanometers to hundreds of microns. Furthermore, signals in the form of cell-adhesive ligands presented from this environment in different size scales and/or geometrical arrangements can change how a cell senses and responds to its surroundings. Biology can thus convey information not only in the concentration of a ligand but through its ability to change the spatial organization of these cues, raising questions both on the mechanisms by which it patterns such information and on the means by which a cell interprets it. This review discusses major findings associated with various systems developed to study cell-adhesive ligand presentation as well as an overview of the important material systems used in these studies. Promising material systems to further investigations in this field are also examined. Future directions will likely include determining how cells sense local and global ligand concentrations, understanding underlying mechanisms that regulate cell behaviors, and investigating the function of more complex cell types and diverse ligands. PMID:24318636

  19. Real-time 2D spatially selective MRI experiments: Comparative analysis of optimal control design methods

    NASA Astrophysics Data System (ADS)

    Maximov, Ivan I.; Vinding, Mads S.; Tse, Desmond H. Y.; Nielsen, Niels Chr.; Shah, N. Jon

    2015-05-01

    There is an increasing need for development of advanced radio-frequency (RF) pulse techniques in modern magnetic resonance imaging (MRI) systems driven by recent advancements in ultra-high magnetic field systems, new parallel transmit/receive coil designs, and accessible powerful computational facilities. 2D spatially selective RF pulses are an example of advanced pulses that have many applications of clinical relevance, e.g., reduced field of view imaging, and MR spectroscopy. The 2D spatially selective RF pulses are mostly generated and optimised with numerical methods that can handle vast controls and multiple constraints. With this study we aim at demonstrating that numerical, optimal control (OC) algorithms are efficient for the design of 2D spatially selective MRI experiments, when robustness towards e.g. field inhomogeneity is in focus. We have chosen three popular OC algorithms; two which are gradient-based, concurrent methods using first- and second-order derivatives, respectively; and a third that belongs to the sequential, monotonically convergent family. We used two experimental models: a water phantom, and an in vivo human head. Taking into consideration the challenging experimental setup, our analysis suggests the use of the sequential, monotonic approach and the second-order gradient-based approach as computational speed, experimental robustness, and image quality is key. All algorithms used in this work were implemented in the MATLAB environment and are freely available to the MRI community.

  20. Real-time 2D spatially selective MRI experiments: Comparative analysis of optimal control design methods.

    PubMed

    Maximov, Ivan I; Vinding, Mads S; Tse, Desmond H Y; Nielsen, Niels Chr; Shah, N Jon

    2015-05-01

    There is an increasing need for development of advanced radio-frequency (RF) pulse techniques in modern magnetic resonance imaging (MRI) systems driven by recent advancements in ultra-high magnetic field systems, new parallel transmit/receive coil designs, and accessible powerful computational facilities. 2D spatially selective RF pulses are an example of advanced pulses that have many applications of clinical relevance, e.g., reduced field of view imaging, and MR spectroscopy. The 2D spatially selective RF pulses are mostly generated and optimised with numerical methods that can handle vast controls and multiple constraints. With this study we aim at demonstrating that numerical, optimal control (OC) algorithms are efficient for the design of 2D spatially selective MRI experiments, when robustness towards e.g. field inhomogeneity is in focus. We have chosen three popular OC algorithms; two which are gradient-based, concurrent methods using first- and second-order derivatives, respectively; and a third that belongs to the sequential, monotonically convergent family. We used two experimental models: a water phantom, and an in vivo human head. Taking into consideration the challenging experimental setup, our analysis suggests the use of the sequential, monotonic approach and the second-order gradient-based approach as computational speed, experimental robustness, and image quality is key. All algorithms used in this work were implemented in the MATLAB environment and are freely available to the MRI community. PMID:25863895

  1. Hierarchical Spatial Analysis of Extreme Precipitation in Urban Areas

    NASA Astrophysics Data System (ADS)

    Rajulapati, C. R.; Mujumdar, P.

    2015-12-01

    Quantification of extreme precipitation is important for hydrologic designs. Due to lack of availability of extreme precipitation data for sufficiently large number of years, estimating the probability of extreme events is difficult and extrapolating the distributions to locations where observations are not available is challenging. In an urban setting, the spatial variation of precipitation can be high; the precipitation amounts and patterns often vary within short distances of less than 10 km. Therefore it is crucial to study the uncertainties in the spatial variation of precipitation in urban areas. In this work, the extreme precipitation is modeled spatially using the Bayesian hierarchical spatial analysis and the spatial variation of return levels is studied. The analysis is carried out with both the Peak over Threshold (PoT) and the Block Maxima approaches for defining the extreme precipitation. The study area is Bangalore city, India. Daily data for seventeen stations in and around Bangalore city are considered in the study. The threshold exceedences are modeled using a Generalized Pareto (GP) distribution and the block maxima are modeled using Generalized Extreme Value (GEV) distribution. In the hierarchical analysis, the statistical model is specified in three layers. The data layer models the data (either block maxima or the threshold exceedences) at each station. In the process layer, the latent spatial process characterized by geographical and climatological covariates (lat-lon, elevation, mean temperature etc.) which drives the extreme precipitation is modeled and in the prior level, the prior distributions that govern the latent process are modeled. Markov Chain Monte Carlo (MCMC) algorithm is used to obtain the samples of parameters from the posterior distribution of parameters. The spatial maps of return levels for specified return periods, along with the associated uncertainties, are obtained. The results show that there is significant variation in

  2. Incorporating spatial context into the analysis of salmonid habitat relations

    USGS Publications Warehouse

    Torgersen, Christian E.; Baxter, Colden V.; Ebersole, J.L.; Gresswell, Bob

    2012-01-01

    In this response to the chapter by Lapointe (this volume), we discuss the question of why it is so difficult to predict salmonid-habitat relations in gravel-bed rivers and streams. We acknowledge that this cannot be an exhaustive treatment of the subject and, thus, identify what we believe are several key issues that demonstrate the necessity of incorporating spatial context into the analysis of fish-habitat data. Our emphasis is on spatial context (i.e., scale and location), but it is important to note that the same principles may be applied with some modification to temporal context, which is beyond the scope of this chapter.

  3. Advanced Coal Wind Hybrid: Economic Analysis

    SciTech Connect

    Phadke, Amol; Goldman, Charles; Larson, Doug; Carr, Tom; Rath, Larry; Balash, Peter; Yih-Huei, Wan

    2008-11-28

    Growing concern over climate change is prompting new thinking about the technologies used to generate electricity. In the future, it is possible that new government policies on greenhouse gas emissions may favor electric generation technology options that release zero or low levels of carbon emissions. The Western U.S. has abundant wind and coal resources. In a world with carbon constraints, the future of coal for new electrical generation is likely to depend on the development and successful application of new clean coal technologies with near zero carbon emissions. This scoping study explores the economic and technical feasibility of combining wind farms with advanced coal generation facilities and operating them as a single generation complex in the Western US. The key questions examined are whether an advanced coal-wind hybrid (ACWH) facility provides sufficient advantages through improvements to the utilization of transmission lines and the capability to firm up variable wind generation for delivery to load centers to compete effectively with other supply-side alternatives in terms of project economics and emissions footprint. The study was conducted by an Analysis Team that consists of staff from the Lawrence Berkeley National Laboratory (LBNL), National Energy Technology Laboratory (NETL), National Renewable Energy Laboratory (NREL), and Western Interstate Energy Board (WIEB). We conducted a screening level analysis of the economic competitiveness and technical feasibility of ACWH generation options located in Wyoming that would supply electricity to load centers in California, Arizona or Nevada. Figure ES-1 is a simple stylized representation of the configuration of the ACWH options. The ACWH consists of a 3,000 MW coal gasification combined cycle power plant equipped with carbon capture and sequestration (G+CC+CCS plant), a fuel production or syngas storage facility, and a 1,500 MW wind plant. The ACWH project is connected to load centers by a 3,000 MW

  4. Multispectral laser imaging for advanced food analysis

    NASA Astrophysics Data System (ADS)

    Senni, L.; Burrascano, P.; Ricci, M.

    2016-07-01

    A hardware-software apparatus for food inspection capable of realizing multispectral NIR laser imaging at four different wavelengths is herein discussed. The system was designed to operate in a through-transmission configuration to detect the presence of unwanted foreign bodies inside samples, whether packed or unpacked. A modified Lock-In technique was employed to counterbalance the significant signal intensity attenuation due to transmission across the sample and to extract the multispectral information more efficiently. The NIR laser wavelengths used to acquire the multispectral images can be varied to deal with different materials and to focus on specific aspects. In the present work the wavelengths were selected after a preliminary analysis to enhance the image contrast between foreign bodies and food in the sample, thus identifying the location and nature of the defects. Experimental results obtained from several specimens, with and without packaging, are presented and the multispectral image processing as well as the achievable spatial resolution of the system are discussed.

  5. Spatial analysis of agro-ecological data: Detection of spatial patterns combining three different methodical approaches

    NASA Astrophysics Data System (ADS)

    Heuer, A.; Casper, M. C.; Vohland, M.

    2009-04-01

    Processes in natural systems and the resulting patterns occur in ecological space and time. To study natural structures and to understand the functional processes it is necessary to identify the relevant spatial and temporal space at which these all occur; or with other words to isolate spatial and temporal patterns. In this contribution we will concentrate on the spatial aspects of agro-ecological data analysis. Data were derived from two agricultural plots, each of about 5 hectares, in the area of Newel, located in Western Palatinate, Germany. The plots had been conventionally cultivated with a crop rotation of winter rape, winter wheat and spring barley. Data about physical and chemical soil properties, vegetation and topography were i) collected by measurements in the field during three vegetation periods (2005-2008) and/or ii) derived from hyperspectral image data, acquired by a HyMap airborne imaging sensor (2005). To detect spatial variability within the plots, we applied three different approaches that examine and describe relationships among data. First, we used variography to get an overview of the data. A comparison of the experimental variograms facilitated to distinguish variables, which seemed to occur in related or dissimilar spatial space. Second, based on data available in raster-format basic cell statistics were conducted, using a geographic information system. Here we could make advantage of the powerful classification and visualization tool, which supported the spatial distribution of patterns. Third, we used an approach that is being used for visualization of complex highly dimensional environmental data, the Kohonen self-organizing map. The self-organizing map (SOM) uses multidimensional data that gets further reduced in dimensionality (2-D) to detect similarities in data sets and correlation between single variables. One of SOM's advantages is its powerful visualization capability. The combination of the three approaches leads to

  6. Analysis of the Spatial Organization of Molecules with Robust Statistics

    PubMed Central

    Lagache, Thibault; Lang, Gabriel; Sauvonnet, Nathalie; Olivo-Marin, Jean-Christophe

    2013-01-01

    One major question in molecular biology is whether the spatial distribution of observed molecules is random or organized in clusters. Indeed, this analysis gives information about molecules’ interactions and physical interplay with their environment. The standard tool for analyzing molecules’ distribution statistically is the Ripley’s K function, which tests spatial randomness through the computation of its critical quantiles. However, quantiles’ computation is very cumbersome, hindering its use. Here, we present an analytical expression of these quantiles, leading to a fast and robust statistical test, and we derive the characteristic clusters’ size from the maxima of the Ripley’s K function. Subsequently, we analyze the spatial organization of endocytic spots at the cell membrane and we report that clathrin spots are randomly distributed while clathrin-independent spots are organized in clusters with a radius of , which suggests distinct physical mechanisms and cellular functions for each pathway. PMID:24349021

  7. Spatial filtering efficiency of monostatic biaxial lidar: analysis and applications.

    PubMed

    Agishev, Ravil R; Comeron, Adolfo

    2002-12-20

    Results of lidar modeling based on spatial-angular filtering efficiency criteria are presented. Their analysis shows that the low spatial-angular filtering efficiency of traditional visible and near-infrared systems is an important cause of low signal/background-radiation ratio (SBR) at the photodetector input The low SBR may be responsible for considerable measurement errors and ensuing the low accuracy of the retrieval of atmospheric optical parameters. As shown, the most effective protection against sky background radiation for groundbased biaxial lidars is the modifying of their angular field according to a spatial-angular filtering efficiency criterion. Some effective approaches to achieve a high filtering efficiency for the receiving system optimization are discussed. PMID:12510915

  8. [Ecological sensitivity of Shanghai City based on GIS spatial analysis].

    PubMed

    Cao, Jian-jun; Liu, Yong-juan

    2010-07-01

    In this paper, five sensitivity factors affecting the eco-environment of Shanghai City, i.e., rivers and lakes, historical relics and forest parks, geological disasters, soil pollution, and land use, were selected, and their weights were determined by analytic hierarchy process. Combining with GIS spatial analysis technique, the sensitivities of these factors were classified into four grades, i.e., highly sensitive, moderately sensitive, low sensitive, and insensitive, and the spatial distribution of the ecological sensitivity of Shanghai City was figured out. There existed a significant spatial differentiation in the ecological sensitivity of the City, and the insensitive, low sensitive, moderately sensitive, and highly sensitive areas occupied 37.07%, 5.94%, 38.16%, and 18.83%, respectively. Some suggestions on the City's zoning protection and construction were proposed. This study could provide scientific references for the City's environmental protection and economic development. PMID:20879541

  9. GIS application on spatial landslide analysis using statistical based models

    NASA Astrophysics Data System (ADS)

    Pradhan, Biswajeet; Lee, Saro; Buchroithner, Manfred F.

    2009-09-01

    This paper presents the assessment results of spatially based probabilistic three models using Geoinformation Techniques (GIT) for landslide susceptibility analysis at Penang Island in Malaysia. Landslide locations within the study areas were identified by interpreting aerial photographs, satellite images and supported with field surveys. Maps of the topography, soil type, lineaments and land cover were constructed from the spatial data sets. There are ten landslide related factors were extracted from the spatial database and the frequency ratio, fuzzy logic, and bivariate logistic regression coefficients of each factor was computed. Finally, landslide susceptibility maps were drawn for study area using frequency ratios, fuzzy logic and bivariate logistic regression models. For verification, the results of the analyses were compared with actual landslide locations in study area. The verification results show that bivariate logistic regression model provides slightly higher prediction accuracy than the frequency ratio and fuzzy logic models.

  10. Near ground level sensing for spatial analysis of vegetation

    NASA Technical Reports Server (NTRS)

    Sauer, Tom; Rasure, John; Gage, Charlie

    1991-01-01

    Measured changes in vegetation indicate the dynamics of ecological processes and can identify the impacts from disturbances. Traditional methods of vegetation analysis tend to be slow because they are labor intensive; as a result, these methods are often confined to small local area measurements. Scientists need new algorithms and instruments that will allow them to efficiently study environmental dynamics across a range of different spatial scales. A new methodology that addresses this problem is presented. This methodology includes the acquisition, processing, and presentation of near ground level image data and its corresponding spatial characteristics. The systematic approach taken encompasses a feature extraction process, a supervised and unsupervised classification process, and a region labeling process yielding spatial information.

  11. Analysis and System Design Framework for Infrared Spatial Heterodyne Spectrometers

    SciTech Connect

    Cooke, B.J.; Smith, B.W.; Laubscher, B.E.; Villeneuve, P.V.; Briles, S.D.

    1999-04-05

    The authors present a preliminary analysis and design framework developed for the evaluation and optimization of infrared, Imaging Spatial Heterodyne Spectrometer (SHS) electro-optic systems. Commensurate with conventional interferometric spectrometers, SHS modeling requires an integrated analysis environment for rigorous evaluation of system error propagation due to detection process, detection noise, system motion, retrieval algorithm and calibration algorithm. The analysis tools provide for optimization of critical system parameters and components including : (1) optical aperture, f-number, and spectral transmission, (2) SHS interferometer grating and Littrow parameters, and (3) image plane requirements as well as cold shield, optical filtering, and focal-plane dimensions, pixel dimensions and quantum efficiency, (4) SHS spatial and temporal sampling parameters, and (5) retrieval and calibration algorithm issues.

  12. A Foundation for Reliable Spatial Proteomics Data Analysis*

    PubMed Central

    Gatto, Laurent; Breckels, Lisa M.; Burger, Thomas; Nightingale, Daniel J. H.; Groen, Arnoud J.; Campbell, Callum; Nikolovski, Nino; Mulvey, Claire M.; Christoforou, Andy; Ferro, Myriam; Lilley, Kathryn S.

    2014-01-01

    Quantitative mass-spectrometry-based spatial proteomics involves elaborate, expensive, and time-consuming experimental procedures, and considerable effort is invested in the generation of such data. Multiple research groups have described a variety of approaches for establishing high-quality proteome-wide datasets. However, data analysis is as critical as data production for reliable and insightful biological interpretation, and no consistent and robust solutions have been offered to the community so far. Here, we introduce the requirements for rigorous spatial proteomics data analysis, as well as the statistical machine learning methodologies needed to address them, including supervised and semi-supervised machine learning, clustering, and novelty detection. We present freely available software solutions that implement innovative state-of-the-art analysis pipelines and illustrate the use of these tools through several case studies involving multiple organisms, experimental designs, mass spectrometry platforms, and quantitation techniques. We also propose sound analysis strategies for identifying dynamic changes in subcellular localization by comparing and contrasting data describing different biological conditions. We conclude by discussing future needs and developments in spatial proteomics data analysis. PMID:24846987

  13. Socio-Spatial Intelligence: social media and spatial cognition for territorial behavioral analysis.

    PubMed

    Luini, Lorenzo P; Cardellicchio, Davide; Felletti, Fulvia; Marucci, Francesco S

    2015-09-01

    Investigative analysts gather data from different sources, especially from social media (SM), in order to shed light on cognitive factors that may explain criminal spatial behavior. A former research shows how tweets can be used to estimate private points of interest. Authors' aim was to demonstrate, as they extend the analysis to a wider statistical base, how social maps and Web applications could be used in investigative analysis and spatial cognition research. A total of 100 Twitter accounts with approximately 250 tweets each were submitted to common geographical techniques (measures such as Convex-Hull, Mean-Center, Median-Center, Standard-Deviation-Ellipse) in order to test the hypothesis that user areas of activity are predictable. Predictions were tested through a set of specific information: clear reference to areas of activity and clear reference about user's residence. Simple algorithms and procedures demonstrated that they could be used to predict where SM users live, giving positive results in about 4/5 cases and giving indications about their home location. In fact, all home positions were found in the Convex-Hull and most of them in the Standard-Deviation-Ellipse. Furthermore, in up to 80% of cases, houses were found within a buffer zone of 1.500 m with Median-Center as centrum (70% using Median-Center as centrum) with a minimum effectiveness threshold of 12-13 tweets. SM may help in studying people mobility and their cognition of space and, moreover, where they live, or their traveling behavior. The processing of geographical data in conjunction with the SM analysis may facilitate the construction of models describing specific behavior of people. The use of geographical information system tools and SM analysis represents an effective approach in order to acquire spatial and territorial information, referred to social relationship. The results may be used successfully in the understanding of social dynamics and for the prevention of criminal behavior

  14. Parametric cost analysis for advanced energy concepts

    SciTech Connect

    Not Available

    1983-10-01

    This report presents results of an exploratory study to develop parametric cost estimating relationships for advanced fossil-fuel energy systems. The first of two tasks was to develop a standard Cost Chart of Accounts to serve as a basic organizing framework for energy systems cost analysis. The second task included development of selected parametric cost estimating relationships (CERs) for individual elements (or subsystems) of a fossil fuel plant, nominally for the Solvent-Refined Coal (SRC) process. Parametric CERs are presented for the following elements: coal preparation, coal slurry preparation, dissolver (reactor); gasification; oxygen production; acid gas/CO/sub 2/ removal; shift conversion; cryogenic hydrogen recovery; and sulfur removal. While the nominal focus of the study was on the SRC process, each of these elements is found in other fossil fuel processes. Thus, the results of this effort have broader potential application. However, it should also be noted that the CERs presented in this report are based upon a limited data base. Thus, they are applicable over a limited range of values (of the independent variables) and for a limited set of specific technologies (e.g., the gasifier CER is for the multi-train, Koppers-Totzek process). Additional work is required to extend the range of these CERs. 16 figures, 13 tables.

  15. Spatial Analysis of Eco-environmental Risk Factors of Cutaneous Leishmaniasis in Southern Iran

    PubMed Central

    Ali-Akbarpour, Mohsen; Mohammadbeigi, Abolfazl; Tabatabaee, Seyed Hamid Reza; Hatam, Gholamreza

    2012-01-01

    Background: Despite the advances in the diagnosis and treatment of leishmaniasis, it is still considered as a severe public health problem particularly in developing countries and a great economic burden on the health resources. The present study was designed and conducted to determine the eco-environmental characteristics of the leishmaniasis disease by spatial analysis. Materials and Methods: In an ecological study, data were collected on eco-environmental factors of Fars province in Iran and on cutaneous leishmaniasis (CL) cases from 2002 to 2009. geographic weighted regression (GWR) was used to analyse the data and compare them with ordinary least square (OLS) regression model results. Moran's Index was applied for analysis of spatial autocorrelation in residual of OLS. P value less than 0.05 was considered as significant and adjusted R2 was used for model preferences. Results: There was a significant spatial autocorrelation in the residuals of OLS model (Z=2.45, P=0.014). GWR showed that rainy days, minimum temperature, wind velocity, maximum relative humidity and population density were the most important eco-environmental risk factors and explained 0.388 of the associated factors of CL. Conclusion: Spatial analysis can be a good tool for detection and prediction of CL disease. In autocorrelated and non-stationary data, GWR model yields a better fitness than OLS regression model. Also, population density can be used as a surrogate variable of acquired immunity and increase the adjusted R2. PMID:22557853

  16. Fourier mode analysis of source iteration in spatially periodic media

    SciTech Connect

    Zika, M.R.; Larsen, E.W.

    1998-12-31

    The standard Fourier mode analysis is an indispensable tool when designing acceleration techniques for transport iterations; however, it requires the assumption of a homogeneous infinite medium. For problems of practical interest, material heterogeneities may significantly impact iterative performance. Recent work has applied a Fourier analysis to the discretized two-dimensional transport operator with heterogeneous material properties. The results of these analyses may be difficult to interpret because the heterogeneity effects are inherently coupled to the discretization effects. Here, the authors describe a Fourier analysis of source iteration (SI) that allows the calculation of the eigenvalue spectrum for the one-dimensional continuous transport operator with spatially periodic heterogeneous media.

  17. Directional spatial frequency analysis of lipid distribution in atherosclerotic plaque

    NASA Astrophysics Data System (ADS)

    Korn, Clyde; Reese, Eric; Shi, Lingyan; Alfano, Robert; Russell, Stewart

    2016-04-01

    Atherosclerosis is characterized by the growth of fibrous plaques due to the retention of cholesterol and lipids within the artery wall, which can lead to vessel occlusion and cardiac events. One way to evaluate arterial disease is to quantify the amount of lipid present in these plaques, since a higher disease burden is characterized by a higher concentration of lipid. Although therapeutic stimulation of reverse cholesterol transport to reduce cholesterol deposits in plaque has not produced significant results, this may be due to current image analysis methods which use averaging techniques to calculate the total amount of lipid in the plaque without regard to spatial distribution, thereby discarding information that may have significance in marking response to therapy. Here we use Directional Fourier Spatial Frequency (DFSF) analysis to generate a characteristic spatial frequency spectrum for atherosclerotic plaques from C57 Black 6 mice both treated and untreated with a cholesterol scavenging nanoparticle. We then use the Cauchy product of these spectra to classify the images with a support vector machine (SVM). Our results indicate that treated plaque can be distinguished from untreated plaque using this method, where no difference is seen using the spatial averaging method. This work has the potential to increase the effectiveness of current in-vivo methods of plaque detection that also use averaging methods, such as laser speckle imaging and Raman spectroscopy.

  18. Spatial Fourier analysis of video photobleaching measurements. Principles and optimization.

    PubMed

    Tsay, T T; Jacobson, K A

    1991-08-01

    The major use of the fluorescence recovery after photobleaching (FRAP) technique is to measure the translational motion of the molecular components in various condensed media. In a conventional laser spot photobleaching experiment, a photomultiplier is used to measure the total brightness levels of the bleached region in the sample, so no spatial information can be directly obtained. In video-FRAP, a series of images after photobleaching is acquired, allowing the spatial character of the recovery to be determined; this permits direct detection of both anisotropic diffusion and flow. To utilize all of the available image data to determine the transport coefficients, a two-dimensional spatial Fourier transform analysis of the images after photobleaching was employed. The change in the transform between two time points reflects the action of diffusion during the interim. An important advantage of this method, which involves taking the ratio of image transforms at different time points, is that it does not require a specific initial condition to be created by laser photobleaching. The ability of the analysis to extract transport coefficients from computer-simulated diffusional recovery is assessed in the presence of increasing amounts of noise. Experimental data analysis from the diffusion of proteins in viscous solutions and from the diffusion of protein receptors on cell surfaces demonstrate the feasibility of the Fourier analysis to obtain transport coefficients from the video FRAP measurement. PMID:1912279

  19. Advanced Materials and Solids Analysis Research Core (AMSARC)

    EPA Science Inventory

    The Advanced Materials and Solids Analysis Research Core (AMSARC), centered at the U.S. Environmental Protection Agency's (EPA) Andrew W. Breidenbach Environmental Research Center in Cincinnati, Ohio, is the foundation for the Agency's solids and surfaces analysis capabilities. ...

  20. Recent advances in the determination of a high spatial resolution geopotential model using chronometric geodesy

    NASA Astrophysics Data System (ADS)

    Lion, Guillaume; Guerlin, Christine; Bize, Sébastien; Wolf, Peter; Delva, Pacôme; Panet, Isabelle

    2016-04-01

    Current methods to determine the geopotential are mainly based on indirect approaches using gravimetric, gradiometric and topographic data. Satellite missions (GRACE, GOCE) have contributed significantly to improve the knowledge of the Earth's gravity field with a spatial resolution of about 90 km, but it is not enough to access, for example, to the geoid variation in hilly regions. While airborne and ground-based gravimeters provide the high resolution, the problem of these technics is that the accuracy is hampered by the heterogeneous coverage of gravity data (ground and offshore). Recent technological advances in atomic clocks are opening new perspectives in the determination of the geopotential. To date, the best of them reach a stability of 1.6×10‑18 (NIST, RIKEN + Univ. Tokyo) in just 7 hours of integration, an accuracy of 2.0×10‑18 (JILA). Using the relation of the relativistic gravitational redshift, this corresponds to a determination of geopotential differences at the 0.1 m²/s² level (or 1 cm in geoid height). In this context, the present work aims at evaluating the contribution of optical atomic clocks for the determination of the geopotential at high spatial resolution. To do that, we have studied a test area surrounding the Massif Central in the middle of southern of France. This region, consists in low mountain ranges and plateaus, is interesting because, the gravitational field strength varies greatly from place to place at high resolution due to the relief. Here, we present the synthetic tests methodology: generation of synthetic gravity and potential data, then estimation of the potential from these data using the least-squares collocation and assessment of the clocks contribution. We shall see how the coverage of the data points (realistic or not) can affect the results, and discuss how to quantify the trade-off between the noise level and the number of data points used.

  1. Preliminary frequency-domain analysis for the reconstructed spatial resolution of muon tomography

    NASA Astrophysics Data System (ADS)

    Yu, B.; Zhao, Z.; Wang, X.; Wang, Y.; Wu, D.; Zeng, Z.; Zeng, M.; Yi, H.; Luo, Z.; Yue, X.; Cheng, J.

    2014-11-01

    Muon tomography is an advanced technology to non-destructively detect high atomic number materials. It exploits the multiple Coulomb scattering information of muon to reconstruct the scattering density image of the traversed object. Because of the statistics of muon scattering, the measurement error of system and the data incompleteness, the reconstruction is always accompanied with a certain level of interference, which will influence the reconstructed spatial resolution. While statistical noises can be reduced by extending the measuring time, system parameters determine the ultimate spatial resolution that one system can reach. In this paper, an effective frequency-domain model is proposed to analyze the reconstructed spatial resolution of muon tomography. The proposed method modifies the resolution analysis in conventional computed tomography (CT) to fit the different imaging mechanism in muon scattering tomography. The measured scattering information is described in frequency domain, then a relationship between the measurements and the original image is proposed in Fourier domain, which is named as "Muon Central Slice Theorem". Furthermore, a preliminary analytical expression of the ultimate reconstructed spatial is derived, and the simulations are performed for validation. While the method is able to predict the ultimate spatial resolution of a given system, it can also be utilized for the optimization of system design and construction.

  2. High dimensional data analysis using multivariate generalized spatial quantiles

    PubMed Central

    Mukhopadhyay, Nitai D.; Chatterjee, Snigdhansu

    2015-01-01

    High dimensional data routinely arises in image analysis, genetic experiments, network analysis, and various other research areas. Many such datasets do not correspond to well-studied probability distributions, and in several applications the data-cloud prominently displays non-symmetric and non-convex shape features. We propose using spatial quantiles and their generalizations, in particular, the projection quantile, for describing, analyzing and conducting inference with multivariate data. Minimal assumptions are made about the nature and shape characteristics of the underlying probability distribution, and we do not require the sample size to be as high as the data-dimension. We present theoretical properties of the generalized spatial quantiles, and an algorithm to compute them quickly. Our quantiles may be used to obtain multidimensional confidence or credible regions that are not required to conform to a pre-determined shape. We also propose a new notion of multidimensional order statistics, which may be used to obtain multidimensional outliers. Many of the features revealed using a generalized spatial quantile-based analysis would be missed if the data was shoehorned into a well-known probabilistic configuration. PMID:26617421

  3. Methods for spectral image analysis by exploiting spatial simplicity

    DOEpatents

    Keenan, Michael R.

    2010-05-25

    Several full-spectrum imaging techniques have been introduced in recent years that promise to provide rapid and comprehensive chemical characterization of complex samples. One of the remaining obstacles to adopting these techniques for routine use is the difficulty of reducing the vast quantities of raw spectral data to meaningful chemical information. Multivariate factor analysis techniques, such as Principal Component Analysis and Alternating Least Squares-based Multivariate Curve Resolution, have proven effective for extracting the essential chemical information from high dimensional spectral image data sets into a limited number of components that describe the spectral characteristics and spatial distributions of the chemical species comprising the sample. There are many cases, however, in which those constraints are not effective and where alternative approaches may provide new analytical insights. For many cases of practical importance, imaged samples are "simple" in the sense that they consist of relatively discrete chemical phases. That is, at any given location, only one or a few of the chemical species comprising the entire sample have non-zero concentrations. The methods of spectral image analysis of the present invention exploit this simplicity in the spatial domain to make the resulting factor models more realistic. Therefore, more physically accurate and interpretable spectral and abundance components can be extracted from spectral images that have spatially simple structure.

  4. Methods for spectral image analysis by exploiting spatial simplicity

    DOEpatents

    Keenan, Michael R.

    2010-11-23

    Several full-spectrum imaging techniques have been introduced in recent years that promise to provide rapid and comprehensive chemical characterization of complex samples. One of the remaining obstacles to adopting these techniques for routine use is the difficulty of reducing the vast quantities of raw spectral data to meaningful chemical information. Multivariate factor analysis techniques, such as Principal Component Analysis and Alternating Least Squares-based Multivariate Curve Resolution, have proven effective for extracting the essential chemical information from high dimensional spectral image data sets into a limited number of components that describe the spectral characteristics and spatial distributions of the chemical species comprising the sample. There are many cases, however, in which those constraints are not effective and where alternative approaches may provide new analytical insights. For many cases of practical importance, imaged samples are "simple" in the sense that they consist of relatively discrete chemical phases. That is, at any given location, only one or a few of the chemical species comprising the entire sample have non-zero concentrations. The methods of spectral image analysis of the present invention exploit this simplicity in the spatial domain to make the resulting factor models more realistic. Therefore, more physically accurate and interpretable spectral and abundance components can be extracted from spectral images that have spatially simple structure.

  5. Gis-Based Spatial Statistical Analysis of College Graduates Employment

    NASA Astrophysics Data System (ADS)

    Tang, R.

    2012-07-01

    It is urgently necessary to be aware of the distribution and employment status of college graduates for proper allocation of human resources and overall arrangement of strategic industry. This study provides empirical evidence regarding the use of geocoding and spatial analysis in distribution and employment status of college graduates based on the data from 2004-2008 Wuhan Municipal Human Resources and Social Security Bureau, China. Spatio-temporal distribution of employment unit were analyzed with geocoding using ArcGIS software, and the stepwise multiple linear regression method via SPSS software was used to predict the employment and to identify spatially associated enterprise and professionals demand in the future. The results show that the enterprises in Wuhan east lake high and new technology development zone increased dramatically from 2004 to 2008, and tended to distributed southeastward. Furthermore, the models built by statistical analysis suggest that the specialty of graduates major in has an important impact on the number of the employment and the number of graduates engaging in pillar industries. In conclusion, the combination of GIS and statistical analysis which helps to simulate the spatial distribution of the employment status is a potential tool for human resource development research.

  6. Mass Spectrometry Based Imaging Techniques for Spatially Resolved Analysis of Molecules

    PubMed Central

    Matros, Andrea; Mock, Hans-Peter

    2013-01-01

    Higher plants are composed of a multitude of tissues with specific functions, reflected by distinct profiles for transcripts, proteins, and metabolites. Comprehensive analysis of metabolites and proteins has advanced tremendously within recent years, and this progress has been driven by the rapid development of sophisticated mass spectrometric techniques. In most of the current “omics”-studies, analysis is performed on whole organ or whole plant extracts, rendering to the loss of spatial information. Mass spectrometry imaging (MSI) techniques have opened a new avenue to obtain information on the spatial distribution of metabolites and of proteins. Pioneered in the field of medicine, the approaches are now applied to study the spatial profiles of molecules in plant systems. A range of different plant organs and tissues have been successfully analyzed by MSI, and patterns of various classes of metabolites from primary and secondary metabolism could be obtained. It can be envisaged that MSI approaches will substantially contribute to build spatially resolved biochemical networks. PMID:23626593

  7. Multi-resolution analysis of high density spatial and temporal cloud inhomogeneity fields from HOPE campaign

    NASA Astrophysics Data System (ADS)

    Lakshmi Madhavan, Bomidi; Deneke, Hartwig; Macke, Andreas

    2015-04-01

    Clouds are the most complex structures in both spatial and temporal scales of the Earth's atmosphere that effect the downward surface reaching fluxes and thus contribute to large uncertainty in the global radiation budget. Within the framework of High Definition Clouds and Precipitation for advancing Climate Prediction (HD(CP)2) Observational Prototype Experiment (HOPE), a high density network of 99 pyranometer stations was set up around Jülich, Germany (~ 10 × 12 km2 area) during April to July 2013 to capture the small-scale variability in cloud induced radiation fields at the surface. In this study, we perform multi-resolution analysis of the downward solar irradiance variability at the surface from the pyranometer network to investigate the dependence of temporal and spatial averaging scales on the variance and spatial correlation for different cloud regimes. Preliminary results indicate that correlation is strongly scale-dependent where as the variance is dependent on the length of averaging period. Implications of our findings will be useful for quantifying the effect of spatial collocation while validating the satellite inferred solar irradiance estimates, and also to explore the link between cloud structure and radiation. We will present the details of our analysis and results.

  8. Spatial analysis of ozone in Atlanta: Regulatory and epidemiologic implications

    SciTech Connect

    Butler, A.J.; Mulholland, J.A.; Wilkinson, J.G.; Russell, A.G.; Tolbert, P.E.

    1998-12-31

    Relationships between ambient levels of selected air pollutants and pediatric asthma exacerbation in Atlanta were studied retrospectively. As a part of this study, spatial distributions of ambient ozone concentrations in the twenty-county Atlanta metropolitan area during the summers of 1993, 1994 and 1995 were estimated and assessed. A universal kriging procedure was used for spatial interpolation of aerometric monitoring station data. In this paper, the spatial distributions of ozone are described, and regulatory and epidemiologic implications are discussed. For the study period, the Atlanta ozone nonattainment area based on the one-hour, exceedance-based standard of 0.12 ppm is estimated to expand from 56 percent of the Atlanta MSA by area and 71 percent by population to 88 percent by area and 96 percent by population under the new eight-hour, concentration-based standard of 0.08 ppm. Regarding asthma exacerbation, a 4 percent increase in pediatric asthma emergency room presentation rate per 20 ppb increase in ambient ozone concentration was observed (p-value = 0.001). Ambient ozone level represents a general indicator of air quality due to its correlation with other pollutants. The use of spatially-resolved ozone estimates in the epidemiologic analysis demonstrates the need to control confounding by demographic covariates.

  9. Advanced BMP Gene Therapies for Temporal and Spatial Control of Bone Regeneration

    PubMed Central

    Wilson, C.G.; Martín-Saavedra, F.M.; Vilaboa, N.; Franceschi, R.T.

    2013-01-01

    Spatial and temporal patterns of bone morphogenetic protein (BMP) signaling are crucial to the assembly of appropriately positioned and shaped bones of the face and head. This review advances the hypothesis that reconstitution of such patterns with cutting-edge gene therapies will transform the clinical management of craniofacial bone defects attributed to trauma, disease, or surgical resection. Gradients in BMP signaling within developing limbs and orofacial primordia regulate proliferation and differentiation of mesenchymal progenitors. Similarly, vascular and mesenchymal cells express BMPs in various places and at various times during normal fracture healing. In non-healing fractures of long bones, BMP signaling is severely attenuated. Devices that release recombinant BMPs promote healing of bone in spinal fusions and, in some cases, of open fractures, but cannot control the timing and localization of BMP release. Gene therapies with regulated expression systems may provide substantial improvements in efficacy and safety compared with protein-based therapies. Synthetic gene switches, activated by pharmacologics or light or hyperthermic stimuli, provide several avenues for the non-invasive regulation of the expression of BMP transgenes in both time and space. Through new gene therapy platforms such as these, active control over BMP signaling can be achieved to accelerate bone regeneration. PMID:23539558

  10. Spatial epidemiological techniques in cholera mapping and analysis towards a local scale predictive modelling

    NASA Astrophysics Data System (ADS)

    Rasam, A. R. A.; Ghazali, R.; Noor, A. M. M.; Mohd, W. M. N. W.; Hamid, J. R. A.; Bazlan, M. J.; Ahmad, N.

    2014-02-01

    Cholera spatial epidemiology is the study of the spread and control of the disease spatial pattern and epidemics. Previous studies have shown that multi-factorial causation such as human behaviour, ecology and other infectious risk factors influence the disease outbreaks. Thus, understanding spatial pattern and possible interrelationship factors of the outbreaks are crucial to be explored an in-depth study. This study focuses on the integration of geographical information system (GIS) and epidemiological techniques in exploratory analyzing the cholera spatial pattern and distribution in the selected district of Sabah. Spatial Statistic and Pattern tools in ArcGIS and Microsoft Excel software were utilized to map and analyze the reported cholera cases and other data used. Meanwhile, cohort study in epidemiological technique was applied to investigate multiple outcomes of the disease exposure. The general spatial pattern of cholera was highly clustered showed the disease spread easily at a place or person to others especially 1500 meters from the infected person and locations. Although the cholera outbreaks in the districts are not critical, it could be endemic at the crowded areas, unhygienic environment, and close to contaminated water. It was also strongly believed that the coastal water of the study areas has possible relationship with the cholera transmission and phytoplankton bloom since the areas recorded higher cases. GIS demonstrates a vital spatial epidemiological technique in determining the distribution pattern and elucidating the hypotheses generating of the disease. The next research would be applying some advanced geo-analysis methods and other disease risk factors for producing a significant a local scale predictive risk model of the disease in Malaysia.

  11. Spatial analysis of antibiotic resistance along metal contaminated streams.

    PubMed

    Tuckfield, R Cary; McArthur, J Vaun

    2008-05-01

    The spatial pattern of antibiotic resistance in culturable sediment bacteria from four freshwater streams was examined. Previous research suggests that the prevalence of antibiotic resistance may increase in populations via indirect or coselection from heavy metal contamination. Sample bacteria from each stream were grown in media containing one of four antibiotics-tetracycline, chloramphenicol, kanamycin, and streptomycin-at concentrations greater than the minimum inhibitory concentration, plus a control. Bacteria showed high susceptibilities to the former two antibiotics. We summarized the latter two more prevalent (aminoglycoside) resistance responses and ten metals concentrations per sediment sample, by Principal Components Analysis. Respectively, 63 and 58% of the variability was explained in the first principal component of each variable set. We used these multivariate summary metrics [i.e., first principal component (PC) scores] as input measures for exploring the spatial correlation between antibiotic resistance and metal concentration for each stream sampled. Results show a significant and negative correlation between metals PC scores versus aminoglycoside resistance scores and suggest that selection for metal tolerance among sediment bacteria may influence selection for antibiotic resistance differently in sediments than in the water column. Our most important finding comes from geostatistical cross-variogram analysis, which shows that increasing metal concentration scores are spatially associated with decreasing aminoglycoside resistance scores--a negative correlation, but holds for contaminated streams only. We suspect our field results are influenced by metal bioavailability in the sediments and by a contaminant promoted interaction or "cocktail effect" from complex combinations of pollution mediated selection agents. PMID:17899247

  12. Event Detection and Spatial Analysis for Characterizing Extreme Precipitation

    NASA Astrophysics Data System (ADS)

    Jeon, S.; Prabhat, M.; Byna, S.; Collins, W.; Wehner, M. F.

    2013-12-01

    Atmospheric Rivers (ARs) are large spatially coherent weather systems with high concentrations of elevated water vapor that often cause severe downpours and flooding over western coastal United States. With the availability of more atmospheric moisture in the future under global warming, we expect ARs to play an important role as a potential cause of extreme precipitation. We have recently developed TECA software for automatically identifying and tracking features in climate datasets. In particular, we are able to identify ARs that make landfall on the western coast of North America. This detection tool examines integrated water vapor field above a certain threshold and performs geometric analysis. Based on the detection procedure, we investigate impacts of ARs by exploring spatial extent of AR precipitation for CMIP5 simulations, and characterize spatial pattern of dependence for future projections under climate change within the framework of extreme value theory. The results show that AR events in RCP8.5 scenario (2076-2100) tend to produce heavier rainfall with higher frequency and longer duration than the events from historical run (1981-2005). Range of spatial dependence between extreme precipitations is concentrated on smaller localized area in California under the highest emission scenario than present day. Preliminary results are illustrated in Figure 1 and 2. Fig 1: Boxplot of annual max precipitation (left two) and max AR precipitation (right two) from GFDL-ESM2M during 25-year time period by station in California, US. Fig 2: Spatial dependence of max AR precipitation calculated from Station 4 (triangle) for historical run (left) and for future projections of RCP8.5 (right) from GFDL-ESM2M. Green and orange colors represent complete dependence and independence between two stations respectively.

  13. Fractal analysis of multiscale spatial autocorrelation among point data

    USGS Publications Warehouse

    De Cola, L.

    1991-01-01

    The analysis of spatial autocorrelation among point-data quadrats is a well-developed technique that has made limited but intriguing use of the multiscale aspects of pattern. In this paper are presented theoretical and algorithmic approaches to the analysis of aggregations of quadrats at or above a given density, in which these sets are treated as multifractal regions whose fractal dimension, D, may vary with phenomenon intensity, scale, and location. The technique is illustrated with Matui's quadrat house-count data, which yield measurements consistent with a nonautocorrelated simulated Poisson process but not with an orthogonal unit-step random walk. The paper concludes with a discussion of the implications of such analysis for multiscale geographic analysis systems. -Author

  14. Spatial Durbin model analysis macroeconomic loss due to natural disasters

    NASA Astrophysics Data System (ADS)

    Kusrini, D. E.; Mukhtasor

    2015-03-01

    Magnitude of the damage and losses caused by natural disasters is huge for Indonesia, therefore this study aimed to analyze the effects of natural disasters for macroeconomic losses that occurred in 115 cities/districts across Java during 2012. Based on the results of previous studies it is suspected that it contains effects of spatial dependencies in this case, so that the completion of this case is performed using a regression approach to the area, namely Analysis of Spatial Durbin Model (SDM). The obtained significant predictor variable is population, and predictor variable with a significant weighting is the number of occurrences of disasters, i.e., disasters in the region which have an impact on other neighboring regions. Moran's I index value using the weighted Queen Contiguity also showed significant results, meaning that the incidence of disasters in the region will decrease the value of GDP in other.

  15. ESTATE: Strategy for Exploring Labeled Spatial Datasets Using Association Analysis

    NASA Astrophysics Data System (ADS)

    Stepinski, Tomasz F.; Salazar, Josue; Ding, Wei; White, Denis

    We propose an association analysis-based strategy for exploration of multi-attribute spatial datasets possessing naturally arising classification. Proposed strategy, ESTATE (Exploring Spatial daTa Association patTErns), inverts such classification by interpreting different classes found in the dataset in terms of sets of discriminative patterns of its attributes. It consists of several core steps including discriminative data mining, similarity between transactional patterns, and visualization. An algorithm for calculating similarity measure between patterns is the major original contribution that facilitates summarization of discovered information and makes the entire framework practical for real life applications. Detailed description of the ESTATE framework is followed by its application to the domain of ecology using a dataset that fuses the information on geographical distribution of biodiversity of bird species across the contiguous United States with distributions of 32 environmental variables across the same area.

  16. An integrated spatial signature analysis and automatic defect classification system

    SciTech Connect

    Gleason, S.S.; Tobin, K.W.; Karnowski, T.P.

    1997-08-01

    An integrated Spatial Signature Analysis (SSA) and automatic defect classification (ADC) system for improved automatic semiconductor wafer manufacturing characterization is presented. Both concepts of SSA and ADC methodologies are reviewed and then the benefits of an integrated system are described, namely, focused ADC and signature-level sampling. Focused ADC involves the use of SSA information on a defect signature to reduce the number of possible classes that an ADC system must consider, thus improving the ADC system performance. Signature-level sampling improved the ADC system throughput and accuracy by intelligently sampling defects within a given spatial signature for subsequent off-line, high-resolution ADC. A complete example of wafermap characterization via an integrated SSA/ADC system is presented where a wafer with 3274 defects is completely characterized by revisiting only 25 defects on an off-line ADC review station. 13 refs., 7 figs.

  17. Unique Systems Analysis Task 7, Advanced Subsonic Technologies Evaluation Analysis

    NASA Technical Reports Server (NTRS)

    Eisenberg, Joseph D. (Technical Monitor); Bettner, J. L.; Stratton, S.

    2004-01-01

    To retain a preeminent U.S. position in the aircraft industry, aircraft passenger mile costs must be reduced while at the same time, meeting anticipated more stringent environmental regulations. A significant portion of these improvements will come from the propulsion system. A technology evaluation and system analysis was accomplished under this task, including areas such as aerodynamics and materials and improved methods for obtaining low noise and emissions. Previous subsonic evaluation analyses have identified key technologies in selected components for propulsion systems for year 2015 and beyond. Based on the current economic and competitive environment, it is clear that studies with nearer turn focus that have a direct impact on the propulsion industry s next generation product are required. This study will emphasize the year 2005 entry into service time period. The objective of this study was to determine which technologies and materials offer the greatest opportunities for improving propulsion systems. The goals are twofold. The first goal is to determine an acceptable compromise between the thermodynamic operating conditions for A) best performance, and B) acceptable noise and chemical emissions. The second goal is the evaluation of performance, weight and cost of advanced materials and concepts on the direct operating cost of an advanced regional transport of comparable technology level.

  18. An information theory analysis of spatial decisions in cognitive development

    PubMed Central

    Scott, Nicole M.; Sera, Maria D.; Georgopoulos, Apostolos P.

    2015-01-01

    Performance in a cognitive task can be considered as the outcome of a decision-making process operating across various knowledge domains or aspects of a single domain. Therefore, an analysis of these decisions in various tasks can shed light on the interplay and integration of these domains (or elements within a single domain) as they are associated with specific task characteristics. In this study, we applied an information theoretic approach to assess quantitatively the gain of knowledge across various elements of the cognitive domain of spatial, relational knowledge, as a function of development. Specifically, we examined changing spatial relational knowledge from ages 5 to 10 years. Our analyses consisted of a two-step process. First, we performed a hierarchical clustering analysis on the decisions made in 16 different tasks of spatial relational knowledge to determine which tasks were performed similarly at each age group as well as to discover how the tasks clustered together. We next used two measures of entropy to capture the gradual emergence of order in the development of relational knowledge. These measures of “cognitive entropy” were defined based on two independent aspects of chunking, namely (1) the number of clusters formed at each age group, and (2) the distribution of tasks across the clusters. We found that both measures of entropy decreased with age in a quadratic fashion and were positively and linearly correlated. The decrease in entropy and, therefore, gain of information during development was accompanied by improved performance. These results document, for the first time, the orderly and progressively structured “chunking” of decisions across the development of spatial relational reasoning and quantify this gain within a formal information-theoretic framework. PMID:25698915

  19. An information theory analysis of spatial decisions in cognitive development.

    PubMed

    Scott, Nicole M; Sera, Maria D; Georgopoulos, Apostolos P

    2015-01-01

    Performance in a cognitive task can be considered as the outcome of a decision-making process operating across various knowledge domains or aspects of a single domain. Therefore, an analysis of these decisions in various tasks can shed light on the interplay and integration of these domains (or elements within a single domain) as they are associated with specific task characteristics. In this study, we applied an information theoretic approach to assess quantitatively the gain of knowledge across various elements of the cognitive domain of spatial, relational knowledge, as a function of development. Specifically, we examined changing spatial relational knowledge from ages 5 to 10 years. Our analyses consisted of a two-step process. First, we performed a hierarchical clustering analysis on the decisions made in 16 different tasks of spatial relational knowledge to determine which tasks were performed similarly at each age group as well as to discover how the tasks clustered together. We next used two measures of entropy to capture the gradual emergence of order in the development of relational knowledge. These measures of "cognitive entropy" were defined based on two independent aspects of chunking, namely (1) the number of clusters formed at each age group, and (2) the distribution of tasks across the clusters. We found that both measures of entropy decreased with age in a quadratic fashion and were positively and linearly correlated. The decrease in entropy and, therefore, gain of information during development was accompanied by improved performance. These results document, for the first time, the orderly and progressively structured "chunking" of decisions across the development of spatial relational reasoning and quantify this gain within a formal information-theoretic framework. PMID:25698915

  20. Advanced AEM by Comprehensive Analysis and Modeling of System Drift

    NASA Astrophysics Data System (ADS)

    Schiller, Arnulf; Klune, Klaus; Schattauer, Ingrid

    2010-05-01

    The quality of the assessment of risks outgoing from environmental hazards strongly depends on the spatial and temporal distribution of the data collected in a survey area. Natural hazards generally emerge from wide areas as it is in the case of volcanoes or land slides. Conventional surface measurements are restricted to few lines or locations and often can't be conducted in difficult terrain. So they only give a spatial and temporary limited data set and therefore limit the reliability of risk analysis. Aero-geophysical measurements potentially provide a valuable tool for completing the data set as they can be performed over a wide area, even above difficult terrain within a short time. A most desirable opportunity in course of such measurements is the ascertainment of the dynamics of such potentially hazardous environmental processes. This necessitates repeated and reproducible measurements. Current HEM systems can't accomplish this adequately due to their system immanent drift and - in some cases - bad signal to noise ratio. So, to develop comprising concepts for advancing state of the art HEM-systems to a valuable tool for data acquisition in risk assessment or hydrological problems, different studies have been undertaken which form the contents of the presented work conducted in course of the project HIRISK (Helicopter Based Electromagnetic System for Advanced Environmental Risk Assessment - FWF L-354 N10, supported by the Austrian Science Fund). The methodology is based upon two paths: A - Comprehensive experimental testing on an existing HEM system serving as an experimental platform. B - The setup of a numerical model which is continuously refined according to the results of the experimental data. The model then serves to simulate the experimental as well as alternative configurations and to analyze them subject to their drift behavior. Finally, concepts for minimizing the drift are derived and tested. Different test series - stationary on ground as well

  1. The Tuition Advance Fund: An Analysis Prepared for Boston University.

    ERIC Educational Resources Information Center

    Botsford, Keith

    Three models for anlayzing the Tuition Advance Fund (TAF) are examined. The three models are: projections by the Institute for Demographic and Economic Studies (IDES), projections by Data Resources, Inc. (DRI), and the Tuition Advance Fund Simulation (TAFSIM) models from Boston University. Analysis of the TAF is based on enrollment, price, and…

  2. A Meta-Analysis of Advance-Organizer Studies.

    ERIC Educational Resources Information Center

    Stone, Carol Leth

    Long term studies of advance organizers (AO) were analyzed with Glass's meta-analysis technique. AO's were defined as bridges from reader's previous knowledge to what is to be learned. The results were compared with predictions from Ausubel's model of assimilative learning. The results of the study indicated that advance organizers were associated…

  3. Spatial frequency analysis of anisotropic drug transport in tumor samples

    PubMed Central

    Russell, Stewart; Samkoe, Kimberley S.; Gunn, Jason R.; Hoopes, P. Jack; Nguyen, Thienan A.; Russell, Milo J.; Alfano, Robert R.; Pogue, Brian W.

    2014-01-01

    Abstract. Directional Fourier spatial frequency analysis was used on standard histological sections to identify salient directional bias in the spatial frequencies of stromal and epithelial patterns within tumor tissue. This directional bias is shown to be correlated to the pathway of reduced fluorescent tracer transport. Optical images of tumor specimens contain a complex distribution of randomly oriented aperiodic features used for neoplastic grading that varies with tumor type, size, and morphology. The internal organization of these patterns in frequency space is shown to provide a precise fingerprint of the extracellular matrix complexity, which is well known to be related to the movement of drugs and nanoparticles into the parenchyma, thereby identifying the characteristic spatial frequencies of regions that inhibit drug transport. The innovative computational methodology and tissue validation techniques presented here provide a tool for future investigation of drug and particle transport in tumor tissues, and could potentially be used a priori to identify barriers to transport, and to analyze real-time monitoring of transport with respect to therapeutic intervention. PMID:24395585

  4. Spatial frequency analysis of anisotropic drug transport in tumor samples

    NASA Astrophysics Data System (ADS)

    Russell, Stewart; Samkoe, Kimberley S.; Gunn, Jason R.; Hoopes, P. Jack; Nguyen, Thienan A.; Russell, Milo J.; Alfano, Robert R.; Pogue, Brian W.

    2014-01-01

    Directional Fourier spatial frequency analysis was used on standard histological sections to identify salient directional bias in the spatial frequencies of stromal and epithelial patterns within tumor tissue. This directional bias is shown to be correlated to the pathway of reduced fluorescent tracer transport. Optical images of tumor specimens contain a complex distribution of randomly oriented aperiodic features used for neoplastic grading that varies with tumor type, size, and morphology. The internal organization of these patterns in frequency space is shown to provide a precise fingerprint of the extracellular matrix complexity, which is well known to be related to the movement of drugs and nanoparticles into the parenchyma, thereby identifying the characteristic spatial frequencies of regions that inhibit drug transport. The innovative computational methodology and tissue validation techniques presented here provide a tool for future investigation of drug and particle transport in tumor tissues, and could potentially be used a priori to identify barriers to transport, and to analyze real-time monitoring of transport with respect to therapeutic intervention.

  5. Reducing spatial uncertainty in climatic maps through geostatistical analysis

    NASA Astrophysics Data System (ADS)

    Pesquer, Lluís; Ninyerola, Miquel; Pons, Xavier

    2014-05-01

    Climatic maps from meteorological stations and geographical co-variables can be obtained through correlative models (Ninyerola et al., 2000)*. Nevertheless, the spatial uncertainty of the resulting maps could be reduced. The present work is a new stage over those approaches aiming to study how to obtain better results while characterizing spatial uncertainty. The study area is Catalonia (32000 km2), a region with highly variable relief (0 to 3143 m). We have used 217 stations (321 to 1244 mm) to model the annual precipitation in two steps: 1/ multiple regression using geographical variables (elevation, distance to the coast, latitude, etc) and 2/ refinement of the results by adding the spatial interpolation of the regression residuals with inverse distance weighting (IDW), regularized splines with tension (SPT) or ordinary kriging (OK). Spatial uncertainty analysis is based on an independent subsample (test set), randomly selected in previous works. The main contribution of this work is the analysis of this test set as well as the search for an optimal process of division (split) of the stations in two sets, one used to perform the multiple regression and residuals interpolation (fit set), and another used to compute the quality (test set); optimal division should reduce spatial uncertainty and improve the overall quality. Two methods have been evaluated against classical methods: (random selection RS and leave-one-out cross-validation LOOCV): selection by Euclidian 2D-distance, and selection by anisotropic 2D-distance combined with a 3D-contribution (suitable weighted) from the most representative independent variable. Both methods define a minimum threshold distance, obtained by variogram analysis, between samples. Main preliminary results for LOOCV, RS (average from 10 executions), Euclidian criterion (EU), and for anisotropic criterion (with 1.1 value, UTMY coordinate has a bit more weight than UTMX) combined with 3D criteria (A3D) (1000 factor for elevation

  6. Advanced Fingerprint Analysis Project Fingerprint Constituents

    SciTech Connect

    GM Mong; CE Petersen; TRW Clauss

    1999-10-29

    The work described in this report was focused on generating fundamental data on fingerprint components which will be used to develop advanced forensic techniques to enhance fluorescent detection, and visualization of latent fingerprints. Chemical components of sweat gland secretions are well documented in the medical literature and many chemical techniques are available to develop latent prints, but there have been no systematic forensic studies of fingerprint sweat components or of the chemical and physical changes these substances undergo over time.

  7. Advanced nuclear rocket engine mission analysis

    SciTech Connect

    Ramsthaler, J.; Farbman, G.; Sulmeisters, T.; Buden, D.; Harris, P.

    1987-12-01

    The use of a derivative of the NERVA engine developed from 1955 to 1973 was evluated for potential application to Air Force orbital transfer and maneuvering missions in the time period 1995 to 2020. The NERVA stge was found to have lower life cycle costs (LCC) than an advanced chemical stage for performing low earth orbit (LEO) to geosynchronous orbit (GEO0 missions at any level of activity greater than three missions per year. It had lower life cycle costs than a high performance nuclear electric engine at any level of LEO to GEO mission activity. An examination of all unmanned orbital transfer and maneuvering missions from the Space Transportation Architecture study (STAS 111-3) indicated a LCC advantage for the NERVA stage over the advanced chemical stage of fifteen million dollars. The cost advanced accured from both the orbital transfer and maneuvering missions. Parametric analyses showed that the specific impulse of the NERVA stage and the cost of delivering material to low earth orbit were the most significant factors in the LCC advantage over the chemical stage. Lower development costs and a higher thrust gave the NERVA engine an LCC advantage over the nuclear electric stage. An examination of technical data from the Rover/NERVA program indicated that development of the NERVA stage has a low technical risk, and the potential for high reliability and safe operation. The data indicated the NERVA engine had a great flexibility which would permit a single stage to perform all Air Force missions.

  8. Advanced Spatial-Division Multiplexed Measurement Systems Propositions-From Telecommunication to Sensing Applications: A Review.

    PubMed

    Weng, Yi; Ip, Ezra; Pan, Zhongqi; Wang, Ting

    2016-01-01

    The concepts of spatial-division multiplexing (SDM) technology were first proposed in the telecommunications industry as an indispensable solution to reduce the cost-per-bit of optical fiber transmission. Recently, such spatial channels and modes have been applied in optical sensing applications where the returned echo is analyzed for the collection of essential environmental information. The key advantages of implementing SDM techniques in optical measurement systems include the multi-parameter discriminative capability and accuracy improvement. In this paper, to help readers without a telecommunication background better understand how the SDM-based sensing systems can be incorporated, the crucial components of SDM techniques, such as laser beam shaping, mode generation and conversion, multimode or multicore elements using special fibers and multiplexers are introduced, along with the recent developments in SDM amplifiers, opto-electronic sources and detection units of sensing systems. The examples of SDM-based sensing systems not only include Brillouin optical time-domain reflectometry or Brillouin optical time-domain analysis (BOTDR/BOTDA) using few-mode fibers (FMF) and the multicore fiber (MCF) based integrated fiber Bragg grating (FBG) sensors, but also involve the widely used components with their whole information used in the full multimode constructions, such as the whispering gallery modes for fiber profiling and chemical species measurements, the screw/twisted modes for examining water quality, as well as the optical beam shaping to improve cantilever deflection measurements. Besides, the various applications of SDM sensors, the cost efficiency issue, as well as how these complex mode multiplexing techniques might improve the standard fiber-optic sensor approaches using single-mode fibers (SMF) and photonic crystal fibers (PCF) have also been summarized. Finally, we conclude with a prospective outlook for the opportunities and challenges of SDM

  9. Advanced Modeling, Simulation and Analysis (AMSA) Capability Roadmap Progress Review

    NASA Technical Reports Server (NTRS)

    Antonsson, Erik; Gombosi, Tamas

    2005-01-01

    Contents include the following: NASA capability roadmap activity. Advanced modeling, simulation, and analysis overview. Scientific modeling and simulation. Operations modeling. Multi-special sensing (UV-gamma). System integration. M and S Environments and Infrastructure.

  10. Drought analysis in Switzerland: spatial and temporal features

    NASA Astrophysics Data System (ADS)

    Di Franca, Gaetano; Molnar, Peter; Burlando, Paolo; Bonaccorso, Brunella; Cancelliere, Antonino

    2015-04-01

    Drought as a natural hazard may have negative impacts even in regions characterized by a general abundance of water resources. The Swiss Alpine region has experienced several extreme meteorological events (heat waves, droughts) during the last fifty years that have caused human and economic losses. Though Swiss climate is far from arid or semi-arid, natural climatic variability, exacerbated by climate change, could lead to more severe impacts from naturally occurring meteorological droughts (i.e. lack or significant reduction of precipitation) in the future. In this work, spatial and temporal features of meteorological droughts in Switzerland have been explored by the identification and probabilistic characterization of historic drought events on gridded precipitation data during the period 1961-2012. The run method has been applied to both monthly and annual precipitation time series to probabilistically characterize drought occurrences as well as to analyze their spatial variability. Spatial features have also been investigated by means of Principal Components Analysis (PCA) applied to Standardized Precipitation Index (SPI) series at 3, 6, and 12-month aggregated time scale, in order to detect areas with distinct precipitation patterns, accounting for seasonality throughout year and including both wet and dry conditions. Furthermore, a probabilistic analysis of drought areal extent has been carried out by applying an SPI-based procedure to derive Severity-Area-Frequency (SAF) curves. The application of run method reveals that Ticino and Valais are the most potentially drought-prone Swiss regions, since accumulated deficit precipitation is significantly higher (up to two times) than in the rest of the country. Inspection of SPI series reveals many events in which precipitation has shown significant anomalies from the average in the period 1961-2012 at the investigated time scales. Anomalies in rainfall seem to exhibit high spatial correlation, showing uniform sub

  11. iGlobe Interactive Visualization and Analysis of Spatial Data

    NASA Technical Reports Server (NTRS)

    Hogan, Patrick

    2012-01-01

    iGlobe is open-source software built on NASA World Wind virtual globe technology. iGlobe provides a growing set of tools for weather science, climate research, and agricultural analysis. Up until now, these types of sophisticated tools have been developed in isolation by national agencies, academic institutions, and research organizations. By providing an open-source solution to analyze and visualize weather, climate, and agricultural data, the scientific and research communities can more readily advance solutions needed to understand better the dynamics of our home planet, Earth

  12. Analysis of global ionospheric TEC temporal-spatial characteristics

    NASA Astrophysics Data System (ADS)

    Jiang, Maofang; Huang, Liangke; Wu, Pituan; Cai, Chenghui; Liu, Lilong

    2015-12-01

    The formation of the ionosphere is mainly the interaction of solar radiation and the earth's atmosphere, in different temporal-spatial environment, the characteristics of the ionosphere is more complex, and the Total Electron Content (TEC) is one of the important parameters of the ionospheric morphology and structure. Therefore, in this paper, using the high-precision TEC time series provided by the International GNSS Service (IGS) as experimental data, by Fast Fourier Transform (FFT) to detect its periodic changes, and then focus on analysis the characteristics of diurnal variation, seasonal variation and annual variation and winter anomaly, simultaneous analysis of the ionospheric characteristics vary with latitude and longitude. The result show that: (1) TEC changes more intense during the day, but the night is quiet, and in different latitudes, the TEC reached peak value at different moment; (2) Winter anomaly exists only during the day, night does not exist; (3) In the same time domain, TEC value decreases gradually with the increase of latitude, and it has different spatial variation features in different hemispheres.

  13. Probabilistic Common Spatial Patterns for Multichannel EEG Analysis

    PubMed Central

    Chen, Zhe; Gao, Xiaorong; Li, Yuanqing; Brown, Emery N.; Gao, Shangkai

    2015-01-01

    Common spatial patterns (CSP) is a well-known spatial filtering algorithm for multichannel electroencephalogram (EEG) analysis. In this paper, we cast the CSP algorithm in a probabilistic modeling setting. Specifically, probabilistic CSP (P-CSP) is proposed as a generic EEG spatio-temporal modeling framework that subsumes the CSP and regularized CSP algorithms. The proposed framework enables us to resolve the overfitting issue of CSP in a principled manner. We derive statistical inference algorithms that can alleviate the issue of local optima. In particular, an efficient algorithm based on eigendecomposition is developed for maximum a posteriori (MAP) estimation in the case of isotropic noise. For more general cases, a variational algorithm is developed for group-wise sparse Bayesian learning for the P-CSP model and for automatically determining the model size. The two proposed algorithms are validated on a simulated data set. Their practical efficacy is also demonstrated by successful applications to single-trial classifications of three motor imagery EEG data sets and by the spatio-temporal pattern analysis of one EEG data set recorded in a Stroop color naming task. PMID:26005228

  14. Advanced surface design for logistics analysis

    NASA Astrophysics Data System (ADS)

    Brown, Tim R.; Hansen, Scott D.

    The development of anthropometric arm/hand and tool models and their manipulation in a large system model for maintenance simulation are discussed. The use of Advanced Surface Design and s-fig technology in anthropometrics, and three-dimensional graphics simulation tools, are found to achieve a good balance between model manipulation speed and model accuracy. The present second generation models are shown to be twice as fast to manipulate as the first generation b-surf models, to be easier to manipulate into various configurations, and to more closely approximate human contours.

  15. Advanced tracking systems design and analysis

    NASA Technical Reports Server (NTRS)

    Potash, R.; Floyd, L.; Jacobsen, A.; Cunningham, K.; Kapoor, A.; Kwadrat, C.; Radel, J.; Mccarthy, J.

    1989-01-01

    The results of an assessment of several types of high-accuracy tracking systems proposed to track the spacecraft in the National Aeronautics and Space Administration (NASA) Advanced Tracking and Data Relay Satellite System (ATDRSS) are summarized. Tracking systems based on the use of interferometry and ranging are investigated. For each system, the top-level system design and operations concept are provided. A comparative system assessment is presented in terms of orbit determination performance, ATDRSS impacts, life-cycle cost, and technological risk.

  16. Characterization of porous surfaces with spatial point pattern analysis

    NASA Astrophysics Data System (ADS)

    Zou, Yibo; Kästner, Markus; Reithmeier, Eduard

    2015-01-01

    Nowadays thermal plasma spray coating is widespread in automobile industry. For example, in the cylinder manufacturing process coatings are applied for friction reduction, wear and corrosion resistance. After the honing process, a coated surface exhibits porous microstructures, which are often characterized in order to understand functional correlations between key parameters of the pores and friction performance. In this paper, spatial point pattern analysis is used to investigate the pores' distribution in a two dimensional space. Methods, such as nearest neighbor analysis and Ripley's K-function, are used to conduct the experiments to analyze the observer's pattern. Different edge correction methods in Ripley's K-function are introduced. Confidence envelopes are simulated using the Monte Carlo method. Experimental results are presented to reveal the patterns of pores, where influences of the selected measurement area on the results are taken into account and further discussed.

  17. Spatially explicit analysis of gastropod biodiversity in ancient Lake Ohrid

    NASA Astrophysics Data System (ADS)

    Hauffe, T.; Albrecht, C.; Schreiber, K.; Birkhofer, K.; Trajanovski, S.; Wilke, T.

    2011-01-01

    The quality of spatial analyses of biodiversity is improved by (i) utilizing study areas with well defined physiogeographical boundaries, (ii) limiting the impact of widespread species, and (iii) using taxa with heterogeneous distributions. These conditions are typically met by ecosystems such as oceanic islands or ancient lakes and their biota. While research on ancient lakes has contributed significantly to our understanding of evolutionary processes, statistically sound studies of spatial variation of extant biodiversity have been hampered by the frequently vast size of ancient lakes, their limited accessibility, and the lack of scientific infrastructure. The European ancient Lake Ohrid provides a rare opportunity for such a reliable spatial study. The comprehensive horizontal and vertical sampling of a species-rich taxon, the Gastropoda, presented here, revealed interesting patterns of biodiversity, which, in part, have not been shown before for other ancient lakes. In a total of 284 samples from 224 different locations throughout the Ohrid Basin, 68 gastropod species, with 50 of them (= 73.5%) being endemic, could be reported. The spatial distribution of these species shows the following characteristics: (i) within Lake Ohrid, the most frequent species are endemic taxa with a wide depth range, (ii) widespread species (i.e. those occurring throughout the Balkans or beyond) are rare and mainly occur in the upper layer of the lake, (iii) while the total number of species decreases with water depth, the proportion of endemics increases, and (iv) the deeper layers of Lake Ohrid appear to have a higher spatial homogeneity of biodiversity. Moreover, gastropod communities of Lake Ohrid and its feeder springs are both distinct from each other and from the surrounding waters. The analysis also shows that community similarity of Lake Ohrid is mainly driven by niche processes (e.g. environmental factors), but also by neutral processes (e.g. dispersal limitation and

  18. Advanced measurement and analysis of surface textures produced by micro-machining processes

    NASA Astrophysics Data System (ADS)

    Bordatchev, Evgueni V.; Hafiz, Abdullah M. K.

    2014-09-01

    Surface texture of a part or a product has significant effects on its functionality, physical-mechanical properties and visual appearance. In particular for miniature products, the implication of surface quality becomes critical owing to the presence of geometrical features with micro/nano-scale dimensions. Qualitative and quantitative assessments of surface texture are carried out predominantly by profile parameters, which are often insufficient to address the contribution of constituent spatial components with varied amplitudes and wavelengths. In this context, this article presents a novel approach for advanced measurement and analysis of profile average roughness (Ra) and its spatial distribution at different wavelength intervals. The applicability of the proposed approach was verified for three different surface topographies prepared by grinding, laser micro-polishing and micro-milling processes. From the measurement and analysis results, Ra(λ) spatial distribution was found to be an effective measure of revealing the contributions of various spatial components within specific wavelength intervals towards formation of the entire surface profile. In addition, the approach was extended to the measurement and analysis of areal average roughness Sa(λ) spatial distribution within different wavelength intervals. Besides, the proposed method was demonstrated to be a useful technique in developing a functional correlation between a manufacturing process and its corresponding surface profile.

  19. Spatial Techniques

    NASA Astrophysics Data System (ADS)

    Jabeur, Nafaa; Sahli, Nabil

    The environment, including the Earth and the immense space, is recognized to be the main source of useful information for human beings. During several decades, the acquisition of data from this environment was constrained by tools and techniques with limited capabilities. However, thanks to continuous technological advances,spatial data are available in huge quantities for different applications. The technological advances have been achieved in terms of hardware and software as well. They are allowing for better accuracy and availability, which in turn improves the quality and quantity of useful knowledge that can be extracted from the environment. They have been applied to geography, resulting in geospatial techniques. Applied to both science and technology, geospatial techniques resulted in areas of expertise, such as land surveying, cartography, navigation, remote sensing, Geographic Infor-mation Systems (GISs), and Global Positioning Systems (GPSs). They had evolved quickly with advances in computing, satellite technology and a growing demand to understand our global environment. In this chapter, we will discuss three important techniques that are widely used in spatial data acquisition and analysis: GPS and remote sensing techniques that are used to collect spatial data and a GIS that is used to store, manipulate, analyze, and visualize spatial data. Later in this book, we will discuss the techniques that are currently available for spatial knowledge discovery.

  20. Recent Advances in Anthocyanin Analysis and Characterization

    PubMed Central

    Welch, Cara R.; Wu, Qingli; Simon, James E.

    2009-01-01

    Anthocyanins are a class of polyphenols responsible for the orange, red, purple and blue colors of many fruits, vegetables, grains, flowers and other plants. Consumption of anthocyanins has been linked as protective agents against many chronic diseases and possesses strong antioxidant properties leading to a variety of health benefits. In this review, we examine the advances in the chemical profiling of natural anthocyanins in plant and biological matrices using various chromatographic separations (HPLC and CE) coupled with different detection systems (UV, MS and NMR). An overview of anthocyanin chemistry, prevalence in plants, biosynthesis and metabolism, bioactivities and health properties, sample preparation and phytochemical investigations are discussed while the major focus examines the comparative advantages and disadvantages of each analytical technique. PMID:19946465

  1. Remote sensing and spatial analysis of aeolian sand dunes: A review and outlook

    NASA Astrophysics Data System (ADS)

    Hugenholtz, Chris H.; Levin, Noam; Barchyn, Thomas E.; Baddock, Matthew C.

    2012-03-01

    For more than four decades remote sensing images have been used to document and understand the evolution of aeolian sand dunes. Early studies focused on mapping and classifying dunes. Recent advances in sensor technology and software have allowed investigators to move towards quantitative investigation of dune form evolution and pattern development. These advances have taken place alongside progress in numerical models, which are capable of simulating the multitude of dune patterns observed in nature. The potential to integrate remote sensing (RS), spatial analysis (SA), and modeling to predict the future changes of real-world dune systems is steadily becoming a reality. Here we present a comprehensive review of significant recent advances involving RS and SA. Our objective is to demonstrate the capacity of these technologies to provide new insight on three important research domains: (1) dune activity, (2) dune patterns and hierarchies, and (3) extra-terrestrial dunes. We outline how several recent advances have capitalized on the improved spatial and spectral resolution of RS data, the availability of topographic data, and new SA methods and software. We also discuss some of the key research challenges and opportunities in the application of RS and SA dune field, including: the integration of RS data with field-based measurements of vegetation cover, structure, and aeolian transport rate in order to develop predictive models of dune field activity; expanding the observational evidence of dune form evolution at temporal and spatial scales that can be used to validate and refine simulation models; the development and application of objective and reproducible SA methods for characterizing dune field pattern; and, expanding efforts to quantify three-dimensional topographic changes of dune fields in order to develop improved understanding of spatio-temporal patterns of erosion and deposition. Overall, our review indicates a progressive evolution in the way sand dunes

  2. The bivariate combined model for spatial data analysis.

    PubMed

    Neyens, Thomas; Lawson, Andrew B; Kirby, Russell S; Faes, Christel

    2016-08-15

    To describe the spatial distribution of diseases, a number of methods have been proposed to model relative risks within areas. Most models use Bayesian hierarchical methods, in which one models both spatially structured and unstructured extra-Poisson variance present in the data. For modelling a single disease, the conditional autoregressive (CAR) convolution model has been very popular. More recently, a combined model was proposed that 'combines' ideas from the CAR convolution model and the well-known Poisson-gamma model. The combined model was shown to be a good alternative to the CAR convolution model when there was a large amount of uncorrelated extra-variance in the data. Less solutions exist for modelling two diseases simultaneously or modelling a disease in two sub-populations simultaneously. Furthermore, existing models are typically based on the CAR convolution model. In this paper, a bivariate version of the combined model is proposed in which the unstructured heterogeneity term is split up into terms that are shared and terms that are specific to the disease or subpopulation, while spatial dependency is introduced via a univariate or multivariate Markov random field. The proposed method is illustrated by analysis of disease data in Georgia (USA) and Limburg (Belgium) and in a simulation study. We conclude that the bivariate combined model constitutes an interesting model when two diseases are possibly correlated. As the choice of the preferred model differs between data sets, we suggest to use the new and existing modelling approaches together and to choose the best model via goodness-of-fit statistics. Copyright © 2016 John Wiley & Sons, Ltd. PMID:26928309

  3. Study of trabecular bone microstructure using spatial autocorrelation analysis

    NASA Astrophysics Data System (ADS)

    Wald, Michael J.; Vasilic, Branimir; Saha, Punam K.; Wehrli, Felix W.

    2005-04-01

    The spatial autocorrelation analysis method represents a powerful, new approach to quantitative characterization of structurally quasi-periodic anisotropic materials such as trabecular bone (TB). The method is applicable to grayscale images and thus does not require any preprocessing, such as segmentation which is difficult to achieve in the limited resolution regime of in vivo imaging. The 3D autocorrelation function (ACF) can be efficiently calculated using the Fourier transform. The resulting trabecular thickness and spacing measurements are robust to the presence of noise and produce values within the expected range as determined by other methods from μCT and μMRI datasets. TB features found from the ACF are shown to correlate well with those determined by the Fuzzy Distance transform (FDT) in the transverse plane, i.e. the plane orthogonal to bone"s major axis. The method is further shown to be applicable to in-vivo μMRI data. Using the ACF, we examine data acquired in a previous study aimed at evaluating the structural implications of male hypogonadism characterized by testosterone deficiency and reduced bone mass. Specifically, we consider the hypothesis that eugonadal and hypogonadal men differ in the anisotropy of their trabecular networks. The analysis indicates a significant difference in trabecular bone thickness and longitudinal spacing between the control group and the testosterone deficient group. We conclude that spatial autocorrelation analysis is able to characterize the 3D structure and anisotropy of trabecular bone and provides new insight into the structural changes associated with osteoporotic trabecular bone loss.

  4. Brazilian Road Traffic Fatalities: A Spatial and Environmental Analysis

    PubMed Central

    de Andrade, Luciano; Vissoci, João Ricardo Nickenig; Rodrigues, Clarissa Garcia; Finato, Karen; Carvalho, Elias; Pietrobon, Ricardo; de Souza, Eniuce Menezes; Nihei, Oscar Kenji; Lynch, Catherine; de Barros Carvalho, Maria Dalva

    2014-01-01

    Background Road traffic injuries (RTI) are a major public health epidemic killing thousands of people daily. Low and middle-income countries, such as Brazil, have the highest annual rates of road traffic fatalities. In order to improve road safety, this study mapped road traffic fatalities on a Brazilian highway to determine the main environmental factors affecting road traffic fatalities. Methods and Findings Four techniques were utilized to identify and analyze RTI hotspots. We used spatial analysis by points by applying kernel density estimator, and wavelet analysis to identify the main hot regions. Additionally, built environment analysis, and principal component analysis were conducted to verify patterns contributing to crash occurrence in the hotspots. Between 2007 and 2009, 379 crashes were notified, with 466 fatalities on BR277. Higher incidence of crashes occurred on sections of highway with double lanes (ratio 2∶1). The hotspot analysis demonstrated that both the eastern and western regions had higher incidences of crashes when compared to the central region. Through the built environment analysis, we have identified five different patterns, demonstrating that specific environmental characteristics are associated with different types of fatal crashes. Patterns 2 and 4 are constituted mainly by predominantly urban characteristics and have frequent fatal pedestrian crashes. Patterns 1, 3 and 5 display mainly rural characteristics and have higher prevalence of vehicular collisions. In the built environment analysis, the variables length of road in urban area, limited lighting, double lanes roadways, and less auxiliary lanes were associated with a higher incidence of fatal crashes. Conclusions By combining different techniques of analyses, we have identified numerous hotspots and environmental characteristics, which governmental or regulatory agencies could make use to plan strategies to reduce RTI and support life-saving policies. PMID:24498051

  5. Effect of spatial normalization on analysis of functional data

    NASA Astrophysics Data System (ADS)

    Gee, James C.; Alsop, David C.; Aguirre, Geoffrey K.

    1997-04-01

    Conventional analysis of functional data often involves a normalization step in which the data are spatially aligned so that a measurement can be made across or between studies. Whether to enhance the signal-to-noise ratio or to detect significant deviations in activation from normal, the method used to register the underlying anatomies clearly impacts the viability of the analysis. Nevertheless, it is common practice to infer only homogeneous transformations, in which all parts of the image volume undergo the same mapping. To detect subtle effects or to extend the analysis to anatomies that exhibit considerable morphological variation, higher dimensional mappings to allow more accurate alignment will be crucial. We describe a Bayesian volumetric warping approach to the normalization problem, which matches local image features between MRI brain volumes, and compares its performance with a standard method (SPM'96) as well as contrast its effect on the analysis of a set of functional MRI studies against that obtained with a 9-parameter affine registration.

  6. [Research of Identify Spatial Object Using Spectrum Analysis Technique].

    PubMed

    Song, Wei; Feng, Shi-qi; Shi, Jing; Xu, Rong; Wang, Gong-chang; Li, Bin-yu; Liu, Yu; Li, Shuang; Cao Rui; Cai, Hong-xing; Zhang, Xi-he; Tan, Yong

    2015-06-01

    The high precision scattering spectrum of spatial fragment with the minimum brightness of 4.2 and the resolution of 0.5 nm has been observed using spectrum detection technology on the ground. The obvious differences for different types of objects are obtained by the normalizing and discrete rate analysis of the spectral data. Each of normalized multi-frame scattering spectral line shape for rocket debris is identical. However, that is different for lapsed satellites. The discrete rate of the single frame spectrum of normalized space debris for rocket debris ranges from 0.978% to 3.067%, and the difference of oscillation and average value is small. The discrete rate for lapsed satellites ranges from 3.118 4% to 19.472 7%, and the difference of oscillation and average value relatively large. The reason is that the composition of rocket debris is single, while that of the lapsed satellites is complex. Therefore, the spectrum detection technology on the ground can be used to the classification of the spatial fragment. PMID:26601348

  7. Hypsometric analysis to identify spatially variable glacial erosion

    NASA Astrophysics Data System (ADS)

    Sternai, P.; Herman, F.; Fox, M. R.; Castelltort, S.

    2011-09-01

    Relatively little research has been undertaken on the use of digital elevation models to recognize the spatially variable glacial imprint of a landscape. Using theoretical topographies and a landscape evolution model, we investigate to what extent the hypsometric analysis of digital elevation models may be used to recognize the glacial signature of mountain ranges. A new morphometric parameter, which we term the hypsokyrtome (from the Greek: ipsos = elevation, kyrtoma = curvature), is derived from the gradient of the hypsometric curve. The efficacy of the hypsometric integral and hypsokyrtome is tested through the study of the Ben Ohau Range, New Zealand, whose glacial imprint has been described previously. With a numerical model we further test the geomorphic parameters in describing the morphologies of regions subject to diverse climatic and tectonic conditions. The hypsokyrtome is highly sensitive to glacial erosion, and the maps produced provide insights into the spatial distribution of glacial erosion. We use SRTM data and focus on two alternative geomorphic settings: the European Alps and the Apennines. The former has been affected by both fluvial and glacial erosion while the latter mainly exhibits a fluvially dominated morphology. The correlation between elevations with increased glacial erosion and Last Glacial Maximum (LGM) equilibrium line altitudes (ELAs) suggests the prevalence of a "glacial buzz saw" in the Alps, indicating that climate may put a limit on alpine topography.

  8. Analysis of an advanced technology subsonic turbofan incorporating revolutionary materials

    NASA Technical Reports Server (NTRS)

    Knip, Gerald, Jr.

    1987-01-01

    Successful implementation of revolutionary composite materials in an advanced turbofan offers the possibility of further improvements in engine performance and thrust-to-weight ratio relative to current metallic materials. The present analysis determines the approximate engine cycle and configuration for an early 21st century subsonic turbofan incorporating all composite materials. The advanced engine is evaluated relative to a current technology baseline engine in terms of its potential fuel savings for an intercontinental quadjet having a design range of 5500 nmi and a payload of 500 passengers. The resultant near optimum, uncooled, two-spool, advanced engine has an overall pressure ratio of 87, a bypass ratio of 18, a geared fan, and a turbine rotor inlet temperature of 3085 R. Improvements result in a 33-percent fuel saving for the specified misssion. Various advanced composite materials are used throughout the engine. For example, advanced polymer composite materials are used for the fan and the low pressure compressor (LPC).

  9. Spatial Analysis of Changes in the Number of Farms during the Farm Crisis

    ERIC Educational Resources Information Center

    Brasier, Kathryn J.

    2005-01-01

    This analysis reexamines factors affecting farm change during the Farm Crisis using spatial analysis techniques to identify important spatial factors and correct for spatial autocorrelation. Results indicate the importance of indicators of farm structure, percent of prime farmland, and state-level processes in predicting changes in the number of…

  10. Using a spatially explicit analysis model to evaluate spatial variation of corn yield

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Spatial irrigation of agricultural crops using site-specific variable-rate irrigation (VRI) systems is beginning to have wide-spread acceptance. However, optimizing the management of these VRI systems to conserve natural resources and increase profitability requires an understanding of the spatial ...

  11. Advanced Techniques for Assessment of Postural and Locomotor Ataxia, Spatial Orientation, and Gaze Stability

    NASA Technical Reports Server (NTRS)

    Wall, Conrad., III

    1999-01-01

    In addition to adapting to microgravity, major neurovestibular problems of space flight include postflight difficulties with standing, walking, turning corners, and other activities that require stable upright posture and gaze stability. These difficulties inhibit astronauts' ability to stand or escape from their vehicle during emergencies. The long-ter7n goal of the NSBRI is the development of countermeasures to ameliorate the effects of long duration space flight. These countermeasures must be tested with valid and reliable tools. This project aims to develop quantitative, parametric approaches for assessing gaze stability and spatial orientation during normal gait and when gait is perturbed. Two of this year's most important findings concern head fixation distance and ideal trajectory analysis. During a normal cycle of walking the head moves up and down linearly. A simultaneous angular pitching motion of the head keeps it aligned toward an imaginary point in space at a distance of about one meter in front of a subject and along the line of march. This distance is called the head fixation distance. Head fixation distance provides the fundamental framework necessary for understanding the functional significance of the vestibular reflexes that couple head motion to eye motion. This framework facilitates the intelligent design of counter-measures for the effects of exposure to microgravity upon the vestibular ocular reflexes. Ideal trajectory analysis is a simple candidate countermeasure based upon quantifying body sway during repeated up and down stair stepping. It provides one number that estimates the body sway deviation from an ideal sinusoidal body sway trajectory normalized on the subject's height. This concept has been developed with NSBRI funding in less than one year. These findings are explained in more detail below. Compared to assessments of the vestibuo-ocular reflex, analysis of vestibular effects on locomotor function is relatively less well developed

  12. Advanced reliability method for fatigue analysis

    NASA Technical Reports Server (NTRS)

    Wu, Y.-T.; Wirsching, P. H.

    1984-01-01

    When design factors are considered as random variables and the failure condition cannot be expressed by a closed form algebraic inequality, computations of risk (or probability of failure) may become extremely difficult or very inefficient. This study suggests using a simple and easily constructed second degree polynomial to approximate the complicated limit state in the neighborhood of the design point; a computer analysis relates the design variables at selected points. Then a fast probability integration technique (i.e., the Rackwitz-Fiessler algorithm) can be used to estimate risk. The capability of the proposed method is demonstrated in an example of a low cycle fatigue problem for which a computer analysis is required to perform local strain analysis to relate the design variables. A comparison of the performance of this method is made with a far more costly Monte Carlo solution. Agreement of the proposed method with Monte Carlo is considered to be good.

  13. Psychometric analysis of five measures of spatial ability.

    PubMed

    Hogan, Thomas P

    2012-02-01

    This study analyzed psychometric properties of five measures of spatial ability on 96 young adults, with supplementary analysis for three of the measures on another sample of 71 young adults. Two measures were taken from the widely cited Kit of Factor-Referenced Cognitive Tests and three other measures were taken from a relatively new source originally intended as laboratory demonstrations. Previous research provided limited information on the psychometric properties of the measures. All five measures yielded adequate reliability and loaded on a single factor. Three measures yielded markedly skewed distributions. Two measures showed clear sex differences with men scoring higher but this difference seemed contaminated by a speed factor; three measures did not show a sex difference. Recommendations for use of the measures in future studies are provided. PMID:22582677

  14. Evapotranspiration Controls Imposed by Soil Moisture: A Spatial Analysis across the United States

    NASA Astrophysics Data System (ADS)

    Rigden, A. J.; Tuttle, S. E.; Salvucci, G.

    2014-12-01

    We spatially analyze the control over evapotranspiration (ET) imposed by soil moisture across the United States using daily estimates of satellite-derived soil moisture and data-driven ET over a nine-year period (June 2002-June 2011) at 305 locations. The soil moisture data are developed using 0.25-degree resolution satellite observations from the Advanced Microwave Scanning Radiometer for the Earth Observing System (AMSR-E), where the 9-year time series for each 0.25-degree pixel was selected from three potential algorithms (VUA-NASA, U. Montana, & NASA) based on the maximum mutual information between soil moisture and precipitation (Tuttle & Salvucci (2014), Remote Sens Environ, 114: 207-222). The ET data are developed independent of soil moisture using an emergent relationship between the diurnal cycle of the relative humidity profile and ET. The emergent relation is that the vertical variance of the relative humidity profile is less than what would occur for increased or decreased ET rates, suggesting that land-atmosphere feedback processes minimize this variance (Salvucci and Gentine (2013), PNAS, 110(16): 6287-6291). The key advantage of using this approach to estimate ET is that no measurements of surface limiting factors (soil moisture, leaf area, canopy conductance) are required; instead, ET is estimated from meteorological data measured at 305 common weather stations that are approximately uniformly distributed across the United States. The combination of these two independent datasets allows for a unique spatial analysis of the control on ET imposed by the availability of soil moisture. We fit evaporation efficiency curves across the United States at each of the 305 sites during the summertime (May-June-July-August-September). Spatial patterns are visualized by mapping optimal curve fitting coefficients across the Unites States. An analysis of efficiency curves and their spatial patterns will be presented.

  15. Modeling and analysis of advanced binary cycles

    SciTech Connect

    Gawlik, K.

    1997-12-31

    A computer model (Cycle Analysis Simulation Tool, CAST) and a methodology have been developed to perform value analysis for small, low- to moderate-temperature binary geothermal power plants. The value analysis method allows for incremental changes in the levelized electricity cost (LEC) to be determined between a baseline plant and a modified plant. Thermodynamic cycle analyses and component sizing are carried out in the model followed by economic analysis which provides LEC results. The emphasis of the present work is on evaluating the effect of mixed working fluids instead of pure fluids on the LEC of a geothermal binary plant that uses a simple Organic Rankine Cycle. Four resources were studied spanning the range of 265{degrees}F to 375{degrees}F. A variety of isobutane and propane based mixtures, in addition to pure fluids, were used as working fluids. This study shows that the use of propane mixtures at a 265{degrees}F resource can reduce the LEC by 24% when compared to a base case value that utilizes commercial isobutane as its working fluid. The cost savings drop to 6% for a 375{degrees}F resource, where an isobutane mixture is favored. Supercritical cycles were found to have the lowest cost at all resources.

  16. The spatial and temporal analysis of forest resources and institutions

    NASA Astrophysics Data System (ADS)

    Schweik, Charles M.

    This study addresses a central puzzle facing the Human Dimensions of Global Change research community: How can we understand the influence of environmental policies on human behavior when little or no information is available on the condition of forest resources? This dissertation capitalizes on new research tools, methods and approaches to overcome the "no information about the resource" problem. Specifically, I combine (1) forest mensuration techniques, (2) Global Positioning Systems, (3) Geographic Information Systems (GIS), (4) spatial statistics, (5) remote sensing, and (6) institutional analysis to analyze forest vegetation patterns. I provide explanation of these patterns by considering the incentive structures driving human decision-making and activity and do this through two studies in very different empirical settings. Both studies apply applicable theory related to human behavior and action. Both examine the incentive structures individuals face as they undertake daily activities related to forest resources. The first study, set in East Chitwan, Nepal, identifies spatial patterns in georeferenced forest inventory data and links these to patterns predicted by optimal foraging subject to institutional constraints. The second study compares forest management in one state and one national forest in Indiana, U.S.A. In this effort, I identify spatio-temporal patterns in the forest vegetation captured by a time series of Landsat multispectral images. The combination of natural forest regrowth and property manager actions in response to incentives and constraints explain these patterns. Substantively, both studies identify change in forest resources associated with combinations of the physical, human community and institutional "landscapes" in their regions. In both cases, geographic attributes of institutions (e.g., laws, rules) are found to influence the type and location of human actions. Methodologically, the two studies provide examples of how to control

  17. Multitemporal spatial pattern analysis of Tulum's tropical coastal landscape

    NASA Astrophysics Data System (ADS)

    Ramírez-Forero, Sandra Carolina; López-Caloca, Alejandra; Silván-Cárdenas, José Luis

    2011-11-01

    The tropical coastal landscape of Tulum in Quintana Roo, Mexico has a high ecological, economical, social and cultural value, it provides environmental and tourism services at global, national, regional and local levels. The landscape of the area is heterogeneous and presents random fragmentation patterns. In recent years, tourist services of the region has been increased promoting an accelerate expansion of hotels, transportation and recreation infrastructure altering the complex landscape. It is important to understand the environmental dynamics through temporal changes on the spatial patterns and to propose a better management of this ecological area to the authorities. This paper addresses a multi-temporal analysis of land cover changes from 1993 to 2000 in Tulum using Thematic Mapper data acquired by Landsat-5. Two independent methodologies were applied for the analysis of changes in the landscape and for the definition of fragmentation patterns. First, an Iteratively Multivariate Alteration Detection (IR-MAD) algorithm was used to detect and localize land cover change/no-change areas. Second, the post-classification change detection evaluated using the Support Vector Machine (SVM) algorithm. Landscape metrics were calculated from the results of IR-MAD and SVM. The analysis of the metrics indicated, among other things, a higher fragmentation pattern along roadways.

  18. Social stress and trauma: synthesis and spatial analysis.

    PubMed

    Harries, K

    1997-10-01

    In the last decade violence has emerged as a public health issue, with concomitant interest in surveillance and prevention. This paper is an extension of earlier work seeking to expand the ecological analysis of violence across jurisdictional boundaries, sharpen the level of resolution of such analysis, and ultimately inform small area policy applications in terms of public health initiatives for violence reduction. The underlying model is drawn from stress theory and rests on a set of social indicators representing stress in the Baltimore area. In the earlier work, a set of 24 variables describing violence and socioeconomic conditions across some 1358 areas was factor analyzed and the resulting scores were mapped and interpreted. The present paper takes the analysis a step further in an attempt to identify groups of observations with common traits in order to assist public health professionals and other relevant decision-makers in the process of trauma surveillance, response, and prevention. Cluster analysis was used to combine most similar observations in terms of the three orthogonal factors, and the resulting cluster affiliations were mapped in geographic space. Although no spatial contiguity constraint was put on the clustering algorithm, many statistical clusters were also found to constitute geographic clusters. This implies that the process identified neighborhoods or parts of neighborhoods with shared traits in terms of the underlying set of stressors. Analysis of this type could be used by policy-makers to classify neighborhoods in terms of their needs for various services in addition to public health interventions, including policing, fire protection, building inspection, social work, and education. PMID:9381238

  19. Progress in Advanced Spectral Analysis of Radioxenon

    SciTech Connect

    Haas, Derek A.; Schrom, Brian T.; Cooper, Matthew W.; Ely, James H.; Flory, Adam E.; Hayes, James C.; Heimbigner, Tom R.; McIntyre, Justin I.; Saunders, Danielle L.; Suckow, Thomas J.

    2010-09-21

    Improvements to a Java based software package developed at Pacific Northwest National Laboratory (PNNL) for display and analysis of radioxenon spectra acquired by the International Monitoring System (IMS) are described here. The current version of the Radioxenon JavaViewer implements the region of interest (ROI) method for analysis of beta-gamma coincidence data. Upgrades to the Radioxenon JavaViewer will include routines to analyze high-purity germanium detector (HPGe) data, Standard Spectrum Method to analyze beta-gamma coincidence data and calibration routines to characterize beta-gamma coincidence detectors. These upgrades are currently under development; the status and initial results will be presented. Implementation of these routines into the JavaViewer and subsequent release is planned for FY 2011-2012.

  20. Recent advances in statistical energy analysis

    NASA Technical Reports Server (NTRS)

    Heron, K. H.

    1992-01-01

    Statistical Energy Analysis (SEA) has traditionally been developed using modal summation and averaging approach, and has led to the need for many restrictive SEA assumptions. The assumption of 'weak coupling' is particularly unacceptable when attempts are made to apply SEA to structural coupling. It is now believed that this assumption is more a function of the modal formulation rather than a necessary formulation of SEA. The present analysis ignores this restriction and describes a wave approach to the calculation of plate-plate coupling loss factors. Predictions based on this method are compared with results obtained from experiments using point excitation on one side of an irregular six-sided box structure. Conclusions show that the use and calculation of infinite transmission coefficients is the way forward for the development of a purely predictive SEA code.

  1. Advancing Usability Evaluation through Human Reliability Analysis

    SciTech Connect

    Ronald L. Boring; David I. Gertman

    2005-07-01

    This paper introduces a novel augmentation to the current heuristic usability evaluation methodology. The SPAR-H human reliability analysis method was developed for categorizing human performance in nuclear power plants. Despite the specialized use of SPAR-H for safety critical scenarios, the method also holds promise for use in commercial off-the-shelf software usability evaluations. The SPAR-H method shares task analysis underpinnings with human-computer interaction, and it can be easily adapted to incorporate usability heuristics as performance shaping factors. By assigning probabilistic modifiers to heuristics, it is possible to arrive at the usability error probability (UEP). This UEP is not a literal probability of error but nonetheless provides a quantitative basis to heuristic evaluation. When combined with a consequence matrix for usability errors, this method affords ready prioritization of usability issues.

  2. Advanced Techniques for Root Cause Analysis

    2000-09-19

    Five items make up this package, or can be used individually. The Chronological Safety Management Template utilizes a linear adaptation of the Integrated Safety Management System laid out in the form of a template that greatly enhances the ability of the analyst to perform the first step of any investigation which is to gather all pertinent facts and identify causal factors. The Problem Analysis Tree is a simple three (3) level problem analysis tree whichmore » is easier for organizations outside of WSRC to use. Another part is the Systemic Root Cause Tree. One of the most basic and unique features of Expanded Root Cause Analysis is the Systemic Root Cause portion of the Expanded Root Cause Pyramid. The Systemic Root Causes are even more basic than the Programmatic Root Causes and represent Root Causes that cut across multiple (if not all) programs in an organization. the Systemic Root Cause portion contains 51 causes embedded at the bottom level of a three level Systemic Root Cause Tree that is divided into logical, organizationally based categorie to assist the analyst. The Computer Aided Root Cause Analysis that allows the analyst at each level of the Pyramid to a) obtain a brief description of the cause that is being considered, b) record a decision that the item is applicable, c) proceed to the next level of the Pyramid to see only those items at the next level of the tree that are relevant to the particular cause that has been chosen, and d) at the end of the process automatically print out a summary report of the incident, the causal factors as they relate to the safety management system, the probable causes, apparent causes, Programmatic Root Causes and Systemic Root Causes for each causal factor and the associated corrective action.« less

  3. Advanced CMOS Radiation Effects Testing Analysis

    NASA Technical Reports Server (NTRS)

    Pellish, Jonathan Allen; Marshall, Paul W.; Rodbell, Kenneth P.; Gordon, Michael S.; LaBel, Kenneth A.; Schwank, James R.; Dodds, Nathaniel A.; Castaneda, Carlos M.; Berg, Melanie D.; Kim, Hak S.; Phan, Anthony M.; Seidleck, Christina M.

    2014-01-01

    Presentation at the annual NASA Electronic Parts and Packaging (NEPP) Program Electronic Technology Workshop (ETW). The material includes an update of progress in this NEPP task area over the past year, which includes testing, evaluation, and analysis of radiation effects data on the IBM 32 nm silicon-on-insulator (SOI) complementary metal oxide semiconductor (CMOS) process. The testing was conducted using test vehicles supplied by directly by IBM.

  4. Advanced CMOS Radiation Effects Testing and Analysis

    NASA Technical Reports Server (NTRS)

    Pellish, J. A.; Marshall, P. W.; Rodbell, K. P.; Gordon, M. S.; LaBel, K. A.; Schwank, J. R.; Dodds, N. A.; Castaneda, C. M.; Berg, M. D.; Kim, H. S.; Phan, A. M.; Seidleck, C. M.

    2014-01-01

    Presentation at the annual NASA Electronic Parts and Packaging (NEPP) Program Electronic Technology Workshop (ETW). The material includes an update of progress in this NEPP task area over the past year, which includes testing, evaluation, and analysis of radiation effects data on the IBM 32 nm silicon-on-insulator (SOI) complementary metal oxide semiconductor (CMOS) process. The testing was conducted using test vehicles supplied by directly by IBM.

  5. The application of spatial analysis based on rough set theory and hierarchical analysis

    NASA Astrophysics Data System (ADS)

    Lin, Zhiyong; Liang, Shuang

    2009-10-01

    As the development of the theory and technology of geographical information, Geographical Information System (GIS) has been widely applied in variety of industries. It usually refers to the analytical problem of multi-factor in GIS thematic application. In this field, the determination of factors' weight is a common and important problem. It actually deals the data when processing the spatial analysis applying GIS, for example, according to the importance of some factor, assign some value to it then process spatial overlay operation using the values and finally conclude some evaluation or result. In reality, there are many factors that affect the some kind of evaluation. Usually, we choose several more important factors as the evaluation criterion in order to make convenient for research. Then we assign some weight values to these factors and process spatial analysis then conclude some decision or evaluation to make support for decision-making. We can choose the factors that can make more impaction on the evaluation or decision-making using the method of Analytical Hierarchy Process (AHP). However, it has strong subjectivity of the factors' weight values assigned by this method. Rough set theory, which can effectively remove the impaction made by artificial factors, can make up the deficiency. It can make the spatial analysis more objective and more effective combining the two methods in GIS spatial analysis.

  6. Advances in Analysis of Longitudinal Data

    PubMed Central

    Gibbons, Robert D.; Hedeker, Donald; DuToit, Stephen

    2010-01-01

    In this review, we explore recent developments in the area of linear and nonlinear generalized mixed-effects regression models and various alternatives, including generalized estimating equations for analysis of longitudinal data. Methods are described for continuous and normally distributed as well as categorical (binary, ordinal, nominal) and count (Poisson) variables. Extensions of the model to three and four levels of clustering, multivariate outcomes, and incorporation of design weights are also described. Linear and nonlinear models are illustrated using an example involving a study of the relationship between mood and smoking. PMID:20192796

  7. Device for high spatial resolution chemical analysis of a sample and method of high spatial resolution chemical analysis

    SciTech Connect

    Van Berkel, Gary J.

    2015-10-06

    A system and method for analyzing a chemical composition of a specimen are described. The system can include at least one pin; a sampling device configured to contact a liquid with a specimen on the at least one pin to form a testing solution; and a stepper mechanism configured to move the at least one pin and the sampling device relative to one another. The system can also include an analytical instrument for determining a chemical composition of the specimen from the testing solution. In particular, the systems and methods described herein enable chemical analysis of specimens, such as tissue, to be evaluated in a manner that the spatial-resolution is limited by the size of the pins used to obtain tissue samples, not the size of the sampling device used to solubilize the samples coupled to the pins.

  8. Advanced Orion Optimized Laser System Analysis

    NASA Technical Reports Server (NTRS)

    1996-01-01

    Contractor shall perform a complete analysis of the potential of the solid state laser in the very long pulse mode (100 ns pulse width, 10-30 hz rep-rate) and in the very short pulse mode (100 ps pulse width 10-30 hz rep rate) concentrating on the operation of the device in the 'hot-rod' mode, where no active cooling the laser operation is attempted. Contractor's calculations shall be made of the phase aberrations which develop during the repped-pulse train, and the results shall feed into the adaptive optics analyses. The contractor shall devise solutions to work around ORION track issues. A final report shall be furnished to the MSFC COTR including all calculations and analysis of estimates of bulk phase and intensity aberration distribution in the laser output beam as a function of time during the repped-pulse train for both wave forms (high-energy/long-pulse, as well as low-energy/short-pulse). Recommendations shall be made for mitigating the aberrations by laser re-design and/or changes in operating parameters of optical pump sources and/or designs.

  9. Spatial Analysis of Stomach Cancer Incidence in Iran.

    PubMed

    Pakzad, Reza; Khani, Yousef; Pakzad, Iraj; Momenimovahed, Zohre; Mohammadian-Hashejani, Abdollah; Salehiniya, Hamid; Towhidi, Farhad; Makhsosi, Behnam Reza

    2016-01-01

    Stomach cancer, the fourth most common cancer and the second leading cause of cancer-related death through the world, is very common in parts of Iran. Geographic variation in the incidence of stomach cancer is due to many different factors. The aim of this study was to assess the geographical and spatial distribution of stomach cancer in Iran using data from the cancer registry program in Iran for the year 2009. The reported incidences of stomach cancer for different provinces were standardized to the world population structure. ArcGIS software was used to analyse the data. Hot spots and high risk areas were determined using spatial analysis (Getis-Ord Gi). Hot and cold spots were determined as more than or less than 2 standard deviations from the national average, respectively. A significance level of 0.10 was used for statistical judgment. In 2009, a total of 6,886 cases of stomach cancers were reported of which 4,891 were in men and 1,995 in women (standardized incidence rates of 19.2 and 10.0, respectively, per 100,000 population). The results showed that stomach cancer was concentrated mainly in northwest of the country in both men and women. In women, northwest provinces such as Ardebil, East Azerbaijan, West Azerbaijan, Gilan, and Qazvin were identified as hot spots (p<0.1). In men, all northwest provinces, Ardabil, East Azerbaijan, Gilan, Qazvin, Zanjan and Kurdistan, the incidences were higher than the national average and these were identified as hot spots (P<0.01). As stomach cancer is clustered in the northwest of the country, further epidemiological studies are needed to identify factors contributing to this concentration. PMID:27165203

  10. Study of academic achievements using spatial analysis tools

    NASA Astrophysics Data System (ADS)

    González, C.; Velilla, C.; Sánchez-Girón, V.

    2012-04-01

    In the 2010/12 academic year the College of Agricultural Engineering of the Technical University of Madrid implemented three new degrees all of them adapted to the European Space for Higher Education. These degrees are namely: Graduate in Agricultural Engineering and Science, Graduate in Food Engineering and Graduate in Agro-Environmental Engineering. A total of 382 new incoming students were finally registered and a survey study was carried out with these students about their academic achievement with the aim of finding the level of dependence among the following variables: the final mark in their secondary studies, the option followed in the secondary studies (Art, Science and Technology, and Humanities and Social Sciences), the mark obtained in the entering examination to the university and in which of the two opportunities per year this examination takes place the latter mark was obtained. Similarly, another group of 77 students were evaluated independently to the former group. These students were those entering the College in the previous academic year (2009/10) and decided to change their curricula to the new ones. Subsequently, using the tools of spatial analysis of geographic information systems, we analyzed the possible relationship between the success or failure at school and the socioeconomic profile of new students in a grade. For this purpose every student was referenced assigning UTM coordinates to their postal addresses. Furthermore, all students' secondary schools were geographically coded considering their typology (public, private, and private subsidized) and fares. Each student was represented by its average geometric point in order to be correlated to their respective record. Following this procedure a map of the performance of each student could be drawn. This map can be used as a reference system, as it includes variables as the distance from the student home to the College, that can be used as a tool to calculate the probability of success or

  11. Spatial resolution attainable in germanium detectors by pulse shape analysis

    SciTech Connect

    Blair, J., Bechtel, NV; Beckedahl, D.; Kammeraad, J.; Schmid, G., LLNL

    1998-05-01

    There are several applications for which it is desirable to calculate the locations and energies of individual gamma-ray interactions within a high purity germanium (HPGe) detector. These include gamma-ray imaging and Compton suppression. With a segmented detector this can be accomplished by analyzing the pulse shapes of the signals from the various segments. We examine the fundamental limits to the spatial resolution attainable with this approach. The primary source of error is the series noise of the field effect transistors (FETs) at the inputs of the charge amplifiers. We show how to calculate the noise spectral density at the output of the charge amplifiers due to an optimally selected FET. This calculation is based only on the detector capacitance and a noise constant for the FET technology. We show how to use this spectral density to calculate the uncertainties in parameters, such as interaction locations and energies, that are derived from pulse shape analysis using maximum likelihood estimation (MLE) applied to filtered and digitized recordings of the charge signals. Example calculations are given to illustrate our approach. Experimental results are given that demonstrate that one can construct complete systems, from detector through data analysis, that come near the theoretical limits.

  12. Signal Adaptive System for Space/Spatial-Frequency Analysis

    NASA Astrophysics Data System (ADS)

    Ivanović, Veselin N.; Jovanovski, Srdjan

    2010-12-01

    This paper outlines the development of a multiple-clock-cycle implementation (MCI) of a signal adaptive two-dimensional (2D) system for space/spatial-frequency (S/SF) signal analysis. The design is based on a method for improved S/SF representation of the analyzed 2D signals, also proposed here. The proposed MCI design optimizes critical design performances related to hardware complexity, making it a suitable system for real time implementation on an integrated chip. Additionally, the design allows the implemented system to take a variable number of clock cycles (CLKs) (the only necessary ones regarding desirable—2D Wigner distribution-presentation of autoterms) in different frequency-frequency points during the execution. This ability represents a major advantage of the proposed design which helps to optimize the time required for execution and produce an improved, cross-terms-free S/SF signal representation. The design has been verified by a field-programmable gate array (FPGA) circuit design, capable of performing S/SF analysis of 2D signals in real time.

  13. Spatial analysis of the tuberculosis treatment dropout, Buenos Aires, Argentina

    PubMed Central

    Herrero, María Belén; Arrossi, Silvina; Ramos, Silvina; Braga, Jose Ueleres

    2015-01-01

    OBJECTIVE Identify spatial distribution patterns of the proportion of nonadherence to tuberculosis treatment and its associated factors. METHODS We conducted an ecological study based on secondary and primary data from municipalities of the metropolitan area of Buenos Aires, Argentina. An exploratory analysis of the characteristics of the area and the distributions of the cases included in the sample (proportion of nonadherence) was also carried out along with a multifactor analysis by linear regression. The variables related to the characteristics of the population, residences and families were analyzed. RESULTS Areas with higher proportion of the population without social security benefits (p = 0.007) and of households with unsatisfied basic needs had a higher risk of nonadherence (p = 0.032). In addition, the proportion of nonadherence was higher in areas with the highest proportion of households with no public transportation within 300 meters (p = 0.070). CONCLUSIONS We found a risk area for the nonadherence to treatment characterized by a population living in poverty, with precarious jobs and difficult access to public transportation. PMID:26270011

  14. Spatial analysis of the tuberculosis treatment dropout, Buenos Aires, Argentina.

    PubMed

    Herrero, María Belén; Arrossi, Silvina; Ramos, Silvina; Braga, Jose Ueleres

    2015-01-01

    OBJECTIVE Identify spatial distribution patterns of the proportion of nonadherence to tuberculosis treatment and its associated factors. METHODS We conducted an ecological study based on secondary and primary data from municipalities of the metropolitan area of Buenos Aires, Argentina. An exploratory analysis of the characteristics of the area and the distributions of the cases included in the sample (proportion of nonadherence) was also carried out along with a multifactor analysis by linear regression. The variables related to the characteristics of the population, residences and families were analyzed. RESULTS Areas with higher proportion of the population without social security benefits (p = 0.007) and of households with unsatisfied basic needs had a higher risk of nonadherence (p = 0.032). In addition, the proportion of nonadherence was higher in areas with the highest proportion of households with no public transportation within 300 meters (p = 0.070). CONCLUSIONS We found a risk area for the nonadherence to treatment characterized by a population living in poverty, with precarious jobs and difficult access to public transportation. PMID:26270011

  15. Value analysis for advanced technology products

    NASA Astrophysics Data System (ADS)

    Soulliere, Mark

    2011-03-01

    Technology by itself can be wondrous, but buyers of technology factor in the price they have to pay along with performance in their decisions. As a result, the ``best'' technology may not always win in the marketplace when ``good enough'' can be had at a lower price. Technology vendors often set pricing by ``cost plus margin,'' or by competitors' offerings. What if the product is new (or has yet to be invented)? Value pricing is a methodology to price products based on the value generated (e.g. money saved) by using one product vs. the next best technical alternative. Value analysis can often clarify what product attributes generate the most value. It can also assist in identifying market forces outside of the control of the technology vendor that also influence pricing. These principles are illustrated with examples.

  16. Advanced stability analysis for laminar flow control

    NASA Technical Reports Server (NTRS)

    Orszag, S. A.

    1981-01-01

    Five classes of problems are addressed: (1) the extension of the SALLY stability analysis code to the full eighth order compressible stability equations for three dimensional boundary layer; (2) a comparison of methods for prediction of transition using SALLY for incompressible flows; (3) a study of instability and transition in rotating disk flows in which the effects of Coriolis forces and streamline curvature are included; (4) a new linear three dimensional instability mechanism that predicts Reynolds numbers for transition to turbulence in planar shear flows in good agreement with experiment; and (5) a study of the stability of finite amplitude disturbances in axisymmetric pipe flow showing the stability of this flow to all nonlinear axisymmetric disturbances.

  17. Performance analysis of advanced spacecraft TPS

    NASA Technical Reports Server (NTRS)

    Pitts, William C.

    1987-01-01

    The analysis on the feasibility for using metal hydrides in the thermal protection system of cryogenic tanks in space was based on the heat capacity of ice as the phase change material (PCM). It was found that with ice the thermal protection system weight could be reduced by, at most, about 20 percent over an all LI-900 insulation. For this concept to be viable, a metal hydride with considerably more capacity than water would be required. None were found. Special metal hydrides were developed for hydrogen fuel storage applications and it may be possible to do so for the current application. Until this appears promising further effort on this feasibility study does not seem warranted.

  18. Advanced analysis techniques for uranium assay

    SciTech Connect

    Geist, W. H.; Ensslin, Norbert; Carrillo, L. A.; Beard, C. A.

    2001-01-01

    Uranium has a negligible passive neutron emission rate making its assay practicable only with an active interrogation method. The active interrogation uses external neutron sources to induce fission events in the uranium in order to determine the mass. This technique requires careful calibration with standards that are representative of the items to be assayed. The samples to be measured are not always well represented by the available standards which often leads to large biases. A technique of active multiplicity counting is being developed to reduce some of these assay difficulties. Active multiplicity counting uses the measured doubles and triples count rates to determine the neutron multiplication (f4) and the product of the source-sample coupling ( C ) and the 235U mass (m). Since the 35U mass always appears in the multiplicity equations as the product of Cm, the coupling needs to be determined before the mass can be known. A relationship has been developed that relates the coupling to the neutron multiplication. The relationship is based on both an analytical derivation and also on empirical observations. To determine a scaling constant present in this relationship, known standards must be used. Evaluation of experimental data revealed an improvement over the traditional calibration curve analysis method of fitting the doubles count rate to the 235Um ass. Active multiplicity assay appears to relax the requirement that the calibration standards and unknown items have the same chemical form and geometry.

  19. Advances in carbonate exploration and reservoir analysis

    USGS Publications Warehouse

    Garland, J.; Neilson, J.; Laubach, S.E.; Whidden, Katherine J.

    2012-01-01

    The development of innovative techniques and concepts, and the emergence of new plays in carbonate rocks are creating a resurgence of oil and gas discoveries worldwide. The maturity of a basin and the application of exploration concepts have a fundamental influence on exploration strategies. Exploration success often occurs in underexplored basins by applying existing established geological concepts. This approach is commonly undertaken when new basins ‘open up’ owing to previous political upheavals. The strategy of using new techniques in a proven mature area is particularly appropriate when dealing with unconventional resources (heavy oil, bitumen, stranded gas), while the application of new play concepts (such as lacustrine carbonates) to new areas (i.e. ultra-deep South Atlantic basins) epitomizes frontier exploration. Many low-matrix-porosity hydrocarbon reservoirs are productive because permeability is controlled by fractures and faults. Understanding basic fracture properties is critical in reducing geological risk and therefore reducing well costs and increasing well recovery. The advent of resource plays in carbonate rocks, and the long-standing recognition of naturally fractured carbonate reservoirs means that new fracture and fault analysis and prediction techniques and concepts are essential.

  20. Spatial Analysis of Breast Cancer Incidence in Iran.

    PubMed

    Mahdavifar, Neda; Pakzad, Reza; Ghoncheh, Mahshid; Pakzad, Iraj; Moudi, Asieh; Salehiniya, Hamid

    2016-01-01

    Breast cancer (BC) is the most common cancer in females (27% of the total) and the main cause of death (16%) due to cancer in women in developed and developing countries. Variations in its incidence rate among geographical areas are due to various contributing factors. Since there have been a lack of studies on this topic in our country, the present spatial analysis of breast cancer incidence in Iran in 2009 was conducted using data from the national cancer registry system. The reported incidences of the disease were standardized according to the World Health Organization population and the direct method. Then data was inserted into the GIS software and finally, using the Hot Spot Analysis (Geties-Ord Gi), high-risk areas were drawn. Provinces with incidences 1.96 SD higher or lower than the national average were considered as hot spots or cold spots, at the significance level of 0.05%. In 2009, a total of 7,582 cases of BC occurred in Iran. The annual incidence was 33.2 per hundred thousand people. Our study showed that the highest incidence of BC in women occurred in the central provinces of the country, Tehran, Isfahan, Yazd, Markazi and Fars. The results of hot spots analysis showed that the distribution of high-risk BC was focused in central parts of Iran, especially Isfahan province (p <0.01). The other provinces were not significantly different from the national average. The higher incidence in central provinces may be due to greater exposure to carcinogens in urban areas, a Western lifestyle and high prevalence of other risk factors. Further epidemiological studies about the etiology and early detection of BC are essential. PMID:27165209

  1. A frequency domain analysis of spatial organization of epicardial maps.

    PubMed

    Sih, H J; Sahakian, A V; Arentzen, C E; Swiryn, S

    1995-07-01

    Mapping of organized rhythms like sinus rhythm uses activation times from individual electrograms, and often assumes that the map for a single activation is similar to maps for subsequent activations. However, during fibrillation, activation times and electrograms are not easy to define, and maps change from activation to activation. Volume and complexity of data make analysis of more than a few seconds of fibrillation difficult. Magnitude Squared Coherence (MSC), a frequency domain measure of the phase consistency between two signals, can be used to help interpret longer data segments without defining activation times or electrograms. Sinus rhythm, flutter, and fibrillation in humans and swine were mapped with an array of unipolar electrodes (2.5 mm apart) at 240 sites on the atrial or ventricular epicardium. Four-second data segments were analyzed. One site near the center of the array was chosen ad hoc as a reference. MSC maps were made by measuring mean MSC from 0-50 Hz between every point in the array relative to the reference. Isocoherence contours were drawn. The effects of bias in the coherence estimate due to misalignment were investigated. Average MSC versus distance from the reference was measured for all rhythms. Results indicate that in a 4-s segment of fibrillation, there can exist some phase consistency between one site and the reference and little or none between a second site and the reference even when both sites are equidistant from the reference. In fibrillation, isocoherence contours are elongated and irregularly shaped, reflecting long-term, but nonuniform, spatial organization. That is, activation during fibrillation cannot be considered as random over a 4-s interval. Bias in the coherence estimate due to misalignment is significant for sinus rhythm and flutter, but can be corrected by manual realignment. Average MSC drops with distance for all rhythms, being most pronounced for fibrillation, MSC maps may provide insights into long

  2. Advanced Remote-sensing Imaging Emission Spectrometer (ARIES): AIRS Spectral Resolution with MODIS Spatial Resolution

    NASA Technical Reports Server (NTRS)

    Pagano, Thomas S.; Chahine, Moustafa T.; Aumann, Hartmut H.; OCallaghan, Fred G.; Broberg, Steve E.

    2006-01-01

    This paper describes a space based instrument concept that will provide scientists with data needed to support key ongoing and future Earth System Science investigations. The measurement approach builds on the observations made by AIRS and MODIS and exceeds their capability with improved spatial and spectral resolution. This paper describes the expected products and the instrument concept that can meet those requirements.

  3. Technology Advancements in the Next Generation of Domain Agnostic Spatial Data Infrastructures

    NASA Astrophysics Data System (ADS)

    Golodoniuc, Pavel; Rankine, Terry; Box, Paul; Atkinson, Rob; Kostanski, Laura

    2013-04-01

    Spatial Data Infrastructures (SDI) are typically composed of a suite of products focused on improving spatial information discovery and access. Proliferation of SDI initiatives has caused the "Yet Another Portal" (YAP) syndrome to emerge with each initiative providing a new mechanism for cataloguing and enabling users to search for spatial information resources. Often coarse-grained and incomplete metadata information available via these SDIs renders them to being analogous with an antiquated library catalogue. We posit that the successful use of SDI resources requires attention to be focused on various semantic aspects of the information contained within - particularly the information models and vocabularies. Currently it is common for understanding of these models and vocabularies to be built into portals. This does not enhance interoperability between SDIs, nor does this provide a means for referencing or searching for a specific feature (e.g., the City of Sydney) without first knowing the location of the information source for the feature and the form in which it is represented. SDI interfaces, such as OGC WFS, provide data from a spatial representation perspective, but do not provide identifiers that can easily be cited or used across system boundaries. The lack of mechanisms to provide stable identifiers of a feature renders it permanently scoped to a particular dataset. The other three important aspects that are commonly lacking in SDIs are the inadequate handling of feature level metadata that is commonly not sufficient enough for more than the most basic data discovery; features delivered through SDI are not well integrated with information systems that deliver statistical information about those features; and, importantly there are inadequate mechanisms to reconcile and associate multiple identities and representations of the same real world feature. In this paper we present an extended view of an SDI architecture with integrated support for information

  4. Current practices in the spatial analysis of cancer: flies in the ointment

    PubMed Central

    Jacquez, Geoffrey M

    2004-01-01

    While many lessons have been learned from the spatial analysis of cancer, there are several caveats that apply to many, if not all such analyses. As "flies in the ointment", these can substantially detract from a spatial analysis, and if not accounted for, can lead to weakened and erroneous conclusions. This paper discusses several assumptions and limitations of spatial analysis, identifies problems of scientific inference, and concludes with potential solutions and future directions. PMID:15479473

  5. Advanced computational tools for 3-D seismic analysis

    SciTech Connect

    Barhen, J.; Glover, C.W.; Protopopescu, V.A.

    1996-06-01

    The global objective of this effort is to develop advanced computational tools for 3-D seismic analysis, and test the products using a model dataset developed under the joint aegis of the United States` Society of Exploration Geophysicists (SEG) and the European Association of Exploration Geophysicists (EAEG). The goal is to enhance the value to the oil industry of the SEG/EAEG modeling project, carried out with US Department of Energy (DOE) funding in FY` 93-95. The primary objective of the ORNL Center for Engineering Systems Advanced Research (CESAR) is to spearhead the computational innovations techniques that would enable a revolutionary advance in 3-D seismic analysis. The CESAR effort is carried out in collaboration with world-class domain experts from leading universities, and in close coordination with other national laboratories and oil industry partners.

  6. A book review of Spatial data analysis in ecology and agriculture using R

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Spatial Data Analysis in Ecology and Agriculture Using R is a valuable resource to assist agricultural and ecological researchers with spatial data analyses using the R statistical software(www.r-project.org). Special emphasis is on spatial data sets; how-ever, the text also provides ample guidance ...

  7. Learning Geospatial Analysis Skills with Consumer-Grade GPS Receivers and Low Cost Spatial Analysis Software

    ERIC Educational Resources Information Center

    Linehan, Peter E.

    2006-01-01

    Spatial analysis technologies are increasingly important tools for all aspects of forest resource management. Field work previously accomplished with map, compass, and engineers' scale is now being augmented, or superseded, by the use of GPS and GIS. Professional-grade GPS receivers and commercial GIS software are preferred for their accuracy and…

  8. Spatial Microsimulation for Rural Policy Analysis in Ireland: The Implications of CAP Reforms for the National Spatial Strategy

    ERIC Educational Resources Information Center

    Ballas, D.; Clarke, G. P.; Wiemers, E.

    2006-01-01

    Microsimulation attempts to describe economic and social events by modelling the behaviour of individual agents. These models have proved useful in evaluating the impact of policy changes at the micro level. Spatial microsimulation models contain geographic information and allow for a regional or local approach to policy analysis. This paper…

  9. METHODS ADVANCEMENT FOR MILK ANALYSIS: THE MAMA STUDY

    EPA Science Inventory

    The Methods Advancement for Milk Analysis (MAMA) study was designed by US EPA and CDC investigators to provide data to support the technological and study design needs of the proposed National Children=s Study (NCS). The NCS is a multi-Agency-sponsored study, authorized under the...

  10. Polybrominated Diphenyl Ethers in Dryer Lint: An Advanced Analysis Laboratory

    ERIC Educational Resources Information Center

    Thompson, Robert Q.

    2008-01-01

    An advanced analytical chemistry laboratory experiment is described that involves environmental analysis and gas chromatography-mass spectrometry. Students analyze lint from clothes dryers for traces of flame retardant chemicals, polybrominated diphenylethers (PBDEs), compounds receiving much attention recently. In a typical experiment, ng/g…

  11. A Meta-Analysis of Advanced Organizer Studies.

    ERIC Educational Resources Information Center

    Stone, Carol Leth

    1983-01-01

    Twenty-nine reports yielding 112 studies were analyzed with Glass's meta-analysis technique, and results were compared with predictions from Ausubel's model of assimilative learning. Overall, advance organizers were shown to be associated with increased learning and retention of material to be learned. (Author)

  12. Advanced GIS Exercise: Predicting Rainfall Erosivity Index Using Regression Analysis

    ERIC Educational Resources Information Center

    Post, Christopher J.; Goddard, Megan A.; Mikhailova, Elena A.; Hall, Steven T.

    2006-01-01

    Graduate students from a variety of agricultural and natural resource fields are incorporating geographic information systems (GIS) analysis into their graduate research, creating a need for teaching methodologies that help students understand advanced GIS topics for use in their own research. Graduate-level GIS exercises help students understand…

  13. NASTRAN documentation for flutter analysis of advanced turbopropellers

    NASA Technical Reports Server (NTRS)

    Elchuri, V.; Gallo, A. M.; Skalski, S. C.

    1982-01-01

    An existing capability developed to conduct modal flutter analysis of tuned bladed-shrouded discs was modified to facilitate investigation of the subsonic unstalled flutter characteristics of advanced turbopropellers. The modifications pertain to the inclusion of oscillatory modal aerodynamic loads of blades with large (backward and forward) varying sweep.

  14. A spatial, kinematical, and dynamical analysis of Abell 400

    NASA Technical Reports Server (NTRS)

    Beers, Timothy C.; Gebhardt, Karl; Huchra, John P.; Forman, William; Jones, Christine; Bothun, Gregory D.

    1992-01-01

    The paper presents a detailed spatial, kinematical, and dynamical analysis for the cluster A400, based on a nearly complete redshift survey of bright galaxies within 1 Mpc of the cluster center. A dispersed component with a high fraction of spiral galaxies at a velocity of 8200 km/s, and a background group with a mean velocity of 13,400 km/s are identified. It is proposed that the main body of A400 is composed of at least two individual subclusters. If subclustering is ignored, the derived dispersion of the 88 galaxies with measured velocities within 4000 km/s of the bright dumbbell galaxy near the cluster center is 702 km/s. When kinematic information is used to split A400 into likely subclusters, the velocity dispersions of the individual units which make up this cluster are on the order of 200-300 km/s. If A400 is considered a single entity, the inferred blue mass-to-light ratio is 1210 solar masses/solar luminosities. It is argued that A400 is an example of a presently occurring merger, and that the individual components of the dumbbell galaxy were once individual D galaxies within the premerger subclusters.

  15. Advanced stress analysis methods applicable to turbine engine structures

    NASA Technical Reports Server (NTRS)

    Pian, T. H. H.

    1985-01-01

    Advanced stress analysis methods applicable to turbine engine structures are investigated. Constructions of special elements which containing traction-free circular boundaries are investigated. New versions of mixed variational principle and version of hybrid stress elements are formulated. A method is established for suppression of kinematic deformation modes. semiLoof plate and shell elements are constructed by assumed stress hybrid method. An elastic-plastic analysis is conducted by viscoplasticity theory using the mechanical subelement model.

  16. Recent Advances in Multidisciplinary Analysis and Optimization, part 3

    NASA Technical Reports Server (NTRS)

    Barthelemy, Jean-Francois M. (Editor)

    1989-01-01

    This three-part document contains a collection of technical papers presented at the Second NASA/Air Force Symposium on Recent Advances in Multidisciplinary Analysis and Optimization, held September 28-30, 1988 in Hampton, Virginia. The topics covered include: aircraft design, aeroelastic tailoring, control of aeroelastic structures, dynamics and control of flexible structures, structural design, design of large engineering systems, application of artificial intelligence, shape optimization, software development and implementation, and sensitivity analysis.

  17. Recent Advances in Multidisciplinary Analysis and Optimization, part 1

    NASA Technical Reports Server (NTRS)

    Barthelemy, Jean-Francois M. (Editor)

    1989-01-01

    This three-part document contains a collection of technical papers presented at the Second NASA/Air Force Symposium on Recent Advances in Multidisciplinary Analysis and Optimization, held September 28-30, 1988 in Hampton, Virginia. The topics covered include: helicopter design, aeroelastic tailoring, control of aeroelastic structures, dynamics and control of flexible structures, structural design, design of large engineering systems, application of artificial intelligence, shape optimization, software development and implementation, and sensitivity analysis.

  18. Recent Advances in Multidisciplinary Analysis and Optimization, part 2

    NASA Technical Reports Server (NTRS)

    Barthelemy, Jean-Francois M. (Editor)

    1989-01-01

    This three-part document contains a collection of technical papers presented at the Second NASA/Air Force Symposium on Recent Advances in Multidisciplinary Analysis and Optimization, held September 28-30, 1988 in Hampton, Virginia. The topics covered include: helicopter design, aeroelastic tailoring, control of aeroelastic structures, dynamics and control of flexible structures, structural design, design of large engineering systems, application of artificial intelligence, shape optimization, software development and implementation, and sensitivity analysis.

  19. Analysis of Spatial Voting Patterns: An Approach in Political Socialization

    ERIC Educational Resources Information Center

    Klimasewski, Ted

    1973-01-01

    Passage of the 26th Amendment gave young adults the right to vote. This study attempts to further student understanding of the electoral process by presenting a method for analyzing spatial voting patterns. The spatial emphasis adds another dimension to the temporal and behavioral-structural approaches in studying the American electoral system.…

  20. A Principal Components Analysis of Dynamic Spatial Memory Biases

    ERIC Educational Resources Information Center

    Motes, Michael A.; Hubbard, Timothy L.; Courtney, Jon R.; Rypma, Bart

    2008-01-01

    Research has shown that spatial memory for moving targets is often biased in the direction of implied momentum and implied gravity, suggesting that representations of the subjective experiences of these physical principles contribute to such biases. The present study examined the association between these spatial memory biases. Observers viewed…

  1. Situated student learning and spatial informational analysis for environmental problems

    NASA Astrophysics Data System (ADS)

    Olsen, Timothy Paul

    Ninth and tenth grade high school Biology student research teams used spatial information analysis tools to site a prairie restoration plot on a 55 acre campus during a four-week environment unit. Students made use of innovative technological practices by applying geographic information systems (GIS) approaches to solving environmental and land use problems. Student learning was facilitated by starting with the students' initial conceptions of computing, local landscape and biological environment, and then by guiding them through a problem-based science project process. The project curriculum was framed by the perspective of legitimate peripheral participation (Lave & Wenger, 1991) where students were provided with learning opportunities designed to allow them to act like GIS practitioners. Sociocultural lenses for learning were employed to create accounts of human mental processes that recognize the essential relationship between these processes and their cultural, historical, and institutional settings (Jacob, 1997; Wertsch, 1991). This research investigated how student groups' meaning-making actions were mediated by GIS tools on the periphery of a scientific community of practice. Research observations focused on supporting interpretations of learners' socially constructed actions and the iterative building of assertions from multiple sources. These included the artifacts students produced, the tools they used, the cultural contexts that constrained their activity, and how people begin to adopt ways of speaking (speech genres) of the referent community to negotiate meanings and roles. Students gathered field observations and interpreted attributes of landscape entities from the GIS data to advocate for an environmental decision. However, even while gaining proficiencies with GIS tools, most students did not begin to appropriate roles from the GIS community of practice. Students continued to negotiate their project actions simply as school exercises motivated by

  2. Strong topographic sheltering effects lead to spatially complex treeline advance and increased forest density in a subtropical mountain region.

    PubMed

    Greenwood, Sarah; Chen, Jan-Chang; Chen, Chaur-Tzuhn; Jump, Alistair S

    2014-12-01

    Altitudinal treelines are typically temperature limited such that increasing temperatures linked to global climate change are causing upslope shifts of treelines worldwide. While such elevational increases are readily predicted based on shifting isotherms, at the regional level the realized response is often much more complex, with topography and local environmental conditions playing an important modifying role. Here, we used repeated aerial photographs in combination with forest inventory data to investigate changes in treeline position in the Central Mountain Range of Taiwan over the last 60 years. A highly spatially variable upslope advance of treeline was identified in which topography is a major driver of both treeline form and advance. The changes in treeline position that we observed occurred alongside substantial increases in forest density, and lead to a large increase in overall forest area. These changes will have a significant impact on carbon stocking in the high altitude zone, while the concomitant decrease in alpine grassland area is likely to have negative implications for alpine species. The complex and spatially variable changes that we report highlight the necessity for considering local factors such as topography when attempting to predict species distributional responses to warming climate. PMID:25141823

  3. Isolation and analysis of ginseng: advances and challenges

    PubMed Central

    Wang, Chong-Zhi

    2011-01-01

    Ginseng occupies a prominent position in the list of best-selling natural products in the world. Because of its complex constituents, multidisciplinary techniques are needed to validate the analytical methods that support ginseng’s use worldwide. In the past decade, rapid development of technology has advanced many aspects of ginseng research. The aim of this review is to illustrate the recent advances in the isolation and analysis of ginseng, and to highlight their new applications and challenges. Emphasis is placed on recent trends and emerging techniques. The current article reviews the literature between January 2000 and September 2010. PMID:21258738

  4. Issues affecting advanced passive light-water reactor safety analysis

    SciTech Connect

    Beelman, R.J.; Fletcher, C.D.; Modro, S.M.

    1992-08-01

    Next generation commercial reactor designs emphasize enhanced safety through improved safety system reliability and performance by means of system simplification and reliance on immutable natural forces for system operation. Simulating the performance of these safety systems will be central to analytical safety evaluation of advanced passive reactor designs. Yet the characteristically small driving forces of these safety systems pose challenging computational problems to current thermal-hydraulic systems analysis codes. Additionally, the safety systems generally interact closely with one another, requiring accurate, integrated simulation of the nuclear steam supply system, engineered safeguards and containment. Furthermore, numerical safety analysis of these advanced passive reactor designs wig necessitate simulation of long-duration, slowly-developing transients compared with current reactor designs. The composite effects of small computational inaccuracies on induced system interactions and perturbations over long periods may well lead to predicted results which are significantly different than would otherwise be expected or might actually occur. Comparisons between the engineered safety features of competing US advanced light water reactor designs and analogous present day reactor designs are examined relative to the adequacy of existing thermal-hydraulic safety codes in predicting the mechanisms of passive safety. Areas where existing codes might require modification, extension or assessment relative to passive safety designs are identified. Conclusions concerning the applicability of these codes to advanced passive light water reactor safety analysis are presented.

  5. Issues affecting advanced passive light-water reactor safety analysis

    SciTech Connect

    Beelman, R.J.; Fletcher, C.D.; Modro, S.M.

    1992-01-01

    Next generation commercial reactor designs emphasize enhanced safety through improved safety system reliability and performance by means of system simplification and reliance on immutable natural forces for system operation. Simulating the performance of these safety systems will be central to analytical safety evaluation of advanced passive reactor designs. Yet the characteristically small driving forces of these safety systems pose challenging computational problems to current thermal-hydraulic systems analysis codes. Additionally, the safety systems generally interact closely with one another, requiring accurate, integrated simulation of the nuclear steam supply system, engineered safeguards and containment. Furthermore, numerical safety analysis of these advanced passive reactor designs wig necessitate simulation of long-duration, slowly-developing transients compared with current reactor designs. The composite effects of small computational inaccuracies on induced system interactions and perturbations over long periods may well lead to predicted results which are significantly different than would otherwise be expected or might actually occur. Comparisons between the engineered safety features of competing US advanced light water reactor designs and analogous present day reactor designs are examined relative to the adequacy of existing thermal-hydraulic safety codes in predicting the mechanisms of passive safety. Areas where existing codes might require modification, extension or assessment relative to passive safety designs are identified. Conclusions concerning the applicability of these codes to advanced passive light water reactor safety analysis are presented.

  6. Spatial analysis on China's regional air pollutants and CO2 emissions: emission pattern and regional disparity

    NASA Astrophysics Data System (ADS)

    Dong, Liang; Liang, Hanwei

    2014-08-01

    China has suffered from serious air pollution and CO2 emission. Challenges of emission reduction policy not only come from technology advancement, but also generate from the fact that, China has pronounced disparity between regions, in geographical and socioeconomic. How to deal with regional disparity is important to achieve the reduction target effectively and efficiently. This research conducts a spatial analysis on the emission patterns of three air pollutants named SO2, NOx and PM2.5, and CO2, in China's 30 provinces, applied with spatial auto-correlation and multi regression modeling. We further analyze the regional disparity and inequity issues with the approach of Lorenz curve and Gini coefficient. Results highlight that: there is evident cluster effect for the regional air pollutants and CO2 emissions. While emission amount increases from western regions to eastern regions, the emission per GDP is in inverse trend. The Lorenz curve shows an even larger unequal distribution of GDP/emissions than GDP/capita in 30 regions. Certain middle and western regions suffers from a higher emission with lower GDP, which reveal the critical issue of emission leakage. Future policy making to address such regional disparity is critical so as to promote the emission control policy under the “equity and efficiency” principle.

  7. Advanced Post-Irradiation Examination Capabilities Alternatives Analysis Report

    SciTech Connect

    Jeff Bryan; Bill Landman; Porter Hill

    2012-12-01

    An alternatives analysis was performed for the Advanced Post-Irradiation Capabilities (APIEC) project in accordance with the U.S. Department of Energy (DOE) Order DOE O 413.3B, “Program and Project Management for the Acquisition of Capital Assets”. The Alternatives Analysis considered six major alternatives: ? No Action ? Modify Existing DOE Facilities – capabilities distributed among multiple locations ? Modify Existing DOE Facilities – capabilities consolidated at a few locations ? Construct New Facility ? Commercial Partnership ? International Partnerships Based on the alternatives analysis documented herein, it is recommended to DOE that the advanced post-irradiation examination capabilities be provided by a new facility constructed at the Materials and Fuels Complex at the Idaho National Laboratory.

  8. "ATLAS" Advanced Technology Life-cycle Analysis System

    NASA Technical Reports Server (NTRS)

    Lollar, Louis F.; Mankins, John C.; ONeil, Daniel A.

    2004-01-01

    Making good decisions concerning research and development portfolios-and concerning the best systems concepts to pursue - as early as possible in the life cycle of advanced technologies is a key goal of R&D management This goal depends upon the effective integration of information from a wide variety of sources as well as focused, high-level analyses intended to inform such decisions Life-cycle Analysis System (ATLAS) methodology and tool kit. ATLAS encompasses a wide range of methods and tools. A key foundation for ATLAS is the NASA-created Technology Readiness. The toolkit is largely spreadsheet based (as of August 2003). This product is being funded by the Human and Robotics The presentation provides a summary of the Advanced Technology Level (TRL) systems Technology Program Office, Office of Exploration Systems, NASA Headquarters, Washington D.C. and is being integrated by Dan O Neil of the Advanced Projects Office, NASA/MSFC, Huntsville, AL

  9. Develop Advanced Nonlinear Signal Analysis Topographical Mapping System

    NASA Technical Reports Server (NTRS)

    Jong, Jen-Yi

    1997-01-01

    During the development of the SSME, a hierarchy of advanced signal analysis techniques for mechanical signature analysis has been developed by NASA and AI Signal Research Inc. (ASRI) to improve the safety and reliability for Space Shuttle operations. These techniques can process and identify intelligent information hidden in a measured signal which is often unidentifiable using conventional signal analysis methods. Currently, due to the highly interactive processing requirements and the volume of dynamic data involved, detailed diagnostic analysis is being performed manually which requires immense man-hours with extensive human interface. To overcome this manual process, NASA implemented this program to develop an Advanced nonlinear signal Analysis Topographical Mapping System (ATMS) to provide automatic/unsupervised engine diagnostic capabilities. The ATMS will utilize a rule-based Clips expert system to supervise a hierarchy of diagnostic signature analysis techniques in the Advanced Signal Analysis Library (ASAL). ASAL will perform automatic signal processing, archiving, and anomaly detection/identification tasks in order to provide an intelligent and fully automated engine diagnostic capability. The ATMS has been successfully developed under this contract. In summary, the program objectives to design, develop, test and conduct performance evaluation for an automated engine diagnostic system have been successfully achieved. Software implementation of the entire ATMS system on MSFC's OISPS computer has been completed. The significance of the ATMS developed under this program is attributed to the fully automated coherence analysis capability for anomaly detection and identification which can greatly enhance the power and reliability of engine diagnostic evaluation. The results have demonstrated that ATMS can significantly save time and man-hours in performing engine test/flight data analysis and performance evaluation of large volumes of dynamic test data.

  10. Advances in catchment scale bank erosion modelling - quantifying the improved representation of temporal and spatial variability

    NASA Astrophysics Data System (ADS)

    Janes, Victoria; Holman, Ian; O'Donnell, Greg; Birkinshaw, Stephen; Kilsby, Chris

    2015-04-01

    Channel bank erosion processes are influenced by numerous factors resulting in high spatial and temporal variability of sediment production. The representation of channel bank erosion is overly simplistic within most catchment models, despite its significance to catchment sediment budgets. Within this study, the physically-based distributed SHETRAN model is modified to incorporate bank vegetation and channel sinuosity factors that influence spatial and temporal bank erosion rates. The modified model simulates the temporal variation of bank erosion in response to high magnitude events with the potential to remove bank vegetation and de-stabilise banks, thereby increasing erodibility. As vegetation re-establishes, simulated bank erodibility decreases. During the recovery period, banks have increased vulnerability to further high magnitude events that will result in increased bank erosion. This enables the model to represent the impact of flood clustering on sediment generation. The modified model also represents the spatial variation of bank erosion as a result of varying channel planform. Channel geometry has also been linked to bank erosion rates as a result of flow circulation within channels. Channel sinuosity shows a non-linear relationship with bank erosion, with bank erosion increasing up to a threshold value of sinuosity and decreasing as sinuosity increases above this point. The original and modified models have been applied to the Eden catchment in north east England. Bank erosion data derived from a GIS overlay methodology covering 150 years has been used to validate the models, indicating annual sediment generation from bank erosion processes within the catchment is 410-4500 t yr-1, equivalent to 2-11% of the catchment sediment budget. Comparison of the original and modified models highlights the improved ability of the modified model to simulate annual variation of bank eroded sediment production; annual sediment production from the original model ranged

  11. Inverse spatial principal component analysis for geophysical survey data interpolation

    NASA Astrophysics Data System (ADS)

    Li, Qingmou; Dehler, Sonya A.

    2015-04-01

    The starting point for data processing, visualization, and overlay with other data sources in geological applications often involves building a regular grid by interpolation of geophysical measurements. Typically, the sampling interval along survey lines is much higher than the spacing between survey lines because the geophysical recording system is able to operate with a high sampling rate, while the costs and slower speeds associated with operational platforms limit line spacing. However, currently available interpolating methods often smooth data observed with higher sampling rate along a survey line to accommodate the lower spacing across lines, and much of the higher resolution information is not captured in the interpolation process. In this approach, a method termed as the inverse spatial principal component analysis (isPCA) is developed to address this problem. In the isPCA method, a whole profile observation as well as its line position is handled as an entity and a survey collection of line entities is analyzed for interpolation. To test its performance, the developed isPCA method is used to process a simulated airborne magnetic survey from an existing magnetic grid offshore the Atlantic coast of Canada. The interpolation results using the isPCA method and other methods are compared with the original survey grid. It is demonstrated that the isPCA method outperforms the Inverse Distance Weighting (IDW), Kriging (Geostatistical), and MINimum Curvature (MINC) interpolation methods in retaining detailed anomaly structures and restoring original values. In a second test, a high resolution magnetic survey offshore Cape Breton, Nova Scotia, Canada, was processed and the results are compared with other geological information. This example demonstrates the effective performance of the isPCA method in basin structure identification.

  12. Structural Analysis of Dusty Plasma Formations Based on Spatial Spectra

    SciTech Connect

    Khakhaev, A. D.; Luizova, L. A.; Piskunov, A. A.; Podryadchikov, S. F.; Soloviev, A. V.

    2008-09-07

    Some advantages of studying the structure of dusty plasma formations using spatial spectra are illustrated by simulated experiments and by processing actual images of dusty structures in dc glow discharge in inert and molecular gases.

  13. Spatial Dependence and Heterogeneity in Bayesian Factor Analysis: A Cross-National Investigation of Schwartz Values

    ERIC Educational Resources Information Center

    Stakhovych, Stanislav; Bijmolt, Tammo H. A.; Wedel, Michel

    2012-01-01

    In this article, we present a Bayesian spatial factor analysis model. We extend previous work on confirmatory factor analysis by including geographically distributed latent variables and accounting for heterogeneity and spatial autocorrelation. The simulation study shows excellent recovery of the model parameters and demonstrates the consequences…

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

    NASA Astrophysics Data System (ADS)

    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.

  15. Geologic spatial analysis. 1988 performance report, August 30, 1987--January 30, 1989

    SciTech Connect

    Thiessen, R.L.; Eliason, J.R.

    1989-12-31

    This report describes the development of geologic spatial analysis research which focuses on conducting comprehensive three-dimensional analysis of regions using geologic data sets that can be referenced by latitude, longitude, and elevation/depth. (CBS)

  16. An advanced image processing method to improve the spatial resolution of ion radiographies.

    PubMed

    Krah, N; Testa, M; Brons, S; Jäkel, O; Parodi, K; Voss, B; Rinaldi, I

    2015-11-01

    We present an optimization method to improve the spatial resolution and the water equivalent thickness (WET) accuracy of ion radiographies. The method is designed for imaging systems measuring for each actively scanned beam spot the lateral position of the pencil beam and at the same time the Bragg curve (behind the target) in discrete steps without relying on tracker detectors to determine the ion trajectory before and after the irradiated volume. Specifically, the method was used for an imaging set-up consisting of a stack of 61 parallel-plate ionization chambers (PPIC) interleaved with absorber plates of polymethyl methacrylate (PMMA) working as a range telescope. The method uses not only the Bragg peak position, but approximates the entire measured Bragg curve as a superposition of differently shifted Bragg curves. Their relative weights allow to reconstruct the distribution of thickness around each scan spot of a heterogeneous phantom. The approach also allows merging the ion radiography with the geometric information of a co-registered x-ray radiography in order to increase its spatial resolution. The method was tested using Monte Carlo simulated and experimental proton radiographies of a PMMA step phantom and an anthropomorphic head phantom. For the step phantom, the effective spatial resolution was found to be 6 and 4 times higher than the nominal resolution for the simulated and experimental radiographies, respectively. For the head phantom, a gamma index was calculated to quantify the conformity of the simulated proton radiographies with a digitally reconstructed radiography (DRR) obtained from an x-ray CT and properly converted into WET. For a distance-to-agreement (DTA) of 2.5 mm and a relative WET difference (RWET) of 2.5%, the passing ratio was 100%/85% for the optimized/non-optimized case, respectively. When the optimized proton radiography was merged with the co-registered DRR, the passing ratio was 100% at DTA  =  1.3 mm and RWET

  17. An advanced image processing method to improve the spatial resolution of ion radiographies

    NASA Astrophysics Data System (ADS)

    Krah, N.; Testa, M.; Brons, S.; Jäkel, O.; Parodi, K.; Voss, B.; Rinaldi, I.

    2015-11-01

    We present an optimization method to improve the spatial resolution and the water equivalent thickness (WET) accuracy of ion radiographies. The method is designed for imaging systems measuring for each actively scanned beam spot the lateral position of the pencil beam and at the same time the Bragg curve (behind the target) in discrete steps without relying on tracker detectors to determine the ion trajectory before and after the irradiated volume. Specifically, the method was used for an imaging set-up consisting of a stack of 61 parallel-plate ionization chambers (PPIC) interleaved with absorber plates of polymethyl methacrylate (PMMA) working as a range telescope. The method uses not only the Bragg peak position, but approximates the entire measured Bragg curve as a superposition of differently shifted Bragg curves. Their relative weights allow to reconstruct the distribution of thickness around each scan spot of a heterogeneous phantom. The approach also allows merging the ion radiography with the geometric information of a co-registered x-ray radiography in order to increase its spatial resolution. The method was tested using Monte Carlo simulated and experimental proton radiographies of a PMMA step phantom and an anthropomorphic head phantom. For the step phantom, the effective spatial resolution was found to be 6 and 4 times higher than the nominal resolution for the simulated and experimental radiographies, respectively. For the head phantom, a gamma index was calculated to quantify the conformity of the simulated proton radiographies with a digitally reconstructed radiography (DRR) obtained from an x-ray CT and properly converted into WET. For a distance-to-agreement (DTA) of 2.5 mm and a relative WET difference (RWET) of 2.5%, the passing ratio was 100%/85% for the optimized/non-optimized case, respectively. When the optimized proton radiography was merged with the co-registered DRR, the passing ratio was 100% at DTA  =  1.3 mm and RWET

  18. Linking Advanced Visualization and MATLAB for the Analysis of 3D Gene Expression Data

    SciTech Connect

    Ruebel, Oliver; Keranen, Soile V.E.; Biggin, Mark; Knowles, David W.; Weber, Gunther H.; Hagen, Hans; Hamann, Bernd; Bethel, E. Wes

    2011-03-30

    Three-dimensional gene expression PointCloud data generated by the Berkeley Drosophila Transcription Network Project (BDTNP) provides quantitative information about the spatial and temporal expression of genes in early Drosophila embryos at cellular resolution. The BDTNP team visualizes and analyzes Point-Cloud data using the software application PointCloudXplore (PCX). To maximize the impact of novel, complex data sets, such as PointClouds, the data needs to be accessible to biologists and comprehensible to developers of analysis functions. We address this challenge by linking PCX and Matlab via a dedicated interface, thereby providing biologists seamless access to advanced data analysis functions and giving bioinformatics researchers the opportunity to integrate their analysis directly into the visualization application. To demonstrate the usefulness of this approach, we computationally model parts of the expression pattern of the gene even skipped using a genetic algorithm implemented in Matlab and integrated into PCX via our Matlab interface.

  19. Neighborhood social capital and crime victimization: comparison of spatial regression analysis and hierarchical regression analysis.

    PubMed

    Takagi, Daisuke; Ikeda, Ken'ichi; Kawachi, Ichiro

    2012-11-01

    Crime is an important determinant of public health outcomes, including quality of life, mental well-being, and health behavior. A body of research has documented the association between community social capital and crime victimization. The association between social capital and crime victimization has been examined at multiple levels of spatial aggregation, ranging from entire countries, to states, metropolitan areas, counties, and neighborhoods. In multilevel analysis, the spatial boundaries at level 2 are most often drawn from administrative boundaries (e.g., Census tracts in the U.S.). One problem with adopting administrative definitions of neighborhoods is that it ignores spatial spillover. We conducted a study of social capital and crime victimization in one ward of Tokyo city, using a spatial Durbin model with an inverse-distance weighting matrix that assigned each respondent a unique level of "exposure" to social capital based on all other residents' perceptions. The study is based on a postal questionnaire sent to 20-69 years old residents of Arakawa Ward, Tokyo. The response rate was 43.7%. We examined the contextual influence of generalized trust, perceptions of reciprocity, two types of social network variables, as well as two principal components of social capital (constructed from the above four variables). Our outcome measure was self-reported crime victimization in the last five years. In the spatial Durbin model, we found that neighborhood generalized trust, reciprocity, supportive networks and two principal components of social capital were each inversely associated with crime victimization. By contrast, a multilevel regression performed with the same data (using administrative neighborhood boundaries) found generally null associations between neighborhood social capital and crime. Spatial regression methods may be more appropriate for investigating the contextual influence of social capital in homogeneous cultural settings such as Japan. PMID

  20. Advances in Mid-Infrared Spectroscopy for Chemical Analysis.

    PubMed

    Haas, Julian; Mizaikoff, Boris

    2016-06-12

    Infrared spectroscopy in the 3-20 μm spectral window has evolved from a routine laboratory technique into a state-of-the-art spectroscopy and sensing tool by benefitting from recent progress in increasingly sophisticated spectra acquisition techniques and advanced materials for generating, guiding, and detecting mid-infrared (MIR) radiation. Today, MIR spectroscopy provides molecular information with trace to ultratrace sensitivity, fast data acquisition rates, and high spectral resolution catering to demanding applications in bioanalytics, for example, and to improved routine analysis. In addition to advances in miniaturized device technology without sacrificing analytical performance, selected innovative applications for MIR spectroscopy ranging from process analysis to biotechnology and medical diagnostics are highlighted in this review. PMID:27070183

  1. Advances in Mid-Infrared Spectroscopy for Chemical Analysis

    NASA Astrophysics Data System (ADS)

    Haas, Julian; Mizaikoff, Boris

    2016-06-01

    Infrared spectroscopy in the 3–20 μm spectral window has evolved from a routine laboratory technique into a state-of-the-art spectroscopy and sensing tool by benefitting from recent progress in increasingly sophisticated spectra acquisition techniques and advanced materials for generating, guiding, and detecting mid-infrared (MIR) radiation. Today, MIR spectroscopy provides molecular information with trace to ultratrace sensitivity, fast data acquisition rates, and high spectral resolution catering to demanding applications in bioanalytics, for example, and to improved routine analysis. In addition to advances in miniaturized device technology without sacrificing analytical performance, selected innovative applications for MIR spectroscopy ranging from process analysis to biotechnology and medical diagnostics are highlighted in this review.

  2. Analysis and design of advanced composite bounded joints

    NASA Technical Reports Server (NTRS)

    Hart-Smith, L. J.

    1974-01-01

    Advances in the analysis of adhesive-bonded joints are presented with particular emphasis on advanced composite structures. The joints analyzed are of double-lap, single-lap, scarf, stepped-lap and tapered-lap configurations. Tensile, compressive, and in-plane shear loads are covered. In addition to the usual geometric variables, the theory accounts for the strength increases attributable to adhesive plasticity (in terms of the elastic-plastic adhesive model) and the joint strength reductions imposed by imbalances between the adherends. The solutions are largely closed-form analytical results, employing iterative solutions on a digital computer for the more complicated joint configurations. In assessing the joint efficiency, three potential failure modes are considered. These are adherend failure outside the joint, adhesive failure in shear, and adherend interlaminar tension failure (or adhesive failure in peel). Each mode is governed by a distinct mathematical analysis and each prevails throughout different ranges of geometric sizes and proportions.

  3. Advanced gamma ray balloon experiment ground checkout and data analysis

    NASA Technical Reports Server (NTRS)

    Blackstone, M.

    1976-01-01

    A software programming package to be used in the ground checkout and handling of data from the advanced gamma ray balloon experiment is described. The Operator's Manual permits someone unfamiliar with the inner workings of the software system (called LEO) to operate on the experimental data as it comes from the Pulse Code Modulation interface, converting it to a form for later analysis, and monitoring the program of an experiment. A Programmer's Manual is included.

  4. [Advances in independent component analysis and its application].

    PubMed

    Chen, Huafu; Yao, Dezhong

    2003-06-01

    The independent component analysis (ICA) is a new technique in statistical signal processing, which decomposes mixed signals into statistical independent components. The reported applications in biomedical and radar signal have demonstrated its good prospect in various blind signal separation. In this paper, the progress of ICA in such as its principle, algorithm and application and advance direction of ICA in future is reviewed. The aim is to promote the research in theory and application in the future. PMID:12856621

  5. Advanced superposition methods for high speed turbopump vibration analysis

    NASA Technical Reports Server (NTRS)

    Nielson, C. E.; Campany, A. D.

    1981-01-01

    The small, high pressure Mark 48 liquid hydrogen turbopump was analyzed and dynamically tested to determine the cause of high speed vibration at an operating speed of 92,400 rpm. This approaches the design point operating speed of 95,000 rpm. The initial dynamic analysis in the design stage and subsequent further analysis of the rotor only dynamics failed to predict the vibration characteristics found during testing. An advanced procedure for dynamics analysis was used in this investigation. The procedure involves developing accurate dynamic models of the rotor assembly and casing assembly by finite element analysis. The dynamically instrumented assemblies are independently rap tested to verify the analytical models. The verified models are then combined by modal superposition techniques to develop a completed turbopump model where dynamic characteristics are determined. The results of the dynamic testing and analysis obtained are presented and methods of moving the high speed vibration characteristics to speeds above the operating range are recommended. Recommendations for use of these advanced dynamic analysis procedures during initial design phases are given.

  6. Advanced image analysis for the preservation of cultural heritage

    NASA Astrophysics Data System (ADS)

    France, Fenella G.; Christens-Barry, William; Toth, Michael B.; Boydston, Kenneth

    2010-02-01

    The Library of Congress' Preservation Research and Testing Division has established an advanced preservation studies scientific program for research and analysis of the diverse range of cultural heritage objects in its collection. Using this system, the Library is currently developing specialized integrated research methodologies for extending preservation analytical capacities through non-destructive hyperspectral imaging of cultural objects. The research program has revealed key information to support preservation specialists, scholars and other institutions. The approach requires close and ongoing collaboration between a range of scientific and cultural heritage personnel - imaging and preservation scientists, art historians, curators, conservators and technology analysts. A research project of the Pierre L'Enfant Plan of Washington DC, 1791 had been undertaken to implement and advance the image analysis capabilities of the imaging system. Innovative imaging options and analysis techniques allow greater processing and analysis capacities to establish the imaging technique as the first initial non-invasive analysis and documentation step in all cultural heritage analyses. Mapping spectral responses, organic and inorganic data, topography semi-microscopic imaging, and creating full spectrum images have greatly extended this capacity from a simple image capture technique. Linking hyperspectral data with other non-destructive analyses has further enhanced the research potential of this image analysis technique.

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

    PubMed Central

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

    2016-01-01

    The spatial distribution of urban service facilities is largely constrained by the road network. In this study, network point pattern analysis and correlation analysis were used to analyze the relationship between road network and healthcare facility distribution. The weighted network kernel density estimation method proposed in this study identifies significant differences between the outside and inside areas of the Ming city wall. The results of network K-function analysis show that private hospitals are more evenly distributed than public hospitals, and pharmacy stores tend to cluster around hospitals along the road network. After computing the correlation analysis between different categorized hospitals and street centrality, we find that the distribution of these hospitals correlates highly with the street centralities, and that the correlations are higher with private and small hospitals than with public and large hospitals. The comprehensive analysis results could help examine the reasonability of existing urban healthcare facility distribution and optimize the location of new healthcare facilities. PMID:27548197

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

    PubMed

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

    2016-01-01

    The spatial distribution of urban service facilities is largely constrained by the road network. In this study, network point pattern analysis and correlation analysis were used to analyze the relationship between road network and healthcare facility distribution. The weighted network kernel density estimation method proposed in this study identifies significant differences between the outside and inside areas of the Ming city wall. The results of network K-function analysis show that private hospitals are more evenly distributed than public hospitals, and pharmacy stores tend to cluster around hospitals along the road network. After computing the correlation analysis between different categorized hospitals and street centrality, we find that the distribution of these hospitals correlates highly with the street centralities, and that the correlations are higher with private and small hospitals than with public and large hospitals. The comprehensive analysis results could help examine the reasonability of existing urban healthcare facility distribution and optimize the location of new healthcare facilities. PMID:27548197

  9. Spatial analysis of storm depths from an Arizona raingage network

    NASA Technical Reports Server (NTRS)

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

    1986-01-01

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

  10. [Advanced data analysis and visualization for clinical laboratory].

    PubMed

    Inada, Masanori; Yoneyama, Akiko

    2011-01-01

    This paper describes visualization techniques that help identify hidden structures in clinical laboratory data. The visualization of data is helpful for a rapid and better understanding of the characteristics of data sets. Various charts help the user identify trends in data. Scatter plots help prevent misinterpretations due to invalid data by identifying outliers. The representation of experimental data in figures is always useful for communicating results to others. Currently, flexible methods such as smoothing methods and latent structure analysis are available owing to the presence of advanced hardware and software. Principle component analysis, which is a well-known technique used to reduce multidimensional data sets, can be carried out on a personal computer. These methods could lead to advanced visualization with regard to exploratory data analysis. In this paper, we present 3 examples in order to introduce advanced data analysis. In the first example, a smoothing spline was fitted to a time-series from the control chart which is not in a state of statistical control. The trend line was clearly extracted from the daily measurements of the control samples. In the second example, principal component analysis was used to identify a new diagnostic indicator for Graves' disease. The multi-dimensional data obtained from patients were reduced to lower dimensions, and the principle components thus obtained summarized the variation in the data set. In the final example, a latent structure analysis for a Gaussian mixture model was used to draw complex density functions suitable for actual laboratory data. As a result, 5 clusters were extracted. The mixed density function of these clusters represented the data distribution graphically. The methods used in the above examples make the creation of complicated models for clinical laboratories more simple and flexible. PMID:21404582

  11. Advanced stress analysis methods applicable to turbine engine structures

    NASA Technical Reports Server (NTRS)

    Pian, Theodore H. H.

    1991-01-01

    The following tasks on the study of advanced stress analysis methods applicable to turbine engine structures are described: (1) constructions of special elements which contain traction-free circular boundaries; (2) formulation of new version of mixed variational principles and new version of hybrid stress elements; (3) establishment of methods for suppression of kinematic deformation modes; (4) construction of semiLoof plate and shell elements by assumed stress hybrid method; and (5) elastic-plastic analysis by viscoplasticity theory using the mechanical subelement model.

  12. Advances in Computational Stability Analysis of Composite Aerospace Structures

    SciTech Connect

    Degenhardt, R.; Araujo, F. C. de

    2010-09-30

    European aircraft industry demands for reduced development and operating costs. Structural weight reduction by exploitation of structural reserves in composite aerospace structures contributes to this aim, however, it requires accurate and experimentally validated stability analysis of real structures under realistic loading conditions. This paper presents different advances from the area of computational stability analysis of composite aerospace structures which contribute to that field. For stringer stiffened panels main results of the finished EU project COCOMAT are given. It investigated the exploitation of reserves in primary fibre composite fuselage structures through an accurate and reliable simulation of postbuckling and collapse. For unstiffened cylindrical composite shells a proposal for a new design method is presented.

  13. Advanced Models for Aeroelastic Analysis of Propulsion Systems

    NASA Technical Reports Server (NTRS)

    Keith, Theo G., Jr.; Mahajan, Aparajit

    1996-01-01

    This report describes an integrated, multidisciplinary simulation capability for aeroelastic analysis and optimization of advanced propulsion systems. This research is intended to improve engine development, acquisition, and maintenance costs. One of the proposed simulations is aeroelasticity of blades, cowls, and struts in an ultra-high bypass fan. These ducted fans are expected to have significant performance, fuel, and noise improvements over existing engines. An interface program was written to use modal information from COBSTAN and NASTRAN blade models in aeroelastic analysis with a single rotation ducted fan aerodynamic code.

  14. Advanced spatio-temporal filtering techniques for photogrammetric image sequence analysis in civil engineering material testing

    NASA Astrophysics Data System (ADS)

    Liebold, F.; Maas, H.-G.

    2016-01-01

    The paper shows advanced spatial, temporal and spatio-temporal filtering techniques which may be used to reduce noise effects in photogrammetric image sequence analysis tasks and tools. As a practical example, the techniques are validated in a photogrammetric spatio-temporal crack detection and analysis tool applied in load tests in civil engineering material testing. The load test technique is based on monocular image sequences of a test object under varying load conditions. The first image of a sequence is defined as a reference image under zero load, wherein interest points are determined and connected in a triangular irregular network structure. For each epoch, these triangles are compared to the reference image triangles to search for deformations. The result of the feature point tracking and triangle comparison process is a spatio-temporally resolved strain value field, wherein cracks can be detected, located and measured via local discrepancies. The strains can be visualized as a color-coded map. In order to improve the measuring system and to reduce noise, the strain values of each triangle must be treated in a filtering process. The paper shows the results of various filter techniques in the spatial and in the temporal domain as well as spatio-temporal filtering techniques applied to these data. The best results were obtained by a bilateral filter in the spatial domain and by a spatio-temporal EOF (empirical orthogonal function) filtering technique.

  15. Advances in Fourier transform infrared spectroscopy of natural glasses: From sample preparation to data analysis

    NASA Astrophysics Data System (ADS)

    von Aulock, F. W.; Kennedy, B. M.; Schipper, C. I.; Castro, J. M.; Martin, D. E.; Oze, C.; Watkins, J. M.; Wallace, P. J.; Puskar, L.; Bégué, F.; Nichols, A. R. L.; Tuffen, H.

    2014-10-01

    Fourier transform infrared spectroscopy (FTIR) is an analytical technique utilized to measure the concentrations of H and C species in volcanic glasses. Water and CO2 are the most abundant volatile species in volcanic systems. Water is present in magmas in higher concentrations than CO2 and is also more soluble at lower pressures, and, therefore it is the dominant volatile forming bubbles during volcanic eruptions. Dissolved water affects both phase equilibria and melt physical properties such as density and viscosity, therefore, water is important for understanding magmatic processes. Additionally, quantitative measurements of different volatile species using FTIR can be achieved at high spatial resolution. Recent developments in analytical equipment such as synchrotron light sources and the development of focal plane array (FPA) detectors allow higher resolution measurements and the acquisition of concentration maps. These new capabilities are being used to characterize spatial gradients (or lack thereof) around bubbles and other textural features, which in turn lead to new insights into the behavior of volcanic feeder systems. Here, practical insights about sample preparation and analysis of the distribution and speciation of volatiles in volcanic glasses using FTIR spectroscopy are discussed. New advances in the field of FTIR analysis produce reliable data at high spatial resolution that can be used to produce datasets on the distribution, dissolution and diffusion of volatiles in volcanic materials.

  16. GIS as an Integration Tool for Hydrologic Modeling: Spatial Data Management, Analysis and Visualization

    NASA Astrophysics Data System (ADS)

    Setegn, S. G.; Lawrence, A.; Mahmoudi, M.

    2015-12-01

    The Applied Research Center at Florida International University (ARC-FIU) is supporting the soil and groundwater remediation efforts of the U.S. Department of Energy (DOE) Savannah River Site (SRS) by developing a surface water model to simulate the hydrology and the fate and transport of contaminants and sediment in the Tims Branch watershed. The first phase of model development was initiated in 2014 using the MIKE SHE/MIKE 11 hydrological modeling package which has a geographic information systems (GIS) user interface built into its system that can directly use spatial GIS databases (geodatabases) for model inputs. This study developed an ArcGIS geodatabase to support the hydrological modeling work for SRS. The coupling of a geodatabase with MIKE SHE/MIKE 11 numerical models can serve as an efficient tool that significantly reduces the time needed for data preparation. The geodatabase provides an advanced spatial data structure needed to address the management, processing, and analysis of large GIS and timeseries datasets derived from multiple sources that are used for numerical model calibration, uncertainty analysis, and simulation of flow and contaminant fate and transport during extreme climatic events. The geodatabase developed is based on the ArcHydro and ArcGIS Base Map data models with modifications made for project specific input parameters. The significance of this approach was to ensure its replicability for potential application in other watersheds. This paper describes the process of development of the SRS geodatabase and the application of GIS tools to pre-process and analyze hydrological model data; automate repetitive geoprocessing tasks; and produce maps for visualization of the surface water hydrology of the Tims Branch watershed. Key Words: GIS, hydrological modeling, geodatabase, hydrology, MIKE SHE/MIKE 11

  17. Insights to urban dynamics through landscape spatial pattern analysis

    NASA Astrophysics Data System (ADS)

    TV, Ramachandra; Aithal, Bharath H.; Sanna, Durgappa D.

    2012-08-01

    Urbanisation is a dynamic complex phenomenon involving large scale changes in the land uses at local levels. Analyses of changes in land uses in urban environments provide a historical perspective of land use and give an opportunity to assess the spatial patterns, correlation, trends, rate and impacts of the change, which would help in better regional planning and good governance of the region. Main objective of this research is to quantify the urban dynamics using temporal remote sensing data with the help of well-established landscape metrics. Bangalore being one of the rapidly urbanising landscapes in India has been chosen for this investigation. Complex process of urban sprawl was modelled using spatio temporal analysis. Land use analyses show 584% growth in built-up area during the last four decades with the decline of vegetation by 66% and water bodies by 74%. Analyses of the temporal data reveals an increase in urban built up area of 342.83% (during 1973-1992), 129.56% (during 1992-1999), 106.7% (1999-2002), 114.51% (2002-2006) and 126.19% from 2006 to 2010. The Study area was divided into four zones and each zone is further divided into 17 concentric circles of 1 km incrementing radius to understand the patterns and extent of the urbanisation at local levels. The urban density gradient illustrates radial pattern of urbanisation for the period 1973-2010. Bangalore grew radially from 1973 to 2010 indicating that the urbanisation is intensifying from the central core and has reached the periphery of the Greater Bangalore. Shannon's entropy, alpha and beta population densities were computed to understand the level of urbanisation at local levels. Shannon's entropy values of recent time confirms dispersed haphazard urban growth in the city, particularly in the outskirts of the city. This also illustrates the extent of influence of drivers of urbanisation in various directions. Landscape metrics provided in depth knowledge about the sprawl. Principal component

  18. Structural Configuration Systems Analysis for Advanced Aircraft Fuselage Concepts

    NASA Technical Reports Server (NTRS)

    Mukhopadhyay, Vivek; Welstead, Jason R.; Quinlan, Jesse R.; Guynn, Mark D.

    2016-01-01

    Structural configuration analysis of an advanced aircraft fuselage concept is investigated. This concept is characterized by a double-bubble section fuselage with rear mounted engines. Based on lessons learned from structural systems analysis of unconventional aircraft, high-fidelity finite-element models (FEM) are developed for evaluating structural performance of three double-bubble section configurations. Structural sizing and stress analysis are applied for design improvement and weight reduction. Among the three double-bubble configurations, the double-D cross-section fuselage design was found to have a relatively lower structural weight. The structural FEM weights of these three double-bubble fuselage section concepts are also compared with several cylindrical fuselage models. Since these fuselage concepts are different in size, shape and material, the fuselage structural FEM weights are normalized by the corresponding passenger floor area for a relative comparison. This structural systems analysis indicates that an advanced composite double-D section fuselage may have a relative structural weight ratio advantage over a conventional aluminum fuselage. Ten commercial and conceptual aircraft fuselage structural weight estimates, which are empirically derived from the corresponding maximum takeoff gross weight, are also presented and compared with the FEM- based estimates for possible correlation. A conceptual full vehicle FEM model with a double-D fuselage is also developed for preliminary structural analysis and weight estimation.

  19. Validation Database Based Thermal Analysis of an Advanced RPS Concept

    NASA Technical Reports Server (NTRS)

    Balint, Tibor S.; Emis, Nickolas D.

    2006-01-01

    Advanced RPS concepts can be conceived, designed and assessed using high-end computational analysis tools. These predictions may provide an initial insight into the potential performance of these models, but verification and validation are necessary and required steps to gain confidence in the numerical analysis results. This paper discusses the findings from a numerical validation exercise for a small advanced RPS concept, based on a thermal analysis methodology developed at JPL and on a validation database obtained from experiments performed at Oregon State University. Both the numerical and experimental configurations utilized a single GPHS module enabled design, resembling a Mod-RTG concept. The analysis focused on operating and environmental conditions during the storage phase only. This validation exercise helped to refine key thermal analysis and modeling parameters, such as heat transfer coefficients, and conductivity and radiation heat transfer values. Improved understanding of the Mod-RTG concept through validation of the thermal model allows for future improvements to this power system concept.

  20. Spatial autocorrelation analysis of hyperspectral imagery for feature selection

    SciTech Connect

    Warner, T.A.; Shank, M.C.

    1997-04-01

    The spatial information in a single spectral image can be estimated from the spatial autocorrelation, which is a measure of how the local variation compares with the overall variance in a scene. In images of random noise, the local variation tends to be similar to the overall variance. In contrast, scenes in which large features can be discerned have clusters of pixels with similar values, which cause the local variation to be much smaller on average than the overall scene variance. Feature selection is the process of finding a subset of the original bands that provides an optimal trade-off between probability of error and classification cost. Three feature selection problems are addressed in this paper: (1) narrow band feature selection, which is the selection of a subset of individual bands; (2) broad band feature selection, in which groups of adjacent bands are selected, and (3) nonadjacent multiple band feature selection, in which selection of the groups of bands is not limited to adjacent bands. Spatial autocorrelation is useful in all three feature selection problems. Tests with simulated data indicate that the spatial autocorrelation based methods consistently identify the best bands or groups of bands. Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) data of eastern Washington state are used to illustrate the technique on real data.

  1. Spatial Analysis of Feline Immunodeficiency Virus Infection in Cougars

    PubMed Central

    Wheeler, David C.; Waller, Lance A.; Biek, Roman

    2010-01-01

    The cougar (Puma concolor) is a large predatory feline found widely in the Americas that is susceptible to feline immunodeficiency virus (FIV), a fast-evolving lentivirus found in wild feline species that is analogous to simian immunodeficiency viruses in wild primates and belongs to the same family of viruses as human immunodeficiency virus. FIV infection in cougars can lead to a weakened immune system that creates opportunities for other infecting agents. FIV prevalence and lineages have been studied previously in several areas in the western United States, but typically without spatially explicit statistical techniques. To describe the distribution of FIV in a sample of cougars located in the northern Rocky Mountain region of North America, we first used kernel density ratio estimation to map the log relative risk of FIV. The risk surface showed a significant cluster of FIV in northwestern Montana. We also used Bayesian cluster models for genetic data to investigate the spatial structure of the feline immunodeficiency virus with virus genetic sequence data. A result of the models was two spatially distinct FIV lineages that aligned considerably with an interstate highway in Montana. Our results suggest that the use of spatial information and models adds novel insight when investigating an infectious animal disease. The results also suggest that the influence of landscape features likely plays an important role in the spatiotemporal spread of an infectious disease within wildlife populations. PMID:21197421

  2. Rockfall hazard analysis using LiDAR and spatial modeling

    NASA Astrophysics Data System (ADS)

    Lan, Hengxing; Martin, C. Derek; Zhou, Chenghu; Lim, Chang Ho

    2010-05-01

    Rockfalls have been significant geohazards along the Canadian Class 1 Railways (CN Rail and CP Rail) since their construction in the late 1800s. These rockfalls cause damage to infrastructure, interruption of business, and environmental impacts, and their occurrence varies both spatially and temporally. The proactive management of these rockfall hazards requires enabling technologies. This paper discusses a hazard assessment strategy for rockfalls along a section of a Canadian railway using LiDAR and spatial modeling. LiDAR provides accurate topographical information of the source area of rockfalls and along their paths. Spatial modeling was conducted using Rockfall Analyst, a three dimensional extension to GIS, to determine the characteristics of the rockfalls in terms of travel distance, velocity and energy. Historical rockfall records were used to calibrate the physical characteristics of the rockfall processes. The results based on a high-resolution digital elevation model from a LiDAR dataset were compared with those based on a coarse digital elevation model. A comprehensive methodology for rockfall hazard assessment is proposed which takes into account the characteristics of source areas, the physical processes of rockfalls and the spatial attribution of their frequency and energy.

  3. Spatial and Statistical Analysis of Leptospirosis in Guilan Province, Iran

    NASA Astrophysics Data System (ADS)

    Nia, A. Mohammadi; Alimohammadi, A.; Habibi, R.; Shirzadi, M. R.

    2015-12-01

    The most underdiagnosed water-borne bacterial zoonosis in the world is Leptospirosis which especially impacts tropical and humid regions. According to World Health Organization (WHO), the number of human cases is not known precisely. Available reports showed that worldwide incidences vary from 0.1-1 per 100 000 per year in temperate climates to 10-100 per 100 000 in the humid tropics. Pathogenic bacteria that is spread by the urines of rats is the main reason of water and soil infections. Rice field farmers who are in contact with infected water or soil, contain the most burden of leptospirosis prevalence. In recent years, this zoonotic disease have been occurred in north of Iran endemically. Guilan as the second rice production province (average=750 000 000 Kg, 40% of country production) after Mazandaran, has one of the most rural population (Male=487 679, Female=496 022) and rice workers (47 621 insured workers) among Iran provinces. The main objectives of this study were to analyse yearly spatial distribution and the possible spatial clusters of leptospirosis to better understand epidemiological aspects of them in the province. Survey was performed during the period of 2009-2013 at rural district level throughout the study area. Global clustering methods including the average nearest neighbour distance, Moran's I and General G indices were utilized to investigate the annual spatial distribution of diseases. At the end, significant spatial clusters have been detected with the objective of informing priority areas for public health planning and resource allocation.

  4. A study of spatial data management and analysis systems

    NASA Technical Reports Server (NTRS)

    Christopher, Clyde; Galle, Richard

    1989-01-01

    The Earth Resources Laboratory of the NASA Stennis Space Center is a center of space related technology for Earth observations. It has assumed the task, in a joint effort with Jackson State University, to reach out to the science community and acquire information pertaining to characteristics of spatially oriented data processing.

  5. Distributed multi-criteria model evaluation and spatial association analysis

    NASA Astrophysics Data System (ADS)

    Scherer, Laura; Pfister, Stephan

    2015-04-01

    Model performance, if evaluated, is often communicated by a single indicator and at an aggregated level; however, it does not embrace the trade-offs between different indicators and the inherent spatial heterogeneity of model efficiency. In this study, we simulated the water balance of the Mississippi watershed using the Soil and Water Assessment Tool (SWAT). The model was calibrated against monthly river discharge at 131 measurement stations. Its time series were bisected to allow for subsequent validation at the same gauges. Furthermore, the model was validated against evapotranspiration which was available as a continuous raster based on remote sensing. The model performance was evaluated for each of the 451 sub-watersheds using four different criteria: 1) Nash-Sutcliffe efficiency (NSE), 2) percent bias (PBIAS), 3) root mean square error (RMSE) normalized to standard deviation (RSR), as well as 4) a combined indicator of the squared correlation coefficient and the linear regression slope (bR2). Conditions that might lead to a poor model performance include aridity, a very flat and steep relief, snowfall and dams, as indicated by previous research. In an attempt to explain spatial differences in model efficiency, the goodness of the model was spatially compared to these four phenomena by means of a bivariate spatial association measure which combines Pearson's correlation coefficient and Moran's index for spatial autocorrelation. In order to assess the model performance of the Mississippi watershed as a whole, three different averages of the sub-watershed results were computed by 1) applying equal weights, 2) weighting by the mean observed river discharge, 3) weighting by the upstream catchment area and the square root of the time series length. Ratings of model performance differed significantly in space and according to efficiency criterion. The model performed much better in the humid Eastern region than in the arid Western region which was confirmed by the

  6. Advanced hydrogen/oxygen thrust chamber design analysis

    NASA Technical Reports Server (NTRS)

    Shoji, J. M.

    1973-01-01

    The results are reported of the advanced hydrogen/oxygen thrust chamber design analysis program. The primary objectives of this program were to: (1) provide an in-depth analytical investigation to develop thrust chamber cooling and fatigue life limitations of an advanced, high pressure, high performance H2/O2 engine design of 20,000-pounds (88960.0 N) thrust; and (2) integrate the existing heat transfer analysis, thermal fatigue and stress aspects for advanced chambers into a comprehensive computer program. Thrust chamber designs and analyses were performed to evaluate various combustor materials, coolant passage configurations (tubes and channels), and cooling circuits to define the nominal 1900 psia (1.31 x 10 to the 7th power N/sq m) chamber pressure, 300-cycle life thrust chamber. The cycle life capability of the selected configuration was then determined for three duty cycles. Also the influence of cycle life and chamber pressure on thrust chamber design was investigated by varying in cycle life requirements at the nominal chamber pressure and by varying the chamber pressure at the nominal cycle life requirement.

  7. Spatial sensitivity analysis of snow cover data in a distributed rainfall-runoff model

    NASA Astrophysics Data System (ADS)

    Berezowski, T.; Nossent, J.; Chormański, J.; Batelaan, O.

    2015-04-01

    As the availability of spatially distributed data sets for distributed rainfall-runoff modelling is strongly increasing, more attention should be paid to the influence of the quality of the data on the calibration. While a lot of progress has been made on using distributed data in simulations of hydrological models, sensitivity of spatial data with respect to model results is not well understood. In this paper we develop a spatial sensitivity analysis method for spatial input data (snow cover fraction - SCF) for a distributed rainfall-runoff model to investigate when the model is differently subjected to SCF uncertainty in different zones of the model. The analysis was focussed on the relation between the SCF sensitivity and the physical and spatial parameters and processes of a distributed rainfall-runoff model. The methodology is tested for the Biebrza River catchment, Poland, for which a distributed WetSpa model is set up to simulate 2 years of daily runoff. The sensitivity analysis uses the Latin-Hypercube One-factor-At-a-Time (LH-OAT) algorithm, which employs different response functions for each spatial parameter representing a 4 × 4 km snow zone. The results show that the spatial patterns of sensitivity can be easily interpreted by co-occurrence of different environmental factors such as geomorphology, soil texture, land use, precipitation and temperature. Moreover, the spatial pattern of sensitivity under different response functions is related to different spatial parameters and physical processes. The results clearly show that the LH-OAT algorithm is suitable for our spatial sensitivity analysis approach and that the SCF is spatially sensitive in the WetSpa model. The developed method can be easily applied to other models and other spatial data.

  8. A sensitivity analysis using different spatial resolution terrain models and flood inundation models

    NASA Astrophysics Data System (ADS)

    Papaioannou, George; Aronica, Giuseppe T.; Loukas, Athanasios; Vasiliades, Lampros

    2014-05-01

    The impact of terrain spatial resolution and accuracy on the hydraulic flood modeling can pervade the water depth and the flood extent accuracy. Another significant factor that can affect the hydraulic flood modeling outputs is the selection of the hydrodynamic models (1D,2D,1D/2D). Human mortality, ravaged infrastructures and other damages can be derived by extreme flash flood events that can be prevailed in lowlands at suburban and urban areas. These incidents make the necessity of a detailed description of the terrain and the use of advanced hydraulic models essential for the accurate spatial distribution of the flooded areas. In this study, a sensitivity analysis undertaken using different spatial resolution of Digital Elevation Models (DEMs) and several hydraulic modeling approaches (1D, 2D, 1D/2D) including their effect on the results of river flow modeling and mapping of floodplain. Three digital terrain models (DTMs) were generated from the different elevation variation sources: Terrestrial Laser Scanning (TLS) point cloud data, classic land surveying and digitization of elevation contours from 1:5000 scale topographic maps. HEC-RAS and MIKE 11 are the 1-dimensional hydraulic models that are used. MLFP-2D (Aronica et al., 1998) and MIKE 21 are the 2-dimensional hydraulic models. The last case consist of the integration of MIKE 11/MIKE 21 where 1D-MIKE 11 and 2D-MIKE 21 hydraulic models are coupled through the MIKE FLOOD platform. The validation process of water depths and flood extent is achieved through historical flood records. Observed flood inundation areas in terms of simulated maximum water depth and flood extent were used for the validity of each application result. The methodology has been applied in the suburban section of Xerias river at Volos-Greece. Each dataset has been used to create a flood inundation map for different cross-section configurations using different hydraulic models. The comparison of resulting flood inundation maps indicates

  9. Advances in nonmarket valuation econometrics: Spatial heterogeneity in hedonic pricing models and preference heterogeneity in stated preference models

    NASA Astrophysics Data System (ADS)

    Yoo, Jin Woo

    In my 1st essay, the study explores Pennsylvania residents. willingness to pay for development of renewable energy technologies such as solar power, wind power, biomass electricity, and other renewable energy using a choice experiment method. Principle component analysis identified 3 independent attitude components that affect the variation of preference, a desire for renewable energy and environmental quality and concern over cost. The results show that urban residents have a higher desire for environmental quality and concern less about cost than rural residents and consequently have a higher willingness to pay to increase renewable energy production. The results of sub-sample analysis show that a representative respondent in rural (urban) Pennsylvania is willing to pay 3.8(5.9) and 4.1(5.7)/month for increasing the share of Pennsylvania electricity generated from wind power and other renewable energy by 1 percent point, respectively. Mean WTP for solar and biomass electricity was not significantly different from zero. In my second essay, heterogeneity of individual WTP for various renewable energy technologies is investigated using several different variants of the multinomial logit model: a simple MNL with interaction terms, a latent class choice model, a random parameter mixed logit choice model, and a random parameter-latent class choice model. The results of all models consistently show that respondents. preference for individual renewable technology is heterogeneous, but the degree of heterogeneity differs for different renewable technologies. In general, the random parameter logit model with interactions and a hybrid random parameter logit-latent class model fit better than other models and better capture respondents. heterogeneity of preference for renewable energy. The impact of the land under agricultural conservation easement (ACE) contract on the values of nearby residential properties is investigated using housing sales data in two Pennsylvania

  10. Advanced Main Combustion Chamber structural jacket strength analysis

    NASA Technical Reports Server (NTRS)

    Johnston, L. M.; Perkins, L. A.; Denniston, C. L.; Price, J. M.

    1993-01-01

    The structural analysis of the Advanced Main Combustion Chamber (AMCC) is presented. The AMCC is an advanced fabrication concept of the Space Shuttle Main Engine main combustion chamber (MCC). Reduced cost and fabrication time of up to 75 percent were the goals of the AMCC with cast jacket with vacuum plasma sprayed or platelet liner. Since the cast material for the AMCC is much weaker than the wrought material for the MCC, the AMCC is heavier and strength margins much lower in some areas. Proven hand solutions were used to size the manifolds cutout tee areas for combined pressure and applied loads. Detailed finite element strength analyses were used to size the manifolds, longitudinal ribs, and jacket for combined pressure and applied local loads. The design of the gimbal actuator strut attachment lugs were determined by finite element analyses and hand solutions.

  11. Whole-genome CNV analysis: advances in computational approaches

    PubMed Central

    Pirooznia, Mehdi; Goes, Fernando S.; Zandi, Peter P.

    2015-01-01

    Accumulating evidence indicates that DNA copy number variation (CNV) is likely to make a significant contribution to human diversity and also play an important role in disease susceptibility. Recent advances in genome sequencing technologies have enabled the characterization of a variety of genomic features, including CNVs. This has led to the development of several bioinformatics approaches to detect CNVs from next-generation sequencing data. Here, we review recent advances in CNV detection from whole genome sequencing. We discuss the informatics approaches and current computational tools that have been developed as well as their strengths and limitations. This review will assist researchers and analysts in choosing the most suitable tools for CNV analysis as well as provide suggestions for new directions in future development. PMID:25918519

  12. Quantitative spatial analysis of the mouse brain lipidome by pressurized liquid extraction surface analysis.

    PubMed

    Almeida, Reinaldo; Berzina, Zane; Arnspang, Eva C; Baumgart, Jan; Vogt, Johannes; Nitsch, Robert; Ejsing, Christer S

    2015-02-01

    Here we describe a novel surface sampling technique termed pressurized liquid extraction surface analysis (PLESA), which in combination with a dedicated high-resolution shotgun lipidomics routine enables both quantification and in-depth structural characterization of molecular lipid species extracted directly from tissue sections. PLESA uses a sealed and pressurized sampling probe that enables the use of chloroform-containing extraction solvents for efficient in situ lipid microextraction with a spatial resolution of 400 μm. Quantification of lipid species is achieved by the inclusion of internal lipid standards in the extraction solvent. The analysis of lipid microextracts by nanoelectrospray ionization provides long-lasting ion spray which in conjunction with a hybrid ion trap-orbitrap mass spectrometer enables identification and quantification of molecular lipid species using a method with successive polarity shifting, high-resolution Fourier transform mass spectrometry (FTMS), and fragmentation analysis. We benchmarked the performance of the PLESA approach for in-depth lipidome analysis by comparing it to conventional lipid extraction of excised tissue homogenates and by mapping the spatial distribution and molar abundance of 170 molecular lipid species across different anatomical mouse brain regions. PMID:25548943

  13. Spatial Autocorrelation Analysis of Chinese Inter-Provincial Industrial Chemical Oxygen Demand Discharge

    PubMed Central

    Zhao, Xiaofeng; Huang, Xianjin; Liu, Yibo

    2012-01-01

    A spatial autocorrelation analysis method is adopted to process the spatial dynamic change of industrial Chemical Oxygen Demand (COD) discharge in China over the past 15 years. Studies show that amount and intensity of industrial COD discharges are on a decrease, and the tendency is more remarkable for discharge intensity. There are large differences between inter-provincial discharge amount and intensity, and with different spatial differentiation features. Global spatial autocorrelation analysis reveals that Global Moran’s I of discharge amount and intensity is on the decrease. In space, there is an evolution from an agglomeration pattern to a discretization pattern. Local spatial autocorrelation analysis shows that the agglomeration area of industrial COD discharge amount and intensity varies greatly in space with time. Stringent environmental regulations and increased funding for environmental protections are the crucial factors to cut down industrial COD discharge amount and intensity. PMID:22829788

  14. Automated defect spatial signature analysis for semiconductor manufacturing process

    DOEpatents

    Tobin, Jr., Kenneth W.; Gleason, Shaun S.; Karnowski, Thomas P.; Sari-Sarraf, Hamed

    1999-01-01

    An apparatus and method for performing automated defect spatial signature alysis on a data set representing defect coordinates and wafer processing information includes categorizing data from the data set into a plurality of high level categories, classifying the categorized data contained in each high level category into user-labeled signature events, and correlating the categorized, classified signature events to a present or incipient anomalous process condition.

  15. A spatial analysis of phosphorus in the Mississippi river basin.

    PubMed

    Jacobson, Linda M; David, Mark B; Drinkwater, Laurie E

    2011-01-01

    Phosphorus (P) in rivers in the Mississippi River basin (MRB) contributes to hypoxia in the Gulf of Mexico and impairs local water quality. We analyzed the spatial pattern of P in the MRB to determine the counties with the greatest January to June P riverine yields and the most critical factors related to this P loss. Using a database of P inputs and landscape characteristics from 1997 through 2006 for each county in the MRB, we created regression models relating riverine total P (TP), dissolved reactive P (DRP), and particulate P (PP) yields for watersheds within the MRB to these factors. Riverine yields of P were estimated from the average concentration of each form of P during January to June for the 10-yr period, multiplied by the average daily flow, and then summed for the 6-mo period. The fraction of land planted in crops, human consumption of P, and precipitation were found to best predict TP yields with a spatial error regression model ( = 0.48, = 101). Dissolved reactive P yields were predicted by fertilizer P inputs, human consumption of P, and precipitation in a multiple regression model ( = 0.42, = 73), whereas PP yields were explained by crop fraction, human consumption of P, and soil bulk density in a spatial error regression model ( = 0.49, = 61). Overall, the Upper Midwest's Cornbelt region and lower Mississippi basin had the counties with the greatest P yields. These results help to point out specific areas where agricultural conservation practices that reduce losses to streams and rivers and point source P removal might limit the intensity or spatial occurrence of Gulf of Mexico hypoxia and improve local water quality. PMID:21546679

  16. Spatial recurrence analysis: A sensitive and fast detection tool in digital mammography

    SciTech Connect

    Prado, T. L.; Galuzio, P. P.; Lopes, S. R.; Viana, R. L.

    2014-03-15

    Efficient diagnostics of breast cancer requires fast digital mammographic image processing. Many breast lesions, both benign and malignant, are barely visible to the untrained eye and requires accurate and reliable methods of image processing. We propose a new method of digital mammographic image analysis that meets both needs. It uses the concept of spatial recurrence as the basis of a spatial recurrence quantification analysis, which is the spatial extension of the well-known time recurrence analysis. The recurrence-based quantifiers are able to evidence breast lesions in a way as good as the best standard image processing methods available, but with a better control over the spurious fragments in the image.

  17. Spatial recurrence analysis: A sensitive and fast detection tool in digital mammography

    NASA Astrophysics Data System (ADS)

    Prado, T. L.; Galuzio, P. P.; Lopes, S. R.; Viana, R. L.

    2014-03-01

    Efficient diagnostics of breast cancer requires fast digital mammographic image processing. Many breast lesions, both benign and malignant, are barely visible to the untrained eye and requires accurate and reliable methods of image processing. We propose a new method of digital mammographic image analysis that meets both needs. It uses the concept of spatial recurrence as the basis of a spatial recurrence quantification analysis, which is the spatial extension of the well-known time recurrence analysis. The recurrence-based quantifiers are able to evidence breast lesions in a way as good as the best standard image processing methods available, but with a better control over the spurious fragments in the image.

  18. Spatial-decomposition analysis of electrical conductivity in ionic liquid.

    PubMed

    Tu, Kai-Min; Ishizuka, Ryosuke; Matubayasi, Nobuyuki

    2014-12-28

    The electrical conductivity of room temperature ionic liquid (IL) is investigated with molecular dynamics simulation. A trajectory of 1 μs in total is analyzed for the ionic liquid [C4mim][NTf2] (1-n-butyl-3-methylimidazolium bis(trifluoromethylsulfonyl)imide, and the anion is also called TFSI or TFSA), and the ion motions are examined in direct connection to the conductivity within the framework formulated previously [K.-M. Tu, R. Ishizuka, and N. Matubayasi, J. Chem. Phys. 141, 044126 (2014)]. As a transport coefficient, the computed electrical conductivity is in fair agreement with the experiment. The conductivity is then decomposed into the autocorrelation term of Nernst-Einstein form and the cross-correlation term describing the two-body motions of ions, and the cross-correlation term is further decomposed spatially to incorporate the structural insights on ion configurations into the dynamic picture. It is observed that the ion-pair contribution to the conductivity is not spatially localized and extends beyond the first coordination shell. The extent of localization of the cross-correlation effect in the conductivity is in correspondence to that of the spatial correlation represented by radial distribution function, which persists over nanometer scale. PMID:25554167

  19. Noise Analysis of Spatial Phase coding in analog Acoustooptic Processors

    NASA Technical Reports Server (NTRS)

    Gary, Charles K.; Lum, Henry, Jr. (Technical Monitor)

    1994-01-01

    Optical beams can carry information in their amplitude and phase; however, optical analog numerical calculators such as an optical matrix processor use incoherent light to achieve linear operation. Thus, the phase information is lost and only the magnitude can be used. This limits such processors to the representation of positive real numbers. Many systems have been devised to overcome this deficit through the use of digital number representations, but they all operate at a greatly reduced efficiency in contrast to analog systems. The most widely accepted method to achieve sign coding in analog optical systems has been the use of an offset for the zero level. Unfortunately, this results in increased noise sensitivity for small numbers. In this paper, we examine the use of spatially coherent sign coding in acoustooptical processors, a method first developed for digital calculations by D. V. Tigin. This coding technique uses spatial coherence for the representation of signed numbers, while temporal incoherence allows for linear analog processing of the optical information. We show how spatial phase coding reduces noise sensitivity for signed analog calculations.

  20. The Nexus of Place and Finance in the Analysis of Educational Attainment: A Spatial Econometric Approach

    ERIC Educational Resources Information Center

    Sutton, Farah

    2012-01-01

    This study examines the spatial distribution of educational attainment and then builds upon current predictive frameworks for understanding patterns of educational attainment by applying a spatial econometric method of analysis. The research from this study enables a new approach to the policy discussion on how to improve educational attainment…

  1. A Meta-Analysis of Correlations of Spatial and Mathematical Tasks.

    ERIC Educational Resources Information Center

    Friedman, Lynn

    The meta analysis reported in this paper considers the implications of combined correlational evidence for the nature of the relationships of mathematical and spatial skills, and for the possibility that spatial skill underlies gender differences in favor of males on mathematical tasks. In all, 136 studies reported in 116 articles and…

  2. Temporal and Spatial Analysis of Monogenetic Volcanic Fields

    NASA Astrophysics Data System (ADS)

    Kiyosugi, Koji

    Achieving an understanding of the nature of monogenetic volcanic fields depends on identification of the spatial and temporal patterns of volcanism in these fields, and their relationships to structures mapped in the shallow crust and inferred in the deep crust and mantle through interpretation of geochemical, radiometric and geophysical data. We investigate the spatial and temporal distributions of volcanism in the Abu Monogenetic Volcano Group, Southwest Japan. E-W elongated volcano distribution, which is identified by a nonparametric kernel method, is found to be consistent with the spatial extent of P-wave velocity anomalies in the lower crust and upper mantle, supporting the idea that the spatial density map of volcanic vents reflects the geometry of a mantle diapir. Estimated basalt supply to the lower crust is constant. This observation and the spatial distribution of volcanic vents suggest stability of magma productivity and essentially constant two-dimensional size of the source mantle diapir. We mapped conduits, dike segments, and sills in the San Rafael sub-volcanic field, Utah, where the shallowest part of a Pliocene magmatic system is exceptionally well exposed. The distribution of conduits matches the major features of dike distribution, including development of clusters and distribution of outliers. The comparison of San Rafael conduit distribution and the distributions of volcanoes in several recently active volcanic fields supports the use of statistical models, such as nonparametric kernel methods, in probabilistic hazard assessment for distributed volcanism. We developed a new recurrence rate calculation method that uses a Monte Carlo procedure to better reflect and understand the impact of uncertainties of radiometric age determinations on uncertainty of recurrence rate estimates for volcanic activity in the Abu, Yucca Mountain Region, and Izu-Tobu volcanic fields. Results suggest that the recurrence rates of volcanic fields can change by more

  3. An advanced probabilistic structural analysis method for implicit performance functions

    NASA Technical Reports Server (NTRS)

    Wu, Y.-T.; Millwater, H. R.; Cruse, T. A.

    1989-01-01

    In probabilistic structural analysis, the performance or response functions usually are implicitly defined and must be solved by numerical analysis methods such as finite element methods. In such cases, the most commonly used probabilistic analysis tool is the mean-based, second-moment method which provides only the first two statistical moments. This paper presents a generalized advanced mean value (AMV) method which is capable of establishing the distributions to provide additional information for reliability design. The method requires slightly more computations than the second-moment method but is highly efficient relative to the other alternative methods. In particular, the examples show that the AMV method can be used to solve problems involving non-monotonic functions that result in truncated distributions.

  4. The analysis of protein pharmaceuticals: near future advances.

    PubMed

    Middaugh, C R

    1994-01-01

    The analysis of protein pharmaceuticals currently involves a complex series of chromatographic, electrophoretic, spectroscopic, immunological and biological measurements to unequivocally establish their identity, purity and integrity. In this review, I briefly consider the possibility that at least the functional identity and integrity of a protein drug might be established by either a single analysis involving X-ray diffraction, NMR or mass spectrometry, or by a chromatographically based multi-detector system in which a number of critical parameters are essentially simultaneously determined. The use of a protein standard to obtain comparative measurements and new advances in the technology of each of these methods is emphasized. A current major obstacle to the implementation of these approaches is the frequent microheterogeneity of protein preparations. The evolution of biological assays into measurements examining more defined intracellular signal transduction events or based on novel biosensors as well as the analysis of vaccines is also briefly discussed. PMID:7765931

  5. Spatial analysis of mass wasting and topography in coastal British Columbia

    NASA Astrophysics Data System (ADS)

    Martin, Y.; Sjogren, D.

    2003-04-01

    The large inventory of mass wasting data collected by Gimbarzevsky (1988) for the Queen Charlotte Islands, British Columbia is an exceptional data base. The archipelago is located approximately 80 km off the coast of British Columbia and is seismically active, having the potential for earthquakes of large magnitude. The climate is mild, wet (1300 to 3600 mm/yr) and very windy. These factors together contribute to a high frequency of landsliding. The inventory consists of 8328 debris slides, debris avalanches, debris flows and debris torrents. Identification and characterization of events were based on 1:50 000 panchromatic aerial photographs and 1:50 000 map sheets. UTM grid cells of area 1 km^2 were used to classify landslide attributes, such as gradient and aspect. Since the original analysis was undertaken, significant advances have been made in the availability of topographic data and techniques to assess the spatial distribution of mass wasting events and associated landscape attributes. The mass wasting events, originally plotted on 1:50 000 NTS map sheets, are digitized and transferred to the 25-m DEM available for the Queen Charlotte Islands. This format allows for improved analysis of the original data base and, in particular, landscape attributes which may affect mass wasting frequency. Sensitivity analysis is undertaken to explore the effects of improved topographic resolution on results. In addition, the GIS format allows us to extend the original analysis using the sophisticated analytical techniques now available. Gimbarzevsky, P. (1988) Mass Wasting on the Queen Charlotte Islands: A Regional Inventory, BC Ministry of Forests and Lands, Land Management Report, 29, 96 pp.

  6. Composite Structure Modeling and Analysis of Advanced Aircraft Fuselage Concepts

    NASA Technical Reports Server (NTRS)

    Mukhopadhyay, Vivek; Sorokach, Michael R.

    2015-01-01

    NASA Environmentally Responsible Aviation (ERA) project and the Boeing Company are collabrating to advance the unitized damage arresting composite airframe technology with application to the Hybrid-Wing-Body (HWB) aircraft. The testing of a HWB fuselage section with Pultruded Rod Stitched Efficient Unitized Structure (PRSEUS) construction is presently being conducted at NASA Langley. Based on lessons learned from previous HWB structural design studies, improved finite-element models (FEM) of the HWB multi-bay and bulkhead assembly are developed to evaluate the performance of the PRSEUS construction. In order to assess the comparative weight reduction benefits of the PRSEUS technology, conventional cylindrical skin-stringer-frame models of a cylindrical and a double-bubble section fuselage concepts are developed. Stress analysis with design cabin-pressure load and scenario based case studies are conducted for design improvement in each case. Alternate analysis with stitched composite hat-stringers and C-frames are also presented, in addition to the foam-core sandwich frame and pultruded rod-stringer construction. The FEM structural stress, strain and weights are computed and compared for relative weight/strength benefit assessment. The structural analysis and specific weight comparison of these stitched composite advanced aircraft fuselage concepts demonstrated that the pressurized HWB fuselage section assembly can be structurally as efficient as the conventional cylindrical fuselage section with composite stringer-frame and PRSEUS construction, and significantly better than the conventional aluminum construction and the double-bubble section concept.

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

    NASA Astrophysics Data System (ADS)

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

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

  8. Building waste management core indicators through Spatial Material Flow Analysis: Net recovery and transport intensity indexes

    SciTech Connect

    Font Vivanco, David; Puig Ventosa, Ignasi; Gabarrell Durany, Xavier

    2012-12-15

    Highlights: Black-Right-Pointing-Pointer Sustainability and proximity principles have a key role in waste management. Black-Right-Pointing-Pointer Core indicators are needed in order to quantify and evaluate them. Black-Right-Pointing-Pointer A systematic, step-by-step approach is developed in this study for their development. Black-Right-Pointing-Pointer Transport may play a significant role in terms of environmental and economic costs. Black-Right-Pointing-Pointer Policy action is required in order to advance in the consecution of these principles. - Abstract: In this paper, the material and spatial characterization of the flows within a municipal solid waste (MSW) management system are combined through a Network-Based Spatial Material Flow Analysis. Using this information, two core indicators are developed for the bio-waste fraction, the Net Recovery Index (NRI) and the Transport Intensity Index (TII), which are aimed at assessing progress towards policy-related sustainable MSW management strategies and objectives. The NRI approaches the capacity of a MSW management system for converting waste into resources through a systematic metabolic approach, whereas the TII addresses efficiency in terms of the transport requirements to manage a specific waste flow throughout the entire MSW management life cycle. Therefore, both indicators could be useful in assessing key MSW management policy strategies, such as the consecution of higher recycling levels (sustainability principle) or the minimization of transport by locating treatment facilities closer to generation sources (proximity principle). To apply this methodological approach, the bio-waste management system of the region of Catalonia (Spain) has been chosen as a case study. Results show the adequacy of both indicators for identifying those points within the system with higher capacity to compromise its environmental, economic and social performance and therefore establishing clear targets for policy

  9. Advanced water window x-ray microscope design and analysis

    NASA Technical Reports Server (NTRS)

    Shealy, D. L.; Wang, C.; Jiang, W.; Lin, J.

    1992-01-01

    The project was focused on the design and analysis of an advanced water window soft-x-ray microscope. The activities were accomplished by completing three tasks contained in the statement of work of this contract. The new results confirm that in order to achieve resolutions greater than three times the wavelength of the incident radiation, it will be necessary to use aspherical mirror surfaces and to use graded multilayer coatings on the secondary (to accommodate the large variations of the angle of incidence over the secondary when operating the microscope at numerical apertures of 0.35 or greater). The results are included in a manuscript which is enclosed in the Appendix.

  10. Advanced Wireless Power Transfer Vehicle and Infrastructure Analysis (Presentation)

    SciTech Connect

    Gonder, J.; Brooker, A.; Burton, E.; Wang, J.; Konan, A.

    2014-06-01

    This presentation discusses current research at NREL on advanced wireless power transfer vehicle and infrastructure analysis. The potential benefits of E-roadway include more electrified driving miles from battery electric vehicles, plug-in hybrid electric vehicles, or even properly equipped hybrid electric vehicles (i.e., more electrified miles could be obtained from a given battery size, or electrified driving miles could be maintained while using smaller and less expensive batteries, thereby increasing cost competitiveness and potential market penetration). The system optimization aspect is key given the potential impact of this technology on the vehicles, the power grid and the road infrastructure.

  11. Advanced Technology Lifecycle Analysis System (ATLAS) Technology Tool Box (TTB)

    NASA Technical Reports Server (NTRS)

    Doyle, Monica; ONeil, Daniel A.; Christensen, Carissa B.

    2005-01-01

    The Advanced Technology Lifecycle Analysis System (ATLAS) is a decision support tool designed to aid program managers and strategic planners in determining how to invest technology research and development dollars. It is an Excel-based modeling package that allows a user to build complex space architectures and evaluate the impact of various technology choices. ATLAS contains system models, cost and operations models, a campaign timeline and a centralized technology database. Technology data for all system models is drawn from a common database, the ATLAS Technology Tool Box (TTB). The TTB provides a comprehensive, architecture-independent technology database that is keyed to current and future timeframes.

  12. Creep analysis of fuel plates for the Advanced Neutron Source

    SciTech Connect

    Swinson, W.F.; Yahr, G.T.

    1994-11-01

    The reactor for the planned Advanced Neutron Source will use closely spaced arrays of fuel plates. The plates are thin and will have a core containing enriched uranium silicide fuel clad in aluminum. The heat load caused by the nuclear reactions within the fuel plates will be removed by flowing high-velocity heavy water through narrow channels between the plates. However, the plates will still be at elevated temperatures while in service, and the potential for excessive plate deformation because of creep must be considered. An analysis to include creep for deformation and stresses because of temperature over a given time span has been performed and is reported herein.

  13. Design, analysis and test verification of advanced encapsulation systems

    NASA Technical Reports Server (NTRS)

    Garcia, A., III

    1982-01-01

    An analytical methodology for advanced encapsulation designs was developed. From these methods design sensitivities are established for the development of photovoltaic module criteria and the definition of needed research tasks. Analytical models were developed to perform optical, thermal, electrical and analyses on candidate encapsulation systems. From these analyses several candidate systems were selected for qualification testing. Additionally, test specimens of various types are constructed and tested to determine the validity of the analysis methodology developed. Identified deficiencies and/or discrepancies between analytical models and relevant test data are corrected. Prediction capability of analytical models is improved. Encapsulation engineering generalities, principles, and design aids for photovoltaic module designers is generated.

  14. Life-cycle cost analysis of advanced design mixer pump

    SciTech Connect

    Hall, M.N., Westinghouse Hanford

    1996-07-23

    This analysis provides cost justification for the Advanced Design Mixer Pump program based on the cost benefit to the Hanford Site of 4 mixer pump systems defined in terms of the life-cycle cost.A computer model is used to estimate the total number of service hours necessary for each mixer pump to operate over the 20-year retrieval sequence period for single-shell tank waste. This study also considered the double-shell tank waste retrieved prior to the single-shell tank waste which is considered the initial retrieval.

  15. Computer modeling for advanced life support system analysis.

    PubMed

    Drysdale, A

    1997-01-01

    This article discusses the equivalent mass approach to advanced life support system analysis, describes a computer model developed to use this approach, and presents early results from modeling the NASA JSC BioPlex. The model is built using an object oriented approach and G2, a commercially available modeling package Cost factor equivalencies are given for the Volosin scenarios. Plant data from NASA KSC and Utah State University (USU) are used, together with configuration data from the BioPlex design effort. Initial results focus on the importance of obtaining high plant productivity with a flight-like configuration. PMID:11540448

  16. ADVISOR: a systems analysis tool for advanced vehicle modeling

    NASA Astrophysics Data System (ADS)

    Markel, T.; Brooker, A.; Hendricks, T.; Johnson, V.; Kelly, K.; Kramer, B.; O'Keefe, M.; Sprik, S.; Wipke, K.

    This paper provides an overview of Advanced Vehicle Simulator (ADVISOR)—the US Department of Energy's (DOE's) ADVISOR written in the MATLAB/Simulink environment and developed by the National Renewable Energy Laboratory. ADVISOR provides the vehicle engineering community with an easy-to-use, flexible, yet robust and supported analysis package for advanced vehicle modeling. It is primarily used to quantify the fuel economy, the performance, and the emissions of vehicles that use alternative technologies including fuel cells, batteries, electric motors, and internal combustion engines in hybrid (i.e. multiple power sources) configurations. It excels at quantifying the relative change that can be expected due to the implementation of technology compared to a baseline scenario. ADVISOR's capabilities and limitations are presented and the power source models that are included in ADVISOR are discussed. Finally, several applications of the tool are presented to highlight ADVISOR's functionality. The content of this paper is based on a presentation made at the 'Development of Advanced Battery Engineering Models' workshop held in Crystal City, Virginia in August 2001.

  17. Analysis of SWOT spatial and temporal samplings over continents

    NASA Astrophysics Data System (ADS)

    Biancamaria, Sylvain; Lamy, Alain; Mognard, Nelly

    2014-05-01

    The future Surface Water and Ocean Topography (SWOT) satellite mission, collaboratively developed by NASA, CNES and CSA, is a joint oceanography/continental hydrology mission planned for launch in 2020. In June 2013, a new SWOT orbit has been selected with a 77.6° inclination, a 21 days repeat cycle and a 891 km altitude. The main satellite payload (a Ka-band SAR Interferometer), will provide 2D maps of water elevation, mask and slope over two swaths, both having a 50 km extent. These two swaths will be separated by a 20 km nadir gap. Most of the studies concerning SWOT published since 2007 have considered a former orbit with a 78° inclination, 22 day repeat orbit and a 970 km altitude and a 60 km extent for each swath. None of them have studied the newly selected orbit and the impact of the 20 km nadir gap on the spatial coverage has not been much explored. The purpose of the work presented here is to investigate the spatial and temporal coverage given this new orbit and the actual swath extent (2*50 km swaths with the 20 km nadir gap in between) and compare it to the former SWOT configuration. It is shown that the new configuration will have almost no impact on the computation of monthly averages, however it will impact the spatial coverage. Because of the nadir gap, the orbit repeatitivity and the swaths extent, 3.6% of the continental surfaces in between 78°S and 78°N will never be observed by SWOT (which was previously equal to 2.2% with the former SWOT configuration). The equatorial regions will be the most impacted, as uncovered area could go up to ~14% locally, whereas it never exceeded 9% with the previous SWOT configuration.

  18. Advanced analysis of metal distributions in human hair

    SciTech Connect

    Kempson, Ivan M.; Skinner, William M.

    2008-06-09

    A variety of techniques (secondary electron microscopy with energy dispersive X-ray analysis, time-of-flight-secondary ion mass spectrometry, and synchrotron X-ray fluorescence) were utilized to distinguish metal contamination occurring in hair arising from endogenous uptake from an individual exposed to a polluted environment, in this case a lead smelter. Evidence was sought for elements less affected by contamination and potentially indicative of biogenic activity. The unique combination of surface sensitivity, spatial resolution, and detection limits used here has provided new insight regarding hair analysis. Metals such as Ca, Fe, and Pb appeared to have little representative value of endogenous uptake and were mainly due to contamination. Cu and Zn, however, demonstrate behaviors worthy of further investigation into relating hair concentrations to endogenous function.

  19. Separation of spatial-temporal patterns ('climatic modes') by combined analysis of really measured and generated numerically vector time series

    NASA Astrophysics Data System (ADS)

    Feigin, A. M.; Mukhin, D.; Volodin, E. M.; Gavrilov, A.; Loskutov, E. M.

    2013-12-01

    The new method of decomposition of the Earth's climate system into well separated spatial-temporal patterns ('climatic modes') is discussed. The method is based on: (i) generalization of the MSSA (Multichannel Singular Spectral Analysis) [1] for expanding vector (space-distributed) time series in basis of spatial-temporal empirical orthogonal functions (STEOF), which makes allowance delayed correlations of the processes recorded in spatially separated points; (ii) expanding both real SST data, and longer by several times SST data generated numerically, in STEOF basis; (iii) use of the numerically produced STEOF basis for exclusion of 'too slow' (and thus not represented correctly) processes from real data. The application of the method allows by means of vector time series generated numerically by the INM RAS Coupled Climate Model [2] to separate from real SST anomalies data [3] two climatic modes possessing by noticeably different time scales: 3-5 and 9-11 years. Relations of separated modes to ENSO and PDO are investigated. Possible applications of spatial-temporal climatic patterns concept to prognosis of climate system evolution is discussed. 1. Ghil, M., R. M. Allen, M. D. Dettinger, K. Ide, D. Kondrashov, et al. (2002) "Advanced spectral methods for climatic time series", Rev. Geophys. 40(1), 3.1-3.41. 2. http://83.149.207.89/GCM_DATA_PLOTTING/GCM_INM_DATA_XY_en.htm 3. http://iridl.ldeo.columbia.edu/SOURCES/.KAPLAN/.EXTENDED/.v2/.ssta/

  20. Engineering genders: A spatial analysis of engineering, gender, and learning

    NASA Astrophysics Data System (ADS)

    Weidler-Lewis, Joanna R.

    This three article dissertation is an investigation into the ontology of learning insofar as learning is a process of becoming. In each article I explore the general questions of who is learning, in what ways, and with what consequences. The context for this research is undergraduate engineering education with particular attention to the construction of gender in this context. The first article is an examination of the organization of freshman engineering design. The second article draws on Lefebvre's spatial triad as both a theory and method for studying learning. The third article is an interview study of LGBTQA students creating their futures as engineers.

  1. Analysis of the impact of spatial resolution on land/water classifications using high-resolution aerial imagery

    USGS Publications Warehouse

    Enwright, Nicholas M.; Jones, William R.; Garber, Adrienne L.; Keller, Matthew J.

    2014-01-01

    Long-term monitoring efforts often use remote sensing to track trends in habitat or landscape conditions over time. To most appropriately compare observations over time, long-term monitoring efforts strive for consistency in methods. Thus, advances and changes in technology over time can present a challenge. For instance, modern camera technology has led to an increasing availability of very high-resolution imagery (i.e. submetre and metre) and a shift from analogue to digital photography. While numerous studies have shown that image resolution can impact the accuracy of classifications, most of these studies have focused on the impacts of comparing spatial resolution changes greater than 2 m. Thus, a knowledge gap exists on the impacts of minor changes in spatial resolution (i.e. submetre to about 1.5 m) in very high-resolution aerial imagery (i.e. 2 m resolution or less). This study compared the impact of spatial resolution on land/water classifications of an area dominated by coastal marsh vegetation in Louisiana, USA, using 1:12,000 scale colour-infrared analogue aerial photography (AAP) scanned at four different dot-per-inch resolutions simulating ground sample distances (GSDs) of 0.33, 0.54, 1, and 2 m. Analysis of the impact of spatial resolution on land/water classifications was conducted by exploring various spatial aspects of the classifications including density of waterbodies and frequency distributions in waterbody sizes. This study found that a small-magnitude change (1–1.5 m) in spatial resolution had little to no impact on the amount of water classified (i.e. percentage mapped was less than 1.5%), but had a significant impact on the mapping of very small waterbodies (i.e. waterbodies ≤ 250 m2). These findings should interest those using temporal image classifications derived from very high-resolution aerial photography as a component of long-term monitoring programs.

  2. Numerical analysis of the spatial range of the Kondo effect

    SciTech Connect

    Busser, C. A.; Martins, G. B.; Ribeiro, L. Costa; Vernek, E.; Anda, E. V.; Dagotto, Elbio R

    2010-01-01

    The spatial length of the Kondo screening is still a controversial issue related to Kondo physics. While renormalization-group and Bethe-Ansatz solutions have provided detailed information about the thermodynamics of magnetic impurities, they are insufficient to study the effect on the surrounding electrons, i.e., the spatial range of the correlations created by the Kondo effect between the localized magnetic moment and the conduction electrons. The objective of this work is to present a quantitative way of measuring the extension of these correlations by studying their effect directly on the local density of states (LDOS) at arbitrary distances from the impurity. The numerical techniques used, the embedded cluster approximation, the finite-U slave bosons, and numerical renormalization group, calculate the Green s functions in real space. With this information, one can calculate how the local density of states away from the impurity is modified by its presence, below and above the Kondo temperature, and then estimate the range of the disturbances in the noninteracting Fermi sea due to the Kondo effect, and how it changes with the Kondo temperature TK. The results obtained agree with results obtained through spin-spin correlations, showing that the LDOS captures the phenomenology of the Kondo cloud as well.

  3. Spatial compression algorithm for the analysis of very large multivariate images

    DOEpatents

    Keenan, Michael R.

    2008-07-15

    A method for spatially compressing data sets enables the efficient analysis of very large multivariate images. The spatial compression algorithms use a wavelet transformation to map an image into a compressed image containing a smaller number of pixels that retain the original image's information content. Image analysis can then be performed on a compressed data matrix consisting of a reduced number of significant wavelet coefficients. Furthermore, a block algorithm can be used for performing common operations more efficiently. The spatial compression algorithms can be combined with spectral compression algorithms to provide further computational efficiencies.

  4. Application of spatial features to satellite land-use analysis. [spectral signature variations

    NASA Technical Reports Server (NTRS)

    Smith, J.; Hornung, R.; Berry, J.

    1975-01-01

    A Level I land-use analysis of selected training areas of the Colorado Front Range was carried out using digital ERTS-A satellite imagery. Level I land-use categories included urban, agriculture (irrigated and dryland farming), rangeland, and forests. The spatial variations in spectral response for these land-use classes were analyzed using discrete two-dimensional Fourier transforms to isolate and extract spatial features. Analysis was performed on ERTS frame 1352-17134 (July 10, 1973) and frame number 1388-17131 (August 15, 1973). On training sets, spatial features yielded 80 to 100 percent classification accuracies with commission errors ranging from 0 to 20 percent.

  5. Information analysis of a spatial database for ecological land classification

    NASA Technical Reports Server (NTRS)

    Davis, Frank W.; Dozier, Jeff

    1990-01-01

    An ecological land classification was developed for a complex region in southern California using geographic information system techniques of map overlay and contingency table analysis. Land classes were identified by mutual information analysis of vegetation pattern in relation to other mapped environmental variables. The analysis was weakened by map errors, especially errors in the digital elevation data. Nevertheless, the resulting land classification was ecologically reasonable and performed well when tested with higher quality data from the region.

  6. The Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER): Data Products for the High Spatial Resolution Imager on NASA's EOS-AMI Platform

    NASA Technical Reports Server (NTRS)

    Abrams, M.

    1999-01-01

    The Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) is a high spatial resolution, multispectral imager with along-track stereo capabilities scheduled for launch on the first NASA spacecraft of the Earth Observing System (EOS AM-1) in mid-1999.

  7. 77 FR 69509 - Combining Modal Responses and Spatial Components in Seismic Response Analysis

    Federal Register 2010, 2011, 2012, 2013, 2014

    2012-11-19

    ... COMMISSION Combining Modal Responses and Spatial Components in Seismic Response Analysis AGENCY: Nuclear... Components in Seismic Response Analysis'' as an administratively changed guide in which there are minor... response analysis of nuclear power plant structures, systems, and components that are important to...

  8. Advanced Video Analysis Needs for Human Performance Evaluation

    NASA Technical Reports Server (NTRS)

    Campbell, Paul D.

    1994-01-01

    Evaluators of human task performance in space missions make use of video as a primary source of data. Extraction of relevant human performance information from video is often a labor-intensive process requiring a large amount of time on the part of the evaluator. Based on the experiences of several human performance evaluators, needs were defined for advanced tools which could aid in the analysis of video data from space missions. Such tools should increase the efficiency with which useful information is retrieved from large quantities of raw video. They should also provide the evaluator with new analytical functions which are not present in currently used methods. Video analysis tools based on the needs defined by this study would also have uses in U.S. industry and education. Evaluation of human performance from video data can be a valuable technique in many industrial and institutional settings where humans are involved in operational systems and processes.

  9. Tool for Sizing Analysis of the Advanced Life Support System

    NASA Technical Reports Server (NTRS)

    Yeh, Hue-Hsie Jannivine; Brown, Cheryl B.; Jeng, Frank J.

    2005-01-01

    Advanced Life Support Sizing Analysis Tool (ALSSAT) is a computer model for sizing and analyzing designs of environmental-control and life support systems (ECLSS) for spacecraft and surface habitats involved in the exploration of Mars and Moon. It performs conceptual designs of advanced life support (ALS) subsystems that utilize physicochemical and biological processes to recycle air and water, and process wastes in order to reduce the need of resource resupply. By assuming steady-state operations, ALSSAT is a means of investigating combinations of such subsystems technologies and thereby assisting in determining the most cost-effective technology combination available. In fact, ALSSAT can perform sizing analysis of the ALS subsystems that are operated dynamically or steady in nature. Using the Microsoft Excel spreadsheet software with Visual Basic programming language, ALSSAT has been developed to perform multiple-case trade studies based on the calculated ECLSS mass, volume, power, and Equivalent System Mass, as well as parametric studies by varying the input parameters. ALSSAT s modular format is specifically designed for the ease of future maintenance and upgrades.

  10. Spectral analysis and filtering techniques in digital spatial data processing

    USGS Publications Warehouse

    Pan, Jeng-Jong

    1989-01-01

    A filter toolbox has been developed at the EROS Data Center, US Geological Survey, for retrieving or removing specified frequency information from two-dimensional digital spatial data. This filter toolbox provides capabilities to compute the power spectrum of a given data and to design various filters in the frequency domain. Three types of filters are available in the toolbox: point filter, line filter, and area filter. Both the point and line filters employ Gaussian-type notch filters, and the area filter includes the capabilities to perform high-pass, band-pass, low-pass, and wedge filtering techniques. These filters are applied for analyzing satellite multispectral scanner data, airborne visible and infrared imaging spectrometer (AVIRIS) data, gravity data, and the digital elevation models (DEM) data. -from Author

  11. Detecting Hotspots from Taxi Trajectory Data Using Spatial Cluster Analysis

    NASA Astrophysics Data System (ADS)

    Zhao, P. X.; Qin, K.; Zhou, Q.; Liu, C. K.; Chen, Y. X.

    2015-07-01

    A method of trajectory clustering based on decision graph and data field is proposed in this paper. The method utilizes data field to describe spatial distribution of trajectory points, and uses decision graph to discover cluster centres. It can automatically determine cluster parameters and is suitable to trajectory clustering. The method is applied to trajectory clustering on taxi trajectory data, which are on the holiday (May 1st, 2014), weekday (Wednesday, May 7th, 2014) and weekend (Saturday, May 10th, 2014) respectively, in Wuhan City, China. The hotspots in four hours (8:00-9:00, 12:00-13:00, 18:00-19:00 and 23:00-24:00) for three days are discovered and visualized in heat maps. In the future, we will further research the spatiotemporal distribution and laws of these hotspots, and use more data to carry out the experiments.

  12. A spatial and genetic analysis of Cowbird host selection

    USGS Publications Warehouse

    Hahn, D.C.; Sedgwick, J.A.; Painter, I.S.; Casna, N.J.

    1999-01-01

    Our study of brood parasitism patterns in forest communities revealed the egg-laying frequency and host selection patterns of female cowbirds. By integrating molecular genetics and spatial data, we have the first published estimate on cowbird laying rates in field studies. The 29 females in the study laid only 1-5 eggs each, much lower than previous estimates from captive cowbirds and extrapolations from ovarian development in capture/recapture studies that had suggested that as many as 40 eggs could be laid per individual cowbird. Cowbird females also were shown for the first time to lay significantly more eggs within the home range areas they established rather than outside the home range. No patterns were uncovered for individual females preferentially parasitizing particular host species

  13. Combining microsimulation and spatial interaction models for retail location analysis

    NASA Astrophysics Data System (ADS)

    Nakaya, Tomoki; Fotheringham, A. Stewart; Hanaoka, Kazumasa; Clarke, Graham; Ballas, Dimitris; Yano, Keiji

    2007-12-01

    Although the disaggregation of consumers is crucial in understanding the fragmented markets that are dominant in many developed countries, it is not always straightforward to carry out such disaggregation within conventional retail modelling frameworks due to the limitations of data. In particular, consumer grouping based on sampled data is not assured to link with the other statistics that are vital in estimating sampling biases and missing variables in the sampling survey. To overcome this difficulty, we propose a useful combination of spatial interaction modelling and microsimulation approaches for the reliable estimation of retail interactions based on a sample survey of consumer behaviour being linked with other areal statistics. We demonstrate this approach by building an operational retail interaction model to estimate expenditure flows from households to retail stores in a local city in Japan, Kusatsu City.

  14. Spatial correlation analysis of cascading failures: Congestions and Blackouts

    NASA Astrophysics Data System (ADS)

    Daqing, Li; Yinan, Jiang; Rui, Kang; Havlin, Shlomo

    2014-06-01

    Cascading failures have become major threats to network robustness due to their potential catastrophic consequences, where local perturbations can induce global propagation of failures. Unlike failures spreading via direct contacts due to structural interdependencies, overload failures usually propagate through collective interactions among system components. Despite the critical need in developing protection or mitigation strategies in networks such as power grids and transportation, the propagation behavior of cascading failures is essentially unknown. Here we find by analyzing our collected data that jams in city traffic and faults in power grid are spatially long-range correlated with correlations decaying slowly with distance. Moreover, we find in the daily traffic, that the correlation length increases dramatically and reaches maximum, when morning or evening rush hour is approaching. Our study can impact all efforts towards improving actively system resilience ranging from evaluation of design schemes, development of protection strategies to implementation of mitigation programs.

  15. Adaptive Modeling, Engineering Analysis and Design of Advanced Aerospace Vehicles

    NASA Technical Reports Server (NTRS)

    Mukhopadhyay, Vivek; Hsu, Su-Yuen; Mason, Brian H.; Hicks, Mike D.; Jones, William T.; Sleight, David W.; Chun, Julio; Spangler, Jan L.; Kamhawi, Hilmi; Dahl, Jorgen L.

    2006-01-01

    This paper describes initial progress towards the development and enhancement of a set of software tools for rapid adaptive modeling, and conceptual design of advanced aerospace vehicle concepts. With demanding structural and aerodynamic performance requirements, these high fidelity geometry based modeling tools are essential for rapid and accurate engineering analysis at the early concept development stage. This adaptive modeling tool was used for generating vehicle parametric geometry, outer mold line and detailed internal structural layout of wing, fuselage, skin, spars, ribs, control surfaces, frames, bulkheads, floors, etc., that facilitated rapid finite element analysis, sizing study and weight optimization. The high quality outer mold line enabled rapid aerodynamic analysis in order to provide reliable design data at critical flight conditions. Example application for structural design of a conventional aircraft and a high altitude long endurance vehicle configuration are presented. This work was performed under the Conceptual Design Shop sub-project within the Efficient Aerodynamic Shape and Integration project, under the former Vehicle Systems Program. The project objective was to design and assess unconventional atmospheric vehicle concepts efficiently and confidently. The implementation may also dramatically facilitate physics-based systems analysis for the NASA Fundamental Aeronautics Mission. In addition to providing technology for design and development of unconventional aircraft, the techniques for generation of accurate geometry and internal sub-structure and the automated interface with the high fidelity analysis codes could also be applied towards the design of vehicles for the NASA Exploration and Space Science Mission projects.

  16. A modified SUnSAL-TV algorithm for hyperspectral unmixing based on spatial homogeneity analysis

    NASA Astrophysics Data System (ADS)

    Yuqian, Wang; Zhenfeng, Shao; Lei, Zhang; Weixun, Zhou

    2014-03-01

    The sparse regression framework has been introduced by many works to solve the linear spectral unmixing problem due to the knowledge that a pixel is usually mixed by less endmembers compared with the endmembers in spectral libraries or the entire hyperspectral data sets. Traditional sparse unmixing techniques focus on analyzing the spectral properties of hyperspectral imagery without incorporating spatial information. But the integration of spatial information would be beneficial to promote the performance of the linear unmixing process. An algorithm called sparse unmixing via variable splitting augmented Lagrangian and total variation (SUnSAL-TV) adds a total variation spatial regularizer besides the sparsity-inducing regularizer to the final unmixing objective function. The total variation spatial regularization is helpful to promote the fractional abundance smoothness. However, the abundance smoothness varies in the image. In this paper, the spatial smoothness is estimated through homogeneity analysis. Then the spatial regularizer is weighted for each pixel by a homogeneity index. The modified algorithm, called homogeneity analysis based SUnSAL-TV (SUnSAL-TVH), integrates the spatial information with finer modelling of spatial smoothness and is supposed insensitive to the noise and more stable. Experiments on synthetic data sets are taken and indicate the validity of our algorithm.

  17. Analysis of field-scale spatial correlations and variations of soil nutrients using geostatistics.

    PubMed

    Liu, Ruimin; Xu, Fei; Yu, Wenwen; Shi, Jianhan; Zhang, Peipei; Shen, Zhenyao

    2016-02-01

    Spatial correlations and soil nutrient variations are important for soil nutrient management. They help to reduce the negative impacts of agricultural nonpoint source pollution. Based on the sampled available nitrogen (AN), available phosphorus (AP), and available potassium (AK), soil nutrient data from 2010, the spatial correlation, was analyzed, and the probabilities of the nutrient's abundance or deficiency were discussed. This paper presents a statistical approach to spatial analysis, the spatial correlation analysis (SCA), which was originally developed for describing heterogeneity in the presence of correlated variation and based on ordinary kriging (OK) results. Indicator kriging (IK) was used to assess the susceptibility of excess of soil nutrients based on crop needs. The kriged results showed there was a distinct spatial variability in the concentration of all three soil nutrients. High concentrations of these three soil nutrients were found near Anzhou. As the distance from the center of town increased, the concentration of the soil nutrients gradually decreased. Spatially, the relationship between AN and AP was negative, and the relationship between AP and AK was not clear. The IK results showed that there were few areas with a risk of AN and AP overabundance. However, almost the entire study region was at risk of AK overabundance. Based on the soil nutrient distribution results, it is clear that the spatial variability of the soil nutrients differed throughout the study region. This spatial soil nutrient variability might be caused by different fertilizer types and different fertilizing practices. PMID:26832723

  18. Advanced probabilistic risk analysis using RAVEN and RELAP-7

    SciTech Connect

    Rabiti, Cristian; Alfonsi, Andrea; Mandelli, Diego; Cogliati, Joshua; Kinoshita, Robert

    2014-06-01

    RAVEN, under the support of the Nuclear Energy Advanced Modeling and Simulation (NEAMS) program [1], is advancing its capability to perform statistical analyses of stochastic dynamic systems. This is aligned with its mission to provide the tools needed by the Risk Informed Safety Margin Characterization (RISMC) path-lead [2] under the Department Of Energy (DOE) Light Water Reactor Sustainability program [3]. In particular this task is focused on the synergetic development with the RELAP-7 [4] code to advance the state of the art on the safety analysis of nuclear power plants (NPP). The investigation of the probabilistic evolution of accident scenarios for a complex system such as a nuclear power plant is not a trivial challenge. The complexity of the system to be modeled leads to demanding computational requirements even to simulate one of the many possible evolutions of an accident scenario (tens of CPU/hour). At the same time, the probabilistic analysis requires thousands of runs to investigate outcomes characterized by low probability and severe consequence (tail problem). The milestone reported in June of 2013 [5] described the capability of RAVEN to implement complex control logic and provide an adequate support for the exploration of the probabilistic space using a Monte Carlo sampling strategy. Unfortunately the Monte Carlo approach is ineffective with a problem of this complexity. In the following year of development, the RAVEN code has been extended with more sophisticated sampling strategies (grids, Latin Hypercube, and adaptive sampling). This milestone report illustrates the effectiveness of those methodologies in performing the assessment of the probability of core damage following the onset of a Station Black Out (SBO) situation in a boiling water reactor (BWR). The first part of the report provides an overview of the available probabilistic analysis capabilities, ranging from the different types of distributions available, possible sampling

  19. Dynamics of land change in India: a fine-scale spatial analysis

    NASA Astrophysics Data System (ADS)

    Meiyappan, P.; Roy, P. S.; Sharma, Y.; Jain, A. K.; Ramachandran, R.; Joshi, P. K.

    2015-12-01

    Land is scarce in India: India occupies 2.4% of worlds land area, but supports over 1/6th of worlds human and livestock population. This high population to land ratio, combined with socioeconomic development and increasing consumption has placed tremendous pressure on India's land resources for food, feed, and fuel. In this talk, we present contemporary (1985 to 2005) spatial estimates of land change in India using national-level analysis of Landsat imageries. Further, we investigate the causes of the spatial patterns of change using two complementary lines of evidence. First, we use statistical models estimated at macro-scale to understand the spatial relationships between land change patterns and their concomitant drivers. This analysis using our newly compiled extensive socioeconomic database at village level (~630,000 units), is 100x higher in spatial resolution compared to existing datasets, and covers over 200 variables. The detailed socioeconomic data enabled the fine-scale spatial analysis with Landsat data. Second, we synthesized information from over 130 survey based case studies on land use drivers in India to complement our macro-scale analysis. The case studies are especially useful to identify unobserved variables (e.g. farmer's attitude towards risk). Ours is the most detailed analysis of contemporary land change in India, both in terms of national extent, and the use of detailed spatial information on land change, socioeconomic factors, and synthesis of case studies.

  20. Using codispersion analysis to quantify and understand spatial patterns in species-environment relationships.

    PubMed

    Buckley, Hannah L; Case, Bradley S; Zimmerman, Jess K; Thompson, Jill; Myers, Jonathan A; Ellison, Aaron M

    2016-07-01

    The analysis of spatial patterns in species-environment relationships can provide new insights into the niche requirements and potential co-occurrence of species, but species abundance and environmental data are routinely collected at different spatial scales. Here, we investigate the use of codispersion analysis to measure and assess the scale, directionality and significance of complex relationships between plants and their environment in large forest plots. We applied codispersion analysis to both simulated and field data on spatially located tree species basal area and environmental variables. The significance of the observed bivariate spatial associations between the basal area of key species and underlying environmental variables was tested using three null models. Codispersion analysis reliably detected directionality (anisotropy) in bivariate species-environment relationships and identified relevant scales of effects. Null model-based significance tests applied to codispersion analyses of forest plot data enabled us to infer the extent to which environmental conditions, tree sizes and/or tree spatial positions underpinned the observed basal area-environment relationships, or whether relationships were a result of other unmeasured factors. Codispersion analysis, combined with appropriate null models, can be used to infer hypothesized ecological processes from spatial patterns, allowing us to start disentangling the possible drivers of plant species-environment relationships. PMID:27037819

  1. Ontology Driven Analysis of Spatio-temporal Phenomena, Aimed At Spatial Planning And Environmental Forecasting

    NASA Astrophysics Data System (ADS)

    Iwaniak, A.; Łukowicz, J.; Strzelecki, M.; Kaczmarek, I.

    2013-10-01

    Spatial planning is a crucial area for balancing civilization development with environmental protection. Spatial planning has a multidisciplinary nature. It must take into account the dynamics of the processes, which could affect the integrity of the environmental system. That is why we need a new approach to modelling phenomena occurring in space. Such approach is offered by ontologies, based on Description Logic (DL) and related to inference systems. Ontology is a system for the knowledge representation, including conceptual scheme and based on this scheme representation of reality. Ontologies can be enriched with additional logical systems. The authors present a way of building domain ontologies for spatial planning, including the representation of spatio-temporal phenomena. Description Logic is supplemented by structures of temporal logic. As a result, the analysis for exploring the topological relations between spatial objects will be extended to include temporal relationships: coincidence, precedence and succession, cause and effect relationship. Spatio-temporal models with temporal logic structures, encoded in ontologies, could be a subject of inference process, performed by semantic reasoners (reasoner engines). Spatio-temporal representations are offered, by so-called upper ontologies, such as GFO, BFO, OCHRE and others. Temporal structures provided in such ontologies, are useful for the analysis of data obtained from environmental and development monitoring systems and for description and representation of historical phenomena. They allow creating the models and scenarios of expected spatial transformation. They will support analysis for spatial development design, decision-making in spatial planning and forecasting of environmental impact.

  2. Abundant Topological Outliers in Social Media Data and Their Effect on Spatial Analysis.

    PubMed

    Westerholt, Rene; Steiger, Enrico; Resch, Bernd; Zipf, Alexander

    2016-01-01

    Twitter and related social media feeds have become valuable data sources to many fields of research. Numerous researchers have thereby used social media posts for spatial analysis, since many of them contain explicit geographic locations. However, despite its widespread use within applied research, a thorough understanding of the underlying spatial characteristics of these data is still lacking. In this paper, we investigate how topological outliers influence the outcomes of spatial analyses of social media data. These outliers appear when different users contribute heterogeneous information about different phenomena simultaneously from similar locations. As a consequence, various messages representing different spatial phenomena are captured closely to each other, and are at risk to be falsely related in a spatial analysis. Our results reveal indications for corresponding spurious effects when analyzing Twitter data. Further, we show how the outliers distort the range of outcomes of spatial analysis methods. This has significant influence on the power of spatial inferential techniques, and, more generally, on the validity and interpretability of spatial analysis results. We further investigate how the issues caused by topological outliers are composed in detail. We unveil that multiple disturbing effects are acting simultaneously and that these are related to the geographic scales of the involved overlapping patterns. Our results show that at some scale configurations, the disturbances added through overlap are more severe than at others. Further, their behavior turns into a volatile and almost chaotic fluctuation when the scales of the involved patterns become too different. Overall, our results highlight the critical importance of thoroughly considering the specific characteristics of social media data when analyzing them spatially. PMID:27611199

  3. Oesophageal cancer mortality in Spain: a spatial analysis

    PubMed Central

    Aragonés, Nuria; Ramis, Rebeca; Pollán, Marina; Pérez-Gómez, Beatriz; Gómez-Barroso, Diana; Lope, Virginia; Boldo, Elena Isabel; García-Pérez, Javier; López-Abente, Gonzalo

    2007-01-01

    Background Oesophageal carcinoma is one of the most common cancers worldwide. Its incidence and mortality rates show a wide geographical variation at a world and regional level. Geographic mapping of age-standardized, cause-specific death rates at a municipal level could be a helpful and powerful tool for providing clues leading to a better understanding of its aetiology. Methods This study sought to describe the geographic distribution of oesophageal cancer mortality for Spain's 8077 towns, using the autoregressive spatial model proposed by Besag, York and Mollié. Maps were plotted, depicting standardised mortality ratios, smoothed relative risk (RR) estimates, and the spatial pattern of the posterior probability of RR being greater than 1. Results Important differences associated with area of residence were observed in risk of dying from oesophageal cancer in Spain during the study period (1989–1998). Among men, excess risk appeared across the north of the country, along a band spanning the length of the Cantabrian coastline, Navarre, the north of Castile & León and the north-west of La Rioja. Excess risk was likewise observed in the provinces of Cadiz and part of Seville in Andalusia, the islands of Tenerife and Gran Canaria, and some towns in the Barcelona and Gerona areas. Among women, there was a noteworthy absence of risk along the mid-section of the Cantabrian seaboard, and increases in mortality, not observed for men, in the west of Extremadura and south-east of Andalusia. Conclusion These major gender- and area-related geographical differences in risk would seem to reflect differences in the prevalence of some well-established and modifiable risk factors, including smoking, alcohol consumption, obesity and diet. In addition, excess risks were in evidence for both sexes in some areas, possibly suggesting the implication of certain local environmental or socio-cultural factors. From a public health standpoint, small-area studies could be very useful for

  4. Recent advances in (soil moisture) triple collocation analysis

    NASA Astrophysics Data System (ADS)

    Gruber, A.; Su, C.-H.; Zwieback, S.; Crow, W.; Dorigo, W.; Wagner, W.

    2016-03-01

    To date, triple collocation (TC) analysis is one of the most important methods for the global-scale evaluation of remotely sensed soil moisture data sets. In this study we review existing implementations of soil moisture TC analysis as well as investigations of the assumptions underlying the method. Different notations that are used to formulate the TC problem are shown to be mathematically identical. While many studies have investigated issues related to possible violations of the underlying assumptions, only few TC modifications have been proposed to mitigate the impact of these violations. Moreover, assumptions, which are often understood as a limitation that is unique to TC analysis are shown to be common also to other conventional performance metrics. Noteworthy advances in TC analysis have been made in the way error estimates are being presented by moving from the investigation of absolute error variance estimates to the investigation of signal-to-noise ratio (SNR) metrics. Here we review existing error presentations and propose the combined investigation of the SNR (expressed in logarithmic units), the unscaled error variances, and the soil moisture sensitivities of the data sets as an optimal strategy for the evaluation of remotely-sensed soil moisture data sets.

  5. Identifying Naturally Occurring Retirement Communities: A Spatial Analysis

    PubMed Central

    Rivera-Hernandez, Maricruz; Yamashita, Takashi; Kinney, Jennifer M.

    2016-01-01

    Objectives Guided by the concept of “aging in place” and potential policy implications, the study analyzed naturally occurring retirement communities (NORCs; 40% or greater house owners and renters aged 65 years and older) and whether there were spatiotemporal patterns in Ohio between 2000 and 2010. Method Data were derived from the 2000 and 2010 census tracts. Geovisualization was used to visually examine the distribution of NORCs in 2000 and 2010. Global Moran’s I was used to quantify the spatial distribution of NORCs in Ohio and Local Moran’s I was used to identify clusters of NORCs (i.e., hot spots). Results The number of NORCs slightly decreased despite the overall increase of the older population from 2000 to 2010. NORCs were identified in one of the 3 most populous counties (i.e., Cuyahoga) and its neighboring counties. A number of hot spots were identified in Cuyahoga County (among Ohio’s most populous and NORC-rich counties), both in 2000 and 2010. There were different patterns including emerging, disappearing, and enduring NORCs and disproportionate distributions of NORCs across the state between 2000 and 2010. Discussion Locating NORCs could aid governments to create “aging in place” sensitive policies to address issues of independence, social care, health care, volunteerism, and community participation. PMID:24958694

  6. Urban expansion analysis based on spatial variables derived from multi-temporal remote sensing imagery

    NASA Astrophysics Data System (ADS)

    Yang, Yetao; Wang, Yingying; Zhou, Qiming; Gong, Jianya

    2008-10-01

    In this research, we focus on the spatial pattern of the urban expansion. The spatial pattern of the urban area can be quantitatively delineated by many spatial variables. Numerous spatial variables have been examined to evaluate their applicability to the urban change. These metrics include road network accessibility, built-up density and some landscape metrics. Remote sensing technology was used for monitoring dynamic urban change. Multi-temporal Landsat TM images (1988, 1991, 1994, 1997, 2000, and 2002) were used for the change detection using post-classification comparison method. The road network and its change were extracted from multitemporal images using the GDPA algorithm. Contagion, one of the landscape metrics, was selected, because it it can describe the heterogeneity of the suburban area, where the landuse change is most likely to happen. Analysis has also been conducted to identify the relationship between urban change and these spatial variables.

  7. Violence, drug markets and racial composition: challenging stereotypes through spatial analysis.

    PubMed

    Lum, Cynthia

    2011-01-01

    Places in which there is a strong spatial connection between violence and drug activity can often evoke particular stereotypes. They are believed to be places marked by high levels of social disorganisation, unemployment, disorder and racial heterogeneity. Yet scholars have argued that the spatial relationship between drug market activity and violence is more complicated and that other factors may explain this geographical connection. In the first article of this two-part series, different types of spatial analysis were employed to describe crime concentrations of drugs and violence. Evidence was found that challenges the notion that places with drug activity are inevitably more violent. This second paper examines what factors predict these variations in drug–violence spatial patterns in Seattle when derived using different spatial methods. The findings indicate that racial composition, disorder and unemployment may not be as salient as once believed in predicting places that are violent drug markets. PMID:22165156

  8. Classifying Urban Land cover using Spatial Weights: A Comparison of Discriminant Analysis and Markov Random Fields

    NASA Astrophysics Data System (ADS)

    Wentz, E.; Song, Y.

    2011-12-01

    Classifying urban area images is challenging because of the heterogeneous nature of the urban landscape. This means that each pixel represents a mixture of classes with potentially highly variable various spectral values. Land cover classification approaches using ancillary data, such as knowledge based or expert systems, have shown to improve the classification accuracy in urban areas, particularly with medium or low-resolution imagery. This is because information other than the spectral signatures is used to assign pixels to classes. Defining rules is challenging and acquiring appropriate ancillary data may not always be possible. The goal of this study is to compare the results of three approaches to classify urban land cover with medium resolution data with and without ancillary information. We compare discriminant analysis, Markov random fields, and an expert system. Furthermore, we explore whether including spatial weights improves classification accuracy of the discriminant model. Discriminant analysis is a statistical technique used to predict group membership for a pixel based on the linear combination of independent variables. Adding spatial weights to this includes a weighted value for neighboring pixels. Markov random fields represent spatial dependencies through conditional relationships defined using Markov principles. In comparison to using spatial dependencies in neighbouring pixels, strict per pixel statistical analysis, however, does not consider the spatial dependencies among neighbouring pixels. Our study showed that approaches using ancillary data continued to outperform strict spectral classifiers but that using a spatial weight improved the results. Furthermore, results demonstrate that when the discriminant analysis technique works well then the spatially weighted approach works better. However, when the discriminant analysis performs ineffectively, those poor results are magnified. This study suggests that spatial weights improve the

  9. Cartographic Modeling: Computer-assisted Analysis of Spatially Defined Neighborhoods

    NASA Technical Reports Server (NTRS)

    Berry, J. K.; Tomlin, C. D.

    1982-01-01

    Cartographic models addressing a wide variety of applications are composed of fundamental map processing operations. These primitive operations are neither data base nor application-specific. By organizing the set of operations into a mathematical-like structure, the basis for a generalized cartographic modeling framework can be developed. Among the major classes of primitive operations are those associated with reclassifying map categories, overlaying maps, determining distance and connectivity, and characterizing cartographic neighborhoods. The conceptual framework of cartographic modeling is established and techniques for characterizing neighborhoods are used as a means of demonstrating some of the more sophisticated procedures of computer-assisted map analysis. A cartographic model for assessing effective roundwood supply is briefly described as an example of a computer analysis. Most of the techniques described have been implemented as part of the map analysis package developed at the Yale School of Forestry and Environmental Studies.

  10. Recent advances in computational structural reliability analysis methods

    NASA Technical Reports Server (NTRS)

    Thacker, Ben H.; Wu, Y.-T.; Millwater, Harry R.; Torng, Tony Y.; Riha, David S.

    1993-01-01

    The goal of structural reliability analysis is to determine the probability that the structure will adequately perform its intended function when operating under the given environmental conditions. Thus, the notion of reliability admits the possibility of failure. Given the fact that many different modes of failure are usually possible, achievement of this goal is a formidable task, especially for large, complex structural systems. The traditional (deterministic) design methodology attempts to assure reliability by the application of safety factors and conservative assumptions. However, the safety factor approach lacks a quantitative basis in that the level of reliability is never known and usually results in overly conservative designs because of compounding conservatisms. Furthermore, problem parameters that control the reliability are not identified, nor their importance evaluated. A summary of recent advances in computational structural reliability assessment is presented. A significant level of activity in the research and development community was seen recently, much of which was directed towards the prediction of failure probabilities for single mode failures. The focus is to present some early results and demonstrations of advanced reliability methods applied to structural system problems. This includes structures that can fail as a result of multiple component failures (e.g., a redundant truss), or structural components that may fail due to multiple interacting failure modes (e.g., excessive deflection, resonate vibration, or creep rupture). From these results, some observations and recommendations are made with regard to future research needs.

  11. Advanced Stress, Strain And Geometrical Analysis In Semiconductor Devices

    SciTech Connect

    Neels, Antonia; Dommann, Alex; Niedermann, Philippe; Farub, Claudiu; Kaenel, Hans von

    2010-11-24

    High stresses and defect densities increases the risk of semiconductor device failure. Reliability studies on potential failure sources have an impact on design and are essential to assure the long term functioning of the device. Related to the dramatically smaller volume of semiconductor devices and new bonding techniques on such devices, new methods in testing and qualification are needed. Reliability studies on potential failure sources have an impact on design and are essential to assure the long term functioning of the device. In this paper, the applications of advanced High Resolution X-ray Diffraction (HRXRD) methods in strain, defect and deformation analysis on semiconductor devices are discussed. HRXRD with Rocking Curves (RC's) and Reciprocal Space Maps (RSM's) is used as accurate, non-destructive experimental method to evaluate the crystalline quality, and more precisely for the given samples, the in-situ strain, defects and geometrical parameters such as tilt and bending of device. The combination with advanced FEM simulations gives the possibility to support efficiently semiconductor devices design.

  12. Utilizing Exploratory Spatial Data Analysis to Examine Health and Environmental Disparities in Disadvantaged Neighborhoods

    PubMed Central

    Osiecki, Kristin M.; Kim, Seijeoung; Chukwudozie, Ifeanyi B.; Calhoun, Elizabeth A.

    2013-01-01

    Health disparities research has focused primarily on racial and socioeconomic differences in health outcomes. Although neighborhood characteristics and the concept of built environment have been shown to affect individual health, measuring the effects of environmental risks on health has been a less developed area of disparities research. To examine spatial associations and the distribution of geographic patterns of sociodemographic characteristics, environmental cancer risk, and cancer rates, we utilized existing data from multiple sources. The findings from our initial analysis, which concerned with proximity to environmental hazards and at-risk communities, were consistent with results of previous studies, which often reported mixed relationships between health disparity indicators and environmental burden. However, further analysis with refined models showed that several key demographic and subdomains of cancer risk measures were shown to have spatial components. With the application of exploratory spatial data analysis, we were able to identify areas with both high rates of poverty and racial minorities to further examine for possible associations to environmental cancer risk. Global spatial autocorrelation found spatial clustering with percent black, percent poverty, point and non-point cancer risks requiring further spatial analysis to determine relationship of significance based on geography. This methodology was based upon particular assumptions associated with data and applications, which needed to be met. We conclude that careful assessment of the data and applications were required to properly interpret the findings in understanding the relationship between vulnerable populations and environmental burden. PMID:26594302

  13. Analysis of primary and secondary influences on spatial neglect.

    PubMed

    Adair, J C; Na, D L; Schwartz, R L; Heilman, K M

    1998-08-01

    When attempting to determine the middle of a line, patients with neglect deviate from true center. Deviation may be induced by perceptual-attentional bias, premotor-intentional bias, or both. Using a video-based apparatus, we decoupled perceptual from premotor influences on line bisection performance in patients with hemispatial neglect to examine (a) the relationship between primary and secondary bias and (b) the relationship of bias type to lesion location. The same video-based procedure was applied to target cancellation to determine if neglect type varied as a function of task. Primary attentional-perceptual bias was found using line bisection in 14/26 subjects, most of whom had lesions involving the posterior hemisphere. Primary premotor-intentional bias on line bisection was more often associated with lesions of frontal-subcortical structures. The neglect type determined by the bisection task agreed with the results of target cancellation in most cases. Secondary bias was determined based upon whether decoupling decreased the magnitude of bisection error (concordant), increased error (discordant), or produced no significant change. Most patients showed a secondary bias, with 12/26 in the discordant group and 11/26 in the concordant group. Discordant secondary bias was more common in premotor-intentional neglect (10/12) than in perceptual-attentional neglect (2/14), whereas concordant bias was more common in the latter group (10/14) compared to the former (1/12). The nonrandom relationship between primary and secondary bias may provide a more detailed description of ways in which anatomically separate components of a cortical network contribute to spatial processing under conditions of perceptuomotor incongruity. PMID:9733554

  14. Spatial analysis and the measurement of urban sprawl

    NASA Astrophysics Data System (ADS)

    Chin, Nancy Ngan Gee

    The thesis extends the research of the SCATTER project which evaluates the understanding of urban sprawl in Europe and examines methods for quantifying sprawl. The thesis extends this by examining the extent to which the definition and identification of sprawl is influenced by the nature of the indicators and measures used, and on the scale at which they are applied. It assesses the suitability of measures used in the US context for the polycentric pattern of European cities. Measures used in the European context have been based on land use densities - this is extended to incorporate measures based on urban form and land use patterns. The findings highlight the difficulties inherent in defining and measuring sprawl, as sprawl is a complex phenomenon with experts in the regions often unable to agree on the patterns and consequences of this type of urban growth. It is not so much a specific land use pattern or set of patterns as a manifestation of concerns which are common features of modern urban growth - regardless of urban form - and which emerge from the emphasis of interpretation and the dimensions of interest to local administrators and land use authorities. The research has identified that measures are sensitive to the spatial area used - even areas with some similarities, such as county and travel to work areas or district and urban areas do not produce consistent results. In Europe therefore measuring sprawl is also complicated by the fact that self contained subcentres set in low density rural areas may contribute to sprawl in the city centre, yet this is not identified by traditional measures of sprawl which assume that areas related to the urban centre are contiguous.

  15. Boundaries, links and clusters: a new paradigm in spatial analysis?

    PubMed Central

    Jacquez, Geoff M.; Kaufmann, Andy; Goovaerts, Pierre

    2008-01-01

    comprehensive description of spatial pattern. PMID:19023453

  16. Spatial sensitivity analysis of snow cover data in a distributed rainfall-runoff model

    NASA Astrophysics Data System (ADS)

    Berezowski, T.; Nossent, J.; Chormański, J.; Batelaan, O.

    2014-10-01

    As the availability of spatially distributed data sets for distributed rainfall-runoff modelling is strongly growing, more attention should be paid to the influence of the quality of the data on the calibration. While a lot of progress has been made on using distributed data in simulations of hydrological models, sensitivity of spatial data with respect to model results is not well understood. In this paper we develop a spatial sensitivity analysis (SA) method for snow cover fraction input data (SCF) for a distributed rainfall-runoff model to investigate if the model is differently subjected to SCF uncertainty in different zones of the model. The analysis was focused on the relation between the SCF sensitivity and the physical, spatial parameters and processes of a distributed rainfall-runoff model. The methodology is tested for the Biebrza River catchment, Poland for which a distributed WetSpa model is setup to simulate two years of daily runoff. The SA uses the Latin-Hypercube One-factor-At-a-Time (LH-OAT) algorithm, which uses different response functions for each 4 km × 4 km snow zone. The results show that the spatial patterns of sensitivity can be easily interpreted by co-occurrence of different environmental factors such as: geomorphology, soil texture, land-use, precipitation and temperature. Moreover, the spatial pattern of sensitivity under different response functions is related to different spatial parameters and physical processes. The results clearly show that the LH-OAT algorithm is suitable for the spatial sensitivity analysis approach and that the SCF is spatially sensitive in the WetSpa model.

  17. Systems analysis and futuristic designs of advanced biofuel factory concepts.

    SciTech Connect

    Chianelli, Russ; Leathers, James; Thoma, Steven George; Celina, Mathias Christopher; Gupta, Vipin P.

    2007-10-01

    The U.S. is addicted to petroleum--a dependency that periodically shocks the economy, compromises national security, and adversely affects the environment. If liquid fuels remain the main energy source for U.S. transportation for the foreseeable future, the system solution is the production of new liquid fuels that can directly displace diesel and gasoline. This study focuses on advanced concepts for biofuel factory production, describing three design concepts: biopetroleum, biodiesel, and higher alcohols. A general schematic is illustrated for each concept with technical description and analysis for each factory design. Looking beyond current biofuel pursuits by industry, this study explores unconventional feedstocks (e.g., extremophiles), out-of-favor reaction processes (e.g., radiation-induced catalytic cracking), and production of new fuel sources traditionally deemed undesirable (e.g., fusel oils). These concepts lay the foundation and path for future basic science and applied engineering to displace petroleum as a transportation energy source for good.

  18. Advanced XAS Analysis for Investigating Fuel Cell Electrocatalysts

    SciTech Connect

    Witkowska, Agnieszka; Principi, Emiliano; Di Cicco, Andrea; Marassi, Roberto

    2007-02-02

    In the paper we present an accurate structural study of a Pt-based electrode by means of XAS, accounting for both the catalytic nanoparticles size distribution and sample inhomogeneities. Morphology and size distribution of the nanoparticles were investigated by scanning electron microscopy (SEM), transmission electron microscopy (TEM) and X-ray diffraction techniques. XAS data-analysis was performed using advanced multiple-scattering techniques (GNXAS), disentangling possible effects due to surface atom contributions in nanoparticles and sample homogeneity, contributing to a reduction of intensity of the structural signal. This approach for XAS investigation of electrodes of FC devices can represent a viable and reliable way to understand structural details, important for producing more efficient catalytic materials.

  19. Analysis of biofluids by paper spray MS: advances and challenges.

    PubMed

    Manicke, Nicholas E; Bills, Brandon J; Zhang, Chengsen

    2016-03-01

    Paper spray MS is part of a cohort of ambient ionization or direct analysis methods that seek to analyze complex samples without prior sample preparation. Extraction and electrospray ionization occur directly from the paper substrate upon which a dried matrix spot is stored. Paper spray MS is capable of detecting drugs directly from dried blood, plasma and urine spots at the low ng/ml to pg/ml levels without sample preparation. No front end separation is performed, so MS/MS or high-resolution MS is required. Here, we discuss paper spray methodology, give a comprehensive literature review of the use of paper spray MS for bioanalysis, discuss technological advancements and variations on this technique and discuss some of its limitations. PMID:26916068

  20. Beam Optics Analysis - An Advanced 3D Trajectory Code

    SciTech Connect

    Ives, R. Lawrence; Bui, Thuc; Vogler, William; Neilson, Jeff; Read, Mike; Shephard, Mark; Bauer, Andrew; Datta, Dibyendu; Beal, Mark

    2006-01-03

    Calabazas Creek Research, Inc. has completed initial development of an advanced, 3D program for modeling electron trajectories in electromagnetic fields. The code is being used to design complex guns and collectors. Beam Optics Analysis (BOA) is a fully relativistic, charged particle code using adaptive, finite element meshing. Geometrical input is imported from CAD programs generating ACIS-formatted files. Parametric data is inputted using an intuitive, graphical user interface (GUI), which also provides control of convergence, accuracy, and post processing. The program includes a magnetic field solver, and magnetic information can be imported from Maxwell 2D/3D and other programs. The program supports thermionic emission and injected beams. Secondary electron emission is also supported, including multiple generations. Work on field emission is in progress as well as implementation of computer optimization of both the geometry and operating parameters. The principle features of the program and its capabilities are presented.

  1. Recent trends in the advanced analysis of bioactive fatty acids.

    PubMed

    Ruiz-Rodriguez, Alejandro; Reglero, Guillermo; Ibañez, Elena

    2010-01-20

    The consumption of dietary fats have been long associated to chronic diseases such as obesity, diabetes, cancer, arthritis, asthma, and cardiovascular disease; although some controversy still exists in the role of dietary fats in human health, certain fats have demonstrated their positive effect in the modulation of abnormal fatty acid and eicosanoid metabolism, both of them associated to chronic diseases. Among the different fats, some fatty acids can be used as functional ingredients such as alpha-linolenic acid (ALA), arachidonic acid (AA), eicosapentaenoic acid (EPA), docosahexaenoic acid (DHA), gamma-linolenic acid (GLA), stearidonic acid (STA) and conjugated linoleic acid (CLA), among others. The present review is focused on recent developments in FAs analysis, covering sample preparation methods such as extraction, fractionation and derivatization as well as new advances in chromatographic methods such as GC and HPLC. Special attention is paid to trans fatty acids due its increasing interest for the food industry. PMID:19525080

  2. Beam Optics Analysis — An Advanced 3D Trajectory Code

    NASA Astrophysics Data System (ADS)

    Ives, R. Lawrence; Bui, Thuc; Vogler, William; Neilson, Jeff; Read, Mike; Shephard, Mark; Bauer, Andrew; Datta, Dibyendu; Beal, Mark

    2006-01-01

    Calabazas Creek Research, Inc. has completed initial development of an advanced, 3D program for modeling electron trajectories in electromagnetic fields. The code is being used to design complex guns and collectors. Beam Optics Analysis (BOA) is a fully relativistic, charged particle code using adaptive, finite element meshing. Geometrical input is imported from CAD programs generating ACIS-formatted files. Parametric data is inputted using an intuitive, graphical user interface (GUI), which also provides control of convergence, accuracy, and post processing. The program includes a magnetic field solver, and magnetic information can be imported from Maxwell 2D/3D and other programs. The program supports thermionic emission and injected beams. Secondary electron emission is also supported, including multiple generations. Work on field emission is in progress as well as implementation of computer optimization of both the geometry and operating parameters. The principle features of the program and its capabilities are presented.

  3. Advanced functional network analysis in the geosciences: The pyunicorn package

    NASA Astrophysics Data System (ADS)

    Donges, Jonathan F.; Heitzig, Jobst; Runge, Jakob; Schultz, Hanna C. H.; Wiedermann, Marc; Zech, Alraune; Feldhoff, Jan; Rheinwalt, Aljoscha; Kutza, Hannes; Radebach, Alexander; Marwan, Norbert; Kurths, Jürgen

    2013-04-01

    Functional networks are a powerful tool for analyzing large geoscientific datasets such as global fields of climate time series originating from observations or model simulations. pyunicorn (pythonic unified complex network and recurrence analysis toolbox) is an open-source, fully object-oriented and easily parallelizable package written in the language Python. It allows for constructing functional networks (aka climate networks) representing the structure of statistical interrelationships in large datasets and, subsequently, investigating this structure using advanced methods of complex network theory such as measures for networks of interacting networks, node-weighted statistics or network surrogates. Additionally, pyunicorn allows to study the complex dynamics of geoscientific systems as recorded by time series by means of recurrence networks and visibility graphs. The range of possible applications of the package is outlined drawing on several examples from climatology.

  4. Procedures for analysis of spatial relationships among ship survey data and sea surface temperature

    NASA Technical Reports Server (NTRS)

    Berry, J. K.; Sailor, J. K.

    1981-01-01

    The establishment of a limited spatial data base for the U.S. eastern seaboard vicinity is discussed along with the demonstration of computer assisted analysis techniques for investigating spatial patterns and relationships among ship survey data and remotely sensed sea surface temperature. Ship survey variables included concentrations of two zooplankton, two icthyoplankton, and two fish species, in addition to physical data of depth to bottom and surface and bottom water temperatures. Continuous spatial distributions of these data were created by both weighted nearest neighbor and iterative smoothing interpolation techniques. Maps of surface water temperature were created by digitizing GOES satellite images. All mapped data were spatially registered by conversion of latitude and longitude coordinates to rotated Lambert conic conformal rectilinear coordinates and stored in grid format of approximately one hundred square kilometers per cell. The analysis of these data include the generation of statistical summaries and maps describing the joint occurrence among variables.

  5. Integration of Spatial and Social Network Analysis in Disease Transmission Studies

    PubMed Central

    Root, Elisabeth D; Giebultowicz, Sophia; Ali, Mohammad; Perez-Heydrich, Carolina; Yunus, Mohammad

    2013-01-01

    This study presents a case study of how social network and spatial analytical methods can be used simultaneously for disease transmission modeling. The paper first reviews strategies employed in previous studies and then offers the example of transmission of two bacterial diarrheal diseases in rural Bangladesh. The goal is to understand how diseases vary socially above and beyond the effects of the local neighborhood context. Patterns of cholera and shigellosis incidence are analyzed in space and within kinship-based social networks in Matlab, Bangladesh. Data include a spatially referenced longitudinal demographic database which consists of approximately 200,000 people and laboratory-confirmed cholera and shigellosis cases from 1983 to 2003. Matrices are created of kinship ties between households using a complete network design and distance matrices are also created to model spatial relationships. Moran's I statistics are calculated to measure clustering within both social and spatial matrices. Combined spatial effects-spatial disturbance models are built to simultaneously analyze spatial and social effects while controlling for local environmental context. Results indicate that cholera and shigellosis always clusters in space and only sometimes within social networks. This suggests that the local environment is most important for understanding transmission of both diseases however kinship-based social networks also influence their transmission. Simultaneous spatial and social network analysis can help us better understand disease transmission and this study has offered several strategies on how. PMID:24163443

  6. Advanced in aerospace lubricant and wear metal analysis

    SciTech Connect

    Saba, C.S.; Centers, P.W.

    1995-09-01

    Wear metal analysis continues to play an effective diagnostic role for condition monitoring of gas turbine engines. Since the early 1960s the United States` military services have been using spectrometric oil analysis program (SOAP) to monitor the condition of aircraft engines. The SOAP has proven to be effective in increasing reliability, fleet readiness and avoiding losses of lives and machinery. Even though historical data have demonstrated the success of the SOAP in terms of detecting imminent engine failure verified by maintenance personnel, the SOAP is not a stand-alone technique and is limited in its detection of large metallic wear debris. In response, improved laboratory, portable, in-line and on-line diagnostic techniques to perfect SOAP and oil condition monitoring have been sought. The status of research and development as well as the direction of future developmental activities in oil analysis due to technological opportunities, advanced in engine development and changes in military mission are reviewed and discussed. 54 refs.

  7. Spatial and temporal variability of VAS radiance measurements by structure and correlation analysis

    NASA Technical Reports Server (NTRS)

    Hillger, Donald W.; Purdom, James F. W.; Jones, Andrew S.; Vonder Haar, Thomas H.

    1988-01-01

    The statistical structure function analysis presently applied to VISSR Atmospheric Sounder (VAS) measurements has been extended to include time, and yields structure plots in either two spatial dimensions or one spatial dimension and time that indicate three-dimensional measurement variability. The analyses that include time as a coordinate also yield an indication of the mean speed and direction of the analyzed data. Results for three-hourly VAS data indicate that sampling at a high, approximately 1-hour, frequency is required in order to correctly monitor VAS measurements' temporal variability in a way equivalent to high spatial resolution.

  8. Ultrafast laser induced breakdown spectroscopy for high spatial resolution chemical analysis

    NASA Astrophysics Data System (ADS)

    Zorba, Vassilia; Mao, Xianglei; Russo, Richard E.

    2011-02-01

    Femtosecond laser induced breakdown spectroscopy (LIBS) was used to identify the spatial resolution limitations and assess the minimal detectable mass restrictions in laser-ablation based chemical analysis. The atomic emission of sodium (Na) and potassium (K) dopants in transparent dielectric Mica matrices was studied, to find that both these elements could be detected from 450 nm diameter ablation craters, full-width-at-half-maximum (FWHM). Under optimal conditions, mass as low as 220 ag was measured, demonstrating the feasibility of using laser-ablation based chemical analysis to achieve high spatial resolution elemental analysis in real-time and at atmospheric pressure conditions.

  9. An exploratory spatial analysis of soil organic carbon distribution in Canadian eco-regions

    NASA Astrophysics Data System (ADS)

    Tan, S.-Y.; Li, J.

    2014-11-01

    As the largest carbon reservoir in ecosystems, soil accounts for more than twice as much carbon storage as that of vegetation biomass or the atmosphere. This paper examines spatial patterns of soil organic carbon (SOC) in Canadian forest areas at an eco-region scale of analysis. The goal is to explore the relationship of SOC levels with various climatological variables, including temperature and precipitation. The first Canadian forest soil database published in 1997 by the Canada Forest Service was analyzed along with other long-term eco-climatic data (1961 to 1991) including precipitation, air temperature, slope, aspect, elevation, and Normalized Difference Vegetation Index (NDVI) derived from remote sensing imagery. In addition, the existing eco-region framework established by Environment Canada was evaluated for mapping SOC distribution. Exploratory spatial data analysis techniques, including spatial autocorrelation analysis, were employed to examine how forest SOC is spatially distributed in Canada. Correlation analysis and spatial regression modelling were applied to determine the dominant ecological factors influencing SOC patterns at the eco-region level. At the national scale, a spatial error regression model was developed to account for spatial dependency and to estimate SOC patterns based on ecological and ecosystem factors. Based on the significant variables derived from the spatial error model, a predictive SOC map in Canadian forest areas was generated. Although overall SOC distribution is influenced by climatic and topographic variables, distribution patterns are shown to differ significantly between eco-regions. These findings help to validate the eco-region classification framework for SOC zonation mapping in Canada.

  10. Spatial characterization of landscapes through multifractal analysis of DEM.

    PubMed

    Aguado, P L; Del Monte, J P; Moratiel, R; Tarquis, A M

    2014-01-01

    Landscape evolution is driven by abiotic, biotic, and anthropic factors. The interactions among these factors and their influence at different scales create a complex dynamic. Landscapes have been shown to exhibit numerous scaling laws, from Horton's laws to more sophisticated scaling of heights in topography and river network topology. This scaling and multiscaling analysis has the potential to characterise the landscape in terms of the statistical signature of the measure selected. The study zone is a matrix obtained from a digital elevation model (DEM) (map 10 × 10 m, and height 1 m) that corresponds to homogeneous region with respect to soil characteristics and climatology known as "Monte El Pardo" although the water level of a reservoir and the topography play a main role on its organization and evolution. We have investigated whether the multifractal analysis of a DEM shows common features that can be used to reveal the underlying patterns and information associated with the landscape of the DEM mapping and studied the influence of the water level of the reservoir on the applied analysis. The results show that the use of the multifractal approach with mean absolute gradient data is a useful tool for analysing the topography represented by the DEM. PMID:25177728

  11. Spatial Characterization of Landscapes through Multifractal Analysis of DEM

    PubMed Central

    Aguado, P. L.; Del Monte, J. P.; Moratiel, R.; Tarquis, A. M.

    2014-01-01

    Landscape evolution is driven by abiotic, biotic, and anthropic factors. The interactions among these factors and their influence at different scales create a complex dynamic. Landscapes have been shown to exhibit numerous scaling laws, from Horton's laws to more sophisticated scaling of heights in topography and river network topology. This scaling and multiscaling analysis has the potential to characterise the landscape in terms of the statistical signature of the measure selected. The study zone is a matrix obtained from a digital elevation model (DEM) (map 10 × 10 m, and height 1 m) that corresponds to homogeneous region with respect to soil characteristics and climatology known as “Monte El Pardo” although the water level of a reservoir and the topography play a main role on its organization and evolution. We have investigated whether the multifractal analysis of a DEM shows common features that can be used to reveal the underlying patterns and information associated with the landscape of the DEM mapping and studied the influence of the water level of the reservoir on the applied analysis. The results show that the use of the multifractal approach with mean absolute gradient data is a useful tool for analysing the topography represented by the DEM. PMID:25177728

  12. An Analysis of Spatial Configuration and its Application to Research in Higher Education.

    ERIC Educational Resources Information Center

    Cole, Nancy S.; Cole, James W. L.

    This paper presents an analysis of the spatial configuration of variables in a multivariate system. The purpose of the analysis is to make clearer the relationships among the variables by locating them in a minimally-dimensioned space. Similarly, individuals are located in the smaller space and related to each other on the basis of the variables…

  13. Detecting the land-cover changes induced by large-physical disturbances using landscape metrics, spatial sampling, simulation and spatial analysis.

    PubMed

    Chu, Hone-Jay; Lin, Yu-Pin; Huang, Yu-Long; Wang, Yung-Chieh

    2009-01-01

    The objectives of the study are to integrate the conditional Latin Hypercube Sampling (cLHS), sequential Gaussian simulation (SGS) and spatial analysis in remotely sensed images, to monitor the effects of large chronological disturbances on spatial characteristics of landscape changes including spatial heterogeneity and variability. The multiple NDVI images demonstrate that spatial patterns of disturbed landscapes were successfully delineated by spatial analysis such as variogram, Moran'I and landscape metrics in the study area. The hybrid method delineates the spatial patterns and spatial variability of landscapes caused by these large disturbances. The cLHS approach is applied to select samples from Normalized Difference Vegetation Index (NDVI) images from SPOT HRV images in the Chenyulan watershed of Taiwan, and then SGS with sufficient samples is used to generate maps of NDVI images. In final, the NDVI simulated maps are verified using indexes such as the correlation coefficient and mean absolute error (MAE). Therefore, the statistics and spatial structures of multiple NDVI images present a very robust behavior, which advocates the use of the index for the quantification of the landscape spatial patterns and land cover change. In addition, the results transferred by Open Geospatial techniques can be accessed from web-based and end-user applications of the watershed management. PMID:22399972

  14. Arc_Mat: a Matlab-based spatial data analysis toolbox

    NASA Astrophysics Data System (ADS)

    Liu, Xingjian; Lesage, James

    2010-03-01

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

  15. Analysis of obstruction reason of urban sewer using spatial association rules

    NASA Astrophysics Data System (ADS)

    Zhu, Hongmei; Luo, Yu

    2009-10-01

    Sewerage network is an important part of municipal infrastructure for a city. Obstruction of sewer causes street flooding and affects people's daily life directly. To investigate reasons why some sewage pipes are blocked frequently in Kunming, China, we employ spatial analysis and data mining technology to analyze the data on the basis of a municipal sewerage geographic information system of the city. In the GIS, all of map layers and attribute tables are organized and saved in a relational database with Geodatabase model. First, we combined SQL attribute query with spatial location query to find out the sewage pipes that are blocked frequently. Then, we carried out buffer analysis and intersect analysis on the layers of the frequently-blocked pipes and buildings along the streets to extract buildings that are close to these frequently-blocked pipes. Joining the buildings in the buffer scope and the frequently-blocked pipes forms a big table prepared for spatial data mining. We used Apriori algorithm to mine spatial association rules from the data in the big table in order to search implicit reasons of obstruction of the pipes. The results from data mining indicate that strong spatial and non-spatial associate rules exist between the obstruction and restaurants in the buildings, as well as attribute slopes and diameters of these sewage pipes.

  16. The effect of spatial resolution on decoding accuracy in fMRI multivariate pattern analysis.

    PubMed

    Gardumi, Anna; Ivanov, Dimo; Hausfeld, Lars; Valente, Giancarlo; Formisano, Elia; Uludağ, Kâmil

    2016-05-15

    Multivariate pattern analysis (MVPA) in fMRI has been used to extract information from distributed cortical activation patterns, which may go undetected in conventional univariate analysis. However, little is known about the physical and physiological underpinnings of MVPA in fMRI as well as about the effect of spatial smoothing on its performance. Several studies have addressed these issues, but their investigation was limited to the visual cortex at 3T with conflicting results. Here, we used ultra-high field (7T) fMRI to investigate the effect of spatial resolution and smoothing on decoding of speech content (vowels) and speaker identity from auditory cortical responses. To that end, we acquired high-resolution (1.1mm isotropic) fMRI data and additionally reconstructed them at 2.2 and 3.3mm in-plane spatial resolutions from the original k-space data. Furthermore, the data at each resolution were spatially smoothed with different 3D Gaussian kernel sizes (i.e. no smoothing or 1.1, 2.2, 3.3, 4.4, or 8.8mm kernels). For all spatial resolutions and smoothing kernels, we demonstrate the feasibility of decoding speech content (vowel) and speaker identity at 7T using support vector machine (SVM) MVPA. In addition, we found that high spatial frequencies are informative for vowel decoding and that the relative contribution of high and low spatial frequencies is different across the two decoding tasks. Moderate smoothing (up to 2.2mm) improved the accuracies for both decoding of vowels and speakers, possibly due to reduction of noise (e.g. residual motion artifacts or instrument noise) while still preserving information at high spatial frequency. In summary, our results show that - even with the same stimuli and within the same brain areas - the optimal spatial resolution for MVPA in fMRI depends on the specific decoding task of interest. PMID:26899782

  17. Rescaled box counting for the topological analysis of spatial data

    SciTech Connect

    Loehle, C.

    1994-04-01

    Topological analysis of surfaces of natural objects can provide information about surface features (ridges, fragmentation, dendritic patterns) and surface roughness. Box counting is a general method useful for such surfaces, but it is currently limited to cases where the x, y, and z directions are all in the same metric. A method, rescaled box counting, is presented for overcoming these limitations. The local first omnidirectional semivariance (lag 1) is calculated for boxes of different sizes. If the semivariance is not small for small box sizes, then the z data need to be scaled up to allow detection of a difference between patches that are significantly different This rescaling converts the z metric into a distance equivalent (z units are converted into distances based on the horizontal distance over which a significant change in z is found to occur). Once rescaling is done, box counting can be used to quantify surface topology.

  18. Advanced High Temperature Reactor Systems and Economic Analysis

    SciTech Connect

    Holcomb, David Eugene; Peretz, Fred J; Qualls, A L

    2011-09-01

    The Advanced High Temperature Reactor (AHTR) is a design concept for a large-output [3400 MW(t)] fluoride-salt-cooled high-temperature reactor (FHR). FHRs, by definition, feature low-pressure liquid fluoride salt cooling, coated-particle fuel, a high-temperature power cycle, and fully passive decay heat rejection. The AHTR's large thermal output enables direct comparison of its performance and requirements with other high output reactor concepts. As high-temperature plants, FHRs can support either high-efficiency electricity generation or industrial process heat production. The AHTR analysis presented in this report is limited to the electricity generation mission. FHRs, in principle, have the potential to be low-cost electricity producers while maintaining full passive safety. However, no FHR has been built, and no FHR design has reached the stage of maturity where realistic economic analysis can be performed. The system design effort described in this report represents early steps along the design path toward being able to predict the cost and performance characteristics of the AHTR as well as toward being able to identify the technology developments necessary to build an FHR power plant. While FHRs represent a distinct reactor class, they inherit desirable attributes from other thermal power plants whose characteristics can be studied to provide general guidance on plant configuration, anticipated performance, and costs. Molten salt reactors provide experience on the materials, procedures, and components necessary to use liquid fluoride salts. Liquid metal reactors provide design experience on using low-pressure liquid coolants, passive decay heat removal, and hot refueling. High temperature gas-cooled reactors provide experience with coated particle fuel and graphite components. Light water reactors (LWRs) show the potentials of transparent, high-heat capacity coolants with low chemical reactivity. Modern coal-fired power plants provide design experience with

  19. Ultra Wideband Indoor Positioning Technologies: Analysis and Recent Advances

    PubMed Central

    Alarifi, Abdulrahman; Al-Salman, AbdulMalik; Alsaleh, Mansour; Alnafessah, Ahmad; Al-Hadhrami, Suheer; Al-Ammar, Mai A.; Al-Khalifa, Hend S.

    2016-01-01

    In recent years, indoor positioning has emerged as a critical function in many end-user applications; including military, civilian, disaster relief and peacekeeping missions. In comparison with outdoor environments, sensing location information in indoor environments requires a higher precision and is a more challenging task in part because various objects reflect and disperse signals. Ultra WideBand (UWB) is an emerging technology in the field of indoor positioning that has shown better performance compared to others. In order to set the stage for this work, we provide a survey of the state-of-the-art technologies in indoor positioning, followed by a detailed comparative analysis of UWB positioning technologies. We also provide an analysis of strengths, weaknesses, opportunities, and threats (SWOT) to analyze the present state of UWB positioning technologies. While SWOT is not a quantitative approach, it helps in assessing the real status and in revealing the potential of UWB positioning to effectively address the indoor positioning problem. Unlike previous studies, this paper presents new taxonomies, reviews some major recent advances, and argues for further exploration by the research community of this challenging problem space. PMID:27196906

  20. Inside Single Cells: Quantitative Analysis with Advanced Optics and Nanomaterials

    PubMed Central

    Cui, Yi; Irudayaraj, Joseph

    2014-01-01

    Single cell explorations offer a unique window to inspect molecules and events relevant to mechanisms and heterogeneity constituting the central dogma of biology. A large number of nucleic acids, proteins, metabolites and small molecules are involved in determining and fine-tuning the state and function of a single cell at a given time point. Advanced optical platforms and nanotools provide tremendous opportunities to probe intracellular components with single-molecule accuracy, as well as promising tools to adjust single cell activity. In order to obtain quantitative information (e.g. molecular quantity, kinetics and stoichiometry) within an intact cell, achieving the observation with comparable spatiotemporal resolution is a challenge. For single cell studies both the method of detection and the biocompatibility are critical factors as they determine the feasibility, especially when considering live cell analysis. Although a considerable proportion of single cell methodologies depend on specialized expertise and expensive instruments, it is our expectation that the information content and implication will outweigh the costs given the impact on life science enabled by single cell analysis. PMID:25430077

  1. Quantitative Computed Tomography and Image Analysis for Advanced Muscle Assessment

    PubMed Central

    Edmunds, Kyle Joseph; Gíslason, Magnus K.; Arnadottir, Iris D.; Marcante, Andrea; Piccione, Francesco; Gargiulo, Paolo

    2016-01-01

    Medical imaging is of particular interest in the field of translational myology, as extant literature describes the utilization of a wide variety of techniques to non-invasively recapitulate and quantity various internal and external tissue morphologies. In the clinical context, medical imaging remains a vital tool for diagnostics and investigative assessment. This review outlines the results from several investigations on the use of computed tomography (CT) and image analysis techniques to assess muscle conditions and degenerative process due to aging or pathological conditions. Herein, we detail the acquisition of spiral CT images and the use of advanced image analysis tools to characterize muscles in 2D and 3D. Results from these studies recapitulate changes in tissue composition within muscles, as visualized by the association of tissue types to specified Hounsfield Unit (HU) values for fat, loose connective tissue or atrophic muscle, and normal muscle, including fascia and tendon. We show how results from these analyses can be presented as both average HU values and compositions with respect to total muscle volumes, demonstrating the reliability of these tools to monitor, assess and characterize muscle degeneration. PMID:27478562

  2. Ultra Wideband Indoor Positioning Technologies: Analysis and Recent Advances.

    PubMed

    Alarifi, Abdulrahman; Al-Salman, AbdulMalik; Alsaleh, Mansour; Alnafessah, Ahmad; Al-Hadhrami, Suheer; Al-Ammar, Mai A; Al-Khalifa, Hend S

    2016-01-01

    In recent years, indoor positioning has emerged as a critical function in many end-user applications; including military, civilian, disaster relief and peacekeeping missions. In comparison with outdoor environments, sensing location information in indoor environments requires a higher precision and is a more challenging task in part because various objects reflect and disperse signals. Ultra WideBand (UWB) is an emerging technology in the field of indoor positioning that has shown better performance compared to others. In order to set the stage for this work, we provide a survey of the state-of-the-art technologies in indoor positioning, followed by a detailed comparative analysis of UWB positioning technologies. We also provide an analysis of strengths, weaknesses, opportunities, and threats (SWOT) to analyze the present state of UWB positioning technologies. While SWOT is not a quantitative approach, it helps in assessing the real status and in revealing the potential of UWB positioning to effectively address the indoor positioning problem. Unlike previous studies, this paper presents new taxonomies, reviews some major recent advances, and argues for further exploration by the research community of this challenging problem space. PMID:27196906

  3. Inside single cells: quantitative analysis with advanced optics and nanomaterials.

    PubMed

    Cui, Yi; Irudayaraj, Joseph

    2015-01-01

    Single-cell explorations offer a unique window to inspect molecules and events relevant to mechanisms and heterogeneity constituting the central dogma of biology. A large number of nucleic acids, proteins, metabolites, and small molecules are involved in determining and fine-tuning the state and function of a single cell at a given time point. Advanced optical platforms and nanotools provide tremendous opportunities to probe intracellular components with single-molecule accuracy, as well as promising tools to adjust single-cell activity. To obtain quantitative information (e.g., molecular quantity, kinetics, and stoichiometry) within an intact cell, achieving the observation with comparable spatiotemporal resolution is a challenge. For single-cell studies, both the method of detection and the biocompatibility are critical factors as they determine the feasibility, especially when considering live-cell analysis. Although a considerable proportion of single-cell methodologies depend on specialized expertise and expensive instruments, it is our expectation that the information content and implication will outweigh the costs given the impact on life science enabled by single-cell analysis. PMID:25430077

  4. Advances in genome-wide DNA methylation analysis

    PubMed Central

    Gupta, Romi; Nagarajan, Arvindhan; Wajapeyee, Narendra

    2013-01-01

    The covalent DNA modification of cytosine at position 5 (5-methylcytosine; 5mC) has emerged as an important epigenetic mark most commonly present in the context of CpG dinucleotides in mammalian cells. In pluripotent stem cells and plants, it is also found in non-CpG and CpNpG contexts, respectively. 5mC has important implications in a diverse set of biological processes, including transcriptional regulation. Aberrant DNA methylation has been shown to be associated with a wide variety of human ailments and thus is the focus of active investigation. Methods used for detecting DNA methylation have revolutionized our understanding of this epigenetic mark and provided new insights into its role in diverse biological functions. Here we describe recent technological advances in genome-wide DNA methylation analysis and discuss their relative utility and drawbacks, providing specific examples from studies that have used these technologies for genome-wide DNA methylation analysis to address important biological questions. Finally, we discuss a newly identified covalent DNA modification, 5-hydroxymethylcytosine (5hmC), and speculate on its possible biological function, as well as describe a new methodology that can distinguish 5hmC from 5mC. PMID:20964631

  5. Lock Acquisition and Sensitivity Analysis of Advanced LIGO Interferometers

    NASA Astrophysics Data System (ADS)

    Martynov, Denis

    Laser interferometer gravitational wave observatory (LIGO) consists of two complex large-scale laser interferometers designed for direct detection of gravitational waves from distant astrophysical sources in the frequency range 10Hz - 5kHz. Direct detection of space-time ripples will support Einstein's general theory of relativity and provide invaluable information and new insight into physics of the Universe. The initial phase of LIGO started in 2002, and since then data was collected during the six science runs. Instrument sensitivity improved from run to run due to the effort of commissioning team. Initial LIGO has reached designed sensitivity during the last science run, which ended in October 2010. In parallel with commissioning and data analysis with the initial detector, LIGO group worked on research and development of the next generation of detectors. Major instrument upgrade from initial to advanced LIGO started in 2010 and lasted until 2014. This thesis describes results of commissioning work done at the LIGO Livingston site from 2013 until 2015 in parallel with and after the installation of the instrument. This thesis also discusses new techniques and tools developed at the 40m prototype including adaptive filtering, estimation of quantization noise in digital filters and design of isolation kits for ground seismometers. The first part of this thesis is devoted to the description of methods for bringing the interferometer into linear regime when collection of data becomes possible. States of longitudinal and angular controls of interferometer degrees of freedom during lock acquisition process and in low noise configuration are discussed in details. Once interferometer is locked and transitioned to low noise regime, instrument produces astrophysics data that should be calibrated to units of meters or strain. The second part of this thesis describes online calibration technique set up in both observatories to monitor the quality of the collected data in

  6. A novel technique of image quality objective measurement by wavelet analysis throughout the spatial frequency range

    NASA Astrophysics Data System (ADS)

    Luo, Gaoyong

    2005-01-01

    An essential determinant of the value of surrogate digital images is their quality. Image quality measurement has become crucial for most image processing applications. Over the past years , there have been many attempts to develop models or metrics for image quality that incorporate elements of human visual sensitivity. However, there is no current standard and objective definition of spectral image quality. This paper proposes a reliable automatic method for objective image quality measurement by wavelet analysis throughout the spatial frequency range. This is done by a detailed analysis of an image for a wide range of spatial frequency content, using a combination of modulation transfer function (MTF), brightness, contrast, saturation, sharpness and noise, as a more revealing metric for quality evaluation. A fast lifting wavelet algorithm is developed for computationally efficient spatial frequency analysis, where fine image detail corresponding to high spatial frequencies and image sharpness in regard to lower and mid -range spatial frequencies can be examined and compared accordingly. The wavelet frequency deconstruction is actually to extract the feature of edges in sub-band images. The technique provides a means to relate the quality of an image to the interpretation and quantification throughout the frequency range, in which the noise level is estimated in assisting with quality analysis. The experimental results of using this method for image quality measurement exhibit good correlation to subjective visual quality assessments.

  7. A novel technique of image quality objective measurement by wavelet analysis throughout the spatial frequency range

    NASA Astrophysics Data System (ADS)

    Luo, Gaoyong

    2004-10-01

    An essential determinant of the value of surrogate digital images is their quality. Image quality measurement has become crucial for most image processing applications. Over the past years , there have been many attempts to develop models or metrics for image quality that incorporate elements of human visual sensitivity. However, there is no current standard and objective definition of spectral image quality. This paper proposes a reliable automatic method for objective image quality measurement by wavelet analysis throughout the spatial frequency range. This is done by a detailed analysis of an image for a wide range of spatial frequency content, using a combination of modulation transfer function (MTF), brightness, contrast, saturation, sharpness and noise, as a more revealing metric for quality evaluation. A fast lifting wavelet algorithm is developed for computationally efficient spatial frequency analysis, where fine image detail corresponding to high spatial frequencies and image sharpness in regard to lower and mid -range spatial frequencies can be examined and compared accordingly. The wavelet frequency deconstruction is actually to extract the feature of edges in sub-band images. The technique provides a means to relate the quality of an image to the interpretation and quantification throughout the frequency range, in which the noise level is estimated in assisting with quality analysis. The experimental results of using this method for image quality measurement exhibit good correlation to subjective visual quality assessments.

  8. Analysis of the Spatial Variation of Hospitalization Admissions for Hypertension Disease in Shenzhen, China

    PubMed Central

    Wang, Zhensheng; Du, Qingyun; Liang, Shi; Nie, Ke; Lin, De-nan; Chen, Yan; Li, Jia-jia

    2014-01-01

    In China, awareness about hypertension, the treatment rate and the control rate are low compared to developed countries, even though China’s aging population has grown, especially in those areas with a high degree of urbanization. However, limited epidemiological studies have attempted to describe the spatial variation of the geo-referenced data on hypertension disease over an urban area of China. In this study, we applied hierarchical Bayesian models to explore the spatial heterogeneity of the relative risk for hypertension admissions throughout Shenzhen in 2011. The final model specification includes an intercept and spatial components (structured and unstructured). Although the road density could be used as a covariate in modeling, it is an indirect factor on the relative risk. In addition, spatial scan statistics and spatial analysis were utilized to identify the spatial pattern and to map the clusters. The results showed that the relative risk for hospital admission for hypertension has high-value clusters in the south and southeastern Shenzhen. This study aimed to identify some specific regions with high relative risk, and this information is useful for the health administrators. Further research should address more-detailed data collection and an explanation of the spatial patterns. PMID:24394218

  9. Spatial Variance in Resting fMRI Networks of Schizophrenia Patients: An Independent Vector Analysis.

    PubMed

    Gopal, Shruti; Miller, Robyn L; Michael, Andrew; Adali, Tulay; Cetin, Mustafa; Rachakonda, Srinivas; Bustillo, Juan R; Cahill, Nathan; Baum, Stefi A; Calhoun, Vince D

    2016-01-01

    Spatial variability in resting functional MRI (fMRI) brain networks has not been well studied in schizophrenia, a disease known for both neurodevelopmental and widespread anatomic changes. Motivated by abundant evidence of neuroanatomical variability from previous studies of schizophrenia, we draw upon a relatively new approach called independent vector analysis (IVA) to assess this variability in resting fMRI networks. IVA is a blind-source separation algorithm, which segregates fMRI data into temporally coherent but spatially independent networks and has been shown to be especially good at capturing spatial variability among subjects in the extracted networks. We introduce several new ways to quantify differences in variability of IVA-derived networks between schizophrenia patients (SZs = 82) and healthy controls (HCs = 89). Voxelwise amplitude analyses showed significant group differences in the spatial maps of auditory cortex, the basal ganglia, the sensorimotor network, and visual cortex. Tests for differences (HC-SZ) in the spatial variability maps suggest, that at rest, SZs exhibit more activity within externally focused sensory and integrative network and less activity in the default mode network thought to be related to internal reflection. Additionally, tests for difference of variance between groups further emphasize that SZs exhibit greater network variability. These results, consistent with our prediction of increased spatial variability within SZs, enhance our understanding of the disease and suggest that it is not just the amplitude of connectivity that is different in schizophrenia, but also the consistency in spatial connectivity patterns across subjects. PMID:26106217

  10. RARE PROJECT: AIR TOXICS DATA ANALYSIS FOR SPATIAL ANALYSIS OF AMBIENT VOCS AT SELECTED CENSUS TRACTS IN HOUSTON-GALVESTON

    EPA Science Inventory

    This is an ORD Regional Applied Research Effort (RARE) study with EPA Region 6 to conduct data analysis geared to spatial analysis for estimation of ambient VOCs at selected census tract areas in Houston-Galveston area. For a better understanding of air toxics impacts in the Hou...

  11. Adverse effects of template-based warping on spatial fMRI analysis

    NASA Astrophysics Data System (ADS)

    Ng, Bernard; Abugharbieh, Rafeef; McKeown, Martin J.

    2009-02-01

    Conventional voxel-based group analysis of functional magnetic resonance imaging (fMRI) data typically requires warping each subject's brain images onto a common template to create an assumed voxel correspondence. The implicit assumption is that aligning the anatomical structures would correspondingly align the functional regions of the subjects. However, due to anatomical and functional inter-subject variability, mis-registration often occurs. Moreover, wholebrain warping is likely to distort the spatial patterns of activation, which have been shown to be important markers of task-related activation. To reduce the amount of mis-registration and distortions, warping at the brain region level has recently been proposed. In this paper, we investigate the effects of both whole-brain and region-level warping on the spatial patterns of activation statistics within certain regions of interests (ROIs). We have chosen to examine the bilateral thalami and cerebellar hemispheres during a bulb-squeezing experiment, as these regions are expected to incur taskrelated activation changes. Furthermore, the appreciable size difference between the thalamus and cerebellum allows for exploring the effects of warping on various ROI sizes. By applying our recently proposed 3D moment-based invariant spatial features to characterize the spatial pattern of fMRI activation statistics, we demonstrate that whole-brain warping generally reduced discriminability of task-related activation differences. Applying the same spatial analysis to ROIs warped at the region level showed some improvements over whole-brain warping, but warp-free analysis resulted in the best performance. We hence suggest that spatial analysis of fMRI data that includes spatial warping to a common space must be interpreted with caution.

  12. Develop advanced nonlinear signal analysis topographical mapping system

    NASA Technical Reports Server (NTRS)

    1994-01-01

    The Space Shuttle Main Engine (SSME) has been undergoing extensive flight certification and developmental testing, which involves some 250 health monitoring measurements. Under the severe temperature, pressure, and dynamic environments sustained during operation, numerous major component failures have occurred, resulting in extensive engine hardware damage and scheduling losses. To enhance SSME safety and reliability, detailed analysis and evaluation of the measurements signal are mandatory to assess its dynamic characteristics and operational condition. Efficient and reliable signal detection techniques will reduce catastrophic system failure risks and expedite the evaluation of both flight and ground test data, and thereby reduce launch turn-around time. The basic objective of this contract are threefold: (1) develop and validate a hierarchy of innovative signal analysis techniques for nonlinear and nonstationary time-frequency analysis. Performance evaluation will be carried out through detailed analysis of extensive SSME static firing and flight data. These techniques will be incorporated into a fully automated system; (2) develop an advanced nonlinear signal analysis topographical mapping system (ATMS) to generate a Compressed SSME TOPO Data Base (CSTDB). This ATMS system will convert tremendous amount of complex vibration signals from the entire SSME test history into a bank of succinct image-like patterns while retaining all respective phase information. High compression ratio can be achieved to allow minimal storage requirement, while providing fast signature retrieval, pattern comparison, and identification capabilities; and (3) integrate the nonlinear correlation techniques into the CSTDB data base with compatible TOPO input data format. Such integrated ATMS system will provide the large test archives necessary for quick signature comparison. This study will provide timely assessment of SSME component operational status, identify probable causes of

  13. Develop advanced nonlinear signal analysis topographical mapping system

    NASA Technical Reports Server (NTRS)

    Jong, Jen-Yi

    1993-01-01

    The SSME has been undergoing extensive flight certification and developmental testing, which involves some 250 health monitoring measurements. Under the severe temperature pressure, and dynamic environments sustained during operation, numerous major component failures have occurred, resulting in extensive engine hardware damage and scheduling losses. To enhance SSME safety and reliability, detailed analysis and evaluation of the measurements signal are mandatory to assess its dynamic characteristics and operational condition. Efficient and reliable signal detection techniques will reduce catastrophic system failure risks and expedite the evaluation of both flight and ground test data, and thereby reduce launch turn-around time. The basic objective of this contract are threefold: (1) Develop and validate a hierarchy of innovative signal analysis techniques for nonlinear and nonstationary time-frequency analysis. Performance evaluation will be carried out through detailed analysis of extensive SSME static firing and flight data. These techniques will be incorporated into a fully automated system. (2) Develop an advanced nonlinear signal analysis topographical mapping system (ATMS) to generate a Compressed SSME TOPO Data Base (CSTDB). This ATMS system will convert tremendous amounts of complex vibration signals from the entire SSME test history into a bank of succinct image-like patterns while retaining all respective phase information. A high compression ratio can be achieved to allow the minimal storage requirement, while providing fast signature retrieval, pattern comparison, and identification capabilities. (3) Integrate the nonlinear correlation techniques into the CSTDB data base with compatible TOPO input data format. Such integrated ATMS system will provide the large test archives necessary for a quick signature comparison. This study will provide timely assessment of SSME component operational status, identify probable causes of malfunction, and indicate

  14. Advanced Diagnostic and Prognostic Testbed (ADAPT) Testability Analysis Report

    NASA Technical Reports Server (NTRS)

    Ossenfort, John

    2008-01-01

    As system designs become more complex, determining the best locations to add sensors and test points for the purpose of testing and monitoring these designs becomes more difficult. Not only must the designer take into consideration all real and potential faults of the system, he or she must also find efficient ways of detecting and isolating those faults. Because sensors and cabling take up valuable space and weight on a system, and given constraints on bandwidth and power, it is even more difficult to add sensors into these complex designs after the design has been completed. As a result, a number of software tools have been developed to assist the system designer in proper placement of these sensors during the system design phase of a project. One of the key functions provided by many of these software programs is a testability analysis of the system essentially an evaluation of how observable the system behavior is using available tests. During the design phase, testability metrics can help guide the designer in improving the inherent testability of the design. This may include adding, removing, or modifying tests; breaking up feedback loops, or changing the system to reduce fault propagation. Given a set of test requirements, the analysis can also help to verify that the system will meet those requirements. Of course, a testability analysis requires that a software model of the physical system is available. For the analysis to be most effective in guiding system design, this model should ideally be constructed in parallel with these efforts. The purpose of this paper is to present the final testability results of the Advanced Diagnostic and Prognostic Testbed (ADAPT) after the system model was completed. The tool chosen to build the model and to perform the testability analysis with is the Testability Engineering and Maintenance System Designer (TEAMS-Designer). The TEAMS toolset is intended to be a solution to span all phases of the system, from design and

  15. Three-dimensional analysis of anisotropic spatially reinforced structures

    NASA Technical Reports Server (NTRS)

    Bogdanovich, Alexander E.

    1993-01-01

    The material-adaptive three-dimensional analysis of inhomogeneous structures based on the meso-volume concept and application of deficient spline functions for displacement approximations is proposed. The general methodology is demonstrated on the example of a brick-type mosaic parallelepiped arbitrarily composed of anisotropic meso-volumes. A partition of each meso-volume into sub-elements, application of deficient spline functions for a local approximation of displacements and, finally, the use of the variational principle allows one to obtain displacements, strains, and stresses at anypoint within the structural part. All of the necessary external and internal boundary conditions (including the conditions of continuity of transverse stresses at interfaces between adjacent meso-volumes) can be satisfied with requisite accuracy by increasing the density of the sub-element mesh. The application of the methodology to textile composite materials is described. Several numerical examples for woven and braided rectangular composite plates and stiffened panels under transverse bending are considered. Some typical effects of stress concentrations due to the material inhomogeneities are demonstrated.

  16. Spatial Analysis of Cryoplanation Landforms in Beringian Uplands, Alaska, USA

    NASA Astrophysics Data System (ADS)

    Nyland, K. E.; Nelson, F. E.

    2015-12-01

    Cryoplanation terraces are large periglacial landforms characteristic of cold, unglaciated mountainous environments. Terrace sequences are composed of alternating slope segments with steep rubble-covered risers and gently sloping treads, culminating in extensive summit flats. Entire Beringian upland landscapes are dominated by these features. Cryoplanation terraces are cut into bedrock and thought to evolve through locally intensified periglacial weathering and mass-movement processes in the vicinity of late-lying snowpatches. Geospatial analysis demonstrates that terrace elevation rises from 100-300 m.a.s.l. on Bering Sea islands to median values greater than 1200 m in the Yukon-Tanana Upland, near the Alaska-Canada border. The regional trends of cryoplanation terrace elevation are similar to those of cirques and reconstructed ELAs across interior and western Alaska, with gradients ranging from 0.74 to 1.2 m km-1. The similarity of these trends indicates close genetic links between glacial cirques and cryoplanation terraces, involving topographic position, continentality gradients, and the mass balance of localized snow accumulation. Cryoplanation terraces can be considered as the periglacial analogs of glacial cirques, and have greater potential as sources of paleoclimatic information than smaller periglacial features more sensitive to short-term climate variations. Process-oriented studies, age determinations, and high-resolution mapping are needed before their paleoenvironmental potential of these landforms can be fully realized.

  17. Spatially resolved δ13C analysis using laser ablation isotope ratio mass spectrometry

    NASA Astrophysics Data System (ADS)

    Moran, J.; Riha, K. M.; Nims, M. K.; Linley, T. J.; Hess, N. J.; Nico, P. S.

    2014-12-01

    Inherent geochemical, organic matter, and microbial heterogeneity over small spatial scales can complicate studies of carbon dynamics through soils. Stable isotope analysis has a strong history of helping track substrate turnover, delineate rhizosphere activity zones, and identifying transitions in vegetation cover, but most traditional isotope approaches are limited in spatial resolution by a combination of physical separation techniques (manual dissection) and IRMS instrument sensitivity. We coupled laser ablation sampling with isotope measurement via IRMS to enable spatially resolved analysis over solid surfaces. Once a targeted sample region is ablated the resulting particulates are entrained in a helium carrier gas and passed through a combustion reactor where carbon is converted to CO2. Cyrotrapping of the resulting CO2 enables a reduction in carrier gas flow which improves overall measurement sensitivity versus traditional, high flow sample introduction. Currently we are performing sample analysis at 50 μm resolution, require 65 ng C per analysis, and achieve measurement precision consistent with other continuous flow techniques. We will discuss applications of the laser ablation IRMS (LA-IRMS) system to microbial communities and fish ecology studies to demonstrate the merits of this technique and how similar analytical approaches can be transitioned to soil systems. Preliminary efforts at analyzing soil samples will be used to highlight strengths and limitations of the LA-IRMS approach, paying particular attention to sample preparation requirements, spatial resolution, sample analysis time, and the types of questions most conducive to analysis via LA-IRMS.

  18. Advancing sensitivity analysis to precisely characterize temporal parameter dominance

    NASA Astrophysics Data System (ADS)

    Guse, Björn; Pfannerstill, Matthias; Strauch, Michael; Reusser, Dominik; Lüdtke, Stefan; Volk, Martin; Gupta, Hoshin; Fohrer, Nicola

    2016-04-01

    Parameter sensitivity analysis is a strategy for detecting dominant model parameters. A temporal sensitivity analysis calculates daily sensitivities of model parameters. This allows a precise characterization of temporal patterns of parameter dominance and an identification of the related discharge conditions. To achieve this goal, the diagnostic information as derived from the temporal parameter sensitivity is advanced by including discharge information in three steps. In a first step, the temporal dynamics are analyzed by means of daily time series of parameter sensitivities. As sensitivity analysis method, we used the Fourier Amplitude Sensitivity Test (FAST) applied directly onto the modelled discharge. Next, the daily sensitivities are analyzed in combination with the flow duration curve (FDC). Through this step, we determine whether high sensitivities of model parameters are related to specific discharges. Finally, parameter sensitivities are separately analyzed for five segments of the FDC and presented as monthly averaged sensitivities. In this way, seasonal patterns of dominant model parameter are provided for each FDC segment. For this methodical approach, we used two contrasting catchments (upland and lowland catchment) to illustrate how parameter dominances change seasonally in different catchments. For all of the FDC segments, the groundwater parameters are dominant in the lowland catchment, while in the upland catchment the controlling parameters change seasonally between parameters from different runoff components. The three methodical steps lead to clear temporal patterns, which represent the typical characteristics of the study catchments. Our methodical approach thus provides a clear idea of how the hydrological dynamics are controlled by model parameters for certain discharge magnitudes during the year. Overall, these three methodical steps precisely characterize model parameters and improve the understanding of process dynamics in hydrological

  19. Landscape equivalency analysis: methodology for estimating spatially explicit biodiversity credits.

    PubMed

    Bruggeman, Douglas J; Jones, Michael L; Lupi, Frank; Scribner, Kim T

    2005-10-01

    We propose a biodiversity credit system for trading endangered species habitat designed to minimize and reverse the negative effects of habitat loss and fragmentation, the leading cause of species endangerment in the United States. Given the increasing demand for land, approaches that explicitly balance economic goals against conservation goals are required. The Endangered Species Act balances these conflicts based on the cost to replace habitat. Conservation banking is a means to manage this balance, and we argue for its use to mitigate the effects of habitat fragmentation. Mitigating the effects of land development on biodiversity requires decisions that recognize regional ecological effects resulting from local economic decisions. We propose Landscape Equivalency Analysis (LEA), a landscape-scale approach similar to HEA, as an accounting system to calculate conservation banking credits so that habitat trades do not exacerbate regional ecological effects of local decisions. Credits purchased by public agencies or NGOs for purposes other than mitigating a take create a net investment in natural capital leading to habitat defragmentation. Credits calculated by LEA use metapopulation genetic theory to estimate sustainability criteria against which all trades are judged. The approach is rooted in well-accepted ecological, evolutionary, and economic theory, which helps compensate for the degree of uncertainty regarding the effects of habitat loss and fragmentation on endangered species. LEA requires application of greater scientific rigor than typically applied to endangered species management on private lands but provides an objective, conceptually sound basis for achieving the often conflicting goals of economic efficiency and long-term ecological sustainability. PMID:16132443

  20. Using principal component analysis to monitor spatial and temporal changes in water quality.

    PubMed

    Bengraïne, Karim; Marhaba, Taha F

    2003-06-27

    Chemical, biological and physical data monitored at 12 locations along the Passaic River, New Jersey, during the year 1998 are analyzed. Principal component analysis (PCA) was used: (i) to extract the factors associated with the hydrochemistry variability; (ii) to obtain the spatial and temporal changes in the water quality. Solute content, temperature, nutrients and organics were the main patterns extracted. The spatial analysis isolated two stations showing a possible point or non-point source of pollution. This study shows the importance of environmental monitoring associated with simple but powerful statistics to better understand a complex water system. PMID:12835021

  1. Spatial analysis of early successional, temperate forest community structure

    NASA Astrophysics Data System (ADS)

    Walker, R. H.; Williams, C. A.; MacLean, R. G.; Epstein, H. E.; Vanderhoof, M. K.

    2013-12-01

    The global importance of sequestration of carbon by temperate forests makes characterizing the regrowth of these forests post-disturbance both ecologically and economically important. High intensity disturbances, such as logging, result in substantial alteration of community composition post-disturbance, creating the potential for alterations to the cycling of carbon, water, and nutrients in the ecosystem. Because logging pressure in New England continues to increase, understanding how forest ecosystems in this region respond to disturbance is crucial. This study aims to characterize interspecies interactions within New England forests by identifying synchronous and asynchronous colocation of species following a disturbance. To accomplish this, line-intercept surveys of vegetation were conducted in a clearcut forest stand located within the Harvard Forest LTER site. Survey data collected two (2010) and five (2013) years post-clearcut were analyzed using a one-dimensional Ripley's K. From 2010 to 2013, an increase in the number of interspecies relationships was observed, indicating the development of community structure. Additionally, the analysis found an increase in total vegetative cover from 2010 to 2013, and also found the majority of observed interspecies relationships to be asynchronous relationships. Together, these results imply an increase in resource competition that had the potential to drive the increase in community structure. Specifically, an increase in community structure led to the development of three distinct sub-communities: homogenous fern, tree seedling canopy over ground cover, and shrub dominated. This creates a patchy landscape in the early successional forest that allows for high species diversity (Shannon's H = 2.455). Based on the results of the Ripley's K analyses, species demonstrated definite patterns of synchronicity and asynchronicity based on both specific species interactions as well as functional group interactions. These

  2. Laminar analysis of 7 T BOLD using an imposed spatial activation pattern in human V1

    PubMed Central

    Polimeni, Jonathan R.; Fischl, Bruce; Greve, Douglas N.; Wald, Lawrence L.

    2010-01-01

    With sufficient image encoding, high-resolution fMRI studies are limited by the biological point-spread of the hemodynamic signal. The extent of this spread is determined by the local vascular distribution and by the spatial specificity of blood flow regulation, as well as by measurement parameters that (i) alter the relative sensitivity of the acquisition to activation-induced hemodynamic changes and (ii) determine the image contrast as a function of vessel size. In particular, large draining vessels on the cortical surface are a major contributor to both the BOLD signal change and to the spatial bias of the BOLD activation away from the site of neuronal activity. In this work, we introduce a laminar surface-based analysis method and study the relationship between spatial localization and activation strength as a function of laminar depth by acquiring 1 mm isotropic, single-shot EPI at 7 T and sampling the BOLD signal exclusively from the superficial, middle, or deep cortical laminae. We show that highly-accelerated EPI can limit image distortions to the point where a boundary-based registration algorithm accurately aligns the EPI data to the surface reconstruction. The spatial spread of the BOLD response tangential to the cortical surface was analyzed as a function of cortical depth using our surface-based analysis. Although sampling near the pial surface provided the highest signal strength, it also introduced the most spatial error. Thus, avoiding surface laminae improved spatial localization by about 40% at a cost of 36% in z-statistic, implying that optimal spatial resolution in functional imaging of the cortex can be achieved using anatomically-informed spatial sampling to avoid large pial vessels. PMID:20460157

  3. Modeling with the Advanced Science Analysis Package (ASAP)

    NASA Astrophysics Data System (ADS)

    Boone, F.; Schilke, P.; Muders, D.; Comito, C.; Leurini, S.; Parise, B.; van der Tak, F.; Menten, K.

    ASAP is a project initiated at the MPIfR which aims at providing a new generation of scientific analysis tools to extract the physical information from the high dynamical range data of current and future instruments. It was motivated by the ALMA project but the concepts and their implementations are applicable to all wavelengths. This presentation is focused on DALIA (Direct Aproach to spectral Line Analysis), a prototype software for forward modeling. It consists of a JAVA graphical user interface through which the user can fit models to observations. The models are stored as binaries and are described by XML files according to a schema. New models developed in any language can thus be easily added to the model database by the user. The different steps of the fit (simulation, evaluation, parameter change) can be executed manually or automatically through an optimization engine. The interface allows the user to have a direct control on the model parameters which can be fixed or constrained. The data to be modeled can be of any type (1D, 2D, 3D, specral, spatial, temporal...) and associations of datasets of different types are supported as long as the axes are identical to those of the model output. In this prototype the FITS format is supported. For spectral synthesis, the spectroscopic data from the molecular databases (Cologne, JPL) are used. This approach is very generic and uses concepts similar to those of the Virtual Observatory. Its integration into the VO would allow astronomers to use the data archives to constrain a model and would permit to store model solutions for each source. These model solutions could thus be easily shared and be improved with the aquisition of new data.

  4. Modeling with the Advanced Science Analysis Package (ASAP)

    NASA Astrophysics Data System (ADS)

    Boone, F.; Schilke, P.; Muders, D.; Comito, C.; Leurini, S.; Parise, B.; van der Tak, F.; Menten, K.

    2005-12-01

    ASAP is a project initiated at the MPIfR which aims at providing a new generation of scientific analysis tools to extract the physical information from the high dynamical range data of current and future instruments. It was motivated by the ALMA project but the concepts and their implementations are applicable to all wavelengths. This presentation is focused on DALIA (Direct Aproach to spectral Line Analysis), a prototype software for forward modeling. It consists of a JAVA graphical user interface through which the user can fit models to observations. The models are stored as binaries and are described by XML files according to a schema. New models developed in any language can thus be easily added to the model database by the user. The different steps of the fit (simulation, evaluation, parameter change) can be executed manually or automatically through an optimization engine. The interface allows the user to have a direct control on the model parameters which can be fixed or constrained. The data to be modeled can be of any type (1D, 2D, 3D, spectral, spatial, temporal...) and associations of datasets of different types are supported as long as the axes are identical to those of the model output. In this prototype the data need to be in FITS format. For spectral synthesis, the spectroscopic data from the molecular databases (Cologne, JPL) are used. This approach is very generic and uses concepts similar to those of the Virtual Observatory. Its integration into the VO would allow astronomers to use the data archives to constrain a model and would permit to store model solutions for each source. These model solutions could thus be easily shared and be improved each time new observations of the source are made.

  5. Improvement of hybrid yield by advanced backcross QTL analysis in elite maize.

    PubMed

    Ho, C.; McCouch, R.; Smith, E.

    2002-08-01

    We applied an advanced backcross breeding strategy to identify quantitative trait loci (QTLs) of agronomic importance in a cross between two elite inbreds of maize, RD6502 (Mo17-type recurrent parent) and RD3013 (Iodent donor parent). Two hundred and four BC(2) families were scored at 106 SSR, 15 AFLP, and 38 Heartbreaker (MITE) loci. BC(2) testcrosses (TC) with B73 were phenotyped at six locations in the Midwest and N.Y. We detected four grain yield, six grain moisture, and three plant height QTLs at which the RD3013 allele had a favorable effect ( p < 0.05). All four yield QTLs were selected as target introgressions in the development of BC(3)TC families. As predicted by BC(2)TC analysis, BC(3)TC entries containing introgressions at yld3.1 and yld10.1 significantly outperformed non-carrier entries by 11.1% (15.6 bu/A at one location) and 6.7% (7.1 bu/A averaged across two locations), respectively, in replicated Midwestern trials ( p < 0.05). Detection of yld10.1 effects in the BC(2)TC by spatial analysis (i.e., incomplete block, response surface, autoregressive, moving average or autoregressive moving average), but not by conventional single point analysis or interval mapping, indicated the utility of local environmental control for QTL mapping in unreplicated maize progeny. This work demonstrated that the advanced backcross QTL method can be applied to identify and manipulate useful QTLs in heterotic inbreds of elite maize. Genetic gains by this approach can be coupled with the maintenance and selection of favorable epistatic gene complexes by traditional hybrid breeding for maize improvement. PMID:12582549

  6. Spatial Analysis of Schistosomiasis in Hubei Province, China: A GIS-Based Analysis of Schistosomiasis from 2009 to 2013

    PubMed Central

    Chen, Yan-Yan; Huang, Xi-Bao; Xiao, Ying; Jiang, Yong; Shan, Xiao-wei; Zhang, Juan; Cai, Shun-Xiang; Liu, Jian-Bing

    2015-01-01

    Background Schistosomiasis remains a major public health problem in China. The major endemic areas are located in the lake and marshland regions of southern China, particularly in areas along the middle and low reach of the Yangtze River. Spatial analytical techniques are often used in epidemiology to identify spatial clusters in disease regions. This study assesses the spatial distribution of schistosomiasis and explores high-risk regions in Hubei Province, China to provide guidance on schistosomiasis control in marshland regions. Methods In this study, spatial autocorrelation methodologies, including global Moran’s I and local Getis–Ord statistics, were utilized to describe and map spatial clusters and areas where human Schistosoma japonicum infection is prevalent at the county level in Hubei province. In addition, linear logistic regression model was used to determine the characteristics of spatial autocorrelation with time. Results The infection rates of S. japonicum decreased from 2009 to 2013. The global autocorrelation analysis results on the infection rate of S. japonicum for five years showed statistical significance (Moran’s I > 0, P < 0.01), which suggested that spatial clusters were present in the distribution of S. japonicum infection from 2009 to 2013. Local autocorrelation analysis results showed that the number of highly aggregated areas ranged from eight to eleven within the five-year analysis period. The highly aggregated areas were mainly distributed in eight counties. Conclusions The spatial distribution of human S. japonicum infections did not exhibit a temporal change at the county level in Hubei Province. The risk factors that influence human S. japonicum transmission may not have changed after achieving the national criterion of infection control. The findings indicated that spatial–temporal surveillance of S. japonicum transmission plays a significant role on schistosomiasis control. Timely and integrated prevention should be

  7. Use of High Spatial Resolution Remote Sensing for Hydro-Geomorphologic Analysis of Medium-sized Arid Basins

    NASA Astrophysics Data System (ADS)

    Sadeh, Yuval; Blumberg, Dan G.; Cohen, Hai; Morin, Efrat; Maman, Shimrit

    2016-04-01

    Arid environments are often remote, expansive, difficult to access and especially vulnerable to flash flood hazards due to the poor understanding of the phenomenon and the lack of meteorological, geomorphological, and hydrological data. For many years, catchment characteristics have been observed using point-based measurements such as rain gauges and soil sample analysis; on the other hand, use of remote sensing technologies can provide spatially continuous hydrological parameters and variables. The advances in remote sensing technologies can provide new geo-spatial data using high spatial and temporal resolution for basin-scale geomorphological analysis and hydrological models. This study used high spatial resolution remote sensing for hydro-geomorphologic analysis of the arid medium size Rahaf watershed (76 km2), located in the Judean Desert, Israel. During the research a high resolution geomorphological map of Rahaf basin was created using WorldView-2 multispectral satellite imageries; surface roughness was estimated using SIR-C and COSMO-SkyMed Synthetic Aperture Radar (SAR) spaceborne sensors; and rainstorm characteristics were extracted using ground-based meteorological radar. The geomorphological mapping of Rahaf into 17 classes with good accuracy. The surface roughness extraction using SAR over the basin showed that the correlation between the COSMO-SkyMed backscatter coefficient and the surface roughness was very strong with an R2 of 0.97. This study showed that using x-band spaceborne sensors with high spatial resolution, such as COSMO-SkyMed, are more suitable for surface roughness evaluation in flat arid environments and should be in favor with longer wavelength operating sensors such as the SIR-C. The current study presents an innovative method to evaluate Manning's hydraulic roughness coefficient (n) in arid environments using radar backscattering. The weather radar rainfall data was calibrated using rain gauges located in the watershed. The

  8. Analysis of spatial and temporal water pollution patterns in Lake Dianchi using multivariate statistical methods.

    PubMed

    Yang, Yong-Hui; Zhou, Feng; Guo, Huai-Cheng; Sheng, Hu; Liu, Hui; Dao, Xu; He, Cheng-Jie

    2010-11-01

    Various multivariate statistical methods including cluster analysis (CA), discriminant analysis (DA), factor analysis (FA), and principal component analysis (PCA) were used to explain the spatial and temporal patterns of surface water pollution in Lake Dianchi. The dataset, obtained during the period 2003-2007 from the Kunming Environmental Monitoring Center, consisted of 12 variables surveyed monthly at eight sites. The CA grouped the 12 months into two groups, August-September and the remainder, and divided the lake into two regions based on their different physicochemical properties and pollution levels. The DA showed the best results for data reduction and pattern recognition in both temporal and spatial analysis. It calculated four parameters (TEMP, pH, CODMn, and Chl-a) to 85.4% correct assignment in the temporal analysis and three parameters (BOD, NH₄+-N, and TN) to almost 71.7% correct assignment in spatial analysis of the two clusters. The FA/PCA applied to datasets of two special clusters of the lake calculated four factors for each region, capturing 72.5% and 62.5% of the total variance, respectively. Strong loadings included DO, BOD, TN, CODCr, CODMn, NH₄+-N, TP, and EC. In addition, box-whisker plots and GIS further facilitated and supported the multivariate analysis results. PMID:19936953

  9. Steady-state Analysis Model for Advanced Fuelcycle Schemes

    2006-05-12

    The model was developed as a part of the study, "Advanced Fuel Cycles and Waste Management", which was performed during 2003—2005 by an ad-hoc expert group under the Nuclear Development Committee in the OECD/NEA. The model was designed for an efficient conduct of nuclear fuel cycle scheme cost analyses. It is simple, transparent and offers users the capability to track down the cost analysis results. All the fuel cycle schemes considered in the model aremore » represented in a graphic format and all values related to a fuel cycle step are shown in the graphic interface, i.e., there are no hidden values embedded in the calculations. All data on the fuel cycle schemes considered in the study including mass flows, waste generation, cost data, and other data such as activities, decay heat and neutron sources of spent fuel and high—level waste along time are included in the model and can be displayed. The user can modify easily the values of mass flows and/or cost parameters and see the corresponding changes in the results. The model calculates: front—end fuel cycle mass flows such as requirements of enrichment and conversion services and natural uranium; mass of waste based on the waste generation parameters and the mass flow; and all costs. It performs Monte Carlo simulations with changing the values of all unit costs within their respective ranges (from lower to upper bounds).« less

  10. Advances in protein complex analysis using mass spectrometry.

    PubMed

    Gingras, Anne-Claude; Aebersold, Ruedi; Raught, Brian

    2005-02-15

    Proteins often function as components of larger complexes to perform a specific function, and formation of these complexes may be regulated. For example, intracellular signalling events often require transient and/or regulated protein-protein interactions for propagation, and protein binding to a specific DNA sequence, RNA molecule or metabolite is often regulated to modulate a particular cellular function. Thus, characterizing protein complexes can offer important insights into protein function. This review describes recent important advances in mass spectrometry (MS)-based techniques for the analysis of protein complexes. Following brief descriptions of how proteins are identified using MS, and general protein complex purification approaches, we address two of the most important issues in these types of studies: specificity and background protein contaminants. Two basic strategies for increasing specificity and decreasing background are presented: whereas (1) tandem affinity purification (TAP) of tagged proteins of interest can dramatically improve the signal-to-noise ratio via the generation of cleaner samples, (2) stable isotopic labelling of proteins may be used to discriminate between contaminants and bona fide binding partners using quantitative MS techniques. Examples, as well as advantages and disadvantages of each approach, are presented. PMID:15611014

  11. Advanced Technology Lifecycle Analysis System (ATLAS) Technology Tool Box (TTB)

    NASA Astrophysics Data System (ADS)

    Doyle, Monica M.; O'Neil, Daniel A.; Christensen, Carissa B.

    2005-02-01

    Forecasting technology capabilities requires a tool and a process for capturing state-of-the-art technology metrics and estimates for future metrics. A decision support tool, known as the Advanced Technology Lifecycle Analysis System (ATLAS), contains a Technology Tool Box (TTB) database designed to accomplish this goal. Sections of this database correspond to a Work Breakdown Structure (WBS) developed by NASA's Exploration Systems Research and Technology (ESRT) Program. These sections cover the waterfront of technologies required for human and robotic space exploration. Records in each section include technology performance, operations, and programmatic metrics. Timeframes in the database provide metric values for the state of the art (Timeframe 0) and forecasts for timeframes that correspond to spiral development milestones in NASA's Exploration Systems Mission Directorate (ESMD) development strategy. Collecting and vetting data for the TTB will involve technologists from across the agency, the aerospace industry and academia. Technologists will have opportunities to submit technology metrics and forecasts to the TTB development team. Semi-annual forums will facilitate discussions about the basis of forecast estimates. As the tool and process mature, the TTB will serve as a powerful communication and decision support tool for the ESRT program.

  12. Steady-State Analysis Model for Advanced Fuel Cycle Schemes.

    2008-03-17

    Version 00 SMAFS was developed as a part of the study, "Advanced Fuel Cycles and Waste Management", which was performed during 2003-2005 by an ad-hoc expert group under the Nuclear Development Committee in the OECD/NEA. The model was designed for an efficient conduct of nuclear fuel cycle scheme cost analyses. It is simple, transparent and offers users the capability to track down cost analysis results. All the fuel cycle schemes considered in the model aremore » represented in a graphic format and all values related to a fuel cycle step are shown in the graphic interface, i.e., there are no hidden values embedded in the calculations. All data on the fuel cycle schemes considered in the study including mass flows, waste generation, cost data, and other data such as activities, decay heat and neutron sources of spent fuel and high-level waste along time are included in the model and can be displayed. The user can easily modify values of mass flows and/or cost parameters and see corresponding changes in the results. The model calculates: front-end fuel cycle mass flows such as requirements of enrichment and conversion services and natural uranium; mass of waste based on the waste generation parameters and the mass flow; and all costs.« less

  13. Advanced research equipment for fast ultraweak luminescence analysis

    NASA Astrophysics Data System (ADS)

    Tudisco, S.; Musumeci, F.; Scordino, A.; Privitera, G.

    2003-10-01

    This article describes new advanced research equipment for fast ultraweak luminescence analysis, which can detect at high sensitivity photons after ultraviolet A laser irradiation in biological probes as well as plant, animal, and human cells. The design and construction of this equipment, developed at the Southern National Laboratory of the National Nuclear Physics Institute, is described with the first experimental results and future developments. The setup, employing a photomultiplier tube working in single photon counting mode, allows accurate and reliable photoluminescence measurements with excitation wavelengths in the range 337-700 nm and the emission wavelength in the range 400-800 nm. With respect to the traditional setup, this new equipment is able to perform measurements starting at a few microseconds after the laser irradiation is switched off and with a large detection efficiency (about 10% of the total solid angle). Moreover, the adopted design assures a low background noise level. A further optimization of the system is under study, with special care for the reliability needed for the delayed luminescence for optical screening project aimed to enhance the detection of the low level photoinduced luminescence from human cells to be used as an optical biopsy technique.

  14. Advances in the analysis of iminocyclitols: Methods, sources and bioavailability.

    PubMed

    Amézqueta, Susana; Torres, Josep Lluís

    2016-05-01

    Iminocyclitols are chemically and metabolically stable, naturally occurring sugar mimetics. Their biological activities make them interesting and extremely promising as both drug leads and functional food ingredients. The first iminocyclitols were discovered using preparative isolation and purification methods followed by chemical characterization using nuclear magnetic resonance spectroscopy. In addition to this classical approach, gas and liquid chromatography coupled to mass spectrometry are increasingly used; they are highly sensitive techniques capable of detecting minute amounts of analytes in a broad spectrum of sources after only minimal sample preparation. These techniques have been applied to identify new iminocyclitols in plants, microorganisms and synthetic mixtures. The separation of iminocyclitol mixtures by chromatography is particularly difficult however, as the most commonly used matrices have very low selectivity for these highly hydrophilic structurally similar molecules. This review critically summarizes recent advances in the analysis of iminocyclitols from plant sources and findings regarding their quantification in dietary supplements and foodstuffs, as well as in biological fluids and organs, from bioavailability studies. PMID:26946023

  15. Safety Analysis of Soybean Processing for Advanced Life Support

    NASA Technical Reports Server (NTRS)

    Hentges, Dawn L.

    1999-01-01

    Soybeans (cv. Hoyt) is one of the crops planned for food production within the Advanced Life Support System Integration Testbed (ALSSIT), a proposed habitat simulation for long duration lunar/Mars missions. Soybeans may be processed into a variety of food products, including soymilk, tofu, and tempeh. Due to the closed environmental system and importance of crew health maintenance, food safety is a primary concern on long duration space missions. Identification of the food safety hazards and critical control points associated with the closed ALSSIT system is essential for the development of safe food processing techniques and equipment. A Hazard Analysis Critical Control Point (HACCP) model was developed to reflect proposed production and processing protocols for ALSSIT soybeans. Soybean processing was placed in the type III risk category. During the processing of ALSSIT-grown soybeans, critical control points were identified to control microbiological hazards, particularly mycotoxins, and chemical hazards from antinutrients. Critical limits were suggested at each CCP. Food safety recommendations regarding the hazards and risks associated with growing, harvesting, and processing soybeans; biomass management; and use of multifunctional equipment were made in consideration of the limitations and restraints of the closed ALSSIT.

  16. Crashworthiness analysis using advanced material models in DYNA3D

    SciTech Connect

    Logan, R.W.; Burger, M.J.; McMichael, L.D.; Parkinson, R.D.

    1993-10-22

    As part of an electric vehicle consortium, LLNL and Kaiser Aluminum are conducting experimental and numerical studies on crashworthy aluminum spaceframe designs. They have jointly explored the effect of heat treat on crush behavior and duplicated the experimental behavior with finite-element simulations. The major technical contributions to the state of the art in numerical simulation arise from the development and use of advanced material model descriptions for LLNL`s DYNA3D code. Constitutive model enhancements in both flow and failure have been employed for conventional materials such as low-carbon steels, and also for lighter weight materials such as aluminum and fiber composites being considered for future vehicles. The constitutive model enhancements are developed as extensions from LLNL`s work in anisotropic flow and multiaxial failure modeling. Analysis quality as a function of level of simplification of material behavior and mesh is explored, as well as the penalty in computation cost that must be paid for using more complex models and meshes. The lightweight material modeling technology is being used at the vehicle component level to explore the safety implications of small neighborhood electric vehicles manufactured almost exclusively from these materials.

  17. Modeling spatial frailties in survival analysis of cucurbit downy mildew epidemics.

    PubMed

    Ojiambo, P S; Kang, E L

    2013-03-01

    Cucurbit downy mildew caused by Pseudoperonospora cubensis is economically the most important disease of cucurbits globally, and the pathogen is disseminated aerially over a large spatial scale. Spatio-temporal spread of the disease was characterized during phase I (low and sporadic disease outbreaks) and II (rapid increase in disease outbreaks) of the epidemic using records collected from sentinel plots from 2008 to 2009 in 23 states in the eastern United States as part of the United States Department of Agriculture Cucurbit Downy Mildew ipmPIPE network. A substantive goal of this study was to explain the pattern of time to disease outbreak using important covariates while accounting for spatially correlated differences in risk of disease outbreak among the states. Survival analyses that accounts for spatial dependence were performed on time to disease outbreak, and posterior median frailties (or random effects) were mapped to identify states with high or low risk for disease outbreak. From February to October, disease occurred in 195 and 172 out of 413 and 556 cases monitored in 2008 and 2009, respectively. Disease outbreaks were spatially aggregated, with a spatial dependence of up to ≈1,025 km where clustering of outbreaks in phase I and II of the epidemic were similar. However, unlike in phase I of the epidemic, space-time point pattern analysis was significant (P < 0.0001) for outbreaks in phase II, during which the highest risk window as estimated by the space-time function was within 1.5 months and 500 km of the initial outbreak. The risk of disease outbreak peaked around July and decreased thereafter until the end of the study period. Spatially correlated analysis of time to disease outbreak indicated the need to incorporate spatial frailties in standard survival analysis models. Evaluation of alternative formulations of the spatial models demonstrated that a Bayesian hierarchical spatially structured frailty model best described time to disease outbreak

  18. Spatially resolved spectroscopy analysis of the XMM-Newton large program on SN1006

    NASA Astrophysics Data System (ADS)

    Li, Jiang-Tao; Decourchelle, Anne; Miceli, Marco; Vink, Jacco; Bocchino, Fabrizio

    2016-04-01

    We perform analysis of the XMM-Newton large program on SN1006 based on our newly developed methods of spatially resolved spectroscopy analysis. We extract spectra from low and high resolution meshes. The former (3596 meshes) is used to roughly decompose the thermal and non-thermal components and characterize the spatial distributions of different parameters, such as temperature, abundances of different elements, ionization age, and electron density of the thermal component, as well as photon index and cutoff frequency of the non-thermal component. On the other hand, the low resolution meshes (583 meshes) focus on the interior region dominated by the thermal emission and have enough counts to well characterize the Si lines. We fit the spectra from the low resolution meshes with different models, in order to decompose the multiple plasma components at different thermal and ionization states and compare their spatial distributions. In this poster, we will present the initial results of this project.

  19. Visualization and analysis of gene expression in tissue sections by spatial transcriptomics.

    PubMed

    Ståhl, Patrik L; Salmén, Fredrik; Vickovic, Sanja; Lundmark, Anna; Navarro, José Fernández; Magnusson, Jens; Giacomello, Stefania; Asp, Michaela; Westholm, Jakub O; Huss, Mikael; Mollbrink, Annelie; Linnarsson, Sten; Codeluppi, Simone; Borg, Åke; Pontén, Fredrik; Costea, Paul Igor; Sahlén, Pelin; Mulder, Jan; Bergmann, Olaf; Lundeberg, Joakim; Frisén, Jonas

    2016-07-01

    Analysis of the pattern of proteins or messengerRNAs (mRNAs) in histological tissue sections is a cornerstone in biomedical research and diagnostics. This typically involves the visualization of a few proteins or expressed genes at a time. We have devised a strategy, which we call "spatial transcriptomics," that allows visualization and quantitative analysis of the transcriptome with spatial resolution in individual tissue sections. By positioning histological sections on arrayed reverse transcription primers with unique positional barcodes, we demonstrate high-quality RNA-sequencing data with maintained two-dimensional positional information from the mouse brain and human breast cancer. Spatial transcriptomics provides quantitative gene expression data and visualization of the distribution of mRNAs within tissue sections and enables novel types of bioinformatics analyses, valuable in research and diagnostics. PMID:27365449

  20. A model-based approach for analysis of spatial structure in genetic data.

    PubMed

    Yang, Wen-Yun; Novembre, John; Eskin, Eleazar; Halperin, Eran

    2012-06-01

    Characterizing genetic diversity within and between populations has broad applications in studies of human disease and evolution. We propose a new approach, spatial ancestry analysis, for the modeling of genotypes in two- or three-dimensional space. In spatial ancestry analysis (SPA), we explicitly model the spatial distribution of each SNP by assigning an allele frequency as a continuous function in geographic space. We show that the explicit modeling of the allele frequency allows individuals to be localized on the map on the basis of their genetic information alone. We apply our SPA method to a European and a worldwide population genetic variation data set and identify SNPs showing large gradients in allele frequency, and we suggest these as candidate regions under selection. These regions include SNPs in the well-characterized LCT region, as well as at loci including FOXP2, OCA2 and LRP1B. PMID:22610118

  1. Spatial statistical analysis of basal stem root disease under natural field epidemic of oil palm

    NASA Astrophysics Data System (ADS)

    Kamu, Assis; Phin, Chong Khim; Seman, Idris Abu; Wan, Hoong Hak; Mun, Ho Chong

    2015-02-01

    Oil palm or scientifically known as Elaeis guineensis Jacq. is the most important commodity crop in Malaysia and has greatly contributed to the economy growth of the country. As far as disease is concerned in the industry, Basal Stem Rot (BSR) caused by Ganoderma boninence remains the most important disease. BSR disease is the most widely studied with information available for oil palm disease in Malaysia. However, there is still limited study on the spatial as well as temporal pattern or distribution of the disease especially under natural field epidemic condition in oil palm plantation. The objective of this study is to spatially identify the pattern of BSR disease under natural field epidemic using two geospatial analytical techniques, which are quadrat analysis for the first order properties of partial pattern analysis and nearest-neighbor analysis (NNA) for the second order properties of partial pattern analysis. Two study sites were selected with different age of tree. Both sites are located in Tawau, Sabah and managed by the same company. The results showed that at least one of the point pattern analysis used which is NNA (i.e. the second order properties of partial pattern analysis) has confirmed the disease is complete spatial randomness. This suggests the spread of the disease is not from tree to tree and the age of palm does not play a significance role in determining the spatial pattern of the disease. From the spatial pattern of the disease, it would help in the disease management program and for the industry in the future. The statistical modelling is expected to help in identifying the right model to estimate the yield loss of oil palm due to BSR disease in the future.

  2. Advanced Coursework Rates by Ethnicity: An 11-Year, Statewide Analysis

    ERIC Educational Resources Information Center

    Fowler, Janis C.

    2013-01-01

    Purpose: The purpose of this study was to examine advanced coursework completion rates, Advanced Placement (AP)/International Baccalaureate (IB) testing rates, AP/IB exam passage rates, and the percentage of AP/IB exam scores at or above the criterion that may exist among Texas public high school students from 2001 to 2012 to ascertain (a) the…

  3. Male biological clock: a critical analysis of advanced paternal age

    PubMed Central

    Ramasamy, Ranjith; Chiba, Koji; Butler, Peter; Lamb, Dolores J.

    2016-01-01

    Extensive research defines the impact of advanced maternal age on couples’ fecundity and reproductive outcomes, but significantly less research has been focused on understanding the impact of advanced paternal age. Yet it is increasingly common for couples at advanced ages to conceive children. Limited research suggests that the importance of paternal age is significantly less than that of maternal age, but advanced age of the father is implicated in a variety of conditions affecting the offspring. This review examines three aspects of advanced paternal age: the potential problems with conception and pregnancy that couples with advanced paternal age may encounter, the concept of discussing a limit to paternal age in a clinical setting, and the risks of diseases associated with advanced paternal age. As paternal age increases, it presents no absolute barrier to conception, but it does present greater risks and complications. The current body of knowledge does not justify dissuading older men from trying to initiate a pregnancy, but the medical community must do a better job of communicating to couples the current understanding of the risks of conception with advanced paternal age. PMID:25881878

  4. Advanced methods of structural and trajectory analysis for transport aircraft

    NASA Technical Reports Server (NTRS)

    Ardema, Mark D.

    1995-01-01

    This report summarizes the efforts in two areas: (1) development of advanced methods of structural weight estimation, and (2) development of advanced methods of trajectory optimization. The majority of the effort was spent in the structural weight area. A draft of 'Analytical Fuselage and Wing Weight Estimation of Transport Aircraft', resulting from this research, is included as an appendix.

  5. An Integrative Platform for Three-dimensional Quantitative Analysis of Spatially Heterogeneous Metastasis Landscapes.

    PubMed

    Guldner, Ian H; Yang, Lin; Cowdrick, Kyle R; Wang, Qingfei; Alvarez Barrios, Wendy V; Zellmer, Victoria R; Zhang, Yizhe; Host, Misha; Liu, Fang; Chen, Danny Z; Zhang, Siyuan

    2016-01-01

    Metastatic microenvironments are spatially and compositionally heterogeneous. This seemingly stochastic heterogeneity provides researchers great challenges in elucidating factors that determine metastatic outgrowth. Herein, we develop and implement an integrative platform that will enable researchers to obtain novel insights from intricate metastatic landscapes. Our two-segment platform begins with whole tissue clearing, staining, and imaging to globally delineate metastatic landscape heterogeneity with spatial and molecular resolution. The second segment of our platform applies our custom-developed SMART 3D (Spatial filtering-based background removal and Multi-chAnnel forest classifiers-based 3D ReconsTruction), a multi-faceted image analysis pipeline, permitting quantitative interrogation of functional implications of heterogeneous metastatic landscape constituents, from subcellular features to multicellular structures, within our large three-dimensional (3D) image datasets. Coupling whole tissue imaging of brain metastasis animal models with SMART 3D, we demonstrate the capability of our integrative pipeline to reveal and quantify volumetric and spatial aspects of brain metastasis landscapes, including diverse tumor morphology, heterogeneous proliferative indices, metastasis-associated astrogliosis, and vasculature spatial distribution. Collectively, our study demonstrates the utility of our novel integrative platform to reveal and quantify the global spatial and volumetric characteristics of the 3D metastatic landscape with unparalleled accuracy, opening new opportunities for unbiased investigation of novel biological phenomena in situ. PMID:27068335

  6. An Integrative Platform for Three-dimensional Quantitative Analysis of Spatially Heterogeneous Metastasis Landscapes

    NASA Astrophysics Data System (ADS)

    Guldner, Ian H.; Yang, Lin; Cowdrick, Kyle R.; Wang, Qingfei; Alvarez Barrios, Wendy V.; Zellmer, Victoria R.; Zhang, Yizhe; Host, Misha; Liu, Fang; Chen, Danny Z.; Zhang, Siyuan

    2016-04-01

    Metastatic microenvironments are spatially and compositionally heterogeneous. This seemingly stochastic heterogeneity provides researchers great challenges in elucidating factors that determine metastatic outgrowth. Herein, we develop and implement an integrative platform that will enable researchers to obtain novel insights from intricate metastatic landscapes. Our two-segment platform begins with whole tissue clearing, staining, and imaging to globally delineate metastatic landscape heterogeneity with spatial and molecular resolution. The second segment of our platform applies our custom-developed SMART 3D (Spatial filtering-based background removal and Multi-chAnnel forest classifiers-based 3D ReconsTruction), a multi-faceted image analysis pipeline, permitting quantitative interrogation of functional implications of heterogeneous metastatic landscape constituents, from subcellular features to multicellular structures, within our large three-dimensional (3D) image datasets. Coupling whole tissue imaging of brain metastasis animal models with SMART 3D, we demonstrate the capability of our integrative pipeline to reveal and quantify volumetric and spatial aspects of brain metastasis landscapes, including diverse tumor morphology, heterogeneous proliferative indices, metastasis-associated astrogliosis, and vasculature spatial distribution. Collectively, our study demonstrates the utility of our novel integrative platform to reveal and quantify the global spatial and volumetric characteristics of the 3D metastatic landscape with unparalleled accuracy, opening new opportunities for unbiased investigation of novel biological phenomena in situ.

  7. An Integrative Platform for Three-dimensional Quantitative Analysis of Spatially Heterogeneous Metastasis Landscapes

    PubMed Central

    Guldner, Ian H.; Yang, Lin; Cowdrick, Kyle R.; Wang, Qingfei; Alvarez Barrios, Wendy V.; Zellmer, Victoria R.; Zhang, Yizhe; Host, Misha; Liu, Fang; Chen, Danny Z.; Zhang, Siyuan

    2016-01-01

    Metastatic microenvironments are spatially and compositionally heterogeneous. This seemingly stochastic heterogeneity provides researchers great challenges in elucidating factors that determine metastatic outgrowth. Herein, we develop and implement an integrative platform that will enable researchers to obtain novel insights from intricate metastatic landscapes. Our two-segment platform begins with whole tissue clearing, staining, and imaging to globally delineate metastatic landscape heterogeneity with spatial and molecular resolution. The second segment of our platform applies our custom-developed SMART 3D (Spatial filtering-based background removal and Multi-chAnnel forest classifiers-based 3D ReconsTruction), a multi-faceted image analysis pipeline, permitting quantitative interrogation of functional implications of heterogeneous metastatic landscape constituents, from subcellular features to multicellular structures, within our large three-dimensional (3D) image datasets. Coupling whole tissue imaging of brain metastasis animal models with SMART 3D, we demonstrate the capability of our integrative pipeline to reveal and quantify volumetric and spatial aspects of brain metastasis landscapes, including diverse tumor morphology, heterogeneous proliferative indices, metastasis-associated astrogliosis, and vasculature spatial distribution. Collectively, our study demonstrates the utility of our novel integrative platform to reveal and quantify the global spatial and volumetric characteristics of the 3D metastatic landscape with unparalleled accuracy, opening new opportunities for unbiased investigation of novel biological phenomena in situ. PMID:27068335

  8. Integrated design and analysis of advanced airfoil shapes for gas turbine engines

    SciTech Connect

    Hill, B.A.; Rooney, P.J.

    1986-01-01

    An integral process in the mechanical design of gas turbine airfoils is the conversion of hot or running geometry into cold or as-manufactured geometry. New and advanced methods of design and analysis must be created that parallel new and technologically advanced turbine components. In particular, to achieve the high performance required of today's gas turbine engines, the industry is forced to design and manufacture increasingly complex airfoil shapes using advanced analysis and modeling techniques. This paper describes a method of integrating advanced, general purpose finite element analysis techniques in the mechanical design process.

  9. Statistics for Time-Series Spatial Data: Applying Survival Analysis to Study Land-Use Change

    ERIC Educational Resources Information Center

    Wang, Ninghua Nathan

    2013-01-01

    Traditional spatial analysis and data mining methods fall short of extracting temporal information from data. This inability makes their use difficult to study changes and the associated mechanisms of many geographic phenomena of interest, for example, land-use. On the other hand, the growing availability of land-change data over multiple time…

  10. Misfits and the Imagined American High School: A Spatial Analysis of Student Identities and Schooling

    ERIC Educational Resources Information Center

    Convertino, Christina

    2015-01-01

    This article provides a socio-spatial analysis of youth identities within the context of school choice reforms. Unable to conform to cultural ideals inscribed in the American school, a diverse group of youth forced out of traditional schools mediate the local production of school choice initiatives through the formation of youth identities as…

  11. Exploratory Data Analysis to Identify Factors Influencing Spatial Distributions of Weed Seed Banks

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Comparing distributions of different species in multiple fields will help us understand the spatial dynamics of weed seed banks, but analyzing observational data requires non-traditional statistical methods. We used classification and regression tree analysis (CART) to investigate factors that influ...

  12. Adaptive Spatial Filtering with Principal Component Analysis for Biomedical Photoacoustic Imaging

    NASA Astrophysics Data System (ADS)

    Nagaoka, Ryo; Yamazaki, Rena; Saijo, Yoshifumi

    Photoacoustic (PA) signal is very sensitive to noise generated by peripheral equipment such as power supply, stepping motor or semiconductor laser. Band-pass filter is not effective because the frequency bandwidth of the PA signal also covers the noise frequency. The objective of the present study is to reduce the noise by using an adaptive spatial filter with principal component analysis (PCA).

  13. The onset of absolute instability of rotating Hagen-Poiseuille flow: A spatial stability analysis

    NASA Astrophysics Data System (ADS)

    Fernandez-Feria, R.; del Pino, C.

    2002-09-01

    A spatial, viscous stability analysis of Poiseuille pipe flow with superimposed solid body rotation is considered. For each value of the swirl parameter (inverse Rossby number) L>0, there exists a critical Reynolds number Rec)(L above which the flow first becomes convectively unstable to nonaxisymmetric disturbances with azimuthal wave number n=-1. This neutral stability curve confirms previous temporal stability analyses. From this spatial stability analysis, we propose here a relatively simple procedure to look for the onset of absolute instability that satisfies the so-called Briggs-Bers criterion. We find that, for perturbations with n=-1, the flow first becomes absolutely unstable above another critical Reynolds number Ret)(L>Rec)(L, provided that L>0.38, with Ret[right arrow]Rec as L[right arrow]infinity. Other values of the azimuthal wave number n are also considered. For Re>Ret)(L, the disturbances grow both upstream and downstream of the source, and the spatial stability analysis becomes inappropriate. However, for Ret, the spatial analysis provides a useful description on how convectively unstable perturbations become absolutely unstable in this kind of flow.

  14. Spatially Resolved Chemical Imaging for Biosignature Analysis: Terrestrial and Extraterrestrial Examples

    NASA Astrophysics Data System (ADS)

    Bhartia, R.; Wanger, G.; Orphan, V. J.; Fries, M.; Rowe, A. R.; Nealson, K. H.; Abbey, W. J.; DeFlores, L. P.; Beegle, L. W.

    2014-12-01

    Detection of in situ biosignatures on terrestrial and planetary missions is becoming increasingly more important. Missions that target the Earth's deep biosphere, Mars, moons of Jupiter (including Europa), moons of Saturn (Titan and Enceladus), and small bodies such as asteroids or comets require methods that enable detection of materials for both in-situ analysis that preserve context and as a means to select high priority sample for return to Earth. In situ instrumentation for biosignature detection spans a wide range of analytical and spectroscopic methods that capitalize on amino acid distribution, chirality, lipid composition, isotopic fractionation, or textures that persist in the environment. Many of the existing analytical instruments are bulk analysis methods and while highly sensitive, these require sample acquisition and sample processing. However, by combining with triaging spectroscopic methods, biosignatures can be targeted on a surface and preserve spatial context (including mineralogy, textures, and organic distribution). To provide spatially correlated chemical analysis at multiple spatial scales (meters to microns) we have employed a dual spectroscopic approach that capitalizes on high sensitivity deep UV native fluorescence detection and high specificity deep UV Raman analysis.. Recently selected as a payload on the Mars 2020 mission, SHERLOC incorporates these optical methods for potential biosignatures detection on Mars. We present data from both Earth analogs that operate as our only examples known biosignatures and meteorite samples that provide an example of abiotic organic formation, and demonstrate how provenance effects the spatial distribution and composition of organics.

  15. Generic Repository Concepts and Thermal Analysis for Advanced Fuel Cycles

    SciTech Connect

    Hardin, Ernest; Blink, James; Carter, Joe; Massimiliano, Fratoni; Greenberg, Harris; Howard, Rob L

    2011-01-01

    The current posture of the used nuclear fuel management program in the U.S. following termination of the Yucca Mountain Project, is to pursue research and development (R&D) of generic (i.e., non-site specific) technologies for storage, transportation and disposal. Disposal R&D is directed toward understanding and demonstrating the performance of reference geologic disposal concepts selected to represent the current state-of-the-art in geologic disposal. One of the principal constraints on waste packaging and emplacement in a geologic repository is management of the waste-generated heat. This paper describes the selection of reference disposal concepts, and thermal management strategies for waste from advanced fuel cycles. A geologic disposal concept for spent nuclear fuel (SNF) or high-level waste (HLW) consists of three components: waste inventory, geologic setting, and concept of operations. A set of reference geologic disposal concepts has been developed by the U.S. Department of Energy (DOE) Used Fuel Disposition Campaign, for crystalline rock, clay/shale, bedded salt, and deep borehole (crystalline basement) geologic settings. We performed thermal analysis of these concepts using waste inventory cases representing a range of advanced fuel cycles. Concepts of operation consisting of emplacement mode, repository layout, and engineered barrier descriptions, were selected based on international progress and previous experience in the U.S. repository program. All of the disposal concepts selected for this study use enclosed emplacement modes, whereby waste packages are in direct contact with encapsulating engineered or natural materials. The encapsulating materials (typically clay-based or rock salt) have low intrinsic permeability and plastic rheology that closes voids so that low permeability is maintained. Uniformly low permeability also contributes to chemically reducing conditions common in soft clay, shale, and salt formations. Enclosed modes are associated

  16. Advanced analysis of complex seismic waveforms to characterize the subsurface Earth structure

    NASA Astrophysics Data System (ADS)

    Jia, Tianxia

    2011-12-01

    This thesis includes three major parts, (1) Body wave analysis of mantle structure under the Calabria slab, (2) Spatial Average Coherency (SPAC) analysis of microtremor to characterize the subsurface structure in urban areas, and (3) Surface wave dispersion inversion for shear wave velocity structure. Although these three projects apply different techniques and investigate different parts of the Earth, their aims are the same, which is to better understand and characterize the subsurface Earth structure by analyzing complex seismic waveforms that are recorded on the Earth surface. My first project is body wave analysis of mantle structure under the Calabria slab. Its aim is to better understand the subduction structure of the Calabria slab by analyzing seismograms generated by natural earthquakes. The rollback and subduction of the Calabrian Arc beneath the southern Tyrrhenian Sea is a case study of slab morphology and slab-mantle interactions at short spatial scale. I analyzed the seismograms traversing the Calabrian slab and upper mantle wedge under the southern Tyrrhenian Sea through body wave dispersion, scattering and attenuation, which are recorded during the PASSCAL CAT/SCAN experiment. Compressional body waves exhibit dispersion correlating with slab paths, which is high-frequency components arrivals being delayed relative to low-frequency components. Body wave scattering and attenuation are also spatially correlated with slab paths. I used this correlation to estimate the positions of slab boundaries, and further suggested that the observed spatial variation in near-slab attenuation could be ascribed to mantle flow patterns around the slab. My second project is Spatial Average Coherency (SPAC) analysis of microtremors for subsurface structure characterization. Shear-wave velocity (Vs) information in soil and rock has been recognized as a critical parameter for site-specific ground motion prediction study, which is highly necessary for urban areas located

  17. Performance analysis of spatial multiplexing MIMO system with time reversal technology

    NASA Astrophysics Data System (ADS)

    Shrestha, Sanjeeb; Dou, Zheng; Khan, Zayed

    2013-03-01

    This paper deals with the performance analysis of Spatial Multiplexing(SM) multiple input multiple output (MIMO) system with time reversal (TR) technology. Focus is given on the spatial multiplexing gain of MIMO than the diversity gain aspect with the notion that the idea of diversity is inseparably associated with the uncertainty of the channel. If transmitter knows Channel State Information (CSI) before transmission, potential benefits can be harvested. TR is used here, to provide Channel State Information (CSI) at the transmitter before transmission. With the features of temporal and spatial focusing, TR not only can provide immunity against fading for spatially multiplexed data stream but also help boost its Multi Stream Interference (MSI) limited performance by mitigating it. The performance analysis of SM-MIMOTR is carried out with the aim of average minimum error probability for quantity of interest data rate. The interest date rate is 19.07 Mbps, where as the average minimum error probably is set to be that of Single Input Multi Output (SIMO) maximum ratio combining system (MRC). BER of Single Input Single Output (SISO) system is also simulated for making comparison tangible. Simulation study shows that Bit Error Rate (BER) performance of the system with the data rate of interest nearly coincides with that of SIMO system at the range of 10-15db and is better than SISO in all simulated Eb/No points. Additionally, from the standpoint of tread off curve, between diversity gain and spatial multiplexing gain, the non linearity nature still holds.

  18. Analysis of spatial-temporal gene expression patterns reveals dynamics and regionalization in developing mouse brain

    PubMed Central

    Chou, Shen-Ju; Wang, Chindi; Sintupisut, Nardnisa; Niou, Zhen-Xian; Lin, Chih-Hsu; Li, Ker-Chau; Yeang, Chen-Hsiang

    2016-01-01

    Allen Brain Atlas (ABA) provides a valuable resource of spatial/temporal gene expressions in mammalian brains. Despite rich information extracted from this database, current analyses suffer from several limitations. First, most studies are either gene-centric or region-centric, thus are inadequate to capture the superposition of multiple spatial-temporal patterns. Second, standard tools of expression analysis such as matrix factorization can capture those patterns but do not explicitly incorporate spatial dependency. To overcome those limitations, we proposed a computational method to detect recurrent patterns in the spatial-temporal gene expression data of developing mouse brains. We demonstrated that regional distinction in brain development could be revealed by localized gene expression patterns. The patterns expressed in the forebrain, medullary and pontomedullary, and basal ganglia are enriched with genes involved in forebrain development, locomotory behavior, and dopamine metabolism respectively. In addition, the timing of global gene expression patterns reflects the general trends of molecular events in mouse brain development. Furthermore, we validated functional implications of the inferred patterns by showing genes sharing similar spatial-temporal expression patterns with Lhx2 exhibited differential expression in the embryonic forebrains of Lhx2 mutant mice. These analysis outcomes confirm the utility of recurrent expression patterns in studying brain development. PMID:26786896

  19. Exploratory Analysis of Spatial-Temporal Patterns of Air Pollution in the City

    NASA Astrophysics Data System (ADS)

    Champendal, Alexandre; Kanevski, Mikhail; Huguenot, Pierre-Emmanuel; Golay, Jean

    2013-04-01

    Air pollution in the city is an important problem influencing environment, well-being of society, economy, management of urban zones, etc. The problem is extremely difficult due to a very complex distribution of the pollution sources, morphology of the city and dispersion processes leading to multivariate nature of the phenomena and high local spatial-temporal variability. The task of understanding, modelling and prediction of spatial-temporal patterns of air pollution in urban zones is an interesting and challenging topic having many research axes from science-based modelling to geostatistics and data mining. The present research mainly deals with a comprehensive exploratory analysis of spatial-temporal air pollution data using statistical, geostatistical and machine learning tools. This analysis helps to 1) understand and model spatial-temporal correlations using variography, 2) explore the temporal evolution of spatial correlation matrix; 3) analyse and visualize an interconnection between measurement stations using network science tools; 4) quantify the availability and predictability of structured patterns. The real data case study deals with spatial-temporal air pollution data of canton Geneva (2002-2011). Carbon dioxide (NO2) have caught our attention. It has effects on health: nitrogen dioxide can irritate the lungs, effects on plants; NO2 contributes to the phenomenon of acid rain. The negative effects of nitrogen dioxides on plants are reducing the growth, production and pesticide resistance. And finally the effects on materials: nitrogen dioxides increase the corrosion. Well-defined patterns of spatial-temporal correlations were detected. The analysis and visualization of spatial correlation matrix for 91 stations were carried out using the network science tools and high levels of clustering were revealed. Moving Window Correlation Matrix and Spatio-temporal variography methods were applied to define and explore the dynamic of our data. More than just

  20. Analysis of the Impact of Soil Heterogeneity on the Spatial Variation of Unsaturated Flow

    NASA Astrophysics Data System (ADS)

    Patterson, Matthew; Gimenez, Daniel; Kerry, Ruth; Goovaerts, Pierre

    2016-04-01

    the numerical model HYDRUS 3D (PC-Progress, Prague, Czech Republic) based on the numerical indices assigned by LISA, was automated. Each of the 100 realizations were run at 10 different inflow rates ranging from 1.44 cm/d to 74.4 cm/d. Each of the 1000 simulations produced resulted in an output of 487 spatially-varied outflows, allowing spatial analysis of the model outputs and comparison to the spatial outputs from the column experiment. Analysis of the effects of the size and spatial location of the synthetic hydraulic property clusters at different flow rates on the spatial distribution of outflow will be presented and discussed.

  1. Learning Bayesian networks from big meteorological spatial datasets. An alternative to complex network analysis

    NASA Astrophysics Data System (ADS)

    Gutiérrez, Jose Manuel; San Martín, Daniel; Herrera, Sixto; Santiago Cofiño, Antonio

    2016-04-01

    The growing availability of spatial datasets (observations, reanalysis, and regional and global climate models) demands efficient multivariate spatial modeling techniques for many problems of interest (e.g. teleconnection analysis, multi-site downscaling, etc.). Complex networks have been recently applied in this context using graphs built from pairwise correlations between the different stations (or grid boxes) forming the dataset. However, this analysis does not take into account the full dependence structure underlying the data, gien by all possible marginal and conditional dependencies among the stations, and does not allow a probabilistic analysis of the dataset. In this talk we introduce Bayesian networks as an alternative multivariate analysis and modeling data-driven technique which allows building a joint probability distribution of the stations including all relevant dependencies in the dataset. Bayesian networks is a sound machine learning technique using a graph to 1) encode the main dependencies among the variables and 2) to obtain a factorization of the joint probability distribution of the stations given by a reduced number of parameters. For a particular problem, the resulting graph provides a qualitative analysis of the spatial relationships in the dataset (alternative to complex network analysis), and the resulting model allows for a probabilistic analysis of the dataset. Bayesian networks have been widely applied in many fields, but their use in climate problems is hampered by the large number of variables (stations) involved in this field, since the complexity of the existing algorithms to learn from data the graphical structure grows nonlinearly with the number of variables. In this contribution we present a modified local learning algorithm for Bayesian networks adapted to this problem, which allows inferring the graphical structure for thousands of stations (from observations) and/or gridboxes (from model simulations) thus providing new

  2. Spatial analysis of mutual fault/fracture and slope controls on rocksliding in Darjeeling Himalaya, India

    NASA Astrophysics Data System (ADS)

    Ghosh, Saibal; Carranza, Emmanuel John M.

    2010-10-01

    In this paper, the Fry analysis was applied to study the spatial patterns (in terms of trends) of rockslides; proportion analysis was applied to study the spatial associations between rockslides and slope aspects; and distance distribution analysis was applied to study the spatial associations of rockslides with different sets of faults/fractures based on trends. In a study area in the Darjeeling district (India), the results of applications of these spatial analytical techniques support a proposition of mutual fault/fracture and slope controls on rocksliding. In different parts of the study area, deep-seated rockslides are associated with (a) NE-trending faults/fractures and SSE-facing slopes, (b) NW-trending faults/fractures and ENE-facing slopes, and (c) NNE-trending faults/fractures and SE- or ENE-facing slopes; whereas shallow translational rockslides are associated with (a) NNE-trending faults/fractures and SE-, NW-, WNW- or WSW-facing slopes, (b) WNW-trending faults/fractures and SW-facing slopes, (c) NNW-trending faults/fractures and ESE- or SW-facing slopes, and (d) NW-trending faults/fractures with SW-facing slopes. Creating and integrating spatial evidence layers representing mutual fault/fracture and slope controls on rocksliding can be achieved satisfactorily via application of evidential belief functions. A predictive map of rockslide susceptibility derived by using slope aspects, slope inclinations and proximity to the faults/fractures that are spatially associated with rockslides is superior to that derives by using slope aspects, slope inclinations and proximity to all faults/fractures. The proposed analytical methods are suitable for first-pass regional-scale assessment of rockslide susceptibility.

  3. Advancements in 3D Structural Analysis of Geothermal Systems

    SciTech Connect

    Siler, Drew L; Faulds, James E; Mayhew, Brett; McNamara, David

    2013-06-23

    Robust geothermal activity in the Great Basin, USA is a product of both anomalously high regional heat flow and active fault-controlled extension. Elevated permeability associated with some fault systems provides pathways for circulation of geothermal fluids. Constraining the local-scale 3D geometry of these structures and their roles as fluid flow conduits is crucial in order to mitigate both the costs and risks of geothermal exploration and to identify blind (no surface expression) geothermal resources. Ongoing studies have indicated that much of the robust geothermal activity in the Great Basin is associated with high density faulting at structurally complex fault intersection/interaction areas, such as accommodation/transfer zones between discrete fault systems, step-overs or relay ramps in fault systems, intersection zones between faults with different strikes or different senses of slip, and horse-tailing fault terminations. These conceptualized models are crucial for locating and characterizing geothermal systems in a regional context. At the local scale, however, pinpointing drilling targets and characterizing resource potential within known or probable geothermal areas requires precise 3D characterization of the system. Employing a variety of surface and subsurface data sets, we have conducted detailed 3D geologic analyses of two Great Basin geothermal systems. Using EarthVision (Dynamic Graphics Inc., Alameda, CA) we constructed 3D geologic models of both the actively producing Brady’s geothermal system and a ‘greenfield’ geothermal prospect at Astor Pass, NV. These 3D models allow spatial comparison of disparate data sets in 3D and are the basis for quantitative structural analyses that can aid geothermal resource assessment and be used to pinpoint discrete drilling targets. The relatively abundant data set at Brady’s, ~80 km NE of Reno, NV, includes 24 wells with lithologies interpreted from careful analysis of cuttings and core, a 1

  4. NEIGHBOUR-IN: Image processing software for spatial analysis of animal grouping

    PubMed Central

    Caubet, Yves; Richard, Freddie-Jeanne

    2015-01-01

    Abstract Animal grouping is a very complex process that occurs in many species, involving many individuals under the influence of different mechanisms. To investigate this process, we have created an image processing software, called NEIGHBOUR-IN, designed to analyse individuals’ coordinates belonging to up to three different groups. The software also includes statistical analysis and indexes to discriminate aggregates based on spatial localisation of individuals and their neighbours. After the description of the software, the indexes computed by the software are illustrated using both artificial patterns and case studies using the spatial distribution of woodlice. The added strengths of this software and methods are also discussed. PMID:26261448

  5. Advanced DInSAR analysis at Campi Flegrei and Vesuvius, Italy

    NASA Astrophysics Data System (ADS)

    Tiampo, K. F.; Camacho, A. G.; Fernandez, J.; Gonzalez, P. J.; Samsonov, S. V.

    2015-12-01

    Geodetic data, the spatial and temporal surface expression of complex geophysical processes in the earth, is being acquired today at unprecedented rates and accuracies. Differential interferometric synthetic aperture radar (DInSAR) is a satellite remote sensing technique used extensively today for mapping ground deformation with high spatial resolution and sub-centimeter precision over large areas that is particularly useful for volcanic monitoring [Massonnet and Feigl, 1998; Rosen et al., 2000]. Here we apply the advanced Multidimensional Small Baseline Subset (MSBAS) InSAR algorithm [Samsonov and d'Oreye, 2012] to several thousand Envisat and RADARSAT-2 images from 1993-2013 and compute time series of ground deformation over the Naples Bay region of Italy. Vesuvius and Campi Flegrei are located in this area in close proximity to the densely populated city of Naples and, as a result, it is one of the most hazardous volcanic areas in the world. We obtain time series of ground deformation at high spatial and temporal resolution that span, for the first time, twenty years. Campi Flegrei underwent continuous subsidence through 1999. Uplift began in 2005, reaching approximately 13 cm by 2013. We model the observed deformation to determine source parameters for subsidence and uplift epochs [Samsonov et al., 2014]. In addition, a typical DInSAR image can contain significant signals from with several different, nonvolcanic sources. For example, we clearly observe decade-long elevation-dependent seasonal oscillations of the vertical displacement component at Vesuvius that are substantially larger than the long-term deformation rate (<0.6 cm/yr). As a result, we employ an eigenpattern decomposition technique known as Karhunen-Loeve expansion (KLE) analysis in order to identify the unique, finite set of correlated deformation patterns associated with volcanic sources at different depths [Tiampo et al., 2004; Tiampo et al., 2012]. Both the inflation and deflation mechanisms

  6. Geographic information systems, remote sensing, and spatial analysis activities in Texas, 2002-07

    USGS Publications Warehouse

    Pearson, D.K.; Gary, R.H.; Wilson, Z.D.

    2007-01-01

    Geographic information system (GIS) technology has become an important tool for scientific investigation, resource management, and environmental planning. A GIS is a computer-aided system capable of collecting, storing, analyzing, and displaying spatially referenced digital data. GIS technology is particularly useful when analyzing a wide variety of spatial data such as with remote sensing and spatial analysis. Remote sensing involves collecting remotely sensed data, such as satellite imagery, aerial photography, or radar images, and analyzing the data to gather information or investigate trends about the environment or the Earth's surface. Spatial analysis combines remotely sensed, thematic, statistical, quantitative, and geographical data through overlay, modeling, and other analytical techniques to investigate specific research questions. It is the combination of data formats and analysis techniques that has made GIS an essential tool in scientific investigations. This document presents information about the technical capabilities and project activities of the U.S. Geological Survey (USGS) Texas Water Science Center (TWSC) GIS Workgroup from 2002 through 2007.

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

    USGS Publications Warehouse

    Saman, D.M.; Cole, H.P.; Odoi, A.; Myers, M.L.; Carey, D.I.; Westneat, S.C.

    2012-01-01

    Background: 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. Methods: 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. Results: 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). Conclusions: 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. ?? 2012 Saman et al.

  8. Geographic Information Systems, Remote Sensing, and Spatial Analysis Activities in Texas, 2002-07

    USGS Publications Warehouse

    Pearson, D.K.; Gary, R.H.; Wilson, Z.D.

    2007-01-01

    Geographic information system (GIS) technology has become an important tool for scientific investigation, resource management, and environmental planning. A GIS is a computer-aided system capable of collecting, storing, analyzing, and displaying spatially referenced digital data. GIS technology is particularly useful when analyzing a wide variety of spatial data such as with remote sensing and spatial analysis. Remote sensing involves collecting remotely sensed data, such as satellite imagery, aerial photography, or radar images, and analyzing the data to gather information or investigate trends about the environment or the Earth's surface. Spatial analysis combines remotely sensed, thematic, statistical, quantitative, and geographical data through overlay, modeling, and other analytical techniques to investigate specific research questions. It is the combination of data formats and analysis techniques that has made GIS an essential tool in scientific investigations. This document presents information about the technical capabilities and project activities of the U.S. Geological Survey (USGS) Texas Water Science Center (TWSC) GIS Workgroup from 2002 through 2007.

  9. A Spatial Cluster Analysis of Tractor Overturns in Kentucky from 1960 to 2002

    PubMed Central

    Saman, Daniel M.; Cole, Henry P.; Odoi, Agricola; Myers, Melvin L.; Carey, Daniel I.; Westneat, Susan C.

    2012-01-01

    Background 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. Methods 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. Results 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). Conclusions 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. PMID:22291980

  10. A ubiquitous method for street scale spatial data collection and analysis in challenging urban environments: mapping health risks using spatial video in Haiti

    PubMed Central

    2013-01-01

    Background Fine-scale and longitudinal geospatial analysis of health risks in challenging urban areas is often limited by the lack of other spatial layers even if case data are available. Underlying population counts, residential context, and associated causative factors such as standing water or trash locations are often missing unless collected through logistically difficult, and often expensive, surveys. The lack of spatial context also hinders the interpretation of results and designing intervention strategies structured around analytical insights. This paper offers a ubiquitous spatial data collection approach using a spatial video that can be used to improve analysis and involve participatory collaborations. A case study will be used to illustrate this approach with three health risks mapped at the street scale for a coastal community in Haiti. Methods Spatial video was used to collect street and building scale information, including standing water, trash accumulation, presence of dogs, cohort specific population characteristics, and other cultural phenomena. These data were digitized into Google Earth and then coded and analyzed in a GIS using kernel density and spatial filtering approaches. The concentrations of these risks around area schools which are sometimes sources of diarrheal disease infection because of the high concentration of children and variable sanitary practices will show the utility of the method. In addition schools offer potential locations for cholera education interventions. Results Previously unavailable fine scale health risk data vary in concentration across the town, with some schools being proximate to greater concentrations of the mapped risks. The spatial video is also used to validate coded data and location specific risks within these “hotspots”. Conclusions Spatial video is a tool that can be used in any environment to improve local area health analysis and intervention. The process is rapid and can be repeated in study

  11. Engineering design and analysis of advanced physical fine coal cleaning technologies

    SciTech Connect

    Not Available

    1992-01-20

    This project is sponsored by the United States Department of Energy (DOE) for the Engineering Design and Analysis of Advanced Physical Fine Coal Cleaning Technologies. The major goal is to provide the simulation tools for modeling both conventional and advanced coal cleaning technologies. This DOE project is part of a major research initiative by the Pittsburgh Energy Technology Center (PETC) aimed at advancing three advanced coal cleaning technologies-heavy-liquid cylconing, selective agglomeration, and advanced froth flotation through the proof-of-concept (POC) level.

  12. SPATIAL AND TEMPORAL ANALYSIS OF NON-URBAN OZONE CONCENTRATIONS OVER THE EASTERN UNITED STATES USING ROTATED PRINCIPAL COMPONENT ANALYSIS

    EPA Science Inventory

    The spatial and temporal variability of 03 concentrations over the eastern United States during the period of 1985 through 1990 was examined through the use of a multivariate statistical technique called Principal Component Analysis. he original data set, which contained 77 corre...

  13. Assessing spatial resolution versus sensitivity from laser speckle contrast imaging: application to frequency analysis.

    PubMed

    Bricq, Stéphanie; Mahé, Guillaume; Rousseau, David; Humeau-Heurtier, Anne; Chapeau-Blondeau, François; Varela, Julio Rojas; Abraham, Pierre

    2012-10-01

    For blood perfusion monitoring, laser speckle contrast (LSC) imaging is a recent non-contact technique that has the characteristic of delivering noise-like speckled images. To exploit LSC images for quantitative physiological measurements, we developed an approach that implements controlled spatial averaging to reduce the detrimental impact of the noise and improve measurement sensitivity. By this approach, spatial resolution and measurement sensitivity can be traded-off in a flexible way depending on the quantitative prospect of the study. As an application, detectability of the cardiac activity from LSC images of forearm using power spectrum analysis is studied through the construction of spatial activity maps offering a window on the blood flow perfusion and its regional distribution. Comparisons with results obtained with signals of laser Doppler flowmetry probes are performed. PMID:22644256

  14. A Spatial Analysis of GEOID03 and GEOID09 in Connecticut

    NASA Astrophysics Data System (ADS)

    Arifuzzaman, Kazi; Hintz, Raymond J.

    2016-06-01

    The National Geodetic Survey (NGS) recommends using a hybrid geoid model to derive orthometric heights from ellipsoid heights. The accuracy of GEOID03 and GEOID09 were assessed independently in Connecticut. The present research analyses the spatial behavior of residuals derived from the comparison of differential levelled NAVD 88 orthometric heights and GPS-derived orthometric heights (using GEOID03 & GEOID09) at 72 benchmarks in Connecticut. Both geometrical and geostatistical analyses were performed on the residuals. A planar regression model indicates a weak spatial relation for residuals derived from GEOID03. This weakness was not noted in the analysis of residuals derived from GEOID09. Results of a four-parameter regression model does not indicate any need for a correction surface. A kriging surface was created with a fitted spherical semivariogram model and suggests GEOID09 captures more spatial variability of geoid undulation than GEOID03 in Connecticut.

  15. In-air ion beam analysis with high spatial resolution proton microbeam

    NASA Astrophysics Data System (ADS)

    Jakšić, M.; Chokheli, D.; Fazinić, S.; Grilj, V.; Skukan, N.; Sudić, I.; Tadić, T.; Antičić, T.

    2016-03-01

    One of the possible ways to maintain the micrometre spatial resolution while performing ion beam analysis in the air is to increase the energy of ions. In order to explore capabilities and limitations of this approach, we have tested a range of proton beam energies (2-6 MeV) using in-air STIM (Scanning Ion Transmission Microscopy) setup. Measurements of the spatial resolution dependence on proton energy have been compared with SRIM simulation and modelling of proton multiple scattering by different approaches. Results were used to select experimental conditions in which 1 micrometre spatial resolution could be obtained. High resolution in-air microbeam could be applied for IBIC (Ion Beam Induced Charge) tests of large detectors used in nuclear and high energy physics that otherwise cannot be tested in relatively small microbeam vacuum chambers.

  16. Research Update: Spatially resolved mapping of electronic structure on atomic level by multivariate statistical analysis

    NASA Astrophysics Data System (ADS)

    Belianinov, Alex; Ganesh, Panchapakesan; Lin, Wenzhi; Sales, Brian C.; Sefat, Athena S.; Jesse, Stephen; Pan, Minghu; Kalinin, Sergei V.

    2014-12-01

    Atomic level spatial variability of electronic structure in Fe-based superconductor FeTe0.55Se0.45 (Tc = 15 K) is explored using current-imaging tunneling-spectroscopy. Multivariate statistical analysis of the data differentiates regions of dissimilar electronic behavior that can be identified with the segregation of chalcogen atoms, as well as boundaries between terminations and near neighbor interactions. Subsequent clustering analysis allows identification of the spatial localization of these dissimilar regions. Similar statistical analysis of modeled calculated density of states of chemically inhomogeneous FeTe1-xSex structures further confirms that the two types of chalcogens, i.e., Te and Se, can be identified by their electronic signature and differentiated by their local chemical environment. This approach allows detailed chemical discrimination of the scanning tunneling microscopy data including separation of atomic identities, proximity, and local configuration effects and can be universally applicable to chemically and electronically inhomogeneous surfaces.

  17. Research Update: Spatially resolved mapping of electronic structure on atomic level by multivariate statistical analysis

    SciTech Connect

    Belianinov, Alex; Panchapakesan, G.; Lin, Wenzhi; Sales, Brian C.; Sefat, Athena Safa; Jesse, Stephen; Pan, Minghu; Kalinin, Sergei V.

    2014-12-02

    Atomic level spatial variability of electronic structure in Fe-based superconductor FeTe0.55Se0.45 (Tc = 15 K) is explored using current-imaging tunneling-spectroscopy. Multivariate statistical analysis of the data differentiates regions of dissimilar electronic behavior that can be identified with the segregation of chalcogen atoms, as well as boundaries between terminations and near neighbor interactions. Subsequent clustering analysis allows identification of the spatial localization of these dissimilar regions. Similar statistical analysis of modeled calculated density of states of chemically inhomogeneous FeTe1 x Sex structures further confirms that the two types of chalcogens, i.e., Te and Se, can be identified by their electronic signature and differentiated by their local chemical environment. This approach allows detailed chemical discrimination of the scanning tunneling microscopy data including separation of atomic identities, proximity, and local configuration effects and can be universally applicable to chemically and electronically inhomogeneous surfaces.

  18. Evidence for fish dispersal from spatial analysis of stream network topology

    USGS Publications Warehouse

    Hitt, N.P.; Angermeier, P.L.

    2008-01-01

    Developing spatially explicit conservation strategies for stream fishes requires an understanding of the spatial structure of dispersal within stream networks. We explored spatial patterns of stream fish dispersal by evaluating how the size and proximity of connected streams (i.e., stream network topology) explained variation in fish assemblage structure and how this relationship varied with local stream size. We used data from the US Environmental Protection Agency's Environmental Monitoring and Assessment Program in wadeable streams of the Mid-Atlantic Highlands region (n = 308 sites). We quantified stream network topology with a continuous analysis based on the rate of downstream flow accumulation from sites and with a discrete analysis based on the presence of mainstem river confluences (i.e., basin area >250 km2) within 20 fluvial km (fkm) from sites. Continuous variation in stream network topology was related to local species richness within a distance of ???10 fkm, suggesting an influence of fish dispersal within this spatial grain. This effect was explained largely by catostomid species, cyprinid species, and riverine species, but was not explained by zoogeographic regions, ecoregions, sampling period, or spatial autocorrelation. Sites near mainstem river confluences supported greater species richness and abundance of catostomid, cyprinid, and ictalurid fishes than did sites >20 fkm from such confluences. Assemblages at sites on the smallest streams were not related to stream network topology, consistent with the hypothesis that local stream size regulates the influence of regional dispersal. These results demonstrate that the size and proximity of connected streams influence the spatial distribution of fish and suggest that these influences can be incorporated into the designs of stream bioassessments and reserves to enhance management efficacy. ?? 2008 by The North American Benthological Society.

  19. Analysis of large scale spatial variability of soil moisture using a geostatistical method.

    PubMed

    Lakhankar, Tarendra; Jones, Andrew S; Combs, Cynthia L; Sengupta, Manajit; Vonder Haar, Thomas H; Khanbilvardi, Reza

    2010-01-01

    Spatial and temporal soil moisture dynamics are critically needed to improve the parameterization for hydrological and meteorological modeling processes. This study evaluates the statistical spatial structure of large-scale observed and simulated estimates of soil moisture under pre- and post-precipitation event conditions. This large scale variability is a crucial in calibration and validation of large-scale satellite based data assimilation systems. Spatial analysis using geostatistical approaches was used to validate modeled soil moisture by the Agriculture Meteorological (AGRMET) model using in situ measurements of soil moisture from a state-wide environmental monitoring network (Oklahoma Mesonet). The results show that AGRMET data produces larger spatial decorrelation compared to in situ based soil moisture data. The precipitation storms drive the soil moisture spatial structures at large scale, found smaller decorrelation length after precipitation. This study also evaluates the geostatistical approach for mitigation for quality control issues within in situ soil moisture network to estimates at soil moisture at unsampled stations. PMID:22315576

  20. A spatial pattern analysis of the halophytic species distribution in an arid coastal environment.

    PubMed

    Badreldin, Nasem; Uria-Diez, J; Mateu, J; Youssef, Ali; Stal, Cornelis; El-Bana, Magdy; Magdy, Ahmed; Goossens, Rudi

    2015-05-01

    Obtaining information about the spatial distribution of desert plants is considered as a serious challenge for ecologists and environmental modeling due to the required intensive field work and infrastructures in harsh and remote arid environments. A new method was applied for assessing the spatial distribution of the halophytic species (HS) in an arid coastal environment. This method was based on the object-based image analysis for a high-resolution Google Earth satellite image. The integration of the image processing techniques and field work provided accurate information about the spatial distribution of HS. The extracted objects were based on assumptions that explained the plant-pixel relationship. Three different types of digital image processing techniques were implemented and validated to obtain an accurate HS spatial distribution. A total of 2703 individuals of the HS community were found in the case study, and approximately 82% were located above an elevation of 2 m. The micro-topography exhibited a significant negative relationship with pH and EC (r = -0.79 and -0.81, respectively, p < 0.001). The spatial structure was modeled using stochastic point processes, in particular a hybrid family of Gibbs processes. A new model is proposed that uses a hard-core structure at very short distances, together with a cluster structure in short-to-medium distances and a Poisson structure for larger distances. This model was found to fit the data perfectly well. PMID:25838060

  1. Semi-blind signal extraction for communication signals by combining independent component analysis and spatial constraints.

    PubMed

    Wang, Xiang; Huang, Zhitao; Zhou, Yiyu

    2012-01-01

    Signal of interest (SOI) extraction is a vital issue in communication signal processing. In this paper, we propose two novel iterative algorithms for extracting SOIs from instantaneous mixtures, which explores the spatial constraint corresponding to the Directions of Arrival (DOAs) of the SOIs as a priori information into the constrained Independent Component Analysis (cICA) framework. The first algorithm utilizes the spatial constraint to form a new constrained optimization problem under the previous cICA framework which requires various user parameters, i.e., Lagrange parameter and threshold measuring the accuracy degree of the spatial constraint, while the second algorithm incorporates the spatial constraints to select specific initialization of extracting vectors. The major difference between the two novel algorithms is that the former incorporates the prior information into the learning process of the iterative algorithm and the latter utilizes the prior information to select the specific initialization vector. Therefore, no extra parameters are necessary in the learning process, which makes the algorithm simpler and more reliable and helps to improve the speed of extraction. Meanwhile, the convergence condition for the spatial constraints is analyzed. Compared with the conventional techniques, i.e., MVDR, numerical simulation results demonstrate the effectiveness, robustness and higher performance of the proposed algorithms. PMID:23012531

  2. Semi-Blind Signal Extraction for Communication Signals by Combining Independent Component Analysis and Spatial Constraints

    PubMed Central

    Wang, Xiang; Huang, Zhitao; Zhou, Yiyu

    2012-01-01

    Signal of interest (SOI) extraction is a vital issue in communication signal processing. In this paper, we propose two novel iterative algorithms for extracting SOIs from instantaneous mixtures, which explores the spatial constraint corresponding to the Directions of Arrival (DOAs) of the SOIs as a priori information into the constrained Independent Component Analysis (cICA) framework. The first algorithm utilizes the spatial constraint to form a new constrained optimization problem under the previous cICA framework which requires various user parameters, i.e., Lagrange parameter and threshold measuring the accuracy degree of the spatial constraint, while the second algorithm incorporates the spatial constraints to select specific initialization of extracting vectors. The major difference between the two novel algorithms is that the former incorporates the prior information into the learning process of the iterative algorithm and the latter utilizes the prior information to select the specific initialization vector. Therefore, no extra parameters are necessary in the learning process, which makes the algorithm simpler and more reliable and helps to improve the speed of extraction. Meanwhile, the convergence condition for the spatial constraints is analyzed. Compared with the conventional techniques, i.e., MVDR, numerical simulation results demonstrate the effectiveness, robustness and higher performance of the proposed algorithms. PMID:23012531

  3. Spatial analysis on human brucellosis incidence in mainland China: 2004–2010

    PubMed Central

    Zhang, Junhui; Yin, Fei; Zhang, Tao; Yang, Chao; Zhang, Xingyu; Feng, Zijian; Li, Xiaosong

    2014-01-01

    Objectives China has experienced a sharply increasing rate of human brucellosis in recent years. Effective spatial monitoring of human brucellosis incidence is very important for successful implementation of control and prevention programmes. The purpose of this paper is to apply exploratory spatial data analysis (ESDA) methods and the empirical Bayes (EB) smoothing technique to monitor county-level incidence rates for human brucellosis in mainland China from 2004 to 2010 by examining spatial patterns. Methods ESDA methods were used to characterise spatial patterns of EB smoothed incidence rates for human brucellosis based on county-level data obtained from the China Information System for Disease Control and Prevention (CISDCP) in mainland China from 2004 to 2010. Results EB smoothed incidence rates for human brucellosis were spatially dependent during 2004–2010. The local Moran test identified significantly high-risk clusters of human brucellosis (all p values <0.01), which persisted during the 7-year study period. High-risk counties were centred in the Inner Mongolia Autonomous Region and other Northern provinces (ie, Hebei, Shanxi, Jilin and Heilongjiang provinces) around the border with the Inner Mongolia Autonomous Region where animal husbandry was highly developed. The number of high-risk counties increased from 25 in 2004 to 54 in 2010. Conclusions ESDA methods and the EB smoothing technique can assist public health officials in identifying high-risk areas. Allocating more resources to high-risk areas is an effective way to reduce human brucellosis incidence. PMID:24713215

  4. Conditional versus unconditional industrial agglomeration: disentangling spatial dependence and spatial heterogeneity in the analysis of ICT firms' distribution in Milan

    NASA Astrophysics Data System (ADS)

    Espa, Giuseppe; Arbia, Giuseppe; Giuliani, Diego

    2013-01-01

    A series of recent papers have introduced some explorative methods based on Ripley's K-function (Ripley in J R Stat Soc B 39(2):172-212, 1977) analyzing the micro-geographical patterns of firms. Often the spatial heterogeneity of an area is handled by referring to a case-control design, in which spatial clusters occur as over-concentrations of firms belonging to a specific industry as opposed to the distribution of firms in the whole economy. Therefore, positive, or negative, spatial dependence between firms occurs when a specific sector of industry is seen to present a more aggregated pattern (or more dispersed) than is common in the economy as a whole. This approach has led to the development of relative measures of spatial concentration which, as a consequence, are not straightforwardly comparable across different economies. In this article, we explore a parametric approach based on the inhomogeneous K-function (Baddeley et al. in Statistica Nederlandica 54(3):329-350, 2000) that makes it possible to obtain an absolute measure of the industrial agglomeration that is also able to capture spatial heterogeneity. We provide an empirical application of the approach taken with regard to the spatial distribution of high-tech industries in Milan (Italy) in 2001.

  5. Factors influencing the spatial extent of mobile source air pollution impacts: a meta-analysis

    PubMed Central

    Zhou, Ying; Levy, Jonathan I

    2007-01-01

    Background There has been growing interest among exposure assessors, epidemiologists, and policymakers in the concept of "hot spots", or more broadly, the "spatial extent" of impacts from traffic-related air pollutants. This review attempts to quantitatively synthesize findings about the spatial extent under various circumstances. Methods We include both the peer-reviewed literature and government reports, and focus on four significant air pollutants: carbon monoxide, benzene, nitrogen oxides, and particulate matter (including both ultrafine particle counts and fine particle mass). From the identified studies, we extracted information about significant factors that would be hypothesized to influence the spatial extent within the study, such as the study type (e.g., monitoring, air dispersion modeling, GIS-based epidemiological studies), focus on concentrations or health risks, pollutant under study, background concentration, emission rate, and meteorological factors, as well as the study's implicit or explicit definition of spatial extent. We supplement this meta-analysis with results from some illustrative atmospheric dispersion modeling. Results We found that pollutant characteristics and background concentrations best explained variability in previously published spatial extent estimates, with a modifying influence of local meteorology, once some extreme values based on health risk estimates were removed from the analysis. As hypothesized, inert pollutants with high background concentrations had the largest spatial extent (often demonstrating no significant gradient), and pollutants formed in near-source chemical reactions (e.g., nitrogen dioxide) had a larger spatial extent than pollutants depleted in near-source chemical reactions or removed through coagulation processes (e.g., nitrogen oxide and ultrafine particles). Our illustrative dispersion model illustrated the complex interplay of spatial extent definitions, emission rates, background concentrations

  6. Current practices in spatial analysis of cancer data: mapping health statistics to inform policymakers and the public

    PubMed Central

    Bell, B Sue; Hoskins, Richard E; Pickle, Linda Williams; Wartenberg, Daniel

    2006-01-01

    Background To communicate population-based cancer statistics, cancer researchers have a long tradition of presenting data in a spatial representation, or map. Historically, health data were presented in printed atlases in which the map producer selected the content and format. The availability of geographic information systems (GIS) with comprehensive mapping and spatial analysis capability for desktop and Internet mapping has greatly expanded the number of producers and consumers of health maps, including policymakers and the public. Because health maps, particularly ones that show elevated cancer rates, historically have raised public concerns, it is essential that these maps be designed to be accurate, clear, and interpretable for the broad range of users who may view them. This article focuses on designing maps to communicate effectively. It is based on years of research into the use of health maps for communicating among public health researchers. Results The basics for designing maps that communicate effectively are similar to the basics for any mode of communication. Tasks include deciding on the purpose, knowing the audience and its characteristics, choosing a media suitable for both the purpose and the audience, and finally testing the map design to ensure that it suits the purpose with the intended audience, and communicates accurately and effectively. Special considerations for health maps include ensuring confidentiality and reflecting the uncertainty of small area statistics. Statistical maps need to be based on sound practices and principles developed by the statistical and cartographic communities. Conclusion The biggest challenge is to ensure that maps of health statistics inform without misinforming. Advances in the sciences of cartography, statistics, and visualization of spatial data are constantly expanding the toolkit available to mapmakers to meet this challenge. Asking potential users to answer questions or to talk about what they see is

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

    NASA Astrophysics Data System (ADS)

    Erfanifard, Y.; Rezayan, F.

    2014-10-01

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

  8. Spatial analysis of myocardial infarction in Iran: National report from the Iranian myocardial infarction registry

    PubMed Central

    Ahmadi, Ali; Soori, Hamid; Mehrabi, Yadollah; Etemad, Koorosh

    2015-01-01

    Background: Myocardial infarction (MI) is a leading cause of mortality and morbidity in Iran. No spatial analysis of MI has been conducted to date. The present study was conducted to determine the pattern of MI incidence and to identify the associated factors in Iran by province. Materials and Methods: This study has two parts. One part is prospective and hospital-based, and the other part is an ecological study. In this study, the data of 20,750 new MI cases registered in Iranian Myocardial Infarction Registry in 2012 were used. For spatial analysis in global and local, spatial autocorrelation, Moran's I, Getis-Ord, and logistic regression models were used. Data were analyzed by Stata software and ArcGIS 9.3. Results: Based on autocorrelation coefficient, a specific pattern was observed in the distribution of MI incidence in different provinces (Moran's I: 0.75, P < 0.001). Spatial pattern of incidence was approximately the same in men and women. MI incidence was clustering in six provinces (North Khorasan, Yazd, Kerman, Semnan, Golestan, and Mazandaran). Out of the associated factors with clustered MI in six provinces, temperature, humidity, hypertension, smoking, and body mass index (BMI) could be mentioned. Hypertension, smoking, and BMI contributed to clustering with, respectively, 2.36, 1.31, and 1.31 odds ratio. Conclusion: Addressing the place-based pattern of incidence and clarifying their epidemiologic dimension, including spatial analysis, has not yet been implemented in Iran. Report on MI incidence rate by place and formal borders is useful and is used in the planning and prioritization in different levels of health system. PMID:26487871

  9. Regional flood frequency analysis using spatial proximity and basin characteristics: Quantile regression vs. parameter regression technique

    NASA Astrophysics Data System (ADS)

    Ahn, Kuk-Hyun; Palmer, Richard

    2016-09-01

    Despite wide use of regression-based regional flood frequency analysis (RFFA) methods, the majority are based on either ordinary least squares (OLS) or generalized least squares (GLS). This paper proposes 'spatial proximity' based RFFA methods using the spatial lagged model (SLM) and spatial error model (SEM). The proposed methods are represented by two frameworks: the quantile regression technique (QRT) and parameter regression technique (PRT). The QRT develops prediction equations for flooding quantiles in average recurrence intervals (ARIs) of 2, 5, 10, 20, and 100 years whereas the PRT provides prediction of three parameters for the selected distribution. The proposed methods are tested using data incorporating 30 basin characteristics from 237 basins in Northeastern United States. Results show that generalized extreme value (GEV) distribution properly represents flood frequencies in the study gages. Also, basin area, stream network, and precipitation seasonality are found to be the most effective explanatory variables in prediction modeling by the QRT and PRT. 'Spatial proximity' based RFFA methods provide reliable flood quantile estimates compared to simpler methods. Compared to the QRT, the PRT may be recommended due to its accuracy and computational simplicity. The results presented in this paper may serve as one possible guidepost for hydrologists interested in flood analysis at ungaged sites.

  10. Different Factors for Different Causes: Analysis of the Spatial Aggregations of Fire Ignitions in Catalonia (Spain).

    PubMed

    González-Olabarria, José Ramón; Mola-Yudego, Blas; Coll, Lluis

    2015-07-01

    The present study analyzes the effects of different socioeconomic factors on the frequency of fire ignition occurrence, according to different original causes. The data include a set of documented ignition points in the region of Catalonia for the period 1995-2008. The analysis focused on the spatial aggregation patterns of the ignitions for each specific ignition cause. The point-based data on ignitions were interpolated into municipality-level information using kernel methods as the basis for defining five ignition density levels. Afterwards, the combination of socioeconomic factors influencing the ignition density levels of the municipalities was analyzed for each documented cause of ignition using a principal component analysis. The obtained results confirmed the idea that both the spatial aggregation patterns of fire ignitions and the factors defining their occurrence were specific for each of the causes of ignition. Intentional fires and those of unknown origin were found to have similar spatial aggregation patterns, and the presence of high ignition density areas was related to high population and high unemployment rates. Additionally, it was found that fires originated from forest work, agricultural activities, pasture burning, and lightning had a very specific behavior on their own, differing from the similarities found on the spatial aggregation of ignitions originated from smokers, electric lines, machinery, campfires, and those of intentional or unknown origin. PMID:25736559

  11. Accuracy enhancement of GPS time series using principal component analysis and block spatial filtering

    NASA Astrophysics Data System (ADS)

    He, Xiaoxing; Hua, Xianghong; Yu, Kegen; Xuan, Wei; Lu, Tieding; Zhang, W.; Chen, X.

    2015-03-01

    This paper focuses on performance analysis and accuracy enhancement of long-term position time series of a regional network of GPS stations with two near sub-blocks, one block of 8 stations in Cascadia region and another block of 14 stations in Southern California. We have analyzed the seasonal variations of the 22 IGS site positions between 2004 and 2011. The Green's function is used to calculate the station-site displacements induced by the environmental loading due to atmospheric pressure, soil moisture, snow depth and nontidal ocean. The analysis has revealed that these loading factors can result in position shift of centimeter level, the displacement time series exhibit a periodic pattern, which can explain about 12.70-21.78% of the seasonal amplitude on vertical GPS time series, and the loading effect is significantly different among the two nearby geographical regions. After the loading effect is corrected, the principal component analysis (PCA)-based block spatial filtering is proposed to filter out the remaining common mode error (CME) of the GPS time series. The results show that the PCA-based block spatial filtering can extract the CME more accurately and effectively than the conventional overall filtering method, reducing more of the uncertainty. With the loading correction and block spatial filtering, about 68.34-73.20% of the vertical GPS seasonal power can be separated and removed, improving the reliability of the GPS time series and hence enabling better deformation analysis and higher precision geodetic applications.

  12. Spatial analysis of drumlins within the Arran, Guelph, and Galt drumlin fields of southern Ontario, Canada

    NASA Astrophysics Data System (ADS)

    Maclachlan, John

    2016-04-01

    Reconstruction of former ice conditions and glacier dynamics in previously glaciated terrains requires understanding of the processes and controls on the development of subglacial landforms such as drumlins. This paper presents a quantitative analysis of the spatial distribution of drumlins identified from digital elevation model (DEM) data within three drumlin fields in southern Ontario, Canada (the Arran, Galt and Guelph drumlin fields) formed in the Late Wisconsin by the Ontario and Georgian Bay ice lobes of the Laurentide Ice Sheet. Detailed field description of a partially excavated drumlin within the Guelph drumlin field provides firther insight to compliment the geomorphometric analysis. Drumlins are identified and their morphological parameters documented using a computer-based process that allows direct comparison of forms within and between individual fields. Statistical analysis of the morphological characteristics and spatial distribution of drumlins within each of the three drumlin fields, using kernel density and nearest neighbour analysis, indicates that drumlins of particular types show distinct patterns of clustering that appear to be are related to several different factors including length of time under ice, bedrock topography, and ice velocity. Sediments exposed in an excavated drumlin within the Guelph drumlin field show a relatively undisturbed older fluvial or glaciofluvial crudely stratified sands draped by a thin veneer of coarse grained deformation till. This stratigraphy is similar to that described from modern drumlins in Iceland and is consistent with models of drumlin formation by subglacial deformation processes. The methodology of drumlin analysis can be applied to the study of any drumlin field with an adequate coverage of digital spatial data. The ability to consistently identify and characterize drumlin morphology and distribution will allow more objective and systematic comparison of these landforms both within and between

  13. A comparative analysis of two highly spatially resolved European atmospheric emission inventories

    NASA Astrophysics Data System (ADS)

    Ferreira, J.; Guevara, M.; Baldasano, J. M.; Tchepel, O.; Schaap, M.; Miranda, A. I.; Borrego, C.

    2013-08-01

    A reliable emissions inventory is highly important for air quality modelling applications, especially at regional or local scales, which require high resolutions. Consequently, higher resolution emission inventories have been developed that are suitable for regional air quality modelling. This research performs an inter-comparative analysis of different spatial disaggregation methodologies of atmospheric emission inventories. This study is based on two different European emission inventories with different spatial resolutions: 1) the EMEP (European Monitoring and Evaluation Programme) inventory and 2) an emission inventory developed by the TNO (Netherlands Organisation for Applied Scientific Research). These two emission inventories were converted into three distinct gridded emission datasets as follows: (i) the EMEP emission inventory was disaggregated by area (EMEParea) and (ii) following a more complex methodology (HERMES-DIS - High-Elective Resolution Modelling Emissions System - DISaggregation module) to understand and evaluate the influence of different disaggregation methods; and (iii) the TNO gridded emissions, which are based on different emission data sources and different disaggregation methods. A predefined common grid with a spatial resolution of 12 × 12 km2 was used to compare the three datasets spatially. The inter-comparative analysis was performed by source sector (SNAP - Selected Nomenclature for Air Pollution) with emission totals for selected pollutants. It included the computation of difference maps (to focus on the spatial variability of emission differences) and a linear regression analysis to calculate the coefficients of determination and to quantitatively measure differences. From the spatial analysis, greater differences were found for residential/commercial combustion (SNAP02), solvent use (SNAP06) and road transport (SNAP07). These findings were related to the different spatial disaggregation that was conducted by the TNO and HERMES

  14. Prospects for higher spatial resolution quantitative X-ray analysis using transition element L-lines

    NASA Astrophysics Data System (ADS)

    Statham, P.; Holland, J.

    2014-03-01

    Lowering electron beam kV reduces electron scattering and improves spatial resolution of X-ray analysis. However, a previous round robin analysis of steels at 5 - 6 kV using Lα-lines for the first row transition elements gave poor accuracies. Our experiments on SS63 steel using Lα-lines show similar biases in Cr and Ni that cannot be corrected with changes to self-absorption coefficients or carbon coating. The inaccuracy may be caused by different probabilities for emission and anomalous self-absorption for the La-line between specimen and pure element standard. Analysis using Ll(L3-M1)-lines gives more accurate results for SS63 plausibly because the M1-shell is not so vulnerable to the atomic environment as the unfilled M4,5-shell. However, Ll-intensities are very weak and WDS analysis may be impractical for some applications. EDS with large area SDD offers orders of magnitude faster analysis and achieves similar results to WDS analysis with Lα-lines but poorer energy resolution precludes the use of Ll-lines in most situations. EDS analysis of K-lines at low overvoltage is an alternative strategy for improving spatial resolution that could give higher accuracy. The trade-off between low kV versus low overvoltage is explored in terms of sensitivity for element detection for different elements.

  15. Advanced Satellite Research Project: SCAR Research Database. Bibliographic analysis

    NASA Technical Reports Server (NTRS)

    Pelton, Joseph N.

    1991-01-01

    The literature search was provided to locate and analyze the most recent literature that was relevant to the research. This was done by cross-relating books, articles, monographs, and journals that relate to the following topics: (1) Experimental Systems - Advanced Communications Technology Satellite (ACTS), and (2) Integrated System Digital Network (ISDN) and Advance Communication Techniques (ISDN and satellites, ISDN standards, broadband ISDN, flame relay and switching, computer networks and satellites, satellite orbits and technology, satellite transmission quality, and network configuration). Bibliographic essay on literature citations and articles reviewed during the literature search task is provided.

  16. Nonlinear displacement analysis of advanced propeller structures using NASTRAN

    NASA Technical Reports Server (NTRS)

    Lawrence, C.; Kielb, R. E.

    1984-01-01

    The steady state displacements of a rotating advanced turboprop are computed using the geometrically nonlinear capabilities of COSMIC NASTRAN Rigid Format 4 and MSC NASTRAN Solution 64. A description of the modified Newton-Raphson algorithm used by Solution 64 and the iterative scheme used by Rigid Format 4 is provided. A representative advanced turboprop, SR3, was used for the study. Displacements for SR3 are computed for rotational speeds up to 10,000 rpm. The results show Solution 64 to be superior for computating displacements of flexible rotating structures. This is attributed to its ability to update the displacement dependent centrifugal force during the solution process.

  17. Improved Cloud and Snow Screening in MAIAC Aerosol Retrievals Using Spectral and Spatial Analysis

    NASA Technical Reports Server (NTRS)

    Lyapustin, A.; Wang, Y.; Laszlo, I.; Kokrkin, S.

    2012-01-01

    An improved cloud/snow screening technique in the Multi-Angle Implementation of Atmospheric Correction (MAIAC) algorithm is described. It is implemented as part of MAIAC aerosol retrievals based on analysis of spectral residuals and spatial variability. Comparisons with AERONET aerosol observations and a large-scale MODIS data analysis show strong suppression of aerosol optical thickness outliers due to unresolved clouds and snow. At the same time, the developed filter does not reduce the aerosol retrieval capability at high 1 km resolution in strongly inhomogeneous environments, such as near centers of the active fires. Despite significant improvement, the optical depth outliers in high spatial resolution data are and will remain the problem to be addressed by the application-dependent specialized filtering techniques.

  18. Collision-free spatial hash functions for structural analysis of billion-vertex chemical bond networks

    NASA Astrophysics Data System (ADS)

    Zhang, Cheng; Bansal, Bhupesh; Branicio, Paulo S.; Kalia, Rajiv K.; Nakano, Aiichiro; Sharma, Ashish; Vashishta, Priya

    2006-09-01

    State-of-the-art molecular dynamics (MD) simulations generate massive datasets involving billion-vertex chemical bond networks, which makes data mining based on graph algorithms such as K-ring analysis a challenge. This paper proposes an algorithm to improve the efficiency of ring analysis of large graphs, exploiting properties of K-rings and spatial correlations of vertices in the graph. The algorithm uses dual-tree expansion (DTE) and spatial hash-function tagging (SHAFT) to optimize computation and memory access. Numerical tests show nearly perfect linear scaling of the algorithm. Also a parallel implementation of the DTE + SHAFT algorithm achieves high scalability. The algorithm has been successfully employed to analyze large MD simulations involving up to 500 million atoms.

  19. Urban Transmission of American Cutaneous Leishmaniasis in Argentina: Spatial Analysis Study

    PubMed Central

    Gil, José F.; Nasser, Julio R.; Cajal, Silvana P.; Juarez, Marisa; Acosta, Norma; Cimino, Rubén O.; Diosque, Patricio; Krolewiecki, Alejandro J.

    2010-01-01

    We used kernel density and scan statistics to examine the spatial distribution of cases of pediatric and adult American cutaneous leishmaniasis in an urban disease-endemic area in Salta Province, Argentina. Spatial analysis was used for the whole population and stratified by women > 14 years of age (n = 159), men > 14 years of age (n = 667), and children < 15 years of age (n = 213). Although kernel density for adults encompassed nearly the entire city, distribution in children was most prevalent in the peripheral areas of the city. Scan statistic analysis for adult males, adult females, and children found 11, 2, and 8 clusters, respectively. Clusters for children had the highest odds ratios (P < 0.05) and were located in proximity of plantations and secondary vegetation. The data from this study provide further evidence of the potential urban transmission of American cutaneous leishmaniasis in northern Argentina. PMID:20207869

  20. An Analysis of Spatial Clustering and Implications for Wildlife Management: A Burrowing Owl Example

    NASA Astrophysics Data System (ADS)

    Fisher, Joshua B.; Trulio, Lynne A.; Biging, Gregory S.; Chromczak, Debra

    2007-03-01

    Analysis tools that combine large spatial and temporal scales are necessary for efficient management of wildlife species, such as the burrowing owl ( Athene cunicularia). We assessed the ability of Ripley’s K-function analysis integrated into a geographic information system (GIS) to determine changes in burrowing owl nest clustering over two years at NASA Ames Research Center. Specifically, we used these tools to detect changes in spatial and temporal nest clustering before, during, and after conducting management by mowing to maintain low vegetation height at nest burrows. We found that the scale and timing of owl nest clustering matched the scale and timing of our conservation management actions over a short time frame. While this study could not determine a causal link between mowing and nest clustering, we did find that Ripley’s K and GIS were effective in detecting owl nest clustering and show promise for future conservation uses.

  1. An analysis of spatial clustering and implications for wildlife management: a burrowing owl example.

    PubMed

    Fisher, Joshua B; Trulio, Lynne A; Biging, Gregory S; Chromczak, Debra

    2007-03-01

    Analysis tools that combine large spatial and temporal scales are necessary for efficient management of wildlife species, such as the burrowing owl (Athene cunicularia). We assessed the ability of Ripley's K-function analysis integrated into a geographic information system (GIS) to determine changes in burrowing owl nest clustering over two years at NASA Ames Research Center. Specifically, we used these tools to detect changes in spatial and temporal nest clustering before, during, and after conducting management by mowing to maintain low vegetation height at nest burrows. We found that the scale and timing of owl nest clustering matched the scale and timing of our conservation management actions over a short time frame. While this study could not determine a causal link between mowing and nest clustering, we did find that Ripley's K and GIS were effective in detecting owl nest clustering and show promise for future conservation uses. PMID:17253092

  2. Advancing effects analysis for integrated, large-scale wildfire risk assessment.

    PubMed

    Thompson, Matthew P; Calkin, David E; Gilbertson-Day, Julie W; Ager, Alan A

    2011-08-01

    In this article, we describe the design and development of a quantitative, geospatial risk assessment tool intended to facilitate monitoring trends in wildfire risk over time and to provide information useful in prioritizing fuels treatments and mitigation measures. The research effort is designed to develop, from a strategic view, a first approximation of how both fire likelihood and intensity influence risk to social, economic, and ecological values at regional and national scales. Three main components are required to generate wildfire risk outputs: (1) burn probability maps generated from wildfire simulations, (2) spatially identified highly valued resources (HVRs), and (3) response functions that describe the effects of fire (beneficial or detrimental) on the HVR. Analyzing fire effects has to date presented a major challenge to integrated risk assessments, due to a limited understanding of the type and magnitude of changes wrought by wildfire to ecological and other nonmarket values. This work advances wildfire effects analysis, recognizing knowledge uncertainty and appropriately managing it through the use of an expert systems approach. Specifically, this work entailed consultation with 10 fire and fuels program management officials from federal agencies with fire management responsibilities in order to define quantitative resource response relationships as a function of fire intensity. Here, we demonstrate a proof-of-concept application of the wildland fire risk assessment tool, using the state of Oregon as a case study. PMID:20981570

  3. Observations Regarding Use of Advanced CFD Analysis, Sensitivity Analysis, and Design Codes in MDO

    NASA Technical Reports Server (NTRS)

    Newman, Perry A.; Hou, Gene J. W.; Taylor, Arthur C., III

    1996-01-01

    Observations regarding the use of advanced computational fluid dynamics (CFD) analysis, sensitivity analysis (SA), and design codes in gradient-based multidisciplinary design optimization (MDO) reflect our perception of the interactions required of CFD and our experience in recent aerodynamic design optimization studies using CFD. Sample results from these latter studies are summarized for conventional optimization (analysis - SA codes) and simultaneous analysis and design optimization (design code) using both Euler and Navier-Stokes flow approximations. The amount of computational resources required for aerodynamic design using CFD via analysis - SA codes is greater than that required for design codes. Thus, an MDO formulation that utilizes the more efficient design codes where possible is desired. However, in the aerovehicle MDO problem, the various disciplines that are involved have different design points in the flight envelope; therefore, CFD analysis - SA codes are required at the aerodynamic 'off design' points. The suggested MDO formulation is a hybrid multilevel optimization procedure that consists of both multipoint CFD analysis - SA codes and multipoint CFD design codes that perform suboptimizations.

  4. Current practices in cancer spatial data analysis: a call for guidance

    PubMed Central

    Pickle, Linda Williams; Waller, Lance A; Lawson, Andrew B

    2005-01-01

    There has long been a recognition that place matters in health, from recognition of clusters of yellow fever and cholera in the 1800s to modern day analyses of regional and neighborhood effects on cancer patterns. Here we provide a summary of discussions about current practices in the spatial analysis of georeferenced cancer data by a panel of experts recently convened at the National Cancer Institute. PMID:15649320

  5. A perturbation analysis of a mechanical model for stable spatial patterning in embryology

    NASA Astrophysics Data System (ADS)

    Bentil, D. E.; Murray, J. D.

    1992-12-01

    We investigate a mechanical cell-traction mechanism that generates stationary spatial patterns. A linear analysis highlights the model's potential for these heterogeneous solutions. We use multiple-scale perturbation techniques to study the evolution of these solutions and compare our solutions with numerical simulations of the model system. We discuss some potential biological applications among which are the formation of ridge patterns, dermatoglyphs, and wound healing.

  6. The spatial metaphor of Utopia in Russian culture and in analysis.

    PubMed

    Tsivinsky, Vladimir

    2014-02-01

    The spatial metaphor of Utopia is considered from a Jungian perspective along with its role in Russian culture and in analysis. Such post-Jungian concepts as the cultural complex and the archetypal story pattern of a victim are used in considering the desperate longing for a rescuer in patients' narratives and in Russian society. A clinical vignette is provided to illustrate these ideas. PMID:24467352

  7. Preliminary spatial analysis of combined BATSE/Ulysses gamma-ray burst locations

    SciTech Connect

    Kippen, R. Marc; Hurley, Kevin; Pendleton, Geoffrey N.

    1998-05-16

    We present the preliminary spatial analysis of 278 bursts that have been localized by BATSE and the two-spacecraft Compton/Ulysses Interplanetary Network. The large number and superior accuracy of the combined BATSE/Ulysses locations provides improved sensitivity to small-angle source properties. We find that the locations are consistent with large- and small-scale isotropy, with no significant small-angle clustering. We constrain the fraction of sources in clusters and discuss the implications for burst repetition.

  8. Frames of reference for helicopter electronic maps - The relevance of spatial cognition and componential analysis

    NASA Technical Reports Server (NTRS)

    Harwood, Kelly; Wickens, Christopher D.

    1991-01-01

    Computer-generated map displays for NOE and low-level helicopter flight were formed according to prior research on maps, navigational problem solving, and spatial cognition in large-scale environments. The north-up map emphasized consistency of object location, wheareas, the track-up map emphasized map-terrain congruency. A component analysis indicates that different cognitive components, e.g., orienting and absolute object location, are supported to varying degrees by properties of different frames of reference.

  9. A tool for the quantitative spatial analysis of mammary gland epithelium

    SciTech Connect

    Ortiz de Solorzano, Carlos; Fernandez-Gonzalez, Rodrigo

    2004-04-09

    In this paper we present a method for the spatial analysis of complex cellular systems based on a multiscale study of neighborhood relationships. A function to measure those relationships, M, is introduced. The refined Relative Neighborhood Graph is then presented as a method to establish vicinity relationships within layered cellular structures, and particularized to epithelial cell nuclei in the mammary gland. Finally, the method is illustrated with two examples that show interactions within one population of epithelial cells and between two different populations.

  10. A Simultaneous Analysis Problem for Advanced General Chemistry Laboratories.

    ERIC Educational Resources Information Center

    Leary, J. J.; Gallaher, T. N.

    1983-01-01

    Oxidation of magnesium metal in air has been used as an introductory experiment for determining the formula of a compound. The experiment described employs essentially the same laboratory procedure but is significantly more advanced in terms of information sought. Procedures and sample calculations/results are provided. (JN)

  11. Design, analysis and test verification of advanced encapsulation systems

    NASA Technical Reports Server (NTRS)

    Garcia, A., III

    1983-01-01

    The analytical methodology for advanced encapsulation designs for the development of photovoltaic modules is presented. Analytical models are developed to test optical, thermal, electrical and structural properties of the various encapsulation systems. Model data is compared to relevant test data to improve model accuracy and develop general principles for the design of photovoltaic modules.

  12. Spatial and temporal statistical analysis of a ground-water level network, Broward County, Florida

    USGS Publications Warehouse

    Swain, E.D.; Sonenshein, R.S.

    1994-01-01

    The U.S. Geological Survey has developed a method to evaluate the spatial and temporal statistics of a continuous ground-water level recorder network in Broward County, Florida. Because the Broward County network is sparse for most spatial statistics, a technique has been developed to define polygons for each well that represent the area monitored by the well within specified criteria. The boundaries of these "confidence polygons" are defined by the endpoints of radial lines oriented toward the other wells. The lengths of these lines are determined as the statistically estimated distances to the points at which ground-water levels can be predicted within specirfied criteria. The confidence polygons indicate: (1) the areal coverage of the network, (2) locations where data are unavailable, and (3) areas of redundant data collection. Comparison with data from a noncontinuous recorder well indicates that the confidence polygons are a good represen- tation of areal coverages. The temporal analysis utilizes statistical techniques similar to those used in the spatial method, defining variations in time rather than in space. Consequently, instead of defining radial distances to points, time intervals are defined over which water-level values can be predicted within a specified confidence. These "temporal confidence intervals" correspond to maximum allowable periods between field measure- ments. To combine all results from the analyses, a single coefficient reflecting the spatial and temporal results has been developed. The coefficient is referred to as the Spatial and Temporal Adequacy and Redundancy Evaluation (STARE) and is determined by three factors: the size of the confidence polygon, the number of times the well is part of a redundant pair, and the temporal confidence interval. This coefficient and the individual results of each analysis are used in evaluating the present network and determining future management decisions.

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

    USGS Publications Warehouse

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

    2003-01-01

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

  14. Laser speckle imaging of rat retinal blood flow with hybrid temporal and spatial analysis method

    NASA Astrophysics Data System (ADS)

    Cheng, Haiying; Yan, Yumei; Duong, Timothy Q.

    2009-02-01

    Noninvasive monitoring of blood flow in retinal circulation will reveal the progression and treatment of ocular disorders, such as diabetic retinopathy, age-related macular degeneration and glaucoma. A non-invasive and direct BF measurement technique with high spatial-temporal resolution is needed for retinal imaging. Laser speckle imaging (LSI) is such a method. Currently, there are two analysis methods for LSI: spatial statistics LSI (SS-LSI) and temporal statistical LSI (TS-LSI). Comparing these two analysis methods, SS-LSI has higher signal to noise ratio (SNR) and TSLSI is less susceptible to artifacts from stationary speckle. We proposed a hybrid temporal and spatial analysis method (HTS-LSI) to measure the retinal blood flow. Gas challenge experiment was performed and images were analyzed by HTS-LSI. Results showed that HTS-LSI can not only remove the stationary speckle but also increase the SNR. Under 100% O2, retinal BF decreased by 20-30%. This was consistent with the results observed with laser Doppler technique. As retinal blood flow is a critical physiological parameter and its perturbation has been implicated in the early stages of many retinal diseases, HTS-LSI will be an efficient method in early detection of retina diseases.

  15. An integrated analysis-synthesis array system for spatial sound fields.

    PubMed

    Bai, Mingsian R; Hua, Yi-Hsin; Kuo, Chia-Hao; Hsieh, Yu-Hao

    2015-03-01

    An integrated recording and reproduction array system for spatial audio is presented within a generic framework akin to the analysis-synthesis filterbanks in discrete time signal processing. In the analysis stage, a microphone array "encodes" the sound field by using the plane-wave decomposition. Direction of arrival of plane-wave components that comprise the sound field of interest are estimated by multiple signal classification. Next, the source signals are extracted by using a deconvolution procedure. In the synthesis stage, a loudspeaker array "decodes" the sound field by reconstructing the plane-wave components obtained in the analysis stage. This synthesis stage is carried out by pressure matching in the interior domain of the loudspeaker array. The deconvolution problem is solved by truncated singular value decomposition or convex optimization algorithms. For high-frequency reproduction that suffers from the spatial aliasing problem, vector panning is utilized. Listening tests are undertaken to evaluate the deconvolution method, vector panning, and a hybrid approach that combines both methods to cover frequency ranges below and above the spatial aliasing frequency. Localization and timbral attributes are considered in the subjective evaluation. The results show that the hybrid approach performs the best in overall preference. In addition, there is a trade-off between reproduction performance and the external radiation. PMID:25786949

  16. Spatial assessment of air quality patterns in Malaysia using multivariate analysis

    NASA Astrophysics Data System (ADS)

    Dominick, Doreena; Juahir, Hafizan; Latif, Mohd Talib; Zain, Sharifuddin M.; Aris, Ahmad Zaharin

    2012-12-01

    This study aims to investigate possible sources of air pollutants and the spatial patterns within the eight selected Malaysian air monitoring stations based on a two-year database (2008-2009). The multivariate analysis was applied on the dataset. It incorporated Hierarchical Agglomerative Cluster Analysis (HACA) to access the spatial patterns, Principal Component Analysis (PCA) to determine the major sources of the air pollution and Multiple Linear Regression (MLR) to assess the percentage contribution of each air pollutant. The HACA results grouped the eight monitoring stations into three different clusters, based on the characteristics of the air pollutants and meteorological parameters. The PCA analysis showed that the major sources of air pollution were emissions from motor vehicles, aircraft, industries and areas of high population density. The MLR analysis demonstrated that the main pollutant contributing to variability in the Air Pollutant Index (API) at all stations was particulate matter with a diameter of less than 10 μm (PM10). Further MLR analysis showed that the main air pollutant influencing the high concentration of PM10 was carbon monoxide (CO). This was due to combustion processes, particularly originating from motor vehicles. Meteorological factors such as ambient temperature, wind speed and humidity were also noted to influence the concentration of PM10.

  17. Spatially Resolved Analysis of Amines Using a Fluorescence Molecular Probe: Molecular Analysis of IDPs

    NASA Technical Reports Server (NTRS)

    Clemett, S. J.; Messenger, S.; Thomas-Keprta, K. L.; Wentworth, S. J.; Robinson, G. A.; McKay, D. S.

    2002-01-01

    Some Interplanetary Dust Particles (IDPs) have large isotope anomalies in H and N. To address the nature of the carrier phase, we are developing a procedure to spatially resolve the distribution of organic species on IDP thin sections utilizing fluorescent molecular probes. Additional information is contained in the original extended abstract.

  18. NASA World Wind: Infrastructure for Spatial Data

    NASA Technical Reports Server (NTRS)

    Hogan, Patrick

    2011-01-01

    The world has great need for analysis of Earth observation data, be it climate change, carbon monitoring, disaster response, national defense or simply local resource management. To best provide for spatial and time-dependent information analysis, the world benefits from an open standards and open source infrastructure for spatial data. In the spirit of NASA's motto "for the benefit of all" NASA invites the world community to collaboratively advance this core technology. The World Wind infrastructure for spatial data both unites and challenges the world for innovative solutions analyzing spatial data while also allowing absolute command and control over any respective information exchange medium.

  19. Integrating Advanced High School Chemistry Research with Organic Chemistry and Instrumental Methods of Analysis

    ERIC Educational Resources Information Center

    Kennedy, Brian J.

    2008-01-01

    This paper describes and discusses the unique chemistry course opportunities beyond the advanced placement-level available at a science and technology magnet high school. Students may select entry-level courses such as honors and advanced placement chemistry; they may also take electives in organic chemistry with instrumental methods of analysis;…

  20. Advanced wavefront measurement and analysis of laser system modeling

    SciTech Connect

    Wolfe, C.R.; Auerback, J.M.

    1994-11-15

    High spatial resolution measurements of the reflected or transmitted wavefronts of large aperture optical components used in high peak power laser systems is now possible. These measurements are produced by phase shifting interferometry. The wavefront data is in the form of 3-D phase maps that reconstruct the wavefront shape. The emphasis of this work is on the characterization of wavefront features in the mid-spatial wavelength range (from 0.1 to 10.0 mm) and has been accomplished for the first time. Wavefront structure from optical components with spatial wavelengths in this range are of concern because their effects in high peak power laser systems. At high peak power, this phase modulation can convert to large magnitude intensity modulation by non-linear processes. This can lead to optical damage. We have developed software to input the measured phase map data into beam propagation codes in order to model this conversion process. We are analyzing this data to: (1) Characterize the wavefront structure produced by current optical components, (2) Refine our understanding of laser system performance, (3) Develop a database from which future optical component specifications can be derived.

  1. Object Based Image Analysis Combining High Spatial Resolution Imagery and Laser Point Clouds for Urban Land Cover

    NASA Astrophysics Data System (ADS)

    Zou, Xiaoliang; Zhao, Guihua; Li, Jonathan; Yang, Yuanxi; Fang, Yong

    2016-06-01

    With the rapid developments of the sensor technology, high spatial resolution imagery and airborne Lidar point clouds can be captured nowadays, which make classification, extraction, evaluation and analysis of a broad range of object features available. High resolution imagery, Lidar dataset and parcel map can be widely used for classification as information carriers. Therefore, refinement of objects classification is made possible for the urban land cover. The paper presents an approach to object based image analysis (OBIA) combing high spatial resolution imagery and airborne Lidar point clouds. The advanced workflow for urban land cover is designed with four components. Firstly, colour-infrared TrueOrtho photo and laser point clouds were pre-processed to derive the parcel map of water bodies and nDSM respectively. Secondly, image objects are created via multi-resolution image segmentation integrating scale parameter, the colour and shape properties with compactness criterion. Image can be subdivided into separate object regions. Thirdly, image objects classification is performed on the basis of segmentation and a rule set of knowledge decision tree. These objects imagery are classified into six classes such as water bodies, low vegetation/grass, tree, low building, high building and road. Finally, in order to assess the validity of the classification results for six classes, accuracy assessment is performed through comparing randomly distributed reference points of TrueOrtho imagery with the classification results, forming the confusion matrix and calculating overall accuracy and Kappa coefficient. The study area focuses on test site Vaihingen/Enz and a patch of test datasets comes from the benchmark of ISPRS WG III/4 test project. The classification results show higher overall accuracy for most types of urban land cover. Overall accuracy is 89.5% and Kappa coefficient equals to 0.865. The OBIA approach provides an effective and convenient way to combine high

  2. Asymptotically exact analysis of stochastic metapopulation dynamics with explicit spatial structure.

    PubMed

    Ovaskainen, Otso; Cornell, Stephen J

    2006-02-01

    We describe a mathematically exact method for the analysis of spatially structured Markov processes. The method is based on a systematic perturbation expansion around the deterministic, non-spatial mean-field theory, using the theory of distributions to account for space and the underlying stochastic differential equations to account for stochasticity. As an example, we consider a spatial version of the Levins metapopulation model, in which the habitat patches are distributed in the d-dimensional landscape Rd in a random (but possibly correlated) manner. Assuming that the dispersal kernel is characterized by a length scale L, we examine how the behavior of the metapopulation deviates from the mean-field model for a finite but large L. For example, we show that the equilibrium fraction of occupied patches is given by p(0)+c/L(d)+O(L(-3d/2)), where p(0) is the equilibrium state of the Levins model and the constant c depends on p(0), the dispersal kernel, and the structure of the landscape. We show that patch occupancy can be increased or decreased by spatial structure, but is always decreased by stochasticity. Comparison with simulations show that the analytical results are not only asymptotically exact (as L-->infinity), but a good approximation also when L is relatively small. PMID:16246386

  3. Spatial and sampling analysis for a sensor viewing a pixelized projector

    NASA Astrophysics Data System (ADS)

    Sieglinger, Breck A.; Flynn, David S.; Coker, Charles F.

    1997-07-01

    This paper presents an analysis of spatial blurring and sampling effects for a sensor viewing a pixelized scene projector. It addresses the ability of a projector to simulate an arbitrary continuous radiance scene using a field of discrete elements. The spatial fidelity of the projector as seen by an imaging sensor is shown to depend critically on the width of the sensor MTF or spatial response function, and the angular spacing between projector pixels. Quantitative results are presented based on a simulation that compares the output of a sensor viewing a reference scene to the output of the sensor viewing a projector display of the reference scene. Dependence on the blur of the sensor and projector, the scene content, and alignment both of features in the scene and sensor samples with the projector pixel locations are addressed. We attempt to determine the projector characteristics required to perform hardware-in-the-loop testing with adequate spatial realism to evaluate seeker functions like autonomous detection, measuring radiant intensities and angular positions or unresolved objects, or performing autonomous recognition and aimpoint selection for resolved objects.

  4. Spatial extreme value analysis to project extremes of large-scale indicators for severe weather

    PubMed Central

    Gilleland, Eric; Brown, Barbara G; Ammann, Caspar M

    2013-01-01

    Concurrently high values of the maximum potential wind speed of updrafts (Wmax) and 0–6 km wind shear (Shear) have been found to represent conducive environments for severe weather, which subsequently provides a way to study severe weather in future climates. Here, we employ a model for the product of these variables (WmSh) from the National Center for Atmospheric Research/United States National Center for Environmental Prediction reanalysis over North America conditioned on their having extreme energy in the spatial field in order to project the predominant spatial patterns of WmSh. The approach is based on the Heffernan and Tawn conditional extreme value model. Results suggest that this technique estimates the spatial behavior of WmSh well, which allows for exploring possible changes in the patterns over time. While the model enables a method for inferring the uncertainty in the patterns, such analysis is difficult with the currently available inference approach. A variation of the method is also explored to investigate how this type of model might be used to qualitatively understand how the spatial patterns of WmSh correspond to extreme river flow events. A case study for river flows from three rivers in northwestern Tennessee is studied, and it is found that advection of WmSh from the Gulf of Mexico prevails while elsewhere, WmSh is generally very low during such extreme events. © 2013 The Authors. Environmetrics published by JohnWiley & Sons, Ltd. PMID:24223482

  5. Spatial-Temporal Epidemiology of Tuberculosis in Mainland China: An Analysis Based on Bayesian Theory

    PubMed Central

    Cao, Kai; Yang, Kun; Wang, Chao; Guo, Jin; Tao, Lixin; Liu, Qingrong; Gehendra, Mahara; Zhang, Yingjie; Guo, Xiuhua

    2016-01-01

    Objective: To explore the spatial-temporal interaction effect within a Bayesian framework and to probe the ecological influential factors for tuberculosis. Methods: Six different statistical models containing parameters of time, space, spatial-temporal interaction and their combination were constructed based on a Bayesian framework. The optimum model was selected according to the deviance information criterion (DIC) value. Coefficients of climate variables were then estimated using the best fitting model. Results: The model containing spatial-temporal interaction parameter was the best fitting one, with the smallest DIC value (−4,508,660). Ecological analysis results showed the relative risks (RRs) of average temperature, rainfall, wind speed, humidity, and air pressure were 1.00324 (95% CI, 1.00150–1.00550), 1.01010 (95% CI, 1.01007–1.01013), 0.83518 (95% CI, 0.93732–0.96138), 0.97496 (95% CI, 0.97181–1.01386), and 1.01007 (95% CI, 1.01003–1.01011), respectively. Conclusions: The spatial-temporal interaction was statistically meaningful and the prevalence of tuberculosis was influenced by the time and space interaction effect. Average temperature, rainfall, wind speed, and air pressure influenced tuberculosis. Average humidity had no influence on tuberculosis. PMID:27164117

  6. Time-dependent analysis of 8 days of CN spatial profiles in comet P/Halley

    NASA Technical Reports Server (NTRS)

    Combi, Michael; Huang, Bormin; Cochran, Anita; Fink, Uwe; Schulz, Rita

    1994-01-01

    CN profiles in comet P/Halley were constructed from observations taken at three observatories during an 8 day period in April 1986. These data provide a time series of CN spatial profiles spanning just over one 7.37 day period from 1986 April 7 to April 15 and sample distances from the nucleus from just over 10(exp 3) km to 10(exp 6) km. The effect of the 7.37 day periodic variation on the CN distribution in P/Halley has been examined by using the time-dependent model applied earlier to a subset of the data. Because of the large spatial scale of the data on April 7, 8, and 9 (approx. 10(exp 6) km), and the corresponding transport time in the coma, information present in the spatial profiles regarding the gas production rate actually covers nearly two full periods. These spatially extended profiles clearly show the wavy structures outside 10(exp 5) km. Such structures were predicted in a previous analysis (Combi & Fink 1993) that was based solely on the photometric light curve and on profiles which only extended to distances less than 10(exp 5) km. We are now able to reproduce the highly variable Halley correction for the variation in gas production rate.

  7. Spatial extreme value analysis to project extremes of large-scale indicators for severe weather.

    PubMed

    Gilleland, Eric; Brown, Barbara G; Ammann, Caspar M

    2013-09-01

    Concurrently high values of the maximum potential wind speed of updrafts (W max) and 0-6 km wind shear (Shear) have been found to represent conducive environments for severe weather, which subsequently provides a way to study severe weather in future climates. Here, we employ a model for the product of these variables (WmSh) from the National Center for Atmospheric Research/United States National Center for Environmental Prediction reanalysis over North America conditioned on their having extreme energy in the spatial field in order to project the predominant spatial patterns of WmSh. The approach is based on the Heffernan and Tawn conditional extreme value model. Results suggest that this technique estimates the spatial behavior of WmSh well, which allows for exploring possible changes in the patterns over time. While the model enables a method for inferring the uncertainty in the patterns, such analysis is difficult with the currently available inference approach. A variation of the method is also explored to investigate how this type of model might be used to qualitatively understand how the spatial patterns of WmSh correspond to extreme river flow events. A case study for river flows from three rivers in northwestern Tennessee is studied, and it is found that advection of WmSh from the Gulf of Mexico prevails while elsewhere, WmSh is generally very low during such extreme events. © 2013 The Authors. Environmetrics published by JohnWiley & Sons, Ltd. PMID:24223482

  8. Analysis of the community structure of abyssal kinetoplastids revealed similar communities at larger spatial scales

    PubMed Central

    Salani, Faezeh Shah; Arndt, Hartmut; Hausmann, Klaus; Nitsche, Frank; Scheckenbach, Frank

    2012-01-01

    Knowledge of the spatial scales of diversity is necessary to evaluate the mechanisms driving biodiversity and biogeography in the vast but poorly understood deep sea. The community structure of kinetoplastids, an important group of microbial eukaryotes belonging to the Euglenozoa, from all abyssal plains of the South Atlantic and two areas of the eastern Mediterranean was studied using partial small subunit ribosomal DNA gene clone libraries. A total of 1364 clones from 10 different regions were retrieved. The analysis revealed statistically not distinguishable communities from both the South-East Atlantic (Angola and Guinea Basin) and the South-West Atlantic (Angola and Brazil Basin) at spatial scales of 1000–3000 km, whereas all other communities were significantly differentiated from one another. It seems likely that multiple processes operate at the same time to shape communities of deep-sea kinetoplastids. Nevertheless, constant and homogenous environmental conditions over large spatial scales at abyssal depths, together with high dispersal capabilities of microbial eukaryotes, maintain best the results of statistically indistinguishable communities at larger spatial scales. PMID:22071346

  9. Rural tourism spatial distribution based on multi-criteria decision analysis and GIS

    NASA Astrophysics Data System (ADS)

    Zhang, Hongxian; Yang, Qingsheng

    2008-10-01

    To study spatial distribution of rural tourism can provide scientific decision basis for developing rural economics. Traditional ways of tourism spatial distribution have some limitations in quantifying priority locations of tourism development on small units. They can only produce the overall tourism distribution locations and whether locations are suitable to tourism development simply while the tourism develop ranking with different decision objectives should be considered. This paper presents a way to find ranking of location of rural tourism development in spatial by integrating multi-criteria decision analysis (MCDA) and geography information system (GIS). In order to develop country economics with inconvenient transportation, undeveloped economy and better tourism resource, these locations should be firstly develop rural tourism. Based on this objective, the tourism develop priority utility of each town is calculated with MCDA and GIS. Towns which should be first develop rural tourism can be selected with higher tourism develop priority utility. The method is used to find ranking of location of rural tourism in Ningbo City successfully. The result shows that MCDA is an effective way for distribution rural tourism in spatial based on special decision objectives and rural tourism can promote economic development.

  10. Spatial analysis of lettuce downy mildew using geostatistics and geographic information systems.

    PubMed

    Wu, B M; van Bruggen, A H; Subbarao, K V; Pennings, G G

    2001-02-01

    ABSTRACT The epidemiology of lettuce downy mildew has been investigated extensively in coastal California. However, the spatial patterns of the disease and the distance that Bremia lactucae spores can be transported have not been determined. During 1995 to 1998, we conducted several field- and valley-scale surveys to determine spatial patterns of this disease in the Salinas valley. Geostatistical analyses of the survey data at both scales showed that the influence range of downy mildew incidence at one location on incidence at other locations was between 80 and 3,000 m. A linear relationship was detected between semivariance and lag distance at the field scale, although no single statistical model could fit the semi-variograms at the valley scale. Spatial interpolation by the inverse distance weighting method with a power of 2 resulted in plausible estimates of incidence throughout the valley. Cluster analysis in geographic information systems on the interpolated disease incidence from different dates demonstrated that the Salinas valley could be divided into two areas, north and south of Salinas City, with high and low disease pressure, respectively. Seasonal and spatial trends along the valley suggested that the distinction between the downy mildew conducive and nonconducive areas might be determined by environmental factors. PMID:18944386

  11. Socio-Demographic Predictors and Distribution of Pulmonary Tuberculosis (TB) in Xinjiang, China: A Spatial Analysis

    PubMed Central

    Wubuli, Atikaimu; Xue, Feng; Jiang, Daobin; Yao, Xuemei; Upur, Halmurat; Wushouer, Qimanguli

    2015-01-01

    Objectives Xinjiang is one of the high TB burden provinces of China. A spatial analysis was conducted using geographical information system (GIS) technology to improve the understanding of geographic variation of the pulmonary TB occurrence in Xinjiang, its predictors, and to search for targeted interventions. Methods Numbers of reported pulmonary TB cases were collected at county/district level from TB surveillance system database. Population data were extracted from Xinjiang Statistical Yearbook (2006~2014). Spatial autocorrelation (or dependency) was assessed using global Moran’s I statistic. Anselin’s local Moran’s I and local Getis-Ord statistics were used to detect local spatial clusters. Ordinary least squares (OLS) regression, spatial lag model (SLM) and geographically-weighted regression (GWR) models were used to explore the socio-demographic predictors of pulmonary TB incidence from global and local perspectives. SPSS17.0, ArcGIS10.2.2, and GeoDA software were used for data analysis. Results Incidence of sputum smear positive (SS+) TB and new SS+TB showed a declining trend from 2005 to 2013. Pulmonary TB incidence showed a declining trend from 2005 to 2010 and a rising trend since 2011 mainly caused by the rising trend of sputum smear negative (SS-) TB incidence (p<0.0001). Spatial autocorrelation analysis showed the presence of positive spatial autocorrelation for pulmonary TB incidence, SS+TB incidence and SS-TB incidence from 2005 to 2013 (P <0.0001). The Anselin’s Local Moran’s I identified the “hotspots” which were consistently located in the southwest regions composed of 20 to 28 districts, and the “coldspots” which were consistently located in the north central regions consisting of 21 to 27 districts. Analysis with the Getis-Ord Gi* statistic expanded the scope of “hotspots” and “coldspots” with different intensity; 30 county/districts clustered as “hotspots”, while 47 county/districts clustered as

  12. Genome Reshuffling for Advanced Intercross Permutation (GRAIP): Simulation and permutation for advanced intercross population analysis

    SciTech Connect

    Pierce, Jeremy; Broman, Karl; Lu, Lu; Chesler, Elissa J; Zhou, Guomin; Airey, David; Birmingham, Amanda; Williams, Robert

    2008-04-01

    Background: Advanced intercross lines (AIL) are segregating populations created using a multi-generation breeding protocol for fine mapping complex trait loci (QTL) in mice and other organisms. Applying QTL mapping methods for intercross and backcross populations, often followed by na ve permutation of individuals and phenotypes, does not account for the effect of AIL family structure in which final generations have been expanded and leads to inappropriately low significance thresholds. The critical problem with na ve mapping approaches in AIL populations is that the individual is not an exchangeable unit. Methodology/Principal Findings: The effect of family structure has immediate implications for the optimal AIL creation (many crosses, few animals per cross, and population expansion before the final generation) and we discuss these and the utility of AIL populations for QTL fine mapping. We also describe Genome Reshuffling for Advanced Intercross Permutation, (GRAIP) a method for analyzing AIL data that accounts for family structure. GRAIP permutes a more interchangeable unit in the final generation crosses - the parental genome - and simulating regeneration of a permuted AIL population based on exchanged parental identities. GRAIP determines appropriate genome-wide significance thresholds and locus-specific Pvalues for AILs and other populations with similar family structures. We contrast GRAIP with na ve permutation using a large densely genotyped mouse AIL population (1333 individuals from 32 crosses). A na ve permutation using coat color as a model phenotype demonstrates high false-positive locus identification and uncertain significance levels, which are corrected using GRAIP. GRAIP also detects an established hippocampus weight locus and a new locus, Hipp9a. Conclusions and Significance: GRAIP determines appropriate genome-wide significance thresholds and locus-specific Pvalues for AILs and other populations with similar family structures. The effect of

  13. [Advances in energy analysis of agro-ecosystems].

    PubMed

    Lu, Hongfang; Lan, Shengfang; Chen, Feipeng; Peng, Shaolin

    2004-01-01

    The energy analysis of agro-ecosystems from the view point of energy flow is a quantitative study on the function of agro-ecosystem, and is one of the most important aspects in agro-ecosystem study. In this paper, the history and some current progresses of energy analysis on agro-ecosystems were reviewed briefly, and the difference and breakthrough of emergy analysis theory with the traditional energy analysis method, some current challenges in front of emergy analysis of agro-ecosystems, and some of the new trends were discussed. Using the direct and indirect cost of solar energy to evaluate any energy or material, emergy analysis is the new development of energy analysis, not only in concept but also on calculation method. Developing to emergy analysis phase, there were still some deficiencies on energy analysis of agro-ecosystem, such as the complicate calculation of transformation and the vacancy of energy index for sustainable development, etc. How to solve these problems combined with the clearing of the maximum Em-power principle, the combination among energy analysis, emergy analysis, material analysis and landscape analysis has made up of the current and future trends of energy analysis of agro-ecosystem. PMID:15139211

  14. Advanced demodulation technique for the extraction of tissue optical properties and structural orientation contrast in the spatial frequency domain

    PubMed Central

    Nadeau, Kyle P.; Durkin, Anthony J.; Tromberg, Bruce J.

    2014-01-01

    Abstract. We have developed a method for extracting spatial frequency information content from biological tissue, which is used to calculate tissue optical properties and determine tissue structural orientation. This demodulation method employs a two-dimensional Hilbert transform using a spiral phase function in Fourier space. The approach presented here allows for the determination of tissue optical properties using a single frame of data for each modulation frequency, increasing imaging speed by two to threefold versus conventional, three-phase spatial frequency domain imaging (SFDI). This new single-phase Hilbert transform approach recovers optical property and scattering orientation index values within 1% and 10% of three-phase SFDI, respectively. These results suggest that, using the Hilbert demodulation technique, SFDI data acquisition speed can be increased significantly while preserving data quality, which will help us move forward toward the implementation of a real-time SFDI platform. PMID:24858131

  15. An advanced structural analysis/synthesis capability - ACCESS 2

    NASA Technical Reports Server (NTRS)

    Schmit, L. A.; Miura, H.

    1976-01-01

    An advanced automated design procedure for minimum-weight design of structures (ACCESS 2) is reported. Design variable linking, constraint deletion, and explicit constraint approximation are used to combine effectively finite-element and nonlinear mathematical programming techniques. The approximation-concepts approach to structural synthesis is extended to problems involving fiber composite structure, thermal effects, and natural frequency constraints in addition to the usual static stress and displacement limitations. Sample results illustrating these features are given.

  16. An advanced structural analysis/synthesis capability - ACCESS 2

    NASA Technical Reports Server (NTRS)

    Schmit, L. A.; Miura, H.

    1978-01-01

    An advanced automated design procedure for minimum weight design of structures (ACCESS 2) is reported. Design variable linking, constraint deletion, and explicit constraint approximation are used to effectively combine finite element and nonlinear mathematical programming techniques. The approximation concepts approach to structural synthesis is extended to problems involving fiber composite structure, thermal effects and natural frequency constraints in addition to the usual static stress and displacement limitations. Sample results illustrating these new features are given.

  17. Systematic analysis of advanced fusion fuel in inertial fusion energy

    NASA Astrophysics Data System (ADS)

    Velarde, G.; Eliezer, S.; Henis, Z.; Piera, M.; Martinez-Val, J. M.

    1997-04-01

    Aneutronic fusion reactions can be considered as the cleanest way to exploit nuclear energy. However, these reactions present in general two main drawbacks.—very high temperatures are needed to reach relevant values of their cross sections—Moderate (and even low) energy yield per reaction. This value is still lower if measured in relation to the Z number of the reacting particles. It is already known that bremsstrahlung overruns the plasma reheating by fusion born charged-particles in most of the advanced fuels. This is for instance the case for proton-boron-11 fusion in a stoichiometric plasma and is also so in lithium isotopes fusion reactions. In this paper, the use of deuterium-tritium seeding is suggested to allow to reach higher burnup fractions of advanced fuels, starting at a lower ignition temperature. Of course, neutron production increases as DT contents does. Nevertheless, the ratio of neutron production to energy generation is much lower in DT-advanced fuel mixtures than in pure DT plasmas. One of the main findings of this work is that some natural resources (as D and Li-7) can be burned-up in a catalytic regime for tritium. In this case, neither external tritium breeding nor tritium storage are needed, because the tritium inventory after the fusion burst is the same as before it. The fusion reactor can thus operate on a pure recycling of a small tritium inventory.

  18. Spatial Intensity Duration Frequency Relationships Using Hierarchical Bayesian Analysis for Urban Areas

    NASA Astrophysics Data System (ADS)

    Rupa, Chandra; Mujumdar, Pradeep

    2016-04-01

    In urban areas, quantification of extreme precipitation is important in the design of storm water drains and other infrastructure. Intensity Duration Frequency (IDF) relationships are generally used to obtain design return level for a given duration and return period. Due to lack of availability of extreme precipitation data for sufficiently large number of years, estimating the probability of extreme events is difficult. Typically, a single station data is used to obtain the design return levels for various durations and return periods, which are used in the design of urban infrastructure for the entire city. In an urban setting, the spatial variation of precipitation can be high; the precipitation amounts and patterns often vary within short distances of less than 5 km. Therefore it is crucial to study the uncertainties in the spatial variation of return levels for various durations. In this work, the extreme precipitation is modeled spatially using the Bayesian hierarchical analysis and the spatial variation of return levels is studied. The analysis is carried out with Block Maxima approach for defining the extreme precipitation, using Generalized Extreme Value (GEV) distribution for Bangalore city, Karnataka state, India. Daily data for nineteen stations in and around Bangalore city is considered in the study. The analysis is carried out for summer maxima (March - May), monsoon maxima (June - September) and the annual maxima rainfall. In the hierarchical analysis, the statistical model is specified in three layers. The data layer models the block maxima, pooling the extreme precipitation from all the stations. In the process layer, the latent spatial process characterized by geographical and climatological covariates (lat-lon, elevation, mean temperature etc.) which drives the extreme precipitation is modeled and in the prior level, the prior distributions that govern the latent process are modeled. Markov Chain Monte Carlo (MCMC) algorithm (Metropolis Hastings

  19. Spatio-Temporal Analysis of UHI using Geo-Spatial Techniques: A case study of Ahmedabad

    NASA Astrophysics Data System (ADS)

    Vyas, A.; Shastri, B.; Joshi, Y.

    2014-11-01

    vulnerabilities to human health, the marginal population affected largely as the natural environment is their only home or their main shelter. Furthermore elderly people also affected in greater amount as their weakening immunes system. Major effects of UHI on environment include: a) Air Quality, b) Energy consumption and c) Human health. To study the causes and effect of UHI of any urban area, the first step is to demarcate the spatial distribution of UHI and its intensity over different time period of the day as well as difference in the temperature of urban area with the surrounding rural areas. Secondly, study of land use land cover change in the area also helps in identifying causes of heat accumulation for particular region. After marking up of intensity, analysis of different zones for understanding the relationship between UHI and urban morphological features can be done which further became suggestive towards planning of urban center that mitigates the effect of UHI. Mainly two approaches are there to demarcate UHI study as: - Field data collection and observations - Remote sensing data analysis For a long period of time observations from interior of the city and outwards of it can analyze by a climatic methods, by observing many days as well as many times of a day continuously to analyze the daily variation law of the heat island effects. As the city is for its developmental approaches may cover an area of hundreds of square kilometers, the ground observation data is not able to provide enough detail about the urban heat island distribution characteristics. The most precise method is the Satellite Remote Sensing method. The UHI phenomenon can be analyzed by using the thermal infrared data obtained meteorological satellite sensing. The atmospheric attenuation can be corrected for the remote sensing data by use of meteorological soundings and ground observation data. Ideally the heat island effect over a city is not same for any other city. Satellite images from AVHRR

  20. Estimation of critical forest structure metrics through the spatial analysis of airborne laser scanner data

    NASA Astrophysics Data System (ADS)

    Andersen, Hans-Erik

    The effective management of complex forest ecosystems depends on quantification of critical forest structure components. Three important structural components include vertical foliage distribution, tree size distribution, and horizontal spatial pattern. Active remote sensing technologies, such as LIght Detection And Ranging (LIDAR), are well-suited for analysis of three-dimensional forest structure. In this research, a methodology was developed to relate the spatial distribution and pattern of LIDAR data to forest structure metrics, through implementation of stochastic modeling and image analysis techniques. An original approach to estimating the vertical distribution of canopy foliage using multiple return LIDAR is presented. A probabilistically transformed estimate of the canopy foliage profile is derived to approximate model-based profiles developed from field data. Plot-wise goodness-of-fit tests showed the transformed LIDAR-based profile provided an improved estimate of the model-based profile. A methodology is presented for estimating canopy cover and LAI using LIDAR. Two machine vision algorithms, based upon mathematical morphology and Bayesian object recognition, were developed for the spatially-explicit analysis of tree size distributions using high-density LIDAR. The mathematical morphological analysis of the canopy surface model yielded estimates of tree height that were correlated with field-based measurements (r = 0.80). The simulation-based Bayesian object recognition algorithm provided inferences on plot-wise functionals, including Lorey's height, basal area, stem number and volume. A comparison of the maximum a posteriori estimate with field-based measurements showed mean errors (+/-1 st.dev.) for: Height 3.9 +/- 8.9 ft; DBH 0.4 +/- 3.2 in; stem volume 6.9 +/- 38.8 ft3 (n = 17). A methodology was developed to quantify the error budget in automated individual tree-based forest surveys. To investigate horizontal spatial patterns, a novel approach to